Health Demography

Health DemographyPaul Andrew Bourne

Health Demography i

Health Demography Paul Andrew BourneDirector, Socio-Medical Research Institute (Formerly, Biostatistician, Dept. ofCommunity Health and Psychiatry, Faculty of Medical Sciences, The University ofthe West Indies, Mona, Jamaica) ii

©Paul A. Bourne, 2011First Published in Jamaica, 2011 byPaul Andrew Bourne66 Long Wall DriveStony Hill,Kingston 9,St. AndrewNational Library of Jamaica Cataloguing DataHealth DemographyIncludes indexISBNBourne, Paul AndrewAll rights reserved. Published, 2011Cover designed by Paul Andrew Bourne iii

PrefaceFor many decades, the study of demography excluded the sub-discipline of health, healthdemography. Demography which concerned itself with the study of human populations (size,distribution, composition of human population, fertility, mortality, migration, data source, lifetables, stable and stationary populations, standardization, morbidity, age-sex composition andpopulation growth) did not see it fitting to include health. Demographic literature andconferences avoided the study of health, although extensive examinations were made onmortality and morbidity. With sub-disciplines like mortality and mortality, health should havebeen a theme or sub-theme therein, but this was not the case. The issues of mortality and morbidity are critical components of health. Those themescannot be hidden from each other as the absence of morbidity was traditionally viewed as health,and mortality was used to compute life expectancy which is an indicator of the health status of apopulation or people. Based on the World Health Organization’s (WHO) conceptualization ofhealth (“Health is state of complete physical, mental and social wellbeing, and not merely beingthe absence of disease or infirmity”1), demographers like other health scientists must recognizethe importance of death and illness in health discourses as well as the broaden definition ofhealth. However, much of the works on health have been widely expounded upon by non-demographers. Health cannot be divorced from mortality and/or morbidity, making healthdemography pivotal in mortality and morbidity studies. Despite the emergence of the biopsychosocial model which (George Engel) is analternative paradigm to the dominant traditional medical model (etiology of diseases or germtheory), the latter model is well established in medical literature because of its scientific basisand its usefulness in addressing particular health conditions. The medical model (or biomedicalmodel) is a causal one in explaining disease causing pathogens, which focuses on acute ratherthan chronic conditions. In Jamaica, life expectancy has more than doubled since the 1900s. Thisdoubling of the life expectancy means demographic transition and health care transformation.The major transformation is the shifting from acute (communicable) to chronic conditions (non-communicable diseases). The shift accounts for demographic transition, the ageing of thepopulation (shift of the population from younger to older ages). With the demographic transitionand health care transformation arising from epidemiological transition (disease transitions), thebiomedical model is well suited as its emphasis is on diseases. From the limitation of thebiomedical model to address non-physical conditions, illness (morbidity) cannot be the focus ofdemographers. Health should not be measured other extreme of the illness pendulum, it shouldbe conceptualized in a broader scope including the social, environmental, economical andpsychological factors. Health in the study of demography cannot be about illness, healthdemography must be all-inclusive of the biological, social, economical, environmental andpsychological conditions. Health demography which is the application of demographic methods to the study ofhealth and health behaviour, therefore, is demography like mortality and morbidity.Demographers for centuries have been studying mortality, morbidity, and building model toexplain mortality (life tables), yet the discipline excluded health demography. It was during the1980s that health demography emerged as sub-discipline in the field of demography. Despite this iv

reality, in the Caribbean, particularly in Jamaica, the majority of studies on health demographyhave been conducted by non-demographers including sociologists, and epidemiologists. In the 1950s, Mortimer Spiegelman (demographer) wrote a book entitled ‘Introduction toDemography’ in which a chapter (Chapter 7) examined ‘Health Statistics’. He recognized theimportance of health in the discourse of demography, yet most the chapter was spent examiningillness. Although in paragraph 4 (section 7.1.1), he introduced the definition of health as wasoffered by the WHO in the Preamble to its Constitution (in 1946), the emphasis was onmorbidity statistics (chronic and acute conditions) as well as disability. For some unknownreason when health is mentioned by many scholars, they tend to revert to illness, negative health.There is no denial that illness, curative care and morbidity statistics are crucial in healthexamination, but that this is a miniscule part in the health discourse. Based on the definition ofhealth forwarded by WHO, health is synonymous with wellbeing and not morbidity (acute and/orchronic conditions). Why then did Spiegelman dedicate a chapter on health to morbidity? Evenin a section entitled health status (section 7.7, page 197), he discussed ‘acute conditions’ (pages197-199), ‘chronic conditions’ (pages 199-200) and ‘disability’ (pages 200-2005). Like manyacademics before him, Spiegelman followed the cosmology of natural scientists examined theclear causal linkage between illness and particular pathogens instead of venturing to the broadpurview of health, wellbeing and not the mere absence of illness. Other demographers like Donald T. Rowland (in Demographic methods and concepts,published in 2003), Peter R. Cox (in Demography, published in 1950), H.S. Shryock, J. S.Siegel, and Associates (in The methods and materials of demography, published in 1976) andNewell (In Methods and models in demography, published in 1988) did not pen a single chapteron health and/or health demography. Recognizing the paucity of information from demographerson health, Jacob S. Siegel and David A. Swanson (in The Methods and Materials ofDemography, second edition, published in 2004) included a chapter on health demography(written by V Lamb and Jacob Siegel). In this Chapter (Chapter 14, pages 341-370), Lamb andSiegel expanded on negative health as forwarded by Spiegelman to 1) problems with health datasources, 2) measures of health status, functioning, and use of health statistics, 3) reproductivehealth, 4) mortality and morbidity, and 5) general analytic devices and health projections models. Clearly, the emergence of health demography cannot be denied by demographers. Lamband Siegel forwarded that health studies can use multivariate logistic regression (dichotomousdependent variable), proportional hazards model, and meta-analysis. Embedded in Lamb andSiegel’s work is the use of complex statistical model to examine health status of the population.This suggesting that there will be exogenous and endogenous variables. Health which is amultidimensional variable is best examined using econometric model, to identify the variousexogenous factors, while health is treated as an endogenous variable. Michael Grossman (an economist) used econometric model to establish exogenousvariables that influence health status, with health being an endogenous variable. Among theexogenous variables were many demographic factors (including age, sex, marital status, socialclass, education). Demography which is concerned about population matters, having recognizedthe importance of modeling health status, must model health of the population, and sub-populations, demographic models of health. Using econometric model, we can identify a systemof simultaneous linear equation that link health changes with germane factors, exogenousvariables. Yet Caribbean demographers lag behind in the use of demographic tools to health data. v

Traditionally, demographers have sought to analyze and provide information on healthfrom the perspective of mortality and/or morbidity. From the mortality tenet, they have capturedand measure health status, by using life expectancy. Life expectancy may be an adequateindicator of length of life. But, this is from a biomedical perspective. Such a yardstick of healthstatus is not in keeping with the conceptual definition furnished by the World HealthOrganization. It should be noted that this conceptual definition which is in the Preamble to theconstitution of the WHO which was signed in July 1946 and became functional in 1948,according to one scholar, from the Centre of Population and Development studies at HarvardUniversity, it is mouthful of sweeping generalization, that is difficult to attain, and at best it is aphantom. (Bok 2004) While we accept that the definition of health as offered by the WHO is comprehensive, amouthful, and an idealistic state, it is not elusive. Based on WHO’s conceptualization of health,it is an end as well as an ingredient to other product. As an end, health can be model in order tounderstand its exogenous factors. This book recognizes the discourse on the conceptualization ofhealth, understand its importance and so will furnish a discussion on wellbeing and health(Chapters 1 & 2). Is there a shift taking place in demography, as the journal entitled‘Demography’ (Demography 1997) published an article by Smith and Kington on the exogenousfactors of health status? The maturing of the field of health demography denotes that is it timefor this to be the case in Caribbean studies. With the increased ageing of the world’s populations, which is more so a case in thedeveloping regions, its implications are multi-fold. This means changes, shifts and new directionin (i) dependency ratios; (ii) employability and labour force; (iii) pension packages; (iv)mortality patterns and hospitalization care; (v) longevity – life span and life expectancy; (vii)health status and family health-care – as the elderly have a wide spectrum of health challenges,and the health costs faced by this age cohort are normally higher, (viii) social and economicdevelopment (including building and other infrastructure) and (ix) demographic andepidemiological transition. Thus, there is a need for demographers to utilise demographictechniques to study the health status of population, particularly among older adulthood (60+years old). This volume consists of 25 chapters. I have introduced happiness in this text in keepingwith the expanded definition of health. Health which is a subjective measure (using WHO’sdefinition of health) cannot be discourse with examining other subjective indexes such ashappiness and life satisfaction (chapters 20 & 21). Initially when happiness was put forward byEd Diener as a measure of wellbeing, it was rigorously opposed by some scholars as subjectiveand so cannot be used to measure health or wellbeing. Happiness, life satisfaction, and health status are among some of the subjective indexesused to evaluate health (or wellbeing) of an individual, community or population. Subjectiveindexes cover a wider gamut of an individual’s life compared to diagnosed health conditions,morbidity, reproductive health and life expectancy. Jamaica has been collecting data since 1989,and this has been used to measure health of the population, gender of the participants and healthwithin area of residence. The use of illness to measure health is negative and does not coverhealth. Happiness therefore like life satisfaction and health status provide a comprehensivecoverage of people’s quality of life than ill-health. The use of objective indexes such asdiagnosed illness, gross domestic product; life expectancy and mortality are among measured vi

that are said to be limited in scope, and justify the usage of the subjective indexes by somescholars. I believe that self-rated health is just as subjective as happiness and life satisfaction. Itfollows therefore that we (demographers) must examine happiness and life satisfaction as a partof health demography. If happiness is synonymous with life satisfaction and self-rated health(used as health thorough this text), then demographers should not shy away from evaluatingdifferent definitions of health and factors that influence the conceptualization of health. Health isan endogenous variable like happiness and life satisfaction. As such, I am forwarding thathappiness and life satisfaction should be incorporate into health demography. Chapters 20 and 21evaluate health, life satisfaction and health of older adult men in Jamaica. Although this cannotbe stated as generalizable to the population, it provides an understanding of the three endogenousvariables that are important in the health discourse, health demography. Chapter 23 examines a subjective index of health (self-reported illness) and an objectiveindex (life expectancy), and found a strong significant association between life expectancy atbirth for the Jamaican population and self-reported illness (correlation coefficient, r = -0.731).Fifty-four percent of life expectancy can be accounted for by self-reported illness (R2 = 0.535).This is validating the use of illness (or morbidity) by academics in measuring health. The penultimate chapter (Chapter 24) evaluates the statistical associations between 1)happiness, 2) life satisfaction and 3) health status. Happiness is the degree to which people judgetheir overall quality of life as favourable. According to Konow and Earley, happiness wascorrelated with unemployment, positive and negative life-events, social networks and intimatefriendships. In chapter 24, happiness was strongly correlated with life satisfaction as bothsubjective indexes are broader than health status and incorporate many aspect of life. Hence, thefinding that very happy older men are highly likely to be very satisfied with life and vice versasuggests that heart disease, hypertension, digestive disorders and headaches are temporal and assuch in assess ones quality of life, they are lowly value and do not contribute to this overallmeasure of wellbeing. Empirical evidence exists in this volume which showed that health is still narrowlyconceptualized by Jamaicans (self-reported illness), and that happiness and life satisfaction ismore comprehensive measures that health (or illness). Within the context of the broadeneddefinition of health, illness should not be used to evaluate health or vice versa. Using a sample ofolder adult men, it appears that happiness and life satisfaction are more composite that health(self-rated). Within the Jamaican context, health demography, therefore, must includehappiness and life satisfaction. This book is written primarily for audience in health care, academic and private sectordemographers, students in demography, health care administrators and social workers who seekto understand health as an endogenous variable and demographic and other factors that accountfor changes in health status of peoples in Jamaica. The etiology of disease is a component to health and health care; it is not the end becausehealth must include the non-physical components. This book recognizes the alternative paradigm(biopsychosocial model), forwards the various chapters on illness and the widerconceptualization of health. The volume is written partly as a result of the paucity of healthdemography in the Caribbean (including Jamaica) and need to commence the discourse on healthdemography in Jamaica. Paul Andrew Bourne February, 2011 vii

AcknowledgementLike many other authors, I am indebted to many people who contributed in different ways to thecompletion of this book. These individuals are 1) Mrs. Evadney Bourne, 2) Kimani Bourne, 3)Kerron Bourne, 4) Paul Andrew Bourne, Jnr, who stayed up with me on countless nights, andlonger on Saturdays and Sundays. Ms. Neva South-Bourne, whose tireless efforts and endlesspatience in proofreading some of the chapters as well as Mrs. Cindi Schofield. I am also indebtedto the Derek Gordon Databank, University of the West Indies, Mona (Jamaica) that made thedataset available from which many of the chapters emerged. The majority of the chapters arepublished works in different journals, and I am grateful for their permission to use the materialsin this book (North American Journal of Medical Sciences, Health, Current Research Journal inSocial Sciences, and Journal of Clinical and Diagnostic Research). Finally, I would like to thankall my co-authored who wrote different articles with me. viii

ContentsPreface ivAcknowledgement viii 1. A conceptual framework of wellbeing in some Western nations 1 2. Health Measurement 23 3. Why demographers should study wellbeing of the aged? 49 4. Wellbeing Discourse 56 5. Variations in social determinants of health using an adolescence population: By different measurements, dichotomization and non-dichotomization of health 107 6. Self-reported health and health care utilization of older people 134 7. Socioeconomic correlates of self-evaluated health status of elderly with diagnosed chronic medical conditions, Jamaica 174 8. Child Health Disparities in an English-Speaking Caribbean nation: Using parents’ views from a national survey 201 9. Health Status of Patients with self-reported Chronic Diseases in Jamaica 230 10. Retesting and refining theories on the association between illness, chronic illness and poverty: Are there other disparities? 260 11. Demographic shifts in health conditions of adolescents aged 10-19 years, Jamaica: Using cross-sectional data for 2002 and 2007 285 12. Determinants of quality of life of youths in an English-speaking Caribbean nation 309 13. Self-rated health of the educated and uneducated classes in Jamaica 330 ix

14. An Epidemiological Transition of Health Conditions, and Health Status of the Old-Old-To-Oldest-Old in Jamaica: A comparative analysis 35515. Health of females in Jamaica: using two cross-sectional surveys 38516. Gender differences in self-assessed health of young adults in an English-speaking Caribbean nation 40517. Disparities in self-rated health, health care utilization, illness, chronic illness and other socio-economic characteristics of the Insured and Uninsured 44618. Self-evaluated health and health conditions of rural residents in a developing Country 47819. Health of males in Jamaica 50620. Happiness among Older Men in Jamaica: Is it a health issue? 53521. Happiness, life satisfaction and health status in a Caribbean nation: Using a cross-sectional survey 56722. Decomposing Mortality Rates and Examining Health Status of the Elderly in Jamaica 60023. The validity of using self-reported illness to measure objective health 62224. A cross-sectional survey of the health status, life satisfaction and happiness of older men in Jamaica - associations between questionnaire scores 64225. The changing faces of diabetes, hypertension and arthritis in a Caribbean population 666 x

CHAPTER 1A conceptual framework of wellbeing in some Western nationsThe aim of this study is to examine and highlight the narrow definition of wellbeing that stillexists in some contemporary Western societies. This definition is in keeping with the biomedicalmodel that views the exposure to specific pathogens as the cause of diseases in organisms. Suchan approach began during the 130ce to 200ce in Ancient Rome, and despite the efforts of theWHO in 1946 to expand the concept, health in Caribbean societies and in particular Jamaica isstill substantially seen as the ‘absence of diseases’ or dysfunctions in the body, which is what isused to indicate wellbeing. Health and wellbeing are multidimensional constructs and so thereis a need for academics to begin vociferously working to encapsulate an operational definition ofwellbeing that can be used in the images of wellbeing and patient care. This paper presents andexamines a conceptual framework on health (or wellbeing) from a biopsychosocial perspective,as well as including an environmental perspective as this is in keeping with an expandedconceptualization of health as forwarded by the WHO in its constitution. Within the discourse,arguments will be presented on both subjective and objective measurements of wellbeing.IntroductionThe traditional view of Western Societies is that health is conceptualized as the ‘absence ofdiseases’. This approach is both narrow and negative in scope as regards health. According toone school of thought, the aforementioned conceptualization of health emphasizes the absence ofsome disease-causing pathogens, and not health (Longest, 2002; Brannon, and Feist, 2007; Rice,1998). Such a perspective is in keeping with the traditional biomedical model that views theexposure to specific pathogens as the cause of diseases in organisms. This began during 130ceto 200ce in Ancient Rome and despite the efforts of the WHO as early as 1946 to expand thisconstruct (WHO, 1948), health in Caribbean societies, in particular Jamaica, is still substantiallyviewed as the ‘absence of diseases’ or dysfunctions, with wellbeing being the opposite of thatstate. Humans are multifaceted and so any conceptualization of health that seeks to measure anaspect of their existence cannot be uni-directional or bi-directional, as health, wellbeing andwellness are multidimensional, which would be in keeping with the complexities of people. 1

Lynch (2003) opines that everything that we do, feel, think and experience interfaces with ourhealth; hence, wellbeing cannot be operationally defined solely based on functional limitationbecause of pathogens, as many events affect the quality of life outside of that space. Thus, thispaper recognizes the need for the discourse, as it will allow for a better measurement of theconcept. In addition to health measurement, this paper seeks to broaden the scope of thedeterminants of health, and in the process help policy-makers to understand this concept. In anationally representative survey of Jamaicans, using observational data on some 2,320 elderlypeople (ages 65+ years), Bourne (2007) finds 12 factors that determine the wellbeing of elderlyJamaicans. Bourne’s wellbeing model is different to that presented in many other studies, as heuses a combination of physical dysfunctions, income and material possessions to conceptualizewellbeing. Bourne’s overall model explains 40.1% of the variance in wellbeing. Again,wellbeing is influenced by more than just biological conditions. However, one scholar [Bok,2004] opined that the WHO’s operationalization of health (or wellbeing) is too broad and byextension difficult to measure. This begs the question, why have we reverted to the ancientconceptualization of wellbeing (or health) and its images to guide patient care? Hence, what arethe different discourses on wellbeing? Therefore, the paper presents and examines a conceptualframework on health (or wellbeing) from a biopsychosocial perspective, in addition to includingthe physical environment in the discourse as well as providing other images within the healthdiscourse, with the aim of aiding health outcome research and patient care.Result and Discussion Wellbeing defined The concept of health according to the WHO is multifaceted. “Health is the state ofcomplete physical, mental and social wellbeing and not merely the absence of disease orinfirmity” (WHO, 1948). From the WHO’s perspective, health status is an indicator ofwellbeing (Crisp, 2005). Wellbeing for some, therefore, is a state of happiness – positive feelingstatus and life satisfaction (Easterlin, 2003; Diener et al., 1985; Diener, 1984) satisfaction ofpreferences or desires, health or prosperity of an individual (Diener, and Suh, 1997a, b; Jones,2001; Crisp, 2005; Whang, 2006), or what psychologists refer to as positive effects. Simply put,wellbeing is subjectively what is ‘good’ for each person (Crisp, 2005). It is sometimes 2

connected with good health. Crisp offered an explanation for this, when he said that “Whendiscussing the notion of what makes life good for the individual living that life, it is preferable touse the term ‘wellbeing’ instead of ‘happiness” (Crisp, 2005). Ergo, the term wellbeing is used interchangeably with words such as ‘happiness’, ‘lifesatisfaction’, and ‘welfare’ by a number of researchers and/or people in intelligentsia (Diener,1984; Easterlin, 2003; Veenhoven, 1993). While some scholars argue that happiness and lifesatisfaction are but a fraction of wellbeing, what is embedded in Diener and Easterlin’s usage ofthose terminologies instead of wellbeing aptly shows that, within the context of amultidisciplinary global market place in which people must operate, the quality of life thatpeople enjoy (or do not enjoy) must be understood before the goals of policy-planning anddecision-making on the desire to improve the welfare, quality of life and/or standard of living ofa people can materialize. Happiness, according to Easterlin (2003) is associated with wellbeing, and also with ill-being (for example depression, anxiety, dissatisfaction). Easterlin (2003) argued that materialresources have the capacity to improve one’s choices, comfort level, state of happiness andleisure, which militates against static wellbeing within the context that developing countries anddeveloped countries had at some point accepted the economic theory that economic wellbeingshould be measured by per capita Gross Domestic Product (GDP) – (i.e. total monetary value ofgoods and services produced within an economy over a stated period per person). Amartya Sen,who is an economist, writes that a plethora of literature exists showing that life expectancy ispositively related to Gross National Product (GNP) per capita. (Anand and Ravallion, 1993; Sen,1989). Such a perspective implies that mortality is lower whenever an economic boom existswithin the society and that this is believed to have the potential to increase development, and byextension the standard of living. Sen, however, was quick to offer a rebuttal in that dataanalyzed have shown that some countries (i.e. Sri Lanka, China and Costa Rica) have hadreduced mortality without a corresponding increase in economic growth (Sen, 1989), and thatthis was attained through other non-income factors such as education, nutrition, immunization,expenditure on public health and poverty removal. The latter factors undoubtedly require incomeresources, and so it is clear that income is unavoidably a critical component in welfare andwellbeing. Some scholars believe that economic growth and/or development is a measure of 3

welfare (Becker et al., 2004). Therefore, those studies on economic wellbeing were able to offer a plethora of answersto national governments on the health status of the people, or the wellbeing and/or illbeing oftheir citizens. No policy formulation on improving the quality of life of the citizens of aparticular space should proceed without firstly unearthing the ‘real’ determinants of wellbeing.From Crisp’s perspective (2005), wellbeing is related to health and the strength of thoseassociations, and secondly planning requires information that is made available by research. Istraditional economists’ operationalization of wellbeing still applicable in contemporary societies,knowing it to be purely objective? If happiness is a state of wellbeing, then if we were to impute depression, anxiety, stress,and illness and/or physical incapacitation, spirituality and environment within the objectivemeasurement of wellbeing, a more holistic valuation would be reached. With the inclusion ofsubjectivity conditions in the measurement of wellbeing, we come closer to an understanding ofpeople’s state of wellness, health and quality of life, as better nutrition, efficient disposal ofsewage and garbage, and a healthy lifestyle also contribute to health status (i.e. wellbeing). Itshould be noted that the biomedical model that is objective, conceptualizes health as the absenceof diseases. This leads to the question, are any of the following diseases – (i) depression, (ii)stress, (iii) fatigue, and (iv) obsession? Hence, an issue arises, does the lack of objectivity meanit should be accepted with scepticism? In order to put forward an understanding of what constitutes wellbeing or illbeing, asystem must be instituted that will allow us to coalesce a measure that will unearth peoples’sense of the overall quality of life from either economic-welfarism (Becker et al. 2004) orpsychological theories (Diener et al., 1997; Kashdan, 2004; Diener, 2000). This must be donewith the general construct of a complex man. Economists like Smith and Kington, and Stutzerand Frey as well as Engel believe that the state of man’s wellbeing is not only influenced byhis/her biologic state, but that it is always dependent on his/her environmental, economical andsociological conditions. Some studies and academics have sought to analyze this phenomenon ina subjective manner by way of general personal happiness, self-rated wellbeing, positive moodsand emotions, agony, hopelessness, depression, and other psychosocial indicators (Arthaud-dayet al., 2005; Diener et al., 1999; Skevington et al., 1997; Diener, 1984). 4

An economist (Easterlin) studying happiness and income, of all social scientists, found anassociation between the two phenomena (Easterlin, 2001a, b), (Stutzer and Frey, 2003). Hebegan with a statement that “the relationship between happiness and income is puzzling”(Easterlin, 2001a: p. 465), and found that people with higher incomes were happier than thosewith lower incomes – he referred to it as a correlation between subjective wellbeing and income(Stutzer, and Frey, 2003). He did not cease at this juncture, but sought to justify this reality,when he said that “those with higher incomes will be better able to fulfil their aspirations, andwith other things being equal, on an average, feel better off.” (Easterlin, 2001a: p. 472).Wellbeing, therefore, can be explained outside of the welfare theory and/or purely onobjectification-objective utility (Kimball, and Willis, 2005; Stutzer, and Frey, 2003). Whereas Easterlin found a bivariate relationship between subjective wellbeing andincome, Stutzer and Frey revealed that the association is a non-linear one. They concretized theposition by offering an explanation that “In the data set for Germany, for example, the simplecorrelation is 0.11 based on 12, 979 observations” (Stutzer, and Frey, 2003). Nevertheless, fromStutzer and Frey’s findings, a position association does exist between subjective wellbeing andincome despite differences over linearity or non-linearity. The issue of wellbeing is embodied in three theories – (1) Hedonism, (2) Desire, and (3)Objective List. Using ‘evaluative hedonism’, wellbeing constitutes the greatest balance ofpleasure over pain (Crisp 2005; Whang 2006: p. 154). With this theorizing, wellbeing is justpersonal pleasantness, which postulates that the more pleasantries an individual receives, thebetter off he/she will be. The very construct of this methodology is the primary reason for acriticism of its approach (i.e. ‘experience machine’), which gave rise to other theories. Crisp(2005), using the work of Thomas Carlyle, described the hedonistic structure of utilitarianism asthe ‘philosophy of swine’, because this concept assumes that all pleasure is on par. Hesummarized this adequately by saying that “… whether they [are] the lowest animal pleasures ofsex or the highest of aesthetic appreciation” (Crisp, 2005). The desire approach, on the other hand, is on a continuum of experienced desires. Thisis popularized by welfare economics, as economists see wellbeing as constituting the satisfactionof preference or desires (Crisp, 2005; Whang 2006: p. 154), which makes for the ranking ofpreferences and assessment by way of money. People are made better off if their current desires 5

are fulfilled. Despite this theory’s strengths, it has a fundamental shortcoming, the issue ofaddiction. This is exemplified by the possible addictive nature of consuming ‘hard drugs’because of the summative pleasure it gives to the recipient. Objective list theory: This approach in measuring wellbeing lists items not merelybecause of pleasurable experiences, nor on ‘desire-satisfaction’, but states that every good thingshould be included, such as knowledge and/or friendship. It is a concept influenced by Aristotle,and “developed by Thomas Hurka (1993) as perfectionism” (Crisp, 2005). According to thisapproach, the constituent of wellbeing is an environment of perfecting human nature. What goeson an ‘objective list’ is based on the reflective judgement or intuition of a person. A criticism ofthis technique is elitism (Crisp, 2005), since an assumption of this approach is that certain thingsare good for people. Crisp (2005) provided an excellent rationale for this limitation, when hesaid that “…even if those people will not enjoy them, and do not even want them.” In the work of Arthaud-Day et al. (2005), applying structural modelling to subjectivewellbeing was found to constitute “(1) cognitive evaluations of ones life (i.e., life satisfaction orhappiness); (2) positive affect; and (3) negative affect.” Subjective wellbeing, therefore, is theindividual’s own viewpoint. If an individual feels his/her life is going well, then we need toaccept this as the person’s reality. One of the drawbacks to this measurement is, it is notsummative, and it lacks generalizability. Studies have shown that subjective wellbeing can be measured on a community level(Bobbit et al., 2005; Lau, 2005) or on a household level (Lau, 2005; Diener 1984), whereas otherexperts have sought to use empiricism (biomedical indicators - absence of disease symptoms, lifeexpectancy; and an economic component - Gross Domestic Product per capita; welfarism -utility function). Powell (1997) in a paper entitled ‘Measures of quality of life and subjective wellbeing’argued that psychological wellbeing is a component of quality of life. He believed that thismeasurement, in particular for older people, must include Life Satisfaction Index, as thisapproach constitutes a number of items based on “cognitively based attitudes toward life ingeneral and more emotion-based judgment”(Powell, 1997). Powell addressed this in twodimensions. Where those means are relatively constant over time, and while seeking to unearth 6

changes in the short-run, ‘for example an intervention’, procedures that mirror changed statesmay be preferable. This can be assessed by way of a twenty-item Positive and Negative AffectSchedule or a ten-item Philadelphia Geriatric Centre Positive Affect and Negative Affect Scale(Powell, 1997). In a reading entitled ‘Objective measures of wellbeing and the cooperation productionproblem’, Gaspart (1998) provided arguments that support the rationale behind theobjectification of wellbeing. His premise for objective quality of life is embedded within thedifficulty as it relates to consistency of measurement when subjectivity is the construct ofoperationalization. This approach takes precedence because an objective measurement ofconcept is of exactness as non-objectification; therefore, the former receives priority over anysubjective preferences. He claimed that for wellbeing to be comparable across individuals,population and communities, there is a need for empiricism. Gaspart discussed a number of economic theorizings (Equal Income Walrasian equilibria,objective egalitarianism, Pareto efficiency; Welfarism), which saw the paper expounding on anumber of mathematical theorems in order to quantify quality of life. Such a stance proposes ahuman predictable, rational form, from which we are able to objectify plans. The very axiomscited by Gaspart emphasized a particular set of assumptions that he used in finalizing ameasurement for wellbeing for man who is a complex social animal. The researcher points to asentence that was written by Gaspart that speaks to the difficulty of objective quality of life; hewrote, “So its objectivism is already contaminated by post-welfarism, opening the door to amixed approach, in which preferences matter as well as objective wellbeing” (Gaspart, 1998).Another group of scholars emphasized the importance of measuring wellbeing outside ofwelfarism and/or purely objectification, when they said that “Although GDP per capita is usuallyused as a proxy for the quality of life in different countries, material gain is obviously only oneof many aspects of life that enhances economic wellbeing” (Becker et al., 2004), and thatwellbeing depends on both the quality and the quantity of life lived by the individual (Easterlin,2001). This is affirmed in a study carried out by Lima and Nova (2006), which found thathappiness, general life satisfaction, social acceptance and actualizations are all directly related tothe GDP per capita for a geographic location (Lima and Nova, 2006). Even though in Europe 7

these were found not to be causal, income provides some predictability of subjective wellbeing,and more so in poor countries than in wealthy nations. (Lima, and Nova, 2006) It should be understood that GDP per capita speaks to the market economic resources,which are produced domestically within a particular geographic space. So increased productionin goods and/or services may generate excess, which can then be exported, and vital products(such as vaccination, sanitary products, vitamins, iron and other commodities) can be purchased,which are able to improve the standard of living and quality of the life of the same peoplecompared to the previous period. One scholar (Caldwell, 1999) has shown that life expectanciesare usually higher in countries with high GDP per capita, which means that income is able topurchase better quality products, which indirectly affects the length of years lived by people.This reality could explain why in economic recession, war and violence, when economic growthis lower (or even non-existent) there is a lower life expectancy. Some of the reasons for thesejustifications are government’s failure to provide for an extensive population in the form ofnutritional care, public health and health-care services. Good health is, therefore, linked toeconomic growth, which further justifies why economists use GDP per capita as an objectivevaluation of standard of living; and why income should definitely be a component in the analysisof health status. There is another twist to this discourse as a country’s GDP per capita may below, but the life expectancy is high because health care is free for the population. Despite thisfact, material living standards undoubtedly affect the health status and wellbeing of a people, aswell as the level of females’ educational attainment. Ringen (1995) in a paper entitled ‘Wellbeing, measurement, and preferences’ argued thatnon-welfarist approaches to measuring wellbeing are possible despite its subjectivity. The directapproach for wellbeing computation through the utility function according to Ringen is not abetter quantification as against the indirect method (i.e. using social indicators). The stancetaken was purely from the vantage point that utility is a function ‘not of goods and preferences’but of products and ‘taste’. The constitution of wellbeing is based on choices. Choices are afunction of individual assets and options. With this premise, Ringen put forward argumentsshowing that people’s choices are sometimes ‘irrational’, which is the make for the departurefrom empiricism. 8

Wellbeing can be computed from either the direct (i.e. consumption expenditure) or theindirect (i.e. disposable income) approach (Ringen, 1995). The former is calculated usingconsumption expenditure, whereas the latter uses disposable income. Rigen noted that in orderto use income as a proxy for wellbeing, we must assume that (1) income is the only resource, and(2) all persons operate in identical market places. On the other hand, the direct approach has twokey assumptions. These are (1) what we can buy is what we can consume and (2) what we canconsume is an expression of wellbeing. From Rigen’s monograph, the assumptions arelimitations. In presenting potent arguments in favour of non-empiricism in the computation ofwellbeing, Ringen highlighted a number of drawbacks to welfarism. According to Ringen: Utility is not a particularly good criterion for wellbeing since it is a function not only of circumstances and preferences, but also of expectation. In the measurement of wellbeing, respect for personal preferences is best sought in non-welfarist approaches that have the quality of preference neutrality; …As soon as preferences are brought into the concept of wellbeing, it cannot but be subjective. (Ringen, 1995) The difficulties of using empiricism to quantify wellbeing have not only been put forwardby Ringen, as O’Donnell and Tait (2003) were equally forthright in arguing that there werechallenges in measuring quality of life quantitatively. O’Donnell and Tait believed that health isa primary indicator of wellbeing. Hence, self-rated health status is a highly reliable proxy ofhealth, which “successfully crosses cultural lines” (O’Donnell, and Tait, 2003). They arguedthat self-reported health status could be used, as they found that all the respondents of chronicdiseases indicated that their health was very poor. To capture the state of the quality of life of humans, we are continuously and increasinglyseeking to ascertain more advanced methods that will allow us to encapsulate a quantification ofwellbeing that is multidimensional and multifaceted (Pacione, 2003). Therefore, an operationaldefinition of wellbeing that sees the phenomenon in a single dimension such as physical health,medical perspective (Farquhar, 1995), material (Lipsey, 1999) and would have excludedindicators such as crime, education, leisure facilities, housing, social exclusion and theenvironment (Pacione 2003; Campbell et al., 1976) as well as subjective indicators, cannot be an 9

acceptable holistic measurement of this construct. This suggests that wellbeing is not simply asingle space; and so, the traditional biomedical conceptual definitions of wellbeing exclude manyindividual satisfactions and in the process reduce the tenets of a superior coverage of quality oflife. One writer noted that the environment positively influenced quality of life (Pacione,2003) of people; in order to establish the validity and reliability of wellbeing, empirical datamust include issues relating to the environment. The quality of the environment is a utilizedcondition in explaining the elements of people’s quality of life. Air and water quality throughindustrial fumes, toxic waste, gases and other pollutants, affect environmental quality. This isdirectly related to the maintenance or lack thereof of societal and personal wellbeing (Pacione,2003). Studies have conclusively shown that environmental issues such as industrial fumes andgases, poor solid waste management, mosquito infestation and poor housing are likely to result inphysiological conditions like respiratory track infections (for example lung infection)and asthma. According to Langlois and Anderson (2002), approximately 30 years ago, a seminalstudy conducted by Smith (1973) “proposed that wellbeing be used to refer to conditions thatapply to a population generally, while quality of life should be limited to individuals’ subjectiveassessments of their lives …” They argue that a distinction between the two variables has beenlost with time. From Langlois and Anderson’s monograph, during the 1960s and 1970s,wellbeing was approached from a quantitative assessment by the use of GDP or GNP (Becker etal., 2004), and unemployment rates; this they refer to as a “rigid approach to the (enquiry of thesubject matter) subject.” According to Langlois and Anderson (2002), the positivism approachto the methodology of wellbeing was objectification, an assessment that was highly favoured byAndrews and Withley (1976) and Campbell et al. (1976). In measuring quality of life, some writers have thought it fitting to use Gross DomesticProduct per capita (i.e. GDP per capita) to which they referred as standard of living (Lipsey,1999; Summers, and Heston 1995). According to Summers and Heston (1995), “The index mostcommonly used until now to compare countries material wellbeing is their GDP POP .” TheUnited Nations Development Programme has expanded on the material wellbeing definition put 10

forward primarily by economists, and has included life expectancy and educational attainment(UNDP, 2005: p. 341) as well as other social indicators (Diener, 1984; Diener, and Suh, 1997).This operational definition of wellbeing has become increasingly popular in the last twenty-fiveyears, but given the expanded definition of health as cited by the WHO, wellbeing must bemeasured in a more comprehensive manner than merely using material wellbeing as seen byeconomists. Despite the fact that quality of life extends beyond the number of years of schooling andmaterial wellbeing, generally wellbeing is substantially construed as an economic phenomenon.Embedded within this construct of a measure is the emphasis on economic resources, and wehave already established that man’s wellbeing is multifaceted. Hence, any definition of thequality of life of people cannot simply analyze spending or the creation of goods and/or servicesthat are economically exchangeable, the number of years of schooling and life expectancy, but itmust include the psychosocial conditions of the people within their natural environment. GDP is the coalesced sum of all the economic resources of people within certaintopography, so this does not capture the psychosocial state of man in attaining the valued GDP.By this approach, we may arrive at a value that is higher than in previous periods, making itseem as though people are doing very well. However, with an increase in GDP, this singlecomponent is insufficient to determine wellbeing, as the increase in GDP may be from (1) moreworking hours, (2) higher rates of pollution and environmental conditions, (3) psychologicalfatigue, (4) social exclusion, (5) human ‘burn out’, (6) reduction in freedom, (7) unhappiness, (8)chronic and acute diseases and so forth. Summers and Heston (1995) note that “However,GDP POP is an inadequate measure of countries immediate material wellbeing, even apart fromthe general practical and conceptual problems of measuring countries national outputs.”Generally, from that perspective, the measurement of quality of life is therefore highly economicand excludes the psychosocial factors, and whether quality of life extends beyond monetaryobjectification. In developing countries, Camfield (2003), in looking at wellbeing from a subjectivevantage point, notes that Diener (1984) argues that subjective wellbeing constitutes the existenceof positive emotions and the absence of negative ones within a space of general satisfaction withlife. According to Camfield (2003) and Cummins’ (1997a, b), this perspective subsumed 11

‘subjective and objective measures of material wellbeing’ along with the absence of illnesses,efficiency, social closeness, security, place in community, and emotional wellbeing, whichimplies that “life’s satisfaction” comprehensively envelopes subjective wellbeing. Diener (2000) in an article entitled ‘Subjective Wellbeing: The Science of Happiness anda Proposal for a National Index’ theorizes that the objectification of wellbeing is embodiedwithin satisfaction of life. His points to a construct of wellbeing called happiness. He cited that: Peoples moods and emotions reflect on-line reactions to events happening to them. Each individual also makes broader judgments about his or her life as a whole, as well as about domains such as marriage and work. Thus, there are a number of separable components of SWB [subjective wellbeing]: life satisfaction (global judgments of ones life), satisfaction with important domains (e.g., work satisfaction), positive affect (experiencing many pleasant emotions and moods), and low levels of negative affect (experiencing few unpleasant emotions and moods). In the early research on SWB, researchers studying the facets of happiness usually relied on only a single self-reported item to measure each construct (Diener, 2000). Diener’s theorizing on wellbeing encapsulates more than the marginalized stance of otheracademics and researchers who enlightened the discourse with economic, psychosocial, orsubjective indicators. He shows that quality of life is multifaceted, and coalescing economic,social, psychological and subjective indicators is more far-reaching in ultimately measuringwellbeing. This work shows a construct that can be used to operationalize a moremultidimensional variable, wellbeing, which widens the tenet of previous operational definitionon the subject. From the theorizing of various writers, it is clear that wellbeing ismultidimensional, multidisciplinary and multispatial. Some writers emphasize the environmentalcomponents of subject matter (Pacione, 1984; Smith, 1973), from the psychosocial aspect(Clarke et al., 2000) and from a social capital vantage point (Glaeser 2001; Putnam 1995;Woolcock 2001). Smith and Kington (1997), using H t = f (H t-1 , P m G o , Bt , MC t ED, Ā t , to conceptualise atheoretical framework for “stock of health,” noted that health in period t, Ht, is the result of 12

health preceding this period (H t-1) , medical care (MC t) , good personal health (G o) , the price ofmedical care (P m ), and bad medical care (Bt) , along with a vector of family education (ED), andall sources of household income (Ā t ). Embedded in this function is the wellbeing that anindividual enjoys (or does not enjoy) (Smith, and Kington, 1997). In seeking to operationalize wellbeing, the United Nations Development Programme(UNDP) in the Human Development Reports (1997, 2000) conceptualized human developmentas a “process of widening people’s choice as well as the level of achieved wellbeing”.Embedded within this definition is the emphasis on materialism in interpreting quality of life.From the UNDP’s Human Development (1993), the human development index (HDI) “…is anormative measure of a desirable standard of living or a measure of the level of living”, whichspeaks to the subjectivity of this valuation irrespective of the inclusion of welfarism (i.e. grossdomestic product (GDP) per capita). The HDI constitutes adjusted educational achievement (E=a 1 * literacy + a 2 * years of schooling, where a1, = 2/3 and a2 = 1/3), life expectancy 1-e(demographic modelling) and income (W (9y) = 1/ (1 - e) * y ). The function W(y) denotes“utility or wellbeing derived from income”. This income component of the HDI is a nationalaverage (i.e. GDP per capita, which is then adjusted for income distribution (W*(y) = W(y) {1 -G}), where G = Gini coefficient). In wanting to disaggregate the HDI within a country, theUNDP (1993) noted that data are not available for many countries, which limits the possibility. An economist writing on ‘objective wellbeing’ summarized the matter simply by statingthat “…one can adopt a mixed approach, in which the satisfaction of subjective preferences istaken as valuable too” (Gaspart, 1998; Cummin, 1997), which is the premise to which this paperwill adhere in keeping with this multidimensional construct, wellbeing. Wellbeing, therefore, inthe context of this paper, will be the overall health status of people, which includes access to andcontrol over material resources, environmental and psychosocial conditions, and per capitaconsumption. New Focus: Healthy Life Expectancy One of the drawbacks to the use of life expectancy is the absence of capturing ‘healthy’years of life. Traditionally, when life expectancy is measured it uses mortality data topredetermine the number of years of life that are yet to be lived by an individual, assuming that 13

he/she subscribes to the same mortality patterns of the group. The emphasis on this approach ison length of life, not on the quality of those lived years. The rationale why healthy lifeexpectancy is important in ageing comes against the background that age means increaseddysfunction and the unavoidable degeneration of the human body. Hence, we must seek toexamine more than just the number of years that an individual is likely to survive, and we shouldbe concerned about the quality of those years. Therefore, in attempt to capture ‘quality of livedyears’, the WHO in 1999 introduced an approach that will allow us to evaluate this, ‘disabilityadjusted life expectancy’ (DALE). DALE is not only concerned with length of years to indicatethe health and wellbeing status of an individual or a nation, but the number of years withoutdisabilities and the severity of their influence by reducing the quality of lived years. DALE is a modification of the traditional ‘life expectancy’ approach in assessing health.It uses the number of years lived as an equivalent to ‘full health’. In calculating DALE, thenumber of years of ill-health is weighted based on severity. This is then subtracted from theexpected overall life expectancy to give what is referred to as years of healthy life. Embedded inthis approach is reduction in years because of numbers, and severity of dysfunctions and HIVexperienced by the individual or people within a particular socio-political geography. Having arrived at ‘healthy life expectancy’, the WHO has found that poorer countries lostmore from their ‘traditional life expectancy’ than developed nations. The reasons put forward bythe WHO are the plethora of dysfunctions and the devastating effects of some tropical diseaseslike malaria that tend to strike children and young adults. The institution found that theseaccount for a 14 percent reduction in life expectancy in poorer countries and 9 percent in moredeveloped nations (WHO, 2000b). This system is in keeping with a more holistic approach tothe measure of health and wellbeing, which this study seeks to capture. By using the 14

biopsychosocial model in the evaluation of the wellbeing of aged Jamaicans, we will begin tounderstand the factors that are likely to influence the quality of lived years of the elderly, and notbe satisfied with the increased length of life of the populace. The rationale behind this study isthat it will assist policy-making on health and social services, long term care and pension schemeplanning, and will aid in the understanding of future health needs and the evaluation of futurehealth programmes. Conclusion The discourse on health began centuries ago, but today the issues have a changed focusbecause of new information, and a modification in epistemology about health. In this discoursesome scholarships have used the ‘absence of diseases’ or dysfunctions as a conceptual definitionof health, and in so doing they work substantially to see health from a mechanistic approach.Such an approach treats patient care from a biomedical science standpoint, and the emphasis ison the biology of the organism. The biomedical model as a study of health fails to appreciate thatlong before any ailments (or dysfunctions) appear within an organism, the socio-physical,cultural and psychological milieu would have had an impact on the quality of that organism.Thus, the use of symptomology as the identification of ill-health, and using the opposite of this toindicate health, is one-dimensional, and fails in its bid to encapsulate all the possible aspects thatinfluence the quality of life, wellbeing, and health of people. Following the clear limitations with the construct of health from the perspective of thebiomedical sciences [model], in 1946 the WHO conceptualized a definition of wellbeing that wascomposite and far reaching, and one scholar (Crisps) refers to this as an elusive dream, which isdifficult to operationalize. Although the debate continued for years, George Engel was the firstscholar and psychiatrist to map out a conceptual framework for the WHO’s new construct forhealth as a working definition that guides how he approached patient care. Engel, in the 1950s,began using what he called the biopsychosocial model in treating psychiatric patients. Hebelieved that when a patient goes to a doctor, the individual’s ailment is a complex apparatus ofdifferent tenets, and not merely the outward appearance, which is the identified symptomology. 15

Engel proposed that the medical fraternity should commence approaching patient care from thevantage point of mind, body, and social conditions. Although some scholars and practitionersconcurred with Engel’s beliefs, and practiced this new model [biopsychosocial], and he (Engel,1978, 1977a, 1977b, 1960) got Rochester Medical School to institute this approach in thecurriculum of medical training, substantially the biomedical approach was widely practiced. Traditionally, people were socialized to use symptomology to identify ill-health and thereverse of this meant ‘health’, so much so that scientists still continue to research in thistradition. Some scholarships argue that Engel’s biopsychosocial model is but an ‘abstraction’ (ora theoretical construct), and so with the objective realities of patient care, the use of morbidity isstill the best indicator of the extent of wellbeing. Gradually, the culturalized tradition of thesupremacy of the biomedical model began to be seriously challenged in the 20th century. A group of authors claim that the United States, in the 20th century, expanded theiroperational definition of health from the traditional ‘absence of diseases’ to the biopsychosocialapproach argued by Engel (Brannon, and Feist, 2007; Engel, 1960). It was not until the 1970sthat a scholar, using empirical data, finally provided an econometric model that encapsulateswhat Engel was arguing some 2 decades before (Grossman). Using data, Grossman (1972)showed that the health status of people in the world is influenced by both biological, and aplethora of other social conditions. He laid the foundation that has shaped the present landscapeof social science research on health, wellbeing and quality of life, so much so that a group ofscholars have used the advanced quantitative method to model happiness, which was conceptualto measuring wellbeing. Today Grossman’s model, with some modifications, is being used by some Caribbeanscholars (Bourne, 2007; Hambleton et al., 2005). Using data from Barbados, Hambleton et al.(2005) showed that health (proxy physical functioning) is a function of biological, cultural andsocial conditions. Bourne (2007), using data from Jamaica, expanded on the operationaldefinition of health (or wellbeing) from physical functionality used by Grossman and Hambletonet al. (2005) to that of a composite index which captures physical, functional and economicwellbeing (material possessions). Bourne’s work did not only add to the operational definition ofhealth, but he showed that environmental and psychological conditions in addition to socialfactors do influence health. 16

In sum, only a few studies in the Caribbean have sought to expand the narrow definitionof health inspite of the WHO’s efforts as well as others. The narrow definition of health is stilldominant in contemporary Jamaica as well as other Caribbean nations, and this primarilyaccounts for the image of health that is held by many peoples. It is this narrow definition ofhealth that fashions the health care system, patient care, data collected on health and peoples’image of health, health care and lifestyle practices. This is not only a challenge for public healthspecialists, but for the general populace as one image of health influences his/her perception ofhealth care, lifestyle and views on preventative health. 17

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Longest, B. B. (2002). Health Policymaking in the United States, 3rd. Chicago: Foundation of the American College Healthcare.Lynch, P. M. (2003). Wellness: A National Challenge. Kingston: Grace Kennedy Foundation.Jones, T. G. (2001). Cognitive and psychosocial predictors of subjective wellbeing in older adultshttp://digitalcommons.wayne.edu/dissertations/AAI3010098/ (Retrieved: 30/06/09).Powell, L.M. (1997). Measures of quality of life and subjective well-being. Generation 21, 45.O’Donnell, V, and Tait, H. (2003). Well-being of the non-reserves Aboriginal population. Statistics Canada Catalogue 89-589.Pacione, M. (2003). Urban environmental quality and human wellbeing- a social geographical perspective. Landscape and Urban Planning, 65:19-30.Pacione, M. (1984). The Definition and Measurement of Quality of Life. Quoted in M. Pacione and G. Gordon (eds.). Quality of Life and Human Welfare. Norwick: Geoboks.Putnam, R. (1995). Bowling Alone: America’s Declining Social Capital. Journal of Democracy, 6:65-78.Rice, P.L. (1998). Health psychology. CA, USA: Brooks/Cole Publishing.Ringen, S. (1995). Well-being, measurement, and preferences. Scandinavian Sociological Association 38, no 1:3-15.Sen, A. (1998). Mortality as an indicator of economic success and failure. The Economic Journal 108:1-25.Skevington, S. M., MacArthur, P., & Somerset, M. (1997). Developing items for the WHOQOL: An investigation of contemporary beliefs about quality of life related to health in Britain. British Journal of Health Psychology, 2:55-72.Smith, D. M. (1973). The Geography of social wellbeing in the United States: An introduction to Territorial Social Indicators. New York: McGraw-Hill.Smith, J.P. and R. Kington. (1997). Demographic and Economic Correlates of Health in Old Age. Demography, 34:159-170.Stutzer, A, and Frey, B.S. (2003). Reported subjective well-being: A challenge for economic theory and economic policy. "http://www.crema-research.ch/papers/2003-07.pdf" http://www.crema-research.ch/papers/2003-07.pdf (Retrieved: 31/08/09). 21

Summers, R, and Heston, A. (1995). Standard of Living: SLPOP An Alternative Measure of Nations Current Material Well-Being. http://pwt.econ.upenn.edu/papers/standard_of_living.pdf (Retrieved: 24/01/09).United Nations Development Programmed, UNDP. (2005). Human development report, 2005. New York: UNDP.United Nations Development Programme, UNDP. (2001). Human Development Report, 2000. New York, United States: UNDP.United Nations Development Programme, UNDP. (1998). Human Development Report, 1997. New York, United States: UNDP.United Nations Development Programme, UNDP. (1994). Human Development Report, 1993. New York, United States: UNDP.Veenhoven, R. (1993). Happiness in nations, subjective appreciation of in 56 nations 1946-1992. Rotterdam, Netherlands: Erasmus University.Whang, K. M. (2006). Wellbeing syndrome in Korea: A view from the perspective of biblical counselling. Evangelical Review of Theology 30:152-161.Woolcock, M. (2001). The Place of Social Capital in Understanding Social and Economic Outcomes. ISUMA, 6:11-17.World Health Organization, WHO. (2000b). WHO Issues New Healthy Life Expectancy Rankings: Japan Number One in New ‘Healthy Life’ System. Washington D.C. & Geneva: WHO.World Health Organization, WHO (1948). Preamble to the Constitution of the World Health Organization as adopted by the International Health Conference, New York, June 19-22, 1946; signed on July 22, 1946 by the representatives of 61 States (Official Records of the World Health Organization, no. 2, p. 100) and entered into force on April 7, 1948. “Constitution of the World Health Organization, 1948.” In Basic Documents, 15th ed. Geneva, Switzerland. 22

CHAPTER 2Health MeasurementJamaicans are not atypical in how they conceptualize health and/or how they address patientcare as the antithesis of diseases or dysfunctions (i.e. health conditions). In the 1900s andearlier, Western Societies were using the biomedical model in the measurement and treatment ofhealth, health attitudes and the utilization of health services. This approach emphasizes sickness,dysfunction, and the identification of symptomology or medical disorders to evaluate health andhealth care. Such an approach places significance on the end (i.e. genetic and physicalconditions), instead of the multiplicity of factors that are likely to result in the existing state, orissues outside of the space of dysfunctions. Notwithstanding the limitations of the biomedicalapproach, it is still practiced by many Caribbean societies, and this is fundamentally the case inJamaica. The current paper is an examination of health measurement, and provides at the sametime a rationale for the need to have a more representative model as opposed to the one-dimensional approach of using pathogens in measuring health. Owing to the importance ofhealth in development, patient care and its significance for other areas in society, this paperseeks to broaden more than just the construct, as it goes to the core of modern societies inhelping them to understand the constitution of health and how patient care should be treated.Thus, it provides a platform for the adoption of the biopsychosocial model, which integratesbiological, social, cultural, psychological and environmental conditions in the assessment ofhealth and the outcome of research, by using observational survey data.1. INTRODUCTIONThe construct of health is more than a concept. It is a “leading characteristic of the members of apopulation...” [1] and, ergo, it plays a direct role in the images of health and health care. Amongthe plethora of reasons for the importance of health are not merely the images created by theconstruct, but also its contribution to the production of different tenets of human existence –illness, morbidity, comorbidity, disability, mortality, life expectancy, wellbeing, and so on, aswell as the guide that it affords for health interactions and interventions. In addition to theaforementioned issues, it is of germane significance in aiding us to understand many of thethings that we see. The definition of this single term ‘health’ is important, as a precise use of the 23

construct fashions and connects other important applications such as growth and development,productivity, health care and people’s expectations of health care professionals. One scholar, inhelping us to understand the meaning of a construct, says that “without a well-defined construct,it is difficult to write good terms and to derive hypotheses for validation purposes” [2].Embedded in Spector’s argument is the ‘theoretical abstraction’ of the construct, and how wemay use it for outcome research. In this paper, the author will review the existing literature andidentify particular measures of health, examining how these differ from the WHO’s conceptualdefinition of health [3]. At the same time, within the limitations of the biomedical model, thestudy will evaluate the usefulness of the biopsychosocial model in health and how the image ofhealth influences the health care of people. 1.2 Image of Health Health, however, is more than a ‘theoretical abstraction’. There is an ‘objective reality’ tothis construct. It explains life, and life is an objective reality. Furthermore, health is a valuabletool that ‘drives’ health policies and influences the determinants of health care. Then there is theissue of health care and how this is planned for, as well as the role that health plays in thedevelopment of a society. Health, wellbeing and poverty are well documented in developmentaleconomics by scholars such as Amartya Sen, Paul Streeten and Martin Ravallion as havingcritical roles in understanding human development (or the lack of it). The fascination with healthand wellbeing in developmental studies is primarily because of the direct association betweendevelopment and health. Jamaica is not atypical in how its people conceptualize health and/or how they addresspatient care. In the 1900s and earlier, western societies used the biomedical approach in themeasurement and treatment of health [5]. The biomedical approach emphasizes sickness,dysfunction, pathogens, and disability and medical disorders in the construction of health. Thisapproach places importance on the outcome (or the end) instead of the multidimensionalconditions that are likely to result in the existing state. Notwithstanding the limitations of thebiomedical approach, it is still practiced by many Caribbean societies, and this is fundamentallythe case in Jamaica. This is atypical in many Western nations, as contemporary demographersstill use the antithesis of illness and disability to write about health [6-8]. Rowland wrote that“Measures of population health are of general interest to demographers, sociologists, 24

geographers and epidemiologists. Interdisciplinary concerns here include comparing nationalprogress through the epidemiologic transition, and identifying social and spatial variations withincountries in patterns of disease and mortality” [5]. The United States has left many Caribbean societies behind in how they conceptualizehealth and treat health care. As early as the commencement of the 20th century [4], the UnitedStates shifted their focus from negative wellbeing (i.e. antithesis of diseases) to positivewellbeing. The antithesis of diseases assumes a bipolar opposite between health and diseases.Embedded in this bipolar thinking is that for one to be healthy, he/she must not be experiencingany symptomology of dysfunctions. Hence, the health of people is measured by mortality ormorbidity statistics. Health, however, is more than just the antithesis of diseases to positivepsychology, inclusive of socio-cultural conditions and the environment. Positive wellbeingencapsulates the biomedical model in addition to psychological, socio-cultural andenvironmental conditions. The name that Engel gave to this new approach is the biopsychosocialmodel. The current paper is a discourse on the limitation of the biomedical model, which willprovide a rationale for the need to have a more representative model as against this one-dimensional approach to the measurement of health. Traditionally, health was conceptualised as the ‘antithesis of diseases’ [4]. Using theantithesis of diseases, this construct utilizes a minimization approach or a negative perspective,adopted by western societies, which saw health as the absence of dysfunctions, morbidityconditions or comorbidity. “This definition of health has been largely the result of thedomination of the biomedical sciences by a mechanistic conception of man. Man is viewed byphysicians primarily as a physio-chemical system” [9]. With this thinking, health professionals’evaluation of patient care and diagnostic treatments is based primarily on the identification ofany symptomology of dysfunctions. Hence the standard that is used in the evaluation of health isthe established norm of any deviation from diseases. Rather than conceptualizing health andstating its determinants, this approach uses the identification of symptomology to measurehealth. Therefore, life expectancy is used here as a measure of health. This assumes that oncean individual is alive, it is because there are no dysfunctions to cause death. Embedded in thisassociation is the influence of dysfunctions on health, but there are no other determinants ofhealth except the various symptomologies of diseases. 25

Outside of diseases, there are other determinants of health. Based on the biopsychosocialmodel that George Engel [10, 11] developed, he proposed an approach to the treatment of thehealth care of psychiatric patients that included biological, social and psychological conditions.Such a conceptual framework, unlike the biomedical sciences, introduces and identifies factorsthat are responsible for the health, and by extension the wellbeing, of a population. One scholarcites that “the states of health and disease [are] the expressions of the success or failureexperienced by the organism in its efforts to respond adaptively to environmental changes” [12].Again, when health is defined as the antithesis of diseases its determinant is solely biological, butthis is clearly one-dimensional, and many scholars have shown that health is, in fact,multidimensional, and composed of biopsychosocial and environmental conditions. Another aspect to health is the positive association between the determinants of healthand health care policies. Health care policy makers use the determinants of health as thebenchmark that directs their planning. Therefore, when health policies are too narrow, the healthdeterminants which fashion a population’s health care will take a minimal approach, as this isbased on the image of health. One scholar puts it succinctly, “…health policies affect healththrough their effects on health determinants” [13], which speaks to the importance of ‘good’hypotheses in the schema of things. It should be noted that the hypotheses allow us to derive thepossible determinants of health, which would be used to evaluate the effectiveness of the healthpolicy, and so show how they affect health (see Figure 1). Determinants of Health – Health Policy Health Bi l i lFigure 1: The relation between health policy and health, and the roles of health determinants 26

The goal of the policy is to decrease the incidence of chronic diseases, high risk sexual behaviour/violence and injury through the adaptation of appropriate behaviours by the population and particularly young children, adolescents and young adults [14]. The general conceptualization of health in Jamaica is the “antithesis of diseases”. Thisexplains why many people emphasize health care for morbidity conditions, genetics, or physicalfunctioning (i.e. their biology). Another indicator of the usage of this perspective can be seen inhow data are collected on health in Jamaica and/or in the wider Caribbean. Such a situationhighlights the minimization or substantially negative approach in the construct of health. Despitethe title of the Ministry of Health’s ‘National Policy for the Promotion of Healthy Lifestyle inJamaica’, throughout the paper the MOH [14] emphasizes mortality, diseases, dysfunctions andreproductive health, which highlights Jamaicans’ perspective on health. This is also evident inthe Planning Institute of Jamaica which is responsible for policy, along with the StatisticalInstitute of Jamaica, collecting information on health by way of (1) preventative (i.e. behaviourmodification), curative (surgical procedures, visits to health practitioners), restorative (physicalrehabilitation), and palliative (i.e. pain management) measures, and ownership of healthinsurance. Thus, the hypotheses that arise from the collected data are in keeping with thenarrowed definition for which the data was initially gathered by the research design exercise.The hypothesis of the presence of pathogens such as poor air being the cause of diseases, orclassification of ill-health, is ancient, within the context that health has been expanding frommere physical functioning for some time. This hypothesis assumes that a person who does nothave an ailment (or disease condition) is healthy, which is categorically false, as healthpsychologists have shown that psychological conditions do influence wellbeing [4]. Thisperspective dates back to Galen in Ancient Rome (i.e. 130 CE – 200 CE). A point is even moreforcefully made in a study by two economists, which found a strong direct relationship betweenhappiness and wellbeing [15]. Other researchers found an association between ‘positive and/ornegative’ mood(s) and wellbeing [16]. This paper is in two parts, designed: (1) to providedetailed evidence that will support the rationale for an expanded concept which looks at healthand wellbeing, and (2) to illustrate the purpose and significance of the expanded model thatEngel termed the biopsychosocial model. This paper however is not arguing for a 27

biopsychosocial hybrid model, which would include biological, economic, social, cultural,psychological and ecological conditions.2. P HYSICAL F UNCTIONING Caring for patients suffering from ill-health has a long history, which dates back to theAgrarian societies. During those earlier periods, man in his quest to address health conditionsdid so primarily from the standpoint of physical functionality. Based on the annals of time, theliterature showed that people would treat biological dysfunctions and sometimes the ‘spirit’ intheir pursuit of making man healthier. This approach dates back as far as ancient Rome (i.e. 130CE – 200 CE). Despite the WHO offering us a better way in the pursuit of happiness andwellness, man continues to return to the biomedical model of health. One of the reasons for thecontinued acceptance of the use of the biomedical model is the dominance of technology in thisprocess. As technology is still primarily intended to address physical dysfunctions and theabsence of pathogens, many studies conducted in early societies have not only linked the conceptof health to medical conditions and by extension health care, but have served as anotherimportant indicator in determining lifespan. In 1884, an Englishman named Francis Galton who was both a mathematician andmedical doctor researched the ‘physical and mental functioning’ of some 9,000 people betweenthe ages of 5 and 80 years [17]. Galton wanted to measure the human life span in relation to thephysical and mental functioning of people, so he sponsored a health exhibition that would allowhim to collect data for analysis. Health was traditionally defined as the “antithesis of diseases”,which explains the predominance of physical functioning in policy making and health care, andjustifies Galton’s wanting data on the physical functioning of people. The 20th century has brought with it massive changes in the typologies of dysfunctions,where deaths have shifted from infectious diseases such as tuberculosis, pneumonia, yellowfever, Black Death (i.e. Bubonic Plague), smallpox and ‘diphtheria’ to illnesses such as cancer,heart disease and diabetes [14]. Although diseases have shifted from infectious to degenerate,chronic non-communicable illnesses and science, medicine and technology have expanded sincethen, and the image of health in contemporary Jamaica still lags behind many developed nations.Morrison [18] titled an article ‘Diabetes and Hypertension: Twin Trouble’ in which heestablishes that diabetes mellitus and hypertension have now become problems in Jamaicans and 28

in the wider Caribbean. This situation was equally corroborated by Callender [19] and Steingo[20] at the 6th International Diabetes and Hypertension Conference, which was held in Jamaica inMarch 2000. They found that there is a positive association between diabetic and hypertensivepatients - 50% of individuals with diabetes had a history of hypertension [19, 20]. Prior to thosescholars’ work, Eldemire [21] found that 34.8% of new cases of diabetes and 39.6% ofhypertension were associated with senior citizens (i.e. ages 60 and over). Accompanying thisperiod of the ‘age of degenerative and man-made illnesses’ are life expectancies that now exceed50 years. Before the establishment of the American Gerontology Association in the 1930s and theirmany scientific studies on the ageing process [17], many studies were done based on thebiomedical model, i.e. physical functioning or illness and/or disease-causing organisms [4].Many official publications used either reported illnesses or the prevalence of seeking medicalcare for measuring sicknesses. Some scholars have still not moved to the post biomedicalpredictors of health status. The dominance of this approach is so strong and present within thetwenty-first century, that many doctors are still treating illnesses and sicknesses without anunderstanding of the psychosocial and economic conditions of their patients. To illustrate thismore vividly, the researcher will quote a sentiment expressed by a medical doctor in ‘TheCaribbean Food and Nutrition Institute’s Quarterly [22]. A public health nutritionist, Dr.Kornelia Buzina [23], says, “When used appropriately, drugs may be the single most importantintervention in the care of an older patient … and may even endanger the health of an olderpatient …” This proposition highlights the paradox in biomedical sciences as well as showing theneed to expand the image of health beyond this negative approach to it. Within the context of the WHO’s definition and growing numbers of studies that haveconcluded that health should be a multidimensional construct, in 2007 a group of medicalpractitioners used physical functionality and dysfunctions to treat an elderly patient who wassuffering from a particular health condition [24]. The researchers put forward an examination ofa 74-year old man who with “...a long history of ischaemic heart disease, presented withincreasingly prolonged episodes of altered consciousness” [24]. The physicians cite theargument that “many elderly patients may have more than one cause for this symptom” [24],which summarizes their perspective and reliance on understanding medical disorders in thedispensing of patient care. Throughout the study, the scholars and medical practitioners did not 29

seek to evaluate the psychological, social, and environmental conditions and their possibleinfluence on the current state of dysfunction of the elderly patient. Despite the seemingcomplexity of the result of the detailed inquiry into the neurological conditions of the patient,and the keen medical examination of the patient, his medical condition continued for yearsunabated. This emphasises the dominance of the biomedical model, and it goes beyond thissingle study, as a review of publications in the West Indian Medical Journal – a medical journalin Jamaica – from 1960-2009 revealed a few studies that have gone beyond the use of thebiomedical approach to the examination of patient care. In seeking to treat the 74-year old patient, the medical practitioners examined and re-evaluated various medical problems. Thus, owing to the thinking of this group of researchers,they used ‘multiple medications’ in the treatment of the patient’s condition. It was clear from theperspective of the scholars that what guided their intervention were the biomedical sciences (i.e.physical functionality or dysfunctions). In this case, health is the ‘antithesis of diseases’. It isthe narrow definition of health – negative health (i.e. biomedical approach) – which explains theimage of health and health care for those scholars and researchers. Apart from the reasons for theuse of diagnosed conditions, life expectancy and other physical issues are utilized in examininghealth, because of the precision in using them to evaluate health as against other approaches thatare more holistic and broader in scope. 2.2 Health measurement The narrow definition of health is the “antithesis of diseases” which Longest [13] says isthe “…absence of infection or the shrinking of a tumour” which can be called dysfunctions (see[1, 4]. As we mentioned earlier, the ‘antithesis of diseases’ idea dates back to Galen in AncientRome. It was widespread in the 1900s, and so medical professionals used this operationaldefinition in patient care. Another fact during this time was that technology was fashioned in thisregard, addressing solely physical dysfunctions. This definitional limitation may be a rationalefor the World Health Organization, nearing the mid-1900s, declaring that health is the “state ofcomplete physical, mental, and social wellbeing, and not merely the absence of diseases orinfirmity” [3]. It should be noted that this conceptual definition which is in the Preamble to theconstitution of the WHO which was signed in July 1946 and became functional in 1948,according to one scholar, from the Centre of Population and Development studies at Harvard 30

University, is a mouthful of sweeping generalizations. According to Bok [25], the definitionoffered by the WHO is too broad and difficult to measure, and at best it is a phantom. Otherintelligentsia point to the WHO’s definition as a difficulty for policy formulation, because itsscope is ‘too broad’ [26]. The question is “Is the conceptual definition formulated by WHO sobroad that those policies faced difficulty in formation”, and by extension should we regress to apre-1946 conceptualization of health because a construct is difficult to operationalize today?Undoubtedly, health extends beyond diseases and is tied to cultural and psychological elements,personal responsibility, lifestyle, environmental and economic influences as well as qualitynutrition [27-41]. Those conditions are termed determinants of health [26]. The WHO’s perspective must have stimulated Dr. George Engel to pursue a modificationof the narrow approach to the health and health care debate. Dr. Engel was a psychiatrist whoformulated the construct called the biopyschosocial model in the 1950s. He believed that when apatient comes to a doctor, for example for a mental disorder, the problem is a symptom not onlyof actual sickness (biomedical), but also of social and psychological conditions [10, 11]. Hetherefore campaigned for years for physicians to use the biopsychosocial model for the treatmentof patients’ complaints, as there is an interrelationship between the mind, the body and theenvironment. He believed so deeply in the model, convinced that it would help in understandingsickness and providing healing, that he introduced it into the curriculum of Rochester medicalschool [42, 43]. Medical psychology and psychopathology was the course that Engel introducedinto the curriculum for first year medical students at the University of Rochester. This approachto the study and practice of medicine was a paradigm shift from the biomedical model that waspopular in the 1980s and 1990s. The Planning Institute of Jamaica and the Statistical Institute of Jamaica employ thebiomedical model in capturing the health status and/or wellbeing of the populace. This approachwas obsolete by the late 20th century, as in 1939 E.V. Cowdy, a cytologist in the United States;expanded on how ageing and health status should be studied in the future. Cowdy broadened thebiomedical model in the measurement of the health status of older adults by including social,psychological and psychiatric information in his study entitled the “Problem of Ageing” [17].The Ministry of Health [MOH] [14], however, has published a document in which it shows thathealth interfaces with biomedical, social and environmental conditions. One of the reasons putforward by the MOH to help in understanding why they arrived at the aforementioned position, 31

was the rationale behind the explanation for the changes in the typology of diseases – that is,from infectious and communicable diseases to chronic conditions. The institution cites that this issubstantially because of the lifestyle practices of Jamaicans. One of the ironies within thedocument was in the ‘main components of the policy for the promotion of a healthy lifestyle inJamaica’, which cites that the goal of the policy was to reduce the incidence of communicableand infectious diseases, which speaks to society’s subconscious emphasis on the biomedicalmodel in conceptualizing health and its treatment. Embedded within the MOH’s 2004publication are repetition and the focus on seeking to reduce physiological conditions that affectthe individual. The MOH admits, however, that health interfaces with body and environment,which is an expansion of the biomedical model, but all indications in their document point to thebiomedical science approach in the application of the policy. The institution recognized thatpsychological factors (for example, self-esteem, and resilience) play a role in influencing health,so much so that it included these within its ‘goal of the strategic approach’, but they were notsupported in the ‘broad objectives of the strategic approach’. Critical to all of this is the acceptance that the definition of health is fundamental to theconstruction of those hypotheses that are used to formulate health policies. According to Longest[13], the conceptualization of health is indeed critical to all the things that rely on its definition.Longest writes: The way in which health is conceptualized or defined in any society is important because it reflects the society’s values regarding health and how far the society might be willing to go in aiding and supporting the pursuit of health among its members [13]. In Jamaica health policies are still driven by physical functioning, which is an obsoleteapproach to addressing health and by extension wellbeing. This limited approach to health andwellbeing means that little consideration is given to other factors such as lifestyle, psychologicalstate, the environment, crime and violence, among others. This of course implies that Jamaica’shealth policy is limited in its orientation, as it is largely driven by hypotheses that supportphysical functioning. 32

2.3 Biomedical Approach Dr. Buzina admits that wellbeing is fundamentally a biomedical process [23]. Thisconceptual framework derives from the Newtonian approach of basic science as the onlymechanism that could garner information, and empiricism being the only apparatus to establishtruth or fact. It is still a practice and social construction that numerous scholars and medicalpractitioners [24] continue to advocate despite new findings. Simply put, many scholarships stillput forward a perspective that the absence of physical dysfunction is synonymous with wellbeing(or health, or wellness). Such a viewpoint appears to hold some dominance in contemporarysocieties, and this is a widespread image held in Jamaica. Then there are issues such as the deathof an elderly person’s life-long partner; a senior citizen taking care of his/her son/daughter whohas HIV/AIDS; an aged person not being able to afford his/her material needs; someone olderthan 64 years who has been a victim of crime and violence and continues to be a victim; seniorswho reside in volatile areas who live with a fear of the worst happening, the inactive aged, andgenerally those who have retired with no social support, are equally sharing the same healthstatus as the elderly who have not been on medication because they are not suffering frombiomedical conditions to the extent that they need to be given drugs. Two medical doctors writing in Kaplan and Saddock’s Synopsis of Psychiatry noted thatphysicians are frequently caught in theorizing that normality is a state of health [44]. Theyargued that doctors’ definition of normality correlates with a traditional model (biomedical) thatemphasizes observable signs and symptoms. Using psychoanalytic theories, Saddock andSaddock [44] remarked that the absence of symptoms as a single factor is not sufficient for acomprehensive outlook on normality. They stated, “Accordingly, most psychoanalysts view acapacity for work and enjoyment as indicating normality…” [44]. Among the challengesassociated with this method (biomedical model), is its emphasis only on curative care. Such anapproach discounts the importance of lifestyle and preventative care. In that, health is measuredbased on experiences with illnesses and/or ailments, with limited recognition being placed onapproaches that militate against sickness and/or diseases. The biomedical approach is somewhatbiased against an understanding of multi-dimensional man, which is not in keeping with theholistic conceptualization of health as offered by the WHO. 33

The new paradigm 34

2.4 Biopsychosocial Approach In the 1950s, George Engel, a physician, teamed with John Romano, a young psychiatrist,to develop a biopsychosocial model for inclusion in the curriculum of the University OfCincinnati College Of Medicine, which measured the health status of people. It is referred to asEngel’s biopsychosocial model. Engel’s biopsychosocial model [10, 11, 43], recognized thatpsychological and social factors coexisted along with biological factors. It was a general theoryof illness and healing, a synergy between medicine, psychiatry and the behavioural sciences [42].Therefore, from Engel’s model, wellbeing must include factors such as motivation, depression(or the lack thereof), biological conditions (such as illnesses and diseases), social systems,cultural, environmental and familial influences on the appearance and occurrence of illness. Some scholars may argue that this paper appears to believe that only quantitative studiesmay provide answers to the examination of the determinants of health. This is absolutely not so,and we use a qualitative study to show people’s perception of what contributes to a particularmedical condition. In a qualitative study that uses in-depth interviews with some 17 Malaysianmen aged between 40 and 75 years old, some scholars examined the perception of these men inrelation to erectile dysfunction (ED) – the sample was a convenient one of men who weresuffering from ED and who were willing to speak about their condition. When the interviewersasked the participants about the possible causes of ED, many of them outlined biomedicalconditions such as diabetes, hypertension, medications, past injuries, ageing and then camelifestyle practices (i.e. smoking) and psychosocial factors [45]. Embedded in this perception isthe respondents’ emphasis on pathophysiological conditions in health measurement andintervention. Although the sampled respondents do believe that psychosocial factors play a rolein health status, it should be noted here that they did not itemize those conditions. This speaks tothe conceptualization of health that these respondents have come to accept, and the fact that theybelieve that health is not limited to biomedical sciences. Using their definition of health, thestudy shows how culture plays a pivotal role in determining how men will seek health careirrespective of the nature of their condition. According to a number of demographers [46, 47], health has been conceptualized as“functioning ability”. These pundits categorized “functioning ability” as – (i) being able toprovide both personal care and independent living but having some difficulty in performing these 35

tasks or in getting about outside the home, (ii) having no functioning difficulties, (iii) beingunable to independently provide personal care, and finally (iv) being able to provide personalcare but not able to manage life in the home independently” [46].3.0 EXPANSION OF THE B IOMEDICAL MODEL Studies reveal that positive moods and emotions are associated with wellbeing [48] as theindividual is able to think, feel and act in ways that foster resource building and involvementwith particular goal materialization [49]. This situation is later internalized, causing theindividual to be self-confident, from which follow a series of positive attitudes that guide furtheractions [50]. Positive mood is not limited to active responses by individuals, but a study showedthat “counting one’s blessings,” “committing acts of kindness”, recognizing and using signaturestrengths, “remembering oneself at one’s best”, and “working on personal goals” all positivelyinfluence wellbeing [50,51]. Happiness is not a mood that does not change with time orsituation; hence, happy people can experience negative moods [52]. Human emotions are the coalescence of not only positive conditions but also negativefactors [53]. Hence, depression, anxiety, neuroticism and pessimism are seen as a measure of thenegative psychological conditions that affect subjective wellbeing [54-56]. From Evans andcolleague [54], Harris et al. [55] and Kashdon’s monographs [56], negative psychologicalconditions affect subjective wellbeing in a negative manner (i.e. guilt, fear, anger, disgust); andthe positive factors influence self-reported wellbeing in a direct way - this was corroborated in astudy conducted by Fromson [57]; and by other scholars [53, 58,59]. Acton and Zodda [60]aptly summarized the negative affective of subjective wellbeing in the sentence that reads“expressed emotion is detrimental to the patients recovery; it has a high correlation with relapseto many psychiatric disorders.” From the theologians’ perspective, spirituality and religiosity are critical components inthe lifespan of people. They believe that man (including woman) cannot be whole withoutreligion. With this fundamental concept, theologians theorize that man cannot be happy, or feelcomfortable without a balance between spirit and body [62]. In order to achieve a state ofpersonal happiness, or self-reported subjective wellbeing, some pundits put forward a constructthat people are fashioned in the image of God, which requires some religiosity before man can behappy or less stressed. Religion is, therefore, association with wellbeing [63-65] as well as low 36

mortality [66]. Religion is seen as the opiate of the people from Karl Marx’ perspective, buttheologians, on the other hand, hypothesize that religion is a coping mechanism againstunhappiness and stress. According to Kart [67], religious guidelines aid wellbeing throughrestrictive behavioural habits which are health risks, such as smoking, drinking alcohol, and evendiet. The discourse of religiosity and spirituality influencing wellbeing is well-documented[68, 69]. Researchers have sought to concretize this issue by studying the influence of religiosityon quality of life, and they have found that a positive association exists between those twophenomena [70]. They found that the relationship was even stronger for men than for women,and that this association was influenced by denominational affiliation. Graham et al.’s [71] studyfound that blood pressure for highly religious male heads of households in Evans County waslow. The findings of this research did not dissipate when controlled for age, obesity, cigarettesmoking, and socioeconomic status. A study of the Mormons in Utah revealed that cancer rateswere lower (by 80%) for those who adhered to Church doctrine [72, 73] than those with weakeradherence. In a study of 147 volunteer Australian males between 18 and 83 years old, Jurkovic andWalker [65] found a high stress level in non-religious as compared to religious men. Theresearchers in constructing a contextual literature quoted many studies that have made a linkbetween non-spirituality and “dryness”, which results in suicide. Even though Jurkovic andWalker’s research was primarily on spiritual wellbeing, it provides a platform that can be used inunderstanding the linkages between the psychological status of people and their generalwellbeing. In a study which looked at young adult women, the researchers found that spiritualityaffects the physical wellbeing of a populace [69]. Embedded within that study is the positiveinfluence of spirituality and religion on the health status of women. Edmondson et al.’s workconstituted of 42 female college students of which 78.8 percent were Caucasian, 13.5 percentAfrican-American, 5.8 percent Asian and 92 percent were non-smokers. Health psychologists concurred with theologians and Christians that religion influencespsychological wellbeing [74, 75]. Taylor [74] argued that religious people are more likely tocope with stressors than non-religious individuals, which explains the former’s better healthstatus. She put forward the position that this may be done through avoidance or vigilant 37

strategies. This response is an aversive coping mechanism in addressing serious monologue orconfrontational and traumatic events. Coping strategies, therefore, are psychological tools usedby individuals to problem-solve issues, without which they are likely to construct stressors andthreaten their own health status. Taylor [74] said that "some religious beliefs also lead to betterhealth practices", producing lower mortality rates from all cancers in Orthodox Christians.4. EVIDENCE OF USE FOR BIOPSYCHOSOCIAL MODEL Even though policy makers are cognizant of the importance of healthy lifestyle practicesand their influence on wellbeing [76], we continue to sideline them in understanding healthstatus, and using this concept in the formulating of hypotheses that will drive a broader policyfocus of health care for the populace. This is evident in our neglect to expand studies for policypurposes that collect data on health using the biopsychological model, meaning that policyformulators are emphasizing physical vulnerability or dysfunction to measure health status. Isthere a study that has sought to use a maximization definition of health that will be able to betterevaluate and plan for the wellbeing of Jamaicans? A study conducted in Barbados reveals that there is a statistical causal relationshipbetween socioeconomic conditions and health status. The findings revealed that 5.2% of thevariation in reported health status was explained by the traditional determinants of health(disease indicators – See Table 5.1.1). Furthermore, when this was controlled for currentexperiences, the percentage fell to 3.2% (falling by 2%). When the current set of socioeconomicconditions were used they accounted for some 4.1% of the variations in health status, while 7.1%were due to lifestyle practices, compared to 33.5% that were as a result of current diseases [34].It holds that the importance placed by medical practitioners on the current illnesses – as anindicator of health status – is not unfounded as people place more value on biomedicalconditions as being responsible for their current health status. Despite this fact, it is obviousfrom the data – using 33.5% - that there are other indicators that explain some 67.5% of thereason why health status should be as it is. Furthermore, with an odds ratio of 0.55 for numberof illnesses, there is a clear suggestion that the more people reporting illnesses, the lower will betheir health status [34]; and this was equally so for more disease symptoms – odds ratio was0.71). 38

Figure 1 above is a depiction of the use of the biopsychosocial model in the study ofhealth status. This research was conducted in Barbados between 1999 and 2000, in which healthstatus was predicted by a composite function of five general typologies of variables. The modelshows that health status is not primarily limited to biomedical conditions – such as diseases andailments – as has been the custom of many scholars. While different indicators as used by theseresearchers may not be possible in this paper because of the limitation of the secondary dataset –for example ‘current lifestyle risk factors’, ‘childhood nutrition’, ‘childhood diseases’,‘environmental factors’, to name a few – despite the data’s shortcomings, the study emphasizesthe use of a multidimensional approach in the study of wellbeing. Bourne [27], using secondary data, encapsulates George Engel’s conceptual idea of amultidimensional model which incorporates biological, social, psychological, environmental andsocial conditions in examining wellbeing. Wellbeing is operationally defined as materialresources, illness and total expenditure of households. The sample is drawn from a nationallyrepresentative survey of 25,018 Jamaicans, some 9.3% of the sample being elderly. From asample of 2,320 elderly Jamaicans (ages 65+ years), Bourne [27] found that 10 of the 14predisposing variables explain 36.8% of the variance in wellbeing. Of the 10 statisticallysignificant variables, the five most important ones, in descending order, are (1) area of residence(β=0.227), (2) cost of medical care (β=0.184), (3) psychological conditions – [total positiveaffective conditions] - (β=0.138), (4) ownership of property (β=0.135), and (5) crime (β=0.111).Among the other factors, which are the 5 least important conditions, are negative affectiveconditions, marital status, educational level, average occupancy per room, age of residents, andthe environment. Thus, whether or not we use Grossman’s model [77], Hambleton et al.’s model[34] or Bourne’s models [27-33] it is clear from them that wellbeing extends beyond biologicalconditions to include psychological, environmental, and social conditions. Another study was conducted by Bourne [30] of some 3,009 elderly Jamaicans (60 yearsand older), with an average age of 71 years and 10 months ± 8 years and 6 months, of which67% (n=2,010) resided in rural areas, 21% (n=634) dwelled in Other Towns and 12% (n=365)lived in the Kingston Metropolitan Area. The mean General Wellbeing of elderly Jamaicans waslow (3.9 out of 14 ± 2.3). Bourne’s model [30] identified 10 explanatory variables which explain40.1% (adjusted R-squared) of the variance in general wellbeing. In this study he deconstructed 39

the general model into (1) economic wellbeing and (2) physical wellbeing (proxy by healthconditions). Using the same set of explanatory variables, the latter model explains 3.2% of thevariability in wellbeing (proxy by health conditions) compared to 41.3% for the former model(i.e. economic wellbeing using material economic resources). General Wellbeing was operationalas material resources and functional limitation (or health conditions). Material economicresources constitute ownership of durable goods (such as motor vehicles, stereo, washingmachines, et cetera); income (proxy by income quintile); and financial support (e.g. socialsecurity and other pensions). Hence, it follows that the biopsychosocial model is a better proxyfor wellbeing; and that functional limitation is still not a good proxy for wellbeing as used byHambleton et al. Grossman and even Smith and Kington [78]. Globally, regionally and especially domestically, the most popular space in researchconcerning wellbeing is the biomedical approach; its popularity is fuelled by the combination ofthe traditional operational definition of health (good physical health) and the dominance of themedical sciences in this field of enquiry. The number of studies on mortality, structuralalterations and functional declines in body systems, genetic alterations induced by exogenousand endogenous factors, prevalence and incidence of diseases, and certain diseases asdeterminants of health, clearly justifies establishing leniency towards medical science in thestudy of health and health care. Engel [10, 11] accredited the biomedical model that governshealth care to the practice of pundits over the last 300 years. This model assumes thatpsychosocial processes are independent of the disease process. Engel argued for the bio-psychosocial model that it includes biological, psychological, and social factors, which is a closematch to the multi-dimensional aspect of man. With this as the base, it can be construed fromEngel’s thrust behind the biopsychosocial model that the previous model is a reductionisticmodel. Engel’s biopsychosocial model in analyzing health emphasizes both health and illness,and maintains that health and illnesses are caused by a multiplicity of factors. Engel’stheorizing, therefore, is better fitted for the definition of health coined by the World HealthOrganization. In Jamaica, only a miniscule number of studies have sought to analyze the effect of thedeath of a family member or close friend, violence, joblessness, psychological disorders andsexual abuse, on wellbeing, or social change on health, area of residence on quality of life and 40

the perception of ageing and its influence on health conditions. Morrison [18] alluded to atransitory shift from infectious communicable diseases to chronic non-communicable diseases asa rationale for the longevity of the Anglophone Caribbean populace. This was equally endorsedby Peña [79], the PAHO/WHO representative in Jamaica. They argued that this was not the onlyreason for the changing life expectancy. Morrison summarized this adequately, when he saidthat: Aiding this transition is not only the increased longevity being enjoyed by our islanders but also the changing lifestyle associated with improved socioeconomic conditions [18] With the post-1994 widened definition of health as put forward by the WHO, people arebecoming increasingly cognizant of the fact that socio-cultural factors such as geographicallocation, income, household size and so on, as well as several psychological factors, explainwellbeing; hence the new definition of health has coalesced biomedical variables and socio-cultural and psychological variables in the new discourse on wellbeing. Stressors may arise from within the individual or outside his/her environment. One suchexternal stressor that may affect the individual is the death of loved ones. Response to themortality of close family members may be more traumatic, depending on expectancy or non-expectancy. Bereavement influences the incidence of mortality. This may result in exhaustion ofthe individuals adaptive reserve. The person’s body wears down and becomes highly vulnerableto morbidity and even death. Rice put forward a study that contradicted an association betweenbereavement and mortality. He wrote that "Fathers who lost sons in war had lower mortalityrates than those who lost son in accidents" [75]. Despite that study, Rice quoted other studies[80] that showed the impact of stress on human physiology. He argued that it is suppressionduring and after bereavement that creates the stressors, which become potent devices formortality and morbidity. Lusyne, Page and Lievens’ [81] study finds that there is an associationbetween bereavement and mortality. However, this is more likely to occur in the short-run (i.e.during the first 6 months after the death of the spouse). As there are a number of confoundingsituations which in the long-run could offset the likelihood of mortality, such as remarriage,social support from other family members, grandchildren and so on, bereavement may notnecessarily be a constant in one’s life. Nevertheless, Lusyne, Page and Lievens affirm with other 41

studies that the loss of a long-time partner may result in the death of the living spouse. Theexplanations given for this eventuality are – (i) role theory as the surviving partner may find therole played by the other partner too stressful and so (ii) may not be able to adapt to the new rolealone; this is more a male phenomenon [81]. The Planning Institute of Jamaica and Statistical Institute of Jamaica collect data on ill-health, and questions are asked based on visits to health practitioners, healers and pharmacies,injuries, ailments, ownership of health insurance, duration of the disease or illness, cost oftreatment for ailments and injuries, and mental disability. Those questions are clearly derivativesfrom the biomedical model, as they seek to address physical functioning without equallyemphasizing culture, lifestyle behaviour, depression, stress, fatigue, trust for others, perceptionof one’s position in current society and the likelihood of one’s place in the future, religiosity,time periods, HIV/AIDS of family members or the individual and how it is likely to influence thehis/her health and wellbeing, social involvement in various institutions, and issues on positiveaffective conditions.5. CONCLUSION In sum, any definition of the construct of health must be multidimensional in nature.Such a definition must include (1) personal and environmental conditions, (2) social factors, (3)psychological conditions, (4) diagnosed illness, and (5) self-determination of wellbeing. If healthis solely based on illnesses (i.e. biomedical model), we would have failed in our bid tooperationally define a construct that is comprehensive enough to encapsulate all the tenets thatwould capture man in his complex milieu. Health is not simply a construct. It plays a criticalrole in the formulation of policy for health care, and in the development of the society. Thus, ifwe emphasize only the biomedical approach to the study of health, its underpinnings could onlybe symptomology. This approach fails to capture issues outside of the mechanistic structure ofman’s conception of biomedical sciences. Concurringly if health care professionals were to useas their premise dysfunctions to indicate health, which is the deviation from the norm, this imageof health would affect policy formulation and intervention programmes which are gearedtowards this narrow conceptualization. But this approach lacks are clear characteristics outsideof illnesses that will encapsulate wellness, wellbeing, and healthy life expectancy in amultidimensional human. Thus, the biomedical model relies on illness identification to capture 42

health and this fashions the health care system, which also limits health coverage outside of thisnegative view of health. This is undoubtedly suboptimal, and does not account for health. Thehealth services in the Caribbean, and in particular Jamaica, are best described as medicalservices, as they are still fundamentally structured around the biomedical model which isembedded as the image of health, and not psychosocial, economic and ecological wellbeing.Although the WHO as early as the 1940s provides a definition of health that is comprehensiveand complex, some scholars believe that it is elusive and by extension immeasurable. There aremerits to the argument of those academics, but the emphasis should not be the difficulty of howoperationalizing the construct labels it ‘elusive’. Instead the goal should have been forresearchers and academics alike to formulate a working definition of the conceptual frameworkcreated by the WHO. Thus, when Grossman in the 1970s moved away from the difficulty posedby the WHO’s conceptual framework, he developed an econometric framework that laid thefoundation for the measure of this seemingly ‘elusive’ construct. Other scholars have built onthe initial theoretical model introduced by Grossman, and Bourne in particular has addedpsychological and environmental conditions to the already established factors of the healthmodel. The constitution of the World Health Organization (WHO) states that “Health is a stateof complete physical, mental and social well-being and not merely the absence of diseases orinfirmity”, [3]. Hence, any use of morbidity statistics, dysfunctions, sickness, diseases or ill-health to conceptualize health is limited, and by extension is a negative approach to the treatmentof this construct. Health, health care, and patient care are critical components in development, asunhealthy people will not be able to offer to the society their maximum, neither will they be ableto comparatively contribute the same to productivity and production as their healthycounterparts. Therefore, the conceptualization of health is not merely a concept but a workingproduct that affects all aspects of society. 43

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58. McCullough, M. E., Bellah, C.G., Kilpatrick, S.D., and Johnson, J.L. (2001) Vengefulness: Relationships With Forgiveness, Rumination, Well-Being, and the Big Five. Personality and Social Psychology Bulletin, 27, 601-610.59. Watson, D., Clark L.A., and Tellegen, A. (1988) Development and validation of brief measures of positive and negative affect: The PANAS Scale. Journal of Personality and Social Psychology, 54, 1063-107060. Watson, D., Clark, L.A., and Tellegen, A. (1988) Positive and negative affectivity and their relation to anxiety and depressive disorders. Journal of Abnormal Psychology, 97, 346-35361. Acton, G. S. and Zodda, J. J. 2005. Classification of psychopathology: Goals and methods in an empirical approach. Theory of Psychology, 15, 373-399.62. Whang, K. M. (2006) Wellbeing syndrome in Korea: A view from the perspective of biblical counseling. Evangelical Review of Theology, 30, 152-161.63. Krause, N. (2006) Religious doubt and psychological well-being: A longitudinal investigation. Review of Religious Research, 47, 287-302.64. Moody, H. R. (2006). Is religion good for your health? The Gerontologist, 14, 147-149.65. Jurkovic, D. and Walker, G. A. (2006) Examining masculine gender-role conflict and stress in relation to religious orientation and spiritual well-being in Australian men. The Journal of Men’s Studies, 14, 1:27-46.66. House, J.S., Robbins, C., and Metzner, J.L. (1982) The Association of Social Relationships and Activities With Mortality: Prospective Evidence From the Tecumseh Community Health Study. American Journal of Epidemiology, 116, 123-140.67. Kart, C. S. (1990) The Realities of Aging: An introduction to gerontology, 3rd. Allyn and Bacon, Boston.68. Frazier, C., Mintz, L. B. and Mobley, M. (2005) A Multidimensional Look at Religious Involvement and Psychological Well-Being Among Urban Elderly African Americans. Journal of Counseling Psychology, 52, 583-590.69. Edmondson, K.A., Lawler, K.A., Jobe, R.L., Younger, J.W., Piferi, R.L. and Jones, W.H. (2005) Spirituality predicts health and cardiovascular responses to stress in young adult women. Journal of Religion and Health, 44, 161-171.70. Franzini, L., and Fernandez-Esquer, Maria Eugene. (2004) Socioeconomic, cultural, and personal influences on health outcomes in low income Mexican-origin individuals in Texas. Social Sciences and Medicine, 59, 1629-1646.71. Graham, T. W., B. H. Kaplan, J. C. Cornoni-Huntley, S. A. James, C. Becker, C. G. Hames, and S. Heyden. (1978) Frequency of church attendance and blood pressure elevation. Journal of Behavioral Medicine, 1, 37-43.72. Gardner, J.W., and Lyon, J.L. (1982) Cancer in Utah Mormon men by lay priesthood level. American Journal of Epidemiology, 116, 243-257.73. Gardner, J.W., and Lyon, J.L. (1982) Cancer in Utah Mormon women by church activity level. American Journal of Epidemiology, 116, 258-265.74. Taylor, S. (1999) Health psychology, 4th ed. United States of America: McGraw-Hill.75. Rice, P. L. (1998) Health psychology. Brooks/Cole Publishing, Los Angeles.76. Jamaica Social Policy Evaluation [JASPEV]. (2003). Annual Progress Report on National Social Policy Goals 2003. Cabinet Office, Kingston.77. Grossman, M. (1972) The demand for health- a theoretical and empirical investigation. National Bureau of Economic Research, New York. 47

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CHAPTER 3Why demographers should study wellbeing of the aged?Traditionally, demographers have sought to analyze and provide information on health from theperspective of mortality. From the mortality tenet, they have captured and measure health status,by using life expectancy and diseases. Life expectancy may be an adequate indicator of length oflife and from a biomedical perspective a yardstick for health status, but such a construct is not inkeeping with the conceptual definition furnished by the World Health Organization – that “healthis a state of complete physical, mental and social wellbeing and not merely the absence ofdiseases or infirmity”. It should be noted that this conceptual definition which is in the Preambleto the constitution of the WHO which was signed in July 1946 and became functional in 1948,according to one scholar, from the Centre of Population and Development studies at HarvardUniversity, it is mouthful of sweeping generalization, that is difficult to attain, and at best it is aphantom. (Bok 2004). This paper recognizes this debate, and understands its importance butunfortunately will not be providing information hereafter thereon as it is not the purpose of thisstudy. Is there a shift taking place in demography, as the journal ‘Demography’, 1997, haspublished an article by Smith and Kington who looked at health status from biopsychologicalconditions? Is this an indicator of shift taking place as some universities do have one departmentcalled epidemiologic and population studies, population and development studies, population andpublic health studies? Now, there is a need not to subjectively qualify the health status of older people, but toprovide a demographic study of this group’s wellbeing. As demographic information is 49

paramount in the analysis of the health status of the elderly, it is highly probable that such astudy will provide the bedrock upon which invaluable information can be garnered on this group.In the past, demographers such as Shryock, Siegal and Associates (1976) did not see it fitting tostudy and provide information on health in their textbook ‘The Methods and Materials ofDemography’ primarily because they were more concerned about issues such as – mortality, lifeexpectancy, fertility, projections and estimations, population composition and distribution.Nevertheless, the issue of health, health status and wellbeing has increasingly become animportant issue to demographers so much so that in the second edition of the text “The Methodsand Material of Demography” edited by Siegal and Swanson; the authors included an entirechapter on health (Chapter 14, 341-370). Our world is always evolving, and with this comes anew set of questions that the old paradigm may be unable to address. This is one of thedynamics of science, addressing new issues that cannot be fitted within the old epistemology ofthe paradigm, which is there to explain particular phenomenon. Demographers have been foryears assessing life expectancy and diseases as indicators of health status of people (see forexample Elo 2001) - believing that it is the best measure to evaluation a people’s generalwellbeing, - but with the increases in non-communicable ailments it is obvious that longevitydoes not pronounced quality lived years (see for example Jamshidi et al. 1992, 172). In keepingwith the science of the disciplines, demographers like Siegel and Swanson and Professor EmilyGrundy have recognized the importance of the study of ageing, quality of life of the lived person,and other issues surrounding health of a population in keeping with the shift in population ageingacross the globe. The old paradigm was not able to account for distinction between the livedyears and the quality of lived years, hence, this is one of the primate reason begin the paradigmshift in health focus by demographers. Evidence in paradigm shift is so clear today that 50

Professor Emily Grundy is not only a demographer but she is a demographic gerontologist. Shehave done extensive work on ageing, quality of lived experience of the aged, demography andpublic health and ageing policy studies. Among the many challenges of contemporary societies is the reality of demographictransition. This implies that the human population is living longer but that this is within thecontext of reduced mortality and fertility along with increases in diseases from the epidemiologictransition. Accompanying the changes in the population structure is not only the shifts which arelikely to present populations but the delay demographic shift that will continue if they are notreversed. Professor Grundy is keeping with the challenges of health woes which are likely tobefall contemporary societies if policy makers do not act today as a precursor for thistomorrow’s problem. Knowing that demography studies population dynamics, in particularmortality, morbidity, fertility and migration, it would be simplistic if they do not venture in thestudy of ageing from the perspective of characteristics of the age-cohorts 65 and beyond years, aswell as the interrelation between population change and human health. Those issues had to beresolved, and so who are more competent than demographers and/or demographic gerontologiststo examine population issues – with which health and ageing falls. In attempt to understand thedeterminants of the population ageing, health must be brought within the existing model. So byintroducing health within the old model, a number of discourses have begun to emerge whichinclude (i) differential of longevity and quality lived years; (ii) public health and longevity; (iii)the feminization of population ageing, (iv) health issues– physical limitation and frailty,wellbeing, nutritional deficiencies- and health care costing of population ageing, and (v) healthtransition – the composite of epidemiologic transition and ‘response of society to health anddisease processes’. 51

These shifts are in keeping with the world population ageing. Their implications includefertility transition (decline), mortality decline, old-age dependency ratios, challenges to publichealth, along with the economic development indictors such as labour force participation rates,and lowered savings. Thus, population ageing is not simply an indicator of demographictransition but that it speaks to a whole shift in the socio-economic indicators and healthconsequences. With this said, demographers have twinned health and demography.Demography is concerned with understanding population dynamics, which include fertility,mortality, migration and life expectancy. From all indications, with demography beingconcerned about how population changes occur, health is one such consequence. In “The Methods and Material of Demography”, Lamb and Siegel commence the chapteron Health Demography with the following statement: “Health is a leading characteristic of themembers of a population, akin other demographic and socioeconomic characteristics” (Lamb andSiegel 2004, 341). They did not cease there but continue that “...increased life expectancy, …hasshifted the focus of population health from quantity of life to the quality of life, …” Embeddedin this thesis is the importance that demographers must now place on quality of life as against thequantity of life (life expectancy). Thus, the length of life expectancy cannot be used as anindicator of health as the absence of ailments is not necessarily an indicator of a ‘good’ quality oflife experienced by an individual. As shown in the JSLC (1997-2002), that the aged populacehave the highest rate of number of days spent in health care, and they share the highestproportion of illnesses and ailment with the children (less than 5 years. These are clearlyindicators that longer life is not necessarily spent as healthier days. With the measures related tofunctioning being increasingly an issue for the elderly, the wellbeing of this group must bestudied from a demographer’s vantage point. 52

Spiegelman (1980) outlines the importance of health in demography, which explains hisrationale for the inclusion of ‘Health Statistics’ in chapter 7 of the text ‘Introduction toDemography’. In this, the author furnishes definitions, and he emphasizes the significance of‘attitude toward health maintenance.’ Still little attention was given to ‘quality of health-care’outside of morbidity. One of the ironies of this text is the author’s recognition that ..Health statistics encompasses not only morbidity statistics, but also data relating to its socio-economic correlates including health attitudes and to utilization of health services (Spiegelman 1980, 171)Nevertheless, despite his acceptance of the importance of socio-economic variables includingthose two to which he refers, the text’s primary focus is on morbidity, which is keeping with auni-directional approach to the study of health. Hence, this study is timely. It will be able toprovide a new focus in the study of health demography in Jamaica as well as providing a moreholistic understanding of the state of the elderly. One scholar who works with the London School of Hygiene and Tropical Medicine,University of London, Professor Emily Grundy, have coined both medical demography andsocial gerontology in order to study ageing, ageing and wellbeing, demography and health, lifecycle influences on migration, fertility annals and health in later years, and primarily on thedemography of ageing with a public health and policy focus. Her professorial status is indemographic gerontology, which speaks to the linkage that has created between socialgerontology and medical demography. By the merging the two fields into one, Professor Grundyhas sought to highlight the need to understand population ageing, demographic transition,mortality and morbidity patterns, health outcomes, and determinants which explain the state ofpeople who happen to have had escape many of the challenges of mortality’s battles. Embedded in Professor Grundy’s works is the recognition that the negative 53

functionality’s consequences of ageing are vital; and so is ageing from demographic vantagepoints, which include a detailed analysis of longevity beyond mortality and fertility whileincorporating all the likely conditions that may influence this demographic transition. Otherfocuses of Professor Grundy’s demographic gerontology are – (i) questioning the differentialbetween longevity and quality life; (ii) understanding the implications of present populationageing and the role that it will play on future population age structure; (iii) recognizing thatpopulation ageing must be met with a coordinated effort to play for its future socio-economicchallenges such as lowered labour force participation, Medicare expenditure, and (iv) the burdenthat the working class will need to absorbed in order to afford the aged population. Despite thepaved way that has been set for Caribbean demographers, limited works exist on the aged from ademographic perspective. From a demographic gerontology view point, increasingly fewerworks exist in the Caribbean and more so Jamaica from demographers. Therefore, the time isright for a demographer to explore demographic gerontology as the discipline is amultidimensional drawn from economics, sociology, geography, epidemiology, and gerontology.Hence, this work is a move afoot in this direction of integrative demography – the use ofdemographic gerontology within the Jamaican context.Contextualizing wellbeing, from the aged perspective Ageing is a significant but neglected dimension of social stratification and the life-course is an essential component of the analysis of status (Turner 1998, 299) Ageing has emerged as a global phenomenon in the wake of the now virtually universal decline in fertility and, to a lesser extent, of increases in life expectancy (Marcoux 2001, 1) In developing countries over the last fifty years, the issue of age and senior citizens’ 54

quality of life has taken center stage in development planning on a planetary scale. The cogentreason for this growing interest is largely due to an understanding by the populace that wellbeingis not necessarily simply a function of material wealth but is most frequently used as what is‘non-instrumental’ or eventually good for a person. Embedded in this reality are thepsychosocial, environmental and economic conditions that are likely to result from the socio-demographic transition of ageing. Associated with population ageing are quality of life issuesthat go far beyond geriatric care, genetics, and determinants of life expectancy. Wellbeing of theelderly extends outside the popular use of physical functioning. What is wellbeing? Accordingto the Webster’s lexicon, wellbeing is ‘a state of being happy, healthy, or prosperous’. Goodphysical health is, therefore, a precondition for wellbeing, but happiness constitutes good life foran individual, which are based on many elements. Moreover, do not forget, from Marcoux(2001) account, ageing is a global phenomenon that is here to stay. Furthermore, we should notturn a blind eye ageing as was pointed out by Turner (1998). 55

CHAPTER 4Wellbeing DiscourseThe term wellbeing is used interchangeable with words such as ‘happiness’, ‘life satisfaction’,and ‘welfare’ by a number of researchers and/or people in intelligentsia (for example by Diener1984; Easterlin 2003; Veenhoven1993). While some scholars argue that happiness and lifesatisfaction are but a fraction of wellbeing, what is embedded in Diener and Easterlin’s usage ofthose terminologies instead of wellbeing aptly showed that, within the context ofmultidisciplinary global market place in which people must operate, the quality of life thatpeople enjoy (or not enjoy) must be understood before the goals of policy, planning and decisionon wanting to improve welfare, quality of life and/or standard of living of a people canmaterialize. Diener et al. (1999) forward a perspective that emphasized the importance of hindrance towellbeing and limitations to its expansion. They write that: The influence of genetics and personality suggests a limit on the degree to which policy can increase SWB [subjective wellbeing] . . . Changes in the environment, although important for short-term wellbeing, lose salience over time through processes of adaptation, and have small effects on long-term SWB (Diener, Suh, Lucas and Smith 1999, 227) It is clear from the writing of Diener et al that policy implementation and execution offerslittle to change the subjective wellbeing of people, and this it would appear must be equally thesame for the elderly. Contrary to this stance, economics theorists suggested that wellbeing canbe expanded by income and employment (see for example Oswald 1997, Pigou 1932), which 56

was also supported by Keister (2003). According to Keister [in an article titled Sharing theWealth: The effect of sibling on adult’s wealth ownership, forwarded that] there is “…little doubtthat material resources can improve quality of life and well...” (Keister 2003, 522). Wellbeing,therefore, can be improved with time through material resources, which is counter to theparticular perspective lauded by some psychologists (see for example Diener ey al. 1999). Happiness, according to Easterlin (2003) is associated with wellbeing, and so does ill-being (for example depression, anxiety, dissatisfaction). Easterlin (2003) argued that materialresources have the capacity to improve ones choices, comfort level, state of happiness andleisure, which militates against static wellbeing. Within the context that developing countriesand developed countries had at some point accepted the economic theory that economicwellbeing should be measured by per capita Gross Domestic Product (GDP) – (i.e. total moneyvalue of goods and services produced within an economy over a stated period per person).Amartya Sen, who is an economist, writes that plethora of literature exist that show that lifeexpectancy is positively related to Gross National Product (GNP) per capita. (Anand andRavallion 1993; Sen 1989, 8). Such a perspective implies that mortality is lower whenevereconomic boom exists within the society and that this is believed to have the potential to increasedevelopment, and by extension standard of living. Sen, however, was quick to offer a rebuttalthat data analyzed have shown that some countries (i.e. Sri Lanka, China and Costa Rica) havehad reduced mortality without a corresponding increase in economic growth (Sen 1989, 9), andthat this was attained through other non-income factors such as education, nutritionimmunization, expenditure on public health and poverty removal. The latter factors,undoubtedly, require income resources and so this is clear that income is unavoidable a criticalcomponent in welfare and wellbeing. It is believed by some scholars that economic growth 57

and/or development is a measure of welfare (see Becker, Philipson and Soares 2004). Therefore, those studies on economic wellbeing were able to offer a plethora of answersto national governments on the health status of the people, or wellbeing and/or ill-being of thecitizens. No policy formulation on improving the quality of life of citizens of a particular spaceshould precede without firstly unearthing ‘real’ determinants of wellbeing. From Crisp’sperspective (2005), wellbeing is related to health, and the strength of those associations, andsecondly planning requires information that is made available by research. Is traditionaleconomists’ operationalization of wellbeing still applicable in contemporary societies, knowingthat this is purely objective? If happiness is a state of wellbeing, then if we were to impute depression, anxiety, stress,and illness and/or physical incapacitation, spirituality and environment within the objectivemeasurement of wellbeing, a more holistic valuation would be reached. With the inclusion ofsubjectivity conditions in the measurement wellbeing, we come closer to an understanding ofpeople’s state of wellness, health and quality of life. As even better nutrition, efficient disposalof sewage and garbage, and a health lifestyle also contribute to health status (i.e. wellbeing). Itshould be noted that the biomedical model that is objective, conceptualizes health as the absenceof diseases. This leads to the question, are any of the following diseases – (i) depression, (ii)stress, (iii) fatigue, and (iv) obsession? Hence, an issue arises, does the lack of objectivity meansaccept with skepticism? Two medical doctors writing in Kaplan and Saddock’s Synopsis of Psychiatry noted thatphysicians are frequently caught in theorizing that normality is a state of health (Saddock, andSaddock 2003). They argued that doctors’ definition of normality correlates with a traditionalmodel (biomedical) that emphasizes observable signs and symptoms. Using psychoanalytic 58

theories, Saddock and Saddock remarked that the absence of symptoms as a single factor is notsufficient for a comprehensive outlook on normality. They stated, “accordingly, mostpsychoanalysts view a capacity for work and enjoyment as indicating normality…” (Saddockand Saddock 2003, 17). Among the challenges with this method (biomedical model), is itsemphasis only on curative care. Such an approach avoids the importance of life style andpreventative care. In that, health is measured based on experiences with illnesses and/or ailment,with limited recognition being placed on approaches that militates against sickness and /ordiseases. The biomedical approach is somewhat biased against an understanding of multi-dimensional man, which is not keeping with the holistic conceptualization of health as offered bythe World Health Organization (WHO). If we intend to utilize the multi-faceted definition of health as forwarded by the WHO,the absence of physical illnesses are insufficient as an approach in analyzing wellbeing. It isgenerally perceived that the biological system of the aged will degenerate (Saddock and Saddock2003; Parshad et al. 1987). One expert thoroughly penned the sentiments of innumerable personsthat “the elderly represents a vulnerable group with several medical conditions, degeneratediseases, cancer …” (Grell 1987, 7). Hence, wrongfully, we conceptualize ill-health primarilyusing physical capacities and cognitive abilities. In the 1950s, George Engel, a physician, teamed with John Romano, a young psychiatrist,to develop a biopsychosocial model, into the curriculum of University of Cincinnati College ofMedicine, which measured the health status of people. It is referred to as Engel’sbiopyschosocial model. Engel’s biopsychosocial model (in Brown 2000), recognizes thatpsychologic and social factors coexisted along with biologic factors. It was a general theory ofillness and healing, a synergy between medicine, psychiatry and the behavioural sciences (in 59

Dowling 2005). Therefore, from Engel model, wellbeing must include factors such as –motivation, depression (or the lack thereof), biologic conditions (such as illnesses and diseases),social systems, cultural, environmental and familial influences on the appearance andoccurrences of illness. Nevertheless, according to demographers (Crimmins, Hayward and Saito 1994; Portraitet al 2001), the terminology, because of its multidimensional tenets, is conceptualized usingindicators of “functioning ability”. These pundits categorized “functioning ability” as – (i) beingable to provide both personal care and independent living but having some difficulty inperforming these tasks or in getting about outside the home, (ii) having no functioningdifficulties, (iii) being unable to independently provide personal care, and finally (iv) being ableto provide personal care but not able to manage life in the home independently” (Crimmins,Hayward and Saito 1994, 162). The concept of health according to the WHO is multifaceted. “Health is state of completephysical, mental and social well, and not merely being the absence of disease or infirmity”(Whang 2005, 153). From the WHO’s perspective, health status is an indicator of wellbeing(See also, Crisp 2005). Wellbeing for some, therefore, is a state of happiness – positive feelingstatus and life satisfaction (see for example, Easterlin 2003; Diener, Larson, Levine, andEmmons 1985; Diener 1984) satisfaction of preferences or desires, health or prosperity of anindividual (Diener and Suh 1997; Jones 2001; Crips 2005; Whang 2005), or what psychologistsrefer to as positive effects (Headey and Wooden 2004). Simply put, wellbeing is subjectivelywhat is ‘good’ for each person (See for example, Crisp 2005). It is sometimes connected withgood health. Crisp offered an explanation for this, when he said that “When discussing thenotion of what makes life good for the individual living that life, it is preferable to use the term 60

‘wellbeing’ instead of ‘happiness” (Crisp 2005), which explains the rationale for this projectutilizing the term wellbeing and not good health. In order to forward an understanding of what constitutes wellbeing or ill being, a systemmust be instituted that will allow us to coalesce a measure that will unearth peoples’ sense ofoverall quality of life from either economic-welfarism (see Becker et al. 2004) or psychologicaltheories (Diener, Suh, and Oishi, 1997; Headey and Wooden 2004; Kashdan 2004; Diener 2000).This must be done with the general construct of a complex man. Economists like Smith andKington, and Stutzer and Frey as well as Engel believe that state of man’s wellbeing is not onlyinfluenced by his/her biologic state but that is always dependent on his/her environment,economic and sociologic conditions. Some studies and academics have sought to analyze thisphenomenon within a subjective manner by way of general personal happiness, self-ratedwellbeing, positive moods and emotions, agony, hopelessness, depression, and otherpsychosocial indicators (Arthaud-day et al. 2005; Diener et al. 1999; Skevington et al.1997;Diener 1984). An economist (Easterlin) studying happiness and income, of all social scientist, found anassociation between the two phenomena (Easterlin 2001a, 2001b), (see also Stutzer and Frey2003). He began with a statement that “the relationship between happiness and income ispuzzling” (Easterlin 2001a, 465), and found people with higher incomes were happier than thosewith lower incomes – he referred to as a correlation between subjective wellbeing and income(see also, Stutzer and Frey 2003, 8). He did not cease at this juncture, but sought to justify thisrealty, when he said that “those with higher income will be better able to fulfill their aspirationand, and other things being equal, on an average, feel better off” (Easterlin 2001a, 472). 61

Wellbeing, therefore, can be explained outside of welfare theory and/or purely on objectification-objective utility (See for example, Kimball and Willis 2005; Stutzer and Frey 2003). Whereas Easterlin found a bivariate relationship between subjective wellbeing andincome, Stutzer and Frey revealed that the association is a non-linear one. They concretized theposition by offering an explanation that “In the data set for Germany, for example, the simplecorrelation is 0.11 based on 12, 979 observations” (Stutzer and Frey 2003, 9). Nevertheless, fromStutzer and Frey’s findings, a position association does exist between subjective wellbeing andincome despite difference over linearity or non-linearity. The issue of wellbeing is embodied in three theories – (1) Hedonism, (2) Desire, and (3)Objective List. Using ‘evaluative hedonism’, wellbeing constitutes the greatest balance ofpleasure over pain (See for example, Crisp 2005; Whang 2005, 154). With this theorizing,wellbeing is just personal pleasantness, which represents that more pleasantries an individualreceives, he/she will be better off. The very construct of this methodology is the primary reasonfor a criticism of its approach (i.e. ‘experience machine’), which gave rise to other theories.Crisp (2005) using the work of Thomas Carlyle described the hedonistic structure ofutilitarianism as the ‘philosophy of swine’, because this concept assumes that all pleasure is onpar. He summarized this adequately by saying that “… whether they [are] the lowest animalpleasures of sex or the highest of aesthetic appreciation” (Crisp 2005). The desire approach, on the other hand, is on a continuum of experienced desires. Thisis popularized by welfare economics. As economists see wellbeing as constituting satisfaction ofpreference or desires (Crisp 2005, 7; Whang 2005, 154), which makes for the ranking ofpreferences and its assessment by way of money. People are made better off, if their current 62

desires are fulfilled. Despite this theory’s strengths, it has a fundamental shortcoming, the issueof addiction. This forwarded by the possible addictive nature of consuming ‘hard drugs’ becauseof the summative pleasure it gives to the recipient. Objective list theory: This approach in measuring wellbeing list items not merelybecause of pleasurable experiences nor on ‘desire-satisfaction’ but that every good thing shouldbe included such as knowledge and-or friendship. It is a concept influenced by Aristotle, and“developed by Thomas Hurka (1993) as perfectionism” (Crisp 2005). According to thisapproach, the constituent of wellbeing is an environment of perfecting human nature. What goeson an ‘objective list’ is based on reflective judgement or intuition of a person. A criticism of thistechnique is elitism (Crisp 2005). Since an assumption of this approach is that, certain thingsare good for people. Crisp (2005) provided an excellent rationale for this limitation, when hesaid that “…even if those people will not enjoy them, and do not even want them”. In Arthaud-day et al work, applying structural modeling, subjective well was found toconstitute “(1) cognitive evaluations of ones life (i.e., life satisfaction or happiness); (2) positiveaffect; and (3) negative affect.” Subjective wellbeing, therefore, is the individual’s ownviewpoint. If an individual feels his/her life is going well, then we need to accept this as theperson’s reality. One of drawbacks to this measurement is, it is not summative, and it lacksgeneralizability. Studies have shown that subjective wellbeing can be measured on a community level(Bobbit et al.2005; Lau 2005; Boelhouwer and Stoop 1999) or on a household level (Lau 2005;Diener 1984), whereas other experts have sought to use empiricism (biomedical indicators -absence of disease symptoms, life expectancy; and an economic component - Gross Domestic 63

Product per capita; welfarism - utility function). Powell (1997) in a paper titled ‘Measures of quality of life and subjective wellbeing’argued that psychological wellbeing is a component of quality of life. He believed that in thismeasurement in particular for the older, must include Life Satisfaction Index, as this approachconstitutes a number of items based on “cognitively based attitudes toward life in general andmore emotion-based judgment”(Powell 1997). Powell addressed this from two-dimensions.Where those means are relatively constant over time while in seeking to unearth changes in theshort-run, ‘for example an intervention’, procedures that mirror changed states may bepreferable. This can be assessed by way of a twenty-item Positive and Negative Affect Scheduleor from a ten-item Philadelphia Geriatric Centre Positive Affect and Negative Affect Scale(Powell 1997). In a reading titled ‘Objective measures of wellbeing and the cooperation productionproblem’, Gaspart (1998) provided arguments that support the rational behind the objectificationof wellbeing. His premise for objective quality of life is embedded within the difficulty as itrelates to consistency of measurement when subjectivity is the construct of operationalization.This approach takes precedence because an objective measurement of concept is of exactness asnon-objectification; therefore, the former receives priority over any subjective preferences. Heclaimed that for wellbeing to be comparable across individuals, population and communities,there is a need for empiricism. Gaspart discussed a number of economic theorizing (Equal Income Walrasian equilibria,objective egalitarianism, Pareto efficiency; Wefarism), which saw the paper expounding on anumber of mathematical theorems in order to quantify quality of life. Such a stance proposes 64

that human predictable, rational from which we are able to objectify their plans. The veryaxioms cited by Gaspart emphasized particular set of assumptions that he used finalizing ameasurement for wellbeing for man who is a complex social animal. The researcher points to asentence that was written by Gaspart that speaks to the difficulty of objective quality of life; hewrote, “So its objectivism is already contaminated by post-welfarism, opening the door to amixed approach, in which preferences matter as well as objective wellbeing” (Gaspart 1998).Another group of scholars emphasized the importance of measuring wellbeing outside awelfarism and/or purely objectification, when they said that “Although GDP per capita is usuallyused as a proxy for the quality of life in different countries, material gain is obviously only oneof many aspects of life that enhance economic wellbeing” (Becker et al. 2004, 1), and thatwellbeing depends on both the quality and the quantity of life lived by the individual (see alsoEasterlin 2001). This is affirmed in a study carried out by Lima and Nova (2006), that foundhappiness, general life satisfaction, social acceptance and actualizations are all directed related toGDP per capita for a geographic location (see Lima and Nova 2006, 9). Even though in Europethese were found not to be causal, income provides some predictability of subjective wellbeingmore so in poor countries than in wealthy nations. (see Lima and Nova 2006, 11) It should be understood that GDP per capita speaks of the market economic resourceswhich are produced domestically within a particular geographic space. So increased productionin goods and/or services may generate excess which can then be exported, and vital products(such as vaccination, sanitary products, vitamins, iron and other commodities) can be purchasedthat is able to improve the standard of living and quality of the life of the same people over theprevious period. One scholar (Caldwell 1999) has shown that life expectancies are usually higherin countries with high GDP per capita, which means that income is able to purchased better 65

quality products, which indirectly affects the length of years lived by people. This realty couldexplain why in economic recession, war and violence, when the economic growth is lower (oreven non-existence) there is a lower life expectancy. Some of the reasons for these justificationsare government’s unavailability to provide for an extensive population in the form of nutritionalcare, public health and health-care services. Good health is, therefore, linked to economicgrowth, which further justifies why economists use GDP per capita as an objective valuation ofstandard of living; and why income should indefinitely be a component in the analysis of healthstatus. There is another twist to this discourse as a country’s GDP per capita may be low, but thelife expectancy is high because health care is free for the population. Despite this fact, materialliving standards undoubtedly affect the health status and wellbeing of a people, as well as thelevel of females’ educational attainment. Ringen (1995) in a paper titled ‘Wellbeing, measurement, and Preferences’ argued thatnon-welfarist approaches to measuring wellbeing are possible despite its subjectivity. The directapproach for wellbeing computation through the utility function according to Ringen is not abetter quantification as against the indirect method (i.e. using social indicators). The stancetaken was purely from the vantage point that utility is a function ‘not of goods and preferences’but of products and ‘taste’. The constitution of wellbeing is based on choices. Choices are afunction of individual assets and options. With this premise, Ringen forwarded arguments whichshow that people’s choices are sometimes ‘irrational’, which is the make for the departure fromempiricism. Wellbeing can be computed from either the direct (i.e. consumption expenditure) or theindirect (i.e. disposable income) approach (Ringen 1995, 8). The former is calculated usingconsumption expenditure, whereas the latter uses disposable income. Rigen noted that in order 66

to use income as a proxy for wellbeing, we must assume that (1) income is the only resource, and(2) all persons operate in identical market places. On the other hand, the direct approach has twokey assumptions. These are (1) what we can buy is what we can consume and (2) and that whatwe can consume, is an expression of wellbeing. From Rigen’s monograph, the assumptions arelimitations. In presenting potent arguments in favour of non-empiricism in the computation ofwellbeing, Ringen highlighted a number of drawbacks to welfarism. According to Ringen: Utility is not a particular good criterion for wellbeing since it is a function not only of circumstances and preferences, but also of expectation. In the measurement of wellbeing, respect for personal preferences is best sought in non-welfarist approaches that have the quality of preference neutrality; …As soon, as preferences are brought into the concept of wellbeing cannot but be subjective. (Ringen 1995, 11) The difficulties in using empiricism to quantify wellbeing has not only beForwarded by Ringen as O’Donnell and Tait (2003) were equally forthwith inarguing there were challenges in measuring quality of life quantitatively. O’Donnell and Taitbelieved that health is a primary indicator of wellbeing. Hence, self-rated health status is a highlyreliable proxy of health which “successfully crosses cultural lines” (O’Donnell and Tait 2003,20). They argued self-reported health status can be used as they found that all the respondents ofchronic diseases indicated that their health was very poor. To capture the state of the quality of life of humans, we are continuously and increasinglyseeking to ascertain more advance methods that will allow us to encapsulate a quantification ofwellbeing that is multidimensional and multifaceted (Pacione, 2003). Therefore, an operational 67

definition of wellbeing that sees the phenomenon on single dimension such as physical health(Steward and King 1994), medical perspective (Farquhar 1995), material (Lipsey 1999) andwould have excluded indicators such as crime, education, leisure facilities, housing, socialexclusion and the environment (Pacione 2003; Campbell et al 1976) as well as subjectiveindicators cannot be an acceptable holistic measurement of this construct. This suggests thatwellbeing is simply not a single space; and so, the traditional biomedical conceptual definitionsof wellbeing exclude many individual satisfactions and in the process reduce the tenets of asuperior coverage of quality of life. One writer noted that the environment positively influenced the quality of life (Pacione2003, 20) of peoples; in order to establish validity and reliability of wellbeing, empirical datamust include issues relating to the environment. The quality of the environment is a utilizedcondition in explaining elements of quality of life of people. Air and water quality throughindustrial fumes, toxic waste, gases and other pollutants affect environmental quality. Thisdirectly related to maintenance or lack thereof of societal and personal wellbeing (Pacione 2003). Studies have conclusively shown that environmental issues such as industrial fumes andgases, poor solid waste management, mosquito infestation and poor housing are likely to result inphysiological conditions like respiratory track infections (for example lung infection), asthma. According to Langlois and Anderson (2002), approximately 30 years ago, a seminalstudies conducted by Smith (1973, 2) “proposed that wellbeing be used to refer to conditions thatapply to a population generally, while quality of life should be limited to individuals’ subjectiveassessments of their lives …” They argue that a distinction between the two variables have beenlost with time. From Langlois and Anderson’s monograph, during the 1960s and 1970s, 68

wellbeing was approached from a quantitative assessment by the use of GDP or GNP (also See,Becker, Philipson and Soares 2004), and unemployment rates; this they refer to as a “rigidapproach to the [enquiry of the subject matter] subject”. According to Langlois and Anderson(2002), the positivism approach to the methodology of wellbeing was objectification, anassessment that was highly favoured by Andrews and Withley, 1976 and Campbell et al 1976. In measuring quality of life, some writers have thought it fitting to use Gross DomesticProduct per capita (i.e. GDP per capita) to which they referred to as standard of living (Lipsey1999; Summers and Heston 1995; Hanson 1986). According to Summers and Heston (1995),“The index most commonly used until now to compare countries material wellbeing is theirGDP POP .” The United Nations Development Programme has expanded on the materialwellbeing definition forwarded primarily by economists, and has included life expectancy andeducational attainment (Human Development Reports, 2005, p. 341) and other social indicators(Diener 1984; Diener and Suh 1997). This operational definition of wellbeing has becomeincreasingly popular in the last twenty-five years, but given the expanded definition of health ascited by the WHO, wellbeing must be measured in a more comprehensive manner than usingmaterial wellbeing as seen by economists. Despite the fact that quality of life extends beyond the number of years of schooling andmaterial wellbeing, generally wellbeing is substantially construed as economic phenomenon.Embedded within this construct of a measure is the emphasis on economic resources, and wehave already establish that man’s wellbeing is multifaceted. Hence, any definition of the qualityof life of people cannot just simply analyze spending or the creation of goods and/or services thatare economically exchangeable, number of years of schooling and life expectancy but this mustinclude the psychosocial conditions of the people within their natural environment. 69

GDP is the coalesced sum of all economic resources of people in certain topography, sothis does not capture the psychosocial state of the man in attaining the valued GDP. By thisapproach, we may arrive at a value that is higher than in previous periods, making it seem asthough people are doing very well. However, with this increase in GDP, this single component isinsufficient to determine wellbeing. As the increase in GDP may be by (1) more working hours,(2) higher rates of pollutions and environmental conditions, (3) psychological fatigue, (4) socialexclusion, (5) human ‘burn out’, (6) reduction in freedom, (7) unhappiness, (8) chronic and acutediseases and so forth. Summers and Heston (1995) note that “However, GDP POP is aninadequate measure of countries immediate material wellbeing, even apart from the generalpractical and conceptual problems of measuring countries national outputs.” Generally, fromthat perspective, the measurement of quality of life is, therefore, highly economic and excludesthe psychosocial factors, and if quality of life extends beyond monetary objectification. In developing countries, Camfield (2003) in looking at wellbeing from a subjectivevantage point notes that Diener (1984) argues that subjective wellbeing constitute the existenceof positive emotions and the absence of negative ones within a space of general satisfaction withlife. According to Camfield, Cummins’ (1997) perspective subsumed ‘subjective and objectivemeasures of material wellbeing’ along with the absence of illnesses, efficiency, social closeness,security, place in community, and emotional wellbeing, which implies that “life’s satisfaction”comprehensively envelopes subjective wellbeing. Diener (2000) in an article titled ‘Subjective Wellbeing: The Science of Happiness and aProposal for a National Index’ theorizes that the objectification of wellbeing is embodied withinsatisfaction of life. His points to a construct of wellbeing called happiness. 70

He cited that: Peoples moods and emotions reflect on-line reactions to events happening to them. Each individual also makes broader judgments about his or her life as a whole, as well as about domains such as marriage and work. Thus, there are a number of separable components of SWB [subjective wellbeing]: life satisfaction (global judgments of ones life), satisfaction with important domains (e.g., work satisfaction), positive affect (experiencing many pleasant emotions and moods), and low levels of negative affect (experiencing few unpleasant emotions and moods). In the early research on SWB, researchers studying the facets of happiness usually relied on only a single self-report item to measure each construct (Diener, 2000, 34). Diener’s theorizing on wellbeing encapsulates more than the marginalized stance of otheracademics and researchers who enlightened the discourse with economic, psychosocial, orsubjective indicators. He shows that quality of life is multifaceted and coalescing economic,social, psychological and subjective indicators is far more reaching in ultimately measuringwellbeing. This work shows a construct that can be used to operationalize a moremultidimensional variable, wellbeing, which widens the tenet of previous operational definitionon the subject. From the theorizing of various writers, it is clear that wellbeing ismultidimensional, multidisciplinary and multispatial. Some writers emphasize the environmentalcomponents of subject matter (Lui 1976; Pacione 1984; Smith 1973), psychosocial aspect(Clarke and Ryff 2000) and from a social capital vantage point (Glaeser 2001; Putnam 1995;Woolcock 2001). According to Smith and Kington (1997), using H t = f (H t-1 , P m G o , Bt , MC t ED, Ā t , ) toconceptualize a theoretical framework for “stock of health” noted that health in period t, Ht, isthe result of health preceding this period (H t-1) , medical care (MC t) , good personal health (G o) ,the price of medical care (P m ), and bad ones (Bt) , and a vector of family education (ED), and all 71

sources of household income (Ā t ). Embedded in this function is the wellbeing that individualenjoys (or not enjoys) (see Smith and Kington 1997, 159-160). In seeking to operationalize wellbeing, the United Nations Development Programme(UNDP) in the Human Development Reports (1997, 2000) conceptualized human developmentas a “process of widening people’s choice as well as the level of achieve wellbeing”. Embeddedwithin this definition is the emphasis of materialism in interpreting quality of life. From theUNDP’s Human Development (1993), the human development index (HDI) “…is a normativemeasure of a desirable standard of living or a measure of the level of living”, which speaks to thesubjectivity of this valuation irrespective of the inclusion of welfarism (i.e. gross domesticproduct (GDP) per capita). The HDI constitute adjusted educational achievement (E= a 1 *literacy + a 2 * years of schooling, where a1, = 2/3 and a2 = 1/3), life expectancy (demographic 1-emodeling) and income (W (9y) = 1/ (1 - e) * y ). The function W(y) denotes “utility orwellbeing derived from income”. This income component of the HDI is a national average (i.e.GDP per capita, which is them adjusted for income distribution (W*(y) = W(y) {1 - G}), whereG = Gini coefficient). In wanting to disaggregate the HDI within a country, the UNDP (1993)noted that data are not available for many countries, which limits the possibility. An economist writing on ‘objective wellbeing’ summarized the matter simply by statingthat “…one can adopt a mixed approach, in which the satisfaction of subjective preferences istaken as valuable too” (Gaspart 1998, 111) (see also Cummin1997a, 2001), which is the premiseupon which this paper will adhere in keeping with this multidimensional construct, wellbeing.Wellbeing, therefore, for this paper will be the overall health status of people, which includeaccess to and control over material resources, environmental and psychosocial conditions, andper capita consumption. 72

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CHAPTER 5Variations in social determinants of health using an adolescencepopulation: By different measurements, dichotomization and non-dichotomization of healthOn examining health literature, no study emerged that evaluated whether the social determinantsvary across measurement, dichotomization, non-dichotomization and aged cohorts. With theabsence of research on the aforementioned areas, it can be extrapolated that social determinantsof health are constant across measurement, dichotomization and non-dichotomization, and thisassumption is embedded in health planning. This paper seeks to elucidate (1) whether socialdeterminants of health vary across measurement of health status (ie self-rated health status orself-reported antithesis of disease) or the cut-off (dichotomization) and/or the non-cut-off ofhealth status (non-dichotomization), (2) examine the similarities between social determinantsfound in the literature and that of using an adolescence population, (3) whether particulardemographic characteristic as well as illness and health status vary by area of residence ofrespondents, (4) the health status of the adolescence population, (5) typology of healthconditions that they experience, and (6) evaluate the antithesis of illness (disease) and self-ratedhealth. The current study extracted a sample of 1, 394 respondents aged 10 to 19 years old fromthe 2007 Jamaica Survey of Living Conditions (JSLC). The present subsample represents 20.6%of the 2007 national cross-sectional sample (n = 6,783). Multivariate logistic and ordinallogistic regression analyses were used to examine the association between many independentvariables and a single dependent variable. In this study, health was measured using (1) self-rated health status or (2) the antithesis of illness (not reporting a health condition). Thedichotomization of each denotes the use of two groups, and non-dichotomization means that self-rated health status was used in its Likert scale form (i.e. very good; good; moderate; poor andvery poor). Antithesis of illness is a better measure than self-reported health status indetermining social determinants because of its explanatory power (53%) compared to those thatused the self-rated health status (at most 38%). There were noticeable variations in socialdeterminants of health among the dichotomized, non-dichotomized health and antithesis ofillness. Social determinants of health vary across the measurement and dichotomization andnon-dichotomization of health status. The findings provide insights into the social determinantsand health, and recommend that we guard against a choiced approach without examining thestudied population in question.IntroductionAdolescents aged 10 to 19 years are among the most studied groups in regard health issues in theCaribbean, particularly sexuality and reproductive health matters [1-4]. Apart of the rationales 107

for the high frequency of studies on those in the adolescence years are owing to the prevalence ofHIV/AIDS, unwanted pregnancy, inconsistent condom usage, mortality arising from theHIV/AIDS virus, and other risky sexual behaviour. With one half of those who are infected withthe HIV/AIDS virus being under 25 years old [1], this provides a justification for the importanceof researching this aged cohort. Statistics revealed that the HIV virus is the 3rd leading cause ofmortality among Jamaicans aged 10-19 years old (3.4 per 100,000, for 1999 to 2002) [5], andagain this provides a validation for the prevalence of studies on this cohort. Outside of theCaribbean, sexuality and reproductive health matters among adolescents are well studied [6-11],suggesting that those issues are national, regional and international. While sexuality and reproductive health matters are critical to the health status of people[1], reproductive health problems as well as sexuality form a part of the general health status.Health is more that the ‘antithesis of diseases’ [12] or reproductive health problems as it extendsto social, psychological or physical wellbeing and not merely the antithesis of diseases [13].Bourne opined that despite the broadened definition of health as offered by the WHO [14],illness is still widely studied in the Caribbean, particularly among medical researchers and/orscholars. A search of the West Indian Medical Journal for the last one half decade (2005-2010), aCaribbean scholarly journal, revealed that the majority of the studies have been on differentvariations of illness, and antithesis of diseases instead of the broadened construct of health. Outside of the West Indian Medical Journal, few Caribbean studies have sought toexamine the health status of adolescents [15-18] but even fewer published research were foundthat examine quality of life of those in the adolescence years [19]. Even though quality of life isa good measure of general health status, international studies exploring quality of life and self-rated health status among the adolescence years are many [20-25] compared to those in Jamaica. 108

A comprehensive review of the literature on health status, particularly among the adolescencepopulation, revealed that none has used a national survey data to examine social determinants ofhealth across different measurement and dichotomization of health (the recoding of the measureinto two groups) to assess whether there is variability in determinants as well as explore thehealth of this cohort. Even among studies which have examined social determinants of health, particularlyamong the population [26-34], few have used the elderly population [35-37] and only men in thepoor and the wealthy social strata [37, 38], but none emerged in a literature research that haveused the adolescent population (ages 10-19 years). On examining health literature, no studyemerged that evaluated whether the social determinants of health vary across measurement,dichotomization and non-dichotomization of health (using the measure in its Likert scale form),and age cohort. With the absence of research on the aforementioned areas, it can be extrapolatedthat social determinants of health are constant across measurement, dichotomization and non-dichotomization, and this assumption is embedded in health planning. The absence of suchinformation means that critical validity to the discourse and use of social determinants wouldhave been lost, as social determinants of health are used in the planning of health policies, futureresearch and in explaining health disparities. Statistics revealed that one in every five Jamaican is aged 10-19 years old [39], whichmeans this is a substantial population and because of its influence of future labour supply it is ofgreat value. Although Pan American Health Organization (PAHO) [5] stated that adolescentsenjoy good health, and only about 2% of morality in 2003, which was equally the case foradolescents in the Americas, this information does not indicate distancing examination from theirhealth status. The current work, therefore, will bridge the gap in the literature by evaluating 109

social determinants of health among those in the adolescence years across varying measurementof health. Using data for 2007 Jamaica Survey of Living Conditions (2007 JSLC), this paperseeks to elucidate (1) whether social determinants of health vary across measurement of healthstatus (ie self-rated health status or self-reported antithesis of disease) or the cut-off(dichotomization) and/or the non-cut-off of health status (non-dichotomization), (2) are theresimilarities between social determinants found in the literature and that of using an adolescencepopulation, (3) whether particular demographic characteristic as well as illness and health statusvary by area of residence of respondents, (4) what is the health status of the adolescencepopulation, (5) typology of health conditions that they experience, and (6) evaluate the antithesisof illness (disease) and self-rated health.Methods and measureDataThe current study extracted a sample of 1, 394 respondents aged 10 to 19 years old from the2007 Jamaica Survey of Living Conditions (JSLC). The inclusion/exclusion criterion for thisstudy is aged 10 to 19 years old. The present subsample represents 20.6% of the 2007 nationalcross-sectional sample (n = 6,783). The JSLC is an annual and nationally representative cross-sectional survey that collects information on consumption, education, health status, healthconditions, health care utilization, health insurance coverage, non-food consumptionexpenditure, housing conditions, inventory of durable goods, social assistance, demographiccharacteristics and other issues [40]. The information is from the civilian and non-institutionalized population of Jamaica. It is a modification of the World Bank’s LivingStandards Measurement Study (LSMS) household survey [41]. An administered questionnairewas used to collect the data. 110

The survey was drawn using stratified random sampling. This design was a two-stagestratified random sampling design where there was a Primary Sampling Unit (PSU) and aselection of dwellings from the primary units. The PSU is an Enumeration District (ED), whichconstitutes a minimum of 100 residences in rural areas and 150 in urban areas. An ED is anindependent geographic unit that shares a common boundary. The country was grouped intostrata of equal size based on dwellings (EDs). Based on the PSUs, a listing of all the dwellingswas made, and this became the sampling frame from which a Master Sample of dwellings wascompiled, which in turn provided the sampling frame for the labour force. One third of theLabour Force Survey (LFS) was selected for the JSLC. Overall, the response rate for the 2007 JSLC was 73.8%. Over 1994 households ofindividuals nationwide are included in the entire database of all ages [40]. A total of 620households were interviewed from urban areas, 439 from other towns and 935 from rural areas.This sample represents 6,783 non-institutionalized civilians living in Jamaica at the time of thesurvey. The JSLC used complex sampling design, and it is also weighted to reflect thepopulation of Jamaica. This study utilized the data set of the 2007 JSLC to conduct our work[42].MeasureAge is a continuous variable which is the number of years alive since birth (using last birthday)Adolescence population is described as the population aged 10 to 19 years old [23]Self-reported illness (or self-reported dysfunction): The question was asked: “Is this a diagnosedrecurring illness?” The answering options are: Yes, Cold; Yes, Diarrhoea; Yes, Asthma; Yes,Diabetes; Yes, Hypertension; Yes, Arthritis; Yes, Other; and No. For the antithesis of disease 111

(illness) a binary variable was created, where 1= not reported a health condition (no to eachillness) and 0 = otherwise (absence of reporting an illness). The use of two groups for self-reported illness denotes that this variable was dichotomized into good health (from not reported ahealth condition) and poor health (i.e. having reported an illness or health condition). Thus, theseven health conditions were treated as dichotomous variables, coded as was previous stated.Self-rated health status: This was taken from the question “How is your health in general?” Theoptions were very good; good; fair; poor and very poor. For purpose of this study, the variablewas either dichotomized or non-dichotomized. The dichotomization of self-rated health statusdenotes the use of two groups. There were four dichotomization of self-rated health status – (1)very poor-to-poor health status and otherwise; (2) good and otherwise; (3) good-to-very goodhealth status and otherwise and (4) moderate-to-very good self reported health status andotherwise. The dichotomized variables were measured as follow: 1= very poor-to-poor health, 0 = otherwise 1= good, 0 = otherwise 1 =good-to-very good, 0 = otherwise 1= moderate-to-very good, 0 = otherwiseThe non-dichotomization of self-rated health status means that the measure remained in its Likertscale form (i.e. very good; good; moderate; poor and very poor health status).Social class (hierarchy): This variable was measured based on income quintile: The upper classeswere those in the wealthy quintiles (quintiles 4 and 5); middle class was quintile 3 and poor thosein lower quintiles (quintiles 1 and 2). 112

Family income is measure using total expenditure of the household as reported by the head.Statistical analysisStatistical analyses were performed using the Statistical Packages for the Social Sciences v 16.0(SPSS Inc; Chicago, IL, USA) for Windows. Descriptive statistics such as mean, standarddeviation (SD), frequency and percentage were used to analyze the socio-demographiccharacteristics of the sample. Chi-square was used to examine the association between non-metric variables, and analysis of variance for metric and non-dichotomous nominal variables.Logistic regression was used to evaluate a dichotomous dependent variable (self-rated healthstatus and antithesis of illness) and some metric and/or non-metric independent variables.However, ordinal logistic regression was used to examine a Likert scale variable (self-ratedhealth status) and some metric and/or non-metric independent variables. A pvalue of < 5% (two-tailed) was used to establish statistical significance. Each model begins with variables identifiedin the literature (Models 1-5), will be tested using the current data and the significant variableshighlighted using an asterisk (Tables 3 and 4).ModelsThe use of multivariate analysis to study health status and subjective wellbeing (i.e. self-reportedhealth) is well established in the literature [36-38]. Previous works have examined thedichotomization of health status in order to establish whether a particular measurement of healthstatus is different from others [43-45]. The current study will employ multivariate analyses toexamine health by different dichotomization and statistical tools to determine if the social 113

determinants remain the same. The use of this approach is better than bivariate analyses as manyvariables can be tested simultaneously for their impact (if any) on a dependent variable. Scholars like Grossman [33], Smith & Kingston [34], Hambleton et al. [37], Bourne[46], Kashdan [47], Yi & Vaupel [48], and the World Health Organization pilot work a 100-question quality of life survey (WHOQOL) [49] have used subjective measures to evaluatehealth. Diener [50,51] has used and argued that self-reported health status can be effectivelyapplied to evaluate health status instead of objective health status measurement, and Bourne [46]found that self-reported health may be used instead of objective health. Embedded in the worksof those researchers is the similarity of self-reported health status and self-reported dysfunctionin assessing health. Thus, in this work we will use self-reported health status and the antithesis ofillness to measure health, and dichotomize self-reported health status as follows (1) good health= 1, 0 = otherwise; (2) good-to-excellent health=1, 0 = otherwise; (3) moderate-to-excellenthealth=1, 0 = otherwise; and (4) very poor-to-poor health= 1, 0 = otherwise. Another measurewas that health was evaluated by all the 5-item scale (from very poor to excellent health status),using ordinal logistic regression. The current study will examine the social determinants of self-rated health of Jamaicanadolescents and whether the social determinants vary by measurement and dichotomizationand/or non-dichotomization of health. Five hypotheses (models) were tested in order todetermine any variability in social determinants based on the measurement of health status.Model (1) is the antithesis of disease, non-dichotomization of self-reported health (antithesis ofdisease); Model (2) is the non-dichotomization of self-rated health status (ie using the 5-itemLikert scale as a continuous variable), and Models (3-6) are the different dichotomized self-ratedhealth status (ie. 3= very poor-to-poor; 4=good, 5=moderate-to-very good 6=good-to-very good). 114

All the models were tested with the same set of social determinants of health, with the onlyvariability being the measurement of health status (self-rated health status), cut-off of health(dichotomization) and/or non-dichotomization of self-rated health status.H A=f (A i , G i , AR i , It , lnD i , ED i, US i , S i , HIi , lnY, CR i , lnMC t , SA i , ε i ) (1) where H A (i.e. self-rated antithesis of diseases) is a function of age of respondents, A i ; sex of individual i, G i ; area of residence, AR i ; current self-reported illness of individual i, It ; logged duration of time that individual i was unable to carry out normal activities (or length of illness), lnD i ; Education level of individual i, ED i ; union status of person i, US i ; social class of person i, S i ; health insurance coverage of person i, HIi ; logged family income, lnY; crowding of individual i, CRi; logged medical expenditure of individual i in time period t, lnMC t ; social assistance of individual i, SA i ; and an error term (ie. residual error). Note that length of illness was removed from the model as it had 93.5% of the cases were missing as well as union status which had 58.2%.H ND=f (A i , G i , AR i , It , lnD i , ED i, US i , S i , HIi , lnY, CR i , lnMC t , SA i , ε i ) (2) Where H ND denotes the non-dichotomization of self-rated health status. Note that length of illness was removed from the model as it had 93.5% of the cases were missing as well as union status which had 58.2%.H D1 =f (A i , G i , AR i , It , lnD i , ED i, US i , S i , HIi , lnY, CR i , lnMC t , SA i , ε i ) (3) Where H D1 is very poor-to-poor self-rated dichotomized health status. 115

Note that length of illness was removed from the model as it had 93.5% of the cases were missing as well as union status which had 58.2%.H D2 =f (A i , G i , AR i , It , lnD i , ED i, US i , S i , HIi , lnY, CR i , lnMC t , SA i , ε i ) (4) Where H D2 is good self-rated dichotomized health status. Note that length of illness was removed from the model as it had 93.5% of the cases were missing as well as union status which had 58.2%.H D1-4 =f (A i , G i , AR i , It , lnD i , ED i, US i , S i , HIi , lnY, CR i , lnMC t , SA i , ε i ) (5) Where H D3 is very moderate-to-very good self-rated dichotomized health status. Note that length of illness was removed from the model as it had 93.5% of the cases were missing as well as union status which had 58.2%.H D1-4 =f (A i , G i , AR i , It , lnD i , ED i, US i , S i , HIi , lnY, CR i , lnMC t , SA i , ε i ) (6) Where H D4 is good-to-excellent self-rated dichotomized health status. Note that length of illness was removed from the model as it had 93.5% of the cases were missing as well as union status which had 58.2%.ResultsDemographic characteristics of studied population Table 5.1 presents information on demographic characteristic of the sampled population.Of the population (n = 1,394), 43.9% has primary or below primary level education, 53.1%secondary level and 3.0% had tertiary level education. 116

Table 5.2 presents information on the particular demographic characteristic as well ashealth status and self-reported illness of respondents by area of residence. Table 5.3 depicts information of variables which explain the antithesis of illness amongthe adolescence population. Table 5.4 shows the different dichotomizations of self-rated health status and non-dichotomized self-rated health status, and the various social determinants which explain each. Table 5.5 examines associations between self-rated health status and antithesis of illness(or disease).Limitations of studyThis study was extracted from a cross-sectional survey dataset (Jamaica Survey of LivingConditions, 2007). Using a nationally representative cross-sectional survey dataset, this researchextracted 1394 adolescent Jamaicans which denote that the work can be used to generalize aboutthe adolescent population in Jamaica at the time in question (2007). However, it cannot be usedto make predictions, forecast, and establish trends or causality about the studied population.Discussion The current work showed that while the majority of Jamaican adolescents have at leastself-rated good health status (92 out of every 100); some indicated at most moderate self-ratedhealth status. Even though only 1.4% of the sample mentioned that they have very poor-to-poorhealth status, 6.5% indicated that they experienced a health condition in the last 30 days. Ofthose who reported a health condition, 5.3% were diagnosed with chronic illness (diabetesmellitus, 3.9%; hypertension, 1.3%). Although 2.4 times more adolescent in rural areas are in the 117

lower class compared with those in urban areas, rural adolescents have a greater good healthstatus compared to their urban counterparts, but this was the reverse for rural and periurbanadolescents. Another important finding was that there is no statistical association between healthconditions and area of residence, but urban and periurban adolescents were more likely to havehealth insurance coverage compared to those in rural areas. In Jamaica, the adolescence population’s health status is comparable to those in theUnited States [23], suggesting that inspite of the socioeconomic disparities between the twonations and among its peoples, the self-reported health status among adolescent Jamaicans isgood. The high health status of those in the adolescence population in Jamaica speaks good ofthe inter dynamics within the countries, but does not imply that they are the same across the twonations or can it be interpreted that the quality of life of Jamaicans is the same as those in theUnited States. Simply put, the adolescence population in Jamaica is experiencing a good healthstatus although HIV/AIDS, unwanted pregnancies, and inconsistent condom usage are high inthis cohort [1-5]. While the aforementioned results about good health status of Jamaican adolescentsconcurs with PAHO’s work in 2003 [5] and others [17], which has continued into 2007, thecurrent paper provides more information on health matters of adolescents aged 10-19 years thanthat offered by PAHO. An adolescent in Jamaica who seeks medical attention is 100% less likelyto report an illness, and those who indicated at least good self-rated health status was 13 timesmore likely not to report an illness. Continuing, adolescents in the upper class are 15 times morelikely to report very poor-to-poor health status compared to those in the lower class. And thatthose who indicated very poor-to-poor health status are more likely to seek medical care (10times), live in crowded household and less likely to spend more on consumption and non- 118

consumption items. On the other hand, those who stated that their health status was at leastmoderate were less likely to live in crowded household, spent more on consumption and non-consumption items. Using a 2007 national probability dataset for the adolescence population inJamaica, we can add value to the existing literature on health status as well as the socialdeterminants of health. Grossman introduced the use of econometric analysis in the examination of health in the1970s to establish determinants of self-rated health [33], which has spiraled a revolution in thisregard since that time. Using data for the world’s population, he identified particular socialdeterminants of health that was later expanded upon by Smith and Kington [34]. Since the earlierpioneers’ work on social determinants of health [33, 34], the WHO joined the discourse in 2000s[27] as well as Marmot [26], Kelly et al. [28]; Marmot and Wilkinson [29]; Solar and Irwin [30];Graham [31]; Pettigrew et al. [32], Bourne [35], Bourne [36], Hambleton et al. [37] and Bourneand Shearer [38], but none of them evaluated whether there was variability in the determinants ofhealth depending on the measurement and/or dichotomization of health. The variability in social determinants of health was established by Bourne and Shearer[38] in a study between men in the poor and the wealthy social strata in a Caribbean nation, butthe literature at large has not recognized the variances in social determinants based on thedichotomization and non-dichotomization self-rated health status, and measurement of heath(using antithesis of illness and self-rated health status). Such a gap in the literature cannot beallowed to persist as it assumes that social determinants are consistent over the measurement ofhealth. Bourne [43] like Manor et al. [44] and Finnas et al. [45] have dichotomized self-reportedhealth status and cautioned future scholars about how the dichotomization can be best done. 119

According to Bourne [43] “The current study found that dichotomi[z]ing poor health status isacceptable assuming that poor health excludes moderate health status, and that it should remainas is and ordinal logistic be used instead of binary logistic regression” [43, p.310], and otherswarned against the large dichotomization of self-rated health status [44,45]. Because self-ratedhealth status is a Likert scale variable, ranging from very poor to very good health status, manyresearchers arbitrarily dichotomized it, but the cut-off is not that simple as was noted by Bourne[43], Manor et al. [44] and Finnas et al. [45]. From data on Jamaicans, Bourne’s work revealed that the cut-off in the dichotomizationof self-rated health status should be best done without moderate health when dichotomizing forpoor health status [43]. All the scholars agreed that narrowed cut-offs are preferable in thedichotomization of self-rated health status, but only a few variables were used (marital status,age, social class, area of residence and self-reported illness) [43-45]. Bourne postulated that “Bycategorising an ordinal measure (i.e., self-reported health) into a dichotomous one, this meansthat some of the original data will be lost in the process.” [43, p.295]. Using many morevariables, the present work highlighted that some social determinants of health are lost as a resultof the dichotomization process. Simply put, the social determinants of health are not consistentacross the dichotomization process which concurs with the literature. While we concur with other scholars that by dichotomizing self-rated health status somesocial determinants are lost in the process [43-45], we will not argue with those who opined thatself-rated health status should remain a Likert scale measure [52, 53]. The evidence is in thatmore social determinants in the non-dichotomized self-rated health do not give a greaterexplanatory power; instead this model had the least explanation. This indicates that more is notnecessarily better, and such information must be taken into account in a decision to cut-off at a 120

particular point. The fact that more social determinants of health emerged when health was non-dichotomized coupled with a lower explanatory power compared with when it is dichotomized asvery poor-to-poor health means that using self-rated health as a Likert scale valve is notpreferable to dichotomizing it. A narrower dichotomization of self-rated health status,particularly very poor-to-poor health, as well as moderate-to-very good health status yieldedgreater explanations than non-dichotomizing health status. This study used both the antithesis of illness and self-rated health status to measure, andevaluates the social determinants of health, and assess whether antithesis of illness is still a bettermeasure of health than self-rated health status. A comparison of the social determinants basedon the measurement of health revealed that for the Jamaican adolescence population, antithesisof illness is a better measure than self-reported health status in determining social determinantsbecause of its explanatory power (53%) compared to those that used the self-rated health status(explanatory power at most 38%). On the other hand, the antithesis of illness had fewer socialdeterminants compared with those in self-rated health status, suggesting that more socialdeterminants of health should not be preferred to fewer because the latter measure had a greatestexplanation. Like dichotomizing self-rated health status, variation also exists amongdichotomization of health and antithesis of illness. Thus, it appears that the antithesis of illnessmay provide a better measure for the social determinants of health than self-rated health status. Diener [50, 51] had postulated that self-reported health status can be effectively appliedto evaluate health status instead of objective health status measurement (morbidity, lifeexpectancy, mortality), and Bourne [46] found a strong statistical association between self-reported illness and particular objective measure of health (life expectancy, r = -0.731); but aweak relationship between self-reported illness and mortality. Using a nationally representative 121

sample 6,782 Jamaicans, one researcher warned against using self-reported illness as a measureof health as he found that men were over-reporting their illness [54], and this means they wereover-rating their antithesis of illness. Those studies highlight the challenges in using subjectivemeasures in evaluating health as they are not consistent like the objective ones such as mortality,life expectancy, and diagnosed morbidity. Nevertheless, on examining the antithesis of illnessand self-rated health status, it was revealed that 2.9% of those who indicated very good healthstatus had an illness compared to 20% of those who reported an illness who had very good healthstatus. From the current work again it emerged that there is disparity between self-reportedillness (or antithesis of illness) and self-rated health status, indicating why caution is required inusing either one or the other. Other disparities between antithesis of illness and self-rated health status highlighted thatantithesis of illness is a better measure of health than self-rated health status. Clearly despite theefforts of the WHO in broadening the conceptualization of health away from the antithesis ofillness, the Jamaican adolescence population has not moved to this new frontier. As when theywere asked to report on the antithesis of illness, they gave lower values than indicated for self-rated health status. Because antithesis of illness captures health more than self-rated healthstatus, this justifies why the former had a greater explanation when the social determinants ofhealth were examined than that of self-rated health status. But, where were their differences inthe variables used in one measure compared with the others? In fact, all the variables used in this study were social determinants that were identified inthe literature [26-38], and many of them were not significant for the adolescence population ofthis research. It can be extrapolated from the current work that social determinants of health for apopulation are not the same for a sub-population, in particular adolescence population. Thus, 122

when the WHO [27] and affiliated scholars [26, 28-32] forwarded social determinants of health,prior to that some scholars like Grossman [33] and Smith and Kington [34] had already socialdeterminants of health of a population. However, none of them stipulated that there aredisparities and variations in these based on the dichotomization, non-dichotomization, sub-population, and measurement of health (ie self-rated health or antithesis of illness). Using a cross-sectional survey (2003 US National Survey of Childrens Health) of some102,353 children aged 0 to 17 years, Victorino and Gauthier [55] established that there weresome variations in social determinants of health based on particular health outcomes. The healthoutcomes used by Victorino and Gauthier are presence of asthma, headaches/migraine, earinfections, respiratory allergy, food/digestive allergy, or skin allergy, which are healthconditions. Another research using the 2003 US National Survey of Childrens Health (NSCH)investigated the association of eight social risk factors on child obesity, socioemotional health,dental health, and global health status [56]. From a research in England, Currie et al. [57] founddisparity in income gradient associated with subjectively assessed general health status, and noevidence of an income gradient associated with chronic conditions except for asthma, mentalillness, and skin conditions. This paper concurs with the literature that there are variations in some socialdeterminants of health status across measurement, dichotomization and non-dichotomization ofhealth. However, the present work went further than the current literature and found thatparticular dichotomization of health had stronger explanatory power, and disparity indeterminants. As such, the variations in social determinants of health vary across thedichotomization and measurement of health as this paper showed that more social factors do nottranslate into greater explanatory power; and that stronger explanation does not denotes more 123

social determinants. And the social determinants of health had the greatest explanatory powerused antithesis of illness to measure health.ConclusionIn summary, the general health status of the adolescence population in Jamaica is good, but 7 inevery 100 have reported an illness of which some had chronic conditions (diabetes mellitus,3.9% and hypertension, 1.3%), and those who classified as being in the wealthy class were morelikely to report very poor-to-poor health status compared with those in the lower class. Anotherimportant finding was that rural adolescents had a greater health status than urban adolescents,but periurban adolescents had the greatest health status. Outside of the aforementioned good health news, the social determinants of self-ratedhealth status vary across the measurement of and dichotomization and non-dichotomization ofhealth and the population used. This work provides invaluable insights into how socialdeterminants should be examined, modify the general social determinants of health offered bythe World Health Organization and some associated scholars. By varying the measurement,dichotomization and non-dichotomization of health, this work provide some justification as towhether a particular dichotomization of health is better or non-dichotomization is preferable todichotomization. This researcher will not join the group of scholars who are purporting for the non-dichotomization of self-rated health status, but we recognized that discourse offers someinformation. However, we will chide researchers against arbitrarily using a particulardichotomization, non-dichotomization and measurement without understanding peoples’perception of health to which they seek to examine, and evaluate these. Thereby, despite the 124

international standardized definition of a phenomenon, people may a different view as to thisissue.DisclosuresThe author reports no conflict of interest with this work.DisclaimerThe researcher would like to note that while this study used secondary data from the 2007Jamaica Survey of Living Conditions (JSLC), none of the errors in this paper should be ascribedto the Planning Institute of Jamaica and/or the Statistical Institute of Jamaica, but to theresearcher.AcknowledgementThe author thank the Data Bank in Sir Arthur Lewis Institute of Social and Economic Studies,the University of the West Indies, Mona, Jamaica for making the dataset (2007 Jamaica Surveyof Living Conditions, JSLC) available for use in this study. 125

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Table 5.1: Demographic characteristic of studied population, n = 1394Characteristic n PercentSex Male 672 48.2 Female 722 51.8Union status Married 1 0.2 Common-law 14 2.4 Visiting 73 12.5 Single 494 84.8Social assistance Yes 232 17.3 No 1108 82.7Area of residence Urban 394 28.3 Periurban 287 20.6 Rural 713 51.1Population Income Quintile Poorest 20% 320 23.0 Second poor 328 23.5 Middle income 287 20.6 Second wealthy 263 18.9 Wealthiest 20% 196 14.1Self-reported illness Yes 89 6.6 No 1251 93.4Self-reported diagnosed illness Influenza 22 28.9 Diarrhoea 1 1.3 Respiratory illness (ie asthma) 16 21.1 Diabetes mellitus 3 3.9 Hypertension 1 1.3 Other conditions (unspecified) 33 43.4Health care-seeking behaviour Yes 50 53.8 No 43 46.2Self-rated health status Very good 631 47.2 Good 601 45.0 Moderate 84 6.3 Poor 18 1.3 Very poor 2 0.1Health insurance coverage No 1123 85.3 Yes 194 14.7Age, mean (Standard deviation, SD) 14.2 years (SD = 2.8 years)Length of illness, median (range) 5 days ( 0 – 36 days) 129

Table 5.2: Particular demographic variables by area of residence, n = 1,394Characteristic Area of residence P, χ2 Urban Periurban RuralSelf-reported illness n (%) n (%) n (%) 0.628, 0.931 Yes 27 (7.1) 15 (5.4) 47 (6.9) No 352 (92.9) 264 (94.6) 635 (93.1)Self-rated health status 24.82, 0.002 Very good 162 (42.7) 141 (50.4) 328 (48.4) Good 172 (45.4) 132 (47.1) 297 (43.9) Moderate 38 (10.0) 7 (2.5) 39 (5.8) Poor 7 (1.8) 0 (0.0) 11 (1.6) Very poor 0 (0.0) 0 (0.0) 2 (0.3)Social class 172.64, < 0.0001 Lower 101 (25.6) 108 (37.6) 439 (61.6) Middle 88 (22.3) 58 (20.2) 141 (19.8) Upper 205 (52.0) 121 (42.2) 133 (18.7)Educational level 37.79, < 0.0001 Primary or below 138 (36.6) 136 (48.6) 312 (46.1) Secondary 213 (56.5) 136 (48.6) 359 (53.0) Tertiary 26 (6.9) 8 (2.9) 6 (0.9)Sex 1.20, 0.548 Male 213 (54.1) 148 (51.6) 361 (50.6) Female 181 (45.9) 139 (48.4) 352 (49.4)Health insurance coverage 9.36, 0.009 Yes 73 (19.4) 37 (13.6) 84 (12.6) No 303 (80.6) 235 (86.4) 585 (87.4)Length of illness, mean ± SD 6.0 ± 5.7 days 7.8 ± 9.0 days 6.4 ± 6.5 days F = 0.42, 0.857 130

Table 5.3: Logistic regression: Variables of antithesis of illness among adolescence population, n = 1,280Characteristic OR CI (95%)Age 1.1 1.0 - 1.3Health care-seeking (1=yes) 0.0 0.0 - 0.01*Health insurance coverage (1=yes) 1.0 0.4 - 2.5Primary education (reference group) 1.0Secondary 1.8 0.9 - 3.7Tertiary 1.9 0.3 - 15.1lnMedical 0.8 0.1 - 5.0Male 1.4 0.7 - 2.6Social assistance from government 1.6 0.6 - 4.4Logged family income 0.8 0.3 - 1.8Rural area (reference group)Urban 1.6 0.7 - 3.8Periurban 1.2 0.5 - 2.9Poor-to-Very poor health status (reference group) 1.0Moderate-to-Very good health status 0.3 0.03 - 2.1Good-to-Very good health status 12.6 6.0 - 26.3*Lower class (reference group)Middle class 1.6 0.5 - 5.2Upper 0.8 0.2 - 3.1Crowding 0.9 0.8 - 1.1Model χ2, P 287.08, < 0.0001-2 LL 327.56R2 0.53Hosmer and Lemeshow χ2 = 4.40, P = 0.82OR denotes odds ratio, CI (95%) means 95% confidence interval and *P < 0.05 131

Table 5.4: Logistic and Ordinal Logistic regression: Factors explaining self-reported health status of adolescents, n = 1,280 Self-rated health status Very poor-to-poor Good Moderate-to-very Good-to-very AllCharacteristic good good OR CI (95%) OR CI (95%) OR CI (95%) OR CI (95%) Estimate CI (95%)Self-reported illness (1=yes) 2.0 0.3 – 15.6 0.1 0.05 – 0.2* 0.5 0.1 – 4.4 0.1 0.05 – 0.2* 1.8 1.1 – 2.4*Age 1.0 0.9 – 1.2 0.9 0.9 – 1.1 1.0 0.8 – 1.2 0.9 0.9 – 1.1 0.02 - 0.03 – 0.1Health care-seeking (1=yes) 10.0 1.0 – 96.5* 0.7 0.3 – 1.9 0.1 0.01 – 0.5* 0.7 0.3 – 2.1 1.0 0.1 – 2.0*Health insurance coverage (1=yes) 0.3 0.04 – 2.8 1.1 0.6 – 2.2 3.0 0.4 – 25.5 1.2 0.6 – 2.4 0.04 - 0.3 – 0.4Primary education (reference group) 1.0 1.0 1.0 1.0 1.0Secondary 0.7 0.3 – 1.9 0.9 0.6 – 1.5 1.4 0.5 – 3.8 1.0 0.6 – 1.6 0.02 - 0.2 – 0.2Tertiary 0.0 0 – 0.0 0.4 0.1 – 1.0 5E+007 0.0 - 0.4 0.2 – 1.3 0.3 0.4 – 1.0Logged Medical expenditure 1.6 0.7 – 3.6 0.6 0.4 – 1.2 0.7 0.4 – 1.2 0.5 0.1 – 1.0*Social assistance from government 0.2 0.03 – 1.7 1.2 0.6 – 2.2 4.8 0.6 – 38.5 1.2 0.6 – 2.3 0.1 - 0.2 – 0.4Lower class (reference group) 1.0 1.0 1.0 1.0 1.0Middle class 0.6 0.1 – 2.9 2.1 0.9 – 4.5 1.8 0.3 – 9.6 2.2 1.0 – 4.8 - 0.7 - 1.0 - - 0.4*Upper 14.9 1.9 – 118.3 * 0.7 0.3 – 1.4 0.1 0.01 – 0.5* 0.7 0.3 – 1.6 - 0.6 - 1.0 - -0.1Rural area (reference group) 1.0 1.0 1.0 1.0 1.0Urban 1.6 0.4 – 3.0 0.6 0.4 – 1.0* 0.9 0.3 – 2.7 0.6 0.4 – 1.0* 0.5 0.2 – 0.8*Periurban 0.0 0.0 - 0.0 3.3 1.3 – 8.2* 2E+0007 3.3 1.53– 8.2* - 0.01 - 0.3 – 0.3Male 0.9 0.3 – 2.3 1.5 1.0 – 2.4 1.1 0.4– 3.0 1.4 0.9 – 2.2 - 0.1 - 0.3 – 1.2Logged family income 0.1 0.04 – 0.4* 1.3 0.9 – 2.0* 8.2 2.8 – 23.8* 2.0 1.2 – 3.4* - 0.30 - 0.6 – -0.001*Crowding 1.6 1.3 – 2.0* 0.9 0.8 – 1.0* 0.6 0.5 – 0.8* 0.9 0.8 – 0.98* 0.1 - 0.01 – 0.1*Model χ2, P 59.66, < 0.0001 113.11, < 0.0001 30.37, < 0.0001 113.11, <0.0001 112.94, < 0.0001-2 LL 146.38 588.76 175.67 588.76 2354.33R2 0.38 0.20 0.31 0.20 Pseudo R2 = 0.10Hosmer and Lemeshow χ2 = 4.6, P = 0.82 χ2 = 4.61, P = 0.80 χ2 = 4.36, P = 0.94 χ2 = 4.61, P = 0.80 Goodness of fit, χ2=5451.14. P < 0.001OR denotes odds ratio; *P < 0.05 132

Table 5.5: Self-rated health status and antithesis of illness, n = 1,330 Self-rated health statusCharacteristic Very good Good Moderate Poor Very poor n (%) n (%) n (%) n (%) n (%)Antithesis of illness No 18 (2.9) 38 (6.4) 26 (31.3) 7 (38.9) 0 (0.0) Yes 611 (97.1) 560 (93.6) 57 (68.7) 11 (61.1) 2 (100.0)χ2 = 125.58, P < 0.0001 Good health (Antithesis of illness)Characteristic No Yes n (%) n (%)Self-rated health status Very good 18 (20.0) 611 (49.2) Good 38 (42.7) 560 (45.1) Moderate 26 (29.2) 57 (4.6) Poor 7 (7.9) 11 (0.9) Very poor 0 (0.0) 2 (0.2)χ2 = 125.58, P < 0.0001 133

CHAPTER 6Self-reported health and health care utilization of older peoplePaul A. Bourne, Christopher A.D. Charles, Cynthia G. Francis & StanWarrenMany studies have examined health status, physical functionality, lifestyle and livingarrangements of the elderly (ages 60+ years); but have not investigated the health, health care-seeking behaviour and health conditions of people 80+ years in developing nations, inparticular Jamaica. Global statistics reveal that the 80+ age group is growing faster than theyounger old population and that come 2050 1 in 9 elderly will be 80+ years. The aims of thisstudy are to (1) examine the health status of the 80+ year population in Jamaica, (2) evaluatewhether there are shifts in the typology of dysfunctions over the last 6 years (2002-2007), (3)examine whether health status and self-reported dysfunctions are correlated for the 80+ agecohort, (4) evaluate the health care-seeking behaviour of those who are 80+ years, and (5)compare and contrast the results of the 80+ year cohort with the general 60+ year cohort. Thecurrent study extracted a sample of 722 elderly 80+ years from the dataset of the JamaicaSurvey of Living Conditions (JSLC). The JSLC is a modification of the World Bank’s HouseholdLiving Standard Survey. In 2007 compared to 2002, diabetes mellitus had the greatest increaseof 550% over the studied period compared to 9% increase in unspecified diseases, and -76.6% inarthritic cases. No significant statistical association was found between health status and area ofresidents (χ2 = 11.899, P > 0.05) likewise between health status and sex of respondents (χ2 =3.867, P > 0.05) and between health status and health care-seekers (χ2 = 3.350, P > 0.05). Astatistical correlation existed between health status and self-reported illness; (χ2 = 13.036, P =0.011), and between health status and income quintile (χ2 = 26.716, P < 0.045); as well asbetween health status and health insurance coverage (χ2 = 21.913 P = 0.039). Health care-seeking is an inelastic commodity as more health insurance coverage or total annual expenditurethis could see an incremental change in health care-seeking behaviour. Money continues toexplain greater health status for the wealthiest 20% of 80+ age cohort in Jamaica. One of theironies in this study is the fact that the poorest 20% recorded the second highest health status. 134

IntroductionIn the Caribbean and Latin America, issues on the elderly (ages 60+ years) have been reviewedby scholars such as Alvarado et al. [16]; Bourne [12-15]; Brathwaite [10, 11]; Eldemire [1-6];Grell [7]; Hambleton and colleagues [9]; Lawson [8]; and others [17-20]. However, Bourne [15],Hambleton et al. [9] and Menéndez et al. [20] have examined health status of the elderly in theLatin America and the Caribbean with only the former investigating the health status of the old-to-oldest elderly (ages 75+). While Hambleton and colleagues, and Menéndez and collaboratorshave examined health status, health conditions and functional capacity of people 60+ years,Bourne [15] studied health and health conditions of elderly 75+ years which means that none ofthose studies have researched the changing pattern of acute and chronic diseases, health care-seeking behaviour and health status for the population 80+ years. Many studies examine the elderly age cohort as a single entity, indicating that they treathealth challenges facing the elderly population (60+ year) as though they are the same across theelderly age cohort - young-old (ages 60-74 years); old-old (ages 75-84 years) and oldest-old(ages 85+). In 2000, statistics revealed that there were 1.4% of the Caribbean population 80+years, 1.8% of Jamaica, 0.9% of Latin America and the Caribbean and 6.9% of the World [21].Based on Figures 1 and 2, the rate of growth in the population 60+ years is greater than that forthe 65+ and 80+ years in the Caribbean as well as in Jamaica; but this does not mean that the 80+age cohort given that they constituted less than 2% should be excluded from research inquiry.The reality is they do exist, and information are needed on them in order to guide public healthpolicies and programmes as current plans are made for this age cohort using information on thegeneral elderly population. 135

Data from the Statistical Institute of Jamaica (STATIN) on mortality goes up to age 75+years [22], but no mortality data are available for those 80+ years. Mortality which is used tocompute life expectancy is therefore not presented for people 80+ years neither are health statusnor health conditions. United Nations’ publication reported data on survival rates, lifeexpectancy, growth rate, sex ration, population and percentage of people in older ages for thoseup to 80+ age cohort which is not the case for STATIN. Neither of the two institutions hasexamined in a single study the health, health conditions and health care-seeking behaviour ofthose 80+ years. Statistics from Pan American Health Organization (PAHO) [23] presentedinformation on health of people 60+ years and again no data is available on those 80+ years andthey constituted 2% of the Jamaica’s population and 1.1% of the world’s population. Thetraditional approach is life expectancy, and health status of the elderly population (60+ years) bydisaggregating the old population and this assumes that the conditions affecting this age cohortremains constant during old age. Bogue opined that the health problems, health conditions and health care-seekingbehaviour (ie health demand) increases with ageing [24], suggesting that aggregating elderly in60+ and examining this age cohort will not provide the health practitioner with a betterunderstanding of the different ageing segment and issues surrounding that age cohort. Statisticsfrom the Planning Institute of Jamaica (PIOJ) and the Statistical Institute of Jamaica revealedthat elderly Jamaicans had the greatest hospital visits and, health conditions than all other agecohorts [25]. Again the data were not disaggregated by the three elderly age cohorts, whichmeant that information is lost in the aggregated data. Concomitantly, 37.9% of all new diabeticcases and 39.8% of new hypertensive cases between January and June 2007 seen in public healthfacilities were accounted by senior Jamaicans (ages 60+ years) [26]. At the same time, 43.8% of 136

elderly (ages 65+ years) in 2007 reported an illness in the 4-week reference period and 75.9%indicated that the illness was a recurring one compared to 74.2% of those 60-64 years whoreported that they were suffering from a recurring illness and 36.6% revealed that they were ill[25]. There is a gap in the literature about the health status, health conditions and health care-seeking behaviour of people 80+ years in the Caribbean in general and Jamaica in particular. The health literature that evaluates functional capacity, health status, health conditionsand health care-seeking behaviour of the elderly 60+ years or even 65+ year span the 3categories of elderly (i.e. young-old; old-old and oldest-old) and does not provide acomprehensive understanding of the elderly cohorts. Hypertension, diabetes mellitus andarthritis are among the five leading cause of morbidity in the elderly (ages 60+ years) populationin Jamaica [26] and this is also the case in Barbados, St. Lucia, Guyana, and Trinidad andTobago, and Uruguay [13, 27]. Using data on a PAHO/WHO survey on health, wellbeing andaging (i.e. SABE), Rossi and Triunfo [28] disaggregated the data for the three elderly age cohortsbut like previous studies, they did not use this to ascertain information on chronic illness, orhealth status. While this data provides invaluable information on the population 60+ years, bynot disaggregating the elderly into the 3 aforementioned categories the data assume that they areaffected at the same rate across the life course. Outside of South America, and Latin America and the Caribbean, using information onelderly 75+ years from Israel, Benyamini et al. [29] found that the health status of young-old(75-84 years) was lower than that for the old-old (85-94 years). A study in Newcastle conductedby Collerton et al. [30] on elderly 85+ years revealed that 77.6% of them rate their health statusas at least good, indicating that the remainder were experiencing at least poor health. A study by 137

Bourne et al. [14], using data for Jamaicans 55+ years, they found that as people age increases,their poor health status increases.. However, Bourne et al’s work [14] found that 52% of elderly 70+ years reported poorhealth compared to 22% of the participants 85+ years in the Newcastle study. Extrapolationfrom the two studies suggests that there is a positive relationship between increased healthconditions and age of old people. Inspite of the literature, there is a gap in the health literature onthe health status, health conditions and health care-seeking behaviour of those 80+ years.Therefore, the aims of this study are to (1) examine health status of the 80+ year population inJamaica, (2) evaluate whether there are shifts in the typology of dysfunctions over the last 6years (2002-2007), (3) examine whether health status and self-reported dysfunctions arecorrelated for those 80+ age cohort, (4) evaluate the health care-seeking behaviour of those 80+years, and (5) compare and contrast the results of the 80+ year cohort with the general 60+ yearcohort. We now turn to the material and methods we used in the current study.Source: Extracted from Department of Economic and Social Affairs Population Divisions, United Nations, (UN).World Population Ageing 1950-2050. New York: 2002.Figure 6.1. Caribbean Elderly population as a percentage of total population 138

Source: Extracted from Department of Economic and Social Affairs Population Divisions, United Nations, (UN).World Population Ageing 1950-2050. New York: 2002.Figure 6.2. Jamaica Elderly population as a percentage of total populationMaterials and MethodsSampleThe current study extracted a sample of 722 elderly participants 80+ years from the dataset of theJamaica Survey of Living Conditions (JSLC): 566 and 159 respondents from 2002 and 2007.The JSLC is jointly administered by the Planning Institute of Jamaica (JSLC) and the StatisticalInstitute of Jamaica (STATIN). JSLC is a national cross-sectional probability survey which isconducted normally between April and May of each year. An-administered instrument(questionnaire) is used to collect data from Jamaicans. The questionnaire was modelled from theWorld Bank’s Living Standards Measurement Study (LSMS) household survey. There are somemodifications to the LSMS, as JSLC is more focused on policy impacts. The questionnairecovered socio-demographic variables – such as education; daily expenses (for past 7-day; food 139

and other consumption expenditure; inventory of durable goods; health variables; crime andvictimization; social safety net and anthropometry. Survey The survey was drawn using stratified random sampling. The design was a two-stagestratified random sampling design where there was a Primary Sampling Unit (PSU) and aselection of dwellings from the primary units. The PSU is an Enumeration District (ED), whichconstitutes a minimum of 100 residences in rural areas and 150 in urban areas. An ED is anindependent geographic unit that shares a common boundary. This means that the country isgrouped into strata of equal size based on dwellings (EDs). Based on the PSUs, a listing of all thedwellings was made, and this became the sampling frame from which a Master Sample ofdwelling was compiled, which in turn provided the sampling frame for the labour force. Onethird of the Labour Force Survey (i.e. LFS) was selected for the JSLC. The sample was weightedto reflect the population of the nation. The non-response rate for the survey for 2007 was 26.2%and 27.7% for 2002. The non-response includes refusals and rejected cases in data cleaning. Statistical analysis The data were collected, stored and retrieved in SPSS for Windows 16.0 (SPSS Inc;Chicago, IL, USA). Descriptive statistics were used to provide information on the socio-demographic variables of the study; and, chi-square was used to examine association betweennon-metric variables and ANOVA was utilized to examine the equality of means among the non-dichotomous variables. In addition to the aforementioned, elasticity of demand and incomeelasticity of demand were computed for health status. 140

Measurement Elasticity of demand measures consumers’ demand responsiveness to changes inparticular product attributes such as price. In this paper, the research will examine healthinsurance elasticity of health care-seeking behaviour, and income elasticity of health care-seeking behaviour.Elasticity is calculated as a percentage of the change in demand (in this case health care-seekingbehaviour) divided by the percentage change in (1) health insurance; and (2) income (ie totalannual expenditure).Elasticity of health care-seeking behaviour with reference health Insurance = % Δ HSB/ %Δ HI Where HSB is health care-seeking behaviour and HI is health insurance coverageElasticity of health care-seeking behaviour with reference to income = % Δ HSB/ %Δ Y Where Y is income (ie total annual expenditure).Elasticity of health care-seeking behaviourwith reference to self-reported illness = % Δ HSB/ %Δ SRI Where SRI is self-reported illnessThe values below will be used to compute the elasticities. 141

Table 6.0. Health insurance, health care-seekers and median total annual expenditure for 2002and 2007 20021 20072Health insurance coverage 16 (2.9%) 45 (29%)Health care-seekers 163 (68.2%) 59 (77.6)Self-reported illness 239 (43.5%) 76 (48.7%)Median Total Annual Expenditure (Range) Ja $170,019.8 Ja $396,576.9 (Ja $1,954,053) (Ja $5,213,338)1 Ja $50.47 + US $1.002 Ja $80.97 = US $1.00Health conditions (ie. self-reported illness or self-reported dysfunction): The question was asked:“Is this a diagnosed recurring illness?” The answering options are: Yes, Cold; Yes, Diarrhoea;Yes, Asthma; Yes, Diabetes; Yes, Hypertension; Yes, Arthritis; Yes, Other; and No.Self-rated health status: “How is your health in general?” And the options were very good; good;fair; poor and very poor.Social class: This variable was measured based on the income quintiles: The upper classes werethose in the wealthy quintiles (quintiles 4 and 5); middle class was quintile 3 and poor those inlower quintiles (quintiles 1 and 2).Health care-seeking behaviour. This is a dichotomous variable which came from the question“Has a doctor, nurse, pharmacist, midwife, healer or any other health practitioner been visited?”with the option (yes or no).National Health Fund (NHF). This is a health coverage provided by the Jamaican Government toreduce the burden on the health care sector. It provides prescription health benefits to allresidents. This was established under the National Health Fund Act which came into being in2003. The NHF subsidies drugs for residents who are affected by any of the 15 illnesses. Theseare (1) arthritis; (2) asthma; (3) benign prostate hyperplasia (BPH); (4) breast cancer; (5) diabetesmellitus; (6) epilepsy; (7) glaucoma; (8) high cholesterol; (9) hypertension; (10) ischemic heartdisease; (11) major depression; (12) prostate cancer; (13) psychosis; (14) rheumatic heartdisease, and (15) vascular disease. 142

Jamaica Drug for the Elderly Programme (JADEP). The JADEP was established by the Ministryof Health in July 2004 to provide drugs for elderly Jamaicans (ages 60+ years), and this was laterhanded over to the NHF as an individual benefit. It enables elderly people to access drugsthrough subsidized payment by the government if the individual is suffering from anycombination of eleven dysfunctions. These are 1) arthritis; 2) asthma; 3) benign prostatehyperplasia; 4) enlarged prostate; 5) cardiac or heart disease; 6) diabetes mellitus; 7) highcholesterol; 8) hypertension (or high blood pressure); 9) psychiatric conditions; 10) vascularconditions (or circulatory problems), and 11) glaucoma.ResultsA sample of 566 elderly 80+ years was extracted for 2002 (39.9% men and 60.1% women) witha mean age of 85.4 years (4.6 years), while the sample for 2007 was 157 elderly 80+ years(37.1% men and 62.9% women) with a mean age of 85.0 years (4.5 years) (Table 6.6.1). Forty-four percent of the 2002 sample reported suffering from an illness and this increased to 48.7% in2007. In 2002, 42.2% of the sample responded to the question of ‘have you visited a health carepractitioner in the last 4-weeks’ compared to 47.8% in 2007. Of those who responded, 68.2%reported yes in 2002 and 77.2% claimed yes in 2007. Based on Table 6.1, there is a shift towardurban areas: 30.2% resided in urban areas in 2007 compared to 10.1% in 2002; 18.7% in semi-urban areas in 2002 and 20.8% in 2007. Shifts were also taking placing in health conditions overthe two periods studied. In 2007 over 2002, in the acute illness category, there were reductions inthe number of elderly suffering from cold and asthma to increases in those suffering fromasthma., Hypertension was the most prevalently diagnosed disease among chronic conditions in2007 (46.8%) and this represented a 1% decline over 2002. Diabetes mellitus had the greatestincrease by 550% over the period studied compared to +9% in unspecified diseases, and -76.6%in arthritic cases (Table 6.1). Similarly, the numbers of 80+ years widowed Jamaicans increasedby 3.8% and the percentage of married sample increased to 25.8% (from 23.3% in 2002). Threepercentage of the elderly 80+ years had health insurance coverage in 2002 and by 2007 this had 143

increased exponentially to 900%. The increased in health insurance coverage can be substantiallyaccounted for by public coverage (+782.8%). Based on Table 6.2, no significant statistical correlation was found between diagnosedhealth conditions and area of residents and that this was the case in both years. In spite of thisreality, the reduction in hypertensive cases can be accounted for by the decline in number ofcases in semi-urban residents, while the urban cases increased. The greatest reduction in arthriticcases were among urban residents followed by rural dwellers and an increase was also observedamong semi-urban residents. Increases in diabetic cases were observed in all three geographicregions with the greatest increase in the semi-urban areas. No significant statistical association was found between health status and area ofresidents (χ2 (df = 8) = 11.899, P > 0.05). No comparison is possible as there were no figures for2002 as the first time that data on health status was recorded was in 2007 (Table 6.3). Table 6.4 showed that a statistical correlation existed between health status and self-reported illness but that the relationship was a weak one (contingency coefficient = 0.278).Furthermore, 46.1% of those who indicated an illness had health status was poor-to-very-poor,with only 2.6% of them having a very good health status, 11.8% a good health status and 39.5%a moderate health status. On the other hand, the 25.1% of those who indicated that they had noillness reported poor-to-very-poor health status compared to the 10.0% who had very goodhealth status and the 25.0% who had good health status. A cross-tabulation between health status and sex of respondents revealed no significantstatistical correlation (χ2 (df = 4) = 3.867, P > 0.05) (Table 6.5). A statistical relationship exists between health status and income quintile (χ2 (df = 16) =26.716, P < 0.045); but that the association was a weak one, cc=0.381.Further examination 144

revealed that the wealthiest 20% had the greatest very good and good health status compared tothe other social classes (Table 6.6). Table 6.6 indicated that the poorest 20% had a very goodhealth status which was greater than that of the other classes. Only 17.4% of the wealthiest 20%reported a poor health status compared to 36.7% of the poorest 20%; 23.3% of the poor; 27.7%of the middle class and 25.9% of the wealthy. The greatest very poor health status was recordedby wealthy respondents (14.8%) followed by the poor (13.3%); middle class (8.8%) and thepoorest 20% (3.3%). No significant statistical association was found between health status and health care-seekers (χ2 (df = 4) = 3.350, P > 0.05) (Table 6.7). Based on Table 6.8, a statistical correlation existed between health status and healthinsurance coverage (χ2 (df = 4) = 21.913 P = 0.039); but that the relationship was a moderateweak one, contingency coefficient = 0.352. On examination, it was revealed that the those withprivate health insurance was most likely to have good health status; those with national healthfund (NHF) was most likely to report moderate health and those with other public coverage alsoso likely to have moderate health status along side those without health insurance coverage. Although no significant statistical association was found between diagnosed healthconditions and health care-seeking behaviour for both 2002 (χ2 (df = 5) = 5.381, P > 0.05) and2007 (χ2 (df = 7) = 6.209, P > 0.05), in 2007, the percentage of the sample with hypertension wasseeking less medical care and this also the case for the arthritic patients, and those with cold.However, increases were recorded for diabetes mellitus, diarrhoea and unspecified dysfunctioncases (Table 6.9). 145

Significant statistical difference was found between those with particular health statusand the amount of money they were able to spend (F statistic [5,152] = 7.134, P < 0.001) (Table6.10). Those with the greatest expenditure had the highest health status (ie very good) followedby those with good. However, those with moderate health status had the least mean annualexpenditure, with those who recorded very poor health status spent more than those with a poorhealth status. Table 6.6.11 revealed that no significant statistical correlation was found between self-reported health conditions and total expenditure (F statistic [5, 30] = 0.396, P > 0.05). In 2007, a significant statistical correlation was found between self-reported healthconditions and total annual expenditure (F statistic [7, 69] = 2.935, P = 0.009) (Table 6.6.11).Based on Table 6.6.11, of those who were diagnosed with either acute or chronic healthconditions, diarrhoea patients spent the most (Ja $597,953.39) followed by diabetic patients (Ja$568,441.75) and the least was spent by asthma patient (Ja $42,703.27). No significant statistical difference existed between the expenditure on particular healthcare facilities and self-reported health conditions: for 2002 (F statistic [7, 53] = 0.288, P = 0.955)and for 2007 (F statistic [7, 46] = 0.119, P = 0.997) (Table 6.12). A cross-tabulation between area of residents and sex of respondents revealed nosignificant statistical correlation for 2002 (χ2 (df = 2) = 0.612, P > 0.05) or 2007 (χ2 (df = 2) =3.958, P > 0.05). Although there was no statistical association between the two aforementionedvariables, it was observed that in 2002 10.6% of women lived in urban areas compared to 9.3%of men and in 2007 the figures increased by 230.2% and 136.6% for women and menrespectively. For 2002, 73.0% of women resided in rural areas compared to 73.0% of men and 146

the percentages fell to 50.8 and 48.0 for men and women respectively. However, in 2007, thepercentage of men who lived in semi-urban areas increased by 53.1% while the number ofwomen declined by 12.4%. These findings indicate urbanization of 80+ year population inJamaica. Based on Figure 6.3, the greatest percentage increase in the ownership of healthinsurance coverage was in the poor cohort (3600%) compared to the poorest 20% (2575%);middle class (855%); wealthy (640%) and the wealthiest 20% (458%).Figure 6.3. Percentage of population 80+ years with health insurance coverage, 2002 and 2007Elasticity of health care-seeking behaviourHealth care-seeking behaviour with respect to health insurance = 0.352, which indicates thathealth care-seeking behaviour of Jamaicans is highly unesponsive to changes in health insurance 147

coverage. With all other things being equal, a 1% change in health insurance will cause a lessthan 1% change in health care-seeking behaviour of the Jamaicans who are 80+ years of age. Health care-seeking behaviour with respect to total annual expenditure (median) = 0.382.The value denotes that health care-seeking behaviour is less responsive to changes in income.With all other things being equal, a 1% change in health insurance will cause a less than 1%change in health care-seeking behaviour of the Jamaicans who are 80+ years of age. Elasticity of health care-seeking behaviour with reference to self-reported illness = 0.94.This finding emphasizes the reluctance of the participants in the sample to seek medical careeven when illnesses are on the rise. Over the period, the percentage change in self-reportedillness was 68.2% which result in a 63.8% change in health care-seeking behaviour with all otherthings being held constant. Health care-seeking therefore is an inelastic commodity becausemore health insurance coverage or total annual expenditure will see an incremental change inhealth care-seeking behaviour.DiscussionThe present research highlighted that at least 1 of every 2 elderly 80+ years reported an illnessand 35 out of every 100 indicated at least poor health status. There was a 5.7% reduction innumber of respondents with diagnosed chronic illness and13.8% more respondents soughtmedical care in 2007 than in 2002. The gender differences in health status were not statisticallysignificant as well as health conditions by area of residence, and health status by area ofresidence. Some 41% of those who sought medical care indicated at least poor health status withhypertension being the most prevalent health condition. 148

In Rossi and Triunfo’s work [28], 6.5% of elderly 60+ years indicated poor (bad) healthstatus. Benyamini et al. [29], found that one-third of elderly (75+ years) in Israel reported poorhealth status which is similar to the findings in the current study (35.1%). These findings indicatethat as people become older their health status decline and this is supported somewhat by thefindings of Collerton et al. [30]. They found that 32.4% of the elderly 85+ years reported poorhealth status. Comparatively, although the age cohort for the present study is not the same as thatCollerton et al’s study, marginally more of the 80+ year Jamaicans had poor health compared tothe elderly in Collerton et al’s study. In the present research unlike the ones mentioned earlier,there is a significant statistical association between self-rated health status and self-reportedillness. Almost two times more 80+ year olds in this study who reported an illness indicated poorhealth status compared to those who did not report an illness. This finding indicates that illnesscan be used to offer some explanation for the poor self-rated health status of the elderly. The prevalence of self-reported illness for the 80+ year old population in Jamaica was 3.1times more than that of the population, 1.3 times more than that for the 60-64 years old and 1.1times more than that for the 65+ year old Jamaicans. Concurringly, the most prevalent diseasesin the current work and that of Collerton et al was hypertension, with 57.5% of elderly 85+having the condition compared to 46.8% of 80+ years, and this was 43% in Rossi and Triunfo’sstudy. In Jamaica, the prevalence of people with hypertension was 2.1 less than the 80+ yearpopulation. There was even a difference in the prevalence of hypertension among those 65+yearsand 80+ years with hypertension 1.3 times more prevalent in the latter group compared to theformer. Furthermore, 1.5 times more of the 80+ age group had diabetes mellitus compared to thepopulation. These findings indicate the health disparity between young old and the 80+ age 149

group as well as the population and 80+ age cohort. The high prevalence of chronic illness inolder people accounts for a higher percentage of them utilising health care practitioners. Statistics from the Planning Institute of Jamaica and the Statistical Institute of Jamaica,for 2 decades (1989-2007), showed that elderly (ages 60+ or 65+ years) sought more health careservices and reported greater number of cases in chronic illnesses than all other age cohorts [25].This paper found that 78 out of every 100 of those 80+ year old sought medical care in the last 4-weeks which is greater than that for those 65+ years (ie. 72%) and the population (66%). InJamaica, the 80+ age cohort sought more medical care in the last 4-weeks compared to the 85+year olds in Newcastle (i.e. one third visited outpatient clinic in the last 3 months, averaging 10%in 4-weeks). Unlike the other studies on the elderly, our study presents comparative information acrosstwo periods. It was revealed that 5.2% more of those 80+ years of age reported an illness in 2007over 2002. Although the percentage of those diagnosed with chronic diseases declined by 5.4%over the two periods, in disaggregating the data it was found that there was a 550% increase inthe number of 80+ year olds with diabetes mellitus in 2007 than in 2002; and a 76.6% decline inarthritic cases. While there were declines in chronic diseases in the 80+ age cohort, no significantstatistical association was found between (1) diagnosed health condition and area of residencesover the period; (2) health status and area of residence, (3) health status and gender ofparticipants, (4) health status and health care-seeking behaviour, and (5) diagnosed healthcondition and health care-seeking behaviour. The World Health Organization (WHO) opined that “The health implications of healthyageing – the physical and mental characteristics of old age and their associated problems – need 150

to be better understood” [31]. This view implies that there should be a better understanding ofthe demands, preparations, and social and economic factors of ageing through policy baseresearch to better plan for the reality of an ageing population in particular the 80+ age cohort.This study corroborates the literature that the health problems of ageing are extensive; but it goesfurther to show the remarkable differences between the 60+ and 80+ age cohorts in terms ofhealth condition . In 2007, 15.5% of the elderly Jamaicans reported an illness and 66% of them soughtmedical care [25], suggesting that 34 out of every 100 Jamaican who indicated a healthconditions did not seek health care but may have used home remedy. Statistics revealed that30.2% of those who indicated an illness used home remedy [25], suggesting that there were illJamaicans who did not seek professional medical care. For the elderly population the statisticsare somewhat different as 43.8% of those 65+ and 36.6% of 60-64 year cohorts reported a healthcondition, with 75.1% of the 60+ population sought medical care which is 2.1% less than thenumber of 80+ years who visited a health care practitioners in the same 4-week period. Thirty-five in every 100 of the 80+ year cohort reported poor-to-very poor health status,yet there was no significant difference in medical expenditure. Interestingly to note is the factthat those who reported diarrhoea and diabetes mellitus spent more than those with otherdiagnosed health conditions but this greater spending was not used for medical expenditure.Those 80+ year olds with very poor health status had a greater total annual expenditure than thepoor, with those in very good health spending the most for a year. Further examination of healthstatus and social class (ie income quintile) showed that the wealthiest 20% had the greatesthealth status followed by poorest 20%. Marmot [32] opined that income is positively associatedwith better health status which is equally the same among 80+ year olds. Continuing, the 151

wealthiest 20% recorded the greatest health status; and their good health was 2.4 times more thanthose in the poorest 20%. Those in the poor 20% evaluated their good health to be greater thanthat for those in the wealthy socioeconomic strata. This finding somewhat supports Marmot’swork, but shows that the upper socioeconomic strata does not always have better healthcompared to the poor income groups. Studies have revealed the significant statistical association between health status andgender. Although there are more studies which show that men have a greater health status thanwomen, some have found that women having a greater health and others revealed little genderdifferences [29, 33-40]. Rudkin [33] found that women have lower levels of wellbeing (i.e.economic) than men, and Benyamini et al [29] found that they had lower self-rated health statusthan men. Rudkin’s finding was further sanctioned by Haveman et al [34] whose study revealedthat retired men’s wellbeing was higher than that of their female counterparts, because menusually received and had more material resources, and more retired benefits compared to womenages 65 years and older. Therefore, with men receiving more than women, and having a moredurable possession than women, their material wellbeing is higher in later life. Courtenay [35]noted from research conducted by the Department of Health and Human Services [36] and theCenters for Disease Control [37] that from the 15 leading causes of death except Alzheimer’sdisease, the death rates are higher for men and boys in all age cohorts compared to women andgirls. Embedded within this theorizing are the differences in fatal diseases that are explained bygender characterisics [38], to which Courtenay [35] explained are due to behavioural practices ofboth genders. The foregoing explains the fact that men are dying 6 years earlier than females[39]. However this study does not concur with the literature in anyway because no statisticalcorrelation was found between the health status and gender of the 80+ year cohort. This work 152

also disagrees with Smith and Kington [40] that income can buy health as this research foundthat the poorest 20% among the 80+ year olds in Jamaica had greater good health that those inthe wealthy socioeconomic strata. However, in the present work the self-reported good healthstatus for those in the wealthiest 20% was 2.4 times more, and this seemingly supports Smith andKington’s work. Health is not a product which is transferrable from one human to another,suggesting that it cannot be bought. It can be extrapolated from the present research that those inthe wealthiest 20% lifestyle, income, sociophysical milieu and health choices are such that theyfoster greater good health, and this does not indicate a purchase of good health over those in thepoorest 20%. Using a sample of 1,006 Jamaicans who indicated that they sought medical care in a 4-week period in 2007, Bourne [41] found that there was no significant statistical associationbetween medical care and health insurance coverage. The current study contradicts that ofBourne’s work as it was found that 12% of the variability in medical care-seeking behaviour canbe explained by health insurance coverage and other studies [42]. In 2002, health insurancecoverage was totally private which saw 3 out of every 100 of the 80+ year elderly havingcoverage. In the post-2003 period when health took on a public aspect, coverage increased to 29out of every 100 in 2007. These findings explain the increase in health care seeking behaviourwhich was recorded in 2007 over 2002: 68.2% in 2002 and 77.6% in 2007. In 2007, 21 out ofevery 100 poorest 20% had health insurance compared to 1 in every 100 in 2002. Thissubstantial increase was also recorded for the poor with 33 out of every 100 having healthinsurance compared to 1 in every 100 in 2002. Hence, the increase in the number of health careseekers is 2007 is due to the poor and poorest who were unable to previously afford health carebecause of financial constraints were now able to do so. 153

In 2007, 43 out of every 100 elderly ages 60-64 years indicated that they were unable toafford medical care compared to 27 out of 100 elderly 65+ years. Concurrently, 22% of theelderly 60-64 years indicated that they used home remedy compared to 24% of the elderly 65+years. Through the JADEP and National Health Insurance programme the out of pocketexpenditure on medical care is substantially reduced, yet only 21% of the poorest 20% hadaccessed to this or private insurance; 33% of the poor; 28% of the middle class; 22% of thewealthy and 44% of the wealthiest 20%. This finding suggests more than cost constraint, it is aself-perception that they are not sufficiently medically ill to require care, the cultural biasesinfavor of folk medicine and their perspectives on living longer. These factors may account for theirresponsiveness of this age cohort to seek medical care within the context of increased healthinsurance coverage and expenditure. This is not atypical as Borghesi and Vercelli [43] showedthat elderly people have a progressively lower elasticity of aspirations to outcome, suggestingtheir unwillingness to carry out some functions and attain particular events is low. This view is apossible explanation for the low responsiveness of the 80+ age cohort in their health care-seeking behavior despite having more health care-choices. The issue which must be raised and addressed in this study is the validity of the self-reported health as a measure of health. The relation of self-reported health to health has beenknown for some time. The scientific literature has shown that self-rated health status is highlyreliable to proxy for health and that this has successfully crossed cultural lines [44]. Anotherstudy conducted by O’Donnell and Tait [45] concluded that self-reported health status can beused to indicate wellbeing as all respondents who had chronic diseases reported very poor health.It is for this rationale why some studies have used self-reported health conditions and healthstatus instead of life expectancy or other objective indices to measure health [46-48] as the latter 154

is narrower than the former and does not encapsulate the extent life as subjective measures. Thiswork has revealed that there is statistical relationship between health status and self-reportedillnesses of elderly (80+ years) Jamaica, but that the association was a weak one. Benyamini etal. [29] found that self-reported health status was strongly associated with shorter term mortality(within the next 4 years) than longer-term mortality (9 years of follow-up) of elderly Israelis. Medical practitioners, social workers, health education and promotion specialists andpublic health practitioners as well as policy makers are now provided with an extensive reviewof the health conditions, shifts in patterns of illness, health care-seeking behaviour and practicesof elderly 80+ years in Jamaica. In excess of 77% of those who reported ill-health soughtmedical care in the 4-week reference period of the survey, which indicates that there are some80+ age individuals who are likely to use home remedy and not seekmedical care because offinancial constraints, and the perception that the illness is not severe enough or they just do notwant to visit a traditional medical practitioner. Close to one-half of those who reported a healthcondition suffered from hypertension and despite only 18 out of every 100 ill 80+ age elderlyhad diabetes mellitus, the number of cases of people suffering from this illness increased by550% in 2007 over 2002. This increased number of reported cases in diabetes mellitus isalarming and must be addressed with urgency by public health specialists. With the urbanization of the 80+ age cohort to urban and semi-urban areas in Jamaica,health practitioners and other specialists must be equally cognizant of this population ageingmigration phenomenon in order to effectively address the needs of the cohort within their newplace of abode. There are no gender differences in the urbanization of this cohort in Jamaica.However, approximately 50% of elderly still reside in rural areas (50.8% men and 48% women). 155

Another interesting finding of the current study is the preponderance of women to men inthe 80+ age cohort. The sex ratio for this cohort was 59 men to every 100 women indicating agreater mortality of men at older ages than women. Concomitantly, the expansion of publichealth insurance for elderly Jamaica has seen an exponential increase in the number of 80+ agedJamaican accessing the service; but most of the cohort is yet to subscribe for this freeprogramme. Again this emphasize the need for a national public health campaign by the NationalHealth Fund to inform senior citizens about the public assistance available to reduce their out ofpocket cost for medical care. In Jamaica, the elderly poorest 20% to the wealthiest 20% has the same access to healthinsurance coverage as this is free for all persons 60+ years. In spite of this reality, the wealthiest20% recorded the greatest health insurance coverage (44%) compared to 21% of the poorest20%; 33% of the poor; 28% of the middle class and 22% of the wealthy. The issue here is notaccess or inaffordability as is the case in other Latin Americans and Caribbean states [42]; butwillingness to access such facilities owing to culturization. The loftiness in the culture explainsthe rationale for the greater percentage of Jamaicans using private health care facilities becausein 2007, 52% of Jamaicans used private health care facilities compared 41% using the free publichealthcare facilities. The elderly would be more set in their ways, and so the willingness torequest and seek assistance from stranger in particular an outsider will be offensive. Thisunwillingness may explain the reluctance of the poorest 20% to subscribing for the free healthinsurance coverage compared to the wealthiest 20%. Health care-seekers are not likely to respond greater than the change in particularindividual attributes because health care-seeking behaviour is an inelastic commodity. An crucialfinding is the participants’ irresponsiveness to changes in health insurance coverage or more total 156

expenditure. It is this fact that explains why health insurance coverage increased by over 180%and this results in a 64% change in health care-seeking behaviour, with all other things beingheld constant. Likewise, a 167% change in total annual expenditure result in a 64% change inhealth care-seeking behaviour with all other things being held constant.ConclusionIn summary, money continues to explain greater health status for the wealthiest 20% of 80+ agecohort in Jamaica. One of the ironies in this study is the fact that the poorest 20% recorded thesecond highest health status, indicating that this social class enjoys a greater health status thanthe wealthy, middle and poor cohorts. Money therefore makes a difference for the wealthiest andnot the wealthy or middle class that are 80+ years old. This contradicts the general perspectivethat poverty is the cause of ill-health [42] as wealthy and middle classes recorded greater poorhealth status that the poorest 20% of 80+ age cohort. Simply put, the poorest 20% reported lesshealth conditions than the two aforementioned age cohorts because access to more financialresources do no mean this will be expended on medical care. The current study highlights acritical issue in that the health care-seeking behaviour of the elderly 80+ years is an inelasticproduct. This inelasticity suggest that health care seeking behaviour is less responsive to self-reported illness, health insurance and the amount of money that the individual is able to spendbecause at this age people do not aspire for much more in their lives.Conflict of interestThe authors have no conflict of interest to report.Disclaimer 157

The researchers would like to note that while this study used secondary data from the JamaicaSurvey of Living Conditions, none of the errors in this paper should be ascribed to the PlanningInstitute of Jamaica or the Statistical Institute of Jamaica, but to the researchers.References1.Eldemire D. The Jamaican elderly: A socioeconomic perspective and policy implications.Social and Economic Studies 1997;46: 175-193.2.Eldemire D. Older women: A situational analysis, Jamaica 1996. New York: United NationsDivision for the Advancement of Women; 1996.3. Eldemire D. A situational analysis of the Jamaican elderly, 1992. Kingston: PlanningInstitute of Jamaica; 1995.4. Eldemire D. The elderly in Jamaica: A gender and development perspective. In Robert, J.H.,Kitts, J., and L.J. Arsenault, eds. Gender, health, and sustainable development. Perspective fromAsia and the Caribbean. Proceedings of workshops held in Singapore, 23-26 January 1995 and inBridgetown, Barbados, 6-9 December 1994. Ottawa: International Development ResearchCentre.5. Eldemire D. The elderly and the family: The Jamaican experience. Bulletin of EasternCaribbean Affairs 1994;19:31-46.6. Eldemire D. The elderly – A Jamaican perspective. In Grell GAC. (ed). The elderly in theCaribbean: Proceedings of continuing medical education symposium. Kingston, Jamaica:University Printery; 1987.7. Grell GAC, editor. The elderly in the Caribbean. Proceedings of a Continuing MedicalEducation Symposium. Kingston, Jamaica; 1987.8. Lawson SC. Culture and Aging: The case of Jamaican Elderly persons. Paper presented at theConference on Caribbean Culture, The University of the West Indies, Mona Campus, Jamaica,March 4-6, 1996.9.Hambleton IR, Clarke K, Broome HL, Fraser HS, Brathwaite F, Hennis AJ. 2005. Historicaland current predictors of self-reported health status among elderly persons in Barbados. RevistaPanamericana de Salud Pứblica 17: 342-352.10. Brathwaite FS. The elderly in the Commonwealth Caribbean: A review of research findings.Ageing and Society 1989;9:297-304. 158

11. Brathwaite FS. The elderly in Barbados: problem and policies. Bulletin of the Pan AmericanHealth Organization 1990;23:314-29.12. Bourne PA. 2008. Medical Sociology: Modelling Well-being for elderly People in Jamaica.West Indian Med J 57:596-04.13. Bourne PA. Growing old in Jamaica: Population Ageing and Senior Citizens’ Wellbeing.Kingston: Department of Community Health and Psychiatry, Faculty of Medical Sciences, theUniversity of the West Indies, Mona, WI; 2009.14. Bourne PA, McGrowder DA, Crawford TV. Decomposing Mortality Rates and ExaminingHealth Status of the Elderly in Jamaica. The Open Geriatric Med J. 2009; 2:34-44.15. Bourne PA. Good Health Status of Older and Oldest Elderly in Jamaica: Are theredifferences between rural and urban areas? Open Geriatric Medicine Journal. 2009; 2:18-27.16. Alvarado BE, Zunzunegui VM, Beland F, Sicotte M, Tellechea L. Social and genderinequalities in depressive symptoms among urban older adults of Latin America and theCaribbean. The J of Gerontology Series B: Psychological Sciences and Social Sciences2007;62:S226-S236.17. Peláez M. Building the foundations for health in old age in the Americas. RevistaPanamericana de Salud Publica 2005;17:299-30618. Albala C, Lebrao ML, Diaz EML, Ham-Chande R, Hennis AJ, Palloni A, Pelaez M, Pratts O.The Health, Well-Being, and Aging ("SABE") survey: methodology applied and profile of thestudy population. Revista Panamericana de Salud Publica 2005;17:307-322.19. Wong R, Pelaez M, Palloni A. Self-reported general health in older adults in Latin Americaand the Caribbean: usefulness of the indicator. Revista Panamericana de Salud Publica 2005;17:323-332.20. Menéndez J, Guevara A, Arcia N, León D, Esther María, Marín C, Alfonso JC. Chronicdiseases and functional limitation in older adults: a comparative study in seven cities of LatinAmerica and the Caribbean. Revista Panamericana de Salud Publica 2005;17: 353-361.21. Department of Economic and Social Affairs Population Divisions, United Nations, (UN).World Population Ageing 1950-2050. New York; 2002.22. Statistical Institute of Jamaica, (STATIN). Demographic Statistics, 2007. Kingston;STATIN; 2008.23. Pan American Health Organization, (PAHO). Health in the Americas, 2007, volume IICountries. Washington DC; 2007. 159

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Table 6.1. Sociodemographic characteristic of sampleVariable 2002 2007 N= 566 N=159Gender Male 39.9 37.1 Female 60.1 62.9Health care-seeking behaviour Yes 68.2 77.6 No 31.8 22.4Health insurance coverage Yes 2.9 29.0 No 97.1 71.0Area of residence Rural 71.2 49.1 Semi-urban 18.7 20.8 Urban 10.1 30.2Self-reported illness Yes 43.5 48.7 No 56.5 51.3Diagnosed Health conditionsAcute: Cold 2.8 1.3 Diarrhoea 2.8 3.9 Asthma - 1.3Chronic: Diabetes mellitus (ie diabetes) 2.8 18.2 Hypertension 47.8 46.8 Arthritis 27.8 6.5 Other 16.7 18.2 Not diagnosed - 3.9Income quintile Poorest 20% 24 18.9 Poor 20.1 18.9 Middle 18.7 29.6 Wealthy 18.2 17.0 Wealthiest 20% 18.9 15.7Age Mean (SD) 85.4 yrs (4.6 yrs) 85.0 yrs (4.5 yrs)Length of illness Median (Range) 10 days (90 days) 7days (998)Number of visits to health practitioner(s) median (range) 1.0 (7) 1.0 (4)Health status Very good NI 6.4 Good NI 18.5 Moderate NI 40.1 Poor NI 26.8 Very poor NI 8.3Marital status Married 23.3 25.8 Never married 22.8 19.4 Divorced 0.7 2.6 Separated 1.8 2.6 Widowed 47.9 49.7 162

Table 6.2. Diagnosed health conditions by area of residenceVariable 20021 20072Diagnosed Health Rural Semi-urban Urban Rural Semi-urban UrbanconditionsCold 3.2 0.0 0.0 0.0 6.3 0.0Diarrhoea 0.0 33.3 0.0 5.3 0.0 4.8Asthma - - - 0.0 0.0 2.4Diabetes 3.2 0.0 0.0 21.1 25.0 14.3Hypertension 48.8 66.7 0.0 47.4 25.0 54.8Arthritis 29.0 0.0 50.0 5.3 6.3 7.1Other 16.1 0.0 50.0 15.8 37.5 11.9No - - - 5.3 0.0 4.8 χ (df = 10) = 15.561, P > 0.05 1 2 χ (df = 14) = 13.607, P > 0.05 2 2 163

Table 6.3. Health status by area of residenceVariable 20021 20072Health status Rural Semi-urban Urban Rural Semi-urban UrbanVery good NI NI NI 6.4 6.1 6.5Good NI NI NI 31.9 18.2 10.4Moderate NI NI NI 38.3 33.3 44.2Poor NI NI NI 21.3 30.3 28.6Very poor NI NI NI 2.1 12.1 10.41 NI χ (df = 8) = 11.899, P > 0.052 2NI No information available 164

Table 6.4. Health status by self-reported illness, 2007Health status Self-reported illness Yes NoVery good 2.6 10.0Good 11.8 25.0Moderate 39.5 40.0Poor 32.9 21.3Very poor 13.2 3.8 χ (df = 4) = 13.036, P = 0.011, cc=0.278 2 2 165

Table 6.5. Health status by genderHealth status Sex1 Man WomanVery good 5.1 7.1Good 16.9 19.4Moderate 35.6 42.9Poor 35.6 21.4Very poor 6.8 9.2 χ (df = 4) = 3.867, P > 0.05 1 2 166

Table 6.6. Health status by genderHealth status Income quintile1 Poorest Poor Middle Wealthy Wealthiest 20% 20%Very good 10.0 6.7 0.0 3.7 17.4Good 13.3 10.0 23.4 7.4 39.1Moderate 36.7 46.7 40.4 48.1 26.1Poor 36.7 23.3 27.7 25.9 17.4Very poor 3.3 13.3 8.5 14.8 0.0 χ (df = 16) = 26.716, P < 0.045, cc=0.3811 2 167

Table 6.7. Health status by health care-seeking behaviourHealth status Health care-seeking behaviour1 Yes NoVery good 1.7 5.9Good 11.9 11.8Moderate 35.6 52.9Poor 35.6 23.5Very poor 15.3 5.9χ (df = 4) = 3.350, P > 0.051 2 168

Table 6.8. Health status by health insurance coverageHealth status Health Insurance Coverage1 Private Public, NHF Public, Other NoVery good 0.0 12.0 0.0 5.5Good 60.0 28.0 0.0 17.3Moderate 20.0 48.0 53.3 38.2Poor 20.0 8.0 46.7 28.2Very poor 0.0 4.0 0.0 10.9 χ (df = 4) = 21.913 P = 0.039, cc=0.3521 2Note: NHF – National Health Fund 169

Table 6.9. Diagnosed health conditions by health care seeking behaviourVariable 20021 20072 Health care-seeking behaviour Health care-seeking behaviourDiagnosed Health Yes No Yes NoconditionsCold 6.0 12.5 1.7 0.0Diarrhoea 3.6 0.0 5.1 0.0Asthma - - 1.7 0.0Diabetes 3.6 0.0 18.6 17.6Hypertension 46.4 50.0 42.4 64.7Arthritis 32.1 12.5 5.1 11.8Other 14.3 25.0 20.3 5.9No - - 5.1 0.0 χ (df = 5) = 5.381, P > 0.05 1 2 χ (df = 7) = 6.209, P > 0.05 2 2 170

Table 6.10. Health status by Annual total expenditure, 2007 Descriptive statistics 95% Confidence Interval Health status Mean Std. Deviation Std. Error Very good 1,447,018.91 1,595,683.12 504,599.31 305,535.97 - 2,588,501.85 Good 651,694.11 561,405.68 104,250.42 438,146.81 - 865,241.41 Moderate 442,482.79 400,604.78 50,471.46 341,591.79 - 543,373.80 Poor 473,225.25 428,012.88 66,043.82 339,847.05 - 606,603.46 Very poor 502,309.96 214,315.07 59,440.31 372,800.66 - 631,819.26 Total 558,288.05 615,473.17 49,120.11 461,261.72 - 655,314.38F statistic [5,152] = 7.134, P < 0.001Values are quoted in Jamaican dollars (US $1.00 = Ja. $80.47, in 2007) 171

Table 6.11. Self-reported health conditions by total expenditure, 2002 and 2007 20021 95% Confidence Interval for Mean Std. LowerSelf-reported health conditions Mean Deviation Std. Error Bound Upper BoundCold 101,186.97 . . . .Diarrhoea 301,830.15 . . . .Diabetes mellitus 227,604.63 . . . .Hypertension 191,674.92 114,769.48 27,835.69 132,665.90 250,683.94Arthritis 180,414.82 153,268.67 48,467.81 70,773.02 290,056.62Unspecified 148,949.44 98,636.87 40,268.33 45,436.40 252,462.48Total 182,970.56 119,752.91 19,958.82 142,452.01 223,489.11 20072 Cold 236,103.72 . . . . Diarrhoea 597,953.39 98,902.35 57,101.30 352,266.33 843,640.45 Asthma 42,703.27 . . . . Diabetes mellitus 568,441.75 417,728.90 111,642.74 327,252.26 809,631.23 Hypertension 310,082.28 233,719.82 38,953.30 231,002.88 389,161.69 Arthritis 188,747.40 123,903.88 55,411.50 34,900.41 342,594.40 Unspecified 496,102.96 343,771.70 91,876.86 297,615.09 694,590.83 No 1,103,454.01 1,320,420.17 762,344.94 2,176,651.5 4,383,559.56 Total 420,692.91 398,170.68 45,375.76 330,319.25 511,066.571 Values are quoted in Jamaican dollars (US $1.00 = Ja. $50.97, in 2002)1 F statistic [5, 30] = 0.396, P > 0.052 Values are quoted in Jamaican dollars (US $1.00 = Ja. $80.47, in 2007)2 F statistic [7, 69] = 2.935, P = 0.009 172

Table 6.12. Self-reported health conditions by medical care expenditure (public and private health care expenditure), 2002 Mean Std. Deviation Std. Error 95% Confidence Interval Self-reported health conditions Upper Bound Lower Bound Upper Bound Lower Bound Upper Bound Cost at Public Cold 0.00 . . . . Health Facility1 Diarrhoea 0.00 0.00 0.00 0.00 0.00 Asthma 0.00 . . . . Diabetes mellitus 120.00 145.68 46.07 15.79 224.21 Hypertension 997.50 3124.79 698.72 -464.95 2459.95 Arthritis 416.67 520.42 300.46 -876.12 1709.45 Unspecified 240.91 406.71 122.63 -32.32 514.14 No 33.33 57.73 33.33 -110.09 176.75 Total 493.14 1983.53 277.75 -64.74 1051.01 Cost at Private Cold 1600.00 . . . . Health Facility2 Diarrhoea 4300.00 3404.41 1965.54 -4157.03 12757.02 Asthma 0.00 . . . . Diabetes mellitus 2855.55 7762.10 2587.37 -3110.93 8822.0378 Hypertension 2147.83 6564.29 1368.75 -690.78 4986.44 Arthritis 833.33 763.763 440.96 -1063.96 2730.62 Unspecified 2316.67 3151.291 909.70 314.43 4318.90 No 1650.00 919.24 650.00 -6609.03 9909.03 Total 2281.48 5482.01 746.01 785.18 3777.781F statistic [7, 53] = 0.288, P = 0.9552F statistic [7, 46] = 0.119, P = 0.997 173

CHAPTER 7Socioeconomic correlates of self-evaluated health status of elderlywith diagnosed chronic medical conditions, JamaicaThe aim of the current study is to examine the health status of elderly Jamaicans in rural, peri-urban and urban areas of residence in Jamaica, and to propose a model to predict the socialdeterminants of poor health status of elderly Jamaicans with at least one chronic disease. A sub-sample of 287 respondents 60 years and older was extracted from a larger nationally cross-sectional survey of 6783 respondents. The stratified multistage probability sampling techniquewas used to draw the survey respondents. A self-administered questionnaire was used to collectthe data from the sample. Descriptive statistics were used to examine the demographiccharacteristics of the sample; chi-square was used to investigate non-metric variables, andlogistic regression was the multivariate technique chosen to determine predictors of poor healthstatus. Approximately thirty six percent of the sample had poor health status. Majority (43.2%)of the sample reported hypertension, 25.4% diabetes mellitus and 13.2% arthritis. Only 35.4% ofthose who indicated that they had at least one chronic illness reported poor health status andthere was a statistical relation between health status and area of residence [χ2 (df = 4) = 11.569,p = 0.021, n = 287]. Rural residents reported the highest poor health status (44.2%) comparedto other town (27.3%) and urban area dwellers (23.7%). The majority of the respondents in thesample had good health, and those with poor health status were more likely to report havinghypertension followed by diabetes mellitus and arthritis. Poor health status was more prevalentamong those of lower economic status in rural areas who reported greater medical health careexpenditure. The prevalence of chronic diseases and levels of disability in older people can bereduced with appropriate health promotion and strategies to prevent non-communicablediseases.IntroductionThe Caribbean has been identified as the most rapidly ageing region of the world. Between 1960and 1995, there was a 76.8% increase in the elderly population.1 Among its regional islandstates, the average growth rate in the elderly population was approximately 5.3% for the 1995-2000 period. The elderly as a percentage of total population was 4.3% in 1950 and is estimatedto reach about 15% by 2020.1 In Jamaica, a similar pattern has been observed with a clear andrapidly rising trend in the elderly as a proportion of the population.2 By 2025 as much as 1 in 7 174

persons will be elderly. Moreover, characterizing this pattern of increasing elderly is thedifferential growth rates within the various sub-age groups over age 60, with the 75 years andabove age group expected to double moving from 2.8% currently to 4.0 % in 2025.3 Eldemire4noted that the elderly in Jamaica represents 10% of the population, and that they were for themost part mentally competent and physically independent. With a calculated life expectancy of75.5 years5, the burden on the healthcare system can be expected to increase. The epidemiologic transition in the Caribbean over the last 40 years has produced anepidemic of lifestyle-related chronic non-communicable diseases.6 Among these are obesity,diabetes, and hypertension, along with such complications as stroke, heart disease, andamputations.6 Cardiovascular disease is by far the leading cause of death at older ages indeveloping countries, although the impact of communicable diseases remains considerable.7 Onecomprehensive analysis attributes nearly 46 percent of all deaths among women aged 60 andover in developing countries in the early 1990s to cardiovascular disease; the correspondingfigure for older men was 42 percent.7 Older people with diabetes are at particularly high risk forheart disease, stroke, eye damage, kidney disease, limb amputation and depression. In the Surveyon Health and Well-Being of Elders (SABE), among those reporting diabetes, at least 60% alsoreported visual problems with or without eye glasses. Among those reporting at least two chronicdiseases, 25% had symptoms of depression.8 Furthermore, SABE indicates that an average of70% of women aged 60 years and older have at least one potentially disabling condition, such aslow vision, arthritis, or urinary incontinence.8 In developed countries, the health and social status of the elderly has received a fairamount of attention.9 With the Caribbean, some progress has been made in terms of research onthe elderly since Braithwaite10 when he noted that data on the Caribbean elderly were extremely 175

limited. With the continuing aging of the population in the Caribbean, gerontological researchhas devoted increasing attention to those at very advanced ages11 and in recent years, there hasbeen increasing interest in issues relating to health of the elderly in the Caribbean. Patterns ofmortality at the most advanced ages are of interest in their own right, indicating variation inhealth status and well-being among this group. Moreover, differences in mortality and trends inthem may give clues about the likelihood of a further extension of life expectancy.12 Rural populations in Caribbean countries generally experience excessive deficiencies inhealth care access, social services, and other goods and services needed for health living. Ruralresidence has significantly influenced health care access and health status. Urban residentsconsistently reported better health status than rural residents and greater satisfaction with theirhealth care.13 Rural residents are more often uninsured,14 and have greater distance to travel fortheir health care needs,13 and are more often plagued by resource inaccessibility.15 A greaterproportion of people from the rural population in Jamaica reported having chronic illnesses, withan even smaller population having insurance of any kind (7.6% in rural areas versus 25.0% inurban areas).16 The aim of the study is to examine the health status of elderly Jamaicans in rural,peri-urban and urban areas of residence. A model to predict the social determinants of poorhealth status of elderly Jamaicans who have reported at least one chronic disease is proposed.MethodsThe current study used cross-sectional survey data collected by the Planning Institute of Jamaica(PIOJ) and the Statistical Institute of Jamaica (STATIN)17 between May and August 2007. Thesample for this study was 287 individuals who indicated having being diagnosed with a chronicillness and who are older than 60 years. The study was extracted from a larger nationallyrepresentative cross-sectional survey of 6,783 Jamaicans. The survey was drawn using stratified 176

random sampling. This design was a two-stage stratified random sampling design where therewas a Primary Sampling Unit (PSU) and a selection of dwellings from the primary units. ThePSU is an Enumeration District (ED), which constitutes of a minimum of 100 dwellings in ruralareas and 150 in urban areas. An ED is an independent geographic unit that shares a commonboundary. This means that the country was grouped into strata of equal size based on dwellings(EDs). Based on the PSUs, a listing of all the dwellings was made, and this became the samplingframe from which a Master Sample of dwelling was compiled, which in turn provided thesampling frame for the labour force. One third of the 2007 Labour Force Survey (LFS) wasselected for the Jamaican Survey of Living Conditions (JSLC, 2007).17 The sample was weightedto reflect the population of the nation. The researchers chose this survey based on the fact that it is the latest survey on thenational population and that that it has data on health status of Jamaicans. A self-administeredquestionnaire was used to collect the data, which were stored and analyzed using SPSS forWindows 16.0 (SPSS Inc; Chicago, IL, USA). The questionnaire was modeled from the WorldBank’s Living Standards Measurement Study (LSMS) household survey. There are somemodifications to the LSMS, as JSLC is more focused on policy impacts. The questionnairecovered areas such as socio-demographic, economic and health variables. The non-response ratefor the survey was 26.2%. Descriptive statistics such as mean, standard deviation (SD), frequency and percentagewere used to analyze the socio-demographic characteristics of the sample. Chi-square was usedto examine the association between non-metric variables, and an Analysis of Variance(ANOVA) was used to test the relationships between metric and non-dichotomous categoricalvariables. Logistic regression examined the relationship between the dependent variable and 177

some predisposed independent (explanatory) variables, because the dependent variable was abinary one (health status: 1 if reported poor health status and 0 if otherwise). The results were presented using unstandardized B-coefficients, Wald statistics, Oddsratio and confidence interval (95% CI). The predictive power of the model was tested using theOmnibus Test of Model and Hosmer and Lemeshow18 was used to examine goodness of fit of themodel. The correlation matrix was examined in order to ascertain whether autocorrelation (ormulticollinearity) existed between variables. Based on Cohen and Holliday19 correlation can below (weak) - from 0 to 0.39, moderate – 0.4-0.69, and strong – 0.7-1.0. This was used to exclude(or allow) a variable in the model. Wald statistics were used to determine the magnitude (orcontribution) of each statistically significant variable in comparison with the others, and theOdds Ratio (OR) for the interpreting of each significant variable. Multivariate regression framework was utilized to assess the relative importance ofvarious demographic, socio-economic characteristics, physical environment and psychologicalcharacteristics, in determining the health status of Jamaicans; and this has also been employedoutside of Jamaica. This approach allowed for the analysis of a number of variablessimultaneously. Secondly, the dependent variable is a binary dichotomous one and this statistictechnique has been utilized in the past to do similar studies. Having identified the determinantsof health status from previous studies, using logistic regression techniques, final models werebuilt for Jamaicans as well as for each of the geographical sub-regions (rural, peri-urban andurban areas) and sex of respondents using only those predictors that independently predict theoutcome. A p-value of 0.05 was used to for all tests of significance. 178

ModelThe use of multivariate analysis in the study of health and subjective wellbeing (ie self-reportedhealth or happiness) is well established20,21 and this is equally the case in Jamaica andBarbados.22,23 The current study will employ multivariate analyses in the study of health status ofold Jamaicans with diagnosed chronic medical conditions. The use of this approach is better thanbivariate analyses as many variables can be tested simultaneously for their impact (if any) on adependent variable.The current study seeks to examine the social determinants of poor health status of old Jamaicanswho reported having at least one chronic medical condition (Equation [1]): H t = f(A i , G i , AR i , FC i , NFC i , MR i , S i , HIi , CR i , MC t , SA i , ε i ) [1]where H t (self-rated current health status in time t) is a function of age of respondents, A i ; sexof individual i, G i ; area of residence, AR i ; food consumption per person per household member,FC i ; non-food consumption per person per household member, NFC i ; marital status of person i,MR i ; social class of person i, S i ; health insurance coverage of person i, HIi ; crowding ofindividual i, CR i ; medical expenditure of individual i in time period t, MC t ; social assistance ofindividual i, SA i and an error term (ie. residual error).MeasureAge is a continuous variable which is the number of years alive since birth (using last birthday).Age group is a non-binary measure: young-old (ages 60 to 74 years); old-old (ages 75 to 84years) and oldest-old (ages 85 years and older).Elderly denotes the chronological age of 60 years and beyond. Self-reported illness (or self-reported dysfunction): The question was asked: “Is this a diagnosed recurring illness?” Theanswering options were: Yes, cold; Yes, diarrhoea; Yes, asthma; Yes, diabetes; Yes, 179

hypertension; Yes, arthritis; Yes, Other; and No. A binary variable was later created from thisconstruct (1 = yes, 0 = otherwise) in order to use in the logistic regression.Health status: “How is your health in general?” And the options were very good; good; fair; poorand very poor. For this study the construct was categorized into 3 groups with (i) good; (ii) fair,and (iii) poor. A binary variable was later created from this variable (1 = good and fair 0 =otherwise).Social class: This variable was measured based on income quintile: The upper classes were thosein the wealthy quintiles (quintiles 4 and 5); middle class was quintile 3 and poor those in lowerquintiles (quintiles 1 and 2).ResultsSocio-demographic characteristicsThe sample was 287 respondents (38.3% of men and 61.7% of women), with 57.1% young-old;33.1% old-old and 9.8% oldest-old. Seventy percent of the sample was head of household;35.5% had poor health status; 70.8% sought health care; 72.0% purchased the prescribedmedication; 33.2% had public health insurance coverage; 39.7% were poor; 26.5% lived in urbanareas, 19.1% in other towns and 54.4% in rural areas (Table 7.1). Majority (43.2%) of the samplereported hypertension; 25.4% diabetes mellitus; 13.2% arthritis and 18.2% unspecified the typeof chronic illness that they were diagnosed with (Table 7.1). Approximately eighteen percent ofthose who indicated that they did not seek care indicated that they could not afford it; 36.7%indicated that they were not ill enough; 13.9% reported that they use home remedy. 180

Bivariate analysesThere was no statistical correlation between health status and self-reported dysfunction (χ2 =1.810, p = 0.404, n= 286) (Table 7.2). Based on Table 7.2, only 35.4% of those who indicatedthat they had at least one chronic medical condition reported poor health status. Table 7.3revealed a statistical relation between health status and area of residence [χ2 (df = 4) = 11.569, p= 0.021, n = 287]. Rural residents reported the highest poor health status (44.2%) compared toother town (27.3%) and urban area residents (23.7%). On the other hand, greatest good healthstatus was reported by urban residents (21.1%), compared with other town (20.0%) and ruralarea residents (14.1%) (Table 7.3). No statistical association was found between diagnosedchronic medical condition and area of residence [χ2 (df = 6) = 10.455, p = 0.107, n = 287] (Table7.4).A statistical correlation was found between self-reported chronic medical condition and socialclass [χ2 (df = 6) = 15.870, p = 0.014, n = 287]. The wealthy was most likely to have diabetesmellitus (36.9%) while the poor (48.2%) and the middle class (51.6%) were mostly likely toindicated hypertension. Approximately ten percent of the wealthy had arthritis compared to12.9% of middle class and 16.7% of poor (Table 7.5).The mean number of day reported to have illness was 71.6 days (SD = 185.1, 95% CI = 49.1 –94.2 days). Urban dwellers reported the least number of days in illness (mean = 7.5 days,SD=10.96, 95% CI = 4.7 – 10.2 days) compared to other town residents (mean = 98 days, SD =216.4, 95% CI = 38.3 – 157.6 days) and rural residents (mean = 90.6 days, SD = 206.9, 95% CI= 56.4 – 124.8 days) - F statistic [2,257] = 5.031, p = 0.006. This was similar for medical health 181

care expenditure - F statistic [2,196] = 0.136, p = 0.001. The mean amount spent on medical carefor urban residents was US $21.85 compared to US $26.12 for other town residents and US$26.81 for rural respondents. On the other hand, there was a statistical difference between annualconsumption expenditure and area of residence - F statistic [2,284] = 10.248, p < 0.001. Themean annual amount spent by urban dwellers was US $8,711.95 than other town dwellers US$7,388.90 and rural residents US $5,445.09 (Table 7.6).Multivariate analysesThe socio-demographic determinants of poor health status of those who indicated beingdiagnosed with chronic illness were sex of respondents (OR = 2.15, 95% CI = 1.009 – 4.578) andfood consumption (OR = 1.00, 95% CI = 1.00 – 1.00) (Table 7.7). Elderly men who revealed thatthey were diagnosed with chronic illness were 2.15 times more likely to indicated poor healththan elderly women (Table 7.7).DiscussionSelf-reported health status has been widely used in censuses, surveys, and observational studiesand there is evidence suggesting that self-reported health is an indicator of general health withgood construct validity24 and is a respectably powerful predictor of mortality risks,25 disability26and morbidity.27 The results of this study showed that the majority of those sampled reportedthemselves to be experiencing good or fair health, while approximately one-third indicated poorhealth. These results concur with those by other researchers from Dominica28 and Trinidad.29 In arecent island wide survey of persons aged 65 years and older conducted in Trinidad in 2002,44% reported their health as fairly good or good. In reviews of the literature, Benyamini &Idler30 and Idler & Benyamini,25 showed that in most studies conducted since the 1980s, theelderly people who self-rated their health as bad presented greater incidence of death than didthose who considered it to be excellent. Among elderly people, self-rated health may present 182

greater sensitivity for men than for women. Since women live longer than men and experiencemore years with diseases and incapacities, they tend to rate their health more negatively than domen, but do not necessarily die because of this, over the short term. Thus, negative self-ratedhealth expressed by women may be more associated with quality of life. On the other hand, whenmen rate their health negatively, they present a greater risk of succumbing to a fatal event.31 There has been a general epidemiological shift from infectious to chronic diseases andthe elderly are one of the main at risk groups. In this study, just over one-third of the respondentswho reported poor health indicated that they had at least one chronic disease. This is less than the80% reported in a study in Trinidad.29 The main chronic illnesses reported by the respondents inthis study were hypertension, diabetes and arthritis. This is in keeping with the study by Rawlinset al31 and other Caribbean studies on this age group.32,33 Furthermore, a study conducted onelderly Jamaicans showed that this age cohort was mainly affected by chronic non-communicable diseases.34 The most common chronic diseases identified among the elderly inJamaica are hypertension, arthritis, diabetes, cardiovascular arrest, stroke and cancer. Patients inthe 60 and over age groups accounted for 37.2% and 41.1%, respectively, of new hypertensiveand diabetic cases.35 Some gender differences have been reported in respect of chronic illnesseswith women at greater risk for hypertension and men cardiovascular diseases.36 Furthermore, in1991, cardiovascular diseases followed by diabetes mellitus and neoplasms were the diseases forwhich Jamaicans 65 years older were most often hospitalized.37 Data for the Caribbean showed that hypertension and arthritis are morbidities thatsignificantly affect both men and women.38 The current study revealed that hypertension was theleading cause of illness among older and oldest elderly in Jamaica, followed by diabetes andarthritis, which concurs somewhat with a past study39 that had hypertension as the leading cause 183

of morbidity of the elderly, followed by arthritis and diabetes mellitus. In another reported study,the most common chronic diseases identified among the elderly were hypertension, arthritis,diabetes, cardiovascular arrest, stroke and cancer.35 Some gender differences have been reportedin respect of chronic illnesses with women at greater risk for hypertension and mencardiovascular diseases.36 In a recent study by Bourne and colleagues, 1.4 percent more womenhad diabetes mellitus than men and this was the same for hypertensive older and oldest elderlyJamaicans. On the other hand, there were 1.6 times more old and oldest elderly Jamaican menwith self-reported arthritis than women.39 These chronic non-communicable diseases continue tointerface within the functional lives of the elderly, which means that they are indeed livinglonger but are faced with lower levels of good health than young adults (ages 15 to 29 years) andmiddle-aged adults (ages 30 to 59 years). According to the JSLC there has been significantincrease in illness/injury among older persons since 1997.40 Data from the 2002 survey indicatethat 34.6 percent of the elderly population surveyed, reported an illness or injury during the four-week reference period.41 Hypertension is one of the most important treatable causes of morbidity and mortalityand accounts for a large proportion of cardiovascular diseases in elderly in Jamaica.42 It is knownto be a major risk factor for the development of diabetic renal disease, and hyperglycaemia alsohas a role in the development of diabetic nephropathy.43 Studies from developed countries havereported prevalence of raised blood pressure among elderly to vary from 60% to 80%.44Furthermore, diabetes mellitus is one of the leading causes of morbidity and mortality amongpersons aged 65 and older.45 About 20% of persons in this age group are estimated to havediabetes, with another 25% in pre-diabetic stages.46 Moreover, because diabetes can beasymptomatic for many years, about 50% of older individuals with diabetes are thought to be 184

undiagnosed.47 In Jamaica, diabetes-related deaths in 1994 had increased 147% over the 1980level and represented the third leading cause of loss of years of potential life among women andtenth among men.48 There is evidence that this is due to the low rates of awareness, treatmentand control among patients with hypertension and diabetes.49,50 Rural populations generally experience excessive deficiencies in healthcare access, socialservices and other goods and services needed for healthy living. Furthermore, 23% of peoplefrom rural Jamaica who reported having a chronic medical condition were not actively engagedin seeking health care because of affordability issues, compared with 9.4% from urban areas.Urban residents consistently reported better health status than rural residents, and greatersatisfaction with their health care.51 There was a statistical correlation between good health statusand area of residence, or self-reported (chronic) recurring illness and age cohort. Furthermore,the data showed that elderly Jamaicans who dwelled in rural area had the lowest self-reportedgood health compared to those who resided in other towns and urban areas. Continuing, thosewho resided in urban residence reported the greatest good health status. In 1997, statistics fromPIOJ and STATIN52 revealed that 54.3 percent of elderly (ages 60 years and over) lived in ruralareas. A study by Bourne39 showed that approximately 7 out of every 10 old and oldest elderly inJamaica lived in rural areas, compared to 6 out of 10 for those 60 years and older of thepopulation. In addition, 20 out of every 100 Jamaicans were below the poverty line, compared to25 out of every 100 in rural Jamaica. Given that the elderly substantially lived in rural areas andthat poverty for this group was 10.2 percent,53 it is not surprising that the elderly in this area ofresidence had a lower level of good health status than the urban elderly in Jamaica. The wealthiest in the society are expected to experience better health due to theirknowledge of health risks and their access to the resources necessary to avoid such risks and treat 185

emerging health conditions.54 But with increasing wealth and development these has been anincrease in chronic disease as lifestyle changes have had a negative impact. The studies foundthat there were large gaps between the mean amounts of money spend by urban residentscompared with their rural counterparts. Furthermore, the elderly who are wealthy were morelikely to have diabetes mellitus while the poor and the middle class were more likely to reporthypertension. This suggests the consumption patterns of the wealthy contribute to ill-health.Thus whereas the poor become ill due to their inability to access their basic human rights, therich become ill as a result of their harmful consumption patterns. According to Sobal andStunkard,55 in developing societies there is a higher likelihood of obesity among men in highersocioeconomic strata. These men are at increased risk of developing type 2 diabetes mellitus56which is increasing in the adult population. Among the demographic correlates of health is thecost of medical care. It is established in health literature that medical care20 and cost of medicalcare21 are among the social determinants of health. In this study, rural residents significantlyspend more money on medical care compared to their urban counterparts. Furthermore, ruralresidents reported the largest amount of days of illness compared to their counterparts living inurban areas or other towns.ConclusionThe general epidemiological shift from infectious to chronic non-communicable diseases inJamaica puts the elderly at risk. Majority of the respondents in the sample had good or fairhealth, and those with poor health status were more likely to report having hypertension followedby diabetes mellitus and arthritis. Poor health status was more prevalent among those of lowereconomic status in rural areas who reported the greatest number of sick days of illness andmedical health care expenditure. The prevalence of chronic diseases and levels of disability in 186

older people can be reduced with appropriate health promotion and strategies to prevent non-communicable diseases. This research provides valuable information on health status and thenon-communicable diseases which affect the elderly in Jamaica. These findings can assist healthcare professionals to specifically and adequately address the health needs of the elderly inJamaica. 187

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Table 7.1: Socio-demographic characteristics of sampleVariable Frequency PercentSex Men 110 38.3 Women 177 61.7Diagnosed chronic medical condition Diabetes mellitus 73 25.4 Hypertension 124 43.2 Arthritis 38 13.2 Other (unspecified) 52 18.2Health care-seeking behavior Sought care 201 70.8 Did not seek care 83 29.2Why didn’t you seek care Could not afford it 14 17.7 Was not ill enough 29 36.7 Preferred home remedies 11 13.9 Didn’t have time to go 6 7.6 Unspecified 19 24.1Purchased medication Prescribed medicine 198 72.0 Partial prescription 8 2.9 Prescribed/over the counter 6 2.2 Over counter 6 2.2 Prescribed, but did not buy 9 3.3 No 48 17.4Health insurance coverage Private 23 8.0 Public 72 25.2 No 191 66.8Health status Good 49 17.1 Fair 136 47.4 Poor 102 35.5Area of residence Urban 76 26.5 Other town 55 19.1 Rural 156 54.4Social class Poor 114 39.7 Middle 62 21.6 Wealthy 111 38.7Household head No 85 29.6 Yes 202 70.2 194

Table 7.2: Health status by self-reported dysfunction Self-reported Dysfunction Health status No Yes Total n (%) n (%) n (%) Good 0 (0.0) 49 (17.2) 49 (17.1) Fair 0 (0.0) 135 (47.4) 135 (47.2) Poor 1 (100.0) 101 (35.4) 102 (35.7) Total 1 285 286χ2 (df = 2) = 1.810, p = 0.404, n=286 195

Table 7.3: Health status by area of residence Area of residence Total Health status Urban Other town Rural Good 16 (21.1) 11 (20.0) 22 (14.1) 49 (17.1) Fair 42 (55.3) 29 (52.7) 65 (41.7) 136 (47.4) Poor 18 (23.7) 15 (27.3) 69 (44.2) 102 (35.5) Total 76 55 156 287χ2 (df = 4) = 11.569, p = 0.021, n=287 196

Table 7.4: Diagnosed chronic medical condition by area of residence Area of residence Total Diagnosed chronic medical condition Urban Other town RuralDiabetes mellitus 25 (32.9) 17 (30.9) 31 (19.9) 73 (25.4) 25 (32.9) 22 (40.0) 77 (49.4) 124 (43.2)Hypertension 9 (11.8) 5 (9.1) 24 (15.4) 38 (13.2)Arthritis 17 (22.4) 11 (20.0) 24 (15.4) 52 (18.1)Other (unspecified)Total 76 55 156 287χ2 (df = 6) = 10.455, p = 0.107, n=287 197

Table 7.5: Self-reported chronic medical condition by social class Social Class Self-reported chronic medical condition Middle Upper Poor class class Total Diabetes mellitus 21 (18.4) 11(17.7) 41 (36.9) 73 (25.4) Hypertension 55 (48.2) 32 (51.6) 37 (33.3) 124(43.2) Arthritis 19 (16.7) 8 (12.9) 11 (9.9) 38 (13.2) Other (unspecified) 19 (16.7) 11 (17.7) 22 (19.8) 52 (18.1) Total 114 62 111 287χ2 (df = 6) = 15.870, p = 0.014, n=287 198

Table 7.6: Annual consumption expenditure, length of illness, total medical expenditure, public medical expenditure,private medical expenditure by area of residence Area of Variable residence 95% Confidence N Mean Std. Deviation Interval †Annual consumption Urban 76 8711.95 6761.20 716695 - 10256.95 expenditure* Other Town 55 7388.90 5271.25 5963.88 - 8813.91 Rural 156 5445.09 4470.72 4738.01 - 6152.17 Total 287 6682.69 5485.63 6045.34 - 7320.03 ††Length of illness Urban 64 7.45 10.96 4.72 - 10.19 Other Town 53 97.98 216.44 38.32 - 157.64 Rural 143 90.55 206.90 56.35 - 124.76 Total 260 71.61 185.10 49.01 - 94.22 †††Number of visit to health care Urban 55 1.65 1.58 1.23 - 2.08 practitioner Other town 39 1.21 .61 1.01 - 1.40 Rural 101 1.42 .85 1.25 - 1.58 Total 195 1.44 1.08 1.29 - 1.59 ††††Medical expenditure* Urban 57 1481.58 1988.75 953.89 - 2009.27 Other town 39 1817.95 2377.57 1047.23 - 2588.67 Rural 103 1805.34 5154.02 798.04 - 2812.64 Total 199 1715.07 3988.73 1157.48 - 2272.67† F statistic [2,284] = 10.248, p < 0.001†† F statistic [2,257] = 5.031, p = 0.006††† F statistic [2,192] = 2.057, p = 0.131†††† F statistic [2,196] = 0.136, p = 0.001 199

Table 7.7: Logistic regression: Predictors of poor health status of those diagnosed with chronicmedical condition Odds Variable Std. Wald ratio Coefficient Error statistic 95.0% C.I. Middle class 0.647 0.527 1.507 1.909 0.680 - 5.360 Upper class 0.427 0.639 0.446 1.533 0.438 - 5.366 †Poor Man 0.765 0.386 3.937* 2.150 1.009 - 4.578 Urban areas -0.314 0.439 0.512 0.730 0.309 - 1.727 Other towns -0.449 0.466 0.931 0.638 0.256 - 1.589 †rural areas Dummy social assistance -0.112 0.461 0.059 0.894 0.362 - 2.207 Crowding 0.173 0.119 2.124 1.189 0.942 - 1.499 Age 0.033 0.022 2.182 1.033 0.989 - 1.079 Married 0.257 0.403 0.406 1.293 0.587 - 2.847 Divorced, separated or 0.629 0.461 1.858 1.875 0.759 - 4.628 widowed †Never married Non-food consumption 0.000 0.000 0.017 1.000 1.000 - 1.000 Food consumption 0.000 0.000 4.088* 1.000 1.000 - 1.000 Dummy health insurance 0.390 0.382 1.039 1.476 0.698 - 3.123 Constant -1.152 1.604 0.516 0.316 -χ (df = 13) = 20.249, p < 0.001; n = 285 2-2 Log likelihood = 238.17Nagelkerke R2 =0.115Hosmer and Lemeshow goodness of fit χ2=7.565, P = 0.477Overall correct classification = 83.5%Correct classification of cases of self-rated poor health status = 99.2%Correct classification of cases of self-rated good health status = 6.3%†Reference group*p < 0.05, **p < 0.01, ***p < 0.001 200

CHAPTER 8Child Health Disparities in an English-Speaking Caribbean nation:Using parents’ views from a national surveyPaul Andrew Bourne , Cynthia Grace Francis & Elaine EdwardsPrevious studies in the English-Speaking Caribbean, and in particular Jamaica, have used apiecemeal approach to the study of child health, and none emerged that has modelled goodhealth status while evaluating other areas of health. The current study seeks to evaluate thegeneral health of children from the perspective of their parents’ views in an English-SpeakingCaribbean nation as well as the typology of dysfunctions, health disparities, social determinantsof self-evaluated health of children, and provide policy formulators as well as health researcherswith pertinent information that can be used to formulate health intervention programmes andguide the focus of future research. A sample of 2,642 children (≤ 18 years) was used for thisanalysis. The data were taken from the 2002 Jamaica Survey of Living Conditions (JSLC).Stratified probability sample was used to collect the data. The JSLC used an administeredquestionnaire to detail recall information on particular activities from parents. Thequestionnaire was modelled from the World Bank’s Living Standards Measurement Study(LSMS) household survey. Multivariate models were used to establish statistical associationbetween good health status and social determinants, health seeking behaviour, and length ofillness. Eleven percent of the sample reported an illness in the last 4-weeks. Of those whoindicated an illness, 16.5% claimed that their illness were non-diagnosed by medicalpractitioners. Fifty-eight percent of those who indicated diagnosed illness had acute conditions(34.7% influenza, 4.5% diarrhoea and 19.2% respiratory diseases), 2% chronic diseases (i.e.diabetes mellitus) and 24.1% unspecified conditions. Six explanatory determinants were foundthat explain good health status: age (OR = 0.95, 95% CI = 0.90-1.00); health care-seekingbehaviour (OR = 0.29, 95% CI = 0.15-0.56); middle class (OR = 5.00, 95% CI = 1.75-14.28);length of illness (OR = 1.00, 95% CI = 1.00-1.00); medical expenditure (OR = 1.00-1.00) andarea of residence (urban – OR = 2.75, 95% CI = 1.36 – 5.57; peri-urban – OR = 3.37, 95% CI= 1.42 – 7.99). Although health indicators such as life expectancy, infant mortality, illnesses,and nutrition as well as socio-economic determinants such as poverty and education haveimproved exponentially in Jamaica as well as in the wider Latin America and the Caribbean,child health disparities still exist in Jamaica. The findings are far reaching, provide more 201

information than objective indices, and can be used to aid policy formulation and guide futureresearch.IntroductionIn 1946, the World Health Organisation1 (WHO) joined the discussion on health which resultedin a conceptual definition that expanded on the popular absence of diseases. The WHO theorizedthat health must incorporate social, economic and psychological variables and not merely theabsence of diseases. This was documented in the preamble to its Constitution1 in 1948. Engel2-6who was a physician later became involved in the discourse and added a conceptual model. Heopined that the treatment of mentally ill-patient must include the physical, social andpsychological conditions. He called this conceptual framework, a biopsychosocial model.Despite the efforts of WHO and Engel to broaden the biomedical model (ie diseases causingpathogens), scholars such as Bok7 argued that the WHO’s conceptual definition of health is toobroad and by extension elusive to operationally measure. He therefore cited that the difficultywith measuring the WHO’s conceptual definition of health is such that it should not be used byresearchers. Bok’s perspective did not include a suggestion to replace this but speaks to thedominance of traditional approach to the measurement of health. The traditional approaches suchas mortality, diagnosed illness and life expectancy have objectively measurable outcomes whichare among the rationales offered for justifications of their usages. Using mortality or morbidity to measure health is a narrow approach. This on the otherhand is on the opposite extreme of the health pendulum as health is more than not havingdysfunctions or death.8 Death is the outcome of some morbidities, accidents, injuries, suicide andother conditions. Those aforementioned issues omit the role that social determinants play on 202

people health. These social determinants include poverty, income, marital status, crime andviolence, culture, and much more.9-27 Poverty is empirically established as strongly correlatedwith poor health.25-27 It affects the quality of the physical environment, nutrition, choices,psychological state of the individual as well as socio-political choices. The deprivation whichresults from poverty may influence ones physical illness, but there are social issues surroundingpoverty that may not result in injuries or even diseases. We can argue within the reality ofcontemporary societies that all peoples have equal access to health and other material resources,which would result in the same health outcome. If we assume this position, it would be highlyflawed as the WHO28 opined that 80% of chronic illnesses were in low and middle incomecountries. This undoubtedly suggests that illness interfaces with poverty and other socio-economic challenges. Poverty does not only impact on illness, it causes pre-mature deaths, lowerquality of life, lower life and unhealthy life expectancy, low development and other social illssuch as crime, high pregnancy rates, and social degradation of the community. Using twodecades worth of data on Jamaica, Bourne29 found that there was a positive correlation betweenpoverty and unemployment; poverty and illness; and crime and unemployment as well as anegative correlation between poverty and not seeking medical care. Illness therefore is an outcome of a plethora of conditions which include biological,social, economic and psychological issues. Many studies in the English-Speaking Caribbean aswell as Cuba that have examined health status of children have substantially only examinedmortality, birth, morbidity and to a lesser extent nutrition.30-37 Those studies are once againhighlighting the strength of the biomedical model in contemporary Caribbean nations, and to alesser extent not recognize the value of the social determinants in health and health care. TheWHO and any other scholars have joined the discourse in the value of social determinants since 203

the 2000 and this has seen many publications on the matter.16-19,21 Although the WHO opinedthat health research and by extension health must include the social determinants,21subconsciously the dominance of the biomedical approach is so engrained in psyche that in 2009WHO published a document entitled ‘World Health Statistics’ and the social determinants wereomitted from the section on health indicators. The document examined mortality, morbidity,typologies of dysfunctions, burden of diseases, immunization, sanitation, healthy lifeexpectancies, health expenditure, health care-utilization and omitted critical social determinantssuch as poverty, marital status, education, and so on. Like WHO, Caribbean scholars are so focused on the objective health measures (such aslife expectancy, mortality and diagnosed morbidity) that their work lack policy inventionstrategy that include critical social determinants. Humans are multi-dimensional animals,suggesting that omitting social determinants are excluding critical tenets that can enhance policyformulation in improving health and guide political actions.18 In 2007, poverty rates in ruralJamaica was twice that of urban poverty39 and within the context of empirical findings the healthstatus of children in the former areas cannot be the same as those in the latter areas. Povertytherefore affects the choices, physical environment, nutrients intakes, health care utilization, andthe quality of life of parents as well as their children. Having identified the weaknesses of manyof the previous studies and the role of social determinant in health and health intervention, thecurrent study will fill this gap by examining child health from the perspective of socialdeterminants (including area of residence). In addition to the identified weakness of many studiesthat have examined health in children, the current study using Casas et al.’s40 work recognize thathealth disparity in Latin America and the Caribbean is accounting for some of the inequalities inhealth outcomes. Casas et al cited that the region demonstrated the greatest disparities in income 204

and other social determinants, indicating a justification for the disparity in infant mortalitybetween poor and developed countries.26 The aims of the present work are to evaluate the generalhealth of children from the perspective of their parents’ views in an English-Speaking Caribbeannation as well as the typology of dysfunctions, health disparities, social determinants of self-evaluated health of children, and provide policy formulators as well as health researchers withpertinent information that can be used to formulate health intervention programmes and guidethe focus of future research.Materials and MethodsThe Jamaica Survey of Living Conditions (JSLC) was commissioned by the Planning Institute ofJamaica (PIOJ) and the Statistical Institute of Jamaica (STATIN) in 1988.39 These twoorganizations are responsible for planning, data collection and policy guideline for Jamaica, andhave been conducting the JSLC annually since 1989.39 The JSLC is a administered questionnairewhere respondents are asked to recall detailed information on particular activities. Thequestionnaire was modelled from the World Bank’s Living Standards Measurement Study(LSMS) household survey.41 There are some modifications to the LSMS, as JSLC is morefocused on policy impacts. The questionnaire covers demographic variables, health,immunization of children 0–59 months, education, daily expenses, non-food consumptionexpenditure, housing conditions, inventory of durable goods and social assistance. Interviewersare trained to collect the data from household members. The survey is conducted between Apriland July annually. The current study extracted a sub-sample of 2,642 respondents 18 years andbelow from a larger nationally cross-sectional survey of 6,782 Jamaicans. This study used thedataset of the JSLC for 2007.42 205

MeasuresTable 8.1 shows the operational definitions of some of the explanatory variables used in thisstudy. An explanation of some of the variables in the model is provided here.Statistical analysisStatistical analyses were performed using the Statistical Packages for the Social Sciences v 16.0(SPSS Inc; Chicago, IL, USA) for Widows. Descriptive statistics such as mean, standarddeviation (SD), frequency and percentage were used to analyze the socio-demographiccharacteristics of the sample. Chi-square was used to examine the association between non-metric variables, and an Analysis of Variance (ANOVA) was used to test the equality of meansamong non-dichotomous categorical variables. Logistic regression examined the relationshipbetween the dichotomous binary dependent variable and some predisposed independent(explanatory) variables (dependent variable was 1 if reported good health status and 0 if poorhealth). A pvalue < 0.05 was selected to established statistical significance. The final model wasbased on those variables that were statistically significant (p < 0.05). Categorical variables werecoded using the ‘dummy coding’ scheme. The predictive power of the model was tested using the ‘omnibus test of model’ andHosmer and Lemeshow’s43 technique was used to examine the model’s goodness of fit. Thecorrelation matrix was examined in order to ascertain whether autocorrelation (or multi-collinearity) existed between variables. Cohen and Holliday44 stated that correlation can below/weak (0–0.39); moderate (0.4–0.69), or strong (0.7–1). This was used in the present study toexclude (or allow) a variable. Where collinearity existed (r > 0.7), variables were entered 206

independently into the model to determine those that should be retained during the final modelconstruction. The final decision on whether to retain was based on the variables’ contribution tothe predictive power of the model and its goodness of fit. Finally, forward stepwise technique inlogistic regression was used to identify variables as well as determine the magnitude (orcontribution) of each statistically significant variable, and the odds ratio (OR) for interpretingeach of the significant variable.ResultsDemographic CharacteristicThe current study had a sample of 2, 642 respondents (ages 0 to 18 years): 50.9% males and49.1% females. Forty-eight percentage of the sample was poor with 25% in the poorest 20%compared to 33% in the wealthy social hierarchies (including 14% in the wealthiest 20%). Fifty-two percent of the sample resided in rural areas compared to 28% in urban and 20% in peri-urban areas. Eleven percent of the sample reported an illness in the last 4-weeks. Of those whoindicated an illness, 16.5% claimed that their illness were non-diagnosed by medicalpractitioners. Self-reported diagnosed illness were 58.2% acute conditions (including 34.7%influenza, 4.5% diarrhoea and 19.2% respiratory diseases), 1% chronic (i.e. diabetes mellitus)and 24.1% unspecified conditions. Of the sample 11.1% answered the question “Have yousought medical care in the last 4-weeks? Of those who responded to the medical care-seekingquestion, 58.4% claimed yes. When the respondents were asked “Why did you not seek medicalcare?” 17.8% said that they could not afford it, 50.8% was not ill enough and 19.5% used homeremedy. Concurrently, 91.4% of the sample indicated at least good self-evaluated health status(including 45.1% excellent health status) with 0.2% claimed that their health status was verypoor. 207

There was a significant statistical difference between the mean age of respondents andself-reported diagnosed health conditions – F statistic = 8.4, P < 0.0001. The mean age of childbeing diagnosed with particular illness was 6.5 years (SD = 5.1; 95% CI = 5.5-7.1). The meanage of children with particular health conditions in sample was 4.8 years (SD = 4.5, influenza);3.5 years (SD = 2.7, diarrhoea); 7.4 years (SD = 4.4, respiratory disease); 12.3 years (SD = 5.9diabetes mellitus) and 8.4 years (SD = 5.9; other – unspecified conditions). Table 8.2 highlights particular social, economic and biological variables by area ofresidence. Three times more children in rural areas were from households in the poorest 20%compared to urban area. Rural children were 3.3 times more likely to experience illness over alonger period than urban children compared to 2 times more than peri-urban children. Theidentified cases of chronic condition (i.e. diabetes mellitus) were a rural matter (1.8%). Table 8.3 shows self-reported diagnosed health conditions by particular demographiccharacteristics. Rural children were highly likely to indicate most of the health conditionscompared to other children from other geographical zones. However, urban children were mostlikely to be diagnosed with respiratory diseases (35.7%) compared to peri-urban children withinfluenza (27.7%) and rural children with diarrhoea (92.3%). All the reported cases of diabetesmellitus were from rural zones (100.0%). Table 8.4 presents information between health care-seeking behaviour and particulardemographic variables. A child who received medical care in the last 4 weeks was 1.8 timesmore likely to have health insurance coverage and 3.9 times more likely to report poor healthstatus. No significant statistical association was found between health care-seeking behaviour 208

and social hierarchy (P = 0.866), health care-seeking behaviour and age (P = 0.503) and healthcare-seeking behaviour and sex of respondents (P = 0.356).Multivariate analysis Table 8.5 highlights the explanatory social determinants of good health status of childrenin Jamaica. Six explanatory determinants were found explain good health status: age (OR = 0.95,95% CI = 0.90-1.00); health care-seeking behaviour (OR = 0.29, 95% CI = 0.15-0.56); middleclass (OR = 5.00, 95% CI = 1.75-14.28); length of illness (OR = 1.00, 95% CI = 1.00-1.00);medical expenditure (OR = 1.00-1.00) and area of residence (urban – OR = 2.75, 95% CI = 1.36– 5.57; peri-urban – OR = 3.37, 95% CI = 1.42 – 7.99). The data were also a good fit for themodel – model chi-square = 46.4, P < 0.0001.DiscussionThe current study highlighted that 89 out of every 100 children in Jamaica did not have an illnessin 4-week period of a survey. Instead of using diseases to measure health, 91 out of every 100reported at least good health status (including 45 out of every 100 very good self-evaluatedhealth statuses). Using health conditions and mortality of children 0 – 18 years, the PanAmerican Organization (PAHO) concluded that most of Jamaica’s children were in goodhealth.45 This finding is concurred by the current study, but this does not provide a holisticunderstanding of the health disparities in child health in the nation. The current findings revealedthat 36 out of every 100 rural children were living in household in the poorest 20% compared to14 out of every 100 in peri-urban households and 11 out of every 100 in urban households. Doesthis account for any health disparity in child health in the country? Concurrently, the presentwork showed that the length of illness experienced by child in rural households was 3.4 times 209

more than for those in urban households and 1.9 times more than that for those in peri-urbanhouseholds. This health disparity that did not emerge in the PAHO’s findings or other studiesthat have examined infant mortality or maternal deaths and/or births. The child health disparitycontinues as the only cases of chronic illness (ie diabetes mellitus) were found in rural children.Another notable health disparity was found in health insurance coverage of children in particularhouseholds. The current research highlighted that 11 out of every 100 children in rural householdhad health coverage compared to 22 out of every 100 in urban households and 16 in every 100 inperi-urban dwellings. Health disparities were also observed between typology of illnesses andsocial hierarchy in which children are in. Comparing the poorest 20% and the wealthiest 20%,the findings revealed that none of the children in wealthiest 20% households had diabetesmellitus compared to 1.8% children in households with the poorest 20%. Interestingly it wasnoted that children in urban households were 2.8 times more likely to claim good health withreference to rural children and ratio was 3.4 times more for peri-urban children with reference torural children. Chronic illness in Jamaica is clearly not limited to adults as the current study found thatthose with diabetes mellitus were rural females. The mean ages of rural female children beingdiagnosed with diabetes mellitus was 12.3 years, suggesting that chronic conditions begin toearly in rural females. The number of cases in diabetes mellitus was spread equally among thepoorest 20%, poor and the wealthy (33.3% respectively). This denotes that Jamaican females willbe living longer with chronic illness, and this has implications for policy intervention, health careexpenditure, public health care utilization and gerontological care in the future. An issue which isembedded in the present study that begs for some clarification is the rationale why urban andboys did not indicate any cases of diabetes. 210

Morrison46 in an article entitled ‘Diabetes and hypertension: Twin Trouble’ establishedthat diabetes mellitus and hypertension have now become two problems for Jamaicans and thewider Caribbean. This situation was equally collaborated by Callender47 at the 6th InternationalDiabetes and Hypertension Conference. They opined that there was a positive associationbetween diabetic and hypertensive patients - 50% of individuals with diabetes had a history ofhypertension, suggesting that those who current had diabetes mellitus are highly likely todevelop hypertension in the future. Embedded here is the immediate need to commence publichealth campaign geared towards parents as well as children who currently have diabetes aboutthe likeliness of developing hypertension and how their lifestyle choices will become critical inlowering this probability. Another issue which emerged from the data is the correlation betweenhealth care-seeking behaviour and good health status. This work found that children who seekcare are 71% less likely to declare good health status. Since 1988 data published in the Jamaica Survey of Living Conditions39 has beenshowing that females seek more medical care than males. The current study provides us withsome understanding of role of socialization in this health disparity. This research revealed thatthere is no statistical association between health care-seeking behaviour and age of children aswell as health care-seeking behaviour and sex of children, suggesting that it is not earlysocialization that accounts for males’ unwillingness to utilize health care services. Hence, thisstudy rules out the role of parents in accounting for males’ actions (or inactions) on health care-seeking in Jamaica. This denotes that the peer group, school, and political agents are among thesocializing institutions responsible for males’ lower choice in medical care-seeking behaviourcompared to females. 211

One of the social determinants of health that is empirically established in health researchas influencing health is education.9-21 The current work concurs with the empirical findings aschildren from middle class households were 5 times more likely to experience good self-evaluated health status with reference to those in poor social hierarchies. It follows that healthdisparity this current as highlighted by this study denotes that education (or the lack of) isexplaining more of the health disparity experienced by children instead of money. Healthinequalities among children of particular households in Jamaica is embedded in the educationalachievement (or lack) of their parents. In Jamaica, the educated class is more likely to beteachers, doctors, nurses, public health practitioners and university graduants who are moreinformed about many issues including health options than the poorer social classes and this istranslated into better health choices. A study on twins in USA found that more years in schooling(i.e. education) was associated with healthier patterns of behaviour. It is this value thataccommodates for the higher health of the middle class over the poor and other socialhierarchies. The current study highlighted yet another health disparity which is difficult toexplain ‘Why the children in the wealthy-to-wealthiest social hierarchies do not have a bettergood self-evaluated health compared to those in the poor-to-poorest households. This work revealed that children in poor and wealthy social hierarchies experience thesame good health status. A part of the explanation for the comparable quality of life between thetwo aforementioned groups lies in the quality of public health care facilities and public health inthe country. With the government health care policy which has removed user fees from publichospitals for children less than 18 years, access to health care is equally opened to all socialclasses. Although access does not represents utilization, within the Jamaican context, childrenwho are taken to public health facilities are provided with a high level of care. Statistics from the 212

Planning Institute of Jamaica and the Statistical Institute of Jamaica showed that private healthcare is pro-wealthy and public pro-poor, suggesting that for the wealthy and children of thosesocial hierarchies to experience comparable self-evaluated health status, the quality of publichealth care is high in Jamaica. Another issue which holds some of the justifications is publichealth. It follows that in Jamaica, water supply, sewerage and food hygiene, and public educationare of a high quality. Even though there are substantial inequalities between the public health forthe wealthy compared to the poor, the physical environment, lower nutrition and diet are notsuch that they erode the quality of public health care and general public health and these arereducing some of the health outcome between the poor and the wealthy. Health therefore cannotbe bought as was forwarded by Smith & Kington15 it is supported by other social determinantssuch as education, choices made by parents and health care system in the nation which whencoalesce produce healthier people. Health care can be purchased, but this does not translate intobetter quality of life for those who are able to access those services. This is equally supportingthe perspectives of Casas et al.40 which forwarded that improvement in health in the LatinAmerica and the Caribbean do not correspond to the economic development levels or theeconomic resources within countries as well as possessed by individuals. Addressing health disparities in children cannot omit the inequality between the lengthsof time spent by children in rural households compared to children of other households. Thecurrent study revealed that there is no significant statistical relationship between self-reportedillness and area of residence, yet children within rural households were 3.4 times more likely toexperience longer time in illness compared to children of urban households and 1.9 times morethan those in peri-urban households. A part of the answer lies in the culture, operationaldefinition of health, choices on experiencing illness and health inequality among the parents 213

within the different geographic areas. One of every two child who was ill was not taken to see ahealth care practitioner because parents’ reported that they were not ill enough. This highlightsnot only the cultural biases which are embedded in many parents and by extension Jamaicansabout when one should visit medical practitioners. From this bias another is the number ofparents who prefer to use home remedy as a first option instead of taking the child immediatelyto the medical practitioner. For one in every 5 children, the parent used home remedy comparedto 9 in every 50 who claimed that affordability was the reasons for not taking the ill-child to amedical doctor. Education in Jamaica is a pro-urban and pro-peri-urban phenomenon making children inrural household more likely to have parents who are less educated compared to urban and peri-urban counterparts. With more than fifty percentages of the Jamaican children residing withparents of rural households, the benefits of education that include the decision to make healthierchoices because of information would be missing from those households. Many rural parents willbe taking decision on health care choices based on their socialization, which includes homeremedy and wait and see when a medical practitioner is needed by the ill-child. This delay ofrural parents to take their ill-children to medical practitioners initially offers an explanation forthem spending longer time with the illness as well as accounting for increased mortality amongthese children. The health inequality that exists in Jamaica on the health status of children can beexplained more so by the retardation of culture, low education and tradition than on income. Although government policy has resulted in the removal of health care user fees forchildren (0 – 18 years) in Jamaica, open access does not denote equality in access. Health careinstitutions in urban and peri-urban areas are in easy access to residents, with this not being thecase for rural residents, addressing cost of care is not putting care in the hand of all. The terrain 214

in rural Jamaica means that public health care choices are not easily accessed by some residentsand the distance is such that unless the conditions is severe many parents will prefer to treat thechild at home or use the traditional healer (i.e. untrained physician). It is this cultural belief thatretard many rural parents from purchasing health insurance coverage, and accounting for thehigh number of cases with diarrhoea. Hence, the association between poverty and ill-health isoperating through education. Poverty leads to increased lower levels of education, and educationreduces poor health status. Using statistics for 2007 on Jamaica, 71% of poverty was in rural areas49. Poverty is notonly a rural phenomenon in Jamaica, but it also denotes material deprivation, social exclusionnutritional deficiency, increases chronic diseases and premature mortality27, 50-53 Poverty meansthat the individual will be unable to afford particular necessities, and good physical milieu, andthese deprivations will be such that food becomes important and the not dietary requirements.The poor will eat (or eat sometimes), but their physical milieu will be low and survival becomesso pronounced that choice in food is never the case. The nutritional deficiency will affect theparents and moreso the foetus.54 According to Martin-Gronert and Ozanne54 fetal overgrowthcan transport glucose and other nutrients from the mother suffering from diabetes mellitus to theunborn child, and means that the fetal intra-uterine milieu will become susceptible to chronicdiseases for the child in later life. Money therefore offers choices in a particular physical environment, social arrangement,food selection and health demand that is not available to someone who does not have it.According to Smith and Kington15, money buys health. This perspective assumes that health is atransferrable product and clearly it is not, but money really open access to things. This isjustification for the lower health of those in the lower socioeconomic strata compared to those in 215

the upper income group. Van et al53 found that those with chronic health conditions were morelikely to be in the lower income group, and this is somewhat concurred by the current study.Clearly, poverty, low education, poor physical environment, nutritional deficiency, puberty andother sedentary and unhealthy lifestyle practices are justifying young rural female prevalence ofdiabetes mellitus54,55. Here the health disparity in health outcomes of children in particularsocioeconomic strata and area of residence are clearly explained by social determinants ofhealth16-19 and justify a rationale for lifestyle behaviour modifications that are needed to bringabout greater responsibility of parents and children in Jamaica. According to Marvicsin56, type I diabetes has been increasing in Western industrializedcountries over the past 2 decades, and that its occurrence appears during puberty (ages 10 to 12years). She stated that 1 in every 400 to 500 children and adolescents had type I diabetes inUnited States. The present study revealed that 9 to every 500 children and adolescents haddiabetes in Jamaica, indicating the extent of this chronic illness in an English-SpeakingCaribbean nation. Statistics from Jamaica revealed that diabetes mellitus was almost 2 timesmore for females than males49. Within the context of the aforementioned findings, it can beextrapolated from the information that the rationale for no male-child having diabetes areembedded in (1) this appears earlier for females, (2) puberty, (3) obesity, (4) insulin resistanceand (5) nutritional deficiency. The present findings highlight that females are more insulin resistant than males which isconcurring to research by Murphy et al.57 The early inception of females with diabetes are owingto the fact that females enter puberty before males58 and that they are more likely to beoverweight than boy59 which increases their risk of having diabetes. Within the general setting,there is a need for chronic diseases management in Jamaica so as to address the current and 216

future challenges, which is only reinforcing a call made by Swaby et al in 200160. Another potentissue which accounts of the wide health disparity in chronic illness between males and females isowing to what Choudhary et al61 termed under-nutrition of girls (ages 10 – 12 years). Thefindings of Choudhary et al’s work61 showed that 7 of every 10 adolescent females were underweight (BMI < 18.5), which adds another dimension to the lifestyle management that is neededfor parents, children, and in particular females, in order to rectify some of the future healthproblems which are accounting for lower health status of women compared to men in Jamaica.Khetarpal and Kochar62 also argued that diet and nutrition among rural women affect morbidityand clinical status of these women, which emphasize the importance of a normal balanced diet inhealth and wellbeing and not the mere consumption of food. They also concur with previousstudies which found an association between income, individual preference, belief, culturaltraditions, physical milieu and morbidity in rural women. These all add a further dimension tothe present study about the role of money, cultural sociophysical milieu in the infection ofdiseases and how these influence unhealthy (or healthy) lifestyle choices. The nutritionaldeficiency in rural women in Jamaica account for the prevalence of diabetes in females 10-12years as these individual become infected with this chronic condition on the premise that theyenter puberty before males, and that it is likely that rural males show later signs of infection after18 years. Khetarpal and Kochar62 provide insights into the prevalence of diabetes in ruralfemales, when they found that 6 out of every 10 rural women (ages 25-45 years) in a ruraldistrict in Yamunanagar (Haryana, India) were anemic owing to their low iron, B complexvitamins and vitamin C intake. This information provides an understanding of the presentnutritional deficiency of rural women and that this is accounted for by material and incomedeprivation, and how this transmitted to rural female children. 217

ConclusionsIn summary, although health indicators such as life expectancy, infant mortality, illnesses, andnutrition as well as socio-economic determinants such as poverty and education have improvedexponentially in the Jamaica as well as in the Wider Latin America and the Caribbean, childhealth disparities still exist within Jamaica. Among the findings that emerged which account forthese are: cultural biases, policy intervention, health care choices disparities and lack ofeducation. The very young age at which rural females were diagnosed with diabetes mellitusspeaks to unhealthy and sedentary lifestyle practices of their mothers during pregnancy, and howthis is affecting their female offspring. The findings are far reaching and can be used to aidpolicy formulation and guide future research. Clearly there is a need for rural Jamaicans tounderstand and ensure that they are having a balanced diet (with nuts, seeds, grains, vegetablesand fruits) as otherwise this will affect not only them, but their children. The challenge of thisbeing materialized will be linked to reduced material and income deprivations in rural Jamaica,coupled with a health-building understanding of what you eat, how it affects your health and howthis influences morbidity in later life and increase the risk of chronic diseases in children.Policy and Research RecommendationsIn the 1990s, in seeking to lower health inequalities in the Jamaica, government policies focusedon poor people. The policies have been able to reduce poverty, but health inequality and childhealth disparities are present in contemporary Jamaica. While poverty plays a role in theimmunology of an individual, the quality of the physical and social environments, loweredaccess to material resources and utilization of particular health care services, many of the health 218

inequalities which government policies should have addressed since the 1990s are still evident inchild health. The issues of fairness in the distribution of health care choices and utilization arenot resulting in removal of child health disparities in Jamaica. The findings which emerged fromthis work provide us with an understanding of some of the health disparities and clearly highlightthat policy focus needs an overhaul for the future. In order to reduce some of the child healthdisparities in contemporary Jamaica, policy intervention must tackle education, cultural biases onhealth, health care definitions, timing in seeking health care, focus on accessibility of ruralpeople to health care, and a direct intensive education campaign towards rural and indigenouspopulations on their perception of illness as well as utilizing medical practitioners as the firstoption. Another issue is an immediate and extensive health campaign on chronic disease. Thisprogramme must to geared toward how to identify early symptoms of chronic illness in children,where to seek care, how to live with chronic illness from in childhood onwards, preventative asagainst curative care, and an intervention progrmme for public health practitioners. Public healthpractitioners need to be sensitized on the earliest of children in particular rural female beingdiagnosed with chronic illnesses which would see medical practitioners testing children on theappearance of particular symptoms and not assume that they are too young. In order to reachrural residents, a new approach is needed that will be established geared towards medicalpractitioners. The new thrust must include taking medical practitioners to the residents such as inschools, churches, house visits, mobile clinics, and remove the emphasis of tackling health ofpoor people as this bottom up approach has not addressed the health inequalities. Consequently,research should begin focusing on premature mortality in rural children, medical practitioners’biases in working in rural areas, cultural and target rural residents in their communities in orderto understand their perception of health care and/or health care utilization as well as health 219

outcome after the new intervention is implemented in rural areas. Another way forward forresearchers is to commence studying health disadvantage, health gaps and health gradients inJamaica with a policy implementation approach. 220

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Table 8.1: Operational definitions of particular variablesVariable Operational definition CodingSelf-evaluated Parents’ evaluation of their 1= moderate-to-very good health status, 0 =health status (or children’s health status. otherwisehealth status) This is taken from the question “In general, would you say your health is excellent, good, moderate, poor or very poor?”Age group Age group is classified into 1 = children ages < 5 years old 4 categories. 2 = children ages 5 – 9 years old 3 = adolescents ages 10 – 14 years old 4 = adolescents ages 15 – 18 years oldCrowding Number of people who live Total number of people in household divided by in a room total number of room excluding kitchen, bathroom and verandahSocial hierarchy Income quintiles were used Low = poorest 20% to poor; middle = middle to measure social class, and quintile and upper = wealthy to wealthiest 20% these range from quintile 1 (poorest 20%) to 5 (wealthiest 20%)Durable good Items owned by household Summation of durable goods members excluding property (or land)Health care- Visits to pharmacies, 1=Visits to health care professionals,seeking medical practitioners, 0=otherwisebehaviour nurses,(health seekingbehaviour)Income Income is measured by consumptionSelf-reported Have you had any illnessillness or injury during the past four weeks? For example, have you had a cold, diarrhoea, asthma, diabetes, hypertension, arthritis or other? 225

Table 8.2: Demographic characteristic of sample, n = 2, 642 Area of residenceVariable Urban Peri-Urban Rural P (%) (%) (%)Age group 0.112 Children < 5 years old 24.3 23.5 22.6 Children 5 – 9 years old 25.2 27.0 28.7 Adolescents: 10 – 14 years old 26.9 29.3 30.0 Adolescents: 15 – 18 years old 23.6 20.2 18.7Health Seeking-behaviour 0.224 No 66.7 57.7 54.8 Yes 33.3 42.3 45.2Health insurance coverage <0.0001 No 77.8 83.6 88.9 Yes 22.2 16.4 11.1Self-reported illness 0.315 None 10.4 10.0 12.1 Yes 89.6 90.0 87.9Self-reported diagnosed health conditions 0.002 Acute Influenza 22.7 53.8 34.1 Diarrhoea 0.0 1.9 7.3 Respiratory diseases 26.7 15.4 17.1 Chronic Diabetes mellitus 0.0 0.0 1.8 Other 25.3 15.4 26.2Self-evaluated health status <0.0001 Very good 42.3 47.1 45.7 Good 46.8 49.6 44.7 Moderate 9.4 2.9 6.7 Poor 1.4 0.4 2.5 Very poor 0.0 0.0 0.4Sex 0.684 Male 49.1 50.7 51.1 Female 50.9 49.3 48.9Social hierarchy <0.0001 Poorest 20% 11.1 13.7 36.4 Poor 14.5 23.1 27.0 Middle 21.0 22.5 18.2 Wealthy 26.6 23.6 12.7 Wealthiest 20% 26.9 17.1 5.6Length of illness mean (SD) 7.7 (8.1) 13.6 (51.0) 25.8 (125) 0.045 226

Table 8.3: Self-reported health conditions by particular social variables Health conditions Acute conditions Chronic OtherVariable Influenza Diarrhoea Respiratory Diabetes P mellitus % % % % %Sex 0.112 Male 46.5 30.8 50.0 0.0 44.3 Female 53.5 69.2 50.0 100.0 55.7Social hierarchy 0.352 Poorest 20% 19.8 15.4 21.4 33.3 28.6 Poor 21.8 53.8 19.6 33.3 20.0 Middle class 27.7 23.1 21.4 0.0 17.1 Wealthy 17.8 7.7 14.3 33.4 17.1 Wealthiest 20% 12.9 0.0 23.2 0.0 17.1Age group <0.0001 Children: ages less than 5 years 59.4 69.2 30.4 0.0 31.4 Children: 5 – 9 years 18.8 30.8 41.1 0.0 22.9 Adolescents: 10 – 14 years 17.8 0.0 19.6 100.0 22.9 Adolescents: 15 – 18 years 4.0 0.0 8.9 0.0 22.9Health care-seeking behaviour 0.002 Yes 41.0 53.8 64.3 66.7 65.7 No 59.0 46.2 35.7 33.3 34.3Area of residence 0.004 Urban 16.8 0.0 35.7 0.0 27.1 Peri-urban 27.7 7.7 14.3 0.0 11.4 Rural 55.4 92.3 50.0 100.0 61.4Number of visits to health care practitioner 1.2 (0.4) 1.1 (0.4) 1.4 (1.0) 1.0 (0.0) 1.3 (0.5) 0.393Mean (SD) 227

Table 8.4: Health care-seeking behaviour by particular social variables Health care-seekingVariable Yes No P % %Age group 0.503 Children < 5 years old 44.4 39.3 Children 5 – 9 years old 28.1 25.4 Adolescents: 10 – 14 years old 17.0 23.8 Adolescents: 15 – 18 years old 10.5 11.5Health insurance coverage 0.027 No 76.6 86.9 Yes 23.4 13.1Self-reported illness 0.138 None 3.5 0.8 Yes 96.5 99.2Health conditions 0.012 Acute Influenza 31.1 53.6 Diarrhoea 5.3 5.5 Respiratory diseases 27.3 18.2 Chronic Diabetes mellitus 1.5 0.9 Other (unspecified) 34.8 21.8Self-evaluated health status 0.006 Very good 18.2 32.2 Good 45.3 45.5 Moderate 22.9 19.0 Poor 12.9 3.3 Very poor 0.6 0.0Sex 0.866 Male 48.5 47.5 Female 51.5 52.5Social hierarchy 0.356 Poorest 20% 18.1 24.6 Poor 19.9 23.8 Middle 22.8 23.0 Wealthy 20.5 16.4 Wealthiest 20% 18.7 12.3 228

Table 8.5: Logistic regression: Explanatory social determinants of good health status of children Odds R2 Explanatory variable Std. Error P ratio 95% C.I. Age 0.027 0.034 0.95 0.90-1.00 0.019 Health care-seeking behaviour 0.331 0.000 0.29 0.15-0.56 0.032 Middle class 0.040 0.535 0.003 5.00 1.75-14.28†Poor classes 1.00 Length of illness 0.001 0.046 1.00 0.99-1.00 0.020 Medical expenditure 0.000 0.044 1.00 1.00-1.00 0.026 Urban area 0.361 0.005 2.75 1.36-5.57 0.035 Peri-urban area 0.440 0.006 3.37 1.42-7.99 0.024†Rural area 1.00Hosmer and Lemeshow goodness of fit χ2 = 6.8 (8), P = 0.6-2LL = 305.3Nagelkerke R2 =0.196†Reference group 229

CHAPTER 9Health Status of Patients with self-reported Chronic Diseases inJamaicaPaul A. Bourne & Donovan A. McGrowderTo examine the physical health status of Jamaicans in rural, peri-urban and urban areas ofresidence. A model was used to determine the significant predictors of poor health status ofJamaicans who reported being diagnosed with a chronic non-communicable disease. Thecurrent study extracted a sub-sample of 714 people from a larger nationally representativecross-sectional survey of 6,783 Jamaicans. A self-administered questionnaire was used to collectthe data from the sample. Descriptive statistics were used to examine the demographiccharacteristics of the sample; chi-square was used to investigate non-metric variables, andlogistic regression was the multivariate technique chosen to determine predictors of poor healthstatus. Approximately one-quarter (25.3%) of the sample reported that they had poor healthstatus. Thirty-three percent of the sample indicated unspecified chronic diseases; 7.8% arthritis,28.9% hypertension, 17.2% diabetes mellitus and 13.3% asthma. Asthma affected 47.2% ofchildren and 23.2% of young adults. Significant predictors of poor health status of Jamaicanswho reported being diagnosed with chronic diseases were age of respondents, area of residenceand inability to work. Majority of the respondents in the sample had good health, and adultswith poor health status were more likely to report having hypertension followed by diabetesmellitus and arthritis, while asthma was the most prevalent among children. Improvement inchronic disease control and health status can be achieved with improved patient education onthe importance of compliance, access to more effective medication and development of supportgroups among chronic disease patients.IntroductionThe rapidly increasing burden of chronic diseases is a key determinant of global public health. In2001, chronic diseases contributed approximately 60% of the 56.5 million total reported deaths 230

in the world and approximately 46% of the global burden of disease (1). The proportion of theburden of non-communicable diseases is expected to increase to 57% by 2020. Furthermore,there is increasing evidence that chronic disease risks begin in fetal life and continue into old age(2). Adult chronic disease, therefore, reflects cumulative differential lifetime exposures todamaging physical and social environments. Almost half of the total chronic disease deaths areattributable to cardiovascular diseases; obesity and diabetes are also showing worrying trends,not only because they already affect a large proportion of the population, but also because theyhave started to appear earlier in life (2). The chronic disease problem is far from being limited to the developed regions of theworld. Contrary to widely held beliefs, developing countries are increasingly suffering from highlevels of public health problems related to chronic diseases. In five out of the six regions of theWorld Health Organization (WHO), deaths caused by chronic diseases dominate the mortalitystatistics (3) and there is evidence that 79% of deaths attributable to chronic diseases areoccurring in developing countries such as those in the Caribbean predominantly in middle-agedmen (3). Most Caribbean countries have experienced a health transition, with decreases infertility and mortality rates and changing disease patterns. Leading up to the mid 1990s, themortality pattern changed from deaths being mainly due to communicable diseases to them beingmainly due to non-communicable diseases (4, 5). More recently, these countries have also beenobserving the re-emergence of ‘old’ communicable diseases and the emergence of newcommunicable diseases, together with an increasing prominence of non-communicable diseases.A study conducted in 10 Caribbean countries during 1975-1979, observed that the leading causesof death were similar to those found in industrialized countries (6). Additionally, with 15-20%and 20-25% of the adult population in English and Dutch-speaking Caribbean countries having 231

diabetes and hypertension, respectively, these non-communicable diseases accounting for thesingle largest expenditure in national drug budgets (7). Morbidity and mortality patterns in recentdecades in Caribbean countries such as Jamaica are largely explained by individual lifestylechoices and social, cultural and economic determinants that affect these choices (8). Jamaica is the third largest island in the Caribbean, comprising of approximately 4,400sq. miles or 10,991 square kilometers in area. Jamaica has a population of approximately 2.6million and has undergone a significant demographic transition in the last 5 decades (9, 10).Some features of this transition include the increase in the median age of the population from 17years to 25 years between 1970 and 2000, the doubling of the proportion of persons older than 60years old to over 10% and the increase in life expectancy at birth from less than 50 years in 1950to greater than 70 years in 2000 (11). As a result, the main causes of illness and death in Jamaicaand many other Caribbean islands and regions at a similar state of development are the chronicnon-communicable diseases (12). There is an increased prevalence of diet-related chronic non-communicable diseases, such as cardio-vascular diseases, diabetes and obesity. Wilks, et al. (13)reporting on a survey of body mass index in an urban population, found that 30.7% of the menwere overweight (7.2% were obese) and 64.7% of the women were overweight (31.5% obese). Inthis same study if was found that hypertension had a prevalence of 19.1% among the males and28.2% among the females; while the prevalence of diabetes was 8.9% and 15.3% among themales and females respectively (13). In a later study Wilks et al. found that the prevalence ofType 2 diabetes mellitus was 9.8% among men, 15.7% among women and 13.4% overall (14).Cooper et al. (15) found a prevalence of 17.1% for hypertension and 8.1% for non-insulindependent diabetes among the Jamaican population. There are indications that mortality andmorbidity due to chronic diseases are increasing, especially among persons over 45 years of age. 232

Chronic diseases such as heart disease, cancer and diabetes negatively affect the generalhealth status and quality of life of individuals (16) and there is the absence in the literature ofstudies looking at the health status of persons in the Caribbean with chronic non-communicablediseases. It is against this background that this study was undertaken. This study was, thereforedesigned to explore any association between chronic non-communicable disease and healthstatus. The aim of the study was to examine the self-reported health status of Jamaicans in rural,peri-urban and urban areas of residence. A model is used to predict the social determinants ofpoor health status of Jamaicans who reported at least one chronic non-communicable disease.MethodThe current study extracted a subsample of 714 people who answered the question of havingsought medical care in the last 4-weeks from a larger nationally representative cross-sectionalsurvey of 6,783 Jamaicans (Jamaica Survey of Living Conditions, 2007) (17). The survey wasdrawn using stratified random sampling. This design was a two-stage stratified random samplingdesign where there was a Primary Sampling Unit (PSU) and a selection of dwellings from theprimary units. The PSU is an Enumeration District (ED), which constitutes a minimum of 100residence in rural areas and 150 in urban areas. An ED is an independent geographic unit thatshares a common boundary. This means that the country was grouped into strata of equal sizebased on dwellings (EDs). Based on the PSUs, a listing of all the dwellings was made, and thisbecame the sampling frame from which a Master Sample of dwelling was compiled, which inturn provided the sampling frame for the labour force. One third of the 2007 Labour ForceSurvey (ie LFS) was selected for the survey (17). The sample was weighted to reflect thepopulation of the nation. 233

This study used JSLC 2007 (17) which was conducted by the Statistical Institute ofJamaica (STATIN) and the Planning Institute of Jamaica (PIOJ) between May and August 2007.The researchers chose this survey based on the fact that it is the latest survey on the nationalpopulation and that that it has data on self-reported health status of Jamaicans. A self-administered questionnaire was used to collect the data, which were stored and analyzed usingSPSS for Windows 16.0 (SPSS Inc; Chicago, IL, USA). The questionnaire was modelled fromthe World Bank’s Living Standards Measurement Study (LSMS) household survey. There aresome modifications to the LSMS, as JSLC is more focused on policy impacts. The questionnairecovered areas such as socio-demographic, economic and health variables. The non-response ratefor the survey was 26.2%. Descriptive statistics such as mean, standard deviation (SD), frequency and percentagewere used to analyze the socio-demographic characteristics of the sample. Chi-square was usedto examine the association between non-metric variables, and an Analysis of Variance(ANOVA) was used to test the relationships between metric and non-dichotomous categoricalvariables. Logistic regression examined the relationship between the dependent variable andsome predisposed independent (explanatory) variables, because the dependent variable was abinary one (self-reported health status: 1 if reported poor health status and 0 if otherwise). The results were presented using unstandardized B-coefficients, Wald statistics, Oddsratio and confidence interval (95% CI). The predictive power of the model was tested using theOmnibus Test of Model and Hosmer & Lemeshow (18) was used to examine goodness of fit ofthe model. The correlation matrix was examined in order to ascertain whether autocorrelation (ormulticollinearity) existed between variables. Based on Cohen & Holliday (19) correlation can below (weak) - from 0 to 0.39; moderate - 0.4-0.69, and strong - 0.7-1.0. This was used to exclude 234

(or allow) a variable in the model. Wald statistics were used to determine the magnitude (orcontribution) of each statistically significant variable in comparison with the others, and theOdds Ratio (OR) for the interpreting of each significant variable. Multivariate regression framework (20) was utilized to assess the relative importance ofvarious demographic, socio-economic characteristics, physical environment and psychologicalcharacteristics, in determining the reported health status of Jamaicans; and this has also beenemployed outside of Jamaica (21, 22). This approach allowed for the analysis of a number ofvariables simultaneously. Secondly, the dependent variable is a binary dichotomous one and thisstatistic technique has been utilized in the past to do similar studies. Having identified thedeterminants of health status from previous studies, using logistic regression techniques, finalmodels were built for Jamaicans as well as for each of the geographical sub-regions (rural, peri-urban and urban areas of residence) and sex of respondents using only those predictors thatindependently predict the outcome. A p-value of 0.05 was used to for all tests of significance.ModelThe use of multivariate analysis in the study of health and subjective wellbeing (i.e. self-reportedhealth or happiness) is well established (23) and this is equally the case in Jamaica and Barbados(24, 25). The use of this approach is better than bivariate analyses as many variables can betested simultaneously for their impact (if any) on a dependent variable. The current study willexamine the social determinants of self-reported health status of Jamaicans (Equation 1).Equation 1 was again tested and decomposed by (i) sex of respondents and (ii) area of residentsin order to ascertain those social predictors of each sub-group.H t =f(A i , G i ,HH i , AR i , I t , J i, lnC, lnD i , ED i, MR i , S i , HIi , lnY, CR i , MC t , SA i , Ti , ε i ) [1] 235

where H t (ie self-rated current health status in time t) is a function of age of respondents, A i ; sexof individual i, G i ; household head of individual i, HH i ; area of residence, AR i ; current self-reported illness of individual i, It ; injuries received in the last 4 weeks by individual i, J i ; loggedconsumption per person per household member, lnC; logged duration of time that individual iwas unable to carry out normal activities, lnD i ; education level of individual i, ED i ; maritalstatus of person i, MR i ; social class of person i, S i ; health insurance coverage of person i, HIi ;logged income, lnY; crowding of individual i, CR i ; medical expenditure of individual i in timeperiod t, MC t ; social assistance of individual i, SA i ; length of time living in current household byindividual i, Ti ; and an error term (ie. residual error).The final models that were derived from the general Equation [1] that can be used to predicthealth status of Jamaicans (Equation [2]); men (Equation [3]); women (Equation [4]); urban area(Equation [5]); other towns (Equation [6]); and rural areas (Equation [7]).H t = f(A i , AR i , lnDUt , ε i ) [2]MeasureAge is a continuous variable which is the number of years alive since birth (using last birthday).Age group is a non-binary measure: children (ages less than 15 years); young adults (ages 15 to30 years); other-aged adults (ages 31 to 59 years); young elderly (ages 60 to 74 years); oldelderly (ages 75 to 84 years) and oldest elderly (ages 85 years and older).Self-reported illness (or self-reported dysfunction): The question was asked: “Is this a diagnosedrecurring illness?” The answering options are: Yes, Cold; Yes, Diarrhoea; Yes, Asthma; Yes,Diabetes; Yes, Hypertension; Yes, Arthritis; Yes, Other; and No. A binary variable was latercreated from this construct (1 = yes, 0 = otherwise) in order to use in the logistic regression. 236

Self-reported health status: “How is your health in general?” And the options were very good;good; fair; poor and very poor. For this study the construct was categorized into 3 groups – (i)good; (ii) fair, and (iii) poor. A binary variable was later created from this variable (1 = good andfair 0 = otherwise).Social class: This variable was measured based on income quintile: The upper classes were thosein the wealthy quintiles (quintiles 4 and 5); middle class was quintile 3 and poor those in lowerquintiles (quintiles 1 and 2).ResultsDemographic characteristics of sampleThe sample constituted 714 respondents (36.7% men and 63.3% women), with a mean age of49.15 years. Majority of the sample was never married (44.7%), 13.4% widowed, 1.7%separated, 3.1% divorced and 37.1% married. Some 25.3% of the sample reported that they hadpoor health status, 31.9% indicated at least good and 42.8% indicated fair. Thirty-three percentof the sample indicated unspecified chronic illness; 7.8% arthritis, 28.9% hypertension, 17.2%diabetes mellitus and 13.3% asthma. Marginally more of the sample was in the upper class(41.6%), 19.7% in the middle class and 38.7% in the lower class (i.e. poor). Majority of therespondents were elderly (ages 60 years and older - 41.6%) compared to 33.6% other-agedadults, 9.7% young adults and 15.1% children. Interestingly, the mean number of person perroom was 4.07 (S.D. 2.63 persons) and in rural areas it was 4.38 (S.D. 2.75 persons) compared to3.9 persons in other towns (S.D. 2.41) and 3.6 persons in urban areas (S.D. 2.42) - F statistic [2,711] = 6.642, p = 0.001. 237

Table 9.1 revealed that there is a statistical correlation between social class, self-evaluated health status, annual income and area of residence (p < 0.001). Just over 50% of therural residents were in the lower class (i.e. poor) compared to 26.4% of other town residents and18.0% of urban dwellers. With regards to self-evaluated health and area of residence, most of theresidents reported fair health status: urban residents (46.5%); other town residents (50.8%) andrural residents (38.4%). On the other hand, 28.6% of rural residents indicated that they had goodself-evaluated health status compared to 31.7% of other town residents and 38.5% of urbandwellers. The mean annual income of rural residents was US$5,873.08 compared toUS$8,218.05 for other town residents and US$10,312.41 for urban residents. Most of the ruralrespondents were in the lower class (52.9%), while 26.4% of the other town residents in thelower class and 18% of the urban dwellers in the lower class. Table 9.2 revealed that there is a statistical correlation between diagnosed chronicdiseases and age group [χ2 (df = 20) = 297.701, p < 0.001, n = 714]. Asthma was primarily anillness for the younger ages and more so affecting children: 47.2% of children and 23.2% ofyoung adults (Table 9.2). The findings revealed as an individual ages, he/she was more likely toreport being diagnosed with hypertension: 0% of children; 8.7% of young adults; 31.7% of otheraged-adults; 35.7% of young old; 50.5% of old-elderly and 48.3% of oldest-elderly. Arthritis wasmore likely to affect older ages than young ages: 0% of children; 1.4% of young adults; 7.1% ofother aged-adults; 12.9% of young-old; 14.4% of old-elderly and 6.9% of oldest-elderly. On theother hand, as an individual age, he/she is more to be aware of the typology of chronic illnessthat he/she has than at young ages (i.e. ages less than 31 years). Interestingly, 2.8% of childrenhad diabetes compared to 4.3% of young adults; 18.3% of other aged-adults; 28.7% of youngold; 19.6% of old-elderly and 17.2% of oldest-elderly. 238

Based on Table 9.3, no statistical correlation was found between diagnosed chronicdisease and social class [χ2 (df = 8) = 13.882, p = 0.085, n = 714]. On the other hand, a statisticalrelationship was found between income, consumption, crowding and chronic disease (p < 0.5;Table 9.4). Furthermore, there is a similarity across the afore-mentioned variable as asthma wasfound to be associated with the most income, consumption and persons per room; andunspecified chronic disease was the second leading reported dysfunction. Diabetes mellitus wasfound to be the third leading reported chronic disease influencing people with more income andconsumption. While hypertension was the third most reporting chronic disease associated withcrowding, it was the fourth most reported dysfunction associated with income and consumptionexpenditure.Multivariate analysesUsing logistic regression analyses, of the 17 variables that were tested for this study, only 3emerged as statistically significant predictors of poor health status of Jamaicans who reportedbeing diagnosed with chronic diseases (Table 9.5): age of respondents (OR = 1.029, 95% CI =1.018 - 1. 040), area of residence (urban areas - OR = 0.352, 95% CI = 0.191 - 0.652; othertowns - OR = 0.352, 95% CI = 0.173 - 0.744) and log duration unable to work (OR = 1.711, 95%CI = 1.280 - 2.271). The model (Equation 2) had statistically significant predictive power [χ2 (4) =59.76.149,p < 0.001; Hosmer and Lemeshow goodness of fit χ2 = 9.956, p = 0.268] and correctly classified74.4% of the sample (correctly classified 92.6% of those who were in poor health and 31.6% ofthose who were not in poor health). The logistic regression model can be written as: Log(probability of poor health status/probability of not reporting poor health status) = -0.704 + 0.028 239

(age) -1.041(urban residents) -1.041 (other towns) + 0.537 (log duration unable to work).Furthermore, the predictors accounted for 24% of the variability in poor health status (Table 9.5).DiscussionHealth is influenced by numerous other factors, particularly lifestyle, the amount of exercise andnutrition. Chronic diseases strongly relate to behavioural risk factors such as smoking, physicalinactivity and unhealthy dietary patterns that tend to precede and exacerbate their traditional riskfactors, such as raised blood pressure, cholesterol and blood glucose levels. There is anassociation between chronic disease and health status and the former has a significant negativeimpact on the physical aspects of health (26). Self-reported health status has been widely used incensuses, surveys, and observational studies and there is evidence suggesting that self-reportedhealth is an indicator of general health with good construct validity (27) and is a respectablypowerful predictor of mortality risks (28), disability (29) and morbidity (30). The results of thisstudy showed that the majority of those sampled reported to be experiencing at least good or fairhealth, while approximately one-quarter indicated poor health. These results concur with thoseby other researchers from Dominica (31) and Trinidad (32). The current study revealed that hypertension was the most common chronic diseaseamong the respondents, followed by diabetes mellitus and arthritis. Hypertension was highestamong the elderly, with just than one-half of the old-elderly and oldest-elderly beinghypertensive. In a study by Sargeant et al. (33), hypertension is more common among womenand the elderly in Jamaica. Studies from developed countries have reported prevalence of raisedblood pressure among elderly to vary from 60% to 80% (34). Hypertension is one of the mostimportant treatable causes of morbidity and mortality and accounts for a large proportion ofcardiovascular diseases in elderly in Jamaica (33). The age and sex adjusted prevalence in 240

Jamaica is 24% (15) with somewhat higher levels in women than in men. The Jamaican HealthyLifestyle Survey Report 2000 (35) noted a prevalence of hypertension of 19.9% among malesand 21.7% among females; prevalence increased with age in both rural and urban populationsand in both sexes. Among persons known to be hypertensive, 42% were on treatment, and of thisgroup, 37.7% had been able to lower and maintain their blood pressure at 140/90 or less. In theCaribbean and the USA, the higher prevalence of hypertension was associated with an increasedprevalence of obesity, especially in women, and with greater intake of dietary sodium (36, 37). Diabetes mellitus is an important cause of morbidity and mortality in Jamaica andrepresents a significant burden on health services. Diabetes was the second leading cause ofchronic disease in this study and was most prevalent among the young old with just under one-third reporting that they have diabetes mellitus. The prevalence of diabetes mellitus is high inJamaica and the Caribbean and many patients have poor metabolic control (38). In Jamaica theprevalence of diabetes among persons 25–74 years old is estimated to be 12% to 16% (14, 39-40), but of which a third is unrecognized (39-40). There is also evidence that the diabetesprevalence has increased (41). In the Jamaican Healthy Lifestyle Survey Report 2000 (35),diabetes mellitus was found in 6.3% of males and 8.2% of females and there was a sharpincrease with age. Awareness of diabetes mellitus among those classified as diabetic by thesurvey was 76.3%. Almost one-third of those classified as diabetic were not being treated, and60% of those who reported being on medication did not have their condition controlled. Theaverage length of stay was 8.3 days for diabetes mellitus in 2002, compared to 6.3 days for allconditions (35). Diabetes mellitus accounts for about 10% of mortality in Jamaica (42) and isranked fourth as the principal cause of death among Jamaicans during the period 1990 to 1994(43). But the impact of diabetes mellitus on mortality is under-reported since the disease may 241

contribute to mortality from such other conditions as cerebrovascular accidents and myocardialinfarctions (44). Furthermore, there is evidence that the high prevalence of diabetes in Jamaica isdue to the low rates of awareness, treatment and control among patients with diabetes mellitus(38). Since having a chronic disease exacerbates individuals’ risk for other long-term diseases,the diseases tend to occur in multiples. For example, diabetes patients are at two to four timesgreater risk of heart disease than non-diabetics (45) which adversely affect the physical healthstatus of these patients. In the Caribbean, there has been growing concern at the apparent increase in asthma inchildren and young adults. In 2001, hospital morbidity patterns and primary care data indicatedthat respiratory illnesses dominated the list of childhood infirmities among children 0-14 years.For children aged 0-4 years, asthma was the major condition for which patients were seen inhealth facilities, a condition mainly attributable to the high incidence of tobacco smoke to whichthese children are exposed (46). In this study, asthma was the predominant chronic diseasesaffecting approximately one-half of the children and almost one quarter of young adults. Asthmais an important public health issue in Jamaica. Exercise-induced asthma has been reported tooccur in 20 per cent of school age children (47). In government hospitals in Jamaica, five percent of clinic visits are asthma related and 25 per cent of respiratory admissions to hospital aredue to asthma (48). Barnes and colleagues (49) studied asthmatic children in Barbados wheretreatment was associated with use of inhalers, but no distinction between bronchodilators andcorticosteroids was made (50). Asthma is a significant cause of mortality in Jamaica, resulting ina death rate of approximately 5 per 100 000 (51). Studies conducted over the last three decades in Third World countries have confirmedthat rheumatoid arthritis occurs throughout the world. Rheumatoid arthritis is a chronic systemic 242

inflammatory disorder that may affect many tissues and organs but particularly the joints, oftenprogressing to destruction of the articular cartilage and ankylosis of the joints (52, 53). Due to itsphysical, social and psychological burden, patients’ experience many difficulties in variousaspects of their lives and can contribute in these patients experiencing poor health. Rheumatoidarthritis is the third chronic illness among the respondents in the study. In India, the prevalenceof rheumatoid arthritis (0.75%) is similar to that in the West (54). The rarity of rheumatoidarthritis in rural Africa contrasts with the high prevalence of the disease in Jamaica, where over2% of the adult population is affected (55). In a study in Latin America, rheumatoid arthritis wasthe reason for seeking medical advice in 22% of rheumatology clinic patients (56). Quality of lifeis significantly low in patients with rheumatoid arthritis, knee osteoarthritis and fibromyalgiasyndrome, whose depression and/or anxiety scores are high (57). Therefore, these patients shouldbe managed using a multidisciplinary approach including psychiatric support. In this study just over one-third of the respondents indicated an unspecified chronicillness. The unspecified chronic diseases could be other chronic non-communicable disease suchas a malignant neoplasm or a chronic communicable disease. In Jamaica, cancers accounted for15% of non-communicable diseases and 9% of total disease burden in 1990. Cancers of thebreast and cervix are the most common neoplasms in women, with rates in 1991 of 22.6 and 19.2per 1,000 population, respectively. Prostate cancer was the number one form of cancer found inmen (58). In 2002 there were 3,769 public hospital discharge diagnoses (4% of total dischargediagnoses) for malignant neoplasms with an equal gender distribution. The types of neoplasmsinvolved for males, in order of decreasing frequency, were: trachea, bronchus, and lungs;prostate; leukemia; and non-Hodgkin’s lymphoma, representing 56% of all cancers. For females,the order was as follows: breast; cervix uteri; other malignant neoplasms of female genital 243

organs; trachea, bronchus, and lungs; leukemia; and non-Hodgkin’s lymphoma, togetherrepresenting 56% of all cancers (59). The unspecified chronic illness may include HIV/AIDS, acommunicable disease, has become a serious public health concern in Jamaica. The nationalincidence of AIDS in 2000 was 352 per 1,000,000 population (60). In addition, the unspecifiedchronic disease may include depression and there is evidence to suggest that depressive disordersfrequently accompany other chronic medical diseases. The 2000 Lifestyle Survey foundapproximately 25 % depressive symptoms in the general population (35). Anderson et al. (61)concluded that the presence of diabetes mellitus increases the risk of depression and studies haveshown that in persons diagnosed with diabetes mellitus the prevalence of depression range from6.1% - 60.7% (62). Majority of the respondents resided in rural areas and just over one-half of these were inthe lower class. The study found that there was an income differential between respondents inrural compared with urban area of residence, with those in the rural having mean annual incomeof approximately two-thirds of their urban counterparts. Diabetes mellitus was found to be thethird leading reported chronic disease influencing persons with greater income and consumption.While hypertension was the third most reported chronic disease associated with crowding, it wasthe fourth most reported dysfunction associated with income and consumption expenditure.According to Sobal and Stunkard (63), in developing societies there is a higher likelihood ofobesity among men in higher socio-economic strata. These men are at increased risk ofdeveloping type 2 diabetes mellitus (64) which is increasing in the adult population. Most of therespondents in this study were female and single women constitute 45% of Jamaican head ofhouseholds (65). In Jamaica, female-headed households are poorer than those headed by malesand twice as likely to be unemployed. Male-headed households are smaller and have a per capita 244

expenditure 10 times higher than female-headed households (66, 67). The 1999 data fromSTATIN show that individuals who live in rural areas, who are in the poorest quintile, and whoare males are less likely to seek health care (68). This under-representation of men in clinics inrural communities is of great concern, as hypertension and diabetes are not gender-specificconditions and could contribute to the poor health status of these men. The ‘silent’ nature ofthese diseases has grave implications for the mortality and morbidity of middle-aged and elderlyJamaican men. Poorer socioeconomic status co-segregates with obesity, even in diabetes (69), as dophysical inactivity, smoking, and low birth weight, which are all known risk factors for type 2diabetes. The prevalence of chronic diseases varied with socioeconomic status with more personsat the lower levels suffering from diabetes, hypertension and depression (70). A recent studyshowed that persons of a lower socioeconomic status have significantly higher mean systolicblood pressures and waist circumference when compared with those of high socioeconomicstanding (70). In Trinidad and Tobago, blood pressure and hypertension were negativelyassociated with income and education in women, while no consistent associations were observedin men (71). Chang et al. (72) found that in younger women in Latin America and the Caribbean,greater education was associated with lower risk of stroke but there was no education-relatedgradient in risk of myocardial infarction. Two Jamaican studies (73, 74), as well as a small studyfrom St Vincent (75), have provided some evidence for a positive association between bloodpressure and socioeconomic position in men. However, rural farmers who have traditional dietsand physical activity patterns generally show a lower prevalence of hypertension than their urbancontemporaries (76). 245

ConclusionThe general epidemiological shift from infectious to chronic non-communicable diseases inJamaica puts the residents at risk. Majority of the respondents in the sample had good health.Adults with poor health status were more likely to report having hypertension followed bydiabetes mellitus and arthritis, while asthma was the most prevalent among children. Poor healthstatus was more prevalent among those of lower economic status in rural areas who reported theleast annual income. Predictors of poor health status of Jamaicans who reported being diagnosedwith a chronic disease were age, area of residence and inability to work, therefore beingunemployed. Given the high prevalence and poor levels of control, hypertension and diabetesmellitus remain formidable issues for public health care in Jamaica and the Caribbean. Poverty,low education and poor access to health care in rural communities intensify the inertia to thelifestyle modifications that are necessary to bring about greater levels of control. We suggest thatfurther improvement in chronic disease control can be achieved with improved patient educationon the importance of compliance, access to more effective medication and development ofsupport groups among patients with chronic disease(s). 246

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Table 9.1: Socio-demographic characteristics of sample Area of residence Variable Urban Other towns Rural pvalue n (%) n (%) n (%)Sex 0.702 Male 70 (35.0) 48 (39.7) 144 (36.6) Female 130 (65.0) 73 (60.3) 249 (63.4)Injury 0.347 Yes 4 (2.0) 6 (5.0) 13 (3.3) No 195 (98.0) 115 (95.0) 380 (96.7)Self-reported chronic illness 0.214 Asthma 33 (16.5) 11 (9.1) 51 (13.0) Diabetes 32 (16.0) 27 (22.3) 64 (16.3) Hypertension 47 (23.5) 41 (33.9) 118 (30.0) Arthritis 16 (8.0) 10 (8.3) 30 (7.6) Unspecified 72 (36.0) 32 (26.4) 130 (33.1)Social class < 0.001 Poor 36 (18.0) 32 (26.4) 208 (52.9) Middle 30 (15.0) 27 (22.3) 84 (21.4) Upper 134 (67.0) 62 (51.3) 101 (25.7)Self-evaluated health status < 0.001 Good 77 (38.5) 38 (31.7) 112 (28.6) Fair 93 (46.5) 61 (50.8) 150 (38.4) Poor 30 (15.0) 21 (17.5) 129 (33.0)Household head 0.082 Yes 105 (52.5) 72 (59.5) 189 (48.1) No 95 (47.5) 49 (40.5) 204 (51.8)Marital status Married 60 (35.3) 34 (31.8) 130 (39.8) 0.166 Never married 78 (45.9) 48 (44.9) 144 (44.0) Divorced 7 (4.1) 6 (5.6) 6 (1.8) Separated 4 (2.4) 4 (3.7) 2 (0.6) Widowed 21 (12.4) 15 (14.0) 45 (13.8)Educational level 0.466 No formal 160 (80.0) 106 (87.6) 319 (81.2) Basic 14 (7.0) 5 (4.1) 33 (8.4) Primary/Preparatory 12 (6.0) 5 (4.1) 25 (6.4) Secondary/High 9 (4.5) 4 (3.3) 13 (3.3) Tertiary 5 (2.5) 1 (0.8) 3 (0.8)Age Mean (SD) 47.5 yrs (25.07 53.36 yrs. 48.7 (25.79 0.114 yrs) (23.61) yr)†Annual Income Mean (SD) US $10,312.41 US $8,218.05 US $5,873.08 < 0.001 (US $9,059.70) (US $7,653.84) (US 4,473.51)Number of visits to health 1.4 (1.1) 1.5 (1.5) 1.4 (1.1) 0.842care practitioner Mean (SD)†Annual Income is quoted in US $ (US$ 1.00 = Ja. $ 80.47 at the time of the survey) 255

Table 9.2: Diagnosed chronic recurring illness by age group Age group Young Other aged- Oldest Children adults adults Young old Old elderly elderly Total Diagnosed chronic illness n (%) n (%) n (%) n (%) n (%) n (%) n (%)Asthma 51 (47.2) 16 (23.2) 18 (7.5) 7(4.1) 2 (2.1) 1 (3.4) 95 (13.3) 3 (2.8) 3 (4.3) 44 (18.3) 49 (28.7) 19 (19.6) 5 (17.2) 123 (17.2)Diabetes mellitus 0 (0.0) 6 (8.7) 76 (31.7) 61 (35.7) 49 (50.5) 14 (48.3) 206 (28.9)Hypertension 0 (0.0) 1 (1.4) 17 (7.1) 22 (12.9) 14 (14.4) 2 (6.9) 56 (7.8)Arthritis 54 (50.0) 43 (62.3) 85 (35.4) 32 (18.7) 13 (13.4) 7 (24.1) 234 (32.8)Other (unspecified) 108 69 240 171 97 29 714 Totalχ2 (df = 20) = 297.701, p < 0.001 256

Table 9.3: Diagnosed chronic illness by social class Social class Poor Middle class Upper class Total Diagnosed chronic illness n (%) n (%) n (%) n (%) Asthma 42 (15.2) 19 (13.5) 34 (11.4) 95 (13.3) Diabetes mellitus 41 (14.9) 16 (11.3) 66 (22.2) 123 (17.2) Hypertension 82 (29.7) 48 (34.0) 76 (25.6) 206 (28.9) 25 (9.1) 12 (8.5) 19 (6.4) 56 (7.8) Arthritis Other (unspecified) 86 (31.2) 46 (32.6) 102 (34.3) 234 (32.8) Total 276 141 297 714χ2 (df = 8) = 13.882, p = 0.085 257

Table 9.4: Crowding, income and annual consumption expenditure by diagnosed chronic disease 95% Confidence interval Std. N Mean Deviation Std. Error Lower Upper †Crowding Asthma 95 5.14 2.88 0.30 4.55 5.72 Diabetes mellitus 123 3.55 2.33 0.21 3.14 3.97

Health Demography

by Paul Bourne Institute on Feb 16, 2011

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