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Child & Adolescent Health
Child & Adolescent Health
Child & Adolescent Health
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Child & Adolescent Health

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Child & Adolescent Health provides answers to many issues in relation to health and reproductive health matters of Jamaicans.

Child & Adolescent Health provides answers to many issues in relation to health and reproductive health matters of Jamaicans.

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  • 1. Child & Adolescent HealthTheory, Principle and Behaviour Paul Andrew Bourne
  • 2. Child & Adolescent HealthTheory, Principle and Behaviour i
  • 3. Child & Adolescent HealthTheory, Principle and Behaviour PAUL ANDREW BOURNE Socio-Medical Research Institute SOCIO-MEDICAL RESEARCH INSTITUTE KINGSTON, JAMAICA, WEST INDIES ii
  • 4. ©Paul A. Bourne, 2011First Published in Jamaica, 2011 byPaul Andrew Bourne66 Long Wall DriveStony Hill,Kingston 9,St. AndrewNational Library of Jamaica Cataloguing DataChild & Adolescent Health: Theory, Principle and BehaviourIncludes indexISBNBourne, Paul AndrewAll rights reserved. Published, 2011Covers designed by Paul Andrew BourneAll the photographs were taken by Paul A. BourneSocio-Medical Research Institute, 66 Long Wall Drive, Stony Hill,Kingston 9, Kingston, Jamaica iii
  • 5. To Evadney It is the big things that envelope history;so make them count, today and every time Paul A. Bourne, 2011 iv
  • 6. PrefaceChild health is among the longstanding issues in health research and this is no different foradolescent health and reproductive health matters. Reproductive health issues have beenprimarily examined as a separate matter from general health in health literature in the Caribbean,particularly Jamaica. When health is studied the Jamaica and the wider Caribbean, it covers 1)illness (diagnosed – HIV/AIDS, et cetera), 2) self-reported health conditions, 3) self-rated healthstatus, 4) quality of life, 5) nutrition, 5) health care delivery, 6) health care system, 7) disability,8) mental health, 9) health consequences, 10) injuries, and 11) emergence and re-emergence ofinfectious diseases. A comprehensive review of the literature (in books, internet, intranet, library searchengines and research publications) in the Caribbean revealed no book that has twinned generalhealth and reproductive health matters of children and adolescent in the region. Health and healthissues are not limited to general health or reproductive health matters as positive construct ofhealth as offered by the World Health Organization (WHO) in the Preamble to its Constitution ismore than illness (biological conditions or germ theory) to include social and psychologicalwellbeing. Wellbeing as an endogenous variable comprises 1) behaviour, 2) choices anddecisions, and 3) health issues including quality of life. According to the Webster‟s lexicon, wellbeing is „a state of being happy, healthy, orprosperous‟. Good physical health is, therefore, a precondition for wellbeing, but happinessconstitutes good life for an individual, which are based on many elements. Moreover, do not v
  • 7. forget, from Marcoux (2001) account, ageing is a global phenomenon that is here to stay.Furthermore, we should not turn a blind eye ageing as was pointed out by Turner (1998). In thisstudy, the researcher will construct a model of the determinants of wellbeing among theJamaican elderly, which includes cultural variables, environmental factors, psychosocialcharacteristics and economic issues in order to mushroom greater discourse and policy changesin keeping with the „new paradigm‟ shift of ageing. 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 one‟s 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 critical vi
  • 8. component in welfare and wellbeing. It is believed by some scholars that economic growthand/or development is a measure of welfare (see Becker, Philipson and Soares 2004). As health is a multi-faceted variable (Portrait et al. 2001) that looks beyond bio-medicalconditions. When wellbeing is mentioned, it goes beyond many of the established operationaldefinitions of health (i.e. physical functioning). Wellbeing is a state of psychological, social andeconomic state and this refers specifically to the worth of this condition in the discourse of socialsciences. Wellbeing is not simply a function of income although income is able to affordsomeone a „good life‟. The UNDP‟s, (UNDP 2006) human development index (HDI) is anindicator of wellbeing, and it is used for comparisons across countries. The HDI uses nationalincome (GDP per capita), heath status and education as causal predictors of wellbeing. Studies revealed that positive moods and emotions is associated with wellbeing (Leung etal. 2005) as the individual is able to think, feel and act in ways that foster resource building andinvolvement with particular goal materialization (Lyubomirsky, King, and Diener 2005). Thissituation is later internalized, causing the individual to be self-confident from which follows aseries of positive attitudes that guides further actions (Sheldon and Lyubomirsky 2006). Positivemood is not limited to active responses by individual, but a study showed that “counting one‟sblessings,” “committing acts of kindness”, recognizing and using signature strengths,“remembering oneself at one‟s best”, and “working on personal goals” are all positivelyinfluence wellbeing (Sheldon and Lyubomirsky 2006; Abbe et al. 2003). Happiness is not amood that does not change with time or situation; hence, happy people can experience negativemoods (Diener and Seligman, 2002). vii
  • 9. 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„wellbeing‟ instead of „happiness” (Crisp 2005), which explains the rationale for this bookillness, health status and quality of life. QoL is widely accepted by medical researchers and clinicians as an alternative paradigmto dysfunction in the measurement of health and treatment of health-care of customers (i.e.patients) (see for example, Seed & Lloyd, 1997; Sullivan et al., 1992). The rationale for thisparadigm is owing to its maximization perspective (also see Longest, 2002; WHO 1948). Manyscholars including economists (such as Sen, 1982; 1985; Easterlin 2001a, 2001b; Stutzer & Frey2003; Di Tella MacCulloch Oswald 2001) have proposed that QoL (or wellbeing) mustincorporate subjective as well as objective conditions. They contend that any construct whichwill be used to capture QoL (or wellbeing) must be such that it embodies economic wellbeing(i.e. Gross Domestic Product per capita growth) and emotional reactions to events as they are a viii
  • 10. part of whole life of an individual. This argument is also forwarded by psychologists such asEdward Diener 1984; Richard Veenhoven 1991, that justify their use of happiness or self-reported overall QoL to assessment wellbeing (see Stutzer & Frey 2003; Veenhoven 1991;Easterlin 2001a. 2001b; Diener 1984, 2000). In order to assess overall QoL of an individual, it is argued that the „best‟ approach to betaken in this regard is to use a questionnaire that will collect information from people onparticular aspects of their lives and overall QoL (see for example, RA Cummins 2005, 2000;Todd Kashdan 2004; Helen Murphy & Elsa Murphy 2003; Michael Pacione 2003). Kashdanwrites that the assessment of subjective wellbeing (or QoL) can be addressed with aquestionnaire on happiness which the aforementioned literature has outlined as the proposition ofother scholars. Murphy & Murphy and Hutchinson et al, on the other hand, believe that QoLassessment can be done by way of self-reported satisfaction with life and subjective assessmentof the life by the individual. A part of this assessment was self-esteem; self-achievement (oractualizations) which are embodied in Abraham Maslow‟s 5 Needs hierarchy. Michael Pacioneopines that “The simplest model states that satisfaction with life in general is weighted sum ofsatisfactions with different domains or aspects of life(for example, job satisfaction) and that , inturn, these domain satisfactions are weighted sums of specific satisfiers and dissatisfiers…Amore complex formulation is the hierarchy of needs of model…” (2003:23). Cummins (2005),on the other hand, provides a contravening argument to the view of Pacione that needs must notbe used as an assessment of life‟s quality of an individual. He argues that the drawback to theuse of needs is embedded in the fact that low degree of needs does not necessarily associate withQoL (Cummins, 2005:700). Hence, Cummins‟ delimitation will not hold in the event that needsare at moderate or high valuations. ix
  • 11. Clearly from the aforementioned positions, child and adolescent health must incorporateall aspect of the wellbeing (or quality of life) of the individual. In order to forward anunderstanding of what constitutes wellbeing or ill being, a system must be instituted that willallow us to coalesce a measure that will unearth peoples‟ sense of overall quality of life fromeither economic-welfarism (see Becker et al. 2004), psychological theories (Diener, Suh, andOishi, 1997; Headey and Wooden 2004; Kashdan 2004; Diener 2000), practices and behaviours.People are made better off, if their current desires are fulfilled, and so any study of health (orwellbeing – quality of life) must assess peoples‟ reproductive health matters and experiences thatinfluence health outcomes. Health is an exogenous as well as an endogenous variable, and when it is used as anendogenous variable it is influenced by many factors. To capture the state of the quality of life ofhumans, we are continuously and increasingly seeking to ascertain more advance methods thatwill allow us to encapsulate a quantification of wellbeing that is multidimensional andmultifaceted. According to Langlois and Anderson (2002), approximately 30 years ago, aseminal studies conducted by Smith (1973, 2) “proposed that wellbeing be used to refer toconditions that apply to a population generally, while quality of life should be limited toindividuals‟ subjective assessments of their lives …” They argue that a distinction between thetwo variables have been lost with time. From Langlois and Anderson‟s monograph, during the1960s and 1970s, wellbeing was approached from a quantitative assessment by the use of GDPor GNP (also See, Becker, Philipson and Soares 2004), and unemployment rates; this they referto as a “rigid approach to the [enquiry of the subject matter] subject”. According to Langlois andAnderson (2002), the positivism approach to the methodology of wellbeing was objectification,an assessment that was highly favoured by Andrews and Withley (1976) and Campbell et al x
  • 12. 1976. This is the rationale behind this book utilization of a positivism methodology (usingeconometric analyses – modeling and surveys). 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. In recognition of the realities above, this book usedsubjective wellbeing, health, health conditions and health status as well as reproductive healthmatters. The question that must be answered by scholars before lambasting subjective wellbeingis “Can subjectivity be a scientifically studied?” 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). Diener (2000) in anarticle titled „Subjective Wellbeing: The Science of Happiness and a Proposal for a NationalIndex‟ theorizes that the objectification of wellbeing is embodied within satisfaction of life. Hispoints to a construct of wellbeing called happiness. Edward Diener who I consider the father of xi
  • 13. happiness as a measure of subjective wellbeing has provided the platform for the scientific studyof subjective wellbeing (happiness). And this has been expensively studied by many economistslike Oswald and Easterlin. Other economists have researched different subjective measure ofhealth like Michael Grossman, Smith and Kington. Grossman used econometric techniques tostudy subjective health of the world‟s population, and this was expanded upon by Smith andKington. According to Smith and Kington (1997), using Ht= f (Ht-1, Pm Go, Bt, MCt ED, Āt, ) toconceptualize a theoretical framework for “stock of health” noted that health in period t, Ht, isthe result of health preceding this period (Ht-1), medical care (MCt), good personal health (Go),the price of medical care (Pm), and bad ones (Bt), and a vector of family education (ED), and allsources of household income (Āt). Embedded in this function is the wellbeing that individualenjoys (or not enjoys) (see Smith and Kington 1997, 159-160). Therefore there is an answer tothe scientific inquiry of any phenomenon, particularly wellbeing and quality of life. Outside ofscientific study of subjective health, Thomas Kuhn has provided enough evidence that the socialscience can research social phenomena with the same degree of scientificness like the naturalsciences like physics, chemistry, mathematics and medicine. With empirical evidence showing that science is not science because it is pure (or natural)provide some focus for the examination of social issues like health and reproductive healthmatters. There is no reason for the separation of general health from reproductive health issues,and this book closes the gap between the seemingly two phenomena in a single volume. Theseparate and distinct marker between general health and reproductive health matters is an elusiveone, should desist and replaced by singled focus. xii
  • 14. This book is the first of its kind in assess health issues –including reproductive healthmatters and health status - in a single volume. Each chapter utilizes a theoretical framework,mathematical, and justifies the comprehensive methodology that is used in therein. Embedded inthe theoretical framework is an econometric technique that is highly mathematical and will notbe simplified in this book. For those readers who are interested in understanding thefundamentals of the theoretical framework, they can do further reading in any advancedmultivariate textbook (regressions – linear, logistic, and discriminant analyses). In keeping withmy belief that written materials must be of low readability, I endeavour to ensure that sufficientexplanations are provided for the methodology as well as each chapter. It follows, therefore, thatall the complex mathematical techniques are hidden, and the methodological principles aresimplified for the purpose of general readership and ease of reading the material. This book is intended to be a text for undergraduate and graduate students indemography, sociology, social work, anthropology, public health, public administration,economics, management studies, public policy, gerontology and general medicine as well ashealth administrators, researchers and policy personnel. The materials are the behaviour,practices, attitudes and perspectives of children and adolescents. Having provides somediscussion on the non-issue of the non-scientificness of subjective views, particularly wellbeing(including happiness, quality of life, illness and health status), the book is an insight into mattersthat have been problematic for years, and some recommendations were given that can be furtherassessed by medical practitioners, public administrators and policy specialists. Paul Andrew Bourne Socio-Medical Research Institute March 2011 xiii
  • 15. Table of ContentsDedication ivPreface vAcknowledgement xviPart 1: HEALTH STATUSChapter 1: Childhood Health in Jamaica: changing patterns in health conditions of children 0-14 years 1Chapter 2: Child Health Disparities in an English-Speaking Caribbean nation: Using parents‟ views from a national survey 30Chapter 3: Self-rated health status of young adolescent females in a middle-income developing country 58Chapter 4: Self-assessed health of young adults in an English-speaking Caribbean nation 77Chapter 5: Quality of Life of Youths in Jamaica 108Chapter 6: Health of children less than 5 years old in an Upper Middle Income Country: Parents‟ views 133Chapter 7: Biosocial determinants of health and health seeking behaviour of male youths in Jamaica 158Chapter 8: Demographic shifts in health conditions of adolescents aged 10-19 years, Jamaica: Using cross-sectional data for 2002 and 2007 184Chapter 9: Self-reported Health of Youth: Using Health Conditions to measure Health 209Chapter 10: The changing faces of diabetes, hypertension and arthritis in a Caribbean population 232Chapter 11: Variations in social determinants of health using an adolescence population: By different measurements, dichotomization and non-dichotomization of health 257Chapter 12: Health status of patients with self-reported chronic diseases in Jamaica 284 xiv
  • 16. Part 2: REPRODUCTIVE HEALTH MATTERSChapter 13: Sociodemographic correlates of age at sexual debut among women of thereproductive years in a middle-income developing nation 311Chapter 14: Young males whose first coitus began at most 15 years old 338Chapter 15: Young males who delay first coitus for the statutory age and beyond in Jamaica 362Chapter 16: Factor Differentials in contraceptive use and demographic profile among females who had their first coital activity at most 16 years versus those at 16+ years old in a developing nation 386Chapter 17: Reproductive health matters: Women whose first sexual intercourse occurred at 20+ years old 418Chapter 18: Sexually assaulted females on their sexual debut: Reproductive health matters 442Chapter 19: Reproductive health matters among Infrequent versus Frequent young adult-male-church attendees 467Chapter 20: Multiple sexual partnerships among young adults in a tropically developing nation: A public health challenge 497Chapter 21: Females with multiple sexual partners and their reproductive health matters: A comprehensive analysis of women aged 15-49 years in a developing nation 530 xv
  • 17. AcknowledgementThe writing of a book is a time consuming and a tedious process, which is assisted by manypeople. A book is not a singulate effort and this must be recognized by the author(s), editor(s)and/or publisher(s). Like many other authors, I am indebted to many people who contributed indifferent ways to the completion 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 oncountless nights, and longer on Saturdays and Sundays. Ms. Neva South-Bourne, whose tirelessefforts and endless patience in proofreading some of the chapters as well as Mrs. CindiScholefield. I am also indebted to the Derek Gordon Databank, University of the West Indies,Mona (Jamaica) that made the dataset available from which many of the chapters emerged. Themajority of the chapters are published works in different journals, and I am grateful for theirpermission to use the materials in this book (North American Journal of Medical Sciences,Health, Current Research Journal in Social Sciences, International Journal of CollaborativeResearch on Internal Medicine and Public Health, HealthMed Journal, and Journal of Clinicaland Diagnostic Research; Journal of Applied Sciences Research). Finally, I would like to thankall my co-authored who wrote different articles with me. Any errors of omission or commissionin this book should not be ascribed to anyone or organizations as these are of the author. xvi
  • 18. Part 1: Health Status 1
  • 19. Chapter 1Childhood Health in Jamaica: changing patterns in healthconditions of children 0-14 years Paul Andrew BourneThe new thrust by WHO is healthy life expectancy. Therefore, health must be more thanmorbidity. It is within this framework that a study on childhood health in Jamaica is of vitalimportance. This paper 1) expands the health literature in Jamaica and by extension theCaribbean, 2) will aid public health practitioners with research findings upon which they are ableto further improve the quality of life of children, 3) investigates the age at with children inJamaica become influenced by particular chronic diseases and 4) assesses the subjectivewellbeing of children. The current study extracted a sample of 8,373 and 2,104 children 0-14years from two surveys collected jointly by the Planning Institute of Jamaica and the StatisticsInstitute of Jamaica for 2002 and 2007 respectively. A self-administered questionnaire was usedto collect the data. Ninety-one percent of children in Jamaica, for 2007, reported good health.The number of children who had diarrhoea fell by 84.2% in 2007 over 2002, and a similarreduction was observed for those with asthma (42.1% in 2002 and 19.7% in 2007). Anothercritical finding was that 1.2% of children, in 2007, had diabetes mellitus compared to none in2002. Public health now has an epidemiological profile of health conditions of children and thedemographic shifts which are occurring and this can be used for effective management andplanning of the new health reality of the Jamaican child.INTRODUCTIONOne of the measures of child health and the health status of the general populace is infantmortality or mortality, which is well studied in Jamaica and the wider Caribbean [1-11]. Thesimple rationale for the use of mortality in evaluating health status is owing to its ease in which itcan be used to precisely measure its outcome unlike other indicators such as quality of life,subjective wellbeing, happiness or life satisfaction [12-22]. Another reason for the use of infantmortality in the measurement of health is because of the strong inverse significant correlationbetween it and/or general mortality and life expectancy [23,24]. There is no denial therefore that 2
  • 20. infant mortality and/or mortality in general play a critical role in determining health outcomes.Although life expectancy emerged from mortality, the former only speak to length of life and notthe quality of those lived years. An individual can live for 40 years or even 100 years, of whichall those years were lived in severe morbidity. It is owing to aforementioned rationale why theWorld Health Organization (WHO) developed a mathematical technique which discount the lifeexpectancy by the years spent in disability or morbidity [25]. The WHO therefore emphasizedhealthy life expectancy and not life expectancy. Health therefore must be more than morbidity asit expands to quality of life. Within the broadest definition of health conceptualized by the WHO in the 1940s [26], issocial, psychological and physical wellbeing and not the mere absence of diseases suggestingthat health is more than living to the quality of those lived years. Health has been expanded tomean much more than the absence of diseases to include measures of healthy life expectancy,happiness, utility, personal preference, and self-reported quality of life [12-22]. Simply put,wellbeing is subjectively what is ‗good‘ for each person [26]. It is sometimes connected withgood health. Crisp [26] 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‗wellbeing‘ instead of ‗happiness‖, which explains the rationale for this project utilizing the termwellbeing and not good health. 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 [26, 27]. With this theorizing, wellbeing is just personal pleasantness, whichrepresents that more pleasantries an individual receives, he/she will be better off. The very 3
  • 21. construct of this methodology is the primary reason for a criticism of its approach (i.e.‗experience machine‘), which gave rise to other theories. Crisp [26] using the work of ThomasCarlyle described the hedonistic structure of utilitarianism as the ‗philosophy of swine‘, becausethis concept assumes that all pleasure is on par. He summarized this adequately by saying that―… whether they [are] the lowest animal pleasures of sex or the highest of aestheticappreciation‖ [26]. 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 [26, 27], which makes for the ranking of preferences and its assessment byway of money. People are made better off, if their current desires are fulfilled. Despite thistheory‘s strengths, it has a fundamental shortcoming, the issue of addiction. This forwarded bythe possible addictive nature of consuming ‗hard drugs‘ because of the summative pleasure itgives 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 as perfectionism‖ [26]. According to this approach, theconstituent of wellbeing is an environment of perfecting human nature. What goes on an‗objective list‘ is based on reflective judgement or intuition of a person. A criticism of thistechnique is elitism. Since an assumption of this approach is that, certain things are good forpeople. Crisp [26] provided an excellent rationale for this limitation, when he said that ―…evenif those people will not enjoy them, and do not even want them‖. 4
  • 22. In Arthaud-day et al work [28], applying structural modeling, subjective well was foundto constitute ―(1) cognitive evaluations of ones life (i.e., life satisfaction or happiness); (2)positive affect; 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. In keeping therefore with the broad definition of health forwarded by the WHO, anystudy of health must go beyond mortality. A comprehensive search of health literature in theCaribbean in particular found no research that 1) using national cross-sectional survey(s)examined health status of children, 2) investigated the changing pattern of morbidity whichaffect children ages 0-14 years, 3) investigated whether health status (ie. subjective wellbeing)and self-reported morbidities (ie health conditions) are correlated, and if they are good measurefor each other, 4) investigated whether from among the health conditions, chronic diseases andthe time they begin to affect children as well as the 5) demographic characteristics of healthconditions affecting children. The current study will examine the aforementioned issues as healthliterature in the region on child health must expand beyond infant mortality. The objectives ofthe study are to 1) expand the health literature in Jamaica and by extension the Caribbean, 2)understand the status of child health outside of mortality, 3) aid public health practitioners withresearch upon which they are able to further improve the quality of life of children by addingquality to their lived years, 4) investigate the age at with children in Jamaica become influencedby chronic disease, it typology and 5) evaluate the subjective wellbeing of children as is done forthe general populace and elderly [30-37]. 5
  • 23. The current study used two cross-sectional surveys which were conducted jointly by thePlanning Institute of Jamaica and the Statistical Institute of Jamaica (for 2002 and 2007) thatcollect data on Jamaicans. A subsample of 8,373 and 2,104 children 0-14 years was extractedfrom a sample of 25,018 and 6,783 respondents for 2002 and 2007 respectively. The survey wasa national probability sample of Jamaica, and it was weighted to reflect the populace and sub-populations. The response rate for each survey was in excess of 72%. Descriptive statistics, suchas mean, standard deviation (SD), frequency and percentage were used to analyze the socio-demographic characteristics of the sample. Chi-square was used to examine the associationbetween non-metric variables, and Analysis of Variance (ANOVA) was used to test therelationships between metric and non-dichotomous categorical variables whereas independentsample t-test was used to examine a statistical correlation between a metric variable and adichotomous categorical variable. The level of significance used in this research was 5% (ie 95%confidence interval).METHODS AND MATERIALSThe current study extracted a sample of 8,373 and 2,104 children 0-14 years from two surveyscollected jointly by the Planning Institute of Jamaica and the Statistics Institute of Jamaica for2002 and 2007 respectively.[38,39] The method of selecting the sample from each survey wassolely based on an individual being less than or equal to 14 years. The survey (Jamaica Survey ofLiving Condition) began in 1989 to collect data from Jamaicans in order to assess policies of thegovernment. Since 1989, yearly the JSLC adds a new module in order to examine thatphenomenon which is critical within the nation. In 2002, the foci were on 1) social safety net and 6
  • 24. 2) crime and victimization; and for 2007, there was no focus. The sample for the earlier surveywas 25,018 respondents and for the latter, it was 6,783 respondents. 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 residence in rural areas and 150 in urban areas. An ED is anindependent geographic unit that shares a common boundary. This means that the country wasgrouped 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 (ie LFS) was selected for the JSLC. [40, 41] The sample wasweighted to reflect the population of the nation. The JSLC 2007 [40] was conducted May and August of that year; while the JSLC 2002was administered between July and October of that year. The researchers chose this survey basedon the fact that it is the latest survey on the national population and that that it has data on self-reported health status of Jamaicans. A self-administered questionnaire was used to collect thedata, which were stored and analyzed using SPSS for Windows 16.0 (SPSS Inc; Chicago, IL,USA). The questionnaire was modelled from the World Bank‘s Living Standards MeasurementStudy (LSMS) household survey. There are some modifications to the LSMS, as JSLC is morefocused on policy impacts. The questionnaire covered areas such as socio-demographic variables– such as education; daily expenses (for past 7-day; food and other consumption expenditure;inventory of durable goods; health variables; crime and victimization; social safety net and 7
  • 25. anthropometry. The non-response rate for the survey for 2007 was 26.2% and 27.7%. The non-response includes refusals and rejected cases in data cleaning.MeasuresSocial 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).Age is a continuous variable in years.Child. A person who has celebrated less than or equal to 14 years.Health 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.Statistical AnalysisDescriptive statistics, such as mean, standard deviation (SD), frequency and percentage wereused to analyze the socio-demographic characteristics of the sample. Chi-square was used toexamine the association between non-metric variables, and Analysis of Variance (ANOVA) was 8
  • 26. used to test the relationships between metric and non-dichotomous categorical variables whereasindependent sample t-test was used to examine a statistical correlation between a metric variableand a dichotomous categorical variable. The level of significance used in this research was 5%(ie 95% confidence interval).RESULTFor this paper there were two samples (8,373 from 2002 data survey and 2,104 from the 2007survey). In 2002, the sample was 50.7% males and 49.3% females compared to 51.3% males and48.7% females for 2007. The mean age for the sample in 2002 was 7.2 years (SD = 4.2 years)and 7.3 years (SD = 4.3 years) for 2007. The proportion of the sample in particular social class(using population income quintile) was relative the same across the two years. The number ofdays recorded as suffering from illness fell by 2 days in 2007 over 2002 (median number of daysexperiencing ill-health). In 2002, 9.4% of the sample reported an illness/injury in the 4-weekperiod of the survey and this increased by 34.0% (to 12.6%). The percent of the sample thatvisited health care practitioners marginally increase from 56.7%, in 2002, to 58.6% in 2007.Concurrently, 9.3% of sample was covered by health insurance (ie total private in 2002) and thisincreased by 62.4% and a part of this was accounted for by a 5.1% having public healthinsurance coverage. In 2002, 62.6% of the sample dwelled in rural areas, 25.1% in semi-urbanareas and 12.3% in urban areas compared to a shift which was noticed in 2007 as 53.2% residedin rural areas and 20.2% in semi-urban areas with 26.6% lived in urban zones (Table 1.1). The general health status of children in Jamaica, for 2007, was good (91.3%) comparedto 6.7% fair and 2.0% poor. 9
  • 27. Interestingly, in the current study, a shift in health condition was noticed in 2007 over2002. The number of children who had diarrhoea fell by 84.2% in 2007 over 2002, and a similarreduction was observed for those with asthma (42.1% in 2002 and 19.7% in 2007). Anothercritical finding was that 1.2% of children, in 2007, had diabetes mellitus compared to none in2002. On the contrary, 37.5% of children, in 2007, had cold which increased from none in 2002(Table 1.1). A cross-tabulation between health conditions and sex of respondents, revealed that nosignificant statistical correlation existed between the two variables and that this was for bothyears: For 2002 - χ2 (df = 2) = 0.232, p> 0.05; and for 2007 - χ2 (df = 5) = 8.915, p> 0.5 (Table1.2). In spite of the aforementioned, the new diabetic cases were accounted for by females (for2007). In 2002, no significant statistical relationship existed between diagnosed healthconditions and area of residents (χ2 (df = 4) = 1.301, p > 0.05). On the other hand, a statisticalcorrelation was observed for 2007 between the aforementioned variables. Furthermore, morechildren in semi-urban areas had cold than those who dwelled in other areas. On the contrary,diabetic cases were found in urban areas and none in other geographical zones. The findingsrevealed also that more rural children had asthma and more urban children had unspecifiedhealth conditions (Table 1.3). Table 1.4 revealed that no significant association was found between diagnosed healthcondition and social class (ie population income quintile). However, the diabetic cases werespread among the lower class (poorest 20%, 1.9%; and poor, 1.8%) and the upper class (wealthy,2.0%). 10
  • 28. The examination of diagnosed health conditions by mean age of respondents revealedthat a significant relationship existed between the two aforementioned variables in 2007, Fstatistic = 4.875, p < 0.001; but none in 2002 - F statistic = 3.334, p > 0.05. In 2007, the meanage of a child with diabetes mellitus was 12.33 years (SD = 2.1 yrs), 95% CI = 7.16 – 17.5(Table 1.5). However the mean age a child with diarrhoea lower than a child and other healthconditions. The first time in the history of the Jamaica Survey of Living Conditions (JSLC) thathealth status and self-reported health condition was collected together was in 2007. Hence, thecurrent study will cross-tabulate both in order to determine whether a significant correlationexist between them and what is the strength of a relationship if one does exist. Based on Table1.6 a weak significant statistical association exist between health status and self-reported healthcondition - χ2 (df = 2) = 174.512, p < 0.0001, cc= 0.282. On further examination of the findings,it was observed that no child was classified has having very good health status. Ninety-fourpercent of sample who had no health condition reported good health compared to 70% of thosewho had at least one health condition. Of those who had at least one health condition, 9.4% ofthem reported poor health status compared to 1% who had no health condition (Table 1.6). Using independent sample t-test, in 2002, the current study found that there was asignificant difference between the mean age of those who sought and not seek medical care –t3.425 , p < 0.001. The mean age of those who do not seek medical care higher, 6.2 years (SD =4.1), compared to those who seek care, 5.2 years (SD = 4.2 years). However, there was nodifference in 2007: seek care – mean age 5.2 years (SD = 4.1 years) and not seek care – meanage 5.8 years (SD = 4.2 years). 11
  • 29. On examination as to whether a significant statistical correlation existed between healthcare-seeking behaviour and sex of respondents, none was found in each year – p > 0.05 (Table1.7).DISCUSSIONIt is established in epidemiology that diseases in childhood do influence poor health in adulthood[42], suggesting the value of child health to health status over the life course. Anotherimportance to the study of health status is its contribution to all typology of development ashuman capital is critical to socio-economic and political systems. In Jamaica, the StatisticalInstitute of Jamaica [42] estimated that for 2007, there was 28.3% of the nation‘s population wasless than 14 years. Simply put, there are 45 children for every 100 working age (ages 15-64years) Jamaican; and to omitted the health status of this cohort is to substantially neglect acritical sector of the population. The current study found that 2 in every 100 children had poorhealth status; and that weak significant statistical correlation existed between health status andself-reported health conditions. This therefore concurs and contradicts another study that foundstatistical association between health conditions and health status [36]. Hambleton et al. [36],examining data for elderly Barbadians, found that self-reported health conditions accounted formost of the variability in health status (ie. current diseases accounted for 33.5% out of R2 =38.3%). This takes the study in the direct of current diseases (ie health conditions) of children inJamaica. This paper revealed 34% increase in cases of self-reported diseases in Jamaicanchildren. Only 13 in 100 children in Jamaica, in 2007, had a least one health condition. Theseconditions include cold, diarrhoea, asthma, diabetes mellitus and other unspecified diseases. In 12
  • 30. 2007, 20 in every 100 children had asthma, 5 out of every 100 diarrhoea cases, 38 in every 100had cold and 21 in every 100 unspecified conditions. Of the different typology of chronicdysfunctions, 12 in every 1,000 reported diabetes mellitus and no cases were found ofhypertension and arthritis. Given the breadth of the unspecified category, this could includecancers, HIV/AIDS and other communicable or non-communicable diseases. In spite of thisuncertainty, what emerged from the current research is the change in pattern of health conditionsof children between 2002 and 2007. A study conducted by Walker [43] found that growthretardation in children influence blood pressure, obesity, and other chronic health conditions, andthat some 5-6% of children in Trinidad and Tobago, and Jamaica are classified in this group.Walker also found that these children are more likely to experience more episodes of diarrhaea,fever and other morbidities. This research revealed that number of cases of asthma, diarrhoea and unspecifiedconditions fell accompanied with a corresponding rise in cold and diabetes mellitus. Interestinglyto note is that the 1.2% of child population that were diagnosed diabetic patients represents 2.3%of the female population. The diabetic cases were not only females, but urban residents. Of thosewith diabetes, 1.9% was in the poorest 20%, 1.8% poor and 2.0% of the wealthy social class.Continuing, the mean age of female diabetic children was 12.3 years; and this indicates the yearage in which diabetes mellitus begin to affect females in Jamaica. The aforementioned findingexplains the disproportionate number of females to males in the general population that havediabetes -14% females to 7.7% males [40]. Although no cases of hypertension was reported inthis paper, it is established that diabetes mellitus is correlated with hypertension. 13
  • 31. Diabetes Mellitus is not the only challenge faced by patients, but McCarthy [44] arguesthat between 30 to 60% of diabetics also suffer from depression, which is a psychiatric illness.Diabetes mellitus does influence the health status of children and follows them across the lifecourse. It affects lifestyle choice, functional capacity, and like McCarthy said the psychologicalstate of people. This health condition also affects other disease. Morrison [45] opined thatdiabetes mellitus and hypertension have now become two problems for Jamaicans and in thewider Caribbean. This situation was equally collaborated by Callender [46] who found that therewas a positive association between diabetic and hypertensive patients - 50% of individuals withdiabetes had a history of hypertension [46]. Children with diabetes mellitus therefore are highlylikely to develop hypertension in the future, and so children in Jamaica in the future will havetwin chronic conditions. This envelope further shifts in health conditions of children in Jamaica;Morrison alluded to a transitory shift from infectious communicable diseases to chronic non-communicable diseases as a rationale for the longevity of the Anglophone Caribbean populaceand this does not mitigates against lowered healthy life expectancy of the sexes in particularfemales who live 6 years more than males [34,42]. Diabetes mellitus and any other typology of chronic diseases do more than affect healthylife expectancy; they are directly correlated with mortality. Statistics from the Statistical Instituteof Jamaica [42] is the leading cause of deaths in female Jamaicans. The reality of changingpattern of health conditions from communicable to non-communicable and the fact that this isaccounted with urban poor and wealthy, indicate that public health policies are needed to addressthis currently and in the future. Another important fact that embedded in the current study is theearly age in which females are having chronic disease, and this indicates the length of time withwhich they will life with this non-curable disease or likeliness of mortality. 14
  • 32. A study on morbidity and mortality patterns in the Caribbean established that thetransition in morbidity is not atypical to Jamaica [47], and that the leading cause of mortality inregion is similar to developed nations. WHO [48] opined that 80% of chronic illnesses were inlow and middle income countries, indicating the preponderance of chronic illness in regions suchas the Caribbean as well as the fact that chronic illnesses are also a part of the landscape ofindustrialized nations. With the changing pattern of morbidity of children in Jamaica, this willsupport modifications in lifestyle behaviour which must begin from children to the populace. Although there is no statistical difference between the 3 area of residents and healthconditions, the fact that the chronic dysfunctions were found in urban areas denote that publichealth policies must begin in earnest in those places. There is another situation that must beexplored here and that is response of health services, and the management of care for those whoare affected by chronic illnesses. It should be noted that 57 out of every 100 children were takenfor medical care which speaks to the high proportion of children despite being ill who were nottaken to traditional medical facilities. A part of the rationale for this non-medical care seekingbehaviour of children is adults‘ definition of health and the cultural perspective of health. Generally, health in Jamaica is defined as the absence of illness which although isnegative and narrow in scope speaks to people‘s perspective on the matter. Interestingly in thisdiscourse is not only the narrowed definition of health, but that severity in health conditions issubstantially what drives medical care-seeking and not on the onset of illness or preventativecare. This goes to the crux of why only 57 out of every 100 children who are ill would be takento health care practitioners as their families are less likely to taken then for conditions such as thecold, but also provide an explanation for the low medical care seeking behaviour for the generalpopulace. 15
  • 33. Statistics revealed that for the last 2 decades (1988-2007), there were 4 times (years) inwhich males sought more medical care than females – 1991 (48.5% males to 47.4% females);1995(59.0% males to 58.9% females): 1997 (60.0% males to 59.3% females) and 2006 (71.7%males to 68.8% females) [30, 41, 40], which speaks to some embedded culturalization for thishealth care-seeking disparity in nation. While this is not atypical to Jamaica [49-51], that factthat the current study revealed that there was no significant statistical difference between maleand female children being taken for medical care, the disparity that exist in the general populacebegin in young adulthood. This is the period in which identify formulation begins in adolescentsand when males begin to imitate the practices of adult men. The adolescent male therefore willseek less medical care because his adult counter believes that this is weak, feminine and reduceshis machoism. One anthropologist in seeking to explain the practices of Caribbean men used sociallearning theory to examine the lifestyle practices of boys [52]. Chevannes [52] argued that theyoung imitate the roles of society members through role modeling of what constitute acceptableand good roles which is supported by reinforcement. The young male is a subset of the society,and if men are less likely to seek health care because of a cultural perspective that they form ofill-health which goes to the crux of their manhood and possibly seeks to threaten it, young malesas soon as they are somewhat responsible for their choices will do more of the same as theirmentors. This gender role of sexes and health disparity which results after childhood is notlimited to Jamaica or the Caribbean but a study carried out by Ali and de Muynck [53] found thatstreet children in Pakistan had a similar gender stereotype about health, health care and medicalcare seeking-behaviour. Using a descriptive cross-sectional study carried out during Septemberand October 2000 of 40 school-aged street children (8-14 years), they found boys were reluctant 16
  • 34. to seek medical care except when there is severity of ill-health, it threatens their economiclivelihood or there is a perceived reduction in functional capacity. The reason being that mildailment is not severe enough to barr them from physical functioning and within the context of thegeneral population that men ought to be tough, this means that they are okay; and so somemorbidity are not for-hospital, which was so the case in Nairobi slums [54]. This again justifieswhy some children in Jamaica are not taken to health practitioners as there is a perception thatsome illness requires home remedy. Statistics revealed that 56.0% of children (ages 0-4) who were not taken for medicaltreatment despite having an illness was because home remedies were used, figure was 32.8% forthose 5-9 years and 25.6% for those 10-19 years [40]. Inaffordability accounted for 33%, 32.5%and 35.9% of those ages 0-4 years, 5-9 years and 10-19 years respectively who were not broughtto health care practitioner even though they were ill.CONCLUSIONThe general health status of children in Jamaica is good; but this mitigate against the relativelylow age with which females are reported to have had diabetes mellitus and the changing patternof health conditions which have occurred since the 2002. Public health now has anepidemiological profile of health conditions of children and the demographic shifts which areoccurring and this can be used for effective management and planning of the new health realityof the Jamaican child. With the removal of health care user fees for children ages 0-18 yearsfrom the health care landscape of Jamaica (since May 28, 2007), the transition to chronic cases inthis cohort means that health care expenditure in the future will rise as we seek to care for thosepatients over there life course. It is critical that future research examine the composition of 17
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  • 38. Planning Institute of Jamaica and Derek Gordon Databank, University of the West Indies[distributors], 2008.38. Statistical Institute Of Jamaica. Jamaica Survey of Living Conditions, 2002 [Computer file].Kingston, Jamaica: Statistical Institute Of Jamaica [producer], 2002. Kingston, Jamaica:Planning Institute of Jamaica and Derek Gordon Databank, University of the West Indies[distributors], 2003.39. Planning Institute of Jamaica, (PIOJ), Statistical Institute of Jamaica, (STATIN). JamaicaSurvey of Living Conditions, 2007. Kingston: PIOJ, STATIN, 2008.40. Planning Institute of Jamaica, (PIOJ), Statistical Institute of Jamaica, (STATIN). JamaicaSurvey of Living Conditions, 2002. Kingston: PIOJ, STATIN, 2003.41. Kuh D, Ben-Shlomo Y, editors. A life course approach to chronic disease epidemiology.New York: Oxford University Press; 1997.42. Statistical Institute of Jamaica, (STATIN). Demographic statistics, 2007. Kingston, STATIN;2008.43. Walker S. Nutrition and child health development. In: Morgan W, editor. Healthissues in the Caribbean. Kingston: Ian Randle; 2005: p. 15-25.44. McCarthy FM. Diagnosing and treating psychological problems in patients with diabetes andhypertension. Cajanus 2000;33:77-83.45. Morrison E. Diabetes and hypertension: Twin trouble. Cajanus. 2000;33:61-63.46. Callender J. Lifestyle management in the hypertensive diabetic. Cajanus. 2000;33:67-70.47. Ivey MA, Legall G, Boisson EV, Hinds A. Mortality trends and potential years of life lost inthe English and Dutch-speaking Caribbean, 1985-2000. West Indian Med J. 2008;57:122-131.48. World Health Organization, (WHO). Preventing Chronic Diseases a vital investment.Geneva: WHO; 2005.49. Stekelenburg J, Jager B, Kolk P, Westen E, Kwaak A, & Wolffers I. Health care seekingbehaviour and utilization of traditional healers in Kalabo, Zambia. Health Policy. 2005;71: 67-81. 21
  • 39. 50. Sudha G, Nirupa C, Rajasakthivel M, Sivasusbramanian S, Sundaram V, Bhatt S,Subramaniam K, Thiruvalluvan E, Matthew R, Renu G & Santha T. Factors influencing the care-seeking behavior of chest symptomatic: a community-based study involving rural and urbanpopulation in Tamil Nadu, South India. Tropical Medicine & Int Health. 2003;8:336-341.51. Akande TM, Owoyemi JO. Healthcare-seeking behaviour in Anyigba, North-Central,Nigeria. Research J of Med Sci. 2009;3:47-51.52. Chevannes B. Learning to be a man: Culture, socialization and gender identity in fiveCaribbean communities. Kingston: University of the West Indies Press; 2001.53. Ali M, de Muynck A. 2005. Illness incidence and health seeking behaviour among streetchildren in Pawalpindi and Islamabad, Pakistan – qualitative study. Child: Care, Health andDevelopment. 2005;31:525-32.54. Taff N, Chepngeno G. 2005. Determinants of health care seeking for children illnesses inNairobi slums. Tropical Medicine and Int Health. 2005;10:240-45. 22
  • 40. Table 1.1. Sociodemographic characteristic of sampleVariable 2002 2007 N= 8373 N=2104Sex Male 50.7 51.3 Female 49.3 48.7Health care-seeking behaviour Yes 56.7 58.6 No 43.3 41.4Health insurance coverage Yes 9.3 15.1 No 90.7 84.9Area of residence Rural 62.6 53.2 Semi-urban 25.1 20.2 Urban 12.3 26.6Self-reported illness Yes 9.4 12.6 No 90.6 87.4Diagnosed Health conditions Cold - 37.5 Diarrhoea 31.6 5.0 Asthma 42.1 19.7 Diabetes mellitus (ie diabetes) - 1.2 Hypertension - - Arthritis - - Other 26.3 20.8 Not - 17.0Population Income quintile Poorest 20% 26.0 26.0 Poor 22.9 22.6 Middle 20.3 19.5 Wealthy 18.0 18.9 Wealthiest 20% 12.8 13.0Age Mean (SD) 7.2 yrs (4.2 yrs) 7.3 yrs (4.3 yrs)Length of illness Median 7 days 5.0 daysNumber of visits to health practitioner(s) median 1.0 1.0Crowding mean (SD) 2.5 persons (1.5 5.5 persons (2.3 persons) persons) 23
  • 41. Table 1.2. Diagnosed health conditions by Sex, 2002 and 2007Variable 20021 20072Diagnosed Health conditions Male Female Male FemaleCold - 35.7 39.2Diarrhoea 27.3 37.5 3.1 6.9Asthma 45.5 37.5 21.7 17.7Diabetes - 0.0 2.3Hypertension - - -Arthritis - - -Other 27.3 25.0 19.4 22.3No - - 20.2 11.5 1 2 χ (df = 2) = 0.232, p> 0.05 2 2 χ (df = 5) = 8.915, p> 0.5 24
  • 42. Table 1.3. Diagnosed health conditions by area of residenceVariable 20021 20072 Rural Semi-urban Urban Rural Semi-urban UrbanDiagnosed HealthconditionsCold - - - 27.0 56.5 36.0Diarrhoea 33.3 40.0 0.0 - 2.2 8.0Asthma 41.7 40.0 50.0 25.4 15.2 18.7Diabetes - - - - - 2.3Hypertension - - - - - -Arthritis - - - - - -Other 25.0 20.0 50.0 20.6 13.0 23.3No - - - 27.0 13.0 12.0 1 2 χ (df = 4) = 1.301, p > 0.05 2 2 χ (df = 10) = 25.079, p = 0.005, cc = 0.297 25
  • 43. Table 1.4. Diagnosed health conditions by Population income quintileVariable 20021 20072Diagnosed Poorest Poor Middle Wealthy Wealthiest Poorest Poor Middle Wealthy WealthiestHealth 20% 20% 20% 20%conditionsCold - - 16.7 14.3 50.0 35.8 37.5 44.3 36.7 30.0Diarrhoea 75.0 - 66.7 57.1 0.0 3.8 12.5 4.9 2.0 0.0Asthma 0.0 - - - - 22.6 17.9 18.0 14.3 27.5Diabetes - - - - - 1.9 1.8 0.0 2.0 0.0Hypertension - - - - - - - - - -Arthritis - - - - - - - - - -Other 25.0 - 1.0 28.6 50.0 28.3 19.6 16.4 20.4 20.0No - - - - 7.5 10.7 16.4 24.5 22.5 1 2 χ (df = 6) = 8.105, p > 0.05 2 2 χ (df = 20) = 25.079, p > 0.05 26
  • 44. Table 1.5. Mean Age of respondent who has a particular health conditionVariable 20021 20072Diagnosed Health conditions Mean age (SD) 95% CI Mean age (SD) 95% CICold - - 4.4 yrs (4.0 yrs) 3.55 – 5.15Diarrhoea 1.5 yrs (1.5yrs) - 0.09 -3.09 3.5 yrs (2.8 yrs) 1.93 – 5.15Asthma 5.0 yrs (3.0 yrs) 2.51-7.49 6.5 yrs (3.5 yrs) 5.51 – 7.47Diabetes - - 12.33 yrs (2.1 yrs) 7.16 – 17.5Hypertension - - - -Arthritis - - - -Other 5.4 yrs (3.8 yrs) 0.62 – 10.18 6.0 yrs (4.5 yrs) 4.82 – 7.26No - - 5.8 yrs (4.3) 4.46 – 7.20 1 F statistic = 3.334, p > 0.05 2 F statistic = 4.875, p < 0.001 27
  • 45. Table 1.6. Health status by self-reported illnessVariable 20021 20072 Self-reported illness Self-reported illness None At least one None At least oneHealth status (in %) (in %) (in %) (in %)Very good - - - -Good - - 94.3 70.2Fair - - 4.7 20.4Poor - - 1.0 9.4 1 In 2002, health status data were not collected. This took place the first time in 2007 2 2 χ (df = 2) = 174.512, p < 0.0001, cc= 0.282 28
  • 46. Table 1.7. Health (or medical) care-seeking behaviour by sexVariable 20021 20072 Sex SexHealth care-seeking behaviour Male Female Male Female Sought care 42.2 44.5 40.8 42.0 Did not seek care 57.8 55.5 59.2 58.01 2 χ (df = 1) = 0.419, p > 0.052 2 χ (df = 1) = 0.040, p > 0.05 29
  • 47. Chapter 2Child Health Disparities in an English-Speaking Caribbeannation: Using parents’ views from a national survey Paul 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 good healthstatus while evaluating other areas of health. The current study seeks 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. A sample of 2,642 children (≤ 18 years) was used for this analysis.The data were taken from the 2002 Jamaica Survey of Living Conditions (JSLC). Stratifiedprobability sample was used to collect the data. The JSLC used an administered questionnaire todetail recall information on particular activities from parents. The questionnaire was modelledfrom the World Bank‘s Living Standards Measurement Study (LSMS) household survey.Multivariate models were used to establish statistical association between good health status andsocial determinants, health seeking behaviour, and length of illness. Eleven percent of the samplereported an illness in the last 4-weeks. Of those who indicated an illness, 16.5% claimed thattheir illness were non-diagnosed by medical practitioners. Fifty-eight percent of those whoindicated 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% unspecifiedconditions. Six explanatory determinants were found that 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);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) 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). Although health indicators suchas life expectancy, infant mortality, illnesses, and nutrition as well as socio-economicdeterminants such as poverty and education have improved exponentially in Jamaica as well asin the wider Latin America and the Caribbean, child health disparities still exist in Jamaica. Thefindings are far reaching, provide more information than objective indices, and can be used to aidpolicy formulation and guide future research. 30
  • 48. 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 onpeople health. These social determinants include poverty, income, marital status, crime andviolence, culture, and much more.9-27 Poverty is empirically established as strongly correlated 31
  • 49. with 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 sincethe 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,21 32
  • 50. subconsciously 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 incomeand 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 general 33
  • 51. health 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 paper used thedataset of the JSLC for 2007.42 34
  • 52. MeasuresTable 2.1 shows the operational definitions of some of the explanatory variables used in thispaper. 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 be 35
  • 53. low/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 enteredindependently 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 home 36
  • 54. remedy. 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. 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 2.2 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 2.3 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 2.4 presents information between health care-seeking behaviour and particulardemographic variables. A child who received medical care in the last 4 weeks was 1.8 times 37
  • 55. more 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 behaviourand 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 analysisTable 2.5 highlights the explanatory social determinants of good health status of children inJamaica. 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. Does 38
  • 56. this 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 timesmore 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 is 39
  • 57. embedded in the present study that begs for some clarification is the rationale why urban andboys did not indicate any cases of diabetes. 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, thispaper 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 the 40
  • 58. socializing institutions responsible for males‘ lower choice in medical care-seeking behaviourcompared to females. 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 paper 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 public 41
  • 59. hospitals 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 thePlanning 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 to 42
  • 60. experience 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 parentswithin 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. 43
  • 61. 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 terrainin 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. 44
  • 62. 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 inthe 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. 45
  • 63. 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 andfuture 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 rural 46
  • 64. females, 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.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. 47
  • 65. 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 healthinequalities 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 reach 48
  • 66. rural 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 healthoutcome 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.References 1. World Health Organization, (WHO). 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: WHO, 1948. 2. Engel G. A unified concept of health and disease. Perspectives in Biology and Med 1960; 3:459-485. 3. Engel G. The care of the patient: art or science? Johns Hopkins Med J 1977; 140:222-232. 4. Engel G. The need for a new medical model: A challenge for biomedicine. Sci 1977; 196:129-136. 5. Engel G. The biopsychosocial model and the education of health professionals. Annals of the New York Academy of Sciences 1978; 310: 169-181 6. Engel, GL. The clinical application of the biopsychosocial model. Am J of Psychiatry 1980; 137:535-544. 7. Bok S. Rethinking the WHO definition of health. Harvard Center for Population and Development Studies, Harvard School of Public Health. Working Paper Series 2004; 14(7). 8. Brannon L. Feist J. Health psychology. An introduction to behavior and health, 6th edn. Los Angeles: Wadsworth; 2007. 49
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  • 70. Table 2.1: 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? 53
  • 71. Table 2.2: 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 54
  • 72. Table 2.3: 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) 55
  • 73. Table 2.4: 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 56
  • 74. Table 2.5: 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 57
  • 75. Chapter 3Self-rated health status of young adolescent females in a middle-income developing country Paul Andrew Bourne & Grace-Ann Phidhelia CornwallThe study of young female adolescents in Jamaica is sparse and few, in particular on self-relatedhealth status. This research seeks to examine the self-related health status of young female 12-17years and to model factors that influence good self-related health status of young femaleadolescents. This paper utilizes 2002 Jamaica Survey of Living Conditions (JSLC). The surveyis a nationally representative cross-sectional one in which data was collected using stratifiedrandom sample, during June-October 2002. It is a modification of the World Bank‘s LivingStandards Measurement Study (LSMS) household survey. The current study used a sub-sampleof 1,565 female respondents between the ages of 12 to 17 years, with a mean age of 14.4 years (±1.7 years). Four variables emerged as accounting for 20.3% of the variability in reported goodself-related health status of young females. Good self-related health status are explained by costof medical care (OR = 0.996, 95% CI = 0.99 - 1.01), private health care insurance coverage (OR= 0.30, 95% CI = 0.01 - 0.09), number of females in household (OR = 0.73, 95% CI = 0.59 -0.90), and healthcare seeking behaviour (OR = 1.25, 95% CI = 1.04 - 1.52). The majority of thefemale adolescents reported good self-related health status. The findings are far reaching and canbe used to guide policy. Any policy that seeks to address wellbeing of female adolescents mustincorporate the advancement of the household, social and economic factors coupled with theneeds of the individual.IntroductionAdolescents and young adults represent a large and growing proportion of the populations ofdeveloping countries around the world. In the English-speaking Caribbean countries, adolescentsrepresent about 20% of the population, or approximately 1.2 million persons according to 2007population data [1]. Adolescence usually refers to the psychological and physiological processesof maturation between the ages of about 12 to 18. It is a transitional period of rapid physical 58
  • 76. (pubertal), emotional, cognitive and social development [2], and is often characterized by theclarification of sexual values and experimentation with sexual behaviours [3]. While adolescentsare generally among the healthiest of any age group, they have special biological needs.Worldwide, studies on adolescent sexual behaviour show that the years of adolescence and thetransition to adulthood are associated with increases in rates of risky behaviour, including the useof drugs and alcohol, delinquency, and unsafe sexual practices [4, 5]. Early initiation of sexualactivity among adolescents has been identified as a major risk factor for a number of negativereproductive health outcomes, including early childbearing and associated implications formaternal and child health outcomes, as well as increased risk for sexually transmitted infections(STIs) including human immunodeficiency virus (HIV) [6]. The last two decades have been marked by significant changes in adolescent health inCaribbean countries. There has been a shift from infectious to social morbidities caused orcontributed by individual risk behaviors and environmental factors [7,8] concurrent with risingunemployment, increased poverty, and reduced health services. Until in the last ten years wehave known relatively little about the health status of youths residing in the Caribbean. In a studyof a clinical population of young people in Jamaica, Smikle et al. [9] found that the mean age atonset of sexual intercourse among males was 12.5 years; 4% of sexually active males reportedusing condoms consistently. According to the Jamaica Reproductive Health Survey of 2002-03,sexual initiation occurs on average at 13.5 years for young men and 15.8 years for young women[10]. The earlier adolescents begin sexual activity, the less likely they are to use contraception,thus increasing their risk of pregnancy and STIs [11]. Soyibo and Lee [12] reported, among ageneral population of Jamaican school-attending adolescents, rates of marijuana, cocaine, andheroin use of 10.2%, 2.2%, and 1.13%, respectively; the alcohol use rate was 50.2%, and the 59
  • 77. tobacco use rate was 16.6%. The country‘s adolescent fertility rate has increased in recent yearsand, at 112 per 1,000 women aged 15-19, is among the highest in the region. Before they reachthe age of 20, 37% of Jamaican women have been pregnant at least once, and 81% of thesepregnancies are unplanned [10]. This concur with another study where more than 75 percent ofpregnancies among 15-24-year-olds are unplanned, and about 40 percent of Jamaican womenhad at least one child before age 20 [13]. Self-rated health is a subjective and general indicator of overall health status. It evaluatesthe health of an individual based on his/her perception of general overall health. This indicatorhas been found to capture important information about the individual‘s overall health and is apowerful predictor of mortality and functional ability [14]. While self-rating of health is a goodmeasure of objective and subjective health [2], it is also a feasible way to measure health inlarge-scale surveys [15, 16]. Self-rated health has been extensively studied in older adultpopulation groups, where a range of factors associated with self-rated health status has beenidentified [17, 18]. Much less is known about the self-rated health status of younger populationssuch as adolescents in Jamaica, and the available information remains limited in scope. Thepublished literature suggests that young people preferentially employ psychological orbehavioural factors as a rating frame for their health [19, 20]. In contrast, for older people,physical well-being plays a more crucial role in assessing their health [21]. Given theobservation that young adults differ from older people in their perception of health, a betterunderstanding and a separate analysis of the factors associated with self-rated health status isneeded for adolescents. Thus, this research seeks to examine the self-related health status ofyoung female Jamaicans and to determine the factors that influence the health status of youngfemales, ages 12 to 17 years. 60
  • 78. MethodDataThe current study is based on data from 2002 Jamaica Survey of Living Conditions (JSLC). TheJSLC is an annual nationally representative survey which collects information on health, healthconditions, health care utilization, and other socio-demographic characteristics of Jamaicans. It isa modification of the World Bank‘s Living Standards Measurement Study (LSMS) householdsurvey [22]. The survey collects information from the non-institutionalized population between June-October 2002. The sample size was 25,018 respondents [23]. The current study uses a subsampleof 1,565 young women (ages 12 through 17 years) from the general JSLC survey for 2002. Themean age of respondents was 14.4 years (±1.7 years). The only inclusion criterion for this paperwas female and age (12 through 17 years). For 2003 to 2006, the Jamaica Surveys of Living Conditions did not collect informationon the health status of Jamaica. Data for 2008 to 2009 are not yet ready, at the time of writingthis paper the researcher was not given access to the 2007 survey data and so the researcher hadto resort to using 2002 survey data to conduct this research 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 an 61
  • 79. independent 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 (LFS) was selected for the JSLC. The sample was weighted toreflect the population of the nation. The non-response rate was 26.2%. The non-responseincludes refusals and rejected cases in data cleaning. Over 1994 households of individuals nationwide are included in the entire database of allages. A total of 620 households were interviewed from urban areas, 439 from other towns and935 from rural areas. This sample represents 6,783 non-institutionalized civilians living inJamaica at the time of the survey. The JSLC used complex sampling design, and it is weighted toreflect the population of Jamaica.MeasureRelated health status was operationalized using the number of self-related illness/injury in thelast four weeks. It is a dummy variable, where 0 = bad related health status (proxied by self-response to having had a least one health condition), 1 = good related health status (proxy by notreporting a health condition). It is taken from the question, ‗Have you had any illness other thandue to injury? For example a cold, diarrhoea, asthma attack, hypertension, diabetes, or any otherillness? And the options were yes = 1 and no = 2.Physical environment is the external surroundings and conditions in which the individuals reside.Natural disaster refers to the number of responses from people who indicated suffering landsides,property damage due to rains, flooding, and soil erosion. 62
  • 80. Negative affective psychological condition identifies the number of responses from a person onhaving loss a breadwinner and/or family member, family having lost its property, householdmember being made redundant, family having difficulties meeting its financial obligations.Crime index = Σ kiTj,The equation represents the frequency with which an individual witnessed or experienced acrime, where i denoted 0, 1 and 2, in which 0 indicated not witnessed or experienced a crime, 1means witnessed 1 to 2, and 2 symbolizes seeing 3 or more crimes.Ti denotes the degree of the different typologies of crime witnessed or experienced by anindividual (where j = 1 …4, which 1= valuables stolen, 2 = attacked with or without a weapon, 3= threatened with a gun, and 4 = sexually assaulted or raped. The summation of the frequency ofcrime by the degree of the incident ranged from 0 and a maximum of 51.Education was proxied by the number of self-reported days that an individual goes to schools.Household crowding (crowding) is the total number of people who are dwelling in the householddivided by the number of rooms that the household occupies excluding kitchen, verandah andbathroom.Social hierarchy: Income quintiles were used to measure social class, and these range fromquintile 1 (poorest 20%) to 5 (wealthiest 20%). Lower is measured by those in quintiles 1 and 2;middle class is represented by those in quintile 3, and upper class indicated those in quintiles 4and 5.Analytic modelMultivariate logistic regression was used to fit the data of the current study. The literature wasused to identify variables for the current paper as well as the dataset. Sixteen variables (Eqn [1]) 63
  • 81. were identified based on the literature and the 2002 Jamaica Survey of Living Conditions. Weexamined correlation matrices to insure that multicollinearity was not an issue. Ht = (Pmc, ED,Ai , MR, AR, CR, PA, F, EN, C, M, FM; CH, PHS, HSB,Q)……(Eqn [1]) Eqn [1] expresses current health status Ht as a function of price of medical care Pmc,education of individual, ED; age of the individual, Ai , marital status, MR; area of residence, AR;Household crowding (proxy by average occupancy per room), CR; psychological conditions,PA; existing pregnancy, F; natural disaster, EN; average consumption per person, C; number ofmales in household, M; number of females in household, FM; number of children in household,CH; having private health insurance coverage, PHS; visits to health practitioners, HSB, and percapita population quintile that the individual‘s family below, Q. The model was modifiedbecause of non-response and low variability. Hence, a number of variables were not including inthe final model, which is reflected of the population and the challenges of non-response and lowvariability. The following variables were omitted from the analysis because the non responserates were high (in excess of 40%). These were positive affective psychological conditions(41.5%, n = 650). Marital status was omitted on two premises; one, non-variability (99.7% ofthose who responded were never married (n = 672) given their ages; and two, the non-responserate (57.1%, n = 893). Only 1.3% of the population were pregnant (n = 14) and this question hada non-response rate of 29.3% (n = 459). The final model was based on those variables that were statistically significant (P <0.05).Using stepwise logistic regression analyses, all variables that were not significant were removedfrom the final model (P > 0.05). Hence, the final model shows that self-related health status is 64
  • 82. determined by cost of medical care, Pmc ; number of females in household, FM; having privatehealth insurance coverage, PHS; visits to healthcare practitioners, HSB (Eqn [2]): Ht = (Pmc, FM, PHS, HSB)……………………………………………………....(Eqn [2])Statistical analysisData was stored and retrieved in the SPSS 16.0; descriptive statistics were used to providepertinent information on the subsample and logistic regression was used to examine the influenceof socio-demographic and psycho-economic variables on self-related health status (or reportedhealth status). The dependent variable was self-related health status and the independentvariables were socio-demographic and psycho-economic variables. Means and frequencydistribution were considered significant at P < 0.05 using chi-square, independent sample t-test,F-test, and multiple logistic regressions. Where collinearity existed (r > 0.7), variables wereentered independently into the model to determine those that should be retained during the finalmodel construction [23]. To derive accurate tests of statistical significance, we used SUDDANstatistical software (Research Triangle Institute, Research Triangle Park, NC), and this adjustedfor the survey‘s complex sampling design.ResultsTable 3.1 presents information on the sociodemographic characteristic of the sample. The samplehad 1,565 respondents: mean age, 14.4 years old (S.D. = 1.7 years); 8.3% reported an illness and1.3% were pregnant. The majority (62%) of the female respondents lived in rural areas, and most(93.8%) had secondary school education. 65
  • 83. Table 3.2 examines information that is associated with good self-related health status ofrespondents. Four variables emerged as accounting for 20.3% of the variability in good self-related health status of young females. The most influential factors that determine self-relatedhealth status of young females (ages 12 to 17 years) were family ownership of private healthinsurance (OR = 0.03, 95%CI: 0.01 - 0.09); the number of females in the household (OR = 0.73,95%CI: 0.59, 0.90); cost of medical care (OR = 0.996, 95%CI: 1.00, 1.01), and health careseeking behaviour (visits to health care practitioners), (OR = 1.25, 95%CI: 1.04, 1.52).DiscussionIn this paper the majority of adolescents reported that they have good self-related health. Thedeterminants of good self-related health status in female adolescents in Jamaica were familyowed private health insurance coverage, number of females in household, cost of medical careand healthcare seeking behaviour (visits to health care practitioners). The findings of this paperconcur with those of another study which assessed youth health in the Caribbean countriesincluding Jamaica where four in five adolescents state that their general health was good [24].This latter study reported that younger adolescents are more likely to report better health and, byage 16, one in six youths reported fair to poor health status [24]. In addition, almost 10% of theyoung people (more boys than girls) report having a handicap, disability, or chronic illness thatlimits their activities. Headaches, physical development and sleep problems are the mostcommon health concerns of young people in the Caribbean [24]. Poor health in adolescents ispositively associated with risk factors such as abuse and parental problems and negativelyassociated with protective factors such as connectedness to family and community [25]. Resnick 66
  • 84. et al. found that parent/family connectedness and perceived school connectedness wereprotective against every health risk behavior measured, except history of pregnancy [26]. In Jamaica, approximately 9% of the population is covered by private health insurance[27]. Persons in the wealthiest consumption quintile were more than four times more likely tohave health insurance coverage than those in the poorest quintile, 35 per cent and 8.5 per centrespectively [28]. The family‘s health care insurance coverage was the main determinant of goodself-related healthcare status of the female adolescents in Jamaica. Those young females whosefamily had them on their private health insurance plan indicated a lower self-related health statuscompared to another young female whose family does not have private health insurance. Thissuggests that health insurance is purchased in keeping with the high probability of the individualbeing likely to become ill (or knowing that the individual suffers from a particular healthcondition). Poverty and lack of health insurance are two powerful socioeconomic influences thatpredispose young people to a wide variety of health problems. Poor adolescents typicallyexperience more health and health-related problems than non-poor adolescents with respect toacute and chronic conditions that restrict activity; overall self-related fair or poor health; andhigher rates of pregnancy, cigarette smoking and depression [29]. Adolescents from poorfamilies and those without health insurance are more likely to seek routine medical care from apublic hospital, outpatient clinic, emergency department, or public health center. Uninsuredadolescents are more likely to miss school and fall behind academically, which may affect theirability to achieve their full potential [30]. In a study done by Newacheck et al. one in every sevenadolescents in the United States, aged 10-18, is uninsured. Uninsured adolescents, as opposed toinsured adolescents, are more likely to be members of poor and minority families [31]. 67
  • 85. The ability of the families of adolescents to afford healthcare is based on their economicstatus. An adolescent family economic status can have a strong influence on adolescents‘perceptions of health, their health behaviors and use of health care [32, 33]. The cost of healthcare was one of the determinant factors of good health status among the female adolescents inJamaica. In a study by Halcon et al. assessing youth health in the Caribbean Community andCommon Market countries including Jamaica, most adolescents (85.9%) reported that they havea place where they usually receive medical care [34]. However, only 36.2% have had a checkupin the last two years. Less than half have seen a dentist in the past two years. If they needcontraception, students would go, first to physicians, followed by drug stores, family planningclinics, and public health clinics. Males are consistently less likely to use healthcare services thanfemales; and they are more likely to believe that adults will not provide confidentiality [34]. According to Figueroa et al. health-seeking behaviour and/or access to healthcare inJamaica appears to have improved between 1993 and 2000 since significantly fewer persons in2000 than in 1993 reported never having had their blood pressure checked and fewer womenreported they had never had a Pap smear. This may be due to a growing health consciousness insectors of the society [35]. In this paper, health seeking behavior was one of the determinants ofgood health status of female adolescents. The use of healthcare services depends on health statusof respondents. The better the health status of an adolescent the lower the health care servicesutilization and vice-versa. The ability of adolescents to obtain healthcare services is an importantindication of whether the healthcare system is meeting their needs. Difficulties experienced byadolescents in accessing healthcare include: long distance to healthcare centre, lack of transportservices and long waiting time for the healthcare services [36]. Understanding adolescents healthseeking behaviour is critical for quality service improvement. 68
  • 86. In a study by Halcon et al. of adolescents in Caribbean countries, crowding was asignificant concern for a number of young people with 29% reporting 2-4 persons slept in a roomand an additional 3.4% indicate more than 5 people slept together [24]. In this paper, crowdingdid not affect the health status of young females neither did negative affective psychologicalconditions; family assets ownership, household income and consumption, and education. It wasalso discovered that there was no statistical difference between the health statuses of those whodwelled in rural, urban or other towns. The number of males in the household and the number ofchildren in the household did not influence the quality of life of young females. However, thenumber of females in the household inversely affects the health status of young femaleadolescents. Although there is no statistical significance between the health status of poor and wealthyyoung females, nearly three quarters of young females in the study resided in the rural areas (62per cent) where incidences of poverty are traditionally higher than those in urban areas. Thisfurther substantiates the fact that household economic status is directly linked to health ofchildren, and rural children are perhaps more vulnerable than their urban counterparts. There areseveral implication associated with phenomenon for young females from rural households.Among them are vulnerability to diseases brought on by nutritional deficiencies, weak immunesystems and low academic performance. These invariably impact on their life chances,psychological self actualization and eventually their inability to break the cycle of poverty.Hence, any policy that seeks to address the wellbeing of female adolescents must incorporate theadvancement of the household, and the social and economic factors coupled with the needs of theindividual. 69
  • 87. ConclusionThe health status of young females in Jamaica is substantially impacted on by family owedprivate health insurance coverage, number of females in household, cost of medical care andhealthcare seeking behaviour (visits to health care practitioner). Embedded in this paper is theimportance of family through either the purchase of health insurance, coverage of the cost ofmedical care and health visits of young females. This paper provided insights into social factorsthat determine the good self-related health status of female adolescents, which will enablehealthcare practitioners to devise appropriate programs to address the health concerns of thisgroup.DisclosuresThe author reports no conflict of interest with this work.DisclaimerThe researchers would like to note that while this paper used secondary data from the JamaicaSurvey of Living Conditions, none of the errors in this paper should be ascribed to the PlanningInstitute of Jamaica and/or the Statistical Institute of Jamaica, but to the researchers.AcknowledgementThe authors 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 available for use in thispaper, and Dr. Donovan McGrowder for editing and other advice that allowed for the completionthe final manuscript.References1) International database [http://www.census.gov/ipc/www/idb/]. 70
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  • 92. Table 3.1: Descriptive analysis of variables of target cohortVariables Descriptive AnalysisAge 14.4 (±1.7 years)Residence 62%= Rural 25.4% = Other Town 12.3% = Urban areaEducational level 5.6% = Primary 93.8% = Secondary 0.6% = TertiaryAverage consumption (per year) US$652.30 (± $607.37)Average income (per year) US$3,699.00 (± $3,167.41)Crowding 2.3( ±1.5 persons)Self reported good health 91.7%Pregnancy (at the time of the survey) 1.3% 75
  • 93. Table 3.2: Socio-demographic and psychological variables of self-related health status ofthe sample Std Error Odds ratio CI (95%) Characteristic β Coefficient Middle class 0.46 0.37 1.58 0.77 - 3.25 Upper class -0.36 0.34 0.70 0.36 - 1.37 Referent group (lower class) 1.00 Cost of medical care 0.00 0.00 0.996* 0.99 - 1.01 Crowding -0.02 0.10 0.98 0.80 - 1.19 Environment 0.65 0.37 1.91 0.93 - 3.91 Negative Affective Conditions -0.03 0.04 0.97 0.91 - 1.04 Assets owned by household -0.02 0.06 0.98 0.88 - 1.10 Age 0.004 0.08 1.00 0.86 - 1.18 Health Insurance -3.37 0.46 0.03*** 0.01 - 0.09 Other Towns -0.07 0.29 0.94 0.54 - 1.64 Urban areas -0.05 0.34 0.95 0.49 - 1.85 Referent group (Rural areas) 1.00 Number of male -0.05 0.12 0.95 0.75 - 1.20 Number of females -0.32 0.11 0.73** 0.59 - 0.90 Number of children 0.06 0.09 1.06 0.88 - 1.26 Average Consumption 0.00 0.00 0.997 1.00 - 1.01 Crime Index -0.01 0.01 0.99 0.98 - 1.01 Average Income 0.00 0.00 0.997 1.00 - 1.01 Visits to Health practitioners 0.23 0.10 1.25* 1.04 - 1.52 Education 0.04 0.03 1.04 0.99 - 1.10Chi-square (19) = 113.87, P < 0.001-2 Log likelihood = 587.25Nagelkerke r-squared = 0.203Overall correct classification = 92.7%Correct classification of cases on good health = 99.2%Correct classification of cases bad health = 18.8%*P < 0.05, **P < 0.01, ***P < 0.001 76
  • 94. Chapter 4Self-assessed health of young adults in an English-speakingCaribbean nation Paul Andrew Bourne & Christopher A.D. CharlesGender differences in self-assessed health in young adults (i.e. ages 15 – 44 years) are under-studied in the English-speaking Caribbean. The aims of the current research are to (1) providedemographic characteristics of young adults; (2) examine self-assessed health of young adults;(3) identify social determinants that explain good health status for young adults; (4) determinethe magnitude of each social determinant, and (5) gender differences in self-assessed health. Thecurrent study extracted a sub-sample of 3,024 respondents from a larger nationally cross-sectional survey of 6,782 Jamaicans. Statistical analyses were performed using the StatisticalPackages for the Social Sciences v 16.0. Descriptive statistics were used to provide demographicinformation on sample. Chi-square was used to examine the association between non-metricvariables, and an Analysis of Variance was used to test the relationships between metric and non-dichotomous categorical variables. Logistic regression examined the relationship between thedependent variable and some predisposed independent variables. One percent of sample claimedinjury and 8% illness. Self-reported diagnosed illnesses were influenza (12.7%); diarrhoea(2.9%); respiratory disease (14.1%); diabetes mellitus (7.8%); hypertension (7.8%); arthritis(2.9%) and unspecified conditions (41.2%). The mean length of illness was 26.0 days (SD =98.9. Nine social determinants and biological condition explained 19.2% of the variability ofself-assessed health. The biological condition accounted for 78.1% of the explanatory model.Injury accounts for a miniscule percentage of illness and so using it to formulate interventionpolicies would lack depth to effectively address health of this cohort.IntroductionGender differences in self-assessed health in young adults (i.e. ages 15 – 44 years) are under-studied in the English-speaking Caribbean. Previous studies that have examined young adultshave focused on reproductive health; survivability; teenage pregnancy; substance use and abuse; 77
  • 95. HIV/AIDS; injuries and impact of injuries on health [1-7]. While studies on injuries have shownthat young males 15 to 44 years are mostly affected by violent-injuries [6, 7], in Jamaicastatistics [8] revealed that many of the deaths occurred in this age group can be accounted for byinjuries. Injuries are among reasons for ill-health and by extension do not constitute a significantpercentage of illness. Injuries accounted for most morbidities and/or mortalities in the world [7],but this is not typical to Jamaica, making studies on injuries germane but lacks extensivecoverage on health. Statistics on Jamaica showed that of the 10 leading causes of mortality, in2002 [8-10], homicides and injuries were the 5th and 10th causes of deaths respectively [10]. In2004, statistics from the World Health Organization (WHO) showed that injuries were the 4thleading cause of morality in Jamaica [11] and in 2006, statistics from the Jamaica Ministry ofHealth [9] indicated that injuries was not among the 5 leading cases of hospital utilisation inJamaica. Policies therefore in Jamaica would not have been formulated using general health statusresearch, but more so from data on injuries, reproductive health, survivability and mortalities.Policy intervention on those issues are pertinent and cannot be neglected from the general pursuitof health, using general health status and health conditions would provide invaluable insightsfrom the individual‘s perspective on those issues; which would add value to addressing healthconcerns that waiting for particular outcomes such as pregnancies, mortality, injuries or crime,violence and victimization by young adults. A study by Hambleton et al. [12] identified thatillness constituted significant percentage of the explanatory power of self-assessed health ofolder Barbadians (ages 60+ years) and while this provides some understanding of the role ofillness on general health status of which may be caused by injuries, the research identified otherfactors (i.e. social determinants) that played roles in health status determination. 78
  • 96. Injuries therefore do account for a percentage of ill-health, indicating that a study of theirtypologies is imperative but this cannot abate or replace a study on general health of youngadults. An extensive reveal of health literature in the English-speaking Caribbean nations found alack of studies on the general health status of young adults. Empirical literature showed that anystudy of health must coalesce biological and social determinants [13- 25], which is also lackingfor young adults. Recently a study by Bourne [26] provided invaluable insights into the typologyof health conditions and the demographic shifts in these between 2002 and 2007. Tables 4.1 to4.3 highlight hospital utilisation for gunshot wounds and suicides, and victim prolife ofindividuals in Jamaica for 2005. The data highlights the crime and hospital utilisation profile,which indicates that health care utilisation and victims of crimes are substantially between 14and 45 years. Age 15 – 45 years does not only represent most of the victims of crime, mortalityand hospital utilization in Jamaica, it also denotes the group which constitutes arrest for majorcrimes. Some of the issues are social and do affect mortality, but what about those persons of thisgroup who are alive and fear being a victim of violence as well as those who reside in thosecommunities in which such incidences are perpetuated each day. In addition what about theirgeneral health as well as those members of this age group who are not likely victims owing toother social conditions such as social hierarchy, area of residence or those who do not reside ininner-cities communities. It is within this context that the current study chose to examine self-reported health of this group in order to provide insights into the health of young adults and thesocial determinants that explain their health status. The aims of the current research are to (1) provide demographic characteristics of youngadults; (2) examine self-assessed health of young adults; (3) identify social determinants that 79
  • 97. explain good health status for young adults; (4) determine the magnitude of each socialdeterminant, and (5) gender differences in self-assessed health.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 [27]. These twoorganizations are responsible for planning, data collection and policy guidelines for Jamaica, andhave been conducting the JSLC annually since 1989 [28]. The JSLC is an administeredquestionnaire where respondents are asked to recall detailed information on particular activities.The questionnaire was modelled from the World Bank‘s Living Standards Measurement Study(LSMS) household survey [28]. 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 3,024 respondents (i.e. ages15 -44 years) from a larger nationally cross-sectional survey of 6,782 Jamaicans. This paper usedthe dataset of the JSLC for 2007 [29].MeasuresAn explanation of some of the variables in the model is provided here. Self-reported is a dummyvariable, where 1 (good health) = not reporting an ailment or dysfunction or illness in the last4 weeks, which was the survey period; 0 (poor health) if there were no self-reported ailments, 80
  • 98. injuries or illnesses. While self-reported ill-health is not an ideal indicator of actual healthconditions because people may underreport, it is still an accurate proxy of ill-health andmortality. Social supports (or networks) denote different social networks with which theindividual is involved (1 = membership of and/or visits to civic organizations or having friendswho visit one‘s home or with whom one is able to network, 0 = otherwise). Psychologicalconditions are the psychological state of an individual, and this is subdivided into positive andnegative affective psychological conditions. Positive affective psychological condition is thenumber of responses with regard to being hopeful, optimistic about the future and life generally.Negative affective psychological condition is number of responses from a person on having losta breadwinner and/or family member, having lost property, being made redundant or failing tomeet household and other obligations. Health status is a binary measure (1=good to excellenthealth; 0= otherwise) which is determined from ―Generally, how do you feel about your health‖?Answers for this question are in a Likert scale matter ranging from excellent to poor. Healthcare-seeking behaviour is derived from the question: Have you visited a health care practitioner,pharmacist or healer in the past four 4 weeks, with an option of yes or no. For the purpose of theregression the responses were coded as 1=yes, 0=otherwise. Crowding is the total number ofindividuals in the household divided by the number of rooms (excluding kitchen, verandah andbathroom). Age is a continuous variable in years.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-demographic 81
  • 99. characteristics 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 relationshipsbetween metric and non-dichotomous categorical variables. Logistic regression examined therelationship between the dependent variable and some predisposed independent (explanatory)variables, because the dependent variable was a binary one (self-reported health status: 1 ifreported good health status and 0 if reported poor health status). The final model was based onthose variables that were statistically significant (p <0.05), and all other variables were removedfrom the final model (p >0.05). Categorical variables were coded using the ‗dummy coding‘scheme or a reference category. The predictive power of the model was tested using the ‗omnibus test of model‘ andHosmer & Lemeshow‘s [30] 3 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 & Holliday [31] 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. Finally, forward stepwise technique in logistic regression was usedto determine the magnitude (or contribution) of each statistically significant variable incomparison with the others, and the odds ratio (OR) for interpreting each of the significantvariables.ModelTo study the relationship between self-assessed health status and social determinants, biologicalconditions and welfare, and logistic regression was used to estimate the following regression 82
  • 100. model. Equation [1] denotes the 20 social, SDHij, 3 welfare variables, Wij, and biologicalcondition, Bi, of self-assessed health status (Hi) and some standard error: , [1]Table 4.6 presents the results from the econometric exercise, which is captured in Equation [2].Equation [2] therefore presents only those variables which are significantly correlated with self-assessed health status of young adults: , [2] where: Hi is the level of self-assessed health status of person i. SDHij denotes the 9 statistically significant social determinants of person i.ResultsThe sample was 3,024 respondents: 47.6% males and 52.4% males. The mean age of the samplewas 28.5 years (SD = 8.8 years). Thirty percent of the sample was single; 20.4% common-law;13% married; and 27.1% in visiting unions. Thirty-six and three-tenth percent of the sample waspoor with 17.1% in the poorest 20% compared to 44.1% in the wealthy social hierarchies, ofwhich 23.2% was in the wealthiest 20%. Forty-five and nine tenth percent of the sample dwelledin rural area, 22% in peri-urban and 32.1% in urban areas. Of the sample population, with respectto the questions on injury and illness 97.1% and 97% responded respectively. Of thoserespondents, 1% claimed injury and 8% mentioned illness. When respondents were askedwhether the illness was diagnosed and the typologies of conditions, 100% stated that the health 83
  • 101. condition was diagnosed by a medical practitioner. The self-reported diagnosed health conditionswere influenza (12.7%); diarrhoea (2.9%); respiratory disease (14.1%); diabetes mellitus (7.8%);hypertension (7.8%); arthritis (2.9%) and unspecified conditions (41.2%). The mean length ofillness was 26.0 days (SD = 98.9), with 1 visit made to a health care practitioner in the last 4-weeks. When respondents were asked if they had visited a health care practitioner (includinghealer, pharmacist, nurse, and wife) in the last 4-weeks, 64.2% said yes. The health careinstitutions were public hospitals (34.8%); private hospitals (7.0%); public health care centres(14%); and private health care centre (51.6%). Twenty percent of the sample had healthinsurance coverage; 89.6% claimed at least good health (including 42.2% very good self-assessed health) compared to 1.9% who stated at least poor health (including 0.3% very poorhealth). A cross-tabulation of health care-seeking behaviour and illness shows no significantstatistical association. Ninety-seven percent of those who seek medical care were ill compared to94% of those who sought medical care in the last 4-weeks.A cross-tabulation between illness and age group revealed a significant statistical association – χ2= 39.4, P < 0.0001. Figure 4.1 provides the information on the age group and percentage ofyoung adults who indicated that they had an illness in the last 4-weeks. No significant statistical association was found between health care-seeking and agegroup (P = 0.608): age 15 – 19 years, 60%; age 20 – 24 years, 53.1%; age 25 – 29, 60.0%; age 30– 34 years, 67.7%; age 35 – 39 years, 68.0% and age 40 – 44 years, 69.%. 84
  • 102. No significant statistical relationship was found between health care-seeking behaviourand social hierarchy (P = 0.339): poorest 20%, 51.1%; poor, 69.2%; middle class, 67.4%;wealthy, 65.5%, and wealthiest 20%, 67.7%. There is a statistical difference between age of respondents who reported havingparticular health conditions – F-test = 4.5, P < 0.001. The mean ages of particular healthconditions were influenza, 29.3 years (SD = 9.2); diarrhea, 32.2 years (SD = 8.7); respiratory,30.3 years (SD = 9.6); diabetes mellitus, 37.3 years (SD = 5.9); hypertension, 36.8 years (SD =7.1) and other, 29.9 years (SD = 9.3). Figure 4.2 highlights young adult who reported injury (%) and illness (%) that dwelled inparticular area of residence controlled for sex of respondents. Figure 4.2 showed that over 50%of those with illness and injury dwelled in rural areas. However, there was no significantstatistical relationship when illness and injury by area of residence was controlled for by sex ofrespondents (illness – male χ2 = 2.6, P < 0.271 and female χ2 = 2.3, P < 0.323; injury – male χ2 =2.5, P < 0.292 and female χ2 = 0.93, P < 0.628). Figure 4.3 shows sex composition of those who utilised health care facilities in Jamaica.Most young adult males utilised private hospitals (36.4%) compare to females who visited publichealth care (72.7%). The least percentage of females visited private hospitals (63.6%) comparedto public health care centres for males (27.3%).Multivariate analysisTables 4.6 represent the results from the econometric exercise: Of the 24 variables that weretested in an initial model, 9 were social determinants and 1 a biological variable. Biologicalvariable (i.e. self-reported illness) accounted for 78.1% of the explanatory power of the model 85
  • 103. (i.e. 15.3%), indicating that the social determinants accounted for 21.9% of the self-assessedhealth status of young adults.Limitations of studyHealth is a function of social, psychological, economic, biological and ecological factors. Basedon the multi-dimensional nature of health determinants, the present study used secondary surveydata and variables such as psychological, ecological and some social issues; such as childhoodhealth history, culture, belief and value system were omitted from the model. Those omissionsreduced the explanatory power of the current study, but provide a platform with which futurestudies can be launched.DiscussionIn the present study, the prevalence of injury in Jamaica for young adults was 1% compared to8% in illness. A cross-tabulation between self-reported injury and self-reported illness showed asignificant statistical relationship. The association was a very weak one, correlation coefficient =0.12 (or 12%). Forty-one of every 100 young adults who reported having an injury stated thatthey had an illness in the last four-weeks, indicating that less than one- half percent of those withan injury had an illness. Concurrently, 2 times more young adult-females sought medical caremore than males. On the other hand, males were 2.3 times likely to record injury while femaleswere 2 times more likely to have an illness in the last 4-weeks. Furthermore, the odds ratio ofrecording better good self-assessed health status for males was 1.5 times more than that offemales. Outside of the gender differences in self-assessed health status, medical care-seekingbehaviour, and injuries, the odds ratio of recording good health married young adults was 1.6times more than their single counterparts and this was similar for peri-urban respondents withreference to rural young adults. On the other hand, a young adult who sought medical care was 86
  • 104. 65% less likely to record good health; young adults with tertiary level education were 47% morelikely to record good health and those who spent more on medical care (i.e. medical care-expenditure) were 1% less likely to have good self-assessed health status. Empirically, research has established that any investigation of health must coalescesocial, psychological, economic and biological variables [12-25, 32-37]. Hambleton et al. [12]went further when he disaggregated the contribution of biological and non-medical conditions ofself-assessed health status. They found that 87.7% of the explanatory power of good health statusof elderly Barbadians could be accounted for by current illness. The present study found thatcurrent illness accounted for 78.1%, which suggests that illness accounted for less of youngadults‘ health status than for elderly people. One of the challenges in effectively comparing theaforementioned issues (which is embedded in the data) is that the perception of people acrossdifferent nations are not the same, and this as well as the age component could account for someaspects of the disparity.. The present study has not only highlighted the role that socialdeterminants play in health status but also that they play a greater role in the health of youngeradults than old people. Statistics seemingly show a large percent of young adults being victims ofinjuries but the current findings indicate that these represent a small part of ill-health of youngadults. The small percent of injuries experienced by young adults denote that using injuries as aguide in health policy intervention would be addressing an even smaller percent of health statusthan illnesses. From the aforementioned results which show that illness contributes more tohealth status than social determinants, along with injuries. It is clear that despite the cultural andbiological differences rooted in both figures, current illness is a strong determinant of self-assessed health status in each region and if health must combine social, biological, psychologicaland ecological determinants, public health interventions that are using any one determinant in 87
  • 105. particular injuries would not be addressing the health concerns of young adults. This empiricalevidence concretizes the rationale for social determinants in the discussion and research onhealth status as well as ill-health. The finding in the present paper showed that social determinants of young adultsconstituted more explanation than for elderly. Therefore the usage of injuries and/or illness tomeasure and guide public intervention denotes that1 in 5 of the health status of young adultswould have been unaddressed in this effort and as much as 9 out of 10 of injury statistics areused in public policy interventions. Current social determinants of health for elderly Barbadiansaccounted for 4.1% of health and historical determinants, suggesting the increased role ofbiological determinant in the health process with ageing. Historical determinants which includededucation, occupation, children, economic situation, childhood nutrition, childhood health anddiseases theoretically is apart of social determinants. Disaggregating social determinants toascertain a value for historical determinants to compare with Hambleton et al.‘s finding in thispaper found that education was the only factor of those identified in the Barbadian health status,and that education accounted for only 0.3% of the explanatory model in this paper. Thereforewithin the limitations of the current study, meaningful comparison using disaggregated socialdeterminants would be close to impossible as the components are not necessarily the same. Inspite of the limitations of the current work, the study can effective compare self-assessed health status as both studies collected this from its population. The current study whichuses data for 2007 and Hambleton et al‘s work used data for December 1999 to June 2000showed that young adults‘ health was between 1.5 to 1.9 times more than that for elderlyBarbadians. Although there are time differences which cannot be discounted for in this paper,there is emerging information in the reduction of health status with ageing. Ageing is a nature 88
  • 106. event. Imagine purchasing a new car, taking this car home and locking it away in the car porchunder cover for 20 years; and on removing the covers although the item was not used, it wouldhave aged. On using the car however increases the deterioration or depreciation on the humanstructure, and therefore account for illness, health care utilisation and lowered health status Theissue of the car symbolizes the natural ageing and progressive depleted state of things and this issimilarly the case for humans. The current study revealed that as young people age, the oddsratio (OR = 0.97) of indicating good health falls by 3% and using the aforementioned statisticswould mean that odds ratio of good health for elderly people should fall. A study by Bourne,McGrowder and Crawford [38] showed that illness affecting elderly Jamaicans was more chronicthan acute compared to the converse in this paper. With the changes in the typology of illnessesfrom acute to chronic conditions, the elderly‘s health status must be lower than that for youngadults. Hence although homicides accounted for more deaths of young adults that elderly people,the health status of the former is still greater and this is due largely to lower risk of biologicalconditions. Again the biology of an individual accounts for greater percentage of self-assessedhealth than external factors such as injuries from accidents. Injuries from accident affect 1 inevery 100 young adults, making its effect on health smaller than illnesses which accounts for 8 inevery 100 young adults.With biological conditions accounting for more of self-assessed health ofolder people, this supports lower health status than young adults and greater health careparticipation for the former as they seek to address the ageing of the organism and the increaseddepreciation owing to old age. Gompertz‘s law in Gavriolov and Gavrilova [39] shows that there is a fundamentalquantitative theory of ageing and mortality of certain species (the examples here are as follows –humans, human lice, mice, fruit flies, and flour beetles. Gompertz‘s law went further to establish 89
  • 107. that human mortality increases twofold with every 8 years of an adult life, which means thatageing increases in geometric progression. This phenomenon means that human mortalityincreases with age of the human adult, but that this becomes less progress in advance ageing.Thus, biological ageing is a process where the human cells degenerate with years (i.e. the cellsdie with increasing in age), which is explored in evolutionary biology [40-43]. But studies haveshown that using evolutionary theory for ―late-life mortality plateaus‖, fail because of thearguable unrealistic set of assumptions that the theory uses to establish itself [44-46]. Ageing therefore denotes gradual deterioration in living organisms as well other non-living items, which accounts for demand in medical care. Medical seeking-behaviour couldindicate either preventative or curative care. The present study revealed that the odds ratio ofgood health of young adults in Jamaica decline by 65% for those who seek medical care.Medical care for young adults therefore is a good measure of curative than preventative care.This also speaks of the cultural impact on health through people‘s conceptual perceptions ofhealth; that health is illness and so care is sought for ill-health as against preventative care. Thecurrent work revealed that 94 out of every 100 young adults who sought medical care were ill;reinforcing the cultural perception of illness and the reason why young adults seek health-care iscurative than preventative for this group. Illness in the current work is substantially a female phenomenon. Young adult femaleswere 2 times more likely to report an illness, and this justifies their greater probability to utilizemedical care seeking in order to address ill-health. These findings have a high degree of validityas statistics from the Ministry of Health (Jamaica) showed that females attended health careinstitutions twice as much as men for curative care since 2000-2007 [9]. Since 1988, statisticsobtained from Jamaicans in national cross-sectional surveys revealed that females were 90
  • 108. approximately more likely to report an illness and utilize medical care than males. Thisreinforced the cultural biasness of illness and health care facilities. Health care facilities areprimarily governed by females for females and this adds to cultural handicap of males affordattending public health care institution on experiencing ill-health. , The feminization of healthcare facilities and the large percent of people in particular females who utilise public health careinstitution is another rationale for males use of private health care facilities. Males on the otherhand will attend medical care facilities when ill-health interfaces with their economic livelihoodand the severity is such that this is the only avenue. This is not atypical to Jamaica as aqualitative study in Pakistan on street children found that boys would attend formal health care ifit affects their economic livelihood and health conditions were severe [47]. Another studyconducted in Anyigba, North-Central, Nigeria found that [48] found that 85 out of every 100respondents waited for less than a week after the onset of illness to seek medical, and that 57 outof every 100 indicated that they would recover without treatment. A Caribbean anthropologist [49] stated that the macho socialisation of the Caribbeanmale accounts for his unwillingness to seek medical care. Caribbean males including Jamaicansare socialised to be strong, do not show weakness, and be involved in particular tasks to exhibittheir masculinity as a result illness is a signal of weakness, therefore accounting for the reasonswhy they are skeptical to visit medical institutions and often times wait for severity. On visitingmedical practitioners, it is sometimes so difficult for traditional medical practioner to offer cure.This then offers an explanation for females living longing than males. Although the currentfindings showed that the odds of recording good health is 1.5 times greater for young adultmales, apart of this is owing to the reality that often times males do not see themselves as ill,visit medical practitioner less and justifies the higher mortality among them than females. The 91
  • 109. social determinants are therefore offering explanation for the biological issues as well,challenges to implement health interventions to improve health of young adults in particularmales are great as definition of illness and severity of symptoms reduce the quality of life ofpeople and this finding concurs with a previous study by Williams et al. [50]. Unlike this paper,Williams et al. [50] found that medical care-seeking behaviour did not differ significant betweenthe sexes, with this paper finding the opposite. Like this paper, Dunlop et al [51] found thatAfrican American men had few physician contacts than minority and non-Hispanic whitewomen. The irresponsiveness of young adult males in seeking health care comparable to theirfemale counterparts in Jamaican extends to even older African American men. With the advancement in literacy and numeracy in the world since the 19th century,specifically in Jamaicans since 1960 (i.e. educational levels), empirical findings showededucation is among the social determinants that influence health status [12-26]. Education affectshealth directly and indirectly. A study on twins in USA found that more years in schooling (i.e.education) was associated with healthier patterns of behaviour. [52], which is an example of thedirect impact of education on health. In the Fujiwara & Kawachi [52] work on increasedschooling was associated with reducing smoking habit and other such healthier practices. Thecurrent study concurs with the literature as the odds ratio of good health status of young adultswith tertiary level education are 1.5 times more than those with primary or below education. Theindirect way that education affects health can be measured using social hierarchy. The presentfindings revealed that the middle class who are the educated ones were 1.5 times more likely toreport good health status and that wealth or income was not correlated with good health status orfor that matter the self-assessed health status of wealthy social hierarchies did not differ fromthose in the poor social hierarchies. 92
  • 110. Empirical evidence existed that among the social determinants of health is marital status.Some research showed that married people are healthier than non-married people [12-25, 53-58].Koo, Rie and Park [54] findings revealed that being married was a ‗good‘ cause for an increasein psychological and subjective wellbeing in old age. Smith and Waitzman [55] offered theexplanation that wives found dissuade their husband from particular risky behaviours such as theuse of alcohol and drugs, and would ensure that they maintain a strict medical regimen coupledwith proper eating habit [53, 56]. In an effort to contextualize the psychosocial and biomedicalhealth status of particular marital status, one demography cited that the death of a spouse meant aclosure to daily communicate and shared activities, which sometimes translate into depressionthat affect the wellbeing more of the elderly who would have had investment must in a partner[57]. They pointed to a paradox within this discourse as ―…this is not observed among men‖.To provide a holistic base to the argument, the researcher will quote a sentence from the findingsof Delbés and Gaymu [57] study that reads ―The widowed have a less positive attitude towardslife than married people, which is not an unexpected result [57]. The present study concurs withthe literature that the health status of married young adults is greater than those who are single,but that this was only explained by females. Those findings highlight the value of marriage tofemales which commences at an early age, and seemingly that the benefits of marriage are notfor males. This is clearly not the case as study by Bourne [58], using data on Jamaicans, foundthat the odds ratio of reported good health was 1.6 times more for married males than theirfemale counterparts. 93
  • 111. Conclusion and policy recommendationsIn sum, statistics for 2007 revealed one in every two Jamaicans was 15-44 years old. This speaksto the importance of a research on this age group. With the demographic reality of young adultsin the country, using injury to examine health is grossly inadequate, narrow and fails tounderstand the matter of health. Health is more that illness as it incorporates social, economic,psychological, ecological and biological determinants. While the biological determinant of self-assessed health of young adult predominates health determinants, injury accounts for a minisculepercentage of illness and so using injury to formulate intervention policies would be lacking indepth to effectively address health of this cohort. Although the health of young adult Jamaicansis very good, there are many health disparities between the sexes which are justifying inequitiesin health outcomes between males and females. The present study highlights some of the health disparities between the sexes and affordsresearch findings that can be used to refashion health policies and research focus in the future.Health policies must utilize the wide spectrum of health determinants in order to address themulti-dimensional nature of health. The use of injuries to measure and guide policies andprogrammes because seemingly there are many young adults who are affected is a misnomer anddoes not capture the gamut of illness or even health of this group of people. The identified health disparities are among reasons for health inequities in healthoutcome, and should justify a call for a research and policy direction that include avoidabilitiessuch as technical, financial and moral as these would provide additional explanations for healthdisparities, choices, inequity and/or inequalities in health outcomes among young adults. 94
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  • 115. 56. Ross, C. E., J. Mirowsky, and K. Goldsteen. 1990. The impact of the family on health. Journal of Marriage and the Family 52:1059-1078.57. Delbés, C., and J. Gaymu. 2002. The shock of widowed on the eve of old age: Male and female experience. Demography 3: 885-914.58. Bourne PA. Self-evaluation of health of married people in Jamaica. (in review) 98
  • 116. Figure 4.1: Illness (%) by age group 99
  • 117. Figure 4.2: Area of residence of those with Injury (%) and Illness (%) controlled for by sex 100
  • 118. Figure 4.3. Sex composition of those who attend health care facilities 101
  • 119. Table 4.1: Treatment for Gunshot wounds at the Accident and Emergency Depts. Of PublicHospitals by Gender and Age cohort (in %): 1999-2002Age cohort Year 1999 2000 2001 2002 Male Female Male Female Male Female Male Female< 5 years 0.8 1.3 0.2 3.1 0.2 0.0 0.0 0.05-9 years 0.3 3.0 0.7 1.9 0.3 1.1 0.3 0.610-19 years 17.9 24.5 16.2 18.5 10.2 17.0 13.9 17.020-29 years 39.0 32.5 40.5 30.2 35.8 19.4 36.6 35.230-44 years 30.6 23.6 31.1 11.1 32.3 26.9 29.3 32.145-64 years 6.6 12.2 6.7 28.4 10.7 22.3 8.9 11.365+ years 3.5 3.0 2.3 11.1 6.7 12.7 8.8 3.6Not unknown 1.4 0.0 2.2 1.2 3.8 0.7 2.3 0.6Total % 100 100 100 100 100 100 100 100Calculated by Paul A. Bourne from Annual Report, 2002 published by the Policy, Planning andDevelopment Division, Ministry of Health, Jamaica 102
  • 120. Table 4.2: Visitation to the Accident and Emergency Depts. Of Public Hospitals for attemptedsuicide by Gender and Age cohort (in %): 2000-2002Age cohort Year 2000 2001 2002 Male Female Male Female Male Female< 5 years 0.0 0.0 1.0 0.0 1.0 0.95-9 years 0.0 3.4 2.0 0.0 2.0 3.510-19 years 19.0 39.3 13.0 49.4 13.0 38.320-29 years 24.1 36.0 20.0 34.8 20.0 36.530-44 years 34.5 13.5 13.0 6.7 13.0 17.445-64 years 12.1 2.2 4.0 3.4 4.0 0.965+ years 6.9 3.4 4.0 2.2 4.0 0.0Not unknown 3.4 2.2 0.0 3.4 1.7 2.6Total % 100 100 100 100 100 100Calculated by Paul A. Bourne from Annual Report, 2002 published by the Policy, Planning andDevelopment Division, Ministry of Health, Jamaica 103
  • 121. Table 4.3: Victims of Major Crimes by Age Cohorts, 2005 Age Group Carnal Murder Shooting Robbery Breaking Rape Abuse Age Group Male Female Total Male Female Total Male Female Total Male Female Total Female Female0-4 2 4 6 3 1 4 0 0 0 0 0 0 3 35-9 3 5 8 0 5 5 1 0 1 0 0 0 27 1510-14 10 8 18 4 11 15 16 11 27 0 6 6 212 22315-19 122 18 140 107 13 120 59 49 108 8 17 25 223 10320-24 268 23 291 212 30 242 162 115 277 52 75 127 122 025-29 252 33 285 192 22 214 233 130 363 81 106 187 48 030-34 223 22 245 161 16 177 198 112 310 114 115 229 28 035-39 177 17 194 138 15 153 199 102 301 140 104 244 23 040-44 139 12 151 107 15 122 171 77 248 116 107 223 17 045-49 72 16 88 68 5 73 146 44 190 98 75 173 12 050-54 46 9 55 46 8 54 98 32 130 75 47 122 7 055 & Over 81 16 97 50 6 56 152 66 218 171 100 271 16 0Unknown 91 5 96 408 3 411 28 9 37 32 14 46 8 2Total 1486 188 1674 1496 150 1646 1463 747 2210 887 766 1653 746 346Total Reported 1674 1646 2210 1653 746 346Source: Statistics department, Jamaica Constabulary Force 104
  • 122. Table 4.4: Age Group of Persons Arrested for Major Crimes for 2005 Age Group Murder Shooting Robbery Breaking Rape C/AbuseAge Group Male Female Total Male Female Total Male Female Total Male Female Total Male Male Total12-15 6 1 7 4 0 4 10 0 10 54 0 54 12 11 9816-20 157 6 163 167 1 168 183 0 183 122 3 125 66 43 74821-25 235 8 243 239 1 240 214 1 215 129 3 132 68 52 95026-30 160 2 162 137 0 137 120 1 121 105 3 108 73 27 62831-35 85 1 86 74 0 74 71 1 72 93 2 95 48 26 40136-40 54 3 57 40 1 41 36 1 37 69 0 69 23 19 24641-45 15 0 15 12 0 12 13 0 13 44 1 45 18 12 11546-50 7 1 8 2 0 2 1 0 1 18 0 18 12 5 4651-55 5 1 6 0 0 0 2 0 2 2 0 2 3 2 1556-60 1 0 1 1 0 1 6 0 6 1 1 2 1 1 1261& Over 0 0 0 2 0 2 2 0 2 3 1 4 2 0 10Unknown 40 0 40 86 0 86 23 0 23 11 0 11 10 0 170Total 765 23 788 764 3 767 681 4 685 651 14 665 336 198 3439Source: Statistics department, Jamaica Constabulary Force 105
  • 123. Table 4.5. Particular variables by sex of respondents Sex PVariable Male (%) Female (%) n = 1,439 n = 1,585Injury 0.037 Yes 1.4 0.6 No 98.6 99.6Illness Yes 5.3 10.5 < 0.0001 No 94.7 89.5Self-assessed health status < 0.0001 Very good 44.8 39.8 Good 47.5 47.4 Moderate 6.3 10.4 Poor 1.1 2.2 Very poor 0.4 0.2Health care-seeking behaviour < 0.0001 Yes 3.5 6.8 No 96.5 93.2Household head < 0.0001 Yes 34.1 73.0 No 65.9 27.0Union status 0.103 Married 12.1 15.1 Common-law 19.7 21.0 Visiting 28.1 26.2 Single 30.8 28.9 Not stated 9.3 8.7Self-reported diagnosed health condition 0.289 Acute: Influenza 12.9 12.7 Diarrhoea 6.5 1.4 Respiratory 16.1 13.4 Chronic: Diabetes 6.5 8.5 Hypertension 11.3 21.1 Arthritis 1.6 3.5 Other (unspecified) 45.2 39.4Area of residence 0.756 Urban 32.2 31.9 Peri-urban 21.4 22.5 Rural 46.4 45.6No. of visits to health care facilities Mean (SD) 1.2 (0.5) 1.5 (1.3) 0.144Age Mean (SD) 28.4 yrs (8.8) 28.5 yrs (8.9) 0.746Medical expenditure Mean (SD) in US $ 16.67 (42.01) 16.42 (26.82) 0.971†US$ 1.00 = Ja. $ 80.47 106
  • 124. Table 4.6. Logistic regression: Explanatory variables of good health status, n = 2, 832 Explanatory variable Std. P R2 Error Odds ratio 95.0% C.I. Social determinants: Age 0.01 0.97 0.96-0.99 < 0.0001 0.004 Crowding 0.03 0.95 0.90-1.00 0.043 0.003 Tertiary 0.28 1.47 1.27-1.81 0.007 0.003 †Primary 1.00 Male 0.14 1.45 1.11-1.91 0.007 0.006 MiddleClass 0.18 1.45 1.02-2.07 0.041 0.003 †Poor classes 1.00 Married 0.21 1.63 1.09-2.43 0.018 0.004 †Single 1.00 Other town 0.18 1.61 1.12-2.30 0.009 0.005 †Rural 1.00 Medical expenditure 0.00 0.99 0.99-1.00 0.017 0.006 Health care- seeking 0.29 0.35 0.20-0.62 < 0.0001 0.009 Biological condition: Self-reported illness 0.24 0.17 0.11-0.28 < 0.0001 0.153Hosmer and Lemeshow goodness of fit χ2 = 4.4 (8), P = 0.82-2LL = 1615.7Nagelkerke R2 =0.196†Reference group 107
  • 125. Chapter 5Quality of Life of Youths in Jamaica Paul Andrew BourneThe current study seeks to examine the quality of life (QoL) of Jamaican youths and to build amodel that will identify its predictors. A multistate probability sample of some 1,338respondents. Data were collected using a 166-item questionnaire. Of the sampled population(N=1,338), the proportion of those respondents age 18 to 25 years was 27% (N=364) and thisconstitutes the sample for the current study. The data were stored and retrieved in SPSS 16.0.Descriptive statistics were used to analyze the data, and logistic regression was used to establishthe model. The power of the study is 0.98 assuming a 95%CI and an alpha of 0.05, whichindicates that the research can detect the differences in people who are classified in the referencegroup (ie. low QoL) and those in moderate to high group. Quality of life of Jamaican youths isdetermined by 4 factors. These factors explain 20% of the variability in quality of life, parent‘seconomic wellbeing has the most influence on the quality of life of Jamaican youths(OR=2.022;95% CI: 1.35, 3.04) followed by moderate religiosity (OR=2.756; 95% CI: 1.47,8.82) and the extent of the welfarism of the state (OR=1.329; 95% CI: 1.04, 1.69); highreligiosity (OR=3.594;95% CI: 1.465, 8.815) and sex (OR=2.011;95% CI: 1.016, 3.280). Thecurrent work offered an understanding of explanatory factor of QoL of youths; and this can beused in public health planning.IntroductionStudies on quality of life (QoL) have substantially been on the adult population (1-12) with someemphasis on the elderly (13-25). Research on the Caribbean have primarily examined QoL of theelderly (14), (16-26) and outside of those scholars, studies have also examined population‘swellbeing (27-28), QoL of sickle cell patients (28) and QoL of Jamaican women (30). Given thatyouths constitutes one-quarter of the nation‘s population, what about their QoL? Scholars likeHerbert Gayle (31); Gayle, Grant, Bryan, Yee-Shui, & Taylor (32); Chevannes & Gayle (33), 108
  • 126. and Chevannes (34) have examined some aspect of life of youths in Caribbean in particularJamaica but they have done so from the perspective of a sectorial qualitative methodology.Those who have used quantitative methodology (ie. survey research) like Lipps, Lowe, Halliday,Morris, & Clarke (35); Lipps, Lowe, Morris, Clarke, & Halliday (36); Anglin-Brown, Weller, &Mullings (37); Anderson (38), Bourne (39) have not examined the general QoL of this cohort. Having pursued a plethora of literature and research on QoL in the Caribbean, in Jamaica,it was realized that there is a dearth of studies on the quality youths in general. Youthsconstitutes a significant segment of the working age population (i.e. productive population –people ages 15 through 60 years) and equally important about this age cohort is the fact that itrepresents the future of any nation. Ergo, we cannot deny the importance of this age cohort tocurrent and future development, health of the workforce and population, and QoL of this groupmust be crucial to clinicians, medical practitioners and policy makers. It is within this context,that this paper seeks to fill the gap in the literature by examining the QoL of Jamaican youths andsecondly to build a model that will identify factors that will explain their QoL. QoL is widely accepted by medical researchers and clinicians as an alternative paradigmto dysfunction in the measurement of health and treatment of health-care of customers (i.e.patients) (40-41). The rationale for this paradigm is owing to its maximization perspective (42-43). Many scholars including economists such as Sen (44-45); Easterlin (5-6); Stutzer & Frey(3); Di Tella, MacCulloch & Oswald (46) have proposed that QoL (or wellbeing) mustincorporate subjective as well as objective conditions. They contend that any construct whichmay be used to capture QoL (or wellbeing) must be such that it embodies economic wellbeing(i.e. Gross Domestic Product per capita growth) and emotional reactions to events as they are a 109
  • 127. part of the whole life of an individual. This argument is also forwarded by psychologists such asEdward Diener (11), Richard Veenhoven (9), that justify their use of happiness or self-reportedoverall QoL to assessment wellbeing (3), (5-6), (9), (11-12). In order to assess overall QoL of an individual, it is argued that the ‗best‘ approach to betaken in this regard is to use a questionnaire that will collect information from people onparticular aspects of their lives and overall QoL (1), (47-50). Kashdan (49) writes that theassessment of subjective wellbeing (or QoL) can be addressed with a questionnaire on happinesswhich the aforementioned literature has outlined as the proposition of other scholars. Murphy &Murphy and Hutchinson et al, on the other hand, believe that QoL assessment can be done byway of self-reported satisfaction with life and subjective assessment of the life by the individual.A part of this assessment was self-esteem; self-achievement (or actualizations) which areembodied in Abraham Maslow‘s 5 hierarchy of Needs. Michael Pacione (50) opines that ―Thesimplest model states that satisfaction with life in general is weighted sum of satisfactions withdifferent domains or aspects of life(for example, job satisfaction) and that, in turn, these domainsatisfactions are weighted sums of specific satisfiers and dissatisfiers…A more complexformulation is the hierarchy of needs of model…‖ (2003, 23).50 Cummins (47), on the otherhand, provides a contravening argument to the view of Pacione that needs must not be used as anassessment of life‘s quality of an individual. He argues that the drawback to the use of needs isembedded in the fact that low degree of needs does not necessarily associate with QoL. Hence,Cummins‘ delimitation will not hold in the event that needs are at moderate or high evaluations. The rationale for this paper is embodied in three main issues. One, the highest rate ofcrime affects this age cohort (ages 18 to 25 years); and two, traumatic incidence of this group is 110
  • 128. high. Thirdly, with the two aforementioned issues identified, why have researchers who omittedthe QoL of this age cohort? This age cohort is equally vulnerable to specific risk of their own(ie. high crime and victimization, high teenage pregnancy, high unemployment) like children(ages 0 to 15 years) and elderly (60 years and older) do; and a research on the QoL of this agegroup will provide invaluable information about this group‘s wellbeing status. In order toestablish a model that can simultaneously examine and provide possible factors that influenceQoL, this paper uses econometric analysis – multivariate analysis- which has been use by otherscholars like Michael Grossman, and Smith & Kingston (see Theoretical Framework) to dosimilar studies.Theoretical FrameworkAn econometric model that was developed by Grossman (10) to evaluate wellbeing in keepingwith WHO‘s definition of wellbeing (8) expanded and modified the Grossman‘s model, whichreads: Ht = ƒ (Ht-1, Go, Bt, MCt, ED) ……………………………………………………..[1] In which the Ht – current health in time period t, is a function of stock of health (Ht-1) inprevious period, Bt – smoking and excessive drinking, and good personal health behaviours(including exercise – Go), Mc,- use of medical care, education of each family member (ED), andall sources of household income, including current income (8). Grossman model encapsulatesbiological conditions, psychological and socioeconomic factors. According to Smith & Kington (8), using Ht= f (Ht-1, Pm Go, Bt, MCt ED, Āt, ) toconceptualize a theoretical framework for ―stock of health‖ noted that health in period t, Ht, isthe result of health preceding this period (Ht-1), medical care (MCt), good personal health (Go), 111
  • 129. the price of medical care (Pm), and bad ones (Bt), and a vector of family education (ED), and allsources of household income (Āt). Embedded in this function is the wellbeing that individualenjoys (or not enjoy) (8). Hence, this paper will be guided by econometric analysis. Secondly, we will use asimilar model like that offered by Grossman, or Smith and Kington to carry out the currentmodel that will be tested as follows:QoLi = ƒ(REi, Wi , RAi, PPIi, AR i, Xi , SSi, Ci , ESi, TIi, Oi, Ai, Ei, ESi,, εi) ………………[2]Where QoLi is the QoL of youths i which is a function of religiosity, REi , welfare index ofyouths i, Wi, race of youths i, RAi, political participation index of person i, PPIi , area ofresidence of youths i, AR i, gender of youths i, Xi , subjective social class of youths i, SSi,confidence in sociopolitical institution index of youths i, Ci, economic situation of youths i, ESi,interpersonal trust of person i, TIi, occupation of person i, Oi , age of person i, Ai , educationallevel of person i, Ei, employment status of person i, ESi,MethodDuring the months of July to August 2006, the Centre of Leadership and Governance,Department of Government (CLG), The University of the West Indies, Mona Campus,conducted a stratified probability sample of 1,338 respondents. The sampling design used for thestudy was that which used by the Statistical Institute of Jamaica. The survey was the first of itskind as it collected data on Jamaican‘s Political Culture. The themes ranged from democracy;civic culture; trust and confidence; perception of wellbeing using Abraham Maslow 5 NeedsItem; preference for private or public sector solving problems in the economy; politicalparticipation and civic engagement; and, leadership, party, and electoral preferences. Face-to-face interviews were used to collect the data on an instrument which took about 90 minutes. Theinstrument consisted of 166 items that were taken from Latinobarometer and Eurobarometercross-cultural survey; the American National Election Studies series; the Harvard/WashingtonPost Leadership survey, the New Zealand Election Surveys and the Cross-cultural Variations inDistributive Justice Perception survey and Carl Stone surveys. The instrument was vetted bysenior scholars, researchers as well as by interviewers within the data divisions of the StatisticalInstitution of Jamaica (STATIN) and Social Development Commission (SDC). After the vettingphase, the questionnaire was pretested in a number of communities across the 14 parishes ofJamaica as well as among UWI faculty and the student population. Modifications were made at a 112
  • 130. training symposium based on the comments of the different interviewers and remarks of trainedresearchers. All the interviewers employed by the CLG‘s team were either data collectors bySTATIN or SDC. Although the interviewers are trained data collectors, they were trained by the CLG teamfor a 3-day period. Dr. Lloyd Waller (project manager of the CLG) was assigned to travellingacross the entire island as a verifier of the interviewers‘ collection of the information fromJamaicans. Furthermore, a part of this paper was to examine Jamaicans‘ QoL, and so questions(needs, physiological needs, social needs, self-esteem and self-actualization) were placed on theinstrument that examined respondent‘s perception on Abraham Maslow‘s 5 Needs hierarchymodel. Prior to data entry, a data template was created by Senior Researcher in the Departmentof Government; Dr. Alfred Lawrence Powell also trained and familiarized the data-entry clerksto the instrument. The data were entered by trained data-entry clerks who are employed in theDepartment of Sociology, Psychology and Social Work. Three different groups independentlyentered the data and these were cross-reference by Paul Andrew Bourne, a demographer andreviewed by Alfred L. Powell for accuracy. Both Bourne and Powell were responsible for thecleaning and validation process of the entered data. Data were stored and retrieved in theStatistical Package for the Social Sciences (SPSS 12). The sampling error was ±3% at the 95%confidence level (i.e. CI). This was done to aid the external validity of the survey, as well as toenhance the associational and inferential statistics. Cronbach alpha was used to test the internalreliability of QoL (ie QoL), which was a 5-item Likert scale question. The Cronbach alpha forQoL was 0.841. Descriptive statistics were used to analyze the data, and logistic regression (ieenter method) was used to establish the model. The dependent variable was QoL and there were14 explanatory ones that included religiosity, the welfare state and so on (Eq (2)). Of thesampled population (N=1,338), the proportion of those respondents age 18 to 25 years was 27%(N=364) and this constitutes the sample for the current study. The overall response rate for thesurvey was 95.7% and that of the youths was 96.4%. The power of the study is 0.98 an alpha of0.05, which indicated that the research can detect a 10% difference in people who were classifiedin the reference group (ie. low QoL) and those in moderate to high group. The correlation matrix was examined in order to ascertain if autocorrelation and/ormulticollinearity existed between variables. Based on Cohen and Holliday17 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. Any correlation that had at least moderate was excluded fromthe model in order to reduce multicollinearity and/or autocorrelation between or among theindependent variables.18-24 Another approach in addressing and/or reducing autocorrelation, is allvariables that were identified from the literature review were included in the model with theexception of those with which the percentage of missing cases were in excess of 30%. 113
  • 131. MeasureQoL is defined as the overall self-reported life satisfaction of an individual. It is measured as themean summation of 5-item need from Abraham Maslow‘s hierarchy. These items were safetyneeds, physiological needs, social needs, self-esteem and self-actualization. Each item was on a10-point Likert scale. Using Cronbach alpha for the five-item scale, reliability was 0.841 (or α =84%). Hence;QoLi = 1/5*∑Ni where i is each need (i.e. i=1, 2, 3, 4, 5)where the QoL index is: 0≤QoLi ≤10. The index valuations are low (where the values can beinterpreted as low (i.e. 0 to 3); moderate (i.e. 4 to 6) and high (i.e. 7 to 10). For the purpose ofthe logistic regression, the dependent variable, QoL, was dummied where 1 (ie Yes)= moderateto high QoL, 0 (ie. No)=otherwise or low.Welfare Index, W. This variable is indexed of the extent of individual‘s or government‘sresponsibility for particular functions within a society. The functions vary from health care,employment and retraining, adequate housing, child-care assistance, replacement income due toloss of job owing to accident, retirement income, disability assistance, and educational assistancefor tertiary training. Each function is on a 10-point Likert Scale, where 1 being the lowest istotally the individual‘s responsibility and 10 being the highest is solely the government‘sresponsibility. Hence, the Welfare Index is the mean summation of the 15-question, 10-pointLikert Scale response. The minimum score is 1 and the maximum is 10.Political Participation Index, PPI. This is the extent of someone‘s involvement in conventional(road blocks, demonstrations, protest, riots etc) or unconventional political activities (internetblogging, etc). PPI = Σbi, bi ≥ 0, and bi represents each ‗yes‘ response to a question on politicalbehaviour, such as voting, involvement in protest which is given a value of 1 and a ‗no‘ wasgiven a value of 0 - 0≤PPI≤19.Results: Sociodemographic Characteristics of SampleOf the sampled population (N=364), 96.4% responded to the question of gender (N=351). Ofthose who indicated as gender, 57.3% (N=201) were females compared to 42.7% (i.e. N=150)males. The mean age of the sample was 21.6 years (SD=2.3 years) (Range =7 yrs: 18 to 25years). Approximately one-half of sampled population had at most secondary level education 114
  • 132. (54.1%, N=191), with 27% (N=94) having had tertiary level education. Furthermore, marginallymore of the sampled population revealed that they are of the working class (53%; N=186), with44% (N=154) indicated being of the middle class. (Table 5.1) One-half of the population had a QoL of 7.2 out of total index of 10, with mostrespondents having a QoL of 7.6 out of 10. Using Analysis of Variance (i.e. ANOVA) is thereno statistical difference between the mean wellbeing of youths, other adults and elderly. Themean wellbeing of youths (N=364, 29.9%) was 6.9 ±1.7(SD); for other adults (N= 810, 64.4%)6.8 ± 1.8(SD), and elderly (N=83, 6.6%) 7.0 ± 1.7 (SD), with F-test (3, 1259) = 0.699, P= 0.552> 0.05. Insert Table 5.1 hereMultivariate AnalysisFrom the observed survey research data, using econometric analysis, we will test the function asfollows:QoLi = ƒ(REi, Wi , RAi, PPIi, AR i, Xi , SSi, Ci , ESi, TIi, Oi, Ai, Ei, EMi,, εi) ………………....[1]Where QoLi is the QoL of youths i which is a function of religiosity, REi , welfare index ofyouths i, Wi, race of youths i, RAi, political participation index of person i, PPIi , area ofresidence of youths i, AR i, gender of youths i, Xi , subjective social class of youths i, SSi,confidence in sociopolitical institution index of youths i, Ci, economic situation of youths i, ESi,interpersonal trust of person i, TIi, occupation of person i, Oi , age of person i, Ai , educationallevel of person i, Ei, employment status of person i, EMi, Using the principle of parsimony, only those variables that are statistically significantwill be used in the final model (i.e. P< 0.05) – Model 2. Hence, Model 2 is as follows:QoLi = ƒ (REi, Wi , Xi , ESi, εi) ………………………………………………….…………....[2] 115
  • 133. The final model (Model 2) explains 20% of the variance in QoL of respondent who is ayouths. Four variables account for the QoL of youths, and these factors are religiosity, extent ofthe welfare index, gender, and economic situation of the youths‘ parents. The most influentialfactor of the 4-variable is the economic situation of the youths‘ parents (Wald Statistic = 11.562;95%CI: 1.348, 3.035; P= 0.001), followed by religiosity (Table 5.2); extent of the welfare systemof the nation (Wald statistic=5.27; 95%CI: 1.043, 1.694; P= 0.022); and last by gender ofrespondent (Wald statistic =4.021; 95%CI: 1.016, 3.980; P= 0.045). Embedded in this finding (Table 5.2) is the influence of a respondent‘s family economicsituation on his/her QoL. It follows that a respondent, whose family‘s economic resource is low,will have a lower QoL compared to his/her counterpart whose family has more economic wealth.This means that a youths‘ QoL is substantially determined by his/her parent‘s economicwellbeing. Another important finding of the current study is the role of state in the QoL ofyouths. The extent of the welfarism of the state was the third most influential factor on QoL of ayouths. We must highlight here that external conditions such as parental economic condition andwelfarism of a nation in which youths reside play a pivotal role in his/her QoL compared tohis/her own internal conditions such as age, religiosity and the gender of the respondents. Despite the fact that internal conditions (i.e. personal characteristics) of the youths play asecondary role to the external characteristics as stated in the aforementioned paragraph, we stillmust examine the significance of personal conditions except that of religiosity. Based on Table5.2, a youths who has a high religiosity has a QoL that is 3 times (Odds Ratio=2.756) more thana youths who has a low religiosity. On the other hand, a respondent who has a moderatereligiosity has a QoL that is 4 times (Odds Ratio= 3.594) greater than that of a youths who has alow religiosity. Thus, a respondent who has a low religiosity has the least QoL, whereas one with 116
  • 134. moderate religiosity had the greatest QoL. It follows that frequently attending church (i.e.outside of christening, baptism, funerals, graduations, weddings) does not indicate higher QoL.However, religiosity is positively associated with QoL of youths (Table 5.2). Insert Table 5.2 here Generally there are no statistical difference between the QoL of youths (6.9 ±1.7 (SD;95%CI: 6.7, 7.1), other adults (6.8±1.8 (SD; 95% CI:6.7, 6.9) and that of elderly Jamaicans (7.0± 1.7 (SD; 95%CI: 6.6, 7.4) – pvalue > 0.05 (Table 5.3). Based on the findings in Table 5.3, theQoL of youths in Jamaica was 6.9. Is there a difference by gender? Further examination of theQoL of youths revealed that the QoL for male youths was greater than that of their femalecounterparts (Table 5.2). Using t-test analysis, on an average the QoL of male youths was 7.2 outof 10 ± 1.6 (SD, N=148) compared to the mean QoL of females being (6.7 ± 1.7(SD) – 2-tailedtest; P= 0.008) (Table 5.4). We wanted to provide a complete understanding of the differentquality of life component, which include safety needs, physiological needs, social needs, self-esteem and self-actualization. Deconstructing the sub-tenets of QoL revealed that malerespondents on an average (7.03 ± 2.5 (SD); p value = 0.003) had greater safety needs comparedto their female counterparts (6.16±2.7 (SD); a similar difference exist between basic needs of thesexes. Using t-test, we found that males had a higher value at basic needs (6.46 ±2.4 (SD); pvalue = 0.03) compared to females (5.86±2.6 (SD); p value =0.03). This was also the case forself-esteem, where on an average males reported a greater self-esteem (7.81±1.9 (SD); p value=0.046) to females (7.38 ± 2.0 (SD); p value 0.046). We found no statistical difference betweensocial needs and QoL, and self-actualization and QoL (P> 0.05). 117
  • 135. Insert Table 5.4 here We need to examine the disparity of QoL of the sexes; and explore its rationale. Wefound that 15.6% more male youths were employed (i.e. 71.3%) compared to their femalecounterparts (55.7%), with 4% less males being unemployed (13.3%) compared to females(17.4%). In addition, approximately 2 times more females (i.e. 25.9%) reported being studentscompared to their male counterparts (15.3%). Based on the aforementioned issue, it is notsurprising that males will have a higher QoL than females. Embedded in these findings is therole the family plays in the QoL of youths. The fact that the parents young males are morequalified at the tertiary level this them with greater QoL as they are a part of a household with abetter QoL compared to young females. Hence the educational attainment of these youths isinterlocked with that of the household and positive association between educational attainmentand QoL will change in the future. However, the fact that more male youths are employed thanfemales still does give them a greater current QoL than females and reiterates the role of thehousehold as well as the state in improvements of their QoL. The above mentioned issues are secondary as can be seen from model; hence, we mustevaluate the parental background with the sexes. In so doing, we found that there was nostatistical difference between the educational level of youths and their fathers – i.e. 13.6% maleyouths and 13.7% female youths (i.e. P= 0.802). Whereas, the educational level of the males‘youths mother is approximately 4% more at the tertiary level (16.7%) compared to youthsfemales‘ mothers (i.e. 13.2%). However, it should be noted here that there is no statisticaldifference between 16.7% and the 13.2% (P>0.05). Statistics from the Jamaica Survey of LivingConditions have shown an increase in the number of female headed households from 44.7% in2001 to 46.7% in 2006 compared to male headed households; and when the figure was 118
  • 136. deconstructed by Area of residence, it was as high as 55.2% for female headed households in theKingston Metropolitan Region, 43.2% in Other towns and 41.7% for Rural female headedhouseholds in addition to the fact that female headed households‘ consumption are lower thanthat of male headed household. The current study has found that there is a difference in QoL ofmale and that of female youths. This is an important phenomenon that must be examined withthe use of qualitative methodology, as a part of this answer lies in people‘s culture and thecurrent research did not seek to investigate this matter. There is a drawback here as thisproposition cannot be examined in this paper as there is no variable called household head.Hence, one of the recommendations is that this be examined in future research. The current study has shown that the economic resources of youths are fundamental tothe QoL of youths, than with the fact that male youths‘ mothers have a greater degree of tertiarylevel education; they will be able to find more economic resources for their sons compared totheir female counterparts. This was also the case that emerged from the subjective social class ofthe youths. Approximately 7% of female youths (53.6%) indicated that they are in the lowerclass to males (i.e. 49.3%); whereas 8% more male youths reported that they were of the middleclass (47.9%) compared to female youths (40.1%). In order to ascertain any over-reported onself-reported social class by sexes, self-reported social class was cross tabulated with educationalattainment of the household, and income. Using a cross-tabulation between the individual‘s self-reported social class and that of mother‘s, individual‘s or father‘s educational level, it was foundthat there was no over-reported as those who had indicated being in the low class had substantialprimary or below education. Those who had reported being in the middle class werepredominantly secondary class as well as those who had indicated upper class. On examinationof mother‘s or father‘s educational attainment, the findings revealed that relationship between 119
  • 137. each of those factors and self-reported social class (P<0.05). Using income to evaluate over-reporting or underreporting of self-reported social class, the research found no statisticalassociation between the two aforementioned variables – F statistic [2,257]=2.541, P=0.081.Hence, subjective social class is relatively a good variable to use to measure social class;however, income is not a ‗good‘ variable to use to evaluate household income as upper classhousehold reported the least income ($10,000 to $14,999 monthly), whereas the middle classhousehold reported the highest income ($25,000 to $29,999 monthly) than for those in lowerclass household (ie. $20,000 to $25,000 monthly). The issue of underreported income isestablished in literature, and this one of the reason why the Planning Institute of Jamaica usedtotal expenditure to proxy income as against the underreported income. This paper has onceagain shown that reported income is not a good measure to use, and so this explains the rationalefor this paper not including income as a part of the model. Is the data a good fit for the model? The data is a good fit for the model as 75% (N=158)of the overall model was correctly classified in the current study. Disaggregating the overallcorrectness of the data revealed that 95% (N=140) of those who indicated a moderate-high QoLwere correctly classified compared to 29% (N=18) of those who reported a low QoL. (Table 5.5). Insert Table 5.5 hereDiscussion and ConclusionStudies in the literature have shown that age, education, race, social class, employment, andoccupation are statistically associated with QoL (5-6), (8), (10), (12). However, these were notfound to be the case in the current research. Why some of the aforementioned factors are notstatistically significant in determining QoL of youths although this is well established in theliterature. Some one-quarter of youths are below the age of 20 years and can be residing withparents and even some of those who are older than 20 years, which can indicate the reliance on 120
  • 138. parental or family support. Thus, the differences that can be seen in age, education, race, socialclass, employment and occupation that usually differ with time will not have emerge in 7 yearswhich are at the earlier stage of educational achievement, employment and occupationtypologies. Some of the important findings that emerged from the current research are the role ofparents‘ economic situation on QoL of youths and secondly the importance of moderatereligiosity and thirdly the significance of nation‘s social security programmes on youths‘wellbeing. Embedded in those findings are the capacities of parents and the nation to provide forthis age cohort of Jamaicans as well as the positive attributes of religiosity on wellbeing. Itfollows that a slowing of economic growth and development of the nation will impact not onlythe ability and capacity of nation, but on the likelihood of youths becoming increasinglyinvolved criminality to subsidize for the lowering of the state in the provision of social assistanceto this age cohort. The same argument can be forwarded about parents‘ economic wellbeing, andits influence on their children, that is the youths. However, what is there religiosity and QoL (orsubjective wellbeing)? Religion and religiosity are established by both theologians and scientific scholars ashaving an influence on QoL of people. There is a discourse as to whether theologians‘perspectives indicate a scientific axiom or a subjective framework to capture their sentiments;but it is clear that non-theologians have now concurred with theologians that religions impact onthe QoL of humans. Religion, therefore, is associated with wellbeing (51-55) as well as lowmortality (56). Religion is seen as the opiate of the people from Karl Marx‘s perspective butTheologians, on the other hand, hypothesized that religion is a coping mechanism againstunhappiness and stress. According to one scholar, Kart (57), religious guidelines aid wellbeing 121
  • 139. in that, through restrictive behavioural habits which are health risk such smoking, drinking ofalcohol, and even diet. Within the context of the literature, the current study has concurred withboth Theologians and academia that religiosity plays a crucible role to improvements in QoL, ofyoung people. Karl Marx had argued that religion is the opiate of the people, suggesting that people willbecome more cooperative with their current position as their existence is not entirely present as apart of life. For them futuristic ends are tied to a ‗good‘ life on reaching heaven. Embedded inMarx‘s proposition is satisfaction with life which is one of the hallmarks of what religionprovide. Edward Diener, Ruut Veehnoven, Richard Cummins, and Sonja Lyubomirsky believethat there is a direct association between satisfaction with life and improvements in QoL, and soone can understand the interrelation between religion and acceptance with one‘s current status inlife and how it will influence not only passivity but also content, self-actualization and byextension satisfaction with life. Another component of religion is the social support that itprovides. The findings of the current study have not found that religiosity is a causal factor indetermining QoL of youths; but, it provides an associational premise. Religiosity is well used inresearch literature as an independent variable in the examination of QoL. Despite the fact thatreligiosity forms personality, we can isolate the outcomes of religiosity and the variablereligiosity, and this paper was concern about religiosity as there was no question on role ofreligiosity in personality formation. They found that the relationship was even stronger for men than for women, and that thisassociation was influenced by denominational affiliation. Graham et al‘s study (55) found thatblood pressure for highly religious male heads of households in Evan County was low. The 122
  • 140. findings of this research did not dissipate when controlled for age, obesity, cigarette smoking,and socioeconomic status. A study on the Mormon in Utah revealed that cancer rates were lower(by 80%) for those who adhere to Church doctrine (58-59) than those with weaker adherence. In a study of 147 volunteer Australian males between 18 and 83 years old, Jurkovic &Walker (53) study found a high stress level of non-religious than compared to religious men.The researchers in constructing a contextual literature quoted many studies that have made a linkbetween non-spirituality and ―dryness‖, which results in suicide. Even though, Jurkovic &Walker‘s research was primarily on spiritual wellbeing, it provides a platform that can be used inunderstanding linkages between psychological status of people and their general wellbeing. In astudy which looked at young adult women, the researchers found that spirituality affects thephysical wellbeing of its populace (60). Embedded within that study is the positive influence ofspirituality and religion on the health status of women. Edmondson‘s et al. work constituted of42 female college students of which 78.8 percent were Caucasian, 13.5 percent African-American, 5.8 percent Asian and 92 percent were non-smokers. In summary, QoL of Jamaican youths is substantially determined by the householdeconomic situation, religiosity and the perceived reported extent of welfare state. Moreover,youths with moderate religiosity had the highest QoL. The study revealed that a youths who hadmoderate religiosity was 4 times more likely to have a greater QoL with reference to one whoreported low religiosity. Whereas a youths who reported high religiosity is 3 times more likelyto report a greater QoL with reference to a youths who reported low religiosity. The current workhas offered us an understanding of possible causal factor of QoL of youths; but this must be 123
  • 141. further studied using longitudinal study in order to establish with finality the causal explanatoryfactors of QoL.Limitation of StudyThis research is a cross-sectional study and ergo cannot be used the same way as an experimentaldesign, which is to establish causality. In addition, based on some of the findings presented inthis paper, questions have emerged that must be addressed, but the current study will not be ableto provide some of those answers. Hence, the researcher recommends that an ethnographicmethodology be utilized to unearth the cultural underpinning that will explain the higher QoL ofmale youths compared to females of the same age cohort.AcknowledgementThe author would like to extend special accommodation to the Centre of Leadership andGovernance, Department of Government, University of the West Indies, Mona, Jamaica forallowing him the privilege to utilize the dataset from which this paper was possible.Reference 1. Murphy H, Murphy EK. Comparing quality of life using the World Health Organization Quality of Life measure (WHOQOL-100) in a clinical and non-clinical sample: Exploring the role of self-esteem, self-efficacy and social functioning. Journal of Mental Health 2006;15:289–300. 2. Prause W, Saletu B, Tribl GG, Rieder A, Rosengerger A, Bolitschek J, Holzinger B, Kaplhammer G, Datschning H, Kunze M, Popovic R, Graetzhofer E, Zeitlhofer J. Effects of socio-demographic variables on health-related quality of life determined by the quality of life index—German version. Human psychopharmacology Clinical and Experimental Journal 2005;20:359-365. 3. Stutzer A, Frey BS. Reported subjective wellbeing: A challenge for economic theory and economic policy, Working Paper 2003-07. Centre for Research in Management, Economics and the Arts; 2003. Retrieved on August 31, 2006 from: http. 4. Easterlin RA. Does economic growth improve the human lot? Some Empirical Evidence. In: David PA, Reder MW, eds. Nations and Households in Economic Growth: Essay in Honour of Moses Abramowitz. New York and London: Academic Press; 1974. 5. Easterlin RA. Income and happiness: Towards a unified theory. Economic Journal 2001;111:465-484 124
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  • 144. ―Constitution of the World Health Organization, 1948.‖ In Basic Documents, 15th ed. Geneva, Switzerland: World Health Organization; 1948.44. Sen A. Choice, Welfare and Measurement. Oxford: Basil Blackwell; 1982.45. Sen A. Well-Being, Agency and Freedom: The Dewey Lectures. Journal of Philosophy 1985;82:169-221.46. Di Tella R, MacCulloch RJ, Oswald AJ. The macroeconomics of happiness. Warwick Economic Research papers, No. 615. England: Department of Economics, the University of Warwick; 2001.47. Cummins RA. Moving from the quality of life concept to a theory. Journal of Intellectual Disability Research 2005;49:699-706.48. Cummins RA. Objective and subjective quality of life: an interactive model. Social Indicators Research 2000;52:55–72.49. Kashdan TB. The assessment of subjective wellbeing (issues raised by the Oxford Happiness Questionnaire). Personality and Individual Differences 2004;36:1225–1232.50. Pacione M. 2003. Urban environmental quality and human wellbeing –a social geographical perspective. Landscape and Urban Planning 2003;65:19-30.51. Krause N. 2006. Religious doubt and psychological wellbeing: A longitudinal investigation. Review of Religious Research 2006;47:287-302.52. Moody HR. Is religion good for your health? Gerontologist 2006;14:147-149.53. Jurkovic D, Walker GA. Examining masculine gender-role conflict and stress in relation to religious orientation and spiritual wellbeing in Australian men. Journal of Men‘s Studies 2006;14:27-46.54. Ardelt M. Effects of religion and purpose in life on elders‘ subjective wellbeing and attitudes toward death. Journal of Religious Gerontology 2003;14:55-77.55. Graham TW, Kaplan BH, Cornoni-Huntley JC, James SA, Becker C, Hames CG, Heyden S. Frequency of church attendance and blood pressure elevation. Journal of Behavioral Medicine 1978;1:37-43.56. House JS, Robbins C, Metzner JL. The association of social relationships and activities with mortality: Prospective evidence from the Tecumseh Community Health Study. American Journal of Epidemiology; 1982;116:123-140. In: Hummer RA, Rogers RG, Nam CB, Ellison CG. Religious involvement and U.S. adult mortality. Demography 1999;36:273-28557. Kart CS. The Realities of Aging: An introduction to gerontology, 3rd. Boston, United States: Allyn and Bacon; 1990.58. Gardner JW, Lyon JL. Cancer in Utah Mormon women by church activity level. American Journal of Epidemiology 1982;116:258-265.59. Gardner JW, Lyon, JL. Cancer in Utah Mormon men by lay priesthood level. American Journal of Epidemiology 1982;116:243-257.60. Edmondson K A, et al. Spirituality predicts health and cardiovascular responses to stress in young adult women. Journal of Religion and Health 2005;44:161-171.61. Chevannes B. Learning to be a man: Culture, socialization and gender identity in five Caribbean communities. Kingston, Jamaica: The Univer. of the West Indies Press; 2001. 127
  • 145. Table 5.1: Sociodemographic Characteristics of Sampled PopulationGender Male 150 (42.7%) Female 201 (57.3%)Age (Mean ± SD) 21.6yrs.± 2.3yrsEducational level Secondary and below 191(54.1%) Post-secondary (i.e. Vocational (skills training)) 68 (19.3%) Tertiary (include colleges, university and professional training). 94 (26.6%)Subjective Social Class Working class 186 (53.0%) Middle class 154(43.9%) Upper class 11 (3.1%)Ethnic background African, Black 274 (76.3%) Mixed (Brown) 74(20.6%) European, white 2 (0.6%) Other 9 (2.6%)Quality of life (Mean ± SD) 6.9 ± 1.7 mode is 7.6. median is 7.2Welfare Index (Mean ± SD) 6.9 (out of 10) ± 1.4 mode is 6.8Political Participation Index (Mean ± SD) 2.1 (out of 15)± 2.7 128
  • 146. Table 5.2: Quality of Life1 of youths by Some Explanatory Variables Wald Coefficient Std. Error statistic P Exp(B)2 95.0% C.I. Lower Upper Religiosity13 1.014 .443 5.246 .022 2.756 1.157 6.562 Religiosity2 1.279 .458 7.807 .005 3.594 1.465 8.815 Welfare Index .284 .124 5.273 .022 1.329 1.043 1.694 Dummy Race4 .026 .606 .002 .966 1.026 .313 3.368 Political Participation Index -.024 .067 .128 .720 .976 .856 1.114 Dummy Area of Residence5 -.294 .505 .339 .560 .745 .277 2.005 Sex6 .699 .348 4.021 .045 2.011 1.016 3.980 socialcl17 -.129 .358 .129 .720 .879 .436 1.774 socialcl2 .954 .971 .965 .326 2.595 .387 17.394 Confidence Index .024 .017 2.096 .148 1.024 .991 1.058 Parent Economic Situation Index .704 .207 11.562 .001 2.022 1.348 3.035 Dummy Trust8 .561 .359 2.443 .118 1.753 .867 3.543 Occupation -.441 .461 .912 .340 .644 .261 1.590 Age -.057 .083 .466 .495 .945 .803 1.112 Dummy Education9 .013 .401 .001 .973 1.013 .461 2.226 Dummy Employment10 .015 .239 .004 .950 1.015 .635 1.622 Constant -3.996 2.400 2.772 .096 .018N=211χ2 (16) =301.65, P = 0.011-2Log likelihood = 2205.62; Nagelkerke R-squared = 0.301 Quality of Life is a dummy variable, where 1=moderate to high quality of life, 0=otherwise.2 Exp (B) is the Odds Ratio3 Religiosity1 is High; Religiosity2 is moderate religiosity, the reference group being low religiosity.4 Race is a dummy variable where 1=African, Blacks and Brown (or Mixed), 0=Otherwise5 Area of Residence is a dummy variable, where 1=St. Andrew or Kingston, 0=Otherwise6 Sex is a dummy variable, where 1=male, 0=Otherwise7 Subjective social class is socialcl1 is middle class, socialcl2 is upper class, with the reference group being lower class8 Interpersonal trust is a dummy variable, where 1=yes , 0=Otherwise9 Education is a dummy variable, 1=Tertiary level education, 0=Post-secondary and below10 Employment is a dummy variable, where 1=employed and 0=otherwise 129
  • 147. Table 5.5: Classification Table for Quality of Life of Youths, N=211 Observed Predicted Dummy QoL Moderat Percentage Low e-High Correct Low 18 45 28.6 Dummy QoL Moderate- 8 140 94.6 High Overall Percentage 74.9 130
  • 148. Table 5.3: Descriptive Statistics for Quality of Life By Age Cohort Std. Std. 95% Confidence N Mean Deviation Error Interval for Mean Age Cohort Lower Upper Bound BoundYouths (ages 18 to 25 years) 357 6.9245 1.69829 .08988 6.7477 7.1012Other Adults (26 to 59 years) 803 6.8068 1.77031 .06247 6.6842 6.9294Elderly (60+ years) 82 6.9854 1.69641 .18734 6.6126 7.3581Total 1242 6.8524 1.74487 .04951 6.7553 6.9495ANOVA [2,1239]=0.817, p value=0.442 > 0.05 131
  • 149. Table 5.4: Quality of Life of Youths in Jamaica By Gender Std. Std. Error Gender N Mean Deviation Mean Male 148 7.2054 1.64116 0.13490Quality ofLife Female 196 6.7198 1.73286 0.12378t=2.652, pvalue=0.008 132
  • 150. Chapter 6Health of children less than 5 years old in an Upper MiddleIncome Country: Parents’ views Paul Andrew BourneHealth literature in the Caribbean, and in particular Jamaica, has continued to use objectiveindices such as mortality and morbidity to examine children‘s health. The current study usessubjective indices such as parent-reported health conditions and health status to evaluate thehealth of children instead of traditional objective indices. The study seeks 1) to examine thehealth and health care-seeking behaviour of the sample from the parents‘ viewpoints; and 2) tocompute the mean age of the sample with a particular illness and describe whether there is anepidemiological shift in these conditions. Two nationally representative cross-sectional surveyswere used for this paper (2002 and 2007). The sample for the current study is 3,062 respondentsaged less than 5 years. For 2002, the study extracted a sample of 2,448 under 5 year olds fromthe national survey of 25,018 respondents, and 614 under 5 year olds were extracted from the2007 survey of 6,728 respondents. Parents-reported information were used to measure issues onchildren under 5 years old. In 2007, 43.4% of the sample had very good health status; 46.7%good health status; 2.5% poor health and 0.3% very poor health status. Almost 15% of childrenhad illnesses in 2002, and 6% more had illnesses in 2007 over 2002. In 2002, the percentage ofthe sample with particular chronic illnesses was: diabetes mellitus (0.6%); hypertension (0.3%)and arthritis (0.3%). However, none was recorded in 2007. The mean age of children less than 5years old with acute health conditions (i.e. diarrhoea, respiratory diseases and influenza)increased over 2002. In 2007, 43.4% of children less than 5 years old had very good healthstatus; 46.7% good health status; 7.1% fair health status; 2.5% poor and 0.3% very poor healthstatus. The association between health status and parent-reported illness was - χ2 (df = 4) =57.494, P < 0.001 – with the relationship being a weak one, correlation coefficient = 0.297. Across-tabulation between health status and parent-reported diagnosed illness found that asignificant statistical correlation existed between the two variables - χ2 (df = 16) = 26.621, P <0.05, cc = 0.422, - with the association being a moderate one, correlation coefficient = 0.422. Across tabulation between health status and health care-seeking behaviour found a significantstatistical association between the two variables - χ2 (df = 4) = 10.513, P < 0.033 - with thecorrelation being a weak one – correlation coefficient = 0.281.Rural children had the least healthstatus. The health disparity that existed between rural and urban less than 5 year olds showed thatthis will not be removed simply because of the abolition of health care utilization fees. 133
  • 151. IntroductionIn many contemporary nations, objective indices such as life expectancy, mortality anddiagnosed morbidity are still being widely used to measure the health of people, a society and/ora nation [1-6]. The World Health Organisation (WHO) in the Preamble to its Constitution in the1940s wrote that health is more important than disease, as it expands to the social, psychologicaland physical wellbeing of an individual [7]; and lately that during the 21st century the emphasismust be on healthy life expectancy [8,9]. In keeping with its opined emphasis, the WHOformulated a mathematical approach that diminished life expectancy by the length and severityof time spent in illness as the new thrust in measuring and examining health. Although healthylife expectancy removes time spent in illness and severity of dysfunctions, it fundamentally restson mortality. The WHO therefore, instead of moving forward, has given some scholars, who areinclined to use objective indices in measuring health, a guilty feeling about continuing thispractice. The Caribbean, and in particular Jamaica, continues to use mortality and morbidity tomeasure the health of children or infants [1-6]. The use of mortality, morbidity and lifeexpectancy is the practice of Caribbean scholars, and is widely used in Jamaica by the: Ministryof Health (MOHJ) [10]; Statistical Institute of Jamaica (STATIN) [11]; Planning Institute ofJamaica (PIOJ) [12]; PIOJ and STATIN [13] as well as the Pan American Health Organization(PAHO) [14] in measuring health. In spite of the conceptual definition opined by the WHO inthe Preamble to its Constitution in 1946, the health of children who are less than 5 years old inJamaica is still measured primarily by using mortality and morbidity statistics. Recently a bookentitled ‗Health Issues in the Caribbean‘ [15] had a section on Child Health; however thearticles were on 1) nutrition and child health development [16] and 2) school achievement and 134
  • 152. behaviour in Jamaican children [17], indicating the void in health literature regarding healthconditions. An extensive review of health literature in the Caribbean region found no study that hasused national survey data to examine the health status of children less than 5 years of age. Thecurrent study fills this gap in the literature by examining the health status of children less than 5years of age using cross-sectional survey data which are based on the views of patients. Theobjectives of this paper are 1) to examine the health and health care-seeking behaviour of thesample; and 2) to evaluate the mean age of the sample with a particular illness and to describewhether there is an epidemiological shift in these conditions.Materials and methodsSampleThe current study used two secondary nationally representative cross-sectional surveys (for 2002and 2007) to carry out this work. The sub-samples are children less than 5 years old, and the onlycriterion for selection was being less than 5 years old. The sample in the current study is 3,062respondents of ages less than 5 years. For 2002, a sub-sample of 2,448 less than-5 year olds wasextracted from the national survey of 25,018 respondents in 2002, and information on 614 lessthan-5 year olds was extracted from the 2007 survey. The survey (Jamaica Survey of LivingConditions) began in 1989 to collect data from Jamaicans in order to assess government policies.Since 1989, the JSLC has added a new module each year in order to examine that phenomenon,which is critical within the nation [18, 19]. In 2002, the focus was on 1) social safety nets, and2) crime and victimization, while for 2007, there was no focus. 135
  • 153. MethodsStratified random sampling technique was used to draw the sample for the JSLC. This designwas a two-stage stratified random sampling design where there was a Primary Sampling Unit(PSU) and a selection of dwellings from the primary units. The PSU is an Enumeration District(ED), which comprises a minimum of 100 residences in rural areas and 150 in urban areas. AnED is an independent geographical unit that shares a common boundary. This means that thecountry was grouped into strata of equal size based on dwellings (EDs). Based on the PSUs, alisting of all the dwellings was made, and this became the sampling frame from which a MasterSample of dwellings was compiled, which in turn provided the sampling frame for the labourforce. One third of the Labour Force Survey (i.e. LFS) was selected for the JSLC [18, 19]. Thesample was weighted to reflect the population of the nation [18-20]. The JSLC 2007 was conducted in May and August of that year; while the JSLC 2002 wasadministered between July and October of that year. The researchers chose this survey based onthe fact that it is the latest survey on the national population, and that that it has data on the self-reported health status of Jamaicans. An administered questionnaire was used to collect the datafrom parents on children less than 5 years old, and the data were stored, retrieved and analyzedusing SPSS for Windows 16.0 (SPSS Inc; Chicago, IL, USA). The questionnaire was modelledon the World Bank‘s Living Standards Measurement Study (LSMS) household survey. There aresome modifications to the LSMS, as the JSLC is more focused on policy impacts. Thequestionnaire covered areas of socio-demographic variables – such as education; daily expenses(for the past 7 days); food and other consumption expenditures; inventory of durable goods;health variables; crime and victimization; social safety net and anthropometry. The non-response 136
  • 154. rates for the 2002 and 2007 surveys were 26.2% and 27.7% respectively. The non-responseincludes refusals and cases rejected in data cleaning.MeasuresSocial class: This variable was measured based on the income quintiles: The upper classes werethose in the wealthy quintiles (quintiles 4 and 5); the middle class was quintile 3 and the poorwere the lower quintiles (quintiles 1 and 2).Age is a continuous variable in years.Health conditions (i.e. parent-reported illness or parent-reported dysfunction): The question wasasked: ―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.Medical care-seeking behaviour was taken from the question ‗Has a health care practitioner,healer or pharmacist been visited in the last 4 weeks?‘ with there being two options: Yes or No.Parent-reported illness status. The question is ‗Have you had any illness other than due to injury(for example a cold, diarrhoea, asthma, hypertension, diabetes or any other illness) in the pastfour weeks? Here the options were Yes or No.Statistical analysisDescriptive statistics, such as mean, standard deviation (SD), frequency and percentage wereused to analyze the socio-demographic characteristics of the sample. Chi-square was used toexamine the association between non-metric variables, and Analysis of Variance (ANOVA) was 137
  • 155. used to test the relationships between metric and non-dichotomous categorical variables, whereasan independent sample t-test was used to examine the statistical correlation between a metricvariable and a dichotomous categorical variable. The level of significance used in this researchwas 5% (i.e. 95% confidence interval).ResultsDemographic characteristic of sampleIn 2002, the sex ratio was 98.8 males (less than 5 years old) to 100 females (less than 5 yearsold), which shifted to 116.2 less than-5 year old males to 100 less than-5 year old females. Thesample over the 6 year period (2002 to 2007) revealed internal migrations to urban zones (Table6.1): In 2002, 59.6% of respondents resided with their parents and/or guardians in rural areas,which declined to 5.07%. The percentage of children less than 5 years of age whose parentswere in the poorest 20% fell to 25.4% in 2007 over 29.6% in 2002. In 2007 over 2002, 1.7 timesless children less than 5 years of age were taken to public hospitals, compared to 1.2 times lesstaken to private hospitals (Table 6.1). Approximately 6% more children less than 5 years wereill in 2007 over 2002. Based on Table 6.1, less than-5 year olds with particular chronic illnesseshad: diabetes mellitus (0.6%); hypertension (0.3%) and arthritis (0.3%). However, none wasrecorded in 2007. There were some occasions on which the response rates were less than 50%: In 2002,health care-seeking behaviour was 14.3%; parent-reported diagnosed health conditions, 14.2%;and visits to health care institutions, 8.9% (Table 6.1). For 2007, the response rate for healthcare-seeking behaviour was 20.2%; parent-reported diagnosed health conditions, 20.2%, and lessthan 11% for cost of medical care. 138
  • 156. Health conditionsBased on Table 6.1, the percentage of less than-5 year olds with particular acute conditions saw adecline in colds and asthmatic cases, as well as chronic conditions. Figure 6.1 revealed that in2007 the mean age of children less than 5 years old with acute health conditions (i.e. diarrhoea,respiratory diseases and influenza) increased over 2002. On the other hand, the mean age ofthose with unspecified illnesses declined from 1.76 years (SD = 1.36 years) to 1.64 years (SD =1.36 years). Concomitantly, the greatest mean age of the sample was 2.71 years (SD = 1.21years) for asthmatics in 2007 and 2.59 years (1.24 years) in 2002. It should be noted here thatthe mean age of a child less than 5 years of age in 2002 with diabetes mellitus was 1.50 years(2.12 years).Health statusIn 2002, the JSLC did not collect data on the general health status of Jamaicans, although thiswas done in 2007. Therefore, no figures were available for health status for 2002. In 2007,43.4% of children less than 5 years old had very good health status; 46.7% good health status;7.1% fair health status; 2.5% poor and 0.3% very poor health status. The response rate for thehealth status question was 96.9%. Ninety-seven percent of the sample was used to examine the association between healthstatus and parent-reported illness - χ2 (df = 4) = 57.494, P < 0.001 – with the relationship being aweak one, correlation coefficient = 0.297. Table 6.2 revealed that 24.2% of children less than 5years of age who reported an illness had very good health status, compared to 2 times more ofthose who did not report an illness. One percent of parents indicated that their children (of less 139
  • 157. than 5 years) who had no illness had poor health status, compared to 5.6 times more of thosewith illness who had poor health status.Health conditions, health status and medical care-seeking behaviourA cross-tabulation between health status and parent-reported diagnosed illness found that asignificant statistical correlation existed between the two variables - χ2 (df = 16) = 26.621, P <0.05, cc = 0.422, - with the association being a moderate one, correlation coefficient = 0.422(Table 6.3). Based on Table 6.3, children less than 5 years old with asthma were less likely toreport very good health status (5.9%), compared to those with colds (30.5%); diarrhoea (22.2%);and unspecified health conditions (22.7%). When health status by parent-reported illness (in %) was examined by gender, asignificant statistical relationship was found, P < 0.001: males - χ2 (df = 4) = 25.932, P < 0.05, cc= 0.320, and females - χ2 (df = 4) = 39.675, P < 0.05, cc = 0.356. The health statuses of malesless than 5 years old in the very good and good categories were greater than those of females(Figure 6.2). However, the females had greater health statuses in fair and poor health status thanmales, with more males reporting very poor health status than females. Based on Figure 6.3, even after controlling health status and parent-reported illness (in%) by area of residence, a significant statistical association was found: urban - χ2 (df = 3) =10.358, P < 0.05, cc = 0.238; semi-urban - χ2 (df = 3) = 9.887, P = 0.021, cc = 0.273, and rural -χ2 (df = 3) = 45.978, P < 0.001, cc = 0.365. Concomitantly, children less than 5 years of age werethe least likely to have very good health status (19.4%) compared to rural (25.8%) and semi-urban children (25.9%). Furthermore, the respondents who resided in urban areas were 2.1 timesmore likely to have parent-reported very poor health status, compared to rural respondents. 140
  • 158. In examining health status and reported illness (in %) by social classes, significantstatistical relationships were found, P < 0.05: poor-to-poorest classes - χ2 (df = 4) = 52.374, P =0.021, cc = 0.393; middle class - χ2 (df = 3) = 8.821, P = 0.032, cc = 0.259, and wealthy class - χ2(df = 3) = 10.691, P = 0.02, cc = 0.234. Based on Figure 6.4, middle class children who are lessthan 5 years old had the greatest very good health status (37%) compared to the wealthy class(26.8%) and the poor-to-poorest classes (16.1%). Fourteen percent of poor-to-poorest classchildren who are less than 5 years old had at most poor health status compared to 0% of themiddle class and 4.9% of the wealthy class, while 1.8% of poor-to-poorest classes less than 5years of age had very poor health status. When health status and parent-reported illness was examined by age, sex, social class,and area of residence, the correlation was a weak one – correlation coefficient = 0.295, P <0.001, n=583. A cross tabulation between health status and health care-seeking behaviour found asignificant statistical association between the two variables - χ2 (df = 4) = 10.513, P < 0.033 -with the correlation being a weak one – correlation coefficient = 0.281. A child less than 5 yearsold was 2.44 times more likely to be taken for medical care if he/she had at most poor healthstatus. On the other hand, a child who had very good health status was 1.97 times more likely notto be taken to health care practitioners (Figure 6.5). In 2007, an examination of the health care-seeking behaviour and parent-reported illnessof the sample revealed no statistical correlation - χ2 (df = 1) = 0.430, P = 0.618. Sixty-twopercent of the sample, who was ill, was taken to health care practitioners, while 38.5% were not.On the other hand, more were taken for medical care than in 2007 in the 4-week period of the 141
  • 159. survey. No statistical correlation was noted for the aforementioned variables in 2002 - χ2 (df = 1)= 1.188, P = 0.276. Of those who reported ill, 63.7% were taken to health care practitioners.DiscussionInfant mortality has been declining since the 1970s, and this has further decreased since 2004[14]; this, as the literature shows, is not a good measure of health. The current study found that,using general health status, children less than 5 years of age in Jamaica had good health. Thefindings revealed that 90 out of every 100 less than-5 year olds had at least good health status,with 44 out of every 100 having very good health status. In spite of the good health status of lessthan-5 year olds in Jamaica in 2007, 20.8% of them had an illness in the 4-week period of thesurvey, which is a 5.9% increase over 2002. It is interesting to note the shift in this paper awayfrom specific chronic illnesses. In 2002, 30 out of every 1,000 less than-5 year olds in Jamaicawere diagnosed with hypertension and arthritis (i.e. parent-reported), with 60 out of 1,000 havingbeen parent-reported with diabetes mellitus. None such cases were found in 2007, suggestingthat in the case of the children who had those particular chronic illnesses, their parents had eithermigrated with them or they had died. Concomitantly, the country is seeing a reduction inchildren less than 5 years old with colds; however, marginal increases were seen in diarrhoea,asthma and unspecified health conditions over the last 6 years. Although there were increasedreported cases of illness over the studied period, in 2007, 62 out of every 100 ill children weretaken to medical practitioners, and this fell from 64 in every 100 in 2002. One of the argumentsput forward by some people is that what retards or abates health care-seeking behaviour ismedical cost. With the abolition of health care user fees for children since 2007, the culture mustbe playing a role in parents and/or guardians not taking children who are ill to medical carefacilities for treatment. 142
  • 160. Medical cost cannot be divorced from the expenditure that must be incurred in taking thechild to the health care facility. In 2007, 25 out of every 100 children less than 5 years of age hadparents and/or guardians who were less than the poverty line. Although this has declined by4.2% since 2002, it nevertheless means that there are children whose parents are incapacitated byother factors. Marmot [21] opined that the financial inability of the poor is what accounts fortheir lowered health status, compared to other social classes. The current study concurs with thefindings of Marmot, as it was revealed that children less than 5 years of age from poorhouseholds had the least health status. This means that poverty is not merely eroding the healthstatus of poor Jamaicans, but that equally it is decreasing the health status of poor children. Rural poverty in Jamaica is at least twice as great as urban poverty, and approximately 4times more than semi-urban [13], which provides another explanation for the poor health statusof children less than 5 years of age. The current study found that 3.2% of those children dwellingin urban zones recorded at most poor health status, compared to 13.6% of rural children,suggesting that the health status of the latter group is 4.3 times worse than the former. Thismeans that poverty in rural zones is exponential, eroding the quality of life of children who areless than 5 years old. Poverty in semi-urban areas was 4% which is 2.5 times less than that forthe nation; and those less than 5 years of age recorded the greatest health status, supportingMarmot‘s perspective that poverty erodes the health status of a people. Hence, the decline inhealth care-seeking behaviour for this sample is embedded in the financial constraints of parentsand/or guardians as well as their geographical challenges. The terrain in rural zones in Jamaica issuch that medical care facilities are not easily accessible to residents compared to urban dwellers.With this terrain constraint comes the additional financial burden of attending medical carefacilities at a location which is not in close proximity to the home of rural residents, and this 143
  • 161. accounts for the vast health disparity between rural and urban children. As a result of the above,the removal of health care utilization fees for children less than 18 years of age does notcorrespond to an increased utilization of medical care services, or lowered numbers of unhealthychildren less than 5 years of age. If rural parents are plagued with financial and locationchallenges, their children will not have been immunized or properly fed, and their nutritionaldeficiency would explain the health disparity that exists between them and urban children whohave easier access to health care facilities. The removal of health care utilization fees is not synonymous with an increasedutilization of medical care for children less than 5 years old, as 46.5% of the sample attendedpublic hospitals for treatment in 2002, and after the abolition of user fees in April 2007utilization fell by 1.7 times compared to 2002. In order to understand stand why there is a switchfrom health care utilization to mere survival, we can examine the inflation rate. In 2007, theinflation rate was 16.8% which is a 133% increase over 2002 (i.e. 7.2%), which translates into a24.7% increase in the prices of food and non-alcoholic beverages, and a 3.4% increase in healthcare costs [22]. Here the choice is between basic necessities and health care utilization, whichfurther erodes health care utilization in spite of the removal of user fees for children. Health status uses the individual self-rating of a person‘s overall health status [23], whichranges from excellent to poor. Health status therefore captures more of people‘s health thandiagnosed illness, life expectancy, or mortality. However, how good a measure is it? Empiricalstudies show that self-reported health is an indicator of general health. Schwarz & Strack [24]cited that a person‘s judgments are prone to systematic and non-systematic biases, suggestingthat it may not be a good measure of health. Diener, [25] however, argued that the subjective 144
  • 162. index seemed to contain substantial amounts of valid variance, indicating that subjectivemeasures provide some validity in assessing health, a position with which Smith concurred [26].Smith [26] argued that subjective indices do have good construct validity and that they are arespectably powerful predictor of mortality risks [27], disability and morbidity [27], though theseproperties vary somewhat with national or cultural contexts. Studies have examined self-reportedhealth and mortality, and have found a significant correlation between a subjective and anobjective measure [27-29]: life expectancy [30]; and disability [28]. Bourne [30] found that thecorrelation between life expectancy and self-reported health status was a strong one (correlationcoefficient, R = 0.731); and that self-rated health accounted for 53% of the variance in lifeexpectancy. Hence, the issue of the validity of subjective and objective indices is good, withSmith [26] opining that the construct validity between the two is a good one. The current research found that parent-reported illness and the health status of childrenless than 5 years of age are significantly correlated. However, the statistical association was aweak one (correlation coefficient = 0.297), suggesting that only 8% of the variance in healthstatus can be explained by parent-reported children‘s illnesses. This is a critical finding whichreinforces the position that self-reported illnesses (or health conditions) only constitute a smallproportion of people‘s health. Therefore, using illness to measure the health status of childrenwho are less than 5 years of age is not a good measure of their health, as illness only accounts for8% of health status. However, based on Bourne‗s work [30], health status is equally as good ameasure of health as life expectancy. One of the positives for the using of health status insteadof life expectancy is its coverage in assessing more of people‘s general health status by usingmortality or even morbidity data. 145
  • 163. ConclusionIn summary, the general health status of children who are less than 5 years old is good; however,social and public health programmes are needed to improve the health status of the ruralpopulation, which will translate into increased health status for their children. The healthdisparity that existed between rural and urban children less than 5 years of age showed that thiswill not be removed simply because of the abolition of health care utilization fees. In keepingwith this reality, public health specialists need to take health care to residents in order to furtherimprove the health status of children who are less than 5 years old.Conflict of interestThe author has no conflict of interest to report.DisclaimerThe researcher would like to note that while this paper used secondary data from the JamaicaSurvey of Living Conditions, 2007, none of the errors that are within this paper should beascribed to the Planning Institute of Jamaica or the Statistical Institute of Jamaica as they are notthere, but owing to the researcher.References 1. Lindo, J. (2006) Jamaican perinatal mortality survey, 2003. Jamaica Ministry of Health. Kingston, pp. 1-40. 2. McCarthy, J.E., and Evans-Gilbert, T. (2009) Descriptive epidemiology of mortality and morbidity of health-indicator diseases in hospitalized children from western Jamaica. American Journal of Tropical Medicine and Hygiene, 80,596-600. 3. Domenach, H., and Guengant, J. (1984) Infant mortality and fertility in the Caribbean basin. Cah Orstom (Sci Hum), 20,265-72. 4. Rodriquez, F.V., Lopez, N.B., and Choonara, I. (2002) Child health in Cuba. Arch Dis Child, 93,991-3. 146
  • 164. 5. McCaw-Binns, A., Holder, Y., Spence, K., Gordon-Strachan, G., Nam, V., and Ashley, D. (2002) Multi-source method for determining mortality in Jamaica: 1996 and 1998. Department of Community Health and Psychiatry, University of the West Indies. International Biostatistics Information Services. Division of Health Promotion and Protection, Ministry of Health, Jamaica. Statistical Institute of Jamaica, Kingston6. McCaw-Binns, A.M., Fox, K., Foster-Williams, K., Ashley, D.E., and Irons, B. (1996) Registration of births, stillbirths and infant deaths in Jamaica. International Journal of Epidemiology, 25,807-813.7. 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. WHO, Geneva.8. World Health Organization, (WHO). (2004) Healthy life expectancy 2002: 2004 World Health Report. WHO, Geneva.9. WHO. (2000) WHO Issues New Healthy Life Expectancy Rankings: Japan Number One in New ‘Healthy Life’ System. WHO; 2000, Washington D.C. & Geneva.10. Jamaica Ministry of Health, (MOHJ). (1992-2007) Annual report 1991-2006. MOHJ, Kingston.11. Statistical Institute of Jamaica, (STATIN). (1981-2009) Demographic statistics, 1980- 2008. STATIN, Kingston.12. Planning Institute of Jamaica, (PIOJ). (1981-2009) Economic and Social Survey, 1980- 2008. PIOJ, Kingston.13. PIOJ, and STATIN. (1989-2009) Jamaica Survey of Living Conditions, 1988-2008. PIOJ and STATIN, Kingston.14. Pan American Health Organization, (PAHO). (2007) Health in the Americas, 2007, volume II Countries. PAHO, Washington DC.15. Morgan, W. (ed). (2005) Health issues in the Caribbean. Ian Randle, Kingston.16. Walker, S. Nutrition and child health development. In Morgan, W. (ed). Health issues in the Caribbean. Ian Randle, Kingston, pp. 15-25.17. Samms-Vaugh, M., Jackson, M., and Ashley, D. (2005) School achievement and behaviour in Jamaican children. In Morgan, W, (ed). Health issues in the Caribbean. Ian Randle, Kingston, pp. 26-37. 147
  • 165. 18. Statistical Institute Of Jamaica. (2008) Jamaica Survey of Living Conditions, 2007 [Computer file]. Kingston, Jamaica: Statistical Institute Of Jamaica [producer], 2007. Kingston, Jamaica: Planning Institute of Jamaica and Derek Gordon Databank, University of the West Indies [distributors].19. Statistical Institute Of Jamaica. (2003) Jamaica Survey of Living Conditions, 2002 [Computer file]. Kingston, Jamaica: Statistical Institute Of Jamaica [producer], 2002. Kingston, Jamaica: Planning Institute of Jamaica and Derek Gordon Databank, University of the West Indies [distributors].20. World Bank, Development Research Group, (2002). Poverty and human resources. Jamaica Survey of Living Conditions (LSLC) 1988-2000: Basic Information.21. Marmot, M (2002) The influence of income on health: Views of an Epidemiologist. Does money really matter? Or is it a marker for something else? Health Affair, 21,31-46.22. Bourne, P.A (2009) Impact of poverty, not seeking medical care, unemployment, inflation, self-reported illness, health insurance on mortality in Jamaica. North American Journal of Medical Sciences, 1, 99-109.23. Kahneman, D., and Riis, J. (2005) Living, and thinking about it, two perspectives. In Huppert, F.A., Kaverne, B. and N. Baylis, The Science of Well-being, Oxford University Press.24. Schwarz, N., and Strack, F. (1999) Reports of subjective well-being: judgmental processes and their methodological implications. In Kahneman, D., Diener, E., Schwarz, N, (eds). Well-being: The Foundations of Hedonic Psychology. Russell Sage Foundation: New York, pp. 61-84.25. Diener, E. (1984) Subjective well-being. Psychological Bulletin, 95,542–75.26. Smith, J. (1994) Measuring health and economic status of older adults in developing countries. Gerontologist, 34, 491-6.27. Idler, E.L., and Benjamin, Y. (1997) Self-rated health and mortality: A Review of Twenty-seven Community Studies. Journal of Health and Social Behavior, 38, 21-37.28. Idler, E.L., and Kasl, S. (1995) Self-ratings of health: Do they also predict change in functional ability? Journal of Gerontology 50B, S344-S353.29. Schechter, S., Beatty, P., and Willis, G.B. (1998) Asking survey respondents about health status: Judgment and response issues. In Schwarz, N., Park, D., Knauper, B., and S. Sudman, S (ed.). Cognition, Aging, and Self-Reports. Ann Arbor. Taylor and Francis, Michigan. 148
  • 166. 30. Bourne, P.A. (2009) The validity of using self-reported illness to measure objective health. North American Journal of Medical Sciences, 1,232-238. 149
  • 167. Table 6.1. Socio-demographic characteristic of sample, 2002 and 2007 2002 2007Variable n % n %Sex Male 1216 49.7 330 53.7 Female 1231 50.3 284 46.7Income quintile Poorest 20% 725 29.6 156 25.4 Poor 554 22.6 140 22.8 Middle 474 19.4 126 20.5 Wealthy 402 16.4 117 19.1 Wealthiest 20% 293 12.0 75 12.2Self-reported illness Yes 345 14.9 125 20.8 No 1969 85.0 475 79.2Visits to health care facilities (hospitals) Private, yes 17 7.8 5 6.7 Public, yes 100 46.3 20 26.7Area of residence Rural 1460 59.6 311 50.7 Semi-urban 682 27.9 125 20.4 Urban 306 12.5 178 29.0Health (or, medical) care-seeking behaviour Yes 221 63.3 76 61.3 No 128 36.7 48 38.7Health insurance coverage Yes, private 211 9.0 66 11.1 Yes, public * * 33 5.5 No 2123 91.0 496 83.4Self-reported diagnosed health conditions Acute Cold 185 53.3 60 48.4 Diarrhoea 20 5.8 9 7.3 Asthma 46 13.3 17 13.7 Chronic Diabetes mellitus 2 0.6 0 0 Hypertension 1 0.3 0 0 Arthritis 1 0.3 0 0 Other (unspecified) 54 15.6 22 17.7 Not diagnosed 38 11.0 16 12.9Number of visits to health care institutions 1.53 (SD = 0.927) 1.43 (SD = 0.989)Duration of illness Mean (SD) 8.51 days (6.952 days) 8.07 days (7.058 days)Cost of medical care Public facilities Median (Range)in USD 2.36 (157.26)1 0.00 (64.62)2 Private facilities Median (Range)in USD 13.76 (117.95)1 10.56 (49.71)21 USD1.00 = Ja. $50.872 USD1.00 = Ja. $80.47*In 2002, all health insurance coverage was private and this was change in 2005 to include some public option 150
  • 168. Table 6.2. Health status by self-reported illness Self-reported illness Health status Yes No n (%) n (%)Very good 30 (24.2) 227 (48.3)Good 61 (49.2) 217 (46.2)Fair 23 (18.5) 19 (4.0)Poor 9 (7.3) 6 (1.3)Very poor 1 (0.1) 1 (0.2)Total 124 470χ2 (df = 4) = 57.494, P < 0.001, cc = 0.297, n = 594 151
  • 169. Table 6.3. Health status by self-reported diagnosed illness Self-reported diagnosed illness Health status Cold Diarrhoea Asthma Unspecified No Very good 18 (30.5) 2 (22.2) 1 (5.9) 5 (22.7) 5 (31.3) Good 31 (52.5) 5 (55.6) 4 (23.5) 11 (50.0) 8 (50.0) Fair 7 (11.9) 2 (22.2) 8 (47.1) 3 (13.6) 3 (18.8) Poor 2 (3.4) 0 (0.0) 4 (23.5) 3 (13.6) 0 (0.0) Very good 1 (1.7) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)Total 59 9 17 22 16χ2 (df = 16) = 26.621, P < 0.05, cc = 0.422, 152
  • 170. Figure 6.1. Mean age of health conditions of children less than 5 years old, 2002 and 2007 153
  • 171. Figure 6.2. Health status by Parent-reported illness (in %) examined by gender 154
  • 172. Figure 6.3. Health status by parent-reported illness (in %) examined by area of residence 155
  • 173. Figure 6.4. Health status by parent-reported illness (in %) examined by social classes 156
  • 174. Figure 6.5. Health status by health care-seeking behaviour 157
  • 175. Chapter 7Biosocial determinants of health and health seeking behaviour ofmale youths in Jamaica Paul Andrew BourneThe current study aims to provide an understanding of the health of young males (ages 15-25years) which has been primarily lacking in the Caribbean, and in particular Jamaica. This paperutilised secondary cross-sectional dataset for 2007 taken from the Jamaica Survey of LivingConditions (JSLC). The questionnaire was modelled from the World Bank‘s Living StandardsMeasurement Study (LSMS) household survey. The current study extracted 607 respondents (15-25 years) from a sample of 6,783 respondents. SPSS for Windows 16.0 (SPSS Inc; Chicago, IL,USA) was used to store, retrieve and analyse the data. A p-value of < 0.05 (two-tailed) was usedto indicate statistical significance. Four variables emerged as statistical significant correlates ofhealth status: self-reported illness, OR = 16950, 95% CI = 46.4-6187362.9; self-reported injury,OR = 114643.2, 95% CI = 100.2-131124116.9; crowding, OR = 0.2, 95% CI = 0.09-0.59 andhead of household, OR = 0.001, 95% CI = 0.0-0.2. None of the identified variables emerged assignificant correlates of the good self-rated health status of male youths - Model χ2= 16.284(8), P< 0.061. Of the variables identified, 1 emerged as a correlate of poor self-rated health status –self-reported illness – OR = 42.2, 95% CI = 2.6-693.2. Poverty is substantially a ruralphenomenon. Almost 30% of rural respondents were classified as being in the poorest 20%,compared to 17.3% of those in semi-urban and 8.7% in urban areas. At the same time, nostatistical association existed between area of residence and self-reported health status, self-reported injury, self-reported diagnosed health conditions and poor health status. The currentstudy does not concur with the established finding that poverty is more common among thechronically ill than among those who are not chronically ill. However, it supports the literaturethat current illness is primarily a response to males‘ willingness to utilize health care. Theimplications for these findings are far-reaching, and public health practitioners now have aplatform upon which they can fashion interventions, health education and future research on thisvulnerable age cohort in Jamaica. 158
  • 176. IntroductionThe Caribbean continues to grapple with an alarming crime problem. Scholars have found thatmuch of it is perpetrated by young males (≤ 30 years of age) [1-8]. Statistics showed that 67.6%of those arrested for major crimes in Jamaica (i.e. murder, shooting, robbery, house-breaking,rape and carnal abuse) were 16-30 years old, and that young males accounted for more than 80%of the numbers (Table 7.1). Bearing this out, for the period 1999-2002, statistics in Jamaicarevealed that more than 50% of those treated for gunshot wounds in the Accident and Emergencydepartments at public hospitals were 10-29 years of age, with the figures being relatively thesame for males and females. A recently conducted study by Powell, Bourne and Waller [9] foundthat 44% of Jamaicans indicated that ‗crime and violence‘ was their most pressing problem, aphenomenon which extends to many other Caribbean nations such as Barbados, Trinidad andTobago, and Guyana [1-8]. The social realities of the crime problem in the region justify (1)studies on crime and violence, and (2) an inquiry into the fear of crime and victimization. Understandably, there are many studies on crime, violence and the fear of crime andvictimization in the Caribbean, but there are also other concerns such as substance abuse, sexualpractices, the survivability of young people, and male marginalization. Those issues have beenstudied and re-studied [10-18], sometimes yearly, but in addition to crime which is a narrowedaspect of the broad social issues that continue to challenge Caribbean peoples, there is a need toexpand research into this social problem. Studies continue to examine crimes, violence and thefear of crime and victimization, and rightfully so in the region and little attention if any has beenplaced on men‘s health, and in particular young men‘s health in the region, except in the area ofreproductive health and sexual practices [19-21]. 159
  • 177. Recently an entire book entitled ―Health Issues in the Caribbean‖ [18] covered topicssuch as child health, reproductive health, the elderly, chronic non-communicable diseases,disability, health care-delivery and health issues in the Caribbean, reinforcing the claim of thelack of research on men‘s health and young males‘ health. A study by Bourne [21] examined―Demographic shifts in the health conditions of adolescents 10-19 years, Jamaica‖, whichprovided pertinent information on this cohort, but again men‘s health or young males‘ health wasnot the emphasis; neither did it capture most of those who attested for crimes, nor those who areinfluenced by crime and violence. With crime being such a dominant social problem and the factthat it is perpetrated by mostly young males, there is the tendency to become overindulgent inthis discourse. However, research conducted by Powell, Bourne and Waller [9] found that only18% of Jamaicans indicated that they have been victims of crime and violence in the last 12months. Clearly, there is an obvious need to expand the research, from crime, violence, fear andvictimization to health status, health conditions and health care-seeking behaviour among theyouth. Apart from being the perpetrators of crime and violence, how is their (1) health status, (2)health care-seeking behaviour and (3) how are the health conditions among young males (15 –25 years)? The current study aims to provide an understanding of the health of young males (ages15-25 years) which has been primarily lacking in the Caribbean, in particular in Jamaica. What isinfluencing their health care seeking behaviour? Those questions cannot be answered from theperspective of a general study on health or the health care-seeking behaviour of Jamaicans [22],as without disaggregating the results, pertinent information is lost on the this cohort because itwould be general findings on the populace. 160
  • 178. Materials and MethodsStudy populationThis paper utilised secondary cross-sectional dataset for 2007 taken from the Jamaica Survey ofLiving Conditions (JSLC). The JSLC is a joint publication from the Planning Institute of Jamaica(PIOJ) and the Statistical Institute of Jamaica (STATIN) for analysis [23-25]. The JSLC began in1988 to collect data on the living conditions of Jamaicans in order to measure governmentpolicies. These cross-sectional surveys were conducted between May and October of each yearacross the 14 parishes of Jamaica. The current study extracted 607 respondents (15-25 years)from a sample of 6,783 respondents [26, 27]. The JSLC used a stratified random probabilitysampling technique to draw the original sample of respondents. The non-response rates were26.2%. The JSLC survey used a complex design with multiple stratifications to ensure that itrepresented the population, marital status, area of residence and social class. The sample wasweighted to reflect the population of Jamaica [23-25].Study instrumentThe JSLC used an administered questionnaire where respondents were asked to recall detailedinformation on particular activities. The questionnaire was modelled using the World Bank‘sLiving Standards Measurement Study (LSMS) household survey [23]. There are somemodifications to the LSMS, as JSLC is more focused on policy impacts. The questionnairecovers demographic variables, health, immunization of children 0–59 months, education, dailyexpenses, non-food consumption expenditure, housing conditions, inventory of durable goodsand social assistance. Interviewers are trained to collect the data from household members. 161
  • 179. Statistical methodsDescriptive statistics were used to analyse the socio-demographic characteristics of the samples.Chi-square analyses were used to examine the association between non-metric variables for areaof residence, and gender of respondents. T-test statistics and Analysis of Variance were used toevaluate metric and either a dichotomous or non-dichotomous variable respectively. Logisticregression analyses examined 1) the association between good health status and some socio-demographic, economic and biological variables, as well as 2) a correlation between self-reported health conditions (illnesses, dysfunctions or ailments) and some socio-demographic,economic and biological variables. SPSS for Windows 16.0 (SPSS Inc; Chicago, IL, USA) wasused to store, retrieve and analyse the data. A p-value of < 0.05 (two-tailed) was used to indicatestatistical significance. The only selection criterion for this paper was based on the males being 15-25 years old.For the model, the selection criteria were based on 1) the literature review; 2) low correlations,and 3) non-response rate. The correlation matrix was examined in order to ascertain ifautocorrelation and/or multicollinearity existed between variables. Based on Cohen & Holliday[28, 29] correlation can be low (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. Where collinearity existed (r >0.7), the variables were entered independently into the model to help determine which oneshould be retained in the final model construction. This was used to exclude or include somevariables, and was based on the variables‘ contribution to the predictive power of the model andits goodness of fit. Such an approach was utilised in order to reduce multicollinearity and/orautocorrelation between or among the independent variables [30-36]. Forward stepwise logisticregression technique was used to determine the magnitude (or contribution) of each statistically 162
  • 180. significant variable in comparison with the others, and the Odds Ratios (OR) aided theinterpretation of each significant variable. To derive accurate tests of statistical significance, theresearcher used SUDDAN statistical software (Research Triangle Institute, Research TrianglePark, NC), and this adjusted for the survey‘s complex sampling design.MeasureAge is a continuous variable which is the number of years alive since birth (using last birthday):from 15 to 25 years.Self-reported illness (or self-reported dysfunction): The question was asked: ―Have you had anillness such as influenza, asthma, et cetera in the past 4-week period?‖Health conditions (i.e. parent-reported illness or parent-reported dysfunction): The question wasasked: ―Is this a diagnosed recurring illness?‖ The answering options are: Yes, Influenza; 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.Medical care-seeking behaviour was taken from the question ‗Has a health care practitioner,healer or pharmacist been visited in the last 4 weeks?‘ with there being two options: Yes or No.Self-rated health status: ―How is your health in general?‖ And the options were: Very good;Good; Fair; Poor and Very poor. For this paper 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). 163
  • 181. Social hierarchy: This variable was measured based on income quintile: The upper classes werethose in the wealthy quintiles (quintiles 4 and 5), the middle class was quintile 3, and the poorwere those in lower quintiles (quintiles 1 and 2).Crowding: This is the total number of people in the household divided by the number of rooms,excluding verandah, kitchen and bathroom.Area of residence is a non-binary variable. 1= urban, 0=otherwise 1=semi-urban, 0=otherwise Reference group is rural areaResultsThe sample was 607 respondents (15-25 years): dwelling in urban areas, 33.9%; semi-urban,20.9%; rural, 45.2%; injured in last 4-week period, 2.4%; self-evaluated illness (in last 4-weekperiod), 3.3%; health care-seeking behaviour, 68.0%; primary or below education, 64.5%;tertiary level education, 6.5%; household heads, 8.9%; very good self-rated health status, 49.2%;good self-rated health status, 44.9%; moderate self-rated health status, 4.6%; poor self-ratedhealth status, 1.0%; and very poor health status, 0.3%. Of those who reported an illness, 75.5%stated the typology of health conditions: influenza, 6.7%; diarrhoea, 13.3%; asthma, 6.7%;hypertension, 6.7%; and other (unspecified), 66.7%. The mean age of the sample was 19.6 years(SD = 3.2 years). The median length of illness (in days) was 5 (range = 1, 28) and the number ofvisits to a health care practitioner was 1 time (range = 1, 3). Of the 8.9% of those who were heads of households, 29.6% were 24 years old; 18.5%were 22 years old; 14.8% were 23 years old; 13.0% were 25 years old; 11.1% were 19 years old;3.7% were 21, 20 and 17 years old; and .9% were 16 years old. Furthermore, a statistical 164
  • 182. difference existed between those who were and those who were not heads of households (Fstatistic = 48.6, P < 0.0001): mean age of those who were household heads was 22.4 years (SD =2.3 years) compared to those who were not household heads (19.4 years ± 3.1 years). There is a statistical difference between the mean length of illness (in days) and area ofresidence (F statistic = 5.706, P = 0.011). Those in urban areas recorded the greater length ofillness, 14.4 days (SD = 10.3 days); semi-urban areas, 6.5 days (SD = 5.8 days) and ruralrespondents, 4.7 days (SD = 2.5 days). Furthermore, a statistical difference was found betweentotal annual household expenditure among the social classes (F-statistic = 64.870, P < 0.0001.The mean annual household expenditure for the sample was USD 8,994.04 (SD = USD6716.46). However, those young males in households of the poorest 20% had an annualhousehold expenditure which was 3.3 times less than those in the households of the wealthiest20% (USD 15,152.73 ± 10,179.74), with the following annual household expenditures beingpoor, USD 6,311.23 ± 2,645.72; middle class households, USD 8,522.97 ± 3,656.07; andwealthy, USD 10,812.74 ± 5,573.11. No statistical difference was found between the annual household expenditure of thosewith illness (USD 11,091.18 ± 13,898.55) and those who did not report an illness (USD 9,001.44± 6,433.52) – t-test = 1.320, P = 0.187. A statistical association existed between household heads and areas of residence (χ2 =6.864, P = 0.032). Almost 7% of those who dwelled in rural areas were household headscompared to 6.3% of those living in semi-urban areas and 13.1% of those who resided in urbanareas. There is no significant statistical association between (1) self-reported illness and socialstanding (χ2 = 1.315, P = 0.859), (2) self-reported injury and social standing (χ2 = 2.640, P = 165
  • 183. 0.620), and (3) self-reported diagnosed health conditions and social standing (χ2 = 12.80, P =0.687). Table 7.2 highlights information on the demographic characteristics of the sample by areaof residence. A significant statistical association was found between social standing and area ofresidence (χ2 = 83.5, P < 0.0001). Almost 30% of rural respondents were in the poorest 20%compared to 17.3% of those in semi-urban areas and 8.7% in urban areas.Multivariate analyses Table 7.3 shows information on factors that are correlated with the health care-seekingbehaviour of the sample. Using stepwise logistic regression, 4 variables emerged as statisticalsignificant correlates of health status: self-reported illness, OR = 16950, 95% CI = 46.4-6187362.9; self-reported injury, OR = 114643.2, 95% CI = 100.2-131124116.9; crowding, OR =0.2, 95% CI = 0.09-0.59 and head of household, OR = 0.001, 95% CI = 0.0-0.2. The modelexplains 86.4% of the variability in the health care-seeking behaviour of respondents, and it is agood fit for the data - Model χ2= 123.91(8), P < 0.0001, Hosmer and Lemeshow goodness of fitχ2=37.781, P = 0.778. Concurrently, 55.1% of the variability in health care-seeking behaviour isaccounted for by self-reported illness, and self-reported injury accounted for 26.2%. Table 7.4 highlights the possible factors of self-rated good health status of the sample.None of the identified variables emerged as significant correlates of good self-rated health statusof male youths - Model χ2= 16.284(8), P < 0.061. Almost 95% of the respondents were used toestablished the model, and it was found that the model is a good fit for the data - Hosmer andLemeshow goodness of fit χ2=5.301 (8), P = 0.725. Table 7.5 examines possible factors that are correlated with poor self-reported healthstatus of respondents. Ninety-three percent of the sample was used to establish the model. Of the 166
  • 184. variables identified, 1 emerged as a correlate of poor self-rated health status – self-reportedillness – OR = 42.2, 95% CI = 2.6-693.2. The model was a good fit for the data - Model χ2=123.91(8), P < 0.0001; Hosmer and Lemeshow goodness of fit χ2=1.206 (8), P =0.997.DiscussionThe current study found that 94 out of every 100 young males (ages 15-25 years) reported atleast good health status. Only 1.3% of the sample indicated poor health status. However, 3.3%indicated having had an illness in the last 4 weeks and 2.4% were injured in the same period oftime. Almost 1 in every 100 young males had reported an acute condition compared to 2 inevery 100 who reported a chronic condition. Of those who reported an illness (n=15), 66.7%indicated other and 6.7% said hypertension. The prevalence of hypertension among young maleswas 2 in every 1,000 persons. Sixty-eight percent of the sample had visited a health carepractitioner in the last 4 weeks; 83% purchased the prescribed medication; 15% had healthinsurance coverage; 58.8% visited a public hospital for treatment compared to 5.9% who used aprivate hospital, 11.8% who utilised public health care centres and 29.4% who attended a privatehealth care centre. Concurrently, the median length of time in illness was 5 days, with themedian number of visits to a health care practitioner being 1. In addition to the afore-mentionedfindings, 27% of poor health status can be explained by self-reported illness, and 47.6% of thevariability in health care-seeking behaviour can be accounted for by illness and 22.6% by injury.Young males who had indicated that they were heads of household were 99.9% less likely toseek health care, and those respondents with more people per room were 76.5% less likely toseek medical care. 167
  • 185. It is empirically established that health status is determined by medical, social,environmental and psychological factors [19,20,37-49], but for this paper self-reported illnesswas the only factor that emerged as being significant, when correlated with health status. Usingdata for elderly Barbadians, Hambleton et al. [43] found that 88% of the variability in self-reported health status could be explained by current diseases, and the current study found 27% ofthe variability in poor health being explained by current self-reported illness. Hambleton andcolleague‘s study [43] did not examine the health care-seeking behaviour of the sample, but thisresearch found that 55.1% of the explanatory power of seeking medical care was accounted forby current self-reported illness. Embedded in this paper is the image of health of young malesand when they seek medical care. This is not atypical, as a qualitative study conducted by Ali &de Muynck [50] in Pakistan found that illness and its severity are responsible for male streetchildren being willing to utilize medical care facilities. Clearly, in Jamaica as well as other non-Caribbean nations [51-54], males‘ image of illness is fundamentally based on illness, injury orthe severity of illness and injury, and not health from the perspective of wellbeing. It is thisnarrow definition of health that influences the decision of young males to seek medical care, andnot preventative health. The current findings show that there is a very good explanation foryoung males‘ health care seeking behaviour in Jamaica (R2 = 86.4%), which suggests that healthis the absence of diseases, and this is what impacts on their demand for health care. Health care-seeking behaviour among the current sample is 68 out of every 100 malescompared to 66 per 100 of the general populace and 68 out of every 100 for females.Concurrently, the rate for young males seeking medical care is 5% more than the rate for malesin the general population and the same as for females in the population. It should also be notedhere that the rate of those with illness in this sample is less than 4% which is 4.7 times less than 168
  • 186. the national average (i.e. 15.5% reported illness). Despite the substantially lowered rate of self-reported illness, young males sought more medical care than males in the wider population. Thisfinding highlights a myth that young males, like their older counterparts, avoid seeking medicalcare, but the issue which emerged from this research is that they seek both curative andpreventative care. Current self-reported illness and injury accounted for 81.3% of the variabilityin the health care-seeking behaviour of young males, supporting the culture which stipulates thatmen are strong and should not show weakness, and that illness is a sign of weakness. Hence, theillnesses which influence health care-seeking behaviour cannot be mild, such as the commoncold or diarrhoea, but more like asthma, hypertension and injuries such as gunshots, knifewounds and other severe conditions that are life-threatening, and therefore require immediatemedical attention. Although only 3.3% of the sample reported an illness and the prevalent rate for each self-reported diagnosed health condition was low (influenza, 0.2%; diarrhoea, 0.3%; asthma, 0.2;hypertension, 0.2%; and other (unspecified), 1.6%), on disaggregating those who reported ahealth condition, it becomes clear that this is a public health problem. Two-thirds of those whoindicated a health condition claimed ‗other‘, indicating a preponderance of some healthconditions and sexually transmitted diseases. A recently conducted study of Jamaicans by Wilkset al. [13] found that only 24.3% of young males (ages 15-24 years) claimed that they had nothad sex in the last 12 months; 48.7% had more than one sexual partner; 75.7% had sexualintercourse at least once per week; 0.9% claimed that they have had a STI in the last year; 65.8%used condoms; and 8.4% had not used a contraceptive method in the last 12 months. Based onWilks et al.‘s study, there are other health conditions apart from sexually transmitted diseaseswhich are dominant in the unspecified health conditions stated in the current sample. Statistics 169
  • 187. from the Ministry of Health (Jamaica) showed that 15% of males aged 10-29 years (in 2006) hadAIDS, which rules out AIDS as the explanation of the unspecified conditions of the currentstudy. Furthermore, examination of the statistics from the Ministry of Health (Jamaica) foundthat in 2006 36.0% of young males (ages 10-29 years) utilised public health care facilities forbites, 54.3% for gunshot wounds, and 43.1% for accidental lacerations. Those conditions mayaccount for the unspecified health conditions identified by the current study, but there is nofinality of this fact without a study of this cohort‘s health, health conditions and injuries. Clearlycrime, violence and victimization are having an influence on the health of young males, and whatabout the fear of crime and victimization on those who are not assaulted, but have witnessed theevents and are fearful from reading and watching the wired media? Concurrently, when the unspecified health conditions were disaggregated by area ofresidence, most of the reported cases were in urban areas, followed by rural and semi-urbanareas. Currently, research cannot account for most of the unspecified health conditions, whichdenotes that public health intervention programmes are designed without consideration beinggiven to this unknown event. But what is known is that almost 71% of the sample utilised publichealth care facilities and they constituted mostly rural respondents, which denotes that publichealth care facilities hold some of the clues to the condition of young males. However, thehypertensive cases were in semi-urban areas, and this offers public health policy makers somepertinent information upon which policies can be framed for young males. Poverty is empirically found as being associated with poor health status and a group ofscholars went as far as to declare that money can buy health [38]. Although Marmot [39] didargue that poverty is associated with poor milieu, nutrition, opportunities and choices, more so 170
  • 188. than the affluent, using the United States, he showed that there was a weak relationship betweenGross National Product and overall health. Embedded in Marmot‘s finding was the fact thatother factors are more of an explanation of poverty and poor health and/or ill-health such aseducation, material deprivation, social environment, racial inequality and occupational hierarchy.He also pointed out that there was a weak statistical association between average income and lifeexpectancy in rich countries, but that within those nations there is a close association between anindividual‘s income and his life expectancy and mortality. Clearly poverty is an influence onillness, and with ill-health also affecting poverty, this could be influenced more by other socialconditions than money (or income). One of the issues which could make the difference betweenMarmot‘s work and this one is how health is measured in each study. Health had a narrowdefinition in Marmot‘s study as it was operationalized by life expectancy or mortality. However what emerged from these findings are (1) poverty is not associated with poorhealth status; (2) poor young males do not seek less health care than the affluent; (3) ruralpoverty (i.e. those in the poorest 20%) was 3.4 times more than urban poverty and 1.7 timesmore than semi-urban poverty; (4) there was no significant statistical association between self-reported illness or injury and area of residence; (5) there was no significant statisticalrelationship between health care-seeking behaviour and area of residence; (6) urban young maleswere 5.5 times more educated at the tertiary level than rural young males; (7) urban young maleshad the greatest length of illness (in days); and (8) illness, injury or self-reported diagnosedhealth conditions are not statistically related to social standing. The current work disproves thefindings of Van Agt et al. [56], which showed that chronic illness is more prevalent among thepoor. However, this paper concurs with Van Agt et al.‘s work [56], in that material deprivationwas highest among the poor, but disproves the finding that the higher prevalence of material 171
  • 189. deprivation was among the chronically ill people. Instead, this paper found that those who werechronically ill were more likely to be in the wealthy social hierarchy than in the poor socialhierarchies. According to Barillas et al. [57], there was a paradox in the national survey data collectedon Guatemalans, as the poor reported less illness than the non-poor, and individuals in rural areasreported less illness than those in urban areas. It appears from the current study that no statisticalassociation between area of residence and self-reported illness and self-reported diagnosed healthconditions and social class would also be a paradox, but it is not the case as these are the realitiesin those nations and not the empirical findings of international health literature. Hence, it is goodto use international empirical findings from one country and create intervention programmes orpublic health education for another geopolitical area. In the current study 14.6% of rural young males claimed that they had an illness in thelast 4 weeks, but Bourne [58] conducted a study on rural men in Jamaican and found that 17%reported an illness. This finding highlights the deceptive nature of using the national average forpublic health planning, as what holds for men in one geo-political zone is not the same for youngmales within the same area. This is also true as Bourne [58] found that (1) 61.2% of rural menvisited a health care practitioner, (2) 2.4% had tertiary level education, (3) 4.9% had healthcoverage, and (4) good health status is a function of social, economic and biological factors.However, in this research health care utilization was greater for young rural males (73.3%);tertiary level respondents were about the same for rural men and young rural males (2.3%);health coverage was significantly more for young rural males (14.5%) than rural men, and nofactor explains the good health status of young males in Jamaica compared to rural men. Hence, 172
  • 190. even among people who live in the same geopolitical zones there are inequalities, suggesting thatpublic health practitioners cannot use national average or sub-national areas of one group to planfor another. Crime is substantially concentrated in urban zones, and given that it is perpetrated moreby young males, and the fact that more of them are victims of crime, it follows therefore that thelonger time spent in illness could be due to gunshot wounds and other injuries, more so than inthe case of rural and semi-urban young males. Illness is not only physical but a psychologicalcondition. This was established long ago by the WHO, and clearly the psychosocial challengesof life account for the health care-seeking and length of illness. The current findings revealedthat those young males who are household heads are almost 100% more likely to seek health careas they need to provide for a household, which indicates that health care switching is occurringamong this cohort in favour of their families. The health care switching which occurs denotesthat many young males who are heads of households will forego health care treatment inresponse to the demands of providing for a household. Not only do they forego health care butthey also forego preventative care, and this delay could account for premature death. Thesocioeconomic challenge of the household also accounts for other risky lifestyles, and may holdanswers to their involvement in criminality and violence. While this paper does not examinewhether there is a statistical association between a household head and crime, it can beextrapolated from the findings that the areas in which young males recorded the most heads ofhousehold status (urban areas, 13.1%; semi-urban, 6.3%; rural, 6.9% - χ2 = 6.86, P = 0.032), areprecisely those areas with the greatest crime and violence. One might ask if this is coincidentalor circumstantial, but it needs to be examined as a possible explanation for high crime as well asthe psychological state of young males in urban areas. 173
  • 191. ConclusionIt is well established in health research that health is a function of social, psychological,environmental and biological factors. Some studies have gone so far as to state the proportion ofthe explanatory variability of each of the afore-mentioned factors, but the current investigationrevealed that none of the factors that have been identified in previous studies were correlatedwith good health status of young males. However, illness emerged as the single factor thataccounts for poor health. Less than 2% of the sample indicated poor health, less than 8% injuryor illness, but more young males visited medical practitioners in the last 4-week period thanmales in Jamaica and equally the same as females in the nation. Unlike other studies done onhealth care-seeking behaviour around the world, none found an explanatory power as high as thisresearch (R2 = 86.4%). Furthermore, illness or injury is primarily responsible for young males‘health care seeking behaviour (81% of the explanatory power, i.e. R2), suggesting that the imageof health is still the opposite of illness and psychosocial wellbeing. A pertinent finding of thecurrent study is the fact that young males who are heads of households are less likely to seekmedical care, which denotes that this group is practicing health care switching for familysurvivability and protection. In sum, the self-rated health status of young males (ages 15 to 25 years) in Jamaica isgood with a small percentage reporting having had an illness or injury in the last 4-week period.The low percentage of those with illness corresponds to 68% health care utilization in the sameperiod, suggesting that young males are seeking medical care but that illness and injury is theprincipal influence on health care-seeking behaviour. The implications for these findings are far 174
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  • 196. Table 7.1: Arrested for Major Crimes By Age Group, 2005 Age Group of Persons Arrested for Major Crimes for 2005 Murder Shooting Robbery Breaking Rape C/AbuseAge Group Male Female Total Male Female Total Male Female Total Male Female Total Male Male Total12-15 6 1 7 4 0 4 10 0 10 54 0 54 12 11 9816-20 157 6 163 167 1 168 183 0 183 122 3 125 66 43 74821-25 235 8 243 239 1 240 214 1 215 129 3 132 68 52 95026-30 160 2 162 137 0 137 120 1 121 105 3 108 73 27 62831-35 85 1 86 74 0 74 71 1 72 93 2 95 48 26 40136-40 54 3 57 40 1 41 36 1 37 69 0 69 23 19 24641-45 15 0 15 12 0 12 13 0 13 44 1 45 18 12 11546-50 7 1 8 2 0 2 1 0 1 18 0 18 12 5 4651-55 5 1 6 0 0 0 2 0 2 2 0 2 3 2 1556-60 1 0 1 1 0 1 6 0 6 1 1 2 1 1 1261& Over 0 0 0 2 0 2 2 0 2 3 1 4 2 0 10Unknown 40 0 40 86 0 86 23 0 23 11 0 11 10 0 170 Total 765 23 788 764 3 767 681 4 685 651 14 665 336 198 3439Source: Compiled by author from data supplied by the Statistics Unit of the Jamaica Constabulary Force (JCF) 179
  • 197. Table 7.2. Demographic characteristic by area of residence, n = 607 Area of residence PCharacteristic Urban Semi-urban RuralSocial standing χ2 = 83., P < 0.0001 Poorest 20% 18 (8.7) 22 (17.3) 82 (29.9) Poor 28 (13.6) 27 (21.3) 75 (27.4) Middle 42 (20.4) 26 (20.5) 49 (17.9) Wealthy 48 (23.3) 24 (18.9) 48 (17.5) Wealthiest 20% 70 (34.0) 28 (22.0) 20 (7.3)Self-reported Injury χ2 = 0.920, P = 0.631 Yes 4 (2.0) 2 (1.6) 8 (3.1) No 193 (98.0) 122 (98.4) 254 (96.9)Marital status χ2 = 4.345, P = 0.361 Married 1 (0.5) 0 (0.0) 1 (0.4) Never married 194 (99.5) 124 (100.0) 253 (98.4) Divorced 0 (0.0) 0 (0.0) 0 (0.0) Separated 0 (0.0) 0 (0.0) 3 (1.2) Widowed 0 (0.0) 0 (0.0) 0 (0.0)Self-evaluated illness χ2 = 2.689, P = 0.261 Yes 4 (2.0) 3 (2.5) 12 (14.6) No 196 (98.0) 118 (97.5) 250 (95.4)Self-reported diagnosed χ2 = 11.000,P = 0.202illness Influenza 0 (0.0) 1 (33.3) 0 (0.0) Diarrhoea 0 (0.0) 0 (0.0) 2 (22.2) Asthma - - - Diabetes mellitus 0 (0.0) 0 (0.0) 1 (11.1) Hypertension 0 (0.0) 1 (33.4) 0 (0.0) Arthritis - - - Other 3 (100.0) 1 (33.3) 6 (66.7)Health insurance coverage χ2 = 0.156,P = 0.925 Yes 31 (15.8) 18 (14.8) 37 (14.5) No 165 (84.2) 104 (85.2) 218 (85.5)Health care-seeking χ2 = 4.243,P = 0.120behaviour Yes 5 (83.3) 1 (25.0) 11 (73.3) No 1 (16.7) 3 (75.0) 4 (26.7)Self-rated health status χ2 = 7.647, P = 0.467Very good 92 (46.2) 60 (48.4) 134 (51.9)Good 91 (45.7) 61 (49.2) 109 (42.2)Moderate 13 (6.5) 3 (2.4) 11 (4.3)Poor 3 (1.5) 0 (0.0) 3 (1.2)Very poor 0 (0.0) 0 (0.0) 1 (0.4) 180
  • 198. Table 7.3. Stepwise logistic regression: Health care-seeking behaviour by explanatory variables Std. 95.0% C.I. Explanatory variable Coefficient Error P Odds ratio R2 Lower Upper change Self-reported illness 0.476 9.738 3.0 0.001 16950.1 46.4 6187362.9 (1=yes) Self-reported injury 0.226 11.650 3.6 0.001 114643.2 100.2 131124116.9 (1=yes) Crowding -1.448 0.5 0.002 0.2 0.1 0.6 0.093 Head of household 0.069 -7.017 2.9 0.014 0.0 0.0 0.2 (1=yes)Model χ2= 123.91(8), P < 0.0001Hosmer and Lemeshow goodness of fit χ2=37.781, P = 0.778Nagelkerke R2 =0.864-2LL = 1525.53n = 575 (94.7%)†Reference group 181
  • 199. Table 7.4. Stepwise logistic regression: Self-rated good health status by variables Std. Odds 95.0% C.I. Variable Coefficient Error P ratio Lower Upper Self-reported illness (1=yes) -0.656 1.1 0.6 0.5 0.1 4.7 Self-reported injury (1=yes) -0.010 1.1 1.0 1.0 0.1 8.2 Age -0.067 0.1 0.2 0.9 0.8 1.1 Crowding -0.029 0.1 0.7 1.0 0.8 1.1 Consumption per person 0.000 0.0 0.5 1.0 1.0 1.0 Head of household (1=yes) 1.340 1.1 0.2 3.8 0.5 32.4 Urban area -0.590 0.4 0.2 0.6 0.3 1.2 Semi-urban 0.719 0.7 0.3 2.1 0.6 7.4 †Rural 1.0 Health care-seeking (1=yes) -1.301 1.3 0.3 0.3 0.0 3.3Model χ2= 16.284(8), P < 0.061Hosmer and Lemeshow goodness of fit χ2=5.301 (8), P = 0.725n = 575 (94.7%)†Reference group 182
  • 200. Table 7.5. Stepwise logistic regression: Self-rated poor health status by variables Std. Odds 95.0% C.I. Variable Coefficient Error P ratio Lower Upper Self-reported illness (1=yes) 3.744 1.4 0.009 42.2 2.6 693.2 Self-reported injury (1=yes) -18.278 7389.8 0.998 0.0 0.0 0.0 Age 0.250 0.1 0.083 1.3 1.0 1.7 Crowding 0.191 0.1 0.104 1.2 1.0 1.5 Consumption per person 0.000 0.0 0.541 1.0 1.0 1.0 Head of household (1=yes) -16.380 4875.4 0.997 0.0 0.0 0.0 Urban area 0.501 0.9 0.581 1.7 0.3 9.8 Semi-urban -16.497 3274.2 0.996 0.0 0.0 0.0 †Rural 1.0 Health care-seeking (1=yes) -18.849 7842.7 0.998 0.0 0.0 0.0 Health insurance (1=yes) -16.130 3686.1 0.997 0.0 0.0 0.0Model χ2= 123.91(8), P < 0.0001Hosmer and Lemeshow goodness of fit χ2=1.206 (8), P =0.997Nagelkerke R2 =0.271-2LL = 55.913n = 565 (93.1%)†Reference group 183
  • 201. Chapter 8Demographic shifts in health conditions of adolescents aged 10-19 years,Jamaica: Using cross-sectional data for 2002 and 2007 Paul A BourneIt is well established in health literature that most adolescents have good health, but this does notmitigate the reality that there are some who are living with chronic and other health conditions.To examine the demographic shifts in health conditions and the typology of health conditionsexperienced by this age cohort. The current study extracted a sample of 5,229 and 1,394adolescents aged 10-19 years from two surveys collected jointly by the Planning Institute ofJamaica and the Statistical Institute of Jamaica for 2002 and 2007 respectively. The survey wasdrawn using stratified random sampling. The sample was weighted to reflect the population ofthe nation. Descriptive statistics and chi-square were used in this paper. The level of significanceused in this research was 5% (i.e., 95% confidence interval). In 2002, most of the respondentshad colds (28.3%), and in 2007 this shifted to unspecified health conditions (35.5%). Thenumber of reported cases of arthritis in adolescents was 0.4% in 2002, which fell by 100% in2007. Increases were observed for: unspecified conditions, 42%; hypertension, 175%; anddiabetes mellitus, 700%. There is an immediate need for health promotion and educationcampaigns geared towards the sensitization of adolescents about the rise in chronic illness and itschallenges, lifestyle practices, and willingness to seek care if particular symptoms are presentlyaffecting them.IntroductionLife expectancy and infant mortality are two of the indicators of the health status of acommunity, society, nation, or population. This emphasizes the rationale behind extensivestudies on those conditions, and a possible paucity of research on adolescents‘ health, except inthe area of reproductive health. In Jamaica, the life expectancy at birth, for 2005-2010, is 69.75years for males and 74.95 years for females [1], which is equally comparable to that of thosepeoples in developed countries [2]. On extensive review of health literature in Jamaica, manystudies have examined infant or general mortality [3-7], sexual lifestyle and reproductive health 184
  • 202. in particular adolescents [8-13], and depression in adolescents [14-15] with an emphasis still onlife expectancy. Adolescent denotes an individual who is aged 10 to 19 years, and is among asection of the young population who will be or is seeking employment, attending school, and byextension, will form a critical part of the human development in the future. In 1991, theadolescent population comprised 22.2% of the total population and this fell to 19.7% in 2007(Table 8.1), indicating that one-fifth of the nation‘s population could be totally or partiallydependent on family, relatives, or the state for survivability.The issue of survivability constitutes more than socio-economic assistance to the health status ofthis group of people. Statistics from the Planning Institute of Jamaica and the Statistical Instituteof Jamaica [16] for 2007, revealed that most adolescents reported no illness/injury in the 4-weekperiod of the JSLC, 23.9% had a recurring illness, 53.7% of those who were ill sought medicalcare, suggesting that the health status of this cohort is relatively good. While this can be deducedfrom the statistics, there is no certainty to this deduction. Using mortality data for adolescents in1998, 1.86% of all mortality could be accounted for by male adolescents compared to 1.19 forfemale adolescents, and this figure increased by 29% for males and fell by 2.5% for females(Table 8.1).Table 8.1 Adolescents Mortality and Live Birth by Sex (female < 20 yrs), 1998-2007.In spite of the aforementioned disparity in mortality of the sexes for adolescents, the fact that20% of all births occur to this cohort, and on average 1.7% of all mortality is accounted for bythis age cohort (Table 8.1), academics in Jamaica continue to be overindulgent in adolescents‘reproductive health research. PAHO [17] however, noted that the health status of adolescents in 185
  • 203. Jamaica is good, which concurs with PIOJ [18], and PIOJ and STATIN‘s publications [16], andlike Jamaican scholars, dedicated more time to reproductive health and opined that 26% of allthose who had injuries from violent acts were adolescents. Using gunshot wounds to examineinjuries of adolescents, disaggregating the figures revealed that more adolescent females wereinjured and sought medical care than males (Tables 8.2, 8.3). Additionally, of the fewer than10% of adolescent Jamaicans who reported an illness or injury in 2007, 54% sought medicalcare, which indicates that some illnesses or injuries are not associated with health careutilization.The text ―Health Issues in the Caribbean‖ contained eight articles on adolescents [19]. Of these,one examined ‗The Health Impact of Injuries‘ and another, ‗Injuries – The BroadConsequences‘, again indicating limitedness of studies on the general health status of this cohort.Injuries comprised only a small percentage of poor health status and while depression is anaspect to the broad definition of health according to the WHO [20], and can be used to proxysome aspect of health, a recently published study by Bourne [21] was not significantly correlatedwith good health status of those who sought medical care in Jamaica. A study by Bourne et al.[22], examining mortality and health status of elderly Jamaicans, revealed that chronic healthconditions were not correlated with age, which may argue for the non-examination of generalhealth conditions for adolescents. Studies have shown that the health status over the life course isnot constant [23-27], and Kuh and Ben-Shlomo [28] showed that as people age, the probabilityof experiencing chronic diseases increase, and so understanding health conditions of the elderlydoes not equate to comprehending health conditions or general health of adolescents. 186
  • 204. According to Kuh and Ben-Shlomo [28], in the last two decades, the main concern of publichealth in developed countries was chronic diseases, and while these accounted for 60% ofmortality in developing countries, and that 80% of chronic illness were in low-to-middle incomecountries [29], the reality is that this expands beyond the elderly. In 2007, 40.2% of elderlyJamaicans indicated that they had an illness; 19.1% of those with diabetes mellitus were 65+ and21% were 60-64 years. Of those with hypertension, 36.5% were 65+ and 33% were 60-64 years,and of those with arthritis, 18.6% were 65+ and 16.9% were 60-64 years [16]. Public health,therefore, cannot singly be about the health status of a particular group over another, orreproductive health and injuries of a particular age-sex cohort to another, but a holisticunderstanding of health status of people over the life course in order to formulate policies thatare embedded in research literature. There is indeed a paucity of health literature on the healthstatus of adolescents, health conditions, and the demographic shifts in health conditions of thisage cohort in Jamaica. Depression and reproductive health are not comprehensive enough toprovide a holistic understanding of adolescents‘ health status in spite of the low percentage ofthose who are experiencing ill-health. This paper aims to examine the demographic shifts inhealth conditions and the typology of health conditions experienced by this age cohort.Materials and MethodThe current study extracted a sample of 5,229 and 1,394 adolescents aged 10-19 years from twosurveys collected jointly by the Planning Institute of Jamaica and the Statistical Institute ofJamaica for 2002 and 2007 respectively [30,31]. The method of selection of the sample fromeach survey was solely based on age (10-19 years). The survey (Jamaica Survey of LivingConditions) was begun in 1989 to collect data from Jamaicans in order to assess policies of the 187
  • 205. government. Each year since 1989, the JSLC has added a new module in order to examine thatphenomenon which is critical within the nation. In 2002, the foci were on 1) social safety net and2) crime and victimization; and for 2007, there was no focus. The sample for the earlier surveywas 25,018 respondents and for the latter, it was 6,783 respondents.The survey was drawn using stratified random sampling. This design was a two-stage stratifiedrandom sampling design where there was a Primary Sampling Unit (PSU) and a selection ofdwellings from the primary units. The PSU is an Enumeration District (ED), which constitutes aminimum of 100 residences in rural areas and 150 in urban areas. An ED is an independentgeographic unit that shares a common boundary. This means that 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 dwelling wascompiled, which in turn provided the sampling frame for the labor force. One third of the LaborForce Survey (i.e., LFS) was selected for the JSLC [30, 31]. The sample was weighted to reflectthe population of the nation.The JSLC 2007 [30] was conducted in May and August of that year, while the JSLC 2002 wasadministered between July and October of that year. The researchers chose this survey based onthe fact that it is the latest survey on the national population and that it has data on self-reportedhealth status of Jamaicans. A self-administered questionnaire was used to collect the data, whichwere stored and analyzed using SPSS for Windows 16.0 (SPSS Inc; Chicago, IL, USA). Thequestionnaire was modeled from the World Bank‘s Living Standards Measurement Study(LSMS) household survey. There are some modifications to the LSMS, as JSLC is more focused 188
  • 206. on policy impacts. The questionnaire covered areas such as socio-demographic variables such aseducation; daily expenses (for past 7-days), food and other consumption expenditures, inventoryof durable goods, health variables, crime and victimization, social safety net, and anthropometry.The non-response rate for the survey for 2007 was 26.2% and 27.7%. The non-response includesrefusals and rejected cases in data cleaning.MeasurementAdolescent: an individual who is aged 10-19 years. Younger adolescent: an individual who isaged 10-14 years. Older adolescent: an individual who is aged 15-19 years.Statistical AnalysisDescriptive statistics such as mean, standard deviation (SD), frequency and percentage were usedto analyze the socio-demographic characteristics of the sample. Chi-square was used to examinethe association between non-metric variables, and an Analysis of Variance (ANOVA) was usedto test the relationships between metric and non-dichotomous categorical variables. The level ofsignificance used in this research was 5% (i.e., 95% confidence interval).ResultsOf the 5,229 adolescents (aged 10-19 years) sampled in 2002, one-half were males, 62.8%resided in rural areas, 24.6% lived in semi-urban zones, and 12.6% dwelled in urban areas. Theresponse rate for the question ―Have you ever had any illness in the past 4 weeks‖ was 95.9%(n=5,017). Two percent of those who were asked the question ―Are you pregnant‖ (n=1,569)remarked yes. Comparatively, of the 1,394 adolescents sampled in 2007, 48.2% was males, 189
  • 207. 51.1% resided in rural area, 28.3% lived in urban zones, and 20.6 dwelled in semi-urban areas.Of the 96.1% (n=1,340) of respondents who were asked the question ―Have you ever had anyillness in the past 4 weeks‖, 6.6% reported yes. In 2002, 63.9% of the sample sought medicalcare, 9.3% were covered by health insurance. Of those who had indicated an illness, 28.3% werediagnosed with a cold, 5.1% diarrhea, 24.6% asthma, 0.4% diabetes mellitus, 0.4% hypertension,0.4% arthritis, 25.0% other, and 15.9% indicated that they were not diagnosed by a medicalpractitioner or a health care worker. In 2007, 53.8% of the sample sought medical care, and14.7% were covered by health insurance (i.e., 9.3% private and 5.4% public coverage). Of thosewho had reported suffering from an illness, 23.7% were diagnosed with a cold, 1.1% diarrhea,17.2% asthma, 3.2% diabetes mellitus, 1.1% hypertension, 35.5% other, and 18.3% indicatedthat they were not diagnosed by a medical practitioner or a health care worker.Figure 8.1 revealed that there was a shift in the typology of health conditions for 2007 over 2002.In 2002, most of the respondents had colds (28.3%) and in 2007, this shifted to unspecifiedhealth conditions (35.5%). The number of reported cases of arthritis in adolescents was 0.4% in2002, which fell by 100% in 2007. The number of reported cases of diarrhea and colds fell andnotable increases for 2007 over 2002 were for unspecified conditions, 42%; hypertension, 175%;and diabetes mellitus, 700%.On further examination of the data, a cross tabulation with health insurance coverage,educational level, and population income quintile by area of residents revealed a significantstatistical correlation (p < 0.05) (Table 8.4). In 2002, rural adolescents were the least covered byhealth insurance and this remained the same in 2007. Concomitantly, the rural areas had the least 190
  • 208. number of people in the wealthiest 20% compared to other geographical zones, with urban areasrecorded the most in the wealthiest 20%.No significant statistical association was found between health conditions and area of residence(P > 0.05). However, there is a shift in the typology of health conditions from colds and diarrheato other illness and to a lesser extent, hypertension. In 2002, 0.4% were reported as beingdiagnosed with hypertension (from rural areas) and this increased 175% in 2007 (to 1.1%), andthis shifted to urban zones (Table 8.4). There is a shift to unclassified health conditions in 2007over 2002, and this was across the 3 geographical areas in Jamaica. The number of adolescentsbeing diagnosed with asthma fell across the geographic zones except in semi-urban areas where amarginal increase was noted, with the greatest movement being in rural areas (+54.2) followedby urban (+24.7%) and a reduction of 7.4% in semi-urban areas. No arthritis was reported in2007 compared to 0.4% in semi-urban areas in 2002.Table 8.4 revealed that there was no significant difference between the lengths of time spentreceiving medical care by area of residence for both years. The number of urban adolescentsdiagnosed with colds fell by more than 100% in 2007 over 2002 and while there was a reductionof the same health condition for rural adolescents, this was not the case for the semi-urbanpopulace. However, based on Table 8.4, there was a 30.2% increase in the number of semi-urbanadolescents who were diagnosed with colds for 2007 over 2002.In 2002, a significant statistical difference was found between those who sought and did not seekmedical care by the typology of health conditions - P < 0.05, χ2 (DF = 7) = 49.823, contingency 191
  • 209. coefficient = 0.392. However, none was found for 2007 – P > 0.05 (Table 8.5). Based on Table8.5, 3.1 times more adolescents who were diagnosed with a cold did not seek medical carecompared to those who did. For the chronic illnesses, except for arthritis, those ill respondentssought medical care. With regards to the unspecified health conditions, 3.4 times more soughthealth care compared to those who did not. For 2007, no statistical difference was observed forhealth conditions and health care-seeking behavior of adolescents. Comparatively, the number ofadolescents seeking medical care for 2007 over 2002 fell for asthma patients, and likewise fordiarrhea and cold patients. However, there was a substantial increase in the number ofadolescents both seeking and not seeking care for diabetes mellitus, and the those seeking carefor hypertension saw a drastic increase.A cross-tabulation between health condition and health insurance coverage revealed that therewas a significant statistical correlation for 2002 [p < 0.05, χ2 (DF = 7) = 35.222, cc = 0.336] andfor 2007 [P < 0.05, χ2 (DF = 12) = 22.641, cc = 0.442] – Table 8.6. Based on Table 8.6, in 2002,most of those who were covered by health insurance had colds (24%) and asthma (52%); and thisshifted to diabetes mellitus (33%) and unspecified conditions in 2007. There was a 30.4%reduction in the number of adolescents covered by health insurance in 2007 over 2002 whoreported having a cold (Table 8.6).The cross-tabulation between health condition and cohort of adolescents revealed that there is nosignificant statistical association (P > 0.05). Although no statistical correlation was identified byTable 8.7, 27.6% of younger adolescents in 2002 reported unspecified illnesses compared to48.6% of the older adolescents. Based on Table 8.7, the number of diabetic cases was zero for 192
  • 210. older adolescents in both years, the number of reported diabetic cases for younger adolescentsincreased by 766.67% (to 5.2%) for 2007 over 2002.Using data for 2007, on investigation of hypertension with diabetes mellitus, it was found that astatistical correlation existed between both conditions (χ2 (DF = 1) = 34.439, P <0.001).Additionally, the study found that 23.5% of those with diabetes mellitus had hypertension.DiscussionPublic health is not about collecting, addressing and formulating policies for an individualpatient as it must focus on diseases and conditions which influence health, and by so doingaddress a large population [32]. Public health therefore must be guided by research on apopulation, and the adolescent is one such sub-population. In Jamaica, this comprises about 20%of the population indicating that by not having research information on this sub-population,policies will be on a trial-and-error basis, which suggests that 1 in every 5 Jamaicans is notunderstood. Concomitantly, health conditions are well researched in adolescents [33-36], butthere is no such study on this sub-population in Jamaica. The current study found that chronicconditions such as diabetes mellitus and hypertension were diagnosed in adolescent Jamaicans.In 2007, 3 out of every 100 adolescent Jamaicans had diabetes and 1 in every 100 had diabetesmellitus. The diabetic cases were all found in younger adolescents (aged 10 to 14 years), whilethe hypertensive cases were only found in older adolescents (aged 15 to 19 years). Interestingly,in this paper a shift in typology of health conditions was observed for 2007 over 2002. In theformer year, the leading health condition was colds (28 out of every 100) and this has shifted tounspecified conditions in the latter year (36 out of every 100). Like colds, the proportion of cases 193
  • 211. of asthma has fallen. However, a critical finding in this paper was the drastic increase in thepercentage of samples with diabetes and hypertension. Although there is a shift towards chronicnon-communicable diseases in 2007 over 2002, the percentage of adolescents seeking medicalcare fell by approximately 10%.Hypertension is viewed as a silent killer [37] and like hypertension, diabetes mellitus is very highin Jamaica [38], indicating that the adolescent will be exposed to chronic diseases managementover the remainder of their lives. Morrison [39], in an article entitled ‗Diabetes and hypertension:Twin Trouble‘, established that diabetes mellitus and hypertension have now become twoproblems for Jamaicans as well as countries in the wider Caribbean area. This situation wasequally correlated by Callender [40] at the 6th International Diabetes and HypertensionConference held in Jamaica in March 2000. Callender [40] found that there was a positiveassociation between diabetic and hypertensive patients—50% of individuals with diabetes had ahistory of hypertension [40]. Prior to those scholars‘ work, Eldermire [41] found that 34.8% ofnew cases of diabetes and 39.6% of hypertension were associated with senior citizens (i.e., age60 and over). Unlike the general populace and the elderly cohort, 24 out of every 100 adolescentshad hypertension and diabetes mellitus, indicating the importance of studying a sub-populationand not assuming that what holds for the general population or a particular sub-population is thesame for another sub-population.Among the challenges associated with chronic conditions are 1) management, 2) cost, 3) impacton the family, 4) influence on lifestyle behavior and 5) psychosocial challenges of thoseconditions. An adolescent with hypertension or diabetes or both, impacts on the functional 194
  • 212. capacity of people in the same age cohort. This is not atypical in Jamaica as the same thinghappens in America [35]. Chronic illnesses in adolescents interface with their schooling,intellectual development, recreation, future employability, and occupational selection. And whenone is afflicted with both conditions (i.e., hypertension and diabetes mellitus), severity in thoseconditions can result in poverty for the family and the individual, and requires non-out-of-pocketassistance such as social welfare or health insurance coverage. Since 2007 in Jamaica, healthcare coverage for children (0-18 years) is free and offers much assistance to those who are poorand suffering from health conditions, and by extension reduces the medical care out-of-pocketpayment for adolescents. In spite of this positive, chronic disease management is a socio-economic and psychological burden not only for the adolescents but their families. Chronicdiseases are more than a public health concern, they account for a substantial percentage ofmortality each year and in the United States studies show that 10% of the adolescent population(or 20 million) have some type of such condition [42, 43], and while the number of Jamaicanadolescents who are affected are substantially a smaller percentage than in America or evenSwitzerland [44]—11.4% of girls and 9.6% of boys—the reality of Jamaican adolescents livingwith chronic diseases do exist.According to the WHO [29], it is estimated that 60% of all mortalities in 2005 were a result ofchronic illnesses. While injuries accounted for more deaths of adolescents in Jamaica thanchronic conditions, understanding general health condition is still as important as reproductivehealth risk and infant mortality, as it could lead to premature mortality or could mean that thecost of health care expenditures by the state could substantially increase if those with chronicconditions live to become part of the elderly population (60+ years). Health denotes longevity, 195
  • 213. and ill-health suggests that the quality of life of those affected will be lower than those with goodhealth. If ill adolescents are to live a long life, health care services should cater to their needs;this postulate was equally uttered by Sawyer et al. [45]There is another management epidemic which this paper has unearthed, which is the shift inhealth conditions to the unspecified classification. With 4 in every 10 Jamaican adolescentshaving unspecified health conditions, and 5 in 10 older adolescents, this silent category could bea premature mortality group for this age cohort. Chronic diseases management therefore musttreat this unspecified category with urgency, as the fact that so many of the sample were in thisgroup, an understanding of its components will provide better modalities of responding to theprecarious health care needs of this silent group.ConclusionsThe general health status of adolescents (aged 10-19 years) in Jamaica is very good, with 93 outof every 100 indicating that they have had no illness/injury in the survey period. In spite of thesmall numbers who have ill-health, the most prevalent health condition in 2007 was in theunspecified category, which is a shift away from colds in 2002. Interestingly, this paper showedan exponential increase in the number of diabetic adolescents in 2007 over 2002. In 2007, thenumber of diabetic adolescents increased by 700% and hypertension increased by 175%,indicating that this is a public health challenge. There is an immediate need for a healthpromotion and education campaign geared towards the sensitization of adolescents about the risein chronic illness and its challenges, lifestyle practices, and willingness to seek care if particularsymptoms are presently affecting them. 196
  • 214. Conflict of InterestThe author has no conflict of interest to report.AcknowledgementThe author would like to extend his deepest appreciation to Ms. Neva South-Bourne forproofreading the final manuscript.References1. Statistical Institute of Jamaica, (STATIN). Demographic statistics, 2007. Kingston, STATIN;2008.2. Department of Economic and Social Affairs, Population Division, United Nations, (UN).World population ageing 1950-2050. New York: UN; 2002.3. McCaw-Binns, A et al. Multi-source method for determining mortality death in Jamaica; 1996and 1998. Consultant report to the Pan American Health Organization, August 2002. 56 pages.4. McCaw-Binns A, et al. Registration of births, stillbirths and infant deaths in Jamaica.International Journal of Epidemiology 1996;25(2):807-813.5. Lindo J. Jamaican perinatal mortality survey, 2003. Consultant report to the Jamaica Ministryof Health, April 2006, 40 pages.6. Fox K, et al. Assessing the level of births and birth registration in Jamaica. Consultant reportto the Jamaica Ministry of Health. April 2006. 29 pages.7. Desai P, et al. Infant mortality rates in three parishes of western Jamaica, 1980. West IndianMed J 1983;32:83-87.8. Gayle H. Adolescent Male Survivability in Jamaica. Kingston: The Jamaica AdolescentReproductive Health Project (Youth. now); 2002.9. Waszak GC, Wedderburn M, McCArraher D, Cuthbertson C, Pottinger A. Sexual violenceand reproductive health among young people in three communities in Jamaica. J InterpersViolence 2006;11:1512-33.10. Ekundayo OJ, Dodson-Stallworth J, Roofe M, Aban IB, Bachmann LH, Kempf MC, Ehiri J,Jolly PE. The determinants of sexual intercourse before age 16 years among rural Jamaicanadolescents. Scientific World J 2007;7:493-50311. Lowe GA, Gibson RC, Christie CD. HIV infection, sexual abuse and social support inJamaican adolescents referred to psychiatric service. West Indian Med J 2008;57(3):307-11.12. Eggleston E, Jackson J, Hardee K. Sexual Attitudes and Behavior Among YoungAdolescents in Jamaica. Family Planning Perspectives 1999;25 (2). 197
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  • 217. 41. Eldemire D. A situational analysis of the Jamaican elderly, 1992. Kingston: The PlanningInstitute of Jamaica; 1995.42. Boice MM. Chronic illness in adolescence. Adolescence 1998;33: 927-939.43. Evans T. A multidimensional assessment of children with chronic physical conditions.Health and Social Work 2004;29.44. Miauton L, Narring F, Michaud P-A. Chronic illness, life style and emotional health inadolescence: results of a cross-sectional survey on the health of 15-20-year-olds in Switzerland.European J of Pediatrics 2004;162(10):682-689.45. Sawyer SM, Blair S, Bowes G. Chronic illness in adolescents: Transfer or transition to adultservices. J of Paediatrics and Child Health 2008; 33(2):88-90. 200
  • 218. Figure 8.1. Health condition for 2002 and 2007 201
  • 219. Table 8.1. Adolescents Mortality and Live Birth by Sex, 1998-2007 YearVariable 1999 2000 2001 2002 2003 2004 2005Occurrence of 20.8 204 20.2 20.0 19.4 19.3 18.7live birth(female < 20yrs)Mortality: Male 1.86 1.76 1.88 1.38 2.34 2.38 2.40 Female 1.18 1.17 1.19 1.61 1.11 1.15 1.16 Total 1.6 1.5 1.6 2.1 1.8 1.8 1.8Source: Figures were computed by author from the Demographic Statistics for 2007 202
  • 220. Table 8.2: Treatment for Gunshot wounds at the Accident and Emergency Depts. Of Public Hospitals by Genderand Age cohort (in %): 1999-2002Age cohort Year 1999 2000 2001 2002 Male Female Male Female Male Female Male Female< 5 years 0.8 1.3 0.2 3.1 0.2 0.0 0.0 0.05-9 years 0.3 3.0 0.7 1.9 0.3 1.1 0.3 0.610-19 years 17.9 24.5 16.2 18.5 10.2 17.0 13.9 17.020-29 years 39.0 32.5 40.5 30.2 35.8 19.4 36.6 35.230-44 years 30.6 23.6 31.1 11.1 32.3 26.9 29.3 32.145-64 years 6.6 12.2 6.7 28.4 10.7 22.3 8.9 11.365+ years 3.5 3.0 2.3 11.1 6.7 12.7 8.8 3.6Not unknown 1.4 0.0 2.2 1.2 3.8 0.7 2.3 0.6Total % 100 100 100 100 100 100 100 100Calculated by Paul A. Bourne from Annual Report, 2002 published by the Policy, Planning and DevelopmentDivision, Ministry of Health, Jamaica 203
  • 221. Table 8.3: Visitation to the Accident and Emergency Depts. Of Public Hospitals for attempted suicide by Genderand Age cohort (in %): 2000-2002Age cohort Year 2000 2001 2002 Male Female Male Female Male Female< 5 years 0.0 0.0 1.0 0.0 1.0 0.95-9 years 0.0 3.4 2.0 0.0 2.0 3.510-19 years 19.0 39.3 13.0 49.4 13.0 38.320-29 years 24.1 36.0 20.0 34.8 20.0 36.530-44 years 34.5 13.5 13.0 6.7 13.0 17.445-64 years 12.1 2.2 4.0 3.4 4.0 0.965+ years 6.9 3.4 4.0 2.2 4.0 0.0Not unknown 3.4 2.2 0.0 3.4 1.7 2.6Total % 100 100 100 100 100 100Calculated by Paul A. Bourne from Annual Report, 2002 published by the Policy, Planning and DevelopmentDivision, Ministry of Health, Jamaica 204
  • 222. Table 8.4. Demographic characteristic of sample 2002 2007 Variable Urban Semi- Rural Urban Semi- Rural urban urbanHealth Insurance coverage* No 87.2 86.3 93.1 80.6 86.4 87.4 Yes, Public 12.8 13.7 6.9 6.1 4.0 5.5 Yes, Private - - - 13.3 9.6 7.0Health conditions Cold 25.0 28.8 28.7 11.1 37.5 26.0 Diarrhoea 3.1 8.8 3.7 0.0 0.0 2.0 Asthma 34.4 17.5 26.2 25.9 18.8 12.0 Diabetes mellitus 0.0 1.3 0.0 0.0 0.0 6.0 Hypertension 0.0 0.0 0.6 3.7 0.0 0.0 Arthritis 0.0 0.3 0.0 - - - Other 25.0 21.3 26.8 40.7 31.3 34.0 No 12.5 21.3 14.0 18.5 12.5 20.0Pregnancy No 98.1 97.0 98.4 Yes 1.9 3.0 1.6Educational level* Primary and below 4.3 3.3 4.7 36.6 48.6 46.1 Secondary or high 93.6 98.2 94.0 56.5 48.6 53.0 University 2.1 1.5 1.3 6.9 2.9 0.9Population Income quintile* Poorest 20% 13.7 15.0 25.7 12.2 12.9 33.0 Poor 14.6 16.7 23.9 13.5 24.7 28.6 Middle 21.1 22.2 22.3 22.3 20.2 19.8 Wealthy 24.4 22.2 18.9 25.1 22.0 14.2 Wealthiest 20% 26.3 23.9 9.2 26.9 20.2 4.5Length of illness – Mean (SD) in 7.19 (6.29) 7.86 7.8 5.96 (5.74) 28.38 33.4days (7.46) (8.14) (89.9) (148)No of visits - Mean (SD) in days 1.4 (1.3) 1.4(0.6) 1.5(1.0) 1.13 1.38 1.19 (0.516) (0.518) (0.402)Health care-seeking behaviour No 48.0 56.6 44.0 40.7 50.0 48.0 Yes 52.0 43.4 56.0 59.3 50.0 52.0Age Mean (SD) in years 14.4 (2.91) 14.4 14.2 14.43 (2.7) 14.22 14.01 (2.85) (2.85) (2.90 (2.7)*P < 0.05 205
  • 223. Table 8.5. Health conditions by medical care-seeking behaviour, 2002 and 2007 2002* 2007 Do not seek Sought medical Do not seek Sought medicalHealth conditions medical care care medical care care % % % %Cold 43.60 14.20 37.20 12.00Diarrhoea 4.50 5.70 0.00 2.00Asthma 19.50 29.10 18.60 16.00Diabetes mellitus 0.00 0.70 2.30 4.00Hypertension 0.00 0.70 0.00 2.00Arthritis 0.80 0.00 0.00 0.00Other 11.30 38.30 32.60 38.00 *P < 0.05, χ2 (df = 7) = 49.823, cc = 0.392 206
  • 224. Table 8.6. Health conditions by health insurance coverageHealth 20021 20072Condition No health Health No health Health insurance insurance insurance insurance Private Public % % % % %Cold 28.7 24.0 26.7 16.7 0.0Diarrhoea 5.6 0.0 1.3 0.0 0.0Asthma 21.9 52.0 17.3 16.7 16.7Diabetes 0.0 4.0 1.3 0.0 33.3mellitusHypertension 0.4 0.0 1.3 0.0 0.0Arthritis 0.0 4.0 - - -Other 27.1 4.0 34.7 50.0 16.7 1 P < 0.05, χ2 (df = 7) = 35.222, cc = 0.336 2 P < 0.05, χ2 (df = 12) = 22.641, cc = 0.442 207
  • 225. Table 8.7. Health condition by age cohort, 2002 and 2007 20021 20072Health condition Adolescents Adolescents Younger Older Younger Older % % % %Cold 29.0 27.2 31.0 11.4Diarrhoea 4.3 6.1 0.0 2.9Asthma 27.2 21.1 19.0 14.3Diabetes mellitus 0.6 0.0 5.2 0.0Hypertension 0.0 0.9 0.0 2.9Arthritis 0.0 0.9 - -Other 22.2 28.9 27.6 48.61,2 Not statistically significant (P > 0.05) 208
  • 226. Chapter 9Self-reported Health of Youth: Using Health Conditions tomeasure HealthIntroductionMost studies that have examined quality of life, wellbeing and health status have substantiallybeen on the entire population (Grossman, 1972; Smith and Kington, 1997; Diener 1984, 2000;diTella R, MacCulloch RJ, Oswald, 200; Lyubomirsky, 2001; Pacione, 2003; Murphy andMurphy, 2006;), elderly (Eldemire, 1987a, 1987b, 1994, 1995a, 1995b, 1996; Grewal et al.,2004; Hambleton and colleagues, 2005; Ali et al., 2007; Bourne, 2007a, 2007b; ), for youngadults (person ages 15 to 50 years) (Hutchinson and colleagues, 2004), and for nations(Blanchflower and Oswald, 2002; Lima and Novo, 2006). Although youth is a vulnerable groupin the Caribbean, in particular Jamaica, research on this group have failed to investigate thegeneral quality of life of this cohort or for that matter health status (Gayle, 2001; Gayle andcolleagues, 2004; Anglin-Brown, Weller, Mullings, 2007; Eyre et al., 2007; Lipps, Lowe,Halliday, Morris, Clarke, 2007; Lipps, Lowe, Morris, Clarke, and Halliday, 2007; McFarlane andcolleagues, 2007; Knight-Madden, Ferguson, Younger, Tulloch-Reid, Samms-Vaughan, Ashley,Wilks, 2007). Hence, what about the youth, their quality of life and/or their health status? In a two part study conducted by Anglin-Brown, Weller and Mullings, the researchersfound some interesting issues about University of the West Indies‘, Mona, Jamaica (UWI)students ages 18 years and older. Part 1 of the study was a survey of 1,219 respondents on their 209
  • 227. sexual health behaviour. This paper was conducted in 2006; and the second part of the study wasa qualitative research on 95 UWI students, Jamaica. Wellness which is a component of qualityof life or wellbeing is the closest caption of a study that investigates quality of life; but thisresearch was highly limited as it focused on sexual behaviour and an intervention programme.Ergo the quality of life or health status of the youth is left untapped and lowly research byCaribbean scholars, in particular Jamaican academics and/or researchers. Hence, the currentstudy seeks to bridge the gap that presently exists in the literature as well as provide an insight onfactors that affect their self-reported health status. Crime statistics show that most of the crimes that are committed by and/or leveled againstyouth or for that matter against young adults (Tables 9.1.1 - 9.1.6) are on the rise and within thiscontext; it is timely that we investigate youth‘s health status. And how are they influenced bycrime and other sociodemographic and psychological variables?MethodThis paper is taken from a secondary observational cross-sectional survey data of 25,018Jamaicans. The data were collected by two reputable statistical institutions within the countrybetween June and October, 2002. The nationally representative survey from which this researchis taken used stratified random sample to collect the pertinent data, across the nation. Thecurrent study selected youths (person ages 15 to 25 years), which totaled 4,719 persons. Datawere stored, retrieved and analyzed using SPSS 12.0. For this research, the author useddescriptive statistics, and bivariate analysis (Cross-Tabulations). Logistic regression was used totest the general hypothesis and establish the final model, Eq. (5). 210
  • 228. MeasuresSelf-reported Health Conditions (or reported Health Illness/dysfunction or ailment): This variable is the summation of all reported health conditions (i.e. number of illness/injury reported by an individual for a 4-week period, which was established by for the survey period).Self-reported Health Status: This is a dummy variable of self-reported health conditions, where 1=low reported health status (or at least one reported health conditions), 0=high reported health status (or reported no health conditions).Crime: Crime Index = Σ kiTj, where Ki The equation represents the frequency with which an individual witnessed or experience a crime, where i denotes0, 1 and 2, in which 0 indicates not witnessing or experiencing a crime, 1 means witnessing 1 to 2, and 2 symbolizes seeing 3 or more crimes. Ti denotes the degree of the different typologies of crime witnessed or experienced by an individual ( where j=1 …4, which 1=valuables stolen, 2=attacked with or without a weapon, 3= threatened with a gun, and 4= sexually assaulted or raped. The summation of the frequency of crime by the degree of the incident ranges from 0 and a maximum of 51.Household crowding: (proxy by the average occupancy of persons per room). Total number of individuals living in a household (Household size – all members) divided by the number of room occupied by that household (excluding the kitchen and bathroom).Physical Environment: This is a dummy variable, which in response to questions – (1) Has this household been affected by landslides, floods, or other natural disasters during the last 12 months) - No (2) was recoded as 0, Yes (1) remained as -1 and not stated was declared as missing; and (2) ‗What do you know or believe has caused these health effects?‘ 211
  • 229. Negative Affective Psychological Condition: Number of responses from a person on having loss a breadwinner and/or family member, loss of property, made redundancy, failure to meet household and other obligations.Positive Affective Psychological Condition: Number of responses with regards to being hopeful, optimistic about the future and life generally.Theoretical FrameworkAll research is driven by either a conceptual or a theoretical framework. It is this framework,which guides the research materials, used, the methodologies, the methods of data collection, theanalysis of data, along with the research objectives and the research questions. Hence, theframework plays a fundamental role in the research process. In this paper we will use atheoretical framework as a similar platform as already being established that will guide thecurrent study, the Grossman Model. The overarching theoretical framework that is adopted in this paper is an econometricmodel that was developed by Grossman (1972), and further modified by Smith and Kington1997, which read (Eqn. (1): Ht = ƒ (Ht-1, Go, Bt, MCt, ED) ……………………………..…………..………… (1) In which the Ht – current health in time period t, stock of health (Ht-1) in previous period, Bt– smoking and excessive drinking, and good personal health behaviours (including exercise –Go), MCt,- use of medical care, education of each family member (ED), and all sources of 212
  • 230. household income (including current income). Grossman‘s model further expanded upon bySmith and Kington to include socioeconomic variables (Equation 2). Ht = H* (Ht-1, Pmc, Po, ED, Et, Rt, At, Go)……..…………..……………………… (2) Eq. (2) expresses current health status Ht as a function of stock of health (Ht-1), price ofmedical care Pmc, the price of other inputs Po, education of each family member (ED), all sourcesof household income (Et), family background or genetic endowments (Go), retirement relatedincome (Rt ), asset income (At,). Grossman‘s model or that of Smith and Kington‘s work was about the population of theworld, and we believe that each geopolitical locality has its own set of idiosyncrasies, culturalover and undertones, and the developing nations equally have a different set of experiencescompared to those of the developed societies. Hence, within the aforementioned context, weexamine the health status of youth in Jamaica. The general hypothesis that will be tested in thispaper will be different from that of Grossman‘s study or that of Smith and Kington‘s work as thispaper age cohort is dissimilar and so are the predisposed variables. This paper will be usingsecondary data which is one the reasons for the chosen set of variables unlike the aforementionedstudies. Despite that fact, specification was used to ensure that all the pertinent variables wereincluded. Ht = f (Pmc, ED, Et, G, L, D,C, N, M,A, I, BL)………………….……………… (3) where Eq. (3) expresses current health status Ht as a function price of medical care Pmc,education of individual (ED), all sources of household income (Et), gender of respondent (G),household crowding (i.e. number of person living in the household, (L), ownership of durable 213
  • 231. goods, (D), crime index, (C), negative affective conditions (N), physical environment, (M),positive affective conditions, (A), living along (I), health seeking behaviour, (BL).Findings: Sociodemographic Characteristics of Sampled PopulationThe total population for this paper is 4, 719 youth (ages 15 to 25 years), of which there were50.5% males (N=2,379) and 49.8% females (N=2,340) with the mean age of the sampledpopulation being 19.5 years ± 3.1 years. The youth were predominantly never married, 97.2%(N=4,315) with 2.7% indicated that they were married (N=120). However, 3.3% of thepopulation reported that they lived alone (N=154). With regards to the educational level of thepopulation, the response rate to this question was 66.4% (N=3,19); and of those who responded,4.4% (N=139) indicated tertiary level, 2.4% (N=75) at most primary level and the remainder,secondary level (N=2,918). On examining the health status of sampled population (N=4,719), 8.8% reported havinghad at least one illness/injury over last 4-week, which was the period of the survey. Ondisaggregating reported health status, we found that 3.9% (N=38) indicated that they hadsuffered from one illness/injury over the survey period with 4.1% (N=180) mentioned 2ailments/injuries and 0.8% (N=175) said 3 illnesses/injuries, compared to none who reportedmore than 3-ailment. A cross-tabulation of health status by gender revealed that there is astatistical association between the two variables (p value < 0.5) (Table 9.2). The findingsrevealed that approximately 2% more females reported that they were affected by at least oneillness/injury compared to their male counterparts (Table 9.2). Nevertheless, only 2.6% (N=116)indicated that they sought health service for the last 4-week (i.e. a referent point in the survey 214
  • 232. period). The findings show that there is no disparity between health seeking behaviour of malesand females (p value > 0.05, Table 9.2). Finding: Hypothesis testingUsing econometric analysis and the concept of not utilizing a variable that has more than 15% ofmissing cases, variable(s) will be withdrawn from Eq. (3) if they violate this criticalspecification. Ht = f (Pmc, ED, Et, G, L, D, C, N, M, A, I, BL)……. ….…..……………………… (3) By aforementioned specification, we will exclude cost of medical care, (Pmc) from Eq.(3), as such the modified hypothesis that we will tested in this paper is Eq. (4): Ht = f (ED, Et, G, L, D, C, N, M, A, I,BL)… ………………..……………………… (4) The model that we will forward for this paper is based on the principle of parsimony,which stipulates that only those variables that are statistically significant (p value < 0.05) will beused for the final model, Eq. (5): Ht = f (Et, L, C, M, I, BL)……………… …..………………………………..………(5)Findings: Examination of Final Model and its Interpretation, Eq. (5)Using the principle of parsimony, of the 11 predisposed variables that were placed in Eq. (4), 6of them explain the variability in reported health status of youth. The 6 factors explain 20%(Nagelkerke R-squared; χ2 (12) = 279.401, p value = 0.001; -2Log likelihood = 1,504.198) of the 215
  • 233. variance in health status of youth. These factors are household income, household crowding,crime, physical environment, living alone, and health seeking behaviour (Table 9.2). The mostinfluential factor is Health seeking behaviour (Wald statistic = 185.6), followed by householdincome (Wald statistic = 15.2), living alone (Wald statistic = 12.3), household crowding (Waldstatistic = 4.4), crime (Wald statistic = 4.1) and lastly by physical environment (Wald statistic =3.9). Of the 6 factors that influence health status of the sampled population, only householdcrowding negative associate with health status with the others showing a positive statisticalassociation. Further examination of the 6 factors revealed that a youth who seeks health care is 46times (ie. Odd ratio more likely to have a lower health status compared to another who does not.A similar result was observed for having experienced crime or a family member being victimizedby crimes. The results revealed that the more crimes that a youth experienced or his/her familymember experienced, he/she is 1 time more likely to have a lower health status. A youth whodwell in a physical environment which is ‗poor‘ is 1.5 times more likely to have a lower healthstatus; and someone who lives along is approximately 3 times more probable to have a lowerhealth status compared to a youth who dwelled with other person. Continuing, the more peoplelive in a room (i.e. household crowding), the more they will report health conditions (i.e. thelower there will be the health status of the individual). Furthermore, from the current research(Table 9.3), we found that a respondents who is in an household who has more income has morehealth conditions or he/she has a lower reported health status. Having established the final model, (Eq. (2)), we need to examine how does the data fitthe model? Of the population for this research (N=4,719), 65% (N=2,955) were used for the 216
  • 234. model. Of the respondents used for this model (Eq. (5)), 92.5% (N=2,79) of the data werecorrected classified: 99.2% of those indicated no reported health status (proxy by dysfunctions)and 23.8% who indicated more than or equal to 1 reported health conditions. (Table 9.4).Discussion and ConclusionHealth, health status and wellbeing are not only important owing to their construction, butbecause of their contribution to production, productivity, all for of development and socialadvancement (or the lack thereof). Hence, the current study is critical to patient care, policydevelopment, fashioning of social programme and broader the provision of an understanding of avulnerable group, youth. Youth constitutes a crucible part of future population dynamics, labourforce participation, productive labour and so any understanding of their health status embodies acomprehension present and future population dynamics. Jamaican youth continue to bemarginalized by the general populace as the society believes that the current state of the crimephenomenon facing the nation is arguable caused by youth, and so little time is spent inunderstanding what makes them who they are as well as the factors that explain theirfunctioning. Health status is a good investigation that will provide us with some insight into thepsyche of youth as well as their open a widow whereby policy makers may effective plan for thisage cohort. The current study has provided us with information that shows that health-care seekingbehaviour is the most primary (or influential) factor of health state. There examination of thisvariable revealed that youth who seek health-care are 46 times more probable to have a lowerhealth state compared to those who do not seek this care. This means that internal factor is mostsignificant to the health state of youth; while household income is second to health-care seeking 217
  • 235. behaviour. The household income of families in which youth dwell is pivotal to their healthstatus or health (i.e. quality of life). This paper has found that youth‘s living arrangement was ofextreme value to their health status, as living along meant that they will be less likely to have agreater health status. On the other hand, the more people live in a room with the elderly, thegreater will be that youth‘s health status. Embedded in this finding is the fact that this suggestedthat the youth will experience more dysfunctions, ailment/illnesses or diseases. This research has refuted some established facts. One such is the fact that educationallevel is not related to health status (this contravenes the works Grossman, 1972; Smith andKington, 1997; Bourne, 2007a, 2007b; Diener, 1985, 2000; Koo, Rie and Park; Freeman andMartin 1999; Ross and Mirowsky, 1999) as well as the relation between material resources (i.e.ownership of durable assets) as well as the well document fact of the strong statisticalrelationship between psychological state and health status. McConville et al. (2005) in ‗Positiveand negative mood in the elderly: the Zenith study’ established that different moods of peopleaffect both their physical as well as their mental wellbeing (Kart, 1990). Notwithstanding thisreality, the other factors are in keeping with the literature that shows the link between onesphysical environment and his/her low health status (Pacione, 2003) and similarly the relationbetween household income and health status or life expectancy (Anand and Ravallion 1993; Sen1989), living alone and health status as well as household crowding and health status. One of the interesting findings of current research lies in the fact that greater householdincome is statistically associated to lower health state. This is contradiction to the literature.Benezeval, Judge and Shouls‘s work (2001) argue that income can buy better health, which wasdisproved by this paper. Another important piece of information was the facts that like other 218
  • 236. scholarships (Smith and Kington, 1997; Case 2001; Kawachi et al 1997), income still lowlyinfluences health status of an individual. Such a finding highlights the fact that income mattersin determining health status. One scholar aptly puts in perspective when he argued that ―Povertyalso leads to increased dangers to health: working environments of poorer people often holdmore environmental risks for illness and disability; other environmental factors, such as lack ofaccess to clean water, disproportionately affect poor families‖ (Murray 2006, 923), whichreiterates the importance of income to health and/or health status of an individual, family, societyor nation. Furthermore, studies exist that clearly show a relationship between persistent andelongated poverty and health and even mortality (Lynch et al. 1997; Menchik 1993; Zick andKen 1991). Within the previous mentioned argument, the current study took its data fromsecondary cross-sectional data and so this contradict can be as a result of situations at the time ofthe survey. The current work is a base upon which further study may build, critique, modify, orrefute. Notwithstanding the aforementioned matter that may arise, we like readers to becognizant that it does not provide all the answers; but it provides a spring board upon whichfuture study may seek to clarify and provide more insight as well as aiding policy makersunderstanding this cohort and thereby effect programmes that will address the perspectives ofthis vulnerable group.AcknowledgementThe author would like to take this opportunity to recognize the contribution of Orville Beckford,Lecturer in the Department of Psychology, Sociology and Social Work, for his comments andsuggestions on different reviewed drafts of this paper. 219
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  • 240. Table 9.2: Sociodemographic Characteristics of Sampled Population By genderDetails Male Female p valueMarital Status 0.001 Married 1.3 4.1 Single 98.6 95.8 Divorced 0.1 0.1 Separated 0.0 0.0 Widowed 0.0 0.0Health Status 0.029 No Illness/injury 92.0 90.4 1 or more illness/injury) 8.0 9.6Living Alone 0.001 No 95.5 97.9 Yes 4.5 2.1Educational level 0.001 Primary and below 3.2 1.5 Secondary & Post-secondary 94.3 92.0 Tertiary 2.6 6.5Health Seeking Behaviour 0.085 No 97.8 97.1 Yes 2.2 2.9Mean age 19.57 yrs. ±3.104yrs 19.62 yrs. ±3.149 yrs.Household crowding 1.9 persons±1.2 2.2 persons ± 1.4 0.001Positive Affective condition 3.7 (out of 6) ± 2.2 3.7 (out of 6) ± 2.3 0.985Negative Affective condition 4.8 (out of 15) ±3.3 4.8 (out of 15) ± 3.4 0.621Crime Index 2.4 (out of 88) ± 8.2 2.4 (out of 88) ± 9.1 0.988 223
  • 241. Table 9.3: Self-reported Health Status of Youth with some Sociodemographic and Psychological Factors, (N=2,955) B S.E. Wald Odds Characteristic p value ratio CI (95%) Lower Upper Durable Goods -0.09 0.024 1.835 0.176 0.968 0.924 1.015 Health seeking 3.838 0.282 185.612 0.000 46.417 26.724 80.621 behaviour Secondary Edu -0.305 0.438 0.483 0.487 0.737 0.312 1.741 Tertiary Edu 0.203 0.520 0.152 0.696 1.225 0.442 3.397 Crime Index 0.014 0.007 4.055 0.044 1.014 1.000 1.027 Gender -0.216 0.146 2.190 0.139 0.806 0.606 1.072 Negative Affective 0.014 0.024 0.353 0.553 1.014 0.968 1.062 Environment 0.372 0.188 3.918 0.048 1.451 1.004 2.097 Positive Affective -0.019 0.033 0.342 0.559 0.981 0.919 1.046 Household Income 0.000 0.000 15.210 0.000 1.000 1.000 1.000 Living Alone 0.992 0.283 12.91 0.000 2.696 1.550 4.690 Household crowding -0.061 0.029 4.377 0.036 0.940 0.888 .996 Constant -2.106 0.522 16.294 0.000 0.122χ2 (12) = 279.401, p value = 0.001-2Log likelihood = 1,504.198,Nagelkerke Squared-R = 0.199 224
  • 242. Table 9.4: Classification Table for Final Model, Eq. (5) Predicted Observed Binary Health Status (1=Dysfunctions) Percentage .00 1.00 Correct Binary Health .00 Status 2669 21 99.2 (1=Dysfuncti ons) 1.00 202 63 23.8 Overall Percentage 92.5 225
  • 243. Table 9.1.1: Arrested for Major Crimes By Age Group, 2005 Age Group of Persons Arrested for Major Crimes for 2005 Murder Shooting Robbery Breaking Rape C/AbuseAge Group Male Female Total Male Female Total Male Female Total Male Female Total Male Male Total12-15 6 1 7 4 0 4 10 0 10 54 0 54 12 11 9816-20 157 6 163 167 1 168 183 0 183 122 3 125 66 43 74821-25 235 8 243 239 1 240 214 1 215 129 3 19 68 52 95026-30 160 2 162 137 0 137 120 1 121 105 3 108 73 27 62831-35 85 1 86 74 0 74 71 1 72 93 2 95 48 26 40136-40 54 3 57 40 1 41 36 1 37 69 0 69 23 19 24641-45 15 0 15 12 0 12 13 0 13 44 1 45 18 12 11546-50 7 1 8 2 0 2 1 0 1 18 0 18 12 5 4651-55 5 1 6 0 0 0 2 0 2 2 0 2 3 2 1556-60 1 0 1 1 0 1 6 0 6 1 1 2 1 1 1261& Over 0 0 0 2 0 2 2 0 2 3 1 4 2 0 10Unknown 40 0 40 86 0 86 23 0 23 11 0 11 10 0 170Total 765 23 788 764 3 767 681 4 685 651 14 665 336 198 3439 Source: Statistics Department, Jamaica Constabulary Force 226
  • 244. Table 9.1.2: Arrested for Major Crimes By Age Group, 2004 Age Group of Persons Arrested for Major Crimes for 2004 Murder Shooting Robbery Breaking Rape C/AbuseAge Group Male Female Total Male Female Total Male Female Total Male Female Total Male Male Total12-15 12 3 15 5 1 6 18 0 18 34 3 37 14 12 10216-20 123 5 128 129 0 129 190 1 191 147 4 151 101 58 75821-25 236 5 241 241 0 241 253 2 255 168 8 176 88 52 105326-30 153 4 157 158 0 158 143 0 143 143 1 144 96 31 72931-35 88 4 92 87 0 87 115 1 116 98 0 98 58 9 48336-40 52 2 54 35 0 35 49 0 49 83 1 84 30 11 26341-45 28 2 30 9 0 9 11 0 11 53 2 55 16 13 13446-50 5 0 5 6 0 6 2 0 2 21 1 22 7 3 4551 & Over 8 0 8 8 0 8 5 0 5 16 1 17 13 2 53Total 705 25 730 678 1 679 786 4 790 763 21 784 423 214 3620 Source: Statistics Department, Jamaica Constabulary Force 227
  • 245. Table 9.1.3: Arrested for Major Crimes By Age Group, 2003 Age Group of Persons Arrested for Major Crimes for 2003 Murder Shooting Robbery Breaking Rape C/AbuseAge Group Male Female Total Male Female Total Male Female Total Male Female Total Male Male Total12-15 5 0 5 3 0 3 16 0 16 44 6 50 37 6 11716-20 114 4 118 149 0 149 231 0 231 143 3 146 115 61 82021-25 210 4 214 218 3 221 267 3 270 130 4 134 124 48 101126-30 137 2 139 105 0 105 206 1 207 128 5 133 89 36 70931-35 81 1 82 89 0 89 145 2 147 113 4 117 86 11 5936-40 59 1 60 41 0 41 57 1 58 74 1 75 34 11 27941-45 27 3 30 18 0 18 18 0 18 25 0 25 22 11 12446-50 17 1 18 10 0 10 6 0 6 13 1 14 14 9 7151 & Over 7 0 7 10 0 10 4 0 4 13 0 13 14 9 57Total 657 16 673 643 3 646 950 7 957 683 24 707 535 202 3720 228
  • 246. Table 9.1.4: Arrested for Major Crimes By Age Group, 2002 Age Group of Persons Arrested for Major Crimes for Year 2002 Murder Shooting Robbery Breaking Rape C/AbuseAge Group Male Female Total Male Female Total Male Female Total Male Female Total Male Male Total12-15 5 1 6 1 2 3 11 0 11 37 3 40 21 10 9116-20 134 4 138 118 7 125 185 1 186 138 5 143 103 58 75321-25 168 5 173 234 0 234 318 2 90 193 7 200 90 36 100326-30 117 3 120 156 1 157 204 2 206 141 1 142 68 27 68631-35 70 0 70 59 1 60 77 4 81 122 3 125 61 11 38936-40 29 2 31 27 0 27 41 0 41 79 0 79 25 16 20141-45 14 1 15 9 0 9 17 0 17 9 1 33 26 5 9846-50 8 1 9 8 0 8 6 1 7 11 1 12 8 4 4151 & Over 4 0 4 1 0 1 1 0 1 6 0 6 6 8 18Total 549 17 566 613 11 624 860 10 870 759 21 780 408 175 3423 Source: Statistics Department, Jamaica Constabulary Force 229
  • 247. Table 9.1.5: Arrested for Major Crimes By Age Group, 2001 Age Group of Persons Arrested for Major Crimes 2001 Murder Shooting Robbery Breaking Rape C/AbuseAge Group Male Female Total Male Female Total Male Female Total Male Female Total Male Male Total12-15 7 0 7 5 0 5 15 1 16 43 4 47 13 12 10016-20 116 5 121 142 2 144 181 2 183 201 8 209 122 33 81221-25 164 4 168 215 1 216 269 2 271 201 4 205 114 43 101726-30 130 4 134 166 2 168 173 0 173 191 4 195 89 30 78931-35 63 2 65 58 1 59 117 3 120 106 5 111 58 16 42936-40 36 2 38 9 2 34 40 1 41 79 1 80 30 9 2941-45 12 1 13 6 0 6 12 0 12 36 1 37 19 6 9346-50 7 1 8 13 0 13 6 0 6 8 1 9 4 5 4551& Over 11 0 11 5 0 5 4 0 4 6 1 7 5 9 41Total 546 19 565 642 8 650 817 9 826 871 29 900 454 163 3558 Source: Statistics Department, Jamaica Constabulary Force 230
  • 248. Table 9.1.6: Victims of Major Crimes by Age Cohorts, 2005 Age Group Victim For Major Crimes For Year 2005 Murder Shooting Robbery Breaking Rape C/Abuse G.Total Age Group Male Female Total Male Female Total Male Female Total Male Female Total Female Female Total 0-4 2 4 6 3 1 4 0 0 0 0 0 0 3 3 16 5-9 3 5 8 0 5 5 1 0 1 0 0 0 27 15 56 10-14 10 8 18 4 11 15 16 11 27 0 6 6 212 223 501 15-19 122 18 140 107 13 120 59 49 108 8 17 25 223 103 719 20-24 268 23 291 212 30 242 162 115 277 52 75 127 122 0 1059 25-29 252 33 285 192 22 214 233 130 363 81 106 187 48 0 1097 30-34 223 22 245 161 16 177 198 112 310 114 115 229 28 0 989 35-39 177 17 194 138 15 153 199 102 301 140 104 244 23 0 915 40-44 139 12 151 107 15 122 171 77 248 116 107 223 17 0 761 45-49 72 16 88 68 5 73 146 44 190 98 75 173 12 0 536 50-54 46 9 55 46 8 54 98 9 130 75 47 122 7 0 368 55 & Over 81 16 97 50 6 56 152 66 218 171 100 271 16 0 658 Unknown 91 5 96 408 3 411 28 9 37 9 14 46 8 2 600 Total 1486 188 1674 1496 150 1646 1463 747 2210 887 766 1653 746 346 8275 Total Reported 1674 1646 2210 1653 746 346Source: Statistics Department, Jamaica Constabulary Force 231
  • 249. Chapter 10The changing faces of diabetes, hypertension and arthritis in aCaribbean population Paul A. Bourne, Samuel McDaniel, Maxwell S. Williams, Cynthia Francis, Maureen D. Kerr-Campbell & Orville W. BeckfordGlobally, chronic illnesses are the leading cause of mortality, and this is no different indeveloping countries, particularly in the Caribbean. Little information emerged in the literatureon the changing faces of particular self-reported chronic diseases. This paper examines thetransitions in the demographic characteristics of those with diabetes, hypertension and arthritis,as we hypothesized that there are changing faces of those with these illnesses. A sample of 592respondents was drawn from the 2002 and 2007 Jamaica Survey of Living Conditions. Onlyrespondents who indicated that they were diagnosed with these particular chronic conditionswere used for the analysis. The prevalence of particular chronic diseases increased from 8 per1,000 in 2002 to 56 per 1,000 in 2007. The average annual increase in particular chronic diseaseswas 17.2%. Diabetes mellitus showed an exponential average annual increase of 185% comparedto hypertension (+ 12.7%) and arthritis (- 3.8%). Almost 5 percent of diabetics were less than 30years of age (2.4% less than 15 years), and 41% less than 59 years. Three percent of hypertensiverespondents were 30 years and under as well as 2% of arthritics. The demographic transition inparticular chronic conditions now demands that data collection on those illnesses be lowered to <15 years. This research highlights the urgent need for a diabetes campaign that extends beyondparents to include vendors, confectionary manufacturers and government, in order to address thetsunami of chronic diseases facing the nation.IntroductionGlobally, chronic illnesses are the leading cause of mortality (60%) [1, 2], and this is no differentin developing countries, particularly in the Caribbean [2-6]. Statistics indicate that 79% of allmortalities are attributable to chronic diseases, and that they are occurring in developingcountries such as those in the Caribbean [3]. Using data for 1989 and 1990, Holder & Lewis [7] 232
  • 250. showed that hypertension and diabetes mellitus were among the 5 leading causes of mortality inthe English-speaking Caribbean and Suriname. The findings from Holder and Lewis indicatedthat mortality resulting from hypertension was highest in Dominica (over 90 per 100,000 of thepopulation) and diabetes crude death rates per 100,000 of the population were the greatest inTrinidad and Tobago (over 85 per 100,000). The 20th century has brought with it massive changes in the typology of diseases, wheredeaths have shifted from infectious diseases such as tuberculosis, pneumonia, yellow fever,Black Death (i.e. Bubonic Plague), smallpox and ‗diphtheria‘ to diseases such as cancer, heartcomplaints and diabetes. Although diseases have moved from infectious to degenerate, chronicnon-communicable illnesses have arisen and are still lingering in spite of all the advances inscience, medicine and technology. Morrison [8] titled an article ‗Diabetes and Hypertension:Twin Trouble‘ in which he established that diabetes mellitus and hypertension have now becometwo problems for Jamaicans and people in the wider Caribbean. This situation was corroboratedby Callender [9] and Steingo at the 6th International Diabetes and Hypertension Conference,which was held in Jamaica in March 2000. They found that there is a positive associationbetween diabetic and hypertensive patients - 50% of individuals with diabetes had a history ofhypertension [9, 10]. Prior to those scholars‘ work, Eldemire [11] found that 34.8% of new casesof diabetes and 39.6% of hypertension were associated with senior citizens (i.e. ages 60 andover). In an article published by Caribbean Food and Nutrition Institute, the prevalence rate ofdiabetes mellitus affecting Jamaicans is noted to be higher than in North American and ―manyEuropean countries‖ [9]. Chronic illnesses have been on the rise in the Caribbean. In a 1996 study conducted byMorrison and colleagues in Trinidad and Tobago [12], they noted that there is an alarming rise in 233
  • 251. the prevalence rate of diabetes mellitus (15-18%). A study in Barbados found that between 1988and 1992 the prevalence rate of diabetes mellitus for the population was 17.5%; 12.5% in mixedpopulation (black/white), 6.0% in white/other and 0.3% in the younger population [13]. Anotherresearch, in Europe, found that the prevalence among newly diagnosed diabetics in Europeanswas 20%; African-Caribbeans, 22%; and in Pakistanis, 33% [14]. They also postulated that thereis an association between poverty and diabetes. Van Agt et al. [15] went further when they foundthat poverty was greater among the chronically ill, with which a later study by the World HealthOrganization [16] concurred. The WHO [16] stated that 80% of chronic illnesses were in lowand middle income countries, emphasizing the association between not only diabetes andpoverty, but chronic conditions and poverty. The relationship between poverty and chronicconditions extends to premature mortality [17]. Findings from the WHO [4] showed that 60% ofglobal mortality is caused by chronic illness, which offers an explanation of the face for thosewith these particular conditions. Within the context of a strong association between poverty andchronic illness, the high prevalence of diabetes mellitus, hypertension and other chronicconditions in developing countries should not be surprising [16, 18]. Yach et al. [18] further opined that the global figure for diabetes is projected to movefrom 171 million (2.8%) in 2000 to 366 million (6.5%) in 2030. Of this figure 298 million ofthese persons will be in developing countries, which reinforces the poverty-illness relationship.Chronic diseases can be likened to a tsunami [19] in developing nations [20-22], and it seems tobe spiralling because of the unhealthy lifestyle of people. The tsunami of chronic illnesses in thedeveloping countries is equally reflected in the Americas [20, 21], and particularly Jamaica. Theface of chronic illness in developing nations is therefore for (1) lower socioeconomic strata, (2) 234
  • 252. rural residents, (3) adults, (4) gender differences, (5) lower educational level, and (6) marriedpeople. A great deal of research exists on the management of chronic illnesses, and rightfully so,as these go to the health status and mortality of a population [23, 24]. The profiles of those withchronic diseases have never been examined in Latin America and the Caribbean, and studiesoutside of this region have used a piecemeal approach to the investigation of chronic conditions.Hence information is available on one or a few of the aforementioned faces of chronic illness,and some research has examined diabetes mellitus and hypertension but not arthritis. The presentgap in the literature will be lowered by this paper examining the faces of chronic illness fromhalf a decade of data. Using data for 2002 and 2007, the current paper will investigate thechanging faces of chronic diseases in Jamaica. The study will utilize three chronic diseases (i.e.diabetes mellitus, hypertension, and arthritis), and analyze health status, health insurance status,health care utilization, chronic illness and other sociodemographic characteristics in order toascertain the transition occurring in the population. We hypothesized that there are changingfaces of those with diabetes, hypertension and arthritis over the last half a decade (2000-2007).Materials and methodsDataThe current study extracted a sample of 592 respondents from the 2002 and 2007 JamaicaSurvey of Living Conditions (JSLC). Only respondents who indicated that they were diagnosedwith particular chronic conditions were used for this analysis (i.e. diabetes mellitus,hypertension, and arthritis). The present subsample represents 0.8% of the 2002 national sample(25,018) and 5.7% of the 2007 sample (6,783). The JSLC is an annual and nationally 235
  • 253. representative cross-sectional survey that collects information on consumption, education, healthstatus, health conditions, health care utilization, health insurance coverage, non-foodconsumption expenditure, housing conditions, inventory of durable goods, social assistance,demographic characteristics and other issues [25]. 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 [26]. A self-administeredquestionnaire was used to collect the data. Overall, the response rate for the 2007 JSLC was 73.8% and 72.3% for 2002. Over 1,994households of individuals nationwide are included in the entire database of all ages [27]. Theresidents of a total of 620 households were interviewed from urban areas, 439 from other townsand 935 from rural areas. This sample represents 6,783 non-institutionalized civilians living inJamaica at the time of the survey. The JSLC used complex sampling design, and it is alsoweighted to reflect the population of Jamaica.Statistical analysisStatistical analyses were performed using the Statistical Packages for the Social Sciences forWindows 16.0 (SPSS Inc; Chicago, IL, USA). Descriptive statistics such as mean, standarddeviation, frequency and percentage were used to analyze the socio-demographic characteristicsof the sample. Chi-square was used to examine the association between non-metric variables,and an Analysis of Variance was used to test the equality of means among non-dichotomouscategorical variables. Means and frequency distribution were considered significant at P < 0.05using chi-square, independent sample t-test, and analysis of variance f test. 236
  • 254. MeasuresTable 10.1 presents the operational definitions of some of the variables used in this paper.ResultsHealth care utilization, health insurance status, particular chronic illness (i.e. diabetes mellitus,hypertension and arthritis), and sociodemographic characteristics are presented in Table 10.2.The findings in Table 10.2 showed that the average annual increase in the particular chronicillness was 17.2% between 2002 and 2007. Arthritis showed an average annual reduction of3.8%, hypertension, + 12.7% and diabetes mellitus, + 185.0%. Furthermore, the average annualincrease in health care utilization (visits to health care institutions) was 11.9% (public hospital, +8.2%; private hospital, + 10.7%; public health care centre, + 8.4%; private health care centre, +17.1%). On average the annual increase in health insurance coverage was + 148%; while thehealth care utilization (health seekers) increased by 11.7%. The particular chronic illnesses haveshifted mostly from urban (67.6%) to rural residents (55.1%). This shift could be attributed tocultural factors affecting how and what individuals eat in rural versus urban areas. The sedentarylifestyles of urban areas also added to the overall dramatic increase in chronic illnesses. Table 10.3 presents information on self-reported diagnosed particular chronic illness bysex of respondents for 2002 and 2007. On average, the annual increase in particular chronicillness in males was 19.0% compared to 16.5% in females. Diabetes mellitus showed the highestannual percentage increase (males 186.7% and females 184.4%), while arthritis fell in females(average annual 7.9%) compared to an increase in males (average annual 10.0%). Hypertensionincreased more in females (average annual 14.0%) compared to 9.7% in males. This could be 237
  • 255. attributed to the increasing absorption of females into the upper echelons of management instressful occupations such as banking and finance, law, and the police force. Table 10.4 examines information on health coverage, health status, health care utilizationand some sociodemographic characteristics by self-reported diagnosed particular chronicillnesses for 2002 and 2007. Based on Table 10.4, although particular chronic illnesses havedecreased in rural respondents, rural dwellers continue to be the face of chronic conditions aswell as married, primary, uninsured, private health centres and those in the lower class. Theaverage annual increase in particular chronic illnesses increased by 22.9% for those in the lowerstrata compared to 11.0% for those in the middle class and 16.0% for those in the wealthysocioeconomic strata. However, the greatest increase occurred in diabetics belonging to theupper class (average annual + 200%) compared to those lower class (116.7%). On the otherhand, the highest average annual increase in hypertension occurred in the lower socioeconomicgroup (26.9%) as compared to those in the middle class (7.4%) and upper socioeconomic strata(7.1%). The massive increase in cases of diabetes within the upper class is clearly not due to thelack of resources for seeking health care. A more detailed analysis of their diet and lifestyle isneeded to ascertain the real causes for the drastic increase relative to other socioeconomicgroups. Table 10.5 presents information on the age of respondents and particular self-reportedchronic conditions for 2002 and 2007. Based on this information, there is a change in the face ofparticular chronic ailments in Jamaica. The face is changing to reflect the inclusion of those lessthan 30 years of age (including children) as distinct from the elderly population. 238
  • 256. DiscussionThe present study revealed that the prevalence of particular chronic diseases (i.e. diabetesmellitus, hypertension and arthritis) increased from 8 per 1,000 in 2002 to 56 per 1,000 in 2007.The average annual increase of particular chronic illnesses was 17.2%. Diabetes mellitusshowed an exponential average annual increase of 185% compared to hypertension (+ 12.7%)and arthritis (- 3.8%). While hypertension remained the most prevalent of the particular chronicdiseases in this paper, diabetes mellitus showed the greatest annual increase. The transitions ofparticular chronic conditions are accounted for by (1) urban-to-rural shift, (2) female-to-male, (3)aged-to-young people, and (4) lower socioeconomic strata to upper class. The average annualincrease in particular chronic diseases was greatest among those in the lower socioeconomicgroups. However when the particular chronic ailments were disaggregated, the findings indicatedthat those in the wealthy socioeconomic group had the largest prevalence increase in diabetesmellitus, hypertension was greatest among those in the lower class and those in the upper classhad the greatest reduction in arthritic cases. Particularly of note is the switching from publichealth care utilization by particular chronically ill respondents to private health care utilization.Similarly, the prevalence of health insurance coverage on average saw an exponential annualincrease of 148%, while health care seeking behaviour over the same period showed a marginalincrease of 12%. There is an emerging body of literature to support the changing face of people withparticular chronic diseases from old ages (30+ years) to younger people including children [28-32]. Traditionally chronic conditions such as diabetes mellitus were mostly prevalent among theelderly. This reality supports the large reservoir of literature on elderly diabetic, hypertensiveand arthritic patients. With the emergence of epidemiological and population transition, much 239
  • 257. attention was placed on diseases in middle and later ages as well as those conditions thataccounted for most of the mortality and morbidity in a population. Because lifestyle practiceswere mostly responsible for chronic illness, many researchers limited their investigation topeople 30+ years old [8-11, 23, 33 and 34]. The present paper supports the literature that particular self-reported chronic diseases(such as diabetes, hypertension and arthritis) are found mostly among the elderly (60+ years).The findings revealed that the mean ages of those with the specific self-reported chronic ailmentshave fallen marginally in Jamaica over the period (2002-2007). This is somewhat deceptive as41% of those with diabetes were less than 60 years of age, compared to 40% of those withhypertension and 31% of arthritic respondents. Two percent of diabetic respondents were lessthan 15 years of age, but no children had hypertension or arthritis. Similarly, increases wereobserved in diabetes and arthritis for the young adult (diabetics aged 15 – 30 years) for theperiod. This is evidence that self-reported particular chronic diseases are changing face asalmost 5% of diabetics were less than 31 years old in 2007 compared to 0% in 2002. Anotheremerging face of particular self-reported chronic illness is that of those with arthritis, as almost2% of cases were among people ages 15-30 years of age. The young face of those with diabetes and other chronic diseases can be accounted for by(1) maternal nutrition during pregnancy [31], (2) diet [35] and the environment [30]. Thesedentary lifestyles of the youth in the population are further entrenched by the modernelectronic games which have removed the young person from the playing field and see himspending longer periods on the couch in front of the television. This hooked-on-egame syndromehas also resulted in the increased consumption of sweet snacks and other so-called junk food.The new face of those with particular chronic diseases is changing, and this reality is therefore a 240
  • 258. cause for public health concern. This means that policy makers, health care practitioners,educators and the wider community need to recognize that chronic conditions such as diabetes,hypertension and arthritis have begun manifesting in young people as well as children. There isan urgent rationale for an intervention campaign that will sensitize educators, medicalpractitioners, parents, and children about the current reality of children and young adults beingdiagnosed with particular chronic illnesses. The intervention programme that should beformulated must include signs of ailments, place of reference, chronic disease management,nutrition, and medical practitioners understanding that testing for diabetes, hypertension andarthritis must be a rudimentary part of medical examinations, even of children, and further, evenif their parents are not experiencing those conditions. The emerging young face of diabetics, and hypertensive and arthritis patients requires anew thrust in the study of mortality and morbidity data for health planning. Although diabetes,hypertension and arthritis may not be among the 10 leading causes of mortality in Jamaica [36]or the developing society, the emergence of those conditions requires researchers, demographers,epidemiologists and policy makers to embark on the inclusion of data on those conditions inpublications in order that they can be examined. In a recently conducted study by Wilks et al.[37], they used teens of 15+ years to present information on those with particular diseases, butneglected to mention the new reality of children of younger ages with particular chronicillnesses. The new reality means that researchers, policy makers and the general society need tobe cognizant of these facts. This will be accommodated by researchers, and in particular thestatistical agency, publishing findings on the new reality in order to commence the discourse andintervention campaign. With the absence of information on the matter, this can be construed as aminiscule problem. However, the new findings are reflecting the early onset of diabetes (< 15 241
  • 259. years) and the provision of data beginning at 15 years omits 0.8% of infected children or 2.4% ofdiabetics. The present paper unearths more information on the new faces of those with particularchronic conditions at younger ages. Fifty-four out of every 100 persons with particular chronicdiseases (i.e. diabetes, hypertension and arthritis) had hypertension, 32 out of every 100 haddiabetes and 15 out of every 100 had arthritis. Despite the majority of those with particularchronic illnesses having hypertension, the prevalence rate for those with diabetes increasedexponentially more than the other conditions. Many studies have established a relationshipbetween poverty and illness [1, 2, 16 and 22], and particularly poverty and chronic illness [15].Van et al.‘s work [15] revealed that chronic diseases were greater among those in the lowersocioeconomic strata than the other social classes, but this paper found that more people in thewealthy class had diabetes, while more hypertensive and arthritic respondents were in the lowersocioeconomic group. The current findings are providing some clarification for Van et al.‘sresearch. Although the prevalence rate of particular chronic illnesses was greater among thewealthy strata for 2002 and 2007, those in the lower socioeconomic group recorded the greatestaverage annual percentage change. On disaggregating the particular chronic diseases, the presentpaper showed that the prevalence of diabetes was greater among the upper than the lower class,and the opposite was noted for hypertension and arthritis. This finding does not only clarify Vanet al.‘s research, but provides pertinent information on the unhealthy lifestyle practices amongthe wealthy, and reinforces the role of material deprivation on health, health conditions andmortality. 242
  • 260. Two scholars opined that money can buy health [38], implying that health is atransferable commodity, and that unhealthy lifestyle practices by the wealthy can be reversedwith money. Clearly Smith and Kington‘s claim [38] can be refuted as 42 out of every 100chronically ill respondents were in the upper class, and more than half of those with diabeteswere part of the wealthy income group. For any postulation to hold true about money purchasinghealth, one of the key axioms that needs to be looked at is the health conditions being loweramong the wealthy than those in the lower class. The wealthy will continue to live by theirdesires, and at the onset of chronic ailments, may be able to reverse this by medical expenditure.It is well established that income is positively correlated with health, as money affords aparticular diet, nutrition, medical facilities, safe drinking water, proper sanitation, leisure andgood physical milieu, but the reality is that whenever unhealthy lifestyle practices become thechoice of an individual, his/her money will not be able to eradicate the onset of diabetes,hypertension, heart disease, or other chronic diseases. Therefore, money enhances the scope ofbetter health, but it cannot buy good health as this is not transferable from one person to the next. The very reason that health is non-transferable is the rationale behind the mortality of thewealthy elderly, and morbidity among the upper class. Socioeconomic status was found to bethe strongest determinant of variations in health [39, 40], as wealth allows for particular choices,opportunities, access, resources and privileges that are not available to the poor. While thosematters provide a virtual door leading to better health, money or wealth does not reduce the riskof ill-health arising from poor choices. A study by Wilks et al. [37] found that most (71%) ofthose in the upper socioeconomic strata currently use alcohol which is more than those in thelower class (59%) and the middle class (64%). Twice as many people in the upper class (14%)had heart attacks compared to those in the middle class (7%) and 6% in the lower class [37]. The