Human ageing in jamaica

Human Ageing, Health, Health Utilization and Policy Implications: An introduction to Behaviour and Practices Paul Andrew Bourne

Human Ageing, Health, Health Utilization and Policy Implications: An introduction to Behaviour and Practices i

Human Ageing, Health, Health Utilization and Policy Implications: An introduction to Behaviour and Practices Paul Andrew Bourne Director Socio-Medical Research Institute ii

©Paul A. Bourne, 2011First Published in Jamaica, 2011 byPaul Andrew Bourne66 Long Wall DriveStony Hill,Kingston 9,St. AndrewNational Library of Jamaica Cataloguing DataHuman Ageing, Health, Health Utilization and Policy Implications: Anintroduction to Behaviour and PracticesIncludes indexISBNBourne, Paul AndrewAll rights reserved. Published , 2011Cover designed by Paul Andrew Bourne iii

List of Acronyms and InitialsAARP American Association of Retired PersonsAIDS Acquired immunodeficiency syndromeBMI Body Mass IndexCI Confidence IntervalDALE Disability Adjusted Life ExpectancyDHEA DehydroepiandrosteroneDNA Deoxyribonucleic acidED Enumeration Districtet al OthersGDP Gross Domestic ProductHSB Health Seeking BehaviourJADEP Jamaica Drug for the Elderly ProgrammeJSLC Jamaica Survey of Living Conditionskg KilogramLFS Labour Force SurveyLFS Labour Force SurveyLSMS World Bank’s Living Standards Measurement Studym meterMOH Ministry of HealthNHF National Health FundOR Odds Ratio iv

P ProbabilityPAHO Pan American Health OrganizationPIOJ Planning Institute of Jamaica ()PSU Primary Sampling UnitQoL Quality of LifeQoL Quality of LifeRGD Registrar General DepartmentSD Standard deviationSES Socioeconomic statusSPSS Statistical Packages for the Social SciencesSTATIN Statistical Institute of JamaicaUS United StatesUN United NationsUNDP United Nations Development ProgrammeUWI The University of the West IndiesWHO World Health Organization v

Table of Contents pageList of Acronyms and Initials ivList of Figures ixList of Tables xiiPreface xxAcknowledgement xxvDedication xxviPart I: Human Ageing 1 Introduction1 Historical Overview On Human Ageing2 Population Ageing and the State of the Elderly in JamaicaPart II: Health: An introduction 47 Introduction3 Health measurement4 A conceptual framework of wellbeing in some Western nationsPart III: Health status: Using health data 975 Paradoxities in self-evaluated health data in a developing country6 Variations in health, illness and health care-seeking behaviour of those in the upper social hierarchies in a Caribbean society7 Self-reported health and medical care-seeking behaviour of uninsured Jamaicans vi

8 Social determinants of self-reported health across the Life Course9 Social Determinants of Health in a developing Caribbean nation: Are there differences based on municipalities and other demographic characteristics?10 Health Inequality in Jamaica, 1988-200711 Hospital Healthcare Utilisation in middle-income developing country12 Inflation, Public Health Care and Utilization in Jamaica13 Self-evaluated health and health conditions of rural residents in a developing country14 Self-reported health and health care utilization of older people15 An Epidemiological Transition of Health Conditions, and Health Status of the Old-Old-To-Oldest-Old in Jamaica: A comparative analysis16 Happiness, life satisfaction and health status in Jamaica17 Dichotomising poor self-reported health status: Using secondary cross- sectional survey data for Jamaica18 Retesting and refining theories on the association between illness, chronic illness and poverty: Are there other disparities?19 Modeling social determinants of self-rated health status of Hypertensive in a middle-income developing nation20 Comparative Analysis of Health Status of men 60+ years and men 73+ years in Jamaica: Are there differences across municipalities?21 Medical Sociology: Modelling Wellbeing for Elderly People in Jamaica22 Health Determinants: Using Secondary Data to Model Predictors of Wellbeing of Jamaicans23 The changing faces of diabetes, hypertension and arthritis in a Caribbean population vii

24 Health status of patients with self-reported chronic diseases in JamaicaPart IV: Psychology of Ageing 65825 Ageing and the MindPart V: Mortality 68226 Impact of poverty, not seeking medical care, unemployment, inflation, self- reported illness, and health insurance on mortality in Jamaica27 Decomposing Mortality Rates and Examining Health Status of the Elderly in JamaicaPart VI: Policy Framework 75528 Agenda setting, Development of legislation, Implementation and Policy Modification29 Major Health Determinants: Are they ignored in the way in which Caribbean Health Services are organized?Part V: Health Insurance Coverage 780 30 Determinants of self-rated private health insurance coverage in JamaicaPart VI: Poverty, Wealthy and Health 80531 Health Disparities and the Social Context of Health Disparity between the Poorest and Wealthiest quintiles in a Developing CountryPart VII: Old-to-Oldest Elderly 83732 Good Health Status of Old-to-Oldest elderly People in Jamaica: Are there difference in rural-urban area?Glossary 866 viii

List of Figures pageFigure 1.1: Selected regions and their percent of pop. 65+ years 13Figure 2.1: Ranked Order of the five leading causes of mortality in the population 65 yrs and older, 1990 33Figure 2.2: Leading causes of self-reported morbidity in the population of seniors, by gender in Barbados and Jamaica. 34Figure 2.3.: Percentage distribution of 5 main causes of deaths by age: 2002-2004 36Figure 3.1: The relation between health policy and health, and the roles of health determinants 55Figure 10.1: Percentage of Men Seeking Medical Care by Percentage of Menreporting Illness 254Figure 10.2: Percentage of People Seeking Medical Care by Prevalence of Poverty 255Figure 10.3: Percentage of Men Seeking Medical Care by Percentage of Menreporting Illness 256Figure 10.4: Percentage of Women Seeking Medical Care by Percentage of Womenreporting Illness 257Figure 10.5: Percentage of people Seeking Medical Care by Percentage withHealth Insurance 258Figure 10.6: Ownership of Health Insurance and Prevalence of Poverty 259Figure 11.1: Public-Private Health Care Utilisation in Jamaica (in %), 1996-2002,2004-2007 Source: Taken from Jamaica Survey of Living Conditions, various issues 283Figure 11.2: Remittances By Income Quintiles and Jamaica (in Percent): 2001-2007Source: Extracted from the Jamaica Survey of Living Conditions, 2007 284Figure 12.1: Inflation By Public Health Care Utilization 299Figure 12.2: Inflation by Private Utilization Care 300Figure 12.3: Cost of Medical care for Public and private health Care 301Figure 12.4: Public and private health Care Utilization 302Figure 12.5: Visits to Public Health Care Facilities and the Number of ReportedIllness/Injury 303Figure 12.6: Health Insurance Coverage and Inflation 304Figure 12.7: Incidence of Poverty and Inflation, 1988-2007 305 ix

Figure 12.8: Public Health Care Utilization and Incidence of Poverty 306Figure 12.9: Private Health Care Utilization and Incidence of poverty 307Figure 12.10: Illness/Injury and Inflation 308Figure 12.11: Cost of Public and private health Care Cost and Inflation 309Figure 12.12: Seeking Medical Care By Inflation 310Figure 12.13: Seeking Medical Care and Incidence of Poverty 311Figure 12.14: Seeking Medical Care and Health Insurance 312Figure 14.1. Caribbean Elderly population as a percentage of total population 367Figure 14.2. Jamaica Elderly population as a percentage of total population 367Figure 14.3. Percentage of population 80+ years with health insurance coverage,2002 and 2007 375Figure 15.1. Diagnosed health conditions, 2002 and 2007 429Figure 15.2. Self-reported illness (in %) by Income Quintile, 2002 and 2007 430Figure 16.1: Percentage change in elderly population by five year age groups, 1991-2001 432Figure 19.1. Health seeking behaviour (in %) by marital status and sex 533Figure 26.1. Not seeking medical care (in %) by Year 714Figure 26.2. Annual Mortality (No. of people) in Years 715Figure 26.3. Not Seeking Medical Care (in %) by Prevalence of poverty rate (in %) 716Figure 26.4. Not Seeking Medical Care (in %) by Unemployment rate (in %) 717Figure 26.5. Not Seeking Medical Care (in %) by Illness/Injury (in %) 718Figure 26.6. Mortality (No of people) by Not Seeking Medical Care (in %) 719Figure 26.7 Prevalence of poverty rate (in %) and Unemployment rate (in %) 720Figure 26.8. Not Seeking Medical Care (in %) by Health Insurance Coverage (in %) 721Figure 26.9. Mortality (No. of people) by Prevalence of Poverty (in %) 722Figure 26.10. Mortality (No. of people) by Unemployment rate (in %) 723 x

Figure 26.11. Prevalence of poverty rate (in %) by Inflation rate (in %) 724Figure 26.12. Not Seeking Medical care (in %) by Inflation rate (in %) 725 xi

List of TablesTable 2.1: Observed & Forecasted Percentage of Elderly 65 years or over in Selected Regions, and the World Countries: 1950, 1975, 2025 and 2050. 14Table 2.2: Observed & Forecasted Percentage of Elderly 60 years or over in Selected Regions, and the World Countries: 1950, 1975, 2025 and 2050. 15Table 2.3: Characteristics of the Three Categories of Elderly, and Ageing transition 18Table 2.4: Percentage of Estimated or Projected Populations of Selected Caribbean Nations, 1980, 2000, 2005 and 2020 24Table 2.5: Total Fertility Rate for Selected Caribbean Nations, Caribbean, and Latin American: 1950-1955 to 2045-2050 26Table 2.6: Life Expectancy at Birth of both Sexes for Selected Caribbean Nations, the Caribbean, and Latin American 27Table 2.7: Life Expectancy at Birth of Jamaicans by Sex, 1880-2004 28Table 2.8: Jamaica: Selected demographic variables, Labour Force Participation (in %). 30Table 5.1 Socio-demographic characteristic of sample by sex of respondents 118Table 5.2 Socio-demographic characteristic of sample by educational level 119Table 5.3 Socio-demographic characteristic of sample by self-reported illness 120Table 5.4 Stepwise Logistic Regression: Good self-rated health status by sociodemographic, economic and biological variables 121Table 5.5 Table 5.5. Stepwise Logistic Regression: Self-reported illnessby sociodemographic and biological variables 122Table 6.1. Demographic characteristics of sample 143Table 6.2. Particular variables by social hierarchy 144Table 6.3. Logistic regression: Moderate-to-very good health status by particular variables 145Table 6.4. Logistic regression: Self-reported illness by particular variables 146Table 6.5. Logistic regression: Self-reported health seeking behaviour by particular variable 147 xii

Table 7.1: Socio-demographic characteristics of sample 167Table 7.2: Sociodemographic characteristic by Sex 168Table 7.3. Health status by Self-reported dysfunction 169Table 7.4. Ordinary Logistic Regression: Correlates of Good Health Statusof Uninsured Jamaicans 170Table 7.5. Ordinary Logistic Regression: Correlates of Medical Care-Seeking Behaviour of Uninsured Jamaicans 171Table 8.1: Good Health Status of Jamaicans by Some Explanatory Variables 189Table 8.2: Good Health Status of Elderly Jamaicans by Some Explanatory Variables 190Table 8.3: Good Health Status of Middle Age Jamaicans by Some Explanatory Variables 191Table 8.4: Good Health Status of Young Adults Jamaicans by Some Explanatory Variables 192Table 9.1: Demographic characteristic of sample 216Table 9.2: Self-rated health status By Sex 217Table 9.3: Diagnosed Self-reported illness By Sex 218Table 9.4: Typology of Self-reported Diagnosed Illness By Sex 219Table 9.5: Diagnosed Self-reported illness By Age group 220Table 9.6: Self-rated Health Status by Age group 221Table 9.7: Predictors of Self-rated Health Status of Jamaicans 222Table 9.8: Predictors of Self-rated Health status of men in Jamaica 223Table 9.9: Predictors of Self-rated Health status of women in Jamaica 224Table 9.10: Predictors of Self-rated Health Status of Jamaicans in Urban Areas 225Table 9.11: Predictors of Self-rated Health Status of Jamaicans in Other towns 226Table 9.12: Predictors of Self-rated Health Status of Jamaicans in Rural Areas 227Table 10.1: Life Expectancy at Birth of Jamaicans by Sex: 1880-2004 249Table 10.2: Inflation, Public-Private Health Care Service Utilization, Incidence ofPoverty, Illness and Prevalence of Population with Health Insurance(in per cent), 1988-2007 250 xiii

Table 10.3: Seeking Medical Care, Self-reported illness, and Gender composition of thosewho report illness and Seek Medical Care in Jamaica (in percentage), 1988-2007 251Table 10.4: Public Health Care Visits (using the JSLC, data) and Actual Health Care Visits(using Ministry of Health Jamaica, data), 1997 and 2004 252Table 10.5: Self-reported Health Status per 1,000 by Population, Men and Women;Sex-Ratio of Self-reported Health Status, and Female to Male Ratio of Self-reportedHealth Status, 1989-2006 253Table 11.1 Discharge, Average Length of Stay, Bed Occupancy and Visits toPublic Hospital Health Care Facilities, 1996-2004 285Table 11.2 Inflation, Public-Private Health Care Service Utilisation, Incidence of Poverty,Illness and Prevalence of Population with Health Insurance (in per cent), 1988-2007 286Table 11.3 Hospital Health Care Utilisation (Using Jamaica Survey of LivingConditions Data) By Income Quintile (%): 1991-2007 287Table 11.4 Demographic Characteristic of Sampled Population, n=1,936 288Table 11.5 Public Hospital Health Care Facility Utilisation by Area of Residence(in percentage), n =1,936 289Table 11.6 Public Hospital Health Care Facility Utilisation By Per Capita PopulationIncome Quintile (in per cent), N=1,936 290Table 11.7.1 Descriptive Statistics of Negative Affective Psychological Conditionsand Per capita Income Quintile 291Table 11.7.2 Multiple Comparison of Negative Affective Psychological Condition byPer Capita Income Quintile 291Table 11.8.1 Descriptive Statistics of Total Positive Affective Psychological Conditionsand Per Capita Income Quintile 292Table 11.8.2 Multiple Comparisons of Positive Affective Conditions by Per Capita IncomeQuintile 292Table 11.10 Logistic Regression: Predictors of Public Hospital Health Care facility utilisationin Jamaica 293 xiv

Table 11.11 Public Hospital Facility Visits (using the JSLC and Ministry of Health Jamaica)By 1997 and 2004 294Table 12.1: Inflation, Public and private health Care Service Utilization, Incidence ofPoverty, Illness and Prevalence of Population with Health Insurance(in per cent), 1988-2007 328Table 12.2:Annual Inflation in Food and Non-Alcoholic beverages and Health Care Cost,2003-2007 329Table 12.3: Percentage of Households Receiving Remittances By Region, 2001-2005 330Table 12.4: Percentage of Households Receiving Remittances By Quintile, 2001-2005 331Table 12.5: Mean Patient Expenditure ($) on Health Care in Public and Private Facilitiesin the Four-Week Reference Period, JSLC 1993-2004, 2006 332Table 12.6: Purchased medication and Seeking Medical Care (Per Cent), 19-2006 333Table 12.7: Distribution of Poverty By Region (Per cent), 1997-2007 333Table 12.8: Distribution of Elderly Population (ages 60 years and older) ByRegion (Per Cent), 1997-2007 334Table 13.1. Demographic characteristics, 2002 and 2007 345Table 13.2: Self-reported health conditions by particular social variables 347Table 13.3. Health care-seeking behaviour by sex, self-reported illness, health coverage,social hierarchy, education, age and length of illness, 2002 and 2007 349Table 13.4. Stepwise Logistic regression: Social and psychological determinantsof self-evaluated health, 2002 and 2007 351Table 13.5. Stepwise Logistic regression: R-squared for social and psychologicaldeterminants of self-evaluated health, 2002 and 2007 352Table 14.1. Sociodemographic characteristic of sample 389Table 14.2. Diagnosed health conditions by area of residence 390Table 14.3. Health status by area of residence 391Table 14.4. Health status by self-reported illness, 2007 392 xv

Table 14.5. Health status by gender 393Table 14.6. Health status by gender 394Table 14.7. Health status by health care-seeking behaviour 395Table 14.8. Health status by health insurance coverage 396Table 14.9. Diagnosed health conditions by health care seeking behaviour 397Table 14.10. Health status by Annual total expenditure, 2007 398Table 14.11. Self-reported health conditions by total expenditure, 2002 and 2007 399Table 14.12. Self-reported health conditions by medical care expenditure(public and private health care expenditure), 2002 400Table 15.1. Socio-demographic characteristics of sample 418Table 15.2. Self-reported illness by sex of respondents, 2002 and 2007 419Table 15.3. Self-reported illness by marital status, 2002 420Table 15.4. Self-reported illness by marital status, 2007 421Table 15.5. Self-reported illness by Age cohort, 2002 and 2007 422Table 15.6. Mean age of oldest-old with particular health conditions 423Table 15.7. Diagnosed Health Conditions by Aged cohort 424Table 15.8. Self-reported illness (in %) by health status 425Table 15.9. Health care-seeking behaviour and health status, 2007 426Table 15.10. Health care-seeking behaviour by health status controlled for aged cohort 427Table 15.11. Logistic regression on Good Health status by variables 428Table 17.1. Socio-demographic characteristic of sample, n = 6,783 486 xvi

Table 17.2. Very poor or poor and moderated-to-very poor self-reported health statusof sexes (in %) 487Table 17.3. Odds ratios for very poor or poor and moderate-to-very poor self-reported healthof sexes by particular variables 488Table 17.4. Odds ratios of poor health status by age cohorts 489Table 18.1: Demographic characteristic of sample, 2002 510Table 18.2. Particular variable by social hierarchy, 2002 511Table 18.3. Self-reported injury, normally go if ill/injured, why didn’t seek care for currentillness, length of illness and number of visits to health practitioner by social hierarchy, 2002 512Table 18.4. Logistic regression: Self-reported illness by particular variables 513Table 18.5. Logistic regression: Self-reported chronic illness by some variable 514Table 19.1. Sociodemographic characteristics of study population, n = 206 534Table 19.2. Sociodemographic characteristics and health care utilization byself-rated health status 535Table 19.3. Sociodemographic characteristics and health care utilization byPopulation Income Quintile 536Table 19.4. Logistic regression: Variables of self-rated health status 537 xvii

Table 20.1: Life Expectancy at Birth of Jamaicans by Sex: 1880-2004 560Table 20.2: Seeking Medical Care, Self-reported illness, and Gender compositionof those who report illness and Seek Medical Care in Jamaica (in %age), 1988-2007 561Table 20.3 Number of older men (60+ years) and difference over each year inJamaica: 1990-2007 562Table 20.4 Sociodemographic characteristics of sample (n =1,432): Men 60+ years 563Table 20.5 Logistic regression: Variables predicting good health status of men 60+ yearsAnd 73+ years in Jamaica 564Table 21.4.: Profile of the surveyed respondents: Variables used in Wellbeing Model 575Table 21.1: Life Expectancy at Birth of Jamaicans by Sex: 1880-2004 587Table 21.2: Jamaica: Selected demographic variables, Labour Force Participation (in %) 588Table 21.3: Growth Rate of Selected Age Group and for Total Population of Jamaica, usingCensus data: 1844-2050 589Table 21.5: Wellbeing Equation of the Jamaican Elderly 590Table 22.1: Percentage and (count) of Marital Status by Gender of respondents 604Table 22.2: A Multivariate Model of Wellbeing of Jamaicans 605Table 22.3: Decomposing the 39.3% of the variance in Wellbeing of Jamaicans,using the squared partial correlation coefficient 606Table 23.1: Operational definitions of particular variables 627Table 23.2. Demographic characteristic of sample, 2002 and 2007 628Table 23.3. Self-reported diagnosed chronic illness by sex of respondents, 2002 and 2007 629Table 23.4: Particular demographic and health variable by diagnosed chronic illness,2002 and 2007 630Table 23.5. Age of respondent by particular chronic illness, 2002 and 2007 631Table 24.1: Socio-demographic characteristics of sample 653Table 24.2: Diagnosed chronic recurring illness by age group 654 xviii

Table 24.3: Diagnosed chronic illness by social class 655Table 24.4: Crowding, income and annual consumption expenditure bydiagnosed chronic disease 656Table 24.5: Logistic regression: Predictor of poor health status of patients who reportedchronic disease 657Table 26.1. Annual Inflation in Food and Non-Alcoholic beverages and Health Care Cost,2003-2007 711Table 26.2. Inflation, Public-Private Health Care Service Utilization,Incidence of Poverty, Illness and Prevalence of Population with Health Insurance (in per cent), 1988-2007 712Table 26.3. Seeking Medical Care, Self-reported illness, and Gender composition of thosewho report illness and Seek Medical Care in Jamaica (in percentage), 1988-2007 713Table 27.1: Socio-demographic characteristic of the respondents 748Table 27.2: Age-specific death rates by older ages and crude death rate, 1998-2007 749Table 27.3: Life expectancy at birth of Jamaicans by sex: 1880-2004 750Table 27.4: Mortality sex ratio by older ages and population, 1998-2006 751Table 27.5: Health status by Age group 752Table 27.6: Diagnosed (chronic) illness by age cohort 753Table 27.7. Poor health status of elderly Jamaicans by some explanatory variables 754Table 30.1: Demographic characteristic of sample by area of residence 801Table 30.2: Good health status by social standing (Per capita population quintile) 802Table 30.3: Good health status by age group 803Table 30.4: Logistic regression: Private health insurance coverage by some variables 804 xix

PrefaceAgeing is not a recent issue in the world as it goes back centuries, to the beginning of humanexistence. The ageing reality was first studied by Denise Eldemire-Shearer (formerly, DeniseEldemire) in Jamaica in the early 1990s. While Denise Eldemire-Shearer’s pioneering work(PhD thesis in 1993) evaluated the epidemiology of ageing in Jamaica, it failed to explore theassociation between ageing and self-rated health status, social determinants of health among theaged population, the relationship between self-reported illness and self-rated health, and many ofthe subsequent works (quantitative and qualitative inquiries) equally did not research thosecritical issues in the discourse of ageing studies. Despite the works having left a gap in theliterature, they provided a comprehensive understanding of ageing, meaning of ageing from anon-medical perspective and an understanding of aged Jamaicans which have aided in theformulation of countless Ageing Policies. The pursuit of truth which is critical to science, albeit social or pure, means thatacademics CANNOT behave as though the gap is filled and nothing is left to research in thediscipline of Ageing Studies as this is not the case. By failing to evaluate self-rated health statusamong the aged as well as social determinants of health of this cohort, the pursuit of truthdictates that scientific inquiry is needed in those areas. An established gap in the literature onAgeing Studies symbolizes the importance of further research as these can provide germanerationale for future policy formulation and intervention programmes. In 2003 a workshop proceedings on ‘Ageing well: A life course perspective’ addressedplethora of germane issues (such as Active ageing: WHO perspectives; Caribbean Ageing andPolicy Implications; Psychological Dimensions of Ageing; Age-friendly primary Health Care: xxi

Ministry of Health’s Perspective; Surgery in the Elderly: A prospective Study in a DevelopingCountry; Surgery in the Elderly: What, Where and How: Reducing Clinical Complications forDiabetes and Hypertension in the Older Population; Diagnostic and Management Approaches toDementia) but none of the articles pursuit the truth of Self-rated Health, Health Care Utilization,social determinants, particularly among the aged – people 60+ years old). In the entirepublication (Ageing Well…) there was an absence of critical empirical studies on the agedpopulation that could aid policy makers with crucial information for effective policy planningand intervention programmes. Although those topic pursued by the various scholars were vital tothe general health of the elderly, more research on different tenets of the aged are unavoidableand cannot continue unresearched when data are able that could aid policy formulation andunderstanding of this aged cohort. In 2005 an entire text on ‘Health Issues in the Caribbean’ edited by Owen Morgan twoarticles and/or studies appeared on ageing, one by Denise Eldemire-Shearer and Yvonne Stewart.Again like early publication in 2003 none of the articles inquired the self-rated health and ageingas well as health care utilization among the elderly. If science is about the pursuit of truths,principles of verifications, logic, precision, then the absence of systematic inquiry on ageing andhealth, ageing and health care utilization, will not advance the understanding of the aged inJamaica, for policy planning and evaluations. Although science continues unabated in our world,we are failing to provide truths in health literature, particularly on the aged. The elderly is agrowing group that ignorant of information will not help understanding the population. Indevelopment planning, ageing and population ageing cannot be excluded for other matters (suchas growth and development, inflation, unemployment, chronic illness and standard of living). xxii

The current text fills the gap in the literature by systematically exploring healthmeasurement, health and ageing, ageing and health care utilization, particularly among agedJamaicans. Knowledge cannot be expounded upon by unresearched phenomena, supporting thepurpose of this book to enhance the revolutionary nature of science in explaining what is, ageingand self reported health. The structure of this book, therefore, substantially reflects an expansionof Denise Eldemire-Shearer’s pioneering work, current works by Janet LaGrande, Chloe Morrisand Eldemire-Shearer. The difference of this work is a gradual progression of a usefulframework for understanding ageing, health and ageing, health care utilization and ageing inJamaica. The book commences with an overview of ageing, definitions of health, determinants ofhealth, health care utilization and disparity in health of the aged males and females in Jamaica. This book is written for audiences of health care practitioners, academics, health andapplied demographers, gerontologists, social workers, sociologists, students of sociology anddemography, policy formulators, health care administrators, psychologists (applied and clinical),elderly, and general readers who wish to understanding the phenomena expounded upon in thisvolume. Econometric tools are used throughout this text that may challenging for some readers,but the author tried to thoroughly explain these issues in a matter than can be grasped by allreaders, with or without statistical skills. In producing this work, it makes use of data from secondary cross-sectional surveys,previously published works in the age of health, health care utilization, ageing, and health andageing to illustrate and demonstrate the practices and behavior of the aged in Jamaica. Like KarlPearson, the author somewhat subscribe to the proposition that good health is inherited ratherthan nurtured by a particular socio-physical milieu, but also thinks that this may not necessarilybe the care among the aged. These thinking led to the examination of plethora of matters on xxiii

health and health care utilization, with particular emphasis on the aged, in order to provide acomprehensive understanding of the phenomena instead of merely hold unsubstantiatedpositions. As a scientist the author cannot claim truths with verifications, that is the basis uponwhich many of the inquiries emerge and new positions are formed. Ageing is a reality that is highly dreaded in many societies, because people believe it isthe slowing and closing of life’s gift. Ageing is a part of the life’s trajectory, which means thatthere is nothing to fear or be apprehensive about as it is certain at the beginning of life that thereis a high probability ageing will occur. Ageing is sometimes refers as ageism (ie. a negativereality) primarily because of the observation of many who are elderly. Ageing does notcommence at 60+ years, it begin at birth and continues throughout life. Some seek a panacea forageing; they desire its disappearance because of its perceived negatives, mythologies andmisnomers. Ageing gracefully is rarely forwarded by many people in societies, even though thisis aired by agencies, people fear death which account for the negative psychological dislike forageing beyond 60 years. Empirical evidence showed that some health conditions are more likely to emerge beyonda particularly chronological age, which increases the psychological negative of ageing at 60+years. It is not the mere onset of health conditions that pose the fear for many, but it is theincreasing likeliness of morality on the introduction of those conditions. With this realty, ageingbeyond a certain chronological value is not a welcoming thing for some people. The seniorsyears merely reflects the commulative status of earlier years coupled with the socio-physicalenvironment, indicating that the objective is not to fear ageing but it is to mindful of thosesituations and how we can make amendments in order to discount poor health in the later years. xxiv

No discourse on ageing and/or health can be completed without an examination of thehealth status of the fasting growing aged cohort in Jamaica, the old-to-oldest elderly. With ruralpoverty being twice that of urban poverty, more elderly residing in rural geopolitical zones, old-to-oldest elderly are mostly unemployable or unemployed, comorbidity increases with advancedage, we need knowledge on the health status of this people and factors that account for good self-rated health status. Chapter 32 provides a comprehensive examination of the aforementionedissues, illness affecting the old elderly versus the oldest-elderly, and the statistical associationbetween illness, poverty and old-age. Now we have a better understanding of those factors that account for old-to-oldest elderlygood health. While the data were goodly fitted for the model, the explanatory power was low ofthose identified predictive factors. This means that good health of this age cohort is notinfluenced by income or social standing, and that there is a need to examine lifestyle risk factors;disease indicators and psychological conditions as this may provide more answers to good healthof Jamaicans 75 years and older. A quantitative assessment has provided use with answers; it isclear from the findings that more information is needed on this age cohort. The researcherrecommends the use of qualitative methodologies to provide in-depth understanding of thosefactors that determine good health of this age cohort. All the chapters were carefully and deliberately chosen in keeping with the focus ofhuman ageing, health, health utilisation and policy formulation. The majority of the chaptershave some advanced statistical techniques, but the author tried to ensure that information providewill give a thorough understanding without any knowledge of advanced statistics. The authorhopes that the information can commence the discourse on human ageing, policy changes, policyimplementations and the rebranding of human ageing in Jamaica. xxv

AcknowledgementsJamaica continues to log behind in the study of self-rated (or reported) health among the aged.Because science cannot be advanced without pursuing truths, it follows that the gaps in theliterature must be met with immediacy in order to provide meanings and guidelines for policymakers and other scientists, and science. This book emerged out of a stay with my aged mother(Ms. Janet “Medda” Green), brother (Mr. Kervin Roger Smith), niece (Janet Smith), nephew(Kevin Smith) and hearing about the comorbidities experienced by the ageing uncle (Mr. GeraldGreen). During the holidaying with ageing mother and being cognizant of the realities of ageing,I was awoken to the realization that ageing is process as I saw the ease with which my motherslept and work with small intervals between. Like her older brother (Mr. Gerald Green), mymother experienced comorbidities such as hypertension, heart conditions, circulatory problemsand respiratory conditions, yet works assiduously in the days and awake in the nights as hungryas an unfed tiger. Ageing became a reality that I began interfacing with, but realize that it wasnot to be dread as both my mother and her brother were lovers of the age, say it as a time aoffering some ‘good’ to the younger generation and challenging many of the stereotypes andfears of ageing, ageism was social construct that they fail to accept and one that bars the psychefor exploring further unchartered areas. This book is, therefore, a verification of the pursuit of truths on health and ageing inJamaica, and is the inspiration of my holiday experience, family, relatives including Uncle Mr.Gerald Green. The creation of this volume is to examine many issues unresearched in the pastand is totally due to the aforementioned individuals and science, the pursuit of truths. xxvi

Dedication This volume is dedicated to Janet Green, Gerald Green, Kervin Smith, Evadney BourneAged people, Jamaicans, Young people xxvii

Human Ageing, Health, Health Utilization and Policy Implications: An introduction to Behaviour and Practices xxviii

Part I: Human Ageing 1

IntroductionFor millennia, the pursuit of truths on longevity (human ageing) were primarily centered around1) lifespan, 2) biology (including genetic and embryology), 3) morbidity and comorbidity 4)functionality (physical and cognitive), 5) mortality, and 6) changes in population structure andcomposition. The majority of those issues were embedded in the biomedical model. The theoriesthat emerged during the earlier years substantially addressed cause of biological ageing(including functional ageing). Because it was long established that ageing was associated withincreased health conditions and mortality, many studies were geared toward pathogens andfinding the curse for morbidities. Those gave rise to plethora of demographic andepidemiological studies on life expectancy, which was in keeping with a logical assessment ofhuman ageing, using empiricism. For centuries, there have been a gradual development of empirical works outside of thehistorical undercurrents of human ageing (lifespan, life expectancy, longevity, genetics,embryology, mortality, and morbidities), these have given currency to inquiries on social ageing(as such as happiness, lifestyle, perceptions, quality of life, health status, ageism). Theperspectives of aged people extend beyond the live years to experiences (including sexuality),social programmes, and taxation. A pioneer in Jamaica who has been investigating humanageing is Denise Eldemire-Shearer (formerly Denise Eldemire). She has dedicated the majorityof academic studies to the examination of human ageing issues, outside of the traditionalbiomedical model. Professor Eldemire-Shearer has expanded the non-biomedical studies onhuman ageing by including areas like health status, challenges of ageing, ageing realities, stressand employment status (as well as productivity). 2

Although Eldemire-Shearer layed the foundations for the revoluation and development inthe literature on human ageing in the Caribbean, particularly Jamaica, her works were notdirected towards modeling the health status, self-health conditions, and chronic disease, usingeconometric analyses. The use of economietric techniques, Ian Hambleton and colleaguesintroduced this to the study of self-rated health status of aged Barbadians. Outside of IanHambleton and colleagues’ study, Paul Bourne has conducted plethora of research on health ofthe aged. The gradual development of scientific studies on health and human ageing in Jamaica,outside of the biomedical model, has provided a more comprehensive understanding andknowledge of the elderly. This volume has not explored the cultural biases and negatives onageing, ageism, but sought to evaluate health and ageing mainly using secondary cross-sectionalsurvey data. The negative perspectives of ageing include 1) worthless burden, 2) can beabandoned for young people, 3) tax burden or liability including economic cost, 4) diseaseinfected, 5) low productivity, 6) humoured and ridiculed by others, and 7) discriminated againstby the society. The negative perceptions of the ageing influence the treatment of the aged. TheJamaican society is one of culture that has many things negative to ascribe about the elder. LikeJamaica, Turish men fear the onset of ageing, as they believe that during this period theeconomic challenge will be intensified because of the turmoil in the nation (McConatha, et al.,2004). This is not the case in societies like Japan, China, and/or Mexican Americans, AsianAmericans, Kung of Botswana, Housa of Nigera as ageing carries with it a high degree ofpresitige and great respect (AARP, 1995; Holmes and Holmes, 1995; Kalavar, 2001; Foos andClark, 2010; Sokolovsky, 1999). A study conducted by Wilks and Colleagues (2008), using data on Jamaicans aged 15-74 3

years old, found that 53% of men aged 65-74 years had sexual relations at least once per monthcompared to 4.2% of females of the same age; 18.5% of elderly males (aged 65-74 years old)reported having diabetes compared with 29.6% of elderly females of the same age; 60.5% elderlymales reported hypertension and 66.1% of females. The elder is an individual who is normal,with more experiences, sexually and physically active like the young, but who have a higherprobability of being influenced with health conditions than their younger aged people. Clearly peoples’ perception on ageing is culturally based and varies across society and/orcultures. Negative views on older people affect the negative attitude toward ageing and thetreatment of them, but these are not of what this volume seeks to address. The text is in responseto the gap in the literature on health and ageing, with the primary purpose of providing empiricalstudies on the phenomena in order to guide principles, theories and develop issues on adultageing in Jamaica. Human ageing is a reality that commenes the day one is born, continues over the lifespanand end at death. Regardless of peoples’ perception of ageing, their attitude toward ageing,human ageing must be understood as the population ages. Knowledge on ageing is critical todevelopment as are inflation, monetary policy, national debt and unemployment. Ageing,therefore, is an important phenomenon that explains current practices, behaviours and lifestylesof the past. This volume examines issues on ageing, population ageing in the Caribbean,particularly Jamaica, health status, health conditions, utilization, and hospitalization ofJamaicans, with emphasis on the elderly. 4

ReferencesAARP. (1999). The AARP grand parenting survey. Washington, DC: Author.Bourne, P.A. 2009. Growing Old in Jamaica: Population Ageing and Senior Citizens’ Wellbeing. Kingston: Department of Community Health and Psychiatry, Faculty of Medical Sciences, the University of the West Indies, MonaErber, Joan. 2005. Aging and Older Adulthood. Canada: Waldsworth, Thomson Learning Inc.Foos, P.W., & Clark, M.C. (2010). Human aging, 2nd ed. Boston: Pearson Education.Holmes, E.R., & Holmes, L.D. (1995). Other cultures, elder years, 2nd ed. Thousand Oaks, CA: Sage.Kalavar, J.M. (2001). Examining ageism: Do male and female college students differ? Educational Gerontology 27, 507-513.McConatha, J.T., Hayta, V., Riesser-Danner, L., McConatha D. (2004). Turkish and US attitudes toward aging. Educational Gerontology 30, 169-183.Sokolovsky, J. (1997). The cultural context of ageing, 2nd ed. New York: Bergin and Garvey Publishers.Wilks R, Younger N, Tulloch-Reid M, McFarlane S, Francis D. (2008). Jamaica health and lifestyle survey 2007-8. Kingston: Tropical Medicine Research Institute, University of the West Indies, Mona. 5

Chapter1 Historical Overview On Human AgeingIn the earlier centuries, pandemic and pestilence destroyed millions of peoples. One suchpandemic was the Oriental or bubonic plague (a rate-based disease, fleas that lived on humansand rats). In early 1330s, it exterminated many lives in Hong Kong and later spread throughoutChina, the continent of Asia and then to Europe. In October 1347, the pestilence was brought toEurope by a group of Italian merchants who had traveled to China on business. On their return tothe ports of Sicily, many of them were found suffering from the plague and some were dead. Thepestilence had traveled all the way Northern Europe to England. In August of the fourteenth century (1348), the people of England named it the ‘Black Death’. It eradicated approximately 40 million people worldwide. Some scholars argue that this disease ‘wiped out’ about one-third to one-half of European’s and Asian’s human population (Rowland 2003), and five years it slaughtered 25 million Europeans. The disease stayed with people until it disappeared in the 1600s. Then during the 1700s, smallpox slew an estimated 100 peoples worldwide. Following those pandemics and plagues, the discoveries of peninsulin along with propersanitation and public health have seen a significant reduction in mortality. Whereas low mortality 6

is not synonymous with all nations – because of warfare and famine- low death rates have beenthe experience of a plethora of the developed societies. This reality is also happening in manydeveloping and emerging nations. Accompanying mortality decline is the issue of the fertilitytransition that began in the France in the 19th century. This has spread throughout Europe,America and Canada, Japan, China, Barbados and Jamaica to name a few countries. Manydeveloped societies are now experiencing what is referred to as ‘below replacement levelfertility. This is where the society automatically replenishes itself by approximately 2.1 births perwomen of child-bearing age (15 – 49 years). There are societies like Barbados, Trinidad and Tobago, Japan, France, Sweden, andCanada among others that have a total fertility rate of approximately 1.6 children per woman ofchild-bearing age, which is an indicator of below replacement level fertility. This coupled withdeclining mortality further explains the next inevitable population challenge, old ages.Population ageing is not simply longer live, but is the health challenges that face not only theindividual but the cost of health, the possibility of reduced economic growth, shifts in diseasepatterns and prevalence and the increasing pressure that it is likely to place on the working agepopulation. The question that few Jamaicans have been asking themselves is ‘what are the scope,implications and challenges of population ageing’ within our declining state (increasingly lessresources). Indicators of population ageing Demographers refer to ageing of world population as demographic ageing (or populationageing, or ageing population). There are a few yardsticks that are used in this process. One, theyuse the median age of the population. This is where one-half of population within a geographicspace is either above or below a certain age (median age). Two, some use the proportion of the 7

human population that is 65 years (some say 60 years) and older, which is 8 – 10 %. For thepurpose of this paper, I will use the latter (8 -10% of the population 60 and 65 years and older).As a demographer, the chronological valuation for old age (or ageing population) is 65 years andbeyond; and so, this will be used throughout this paper except in a further cases, and when this isthe case, I will specify to this end. Population ageing means longer life and not necessarily quality living. In this article, Iuse ageing totally in the sense of longer life. With this said, there is an indication that Jamaica’spopulation have been ageing, and when did this began? Another germane question that is ofsignificance is ‘Is there a gender disparity in longer life, and which sex is likely to live longer inJamaica?’ I will begin with life expectancy as the symbolic representation of population ageing. Implications of population ageing Furthermore, Jamaica like Montserrat and Barbados are experiencing the return of someof those people who migrated in the 1950s-1960s, who are elderly along with the continuousnegative migration of young people, thereby increasingly expanding the population ageing inthose societies. This is an explanation of the population ageing occurring within many of theCaribbean nations. Therefore, many Caribbean countries began experiencing population ageingin 1960s but it has recently begun to be of concern because of the emphasis of this matter on theworld stage. Ageing inevitable means longer life, that affects the population composition andstructure. In that as the population ages, the base of the population pyramid narrows, while theupper portion expands. If reduced fertility continues without any major catastrophe in the future,what we are likely to experience is people living longer, and the death rates at older ages willbegin to naturally increase thereby changing the population age structure further. Another result 8

of this demographic ageing is increased disability that will result. Whereas technologicaladvances have added years to people’s lives, it has not reduced ailments. So people will beliving longer, but with more disability. Global life expectancy has risen from 47 years in 1950-1955 to 65 years and beyond in 2000-2005 and 2005-2015, which is similar for Jamaica,Trinidad and Tobago, Bahamas and Barbados (United Nations 2006:87-89; United Nations 2005:xxii: STATIN 2003). One of the probabilistic results of ageing is the reduction on the workingaged and the youthful population. These provide shifts in the population pyramid as it contractsat younger ages and expand at older ages. This is reiterated in a publication of the CaribbeanFood and Nutrition Institute (1999:191) that stated, “By the year 2050, there will be olderpersons than children in the world, the majority of whom will be females and widowed orwithout a partner. The Caribbean is likely to mirror this phenomenon…” The Statistical Instituteof Jamaica pointed out that those societies that were at the early stage of the demographictransition in which fertility remains high and mortality decline are now experiencing increasingin younger population. However, for those that at the late stage, where fertility is declining andmortality is stationary, the younger sector of the population is smaller than the segment 60 yearsand older (STATIN 2003). This is in keeping with the global perspective on demographictransition. Within the 21st century, population ageing and shifts in health status of the population aresynonymous constructs, along with the deviations between living longer and living healthier.Notwithstanding these realities, scientific study on the aged population is more recent than theconstruct itself. Erber credited a Belgian mathematician and astronomer, Adolphe Quetelet, in1835, for studying the different stages that men pass through during their lifetime. The work is apivotal landmark in the study of the ageing process. As population ageing is reality in the 9

Caribbean, Jamaica and other developed nations that have begun in earnest to project the likesocio-economic of “greying” populations within the general setting of aged dependency, supportratios and many issues associated with demographic transition. In 1884, an Englishman named Francis Galton who was both a mathematician andmedical doctor researched ‘physical and mental functioning’ of some 9,000 people between theages of 5 and 80 years (Erber 2005:4). As mathematician like his predecessor, AdolpheQuetelet, Galton want to measure human life span, physical and mental functioning of people.Therefore, he sponsored a health exhibition that would allow him to have data for analysis. Thisbegs the question – what explains that fascination of man in seeking to understand ageing, and inparticular, his/her intrigue with the aged and their wellbeing? Even though, the ageing process is lifelong and though this may be constructed withineach society differently, many decades have elapsed since Galton’s study on the health status ofpeople. Despite changes in human development and the shifts in world population towarddemographic ageing – people living beyond 65 years (see ILO 2000; Wise 1997), the issues ofthe aged and their health status, in particular general wellbeing, have not taken front stage on theradar of demographers unlike many other demographic issues. This is especially true for theCaribbean. There are signs indicating that population ageing in the 21st century is affecting manyindustrialized societies. These societies are affected through low fertility, which speaks to thefuture problems of – high age dependency ratios, high support ratio, and future changes inpopulation size and structure. Among the challenge of low fertility in industrialized nations arethe difficulties that it posses for population replacement, reduced juvenile dependency, lowerpotential fertility, and increased old-age ratio. There are some non-demographic issues that spill 10

offs of population ageing such as the consequences for future pension allocations, hospitalizationexpenditure for the aged. A demographer, Alain Marcoux, measured population ageing in an article titled‘Population ageing in developing societies: How urgent are the issues?’ as a specified valuationof the general population being 60 years and older. The benchmark that was used to establish thissituation is the proportion of the population who are aged 60 years and over exceeds 10%)whereas another group of scholars Gavrilov and Heuveline used 65 years and beyond thatexceeds 8-10%. These include for example - Germany, Greece, Italy, Bulgaria and Japan;U.S.A; Sweden – Figure 1.1, below). Interestingly, Greece and Italy’s aged population (people60 years and older) in 2000 stood at least 24% of the total population, which indicate completionof the fertility and mortality transition, and the high burden being placed on the workingpopulation. Those societies’ fertility decline began early and their mortality at older ages hasbeen declining; this justifies their ageing population. The issue of the ageing of a population cannot be simply overlooked as such; a situationwill affect labour supply, pension system, health care facilities, products demanded, mortality,morbidity, and public expenditure among other events. It [ageing] is not simply about mortality,fertility and/or morbidity. The phenomenon is about people, their environment and how theymust coexist in order to survive, and how institutions that do exist to enhance longevity. Ageing,therefore, is here to stay. In order to grasp the complexities of this phenomenon, Lawson’smonograph adequately provides a summative position on the matter. She noted that: Actually, it is predicted (U.N) that developing countries are likely to have an older generation crisis about the year 2030, that is about the same time as most developed countries (Lawson 1996:1) 11

This demographic transition is not only promogated by Lawson, but is concurred on byCowgill who believed that come the next half-century (2030), there is strong possibility thistransition will plague developing nations. This is no different for the developed nations. Threecenturies ago, the issue of ageing would not constitute one out of twenty-five of the totalpopulation, or even more than this as is the case in the 21st Century. According to Lawson, “Theworld is going to have to learn to live with populations containing a much higher proportion ofolder people…” The speed at which a population will age (60 years and over) in countries in theLatin America and the Caribbean (shift from 8 to 15 %) will be shorter than two-fifths theduration of time it took the United States and between one-fifth and two-fifths for WesternEuropean country to attain similar levels (McEniry et al. 2005; Palloni et al. 2002). The rate ofgrowth in the ageing populace in Latin America and the Caribbean is not only realty, but theissue is; will the elderly’s care and well-being reside squarely on the shoulders of the young? Seniors cannot be neglected as they will constitute an increasingly larger percentage oftotal population and sub-populations in different topography than in previous centuries.Furthermore, from all indications, in the developing world, the elderly population will continueto increase as a proportion of the globe’s population which is in keeping the world’s ageingstatistics. According to Randal and German, the numbers of aged living in developing countrieswill more than double by 2025, “reaching 850 million”. The Caribbean is not different asaccording to Grell, the English-speaking Caribbean from the 1970 census revealed that between8.8 and 9.8 percent of the populace were 60 years and older. A matter Lawson noted began inJamaica since the 1900. From a study commissioned by the Planning Institute of Jamaica, it was noted that theglobe’s population grew at a rate of 1.7 percent per annum, with the population of the seniors (60 12

years and older) growing at 2.5 percent. A point of emphasis was the monthly growth rate forthe elderly in developing countries (3.3 %), with a projected population forecast of seniors forJamaica for 2020 to be 15 percent. From the World Development Indicators report, in 2003, 6.9percent of Jamaicans were 65 years and older. Eldemire noted that the increased aged populacein Jamaica began in the 1960’s. From statistical reports, the percent has continued to increasepost-2000. STATIN in ‘Demographic Statistics, 2004’ reported that 10 percent of Jamaica’spopulation are 60 years and older, which is supported by Eldemire contrary to the viewpoints ofGibbings. Despite the indecisiveness to reach consensus on a definition of ageing from theUnited Nations’ perspective on the elderly, ‘old age’ begins at 60 years while demographersconceptualize this variable as ages 65 years and older. “Where ‘Old age’ begins is not preciselydefined, the unset of older age is usually considered 60 or 65 years of age” (WHO 2002, 125).Nevertheless, this project is a partial fulfillment of a demography degree, and so will subscribe todemographic conceptualizations, primarily. Whereas, some developing countries will begin toexperience this come 2030 most societies would have been exposed to this by 2050. U.S.A Sw eden Major Area, region and country Germany Italy Europe Japan India China Latin America and the Caribbean Af rica World 0 10 20 30 40 Percentage of the Elderly (65+ years) 1950 2000 2050 Figure 1.1: Selected regions and their percent of pop. 65+ years Source: United Nations 2005: World Population Prospects: The 2004 revision (page 20) 13

Chapter2 POPULATION AGEING and the STATE of the ELDERLY In Jamaica Introduction Ageing is not a recent phenomenon; it goes back centuries. Currently, the differences arepace and level. The distinction here is, pace denotes the rate of growth per annum; and levelrepresents the percentage of the population who are experiencing a certain event. These conceptswill be made clearer with the use of various illustrations throughout this paper. As in 2007, it isestimated that the percentage of people 65 years or over is estimated to be 7.5% and come 2050,the figure is projected to reach 16.1%, which is a 115% increase in 43 years. On the contrary,between 1950 and 2007, the percentage of people ≥ 65 years rose by only 2.2%. (Table 1.1).However, by 2030, 1 in every 8 (12.5% of the globe’s population) humans will be 65 years andolder, and this is coming from 6.9% in 2000. But there is a discourse as to whether or not ‘oldage’ begins are 60 or 65 years; hence, we will present the figures as if we were using 60 years.Thus, if we are to use 60 years and older, the trends are relatively similar to those for ages 65year or over. As in 1950, the world’s population aged 60 years and older was 1 in 15 (8.2%); butin 2007, the figure rose to 1 in 9 (10.7%), and the projected 21.7 percent (or 1 in 5) by 2050(United Nations, 2007:72) (Table 2). Based on percentages, the world’s elderly population (≥ 60years) between 1950 and 1975 increased by 0.4%. However, between 1975 and 2007, thepercentage of ‘old people’ rose by 2.1% but for 2025-2050, the increase is expected to be 6.6%. Insert Table 2.1. Presently, China, United States, Germany, India, Sweden, Italy, and Japan have in excessof 50 percent of the world’s population who are 65 years or older. But, does population-- ageingstop with those societies only? The yardstick for measuring an ageing population is having 8-10% of the population reaching at least 65 years. As of 2025, the Caribbean will have an 14

estimated 11.4% of its population ≥ 65 years. Statistics show that the percentage of Caribbeanpopulation ≥ 65 years is more than that for the combined of Latin American and the Caribbean(See Tables 2.1, 2.2). “Since population ageing refers to changes in the entire age distribution,any single indicator might appear insufficient to measure it” (Gavrilov, and Heuveline, 2003:3),which appears to have befallen many Caribbean states. This is evident in the political landscapeof Caribbean nations as the issue of demographic ageing has not taken on as a serious issue asdebt burden, inflation, unemployment, crime and international relations. The rationale for thisdelay is embedded in perception that critical as that time. But this position is far from the truth.For the reason that, apart from the demographic transition that is taking place globally andequally within the Caribbean, there is another aspect to this phenomenon. As the implications ofageing range from pension schemes problems, higher health care costs and initiatives. These donot cease there, as there are two important issues that we have yet to address, how we will bedealing with production and productivity within the context of an ageing nation (‘shrinkinglabour force because of ageing’; ‘possibly the bankruptcy of social security systems’). Onemedium has written that two-thirds of people ≥ 65 years are alive today (BRW, 1999), whichstrengthens the issue of taking population ageing to the forefront of national debate. Thus, it isclear that population ageing is a global phenomenon; but what is the extent of this in Caribbeanstates? To further comprehend this phenomenon or to explain this unbounded demographicreality; I will contextualize this paper within a global framework, with particular emphasis onselected Caribbean and more so on Jamaica. Insert Table 2.2 Ageing Defined. Ageing is a significant but neglected dimension of social stratification and the life-course is an essential component of the analysis of status (Turner 1998:299) “Where ‘Old age’ begins is not precisely defined, the onset of older age is usuallyconsidered 60 or 65 years of age” (WHO 2002:125). The indecisiveness to reach consensus on adefinition of ageing in spite of the United Nations’ perspective on the elderly, which ischronological ageing that begins at 60 years, yet demographers and many statisticians continueto conceptualize this variable as beginning at age 65 years (Lauderdale 2001; Elo 2001; Mantonand Land 2000; Preston et al. 1996; Smith and Kington 1997; Rudkin 1993). This moot point 15

will not be settled in this paper, but what will happen here is that the various perspectives will bepresented to the readers. As a demographer, however, I will primarily be using the chronologicalage of 65 years and older to present the commencement of ‘old age’ (or ageing). But one shouldkeep in mind (as Turner date outlines) that ageing is a ‘social stratification’ which is neglectedwithin the discourse of social stratification. In medieval times, Thane (2000) notes that ‘old age’ were defined as 60 years and older.She justified this by forwarding an argument for the established age. In medieval England, menand women ceased at 60 years to be liable for compulsory service under labour laws or toparticipate in military duties. Ancient Rome, on the other hand, ‘old age’ began from early 40 to70 years, with 60 years being “some sort of annus climactorius”. Demographers see the seniors -the elderly or the aged (old people) - as individuals 65 years and older, and not an individual whois 60 years of age. Western societies use 65 years and older to represent the elderly (seniors) asthis is the period when people become fully eligible for Social Security benefits. Irrespective ofthe commencement age of the elderly, there is a wholesale agreement that the aged at thebeginning of the next generation will be a real social challenge. One scholar emphasized thatthere is no absoluteness in the operational definition of the “elderly” (Eldemire 1995:1). Shecommented that from the World Assembly of Ageing (which was held in Vienna in 1982), the“elderly” is using the chronological age of 60 years and older ‘as the beginning of the ageingprocess’. Jamaica having signed the Vienna Declaration of Ageing, which defines ageing tobegin at 60 years, Eldermire questioned academics and other scholars for their rationale in using65 years. I will now classify the ageing in two main categories, (1) chronological and (2)biological ageing. Chronological ageing Within the study of demography, the elderly begins at the chronological age of 65 years –using the unit of analysis of time, based on the number of years and months that has elapsedsince birth (Erber 2005; Iwashyna et al. 1998; Preston, et al. 1996; Smith and Waitzman 1994).However, based on the monographs from other scholars (such as - Marcoux 2001; Eldemire1997; PAHO and WHO 1997; Eldemire 1995; Eldemire 1994; Barrett 1987), the issue of theaged begins at 60 years. Hence, the issue of the aged continues to battle from non-standardization. For those who use 60 years, they adopt this value because of the World 16

Assembly on Ageing (in Vienna, Austria: July-August 1982), which postulates that ageingbegins at the chronological of 60 years. The Canadian statistical agency used age 65 years as the dividing line between “young”and “old” (Moore et al. 1997, 2; Smith and Waitzman 1994; Preston, et al., 1996). The issue ofusing the chronological age of 65 years to measure older adulthood according to one academiacomes from the minimum age at which the Social Security System begins disbursing paymentfor pension to people living with the United States (Erber 2005:12). It is argued that in 1935, theU.S. government modeled this from the German’s retirement system. This explains the use of 65years of age by many scholar, practitioners and non-professionals ever since. This approach sub-divides ageing into three categories. These are (i) young-old (ages 65 through 74 years), (ii) old-old (ages 75-84 years) and oldest-old (ages 85 years and beyond). However, is there a differencebetween biological and chronological ageing? Biological ageing Organisms age naturally, which explains biological ageing. This approach emphasizesthe longevity of the cells, in relation to the number of years the organism can live. Thus, in thisconstruction, the human body (an organism) is valued based on physical appearance and/or stateof the cells. Embedded in this apparatus is the genetic composition of the survivor. This occurswhere the body’s longevity is explained by genetic components. Gompertz’s law in Gavriolovand Gavrilova (2001) shows that there is a fundamental quantitative theory of ageing andmortality of certain species (the examples here are as follows – humans, human lice, rats mice,fruit flies, and flour beetles (, Gavriolov and Gavrilova 1991). Gompertz’s law went further toestablish that human mortality increases twofold with every 8 years of an adult life, which meansthat ageing increases in geometric progression. This phenomenon means that human mortalityincreases with the age of an adult, but that this becomes less progressive in advanced ageing.Thus, biological ageing is a process where the human cells degenerate with years (the cells diewith increasing in age), which is explored in evolutionary biology (see Charlesworth 1994). Butstudies have shown that using evolutionary theory for “late-life mortality plateaus”, can failbecause of the arguably the unrealistic set of assumptions that the theory uses to establish itself. Reliability theory, on the other hand, is a better fitted explanation for the ageing ofhumans than that argued by Gompertz’s law as the ‘failing law’ speaks to deterioration of human 17

organisms with age (Gavrilov and Gavrilova 2001) as well as a non-ageing term. The latterbased on Gavrilov and Gavrilova (2001) can occur because of accidents and acute infection,which is called “extrinsic causes of death”. While Gompertz’s law speaks to mortality in ageingorganism due to age-related degenerative illnesses such as heart diseases and cancers, a part ofthe reliability function is Gompertz’s function as well as the non-ageing component. When the biological approach is used to measure ageing, it may be problematic as twodifferent individuals with the same organs and physical appearance may not be able to perform atthe same rates, which speaks to the difficulty in using this construct to measure ageing.Nevertheless, this construct is able to compare and contrast organisms in relation to the numberof years, a cell may be likely to exist. Erber (2005) argues that this is undoubtedly subjective, aswe are unable within a definite realm to predict the life span of a living cell (Erber 2005:9).Interestingly, the biological approach highlights the view that the ageing process comes withchanges in physical functioning. The oldest-old categorization is said to be the least physicalfunctioning compared to the other classification in chronological ageing. The young-old, on theother hand, are more likely to be the most functioning as the organism is just beginning thetransition into the aged arena (Erber 2005; Brannon and Fiest 2004). In order to avoid such pitfalls in constructions that may arise with the use of thebiological approach, ergo, for all intent and purposes, given the nature of policy implications ineffective planning, the researcher is forwarding the perspective that seniority in age commencesat age 65 years – using the chronological ageing approach. In summarizing the ageing transition, both chronological and biological ageing have asimilar tenet; in that, as we move from young-old to oldest-old, the body deteriorates and whatwas of low severity in the earlier part of the ageing process becomes crucial in the latter stage.Hence, at the introductory stage of the ageing transition, the individual may feel the same aswhen he/she was in the working age-population, but the reality is that the body is in a decliningmode. Because humans are continuously operating with negatives and positive, as he/shebecomes older – using the ageing transition (65 years and older) – the losses (or negatives)outweigh the positives. This simply means that the functionality limitation of the body falls, andso opens the person up to a higher probability of becoming susceptible to morbidity andmortality. Secondly, their environment, which may not have been problematic in the past, now 18

becomes a health hazard. One University of Chicago scholar summarizes this quite well in Table2.3: Table 2.3: Characteristics of the Three Categories of Elderly, and Ageing transition Characteristic The Ageing Transition Young-old Aged Oldest-Old Heath problems Low Moderate High Physical disability Low Moderate High Demand for medical care Low Moderate High Demand for public service Low Moderate High Demands on children Low Moderate High Dependency on other Low Moderate High Social isolation Low Moderate High Source: This is taken from Essays in Human Ecology 4. Bogue 1999, 3. 1 Donald Bogue (1999) used aged (age 75 – 84 years) to refer to what this paper calls old-old Historical Issues on Population Ageing: Global Perspectives. Ageing has emerged as a global phenomenon in the wake of the now virtually universal decline in fertility and, to a lesser extent, of increases in life expectancy (Marcoux 2001:1) In the earlier centuries, pandemic and pestilence would destroy millions of lives. Anexample here is, in the fourteenth century, the ‘Black Death’, killed approximately 40 millionpeople worldwide. One scholar argues that this disease ‘wiped out’ about one-third to one-halfof European’s and Asian’s human population (Rowland, 2003). As during the 1700s, smallpoxkilled an estimated 100 peoples worldwide. This reality explains why population ageing was nota phenomenon then, as the deaths were high and widespread. Therefore, the person was notlikely to live beyond fifty years. Following those pandemics and plagues, the discoveries ofpeninsulin along with proper sanitation and public health have seen a significant reduction in 19

mortality. Whereas low mortality is not synonymous with all nations, low death rates have beenthe experience of a plethora of the developed societies. This reality is also happening in manydeveloping and emerging nations. Accompanying mortality decline is the issue of the fertilitytransition that began in France in the 19th century. It is argued, that reduction in fertility isprimarily a cause of population ageing today as well as a steady decline in mortality rates. Even though, the ageing process is life long and though it may be constructed differentlywithin each society, many decades have elapsed since Galton’s study on the health status ofpeople. Despite changes in human development and the shifts in world population towarddemographic ageing – people living beyond 65 years (see ILO, 2000; Wise, 1997), the issues ofthe aged and their health status, in particular general wellbeing, have not taken front stage on theradar of demographers, unlike many other demographic issues. The 20th century has brought with it massive changes in typologies of diseases wheredeaths have shifted from infectious diseases such as tuberculosis, pneumonia, yellow fever,Black Death (Bubonic Plague), smallpox and ‘diphtheria’ to diseases such as cancers, heartillnesses, and diabetes. Although diseases have shifted from infectious to degenerate, chronicnon-communicable illnesses have arisen and are still lingering within all the advances in science,medicine and technology. One demographer showing the extent of human destruction due to theBlack Death mentioned that this plague reduced Europe’s population by one-quarter (Rowland,2003:14). Accompanying this period of the ‘age of degenerative and man-made illnesses’ is lifeexpectancies that now exceed 50 years. So while people aged 70 years and beyond in manydeveloped and a few developing states, the question is - Are they living a healthier life – how istheir wellbeing within the increases in life expectancy? Alternatively, is it that we are just stuckon life expectancies and diseases as primary predictors of wellbeing – or health status? Before the establishments of the American Gerontology Association in the 1930s andtheir many scientific studies on the ageing process (Erber, 2005), many studies were done basedon the biomedical model (physical functioning or illness and/or disease-causing organism),(Brannon, & Feist, 2004:9). Many official publications used either (i) reported illnesses andailments, or (ii) prevalence of seeking medical care for sicknesses. Some scholars have still notmoved to the post biomedical predictors of health status. The dominance of this approach is sostrong and present within the twenty first century, that many doctors are still treating illnesses 20

and sicknesses without an understanding of the psychosocial and economic conditions of theirpatients. To illustrate this more vividly, the researcher will quote a sentiment made by a medicaldoctor in ‘The Caribbean Food and Nutrition Institute Quarterly, 1999. A public healthnutritionist, Dr. Kornelia Buzina, says that “when used appropriately, drugs may be the singlemost important intervention in the care of an older patient … and may even endanger the healthof an older patient …” (quoted in the editorial of Caribbean Food and Nutrition Institute1999:180). A demographer, Alain Marcoux, measured population ageing in an article titled‘Population ageing in developing societies: How urgent are the issues?’ as a specified valuationof the general population being 60 years and older. The benchmark that was used to establish thissituation is the proportion of the population who are aged 60 years and over exceeds 10%(Marcoux 2001:1), whereas another group of scholars Gavrilov & Heuveline (Gavrilov, &Heuveline, 2003) used 65 years and beyond that exceeds 8-10%. These include for example -Germany, Greece, Italy, Bulgaria and Japan; U.S.A; Sweden (Goulding, & Rogers, 2003).Interestingly, Greece and Italy’s aged population (people 60 years and older) in 2000 stood atleast 24% of the total population (Mirkin, & Weinberger, 2001), which indicates the completionof the fertility and mortality transition, and the high burden being placed on the workingpopulation. Those societies’ fertility decline began early and their mortality at older ages hasbeen declining; this justifies their ageing population. This is not only confined to developedsocieties as it is spreading to the entire world. Demographic Trends: The Global perspective Globally, trends in population ageing are such that demographic ageing is seen as afundamental phenomenon of concern both inside and outside of the intelligentsia class. I willdisplay the issue in great detail below, as the figures will speak of the trends that we have seenmore so since the 1900s. And that this progression will continue in the next 50 years. The agedpersons >65 years and older in 1950 was 5.2%, and by 1995 the figure rose to 6.5%. But, duringthe 1950s-1960s, the 65+ age cohort rose by 0.1%, which may be marginal but it earmarks thebeginning a demographic phenomenon. In 1999, persons aged 65 years and older were 410.5 million, and one year later the figurerose to 420 million, which is a 2.3 percentage increase over the previous year. In addition during 21

2000 to 2030, it is estimated that aged persons >65 years, will rise from an approximated 550million to a projected 973 million (76.9%). By 2050, the persons aged 65 years and beyond, willbe some 13.8% of the world’s population. Currently, the developed nations sharedisproportionately more of the aged persons >65 years, this reality is not projected to change inthe future. However, by 2030, the absolute number of aged >65 years in the developing societiesis expected to triple, which will not be the same for the developed nations (from 249 million in2000 to 690 million by 2030). In summary, during 1950-2000, the elderly population (persons65+) increased by 1.7%. However, from 2000-2050, the same aged cohort will rise by 6.9%,which denotes a 100% increase in 50 years. The statistics reveal that come 2050 most of the aged population will be residing indeveloping countries. In addition, by 2030 the population 65-and older in developing societieswould have increased by 140 percent, which is 40% more elderly in developing nations than inthe world. Importantly, the aged are on the upper end of the ageing spectrum; and this affects thepopulation dynamics of the society. The total human population, within any geographic area,constitutes children, youth, working aged people and the elderly. With this said, the “graying”(spelling not consistent throughout) of a population is caused by fertility decline, reducedmortality and migration of the young and return of retirees coupled with increases in lifeexpectancies. Where the elderly population outgrows the younger population, this constricts thepopulation structure at younger ages and expanding it at older ages (Rowland, 2003:98). This isreferred to as demographic transition. It is the experience of many developed countries thatstarted with France, but has increasingly become a phenomenon for many developing nations. The demographic development of the world is not limited to the increase in persons 65years and older but the reduction of the children population (persons 0 – 14 years). In 1950, thechildren population was 34.3% of the globe’s population, and in 1975 the figure rose to 36.8%,and in 2007 the United Nations (2007:72) wrote that this is expected to be 27.6% and come2050, 20.2%. Accompanying this reduction in the children population is the increase in themedian age of the world’s population. As at the state of the 1950, this was 23.9 years, it fell to22.4 years in 1975 and is estimated to rise to 28.1 years in 2007 and project to reach 37.8 years,which is an indication of population ageing. The increase in proportion of people ≥ 65 andchanges in the median age can be simply explained by mortality changes, which demographers 22

use life expectancy to explain. In life expectancy at birth during 1950-1955 was 46.6%, in 1975-1980, 59.9 years, and 2005-2010, 66.5 years and come 2045-2050 it is expected to reach 75.1years. In the more developed nations, currently (in 2007) estimated by the United Nations,2007:74), 20.7% of the population are persons ≥ 60 years, 15.5% are persons ≥ 65 years, and3.9% are persons ≥ 80 years. The life expectancy for people in these regions is more than theworld’s figure, as the United Nations (2007:75) writes that during 2005-2010, it is 76.2 years.However, in Northern Europe, it is 78.7 years, Southern Europe; it is 79.1 years, WesternEurope, 79.6 years, and in Northern America, 78.2 years. Thus, population ageing is indeed aglobal phenomenon and more so in developed nations, but what about the Caribbean and inparticular Jamaica? Demographic trends: Selected Caribbean Nations Ageing inevitably means longer life that affects the population composition and structure.Due to the fact that as the population ages, the base of the population pyramid narrows, while theupper portion expands. Demographers argue that this is substantially due to the fertility transitionand reduced mortality at older ages. If reduced fertility continues without any major catastrophein the future, what we are likely to experience is people living longer, and the death rates at olderages will begin to naturally increase thereby changing the population age structure further.Global life expectancy has risen from 47 years in 1950-1955 to 65 years and beyond in 2000-2005 and 2005-2015, which is similar for Jamaica, Trinidad and Tobago, Bahamas and Barbados(United Nations, 2006:87-89; United Nations, 2005: xxii: STATIN, 2003). One of theprobabilistic results of ageing is the reduction on the working aged and the youthful population.These provide shifts in the population pyramid as it contracts at younger ages and expand atolder ages. This is reiterated in a publication of the Caribbean Food and Nutrition Institute(1999) that stated, “By the year 2050, there will be (shouldn’t more go here) older persons thanchildren in the world, the majority of whom will be females and widowed or without a partner.The Caribbean is likely to mirror this phenomenon…” (Caribbean Food and Nutrition,1999:191). The Statistical Institute of Jamaica pointed out that those societies that were at theearly stage of the demographic transition in which fertility remains high and mortality decline arenow experiencing an increase in the younger population. However, for those that are at the latestage, where fertility is declining and mortality is stationary, the younger sector of the population 23

is smaller than the segment 60 years and older (STATIN, 2003). This is in keeping with theglobal perspective on demographic transition. I will present a graphical display of the populations of the World and the Caribbean oftwo age cohorts, children (0-14 years) and elderly (65+), as an indication of the similarities thesedemographic trends. A further subdivision of selected Caribbean nations’ proportion of childrenand elderly populations are presented in Table 2.4.Table 2.4: Percentage of Estimated or Projected Populations of Selected Caribbean Nations,1980, 2000, 2005 and 2020 1980 2000 2005 2020Country 0-14 60+ yrs 0-14 60+ 0-14 yrs 60+ 0-14 60+ yrs yrs yrs yrs yrs yrsBarbados 29.6 14.1 22.5 14.1 18.9 13.2 19.4 19.3Guyana 40.9 5.7 30.2 6.3 29.4 7.4 23.0 11.3Jamaica 40.3 9.3 28.3 9.0 31.2 10.2 20.4 12.4Suriname 39.8 6.3 32.4 7.9 30.1 9.0 24.2 9.8Trinidad 34.3 8.1 28.6 8.4 21.5 10.7 23.5 13.3& TobagoCaribbean 36.7 8.6 29.9 9.9 27.7 10.7 24.2 14.2Source: United Nations. 2005c: World Population Prospects: The 2004 Revision Demographic development in the Caribbean has taken a similar path like the rest of theworld (Population Reference Bureau, 2007; STATIN, 2006; United Nations, 2005c). Over theyears, the movement has being such that mortality and fertility has been declining, and thepopulation 65 years and older has been increasing proportionately more than proportion who arechildren (See Tables 2.5, 2.6).. 24

By the standard that if a population of aged person using ≥ 60 years exceeds 8-10% of thepopulation, there is the issue of demographic ageing. So since 1980, countries like Barbados,Jamaica, Trinidad and Tobago and generally the Caribbean have been experiencing thisphenomenon (Table 2.4). From the Table, by 2020, Barbados’ elderly population will be higherthan that of the Caribbean’s average. Among the factors of population ageing are mortality andfertility. Thus, merely using the proportion of persons who are either 65+ or 0-14 years is anindicator of demographic transition but mortality and fertility are critical determinants of ageingpopulation. According to the United Nations (2007:5), Decreasing fertility has been the primary cause of population ageing because, as fertility moves steadily to lower levels, people of reproductive age have fewer children relative to those of older generations, with the result that sustained fertility reductions eventually lead to reduction of the proportion of children and young persons in a population and a corresponding increase of the proportion in older groups (UN, 2007:5) The United Nations’ perspective has highlighted the importance of including fertility indemographic transition discourse as well as mortality. Statistics reveal that the total fertility rate(TFR) for 1970-1975 for the world was 4.49 and for 2000-2005, it fell to 2.65; whereas in LatinAmerica and the Caribbean between 1970-1975, it was 5.05 and this was further reduced to 2.55in 2000-2005 (United Nations 2005c, xxi). Concurrently, in 2005, total fertility in The Bahamasis 2.2, in Barbados it is 1.5, for Jamaica 2.3 and for Trinidad and Tobago, 1.6 (United Nations2006, 87-89). Barbados and the twin islands of Trinidad and Tobago are experiencing belowreplacement level fertility (Total Fertility Rate – TFR of 2.1 – United Nations 2000, 4), aproblem presently faced by many developed nations such as those in Southern and Easter Europeand the United States (United Nations 2005c, xxi). I have presented Table 5Table 5, for a moredetailed assessment of the total fertility trends of selected Caribbean States, the Caribbean andLatin America, in an effort for us to see the trend in this phenomenon, and the implications ofthis for population ageing come 2050. 25

Table 2.5: Total Fertility Rate for Selected Caribbean Nations, Caribbean, and Latin American: 1950-1955 to 2045-2050 Countries 1950- 1975- 2005- 2025- 2045- 1955 1980 2010 2030 2050 Bahamas 4.1 3.2 2.2 1.9 1.9 Barbados 4.7 2.2 1.5 1.8 1.9 Belize 6.7 6.2 2.8 2.0 1.9 Dominican Rep 7.4 4.7 2.6 2.1 1.9 Guyana 6.7 3.9 2.1 1.9 1.9 Haiti 6.3 6.0 3.6 2.5 2.1 Jamaica 4.2 4.0 2.3 2.0 1.9 Suriname 6.6 4.2 2.4 2.0 1.9 Trinidad & 5.3 3.4 1.6 1.8 1.9 Tobago Caribbean 5.2 3.6 2.4 2.1 1.9 Latin America & 5.9 4.5 2.4 2.0 1.9 Caribbean Source: World Population Ageing 2007 Another determinant of the demographic transition is mortality. The mortality statisticsare used to compute the life expectancies, and so the researcher will use the latter as it is anindicator of the former. Mortality in the Caribbean has been falling and this can be seeing fromthe increased life expectancies, which are highly comparable with those in developed nations,which is beyond 71 years(United Nations 2007 – See Table 2.6, below). 26

Table 2.6: Life Expectancy at Birth of both Sexes for Selected Caribbean Nations, the Caribbean, and Latin American Countries 1950- 1975- 2005- 2025- 2045- 1955 1980 2010 2030 2050 Bahamas 59.8 67.2 72.1 78.0 82.0 Barbados 57.5 71.4 76.4 79.2 81.4 Belize 57.7 69.7 71.7 74.0 78.0 Dominican Rep 45.9 61.9 68.6 73.8 77.7 Guyana 52.3 60.7 65.4 70.6 74.2 Haiti 37.6 50.6 53.5 62.2 70.1 Jamaica 55.8 70.1 71.1 75.0 77.7 Suriname 56.0 65.1 70.2 74.7 78.1 Trinidad & 59.0 68.3 70.1 74.1 78.5 Tobago Caribbean 52.2 64.5 68.7 73.2 76.9 Latin America & 51.4 63.0 72.9 76.8 79.5 Caribbean Source: World Population Ageing 2007 Demographic Trends: Jamaica The use of life expectancy, mortality, and total fertility rates are just some of the wayswith which demographic development can be shown. Instead of showing both mortality and lifeexpectancy, for this section of the paper the researcher will use life expectancy. As mortalityrates are used to calculate the life expectancy at various ages (Table 2.7). Another way ofdepicting population changes is through the use of a population pyramid. In this section, theresearcher will use Jamaica’s population pyramid since 2000 to depict the demographictransition occurring in this society, and then percentages of the elderly people with regard to thetotal population. It should be noted that the nation’s population pyramid in the year 2000showed a narrow top and a broad base. But by 2025, the population narrows at the base andbegins to expand at the middle, and come 2050, note how the population contrasts at the base aswe move toward an ageing population. Come 2050 and beyond, Jamaica’s oldest elderly will be substantially more females. The“graying” of the Jamaica’s population is coming, and has already made its way within the 27

society. From a demographic perspective, relatively speaking a society is said to be oldwhenever the population of person aged 60 or over (and some scholars use 65 years or over)exceeds 8-10%, which is the case in Jamaica (Appendix I). This is not the only indicator as lifeexpectancy can be used to show population ageing. Jamaica’s life expectancy at birth for malesbetween 1879 and 1882 was 37.02 years and for females it was 39.80 years, between 2002 and2004 males’ life expectancy rose to 71.26 years and that of the females’ to 77.07 years, which isa clear indictor of demographic ageing (See Table 2.7). Table 2.7: Life Expectancy at Birth of Jamaicans by Sex, 1880-2004 Average Expected Years of Life at Birth Period: Male Female 1880-1882 37.02 39.80 1890-1892 36.74 38.30 1910-1912 39.04 41.41 1920-1922 35.89 38.20 1945-1947 51.25 54.58 1950-1952 55.73 58.89 1959-1961 62.65 66.63 1969-1970 66.70 70.20 1979-1981 69.03 72.37 1989-1991 69.97 72.64 1999-2001 70.94 75.58 2002-2004 71.26 77.07 Sources: Demographic Statistics (1972-2006) From records of the Population Division of the United Nations, Jamaica’s population 60years and older in 2050, using the medium (should it be median) variant, is likely to be 24% of 28

the entire population, with 18.1% being 65 years and older, compared to approximately 5%being 80+ years. These shifts mean more degenerated conditions at older ages, increaseddisability and diminished quality of life. The disparity in gender composition speaks to thehigher morbidity in women and higher mortality for men (see Newman 2000: 8). In 2004, Jamaica’s old-aged population stood at 7.7 percent. According to WHO/SEARC(1999), India’s elderly population was 7.7 percent. During 2004-1991, the elderly population ofJamaica rose by 3.28 percent. When the elderly is strictly operationalized within ademographer’s space (65 years and beyond), on an average the elderly population grew by 3.62percent. The data in Appendix II reveal that for every 100 working-aged of the population thereare approximately 13 elderly that is dependent on them. This reality is within approximately 30percent of the population being children. Over the same period, the number of child-to-total-population grew by - 4.4 percent and by -10.08 percent for the youth. Within this context, thereis a need to analyze the labour force participation of aged Jamaicans as there would be socio-economic implications if this were to be declining in the nation. There is little debate within the public arena about the increasing decline of the labourforce participation rate of aged Jamaicans. In 1980, the labour force participation rate (in %) was46.4% and it is estimated that this to be 26.6% in 2007. This represents a 43% reduction in thenumber of people 65+ years who were actively involved in the labour force. When the labourforce participation rate is decomposed by sexes, the figures reveal a more telling disparity. Asfor females, in 1980, there were 30.4% of women actively involved within the labour force, but itis estimated to be 13.8% in 2007, which is a 55% reduction in the number of employed females.With respect to males’ involvement in the labour force, it is projected to fall to 41.4% in 2007,which is coming from 65.3% in 1980. The labour force participation rate for men will fall by23% compared to that of females that will decline by 55%. This is within the context of femalesliving longer than their male counterparts, and that the retirement age for females is 60 years andnot 65 years (Table 2.8). Therefore, if we are to extrapolate a reduced 5 years for females, thelabour force participation rate will increase further by at least percentage points. 29

Table 2.8: Jamaica: Selected demographic variables, Labour Force Participation (in %).Total (% of population4) 1950 1975 2007 2025 2050 60+ 5.8 8.5 10.3 15.0 23.6 65+ 3.9 5.8 7.6 10.3 17.7 80+ 0.2 0.8 2.0 2.3 5.6Female 1950 1975 2007 2025 2050 60+ 6.6 9.0 10.7 16.1 25.9 65+ 4.4 6.3 8.1 11.0 19.9 80+ 0.3 1.0 2.2 2.6 6.9Male 1950 1975 2007 2025 2050 60+ 5.0 8.0 9.9 13.8 21.3 65+ 3.2 5.3 7.1 9.7 15.4 80+ 0.2 0.6 1.8 2.0 4.3 1950 1975 2007 2025 2050Median age 22.2 17.0 24.9 30.7 39.3Labour Force Participation 1980 1990 2007 2010 2020 65+ 46.4 37.1 26.6 26.6 25.1 65+ 30.4 23.6 13.8 13.1 12.3 65+ 65.3 53.6 41.4 40.7 39.6United Nations, 2007:308-309 Another variable that can be used to indicate population ageing is the median age. Themedian age denotes a value that where one-half of the population is above or below that age.Continuing, the median age for Jamaica’s populace in 1950 was 22.2 years and it is estimated toreach 24.9 years in 2007 and come 2025 31 years, and by 2050 it should increase by another 8.6years. It should be note here, that demographers use a median age of 30 years to indicate anageing population. Thus, population ageing is without a doubt a Jamaican phenomenon like theNational debt problem and other social issues such as crime and teenage pregnancy. Without effective population planning for the elderly, come the next four decades, theold-aged population will become a burden to the working aged-populace in respect to medicalcare, nursing care, pension, other social insurance and survivability cost. With this impendingsocial reality, there is a high probability that the old-aged will be called on to provideincreasingly more of their needs for themselves within the construct of limited resources fromdeveloping societies. The physiological changes with ageing such as loss of hair, wrinkling ofthe skin, decrease in height, and loss of teeth are not the only issue of old age but there are othercritical factors that affect their wellbeing. State of the Elderly, with emphasis on Caribbean and Jamaica The Caribbean like many developed countries is now faced with the daunting task ofaddressing the “graying” of its population, because of mortality and fertility decline, which 30

began1960s. To show that this is a challenge to geographic topography, the region launched itsfirst forum titled ‘The Caribbean Symposium on Population Ageing’ in November 2004 in Portof Span, Trinidad and Tobago, in order to strategize about this inevitable demographic transition,which began in earnest in developed societies. This is a precursor to its predecessor which washeld in Vienna in 1982 called ‘The First Assembly on Ageing’ and another named ‘SecondWorld Assembly on Ageing’, which was in Madrid in 2002. Like the developed world, theCaribbean islands are cognizant that policy implementation and mechanism are needed to forgean equitable solution for this phenomenon. With the Symposium comes the recognition thatageing is not limited to its call but that it affects the general society, future generations andpolitical decisions. Ergo, what is the state of the grayed population in Caribbean and more sowithin Jamaica. A study revealed that there is a statistical causal relationship between socioeconomicconditions and the health status of Barbadians. The findings revealed that 5.2% of the variationin reported health status was explained by the traditional determinants of health. Furthermore,when this was controlled for current experiences, this percent fell to 3.2% (falling by 2%).When the current set of socioeconomic conditions were used they account for some 4.1% of thevariation in health status, while 7.1% were due to lifestyle practices compared to 33.5% that wasas a result of current diseases (see Hambleton et al. 2005). It holds that importance place bymedical practitioners on the current illnesses – as an indicator of health status – is not unfoundedas people place more value on biomedical conditions as responsible for their current healthstatus. Despite this fact, it is obvious from the data – using 33.5% - that there are otherindicators that explain some 67.5% of the reason why health status is as it is. Furthermore, withan odds ratio of 0.55 for number of illness, there is clearly suggesting that the more peoplereported illness, the lower will be their health status. (See Hambleton 2005); and this was equallyso for more disease symptoms – odds ratio was 0.71) Accompanying the reduction in physical functioning which is a feature of biologicalageing (Erber 2005) is the fact that the Jamaican elderly spend the most number of daysreceiving medical care for illnesses and/or injuries (see PIOJ and STATIN 2002:4.1). In addition,they experience the highest rate of protracted illness the country, with the “… very young andthe elderly being the most vulnerable” (PIOJ and STATIN 1997:45). Embedded in this finding isthe poor health status of the elderly despite living longer. Essentially, this particular group is 31

suffering from ill health caused by diabetes, stress, psychiatric disorders and chronic diseases,which translates into lower quality of life while their life is prolonged (see PIOJ and STATIN1994:22.1; 1990:20.1), which means they are living longer but suffering more - the high cost oflongevity of life. A Ministry of Health (MOH) report notes that the prevalence of chronic illnesses has alsoincreased with ageing and that this is even more pronounced for those 65 years and older, withmore males than females spending more time in health care facility (MOH, 2004:75), using thedischarge rate – 975.1 per 10,000 for males compared to 817.1 per 10,000 females. Interestingly,when a detailed analysis was done of the data, seniors who reside in rural areas were sufferingmore than their counterparts who live in other zones (PIOJ and STATIN 2000:58). A PIOJ andSTATIN (1995:32) report summarizes the wellbeing status of those 60 years and older, whenthey say “… our 60 year olds exhibited the highest prevalence of protracted illness/injuries”. Thesituation is speaksof is a state of well-being for the elderly that is not in keeping with thepositives of the advancement in medicine and medical technology. There is definitely a disparitybetween the seniors’ wellbeing reality and their lived years, which reiterates the need to measurewellbeing outside of the traditional biomedical model. From the findings of a cross-sectional study conducted by Powell, Bourne and Waller(2007) of some 1,338 Jamaicans, 19.0% of respondents perceived that their economic well-beingto be ‘very bad’. In addition, when they asked, “Does your salary and the total of your family’ssalary allow you to satisfactorily cover your needs”, 57.4% of them felt that this “does not cover”their expenses (Powell, Bourne and Waller 2007:29). What is the situation of the elderly seeingthat this group is even more (or equally) vulnerable than other age cohorts? The answer to this isembedded within JSLC reports. The JSLC (1997) makes it clear that the aged population(22.6%) and the children (less than five years – 14.7%) reported the highest number ofillness/injury, with those who resided in the rural areas being more vulnerable than those in otherzones are. In order to capture the severity of the issues faced by the Jamaican aged, if we are toconvert the mean number of days of reported illnesses into monetary terms, then the medicalexpenditure of the elderly would have helped to erode their well-being, along with the illnessesand their severity. Then, when retirement, loss of income, the cost associated with protractedailments, and the psychological challenges associated with ageing are collated and included inthe daily life of the elderly, within the context of a shrinking economy, rising prices, the poor and 32

the elderly in particular the poor aged would be more vulnerable than other age groups withinthis society. There is an interconnection between economics and demography. In that,economists are concerned about human economic decisions at the micro and the macro level.The demographer, on the other hand, invests time in studying the science of human population.Therefore, while the demographer is not interested in the costing of decisions, the economistrequires a thorough understanding of the principles of the human population, in an effort toeffective comprehend how people within a particular geographic area are probable able to makedecision. The interconnectivity is evident that at the London School of Economics, thedepartment of demography is a subsection. A study on the elderly published in the Caribbean Food and Nutrition Institute’smagazine Cajanus found that 70% of individuals who were patients within different typologiesof health services were senior citizens (Caribbean Food and Nutrition Institute 1999; Anthony1999). Among the many issues that the research reported on are the six major causes ofmorbidity and mortality identified by the Caribbean Epidemiology Centre that is of paramountimportance to this discussion; the influence of - cerebrovascular, cardiovascular, neoplasm,diabetes, hypertension and acute respiratory infection (Figure 2.1). The diagram below depictsthe ranked order of the five leading causes of death for people 65 and over of selected Caribbeancountries in 1990. Trinidad & Tobago St. Lucia A cute respiratory inf ections Monts errat Hypertension Jam aica Diabetes Country Neoplasms Guyana Cardiovascular Dom inica disease Cerebrovascular disease Barbados Baham as 0 1 2 3 4 5 Ranked Order of 5 leading causes of mortalityFigure 2.1: Ranked Order of the five leading causes of mortality in the population 65 yrs and older, 1990Source: adopted from Caribbean Food and Nutrition Institute 1999: 222 33

In seeking to explain the severity of the health status of Caribbean nationals, usingBarbados and Jamaica, the Caribbean Food and Nutrition Institute (1999) presents the 5-leadingcauses of morbidity as reported by seniors. The data revealed that the primary cause of illnessesin Barbados and Jamaica was hypertension. In both countries, hypertension was a femalephenomenon – in Barbados, females reporting 44.6% compared to 33.1% for males and inJamaica it was 55.4% for females and 30.3% of males (Figure 2.2, below). Stroke Heart disease Jamaica Female Diseases Jamaica Male Arthritis Barbados Female Dia betes Barbados Female Barbados Male Hyp erte nsion 0 20 40 60 Percentage Source: Figure taken from Caribbean Food and Nutrition Institute 1999:225. Figure 2.2: Leading causes of self-reported morbidity in the population of seniors, by gender in Barbados and Jamaica. The data in Figure 2.2 shows that hypertension and arthritis are morbidities thatsignificantly plague both men and women in both Caribbean countries. These chronic non-communicable diseases continue to interface within the functional lives of the elderly, whichmean that they are indeed living longer but are faced with lowered wellbeing. Secondly, if they 34

are poor with proper and adequate health care coverage – which could be private or public - theimplications of the cost of care along with the daily living could further add stresses to the statusof life experienced by the elderly. Hence, living longer although it is directly related to reducedmortality, this does not speak to the lifestyle changes and their positive influences on thewellbeing of seniors. A study conducted by Costa, using secondary data drawn from the recordsof the Union Army (UA) pension programme that covered some 85% of all UA, show there is anassociation between chronic conditions and functional limitation – which include difficultywalking, bending, blindness in at least one eye and deafness (Costa 2002). Among thesignificant findings is – (i) the predictability between congestive heart failure of men andfunctional limitation (walking and bending). Although Costa’s study was on men, this equallyapplies to women as biological ageing reduces physical functioning, and so any chronic ailmentwill only further add to the difficulties of movement of the aged, be it man or woman. Like many developed countries, Jamaica is able to boast of its notable achievement inprogress made toward advancing the health status of its populace, during the twentieth century –the postponement of death, lowering fertility, high nutrition and sanitation and more importantlythe increasing life expectancy. Analyzing data on life expectancy indicate that the country’shealth status is reasonably good, as the values for life span is similar to those in some FirstWorld societies – over 70 years. Nevertheless, those positives are not sufficient to outweigh the increases in chronic non-communicable diseases - hypertension, diabetes, cardiovascular diseases, neoplasm, depressionand arthritis. These diseases are on the rise in the world and are no different in Jamaica. Theycontinue to plague those who are more so 60 years and older, of a particular socioeconomicstatus, and who live in rural Jamaica (Ministry of Health 2004, 133; Jamaica Social PolicyEvaluation 2003; Planning Institute of Jamaica [PIOJ] and Statistical Institute of Jamaica[STATIN] 2000:58). In an article published by Caribbean Food and Nutrition Institute, theprevalence rate of diabetes mellitus affecting Jamaicans is higher than in North America and“many European countries”. (Callender 2000:67). Diabetes Mellitus is not the only challengefaced by patients, but McCarthy (2000) argues that about 30% to 60% of diabetics also sufferfrom depression, which is a psychiatric illness. Such a situation further complicates the woes ofthe elderly as they seek to balance other psychosological conditions with the diabetes andhypertension along with the stress which is frequently associated with the illness. 35

Furthermore, in attempting to contextualize the state of the Jamaican elderly, theresearcher will provide a diagram depicting the five main causes of death by different age groupsbetween 2002 and 2004. The diagram shows that while life expectancies are increasing, thatmortality from non-communicable diseases such as heart diseases, cerebrovascular diseases anddiabetes are indeed high for the elderly and are thereby lowering their wellbeing (Figure 2.3). In 2003, data presented by the Ministry of Health Jamaica in its ‘Annual Report’ showedthat of the patients who are 65 years and older, 29.7% of them were discharged from inpatientcare because of ‘circulatory system diseases’, and nutrition and endocrine ailments accounted for12.6%. While it is true that these diseases influence physical inactivity, the conditions of copingwith these as well as the cost of care undoubtedly should be aiding to lower the wellbeing statusof these people. 70+ Other heart disease 60-69 Ischaemic 50-59 Age cohorts Homocides 40-49 Diabetes 30-39 15-29 cerebrovascu lar under 15 0 20 40 60 80 Percent dis tribution of 5 m ain caus es of deathsFigure 2.3.: Percentage distribution of 5 main causes of deaths by age: 2002-2004Source: Adopted from the Demographic Statistics, 2005, (STATIN 2006:x). Findings from studies by the Planning Institute of Jamaica show that while the generalhealth status is commendable, increases in chronic illnesses are undoubtedly eroding the quality 36

of life enjoyed by people who are 65 years and older (PIOJ and STATIN 2000:58-59; 1997:45).The report revealed that, “In 2000, the survey also demonstrated the importance of recurrent(chronic) illness as the cause of ill health among the elderly” (PIOJ and STATIN 2000:58). Howis the status of elderly within general setting of higher recurrence of chronic non-communicablediseases and their severity among senior citizens? Within the macho culture of Jamaica,generally, men do not seek preventative care because it is seen as weak. Such a position is learntfrom the culture, which states that boys should “suppress reaction to pain” (Chevannes 2001:37). State of the Elderly: Disparity in the Sexes Chevannes provided the explanation for this behaviour by men, that it is entrenched insocial learning theory. Where the young imitates the roles of society’s members through role-modeling of what constitutes acceptable and good roles which is supported by reinforcement(Chevannes 2001:17). The gender role of sexes is not limited to Jamaica or the Caribbean but astudy carried out by Ali and Muynck (2005) of street children in Pakistan found a similar genderstereotype in that nation. It was a descriptive cross-sectional study carried out during Septemberand October 2000, of 40 school-aged street children (8-14 years). The sample was substantiallymales (80%), with a mean age of 9 years (± 2 years). The methods of data collection were (i)semi-structured interviews, and (ii) a few focus group discussions. Ali and Muynck (2005)found that the sampled population would seek medical care based on severity of illnesses andfinancial situation. Another finding was that they referred to use home remedy. The reasonbeing that mild ailment is not severity enough to barr them from physical functioning, whichmean that they are okay; and so some morbidities are not for-hospital, which was so the case inNairobi slums (Taff and Chepngeno 2005:421). PIOJ and STATIN (1998) report that “The difference by gender was significant, with10.9 per cent of females reporting illness, compared with 8.5 per cent of males” (PIOJ andSTATIN 1998:45), which is the case even in 2002, that is the rate was 14.6% for females and10.4% for males, and in 2004 it was 13.6% for females and 8.9% for male (PIOJ and STATIN2006; 2003). From statement in the JSLC 2000 “Women have traditionally utilized health careservices more than men and these interactions have allowed closer monitoring and earlierdiagnosis of health conditions among women” (PIOJ and STATIN 2001:58), then this begs the 37

question – Are the aggregate data reported reflecting the views of the elderly or more so thefemales? However, what is true is that they [men] will visit health practitioners because thestates of their chronic impairments are severe. This is evident in the higher number of treatedcases in some ailments over that of females – from the hospitalization discharge rate for thepersons 65 years and over, the rate for men is 975.1 per 10, 000 compared to 817.1 per 10, 000females. (Ministry of Health 2004:75, 133). The elderly, on the other hand, are more responsiveto their ill-health and seek medical attention readily, but what about the psychological state ofthis age cohort from things such as – loss of partner, reduction in social support, fear of beingvictimized and so forth. As a result, it should not be surprising that the elderly Jamaicans seekmore medical attention than other age cohorts, which is captured in them indicating more self-reported illnesses and injuries and a higher mean number of days spent in medical care (PIOJ andSTATIN 2006; 2003; 1998). Hence, is the state of the elderly worse than that which is reportedin the JSLC? It should be noted that the data presented in all the official statistics on the healthstatus of Jamaicans are still measuring health using the old biomedical model (using reported andtreated illnesses and/or injuries) - (JSLC; MOH 2004). This approach is single focused as itomits the role environment, social exclusion, fear of crime and victimization as well asdepression, and stress among other factors as determinants of individuals’ wellbeing. Conclusion This paper responds to the underlining concerns of the continuous increase in populationageing in the world. The fast ageing of populations, unless managed in a proactive manner, couldimpose serious challenges for policy makers in the Caribbean and Jamaica. Noteworthy is that aparticular level of economic development is needed in order to deal with the challenges of thisdemographic transition. The demographic composition and structure of future world populationand subpopulation must be understood within policy framework. The challenges that are likelyto arise from an ageing population on public expenditure, on pensions and health care,particularly in the absence of reforms in pensions and health services, could lead to a build-up ofpublic debt in developing countries in specific Caribbean islands In conclusion, the graying of population is not restricted to developed societies such asJapan, Germany, Canada, China, United States and Italy to name a few, but it is a current realityfor nations like Barbados, Trinidad and Tobago and Jamaica. Currently Jamaica does not see the 38

demographic transition of ageing as an issue but come 2030 or beyond, it will be a problem formany developing states including that of Jamaica. The yardstick that is used as a symbol of the impending problem in demographic ageingis if a state’s population 60 years or over is between 8 to 10 percent and beyond. The earlysignals of demographic ageing, in Jamaica, began as early as in the 1960s, when the societybegan experiencing mortality and fertility declines. With the introduction of family planning inthe 1970s, the high fertility in the 1960s has been reduced by some 300%. Statistics reveal thatthe aged population of Jamaica is in excess of 10 percent as of 2005, within the context of anincreasing decline in the population 0 to 14 years. This population (age cohort 0-14 years) stoodat 40.3 percent in 1980 and in 25 years (2005), the population has being reduced to 31.2 percent.The conditions of ageing in Jamaica are not only a demographic issue but are disproportionatelybecoming a social, economic and political matter. In keeping with public health measure in theform of better sanitary, food and water security and quality and vaccination, mortality was cut,which is explanation for the high life expectancy of in excess of 75 years since 2004, to the bestof the researcher’s knowledge, no study has sought to examine the likely socioeconomic costs ofageing come 2015 to 2050 and beyond. Despite all the gains of technology, public health, education, lifestyle behaviouralpractices and high life expectancy, non-communicable diseases are on the rise and continue toplague people age 60 years or over. Thus, accompanying population ageing is more ill-wellsenior citizens. Within this general setting, there is a need for medical research on the wayforward in patient care as well as a demand exist for advanced quantitative assessment of themodel, which will evaluate wellbeing of the Jamaican elderly. This will foster a comprehensiveunderstanding of how health should be operationalized, and we then would be able to plan forageing in more informed manner than what presently obtains in our society. One of the socioeconomic and political challenges that the Caribbean in particularJamaica faces is the difficulty with which population ageing will become an economic cost.Population ageing does not simply mean “graying” of population (or proportionately morepersons ages 60 years or older or 65+) but with living longer comes the responsibility of payingsocial security like pension for a longer period of time. Another issue that we have failed toaddress in all of this discussion is the lowered taxes that are going to be collected as a result ofdemographic ageing. Within the same construct is the dwindling of the children population and 39

lowered fertility, which means that come 2010 and beyond the elderly dependency ratio will beincreasingly more than in previous years. These developments will mean challenges for publicbudgets, and health care expenditures. The reality is, demographic ageing is here in theCaribbean and equally so in Jamaica. Systems and structures are needed to addressing the newdemand for this age cohort, along with the biopsychosocial state of ageing. 40

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Table 2.1: Observed & Forecasted Percentage of Elderly 65 years or over in Selected Regions, and the World Countries: 1950, 1975, 2025 and 2050. 1950 1975 2007 2025 2050 % % % % %World 5.2 5.7 7.5 10.5 16.1Africa 3.2 3.1 3.4 4.2 6.7Latin America &the Caribbean 3.7 4.3 6.3 10.1 18.4Caribbean 4.5 5.4 7.8 11.4 18.9China 4.5 4.4 7.9 13.7 23.6India 3.3 3.8 5.4 8.1 14.8Japan 4.9 7.9 27.9 35.2 41.7Europe 8.2 11.4 16.1 21.0 27.6Italy 8.3 12.0 20.4 26.4 35.5Germany 9.7 14.8 19.6 23.9 25.4Sweden 10.3 15.1 17.6 22.1 24.7USA 8.3 10.5 12.4 17.7 20.6Source: United Nations, 2007 45

Table 2.2: Observed & Forecasted Percentage of Elderly 60 years or over in Selected Regions, and the World Countries: 1950, 1975, 2025 and 2050. 1950 1975 2007 2025 2050 % % % % %World 8.2 8.6 10.7 15.1 21.7Africa 5.3 5.0 5.3 6.4 10.0Latin America &the Caribbean 6.0 6.5 9.1 14.5 24.1Caribbean 6.9 8.1 11.1 16.4 24.8China 7.5 6.9 11.4 20.1 31.0India 5.6 6.2 8.1 12.0 20.7Japan 7.7 11.4 27.9 35.2 41.7Europe 12.1 16.4 21.1 28.0 34.5Italy 12.2 17.4 26.4 34.4 41.3Germany 14.6 20.4 25.3 32.1 35.0Sweden 14.9 21.0 24.1 28.3 30.9USA 12.5 14.8 17.2 23.8 26.4Source: United Nations, 2007 46

Part II: Health: An introduction 47

IntroductionThe historiographical view of health currently accounts for its transformation, products,measures and conceptualization. The contemporary conceptual of health dates back to the 1940s.In 1946, in the Preamble to its Constitution, the World Health Organization (WHO) wrote thathealth is more than the absence of diseases to physical, social and psychological wellbeing. Sucha commutative perspective of health was in response to centuries of discourse on theminimization conceptualization and how the definition of health could be widened. Thedefinition of health is important because it is a product, end and a component that is crucial tohuman existence and development. The previous definition of health was a minimized one that was developed around anarrowed perspective, the antithesis of illness. In prehistoric times (10,000 BCE), health wasviewed as endangerment of the body from outside sources, particularly spirits (in Jamaica is isreferred to as “Duppy”). Such a narrowed conceptualization guide and formulate health careservices, treatment and thinking. Simply put health and health response was primarily around thestate of the human body. This belief continued into 1800-700 BCE when it was modified fromthe prehistoric definition to the emergence of endangerment of the gods, who send disease as apunishment for human wrongdoings. During this period, the cosmology of health was aroundreligious interpretations, the epistemology of health was based on this religious cosmology. Throughout the centuries the conceptualization of health has been modified to readdisease, with less reference to god. However, the subculture of health was viewed as a gift fromgod, and that illness was a indicator of punishment. The definition of health, therefore, grew intothe absence of illness, a narrow one but this guided intervention programmes. It was during the 48

period of Galenian in Ancient Rome (130 CE – 200 CE) that health was viewed as the absence ofpathogens, such as bad air or body fluids that cause disease. This led to a mechanical approach tothe study of health and restoration of health, by extension the preservation of life. The Ancient Romains believed that health was a positive illness – meaning that the curefor disease could result in healthy bodies (humans). This perspective embodies the biomedicalmodel, the causal link between between disease and ill-health and the absence of illness andwellness. Such a viewpoint exclusively surrounds illness, the biological component, and nothealth, which heralded a mechanistic approach to studying and viewing health. The ushering ofthe biomedical approach to the study of health was a cross over of empiricism, logic,verification, reliability (consistency) and gradual development to health and health. Illness whichwas objectively measured supported a pure science approach, but excluded the other tenets thatconstitute a human. Humans are multidimensional beings, indicating that physical is a singlecomponent of whole person. People are, therefore, mind, body and social beings and anydefinition of health must constitute all these elements before we can state that we are addressingthe concerns of humans. Although the cosmology of humans is that of mind, body and social beings, thebiomedical approach to health, health study and health measurement in still dominant. Duringthe 20th century, while the biomedical model reins supreme, infectious diseases such assmallpox, yellow fever, tuberculosis, cholera and malaria ravished many lives and people wantedcures for those conditions. In response to finding cures, the association between illness anddisease was critical as this enveloped the continuation of life outside of illnesses. The infectiousdiseases accounted for low life expectancy, and providing a cure for those health conditions 49

would mean extending life and sharing all forms of development. Following the epidemiological transition from infectious diseases to chronic healthconditions (such as heart disease, hypertension, diabetes, arthritis, respiratory ailments), it begana discussion on the relevance of the biomedical model (Stone, 1987). The biomedical model wasquestioned by scholars as they sought a new paradigm that would be in keeping withmultidimensional aspect of humans. Questionning the relevance of the biomedical model, fuelledplethora of propositions that final yield a biopsychosocial model that developed by Dr. GeorgeEngel. Engel’s explanations of curing mental health was totally in keeping with the broadendefinition offered by the WHO. It was not before the 1800ss (the time of Freud in Austria, late 1800s) that health wasrecognized as being influenced by emotions and the mind. Despite this recognition by Freud,health as a long history of the predominance of a narrowed perspectives, the absence of illness,that drove the pharmacological and medical technology industries. Those industries have spentbillions of dollars on finding cures for particular ailments and health conditions, and in returnhave invested trillions of dollars on medicine, tools and approaches for addressing illness. Thepharmacological and medical technology industries have a dominance of biomedical model thatthey continue to promote as relevant inspite of its one dimensional nature in health and healthcare. This part (Part II) will explore the definitions and operationalizations of health as theywill provide the basis upon which we can understand Jamaicans’ views on health and health caredemand, provisions and allocations. 50

ReferenceBourne, P.A. (2010). Health measurement. Health 2(5):465-476.Stone, G.C. (1987). The scope of health psychology. In G.C. Stone, S.M. Weiss, J.D. Matarazzo, N.E. Miller, J. Rodin, C.D. Belar, et al. (Eds), Health psychology: A discipline and professional (pp. 27-40). Chicago: University of Chicago Press. 51

Chapter3 Health MeasurementJamaicans are not atypical in how they conceptualize health and/or how they address patientcare as the antithesis of diseases or dysfunctions (health conditions). In the 1900s and earlier,Western Societies were using the biomedical model in the measurement and treatment of health,health attitudes and the utilization of health services. This approach emphasizes sickness,dysfunction, and the identification of symptomology or medical disorders to evaluate health andhealth care. Such an approach places significance on the end (. genetic and physical conditions),instead of the multiplicity of factors that are likely to result in the existing state, or issues outsideof the space of dysfunctions. Notwithstanding the limitations of the biomedical approach, it isstill practiced by many Caribbean societies, and this is fundamentally the case in Jamaica. Thecurrent paper is an examination of health measurement, and provides at the same time arationale for the need to have a more representative model as opposed to the one-dimensionalapproach of using pathogens in measuring health. Owing to the importance of health indevelopment, patient care and its significance for other areas in society, this paper seeks tobroaden more than just the construct, as it goes to the core of modern societies in helping themto understand the constitution of health and how patient care should be treated. Thus, itprovides a platform for the adoption of the biopsychosocial model, which integrates biological,social, cultural, psychological and environmental conditions in the assessment of health and theoutcome of research, by using observational survey data.1. INTRODUCTIONThe construct of health is more than a concept. It is a “leading characteristic of the members of apopulation...” [1] and, ergo, it plays a direct role in the images of health and health care. Amongthe plethora of reasons for the importance of health are not merely the images created by theconstruct, but also its contribution to the production of different tenets of human existence –illness, morbidity, comorbidity, disability, mortality, life expectancy, wellbeing, and so on, aswell as the guide that it affords for health interactions and interventions. In addition to theaforementioned issues, it is of germane significance in aiding us to understand many of thethings that we see. The definition of this single term ‘health’ is important, as a precise use of the 52

construct fashions and connects other important applications such as growth and development,productivity, health care and people’s expectations of health care professionals. One scholar, inhelping us to understand the meaning of a construct, says that “without a well-defined construct,it is difficult to write good terms and to derive hypotheses for validation purposes” [2].Embedded in Spector’s argument is the ‘theoretical abstraction’ of the construct, and how wemay use it for outcome research. In this paper, the author will review the existing literature andidentify particular measures of health, examining how these differ from the WHO’s conceptualdefinition of health [3]. At the same time, within the limitations of the biomedical model, thestudy will evaluate the usefulness of the biopsychosocial model in health and how the image ofhealth influences the health care of people. 1.2 Image of Health Health, however, is more than a ‘theoretical abstraction’. There is an ‘objective reality’ tothis construct. It explains life, and life is an objective reality. Furthermore, health is a valuabletool that ‘drives’ health policies and influences the determinants of health care. Then there is theissue of health care and how this is planned for, as well as the role that health plays in thedevelopment of a society. Health, wellbeing and poverty are well documented in developmentaleconomics by scholars such as Amartya Sen, Paul Streeten and Martin Ravallion as havingcritical roles in understanding human development (or the lack of it). The fascination with healthand wellbeing in developmental studies is primarily because of the direct association betweendevelopment and health. Jamaica is not atypical in how its people conceptualize health and/or how they addresspatient care. In the 1900s and earlier, western societies used the biomedical approach in themeasurement and treatment of health [5]. The biomedical approach emphasizes sickness,dysfunction, pathogens, and disability and medical disorders in the construction of health. Thisapproach places importance on the outcome (or the end) instead of the multidimensionalconditions that are likely to result in the existing state. Notwithstanding the limitations of thebiomedical approach, it is still practiced by many Caribbean societies, and this is fundamentallythe case in Jamaica. This is atypical in many Western nations, as contemporary demographersstill use the antithesis of illness and disability to write about health [6-8]. Rowland wrote that“Measures of population health are of general interest to demographers, sociologists,geographers and epidemiologists. Interdisciplinary concerns here include comparing national 53

progress through the epidemiologic transition, and identifying social and spatial variations withincountries in patterns of disease and mortality” [5]. The United States has left many Caribbean societies behind in how they conceptualizehealth and treat health care. As early as the commencement of the 20th century [4], the UnitedStates shifted their focus from negative wellbeing (antithesis of diseases) to positive wellbeing.The antithesis of diseases assumes a bipolar opposite between health and diseases. Embedded inthis bipolar thinking is that for one to be healthy, he/she must not be experiencing anysymptomology of dysfunctions. Hence, the health of people is measured by mortality ormorbidity statistics. Health, however, is more than just the antithesis of diseases to positivepsychology, inclusive of socio-cultural conditions and the environment. Positive wellbeingencapsulates the biomedical model in addition to psychological, socio-cultural andenvironmental conditions. The name that Engel gave to this new approach is the biopsychosocialmodel. The current paper is a discourse on the limitation of the biomedical model, which willprovide a rationale for the need to have a more representative model as against this one-dimensional approach to the measurement of health. Traditionally, health was conceptualised as the ‘antithesis of diseases’ [4]. Using theantithesis of diseases, this construct utilizes a minimization approach or a negative perspective,adopted by western societies, which saw health as the absence of dysfunctions, morbidityconditions or comorbidity. “This definition of health has been largely the result of thedomination of the biomedical sciences by a mechanistic conception of man. Man is viewed byphysicians primarily as a physio-chemical system” [9]. With this thinking, health professionals’evaluation of patient care and diagnostic treatments is based primarily on the identification ofany symptomology of dysfunctions. Hence the standard that is used in the evaluation of health isthe established norm of any deviation from diseases. Rather than conceptualizing health andstating its determinants, this approach uses the identification of symptomology to measurehealth. Therefore, life expectancy is used here as a measure of health. This assumes that oncean individual is alive, it is because there are no dysfunctions to cause death. Embedded in thisassociation is the influence of dysfunctions on health, but there are no other determinants ofhealth except the various symptomologies of diseases. Outside of diseases, there are other determinants of health. Based on the biopsychosocialmodel that George Engel [10, 11] developed, he proposed an approach to the treatment of the 54

health care of psychiatric patients that included biological, social and psychological conditions.Such a conceptual framework, unlike the biomedical sciences, introduces and identifies factorsthat are responsible for the health, and by extension the wellbeing, of a population. One scholarcites that “the states of health and disease [are] the expressions of the success or failureexperienced by the organism in its efforts to respond adaptively to environmental changes” [12].Again, when health is defined as the antithesis of diseases its determinant is solely biological, butthis is clearly one-dimensional, and many scholars have shown that health is, in fact,multidimensional, and composed of biopsychosocial and environmental conditions. Another aspect to health is the positive association between the determinants of healthand health care policies. Health care policy makers use the determinants of health as thebenchmark that directs their planning. Therefore, when health policies are too narrow, the healthdeterminants which fashion a population’s health care will take a minimal approach, as this isbased on the image of health. One scholar puts it succinctly, “…health policies affect healththrough their effects on health determinants” [13], which speaks to the importance of ‘good’hypotheses in the schema of things. It should be noted that the hypotheses allow us to derive thepossible determinants of health, which would be used to evaluate the effectiveness of the healthpolicy, and so show how they affect health (Figure 3.1). Determinants Health Policy of Health – Health Biological conditionsFigure 3.1: The relation between health policy and health, and the roles of health determinants The goal of the policy is to decrease the incidence of chronic diseases, high risk sexual behaviour/violence and injury through the adaptation of appropriate behaviours by the population and particularly young children, adolescents and young adults [14]. The general conceptualization of health in Jamaica is the “antithesis of diseases”. Thisexplains why many people emphasize health care for morbidity conditions, genetics, or physical 55

functioning (their biology). Another indicator of the usage of this perspective can be seen in howdata are collected on health in Jamaica and/or in the wider Caribbean. Such a situation highlightsthe minimization or substantially negative approach in the construct of health. Despite the titleof the Ministry of Health’s ‘National Policy for the Promotion of Healthy Lifestyle in Jamaica’,throughout the paper the MOH [14] emphasizes mortality, diseases, dysfunctions andreproductive health, which highlights Jamaicans’ perspective on health. This is also evident inthe Planning Institute of Jamaica which is responsible for policy, along with the StatisticalInstitute of Jamaica, collecting information on health by way of (1) preventative (behaviourmodification), curative (surgical procedures, visits to health practitioners), restorative (physicalrehabilitation), and palliative (. pain management) measures, and ownership of health insurance.Thus, the hypotheses that arise from the collected data are in keeping with the narroweddefinition for which the data was initially gathered by the research design exercise. Thehypothesis of the presence of pathogens such as poor air being the cause of diseases, orclassification of ill-health, is ancient, within the context that health has been expanding frommere physical functioning for some time. This hypothesis assumes that a person who does nothave an ailment (or disease condition) is healthy, which is categorically false, as healthpsychologists have shown that psychological conditions do influence wellbeing [4]. Thisperspective dates back to Galen in Ancient Rome (. 130 CE – 200 CE). A point is even moreforcefully made in a study by two economists, which found a strong direct relationship betweenhappiness and wellbeing [15]. Other researchers found an association between ‘positive and/ornegative’ mood(s) and wellbeing [16]. This paper is in two parts, designed: (1) to providedetailed evidence that will support the rationale for an expanded concept which looks at healthand wellbeing, and (2) to illustrate the purpose and significance of the expanded model thatEngel termed the biopsychosocial model. This paper however is not arguing for abiopsychosocial hybrid model, which would include biological, economic, social, cultural,psychological and ecological conditions.2. P HYSICAL F UNCTIONING Caring for patients suffering from ill-health has a long history, which dates back to theAgrarian societies. During those earlier periods, man in his quest to address health conditionsdid so primarily from the standpoint of physical functionality. Based on the annals of time, the 56

literature showed that people would treat biological dysfunctions and sometimes the ‘spirit’ intheir pursuit of making man healthier. This approach dates back as far as ancient Rome (. 130 CE– 200 CE). Despite the WHO offering us a better way in the pursuit of happiness and wellness,man continues to return to the biomedical model of health. One of the reasons for the continuedacceptance of the use of the biomedical model is the dominance of technology in this process.As technology is still primarily intended to address physical dysfunctions and the absence ofpathogens, many studies conducted in early societies have not only linked the concept of healthto medical conditions and by extension health care, but have served as another importantindicator in determining lifespan. In 1884, an Englishman named Francis Galton who was both a mathematician andmedical doctor researched the ‘physical and mental functioning’ of some 9,000 people betweenthe ages of 5 and 80 years [17]. Galton wanted to measure the human life span in relation to thephysical and mental functioning of people, so he sponsored a health exhibition that would allowhim to collect data for analysis. Health was traditionally defined as the “antithesis of diseases”,which explains the predominance of physical functioning in policy making and health care, andjustifies Galton’s wanting data on the physical functioning of people. The 20th century has brought with it massive changes in the typologies of dysfunctions,where deaths have shifted from infectious diseases such as tuberculosis, pneumonia, yellowfever, Black Death (. Bubonic Plague), smallpox and ‘diphtheria’ to illnesses such as cancer,heart disease and diabetes [14]. Although diseases have shifted from infectious to degenerate,chronic non-communicable illnesses and science, medicine and technology have expanded sincethen, and the image of health in contemporary Jamaica still lags behind many developed nations.Morrison [18] titled an article ‘Diabetes and Hypertension: Twin Trouble’ in which heestablishes that diabetes mellitus and hypertension have now become problems in Jamaicans andin the wider Caribbean. This situation was equally corroborated by Callender [19] and Steingo[20] at the 6th International Diabetes and Hypertension Conference, which was held in Jamaica inMarch 2000. They found that there is a positive association between diabetic and hypertensivepatients - 50% of individuals with diabetes had a history of hypertension [19, 20]. Prior to thosescholars’ work, Eldemire [21] found that 34.8% of new cases of diabetes and 39.6% ofhypertension were associated with senior citizens (. ages 60 and over). Accompanying thisperiod of the ‘age of degenerative and man-made illnesses’ are life expectancies that now exceed 57

50 years. Before the establishment of the American Gerontology Association in the 1930s and theirmany scientific studies on the ageing process [17], many studies were done based on thebiomedical model, . physical functioning or illness and/or disease-causing organisms [4]. Manyofficial publications used either reported illnesses or the prevalence of seeking medical care formeasuring sicknesses. Some scholars have still not moved to the post biomedical predictors ofhealth status. The dominance of this approach is so strong and present within the twenty-firstcentury, that many doctors are still treating illnesses and sicknesses without an understanding ofthe psychosocial and economic conditions of their patients. To illustrate this more vividly, theresearcher will quote a sentiment expressed by a medical doctor in ‘The Caribbean Food andNutrition Institute’s Quarterly [22]. A public health nutritionist, Dr. Kornelia Buzina [23], says,“When used appropriately, drugs may be the single most important intervention in the care of anolder patient … and may even endanger the health of an older patient …” This propositionhighlights the paradox in biomedical sciences as well as showing the need to expand the imageof health beyond this negative approach to it. Within the context of the WHO’s definition and growing numbers of studies that haveconcluded that health should be a multidimensional construct, in 2007 a group of medicalpractitioners used physical functionality and dysfunctions to treat an elderly patient who wassuffering from a particular health condition [24]. The researchers put forward an examination ofa 74-year old man who with “...a long history of ischaemic heart disease, presented withincreasingly prolonged episodes of altered consciousness” [24]. The physicians cite theargument that “many elderly patients may have more than one cause for this symptom” [24],which summarizes their perspective and reliance on understanding medical disorders in thedispensing of patient care. Throughout the study, the scholars and medical practitioners did notseek to evaluate the psychological, social, and environmental conditions and their possibleinfluence on the current state of dysfunction of the elderly patient. Despite the seemingcomplexity of the result of the detailed inquiry into the neurological conditions of the patient,and the keen medical examination of the patient, his medical condition continued for yearsunabated. This emphasises the dominance of the biomedical model, and it goes beyond thissingle study, as a review of publications in the West Indian Medical Journal – a medical journalin Jamaica – from 1960-2009 revealed a few studies that have gone beyond the use of the 58

biomedical approach to the examination of patient care. In seeking to treat the 74-year old patient, the medical practitioners examined and re-evaluated various medical problems. Thus, owing to the thinking of this group of researchers,they used ‘multiple medications’ in the treatment of the patient’s condition. It was clear from theperspective of the scholars that what guided their intervention were the biomedical sciences (.physical functionality or dysfunctions). In this case, health is the ‘antithesis of diseases’. It isthe narrow definition of health – negative health (. biomedical approach) – which explains theimage of health and health care for those scholars and researchers. Apart from the reasons for theuse of diagnosed conditions, life expectancy and other physical issues are utilized in examininghealth, because of the precision in using them to evaluate health as against other approaches thatare more holistic and broader in scope. 2.2 Health measurement The narrow definition of health is the “antithesis of diseases” which Longest [13] says isthe “…absence of infection or the shrinking of a tumour” which can be called dysfunctions (see[1, 4]. As we mentioned earlier, the ‘antithesis of diseases’ idea dates back to Galen in AncientRome. It was widespread in the 1900s, and so medical professionals used this operationaldefinition in patient care. Another fact during this time was that technology was fashioned in thisregard, addressing solely physical dysfunctions. This definitional limitation may be a rationalefor the World Health Organization, nearing the mid-1900s, declaring that health is the “state ofcomplete physical, mental, and social wellbeing, and not merely the absence of diseases orinfirmity” [3]. It should be noted that this conceptual definition which is in the Preamble to theconstitution of the WHO which was signed in July 1946 and became functional in 1948,according to one scholar, from the Centre of Population and Development studies at HarvardUniversity, is a mouthful of sweeping generalizations. According to Bok [25], the definitionoffered by the WHO is too broad and difficult to measure, and at best it is a phantom. Otherintelligentsia point to the WHO’s definition as a difficulty for policy formulation, because itsscope is ‘too broad’ [26]. The question is “Is the conceptual definition formulated by WHO sobroad that those policies faced difficulty in formation”, and by extension should we regress to apre-1946 conceptualization of health because a construct is difficult to operationalize today?Undoubtedly, health extends beyond diseases and is tied to cultural and psychological elements, 59

personal responsibility, lifestyle, environmental and economic influences as well as qualitynutrition [27-41]. Those conditions are termed determinants of health [26]. The WHO’s perspective must have stimulated Dr. George Engel to pursue a modificationof the narrow approach to the health and health care debate. Dr. Engel was a psychiatrist whoformulated the construct called the biopyschosocial model in the 1950s. He believed that when apatient comes to a doctor, for example for a mental disorder, the problem is a symptom not onlyof actual sickness (biomedical), but also of social and psychological conditions [10, 11]. Hetherefore campaigned for years for physicians to use the biopsychosocial model for the treatmentof patients’ complaints, as there is an interrelationship between the mind, the body and theenvironment. He believed so deeply in the model, convinced that it would help in understandingsickness and providing healing, that he introduced it into the curriculum of Rochester medicalschool [42, 43]. Medical psychology and psychopathology was the course that Engel introducedinto the curriculum for first year medical students at the University of Rochester. This approachto the study and practice of medicine was a paradigm shift from the biomedical model that waspopular in the 1980s and 1990s. The Planning Institute of Jamaica and the Statistical Institute of Jamaica employ thebiomedical model in capturing the health status and/or wellbeing of the populace. This approachwas obsolete by the late 20th century, as in 1939 E.V. Cowdy, a cytologist in the United States;expanded on how ageing and health status should be studied in the future. Cowdy broadened thebiomedical model in the measurement of the health status of older adults by including social,psychological and psychiatric information in his study entitled the “Problem of Ageing” [17].The Ministry of Health [MOH] [14], however, has published a document in which it shows thathealth interfaces with biomedical, social and environmental conditions. One of the reasons putforward by the MOH to help in understanding why they arrived at the aforementioned position,was the rationale behind the explanation for the changes in the typology of diseases – that is,from infectious and communicable diseases to chronic conditions. The institution cites that this issubstantially because of the lifestyle practices of Jamaicans. One of the ironies within thedocument was in the ‘main components of the policy for the promotion of a healthy lifestyle inJamaica’, which cites that the goal of the policy was to reduce the incidence of communicableand infectious diseases, which speaks to society’s subconscious emphasis on the biomedicalmodel in conceptualizing health and its treatment. Embedded within the MOH’s 2004 60

publication are repetition and the focus on seeking to reduce physiological conditions that affectthe individual. The MOH admits, however, that health interfaces with body and environment,which is an expansion of the biomedical model, but all indications in their document point to thebiomedical science approach in the application of the policy. The institution recognized thatpsychological factors (for example, self-esteem, and resilience) play a role in influencing health,so much so that it included these within its ‘goal of the strategic approach’, but they were notsupported in the ‘broad objectives of the strategic approach’. Critical to all of this is the acceptance that the definition of health is fundamental to theconstruction of those hypotheses that are used to formulate health policies. According to Longest[13], the conceptualization of health is indeed critical to all the things that rely on its definition.Longest writes: The way in which health is conceptualized or defined in any society is important because it reflects the society’s values regarding health and how far the society might be willing to go in aiding and supporting the pursuit of health among its members [13]. In Jamaica health policies are still driven by physical functioning, which is an obsoleteapproach to addressing health and by extension wellbeing. This limited approach to health andwellbeing means that little consideration is given to other factors such as lifestyle, psychologicalstate, the environment, crime and violence, among others. This of course implies that Jamaica’shealth policy is limited in its orientation, as it is largely driven by hypotheses that supportphysical functioning. 2.3 Biomedical Approach Dr. Buzina admits that wellbeing is fundamentally a biomedical process [23]. Thisconceptual framework derives from the Newtonian approach of basic science as the onlymechanism that could garner information, and empiricism being the only apparatus to establishtruth or fact. It is still a practice and social construction that numerous scholars and medicalpractitioners [24] continue to advocate despite new findings. Simply put, many scholarships stillput forward a perspective that the absence of physical dysfunction is synonymous with wellbeing(or health, or wellness). Such a viewpoint appears to hold some dominance in contemporarysocieties, and this is a widespread image held in Jamaica. Then there are issues such as the deathof an elderly person’s life-long partner; a senior citizen taking care of his/her son/daughter whohas HIV/AIDS; an aged person not being able to afford his/her material needs; someone older 61

than 64 years who has been a victim of crime and violence and continues to be a victim; seniorswho reside in volatile areas who live with a fear of the worst happening, the inactive aged, andgenerally those who have retired with no social support, are equally sharing the same healthstatus as the elderly who have not been on medication because they are not suffering frombiomedical conditions to the extent that they need to be given drugs. Two medical doctors writing in Kaplan and Saddock’s Synopsis of Psychiatry noted thatphysicians are frequently caught in theorizing that normality is a state of health [44]. Theyargued that doctors’ definition of normality correlates with a traditional model (biomedical) thatemphasizes observable signs and symptoms. Using psychoanalytic theories, Saddock andSaddock [44] remarked that the absence of symptoms as a single factor is not sufficient for acomprehensive outlook on normality. They stated, “Accordingly, most psychoanalysts view acapacity for work and enjoyment as indicating normality…” [44]. Among the challengesassociated with this method (biomedical model), is its emphasis only on curative care. Such anapproach discounts the importance of lifestyle and preventative care. In that, health is measuredbased on experiences with illnesses and/or ailments, with limited recognition being placed onapproaches that militate against sickness and/or diseases. The biomedical approach is somewhatbiased against an understanding of multi-dimensional man, which is not in keeping with theholistic conceptualization of health as offered by the WHO. 2.4 Biopsychosocial Approach In the 1950s, George Engel, a physician, teamed with John Romano, a young psychiatrist,to develop a biopsychosocial model for inclusion in the curriculum of the University OfCincinnati College Of Medicine, which measured the health status of people. It is referred to asEngel’s biopsychosocial model. Engel’s biopsychosocial model [10, 11, 43], recognized thatpsychological and social factors coexisted along with biological factors. It was a general theoryof illness and healing, a synergy between medicine, psychiatry and the behavioural sciences [42].Therefore, from Engel’s model, wellbeing must include factors such as motivation, depression(or the lack thereof), biological conditions (such as illnesses and diseases), social systems,cultural, environmental and familial influences on the appearance and occurrence of illness. Some scholars may argue that this paper appears to believe that only quantitative studiesmay provide answers to the examination of the determinants of health. This is absolutely not so, 62

and we use a qualitative study to show people’s perception of what contributes to a particularmedical condition. In a qualitative study that uses in-depth interviews with some 17 Malaysianmen aged between 40 and 75 years old, some scholars examined the perception of these men inrelation to erectile dysfunction (ED) – the sample was a convenient one of men who weresuffering from ED and who were willing to speak about their condition. When the interviewersasked the participants about the possible causes of ED, many of them outlined biomedicalconditions such as diabetes, hypertension, medications, past injuries, ageing and then camelifestyle practices (. smoking) and psychosocial factors [45]. Embedded in this perception is therespondents’ emphasis on pathophysiological conditions in health measurement and intervention.Although the sampled respondents do believe that psychosocial factors play a role in healthstatus, it should be noted here that they did not itemize those conditions. This speaks to theconceptualization of health that these respondents have come to accept, and the fact that theybelieve that health is not limited to biomedical sciences. Using their definition of health, thestudy shows how culture plays a pivotal role in determining how men will seek health careirrespective of the nature of their condition. According to a number of demographers [46, 47], health has been conceptualized as“functioning ability”. These pundits categorized “functioning ability” as – (i) being able toprovide both personal care and independent living but having some difficulty in performing thesetasks or in getting about outside the home, (ii) having no functioning difficulties, (iii) beingunable to independently provide personal care, and finally (iv) being able to provide personalcare but not able to manage life in the home independently” [46].3.0 EXPANSION OF THE B IOMEDICAL MODEL Studies reveal that positive moods and emotions are associated with wellbeing [48] as theindividual is able to think, feel and act in ways that foster resource building and involvementwith particular goal materialization [49]. This situation is later internalized, causing theindividual to be self-confident, from which follow a series of positive attitudes that guide furtheractions [50]. Positive mood is not limited to active responses by individuals, but a study showedthat “counting one’s blessings,” “committing acts of kindness”, recognizing and using signaturestrengths, “remembering oneself at one’s best”, and “working on personal goals” all positively 63

influence wellbeing [50,51]. Happiness is not a mood that does not change with time orsituation; hence, happy people can experience negative moods [52]. Human emotions are the coalescence of not only positive conditions but also negativefactors [53]. Hence, depression, anxiety, neuroticism and pessimism are seen as a measure of thenegative psychological conditions that affect subjective wellbeing [54-56]. From Evans andcolleague [54], Harris et al. [55] and Kashdon’s monographs [56], negative psychologicalconditions affect subjective wellbeing in a negative manner (. guilt, fear, anger, disgust); and thepositive factors influence self-reported wellbeing in a direct way - this was corroborated in astudy conducted by Fromson [57]; and by other scholars [53, 58,59]. Acton and Zodda [60]aptly summarized the negative affective of subjective wellbeing in the sentence that reads“expressed emotion is detrimental to the patients recovery; it has a high correlation with relapseto many psychiatric disorders.” From the theologians’ perspective, spirituality and religiosity are critical components inthe lifespan of people. They believe that man (including woman) cannot be whole withoutreligion. With this fundamental concept, theologians theorize that man cannot be happy, or feelcomfortable without a balance between spirit and body [62]. In order to achieve a state ofpersonal happiness, or self-reported subjective wellbeing, some pundits put forward a constructthat people are fashioned in the image of God, which requires some religiosity before man can behappy or less stressed. Religion is, therefore, association with wellbeing [63-65] as well as lowmortality [66]. Religion is seen as the opiate of the people from Karl Marx’ perspective, buttheologians, on the other hand, hypothesize that religion is a coping mechanism againstunhappiness and stress. According to Kart [67], religious guidelines aid wellbeing throughrestrictive behavioural habits which are health risks, such as smoking, drinking alcohol, and evendiet. The discourse of religiosity and spirituality influencing wellbeing is well-documented[68, 69]. Researchers have sought to concretize this issue by studying the influence of religiosityon quality of life, and they have found that a positive association exists between those twophenomena [70]. They found that the relationship was even stronger for men than for women,and that this association was influenced by denominational affiliation. Graham et al.’s [71] studyfound that blood pressure for highly religious male heads of households in Evans County waslow. The findings of this research did not dissipate when controlled for age, obesity, cigarette 64

smoking, and socioeconomic status. A study of the Mormons in Utah revealed that cancer rateswere lower (by 80%) for those who adhered to Church doctrine [72, 73] than those with weakeradherence. In a study of 147 volunteer Australian males between 18 and 83 years old, Jurkovic andWalker [65] found a high stress level in non-religious as compared to religious men. Theresearchers in constructing a contextual literature quoted many studies that have made a linkbetween non-spirituality and “dryness”, which results in suicide. Even though Jurkovic andWalker’s research was primarily on spiritual wellbeing, it provides a platform that can be used inunderstanding the linkages between the psychological status of people and their generalwellbeing. In a study which looked at young adult women, the researchers found that spiritualityaffects the physical wellbeing of a populace [69]. Embedded within that study is the positiveinfluence of spirituality and religion on the health status of women. Edmondson et al.’s workconstituted of 42 female college students of which 78.8 percent were Caucasian, 13.5 percentAfrican-American, 5.8 percent Asian and 92 percent were non-smokers. Health psychologists concurred with theologians and Christians that religion influencespsychological wellbeing [74, 75]. Taylor [74] argued that religious people are more likely tocope with stressors than non-religious individuals, which explains the former’s better healthstatus. She put forward the position that this may be done through avoidance or vigilantstrategies. This response is an aversive coping mechanism in addressing serious monologue orconfrontational and traumatic events. Coping strategies, therefore, are psychological tools usedby individuals to problem-solve issues, without which they are likely to construct stressors andthreaten their own health status. Taylor [74] said that "some religious beliefs also lead to betterhealth practices", producing lower mortality rates from all cancers in Orthodox Christians.4. EVIDENCE OF USE FOR BIOPSYCHOSOCIAL MODEL Even though policy makers are cognizant of the importance of healthy lifestyle practicesand their influence on wellbeing [76], we continue to sideline them in understanding healthstatus, and using this concept in the formulating of hypotheses that will drive a broader policyfocus of health care for the populace. This is evident in our neglect to expand studies for policypurposes that collect data on health using the biopsychological model, meaning that policyformulators are emphasizing physical vulnerability or dysfunction to measure health status. Isthere a study that has sought to use a maximization definition of health that will be able to better 65

evaluate and plan for the wellbeing of Jamaicans? A study conducted in Barbados reveals that there is a statistical causal relationshipbetween socioeconomic conditions and health status. The findings revealed that 5.2% of thevariation in reported health status was explained by the traditional determinants of health(disease indicators – Table 1.1.1). Furthermore, when this was controlled for currentexperiences, the percentage fell to 3.2% (falling by 2%). When the current set of socioeconomicconditions were used they accounted for some 4.1% of the variations in health status, while 7.1%were due to lifestyle practices, compared to 33.5% that were as a result of current diseases [34].It holds that the importance placed by medical practitioners on the current illnesses – as anindicator of health status – is not unfounded as people place more value on biomedicalconditions as being responsible for their current health status. Despite this fact, it is obviousfrom the data – using 33.5% - that there are other indicators that explain some 67.5% of thereason why health status should be as it is. Furthermore, with an odds ratio of 0.55 for numberof illnesses, there is a clear suggestion that the more people reporting illnesses, the lower will betheir health status [34]; and this was equally so for more disease symptoms – odds ratio was0.71). Figure 1 above is a depiction of the use of the biopsychosocial model in the study ofhealth status. This research was conducted in Barbados between 1999 and 2000, in which healthstatus was predicted by a composite function of five general typologies of variables. The modelshows that health status is not primarily limited to biomedical conditions – such as diseases andailments – as has been the custom of many scholars. While different indicators as used by theseresearchers may not be possible in this paper because of the limitation of the secondary dataset –for example ‘current lifestyle risk factors’, ‘childhood nutrition’, ‘childhood diseases’,‘environmental factors’, to name a few – despite the data’s shortcomings, the study emphasizesthe use of a multidimensional approach in the study of wellbeing. Bourne [27], using secondary data, encapsulates George Engel’s conceptual idea of amultidimensional model which incorporates biological, social, psychological, environmental andsocial conditions in examining wellbeing. Wellbeing is operationally defined as materialresources, illness and total expenditure of households. The sample is drawn from a nationallyrepresentative survey of 25,018 Jamaicans, some 9.3% of the sample being elderly. From a 66

sample of 2,320 elderly Jamaicans (ages 65+ years), Bourne [27] found that 10 of the 14predisposing variables explain 36.8% of the variance in wellbeing. Of the 10 statisticallysignificant variables, the five most important ones, in descending order, are (1) area of residence(β=0.227), (2) cost of medical care (β=0.184), (3) psychological conditions – [total positiveaffective conditions] - (β=0.138), (4) ownership of property (β=0.135), and (5) crime (β=0.111).Among the other factors, which are the 5 least important conditions, are negative affectiveconditions, marital status, educational level, average occupancy per room, age of residents, andthe environment. Thus, whether or not we use Grossman’s model [77], Hambleton et al.’s model[34] or Bourne’s models [27-33] it is clear from them that wellbeing extends beyond biologicalconditions to include psychological, environmental, and social conditions. Another study was conducted by Bourne [30] of some 3,009 elderly Jamaicans (60 yearsand older), with an average age of 71 years and 10 months ± 8 years and 6 months, of which67% (n=2,010) resided in rural areas, 21% (n=634) dwelled in Other Towns and 12% (n=365)lived in the Kingston Metropolitan Area. The mean General Wellbeing of elderly Jamaicans waslow (3.9 out of 14 ± 2.3). Bourne’s model [30] identified 10 explanatory variables which explain40.1% (adjusted R-squared) of the variance in general wellbeing. In this study he deconstructedthe general model into (1) economic wellbeing and (2) physical wellbeing (proxy by healthconditions). Using the same set of explanatory variables, the latter model explains 3.2% of thevariability in wellbeing (proxy by health conditions) compared to 41.3% for the former model (.economic wellbeing using material economic resources). General Wellbeing was operational asmaterial resources and functional limitation (or health conditions). Material economic resourcesconstitute ownership of durable goods (such as motor vehicles, stereo, washing machines, etcetera); income (proxy by income quintile); and financial support (e.g. social security and otherpensions). Hence, it follows that the biopsychosocial model is a better proxy for wellbeing; andthat functional limitation is still not a good proxy for wellbeing as used by Hambleton et al.Grossman and even Smith and Kington [78]. Globally, regionally and especially domestically, the most popular space in researchconcerning wellbeing is the biomedical approach; its popularity is fuelled by the combination ofthe traditional operational definition of health (good physical health) and the dominance of themedical sciences in this field of enquiry. The number of studies on mortality, structuralalterations and functional declines in body systems, genetic alterations induced by exogenous 67

and endogenous factors, prevalence and incidence of diseases, and certain diseases asdeterminants of health, clearly justifies establishing leniency towards medical science in thestudy of health and health care. Engel [10, 11] accredited the biomedical model that governshealth care to the practice of pundits over the last 300 years. This model assumes thatpsychosocial processes are independent of the disease process. Engel argued for the bio-psychosocial model that it includes biological, psychological, and social factors, which is a closematch to the multi-dimensional aspect of man. With this as the base, it can be construed fromEngel’s thrust behind the biopsychosocial model that the previous model is a reductionisticmodel. Engel’s biopsychosocial model in analyzing health emphasizes both health and illness,and maintains that health and illnesses are caused by a multiplicity of factors. Engel’stheorizing, therefore, is better fitted for the definition of health coined by the World HealthOrganization. In Jamaica, only a miniscule number of studies have sought to analyze the effect of thedeath of a family member or close friend, violence, joblessness, psychological disorders andsexual abuse, on wellbeing, or social change on health, area of residence on quality of life andthe perception of ageing and its influence on health conditions. Morrison [18] alluded to atransitory shift from infectious communicable diseases to chronic non-communicable diseases asa rationale for the longevity of the Anglophone Caribbean populace. This was equally endorsedby Peña [79], the PAHO/WHO representative in Jamaica. They argued that this was not the onlyreason for the changing life expectancy. Morrison summarized this adequately, when he saidthat: Aiding this transition is not only the increased longevity being enjoyed by our islanders but also the changing lifestyle associated with improved socioeconomic conditions [18] With the post-1994 widened definition of health as put forward by the WHO, people arebecoming increasingly cognizant of the fact that socio-cultural factors such as geographicallocation, income, household size and so on, as well as several psychological factors, explainwellbeing; hence the new definition of health has coalesced biomedical variables and socio-cultural and psychological variables in the new discourse on wellbeing. Stressors may arise from within the individual or outside his/her environment. One suchexternal stressor that may affect the individual is the death of loved ones. Response to themortality of close family members may be more traumatic, depending on expectancy or non- 68

expectancy. Bereavement influences the incidence of mortality. This may result in exhaustion ofthe individuals adaptive reserve. The person’s body wears down and becomes highly vulnerableto morbidity and even death. Rice put forward a study that contradicted an association betweenbereavement and mortality. He wrote that "Fathers who lost sons in war had lower mortalityrates than those who lost son in accidents" [75]. Despite that study, Rice quoted other studies[80] that showed the impact of stress on human physiology. He argued that it is suppressionduring and after bereavement that creates the stressors, which become potent devices formortality and morbidity. Lusyne, Page and Lievens’ [81] study finds that there is an associationbetween bereavement and mortality. However, this is more likely to occur in the short-run (.during the first 6 months after the death of the spouse). As there are a number of confoundingsituations which in the long-run could offset the likelihood of mortality, such as remarriage,social support from other family members, grandchildren and so on, bereavement may notnecessarily be a constant in one’s life. Nevertheless, Lusyne, Page and Lievens affirm with otherstudies that the loss of a long-time partner may result in the death of the living spouse. Theexplanations given for this eventuality are – (i) role theory as the surviving partner may find therole played by the other partner too stressful and so (ii) may not be able to adapt to the new rolealone; this is more a male phenomenon [81]. The Planning Institute of Jamaica and Statistical Institute of Jamaica collect data on ill-health, and questions are asked based on visits to health practitioners, healers and pharmacies,injuries, ailments, ownership of health insurance, duration of the disease or illness, cost oftreatment for ailments and injuries, and mental disability. Those questions are clearly derivativesfrom the biomedical model, as they seek to address physical functioning without equallyemphasizing culture, lifestyle behaviour, depression, stress, fatigue, trust for others, perceptionof one’s position in current society and the likelihood of one’s place in the future, religiosity,time periods, HIV/AIDS of family members or the individual and how it is likely to influence thehis/her health and wellbeing, social involvement in various institutions, and issues on positiveaffective conditions. 69

5. CONCLUSION In sum, any definition of the construct of health must be multidimensional in nature.Such a definition must include (1) personal and environmental conditions, (2) social factors, (3)psychological conditions, (4) diagnosed illness, and (5) self-determination of wellbeing. If healthis solely based on illnesses (biomedical model), we would have failed in our bid to operationallydefine a construct that is comprehensive enough to encapsulate all the tenets that would captureman in his complex milieu. Health is not simply a construct. It plays a critical role in theformulation of policy for health care, and in the development of the society. Thus, if weemphasize only the biomedical approach to the study of health, its underpinnings could only besymptomology. This approach fails to capture issues outside of the mechanistic structure ofman’s conception of biomedical sciences. Concurringly if health care professionals were to useas their premise dysfunctions to indicate health, which is the deviation from the norm, this imageof health would affect policy formulation and intervention programmes which are gearedtowards this narrow conceptualization. But this approach lacks are clear characteristics outsideof illnesses that will encapsulate wellness, wellbeing, and healthy life expectancy in amultidimensional human. Thus, the biomedical model relies on illness identification to capturehealth and this fashions the health care system, which also limits health coverage outside of thisnegative view of health. This is undoubtedly suboptimal, and does not account for health. Thehealth services in the Caribbean, and in particular Jamaica, are best described as medicalservices, as they are still fundamentally structured around the biomedical model which isembedded as the image of health, and not psychosocial, economic and ecological wellbeing.Although the WHO as early as the 1940s provides a definition of health that is comprehensiveand complex, some scholars believe that it is elusive and by extension immeasurable. There aremerits to the argument of those academics, but the emphasis should not be the difficulty of howoperationalizing the construct labels it ‘elusive’. Instead the goal should have been forresearchers and academics alike to formulate a working definition of the conceptual frameworkcreated by the WHO. Thus, when Grossman in the 1970s moved away from the difficulty posedby the WHO’s conceptual framework, he developed an econometric framework that laid thefoundation for the measure of this seemingly ‘elusive’ construct. Other scholars have built onthe initial theoretical model introduced by Grossman, and Bourne in particular has added 70

psychological and environmental conditions to the already established factors of the healthmodel. The constitution of the World Health Organization (WHO) states that “Health is a stateof complete physical, mental and social well-being and not merely the absence of diseases orinfirmity”, [3]. Hence, any use of morbidity statistics, dysfunctions, sickness, diseases or ill-health to conceptualize health is limited, and by extension is a negative approach to the treatmentof this construct. Health, health care, and patient care are critical components in development, asunhealthy people will not be able to offer to the society their maximum, neither will they be ableto comparatively contribute the same to productivity and production as their healthycounterparts. Therefore, the conceptualization of health is not merely a concept but a workingproduct that affects all aspects of society. 71

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Chapter4 A conceptual framework of wellbeing in some Western nationsThe aim of this study is to examine and highlight the narrow definition of wellbeing that stillexists in some contemporary Western societies. This definition is in keeping with the biomedicalmodel that views the exposure to specific pathogens as the cause of diseases in organisms. Suchan approach began during the 130ce to 200ce in Ancient Rome, and despite the efforts of theWHO in 1946 to expand the concept, health in Caribbean societies and in particular Jamaica isstill substantially seen as the ‘absence of diseases’ or dysfunctions in the body, which is what isused to indicate wellbeing. Health and wellbeing are multidimensional constructs and so thereis a need for academics to begin vociferously working to encapsulate an operational definition ofwellbeing that can be used in the images of wellbeing and patient care. This paper presents andexamines a conceptual framework on health (or wellbeing) from a biopsychosocial perspective,as well as including an environmental perspective as this is in keeping with an expandedconceptualization of health as forwarded by the WHO in its constitution. Within the discourse,arguments will be presented on both subjective and objective measurements of wellbeing.IntroductionThe traditional view of Western Societies is that health is conceptualized as the ‘absence ofdiseases’. This approach is both narrow and negative in scope as regards health. According toone school of thought, the aforementioned conceptualization of health emphasizes the absence ofsome disease-causing pathogens, and not health (Longest, 2002; Brannon, and Feist, 2007; Rice,1998). Such a perspective is in keeping with the traditional biomedical model that views theexposure to specific pathogens as the cause of diseases in organisms. This began during 130ceto 200ce in Ancient Rome and despite the efforts of the WHO as early as 1946 to expand thisconstruct (WHO, 1948), health in Caribbean societies, in particular Jamaica, is still substantiallyviewed as the ‘absence of diseases’ or dysfunctions, with wellbeing being the opposite of thatstate. Humans are multifaceted and so any conceptualization of health that seeks to measure an 77

aspect of their existence cannot be uni-directional or bi-directional, as health, wellbeing andwellness are multidimensional, which would be in keeping with the complexities of people.Lynch (2003) opines that everything that we do, feel, think and experience interfaces with ourhealth; hence, wellbeing cannot be operationally defined solely based on functional limitationbecause of pathogens, as many events affect the quality of life outside of that space. Thus, thispaper recognizes the need for the discourse, as it will allow for a better measurement of theconcept. In addition to health measurement, this paper seeks to broaden the scope of thedeterminants of health, and in the process help policy-makers to understand this concept. In anationally representative survey of Jamaicans, using observational data on some 2,320 elderlypeople (ages 65+ years), Bourne (2007) finds 12 factors that determine the wellbeing of elderlyJamaicans. Bourne’s wellbeing model is different to that presented in many other studies, as heuses a combination of physical dysfunctions, income and material possessions to conceptualizewellbeing. Bourne’s overall model explains 40.1% of the variance in wellbeing. Again,wellbeing is influenced by more than just biological conditions. However, one scholar [Bok,2004] opined that the WHO’s operationalization of health (or wellbeing) is too broad and byextension difficult to measure. This begs the question, why have we reverted to the ancientconceptualization of wellbeing (or health) and its images to guide patient care? Hence, what arethe different discourses on wellbeing? Therefore, the paper presents and examines a conceptualframework on health (or wellbeing) from a biopsychosocial perspective, in addition to includingthe physical environment in the discourse as well as providing other images within the healthdiscourse, with the aim of aiding health outcome research and patient care.Result and Discussion Wellbeing defined The concept of health according to the WHO is multifaceted. “Health is the state ofcomplete physical, mental and social wellbeing and not merely the absence of disease orinfirmity” (WHO, 1948). From the WHO’s perspective, health status is an indicator ofwellbeing (Crisp, 2005). Wellbeing for some, therefore, is a state of happiness – positive feelingstatus and life satisfaction (Easterlin, 2003; Diener et al., 1985; Diener, 1984) satisfaction ofpreferences or desires, health or prosperity of an individual (Diener, and Suh, 1997a, b; Jones,2001; Crisp, 2005; Whang, 2006), or what psychologists refer to as positive effects. Simply put, 78

wellbeing is subjectively what is ‘good’ for each person (Crisp, 2005). It is sometimesconnected with good health. Crisp offered an explanation for this, when he said that “Whendiscussing the notion of what makes life good for the individual living that life, it is preferable touse the term ‘wellbeing’ instead of ‘happiness” (Crisp, 2005). Ergo, the term wellbeing is used interchangeably with words such as ‘happiness’, ‘lifesatisfaction’, and ‘welfare’ by a number of researchers and/or people in intelligentsia (Diener,1984; Easterlin, 2003; Veenhoven, 1993). While some scholars argue that happiness and lifesatisfaction are but a fraction of wellbeing, what is embedded in Diener and Easterlin’s usage ofthose terminologies instead of wellbeing aptly shows that, within the context of amultidisciplinary global market place in which people must operate, the quality of life thatpeople enjoy (or do not enjoy) must be understood before the goals of policy-planning anddecision-making on the desire to improve the welfare, quality of life and/or standard of living ofa people can materialize. Happiness, according to Easterlin (2003) is associated with wellbeing, and also with ill-being (for example depression, anxiety, dissatisfaction). Easterlin (2003) argued that materialresources have the capacity to improve one’s choices, comfort level, state of happiness andleisure, which militates against static wellbeing within the context that developing countries anddeveloped countries had at some point accepted the economic theory that economic wellbeingshould be measured by per capita Gross Domestic Product (GDP) – (. total monetary value ofgoods and services produced within an economy over a stated period per person). Amartya Sen,who is an economist, writes that a plethora of literature exists showing that life expectancy ispositively related to Gross National Product (GNP) per capita. (Anand and Ravallion, 1993; Sen,1989). Such a perspective implies that mortality is lower whenever an economic boom existswithin the society and that this is believed to have the potential to increase development, and byextension the standard of living. Sen, however, was quick to offer a rebuttal in that dataanalyzed have shown that some countries (. Sri Lanka, China and Costa Rica) have had reducedmortality without a corresponding increase in economic growth (Sen, 1989), and that this wasattained through other non-income factors such as education, nutrition, immunization,expenditure on public health and poverty removal. The latter factors undoubtedly require incomeresources, and so it is clear that income is unavoidably a critical component in welfare andwellbeing. Some scholars believe that economic growth and/or development is a measure of 79

welfare (Becker et al., 2004). Therefore, those studies on economic wellbeing were able to offer a plethora of answersto national governments on the health status of the people, or the wellbeing and/or illbeing oftheir citizens. No policy formulation on improving the quality of life of the citizens of aparticular space should proceed without firstly unearthing the ‘real’ determinants of wellbeing.From Crisp’s perspective (2005), wellbeing is related to health and the strength of thoseassociations, and secondly planning requires information that is made available by research. Istraditional economists’ operationalization of wellbeing still applicable in contemporary societies,knowing it to be purely objective? If happiness is a state of wellbeing, then if we were to impute depression, anxiety, stress,and illness and/or physical incapacitation, spirituality and environment within the objectivemeasurement of wellbeing, a more holistic valuation would be reached. With the inclusion ofsubjectivity conditions in the measurement of wellbeing, we come closer to an understanding ofpeople’s state of wellness, health and quality of life, as better nutrition, efficient disposal ofsewage and garbage, and a healthy lifestyle also contribute to health status (. wellbeing). Itshould be noted that the biomedical model that is objective, conceptualizes health as the absenceof diseases. This leads to the question, are any of the following diseases – (i) depression, (ii)stress, (iii) fatigue, and (iv) obsession? Hence, an issue arises, does the lack of objectivity meanit should be accepted with scepticism? In order to put forward an understanding of what constitutes wellbeing or illbeing, asystem must be instituted that will allow us to coalesce a measure that will unearth peoples’sense of the overall quality of life from either economic-welfarism (Becker et al. 2004) orpsychological theories (Diener et al., 1997; Kashdan, 2004; Diener, 2000). This must be donewith the general construct of a complex man. Economists like Smith and Kington, and Stutzerand Frey as well as Engel believe that the state of man’s wellbeing is not only influenced byhis/her biologic state, but that it is always dependent on his/her environmental, economical andsociological conditions. Some studies and academics have sought to analyze this phenomenon ina subjective manner by way of general personal happiness, self-rated wellbeing, positive moodsand emotions, agony, hopelessness, depression, and other psychosocial indicators (Arthaud-dayet al., 2005; Diener et al., 1999; Skevington et al., 1997; Diener, 1984). 80

An economist (Easterlin) studying happiness and income, of all social scientists, found anassociation between the two phenomena (Easterlin, 2001a, b), (Stutzer and Frey, 2003). Hebegan with a statement that “the relationship between happiness and income is puzzling”(Easterlin, 2001a: p. 465), and found that people with higher incomes were happier than thosewith lower incomes – he referred to it as a correlation between subjective wellbeing and income(Stutzer, and Frey, 2003). He did not cease at this juncture, but sought to justify this reality,when he said that “those with higher incomes will be better able to fulfil their aspirations, andwith other things being equal, on an average, feel better off.” (Easterlin, 2001a: p. 472).Wellbeing, therefore, can be explained outside of the welfare theory and/or purely onobjectification-objective utility (Kimball, and Willis, 2005; Stutzer, and Frey, 2003). Whereas Easterlin found a bivariate relationship between subjective wellbeing andincome, Stutzer and Frey revealed that the association is a non-linear one. They concretized theposition by offering an explanation that “In the data set for Germany, for example, the simplecorrelation is 0.11 based on 12, 979 observations” (Stutzer, and Frey, 2003). Nevertheless, fromStutzer and Frey’s findings, a position association does exist between subjective wellbeing andincome despite differences over linearity or non-linearity. The issue of wellbeing is embodied in three theories – (1) Hedonism, (2) Desire, and (3)Objective List. Using ‘evaluative hedonism’, wellbeing constitutes the greatest balance ofpleasure over pain (Crisp 2005; Whang 2006: p. 154). With this theorizing, wellbeing is justpersonal pleasantness, which postulates that the more pleasantries an individual receives, thebetter off he/she will be. The very construct of this methodology is the primary reason for acriticism of its approach (. ‘experience machine’), which gave rise to other theories. Crisp(2005), using the work of Thomas Carlyle, described the hedonistic structure of utilitarianism asthe ‘philosophy of swine’, because this concept assumes that all pleasure is on par. Hesummarized this adequately by saying that “… whether they [are] the lowest animal pleasures ofsex or the highest of aesthetic appreciation” (Crisp, 2005). The desire approach, on the other hand, is on a continuum of experienced desires. Thisis popularized by welfare economics, as economists see wellbeing as constituting the satisfactionof preference or desires (Crisp, 2005; Whang 2006: p. 154), which makes for the ranking ofpreferences and assessment by way of money. People are made better off if their current desiresare fulfilled. Despite this theory’s strengths, it has a fundamental shortcoming, the issue of 81

addiction. This is exemplified by the possible addictive nature of consuming ‘hard drugs’because of the summative pleasure it gives to the recipient. Objective list theory: This approach in measuring wellbeing lists items not merelybecause of pleasurable experiences, nor on ‘desire-satisfaction’, but states that every good thingshould be included, such as knowledge and/or friendship. It is a concept influenced by Aristotle,and “developed by Thomas Hurka (1993) as perfectionism” (Crisp, 2005). According to thisapproach, the constituent of wellbeing is an environment of perfecting human nature. What goeson an ‘objective list’ is based on the reflective judgement or intuition of a person. A criticism ofthis technique is elitism (Crisp, 2005), since an assumption of this approach is that certain thingsare good for people. Crisp (2005) provided an excellent rationale for this limitation, when hesaid that “…even if those people will not enjoy them, and do not even want them.” In the work of Arthaud-Day et al. (2005), applying structural modelling to subjectivewellbeing was found to constitute “(1) cognitive evaluations of ones life (., life satisfaction orhappiness); (2) positive affect; and (3) negative affect.” Subjective wellbeing, therefore, is theindividual’s own viewpoint. If an individual feels his/her life is going well, then we need toaccept this as the person’s reality. One of the drawbacks to this measurement is, it is notsummative, and it lacks generalizability. Studies have shown that subjective wellbeing can be measured on a community level(Bobbit et al., 2005; Lau, 2005) or on a household level (Lau, 2005; Diener 1984), whereas otherexperts have sought to use empiricism (biomedical indicators - absence of disease symptoms, lifeexpectancy; and an economic component - Gross Domestic Product per capita; welfarism -utility function). Powell (1997) in a paper entitled ‘Measures of quality of life and subjective wellbeing’argued that psychological wellbeing is a component of quality of life. He believed that thismeasurement, in particular for older people, must include Life Satisfaction Index, as thisapproach constitutes a number of items based on “cognitively based attitudes toward life ingeneral and more emotion-based judgment”(Powell, 1997). Powell addressed this in twodimensions. Where those means are relatively constant over time, and while seeking to unearthchanges in the short-run, ‘for example an intervention’, procedures that mirror changed statesmay be preferable. This can be assessed by way of a twenty-item Positive and Negative AffectSchedule or a ten-item Philadelphia Geriatric Centre Positive Affect and Negative Affect Scale 82

(Powell, 1997). In a reading entitled ‘Objective measures of wellbeing and the cooperation productionproblem’, Gaspart (1998) provided arguments that support the rationale behind theobjectification of wellbeing. His premise for objective quality of life is embedded within thedifficulty as it relates to consistency of measurement when subjectivity is the construct ofoperationalization. This approach takes precedence because an objective measurement ofconcept is of exactness as non-objectification; therefore, the former receives priority over anysubjective preferences. He claimed that for wellbeing to be comparable across individuals,population and communities, there is a need for empiricism. Gaspart discussed a number of economic theorizings (Equal Income Walrasian equilibria,objective egalitarianism, Pareto efficiency; Welfarism), which saw the paper expounding on anumber of mathematical theorems in order to quantify quality of life. Such a stance proposes ahuman predictable, rational form, from which we are able to objectify plans. The very axiomscited by Gaspart emphasized a particular set of assumptions that he used in finalizing ameasurement for wellbeing for man who is a complex social animal. The researcher points to asentence that was written by Gaspart that speaks to the difficulty of objective quality of life; hewrote, “So its objectivism is already contaminated by post-welfarism, opening the door to amixed approach, in which preferences matter as well as objective wellbeing” (Gaspart, 1998).Another group of scholars emphasized the importance of measuring wellbeing outside ofwelfarism and/or purely objectification, when they said that “Although GDP per capita is usuallyused as a proxy for the quality of life in different countries, material gain is obviously only oneof many aspects of life that enhances economic wellbeing” (Becker et al., 2004), and thatwellbeing depends on both the quality and the quantity of life lived by the individual (Easterlin,2001). This is affirmed in a study carried out by Lima and Nova (2006), which found thathappiness, general life satisfaction, social acceptance and actualizations are all directly related tothe GDP per capita for a geographic location (Lima and Nova, 2006). Even though in Europethese were found not to be causal, income provides some predictability of subjective wellbeing,and more so in poor countries than in wealthy nations. (Lima, and Nova, 2006) It should be understood that GDP per capita speaks to the market economic resources,which are produced domestically within a particular geographic space. So increased productionin goods and/or services may generate excess, which can then be exported, and vital products 83

(such as vaccination, sanitary products, vitamins, iron and other commodities) can be purchased,which are able to improve the standard of living and quality of the life of the same peoplecompared to the previous period. One scholar (Caldwell, 1999) has shown that life expectanciesare usually higher in countries with high GDP per capita, which means that income is able topurchase better quality products, which indirectly affects the length of years lived by people.This reality could explain why in economic recession, war and violence, when economic growthis lower (or even non-existent) there is a lower life expectancy. Some of the reasons for thesejustifications are government’s failure to provide for an extensive population in the form ofnutritional care, public health and health-care services. Good health is, therefore, linked toeconomic growth, which further justifies why economists use GDP per capita as an objectivevaluation of standard of living; and why income should definitely be a component in the analysisof health status. There is another twist to this discourse as a country’s GDP per capita may below, but the life expectancy is high because health care is free for the population. Despite thisfact, material living standards undoubtedly affect the health status and wellbeing of a people, aswell as the level of females’ educational attainment. Ringen (1995) in a paper entitled ‘Wellbeing, measurement, and preferences’ argued thatnon-welfarist approaches to measuring wellbeing are possible despite its subjectivity. The directapproach for wellbeing computation through the utility function according to Ringen is not abetter quantification as against the indirect method (. using social indicators). The stance takenwas purely from the vantage point that utility is a function ‘not of goods and preferences’ but ofproducts and ‘taste’. The constitution of wellbeing is based on choices. Choices are a functionof individual assets and options. With this premise, Ringen put forward arguments showing thatpeople’s choices are sometimes ‘irrational’, which is the make for the departure fromempiricism. Wellbeing can be computed from either the direct (. consumption expenditure) or theindirect (disposable income) approach (Ringen, 1995). The former is calculated usingconsumption expenditure, whereas the latter uses disposable income. Rigen noted that in orderto use income as a proxy for wellbeing, we must assume that (1) income is the only resource, and(2) all persons operate in identical market places. On the other hand, the direct approach has twokey assumptions. These are (1) what we can buy is what we can consume and (2) what we can 84

consume is an expression of wellbeing. From Rigen’s monograph, the assumptions arelimitations. In presenting potent arguments in favour of non-empiricism in the computation ofwellbeing, Ringen highlighted a number of drawbacks to welfarism. According to Ringen: Utility is not a particularly good criterion for wellbeing since it is a function not only of circumstances and preferences, but also of expectation. In the measurement of wellbeing, respect for personal preferences is best sought in non-welfarist approaches that have the quality of preference neutrality; …As soon as preferences are brought into the concept of wellbeing, it cannot but be subjective. (Ringen, 1995) The difficulties of using empiricism to quantify wellbeing have not only been put forwardby Ringen, as O’Donnell and Tait (2003) were equally forthright in arguing that there werechallenges in measuring quality of life quantitatively. O’Donnell and Tait believed that health isa primary indicator of wellbeing. Hence, self-rated health status is a highly reliable proxy ofhealth, which “successfully crosses cultural lines” (O’Donnell, and Tait, 2003). They arguedthat self-reported health status could be used, as they found that all the respondents of chronicdiseases indicated that their health was very poor. To capture the state of the quality of life of humans, we are continuously and increasinglyseeking to ascertain more advanced methods that will allow us to encapsulate a quantification ofwellbeing that is multidimensional and multifaceted (Pacione, 2003). Therefore, an operationaldefinition of wellbeing that sees the phenomenon in a single dimension such as physical health,medical perspective (Farquhar, 1995), material (Lipsey, 1999) and would have excludedindicators such as crime, education, leisure facilities, housing, social exclusion and theenvironment (Pacione 2003; Campbell et al., 1976) as well as subjective indicators, cannot be anacceptable holistic measurement of this construct. This suggests that wellbeing is not simply asingle space; and so, the traditional biomedical conceptual definitions of wellbeing exclude manyindividual satisfactions and in the process reduce the tenets of a superior coverage of quality oflife. One writer noted that the environment positively influenced quality of life (Pacione,2003) of people; in order to establish the validity and reliability of wellbeing, empirical datamust include issues relating to the environment. The quality of the environment is a utilizedcondition in explaining the elements of people’s quality of life. Air and water quality throughindustrial fumes, toxic waste, gases and other pollutants, affect environmental quality. This is 85

directly related to the maintenance or lack thereof of societal and personal wellbeing (Pacione,2003). Studies have conclusively shown that environmental issues such as industrial fumes andgases, poor solid waste management, mosquito infestation and poor housing are likely to result inphysiological conditions like respiratory track infections (for example lung infection)and asthma. According to Langlois and Anderson (2002), approximately 30 years ago, a seminalstudy conducted by Smith (1973) “proposed that wellbeing be used to refer to conditions thatapply to a population generally, while quality of life should be limited to individuals’ subjectiveassessments of their lives …” They argue that a distinction between the two variables has beenlost with time. From Langlois and Anderson’s monograph, during the 1960s and 1970s,wellbeing was approached from a quantitative assessment by the use of GDP or GNP (Becker etal., 2004), and unemployment rates; this they refer to as a “rigid approach to the (enquiry of thesubject matter) subject.” According to Langlois and Anderson (2002), the positivism approachto the methodology of wellbeing was objectification, an assessment that was highly favoured byAndrews and Withley (1976) and Campbell et al. (1976). In measuring quality of life, some writers have thought it fitting to use Gross DomesticProduct per capita (GDP per capita) to which they referred as standard of living (Lipsey, 1999;Summers, and Heston 1995). According to Summers and Heston (1995), “The index mostcommonly used until now to compare countries material wellbeing is their GDP POP .” TheUnited Nations Development Programme has expanded on the material wellbeing definition putforward primarily by economists, and has included life expectancy and educational attainment(UNDP, 2005: p. 341) as well as other social indicators (Diener, 1984; Diener, and Suh, 1997).This operational definition of wellbeing has become increasingly popular in the last twenty-fiveyears, but given the expanded definition of health as cited by the WHO, wellbeing must bemeasured in a more comprehensive manner than merely using material wellbeing as seen byeconomists. Despite the fact that quality of life extends beyond the number of years of schooling andmaterial wellbeing, generally wellbeing is substantially construed as an economic phenomenon.Embedded within this construct of a measure is the emphasis on economic resources, and wehave already established that man’s wellbeing is multifaceted. Hence, any definition of thequality of life of people cannot simply analyze spending or the creation of goods and/or services 86

that are economically exchangeable, the number of years of schooling and life expectancy, but itmust include the psychosocial conditions of the people within their natural environment. GDP is the coalesced sum of all the economic resources of people within certaintopography, so this does not capture the psychosocial state of man in attaining the valued GDP.By this approach, we may arrive at a value that is higher than in previous periods, making itseem as though people are doing very well. However, with an increase in GDP, this singlecomponent is insufficient to determine wellbeing, as the increase in GDP may be from (1) moreworking hours, (2) higher rates of pollution and environmental conditions, (3) psychologicalfatigue, (4) social exclusion, (5) human ‘burn out’, (6) reduction in freedom, (7) unhappiness, (8)chronic and acute diseases and so forth. Summers and Heston (1995) note that “However,GDP POP is an inadequate measure of countries immediate material wellbeing, even apart fromthe general practical and conceptual problems of measuring countries national outputs.”Generally, from that perspective, the measurement of quality of life is therefore highly economicand excludes the psychosocial factors, and whether quality of life extends beyond monetaryobjectification. In developing countries, Camfield (2003), in looking at wellbeing from a subjectivevantage point, notes that Diener (1984) argues that subjective wellbeing constitutes the existenceof positive emotions and the absence of negative ones within a space of general satisfaction withlife. According to Camfield (2003) and Cummins’ (1997a, b), this perspective subsumed‘subjective and objective measures of material wellbeing’ along with the absence of illnesses,efficiency, social closeness, security, place in community, and emotional wellbeing, whichimplies that “life’s satisfaction” comprehensively envelopes subjective wellbeing. Diener (2000) in an article entitled ‘Subjective Wellbeing: The Science of Happiness anda Proposal for a National Index’ theorizes that the objectification of wellbeing is embodiedwithin satisfaction of life. His points to a construct of wellbeing called happiness. He cited that: Peoples moods and emotions reflect on-line reactions to events happening to them. Each individual also makes broader judgments about his or her life as a whole, as well as about domains such as marriage and work. Thus, there are a number of separable components of SWB [subjective wellbeing]: life satisfaction (global judgments of ones life), satisfaction with important domains (e.g., work satisfaction), positive affect (experiencing many pleasant emotions and moods), and low levels of negative affect (experiencing few unpleasant emotions and moods). In the early research on SWB, 87

researchers studying the facets of happiness usually relied on only a single self-reported item to measure each construct (Diener, 2000). Diener’s theorizing on wellbeing encapsulates more than the marginalized stance of otheracademics and researchers who enlightened the discourse with economic, psychosocial, orsubjective indicators. He shows that quality of life is multifaceted, and coalescing economic,social, psychological and subjective indicators is more far-reaching in ultimately measuringwellbeing. This work shows a construct that can be used to operationalize a moremultidimensional variable, wellbeing, which widens the tenet of previous operational definitionon the subject. From the theorizing of various writers, it is clear that wellbeing ismultidimensional, multidisciplinary and multispatial. Some writers emphasize the environmentalcomponents of subject matter (Pacione, 1984; Smith, 1973), from the psychosocial aspect(Clarke et al., 2000) and from a social capital vantage point (Glaeser 2001; Putnam 1995;Woolcock 2001). Smith and Kington (1997), using H t = f (H t-1 , P m G o , Bt , MC t ED, Ā t , to conceptualise atheoretical framework for “stock of health,” noted that health in period t, Ht, is the result ofhealth preceding this period (H t-1) , medical care (MC t) , good personal health (G o) , the price ofmedical care (P m ), and bad medical care (Bt) , along with a vector of family education (ED), andall sources of household income (Ā t ). Embedded in this function is the wellbeing that anindividual enjoys (or does not enjoy) (Smith, and Kington, 1997). In seeking to operationalize wellbeing, the United Nations Development Programme(UNDP) in the Human Development Reports (1997, 2000) conceptualized human developmentas a “process of widening people’s choice as well as the level of achieved wellbeing”.Embedded within this definition is the emphasis on materialism in interpreting quality of life.From the UNDP’s Human Development (1993), the human development index (HDI) “…is anormative measure of a desirable standard of living or a measure of the level of living”, whichspeaks to the subjectivity of this valuation irrespective of the inclusion of welfarism (. grossdomestic product (GDP) per capita). The HDI constitutes adjusted educational achievement (E=a 1 * literacy + a 2 * years of schooling, where a1, = 2/3 and a2 = 1/3), life expectancy 1-e(demographic modelling) and income (W (9y) = 1/ (1 - e) * y ). The function W(y) denotes“utility or wellbeing derived from income”. This income component of the HDI is a nationalaverage (GDP per capita, which is then adjusted for income distribution (W*(y) = W(y) {1 - G}), 88

where G = Gini coefficient). In wanting to disaggregate the HDI within a country, the UNDP(1993) noted that data are not available for many countries, which limits the possibility. An economist writing on ‘objective wellbeing’ summarized the matter simply by statingthat “…one can adopt a mixed approach, in which the satisfaction of subjective preferences istaken as valuable too” (Gaspart, 1998; Cummin, 1997), which is the premise to which this paperwill adhere in keeping with this multidimensional construct, wellbeing. Wellbeing, therefore, inthe context of this paper, will be the overall health status of people, which includes access to andcontrol over material resources, environmental and psychosocial conditions, and per capitaconsumption. New Focus: Healthy Life Expectancy One of the drawbacks to the use of life expectancy is the absence of capturing ‘healthy’years of life. Traditionally, when life expectancy is measured it uses mortality data topredetermine the number of years of life that are yet to be lived by an individual, assuming thathe/she subscribes to the same mortality patterns of the group. The emphasis on this approach ison length of life, not on the quality of those lived years. The rationale why healthy lifeexpectancy is important in ageing comes against the background that age means increaseddysfunction and the unavoidable degeneration of the human body. Hence, we must seek toexamine more than just the number of years that an individual is likely to survive, and we shouldbe concerned about the quality of those years. Therefore, in attempt to capture ‘quality of livedyears’, the WHO in 1999 introduced an approach that will allow us to evaluate this, ‘disabilityadjusted life expectancy’ (DALE). DALE is not only concerned with length of years to indicatethe health and wellbeing status of an individual or a nation, but the number of years withoutdisabilities and the severity of their influence by reducing the quality of lived years. 89

DALE is a modification of the traditional ‘life expectancy’ approach in assessing health.It uses the number of years lived as an equivalent to ‘full health’. In calculating DALE, thenumber of years of ill-health is weighted based on severity. This is then subtracted from theexpected overall life expectancy to give what is referred to as years of healthy life. Embedded inthis approach is reduction in years because of numbers, and severity of dysfunctions and HIVexperienced by the individual or people within a particular socio-political geography. Having arrived at ‘healthy life expectancy’, the WHO has found that poorer countries lostmore from their ‘traditional life expectancy’ than developed nations. The reasons put forward bythe WHO are the plethora of dysfunctions and the devastating effects of some tropical diseaseslike malaria that tend to strike children and young adults. The institution found that theseaccount for a 14 percent reduction in life expectancy in poorer countries and 9 percent in moredeveloped nations (WHO, 2000b). This system is in keeping with a more holistic approach tothe measure of health and wellbeing, which this study seeks to capture. By using thebiopsychosocial model in the evaluation of the wellbeing of aged Jamaicans, we will begin tounderstand the factors that are likely to influence the quality of lived years of the elderly, and notbe satisfied with the increased length of life of the populace. The rationale behind this study isthat it will assist policy-making on health and social services, long term care and pension schemeplanning, and will aid in the understanding of future health needs and the evaluation of futurehealth programmes. Conclusion The discourse on health began centuries ago, but today the issues have a changed focusbecause of new information, and a modification in epistemology about health. In this discoursesome scholarships have used the ‘absence of diseases’ or dysfunctions as a conceptual definitionof health, and in so doing they work substantially to see health from a mechanistic approach. 90

Such an approach treats patient care from a biomedical science standpoint, and the emphasis ison the biology of the organism. The biomedical model as a study of health fails to appreciate thatlong before any ailments (or dysfunctions) appear within an organism, the socio-physical,cultural and psychological milieu would have had an impact on the quality of that organism.Thus, the use of symptomology as the identification of ill-health, and using the opposite of this toindicate health, is one-dimensional, and fails in its bid to encapsulate all the possible aspects thatinfluence the quality of life, wellbeing, and health of people. Following the clear limitations with the construct of health from the perspective of thebiomedical sciences [model], in 1946 the WHO conceptualized a definition of wellbeing that wascomposite and far reaching, and one scholar (Crisps) refers to this as an elusive dream, which isdifficult to operationalize. Although the debate continued for years, George Engel was the firstscholar and psychiatrist to map out a conceptual framework for the WHO’s new construct forhealth as a working definition that guides how he approached patient care. Engel, in the 1950s,began using what he called the biopsychosocial model in treating psychiatric patients. Hebelieved that when a patient goes to a doctor, the individual’s ailment is a complex apparatus ofdifferent tenets, and not merely the outward appearance, which is the identified symptomology.Engel proposed that the medical fraternity should commence approaching patient care from thevantage point of mind, body, and social conditions. Although some scholars and practitionersconcurred with Engel’s beliefs, and practiced this new model [biopsychosocial], and he (Engel,1978, 1977a, 1977b, 1960) got Rochester Medical School to institute this approach in thecurriculum of medical training, substantially the biomedical approach was widely practiced. Traditionally, people were socialized to use symptomology to identify ill-health and thereverse of this meant ‘health’, so much so that scientists still continue to research in thistradition. Some scholarships argue that Engel’s biopsychosocial model is but an ‘abstraction’ (ora theoretical construct), and so with the objective realities of patient care, the use of morbidity isstill the best indicator of the extent of wellbeing. Gradually, the culturalized tradition of thesupremacy of the biomedical model began to be seriously challenged in the 20th century. A group of authors claim that the United States, in the 20th century, expanded theiroperational definition of health from the traditional ‘absence of diseases’ to the biopsychosocialapproach argued by Engel (Brannon, and Feist, 2007; Engel, 1960). It was not until the 1970sthat a scholar, using empirical data, finally provided an econometric model that encapsulates 91

what Engel was arguing some 2 decades before (Grossman). Using data, Grossman (1972)showed that the health status of people in the world is influenced by both biological, and aplethora of other social conditions. He laid the foundation that has shaped the present landscapeof social science research on health, wellbeing and quality of life, so much so that a group ofscholars have used the advanced quantitative method to model happiness, which was conceptualto measuring wellbeing. Today Grossman’s model, with some modifications, is being used by some Caribbeanscholars (Bourne, 2007; Hambleton et al., 2005). Using data from Barbados, Hambleton et al.(2005) showed that health (proxy physical functioning) is a function of biological, cultural andsocial conditions. Bourne (2007), using data from Jamaica, expanded on the operationaldefinition of health (or wellbeing) from physical functionality used by Grossman and Hambletonet al. (2005) to that of a composite index which captures physical, functional and economicwellbeing (material possessions). Bourne’s work did not only add to the operational definition ofhealth, but he showed that environmental and psychological conditions in addition to socialfactors do influence health. In sum, only a few studies in the Caribbean have sought to expand the narrow definitionof health inspite of the WHO’s efforts as well as others. The narrow definition of health is stilldominant in contemporary Jamaica as well as other Caribbean nations, and this primarilyaccounts for the image of health that is held by many peoples. It is this narrow definition ofhealth that fashions the health care system, patient care, data collected on health and peoples’image of health, health care and lifestyle practices. This is not only a challenge for public healthspecialists, but for the general populace as one image of health influences his/her perception ofhealth care, lifestyle and views on preventative health. 92

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Part III: Health status: UsingHealth data 97

Chapter5 Paradoxities in self-evaluated health data in a developing countryStatistics showed that males reported fewer illnesses and greater mortality rates than females,but are outlived by approximately 6 years by their female counterparts, yet their self-rated healthstatus is the same as that of females. This study examines if there (1) Are there paradoxes inhealth disparity between the sexes in Jamaica; (2) are there an explanation for the disparityoutside of education, marital status, and area of residence? Good health status was correlatedwith self-reported illness (OR =0.23, 95% CI = 0.09-0.59); medical care-seeking behaviour (OR= 0.51, 95% CI = 0.36-0.72); age of respondents (OR = 0.96, 95% CI = 0.96-0.97), and income(OR = 1.00, 95% CI = 1.00-1.00) Self-reported illness of respondents is statistical correlatedwith sex (OR = 0.25, 95% CI = 0.10-0.62); head of household (OR = 0.33, 95% CI = 0.12-0.96); age of respondents (OR = 1.04, 95% CI = 1.01-1.07) and current good self-rated healthstatus (OR = 0.32, 95% CI = 0.12-0.84). This paper highlights that caution must be used byresearchers in interpreting self-reported health data of males.IntroductionJamaica began collecting data on the living standard of its people in 1988, and to date, statisticsshowed that females continue to report more illnesses, attend medical care more than male [1],and outlive males on average by 6 years [2]. Concurrently, a study by Hutchinson et al. [3], onthe wellbeing and life satisfaction of Jamaicans, showed that women had lower psychologicalwellbeing and life satisfaction than men, which highlights some paradoxities in the health data.However, Bourne [4] found that there was no significant statistical difference between thecurrent good health status of males and females. He however found that there was no statisticalcorrelation between medical care-seeking behaviour and sex of respondents, suggesting thatreporting more illnesses does not mean that females are any more willing to address theidentified health conditions than males. 98

A research on rural Jamaican women in the reproductive ages of 15 to 49 [5] showed79% were never married; 20% married; 90% had secondary level education; 45% poor (ie 22%below the poverty line); and 15.3% reported an illness while only 5% had health insurancecoverage. In Jamaica, poverty is a rural phenomenon (ie in 2007, 15.3% of rural individuals werebelow the poverty line compared to 4% of semi-urban Jamaicans and 6.2% of urban peoples).Males’ per capita consumption was 1.2 times more than that for females; female-headedhousehold had higher prevalence of poverty compared to male-headed household [1], it followsthat socio-demographic and economic challenges faced by females is not discounting from themliving longer than men. A study by Bourne [6] showed that elderly men in Jamaica are healthierthan their female counterparts, suggesting that longer life does not imply healthy life expectancy.Statistics showed that females are more likely to be unemployed [7]; poorer; live longer; reportmore illness; visit health care practitioners more than men; and are less healthier than men inlater life; on average more educated; yet still their health status is generally equivocal to that ofmales [8]. Examining mortality data of the sexes for aged Jamaicans, Bourne et al. [9] found thatmortality at older ages was between 115 and 120 males to 100 females. A study by Abel et al.[10] found that suicide rate for males was 9 times greater than that of females which indicatesthat mortality for males is not only greater at older ages but that this is occurring voluntarilythroughout their life span. Using secondary data of 8,373 Jamaican children (ages less than 15 years) for 2002 and2104 for 2007, Bourne [11] found that there was no significance between the sexes healthconditions; however, female children are taken to health care practitioners more than malechildren. A research of 5229 and 1394 adolescents 10 to 19 years in Jamaica, Bourne’s [12]findings showed that mortality for males were greater than that for females; a significant 99

statistical correlation existed between health conditions; but none between health conditions andage cohort of the sample. Furthermore, he found that in 2007, 96% of adolescents did not reportan illness in the past 4-weeks; 54% sought medical care; and 15% had health insurance coverage.One of the drawbacks of Bourne’s work [12] was the fact that health condition was notdisaggregated by sexes; however, invaluable information was provided that showed the lowwillingness of adolescents to seek medical care. On the contrary, a study on children showed thatwhile there is no significant difference between the health statuses of the sexes, females aresocialized to seek more medical care than male children [11] and that this continues over theirlife course [1]. The literature highlights the fact that the health status disparity does not commence inchildhood, which denotes that females longer life and males’ greater health status in later life is aparadox that must be unraveled by researchers. Interestingly to note that while the literatureexplains Hutchinson et al’s work as to why women have a lower psychological wellbeing andlife satisfaction, it does not provide an understanding for the plethora of other studies whichshowed no significant statistical difference between the general self-rated health of the sexes[4,8] and childhood [11]; the greater health status of elderly men within the context that femalesreported more illness, live longer and statistics showed that mortality at all ages is greater formales than females [2]. There is a lack of information on the paradox of health disparity betweenthe sexes in Jamaica and this research seeks to fill this gap in the literature. The current researchseeks to answer the following questions: (1) Are there paradoxes in health disparity between thesexes in Jamaica; (2) are there an explanation for the disparity outside of education, maritalstatus, and area of residence? 100

Materials and methodsDataThe current study utilized a dataset collected jointly by the Planning Institute of Jamaica and theStatistical Institute of Jamaica [13]. The survey was conducted between May and August of2007. The Jamaica Survey of Living Conditions (JSLC) which began in 1988 and it is amodification of the World Bank’s Living Standards Measurement [1, 14]. The sample size was6,783 respondents, with a non-response rate being 26.2%. The JSLC is a cross-sectional survey which used stratified random sampling techniquesto draw the sample. It is a national probability survey, and data were collected across the 14parishes of the island. The design for the JSLC was a two-stage stratified random samplingdesign where there was a Primary Sampling Unit (PSU) and a selection of dwellings from theprimary units. The PSU is an Enumeration District (ED), which constitutes a minimum of 100residences in rural areas and 150 in urban areas. An ED is an independent geographic unit thatshares a common boundary. This means that the country was grouped into strata of equal sizebased on dwellings (EDs). Based on the PSUs, a listing of all the dwellings was made, and thisbecame the sampling frame from which a Master Sample of dwelling was compiled, which inturn provided the sampling frame for the labour force. The sample was weighted to reflect thepopulation of the nation.InstrumentAn administered instrument was used to collect the data from respondents. The questionnairecovers socio-demographic variables such as education, age, consumption; and others variablesfor example social security; self-rated health status; self-reported health conditions; medical care;inventory of durable goods; living arrangements, immunization of children 0–59 months and 101

other issues. Many survey teams were sent to each parish according to the sample size. Theteams consisted of trained supervisors and field workers from the Statistical agency of Jamaica.Statistical AnalysesThe Statistical Packages for the Social Sciences - SPSS-PC for Windows version 16.0 (SPSSInc; Chicago, IL, USA) – was used to store, retrieve and analyze the data. Descriptive statisticssuch as median, mean, percentages, and standard deviation were used to provide backgroundinformation on the sample. Cross tabulations were used to examine non-metric dependent andindependent variables. Analysis of variance was used to evaluate a metric and a non-dichotomous variable. Ordinal logistic regression was used to determine socio-demographic,economic and biological correlates of health status of Jamaicans, and identify whether theeducated have a greater self-rated health status than uneducated respondents. A 95% confidenceinterval was used to examine whether a variable is statistical significant or not. There was no selection criterion used for the current study. On the other hand, for themodel, the selection criteria were based on 1) the literature; 2) low correlations, and 3) non-response rate. The correlation matrix was examined in order to ascertain if autocorrelation and/ormulticollinearity existed between variables. Based on Cohen & Holliday [15] and Cohen &Cohen [16], low (weak) correlation ranges from 0.0 to 0.39; moderate – 0.4-0.69, and strong –0.7-1.0. Any correlation that had at least a moderate value was excluded from the model in orderto reduce multicollinearity and/or autocorrelation between or among the independent variables[17-21].ModelsHealth is a multifactorial construct. This indicates that it is best explained with many variables asagainst a single factor. Health is empirically established as is determined by many factors [22- 102

37], and therefore is best established with the use of multivariate regression technique [22-37].The current study seeks to establish the socio-demographic, economic and biological correlatesof self-rated health; and self-reported illness so as to examine the paradoxes in health disparitybetween the sexes. The aforementioned construct will be tested in two econometric models.Model [1] is good self-rated health statuses and is associated with socio-demographic, economicand biological variables; and Model [2] is self-reported illness and is related to socio-demographic, economic and self-rated health status.H t =f(A i , G i ,HH i , AR i , I t , J i, lnC, lnD i , ED i, MR i , S i , HIi , lnY, CR i , MC t , SA i , Ti , ε i ) (1) where H t (. self-rated current health status in time t) is a function of age of respondents, A i ; sex of individual i, G i ; household head of individual i, HH i ; area of residence, AR i ; current self-reported illness of individual i, I t ; injuries received in the last 4 weeks by individual i, J i ; logged consumption per person per household member, lnC; logged duration of time that individual i was unable to carry out normal activities, lnD i ; Education level of individual i, ED i ; marital status of person i, MR i ; social class of person i, S i ; health insurance coverage of person i, HIi ; logged income, lnY; crowding of individual i, CRi; medical expenditure of individual i in time period t, MC t ; social assistance of individual i, SA i ; length of time living in current household by individual i, Ti ; and an error term (ie. residual error).It ,=f(A i , G i ,HH i , AR i , J i, lnC, lnD i , ED i, MR i , S i , HIi , lnY, CR i , MC t , SA i , Ti , H t , ε i ) (2) where It (. self-reported illness in last 4-weeks) is a function of age of respondents, A i ; sex of individual i, G i ; household head of individual i, HH i ; area of residence, AR i ; injuries received in the last 4 weeks by individual i, J i ; logged consumption per person per household member, lnC; logged duration of time that individual i was unable to carry out normal activities, lnD i ; Education level of individual i, ED i ; marital status of person i, 103

MR i ; social class of person i, S i ; health insurance coverage of person i, HIi ; logged income, lnY; crowding of individual i, CRi; medical expenditure of individual i in time period t, MC t ; social assistance of individual i, SA i ; length of time living in current household by individual i, Ti ; self-rated current good health status, H t ; and an error term (ie. residual error).Models [1] and [2] were modified owing to [3] and [4] owing to collinearity of consumption andincome (r ≥ 0.7) and non-response of injury (over 70%).H t =f(A i , G i ,HH i , AR i , I t , lnD i , ED i, MR i , S i , HI i , lnY, CR i , MC t , SA i , Ti , ε i ) (3)It ,=f(A i , G i ,HH i , AR i , lnD i , ED i, MR i , S i , HIi , lnY, CR i , MC t , SA i , Ti , H t , ε i ) (4)Measurement of variablesHealth in the current study is measured using (1) self-rated health status (self-rated health), and(2) self-reported illness. Self-rated health status was derived from the question “Generally, howis your health?” with the options being very good; good; fair (or moderate); poor or very poor.”The ordinal nature of this variable was kept the literature [38-40].Self-reported illness was derived from the question, “Have you had any illnesses other thaninjury? The examples are cold; diarrhoea; asthma attack, hypertension, arthritis; diabetes mellitusor any other illness? (In the past four weeks)? The options were (1) yes and (2) no. This variablewas re-coded as a binary value, where 1= yes and 0= otherwise.Self-reported diagnosed recurring illness was derived from “Is this a diagnosed recurring illness?The options were: (1) yes, cold; (2) yes, diarrhoea; (3) yes, asthma; (4) yes, diabetes mellitus; (5)yes, hypertension; (6) yes, arthritis; (7) yes, other; (8) no.Medical care-seeking behaviour was taken from the question ‘Has a health care practitioner,healer, or pharmacist being visited in the last 4 weeks?’ with there being two options Yes or No. 104

Medical care-seeking behaviour therefore was coded as a binary measure where 1=Yes and 0=otherwise.Income. Total annual expenditure was used to measure income.Social standing. Income quintile was used to measure social standing. The income quintilesranged from poorest 20% to wealthiest 20%.ResultsDemographic characteristic of sampleThe sample was 6,782 respondents: 48.7% males and 51.3 females. The mean age of the samplewas 30.0 years (SD = 21.8 years). Almost 15% reported having had an illness in the last 4weeks: 89.1% reported that the illness was diagnosed by a medical practitioner - cold (14.9%);diarrhoea (2.7%); asthma (9.5%); diabetes mellitus (12.3%); hypertension (20.6%); arthritis(5.6%) and unspecified (23.4%).Bivariate analysesThe findings showed that females were more likely to (1) be widowed (7.3% females to 2.3%males); (2) be older (mean age: 30.6 years females to 29.1 years males) – t = -2.8, P = 0.05; (3)report illness (17.5% females to 12.1% males); and (4) spend on medical expenditure (Table5.1). However, there was no significant statistical difference between the sexes (1) seekingmedical care; (2) social standing; and (3) educational levels. Tertiary level graduates were substantially more likely to be in the wealthiest class(54%), and dwelled in urban areas (63.4%). Concomitantly, they reported more illness thansecondary level respondents (9.2% tertiary to 5.4% secondary), but less than those with primaryor below level education (16.2%) (Table 5.2). 105

Table 5.3 showed significant statistical associations between (1) marital status and self-reported illness (P < 0.05); (2) area of residence and self-reported illness (P < 0.05), and (3)medical care expenditure and self-reported illness (P < 0.05). A significant statistical association between health care-seeking behaviour (in %) andsocial standing of respondents – χ2 =17.12, P = 0.002. The findings revealed that as socialstanding increases from poorest 20% to wealthiest 20%, health care-seeking behaviour (in %)increases: poorest 20%, 54.7%; poor, 63.2%; middle class, 66.4%; wealthy, 68.4%, andwealthiest 20%, 73.5%.Multivariate analysesGood health status of Jamaicans was correlated with self-reported illness (OR =0.23, 95% CI =0.09-0.59); medical care-seeking behaviour (OR = 0.51, 95% CI = 0.36-0.72); age ofrespondents (OR = 0.96, 95% CI = 0.96-0.97), and income (OR = 1.00, 95% CI = 1.00-1.00)(Table 4). The model is a good fit for the data – χ2 = 114.7, P < 0.001, Hosmer and LemeshowTest P= 0.776. Furthermore, the aforementioned variables accounted 20% of the variability ingood health status of Jamaican (R-squared = 0.20) (Table 5.4). Self-reported illness of respondents is statistically correlated with sex (OR = 0.25, 95%CI = 0.10-0.62); head of household (OR = 0.33, 95% CI = 0.12-0.96); age of respondents (OR =1.04, 95% CI = 1.01-1.07) and current good self-rated health status (OR = 0.32, 95% CI = 0.12-0.84) (Table 5). The model is a very good fit for the data – χ2 = 33.7, P < 0.001, Hosmer andLemeshow Test P = 0.766 (Table 5.5). 106

DiscussionThere are enough empirical studies that agree that there was a positive statistical correlationbetween income, education, married people, social class and health status of people. The currentstudy concurs with the literature that there is a positive association between income and healthstatus. However, this paper did not find a significant statistical correlation between education,marital status, social class and self-rated health of Jamaicans. The current work highlights anumber of disparities between the literature and this paper. Many studies have shown thatincome is strongly and positively correlated with health status [22, 24]; however, this studydisagreed with those findings as it found that income’s contribution was 1% of the explanatorypower of 20%. Furthermore, income contributed the least to current good self-rated health statusof Jamaicans. Hambleton et al. [23], using elderly Barbadians, found that self-reported illnessaccounted for the most variability in health status, which is concurred by the current study andtherefore emphasizes the secondary role that income plays in influencing health status.Concurrently, in Jamaica, medical care-seeking behaviour is not an indicator of preventative careas those who sought health care were 49% less likely to report good health; and those who didnot have an illness spent more on health care compared to those who indicated an ailment.Embedded in this finding is the concept of health that Jamaicans hold and how medical care isstill synonymous with illnesses, but that those who are not sick spent more on health care and arehealthier indicating that preventative care is being practiced by Jamaicans. Apart from these findings that emerged in the data, a number of health disparities wereidentified and some could be considered as paradoxical events. The study found that men were75% less likely to report an illness than females; however, there was no significant statisticaldifference between the health statuses of the sexes. Males reported greater income than females,yet there was no significance between their health care expenditure and health care-seeking 107

behaviour. Is it a paradox that males reported less dysfunctions; attend health care institutionsequally as females; and their health status is no better than that of females? The paradox does notcease there as males are outlived by females; experienced greater mortality at all ages thanfemales; and again indicated fewer ailments than females. Is this paradox? Comparatively, using statistics from the Ministry of Health in Jamaica (actual visits topublic hospitals), Planning Institute of Jamaica and Statistical Institute of Jamaica (ie. self-reported visits) to measure the validity of self-reported health data, in 1997, it was showed that in33.1% of Jamaicans attended public hospitals [38] compared to 32.1% who reported havingattended public hospitals. Furthermore, in 2004, 52.9% of Jamaicans visited public hospitals [38]compared to 46.8% self-reported as having visited public hospitals. When the data wasdisaggregated by sex, in 2004, actual visits for females were 69.8% compared to 65.7% self-reported; while for males actual visits were 30.2% compared to self-reported visits of 64.2%.Using curative visits from the Ministry of Health data, 33% of males visited health care facilitiesto address particular illness; however, 9% of males reported that they had an illness. Embeddedin the data are the extent to which males under-report their illnesses, which further emphasizesthe paradoxities in the health data. Self-rated health data for females is therefore highly accurate;but this is not the case for males. It was a paradox in the health data to find that males reportedfewer illnesses, experience greater mortality at all ages, and had greater income; yet their healthstatus was the same as that of males. There are clearly paradoxities in the health data between the sexes in Jamaica. If malesare under-reporting their illnesses by approximately 50%, statistics on health data are thereforefallacious; and that caution must be used in using self-reported health data for males. Thisparadox can be unraveled in the definition of health and socialization of males in Jamaica. 108

Caribbean males in particular Jamaicans are socialized to be strong, brave, and masculinity istied to strength and so justify the emphasis of physique, and strength. The converse explains whythey neglect weakness or the appearance of weakness which include illnesses. Ill-health isconceptualized as weakness and within the context of the socialization; males will not openlyspeak of illness, avoid medical care-seeking behaviour and visit health care institution on theseverity of the illness. Statistics from the Ministry of Health showed that since 2000-to-2004, femalesoutnumber males by 2 to 1 in terms of visits to health care institution [38]. However, usingreported data for the same period, the figures were: in 2000 – 57.4% males and 63.2% females;in 2001 -56.3% males and 68.2% females; in 2001 – 62.1% males and 65.3% females and 2004 –64.2% males and 65.7% females. Clearly the self-reported data are not in keeping with the actualdata; and this denotes that males are over-stating their health care visits. On the other hand, using2004 on actual visits, 69.8% of Jamaican females utilized health care facilities compared to 66%of females who reported health care visit. Within the context of over-statement of health careseeking behaviour and understatement of illness by males in Jamaica, this goes to the crux of thesocialization and its influence on health care. A Caribbean anthropologist, Chevannes [39], opined that Caribbean males suppressedresponses to pain, which justifies a low, turn out to health care facilities and higher mortalityrates. This is not atypical to Caribbean males. Ali & de Muynck [40] in examining street childrenin Pakistan found a similar gender stereotype. A descriptive cross-sectional study carried outduring September and October 2000, of 40 school-aged street children (8-14 years) showed thatseverity of illnesses and on the onset that ill-health begins to threaten financial opportunities thatmales sought medical care. Ali & de Muynck’s study therefore provides some understanding for 109

the reluctance of males seeking medical care although they have greater income. With 49% ofJamaicans being males, within the context of the socialization, this explains income’s weakcorrelation with health status. This negative emotional irresponsiveness to medical care-seekingin Jamaica is not limited to males as females are apart of the current study which found nosignificant statistical difference between them and males seeking health care. Another paradox which is embedded in health data is the fact that people who spent moreon medical care reported fewer illnesses; males reported fewer ailments; yet they are nothealthier than females. Once again the explanation for this is embodied in the socialization,negative view that Jamaicans have of health, health reporting and males unwillingness toseparate health from weakness, weakness from femininity, and how men respond to theinterviewers. There is evidence that males are under-reporting their illness in the JSLC’s cross-sectional survey, which means that self-reported health data males cannot be trusted. Theresearcher is proposing that a part of the rationale is under-statement of illnesses by males inJamaica is owing to the sex of the interviewers. Most interviewers employed by the StatisticalInstitute of Jamaica to collect data from Jamaicans are females, and within the context of notwanting to exhibit weaknesses based on the definition of health, males are understating theirillness in order to create the perception that they are strong which must exclude reporting illness.The issue appears to be extensive as statistics from the Ministry of Health for 2004 showed thatfor curative visits, females outnumber males by 2 to 1 [38]. Although the researcher was unableto ascertain the Ministry of Health Annual Report for 2007, the 2006 report showed the sameratios as for 2000 to 2004, which implies that gender is creating a noise when collecting data onmen’s health in Jamaica. 110

Is it a paradox that the educated are wealthier, have greater income and still are nothealthier than the poor with less financial resources? This is not a paradox as weak relationshipbetween health status and educational level disappear on the inclusion of income. The currentwork does show that bivariate relationship existed between education and healthier people; butthat when income and education is placed in a single model, education no longer becomessignificantly associated with good health status. The current findings concur with the literaturewhich found that when subjective wellbeing, which is a measure of subjective health, wascontrolled for income and other variables, the statistical correlation between education and healthdisappears [41-43]. Smith & Kington [4] wrote, “Good health is an outcome that people desire, and higherincome enables them to purchase more of it” which implies that (1) health can be bought and (2)those with lower income will have a lower health status. Although the literature as concurredwith this study that income is positively associated with health, income’s contribution to healthin Jamaica is weak indicating that while more income is correlated with better health status,Smith & Kington perspective must be refined as there was no significant statistical correlationbetween socio-economic class and health status. In Jamaica, there is no statistical differencebetween the health statuses of the socio-economic classes and this is equally the case whenhealth is measured using health conditions. On the other hand, there is a clear paradox in thehealth data of the current study as income is correlated with better health status, yet the wealthyclasses do not have greater health status or fewer reported illness than the lower socio-economicclasses. The rationales that account for the paradoxes that emerged from the current study arelifestyle practices of the wealthy; the acceptance of the state of the poor, and that income’s 111

contribution to health is not its purchase but it better. Marmot [44] opined that poverty isassociated with greater infant mortality, more ill-health, material and social deprivation, poorconditions, and greater inequality in occupation, employment and income inequality. Within theinequalities that favour the wealthy, income means that they can afford, purchase and buy goodwith which they need. Wilkinson [45] found a weak relationship between average income andlife expectancy in wealthy nations and Sen [46] found that increased life expectancy in Britainbetween 1901 and 1960 occurred during slow growth of per capita GDP (Gross DomesticProduct). Sen continued that the improvement in life expectancy was owing to support policiessuch as sharing of health care and limited food supply. Another found a non-linear increase inthe probability of dying with increased income [47], suggesting that income fulfills two roles (1)access to better socio-material resources, and (2) retards the positives of access to become anegative. There is a paradox in income as while wealthy Jamaicans has more income and access tomore socio-material and political resources; their health status is not greater than the under-privileged, poor and poorest 20%. Concurrently, income’s contribution to health status inJamaica is minimal and Jamaicans who seek more health care and experiencing more ill-health,it follows that affluent individuals should be encountering more illness; but this was not the casein Jamaica. Having established that health data collected from males indicate a low validity, with49% of the sample being males, it follows that paradoxities identified in the current studyhighlights the difficulties in interpreting health data in Jamaica. 112

ConclusionThere are some paradoxities in self-reported health data in Jamaica. Although some of theseparadoxities are highlighted in this paper, caution now must be used by researchers ininterpreting self-reported health data collected from males as they are clearly under-reportingillnesses and over-stating their health care seeking behaviour. Inspite of the paradoxities in thedata, self-reported health collected on females in Jamaica is of high quality. This denotes that theparadoxities within the health data have provided critical answers to males’ reluctance in visitinghealth care facilities, their unwillingness to openly speak about illnesses and the fact that theyhave concealed information on their health. Therefore a new approach is needed in solicitinginformation from males about their health status. 113

Conflict of interestThere is no conflict of interest to report.DisclaimerThe researcher would like to note that while this study 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. 114

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Table 5.1. Socio-demographic characteristic of sample by sex of respondentsCharacteristic Sex Male Female Total P % % %Educational level > 0.05Primary or below 87.9 86.6 87.3Secondary 10.5 11.0 10.8Tertiary 1.6 2.4 2.0Total 3207 3385 6592Social standing > 0.05Poorest 20% 20.3 19.3 19.8Poor 19.4 20.5 20.0Middle 19.3 20.6 19.9Wealthy 20.2 19.7 19.9Wealthiest 20% 20.9 19.9 20.4Total 3303 3479 6782Marital status < 0.05Married 24.3 22.4 23.3Never married 71.1 67.4 69.2Divorced 1.6 1.8 1.7Separated 0.7 1.0 0.9Widowed 2.3 7.3 4.9Total 2150 2384 4534Area of residenceUrban 28.5 30.4 29.5 > 0.05Semi-urban 21.4 21.6 21.4Rural 50.1 47.9 49.0Total 3303 3479 6782Medical care-seeking behaviour > 0.05Yes 62.3 67.6 65.6No 37.7 32.4 34.5Total 406 599 1005Self-reported illness < 0.05Yes 12.1 17.5 14.9No 87.9 82.5 85.1Total 3208 3381 6589Age Mean (SD) in years 29.1 (21.5) 30.6 (21.9) 29.9 (21.8) < 0.05Medical Expenditure1 Mean (SD) 9.31 (15.48) 11.19 10.46 > 0.05in US$ (36.51) (30.23)1 Rate in 2007:1US$= Ja$80.47 118

Table 5.2. Socio-demographic characteristic of sample by educational levelCharacteristic Educational level Primary Secondary Tertiary Total P % % %Social standing < 0.05Poorest 20% 20.3 19.7 3.8 19.9Poor 20.0 21.7 7.6 20.0Middle 19.4 24.5 16.0 19.9Wealthy 19.9 20.3 19.1 19.9Wealthiest 20% 20.3 13.7 53.4 20.2Total 5752 709 131 6592Marital status < 0.05Married 25.5 0.0 16.9 23.4Never married 66.1 99.7 81.5 69.1Divorced 1.9 0.0 1.5 1.7Separated 1.0 0.3 0.0 0.9Widowed 5.5 0.0 0.0 5.0Total 4048 344 130 4522Area of residence < 0.05Urban 28.8 30.0 63.4 29.6Semi-urban 22.0 19.2 16.4 21.6Rural 49.2 50.8 20.6 48.8Total 5752 709 131 6592Medical care-seeking behaviour >0.05Yes 65.7 60.0 66.7 65.5No 34.3 40.0 33.3 34.5Total 953 40 12 1005Self-reported illness < 0.05Yes 16.2 5.4 9.2 14.9No 83.8 94.6 90.8 85.1Total 5736 705 130 6571Health insurance coverage < 0.05None 79.8 83.7 57.8 79.8Private coverage 12.0 11.7 35.9 12.5Public coverage 8.2 4.6 6.3 7.7Total 5682 689 128 6499Age Mean (SD) in years 32.0 14.6 26.4 30.0 < 0.05 (22.6) (1.7) (10.6) (21.8Medical Expenditure1 Mean (SD) 10.44 12.31 5.79 10.46 >0.05in US$ (30.78) (18.73) (5.51) (30.23)1 Rate in 2007:1US$= Ja$80.47 119

Table 5.3. Socio-demographic characteristic of sample by self-reported illness Self-reported illness P Yes No Total % % %Social standing >0.05Poorest 20% 19.7 20.0 19.9Poor 18.1 20.4 20.0Middle 20.9 19.8 19.9Wealthy 20.4 19.7 19.8Wealthiest 20% 20.9 20.2 20.3Total 980 5609 6589Marital status <0.05Married 35.9 20.9 23.3Never married 46.9 73.4 69.2Divorced 3.1 1.4 1.7Separated 1.7 0.8 0.9Widowed 12.5 3.5 4.9Total 721 3801 4522Area of residence <0.05Urban 26.6 30.1 29.6Semi-urban 18.7 21.9 21.5Rural 54.7 47.9 48.9Total 980 5609 6589Medical care-seeking behaviour >0.05Yes 65.1 77.4 65.4No 34.9 22.6 34.6Total 970 31 1001Health insurance coverage <0.05None 75.3 80.6 79.8Private coverage 11.5 12.7 12.5Public coverage 13.3 6.8 7.7Total 978 5525 6503Age Mean (SD) in years 42.0 28.0 < 0.05 (27.7) (20.0)Medical Expenditure1 Mean (SD) in US$ 9.30 38.80 <0.05 (18.27) (126.09)1Rate in 2007:US$1.00 = Ja$80.47 120

Table 5.4. Stepwise Logistic Regression: Good self-rated health status by sociodemographic,economic and biological variables R-squared Variable SE P Odds ratio 95.0% C.I.Self-reported illness 0.48 0.002 0.23 0.09-0.59 0.02Medical care-seeking 0.18 0.000 0.51 0.36-0.72 0.02Age 0.01 0.000 0.97 0.96-0.97 0.15Income 0.00 0.007 1.00 1.00-1.00 0.01 Constant 0.54 0.000 16.03-2 LL = 857.3Hosmer and Lemeshow Test P = 0.776Χ2 = 114.7, P < 0.001R-squared = 0.20N=6049 (89.2%) 121

Table 5.5. Stepwise Logistic Regression: Self-reported illness by sociodemographicand biological variables R-square Variable SE P Odds ratio 95.0% C.I. Male 0.47 0.003 0.25 0.10-0.63 0.059 Head Household 0.54 0.043 0.33 0.12-0.96 0.024 Age 0.01 0.010 1.04 1.01-1.07 0.021 Good Health 0.49 0.020 0.32 0.12-0.84 0.075-2 LL = 177.7Hosmer and Lemeshow Test P = 0.766χ2 = 33.7, P < 0.001R-squared = 0.19N=6049 (89.2%) 122

Chapter6 Variations in health, illness and health care-seeking behaviour of those in the upper social hierarchies in a Caribbean societyLittle research exists in the Caribbean, and in particular Jamaica, on the upper class, and nostudy emerged from a search of the literature examining health, illness, and health care-seekingbehaviour of this group. To provide pertinent information on the upper class in regards to theirgeneral health status, illnesses, typology of illnesses, health care seeking behaviours and factorswhich determine their (1) moderate-to-very good health status, (2) illness, and (3) health careseeking behaviour in order to make available to policy specialists and public health practitionersinformation on this group, to be used as a guide in their decision making policies. The majorityof the sample stated at least good health status (83.3%), with 0.5% indicating very poor healthstatus, and 15.3% who indicated an illness in the last 4-week period. Four variables emerged asstatistically correlated with moderate-to-very good health status of those in the upper class (.second wealthy and wealthiest 20%) - Model fit χ2 = 57.54, P < 0.0001. The model explained33.2% of the variance in moderate-to-very good health status, and that the model is a good fitfor the data. Three variables emerged as statistically correlated with self-reported illness -Model fit χ2 = 1087.7, P < 0.0001. The significant variables (. health care-seeking behaviour,good health status, and marital status) accounted for 72.4% of the variability in self-reportedillness. Three variables emerged as statistically significant correlates of health care-seekers -Model fit χ2 = 995.45, P < 0.0001. The statistically significant correlates (. good health status,self-reported illness, marital status) accounted for 76.4% of the variance in health care-seekingbehaviour of the upper class. Rural residents continue to have lower moderate-to-very goodhealth status when compared to the general population, and the second wealthy and thewealthiest 20% in Jamaica. Although only 4 percent of the upper social hierarchy utilize thepublic health care system, there is still a demand for public health services for this group, and itmust be taken into account as a part of the general planning for the health care system of thecountry. 123

IntroductionStudies have long established health disparities between the poor and the wealthy classes, andthis is no different in Latin America and the Caribbean [1-17]. According to the World HealthOrganization [7], 80% of chronic illnesses were in low and middle income countries, whichillustrate the dichotomy between illness and material deprivation. The dichotomy between illnessand poverty is only limited to low-to-middle income nations, as a study in the Netherlands foundthat those who were chronically ill were more likely to be poor [15], and this was also found inother European nations [16,17]. The association between insufficient money and health is notlimited to illness, but the WHO [7] opined that 60% of global mortality is caused by chronicillness, which raised another issue, the relationship between poverty and premature mortality. Marmot [8] postulated that money makes a difference in health, infant mortality andgeneral morality. The association between income and health expands beyond the directrelationship between income and access to good physical and social milieu, good nutrition andaccess to high quality health care services, to the indirect association between income and healththrough access to education, employment, material resources and occupational class. Clearlythere are inequalities in health between those in the upper class and those in the lower class [18,19], but limited studies existed on the wealthy and the wealthiest 20% in nations. In keepingwith public health aims, many studies have been carried out on the poor; poverty and illness;poverty and productivity; chronic illness, capabilities and poverty, but what about the secondwealthy and the wealthiest 20% in regard to their health, illness, health care-seeking behaviourand factors which influence health, illness and health care-seeking behaviour? Public health is about improvements in the health conditions of all members of a societyand not just a particular group. Embedded in the mandate of public health is the access to 124

information which will guide policy formulation, intervention and health education programmes,and so information is equally needed on the affluent groups. Limited information, if any, existsin the Caribbean on the health of the second wealthy and wealthiest 20% classes. While generalstatistics indicate that the upper class has a greater health status and more access to materialresources than the poor class, the former group constitutes a percentage of the population andmust be studied like the poor class. The current study revealed that the prevalence rate of theupper class utilizing public health care facilities (hospitals and health centres) was 4%,suggesting that this group must be planned for, as they utilize and demand public health careresources like other social classes. Concurringly, this research showed that 3% of those in thewealthy social class had chronic illnesses, and that 1% had diabetes mellitus, which denotes thatpublic health must make available resources for this group. Within the context that the uppersocial class utilizes public health care resources, it is surprising that no studies exist in Jamaicathat have examined health, illness, and the health care seeking-behaviour of this social group. The current study aims to provide pertinent information on the upper class in regards totheir general health status, illness, typology of illness, health care seeking behaviours and factorswhich determine their (1) moderate-to-very good health status, (2) illness, and (3) health careseeking behaviour, in order to make available to policy specialists and public health practitionersinformation on this group, which will serve as a guide for their decision-making policies.Methods and materialsSampleA sample of 2,734 respondents from the wealthiest 20% and second wealthy social hierarchywas extracted from a cross-sectional survey of 6,783 respondents: 50.5% in the wealthiest 20%and 49.5% in the second wealthy group. The survey was carried out jointly by the Planning 125

Institute of Jamaica and the Statistical Institute of Jamaica [20]. The method of selection of thesample from each survey was based solely on rural residence. The survey (Jamaica Survey ofLiving Conditions) was begun in 1989, collecting data from Jamaicans in order to assessgovernment policies. Each year since 1989, the JSLC has added a new module in order toexamine that phenomenon which is critical within the nation. In 2002, the foci were on 1) socialsafety net and 2) crime and victimization; while for 2007, there was no focus. The current samplewas extracted from the 2007 dataset. 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), whichis composed of a minimum of 100 residences in rural areas and 150 in urban areas. An ED is anindependent geographical 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 ofdwellings 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 [20]. The sample wasweighted to reflect the general population of the nation. The JSLC 2007 [20] was conducted in May and August of that year. An administeredquestionnaire was used to collect the data, which were stored and analyzed using SPSS forWindows 16.0 (SPSS Inc; Chicago, IL, USA). The questionnaire was modelled on the WorldBank’s Living Standards Measurement Study (LSMS) household survey. There are somemodifications to the LSMS, as the JSLC is more focused on policy impacts. The questionnairecovered areas such as socio-demographic variables, for example education, daily expenses (for 126

the past 7-day period), food and other consumption expenditures, inventory of durable goods,health variables, crime and victimization, social safety net, and anthropometry. Thequestionnaire contains standardized items such as socio-demographic variables, excluding crimeand victimization, which were added in 2002 and later removed from the instrument, with theexception of a few new modules each year. The non-response rate for the survey for 2007 was27.7%. The non-response includes refusals and cases rejected in data cleaning.MeasuresSelf-rated health status: is measured using people’s self-rating of their overall health status [21],which ranges from excellent to poor. The question that was asked in the survey was “How isyour health in general?” And the options were very good; good; fair; poor and very poor. For thepurpose of the model in this study, self-rated health was coded as a binary variable (1= good, 0 =Otherwise) [21-28]. The binary good health status was used as the dependent variable.Self-reported illness (or self-reported dysfunction): The question was asked: “Is this a diagnosedrecurring illness?” The answering options are: Yes, Influenza; Yes, Diarrhoea; Yes, Respiratorydiseases; Yes, Diabetes; Yes, Hypertension; Yes, Arthritis; Yes, Other; and No. A binaryvariable was later created from this construct (1=no 0=otherwise) in order to be applied in thelogistic regression.Age is a continuous variable which is the number of years alive since birth (using last birthday).Age groups were classified as children, young adults, other adults, young-old (or young-elderly),old-old, and oldest-old: children – 0 to 14 years; young adults – 15 to 30 years; other adults – 31to 59 years; young-old – 60 to 74 years; old-old - 75 – 84 years and oldest-old – 85+ years.Medical care-seeking behaviour was taken from the question ‘Has a health care practitioner orpharmacist been visited in the last 4 weeks?’ with there being two options: Yes or No. Medical 127

care-seeking behaviour therefore was coded as a binary measure where 1= Yes and 0 =otherwise.Crowding is the total number of individuals in the household divided by the number of rooms(excluding kitchen, verandah and bathroom).Sex: This is a binary variable where 1= male and 0 = otherwise.Social supports (or networks) denote different social networks with which the individual isinvolved (1 = membership of and/or visits to civic organizations, or having friends who visitone’s home or with whom one is able to network, 0 = otherwise).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 t-test and an Analysis of Variance (ANOVA)were used to test the relationships between metric and/or dichotomous and non-dichotomouscategorical variables. Box-plots were used to examine what was happening among age, self-reported illness, and social hierarchy as well as age, typology of illness and social hierarchy (.poorest 20% and wealthiest 20%). Multiple logistic regression techniques were conducted toidentify parameters and their estimates. Stepwise logistic regression technique was used todetermine the contribution of each significant determinant to the model. A p-value less than 0.05(two-tailed) was selected to indicate statistical significance (. 95% confidence interval). 128

ResultsTable 6.1 presents information on the socio-demographic characteristics of the sample. Onepercent of the sample reported an injury. Of those who reported an injury, 67.9% stipulated theinjury experienced in the last 4weeks. Domestic accidents and incidents accounted for 47.3% ofthe injuries experienced. Fifteen percent of the sample indicated an illness in the last 4 weeks. Ofthose who reported an illness, 89.1% stipulated the typology of the health condition. When the respondents were asked if they had purchased the prescribed medication,67.7% said yes. Of those who did not purchase the medication, 9.5% claimed they were unableto afford it; 39.7% said they were not ill enough; 27.6% remarked that they used a home remedy;5.2% indicated that they did not have the time and 18.1% stated other. Seventy-one percent ofthe sample sought medical care in the last 4weeks, 32.5% had health insurance coverage (23.7%private). The majority of the sample stated at least good health status (83.3%), with 0.5%indicating very poor health status. Of the sample, only 10.6% indicated where the medical visit took place in the last4weeks. Of those who responded (n=288), 27.4% indicated a public hospital, 61.8% said aprivate health care centre and 12.5% remarked that it was a public health care centre. Twenty-nine percent of those who responded to typology of medical facility used in the last 4weeks hadchronic conditions and attended a public facility. The prevalence rate of the upper class utilizingpublic health care facilities (hospitals and health centres) was 4% (3% had a chronic illness; ofthe 3%, 1% had diabetes mellitus). There was no significant statistical association between marital status and socialhierarchy (second wealthy or wealthiest 20%) – χ2 = 8.518, P = 0.744. 129

Table 6.2 shows information on particular variables and social hierarchy. A significantstatistical relationship existed between area of residence and social hierarchy. Those in thewealthiest 20% were more likely to be urban dwellers (48.6%) than those in the second wealthysocial group (36.9%) - χ2 = 57.002, P < 0.0001. Rural dwellers were more likely to be wealthy (59.1%) compared to semi-urban residents(50.1%) and urban respondents (42.1%). Concurringly, urban settlers were more likely to be inthe wealthiest 20% (57.9%) compared to semi-urban (49.9%) and rural respondents (40.9%) – P< 0.0001. There was a significant statistical association between educational level and socialhierarchy (χ2 = 30.53, P < 0.0001). Those in the wealthiest 20% were more likely to be educatedat the tertiary level (5.3%), as compared to those in the second wealthy social group (1.9%).Likewise there was a statistical relationship between health insurance coverage and socialhierarchy (χ2 = 113.27, P < 0.0001). Forty-two percent of those in the wealthiest 20% had healthinsurance coverage compared to 22.6% of those in the second wealthy social group. There were significant statistical differences between those in the wealthy and thewealthiest 20% (1) age ( t = - 4.745, P < 0.001) – mean age of the wealthy 30.14 ± 21.1, and thewealthiest 20% 33.9 ± 20.4; (2) crowding (t = 15.991, P < 0.0001 – mean household crowdingfor those in the wealthy group was 4.2 ± 2.2 compared to 3.0 ± 1.6 for those in the wealthiest20%, and (3) total expenditure (t = - 16.219, P < 0.0001) – mean total expenditure for those inthe wealthy group was USD 9,713.00 ± USD 5,327.88 and those in the wealthiest 20% was USD14,915.29 ± USD 10,550.99. Furthermore, there was a significant statistical difference betweenmean duration of illness of those in the second wealthy social group (23.8 days ± 96) and thosein the wealthiest 20% (9.9 days ± 18.7) – t = 1.985, P = 0.048; but none between duration of 130

marriage and social hierarchy (wealthy, 16.7 years ± 14.6; wealthiest 20%, 17.3 ± 13.6) – t = -0.593, P = 0.553.Multivariate analysesTable 6.3 shows information on particular variables that are correlated (or not) with self-reportedmoderate-to-very good health status of the sample. Four variables emerged as statisticallycorrelated with moderate-to-very good health status of those in the upper class (. second wealthyand wealthiest 20%) - Model fit χ2 = 57.54, P < 0.0001. The model explained 33.2% of thevariance in moderate-to-very good health status, and the model is a good fit for the data (Hosmerand Lemeshow goodness of fit χ2 = 2.87, P = 0.94, -2LL = 194.22). Eighty-one percent of thedata were correctly classified: 94.9% of those who had indicated moderate-to-very good healthstatus and 33.3% of those that were classified into poor and very poor health status. Table 6.4 presents information on variables that either correlated or did not correlate withself-reported illness of the sample. Three variables emerged as statistically correlated with self-reported illness - Model fit χ2 = 1087.7, P < 0.0001. The significant variables (health care-seeking behaviour, good health status, and marital status) accounted for 72.4% of the variabilityin self-reported illness. The model is a good fit for the data (Hosmer and Lemeshow goodness offit χ2 = 8.11, P = 0.42, -2LL = 649.69). Ninety-five percent of the data were correctly classified:72.2% of those who were classified as having an illness and 99.6% of those who did not reportan illness. Table 5 displays variables that seek to explain the variability in self-reported health care-seeking behaviour of the sample. Three variables emerged as statistically significant correlates ofhealth care-seekers - Model fit χ2 = 995.45, P < 0.0001. The statistically significant correlates (. 131

good health status, self-reported illness, marital status) accounted for 76.4% of the variance inhealth care-seeking behaviour of the upper class. The model was a good fit for the data - Hosmerand Lemeshow goodness of fit χ2 = 3.64, P = 0.90. Ninety-five percent of the data were correctlyclassified: 96.2% of those who had selected seeking medical care in the last 4 weeks and 95.3%of those who did not seek medical care.DiscussionThe present work revealed that 88 out of every 100 respondents in the upper class in Jamaicaindicated that their health status was at least good, with only 5 in every 1,000 experiencing verypoor health statuses. One in every 100 had an injury and 15 per 100 had an illness in the last 4-week period. The prevalence rate of self-reported diagnosed acute health conditions was 36 per1,000 and 96 per 1,000 for chronic conditions. Twenty-four per 1,000 had diabetes mellitus; 28out of every 1,000 had hypertension and 7 per 1,000 reported having been diagnosed witharthritis. Seventy-one percent sought medical care; there was no significant statistical associationbetween (1) self-reported injury and being second wealthy or in the wealthiest 20% as well as (2)between self-reported illness and social hierarchy (second wealthy or wealthiest 20%). The meanlength of time experiencing the current illness (in days) was greater for those in the secondwealthy class, as compared to those in the wealthiest 20%. Although only 1% of the samplereported an injury in the study, 47.3% of the injuries were owing to domestic accidents anddomestic incidents, and 21.1% were due to motor vehicle accidents. Four percent of the sampleutilized public health care facilities for their last medical visit, and 11.8% of the sample wereelderly (ages 60 years and beyond), 24.6% children (ages less than 15 years); 49.6% of those inthe wealthiest 20% dwelled in urban areas compared to 36.9% of those in the second wealthysocial group. Those in the wealthiest 20%, according to average total expenditure, were 1.5 times 132

more than those in the second wealthy class and they were 2.9 times more educated at the tertiarylevel. Concurringly, rural upper class respondents had the lowest moderate-to-very good healthstatus; those with good health status were 48% less likely to seek medical care; those withillnesses were 449 times more likely to seek medical care, and married upper class respondentswere 45% less likely to seek health care, while married wealthy residents were 2.3 times morelikely to report an illness. Marmot [8] asked the question “Does money matter for health? If so, why?” and opinedthat it does in terms of access to good nutrition, material resources, lower infant mortality, healthcare choices, and a good physical environment compared to those in the lower socioeconomicgroup. Clearly there are differences in health outcomes between the social hierarchies [1-17], butdoes money matter for health between the second wealthy and the wealthiest 20%? The currentstudy found that money does not matter for health between the wealthy and the wealthiest 20%.Money does not matter for the general health status of the wealthy and the wealthiest 20%, butalso for self-reported injuries and illnesses (both acute and chronic conditions). Embedded in thisfinding is the reality that there is a basic amount of money necessary, and any more than that willnot improve the health of the individual. This work showed that those in the wealthiest 20% onaverage spent almost 2 times more than those in the second wealthy class, and are about 3 timesmore educated at the tertiary level, but this does not produce additional improvements in healthfor the wealthiest 20%. The present paper found that a large health disparity occurred between upper classrespondents and geographic area of residents, which concurs with the findings of Vila et al.’swork. Vila et al.’s research [9] used self-reported health status (. fair-to-poor health status) andfound that lower socioeconomic class residents of Milwakee had the greatest fair-to-poor health 133

status with those in the upper class indicated the least fair-to-poor health status. Concurringly,they also found that upper socioeconomic group had the greatest health in the city, which wasdifferent in this research. In this study, upper socioeconomic group who resided in semi-urbanareas were the healthiest, and had lower total annual expenditure than those upper classrespondents who lived in urban areas. The huge health disparity was found between the upperclass rural and semi-urban dwellers, suggesting that lifestyle practices in semi-urban geographicareas was greatest and was remarkably different from that of upper class rural respondents. However, the health disparity is among those who dwell in particular geographical areas,and those who have health insurance coverage, and not between the wealthy and the wealthiest20%. Rural upper class Jamaicans had the least moderate-to-very good health status. This healthdisparity is substantial as upper class semi-urban residents were 4.8 times more likely to reportmoderate-to-very good health status, and those who dwelled in urban areas were 4.3 times morelikely to report moderate-to-very good health status compared to those in the rural areas. Suchinequality in health emphasized that the lifestyle of rural residents is such that money does notequate their health status with those of their other wealthy urban and semi-urban peers. This isembedded in the present work as there is no significant statistical correlation between self-reported illness and area of residence, or area of residence and health care seeking behaviour ofthe upper class. It follows that it is not money and illness that separate the rural from the otheraffluent respondents, but this must be therefore embedded in the cultural differences betweenpeople. Another finding which emerged from the current research is the fact that married upperclass respondents reported more illness than those who were never married, yet the former groupsought less medical attention than the latter group. Although married upper class respondentsreported more illness, there was no statistical correlation between marital status and moderate-to- 134

very good health status. A plethora of studies have examined the health status of married andnon-married respondents and the verdict is that the former group’s health status is greater [29-35], which means that money removes this health disparity. According to Moore et al. [35], people who reside with a spouse have a different base ofsupport which aids in better health choices and justifies greater health status, as against thosewithout social support from a marital union. This was also found in earlier studies by Smith andWaitzman [31] and Lillard and Panis [34]. Cohen and Wills [36] found that perceived supportfrom one’s spouse increased well-being, while Ganster et al. [37] reported that support fromsupervisors, family members and friends was related to low health complaints. Another studyfound that being married was a ‘good’ cause for an increase in psychological and subjectivewell-being in old age [38]. Smith and Waitzman [31] offered the explanation that wives werelikely to dissuade their husbands from particular risky behaviours such as the use of alcohol anddrugs, and would ensure that they maintained a strict medical regimen coupled with propereating habits. On the contrary, this paper revealed that married affluent Jamaicans were morelikely to report illness, as compared to never-married wealthy respondents, but that this does nottranslate into better health status for one group over the other. Using the relationship of the absence of illness to health of the wealthy-to-wealthiest 20%of Jamaicans, this should denote that the wealthiest should be healthier than the second wealthy.Clearly, there is a cognitive disparity between the image of health and illness. Illness is wellestablished to be a narrow approach to the conceptualization of health [39-46], and this is whatemerged as the case for the upper class. According to the WHO [39], health is social,psychological and physical wellbeing and not merely the absence of illness. Clearly upper classrespondents subscribe to this conceptualization as experiencing illness was correlated with low 135

moderate-to-very good health status, but illness was not a factor which determines the moderate-to-very good health status of those in the upper class. Ferrer and Palmer’s work [14] revealed marginal health variabilities between thosepeople in the second wealthy and the wealthiest 20%, and using self-reported to measure healthstatus, this study found no statistical association between self-reported health and the two socialhierarchies. The present work goes further than Ferrer and Palmer’s research that used healthstatus and investigated general illness and particular health conditions and those in the secondwealthy and the wealthiest 20%. Ferrer and Palmer’s research did not examine illness orparticular typology of illness. Statistics revealed that 15.5% of Jamaicans reported an illness inthe last 4weeks in 2007 [47] compared to 15.3% of those in the upper class. Seemingly there isno difference between self-reported illness in the population and those in the upper class, butfurther examination of the diagnosed health conditions revealed some differences between thepopulation and the subpopulation. For the population, the prevalence rates for people withasthma were 87 per 1,000; diabetes mellitus, 120 per 1,000; hypertension, 224 per 1,000 andarthritis, 88 per 1,000 [47] compared to those in the upper class, being asthma, 12 per 1,000;diabetes mellitus, 24 per 1,000; hypertension, 28 per 1,000 and arthritis, 7 per 1,000. Thefindings of this study highlight that those in the affluent social hierarchy have a lower prevalenceof chronic illness than people in the general population of Jamaica, which concurs with theliterature that those in the lower socioeconomic group were more likely to experience morechronic illness than the affluent. Although those in the wealthy-to-wealthiest 20% group inJamaica had a lower prevalence of chronic health conditions compared to the general population,they had a prevalence rate of 37 per 1,000 for other health conditions. The other conditions constitute ailments such as prostate and breast cancers, ischemic 136

heart disease, malignant neoplasm of the trachea, bronchus and other heart diseases. Statistics onthe mortality of males 5 years and older revealed that cerebro-vascular diseases, diabetesmellitus, ischemic heart diseases, malignant neoplasm of the prostate, hypertensive disease,chronic lower respiratory infections, other heart diseases and malignant neoplasm of the tracheaand HIV were among the 10 leading causes of death [48]. For females 5 years and older it wasabout the same as the 10 leading causes of death for males, except for malignant neoplasm of theprostate and malignant neoplasm of the trachea, these being replaced by malignant neoplasm ofthe breast and pneumonia. Although the upper class clearly has lower prevalence rates of particular chronicillnesses, compared to the general population, and more than those in the poorest 20% [47],diabetes mellitus, hypertension and other health conditions are high among them and mayexplain the levels of mortality among those therein. Chronic illnesses are linked to lifestylecauses, and though they have lower rates of chronic illness than people in the lowersocioeconomic group, the reality among the upper class are that their lifestyle explains theirparticular morbidity and mortality. A study by Wilks et al. [49] found that 64.3% of Jamaicanswere currently using alcohol (. liquor, wine, beer or stout, and mixed alcoholic coolers), 13.5%used marijuana, 14.5% smoked cigarettes, and the rates were even greater for males thanfemales. Concurringly, 71% of those in the upper class consumed alcohol (. 84.3% of males and48.7% of females); 9.8% smoked cigarettes (12.4% of males and 6.7% of females); 10.4%smoked marijuana (16.9% of males and 2.2% of females) and 10.5% used illegal drugs (17.1%of males and 2.7% of females) [49]. Furthermore, the percentage of upper class males whoconsumed alcohol was more than for those males in the lower (76.1%) and the middle class(79.4%) [49]. Unhealthy lifestyle practices are therefore responsible for the composition of 137

illnesses which are experienced by the upper class and account for many of their ailments.Furthermore, it is clear from the findings that among the upper socioeconomic class there are novulnerable groups, but what is equally evident is that socioeconomic status accounted for a majorrole in determining the health status of upper class Jamaica as was found for all socioeconomicclassess in Blanc et al.’s work [11].ConclusionWhile poverty is associated with illness and illness is more related to poverty and lower healthstatus for the poor than for those in the upper class, the same is not true of the relationshipbetween the wealthy and the wealthiest 20% in Jamaica. It follows that money and wealth,beyond a certain amount, does not add any further improvements to good health status. Incomeand wealth beyond that which is accessible to the second wealthy in Jamaica do not providethose beyond that with any greater health status. However, what emerged from the current workis that the health disparity between the rural areas’ affluent people and others is vast, suggestingthat there are some underlying cultural conditions which exist among the rich of differentgeographical areas, and which do not disappear because the individual is wealthy. Anotherpertinent finding is that the wealthy spent more days in illness compared to the wealthiest 20%,but this does not translate into lower moderate-to-very good health status. A part of thejustification for this non-health disparity is owing to their conceptualization of health comparedto the image of illness. There are affluent Jamaicans who utilize the public health care system, and many of themhave diabetes mellitus. Within the context of the utilization of the public health care system bythe wealthy, although the percentage is very small, the current finding are important to public 138

health policy makers in understanding the service utilization of this group and their health, andillness profile. In summary, money and wealth beyond that which is accessible by the second wealthy inJamaica will show no further disparity in moderate-to-very good health status. The paperhighlighted the fact that health insurance coverage is not a good measure of health care-seekingbehaviour and illness is not a good proxy for the health status of the upper class. However, thehealth disparity which existed for the general society among the different areas of residents is thesame for the upper class. Rural residents continue to have lower moderate-to-very good healthstatus than the general population, and the second wealthy and the wealthiest 20% in Jamaica.Although only 4 percent of the upper social hierarchy utilizes the public health care system, thereis still a demand for public health services for this group, and it must be taken into account as apart of the general planning for the health care system of the country.Conflict of interestThe author has no conflict to interest to report 139

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Table 6.1. Demographic characteristics of sampleCharacteristics Frequency %Social hierarchy Second wealthy 1352 49.5 Wealthiest 20% 1382 50.5Sex Male 1356 49.6 Female 1378 50.4Area of residence Urban 1184 43.3 Semi-urban 706 25.8 Rural 844 30.9Injury Yes 28 1.1 No 2622 98.9Self-reported typology of injury Motor vehicle accident 4 21.1 Domestic accident 7 36.8 Industrial accident 5 26.3 Domestic incident 2 10.5 Other (unspecified events) 1 5.3Self-reported illness Yes 405 15.3 No 2237 84.7Self-reported diagnosed illness Acute conditions Influenza 56 15.5 Diarrhoea 8 2.2 Respiratory 34 9.4Chronic condition Diabetes mellitus 66 18.3 Hypertension 76 21.1 Arthritis 19 5.3 Other 102 28.3Educational level Primary or below 2311 87.3 Secondary 241 9.1 Tertiary 95 3.6Length of time married median (inn years) 12 (Range = 1, 71)Number of visits to medical practitioners in last 4-weeks 1.4 (1.1)mean (SD)Length of illness median (in days) 5 (Range = 0,200) 143

Table 6.2. Particular variables by social hierarchy Social hierarchy P Wealthy Wealthiest 20%Area of residence n (%) n (%) χ2 = 57.002, P < 0.0001 Urban 499 (36.9) 685 (49.6) Semi-urban 354 (26.2) 352 (25.5) Rural 499 (36.9) 345 (25.0)Sex χ2 = 0.074, P = 0.407 Male 667 (49.3) 689 (49.9) Female 685 (50.7) 693 (50.1)Self-reported diagnosed health condition χ2 = 5.190, P = 0.520 Acute conditions Influenza 32 (17.9) 24 (13.2) Diarrhoea 3 (1.7) 5 (2.7) Asthma 12 (6.7) 22 (12.2) Chronic conditions Diabetes mellitus 33 (18.4) 33 (18.1) Hypertension 38 (21.2) 38 (18.1) Arthritis 8 (4.5) 11 (6.0) Other (unspecified) 53 (29.0) 49 (26.9)Health care-seeking behaviour χ2 = 1.272, P = 0.154 Yes 141 (68.4) 155 (73.5) No 65 (31.6) 56 (26.5)Self-reported illness χ2 = 0.000, P = 0.520 Yes 200 (15.3) 205 (15.3) No 1105 (84.7) 1132 (84.7)Self-reported health status χ2 = 8.815, P = 0.066 Very good 567 (43.2) 531 (40.0) Good 536 (40.8) 565 (42.5) Fair 157 (12.0) 185 (13.9) Poor 42 (3.2) 45 (3.4) Very poor 11 (0.8) 3 (0.2) 144

Table 6.3. Logistic regression: Moderate-to-very good health status by particular variables Odds Coefficient Std. Error Wald P ratio 95% CI Age -0.051 0.013 15.260 0.000 0.95 0.93, 0.98 Male -0.351 0.387 0.822 0.365 0.70 0.33, 1.50 Self-reported illness -19.926 13414.774 0.000 0.999 0.00 0.000, Married -0.353 0.433 0.666 0.415 0.70 0.30, 1.64 Divorced, separated or -0.383 0.549 0.487 0.485 0.68 0.23, 2.00 widowed †Never married 1.00 Health insurance 0.997 0.408 5.976 0.015 2.71 1.22, 6.02 Medical expenditure 0.000 0.000 4.712 0.030 1.00 1.00, 1.00 Urban area 1.474 0.439 11.258 0.001 4.37 1.85, 10.34 Other town 1.584 0.511 9.622 0.002 4.88 1.79, 13.26 †Rural area 1.00 Head of household 0.031 0.410 0.006 0.940 1.03 0.46, 2.30 Per capita consumption 0.000 0.000 0.206 0.650 1.00 1.00, 1.00Model fit χ = 57.54, P < 0.0001 2Hosmer and Lemeshow goodness of fit χ2 = 2.87, P = 0.94-2LL = 194.22Nagelkerke R2 =0.332†Reference group 145

Table 6.4. Logistic regression: Self-reported illness by particular variables Std. Wald Odds 95.0% C.I. Variable Coefficient Error statistic P ratio Age 0.013 0.008 2.769 0.096 1.01 1.0, 1.03 Male -0.415 0.233 3.188 0.074 0.66 0.42, 1.04 Married 0.821 0.260 9.960 0.002 2.27 1.37, 3.79 Divorced, separated or wid -0.141 0.421 0.113 0.737 0.87 0.38, 1.98 †Never married 1.00 Health insurance -0.259 0.244 1.132 0.287 0.77 0.48, 1.24 Urban area -0.347 0.257 1.832 0.176 0.71 0.43, 1.17 Other town -0.219 0.294 0.551 0.458 0.80 0.45, 1.43 †Rural area 1.00 Head of household 0.408 0.243 2.810 0.094 1.50 0.93, 2.42 Per capita consumption 0.000 0.000 0.595 0.440 1.00 1.00, 1.00 Good health status -1.872 0.248 56.921 0.000 0.15 0.10, 0.25 Health care-seekers 6.080 0.417 212.549 0.000 437.11 193.02, 989.89Model fit χ2 = 1087.7, P < 0.0001Hosmer and Lemeshow goodness of fit χ2 = 8.11, P = 0.62-2LL = 649.69Nagelkerke R2 =0.724†Reference group 146

Table 6.5. Logistic regression: Self-reported health seeking behaviour by particular variable Std. Wald Odds 95.0% C.I. Coefficient Error statistic P ratio Age 0.014 0.008 3.080 0.079 1.02 1.00, 1.03 Male -0.109 0.260 0.175 0.676 0.90 0.54, 1.49 Married -0.601 0.295 4.151 0.042 0.55 0.31, 0.98 Divorced, separated or wid -0.291 0.445 0.429 0.513 0.75 0.31, 1.79 † Never married 1.00 Health insurance 0.463 0.269 2.954 0.086 1.59 0.94, 2.69 Urban area 0.134 0.287 0.218 0.640 1.14 0.65, 2.01 Other town -0.034 0.328 0.011 0.918 0.97 0.51, 1.84 †Rural area 1.00 Head of household -0.069 0.270 0.066 0.797 0.93 0.55, 1.58 Per capita consumption 0.000 0.000 0.042 0.837 1.00 1.00, 1.00 Self-reported illness 6.108 0.417 214.598 0.000 449.37 198.47, 1017.42 Good health status -0.658 0.266 6.147 0.013 0.52 0.31, 0.87Model fit χ2 = 995.45, P < 0.0001Hosmer and Lemeshow goodness of fit χ2 = 3.64, P = 0.90-2LL = 446.41Nagelkerke R2 =0.764†Reference group 147

Chapter7 Self-reported health and medical care- seeking behaviour of uninsured JamaicansOn examination of the literature in Latin America and the Caribbean, and in particular Jamaica,no study could be found that investigated the health and health care-seeking behaviour ofuninsured people. This study bridges the gap in the literature, by evaluating uninsuredJamaicans’ medical care-seeking behaviour and good health status. Good health of uninsuredJamaicans is correlated -reported biological condition (OR =0.114, 95% CI = 0.090 -0 .145)followed by age (OR =0.952, 95% CI = 0.946- 0.959); gender (OR = 1.501, 95% CI = 1.221–1.845); consumption (OR = 1.000, 95% CI = 1.000–1.000); social class (upper class OR = 0.563,95% CI = 0.357–0.888); education (secondary and above OR = 0.622, 95%CI = 0.402–0.963),and area of residence (other towns OR = 1.351, 95% CI = 1.026–1.778). Medical care-seekingbehaviour is associated with age (OR = 1.020, 95% CI = 1.006 – 1.033); poor health status (OR= 2.303, 95% CI = 1.533–3.461), and marital status (married OR = 0.518, 95% CI = 0.325–0.824). The findings are far reaching and provide an understanding of the uninsured, and theinformation can be used to aid public health intervention and education programmes.IntroductionPoverty is among the reasons for some people in developing nations not seeking medical care;and it also explains premature death owing to low health care utilization. The World HealthOrganization (WHO) [1] opined that 80% of chronic illnesses were in low and middle incomecountries, suggesting that poverty interfaces with illness and creates other socio-economicchallenges. Poverty does not only impact on illness, it causes premature deaths, lower quality oflife, lower life and healthy life expectancy, low development and other social ills such as crime,high pregnancy rates, and social degradation of the community. According to Bourne & Beckford[2], there is a positive correlation between poverty and unemployment; poverty and illness; and 148

crime and unemployment. Sen [3] encapsulated this well when he put forward the idea that lowlevels of unemployment in the economy are associated with higher levels of capabilities. TheWHO [1] opined that 60% of global mortality is caused by chronic illness, and within the contextthat four-fifths of chronic dysfunctions are in low-to-middle income countries, health insurancecoverage reduces the burden of out-of-pocket medical expenditure for the individual and thefamily. Jamaica is among those countries classified as developing nations. Hence, the challengeswhich were stated earlier also influence the quality of life of some people within the society. In1988, Jamaica’s unemployment rate was 18.9% and 2 decades later (2007), it fell by 67.2% (to6.2%) which indicates close to full-employment. [4] This significant reduction in unemploymentrates cannot be the only indicator used to evaluate the socio-economic status of Jamaica, or for ahasty conclusion to be drawn that the quality of life of Jamaicans is better in 2007 compared to1988. In 1988 the inflation rate in Jamaica was 8.8% and this increased by over 90%, suggestingthat the economic cost of living for Jamaicans was substantially higher than twenty years earlier.It is important to note that the inflation rate in 2007 (16.8%) increased by 194.7% over 2006. Anational representative probability sample cross-sectional survey of 1,338 Jamaicans which wasconducted in 2007 revealed that 68.7% of respondents claimed that their current economicsituation was at most the same compared to 12 months ago, and of this figure 25% mentioned thatit was worse. [5] Furthermore, 62% of the sample indicated that their salaries were not able tosatisfactorily cover their basic needs, and 71.9% claimed that they were concerned about thelikelihood of being unemployed in the next 12 months. Those realities, then, explain why in 2007,the number of Jamaicans seeking medical care fell to 66% over 70% in the previous year; whilethe self-reported figures rose to an unprecedented 15.5%. 149

In Jamaica, rural poverty is twice (15.3%) that of urban poverty (6.2%). [4] This maycreate the impression that urban poverty is low and does not demand an examination. Poverty ispoverty and whether it occurs in rural, peri-urban and urban areas; its effect is the same. Hence,when poverty is coupled with unemployment, chronic illnesses will require health care for eitherpreventive or curative measures which must lead to a financial commitment that can erode theirresources or that of their families. [5] In 2007, statistics on health in Jamaica showed that 50.8%of people in the poorest income quintile (. below the poverty line) indicated that they were unableto afford to seek medical care, compared to 36.7% of those just above the poverty line and 7.1%of those in the wealthiest income quintile. [4] It is private health insurance and social securitythat facilitate access to medical care for the poor and do assist in reducing the financialcommitment of individuals and families for those with chronic or recurring illnesses. Twenty-oneof every 100 Jamaican in 2007 has health insurance coverage, suggesting that the majority ofpeople pay for medical care out of their pockets. Many studies have examined the insured and health care demand of the general populace[6-10] but on reviewing the literature no study was found in Latin America and the Caribbean, inparticular Jamaica, that has investigated the uninsured in regards to their medical care-seekingbehaviour and health status. According to Call & Ziegenfuss, [7] health insurance is a significantpredictor of access to medical care services, and people who do not have access to healthinsurance have less possibilities of accessing health care services. This was contradicted byBourne [11] who found that health insurance is not significant when correlated with the medicalcare-seeking behaviour of Jamaicans or a predictor of the good health of Jamaicans [11] or femaleJamaicans. [12] Call & Ziegenfuss [7] added that rural residents are more restricted from accessto health insurance coverage than urban citizens, suggesting that medical care-seeking behaviour 150

would be lower for rural than urban residents. While Call & Ziegenfuss’ perspectives provide uswith basic information about the insured, it is inadequate for this cohort of people based on thefindings of Bourne [11], and Bourne & Rhule [12]. For 2007, statistics revealed that 21.2% of Jamaicans had health insurance coverage and66% sought medical care, indicating that most of the people who utilized medical care servicesdid not use health coverage. Within the context of the global economic downturn, increased jobredundancies and prices of commodities, the uninsured will be asked to pay more for medicalcare. Apart from the increased odds of not utilizing health care services, little is known about theuninsured in Latin American and the Caribbean, and in particular Jamaica. This study will bridgethe gap in the literature, by evaluating their health status, medical care-seeking behaviour, and themedical conditions of uninsured Jamaicans in order to establish whether there are differences inthe three geographical regions, and to use the information for public health intervention andpolicy formulation. The researcher used data from the 2007 Jamaica Survey of Living Conditionsto evaluate medical care-seeking behaviour, medical conditions, purchased medication, and thehealth status of uninsured Jamaicans as well as building two models for good health status andhealth care-seeking behaviour of this uninsured group.Methods and materialsDataThe current study extracted a sample of 5,203 respondents 15 years of age and over from anational probability cross-sectional survey (Jamaica Survey of Living Conditions, JSLC) of 6,782Jamaicans [13-15]. The cross-sectional survey was conducted between May and August 2007from the 14 parishes across Jamaica and included 6,782 people of all ages [16]. The JSLC used 151

stratified random probability sampling technique to draw the original sample of respondents, witha non-response rate of 26.2%. The sample was weighted to reflect the population. [13-15]Study instrumentThe JSLC used an administered questionnaire where respondents were asked to recall detailedinformation on particular activities. The questionnaire was modelled on the World Bank’s LivingStandards Measurement Study (LSMS) household survey. There are some modifications to theLSMS, as the JSLC is more focused on policy impacts. The questionnaire covers demographicvariables, health, and other issues. Interviewers were trained to collect the data from householdmembers. Data on 5, 203 individuals who indicated not having health insurance coverage wasused in data analysis.Statistical methodsDescriptive statistics such as mean, standard deviation, frequency and percentage were used toanalyze the socio-demographic characteristics of the sample. Chi-square analyses were used toexamine the association between non-metric variables for area of residence, and gender ofrespondents. Logistic regression analyses examined 1) the relationship between good healthstatus and some socio-demographic, economic and biological variables; as well as 2) a correlationbetween medical care-seeking behaviour and some socio-demographic, economic and biologicalvariables. The statistical package SPSS for Windows version 16.0 (SPSS Inc; Chicago, IL, USA)was used to analyze the data. A p-value less than 5% was used to indicate statistical significance. The correlation matrix was examined in order to ascertain if autocorrelation and/ormulticollinearity existed between variables. Based on Cohen and Holliday [17] correlation can below (weak) - from 0 to 0.39; moderate – 0.4-0.69, and strong – 0.7-1.0. The approach inaddressing collinearity (r > 0.6) was to independently enter variables in the model to determine 152

which one should be retained during the final model construction. The method of retaining orexcluding a variable from the model was based on the variables’ contribution to the predictivepower of the model and its goodness of fit. [18-24] Wald statistics were used to determine themagnitude (or contribution) of each statistically significant variable in comparison with theothers, and the Odds Ratio (OR) for the interpreting of each significant variable.ModelsThe current study will employ multivariate analyses in the study of the health status (Equation[1]) and medical care seeking behaviour of Jamaicans (Equation [2]). The use of this approach isbetter than bivariate analyses as many variables can be tested simultaneously for their impact (ifany) on a dependent variable.H t =f(A i , G i , HH i , AR i , lnC, ED i, MR i , S i , ∑MC t , SRIi , ε i ) 1 Where H t (. self-rated good current health status in time t) is a function of age of respondents A i ; sex of individual i, G i ; household head of individual i, HH i ; area of residence, AR i ; logged consumption per person per household member, lnC; Education level of individual i, ED i ; marital status of person i, MR i ; social class of person i, S i ; summation of medical expenditure of individual i in time period t, MC t ; self-reported illness, SRIi , and an error term (. residual error).MCSBi =f(PH t ,A i , G i , HH i , AR i , lnC, ED i, MR i , S i , CR i , ε i ) 2 Where MCSBi is medical care-seeking behaviour of individual i is a function of PH t (ie self-rated poor current health status in time t of individual i); age of respondents A i ; sex of individual i, G i ; household head of individual i, HH i ; area of residence, AR i ; logged consumption per person per household member, lnC; education level of individual i, ED i ; marital status of person i, MR i ; social class of person i, S i ; logged consumption per person 153

per household member i, lnC; crowding of person i, CR i; and an error term (. residual error).From Equation (1) was derived Equation (3) and Equation (4): H t =f(A i , lnC, SRIi , S i , ED i, AR i , G i , ε i ) 3 MCSB i =f(PH t ,A i , MR i , ε i ) 4MeasuresAn explanation of some of the variables in the model is provided here. Self-reported illness statusis a dummy variable, where 1 = reporting an ailment or dysfunction or illness in the last 4 weeks,which was the survey period; 0 if there were no self-reported ailments, injuries or illnesses. [11,12, 25] While self-reported ill-health is not an ideal indicator of actual health conditions becausepeople may under-report, it is still an accurate proxy of ill-health and mortality. [26, 27] Healthstatus is a binary measure where 1=good to excellent health; 0= otherwise which is determinedfrom “Generally, how do you feel about your health”? Answers for this question were on a Likertscale matter ranging from excellent to poor. Age group was classified as children (ages less than15 years); young adults (ages 15 through 30 years); other aged adults (ages 30 through 59 years);young-old (ages 60 through 74 years); old-old (ages 75 through 84 years) and oldest-old (ages85+ years). Medical care-seeking behaviour was taken from the question ‘Has a health carepractitioner, healer , or pharmacist been visited in the last 4 weeks?’ with there being two optionsYes or No. Medical care-seeking behaviour therefore was coded as a binary measure where1=Yes and 0= otherwise. 154

ResultsSocio-demographic characteristics of sampleThe sample was 5,203 uninsured respondents (49.2% males and 50.8% females). Of the sample,32.9% were children; 26.9% young adults; 30.0% other aged adults; 10.8% elderly. The majorityof those sampled had good health status (82.9%); 73% were never married; 62.0% visited medicalcare-seeking behaviour; 60.3% had at most no formal education; 52.2% lived in rural areas;21.0% in semi-urban areas and 26.8% in urban areas. Fifty-nine percent of the sample purchasedthe prescribed medication, and 14.2% reported an illness. Of those who reported ailments, 89.5%revealed that they were diagnosed by health care practitioners. Approximately 17% indicatedcold; 3.5% diarrhoea; 9.8% asthma; 19.7% hypertension; 5.5% arthritis; 25.3% and unspecifieddysfunctions. Forty-five percent of the sample was poor (23.1% below the poverty line), 20.9%in the middle class, and 34.1% were classified as wealthy (14.8% in the wealthiest group). A significant statistical correlation was found between medical care-seeking behaviourand health status (χ2 (df = 2) =36.199, P < 0.001, n=752). Seventy-six percent (N= 160) of thosewho reported poor health status sought medical care compared to 68.0% (n = 174) of those whoreported fair health status and 50.6% (n= 170) of those who indicated good health status. Table 7.1 revealed that significantly more rural residents were poor (58.7%) compared to34.9% of semi-urban and 26.5% of urban dwellers. Only 21.2% of rural respondents were in theupper class which was significantly lower than those in semi-urban areas (42.6%) and thepercentage is even greater in urban zones (52.5%). A cross-tabulation between health status and area of residence revealed a statisticalcorrelation (P<0.001). Further examination showed that substantially more rural respondentsindicated poor health status (6.3%) than semi-urban (3.3%) and urban (3.9%) (see Table 7.1). 155

Significantly more rural dwellers reported being diagnosed with a recurring illness (15.9%) thansemi-urban (11.8%) and urban respondents (12.7%). No significant statistical correlation wasfound between medical care-seeing behaviour and area of residence (P= 0.375). Seventeen percent of females reported a recurring illness which was significantly morethan the 12% for males (Table 7.2). Of the diagnosed recurring illness, approximately twice asmany females reported diabetes mellitus (11.3%) and hypertension (24.6%) than males (6.1%)and 12.6% respectively. While more males indicated cold (18.1%); diarrhoea (3.6%); asthma(11.3%); arthritis (6.5%); and unspecified (27.5%) compared to females – cold (15.6%); diarrhoea(3.4%); asthma (8.8%); arthritis (4.7%), and 23.7% unspecified ailments. A cross-tabulation between health status and self-reported illness found that there was asignificant statistical correlation (χ2 (df = 2) = 989.552, P < 0.001). The association was amoderately strong one (contingency coefficient = 0.401). Further examination of the resultsrevealed that 89.4% (n=3,964) of those who reported no illness had good health status, and only43.7% of respondents with an ailment indicated poor health status. Approximately 22% ofindividuals with at least one dysfunction had poor health status compared to 2.3% of those whodid not have an illness (Table 7.3). A significant statistical correlation existed between self-reported illness and age cohort (χ2(df = 5) = 407.365, P < 0.001, n = 5,189). The findings revealed that 12.4% children reported atleast one illness compared to 5.5% of young adults and following this age cohort self-reportedillness increased to 14.7% for other aged adults; 33.3% of young old; 49.7% of old-old and 51.2%of oldest-old. 156

Multivariate Analysis Table 7.4 examines variables that seek to explain the good health status of insuredJamaicans. Good health statuses of uninsured Jamaicans are correlated with socio-demographic,economic and biological factors. The correlates of good health status of uninsured Jamaicans arestatistically significant (χ2 (df = 15) =993.114, P < 0.001; -2 Log likelihood = 2554.359;Nagelkerke R2 =0.390; Hosmer and Lemeshow goodness of fit χ2=11.159), and 84.6% of the datawere correctly classified: 94.9% of cases in good health status were correctly classified and46.6% were cases with poor health status. Table 7.5 presents information on variables that determine (or not) the medical care-seeking behaviour of uninsured Jamaicans. The correlates that explain medical care-seekingbehaviour of uninsured respondents are statistically significant χ2 (df = 14) = 47.79, P < 0.001; -2Log likelihood = 648.32; Nagelkerke R2 =0.117; Hosmer and Lemeshow goodness of fitχ2=4.480), and 67.5% of the data were correctly classified: 88.1% of data correctly classifiedmedical care-seeking behaviour and 30.0% of data otherwise.DiscussionCaribbean societies, in particular Jamaica, have seen an increase in illnesses such as HIV/AIDS,malignant neoplasm, diabetes mellitus, hypertension, ischaemic heart disease, and arthritis [28-33] which require continued treatment. Although this is a reality, only 21.2% of Jamaicans hadhealth insurance coverage in 2007, indicating that the majority of people are without healthinsurance coverage and many people will not be able to afford medical care. The current study found that approximately one-half of Jamaicans who do not have healthinsurance were poor compared to 34.1% of the wealthy and 20.9% of those in the middle class.Substantially more Jamaicans below the poverty line (23.1%) did not have health insurance 157

compared to 14.8% of those in the wealthiest 20%. In addition, 33% were children compared to11% who were older than 60 years. Although there is a preponderance of Jamaicans who are poorand uninsured, this research found that there was no statistical difference between medical care-seeking behaviour and social class; medical care-seeking behaviour and sex; and health care-seeking behaviour and area of residence. Embedded in this finding is the dominance of a non-medical care-seeking behaviour culture in Jamaica, and it is so fundamental that education, socialclass and income are not able to retard the practice. This is captured in an analysis of the studythat had 44 out of every 100 respondents indicating that they were ill enough to seek medical carecompared to 34 out of every 100 in the population; and 18 out of every 100 stated they preferredhome remedies compared to 30 in 100 in the populace. Sixty-six out of every 100 Jamaicans sought medical care, comprising the poorest 20%-to-wealthiest 20% in 2007. The current study revealed that 45 out of every 100 poor people werenot covered by health insurance compared to 17 out of 50 for the wealthy and 21 out of 100 forthe middle class. Concomitantly, 33 out of every 100 children (less than 15 years) and 60 out ofevery 100 Jamaicans who had no formal education were not covered by health insurance. Therationale which accounts for the fact that there is no significant difference in medical care-seekingbehaviour among the social classes is embedded in the removal of user fees in the health caresystem; and how this has narrowed the health care-seeking behaviour gap between the poor andthe wealthy. In 2007, the government of Jamaica introduced national health insurance coverage forthose who suffer from particular illnesses, as well as for those who are older than 60 years. Thissocial security coverage commissioned by the Jamaican government eliminates health insurancefor ‘unwell’ patients, suggesting that health is conceptualized as diseases, which is not in keeping 158

with an operationalization of health offered by the WHO. [34] According to the WHO, healthdoes not only mean the absence of disease, but it must include social, psychological and physicalwellbeing. The health insurance coverage offered by the government explains the low uninsuredgroup among the Jamaican elderly. Hence, this means that most of those who possess healthinsurance would have private coverage; the high ‘unwell’ Jamaicans therefore justify the highnon-insured group in the nation. This paper examines the uninsured or the ‘unwell’. This analysis has found that good health status can be determined by age, consumption,self-reported illness, social class, education, area of residence and gender of respondents, whichconcurs with other studies. [35-39] While this study is the first of its type in Jamaica, its findingsare similar to other multivariate studies that have examined the health status of people. Using datafor elderly Barbadians, Hambleton et al.’s work [35] found that dysfunction accounted for themost explanatory power in health status, which is confirmed by this analysis. The model that wasdeveloped for the good health status of uninsured Jamaicans was based on the 7 aforementionedvariables with a coefficient of determination of the current study being 39.0% (Nagelkerke R2=0.390). This predictive model seems weak; but Hambleton et al’s work on elderly Barbadianshad a coefficient of determination of 38.2%, indicating that the analysis of this paper is relativelygood in keeping with a non-Jamaican study of a similar nature. In spite of the similarities, there are some notable differences with other studies. Eight-three out of every 100 uninsured Jamaicans reported at least good health status; 20 out of every100 were hypertensive; 9 out of 100 diabetic and 6 out of 100 arthritic compared to the percentageof respondents in the population with particular health conditions: hypertension, 22 out of every100; diabetes mellitus, 12 out of every 100; and, arthritis, 9 out of every 100. It is interesting tonote that Jamaicans have a preference for private health care utilization [15] but this is not the 159

case for the uninsured. In 2007, 52 out of every 100 Jamaican visited private health care servicescompared to 6 out of every 100 of the uninsured. The percentage of uninsured who visited publichealth care facilities (34 out of every 100) was also lower than in the general populace (41 out ofevery 100). The analysis of this study went further than that of other identified studies as it found thatuninsured Jamaicans who resided in rural areas reported a greater percentage of illnesses,followed by urban, than other town residents. Marmot [35] opined that income influences healthas it provides access to more resources, medical services, and lower infant mortality. The analysisof this work concurs with Marmot [35] and PAHO et al. [9] as consumption (which can proxyincome) is positively correlated with good health status. With this reality, there seems to be aparadox, as those in the wealthy classes had lower good health status than those in the poorclasses. Income undoubtedly provides access to more resources, better physical conditions andopens the way to better quality of water and food; it also offers individuals, societies or nationsthe highest quality medical services which cannot be accessed by the poor. [35] There is anotherside to this discourse in that the lifestyle practices of the wealthy help to erode the advantages ofincome. According to Bourne, McGrowder & Holder-Nevins, [41] health behaviour which is afunction of one’s culture suggests that the wealthy will continue their involvement in parties andother social arrangements which will involve the use of alcoholic beverages, smoking and otherrisky lifestyle practices that reduce the advantage of income. While income can buy access tobetter medical services, this paper highlights that it cannot buy good health. It is clear from thecurrent study that wealthy uninsured Jamaicans are using their income the wrong way in regardsto its negative impact on health. Insufficient money is associated with more illness; however, this 160

study has revealed that there is no statistical difference between the wealthy and the poor seekingmedical care. Although the wealthy substantially used private health care facilities and the poorutilized public health facilities, [15] embedded in this analysis therefore is the fact that the qualityof primary level care in Jamaica is of a high standard. While there is no difference between the wealthy uninsured and the poor uninsuredseeking medical care, the study revealed that those with poor health status were 2.3 times morelikely to seek health care services than those in good health. The analysis of this work showedthat 22 out of every 100 uninsured Jamaicans who indicated at least one health condition reportedpoor health status. Hence this study highlights the fact that there is a disparity betweenrespondents’ conceptualization of health status and that of illness, as 44% of uninsured illrespondents indicated that they had good health status. The JSLC report revealed that the prevalence of recurrent (chronic) diseases is highestamong individuals 65 years and over. [41] According to PIOJ & STATIN [42] individuals 60-64years were 1.5 times more likely to report an injury than children less than five years old, and thefigure was even higher for those 64 years and older (2.5 times more). It should be noted here thatthis increase in self-reported cases of injuries/ailments does not represent an increase in theincidence of cases as the JSLC for 2004 said that the proportion of recurring/chronic cases fellfrom 49.2% in 2002 to 38.2% in 2004 [43]. Eldemire [44] found that 34.8% of new cases ofdiabetes and 39.6% of hypertension were associated with senior citizens (. ages 60 and over).Bourne, McGrowder, & Crawford [39] found that the poor health status of people 60 to 64 yearswas 33.2% and this increased to 36.1% for elderly 65 to 69 years, 49.4% for elderly 70 to 74years and 51.7% for those 75 years and older, emphasizing the positive correlation betweenincreased ailments and ageing of the Jamaican elderly. 161

An analysis of the current study revealed that there is no significant difference among thepopulations across the 3 geographical areas in Jamaica in regards to health care-seekingbehaviour, suggesting that the uninsured medical care-seeking behaviour is the same in the 3geographical areas. This research concurs with the finding of a study by Call & Ziegenfuss [7]meaning that the uninsured in Jamaica are not atypical as they are in keeping with those inMinnesota, United States. Further, no significant correlation was found among urban, semi-urban,rural and educational levels of uninsured Jamaicans which were similar to that of Call &Ziegenfuss. Many studies have shown that married people (or those in unions) had greater healthstatus than those who were never married. [45-51]. The current work disagreed with thosefindings as it found that there was no significant statistical correlation between good health statusof married uninsured people, and those who were never married, or separated, divorced orwidowed. Analysis of this research revealed that those who were married were 48.2% less likelyto seek medical care than those who were never married. The answer to this lies in the lifestylepractices of these people. Smith & Waitzman [49] offered the explanation that wives were able todissuade their husband from particular risky behaviours such as the use of alcohol and drugs, andwould ensure that they maintain a strict medical regimen coupled with proper eating habits.[50,51] Koo, Rie & Park’s findings [48] revealed that being married was a ‘good’ cause for anincrease in psychological and subjective wellbeing in old age. This study is the first of its kind inthe Caribbean, in particular Jamaica, which models the health care-seeking behaviour ofuninsured respondents, and so there is nothing to compare it with. The coefficient ofdetermination for this model was 11.9%, which means that although it is low its validation willneed further research. 162

Limitation of studyA single cross-sectional study cannot be used to examine causality, as well as a snap shot surveycannot effectively capture the continuous matter of the variables. The severity of illness wasexcluded from the medical care-seeking behaviour model because of missing cases and this couldhave been critical to the study.ConclusionThe findings of this research are far reaching and provide an understanding of the uninsured, andthe information can be used to aid public health intervention and education programmes.Conflict of interestThere is no conflict of interest to report. 163

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Table 7.1: Socio-demographic characteristics of sample Area of residence PVariable Urban Semi-urban Rural n (%) n (%) n (%)Sex 0.284 Male 662 (47.4) 544 (49.9) 1354 (49.9) Female 735 (52.6) 547 (50.1) 1361 (50.1)Social class < 0.001 Poor 370 (26.5) 381 (34.9) 1594 (58.7) Middle 294 (21.0) 245 (22.5) 546 (20.1) Upper 733 (52.5) 465 (42.6) 575 (21.2)Age group 0.002 Children 418 (29.9) 334 (30.6) 961 (35.4) Young adults 411 (29.4) 306 928.0) 646 (23.8) Other aged adults 416 (29.8) 344 (31.5) 803 (29.6) Young old 93 (6.7) 72 (6.6) 199 (7.3) Old-old 48 (3.4) 27 (2.5) 82 (3.0) Oldest-old 11 (0.8) 8 (0.7) 24 (0.9)Health status < 0.001 Good 1137 (81.7) 956 (87.6) 2202 (81.6) Fair 201 (14.4) 99 (9.1) 329 (12.2) Poor 54 (3.9) 36 (3.3) 169 (6.3)Education < 0.001 No formal 841 (60.4) 687 (63.1) 1599 (59.1) Basic 174 (12.5) 118 (10.8) 362 (13.4) Primary/preparatory 168 (12.1) 158 (14.5) 429 (15.8) Secondary/High 166 (11.9) 111 (10.2) 300 (11.1) Tertiary 43 (3.1) 14 (1.3) 17 (0.6)Marital status 0.012 Married 177 (18.3) 132 (17.5) 382 (21.9) Never married 721 (74.5) 562 (74.6) 1245 (71.4) Divorced 18 (1.9) 17 (2.3) 15 (0.9) Separated 5 (0.5) 8 (1.1) 20 (1.1) Widowed 47 (4.9) 34 (4.5) 82 (4.7)Self-reported illness 0.001 Yes 176 (12.7) 128 (11.8) 432 (15.9) No 1215 (87.30 958 (88.2) 2280 (84.1)Medical care-seeking behaviour 0.375 Yes 120 (66.3) 78 (59.5) 270 (60.9) No 61 (33.7) 53 (40.5) 173 (39.1)Number of visits to medical 1.4 days (SD 1.4 days 1.4 days (SD 0.846facilities = 0.7) (SD= 1.3) = 1.0) 167

Table 7.2: Sociodemographic characteristic by SexVariable Sex P Male FemaleSelf-reported illness < 0.001 Yes 298 (11.7) 438 (16.6) No 2256 (88.3) 2197 (83.4)Diagnosed Self-reported illness < 0.001 Cold 56 (18.1) 69 (15.6) Diarrhoea 11 (3.6) 15 (3.4) Asthma 35 (11.3) 39 (8.8) Diabetes mellitus 19 (6.1) 50 (11.3) Hypertension 39 (12.6) 109 (24.6) Arthritis 20 (6.5) 21 (4.7) Other (unspecified) 85 (27.5) 105 (23.7) No 44 (14.2) 35 (7.9)Medical care-seeking behaviour 0.101 Yes 182 (58.5) 286 (64.4) No 129 (41.5) 158 (35.6)Purchase medication 0.251 Prescribed medicine 170 (56.9) 259 (60.1) Partial prescription 3 (1.0) 13 (3.0) Prescribed/over the counter 9 (3.0) 15 (3.5) Over counter 20 (6.7) 25 (5.8) Prescribed/did not buy 9 (3.0) 17 (3.9) None prescribed required 88 (29.4) 102 (23.7)Number of visits to medical facilities Mean (SD) 1.3 days (0.7) 1.4 days (1.1) 0.252 168

Table 7.3. Health status by Self-reported dysfunction Self-reported Dysfunction At least one Health Status No ailment ailment Total n (%) n (%) n (%) Good 3964 (89.4) 320 (43.7) 4284 (82.9) Fair 372 (8.4) 255 (34.8) 627 (12.1) Poor 100 (2.3) 158 (21.6) 258 (5.0) Total 4436 733 5169χ2 (df = 2) =989.552, P < 0.001 169

Table 7.4. Ordinary Logistic Regression: Correlates of Good Health Status of UninsuredJamaicans Wald Odds Variable Coefficient Std Error statistic ratio 95.0% C.I. Age -0.049 0.004 191.667 0.95 0.95 -0.96*** Logged consumption per capita 0.000 0.000 11.692 1.00 1.00 - 1.00** Self reported illness -2.168 0.121 323.527 0.11 0.09 -0.15*** Middle class 0.086 0.154 0.314 1.09 0.81 - 1.47 Upper class -0.575 0.233 6.107 0.56 0.36 - 0.89* †Lower class 1.00 Married 0.138 0.129 1.154 1.15 0.89 -1.48 Divorced/separated/widowed -0.217 0.192 1.277 0.81 0.55 - 1.17 †Never married 1.00 Primary schooling 19.089 40192.970 0.000 0.00 -0.00 Secondary and above -0.475 0.223 4.525 0.62 0.40 - 0.96* †No formal education 1.00 Urban area -0.115 0.124 0.870 0.89 0.70 -1.14 Other town 0.301 0.140 4.593 1.35 1.03 -1.78* †Rural area 1.00 Man 0.406 0.105 14.872 1.50 1.22 -1.85*** Household head 0.097 0.113 0.741 1.10 0.88 -1.37 Cost of public medical care 0.000 0.000 0.040 1.00 1.00 - 1.00 Cost of private medical care 0.000 0.000 3.003 1.00 1.00 -1.00χ2 (df = 15) =993.114, P < 0.001-2 Log likelihood = 2554.359Nagelkerke R2 =0.390Hosmer and Lemeshow goodness of fit χ2=11.159, P = 0.693Overall correct classification = 84.6%Correct classification of cases of good health status = 94.9%Correct classification of cases of poor health status = 46.6%†Reference group*P < 0.05, **P < 0.01, ***P < 0.001 170

Table 7.5. Ordinary Logistic Regression: Correlates of Medical Care-Seeking Behaviour ofUninsured Jamaicans Std. Wald Odds Variable Coefficient Error statistic ratio 95% C.I. Man -0.282 0.205 1.894 0.76 0.51 - 1.13 Age 0.019 0.007 8.213 1.02 1.01 - 1.03** Middle class 0.544 0.284 3.675 1.72 0.99 - 3.00 Upper class 0.683 0.427 2.558 1.98 0.86 - 4.57 †Lower 1.00 Poor health 0.834 0.208 16.139 2.30 1.53 - 3.46*** Urban area 0.070 0.248 0.079 1.07 0.66 - 1.75 Other town -0.243 0.260 0.877 0.78 0.47 - 1.31 †Rural 1.00 Crowding 0.111 0.067 2.749 1.12 0.98 - 1.27 Per capita consumption 0.000 0.000 0.017 1.00 1.00 - 1.00 Secondary and above 0.431 0.571 0.569 1.54 0.50 - 4.71 †No formal education 1.00 Married -0.659 0.237 7.720 0.52 0.33 -0 .82** Divorced, separated/widowed -0.453 0.332 1.864 0.62 0.33 - 1.22 †Never married 1.00 Head household -0.210 0.218 0.933 0.81 0.53 - 1.24χ2 (df = 14) = 47.79, P < 0.001-2 Log likelihood = 648.32Nagelkerke R2 =0.117Hosmer and Lemeshow goodness of fit χ2=4.480, P = 0.811Overall correct classification = 67.5%Correct classification of cases of medical care-seeking behaviour = 88.1%Correct classification of cases of no medical care-seeking behaviour = 30.0%†Reference group*P < 0.05, **P < 0.01, ***P < 0.001 171

Chapter8 Social determinants of self-reported health across the Life CourseThe socio-psychological and economic factors produced inequalities in health and need to beconsidered in health development. In spite of this, extensive review of health Caribbean revealedthat no study has examined health status over the life course of Jamaicans. With the value ofresearch to public health, this study is timely and will add value to understanding the elderly,middle age and young adults in Jamaica. The aim of this study is to develop models that can beused to examine (or evaluate) social determinants of health of Jamaicans across the life course,elderly, middle age and young adults. Eleven variables emerged as statistically significantpredictors of current good health Status of Jamaicans (p<0.05). The factors are retirementincome (95%CI=0.49-0.96), logged medical expenditure (95% CI =0.91-0.99), marital status(Separated or widowed or divorced: 95%CI=0.31-0.46; married: 95%CI=0.50-0.67; Nevermarried), health insurance (95%CI=0.029-0.046), area of residence (other towns:, 95%CI=1.05-1.46; rural area:), education (secondary: 95%CI=1.17-1.58; tertiary: 95%CI=1.47-2.82;primary or below: OR=1.00), social support (95%CI=0.75-0.96), gender (95%CI=1.281-1.706),psychological affective conditions (negative affective: 95%CI=0.939-0.98; positive affective:95%CI:1.05-1.11), number of males in household (95%CI:1.07-1.24), number of children inhousehold (95%CI=1.12-1.27) and previous health status. There are disparities in the socialdeterminants of health across the life course, which emerged from the current findings. Thefindings are far reaching and can be used to aid policy formulation and how social determinantsof health are viewed in the future.I NTRODUCTIONHealth is a multidimensional construct which goes beyond dysfunctions (illnesses, ailment orinjuries) [1-14]. Although World Health Organization (WHO) began this broaden conceptualframework in the late 1940s [1], Engel [3] was the first to develop the biopsychosocial model thatcan be used to examine and treat health of mentally ill patient. Engel’s biopsychosocial modelwas both in keeping with WHO’s perspective of health and again a conceptual model of health.Both WHO and Engel’s works were considered by some scholar as too broad and as such difficult 172

to measure [15]; although this perspective has some merit, scholars have ventured into usingdifferent proxy to evaluate the ideal conceptual definition forwarded by WHO for some time now. Psychologists have argued that the use of diseases to proxy health is unidirectional (ornegative) [2], and that the inclusion of social, economic and psychological conditions in health isbroader and more in keeping with the WHO’s definition of health than diseases. Diener was thefirst psychologist to forward the use of happiness to proxy health (or wellbeing) of an individual[16, 17]. Instead of debating along the traditional cosmology health, Diener took the discussioninto subjective wellbeing. He opined that happiness is a good proxy for subjective wellbeing of aperson, and embedded therein is wider scope for health than diseases. Unlike classical economistswho developed Gross Domestic Product per capita (GDP) to examine standard of living (orobjective wellbeing) of people as well this being an indicator of health status along with otherindicators such as life expectancy, Diener and others believe that people are the best judges oftheir state. This is no longer a debate, as some economists have used happiness as a proxy ofhealth and wellbeing [18-20]; and they argued that it is a good measurement tool of the concept.Theoretical Framework Whether the proxy of health (or wellbeing) is happiness, self-reported health status, self-rated health conditions, life satisfaction or ill-being, it was not until in the 1970s that econometricanalyses were employed to the study of health. Grossman [9] used econometric to capture factorsthat simultaneously determine health stock of a population. Grossman’s work transformed theconceptual framework outlined by WHO and Engel to a theoretical framework for the study ofhealth. Using data for the world, Grossman established an econometric model that capturesdeterminants of health. The model read (Model 1): H t = ƒ (H t-1 , G o , B t , MC t , ED) ……………………………………………….. Model (1) 173

where H t – current health in time period t , stock of health (H t-1 ) in previous period , B t –smoking and excessive drinking, and good personal health behaviours (including exercise – G o ),MC t ,- use of medical care, education of each family member (ED), and all sources of householdincome (including current income). Grossman’s model was good at the time; however, one of the drawbacks to this model wasthe fact that some crucible factors were omitted by the aforementioned model. Based on thatlimitation, using literature, Smith and Kington [10] refined, expanded and modified Grossman’swork as it omitted important variables such as price of other inputs and family background orgenetic endowment which are crucible to health status. They refined Grossman’s work to includesocioeconomic variables as well as some other factors [Model (2)]. H t = H* (H t-1 , P mc , P o , ED, Et , R t , A t , G o ) ………………………..…………… Model (2) Model (2) expresses current health status H t as a function of stock of health (H t-1 ), priceof medical care P mc , the price of other inputs P o , education of each family member (ED), allsources of household income (Et ), family background or genetic endowments (G o ), retirementrelated income (R t ), asset income (A t ). It is Grossman’s work that accounts for economists like Veenhoven’s [20] and Easterlin’s[19] works that used econometric analysis to model factors that determine subjective wellbeing.Like Veenhoven [20], Easterlin [19] and Smith and Kington [10], Hambleton et al. [6] used thesame theoretical framework developed by Grossman to examine determinants of health of elderly(ages 65+ years) in Barbados. Hambleton et al.’s work refined the work of Grossman and addedsome different factors such as geriatric depression index; past and current nutrition; crowding;number of children living outside of household; and living alone. Unlike Grossman’s study, hefound that current disease conditions accounted for 67.2% of the explained variation in health 174

status of elderly Barbadians, with life style risks factors accounting for 14.2%, and social factors18.6%. One of the additions to Grossman’s work based on Hambleton et al.’s study was actualproportion of each factor on health status and life style risk factors. A study published in 2004, using life satisfaction and psychological wellbeing to proxywellbeing of 2,580 Jamaicans, Hutchinson et al. [21] employed the principles in econometricanalysis to examine social and health factors of Jamaicans. Other studies conducted by Bourne ondifferent groups and sub-groups of the Jamaican population have equally used the principles ofeconometric analysis to determine factors that explain health, quality of life or wellbeing [5, 8, 22,23]. Despite the contribution of Hutchinson et al’s and Bourne’s works to the understanding ofwellbeing, there is a gap in the literature on a theoretical framework explains good health status ofthe life course of Jamaicans. The current study will model predictors of good health status ofJamaicans as well as good health status of young adults, middle age adults and elderly in order toprovide a better understanding of the factors that influence each cohort.METHODSParticipants and questionnaireThe current research used a nationally cross-sectional survey of 25,018 respondents from the 14parishes in Jamaica. The survey used stratified random probability sampling technique to drawthe 25,018 respondents. The non-response rate for the survey was 29.7% with 20.5% who did notrespond to particular questions, 9.0% did not participated in the survey and another 0.2% wasrejected due to data cleaning. The study used secondary cross-sectional data from the JamaicaSurvey of Living Conditions (JSLC). The JSLC was commissioned by the Planning Institute ofJamaica (PIOJ) and the Statistical Institute of Jamaica (STATIN). These two organizations areresponsible for planning, data collection and policy guideline for Jamaica. 175

The JSLC is a self-administered questionnaire where respondents are asked to recall detailedinformation on particular activities. The questionnaire covers demographic variables, health,immunization of children 0 to 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.ModelThe multivariate model used in this study is a modification of those of Grossman and Smith &Kington which captures the multi-dimensional concept of health, and health status. The presentstudy further refine the two aforementioned works and in the process adds some new factors suchas psychological conditions, crowding, house tenure, number of people per household and adeconstruction of the numbers by particular characteristics . males, females and children (ages ≤14 years). Another fundamental difference of the current research and those of Grossman, andSmith and Kington is that it is area specific as it is focused on Jamaican residents. The proposed model that this research seeks to evaluate is displayed below [Model (3)]:H t = f(H t-1 ,P mc , ED i , R t , At , Q t , HH t , C i , En i , MS i , HI i , HT i , SS i , LL i ,X i , CR i , D i , O i , Σ(NP i ,PP i ), M i ,N i , FS i , Ai ,Wi , ε i )….. Model (3) The current health status of a Jamaica, H t , is a function of 23 explanation variables, whereH t is current health status of person i, if good or above (. no reported health conditions four weekleading up to the survey period), 0 if poor (. reported at least one health condition); H t-1 is stock ofhealth for previous period; lnPmc is logged cost of medical care of person i; ED i is educationallevel of person i, 1 if secondary, 1 if tertiary and the reference group is primary and below; Rt isretirement income of person i, 1 if receiving private and/or government pension, 0 if otherwise;HI i is health insurance coverage of person i, 1 if have a health insurance policy, 0 if otherwise;HT i is house tenure of person i, 1 if rent, 0 if squatted; Xi is gender of person i, 1 if female, 0 if 176

male; CRi is crowding in the household of person i; Σ(NPi,PPi) NPi is the summation of allnegative affective psychological conditions and PPi is the summation of all positive affectivepsychological conditions; M i is number of male in household of person i and Fi is number offemale in household of person i; Ai is the age of the person i and N i is number of children inhousehold of person i; LLi is living arrangement where 1= living with family members orrelative, and 0=otherwise and social standing (or social class), W i .Statistical analysisStatistical analyses were performed using Statistical Packages for the Social Sciences (SPSS) forWindows, Version 16.0 (SPSS Inc; Chicago, IL, USA). A single hypothesis was tested, whichwas ‘health status of rural resident is a function of demographic, social, psychological andeconomic variables.’ The enter method in logistic regression was used to test the hypothesis inorder to determine those factors that influence health status of rural residents if the dependentvariable is a binary one; and linear multiple regression in the event the dependent variable was anormally distributed metric variable . The final model was established based on those variablesthat are statistically significant (ie. p < 0.05) – ie 95% confidence interval (CI), and all othervariables were removed from the final model (p>0.05). Continuing, categorical variables werecoded using the ‘dummy coding’ scheme. The predictive power of the model was tested using Omnibus Test of Model and Hosmerand Lemeshow [24] was used to examine goodness of fit of the model. The correlation matrix wasexamined in order to ascertain whether autocorrelation (or multi-collinearity) existed betweenvariables. Cohen and Holliday [25] stated that correlation can be low/weak (0 to 0.39); moderate(0.4-0.69), or strong (0.7-1.0). This was used in this study to exclude (or allow) a variable in themodel. Where collinearity existed (r > 0.7), variables were entered independently into the model 177

to determine those that should be retained during the final construction of the model. To deriveaccurate tests of statistical significance, we used SUDDAN statistical software (Research TriangleInstitute, Research Triangle Park, NC), and this was adjusted for the survey’s complex samplingdesign. Finally, Wald statistics was used to determine the magnitude (or contribution) of eachstatistically significant variables in comparison with the others, and the odds ratio (OR) for theinterpreting each significant variables.Results: Modelling Current Good Health Status of Jamaicans, Elderly, Middle Age andYoung adultsPredictors of current Good Health Status of Jamaicans. Using logistic regression analyses, elevenvariables emerged as statistically significant predictors of current good health status of Jamaicans(p<0.05, see Model 4). The factors are retirement income, logged medical expenditure, maritalstatus, health insurance, area of residence, education, social support, gender, psychologicalaffective conditions, number of males in household, number of children in household andprevious health status (Table 8.1). H t = f(H t-1 , Rt , Pmc , ED i , MS i , HI i , SS i ,ARi , Xi , Σ(NPi ,PPi ), M i ,N i , ε i )...……..... Model(4) The model [ie Model (4)] had statistically significant predictive power (χ2 (27) =1860.639,p < 0.001; Hosmer and Lemeshow goodness of fit χ2=4.703, p = 0.789) and overall correctlyclassified 85.7% of the sample (correct classified 98.3% of cases of good health status andcorrectly classified 33.9% of cases of dysfunctions). There was a moderately strong statistical correlation between age, marital status,education, retirement income, per capita income quintiles, property ownership, and so these wereomitted from the initial model (ie model 3). Based on that fact, three age groups were classified(young adults – ages 15 to 29 years; middle age adults – ages 30 to 59 years; and elderly – ages 178

60+ years) and the initial model was once again tested. There were some modifications of theinitial model in keeping with the age group. For young adults the initial model was amended byexcluding retirement income, property ownership, divorced, separated or widowed, number ofchildren in household, and house tenure. The exclusion was based on the fact that more than 15%of cases missing in some categories and a high correlation between variables.Predictors of current Good Health Status of elderly Jamaicans. From the logistic regressionanalyses that were used on the data, eight variables were found to be statistically significant inpredicting good health Status of elderly Jamaicans (P < 0.5) (see Model 5). These factors wereeducation, marital status, health insurance, area of residence, gender, psychological conditions,number of males in household, number of children in household and previous health status (seeTable 8.2). H t = f(H t-1 , ED i , MS i , HI i , ,ARi , Xi , Σ(PPi ), M i ,N i , ε i )...……………………... Model (5) The model had statistically significant predictive power (model χ2 (27) =595.026, P <0.001; Hosmer and Lemeshow goodness of fit χ2=5.736, p = 0.677) and overall correctlyclassified 75.5% of the sample (correctly classified 94.6% of cases of good or beyond healthstatus and correct classified 44.7% of cases of dysfunctions). Predictors of current Good Health Status of middle age Jamaicans. Using logisticregression, six variables emerged as statistical significant predictors of current good health statusof middle age Jamaican (p < 0.05) (Model 6). These factors are logged medical expenditure,physical environment, health insurance, gender of respondents, psychological condition, numberof children in household and previous health status (see Table 8.3) H t = f(H t-1 , P mc , En i , HI i , X i , Σ(NP i ),N i , ε i ).......................……………………………..... Model(6) 179

Based on Table 8.3, the model had statistically significant predictive power (model χ2 (27)=547.543, p < 0.001; Hosmer and Lemeshow goodness of fit χ2=4.318, p = 0.827) and overallcorrectly classified 87.2% of the sample (correctly classified 98.3% of cases of good or beyondhealth status and correct classified 28.2% of cases of dysfunctions).Predictors of current Good Health Status of young adult in Jamaica. Using logistic regression, twovariables emerged as statistically significant predictors of current good health status of youngadults in Jamaica (p<0.05) (Model 7). These are health insurance coverage, psychologicalcondition, social class and previous health status (Table 4).H t = f(H t-1 , W i , HI i , Σ(NP i ), ε i )...............................................…………………………….....Model (7) From Table 8.3, the model had statistically significant predictive power (model χ2 (19)=453.733, p < 0.001;8. Hosmer and Lemeshow goodness of fit χ2=5.185, p = 0.738) and overallcorrectly classified 92.6% of the sample (correctly classified 99.0% of cases of good or beyondhealth status and correct classified 28.2% of cases of dysfunctions).Limitations to the Models Good Health Status of Jamaicans [Model (4)], elderly [ie Model (5)], middle age adults[Model (6)], and young adults [Model (7) are derivatives of Model (3). Good Health Status[Model (4) – Model (7)] cannot be distinguished and tested over different time periods, persondifferential, and these are important components of good health. H t = f(H t-1 , R t , P mc , ED i , MS i , HI i , SS i ,AR i , X i , Σ(NP i ,PP i ), M i ,N i , ε i )...………………………..... Model (4) H t = f(H t-1 , ED i , MS i , HI i , ,AR i , X i , Σ(PP i ), M i ,N i , ε i )...………………………………………..... Model (5) H t = f(H t-1 , P mc , En i , HI i , X i , Σ(NP i ),N i , ε i )....................................……………………………..... Model (6) H t = f(H t-1 , Wi , HI i , Σ(NP i ), ε i ).......................................................……………………….…….......Model (7) 180

H t = f(H t-1 ,P mc , ED i , R t , A t , Q t , HH t , C i , En i , MS i , HI i , HT i , SS i , LL i ,X i , CR i , D i , O i , Σ(NP i ,PP i ), M i ,N i , FS i , A i , Wi ,ε i )………………………………………………………………………..Model (3) The current work is a major departure from Grossman’s theoretical model as he assumedthat factors affecting good health Status over the life course are the same, this study disagreedwith this fundamental assumption. This study revealed that predictors of good health status arenot necessarily the same across the life course, and differently from that of the general populace.Despite those critical findings, healthy time gained can increase good health status directly andindirectly but this cannot be examined by using a single cross-sectional study. Health does notremain constant over any specified period, and to assume that this is captured in age is to assumethat good or bad health change over year (s). Health stock changes over short time intervals, andso must be incorporated within any health model. People are different even across the same ethnicity, nationality, next of kin andsocialization. This was not accounted for in the Grossman’s or the current work, as this is one ofthe assumptions. Neither Grossman’s study nor the current research recognized the importance ofdifferences in individuals owing to culture, socialization and genetic composition. Eachindividual’s is different even if that person’s valuation for good health Status is the same assomeone else who share similar characteristics. Hence, a variable P representing the individualshould be introduced to this model in a parameter α (p). Secondly, the individual’s good (or bad)health is different throughout the course of the year and so time is an important factor. Thus, theresearcher is proposing the inclusion of a time dependent parameter in the model. Therefore, thegeneral proposition for further studies is that the function should incorporate α (p, t) a parameterdepending on the individual and time. 181

An unresolved assumption of this work which continues from Grossman’s model is thatpeople choose health stock so that desired health is equal to actual health. The current data cannottest this difference in the aforementioned health status and so the researcher recommends thatfuture study to account for this disparity so we can identify factors of actual health and differencebetween the two models.Discussions This study has modelled current good status of Jamaicans. Defining health into twocategories (good – not reported an acute or illness; or poor – reported illness or ailment), thisstudy has found that using logistic regression health status can be modeled for Jamaicans. Thefindings revealed that the probability of predicting good health status of Jamaicans was 0.789,using eleven factors; and that approximately 86% of the data was correctly classified in this study.Continuing, in Model (4) approximately 98% of those who had reported good health status werecorrectly classified, suggesting that using logistic regression to examine good health status of theJamaican population with the eleven factors that emerged is both a good predictive model and agood evaluate or current good health status of the Jamaican population. This is not the first studyto examine current good health status or quality of life in the Caribbean or even Jamaica [6, 21-23, 26], but that none of those works have established a general and sub-models of good healthover the life course. In Hambleton et al’s work, the scholars identified the factors (historical, current, life style,diseases) and how much of health they explain (R2=38.2%). However, they did not examine thegoodness of fit of the model or the correctness of fit of the data. Bourne’s works [12,13] weresimilar to that of Hambleton et al’s study, as his study identified more factors (psychologicalconditions; physical environment, number of children or males or females in household and socialsupport) and had a greater explanatory power (adjusted r square = 0.459) but again the goodness 182

of fit and correctness of fit of the data were omitted. Again this was the case in Hutchinson et al.’sresearch. Like previous studies in the Caribbean that have examined health status [6, 21-23, 26],those conducted by the WHO and other scholars [27-32] did not explore whether socialdeterminants of health vary across the life course. Because this was not done, we have assumedthat the social determinants are the same across the life. However, a study by Bourne andEldemire-Shearer [33] introduced into the health literature that social determinants differ acrosssocial strata for men. Such a work brought into focus that there are disparities in the socialdeterminants of health across particular social characteristic and so researchers should notarbitrarily assume that they are the same across the life course. While Bourne and Eldemire-Shearer’s work [33] was only among men across different social strata in Jamaica (poor andwealthy), the current study shows that there are also differences in social and psychologicaldeterminants of health across the life course. The current study has concluded that the factors identified to determine good health statusfor elderly, had the lowest goodness of fit (approximately 68%) while having the greatestexplanatory power (R2= 35%). The findings also revealed low explanatory powers for youngadults (R2=22.6%) and middle age adults (R2=23%), with latter having a greater goodness of fitfor the data as this is owing to having more variables to determine good health. Such a findinghighlights that we know more about the social determinants for the elderly than across other agecohorts (middle-aged and young adults). And that using survey data for a population to ascertainthe social determinants of health is more about those for the elderly than across the life course ofa population. 183

Another important finding is of the eleven factors that emerge to explain good healthstatus of Jamaicans, when age cohorts were examine it was found that young adults had the leastnumber of predictors (ie health insurance, social class and negative affective psychologicalconditions). This suggests that young adult’s social background and health insurance areimportant factors that determine their good health status and less of other determinants that affectthe elderly and middle age adults. It should be noted that young adult is the only age cohort withwhich social standing is a determinant of good health. Even though the good health status modelthat emerged from this study is good, the low explanatory power indicates that young adults areunique and further study is needed on this group in order to better understand those factors thataccount for their good health. Furthermore, this work revealed that as people age, the socialdeterminants of health of the population are more in keeping with those of the elderly than atyounger ages. Hence, the social determinants identified by Grossman [9], Smith and Kington [10]and purported by Abel-Smith [11] as well as the WHO [27] and affiliated researchers [28-32] aremore for the elderly population than the population across the life course.ConclusionsThere are disparities in the social determinants of health across the life course, which emergedfrom the current findings. The findings are far reaching and can be used to aid policy formulationand how we examine social determinants of health. Another issue which must be researched iswhether there are disparities in social determinants of health based on the conceptualization andmeasurement of health status (using self-reported health, and health conditions).DisclosuresThe author reports no conflict of interest with this work. 184

DisclaimerThe researcher would like to note that while this study used secondary data from the JamaicaSurvey of Living Conditions (JSLC), none of the errors in this paper should be ascribed to thePlanning Institute of Jamaica (PIOJ) and/or the Statistical Institute of Jamaica (STATIN), but tothe researcher.AcknowledgementThe author thanks 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 (2002 JSLC) availablefor use in this study, and the National Family Planning Board for commissioning the survey. 185

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Table 8.1: Good Health Status of Jamaicans by Some Explanatory Variables CI (95%) Wald statistic Odds Variable Coefficient Std Error. P Ratio Lower Upper Middle Quintile -0.03 0.10 0.09 0.764 0.97 0.81 1.17 Two Wealthiest Quintiles -0.11 0.10 1.26 0.261 0.90 0.74 1.09 Poorest-to-poor Quintiles* Retirement Income -0.38 0.17 4.88 0.027 0.68 0.49 0.96 Household Head 0.17 0.29 0.37 0.543 1.19 0.68 2.08 Logged Medical Expenditure -0.05 0.02 5.10 0.024 0.95 0.91 0.99 Average Income 0.00 0.00 1.56 0.212 1.00 1.00 1.00 Average Consumption 0.00 0.00 0.16 0.689 1.00 1.00 1.00 Environment 0.01 0.07 0.02 0.891 1.01 0.88 1.16 Separated or Divorced or Widowed -0.97 0.10 87.36 0.000 0.38 0.31 0.46 Married -0.55 0.08 53.05 0.000 0.58 0.50 0.67 Never married* Health Insurance -3.31 0.12 776.64 0.000 0.04 0.03 0.05 Other Towns 0.21 0.08 6.64 0.010 1.24 1.05 1.46 Urban Area -0.01 0.13 0.00 0.952 0.99 0.78 1.27 Rural Area* House Tenure - Rent -1.08 0.88 1.48 0.224 0.34 0.06 1.93 House Tenure - Owned -0.42 0.55 0.58 0.447 0.66 0.23 1.93 House Tenure- Squatted* Secondary Education 0.31 0.08 15.81 0.000 1.36 1.17 1.58 Tertiary Education 0.71 0.17 18.09 0.000 2.03 1.45 2.82 Primary and below* Social Support -0.17 0.07 6.33 0.012 0.85 0.75 0.96 Living Arrangement -0.06 0.13 0.20 0.659 0.95 0.73 1.22 Crowding -0.01 0.04 0.08 0.772 0.99 0.91 1.07 Land ownership -0.07 0.07 0.90 0.342 0.93 0.81 1.08 Gender 0.39 0.07 28.67 0.000 1.48 1.28 1.71 Negative Affective -0.04 0.01 14.96 0.000 0.96 0.94 0.98 Positive Affective 0.07 0.01 26.26 0.000 1.08 1.05 1.11 Number of males in household 0.14 0.04 13.36 0.000 1.15 1.07 1.24 Number of females in household 0.06 0.04 2.36 0.124 1.06 0.98 1.14 Number of children in household 0.17 0.03 29.16 0.000 1.19 1.12 1.27 Constant 1.89 0.65 8.31 0.004 6.59χ2 (27) =1860.639, p < 0.001; n = 8,274-2 Log likelihood = 6331.085Hosmer and Lemeshow goodness of fit χ2=4.703, p = 0.789.Nagelkerke R2 =0.320Overall correct classification = 85.7% (N=7,089)Correct classification of cases of good or beyond health status =98.3% (N=6,539)Correct classification of cases of dysfunctions =33.9% (N=550); *Reference group 189

Table 8.2: Good Health Status of Elderly Jamaicans by Some Explanatory Variables Std Wald Odds Coefficient Error statistic P Ratio CI (95%) Lower Upper Middle Quintile -0.10 0.15 0.47 0.495 0.90 0.67 1.22 Two Wealthiest Quintiles 0.12 0.17 0.47 0.491 1.12 0.81 1.56 Poorest-to-poor quintiles Retirement Income -0.22 0.22 1.00 0.317 0.81 0.53 1.23 Household Head 0.89 0.65 1.86 0.172 2.44 0.68 8.76 Logged Medical Expenditure -0.06 0.04 2.16 0.142 0.95 0.88 1.02 Average Income 0.00 0.00 0.93 0.335 1.00 1.00 1.00 Environment -0.16 0.12 1.80 0.180 0.86 0.68 1.08 Separated or Divorced or -0.49 0.15 11.00 0.001 0.61 0.46 0.82 Widowed Married -0.33 0.15 4.82 0.028 0.72 0.54 0.97 Never married* -3.35 0.22 241.88 0.000 0.04 0.02 0.05 Health Insurance Other Towns 0.33 0.14 5.32 0.021 1.39 1.05 1.83 Urban 0.40 0.21 3.48 0.062 1.49 0.98 2.27 Rural areas* House tenure - rented -20.37 40192.9 0.00 1.000 0.00 0.00 House tenure - owned 1.22 1.24 0.96 0.327 3.38 0.30 38.60 House tenure – squatted* Secondary Education -0.46 0.11 16.06 0.000 0.63 0.51 0.79 Tertiary Education 0.81 0.35 5.45 0.020 2.26 1.14 4.47 Primary or below* Social support -0.08 0.11 0.47 0.495 0.93 0.75 1.15 Living arrangement 0.26 0.18 2.11 0.146 1.30 0.91 1.84 Crowding -0.05 0.09 0.29 0.593 0.95 0.80 1.14 Landownership 0.17 0.13 1.72 0.190 1.19 0.92 1.54 Gender 0.47 0.12 14.67 0.000 1.60 1.26 2.04 Negative Affective -0.03 0.02 1.97 0.160 0.97 0.94 1.01 Positive Affective 0.07 0.02 9.26 0.002 1.07 1.03 1.12 Number of male 0.18 0.07 6.75 0.009 1.19 1.04 1.36 Number of females 0.05 0.07 0.49 0.485 1.05 0.91 1.21 Number of children 0.22 0.06 12.09 0.001 1.24 1.10 1.40 Constant -1.32 1.44 0.83 0.362 0.27χ2 (27) =595.026, p < 0.001; n = 2,002-2 Log likelihood = 2,104.66Hosmer and Lemeshow goodness of fit χ2=5.736, p = 0.677.Nagelkerke R2 =0.347Overall correct classification = 75.5% (N=1.492)Correct classification of cases of good or beyond health status =94.6% (N=1,131)Correct classification of cases of dysfunctions =44.7% (N=361);*Reference group 190

Table 8.3: Good Health Status of Middle Age Jamaicans by Some Explanatory Variables Std Wald Odds Coefficient Error statistic P Ratio CI (95%) Lower Upper Middle Quintile 0.03 0.15 0.04 0.834 1.03 0.76 1.40 Two Wealthiest Quintiles -0.29 0.15 3.67 0.055 0.75 0.56 1.01 Poorest-to-poor Quintiles* Retirement Income -0.57 0.36 2.44 0.119 0.57 0.28 1.16 Household Head 0.50 0.45 1.24 0.265 1.66 0.68 4.01 Logged Medical Expenditure -0.09 0.04 6.44 0.011 0.91 0.85 0.98 Average Income 0.00 0.00 0.53 0.465 1.00 1.00 1.00 Environment 0.31 0.12 7.41 0.006 1.37 1.09 1.71 Separated or Divorced or Widowed -0.20 0.23 0.77 0.380 0.82 0.53 1.28 Married -0.18 0.11 2.68 0.102 0.84 0.68 1.04 Never married* Health Insurance -3.04 0.17 320.76 0.000 0.05 0.03 0.07 Other Towns 0.11 0.12 0.75 0.387 1.11 0.87 1.42 Urban -0.01 0.19 0.00 0.963 0.99 0.68 1.44 Rural areas* House tenure - rented 17.94 20029.78 0.00 0.999 0.00 House tenure - owned -1.33 1.12 1.43 0.232 0.26 0.03 2.35 House tenure – squatted* Secondary education 0.19 0.13 2.11 0.146 1.20 0.94 1.55 Tertiary education 0.34 0.23 2.23 0.135 1.41 0.90 2.21 Primary or below* Social support -0.08 0.10 0.57 0.450 0.93 0.76 1.13 Living Arrangement -0.19 0.21 0.87 0.351 0.83 0.55 1.24 Crowding -0.05 0.06 0.65 0.419 0.95 0.85 1.07 Landownership -0.13 0.11 1.47 0.226 0.88 0.71 1.08 Gender 0.51 0.11 21.41 0.000 1.66 1.34 2.06 Negative Affective -0.08 0.02 24.66 0.000 0.92 0.90 0.95 Positive Affective 0.05 0.02 4.51 0.034 1.05 1.00 1.10 Number of males in house 0.03 0.06 0.23 0.630 1.03 0.92 1.14 Number of female in house 0.08 0.06 2.09 0.149 1.08 0.97 1.21 Number of children in house 0.10 0.04 5.47 0.019 1.11 1.02 1.21 Constant 3.29 1.25 6.89 0.009 26.77χ (27) =547.543, p < 0.001; n = 3,799 2-2 Log likelihood = 2,776.972Hosmer and Lemeshow goodness of fit χ2=4.318, p = 0.827.Nagelkerke R2 =0.230Overall correct classification = 87.2% (N=3,313)Correct classification of cases of good or beyond health status =98.3% (N=3,143)Correct classification of cases of dysfunctions =28.2% (N=170);*Reference group 191

Table 8.4: Good Health Status of Young Adults Jamaicans by Some Explanatory Variables Wald Odds CI (95%) Coefficient Std Error statistic P Ratio Lower Upper Middle Quintile -0.06 0.19 0.10 0.747 0.94 0.65 1.37 Two Wealthiest Quintiles -0.59 0.18 11.10 0.001 0.55 0.39 0.78 Poorest-to-poor quintiles* Household Head -0.25 0.39 0.41 0.520 0.78 0.36 1.68 Logged Medical Expenditure 0.01 0.04 0.09 0.760 1.01 0.93 1.10 Average Income 0.00 0.00 3.29 0.070 1.00 1.00 1.00 Environment -0.03 0.13 0.04 0.840 0.97 0.75 1.26 Health Insurance -3.73 0.21 321.51 0.000 0.02 0.02 0.04 Other Towns 0.23 0.15 2.42 0.120 1.26 0.94 1.69 Urban -0.05 0.18 0.07 0.788 0.95 0.68 1.34 Rural area* Secondary education -0.06 0.41 0.02 0.886 0.94 0.43 2.09 Tertiary education -0.39 0.47 0.70 0.405 0.68 0.27 1.69 Primary and below* Social support -0.14 0.13 1.22 0.269 0.87 0.68 1.12 Crowding 0.04 0.06 0.65 0.420 1.05 0.94 1.16 Gender 0.19 0.15 1.60 0.206 1.20 0.90 1.60 Negative Affective -0.04 0.02 4.22 0.040 0.96 0.93 1.00 Positive Affective 0.07 0.03 6.81 0.009 1.07 1.02 1.13 Number of males in house 0.13 0.07 3.67 0.055 1.13 1.00 1.29 Number of females in house 0.06 0.06 0.87 0.351 1.06 0.94 1.20 Married 0.08 0.22 0.13 0.717 1.09 0.70 1.68 Never married* Constant 2.75 0.67 16.62 0.000 15.57χ2 (19) =453.733, p < 0.001; n = 4,174-2 Log likelihood = 2,091.88Hosmer and Lemeshow goodness of fit χ2=5.185, p = 0.738.Nagelkerke R2 =0.226Overall correct classification = 92.6% (N=3,864)Correct classification of cases of good or beyond health status =99.0% (N=3,757)Correct classification of cases of dysfunctions =28.2% (N=107);*Reference group 192

Chapter9 Social Determinants of Health in a developing Caribbean nation: Are there differences based on municipalities and other demographic characteristics?This study examined socioeconomic determinants of self-reported health status of Jamaicans andwhether self-reported illness is a good measure of health status. In addition, the study wentfurther to identify the predictors of the sexes and different area of residences as those cohortshave different economic characteristics. Age, self-reported illness and consumption weredeterminants across the sexes, and area of residences. Education and social class were correlateof women and not men and social assistance a predictor of health status for men and not women.Although dwellers in urban areas have less determinants, it had the greatest explanatory power(45.7%) compared to rural areas (44.5%) and urban residence (30.5%). Length of time inhousehold and education were social determinants synonymous with only urban areas; socialclass and gender were social predictors of only rural areas while age, self-reported ill andconsumption were correlates of all area of residences. A critical finding that emerged from thisstudy is the fact that self-reported health status is a good predictor of health status and so can beused if self-rated health status is not available. Generally, the social determinants of healthstatus of Jamaicans are mostly the same across the sexes, and the difference area of residences.IntroductionTraditionally, in Western Societies, health is the ‘absence of diseases’. This approach is bothnarrow and negative in scope. According to some scholars, the aforementioned conceptualizationemphasizes the absence of some disease causing pathogens, and not really health [1, 2]. Such aperspective is in keeping with traditional biomedical model that views the exposure to specificpathogen as the cause of diseases in organisms. This began during 130ce to 200ce in AncientRome and despite the efforts of the WHO as early as in 1946 to expand this construct [3]; health 193

in Caribbean societies in particular Jamaica is still substantially viewed as the ‘absence ofdiseases’ or dysfunctions, with wellbeing being the opposite of that state. Lynch [4] opines that everything that we do, feel, think and experience interface with ourhealth. Hence, health status cannot be operationally defined solely based on functional limitationbecause of pathogens as many events affect ones quality of life outside of that space. Theconcept of health according to the WHO is multifaceted. The WHO [3] wrote in its preamble toits Constitution that “Health is state of complete physical, mental and social wellbeing, and notmerely being the absence of disease or infirmity”. From the WHO’s perspective, health status isan indicator of wellbeing [5] and that there are social determinants of health status. One scholar [6] opined that the WHO operationalization of health (or wellbeing) is toobroad and by extension difficult to measure. While there are some merits to this perspective,some researchers have used happiness [7-11], life satisfaction [5, 12-16], and self-reported healthstatus to proxy health. The argument is that those constructs are broad and cover wellbeing (orhealth) and so partially dismisses the propositions of Bok. This in part is owing to the fact thatresearchers continue to investigate in order to ascertain a better measure of health (or wellbeing). A part from the discourse on operational definition of health, the WHO conceptualizationof health identifies social determinants and not merely biological factors. Engel [17-20] believedthat the state of man’s wellbeing is not only influenced by his/her biologic state but that isalways dependent on his/her environment, economic and sociologic conditions. Usingeconometric analyses, Grossman [21] was the first to develop a model that identified some of thesocial determinants of health status. He found that smoking and excessive drinking, and goodpersonal health behaviours (including exercise), use of medical care, education of each familymember, and all sources of household income (including current income); to be determinants of 194

health status. Smith & Kington [22] expanded on the social determinants developed byGrossman, by including and refining some of the factors. They found that the price of medicalcare, the price of other inputs, family background or genetic endowments, retirement relatedincome, and asset income can be perceived as social predictors of wellbeing. There is a thrust by the WHO to examine social determinants of health for the individualand the population [23]. A part of the rationale for this drive is the role poverty plays inproducing health inequalities and the need to examine health development. Many researcherswho are affiliated with the WHO [24-26] and others [27, 28] have been reviewing and examiningsocial determinants of health. Caribbean scholars [29–33] have been using econometric analysesto establish social determinants of health (or wellbeing); ergo such is the rationale for its usage inthis research. Hambleton et al. [33] went further to include self-reported illness along with somesocial determinants of health in a study of elderly Barbadians. Their work used data on theelderly population and this has never been applied to data for the population. No such study inthe Caribbean, in particular Jamaica, has been identified in the literature which has examinedwhether self-reported illness is highly correlated with self-rated health status as well as socialdeterminants of self-evaluated health status, using national probability data. It is within thisframework that this study examined factors that determined self-reported health status ofJamaicans including whether self-reported health conditions are highly correlated with self-evaluated health status; and to decompose this for sex and area of residence using a modelderived by econometric analysis. This will be done by testing a general hypothesis which readssocio-economic variables and self-reported illness are determinants of self-evaluated healthstatus (Equation [1]). 195

MethodThe current study used a sample of 6,783 respondents. The sample was drawn from a largenationally representative cross-sectional survey of 6,783 Jamaicans [34]. The survey was drawnusing stratified random sampling. This design was a two-stage stratified random sampling designwhere there was a Primary Sampling Unit (PSU) and a selection of dwellings from the primaryunits. The PSU is an Enumeration District (ED), which constitutes of a minimum of 100dwellings in rural areas and 150 in urban areas. An ED is an independent geographic unit thatshares a common boundary. This means that the country was grouped into a strata of equal sizebased on dwellings (EDs). Pursuant to the PSUs, a listing of all the dwellings was made, andthis became the sampling frame from which a Master Sample of dwellings was compiled, whichin turn provided the sampling frame for the labour force. One third of the 2007 Labour ForceSurvey (LFS) was selected for the survey. This study used JSLC 2007 which was conducted by the Statistical Institute of Jamaica(STATIN) and the Planning Institute of Jamaica (PIOJ) between May and August 2007. Theresearchers chose this survey based on the fact that it is the latest survey on the nationalpopulation and that it has data on self-rated health status of Jamaicans. An administeredquestionnaire was used to collect the data, which were stored and analyzed using SPSS forWindows 16.0 (SPSS Inc; Chicago, IL, USA). The questionnaire was modelled from the WorldBank’s Living Standards Measurement Study (LSMS) household survey. There are somemodifications to the LSMS, as JSLC is more focused on policy impacts. The questionnairecovered areas such as socio-demographic, economic and health variables. The non-response ratefor the survey was 26.2%. 196

Descriptive statistics such as mean, standard deviation (SD), frequency and percentagewere used to analyze the socio-demographic characteristics of the sample. Chi-square was usedto examine the association between non-metric variables, and an Analysis of Variance(ANOVA) was used to test the relationships between metric and non-dichotomous categoricalvariables. Logistic regression examined the relationship between the dependent variable andsome predisposed independent (explanatory) variables, because the dependent variable was abinary one (self-reported health status: 1 if reported good health status and 0 if poor health). The results were presented using unstandardized B-coefficients, Wald statistics, Oddsratio and confidence interval (95% CI). The predictive power of the model was tested using theOmnibus Test of Model and Hosmer & Lemeshow [35] were used to examine the goodness of fitof the model. The correlation matrix was examined in order to ascertain whether autocorrelation(or multicollinearity) existed between variables. Based on Cohen & Holliday [36] correlation canbe low (weak) - from 0 to 0.39; moderate – 0.4-0.69, and strong – 0.7-1.0. This was used toexclude (or allow) a variable in the model. Wald statistics were used to determine the magnitude(or contribution) of each statistically significant variable in comparison with the others, and theOdds Ratio (OR) for the interpreting of each significant variable. Multivariate regression framework [29,30] was utilized to assess the relative importanceof various demographic, socio-economic characteristics, physical environment and psychologicalcharacteristics, in determining the health status of Jamaicans; and this has also been employedoutside of Jamaica [21,22,33]. This approach allowed for the analysis of a number of variablessimultaneously. Secondly, the dependent variable is a binary dichotomous one and thisstatistical technique has been utilized in the past to do similar studies. Having identified thedeterminants of health status from previous studies, using logistic regression techniques; final 197

models were built for Jamaicans as well as for each of the geographical sub-regions (rural, peri-urban and urban areas) and sex of respondents using only those predictors that independentlypredict the outcome. A p-value of 0.05 was used for all tests of significance.ModelThe use of multivariate analysis in the study of health and subjective w

Human ageing in jamaica

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