Health and Other Aspects of the Quality of Life of Older People

Celebrating the United Nations' International Year of Older Persons, in September 1999 a survey research project was undertaken throughout the Northern Interior Health Region (NIHR) of British Columbia. A total of 875 people completed 23-page questionnaires, the average age of the respondents was 69 and the range ran from 55 to 95 years. Responses to the SF-36 questionnaire indicated that for male respondents aged 55–64, the mean score for the 8 dimensions was 74.4. This mean was practically identical to that of the United States norm for such people (74.5) and lower than that for the United Kingdom (77.4). For male respondents aged 65 and older, the mean was 68.3. This was numerically higher but again practically the same as that of the norm for the United States (68.1). For females aged 55–64, the mean score for 8 dimensions was 73. This was superior to that of the United States norm of (70.6) for such people and lower than that for the United Kingdom (74.6). For female respondents aged 65 and older, the mean score was 65.4. This was practically identical to that of the United States (65.5).Comparing 18 average figures for our respondents on satisfaction with specific domains of life (e.g., financial security, health, friendships) and life as a whole with those of average adults in Prince George in November 1999, we found that in all but two cases the older people's scores were higher. Only in the cases of satisfaction with health and overall happiness were older people's scores lower, and the differences were not statistically significant.Eleven percent of our respondents reported that they had been a victim of a crime in the last year, compared to 38% in our 1997 adult victimization survey. Older people had a more benign view than ordinary adults of the growth of crime in their neighbourhood and city, although exactly 64% of both groups thought that crime had increased in Canada. Although older people had a more optimistic view than other adults of the increase in crime in their neighbourhoods, fewer of the former than the latter felt safe out at night. Nevertheless, compared to adults surveyed in 1997, the behaviour of respondents in our survey of older people was not as constrained by concerns of criminal victimization.Two or three of the 8 SF-36 health dimensions explained 37% of the variation in life satisfaction scores, 34% of variation in happiness scores, 34% in satisfaction with the overall quality of life scores and 22% in satisfaction with one's overall standard of living. In every case, Mental Health was the dimension that had the greatest impact on our four dependent variables.When all of our potential predictors were entered into a regression equation simultaneously, we found that they could explain 60% of the variance in life satisfaction scores, 44% in happiness scores, 58% in satisfaction with the overall quality of life scores and 59% in satisfaction with one's overall standard of living scores.     

Health and the Quality of Life

The aim of this investigation was to explain theimpact of peoples self-reported health on theirlevels of satisfaction with their health, and theimpact of these things plus satisfaction with otherspecific domains of their lives on the perceivedquality of their lives. The latter was operationalized as general happiness, satisfactionwith life as a whole and overall satisfaction with thequality of life. Seven hundred and twenty-three (723)usable questionnaires returned from a mailout randomsample of 2500 households of Prince George, BritishColumbia in November 1998 formed the working data-setfor our analyses. Among other things, mean respondentscores on the SF-36 health profile were found to belower than published norms from the UK, USA,Netherlands and Sweden, but higher than scores fromAberdeen, Scotland. Mean scores on the CES-Ddepression scale also indicated that our respondentstended to have more depressive symptoms thancomparison groups in Winnipeg and the USA. A review oftrends in mean scores on 17 quality of life items(e.g., satisfaction with family life, financialsecurity, recreation, etc.) from 1994, 1997 and 1998revealed that there were only 7 statisticallysignificant changes across the four year period andthey were all negative. Multivariate regressionanalysis showed that health status measured with avariety of indicators could explain 56% of thevariation in respondents reported satisfaction withtheir health. A combination of health status plusdomain satisfaction indicators could explain 53% ofthe variation in respondents reported happiness, 68%of reported life satisfaction and 63% of reportedsatisfaction with the overall quality of life. Sixtypercent of the explained variation in happiness scoreswas attributable to self-reported health scores, whileonly 18% of the explained variation in satisfactionwith life and with the overall quality of life scoreswas attributable self-reported health scores.     

Quality of Life Across Life Domains: Family Structure and Relations

Social Indicators Research - This paper aims to evaluate how the Korean family fares in terms of itsquality of life. Specifically, it examines the perceived quality of relationships among family...     

Religiosity and Life Satisfaction Across the Life Course

Scant attention has been paid to social catalysts of the increase in religiosity in the maturational and aging process. Using the 1988 Gallup Survey, this paper first explores four major measures of religiosity (personal devotion, participation in public ritual, divine interaction, and preference for public or privatized religiosity) for seven age groups. Next, the impact of these religiosity measures on satisfaction with life is assessed for each of the major age categories. In light of these findings, the authors move toward developing a theory of religiosity and life course.     

Self Report Co-Morbidity and Health Related Quality of Life – A Comparison with Record Based Co-Morbidity Measures

The purpose of this projectwas to compare three hospital-based measures ofco-morbidity to patient self-reportco-morbidity and to determine the relativeproportion of outcome predicted by each of theco-morbidity measures in a population ofindividuals receiving major joint arthroplasty. Baseline measures using the SF-36 generalhealth questionnaire and the Western OntarioMcMaster Osteoarthritis Index (WOMAC) wereobtained from 518 persons undergoing total kneeor hip replacement. A second measure wasobtained six months post-surgery. Co-morbiditywas calculated by summing the self-reportedco-morbidity at baseline, using both thechart-based and administrative data version ofCharlson's Co-morbidity Index, and by summingthe number of International Classification ofDiseases – Version 9 (ICD-9) codes appearingin the electronic health record. Linearregression was used to determine how much ofthe variation in outcome was explained by eachof the co-morbidity measurement methods. Self-report co-morbidity explained as muchvariation in outcome as the hospital-basedindices. Self-report co-morbidity did notperform as well as the other methods inexplaining the variance in health systemutilization. It was concluded that self-reportco-morbidity is minimally as useful asrecord-based systems when measuring the impactof co-morbidity on health related quality oflife (HRQL). This is an important finding, asprivacy legislation, the time until data isavailable and cost are all barriers to usingrecord-based co-morbidity measures.     

Quality of Life Across Population Groups: Women in the Workplace: Gender and Wage Differentials

Social Indicators Research - The purpose of this study is to clarify the real causes of gender wage differentials in Korea by analyzing changes over the period 1988–1999. The participation...     

Determinants of Health and the Quality of Life in the Bella Coola Valley

The aim of this investigation is to obtain some baseline self-reported data on the health status and overall quality of life of all residents of the Bella Coola Valley of British Columbia aged 17 years or older, and to measure the impact of a set of designated health determinants on their health and quality of life. In the period from August to November 2001, a variety of procedures were used to ensure that all eligible residents of the Valley received a copy of our questionnaire, and 687 useable questionnaires were obtained for our working dataset. Health status was measured by SF-36 and the U.S. Centers for Disease Control healthy days items. Thirty-one items were used to measure the Provincial Health Officer’s designated determinants of health in four clusters, namely, biological, social and economic, health behaviours and health services determinants. Quality of life was measured by satisfaction levels in 13 specific domains of life (e.g., family, financial security), four global items (e.g., happiness, life satisfaction) and one global Subjective Well-Being Index. Besides obtaining baseline figures on all our measures for the Valley, we made some comparisons among our figures and those from other areas, e.g., Prince George, BC. Most of the measures indicated that the health status and quality of life of Bella Coola Valley residents were lower than those of Prince George residents. For the sample as a whole, SF-36 scores on the eight dimensions ran from 82.3 (physical functioning) to 50.0 (social functioning), with a mean of 62.7. Residents in the Valley averaged 6.5 days in the past 30 in which their health was physically not good, 5.5 days when it was mentally not good and 4.1 days when their health limited their usual daily activities. Eleven percent of respondents described their general health as “excellent” and another 27% said it was “very good”. On a 7-point scale from 1=very dissatisfied to 7=very satisfied, respondents had average life satisfaction and satisfaction with the overall quality of life scores of 5.5. For specific domains of life, the lowest mean level of satisfaction was reported for federal and provincial government officials (3.3) and the highest was reported for living partners and personal safety around home (5.8). Regarding bivariate relations, each of the eight dimensions of SF-36 was significantly correlated with a single item measure of general health, and five of the eight were significantly correlated with the number of good health days. Happiness and the Subjective Well-Being Index were positively but moderately correlated with six of the eight dimensions, and life satisfaction was positively correlated with five. Age was negatively related to general health, but positively related to life satisfaction. Not being of aboriginal descent was positively related to all of the four global health indicators and to the Subjective Well-Being Index. Education was positively related to the four global health measures but not to the three global quality of life measures. The Social Support and Good Family Indexes were positively related to all seven global measures. There was a positive correlation between six of the seven global measures and the frequency with which respondents participated in activities sponsored by voluntary organizations. Frequency of smoking was negatively associated with every global dependent variable except the Physical Health Index. Frequency of skipping meals was negatively associated and average hours of sleep per night was positively associated with all seven global measures. Turning to multivariate relationships, the four clusters of health determinants explained from 12% (SF-36 Mental Health Index) to 24% (general health) of the variance in the dependent global health variables, and from 20% (happiness) to 26% (Subjective Well-Being Index) of the variance in the dependent global quality of life variables. Adding domain satisfaction scores to the total set of predictors allowed us to explain from 20% (SF-36 Mental health Index) to 29% (general health) of the variance in the dependent global health variables, and from 39% (happiness) to 62% (life satisfaction) in the dependent global quality of life variables. By including measures of social support and good family relationships in our set of health determinants, we practically guaranteed that the latter would be relatively strongly predictive of global quality of life.     

Empirical Comparison Between Capability and Two Health-Related Quality of Life Measures

The Investigating Choice Experiments Capability Measure (ICECAP) is a new preference-based measure of the extent to which a person is able to achieve attributes or capabilities related to the quality of life. Conceptually, it differs from health-related quality of life (HRQoL) as the focus is upon the ability or capacity to achieve as distinct from the current experience of the attributes. The objective of this study was to explore the empirical relationships between capability as assessed by the ICECAP for Adults (ICECAP-A) and HRQoL as assessed by the Assessment of Quality of Life (AQoL)-8D and the five-level EuroQol Five Dimensions questionnaire (EQ-5D). To compare these measures, the study employed self-reported survey data from the healthy public and from seven disease areas in five countries. Results indicate that, despite their conceptual origins, the ICECAP-A is strongly associated with the AQoL-8D and that the clear distinction between capabilities and HRQoL found in other studies is attributable to the use of the EQ-5D in the comparison and the weaker association between the EQ-5D and ICECAP-A. The suggestion that ICECAP-A should be included in evaluation studies along with a HRQoL instrument is more persuasive when the instrument is the EQ-5D. The case for its inclusion with other HRQoL instruments requires further research and evaluation.     

Issues in Evaluating Importance Weighting in Quality of Life Measures

For most empirical research investigating the topic of importance weighting in quality of life (QoL) measures, the prevailing approach has been to use (1) a limited choice of global QoL measures as criterion variables (often a single one) to determine the performance of importance weighting, (2) a limited option of weighting methods to develop importance weighting, and (3) a limited number of domains to construct the (formative-indicator) measures. Although limitations resulted from a limited choice of global QoL measures as criterion variables to determine the performance of importance weighting and a limited option of weighting methods to develop importance weighting have been recognized previously, little attention has been paid to the impact of non-comprehensive domains in QoL measures constructed based on the formative-indicator approach. Using empirical data, this article revealed the potential impacts of non-comprehensive domains on the evaluation of importance weighting in QoL measures. Results presented in this article showed that both of the two most popular methods of evaluating the performance of importance weighting in QoL measures, correlation and moderated regression analysis, could produce misleading results in the situation when QoL measures constructed using the formative-indicator approach did not include comprehensive domains. Issues discussed in this article are of great importance to research in the field of QoL, especially on the topic of importance weighting in QoL measures.     

The Quality of Life in Korea: Comparative and Dynamic Perspectives

Social Indicators Research -     

Healthy Days,Health Satisfaction and Satisfaction with the Overall Quality of Life

In this note we report results of 6 surveysusing the United States Centers for DiseaseControl and Prevention indicators of healthstatus, taken from the Behavioral Risk FactorSurveillance System. Generally speaking, wefound that the CDC healthy days variables couldplay a useful role in survey research aimed atassessing the impact of measured health statuson people's satisfaction with their own healthand with the overall quality of their lives.More precisely, using stepwise regressions wefound: (1) The three healthy days variablesexplained from 16 to 27 percent of the variancein General Health scores. The limited activitydays variable remained as a significantpredictor in only one of the six regressionsand the not good physical health days variablewas most influential in every sample. (2) Thethree healthy days variables explained from 19to 32 percent of the variance in healthsatisfaction scores, and the not good physicalhealth days variable was again most influentialin every sample. (3) The three healthy daysvariables explained from 12 to 39 percent ofthe variance in quality-of-life satisfactionscores, with the not good mental healthvariable most influential in every sample. (4)The four CDC variables together explained from40 to 55 percent of the variance in healthsatisfaction scores, with the General Healthvariable always dominating the set ofpredictors by a fairly wide margin. (5) Thefour CDC variables together explained from 17to 28 percent of the variance inquality-of-life satisfaction scores, with theGeneral Health variable most influential inthree samples and the not good mental healthvariable most influential in the other three.(6) When the four CDC variables plus the healthsatisfaction variable were used as potentialpredictors, we were able to explain from 29 to40 percent of the variance in quality-of-lifesatisfaction scores. In every sample, theGeneral Health and limited activity daysvariables had no significant impact. (7) Usingstructural equation modeling, we found GeneralHealth does not have a direct effect onsatisfaction with the overall quality of lifebut rather only an indirect effect throughhealth satisfaction. The General Health, notgood physical health, and not good mentalhealth days variables account for 51% of thevariation in health satisfaction, and healthsatisfaction, not good physical health and notgood mental health days variables account for30% of the variation in satisfaction with theoverall quality of life.     

Perceived Quality of Life and Self-Rated Health among First-Year University Students

This study compares health status and qualityof life assessments of first-year universitystudents with those of their same-age workingcounterparts. Subjects and materials for eachgroup were gathered in 1999 from twocross-sectional data sets from the Swedishregion of Östergötland, covering malesand females aged 20–34 years. Subjects'perceived quality of life (QoL) and self-ratedhealth (SRH) were assessed on a 10-point scale(Ladder scale) and a five-point scale,respectively. Gender-based comparison revealedthat, for both males and females, first-yearuniversity students' average perceived QoL waslower than that of their working counterparts(p < 0.0001 in all instances). A higherproportion of students than expected ratedtheir health as ``average' or as ``low'(p < 0.0001). Perceived QoL was significantlycorrelated with SRH in both groups. Differencesin perceived QoL and SRH exist between studentsand their full-time working peers, and thedeterminants of these differences deservesgreater attention. Knowledge of thedeterminants of SRH and perceived QoL amonguniversity students might then be translatedinto sound and effective public-health practiceand intervention programs.     

Stability and Sensitivity in Perceived Quality of Life Measures: Some Panel Results

The aim of this study was to test a fundamental assumption concerning 27 of the most frequently used measures to assess aspects of the quality of people’s lives, e.g., measures concerning happiness, satisfaction with life as a whole, with the quality of one’s life, with domains of life (job, marriage, friendships), and with perceived gaps between what one has compared to what one wants, what one’s neighbor has and so on. The assumption is that such measures are sensitive to changes in the circumstances of one’s life measured by self-perceptions of change and by self-assessments of the net balance of salient positive and negative events one has experienced in some specified period of time. A total of 462 residents of British Columbia distributed across 3 different panels completed mailed-out questionnaires at 3 points in time in 2005, 06 and 07. Among other things, we found that measuring year-by-year changes in respondents’ life circumstances by reports of their own perception and experienced life events, on average the values of the 27 variables changed in ways that were consistent with respondents’ reported changes in 49.7% of the cases examined. The success rate of the assumption using self-perceptions of change (61.7%) was much higher than the success rate using a net balance of experienced events (37.3%).     

Health,Quality of Care and Quality of Life: A Case of Frail Older Adults

This study explores the relationship between health, quality of care of geriatric case management and quality of life for the purpose of furthering the understanding of the relationship between quality of life and geriatric case management. Using survey data from a group of frail older adults, this study assesses the relative merit of two mediation hypotheses: one considering health as a mediator for quality of care of geriatric case management and quality of life, and the other considering quality of care of geriatric case management as a mediator for health and quality of life. The study findings show that quality of care of geriatric case management, measured by client satisfaction, was not a mediator between health and quality of life (measured by life satisfaction). There was a significant positive association between quality of care of geriatric case management and quality of life. Although the significant association between quality of care of geriatric case management and quality of life could not be mediated by either self-rated health or self-reported physical activity levels, it was completely mediated by health satisfaction. These findings provided preliminary empirical evidence to support a significant relationship between quality of care of geriatric case management and quality of life.     

Education and Physical Health Trajectories in Later Life: A Comparative Study

The cumulative (dis)advantage hypothesis states that health disparities between education groups increase with age. The present study examined this hypothesis in a comparative analysis of the United States, the United Kingdom, the Netherlands, and Sweden. These countries offer sharp contrasts in the social conditions that may intensify or inhibit processes of cumulative (dis)advantage. Using harmonized panel data from the HRS, ELSA, and SHARE, the study applied Poisson multilevel regression models to trace changes in the number of chronic conditions and functional limitations of people aged 50–76 (N = 16,887 individuals; 71,154 observations). The four countries showed a clear gradient in levels of physical health and in the extent to which health trajectories were shaped by education. Across all ages and cohorts, health problems were most prevalent in the United States, less prevalent in the United Kingdom and the Netherlands, and least prevalent in Sweden. A similar cross-national gradient was found for the size of health gaps between education groups and for the extent to which these gaps widened with age. Gaps were largest in the United States, smaller in the United Kingdom and in the Netherlands, and smallest in Sweden.     

Using Perceived Health to Test the Construct-related Validity of Global Quality of Life

Quality of life (QOL) is considered as aglobal, yet unidimensional, subjectiveassessment of one's satisfaction with life. Weexamine the construct validity of the availableindicators of global QOL by constructing acausal model in which QOL is viewed as causallyresponding to several dimensions of perceivedhealth. Global QOL is measured with fiveindicators derived from the literature, andperceived health is measured by eightdimensions of the SF-36 Health Survey. Thestructural equation model describes the QOL andperceived health assessments of 306 coronaryartery bypass graft (CABG) patients andprovides a stringent test of theunidimensionality of the global QOL indicators.The evidence regarding QOL is worrisome, butnot devastating. The acceptable model fit wasachieved by introducing direct effects leadingfrom the General Health Perceptions concept totwo of the five indicators of global QOL. Thissuggests that there are some mechanisms thatinfluence these indicators without firstaltering QOL, or that these indicators are notresponding in unison to QOL. Furthermore, theFaces QOL indicator required measurement errorcorrelations to two of the perceived healthindicators. This also suggests that there aremechanisms beyond pure QOL that act upon thisindicator. But the problematic effects anderror correlations are modest, so the evidenceagainst these indicators is not particularlystrong. Overall, the Self-Anchoring StrivingScale (SASS) indicator and the Life-as-a -Wholeindicator (from Multiple Discrepancies Theory)seem to be the cleanest indicators of globalQOL. General health perceptions and perceivedmental health both influenced global QOL, whilethe other six health perception concepts had noconsistent impact on global QOL.     

The Relative Contribution of Health Status and Quality of Life Domains in Subjective Health in Old Age

To analyze the influence of different health status dimensions and quality of life (QoL) domains on older adults’ subjective health, and to assess the role that residential satisfaction plays in these relationships. A QoL survey was conducted on a representative sample of the community-dwelling older adult population in Madrid province (Spain). Logistic regression models were applied to studying: the health status dimensions associated with satisfaction with health; the relationship between satisfaction with health and other QoL domains; and, the influence of these domains on satisfaction with life. Sociodemographic and residential characteristics were included in all the models. The determinants of satisfaction with health in the first model were: mobility, usual activities, morbidity, and satisfaction with neighborhood. QoL domains associated with health were: leisure activities, neighborhood, and finances. Satisfaction with life was explained by these three domains, along with age, family and health. In sum, leisure, neighborhood, and finances showed a positive effect on satisfaction with health and with life.     

老年人口健康生活质量评价原则的探讨

老年人口健康生活质量的评价是社会养老保障决策过程中的重要依据之一。目前 ,尽管各国都进行了许多有关的评价研究 ,但老年人口生活质量的评价还没有较成熟的权威性量表 ,各种方法各有利弊。本文结合传统的老年人健康状态和功能评价 ,以及老年人口的特点 ,探讨了老年人健康状态和功能评价的思路和内容     

The Use of the Shye's Systemic Quality Life Model in the Examination of Child Protection Officers Decision

The paper presents the results of a systematicstudy of the factors that child protectionofficers consider in their decisions of whetheror not to remove children at risk from theirhomes. A sample of 194 child protectionofficers in Israel completed a questionnaireconstructed on the basis of Shye's SystemicQuality of Life Model (1979, 1985), which tapsthe psychological, physical, social, andcultural dimensions of the quality of life.Questions were answered on 368 children fairlyevenly divided between those they decided toremove from home and those they decided to keepat home. The findings show 85% of the decisions werecorrectly classified on the basis of the model,and show close associations between the qualityof life dimensions and the decisions. Theworkers evaluated both the current quality oflife and their parents' enabling good qualityof life as higher among the children whom theyrecommended keeping at home than among thosethey recommended removing. Similarly, theypredicted that the children they recommendedremain would have a higher quality of life athome in the future than those they recommendedbe removed. The psychological dimension of thequality of life contributed more to thedecision than the physical, and these more thanthe social and cultural.     

Investigating Health Selection Within Mexico and Across the US Border

Despite acquiring lower levels of attainment and earnings, Mexican immigrants exhibit favorable health outcomes relative to their native-born counterparts. And while scholars attempt to reconcile this so-called paradoxical relationship with a variety of theoretical and empirical approaches, patterns of selective migration continue to receive considerable attention. The present study contributes to the literature on health selection by extending the healthy migrant hypothesis in a number of ways. First, we rely on a unique combination of datasets to assess whether the healthy are disproportionately more likely to migrate. We use the latest wave of the Mexican Family Life Survey and the 2013 Migrante Study, a survey that is representative of Mexican-born persons who are actively migrating through Tijuana. Pooling these data also allow us to differentiate between internal and US-bound migrants to shed light on their respective health profiles. Results provide modest support for the healthy migrant hypothesis. Although those who report better overall health are more likely to migrate, we find that the presence of certain chronic conditions increases migration risk. Our findings also suggest that internal migrants are healthier than those traveling to the US, though this is largely because those moving within Mexico reflect a younger and more educated population. This study takes an important step in uncovering variation across migrant flows and highlights the importance of the timing at which health is measured in the migration process.