Does socio-economic advantage lead to a longer, healthier old age?

A growing divide: Trends in social inequalities in healthy longevity in Australia, 2001-20

This study examines two decades of change in social inequalities in life and health expectancy among older adults in Australia, one of the few countries that escaped an economic recession during the global financial crisis. We compare adults aged 45+ across three measures of individual socio-economic position-education, occupation, and household wealth-and use multistate life tables to estimate total life expectancy (TLE) and life expectancy free of limiting long-term illness (LLTI-free LE) based on 20 waves of the Household, Income and Labour Dynamics in Australia Survey (2001-20). Our findings highlight substantial social disparities in both TLE and LLTI-free LE in Australia. Grouping individuals by household wealth shows striking differentials in LLTI-free LE. We observe widening social disparities in healthy longevity over time by all three measures of socio-economic position. This diverging trend in healthy longevity is troubling against the backdrop of widening income and wealth inequalities in Australia.

Spatial heterogeneity of human lifespan in relation to living environment and socio-economic polarization: a case study in the Beijing-Tianjin-Hebei region, China

The spatial heterogeneity and influence factors of public lifespan have been reported worldwide at the national level or typical longevous areas. However, few sub-national studies considering the living environment and socio-economic level together have been explored in the imbalanced developed region with a huge population base and deteriorated air quality. In this paper, spatial heterogeneity of lifespan integrating environment and socio-economic influence factors was investigated in the Beijing-Tianjin-Hebei (BTH) region of China using geographically weighted regression (GWR). Five indicators were constructed to determine the lifespan based on the three national censuses (1990-2010) in the BTH region. The results showed that the areas with higher CH (centenarians per 100,000 inhabitants) and centenarity index (CI) exhibited changing distribution in the BTH region, whereas those with lower CH and CI and extreme value of the ultra-octogenarian index (UOI) and LI (> 90/ > 65) maintained a relatively stable feature through time. But as lifespan indicators increase overall, the differences between the counties/districts widen. Furthermore, remarkable spatial heterogeneity was detected for the associations between the significant environmental and socio-economic variables and lifespan indicators. Although the natural geographic condition (altitude) still exhibited a negative influence on the longevity of the population, the socio-economic factors (GDP_pc and income level) showed a more dominant influence on the extension of the elderly and longevity population. Correspondingly, the widened unbalance of population lifespan (UOI, LI, CH) was considered closely related to the socio-economic polarization, and the adverse effects of air pollution on life expectancy at birth (LEB) have also emerged. To further improve the overall lifespan level and narrow the lifespan gap in the BTH region, future work on cleaner air and more balanced development is still needed.

Age, Education, and Stress Affect Ageing Males' Symptoms More than Lifestyle Does: The Wroclaw Male Study

An increasing number of subjects are affected by health problems related to the advanced involutional processes. It is extremely important to identify the determinants of the rate of occurrence of physiological, psychological, and social manifestations of aging. The aim was to determine how factors such as lifestyle, level of education, or severity of stressful life events indicate the appearance of aging symptoms in adult men. The material consisted of data of ethnically homogeneous group of 355 men (32−87 years), invited to the study as a part of the Wroclaw Male Study research project. The analyzed features included (1) socioeconomic status: age, educational level, marital status, and having children; (2) elements of lifestyle: alcohol drinking, cigarette smoking, and physical activity; (3) major and most important stressful life events—the Social Readjustment Rating Scale; (4) symptoms related to male aging—the Aging Males’ Symptoms. The backward stepwise regression models, the Kruskal−Wallis test, and multiple comparisons of mean ranks were used. Noncentrality parameter δ (delta), two-tailed critical values of the test, and test power with α = 0.05 were calculated. Among the analyzed variables, age was most strongly associated with the intensity of almost all groups of andropausal symptoms in men (p = 0.0001), followed by the level of education (p = 0.0001) and the intensity of stressful life events (p = 0.0108). Selected lifestyle elements turned out to be much less important (p > 0.01). Preventive actions aimed at slowing down the intensification of involutional processes, including teaching strategies for coping with stressful life events, should be implemented in groups of men with specific risk factors from an early age.

Social Determinants of Remaining Life Expectancy at Age 60: A District-Level Analysis in Germany

Remaining life expectancy at age 60 (in short: RLE) is an important indicator of the health status of a population's elders. Until now, RLE has not been thoroughly investigated at the district level in Germany. In this study we analyzed, based on recent publicly available data (2015-2017), and for men and women separately, how large the RLE differences were in Germany across the 401 districts. Furthermore, we examined a wide range of potential social determinants in terms of their bivariate and multivariate (i.e., partial) impact on men's and women's RLE. Men's district-level RLE ranged between 19.89 and 24.32 years, women's district-level RLE between 23.67 and 27.16 years. The best single predictor both for men's and women's RLE at district level was 'proportion of employees with academic degree' with standardized partial regression coefficients of 0.42 (men) and 0.51 (women). Second and third in rank were classic economic predictors, such as 'household income' (men), 'proportion of elder with financial elder support' (women), and 'unemployment' (men and women). Indicators expressing the availability of medical services and staffing levels of nursing homes and services had at best a marginal partial impact. This study contributes to the growing body of evidence that a population's educational level is a decisive determinant of population health resp. life expectancy in contemporary industrialized societies.

On the measurement of healthy lifespan inequality

Background

Current measures to monitor population health include indicators of (i) average length-of-life (life expectancy), (ii) average length-of-life spent in good health (health expectancy), and (iii) variability in length-of-life (lifespan inequality). What is lacking is an indicator measuring the extent to which healthy lifespans are unequally distributed across individuals (the so-called ‘healthy lifespan inequality’ indicators).

Methods

We combine information on age-specific survival with the prevalence of functional limitation or disability in Spain (2014–2017) by sex and level of education to estimate age-at-disability onset distributions. Age-, sex- and education-specific prevalence rates of adult individuals’ daily activities limitations were based on the GALI index derived from Spanish National Health Surveys held in 2014 and 2017. We measured inequality using the Gini index.

Results

In contemporary Spain, education differences in health expectancy are substantial and greatly exceed differences in life expectancy. The female advantage in life expectancy disappears when considering health expectancy indicators, both overall and across education groups. The highly educated exhibit lower levels of lifespan inequality, and lifespan inequality is systematically higher among men. Our new healthy lifespan inequality indicators suggest that the variability in the ages at which physical daily activity limitations start are substantially larger than the variability in the ages at which individuals die. Healthy lifespan inequality tends to decrease with increasing educational attainment, both for women and for men. The variability in ages at which physical limitations start is slightly higher for women than for men.

Conclusions

The suggested indicators uncover new layers of health inequality that are not traceable with currently existing approaches. Low-educated individuals tend to not only die earlier and spend a shorter portion of their lives in good health than their highly educated counterparts, but also face greater variation in the eventual time of death and in the age at which they cease enjoying good health—a multiple burden of inequality that should be taken into consideration when evaluating the performance of public health systems and in the elaboration of realistic working-life extension plans and the design of equitable pension reforms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12963-021-00279-8.

Spatiotemporal trends in life expectancy and impacts of economic growth and air pollution in 134 countries: A Bayesian modeling study

Life expectancy (LE) varies across countries in space and time, and economic growth and air pollution are two important influence factors to LE. This study mainly aims to investigate spatiotemporal trends in LE in 134 countries from 1960 to 2016 by using Bayesian spatiotemporal modeling. Further, the relations between per capita gross domestic product (GDP_pc) and population-weighted fine particulate matter (pwPM_2.5) and LE are investigated from a global perspective from 1998 to 2016 by using the Bayesian regression model. The results illustrated the heterogeneity of spatiotemporal trends in LE globally. Specifically, Africa and South-East Asia show much lower LE levels, and the Americas, European, and Western Pacific exhibit a relatively higher LE level compared to the overall level. The countries with low overall levels of LE show a relatively stronger upward trend than the overall upward trend and vice versa. In addition, this study demonstrates that the spatial differences in effects of influence factors on LE in the six WHO regions in the 134 countries. Africa shows the highest positive regression coefficient of GDP_pc and lowest negative regression coefficient of pwPM_2.5 on LE than other regions in the world. Furthermore, it shows the complexity of the interaction between economic growth and air pollution on LE across six WHO regions. Our findings suggest the public policies to reduce the health damage caused by air pollution, especially in Africa, Eastern Mediterranean, and Europe where the pwPM_2.5 negatively affect the LE benefits from economic growth.

Geographical socioeconomic inequalities in healthy life expectancy in Japan, 2010-2014: An ecological study

Background

Area differences in life expectancy (LE) and healthy life expectancy (HLE) in large geographical units have been monitored around the world. Area characteristics may be based on culture, history, socioeconomic status and discrimination in smaller geographical units, so it is important to consider these when looking at health inequality. We aimed to evaluate LE, HLE, and non-healthy life expectancy (NHLE) in 1707 municipalities using Areal Deprivation Index (ADI) in Japan for the first time.

Methods

We calculated the observed LE, HLE, and NHLE using death, population, and Long-term care insurance data for 2010-2014 and applied the variance weighted least squares model to estimate LE, HLE, and NHLE by 100 percentiles using the standardized ADI.

Findings

The estimated LE, HLE, and NHLE became lower as the deprivation index worsened: the differences between the most and least deprived areas for HLE were 2·49 years for LE and 2·32 years for HLE in males; 1·22 years for LE and 0·93 years for HLE in females. The observed LE and HLE in the most deprived areas were much lower than other areas.

Interpretation

Using ADI has enabled us to see the disparity within municipalities precisely. LE and HLE outlier for the 100th percentile might be linked to historical areal deprivation and marginalization. Precise monitoring of socioeconomic status-based health inequalities could help manage these inequalities by identifying the groups most in need of intervention.

Funding

The Ministry of Education, Science and Culture of Japan (a Grant-in-Aid for Scientific Research [A] No. 20H00040 and 18H04071).

Healthy ageing for all? Comparisons of socioeconomic inequalities in health expectancies over two decades in the Cognitive Function and Ageing Studies I and II

Background

Despite increasing life expectancy (LE), cross-sectional data show widening inequalities in disability-free LE (DFLE) by socioeconomic status (SES) in many countries. We use longitudinal data to better understand trends in DFLE and years independent (IndLE) by SES, and how underlying transitions contribute.

Methods

The Cognitive Function and Ageing Studies (CFAS I and II) are large population-based studies of those aged ≥65 years in three English centres (Newcastle, Nottingham, Cambridgeshire), with baseline around 1991 (CFAS I, n = 7635) and 2011 (CFAS II, n = 7762) and 2-year follow-up. We defined disability as difficulty in activities of daily living (ADL), dependency by combining ADLs and cognition reflecting care required, and SES by area-level deprivation. Transitions between disability or dependency states and death were estimated from multistate models.

Results

Between 1991 and 2011, gains in DFLE at age 65 were greatest for the most advantaged men and women [men: 4.7 years, 95% confidence interval (95% CI) 3.3–6.2; women: 2.8 years, 95% CI 1.3–4.3]. Gains were due to the most advantaged women having a reduced risk of incident disability [relative risk ratio (RRR):0.7, 95% CI 0.5–0.8], whereas the most advantaged men had a greater likelihood of recovery (RRR: 1.8, 95% CI 1.0–3.2) and reduced disability-free mortality risk (RRR: 0.4, 95% CI 0.3–0.6]. Risk of death from disability decreased for least advantaged men (RRR: 0.7, 95% CI 0.6–0.9); least advantaged women showed little improvement in transitions. IndLE patterns across time were similar.

Conclusions

Prevention should target the most disadvantaged areas, to narrow inequalities, with clear indication from the most advantaged that reduction in poor transitions is achievable.

Biases in health expectancies due to educational differences in survey participation of older Europeans: It's worth weighting for

Health expectancies are widely used by policymakers and scholars to analyse the number of years a person can expect to live in good health. Their calculation requires life tables in combination with prevalence rates of good or bad health from survey data. The structure of typical survey data, however, rarely resembles the education distribution in the general population. Specifically, low-educated individuals are frequently underrepresented in surveys, which is crucial given the strong positive correlation between educational attainment and good health. This is the first study to evaluate if and how health expectancies for 13 European countries are biased by educational differences in survey participation. To this end, calibrated weights that consider the education structure in the 2011 censuses are applied to measures of activity limitation in the Survey of Health, Ageing and Retirement in Europe. The results show that health expectancies at age 50 are substantially biased by an average of 0.3 years when the education distribution in the general population is ignored. For most countries, health expectancies are overestimated; yet remarkably, the measure underestimates health for many Central and Eastern European countries by up to 0.9 years. These findings highlight the need to adjust for distortion in health expectancies, especially when the measure serves as a base for health-related policy targets or policy changes.

Who Initiates the Help Older Parents Give to Midlife Children

OBJECTIVES

Older parents continue to help children after these children have been adults for decades. We utilize a typology approach to assess who initiates the help. We ask whether profiles of help initiation are associated with how often older parents help and how they evaluate their helping behaviors.

METHODS

Older parents (N = 241; Mage = 80.12) indicated the extent to which they volunteered to help children and helped per child's request. Parents reported their resources and obligation to help, child problems, frequency, and evaluation (rewards/stresses) of helping.

RESULTS

Latent profile analysis reveals four profiles representing parents who are initiators (n = 65), responders (n = 56), initiators/responders (n = 50), and uninvolved (n = 69). Resources, needs, and individual beliefs differentiate profiles. Parents offer the same amount of help regardless of who initiates such help. Parents who are initiators/responders view helping as more rewarding than parents who are initiators and more stressful than uninvolved parents.

DISCUSSION

This study reveals variation in the initiation of older parents' help and refines our understanding of family help in late life. Findings may suggest a parental expectation for children to be competent in adulthood regardless of their resources and willingness to help.

Occupational inequality in health expectancy in Denmark

Background: The pension age in Denmark is adjusted in line with projected increasing life expectancy without taking health differentials between occupational groups into account. The purpose was to study occupational disparities in partial life expectancy and health expectancy between the ages of 50 and 75. Methods: Register data on occupation and mortality were combined with data from the Danish part of Survey of Health, Ageing and Retirement in Europe in 2010–2014 ( N=3179). Expected lifetime without and with activity limitations and without and with long-term illness was estimated by Sullivan’s method and comparisons made between four occupational groups. Results: We found clear differences between occupational groups. Expected lifetime without activity limitations between the ages of 50 and 75 was about 4.5 years longer for men and women in high skilled white-collar occupations than for men and women in low skilled blue-collar occupations. Men in high skilled blue-collar and low skilled white-collar occupations could expect 2.3 and 3.8 years shorter lifetimes without activity limitations, respectively, than men in high skilled white-collar occupations. For women in low skilled white-collar occupations, lifetime without activity limitations was 2.6 years shorter than for women in high skilled white-collar occupations. Due to few observations, no results were obtained for women in the high skilled blue-collar group. The social gradient was also significant when health was measured by years without long-term illness. Conclusions: The results support implementation of a flexible pension scheme to take into account the health differentials between occupational groups.

Socioeconomic differences in healthy and disease-free life expectancy between ages 50 and 75: a multi-cohort study

Background

There are striking socioeconomic differences in life expectancy, but less is known about inequalities in healthy life expectancy and disease-free life expectancy. We estimated socioeconomic differences in health expectancies in four studies in England, Finland, France and Sweden.

Methods

We estimated socioeconomic differences in health expectancies using data drawn from repeated waves of the four cohorts for two indicators: (i) self-rated health and (ii) chronic diseases (cardiovascular, cancer, respiratory and diabetes). Socioeconomic position was measured by occupational position. Multistate life table models were used to estimate healthy and chronic disease-free life expectancy from ages 50 to 75.

Results

In all cohorts, we found inequalities in healthy life expectancy according to socioeconomic position. In England, both women and men in the higher positions could expect 82–83% of their life between ages 50 and 75 to be in good health compared to 68% for those in lower positions. The figures were 75% compared to 47–50% for Finland; 85–87% compared to 77–79% for France and 80–83% compared to 72–75% for Sweden. Those in higher occupational positions could expect more years in good health (2.1–6.8 years) and without chronic diseases (0.5–2.3 years) from ages 50 to 75.

Conclusion

There are inequalities in healthy life expectancy between ages 50 and 75 according to occupational position. These results suggest that reducing socioeconomic inequalities would make an important contribution to extending healthy life expectancy and disease-free life expectancy.

Socio-Economic Inequalities in Life Expectancy and Health Expectancy at Age 50 and over in European Countries

Abstract Based on the demographic ageing, many European governments have modified the statutory retirement age. However, in general, life expectancy (LE) and health expectancy (HE) are not uniformly distributed, being both lower among the least advantaged groups. Thus, a systematic search and review of the literature has been conducted to identify socioeconomic inequalities in LE and HE at age 50 and over in European countries. Twenty-nine studies were included in the review. Across Europe, people in a more advantaged position can expect to live longer, more years in good health and less in bad health, and therefore a lower percentage of their lives in bad health. Zusammenfassung: Sozioökonomische Ungleichheiten in der Lebens- und Gesundheitserwartung im Alter von 50 und älter in Europäischen Ländern. Erkenntnisse für die Debatte der Rentenpolitik Vor dem Hintergrund der demographischen Alterung haben viele europäische Regierungen das Renteneintrittsalter modifiziert. Allerdings sind Lebensund Gesundheitserwartungen nicht gleichmäßig verteilt, sondern sind in benachteiligten Bevölkerungsgruppen niedriger. Um sozioökonomische Ungleichheiten in der Lebens- und Gesundheitserwartung von Individuen im Alter von 50 Jahren und älter zu betrachten, wurde eine systematische Suche und Begutachtung der Literatur in den europäischen Ländern durchgeführt. Es wurden 29 Studien in der Begutachtung miteinbezogen. Es zeigt sich, dass Individuen in vorteilhaften Positionen erwarten können länger zu leben, länger gesund zu sein und weniger häufig einen schlechten Gesundheitszustand aufweisen, was der Grund dafür ist, dass sie auch einen geringeren Anteil ihrer Lebenszeit in schlechter Gesundheit verbringen.

Revisiting Mobility Limitations of Seniors in Singapore, 1995 to 2011

Singapore’s life expectancy at birth and at age 65 continues to improve. Although this is a positive development, it is necessary to understand how much of this increased life expectancy is spent with and without mobility limitations. This research uses the latest round of the National Survey of Senior Citizens to examine the situation in 2011 and the possible changes that may have occurred since the last survey in 2005. It seeks to add to earlier research in this area in Singapore and uses the prevalence-based Sullivan method to calculate lifetime free of mobility limitations for this population. Pertinent conclusions drawn from this research include evidence pointing to changing prevalence rates among the older adult population and observations that suggest the possibility of a compression of morbidity for this population in 2011 compared with an expansion of morbidity observed in the previous survey conducted in 2005. The research also shows that women continue to be disadvantaged as they age compared with men.

Retirement and perceived social inferiority strongly link with health inequalities in older age: decomposition of a concentration index of poor health based on Polish cross-sectional data

Background

Identifying mechanisms that generate and sustain health inequalities is a prerequisite for developing effective policy response, but little is known about factors contributing to health inequalities in older populations in post-transitional European countries such as Poland. Demographic aging of all populations requires new and deeper insights.

Methods

Data came from the Polish edition of the cross-sectional European Social Survey, Wave 6 (2012). Logistic regression was applied to identify socioeconomic factors relevant to self-assessed health in a population aged 45 or over. Decomposition of a concentration index provided information about the distribution of health-relevant demographics and social characteristics along a socioeconomic continuum, and their contributions to observed health inequalities.

Results

Overall, 17.4 % of respondents aged 45 or over assessed their health as poor or very poor. Predictors of poor health included income insufficiency, disability or retirement, retirement, low social activity, and social position. A steep socioeconomic gradient in self-assessed health in Polish population was found. The primary contributor to the observed health inequality (as summarized by concentration index) was income, followed by labor market situation, particularly retirement. Self-assessed place in society contributed to overall inequality, scoring similarly to social activity. Contributions from age and education were moderate but non-significant, gender was negligible, and chronological aging explained neither poor health nor socioeconomic health inequalities.

Conclusions

Although elderly people represent a particularly vulnerable group, their disadvantages are associated with social rather than natural causes. Policies addressing health inequalities in aging populations must provide systemic opportunities for maintaining good health. Transitioning to retirement is a critical entry point for policy action that stimulates social engagement and maintains self-esteem of older people.

Socioeconomic determinants of health inequalities among the older population in India: a decomposition analysis

This study quantified and decomposed health inequalities among the older population in India and analyzes how health status varies for populations between 60 to 69 years and 70 years and above. Data from the 60th round of the National Sample Survey (NSS) was used for the analyses. Socioeconomic inequalities in health status were measured by using Concentration Index (CI) and further decomposed to find critical determinants and their relative contributions to total health inequality. Overall, CI estimates were negative for the older population as a whole (CI = -0.1156), as well as for two disaggregated groups, 60 to 69 years (CI = -0.0943) and 70 years and above (CI = -0.08198). This suggests that poor health status is more concentrated among the socioeconomically disadvantaged older population. Decomposition analyses revealed that poor economic status (54 %) is the dominant contributor to total health inequalities in the older population, followed by illiteracy (24 %) and rural place of residence (20 %). Other indicators, such as religion, gender and marital status were positive, while Caste was negatively associated with health inequality in the older populations. Finally, a comparative assessment of decomposition results suggest that critical contributors for health inequality vary for the older population of 60 to 69 years and 70 years and above. These findings provide important insights on health inequalities among the older population in India. Implications are advanced.

A Systematic Literature Review of Studies Analyzing Inequalities in Health Expectancy among the Older Population

Aim

To collect, organize and appraise evidence of socioeconomic and demographic inequalities in health and mortality among the older population using a summary measure of population health: Health Expectancy.

Methods

A systematic literature review was conducted. Literature published in English before November 2014 was searched via two possible sources: three electronic databases (Web of Science, Medline and Embase), and references in selected articles. The search was developed combining terms referring to outcome, exposure and participants, consisting in health expectancy, socioeconomic and demographic groups, and older population, respectively.

Results

Of 256 references identified, 90 met the inclusion criteria. Six references were added after searching reference lists of included articles. Thirty-three studies were focused only on gender-based inequalities; the remaining sixty-three considered gender along with other exposures. Findings were organized according to two leading perspectives: the type of inequalities considered and the health indicators chosen to measure health expectancy. Evidence of gender-based differentials and a socioeconomic gradient were found in all studies. A remarkable heterogeneity in the choice of health indicators used to compute health expectancy emerged as well as a non-uniform way of defining same health conditions.

Conclusions

Health expectancy is a useful and convenient measure to monitor and assess the quality of ageing and compare different groups and populations. This review showed a general agreement of results obtained in different studies with regard to the existence of inequalities associated with several factors, such as gender, education, behaviors, and race. However, the lack of a standardized definition of health expectancy limits its comparability across studies. The need of conceiving health expectancy as a comparable and repeatable measure was highlighted as fundamental to make it an informative instrument for policy makers.

Evaluating access to primary health care among older women and men in Barbados using preventable hospitalization

We evaluated access to primary health care for older women and men in Barbados, a developing country, using a widely accepted access indicator, hospitalization for ambulatory care sensitive conditions. Using 2003-2008 data, we calculated gender-specific total annual population-based rates of these hospitalizations per 1,000 older women and men and individual rates for the six most prevalent conditions. Across the 6 years, these hospitalizations increased 33.6% for women, 30.6% for men (both P < .0001). However, the average rate for diabetes fell 32% for women, 36% for men. Findings suggest an opportunity to improve access to primary health care, particularly for older women.

Expansion of morbidity: trends in healthy life expectancy of the elderly population

Objective: to analyze the changes in life expectancy (LE) and disability-free life expectancy (DFLE) in São Paulo's elderly population to assess the occurrence of compression or expansion of morbidity, between 2000 and 2010. Methods: cross-sectional and population survey, based on official data for the city of São Paulo, Brazil, and data obtained from the Health, Well-Being and Aging Survey (SABE). Functional disability was defined as difficulty in performing at least one basic activity of daily living. The Sullivan method was used to calculate LE and DFLE for the years 2000 to 2010. Results: from 2000 to 2010, there was an increase in disabled life expectancy (DLE) in all age groups and both sexes. The proportion of years of life free of disability, at 60 years of age, decreased from 57.94% to 46.23% in women, and from 75.34% to 63.65% in men. At 75 years of age, this ratio decreased from 47.55% to 34.54% in women, and from 61.31% to 56.01% in men. Conclusion: the expansion of morbidity is an ongoing process in the elderly population of the municipality of São Paulo, in the period of 2000-2010. These results can contribute to the development of preventive strategies and planning of adequate health services to future generations of seniors.

Effect of the elimination of chronic diseases on disability-free life expectancy among elderly individuals in Sao Paulo, Brazil, 2010

The scope of this study was to establish whether the elimination of certain chronic diseases is capable of leading to the compression of morbidity among elderly individuals in Sao Paulo (Brazil), 2010. A population-based, cross-sectional study was carried out with official data for the city of Sao Paulo (Brazil) in 2010 and data from the SABE (Health, Wellbeing and Ageing) study. A total of 907 elderly individuals were evaluated, 640 of whom were women (64.6%). Sullivan's method was used for the calculation of disability-free life expectancy (DFLE). Life tables for cause elimination were used to calculate the probabilities of death with the elimination of health conditions. In absolute terms, the gains in LE and DFLE were greater in the younger age group (60 to 74 years) in both genders. In relative terms (%DFLE in LE), the gains were higher among women aged 75 years or older and among men aged 60 years. If eliminated, heart disease was the condition that would most lead to the compression of morbidity in both genders. The elimination of chronic diseases from the elderly population could lead to a compression of morbidity in men and women at both 60 years of age and 75 years of age or older.

A study of air pollutants influencing life expectancy and longevity from spatial perspective in China

Life expectancy and longevity are influenced by air pollutants and socioeconomic status, but the extend and significance are still unclear. Better understanding how the spatial differences of life expectancy and longevity are affected by air pollutants is needed for generating public health and environmental strategies since the whole of China is now threatened by deteriorated air quality. 85 major city regions were chosen as research areas. Geographically Weighted Regression (GWR) and Stepwise Regression (SR) were used to find the spatial correlations between health indicators and air pollutants, adjusted by per capita GDP(1). The results were, regions with higher life expectancy were mainly located in the east area and areas with good air quality, a regional difference of 10 μg/m(3) in ambient air SO2(2) could cause adjusted 0.28 year's difference in life expectancy, a regional difference of 10 μg/m(3) in ambient air PM10(3) could lead to a longevity ratio difference of 2.23, and per capita GDP was positively associating with life expectancy but not longevity ratio, with a regional difference of 10,000 RMB(4) associating with adjusted 0.49 year's difference in life expectancy. This research also showed the evidences that there exist spatially differences for ambient air PM10 and SO2 influencing life expectancy and longevity in China, and this influences were clearer in south China.

Predicting fat-free mass index and sarcopenia in assisted-living older adults

Age-related muscle loss, termed sarcopenia, has been linked to functional deficits and an increased risk of falling. Such risk is of alarming concern due to the high disability and mortality rates associated with falling in older adults. Our laboratory recently developed a prediction model for fat-free mass index (FFMI) and, subsequently, sarcopenia within a community-dwelling older adult population using functional measures that are easily accessible to clinicians. The purpose of this study was to (1) determine how our prediction model performed in an older and less mobile assisted-living population, and if performance of the model was poor; (2) to improve and modify our previous prediction model using data acquired from this unique population. Forty assisted-living older adults (10 males) aged 86.1 ± 6.2 years participated in the study. Each completed four questionnaires to examine their mental and physical health status and anxiety levels related to falling. Anthropometric, balance, strength, and gait tests were conducted. Fat-free mass values, determined by bioelectrical impedance analysis, were normalized by height to obtain FFMI. Using an algorithm proposed by the European Working Group on Sarcopenia in Older People, FFMI along with grip strength and gait speed were used to identify sarcopenic individuals. FFMI was significantly correlated with sex, body mass index (BMI), circumference measures, handgrip strength, gait velocity, and measures of gait variability. The percentage of the variable variation explained by our previous model was reduced for a population of assisted-living older adults (R(2) of 0.6744 compared to the reported R(2) of 0.9272 for community-dwelling older adults; McIntosh et al. Age (Dordrecht, Netherlands), 2013). The prediction equation that accounted for the greatest variability of FFMI for the assisted living group included the independent variables of forearm circumference, BMI, handgrip strength, and variability of the double support time during gait (adjusted R(2) = 0.7950). This prediction model could be used by clinicians working in an assisted-living facility to identify individuals with reduced muscle mass and, once identified, aid with the planning and implementation of appropriate intervention strategies to attenuate the progression of additional muscle loss and improve quality of life.

Using mortality follow-up of surveys to estimate social inequalities in healthy life years

BACKGROUND

The estimation of healthy life years (HLY) by socio-economic status (SES) requires two types of data: the prevalence of activity limitation by SES generally extracted from surveys and mortality rates by SES generally derived from a linkage between the SES information in population databases (census, register) and mortality records. In some situations, no population-wide databases are available to produce mortality rates by SES, and therefore some alternatives must be explored. This paper assesses the validity of calculating HLY by SES using mortality rates derived from a linkage between surveys and mortality records.

METHODS

TWO SURVEYS WERE CHOSEN TO EXPLORE THE VALIDITY OF THE PROPOSED APPROACH: The Belgian Health Interview Survey (HIS) and the Belgian Survey on Income and Living Conditions (SILC). The mortality follow-up of these surveys were used to calculate HLY by educational level at age 25. These HLY were compared with HLY estimates calculated using the mortality follow-up of the 2001 census. The validity of this approach was evaluated against two criteria. First, the HLY calculated using the census and those calculated using the surveys must not be significantly different. Second, survey-based HLY must show significant social inequalities since such inequalities have been consistently reported with census-based HLY.

RESULTS

Both criteria were met. First, for each educational category, no statistically significant difference was found when comparing census-based and survey-based HLY estimates. For instance, men in the lowest educational category have shown a HLY of 34 years according to the HIS, and while this figure was 35.5 years according to the census, this difference was not statistically significant. Second, the survey-based HLY have shown a significant social gradient. For instance, men in the highest educational category are expected to live 9.5 more HLY than their counterparts in the lowest educational category based on the HIS estimates, compared with 7.3 HLY based on the census estimates.

CONCLUSIONS

This article suggests that using the mortality follow-up of a nationally representative cross-sectional survey is a valid approach to monitor social inequalities in HLY in the absence of population-wide data.

A transição de saúde e as mudanças na expectativa de vida saudável da população idosa: possíveis impactos da prevenção de doenças crônicas

O objetivo foi avaliar o impacto da eliminação das doenças crônicas sobre a expectativa de vida livre de incapacidade da população idosa. Estudo transversal, de base populacional, utilizando dados oficiais secundários para o Município de São Paulo, Brasil, em 2000, e dados obtidos do Estudo SABE. Tábuas de vida de eliminação de causas foram utilizadas para calcular as probabilidades de morte com a eliminação de doenças. As enfermidades eliminadas que geraram o maior aumento de expectativa de vida livre de incapacidade, para o sexo feminino, foram a doença cardíaca (em primeiro lugar), o diabetes mellitus (em segundo lugar) e a hipertensão arterial (em terceiro lugar). Já para o sexo masculino, as doenças eliminadas que geraram maior aumento de expectativa de vida livre de incapacidade foram a doença cardíaca (em primeiro lugar), a hipertensão arterial (em segundo lugar), a queda (em terceiro lugar aos 60 anos) e a doença pulmonar crônica (em terceiro lugar aos 75 anos). A classificação das doenças crônicas, segundo o impacto na expectativa de vida livre de incapacidade, poderá auxiliar no planejamento de programas de prevenção e promoção da saúde.

Ageing in the European Union

The ageing of European populations presents health, long-term care, and welfare systems with new challenges. Although reports of ageing as a fundamental threat to the welfare state seem exaggerated, societies have to embrace various policy options to improve the robustness of health, long-term care, and welfare systems in Europe and to help people to stay healthy and active in old age. These policy options include prevention and health promotion, better self-care, increased coordination of care, improved management of hospital admissions and discharges, improved systems of long-term care, and new work and pension arrangements. Ageing of the health workforce is another challenge, and policies will need to be pursued that meet the particular needs of older workers (ie, those aged 50 years or older) while recruiting young practitioners.

[Socioeconomic inequalities in the onset and progression of disability in a cohort of older people in Santiago (Chile)]

OBJECTIVE

To describe and compare socioeconomic inequalities in the onset and progression of disability in a cohort of Chilean community-dwelling older people that provides unprecedented information about this process in Chile.

METHODS

The data were drawn from a 10-year longitudinal study (2000-2010) that followed a probabilistic and representative sample of the SABE (Health, Welfare and Aging) cohort. The present study was based on 78% (1019) of the baseline sample of adults aged 60 years or more living in Santiago, Chile. Functional limitation was defined on the basis of a combination of six basic activities of daily living, seven instrumental activities, and seven mobility activities (limited, no limited). Socioeconomic position (high, medium and low) was assessed by combining measures of household equipment, wealth, and education.

RESULTS

The initial prevalence of functional limitation was 47.3% (95%CI: 44.2-50.4) with a clear socioeconomic gradient (60.1% low, 47.5% medium, and 28.7% high; p<0.001). At the end of the follow-up, older adults with low socioeconomic status remained functionally limited while those with high socioeconomic status remained non-limited. The incidence density of functional limitation also followed a socioeconomic gradient (5.33, 6.59 and 7.73 per 100 years-person for low, medium and high socioeconomic status). Social inequalities were also observed for mortality.

CONCLUSION

This study corroborates the social stratification of functional status and mortality, suggesting that aging is not a leveler of inequalities. In Latin-American countries, policies should aim to reduce inequalities by attempting to limit exposure to risk factors and to compensate for deficiencies (especially among the poorest older people) in order to prevent the progression of functional impairment to disability.

A cross-sectional study on socioeconomic status and health-related quality of life among elderly Chinese

OBJECTIVES

To examine the association between socioeconomic status (SES) and health-related quality of life (HRQOL) in a sample of elderly Chinese people in Hong Kong.

STUDY DESIGN

Cross-sectional study.

SETTING

18 elderly health centers in Hong Kong.

PARTICIPANTS

This study was based on a cohort aged 65 years or above who were enrolled in the Elderly Health Services from 1998 to 2005 in Hong Kong. Initially, 3324 individuals were randomly sampled from the baseline database. In the end, 2441 successful cases were obtained for the telephone survey. After excluding cases with missing SES or HRQOL information and the cases whose questionnaires were answered by their family members, 2347 individuals were included in the final analysis.

RESULTS

Elderly Chinese with less subjective economic hardship reported much better self-rated health (SRH) (OR 1.57-4.70, all p<0.01)< and higher Medical Outcomes Study short form (SF)12 scores (β 2.56-10.26, all p<0.01) than those with economic hardship. Male individuals in the highest education and occupation subgroup reported better HRQOL comparing with the baseline subgroup (OR for SRH 1.91-3.26, p<0.01; β 2.63-4.96, p<0.05). Two economic indicators, income and expenditure, only showed significant positive associations with physical SF12 scores for men (β 2.91-5.42, all p<0.05). Housing tenure was associated with SRH (OR 1.34 for men and 1.27 for women, p<0.05) but not SF12 scores.

CONCLUSIONS

Economic hardship showed the strongest association with HRQOL among all SES indicators. Educational level, occupational level and economic indicators tended to associate with physical HRQOL only among elderly Chinese men. More attention should be placed on subjective SES indicators when investigating influences on HRQOL among elderly Chinese people.

Measuring inequalities in health: what do we know? What do we need to know?

We argue that policy analysis aiming at curving inequalities in health calls for a better understanding of what we know about its measurement pathways. Assuming that health is a good that individuals trade off against other goods, unavoidable health inequalities result when after controlling for unavoidable factors (e.g., age and gender), differences in socioeconomic status of an individual systemically engender differences in health outcomes. However, the measurement of such inequality and underpinning reasons behind are not suggestive of a clear picture. In reviewing the literature, we conclude that it is unclear what the evidence suggests about the reasons for health inequalities as well as the best possible instruments to measure both inequality and socioeconomic health gradients. We provide an evaluation of the different sources of health inequity and we draw upon measurement issues and their policy significance.

Quality of life among the Brazilian adult population using the generic SF-8 questionnaire

The objective of this study was to assess the quality of life in the Brazilian adult population, based on the U.S. standard population. It involved a cross-sectional population-based study with probabilistic sampling of 2,420 individuals (725 men and 1695 women) aged 40 or more in different geographic regions of Brazil. A socio-demographic questionnaire and the SF-8 (Short Form-8) were administered in interview form. Descriptive statistics, analysis of variance, the Mann-Whitney test and Tukey's test were used in the analysis. Females, populations in the northeastern region, the population of the regions of Brasília (Distrito Federal), Campo Grande (Mato Grosso do Sul State) and Goiania (Goiás State), Brazil, demonstrated worse quality of life. Age, education and income had influence over quality of life domains. This study presents quality of life estimates for the Brazilian adult population, based on the SF-8 questionnaire. The mean values on the subscales and components of the SF-8 appeared to be influenced by gender, geographic region, family income, age and schooling.

Health inequalities in Rio de Janeiro, Brazil: lower healthy life expectancy in socioeconomically disadvantaged areas

OBJECTIVES

We investigated deprivation and inequalities in life expectancy and healthy life expectancy by location in Rio de Janeiro, Brazil.

METHODS

We conducted a health survey of 576 adults in 2006. Census tracts were stratified by income level and categorization as a slum. We determined health status by degree of functional limitation, according to the approach proposed by the World Health Organization. We calculated healthy life expectancies by Sullivan's method with abridged life table.

RESULTS

We found the worst indicators in the slum stratum. The life expectancy at birth of men living in the richest parts of the city was 12.8 years longer than that of men living in deprived areas. For both men and women older than age 65 years, healthy life expectancy was more than twice as high in the richest sector as in the slum sector.

CONCLUSIONS

Our analysis detailed the excess burden of poor health experienced by disadvantaged populations of Rio de Janeiro. Policy efforts are needed to reduce social inequalities in health in this city, especially among the elderly.

Gender gaps in life expectancy and expected years with activity limitations at age 50 in the European Union: associations with macro-level structural indicators

Women generally live longer than men, but women's longer lives are not necessarily healthy lives. The aim of this article is to describe the pattern of gender differences in expected years with and without activity limitations across 25 EU countries and to explore the association between gender differences and macro-level factors. We applied to the Eurostat life table's data from the Statistics of Income and Living Conditions Survey to estimate gender differences in life expectancy with and without activity limitations at age 50 for 2005. We studied the relationship between the gender differences and structural indicators using meta-regression techniques. Differences in years with activity limitations between genders were associated with the life expectancy (LE) and the size of the gender difference in LE. Gender difference in years with activity limitations were larger as the gross domestic product, the expenditure on elderly care and the indicator of life-long learning decreased, and as the inequality in income distribution increased. There was evidence of disparity in the associations between the more established EU countries (EU15) and the newer EU10 countries. Among the EU15, gender differences were positively associated with income inequality, the proportion of the population with a low education and the men's mean exit age from labour force. Among the EU10, inequalities were smaller with increasing expenditure in elderly care, with decreasing poverty risk and with decreasing employment rate of older people. The association between structural indicators and the gender gap in years with activity limitations suggests that gender differences can be reduced.

Socioeconomic and behavioral risk factors for mortality in a national 19-year prospective study of U.S. adults

Many demographic, socioeconomic, and behavioral risk factors predict mortality in the United States. However, very few population-based longitudinal studies are able to investigate simultaneously the impact of a variety of social factors on mortality. We investigated the degree to which demographic characteristics, socioeconomic variables and major health risk factors were associated with mortality in a nationally-representative sample of 3617 U.S. adults from 1986 to 2005, using data from the 4 waves of the Americans' Changing Lives study. Cox proportional hazard models with time-varying covariates were employed to predict all-cause mortality verified through the National Death Index and death certificate review. The results revealed that low educational attainment was not associated with mortality when income and health risk behaviors were included in the model. The association of low income with mortality remained after controlling for major behavioral risks. Compared to those in the "normal" weight category, neither overweight nor obesity was significantly associated with the risk of mortality. Among adults age 55 and older at baseline, the risk of mortality was actually reduced for those were overweight (hazard rate ratio = 0.83) and those who were obese (hazard rate ratio = 0.68), controlling for other health risk behaviors and health status. Having a low level of physical activity was a significant risk factor for mortality (hazard rate ratio = 1.58). The results from this national longitudinal study underscore the need for health policies and clinical interventions focusing on the social and behavioral determinants of health, with a particular focus on income security, smoking prevention/cessation, and physical activity.

Health inequality: what does it mean and how can we measure it?

Reducing socioeconomic inequalities in health has become an important government objective. International organizations, such as the WHO, have played an important role providing the principles to encourage action in many countries. Evidence of socioeconomic inequalities in health is widespread. National and cross-national research has led to the development of a new set of methodological tools to address the challenges that the available data present. Several methods have been used in the literature to measure inequalities in health; the concentration index approach is becoming widely used. In the future, the research agenda will continue to shift away from documenting health inequalities toward efforts to support the development of policies to improve the health of the most deprived populations and to reduce inequalities in health.

Effects of environmental change on wildlife health

Environmental change has negatively affected most biological systems on our planet and is becoming of increasing concern for the well-being and survival of many species. At an organism level, effects encompass not only endocrine disruptions, sex-ratio changes and decreased reproductive parameters, but also include teratogenic and genotoxic effects, immunosuppression and other immune-system impairments that can lead directly to disease or increase the risk of acquiring disease. Living organisms will strive to maintain health by recognizing and resolving abnormal situations, such as the presence of invading microorganisms or harmful peptides, abnormal cell replication and deleterious mutations. However, fast-paced environmental changes may pose additional pressure on immunocompetence and health maintenance, which may seriously impact population viability and persistence. Here, we outline the importance of a functional immune system for survival and examine the effects that exposure to a rapidly changing environment might exert on immunocompetence. We then address the various levels at which anthropogenic environmental change might affect wildlife health and identify potential deficits in reproductive parameters that might arise owing to new immune challenges in the context of a rapidly changing environment. Throughout the paper, a series of examples and case studies are used to illustrate the impact of environmental change on wildlife health.

The effect of change in educational composition on population ageing

Official Swedish demographic projections have systematically underestimated the number of older people. One explanation behind the underestimation may be found in the fact that the demographic projections are not taking into account socio-economic mortality differentials. We performed alternative demographic scenarios based on assumptions of unchanged and continuing declining mortality, with and without taking into account socio-economic gradients in mortality. According to a scenario based on assumption on declining mortality rates per age group, sex and educational level, the number of older persons (65+) in Sweden will increase by 62% during the period 2000-2035. This can be compared to an increase by 54% in a scenario that does not take into account future structural differences in educational levels and the latest trends in socio-economic inequality in life expectancy (the method used by statistical offices). The socio-economic structure of the older population is significantly changing over the years. We project that by year 2035, only 20% of women 80 years and older will have a low educational level, compared to about 75-80% today. The change in socio-economic structure is similar for the older men. Standard demographic projections that do not take into account socio-economic mortality differentials, risk underestimating the number of older people and hiding dramatic changes in population composition. Taking into account socio-economic mortality differentials results in alternative projections giving us new information regarding the future size and socio-economic composition of the older population. We recommend use of this information in health care and long-term care human resources planning or when assessing financial sustainability of health care, long-term care and pension systems in the future.

Population ageing in Sweden: the effect of change in educational composition on the future number of older people suffering severe ill-health

We investigate how expected changes in the educational level composition of the older population may affect future prevalence of severe ill-health among older people in Sweden. Previous research has indicated that the number of older people, given educational differentials in mortality and expected changes in educational composition during the next decades, may increase more than expected following official population projections in Sweden. Eight alternative scenario projections for the possible development in the number of people with severe ill-health in Sweden between 2000 and 2035 are presented. Scenario projections, where both morbidity and mortality inequalities by educational level are taken into account, are compared with scenarios in which only age and gender are modelled. The projections are made with both constant and decreasing mortality. The calculations show that the expected increases in severe ill-health as a result from the ageing of the population in the period 2000-2035 might, to a large extent, be counteracted by the increase in the educational level of the Swedish population. We recommend therefore that in projections of the prevalence of ill-health, in addition to the ageing of the population, also changes in educational level should be taken into account.

Ill, worried or worried sick? Inter-relationships among indicators of wellbeing among older people in Sweden

This study examined the associations between a large set of health indicators and wellbeing among older people (aged 66 or more years) in Sweden. The data were drawn from the Swedish Panel Survey of Ageing and the Elderly (PSAE), with variables covering information about health, daily activities, social interaction, anxieties and worries, and economic hardship. A series of confirmative factor analyses were used to reveal if and how indicators of living conditions could be subdivided into latent factors, and several socio-economic and socio-demographic variables were used as their predictors. Differences between men and women and between a number of age groups of old people were systematically scrutinised. The preferred representation of the data was a nested model that identified one global factor, which related to all manifest indicators, and three residual factors that measured the specific experiences of physical impairment, psychosocial distress and economic difficulties. The findings improve our understanding of the relationships between indicators of health and wellbeing and the various latent dimensions that simultaneously affect response patterns. More importantly, they also facilitate our understanding of older people's wellbeing and assists the interpretation of single, commonly used indicators such as subjective health.

Inequalities in health at older ages: a longitudinal investigation of the onset of illness and survival effects in England

BACKGROUND

previous studies have suggested a decline in the relationship between socioeconomic circumstances and health or functioning in later life, but this may be due to survival effects.

OBJECTIVE

to examine whether wealth gradients in the incidence of illness decline with age, and, if so, whether this decline is explained by differential mortality.

METHODS

the study included participants in the first two waves of the English Longitudinal Study of Ageing (ELSA), a large national longitudinal study of the population aged 50+ in England, who reported good health, no functional impairment, or no heart disease at baseline. Wealth inequalities in onset of illness over 2 years were examined across age groups, with and without the inclusion of mortality. Outcome measures were functional impairment, heart disease, self-reported health, and all-cause mortality (in conjunction with self-reported health and disability) or circulatory-related mortality (in relation to heart disease).

RESULTS

wealth predicted onset of functional impairment equally across age groups. For self-reported health and heart disease, wealth gradients in the onset of illness declined with age. Selective mortality contributed to this decline in the oldest age groups.

CONCLUSIONS

socioeconomic inequality in developing new health problems persist into old age for certain illnesses, particularly functional impairment, but not for heart disease. Selective mortality explains only some of the decline in health inequalities with age.

Reproductive history, socioeconomic status and disability in the women aged 65 years or older in Turkey

Pregnancy and childbirth are an important physiological and emotional phenomenon in their lives for most women and studies have shown that this process may have a significant impact on their health at later ages. The objective of the study is to examine the relationship between functional disabilities in women over the age of 65 and their reproductive history and socioeconomic status. This is a cross-sectional study. The study group consisted of 543 women aged 65 or over. A general questionnaire and the Brief Disability Questionnaire (BDQ) were used to collect data with face-to-face interview in home visits. Of the women 79.2% have disability. First childbirth was experienced at the average age of 19.6+/-3.3 and the average age at which the women experienced their last delivery was 32.5+/-6.3. Parity was 4.1+/-1.7. Advanced age, being widowed and illiterate, less income, being outside of the middle class and having more than four children are important determinants for later life disability. The study highlights the importance of focusing not just on the short-term effects of childbearing and socioeconomic factors, but also of taking into account the possibility of long-term effects on disability in older women.

Education differences in life expectancy with cognitive impairment

Background

Low education has an impact on life expectancy and level of cognition, but little is known on its effect on life expectancy with cognitive impairment.

Methods

The Medical Research Council Cognitive Function and Ageing Study (MRC CFAS) collected population-based longitudinal data on people aged 65 years and older including measures of education and cognitive impairment, using the Mini-Mental State Examination (MMSE), for five geographically diverse areas around England and Wales interviewed between 1991 and 2003. Transitions between health states were calculated using Markov chain methods. Life expectancy in different states of cognitive function as measured by MMSE were further explored for different education groups. The effect of fixed and educationally based cut points for cognitive impairment are investigated.

Results

Life expectancy spent with cognitive impairment is fairly constant with increasing age at around 1.4 years in men and 2.5 years in women, though this reflects a large increase in the proportion of life spent with cognitive impairment. The differences seen between education groups for the proportion of total life with cognitive impairment (men 13% and women 22% of life lived for low education vs men 7% and women 12% in high education group) disappear when education-adjusted cut points are used (10% in men and 17% in women at age 65 for all education groups).

Conclusions

The results show that there is a substantial amount of life expectancy with cognitive impairment in both men and women. The impairment burden is just as great for those with high education as the lowest educated group.

Inequalities in healthy life years in the 25 countries of the European Union in 2005: a cross-national meta-regression analysis

BACKGROUND

Although life expectancy in the European Union (EU) is increasing, whether most of these extra years are spent in good health is unclear. This information would be crucial to both contain health-care costs and increase labour-force participation for older people. We investigated inequalities in life expectancies and healthy life years (HLYs) at 50 years of age for the 25 countries in the EU in 2005 and the potential for increasing the proportion of older people in the labour force.

METHODS

We calculated life expectancies and HLYs at 50 years of age by sex and country by the Sullivan method, which was applied to Eurostat life tables and age-specific prevalence of activity limitation from the 2005 statistics of living and income conditions survey. We investigated differences between countries through meta-regression techniques, with structural and sustainable indicators for every country.

FINDINGS

In 2005, an average 50-year-old man in the 25 EU countries could expect to live until 67.3 years free of activity limitation, and a woman to 68.1 years. HLYs at 50 years for both men and women varied more between countries than did life expectancy (HLY range for men: from 9.1 years in Estonia to 23.6 years in Denmark; for women: from 10.4 years in Estonia to 24.1 years in Denmark). Gross domestic product and expenditure on elderly care were both positively associated with HLYs at 50 years in men and women (p<0.039 for both indicators and sexes); however, in men alone, long-term unemployment was negatively associated (p=0.023) and life-long learning positively associated (p=0.021) with HLYs at 50 years of age.

INTERPRETATION

Substantial inequalities in HLYs at 50 years exist within EU countries. Our findings suggest that, without major improvements in population health, the target of increasing participation of older people into the labour force will be difficult to meet in all 25 EU countries.

FUNDING

EU Public Health Programme.

Poverty, wealth inequality and health among older adults in rural Cambodia

Little research exists on health determinants among adults living in economically deprived regions despite the fact that these areas comprise a good part of the world. This paper examines the distribution of wealth then tests associations between wealth inequality and a variety of health outcomes, among older adults, in one of the world's poorest regions--rural Cambodia. Data from the 2004 Survey of the Elderly in Cambodia are employed. Using a disablement framework to conceptualize health, associations between four health components and a wealth inequality measure are tested. The wealth inequality measure is based on an index that operationalizes wealth as ownership of household assets and household structural components. Results confirm difficult economic conditions in rural Cambodia. The lowest wealth quintile lives in households that own nothing, while the next quintiles are only slightly better off. Nevertheless, logistic regressions that adjust for other covariates indicate heterogeneity in health across quintiles that appear qualitatively similar, with the bottom quintiles reporting the most health problems. An exception is disability, which presents a U-shaped association. It is difficult to determine mechanisms behind the relationship using cross-sectional data, but the paper speculates on possible causal directions, both from wealth to health and vice-versa. The analysis suggests the ability to generalize the relationship between wealth inequality and health to extremely poor populations as a very small difference in wealth makes a relatively large difference with respect to health associations among those in meager surroundings.