Health Inequalities In Later Life Research Articles

Does the Economic Status of Adult Children Influence Self-Rated Health Among Older Adults in China?

We aim to investigate the association between children's economic status and parents' self-rated health and examine the potential mediating mechanisms for this relationship. Utilizing nationally representative data in China in 2014, this study predicted parent's self-rated health from children's economic status using inverse probability of treatment weighting to account for selection and endogeneity bias. We further examined depressive symptoms, kin and nonkin social support networks, emotional closeness to children, and economic support from children, as potential mediators of this relationship. The study reveals that parents whose children had greater economic success tended to have better self-rated health. For both rural and urban older adults, depressive symptoms served as the most influential mediator. However, only among rural older adults did the size of their support networks mediate the relationship between children's economic status and perceived health. The results from this study suggest that children's economic success contributes to better self-rated health among older adults. In part, this relationship was explained by better emotional well-being and greater availability of support resources among parents in rural areas with successful children. This quasi-causal analysis demonstrates that adult children remain important for the well-being of their older parents in China, but also suggests that health inequalities in later life are exacerbated by the chance of having economically successful offspring.

Health inequalities in later life.

British Journal of Community NursingVol. 28, No. 3 While's WordsHealth inequalities in later lifeAlison WhileAlison WhileEmeritus Professor of Community Nursing, Florence Nightingale Faculty of Nursing, King’s College London and Midwifery and Fellow of the Queen’s Nursing InstituteSearch for more papers by this authorAlison WhilePublished Online:28 Feb 2023https://doi.org/10.12968/bjcn.2023.28.3.112AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article References Centre for Ageing Better. Ethnic health inequalities in later life. 2021a. https://ageing-better.org.uk/resources/ethnic-health-inequalities-in-later-life?gclid=Cj0KCQiAlKmeBhCkARIsAHy7WVuRwyV0d0gRE_V7w5VfPIR9a3t7pSnhoR4R-yB8OvhbSywWIDxxKUkaAlNDEATw_wcB (accessed 02 February 2023) Google ScholarCentre for Ageing Better. Boom and bust? The last baby boomers and their prospects for later life. 2021b. https://ageing-better.org.uk/sites/default/files/2021-11/boom-and-bust-report-the-last-baby-boomers.pdf (accessed 02 February 2023) Google ScholarCentre for Ageing Better. The State of Ageing 2022. 2022. https://ageing-better.org.uk/sites/default/files/2022-04/The-State-of-Ageing-2022-online.pdf (accessed 02 February 2023) Google ScholarNHS England. The NHS Long Term Plan. 2019. https://www.longtermplan.nhs.uk/wp-content/uploads/2019/08/nhs-long-term-plan-version-1.2.pdf (accessed 02 February 2023) Google ScholarOffice for National Statistics. Health state life expectancy by national deprivation deciles, England: 2018 to 2020. 2022. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthinequalities/bulletins/healthstatelifeexpectanciesbyindexofmultipledeprivationimd/2018to2020 (accessed 02 February 2023) Google ScholarPublic Health England. An evidence summary of health inequalities in older populations in coastal and rural areas. 2019a. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/824717/Health_Inequalities_in_Ageing_in_Rural_and_Coastal_Areas-Messages_and_summary.pdf (accessed 02 February 2023) Google ScholarPublic Health England. Guidance. All our health: about the framework. 2019b. https://www.gov.uk/government/publications/all-our-health-about-the-framework/all-our-health-about-the-framework Google ScholarPublic Health England. Guidance: Health disparities and health inequalities: applying All our Health. 2022. https://www.gov.uk/government/publications/health-disparities-and-health-inequalities-applying-all-our-health/health-disparities-and-health-inequalities-applying-all-our-health#taking-action (accessed 02 February 2023) Google ScholarStopforth S, Kapadia D, Nazroo J, Béécares L. Ethnic inequalities in health in later life, 1993—2017: The persistence of health disadvantage over more than two decades. Ageing and Society: 1-29. https://doi.org/10.1017/S0144686X2100146X Google ScholarThe Health Foundation. Quantifying health inequalities in England. 2022. https://www.health.org.uk/news-and-comment/charts-and-infographics/quantifying-health-inequalities (accessed 02 February 2023) Google ScholarThe King’s Fund. What are health inequalities? 2022. https://www.kingsfund.org.uk/publications/what-are-health-inequalities#impact-of-covid-19 (accessed 02 February 2023) Google ScholarUniversity of Central Tancashire. A tale of two countrysides: remote and rural health and medicine. 2022. https://www.uclan.ac.uk/assets/pdf/rural-medicine-and-health-report.pdf (accessed 02 February 2023) Google Scholar FiguresReferencesRelatedDetails 2 March 2023Volume 28Issue 3ISSN (print): 1462-4753ISSN (online): 2052-2215 Metrics History Published online 28 February 2023 Published in print 2 March 2023 Information© MA Healthcare LimitedPDF download

Social protection expenditure on health in later life in 20 European countries: Spending more to reduce health inequalities

BackgroundThis study aims to examine whether higher social protection expenditure reduces the negative association of life-course socioeconomic disadvantages with subjective and objective health status and trajectories in later life. MethodsWe used SHARE data from participants living in 20 European countries aged 50 to 96. Seven waves allowed to examine the trajectories of health inequalities in later life. We used linear mixed-effects models stratified by sex to examine the association between life-course socioeconomic disadvantage and subjective (self-rated health, SRH, N = 55,443) and objective (grip strength, N = 54,718) health. Cross-level interactions between net social protection expenditure as percentage of gross domestic product and life-course socioeconomic disadvantage tested for the moderating effect of social expenditures on the association of disadvantage with SRH and grip strength in later life. FindingsHigher social protection expenditure reduced socioeconomic health inequalities in both men and women for grip strength, and in women but not men for SRH. For SRH, the health-inequality-reducing effect of social protection expenditure became weaker with increasing age. This was not observed in grip strength. Some separate expenditure functions (disability, family and children) were found to have inequality-widening effects in men's and women's SRH, which were either offset or overcompensated by the other functions. No inequality-widening effects were observed in grip strength. InterpretationHigher social spending reduces life-course socioeconomic inequalities in women's subjective health and in men's and women's objective health. However, some specific social protection policies may have the unintentional effect of increasing inequalities in people's evaluation of their own health.

Role of contextual and compositional characteristics of schools for health inequalities in childhood and adolescence: protocol for a scoping review

IntroductionChildhood and adolescence are crucial life stages for health trajectories and the development of health inequalities in later life. The relevance of schools for health and well-being of children and...

Socioeconomic Inequalities in Home-Care Use Across Regional Long-term Care Systems in Europe.

ObjectivesWe examine whether socioeconomic inequalities in home-care use among disabled older adults are related to the contextual characteristics of long-term care (LTC) systems. Specifically, we investigate how wealth and income gradients in the use of informal, formal, and mixed home-care vary according to the degree to which LTC systems offer alternatives to families as the main providers of care (“de-familization”).MethodWe use survey data from SHARE on disabled older adults from 136 administrative regions in 12 European countries and link them to a regional indicator of de-familization in LTC, measured by the number of available LTC beds in care homes. We use multinomial multilevel models, with and without country fixed-effects, to study home-care use as a function of individual-level and regional-level LTC characteristics. We interact financial wealth and income with the number of LTC beds to assess whether socioeconomic gradients in home-care use differ across regions according to the degree of de-familization in LTC.ResultsWe find robust evidence that socioeconomic status inequalities in the use of mixed-care are lower in more de-familized LTC systems. Poorer people are more likely than the wealthier to combine informal and formal home-care use in regions with more LTC beds. SES inequalities in the exclusive use of informal or formal care do not differ by the level of de-familization.DiscussionThe results suggest that de-familization in LTC favors the combination of formal and informal home-care among the more socioeconomically disadvantaged, potentially mitigating health inequalities in later life.

Associations between contextual and compositional characteristics of early childcare facilities with health, health behaviours and well-being among young children aged 06 years: protocol for a scoping review

IntroductionEarly childhood is an important life stage which is crucial for determining health and health inequalities in later life. At the meso-level (institutional-level), early childcare facilities (eg, kindergartens, preschools) are...

The Education of Multiple Family Members and the Life-Course Pathways to Cognitive Impairment.

This article asks how the educational attainments of multiple family members, including parents and offspring, are associated with the cognitive health of older adults in the United States. We use panel data from the U.S. Health and Retirement Study (2000-2012) to examine how the education of an individual, their parent(s), and their offspring are associated with the prevalence of moderate/severe cognitive impairment and the onset of cognitive impairment among older adults using logistic regression and discrete-time event history analysis, respectively. We found that when combined, only the education of the individual is inversely associated with cognitive impairment at baseline. However, both the educational attainments of an individual and their offspring are negatively associated with the risk of becoming cognitively impaired, among individuals who were not already cognitively impaired. Conversely, parental education was not predictive of being cognitively impaired or the onset of impairment. Furthermore, we found that respondent gender did not moderate the relationship between a family member's education and respondent cognitive health. This study adds to current research by asking how resources from earlier and subsequent generations matter for older adults' cognitive health. Although we found little evidence that parental education matters at this life stage, results suggest that offspring education has a salient positive effect on later-life cognitive health. This finding underscores an overlooked source of health disparities-offspring resources-and highlights how a family perspective remains a powerful tool for understanding health inequalities in later life.

Lifetime employment histories and their relationship with 10-year health trajectories in later life: evidence from England.

BackgroundEmployment histories influence health. However, most studies have so far investigated cross-sectional associations between employment histories and health, failing to recognize health as a dynamic process in later life.MethodsWe use Waves 3–8 of the English Longitudinal Study of Ageing, including retrospective information on respondents’ employment activities. We used dynamic hamming distances to summarize lifetime employment histories up to state pension age (64 for men and 59 for women). Multilevel growth curve models were then used to estimate the influence of lifetime employment histories on later life health trajectories over a 10-year period using quality of life (QoL), somatic health, and depression.ResultsNet of selection effect and a host of contemporaneous material and social resources, men who exited early started off with poorer health than those with continuous attachment to the labour market but had a very similar health profile by the end of the 10-year period considered. Among women, better somatic health and higher QoL were observed among those who had employment breaks for family care, and this health advantage was maintained over time. Lifetime employment histories are not related to depression for either men or women.ConclusionOverall, differences in health by employment histories level off only among men who left earlier and those continuously employed. Flexible arrangements for men in poor health who benefit from leaving the labour market early and supporting women who wish to take breaks for family care may help reduce health inequalities in later life.

Trajectories of material living standards, physical health and mental health under a universal pension

ObjectiveAged pension schemes aim to support material and non-material well-being of older populations. The current work aimed to describe dominant trajectories of material living standards in the decades prior to...

The role of personal social networks on health inequalities across European regions

The role of personal social networks on health inequalities is little understood. Theoretically, the characteristics of social network features can contribute to, both, increase and attenuate health inequalities. Few empirical studies that focus on the interaction between socioeconomic position and social networks provide little insight on the topic. Using data from the Survey of Health, Ageing and Retirement in Europe, this study analyses the moderation role of personal social networks on health inequalities in later life among northern, central, and southern European regions. Social advantages of higher socioeconomic individuals are re-enforced by the quality of social connections and the provision of social support. In turn, health inequality is attenuated by marital partnership and participation on social activities that benefits more the health of people at lower socioeconomic positions. Furthermore, results suggest that the influence of social network features on health inequalities is shaped by regions’ different policy commitments to familiarization/defamilialization pressures.

Ties and inequalities in later life: welfare state regime and the role of social networks in health inequalities in later life in Europe

ABSTRACTCross-national comparisons on health inequalities have puzzled health researchers in the last years. Contrary to what is theoretically expected, Northern European countries, known for their advanced welfare state regime and universalistic policies in health and social protection, do not present smaller health inequalities than other European nations. Within the debate triggered by these surprising results, some authors consider the possibility that the differences among the welfare state regimes may be shaping the relevance of specific pathways or mechanisms underlining the association between socioeconomic position (SEP) and health. This research addresses this hypothesis by comparing the contribution of social networks to health inequality in later life across different welfare state regimes. Mediation effects between SEP and health by social networks variables are compared across four different welfare state regimes, using data from Survey of Health, Ageing, and Retirement in Europe. Findings suggest that the socioeconomic advantages in health are partially explained by the differentials in social integration and quality of social ties. Welfare state regimes appear to shape the contribution of social networks in health inequality concerning the implications of the exchanges of social support in health.

Patterns and causes of health inequalities in later life: a Bourdieusian approach.

This study explores the relationship between social class and health change in older people in a path analysis, using data from the English Longitudinal Study of Ageing (n=6241) in a Bourdieusian theoretical framework. Bourdieu drew a distinction between the occupational characteristics by which people are classified and the secondary properties of class that relate to lifestyle (economic, cultural and social capitals). Our path model includes both occupational and secondary characteristics of objective social class as well as a measure of subjective social class. We investigate the effects of the predictors on change in three health outcomes (self-rated health, number of symptoms of depression and number of difficulties with the activities of daily living). The analysis adds to Bourdieusian research by showing how the effects of objective social class on health are partially mediated by perceived social status. It also adds to substantive research on the relationship between class and health by suggesting that class-related health inequalities do persist for older people, even for those who are not in paid employment. It suggests that a large amount of the effect of occupation on the health of older people is not direct but indirect; through their personal wealth and lifestyle.

Commentary: Socioeconomic status and hypertension in low- and middle-income countries: can we learn anything from existing studies?

of Northwest China from 1982 to 2010. PLoS One 2013;8:e61779. 55. Bezerra VM, Andrade ACS, Cesar CC, Caiaffa WT. Quilombo communities in Vitoria da Conquista, Bahia state, Brazil: Hypertension and associated factors. Cad Saude Publica 2013;29:1889–902. 56. Razzaque A, Nahar L, Abu Haider Mohammad Golam M, Karar Zunaid A, Mohammad Shafiqul I, Yunus M. Sociodemographic differentials of selected noncommunicable diseases risk factors among adults in Matlab, Bangladesh: findings from a WHO STEPS survey. Asia Pac J Public Health 2011;23:183–91. 57. Soman CR, Kutty VR. Methodological errors uncovered? Int J Cardiol 2000;74:243–45. 58. White C. Suspected research fraud: difficulties of getting at the truth. BMJ 2005;331:281–88. 59. Lei XY, Yin NN, Zhao YH. Socioeconomic status and chronic diseases: the case of hypertension in China. China Econ Rev 2012;23:105–21. 60. World Bank. World Development Indicators: Poverty Rates at National Poverty Lines. 2014 http://wdi.worldbank.org/table/ 2.7 (12 May 2014, date last accessed) 61. Reddy KS, Yusuf S. Emerging epidemic of cardiovascular disease in developing countries. Circulation 1998;97:596–601. 62. Carnethon MR, Evans NS, Church TS et al. Joint associations of physical activity and aerobic fitness on the development of incident hypertension: coronary artery risk development in young adults. Hypertension 2010;56:49–55. 63. Walker E, Hernandez AV, Kattan MW. Meta-analysis: Its strengths and limitations. Cleve Clin J Med 2008;75:431–39. 64. Egger M, Schneider M, Davey Smith G. Spurious precision? Meta-analysis of observational studies. BMJ 1998;316:140–44. 65. Beckett M. Converging health inequalities in later life an artifact of mortality selection. J Health Soc Behav 2000;41:106–19. 66. Dupre ME. Educational differences in health risks and illness over the life course: a test of cumulative disadvantage theory. Soc Sci Res 2008;37:1253–66. 67. Vathesatogkit P, Batty GD, Woodward M. Socioeconomic disadvantage and disease-specific mortality in Asia: systematic review with meta-analysis of population-based cohort studies. J Epidemiol Community Health 2014;68:375–83. 68. Prabhakaran P, Ajay VS, Prabhakaran D et al. Global cardiovascular disease research survey. J Am Coll Cardiol 2007;50:2322–28. 69. Fitzmaurice GM, Laird NM, Ware JH. Applied Longitudinal Analysis. Hoboken, NJ: Wiley-Interscience, 2004.

Major drivers of health inequalities in later life and future research needs.

Europe is the oldest region in the world and its life expectancy is currently increasing at around about 12 months every 5 years. When added to population re-structuring as a result of demographic change, this means that by 2060 30% of the European population will be aged 65 years and over and with those aged 80 and over being the fastest growing age group. The European Union is placing a high priority on healthy ageing and its key indicator is Healthy Life Years (HLY). It is already obvious from the variation in HLY that not all European populations are ageing healthily. For example in France, life expectancy at age 50 for women is 22.9 years, with 9.9 years of healthy life. In comparison women’s life expectancy at age 50 in Latvia is 17.2 years, with only 4.3 years of healthy life. In 2009 the European Commission funded the FUTURAGE project, whose aim was to develop a definitive road map for ageing research for Europe for the next 10-15 years. Seven major research priority themes were identified by FUTURAGE according to a standard format covering: the significance of the theme; the fundamental insights necessary for future research; an overview of current research knowledge; and the main priority topics within the general theme (full report available at http://futurage.group.shef.ac.uk/road-map-launch-conference.html). Here we focus on one of these seven themes, that of ‘Unequal Ageing’. Six challenges related to future European ageing research were identified in the area of unequal ageing: Monitoring inequalities; Health in work and retirement; Inequalities and discrimination on health; Ageing and migration; Focus on the very old; and Inequalities and discrimination in the labour market. These challenges, as well as examples of specific research questions, can be described in the context of a life course perspective and the World Health Organisation model of health transitions. FUTURAGE represented the most extensive consultation ever conducted in this research area, and it included all major stakeholders and active users of ageing research. ‘Unequal Ageing’ was identified as one of the main research priorities for the road map and within this the challenge to monitor inequalities across Europe. To be able to address this challenge demands not only a concerted collection of truly harmonised measures across Europe, but also that they are appropriate at a country or regional level.

Paying the price? The impact of smoking and obesity on health inequalities in later life

The aims of the study are twofold: (i) to explore the impact of socioeconomic position, as measured 13 years earlier, on cognitive functioning and mobility impairment in later life, and (ii) to explore the extent to which obesity and smoking status can explain socioeconomic inequalities in cognitive and mobility impairments in later life. Data from a nationally representative sample of Swedish adults aged 56-76 in 1991 who were re-interviewed 13 years later in 2004, was analysed to explore the impact of socioeconomic position, smoking, and obesity on cognitive and physical functioning in late life. The results showed that both smoking and obesity in late mid-life were stratified by socioeconomic position. Moreover, the results showed significant associations between socioeconomic position and both cognitive and physical functioning in later life. However, these inequalities in late life function could only partially be explained by the socioeconomic differences in smoking and obesity. The findings of this study suggest that socioeconomic differences in the rates of smoking and obesity may explain some, but not all, of the socioeconomic inequalities in physical and cognitive functioning during old age.

International migration and health inequalities in later life

ABSTRACTThe aim of this paper is to ascertain the existence of differences in self-perceived health and depression between immigrants and native-born populations aged 50 years and older living in Western and Northern European countries. We examine the effect of country of origin, length of time in the host country and citizenship on the health of adults, using data from the Survey on Health, Ageing and Retirement in Europe (SHARE). As the logistic regressions reveal, some immigrant groups are more likely to perceive worse self-rated health and to suffer from depression than native-born groups, even when demographic and socio-economic variables are taken into account. In particular, people born in Eastern Europe living in Germany, France and Sweden have the highest odds ratio of poor health with respect to natives. Nativity status, duration and citizenship clearly contribute towards explaining health differences which are shown to vary significantly across countries. Furthermore, the perception of poor health rises as the length of stay increases, although a non-linear pattern was found. Results indicate that greater efforts by policy makers are needed in order to improve the health of specific middle-aged and older groups of immigrants in Europe.

Socioeconomic inequalities in circulatory and all-cause mortality after retirement: the impact of mid-life income and old-age pension. Evidence from the Uppsala Birth Cohort Study

BackgroundThe aim of this study was to explore the impact of mid-life income and old-age pensions on the risk of mortality in later life. Furthermore, the study explored whether income...

Health inequalities in ageing societies

The age distribution of the world’s population is undergoing a profound transformation. As mortality and fertility have fallen, the age distribution has been shifting gradually to older ages (UN 2007). In the next 45 years, the global population aged 60 years and above will triple. By 2050, one-third of the European population will be aged 60 and above. In lowand middle-income countries, the proportion of older people is growing even faster than in highincome countries (WHO 2008). According to the WHO Commission on Social Determinants of Health, global population ageing makes exploring and understanding social determinants of health among older people an increasingly important challenge (WHO 2008). While this issue was neglected by social epidemiology for a long time, gerontological results indicating that old age is not a uniform phase of life, but characterised by social differences have led to an increasing interest. Today there are some studies describing health inequalities in older populations (e.g. McMunn et al. 2006). Overall, these studies indicate that there is also a social gradient in health among older people, although health inequalities tend to be smaller than among middle-age groups. In the following, three important open issues concerning health inequalities in ageing societies are outlined. First, it can be questioned whether standard measures of socio-economic position like education, occupational class, and income are appropriate for older people. There is an intense discussion in sociology of ageing about concepts and measures of social inequality in older ages. While this debate continues, it has been suggested that (a) studies should focus on a set of measures rather than a single indicator to explore the multi-dimensional nature of socioeconomic position in later life, and (b) studies should include indicators, such as assets or home ownership that can be expected to reflect economic advantages or disadvantages accumulated over the life course (Knesebeck et al. 2007; for a general discussion of measurement of social determinants see also McQueen 2009). Second, as it is still unclear how and why health inequalities vary with age, it seems important to intensify the integration of life course approaches into social epidemiology (Blane 2006; Power and Kuh 2006). These approaches highlight the role of the accumulation of disadvantage over the life course—combining the amount of time different people have spent in more or less disadvantaged circumstances. Health inequality between social groups in this regard is a result of inequalities in the accumulation of social, psychological, and biological advantages and disadvantages over time. Life course approaches help to understand how these social, psychological, and biological factors operating at different stages of the life course contribute to the development of health inequalities in later life. Third, while there are an increasing number of studies describing health inequalities in older ages, there is not much known about the specific factors contributing to these health inequalities. Moreover, it is not certain whether the Olaf von dem Knesebeck is head of the Department of Medical Sociology at the University Medical Center Hamburg-Eppendorf. He is interested in research on social determinants of health and health services research, both with a special focus on older ages and international comparisons.

Differences in self-rated health among older adults according to socioeconomic circumstances: the Bambuí Health and Aging Study

Self-rated health is influenced by socioeconomic circumstances, but related differences in its structure have received little attention. The objective of this study was to examine whether self-rated health structure differs according to socioeconomic circumstances in later life. The study included 1,505 individuals (86.4%) residing in Bambuí and aged 60 years or older. Correlates of self-rated health among lower-income older adults (monthly household income < USD 240.00) and higher-income seniors were assessed. Social network stood out as a major factor in the structure of self-rated health among the poorest. Psychological distress was independently associated with worse self-rated health among the poorest, while perceptions by the wealthiest were broader, including psychological distress, insomnia, Trypanosoma cruzi infection, use of medications, and access to health services. Physician visits and hospitalizations were associated with self-rated health in both groups. Our results show important differences in the structure of self-rated health according to socioeconomic circumstances and reinforce the need for policies to reduce health inequalities in later life.

Mortality Selection and Sample Selection: A Comment on Beckett

Mortality Selection and Sample Selection: A Comment on Beckett* ANDREW NOYMER University of CaIifornia—BerkeIey Journal of Health and Social Behavior 2001, Vol 42 (Septmber): 326-327 In an interesting article, Megan Beckett (2000) examines the important question of converging health inequalities in later life. Many studies have shown that the differences in health across socioeconomic strata narrow at older ages. Using panel data from the National Health and Nutrition Examination Survey (NHANES), Beckett shows that the converging health inequality cannot be accounted for by mortality selection. The pre- sent comment reconsiders Beckett’s approach to the selection problem, which, while creative, is open to multiple interpretations. Consider the phenomenon that would cause converging health inequalities at later ages to be an “artifact,” as Beckett puts it, of mortality selection. At younger ages, persons with high- er socioeconomic status (SES) have lower lev- els of health problems than those with lower SES. At older ages, the prevalence of health problems in the two groups is closer to parity. If patterns in morbidity are mirrored in mortal- ity, then at older ages a lower SES cohort (higher morbidity and mortality) will be small- er compared to its starting size than a higher SES cohort (lower morbidity and mortality). Since the seminal work of Vaupel, Manton, and Stallard (1979) and Keyfitz and Littman (1979), many demographers have assumed that there are different rates of “frailty” within a population, which determine an individual’s deviation, at any age, from some baseline mor- tality risk. According to the frailty hypothesis, those who die at young ages tend to have high frailty, which skews the distribution of sur- vivors to be more robust. If this condition of nonrandom mortality risks is met, then the aged low SES cohort will be more robust than ‘Address correspondence to: Andrew Noymer, Departments of Sociology and Demography, University of Califomia-—Berkeley, 2232 Pied- mont Avenue, Berkeley, CA 94720; email: andrew@demog.berkeley.edu. when it started out. This reversal of fortune over the life course is called “cohort inversion” (Hobcraft, Menken, and Preston 1982). On the other hand, the low mortality, high SES cohort will have a much less-changed frailty distribu- tion, and will experience less cohort inversion. The greater cohort inversion of the low SES cohort could be enough to overcome the mor- tality disadvantage of being low SES. This problem must be analyzed cautiously, however, as the entire framework for understanding mortality selection effects rests on a counter- factual foundation. If we hold that convergence is a result of mortality selection, we imply that an intrinsic differential persists into older ages and that we would observe it were it not for the selection efiect. On the other hand, if we hold that the convergence is either intrinsic or the result of, for example, access to Medicare (Beckett 2000), we posit that even without selection we would see convergence. In both cases, there is the troubling verb “would.” In reality, we can only observe vital rates that do occur, not those that would occur if some con- dition is met. The general problem of sample selection is encountered frequently in the social sciences (cf. Stolzenberg and Relles 1997; Winship and Mare 1992), and as Beckett (2000) notes, dif- ferential mortality is just a special case of the more general problem. Although we cannot simply “control for” (i.e., condition on) selec- tion bias the same way we would a confound- ing variable, statistical techniques do exist that try to counteract the bias. However, mortality selection is a very special case of sample selec- tion, all the more so if the dependent variable in question is itself health-related. Because of cohort inversion, sample selection due to mor- tality has causal implications beyond nonran- dom missing data in panel followups. This is what makes Beckett’s approach problematic. Consider the statistical technique used by Beckett to set up the hypothetical of no mor- 326