Tracing the origins of successful aging: The role of childhood conditions and social inequality in explaining later life health
Highlights
► This study uses unique life history data from 13 European countries to trace the origins of successful aging. ► Childhood conditions greatly impact individuals' odds of aging successfully, independent of later life risk factors. ► Lower social inequality in a country is associated with higher odds of aging well. ► Welfare state policies have the capacity to improve conditions for healthy and active aging from early life onwards.
Introduction
In the preamble to the Constitution of the World Health Organization (WHO), health is defined as “a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity.” Against the background of growing concern about trends in the health of older people in particular (see Crimmins & Béltran-Sánchez, 2011, for a recent review), Rowe and Kahn, 1997, Rowe and Kahn, 1998 introduced a highly influential conceptualization of ‘successful aging’, which added a social component to merely biomedical conceptualizations of healthy aging. Rowe and Kahn's (1997: 439) definition of successful aging as “avoidance of disease and disability, maintenance of high physical and cognitive function, and sustained engagement in social and productive activities” thus corresponds well to WHO's multidimensional definition of health and has become a commonly applied “gold standard of aging” (Dillaway & Byrnes, 2009: 706).
Numerous studies have shown that current socioeconomic status (SES), health behaviors, or religious beliefs, for example, are strong predictors of successful aging (e.g., Crowther, Parker, Achenbaum, Larimore, & Koenig, 2002; Haveman-Nies, de Groot, & van Staveren, 2003; McLaughlin, Connell, Heeringa, Li, & Roberts, 2010). While these characteristics mainly describe elders' contemporary circumstances, recent research suggested that early- or midlife factors, such as family background, work characteristics, or the experience of incarceration, matter as well (e.g., Britton, Shipley, Singh-Mannoux, & Marmot, 2008; Pruchno, Wilson-Genderson, Rose, & Cartwright, 2010). Moreover, a growing body of evidence indicates that childhood SES and health, for example, exhibit long-term influences on individuals' health (e.g., Blackwell, Hayward, & Crimmins, 2001; Haas, 2008; Luo & Waite, 2005) and mortality (e.g., Frijters, Hatton, Martin, & Shileds, 2010; Galobardes, Lynch, & Smith, 2004; Hayward & Gorman, 2004). To our knowledge, though, there has been little research explicitly aimed at tracing the origins of successful aging to a broader array of childhood conditions (see Schafer & Ferraro, 2011, for an exception).
A first objective of the present study, therefore, was to explore the potential role of parental SES as well as childhood health and cognition in determining whether individuals succeed in aging well, controlling for contemporary individual characteristics. Data was drawn from the Survey of Health, Ageing and Retirement in Europe (SHARE), including recently collected retrospective information on participants aged 50 or over from 13 Continental European countries who participated in the SHARELIFE study. We complemented this life course perspective on successful aging with a multilevel perspective. Since previous comparative research revealed significant cross-national variation in the prevalence of successful aging (Hank, 2011a), we secondly tested whether and how contemporary societal context contributes to aging well, focusing on the role of income inequality.
The remainder of this article is structured as follows: the next section provides a brief overview of previous research investigating associations between childhood conditions and social inequality with later life health. From this review we derive our hypotheses for the present study. We then describe the data and methods used in the analysis, followed by a presentation of empirical findings. We present our conclusions in the final section.
Section snippets
Studies relating childhood living conditions to adult health
Although a large number of early life circumstances may affect adult health, research indicating negative impacts of adverse childhood conditions on later life health has suggested that two aspects in particular might be important: early health and SES. These factors may affect adult health directly or indirectly. On one hand, early nutritional deprivation, for example, might directly initiate negative health trajectories during the individual's childhood, which may persist or even aggravate
Data
This study uses baseline interviews from the first two waves of the Survey of Health, Ageing and Retirement in Europe (SHARE; cf. Börsch-Supan, Hank, Jürges, & Schröder, 2010), which were conducted in 2004–05 and 2006–07, respectively. These data were complemented with retrospective information on participants' childhood living conditions, collected in 2008–09 during the survey's third round as part of the SHARELIFE project (see Schröder, 2011, for methodological details). SHARELIFE data are
Results
The explanatory variables were included stepwise into the regression, that is, we started with a so called ‘empty’ model that contained only the constant and the macro-level error term (Model 1). The contemporary (i.e., later life) micro-level control variables were introduced in Model 2, which was complemented by our set of childhood variables in Model 3. Finally, we added the Gini coefficient as a macro-level variable in Model 4 (see Table 2). Note that all findings reported here are based on
Discussion
Exploiting new data from the SHARELIFE project, which allowed us to integrate life course and multilevel perspectives on successful aging, the present study had two main objectives: first, to explore the potential role of parental SES as well as childhood health and cognition in determining whether Europeans succeed in aging well; second, to test whether and how social inequality (measured by a country's Gini coefficient) relates to individuals' odds of meeting Rowe and Kahn, 1997, Rowe and
Acknowledgments
We are grateful for comments by three anonymous reviewers. This paper uses data from SHARELIFE release 1, as of November 24th 2010 and from SHARE release 2.5.0, as of May 24th 2011. The SHARE data collection has been primarily funded by the European Commission through the 5th framework program (project QLK6-CT-2001-00360 in the thematic program Quality of Life), through the 6th framework program (projects SHARE-I3, RII-CT-2006-062193, COMPARE, CIT5-CT-2005-028857, and SHARELIFE,
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