Elsevier

Social Science & Medicine

Volume 207, June 2018, Pages 11-18
Social Science & Medicine

Quality of life at the retirement transition: Life course pathways in an early ‘baby boom’ birth cohort

https://doi.org/10.1016/j.socscimed.2018.04.011Get rights and content

Highlights

  • The first use of life-course prospective data from an ageing ‘baby-boom’ cohort.

  • Models pathways by which early-life factors influence later-life quality of life.

  • We identify direct and indirect pathways of influence.

  • Effects of earlier life factors were mostly mediated by later-life factors.

  • Adverse childhood events directly affected later-life quality of life.

Abstract

Promoting quality of life (QoL) in later life is an important policy goal. However, studies using prospective data to explore the mechanisms by which earlier events influence QoL in older age are lacking. This study is the first to use prospective data to investigate pathways by which a range of measures of life-course socioeconomic status contribute to later-life QoL. The study uses data from the Newcastle Thousand Families Study cohort (N = 1142), an early ‘baby-boom’ birth cohort born in 1947 in Newcastle upon Tyne, an industrial city in north-east England. Using prospective survey data collected between birth and later adulthood (N = 393), a path analysis investigated the effects and relative contributions of a range of life-course socioeconomic factors to QoL at age 62–64 measured using the CASP-19 scale. Strong positive effects on later-life QoL were found for advantaged occupational status in mid-life and better self-reported health, employment and mortgage-freedom in later adulthood. Significant positive indirect effects on QoL were found from social class at birth and achieved education level, mediated through later-life socioeconomic advantage. Experiencing no adverse events by age five had a large total positive effect on QoL at age 62–64, comprising a direct effect and indirect effects, mediated through education, mid-life social class and later-life self-reported health. Results support a pathway model with the effects of factors in earlier life acting via later-life factors, and an accumulation model with earlier-life factors having large total, cumulative effects on later-life QoL. The presence of a direct effect of adverse childhood events by age five on QoL suggests a ‘critical period’ and indicates that policies across the life-course are needed to promote later-life QoL, with policies directed towards older adults perhaps too late to ‘undo the damage’ of earlier adverse events.

Introduction

This study is, as far as the authors are aware, the first to use prospective data to investigate the effects of socioeconomic status across the life-course on later-life quality of life (QoL). This study uses data from a UK early ‘baby-boom’ cohort. It has been suggested that the post-war ‘baby-boom’ cohort who, in the UK, lived through the inception of the welfare state, periods of stable employment, high levels of social mobility and increasing prosperity, is ‘reinventing’ older age (Sargent et al., 2013). On average, this cohort is entering later life healthier and wealthier (Johnson, 2015) than previous cohorts with, for many, older age an attractive ‘third age’ stage of the life-course (Phillipson, 2013b). Increases in older people's incomes and healthy life expectancy mean that notions of ‘ageing well’ have progressed beyond the absence of poverty and poor health (Wiggins et al., 2004, 2008) and promoting broader notions of ‘quality’ in later life have become important goals (Kendig et al., 2016).

Yet, as there are well-documented inequalities in wealth and in life expectancy (Marmot, 2010), so there are inequalities in QoL. Indeed, later-life QoL has been found to have an occupational status gradient similar to those found for mortality and morbidity (Blane et al., 2007). As early ‘baby boomers’ are often assumed to have largely lived uniquely fortunate lives, limited attention has been given to the existence of inequalities, including in QoL, in this cohort (Kendig et al., 2016). This study explores life-course factors associated with later-life QoL in this ‘lucky’ cohort.

Significant contributions to later-life QoL have been identified from current health status and both current and mid-life socioeconomic circumstances (Jivraj et al., 2014; Kendig et al., 2016; Niedzwiedz et al., 2012; Wahrendorf, 2015; Zaninotto et al., 2009). In addition to these proximal influences, life-course research is increasingly identifying earlier-life influences on later-life QoL. The life-course perspective seeks to explain, often neglected, within-group differences among older adults by highlighting earlier-life circumstances that can result in diverse trajectories in later life (Dannefer, 2003; O'Rand, 1996). From a life-course perspective, each life stage must be viewed in the context of the preceding stages and, by the time older adulthood is reached, a complex set of interacting and competing events will have shaped outcomes. Earlier-life influences on later-life QoL are less well documented than proximal influences (Platts et al., 2015). However, retrospective life history data has provided early evidence of the influence of childhood socioeconomic position on older adults' QoL (Wahrendorf and Blane, 2014).

Accumulation, pathway and critical period models are among the most widely-used conceptual models for the life-course determinants of later-life QoL (Niedzwiedz et al., 2012). Accumulation models, such as cumulative (dis-)advantage (Dannefer, 2003) and cumulative inequality (Ferraro and Shippee, 2009), suggest that inequalities are primarily structurally generated from birth (and even before) and are perpetuated and amplified over the life-course (Crystal and Shea, 1990). There is evidence for the impact of accumulated (dis)-advantage on later-life QoL, with exposure to multiple periods of low socioeconomic status across the life-course associated with reduced later-life QoL (Otero-Rodríguez et al., 2011; Niedzwiedz et al., 2012).

Research examining how individual life-course histories influence later-life QoL is under-developed (Platts et al., 2015; Wahrendorf, 2015). Specifically, research into the pathways by which earlier events influence later-life QoL is lacking (Bhatta et al., 2017; Niedzwiedz et al., 2012; Read et al., 2016). Pathway models stress the importance of trajectories, exploring the mediating effects of adult circumstances on earlier exposures. Determining the influence of childhood circumstances on adult outcomes is complex, requiring attention to both direct and indirect pathways of influence (Pavalko and Caputo, 2013). There is evidence that earlier-life outcomes most often indirectly influence later-life QoL with their effects mediated (often fully) by later-life outcomes. For example, as educational attainment is an earlier-life predictor of QoL that is strongly correlated with later predictors, it is likely that the direct effects of education on later-life QoL will be reduced. Indeed, in their study of Australian ‘baby boomers’, Kendig et al. (2016) found the effects of earlier socioeconomic status, including education, on QoL were largely mediated by later-life socioeconomic status.

However, the slate of earlier life is not always ‘wiped clean’ (Schafer et al., 2011) and early disadvantage can directly impact on later-life outcomes. There is some evidence for direct effects of childhood circumstances on adult QoL. For example, the number of books, recorded retrospectively, in the childhood home (a proxy measure of human capital) was found to directly affect later-life QoL (Kendig et al., 2016). Most recently, Bhatta et al. (2018) found a negative direct effect of parental education on QoL among older adults in India (they theorise that this could be explained by unrealistic expectations placed on the offspring of highly-educated parents). Direct effects of earlier-life circumstances can be interpreted as evidence of a ‘critical period’ (Bhatta et al., 2017). Critical period (or latent effects) models suggest that, independent of other life-course exposures, events during a critical period (where an individual is particularly vulnerable; for example, during growth in adolescence) have a lasting impact on later-life health (Ben-Shlomo and Kuh, 2002).

This present study aims to explore pathways through which a range of socioeconomic factors across the life-course influence later-life QoL. A path analysis, combining a priori theory and statistical testing, is used to decompose the total estimated effects of each factor into those that influence QoL directly and those with an indirect effect mediated through ‘down-stream’ factors. As most birth cohorts are yet to reach older age and no prospective early-years data available in the surveys of older adults, a lack of prospective data is a particular challenge for research into the life-course predictors of later-life QoL. Previous studies of later-life QoL have been forced to rely either on retrospective (Wahrendorf and Blane, 2014) or on cross-sectional data (Hyde et al., 2015). These studies are likely to suffer from bias introduced by limited recall and confounding intervening experiences (Pavalko and Caputo, 2013) and the inability to correctly model the life-course. Our study, the first to use prospective data collected from birth and across the life-course, allows us to overcome these sources of bias, resulting in more robust estimates of the pathways affecting QoL.

Section snippets

Methods

Path analysis, an extension of multivariable regression, is a model-testing procedure, with the path model built on theory and existing knowledge. Based on the existing literature, a range of socioeconomic characteristics found to influence QoL were identified and modelled. While there are many pathways that could be modelled, there is a trade-off between completeness and parsimony (Platts et al., 2015). While theory can guide the selection of characteristics and potential paths, path analysis

Sample characteristics

Table 2 reports descriptive statistics for the sample. The mean CASP-19 score was 44.0 (S.E. 0.46). Characteristics of the sample included in this analysis were not significantly different to those of the whole cohort.

Bivariate correlations

Table 2 also reports bivariate correlations among the variables that formed the basis of the estimated path model. The strongest correlations were found between later-life self-rated health, mid-life occupational social class and adverse events in childhood.

Path analysis results

Fig. 1 illustrates

Discussion

This study adds to the limited existing knowledge of life-course predictors of QoL in older age (Blane et al., 2004) by exploring pathways through which socioeconomic advantage across the life-course contributed to later-life QoL in an early ‘baby-boom’ birth cohort.

Conclusion

Now that older-age is no longer necessarily characterised by poverty and poor health, policies have focused on promoting broader notions of ‘quality’ in later life. As a measure of later-life QoL, the CASP-19 scale was developed to move beyond a focus on decline and dependency in older age and reflect the positive and beneficial aspects of the ‘third age’ (Hyde et al., 2015). This study is the first to use prospective data to address the ‘fundamental question’ of whether the mechanisms by which

Acknowledgments

The authors gratefully acknowledge the Newcastle Thousand Families Study members for their continued participation in this study. We also thank two anonymous reviewers for their constructive comments. This work was supported by the Economic and Social Research Council [grant number: ES/J500082/1].

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