Keywords

Introduction

The long-lasting influence of childhood socioeconomic circumstances on adulthood health has been documented across two decades of flourishing research in the fields of social epidemiology, medical sociology and life course (Boyce & Hertzman, 2018; Cohen et al., 2010; Demetriou et al., 2015; Galobardes et al., 2004; Galobardes et al., 2008; Kuh et al., 2004). However, largely because most evidence to date has been based on birth cohort studies that were initiated after World War II, whether this influence remains in the second half of life (50 years and after) remains unclear. For example, in the United Kingdom, birth cohort studies started in 1946, 1958 and 1970, and the oldest participants from these studies had just entered their seventh decade in 2016. As researchers wait for the maturation of birth cohort studies, detailed retrospective information collected in longitudinal panel studies of respondents aged 50 years and older, such as the Health and Retirement Study in the United States, the English Longitudinal Study of Ageing in England, and the Survey of Health, Ageing and Retirement in Europe (SHARE), can contribute to the understanding of the long-lasting influence of childhood, including socioeconomic circumstances, on old-age health. Specifically, these longitudinal studies collected information about the life course between childhood and the second half of life, thereby offering an opportunity to investigate whether the influence of childhood socioeconomic circumstances on health in the second half of life is attenuated by adulthood socioeconomic characteristics. Moreover, owing to their panel design, these studies have allowed changes in health statuses or health trajectories to be examined. In 2016, the LIFETRAIL project (LIFETRAIL) was launched within the LIVES research program to consolidate the evidence about this long-lasting influence of childhood on health in older age by using the SHARE data and to examine whether adulthood socioeconomic characteristics can attenuate this influence. In this review, we summarise two findings of the LIFETRAIL project. First is the gendered impact of childhood socioeconomic disadvantage on health and illness in older age (health statuses and health trajectories). Then, we assess to what extent the influence of childhood socioeconomic disadvantage is attenuated or mediated by adulthood socioeconomic characteristics. Second, we take advantage of SHARE’s multi-country design to examine whether the childhood socioeconomic disadvantage and older-age health links differ across welfare states. Finally, these results are discussed in light of their strengths and limitations to determine their level of causality.

Background

The lack of resources is a driver of vulnerability, which is defined as the inability to avoid, cope with, and recover from individual, social, and environmental stressors (Spini et al., 2017). The consequences of such inabilities are more detrimental when they occur during critical or sensitive periods of the life course (Ben-Shlomo & Kuh, 2002; Wadsworth, 1997) and when they accumulate over time through long lifetime exposure to stressors (e.g., living in poverty or living in highly deprived or polluted neighbourhoods). In addition, people are more at risk of vulnerability when they do not have sufficient reserves to recover from stressors (Cullati et al., 2018).

The life course perspective suggests that complex social dynamic processes lie at the origin of vulnerability in health (Burton-Jeangros et al., 2015). In the LIFETRAIL project, the precursors of poor health status and of an accelerated declining health trajectory in the second half of life were sought in people’s exposure to disadvantaged structural and interpersonal stress and lack of socioeconomic resources in childhood and adulthood. In other words, health status and health trajectory in old age were considered the result of a social process. The dynamics of this social process were considered in light of two models in life course epidemiology. First, the accumulation model (O’Rand, 1996) suggests that the lifetime duration of exposure to environmental and socioeconomic disadvantages is the driver of health inequalities. The longer the individual is exposed to disadvantages, the higher the risk of poor health and being diagnosed with illnesses. An accumulation of exposures to disadvantages over the life course (from childhood to adulthood) places these people at higher risk of exposure to stress, lower development of the (social, economic, cognitive) resources required to counteract stressors, and, ultimately, to increasing later-life health differences between disadvantaged and advantaged groups (Dannefer, 2003, 2020). A second model, the critical period model (Ben-Shlomo & Kuh, 2002; Wadsworth, 1997), hypothesises that health differences are explained by exposures that occur in specific periods of human development. In utero life, infancy, childhood, adolescence, and young adulthood are critical and sensitive periods for the development of physical and mental health as well as the resources required to sustain this health over the life course. Therefore, exposure to structural and interpersonal adversities during these periods may lead to potentially irreversible damage or ‘structural’, permanent differences in later-life health.

Based on the accumulation and critical period models, the LIFETRAIL project examined the mechanisms underlying the long-term effects of retrospective childhood socioeconomic disadvantage on (1) health status and (2) health trajectories in older age.

A Multidimensional Measure of Childhood Socioeconomic Disadvantage

The LIFETRAIL project used a comprehensive and multidimensional measure of childhood socioeconomic disadvantage. In the SHARE study, life course information was measured with the ‘SHARELIFE’ module, which was administered during the third (2008/2009) and seventh (2017) waves of data collection. SHARELIFE consisted mainly of a detailed retrospective assessment of respondents’ life course.

Childhood socioeconomic disadvantage was operationalised according to the Wahrendorf and Blane measure of childhood circumstances (Wahrendorf & Blane, 2015). This measure is an index combining four binary indicators of disadvantaged socioeconomic circumstances at the age of 10 years. First, the occupational position of the main breadwinner was constructed on the basis of a reclassification of the main occupational groups of the International Standard Classification of Occupations (ISCO) according to their skill levels (Wahrendorf et al., 2013). The first and second skill levels were grouped as ‘disadvantaged’ and the third and fourth levels as ‘advantaged’ occupational positions. Second, a binary item was constructed for the number of books at home, with ‘none to 10 books’ being an indicator of social disadvantage (Evans et al., 2010). Third, household overcrowding used information related to the number of people living in the household and the number of rooms (excluding kitchens, bathrooms, and hallways). We combined the information to specify that more than one person living in the household per room was equal to overcrowding (Marsh et al., 1999). Fourth, the quality of the household was assessed by the presence of the following facilities: fixed bath, cold running water supply, hot running water supply, inside toilet, and central heating. If none of this equipment was present, the household was coded as ‘disadvantaged’ (Dedman et al., 2001). By summing these four binary indicators, we computed a five-level categorical variable of childhood socioeconomic disadvantage (most disadvantaged, disadvantaged, middle, advantaged and most advantaged).

With this index, we examined the influences of childhood socioeconomic disadvantage on multiple health outcomes, which we grouped as follows (WHO, 1946) for the purposes of this review: physical health (muscle strength, peak expiratory flow); chronic conditions (cancer onset, metabolic syndrome, multimorbidity, and polypharmacy); functional health (disability and frailty); mental health (cognitive function, depression, and sleep troubles); and health behaviour (physical inactivity). We also examined two indicators of general health (the single item ‘self-rated health’, an umbrella indicator capturing most dimensions of health (Cullati et al., 2020), and well-being). All health outcomes were self-reported indicators based on single questions or validated scales (Euro-D for late life for depression (Prince et al., 1999); quality of life (CASP-19) for well-being (Hyde et al., 2003); functional limitations with activities of daily living, ADL and IADL, for disability (Katz et al., 1963; Lawton & Brody, 1969)), except for two biomarkers, muscle strength (based on grip strength (Leong et al., 2015)) and lung function (based on peak expiratory flow (Wright, 1978)). Cognitive function was measured with cognitive tests (measuring verbal fluency (Rosen, 1980) and delayed recall (Harris & Dowson, 1982)). For frailty, we built a score based on the phenotype of Fried (Fried et al., 2001).

Gender Differences in the Association between Childhood Socioeconomic Disadvantage and Health in Older Age: Do Women Pay the Price?

Association of Childhood Socioeconomic Disadvantage with Late-Life Health Status

In both men and women, based on minimally adjusted models, we observed that the index of childhood socioeconomic disadvantage was associated with physical health, chronic conditions, functional health, and mental health in older age (Table 14.1, part A). Men and women who grew up in disadvantaged socioeconomic households had poorer physical health (lower grip strength (Cheval, et al., 2018a)); more frequently reported chronic conditions (greater incidence of cancer (Bernadette W. A. van der Linden et al., 2018), metabolic syndrome and multimorbidity (Jungo et al., 2020)); reported lower functional health (higher IADL (Landös et al., 2019) and higher frailty (van der Linden, Cheval, et al., 2020a) and poorer mental health (higher depressive symptoms (von Arx et al., 2019)) than participants in advantaged socioeconomic households. Of note, for cancer onset (van der Linden et al., 2018), we observed a higher risk of overall cancer among men and women born in advantaged households. This result can be explained by the higher rates of cancer screening among socioeconomically advantaged people. Among women only, we observed additional associations of the index of childhood socioeconomic disadvantage with polypharmacy, limitations in activities of daily living (ADL), sleep troubles, and physical inactivity (Jungo et al., 2020; Landös et al., 2019; van de Straat et al., 2020; Cheval et al., 2018b).

Table 14.1 Summary of (A) the associations of the childhood socioeconomic disadvantage index with health, illness and behaviour outcomes in the second half of life among men and women and (B) whether the association was partially or fully attenuated by socioeconomic conditions and status in adulthood
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In analyses that grouped men and women, we observed supplementary robust associations of childhood socioeconomic disadvantage with physical health (grip strength (Cheval et al., 2018a), lung function (Cheval et al., 2019a)) and general health (self-rated health (Sieber et al., 2019)). These results suggested that the index of childhood socioeconomic disadvantage (Wahrendorf & Blane, 2015) was a heuristic indicator of socioeconomic circumstances in early life. This finding raised the question of what within this index drives this relationship. After disaggregating it and examining the four binary factors separately, we observed that, among both men and women, most associations were driven by the number of books and less frequently by household (overcrowding, number of facilities) and occupation of the main breadwinner indicators (Table 14.2). This remarkable result points out the importance of the cultural dimension in the measure of socioeconomic resources, which may play a key role in the transformation of social inequality into health inequalities (Abel, 2008).

Table 14.2 Summary of significant childhood socioeconomic factors associated with six health trajectories (A) before and (B) after adjustment for adulthood socioeconomic characteristics. (Cheval, Orsholits, et al., 2019c)
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The Influence of Adulthood Socioeconomic Characteristics

Considering that a disadvantaged start in life does not necessarily impair health for the rest of the life course, we investigated whether the above associations can be cancelled or attenuated by adult-life socioeconomic characteristics (three indicators: educational achievement in early adulthood, main occupation in middle age and satisfaction with household income in older age). After adjusting for these three indicators of adult-life socioeconomic characteristics (Table 14.1, part B), the results showed that in men, the impact of socioeconomic disadvantage in the beginning of life disappeared for most health dimensions (physical health, functional health, and mental health). For example, childhood socioeconomic disadvantage was no longer associated with muscle strength, metabolic syndrome, IADL, frailty and depressive symptoms. In contrast, in women, childhood socioeconomic disadvantage remained associated with seven of the ten health indicators, representing the health dimensions of chronic conditions and functional and mental health. Notably, these results were robust to adjustment with risk factors associated with the outcomes and to adjustment with other childhood circumstances, such as health status and adverse experiences (Cheval et al., 2019b; van der Linden, Cheval, et al., 2020a; von Arx et al., 2019).

In summary, men were better able to compensate for a difficult socioeconomic start in life, while women seemed to pay the price of this bad start. At least for women, our results supported the critical period model, i.e., that exposure to socioeconomic disadvantages in early life may lead to potentially permanent differences lasting into old age. Gender inequalities in education and occupation in the twentieth century could be one of the main explanations. Indeed, most women who grew up during the first half of the twentieth century may have faced social barriers in accessing life course opportunities, such as access to skills (due to social limitations in pursuing education at the higher secondary and tertiary levels), economic resources (due to social limitations in access to employment), and social resources (Breen et al., 2010). These social barriers could also be linked to the internalisation of and conformity to misleading norms such as gender norms related to the division of paid and family work (Widmer & Spini, 2017).

Association of Childhood Socioeconomic Circumstances with Late-Life Health Trajectories

We tested whether childhood socioeconomic disadvantage could affect health trajectories (Burton-Jeangros et al., 2015) or the evolution of health throughout ageing. For example, we investigated potential accelerated or reduced rates of health decline between disadvantaged and advantaged groups (Dannefer, 2003, 2020). The main result was that participants’ health trajectories throughout ageing (or slopes) ran mostly parallel between childhood socioeconomic groups—a result that did not support the accumulation model. This finding has also been reported in a multi-outcome study suggesting that childhood socioeconomic disadvantage robustly influenced health status but not health trajectories (Cheval, Orsholits, et al., 2019c) and in single-outcome studies (Sieber et al., 2020; van de Straat et al., 2020; van der Linden, Cheval, et al., 2020a). One exception, however, was observed for cognitive function (Aartsen et al., 2019). We observed that participants who grew up in advantaged households had stronger declines in verbal fluency (an indicator of cognitive function) compared to disadvantaged participants, but this decline started at a later age and from higher levels of fluency. This result supported the cognitive reserve hypothesis (Stern, 2009) and suggests that cognitive reserves delay cognitive decline throughout ageing, but that deterioration occurs more rapidly as decline begins. The mechanism behind this effect could be that participants with socioeconomic advantages had a greater chance of building and maintaining cognitive reserves throughout their life course: They were more likely to live in family environments with higher mental stimulation, increased encouragement of learning and curiosity, and endorsement of healthy behaviours (such as practicing regular physical activities and eating a healthy diet); had a greater chance of achieving a higher level of educational achievement; and might have well-off occupations that allowed more leisure time and higher income. This mechanism applies to the SHARE participants who lived most of their professional lives during the second half of the twentieth century, but it would be hazardous to generalise to more recent cohorts.

Multilevel Perspective on the Influence of Childhood Socioeconomic Circumstances on Health in Older Age: The Importance of Welfare States and Social Protections

We explored the multilevel dimension of vulnerability (Spini et al., 2017) in health in older age through macro- (welfare regimes, social protection expenditure) and meso-level (neighbourhood) perspectives.

Macro Level: The Welfare Regimes

We examined whether country-level social protection offered by institutions could attenuate the negative influence of a poor socioeconomic start in life. We approached social protection through the welfare regimes approach, using the typology of Ferrera (1996), an extension of the Esping-Andersen welfare regime typology (Esping-Andersen, 2006). We grouped countries included in SHARE into the following welfare regimes: Scandinavian, Bismarckian, Southern European, and Eastern European. We observed that in the Scandinavian (important interventionist state, generous redistributive system) and Southern European regimes (fragmented welfare system, more important reliance on the family and charitable sector), the association between childhood socioeconomic disadvantage and self-rated health became nonsignificant when including adulthood socioeconomic characteristics. In contrast, this association remained in the Bismarckian (minimal redistributive system administered by the employer, importance of the family) and Eastern European regimes (shift from universalist communist welfare to marketised welfare) (Sieber et al., 2020). For frailty, the association vanished in the Eastern European regime and appeared in the Bismarckian regime (van der Linden, Sieber, et al., 2020b). Considering each adulthood socioeconomic characteristic separately, we observed that education attenuated the association between childhood and self-rated health in Scandinavian and Southern European regimes but not in the other welfare regimes (Sieber et al., 2019). Occupation demonstrated similar results, as it attenuated the association between childhood and self-rated health in the Scandinavian and Bismarckian regimes only.

Macro Level: Social Protection Expenditure

Although informative, these results related to social protection are restricted by the limitations of the welfare regime approach. This approach represents an insufficiently detailed proxy of social protection, as the clustering of countries is broad and lacks specificity (Lundberg et al., 2015). Moreover, such an approach can result in inconsistent patterns in how social democratic welfare regimes may reduce social inequalities in health in comparison to other regimes (Brennenstuhl et al., 2012). Thus, we implemented the social protection expenditure approach in this line of investigation and used the net social protection expenditure of the European System of Integrated Social Protection Statistics (European Union, 2019), an indicator in which expenditures on social protection policies are computed as the percentage of the country’s gross domestic product. We found that longer exposure to socioeconomic disadvantage throughout the life course (using a score combining socioeconomic disadvantages in childhood, young adulthood, middle age and older age)Footnote 1 was associated with worse subjective (self-rated health) and objective (lower muscle strength) health among women and men. This result supported the accumulation model, as living for a longer time in disadvantaged socioeconomic conditions over the life course increased the risk of poor subjective and objective health. Social protection expenditure was not directly associated with self-rated health and muscle strength, as expected. However, social protection expenditures attenuated the negative influence of life course socioeconomic disadvantage, and while this attenuation was observed in both genders for objective health, it varied between genders for subjective health: Higher social protection expenditure reduced the negative effect of life course socioeconomic disadvantage in women’s self-rated health only (Sieber et al., 2022), suggesting that women benefited more from social protection expenditure than men.

Meso Level: The Neighbourhood

We also focused on a meso-level factor, the neighbourhood, by examining the association between neighbourhood characteristics and depression and how childhood socioeconomic circumstances might modify this association (Baranyi et al., 2019). We observed that childhood socioeconomic circumstances might influence vulnerability to neighbourhood effects in older age. Participants who grew up in better circumstances were at lower risk of developing depression when living in a residential area with good access to local services. In contrast, they were at higher risk of developing depression when residing in areas with high neighbourhood nuisances.

Multidomain Perspective on the Influence of Childhood Socioeconomic Circumstances on Health in Older Age

To explore the multidomain dimension of vulnerability (Spini et al., 2017) in health in older age, we focused on marital life. We examined whether childhood socioeconomic disadvantage moderated the relationship between later-life widowhood and depressive symptoms in older age (Recksiedler et al., 2021). The hypothesis was that childhood socioeconomic disadvantage might trigger cumulative adversity and stressors across the life course that would shape how individuals may come through the stressful life event of widowhood later on. We found that experiencing widowhood and childhood socioeconomic disadvantages were both linked to depressive symptoms in old age. However, we found no evidence that childhood socioeconomic disadvantage aggravated the link between later-life widowhood and depressive symptoms. This result suggested that the experience of becoming bereaved in old age was an impactful transition that similarly triggered the mental health of individuals across different childhood socioeconomic circumstances.

Discussion of the Limitations

We discuss these findings in light of some of the criteria for causation from Hill (Hill, 2015). Foremost, it is important to note that this project is based on observational data, which poses a significant limitation in reaching a causal level in the findings compared to a project based on experimental data. Moreover, we did not perform any causal inference analysis. Therefore, we cannot conclude that the association of childhood socioeconomic circumstances with health is causal. Nevertheless, a number of points strengthen the argument for a causal relationship between childhood and health. First, exposure to childhood circumstances is chronologically ordered before the outcomes. Second, across all health outcomes, we observed a gradient across the five categories of the childhood socioeconomic variable (the higher the advantage was, the lower the risk of illness or the lower the health deterioration). Thus, this gradient suggests a dose-response relationship between exposure (childhood socioeconomic circumstances) and outcome (health). Third, the consistency of the link between childhood socioeconomic circumstances and multiple health outcomes suggests a potential causal relationship. Fourth, there is biological plausibility behind this association. Along with the social and psychological stress mechanisms outlined in the introduction, we also acknowledge that biological mechanisms can operate behind the association of childhood socioeconomic disadvantage with later-life health. Previous studies have suggested that social exposure could impact biological markers and systems, such as epigenetic (Fiorito et al., 2017; Hughes et al., 2018), inflammation (Castagné, Delpierre, et al., 2016a; Castagné, Kelly-Irving, et al., 2016b; Pollitt et al., 2008) and microbiome (Liss et al., 2018; Liu et al., 2019; Qin et al., 2012; Wirbel et al., 2019) outcomes, indicating that several biological pathways may underlie this association.

Finally, a number of limitations need to be stated. First, in SHARE, a small number of participants answered the SHARELIFE module, thereby creating a selection bias in the data. Second, as with all longitudinal panel studies, participant attrition is an issue. To limit this issue, all analyses were adjusted for participant attrition. Third, childhood information was collected retrospectively, which increased the risk of information bias. Fourth, the lack of data about genetic, microbiome, and inflammatory markers in SHARE impeded adjustment of the childhood and health association with these confounders.

Conclusion

In conclusion, the LIFETRAIL project has provided evidence supporting the long-lasting influence of childhood socioeconomic circumstances on women’s health in the second half of life and suggested that social protection may attenuate the negative influence of a poor socioeconomic start in life. For the European cohorts of the SHARE study, men were able to compensate for a bad start in life, while women seemed to pay the price of such a start throughout their life. The explanation for this persistent inequality remains an open question. The answer probably lies as much in social factors (e.g., access to education and occupation, misleading norms) as in possible gender-specific biological mechanisms.

The LIFETRAIL project continues its work at the #PophealthLab of the University of Fribourg in collaboration with the LIVES Center.