The Effects of Childhood, Adult, and Community Socioeconomic Conditions on Health and Mortality among Older Adults in China

Abstract

Using a large, nationally representative longitudinal sample of Chinese aged 65 and older, this study examines the effects of childhood, adult, and community socioeconomic conditions on mortality and several major health outcomes. The role of social mobility is also tested. We find that childhood socioeconomic conditions exert long-term effects on functional limitations, cognitive impairment, self-rated health, and mortality independent of adult and community socioeconomic conditions. Achieved conditions matter for most outcomes as well, considering that adult and community socioeconomic conditions have additional impacts on health among Chinese elders. The majority of the effects of childhood conditions are not mediated by adult and community conditions. The results also show that social mobility and health in later life are linked in complex ways and that psychosocial factors have marginal explanatory power for the effects of socioeconomic conditions. Overall, this study provides new longitudinal evidence from China to support the notion that health and mortality at older ages are influenced by long-term and dynamic processes structured by the social stratification system. We discuss our findings in the context of the life course and ecological perspective, emphasizing that human development is influenced by a nexus of social experiences that impact individuals throughout life.

Studying Disability Trends in Aging Populations

“…A growing number of studies have shown that beyond the individual level, macrosocioeconomic development and ecological (or socio-ecological) factors also play a role in individual physical functioning and disability at older ages (e.g., Beard et al 2009;Clarke et al 2009;Freedman et al 2008a;Pruchno et al 2012;Wen and Gu 2011;Zeng et al 2010). Collectively, these studies show that lower rates of disability are associated with more affluent neighborhoods/communities.…”

“…Explanations for why individuals with higher SES have better physical functioning is generally attributed to health knowledge, behaviors, psychosocial factors (e.g., social support), and material resources (e.g., housing conditions and access to healthcare) (see Martin et al 2011;Wen and Gu 2011). The avoidance of smoking and a sedentary lifestyle, maintaining social ties, purchasing health commodities, and receiving timely medical treatment and care are all likely mechanisms that explain why people with higher socioeconomic status have lower levels of disability than those with lower socioeconomic status.…”

Families and Health: A Review

“…Next to showing a consistently negative correlation between low early-life SES and self-rated health in adulthood, studies also revealed a significant relationship between childhood SES and older adults' risk of suffering from functional limitations (e.g., Haas 2008;Huang et al 2011;Wen and Gu 2011), cognitive impairment (e.g., Wen and Gu 2011;Zhang et al 2008), as well as chronic conditions and depressive symptoms (e.g., Luo and Waite 2005;Pavela and Latham 2016). Along the same lines, poor childhood health was shown to have long-term negative effects on, for example, individuals' functional status (e.g., Haas 2008;Huang et al 2011) and chronic health conditions (e.g., Blackwell et al 2001;Haas 2007).…”

Concordance and discordance between objectively and subjectively measured successful aging and their linkages with mortality

“…To obtain robust results, we controlled several sets of covariates that are shown in the literature to be associated with mortality (Wen and Gu, 2011); the covariates included demographics, socioeconomic status, and health practice. Demographics included age, residence (urban vs. rural), and ethnicity (Han vs. non-Han).…”

“…To reduce possible bias due to missing values in the analysis and inferences, we employed multiple imputation techniques for all variables. We did not apply sampling weights to the regression models because the CLHLS weight variable was unable to reflect the national population distributions with respect to variables other than age, sex, and urban/rural residence (Wen and Gu, 2011) We also performed additional tests to examine improved predictive power of concordance and discordance of OSA and SSA for mortality risk (controlling for all covariates in the analysis) by performing two alternative models that treated OSA and SSA as two independent variables. All analyses were performed using STATA 13.0.…”