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. 2014 May;69(3):451-60.
doi: 10.1093/geronb/gbt122. Epub 2014 Feb 4.

Early-life socioeconomic status and mortality in later life: an integration of four life-course mechanisms

Tetyana Pudrovska  1 , Benedicta Anikputa
Affiliations

Early-life socioeconomic status and mortality in later life: an integration of four life-course mechanisms

Tetyana Pudrovska et al. J Gerontol B Psychol Sci Soc Sci. 2014 May.

Abstract

Objectives: Using data from the Wisconsin Longitudinal Study, we examine (a) how socioeconomic status (SES) at age 18 affects all-cause mortality at ages 54-72, and (b) whether the effect of early-life SES is consistent with the critical period, accumulation of risks, social mobility, and pathway models. We also explore gender differences in the effect of early-life SES and life-course mechanisms.

Method: Participants (N = 6,547) were surveyed in 1957, 1975, and 1993, with vital status established until 2011. We combine discrete-time survival analysis with structural equation modeling. SES and health behaviors are modeled as latent factors.

Results: Early-life SES affects mortality indirectly via status attainment and health behaviors in adulthood and midlife. This finding is contrary to the critical period and consistent with the pathway model. Persistent disadvantage at three life stages is a strong risk factor for mortality, thus, supporting the accumulation of risks. Moreover, the mortality risk of individuals who experienced downward socioeconomic mobility is comparable to their peers with persistent disadvantage.

Discussion: This study highlights the complexity of interrelated life-course processes underlying the effect of early-life SES on mortality in later life.

Keywords: Gender; Health behaviors; Life course; Mortality; Socioeconomic status..

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Figures

Figure 1.
Figure 1.
The discrete-time survival model with latent variables estimating the effects of SES on mortality: The Wisconsin Longitudinal Study, 1957–2011 (N = 6,547). SES = socioeconomic status; HB = health behaviors. The measurement model for SES and health behavior factors is shown in Table 1.
Figure 2.
Figure 2.
Predicted probability of mortality based on social mobility categories: The Wisconsin Longitudinal Study, 1957–2011 (N = 6,547). Based on the best-fitting model shown in Table 2 to which all possible interactions among latent factors (SES in 1957, 1975, and 1993) were added. “High” refers to high SES at a given life stage (1 SD above the mean). “Low” refers to low SES at a given life stage (1 SD below the mean).
See this image and copyright information in PMC

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