Early-Life Socioeconomic Disadvantage and Metabolic Health Disparities
Camelia E Hostinar1, Kharah M Ross, Edith Chen
1From the Psychology Department (Hostinar), University of California, Davis, California; Psychology Department (Ross), University of California, Los Angeles, California; and Psychology Department and Institute for Policy Research (Chen, Miller), Northwestern University, Evanston, Illinois.
Objective:
A quarter of the world's population have metabolic syndrome (MetS). MetS prevalence is stratified by socioeconomic status (SES), such that low SES is associated with higher MetS risk. The present study examined the relative roles of early-life SES and current SES in explaining MetS risk.
Methods:
Participants (N = 354; ages = 15-55 years, M [SD] = 36.5 [10.7] years; 55% female; 72.9% white, 16.9% Asian, 10.2% others) were evaluated for SES and MetS. All were in good health, defined as free of chronic medical illness and acute infectious disease. Using occupational status as a proxy for SES, we recruited roughly equal numbers of participants with low-low, low-high, high-low, and high-high combinations of early-life and current SES. We used the International Diabetes Federation definition for MetS using race- and sex-specific cutoffs for waist circumference, triglyceride levels, high-density lipoprotein cholesterol, blood pressure, and glycosylated hemoglobin levels.
Results:
Analyses revealed a main effect of low early-life SES on increased MetS risk according to the three separate definitions. They included the traditional MetS diagnosis (odds ratio [OR] = 1.53, confidence interval [CI] = 1.01-2.33, p = .044), the number of MetS components for which diagnostic thresholds were met (OR = 1.61, CI = 1.10-2.38, p = .015), and a continuous indicator of metabolic risk based on factor analysis (F(1,350) = 6.71, p = .010, partial η = .019). There was also a significant interaction of early-life SES and current SES in predicting MetS diagnosis (OR = 1.54, CI = 1.02-2.34). The main effects of current SES were nonsignificant in all analyses.
Conclusions:
These findings suggest that MetS health disparities originate in childhood, which may be an opportune period for interventions.
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