Abstract
Introduction: Subjective social status (SSS) is inversely related to allostatic load (AL) markers, but little is known in Hispanics/Latinos. We assessed the hypotheses that SSS would be inversely associated with total AL and subsystem scores, regardless of objective socioeconomic status (OSS). Methods: Data were from baseline of the HCHS/SOL (n = 12,722, aged 18-74y). We assessed SSS using a 10-step ladder. Participants identified on which step they stood in relation to other people in the U.S. Higher scores indicated higher SSS (range: 1-10). Participants self-reported OSS as household income, educational attainment, and employment status. AL was comprised of 16 physiological markers from the parasympathetic (n=2; heart rate variability), inflammation (n=2; C-reactive protein, white blood cell), metabolic (anthropometrics, lipids, glucose, insulin resistance; n=8), and cardiopulmonary (blood and pulse pressures, resting heart rate, lung function; n=4) subsystems. Each marker was assigned a score of 1 if the value exceeded clinical cut-offs (or high-risk quartiles) or the participant reported taking medication to alter the marker. Otherwise, the marker was assigned a score of 0. Scores were summed across the 16 markers to create an AL score (0-16), with higher scores indicating higher AL. Scores were then dichotomized as high (vs. low) if scores were ≥ AL and subsystem medians. Multivariate-adjusted, survey-weighted linear and logistic regression models tested the association of SSS with AL and subsystem scores. Results: Sample means (95% CI) for SSS and AL were 4.4 (4.3-4.5) and 4.2 (4.1-4.3), respectively. A one-step increase on the SSS ladder was associated with lower AL ((β(SE): -0.1(0.02), p=0.003) and metabolic system (-0.04(0.01), p=0.001) scores. After adjusting for OSS, the association between SSS and AL was attenuated (-0.03(0.02), p=0.09), but remained significant for metabolic system scores (-0.03(0.01), p=0.01). When modeling dichotomized AL, a one-step increase was associated with lower odds of high AL (Odds Ratio (OR); 95% Confidence Intervals (CI): 0.94 (0.91-0.98), p=0.001), high parasympathetic system (0.96 (0.93-1.00), p=0.03), and high metabolic system (0.95 (0.92-0.98)) scores. After adjusting for OSS, higher SSS remained associated with lower odds of high AL (0.95 (0.92-0.99), p=0.01) and high metabolic system (0.96 (0.92-0.99), p=0.01) scores, but the association between SSS and lower parasympathetic subsystem scores was attenuated (0.97 (0.94-1.00), p=0.08). SSS was not associated with inflammation or cardiopulmonary subsystems. Conclusions: Among Hispanics/Latinos living in the U.S, OSS attenuated the relationship between SSS and AL. SSS may be influencing AL through the metabolic system, and could provide unique psychological and biobehavioral targets for reducing metabolic risk disparities among Hispanics/Latinos living in the U.S.
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