Social adversity, stress, and alcohol problems: Are racial/ethnic minorities and the poor more vulnerable?

Abstract

Objective: Experiences of racial/ethnic bias and unfair treatment are risk factors for alcohol problems, and population differences in exposure to these social adversities (i.e., differential exposure) may contribute to alcohol-related disparities. Differential vulnerability is another plausible mechanism underlying health disparities, yet few studies have examined whether populations differ in their vulnerability to the effects of social adversity on psychological stress and the effects of psychological stress on alcohol problems.

Method: Data from the 2005 U.S. National Alcohol Survey (N = 4,080 adult drinkers) were analyzed using structural equation modeling to assess an overall model of pathways linking social adversity, depressive symptoms, heavy drinking, and alcohol dependence. Multiple group analyses were conducted to assess differences in the model's relationships among Blacks versus Whites, Hispanics versus Whites, and the poor (income below the federal poverty line) versus non-poor (income above the poverty line).

Results: The overall model explained 48% of the variance in alcohol dependence and revealed significant pathways between social adversity and alcohol dependence involving depressive symptoms and heavy drinking. The effects of social adversity and depressive symptoms were no different among Blacks and Hispanics compared with Whites. However, the poor (vs. non-poor) showed stronger associations between unfair treatment and depressive symptoms and between depressive symptoms and heavy drinking.

Conclusions: Contrary to some prior studies, these findings suggest that racial disparities in alcohol problems may be more a function of racial/ethnic minorities' greater exposure, rather than vulnerability, to chronic stressors such as social adversity. However, observed differences between the poor and non-poor imply that differential vulnerability contributes to socioeconomic disparities in alcohol problems. Efforts to reduce both differential exposure and vulnerability might help to mitigate these disparities.

Figure 1

The overall model in the full sample. Model χ² = 136.0 (46, n = 3,525),p < .001; comparative fit index = .94; Tucker–Lewis index = .97; root mean square error of approximation = .024. Model shows standardized parameter estimates and controls for sex, age, poverty level, employment status, and education in predicting depressive symptoms, heavy drinking, and alcohol dependence (nonsignificant covariates removed). Dashed line (----) represents a tested, but nonsignificant, path. For racial stigma, 1 = stereotypes about my race or ethnic group have affected me personally, 2 = my race or ethnic group influences how people act with me, and 3 = many people have a problem with viewing my racial or ethnic group as equal. For depressive symptoms, 1 = I felt depressed, 2 = I felt sad, 3 = I felt lonely, 4 = I enjoyed life (reverse coded), 5 = I was happy (reverse coded), and 6 = I was bothered by things that don’t usually bother me. *p <.05; ***p < .001.

Figure 2

Differences in vulnerability between poor and non-poor respondents. Non-poor (at or above federal poverty level): Model χ² = 111.9 (39, n = 3,063), p < .001; comparative fit index (CFI) = .94; Tucker-Lewis index (TLI) = .97; root mean square error of approximation (RMSEA) = .025. Poor (below federal poverty level): Model χ² = 53.05 (40, n = 462),p = .08; CFI = .94; TLI = .96; RMSEA = .027. Model shows standardized parameter estimates and controls for sex, age, employment status, and education in predicting depressive symptoms, heavy drinking, and alcohol dependence (nonsignificant covariates removed). ***p <.001.