Descriptive statistics illustrating study variables adjusted for the sample weights are shown in . Participants’ mean age was 46 years, 52% were women (632 unweighted cases), 26% were currently married and 57% were non-Hispanic black, 22% Latino and 19% non-Hispanic white. One-third (33%) reported education beyond high school and 23% reported annual household incomes of >$35K. Thirty-seven per cent reported that they currently smoked, 24% never engaged in physical activity, mean BMI was 31, and mean waist circumference was 98 centimetres (about 39 inches). Results from tests for multicollinearity among the independent variables showed variance inflation factors of 1.3–1.6, well below the cut point of 4.0 commonly considered indicative of multicollinearity. Similarly, tolerances ranged from 0.61 to 0.76, comfortably above the levels of ≤0.20 considered to be indicative of multicollinearity.
Descriptive statistics for study variables – full sample (N = 919)
Results presented in provide partial support for our hypothesis that SEP is associated with multiple CVD risk factors. Household income <$10K was positively associated with depressive symptoms (p<0.001), current smoking (p = 0.05), physical inactivity (p<0.05) and waist circumference (p<0.05). Income $10–19K was also positively associated with depressive symptoms (p<0.01). Relationships between income and BMI were in the expected direction but not statistically significant.
Table 3 Depressive symptoms, smoking, physical activity, BMI and waist circumference regressed on education, income, everyday unfair treatment, acute unfair treatment, financial vulnerability, neighbourhood social environment stress, neighbourhood physical environment (more ...)
Participants who had completed high school were more likely than those with some college to report current smoking (p<0.01), and those with less than a high school education were less likely to report physical activity (p<0.05). A significant association between <12 years of education and depressive symptoms when income was not included in the model (results not shown) was no longer significant when income was included in model 1. Coefficients for relationships between education and psychosocial stressors and anthropometric indicators were not statistically significant.
Results shown in model 2 () indicate that psychosocial stressors are associated with four of the five CVD risk factors examined here. Everyday (p<0.001) and acute (p<0.05) unfair treatment, financial vulnerability (p<0.05), neighbourhood social environment (p<0.001) and acute life events (p<0.001) are each significantly associated with symptoms of depression. Regression coefficients for relationships between income and depressive symptoms were reduced by 32% (income <$10K) and 21% (income $10–19.9K), but remained statistically significant. Model 2 accounted for three times the proportion of variance in depressive symptoms explained in model 1 (28% versus 9%).
Indicators of financial vulnerability (p<0.05), neighbourhood physical environment (p<0.05), and acute life events (p<0.05) were significantly associated with current smoking. The inclusion of psychosocial stressors reduced the association between income <$10K and current smoking to non-significance, and the amount of variance explained by the model increased significantly (p = 0.01).
Financial vulnerability (p<0.01) and acute unfair treatment (p<0.05) were significantly and negatively associated with level of physical activity. The inclusion of psychosocial stressors in model 2 reduced the relationship between income <$10K and physical activity to non-significance, and between education below high school and physical activity by 21% (p<0.05), and increased the amount of variation explained significantly (p<.01). Finally, acute life events was significantly associated with waist circumference (p<0.01) and reduced the relationship between income <$10K and waist circumference in model 1 to non-significance.
To test the hypothesis that indicators of psychosocial stress mediate relationships between SEP and symptoms of depression, smoking, physical activity and waist circumference, we examined relationships between indicators of psychosocial stress, income and education. After controlling for other demographic variables, we found no relationship between education and any of the indicators of psychosocial stress considered in these models (results not shown). Household income was significantly associated with financial vulnerability and acute life events (). Combined with results shown in , these findings provide evidence that is consistent with the hypothesis that relationships between income and symptoms of depression, current smoking, physical activity and waist circumference are partially or fully mediated through the effects of income on financial vulnerability and acute life events as indicators of psychosocial stress.
Table 4 Everyday unfair treatment, acute unfair treatment, financial vulnerability, neighbourhood social environment, neighbourhood physical environment and acute life events regressed on household income (controlling for age, gender, marital status, number in (more ...)
Results from (model 1) and are summarised in . Education, net of income, affects mainly smoking and physical activity, whereas income affects depressive symptoms and waist circumference in addition to smoking and physical activity. Overall, income is a more consequential risk factor for CVD in this population. Results shown in (model 2) indicate that relationships between income and four of the five indicators of CVD risk are at least partially mediated through increased levels of financial vulnerability and acute life events. Several additional indicators of psychosocial stress make significant independent contributions to the dependent variables, but we did not find evidence that they mediate relationships between SEP and indicators of CVD risk in this sample.
Relationships between income and education, and psychosocial stress, psychosocial distress, behavioural and anthropometric risk factors (summary of results shown in , model 1 and ). (Further details available online.)
Symptoms of depression and behavioural and anthropometric risk factors
shows results from analyses testing the contributions of depressive symptoms (model 3); and behavioural risk factors (model 4).
Table 5 Smoking, physical activity, BMI and waist circumference regressed on education, income, everyday unfair treatment, acute unfair treatment, financial vulnerability, neighbourhood social environment stress, neighbourhood physical environment stress, acute (more ...)
Results shown for model 3 indicate that depressive symptoms are significantly associated with current smoking (p<0.001) and waist circumference (p<0.05), but not physical activity or BMI, although the latter coefficients are in the expected direction. The inclusion of depressive symptoms in model 3 significantly improves the fit of the models for both current smoking (p<0.01) and waist circumference (p<0.05), indicating that depressive symptoms contribute independently to the explanatory value for these dependent variables. For each unit increase in depressive symptoms, there was a 2.97 cm increase in waist circumference.
Results for model 4 indicate significant negative associations between current smoking and both BMI (p<0.001) and waist circumference (p<0.01). Relationships between physical activity and BMI and waist circumference were in the expected direction but were not statistically significant. The size of the coefficient for depressive symptoms increased from 0.51 to 0.96 for BMI (n.s.) and from 2.97 to 3.71 (p<0.05) for waist circumference. This suppression effect47
occurred because the direct effects of depressive symptoms on waist circumference were positive whereas the mediated effects (through probability of current smoking) were negative, so the full effects of depressive symptoms on waist circumference were not visible until the effect of current smoking was controlled. The addition of behavioural predictors in model 4 increased the overall explained variance for BMI from 0.02 to 0.07 (p<0.001) and for waist circumference from 0.06 to 0.09 (p<0.01). Findings from (model 2) and are summarised in .
Relational pathways between income, psychosocial stress, psychological distress, current smoking, physical inactivity and waist circumference (summary of results shown in -). (Further details available online.)