Life course socioeconomic position, depressive symptoms, and cardiovascular disease mortality in the Alameda County Study 1965-2000.

Abstract

Background: Lower socioeconomic position (SEP) over the life course has been posited as a contributing factor in the development of chronic illnesses, including cardiovascular disease (CVD) and subsequent mortality (CVDM). Lower SEP has also been shown to be associated with an increased risk of mental health problems, such as multiple depressive symptoms (MDS). The ways in which SEP has been measured have varied, but examination of the variability in associations of measures based on a single SEP indicator such as household income (HI) with health outcomes is limited, especially within gender. Methods: Data from the Alameda County Study was used to study the relationships of interest. Using three measures of HI to capture SEP- HI in 1994 (HI94), average HI (AHI), and HI trajectory groups (HITG), associations between each HI measure and CVDM (Chapter 2) and MDS (Chapter 3) were studied. Chapter 4 examined cumulative socioeconomic disadvantage (CSD) based on HI, education, father’s education, and father’s occupation in relation to CVDM. Results: Chapter 2 analyses suggested inverse associations between lower quartiles of HI94 and the hazards of CVDM among men, and between higher AHI and the hazards of CVDM among women. In chapter 3, results showed inverse associations between quartiles of HI94 and AHI, lower HITG, HI94 and AHI with the odds of MDS for men. Associations were of greatest magnitude for HITG and HI94 compared to the quartile measures and AHI, respectively. Among women, those in the lowest HITG had increased odds of MDS. Chapter 4 analyses revealed that being most disadvantaged was associated with increased hazards of CVDM among women but not men. Associations were of greatest magnitude for CSD scores that included HITG. Conclusions: Men and women with higher SEP or lower CSD were less likely to experience CVDM or MDS, but the magnitude of these associations varied with changes in the HI measure utilized. These results show the need to consider gender-specific SEP measures, as well as to carefully select the SEP measures as the associations with different health outcomes may vary dependent upon the specific measure examined.