Background: Health behaviors may contribute to socioeconomic inequalities in mortality, although the extent of such contribution remains unclear. We assessed the extent to which smoking, alcohol consumption, and physical inactivity have mediated the association between socioeconomic status (SES) and all-cause mortality in a representative sample of US adults. Methods: Initiated in 1992, the Health and Retirement Study is a longitudinal, biennial survey of a national sample of US adults born between 1931 and 1941. Our analyses are based on a sample of 8037 participants enrolled in 1992 and followed for all-cause mortality from 1998 through 2008. We used exploratory and confirmatory factor analysis to derive a measure of adult SES based on respondents’ education, occupation, labor force status, household income, and household wealth. Potential mediators (smoking, alcohol consumption, and physical inactivity) were assessed biennially. We used inverse probability–weighted mediation models to account for time-varying covariates. Results: During the 10-year mortality follow-up, 859 (10%) participants died. After accounting for age, sex, and baseline confounders, being in the most-disadvantaged quartile of SES compared with the least disadvantaged was associated with a mortality risk ratio of 2.84 (95% confidence interval = 2.25–3.60). Together, smoking, alcohol consumption, and physical inactivity explained 68% (35–104%) of this association, leaving a risk ratio of 1.59 (1.03–2.45) for low SES. Conclusions: The distribution of health-damaging behaviors may explain a substantial proportion of excess mortality associated with low SES in the United States, suggesting the importance of social inequalities in unhealthy behaviors.

Women are disproportionally affected by human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) in sub-Saharan Africa (SSA). The determinants of gender inequality in HIV/AIDS may vary across countries and require country-specific interventions to address them. This study aimed to identify the socio-demographic and behavioral characteristics underlying gender inequalities in HIV/AIDS in 21 SSA countries. We applied an extension of the Blinder-Oaxaca decomposition approach to data from Demographic and Health Surveys and AIDS Indicator Surveys to quantify the differences in HIV/AIDS prevalence between women and men attributable to socio-demographic factors, sexual behaviours, and awareness of HIV/AIDS. We decomposed gender inequalities into two components: the percentage attributable to different levels of the risk factors between women and men (the “composition effect”) and the percentage attributable to risk factors having differential effects on HIV/AIDS prevalence in women and men (the “response effect”). Descriptive analyses showed that the difference between women and men in HIV/AIDS prevalence varied from a low of 0.68 % (P = 0.008) in Liberia to a high of 11.5 % (P < 0.001) in Swaziland. The decomposition analysis showed that 84 % (P < 0.001) and 92 % (P < 0.001) of the higher prevalence of HIV/AIDS among women in Uganda and Ghana, respectively, was explained by the different distributions of HIV/AIDS risk factors, particularly age at first sex between women and men. In the majority of countries, however, observed gender inequalities in HIV/AIDS were chiefly explained by differences in the responses to risk factors; the differential effects of age, marital status and occupation on prevalence of HIV/AIDS for women and men were among the significant contributors to this component. In Cameroon, Guinea, Malawi and Swaziland, a combination of the composition and response effects explained gender inequalities in HIV/AIDS prevalence. The factors that explain gender inequality in HIV/AIDS in SSA vary by country, suggesting that country-specific interventions are needed. Unmeasured factors also contributed substantially to the difference in HIV/AIDS prevalence between women and men, highlighting the need for further study.

The Sustainable development goals (SDGs) have the potential to have a significant impact on maternal and child health through their commitments both to directly addressing health services and to improving factors that form the foundation of social determinants of health. To achieve change at scale, national laws and policies have a critical role to play in implementing the SDGs’ commitments. One particular policy that could advance a range of SDGs and importantly improve maternal and infant health is paid parental leave. This article analyzes literature on paid leave and related policies relevant to SDG 1 (poverty), SDG 3 (health), SDG 5 (gender equality), SDG 8 (decent work), and SDG 10 (inequality). In addition, this article presents global data on the prevalence of policies in all 193 UN Member States. A review of the literature finds that paid parental leave may support improvements across a range of SDG outcomes relevant to maternal and child health. Across national income levels, paid leave has been associated with lower infant mortality and higher rates of immunizations. In high-income countries, studies have found that paid leave increases exclusive breastfeeding and may improve women’s economic outcomes. However, factors including the duration of leave, the wage replacement rate, and whether leave is made available to both parents importantly shape the impacts of paid leave policies. While most countries now offer at least some paid maternal leave, many provide less than the 6 months recommended for exclusive breastfeeding, and only around half as many provide paternal leave. To accelerate progress on the SDGs’ commitments to maternal and child health, we should monitor countries’ actions on enacting or strengthening paid leave policies. Further research is needed on the duration, wage replacement rate, and availability of leave before and after birth that would best support both child and parental health outcomes and social determinants of health more broadly. In addition, further work is needed to understand the extent to which paid leave policies extend to the informal economy, where the majority of women and men in low- and middle-income countries work.

Background: Early-life socioeconomic status (SES) is associated with adult chronic disease, but it is unclear whether this effect is mediated entirely via adult SES or whether there is a direct effect of adverse early-life SES on adult disease. Major challenges in evaluating these alternatives include imprecise measurement of early-life SES and bias in conventional regression methods to assess mediation. In particular, conventional regression approaches to direct effect estimation are biased when there is time-varying confounding of the association between adult SES and chronic disease by chronic disease risk factors. Methods: First-reported heart disease, diabetes, and stroke diagnoses were assessed in a national sample of 9760 Health and Retirement Study participants followed biennially from 1992 through 2006. Early-life and adult SES measures were derived using exploratory and confirmatory factor analysis. Early-life SES was measured by parental education, father's occupation, region of birth, and childhood rural residence. Adult SES was measured by respondent's education, occupation, labor force status, household income, and household wealth. Using marginal structural models, we estimated the direct effect of early-life SES on chronic disease onset that was not mediated by adult SES. Marginal structural models were estimated with stabilized inverse probability-weighted log-linear models to adjust for risk factors that may have confounded associations between adult SES and chronic disease. Results: During follow-up, 24%, 18%, and 9% of participants experienced first onset of heart disease, diabetes, and stroke, respectively. Comparing those in the most disadvantaged with the least disadvantaged quartile, early-life SES was associated with coronary heart disease (risk ratio = 1.30 [95% confidence interval = 1.12–1.51]) and diabetes (1.23 [1.02–1.48]) and marginally associated with stroke via pathways not mediated by adult SES. Conclusions: Our results suggest that early-life socioeconomic experiences directly influence adult chronic disease outcomes.