Previous studies have demonstrated an inverse association between chronic psychosocial stress and leukocyte telomere length (LTL), a potential marker of cellular aging. However, due to paucity of longitudinal data, responses of LTL and the LTL aging trajectory to changes in chronic stress exposure remain less well understood. Using data from the Stress I and II ancillary studies of the Multi-Ethnic Study of Atherosclerosis, we estimated the 10-year longitudinal (n = 1,158) associations of within-person changes in chronic stress with changes in LTL, as well as the pooled, cross-sectional associations of chronic stress and LTL (total n = 2,231). We measured chronic stress from both individual and neighborhood-environment sources. At the individual level, we calculated a summary score of each participant's rating of their ongoing (>6 months) material/social problems as moderately/very stressful on the Chronic Burden Scale. Neighborhood-level stress was measured using a summary score of reverse-coded MESA Neighborhood safety, aesthetic quality, and social cohesion scales. Quantiles of these scores were empirically categorized as high, moderate, or low stress. We then summed these individual- and neighborhood-level categorical variables for a total stress measure. Longitudinal within-person associations were estimated with fixed-effects models, which control for all time-invariant confounding, with additional control for time-varying demographics, lagged behaviors and chronic conditions, and specimen storage duration, as well as correction for regression to the mean. Change from low to high total chronic stress was associated with telomere shortening by 0.054 units [95% confidence interval: -0.095, -0.013] over 10 years. This was consistent with, though stronger in magnitude than, cross-sectional estimates. Change in individual-level stress was the primary driver of this effect. We also found suggestive evidence that 1) individuals with persistently high stress experienced the least shortening of telomeres, and 2) changes in individual-level stress were associated with stronger telomere shortening among women, whereas changes in neighborhood stress were associated with stronger shortening among men. Our findings provide longitudinal support to existing evidence, and point to interesting dynamics in telomere attrition across stress levels and genders.

Risk factors can drive socioeconomic inequalities in cardiovascular disease (CVD) through differential exposure and differential vulnerability. In this paper, we show how econometric decomposition directly enables simultaneous, policy-oriented assessment of these 2 mechanisms. We specifically estimate contributions of neighborhood environment and proximal risk factors to socioeconomic inequality in CVD incidence via these mechanisms. We followed 5,608 participants in the Multi-Ethnic Study of Atherosclerosis (2000-2012) to their first CVD event (median length of follow-up, 12.2 years). We used a summary measure of baseline socioeconomic position (SEP). Covariates included baseline demographics, neighborhood characteristics, and psychosocial, behavioral, and biomedical risk factors. Using Poisson models, we decomposed the difference (inequality) in incidence rates between low- and high-SEP groups into contributions of 1) differences in covariate means (differential exposure) and 2) differences in CVD risk associated with covariates (differential vulnerability). Notwithstanding large uncertainty in neighborhood estimates, our analysis suggested that differential exposure to poorer neighborhood socioeconomic conditions, adverse social environment, diabetes, and hypertension accounted for most of the inequality. Psychosocial and behavioral contributions were negligible. Further, neighborhood SEP, female sex, and white race were more strongly associated with CVD among low-SEP (vs. high-SEP) participants. These differentials in vulnerability also accounted for nontrivial portions of the inequality and could have important implications for intervention.

The Emotional Well-Being and Economic Burden (EMOT-ECON) Research Network is one of six research networks funded by the National Institutes of Health (NIH) to advance research about emotional well-being (EWB), and the only one that focuses on addressing how economic burden due to disease or illness affects EWB. The network convened researchers, patients, patient advocates, health care providers and other stakeholders from across the US to discuss the significance of addressing the impact of the economic burden of disease on EWB, the complexity of this prevalent problem for patients and families, and the research gaps that still need to be studied to ultimately develop strategies to reduce the impact of economic burden of disease on EWB and health. Participants identified some important future areas of research as those investigating: (i) prevalent and relevant emotions for patients experiencing economic burden of disease and financial hardship, and how their broader outlook on life is impacted; (ii) constructs and contexts that influence whether the economic burden is stressful; (iii) strategies to deal and cope and their positive or negative effects on EWB and health; and (iv) multi-level and multi-stakeholder interventions to address economic factors (e.g., costs, ability to pay), administrative burdens, education and training, and especially patients' emotional as well as financial status.

Background

Statins are a class of cholesterol-lowering drugs that affect many intracellular pathways that may have implications for chemoprevention against cancer. Epidemiologic data on statins and breast cancer are conflicting. We analyzed updated data from the Women's Health Initiative (WHI) to assess the relationship between statins and breast cancer risk.

Methods

The population included 154,587 postmenopausal women ages 50 to 79 years, with 7,430 pathologically confirmed cases of breast cancer identified over an average of 10.8 (SD, 3.3) years. Information on statins was collected at baseline and years one, three, six, and nine. Self- and interviewer-administered questionnaires were used to collect information on risk factors. Cox proportional hazards regression was used to calculate HRs with 95% confidence intervals (CI) to evaluate the relationship between statin use and cancer risk. Statistical tests were two-sided.

Results

Statins were used by 11,584 (7.5%) women at baseline. The annualized rate of breast cancer was 0.42% among statin users and 0.42% among nonusers. The multivariable adjusted HR of breast cancer for users versus nonusers was 0.94 (95% CI, 0.83-1.06). In the multivariable-adjusted, time-dependent model, the HR for simvastatin was 0.87 (95% CI, 0.71-1.07). There was no significant trend by overall duration of use (P value for trend 0.68). There was no effect of tumor stage, grade, or hormone receptor status.

Conclusion

Overall, statins were not associated with breast cancer risk.

Impact

Our study is one of the largest prospective observational studies on this topic, and substantially adds to the literature suggesting no relationship between statins and breast cancer risk.