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Climate Change and Impaired Population Health – Perspectives From Countries on Opposite Ends of the Economic Spectrum

Mortality Risk Information, Survival Expectations, Sexual Behaviors and Covid-19

Bootstraps of Oppression: A Theoretical Framework of Structural Inequality in Policy Decision Making

Alternative Trajectories in Body Weight, Mental and Cognitive Health among Older Americans: Roles of Genetics and Earlier SES

Deep learning and, specifically, convoltional neural networks (CNN) represent a class of powerful models that facilitate the understanding of many problems in computer vision. When combined with a reasonable amount of data, CNNs can outperform traditional models for many tasks, including image classification. In this work, we utilize these powerful tools with imagery data collected through Google Street View images to perform virtual audits of neighborhood characteristics. We further investigate different architectures for chronic disease prevalence regression through networks that are applied to sets of images rather than single images. We show quantitative results and demonstrate that our proposed architectures outperform the traditional regression approaches.

This study investigated whether changes in neighborhood context induced by neighborhood relocation mediated the impact of the Moving to Opportunity (MTO) housing voucher experiment on adolescent mental health. Mediators included participant-reported neighborhood safety, social control, disorder, and externally-collected neighborhood collective efficacy. For treatment group members, improvement in neighborhood disorder and drug activity partially explained MTO's beneficial effects on girls' distress. Improvement in neighborhood disorder, violent victimization, and informal social control helped counteract MTO's adverse effects on boys' behavioral problems, but not distress. Housing mobility policy targeting neighborhood improvements may improve mental health for adolescent girls, and mitigate harmful effects for boys.

Black sexual and gender minorities (SGM) are at greater risk for HIV compared to their White, cisgender, heterosexual counterparts. Linkage to culturally sensitive health care is, therefore, pivotal for HIV prevention and treatment of Black SGM. Unfortunately, social and structural challenges undermine Black SGM individuals' abilities to obtain adequate health care services, indicating a need to understand Black SGM perceptions of health care. To address this gap, we interviewed Black men who have sex with men and transwomen about their experiences with health care providers. Participants discussed needs and concerns, including provider SGM identity diversity and education; assumptions, judgment, stigma, and discrimination; and ability to establish a personal bond, trust, and familiarity. Black SGM indicated that providers often did not meet their needs in different ways regarding their SGM identities. Findings suggest a need for provider cultural sensitivity education programs that address the needs of Black SGM in health care.

  BACKGROUND: Stroke is a leading cause of morbidity and mortality in the United States. Associations between short-term exposures to particulate matter (PM) air pollution and stroke are inconsistent. Many prior studies have used administrative and hospitalization databases where misclassification of the type and timing of the stroke event may be problematic. METHODS: In this case-crossover study, we used a nationwide kriging model to examine short-term ambient exposure to PM10 and PM2.5 and risk of ischemic and hemorrhagic stroke among men enrolled in the Health Professionals Follow-up Study. Conditional logistic regression models were used to obtain estimates of odds ratios (OR) and 95% confidence intervals (CI) associated with an interquartile range (IQR) increase in PM2.5 or PM10. Lag periods up to 3 days prior to the stroke event were considered in addition to a 4-day average. Stratified models were used to examine effect modification by patient characteristics. RESULTS: Of the 727 strokes that occurred between 1999 and 2010, 539 were ischemic and 122 were hemorrhagic. We observed positive statistically significant associations between PM10 and ischemic stroke (ORlag0-3 = 1.26; 95% CI: 1.03-1.55 per IQR increase [14.46 μg/m3]), and associations were elevated for nonsmokers, aspirin nonusers, and those without a history of high cholesterol. However, we observed no evidence of a positive association between short-term exposure to PM and hemorrhagic stroke or between PM2.5 and ischemic stroke in this cohort. CONCLUSIONS: Our study provides evidence that ambient PM10 may be associated with higher risk of ischemic stroke and highlights that ischemic and hemorrhagic strokes are heterogeneous outcomes that should be treated as such in analyses related to air pollution.

Faculty associate Rashawn Ray investigates the social and environmental changes needed in order to remove neighborhood barriers to regular physical exercise

Faculty associate Jerome Dugan investigates the relationship between socioeconomic status, health insurance coverage, and affordable quality care