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Recent attention to the interrelationship between racism, socioeconomic status (SES) and health has led to a small, but growing literature of empirical work on the role of structural racism in population health. Area-level racial inequities in SES are an indicator of structural racism, and the associations between structural racism indicators and self-rated health are unknown. Further, because urban-rural differences have been observed in population health and are associated with different manifestations of structural racism, explicating the role of urban-rural classification is warranted. This study examined the associations between racial inequities in SES and self-rated health by county urban-rural classification. Using data from County Health Rankings and American Communities Surveys, black-white ratios of SES were regressed on rates of fair/poor health in U.S. counties. Racial inequities in homeownership were negatively associated with fair/poor health ( β  = −0.87, s.e. = 0.18), but racial inequities in unemployment were positively associated with fair/poor health ( β  = 0.03, s.e. = 0.01). The associations between structural racism and fair/poor health varied by county urban-rural classification. Potential mechanisms include the concentration of resources in racially segregated counties with high racial inequities that lead to better health outcomes, but are associated with extreme black SES disadvantage. Racial inequities in SES are a social justice imperative with implications for population health that can be targeted by urban-rural classification and other social contextual characteristics.

This study examined the changes in sleep duration (total sleep time, night‐time sleep and daytime naps) after retirement transitions in China using a panel dataset of the China Health and Retirement Longitudinal Study in 2011, 2013 and 2015 with a total of 48,458 respondents. Linear regression analysis with generalized estimating equations was employed to examine the changes in sleep duration after transitions between different types of employment status. After controlling for the confounders, the results showed that the retired population and the population working in agricultural sectors slept 8.02 ( p  < .01) and 5.19 ( p  < .01) minutes longer than the population working in non‐agricultural sectors, respectively. Employment transition also had significant effects on sleep duration. Transition from non‐agricultural sectors to retirement increased total sleep time by 13.58 ( p  < .01) minutes and also raised the probability of daytime naps by 18% (OR = 1.18,  p  < .01). Transition from agricultural employment to retirement did not significantly affect the total sleep time, but significantly increased the probability of daytime naps (OR = 1.12,  p  = .02). Reentering the non‐agricultural sectors for the retirees did not significantly affect night‐time sleep, but decreased the probability of daytime naps (OR = 0.73,  p  < .01) and daytime nap duration (by 5.26 min,  p  = .01). In conclusion, people in China increased their sleep duration after transitions to retirement, but the magnitudes were much smaller than those in Western countries. Differences may be attributed to an abundant amount of Chinese people working in agricultural sectors, the high volume of retired people reentering the work force and the large proportion of people in China that had daytime naps at baseline.

Background Recent years have seen increased interest in the role of neighborhood factors in chronic diseases such as cancers. Less is known about the role of neighborhood factors beyond individual demographics such as age or education. It is particularly important to examine neighborhood effects on health among African American men and women, considering the disproportionate impact of cancer on this group. This study evaluated the unique contribution of neighborhood characteristics (e.g., racial/ethnic diversity, income) beyond individual demographics, to cancer control behaviors in African American men and women. Methods Individual-level data were drawn from a national survey (N = 2,222). Participants’ home addresses were geocoded and merged with neighborhood data from the American Community Survey. Multi-level regressions examined the unique contribution of neighborhood characteristics beyond individual demographics, to a variety of cancer risk, prevention, and screening behaviors. Results Neighborhood racial/ethnic diversity, median income, and percentage of home ownership made modest significant contributions beyond individual factors, in particular to smoking status where these factors were associated with lower likelihood of smoking (ps < .05). Men living in neighborhoods with older residents, and greater income and home ownership were significantly more likely to report prostate specific antigen testing (ps < .05). Regional analyses suggested different neighborhood factors were associated with smoking status depending on the region. Conclusion Findings provide a more nuanced understanding of the interplay of social determinants of health and neighborhood social environment among African American men and women, with implications for cancer control interventions to eliminate cancer disparities.

Rural coastal areas are highly vulnerable to climate change impacts. In the USA, much energy is devoted to conserving rural coastal ecosystems by promoting their adaptation to climate change. However, these areas are also home to vulnerable and underserved communities who can be challenging to engage in climate adaptation discussions. Churches—as trusted social institutions—may offer a structure through which government decision-makers and rural residents can engage to improve the resilience of these rural coastal regions. We employed collaborative learning to engage government decision-makers and rural church members on the topic of climate impacts on Maryland’s Eastern Shore of the Chesapeake Bay. We analyzed the collaborative learning process and its outcomes using ethnographic methods. In this paper, we present our approach and discuss the benefits and challenges of collaborative learning with rural churches. We found that this approach yielded major benefits including greater understanding of capacities and limitations in addressing environmental challenges, increased trust and social networks, expanded engagement with a greater diversity of stakeholders, increased opportunities for new conversations, new pathways toward interventions, and stakeholder empowerment. Collaborating with churches is not without challenges though; it requires considerable time and effort and presents difficulties in navigating social hierarchies and specialized language, identifying common goals, grappling with the newness of climate change, and overcoming institutional barriers. Despite these challenges, we conclude that collaborative learning with churches is a valuable approach for information exchange and network-building toward more resilient rural coasts.

Estimating Short- and Long-Term Effects on Population Change Resulting From Hurricane Exposure in U.S. Counties, 1970-2017

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

Segregation in Place: Estimating the Contribution of White Flight to Racial Segregation in the 21st Century

Objective: This study aimed to examine the explanatory role of health behaviors, socioeconomic position (SEP), and psychosocial stressors on racial/ethnic obesity disparities in a multiethnic and multiracial sample of adults. Methods: Using data from the Chicago Community Adult Health Study (2001-2003), Oaxaca-Blinder decomposition analysis was conducted to quantify the extent to which health behaviors (fruit and vegetable consumption and physical activity), SEP, and cumulative stressors (e.g., perceived discrimination, financial strain) each explained differences in obesity prevalence in Black, US-born Hispanic, and non-US-born Hispanic compared with non-Hispanic White participants. Results: SEP and health behaviors did not explain obesity differences between racial/ethnic minorities and White individuals. Having high levels of stress in four or more domains explained 4.46% of the differences between Black and White individuals, whereas having high levels of stress in three domains significantly explained 14.13% of differences between US-born Hispanic and White. Together, the predictors explained less than 20% of differences between any racial/ethnic minority group and White individuals. Conclusions: Exposure to stressors may play a role in obesity disparities, particularly among Black and US-born Hispanic individuals. Other obesity-related risk factors need to be examined to understand the underlying mechanisms explaining obesity disparities.

Although tobacco smoking, pan chewing and alcohol drinking are important risk factors for head and neck cancer (HNC), the HNC risks conferred by products available in Nepal for these habits are unknown. We assessed the associations of tobacco smoking, chewing habits, and alcohol drinking with HNC risk in Nepal. A case–control study was conducted in Nepal with 549 incident HNC cases and 601 controls. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using unconditional logistic regression adjusting for potential confounders. We observed increased HNC risk for tobacco smoking (OR: 1.54; 95% CI: 1.14, 2.06), chewing habits (OR: 2.39; 95% CI: 1.77, 3.23), and alcohol drinking (OR: 1.57; 95% CI: 1.14, 2.18). The population attributable fraction (PAF) was 24.3% for tobacco smoking, 39.9% for chewing habits and 23.0% for alcohol drinking. Tobacco smoking, chewing habits, and alcohol drinking might be responsible for 85.3% of HNC cases. Individuals who smoked tobacco, chewed products and drank alcohol had a 13‐fold increase in HNC risk (OR: 12.83; 95% CI: 6.91, 23.81) compared to individuals who did not have any of these habits. Both high frequency and long duration of these habits were strong risk factors for HNC among the Nepalese with clear dose–response trends. Preventive strategies against starting these habits and support for quitting these habits are necessary to decrease the incidence of HNC in Nepal.

Objective Exposure to early adversity carries long term harmful consequences for children's health and development. This study aims to 1) estimate the prevalence of childhood adversity for Australian children from infancy to 10-11 years, and 2) document inequalities in the distribution of adversity according to socioeconomic position (SEP), Indigenous status, and ethnicity. Methods Adversity was assessed every two years from 0-1 to 10-11 years in the nationally representative birth cohort of the Longitudinal Study of Australian Children (N=5,107). Adversity included legal problems; family violence; household mental illness; household substance abuse; harsh parenting; parental separation/divorce; unsafe neighborhood; family member death; and bullying (from 4-5 years). Adversities were examined individually and summed for a measure of multiple adversity (2+ adverse experiences). Results By 10-11 years, 52.8% (95% CI 51.0-54.7) of children had been exposed to two or more adversities. When combined with low SEP, children from ethnic minority and from Indigenous backgrounds had four to eight times the odds of exposure to two or more adversities than children from higher SEP Anglo-Euro backgrounds, respectively (OR 4.3, 95% CI 2.8-6.6 and OR 8.1, 95% CI 4.4-14.8). Ethnic minority and Indigenous children from higher SEP backgrounds had increased odds of exposure to multiple adversity than similarly advantaged Anglo-Euro children (OR 1.8, 95% CI 1.4-2.3 and OR 2.3, 95% CI 1.3-4.3, respectively). Conclusions Addressing early adversity is a significant opportunity to promote health over the life course, and reduce health inequalities experienced by marginalized groups of children.