Background Coronavirus disease 2019 (COVID-19) is a public health emergency of international concern and has caused traumatic experience for nurses worldwide. However, the prevalence of depression and anxiety symptoms in nurses, and how psychosocial factors influence nurses in this public crisis are unknown. Objectives To determine the effect of COVID-19 on the mental health of nurses and the prevalence of anxiety and depression symptoms among nurses in China during the outbreak. Design A cross-sectional study. Settings and participants A total of 3,228 nurses in Sichuan Province and Wuhan City were selected by convenience sampling. All participants were invited to complete the questionnaire through WeChat from January 27 to February 3, 2020. Methods A self-reported questionnaire combining depression and anxiety scale was used to collect data anonymously. Binary and multivariate logistic regression was applied to measure the odds of psychosocial factors of anxiety and depression and perceived health, respectively. Results The total incidence of depression (34.3%) and anxiety (18.1%) during the COVID-19 outbreak was lower than that during the SARS outbreak; however, the rate of depression in our study (47.1%) was high and similar in a recent study (50.4%) about the health care workers exposed to COVID-19 in China. The results indicated that COVID-19-related stress, relationship quality with family, and demographic characteristics were associated with depression, anxiety, and perceived health status. Furthermore, the prevalence of depression was similar between nurses working in low-risk COVID-19 wards was as high as working in high-risk COVID-19 wards (OR, 1.078; 95% CI, 0.784–1.481). Conclusions Our study revealed the high prevalence of depression and anxiety among nurses during the outbreak of COVID-19. COVID-19 factors and psychosocial factors were associated with mental health of nurses. The results suggest that hospitals should implement effective mental health promotion programs focused on occupational safety and family support to improve the well-being of nurses.

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Background: Structural inequities have important implications for the health of marginalized groups. Neighborhood-level redlining and lending bias represent state-sponsored systems of segregation, potential drivers of adverse health outcomes. We sought to estimate the effect of redlining and lending bias on breast cancer mortality and explore differences by race. Methods: Using Georgia Cancer Registry data, we included 4,943 non-Hispanic White (NHW) and 3,580 non-Hispanic Black (NHB) women with a first primary invasive breast cancer diagnosis in metro-Atlanta (2010–2014). Redlining and lending bias were derived for census tracts using the Home Mortgage Disclosure Act database. We calculated hazard ratios and 95% confidence intervals (CI) for the associations of redlining, lending bias on breast cancer mortality and estimated race-stratified associations. Results: Overall, 20% of NHW and 80% of NHB women lived in redlined census tracts, and 60% of NHW and 26% of NHB women lived in census tracts with pronounced lending bias. Living in redlined census tracts was associated with a nearly 1.60-fold increase in breast cancer mortality (hazard ratio = 1.58; 95% CI, 1.37–1.82) while residing in areas with substantial lending bias reduced the hazard of breast cancer mortality (hazard ratio = 0.86; 95% CI, 0.75–0.99). Among NHB women living in redlined census tracts, we observed a slight increase in breast cancer mortality (hazard ratio = 1.13; 95% CI, 0.90–1.42); among NHW women the association was more pronounced (hazard ratio = 1.39; 95% CI, 1.09–1.78). Conclusions: These findings underscore the role of ecologic measures of structural racism on cancer outcomes. Impact: Place-based measures are important contributors to health outcomes, an important unexplored area that offers potential interventions to address disparities.

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