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This article examines the role of Black American nurses during the 1918–1919 influenza pandemic and the aftermath of World War I. The pandemic caused at least 50 million deaths worldwide and 675 000 in the United States. It occurred during a period of pervasive segregation and racial violence, in which Black Americans were routinely denied access to health, educational, and political institutions. We discuss how an unsuccessful campaign by Black leaders for admission of Black nurses to the Red Cross, the Army Nurse Corps, and the Navy Nurse Corps during World War I eventually created opportunities for 18 Black nurses to serve in the army during the pandemic and the war’s aftermath. Analyzing archival sources, news reports, and published materials, we examine these events in the context of nursing and early civil rights history. This analysis demonstrates that the pandemic incrementally advanced civil rights in the Army Nurse Corps and Red Cross, while providing ephemeral opportunities for Black nurses overall. This case study reframes the response to epidemics and other public health emergencies as potential opportunities to advance health equity. In 1918, Aileen Cole and Clara Rollins ached to become Red Cross war nurses. 1  Cole, aged 24 years, had recently passed her registration exams, and Rollins, 34, had years of nursing experience. 2  The two boarded with other nurses in a Washington, DC, brick row house near Freedmen’s Hospital, where they had all graduated from the rigorous nurse training school. The Red Cross had enrolled Cole and Rollins on paper, but had done nothing else: the US Army and Navy, for which the Red Cross served as the official recruiter, did not accept Black nurses. 3 In October, the influenza pandemic brought change. The Red Cross called up Cole, Rollins, and several other Black nurses for civilian duty, and sent them to West Virginia to battle pandemic influenza. 4  This 1918–1919 pandemic was responsible for at least 50 million deaths worldwide and 675 000 in the United States. 5  It also created opportunities for previously excluded Black nurses, including the first 18 to serve in the Army Nurse Corps (ANC) between December 1918 and August 1919. 6 Although Black nurses’ roles in World War I and the pandemic have been noted by numerous historians, this article represents the first effort to move these nurses from periphery to center, and to critically analyze their struggle to serve as a seminal episode in the long and ongoing movement for civil rights and racial health equity. 7  Using archival materials, news reports, census records, and published literature, we highlight how Black nurses fulfilled a critical need for skilled care during the pandemic and the war’s aftermath, but received little recognition. We also show how nurses and Black community leaders viewed this service as a political act. We present this story as a historical case study of nursing and racism in a public health emergency, while raising transhistorical questions: Do public health emergencies spur advancements in health equity? Or do they merely allow exploitation of already-marginalized persons? Although a single case study cannot offer definitive answers, it can provide valuable insights.

OBJECTIVE: Children exposed to institutional rearing often exhibit problems across a broad array of developmental domains. We compared the consequences of long-term, high-quality foster care versus standard institution-based care, which began in early childhood on cardiometabolic and immune markers assessed at the time of adolescence. METHODS: The Bucharest Early Intervention Project is a longitudinal investigation of children institutionalized during early childhood (ages 6 to 30 months at baseline) who were subsequently randomized to either high-quality foster care or continued institutional care. At the age of 16 years, 127 respondents participated in a biomarker collection protocol, including 44 institutionalized children randomly assigned to receive care as usual, 41 institutionalized children randomized to be removed from institutional care and placed in high-quality foster care in infancy, and a control group of 42 demographically matched children raised in biological families. Outcomes included body mass index (BMI), systolic and diastolic blood pressure, C-reactive protein, interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor α, glycosylated hemoglobin A1c, and Epstein-Barr virus antibody titers. RESULTS: Early institutional rearing was not associated with differences in cardiometabolic or immune markers. Randomization to foster care and age of placement into foster care were also unrelated to these markers, with the exception of BMI z-score, where children assigned to care as usual had lower BMI z-scores relative to children assigned to foster care (-0.23 versus 0.08, p = .06), and older age at placement was associated with lower BMI (β = -0.07, p = .03). CONCLUSIONS: The impact of institutional rearing on measures of cardiometabolic health and immune system functioning is either absent or not evident until later in development. These findings provide new insights into the biological embedding of adversity and how it varies developmentally and across regulatory systems and adversity type.

India’s cities face key challenges to improving public health outcomes. First, unequally distributed public resources create insanitary conditions, especially in slums – threatening everyone’s health, as suggested by poor child growth even amongst the wealthiest. Second, devolving services to elected bodies works poorly for highly technical services like public health. Third, services are highly fragmented. This paper examines the differences in the organisation and management of municipal services in Chennai and Delhi, two cities with sharply contrasting health indicators. Chennai mitigates these challenges by retaining professional management of service delivery and actively serving vulnerable populations − while services in Delhi are quite constrained. Management and institutional issues have received inadequate attention in the public health literature on developing countries, and the policy lessons from Chennai have wide relevance.

Neighborhood attributes have been shown to influence health, but advances in neighborhood research has been constrained by the lack of neighborhood data for many geographical areas and few neighborhood studies examine features of nonmetropolitan locations. We leveraged a massive source of Google Street View (GSV) images and computer vision to automatically characterize national neighborhood built environments. Using road network data and Google Street View API, from December 15, 2017-May 14, 2018 we retrieved over 16 million GSV images of street intersections across the United States. Computer vision was applied to label each image. We implemented regression models to estimate associations between built environments and county  health outcomes , controlling for county-level demographics, economics, and  population density . At the county level, greater presence of highways was related to lower chronic diseases and  premature mortality . Areas characterized by street view images as ‘rural’ (having limited infrastructure) had higher obesity,  diabetes , fair/poor self-rated health, premature mortality, physical distress, physical inactivity and teen birth rates but lower rates of excessive drinking. Analyses at the  census  tract level for 500 cities revealed similar adverse associations as was seen at the county level for neighborhood indicators of less urban development. Possible mechanisms include the greater abundance of services and facilities found in more developed areas with roads, enabling access to places and resources for promoting health. GSV images represents an underutilized resource for building national data on neighborhoods and examining the influence of built environments on community health outcomes across the United States.

Plant phenology (e.g. timing of spring green-up, flowering) is among the most sensitive indicator of ecological response to ongoing climate variability and change. While previous studies have documented changes in the timing of spring green-up and flowering across different parts of the world, empirical evidence regarding how such ongoing ecological changes impact allergic disease burden at population level is lacking. Because earlier spring green-up may increase season length for tree pollen, we hypothesized that early onset of spring (negative anomaly in start of season (SOS)) will be associated with increased hay fever burden. To test this, we first calculated a median cardinal date for SOS for each county within the contiguous US for the years 2001-2013 using phenology data from the National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer (MODIS). We categorized yearly deviations in SOS for each county from their respective long-term averages as: very early (>3 wks early), early (1-3 wks early), average (within 1 wk), late (1-3 wks late) and very late (> 3 wks late). We linked these data to 2002-2013 National Health Interview Survey data, and investigated the association between changes in SOS and hay fever prevalence using logistic regression. We observed that adults living in counties with a very early onset of SOS had a 14% higher odds of hay fever compared to the reference group, i.e. those living in counties where onset of spring was within the normal range (Odds Ratios (OR): 1.14. 95% Confidence Interval (CI): 1.03-1.27). Likewise, adults living in counties with very late onset of SOS had a 18% higher odds hay fever compared to the reference group (OR: 1.18, CI: 1.05-1.32). Our data provides the first-ever national scale assessment of the impact of changing plant phenology-linked to ongoing climate variability and change-on hay fever prevalence. Our findings are likely tied to changes in pollen dynamics, i.e early onset of spring increases the duration of exposure to tree pollen, while very late onset of spring increases the propensity of exposure because of simultaneous blooming.

  Background Psychosocial stress has been implicated as a risk factor for overweight and obesity. However, research on psychosocial stressors and overweight and obesity has typically focused on single stressors in isolation, which may overestimate the impact of a specific stressor and fail to describe the role of cumulative stress on overweight and obesity risk. Purpose This study explores the association between overweight/obesity and cumulative exposure to a wide range of psychosocial stressors, among a multiracial/ethnic sample of adults. Methods Using secondary data from the Chicago Community Adult Health Study (n = 2,983), we conducted multinomial logistic regression analyses to quantify associations between eight psychosocial stressors, individually and in combination, and measured overweight and obesity, adjusted for sociodemographic factors, alcohol use and smoking. Results In separated covariate-adjusted models, childhood adversities (odds ratio [OR] = 1.16; confidence interval [CI] = [1.03, 1.30]), acute life events (OR = 1.18; CI = [1.04, 1.34]), financial strain (OR = 1.30; CI = [1.15, 1.47]), and relationship stressors (OR = 1.18; CI = [1.04, 1.35]) were associated with increased odds of obesity. In a model adjusted for all stressors simultaneously, financial strain was the only stressor independently associated with overweight (OR = 1.17; CI = [1.00, 1.36]) and obesity (OR = 1.21; CI = [1.05, 1.39]). Participants with stress exposure in the highest quintile across 2, 3, or ≥4 (compared to no) types of stressors had significantly higher odds of obesity. Conclusions Multiple types of stressors may be risk factors for obesity, and cumulative exposure to these stressors may increase the odds of obesity. Reducing exposure to stressors at the population level may have the potential to contribute to reducing the burden of obesity.  

Purpose Limited research has examined maternal experiences of racial/ethnic discrimination in relation to child cardiometabolic health. In this study, we investigated whether maternal experiences of ethnic discrimination were associated with cardiometabolic risk in Hispanic/Latino youth several years later. Methods Our sample included 1146 youth (8–16 years) from the Study of Latino Youth (2012–2014), who were children of the Hispanic Community Health Study/Study of Latinos participants (2008–2011). We used regression models to examine the prospective associations between maternal report of ethnic discrimination in relation to her child's  body mass index  (BMI) z-score,  metabolic syndrome  score (MetS), and high sensitivity  C-reactive protein  (hsCRP) levels 2 years later. Results Maternal ethnic discrimination was associated with youth hsCRP, but not BMI or MetS (P -values >.05). Adjusting for age, nativity, and national background, maternal ethnic discrimination was associated with higher (log) hsCRP levels (β = 0.18, 95% CI = 0.04 to 0.32) in children. This association was robust to adjustment for maternal and household characteristics (β = 0.17, 95% CI = 0.04 to 0.31), as well as  maternal depression  and maternal BMI. Conclusions Maternal ethnic discrimination is associated with inflammation among Hispanic/Latino youth, and not BMI z-score or MetS. Studies are needed to address temporality and pathways.

There is a growing recognition of social media data as being useful for understanding local area patterns. In this study, we sought to utilize geotagged tweets—specifically, the frequency and type of food mentions—to understand the neighborhood food environment and the social modeling of food behavior. Additionally, we examined associations between aggregated food-related tweet characteristics and prevalent chronic health outcomes at the census tract level. We used a Twitter streaming application programming interface (API) to continuously collect ~1% random sample of public tweets in the United States. A total of 4,785,104 geotagged food tweets from 71,844 census tracts were collected from April 2015 to May 2018. We obtained census tract chronic disease outcomes from the CDC 500 Cities Project. We investigated associations between Twitter-derived food variables and chronic outcomes (obesity, diabetes and high blood pressure) using the median regression. Census tracts with higher average calories per tweet, less frequent healthy food mentions, and a higher percentage of food tweets about fast food had higher obesity and hypertension prevalence. Twitter-derived food variables were not predictive of diabetes prevalence. Food-related tweets can be leveraged to help characterize the neighborhood social and food environment, which in turn are linked with community levels of obesity and hypertension.

O besity rates in the U.S. are associated with area-level, food-related characteristics. Studies have previously examined the role of structural racism (policies/practices that advantaged White Americans and deprived other racial/ethnic minority groups), but racial inequalities in socioeconomic status (SES) is a novel indicator. The aim of this study is to determine the associations between racial inequalities in SES with obesity and obesogenic environments. Data from 2007⁻2014 County Health Rankings and 2012⁻2016 County Business Patterns were combined to assess the associations between relative SES comparing Blacks to Whites with obesity, and number of grocery stores and fast food restaurants in U.S. counties. Random effects linear and Poisson regressions were used and stratified by county racial composition. Racial inequality in poverty, unemployment, and homeownership were associated with higher obesity rates. Racial inequality in median income, college graduates, and unemployment were associated with fewer grocery stores and more fast food restaurants. Associations varied by county racial composition. The results demonstrate that a novel indicator of structural racism on the county-level is associated with obesity and obesogenic environments. Associations vary by SES measure and county racial composition, suggesting the ability for targeted interventions to improve obesogenic environments and policies to eliminate racial inequalities in SES.

Air pollution is a persistent and well-established public health problem in India: emissions from coal-fired power plants have been associated with over 80,000 premature deaths in 2015. Premature deaths could rise by four to five times this number by 2050 without additional pollution controls. We site a model 500 MW coal-fired electricity generating unit at eight locations in India and examine the benefits and costs of retrofitting the plant with a flue-gas desulfurization unit to reduce sulfur dioxide emissions. We quantify the mortality benefits associated with the reduction in sulfates (fine particles) and value these benefits using estimates of the value per statistical life transferred to India from high income countries. The net benefits of scrubbing vary widely by location, reflecting differences in the size of the exposed population. They are highest at locations in the densely populated north of India, which are also among the poorest states in the country.