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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.

Maryland Health Care Commission project includes Marian Moser-Jones, Edmond Shenassa and Marie Thoma

Hazards of childbirth persist in rich and poor nations

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.

  BACKGROUND: The significance of the timing and chronicity of childhood adversity for depression outcomes later in life is unclear. Identifying trajectories of adversity throughout childhood would allow classification of children according to the accumulation, timing, and persistence of adversity, and may provide unique insights into the risk of subsequent depression. METHODS: Using data from the Avon Longitudinal Study of Parents and Children, we created a composite adversity score comprised of 10 prospectively assessed domains (e.g., violent victimization, inter-parental conflict, and financial hardship) for each of eight time points from birth through age 11.5 years. We used semiparametric group-based trajectory modeling to derive childhood adversity trajectories and examined the association between childhood adversity and depression outcomes at the age of 18 years. RESULTS: Among 9,665 participants, five adversity trajectories were identified, representing stable-low levels (46.3%), stable-mild levels (37.1%), decreasing levels (8.9%), increasing levels (5.3%), and stable-high levels of adversity (2.5%) from birth through late childhood. Approximately 8% of the sample met criteria for probable depression at 18 years and the mean depression severity score was 3.20 (standard deviation = 3.95, range 0-21). The risk of depression in young adulthood was elevated in the decreasing (odds ratio [OR] = 1.72, 95% confidence interval [CI] = 1.19-2.48), increasing (OR = 1.81, 95% CI = 1.15-2.86), and stable-high (OR = 1.80, 95% CI = 1.00-3.23) adversity groups, compared to those with stable-low adversity, when adjusting for potential confounders. CONCLUSIONS: Children in trajectory groups characterized by moderate or high levels of adversity at some point in childhood exhibited consistently greater depression risk and depression severity, regardless of the timing of adversity.

PURPOSE: We aimed to estimate latent classes of concurrent polysubstance use and test for sexual orientation differences in latent class memberships with representative data from adolescents living in 19 U.S. states. We also tested whether sex, race/ethnicity, and age moderated the sexual identity differences in polysubstance use class memberships. METHODS: We analyzed data from 119,437 adolescents from 19 states who participated in the 2015 Youth Risk Behavior Survey. Latent class analysis characterized polysubstance use patterns based on self-reported frequency of lifetime and past-month use of alcohol (including heavy episodic drinking), tobacco (cigarettes, cigars, and smokeless tobacco), and marijuana. Multinomial logistic regression models tested differences in latent class memberships by sexual identity. Interaction terms tested whether sex, race/ethnicity, and age moderated the sexual identity differences in polysubstance use class memberships. RESULTS: A six-class model of polysubstance use fit the data best and included nonusers (61.5%), experimental users (12.2%), marijuana-alcohol users (14.8%), tobacco-alcohol users (3.8%), medium-frequency three-substance users (3.6%), and high-frequency three-substance users (4.1%). Gay/lesbian- and bisexual-identified adolescents had significantly higher odds than heterosexual-identified adolescents of being in all of the user classes compared with the nonuser class. These sexual identity differences in latent polysubstance use class memberships were generally larger for females than for males, varied occasionally by race/ethnicity, and were sometimes larger for younger ages. CONCLUSION: Compared with their heterosexual peers, gay/lesbian and bisexual adolescents-especially females-are at heightened risk of engaging in multiple types of polysubstance use. Designing, implementing, and evaluating interventions will likely reduce these sexual orientation disparities.