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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.

BACKGROUND: Using a population-based sample of youth, we examined rates of cigarette use and trends in cigarette use disparities between heterosexual youth and 3 subgroups of sexual minority youth (SMY) (ie, lesbian or gay, bisexual, and unsure) from 2005 to 2015. METHODS: Data are from 6 cohorts of the Youth Risk Behavior Survey, a national, biennial, school-based survey of ninth- to 12th-grade students in the United States (n = 404 583). Sex-stratified analyses conducted in 2017 examined trends in 2 cigarette-related behaviors: lifetime cigarette use and heavy cigarette use (20+ days in the past 30). RESULTS: Disparities in lifetime cigarette use between lesbian and heterosexual girls were statistically smaller in 2015 relative to 2005 (adjusted odds ratio [aOR] 0.29; 95% confidence interval [CI] 0.12–0.75; P = .011). Sexual orientation disparities in heavy use were narrower for bisexual boys in 2015 compared with 2005 (aOR 0.39; 95% CI 0.17–0.90; P = .028). Girls and boys unsure of their sexual identity had wider disparities in heavy use in 2015 (aOR 3.85; 95% CI 1.39–11.10; P = .009) relative to 2005 (aOR 2.44; 95% CI 1.22–5.00; P = .012). CONCLUSIONS: SMY remain at greater risk for cigarette-related behaviors despite greater acceptance of lesbian, gay, and bisexual people in the United States. Focused policies and programs aimed at reducing rates of SMY cigarette use are warranted, particularly for youth questioning their sexual identity.

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.

Qualitative research helps to document stories of "stigma and survival"

  BACKGROUND: Research implicates acute and chronic stressors in racial/ethnic health disparities, but the joint impact of multiple stressors on racial/ethnic disparities in cardiovascular health is unknown. METHODS: In 25 062 women (24 053 white; 256 Hispanic; 440 black; 313 Asian) articipating in the Women's Health Study follow-up cohort, we examined the relationship between cumulative psychosocial stress (CPS) and ideal cardiovascular health (ICH), as defined by the American Heart Association's 2020 strategic Impact Goals. This health metric includes smoking, body mass index, physical activity, diet, blood pressure, total cholesterol, and glucose, with higher levels indicating more ICH and less cardiovascular risk (score range, 0-7). We created a CPS score that summarized acute stressors (eg, negative life events) and chronic stressors (eg, work, work-family spillover, financial, discrimination, relationship, and neighborhood) and traumatic life event stress reported on a stress questionnaire administered in 2012 to 2013 (score range, 16-385, with higher scores indicating higher levels of stress). RESULTS: White women had the lowest mean CPS scores (white: 161.7±50.4; Hispanic: 171.2±51.7; black: 172.5±54.9; Asian: 170.8±50.6; P overall <0.01). Mean CPS scores remained higher in Hispanic, black, and Asian women than in white women after adjustment for age, socioeconomic status (income and education), and psychological status (depression and anxiety) ( P<0.01 for each). Mean ICH scores varied by race/ethnicity ( P<0.01) and were significantly lower in black women and higher in Asian women compared with white women (β-coefficient [95% CI]: Hispanics, -0.02 [-0.13 to -0.09]; blacks, -0.34 [-0.43 to -0.25]; Asians, 0.34 [0.24 to 0.45]); control for socioeconomic status and CPS did not change these results. Interactions between CPS and race/ethnicity in ICH models were not significant. CONCLUSIONS: Both CPS and ICH varied by race/ethnicity. ICH remained worse in blacks and better in Asians compared with whites, despite taking into account socioeconomic factors and CPS.

Racial disparities in obesity among men are accompanied by positive associations between income and obesity among Black men only. Race also moderates the positive association between marital status and obesity. This study sought to determine how race, income, and marital status interact on obesity among men. Using data from the 2007 to 2014 National Health and Nutrition Examination Survey, obesity was measured as body mass index ≥30 kg/m 2  among 6,145 Black and White men. Income was measured by percentage of the federal poverty line and marital status was categorized as currently, formerly, or never married. Using logistic regression and interaction terms, the associations between income and obesity were assessed by race and marital status categories adjusted for covariates. Black compared to White (OR = 1.19, 95% CI [1.03, 1.38]), currently married compared to never married (OR = 1.45, 95% CI [1.24, 1.69]), and high-income men compared to low income men (OR = 1.26, 95% CI [1.06, 1.50]) had higher odds of obesity. A three-way interaction was significant and analyses identified that income was positively associated with obesity among currently married Black men and never married White men with the highest and lowest probabilities of obesity, respectively. High-income, currently married Black men had higher obesity rates and may be at increased risk for obesity-related morbidities.

Public expenditures on non-contributory pensions are equivalent to at least 1 percent of GDP in several countries in Latin America and is expected to increase. We explore the effect of noncontributory pensions on the well-being of the beneficiary population by studying the Pension 65 program in Peru, which uses a poverty eligibility threshold. We find that the program reduced the average score of beneficiaries on the Geriatric Depression Scale by nine percent and reduced the proportion of older adults doing paid work by four percentage points. Moreover, households with a beneficiary increased their level of consumption by 40 percent. All these effects are consistent with the findings of Galiani, Gertler and Bando (2016) in their study on a non-contributory pension scheme in Mexico. Thus, we conclude that the effects of non-contributory pensions on well-being in rural Mexico can be largely generalized to Peru