Unpacking Neighborhood Socioeconomic Status in Children's Health Research from an Environmental Justice Perspective: A Scoping Review.

PURPOSE OF REVIEW: Clearly defining and measuring neighborhood socioeconomic status (nSES) is a key first step in achieving environmental justice, as the disproportionate distribution of environmental hazards and access to resources is heavily influenced by socioeconomic factors. This scoping review explores the definition of neighborhoods, measurement of neighborhood socioeconomic status (nSES), and studies that evaluated the association between nSES and child health in accordance with PRISMA guidelines. RECENT FINDINGS: We identified 4112 articles published on US pediatric populations between 2013 and 2022. We identified 170 distinct indicators across seven broad domains of nSES used to create 121 different measures of nSES across the 206 publications included in this review. While there is considerable interest in nSES and children's health, there is also substantial variation in the measurement of neighborhood as a geographic unit and nSES as a construct. We observed methodological challenges related to the identification of neighborhood boundaries, indicator selection, and nSES measure definition(s). We discuss common pitfalls in neighborhood research that can complicate identifying, targeting, and resolving environmental injustices. Lastly, we put forward a series of recommendations to reduce measurement error and improve inference, in addition to reporting recommendations for neighborhoods and health research that can aid in improving our understanding of pathways between neighborhood context and child health, inform policy development, and allocate resources to achieve environmental justice.

Maternal Pre-Pregnancy BMI, Breastfeeding, and Child BMI.

OBJECTIVES: Breastfeeding practices may protect against offspring obesity, but this relationship is understudied among women with obesity. We describe the associations between breastfeeding practices and child BMI for age z-score (BMIz), stratified by maternal BMI. METHODS: We analyzed 8134 dyads from 21 cohorts in the Environmental Influences on Child Health Outcomes Program. Dyads with data for maternal pre-pregnancy BMI, infant feeding practices, and ≥1 child BMI assessment between the ages of 2 and 6 years were included. The associations between breastfeeding practices and continuous child BMIz were assessed by using multivariable linear mixed models. RESULTS: Maternal pre-pregnancy BMI category prevalence was underweight: 2.5%, healthy weight: 45.8%, overweight: 26.0%, and obese: 25.6%. Median child ages at the cessation of any breastfeeding and exclusive breastfeeding across the 4 BMI categories were 19, 26, 24, and 17 weeks and 12, 20, 17, and 12 weeks, respectively. Results were in the hypothesized directions for BMI categories. Three months of any breastfeeding was associated with a lower BMIz among children whose mothers were a healthy weight (-0.02 [-0.04 to 0.001], P = .06), overweight (-0.04 [-0.07 to -0.004], P = .03), or obese (-0.04 [-0.07 to -0.006], P = .02). Three months of exclusive breastfeeding was associated with a lower BMIz among children whose mothers were a healthy weight (-0.06 [-0.10 to -0.02], P = .002), overweight (-0.05 [-0.10 to 0.005], P = .07), or obese (-0.08 [-0.12 to -0.03], P = .001). CONCLUSIONS: Human milk exposure, regardless of maternal BMI category, was associated with a lower child BMIz in the Environmental Influences on Child Health Outcomes cohorts, supporting breastfeeding recommendations as a potential strategy for decreasing the risk of offspring obesity.

Associations between area-level arsenic exposure and adverse birth outcomes: An Echo-wide cohort analysis.

BACKGROUND: Drinking water is a common source of exposure to inorganic arsenic. In the US, the Safe Drinking Water Act (SDWA) was enacted to protect consumers from exposure to contaminants, including arsenic, in public water systems (PWS). The reproductive effects of preconception and prenatal arsenic exposure in regions with low to moderate arsenic concentrations are not well understood. OBJECTIVES: This study examined associations between preconception and prenatal exposure to arsenic violations in water, measured via residence in a county with an arsenic violation in a regulated PWS during pregnancy, and five birth outcomes: birth weight, gestational age at birth, preterm birth, small for gestational age (SGA), and large for gestational age (LGA). METHODS: Data for arsenic violations in PWS, defined as concentrations exceeding 10 parts per billion, were obtained from the Safe Drinking Water Information System. Participants of the Environmental influences on Child Health Outcomes Cohort Study were matched to arsenic violations by time and location based on residential history data. Multivariable, mixed effects regression models were used to assess the relationship between preconception and prenatal exposure to arsenic violations in drinking water and birth outcomes. RESULTS: Compared to unexposed infants, continuous exposure to arsenic from three months prior to conception through birth was associated with 88.8 g higher mean birth weight (95% CI: 8.2, 169.5), after adjusting for individual-level confounders. No statistically significant associations were observed between any preconception or prenatal violations exposure and gestational age at birth, preterm birth, SGA, or LGA. CONCLUSIONS: Our study did not identify associations between preconception and prenatal arsenic exposure, defined by drinking water exceedances, and adverse birth outcomes. Exposure to arsenic violations in drinking water was associated with higher birth weight. Future studies would benefit from more precise geodata of water system service areas, direct household drinking water measurements, and exposure biomarkers.

Latent Class Analysis of Prenatal Substance Exposure and Child Behavioral Outcomes.

OBJECTIVES: To predict behavioral disruptions in middle childhood, we identified latent classes of prenatal substance use. STUDY DESIGN: As part of the Environmental influences on Child Health Outcomes Program, we harmonized prenatal substance use data and child behavior outcomes from 2195 women and their 6- to 11-year-old children across 10 cohorts in the US and used latent class-adjusted regression models to predict parent-rated child behavior. RESULTS: Three latent classes fit the data: low use (90.5%; n = 1986), primarily using no substances; licit use (6.6%; n = 145), mainly using nicotine with a moderate likelihood of using alcohol and marijuana; and illicit use (2.9%; n = 64), predominantly using illicit substances along with a moderate likelihood of using licit substances. Children exposed to primarily licit substances in utero had greater levels of externalizing behavior than children exposed to low or no substances (P = .001, d = .64). Children exposed to illicit substances in utero showed small but significant elevations in internalizing behavior than children exposed to low or no substances (P < .001, d = .16). CONCLUSIONS: The differences in prenatal polysubstance use may increase risk for specific childhood problem behaviors; however, child outcomes appeared comparably adverse for both licit and illicit polysubstance exposure. We highlight the need for similar multicohort, large-scale studies to examine childhood outcomes based on prenatal substance use profiles.

The Environmental Influences on Child Health Outcomes (ECHO)-Wide Cohort.

The Environmental Influences on Child Health Outcomes (ECHO)-Wide Cohort Study (EWC), a collaborative research design comprising 69 cohorts in 31 consortia, was funded by the National Institutes of Health (NIH) in 2016 to improve children's health in the United States. The EWC harmonizes extant data and collects new data using a standardized protocol, the ECHO-Wide Cohort Data Collection Protocol (EWCP). EWCP visits occur at least once per life stage, but the frequency and timing of the visits vary across cohorts. As of March 4, 2022, the EWC cohorts contributed data from 60,553 children and consented 29,622 children for new EWCP data and biospecimen collection. The median (interquartile range) age of EWCP-enrolled children was 7.5 years (3.7-11.1). Surveys, interviews, standardized examinations, laboratory analyses, and medical record abstraction are used to obtain information in 5 main outcome areas: pre-, peri-, and postnatal outcomes; neurodevelopment; obesity; airways; and positive health. Exposures include factors at the level of place (e.g., air pollution, neighborhood socioeconomic status), family (e.g., parental mental health), and individuals (e.g., diet, genomics).

Trends in Screen Time Use Among Children During the COVID-19 Pandemic, July 2019 Through August 2021.

Importance: The COVID-19 pandemic led to widespread lockdowns and school closures that may have affected screen time among children. Although restrictions were strongest early in the pandemic, it is unclear how screen time changed as the pandemic progressed. Objective: To evaluate change in children's screen time from before the pandemic to during the pandemic, from July 2019 through August 2021. Design, Setting, and Participants: This is a longitudinal cohort study with repeated measures of screen time collected before the pandemic and during 2 pandemic periods. Children aged 4 to 12 years and their parent were enrolled in 3 pediatric cohorts across 3 states in the US participating in the Environmental Influences of Child Health Outcomes (ECHO) Program. Data analysis was performed from November 2021 to July 2022. Exposures: COVID-19 pandemic period: prepandemic (July 2019 to March 2020), pandemic period 1 (December 2020 to April 2021), and pandemic period 2 (May 2021 to August 2021). Main Outcomes and Measures: The primary outcomes were total, educational (not including remote school), and recreational screen time assessed via the ECHO Child Media Use questionnaire. Linear mixed-effects models were used for screen time adjusted for child's age, number of siblings, sex, race, ethnicity, and maternal education. Results: The cohort included 228 children (prepandemic mean [SD] age, 7.0 [2.7] years; 100 female [43.9%]) with screen time measured during the prepandemic period and at least once during the pandemic period. Prepandemic mean (SD) total screen time was 4.4 (3.9) hours per day and increased 1.75 hours per day (95% CI, 1.18-2.31 hours per day) in the first pandemic period and 1.11 hours per day (95% CI, 0.49-1.72 hours per day) in the second pandemic period, in adjusted models. Prepandemic mean (SD) recreational screen time was 4.0 (3.5) hours per day and increased 0.89 hours per day (95% CI, 0.39-1.39 hours per day) in the first pandemic period and 0.70 hours per day (95% CI, 0.16-1.25 hours per day) in the second pandemic period. Prepandemic mean (SD) educational screen time was 0.5 (1.2) hours per day (median [IQR], 0.0 [0.0-0.4] hours per day) and increased 0.93 hours per day (95% CI, 0.67-1.19 hours per day) in the first pandemic period and 0.46 hours per day (95% CI, 0.18-0.74 hours per day) in the second pandemic period. Conclusions and Relevance: These findings suggest that screen time among children increased during the COVID-19 pandemic and remained elevated even after many public health precautions were lifted. The long-term association of increased screen time during the COVID-19 pandemic with children's health needs to be determined.

Sociodemographic Variation in Children's Health Behaviors During the COVID-19 Pandemic.

Background: Societal changes during the COVID-19 pandemic may affect children's health behaviors and exacerbate disparities. This study aimed to describe children's health behaviors during the COVID-19 pandemic, how they vary by sociodemographic characteristics, and the extent to which parent coping strategies mitigate the impact of pandemic-related financial strain on these behaviors. Methods: This study used pooled data from 50 cohorts in the Environmental influences on Child Health Outcomes Program. Children or parent proxies reported sociodemographic characteristics, health behaviors, and parent coping strategies. Results: Of 3315 children aged 3-17 years, 49% were female and 57% were non-Hispanic white. Children of parents who reported food access as a source of stress were 35% less likely to engage in a higher level of physical activity. Children of parents who changed their work schedule to care for their children had 82 fewer min/day of screen time and 13 more min/day of sleep compared with children of parents who maintained their schedule. Parents changing their work schedule were also associated with a 31% lower odds of the child consuming sugar-sweetened beverages. Conclusions: Parents experiencing pandemic-related financial strain may need additional support to promote healthy behaviors. Understanding how changes in parent work schedules support shorter screen time and longer sleep duration can inform future interventions.

Characteristics of Individuals in the United States Who Used Opioids During Pregnancy.

Background: Opioid use has disproportionally impacted pregnant people and their fetuses. Previous studies describing opioid use among pregnant people are limited by geographic location, type of medical coverage, and small sample size. We described characteristics of a large, diverse group of pregnant people who were enrolled in the Environmental Influences on Child Health Outcomes (ECHO) Program, and determined which characteristics were associated with opioid use during pregnancy. Materials and Methods: Cross-sectional data obtained from 21,905 pregnancies of individuals across the United States enrolled in the ECHO between 1990 and 2021 were analyzed. Medical records, laboratory testing, and self-report were used to determine opioid-exposed pregnancies. Multiple imputation methods using fully conditional specification with a discriminant function accounted for missing characteristics data. Results: Opioid use was present in 2.8% (n = 591) of pregnancies. The majority of people who used opioids in pregnancy were non-Hispanic White (67%) and had at least some college education (69%). Those who used opioids reported high rates of alcohol use (32%) and tobacco use (39%) during the pregnancy; although data were incomplete, only 5% reported heroin use and 86% of opioid use originated from a prescription. After adjustment, non-Hispanic White race, pregnancy during the years 2010-2012, higher parity, tobacco use, and use of illegal drugs during pregnancy were each significantly associated with opioid use during pregnancy. In addition, maternal depression was associated with increased odds of opioid use during pregnancy by more than two-fold (adjusted odds ratio 2.42, 95% confidence interval: 1.95-3.01). Conclusions: In this large study of pregnancies from across the United States, we found several factors that were associated with opioid use among pregnant people. Further studies examining screening for depression and polysubstance use may be useful for targeted interventions to prevent detrimental opioid use during pregnancy, while further elucidation of the reasons for use of prescription opioids during pregnancy should be further explored.

Impact of the COVID-19 pandemic on children's sleep habits: an ECHO study.

BACKGROUND: Sleep in childhood is affected by behavioral, environmental, and parental factors. We propose that these factors were altered during the COVID-19 pandemic. This study investigates sleep habit changes during the pandemic in 528 children 4-12 years old in the US, leveraging data from the Environmental Influences on Child Health Outcomes (ECHO) Program. METHODS: Data collection occurred in July 2019-March 2020 (pre-pandemic) and two pandemic periods: December 2020-April 2021 and May-August 2021. Qualitative interviews were performed in 38 participants. RESULTS: We found no changes in sleep duration, but a shift to later sleep midpoint during the pandemic periods. There was an increase in latency at the first pandemic collection period but no increase in the frequency of bedtime resistance, and a reduced frequency of naps during the pandemic. Qualitative interviews revealed that parents prioritized routines to maintain sleep duration but were more flexible regarding timing. Children from racial/ethnic minoritized communities slept less at night, had later sleep midpoint, and napped more frequently across all collection periods, warranting in-depth investigation to examine and address root causes. CONCLUSIONS: The COVID-19 pandemic significantly impacted children sleep, but parental knowledge of the importance of sleep might have played a significant protective role. IMPACT: During the COVID-19 pandemic, US children changed their sleep habits, going to bed and waking up later, but their sleep duration did not change. Sleep latency was longer. Parental knowledge of sleep importance might have played a protective role. Regardless of data collection periods, children from racial/ethnic minoritized communities slept less and went to bed later. This is one of the first study on this topic in the US, including prospective pre-pandemic qualitative and quantitative data on sleep habits. Our findings highlight the pandemic long-term impact on childhood sleep. Results warrants further investigations on implications for overall childhood health.

COVID-19 Pandemic Experiences and Symptoms of Pandemic-Associated Traumatic Stress Among Mothers in the US.

Importance: The primary outcomes of the COVID-19 pandemic on the mental health of women with children remain largely unknown. Objectives: To identify and describe clusters of mothers of children participating in the Environmental influences on Child Health Outcomes (ECHO) Program that characterize pandemic-associated hardships, coping mechanisms, and behaviors, and to evaluate associations between pandemic-associated hardships, coping strategies, and behavior changes with pandemic-associated traumatic stress symptoms. Design, Setting, and Participants: This multicenter cohort study investigated experiences during the COVID-19 pandemic between April 2020 and August 2021 among maternal caregivers of children participating in the ECHO Program. Data from self-identified mothers of ECHO-enrolled children from 62 US cohorts were included in analyses. Data were analyzed from November 2021 to July 2022. Exposures: The primary exposures were pandemic-associated changes in mothers' health, health care utilization, work and finances, coping strategies, and health-associated behaviors. Exposures were assessed via a self-reported questionnaire designed by ECHO investigators. Main Outcomes and Measures: The primary outcome was the total symptoms score of pandemic-associated traumatic stress (PTS), defined as the number of items endorsed at least sometimes or more frequently, from a 10-item self-report measure. Results: The study surveyed 11 473 mothers (mean [SD] age, 37.8 [7.4] years; 342 American Indian [2.98%], 378 Asian [3.29%], 1701 Black [14.83%], and 7195 White [62.71%]; 2184 with Hispanic/Latina ethnicity [19.04%]) and identified 2 clusters that best characterized their COVID-19 pandemic experiences-one characterized by higher life disruptions (eg, to work and health care), higher social isolation, more coping behaviors to mitigate the outcomes of the pandemic, and more changes to their health behavior routines (high change [1031 mothers]) and the other characterized by lower changes (low change [3061 mothers]). The high change cluster was more socioeconomically advantaged and reported higher PTS (mean [SD] number of symptoms, 3.72 [2.44] vs 2.51 [2.47]). Across both clusters, higher pandemic-associated hardships, coping mechanisms, and behavior changes were associated with higher PTS, and these associations were greater in the low change cluster. Conclusions and Relevance: In this study of more than 11 000 US mothers, associations between socioeconomic factors, stressful life events, and mental health sequelae were complex. Accordingly, programs, policies, and practices targeting mental health during public health crises such as the COVID-19 pandemic should consider the range and configuration of hardships in designing the most effective interventions to mitigate long-term outcomes.

Health Behavior Changes during the COVID-19 Pandemic: A Longitudinal Analysis among Children.

This longitudinal study compared children's health behaviors before the COVID-19 pandemic versus during the pandemic. This analysis examined the association between individual-level characteristics and health behavior change. Four prospective cohort studies in the Environmental influences on Child Health Outcomes (ECHO) Program contributed data. Children aged 4−12 years and their caregivers were recruited in California, Colorado, North Dakota, and New Hampshire. Dietary intake, physical activity, screen time, and sleep duration were assessed with questionnaires pre-pandemic and during the pandemic. The final sample included 347 children: 47% female and 62% non-Hispanic White. Compared with pre-pandemic, weekday screen time duration was higher during the pandemic (3.0 vs. 4.5 h, p < 0.001). Unadjusted increases in screen time duration differed by race and ethnicity: 1.3 h/day for non-Hispanic White children, 2.3 h/day for Hispanic children, and 5.3 h/day for non-Hispanic Black children. Overall, no changes occurred in sugar-sweetened beverage (SSB) intake (p = 0.26), discretionary food intake (p = 0.93), and physical activity (p = 0.15). Sleep duration increased by 30 min among children who did not meet sleep recommendations pre-pandemic. Child sex and maternal education level were not associated with health behavior change. The pandemic may have exacerbated disparities in some health behaviors. Families may need support to re-establish healthy routines.

Racial/ethnic disparities in subjective sleep duration, sleep quality, and sleep disturbances during pregnancy: an ECHO study.

In the United States, racial/ethnic minoritized groups experience worse sleep than non-Hispanic Whites (nHW), but less is known about pregnant people. This is a key consideration since poor sleep during pregnancy is common and associated with increased risk of adverse perinatal outcomes. This study reports the prevalence of subjective sleep measures in a multi-racial/ethnic pregnant population from the Environmental influences on Child Health Outcomes (ECHO) program. Participants' self-reported race and ethnicity were grouped into: nHW, non-Hispanic Black/African American (nHB/AA), Hispanic, non-Hispanic Asian (nHA). Analyses examined trimester-specific (first (T1), second (T2), third (T3)) nocturnal sleep duration, quality, and disturbances (Pittsburgh Sleep Quality Index and ECHO maternal sleep health questionnaire). Linear or multinomial regressions estimated the associations between race/ethnicity and each sleep domain by trimester, controlling for body mass index and age, with nHW as reference group. We repeated analyses within maternal education strata. nHB/AA participants reported shorter sleep duration (T2: ß = -0.55 [-0.80,-0.31]; T3: ß = -0.65 [-0.99,-0.31]) and more sleep disturbances (T2: ß = 1.92 [1.09,2.75]; T3: ß = 1.41 [0.09,2.74]). Hispanic participants reported longer sleep duration (T1: ß = 0.22 [0.00004,0.44]; T2: ß = 0.61 [0.47,0.76]; T3: ß = 0.46 [0.22,0.70]), better sleep quality (Reference group: Very good. Fairly good T1: OR = 0.48 [0.32,0.73], T2: OR = 0.36 [0.26,0.48], T3: OR = 0.31 [0.18,0.52]. Fairly bad T1: OR = 0.27 [0.16,0.44], T2: OR = 0.46 [0.31, 0.67], T3: OR = 0.31 [0.17,0.55]), and fewer sleep disturbances (T2: ß = -0.5 [-1.0,-0.12]; T3: ß = -1.21 [-2.07,-0.35]). Differences persisted within the high-SES subsample. Given the stark racial/ethnic disparities in perinatal outcomes and their associations with sleep health, further research is warranted to investigate the determinants of these disparities.

Changes in BMI During the COVID-19 Pandemic.

BACKGROUND AND OBJECTIVES: Experts hypothesized increased weight gain in children associated with the coronavirus disease 2019 (COVID-19) pandemic. Our objective was to evaluate whether the rate of change of child body mass index (BMI) increased during the COVID-19 pandemic compared with prepandemic years. METHODS: The study population of 1996 children ages 2 to 19 years with at least 1 BMI measure before and during the COVID-19 pandemic was drawn from 38 pediatric cohorts across the United States participating in the Environmental Influences on Child Health Outcomes-wide cohort study. We modeled change in BMI using linear mixed models, adjusting for age, sex, race, ethnicity, maternal education, income, baseline BMI category, and type of BMI measure. Data collection and analysis were approved by the local institutional review board of each institution or by the central Environmental Influences on Child Health Outcomes institutional review board. RESULTS: BMI increased during the COVID-19 pandemic compared with previous years (0.24 higher annual gain in BMI during the pandemic compared with previous years, 95% confidence interval 0.02 to 0.45). Children with BMI in the obese range compared with the healthy weight range were at higher risk for excess BMI gain during the pandemic, whereas children in higher-income households were at decreased risk of BMI gain. CONCLUSIONS: One effect of the COVID-19 pandemic is an increase in annual BMI gain during the COVID-19 pandemic compared with the 3 previous years among children in our national cohort. This increased risk among US children may worsen a critical threat to public health and health equity.

Identification of Measurement Needs to Prevent Childhood Obesity in High-Risk Populations and Environments.

INTRODUCTION: Children at highest obesity risk include those from certain racial/ethnic groups, from low-income families, with disabilities, or living in high-risk communities. However, a 2013 review of the National Collaborative for Childhood Obesity Research Measures Registry identified few measures focused on children at highest obesity risk. The objective is to (1) identify individual and environmental measures of diet and physical activity added to the Measures Registry since 2013 used among high-risk populations or settings and (2) describe methods for their development, adaptation, or validation. METHODS: Investigators screened references in the Measures Registry from January 2013 to September 2017 (n=351) and abstracted information about individual and environmental measures developed for, adapted for, or applied to high-risk populations or settings, including measure type, study population, adaptation and validation methods, and psychometric properties. RESULTS: A total of 38 measures met inclusion criteria. Of these, 30 assessed individual dietary (n=25) or physical activity (n=13) behaviors, and 11 assessed the food (n=8) or physical activity (n=7) environment. Of those, 17 measures were developed for, 9 were applied to (i.e., developed in a general population and used without modification), and 12 were adapted (i.e., modified) for high-risk populations. Few measures were used in certain racial/ethnic groups (i.e., American Indian/Alaska Native, Hawaiian/Pacific Islander, and Asian), children with disabilities, and rural (versus urban) communities. CONCLUSIONS: Since 2013, a total of 38 measures were added to the Measures Registry that were used in high-risk populations. However, many of the previously identified gaps in population coverage remain. Rigorous, community-engaged methodologic research may help researchers better adapt and validate measures for high-risk populations.

Methods and Risks of Bias in Natural Experiments in Obesity: Opportunities for the Future Informed by a Systematic Review.

OBJECTIVE: This paper promotes rigorous methods and designs currently underutilized in obesity research, informed by a recent systematic review of the methods and risks of bias in studies of policies, programs, and built environment changes for obesity prevention and control. METHODS: To determine the current state of the field, relevant databases from 2000 to 2017 were searched to identify studies that fit the inclusion criteria. Study design, analytic approach, and other details of study methods were abstracted. These findings inform recommendations for obesity researchers and the field as a whole. RESULTS: Previously identified were 156 natural experiment studies. Most were cross-sectional (35%), pre-post single group comparison (31%), or difference-in-differences designs (29%). Few used rigorous causal designs such as interrupted time series with more than two time points, propensity score methods, or instrumental variables. The potential relevance for obesity research is discussed, and recommendations for obesity researchers are provided. CONCLUSIONS: To strengthen natural experiment study designs and enhance the validity of results, researchers should carefully consider and control for confounding and selection of comparison groups and consider study designs that address these biases.

Economic Insecurity and Deaths of Despair in US Counties.

Recent research has implicated economic insecurity in increasing midlife death rates and "deaths of despair," including suicide, chronic liver disease, and drug and alcohol poisoning. In this ecological longitudinal study, we evaluated the association between changes in economic insecurity and increases in deaths of despair and midlife all-cause mortality in US counties during 2000-2015. We extended a previously developed measure of economic insecurity using indicators from the Census and Federal Reserve Bank in US counties for the years 2000 and 2010. Linear regression models were used to estimate the association of change in economic insecurity with change in death rates through 2015. Counties experiencing elevated economic insecurity in either 2000 or 2010 had higher rates of deaths of despair and all-cause midlife mortality at baseline but similar rates of increase in deaths of despair from 2001 to 2015 compared with counties with stable low economic insecurity. Counties in the highest tertile of economic insecurity in 2000 and 2010 had 41% (95% confidence interval: 1.36, 1.47) higher midlife mortality rates at baseline and a rate of increase of 2% more per 5-year period (95% confidence interval: 1.00, 1.03) than counties with stable low economic insecurity. Economic insecurity may represent a population-level driver of US death trends.

Consumer credit, chronic disease and risk behaviours.

BACKGROUND: Credit scores have been identified as a marker of disease burden. This study investigated credit scores' association with chronic diseases and health behaviours that are associated with chronic diseases. METHODS: This cross-sectional analysis included data on 2083 residents of Philadelphia, Pennsylvania, USA in 2015. Nine-digit ZIP code level FICO credit scores were appended to individual self-reported chronic diseases (obesity, diabetes, hypertension) and related health behaviours (smoking, exercise, and salt intake and medication adherence among those with hypertension). Models adjusted for individual-level and area-level demographics and retail pharmacy accessibility. RESULTS: Median ZIP code credit score was 665 (SD=58). In adjusted models, each 50-point increase in ZIP code credit score was significantly associated with: 8% lower chronic disease risk; 6% lower overweight/obesity risk, 19% lower diabetes risk; 9% lower hypertension risk and 14% lower smoking risk. Other health behaviours were not significantly associated. Compared with high prime credit, subprime credit score was significantly associated with a 15%-70% increased risk of chronic disease, following a dose-response pattern with a prime rating. CONCLUSION: Lower area level credit scores may be associated with greater chronic disease prevalence but not necessarily with related health behaviours. Area-level consumer credit may make a novel contribution to identifying chronic disease patterns.

Consumer credit scores as a novel tool for identifying health in urban U.S. neighborhoods.

PURPOSE: Credit scores may operate as a socioeconomic indicator of health: they represent cumulative financial history that directly influences ability to access financial and nonfinancial resources related to health. Yet, little is known about the relationship of credit score and health or to traditional measures of socioeconomic position (SEP). Our objectives were to (1) evaluate the association between area-level credit score and individual self-rated health and (2) compare credit score to traditional markers of area-level SEP in predicting self-rated health. METHODS: Equifax estimates of average household credit score in 2015 among nine-digit zip code regions were combined with a representative survey of 2083 residents of Philadelphia to estimate the correlation with income, housing value, education, and occupational status and then predict the odds of self-rated health for credit score and each SEP measure. RESULTS: Credit score was moderately correlated with SEP markers (r = -0.78 to 0.49). After adjusting for area- and individual-level SEP and demographic factors, each SD increase in credit score is associated with 26% greater odds of better self-rated health (odds ratio = 1.26, 95% confidence interval: 1.09-1.46). Credit score had a larger effect size than other SEP markers. CONCLUSIONS: Credit score may be a useful complement to traditional measures of SEP in assessing health outcomes.

Methods for Evaluating Natural Experiments in Obesity: A Systematic Review.

Background: Given the obesity pandemic, rigorous methodological approaches, including natural experiments, are needed. Purpose: To identify studies that report effects of programs, policies, or built environment changes on obesity prevention and control and to describe their methods. Data Sources: PubMed, CINAHL, PsycINFO, and EconLit (January 2000 to August 2017). Study Selection: Natural experiments and experimental studies evaluating a program, policy, or built environment change in U.S. or non-U.S. populations by using measures of obesity or obesity-related health behaviors. Data Extraction: 2 reviewers serially extracted data on study design, population characteristics, data sources and linkages, measures, and analytic methods and independently evaluated risk of bias. Data Synthesis: 294 studies (188 U.S., 106 non-U.S.) were identified, including 156 natural experiments (53%), 118 experimental studies (40%), and 20 (7%) with unclear study design. Studies used 106 (71 U.S., 35 non-U.S.) data systems; 37% of the U.S. data systems were linked to another data source. For outcomes, 112 studies reported childhood weight and 32 adult weight; 152 had physical activity and 148 had dietary measures. For analysis, natural experiments most commonly used cross-sectional comparisons of exposed and unexposed groups (n = 55 [35%]). Most natural experiments had a high risk of bias, and 63% had weak handling of withdrawals and dropouts. Limitation: Outcomes restricted to obesity measures and health behaviors; inconsistent or unclear descriptions of natural experiment designs; and imperfect methods for assessing risk of bias in natural experiments. Conclusion: Many methodologically diverse natural experiments and experimental studies were identified that reported effects of U.S. and non-U.S. programs, policies, or built environment changes on obesity prevention and control. The findings reinforce the need for methodological and analytic advances that would strengthen evaluations of obesity prevention and control initiatives. Primary Funding Source: National Institutes of Health, Office of Disease Prevention, and Agency for Healthcare Research and Quality. (PROSPERO: CRD42017055750).

Swing voting in the 2016 presidential election in counties where midlife mortality has been rising in white non-Hispanic Americans.

Understanding the effects of widespread disruption of the social fabric on public health outcomes can provide insight into the forces that drive major political realignment. Our objective was to estimate the association between increases in mortality in middle-aged non-Hispanic white adults from 1999 to 2005 to 2009-2015, health inequalities in life expectancy by income, and the surge in support for the Republican Party in pivotal US counties in the 2016 presidential election. We conducted a longitudinal ecological study in 2764 US counties from 1999 to 2016. Increases in mortality were measured using age-specific (45-54 years of age) all-cause mortality from 1999 to 2005 to 2009-2015 at the county level. Support for the Republican Party was measured as the party's vote share in the presidential election in 2016 adjusted for results in 2008 and 2012. We found a significant up-turn in mortality from 1999 to 2005 to 2009-2015 in counties where the Democratic Party won twice (2008 and 2012) but where the Republican Party won in 2016 (+10.7/100,000), as compared to those in which the Democratic Party won in 2016 (-15.7/100,000). An increase in mortality of 15.2/100,000 was associated with a significant (p < 0.001) 1% vote swing from the 2008-2012 average to 2016. We also found that counties with wider health inequalities in life expectancy were more likely to vote Republican in 2016, regardless of the previous voting patterns. Counties with worsening premature mortality in the last 15 years and wider health inequalities shifted votes toward the Republican Party presidential candidate. Further understanding of causes of unanticipated deterioration in health in the general population can inform social policy.