Impact of county and state immigration policies on immigrant household enrollment in the supplemental nutrition assistance program.

Introduction: Low-income immigrants who are eligible to participate in the Supplemental Nutrition Assistance Program (SNAP) participate at lower rates compared to non-immigrants. Immigrant households may be more likely to participate in SNAP if they live in areas with policies that integrate them into society and protect them from deportation. Methods: Data on low-income immigrant households came from the 2019 American Community Survey (N = 87,678). The outcome was whether any household member received SNAP in the previous 12 months. Immigrant policy exposures came from two sources: the State Immigration Policy Resource, which includes 18 immigrant criminalizing and integrating policies, and a database that identified 'sanctuary policies' (SP), which we summarized at the county level. Multivariable logistic regression adjusted for person/household-level and area-level confounders. Results: Living in a jurisdiction with a SP was associated with 21% higher odds of enrolling in SNAP compared to living in a jurisdiction without a SP (adjusted odds ratio [aOR] 1.21, 95% CI=1.11,1.31). Relative to the least immigrant friendly states, living in the most immigrant-friendly states was associated with 16% higher odds of SNAP enrollment (aOR=1.16, 95%CI=1.06-1.28). When SP and state-level immigrant friendly policy environment were cross-classified, SNAP participation was 23% and 26% higher for those living in jurisdictions with one- and both- exposures, respectively, relative to those with neither (aOR 1.23; CI 1.12,1.36; aOR 1.26; CI 1.15,1.37). Conclusions: Many at high risk of food insecurity - including immigrants and citizens in households with immigrants - are eligible for SNAP but under-enroll. Policies that welcome and safeguard immigrants could reduce under enrollment.

Adolescent mental distress in the wake of climate disasters.

Objective: Retrospective exposure to a higher number and prolonged duration of climate-related disasters could be positively associated with adolescent mental distress. Methods: Person-level data came from 38,616 high-school students residing in 22 urban public-school districts in 14 states (U.S. Youth Risk Behavior Survey, 2019). Each district's federally declared climate-related catastrophes (severe storms, floods, wildfire, etc.) came from the Federal Emergency Management Agency. Logistic regression models estimated the adjusted odds ratios (aOR) of adolescent mental distress (MD, using survey responses feeling prolonged sadness/ hopelessness and short sleep duration) according to disaster events and days during three exposure periods (past 2-, 5-, 10-years); adjusted for age, gender, race/ethnicity, socio-economic disadvantage, feeling unsafe at school, district area size, district poverty, and region. Results: Over 10 years, the median number of disaster events was 3 and total disaster days was 64. Adolescents experiencing the highest number of disaster days (top quartile vs. less) had 25% higher odds of MD when exposed within the past 2-years (aOR 1.25 [95% CI 1.14, 1.38]), and 20% higher odds of MD when exposed within the past 5-years (aOR 1.20 95% CI 1.07, 1.35). The odds of MD were not statistically associated with exposure periods that extended to 10 years, nor disaster events (instead of disaster days, all p-values > 0.1). Conclusions: Severe weather will become more frequent and last longer with human-induced climate warming. More studies like this are needed to understand the broad range of adverse effects and enhance planning and preparedness including preparing for worsening mental health among adolescents.

Spatial scale effects on associations between built environment and cognitive function: Multi-Ethnic Study of Atherosclerosis.

Built environments have the potential to favorably support cognitive function. Despite growing work on this topic, most of the work has ignored variation in the spatial scale of the effect. The issue with spatial scale effects is that the size and shape of the areal unit within which built environment characteristics are measured naturally influence the built environment exposure metric and thus the estimated associations with health. We used spatial distributed lag modeling (DLM) to estimate how associations between built environment exposures (walkable destinations [WD], social destinations [SD]) and change in cognition varied across distance of these destinations from participants' residences. Cognition was assessed as maintained/improved processing speed (PS) and global cognition (GC). Person-level data from Exam 5 (2010-2012) and Exam 6 (2016-2018) of the Multi-Ethnic Study of Atherosclerosis was used (N = 1380, mean age 67). Built environment data were derived from the National Establishment Time Series. Higher availability of walkable and social destinations at closer distance from participants' residence was associated with maintained/improved PS. The adjusted associations between maintained/improved PS and destinations waned with increasing distance from the residence; associations were evident until approximately 1.9-km for WD and 1.5-km for SD. Associations were most apparent for participants living in areas with high population density. We found little evidence for associations between change in GC and built environment at any distance. These results highlight the importance of identifying appropriate spatial scale to understand the mechanisms for built environment-cognition associations.

Do respiratory virus infections modify associations of asthma exacerbation with aeroallergens or fine particulate matter? A time series study in Philadelphia PA.

Respiratory virus infections are related to over 80% of childhood asthma exacerbations. They enhance pro-inflammatory mediator release, especially for sensitized individuals exposed to pollens/molds. Using a time-series study design, we investigated possible effect modification by respiratory virus infections of the associations between aeroallergens/PM2.5 and asthma exacerbation rates. Outpatient, emergency department (ED), and inpatient visits for asthma exacerbation among children with asthma (28,540/24,444 [warm/cold season]), as well as viral infection counts were obtained from electronic health records of the Children's Hospital of Philadelphia from 2011 to 2016. Rate ratios (RRs, 90th percentile vs. 0) for late-season grass pollen were 1.00 (0.85-1.17), 1.04 (0.95-1.15), and 1.12 (0.96-1.32), respectively, for respiratory syncytial virus (RSV) counts within each tertile. However, similar trends were not observed for weed pollens/molds or PM2.5. Overall, our study provides little evidence supporting effect modification by respiratory viral infections.

Neighborhood gentrification, wealth, and co-ethnic density associations with acculturation stressors among Chinese immigrants.

Objective: This study examined the cross-sectional relationships between neighborhood social composition and gentrification, and acculturation stressors. Methods: Person-level data came from first-generation Chinese immigrants enrolled in the Immigrant Enclaves Study (Philadelphia, Pennsylvania, baseline 2018-2020, N = 512). A validated scale was used to assess 22 stressors associated with migration or acculturation. Neighborhood characteristics from the American Community Survey 2015-2019 and 2008-2012 included: tract proportion of foreign born Chinese, neighborhood wealth, and past decade gentrification. Most neighborhood exposures were modeled as continuous as well as binary variables (intended to represent highest level of neighborhood exposure). Multivariable negative binomial regression adjusted for age, gender, income, education, employment, language, years in the U.S., and neighborhood variables (proportion co-ethnic, and neighborhood per capita income). Results: The majority of participants spoke Mandarin (68% vs Cantonese 32%), mean participant age was 52.7 years old, years in the US was 18, and nearly one-half of the sample had less than 8 years of education. Mean number of stressors was 5.9 with nearly 20% of participants reporting 11 or more stressors. Multivariable results found the number of acculturation stressors was 18% lower for residents in the highest co-ethnic density neighborhoods and 13% lower for residents in the highest wealth areas, compared to other areas (expß 0.82, 95% CI [CI] 0.69, 0.98; expß 0.87, CI 0.75, 1.01, respectively). Stressors were no different whether participants lived in gentrified areas or not. Conclusions: Among middle-aged Chinese immigrants, acculturation stress was lower for residents in neighborhoods with higher proportion of Chinese immigrants and for residents in neighborhoods with higher wealth, whereas gentrification had no influence on acculturation stress. More work on this topic is needed with vulnerable populations such as this one, informed by local context.

County- and state-level immigration policies are associated with Supplemental Nutrition Assistance Program (SNAP) participation among Latino households.

The purpose of this study was to investigate the association between county- and state-level immigrant criminalizing and integrating policies and Latino household participation in the largest safety net program against food insecurity in the U.S., the Supplemental Nutrition Assistance Program (SNAP). Our outcome, county-level proportion of SNAP-participating Latino households, and county-level covariates were obtained from the American Community Survey 1-year county files (N = 675 counties) for 13 years (2007-2019). Our exposures were county-level presence of sanctuary policies and a state-level immigrant friendliness score, created based on 19 immigrant criminalizing and integrating state-level policies obtained from the Urban Institute's State Immigration Policies Resource. We classified every county in the sample as 1) sanctuary policy + immigrant friendly state, 2) sanctuary policy + immigrant unfriendly state, 3) no sanctuary policy + immigrant friendly state, and 4) no sanctuary policy + immigrant unfriendly state. Using multivariable generalized linear models that adjusted for poverty levels and other social composition characteristics of counties, we found that county-level SNAP participation among Latino households was 1.1 percentage-point higher in counties with sanctuary policies (B = 1.12, 95%CI = 0.26-1.98), compared to counties with no sanctuary policies, and 1.6 percentage-point higher in counties with sanctuary policies in immigrant friendly states (B = 1.59, 95%CI = 0.33-2.84), compared to counties with no sanctuary policy in immigrant unfriendly states. Local and state immigration policy, even when unrelated to SNAP eligibility, may influence SNAP participation among Latino households. Jurisdictions which lack sanctuary policies or have more criminalizing and less integrating policies should consider adopting targeted outreach strategies to increase SNAP enrollment among Latino households.

Evaluation of evidence for interaction between PM2.5 and aeroallergens on childhood asthma exacerbation in Philadelphia, PA, 2011 to 2016.

Fine particulate matter (PM2.5) and aeroallergens (i.e., pollen, molds) are known triggers of asthma exacerbation. Despite mechanistic evidence suggesting synergistic effects between PM2.5 and asthma exacerbation, little epidemiologic work has been performed in children, which has exhibited inconsistency. We conducted a time-series study to explore their interactions using electronic health records (EHR) data in Philadelphia, PA, for asthma diagnoses in outpatient, emergency department [ED], and inpatient settings. Daily asthma exacerbation cases (28,540 asthma exacerbation case encounters) were linked to daily ambient PM2.5 and daily aeroallergen levels during the aeroallergen season of a six-year period (mid-March to October 2011-2016). Asthma exacerbation counts were modeled using quasi-Poisson regression, where PM2.5 and aeroallergens were fitted with distributed lag non-linear functions (lagged from 0 to 14-days), respectively, when modeled as the primary exposure variables. Regression models were adjusted for mean daily temperature/relative humidity, long-term and seasonal trends, day-of-week, and major U.S. holidays. Increasing gradient of RR estimates were observed for only a few primary exposure risk factors [PM2.5 (90th vs. 5th percentile)/aeroallergens (90th percentile vs. 0)], across different levels of effect modifiers. For example, RRs for the association between late-season grass pollen (lag1) and asthma exacerbation were higher at higher levels of PM2.5, 5-days preceding the exacerbation event (low PM2.5: RR = 1.01, 95% CI: 0.93-1.09; medium PM2.5: 1.04, 95% CI: 0.96-1.12; high PM2.5: 1.09, 95% CI: 1.01-1.19). However, most of the highest RRs for aeroallergens were instead observed for days with low- or medium- PM2.5 levels; likewise, when PM2.5 was modeled as the primary exposure with aeroallergens as the effect modifier. Most of the RR estimates did not exhibit gradients that suggested synergism, and were of relatively high imprecision. Overall, our study suggested no evidence for interactions between PM2.5 and aeroallergens in their relationships with childhood asthma exacerbation.

Longitudinal association between density of retail food stores and body mass index in Mexican school children and adolescents.

BACKGROUND: Obesity is rapidly increasing in Mexican children and adolescents, while food environments are rapidly changing. We evaluated the association between changes in retail food stores and change in body mass index (BMI) in Mexican children and adolescents. METHODS: Data on 7507 participants aged 5-19 years old came from the Mexican Family Life Survey 2002-2012. Density of food stores at the municipal-level (number of food stores/area in km2) came from the Economic Censuses of 1999, 2004 and 2009. We categorized food stores as small food retail (small neighborhood stores, tiendas de abarrotes in Mexico), specialty foods, fruit/vegetables, convenience foods, and supermarkets. Associations between change in food stores and change in BMI were estimated using five longitudinal linear fixed-effects regression models (one per type of food store) adjusted for age, parental education, municipal-level socioeconomic deprivation and population density. Density of each food store type was operationalized as quartiles. Analyses were stratified by urbanization. RESULTS: There was an inverse dose-response association between increases in fruit/vegetable store density and BMI (ß = -0.455 kg/m2, ß = -0.733 kg/m2, and ß = -0.838 kg/m2 in the second, third, and fourth quartile). In non-urban areas, children living in municipalities with the highest density of small food retail stores experienced a reduction in BMI (ß = -0.840 kg/m2). In urban areas, there was an inverse association between specialty food stores with BMI (ß = -0.789 kg/m2 in third quartile, and ß = -1.204 kg/m2 in fourth quartile). We observed dynamic associations with age; results suggested stronger associations in adolescents. CONCLUSIONS: The availability of fruit/vegetable stores may influence a reduction in children and adolescents BMI. These results indicate that policy approaches could be tailored by type of food store - with some consideration for level of urbanization and children's age.

Changes in physical activity after joining a bikeshare program: a cohort of new bikeshare users.

BACKGROUND: There are hundreds of bikeshare programs worldwide, yet few health-related evaluations have been conducted. We enrolled a cohort of new bikeshare members in Philadelphia (Pennsylvania, USA) to assess whether within-person moderate and vigorous physical activity (MVPA) increased with higher use of the program and whether effects differed for vulnerable sub-groups. METHODS: During 2015-2018, 1031 new members completed baseline and one-year follow-up online surveys regarding their personal characteristics and past 7-day MVPA minutes per week (minutes per week with- and without walking). Participants were linked to their bikeshare trips to objectively assess program use. Negative binomial (for continuous outcomes) and multinomial (for categorical outcomes) regression adjusted for person characteristics (socio-demographics, health), weather, biking-infrastructure, and baseline biking. RESULTS: Participant median age was 30, 25% were of Black or Latino race/ethnicity, and 30% were socioeconomically disadvantaged. By follow-up, personal bike ownership increased and 75% used bikeshare, although most used it infrequently. Per 10 day change in past year (PY) bikeshare use, non-walking MVPA min/wk increased 3% (roughly 6 min/wk, P < 0.014). More days of bikeshare was also associated with change from inactive to more active (odds ratio for ≥ 15 days in PY vs. no bikeshare use 1.80, CI 1.05-3.09, P < 0.03). Results were consistent across vulnerable sub-groups. In general, impacts on MVPA were similar when exposure was personal bike or bikeshare. CONCLUSIONS: Bikeshare facilitated increases in cycling, slightly increased non-walking MVPA, and showed potential for activating inactive adults; however, for larger program impact, members will need to use it more frequently.

Comparing effects of Euclidean buffers and network buffers on associations between built environment and transport walking: the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Transport walking has drawn growing interest due to its potential to increase levels of physical activities and reduce reliance on vehicles. While existing studies have compared built environment-health associations between Euclidean buffers and network buffers, no studies have systematically quantified the extent of bias in health effect estimates when exposures are measured in different buffers. Further, prior studies have done the comparisons focusing on only one or two geographic regions, limiting generalizability and restricting ability to test whether direction or magnitude of bias are different by context. This study aimed to quantify the degree of bias in associations between built environment exposures and transport walking when exposures were operationalized using Euclidean buffers rather than network buffers in diverse contexts. METHODS: We performed a simulations study to systematically evaluate the degree of bias in associations between built environment exposures in Euclidean buffers and network buffers and transport walking, assuming network buffers more accurately captured true exposures. Additionally, we used empirical data from a multi-ethnic, multi-site cohort to compare associations between built environment amenities and walking for transport where built environment exposures were derived using Euclidean buffers versus network buffers. RESULTS: Simulation results found that the bias induced by using Euclidean buffer models was consistently negative across the six study sites (ranging from -80% to -20%), suggesting built environment exposures measured using Euclidean buffers underestimate health effects on transport walking. Percent bias was uniformly smaller for the larger 5 km scale than the 1 km and 0.25 km spatial scales, independent of site or built environment categories. Empirical findings aligned with the simulation results: built environment-health associations were stronger for built environment exposures operationalized using network buffers than using Euclidean buffers. CONCLUSION: This study is the first to quantify the extent of bias in the magnitude of the associations between built environment exposures and transport walking when the former are measured in Euclidean buffers vs. network buffers, informing future research to carefully conceptualize appropriate distance-based buffer metrics in order to better approximate real geographic contexts. It also helps contextualize existing research in the field that used Euclidean buffers when that were the only option. Further, this study provides an example of the uncertain geographic context problem.

Exploring inequalities in life expectancy and lifespan variation by race/ethnicity and urbanicity in the United States: 1990 to 2019.

Background/Objective: Investigating trends in life expectancy and lifespan variation can highlight disproportionate mortality burdens among population subgroups. We examined inequalities in life expectancy and lifespan variation by race/ethnicity and by urbanicity in the US from 1990 to 2019. Methods: Using vital registration data for 322.0 million people in 3,141 counties from the National Center for Health Statistics, we obtained life expectancy at birth and lifespan variation for 16 race/ethnicity-gender-urbanicity combinations in six 5-year periods (1990-1994 to 2015-2019). Race/ethnicity was categorized as Hispanic, and non-Hispanic White, Black, and Asian/Pacific Islander. Urbanicity was categorized as metropolitan vs nonmetropolitan areas, or in six further detailed categorizations. Life expectancy and lifespan variation (coefficient of variation) were computed using life tables. Results: In 2015-2019, residents in metropolitan areas had higher life expectancies than their nonmetropolitan counterparts (79.6 years compared to 77.0 years). The widest inequality in life expectancy occurred between Asian/Pacific Islander women and Black men, with a 17.7-year gap for residents in metropolitan areas and a 16.9-year gap for residents in nonmetropolitan areas. Nonmetropolitan areas had greater dispersion around average age at death. Black individuals had the highest lifespan variations in both metropolitan and nonmetropolitan areas. Until the mid-2010s, life expectancy increased while lifespan variation decreased; however, recent trends show stagnation in life expectancy and increases in lifespan variation. Metropolitan-nonmetropolitan inequalities in both life expectancy and lifespan variation widened over time. Conclusion: Despite previous improvements in longevity, life expectancy is now stagnating while lifespan variation is increasing. Our results highlight that early-life deaths (i.e., young- and middle-age mortality) disproportionately affect Black individuals, who not only live the shortest lifespans but also have the most variability with respect to age at death.

Socioeconomic deprivation and changes in the retail food environment of Mexico from 2010 to 2020.

We aimed to analyze the change in the retail food environment of Mexican municipalities from 2010 to 2020, and to assess if these trends were modified by socioeconomic deprivation. We used data from the National Statistical Directory of Economic Units. Changes in the food store count were estimated using fixed-effects Poisson regression models, including coefficients for time, socioeconomic deprivation, and their interaction. We found a rapid growth in convenience stores, seed-grain stores, and supermarkets while small food retail stores declined. Urban areas had a higher count of all types of food stores; however, the steepest increases in food stores were observed in non-urban areas. The increase in convenience stores, supermarkets, specialty food stores, fruit-vegetable stores, and seed-grain stores was greater in the most deprived areas, compared to the least deprived areas. There has been a substantial expansion and rapid change in Mexico's food environment, mainly driven by increases in convenience stores and supermarkets in more deprived and less urbanized areas.

Alcohol outlets and alcohol consumption in changing environments: prevalence and changes over time.

BACKGROUND: To examine whether changes in density of neighborhood alcohol outlets affected changes in alcohol consumption 1-year after regulatory changes increased alcohol availability. METHODS: Person-level data came from a population-based cohort (aged 21-64) residing in/around the Philadelphia, Pennsylvania metropolitan area (2016-2018, N = 772). Fifty-eight percent lived in a state that began implementing new regulations (Pennsylvania) and the remainder lived in states without major regulatory changes (Delaware and New Jersey). Alcohol consumption was assessed as days per week (pw), drinks pw, high consumption (≥8 drinks pw), and binge drinking. Availability of off-premise alcohol outlets was assessed using 1-mile density and distance. Regression models adjusted for age, gender, race/ethnicity, income, education, health status, state and population density. RESULTS: Cross-sectional analyses found that higher outlet density was associated with more alcohol consumption (days, drinks, high consumption; all p < 0.03) and residing farther from an outlet was associated with less alcohol consumption (days and drinks; all p < 0.04). In longitudinal analyses, relative to no change in outlets, exposure to more outlets was associated with 64% higher odds of drinking on more days pw (p < 0.049) and 55% higher odds of consuming more drinks pw (p < 0.081). However, the longitudinal association between changes in outlets and changes in consumption did not differ for residents in Pennsylvania vs. nearby states. In cross-sectional and longitudinal analyses, outlets were not related to binge drinking. CONCLUSION: Off-premise outlets were associated with alcohol consumption consistently in cross-sectional analysis and in some longitudinal analyses. Results can inform future studies that wish to evaluate longer-term changes in increased alcohol availability and effects on consumption.

Longitudinal associations between objective and perceived healthy food environment and diet: The Multi-Ethnic Study of Atherosclerosis.

INTRODUCTION: Research examining the influence of neighborhood healthy food environment on diet has been mostly cross-sectional and has lacked robust characterization of the food environment. We examined longitudinal associations between features of the local food environment and healthy diet, and whether associations were modified by race/ethnicity. METHODS: Data on 3634 adults aged 45-84 followed for 10 years were obtained from the Multi-Ethnic Study of Atherosclerosis. Diet quality was assessed using the Alternative Healthy Eating Index at Exam 1 (2000-2002) and Exam 5 (2010-2012). We assessed four measures of the local food environment using survey-based measures (e.g. perceptions of healthier food availability) and geographic information system (GIS)-based measures (e.g. distance to and density of healthier food stores) at Exam 1 and Exam 5. Random effects models adjusted for age, sex, education, moving status, per capita adjusted income, and neighborhood socioeconomic status, and used interaction terms to assess effect measure modification by race/ethnicity. RESULTS: Net of confounders, one standard z-score higher average composite local food environment was associated with higher average AHEI diet score (ß=1.39, 95% CI: 1.05, 1.73) over the follow-up period from Exam 1 to 5. This pattern of association was consistent across both GIS-based and survey-based measures of local food environment and was more pronounced among minoritized racial/ethnic groups. There was no association between changes in neighborhood environment and change in AHEI score, or effect measure modification by race/ethnicity. CONCLUSION: Our findings suggest that neighborhood-level food environment is associated with better diet quality, especially among racially/ethnically minoritized populations.

Potential impacts of policies to reduce purchasing of ultra-processed foods in Mexico at different stages of the social transition: an agent-based modelling approach.

OBJECTIVES: To develop a simulation framework for assessing how combinations of taxes, nutrition warning labels and advertising levels could affect purchasing of ultra-processed foods (UPF) in Latin American countries and to understand whether policies reinforce or reduce pre-existing social disparities in UPF consumption. DESIGN: We developed an agent-based simulation model using international evidence regarding the effect of price, nutrition warning labels and advertising on UPF purchasing. SETTING: We estimated policy effects in scenarios representing two stages of the 'social transition' in UPF purchasing: (1) a pre-transition scenario, where UPF purchasing is higher among high-income households, similar to patterns in Mexico; and (2) a post-transition scenario where UPF purchasing is highest among low-income households, similar to patterns in Chile. PARTICIPANTS: A population of 1000 individual agents with levels of age, income, educational attainment and UPF purchasing similar to adult women in Mexico. RESULTS: A 20 % tax would decrease purchasing by 24 % relative to baseline in both the pre- and post-transition scenarios, an effect that is similar in magnitude to that of a nutrition warning label policy. A 50 % advertising increase or decrease had a comparatively small effect. Nutrition warning labels were most effective among those with higher levels of educational attainment. Labelling reduced inequities in the pre-transition scenario (i.e. highest UPF purchasing among the highest socio-economic group) but widened inequities in the post-transition scenario. CONCLUSIONS: Effective policy levers are available to reduce UPF purchasing, but policymakers should anticipate that equity impacts will differ depending on existing social patterns in UPF purchasing.

Exploring the spatial scale effects of built environments on transport walking: Multi-Ethnic Study of Atherosclerosis.

We employed a longitudinal distributed lag modeling approach to systematically estimate how associations between built environment features and transport walking decayed with the increase of distance from home to built environment destinations. Data came from a cohort recruited from six U.S. cities (follow-up 2000-2010, N = 3913, baseline mean age 60). Built environment features included all walkable destinations, consisting of common and popular destinations for daily life. We also included two subsets frequent social destinations and food stores to examine if the spatial scale effects differed by varying density for different types of built environment destinations. Adjusted results found that increases in transport walking diminished when built environment destinations were farther, although distance thresholds varied across different types of built environment destinations. Higher availability of walking destinations within 2-km and frequent social destinations within 1.6-km were associated with transport walking. Food stores were not associated with transport walking. This new information will help policymakers and urban designers understand at what distances each type of built environment destinations influences transport walking, in turn informing the development of interventions and/or the placement of amenities within neighborhoods to promote transport walking. The findings that spatial scales depend on specific built environment features also highlight the need for methods that can more flexibly estimate associations between outcomes and different built environment features across varying contexts, in order to improve our understanding of the spatial mechanisms involved in said associations.

Reply to Vale et al. Comment on "Zhong et al. Sugar-Sweetened and Diet Beverage Consumption in Philadelphia One Year after the Beverage Tax. Int. J. Environ. Res. Public Health 2020, 17, 1336".

Thank you for the opportunity to respond to the recent letter to the editor regarding our paper "Sugar-Sweetened and Diet Beverage Consumption in Philadelphia One Year after the Beverage Tax" [...].

The built and social neighborhood environment and child obesity: A systematic review of longitudinal studies.

The built and social neighborhood environment where a child lives has been increasingly studied as an exposure that may affect child weight long term. We conducted a systematic review of primary research articles published in 2011 through 2019 that reported results from longitudinal analyses of associations between neighborhood environment characteristics and child obesity or weight. Neighborhood environment measures included proximity to food stores, parks, and recreational facilities, walkability, crime, perceived safety, and social cohesion. Information on study population, exposure and outcome measures, and main results were extracted from 39 studies and results were presented for full cohorts and stratified by sex. Most studies were prospective cohorts (90%) with a median follow-up time of six years. Studies analyzing changes in the neighborhood versus changes in weight were less common than approaches analyzing baseline measures of the neighborhood environment in relation to obesity incidence or weight trajectories. Associations varied by sex, race/ethnicity, and age group. Within the food environment domain, the strongest evidence of adverse impact was for fast food restaurants but the effect was only apparent among girls. Results suggested green space, parks, and recreational facilities may have a beneficial effect on weight. Increased crime and low perceived safety may be risk factors for increased weight although not all studies were consistent. Standardization of measures across studies, investigation of multiple social and physical environment measures simultaneously, effect modification by demographic characteristics, and change in the environment vs change in weight analyses are needed to strengthen conclusions.

Longitudinal associations of neighborhood environment features with pediatric body mass index.

INTRODUCTION: It has been posited that policies to promote child health and prevent obesity should target neighborhood environments but evidence on the impact of neighborhoods on child weight is conflicting and longitudinal studies (which have benefits for causal inference) are scarce. METHODS: We used electronic health records (2007-2016) from an urban, pediatric integrated delivery system and linked children (N = 51,873, ages 6-19 years, 77% African American) to neighborhood-level data to investigate how changes in neighborhood environments relate to changes in body mass index (BMI). Measures of neighborhood environment were resources for healthy foods and physical activity ('resources'), greenness, violent crime rate, perceived safety and social cohesion. Fixed effects models estimated associations between changes in neighborhood environment exposures and changes in BMI z-score and whether effects differed by sex, baseline age, neighborhood socioeconomic status and population density. RESULTS: Approximately 22% of the cohort was obese (BMI z-score ≥ 95th percentile). In adjusted models, increases in neighborhood greenness and perceived safety were associated with decreases in BMI z-score (mean change in BMI z-score for 1-SD increase for both: -0.012; 95% CI= (-0.018, -0.007)). Increases in neighborhood safety had a stronger effect in children ages 6-10 years than in older children. Increases in social cohesion were associated with increases in BMI z-score (mean change: 0.005 95% CI = (0.003, 0.008)) especially in boys. Increases in food and physical activity resources were not associated with changes in BMI. CONCLUSIONS: This study suggests that increasing neighborhood greenness and safety are potential approaches to reduce children's BMI.

Educational inequalities in obesity: a multilevel analysis of survey data from cities in Latin America.

OBJECTIVE: Using newly harmonised individual-level data on health and socio-economic environments in Latin American cities (from the Salud Urbana en América Latina (SALURBAL) study), we assessed the association between obesity and education levels and explored potential effect modification of this association by city-level socio-economic development. DESIGN: This cross-sectional study used survey data collected between 2002 and 2017. Absolute and relative educational inequalities in obesity (BMI ≥ 30 kg/m2, derived from measured weight and height) were calculated first. Then, a two-level mixed-effects logistic regression was run to test for effect modification of the education-obesity association by city-level socio-economic development. All analyses were stratified by sex. SETTING: One hundred seventy-six Latin American cities within eight countries (Brazil, Chile, Colombia, Costa Rica, El Salvador, Guatemala, Mexico and Peru). PARTICIPANTS: 53 186 adults aged >18 years old. RESULTS: Among women, 25 % were living with obesity and obesity was negatively associated with educational level (higher education-lower obesity) and this pattern was consistent across city-level socio-economic development. Among men, 18 % were living with obesity and there was a positive association between education and obesity (higher education-higher obesity) for men living in cities with lower levels of development, whereas for those living in cities with higher levels of development, the pattern was inverted and university education was protective of obesity. CONCLUSIONS: Among women, education was protective of obesity regardless, whereas among men, it was only protective in cities with higher levels of development. These divergent results suggest the need for sex- and city-specific interventions to reduce obesity prevalence and inequalities.