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IntroductionResearch 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.MethodsData 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.ResultsNet of confounders, one standard z-score higher average composite local food environment was associated with higher average AHEI diet score (β=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.ConclusionOur findings suggest that neighborhood-level food environment is associated with better diet quality, especially among racially/ethnically minoritized populations.

ObjectiveTo examine whether the density of neighbourhood restaurants affected the frequency of eating restaurant meals and subsequently affected diet quality.DesignCross-sectional and longitudinal designs. Structural equation models assessed the indirect relationship between restaurant density (≤3 miles (4·8 km) of participant addresses) and dietary quality (Healthy Eating Index 2010 (HEI)) via the frequency of eating restaurant meals, after adjustment for sociodemographics, select health conditions, region, residence duration and area-level income.SettingUrbanised areas in multiple regions of the USA, years 2000-2002 and 2010-2012.ParticipantsParticipants aged 45-84 years were followed for 10 years (n 3567).ResultsMedian HEI (out of 100) was fifty-nine at baseline and sixty-two at follow-up. The cross-sectional analysis found that residing in areas with a high density of restaurants (highest-ranked quartile) was associated with 52 % higher odds of frequently eating restaurant meals (≥3 times/week, OR: 1·52, 95 % CI 1·18, 1·98) and 3 % higher odds of having lower dietary quality (HEI lowest quartile < 54, OR: 1·03, 95 % CI 1·01, 1·06); associations were not sustained in longitudinal analyses. The cross-sectional analysis found 34 % higher odds of having lower dietary quality for those who frequently ate at restaurants (OR: 1·34, 95 % CI 1·12, 1·61), and more restaurant meals (over time increase ≥ 1 time/week) were associated with higher odds of having worse dietary quality at follow-up (OR: 1·21, 95 % CI 1·00, 1·46).ConclusionsRestaurant density was associated with frequently eating out in cross-sectional and longitudinal analyses but was associated with the lower dietary quality only in cross-sectional analyses. Frequent restaurant meals were negatively related to dietary quality. Interventions that encourage less frequent eating out may improve population dietary quality.

Longitudinal associations between neighborhood characteristics and body mass index (BMI; weight (kg)/height (m)2) were assessed from 2000 to 2011 among 5,919 participants in the Multi-Ethnic Study of Atherosclerosis. The perceived availability of healthy food and walking environment were assessed via surveys, and 1-mile (1.6-km) densities of supermarkets, fruit-and-vegetable stores, and recreational facilities were obtained through a commercial database. Econometric fixed-effects models were used to estimate the association between within-person changes in neighborhood characteristics and within-person change in BMI. In fully adjusted models, a 1-standard-deviation increase in the healthy food environment index was associated with a 0.16-kg/m2 decrease in BMI (95% confidence interval (CI): -0.27, -0.06) among participants with obesity at baseline. A 1-standard-deviation increase in the physical activity environment index was associated with 0.13-kg/m2 (95% CI: -0.24, -0.02) and 0.14-kg/m2 (95% CI: -0.27, -0.01) decreases in BMI for participants who were overweight and obese at baseline, respectively. Paradoxically, increases in the physical activity index were associated with BMI increases in persons who were normal-weight at baseline. This study provides preliminary longitudinal evidence that favorable changes in neighborhood physical environments are related to BMI reductions in obese persons, who comprise a substantial proportion of the US population.

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. [ABSTRACT FROM AUTHOR]

We investigated the relationships between neighborhood socio-demographic characteristics (socioeconomic status [SES], percentage of Black residents, and percentage of Hispanic residents) and survey-based measures of the social environment (social cohesion, safety) and the physical environment (healthy food environment, walking environment) in six sites from 2000 through 2011. Neighborhood environments were patterned by area SES and racial/ethnic composition, such that higher SES and lower percentage minority neighborhoods had better physical and social environments. Increasing disparities over time were observed for some neighborhood environments. Further research should explore the role of neighborhood environments in maintaining or increasing social disparities in health.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]