Food insecurity in high-risk rural communities before and during the COVID-19 pandemic.

Objective: To perform a geospatial analysis of food insecurity in a rural county known to have poor health outcomes and assess the effect of the COVID-19 pandemic. Methods: In 2020, we mailed a comprehensive cross-sectional survey to all households in Sullivan County, a rural county with the second-worst health outcomes among all counties in New York State. Surveys of households included validated food insecurity screening questions. Questions were asked in reference to 2019, prior to the pandemic, and for 2020, in the first year of the pandemic. Respondents also responded to demographic questions. Raking adjustments were performed using age, sex, race/ethnicity, and health insurance strata to mitigate non-response bias. To identify significant hotspots of food insecurity within the county, we also performed geospatial analysis. Findings: From the 28,284 households surveyed, 20% of households responded. Of 4725 survey respondents, 26% of households reported experiencing food insecurity in 2019, and in 2020, this proportion increased to 35%. In 2020, 58% of Black and Hispanic households reported experiencing food insecurity. Food insecurity in 2020 was also present in 58% of unmarried households with children and in 64% of households insured by Medicaid. The geospatial analyses revealed that hotspots of food insecurity were primarily located in or near more urban areas of the rural county. Conclusions: Our countywide health survey in a high-risk rural county identified significant increases of food insecurity in the first year of the COVID-19 pandemic, despite national statistics reporting a stable rate. Responses to future crises should include targeted interventions to bolster food security among vulnerable rural populations.

Influence of the food environment on obesity risk in a large cohort of US veterans by community type.

OBJECTIVE: The aim of this study was to examine relationships between the food environment and obesity by community type. METHODS: Using electronic health record data from the US Veterans Administration Diabetes Risk (VADR) cohort, we examined associations between the percentage of supermarkets and fast-food restaurants with obesity prevalence from 2008 to 2018. We constructed multivariable logistic regression models with random effects and interaction terms for year and food environment variables. We stratified models by community type. RESULTS: Mean age at baseline was 59.8 (SD = 16.1) years; 93.3% identified as men; and 2,102,542 (41.8%) were classified as having obesity. The association between the percentage of fast-food restaurants and obesity was positive in high-density urban areas (odds ratio [OR] = 1.033; 95% CI: 1.028-1.037), with no interaction by time (p = 0.83). The interaction with year was significant in other community types (p < 0.001), with increasing odds of obesity in each follow-up year. The associations between the percentage of supermarkets and obesity were null in high-density and low-density urban areas and positive in suburban (OR = 1.033; 95% CI: 1.027-1.039) and rural (OR = 1.007; 95% CI: 1.002-1.012) areas, with no interactions by time. CONCLUSIONS: Many healthy eating policies have been passed in urban areas; our results suggest such policies might also mitigate obesity risk in nonurban areas.

Effects of Inclusion of Food Purchase Restrictions and Incentives in a Food Benefit Program on Diet Quality and Food Purchasing: Results From a Randomized Trial.

BACKGROUND: There is interest in reshaping the Supplemental Nutrition Assistance Program (SNAP) to better support family nutrition. OBJECTIVE: The Grocery Assistance Program Study (GAPS) for Families evaluated the effects of prohibiting using program funds for the purchase of certain sugary foods on the nutritional quality of foods purchased and consumed by program participants. DESIGN: A randomized experimental trial was carried out with participants randomized to one of three food benefit conditions. Baseline and follow-up measures collected included interviewer-administered 24-hour dietary recalls, food purchase receipts, food security, height, and weight. PARTICIPANT/SETTING: Adult-child dyads in households eligible for SNAP but currently not enrolled were recruited from the Minneapolis/St Paul MN metropolitan area from May of 2018 through May of 2019. A total of 293 adult-child dyads received the intervention as allocated. Of these dyads, 233 adults completed follow-up measures and met criteria for inclusion in the analytic sample, resulting in an attrition rate of 20.5%. A total of 224 children completed follow-up measures and met criteria for inclusion in the analytic sample, resulting in an attrition rate of 23.5%. INTERVENTION: Participants were randomized to 1 of 3 conditions: restriction (not allowed to buy sugar-sweetened beverages [SSB], sweet baked goods, or candy with program funds); restriction paired with incentive (30% incentive for fruits and vegetables [FV] purchased with funds); and control (funds provided with no restrictions or incentives). Funds were provided on a 4-week cycle for 20 weeks via a study-provided debit card. MAIN OUTCOME MEASURES: The primary outcome was the Healthy Eating Index (HEI)-2015 total score. Additional outcomes included selected HEI-2015 component scores; energy intake; food security; body weight; and purchasing of SSB, sweet baked goods, candies, fruits, and vegetables. STATISTICAL ANALYSIS: Linear regression analyses were conducted with change in the outcome regressed on treatment condition for the primary outcome analyses. RESULTS: No differences were observed between conditions in change in the nutrition and food security measures examined. Purchases of SSB and sweet baked goods and candies significantly differed by experimental condition. Purchase of restricted foods was lower at follow-up in the restriction and restriction paired with incentive conditions compared with the control condition. For example, spending on SSB at follow-up was significantly lower in the restriction ($2.66/week) and restriction paired with incentive ($2.06/week) conditions in comparison with control condition ($4.44/week) (P < 0.0003 and P < 0.0001, respectively). CONCLUSIONS: This study failed to find evidence in support of prohibiting the purchase of sugary foods with food program funds as a strategy to improve program participant nutrition, even when paired with an FV incentive. Research carried out in the context of the SNAP program is needed for a more robust evidence base.

Gentrification and childhood obesity: Evidence from New York City public school students in public housing.

OBJECTIVE: The study objective was to determine the effect of gentrification on the weight outcomes of New York City public school students living in public housing. METHODS: In a prospective cohort of 19,022 New York City public school students in public housing followed during 2009-2017, weight outcomes of students living in public housing buildings in gentrified neighborhoods were compared to those living in consistently low-socioeconomic-status neighborhoods; assignment was quasi-random in each borough. RESULTS: Among the 42,182 student-year observations, gentrification did not increase weight outcomes significantly, for BMI z scores (0.037; 95% CI: -0.012 to 0.086), obesity (0.6 percentage points [pp]; 95% CI: -0.9 to 2.1), or overweight (1.3 pp; 95% CI: -0.7 to 3.2). However, heterogeneous effects by borough were found, where the gentrification in Manhattan increased students' BMI z scores by 0.19 (95% CI: 0.09-0.29), obesity by 3.4 pp (95% CI: 0.03-6.5), and overweight by 9.2 pp (95% CI: 6.3-12.1). No heterogeneity by race and ethnicity, gender, or age was found. CONCLUSIONS: With strong internal validity, this study shows that neighborhood gentrification differentially influenced children's health through obesity, based on borough of residence. Such findings could inform policies or interventions focused on subpopulations and geographies.

"I Don't Want an App to Do the Work for Me": A Qualitative Study on the Perception of Online Grocery Shopping From Small Food Retailers.

BACKGROUND: Small food retailers often stock energy-dense convenience foods, and they are ubiquitous in low-income urban settings. With the rise in e-commerce, little is known about the acceptability of online grocery shopping from small food retailers. OBJECTIVE: To explore perceptions of the role of small food retailers (bodegas) in food access and the acceptability of online grocery shopping from bodegas among customers and owners in a diverse New York City urban neighborhood with low incomes. DESIGN: In-depth interviews were conducted with bodega owners and adult customers between May and July 2022. PARTICIPANTS/SETTING: Bodega owners who either had (n = 4) or had not (n = 2) implemented a locally designed online grocery system. Customers (n = 25) were recruited through purposive sampling and were eligible if they purchased at bodegas (>once per month), had low income (household income ≤130% of the federal poverty level or Supplemental Nutrition Assistance Program [SNAP] participants), and owned smartphones. ANALYSES PERFORMED: All interviews were transcribed and analyzed in MAXQDA (Verbi Software, Berlin, Germany), using grounded theory. RESULTS: To owners and customers, bodegas were seen as good neighbors providing culturally appropriate foods and an informal financial safety net. Their perceptions concerning food cost and availability of healthy foods in bodegas diverged. Although most perceived online grocery from bodegas as a positive community resource, they also believed it was not suited to their own community because of the bodega's proximity to customers' homes and the low digital literacy of some community members. Customers reported social norms of pride in not using online grocery shopping. Owners and customers believed the service would more likely be used if government benefits such as SNAP allowed payment for online orders. Both suggested improved outreach to increase program awareness and uptake. CONCLUSIONS: Online grocery shopping from small food retailers may be acceptable in urban communities with low income and was perceived as a community resource. However, important barriers need to be addressed, such as social norms related to pride in not using online grocery services, digital literacy, program awareness, and allowing SNAP payment for online orders from bodegas.

Menu Labeling and Calories Purchased in Restaurants in a US National Fast Food Chain.

Importance: Menu labeling has been implemented in restaurants in some US jurisdictions as early as 2008, but the extent to which menu labeling is associated with calories purchased is unclear. Objective: To estimate the association of menu labeling with calories and nutrients purchased and assess geographic variation in results. Design, Setting, and Participants: A cohort study was conducted with a quasi-experimental design using actual transaction data from Taco Bell restaurants from calendar years 2007 to 2014 US restaurants with menu labeling matched to comparison restaurants using synthetic control methods. Data were analyzed from May to October 2023. Exposure: Menu labeling policies in 6 US jurisdictions. Main Outcomes and Measures: The primary outcome was calories per transaction. Secondary outcomes included total and saturated fat, carbohydrates, protein, sugar, fiber, and sodium. Results: The final sample included 2329 restaurants, with menu labeling in 474 (31 468 restaurant-month observations). Most restaurants (94.3%) were located in California. Difference-in-differences model results indicated that customers purchased 24.7 (95% CI, 23.6-25.7) fewer calories per transaction from restaurants in the menu labeling group in the 3- to 24-month follow-up period vs the comparison group, including 21.9 (95% CI, 20.9-22.9) fewer calories in the 3- to 12-month follow-up period and 25.0 (95% CI, 24.0-26.1) fewer calories in the 13- to 24-month follow-up period. Changes in the nutrient content of transactions were consistent with calorie estimates. Findings in California were similar to overall estimates in magnitude and direction; yet, among restaurants outside of California, no association was observed in the 3- to 24-month period. The outcome of menu labeling also differed by item category and time of day, with a larger decrease in the number of tacos vs other items purchased and a larger decrease in calories purchased during breakfast vs other times of the day in the 3- to 24-month period. Conclusions and Relevance: In this quasi-experimental cohort study, fewer calories were purchased in restaurants with calorie labels compared with those with no labels, suggesting that consumers are sensitive to calorie information on menu boards, although associations differed by location.

Demographic, social and geographic factors associated with glycaemic control among US Veterans with new onset type 2 diabetes: a retrospective cohort study.

OBJECTIVES: This study evaluated whether a range of demographic, social and geographic factors had an influence on glycaemic control longitudinally after an initial diagnosis of diabetes. DESIGN, SETTING AND PARTICIPANTS: We used the US Veterans Administration Diabetes Risk national cohort to track glycaemic control among patients 20-79-year old with a new diagnosis of type 2 diabetes. PRIMARY OUTCOME AND METHODS: We modelled associations between glycaemic control at follow-up clinical assessments and geographic factors including neighbourhood race/ethnicity, socioeconomic, land use and food environment measures. We also adjusted for individual demographics, comorbidities, haemoglobin A1c (HbA1c) at diagnosis and duration of follow-up. These factors were analysed within strata of community type: high-density urban, low-density urban, suburban/small town and rural areas. RESULTS: We analysed 246 079 Veterans who developed a new type 2 diabetes diagnosis in 2008-2018 and had at least 2 years of follow-up data available. Across all community types, we found that lower baseline HbA1c and female sex were strongly associated with a higher likelihood of within-range HbA1c at follow-up. Surprisingly, patients who were older or had more documented comorbidities were more likely to have within-range follow-up HbA1c results. While there was variation by community type, none of the geographic measures analysed consistently demonstrated significant associations with glycaemic control across all community types.

Association between racial residential segregation and walkability in 745 U.S. cities.

Despite higher chronic disease prevalence, minoritized populations live in highly walkable neighborhoods in US cities more frequently than non-minoritized populations. We investigated whether city-level racial residential segregation (RRS) was associated with city-level walkability, stratified by population density, possibly explaining this counterintuitive association. RRS for Black-White and Latino-White segregation in large US cities was calculated using the Index of Dissimilarity (ID), and walkability was measured using WalkScore. Median walkability increased across increasing quartiles of population density, as expected. Higher ID was associated with higher walkability; associations varied in strength across strata of population density. RRS undergirds the observed association between walkability and minoritized populations, especially in higher population density cities.

COVID-19 vaccines for children: Racial and ethnic disparities in New York City.

Vaccination is an indispensable tool to reduce negative outcomes due to COVID-19. Although COVID-19 disproportionately affected lower income and Black and Hispanic communities, these groups have had lower population-level uptake of vaccines. Using detailed cross-sectional data, we examined racial and ethnic group differences in New York City schoolchildren becoming fully vaccinated (two doses) within 6 months of vaccine eligibility. We matched school enrollment data to vaccination data in the Citywide Immunization Registry, a census of all vaccinations delivered in New York City. We used ordinary least squares regression models to predict fully vaccinated status, with key predictors of race and ethnicity using a variety of different control variables, including residential neighborhood or school fixed effects. We also stratified by borough and by age. The sample included all New York City public school students enrolled during the 2021-2022 school year. Asian students were most likely to be vaccinated and Black and White students least likely. Controlling for student characteristics, particularly residential neighborhood or school attended, diminished some of the race and ethnicity differences. Key differences were also present by borough, both overall and by racial and ethnic groups. In sum, racial and ethnic disparities in children's COVID-19 vaccination were present. Vaccination rates varied by the geographic unit of borough; controlling for neighborhood characteristics diminished some disparities by race and ethnicity. Neighborhood demographics and resources, and the attributes, culture and preferences of those who live there may affect vaccination decisions and could be targets of future efforts to increase vaccination rates.

Evaluating the outcomes and implementation determinants of interventions co-developed using human-centered design to promote healthy eating in restaurants: an application of the consolidated framework for implementation research.

Background: Restaurants are an emerging yet underutilized setting to facilitate healthier eating, particularly among minoritized communities that disproportionately experience health inequities. The present study aimed to examine outcomes from interventions co-developed using Human-Centered Design (HCD) in two Latin American restaurants, including sales of healthier menu items (HMI) and the consumer nutrition environment. In addition, we aimed to assess implementation outcomes (acceptability, fidelity, and sustainability) and elucidate the determinants for implementation using the Consolidated Framework for Implementation Research. Methods: This study used a mixed-methods, longitudinal design. Data were collected pre-, during, and post-intervention testing. Intervention outcomes were examined through daily sales data and the Nutrition Environment Measures Survey for Restaurants (NEMS-R). Changes in HMI sales were analyzed using interrupted time series. Implementation outcomes and determinants were assessed through site visits [observations, interviews with staff (n = 19) and customers (n = 31)], social media monitoring, and post-implementation key informant interviews with owners and staff. Qualitative data were analyzed iteratively by two independent researchers using codes developed a priori based on CFIR. Results: The HCD-tailored interventions had different outcomes. In restaurant one (R1), where new HMI were introduced, we found an increase in HMI sales and improvements in NEMS-R scores. In restaurant two, where existing HMI were promoted, we found no significant changes in HMI sales and NEMS-R scores. Acceptance was high among customers and staff, but fidelity and sustainability differed by restaurant (high in R1, low in R2). Barriers and facilitators for implementation were found across all CFIR constructs, varying by restaurant and intervention. Most relevant constructs were found in the inner setting (restaurant structure, implementation climate), individual characteristics, and process (HCD application). The influence of outer setting constructs (policy, peer pressure) was limited due to lack of awareness. Conclusion: Our findings provide insights for interventions developed in challenging and constantly changing settings, as in the case of restaurants. This research expands the application of CFIR to complex and dynamic community-based settings and interventions developed using HCD. This is a significant innovation for the field of public health nutrition and informs future interventions in similarly dynamic and understudied settings.

The link between gentrification, children's egocentric food environment, and obesity.

While advocates argue that gentrification changes the neighborhood food environment critical to children's diet and health, we have little evidence documenting such changes or the consequences for their health outcomes. Using rich longitudinal, individual-level data on nearly 115,000 New York City children, including egocentric measures of their food environment and BMI, we examine the link between neighborhood demographic change ("gentrification"), children's access to restaurants and supermarkets, and their weight outcomes. We find that children in rapidly gentrifying neighborhoods see increased access to fast food and wait-service restaurants and reduced access to corner stores and supermarkets compared to those in non-gentrifying areas. Boys and girls have higher BMI following gentrification, but only boys are more likely to be obese or overweight. We find public housing moderates the relationship between gentrification and weight, as children living in public housing are less likely to be obese or overweight.

Effect of Financial Incentives and Default Options on Food Choices of Adults With Low Income in Online Retail Settings: A Randomized Clinical Trial.

Importance: Despite recent growth in online redemption of Supplemental Nutrition Assistance Program (SNAP) benefits, no previous work has tested the impact of economic and behavioral economic strategies on food purchasing behaviors in an online grocery retail setting among adults with low income. Objective: To examine the extent to which financial incentives and default shopping cart options influence fruit and vegetable purchases. Design, Setting, and Participants: This randomized clinical trial used an experimental online grocery store for adults who currently or have ever received SNAP benefits. From October 7 to December 2, 2021, participants were instructed to shop for a week's worth of groceries for their household, with a budget tailored to household size; no payment was taken. Interventions: Random assignment to 1 of 4 conditions: no intervention, 50% discount on eligible fruits and vegetables, prefilled shopping carts with tailored fruit and vegetable items (ie, default options), or a combination of the discount and default options. Main Outcomes and Measures: The primary outcome was the percentage of nondiscounted dollars spent on eligible fruit and vegetables per basket. Results: Of 2744 participants, mean (SD) age was 46.7 (16.0) years, and 1447 (52.7%) identified as women. A total of 1842 participants (67.1%) reported currently receiving SNAP benefits and 1492 (54.4%) reported shopping online for groceries in the previous 12 months. Participants spent a mean (SD) 20.5% (23.5%) of total dollars on eligible fruits and vegetables. Compared with no intervention, those in the discount condition spent 4.7% (98.3% CI, 1.7%-7.7%) of more total dollars on eligible fruits and vegetables; those in the default condition, 7.8% (98.3% CI, 4.8%-10.7%) more; and those in the combination condition, 13.0% (98.3% CI, 10.0%-16.0%) more (P < .001 for all). There was no difference between the discount and the default conditions (P = .06), but the effect in the combination condition was significantly larger than both discount and default conditions (P < .001). Default shopping cart items were purchased by 679 participants (93.4%) in the default condition and 655 (95.5%) in the combination condition, whereas 297 (45.8%) in the control and 361 (52.9%) in the discount conditions purchased those items (P < .001). No variation was observed by age, sex, or race and ethnicity, and results were similar when those who reported never shopping online for groceries were excluded. Conclusions and Relevance: In this randomized clinical trial, financial incentives for fruits and vegetables and default options, especially in combination, led to meaningful increases in online fruit and vegetable purchases among adults with low income. Trial Registration: ClinicalTrials.gov Identifier: NCT04766034.

The Effects of Owner-Occupied Housing on Student Outcomes: Evidence from NYC.

The view of owning a home as integral to the "American dream" is enshrined in numerous policies designed to promote homeownership. Whether or not these policies are worth their cost is unclear and depends, in part, on the extent to which owner-occupied housing (OOH) confers socially important benefits. Yet identifying the effects of OOH is complicated, not only due to standard concerns about selection, but also because OOH tends to be located in neighborhoods with better amenities (including schools) and is often synonymous with living in a single-family home. In this paper we use rich, longitudinal student-level data to examine whether students in OOH have better academic and health outcomes than those in renter occupied housing (ROH). We address concerns about selection using student fixed effects and a rich set of individual, building, and neighborhood controls. We find that that there is notable variation in both the characteristics and size of OOH and the types of students who live in OOH in NYC. While raw differences show that students who live in OOH have better outcomes-they are less likely to be chronically absent, obese, or overweight and have higher standardized test scores-much of this disparity is explained by differences in the students who select into OOH. In models where we account for selection into OOH and building type with rich controls and student fixed effects, we find small positive effects of moving into OOH on attendance and math scores with no consistent evidence of any impacts of OOH on BMI or obesity, suggesting that policies that promote homeownership might be oversold.

Disparities in routine healthcare utilization disruptions during COVID-19 pandemic among veterans with type 2 diabetes.

BACKGROUND: While emerging studies suggest that the COVID-19 pandemic caused disruptions in routine healthcare utilization, the full impact of the pandemic on healthcare utilization among diverse group of patients with type 2 diabetes is unclear. The purpose of this study is to examine trends in healthcare utilization, including in-person and telehealth visits, among U.S. veterans with type 2 diabetes before, during and after the onset of the COVID-19 pandemic, by demographics, pre-pandemic glycemic control, and geographic region. METHODS: We longitudinally examined healthcare utilization in a large national cohort of veterans with new diabetes diagnoses between January 1, 2008 and December 31, 2018. The analytic sample was 733,006 veterans with recently-diagnosed diabetes, at least 1 encounter with veterans administration between March 2018-2020, and followed through March 2021. Monthly rates of glycohemoglobin (HbA1c) measurements, in-person and telehealth outpatient visits, and prescription fills for diabetes and hypertension medications were compared before and after March 2020 using interrupted time-series design. Log-linear regression model was used for statistical analysis. Secular trends were modeled with penalized cubic splines. RESULTS: In the initial 3 months after the pandemic onset, we observed large reductions in monthly rates of HbA1c measurements, from 130 (95%CI,110-140) to 50 (95%CI,30-80) per 1000 veterans, and in-person outpatient visits, from 1830 (95%CI,1640-2040) to 810 (95%CI,710-930) per 1000 veterans. However, monthly rates of telehealth visits doubled between March 2020-2021 from 330 (95%CI,310-350) to 770 (95%CI,720-820) per 1000 veterans. This pattern of increases in telehealth utilization varied by community type, with lowest increase in rural areas, and by race/ethnicity, with highest increase among non-hispanic Black veterans. Combined in-person and telehealth outpatient visits rebounded to pre-pandemic levels after 3 months. Despite notable changes in HbA1c measurements and visits during that initial window, we observed no changes in prescription fills rates. CONCLUSIONS: Healthcare utilization among veterans with diabetes was substantially disrupted at the onset of the pandemic, but rebounded after 3 months. There was disparity in uptake of telehealth visits by geography and race/ethnicity.

A Matched Analysis of the Association Between Federally Mandated Smoke-Free Housing Policies and Health Outcomes Among Medicaid-Enrolled Children in Subsidized Housing, New York City, 2015-2019.

Smoke-free housing policies are intended to reduce the deleterious health effects of secondhand smoke exposure, but there is limited evidence regarding their health impacts. We examined associations between implementation of a federal smoke-free housing rule by the New York City Housing Authority (NYCHA) and pediatric Medicaid claims for asthma, lower respiratory tract infections, and upper respiratory tract infections in the early post-policy intervention period. We used geocoded address data to match children living in tax lots with NYCHA buildings (exposed to the policy) to children living in lots with other subsidized housing (unexposed to the policy). We constructed longitudinal difference-in-differences models to assess relative changes in monthly rates of claims between November 1, 2015, and December 31, 2019 (the policy was introduced on July 30, 2018). We also examined effect modification by baseline age group (≤2, 3-6, or 7-15 years). In New York City, introduction of a smoke-free policy was not associated with lower rates of Medicaid claims for any outcomes in the early postpolicy period. Exposure to the smoke-free policy was associated with slightly higher than expected rates of outpatient upper respiratory tract infection claims (incidence rate ratio = 1.05, 95% confidence interval: 1.01, 1.08), a result most pronounced among children aged 3-6 years. Ongoing monitoring is essential to understanding long-term health impacts of smoke-free housing policies.

Long-Term Trends in Secondhand Smoke Exposure in High-Rise Housing Serving Low-Income Residents in New York City: Three-Year Evaluation of a Federal Smoking Ban in Public Housing, 2018-2021.

INTRODUCTION: In July 2018, the U.S. Department of Housing and Urban Development passed a rule requiring public housing authorities to implement smoke-free housing (SFH) policies. We measured secondhand smoke (SHS) exposure immediately before, and repeatedly up to 36 months post-SFH policy implementation in a purposeful sample of 21 New York City (NYC) high-rise buildings (>15 floors): 10 NYC Housing Authority (NYCHA) buildings subject to the policy and 11 privately managed buildings in which most residents received housing vouchers (herein "Section 8"). AIMS AND METHODS: We invited participants from nonsmoking households (NYCHA n = 157, Section-8 n = 118) to enroll in a longitudinal air monitoring study, measuring (1) nicotine concentration with passive, bisulfate-coated filters, and (2) particulate matter (PM2.5) with low-cost particle sensors. We also measured nicotine concentrations and counted cigarette butts in common areas (n = 91 stairwells and hallways). We repeated air monitoring sessions in households and common areas every 6 months, totaling six post-policy sessions. RESULTS: After 3 years, we observed larger declines in nicotine concentration in NYCHA hallways than in Section-8, [difference-in-difference (DID) = -1.92 µg/m3 (95% CI -2.98, -0.87), p = .001]. In stairwells, nicotine concentration declines were larger in NYCHA buildings, but the differences were not statistically significant [DID= -1.10 µg/m3 (95% CI -2.40, 0.18), p = .089]. In households, there was no differential change in nicotine concentration (p = .093) or in PM2.5 levels (p = .385). CONCLUSIONS: Nicotine concentration reductions in NYCHA common areas over 3 years may be attributable to the SFH policy, reflecting its gradual implementation over this time. IMPLICATIONS: Continued air monitoring over multiple years has demonstrated that SHS exposure may be declining more rapidly in NYCHA common areas as a result of SFH policy adherence. This may have positive implications for improved health outcomes among those living in public housing, but additional tracking of air quality and studies of health outcomes are needed. Ongoing efforts by NYCHA to integrate the SFH policy into wider healthier-homes initiatives may increase policy compliance.

Exposure to local violent crime and childhood obesity and fitness: Evidence from New York City public school students.

This paper estimates the relationship between neighborhood violent crime and child and adolescent weight and fitness. It uses detailed data from the Fitnessgram assessments of public school students in New York City matched to point specific crime data geocoded to students' residential location. Our empirical approach compares the weight and fitness outcomes of students exposed to a violent crime on their residential H-block with those living in the same census tract but not exposed to violent crime in close proximity to their home. We find for adolescent girls, increases in BMI that range from 0.01 to 0.035 standard deviations and an increase in the probability of overweight of 0.5 to 1.7 percentage points. We find little evidence that BMI, obesity, and overweight change as a result of violent crime for adolescent boys, and younger children. Results are not explained by declines in physical fitness.

Age-Specific Differences in Online Grocery Shopping Behaviors and Attitudes among Adults with Low Income in the United States in 2021.

Background: Online grocery shopping has surged in popularity, but we know little about online grocery shopping behaviors and attitudes of adults with low income, including differences by age. Methods: From October to November 2021, we used a survey research firm to recruit a convenience sample of adults who have ever received Supplemental Nutrition Assistance Program (SNAP) benefits (n = 3526). Participants completed an online survey designed to assess diet and online food shopping behaviors. Using logistic regression, we examined the relationship between participant characteristics, including age, and the likelihood of online grocery shopping, and separately examined variation in the reasons for online grocery shopping by age. Results: About 54% of the participants reported shopping online for groceries in the previous 12 months. Odds of online shopping were higher for those aged 18−33 years (OR = 1.95 (95% CI: 1.52, 2.52; p < 0.001)) and 34−44 years (OR = 1.50 (95% CI: 1.19, 1.90; p < 0.001)) than for those aged ≥65 years. Odds were also higher for those who were food insecure and those with income below USD 20,000, higher educational attainment, and higher fruit and vegetable intake. Low prices were the most popular reason for online grocery shopping (57%). Adults aged 18−33 years old had higher odds of reporting low prices as a motivating factor than older adults (OR = 2.34 (95% CI: 1.78, 3.08; p < 0.001)) and lower odds of reporting being discouraged by lack of social interaction (OR = 0.34 (95% CI: 0.25, 0.45; p < 0.001)). Conclusion: Strategies for making online grocery shopping more affordable for adults with lower income may be promising, especially online produce. For older adults, additional support may be needed to make online shopping a suitable replacement for in-store shopping, such as education on technology and combining it with opportunities for social support.