Association of Park Renovation With Park Use in New York City.

Importance: Equity-driven citywide park redesign and renovation, such as the Community Parks Initiative (CPI), has the potential to increase park use and opportunities for physical activity in underserved communities. Objective: To evaluate changes in patterns of park use following park redesign and renovation in low-income New York City (NYC) neighborhoods. Design, Setting, and Participants: The Physical Activity and Redesigned Community Spaces study was a prospective quality improvement preintervention-postintervention study design with matched control parks. Thirty-three intervention and 21 control neighborhood parks were selected based on specific criteria related to poverty rates, population growth, and population density in park neighborhoods and not having received more than $250 000 in investment in the past 2 decades. Data were collected at baseline (prerenovation) and 2 follow-up points (3 months and 1 year post renovation) between June 5 and December 4 from 2016 to 2022. Participants were individuals observed as users of study parks. Intervention: The CPI, which involved the redesign and renovation of neighborhood parks by the municipal government of New York City. Main Outcomes and Measures: Main outcomes encompassed park use and physical activity levels assessed using the well-validated System for Observing Play and Recreation in Communities. Park use was quantified by total number of park users, categorized by age group (≤20 years vs ≥21 years), sex, and physical activity level (sitting or standing vs walking or vigorous activity). Changes in outcomes between groups were compared via the generalized estimation equation. Results: A total of 28 322 park users were observed across 1458 scans. At baseline, 6343 of 10 633 users (59.7%) were 20 years or younger, 4927 of 10 632 (46.3%) were female and 5705 (53.7%) were male, and 4641 of 10 605 (43.8%) were sitting or standing. Intervention parks showed more net park users compared with control parks from baseline to the final follow-up (difference-in-difference relative rate ratio, 1.69 [95% CI, 1.22-2.35] users/scan; P = .002). The association was driven by a significant increase in adult users at intervention parks and overall decrease in all users at control parks. Park users engaging in sitting or standing at intervention parks increased (difference, 4.68 [95% CI, 1.71-7.62] users/scan; P = .002) and park users engaging in walking or vigorous physical activity at control parks decreased (difference, -7.30 [95% CI, -10.80 to -4.26] users/scan; P < .001) over time. Conclusions and Relevance: In this quality improvement study, park redesign and renovation were positively associated with park use in low-income neighborhoods. However, park renovations may need to be accompanied by other programmatic strategies to increase physical activity.

State-Level Firearm Laws and Firearm Homicide in US Cities: Heterogenous Associations by City Characteristics.

Despite well-studied associations of state firearm laws with lower state- and county-level firearm homicide, there is a shortage of studies investigating differences in the effects of distinct state firearm law categories on various cities within the same state using identical methods. We examined associations of 5 categories of state firearm laws-pertaining to buyers, dealers, domestic violence, gun type/trafficking, and possession-with city-level firearm homicide, and then tested differential associations by city characteristics. City-level panel data on firearm homicide cases of 78 major cities from 2010 to 2020 was assessed from the Centers for Disease Control and Prevention's National Vital Statistics System. We modeled log-transformed firearm homicide rates as a function of firearm law scores, city, state, and year fixed effects, along with time-varying city-level confounders. We considered effect measure modification by poverty, unemployment, vacant housing, and income inequality. A one z-score increase in state gun type/trafficking, possession, and dealer law scores was associated with 25% (95% confidence interval [CI]:-0.37,-0.1), 19% (95% CI:-0.29,-0.07), and 17% (95% CI:-0.28, -0.4) lower firearm homicide rates, respectively. Protective associations were less pronounced in cities with high unemployment and high housing vacancy, but more pronounced in cities with high income inequality. In large US cities, state-level gun type/trafficking, possession, and dealer laws were associated with lower firearm homicide rates, but buyers and domestic violence laws were not. State firearm laws may have differential effects on firearm homicides based on city characteristics, and city-wide policies to enhance socioeconomic drivers may add benefits of firearm laws.

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.

Beyond traffic jam alleviation: evaluating the health and health equity impacts of New York City's congestion pricing plan.

New York City (NYC) is slated to be the first jurisdiction in the USA to implement a cordon-based congestion tax, which will be levied on vehicles entering its Central Business District. Several cities around the world, for example, London and Stockholm, have had similar cordon-based pricing programmes, defined as road pricing that charges drivers a fee for entering a specified area (typically a congested urban centre). In addition to reducing congestion and creating revenue, projections suggest the NYC congestion pricing plan may yield meaningful traffic-related air quality improvements that could result in health benefits. NYC is a large city with high air pollution and substantial racial/ethnic and socioeconomic health inequities. The distinct geography and meteorological conditions of the city also suggest that the policy's impact on air quality may extend beyond the NYC metropolitan area. As such, the potential breadth, directionality and magnitude of health impacts on communities who might be heavily affected by the nation's first congestion pricing plan should be empirically investigated. We briefly review evaluation studies of other cordon-based congestion pricing policies and argue that implementation of this policy provides an excellent opportunity to employ a quasi-experimental study design to evaluate the policy's impacts on air quality and health outcomes across population subgroups using a health equity lens. We discuss why real-time evaluations of the NYC congestion pricing plan can potentially help optimise benefits for communities historically negatively affected by traffic-related air pollution. Assessing intended and unintended impacts on health equity is key to achieving these goals.

Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network.

INTRODUCTION: Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved. METHODS AND ANALYSIS: The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0-17 years only (component A), three centres conduct surveillance in young adults aged 18-44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression. ETHICS AND DISSEMINATION: The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.

Associations between a Novel Measure of Census Tract-Level Credit Insecurity and Frequent Mental Distress in US Urban Areas, 2020.

Access to and utilization of consumer credit remains an understudied social determinant of health. We examined associations between a novel, small-area, multidimensional credit insecurity index (CII), and the prevalence of self-reported frequent mental distress across US cities in 2020. The census tract-level CII was developed by the Federal Reserve Bank of New York using Census population information and a nationally representative sample of anonymized Equifax credit report data. The CII was calculated for tracts in 766 cities displayed on the City Health Dashboard at the time of analysis, predominantly representing cities with over 50,000 residents. The CII combined data on tract-level participation in the formal credit economy with information on the percent of individuals without revolving credit, percent with high credit utilization, and percent with deep subprime credit scores. Tracts were classified as credit-assured, credit-likely, mid-tier, at-risk, or credit-insecure. We used linear regression to examine associations between the CII and a modeled tract-level measure of frequent mental distress, obtained from the CDC PLACES project. Regression models were adjusted for neighborhood economic and demographic characteristics. We examined effect modification by US region by including two-way interaction terms in regression models. In adjusted models, credit-insecure tracts had a modestly higher prevalence of frequent mental distress (prevalence difference = 0.38 percentage points; 95% CI = 0.32, 0.44), compared to credit-assured tracts. Associations were most pronounced in the Midwest. Local factors impacting credit access and utilization are often modifiable. The CII, a novel indicator of community financial well-being, may be an independent predictor of neighborhood health in US cities and could illuminate policy targets to improve access to desirable credit products and downstream health outcomes.

Age and sex differences in the association between neighborhood socioeconomic environment and incident diabetes: Results from the diabetes location, environmental attributes and disparities (LEAD) network.

Objective: Worse neighborhood socioeconomic environment (NSEE) may contribute to an increased risk of type 2 diabetes (T2D). We examined whether the relationship between NSEE and T2D differs by sex and age in three study populations. Research design and methods: We conducted a harmonized analysis using data from three independent longitudinal study samples in the US: 1) the Veteran Administration Diabetes Risk (VADR) cohort, 2) the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, and 3) a case-control study of Geisinger electronic health records in Pennsylvania. We measured NSEE with a z-score sum of six census tract indicators within strata of community type (higher density urban, lower density urban, suburban/small town, and rural). Community type-stratified models evaluated the likelihood of new diagnoses of T2D in each study sample using restricted cubic splines and quartiles of NSEE. Results: Across study samples, worse NSEE was associated with higher risk of T2D. We observed significant effect modification by sex and age, though evidence of effect modification varied by site and community type. Largely, stronger associations between worse NSEE and diabetes risk were found among women relative to men and among those less than age 45 in the VADR cohort. Similar modification by age group results were observed in the Geisinger sample in small town/suburban communities only and similar modification by sex was observed in REGARDS in lower density urban communities. Conclusions: The impact of NSEE on T2D risk may differ for males and females and by age group within different community types.

Long-Term Exposure to Walkable Residential Neighborhoods and Risk of Obesity-Related Cancer in the New York University Women's Health Study (NYUWHS).

BACKGROUND: Living in neighborhoods with higher levels of walkability has been associated with a reduced risk of obesity and higher levels of physical activity. Obesity has been linked to increased risk of 13 cancers in women. However, long-term prospective studies of neighborhood walkability and risk for obesity-related cancer are scarce. OBJECTIVES: We evaluated the association between long-term average neighborhood walkability and obesity-related cancer risk in women. METHODS: The New York University Women's Health Study (NYUWHS) is a prospective cohort with 14,274 women recruited between 1985 and 1991 in New York City and followed over nearly three decades. We geocoded residential addresses for each participant throughout follow-up and calculated an average annual measure of neighborhood walkability across years of follow-up using data on population density and accessibility to destinations associated with geocoded residential addresses. We used ICD-9 codes to characterize first primary obesity-related cancers and employed Cox proportional hazards models to assess the association between average neighborhood walkability and risk of overall and site-specific obesity-related cancers. RESULTS: Residing in neighborhoods with a higher walkability level was associated with a reduced risk of overall and site-specific obesity-related cancers. The hazards ratios associated with a 1-standard deviation increase in average annual neighborhood walkability were 0.88 (95% CI: 0.85, 0.93) for overall obesity-related cancer, 0.89 (95% CI: 0.84, 0.95) for postmenopausal breast cancer, 0.82 (95% CI: 0.68, 0.99) for ovarian cancer, 0.87 (95% CI: 0.76, 0.99) for endometrial cancer, and 0.68 (95% CI: 0.49, 0.94) for multiple myeloma, adjusting for potential confounders at both the individual and neighborhood level. The association between neighborhood walkability and risk of overall obesity-related cancer was stronger among women living in neighborhoods with higher levels of poverty compared with women living in areas with lower poverty levels (pInteraction=0.006). DISCUSSION: Our study highlights a potential protective role of neighborhood walkability in preventing obesity-related cancers in women. https://doi.org/10.1289/EHP11538.

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.

Validation of a geospatial aggregation method for congressional districts and other US administrative geographies.

Stakeholders need data on health and drivers of health parsed to the boundaries of essential policy-relevant geographies. US Congressional Districts are an example of a policy-relevant geography which generally lack health data. One strategy to generate Congressional District heath data metric estimates is to aggregate estimates from other geographies, for example, from counties or census tracts to Congressional Districts. Doing so requires several methodological decisions. We refine a method to aggregate health metric estimates from one geography to another, using a population weighted approach. The method's accuracy is evaluated by comparing three aggregated metric estimates to metric estimates from the US Census American Community Survey for the same years: Broadband Access, High School Completion, and Unemployment. We then conducted four sensitivity analyses testing: the effect of aggregating counts vs. percentages; impacts of component geography size and data missingness; and extent of population overlap between component and target geographies. Aggregated estimates were very similar to estimates for identical metrics drawn directly from the data source. Sensitivity analyses suggest the following best practices for Congressional district-based metrics: utilizing smaller, more plentiful geographies like census tracts as opposed to larger, less plentiful geographies like counties, despite potential for less stable estimates in smaller geographies; favoring geographies with higher percentage population overlap.

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.

Assessing the association between food environment and dietary inflammation by community type: a cross-sectional REGARDS study.

BACKGROUND: Communities in the United States (US) exist on a continuum of urbanicity, which may inform how individuals interact with their food environment, and thus modify the relationship between food access and dietary behaviors. OBJECTIVE: This cross-sectional study aims to examine the modifying effect of community type in the association between the relative availability of food outlets and dietary inflammation across the US. METHODS: Using baseline data from the REasons for Geographic and Racial Differences in Stroke study (2003-2007), we calculated participants' dietary inflammation score (DIS). Higher DIS indicates greater pro-inflammatory exposure. We defined our exposures as the relative availability of supermarkets and fast-food restaurants (percentage of food outlet type out of all food stores or restaurants, respectively) using street-network buffers around the population-weighted centroid of each participant's census tract. We used 1-, 2-, 6-, and 10-mile (~ 2-, 3-, 10-, and 16 km) buffer sizes for higher density urban, lower density urban, suburban/small town, and rural community types, respectively. Using generalized estimating equations, we estimated the association between relative food outlet availability and DIS, controlling for individual and neighborhood socio-demographics and total food outlets. The percentage of supermarkets and fast-food restaurants were modeled together. RESULTS: Participants (n = 20,322) were distributed across all community types: higher density urban (16.7%), lower density urban (39.8%), suburban/small town (19.3%), and rural (24.2%). Across all community types, mean DIS was - 0.004 (SD = 2.5; min = - 14.2, max = 9.9). DIS was associated with relative availability of fast-food restaurants, but not supermarkets. Association between fast-food restaurants and DIS varied by community type (P for interaction = 0.02). Increases in the relative availability of fast-food restaurants were associated with higher DIS in suburban/small towns and lower density urban areas (p-values < 0.01); no significant associations were present in higher density urban or rural areas. CONCLUSIONS: The relative availability of fast-food restaurants was associated with higher DIS among participants residing in suburban/small town and lower density urban community types, suggesting that these communities might benefit most from interventions and policies that either promote restaurant diversity or expand healthier food options.

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.

Alignment of Ending the HIV Epidemic Priority Jurisdictions With Availability of HIV Service Organizations: An Ecological Study.

We sought to describe and quantify the association between HIV service organization availability, HIV burden, and HIV awareness and prevention in the 57 priority jurisdictions selected as part of the U.S. Ending the HIV Epidemic initiative. On average, jurisdictions with more per capita organizations had more people living with HIV, more individuals aware of their positive status, and more individuals prescribed PrEP (b = 0.3; 95% CI [0.2, 0.5] for each additional case per 1,000 people in the first metric, and b = 0.3; 95% CI [0.2, 0.4] and b = 0.1; 95% CI [< 0.1, 0.1], respectively, for each percentage point change in the second two metrics), accounting for jurisdiction size. Several jurisdictions were outliers in the modeled associations and may reflect comparatively better, or worse, performance than similar jurisdictions. This information can assist in evaluating resource allocation and determining whether availability translates to accessibility.

Establishing the criterion validity of an adapted dietary screener for Asian Americans amongst Chinese American adults.

OBJECTIVE: To assess the criterion validity of a dietary screener questionnaire adapted for Asian Americans (ADSQ) compared to Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA-24) food diary data amongst Chinese American Adults (CHAs). The ADSQ incorporated example ethnic foods from six Asian American groups. Lessons learned with respect to translating the ADSQ from English into Simplified Chinese were also documented. DESIGN: Agreement between a two-day food diary (one weekend day and one weekday) and the ADSQ was assessed for vegetable, fruit, dairy, added sugar, fiber, calcium, and whole grain intake using paired t-tests to compare means and Spearman correlations to assess agreement between intake of food components. SETTING: Data were collected online and via phone interviews. PARTICIPANTS: Thirty-three CHAs aged 19-62 years (63.6% female). RESULTS: Mean differences were small for fruit, dairy, fiber, calcium, and whole grain intake, but were significantly different for vegetables and added sugar intake. Spearman correlations were < 0.5 and non-significant (p > 0.05) for all components. Both the ASA-24 and the ADSQ identified the same categories where CHAs intake is misaligned with dietary recommendations: whole grains, total fruit, and dairy. Difficulties were encountered in translating 13 out of 26 questions. CONCLUSIONS: The ADSQ may be a useful tool to identify intervention targets for improving dietary quality, but caution is warranted when interpreting vegetable and added sugar estimates. Differences in the English and Chinese languages underscore the need to take into account both literal translations and semantics in translating the ADSQ into other languages.

Relative validity of a Diet Risk Score (DRS) for Chinese American adults.

Objective: The objective of this study was to evaluate the relative validity of the nine-item Diet Risk Score (DRS) among Chinese American adults using Healthy Eating Index (HEI)-2015 scores. We provide insights into the application of the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) for this population, and report on lessons learned from carrying out participant recruitment during the COVID-19 pandemic. Methods: Thirty-three Chinese American adults (mean age=40; 36% male) were recruited from the community and through ResearchMatch. Participants completed the DRS and two 24-hour food records, which were entered into the ASA 24-Hour Dietary Assessment Tool (ASA24) by community health workers (CHWs). HEI-2015 scores were calculated from each food record and an average score was obtained for each participant. One-way analysis of variance and Spearman correlations were used to compare total and component scores between the DRS and HEI-2015. Results: Mean HEI-2015 score was 56.7/100 (SD 10.6) and mean DRS score was 11.8/27 (SD 4.7), with higher scores reflecting better and worse diets, respectively. HEI-2015 and DRS scores were inversely correlated (r=-0.43, p<0.05). The strongest correlations were between HEI-2015 Total Vegetables and DRS Vegetables (r=-0.5, p<0.01), HEI-2015 Total Vegetables and Green Vegetables (r=-0.43, p=0.01) and HEI-2015 Seafood/Plant Protein and DRS Fish (r=-0.47, p<0.01). The inability to advertise and recruit for the study in person at community centres due to pandemic restrictions impeded the recruitment of less-acculturated individuals. A lack of cultural food items in the ASA24 database made it difficult to record dietary intake as reported by participants. Conclusion: The DRS can be a valuable tool for physicians to identify and reach Chinese Americans at risk of cardiometabolic disease.

Risk of post-acute sequelae of SARS-CoV-2 infection associated with pre-coronavirus disease obstructive sleep apnea diagnoses: an electronic health record-based analysis from the RECOVER initiative.

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) has been associated with more severe acute coronavirus disease-2019 (COVID-19) outcomes. We assessed OSA as a potential risk factor for Post-Acute Sequelae of SARS-CoV-2 (PASC). METHODS: We assessed the impact of preexisting OSA on the risk for probable PASC in adults and children using electronic health record data from multiple research networks. Three research networks within the REsearching COVID to Enhance Recovery initiative (PCORnet Adult, PCORnet Pediatric, and the National COVID Cohort Collaborative [N3C]) employed a harmonized analytic approach to examine the risk of probable PASC in COVID-19-positive patients with and without a diagnosis of OSA prior to pandemic onset. Unadjusted odds ratios (ORs) were calculated as well as ORs adjusted for age group, sex, race/ethnicity, hospitalization status, obesity, and preexisting comorbidities. RESULTS: Across networks, the unadjusted OR for probable PASC associated with a preexisting OSA diagnosis in adults and children ranged from 1.41 to 3.93. Adjusted analyses found an attenuated association that remained significant among adults only. Multiple sensitivity analyses with expanded inclusion criteria and covariates yielded results consistent with the primary analysis. CONCLUSIONS: Adults with preexisting OSA were found to have significantly elevated odds of probable PASC. This finding was consistent across data sources, approaches for identifying COVID-19-positive patients, and definitions of PASC. Patients with OSA may be at elevated risk for PASC after SARS-CoV-2 infection and should be monitored for post-acute sequelae.

Life Expectancy and Built Environments in the U.S.: A Multilevel Analysis.

INTRODUCTION: The purpose of this study is to examine the associations between built environments and life expectancy across a gradient of urbanicity in the U.S. METHODS: Census tract‒level estimates of life expectancy between 2010 and 2015, except for Maine and Wisconsin, from the U.S. Small-Area Life Expectancy Estimates Project were analyzed in 2022. Tract-level measures of the built environment included: food, alcohol, and tobacco outlets; walkability; park and green space; housing characteristics; and air pollution. Multilevel linear models for each of the 4 urbanicity types were fitted to evaluate the associations, adjusting for population and social characteristics. RESULTS: Old housing (built before 1979) and air pollution were important built environment predictors of life expectancy disparities across all gradients of urbanicity. Convenience stores were negatively associated with life expectancy in all urbanicity types. Healthy food options were a positive predictor of life expectancy only in high-density urban areas. Park accessibility was associated with increased life expectancy in all areas, except rural areas. Green space in neighborhoods was positively associated with life expectancy in urban areas but showed an opposite association in rural areas. CONCLUSIONS: After adjusting for key social characteristics, several built environment characteristics were salient risk factors for decreased life expectancy in the U.S., with some measures showing differential effects by urbanicity. Planning and policy efforts should be tailored to local contexts.

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.