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Abstract Background Despite the potential for community health worker (CHW)-led programs to improve the health of people with justice involvement (PWJI), little is known about the practical implementation of such models. We explored barriers and facilitators to implementation of a municipal CHW program, the Health Justice Network (NYC HJN), led by the New York City Department of Health and Mental Hygiene (DOHMH) in partnership with three reentry-focused community-based organizations (CBOs) and three federally qualified health centers (FQHCs) that was designed to serve the health and social service needs of PWJI. Methods Eighteen in-depth qualitative interviews were conducted with a purposive sample of CHWs, partner site supervisors, and DOHMH staff. Interviews were conducted virtually and transcribed verbatim. Codes and themes were developed using the Consolidated Framework for Implementation Research (CFIR) to understand facilitators and barriers to NYC HJN implementation. Results Important facilitators to implementation included: lived experience of CHWs, as well as NYC HJN’s voluntary nature, lack of onerous eligibility criteria, and prioritization of participant needs. One barrier was the lack of a formal implementation protocol. Themes identified as facilitators in some instances and barriers in others were CHW integration into site partners, the expansive scope of work for CHWs, the integration of a trauma-informed approach, values alignment and existing infrastructure, leadership engagement, CHW training and support, and input, feedback, and communication. Conclusions Findings will help inform how to successfully implement future CHW-led interventions for PWJI with municipal, health, and social service partners.

Abstract Background New York City (NYC) was the first COVID-19 epicenter in the United States and home to one of the country’s largest contact tracing programs, NYC Test & Trace (T2). Understanding points of attrition along the stages of program implementation and follow-up can inform contact tracing efforts for future epidemics or pandemics. The objective of this study was to evaluate the completeness and timeliness of T2 case and contact notification and monitoring using a “cascade of care” approach. Methods This cross-sectional study included all SARS-CoV-2 cases and contacts reported to T2 from May 31, 2020 to January 1, 2022. Attrition along the “cascade of care” was defined as: (1) attempted, (2) reached, (3) completed intake (main outcome), (4) eligible for monitoring, and (5) successfully monitored. Timeliness was assessed: (1) by median days from a case’s date of testing until their positive result was reported to T2, (2) from result until the case was notified by T2, and (3) from a case report of a contact until notification of the contact. Results A total of 1.45 million cases and 1.38 million contacts were reported to T2 during this period. For cases, attrition occurred evenly across the first three cascade steps (~-12%) and did not change substantially until the Omicron wave in December 2021. During the Omicron wave, the proportion of cases attempted dropped precipitously. For contacts, the largest attrition occurred between attempting and reaching (-27%), and attrition rose with each COVID-19 wave as contact volumes increased. Attempts to reach contacts discontinued entirely during the Omicron wave. Overall, 67% of cases and 49% of contacts completed intake interviews (79% and 57% prior to Omicron). T2 was timely, with a median of 1 day to receive lab results, 2 days to notify cases, and

ABSTRACT Severe COVID-19 has been associated with coinfections with bacterial and fungal pathogens. Notably, patients with COVID-19 who develop Staphylococcus aureus bacteremia exhibit higher rates of mortality than those infected with either pathogen alone. To understand this clinical scenario, we collected and examined S. aureus blood and respiratory isolates from a hospital in New York City during the early phase of the pandemic from both SARS-CoV-2+ and SARS-CoV-2− patients. Whole genome sequencing of these S. aureus isolates revealed broad phylogenetic diversity in both patient groups, suggesting that SARS-CoV-2 coinfection was not associated with a particular S. aureus lineage. Phenotypic characterization of the contemporary collection of S. aureus isolates from SARS-CoV-2+ and SARS-CoV-2− patients revealed no notable differences in several virulence traits examined. However, we noted a trend toward overrepresentation of S. aureus bloodstream strains with low cytotoxicity in the SARS-CoV-2+ group. We observed that patients coinfected with SARS-CoV-2 and S. aureus were more likely to die during the acute phase of infection when the coinfecting S. aureus strain exhibited high or low cytotoxicity. To further investigate the relationship between SARS-CoV-2 and S. aureus infections, we developed a murine coinfection model. These studies revealed that infection with SARS-CoV-2 renders mice susceptible to subsequent superinfection with low cytotoxicity S. aureus. Thus, SARS-CoV-2 infection sensitizes the host to coinfections, including S. aureus isolates with low intrinsic virulence.IMPORTANCEThe COVID-19 pandemic has had an enormous impact on healthcare across the globe. Patients who were severely infected with SARS-CoV-2, the virus causing COVID-19, sometimes became infected with other pathogens, which is termed coinfection. If the coinfecting pathogen is the bacterium Staphylococcus aureus, there is an increased risk of patient death. We collected S. aureus strains that coinfected patients with SARS-CoV-2 to study the disease outcome caused by the interaction of these two important pathogens. We found that both in patients and in mice, coinfection with an S. aureus strain lacking toxicity resulted in more severe disease during the early phase of infection, compared with infection with either pathogen alone. Thus, SARS-CoV-2 infection can directly increase the severity of S. aureus infection.

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.

Abstract 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

Abstract 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 0.05) 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.

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.

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.

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.

Abstract 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.

Here, the authors show that SARS-CoV-2 infection causes gut microbiome dysbiosis and gut epithelial cell alterations in a mouse model, and correlate dysbiosis observed in COVID-19 patients with blood stream infections, matching reads of bacterial sequences from stool samples to organisms found in the blood.

Abstract Previous studies have explored using calibrated low-cost particulate matter (PM) sensors, but important research gaps remain regarding long-term performance and reliability. Evaluate longitudinal performance of low-cost particle sensors by measuring sensor performance changes over 2 years of use. 51 low-cost particle sensors (Airbeam 1 N = 29; Airbeam 2 N = 22) were calibrated four times over a 2-year timeframe between 2019 and 2021. Cigarette smoke-specific calibration curves for Airbeam 1 and 2 PM sensors were created by directly comparing simultaneous 1-min readings of a Thermo Scientific Personal DataRAM PDR-1500 unit with a 2.5 µm inlet. Inter-sensor variability in calibration coefficient was high, particularly in Airbeam 1 sensors at study initiation. Calibration coefficients for both sensor types trended downwards over time to

Abstract Introduction State cancer prevention and control programs rely on public health surveillance data to set objectives to improve cancer prevention and control, plan interventions, and evaluate state-level progress towards achieving those objectives. The goal of this project was to evaluate the validity of using electronic health records (EHRs) based on common data model variables to generate indicators for surveillance of cancer prevention and control for these public health programs. Methods Following the methodological guidance from the PRISMA Extension for Scoping Reviews, we conducted a literature scoping review to assess how EHRs are used to inform cancer surveillance. We then developed 26 indicators along the continuum of the cascade of care, including cancer risk factors, immunizations to prevent cancer, cancer screenings, quality of initial care after abnormal screening results, and cancer burden. Indicators were calculated within a sample of patients from the New York City (NYC) INSIGHT Clinical Research Network using common data model EHR data and were weighted to the NYC population using post-stratification. We used prevalence ratios to compare these estimates to estimates from the raw EHR of NYU Langone Health to assess quality of information within INSIGHT, and we compared estimates to results from existing surveillance sources to assess validity. Results Of the 401 identified articles, 15% had a study purpose related to surveillance. Our indicator comparisons found that INSIGHT EHR-based measures for risk factor indicators were similar to estimates from external sources. In contrast, cancer screening and vaccination indicators were substantially underestimated as compared to estimates from external sources. Cancer screenings and vaccinations were often recorded in sections of the EHR that were not captured by the common data model. INSIGHT estimates for many quality-of-care indicators were higher than those calculated using a raw EHR. Conclusion Common data model EHR data can provide rich information for certain indicators related to the cascade of care but may have substantial biases for others that limit their use in informing surveillance efforts for cancer prevention and control programs.

IntroductionThe literature is limited on the impact of neighborhood parks on quality of life (QoL) and the mechanism linking them.MethodsIn this paper, we applied the structural equation model to data from a cross-sectional sample of 650 participants in low-income communities of New York City, we examined the associations of neighborhood park use vs. park perception and QoL, and whether these associations were mediated through self-reported perceived stress. We also examined whether park use mediated the relationship between park perception and QoL.ResultsWe found that park use had a significant but weak association with QoL (standardized β = 0.08, 95% confidence interval (CI): 0.02, 0.15, p = 0.02), but this relationship was not mediated by self-reported stress. Park perception was more strongly associated with QoL than park use (standardized β = 0.23, 95% CI: 0.16, 0.30, p < 0.01), and this was partly mediated by self-reported stress (indirect effect- standardized β = 0.08, 95% CI: 0.03, 0.13, p < 0.01) and, to a lesser extent, by park use (indirect effect- standardized β = 0.01, 95% CI: 0.00, 0.02, p = 0.01).DiscussionHaving well-perceived parks appears to be an important factor for QoL independent of park use, suggesting that quality parks may benefit everyone in a community beyond park users. This strengthens the argument in favor of increasing park investment as a strategy to improve population wellbeing.

Background African American and Hispanic populations have been affected disproportionately by COVID-19. Reasons are multifactorial and include social and structural determinants of health. During the onset and height of the pandemic, evidence suggested decreased access to SARS CoV-2 testing. In 2020, the National Institutes of Health launched the Rapid Acceleration of Diagnostics (RADx)- Underserved Populations initiative to improve SARS CoV-2 testing in underserved communities. In this study, we explored attitudes, experiences, and barriers to SARS CoV-2 testing and vaccination among New York City public housing residents. Methods Between December 2020 and March 2021, we conducted 9 virtual focus groups among 36 low-income minority residents living in New York City public housing. Results Among residents reporting a prior SARS CoV-2 test, main reasons for testing were to prepare for a medical procedure or because of a high-risk exposure. Barriers to testing included fear of discomfort from the nasal swab, fear of exposure to COVID-19 while traveling to get tested, concerns about the consequences of testing positive and the belief that testing was not necessary. Residents reported a mistrust of information sources and the health care system in general; they depended more on “word of mouth” for information. The major barrier to vaccination was lack of trust in vaccine safety. Residents endorsed more convenient testing, onsite testing at residential buildings, and home self-test kits. Residents also emphasized the need for language-concordant information sharing and for information to come from “people who look like [them] and come from the same background as [them]”. Conclusions Barriers to SARS CoV-2 testing and vaccination centered on themes of a lack of accurate information, fear, mistrust, safety, and convenience. Resident-endorsed strategies to increase testing include making testing easier to access either through home or onsite testing locations. Education and information sharing by trusted members of the community are important tools to combat misinformation and build trust.

Summary: Background: Stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested. Methods: We present a method for computationally modelling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning. Findings: We found six clusters of PASC patients, each with distinct profiles of phenotypic abnormalities, including clusters with distinct pulmonary, neuropsychiatric, and cardiovascular abnormalities, and a cluster associated with broad, severe manifestations and increased mortality. There was significant association of cluster membership with a range of pre-existing conditions and measures of severity during acute COVID-19. We assigned new patients from other healthcare centres to clusters by maximum semantic similarity to the original patients, and showed that the clusters were generalisable across different hospital systems. The increased mortality rate originally identified in one cluster was consistently observed in patients assigned to that cluster in other hospital systems. Interpretation: Semantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC. Funding: NIH (TR002306/OT2HL161847-01/OD011883/HG010860), U.S.D.O.E. (DE-AC02-05CH11231), Donald A. Roux Family Fund at Jackson Laboratory, Marsico Family at CU Anschutz.

Abstract Background Diabetes and hypertension disparities are pronounced among South Asians. There is regional variation in the prevalence of diabetes and hypertension in the US, but it is unknown whether there is variation among South Asians living in the US. The objective of this study was to compare the burden of diabetes and hypertension between South Asian patients receiving care in the health systems of two US cities. Methods Cross-sectional analyses were performed using electronic health records (EHR) for 90,137 South Asians receiving care at New York University Langone in New York City (NYC) and 28,868 South Asians receiving care at Emory University (Atlanta). Diabetes was defined as having 2 + encounters with a diagnosis of diabetes, having a diabetes medication prescribed (excluding Acarbose/Metformin), or having 2 + abnormal A1C levels (≥ 6.5%) and 1 + encounter with a diagnosis of diabetes. Hypertension was defined as having 3 + BP readings of systolic BP ≥ 130 mmHg or diastolic BP ≥ 80 mmHg, 2 + encounters with a diagnosis of hypertension, or having an anti-hypertensive medication prescribed. Results Among South Asian patients at these two large, private health systems, age-adjusted diabetes burden was 10.7% in NYC compared to 6.7% in Atlanta. Age-adjusted hypertension burden was 20.9% in NYC compared to 24.7% in Atlanta. In Atlanta, 75.6% of those with diabetes had comorbid hypertension compared to 46.2% in NYC. Conclusions These findings suggest differences by region and sex in diabetes and hypertension risk. Additionally, these results call for better characterization of race/ethnicity in EHRs to identify ethnic subgroup variation, as well as intervention studies to reduce lifestyle exposures that underlie the elevated risk for type 2 diabetes and hypertension development in South Asians.

Introduction: Geographic disparities in diabetes burden exist throughout the United States (US), with many risk factors for diabetes clustering at a community or neighborhood level. We hypothesized that the likelihood of new onset type 2 diabetes (T2D) would differ by community type in three large study samples covering the US. Research design and methods: We evaluated the likelihood of new onset T2D by a census tract-level measure of community type, a modification of RUCA designations (higher density urban, lower density urban, suburban/small town, and rural) in three longitudinal US study samples (REGARDS [REasons for Geographic and Racial Differences in Stroke] cohort, VADR [Veterans Affairs Diabetes Risk] cohort, Geisinger electronic health records) representing the CDC Diabetes LEAD (Location, Environmental Attributes, and Disparities) Network. Results: In the REGARDS sample, residing in higher density urban community types was associated with the lowest odds of new onset T2D (OR [95% CI]: 0.80 [0.66, 0.97]) compared to rural community types; in the Geisinger sample, residing in higher density urban community types was associated with the highest odds of new onset T2D (OR [95% CI]: 1.20 [1.06, 1.35]) compared to rural community types. In the VADR sample, suburban/small town community types had the lowest hazard ratios of new onset T2D (HR [95% CI]: 0.99 [0.98, 1.00]). However, in a regional stratified analysis of the VADR sample, the likelihood of new onset T2D was consistent with findings in the REGARDS and Geisinger samples, with highest likelihood of T2D in the rural South and in the higher density urban communities of the Northeast and West regions; likelihood of T2D did not differ by community type in the Midwest. Conclusions: The likelihood of new onset T2D by community type varied by region of the US. In the South, the likelihood of new onset T2D was higher among those residing in rural communities.

Abstract Objective COVID‐19 has changed diet and food shopping behaviors, but a lack of disaggregated data by racial and ethnic subgroup makes it challenging to identify whether specific populations are experiencing greater challenges in safely securing an adequate food supply and engaging in healthy eating behaviors during the pandemic. Thus, the objective of this study was to measure such changes among Asian–American (AA) adults, overall and by ethnic subgroup. Methods Using a nationally derived nonprobability sample, 3084 AA adults were recruited, including 1737 East Asian, 570 South Asian, 587 Southeast Asian, and 124 multiethnic Asian adults. Participants completed an online survey with questions related to sociodemographics, health status, and diet and food shopping behaviors, including questions related to COVID‐19. Logistic and linear regression were used to compare differences in survey responses by Asian ethnic subgroup. Results Compared to other AA subgroups, a higher percentage of Asian Indian (17%), Filipino (13%), Vietnamese (12%), and Korean (11%) adults reported no longer getting food resources they were receiving before COVID‐19 (e.g., mobile meals, food pantry items). The percentage of Filipino (8%) and Vietnamese (7%) adults who reported not having enough money to buy food they need was also higher than other AA subgroups. And a higher percentage of Asian Indian adults (7%) reported not having a way to get to the food store since COVID‐19 than other AA subgroups. Conclusions Previous work has not included disaggregated data, which may mask important disparities in food access and food insecurity among people hit hardest by COVID‐19, such as Filipino, Vietnamese, and Asian Indian households.

Secondhand tobacco smoke (SHS) exposure has declined due to smoking reductions, expanding workplace and public smoke-free air laws, and smoke-free housing policy promotion. Population-based studies examining objective SHS exposure biomarkers have documented reductions over time, however non-smoking urban adults are more likely to have elevated cotinine (a metabolite of nicotine) compared with national averages. Evidence suggests residential housing type may impact urban SHS exposure risk. Direct associations between multiunit housing (MUH) and elevated cotinine have been identified among children but not yet examined among adults. We used data from the cross-sectional 2004 and 2013/14 New York City Health and Nutrition Examination Surveys to investigate associations between MUH (single-family versus 2; 3–99; and 100 + units) and likelihood of elevated serum cotinine among nonsmoking adults (2004: n = 1324; 2013/14: n = 946), adjusting for socio-demographics (sex, age, race/ethnicity, education, income) and self-reported SHS exposure variables. Combined and single-year adjusted multivariable regressions were conducted. Elevated cotinine was defined as a serum level of ≥ 0.05 ng/ml. Combined year adjusted multivariable regression analyses found no difference in elevated cotinine by housing type among non-smoking adults. By survey year, elevated cotinine did not vary by housing type in 2004, while non-smoking adults in 3–99 unit buildings were twice as likely to have elevated cotinine compared with single family residents in 2013/14 (adjusted Odds Ratio = 2.55 (1.13, 5.79)). While SHS exposure has declined, relative burden may be increasing among MUH residents. In urban settings with extensive MUH, attention to housing-based policies and programmatic interventions is critical to reducing SHS exposure.

Small primary care practices are critical to advancing Affordable Care Act (ACA) aims, yet their efforts and experiences remain little studied. We examine two strategies derived from ACA population-health provisions—enhanced use of electronic health records (EHRs) and community health worker (CHW)–led peer coaching—for hypertension control in sixteen small practices serving South Asian immigrant communities in New York City. Based on interviews with physicians, staff, and CHWs, we analyze “street-level” dilemmas encountered in implementing the strategies. Findings indicate that the strategies reinforce clinic-community social ties but present distinct challenges for small practices: internal management constraints that impede formal CHW-physician contact, and external incentives linked to EHR tools that, physicians and staff perceive, do not meet immigrant communities’ needs and expectations in medical encounters.

Background Post-acute sequelae of COVID-19 (PASC) includes a heterogeneous group of patients with variable symptomatology, who may respond to different therapeutic interventions. Identifying phenotypes of PASC and therapeutic strategies for different subgroups would be a major step forward in management. Methods In a prospective cohort study of patients hospitalized with COVID-19, 12-month symptoms and quantitative outcome metrics were collected. Unsupervised hierarchical cluster analyses were performed to identify patients with: (1) similar symptoms lasting ≥4 weeks after acute SARS-CoV-2 infection, and (2) similar therapeutic interventions. Logistic regression analyses were used to evaluate the association of these symptom and therapy clusters with quantitative 12-month outcome metrics (modified Rankin Scale, Barthel Index, NIH NeuroQoL). Results Among 242 patients, 122 (50%) reported ≥1 PASC symptom (median 3, IQR 1–5) lasting a median of 12-months (range 1–15) post-COVID diagnosis. Cluster analysis generated three symptom groups: Cluster1 had few symptoms (most commonly headache); Cluster2 had many symptoms including high levels of anxiety and depression; and Cluster3 primarily included shortness of breath, headache and cognitive symptoms. Cluster1 received few therapeutic interventions (OR 2.6, 95% CI 1.1–5.9), Cluster2 received several interventions, including antidepressants, anti-anxiety medications and psychological therapy (OR 15.7, 95% CI 4.1–59.7) and Cluster3 primarily received physical and occupational therapy (OR 3.1, 95%CI 1.3–7.1). The most severely affected patients (Symptom Cluster 2) had higher rates of disability (worse modified Rankin scores), worse NeuroQoL measures of anxiety, depression, fatigue and sleep disorder, and a higher number of stressors (all PConclusions We identified three clinically relevant PASC symptom-based phenotypes, which received different therapeutic interventions with varying response rates. These data may be helpful in tailoring individual treatment programs.

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.

Abstract Background Tobacco remains a leading cause of preventable death in the U.S., responsible for more than 440,000 deaths each year. Approximately 10% of these deaths are attributable to exposure of non-smokers to secondhand smoke (SHS). Residents living in public multi-unit housing (MUH) are at excess risk for SHS exposure compared to the general population. On November 30, 2016, the U.S. Department of Housing and Urban Development (HUD) passed a rule requiring all public housing agencies to implement smoke-free housing (SFH) policies in their housing developments by July 30, 2018. Methods As part of a larger natural experiment study, we designed a protocol to evaluate indoor SHS levels before and after policy implementation through collection of repeat indoor air samples in non-smoking apartments and common areas of select high-rise NYCHA buildings subject to the HUD SFH rule, and also from socio-demographically matched private-sector high-rise control buildings not subject to the rule. A baseline telephone survey was conducted in all selected buildings to facilitate rapid recruitment into the longitudinal study and assess smoking prevalence, behaviors, and attitudes regarding the SFH policy prior to implementation. Data collection began in early 2018 and will continue through 2021. Discussion The baseline survey was completed by 559 NYCHA residents and 471 comparison building residents (response rates, 35, and 32%, respectively). Smoking prevalence was comparable between study arms (15.7% among NYCHA residents and 15.2% among comparison residents). The majority of residents reported supporting a building-wide smoke-free policy (63.0 and 59.9%, respectively). We enrolled 157 NYCHA and 118 comparison non-smoking households into the longitudinal air monitoring study and performed air monitoring in common areas. Follow up surveys and air monitoring in participant households occur every 6 months for 2.5 years. Capitalizing on the opportunity of this federal policy rollout, the large and diverse public housing population in NYC, and robust municipal data sources, this study offers a unique opportunity to evaluate the policy’s direct impacts on SHS exposure. Methods in this protocol can inform similar SFH policy evaluations elsewhere.

Physical and social environments of parks and neighborhoods influence park use, but the extent of their relative influence remains unclear. This cross-sectional study examined the relationship between the physical and social environment of parks and both observed and self-reported park use in low-income neighborhoods in New York City. We conducted community- (n = 54 parks) and individual-level (n = 904 residents) analyses. At the community level, observed park use was measured using a validated park audit tool and regressed on the number of facilities and programmed activities in parks, violent crime, stop-and-frisk incidents, and traffic accidents. At the individual level, self-reported park use was regressed on perceived park quality, crime, traffic-related walkability, park use by others, and social cohesion and trust. Data were collected in 2016–2018 and analyzed in 2019–2020. At the community level, observed park use was negatively associated with stop-and-frisk (β = −0.04; SE = 0.02; p < 0.05) and positively associated with the number of park facilities (β = 1.46; SE = 0.57; p < 0.05) and events (β = 0.16; SE = 0.16; p < 0.01). At the individual level, self-reported park use was positively associated with the social cohesion and trust scale (β = 0.02; SE = 0.01; p < 0.05). These results indicate that physical and social attributes of parks, but not perceptions of parks, were significantly associated with park use. The social environment of neighborhoods at both community and individual levels was significantly related to park use. Policies for increasing park use should focus on improving the social environment of parks and surrounding communities, not only parks' physical attributes. These findings can inform urban planning and public health interventions aimed at improving the well-being of residents in low-income communities.

Abstract Background The built environment plays a critical role in promoting physical activity and health. The association between parks, as a key attribute of the built environment, and physical activity, however, remains inconclusive. This project leverages a natural experiment opportunity to assess the impact of the Community Parks Initiative (CPI), a citywide park redesign and renovation effort in New York City, on physical activity, park usage, psychosocial and mental health, and community wellbeing. Methods The project will use a longitudinal design with matched controls. Thirty intervention park neighborhoods are socio-demographically matched to 20 control park neighborhoods. The study will investigate whether improvements in physical activity, park usage, psychosocial and mental health, and community wellbeing are observed from baseline to 3 years post-renovation among residents in intervention vs. control neighborhoods. Discussion This study represents a rare opportunity to provide robust evidence to further our understanding of the complex relationship between parks and health. Findings will inform future investments in health-oriented urban design policies and offer evidence for addressing health disparities through built environment strategies.

Purpose: Capacity to monitor non-communicable diseases (NCDs) at state or local levels is limited. Emerging approaches include using biomeasures and electronic health record (EHR) data. In 2004, New York City (NYC) performed a population-based health study on adult residents using biomeasures (NYC Health and Nutrition Examination Study, or NYC HANES), modeled after NHANES. A second NYC HANES was launched in 2013 to examine change over time, evaluate municipal policies, and validate a proposed EHR-based surveillance system. We describe the rationale and methods of NYC HANES 2013–2014. Methods: NYC HANES was a population-based, cross-sectional survey of NYC adults using three-stage cluster sampling. Between August 2013 and June 2014, selected participants completed a health interview and physical exam (blood pressure, body mass index, and waist circumference). Fasting biomeasures included diabetes, lipid profiles, kidney function, environmental biomarkers, and select infectious diseases. Results: Of the 3065 households approached, 2742 were eligible and 1827 were successfully screened (67%). A total of 1524 of eligible participants completed the survey (54%), for an overall response rate of 36%. Conclusion: Completing a second NYC HANES a decade after the first study affords an opportunity to understand changes in prevalence, awareness and control of NCDs and evaluate municipal efforts to manage them.

In April 1947, during a smallpox outbreak in New York City (NYC), >6,000,000 people were vaccinated. To determine whether vaccination increased cardiac death, we reviewed NYC death certificates for comparable periods in 1946 and 1948 (N = 81,529) and calculated adjusted relative death rates for the postvaccination period. No increases in cardiac deaths were observed.

IntroductionBody mass index (BMI) and indicators of central adiposity have been associated with cardiovascular disease (CVD) risk factors, but ambiguity remains about which measure optimally predicts CVD risk and is best suited for different racial/ethnic groups. We sought to characterize excess adiposity among New York City adults and assess the potential associations between multiple adiposity indicators and CVD risk factors, by race/ethnicity.MethodsThe New York City Health and Nutrition Examination Survey (NYC HANES) is a population-based survey of noninstitutionalized New York City adult residents aged 20 years or older. We compared the prevalence of obesity (BMI ≥30 kg/m2), elevated waist circumference (>102 cm for men, >88 cm for women), and elevated waist-to-height ratio (≥0.5) for participants in the 2004 NYC HANES (n = 1,912) and the 2003-2004 National Health and Nutrition Examination Survey (n = 4,075). Logistic regression was used to assess potential associations between each of these indicators of excess adiposity and CVD risk factors (diabetes, impaired fasting glucose, hypertension, and hypercholesterolemia), overall and by race/ethnicity.ResultsThe prevalence of obesity among NYC HANES participants was 26% and of elevated waist circumference was 46%, both significantly lower than national estimates (31% and 52%, respectively), whereas the prevalence of elevated waist-to-height ratio was higher (82% vs 79%). Most measures of excess adiposity were significantly associated with all CVD risk factors. No single measure of excess adiposity emerged as most consistently predictive of CVD risk in the general population or by race/ethnicity.ConclusionNew York City has a lower prevalence of obesity and elevated waist circumference but a higher prevalence of elevated waist-to-height ratio than found nationally. Further investigation into the optimal adiposity measure to predict CVD risk across racial/ethnic populations may be warranted.

Introduction Colorectal cancer is the second leading cause of cancer death in New York City. In March 2003, the New York City Department of Health and Mental Hygiene recommended colonoscopy every 10 years as the preferred screening test for adults aged 50 years and older in New York City. To screen all eligible adults in New York City would require that approximately 200,000 colonoscopy exams be performed annually. As part of this recommendation, we evaluated current colonoscopy capacity in New York City hospitals. Methods We surveyed endoscopy suite nursing or administrative staff at all 66 adult acute care hospitals performing colonoscopy in New York City. Data on colonoscopy procedures performed in 2002 were collected between February and June 2003. Results All hospitals and two affiliated clinics responded. The number of hospital-based colonoscopy exams performed in 2002 was estimated to be 126,000. Of these, 53,600 (43%) were estimated to be for screening. Hospitals reported their maximum annual capacity to be 195,200, approximately 69,100 more than current practice. Reported barriers to performing more colonoscopy exams included inadequate suite time and space (31%), inadequate staffing (28%), and insufficient patient referrals (24%). Conclusion In 2003, endoscopy suites at New York City hospitals performed approximately one quarter of the estimated citywide need of 200,000 screening colonoscopies. Procedures conducted in outpatient office settings were not assessed. Most endoscopy suites, particularly private hospitals, reported having the capacity to conduct additional procedures. Hospitals and endoscopy suites should prioritize the development of institutional measures to increase the number of persons receiving screening colonoscopy.