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Studies have recently begun to explore the potential long-term health impacts of homeownership policies implemented in the New Deal era. We investigated the association between assigned grades of lending risk by the Home Owners' Load Corporation (HOLC) maps from the 1930s and present-day prevalence of three cardiovascular risk factors (diabetes and obesity in 2020, and hypertension in 2019), estimated at the census tract level in the United States. To minimize potential confounding, we adjusted for sociodemographic data from the time period when HOLC maps were made. We calculated propensity scores (predicted probability of receiving a HOLC grade) and created a pseudo-population using inverse probability weighting. We then employed marginal structural models to estimate prevalence differences comparing A vs. B, B vs. C, and C vs. D HOLC grades. Adjusting only for regions, a less desirable HOLC grade was associated with higher estimated prevalence rates of present-day cardiovascular risk factors; however, most differences were no longer significant after applying propensity score methods. The one exception was that the prevalence of diabetes, hypertension, and obesity were all higher in C vs. B graded census tracts, while no differences were observed for C and D and A and B comparisons. These results contribute to a small body of evidence that suggests historical "yellowlining" (as C grade was in color yellow) may have had persistent impacts on neighborhood-level cardiovascular risk factors 80 years later.
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We characterized comorbidity profiles and cardiometabolic risk factors among older adults with multiple chronic conditions (MCCs) in New York City using an intersectionality approach. Electronic health record data were obtained from the INSIGHT Clinical Research Network on 367,901 New York City residents aged 50 years or older with MCCs. Comorbidity profiles were heterogeneous. The most common profile across sex and racial and ethnic groups was co-occurring hypertension and hyperlipidemia; prevalence of these 2 conditions differed across groups (4.7%-7.3% co-occurrence alone, 65.1%-88.0% with other conditions). Significant sex and racial and ethnic differences were observed, which may reflect accumulated disparities in risk factors and health care access across the life course.
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Afecciones Crónicas Múltiples , Humanos , Ciudad de Nueva York/epidemiología , Masculino , Femenino , Anciano , Persona de Mediana Edad , Afecciones Crónicas Múltiples/epidemiología , Factores de Riesgo , Prevalencia , Hipertensión/epidemiología , Anciano de 80 o más Años , Comorbilidad , Registros Electrónicos de SaludRESUMEN
OBJECTIVE: To perform a detailed characterisation of diabetes burden and pre-diabetes risk in a rural county with previously documented poor health outcomes in order to understand the local within-county distribution of diabetes in rural areas of America. DESIGN, SETTING, AND PARTICIPANTS: In 2021, we prospectively mailed health surveys to all households in Sullivan County, a rural county with the second-worst health outcomes of all counties in New York State. Our survey included questions on demographics, medical history and the American Diabetes Association's Pre-diabetes Risk Test. PRIMARY OUTCOME AND METHODS: Our primary outcome was an assessment of diabetes burden within this rural county. To help mitigate non-response bias in our survey, raking adjustments were performed across strata of age, sex, race/ethnicity and health insurance. We analysed diabetes prevalence by demographic characteristics and used geospatial analysis to assess for clustering of diagnosed diabetes cases. RESULTS: After applying raking procedures for the 4725 survey responses, our adjusted diagnosed diabetes prevalence for Sullivan County was 12.9% compared with the 2019 Behavioural Risk Factor Surveillance System (BRFSS) estimate of 8.6%. In this rural area, diagnosed diabetes prevalence was notably higher among non-Hispanic Black (21%) and Hispanic (15%) residents compared with non-Hispanic White (12%) residents. 53% of respondents without a known history of pre-diabetes or diabetes scored as high risk for pre-diabetes. Nearest neighbour analyses revealed that hotspots of diagnosed diabetes were primarily located in the more densely populated areas of this rural county. CONCLUSIONS: Our mailed health survey to all residents in Sullivan County demonstrated higher diabetes prevalence compared with modelled BRFSS estimates that were based on small telephone samples. Our results suggest the need for better diabetes surveillance in rural communities, which may benefit from interventions specifically tailored for improving glycaemic control among rural residents.
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Diabetes Mellitus , Encuestas Epidemiológicas , Estado Prediabético , Población Rural , Humanos , Masculino , Femenino , New York/epidemiología , Estado Prediabético/epidemiología , Persona de Mediana Edad , Estudios Transversales , Adulto , Población Rural/estadística & datos numéricos , Anciano , Prevalencia , Diabetes Mellitus/epidemiología , Factores de Riesgo , Adulto Joven , AdolescenteRESUMEN
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. IMPORTANCE: The 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.
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COVID-19 , Coinfección , SARS-CoV-2 , Infecciones Estafilocócicas , Staphylococcus aureus , COVID-19/complicaciones , COVID-19/microbiología , Coinfección/microbiología , Coinfección/virología , Staphylococcus aureus/genética , Staphylococcus aureus/patogenicidad , Infecciones Estafilocócicas/microbiología , Humanos , Animales , Ratones , SARS-CoV-2/genética , Filogenia , Femenino , Ciudad de Nueva York/epidemiología , Masculino , Virulencia , Persona de Mediana Edad , Secuenciación Completa del Genoma , Bacteriemia/microbiología , Modelos Animales de Enfermedad , AncianoRESUMEN
INTRODUCTION: Tobacco smoke exposure (TSE) among individuals who do not smoke has declined in the USA, however, gaps remain in understanding how TSE patterns across indoor venues-including in homes, cars, workplaces, hospitality venues, and other areas-contribute to TSE disparities by income level. METHODS: We obtained data on adults (ages 18+, N=9909) and adolescents (ages 12-17, N=2065) who do not smoke from the National Health and Nutrition Examination Survey, 2013-2018. We examined the prevalence of self-reported, venue-specific TSE in each sample, stratified by poverty income ratio (PIR) quartile. We used linear regression models with a log-transformed outcome variable to explore associations between self-reported TSE and serum cotinine. We further explored the probability of detectable cotinine among individuals who reported no recent TSE, stratified by PIR. RESULTS: Self-reported TSE was highest in cars (prevalence=6.2% among adults, 14.2% among adolescents). TSE in own homes was the most strongly associated with differences in log cotinine levels (ß for adults=1.92, 95% CI=1.52 to 2.31; ß for adolescents=2.37 95% CI=2.07 to 2.66), and the association between home exposure and cotinine among adults was most pronounced in the lowest PIR quartile. There was an income gradient with regard to the probability of detectable cotinine among both adults and adolescents who did not report recent TSE. CONCLUSIONS: Homes and vehicles remain priority venues for addressing persistent TSE among individuals who do not smoke in the USA. TSE survey measures may have differential validity across population subgroups.
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OBJECTIVE: There are persistent disparities in pediatric asthma morbidity in the U.S. We linked claims data with information on neighborhood-level risk factors to explore drivers of asthma disparities among Medicaid-enrolled children in New York City subsidized housing. METHODS: We constructed a cohort of Medicaid-enrolled children living in public or other subsidized housing, based on residential address, in NYC between 2016 and 2019 (n = 108,969). We examined claims-derived asthma prevalence across age and racial and ethnic groups, integrating census tract-level information and using the Bayesian Improved Surname Geocoding (BISG) algorithm to address high rates of missing data in self-reported race and ethnicity. We used inverse probability weighting (IPW) to explore the extent to which disparities persisted when exposure to asthma risk factors - related to the built environment, neighborhood poverty, and air quality - were balanced across groups. This analysis was conducted in 2022-2023. RESULTS: Claims-derived asthma prevalence was highest among children <7 years at baseline and among non-Hispanic Black and Hispanic children. For example, among children aged 3-6 years at baseline, claims-derived prevalence was 17.3% and 18.1% among non-Hispanic Black and Hispanic children, respectively, compared to 9.3% and 9.0% among non-Hispanic White and non-Hispanic Asian American/Pacific Islander children. Using IPW to balance exposure to asthma risk factors across racial and ethnic groups attenuated, but did not eliminate, disparities in asthma prevalence. CONCLUSIONS: We found high asthma burden among children living in subsidized housing. Modifiable place-based characteristics may be important contributors to pediatric asthma disparities.
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Asma , Medicaid , Adolescente , Niño , Preescolar , Femenino , Humanos , Lactante , Masculino , Asma/etnología , Asma/epidemiología , Etnicidad/estadística & datos numéricos , Disparidades en el Estado de Salud , Medicaid/estadística & datos numéricos , Características del Vecindario , Ciudad de Nueva York/epidemiología , Prevalencia , Vivienda Popular/estadística & datos numéricos , Características de la Residencia/estadística & datos numéricos , Factores de Riesgo , Estados Unidos/epidemiología , Grupos RacialesRESUMEN
BACKGROUND: Research on health benefits due to exposure to green space, such as tree canopy coverage, has predominantly focused on canopy coverage in home neighborhoods. Yet exposures to tree canopy coverage in other spaces visited during the week or on weekends outside the home neighborhoods remains largely unexplored. OBJECTIVES: We examined whether differences in coverage levels of tree canopy in neighborhoods visited compared to home neighborhoods was associated with lower prevalence of coronary heart disease (CHD) and stroke, adjusting for exposure to home canopy coverage. We further investigated if the associations varied across levels of home canopy coverage, and if they were more pronounced on weekdays or weekends. METHODS: We used 2018 mobile phone data from the twenty largest U.S. Metropolitan Statistical Areas (MSAs). For each home census tract, we derived a weighted tree canopy coverage exposure from all visited tracts based on the proportion of visits to other tracts by home tract residents. We subtracted home canopy coverage from the weighted canopy coverage in each of the visited tracts to calculate tract-specific differences. We evaluated associations between differences in tree canopy coverage and prevalence of CHD and stroke via spatial error models, adjusting for tract-level home canopy coverage, MSA, socioeconomic and built environment characteristics. RESULTS: For every ten-percentage-point increase in tree canopy coverage in visited tracts relative to home tracts, there was a 0.32-0.34% decrease in stroke prevalence. Association with CHD prevalence was not observed after adjusting for spatial autocorrelation. Variations between weekdays and weekends were minimal. The difference in tree canopy coverage was associated with CHD prevalence only for home tracts with low tree canopy coverage, while the difference was associated with stroke prevalence across home tracts with low, moderate, and high tree canopy coverage, with diminishing effect size. DISCUSSION: This study identified that greater tree canopy coverage in visited neighborhoods relative to home neighborhoods was associated with lower stroke prevalence, and associations varied across home neighborhoods with different tree canopy coverage levels. It emphasized the need to factor in the neighborhood mobility networks in urban planning initiatives to promote cardiovascular health.
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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.
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In January 2015, the New York City Department of Health and Mental Hygiene launched Harlem Health Advocacy Partners (HHAP), a place-based initiative to demonstrate the capacity of a CHW workforce to improve the health of residents of public housing. The long-term goal of HHAP is to improve the population health of residents of public housing in East and Central Harlem and to close racial gaps in health and social outcomes. A variety of evaluation approaches have been used to assess the initiative. This paper describes the HHAP model and methods for evaluating the program.
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Agentes Comunitarios de Salud , Ciudad de Nueva York , Humanos , Evaluación de Programas y Proyectos de Salud , Vivienda Popular , Gobierno LocalRESUMEN
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 $250â¯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 28â¯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.
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Ejercicio Físico , Inversiones en Salud , Adulto , Humanos , Femenino , Masculino , Adulto Joven , Ciudad de Nueva York , Estudios Prospectivos , Gobierno LocalRESUMEN
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.
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Ciudades , Armas de Fuego , Homicidio , Humanos , Homicidio/estadística & datos numéricos , Armas de Fuego/legislación & jurisprudencia , Armas de Fuego/estadística & datos numéricos , Estados Unidos/epidemiología , Gobierno Estatal , Factores SocioeconómicosRESUMEN
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.
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Veteranos , Masculino , Humanos , Persona de Mediana Edad , Obesidad/epidemiología , Modelos Logísticos , Comida Rápida/efectos adversos , Características de la Residencia , RestaurantesRESUMEN
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.
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Diabetes Mellitus Tipo 2 , Niño , Humanos , Adolescente , Adulto Joven , Diabetes Mellitus Tipo 2/epidemiología , Registros Electrónicos de Salud , Prevalencia , Incidencia , AlgoritmosRESUMEN
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.
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Contaminantes Atmosféricos , Contaminación del Aire , Equidad en Salud , Humanos , Contaminantes Atmosféricos/análisis , Material Particulado/análisis , Ciudad de Nueva York , Contaminación del Aire/análisis , Costos y Análisis de CostoRESUMEN
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.
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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.
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Tramo Censal , Características de la Residencia , Humanos , Ciudades , Proyectos de Investigación , New YorkRESUMEN
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.
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Neoplasias , Caminata , Humanos , Femenino , Estudios Prospectivos , Universidades , Planificación Ambiental , Obesidad/epidemiología , Características de la Residencia , Salud de la Mujer , Neoplasias/epidemiología , Ciudad de Nueva York/epidemiologíaRESUMEN
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.
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Diabetes Mellitus Tipo 2 , Veteranos , Humanos , Femenino , Adulto Joven , Adulto , Persona de Mediana Edad , Anciano , Diabetes Mellitus Tipo 2/epidemiología , Hemoglobina Glucada , Glucemia , Estudios Retrospectivos , Control Glucémico , Etnicidad , GeografíaRESUMEN
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.