Neighborhood Disadvantage and Risk of Heart Failure: The Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study.

BACKGROUND: Heart failure (HF) affects >6 million US adults, with recent increases in HF hospitalizations. We aimed to investigate the association between neighborhood disadvantage and incident HF events and potential differences by diabetes status. METHODS: We included 23 645 participants from the REGARDS study (Reasons for Geographic and Racial Differences in Stroke), a prospective cohort of Black and White adults aged ≥45 years living in the continental United States (baseline 2005-2007). Neighborhood disadvantage was assessed using a Z score of 6 census tract variables (2000 US Census) and categorized as quartiles. Incident HF hospitalizations or HF-related deaths through 2017 were adjudicated. Multivariable-adjusted Cox regression was used to examine the association between neighborhood disadvantage and incident HF. Heterogeneity by diabetes was assessed using an interaction term. RESULTS: The mean age was 64.4 years, 39.5% were Black adults, 54.9% females, and 18.8% had diabetes. During a median follow-up of 10.7 years, there were 1125 incident HF events with an incidence rate of 3.3 (quartile 1), 4.7 (quartile 2), 5.2 (quartile 3), and 6.0 (quartile 4) per 1000 person-years. Compared to adults living in the most advantaged neighborhoods (quartile 1), those living in neighborhoods in quartiles 2, 3, and 4 (most disadvantaged) had 1.30 (95% CI, 1.06-1.60), 1.36 (95% CI, 1.11-1.66), and 1.45 (95% CI, 1.18-1.79) times greater hazard of incident HF even after accounting for known confounders. This association did not significantly differ by diabetes status (interaction P=0.59). For adults with diabetes, the adjusted incident HF hazards comparing those in quartile 4 versus quartile 1 was 1.34 (95% CI, 0.92-1.96), and it was 1.50 (95% CI, 1.16-1.94) for adults without diabetes. CONCLUSIONS: In this large contemporaneous prospective cohort, neighborhood disadvantage was associated with an increased risk of incident HF events. This increase in HF risk did not differ by diabetes status. Addressing social, economic, and structural factors at the neighborhood level may impact HF prevention.

Associations between PM2.5 and O3 exposures and new onset type 2 diabetes in regional and national samples in the United States.

BACKGROUND: Exposure to particulate matter ≤2.5 µm in diameter (PM2.5) and ozone (O3) has been linked to numerous harmful health outcomes. While epidemiologic evidence has suggested a positive association with type 2 diabetes (T2D), there is heterogeneity in findings. We evaluated exposures to PM2.5 and O3 across three large samples in the US using a harmonized approach for exposure assignment and covariate adjustment. METHODS: Data were obtained from the Veterans Administration Diabetes Risk (VADR) cohort (electronic health records [EHRs]), the Reasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort (primary data collection), and the Geisinger health system (EHRs), and reflect the years 2003-2016 (REGARDS) and 2008-2016 (VADR and Geisinger). New onset T2D was ascertained using EHR information on medication orders, laboratory results, and T2D diagnoses (VADR and Geisinger) or report of T2D medication or diagnosis and/or elevated blood glucose levels (REGARDS). Exposure was assigned using pollutant annual averages from the Downscaler model. Models stratified by community type (higher density urban, lower density urban, suburban/small town, or rural census tracts) evaluated likelihood of new onset T2D in each study sample in single- and two-pollutant models of PM2.5 and O3. RESULTS: In two pollutant models, associations of PM2.5, and new onset T2D were null in the REGARDS cohort except for in suburban/small town community types in models that also adjusted for NSEE, with an odds ratio (95% CI) of 1.51 (1.01, 2.25) per 5 µg/m3 of PM2.5. Results in the Geisinger sample were null. VADR sample results evidenced nonlinear associations for both pollutants; the shape of the association was dependent on community type. CONCLUSIONS: Associations between PM2.5, O3 and new onset T2D differed across three large study samples in the US. None of the results from any of the three study populations found strong and clear positive associations.

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.

Assessing Measurement Invariance of a Land Use Environment Construct Across Levels of Urbanicity.

Variation in the land use environment (LUE) impacts the continuum of walkability to car dependency, which has been shown to have effects on health outcomes. Existing objective measures of the LUE do not consider whether the measurement of the construct varies across different types of communities along the rural/urban spectrum. To help meet the goals of the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, we developed a national, census tract-level LUE measure which evaluates the road network and land development. We tested for measurement invariance by LEAD community type (higher density urban, lower density urban, suburban/small town, and rural) using multiple group confirmatory factor analysis. We determined that metric invariance does not exist; thus, measurement of the LUE does vary across community type with average block length, average block size, and percent developed land driving most shared variability in rural tracts and with intersection density, street connectivity, household density, and commercial establishment density driving most shared variability in higher density urban tracts. As a result, epidemiologic studies need to consider community type when assessing the LUE to minimize place-based confounding.

Latent growth trajectories of county-level diabetes prevalence in the United States, 2004-2017, and associations with overall environmental quality.

The prevalence of type 2 diabetes (T2D) has increased in the United States, and recent studies suggest that environmental factors contribute to T2D risk. We sought to understand if environmental factors were associated with the rate and magnitude of increase in diabetes prevalence at the county level. Methods: We obtained age-adjusted diabetes prevalence estimates from the CDC for 3,137 US counties from 2004 to 2017. We applied latent growth mixture models to these data to identify classes of counties with similar trends in diabetes prevalence over time, stratified by Rural Urban Continuum Codes (RUCC). We then compared mean values of the US EPA Environmental Quality Index (EQI) 2006-2010, overall and for each of the five domain indices (air, water, land, sociodemographic, and built), with RUCC-specific latent class to examine associations of environmental factors and class of diabetes prevalence trajectory. Results: Overall diabetes prevalence trends between 2004 and 2017 were similar across all RUCC strata. We identified two classes among metropolitan urbanized (RUCC 1) counties; four classes among non-metro urbanized (RUCC 2) counties; and three classes among less urbanized (RUCC 3) and thinly populated (RUCC 4) counties. Associations with overall EQI values and class of diabetes prevalence trends differed by RUCC strata, with the clearest association between poor air EQI and steeper increases in diabetes prevalence among rural counties (RUCC 3 and 4). Conclusions: Similarities in county-level diabetes prevalence trends between 2004 and 2017 were identified for each RUCC strata, although associations with environmental factors varied by rurality.

Urban and rural differences in new onset type 2 diabetes: Comparisons across national and regional samples in the diabetes LEAD network.

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.

Categorizing community type for epidemiologic evaluation of community factors and chronic disease across the United States.

Existing classifications of community type do not differentiate urban cores from surrounding non-rural areas, an important distinction for analyses of community features and their impact on health. Inappropriately classified community types can introduce serious methodologic flaws in epidemiologic studies and invalid inferences from findings. To address this, we evaluate a modification of the United States Department of Agriculture's Rural Urban Commuting Area codes at the census tract, propose a four-level categorization of community type, and compare this with existing classifications for epidemiologic analyses. Compared to existing classifications, our method resulted in clearer geographic delineations of community types within urban areas.

Evaluation of associations between estimates of particulate matter exposure and new onset type 2 diabetes in the REGARDS cohort.

BACKGROUND: Studies of PM2.5 and type 2 diabetes employ differing methods for exposure assignment, which could explain inconsistencies in this growing literature. We hypothesized associations between PM2.5 and new onset type 2 diabetes would differ by PM2.5 exposure data source, duration, and community type. METHODS: We identified participants of the US-based REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort who were free of diabetes at baseline (2003-2007); were geocoded at their residence; and had follow-up diabetes information. We assigned PM2.5 exposure estimates to participants for periods of 1 year prior to baseline using three data sources, and 2 years prior to baseline for two of these data sources. We evaluated adjusted odds of new onset diabetes per 5 µg/m3 increases in PM2.5 using generalized estimating equations with a binomial distribution and logit link, stratified by community type. RESULTS: Among 11,208 participants, 1,409 (12.6%) had diabetes at follow-up. We observed no associations between PM2.5 and diabetes in higher and lower density urban communities, but within suburban/small town and rural communities, increases of 5 µg/m3 PM2.5 for 2 years (Downscaler model) were associated with diabetes (OR [95% CI] = 1.65 [1.09, 2.51], 1.56 [1.03, 2.36], respectively). Associations were consistent in direction and magnitude for all three PM2.5 sources evaluated. SIGNIFICANCE: 1- and 2-year durations of PM2.5 exposure estimates were associated with higher odds of incident diabetes in suburban/small town and rural communities, regardless of exposure data source. Associations within urban communities might be obfuscated by place-based confounding.

Unconventional Natural Gas Development and Hospitalization for Heart Failure in Pennsylvania.

BACKGROUND: Growing literature linking unconventional natural gas development (UNGD) to adverse health has implicated air pollution and stress pathways. Persons with heart failure (HF) are susceptible to these stressors. OBJECTIVES: This study sought to evaluate associations between UNGD activity and hospitalization among HF patients, stratified by both ejection fraction (EF) status (reduced [HFrEF], preserved [HFpEF], not classifiable) and HF severity. METHODS: We evaluated the odds of hospitalization among patients with HF seen at Geisinger from 2008 to 2015 using electronic health records. We assigned metrics of UNGD activity by phase (pad preparation, drilling, stimulation, and production) 30 days before hospitalization or a frequency-matched control selection date. We assigned phenotype status using a validated algorithm. RESULTS: We identified 9,054 patients with HF with 5,839 hospitalizations (mean age 71.1 ± 12.7 years; 47.7% female). Comparing 4th to 1st quartiles, adjusted odds ratios (95% confidence interval) for hospitalization were 1.70 (1.35 to 2.13), 0.97 (0.75 to 1.27), 1.80 (1.35 to 2.40), and 1.62 (1.07 to 2.45) for pad preparation, drilling, stimulation, and production metrics, respectively. We did not find effect modification by HFrEF or HFpEF status. Associations of most UNGD metrics with hospitalization were stronger among those with more severe HF at baseline. CONCLUSIONS: Three of 4 phases of UNGD activity were associated with hospitalization for HF in a large sample of patients with HF in an area of active UNGD, with similar findings by HFrEF versus HFpEF status. Older patients with HF seem particularly vulnerable to adverse health impacts from UNGD activity.

Street-level noise in an urban setting: assessment and contribution to personal exposure.

BACKGROUND: The urban soundscape, which represents the totality of noise in the urban setting, is formed from a wide range of sources. One of the most ubiquitous and least studied of these is street-level (i.e., sidewalk) noise. Mainly associated with vehicular traffic, street level noise is hard to ignore and hard to escape. It is also potentially dangerous, as excessive noise from any source is an important risk factor for adverse health effects. This study was conducted to better characterize the urban soundscape and the role of street level noise on overall personal noise exposure in an urban setting. METHODS: Street-level noise measures were obtained at 99 street sites located throughout New York City (NYC), along with data on time, location, and sources of environmental noise. The relationship between street-level noise measures and potential predictors of noise was analyzed using linear and logistic regression models, and geospatial modeling was used to evaluate spatial trends in noise. Daily durations of street-level activities (time spent standing, sitting, walking and running on streets) were estimated via survey from a sample of NYC community members recruited at NYC street fairs. Street-level noise measurements were then combined with daily exposure durations for each member of the sample to estimate exposure to street noise, as well as exposure to other sources of noise. RESULTS: The mean street noise level was 73.4 dBA, with substantial spatial variation (range 55.8-95.0 dBA). Density of vehicular (road) traffic was significantly associated with excessive street level noise levels. Exposure duration data for street-level noise and other common sources of noise were collected from 1894 NYC community members. Based on individual street-level exposure estimates, and in consideration of all other sources of noise exposure in an urban population, we estimated that street noise exposure contributes approximately 4% to an average individual's annual noise dose. CONCLUSIONS: Street-level noise exposure is a potentially important source of overall noise exposure, and the reduction of environmental sources of excessive street- level noise should be a priority for public health and urban planning.

Mass transit ridership and self-reported hearing health in an urban population.

Information on prevalence and risk factors associated with self-reported hearing health among mass transit riders is extremely limited, even though evidence suggests mass transit may be a source of excessive exposure to noise. Data on mass transit ridership were collected from 756 study participants using a self-administered questionnaire. Hearing health was measured using two symptom items (tinnitus and temporary audiometric threshold shift), two subjective measures (self-rated hearing and hearing ability), and two medical-related questions (hearing testing and physician-diagnosed hearing loss). In logistic regression analyses that controlled for possible confounders, including demographic variables, occupational noise exposure, nonoccupational noise exposure (including MP3 player use) and use of hearing protection, frequent and lengthy mass transit (all forms) ridership (1,100 min or more per week vs. 350 min or less per week) was the strongest predictor of temporary threshold shift symptoms. Noise abatement strategies, such as engineering controls, and the promotion of hearing protection use should be encouraged to reduce the risk of adverse impacts on the hearing health of mass transit users.

Exposures to transit and other sources of noise among New York City residents.

To evaluate the contributions of common noise sources to total annual noise exposures among urban residents and workers, we estimated exposures associated with five common sources (use of mass transit, occupational and nonoccupational activities, MP3 player and stereo use, and time at home and doing other miscellaneous activities) among a sample of over 4500 individuals in New York City (NYC). We then evaluated the contributions of each source to total noise exposure and also compared our estimated exposures to the recommended 70 dBA annual exposure limit. We found that one in ten transit users had noise exposures in excess of the recommended exposure limit from their transit use alone. When we estimated total annual exposures, 90% of NYC transit users and 87% of nonusers exceeded the recommended limit. MP3 player and stereo use, which represented a small fraction of the total annual hours for each subject on average, was the primary source of exposure among the majority of urban dwellers we evaluated. Our results suggest that the vast majority of urban mass transit riders may be at risk of permanent, irreversible noise-induced hearing loss and that, for many individuals, this risk is driven primarily by exposures other than occupational noise.