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This study examined overall and gender-specific associations between place-based characteristics and opposite-sex exchange sex among people who inject drugs (PWID) in the U.S. PWID were recruited from 19 metropolitan statistical areas (MSAs) for the Centers for Disease Control and Prevention’s 2012 National HIV Behavioral Surveillance. Administrative data were used to describe the economic, social, and political features of the ZIP codes, MSAs, counties, and states where PWID lived. Multilevel modeling estimated associations of place characteristics and exchange sex. We found that 52% of women and 23% of men reported past-year opposite-sex exchange sex (N = 7599). Female PWID living in states with stronger policies supporting working caregivers had lower odds of exchange sex (aOR = 0.80; 95% CI 0.69, 0.94). PWID living in ZIP codes with greater economic deprivation had higher odds of exchange sex (aOR = 1.10; 95% CI 1.03, 1.17). We found that a high percentage of male PWID exchanged sex with women; determinants and risks of this group merit exploration. If future research establishes that the relationships identified here are causal, interventions to reduce exchange sex among PWID should include policies supporting working caregivers and reducing poverty rates.

Racial/ethnic homophily in sexual partnerships (partners share the same race/ethnicity) has been associated with racial/ethnic disparities in HIV. Structural racism may partly determine racial/ethnic homophily in sexual partnerships. This study estimated associations of racial/ethnic concentration and mortgage discrimination against Black and Latino residents with racial/ethnic homophily in sexual partnerships among 7847 people who inject drugs (PWID) recruited from 19 US cities to participate in CDC’s National HIV Behavioral Surveillance. Racial/ethnic concentration was defined by two measures that respectively compared ZIP code-level concentrations of Black residents to White residents and Latino residents to White residents, using the Index of Concentration at the Extremes. Mortgage discrimination was defined by two measures that respectively compared county-level mortgage loan denial among Black applicants to White applicants and mortgage loan denial among Latino applicants to White applicants, with similar characteristics (e.g., income, loan amount). Multilevel logistic regression models were used to estimate associations. Interactions of race/ethnicity with measures of racial/ethnic concentration and mortgage discrimination were added to the final multivariable model and decomposed into race/ethnicity-specific estimates. In the final multivariable model, among Black PWID, living in ZIP codes with higher concentrations of Black vs. White residents and counties with higher mortgage discrimination against Black residents was associated with higher odds of homophily. Living in counties with higher mortgage discrimination against Latino residents was associated with lower odds of homophily among Black PWID. Among Latino PWID, living in ZIP codes with higher concentrations of Latino vs. White residents and counties with higher mortgage discrimination against Latino residents was associated with higher odds of homophily. Living in counties with higher mortgage discrimination against Black residents was associated with lower odds of homophily among Latino PWID. Among White PWID, living in ZIP codes with higher concentrations of Black or Latino residents vs. White residents was associated with lower odds of homophily, but living in counties with higher mortgage discrimination against Black residents was associated with higher odds of homophily. Racial/ethnic segregation may partly drive same race/ethnicity sexual partnering among PWID. Future empirical evidence linking these associations directly or indirectly (via place-level mediators) to HIV/STI transmission will determine how eliminating discriminatory housing policies impact HIV/STI transmission.

This exploratory analysis investigates relationships of place characteristics to HIV testing among people who inject drugs (PWID). We used CDC's 2012 National HIV Behavioral Surveillance (NHBS) data among PWID from 19 US metropolitan statistical areas (MSAs); we restricted the analytic sample to PWID self-reporting being HIV negative (N = 7477). Administrative data were analyzed to describe the 1. Sociodemographic Composition; 2. Economic disadvantage; 3. Healthcare Service/Law enforcement; and 4. HIV burden of the ZIP codes, counties, and MSAs where PWID lived. Multilevel models tested associations of place characteristics with HIV testing. Fifty-eight percent of PWID reported past-year testing. MSA-level per capita correctional expenditures were positively associated with recent HIV testing among black PWID, but not white PWID. Higher MSA-level household income and imbalanced sex ratios (more women than men) in the MSA were associated with higher odds of testing. HIV screening for PWID is suboptimal (58%) and needs improvement. Identifying place characteristics associated with testing among PWID can strengthen service allocation and interventions in areas of need to increase access to HIV testing.

Neighborhood social and physical factors shape sexual network characteristics in HIV-seronegative adults in the United States. This multilevel analysis evaluated whether these relationships also exist in a predominantly HIV-seropositive cohort of women. This cross-sectional multilevel analysis included dm 734 women enrolled in the Women's Interagency HIV Study's sites in the U S South. Center track-level contextual data captured socioeconomic disadvantage (e.g., tract poverty), number of alcohol outlets, and number of nonprofits in the census tracts where women lived; participant-level data, including perceived neighborhood cohesion, were gathered via survey. We used hierarchical generalized linear models to evaluate relationships between tract characteristics and two outcomes: perceived main sex partner risk level (e.g., partner substance use) and perceived main sex partner non-monogamy. We tested whether these relationships varied by women's HIV. Greater tract-level socioeconomic disadvantage was associated with greater sex partner risk (OR = 1.29, 95 % CI = 1.06-1.58) among HIV-seropositive women and less partner non-monogamy among HIV-seronegative women (OR = 0.69, 95 % CI = 0.51-0.92). Perceived neighborhood trust and cohesion was associated with lower partner risk (OR = 0.83, 95 % CI = 0.69-1.00) for HIV-seropositive and HIV-seronegative women. The tract-level number of alcohol outlets and non-profits were not associated with partner risk characteristics. Neighborhood characteristics are associated with perceived sex partner risk and non-monogamy among women in the South; these relationships vary by HIV status. Future studies should examine causal relationships and explore the pathways through which neighborhoods influence partner selection and risk characteristics.

Exposure to environmental noise from traffic is common in urban areas and has been linked to increased risks of adverse health effects including cardiovascular disease. Because traffic sources also produce air pollutants that increase the risk of cardiovascular morbidity, associations between traffic exposures and health outcomes may involve confounding and/or synergisms between air pollution and noise. While prior studies have characterized intraurban spatial variation in air pollution in New York City (NYC), limited data exists on the levels and spatial variation in noise levels. We measured 1-week equivalent continuous sound pressure levels (Leq) at 56 sites during the fall of 2012 across NYC locations with varying traffic intensity and building density that are routinely monitored for combustion-related air pollutants. We evaluated correlations among several noise metrics used to characterize noise exposures, including Leq during different time periods (night, day, weekday, weekend), Ldn (day-night noise), and measures of intermittent noise defined as the ratio of peak levels to median and background levels. We also examined correlations between sound pressure levels and co-located simultaneous measures of nitric oxide (NO), nitrogen dioxide (NO2), fine particulate matter (PM2.5), and black carbon (BC) as well as estimates of traffic and building density around the monitoring sites. Noise levels varied widely across the 56 monitoring sites; 1-week Leq varied by 21.6 dBA (range 59.1–80.7 dBA) with the highest levels observed during the weekday, daytime hours. Indices of average noise were well correlated with each other (r > 0.83), while indices of intermittent noise were not well correlated with average noise levels (r

USA is experiencing a paradigm shift in public housing policy: while policies used to place people who qualified for housing assistance into spatially concentrated housing complexes, they now seek to geographically disperse them, often to voucher-subsidized rental units in the private market. Programs that relocate residents from public housing complexes tend to move them to neighborhoods that are less impoverished and less violent. To date, studies have reached conflicting findings about the relationship between public housing relocations and depression among adult relocaters. The present longitudinal multilevel analysis tests the hypothesis that pre-/postrelocation improvements in local economic conditions, social disorder, and perceived community violence are associated with declines in depressive symptoms in a cohort of African-American adults; active substance misusers were oversampled. We tested this hypothesis in a cohort of 172 adults who were living in one of seven public housing complexes scheduled for relocation and demolition in Atlanta, GA; by design, 20 % were dependent on substances and 50 % misused substances but were not dependent. Baseline data captured prerelocation characteristics of participants; of the seven census tracts where they lived, three waves of postrelocation data were gathered approximately every 9 months thereafter. Surveys were administered at each wave to assess depressive symptoms measured using the Center for Epidemiologic Studies Depression Scale (CES-D), perceived community violence, and other individual-level covariates. Participants' home addresses were geocoded to census tracts at each wave, and administrative data sources were used to characterize tract-level economic disadvantage and social disorder. Hypotheses were tested using multilevel models. Between waves 1 and 2, participants experienced significant improvements in reported depressive symptoms and perceived community violence and in tract-level economic disadvantage and social disorder; these reductions were sustained across waves 2–4. A 1 standard deviation improvement in economic conditions was associated with a 1-unit reduction in CES-D scores; the magnitude of this relationship did not vary by baseline substance misuse or gender. Reduced perceived community violence also predicted lower CES-D scores. Our objective measure of social disorder was unrelated to depressive symptoms. We found that relocaters who experienced greater pre-/postrelocation improvements in economic conditions or in perceived community violence experienced fewer depressive symptoms. Combined with past research, these findings suggest that relocation initiatives should focus on the quality of the places to which relocaters move; future research should also identify pathways linking pre-/postrelocation changes in place characteristics to changes in mental health.

Although intra-urban air pollution differs by season, few monitoring networks provide adequate geographic density and year-round coverage to fully characterize seasonal patterns. Here, we report winter intra-urban monitoring and land-use regression (LUR) results from the New York City Community Air Survey (NYCCAS). Two-week integrated samples of fine particles (PM(2.5)), black carbon (BC), nitrogen oxides (NO(x)) and sulfur dioxide (SO(2)) were collected at 155 city-wide street-level locations during winter 2008-2009. Sites were selected using stratified random sampling, randomized across sampling sessions to minimize spatio-temporal confounding. LUR was used to identify GIS-based source indicators associated with higher concentrations. Prediction surfaces were produced using kriging with external drift. Each pollutant varied twofold or more across sites, with higher concentrations near midtown Manhattan. All pollutants were positively correlated, particularly PM(2.5) and BC (Spearman's r=0.84). Density of oil-burning boilers, total and truck traffic density, and temporality explained 84% of PM(2.5) variation. Densities of total traffic, truck traffic, oil-burning boilers and industrial space, with temporality, explained 65% of BC variation. Temporality, built space, bus route location, and traffic density described 67% of nitrogen dioxide variation. Residual oil-burning units, nighttime population and temporality explained 77% of SO(2) variation. Spatial variation in combustion-related pollutants in New York City was strongly associated with oil-burning and traffic density. Chronic exposure disparities and unique local sources can be identified through year-round saturation monitoring.

Routine air monitoring provides data to assess urban scale temporal variation in pollution concentrations in relation to regulatory standards, but is not well suited to characterizing intraurban spatial variation in pollutant concentrations from local sources. To address these limitations and inform local control strategies, New York City developed a program to track spatial patterns of multiple air pollutants in each season of the year. Monitor locations include 150 distributed street-level sites chosen to represent a range of traffic, land-use and other characteristics. Integrated samples are collected at each distributed site for one 2-week session each season and in every 2-week period at five reference locations to track city-wide temporal variation. Pollutants sampled include PM(2.5) and constituents, nitrogen oxides, black carbon, ozone (summer only) and sulfur dioxide (winter only). During the first full year of monitoring more than 95% of designed samples were completed. Agreement between colocated samples was good (absolute mean % difference 3.2-8.9%). Street-level pollutant concentrations spanned a much greater range than did concentrations at regulatory monitors, especially for oxides of nitrogen and sulfur dioxide. Monitoring to characterize intraurban spatial gradients in ambient pollution usefully complements regulatory monitoring data to inform local air quality management.

We modeled the intraurban distribution of nitrogen dioxide (NO(2)), a marker for traffic pollution, with land use regression, a promising new exposure classification technique. We deployed diffusion tubes to measure NO(2) levels at 39 locations in the fall of 2003 in San Diego County, CA, USA. At each sample location, we constructed circular buffers in a geographic information system and captured information on roads, traffic flow, land use, population and housing. Using multiple linear regression, we were able to predict 79% of the variation in NO(2) levels with four variables: traffic density within 40-300 m of the sampling location, traffic density within 300-1000 m, length of road within 40 m and distance to the Pacific coast. Applying this model to validation samples showed that the model predicted NO(2) levels within, on average, 2.1 p.p.b for 12 training sites initially excluded from the model. Our evaluation of this land use regression model showed that this method had excellent prediction and robustness in a North American context. These models may be useful tools in evaluating health effects of long-term exposure to traffic-related pollution.