Faculty Bibliography

BACKGROUND:Few studies examine relationships between built environment (BE) and type 2 diabetes mellitus (T2DM) using spatial models, investigate BE domains apart from food environment or physical activity resources or conduct sensitivity analysis of methodological choices made in measuring BE. We examine geographic heterogeneity of T2DM, describe how heterogeneity in T2DM relates to BE and estimate associations of T2DM with BE. METHODS:Individual-level electronic health records (n=41 203) from the Duke Medicine Enterprise Data Warehouse (2007-2011) were linked to BE based on census block. Data on housing damage, property disorder, territoriality, vacancy and public nuisances were used to estimate BE based on four different construction methods (CMs). We used race-stratified aspatial and spatial Bayesian models to assess geographic heterogeneity in T2DM and associations of T2DM with BE. RESULTS:Among whites, a 1 SD increase in poor quality BE was associated with a 1.03 (95% credible interval 1.01 to 1.06) and 1.06 (95 % credible interval 1.02 to 1.11) increased risk of T2DM for poor quality BE CM1 and CM2, respectively. Among blacks/African Americans, associations between T2DM and BE overlapped with the null for all CMs. The addition of BE to white models reduced residual geographic heterogeneity in T2DM by 4%-15%, depending on CM. In black/African-American models, BE did not affect residual heterogeneity. CONCLUSION/CONCLUSIONS:Associations of T2DM with BE were sensitive to CM and geographic heterogeneity in T2DM differed by race/ethnicity. Findings underscore the need to consider multiple methods of estimating BE and consider differences in relationships by race/ethnicity.

Neighborhood characteristics such as racial segregation may be associated with type 2 diabetes mellitus, but studies have not examined these relationships using spatial models appropriate for geographically patterned health outcomes. We constructed a local, spatial index of racial isolation (RI) for black residents in a defined area, measuring the extent to which they are exposed only to one another, to estimate associations of diabetes with RI and examine how RI relates to spatial patterning in diabetes. We obtained electronic health records from 2007-2011 from the Duke Medicine Enterprise Data Warehouse. Patient data were linked to RI based on census block of residence. We used aspatial and spatial Bayesian models to assess spatial variation in diabetes and relationships with RI. Compared with spatial models with patient age and sex, residual geographic heterogeneity in diabetes in spatial models that also included RI was 29% and 24% lower for non-Hispanic white and black residents, respectively. A 0.20-unit increase in RI was associated with an increased risk of diabetes for white (risk ratio = 1.24, 95% credible interval: 1.17, 1.31) and black (risk ratio = 1.07, 95% credible interval: 1.05, 1.10) residents. Improved understanding of neighborhood characteristics associated with diabetes can inform development of policy interventions.

Globally, the majority of childhood deaths in the post-neonatal period are caused by infections that can be effectively treated or prevented with inexpensive interventions delivered through even very basic health facilities. To understand the role of inadequate health systems on childhood mortality in Kenya, we assemble a large, retrospective cohort of children (born 1996-2013) and describe the health systems context of each child using health facility survey data representative of the province at the time of a child's birth. We examine the relationship between survival beyond 59 months of age and geographic distribution of health facilities, quality of services, and cost of services. We find significant geographic heterogeneity in survival that can be partially explained by differences in distribution of health facilities and user fees. Higher per capita density of health facilities resulted in a 25% reduction in the risk of death (HRR = 0.73, 95% CI:0.58 to 0.91) and accounted for 30% of the between-province heterogeneity in survival. User fees for sick-child visits increased risk by 30% (HRR = 1.30, 95% CI:1.11 to 1.53). These results implicate health systems constraints in child mortality, quantify the contribution of specific domains of health services, and suggest priority areas for improvement to accelerate reductions in child mortality.

PURPOSE:To determine how strabismus diagnosis varies within a given community and across communities among children with Medicaid health insurance. DESIGN:Retrospective cohort analysis. PARTICIPANTS:Children aged ≤10 years enrolled in Medicaid in Michigan or North Carolina during 2009. METHODS:Children who met the study inclusion criteria were identified from the Medicaid Analytic Extract database, which includes claims data for all children enrolled in Medicaid throughout the United States. Residential location was determined by the last known 5-digit ZIP code for each child, which was linked to the centroid of a ZIP Code Tabulation Area (ZCTA) for geo-referencing and spatial analyses. International Classification of Diseases, 9th Revision, Clinical Modification billing codes were used to identify children diagnosed with strabismus (code 378.xx). Bayesian hierarchical intrinsic conditional autoregressive spatial probit models were used to determine the risk of a child receiving a strabismus diagnosis in communities throughout Michigan and North Carolina. Maps display communities (ZCTAs) where the 95% credible intervals for the spatial random effects estimates do not cross zero, allowing for identification of locations with increased and decreased strabismus diagnosis risk relative to other communities in the states. MAIN OUTCOME MEASURES:Likelihood of receiving a diagnosis of strabismus. RESULTS:In 2009, among 519 212 eligible children in Michigan, 7535 (1.5%) received ≥1 strabismus diagnosis, and in North Carolina, 5827 of 523 886 eligible children (1.1%) were diagnosed with strabismus. In both states, the proportion receiving a strabismus diagnosis among black (0.9% in Michigan; 0.7% in North Carolina) and Hispanic (1.1% in Michigan; 0.8% in North Carolina) children was lower than the proportion for white children (1.8% in Michigan; 1.6% in North Carolina). Children living in poorer communities in both states were less likely to be diagnosed with strabismus independent of their race/ethnicity. CONCLUSIONS:A child's likelihood of being diagnosed with strabismus is associated with characteristics of the residential community where he or she resides. The findings of this study highlight the importance of ensuring that children who live in less affluent communities have access to the necessary services and eye care professionals to properly diagnose and treat them for this condition.

BACKGROUND:Researchers and policymakers are increasingly focused on combined exposures to social and environmental stressors, especially given how often these stressors tend to co-locate. Such exposures are equally relevant in urban and rural areas and may accrue disproportionately to particular communities or specific subpopulations. OBJECTIVES:To estimate relationships between racial isolation (RI), a measure of the extent to which minority racial/ethnic group members are exposed to only one another, and long-term particulate matter with an aerodynamic diameter of <2.5μ (PM2.5) and ozone (O3) levels in urban and nonurban areas of the eastern two-thirds of the US. METHODS:Long-term (5year average) census tract-level PM2.5 and O3 concentrations were calculated using output from a downscaler model (2002-2006). The downscaler uses a linear regression with additive and multiplicative bias coefficients to relate ambient monitoring data with gridded output from the Community Multi-scale Air Quality (CMAQ) model. A local, spatial measure of RI was calculated at the tract level, and tracts were classified by urbanicity, RI, and geographic region. We examined differences in estimated pollutant exposures by RI, urbanicity, and demographic subgroup (e.g., race/ethnicity, education, socioeconomic status, age), and used linear models to estimate associations between RI and air pollution levels in urban, suburban, and rural tracts. RESULTS:High RI tracts (≥80th percentile) had higher average PM2.5 levels in each category of urbanicity compared to low RI tracts (<20th percentile), with the exception of the rural West. Patterns in O3 levels by urbanicity and RI differed by region. Linear models indicated that PM2.5 concentrations were significantly and positively associated with RI. The largest association between PM2.5 and RI was observed in the rural Midwest, where a one quintile increase in RI was associated with a 0.90μg/m(3) (95% confidence interval: 0.83, 0.99μg/m(3)) increase in PM2.5 concentration. Associations between O3 and RI in the Northeast, Midwest and West were positive and highest in suburban and rural tracts, even after controlling for potential confounders such as percentage in poverty. CONCLUSION:RI is associated with higher 5year estimated PM2.5 concentrations in urban, suburban, and rural census tracts, adding to evidence that segregation is broadly associated with disparate air pollution exposures. Disproportionate burdens to adverse exposures such as air pollution may be a pathway to racial/ethnic disparities in health.

BACKGROUND:Research surrounding the built environment (BE) and health has resulted in inconsistent findings. Experts have identified the need to examine methodological choices, such as development and testing of BE indices at varying spatial scales. We sought to examine the impact of construction method and spatial scale on seven measures of the BE using data collected at two time points. METHODS:The Children's Environmental Health Initiative conducted parcel-level assessments of 57 BE variables in Durham, NC (parcel N = 30,319). Based on a priori defined variable groupings, we constructed seven mutually exclusive BE domains (housing damage, property disorder, territoriality, vacancy, public nuisances, crime, and tenancy). Domain-based indices were developed according to four different index construction methods that differentially account for number of parcels and parcel area. Indices were constructed at the census block level and two alternative spatial scales that better depict the larger neighborhood context experienced by local residents: the primary adjacency community and secondary adjacency community. Spearman's rank correlation was used to assess if indices and relationships among indices were preserved across methods. RESULTS:Territoriality, public nuisances, and tenancy were weakly to moderately preserved across methods at the block level while all other indices were well preserved. Except for the relationships between public nuisances and crime or tenancy, and crime and housing damage or territoriality, relationships among indices were poorly preserved across methods. The number of indices affected by construction method increased as spatial scale increased, while the impact of construction method on relationships among indices varied according to spatial scale. CONCLUSIONS:We found that the impact of construction method on BE measures was index and spatial scale specific. Operationalizing and developing BE measures using alternative methods at varying spatial scales before connecting to health outcomes allows researchers to better understand how methodological decisions may affect associations between health outcomes and BE measures. To ensure that associations between the BE and health outcomes are not artifacts of methodological decisions, researchers would be well-advised to conduct sensitivity analysis using different construction methods. This approach may lead to more robust results regarding the BE and health outcomes.

BACKGROUND:Previous research has linked polybrominated diphenyl ether (PBDE) exposure to poor birth outcomes and altered thyroid hormone levels. OBJECTIVES/OBJECTIVE:We examined whether maternal PBDE serum levels were associated with infant birth weight (g), head circumference (cm), birth length (cm), and birth weight percentile for gestational age. We explored the potential for a mediating role of thyroid hormone levels. METHODS:During 2008-2010, we recruited 140 pregnant women in their third trimester as part of a larger clinical obstetrics study known as Healthy Pregnancy, Healthy Baby. Blood samples were collected during a routine prenatal clinic visit. Serum was analyzed for PBDEs, phenolic metabolites, and thyroid hormones. Birth outcome information was abstracted from medical records. RESULTS:In unadjusted models, a two-fold increase in maternal BDE 153 was associated with an average decrease in head circumference of 0.32cm (95% CI: -0.53, -0.12); however, this association was attenuated after control for maternal risk factors. BDE 47 and 99 were similarly negatively associated but with 95% confidence intervals crossing the null. Associations were unchanged in the presence of thyroid hormones. CONCLUSIONS:Our data suggest a potential deleterious association between maternal PBDE levels and infant head circumference; however, confirmatory studies are needed in larger sample sizes. A mediating role of thyroid hormones was not apparent.