Segregation and Childhood Blood Lead Levels in North Carolina.

BACKGROUND AND OBJECTIVES: Using a local measure of racial residential segregation, estimate the association between racial residential segregation and childhood blood lead levels between the early 1990s and 2015 in North Carolina. METHODS: This population-based observational study uses individual-level blood lead testing records obtained from the NC Department of Health and Human Services for 320 916 children aged <7 years who were tested between 1992 and 1996 or 2013 and 2015. NC childhood blood lead levels were georeferenced to the census tract. Neighborhood racial residential segregation, assessed using a local, spatial measure of the racial isolation of non-Hispanic Blacks (RINHB), was calculated at the census tract level. RESULTS: From 1990 to 2015, RINHB increased in 50% of 2195 NC census tracts, although the degree of change varied by geographic region. In 1992 to 1996 blood lead testing data, a 1-standard-deviation increase in tract-level RINHB was associated with a 2.86% (95% confidence interval: 0.96%-4.81%) and 2.44% (1.34%-3.56%) increase in BLL among non-Hispanic Black and non-Hispanic White children, respectively. In 2013 to 2015 blood lead testing data, this association was attenuated but persisted with a 1-standard-deviation increase in tract-level RINHB associated with a 1.59% (0.50%-2.70%) and 0.76% (0.08%-1.45%) increase in BLL among non-Hispanic Black and non-Hispanic White children, respectively. In the supplemental information, we show the change in racial residential segregation across the entire United States, demonstrating that RINHB increased in 69% of 72 899 US census tracts. CONCLUSIONS: Racially isolated neighborhoods are associated with higher childhood lead levels, demonstrating the disproportionate environmental burdens borne by segregated communities and warranting attention to providing whole child health care.

SPATIAL DISTRIBUTED LAG DATA FUSION FOR ESTIMATING AMBIENT AIR POLLUTION.

We introduce spatial (DLfuse) and spatiotemporal (DLfuseST) distributed lag data fusion methods for predicting point-level ambient air pollution concentrations, using, as input, gridded average pollution estimates from a deterministic numerical air quality model. The methods incorporate predictive information from grid cells surrounding the prediction location of interest and are shown to collapse to existing downscaling approaches when this information adds no benefit. The spatial lagged parameters are allowed to vary spatially/spatiotemporally to accommodate the setting where surrounding geographic information is useful in one area/time but not in another. We apply the new methods to predict ambient concentrations of eight-hour maximum ozone and 24-hour average PM2.5 at unobserved spatial locations and times, and compare the predictions with those from several state-of-the-art data fusion approaches. Results show that DLfuse and DLfuseST often provide improved model fit and predictive accuracy when the lagged information is shown to be beneficial. Code to apply the methods is available in the R package DLfuse.

The Texas flood registry: a flexible tool for environmental and public health practitioners and researchers.

BACKGROUND: Making landfall in Rockport, Texas in August 2017, Hurricane Harvey resulted in unprecedented flooding, displacing tens of thousands of people, and creating environmental hazards and exposures for many more. OBJECTIVE: We describe a collaborative project to establish the Texas Flood Registry to track the health and housing impacts of major flooding events. METHODS: Those who enroll in the registry answer retrospective questions regarding the impact of storms on their health and housing status. We recruit both those who did and did not flood during storm events to enable key comparisons. We leverage partnerships with multiple local health departments, community groups, and media outlets to recruit broadly. We performed a preliminary analysis using multivariable logistic regression and a binomial Bayesian conditional autoregressive (CAR) spatial model. RESULTS: We find that those whose homes flooded, or who came into direct skin contact with flood water, are more likely to experience a series of self-reported health effects. Median household income is inversely related to adverse health effects, and spatial analysis provides important insights within the modeling approach. SIGNIFICANCE: Global climate change is likely to increase the number and intensity of rainfall events, resulting in additional health burdens. Population-level data on the health and housing impacts of major flooding events is imperative in preparing for our planet's future.

Leveraging Data Analytics and Scalable Information Technology Tools to Deliver a Culture of Care during an Emergent Natural Disaster.

Rice University's Culture of Care represents a commitment to ensuring that all are treated with respect, compassion, and deep care. Rice leveraged information technology (IT) to deliver its Culture of Care, in responding to Hurricane Harvey. IT tools were used to gather key information on Rice's over 12000 community members. These data were fused with structured university data, enabling data-driven disaster response, with actionable information pushed to local managers. Our successful communication and response programs were all driven by the data analyses.

Geosocial Factors Associated With Adherence to Statin Medications.

BACKGROUND: Individual patient characteristics, social determinants, and geographic access may be associated with patients engaging in appropriate health behaviors. OBJECTIVE: To assess the relationship between statin adherence, geographic accessibility to pharmacies, and neighborhood sociodemographic characteristics in Michigan. METHODS: The proportion of days covered (PDC) was calculated from pharmacy claims of a large insurer of adults who had prescriptions for statins between July 2009 and June 2010. A PDC ≥0.80 was defined as adherent. The predictor of interest was a ZIP code tabulation area (ZCTA)-level measure of geographic accessibility to pharmacies, measured using a method that integrates availability and access into a single index. We fit unadjusted models as well as adjusted models controlling for age, sex, and ZCTA-level measures of socioeconomic status (SES), racial isolation (RI) of non-Hispanic blacks, and urbanicity. RESULTS: More than 174 000 patients' claims data were analyzed. In adjusted models, pharmacy access was not associated with adherence (0.99; 95% CI: 0.96, 1.03). Greater RI (0.87; 95% CI: 0.85, 0.88) and urban status (0.93; 95% CI: 0.89, 0.96) were associated with lower odds of adherence. Individuals in ZCTAs with higher SES had higher odds of adherence, as were men and older age groups. CONCLUSION AND RELEVANCE: Adherence to statin prescriptions was lower for patients living in areas characterized as being racially segregated or lower income. Initiating interventions to enhance adherence, informed by understanding the social and systematic barriers patients face when refilling medication, is an important public health initiative that pharmacists practicing in these areas may undertake.

Access to chiropractic care and the cost of spine conditions among older adults.

OBJECTIVES: Chiropractic care is a service that operates outside of the conventional medical system and is reimbursed by Medicare. Our objective was to examine the extent to which accessibility of chiropractic care affects spending on medical spine care among Medicare beneficiaries. STUDY DESIGN: Retrospective cohort study that used beneficiary relocation as a quasi-experiment. METHODS: We used a combination of national data on provider location and Medicare claims to perform a quasi-experimental study to examine the effect of chiropractic care accessibility on healthcare spending. We identified 84,679 older adults enrolled in Medicare with a spine condition who relocated once between 2010 and 2014. For each year, we measured accessibility using the variable-distance enhanced 2-step floating catchment area method. Using data for the years before and after relocation, we estimated the effect of moving to an area of lower or higher chiropractic accessibility on spine-related spending adjusted for access to medical physicians. RESULTS: There are approximately 45,000 active chiropractors in the United States, and local accessibility varies considerably. A negative dose-response relationship was observed for spine-related spending on medical evaluation and management as well as diagnostic imaging and testing (mean differences, $20 and $40, respectively, among those exposed to increasingly higher chiropractic accessibility; P <.05 for both). Associations with other types of spine-related spending were not significant. CONCLUSIONS: Among older adults, access to chiropractic care may reduce medical spending on services for spine conditions.

Geographic variation in spatial accessibility of U.S. healthcare providers.

BACKGROUND: Growing physician maldistribution and population demographic shifts have contributed to large geographic variation in healthcare access and the emergence of advanced practice providers as contributors to the healthcare workforce. Current estimates of geographic accessibility of physicians and advanced practice providers rely on outdated "provider per capita" estimates that have shortcomings. PURPOSE: To apply state of the art methods to estimate spatial accessibility of physician and non-physician clinician groups and to examine factors associated with higher accessibility. METHODS: We used a combination of provider location, medical claims, and U.S. Census data to perform a national study of health provider accessibility. The National Plan and Provider Enumeration System was used along with Medicare claims to identify providers actively caring for patients in 2014 including: primary care physicians (i.e., internal medicine and family medicine), specialists, nurse practitioners, and chiropractors. For each U.S. ZIP code tabulation area, we estimated provider accessibility using the Variable-distance Enhanced 2 step Floating Catchment Area method and performed a Getis-Ord Gi* analysis for each provider group. Generalized linear models were used to examine associations between population characteristics and provider accessibility. RESULTS: National spatial patterns of the provider groups differed considerably. Accessibility of internal medicine most resembled specialists with high accessibility in urban locales, whereas relative higher accessibility of family medicine physicians was concentrated in the upper Midwest. In our adjusted analyses independent factors associated with higher accessibility were very similar between internal medicine physicians and specialists-presence of a medical school in the county was associated with approximately 70% higher accessibility and higher accessibility was associated with urban locales. Nurse practitioners were similar to family medicine physicians with both having higher accessibility in rural locales. CONCLUSIONS: The Variable-distance Enhanced 2 step Floating Catchment Area method is a viable approach to measure spatial accessibility at the national scale.

The Rate Stabilizing Tool: Generating Stable Local-Level Measures of Chronic Disease.

Accurate and precise estimates of local-level epidemiologic measures are critical to informing policy and program decisions, but they often require advanced statistical knowledge, programming/coding skills, and extensive computing power. In response, we developed the Rate Stabilizing Tool (RST), an ArcGIS-based tool that enables users to input their own record-level data to generate more reliable age-standardized measures of chronic disease (eg, prevalence rates, mortality rates) or other population health outcomes at the county or census tract levels. The RST uses 2 forms of empirical Bayesian modeling (nonspatial and spatial) to estimate age-standardized rates and 95% credible intervals for user-specified geographic units. The RST also provides indicators of the reliability of point estimates. In addition to reviewing the RST's statistical techniques, we present results from a simulation study that illustrates the key benefit of smoothing. We demonstrate the dramatic reduction in root mean-squared error (rMSE), indicating a better compromise between accuracy and stability for both smoothing approaches relative to the unsmoothed estimates. Finally, we provide an example of the RST's use. This example uses heart disease mortality data for North Carolina census tracts to map the RST output, including reliability of estimates, and demonstrates a subsequent statistical test.

Geographical access to electroconvulsive therapy services in Texas.

AIMS: Electroconvulsive Therapy (ECT) is a well-established and effective treatment in mood disorders but the use of ECT in Texas is much lower than the general average among the United States. Our goal is to explore the geographical accessibility of Electroconvulsive Services in Texas. METHODS: 22 ECT Centers in Texas listed in State's 2016 annual ECT report were enrolled and georeferenced. We used Esri's StreetMap Premium Network release 1 network dataset to generate 1-hour drive time service areas for these ECTs. We estimated populations within these service areas based on US Census Tract level population-weighted centroids; generated from the 2015, American Community Survey (ACS) estimates at the US Census Block Group level. RESULTS: About 75% (19,851,802 of 26,538,614) of Texas total population is within a 1-hour drive time to any ECT Services location. When focusing on population below the poverty level from 2015 Block Group level ACS data: 68% (3,046,141 of 4,472,451) are within a 1-hour drive time. CONCLUSIONS: ECT services are geographically accessible in Texas. Other barriers may contribute to lower use of ECT.

Access to Ophthalmologists in States Where Optometrists Have Expanded Scope of Practice.

Importance: As the United States considers how to best structure its health care services, specialty care availability is receiving increased focus. This study assesses whether patients lack reasonable access to ophthalmologists in states where optometrists have been granted expanded scope of practice. Objective: To determine the estimated travel time (ETT) to the nearest ophthalmologist office for persons residing in states that have expanded scope of practice for optometrists, and to quantify ETT to the nearest ophthalmologist for Medicare beneficiaries who received surgical care from optometrists in those states between 2008 and 2014. Design, Setting, and Participants: This study used data from the 2010 US census, a 2016 American Academy of Ophthalmology member database, and a data set of claims data for a random sample of 20% of beneficiaries enrolled in Medicare nationwide from 2008 to 2014 (n=14 063 725). Combining these sources with geographic information systems analysis, the ETT to the nearest ophthalmologist office was calculated for every resident of Kentucky, Oklahoma, and New Mexico. This study also assessed ETT to the nearest ophthalmologist for Medicare beneficiaries in those states who had received surgery from an optometrist from 2008 to 2014. Data analyses were conducted from July 2016 to July 2017. Main Outcomes and Measures: The proportion of residents of Kentucky, Oklahoma, and New Mexico who live within an ETT of 10, 30, 45, 60, or 90 minutes of the nearest ophthalmologist office. Results: The study included 4 339 367 Kentucky residents, 3 751 351 Oklahoma residents, and 2 059 179 New Mexico residents. Of these, 5 140 547 (50.6%) were female. Racial/ethnic composition included 7 154 847 people (70.5%) who were white, 640 608 (6.3%) who were black, and 1 418 246 (14.0%) who were Hispanic. The mean (SD) age was 37.8 (22.8) years. More than 75% of residents in the 3 states lived within an ETT of 30 minutes to the nearest ophthalmology office, and 94% to 99% of residents lived within an ETT of 60 minutes to the nearest ophthalmology office. Among Medicare beneficiaries who received surgery by optometrists, 58.3%, 51.1%, and 46.9% in Kentucky, Oklahoma, and New Mexico, respectively, lived within an ETT of 30 minutes from the nearest ophthalmologist office. Conclusions and Relevance: In the states where optometrists have expanded scope of practice, most residents lived within an ETT of 30 minutes of the nearest ophthalmologist office, as do half of Medicare beneficiaries who received surgical care from optometrists. These results can help inform policy makers when weighing the pros and cons of scope of practice expansion for optometrists.

Assessing Geographic Variation in Strabismus Diagnosis among Children Enrolled in Medicaid.

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.

Putting chronic disease on the map: building GIS capacity in state and local health departments.

Techniques based on geographic information systems (GIS) have been widely adopted and applied in the fields of infectious disease and environmental epidemiology; their use in chronic disease programs is relatively new. The Centers for Disease Control and Prevention's Division for Heart Disease and Stroke Prevention is collaborating with the National Association of Chronic Disease Directors and the University of Michigan to provide health departments with capacity to integrate GIS into daily operations, which support priorities for surveillance and prevention of chronic diseases. So far, 19 state and 7 local health departments participated in this project. On the basis of these participants' experiences, we describe our training strategy and identify high-impact GIS skills that can be mastered and applied over a short time in support of chronic disease surveillance. We also describe the web-based resources in the Chronic Disease GIS Exchange that were produced on the basis of this training and are available to anyone interested in GIS and chronic disease (www.cdc.gov/DHDSP/maps/GISX). GIS offers diverse sets of tools that promise increased productivity for chronic disease staff of state and local health departments.

Spatial modeling for groundwater arsenic levels in North Carolina.

To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area.