Evaluation of the positional difference between two common geocoding methods

Multicenter Analysis of Attrition from the Pediatric Tuberculosis Infection Care Cascade in Boston

OBJECTIVE

To characterize losses from the pediatric tuberculosis (TB) infection care cascade to identify ways to improve TB infection care delivery.

STUDY DESIGN

We conducted a retrospective cohort study of children (age <18 years) screened for TB within 2 Boston-area health systems between January 2017 and May 2019. Patients who received a tuberculin skin test (TST) and/or an interferon gamma release assay (IGRA) were included.

RESULTS

We included 13 353 tests among 11 622 patients; 93.9% of the tests were completed. Of 199 patients with positive tests for whom TB infection evaluation was clinically appropriate, 59.3% completed treatment or were recommended to not start treatment. Age 12-17 years (vs < 5 years; aOR 1.59; 95% CI, 1.32-1.92), non-English/non-Spanish language preference (vs English; aOR, 1.34; 95% CI, 1.02-1.76), and receipt of an IGRA (vs TST, aOR, 30.82; 95% CI, 21.92-43.34) were associated with increased odds of testing completion. Odds of testing completion decreased as census tract social vulnerability index quartile increased (ie, social vulnerability worsened; most vulnerable quartile vs least vulnerable quartile, aOR, 0.77; 95% CI, 0.60-0.99). Odds of completing treatment after starting treatment were higher in females (vs males; aOR, 2.35; 95% CI, 1.14-4.85) and were lower in patients starting treatment in a primary care clinic (vs TB/infectious diseases clinic; aOR, 0.44; 95% CI, 0.27-0.71).

CONCLUSIONS

Among children with a high proportion of negative TB infection tests, completion of testing was high, but completion of evaluation and treatment was moderate. Transitions toward IGRA testing will improve testing completion; interventions addressing social determinants of health are important to improve treatment completion.

Breathing Room: Industrial Zoning and Asthma Incidence Using School District Health Records in the City of Santa Ana, California

Background: Traffic and industrial emissions are associated with increased pediatric asthma morbidity. However, few studies have examined the influence of city industrial zoning on pediatric asthma outcomes among minoritized communities with limited access to air monitoring. Methods: In this cross-sectional analysis of 39,974 school-aged students in Santa Ana, CA, we investigated the effect of proximity to areas zoned for industrial use on pediatric asthma prevalence, physical fitness, school attendance, and standardized test scores. Results: The study population was 80.6% Hispanic, with 88.2% qualifying for free/reduced lunch. Compared to students living more than 1 km away from industrial zones, those living within 0.5 km had greater odds of having asthma (adjusted OR 1.21, 95% CI 1.09 to 1.34, p < 0.001). Among children with asthma, those living between 0.5−1.0 km had greater odds of being overweight or obese (aOR 1.47, 95% CI 1.00, 2.15, p = 0.047). Industrial zone proximity was not significantly associated with worse fitness and academic outcomes for students with asthma. Conclusion: These findings suggest that industrial zone proximity is associated with increased pediatric asthma in a predominantly Latino community in Southern California.

Uncertainty in geospatial health: challenges and opportunities ahead

PURPOSE

Uncertainty is not always well captured, understood, or modeled properly, and can bias the robustness of complex relationships, such as the association between the environment and public health through exposure, estimates of geographic accessibility and cluster detection, to name a few.

METHODS

We review current challenges and future opportunities as geospatial data and analyses are applied to the field of public health. We are particularly interested in the sources of uncertainty in geospatial data and how this uncertainty may propagate in spatial analysis.

RESULTS

We present opportunities to reduce the magnitude and impact of uncertainty. Specifically, we focus on (1) the use of multiple reference data sources to reduce geocoding errors, (2) the validity of online geocoders and how confidentiality (e.g., HIPAA) may be breached, (3) use of multiple reference data sources to reduce geocoding errors, (4) the impact of geoimputation techniques on travel estimates, (5) residential mobility and how it affects accessibility metrics and clustering, and (6) modeling errors in the American Community Survey. Our paper discusses how to communicate spatial and spatiotemporal uncertainty, and high-performance computing to conduct large amounts of simulations to ultimately increase statistical robustness for studies in public health.

CONCLUSIONS

Our paper contributes to recent efforts to fill in knowledge gaps at the intersection of spatial uncertainty and public health.

Assessment of spatial mobility among young men who have sex with men within and across high HIV prevalence neighborhoods in New York city: The P18 neighborhood study

The purpose of this study was to examine and quantify spatial mobility among HIV-negative young men who have sex with men (YMSM) within and across high prevalence HIV neighborhoods in New York City (NYC). We completed an analysis with global positioning system (GPS) and survey data to quantify spatial mobility for participants enrolled in the P18 Neighborhood Study (analytic n = 211; 83.4%). Spatial mobility was documented with self-reported survey data and objective GPS data, which was uncorrelated. Nearly one-quarter of participants (26.1%) said that they consider the neighborhood in which they currently live to differ from the neighborhood in which they had sex most frequently. In addition, 62.9% of participants' GPS points were recorded in NYC ZIP Code Tabulation Areas within the highest quartile of HIV prevalence. Future studies of YMSM populations should be conducted to examine how environments beyond the residential neighborhood can influence sexual health, which may guide HIV prevention services.

Evaluation of trauma resources in rural northern Alberta identifies opportunities for improvement

Background

The care of rural trauma patients in northern Alberta can be extremely challenging because of the vast geographic area, the limited access to health care facilities and the lack of adequate resources to manage severe injuries. Identifying gaps in equipment and personnel in rural centres can provide opportunities for improving the care of injured patients in these environments. We conducted a survey based on Canadian Accreditation Council quality indicators to evaluate trauma infrastructure and human resources in rural centres across northern Alberta.

Methods

A standardized survey was developed to assess the availability of trauma-specific equipment and personnel across the prehospital and emergency department (ED) settings. The survey was distributed to 50 peripheral hospitals biannually from January 2017 to September 2018. Two-tailed paired t tests were used to evaluate changes in survey responses; a p value of less than 0.05 was considered statistically significant.

Results

The survey response rate was 100%. By the end of the study period, there were significant improvements in the number of providers (p = 0.04), nurses (p = 0.01) and dedicated trauma resuscitation bays (p = 0.04) in the ED for managing injured patients. There were also significant increases in the availability of equipment, including advanced airway management tools (p = 0.02), rapid infusion devices (p = 0.02) and warmers (p = 0.04). Access to x-ray equipment (p = 0.03) and computed tomography (CT) scanners (p = 0.04) as well as equipment to support telehealth and teleconferencing (p = 0.04) increased during the study period. Access to, and supply of, blood products also increased significantly (p = 0.02) during the study period.

Conclusion

Our study demonstrates that the trauma resources of rural health care centres may be evaluated in a standardized fashion centres, and the results point to opportunities to remedy gaps in equipment and personnel. Our methods may be applied to any trauma network that serves geographically large areas with a sparse distribution of health care facilities, to provide critical information for the optimization of resources in rural trauma.

School proximity and census tract correlates of e-cigarette specialty retail outlets (vape shops) in central Texas

E-cigarettes are the most widely used tobacco product among middle and high school students in the United States. This study investigates the proximity of e-cigarette retail outlets (vape shops) to middle and high schools in Austin, Texas, as well as the sociodemographic determinants of outlet presence, at the census tract level. A proximity analysis was conducted using school geo-data derived from the Texas Education Agency and vape shop geo-data derived from a validated online search. Logistic regressions using 5-year estimates of the 2014 American Community Survey were performed to determine the correlates of vape shop presence in census tracts. Overall, 20% of the census tracts in Austin, Texas, had at least one vape shop. The proportion of vape shop-containing census tracts that met the criteria for classification as a “poverty area” (36.5%) was greater than that of vape shop-free census tracts (26.3%). Vape shops were more likely to be present in census tracts classified as poverty areas; however, the odds of vape shop presence declined as the percentage of the non-Hispanic Black population and the percentage of persons aged 10–14 years in census tracts increased. About 40% of the vape shops were located within 0.5 miles of a middle or high school. Sociodemographic disparities exist in the e-cigarette retail environment. In addition to the need to address the disparities identified in this study, our results showing the presence of vape shops within walkable distances of schools calls for tighter regulations and continued surveillance around the marketing practices of e-cigarette retailers.

Factors Associated with Duration of Overall Treatment Time for Cervical Cancer Treated with Definitive Chemoradiotherapy

Introduction

For women with intact cervical cancer treated by definitive chemoradiotherapy, the adverse impact of treatment prolongation is well-established. We aimed to identify potentially modifiable factors associated with the unwanted increase in the time required to complete the prescribed course of therapy.

Methods

We retrospectively examined treatment records of 104 consecutive cervical cancer patients receiving chemoradiation for cervical cancer, which included cervical high-dose-rate intracavitary brachytherapy performed at a single referral center. Association of factors, including distance to care, driving time, and income level with overall treatment time, was explored.

Results

Guideline-concordant treatment duration was achieved in 34% of cases. There was no significant correlation between treatment duration and any of the patient-related characteristics assessed in this study. Transitioning of the radiation oncology physician staffing at the brachytherapy center from a private practice non-integrated group to a large integrated group was associated with a decrease in mean overall treatment time, 61 vs. 68 days, p = 0.007.

Conclusions

We did not identify a modifiable patient-related factor amenable to a financial intervention. Administration of brachytherapy within an integrated system resulted in a shortened duration of the entire course of therapy for intact cervical cancer.

Location of Pre-exposure Prophylaxis Services Across New York City Neighborhoods: Do Neighborhood Socio-demographic Characteristics and HIV Incidence Matter?

Despite an increasing pre-exposure prophylaxis (PrEP) use among populations at highest risk of HIV acquisition, comprehensive and easy access to PrEP is limited among racial/ethnic minorities and low-income populations. The present study analyzed the geographic distribution of PrEP providers and the relationship between their location, neighborhood characteristics, and HIV incidence using spatial analytic methods. PrEP provider density, socio-demographics, healthcare availability, and HIV incidence data were collected by ZIP-code tabulation area in New York City (NYC). Neighborhood socio-demographic measures of race/ethnicity, income, insurance coverage, or same-sex couple household, were not associated with PrEP provider density, after adjusting for spatial autocorrelation, and PrEP providers were located in high HIV incidence neighborhoods (P < 0.01). These findings validate the need for ongoing policy interventions (e.g. public health detailing) vis-à-vis PrEP provider locations in NYC and inform the design of future PrEP implementation strategies, such as public health campaigns and navigation assistance for low-cost insurance.

GIScience and cancer: State of the art and trends for cancer surveillance and epidemiology

Maps are well recognized as an effective means of presenting and communicating health data, such as cancer incidence and mortality rates. These data can be linked to geographic features like counties or census tracts and their associated attributes for mapping and analysis. Such visualization and analysis provide insights regarding the geographic distribution of cancer and can be important for advancing effective cancer prevention and control programs. Applying a spatial approach allows users to identify location-based patterns and trends related to risk factors, health outcomes, and population health. Geographic information science (GIScience) is the discipline that applies Geographic Information Systems (GIS) and other spatial concepts and methods in research. This review explores the current state and evolution of GIScience in cancer research by addressing fundamental topics and issues regarding spatial data and analysis that need to be considered. GIScience, along with its health-specific application in the spatial epidemiology of cancer, incorporates multiple geographic perspectives pertaining to the individual, the health care infrastructure, and the environment. Challenges addressing these perspectives and the synergies among them can be explored through GIScience methods and associated technologies as integral parts of epidemiologic research, analysis efforts, and solutions. The authors suggest GIScience is a powerful tool for cancer research, bringing additional context to cancer data analysis and potentially informing decision-making and policy, ultimately aimed at reducing the burden of cancer.

Assessing the Reliability of Performing Citywide Chronic Disease Surveillance Using Emergency Department Data from Sentinel Hospitals

Given the inequalities in the distribution of disease burden, geographically detailed methods of disease surveillance are needed to identify local hot spots of chronic disease. However, few data sources include the patient-level addresses needed to perform these studies. Given that individual hospitals would have access to this geographically granular data, this study assessed the reliability of estimating chronic disease prevalence using emergency department surveillance at specific hospitals. Neighborhood-level diabetes, hypertension, and asthma prevalence were estimated using emergency claims data from each individual hospital in New York City from 2009-2012. Estimates were compared to prevalence obtained from a traditional health survey. A multivariable analysis also was performed to identify which individual hospitals were more accurate at estimating citywide disease prevalence. Among 52 hospitals, variation was found in the accuracy of disease prevalence estimates using emergency department surveillance. Estimates at some hospitals, such as NYU Langone Medical Center, had strong correlations for all diseases studied (diabetes: 0.81, hypertension: 0.84, and asthma: 0.84). Hospitals with patient populations geographically distributed throughout New York City had better accuracy in estimating citywide disease prevalence. For diabetes and hypertension, hospitals with racial/ethnic patient distributions similar to Census estimates and higher fidelity of diagnosis coding also had more accurate prevalence estimates. This study demonstrated how citywide chronic disease surveillance can be performed using emergency data from specific sentinel hospitals. The findings may provide an alternative means of mapping chronic disease burden by using existing data, which may be critical in regions without resources for geographically detailed health surveillance.

Accuracy of two geocoding methods for geographic information system-based exposure assessment in epidemiological studies

BACKGROUND

Environmental exposure assessment based on Geographic Information Systems (GIS) and study participants' residential proximity to environmental exposure sources relies on the positional accuracy of subjects' residences to avoid misclassification bias. Our study compared the positional accuracy of two automatic geocoding methods to a manual reference method.

METHODS

We geocoded 4,247 address records representing the residential history (1990-2008) of 1,685 women from the French national E3N cohort living in the Rhône-Alpes region. We compared two automatic geocoding methods, a free-online geocoding service (method A) and an in-house geocoder (method B), to a reference layer created by manually relocating addresses from method A (method R). For each automatic geocoding method, positional accuracy levels were compared according to the urban/rural status of addresses and time-periods (1990-2000, 2001-2008), using Chi Square tests. Kappa statistics were performed to assess agreement of positional accuracy of both methods A and B with the reference method, overall, by time-periods and by urban/rural status of addresses.

RESULTS

Respectively 81.4% and 84.4% of addresses were geocoded to the exact address (65.1% and 61.4%) or to the street segment (16.3% and 23.0%) with methods A and B. In the reference layer, geocoding accuracy was higher in urban areas compared to rural areas (74.4% vs. 10.5% addresses geocoded to the address or interpolated address level, p < 0.0001); no difference was observed according to the period of residence. Compared to the reference method, median positional errors were 0.0 m (IQR = 0.0-37.2 m) and 26.5 m (8.0-134.8 m), with positional errors <100 m for 82.5% and 71.3% of addresses, for method A and method B respectively. Positional agreement of method A and method B with method R was 'substantial' for both methods, with kappa coefficients of 0.60 and 0.61 for methods A and B, respectively.

CONCLUSION

Our study demonstrates the feasibility of geocoding residential addresses in epidemiological studies not initially recorded for environmental exposure assessment, for both recent addresses and residence locations more than 20 years ago. Accuracy of the two automatic geocoding methods was comparable. The in-house method (B) allowed a better control of the geocoding process and was less time consuming.

Quantifying spatial misclassification in exposure to noise complaints among low-income housing residents across New York City neighborhoods: a Global Positioning System (GPS) study

PURPOSE

To examine if there was spatial misclassification in exposure to neighborhood noise complaints among a sample of low-income housing residents in New York City, comparing home-based spatial buffers and Global Positioning System (GPS) daily path buffers.

METHODS

Data came from the community-based NYC Low-Income Housing, Neighborhoods and Health Study, where GPS tracking of the sample was conducted for a week (analytic n = 102). We created a GPS daily path buffer (a buffering zone drawn around GPS tracks) of 200 m and 400 m. We also used home-based buffers of 200 m and 400 m. Using these "neighborhoods" (or exposure areas), we calculated neighborhood exposure to noisy events from 311 complaints data (analytic n = 143,967). Friedman tests (to compare overall differences in neighborhood definitions) were applied.

RESULTS

There were differences in neighborhood noise complaints according to the selected neighborhood definitions (P < .05). For example, the mean neighborhood noise complaint count was 1196 per square kilometer for the 400-m home-based and 812 per square kilometer for the 400-m activity space buffer, illustrating how neighborhood definition influences the estimates of exposure to neighborhood noise complaints.

CONCLUSIONS

These analyses suggest that, whenever appropriate, GPS neighborhood definitions can be used in spatial epidemiology research in spatially mobile populations to understand people's lived experience.

Local spatial clustering in youths' use of tobacco, alcohol, and marijuana in Boston

BACKGROUND

Understanding geographic variation in youth drug use is important for both identifying etiologic factors and planning prevention interventions. However, little research has examined spatial clustering of drug use among youths by using rigorous statistical methods.

OBJECTIVES

The purpose of this study was to examine spatial clustering of youth use of tobacco, alcohol, and marijuana.

METHODS

Responses on tobacco, alcohol, and marijuana use from 1,292 high school students ages 13-19 who provided complete residential addresses were drawn from the 2008 Boston Youth Survey Geospatial Dataset. Response options on past month use included "none," "1-2," "3-9," and "10 or more." The response rate for each substance was approximately 94%. Spatial clustering of youth drug use was assessed using the spatial Bernoulli model in the SatScan™ software package.

RESULTS

Approximately 12%, 36%, and 18% of youth reported any past-month use of tobacco, alcohol, and/or marijuana, respectively. Two clusters of elevated past tobacco use among Boston youths were generated, one of which was statistically significant. This cluster, located in the South Boston neighborhood, had a relative risk of 5.37 with a p-value of 0.00014. There was no significant localized spatial clustering in youth past alcohol or marijuana use in either the unadjusted or adjusted models.

CONCLUSION

Significant spatial clustering in youth tobacco use was found. Finding a significant cluster in the South Boston neighborhood provides reason for further investigation into neighborhood characteristics that may shape adolescents' substance use behaviors. This type of research can be used to evaluate the underlying reasons behind spatial clustering of youth substance and to target local drug abuse prevention interventions and use.

Change in alcohol outlet density and alcohol-related harm to population health (CHALICE): a comprehensive record-linked database study in Wales

Background

Excess alcohol consumption has serious adverse effects on health and results in violence-related harm.

Objective

This study investigated the impact of change in community alcohol availability on alcohol consumption and alcohol-related harms to health, assessing the effect of population migration and small-area deprivation.

Design

A natural experiment of change in alcohol outlet density between 2006 and 2011 measured at census Lower Layer Super Output Area level using observational record-linked data.

Setting

Wales, UK; population of 2.5 million aged ≥ 16 years.

Outcome measures

Alcohol consumption, alcohol-related hospital admissions, accident and emergency (A&E) department attendances from midnight to 06.00 and violent crime against the person.

Data sources

Licensing Act 2003 [Great Britain.Licensing Act 2003. London: The Stationery Office; 2003. URL:www.legislation.gov.uk/ukpga/2003/17/contents(accessed 8 June 2015)] data on alcohol outlets held by the 22 local authorities in Wales, alcohol consumption data from annual Welsh Health Surveys 2008–12, hospital admission data 2006–11 from the Patient Episode Database for Wales (PEDW) and A&E attendance data 2009–11 were anonymously record linked to the Welsh Demographic Service age–sex register within the Secure Anonymised Information Linkage Databank. A final data source was recorded crime 2008–11 from the four police forces in Wales.

Methods

Outlet density was estimated (1) as the number of outlets per capita for the 2006 static population and the per quarterly updated population to assess the impact of population migration and (2) using new methods of network analysis of distances between each household and alcohol outlets within 10 minutes of walking and driving. Alcohol availability was measured by three variables: (1) the previous quarterly value; (2) positive and negative change over the preceding five quarters; and (3) volatility, a measure of absolute quarterly changes during the preceding five quarters. Longitudinal statistical analysis used multilevel Poisson models of consumption and Geographically Weighted Regression (GWR) spatial models of binge drinking, Cox regression models of hospital admissions and A&E attendance and GWR models of violent crime against the person, each as a function of alcohol availability adjusting for confounding variables. The impact on health inequalities was investigated by stratifying models within quintiles of the Welsh Index of Multiple Deprivation.

Results

The main finding was that change in walking outlet density was associated with alcohol-related harms: consumption, hospital admissions and violent crime against the person each tracked the quarterly changes in outlet density. Alcohol-related A&E attendances were not clinically coded and the association was less conclusive. In general, social deprivation was strongly associated with the outcome measures but did not substantially modify the associations between the outcomes and alcohol availability. We found no evidence for an important effect of population migration.

Limitations

Limitations included the absence of any standardised methods of alcohol outlet data collation, processing and validation, and incomplete data on on-sales and off-sales. We were dependent on the quality of clinical coding and administrative records and could not identify alcohol-related attendances in the A&E data set.

Conclusion

This complex interdisciplinary study found that important alcohol-related harms were associated with change in alcohol outlet density. Future work recommendations include defining a research standard for recording outlet data and classification of outlet type, the methodological development of residence-based density measures and a health economic analysis of model-predicted harms.

Funding

The National Institute for Health Research Public Health Research programme. Additional technical and computing support was provided by the Farr Institute at Swansea University, made possible by the following grant:

Centre for the Improvement of Population Health through E-records Research (CIPHER) and Farr Institute capital enhancement. CIPHER and the Farr Institute are funded by Arthritis Research UK, the British Heart Foundation, Cancer Research UK, the Chief Scientist Office (Scottish Government Health Directorates), the Economic and Social Research Council, the Engineering and Physical Sciences Research Council, the Medical Research Council, the National Institute for Health Research, the National Institute for Social Care and Health Research (Welsh Government) and the Wellcome Trust (grant reference MR/K006525/1).

Rationale, Design and Methods of the Ecological Study of Sexual Behaviors and HIV/STI among African American Men Who Have Sex with Men in the Southeastern United States (The MARI Study)

BACKGROUND

This paper describes the rationale, design, and methodology of the Ecological Study of Sexual Behaviors and HIV/STI among African American Men Who Have Sex with Men (MSM) in the Southeastern United States (U.S.; known locally simply as the MARI Study).

METHODS

Participants are African American MSM aged 18 years and older residing in the deep South.

RESULTS

Between 2013 and 2015, 800 African American MSM recruited from two study sites (Jackson, MS and Atlanta, GA) will undergo a 1.5-hour examination to obtain anthropometric and blood pressure measures as well as to undergo testing for sexually transmitted infections (STI), including HIV. Intrapersonal, interpersonal, and environmental factors are assessed by audio computer-assisted self-interview survey. Primary outcomes include sexual risk behaviors (e.g., condomless anal sex) and prevalent STIs (HIV, syphilis, gonorrhea, and Chlamydia).

CONCLUSION

The MARI Study will typify the HIV environmental 'riskscape' and provide empirical evidence into novel ecological correlates of HIV risk among African American MSM in the deep South, a population most heavily impacted by HIV. The study's anticipated findings will be of interest to a broad audience and lead to more informed prevention efforts, including effective policies and interventions, that achieve the goals of the updated 2020 U.S. National HIV/AIDS Strategy.

A Mixed Methods Comparison of Urban and Rural Retail Corner Stores

Efforts to transform corner stores to better meet community dietary needs have mostly occurred in urban areas but are also needed in rural areas. Given important contextual differences between urban and rural areas, it is important to increase our understanding of the elements that might translate successfully to similar interventions involving stores in more rural areas. Thus, an in-depth examination and comparison of corner stores in each setting is needed. A mixed methods approach, including windshield tours, spatial visualization with analysis of frequency distribution, and spatial regression techniques were used to compare a rural North Carolina and large urban (Los Angeles) food environment. Important similarities and differences were seen between the two settings in regards to food environment context, spatial distribution of stores, food products available, and the factors predicting corner store density. Urban stores were more likely to have fresh fruits (Pearson chi2 = 27.0423; p < 0.001) and vegetables (Pearson chi2 = 27.0423; p < 0.001). In the urban setting, corner stores in high income areas were more likely to have fresh fruit (Pearson chi2 = 6.00; p = 0.014), while in the rural setting, there was no difference between high and low income area in terms of fresh fruit availability. For the urban area, total population, no vehicle and Hispanic population were significantly positively associated (p < 0.05), and median household income (p < 0.001) and Percent Minority (p < 0.05) were significantly negatively associated with corner store count. For the rural area, total population (p < 0.05) and supermarket count were positively associated (p < 0.001), and median household income negatively associated (P < 0.001), with corner store count. Translational efforts should be informed by these findings, which might influence the success of future interventions and policies in both rural and urban contexts.

The role of neighborhood characteristics in racial/ethnic disparities in type 2 diabetes: results from the Boston Area Community Health (BACH) Survey

Racial/ethnic disparities in the prevalence of type 2 diabetes mellitus (T2DM) are well documented and until recently, research has focused almost exclusively on individual-based determinants as potential contributors to these disparities (health behaviors, biological/genetic factors, and individual-level socio-demographics). Research on the role of neighborhood characteristics in relation to racial/ethnic disparities in T2DM is very limited. Therefore, the aim of this research is to identify and estimate the contribution of specific aspects of neighborhoods that may be associated with racial/ethnic disparities in T2DM. Data from the Boston Area Community Health III Survey (N = 2764) was used in this study, which is a community-based random-sample survey of adults in Boston, Massachusetts from three racial/ethnic groups (Black, Hispanic, and White). We applied two-level random intercepts logistic regression to assess the associations between race/ethnicity, neighborhood characteristics (census tract socioeconomic status, racial composition, property and violent crime, open space, geographic proximity to grocery stores, convenience stores, and fast food, and neighborhood disorder) and prevalent T2DM (fasting glucose > 125 mg/dL, HbA1c ≥ 6.5%, or self-report of a T2DM diagnosis). Black and Hispanic participants had 2.89 times and 1.48 times the odds of T2DM as White participants, respectively. Multilevel models indicated a significant between-neighborhood variance estimate of 0.943, providing evidence of neighborhood variation. Individual demographics (race/ethnicity, age and gender) explained 22.3% of the neighborhood variability in T2DM. The addition of neighborhood-level variables to the model had very little effect on the magnitude of the racial/ethnic disparities and on the between-neighborhood variability. For example, census tract poverty explained less than 1% and 6% of the excess odds of T2DM among Blacks and Hispanics and only 1.8% of the neighborhood variance in T2DM. While the findings of this study overall suggest that neighborhood factors are not a major contributor to racial/ethnic disparities in T2DM, further research is needed including data from other geographic locations.

Neighborhood-Level LGBT Hate Crimes and Bullying Among Sexual Minority Youths: A Geospatial Analysis

The goal of this study was to evaluate a novel measure of environmental risk factors for bullying among sexual minority youths. Data on lesbian, gay, bisexual, and transgender (LGBT) assault hate crimes were obtained from police records, geocoded, and then linked to individual-level data on bullying and sexual orientation from the 2008 Boston Youth Survey Geospatial Dataset (N = 1,292; 108 sexual minorities). Results indicated that sexual minority youths who reported relational and electronic bullying were more likely to reside in neighborhoods with higher LGBT assault hate crime rates. There was no asso- ciation between LGBT assault hate crimes and bullying among heterosexual youths, pro- viding evidence for specificity to sexual minority youth. Moreover, no relationships were observed between sexual minority bullying and neighborhood-level violent and property crimes, indicating that the results were specific to LGBT assault hate crimes.

Examination of spatial polygamy among young gay, bisexual, and other men who have sex with men in New York City: the P18 cohort study

The few previous studies examining the influence of the neighborhood context on health and health behavior among young gay, bisexual, and other men who have sex with men (YMSM) have predominantly focused on residential neighborhoods. No studies have examined multiple neighborhood contexts among YMSM or the relationships between sociodemographic characteristics, psychosocial factors, social support network characteristics, health behaviors, and neighborhood concordance. In this study, we assessed spatial polygamy by determining the amount of concordance between residential, social, and sex neighborhoods (defined as boroughs) in addition to examining individual-level characteristics that may be associated with neighborhood concordance. These data come from the baseline assessment of Project 18, a cohort of racially and ethnically diverse YMSM residing in the New York City metropolitan area. Participants (N = 598) provided information on their residential, social, and sex boroughs as well as information on their sociodemographic characteristics, psychosocial factors, social support network characteristics, and health behaviors (e.g., substance use and condomless sex). Descriptive analyses were conducted to examine the distribution of boroughs reported across all three contexts, i.e., residential, social, and sex boroughs. Next, concordance between: (1) residential and social boroughs; (2) residential and sex boroughs; (3) social and sex boroughs; and (4) residential, social, and sex boroughs was assessed. Finally, bivariable analyses were conducted to examine the relationships between sociodemographic characteristics, psychosocial factors, social support network characteristics, and health behaviors in relation to borough concordance. Approximately two-thirds of participants reported concordance between residential/socializing, residential/sex, and sex/socializing boroughs, whereas 25% reported concordance between all three residential/socializing/sex boroughs. Borough concordance varied by some individual-level characteristics. For example, White YMSM and YMSM reporting lower perceived socioeconomic status were significantly more likely to report residential/socializing/sex borough concordance (p < 0.001). With regard to psychosocial factors, YMSM who reported experiencing gay-related stigma in public forums were more likely to report discordant socializing/sex and residential/socializing/sex boroughs (p < 0.001). Greater frequency of communication with network members (≥weekly) was associated with less residential/social borough concordance (p < 0.05). YMSM who reported residential/socializing/sex borough concordance were more likely to report recent (last 30 days) alcohol use, recent marijuana use, and recently engaging in condomless oral sex (all p < 0.05). These findings suggest that spatial polygamy, or an individual moving across and experiencing multiple neighborhood contexts, is prevalent among urban YMSM and that spatial polygamy varies by multiple individual-level characteristics. Future research among YMSM populations should consider multiple neighborhood contexts in order to provide a more nuanced understanding of how and which neighborhood contexts influence the health and well-being of YMSM. This further examination of spatial polygamy (and individual-level characteristics associated with it) may increase understanding of the most appropriate locations for targeted disease prevention and health promotion interventions (e.g., HIV prevention interventions).

Geocoding large population-level administrative datasets at highly resolved spatial scales

Using geographic information systems to link administrative databases with demographic, social, and environmental data allows researchers to use spatial approaches to explore relationships between exposures and health. Traditionally, spatial analysis in public health has focused on the county, zip code, or tract level because of limitations to geocoding at highly resolved scales. Using 2005 birth and death data from North Carolina, we examine our ability to geocode population-level datasets at three spatial resolutions - zip code, street, and parcel. We achieve high geocoding rates at all three resolutions, with statewide street geocoding rates of 88.0% for births and 93.2% for deaths. We observe differences in geocoding rates across demographics and health outcomes, with lower geocoding rates in disadvantaged populations and the most dramatic differences occurring across the urban-rural spectrum. Our results suggest highly resolved spatial data architectures for population-level datasets are viable through geocoding individual street addresses. We recommend routinely geocoding administrative datasets to the highest spatial resolution feasible, allowing public health researchers to choose the spatial resolution used in analysis based on an understanding of the spatial dimensions of the health outcomes and exposures being investigated. Such research, however, must acknowledge how disparate geocoding success across subpopulations may affect findings.

A comparison between self-reported and GIS-based proxies of residential exposure to environmental pollution in a case-control study on lung cancer

In epidemiological studies both questionnaire results and GIS modeling have been used to assess exposure to environmental risk factors. Nevertheless, few studies have used both these techniques to evaluate the degree of agreement between different exposure assessment methodologies. As part of a case-control study on lung cancer, we present a comparison between self-reported and GIS-derived proxies of residential exposure to environmental pollution. 649 subjects were asked to fill out a questionnaire and give information about residential history and perceived exposure. Using GIS, for each residence we evaluated land use patterns, proximity to major roads and exposure to industrial pollution. We then compared the GIS exposure-index values among groups created on the basis of questionnaire responses. Our results showed a relatively high agreement between the two methods. Although none of these methods is the "exposure gold standard", understanding similarities, weaknesses and strengths of each method is essential to strengthen epidemiological evidence.

Ensuring Confidentiality of Geocoded Health Data: Assessing Geographic Masking Strategies for Individual-Level Data

Public health datasets increasingly use geographic identifiers such as an individual's address. Geocoding these addresses often provides new insights since it becomes possible to examine spatial patterns and associations. Address information is typically considered confidential and is therefore not released or shared with others. Publishing maps with the locations of individuals, however, may also breach confidentiality since addresses and associated identities can be discovered through reverse geocoding. One commonly used technique to protect confidentiality when releasing individual-level geocoded data is geographic masking. This typically consists of applying a certain amount of random perturbation in a systematic manner to reduce the risk of reidentification. A number of geographic masking techniques have been developed as well as methods to quantity the risk of reidentification associated with a particular masking method. This paper presents a review of the current state-of-the-art in geographic masking, summarizing the various methods and their strengths and weaknesses. Despite recent progress, no universally accepted or endorsed geographic masking technique has emerged. Researchers on the other hand are publishing maps using geographic masking of confidential locations. Any researcher publishing such maps is advised to become familiar with the different masking techniques available and their associated reidentification risks.

Lesbian, gay, bisexual, and transgender hate crimes and suicidality among a population-based sample of sexual-minority adolescents in Boston

OBJECTIVES

We examined whether past-year suicidality among sexual-minority adolescents was more common in neighborhoods with a higher prevalence of hate crimes targeting lesbian, gay, bisexual, and transgender (LGBT) individuals.

METHODS

Participants' data came from a racially/ethnically diverse population-based sample of 9th- through 12th-grade public school students in Boston, Massachusetts (n = 1292). Of these, 108 (8.36%) reported a minority sexual orientation. We obtained data on LGBT hate crimes involving assaults or assaults with battery between 2005 and 2008 from the Boston Police Department and linked the data to the adolescent's residential address.

RESULTS

Sexual-minority youths residing in neighborhoods with higher rates of LGBT assault hate crimes were significantly more likely to report suicidal ideation (P = .013) and suicide attempts (P = .006), than were those residing in neighborhoods with lower LGBT assault hate crime rates. We observed no relationships between overall neighborhood-level violent and property crimes and suicidality among sexual-minority adolescents (P > .05), providing evidence for specificity of the results to LGBT assault hate crimes.

CONCLUSIONS

Neighborhood context (i.e., LGBT hate crimes) may contribute to sexual-orientation disparities in adolescent suicidality, highlighting potential targets for community-level suicide-prevention programs.

An evaluation framework for comparing geocoding systems

BACKGROUND

Geocoding, the process of converting textual information describing a location into one or more digital geographic representations, is a routine task performed at large organizations and government agencies across the globe. In a health context, this task is often a fundamental first step performed prior to all operations that take place in a spatially-based health study. As such, the quality of the geocoding system used within these agencies is of paramount concern to the agency (the producer) and researchers or policy-makers who wish to use these data (consumers). However, geocoding systems are continually evolving with new products coming on the market continuously. Agencies must develop and use criteria across a number axes when faced with decisions about building, buying, or maintaining any particular geocoding systems. To date, published criteria have focused on one or more aspects of geocode quality without taking a holistic view of a geocoding system's role within a large organization. The primary purpose of this study is to develop and test an evaluation framework to assist a large organization in determining which geocoding systems will meet its operational needs.

METHODS

A geocoding platform evaluation framework is derived through an examination of prior literature on geocoding accuracy. The framework developed extends commonly used geocoding metrics to take into account the specific concerns of large organizations for which geocoding is a fundamental operational capability tightly-knit into its core mission of processing health data records. A case study is performed to evaluate the strengths and weaknesses of five geocoding platforms currently available in the Australian geospatial marketplace.

RESULTS

The evaluation framework developed in this research is proven successful in differentiating between key capabilities of geocoding systems that are important in the context of a large organization with significant investments in geocoding resources. Results from the proposed methodology highlight important differences across all axes of geocoding system comparisons including spatial data output accuracy, reference data coverage, system flexibility, the potential for tight integration, and the need for specialized staff and/or development time and funding. Such results can empower decisions-makers within large organizations as they make decisions and investments in geocoding systems.

Impact of geocoding methods on associations between long-term exposure to urban air pollution and lung function

BACKGROUND

Errors in address geocodes may affect estimates of the effects of air pollution on health.

OBJECTIVE

We investigated the impact of four geocoding techniques on the association between urban air pollution estimated with a fine-scale (10 m × 10 m) dispersion model and lung function in adults.

METHODS

We measured forced expiratory volume in 1 sec (FEV1) and forced vital capacity (FVC) in 354 adult residents of Grenoble, France, who were participants in two well-characterized studies, the Epidemiological Study on the Genetics and Environment on Asthma (EGEA) and the European Community Respiratory Health Survey (ECRHS). Home addresses were geocoded using individual building matching as the reference approach and three spatial interpolation approaches. We used a dispersion model to estimate mean PM10 and nitrogen dioxide concentrations at each participant's address during the 12 months preceding their lung function measurements. Associations between exposures and lung function parameters were adjusted for individual confounders and same-day exposure to air pollutants. The geocoding techniques were compared with regard to geographical distances between coordinates, exposure estimates, and associations between the estimated exposures and health effects.

RESULTS

Median distances between coordinates estimated using the building matching and the three interpolation techniques were 26.4, 27.9, and 35.6 m. Compared with exposure estimates based on building matching, PM10 concentrations based on the three interpolation techniques tended to be overestimated. When building matching was used to estimate exposures, a one-interquartile range increase in PM10 (3.0 μg/m3) was associated with a 3.72-point decrease in FVC% predicted (95% CI: -0.56, -6.88) and a 3.86-point decrease in FEV1% predicted (95% CI: -0.14, -3.24). The magnitude of associations decreased when other geocoding approaches were used [e.g., for FVC% predicted -2.81 (95% CI: -0.26, -5.35) using NavTEQ, or 2.08 (95% CI -4.63, 0.47, p = 0.11) using Google Maps].

CONCLUSIONS

Our findings suggest that the choice of geocoding technique may influence estimated health effects when air pollution exposures are estimated using a fine-scale exposure model.

A review of exposure assessment methods in epidemiological studies on incinerators

Incineration is a common technology for waste disposal, and there is public concern for the health impact deriving from incinerators. Poor exposure assessment has been claimed as one of the main causes of inconsistency in the epidemiological literature. We reviewed 41 studies on incinerators published between 1984 and January 2013 and classified them on the basis of exposure assessment approach. Moreover, we performed a simulation study to explore how the different exposure metrics may influence the exposure levels used in epidemiological studies. 19 studies used linear distance as a measure of exposure to incinerators, 11 studies atmospheric dispersion models, and the remaining 11 studies a qualitative variable such as presence/absence of the source. All reviewed studies utilized residence as a proxy for population exposure, although residence location was evaluated with different precision (e.g., municipality, census block, or exact address). Only one study reconstructed temporal variability in exposure. Our simulation study showed a notable degree of exposure misclassification caused by the use of distance compared to dispersion modelling. We suggest that future studies (i) make full use of pollution dispersion models; (ii) localize population on a fine-scale; and (iii) explicitly account for the presence of potential environmental and socioeconomic confounding.

Investigating impacts of positional error on potential health care accessibility

Accessibility to health services at the local or community level is an effective approach to measuring health care delivery in various constituencies in Canada and the United States. GIS and spatial methods play an important role in measuring potential access to health services. The Three-Step Floating Catchment Area (3SFCA) method is a GIS based procedure developed to calculate potential (spatial) accessibility as a ratio of primary health care (PHC) providers to the surrounding population in urban settings. This method uses PHC provider locations in textual/address format supplied by local, regional, or national health authorities. An automated geocoding procedure is normally used to convert such addresses to a pair of geographic coordinates. The accuracy of geocoding depends on the type of reference data and the amount of value-added effort applied. This research investigates the success and accuracy of six geocoding methods as well as how geocoding error affects the 3SFCA method. ArcGIS software is used for geocoding and spatial accessibility estimation. Results will focus on two implications of geocoding: (1) the success and accuracy of different automated and value-added geocoding; and (2) the implications of these geocoding methods for GIS-based methods that generalise results based on location data.

Spatial error in geocoding physician location data from the AMA Physician Masterfile: implications for spatial accessibility analysis

The accuracy of geocoding hinges on the quality of address information that serves as input to the geocoding process; however errors associated with poor address quality are rarely studied. This paper examines spatial errors that arise due to incorrect address information with respect to physician location data in the United States. Studies of spatial accessibility to physicians in the U.S. typically rely on data from the American Medical Association's Physician Masterfile. These data are problematic because a substantial proportion of physicians only report a mailing address, which is often the physician's home (residential) location, rather than the address for the location where health care is provided. The incorrect geocoding of physicians' practice locations based on inappropriate address information results in a form of geocoding error that has not been widely analyzed. Using data for the Chicago metropolitan region, we analyze the extent and implications of geocoding error for measurement of spatial accessibility to primary care physicians. We geocode the locations of primary care physicians based on mailing addresses and office addresses. The spatial mismatch between the two is computed at the county, zip code and point location scales. Although mailing and office address locations are quite close for many physicians, they are far apart (>20 km) for a substantial minority. Kernel density estimation is used to characterize the spatial distribution of physicians based on office and mailing addresses and to identify areas of high spatial mismatch between the two. Errors are socially and geographically uneven, resulting in overestimation of physician supply in some high-income suburban communities, and underestimation in certain central city locations where health facilities are concentrated. The resulting errors affect local measures of spatial accessibility to primary care, biasing statistical analyses of the associations between spatial access to care and health outcomes.

Validation of walk score for estimating neighborhood walkability: an analysis of four US metropolitan areas

Neighborhood walkability can influence physical activity. We evaluated the validity of Walk Score^® for assessing neighborhood walkability based on GIS (objective) indicators of neighborhood walkability with addresses from four US metropolitan areas with several street network buffer distances (i.e., 400-, 800-, and 1,600-meters). Address data come from the YMCA-Harvard After School Food and Fitness Project, an obesity prevention intervention involving children aged 5–11 years and their families participating in YMCA-administered, after-school programs located in four geographically diverse metropolitan areas in the US (n = 733). GIS data were used to measure multiple objective indicators of neighborhood walkability. Walk Scores were also obtained for the participant’s residential addresses. Spearman correlations between Walk Scores and the GIS neighborhood walkability indicators were calculated as well as Spearman correlations accounting for spatial autocorrelation. There were many significant moderate correlations between Walk Scores and the GIS neighborhood walkability indicators such as density of retail destinations and intersection density (p < 0.05). The magnitude varied by the GIS indicator of neighborhood walkability. Correlations generally became stronger with a larger spatial scale, and there were some geographic differences. Walk Score^® is free and publicly available for public health researchers and practitioners. Results from our study suggest that Walk Score^® is a valid measure of estimating certain aspects of neighborhood walkability, particularly at the 1600-meter buffer. As such, our study confirms and extends the generalizability of previous findings demonstrating that Walk Score is a valid measure of estimating neighborhood walkability in multiple geographic locations and at multiple spatial scales.