Measuring Local-Area Racial Segregation for Medicare Hospital Admissions.

Importance: Considerable racial segregation exists in US hospitals that cannot be explained by where patients live. Approaches to measuring such segregation are limited. Objective: To measure how and where sorting of older Black patients to different hospitals occurs within the same health care market. Design, Setting, and Participants: This retrospective cross-sectional study used 2019 Medicare claims data linked to geographic data. Hospital zip code markets were based on driving time. The local hospital segregation (LHS) index was defined as the difference between the racial composition of a hospital's admissions and the racial composition of the hospital's market. Assessed admissions were among US Medicare fee-for-service enrollees aged 65 or older living in the 48 contiguous states with at least 1 hospitalization in 2019 at a hospital with at least 200 hospitalizations. Data were analyzed from November 2022 to January 2024. Exposure: Degree of residential segregation, ownership status, region, teaching hospital designation, and disproportionate share hospital status. Main Outcomes and Measures: The LHS index by hospital and a regional LHS index by hospital referral region. Results: In the sample of 1991 acute care hospitals, 4 870 252 patients (mean [SD] age, 77.7 [8.3] years; 2 822 006 [56.0%] female) were treated, including 11 435 American Indian or Alaska Native patients (0.2%), 129 376 Asian patients (2.6%), 597 564 Black patients (11.9%), 395 397 Hispanic patients (7.8), and 3 818 371 White patients (75.8%). In the sample, half of hospitalizations among Black patients occurred at 235 hospitals (11.8% of all hospitals); 878 hospitals (34.4%) exhibited a negative LHS score (ie, admitted fewer Black patients relative to their market area) while 1113 hospitals (45.0%) exhibited a positive LHS (ie, admitted more Black patients relative to their market area); of all hospitals, 79.4% exhibited racial admission patterns significantly different from their market. Hospital-level LHS was positively associated with government hospital status (coefficient, 0.24; 95% CI, 0.10 to 0.38), while New York, New York; Chicago, Illinois; and Detroit, Michigan, hospital referral regions exhibited the highest regional LHS measures, with hospital referral region LHS scores of 0.12, 0.16, and 0.21, respectively. Conclusions and Relevance: In this cross-sectional study, a novel measure of LHS was developed to quantify the extent to which hospitals were admitting a representative proportion of Black patients relative to their market areas. A better understanding of hospital choice within neighborhoods would help to reduce racial inequities in health outcomes.

Residential Redlining, Neighborhood Trajectory, and Equity of Breast and Colorectal Cancer Care.

OBJECTIVE: This study aimed to determine the influence of structural racism, vis-à-vis neighborhood socioeconomic trajectory, on colorectal and breast cancer diagnosis and treatment. SUMMARY BACKGROUND DATA: Inequities in cancer care are well documented in the United States but less is understood about how historical policies like residential redlining and evolving neighborhood characteristics influence current gaps in care. METHODS: This retrospective cohort study included adult patients diagnosed with colorectal or breast cancer between 2010 and 2015 in 7 Indiana cities with available historic redlining data. Current neighborhood socioeconomic status was determined by the Area Deprivation Index (ADI). Based on historic redlining maps and current ADI, we created four "Neighborhood Trajectory" categories: Advantage Stable, Advantage Reduced, Disadvantage Stable, Disadvantage Reduced. Modified Poisson regression models estimated the relative risks (RR) of Neighborhood Trajectory on cancer stage at diagnosis and receipt of cancer-directed surgery (CDS). RESULTS: A final cohort derivation identified 4,862 cancer patients with colorectal or breast cancer. Compared to Advantage Stable neighborhoods, Disadvantage Stable neighborhood was associated with late-stage diagnosis for both colorectal and breast cancer (RR=1.30 [95% CI=1.05 - 1.59]; RR=1.41 [1.09 - 1.83], respectively). Black patients had lower likelihood of receiving CDS in Disadvantage Reduced neighborhoods (RR=0.92 [0.86 - 0.99]) than White patients. CONCLUSIONS: Disadvantage Stable neighborhoods were associated with late-stage diagnosis for breast and colorectal cancer. Disadvantage Reduced (gentrified) neighborhoods were associated with racial-inequity in CDS. Improved neighborhood socioeconomic conditions may improve timely diagnosis but could contribute to racial inequities in surgical treatment.

Cancer Epidemiology in the Northeastern United States (2013-2017).

We tested the hypotheses that adult cancer incidence and mortality in the Northeast region and in Northern New England (NNE) were different than the rest of the United States, and described other related cancer metrics and risk factor prevalence. Using national, publicly available cancer registry data, we compared cancer incidence and mortality in the Northeast region with the United States and NNE with the United States overall and by race/ethnicity, using age-standardized cancer incidence and rate ratios (RR). Compared with the United States, age-adjusted cancer incidence in adults of all races combined was higher in the Northeast (RR, 1.07; 95% confidence interval [CI] 1.07-1.08) and in NNE (RR 1.06; CI 1.05-1.07). However compared with the United States, mortality was lower in the Northeast (RR, 0.98; CI 0.98-0.98) but higher in NNE (RR, 1.05; CI 1.03-1.06). Mortality in NNE was higher than the United States for cancers of the brain (RR, 1.16; CI 1.07-1.26), uterus (RR, 1.32; CI 1.14-1.52), esophagus (RR, 1.36; CI 1.26-1.47), lung (RR, 1.12; CI 1.09-1.15), bladder (RR, 1.23; CI 1.14-1.33), and melanoma (RR, 1.13; CI 1.01-1.27). Significantly higher overall cancer incidence was seen in the Northeast than the United States in all race/ethnicity subgroups except Native American/Alaska Natives (RR, 0.68; CI 0.64-0.72). In conclusion, NNE has higher cancer incidence and mortality than the United States, a pattern that contrasts with the Northeast region, which has lower cancer mortality overall than the United States despite higher incidence. Significance: These findings highlight the need to identify the causes of higher cancer incidence in the Northeast and the excess cancer mortality in NNE.

A Survey of Cancer Risk Behaviors, Beliefs, and Social Drivers of Health in New Hampshire and Vermont.

Compared with urban areas, rural areas have higher cancer mortality and have experienced substantially smaller declines in cancer incidence in recent years. In a New Hampshire (NH) and Vermont (VT) survey, we explored the roles of rurality and educational attainment on cancer risk behaviors, beliefs, and other social drivers of health. In February-March 2022, two survey panels in NH and VT were sent an online questionnaire. Responses were analyzed by rurality and educational attainment. Respondents (N = 1,717, 22%) mostly lived in rural areas (55%); 45% of rural and 25% of urban residents had high school education or less and this difference was statistically significant. After adjustment for rurality, lower educational attainment was associated with smoking, difficulty paying for basic necessities, greater financial difficulty during the COVID-19 pandemic, struggling to pay for gas (P < 0.01), fatalistic attitudes toward cancer prevention, and susceptibility to information overload about cancer prevention. Among the 33% of respondents who delayed getting medical care in the past year, this was more often due to lack of transportation in those with lower educational attainment (21% vs. 3%, P = 0.02 adjusted for rurality) and more often due to concerns about catching COVID-19 among urban than rural residents (52% vs. 21%; P < 0.001 adjusted for education). In conclusion, in NH/VT, smoking, financial hardship, and beliefs about cancer prevention are independently associated with lower educational attainment but not rural residence. These findings have implications for the design of interventions to address cancer risk in rural areas. Significance: In NH and VT, the finding that some associations between cancer risk factors and rural residence are more closely tied to educational attainment than rurality suggest that the design of interventions to address cancer risk should take educational attainment into account.

Impact of Rurality on Geriatric Emergency General Surgery Patients in New Hampshire.

BACKGROUND: Geriatric patients requiring emergency general surgery (EGS) have significant risk of morbidity and mortality. Rural patients face decreased access to care. We sought to characterize the EGS needs and impact of rurality for geriatric residents of New Hampshire. STUDY DESIGN: A retrospective cohort study of the New Hampshire Uniform Healthcare Facility Discharge Dataset, including patients 65 years and older with urgent/emergent admission who underwent 1 of 7 EGS procedures, grouped by urban or rural county of residence, discharged between 2012-2015. RESULTS: New Hampshire has 26 acute care hospitals: 10 (38.5%) are in urban counties and 16 (61.5%) are in rural counties. Thirteen (50.0%) are critical access hospitals (1 urban and 12 rural). Of 2,445 geriatric patient discharges, 40% of patients were from rural counties and were demographically similar to urban patients. Rural patients were more likely to present as a hospital transfer (15.4% vs 2.5%, p < 0.01), receive care at a critical access hospital (24.1% vs 1.0%, p < 0.01), receive care outside their home county (32.5% vs 12.8%, p < 0.01), and be transferred to another hospital after surgery. Rural and urban patients underwent similar procedures, with similar lengths of stay, cost of index hospitalization, and mortality. CONCLUSIONS: Rural geriatric patients in New Hampshire are more likely to receive care outside of their home county or be transferred to another hospital. Costs of care were similar but are likely underestimated for rural patients. There was no difference in unadjusted mortality. Further investigation is merited to determine the reasons for hospital transfer in the geriatric EGS population to evaluate which patients may benefit most from remaining close to home vs transferring to other facilities.

Use of a Novel Network-Based Linchpin Score to Characterize Accessibility to the Oncology Physician Workforce in the United States.

Importance: Physician headcounts provide useful information about the cancer care delivery workforce; however, efforts to track the oncology workforce would benefit from new measures that capture how essential a physician is for meeting the multidisciplinary cancer care needs of the region. Physicians are considered linchpins when fewer of their peers are connected to other physicians of the same specialty as the focal physician. Because they are locally unique for their specialty, these physicians' networks may be particularly vulnerable to their removal from the network (eg, through relocation or retirement). Objective: To examine a novel network-based physician linchpin score within nationwide cancer patient-sharing networks and explore variation in network vulnerability across hospital referral regions (HRRs). Design, Setting, and Participants: This cross-sectional study analyzed fee-for-service Medicare claims and included Medicare beneficiaries with an incident diagnosis of breast, colorectal, or lung cancer from 2016 to 2018 and their treating physicians. Data were analyzed from March 2022 to October 2022. Exposures: Physician characteristics assessed were specialty, rurality, and Census region. HRR variables assessed include sociodemographic and socioeconomic characteristics and use of cancer services. Main Outcomes and Measures: Oncologist linchpin score, which examined the extent to which a physician's peers were connected to other physicians of the same specialty as the focal physician. Network vulnerability, which distinguished HRRs with more linchpin oncologists than expected based on oncologist density. χ2 and Fisher exact tests were used to examine relationships between oncologist characteristics and linchpin score. Spearman rank correlation coefficient (ρ) was used to measure the strength and direction of relationships between HRR network vulnerability, oncologist density, population sociodemographic and socioeconomic characteristics, and cancer service use. Results: The study cohort comprised 308 714 patients with breast, colorectal, or lung cancer. The study cohort of 308 714 patients included 161 206 (52.2%) patients with breast cancer, 76 604 (24.8%) patients with colorectal cancer, and 70 904 (23.0%) patients with lung cancer. In our sample, 272 425 patients (88%) were White, and 238 603 patients (77%) lived in metropolitan areas. The cancer patient-sharing network included 7221 medical oncologists and 3573 radiation oncologists. HRRs with more vulnerable networks for medical oncology had a higher percentage of beneficiaries eligible for Medicaid (ρ, 0.19; 95% CI, 0.08 to 0.29). HRRs with more vulnerable networks for radiation oncology had a higher percentage of beneficiaries living in poverty (ρ, 0.17; 95% CI, 0.06 to 0.27), and a higher percentage of beneficiaries eligible for Medicaid (ρ, 0.21; 95% CI, 0.09 to 0.31), and lower rates of cohort patients receiving radiation therapy (ρ, -0.18; 95% CI, -0.28 to -0.06; P = .003). The was no association between network vulnerability for medical oncology and percent of cohort patients receiving chemotherapy (ρ, -0.03; 95% CI, -0.15 to 0.08). Conclusions and Relevance: This study found that patient-sharing network vulnerability was associated with poverty and lower rates of radiation therapy. Health policy strategies for addressing network vulnerability may improve access to interdisciplinary care and reduce treatment disparities.

Neighborhood Environments and Utilitarian Walking Among Older vs. Younger Rural Adults.

Introduction: Walking has the potential to promote health across the life span, but age-specific features of the neighborhood environment (NE), especially in rural communities, linked with walking have not been adequately characterized. This study examines the relationships between NE and utilitarian walking among older vs. younger adults living in US rural towns. Methods: Data for this cross-sectional study came from telephone interviews in 2011-2012 with 2,140 randomly sampled younger (18-64 years, n = 1,398) and older (65+ years, n = 742) adults, collecting personal and NE perception variables. NE around each participant's home was also measured objectively using geographic information system techniques. Separate mixed-effects logistic regression models were estimated for the two age groups, predicting the odds of utilitarian walking at least once a week. Results: Perceived presence of crosswalks and pedestrian signals was significantly related to utilitarian walking in both age groups. Among older adults, unattended dogs, lighting at night, and religious institutions were positively while steep slope was negatively associated with their walking. For younger adults, traffic speed (negative, -), public transportation (positive, +), malls (-), cultural/recreational destinations (+), schools (+), and resource production land uses such as farms and mines (-) were significant correlates of utilitarian walking. Conclusion: Different characteristics of NE are associated with utilitarian walking among younger vs. older adults in US rural towns. Optimal modifications of NE to promote walking may need to reflect these age differences.

Individual Mobility and Uncertain Geographic Context: Real-time Versus Neighborhood Approximated Exposure to Retail Tobacco Outlets Across the US.

There is growing interest in the way exposure to neighborhood risk and protective factors affects the health of residents. Although multiple approaches have been reported, empirical methods for contrasting the spatial uncertainty of exposure estimates are not well established. The objective of this paper was to contrast real-time versus neighborhood approximated exposure to the landscape of tobacco outlets across the contiguous US. A nationwide density surface of tobacco retail outlet locations was generated using kernel density estimation (KDE). This surface was linked to participants' (N p = 363) inferred residential location, as well as to their real-time geographic locations, recorded every 10 min over 180 days. Real-time exposure was estimated as the hourly product of radius of gyration and average tobacco outlet density (N hour = 304, 164 h). Ordinal logit modeling was used to assess the distribution of real-time exposure estimates as a function of each participant's residential exposure. Overall, 61.3% of real-time, hourly exposures were of relatively low intensity, and after controlling for temporal and seasonal variation, 72.8% of the variance among these low-level exposures was accounted for by residence in one of the two lowest residential exposure quintiles. Most moderate to high intensity exposures (38.7% of all real-time, hourly exposures) were no more likely to have been contributed by subjects from any single residential exposure cluster than another. Altogether, 55.2% of the variance in real-time exposures was not explained by participants' residential exposure cluster. Calculating hourly exposure estimates made it possible to directly contrast real-time observations with static residential exposure estimates. Results document the substantial degree that real-time exposures can be misclassified by residential approximations, especially in residential areas characterized by moderate to high retail density levels.

Validation of commercial business lists as a proxy for licensed alcohol outlets.

BACKGROUND: Studies of retail alcohol outlets are restricted to regions due to lack of U.S. national data. Commercial business lists (BL) offer a possible solution, but no data exists to determine if BLs could serve as an adequate proxy for license data. This paper compares geospatial measures of alcohol outlets derived from a commercial BL with license data for a large US state. METHODS: We validated BL data as a measure of off-premise alcohol outlet density and proximity compared to license data for 5528 randomly selected California residential addresses. We calculated three proximity measures (Euclidean distance, road network travel time and distance) and two density measures (kernel density estimation and the count within a 2-mile radius) for each dataset. The data was acquired in 2015 and processed and analyzed in 2015 and 2016. RESULTS: Correlations and reliabilities between density (correlation 0.98; Cronbach's α 0.97-0.99) and proximity (correlations 0.77-0.86; α 0.87-0.92) measures were high. For proximity, BL data matched license in 55-57% of addresses, overstated distance in 19%, and understated in 24-26%. CONCLUSIONS: BL data can serve as a reliable proxy for licensed alcohol outlets, thus extending the work that can be performed in studies on associations between retail alcohol outlets and drinking outcomes.

Geographic variation in the relationship between body mass index and the built environment.

Studies examining associations between weight status and neighborhood built environment (BE) have shown inconsistent results and have generally focused on urban settings. However, many Americans do not live in metropolitan areas and BE impacts may be different outside of metropolitan areas. We sought to examine whether the relationship between body mass index (BMI) and neighborhood BE exists and varies by geographic region across small towns in the United States. We conducted telephone surveys with 2156 adults and geographic information systems data in nine towns located within three geographic regions (Northeast, Texas, Washington) in 2011 and 2012. Multiple regression models examined the relationship between individual BMI and BE measures. Most physical activity variables were significantly associated with lower BMI in all geographic regions. We saw variation across geographic region in the relationship between characteristics of the BE variables and BMI. Some perceived and objectively-measured characteristics of the BE were significantly associated with adult BMI, but significant relationships varied by geographic region. For example, in the Northeast, perceived attractiveness of the neighborhood as a reason for why they chose to live there was associated with lower BMI; in Texas, the perceived presence of a fast food restaurant was negatively associated with BMI; in Washington, perceived presence of trees along the streets was associated with lower BMI. Our findings suggest that regional variation plays a role in the relationship between adult BMI and BE characteristics in small towns. Regardless of geographic location, interventions should encourage utilitarian walking and other forms of physical activity.

Is the closest facility the one actually used? An assessment of travel time estimation based on mammography facilities.

BACKGROUND: Characterizing geographic access depends on a broad range of methods available to researchers and the healthcare context to which the method is applied. Globally, travel time is one frequently used measure of geographic access with known limitations associated with data availability. Specifically, due to lack of available utilization data, many travel time studies assume that patients use the closest facility. To examine this assumption, an example using mammography screening data, which is considered a geographically abundant health care service in the United States, is explored. This work makes an important methodological contribution to measuring access--which is a critical component of health care planning and equity almost everywhere. METHOD: We analyzed one mammogram from each of 646,553 women participating in the US based Breast Cancer Surveillance Consortium for years 2005-2012. We geocoded each record to street level address data in order to calculate travel time to the closest and to the actually used mammography facility. Travel time between the closest and the actual facility used was explored by woman-level and facility characteristics. RESULTS: Only 35% of women in the study population used their closest facility, but nearly three-quarters of women not using their closest facility used a facility within 5 min of the closest facility. Individuals that by-passed the closest facility tended to live in an urban core, within higher income neighborhoods, or in areas where the average travel times to work was longer. Those living in small towns or isolated rural areas had longer closer and actual median drive times. CONCLUSION: Since the majority of US women accessed a facility within a few minutes of their closest facility this suggests that distance to the closest facility may serve as an adequate proxy for utilization studies of geographically abundant services like mammography in areas where the transportation networks are well established.

Secondary GIS built environment data for health research: guidance for data development.

Built environment (BE) data in geographic information system (GIS) format are increasingly available from public agencies and private providers. These data can provide objective, low-cost BE data over large regions and are often used in public health research and surveillance. Yet challenges exist in repurposing GIS data for health research. The GIS data do not always capture desired constructs; the data can be of varying quality and completeness; and the data definitions, structures, and spatial representations are often inconsistent across sources. Using the Small Town Walkability study as an illustration, we describe (a) the range of BE characteristics measurable in a GIS that may be associated with active living, (b) the availability of these data across nine U.S. small towns, (c) inconsistencies in the GIS BE data that were available, and (d) strategies for developing accurate, complete, and consistent GIS BE data appropriate for research. Based on a conceptual framework and existing literature, objectively measurable characteristics of the BE potentially related to active living were classified under nine domains: generalized land uses, morphology, density, destinations, transportation system, traffic conditions, neighborhood behavioral conditions, economic environment, and regional location. At least some secondary GIS data were available across all nine towns for seven of the nine BE domains. Data representing high-resolution or behavioral aspects of the BE were often not available. Available GIS BE data - especially tax parcel data - often contained varying attributes and levels of detail across sources. When GIS BE data were available from multiple sources, the accuracy, completeness, and consistency of the data could be reasonable ensured for use in research. But this required careful attention to the definition and spatial representation of the BE characteristic of interest. Manipulation of the secondary source data was often required, which was facilitated through protocols.

The built environment and utilitarian walking in small U.S. towns.

OBJECTIVES: The role of the built environment on walking in rural United States (U.S.) locations is not well characterized. We examined self-reported and measured built environment correlates of walking for utilitarian purposes among adult residents of small rural towns. METHODS: In 2011-12, we collected telephone survey and geographic data from 2152 adults in 9 small towns from three U.S. regions. We performed mixed-effects logistic regression modeling to examine relationships between built environment measures and utilitarian walking ("any" versus "none"; "high" [≥150min per week] versus "low" [<150min per week]) to retail, employment and public transit destinations. RESULTS: Walking levels were lower than those reported for populations living in larger metropolitan areas. Environmental factors significantly (p<0.05) associated with higher odds of utilitarian walking in both models included self-reported presence of crosswalks and pedestrian signals and availability of park/natural recreational areas in the neighborhood, and also objectively measured manufacturing land use. CONCLUSIONS: Environmental factors associated with utilitarian walking in cities and suburbs were important in small rural towns. Moreover, manufacturing land use was associated with utilitarian walking. Modifying the built environment of small towns could lead to increased walking in a sizeable segment of the U.S. population.

Geographic access to breast imaging for US women.

PURPOSE: The breast imaging modalities of mammography, ultrasound, and MRI are widely used for screening, diagnosis, treatment, and surveillance of breast cancer. Geographic access to breast imaging services in various modalities is not known at a national level overall or for population subgroups. METHODS: A retrospective study of 2004-2008 Medicare claims data was conducted to identify ZIP codes in which breast imaging occurred, and data were mapped. Estimated travel times were made for each modality for 215,798 census block groups in the contiguous United States. Using Census 2010 data, travel times were characterized by sociodemographic factors for 92,788,909 women aged ≥30 years, overall, and by subgroups of age, race/ethnicity, rurality, education, and median income. RESULTS: Overall, 85% of women had travel times of ≤20 minutes to nearest mammography or ultrasound services, and 70% had travel times of ≤20 minutes for MRI with little variation by age. Native American women had median travel times 2-3 times longer for all 3 modalities, compared to women of other racial/ethnic groups. For rural women, median travel times to breast imaging services were 4-8-fold longer than they were for urban women. Black and Asian women had the shortest median travel times to services for all 3 modalities. CONCLUSIONS: Travel times to mammography and ultrasound breast imaging facilities are short for most women, but for breast MRI, travel times are notably longer. Native American and rural women are disadvantaged in geographic access based on travel times to breast imaging services. This work informs potential interventions to reduce inequities in access and utilization.

Local geographic variation in chronic liver disease and hepatocellular carcinoma: contributions of socioeconomic deprivation, alcohol retail outlets, and lifestyle.

PURPOSE: Hepatocellular carcinoma (HCC) incidence rates continue to increase in the United States. Geographic variation in rates suggests a potential contribution of area-based factors, such as neighborhood socioeconomic deprivation, retail alcohol availability, and access to health care. METHODS: Using the National Institutes of Health-American Association of Retired Persons Diet and Health Study, we prospectively examined area socioeconomic variations in HCC incidence (n = 434 cases) and chronic liver disease (CLD) mortality (n = 805 deaths) and assessed contribution of alcohol outlet density, health care infrastructure, diabetes, obesity, and health behaviors. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated from hierarchical Cox regression models. RESULTS: Area socioeconomic deprivation was associated with increased risk of HCC incidence and CLD mortality (HR, 1.48; 95% CI, 1.03-2.14 and HR, 2.36; 95% CI, 1.79-3.11, respectively) after accounting for age, sex, and race. After additionally accounting for educational attainment and health risk factors, associations for HCC incidence were no longer significant; associations for CLD mortality remained significant (HR, 1.78; 95% CI, 1.34-2.36). Socioeconomic status differences in alcohol outlet density and health behaviors explained the largest proportion of socioeconomic status-CLD mortality association, 10% and 29%, respectively. No associations with health care infrastructure were observed. CONCLUSIONS: Our results suggest a greater effect of area-based factors for CLD than HCC. Personal risk factors accounted for the largest proportion of variance for HCC but not for CLD mortality.

Retail tobacco exposure: using geographic analysis to identify areas with excessively high retail density.

INTRODUCTION: There is great disparity in tobacco outlet density (TOD), with density highest in low-income areas and areas with greater proportions of minority residents, and this disparity may affect cancer incidence. We sought to better understand the nature of this disparity by assessing how these socio-demographic factors relate to TOD at the national level. METHODS: Using mixture regression analysis and all of the nearly 65,000 census tracts in the contiguous United States, we aimed to determine the number of latent disparity classes by modeling the relations of proportions of Blacks, Hispanics, and families living in poverty with TOD, controlling for urban/rural status. RESULTS: We identified six disparity classes. There was considerable heterogeneity in relation to TOD for Hispanics in rural settings. For Blacks, there was no relation to TOD in an urban moderate disparity class, and for rural census tracts, the relation was highest in a moderate disparity class. CONCLUSIONS: We demonstrated the utility of classifying census tracts on heterogeneity of tobacco risk exposure. This approach provides a better understanding of the complexity of socio-demographic influences of tobacco retailing and creates opportunities for policy makers to more efficiently target areas in greatest need.

Predictors of tobacco outlet density nationwide: a geographic analysis.

OBJECTIVE: To elucidate how demographics of US Census tracts are related to tobacco outlet density (TOD). METHOD: The authors conducted a nationwide assessment of the association between socio-demographic US Census indicators and the density of tobacco outlets across all 64,909 census tracts in the continental USA. Retail tobacco outlet addresses were determined through North American Industry Classification System codes, and density per 1000 population was estimated for each census tract. Independent variables included urban/rural; proportion of the population that was black, Hispanic and women with low levels of education; proportion of families living in poverty and median household size. RESULTS: In a multivariate analysis, there was a higher TOD per 1000 population in urban than in rural locations. Furthermore, higher TOD was associated with larger proportions of blacks, Hispanics, women with low levels of education and with smaller household size. Urban-rural differences in the relation between demographics and TOD were found in all socio-demographic categories, with the exception of poverty, but were particularly striking for Hispanics, for whom the relation with TOD was 10 times larger in urban compared with rural census tracts. CONCLUSIONS: The findings suggest that tobacco outlets are more concentrated in areas where people with higher risk for negative health outcomes reside. Future studies should examine the relation between TOD and smoking, smoking cessation, as well as disease rates.

Community variation in adolescent access to indoor tanning facilities.

Melanoma rates among younger women in New Hampshire (NH) are rising. In urban studies, youth proximity to tanning facilities has been linked to indoor tanning, a proven cause of melanoma. Youth access has not been examined in rural settings. To determine on a statewide basis the influence of rurality and community income level on female students' ease of access to tanning facilities, all NH tanning facilities (N = 261) and high schools (N = 77) in 2011 were spatially and statistically analyzed to determine schools with more facilities within 2 miles of the school and greater capacity (fewer female students per facility), for indoor tanning. Schools above the state-wide average for both measures were classified as "Easy Access" to indoor tanning. Among NH high schools, 74 % have 1 or more tanning facility within two miles and 22 % have "Easy Access" to tanning facilities. Ease of access did not differ by rurality. Lower-income school status was an independent predictor of both greater capacity and "Easy Access". While urban and rural teens have similar access to indoor tanning, female students in lower-income communities have easier access. Variations in access by community size and income must be considered in planning interventions to address youth indoor tanning.

A comparison of individual versus community influences on youth smoking behaviours: a cross-sectional observational study.

OBJECTIVES: To compare individual with community risk factors for adolescent smoking. DESIGN: A cross-sectional observational study with multivariate analysis. SETTING: National telephone survey. PARTICIPANTS: 3646 US adolescents aged 13-18 years in 2007 recruited through a random digit-dial survey. OUTCOME MEASURES: Ever tried smoking and, among experimental smokers, smoking intensity (based on smoking in past 30 days). RESULTS: One-third of participants (35.6%, N=1297) had tried smoking. After controlling for individual risk factors, neither tobacco outlet density nor proximity were associated with tried smoking or smoking intensity. Associations with trying smoking included age (adjusted OR (AOR)=1.23, 95% CI 1.16 to 1.31), lower socioeconomic status (AOR=0.82, 95% CI 0.74 to 0.91), sibling smoking (AOR=2.13, 95% CI 1.75 to 2.59), friend smoking (AOR=2.60, 95% CI 2.19 to 3.10 for some and AOR=7.01, 95% CI 5.05 to 9.74 for most), movie smoking exposure (AOR=2.66, 95% CI 1.95 to 3.63), team sports participation (AOR=0.69, 95% CI 0.54 to 0.89) and sensation seeking (AOR=7.72, 95% CI 5.26 to 11.34). Among experimental smokers, age (AOR=1.32, 95% CI 1.21 to 1.44), minority status (AOR=0.48, 95% CI 0.30 to 0.79 for Black; AOR=0.46, 95% CI 0.31 to 0.69 for Hispanic; AOR=0.53, 95% CI 0.43 to 0.85 for mixed race/other), friend smoking (AOR=3.37, 95% CI 2.37 to 4.81 for some; AOR=20.27, 95% CI 13.22 to 31.08 for most), team sports participation (AOR=0.38, 95% CI 0.26 to 0.55) and sensation seeking (AOR=6.57, 95% CI 3.71 to 11.64) were associated with smoking intensity. CONCLUSIONS: The study suggests that interventions and policies to prevent and reduce youth smoking should focus on individual risk factors for smoking, including supporting participation in team sports, minimising exposure to movie smoking, addressing the social influence of friend smoking and addressing experience seeking among high sensation-seekers.

Density estimation and adaptive bandwidths: a primer for public health practitioners.

BACKGROUND: Geographic information systems have advanced the ability to both visualize and analyze point data. While point-based maps can be aggregated to differing areal units and examined at varying resolutions, two problems arise 1) the modifiable areal unit problem and 2) any corresponding data must be available both at the scale of analysis and in the same geographic units. Kernel density estimation (KDE) produces a smooth, continuous surface where each location in the study area is assigned a density value irrespective of arbitrary administrative boundaries. We review KDE, and introduce the technique of utilizing an adaptive bandwidth to address the underlying heterogeneous population distributions common in public health research. RESULTS: The density of occurrences should not be interpreted without knowledge of the underlying population distribution. When the effect of the background population is successfully accounted for, differences in point patterns in similar population areas are more discernible; it is generally these variations that are of most interest. A static bandwidth KDE does not distinguish the spatial extents of interesting areas, nor does it expose patterns above and beyond those due to geographic variations in the density of the underlying population. An adaptive bandwidth method uses background population data to calculate a kernel of varying size for each individual case. This limits the influence of a single case to a small spatial extent where the population density is high as the bandwidth is small. If the primary concern is distance, a static bandwidth is preferable because it may be better to define the "neighborhood" or exposure risk based on distance. If the primary concern is differences in exposure across the population, a bandwidth adapting to the population is preferred. CONCLUSIONS: Kernel density estimation is a useful way to consider exposure at any point within a spatial frame, irrespective of administrative boundaries. Utilization of an adaptive bandwidth may be particularly useful in comparing two similarly populated areas when studying health disparities or other issues comparing populations in public health.