Objectives We examined whether the geographic density of alcohol retailers was greater in geographic areas with higher levels of demographic characteristics that predict health disparities. Methods We obtained the locations of all alcohol retailers in the continental United States and created a map depicting alcohol retail outlet density at the US Census tract level. US Census data provided tract-level measures of poverty, education, crowding, and race/ethnicity. We used multiple linear regression to assess relationships between these variables and retail alcohol density. Results In urban areas, retail alcohol density had significant nonlinear relationships with Black race, Latino ethnicity, poverty, and education, with slopes increasing substantially throughout the highest quartile for each predictor. In high-proportion Latino communities, retail alcohol density was twice as high as the median density. Retail alcohol density had little or no relationship with the demographic factors of interest in suburban, large town, or rural census tracts. Conclusions Greater density of alcohol retailers was associated with higher levels of poverty and with higher proportions of Blacks and Latinos in urban census tracts. These disparities could contribute to higher morbidity in these geographic areas.

Background The breast imaging modalities of mammography, ultrasound, and magnetic resonance imaging (MRI) are widely used for screening, diagnosis, treatment, and surveillance of breast cancer. Geographic access to breast imaging modalities is not known at a national level overall or for population subgroups. Methods A retrospective study of 2004-2008 Medicare claims data to identify ZIP codes in which breast imaging occurred, and data were mapped. We estimated travel times to each modality for 215,798 census block groups in the contiguous U.S. Using Census 2010 data, we characterized travel times by socio-demographic 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, and 70% had travel times of ≤20 minutes for MRI with little variation by age. Native American women had median travel times 2-3-fold longer to all three modalities, compared to women of other racial/ethnic groups. For rural women, median travel times to breast imaging were 4-8-fold longer than for urban women. Black and Asian women had shortest median travel times to all three modalities. Conclusion Travel times to mammography and ultrasound breast imaging are short for most women, but to breast MRI travel times are notably longer. Native American and rural women are disadvantaged in geographic access based on travel times to breast imaging. This work informs potential interventions to reduce inequities in access and utilization.

Purpose This study examined the concordance between individuals’ self‐reported rural‐urban category of their community and ZIP Code‐derived Rural‐Urban Commuting Area (RUCA) category. Methods An Internet‐based survey, administered from August 2017 through November 2017, was used to collect participants’ sociodemographic characteristics, self‐reported ZIP Code of residence, and perception of which RUCA category best describes the community in which they live. We calculated weighted kappa (ĸ) coefficients (95% confidence interval [CI]) to test for concordance between participants’ ZIP Code‐derived RUCA category and their selection of RUCA descriptor. Descriptive frequency distributions of participants' demographics are presented. Findings A total of 622 survey participants, residents of New Hampshire (63%) and Vermont (37%), responded to the survey's self‐reported rural‐urban category. The overall ĸ was 0.33 (95% CI: 0.27‐0.38). The highest concordance was found among those living in a small rural area (N = 81, 13%): 62% of this group identified their communities as small rural. Sixty‐five percent (300/459) of participants residing in urban or large rural areas reported their community as more rural (small rural or isolated). Sixty‐eight percent (111/163) of participants living in small rural or isolated areas identified their community as more urban (large rural or urban). Conclusions Discordance was found between self‐report of rural‐urban category and ZIP Code‐derived RUCA designation. Caution is warranted when attributing rural‐urban designation to individuals based on geographic unit, since perceived rurality/urbanicity of their community that relates to health behaviors may not be reflected.

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Background Uptake of breast magnetic resonance imaging (MRI) coupled with breast cancer risk assessment offers the opportunity to tailor the benefits and harms of screening strategies for women with differing cancer risks. Despite the potential benefits, there is also concern for worsening population-based health disparities. Methods Among 316,172 women aged 35-69 years from five Breast Cancer Surveillance Consortium registries (2007-2012), we examined 617,723 negative screening mammograms and 1,047 screening MRIs. We examined the relative risks (RRs) of MRI use by women with <20% lifetime breast cancer risk and RR in the absence of MRI use by women with ≥20% lifetime risk. Results Among women with <20% lifetime risk, non-Hispanic white women were 62% more likely than non-white women to receive a MRI (95% confidence interval 1.32-1.98). Of these women, those with some college or technical school were 43% more likely and those who had at least a college degree were 132% more likely to receive an MRI compared to those with a high school education or less. Among women with ≥20% lifetime risk, there was no statistically significant difference in use of screening MRI by race or ethnicity, but high-risk women with a high school education or less were less likely to receive screening MRI than women who had graduated from college (RR 0.40; 95% CI 0.25-0.63). Conclusions Uptake of screening breast MRI into clinical practice has the potential to worsen population-based health disparities. Policies, beyond health insurance coverage, should ensure that use of this screening modality reflects evidence-based guidelines.