{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T16:03:47Z","timestamp":1790870627588,"version":"4.1.0"},"reference-count":33,"publisher":"American Medical Association (AMA)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Studies have shown a strong association between pharmacy closures and deserts and neighborhood racial and ethnic demographics.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To examine the association between racial and ethnic demographics and pharmacy availability and visits at the US census block group (CBG) level.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This cross-sectional study used mobility data extracted from mobile phones from January 2019 to January 2020 (prepandemic period) and January 2023 to January 2024 (postpandemic period). Race, ethnicity, and socioeconomic data at the CBG level were obtained from the 2019 American Community Survey (ACS) 5-year estimates. Logistic and linear regression models were fitted to study the association between the presence or absence of a pharmacy and pharmacies per 10\u202f000 people and CBG demographics. CBGs were classified as racially and\/or ethnically diverse, predominantly racially and\/or ethnically minoritized, or predominantly White. Data were analyzed between May 2024 and February 2026.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n Model-estimated association between pharmacy availability, pharmacies per 10\u202f000 people and CBG demographics, and the proportion of pharmacy visits by racial and ethnic composition of CBGs.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n This study included 112\u202f655 urban CBGs in 45 US states and Washington, DC, comprising 158\u202f082\u202f463 individuals. The mean of median (SD) age of the overall study population was 39.9 (9.4) years; 77\u202f184\u202f341 individuals (48.7%) were male and 80\u202f898\u202f122 (51.3 %) were female. The racial and ethnic composition according to the ACS was 2\u202f131\u202f706 (1.3%) American Indian or Alaska Native, 567\u202f179 (0.4%) Hispanic, 7\u202f721\u202f195 (4.9%) non-Hispanic Asian, 23\u202f977\u202f801 (15.2%) non-Hispanic Black, 554\u202f833 (0.4%) non-Hispanic Native Hawaiian or Other Pacific Islander, and 95\u202f761\u202f561 (60.6%) non-Hispanic White. CBGs with predominantly racially and\/or ethnically minoritized and racially and\/or ethnically diverse populations had lower odds of having at least 1 pharmacy compared with predominantly White CBGs in both prepandemic (odds ratio [OR], 0.44; 95% CI, 0.41-0.47) and postpandemic (OR, 0.84; 95% CI, 0.81-0.88) periods. Predominantly White CBGs had 15% (coefficient, 0.85; 95% CI, 0.82-0.88) more pharmacies per 10\u202f000 people than CBGs with predominantly minoritized populations in the prepandemic and postpandemic periods. Mobile devices from predominantly White CBGs mostly visited pharmacies in CBGs with similar demographics, whereas mobile devices from other CBGs visited pharmacies in racially and\/or ethnically diverse CBGs.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this cross-sectional study, mobile devices from CBGs with fewer pharmacies were more likely to visit pharmacies in CBGs with racially and\/or ethnically diverse populations. As pharmacy closures and deserts continue to occur disproportionately in communities with predominantly Black and Latinx populations, measuring correlations with health and developing policy solutions that enable access to medicines and other health care resources are important.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2026.37087","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T15:44:26Z","timestamp":1790869466000},"page":"e2637087","source":"Crossref","is-referenced-by-count":0,"title":["Census Block Group Demographics, Mobility Patterns, and Pharmacy Visits"],"prefix":"10.1001","volume":"9","author":[{"given":"Elaine O.","family":"Nsoesie","sequence":"first","affiliation":[{"name":"Department of Global Health, School of Public Health, Boston University, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zou","family":"Yang","sequence":"additional","affiliation":[{"name":"Thayer School of 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