{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T11:40:09Z","timestamp":1765539609189,"version":"3.48.0"},"reference-count":42,"publisher":"BMJ","issue":"6","funder":[{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["P30CA225520"],"award-info":[{"award-number":["P30CA225520"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["Tob Control"],"accepted":{"date-parts":[[2024,8,6]]},"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Significant progress has been made in reducing maternal exposure to tobacco smoke and subsequent adverse birth outcomes, however, reductions may require strategies that reduce the availability of tobacco retailers. In this study, we investigated the relationship between tobacco retailer density and birth outcomes across the USA and predicted the potential impact of a tobacco retailer density cap on these outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Annual US county (n=3105), rates of preterm birth, low birth weight, small-for-gestational age, all-cause infant mortality and sudden infant death syndrome (SIDS) were calculated using National Vital Statistics System data. Tobacco retailers were identified from the National Establishment Time-Series Database. We used Poisson regression to estimate the effect of capping retailer density at 1.4 retailers per 1000 population, controlling for county demographics and air pollution, using propensity score weighting.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Tobacco retailer density was positively associated with most adverse birth outcomes. We estimate that a nationwide cap on tobacco retailer density, implemented in 2016, would have resulted in a reduction of 4275 (95% CI 2210 to 6392) preterm births, 6096 (95% CI 4421 to 7806) small-for-gestational-age births, 3483 (95% CI 2615 to 4378) low birthweight births, 538 (95% CI 345 to 733) all-cause infant deaths and 107 (95% CI 55 to 158) SIDS deaths in that year.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Higher rates of adverse birth outcomes were seen in counties with high tobacco retailer density compared with those with low density. These results provide further support for regulating tobacco retail density to reduce adverse health outcomes associated with tobacco use.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/tc-2024-058779","type":"journal-article","created":{"date-parts":[[2024,8,26]],"date-time":"2024-08-26T00:36:05Z","timestamp":1724632565000},"page":"775-782","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Tobacco retailer density and its association with birth outcomes in the USA: 2000\u20132016"],"prefix":"10.1136","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9563-203X","authenticated-orcid":false,"given":"Chris D","family":"Baggett","sequence":"first","affiliation":[{"name":"Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, North Carolina, USA"},{"name":"Lineberger Comprehensive Cancer Center, UNC School of Medicine, Chapel Hill, North Carolina, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David B","family":"Richardson","sequence":"additional","affiliation":[{"name":"UCI Susan & Henry Samueli College of Health Sciences, Irvine, California, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tzy-Mey","family":"Kuo","sequence":"additional","affiliation":[{"name":"Lineberger Comprehensive Cancer Center, UNC School of Medicine, Chapel Hill, North Carolina, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jacqueline E","family":"Rudolph","sequence":"additional","affiliation":[{"name":"Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8361-7342","authenticated-orcid":false,"given":"Amanda Y","family":"Kong","sequence":"additional","affiliation":[{"name":"Department of Family and Preventive Medicine, The University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA"},{"name":"TSET Health Promotion Research Center, The University of Oklahoma Stephenson Cancer Center, Oklahoma City, Oklahoma, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3318-8524","authenticated-orcid":false,"given":"Kurt M","family":"Ribisl","sequence":"additional","affiliation":[{"name":"Lineberger Comprehensive Cancer Center, UNC School of Medicine, Chapel Hill, North Carolina, USA"},{"name":"Health Behavior, UNC Gillings School of Global Public Health, Chapel Hill, North Carolina, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3283-542X","authenticated-orcid":false,"given":"Shelley D","family":"Golden","sequence":"additional","affiliation":[{"name":"Lineberger Comprehensive Cancer Center, UNC School of Medicine, Chapel Hill, North Carolina, USA"},{"name":"Health Behavior, UNC Gillings School of Global Public Health, Chapel Hill, North Carolina, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"239","published-online":{"date-parts":[[2024,8,21]]},"reference":[{"key":"2025121203351127000_34.6.775.1","doi-asserted-by":"crossref","DOI":"10.1016\/j.pmedr.2019.101031","article-title":"Neighborhood racial, ethnic, and income disparities in accessibility to multiple tobacco retailers: Mecklenburg County, North Carolina, 2015","volume":"17","author":"Kong","year":"2020","journal-title":"Prev Med Rep"},{"key":"2025121203351127000_34.6.775.2","doi-asserted-by":"publisher","DOI":"10.1093\/ntr\/ntaa223"},{"key":"2025121203351127000_34.6.775.3","doi-asserted-by":"publisher","DOI":"10.1136\/tobaccocontrol-2021-056717"},{"key":"2025121203351127000_34.6.775.4","doi-asserted-by":"publisher","DOI":"10.1093\/ntr\/ntz153"},{"key":"2025121203351127000_34.6.775.5","doi-asserted-by":"publisher","DOI":"10.1093\/ntr\/ntu168"},{"key":"2025121203351127000_34.6.775.6","doi-asserted-by":"crossref","DOI":"10.1016\/j.pmedr.2019.101005","article-title":"County-level associations between tobacco retailer density and smoking prevalence in the USA, 2012","volume":"17","author":"Golden","year":"2020","journal-title":"Prev Med Rep"},{"key":"2025121203351127000_34.6.775.7","doi-asserted-by":"crossref","first-page":"179","DOI":"10.7150\/ijms.4.179","article-title":"The geography of chronic obstructive pulmonary disease across time: California in 1993 and 1999","volume":"4","author":"Lipton","year":"2007","journal-title":"Int J Med Sci"},{"key":"2025121203351127000_34.6.775.8","doi-asserted-by":"publisher","DOI":"10.1080\/15412550500346543"},{"key":"2025121203351127000_34.6.775.9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ypmed.2016.05.003"},{"key":"2025121203351127000_34.6.775.10","doi-asserted-by":"publisher","DOI":"10.1136\/tobaccocontrol-2017-053945"},{"key":"2025121203351127000_34.6.775.11","doi-asserted-by":"crossref","unstructured":"Kong AY , Baggett CD , Gottfredson NC , et al . 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