{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T15:18:22Z","timestamp":1770995902731,"version":"3.50.1"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2023,9,6]],"date-time":"2023-09-06T00:00:00Z","timestamp":1693958400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["K01CA242530"],"award-info":[{"award-number":["K01CA242530"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Introduction<\/jats:title>\n                  <jats:p>First-order Markov models assume future tobacco use behavior is dependent on current tobacco use and are often used to characterize patterns of tobacco use over time. Higher-order Markov models that assume future behavior is dependent on current and prior tobacco use may better estimate patterns of tobacco use.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Aims and Methods<\/jats:title>\n                  <jats:p>This study compared Markov models of different orders to examine whether incorporating information about tobacco use history improves model estimation of tobacco use and estimated tobacco use transition probabilities. We used data from four waves of the Population Assessment of Tobacco and Health Study. In each Wave, a participant was categorized into one of the following tobacco use states: never smoker, former smoker, menthol cigarette smoker, non-menthol cigarette smoker, or e-cigarette\/dual user. We compared first-, second-, and third-order Markov models using multinomial logistic regression and estimated transition probabilities between tobacco use states.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>`Results<\/jats:title>\n                  <jats:p>The third-order model was the best fit for the data. The percentage of former smokers, menthol cigarette smokers, non-menthol cigarette smokers, and e-cigarette\/dual users in Wave 3 that remained in the same tobacco use state in Wave 4 ranged from 63.4% to 97.2%, 29.2% to 89.8%, 34.8% to 89.7%, and 20.5% to 80.0%, respectively, dependent on tobacco use history. Individuals who were current tobacco users, but former smokers in the prior two years, were most likely to quit.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Transition probabilities between tobacco use states varied widely depending on tobacco use history. Higher-order Markov models improve estimation of tobacco use over time and can inform understanding of trajectories of tobacco use behavior.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Implications<\/jats:title>\n                  <jats:p>Findings from this study suggest that transition probabilities between tobacco use states vary widely depending on tobacco use history. Tobacco product users (cigarette or e-cigarette\/dual users) who were in the same tobacco use state in the prior two years were least likely to quit. Individuals who were current tobacco users, but former smokers in the prior two years, were most likely to quit. Quitting smoking for at least two years is an important milestone in the process of cessation.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/ntr\/ntad171","type":"journal-article","created":{"date-parts":[[2023,9,4]],"date-time":"2023-09-04T21:03:11Z","timestamp":1693861391000},"page":"194-202","source":"Crossref","is-referenced-by-count":1,"title":["Improving Prediction of Tobacco Use Over Time: Findings from Waves 1\u20134 of the Population Assessment of Tobacco and Health Study"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0183-6753","authenticated-orcid":false,"given":"Sarah D","family":"Mills","sequence":"first","affiliation":[{"name":"Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina , Chapel Hill, NC , USA"},{"name":"Lineberger Comprehensive Cancer Center, University of North Carolina , Chapel Hill, NC , 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