{"doi":"10.1111/ajad.13524","title":"Factors associated with transitions in tobacco product use states among young adults aged 18–29 years","abstract":"BACKGROUND AND OBJECTIVES: This study examined young adults' tobacco use transitions based on their past 30-day use states, and identified factors associated with their transitions. METHODS: Participants (N = 12377) were young adults aged 18-29 years at Wave 1 of the Population Assessment of Tobacco and Health (PATH) study. Self-reported tobacco use states were categorized by the number of past-month use days (0, 1-4, 5-8, 9-12, 13-30 days) for cigarettes, electronic cigarettes [e-cigarettes], traditional cigars, filtered cigars, cigarillos, smokeless tobacco (SLT), and hookah. Multistate Markov models examined transitions between use states across Waves 1-5 of unweighted PATH data and multinomial logistic regressions examined predictors of transitions. RESULTS: Most young adults remained nonusers across adjacent waves for all products (88%-99%). Collapsed across waves, transitioning from use at any level to nonuse (average 46%-67%) was more common than transitioning from nonuse to use at any level (average 4%-10%). Several factors that predicted riskier patterns of use (i.e., transitioning to use and/or remaining a user across adjacent waves) were similar across most products: male, Black, Hispanic, lower education levels, and lower harm perceptions. In contrast, other factors predicted riskier patterns for only select products (e.g., e-cigarette and SLT use among Whites). DISCUSSION AND CONCLUSIONS: Few sampled young adults escalated their tobacco use over time, and escalations for many products were predicted by similar factors. SCIENTIFIC SIGNIFICANCE: Prevention and regulatory efforts targeted towards adolescents should continue, but also be expanded into young adulthood. These same efforts should consider both shared and unique factors that influence use transitions.","journal":"American Journal on Addictions","year":2024,"id":467381,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.78,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":484591,"name":"Nicholas A. Turiano","orcid":"0000-0002-2266-2959","position":1,"is_corresponding":false},{"id":445024,"name":"Bethany C. Bray","orcid":"0000-0001-8627-3939","position":2,"is_corresponding":false},{"id":975945,"name":"Andrea R. Milstred","orcid":"0000-0001-5477-3007","position":3,"is_corresponding":false},{"id":691904,"name":"Margaret G. Childers","orcid":null,"position":4,"is_corresponding":false},{"id":653463,"name":"Geri Dino","orcid":"0000-0002-1613-2011","position":5,"is_corresponding":false},{"id":490190,"name":"Katelyn F. Romm","orcid":"0000-0002-9552-0732","position":6,"is_corresponding":false},{"id":484592,"name":"Melissa D. Blank","orcid":"0000-0001-5965-7224","position":0,"is_corresponding":true}],"reference_count":34,"raw_metadata":null,"created_at":"2026-07-19T02:05:10.907983Z","pmid":"38402462","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}