{"doi":"10.1093/ntr/ntae303","title":"Considering Relative Rurality in Tobacco Regulatory Science","abstract":"The overarching goal of our TCORS Center, AppalTRUST (Appalachian Tobacco Regulatory Science Team), is to evaluate the impact of the Federal Drug Administration (FDA) Center for Tobacco Products (CTP) regulatory policies in rural communities. Our Center focuses on a historically understudied population disproportionately affected by tobacco use. As of 2018-2019, Kentucky had a tobacco product use prevalence among adults that was nearly 10 points above the national average (24.8% vs. 15.4%).1 More recently, the use rate of any tobacco product was estimated to be higher in rural Kentucky (32.4%) versus urban locations in the state (26.4%).2 To capture the variability of tobacco use in rural places, our Center purposely chose to include two rural catchment areas within Appalachian Kentucky; one inarguably rural and the other semi-rural/peri-urban, bordering on a metropolitan area. With data collection ongoing, the purpose of this commentary is to describe an adaptable method for quantifying rurality in Appalachian communities. Rurality is challenging to define using solely quantitative or qualitative measures, since it exists in reality as a continuum, rather than simply urbanity’s binary opposite. In this commentary, we explore an alternative measure of rurality, the Index of Relative Rurality (IRR),3 that could provide novel insight into the relationship between rurality and tobacco use, which we suspect is more nuanced than suggested by previous research. In national measures, rurality has been variously defined with respect to population size, nearness to urban areas, commuting flows, and “remoteness.” The most widely used rurality measures are released decennially by the USDA Economic Research Service,4 including Rural-Urban Continuum (RUC) codes, Primary Rural-Urban Commuting Area (RUCA) codes, and Frontier and Remote Areas (FAR) codes. RUC codes are ordinal, based solely on proximity to the nearest metro area and the size of that area; RUCA codes extend RUC codes by also including commuting patterns, but these codes are categorical rather than ordinal; and FAR codes are not applicable to urban areas, so not all locations have them. The limitation of these measures in our context is that they are typically or necessarily dichotomized, which prevents gauging differences, such as tobacco use prevalence, among communities with varying rurality. In contrast to RUC, RUCA, and FAR codes, the IRR is a composite score capturing the rurality of a geographic area (e.g., census tract, zip code area, or county) relative to all other geographic areas at the same level in the United States. IRR codes are continuous, with scores closer to 0 indicating the least rural/most urban, and those closer to 1 suggesting the highest degree of rurality. IRR codes are the unweighted averages of four attributes, each rescaled to range from 0 to 1: log-transformed population size, log-transformed population density, network distance (i.e., degree of remoteness) to the nearest metropolitan county, and built-up area (urban development as a percentage of total land area). The IRR has two immediate advantages for studying tobacco regulatory science (TRS) in rural areas: (1) it can be evaluated at any level of geography for which there are corresponding data available (whereas other measures of rural/urban status depend on fixed geographies, such as distance of a county to nearest metro); and (2) it is a continuous measure that does not rely on specific cutoffs and thus can be used as a scale variable in analysis.5 An additional benefit of the IRR is that it can be used to quantify rurality of the “activity space” of an individual, namely the geographic area bounded by places they visit on a regular basis. While the IRR has been used in a limited number of prior studies,5,6 to our knowledge it has not previously been applied to TRS, despite its potential for better illustrating patterns of exposure to tobacco policies and marketing in routine crossing of ad","journal":"Nicotine & Tobacco Research","year":2024,"id":470200,"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":0.7686,"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":1304243,"name":"Ann E. Kingsolver","orcid":"0000-0002-3691-3050","position":1,"is_corresponding":false},{"id":1172917,"name":"W. Jay Christian","orcid":"0000-0001-6904-3971","position":2,"is_corresponding":false},{"id":1175744,"name":"Ellen J. Hahn","orcid":"0000-0002-8480-1010","position":3,"is_corresponding":false},{"id":659558,"name":"Teresa M. Waters","orcid":"0000-0002-3823-5177","position":4,"is_corresponding":false},{"id":366590,"name":"Shyanika W. Rose","orcid":"0000-0002-4200-1197","position":5,"is_corresponding":false},{"id":401772,"name":"Mikhail N. Koffarnus","orcid":"0000-0002-7923-7734","position":6,"is_corresponding":false},{"id":997323,"name":"Seth Himelhoch","orcid":"0000-0002-2183-0340","position":7,"is_corresponding":false},{"id":598377,"name":"Mary Kay Rayens","orcid":"0000-0001-8465-8763","position":0,"is_corresponding":true}],"reference_count":12,"raw_metadata":null,"created_at":"2026-07-19T02:05:36.656771Z","pmid":"39700459","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":[]}