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      Smoking prevalence and trends among a U.S. national sample of women of reproductive age in rural versus urban settings

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          Abstract

          U.S. smoking prevalence is declining at a slower rate in rural than urban settings and contributing to regional health disparities. Cigarette smoking among women of reproductive age is particularly concerning due to the potential for serious maternal and infant adverse health effects should a smoker become pregnant. The aim of the present study was to examine whether this rural-urban disparity impacts women of reproductive age (ages 15–44) including pregnant women. Data came from the ten most recent years of the U.S. National Survey on Drug Use and Health (2007–2016). We estimated prevalence of current smoking and nicotine dependence among women categorized by rural-urban residence, pregnancy status, and trends using chi-square testing and multivariable modeling while adjusting for common risk factors for smoking. Despite overall decreasing trends in smoking prevalence, prevalence was higher among rural than urban women of reproductive age overall ( χ 2 (1) = 579.33, p < .0001) and among non-pregnant ( χ 2 (1) = 578.0, p < .0001) and pregnant ( χ 2 (1) = 79.69, p < .0001) women examined separately. An interaction between residence and pregnancy status showed adjusted odds of smoking among urban pregnant compared to non-pregnant women (AOR = .58, [.53 –.63]) were lower than those among rural pregnant compared to non-pregnant women (AOR = 0.75, [.62 –.92]), consistent with greater pregnancy-related smoking cessation among urban pregnant women. Prevalence of nicotine dependence was also higher in rural than urban smokers overall ( χ 2 (2) = 790.42, p < .0001) and among non-pregnant ( χ 2(2) = 790.58, p < .0001) and pregnant women examined separately ( χ 2(2) = 63.69, p < .0001), with no significant changes over time. Associations involving residence and pregnancy status remained significant in models adjusting for covariates ( ps < 0.05). Results document greater prevalence of smoking and nicotine dependence and suggest less pregnancy-related quitting among rural compared to urban women, disparities that have potential for direct, multi-generational adverse health impacts.

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          Tobacco control and the reduction in smoking-related premature deaths in the United States, 1964-2012.

          January 2014 marks the 50th anniversary of the first surgeon general's report on smoking and health. This seminal document inspired efforts by governments, nongovernmental organizations, and the private sector to reduce the toll of cigarette smoking through reduced initiation and increased cessation. To model reductions in smoking-related mortality associated with implementation of tobacco control since 1964. Smoking histories for individual birth cohorts that actually occurred and under likely scenarios had tobacco control never emerged were estimated. National mortality rates and mortality rate ratio estimates from analytical studies of the effect of smoking on mortality yielded death rates by smoking status. Actual smoking-related mortality from 1964 through 2012 was compared with estimated mortality under no tobacco control that included a likely scenario (primary counterfactual) and upper and lower bounds that would capture plausible alternatives. National Health Interview Surveys yielded cigarette smoking histories for the US adult population in 1964-2012. Number of premature deaths avoided and years of life saved were primary outcomes. Change in life expectancy at age 40 years associated with change in cigarette smoking exposure constituted another measure of overall health outcomes. In 1964-2012, an estimated 17.7 million deaths were related to smoking, an estimated 8.0 million (credible range [CR], 7.4-8.3 million, for the lower and upper tobacco control counterfactuals, respectively) fewer premature smoking-related deaths than what would have occurred under the alternatives and thus associated with tobacco control (5.3 million [CR, 4.8-5.5 million] men and 2.7 million [CR, 2.5-2.7 million] women). This resulted in an estimated 157 million years (CR, 139-165 million) of life saved, a mean of 19.6 years for each beneficiary (111 million [CR, 97-117 million] for men, 46 million [CR, 42-48 million] for women). During this time, estimated life expectancy at age 40 years increased 7.8 years for men and 5.4 years for women, of which tobacco control is associated with 2.3 years (CR, 1.8-2.5) (30% [CR, 23%-32%]) of the increase for men and 1.6 years (CR, 1.4-1.7) (29% [CR, 25%-32%]) for women. Tobacco control was estimated to be associated with avoidance of 8 million premature deaths and an estimated extended mean life span of 19 to 20 years. Although tobacco control represents an important public health achievement, efforts must continue to reduce the effect of smoking on the nation's death toll.
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            The nicotine dependence syndrome scale: a multidimensional measure of nicotine dependence.

            We report the development of a new multidimensional questionnaire to measure nicotine dependence, based on Edwards's syndromal conceptualization of dependence. We present three studies. In study 1, we administered the Nicotine Dependence Syndrome Scale (NDSS) to 317 smokers in a smoking cessation study. Factor analysis of the NDSS revealed five factors: Drive (craving and withdrawal, and subjective compulsion to smoke), priority (preference for smoking over other reinforcers), tolerance (reduced sensitivity to the effects of smoking), continuity (regularity of smoking rate), and stereotypy (invariance of smoking). A single overall score based on the first principal component, NDSS-T, was retained as a single core measure of dependence. The NDSS showed promising psychometric properties: NDSS-T and factor scores showed strong associations with dependence-relevant measures, even when we controlled for scores on the Fagerström Tolerance Questionnaire (FTQ); and the NDSS predicted urges when smoking, withdrawal in acute abstinence, and outcome in cessation. The five factor scores showed differential patterns of correlations with external validators, supporting the multidimensionality of the measure. In study 2, we revised the NDSS to expand some subscales and administered it to 802 smokers in a cessation study. The same five factors were extracted, the internal reliability of some subscales was improved, and the factor scores again showed associations with dependence-relevant validators, which were largely maintained when we controlled for FTQ scores. In study 3, with 91 smokers in a cessation trial, we established that the test-retest reliability of the subscales was adequate. Thus, the NDSS presents a valid multidimensional assessment of nicotine dependence that may expand on current measures.
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              A growing geographic disparity: Rural and urban cigarette smoking trends in the United States

              Rural areas of the United States have a higher smoking prevalence than urban areas. However, no recent studies have rigorously examined potential changes in this disparity over time or whether the disparity can be explained by demographic or psychosocial characteristics associated with smoking. The present study used yearly cross sectional data from the National Survey on Drug Use and Health from 2007 through 2014 to examine cigarette smoking trends in rural versus urban areas of the United States. The analytic sample included 303,311 respondents. Two regression models were built to examine (a) unadjusted rural and urban trends in prevalence of current smoking and (b) whether differences remained after adjusting for demographic and psychosocial characteristics. Results of the unadjusted model showed disparate and diverging cigarette use trends during the 8-year time period. The adjusted model also showed diverging trends, initially with no or small differences that became more pronounced across the 8-year period. We conclude that differences reported in earlier studies may be explained by differences in rural versus urban demographic and psychosocial risk factors, while more recent and growing disparities appear to be related to other factors. These emergent differences may be attributable to policy-level tobacco control and regulatory factors that disproportionately benefit urban areas such as enforcement of regulations around the sale and marketing of tobacco products and treatment availability. Strong federal policies and targeted or tailored interventions may be important to expanding tobacco control and regulatory benefits to vulnerable populations including rural Americans.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                28 November 2018
                2018
                : 13
                : 11
                : e0207818
                Affiliations
                [1 ] Vermont Center on Behavior and Health, University of Vermont, Burlington, Vermont, United States of America
                [2 ] Department of Psychiatry, University of Vermont, Burlington, Vermont, United States of America
                [3 ] Ohio Colleges of Medicine Government Resource Center, The Ohio State University, Columbus, OH, United States of America
                [4 ] Department of Psychological Science, University of Vermont, Burlington, Vermont, United States of America
                [5 ] Medical Biostatistics, University of Vermont, Burlington, Vermont, United States of America
                [6 ] Westat, Center for Evaluation and Coordination of Training and Research (CECTR) in Tobacco Regulatory Science, Rockville, Maryland, United States of America
                [7 ] Department of Oncology, Georgetown University Medical Center, Washington District of Columbia, United States of America
                [8 ] Rehabilitation Institute, Southern Illinois University, Carbondale, Illinois, United States of America
                [9 ] Department of Health Behavior, Roswell Park Comprehensive Cancer Center, Buffalo, New York, United States of America
                Brown University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                ‡ These authors also contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-8954-8763
                http://orcid.org/0000-0002-9763-1129
                Article
                PONE-D-18-24385
                10.1371/journal.pone.0207818
                6261597
                30485376
                2c12bf57-9173-411b-ac57-9c2dfd6ecbd2

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 18 August 2018
                : 6 November 2018
                Page count
                Figures: 2, Tables: 3, Pages: 14
                Funding
                Funded by: National Institute on Drug Abuse (US)
                Award ID: U54CA189222
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000026, National Institute on Drug Abuse;
                Award ID: P50DA036114
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: P50CA180908
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: U54CA189222
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000026, National Institute on Drug Abuse;
                Award ID: T32DA07242
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: P20GM103644
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000071, National Institute of Child Health and Human Development;
                Award ID: R01HD078332
                Award Recipient :
                Funded by: National Institute of Child Health and Human Development (US)
                Award ID: R01HD075669
                Award Recipient :
                All of the following awards are awarded to SH. This research was conducted as part of the activities of the Tobacco Centers of Regulatory Science (TCORS) Vulnerable Populations Working Group, which is a collaborative effort supported by the National Institutes of Health (NIH) https://www.nih.gov/health-information and Food and Drug administration (FDA) https://www.fda.gov/. Support came from TCORS award P50DA036114 from the National Institute on Drug Abuse (NIDA) https://www.drugabuse.gov/ and FDA, TCORS Award P50CA180908 from the National Cancer Institute (NCI) https://www.cancer.gov/ and FDA, Center for Evaluation and Coordination of Training and Research award U54CA189222 from NCI and FDA, Institutional Training Grant award T32DA07242 from NIDA, Centers of Biomedical Research Excellence P20GM103644 award from the National Institute on General Medical Sciences https://www.nigms.nih.gov, and Research awards R01HD078332 from the National Institute of Child Health and Human Development (NICHD) https://www.nichd.nih.gov/ and R01HD075669 from NICHD and Centers for Disease Control and Prevention https://www.cdc.gov. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or Food and Drug Administration. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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                All relevant data and materials may be located here: ( https://www.datafiles.samhsa.gov/study-series/national-survey-drug-use-and-health-nsduh-nid13517).

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