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      Smoking prevalence in Medicaid has been declining at a negligible rate

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          Abstract

          Background

          In recent decades the overall smoking prevalence in the US has fallen steadily. This study examines whether the same trend is seen in the Medicaid population.

          Methods and findings

          National Health Interview Survey (NHIS) data from 17 consecutive annual surveys from 1997 to 2013 (combined N = 514,043) were used to compare smoking trends for 4 insurance groups: Medicaid, the Uninsured, Private Insurance, and Other Coverage. Rates of chronic disease and psychological distress were also compared.

          Results

          Adjusted smoking prevalence showed no detectable decline in the Medicaid population (from 33.8% in 1997 to 31.8% in 2013, trend test P = 0.13), while prevalence in the other insurance groups showed significant declines (38.6%-34.7% for the Uninsured, 21.3%-15.8% for Private Insurance, and 22.6%-16.8% for Other Coverage; all P’s<0.005). Among individuals who have ever smoked, Medicaid recipients were less likely to have quit (38.8%) than those in Private Insurance (62.3%) or Other Coverage (69.8%; both P’s<0.001). Smokers in Medicaid were more likely than those in Private Insurance and the Uninsured to have chronic disease (55.0% vs 37.3% and 32.4%, respectively; both P’s<0.01). Smokers in Medicaid were also more likely to experience severe psychological distress (16.2% for Medicaid vs 3.2% for Private Insurance and 7.6% for the Uninsured; both P’s<0.001).

          Conclusions

          The high and relatively unchanging smoking prevalence in the Medicaid population, low quit ratio, and high rates of chronic disease and severe psychological distress highlight the need to focus on this population. A targeted and sustained campaign to help Medicaid recipients quit smoking is urgently needed.

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          Most cited references13

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          Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey.

          This study presents estimates of lifetime and 12-month prevalence of 14 DSM-III-R psychiatric disorders from the National Comorbidity Survey, the first survey to administer a structured psychiatric interview to a national probability sample in the United States. The DSM-III-R psychiatric disorders among persons aged 15 to 54 years in the noninstitutionalized civilian population of the United States were assessed with data collected by lay interviewers using a revised version of the Composite International Diagnostic Interview. Nearly 50% of respondents reported at least one lifetime disorder, and close to 30% reported at least one 12-month disorder. The most common disorders were major depressive episode, alcohol dependence, social phobia, and simple phobia. More than half of all lifetime disorders occurred in the 14% of the population who had a history of three or more comorbid disorders. These highly comorbid people also included the vast majority of people with severe disorders. Less than 40% of those with a lifetime disorder had ever received professional treatment, and less than 20% of those with a recent disorder had been in treatment during the past 12 months. Consistent with previous risk factor research, it was found that women had elevated rates of affective disorders and anxiety disorders, that men had elevated rates of substance use disorders and antisocial personality disorder, and that most disorders declined with age and with higher socioeconomic status. The prevalence of psychiatric disorders is greater than previously thought to be the case. Furthermore, this morbidity is more highly concentrated than previously recognized in roughly one sixth of the population who have a history of three or more comorbid disorders. This suggests that the causes and consequences of high comorbidity should be the focus of research attention. The majority of people with psychiatric disorders fail to obtain professional treatment. Even among people with a lifetime history of three or more comorbid disorders, the proportion who ever obtain specialty sector mental health treatment is less than 50%. These results argue for the importance of more outreach and more research on barriers to professional help-seeking.
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            Annual healthcare spending attributable to cigarette smoking: an update.

            Fifty years after the first Surgeon General's report, tobacco use remains the nation's leading preventable cause of death and disease, despite declines in adult cigarette smoking prevalence. Smoking-attributable healthcare spending is an important part of overall smoking-attributable costs in the U.S.
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              An invariant dimensional liability model of gender differences in mental disorder prevalence: evidence from a national sample.

              Epidemiological studies of categorical mental disorders consistently report that gender differences exist in many disorder prevalence rates and that disorders are often comorbid. Can a dimensional multivariate liability model be developed to clarify how gender impacts diverse, comorbid mental disorders? We pursued this possibility in the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; N = 43,093). Gender differences in prevalence were systematic such that women showed higher rates of mood and anxiety disorders, and men showed higher rates of antisocial personality and substance use disorders. We next investigated patterns of disorder comorbidity and found that a dimensional internalizing-externalizing liability model fit the data well, where internalizing is characterized by mood and anxiety disorders, and externalizing is characterized by antisocial personality and substance use disorders. This model was gender invariant, indicating that observed gender differences in prevalence rates originate from women and men's different average standings on latent internalizing and externalizing liability dimensions. As hypothesized, women showed a higher mean level of internalizing, while men showed a higher mean level of externalizing. We discuss implications of these findings for understanding gender differences in psychopathology and for classification and intervention. PsycINFO Database Record (c) 2012 APA, all rights reserved.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                25 May 2017
                2017
                : 12
                : 5
                : e0178279
                Affiliations
                [1 ]Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, California, United States of America
                [2 ]Moores Cancer Center, University of California, San Diego, La Jolla, California, United States of America
                [3 ]Department of Mathematics, University of California, San Diego, La Jolla, California, United States of America
                [4 ]Department of Health Care Services, Sacramento, California, United States of America
                University College London, UNITED KINGDOM
                Author notes

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

                • Conceptualization: SHZ CMA YLZ.

                • Formal analysis: YLZ ACG SHZ CMA.

                • Funding acquisition: NDK SHZ.

                • Investigation: SHZ CMA YLZ NDK.

                • Methodology: SHZ ACG YLZ.

                • Resources: NDK SHZ.

                • Writing – original draft: SHZ CMA YLZ.

                • Writing – review & editing: SHZ CMA YLZ ACG NDK.

                Author information
                http://orcid.org/0000-0002-4149-3441
                Article
                PONE-D-16-35379
                10.1371/journal.pone.0178279
                5479677
                28542637
                89a9eb40-102a-4365-aae1-92fe2d56f0a4
                © 2017 Zhu et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 2 September 2016
                : 10 May 2017
                Page count
                Figures: 3, Tables: 4, Pages: 15
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100005227, Centers for Medicare and Medicaid Services;
                Award ID: 1B1-CMS330883
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: U01-CA154280
                Award Recipient :
                This work was supported by the Centers for Medicare and Medicaid Services https://www.cms.gov/ (Grant #1B1-CMS330883, NDK) and by the National Cancer Institute under the State and Community Tobacco Initiative http://www.cancer.gov/ (Grant #U01-CA154280, SHZ). The conclusions presented in this paper are those of the authors and do not reflect the official policy of the sponsors. The study sponsors had no role in study design; data collection, analysis, or interpretation; writing of the report; or the decision to submit for publication.
                Categories
                Research Article
                Engineering and Technology
                Management Engineering
                Risk Management
                Insurance
                Biology and Life Sciences
                Behavior
                Habits
                Smoking Habits
                Social Sciences
                Economics
                Health Economics
                Health Insurance
                Medicine and Health Sciences
                Health Care
                Health Economics
                Health Insurance
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Confidence Intervals
                People and Places
                Demography
                People and Places
                Population Groupings
                Age Groups
                Adults
                Medicine and Health Sciences
                Pulmonology
                Smoking Related Disorders
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Substance-Related Disorders
                Smoking Related Disorders
                Medicine and Health Sciences
                Public and Occupational Health
                Substance-Related Disorders
                Smoking Related Disorders
                Medicine and Health Sciences
                Custom metadata
                The data used in this study is from the National Health Interview Survey (NHIS) dataset, available for public use from the Centers for Disease Control and Prevention (CDC). All data, instruments, and related documentation can be accessed at https://www.cdc.gov/nchs/nhis/data-questionnaires-documentation.htm.

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