Marjaana Pennanen1, Ulla Broms1, Tellervo Korhonen2, Ari Haukkala3, Timo Partonen4, Annamari Tuulio-Henriksson5, Tiina Laatikainen6, Kristiina Patja7, Jaakko Kaprio8. 1. Hjelt Institute, Department of Public Health, University of Helsinki, P.O. Box 41, Mannerheimintie 172, 00014 Helsinki, Finland; National Institute for Health and Welfare, P.O. Box 30, Mannerheimintie 166, FI-00271 Helsinki, Finland; Health and Social Services Department, Municipality of Askola, Askolantie 30, FI-07500 Askola, Finland. 2. Hjelt Institute, Department of Public Health, University of Helsinki, P.O. Box 41, Mannerheimintie 172, 00014 Helsinki, Finland; National Institute for Health and Welfare, P.O. Box 30, Mannerheimintie 166, FI-00271 Helsinki, Finland. 3. Department of Social Research, University of Helsinki, P.O. Box 54, Unioninkatu 37, 00014 Helsinki, Finland. 4. National Institute for Health and Welfare, P.O. Box 30, Mannerheimintie 166, FI-00271 Helsinki, Finland. 5. National Institute for Health and Welfare, P.O. Box 30, Mannerheimintie 166, FI-00271 Helsinki, Finland; Social Insurance Institution of Finland, P.O. Box 20, Nördenskiöldinkatu 12, 00232 Helsinki, Finland. 6. National Institute for Health and Welfare, P.O. Box 30, Mannerheimintie 166, FI-00271 Helsinki, Finland; Institute of Public Health and Clinical Nutrition, University of Eastern Finland, P.O. Box 1627, Yliopistonranta 1, FI-70211 Kuopio, Finland; Hospital District of North Karelia, P.O. Box 111, Tikkamäentie 16, FI-80101 Joensuu, Finland. 7. National Institute for Health and Welfare, P.O. Box 30, Mannerheimintie 166, FI-00271 Helsinki, Finland; Pro Medico, P.O. Box 49, Mäkelänkatu 2, 00501 Helsinki, Finland. 8. Hjelt Institute, Department of Public Health, University of Helsinki, P.O. Box 41, Mannerheimintie 172, 00014 Helsinki, Finland; National Institute for Health and Welfare, P.O. Box 30, Mannerheimintie 166, FI-00271 Helsinki, Finland; Institute for Molecular Medicine Finland (FIMM), P.O. Box 20, Tukholmankatu 8, 00290 Helsinki, Finland. Electronic address: jaakko.kaprio@helsinki.fi.
Abstract
INTRODUCTION: Low socio-economic status (SES) is strongly related to smoking, but studies examining the association of SES with nicotine dependence (ND) are scarce. The aim of this study was to examine the associations of SES and marital status with smoking, multiple measures of ND, and cotinine as a nicotine intake biomarker. METHODS: The sample comprised 1746 ever smokers, sampled from the National FINRISK 2007 Study, who had completed a tobacco specific questionnaire in addition to the standard clinical examination. The Fagerström Test for Nicotine Dependence (FTND), the Heaviness of Smoking Index (HSI), the Nicotine Dependence Syndrome Scale (NDSS), and the Hooked On Nicotine Checklist (HONC) were assessed, while plasma cotinine was measured as a biomarker of nicotine exposure in daily smokers. Univariate and multivariate associations were assessed by linear regression and multinomial logistic regression. RESULTS: In multivariate models, lower education was associated with higher FTND and HSI, income with HSI, and occupation with HSI (men only), FTND, HONC and NDSS scores. Lower education was related to higher cotinine levels among daily smokers, although the association diminished slightly after adjusting for daily smoking amount. Living without a spouse was associated with daily smoking and higher ND. CONCLUSION: In this cross-sectional study low SES was linked with higher ND among current smokers, while low SES was associated with higher cotinine levels among daily smokers. Living alone was linked with higher ND. Longitudinal studies are warranted to further explore these associations. As lower SES smokers are more addicted they may need more targeted cessation services to succeed in quitting smoking.
INTRODUCTION: Low socio-economic status (SES) is strongly related to smoking, but studies examining the association of SES with nicotine dependence (ND) are scarce. The aim of this study was to examine the associations of SES and marital status with smoking, multiple measures of ND, and cotinine as a nicotine intake biomarker. METHODS: The sample comprised 1746 ever smokers, sampled from the National FINRISK 2007 Study, who had completed a tobacco specific questionnaire in addition to the standard clinical examination. The Fagerström Test for Nicotine Dependence (FTND), the Heaviness of Smoking Index (HSI), the Nicotine Dependence Syndrome Scale (NDSS), and the Hooked On Nicotine Checklist (HONC) were assessed, while plasma cotinine was measured as a biomarker of nicotine exposure in daily smokers. Univariate and multivariate associations were assessed by linear regression and multinomial logistic regression. RESULTS: In multivariate models, lower education was associated with higher FTND and HSI, income with HSI, and occupation with HSI (men only), FTND, HONC and NDSS scores. Lower education was related to higher cotinine levels among daily smokers, although the association diminished slightly after adjusting for daily smoking amount. Living without a spouse was associated with daily smoking and higher ND. CONCLUSION: In this cross-sectional study low SES was linked with higher ND among current smokers, while low SES was associated with higher cotinine levels among daily smokers. Living alone was linked with higher ND. Longitudinal studies are warranted to further explore these associations. As lower SES smokers are more addicted they may need more targeted cessation services to succeed in quitting smoking.
Authors: Nicolle M Krebs; Allshine Chen; Junjia Zhu; Dongxiao Sun; Jason Liao; Andrea L Stennett; Joshua E Muscat Journal: Am J Epidemiol Date: 2016-06-16 Impact factor: 4.897