Emmanuel Wiernik1, Guillaume Airagnes2, Emeline Lequy3, Ramchandar Gomajee4, Maria Melchior4, Anne-Laurence Le Faou5, Frédéric Limosin6, Marcel Goldberg7, Marie Zins8, Cédric Lemogne6. 1. Inserm, UMS 011, Population-based Epidemiological Cohorts, Villejuif, France. 2. Inserm, UMS 011, Population-based Epidemiological Cohorts, Villejuif, France; Inserm, UMR 1168, VIMA, Villejuif, France; AP-HP, Hôpitaux Universitaires Paris Ouest, Centre Ambulatoire d'Addictologie, Paris, France; Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine, Paris, France. Electronic address: guillaume.airagnes@aphp.fr. 3. Inserm, UMS 011, Population-based Epidemiological Cohorts, Villejuif, France; Inserm, UMR 1168, VIMA, Villejuif, France. 4. Sorbonne Universités, UPMC Université Paris 06, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP UMRS 1136), F75012 Paris, France. 5. AP-HP, Hôpitaux Universitaires Paris Ouest, Centre Ambulatoire d'Addictologie, Paris, France. 6. Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine, Paris, France; AP-HP, Hôpitaux Universitaires Paris Ouest, Service de Psychiatrie de l'adulte et du sujet âgé, Paris, France; Inserm, U894, Centre Psychiatrie et Neurosciences, Paris, France. 7. Inserm, UMS 011, Population-based Epidemiological Cohorts, Villejuif, France; Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine, Paris, France. 8. Inserm, UMS 011, Population-based Epidemiological Cohorts, Villejuif, France; Inserm, UMR 1168, VIMA, Villejuif, France; Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine, Paris, France.
Abstract
AIMS: To examine the cross-sectional and longitudinal associations between depressive symptoms and electronic cigarette (e-cig) use in a large population-based sample while taking into account smoking status and sociodemographic confounders. METHODS: Participants from the French Constances cohort were included from February 2012 to December 2016. Smoking status, e-cig use (never/ever/current) and nicotine concentration were self-reported. Depressive symptoms were measured with the Center for Epidemiologic Studies Depression (CES-D) scale. Logistic regressions were used to provide odds ratios (ORs) and 95% confidence intervals (95%CI) of e-cig use according to depressive symptoms, adjusting for age, sex and education. RESULTS: In cross-sectional analyses (n = 35,337), depressive symptoms (i.e. a CES-D score ≥ 19) were associated with both ever (OR [95%CI]: 1.67 [1.53-1.82]) and current (1.73 [1.53-1.96]) e-cig use with a dose-dependent relationship (p-trend<0.001). In longitudinal analyses (n = 30,818), depressive symptoms at baseline were associated with current e-cig use at follow-up (2.02 [1.72-2.37]) with a similar dose-dependent relationship. These associations were mainly significant among smokers or former smokers at baseline. Furthermore, among smokers at baseline, depressive symptoms were associated with dual consumption at follow-up (1.58 [1.41-1.77]), whereas among former smokers, they were associated with either smoking only (1.52 [1.34-1.73]) or e-cig use only (2.02 [1.64-2.49]), but not with dual consumption (1.11 [0.73-1.68]) at follow-up. Finally, depressive symptoms were positively associated with nicotine concentration among e-cig users at baseline. CONCLUSIONS: Depressive symptoms were positively associated with e-cig use in both cross-sectional and longitudinal analyses with a dose-dependent relationship. In addition, nicotine concentration and depressive symptoms were positively associated.
AIMS: To examine the cross-sectional and longitudinal associations between depressive symptoms and electronic cigarette (e-cig) use in a large population-based sample while taking into account smoking status and sociodemographic confounders. METHODS:Participants from the French Constances cohort were included from February 2012 to December 2016. Smoking status, e-cig use (never/ever/current) and nicotine concentration were self-reported. Depressive symptoms were measured with the Center for Epidemiologic Studies Depression (CES-D) scale. Logistic regressions were used to provide odds ratios (ORs) and 95% confidence intervals (95%CI) of e-cig use according to depressive symptoms, adjusting for age, sex and education. RESULTS: In cross-sectional analyses (n = 35,337), depressive symptoms (i.e. a CES-D score ≥ 19) were associated with both ever (OR [95%CI]: 1.67 [1.53-1.82]) and current (1.73 [1.53-1.96]) e-cig use with a dose-dependent relationship (p-trend<0.001). In longitudinal analyses (n = 30,818), depressive symptoms at baseline were associated with current e-cig use at follow-up (2.02 [1.72-2.37]) with a similar dose-dependent relationship. These associations were mainly significant among smokers or former smokers at baseline. Furthermore, among smokers at baseline, depressive symptoms were associated with dual consumption at follow-up (1.58 [1.41-1.77]), whereas among former smokers, they were associated with either smoking only (1.52 [1.34-1.73]) or e-cig use only (2.02 [1.64-2.49]), but not with dual consumption (1.11 [0.73-1.68]) at follow-up. Finally, depressive symptoms were positively associated with nicotine concentration among e-cig users at baseline. CONCLUSIONS:Depressive symptoms were positively associated with e-cig use in both cross-sectional and longitudinal analyses with a dose-dependent relationship. In addition, nicotine concentration and depressive symptoms were positively associated.
Authors: Kayla Rae Farrell; Michael Weitzman; Emma Karey; Teresa K Y Lai; Terry Gordon; Shu Xu Journal: BMC Public Health Date: 2022-06-07 Impact factor: 4.135
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Authors: Olufunmilayo H Obisesan; Mohammadhassan Mirbolouk; Albert D Osei; Olusola A Orimoloye; S M Iftekhar Uddin; Omar Dzaye; Omar El Shahawy; Mahmoud Al Rifai; Aruni Bhatnagar; Andrew Stokes; Emelia J Benjamin; Andrew P DeFilippis; Michael J Blaha Journal: JAMA Netw Open Date: 2019-12-02