Toward a comprehensive developmental model of smoking initiation and nicotine dependence

Abstract

Background This study aims to identify predictors of smoking initiation and nicotine dependence (ND) to develop a comprehensive risk-factor model based on Kendler’s development model for major depression. Methods Data were drawn from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), Wave 2 (n = 34,653). Risk factors were divided into 5 developmental tiers according to Kendler’s model (childhood, early adolescence, late adolescence, adulthood, past-year). Hierarchical logistic regression models were built to predict the risk of smoking initiation and the risk of ND, given initiation. The continuation ratio (CR) was tested by ordinal logistic regression to examine whether the impact of the predictors was the same on smoking initiation or ND. Results The final models highlighted the importance of different tiers for each outcome. The CR identified substantial differences in the predictors of smoking initiation versus ND. Childhood tier appears to be more determinant for smoking initiation while the effect of more distal tiers (i.e. childhood and early adolescence) was tempered by more proximal ones (i.e. late adolescence, adulthood and past-year) in ND, with few sex differences. Conclusions The differential effect of some predictors on each outcome shows the complexity of pathways from smoking initiation to ND. While some risk factors may be shared, others impact only at one stage or have even an inverse effect. An adaptation of Kendler’s developmental model for major depression showed high predictive power for smoking initiation and ND.

A review of epidemiologic research on smoking behavior among persons with alcohol and illicit substance use disorders

“…Similar to smoking, current and lifetime nicotine dependence prevalences were higher among adults with past-year AUDs/ SUDs and lifetime AUDs than those without (Table 3). While this was generally consistent across studies, a study using data from adults who reported lifetime smoking and completed Wave 2 of the NESARC found that respondents with a past-year AUD were more likely to report past-year nicotine dependence while adults with lifetime AUD were less likely to report past-year nicotine dependence compared to those without AUDs 40 perhaps due to those with remitted AUDs being more likely to quit smoking (see Table 4). In that study, there were no significant gender differences in the relationships between AUDs/SUDs and past-year nicotine dependence 40 .…”

“…While this was generally consistent across studies, a study using data from adults who reported lifetime smoking and completed Wave 2 of the NESARC found that respondents with a past-year AUD were more likely to report past-year nicotine dependence while adults with lifetime AUD were less likely to report past-year nicotine dependence compared to those without AUDs 40 perhaps due to those with remitted AUDs being more likely to quit smoking (see Table 4). In that study, there were no significant gender differences in the relationships between AUDs/SUDs and past-year nicotine dependence 40 . Average level of nicotine dependence, as measured by the Fagerström Test for Nicotine Dependence 42 , was higher for German adults with current or remitted alcohol dependence compared to adults without alcohol use problems.…”

“…Three of the studies reported data from U.S. adults 38–40 and one study reported data from German adults 41 . Similar to smoking, current and lifetime nicotine dependence prevalences were higher among adults with past-year AUDs/ SUDs and lifetime AUDs than those without (Table 3).…”

“…Two studies found mixed results regarding gender differences in the link between AUDs/SUDs and nicotine dependence 38,40 . One study 38 found AUDs/SUDs were associated with nicotine dependence for both men and women (e.g., AUD: men OR=3.9, 95% CI=3.4, 4.5, women OR=5.1, 95% CI=4.3, 6.1; SUD: men OR=7.1, 95% CI=5.7, 8.8, women OR=9.5, 95% CI=6.7, 13.7).…”

Probability and predictors of treatment-seeking for substance use disorders in the U.S

“…Despite their high prevalence and numerous associated adverse health consequences (Aharonovich et al, 2002; Blanco et al, 2014b; Degenhardt and Hall, 2012; García-Rodrígueza et al, 2014), many individuals with SUD do not receive treatment (Blanco et al, 2013a; Compton et al, 2007; Edlund et al, 2012; Hasin et al, 2007; Kessler et al, 1999; Olfson et al, 1998; Regier et al, 1993). The great extent of unmet need for substance abuse treatment underscores the critical public health importance of understanding factors that promote the flow of individuals with SUDs into treatment.…”