Christine Schaffran

Racial/Ethnic Differences in Cigarette Smoking Initiation and Progression to Daily Smoking: A Multilevel Analysis

OBJECTIVES We sought to identify individual and contextual predictors of adolescent smoking initiation and progression to daily smoking by race/ethnicity. METHODS We used data from the National Longitudinal Study of Adolescent Health to estimate the effects of individual (adolescent, family, peer) and contextual (school and state) factors on smoking onset among nonsmokers (n = 5374) and progression to daily smoking among smokers (n = 4474) with multilevel regression models. RESULTS Individual factors were more important predictors of smoking behaviors than were contextual factors. Predictors of smoking behaviors were mostly common across racial/ethnic groups. CONCLUSIONS The few identified racial/ethnic differences in predictors of smoking behavior suggest that universal prevention and intervention efforts could reach most adolescents regardless of race/ethnicity. With 2 exceptions, important contextual factors remain to be identified.

Molecular Mechanism for a Gateway Drug: Epigenetic Changes Initiated by Nicotine Prime Gene Expression by Cocaine

The finding that nicotine enhances the brain’s response to cocaine may explain how smoking acts as a gateway drug for this addictive stimulant. Another Reason to Shun Cigarettes Illicit drugs sap the strength of the human population. Yet, our efforts to control their use, through law enforcement or medicine, are weak and largely ineffectual. Most drugs of abuse act on the reward centers of the brain, setting up positive incentive cycles that lead to addiction. These mechanistic insights have not yet yielded treatments that curtail drug use, but new research has delivered some potentially practical knowledge. Levine et al. now show that nicotine alters the brain to make it more susceptible to cocaine’s addicting effects, and suggest that interfering with this reprogramming may rein in cocaine abuse. The authors pretreated mice with nicotine to mimic the effects of smoking and detected an increase in the behavioral and neuronal activity responses that mice typically exhibit when given cocaine, relative to animals that had not been pretreated. In contrast, cocaine did not have the reciprocal effect on nicotine responses. So, how does nicotine engineer this cocaine supersensitivity? By taking a close look at histone proteins—which package DNA as chromatin—in the reward centers of the brain (the striatum), the authors found that certain histones were hyperacetylated, a state that results in augmented gene expression, consistent with the exaggerated response to cocaine. Encouraging, but preliminary at this point, is the idea that activators of histone deacetylases, which decrease histone acetylation, might counteract the effect of nicotine and perhaps other stimuli that prime the response to cocaine. Confining the action of these putative drugs to the striatum would enhance their chances of achieving selective efficacy and low toxicity, although the tools for targeting these agents are not yet available. An epidemiological analysis described in the paper by Levine et al. reinforces the urgency of translating these results: Most cocaine addicts began using the drug after they started smoking cigarettes, as would be expected if the mechanism operative in mice is mimicked in humans. Cocaine abusers are often administered nicotine replacement therapy to help curb their smoking habits; if the authors’ findings hold up in humans, nicotine replacement therapy might actually exacerbate the patient’s cocaine addiction, a highly undesirable side effect. Finally, using cocaine while smoking increases the risk of becoming dependent on the drug: another healthy reason not to smoke. In human populations, cigarettes and alcohol generally serve as gateway drugs, which people use first before progressing to marijuana, cocaine, or other illicit substances. To understand the biological basis of the gateway sequence of drug use, we developed an animal model in mice and used it to study the effects of nicotine on subsequent responses to cocaine. We found that pretreatment of mice with nicotine increased the response to cocaine, as assessed by addiction-related behaviors and synaptic plasticity in the striatum, a brain region critical for addiction-related reward. Locomotor sensitization was increased by 98%, conditioned place preference was increased by 78%, and cocaine-induced reduction in long-term potentiation (LTP) was enhanced by 24%. The responses to cocaine were altered only when nicotine was administered first, and nicotine and cocaine were then administered concurrently. Reversing the order of drug administration was ineffective; cocaine had no effect on nicotine-induced behaviors and synaptic plasticity. Nicotine primed the response to cocaine by enhancing its ability to induce transcriptional activation of the FosB gene through inhibition of histone deacetylase, which caused global histone acetylation in the striatum. We tested this conclusion further and found that a histone deacetylase inhibitor simulated the actions of nicotine by priming the response to cocaine and enhancing FosB gene expression and LTP depression in the nucleus accumbens. Conversely, in a genetic mouse model characterized by reduced histone acetylation, the effects of cocaine on LTP were diminished. We achieved a similar effect by infusing a low dose of theophylline, an activator of histone deacetylase, into the nucleus accumbens. These results from mice prompted an analysis of epidemiological data, which indicated that most cocaine users initiate cocaine use after the onset of smoking and while actively still smoking, and that initiating cocaine use after smoking increases the risk of becoming dependent on cocaine, consistent with our data from mice. If our findings in mice apply to humans, a decrease in smoking rates in young people would be expected to lead to a decrease in cocaine addiction.

Educational Attainment and Smoking Among Women: Risk Factors and Consequences for Offspring

We examine the association between education and smoking by women in the population, including smoking during pregnancy, and identify risk factors for smoking and the consequences of smoking in pregnancy for childrens smoking and behavioral problems. Secondary analyses of four national data sets were implemented: The National Survey of Drug Use and Health (2006), the National Longitudinal Survey of Youth (1979-2004); the National Longitudinal Survey of Adolescent Health (Wave III); National Health and Nutrition Examination Survey (2005-2006). The lower the level of education, the greater the risk of being a current smoker, smoking daily, smoking heavily, being nicotine dependent, starting to smoke at an early age, having higher levels of circulating cotinine per cigarettes smoked, and continuing to smoke in pregnancy. The educational gradient is especially strong in pregnancy. Educational level and smoking in pregnancy independently increase the risk of offspring smoking and antisocial and anxious/depressed behavior problems. These effects persist with control for other covariates, except maternal age at childs birth, which accounts for the impact of education on offspring smoking and anxious/depressed behavior problems. Women with low education should be the target of public health efforts toward reducing tobacco use. These efforts need to focus as much on social conditions that affect womens lives as on individual level interventions. These interventions would have beneficial effects not only for the women themselves but also for their offspring.

Salivary cotinine concentration versus self-reported cigarette smoking: Three patterns of inconsistency in adolescence.

The present study examined the extent and sources of discrepancies between self-reported cigarette smoking and salivary cotinine concentration among adolescents. The data are from household interviews with a cohort of 1,024 adolescents from an urban school system. Histories of tobacco use in the last 7 days and saliva samples were obtained. Logistic regressions identified correlates of three inconsistent patterns: (a) Pattern 1-self-reported nonsmoking among adolescents with cotinine concentration above the 11.4 ng/mg cutpoint (n = 176), (b) Pattern 2-low cotinine concentration (below cutpoint) among adolescents reporting having smoked within the last 3 days (n = 155), and (c) Pattern 3-high cotinine concentration (above cutpoint) among adolescents reporting not having smoked within the last 3 days (n = 869). Rates of inconsistency were high among smokers defined by cotinine levels or self-reports (Pattern 1 = 49.1%; Pattern 2 = 42.0%). Controlling for other covariates, we found that reports of nonsmoking among those with high cotinine (Pattern 1) were associated with younger age, having few friends smoking, little recent exposure to smokers, and being interviewed by the same interviewer as the parent and on the same day. Low cotinine concentration among self-reported smokers (Pattern 2) was negatively associated with older age, being African American, number of cigarettes smoked, depth of inhalation, and exposure to passive smoke but positively associated with less recent smoking and depressive symptoms. High cotinine concentrations among self-reported nonsmokers was positively associated with exposure to passive smoke (Pattern 3). The data are consonant with laboratory findings regarding ethnic differences in nicotine metabolism rate. The inverse relationship of cotinine concentration with depressive symptoms has not previously been reported. Depressed adolescent smokers may take in smaller doses of nicotine than nondepressed smokers; alternatively, depressed adolescents may metabolize nicotine more rapidly.

Developmental trajectories of criteria of nicotine dependence in adolescence

We describe the nature and predictors of developmental trajectories of symptoms of DSM-IV nicotine dependence in adolescence following smoking initiation. Data are from a longitudinal cohort of 324 new smokers from grades 6-10 in the Chicago Public Schools, interviewed 5 times at 6-month intervals. Monthly data on DSM-IV symptoms of nicotine dependence were available for 36 months. Growth mixture modeling was applied to the monthly histories to identify trajectories of DSM-IV criteria of nicotine dependence. A four-class solution best fitted the data: no DSM criterion (47.7%); early onset/chronic course (19.8%); early onset/remission (17.3%); late onset (15.2%). Blunt use prior to cigarette use was associated with the three symptomatic trajectories. Conduct disorder and prior heavy smoking were associated with Class 2 (chronic). Conduct disorder differentiated Class 2 from Class 4 (late onset), while pleasant initial sensitivity to the first tobacco experience was associated with Classes 2 and 3 (remit) and differentiated Class 2 from Class 4. Novelty seeking characterized Class 3. Parental dependence differentiated chronicity (Class 2) from remission (Class 3) among those who developed symptoms early. Being Hispanic reduced membership in Classes 3 and 4, and being male for Class 3. The data highlight the importance of parental nicotine dependence as a risk factor for early and sustained nicotine dependence by the offspring, pleasant initial sensitivity and conduct disorder for early onset of dependence, and blunt use prior to smoking for all trajectories. The factors important for onset of dependence are not necessarily the same as those for sustained course.

Age-related differences in cigarette smoking among whites and African-Americans: evidence for the crossover hypothesis.

BACKGROUND Age crossover describes the age-related reversal in prevalence of current cigarette smoking among non-Hispanic whites and African-Americans, with prevalence higher among whites than African-Americans in adolescence but lower in adulthood. Prior studies have examined smoking patterns in separate adolescent and adult samples and have not sought to identify factors that could account for crossover. We conducted analyses using national samples to identify factors that account for crossover and estimate their impact on crossover age. METHODS Analyses are based on national samples of lifetime smokers 12-49 years old in the 2006-2008 aggregated National Surveys on Drug Use and Health (N=61, 757) (SAMHSA, 2007-2009) and on multiple birth cohorts followed over 21 cross-sectional surveys. RESULTS We identified crossover for cigarette smoking in the US population at about age 29. Crossover is partially explained by differences between whites and African-Americans in education and marital status, and more weakly by the opposite impact of age of smoking onset on persistence of smoking in the two groups. Controlling for smoking history, education and social role participation would raise crossover in current smoking by more than 14 years. Rates of current smoking among lifetime smokers at four different age categories in multiple birth cohorts followed from ages 12-17 to 35 and over in 21 surveys spanning 24 years confirm the age-related patterns observed cross-sectionally. CONCLUSION Age crossover for current smoking appears among whites and African-Americans. Efforts targeted toward improving educational levels of young people would have the strongest impact in decreasing persistent smoking, especially among African-Americans.

Comorbid psychiatric disorders and nicotine dependence in adolescence

AIMS To examine bidirectional influences of onset of psychiatric disorders and nicotine dependence among adolescent smokers. DESIGN A prospective longitudinal cohort of adolescents and mothers drawn from a large city school system. Adolescents were interviewed five times and mothers three times over 2 years. SETTING Chicago, Illinois. PARTICIPANTS Subsample of adolescent smokers (n = 814). MEASUREMENTS Selected DSM-IV psychiatric disorders, nicotine dependence and selected risk factors were ascertained. FINDINGS Among lifetime smokers, 53.7% experienced at least one nicotine dependence criterion; 26.1% full dependence; 14.1% experienced an anxiety disorder, 18.8% a mood disorder and 29.5% a disruptive disorder. Nicotine dependence and psychiatric disorders were comorbid: nicotine-dependent youths had higher rates of individual and multiple disorders than those not dependent. Controlling for other covariates, mood disorder and nicotine dependence did not predict each other; anxiety disorder predicted nicotine dependence. Bidirectional influences were observed for disruptive disorder and nicotine dependence. Predictors of onset of full nicotine dependence included earlier onset age of tobacco use, high initial pleasant sensitivity to tobacco, alcohol and illicit drug use, abuse and dependence and parental nicotine dependence. Predictors of psychiatric disorder onset included gender, race/ethnicity, other psychiatric disorders, illicit drug abuse or dependence and parental depression and delinquency. CONCLUSIONS Initial pleasant experiences of smoking are predictive of later development of nicotine dependence. There may be reciprocal influences between disruptive disorder and development of nicotine dependence in adolescence, and intergenerational transmission of parental nicotine dependence and psychopathology.

Trajectories of criteria of nicotine dependence from adolescence to early adulthood

BACKGROUND To identify patterns and correlates of developmental trajectories of DSM-IV nicotine dependence criteria from adolescence to early adulthood. METHODS The analytical sample of lifetime smokers (N=877) is from a longitudinal cohort of 6th-10th graders drawn from an urban school system. Subjects were interviewed 5 times at 6-month intervals and once 4.5 years later. Growth mixture models were estimated to identify trajectories of DSM-IV nicotine dependence criteria over ages 12-23. RESULTS A four-class solution fitted the data best: No dependence criteria (class 1, 32.0%); early onset/chronic course (class 2, 26.1%); early onset/remission (class 3, 15.4%); late onset (class 4, 26.5%). There appeared to be three critical periods. At ages 12-15, symptoms increased rapidly. As of age 16, the early onset/chronic class stabilized at high levels of symptoms, the early onset/remission class started its symptomatic decline, and the late onset class experienced a sharp increase in symptoms. At age 20, there was a convergence in the prevalence of symptoms experienced at high (classes 2 and 4) and low levels (classes 1 and 3). Extensiveness of smoking and marijuana use were associated with higher baseline levels of nicotine dependence criteria. Anxiety disorders were associated with all three symptomatic trajectories. Parental smoking and nicotine dependence were associated specifically with the early/chronic class, while pleasant initial sensitivity and earlier onset ages of cigarette and marijuana use characterized the two early onset classes (2 and 3). CONCLUSIONS Trajectories of dependence criteria constitute an advantageous phenotype for research and intervention over static summaries of smoking behaviors.

Risk and Protective Factors for Nicotine Dependence in Adolescence.

BACKGROUND We investigated the role of psychosocial and proximal contextual factors on nicotine dependence in adolescence. METHODS Data on a multiethnic cohort of 6th to 10th graders from the Chicago public schools were obtained from four household interviews conducted with adolescents over two years and one interview with mothers. Structural equation models were estimated on 660 youths who had smoked cigarettes by the first interview. RESULTS Pleasant initial sensitivity to tobacco use, parental nicotine dependence (ND), adolescent ND and extensiveness of smoking at the initial interview had the strongest total effects on adolescent ND two years later. Perceived peer smoking and adolescent conduct problems were of lesser importance. Parental ND directly impacted adolescent ND two years later and had indirect effects through pleasant initial sensitivity and initial extensiveness of smoking. Parental depression affected initial adolescent dependence and depression but adolescent depression had no effect on ND. The model had greater explanatory power for males than females due partly to the stronger effect of conduct problems on dependence for males than females. CONCLUSIONS The findings underscore the importance of the initial drug experience and familial factors on adolescent nicotine dependence and highlight the factors to be the focus of efforts targeted toward preventing ND among adolescents.

Linking measures of adult nicotine dependence to a common latent continuum and a comparison with adolescent patterns.

BACKGROUND An ongoing debate regarding the nature of nicotine dependence (ND) is whether the same instrument can be applied to measure ND among adults and adolescents. Using a hierarchical item response model (IRM), we examined evidence for a common continuum underlying ND symptoms among adults and adolescents. METHOD The analyses are based on two waves of interviews with subsamples of parents and adolescents from a multi-ethnic longitudinal cohort of one thousand and thirty-nine 6-10th graders from the Chicago Public Schools (CPS). Adults and adolescents who reported smoking cigarettes the last 30 days prior to waves 3 and 5 completed three common instruments measuring ND symptoms and one item measuring loss of autonomy. RESULTS A stable continuum of ND, first identified among adolescents, was replicated among adults. However, some symptoms, such as tolerance and withdrawal, differed markedly across adults and adolescents. The majority of mFTQ items were observed within the highest levels of ND, the NDSS items within the lowest levels, and the DSM-IV items were arrayed in the middle and upper third of the continuum of dependence severity. Loss of autonomy was positioned at the lower end of the continuum. We propose a ten-symptom measure of ND for adolescents and adults. CONCLUSIONS Despite marked differences in the relative severity of specific ND symptoms in each group, common instrumentation of ND can apply to adults and adolescents. The results increase confidence in the ability to describe phenotypic heterogeneity in ND across important developmental periods.