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Cognitive mediators and disparities in the relation between teen depressiveness and smoking
Drug and Alcohol Dependence 140 (2014) 56–62
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Drug and Alcohol Dependence journal homepage: www.elsevier.com/locate/drugalcdep
Cognitive mediators and disparities in the relation between teen depressiveness and smoking Ritesh Mistry a,b,∗ , Giridhara R. Babu c,d , Tanmay Mahapatra c , William J. McCarthy a a
Center for Cancer Prevention and Control Research, University of California, Los Angeles, United States Department of Health Behavior and Health Education, University of Michigan, United States Department of Epidemiology, University of California, Los Angeles, United States d Indian Institute of Public Health-Hyderabad (Bangalore Wing), Public Health Foundation of India, India b c
a r t i c l e
i n f o
Article history: Received 13 September 2013 Received in revised form 4 February 2014 Accepted 18 March 2014 Available online 30 March 2014 Keywords: Adolescent Smoking Mediation Depression Gender Race/ethnicity
a b s t r a c t Background: Depressiveness and tobacco use in adolescents are linked, however, there is limited evidence about the cognitive mediators involved and how the role of mediators may differ by gender and racial/ethnic subgroups. Methods: We used a racially/ethnically diverse population-based cross-sectional sample of middle and high school students (n = 24,350). Logistic regression models measured the associations of depressiveness with tobacco smoking status, and whether smoking-related knowledge and attitudes (KA) and smoking refusal self-efficacy (SE) attenuated the associations indicating preliminary evidence of mediation. Results: Depressiveness was associated with intention to smoke (OR = 2.41; 95% CI = 2.22, 2.61), experimental smoking (OR = 1.93; 95% CI = 1.72, 2.17) and established smoking (OR = 1.85; 95% CI = 1.57, 2.18). The percent attenuation of these associations due to the inclusion of smoking-related KA and smoking refusal SE was 58% for intention to smoke (p < 0.001), 68% for experimental smoking (p < 0.001) and 86% for established smoking (p < 0.001). The association of depressiveness with established smoking did not remain statistically significant (OR = 1.16; CI = 0.97, 1.40) after including smoking-related KA and smoking refusal SE. Attenuation was more pronounced in males and white students. Conclusions: The results suggest that smoking-related KA and smoking refusal SE attenuated the relation between depressiveness and smoking, indicating that they may serve as mediators of the link between depressiveness and smoking. Tobacco use prevention programs targeting teens with the aim of increasing anti-smoking KA and smoking refusal SE may benefit from addressing depressiveness, particularly by using gender and racially/ethnically tailored strategies. The cross-sectional nature of the data precludes causal inferences. © 2014 Elsevier Ireland Ltd. All rights reserved.
1. Introduction The rates of adolescent tobacco use in the United States remain unacceptably high. It is estimated that about 20% of adolescents are current tobacco smokers (i.e., those who smoked on at least 1 day in the past month) and about 7% are frequent smokers (i.e., those who smoked on 20 or more days in the past month; Centers for Disease Control and Prevention, 2010). Depression and depressive symptoms have been identified as both antecedents (Fergusson et al., 2003) and consequences (Boden et al., 2010; Goodman and
∗ Corresponding author at: Department of Health Behavior and Health Education, University of Michigan School of Public Health, 1415 Washington Heights, SPH I, Room 3806, Ann Arbor, MI 48109-2029, United States. Tel.: +1 734 936 1318. E-mail address: [email protected] (R. Mistry). http://dx.doi.org/10.1016/j.drugalcdep.2014.03.022 0376-8716/© 2014 Elsevier Ireland Ltd. All rights reserved.
Capitman, 2000) of adolescents smoking (Chaiton et al., 2009; Steuber and Danner, 2006), and contribute to the initiation of and transition into regular smoking (Audrain-McGovern et al., 2004; Fergusson et al., 2003). Prolonged feelings of sadness or hopelessness, common depression symptoms, are linked with adolescent smoking (Mistry et al., 2009). With the prevalence of current or recent depression among adolescents in the United States at 6% (Costello et al., 2006) and the prevalence of prolonged recent sadness and hopelessness at 29% (Eaton et al., 2012), it is important to understand potential pathways by which depressiveness impacts smoking, especially because smoking is an important risk factor for major chronic diseases (US Department of Health and Human Services, 2010). A number of theories posit that health risk behaviors such as tobacco use are partially determined by cognitive factors such as perceived risks and benefits of a health risk behavior as well
R. Mistry et al. / Drug and Alcohol Dependence 140 (2014) 56–62
Smoking knowledge & atudes
Peer smoking, Ease of access to tobacco
Smoking refusal self-efficacy
DEPRESSIVENESS
SMOKING
Age, Gender, Race/Ethnicity, Academic Performance Fig. 1. Conceptual framework of factors involved in the link between depressiveness and smoking.
as self-efficacy (Health Belief Model, Social Cognitive Theory) to not engage in unhealthful behaviors despite other influences. Social Cognitive Theory additionally posits that there is interplay between cognition (e.g., beliefs, knowledge, attitudes, perceived self-efficacy) and affect (e.g. depressive symptoms) that influences behavior. The cognitive processes involved during adolescence in the link between depressive symptoms and smoking have been studied empirically to a limited extent, while further research is required particularly using diverse population-based samples. Studies in adults suggest that expectations held about whether smoking reduces negative emotions (McChargue et al., 2004; Schleicher et al., 2009) and self-efficacy to refuse tobacco when offered by others (Kear, 2002) mediate the relation. In addition, the research in adolescent samples suggests that mediators of the link between depressive symptoms and smoking include social influences such as peer approval of tobacco use (Ritt-Olson et al., 2005), smoking refusal self-efficacy (Minnix et al., 2011), perceived smoking reward (Audrain-McGovern et al., 2012) and risk (Rodriguez et al., 2007) as well as outcome expectancies (Spruijt-Metz et al., 2005). These studies have helped elucidate the potential pathways, however, data are needed about the underlying heterogeneity in the role of potential mediators across important socio-demographic factors such as gender and race/ethnic identification. Research that helps to illuminate the cognitive pathways involved in the link between depressive symptoms and smoking in adolescents could be useful for designing prevention programs. The literature suggests uneven efficacy of affect based adolescent tobacco use prevention programs (Flay, 2009) and that the efficacy of prevention programs may be moderated by depressive symptoms (Johnson et al., 2007; Sun et al., 2007). Knowledge of the cognitive pathways involved may help identify which factors to focus upon and how to design programs to better tailor intervention strategies for gender and race/ethnic subgroups of adolescents based on whether they are experiencing depressive symptoms. In this study, we used data from a large racially/ethnically diverse population-based sample to examine the association between feelings of depressiveness and smoking in adolescents, and tested two cognitive factors (Fig. 1) for cross-sectional evidence of mediation. Though cross-sectional data are not ideal for making causal inferences and testing mediation, the results can provide hypothesis-generating evidence that could inform further research using longitudinal and experimental designs. We chose to examine smoking-related knowledge and attitudes (KA) and smoking refusal self-efficacy (SE) as potential mediators because these constructs are key factors that many tobacco use prevention
57
education programs, particularly school-based program, aim to modify in order to reduce youth tobacco use risk. In addition, depression and depressive symptoms have been shown to affect information processing (Schwarz et al., 1991; Trope et al., 2001) and decision-making (Bechara et al., 2000), which may impact skills and knowledge gained from tobacco use prevention education programs. We anticipated that prolonged sadness or hopelessness, commonly reported symptoms of depression and depressive symptoms, would impair the ability of adolescents to process tobacco use prevention information and acquire tobacco refusal skills. As a result, adolescents who reported depressiveness may have also reported less anti-tobacco knowledge and attitudes as well as lower tobacco refusal self-efficacy. Hence, we hypothesized that there would be positive associations between depressiveness and adolescent smoking status (intention to smoke, experimental smoking and established smoking) in the sample, and that these associations would be attenuated by smoking-related KA and smoking refusal SE indicating evidence of potential mediation. We also hypothesized that the attenuation in the relation between depressiveness and smoking due to smoking-related KA and smoking refusal SE would differ by gender and race/ethnicity, because there is substantial differential risk of depressive symptoms and tobacco use between adolescent males and females (Fryar et al., 2009), and categories of race/ethnicity (Centers for Disease Control and Prevention, 2010; Kafilat Tolani, 2012). 2. Methods 2.1. Sample We used population-based cross-sectional survey data from the 2003–2004 California Student Tobacco Survey (CSTS), a stratified two-stage cluster sampling inschool survey of 25,868 middle and high schools students in 226 California schools (McCarthy et al., 2008). The CSTS participants were sampled from 12 regions (strata), which were formed on the basis of county demographic and socioeconomic characteristics. First, schools in each stratum were randomly selected with probabilities proportional to size of enrollment. Intact classes of required courses were randomly sampled from selected schools. Active parental consent to participate was obtained, which resulted in a student participation rate of 69.6%, for a total of 24,350 students in our study. 2.2. Measures Intention to smoke was measured using the question “Do you think you will smoke tobacco at any time during the next year?” Having an intention to use tobacco was defined as responses of “Definitely yes” or “Probably yes” and not having an intention to use was defined as “Definitely no” or “Probably no.” Experimental smoking and established smoking were assessed using two items: “About how many cigarettes have you smoked in your entire life,” and “During the past 30 days, on how many days did you smoke cigarettes.” Experimental smoking was defined as having smoked less than 100 cigarettes in one’s lifetime and having smoked during the last 30 days. Established smoking was defined as having smoked 100 or more cigarettes in one’s lifetime and having smoked in the last 30 days. Depressiveness was assessed using the commonly used United States Youth Behavioral Risk Survey question: “During the last 12 months, did you feel sad or hopeless almost every day for 2 or more weeks?” This is a widely used surveillance measure of depressive symptoms (Eaton et al., 2012) and has been associated with measures of negative affect such as unrealistic fatalism (Jamieson and Romer, 2008) and suicidal ideation (Jamieson and Romer, 2008). Smoking-related KA was assessed through standardized scores on an ad-hoc 12-item scale (Cronbach’s alpha = 0.71). The items included in the scale asked about whether smoking: reduces weight gain; is a way to lose friends; results in shorter lives; makes one appear more grown up; makes one more relaxed; makes one look cool; cigars are as bad as cigarettes; if those who smoke have more friends, look more cool or fit in; risk harming themselves if they smoke 1–5 cigarettes a day; and whether it is safe to smoke for a year or two as long as one quits. There were four Likert-type response categories from “Definitely yes” to “Definitely not,” which were coded as 0, 33, 66 or 100 with higher scores reflecting more accurate knowledge about and more negative attitudes toward tobacco use. An average score across all items was created and then standardized. Smoking refusal SE was defined as low if the response to the question “How hard would it be to refuse or to say “no” to a friend who offered you a cigarette?” was “Very hard” or “Hard” and high if the response was “Easy” or “Very easy”.
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Study covariates included age (categorized as 12 yrs or less, 13–14 yrs, 15–16 yrs and 17 yrs or more), gender, race/ethnicity (categorized as white, Hispanic, Asian/Pacific Islanders, African American and American Indian/Alaskan Natives), academic performance (categorized as Superior = Mostly A’s; Good = A’s and B’s; Fair = Mostly B’s, and B’s and C’s; Poor = Mostly C’s or worse), perceived peer smoking (defined as “Low” if respondents reported that <20% of peers smoke, “Moderate” if 21–60% and “High” if >61%) and perceived ease of obtaining tobacco (categorized as “Easy” and “Hard”). Fig. 1 shows that age, gender, race/ethnicity and educational performance were expected to be potential confounders of the relation between depressiveness and smoking (Brunswick and Messeri, 1984; Klungsoyr et al., 2006; Young and Rogers, 1986). Because perceived peer smoking and ease of access to tobacco are not likely to be associated with depressiveness (Hover and Gaffney, 1988), they were not hypothesized to cofound the relation between depressiveness and smoking, but were hypothesized to confound the association of smoking-related KA and smoking refusal SE (i.e., the hypothesized mediators) with smoking outcomes. 2.3. Analysis First, we conducted descriptive analyses of the study variables. Second, we used the causal steps approach to measure evidence of mediation (MacKinnon and Fairchild, 2009). The percent attenuation in the association between depressiveness and smoking after inclusion of the cognitive cofactors (anti-smoking KA and smoking refusal SE) was used to measure preliminary mediation. We used logistic regression to estimate the association of depressiveness with each smoking measure controlling for age, educational performance, gender and race/ethnicity (Model Set 1). Because we hypothesized that peer smoking and perceived ease of access to tobacco would confound the association of smoking status with smoking-related KA and smoking refusal SE, but not likely to be associated with depressiveness, we did not include them as covariates in Model Set 1. In Model Set 2, we added smokingrelated KA, perceived peer smoking and perceived ease of access to tobacco to the variables included in Model Set 1. In Model Set 3, the fully controlled models, we added smoking refusal SE to the variables included in Model Set 2. Attenuation after inclusion of smoking-related KA was measured as percent reductions of the Model Set 1 coefficients for the association between depressiveness and each smoking measure when compared to the corresponding coefficients in Model Set 2. Similarly, attenuation after inclusion of both smoking-related KA and smoking refusal SE was obtained as percent reductions in the Model Set 1 coefficients for the association between depressiveness and each smoking measure, when compared to the corresponding coefficients in Model Set 3. Finally, we analyzed whether the fully controlled association between depressiveness and smoking status (Model Set 3) and percent attenuation due to inclusion of smoking-related KA and smoking refusal SE differed based on gender and race/ethnicity by stratifying the regression analysis by these two demographic variables. Statistical analysis was conducted using SAS 9.1. Results were adjusted for the survey sampling design, and weighted to represent California middle and high school students.
3. Results Table 1 shows the distribution of study variables and crosstabulations of depressiveness and smoking status with the covariates. Nearly 50% of participants were 15 or more years of age, and there were more females (53%) than males (47%); the gender distribution was similar across race/ethnicity, i.e. 52–55% female and 45–48% male. The participants were mostly white (42%) or Hispanic (34%), but Asian/Pacific Islanders (16%), African Americans (7%) and American Indians/Alaskan natives (2%) were also included in the sample. Depressiveness was reported by about 28% of the participants, and was most frequently reported by Hispanics (30%) and African Americans (30%). Intention to smoke, experimental smoking and established smoking were reported by 15%, 6% and 3% of the participants, respectively, with Hispanics most frequently reporting intention to smoke (17%) and experimental smoking (8%) while whites most frequently reporting established smoking (5%). Table 2 shows results from the logistic regression analysis using Model Sets 1–3 as described above and the estimated attenuation in the association between depressiveness and smoking status due to the inclusion of smoking-related KA and smoking refusal SE. Results from Model Set 1 show that students who reported depressiveness were at 2.41 times higher odds of reporting intention to smoke (95% CI: 2.22, 2.61), 1.93 times higher odds of reporting experimental smoking (95% CI: 1.72, 2.17) and 1.85 times higher odds of reporting established smoking (95% CI: 1.57, 2.18). When the measure for smoking-related KA was added to Model Set 1 the odds ratios for
each outcome were attenuated (Model Set 2) by 54% for intention to smoke (p < 0.001), 68% for experimental smoking (p < 0.001) and 75% for established smoking (p < 0.001). When the measures of both smoking-related KA and smoking refusal SE (Model Set 3) were added to Model Set 1, the odd ratios were attenuated even further as compared to Model Set 1 for intention to smoke (58%, p < 0.001) and established smoking (86%, p < 0.001), but not for experimental smoking (68%, p < 0.001). The odds ratio for the relation between depressiveness and established smoking became non-significant in Model Set 3. Table 3 shows the regression results stratified by gender and race/ethnicity in order to assess whether the fully controlled associations between depressiveness and smoking outcomes (Model Set 3) and percent attenuation due to smoking-related KA and smoking refusal SE were modified by these demographic variables. The results show that fully controlled associations of depressiveness with intention to smoke and established smoking was significantly greater for female versus male students, and Hispanic students versus white students. This is evident from the odds ratio point estimates of Model Set 3 for intention to smoke and established smoking for one gender or race/ethnicity being outside of the corresponding 95% confidence intervals for the other gender or race/ethnicity. The results also show that percent attenuation due to smokingrelated KA and smoking refusal SE for intention to smoke and established smoking was, respectively, 53% and 73% for female students compared to 67% and 100% for males students, and 51% and 54% for Hispanic students versus 65% and 100% for white students.
4. Discussion This study analyzed a large racially/ethnically diverse population-based sample of middle and high school students to preliminarily assess mediation by two cognitive factors in the link between depressiveness and tobacco smoking. We examined smoking-related KA and smoking refusal SE as potential mediators because they may be negatively influence by depressive symptoms (Schwarz et al., 1991; Trope et al., 2001) and because they are important modifiable factors that many tobacco use prevention education programs aim to improve (Lantz et al., 2000). The results add to the current literature by finding preliminary evidence of the mediational roles of smoking-related KA and smoking refusal SE as shown by the attenuation of the associations of depressive symptoms with smoking status. Prior research suggests that smoking-related KA and smoking refusal SE may act as mediators (Finney Rutten et al., 2008; Minnix et al., 2011; Rodriguez et al., 2007), however how the mediating roles of these factors vary across gender and racial/ethnic subgroups has not been examined to our knowledge. This study shows that attenuation due to smoking-related KA and smoking refusal SE differed based on gender and racial/ethnic identification indicating the these demographic factors may serve as important moderators. The findings indicate that smoking-related KA and smoking refusal SE may completely explain away the association between depressiveness and established smoking, and substantially attenuated the association of depressiveness with intention to smoke and experimental smoking. This suggests good preliminary evidence of mediation. Consistent with other literature (Waller et al., 2006), the association of depressiveness with intention to smoke and established smoking was higher in female compared to male students. In Hispanic compared to non-Hispanic students, the association of depression on intention to smoke and established smoking was also higher, but this was not consistent research in Hispanic adults (Berg et al., 2012) despite evidence suggesting
Table 1 Descriptive analysis of study participants (n = 24,350). % (n)
Depressiveness, % (n)
Smoking outcomes, % (n)
Intention
Smoking refusal self-efficacy, % (n) Experimental
Smoking knowledge and attitude
Established
No
Yes
No
Yes
No
Yes
No
Low
High
Mean
SE
72.3 (15,750)
82.8 82.6 89.0 91.4
−0.01 p < 0.001 0.08 −0.04 −0.03 −0.01
0.00
99.8 98.7 95.5 92.9
13.8 (3256) p < 0.010 17.2 17.4 11.0 8.6
86.3 (20,429)
98.2 94.2 31.9 90.9
3.1 (733) p < 0.001 0.3 1.3 4.5 7.1
96.8 (22,712)
95.7 86.4 80.9 78.1
6.3 (1475) p < 0.001 1.8 5.8 8.1 9.1
93.7 (21,970)
79.8 72.3 69.4 70.6
14.9 (3603) p < 0.001 4.3 13.6 19.2 21.9
85.1 (20,569)
20.9 30.5 30.0 18.7
27.7 (6024) p < 0.001 20.2 27.7 30.6 29.4
0.01 0.01 0.01 0.01
Gender Female Male
53.0 47.0
p < 0.001 30.8 24.0
69.2 76.1
p < 0.001 14.1 15.7
85.9 84.3
p < 0.001 6.0 6.6
94.0 93.4
p < 0.001 2.4 4.0
97.6 96.0
p < 0.001 12.8 14.7
87.2 85.3
p < 0.001 0.05 −0.07
0.00 0.01
Race/ethnicity White Caucasian Hispanic Asian/Pacific Islander African American American Indian/AN
42.0 33.5 15.5 7.2 1.9
p < 0.001 25.2 30.1 28.8 30.0 26.2
74.8 70.0 71.3 70.0 73.8
p < 0.001 15.3 17.3 10.8 11.3 12.2
84.7 82.7 89.2 88.7 87.8
p < 0.001 6.0 7.8 4.3 5.1 7.4
94.0 92.2 95.7 94.9 92.6
p < 0.001 4.6 2.0 2.3 1.7 2.8
95.4 98.0 97.7 98.3 97.2
p < 0.001 11.5 16.5 13.8 12.0 18.9
88.5 83.5 86.2 88.0 81.1
p < 0.001 0.05 −0.07 0.01 −0.06 −0.05
0.01 0.01 0.02 0.01 0.03
Academic performance Superior Good Fair Poor
25.0 33.2 27.9 13.9
p < 0.001 22.8 25.4 29.5 37.6
77.2 74.6 70.6 62.4
p < 0.001 9.2 11.5 18.4 29.4
90.8 88.5 81.6 70.6
p < 0.001 3.2 4.7 7.9 14.0
96.8 95.3 92.1 86.0
p < 0.001 2.0 2.2 3.7 7.3
98.0 97.8 96.3 92.7
p < 0.05 12.0 12.0 13.5 20.1
88.0 88.0 86.5 79.9
p < 0.001 0.09 0.05 −0.04 −0.21
0.02 0.01 0.01 0.01
Peers smoking Low Moderate High
49.5 39.7 10.8
p < 0.001 22.3 31.4 37.7
77.7 68.6 62.4
p < 0.001 6.6 19.5 36.8
93.4 80.5 63.2
p < 0.001 2.7 8.4 15.9
97.3 91.6 84.2
p < 0.001 0.9 4.2 9.8
99.1 95.8 90.2
p < 0.001 13.7 12.2 19.6
86.3 87.8 80.4
p < 0.001 0.06 −0.03 −0.24
0.00 0.01 0.01
Tobacco ease of access Hard Easy
64.3 35.7
p < 0.001 24.2 33.7
75.9 66.3
p < 0.001 8.9 26.0
91.1 74.0
p < 0.001 4.0 10.4
96.0 89.6
p < 0.001 1.5 6.1
98.5 93.9
p < 0.001 13.1 14.7
86.9 85.3
p < 0.001 0.06 −0.13
0.00 0.01
100 (24,350)
R. Mistry et al. / Drug and Alcohol Dependence 140 (2014) 56–62
Yes Column sample size Age 12 yrs or less 13–14 yrs 15–16 yrs 17 yrs or more
59
60
R. Mistry et al. / Drug and Alcohol Dependence 140 (2014) 56–62
Table 2 Association between depressiveness and smoking measures, and mediation due to smoking-related knowledge and attitudes (KA) and smoking refusal self-efficacy (SE) (n = 24,350). Smoking outcomes
Intention to smoke Experimental smoking Established smoking a b c ** ***
Model Set 1a
Model Set 2b
Model Set 3c
Percent mediation in relation to model Set 1
OR
OR
OR
Smoking KA
95% CI ***
2.41 1.93*** 1.85***
2.22, 2.61 1.72, 2.17 1.57, 2.18
95% CI ***
1.84 1.47*** 1.34**
1.68, 2.01 1.30, 1.67 1.12, 1.60
95% CI ***
1.73 1.47*** 1.16
1.58, 1.90 1.30, 1.67 0.97, 1.40
Smoking KA and smoking refusal SE
***
57.80*** 68.03*** 86.21***
54.35 68.03*** 74.63***
Adjusted for age, gender, race/ethnicity and educational performance. Adjusted for smoking-related KA, peer smoking and perceived ease of access to tobacco, in addition to Model Set 1 covariates. Adjusted for smoking refusal SE, in addition to Model Set 2 covariates. p < 0.01. p < 0.001.
greater prevalence of depressiveness and smoking from studies in Hispanic populations (Lorenzo-Blanco et al., 2011) and national data comparing racial/ethnic subgroups (Johnston et al., 2014). Attenuation after the inclusion of smoking-related KA and smoking refusal SE was more pronounced in male and white students. The results point toward researching the integration of the management and reduction of negative affective symptoms such as depressiveness as part of adolescent tobacco use prevention programs, especially those that aim to increase anti-tobacco KA and smoking refusal SE. For example, identification of students with significant depressive symptoms and referral to mental health services may enhance tobacco use prevention or other health education efforts. The literature suggests that addressing depression as part of smoking cessation interventions in adults has positive impacts (Gierisch et al., 2012), however, research with respect to
tobacco use prevention and cessation in adolescent populations with depressive symptoms and depression is needed (DeHay et al., 2012). Moreover, the results suggest that designing tobacco use prevention strategies to improve anti-smoking KA and smoking refusal SE should be done in a manner that is salient to adolescents experiencing depressive symptoms and are at high risk for depression. Such adolescents may require different modes of delivery and content of tobacco use prevention education and skill building exercises, particularly for male and white adolescents. Finally, adolescent depression and depressiveness is in itself of public health importance. Effective programs and services for primary prevention and treatment of depression in adolescents are not readily available, especially for socio-economically disadvantaged youth. Preventing adolescent depressiveness may reduce the risk of tobacco use initiation (Dudas et al., 2005; Roberts et al., 2011)
Table 3 Moderating effect of gender and race/ethnicity on the association of depressiveness with smoking outcomes and mediation due to smoking-related knowledge and attitudes (KA) and smoking refusal self-efficacy (SE) (n = 24,350). Model Set 1a
Model Set 2b
Model Set 3c
Percent mediation
OR
95% CI
OR
95% CI
OR
95% CI
Smoking KA
Smoking KA and smoking refusal SE
Female Intention to smoke Experimental smoking Established smoking
2.56 1.98 1.98
2.28, 2.88 1.68, 2.33 1.53, 2.56
1.97 1.49 1.48
1.74, 2.24 1.25, 1.77 1.13, 1.94
1.88 1.47 1.38
1.66, 2.14 1.24, 1.75 1.04, 1.82
50.76 67.11 67.57
53.19 68.03 72.46
Male Intention to smoke Experimental smoking Established smoking
2.13 1.83 1.64
1.88, 2.42 1.53, 2.19 1.30, 2.06
1.61 1.45 1.18
1.40, 1.86 1.20, 1.75 0.92, 1.52
1.50 1.44 0.99
1.30, 1.73 1.20, 1.74 0.77, 1.29
62.11 68.97 84.75
66.67 69.44 100.00
White Intention to smoke Experimental smoking Established smoking
2.26 2.04 1.59
1.98, 2.57 1.69, 2.46 1.28, 1.99
1.63 1.56 1.13
1.41, 1.89 1.28, 1.89 0.89, 1.43
1.55 1.57 1.00
1.34, 1.80 1.29, 1.91 0.78, 1.28
61.35 64.10 88.50
64.52 63.69 100.00
Hispanic Intention to smoke Experimental smoking Established smoking
2.50 1.80 2.50
2.17, 2.87 1.48, 2.18 1.74, 3.58
2.07 1.45 2.02
1.78, 2.41 1.19, 1.77 1.38, 2.94
1.97 1.41 1.84
1.69, 2.30 1.15, 1.72 1.26, 2.71
48.31 68.97 49.50
50.76 70.92 54.35
Asian/Pacific Islander Intention to smoke Experimental smoking Established smoking
2.35 2.07 1.75
1.84, 2.99 1.45, 2.96 1.07, 2.86
1.79 1.50 1.23
1.37, 2.33 1.03, 2.18 0.72, 2.10
1.66 1.48 1.06
1.27, 2.18 1.02, 2.17 0.62, 1.84
55.87 66.67 81.30
60.24 67.57 94.34
African American Intention to smoke Experimental smoking Established smoking
2.41 2.31 1.44
1.68, 3.47 1.38, 3.84 0.58, 3.55
1.79 1.65 0.72
1.20, 2.67 0.95, 2.88 0.25, 2.04
1.67 1.58 0.64
1.11, 2.52 0.90, 2.76 0.22, 1.87
55.87 60.61 –
59.88 63.29 –
American Indian/AN Intention to smoke Experimental smoking Established smoking
2.20 0.92 1.88
1.05, 4.60 0.33, 2.59 0.40, 8.90
1.61 0.90 1.80
0.68, 3.77 0.30, 2.73 0.30, 10.68
1.31 0.86 1.32
0.52, 3.33 0.28, 2.67 0.18, 9.46
62.11 – 55.56
76.34 – 75.76
Smoking outcomes
a b c
Adjusted for age, gender, race/ethnicity and educational performance. Adjusted for smoking-related KA, peer smoking and perceived ease of access to tobacco, in addition to Model Set 1 covariates. Adjusted for smoking refusal SE, in addition to Model Set 2 covariates.
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and other behavioral risks (Mistry et al., 2009). More research is, therefore, required to better understand the determinants of adolescent depressiveness and to identify efficacious prevention and treatment strategies.
4.1. Strengths and limitations To our knowledge, there is little information in the scientific literature on the possible mediational roles of smoking-related KA and smoking refusal SE in the pathways linking depressiveness and smoking in adolescent and how they vary across racial/ethnic and gender strata. This study adds to the current literature by examining these potential mediators using a large racially/ethnically diverse population-based sample of adolescents. As with any crosssectional observational study, however, the results from this study preclude assessment of causal direction, and should be cautiously interpreted including with respect to the amount of mediation. Nonetheless the results are useful for generating hypotheses about mediation for further testing via prospective and experimental data, which we suggest as next steps. The study also aimed to take into account the most relevant risk factors of adolescent tobacco use in the analysis. Although we could not include all potential confounders, the inclusion of perceived peer smoking and perceived ease of access to tobacco may serve as proxies for many factors commonly associated with smoking-related KA, smoking refusal SE and smoking status, such as community norms about tobacco use, social acceptance/stigma around smoking, as well as actual availability, financial access and social access to tobacco products. By controlling for perceived peer smoking and perceived ease of access to tobacco and relevant demographic and other covariates, we aimed to minimize confounding. However, as always there remained the possibility of confounding due to unmeasured variables. We also were limited to using self-reported data on smoking status, which are not ideal, but the data were collected confidentially to limit biases. The procedures used to collect these data have been widely used and have shown good validity and reliability when self-administered anonymously within classroom settings (Stanton et al., 1996). Finally, we used single-item measures of depressiveness, intention to smoke and smoking refusal SE. These, however, are commonly used measures in national and state level surveillance of youth behavioral risk factors. In addition, the measure of depressiveness has been consistently associated with mental health outcomes such as suicidal ideation (Jamieson and Romer, 2008) and health risk behaviors (Mistry et al., 2009). In summary, due to the cross-sectional nature of the data and the limitations due to the measurement of key study constructs, our results were not conclusive, but hypothesis generating and require further validation through studies using more detailed measures and rigorous study designs.
4.2. Conclusions Depressiveness was reported by a significant proportion of the sample and was consistently associated with various measures of smoking status, particularly in female and Hispanic students. The associations between depressiveness and smoking outcomes were attenuated by smoking-related KA and smoking refusal SE, indicating preliminary evidence of mediation. Despite the limitations of using cross-sectional data to evaluate mediation, these results suggest that tobacco use prevention programs targeting middle and high school aged students may benefit from addressing depressiveness, particularly by using gender and racially/ethnically tailored strategies.
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Role of funding source This study was supported with funding from the California Tobacco Related Disease Research Program (17KT0030). Contributors RM originated the study concept and wrote the paper. GB assisted with writing the paper and provided critical reviews. TM conducted the data analysis and provided critical reviews. WM ensured the scientific integrity of the research and provided critical reviews. Conflict of interest The authors declare that there are no conflicts of interest in relation to the information presented in this manuscript. References Audrain-McGovern, J., Lerman, C., Wileyto, E.P., Rodriguez, D., Shields, P.G., 2004. Interacting effects of genetic predisposition and depression on adolescent smoking progression. Am. J. Psychiatry 164, 1224–1230. Audrain-McGovern, J., Rodriguez, D., Rodgers, K., Cuevas, J., Sass, J., Riley, T., 2012. Reward expectations lead to smoking uptake among depressed adolescents. Drug Alcohol Depend. 120, 181–189. Bechara, A., Damasio, H., Damasio, A.R., 2000. Emotion, decision making and the orbitofrontal cortex. Cereb. Cortex 10, 295–307. Berg, C.J., Kirch, M., Hooper, M.W., McAlpine, D., An, L.C., Boudreaux, M., Ahluwalia, J.S., 2012. Ethnic group differences in the relationship between depressive symptoms and smoking. Ethn. Health 17, 55–69. Boden, J.M., Fergusson, D.M., Horwood, L.J., 2010. Cigarette smoking and depression: tests of causal linkages using a longitudinal birth cohort. Br. J. Psychiatry 196, 440–446. Brunswick, A.F., Messeri, P.A., 1984. Origins of cigarette smoking in academic achievement, stress and social expectations: does gender make a difference. J. Early Adolesc. 4, 353–370. Centers for Disease Control and Prevention, 2010. Cigarette use among high school students – United States, 1991–2009. MMWR 59, 797–801. Chaiton, M.O., Cohen, J.E., O’Loughlin, J., Rehm, J., 2009. A systematic review of longitudinal studies on the association between depression and smoking in adolescents. BMC Public Health 9, 356. Costello, J.E., Alaattin, E., Adrian, A., 2006. Is there an epidemic of child or adolescent depression? J. Child Psychol. Psychiatry 47, 1263–1271. DeHay, T., Morris, C., May, M.G., Devine, K., Waxmonsky, J., 2012. Tobacco use in youth with mental illnesses. J. Behav. Med. 35, 139–148. Dudas, R.B., Hans, K., Barabas, K., 2005. Anxiety, depression and smoking in schoolchildren – implications for smoking prevention. J. Roy. Soc. Promot. Health 125, 87–92. Eaton, D.K., Kann, L., Kinchen, S., Shanklin, S., Flint, K.H., Hawkins, J., Harris, W.A., Lowry, R., McManus, T., Chyen, D., Whittle, L., Lim, C., Wechsler, H., 2012. Youth risk behavior surveillance – United States, 2011. MMWR Surveill. Summ. 61, 1–162. Fergusson, D.M., Goodwin, R.D., Horwood, L.J., 2003. Major depression and cigarette smoking: results of a 21-year longitudinal study. Psychol. Med. 33, 1357–1367. Finney Rutten, L.J., Augustson, E.M., Moser, R.P., Beckjord, E.B., Hesse, B.W., 2008. Smoking knowledge and behavior in the United States: sociodemographic, smoking status, and geographic patterns. Nicotine Tob. Res. 10, 1559–1570. Flay, B.R., 2009. The promise of long-term effectiveness of school-based smoking prevention programs: a critical review of reviews. Tob. Induc. Dis. 5, 7. Fryar, C.D., Merino, M., Hirsch, R., Porter, K.S., 2009. Smoking, alcohol use, and illicit drug use reported by adolescents aged 12–17 years: United States, 1999–2004. In: Natl. Health Stat. Rep. 1. Gierisch, J.M., Bastian, L.A., Calhoun, P.S., McDuffie, J.R., Williams, J.W., 2012. Smoking cessation interventions for patients with depression: a systematic review and meta-analysis. J. Gen. Intern. Med. 27, 351–360. Goodman, E., Capitman, J., 2000. Depressive symptoms and cigarette smoking among teens. Pediatrics 106, 748–755. Hover, S.J., Gaffney, L.R., 1988. Factors associated with smoking behavior in adolescent girls. Addict. Behav. 13, 139–145. Jamieson, P.E., Romer, D., 2008. Unrealistic fatalism in US youth ages 14 to 22: prevalence and characteristics. J. Adolesc. Health 42, 154–160. Johnson, C.A., Cen, S., Gallaher, P., Palmer, P.H., Xiao, L., Ritt-Olson, A., Unger, J.B., 2007. Why smoking prevention programs sometimes fail. Does effectiveness depend on sociocultural context and individual characteristics? Cancer Epidemiol. Biomarkers Prev. 16, 1043–1049. Johnston, L.D., O’Malley, P.M., Miech, R.A., Bachman, J.G., Schulenberg, J.E., 2014. 2013 Overview: Key Findings on Adolescent Drug Use. Institute for Social Research, Ann Arbor, MI, pp. 85.
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Kafilat Tolani, J., 2012. Ethnic differences in susceptibility to smoking and intention to smoke on smoking behavior among adolescents. J. Community Med. Health Educ. 2, 143. Kear, M.E., 2002. Psychosocial determinants of cigarette smoking among college students. J. Community Health Nurs. 19, 245–257. Klungsoyr, O., Nygard, J.F., Sorensen, T., Sandanger, I., 2006. Cigarette smoking and incidence of first depressive episode: an 11-year, population-based follow-up study. Am. J. Epidemiol. 163, 421–432. Lantz, P.M., Jacobson, P.D., Warner, K.E., Wasserman, J., Pollack, H.A., Berson, J., Ahlstrom, A., 2000. Investing in youth tobacco control: a review of smoking prevention and control strategies. Tob. Control 9, 47–63. Lorenzo-Blanco, E.I., Unger, J.B., Ritt-Olson, A., Soto, D., Baezconde-Garbanati, L., 2011. Acculturation, gender, depression, and cigarette smoking among U.S. Hispanic youth: the mediating role of perceived discrimination. J. Youth Adolesc. 40, 1519–1533. MacKinnon, D.P., Fairchild, A.J., 2009. Current directions in mediation analysis. Curr. Direct. Psychol. Sci. 18, 16–20. McCarthy, W.J., Dietsch, B., Hanson, T.L., Zheng, C.H., 2008. Evaluation of the In-School Tobacco Use Prevention Education Program, 2003–2004. California Department of Public Health, Sacremento, CA. McChargue, D.E., Spring, B., Cook, J.W., Neumann, C.A., 2004. Reinforcement expectations explain the relationship between depressive history and smoking status in college students. Addict. Behav. 29, 991–994. Minnix, J.A., Blalock, J.A., Marani, S., Prokhorov, A.V., Cinciripini, P.M., 2011. Self-efficacy mediates the effect of depression on smoking susceptibility in adolescents. Nicotine Tob. Res. 13, 699–705. Mistry, R., McCarthy, W.J., Yancey, A.K., Lu, Y., Patel, M., 2009. Resilience and patterns of health risk behaviors in California adolescents. Prev. Med. 48, 291–297. Ritt-Olson, A., Unger, J., Valente, V., Nezami, E., Chou, C., Trinidad, D., Milam, J., Earleywine, M., Tan, S., Johnson, C.A., 2005. Exploring peers as a mediator of the association between depression and smoking in young adolescents. Subst. Use Misuse 40, 77–98. Roberts, C., Williams, R., Kane, R., Pintabona, Y., Cross, D., Zubrick, S., Silburn, S., 2011. Impact of a mental health promotion program on substance use in young adolescents. Adv. Mental Health 10, 72–82.
Rodriguez, D., Romer, D., Audrain-McGovern, J., 2007. Beliefs about the risks of smoking mediate the relationship between exposure to smoking and smoking. Psychosom. Med. 69, 106–113. Schleicher, H.E., Harris, K.J., Catley, D., Nazir, N., 2009. The role of depression and negative affect regulation expectancies in tobacco smoking among college students. J. Am. Coll. Health 57, 507–512. Schwarz, N., Bless, H., Bohner, G., 1991. Mood and persuasion: affective states influence processing of persuasive communications. Adv. Exp. Soc. Psychol. 24, 161–199. Spruijt-Metz, D., Gallaher, P., Unger, J.B., Johnson, C.A., 2005. Unique contributions of meanings of smoking and outcome expectancies to understanding smoking initiation in middle school. Ann. Behav. Med. 30, 104–111. Stanton, W.R., McClelland, M., Elwood, C., Ferry, D., Silva, P.A., 1996. Prevalence, reliability and bias of adolescents’ reports of smoking and quitting. Addiction 91, 1705–1714. Steuber, T.L., Danner, F., 2006. Adolescent smoking and depression: which comes first. Addict. Behav. 31, 133–136. Sun, P., Unger, J.B., Guo, Q., Gong, J., Ma, H., Palmer, P.H., Chou, C.-P., Li, Y., Sussman, S., Ritt-Olson, A., 2007. Comorbidity between depression and smoking moderates the effect of a smoking prevention program among boys in China. Nicotine Tob. Res. 9, S599–S609. Trope, Y., Ferguson, M., Raghunathan, R., Forgas, J.P. (Eds.), 2001. Hand book of affect and social cognition. Lawrence Erlbaum Associates Publishers, Mahwah, NJ, US, pp. 256–274, xviii, 457 pp. US Department of Health and Human Services, 2010. How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease: A Report of the Surgeon General. Department of Health and Human Services Centers for Disease Control and Prevention National Center for Chronic Disease Prevention and Health Promotion Office on Smoking and Health, Atlanta, GA. Waller, M.W., Hallfors, D.D., Halpern, C.T., Iritani, B.J., Ford, C.A., Guo, G., 2006. Gender differences in associations between depressive symptoms and patterns of substance use and risky sexual behavior among a nationally representative sample of U.S. adolescents. Arch. Women’s Ment. Health 9, 139–150. Young, T.L., Rogers, K.D., 1986. School performance and characteristics preceding onset of smoking in high school students. Am. J. Dis. Child. 140, 225–257.
Contents lists available at ScienceDirect
Drug and Alcohol Dependence journal homepage: www.elsevier.com/locate/drugalcdep
Cognitive mediators and disparities in the relation between teen depressiveness and smoking Ritesh Mistry a,b,∗ , Giridhara R. Babu c,d , Tanmay Mahapatra c , William J. McCarthy a a
Center for Cancer Prevention and Control Research, University of California, Los Angeles, United States Department of Health Behavior and Health Education, University of Michigan, United States Department of Epidemiology, University of California, Los Angeles, United States d Indian Institute of Public Health-Hyderabad (Bangalore Wing), Public Health Foundation of India, India b c
a r t i c l e
i n f o
Article history: Received 13 September 2013 Received in revised form 4 February 2014 Accepted 18 March 2014 Available online 30 March 2014 Keywords: Adolescent Smoking Mediation Depression Gender Race/ethnicity
a b s t r a c t Background: Depressiveness and tobacco use in adolescents are linked, however, there is limited evidence about the cognitive mediators involved and how the role of mediators may differ by gender and racial/ethnic subgroups. Methods: We used a racially/ethnically diverse population-based cross-sectional sample of middle and high school students (n = 24,350). Logistic regression models measured the associations of depressiveness with tobacco smoking status, and whether smoking-related knowledge and attitudes (KA) and smoking refusal self-efficacy (SE) attenuated the associations indicating preliminary evidence of mediation. Results: Depressiveness was associated with intention to smoke (OR = 2.41; 95% CI = 2.22, 2.61), experimental smoking (OR = 1.93; 95% CI = 1.72, 2.17) and established smoking (OR = 1.85; 95% CI = 1.57, 2.18). The percent attenuation of these associations due to the inclusion of smoking-related KA and smoking refusal SE was 58% for intention to smoke (p < 0.001), 68% for experimental smoking (p < 0.001) and 86% for established smoking (p < 0.001). The association of depressiveness with established smoking did not remain statistically significant (OR = 1.16; CI = 0.97, 1.40) after including smoking-related KA and smoking refusal SE. Attenuation was more pronounced in males and white students. Conclusions: The results suggest that smoking-related KA and smoking refusal SE attenuated the relation between depressiveness and smoking, indicating that they may serve as mediators of the link between depressiveness and smoking. Tobacco use prevention programs targeting teens with the aim of increasing anti-smoking KA and smoking refusal SE may benefit from addressing depressiveness, particularly by using gender and racially/ethnically tailored strategies. The cross-sectional nature of the data precludes causal inferences. © 2014 Elsevier Ireland Ltd. All rights reserved.
1. Introduction The rates of adolescent tobacco use in the United States remain unacceptably high. It is estimated that about 20% of adolescents are current tobacco smokers (i.e., those who smoked on at least 1 day in the past month) and about 7% are frequent smokers (i.e., those who smoked on 20 or more days in the past month; Centers for Disease Control and Prevention, 2010). Depression and depressive symptoms have been identified as both antecedents (Fergusson et al., 2003) and consequences (Boden et al., 2010; Goodman and
∗ Corresponding author at: Department of Health Behavior and Health Education, University of Michigan School of Public Health, 1415 Washington Heights, SPH I, Room 3806, Ann Arbor, MI 48109-2029, United States. Tel.: +1 734 936 1318. E-mail address: [email protected] (R. Mistry). http://dx.doi.org/10.1016/j.drugalcdep.2014.03.022 0376-8716/© 2014 Elsevier Ireland Ltd. All rights reserved.
Capitman, 2000) of adolescents smoking (Chaiton et al., 2009; Steuber and Danner, 2006), and contribute to the initiation of and transition into regular smoking (Audrain-McGovern et al., 2004; Fergusson et al., 2003). Prolonged feelings of sadness or hopelessness, common depression symptoms, are linked with adolescent smoking (Mistry et al., 2009). With the prevalence of current or recent depression among adolescents in the United States at 6% (Costello et al., 2006) and the prevalence of prolonged recent sadness and hopelessness at 29% (Eaton et al., 2012), it is important to understand potential pathways by which depressiveness impacts smoking, especially because smoking is an important risk factor for major chronic diseases (US Department of Health and Human Services, 2010). A number of theories posit that health risk behaviors such as tobacco use are partially determined by cognitive factors such as perceived risks and benefits of a health risk behavior as well
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Smoking knowledge & atudes
Peer smoking, Ease of access to tobacco
Smoking refusal self-efficacy
DEPRESSIVENESS
SMOKING
Age, Gender, Race/Ethnicity, Academic Performance Fig. 1. Conceptual framework of factors involved in the link between depressiveness and smoking.
as self-efficacy (Health Belief Model, Social Cognitive Theory) to not engage in unhealthful behaviors despite other influences. Social Cognitive Theory additionally posits that there is interplay between cognition (e.g., beliefs, knowledge, attitudes, perceived self-efficacy) and affect (e.g. depressive symptoms) that influences behavior. The cognitive processes involved during adolescence in the link between depressive symptoms and smoking have been studied empirically to a limited extent, while further research is required particularly using diverse population-based samples. Studies in adults suggest that expectations held about whether smoking reduces negative emotions (McChargue et al., 2004; Schleicher et al., 2009) and self-efficacy to refuse tobacco when offered by others (Kear, 2002) mediate the relation. In addition, the research in adolescent samples suggests that mediators of the link between depressive symptoms and smoking include social influences such as peer approval of tobacco use (Ritt-Olson et al., 2005), smoking refusal self-efficacy (Minnix et al., 2011), perceived smoking reward (Audrain-McGovern et al., 2012) and risk (Rodriguez et al., 2007) as well as outcome expectancies (Spruijt-Metz et al., 2005). These studies have helped elucidate the potential pathways, however, data are needed about the underlying heterogeneity in the role of potential mediators across important socio-demographic factors such as gender and race/ethnic identification. Research that helps to illuminate the cognitive pathways involved in the link between depressive symptoms and smoking in adolescents could be useful for designing prevention programs. The literature suggests uneven efficacy of affect based adolescent tobacco use prevention programs (Flay, 2009) and that the efficacy of prevention programs may be moderated by depressive symptoms (Johnson et al., 2007; Sun et al., 2007). Knowledge of the cognitive pathways involved may help identify which factors to focus upon and how to design programs to better tailor intervention strategies for gender and race/ethnic subgroups of adolescents based on whether they are experiencing depressive symptoms. In this study, we used data from a large racially/ethnically diverse population-based sample to examine the association between feelings of depressiveness and smoking in adolescents, and tested two cognitive factors (Fig. 1) for cross-sectional evidence of mediation. Though cross-sectional data are not ideal for making causal inferences and testing mediation, the results can provide hypothesis-generating evidence that could inform further research using longitudinal and experimental designs. We chose to examine smoking-related knowledge and attitudes (KA) and smoking refusal self-efficacy (SE) as potential mediators because these constructs are key factors that many tobacco use prevention
57
education programs, particularly school-based program, aim to modify in order to reduce youth tobacco use risk. In addition, depression and depressive symptoms have been shown to affect information processing (Schwarz et al., 1991; Trope et al., 2001) and decision-making (Bechara et al., 2000), which may impact skills and knowledge gained from tobacco use prevention education programs. We anticipated that prolonged sadness or hopelessness, commonly reported symptoms of depression and depressive symptoms, would impair the ability of adolescents to process tobacco use prevention information and acquire tobacco refusal skills. As a result, adolescents who reported depressiveness may have also reported less anti-tobacco knowledge and attitudes as well as lower tobacco refusal self-efficacy. Hence, we hypothesized that there would be positive associations between depressiveness and adolescent smoking status (intention to smoke, experimental smoking and established smoking) in the sample, and that these associations would be attenuated by smoking-related KA and smoking refusal SE indicating evidence of potential mediation. We also hypothesized that the attenuation in the relation between depressiveness and smoking due to smoking-related KA and smoking refusal SE would differ by gender and race/ethnicity, because there is substantial differential risk of depressive symptoms and tobacco use between adolescent males and females (Fryar et al., 2009), and categories of race/ethnicity (Centers for Disease Control and Prevention, 2010; Kafilat Tolani, 2012). 2. Methods 2.1. Sample We used population-based cross-sectional survey data from the 2003–2004 California Student Tobacco Survey (CSTS), a stratified two-stage cluster sampling inschool survey of 25,868 middle and high schools students in 226 California schools (McCarthy et al., 2008). The CSTS participants were sampled from 12 regions (strata), which were formed on the basis of county demographic and socioeconomic characteristics. First, schools in each stratum were randomly selected with probabilities proportional to size of enrollment. Intact classes of required courses were randomly sampled from selected schools. Active parental consent to participate was obtained, which resulted in a student participation rate of 69.6%, for a total of 24,350 students in our study. 2.2. Measures Intention to smoke was measured using the question “Do you think you will smoke tobacco at any time during the next year?” Having an intention to use tobacco was defined as responses of “Definitely yes” or “Probably yes” and not having an intention to use was defined as “Definitely no” or “Probably no.” Experimental smoking and established smoking were assessed using two items: “About how many cigarettes have you smoked in your entire life,” and “During the past 30 days, on how many days did you smoke cigarettes.” Experimental smoking was defined as having smoked less than 100 cigarettes in one’s lifetime and having smoked during the last 30 days. Established smoking was defined as having smoked 100 or more cigarettes in one’s lifetime and having smoked in the last 30 days. Depressiveness was assessed using the commonly used United States Youth Behavioral Risk Survey question: “During the last 12 months, did you feel sad or hopeless almost every day for 2 or more weeks?” This is a widely used surveillance measure of depressive symptoms (Eaton et al., 2012) and has been associated with measures of negative affect such as unrealistic fatalism (Jamieson and Romer, 2008) and suicidal ideation (Jamieson and Romer, 2008). Smoking-related KA was assessed through standardized scores on an ad-hoc 12-item scale (Cronbach’s alpha = 0.71). The items included in the scale asked about whether smoking: reduces weight gain; is a way to lose friends; results in shorter lives; makes one appear more grown up; makes one more relaxed; makes one look cool; cigars are as bad as cigarettes; if those who smoke have more friends, look more cool or fit in; risk harming themselves if they smoke 1–5 cigarettes a day; and whether it is safe to smoke for a year or two as long as one quits. There were four Likert-type response categories from “Definitely yes” to “Definitely not,” which were coded as 0, 33, 66 or 100 with higher scores reflecting more accurate knowledge about and more negative attitudes toward tobacco use. An average score across all items was created and then standardized. Smoking refusal SE was defined as low if the response to the question “How hard would it be to refuse or to say “no” to a friend who offered you a cigarette?” was “Very hard” or “Hard” and high if the response was “Easy” or “Very easy”.
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Study covariates included age (categorized as 12 yrs or less, 13–14 yrs, 15–16 yrs and 17 yrs or more), gender, race/ethnicity (categorized as white, Hispanic, Asian/Pacific Islanders, African American and American Indian/Alaskan Natives), academic performance (categorized as Superior = Mostly A’s; Good = A’s and B’s; Fair = Mostly B’s, and B’s and C’s; Poor = Mostly C’s or worse), perceived peer smoking (defined as “Low” if respondents reported that <20% of peers smoke, “Moderate” if 21–60% and “High” if >61%) and perceived ease of obtaining tobacco (categorized as “Easy” and “Hard”). Fig. 1 shows that age, gender, race/ethnicity and educational performance were expected to be potential confounders of the relation between depressiveness and smoking (Brunswick and Messeri, 1984; Klungsoyr et al., 2006; Young and Rogers, 1986). Because perceived peer smoking and ease of access to tobacco are not likely to be associated with depressiveness (Hover and Gaffney, 1988), they were not hypothesized to cofound the relation between depressiveness and smoking, but were hypothesized to confound the association of smoking-related KA and smoking refusal SE (i.e., the hypothesized mediators) with smoking outcomes. 2.3. Analysis First, we conducted descriptive analyses of the study variables. Second, we used the causal steps approach to measure evidence of mediation (MacKinnon and Fairchild, 2009). The percent attenuation in the association between depressiveness and smoking after inclusion of the cognitive cofactors (anti-smoking KA and smoking refusal SE) was used to measure preliminary mediation. We used logistic regression to estimate the association of depressiveness with each smoking measure controlling for age, educational performance, gender and race/ethnicity (Model Set 1). Because we hypothesized that peer smoking and perceived ease of access to tobacco would confound the association of smoking status with smoking-related KA and smoking refusal SE, but not likely to be associated with depressiveness, we did not include them as covariates in Model Set 1. In Model Set 2, we added smokingrelated KA, perceived peer smoking and perceived ease of access to tobacco to the variables included in Model Set 1. In Model Set 3, the fully controlled models, we added smoking refusal SE to the variables included in Model Set 2. Attenuation after inclusion of smoking-related KA was measured as percent reductions of the Model Set 1 coefficients for the association between depressiveness and each smoking measure when compared to the corresponding coefficients in Model Set 2. Similarly, attenuation after inclusion of both smoking-related KA and smoking refusal SE was obtained as percent reductions in the Model Set 1 coefficients for the association between depressiveness and each smoking measure, when compared to the corresponding coefficients in Model Set 3. Finally, we analyzed whether the fully controlled association between depressiveness and smoking status (Model Set 3) and percent attenuation due to inclusion of smoking-related KA and smoking refusal SE differed based on gender and race/ethnicity by stratifying the regression analysis by these two demographic variables. Statistical analysis was conducted using SAS 9.1. Results were adjusted for the survey sampling design, and weighted to represent California middle and high school students.
3. Results Table 1 shows the distribution of study variables and crosstabulations of depressiveness and smoking status with the covariates. Nearly 50% of participants were 15 or more years of age, and there were more females (53%) than males (47%); the gender distribution was similar across race/ethnicity, i.e. 52–55% female and 45–48% male. The participants were mostly white (42%) or Hispanic (34%), but Asian/Pacific Islanders (16%), African Americans (7%) and American Indians/Alaskan natives (2%) were also included in the sample. Depressiveness was reported by about 28% of the participants, and was most frequently reported by Hispanics (30%) and African Americans (30%). Intention to smoke, experimental smoking and established smoking were reported by 15%, 6% and 3% of the participants, respectively, with Hispanics most frequently reporting intention to smoke (17%) and experimental smoking (8%) while whites most frequently reporting established smoking (5%). Table 2 shows results from the logistic regression analysis using Model Sets 1–3 as described above and the estimated attenuation in the association between depressiveness and smoking status due to the inclusion of smoking-related KA and smoking refusal SE. Results from Model Set 1 show that students who reported depressiveness were at 2.41 times higher odds of reporting intention to smoke (95% CI: 2.22, 2.61), 1.93 times higher odds of reporting experimental smoking (95% CI: 1.72, 2.17) and 1.85 times higher odds of reporting established smoking (95% CI: 1.57, 2.18). When the measure for smoking-related KA was added to Model Set 1 the odds ratios for
each outcome were attenuated (Model Set 2) by 54% for intention to smoke (p < 0.001), 68% for experimental smoking (p < 0.001) and 75% for established smoking (p < 0.001). When the measures of both smoking-related KA and smoking refusal SE (Model Set 3) were added to Model Set 1, the odd ratios were attenuated even further as compared to Model Set 1 for intention to smoke (58%, p < 0.001) and established smoking (86%, p < 0.001), but not for experimental smoking (68%, p < 0.001). The odds ratio for the relation between depressiveness and established smoking became non-significant in Model Set 3. Table 3 shows the regression results stratified by gender and race/ethnicity in order to assess whether the fully controlled associations between depressiveness and smoking outcomes (Model Set 3) and percent attenuation due to smoking-related KA and smoking refusal SE were modified by these demographic variables. The results show that fully controlled associations of depressiveness with intention to smoke and established smoking was significantly greater for female versus male students, and Hispanic students versus white students. This is evident from the odds ratio point estimates of Model Set 3 for intention to smoke and established smoking for one gender or race/ethnicity being outside of the corresponding 95% confidence intervals for the other gender or race/ethnicity. The results also show that percent attenuation due to smokingrelated KA and smoking refusal SE for intention to smoke and established smoking was, respectively, 53% and 73% for female students compared to 67% and 100% for males students, and 51% and 54% for Hispanic students versus 65% and 100% for white students.
4. Discussion This study analyzed a large racially/ethnically diverse population-based sample of middle and high school students to preliminarily assess mediation by two cognitive factors in the link between depressiveness and tobacco smoking. We examined smoking-related KA and smoking refusal SE as potential mediators because they may be negatively influence by depressive symptoms (Schwarz et al., 1991; Trope et al., 2001) and because they are important modifiable factors that many tobacco use prevention education programs aim to improve (Lantz et al., 2000). The results add to the current literature by finding preliminary evidence of the mediational roles of smoking-related KA and smoking refusal SE as shown by the attenuation of the associations of depressive symptoms with smoking status. Prior research suggests that smoking-related KA and smoking refusal SE may act as mediators (Finney Rutten et al., 2008; Minnix et al., 2011; Rodriguez et al., 2007), however how the mediating roles of these factors vary across gender and racial/ethnic subgroups has not been examined to our knowledge. This study shows that attenuation due to smoking-related KA and smoking refusal SE differed based on gender and racial/ethnic identification indicating the these demographic factors may serve as important moderators. The findings indicate that smoking-related KA and smoking refusal SE may completely explain away the association between depressiveness and established smoking, and substantially attenuated the association of depressiveness with intention to smoke and experimental smoking. This suggests good preliminary evidence of mediation. Consistent with other literature (Waller et al., 2006), the association of depressiveness with intention to smoke and established smoking was higher in female compared to male students. In Hispanic compared to non-Hispanic students, the association of depression on intention to smoke and established smoking was also higher, but this was not consistent research in Hispanic adults (Berg et al., 2012) despite evidence suggesting
Table 1 Descriptive analysis of study participants (n = 24,350). % (n)
Depressiveness, % (n)
Smoking outcomes, % (n)
Intention
Smoking refusal self-efficacy, % (n) Experimental
Smoking knowledge and attitude
Established
No
Yes
No
Yes
No
Yes
No
Low
High
Mean
SE
72.3 (15,750)
82.8 82.6 89.0 91.4
−0.01 p < 0.001 0.08 −0.04 −0.03 −0.01
0.00
99.8 98.7 95.5 92.9
13.8 (3256) p < 0.010 17.2 17.4 11.0 8.6
86.3 (20,429)
98.2 94.2 31.9 90.9
3.1 (733) p < 0.001 0.3 1.3 4.5 7.1
96.8 (22,712)
95.7 86.4 80.9 78.1
6.3 (1475) p < 0.001 1.8 5.8 8.1 9.1
93.7 (21,970)
79.8 72.3 69.4 70.6
14.9 (3603) p < 0.001 4.3 13.6 19.2 21.9
85.1 (20,569)
20.9 30.5 30.0 18.7
27.7 (6024) p < 0.001 20.2 27.7 30.6 29.4
0.01 0.01 0.01 0.01
Gender Female Male
53.0 47.0
p < 0.001 30.8 24.0
69.2 76.1
p < 0.001 14.1 15.7
85.9 84.3
p < 0.001 6.0 6.6
94.0 93.4
p < 0.001 2.4 4.0
97.6 96.0
p < 0.001 12.8 14.7
87.2 85.3
p < 0.001 0.05 −0.07
0.00 0.01
Race/ethnicity White Caucasian Hispanic Asian/Pacific Islander African American American Indian/AN
42.0 33.5 15.5 7.2 1.9
p < 0.001 25.2 30.1 28.8 30.0 26.2
74.8 70.0 71.3 70.0 73.8
p < 0.001 15.3 17.3 10.8 11.3 12.2
84.7 82.7 89.2 88.7 87.8
p < 0.001 6.0 7.8 4.3 5.1 7.4
94.0 92.2 95.7 94.9 92.6
p < 0.001 4.6 2.0 2.3 1.7 2.8
95.4 98.0 97.7 98.3 97.2
p < 0.001 11.5 16.5 13.8 12.0 18.9
88.5 83.5 86.2 88.0 81.1
p < 0.001 0.05 −0.07 0.01 −0.06 −0.05
0.01 0.01 0.02 0.01 0.03
Academic performance Superior Good Fair Poor
25.0 33.2 27.9 13.9
p < 0.001 22.8 25.4 29.5 37.6
77.2 74.6 70.6 62.4
p < 0.001 9.2 11.5 18.4 29.4
90.8 88.5 81.6 70.6
p < 0.001 3.2 4.7 7.9 14.0
96.8 95.3 92.1 86.0
p < 0.001 2.0 2.2 3.7 7.3
98.0 97.8 96.3 92.7
p < 0.05 12.0 12.0 13.5 20.1
88.0 88.0 86.5 79.9
p < 0.001 0.09 0.05 −0.04 −0.21
0.02 0.01 0.01 0.01
Peers smoking Low Moderate High
49.5 39.7 10.8
p < 0.001 22.3 31.4 37.7
77.7 68.6 62.4
p < 0.001 6.6 19.5 36.8
93.4 80.5 63.2
p < 0.001 2.7 8.4 15.9
97.3 91.6 84.2
p < 0.001 0.9 4.2 9.8
99.1 95.8 90.2
p < 0.001 13.7 12.2 19.6
86.3 87.8 80.4
p < 0.001 0.06 −0.03 −0.24
0.00 0.01 0.01
Tobacco ease of access Hard Easy
64.3 35.7
p < 0.001 24.2 33.7
75.9 66.3
p < 0.001 8.9 26.0
91.1 74.0
p < 0.001 4.0 10.4
96.0 89.6
p < 0.001 1.5 6.1
98.5 93.9
p < 0.001 13.1 14.7
86.9 85.3
p < 0.001 0.06 −0.13
0.00 0.01
100 (24,350)
R. Mistry et al. / Drug and Alcohol Dependence 140 (2014) 56–62
Yes Column sample size Age 12 yrs or less 13–14 yrs 15–16 yrs 17 yrs or more
59
60
R. Mistry et al. / Drug and Alcohol Dependence 140 (2014) 56–62
Table 2 Association between depressiveness and smoking measures, and mediation due to smoking-related knowledge and attitudes (KA) and smoking refusal self-efficacy (SE) (n = 24,350). Smoking outcomes
Intention to smoke Experimental smoking Established smoking a b c ** ***
Model Set 1a
Model Set 2b
Model Set 3c
Percent mediation in relation to model Set 1
OR
OR
OR
Smoking KA
95% CI ***
2.41 1.93*** 1.85***
2.22, 2.61 1.72, 2.17 1.57, 2.18
95% CI ***
1.84 1.47*** 1.34**
1.68, 2.01 1.30, 1.67 1.12, 1.60
95% CI ***
1.73 1.47*** 1.16
1.58, 1.90 1.30, 1.67 0.97, 1.40
Smoking KA and smoking refusal SE
***
57.80*** 68.03*** 86.21***
54.35 68.03*** 74.63***
Adjusted for age, gender, race/ethnicity and educational performance. Adjusted for smoking-related KA, peer smoking and perceived ease of access to tobacco, in addition to Model Set 1 covariates. Adjusted for smoking refusal SE, in addition to Model Set 2 covariates. p < 0.01. p < 0.001.
greater prevalence of depressiveness and smoking from studies in Hispanic populations (Lorenzo-Blanco et al., 2011) and national data comparing racial/ethnic subgroups (Johnston et al., 2014). Attenuation after the inclusion of smoking-related KA and smoking refusal SE was more pronounced in male and white students. The results point toward researching the integration of the management and reduction of negative affective symptoms such as depressiveness as part of adolescent tobacco use prevention programs, especially those that aim to increase anti-tobacco KA and smoking refusal SE. For example, identification of students with significant depressive symptoms and referral to mental health services may enhance tobacco use prevention or other health education efforts. The literature suggests that addressing depression as part of smoking cessation interventions in adults has positive impacts (Gierisch et al., 2012), however, research with respect to
tobacco use prevention and cessation in adolescent populations with depressive symptoms and depression is needed (DeHay et al., 2012). Moreover, the results suggest that designing tobacco use prevention strategies to improve anti-smoking KA and smoking refusal SE should be done in a manner that is salient to adolescents experiencing depressive symptoms and are at high risk for depression. Such adolescents may require different modes of delivery and content of tobacco use prevention education and skill building exercises, particularly for male and white adolescents. Finally, adolescent depression and depressiveness is in itself of public health importance. Effective programs and services for primary prevention and treatment of depression in adolescents are not readily available, especially for socio-economically disadvantaged youth. Preventing adolescent depressiveness may reduce the risk of tobacco use initiation (Dudas et al., 2005; Roberts et al., 2011)
Table 3 Moderating effect of gender and race/ethnicity on the association of depressiveness with smoking outcomes and mediation due to smoking-related knowledge and attitudes (KA) and smoking refusal self-efficacy (SE) (n = 24,350). Model Set 1a
Model Set 2b
Model Set 3c
Percent mediation
OR
95% CI
OR
95% CI
OR
95% CI
Smoking KA
Smoking KA and smoking refusal SE
Female Intention to smoke Experimental smoking Established smoking
2.56 1.98 1.98
2.28, 2.88 1.68, 2.33 1.53, 2.56
1.97 1.49 1.48
1.74, 2.24 1.25, 1.77 1.13, 1.94
1.88 1.47 1.38
1.66, 2.14 1.24, 1.75 1.04, 1.82
50.76 67.11 67.57
53.19 68.03 72.46
Male Intention to smoke Experimental smoking Established smoking
2.13 1.83 1.64
1.88, 2.42 1.53, 2.19 1.30, 2.06
1.61 1.45 1.18
1.40, 1.86 1.20, 1.75 0.92, 1.52
1.50 1.44 0.99
1.30, 1.73 1.20, 1.74 0.77, 1.29
62.11 68.97 84.75
66.67 69.44 100.00
White Intention to smoke Experimental smoking Established smoking
2.26 2.04 1.59
1.98, 2.57 1.69, 2.46 1.28, 1.99
1.63 1.56 1.13
1.41, 1.89 1.28, 1.89 0.89, 1.43
1.55 1.57 1.00
1.34, 1.80 1.29, 1.91 0.78, 1.28
61.35 64.10 88.50
64.52 63.69 100.00
Hispanic Intention to smoke Experimental smoking Established smoking
2.50 1.80 2.50
2.17, 2.87 1.48, 2.18 1.74, 3.58
2.07 1.45 2.02
1.78, 2.41 1.19, 1.77 1.38, 2.94
1.97 1.41 1.84
1.69, 2.30 1.15, 1.72 1.26, 2.71
48.31 68.97 49.50
50.76 70.92 54.35
Asian/Pacific Islander Intention to smoke Experimental smoking Established smoking
2.35 2.07 1.75
1.84, 2.99 1.45, 2.96 1.07, 2.86
1.79 1.50 1.23
1.37, 2.33 1.03, 2.18 0.72, 2.10
1.66 1.48 1.06
1.27, 2.18 1.02, 2.17 0.62, 1.84
55.87 66.67 81.30
60.24 67.57 94.34
African American Intention to smoke Experimental smoking Established smoking
2.41 2.31 1.44
1.68, 3.47 1.38, 3.84 0.58, 3.55
1.79 1.65 0.72
1.20, 2.67 0.95, 2.88 0.25, 2.04
1.67 1.58 0.64
1.11, 2.52 0.90, 2.76 0.22, 1.87
55.87 60.61 –
59.88 63.29 –
American Indian/AN Intention to smoke Experimental smoking Established smoking
2.20 0.92 1.88
1.05, 4.60 0.33, 2.59 0.40, 8.90
1.61 0.90 1.80
0.68, 3.77 0.30, 2.73 0.30, 10.68
1.31 0.86 1.32
0.52, 3.33 0.28, 2.67 0.18, 9.46
62.11 – 55.56
76.34 – 75.76
Smoking outcomes
a b c
Adjusted for age, gender, race/ethnicity and educational performance. Adjusted for smoking-related KA, peer smoking and perceived ease of access to tobacco, in addition to Model Set 1 covariates. Adjusted for smoking refusal SE, in addition to Model Set 2 covariates.
R. Mistry et al. / Drug and Alcohol Dependence 140 (2014) 56–62
and other behavioral risks (Mistry et al., 2009). More research is, therefore, required to better understand the determinants of adolescent depressiveness and to identify efficacious prevention and treatment strategies.
4.1. Strengths and limitations To our knowledge, there is little information in the scientific literature on the possible mediational roles of smoking-related KA and smoking refusal SE in the pathways linking depressiveness and smoking in adolescent and how they vary across racial/ethnic and gender strata. This study adds to the current literature by examining these potential mediators using a large racially/ethnically diverse population-based sample of adolescents. As with any crosssectional observational study, however, the results from this study preclude assessment of causal direction, and should be cautiously interpreted including with respect to the amount of mediation. Nonetheless the results are useful for generating hypotheses about mediation for further testing via prospective and experimental data, which we suggest as next steps. The study also aimed to take into account the most relevant risk factors of adolescent tobacco use in the analysis. Although we could not include all potential confounders, the inclusion of perceived peer smoking and perceived ease of access to tobacco may serve as proxies for many factors commonly associated with smoking-related KA, smoking refusal SE and smoking status, such as community norms about tobacco use, social acceptance/stigma around smoking, as well as actual availability, financial access and social access to tobacco products. By controlling for perceived peer smoking and perceived ease of access to tobacco and relevant demographic and other covariates, we aimed to minimize confounding. However, as always there remained the possibility of confounding due to unmeasured variables. We also were limited to using self-reported data on smoking status, which are not ideal, but the data were collected confidentially to limit biases. The procedures used to collect these data have been widely used and have shown good validity and reliability when self-administered anonymously within classroom settings (Stanton et al., 1996). Finally, we used single-item measures of depressiveness, intention to smoke and smoking refusal SE. These, however, are commonly used measures in national and state level surveillance of youth behavioral risk factors. In addition, the measure of depressiveness has been consistently associated with mental health outcomes such as suicidal ideation (Jamieson and Romer, 2008) and health risk behaviors (Mistry et al., 2009). In summary, due to the cross-sectional nature of the data and the limitations due to the measurement of key study constructs, our results were not conclusive, but hypothesis generating and require further validation through studies using more detailed measures and rigorous study designs.
4.2. Conclusions Depressiveness was reported by a significant proportion of the sample and was consistently associated with various measures of smoking status, particularly in female and Hispanic students. The associations between depressiveness and smoking outcomes were attenuated by smoking-related KA and smoking refusal SE, indicating preliminary evidence of mediation. Despite the limitations of using cross-sectional data to evaluate mediation, these results suggest that tobacco use prevention programs targeting middle and high school aged students may benefit from addressing depressiveness, particularly by using gender and racially/ethnically tailored strategies.
61
Role of funding source This study was supported with funding from the California Tobacco Related Disease Research Program (17KT0030). Contributors RM originated the study concept and wrote the paper. GB assisted with writing the paper and provided critical reviews. TM conducted the data analysis and provided critical reviews. WM ensured the scientific integrity of the research and provided critical reviews. Conflict of interest The authors declare that there are no conflicts of interest in relation to the information presented in this manuscript. References Audrain-McGovern, J., Lerman, C., Wileyto, E.P., Rodriguez, D., Shields, P.G., 2004. Interacting effects of genetic predisposition and depression on adolescent smoking progression. Am. J. Psychiatry 164, 1224–1230. Audrain-McGovern, J., Rodriguez, D., Rodgers, K., Cuevas, J., Sass, J., Riley, T., 2012. Reward expectations lead to smoking uptake among depressed adolescents. Drug Alcohol Depend. 120, 181–189. Bechara, A., Damasio, H., Damasio, A.R., 2000. Emotion, decision making and the orbitofrontal cortex. Cereb. Cortex 10, 295–307. Berg, C.J., Kirch, M., Hooper, M.W., McAlpine, D., An, L.C., Boudreaux, M., Ahluwalia, J.S., 2012. Ethnic group differences in the relationship between depressive symptoms and smoking. Ethn. Health 17, 55–69. Boden, J.M., Fergusson, D.M., Horwood, L.J., 2010. Cigarette smoking and depression: tests of causal linkages using a longitudinal birth cohort. Br. J. Psychiatry 196, 440–446. Brunswick, A.F., Messeri, P.A., 1984. Origins of cigarette smoking in academic achievement, stress and social expectations: does gender make a difference. J. Early Adolesc. 4, 353–370. Centers for Disease Control and Prevention, 2010. Cigarette use among high school students – United States, 1991–2009. MMWR 59, 797–801. Chaiton, M.O., Cohen, J.E., O’Loughlin, J., Rehm, J., 2009. A systematic review of longitudinal studies on the association between depression and smoking in adolescents. BMC Public Health 9, 356. Costello, J.E., Alaattin, E., Adrian, A., 2006. Is there an epidemic of child or adolescent depression? J. Child Psychol. Psychiatry 47, 1263–1271. DeHay, T., Morris, C., May, M.G., Devine, K., Waxmonsky, J., 2012. Tobacco use in youth with mental illnesses. J. Behav. Med. 35, 139–148. Dudas, R.B., Hans, K., Barabas, K., 2005. Anxiety, depression and smoking in schoolchildren – implications for smoking prevention. J. Roy. Soc. Promot. Health 125, 87–92. Eaton, D.K., Kann, L., Kinchen, S., Shanklin, S., Flint, K.H., Hawkins, J., Harris, W.A., Lowry, R., McManus, T., Chyen, D., Whittle, L., Lim, C., Wechsler, H., 2012. Youth risk behavior surveillance – United States, 2011. MMWR Surveill. Summ. 61, 1–162. Fergusson, D.M., Goodwin, R.D., Horwood, L.J., 2003. Major depression and cigarette smoking: results of a 21-year longitudinal study. Psychol. Med. 33, 1357–1367. Finney Rutten, L.J., Augustson, E.M., Moser, R.P., Beckjord, E.B., Hesse, B.W., 2008. Smoking knowledge and behavior in the United States: sociodemographic, smoking status, and geographic patterns. Nicotine Tob. Res. 10, 1559–1570. Flay, B.R., 2009. The promise of long-term effectiveness of school-based smoking prevention programs: a critical review of reviews. Tob. Induc. Dis. 5, 7. Fryar, C.D., Merino, M., Hirsch, R., Porter, K.S., 2009. Smoking, alcohol use, and illicit drug use reported by adolescents aged 12–17 years: United States, 1999–2004. In: Natl. Health Stat. Rep. 1. Gierisch, J.M., Bastian, L.A., Calhoun, P.S., McDuffie, J.R., Williams, J.W., 2012. Smoking cessation interventions for patients with depression: a systematic review and meta-analysis. J. Gen. Intern. Med. 27, 351–360. Goodman, E., Capitman, J., 2000. Depressive symptoms and cigarette smoking among teens. Pediatrics 106, 748–755. Hover, S.J., Gaffney, L.R., 1988. Factors associated with smoking behavior in adolescent girls. Addict. Behav. 13, 139–145. Jamieson, P.E., Romer, D., 2008. Unrealistic fatalism in US youth ages 14 to 22: prevalence and characteristics. J. Adolesc. Health 42, 154–160. Johnson, C.A., Cen, S., Gallaher, P., Palmer, P.H., Xiao, L., Ritt-Olson, A., Unger, J.B., 2007. Why smoking prevention programs sometimes fail. Does effectiveness depend on sociocultural context and individual characteristics? Cancer Epidemiol. Biomarkers Prev. 16, 1043–1049. Johnston, L.D., O’Malley, P.M., Miech, R.A., Bachman, J.G., Schulenberg, J.E., 2014. 2013 Overview: Key Findings on Adolescent Drug Use. Institute for Social Research, Ann Arbor, MI, pp. 85.
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