Associations Between Individual and Contextual Factors and Smoking in 13,293 Mexican Students Edna Arillo-Santillan, MSc, Eduardo Lazcano-Ponce, DrSc, Mauricio Hernandez-Avila, DrSc, Esteve Fernández, DrSc, Betania Allen, MA, Raydel Valdes, MSc, Jonathan Samet, DrSc Objective:
Factors correlated with cigarette smoking in young people have yet to be documented in most developing countries. This study assesses the correlates of smoking in Mexican young people.
Methods:
School-based, cross-sectional study in the central Mexican state of Morelos during the 1998 –1999 school year of 13,293 public school students aged 11 to 24 years. Multinomial logistic regression models were constructed with smoking as the dependent variable.
Results:
Regular smoking (one or more cigarettes daily) prevalence was 13.1% (95% confidence interval [CI]⫽12.2–13.9) in males, and 6.1% (95% CI⫽5.6 – 6.6) in females. Frequent alcohol intoxication was strongly associated with regular smoking (females, odds ratio [OR]⫽68.5, 95% CI⫽37.6 –125.2; males, OR⫽34.5, 95% CI⫽22.6 –52.7). Regular smoking was associated with illegal drug use and smoking by both parents in females, and with illegal drug use in males (males, OR⫽4.9, 95% CI⫽3.7– 6.5). Also associated with tobacco smoking were high socioeconomic status, low academic achievement, illegal drug use by peers, marijuana use by parents, and depression in adolescents.
Conclusions: This study documents a strong correlation between tobacco smoking and other health risk behaviors, especially alcohol and drug abuse. In young women especially, the risk of tobacco use increased with alcohol abuse and higher socioeconomic status. School-based interventions are needed that focus on preventing smoking and also take into account other unhealthy behaviors. (Am J Prev Med 2005;28(1):41–51) © 2005 American Journal of Preventive Medicine
Introduction
W
orldwide, at the beginning of the 21st century, almost 20% of 13- to 15-year-olds use some type of tobacco product.1 In Mexico, according to the 2002 National Survey on Addictions,2 almost half of the adolescents surveyed (aged 12 to 17) who smoked cigarettes had begun smoking before age 15.2 There is evidence that adolescent smokers have more serious health problems and use health services more frequently.3,4 Moreover, lower levels of physical activity,5 and a greater number of psychosocial problems and depression6 have also been documented among adolescent smokers.
From the Center for Population Health Research, National Institute of Public Health (Arillo-Santillan, Lazcano-Ponce, Hernandez-Avila, Allen, Valdes), Cuernavaca, Morelos, Mexico; Catalan Institute of Oncology (Fernández), Barcelona, Catalunya, Spain; and Bloomberg School of Public Health, Johns Hopkins University (Samet), Baltimore, Maryland Address correspondence and reprint quests to: Dr. Eduardo Lazcano-Ponce, Director de Enfermedades Crónicas, Centro de Investigación en Salud Poblacional, Instituto Nacional de Salud Pública, Avenida Universidad 655, Colonia Sta. Ma. Ahuacatitlán, Cuernavaca, Morelos, Mexico. E-mail:
[email protected].
Parents’ health-risk behaviors have an impact on the behavior of their children,7 as they contribute to healthy or unhealthy lifestyles, including an increased risk for cigarette smoking. Smoking may be perceived by adolescents as the key to establishing autonomy, independence, intimacy, and identity.8 A number of experiences during childhood have been strongly associated with the initiation of smoking, and include parental history of smoking and alcohol abuse at home.9 Studies in several countries have shown that in the general population, but especially among adolescents and young adults, there is a positive relationship between smoking and alcohol consumption, although the strength of association has been reported as moderate. There is evidence that nicotine facilitates alcohol consumption,10 and alcohol reinforces cigarette smoking, likely explained by a phenomenon of cross-tolerance.11 In addition, some of the same genetic factors may increase risk for both tobacco and alcohol consumption.12,13 Studies have also shown that smoking and alcohol consumption are frequently concurrent predictors of illegal drug use.14
Am J Prev Med 2005;28(1) © 2005 American Journal of Preventive Medicine • Published by Elsevier Inc.
0749-3797/05/$–see front matter doi:10.1016/j.amepre.2004.09.002
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While factors that predict smoking in adolescents have been broadly documented in developed nations,15 there is little information in developing countries.16 The objective of this study was to assess whether greater prevalence of regular cigarette smoking among Mexican adolescents is associated with excessive alcohol use, illegal drug use, and higher socioeconomic status, and if it is also influenced by parental behavior.
Methods For this study, baseline data from an ongoing cohort study were analyzed. First, the questionnaire was pilot tested in 1998 in 3250 public school students (at junior high through college levels) in the capital city of Morelos State. Next, during the 1998 –1999 academic year, data were collected from 13,293 adolescents and young adults aged 11 to 24. The sample was representative of the public school population in Morelos. Eligible cohort participants were selected through probabilistic, stratified sampling. A sampling frame was developed of all public schools in Morelos State at the junior high, high school, and postsecondary level, including academic and technical educational facilities in urban, suburban, and rural areas. A systematic random sample of schools was obtained with probability proportional to size; the sampling unit was the school. Therefore, it was equally possible for any of the schools in the state to be selected and their inclusion in the study was based on population density in each area. The study was approved by the Ethics Committee of the National Institute of Public Health of Mexico. Confidentiality was protected through use of bar codes to identify the questionnaires; students did not write their names on the questionnaires. The participants responded to the selfadministered questionnaire in the school setting, but only study personnel (rather than teachers) handled questionnaires. Informed consent was obtained from both adolescent study participants and their parents (in meetings with the parents’ associations for each school, before data collection). Only students present on the day of the survey were eligible to participate; the response rate was 98.6%. Questionnaire items were focused on the following topics: (1) sociodemographic characteristics (age, family income, place of residence, parents’ schooling, parents’ occupation, housing conditions); (2) academic achievement based on self-reported average grades during the last year in school; (3) students’ smoking, alcohol and illegal drug use, and sexual activity; (4) illegal drug use of peers; and (5) parents’ smoking and alcohol and marijuana use. The same questionnaire was used for all age groups, and older students generally completed the questionnaire more quickly than younger students.
Definition of Study Variables Categories for adolescent smokers were based on the stages and levels of smoking proposed by Flay et al.15 specifically for adolescents: never users (have never tried cigarettes); experimenters (includes Flay’s “triers” and “experimenters,” and defined as those who take puffs or smoke less than one cigarette per day, or did so in the past), and regular smokers (smoke one or more cigarettes a day).
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The category for alcohol use is level of intoxication, and is similar to a category used in the Monitoring the Future study of U.S. adolescents.17 Level of intoxication is useful for studying patterns of alcohol consumption involving large quantities of alcohol, with intoxication occurring frequently, a behavior pattern observed in this study sample.18,19 This category had three levels: no alcohol intoxication, severe alcohol intoxication no more than once every 2 weeks, and severe alcohol intoxication more than once every 2 weeks. The category for drug use is based on the type of use in the study population; reported drug use was extremely low.17 Therefore, drug users were grouped into a single category of ever using in lifetime any type of illegal drug. Participants were also asked if they had peers who used illegal drugs, and if so, whether they were acquaintances or friends. Students were asked if their parents smoked and if they used marijuana. Depression was measured using the first factor of the Zung scale, with ten variables and answers on a 4-point scale ranging from never to often (␣⫽0.87). The academic achievement index consisted of self-reporting of the grade point average obtained in the previous year in school, on a scale of 1 to 10 (the grading scale used in Mexico). These responses were categorized into four achievement levels: high, medium, low, and failing. Place of residence (municipality) was categorized as rural, suburban, or urban, as defined by the National Institute of Statistics, Geography and Informatics. The socioeconomic status index was an ordinal variable from 1 to 10 generated through main components analysis based on characteristics of housing (type of flooring, presence of potable water and sewage system); household income; home ownership; car ownership; and presence of stationary propane gas tank, refrigerator, telephone, color television, and video cassette recorder. Cronbach’s alpha for this index was 0.6869.
Data Analysis Data were analyzed separately for males and females, due to known gender differences in cigarette smoking.20,21 However, when data for high school and university students were analyzed separately, results were very similar for both school levels. Therefore, to obtain greater statistical power and since the data were similar, the two groups were combined in the analysis. The first strategy consisted of constructing multivariate logistic regression models adjusted by age. Second, multivariate models adjusted by the other variables were generated and used to evaluate possible correlates.22 The dependent variable was cigarette smoking classified in three categories (never users, experimenters, and regular smokers, with never users taken as the reference category). The multinomial model makes assumptions with regard to equivalence of effect in transitions across these three categories, thereby modeling the transition from never smoker to experimenter and the transition from experimenter to regular smoker. Likewise, multivariate logistic regression models stratified by school level (junior high school and high school/college) were used to evaluate effect independent of age, as school level and age are colinear. These models provided the odds ratio (OR) and the corresponding 95% confidence interval (CI). A multilevel model was also used to examine determinants of smoking on an aggregate level, specifically school and
American Journal of Preventive Medicine, Volume 28, Number 1
Table 1. Characteristics of 13,293 students aged 11 to 24 years, Morelos, Mexico, 1998 –1999. Females
Age (years) 11–12 13–14 15–17 18–24 Socioeconomic index Low Middle High Residence Rural Suburban Urban School level Junior high school High school/university Academic achievementa High Medium Low Failing Cigarette smoking Never smokers Experimenters (few puffs taken anytime to ⬍1 cigarette/day) Regular smokers (ⱖ1 cigarette/day) Alcohol intoxicationb Never Occasional Frequent History of illegal drug use No Yes History of sexual activity No Yes Parental smoking Neither One parent Both parents Parental marijuana smoking (adolescent knowledge of) No Yes Parents’ marital status Parents are married or live together Divorced/separated Widowed Child is orphaned Acquaintances who use drugs No Yes, but they are not friends Yes, they are friends Depression, Zung scale No Yes
Males
Total
n
(%)
n
(%)
n
(%)
7468
56.2
5825
43.8
13,293
100
1957 3374 1430 707
26.2 45.2 19.1 9.5
1694 2748 811 572
29.1 47.2 13.9 9.8
3651 6122 2241 1279
27.5 46.0 16.9 9.6
2218 3399 1851
29.7 45.5 24.8
1114 3440 1271
19.1 59.1 21.8
3332 6839 3122
25.1 51.4 23.5
2863 1959 2646
38.4 26.2 35.4
2406 1301 2118
41.3 22.3 36.4
5269 3260 4764
39.7 24.5 35.8
5506 1962
73.7 26.3
4591 1234
78.8 21.1
10097 3196
76.0 24.0
2443 3642 1278 105
32.7 48.8 17.1 1.4
1215 2874 1537 199
20.9 49.3 26.4 3.4
3658 6516 2815 304
27.5 49.0 21.2 2.3
5899 1114
79.0 14.9
3474 1590
59.6 27.3
9373 2704
70.5 20.3
455
6.1
761
13.1
1216
9.2
5120 2266 82
68.6 30.3 1.1
3492 2091 242
60.0 36.0 4.0
8612 4357 324
64.8 32.8 2.4
7221 247
96.7 3.3
5298 527
90.9 9.1
12519 774
94.2 5.8
6790 678
90.9 9.1
4572 1253
78.5 21.5
11362 1931
85.5 14.5
7084 326 58
94.8 4.4 0.8
4600 1084 141
79.0 18.6 2.4
11684 1410 199
87.9 10.6 1.5
7437 31
98.6 0.4
5789 36
99.4 0.6
13226 67
99.5 0.5
6616 494 212 146
88.6 6.6 2.8 2.0
5400 230 118 77
92.7 4.0 2.0 1.3
12016 724 330 223
90.4 5.4 2.5 1.7
7054 143 271
94.4 1.9 3.6
5134 188 503
88.1 3.2 8.6
12118 331 774
91.7 2.5 5.8
6600 868
88.4 11.6
5601 224
96.2 3.8
12,201 1092
91.8 8.2
Scale of 1 to 10, with 10 highest, and ⱕ6 failing. Never⫽may consume alcohol but not to point of intoxication; occasional intoxication⫽intoxication to extent of having difficulty walking or standing from two to three times a month to one to five times a year; frequent intoxication⫽intoxication to extent of having difficulty walking or standing from once or twice a week to every day.
a
b
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municipality.23 The multilevel modeling approach used dichotomized smoking level (smokes daily, yes or no) as the dependent variable, and adjusted for the variables associated with cigarette smoking in adolescents. The two multilevel models were designed for data grouped in hierarchic levels, and allowed evaluation of changes in the dependent variable— cigarette smoking in adolescents—attributable to individual circumstances or contextual effects such as the respondent’s school and municipality. The STATA statistical package, release 6.0 (Stata Corp, College Station TX, 1999) was used for all analyses.
Results Sociodemographic Characteristics Of the total study sample—13,293 adolescents and young adults—56.2% were female. A total of 39.7% lived in rural areas, 24.5% in suburbs, and 35.8% in urban areas. Slightly less than half (48.8%) of respondents were aged 11 to 14. The prevalence of regular smoking was 13.1% (95% CI⫽12.2–13.9) in males, compared to 6.1% (95% CI⫽5.6 – 6.6) in females, with a male:female ratio of 2:1. The prevalence of experimenters was 27.3% (95% CI⫽26.1–28.4) in males, and 14.9% in females (95% CI⫽14.1–15.7) (Table 1). The prevalence of regular smoking increased with age in both genders (Figure 1). The prevalence of regular smoking among males was 14.2% in junior high school and 32.4% in high school/college. Prevalence of regular smoking among young women was 5.2% in junior high and 13.1% in high school/college (Table 4).
Cigarette Smoking Risk Factors Experimenters. For the study population as a whole, male gender was associated with experimenting with cigarette smoking (OR⫽2.3, 95% CI⫽2.1–2.5). Age was also associated with experimenting, with the highest prevalence among males aged 15 to 17 (31.4%). When considering both genders, the 15- to 17-year-olds were 1.9 times more likely to be experimenters as compared to students aged ⬍13 (95% CI⫽1.6 –2.5). Various unhealthy lifestyle behaviors were also strongly associated with experimenting with cigarette smoking, including frequent severe alcohol intoxication (OR⫽2.5, 95% CI⫽2.0 –3.1). Adolescent knowledge of parents’ marijuana consumption was also associated with the adolescent being an experimenter with cigarettes (OR⫽2.2, 95% CI⫽1.2– 4.1). Regular smokers. Factors associated with regular cigarette smoking were similar to those found in experimenters. The strongest association was found between cigarette smoking and a history of frequent severe alcohol intoxication (OR⫽35.5, 95% CI⫽25.0 –50.3). Regular smoking was also associated with using illegal drugs at least once in lifetime (OR⫽3.2, 95% CI⫽2.5– 44
Figure 1. Prevalence of current smoking among public school students (n ⫽13,293), Morelos State, Mexico, 1998 – 1999.
4.1); cigarette smoking by both parents (OR⫽2.0, 95% CI⫽1.3–3.1); and adolescent knowledge of parent(s) use of marijuana (OR⫽3.4, 95% CI⫽1.6 –7.2). In addition, there was a strong association between regular smoking and having peers who consumed illegal drugs, especially if those peers were friends (OR⫽2.9, 95% CI⫽2.3–3.7). Finally, depression was also associated with regular smoking (OR⫽1.7, 95% CI⫽1.4 –2.2) (Table 2). Comparing regular smokers and experimenters. Factors consistently associated with regular smoking, as compared with experimenters, were higher socioeconomic status, living in an urban area (as compared to rural), low academic achievement, and especially, frequent severe alcohol intoxication (OR⫽7.0, 95% CI⫽5.1–9.7). Other factors strongly associated with regular smoking, as compared to experimenting with
American Journal of Preventive Medicine, Volume 28, Number 1
Table 2. Adjusted ORs for cigarette smoking among 13,293 students in Morelos, Mexico, 1998 –1999 Experimenters (few puffs taken anytime to <1 cigarette/day) Males % Gender Females Males Age (years)a 11–12 13–14 15–17 18–24 School levelb Junior high school High school/university Socioeconomic index Low Middle High Residence Rural Suburban Urban Academic achievementc High Medium Low Failing Alcohol intoxicationd Never Occasional Frequent History of illegal drug use No Yes History of sexual activity No Yes Parental smoking Neither One parent Both parents Parents’ marital status Parents are married or live together Divorced/separated Widowed Child is orphaned Parental marijuana smoking (adolescent knowledge of) No Yes Acquaintances who use drugs No Yes, but they are not friends Yes, they are friends Depression, Zung scale No Yes
Regular smokers (>1 cigarette/day)
Females %
OR (95% CI)
Males %
14.9
1.0 2.3 (2.1–2.5)
13.1
27.3
Females %
OR (95% CI)
6.1
1.0 2.3 (2.0–2.7)
23.4 28.6 31.4 26.6
10.7 14.5 19.8 18.5
1.0 1.3 (1.2–1.5) 1.9 (1.6–2.5) 1.9 (1.6–2.2)
11.7 9.6 17.5 27.3
5.1 4.2 7.0 16.1
1.0 0.8 (0.7–1.0) 1.8 (1.5–2.1) 3.7 (3.0–4.4)
27.0 28.4
13.3 19.3
1.0 1.0 (0.9–1.1)
10.3 23.2
4.5 10.6
1.0 2.3 (1.4–3.8)
28.8 28.6 22.3
12.4 15.1 17.6
1.0 1.1 (1.0–1.3) 0.9 (0.8–1.0)
11.2 9.5 24.3
3.5 4.3 12.6
1.0 1.0 (0.8–1.2) 1.6 (1.3–1.9)
28.5 28.5 25.1
12.6 16.2 16.4
1.0 1.0 (0.9–1.1) 0.9 (0.8–1.0)
7.2 11.0 21.1
2.6 4.0 11.5
1.0 1.2 (1.0–1.5) 1.8 (1.5–2.2)
19.6 29.0 29.9 30.7
11.0 15.5 19.6 30.5
1.0 1.7 (1.5–1.9) 1.9 (1.6–2.2) 2.8 (2.1–3.7)
7.3 13.0 16.6 21.6
4.2 6.4 8.2 12.4
1.0 1.9 (1.5–2.3) 2.2 (1.8–2.7) 4.2 (2.8–6.3)
21.2 37.2 30.2
8.0 30.2 24.4
1.0 4.2 (3.8–4.7) 5.0 (3.6–7.0)
2.9 25.6 50.4
1.2 15.8 43.9
1.0 14.4 (12.0–17.3) 35.5 (25.0–50.3)
26.4 36.6
14.2 37.2
1.0 2.5 (2.0–3.1)
10.1 43.1
5.3 29.2
1.0 3.2 (2.5–4.1)
26.6 30.0
13.8 26.1
1.0 1.3 (1.1–1.5)
7.0 35.1
4.5 22.3
1.0 2.8 (2.4–3.3)
26.8 29.8 22.7
14.7 19.6 17.3
1.0 1.2 (1.0–1.4) 0.8 (0.6–1.2)
11.4 18.7 27.0
5.3 16.6 31.0
1.0 1.6 (1.3–1.9) 2.0 (1.3–3.1)
26.9 33.4 27.1 37.7
14.6 18.6 15.1 14.4
1.0 1.4 (1.1–1.7) 1.1 (0.8–1.4) 1.3 (0.9–1.8)
13.4 8.3 7.6 9.1
6.4 4.3 4.2 2.0
1.0 0.9 (0.3–1.3) 0.9 (0.5–1.5) 0.7 (0.4–1.5)
27.3 33.3
14.8 32.3
1.0 2.2 (1.2–4.1)
13.0 30.6
6.0 22.6
1.0 3.4 (1.6–7.2)
26.8 30.8 31.0
14.3 19.6 27.3
1.0 1.1 (0.8–1.5) 1.3 (1.1–1.7)
9.4 34.0 42.9
4.6 25.2 33.9
1.0 2.2 (1.6–3.1) 2.9 (2.3–3.7)
27.0 33.5
14.2 20.4
1.0 1.4 (1.2–1.7)
12.6 23.7
5.5 10.8
1.0 1.7 (1.4–2.2)
CI, confidence interval; OR, odds ratio. a ORs adjusted for all variables included in table, except school level. b ORs adjusted for all variables included in table, except age. c Scale of 1 to 10, with 10 highest, and ⱕ6 failing. d Never⫽may consume alcohol but not to point of intoxication; occasional intoxication⫽intoxication to extent of having difficulty walking or standing from two to three times a month up to one to five times a year; frequent intoxication⫽intoxication to extent of having difficulty walking or standing from once or twice a week to every day.
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Table 3. Adjusted ORs for experimenters versus regular smokers among students in Morelos, Mexico, 1998 –1999 Regular smokers (>1 cigarette/day) Total OR (95% CI) Gender Females Males Age (years)a 11–12 13–14 15–17 18–24 School levelb Junior high school High school/university Socioeconomic index Low Middle High Residence Rural Suburban Urban Academic achievementc High Medium Low Failing Alcohol intoxicationd Never Occasional Frequent History of illegal drug use No Yes History of sexual activity No Yes Parental smoking Neither One parent Both parents Parents’ marital status Parents married or living together Divorced Widowed Child is orphaned Parental marijuana smoking (adolescent knowledge of) No Yes Acquaintances who use drugs No Yes, but they are not friends Yes, they are friends Depression, Zung scale No Yes
Females OR (95% CI)
Males OR (95% CI)
1.0 0.6 (0.5–0.7) 0.8 (0.7–1.0) 1.4 (1.1–1.7)
1.0 0.6 (0.4–0.8) 0.7 (0.5–0.9) 1.4 (0.9–2.0)
1.0 0.6 (0.5–0.8) 1.0 (0.7–1.4) 1.3 (1.0–1.8)
1.0 1.5 (1.3–1.7)
1.00 1.4 (1.1–1.7)
1.00 1.6 (1.3–2.0)
1.0 0.9 (0.7–1.1) 1.9 (1.5–2.3)
1.00 0.9 (0.7–1.3) 2.0 (1.4–2.7)
1.00 0.9 (0.7–1.1) 1.8 (1.3–2.4)
1.0 1.2 (1.0–1.5) 2.2 (1.8–2.7)
1.00 1.1 (0.8–1.7) 2.6 (1.9–3.6)
1.00 1.3 (1.0–1.8) 2.0 (1.6–2.5)
1.0 1.1 (0.9–1.4) 1.2 (0.9–1.5) 1.6 (1.0–2.3)
1.00 1.1 (0.8–1.4) 1.1 (0.8–1.5) 1.0 (0.5–2.1)
1.00 1.2 (0.9–1.6) 1.2 (0.9–1.7) 1.9 (1.1–3.2)
1.0 3.5 (2.9–4.3) 7.0 (5.1–9.7)
1.00 3.0 (2.2–4.0) 8.7 (4.6–16.5)
1.00 4.0 (3.1–5.0) 7.0 (4.7–10.2)
1.0 1.3 (1.0–1.6)
1.00 1.1 (0.7–1.6)
1.00 1.4 (1.1–1.9)
1.0 2.2 (1.8–2.5)
1.00 1.8 (1.3–2.3)
1.00 2.5 (2.0–3.1)
1.0 1.3 (1.1–1.6) 2.3 (1.5–3.5)
1.00 1.4 (0.9–2.2) 3.0 (1.3–7.0)
1.00 1.3 (1.0–1.6) 2.0 (1.2–3.4)
1.0 0.6 (0.4–0.9) 0.7 (0.4–1.3) 0.5 (0.2–1.1)
1.00 0.6 (0.3–1.0) 0.6 (0.3–1.4) 0.5 (0.1–1.6)
1.00 0.7 (0.4–1.2) 1.0 (0.4–2.1) 0.6 (0.2–1.4)
1.0 1.6 (0.8–3.1)
1.0 1.4 (0.5–4.0)
1.0 1.7 (0.7–4.2)
1.0 2.1 (1.5–2.8) 2.2 (1.8–2.8)
1.0 2.7 (1.5–4.6) 2.5 (1.7–3.7)
1.0 1.7 (1.2–2.5) 2.0 (1.5–2.7)
1.0 1.3 (1.0–1.6)
1.0 1.4 (1.0–1.9)
1.0 1.1 (0.8–1.7)
1.0 1.2 (1.0–1.4)
CI, confidence interval; OR, odds ratio. a Odds ratios adjusted for all variables included in table, except school level. b ORs adjusted for all variables included in table, except age. c Scale of 1 to 10, with 10 highest, and ⱕ6 failing. d Never⫽may consume alcohol but not to point of intoxication; occasional intoxication⫽intoxication to extent of having difficulty walking or standing from two to three times a month up to one to five times a year; frequent intoxication⫽intoxication to the point of having difficulty walking or standing from once or twice a week to every day.
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American Journal of Preventive Medicine, Volume 28, Number 1
Table 4. Adjusted ORs for regular tobacco consumption (ⱖ1 cigarette/day) among students in Morelos, Mexico, by school level, 1998 –1999 Junior high school %
OR (95% CI)
High school/university %
OR (95% CI)
a
Gender Female Male Socioeconomic indexa Low Middle High Residencea Rural Suburban Urban Academic achievementa,b High grades Medium grades Low grades Failing grades Alcohol intoxicationa Neverc Occasional Frequent History of illegal drug usea No Yes History of sexual activitya No Yes Parental smokinga Neither One parents Both parents Parents’ marital statusa Parents married or live together Divorced Widowed Child is orphaned Parental marijuana smoking (adolescent knowledge of) No Yes Acquaintances who use drugs No Yes, but they are not friends Yes, they are friends Depression, Zung scale No Yes
5.2 14.2
1.0 2.0 (1.6–2.4)
13.1 32.4
1.0 2.2 (1.7–2.9)
6.1 6.8 18.3
1.0 0.8 (0.6–1.1) 1.5 (1.1–1.9)
13.8 16.6 27.5
1.0 1.2 (0.8–1.7) 1.4 (1.0–2.0)
4.7 6.7 16.8
1.0 1.1 (0.8–1.4) 1.8 (1.4–2.3)
14.1 13.8 25.4
1.0 1.0 (0.7–1.4) 1.4 (1.0–2.0)
4.8 9.3 13.1 22.4
1.0 1.9 (1.5–2.5) 2.2 (1.6–2.9) 3.7 (2.1–6.5)
10.4 20.9 29.1 37.3
1.0 1.9 (1.4–2.7) 2.3 (1.6–3.3) 4.1 (2.0–8.2)
1.7 29.7 65.4
1.0 17.2 (13.7–21.6) 39.0 (25.4–60.0)
4.6 32.7 74.7
1.0 7.7 (5.7–10.5) 24.2 (12.8–45.8)
7.0 58.9
1.0 3.2 (2.3–4.5)
16.1 64.5
1.0 2.6 (1.8–3.7)
5.2 42.5
1.0 3.2 (2.6–4.0)
12.9 43.4
1.0 2.2 (1.7–2.9)
7.4 20.0 30.9
1.0 1.5 (1.1–1.9) 1.6 (1.0–2.7)
17.0 39.2 52.9
1.0 1.7 (1.2–2.3) 3.1 (1.3–7.2)
9.3 5.3 4.5 5.4
1.0 1.0 (0.6–1.6) 1.0 (0.5–2.0) 1.0 (0.4–2.2)
20.5 15.5 13.8 7.7
1.0 1.0 (0.5–1.9) 1.1 (0.5–2.5) 0.6 (0.1–3.1)
8.8 39.3
1.0 5.5 (1.7–17.4)
19.8 41.2
1.0 1.5 (0.4–2.3)
6.2 37.1 56.6
1.0 2.9 (1.9–4.3) 3.5 (2.6–4.8)
15.5 48.7 56.6
1.0 1.9 (1.1–3.2) 2.5 (1.9–3.6)
8.5 14.2
1.0 1.8 (1.3–2.5)
19.4 25.2
1.0 1.5 (1.0–2.2)
a
ORs adjusted for all variables included in the table. Scale of 1 to 10, with 10 highest, and ⱕ6 a failing grade. Never⫽may consume alcohol but not to point of intoxication; occasional intoxication⫽intoxication to extent of having difficulty walking or standing from two to three times a month up to one to five times a year; frequent intoxication⫽intoxication to the point of having difficulty walking or standing from once or twice a week to every day.
b c
cigarettes, were both parents being smokers and having friends who use illegal drugs (Table 3).
Risk Factors Associated with Cigarette Smoking by Education Level The association between cigarette smoking was twice as great among high school and college students as compared to junior high school students (Table 4). Factors
associated with cigarette smoking when stratified by education level were male gender, higher socioeconomic status, living in an urban area, and a history of low academic achievement. As was true when stratifying by gender or comparing levels of use (experimenters vs regular smokers), a strong association was found between cigarette smoking and frequent, severe intoxication with alcohol, both for junior high school students Am J Prev Med 2005;28(1)
47
80 70 60 50 40 30 20 10 0
High Middle Low Never Every 2 weeks to once a year
>Every 2 weeks
c
%
Prevalence of regular smokers
Male students
So ci oe st co at no us m i
Prevalence of regular smokers
Female students % 80 70 60 50 40 30 20 10 0
Never
Every 2 weeks >Every to once a year 2 weeks
High ic Middle om n o Low ec us i o t at c s So
Frequency of alcohol consumption
Frequency of alcohol consumption
Figure 2. Prevalence of smoking and immoderate alcohol consumption by socioeconomic status among female public school students (n ⫽7468) in Morelos State, Mexico, 1998 –1999.
(OR⫽39.0, 95% CI⫽25.4 – 60.0) and high school and college students (OR⫽24.2, 95% CI⫽12.8 – 45.8). Other associations were depression, friends who use illegal drugs, and knowledge of parent(s) use of marijuana (OR⫽5.5, 95% CI⫽1.7–17.4).
Interactions Among Excessive Alcohol Consumption, Illegal Drug Use, and Socioeconomic Level, as Function of Cigarette Smoking For males in the study sample, the highest prevalence of smoking (85.3%) was found to be among those who have a history of regular severe alcohol intoxication as well as illegal drug use. Very high prevalence of cigarette smoking was also found in students of the highest socioeconomic status who also frequently became severely intoxicated with alcohol: 75.8% for females and 76.7% for males (Figure 2). The multivariate logistic regression model demonstrated an interaction between severe alcohol intoxication and socioeconomic status in terms of an increased likelihood of cigarette smoking.
Differences in Daily Smoking Related to Contextual Factors The multilevel models, which focused on the school attended and the municipality the students lived in, compared nonsmokers with smokers in a sample of 10,589 students (Table 5). The model focusing on geographic area of residence showed that 17% of the variance in smoking can be attributed to the municipality that the student lives in. The model focusing on the school attended shows that 14% of variance in smoking is attributable to the school context. The remaining variance is due to individual factors. Thus, although the detailed nature of the relationship between contextual factors—school the student attends 48
or municipality where the student lives—remains unclear, this analysis does indicate that daily smoking is conditioned by school-level and residence-level characteristics. That is, in addition to individual characteristics, context—school attended or municipality of residence—is also a predictor of some of the likelihood of smoking daily.
Discussion Previous studies have suggested interactions among health-risk behaviors, particularly links between tobacco and alcohol use. In this respect, the primary factors associated with smoking in this study among Mexican young people were frequent alcohol intoxication and illegal drug use. Having initiated sexual activity and low academic achievement also appeared as correlates of smoking. In addition, parental cigarette and marijuana smoking, and peer use of illegal drugs were associated with adolescent cigarette smoking. While there was a very strong association between regular smoking and frequent alcohol intoxication in both genders, there were also significant interactions among risk of smoking, higher socioeconomic status, and frequent severe alcohol intoxication. Most of the variability in cigarette smoking by students was explained by individual factors, but the multilevel models showed that significant variance could be attributed to place of residence (municipality) or specific school. Other studies have shown an association between alcohol and cigarette smoking in young people.24 One study specifically indicated that adolescents who smoke cigarettes are more likely to abuse alcohol.25 Previous reports have indicated that alcohol consumption is directly associated with the number of cigarettes smoked by young people, while the smoking habit is not related to immoderate alcohol consumption among young adults.26 In addition, some studies indi-
American Journal of Preventive Medicine, Volume 28, Number 1
Table 5. Multilevel modeling results for associations between regular smoking (ⱖ1 cigarette/day) and individual, school, and geographic factors in students (n ⫽ 10,589) in Morelos, Mexico, 1998 –1999a Model I (33 municipalities) regression coeficients
Model II (112 schools) regression coefficients
Fixed effects

SE
p

SE
p
Intercept Municipality School Gender Females Males Age (years) 11–12 13–14 15–17 18–24 Academic achievement High Medium Low Failing Alcohol intoxication Never Occasional Frequent History of illegal drug use No Yes Depression, Zung scale No Yes History of sexual activity No Yes Residence Rural Suburban Urban Random effects 2 u2
1.118 0.003
0.361 0.004
0.002 0.415
0.156
0.397
0.695
0.005
0.001
0.000
a
0.524
0.083
0.000
0.522
0.083
0.000
0.020 0.202 0.132
0.121 0.115 0.129
0.868 0.080 0.308
0.065 0.000 0.250
0.121 0.120 0.130
0.594 1.00 0.054
1.513 0.855 0.693
0.226 0.215 0.221
0.000 0.000 0.002
1.506 0.833 0.679
0.226 0.215 0.220
0.000 0.000 0.002
3.235 0.838
0.187 0.170
0.000 0.000
3.091 0.837
0.189 0.171
0.000 0.000
1.385
0.123
0.000
1.398
0.123
0.000
0.531
0.128
0.000
0.557
0.128
0.000
1.030
0.087
0.000
0.943
0.088
0.000
0.492 0.398
0.111 0.109
0.000 0.000
0.280 0.233
0.114 0.111
0.015 0.036
0.0923 0.1779
0.0685 0.1417
Dependent variable: smoker daily (yes/no).
cate that tobacco and alcohol use are converging in young men and women.27 According to an international survey on cigarette smoking among young people, the proportion of smokers is significantly higher among young men than young women.28 This is consistent with our findings in Morelos State, where the ratio was two male smokers for every female smoker. Other studies have found that an important correlate for smoking among young women is smoking by family members.29 This is similar to associations observed in the present study, which shows a 70% increase in the risk of smoking among young women when one parent smoked, and 3.1 times higher when both parents smoked. Some behaviors associated with cigarette smoking are adopted during adolescence. In this respect, a study in Spain reported that for both genders, those who drink
alcohol, have had sexual relations, have tried illegal drugs, and have more money are those who smoke more.30 These results could be related to these findings, since for young women in Morelos State, the highest prevalence of smoking (75.8%) was found to be among those who report frequent and severe alcohol intoxication and who have the highest socioeconomic status. Persistence of the smoking habit has been associated with a long period of drug dependence or abuse, and also with having friends who smoke.31 In the current study, the highest prevalence of smoking (85.3%) among young men was found among those with a history of regular severe alcohol intoxication and illegal drug use. The prevalence of illegal drug use overall was greater among those who use alcohol and tobacco.32 A number of surveys conducted in school settings, in both developed and developing countries with varying Am J Prev Med 2005;28(1)
49
political, social, economic, and cultural characteristics, report similar risk factors for smoking as those found in this study, such as low academic achievement,33 parents who smoke, or the influence of friends and close peers34 (although in the current study, only the influence of peer use of illegal drugs was studied, and not peer cigarette smoking). However, unlike reports in other countries, there was a dose–response gradient between smoking and high socioeconomic status in young women. A number of reports in the literature have established poor school success as a risk factor for criminal activities, including substance abuse.35 Low academic achievement reflects a limited perception of future opportunities, and the use of illegal substances seems to emerge as a response to frustration, one of the results of low academic achievement.36 There is substantial empirical evidence for an association between academic difficulties and drug abuse, even if temporary.37 Moreover, some evidence suggests that addictions at an early age can contribute to low academic achievement and dropping out of school.38 The multilevel analysis showed that in this study sample, smoking differed by school and also by the specific municipality the students lived in. The effect of the school on smoking was also found in studies in the United States, Spain, and a multicenter study in Estonia, Finland, and Russia.39 – 41 Specifically, in the Spanish study, whether the school enforced antismoking rules was the main factor predicting smoking prevalence.40 These findings and our own indicate the importance of nonsmoking policies in schools and in the community at large.
Study Limitations Several limitations of this study should be mentioned. First, because it was based on a cross-sectional survey, inferences about causality are not possible. With regard to possible bias in the classification of smokers, because results were based on self-reports, quantity and frequency could have been underestimated, although previous similar studies have demonstrated that any misclassification is minimal and the level of association and dose–response gradient in ordinal variables observed in this study have been consistently documented in other studies.42– 44 The confidentiality of responses in this study was guaranteed, and smoking was not the central topic in the questionnaire, which worked against under-reporting bias. Regarding misclassification of smokers and nonsmokers, this type of error would be randomly distributed among smokers and nonsmokers.43 In addition, the study population included only students from public schools, and thus is not representative of young people in private schools or not enrolled in school. Therefore, findings are not representative of Mexican youth in general. (In 2000, 78.6% of 13- to 15-year-olds, 50
What This Study Adds . . . Initiation of cigarette smoking occurs largely during adolescence, and is associated with abuse of alcohol and parental smoking. This study of Mexican public school students found a very strong association between regular smoking and frequent, severe alcohol intoxication, and a lesser association with parental smoking. Contextual factors explained a significant part of the variance in smoking; multilevel analysis showed that 17% of variance was attributed to the municipality of residence and 14% to school context.
42.8% of 16- to 19-year-olds, and 16.7% of 20- to 24-yearolds attended school in Morelos State.45,46)
Conclusions In many developing countries, including Mexico, cigarette smoking is on the rise among adolescents and young adults.47 Joint consumption of tobacco and alcohol among young people of high socioeconomic status and low academic achievement who use illegal drugs is apparent from these data. Therefore, initiatives discouraging cigarette smoking should be designed in an integrated way so that they include these factors. The implementation of interventions in school settings should vary according to risk patterns related to academic achievement and socioeconomic status as well. Smoking prevention programs for Mexican young people in schools should include strategies such as strengthening the ability of schools to stay smoke-free, educating parents and teachers about the importance of preventing cigarette smoking in youth, smoking bans in the broader community, and especially school-based programs that take into account multiple risk factors for cigarette smoking, including alcohol use, drug use, peer influence, and parental influence. This project was carried out with financial support from the Bristol Myers-Squibb Foundation of New York, as part of “Better Health for Women: A Global Health Program.” In addition, Mexico’s National Council of Science and Technology and National Institute of Public Health, and the Catalan Institute of Oncology in Barcelona, Spain partially financed the data analysis. The Departments of Public Education and Health in Morelos State, Mexico, provided all necessary operational assistance for data collection. No financial conflict of interest was reported by the authors of this paper.
American Journal of Preventive Medicine, Volume 28, Number 1
References 1. Global Youth Tobacco Survey Collaborative Group. Tobacco use among youth: a cross country comparison. Tob Control 2002;11:252–70. 2. Secretaría de Salud. Encuesta Nacional de Adicciones 2002. Tabaco, alcohol y otras drogas. Resumen ejecutivo. Mexico City: Secretaría de Salud, 2002. 3. Holmen T, Barrett E, Holmen J, et al. Health problems in teenage daily smokers versus nonsmokers, Norway, 1995–1997. Am J Epidemiol 2000;151:148 –55. 4. Fernandez E, Schiaffino A, Rajmil L, et al. Re: “Health problems in teenage daily smokers versus nonsmokers, Norway, 1995–1997: the Nord-Trondelag Health Study”. Am J Epidemiol 2000;152:395– 6 (letter). 5. Aarnio M, Kujala UM, Kaprio J. Associations of health-related behaviors, school type and health status to physical activity patterns in 16 year old boys and girls. Scand J Soc Med 1997;25:156 – 67. 6. Patton GC, Hibbert M, Rosier MJ, et al. Is smoking associated with depression and anxiety in teenagers? Am J Public Health 1996;86:225–30. 7. Wickrama K, Conger R, Wallace L, et al. The intergenerational transmission of health-risk behaviors: adolescent lifestyles and gender moderating effects. J Health Social Behav 1999;40:258 –72. 8. Perry CH. The Tobacco industry and underage youth smoking. tobacco industry documents from the Minnesota litigation. Arch Pediatr Adolesc Med 1999;153:935– 41. 9. Anda R, Croft J, Felitti V, et al. Adverse childhood experiences and smoking during adolescence and adulthood. JAMA 1999;282:1656 – 8. 10. Bien TH, Burge R. Smoking and drinking: a review of the literature. Int J Addict 1990;25:1429 –54. 11. Zacny JB. Behavior aspects of alcohol–tobacco interactions. Recent Dev Alcohol 1990;8:205–19. 12. Collins AC. Genetic influences on tobacco use: a review of human and animal studies. Int J Addict 1991;25:35–55. 13. Swan GE, Carmelli D, Rosenman RH, et al. Smoking and alcohol consumption in adult male twins: genetic heritability and shared environmental influences. J Substance Abuse 1990;2:39 –50. 14. Best D, Rawaf S, Rowley J, et al. Drinking and smoking as concurrent predictors of illicit drug use and positive drug attitudes in adolescents. Drug Alcohol Depend 2000;60:319 –21. 15. Flay BR, Hu FB, Richardson J. Psychosocial predictors of different stages of cigarette smoking among high school students. Prev Med 1998;27:A9 –A18. 16. Melby JN, Conger RD, Conger KJ, et al. Effects of parental behavior on tobacco use by young male adolescents. J Marriage Fam 1993;55:439 –54. 17. O’Malley PM, Johnston LD, Bachman JG. Alcohol use among adolescents. Alcohol Health Res World 1998;22:85–93. 18. Lazcano-Ponce E, Hernandez B, Cruz-Valdez A, et al. Chronic disease risk factors among healthy adolescents attending public schools in the state of Morelos, Mexico. Arch Med Res 2003;34:222–36. 19. Herrera-Vazquez M, Wagner F, Velazco Mondragón E, Borges G, LazcanoPonce E. Onset of alcohol and tobacco use and transition to other drug use among students from Morelos, Mexico. Salud Publica Mex 2004;46: 132– 40. (in Spanish) 20. Amos A. Women and smoking. Br Med Bull 1996;52:74 – 89. 21. Waldron I. Patterns and causes of gender differences in smoking. Soc Sci Med 1991;32:989 –1005. 22. Kleinbaum D. Una introducción al análisis de regresión logística. Revisiones Salud Pública 1993;3:61–105. 23. Bingenheimer JB, Raudenbush SW. Statistical and substantive inferences in public health: issues in the application of multilevel models. Annu Rev Public Health 2004;25:53–77. 24. Norton E, Lindrooth R, Ennett S. Controlling for the endogeneity of peer substance use on adolescent alcohol and tobacco use. Health Econ 1998;7:439 –53. 25. Frazier AL, Fisher L, Camargo CA, Tomeo C, Colditz G. Association of adolescent cigar use with other high-risk behaviors. Pediatrics 2000; 106:E26.
26. Leone O, Archilli E, Leone A, et al. Smoking habit and alcohol consumption in schoolboys. In: Slama K, ed. Tobacco and health. New York: Plenum Press, 1995: 589 –90. 27. Mendoza R, Batista JM, Sánchez M, et al. El consumo de tabaco, alcohol y otras drogas en los adolescentes escolarizados españoles. Gac Sanit 1998; 12:263–71. 28. Warren C, Riley L, Asma S, et al. El consumo de tabaco entre los jóvenes: informe de la vigilancia de la Encuesta Mundial Sobre Tabaco y los Jóvenes. Bull World Health Organ 2000;78:868 –76. 29. Robinson L, Klesges R, Zbikowski S. Gender and ethnic differences in young adolescents’ sources of cigarettes. Tob Control 1998;7:353–9. 30. Diez E, Barniol J, Nebot M, et al. Comportamientos relacionados con la salud en estudiantes de secundaria: relaciones sexuales y consumo de tabaco, alcohol y cannabis. Gac Sanit 1998;12:272– 80. 31. Lewinsohn PM, Brown RA, Seeley JR, et al. Psychosocial correlates of cigarette smoking abstinence, experimentation, persistence and frequency during adolescence. Nicotine Tob Res 2000;2:121–31. 32. Chen KT, Chen CJ, Fagot-Campagna A, Narayan KM. Tobacco, betel quid, alcohol, and illicit drug use among 13- to 35-year-olds in I-Lan, rural Taiwan: prevalence and risk factors. Am J Public Health 2001;91:1130 – 4. 33. Escobedo LG, Marcus S, Holtzman D, et al. Sports participation, age at smoking initiation, and the risk of smoking among U.S. high school students. JAMA 1993;269:1391–5. 34. Zhu BP, Liu M, Shelton D, et al. Cigarette smoking and its risk fact among elementary school students in Beijing. Am J Public Health 1996;86:368 –75. 35. Hirschi T. Causes of delinquency. Berkeley: University of California Press, 1969. 36. Hu T, Lin Z, Keeler TE. Teenage smoking, attempts to quit, and school performance. Am J Public Health 1988;88:940 –3. 37. Leiber M, Farnsworth M. Strain theory revised: economic goals, educational means, and delinquency. Am Sociological Rev 1989;54:263–74. 38. Schulemberg J, Bachman J, O’Malley P, et al. High school educational success and subsequent substance use: a panel analysis following adolescents into young adulthood. J Health Social Behav 1994;35:45– 62. 39. Novak SP, Clayton RR. The influence of school environment and selfregulation on transitions between stages of cigarette smoking: a multilevel analysis. Health Psychology 2001;20:196 –207. 40. Pinilla J, Gonzalez B, Barber P, Santana Y. Smoking in young adolescents: an approach with multilevel discrete choice models. J Epidemiol Community Health 2002;56:227–32. 41. Parna K, Rahu K, Fischer K, et al. Smoking and associated factors among adolescents in Tallinn, Helsinki and Moscow: a multilevel analysis. Scand J Public Health 2003;31:350 – 8. 42. Dolcini MM, Adler NE, Ginsberg D. Factors influencing agreement between self-reports and biological measures of smoking among adolescents. J Res Adolesc 1996;6:515– 42. 43. Wells J, English P, Posner S, et al. Misclassification rates for current smokers misclassified as nonsmokers. Am J Public Health 1998;88:1503–9. 44. Patrick DL, Cheadle A, Thompson DC, et al. The validity of self-reported smoking: a review and meta analysis. Am J Public Health. 1994;84:1086 –93. 45. Instituto Nacional de Estadística Geografía e Informática. XII Censo General de Población y Vivienda, 2000. Tabulados básicos. Aguascalientes, Ags., 2001. Porcentaje de la población de 5 a 15 años que asiste a la escuela por entidad federativa según grupos de edad y sexo, 2000. Available at: www.inegi.gob.mx/est/contenidos/espanol/tematicos/mediano/ent.asp? t⫽medu06&c⫽3273. Accessed July, 2004. 46. Instituto Nacional de Estadística Geografía e Informática. XII Censo General de Población y Vivienda, 2000. Tabulados básicos. Aguascalientes, Ags., 2001. Porcentaje de la población de 16 a 24 años que asiste a la escuela por entidad federativa según grupos de edad y sexo, 2000. Available at: http://www.inegi.gob.mx/est/contenidos/espanol/tematicos/mediano/ent. asp?t⫽medu07&c⫽3274. 47. Arillo-Santillán E, Fernández E, Hernández-Avila M, et al. Prevalencia de tabaquismo y bajo desempeño escolar, en estudiantes de 11 a 24 años de edad del estado de Morelos, México. Salud Publica Mex 2002;44:S54 –S66.
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