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American Journal of Epidemiology Advance Access published online on February 23, 2007
American Journal of Epidemiology, doi:10.1093/aje/kwm010
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American Journal of Epidemiology Copyright © 2007 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.

Original Contribution

Urine Nicotine Metabolites and Smoking Behavior in a Multiracial/Multiethnic National Sample of Young Adults

Denise B. Kandel1,2,3, Mei-Chen Hu1, Christine Schaffran3, J. Richard Udry4,5 and Neal L. Benowitz6,7,8

1 Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY
2 Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY
3 New York State Psychiatric Institute, New York, NY
4 Department of Sociology, College of Arts and Sciences, University of North Carolina, Chapel Hill, NC
5 Department of Maternal and Child Health, School of Public Health, University of North Carolina, Chapel Hill, NC
6 Department of Medicine, School of Medicine, University of California San Francisco, San Francisco, CA
7 Department of Psychiatry, School of Medicine, University of California San Francisco, San Francisco, CA
8 Department of Biopharmaceutical Sciences, School of Pharmacy, University of California San Francisco, San Francisco, CA

Correspondence to Dr. Denise B. Kandel, Columbia University, 1051 Riverside Drive, Unit 20, New York, NY 10032 (e-mail: dbk2{at}columbia.edu).

Received for publication June 15, 2006. Accepted for publication October 2, 2006.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Nicotine metabolism has been hypothesized to affect patterns of smoking. The recent development of a noninvasive measure of nicotine metabolism, the nicotine metabolite ratio (trans-3'-hydroxycotinine/cotinine), makes it possible to examine the association between rate of nicotine metabolism and smoking behavior in the general population. This US study examined group differences in the ratio measured in urine and the association between the ratio and multiple measures of smoking behavior and nicotine dependence in a large, national representative sample of young adults. The sample included 900 daily smokers aged 18–26 years from wave III (2001–2002) of the National Longitudinal Survey of Adolescent Health. Nicotine dependence was measured by using the Fagerström Test for Nicotine Dependence. Females had higher nicotine metabolite ratios than males; Whites and Hispanics had higher nicotine metabolite ratios than African Americans or Asians. This finding is consistent with those from laboratory studies of older smokers based on intravenous infusion of nicotine. No significant association was found between the nicotine metabolite ratio and number of cigarettes smoked per day or nicotine dependence. The availability of a noninvasive measure makes possible systematic testing of causal hypotheses generated by laboratory studies in the general population.

adolescent; metabolism; nicotine; smoking; tobacco use disorder; urine

Abbreviations: Add Health, National Longitudinal Survey of Adolescent Health; COT, cotinine; CPD, number of cigarettes smoked per day; FTND, Fagerström Test for Nicotine Dependence; 3HC, trans-3'-hydroxycotinine


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Nicotine is the primary psychoactive component of tobacco. Nicotine is metabolized primarily to cotinine (COT), which is itself metabolized to trans-3'-hydroxycotinine (3HC) (1). The rate of nicotine metabolism has been hypothesized to affect smoking patterns, including extensiveness of smoking, progression of smoking, persistence of smoking, and nicotine dependence (2–4). Persons who metabolize nicotine rapidly may need to smoke more extensively to achieve the same level of nicotine in the body as those who metabolize nicotine slowly (5). The liver enzyme cytochrome P-450 CYP2A6 is primarily responsible for the metabolism of nicotine to COT and appears to be exclusively or nearly exclusively responsible for the metabolism of COT to 3HC (6–9).

To date, the associations between nicotine metabolism and smoking behavior have been ascertained from CYP2A6 genetic polymorphisms associated with variation in nicotine metabolism activity. Results are inconsistent. Some studies show that adult and adolescent smokers with CYP2A6 gene variants associated with very slow nicotine metabolism smoke fewer cigarettes per day than smokers with normal or intermediate rates of metabolism, whereas those with a very fast metabolism smoke more cigarettes (2–4, 10–13). Other studies have failed to find these associations (e.g., 14–17). Patterns regarding dependence appear to differ among adolescent and adult smokers. Among adults, slow metabolism is associated with decreased rates of dependence (4, 10, 18–20). However, one study suggests that adolescents with a slow metabolism are more likely to progress to dependence (13). A recent study found that adolescents with the slowest CYP2A6 activity were most likely to remain current smokers by age 18 years (21).

Examination of the hypothesis that nicotine metabolism is associated with smoking behavior requires large population samples with measures of smoking and nicotine metabolism. Until recently, this type of study was unfeasible. The most direct method for assessing the rate of nicotine metabolism requires intravenous infusion of nicotine and measurement of serial blood levels, which can be accomplished in a laboratory setting only (22). However, it has recently been shown that the nicotine metabolite ratio of 3HC to COT in plasma or saliva is highly correlated with oral clearance of nicotine and is thought to index CYP2A6 activity (9). 3HC/COT ratios in urine and plasma are highly correlated (9). The 3HC/COT ratio differs significantly in persons with CYP2A6 gene variants associated with reduced enzymatic activity compared with variants associated with normal activity, although the ratio across gene variant groupings overlaps considerably (23). The development of this noninvasive technique makes it possible for the first time to examine the association between nicotine metabolism and smoking behavior in the general population.

Benowitz et al. (24) used this noninvasive approach in a self-selected sample of 72 mainly White adult smokers. The urine nicotine metabolite ratio was significantly correlated with number of cigarettes smoked per day (CPD), especially among Whites, but was uncorrelated with the Fagerström Test for Nicotine Dependence (FTND). The ratio was higher among Whites than other racial/ethnic groups. These findings replicated those from laboratory studies that documented extensive racial/ethnic differences in nicotine metabolism rates. Compared with Whites or Hispanics, African Americans and Asians metabolize nicotine more slowly (25, 26).

In this paper, we describe racial/ethnic differences in the nicotine metabolite ratio and its association with multiple measures of smoking behavior, including nicotine dependence, in a subset of a large, national representative sample of young adult smokers. We also examine the excretion of nicotine metabolites in urine as indicators of daily intake of nicotine and their associations with smoking behavior and nicotine dependence. Because of its large size and multiethnic representation, this sample is well suited for examining subgroup differences in rates of nicotine metabolism. These differences are of particular interest given the differences in smoking patterns across racial/ethnic groups documented in epidemiologic studies. Rates of smoking and nicotine dependence among young adults are lower for African Americans than for Whites (27–31).


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
Source of data
Data were derived from wave III of the National Longitudinal Survey of Adolescent Health (Add Health), a subset of US participants in a school survey conducted in 1994–1995 among a national representative sample of 90,118 adolescents in grades 7–12 (32, 33). In 1995 (wave I), representative samples of survey participants and nonparticipants were selected for follow-up (mean age, 15.5 years; standard deviation, 1.7). Siblings and co-twins, if not originally sampled, were added to generate a genetically informative sample but were excluded from weighted national estimates. Wave I interviews were completed with 20,745 adolescents (80 percent participation rate, including 1,821 unweighted cases). In 1996 (wave II), 14,738 of 16,706 wave I adolescents in target grades 7–11 were reinterviewed. In 2001–2002, all students interviewed at wave I were targeted for wave III (n = 20,058), except 687 unweighted cases no longer part of the genetic sample because of a missing pair member or misattribution as a twin. In wave III, interviews were completed with 15,197 youths whose mean age was 21.8 years (standard deviation, 1.9) (75.8 percent participation rate) (refer to the following website: www.cpc.unc.edu/addhealth/). A urine sample was collected from respondents at a random time. Those not reinterviewed were slightly older, more likely to be males, from single-parent families, and more often delinquent than those interviewed; smoking rates were similar in both groups.

Analytical sample
At wave III, 2,982 youths (excluding genetic cases) reported smoking on 30 of the last 30 days and were assumed to have smoked on the survey day. An analytical subsample of 1,016 cases was selected, which included all the minorities (African Americans (n = 307), Hispanics (n = 274), and Asians (n = 125)) and a random subsample of Whites to equal the number of African Americans (n = 310); 904 respondents provided urine samples. The subjects who did not provide samples did not differ from those who did regarding demographic characteristics and smoking patterns. Since COT has a half-life of 16–20 hours, the current smokers in the analytical sample were expected to have detectable COT levels.

The Clinical Pharmacology Laboratory at the University of California, San Francisco, assayed the urine samples for COT and 3HC. Four cases whose 3HC or COT values were lower than 10 ng/ml were excluded because of the mathematical instability of the 3HC/COT ratio at low values. The analytical sample included 271 Whites, 271 African Americans, 244 Hispanics, and 114 Asians. Subjects were aged 18–26 years (mean age, 21.8 years; standard deviation, 2.1 years). Mean educational level was 12.3 years (standard deviation, 2.7). Add Health could not provide statistical weights for this selected sample.

Measurement of nicotine metabolites
The urine samples were assayed for COT and 3HC by using liquid chromatography mass spectrometry (9).

Statistical analyses
We calculated descriptive statistics for urine concentrations of COT, 3HC, and the log-transformed 3HC/COT ratio, as well as the distributions of covariates. Multivariate regressions estimated the association of the logged ratio with sociodemographic characteristics, smoking history, nicotine dependence, and body mass index in the total sample, by gender and race/ethnicity.

Definition of variables
Predicted variables.

  • Urine COT: range, 8.3–5,737.3 ng/ml.
  • Urine 3HC: range, 12.2–60,537 ng/ml. Two values were higher than 35,000 ng/ml.
  • The 3HC/COT ratio was log transformed in the multivariate models.

Covariates.

  • Race/ethnicity: non-Hispanic White, non-Hispanic African American, Hispanic, Asian. Of Hispanics, 40.2 percent were uniquely Mexican/Chicano and 23.8 percent were uniquely Puerto Rican.
  • Gender: male, female.
  • Age (years).
  • Education (years).
  • Onset age at smoking a whole cigarette.
  • CPD: based on the question, "During the past 30 days, on the days you smoked, how many cigarettes did you smoke each day?" Coded 1–≥40.
  • Current nicotine dependence: measured by the FTND (34). Respondents were asked about six symptoms experienced in the last 30 days: 1) time to smoking the first cigarette of the day; 2) finds it difficult not to smoke in places where it is forbidden; 3) which cigarette of the day would most hate to give up; 4) CPD; 5) smokes more frequently the first 2 hours of the day; 6) smokes even if ill. Symptoms 1 and 4 were coded 0–3, others 0, 1 ({alpha} = 0.65). A score of 4 defined nicotine dependence (35).
  • Initial sensitivity to smoking experience (modified Pomerleau et al. scale (36); added two items). Extent to which smokers experienced each of nine symptoms with their first few cigarettes. Scored 1 = none to 4 = intense experience. Three scales averaged the scores of component items: 1) pleasant symptoms (pleasant sensations, relaxation, pleasurable rush or buzz; {alpha} = 0.77); 2) unpleasant symptoms (unpleasant sensations, nausea, coughing, difficulty inhaling, heart pounding; {alpha} = 0.80); 3) dizziness.
  • Body mass index: Weight in kilograms divided by the square of height in meters.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
Smoking patterns
On average, these young adults smoked 12 cigarettes per day and had a low FTND dependence score (table 1). CPD was lower in women than men and was lower in minorities than Whites. Minorities, especially African Americans and Asians, started smoking a whole cigarette at a later age than Whites, on average 1.5 years later. Hispanics and Asians scored lower than Whites on the FTND (table 1). Compared with males, females experienced fewer pleasant and more unpleasant symptoms with their initial cigarette; African Americans experienced fewer unpleasant symptoms than Whites did.


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  		TABLE 1. Patterns of smoking among youths who smoked every day in the past 30 days in the total study sample, by gender and race/ethnicity (wave III of the National Longitudinal Survey of Adolescent Health, United States, 2001–2002; n = 900)

 
Distributions of nicotine metabolite excretion data
The distribution of the absolute urine 3HC/COT ratio in the sample is displayed in figure 1. Distributions of the logged ratios by race/ethnicity are shown in figure 2.


Figure 1
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  		FIGURE 1. Frequency histogram of distribution of urine trans-3'-hydroxycotinine/cotinine ratios (wave III of the National Longitudinal Survey of Adolescent Health, United States, 2001–2002; n = 900).

 

Figure 2
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  		FIGURE 2. Frequency histogram of distribution of trans-3'-hydroxycotinine/cotinine ratios by race (wave III of the National Longitudinal Survey of Adolescent Health, United States, 2001–2002; n = 900). Log-transformed values.

 
There were strong gender and racial/ethnic differences in average values of the 3HC/COT ratio. It was higher among women than men, higher among Whites than African Americans, and lowest among Asians (table 2).


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  		TABLE 2. Mean urine nicotine metabolite levels by race/ethnicity in the total sample and 3HC{dagger}/COT{dagger} ratio by gender and race/ethnicity among youths who smoked every day in the past 30 days (wave III of the National Longitudinal Survey of Adolescent Health, United States, 2001–2002; n = 900)

 
Correlates of the 3HC/COT ratio
There were significant gender and racial/ethnic associations with the ratio (table 3). In the total sample, when we controlled for other covariates, there were two highly significant predictors: gender, with females having a higher ratio than males; and race/ethnicity, with African Americans and Asians having a lower ratio than Whites. The same racial/ethnic differences were observed among females, whereas, among males, only Asians had a lower ratio than Whites. Among females, higher age at onset of smoking a whole cigarette was negatively associated with the ratio.


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  		TABLE 3. Multiple regression predicting 3HC{dagger}/COT{dagger} ratio (log transformed) in the total sample and by gender and race/ethnicity among youths who smoked every day in the past 30 days (wave III of the National Longitudinal Survey of Adolescent Health, United States, 2001–2002; n = 900)

 
There were several racial/ethnic subgroup differences. White and Hispanic females had higher ratios than males; the reverse was observed among Asians. Higher education was positively associated with the ratio among African Americans. At the univariate level, unpleasant symptoms occurring during the initial smoking experience were negatively associated with the ratio among Hispanics, and pleasant symptoms and dizziness were negatively associated among Asians. After we controlled for other covariates, unpleasant symptoms were the only symptoms of initial sensitivity that remained significant among Hispanics, as was found for dizziness among Asians. With control for other covariates, none of the other variables included in the models—CPD, nicotine dependence (FTND), or body mass index—had any unique association with the ratio in any racial/ethnic group.

In their sample of heavy smokers, Benowitz et al. (24) reported a significant association between CPD and the ratio. To parallel this analysis among heavy smokers in this sample, we identified those who met criteria for dependence according to the FTND and those who did not, excluding the CPD item. The association was null in both groups. Similarly, no association was found between the ratio and CPD in each of four quantities on the 3HC/COT ratio (data not presented.)

The nicotine metabolite ratio, individual nicotine dependence symptoms, and initial sensitivity experiences
Although the total nicotine dependence FTND score was unrelated to the nicotine metabolite ratio, we examined separately each FTND symptom in the total sample, by gender and race/ethnicity, to investigate in greater detail potential associations of the ratio with specific nicotine dependence symptoms. We also examined associations with individual initial sensitivity items. Testing of all scale items individually, particularly across subgroups, inflates type 1 error.

Very few significant associations emerged. CPD was significant among females (r = 0.12, p < 0.05), as observed in the unadjusted odds from the regression models in table 3 based on an open-ended question about number of cigarettes smoked in the last 30 days. Hating to give up the first cigarette of the day was negatively associated for Whites (r = –0.13, p < 0.05).

Two unpleasant symptoms associated with initial smoking—coughing (r = –0.10, p < 05) and heart pounding (r = –0.12, p < 0.01)—were negatively associated with the ratio among males. Unpleasant sensations were positively associated among Whites (r = 0.12, p < 0.05); nausea was positively associated among African Americans (r = 0.13, p < 0.05); and coughing (r = –0.19, p < 0.01), difficulty inhaling (r = –15, p < 0.05), and heart pounding (r = –0.14, p < 0.05) were negatively associated among Hispanics. Pleasurable rush (r = –28, p < 0.01) and dizziness (r = –0.31, p < 0.001) were negatively associated among Asians.

Urine metabolite concentrations and smoking behavior
The COT level in smokers is determined by daily nicotine intake, the fraction of nicotine converted to COT, and the rate of COT metabolism (37). Although not precise, COT levels have been used to indicate daily nicotine intake.

Because 3HC is the major urinary metabolite of nicotine, the sum of COT and 3HC may be a better measure than COT alone of total daily nicotine intake. There was a significant correlation between total FTND score and COT, 3HC, and the sum of these two metabolites (table 4). The three measures were also highly correlated with number of cigarettes smoked in the last 30 days and individual FTND items, except hating to give up the first cigarette of the day, which was uncorrelated with 3HC. Difficulty not smoking when forbidden to had the lowest association of any of the remaining five symptoms with the metabolites. The initial sensitivity items were uncorrelated with any of the metabolite concentrations.


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  		TABLE 4. Pearson correlations (r) between COT,{dagger} 3HC,{dagger} and the sum of the two metabolites and selected variables among youths who smoked every day in the past 30 days in the total sample (wave III of the National Longitudinal Survey of Adolescent Health, United States, 2001–2002; n = 900)

 
The concentration of COT per cigarette smoked can be taken as an indicator of nicotine intake per cigarette, reflecting how intensively the average cigarette is smoked. We estimated nicotine intake per cigarette smoked by dividing the subjects' urine COT concentration by total CPD in the last 30 days. Compared with men, women had a lower COT level per cigarette smoked in the past 30 days (Formula = 137.0 ng/ml; standard deviation, 142.5 vs. 162.0 ng/ml; standard deviation, 241.1), but the difference was not statistically significant (p < 0.10). Whites had the lowest COT levels per cigarette smoked (Formula = 99.5 ng/ml; standard deviation, 122.9 ng/ml); the difference between Whites and all other racial/ethnic groups was significant at p < 0.001. African Americans had the highest levels (Formula = 230.4 ng/ml; standard deviation, 266.5 ng/ml) of any group. Asians and Hispanics had very similar COT levels (Formula = 127.4 ng/ml; standard deviation, 126.4 ng/ml and Formula = 131.9 ng/ml; standard deviation, 204.2 ng/ml, respectively), which were significantly lower than those of African Americans.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
This paper presents novel data on the relation between urine metabolites of nicotine and smoking behavior among young adults in a nationally representative multiracial/multiethnic sample. We examined these associations with a noninvasive method for assessing nicotine clearance, the nicotine metabolite ratio of 3HC (the major metabolite of COT) over COT (the proximate metabolite of nicotine). The 3HC/COT ratio in plasma or saliva is highly correlated with oral clearance of nicotine and is thought to be a marker of CYP2A6 activity (9).

Our sample is of particular interest because young adults are often in an early stage of developing nicotine addiction. We focused on only daily smokers, for whom the urine metabolite data were the most useful given the relative short half-life of these metabolites. The average number of cigarettes smoked was 12 per day, well below the national average of 16.8 per day (38). The average FTND score for our subjects was 3.3, indicating a relatively low level of dependence. Men smoked on average more cigarettes than women, and Whites smoked considerably more than African Americans, Hispanics, or Asians. Racial/ethnic differences in rates of smoking are consistent with those for young adults in their twenties in the general population observed in other national data sets (39, 40).

As indicators of daily intake of nicotine, we used urine concentration of COT and the sum of COT and 3HC. In general, the findings for COT and 3HC were similar. These measures were significantly associated with CPD, as expected, and with sex, race/ethnicity, and education—reflecting differences in cigarette smoking in these subgroups. The COT, 3HC, and COT + 3HC measures were also significantly correlated with total FTND score and the individual items. The strongest correlations were with time to smoking the first cigarette after awakening and CPD. These findings are consistent with those from many (but not all) prior studies that have documented that extent of dependence on nicotine is related to daily intake of nicotine (41).

As an indicator of nicotine intake per cigarette, we examined COT concentration normalized for number of cigarettes smoked. This index of nicotine intake per cigarette was considerably higher in African Americans compared with other racial/ethnic groups. Similar findings have been reported using plasma or saliva COT normalized for cigarette smoking (41, 42).

As a phenotypic marker of the rate of nicotine metabolism, we examined the distribution of the nicotine metabolite ratio in the total sample and among racial/ethnic subgroups. Women had higher 3HC/COT ratios on average than men; Whites and Hispanics had higher ratios than African Americans or Asians, consistent with findings from other studies using intravenous infusion of nicotine to determine directly the rate of nicotine metabolism (25, 41, 43) and a recent investigation based on the ratio in a multiethnic sample of adolescents seeking treatment for smoking cessation (44). At this time, we cannot explain the observation that the metabolite ratios were greater for women than men among Whites and Hispanics only. Of note is that the rate of nicotine metabolism was slower in African Americans and Asians than in Whites or Hispanics. Perhaps whatever genetic differences explain slower metabolism in these racial groups may affect sensitivity to sex hormones. Indeed, prior studies have found a gradient in the rate of nicotine metabolism from men to premenopausal women to women using oral contraceptives to pregnant women (43).

Nicotine metabolism is hypothesized to be a determinant of smoking behavior. We found no significant relation between the 3HC/COT ratio and CPD. It is unclear why we did not replicate the findings of the majority of studies in which genotypes of nicotine metabolism were used. Perhaps we had very few very slow metabolizers, although this possibility would be surprising given the substantial number of Asians, among whom the prevalence of slow metabolizers is higher, in our population. We speculated that the lack of relation between the nicotine metabolite ratio and cigarette use is associated with the relatively low level of smoking (average CPD = 12) among our subjects, who may not have been as nicotine dependent or whose smoking may have been more constrained by environmental restrictions compared with older, heavier smokers studied by other investigators. Our speculation was not supported by additional data analysis. The association was still null within each of four groups varying in the extensiveness of smoking. Our data suggest that the rate of nicotine metabolism is not an important determinant of smoking behavior in young smokers. Titration of nicotine intake with related changes in smoking behavior due to individual variation in the rate of nicotine metabolism appears to be more relevant to smokers in a more mature stage of nicotine addiction.

Similarly, among our subjects, there was no relation between the nicotine metabolite ratio and level of dependence. We also examined response to the first smoked cigarette of the day because it might predict progression from experimentation to addictive smoking. The rate of nicotine metabolism would be expected to influence how long nicotine stays in the body and potentially the experience from smoking the first cigarette. We found no association between the ratio and the response to the first cigarette. We found significant associations between the nicotine metabolite ratio and some initial sensitivity responses by sex and race/ethnicity: heart pounding in men, unpleasant symptoms in Hispanics, and dizziness in Asians. In these subgroups, slow metabolizers experienced more adverse symptoms from their first cigarette. Why this finding was observed in some subgroups but not others is not clear. As in all subgroup analyses, replication in future studies is needed.

In summary, we have demonstrated the utility of using urine nicotine metabolite measurements to study racial/ethnic and sex differences in smokers and smoking behavior among young adults. Our findings with respect to sex and race/ethnicity differences in nicotine metabolite ratio generally replicate results regarding nicotine metabolism from studies of older smokers that used more invasive laboratory methods. The noninvasive urine metabolite ratio approach can be used for large population studies in which more invasive methods are unfeasible. Replication of findings among young adult smokers is important to understanding how smokers differ early in their smoking history, before they have reached the maximal level of nicotine dependence.

A limitation of our study is that we considered only daily smokers—that is, chronic smokers who had already developed some level of nicotine dependence. Further studies are needed to determine how differences in nicotine metabolism predict the transition from experimental smoking to addiction and the ability of addicted smokers to quit. That the rate of nicotine metabolism may influence these behaviors is suggested by studies of the CYP2A6 genotype showing differences in very slow metabolizers compared with others, although the patterns may differ at different phases of the life cycle. Since genetically defined very slow metabolizers account for only a small percentage of all smokers, measurement of a nicotine metabolism phenotype, such as the nicotine metabolite ratio, is needed for population studies.


   ACKNOWLEDGMENTS
 
Work on this article was partially supported by research grant DA13288 (D. B. Kandel, principal investigator), a research scientist award (DA00081) to D. B. Kandel from the National Institute on Drug Abuse, and research grant DA02277 to N. L. Benowitz from the National Institute on Drug Abuse. The data are from Add Health, a program project designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris and funded by grant P01-HD31921 from the National Institute of Child Health and Human Development, with cooperative funding from 17 other agencies.

Data used in the analyses were obtained through subcontract 12049901R with the Carolina Population Center. Persons interested in obtaining data files from Add Health should contact Add Health, Carolina Population Center, 123 W. Franklin Street, Chapel Hill, NC 27516-2524 (http://www.cpc.unc.edu/addhealth/contract.html).

Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for their assistance in the original design.

Conflict of interest: N. L. Benowitz is an occasional paid consultant to pharmaceutical companies that market smoking cessation products. He has served as an expert paid witness in litigation against tobacco companies.


   References
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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