Nicotine dependence and its familial aggregation in Chinese

Tianhua Niua, Changzhong Chena,b, Jiatong Nib, Binyan Wanga,b, Zhian Fangb, Hong Shaoc and Xiping Xua,b,c,d

a Program for Population Genetics, Harvard School of Public Health, Boston, MA, USA.
b Institute for Biomedicine, Anhui Medical University, Hefei, China.
c Department of Biology and Genetics, Beijing Medical University, Beijing 100083, China.
d Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Reprint requests to: Xiping Xu, Program for Population Genetics, FXB-101, Harvard School of Public Health, 665 Huntington Avenue, Boston, MA 02115–6096, USA. E-mail: xxu{at}hohp.harvard.edu


    Abstract
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Background Nicotine dependence is a significant public health problem. This study attempted to characterize the prevalence and familial aggregation of nicotine dependence in China.

Methods In 1998, we initiated a community-based cross-sectional study among residents of the Yuexi County in Anqing, China. A total of 991 current smokers from 488 randomly selected nuclear families were recruited and surveyed by use of the standardized Fagerstrom Test of Nicotine Dependence (FTND) questionnaire and the Revised Tolerance Questionnaire (RTQ). All study subjects were offspring in their respective nuclear families, and 478 male-male pairs (aged 41.7 ± 12.1 years) were finally used for data analyses, because the number of female current smokers (n = 5) was too small.

Results The correlation coefficient of the FTND and the RTQ scores was as high as 0.84 (P < 0.0001). Nicotine dependence, defined as an FTND score >=8 or an RTQ score >=28, had a prevalence of 12.7% and 11.1%, respectively. The respective sibling recurrent risk was 1.7 and 2.4, according to the FTND or the RTQ criteria. The adjusted odds ratios and 95% CI of nicotine dependence of second siblings in families in which the first sibling was nicotine dependent were 2.13 (95% CI : 1.02–4.43) and 3.50 (95% CI : 1.65–7.36) respectively, according to the FTND and RTQ criteria.

Conclusions The prevalence of nicotine dependence in male current smokers in China was comparable to that reported in previous US and European studies. Our findings suggest that genetic influences may play an important role in vulnerability to nicotine addiction.

Keywords Nicotine dependence, smoking, familial aggregation, recurrent risk, regression model

Accepted 23 August 1999


    Introduction
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
The persistence of cigarette smoking, despite widespread awareness of adverse health effects, can be explained by an underlying dependence on nicotine.1 The pharmacological and behavioural basis for nicotine dependence acts in a way similar to that of cocaine and heroin.1,2 Furthermore, tobacco holds a special status as a ‘gateway’ substance in the development of other drug dependencies, not only because tobacco use reliably predicts use of other psychoactive substances such as alcohol or opioids, but also because people who use tobacco are more likely to develop dependent patterns of use than those who use most other additive drugs.1

The epidemic of dependence to nicotine has enormous consequences for public health. It has been estimated that in the US 40 million smokers are addicted to nicotine.3 China, with 20% of the world's population, produces and consumes about 30% of the world's cigarettes. China already attributes almost a million deaths a year to tobacco use,4,5 and this figure is more than in any other country. Tobacco will eventually kill one-third of all young men in China, and will kill half of all persistent cigarette smokers.6 A better understanding of nicotine dependence, and implementation of improved measures for curbing cigarette smoking, will contribute to a substantial improvement in this picture over the next decade. Life-time prevalence rates of Diagnostic and Statistical Manual (DSM)-III tobacco dependence were reported as 27% and 1% in male and female popu-lations, respectively,7 in Hong Kong and 39% and 2%, respectively, in Shanghai.8

In this study, we aim to calculate the prevalence and the sibling recurrent risk ({lambda}s) of nicotine dependence on the basis of data collected from a recent epidemiological study of currently smoking men in Yuexi, China.


    Materials and Methods
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Study site
A random sample of 991 current smokers (‘current smoking’ status is defined as: more than one cigarette smoked per day for at least a year), which comprised 488 sibling pairs, was drawn from residents aged >=15 in Yuexi, County of Anqing in southeastern China. A total of 483 independent sibling pairs, 99% of the sample, were interviewed at their homes from December 1988 through January 1999. These 966 respondents consisted of 478 independent male-male pairs and five independent male-female pairs. This sample represents the population at this age group in the area.

Procedures
The Chinese translations of the Fagerstrom Test of Nicotine Dependence (FNTD)9 and the Revised Tolerance Questionnaire (RTQ)10 were employed as an efficient and non-invasive way to rapidly gather information on nicotine addiction in the study population. The survey team was made up of locally hired interviewers fluent in the dialect of the region. A letter explaining the purpose of the study was sent to each participant. Local officials and health centres arranged for the interviews and measurements to take place at the central office at times convenient to the participants. Additional visits were requested for subjects with missing or ambiguous data.

Diagnostic definition of nicotine addiction
The FTND and RTQ scores are considered the best measurement tools in the field of nicotine dependence assessment. These scores reflect the level of severity. Based on our data, two criteria were used to define nicotine dependence: (1) an FTNQ score of >=8 and (2) an RTQ score of >=28.

Statistical analyses
The outcome variables were FTND and RTQ scores. Our analyses were conducted in several stages. First, we investigated the prevalence of each dependence symptom for both FTNQ and RTQ in the first and the second siblings. Second, we calculated the distribution of these scores for the two siblings separately and together. Third, the correlation of FTND and RTQ scores was estimated. Fourth, we developed predictive models of FTND and RTQ, based on other smoking-related phenotypes. Finally, we performed multiple logistic regression to assess the odds ratio (OR) of nicotine-dependent second siblings to the first siblings' nicotine addiction status. All P-values were two-tailed.


    Results
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 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
The study sample consisted of 956 male current smokers (478 sibling pairs) with complete data on the FTNQ and RTQ. The mean age was 41.7 ± 12.1 years. The prevalence of nicotine dependence as reflected by the completed RTQ and FTND is presented in Tables 1 and 2GoGo, respectively. The correlation coeffi-cient of the FTND and the RTQ scores was 0.84 in the overall sample and reached statistical significance for both the first and the second siblings (P < 0.0001) separately. According to the RTQ criteria (nicotine dependence is defined as a score >=28), the prevalence of nicotine dependence was 12.1% and 10.3% in the first and the second currently-smoking siblings, respectively. According to the FTND criteria (nicotine dependence is defined as a score >=8), the prevalence of nicotine dependence was 12.3% and 13.0% in the first and the second currently-smoking siblings, respectively. {lambda}s was estimated to be 2.4 and 1.7 by the RTQ and FTND criteria, respectively. Table 3Go presents the respective distribution of RTQ and FTND scores in the first and the second siblings. Of the subjects, 20.2% had an RTQ score of <8, and 13.2% of subjects had an RTQ score >=28; 34.5% had an FTND score of <2, and 31.1% had an FTND score of >=6. In the linear regression model, the age at which subjects started to smoke, the number of years cigarettes were smoked, the number of cigarettes smoked per day, and the total pack-years were all found to be significantly correlated with both the FTND score (Pearson Correlation Coefficients were 0.24, 0.20, 0.68, and 0.47, respectively) and the RTQ score (Pearson Correlation Coefficients were 0.26, 0.26, 0.63, and 0.48, respectively).


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Table 1 Prevalence in a rural Chinese population of nicotine dependence as determined by the Revised Tolerance Questionnaire (RTQ)
 

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Table 2 Prevalence in a rural Chinese population of tobacco dependence as determined by the Fagerstrom Test of Nicotine Dependence (FTND)
 

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Table 3 Distribution of the score from Revised Questionnaire and Fagestrom Questionnaire
 
Table 4Go presents the adjusted OR and 95% CI of nicotine dependence in second siblings of nicotine-dependent first siblings. The results were presented according to both FTND and RTQ scores, respectively. According to the RTQ criteria, the second sibling had a 3.50 (95% CI : 1.65–7.36) increased risk of having nicotine dependence when the first sibling had nicotine dependence. According to the FTND criteria, the second sibling had a 2.13 (95% CI : 1.02–4.43) increased risk of nicotine dependence if the first sibling was dependent on nicotine.


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Table 4 Nicotine dependence of second sibling by the status of first sibling
 

    Discussion
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 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
In this study, we attempt to address the prevalence as well as the familial aggregation of nicotine addiction in a Chinese rural population. We limited our focus to men alone, since smoking is rare among Chinese women. Overall, we found a significant and substantial familial component of nicotine addiction, which provides a justification for further genetic dissection of the aetiology of this addictive disorder.

Results from twin studies indicate that both the acquisition and maintenance of the smoking habit are influenced by heredity.11 Heritability estimates were 47–76% for smoking initiation (varying as a function of concordance or discordance for early environmental experiences) and 62% for smoking persistence.12 Moreover, smoking is found to be as heritable as alcohol consumption, and the magnitude of genetic effect on smoking is at least as great as that on alcoholism.11

The Fagerstrom Tolerance Questionnaire (FTQ) has been widely used to assess tobacco dependence. Previous studies reported modest correlations between FTQ scores and plasma nicotine levels and urinary cotinine levels, and withdrawal symptoms.13 The FTND is the revised version of FTQ, which represents a distinct improvement over the FTQ.10,14–16 Internal consistency was improved and a unitary factor structure emerged.14 Both internal consistency and the predictive validity (assessed via regression analyses involving expired alveolar carbon monooxide [COa] and saliva cotinine levels) were enhanced in FTND.

Fagerstrom et al.9 proposed a five-level categorization of FTND scores from very low dependence to very high dependence, i.e. very low (0–2 points), low (3–4 points), medium (5 points), high (6–7 points), and very high (8–10 points). Thus our definition of nicotine addiction by the FTND criteria corresponds to a very high level of nicotine dependence. If we consider an FTND score >=6 (‘high level’ nicotine dependence) as the threshold for defining nicotine addiction, the prevalence in this Chinese population is 31.1%, which is comparable to that reported in the US (36.0%)17 and in Austria (36.5%).18

Tate and Schmitz10 pointed out the need for further refinement of the FTQ, even beyond FTND, to improve its reporting of psychometric properties. By changes in item wording, scale format, and the addition/deletion of items, the RTQ was proposed as a psychometrically better instrument to assess nicotine addiction than the FTQ. The RTQ uses five-point Likert scales, which allows more variability in behaviour, and rewording of certain items has reduced ambiguity.10 Moreover, RTQ is shown to have a close approximation to a unidimensional measure of nicotine dependence. Our study is the first of its kind to use both the FTND and RTQ to assess the degree of nicotine addiction in a community-based random sample. A high consistency between the FTND and the RTQ scores confirmed that both measures accurately reflect the extent of nicotine addiction.

In agreement with Henningfield et al.,19 our study suggests that the number of cigarettes smoked per day is a variable that shows the highest correlation with an increase in the risk of nicotine dependence. Our findings also demonstrate that smoking more cigarettes, smoking for a longer duration, and starting smoking at a younger age are all positively and significantly associated with a higher FTND or RTQ score for nicotine dependence. These findings agree with results of other studies.13,19,20

There are several strengths of this investigation. First, our study is novel because it uses both FTQ and FTND scores in defining nicotine addiction and in estimating {lambda}s, thus providing a critical piece of information in power calculation and study design for analysis of genetic linkage in affected sibpairs. Second, the study population is homogeneous with regard to lifestyle, social/cultural norms, diet, and ethnicity. Third, few subjects included in this study use nicotine replacement therapy (e.g. nicotine chewing gum, skin patches, nasal sprays, and inhalers) or take pharmacotherapies such as mecamylamine and clonidine, and therefore the confounder of drug intervention is greatly minimized. Finally, we used a community-based research design, so a selection bias is unlikely to be present.

The present study has several limitations. First, our study focused on male-male currently-smoking sibling pairs in a Chinese population. The findings reported here are therefore only relevant to Chinese men who are current smokers. Furthermore, these results may not be generalized to other ethnic groups with different population characteristics. However, since the smoking rate in Chinese rural women aged >=15 years is extremely low (<1%), and both the FTND and the RTQ are most appropriate when administered to current smokers, our results still provide excellent estimates of the prevalence of nicotine dependence and familial aggregation in this Chinese population. Second, the significant familial aggregation findings revealed by this study may be attributable to both shared genes and a shared household environment between the two siblings. Household environmental factors such as negative life events afflicting all family members21 and parental smoking,22 have been previously related to a higher rate of cigarette smoking. These household environmental factors may have a critical impact on nicotine dependence for both the first and the second siblings, introducing uncontrolled confounding biases that may lead to an overestimate of the magnitude of familial aggregation. However, few studies have attempted to address the contributions of these factors in nicotine dependence, and their roles are not well characterized. Therefore, further studies are clearly needed to assess their influences more specifically.

In summary, our results provide compelling evidence that nicotine dependence has a substantial familial component, thus indicating that genetic factors may have a great influence in conferring vulnerability to nicotine addiction. Since few genes have been pinpointed as potentially associated with nicotine addiction, genome-wide screening studies of this addictive disorder may help to identify novel genes responsible for nicotine dependence, and this may lead to both a better understanding of disease pathophysiology and the discovery of potential targets for drug development.


    Acknowledgments
 
We wish to acknowledge the assistance and co-operation of the faculty and staff of the Anhui Medical University, Anqing Public Health Bureau and Anqing Hospital. Drs Changzhong Chen and Binyan Wang were supported in part by Fogarty International Center Training Grant TW00828.


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 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
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