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RESEARCH AND PRACTICE |
The authors are with the Stanford Center for Research in Disease Prevention, Department of Medicine, Stanford University School of Medicine, Palo Alto, Calif.
Correspondence: Requests for reprints should be sent to Marilyn A. Winkleby, PhD, MPH, Stanford Center for Research in Disease Prevention, 1000 Welch Rd, Palo Alto, CA 94304-1825 (e-mail: winkleby{at}stanford.edu).
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Objectives. This study identified mutually exclusive groups of men at high and low risk for use of chewing tobacco and for quitting.
Methods. Analyses used a national sample of 1340 non-Hispanic Black, 1358 Mexican American, and 1673 non-Hispanic White men, aged 25 to 64, who participated in the National Health and Nutrition Examination Survey III from 1988 to 1994. Signal detection analysis was used to delineate high- and low-risk subgroups; survival analysis was used to estimate hazard curves for comparing age at onset for chewing tobacco use with that for smoking.
Results. Rural, lower-income Black and White men had the highest regular use of chewing tobacco (33.3%), followed by rural, higher-income men regardless of race/ethnicity (14.9%). Southern men who began using chewing tobacco during adulthood had the lowest quit rate (22.5%). In sharp contrast to smoking, chewing tobacco showed a continued onset throughout adulthood.
Conclusions. Because subgroups of men show highly different chewing tobacco use and quit rates and because age at chewing tobacco onset occurs across the life span, prevention and cessation programs should be specific to different risk groups and distinct from smoking programs.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Over the last 20 years, prevalence rates for most groups have decreased; only White men aged 18 to 34 showed a higher prevalence rate in 1991 than in 1970.9 Despite recent trends suggesting that the overall use of chewing tobacco may be stabilizing,9 the continuing danger is that prevalence rates may not decrease further or that they may increase. The tobacco industry has shown remarkable flexibility in adjusting its marketing strategy to keep tobacco use at high levels. For example, the prevalence of chewing tobacco use among White men aged 18 to 24 increased 5-fold (from 2.2% in 1970 to 10.1% in 1991) during an extensive chewing tobacco advertisement and promotional campaign targeting this specific age group.10–12 Furthermore, the tobacco industry and even some researchers have suggested that switching to chewing tobacco may be an acceptable, safer alternative to smoking; this suggestion can only serve to increase its popularity.13 These concerns underscore the need to identify patterns of use among different sociodemographic groups and those at highest risk.
National surveys on the health of Americans, such as the National Health Interview Survey and the Behavioral Risk Factor Survey, regularly report overall prevalence rates of chewing tobacco use. However, these reports rarely present in-depth information about the characteristics of those who have chewed regularly and those who have quit. In the current analyses, we were interested in the relation of multiple sociodemographic factors to chewing and quitting and whether these factors delineated distinct high- and low-risk subgroups. Such delineation can aid in the development of tailored prevention and cessation programs and can help counter the pro-tobacco influences that promote chewing tobacco use.
In this study, we used signal detection methodology to identify distinct subgroups of men who had ever used chewing tobacco regularly and who had quit, based on national data collected in the National Health and Nutrition Examination Survey III (NHANES III). In addition, we compared the age at onset for chewing tobacco users and for cigarette smokers to contribute to our understanding of the differences between each form of tobacco use. We focused our study on men because very few women use chewing tobacco.9
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Our analytic sample included 1340 Black, 1358 Mexican American, and 1673 White men between 25 years (to ensure that most men had completed their education and passed the average age for initiation of chewing tobacco) and 64 years of age (to avoid problems of selection effects resulting from typical life changes at older ages, such as poorer health, retirement, and health care coverage).17 We excluded data for men from other racial/ethnic groups (n = 206 "other Hispanic" and "non-Hispanic") and interviews that were coded as unreliable (n = 10). We do not present descriptive data on the characteristics of the NHANES III sample because they have been published elsewhere.17
Measures
Sociodemographic.
Age was calculated in years from the participants' reported birthdate. Respondents who reported their race/ethnicity as nonHispanic Blacks, Mexican or Mexican Americans, or non-Hispanic Whites were included. Education was measured as the highest grade or year of school completed. Family income was the total combined family income during the past 12 months, and family income ratio was family income divided by family size. Urban status was defined as "central and fringe metropolitan counties of 1 million or more," and other counties with fewer than 1 million were designated as rural status. Geographic region of residence was defined as Northeast, South, Midwest, and West.
Tobacco use. Respondents were classified as lifetime regular users of chewing tobacco if they reported ever having used chewing tobacco or snuff (yes/no) and stated an age when chewing tobacco was first used fairly regularly. Current chewers reported using chewing tobacco at the time of the interview (yes/no). Quitters were classified as lifetime regular users not currently using chewing tobacco. Current smokers had smoked at least 100 cigarettes in their lifetime (yes/no) and currently smoked (yes/no). Age at chewing tobacco onset was defined as the age when chewing tobacco was first used fairly regularly. Age at cigarette smoking onset was defined similarly. Amount of chewing tobacco use was defined as the number of containers used each week.
Less than 1% of the data were missing for the variables we analyzed, except for family income, which had 8% of the data missing.
Data Analysis
Signal detection analysis.
We used signal detection analysis, a method of recursive partitioning (classification trees), to identify distinct risk subgroups based on the sociodemographic factors.18,19 This methodology is particularly well suited for identifying interrelationships between multiple factors related to poor health and groups at high and low risk for a particular health outcome. Signal detection models sequentially partition the data to identify subgroups that are mutually exclusive and maximally discriminated from each other, based on the probability of the outcome, which must be binary. The independent variables are entered, and the algorithm then selects a variable and cutpoint based on a combined optimal measure of sensitivity and specificity with regard to the outcome variable.
Unlike regression analysis, signal detection analysis is not highly affected by the collinearity of variables in the model (e.g., family income and family income ratio). After choosing and splitting on the first optimally efficient variable, the signal detection program separately searches each subgroup or "branch" of the first split for the next most efficient variable and cutpoint, again using all initial independent variables as candidates. This procedure is repeated separately in each subgroup and ends when (1) subgroup samples become small (n < 25), (2) no further significant discriminating variables are found (P < .001), or (3) no further independent variables remain. The results are displayed as classification trees.
We ran separate signal detection analyses for the 2 binary (yes/no) outcome variables of lifetime regular use of chewing tobacco and quitting. Each signal detection analysis included age, education, family income, family income ratio, race/ethnicity, urban or rural status, and geographic region of residence. Age at onset was included in the analyses of quitting.
Subgroup profiles. We used SUDAAN, Version 7.11 (Research Triangle Institute, Research Triangle Park, NC), to calculate weighted means, percentages, and standard deviations to examine the characteristics, or profiles, of the subgroups identified by the signal detection analysis. SUDAAN incorporated sampling weights that adjusted for unequal sampling probabilities resulting from the complex NHANES III sample design. The subgroup profiles included all of the variables used in the signal detection models as well as amount of chewing tobacco used each week and smoking status.
Survival analysis. We conducted survival analyses with SAS, Version 6.12 (SAS Institute Inc, Cary, NC), to estimate the hazard rates for age at onset for chewing tobacco use and cigarette smoking. The hazard curve for each event gives the instantaneous rate of the event at each time point. Unlike a survival curve, which can only decrease, hazard curves can increase and decrease depending on the underlying event probabilities, allowing one to observe more easily whether different periods of life are subject to higher risk. In this analysis, our interest was to create a graphical representation of the pattern of risk to compare the 2 types of tobacco use rather than to compare the actual incidence rates. The hazard plot was preferred over a simple bar graph of frequencies because of the large differences in the prevalence rates of chewing and smoking.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Signal Detection Analysis and Subgroup Profiles
Lifetime regular use of chewing tobacco.
The first signal detection analysis examined factors associated with lifetime regular use of chewing tobacco. The signal detection model identified 5 subgroups (Figure 1
). The overall rate of lifetime use was 10.7%, and high-risk and low-risk groups were defined in relation to this overall rate. The first sociodemographic variable that distinguished lifetime regular users was urban or rural status. Among rural men, family income and race/ethnicity distinguished 2 subgroups with significantly different rates of use. Black and White men with family incomes of $8500 or less reported the highest regular use rate (33.3%, group 1), whereas Mexican American men with family incomes of $8500 or less reported a substantially lower rate (7.7%, group 2). Regardless of race/ethnicity, rural men with family incomes greater than $8500 had a higher rate of regular use (14.9%, group 3) than men overall. Among urban men, geographic region of residence was the only additional distinguishing variable. Men living in the South had more than twice the rate of regular use (9.1%, group 5) as men not living in the South (4.4%, group 4), but rates for both groups were lower than the overall rate.
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, these men were predominantly Black (65%) and from the South (76%). Although their mean age was 44.9 years, most had not completed high school (62%), and their average family income was very low ($5594). Rural, higher-income men (group 3) were the next highest risk subgroup. These men were predominantly White (49%), with the remainder split equally among Blacks (26%) and Mexican Americans (25%). Two thirds of these men were from the South (62%). These men were more highly educated than the highest risk group, with 65% completing a high school education or higher, and their income was substantially higher ($32 905). Among those who were still current users of chewing tobacco, men in the 2 highest risk subgroups used more chewing tobacco each week than did men in the low-risk subgroups (4.1 or more containers per week vs 3.2 or fewer). Men in the highest risk group were much more likely to be smokers (61%) than were men in the other groups (35%–39%).
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). The signal detection analysis identified geographic region of residence as the first distinguishing variable, with nonsouthern men reporting higher rates of quitting (72.3%, group 1) than the overall rate. For southern men, age at onset was the next distinguishing variable and yielded 2 groups: those younger than 38 years and those 38 years and older. Men who started using chewing tobacco at younger ages were substantially more likely to quit than were men who started using chewing tobacco at older ages (58.5%, group 2; 22.5%, group 3).
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). A much larger proportion of these high-risk men had not completed high school (65% vs 26%, group 1; 43%, group 2), but they were less likely to be smokers (25%) compared with the other 2 groups of men (34%, group 1; 41%, group 2).
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). Both hazard curves showed a rapid increase in onset of tobacco use beginning at about age 10 and peaking at about age 18. For cigarettes, the decrease after the peak hazard was quite steep, but onset became negligible after age 35. In sharp contrast, for chewing tobacco, the decrease after the peak was more gradual than for smoking, and a second increase was evident in adulthood, reaching a peak at age 55. The hazard curve then decreased steeply, but the curve never became flat, suggesting a continuing risk for onset of chewing tobacco use late in life.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Consistent with previous research, our data indicated that rural status is a prime determinant of ever using chewing tobacco regularly.8,9 Compared with the overall rate (10.7%), urban men had a lower risk for regular use, especially urban men not living in the South. Among rural men, the most striking findings were the particularly high rate of regular lifetime use for lower-income Black and White men (33.3%) and the particularly low rate for lower-income Mexican American men (7.7%). Race/ethnicity did not distinguish among higher-income rural men who also had high rates of lifetime use (14.9%). These results suggest that if prevention resources are limited, they should be directed primarily to rural, lower-income Black and White men and secondarily to rural, higher-income men regardless of race/ethnicity.
Data on quitting indicated that nearly three quarters of the lifetime regular users not living in the South had successfully quit, whereas far fewer southern men had quit. More cessation programs may be available in nonsouthern regions, or there may be fewer social and cultural supports for continued use of chewing tobacco. These data suggest that lowering prevalence rates will require a more concerted effort in the South. In addition, southern men who began using chewing tobacco during later adulthood need special outreach efforts. Although the sample size for this group was small and argues for caution when interpreting the results, several hypotheses regarding the low quit rates among these men with late onset are tenable. Perhaps because of their late start, these men have not had time to quit. Alternatively, their late start and relatively low rate of cigarette smoking may mean that they had fewer reasons to think about quitting (e.g., few health problems related to tobacco use). Other research has suggested that chewers who are motivated to quit are more dependent on nicotine, have received advice to quit from health professionals, and have experienced more tobacco-related health problems compared with chewers who are less interested in quitting.20
Education, often a key predictor of tobacco use and other health risk factors, was not a significant determinant of risk groups in the signal detection analysis, but it was a distinguishing factor in the profiling of subgroups. The highest risk groups for regular use and not quitting both had very low educational attainment; two thirds never completed high school. These men also had lower incomes, were older, and were more likely to be from the rural South than were the men in the other subgroups. These findings have implications for intervention efforts. For example, prevention and cessation programs may need to pay particular attention to issues of literacy, community resources, and social and cultural norms.
Survival analyses indicated that the risk for onset of regular chewing tobacco use continued well into middle age and beyond, whereas the risk for onset of regular cigarette smoking became negligible by middle age. If chewing onset occurs across the life span, there are many implications for interventions. For example, prevention messages must address middle-aged and older men, in addition to adolescents and young adults. Because smoking prevention programs focus primarily on adolescents, chewing tobacco programs that are offered only in tandem with school- or community-based smoking programs will likely miss a substantial number of men who initiate use during adulthood. Chewing tobacco prevention and cessation programs are needed beyond high school, vocational school, and college and in settings outside of school. The workplace is a viable setting for delivering programs to middle-aged and older men. In addition, some research suggests that cessation interventions located at the site of health care services, such as dentist offices, can be successful with chewing tobacco users.21,22
Overall, more research establishing the efficacy of chewing tobacco cessation interventions of all kinds (e.g., group counseling, self-help, nicotine replacement therapies) is needed to augment the relatively small body of literature in this area.21–27
The results and conclusions of this analysis were subject to limitations of the NHANES III data. NHANES III was a cross-sectional survey and did not allow inferences about developmental or causal pathways. Rural status classification was imprecise because the disseminated database collapsed a 10-point rural and urban continuum code into 2 categories to prevent identification of the sampled counties. The interview was designed for breadth, not depth of coverage (e.g., no definition of "regular use of chewing tobacco" was included), and like other self-report interview methodologies, it was subject to recall bias (e.g., potential underreporting of current chewing tobacco use). This study analyzed data for White, Black, and Mexican American men only, which limits the generalizability of results, but NHANES III included large samples of adults in each racial/ethnic group from households at both the upper and the lower levels of educational attainment, thus strengthening the validity of findings related to socioeconomic status.
This study used signal detection and survival analysis methodologies to identify specific groups of men at risk for using chewing tobacco and not quitting and found evidence that the ages at onset for chewing tobacco and for smoking were substantially different. However, both the signal detection and the survival analyses should be considered exploratory rather than hypothesis testing. Future studies need to establish the replicability of the subgroups of chewing tobacco users identified in this study and the findings related to chewing tobacco onset.
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Acknowledgments |
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The authors gratefully acknowledge David Ahn for data analysis; Helena Kraemer for her biostatistical expertise; Stephen P. Fortmann, Lisa Henriksen, Gregory J. Norman, and Nina Schleicher for their valuable comments on an earlier draft of the paper; and Alana Koehler for technical assistance.
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Footnotes |
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Accepted for publication January 10, 2001.
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References |
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