Estimating the Effect of Smoking Cessation on Weight Gain: An Instrumental Variable Approach

Healthy People 2010 identifies tobacco use and obesity as important focus areas for the United States public health community (U.S. Department of Health and Human Services 2000). The two priorities share an important link. Over the past 25 years, a number of studies have documented the changes in body weight that result from smoking cessation. The research has generally concluded that smoking cessation is associated with a statistically significant increase in body weight among quitters (Coates and Li 1983; Manley and Boland 1983; Albanes et al. 1987; Klesges et al. 1989; Shimokata, Muller, and Andres 1989; Moffart and Owens 1991; Williamson et al. 1991; Flegal et al. 1995; Klesges et al. 1997, 1998; Froom, Melamed, and Benbassat 1998; Mizoue et al. 1998; Froom et al. 1999; Hudmond et al. 1999). Estimates of postcessation weight gain range considerably. A review of the smoking and body weight literature by Klesges et al. (1989) found that estimates of weight gain associated with cessation range from 0.2 to 8.2 kg depending on the sample, study design, and follow-up period. Through their meta-analysis of these studies, the authors concluded that smokers gain an average of 2.9 kg after quitting. In these studies researchers took the basic approach of comparing average weight gain of quitters to that of continuing smokers. Typically the analyses controlled for differences across the two groups with variables including age, sex, and baseline body weight. A problem with this approach is that the two groups are likely to differ in unmeasured variables—such as general concern for health or present versus future orientation—that may be related to weight gain. These differences could confound estimates of the true causal effect of cessation on weight gain. Unmeasured confounders could cause the estimates derived from comparing quitters to continuing smokers to be biased either upwards or downwards. Quitters are known to be less concerned on average about weight gain than continuing smokers, particularly in the case of women (Meyers et al. 1997). This suggests quitters may be more prone to weight gain than continuing smokers, implying that the comparison between the two groups would be biased upwards from the true causal effect. On the other hand, quitters have been shown to be different from continuing smokers in three ways that could produce a downward bias in estimated weight gain. First, a primary motivation for quitting smoking is general concern about health (McCaul et al. 2006). Second, quitters are more future-oriented on average (Bickel, Odum, and Madden 1999). Third, quitters are less impulsive on average (Wurtman 1993; Cinciripini et al. 2003; Terracciano and Costa 2004). All three of these factors could mean that quitters, compared with continuing smokers, are less prone to weight gain. One other factor could produce a bias, but it is not clear in which direction. Quitters tend to be less depressed and exhibit less negative affect at the time of successful quitting than continuing smokers (Cinciripini et al. 2003). These differences in emotional states have been associated in various studies with both weight loss and weight gain (Wurtman 1993; Barefoot et al. 1998). Indeed, the Diagnostic and Statistical Manual of the American Psychiatric Association, 4th Edition (DSM-IV) cites “significant weight loss/gain” as one of the nine symptoms of depression (American Psychiatric Association 1994, p. 161). Depending on their relative magnitudes, the confounding factors described above could produce an overestimate or underestimate of the true effect of cessation on weight gain. It is also theoretically possible that the cofounders offset each other, causing the conventional estimates to be accurate. Thus, we do not know whether previous estimates are too high, too low, or just right. The only way to answer this question definitively is to examine a situation in which people have been randomized to be quitters or continuing smokers, thus ensuring that unmeasured confounders are equal on average across the groups being compared. In this study we adopt a variant of this approach by applying an instrumental variables (IVs) method to previously published randomized cessation trials.