Article

A propensity analysis of cigarette smoking and mortality with consideration of the effects of alcohol.

Department of Cardiology, The Cleveland Clinic Foundation, Ohio 44195, USA.
The American Journal of Cardiology (Impact Factor: 3.28). 04/2001; 87(6):706-11.
Source: PubMed

ABSTRACT

Although it is well established that cigarette smoking causes excess mortality, the extent of the increased risk has been challenged because self-selection biases and confounding factors may not have been adequately accounted for in prior studies. We therefore performed a propensity analysis on a population-based cohort. A logistic regression model was used to generate a propensity score for current smoking in 6,099 adults (mean age 46 years, 54% men, 36% current smokers) participating in the National Heart Lung and Blood Institute's (NHLBI) Lipid Research Clinic Prevalence Study. During 12 years of follow-up, 513 subjects (8%) died. After adjusting for age, current smoking was strongly associated with death (compared with never and former smokers, relative risk [RR] 2.69, 95% confidence interval [CI] 1.98 to 0.64, p <0.0001 and RR 1.79, 95% CI 1.26 to 2.55, p = 0.001, respectively). After adjusting for a propensity score based on 27 covariates and the covariates themselves, current smoking remained strongly and independently predictive of excessive death risk in smokers compared with never and former smokers (adjusted RR 2.96, 95% CI 2.16 to 4.05, p <0.0001 and adjusted RR 1.87, 95% CI 1.31 to 2.67, p = 0.0006, respectively). Although smokers were more likely to also drink alcohol, an interaction was noted, whereby, after adjustment for propensity score and other covariates, current smoking was associated with a moderately strong increase in mortality among drinkers (adjusted RR 2.00, 95% CI 1.42 to 2.82, p <0.0001), but was also associated with a markedly increased death risk among nondrinkers (adjusted RR 4.74, 95% CI 3.24 to 6.92, p <0.0001). The independent association of smoking with death even after a rigorous propensity analysis argues that it is highly unlikely that the link between smoking and mortality is materially biased or confounded.

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    • "The procedure is multivariate in that it takes into account a set of potential confounding variables simultaneously. Propensity stratifi cation was used, for example, to demonstrate that cancer can be caused by smoking and not by a host of variables—such as gender, age, or access to medical care—that are at least somewhat correlated with smoking (Foody et al., 2001; Rubin, 2006). Each social support predictor was tested independently because the stratifi cation models were different for each. "
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    ABSTRACT: Multiple studies have shown social network variables to mediate and predict drinking outcome, but, because of self-selection biases, these studies cannot reliably determine whether the influence is causal or correlational. The goal of this study was to evaluate evidence for a causal role for social network characteristics in determining long-term outcomes using state-of-the-art statistical methods. Outpatient and aftercare clients enrolled in Project MATCH (N = 1,726) were assessed at intake and at 3, 6, 9, 12, and 15 months; the outpatient sample was also followed to 39 months. Generalized linear modeling with propensity stratification tested whether changes in social network ties (i.e., number of pro-abstainers and pro-drinkers) at Month 9 predicted percentage of days abstinent and drinks per drinking day at 15 and 39 months, covarying for Alcoholics Anonymous (AA) attendance at Month 9. An increase in the number of pro-drinkers predicted worse drinking outcomes, measured by percentage of days abstinent and drinks per drinking day, at Months 15 and 39 (p < .0001). An increase in the number of pro-abstainers predicted more percentage of days abstinent for both time periods (p < .01). The social network variables uniquely predicted 5%-12% of the outcome variance; AA attendance predicted an additional 1%-6%. Network composition following treatment is an important and plausibly causal predictor of alcohol outcome across 3 years, adjusting for multiple confounders. The effects are consistent across patients exhibiting a broad range of alcohol-related impairment. Results support the further development of treatments that promote positive social changes and highlight the need for additional research on the determinants of social network changes.
    Full-text · Article · May 2012 · Journal of studies on alcohol and drugs
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    • "The procedure is multivariate in that it takes into account a set of potential confounding variables simultaneously. Propensity stratifi cation was used, for example, to demonstrate that cancer can be caused by smoking and not by a host of variables—such as gender, age, or access to medical care—that are at least somewhat correlated with smoking (Foody et al., 2001; Rubin, 2006). Each social support predictor was tested independently because the stratifi cation models were different for each. "
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    ABSTRACT: Objective: Multiple studies have shown social network variables to mediate and predict drinking outcome, but, because of self-selection biases, these studies cannot reliably determine whether the infl uence is causal or correlational. The goal of this study was to evaluate evidence for a causal role for social network characteristics in deter-mining long-term outcomes using state-of-the-art statistical methods. Method: Outpatient and aftercare clients enrolled in Project MATCH (N = 1,726) were assessed at intake and at 3, 6, 9, 12, and 15 months; the outpatient sample was also followed to 39 months. Generalized linear modeling with propensity stratifi cation tested whether changes in social network ties (i.e., number of pro-abstainers and pro-drinkers) at Month 9 predicted percentage of days abstinent and drinks per drinking day at 15 and 39 months, covarying for Alcoholics Anonymous (AA) attendance at Month 9. Results: An increase in the number of pro-drinkers predicted worse drinking outcomes, measured by percentage of days abstinent and drinks per drinking day, at Months 15 and 39 (p < .0001). An increase in the number of pro-abstainers predicted more percentage of days abstinent for both time periods (p < .01). The social network variables uniquely predicted 5%–12% of the outcome variance; AA attendance predicted an additional 1%–6%. Conclusions: Network composition following treatment is an important and plausibly causal predictor of alcohol outcome across 3 years, adjusting for multiple confounders. The effects are consistent across patients exhibiting a broad range of alcohol-related impairment. Results support the further development of treatments that promote positive social changes and highlight the need for additional research on the determinants of social network changes.
    Full-text · Article · Nov 2011 · Journal of studies on alcohol and drugs
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    • "Tobacco smoking and alcohol risk drinking are probable causal factors in more than 120 causes of death (John and Hanke, in press). On the other hand, Foody et al. (2001) by extensively controlling for confounders show a mortality risk among smokers who drank alcohol to be increased but also among those smokers who did not drink any alcohol. Taken together, there is uniform evidence about the interrelationship of smoking and nicotine dependence with alcohol risk drinking, abuse and dependence. "
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    ABSTRACT: Little is known about the synergies of smoking and alcohol consumption in medical care patients. The objective, therefore, is to estimate the coincidence of hazardous and harmful alcohol consumption as well as alcohol abuse and dependence with tobacco smoking in a general hospital and general practices. Three samples of 18-64 year olds include 510 consecutively admitted currently smoking in-patients of a general hospital, 271 patients of a randomized sample of general practices, and 1567 current smokers from a regional population in Germany. Data include the number of cigarettes and a diagnosis of alcohol dependence and abuse (DSM), harmful or hazardous alcohol use. The rates of current daily cigarette smokers with an alcohol dependence or abuse, harmful or hazardous alcohol consumption are 47.1% in the general hospital and 32.1% in the general practice sample compared with 18.4% in the general population. The rates increase from nonsmokers to smokers and with the number of cigarettes. The findings fit into the evidence about alcohol and tobacco interactions in morbidity and mortality. General medical care settings are appropriate for the detection of alcohol dependence or abuse via smoking.
    Full-text · Article · Apr 2003 · Drug and Alcohol Dependence
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