Article

Impact of smoking and preexisting illness on estimates of the fractions of deaths associated with underweight, overweight, and obesity in the US population

National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD 20782, USA.
American Journal of Epidemiology (Impact Factor: 4.98). 11/2007; 166(8):975-82. DOI: 10.1093/aje/kwm152
Source: PubMed

ABSTRACT Studies of body weight and mortality sometimes exclude participants who have ever smoked or who may have had preexisting illness at baseline. This exclusionary approach was applied to data from the National Health and Nutrition Examination Surveys to investigate the potential effects of smoking and preexisting illness on estimates of the attributable fractions of US deaths in 2000 that were associated with different levels of body mass index (BMI; weight (kg)/height (m2). Synthetic estimates were calculated by using postexclusion relative risks for BMI categories in place of BMI relative risks from the full sample, holding the relative risks for all other covariates constant. When the postexclusion relative risks were used, the attributable fractions of deaths associated with underweight and with higher levels of obesity increased slightly and the attributable fractions of deaths associated with overweight and with grade 1 obesity decreased slightly. The relative risks for BMI categories did not show large or systematic changes after simultaneous exclusion of ever smokers, persons with a history of cancer or cardiovascular disease, and persons who died early in the follow-up period or had their heights and weights measured at older ages. These analyses suggest that residual confounding by smoking or preexisting illness had little effect on previous estimates of attributable fractions from nationally representative data with measured heights and weights.

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    • "( ≥70 y SALSA ) McAuley et al , 25 2010 Seccareccia et al , 43 1998 ( women 45 - 69 y ) Tice et al , 46 2006 Arndt et al , 39 2007 Walter et al , 48 2009 ( disabled ) Sui et al , 41 2007 Hanson et al , 44 1995 Fontaine et al , 40 2012 ( 60 - 70 y SALSA ) Locher et al , 81 2007 Fontaine et al , 40 2012 ( ≥70 y SAHS ) Fontaine et al , 40 2012 ( 60 - 70 y SAHS ) Seccareccia et al , 43 1998 ( women 20 - 44 y ) Petursson et al , 47 2011 ( women ) Seccareccia et al , 43 1998 ( men 45 - 69 y ) Lang et al , 23 2008 ( men ) Fontaine et al , 40 2012 ( 18 <60 y SAHS ) Flegal et al , 30 2007 ( ≥70 y ) Walter et al , 48 2009 ( nondisabled ) Petursson et al , 47 2011 ( men ) McTigue et al , 68 2006 ( whites ) Flegal et al , 30 2007 ( 60 - 69 y ) Greenberg et al , 54 2007 Sonestedt et al , 110 2011 Flegal et al , 30 2007 ( 25 - 59 y ) Lang et al , 23 2008 ( women ) Katzmarzyk et al , 77 2001 Katzmarzyk et al , 74 2012 McTigue et al , 68 2006 ( blacks ) Data markers indicate hazard ratios and error bars indicate 95% confidence intervals . SAHS indicates San An - tonio Heart Study ; and SALSA , Sacramento Area Latino Study on Aging . "
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    ABSTRACT: Estimates of the relative mortality risks associated with normal weight, overweight, and obesity may help to inform decision making in the clinical setting. To perform a systematic review of reported hazard ratios (HRs) of all-cause mortality for overweight and obesity relative to normal weight in the general population. PubMed and EMBASE electronic databases were searched through September 30, 2012, without language restrictions. Articles that reported HRs for all-cause mortality using standard body mass index (BMI) categories from prospective studies of general populations of adults were selected by consensus among multiple reviewers. Studies were excluded that used nonstandard categories or that were limited to adolescents or to those with specific medical conditions or to those undergoing specific procedures. PubMed searches yielded 7034 articles, of which 141 (2.0%) were eligible. An EMBASE search yielded 2 additional articles. After eliminating overlap, 97 studies were retained for analysis, providing a combined sample size of more than 2.88 million individuals and more than 270,000 deaths. Data were extracted by 1 reviewer and then reviewed by 3 independent reviewers. We selected the most complex model available for the full sample and used a variety of sensitivity analyses to address issues of possible overadjustment (adjusted for factors in causal pathway) or underadjustment (not adjusted for at least age, sex, and smoking). Random-effects summary all-cause mortality HRs for overweight (BMI of 25-<30), obesity (BMI of ≥30), grade 1 obesity (BMI of 30-<35), and grades 2 and 3 obesity (BMI of ≥35) were calculated relative to normal weight (BMI of 18.5-<25). The summary HRs were 0.94 (95% CI, 0.91-0.96) for overweight, 1.18 (95% CI, 1.12-1.25) for obesity (all grades combined), 0.95 (95% CI, 0.88-1.01) for grade 1 obesity, and 1.29 (95% CI, 1.18-1.41) for grades 2 and 3 obesity. These findings persisted when limited to studies with measured weight and height that were considered to be adequately adjusted. The HRs tended to be higher when weight and height were self-reported rather than measured. Relative to normal weight, both obesity (all grades) and grades 2 and 3 obesity were associated with significantly higher all-cause mortality. Grade 1 obesity overall was not associated with higher mortality, and overweight was associated with significantly lower all-cause mortality. The use of predefined standard BMI groupings can facilitate between-study comparisons.
    JAMA The Journal of the American Medical Association 01/2013; 309(1):71-82. DOI:10.1001/jama.2012.113905 · 30.39 Impact Factor
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    • "With appropriate control for smoking and reverse causality, both overweight and obesity are associated with important increases in all-cause and cause-specific mortality, and in particular with cardiovascular disease mortality (Lawlor, 2006). On the other hand, Flegal et al. (2007) demonstrated that residual confounding by smoking or pre existing illness had little effect on previous estimates of attributable fractions from nationally representative data with measured heights and weights (Flegal, 2007). With these discrepancies existing, it may be difficult to estimate deaths attributable to obesity with adequate accuracy and precision. "
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