Issues related to modeling the body mass index-mortality association: the shape of the association and the effects of smoking status

被引:19
|
作者
Durazo-Arvizu, R. A. [1 ]
Cooper, R. S. [1 ]
机构
[1] Loyola Univ, Dept Epidemiol & Prevent Med, Maywood, IL 60153 USA
关键词
BMI; all-cause mortality; model; smoking; confounders; data exclusion;
D O I
10.1038/ijo.2008.86
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Research on the relationship between body mass index ( BMI) and mortality has led to conflicting results; a lack of agreement about how to adjust for confounders, such as smoking status, has added to the problem. Complicating such analyses is the fact that the BMI - mortality association is not a symmetric quadratic relationship; the distribution tends to be skewed to the right, causing the optimal BMIFwhere mortality is at a minimumFto be overestimated. One way to overcome this problem is by transformation of the BMI distribution to normality. The authors suggest several approaches for doing so, including the use of 1/ BMI, or lean body mass index, instead of BMI in modeling. Data sets on 50 cohorts from approximately 30 international studies were used to examine the association ( direct, inverse, quadratic or none) between BMI and mortality and to investigate the possible interaction of smoking status. Of the 50 cohorts, 36 showed a quadratic association between BMI and mortality, 10 showed no association and 1 showed a direct association between lean BMI and mortality. Only three cohorts showed a significant interaction between BMI and smoking, which was approximately what one would expect from a 5% significance test, even if no interaction existed. The association between BMI and mortality is not changed when smoking status is ignored in a model or when data on smokers are excluded from analysis. The methodology used in this study could be extended to look for other interactions.
引用
收藏
页码:S52 / S55
页数:4
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