Preston Samuel H, Fishman Ezra, Stokes Andrew
Population Studies Center, University of Pennsylvania, Philadelphia.
Department of Global Health, Boston University, Boston, MA.
Ann Epidemiol. 2015 Dec;25(12):907-11.e1-2. doi: 10.1016/j.annepidem.2015.07.012. Epub 2015 Aug 19.
The health consequences of obesity are often assessed using categorical, self-reported data on body mass index (BMI). This article investigates the combined effects of categorization and self-report bias on the estimated association between obesity and mortality.
We used the National Health and Nutrition Examination Survey (1988-2008) linked to death records through 2011. Cox models and age-standardized death rates were used to evaluate the effects of categorization and self-report bias on the mortality risks and percent of deaths attributable to obesity.
Despite a correlation between measured and self-reported BMI of 0.96, self-reports miscategorized 20% of adults. Hazard ratios using self-reports were overstated for the obese 1 (BMI, 30-35 kg/m(2)) and obese 2 (BMI ≥ 35 kg/m(2)) categories. The bias was much smaller using a continuous measure of BMI. In contrast, the percent of deaths attributable to excess weight was lower using self-reported versus measured data because self-reports led to systematic downward bias in the BMI distribution.
Categorization of BMI and self-report bias combine to produce substantial error in the estimated hazard ratios and percent of deaths attributable to obesity. Future studies should use caution when estimating the association between obesity and mortality using categorical self-reported data.
肥胖对健康的影响通常使用关于体重指数(BMI)的分类且自我报告的数据来评估。本文研究了分类和自我报告偏差对肥胖与死亡率之间估计关联的综合影响。
我们使用了与截至2011年的死亡记录相链接的国家健康与营养检查调查(1988 - 2008年)。Cox模型和年龄标准化死亡率被用于评估分类和自我报告偏差对死亡风险以及肥胖所致死亡百分比的影响。
尽管测量的BMI与自我报告的BMI之间的相关性为0.96,但自我报告将20%的成年人分类错误。使用自我报告得出的肥胖1类(BMI,30 - 35千克/米²)和肥胖2类(BMI≥35千克/米²)的风险比被高估。使用BMI的连续测量时偏差要小得多。相比之下,使用自我报告数据与测量数据相比,超重所致死亡百分比更低,因为自我报告导致BMI分布出现系统性向下偏差。
BMI分类和自我报告偏差共同作用,在估计的风险比和肥胖所致死亡百分比方面产生了大量误差。未来研究在使用分类自我报告数据估计肥胖与死亡率之间的关联时应谨慎。