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使用特定性别的体重指数来优化与身高的低相关性以及与肥胖的高相关性:一项英国生物银行研究。

Use of Sex-Specific Body Mass Index to Optimize Low Correlation With Height and High Correlation With Fatness: A UK Biobank Study.

作者信息

Feng Qi, Kim Jean H, Xie Junqing, Bešević Jelena, Conroy Megan, Omiyale Wemimo, Wu Yushan, Woodward Mark, Lacey Ben, Allen Naomi

出版信息

Am J Epidemiol. 2024 Feb 5;193(2):296-307. doi: 10.1093/aje/kwad195.

Abstract

Body mass index (BMI; weight (kg)/height (m)2) is commonly used to measure general adiposity. However, evidence of its appropriateness for males and females remains inconsistent. We aimed to identify the most appropriate sex-specific power value that height should be raised to in the formula and the value that would make it achieve height independency and body fatness dependency. We randomly assigned UK Biobank participants recruited in the United Kingdom between 2006 and 2010 (n = 489,873; mean age = 56.5 years; 94.2% White) to training and testing sets (80%:20%). Using height raised to the power of -50.00 to 50.00, we identified the optimal power value that either minimized correlation with height or maximized correlation with body fat percentage, using age-adjusted correlations. The optimal power values for height were 1.77 for males and 1.39 for females. The new formulas resulted in 4.5% of females and 2.4% of males being reclassified into a different BMI category. The formulas did not show significant improvement (in terms of area under the receiver operating characteristic curve, sensitivity, and specificity) in identifying individuals with excessive body fat percentage or in predicting risk of all-cause mortality. Therefore, the conventional BMI formula is still valuable in research and disease screening for both sexes.

摘要

体重指数(BMI;体重(千克)/身高(米)²)通常用于衡量总体肥胖程度。然而,其对男性和女性适用性的证据仍不一致。我们旨在确定公式中身高应提升到的最合适的性别特异性幂值,以及使其实现身高独立性和身体脂肪依赖性的值。我们将2006年至2010年在英国招募的英国生物银行参与者(n = 489,873;平均年龄 = 56.5岁;94.2%为白人)随机分配到训练集和测试集(80%:20%)。使用提升到 -50.00至50.00幂的身高,我们通过年龄调整后的相关性确定了使与身高的相关性最小化或与体脂百分比的相关性最大化的最佳幂值。男性身高的最佳幂值为1.77,女性为1.39。新公式导致4.5%的女性和2.4%的男性被重新分类到不同的BMI类别。在识别体脂百分比过高的个体或预测全因死亡率风险方面,这些公式(在受试者工作特征曲线下面积、敏感性和特异性方面)没有显示出显著改善。因此,传统的BMI公式在两性的研究和疾病筛查中仍然很有价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/193f/10840076/ce1206a5a98c/kwad195f1.jpg

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