Exploration of an alternative to body mass index to characterize the relationship between height and weight for prediction of metabolic phenotypes and cardiovascular outcomes

被引:9
作者
Shuey, Megan M. [1 ]
Huang, Shi [2 ]
Levinson, Rebecca T. [1 ]
Farber-Eger, Eric [1 ]
Cahill, Katherine N. [1 ]
Beckman, Joshua A. [1 ]
Koethe, John R. [1 ]
Silver, Heidi J. [1 ,3 ]
Niswender, Kevin D. [1 ,3 ]
Cox, Nancy J. [1 ]
Harrell, Frank E., Jr. [2 ]
Wells, Quinn S. [1 ,4 ,5 ]
机构
[1] Vanderbilt Univ, Med Ctr, Dept Med, 2525 West End Ave,Suite 300, Nashville, TN 37203 USA
[2] Vanderbilt Univ, Sch Med, Dept Biostat, Nashville, TN 37212 USA
[3] Tennessee Valley Healthcare Syst, Dept Vet Affairs, Nashville, TN USA
[4] Vanderbilt Univ, Med Ctr, Dept Pharmacol, 2525 West End Ave,Suite 300, Nashville, TN 37203 USA
[5] Vanderbilt Univ, Med Ctr, Dept Biomed Informat, 2525 West End Ave,Suite 300, Nashville, TN 37203 USA
关键词
body mass index; cardiovascular disease; metabolic syndrome; prediction modeling; RISK;
D O I
10.1002/osp4.543
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objective Body mass index (BMI) is the most commonly used predictor of weight-related comorbidities and outcomes. However, the presumed relationship between height and weight intrinsic to BMI may introduce bias with respect to prediction of clinical outcomes. A series of analyses comparing the performance of models representing weight and height as separate interacting variables to models using BMI were performed using Vanderbilt University Medical Center's deidentified electronic health records and landmark methodology. Methods Use of BMI or height-weight interaction in prediction models for established weight-related cardiometabolic traits and metabolic syndrome was evaluated. Specifically, prediction models for hypertension, diabetes mellitus, low high-density lipoprotein, and elevated triglycerides, atrial fibrillation, coronary artery disease, heart failure, and peripheral artery disease were developed. Model performance was evaluated using likelihood ratio, R-2, and Somers' Dxy rank correlation. Differences in model predictions were visualized using heat maps. Results Compared to BMI, the maximally flexible height-weight interaction model demonstrated improved prediction, higher likelihood ratio, R-2, and Somers' Dxy rank correlation, for event-free probability for all outcomes. The degree of improvement to the prediction model differed based on the outcome and across the height and weight range. Conclusions Because alternative measures of body composition such as waist-to-hip ratio are not routinely collected in the clinic clinical risk models quantifying risk based on height and weight measurements alone are essential to improve practice. Compared to BMI, modeling height and weight as independent, interacting variables results in less bias and improved predictive accuracy for all tested traits. Considering an individual's height and weight opposed to BMI is a better method for quantifying individual disease risk.
引用
收藏
页码:124 / 130
页数:7
相关论文
共 19 条
[11]   Waist-to-height ratio, body mass index and waist circumference for screening paediatric cardio-metabolic risk factors: a meta-analysis [J].
Lo, K. ;
Wong, M. ;
Khalechelvam, P. ;
Tam, W. .
OBESITY REVIEWS, 2016, 17 (12) :1258-1275
[12]  
Michels KB, 1998, AM J EPIDEMIOL, V147, P167
[13]   Comparison of anthropometric indices (body mass index, waist circumference, waist to hip ratio and waist to height ratio) in predicting risk of type II diabetes in the population of Yazd, Iran [J].
Mirzaei, Masoud ;
Khajeh, Mohammad .
DIABETES & METABOLIC SYNDROME-CLINICAL RESEARCH & REVIEWS, 2018, 12 (05) :677-682
[14]  
Pi-Sunyer FX, 1998, AM J CLIN NUTR, V68, P899
[15]   Development of a large-scale de-identified DNA biobank to enable personalized medicine [J].
Roden, D. M. ;
Pulley, J. M. ;
Basford, M. A. ;
Bernard, G. R. ;
Clayton, E. W. ;
Balser, J. R. ;
Masys, D. R. .
CLINICAL PHARMACOLOGY & THERAPEUTICS, 2008, 84 (03) :362-369
[16]   High Body Mass Index is an Important Risk Factor for the Development of Type 2 Diabetes [J].
Sanada, Hironobu ;
Yokokawa, Hirohide ;
Yoneda, Minoru ;
Yatabe, Junichi ;
Yatabe, Midori Sasaki ;
Williams, Scott M. ;
Felder, Robin A. ;
Jose, Pedro A. .
INTERNAL MEDICINE, 2012, 51 (14) :1821-1826
[17]   Accuracy of anthropometric indicators of obesity to predict cardiovascular risk [J].
Schneider, Harald J. ;
Glaesmer, Heide ;
Klotsche, Jens ;
Boehler, Steffen ;
Lehnert, Hendrik ;
Zeiher, Andreas M. ;
Maerz, Winfried ;
Pittrow, David ;
Stalla, Guenter K. ;
Wittchen, Hans-Ulrich .
JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM, 2007, 92 (02) :589-594
[18]   Harmonizing the Metabolic Syndrome A Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity [J].
Alberti, K. G. M. M. ;
Eckel, Robert H. ;
Grundy, Scott M. ;
Zimmet, Paul Z. ;
Cleeman, James I. ;
Donato, Karen A. ;
Fruchart, Jean-Charles ;
James, W. Philip T. ;
Loria, Catherine M. ;
Smith, Sidney C., Jr. .
CIRCULATION, 2009, 120 (16) :1640-1645
[19]  
WHO Consultation, 2000, WHO TECH REP SER, V894, P1