Comparing Methods for Identifying Biologically Implausible Values in Height, Weight, and Body Mass Index Among Youth

• Published in: American journal of epidemiology Vol. 182; no. 4; pp. 359 - 365
• Main Authors: Lawman, Hannah G, Ogden, Cynthia L, Hassink, Sandra, Mallya, Giridhar, Vander Veur, Stephanie, Foster, Gary D
• Format: Journal Article
• Language: English
• Published: United States Oxford Publishing Limited (England) 15-08-2015; Oxford University Press
• Subjects: Adolescent; African Americans; African Americans - statistics & numerical data; Anthropometry; Bias; Body Height; Body Mass Index; Body Weight; Child; Children & youth; Data Interpretation, Statistical; Female; Height; Humans; Longitudinal Studies; Male; Obesity; Obesity, Morbid - epidemiology; Obesity, Morbid - ethnology; Pediatric Obesity - epidemiology; Pediatric Obesity - ethnology; Philadelphia - epidemiology; Practice of Epidemiology; Prevalence; Weight; Philadelphia Pennsylvania; biologically implausible values; body mass index; obesity; youth
• ISSN: 0002-9262; 1476-6256
• DOI: 10.1093/aje/kwv057

As more epidemiologic data on childhood obesity become available, researchers are faced with decisions regarding how to determine biologically implausible values (BIVs) in height, weight, and body mass index. The purpose of the current study was 1) to track how often large, epidemiologic studies address BIVs, 2) to review BIV identification methods, and 3) to apply those methods to a large data set of youth to determine the effects on obesity and BIV prevalence estimates. Studies with large samples of anthropometric data (n > 1,000) were reviewed to track whether and how BIVs were defined. Identified methods were then applied to a longitudinal sample of 13,662 students (65% African American, 52% male) in 55 urban, low-income schools that enroll students from kindergarten through eighth grade (ages 5-13 years) in Philadelphia, Pennsylvania, during 2011-2012. Using measured weight and height at baseline and 1-year follow-up, we compared descriptive statistics, weight status prevalence, and BIV prevalence estimates. Eleven different BIV methods were identified. When these methods were applied to a large data set, severe obesity and BIV prevalence ranged from 7.2% to 8.6% and from 0.04% to 1.68%, respectively. Approximately 41% of large epidemiologic studies did not address BIV identification, and existing identification methods varied considerably. Increased standardization of the identification and treatment of BIVs may aid in the comparability of study results and accurate monitoring of obesity trends.