Development of gender- and age group-specific equations for estimating body weight from anthropometric measurement in Thai adults
Kaweesak Chittawatanarat1,2, Sakda Pruenglampoo3, Vibul Trakulhoon4, Winai Ungpinitpong5, Jayanton Patumanond2
1Department of Surgery, Faculty of Medicine, 2Clinical Epidemiology Unit, 3Research Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand; 4Department of Surgery, Bhumibol Adulyadej Hospital, Bangkok, Thailand; 5Surgical Unit, Surin Hospital, Surin, Thailand
Background: Many medical procedures routinely use body weight as a parameter for calculation. However, these measurements are not always available. In addition, the commonly used visual estimation has had high error rates. Therefore, the aim of this study was to develop a predictive equation for body weight using body circumferences.
Methods: A prospective study was performed in healthy volunteers. Body weight, height, and eight circumferential level parameters including neck, arm, chest, waist, umbilical level, hip, thigh, and calf were recorded. Linear regression equations were developed in a modeling sample group divided by sex and age (younger <60 years and older ≥60 years). Original regression equations were modified to simple equations by coefficients and intercepts adjustment. These equations were tested in an independent validation sample.
Results: A total of 2000 volunteers were included in this study. These were randomly separated into two groups (1000 in each modeling and validation group). Equations using height and one covariate circumference were developed. After the covariate selection processes, covariate circumference of chest, waist, umbilical level, and hip were selected for single covariate equations (Sco). To reduce the body somatotype difference, the combination covariate circumferences were created by summation between the chest and one torso circumference of waist, umbilical level, or hip and used in the equation development as a combination covariate equation (Cco). Of these equations, Cco had significantly higher 10% threshold error tolerance compared with Sco (mean percentage error tolerance of Cco versus Sco [95% confidence interval; 95% CI]: 76.9 [74.2–79.6] versus 70.3 [68.4–72.3]; P < 0.01, respectively). Although simple covariate equations had more evidence errors than the original covariate equations, there was comparable error tolerance between the types of equations (original versus simple: 74.5 [71.9–77.1] versus 71.7 [69.2–74.3]; P = 0.12, respectively). The chest containing covariate (C) equation had the most appropriate performance for Sco equations (chest versus nonchest: 73.4 [69.7–77.1] versus 69.3 [67.0–71.6]; P = 0.03, respectively). For Cco equations, although there were no differences between covariates using summation of chest and hip (C+Hp) and other Cco but C+Hp had a slightly higher performance validity (C+Hp versus other Cco [95% CI]: 77.8 [73.2–82.3] versus 76.5 [72.7–80.2]; P = 0.65, respectively).
Conclusion: Body weight can be predicted by height and circumferential covariate equations. Cco had more Sco error tolerance. Original and simple equations had comparable validity. Chest- and C+Hp-containing covariate equations had more precision within the Sco and Cco equation types, respectively.
Keywords: body weight, anthropometry, circumference, Thai, linear models
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