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Accepted manuscript

Comparison of BMI, triponderal mass index, and paediatric body adiposity Index for predicting body fat and screening obesity in preschool children

Published online by Cambridge University Press:  11 November 2024

Yimin Wang
Affiliation:
School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, People’s Republic of China.
Ke Xu
Affiliation:
School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, People’s Republic of China.
Miyuan Wang
Affiliation:
School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, People’s Republic of China.
Paiziyetia
Affiliation:
School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, People’s Republic of China.
Wenli Dong
Affiliation:
School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, People’s Republic of China.
Mengna Wei
Affiliation:
School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, People’s Republic of China.
Yanfen Jiang
Affiliation:
School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, People’s Republic of China.
Wenqi Xia
Affiliation:
School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, People’s Republic of China.
Jiameng Zhou
Affiliation:
School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, People’s Republic of China.
Jianduan Zhang*
Affiliation:
School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, Hubei, 430030, People’s Republic of China.
*
Address correspondence to: Jianduan Zhang, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China [[email protected]], 027-83657956.
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Abstract

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Several novel anthropometric indices, including paediatric body adiposity index (BAIp) and triponderal mass index (TMI), have emerged as potential tools for estimating body fat in preschool children. However, their comparative validity and accuracy, particularly when compared to established indicators such as Body Mass Index (BMI), have not been thoroughly investigated. This cross-sectional study enrolled 2869 preschoolers aged 3-6 years in Wuhan, China. The nonparametric Bland–Altman analysis was employed to evaluate the agreement between BMI, BAIp, and TMI with percentage of body fat (PBF), determined by bioimpedance analysis (BIA), serving as the reference measure of adiposity. Additionally, Receiver Operating Characteristic Curve (ROC) analysis was conducted to assess the effectiveness of BMI, BAIp, and TMI in screening for obesity. BAIp demonstrated the least bias in estimating PBF, showing discrepancies of 3.64% (95%CI: 3.40% to 4.12%) in boys and 3.95% (95%CI: 3.79% to 4.23%) in girls. Conversely, BMI underestimated PBF by 3.89% (95%CI: 3.70% to 4.37%)in boys and 4.81% (95%CI: 4.59% to 5.09%) in girls, while TMI also underestimated PBF by 5.15% (95%CI: 4.90% to 5.52%) in boys and 5.68% (95%CI: 5.30% to 5.91%) in girls. BAIp exhibited the highest area under the curve (AUC) values (AUC=0.867-0.996) in boys, whereas in girls, there was no statistically significant difference between BMI (AUC = 0.936, 95% CI: 0.921-0.948) and BAIp(AUC = 0.901, 95% CI 0.883-0.916) in girls (P=0.054). In summary, when considering the identification of obesity, BAIp shows promise as a screening tool for both boys and girls.

Type
Research Article
Copyright
© The Authors 2024