Dataset Information

A point system to predict the future risk of obesity in 10-year-old children.

ABSTRACT:

Background

A 4-year longitudinal study was conducted to develop a model and a point system for predicting childhood obesity.

Methods

This study included 1,504 Japanese 10-year-old children who underwent health check-ups between 2011 and 2015. Multivariable logistic regression analysis was conducted using the explanatory variables overweight and lifestyle. Obesity was defined as percentage overweight (POW) ≥ 20% calculated by the following equation: (actual weight - standard weight by height and sex)/standard weight by height and sex × 100 (%). The model was validated using the Hosmer-Lemeshow test on 10-year-olds.

Results

Our prediction model for development of childhood obesity was based on seven binary variables: sex, lack of sleep, ≥2-h use of television/ games/ smartphone, hypertension, dyslipidemia, hepatic dysfunction, and being overweight. The area under the curve of the receiver operating characteristic curve was 0.803 (95% confidence interval, 0.740 to 0.866). When validated in non-obese children (n = 415), there was no significant difference between actual and predicted numbers of children with obesity (Hosmer-Lemeshow chi-square = 7.90, p = 0.18).

Conclusions

The validated prediction model and point score for obesity development were shown to be useful tools for predicting the future 4-year risk of developing obesity among 10 years-old children. The point system may be useful for reducing the occurrence of childhood obesity and promoting better health.

SUBMITTER: Sonoda R

PROVIDER: S-EPMC10149319 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

A point system to predict the future risk of obesity in 10-year-old children.

Sonoda Risa R Tokiya Mikiko M Touri Kenichi K Tanomura Yuichi Y Yada Kimihiro K Funakoshi Yayoi Y Saito Isao I

Environmental health and preventive medicine 20230101

<h4>Background</h4>A 4-year longitudinal study was conducted to develop a model and a point system for predicting childhood obesity.<h4>Methods</h4>This study included 1,504 Japanese 10-year-old children who underwent health check-ups between 2011 and 2015. Multivariable logistic regression analysis was conducted using the explanatory variables overweight and lifestyle. Obesity was defined as percentage overweight (POW) ≥ 20% calculated by the following equation: (actual weight - standard weight ...[more]

PMID: 37081623

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Dataset Information

A point system to predict the future risk of obesity in 10-year-old children.

Background

Methods

Results

Conclusions

Publications

A point system to predict the future risk of obesity in 10-year-old children.

Similar Datasets

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