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Published on: February 2, 2017
Predicting total fat mass from skinfold thicknesses in Japanese prepubertal children: a cross-sectional and
Taishi Midorikawa1, Megumi Ohta, Yuki Hikihara
1College of Health and Welfare, J.F. Oberlin University, Tokiwamachi, Machida, Tokyo, Japan. taishi@obirin.ac.jp
Insights
New prediction equations accurately estimate fat mass in Japanese children using skinfold thickness measurements. These regression-based equations show strong validity for field research, though they may underestimate fat mass in obese children.
Area of Science:
- Pediatric endocrinology
- Human physiology
- Anthropometry
Background:
- Accurate assessment of body composition, specifically fat mass, is crucial for monitoring child health.
- Existing methods for estimating fat mass may not be practical for large-scale field studies.
- Development of reliable, non-invasive prediction equations is needed for pediatric populations.
Purpose of the Study:
- To develop and validate regression-based prediction equations for estimating fat mass from skinfold thickness in Japanese children.
- To assess the cross-sectional and longitudinal accuracy of these developed equations.
- To evaluate the utility of skinfold-derived equations for field research in pediatric populations.
Main Methods:
- Development of prediction equations using dual-energy X-ray absorptiometry (DXA) for reference fat mass and skinfold calipers (triceps, subscapular) in 127 Japanese children (6-12 years).
- Validation of equations using cross-sectional data from a separate group and longitudinal data from a subset of subjects after one year.
- Statistical analysis included correlation and Bland-Altman analysis to assess agreement and bias.
Main Results:
- Strong correlations (R²=0.91-0.92, p<0.01) were found between DXA-measured fat mass and skinfold-derived predictions in the development group.
- The prediction equations demonstrated good agreement between measured and predicted total fat mass in both cross-sectional and longitudinal validation groups.
- Bland-Altman analysis revealed some bias in the cross-sectional validation group, and equations tended to underestimate fat mass in obese children.
Conclusions:
- Regression-based prediction equations using skinfold thickness are effective for estimating total fat mass in Japanese children.
- These equations offer a practical and valid tool for field research, particularly for non-obese children.
- Further refinement may be needed to improve accuracy for obese pediatric populations in field settings.
Abstract:
The present study was performed to develop regression based prediction equations for fat mass from skinfold thickness in Japanese children, and to investigate the cross-sectional and longitudinal validity of these equations. A total of 127 healthy Japanese prepubertal children aged 6-12 years were randomly separated into two groups: the model development group (54 boys and 44 girls) and the cross-sectional validation group (18 boys and 11 girls). Fat mass was initially determined by using DXA (Hologic Delphi A-QDR whole-body scanner) to provide reference data. Then, fat thickness was measured at triceps and subscapular using an Eiken-type skinfold calipers. Multiple anthropometric and DXA measures were obtained one year later for 28 of the original 127 subjects (longitudinal validation group: 14 boys and 14 girls). Strong significant correlations were observed between total fat mass by DXA measurement and the skinfold thickness × height measures by caliper in the model development group of boys and girls (R2=0.91-0.92, p<0.01). When these fat mass prediction equations were applied to the cross-sectional and longitudinal validation groups, the measured total fat mass was also very similar to the predicted fat mass. In addition, there were significant correlations between the measured and predicted total fat mass for boys and girls, respectively, although Bland-Altman analysis indicated a bias in cross-sectional validation group. Skinfold-derived prediction equations underestimate for obese children but are generally useful for estimating total fat mass in field research.
