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Prevention of Non Communicable Diseases

Prediction of fat mass from anthropometry at ages 7 to 9 years in Samoans: a cross-sectional study in the Ola Tuputupua’e cohort

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Abstract

Background/objective

With increasing obesity prevalence in children globally, accurate and practical methods for quantifying body fat are critical for effective monitoring and prevention, particularly in high-risk settings. No population is at higher risk of obesity than Pacific Islanders, including children living in the independent nation of Samoa. We developed and validated sex-specific prediction models for fat mass in Samoan children.

Subjects/methods

Dual X-ray absorptiometry (DXA) assessments of fat mass and weight, height, circumferences, and skinfolds were obtained from 356 children aged 7–9 years old in the Ola Tuputupua’e “Growing Up” study. Sex-specific models were developed from a randomly selected model development sample (n = 118 females, n = 120 males) using generalized linear regressions. In a validation sample (n = 59 females; n = 59 males), Lin’s concordance and Bland-Altman limits-of-agreement (LoA) of DXA-derived and predicted fat mass from this study and other published models were examined to assess precision and accuracy.

Results

Models to predict fat mass in kilograms were: e^[(−0.0034355 * Age8 − 0.0059041 * Age9 + 1.660441 * ln (Weight (kg))−0.0087281 * Height (cm) + 0.1393258 * ln[Suprailiac (mm)] − 2.661793)] for females and e^[−0.0409724 * Age8 − 0.0549923 * Age9 + 336.8575 * [Weight (kg)]−2 − 22.34261 * ln (Weight (kg)) [Weight (kg)]−1 + 0.0108696 * Abdominal (cm) + 6.811015 * Subscapular (mm)−2 − 8.642559 * ln (Subscapular (mm)) Subscapular (mm)−2 − 1.663095 * Tricep (mm)−1 + 3.849035]for males, where Age8 = Age9 = 0 for children at age 7 years, Age8 = 1 and Age9 = 0 at 8 years, Age8 = 0 and Age9 = 1 at 9 years. Models showed high predictive ability, with substantial concordance (ρC > 0.96), and agreement between DXA-derived and model-predicted fat mass (LoA female = −0.235, 95% CI:−2.924–2.453; male = −0.202, 95% CI:−1.977–1.572). Only one of four existing models, developed in a non-Samoan sample, accurately predicted fat mass among Samoan children.

Conclusions

We developed models that predicted fat mass in Samoans aged 7–9 years old with greater precision and accuracy than the majority of existing models that were tested. Monitoring adiposity in children with these models may inform future obesity prevention and interventions.

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Fig. 1: Sex-specific associations of anthropometric characteristics with fat mass derived from dual-energy X-ray absorptiometry (DXA) in Samoan children at ages 7 to 9 years (N = 356).
Fig. 2: Concordance and 95% limits of agreement between the observed fat mass using dual-energy X-ray absorptiometry and model predicted fat mass in the validation sample set of Samoan children (n = 59 females, n = 59 males).

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Data availability

Data are available upon reasonable request to the corresponding author.

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Acknowledgements

We are very grateful to the children and families who participate, as well as, our partners in the Samoa Ministry of Health, Bureau of Statistics, Ministry of Women, Community, Social Development, and the OLaGA field team (especially Vaimoana Lupematasila Filipo, Maria Siulepa Arorae, Fa’atali Tafunaina, Folla Unasa, Melania Selu, Lupesina Vesi, and Kima Savusa). Thank you to Dr. Hudda for critical advice, which contributed to the final manuscript. The Ola Tuputupua’e study received financial support from the following sources: Yale University (Faculty Funding, David Dull Internship Fund, Jan A.J. Stolwijk Fellowship Fund, Downs International Health Student Travel Fellowship, Thomas C. Barry Travel Fellowship), US National Institutes of Health (NIH) Minority and Health Disparities International Research Training Program (NIMHD T37MD008655), U.S. Fulbright Graduate Student Research Fellowship, Brown University (International Health Institute, Nora Kahn Piore Award, and Framework in Global Health Program), Brown University Population Studies and Training Center which receives funding from the NIH for training (T32 HD007338) and general support (P2C HD041020), and NIH National Lung, Health, Blood Institute for infrastructure support (R01 HL093093 and HL140570). CCC was supported by Yale-Brown Ivy Plus Exchange Program, Ruth L. Kirschstein Predoctoral Individual National Research Service Award (NIH 1F31HL147414), and the Fogarty Global Health Equity Scholars Program (FIC D43TW010540). WJ acknowledges support from the National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, which is a partnership between University Hospitals of Leicester NHS Trust, Loughborough University, and the University of Leicester.

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Author notes

  1. These authors contributed equally: Stephen T. McGarvey, Nicola L. Hawley.

Authors and Affiliations

  1. Department of Epidemiology, International Health Institute, School of Public Health, Brown University, 121 South Main Street, Providence, RI, 02906, USA

    Courtney C. Choy, Take Naseri, Stephen T. McGarvey & Nicola L. Hawley

  2. Department of Chronic Disease Epidemiology, Yale School of Public Health, 60 College Street, New Haven, CT, 06520, USA

    Courtney C. Choy & Nicola L. Hawley

  3. School of Sport, Exercise, and Health Sciences, Loughborough University, Epinal Way, Loughborough, LE11 3TU, UK

    William Johnson

  4. Institute for Physical Activity and Nutrition (IPAN), Deakin University, 221 Burwood Highway, Burwood, VIC, 3125, Australia

    Rachel L. Duckham

  5. Australian Institute for Musculoskeletal Science (AIMSS), The University of Melbourne and Western Health, 176 Furlong Road, St. Albans, VIC, 3021, Australia

    Rachel L. Duckham

  6. Ministry of Health, Ififi Street, Motootua, Apia, Samoa

    Take Naseri & Christina Soti-Ulberg

  7. Lutia i Puava ae Mapu i Fagalele, Apia, Samoa

    Muagututia S. Reupena

  8. Center for Children’s Environmental Health, Department of Epidemiology, School of Public Health, Brown University, 121 South Main Street, Providence, RI, 02906, USA

    Joseph M. Braun

  9. Department of Anthropology, Brown University, 128 Hope Street, Providence, RI, 02912, USA

    Stephen T. McGarvey

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Contributions

CCC conceptualized this project for her Ph.D. dissertation with WJ, RLD, TN, JMB, STM, and NLH. CCC analyzed the data with statistical support from WJ, interpreted data from dual x-ray absorptiometry scans with RLD, drafted the initial manuscript with guidance from STM and NLH, and revised with WJ, JMB, RLD, CSU, and TN. CCC and NLH designed the study and directed data collection with support and assistance from CSU, TN, MSR, and RLD. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Nicola L. Hawley.

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Choy, C.C., Johnson, W., Duckham, R.L. et al. Prediction of fat mass from anthropometry at ages 7 to 9 years in Samoans: a cross-sectional study in the Ola Tuputupua’e cohort. Eur J Clin Nutr 77, 495–502 (2023). https://doi.org/10.1038/s41430-022-01256-6

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