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

World Bank Group. Non-Communicable Disease (NCD) Roadmap Report (English) Washington, DC: World Bank Group; 2014. http://documents.worldbank.org/curated/en/534551468332387599/Non-Communicable-Disease-NCD-Roadmap-Report. Accessed 25 Mar 2018.

NCD Risk Factor Collaboration (NCD RisC). Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128.9 million children, adolescents, and adults. Lancet. 2017;390:2627–42.

Article  Google Scholar 

Simmonds M, Llewellyn A, Owen CG, Woolacott N. Predicting adult obesity from childhood obesity: a systematic review and meta‐analysis. Obes Rev. 2016;17:95–107.

Article  Google Scholar 

Borga M, West J, Bell JD, Harvey NC, Romu T, Heymsfield SB, et al. Advanced body composition assessment: from body mass index to body composition profiling. J Investig Med. 2018;66:1–9.

Article  Google Scholar 

Fields DA, Goran MI. Body composition techniques and the four-compartment model in children. J Appl Physiol. 2000;89:613–20.

Article  Google Scholar 

Tyrrell V, Richards G, Hofman P, Gillies G, Robinson E, Cutfield W. Obesity in Auckland school children: a comparison of the body mass index and percentage body fat as the diagnostic criterion. Int J Obes. 2001;25:164–9.

Article  Google Scholar 

Wong MC, Ng BK, Kennedy SF, Hwaung P, Liu EY, Kelly NN, et al. Children and adolescents’ anthropometrics body composition from 3‐D optical surface scans. Obesity. 2019;27:1738–49.

Article  Google Scholar 

Rush EC, Puniani K, Valencia M, Davies P, Plank L. Estimation of body fatness from body mass index and bioelectrical impedance: comparison of New Zealand European, Maori and Pacific Island children. Eur J Clin Nutr. 2003;57:1394–401.

Article  Google Scholar 

NCD RisC. Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight. Elife 2021;10:e60060.

Article  Google Scholar 

Slaughter MH, Lohman TG, Boileau R, Horswill C, Stillman R, Van Loan M, et al. Skinfold equations for estimation of body fatness in children and youth. Hum Biol. 1988;60:709–23.

Goran MI, Driscoll P, Johnson R, Nagy TR, Hunter G. Cross-calibration of body-composition techniques against dual-energy X-ray absorptiometry in young children. Am J Clin Nutr. 1996;63:299–305.

Article  Google Scholar 

Dezenberg CV, Nagy TR, Gower BA, Johnson R, Goran MI. Predicting body composition from anthropometry in pre-adolescent children. Int J Obes. 1999;23:253–9.

Article  Google Scholar 

Hudda MT, Fewtrell MS, Haroun D, Lum S, Williams JE, Wells JC, et al. Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data. BMJ. 2019;366:l4293.

Duncan JS, Duncan EK, Schofield G. Ethnic-specific body mass index cut-off points for overweight and obesity in girls. NZ Med J. 2010;123:22–9.

Google Scholar 

Thompson AA, Duckham RL, Desai MM, Choy CC, Sherar LB, Naseri T, et al. Sex differences in the associations of physical activity and macronutrient intake with child body composition: A cross‐sectional study of 3‐to 7‐year‐olds in Samoa. Pediatr Obes. 2020;15:e12603.

Article  Google Scholar 

Samoa Bureau of Statistics. Samoa Demographic and Health Survey. Apia, Samoa: Samoa Bureau of Statistics, Government of Samoa, 2014.

The World Bank. Samoa: Databank Washington, DC: The World Bank Group; 2022. https://data.worldbank.org/country/samoa.

Central Intelligence Agency. The World FactBook: Samoa. https://www.cia.gov/the-world-factbook/countries/samoa/. Accessed 6 May 2022.

Troubat N, Faaloa E, Aliyeva R. The State of Food Security and Nutrition in Samoa, based on the analysis of the 2018 Household Income and Expenditure Survey. Apia, Samoa, FAO 2020.

Choy CC, Desai MM, Park JJ, Frame EA, Thompson AA, Naseri T, et al. Child, maternal and household-level correlates of nutritional status: a cross-sectional study among young Samoan children. Public health Nutr. 2017;20:1235–47.

Article  Google Scholar 

Cameron N, Schell L. Human growth and development. Academic Press, 2021.

Rush E, Tautolo el S, Paterson J, Obolonkin V. Pacific Islands Families Study: signs of puberty are associated with physical growth at ages 9 and 11 years. NZ Med J. 2015;128:24–33.

Google Scholar 

Cole TJ, Pan H, Butler GE. A mixed effects model to estimate timing and intensity of pubertal growth from height and secondary sexual characteristics. Ann Hum Biol. 2014;41:76–83.

Article  Google Scholar 

Roubenoff R, Kehayias JJ, Dawson-Hughes B, Heymsfield SB. Use of dual-energy x-ray absorptiometry in body-composition studies: not yet a “gold standard”. Am J Clin Nutr. 1993;58:589–91.

Article  Google Scholar 

Onis MD, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85:660–7.

Article  Google Scholar 

World Health Organization (WHO). Waist circumference and waist-hip ratio: report of a WHO expert consultation, Geneva, 8–11 December 2008. 2011.

Callaway C, Chumlea W, Bouchard C, Himes J, Lohman T, Martin A, et al. Circumferences anthropometric standardization reference manual. Human Kinetics Books: Champaign, IL, 1988, p. 39–54.

Almeida SM, Furtado JM, Mascarenhas P, Ferraz ME, Silva LR, Ferreira JC, et al. Anthropometric predictors of body fat in a large population of 9‐year‐old school‐aged children. Obes Sci Pract. 2016;2:272–81.

Article  Google Scholar 

Royston P, Sauerbrei W. Multivariable model-building: a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables. John Wiley & Sons; 2008.

Royston P, Altman DG. Regression using fractional polynomials of continuous covariates: parsimonious parametric modelling. J R Stat Soc: Ser C (Appl Stat). 1994;43:429–53.

Google Scholar 

Steichen TJ, Cox NJ. A note on the concordance correlation coefficient. Stata J. 2002;2:183–9.

Article  Google Scholar 

Lawrence I, Lin K. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 1989;45:255–68.

Bland JM, Altman D. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;327:307–10.

Article  Google Scholar 

McBride G. A proposal for strength-of-agreement criteria for Lin’s concordance correlation coefficient. NIWA client report: HAM2005-062 2005;62.

Amrhein V, Greenland S, McShane B. Scientists rise up against statistical significance. Nature Publishing Group, 2019.

Smith G. Multiple regression. In: Smith G (ed). Essential statistics, regression, and econometrics. Academic Press: Boston, 2015, p. 297–331.

Popkin BM, Gordon-Larsen P. The nutrition transition: worldwide obesity dynamics and their determinants. Int J Obes Relat Metab Disord : J Int Assoc Study Obes. 2004;28:S2–9.

Article  Google Scholar 

Popkin BM, Adair LS, Ng SW. Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev. 2012;70:3–21.

Article  Google Scholar 

Jin B, Lin H, Yuan J, Dong G, Huang K, Wu W, et al. Abdominal adiposity and total body fat as predictors of cardiometabolic health in children and adolescents with obesity. Front Endocrinol. 2020;11:579.

Article  Google Scholar 

Ellis K. Measuring body fatness in children and young adults: comparison of bioelectric impedance analysis, total body electrical conductivity, and dual-energy X-ray absorptiometry. Int J Obes Relat Metab Disord: J Int Assoc Study Obes. 1996;20:866–73.

Google Scholar 

Cole TJ, Fewtrell MS, Prentice A. The fallacy of using percentage body fat as a measure of adiposity. Am J Clin Nutr. 2008;87:1959–1959.

Article  Google Scholar 

Cameron N, Griffiths PL, Wright MM, Blencowe C, Davis NC, Pettifor JM, et al. Regression equations to estimate percentage body fat in African prepubertal children aged 9 y. Am J Clin Nutr. 2004;80:70–5.

Article  Google Scholar 

L’Abée C, Visser GH, Liem ET, Kok DE, Sauer PJ, Stolk RP. Comparison of methods to assess body fat in non-obese six to seven-year-old children. Clin Nutr. 2010;29:317–22.

Article  Google Scholar 

Hudda MT, Wells JC, Adair LS, Alvero-Cruz JR, Ashby-Thompson MN, Ballesteros-Vásquez MN, et al. External validation of a prediction model for estimating fat mass in children and adolescents in 19 countries: individual participant data meta-analysis. BMJ. 2022;378:e071185.

Stomfai S, Ahrens W, Bammann K, Kovacs E, Mårild S, Michels N, et al. Intra-and inter-observer reliability in anthropometric measurements in children. Int J Obes. 2011;35:S45–51.

Article  Google Scholar 

Pacific Community (SPC). Pacific Noncommunicable Disease Summit: Translating global and regional commitments into local action (20–22 June 2016, Tonga) summit report. SPC: Noumea, New Caledonia, 2016.

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