Body mass index vs deuterium dilution method for establishing childhood obesity prevalence, Ghana, Kenya, Mauritius, Morocco, Namibia, Senegal, Tunisia and United Republic of Tanzania

Diouf, Adama and Adom, Theodosia and Aouidet, Abdel and El Hamdouchi, Asmaa and Joonas, Noorjehan I and Loechl, Cornelia U and Leyna, Germana H and Mbithe, Dorcus and Moleah, Thabisile and Monyeki, Andries and Nashandi, Hilde Liisa and Somda, Serge MA and Reilly, John J (2018) Body mass index vs deuterium dilution method for establishing childhood obesity prevalence, Ghana, Kenya, Mauritius, Morocco, Namibia, Senegal, Tunisia and United Republic of Tanzania. Bulletin of the World Health Organization, 96. pp. 772-781. ISSN 1564-0604 (https://doi.org/10.2471/BLT.17.205948)

[thumbnail of Diouf-etal-WHO-2018-Body-mass-index-vs-deuterium-dilution-method-for-establishing-childhood-obesity-prevalence]
Preview
Text. Filename: Diouf_etal_WHO_2018_Body_mass_index_vs_deuterium_dilution_method_for_establishing_childhood_obesity_prevalence.pdf
Final Published Version
License: Creative Commons Attribution 3.0 logo

Download (1MB)| Preview

Abstract

Objective -- To compare the World Health Organization (WHO) body mass index (BMI)-for-age definition of obesity against measured body fatness in African children. Methods -- In a prospective multicentre study over 2013 to 2017, we recruited 1516 participants aged 8 to 11 years old from urban areas of eight countries (Ghana, Kenya, Mauritius, Morocco, Namibia, Senegal, Tunisia and United Republic of Tanzania). We measured height and weight and calculated BMI-for-age using WHO standards. We measured body fatness using the deuterium dilution method and defined excessive body fat percentage as > 25% in boys and > 30% in girls. We calculated the sensitivity and specificity of BMI z-score > +2.00 standard deviations (SD) and used receiver operating characteristic analysis and the Youden index to determine the optimal BMI z-score cut-off for classifying excessive fatness. Findings -- The prevalence of excessive fatness was over three times higher than BMI-for-age-defined obesity: 29.1% (95% CI: 26.8 to 31.4; 441 children) versus 8.8% (95% CI: 7.5 to 10.4; 134 children). The sensitivity of BMI z-score > +2.00 SD was low (29.7%, 95% CI: 25.5 to 34.2) and specificity was high (99.7%, 95% CI: 99.2 to 99.9). The receiver operating characteristic analysis found that a BMI z-score +0.58 SD would optimize sensitivity, and at this cut-off the area under the curve was 0.86, sensitivity 71.9% (95% CI: 67.4 to 76.0) and specificity 91.1% (95% CI: 89.2 to 92.7). Conclusion -- While BMI remains a practical tool for obesity surveillance, it underestimates excessive fatness and this should be considered when planning future African responses to the childhood obesity pandemic.