Monthly Key Publication Reviews

Publication: Freedman, David & Zemel, Babette & Dietz, William & Daymont, Carrie. (2024). Screening Accuracy of BMI for Adiposity Among 8- to 19-Year-Olds. Pediatrics. 154. 10.1542/peds.2024-065960. Published: March 2024

Reviewer: Wilma de Guzman-Bato, MD, DPPS, DPCMNP; Pediatrician; Adult and Pediatric Medical Nutrition Specialist; Medical Officer IV – Department of Pediatrics, Batangas Medical Center

Why is This Paper Important: Overweight and obesity are defined by the World Health Organization (WHO) as “abnormal or excessive fat accumulation that presents a risk to health”. They are part of the triple burden of malnutrition affecting children around the Philippines. Obesity puts children and adolescents at risk for serious short- and long-term adverse health outcomes later in life, including cardiovascular disease, hypertension, dyslipidemia, insulin resistance, Type 2 Diabetes Mellitus, and nonalcoholic fatty liver disease (NAFLD).

The Expanded National Nutrition Survey conducted by the Department of Science and Technology – Food and Nutrition Research Institute (FNRI) in 2019 reported that nearly one in 10 children, aged 5 to 10 years old and 10 to 19 years old respectively, are overweight. Its prevalence among Filipino adolescents significantly increased from 11.6 percent (%) in 2018 to 13 percent (%) in 2021.

Measuring Body Mass Index (BMI) and assessing weight classification is a screening step that allows the pediatrician or other healthcare workers to initiate obesity evaluation. However, the American Academy of Pediatrics (AAP) has acknowledged criticisms that BMI cannot distinguish between fat and lean mass. This study reinforces the use of BMI as the most appropriate clinical tool to screen for excess adiposity and make the clinical diagnosis of overweight or obesity.

Summary: BMI is based only on weight and height, which can be a poor indicator of adiposity among those with normal or relatively low adiposity. The limitations of BMI, such as its inability (1) to distinguish between fat and lean mass, and (2) to characterize body fat distribution, have been recognized. The study evaluated the relationship between BMI and adiposity within a contemporary cohort of 6928 8- to 19-year-olds in the United States using National Health and Nutrition Examination Survey data. A key finding is that the combination of age and BMI predicts the vast majority (90%–94%) of the variability in dual-energy x-ray absorptiometry (DXA) -measured fat mass and lean mass indexed to height within each sex.

Although BMI ≥95th percentile is associated with both increased adiposity and increased lean mass, the likelihood of increased adiposity was about twice as high as the likelihood of increased lean mass. Participants with a BMI ≥ CDC 95th percentile were 29 times more likely to have a high FMI than participants with lower BMIs. It was noted that the association between elevated BMI and increased adiposity is very strong for youth with BMI ≥95th percentile, but is not for youth with lower BMIs, including in the overweight range (BMI 90th percentile). Sex differences in the pattern of lean versus adipose tissue accretion over puberty are also redemonstrated in their analysis, where a steady increase in the fat mass index is seen only in girls across the entire age range studied, whereas a near-linear increase in lean mass index over this age range is seen only in boys.

DXA scans which is considered as a gold standard for body composition were acquired – this is one of the strengths of the study including the evaluation across the full BMI/adiposity spectrum, and inclusion of practical screening characteristics to describe associations between BMI ≥95th percentile and body composition. Limitations of the study include the cross-sectional study design, exclusion of children <8 years of age, and lack of data on regional distribution of adiposity. Several alternatives have been proposed, and many focus on waist circumference (WC). However, WC has its limitations too – it is challenging to standardize WC measurement across health care providers, it is difficult to measure WC among individuals with high BMIs, and the optimal cut points for a high waist are uncertain. Despite its limitations, a high BMI is a very good screening tool for identifying children and adolescents with elevated adiposity.¹

Commentary: Obesity is the most prevalent nutritional disorder among children and adolescents throughout the world.² Among Filipino children aged 5 to 10, overweight rates increased significantly from 10.4% in 2019 to 14% in 2022, and among adolescents aged 10 to 19, it increased from 10.7% in 2019 to 13% in 2022.³ Being underweight, overweight, or obese during childhood and adolescence is associated with adverse health consequences throughout the life-course. In particular, overweight and obesity are global health problems contributing to an increasing noncommunicable disease burden. Obesity, in addition to having disease-specific effects, may accelerate the rate of aging affecting all aspects of physiology and thus shortening life and health span.⁴

Within this context, as a Pediatrician and a Medical Nutrition Physician, I do think that there is really a need to track obesity across the lifespan which underscores the importance of primary and secondary prevention and treatment efforts early in life. These efforts include evaluating for obesity using BMI; identifying children and adolescents at high risk; providing or referring to evidence-based obesity treatments for children, youth, and their families.⁵ In our country, especially in a government setting, DXA is not available, expensive and difficult to implement. In clinical practice, BMI is frequently used as both a screening and diagnostic tool for detecting excess body fat because of its ease of use and low cost. BMI is a validated proxy measure of underlying adiposity that is replicable and can track weight status in children and adolescents.5 This study reminds us that a standardized use of BMI to identify patients with obesity is a first step. Additional risk stratification for how a specific BMI affects an individual’s health should be patient-centered and include additional data from the history and diagnostic testing. Further, treatment goals should be focused on health and quality-of-life outcomes, as opposed to a number or percentile on a growth chart.

References:

Jaime M. Moore, Stephen R. Daniels; BMI: Still Going Strong at Age 50. Pediatrics July 2024; 154 (1): e2024066370. 10.1542/peds.2024-066370
ESPGHAN Committee on Nutrition; Agostoni C, Braegger C, Decsi T, Kolacek S, Koletzko B, Mihatsch W, Moreno LA, Puntis J, Shamir R, Szajewska H, Turck D, van Goudoever J. Role of dietary factors and food habits in the development of childhood obesity: a commentary by the ESPGHAN Committee on Nutrition. J Pediatr Gastroenterol Nutr. 2011 Jun;52(6):662-9. doi: 10.1097/MPG.0b013e3182169253. PMID: 21593641.
Department of Science and Technology, Food and Nutrition Research Institution. Expanded National Nutrition Survey, 2019 and 2022.
Chourdakis M. Obesity: Assessment and prevention: Module 23.2 from Topic 23 "Nutrition in obesity". Clin Nutr ESPEN. 2020 Oct;39:1-14. doi: 10.1016/j.clnesp.2020.07.012. Epub 2020 Aug 8. PMID: 32859301.
Hampl SE, Hassink SG, Skinner AC, Armstrong SC, Barlow SE, Bolling CF, Avila Edwards KC, Eneli I, Hamre R, Joseph MM, Lunsford D, Mendonca E, Michalsky MP, Mirza N, Ochoa ER, Sharifi M, Staiano AE, Weedn AE, Flinn SK, Lindros J, Okechukwu K. Clinical Practice Guideline for the Evaluation and Treatment of Children and Adolescents With Obesity. Pediatrics. 2023 Feb 1;151(2):e2022060640. doi: 10.1542/peds.2022-060640. Erratum in: Pediatrics. 2024 Jan 1;153(1):e2023064612. doi: 10.1542/peds.2023-064612. PMID: 36622115.