Hostname: page-component-848d4c4894-xm8r8 Total loading time: 0 Render date: 2024-06-30T06:39:10.209Z Has data issue: false hasContentIssue false
  • English
  • Français

Comparison of international height and BMI-for-age growth references and their correlation with adiposity in Brazilian schoolchildren

Published online by Cambridge University Press:  23 January 2024

Mariane Helen de Oliveira Open the ORCID record for Mariane Helen de Oliveira [Opens in a new window] ,
Roberto Fernandes da Costa Open the ORCID record for Roberto Fernandes da Costa [Opens in a new window] ,
Mauro Fisberg Open the ORCID record for Mauro Fisberg [Opens in a new window] ,
Luiz Fernando Martins Kruel  and
Wolney Lisboa Conde
Mariane Helen de Oliveira*
Affiliation:
Department of Nutrition, School of Public Health, University of São Paulo, São Paulo 01246-904, Brazil
Roberto Fernandes da Costa
Affiliation:
Faculty of Health Sciences, Universidad Autónoma de Chile, Providencia, Chile
Mauro Fisberg
Affiliation:
Department of Paediatrics’, Federal University of São Paulo, São Paulo, Brazil
Luiz Fernando Martins Kruel
Affiliation:
School of Physical Education, Physiotherapy and Dance, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
Wolney Lisboa Conde
Affiliation:
Department of Nutrition, School of Public Health, University of São Paulo, São Paulo 01246-904, Brazil
*
*Corresponding author: Mariane Helen de Oliveira, email marianehelen@alumni.usp.br
Get access Rights & Permissions [Opens in a new window]

Abstract

This study verified the diagnostic accuracy of the nutritional status classified by the international height and BMI references of the World Health Organization (WHO) (WHO/2007), International Obesity Task Force (IOTF/2012) and MULT (2023). The data pool was composed by 22 737 subjects aged five to 16 years from the Santos and Porto Alegre surveys. A correlation matrix between the z-scores of the BMI references and the skinfold measurements was calculated through the Pearson correlation coefficient (r), and the subject’s nutritional status was classified according to the international growth references. The accuracy for diagnosing obesity was performed separately by sex and using the 95th percentile of the triceps and subscapular skinfold sum, while Lin’s concordance coefficient, Bland–Altman method and the Cohen’s Kappa coefficient (Kappa) were used to verify the concordance and reliability among the BMI references. The correlation matrix showed a high positive correlation among the BMI z-scores (r ≥ 0·99) and among the skinfold measurements (r ≥ 0·86). The prevalence of stunting was higher when applying the MULT reference (3·4 %) compared with the WHO reference (2·3 %). The Bland–Altman plots showed the lowest critical difference (CD) between the height references of WHO and MULT (CD = 0·22). Among the BMI references, the WHO obesity percentile presented lower performance than MULT for boys, presenting a lower +LR value (WHO = 6·99/MULT 18 years = 10·99; 19 years = 8·99; 20 years = 8·09) for the same −LR values (0·04). Therefore, MULT reference holds promise as a valuable tool for diagnosing childhood obesity, particularly when considering sex differences. This enhances its suitability for assessing the nutritional status of Brazilian schoolchildren.

Keywords

ChildAdolescentNutrition AssessmentStature by AgeBMI
Type
Research Article
Information
British Journal of Nutrition , Volume 131 , Issue 10 , 28 May 2024 , pp. 1699 - 1708
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of The Nutrition Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Development Initiatives (2018) Global Nutrition Report: Shining a Light to Spur Action on Nutrition. Bristol: Development Initiatives.Google Scholar
United Nations Children’s Fund, World Health Organization & International Bank for Reconstruction and Development/The World Bank (2023) Levels and Trends in Child Malnutrition: Key Findings of the 2021 Edition of the Joint Child Malnutrition Estimates. Geneva: World Health Organization.Google Scholar
Conde, WL & Monteiro, CA (2014) Nutrition transition and double burden of undernutrition and excess of weight in Brazil. Am J Clin Nutr 100, S1617–S1622.CrossRefGoogle ScholarPubMed
Juhola, J, Magnussen, CG, Viikari, JSA, et al. (2011) Tracking of serum lipid levels, blood pressure, and body mass index from childhood to adulthood: the cardiovascular risk in young Finns study. J Pediatr 159, 584–590.CrossRefGoogle ScholarPubMed
Bentham, J, Di Cesare, M, Bilano, V, et al. (2017) 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 390, 2627–2642.Google Scholar
Costa, RF, Santos, NS, Goldraich, NP, et al. (2012) Metabolic syndrome in obese adolescents: a comparison of three different diagnostic criteria. J Pediatr (Rio J) 88, 303–309.Google ScholarPubMed
Ward, ZJ, Long, MW, Resch, SC, et al. (2017) Simulation of growth trajectories of childhood obesity into adulthood. N Engl J Med 377, 2145–2153.CrossRefGoogle ScholarPubMed
Cunningham, SA, Kramer, MR & Narayan, KMV (2014) Incidence of childhood obesity in the United States. N Engl J Med 370, 403–411.CrossRefGoogle ScholarPubMed
Tran, MK, Krueger, PM, McCormick, E, et al. (2016) Body mass transitions through childhood and early adolescence: a multistate life table approach. Am J Epidemiol 183, 643–649.CrossRefGoogle ScholarPubMed
De Oliveira, MH, Dos Santos Pereira, D, Melo, DS, et al. (2022) Accuracy of international growth charts to assess nutritional status in children and adolescents: a systematic review. Rev Paul Pediatr 40, e2021016.CrossRefGoogle Scholar
Ferreira, AA (2012) Evaluation of the growth of children: path of the growth charts. Demetra (Rio J) 7, 191–202.Google Scholar
Saari, A, Sankilampi, U, Hannila, ML, et al. (2011) New Finnish growth references for children and adolescents aged 0–20 years: length/height-for-age, weight-for-length/height, and body mass index-for-age. Ann Med 43, 235–248.CrossRefGoogle ScholarPubMed
De Oliveira, MH, Araújo, J, Ramos, E, et al. (2023) MULT: new height references and their efficiency in multi-ethnic populations. Am J Hum Biol 35, e23859.CrossRefGoogle ScholarPubMed
De Oliveira, MH, Araújo, J, Severo, M, et al. (2023) MULT: a new BMI reference to assess nutritional status of multi-ethnic children and adolescents. Am J Hum Biol 35, e23946.CrossRefGoogle Scholar
WHO Multicentre Growth Reference Study Group (2006) WHO Child Growth Standards: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age - methods and development. Acta Paediatr Suppl 450, 76–85.Google Scholar
De Onis, M, Onyango, AW, Borghi, E, et al. (2007) Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ 85, 660–667.CrossRefGoogle ScholarPubMed
Cole, TJ & Lobstein, T (2012) Extended international (IOTF) body mass index cut-offs for thinness, overweight and obesity. Pediatr Obes 7, 284–294.CrossRefGoogle ScholarPubMed
Cole, TJ, Bellizzi, MC, Flegal, KM, et al. (2000) Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 320, 1–6.CrossRefGoogle ScholarPubMed
Kuczmarski, RJ, Ogden, CL, Guo, SS, et al. (2002) 2000 CDC Growth Charts for the United States: methods and development. Vital Health Stat 266, 1–190.Google Scholar
Birch, L, Perry, R, Hunt, LP, et al. (2019) What change in body mass index is associated with improvement in percentage body fat in childhood obesity? A meta-regression. BMJ Open 9, e028231.CrossRefGoogle ScholarPubMed
Costa, RF, Cintra, ID & Fisberg, M (2006) Prevalence of overweight and obesity in school children of Santos city, Brazil. Arq Bras Endocrinol Metabol 50, 60–67.CrossRefGoogle ScholarPubMed
Careno, MF, Silva, JP & Martins, MCB (2015) African and Afro-Brazilian presence in the baixada Santista region. Simpósio Int Ciências Integradas 1–7.Google Scholar
Instituto de Pesquisa Econômica Aplicada (IPEA) (2011) Profile of migrants in São Paulo. Brasilia: IPEA.Google Scholar
Guerreiro-Junior, VF (2007) From Porto dos Casais to Porto Alegre: The demographic and evolutionary trajectory of a city revealed through uniparental genetic markers.[Master's Thesis]. Federal University of Rio Grande do Sul, 1–88.Google Scholar
WHO Expert Committee (1995) Physical Status: The Use and Interpretation of Anthropometry. WHO Library Cataloguing. Geneva: WHO.Google Scholar
Pearson, K, Fisher, RA & Inman, HF (1994) Fisher on statistical tests: a 1935 exchange from nature. Am Stat 48, 2–11.CrossRefGoogle Scholar
De Quadros, TMB, Gordia, AP, Andaki, ACR, et al. (2019) Utility of anthropometric indicators to screen for clustered cardiometabolic risk factors in children and adolescents. J Pediatr Endocrinol Metab 32, 49–55.CrossRefGoogle ScholarPubMed
Tang, HK, Bowe, SJ, Nguyen, THHD, et al. (2020) Triceps and subscapular skinfold thickness percentiles of a school-based sample of adolescents in Ho Chi Minh City, Vietnam. Eur J Clin Nutr 74, 1483–1487.CrossRefGoogle ScholarPubMed
Van Stralen, KJ, Stel, VS, Reitsma, JB, et al. (2009) Diagnostic methods I: sensitivity, specificity, and other measures of accuracy. Kidney Int 75, 1257–1263.CrossRefGoogle ScholarPubMed
Lin, LIK (1989) A concordance correlation coefficient to evaluate reproducibility. Biom J 45, 255.Google ScholarPubMed
Cohen, J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20, 37–46.CrossRefGoogle Scholar
Cohen, J (1968) Weighted Kappa: nominal scale agreement with provision for scaled disagreement for partial credit. Psychol Bull 70, 213–220.CrossRefGoogle ScholarPubMed
Bland, MJ & Altman, DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 327, 307–310.CrossRefGoogle Scholar
Loomba-Albrecht, LA & Styne, DM (2009) Effect of puberty on body composition. Curr Opin Endocrinol Diabetes Obes 16, 10–15.CrossRefGoogle ScholarPubMed
R Core Team (2022) R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing.Google Scholar
Rosario, AS, Schienkiewitz, A & Neuhauser, H (2011) German height references for children aged 0 to under 18 years compared to WHO and CDC growth charts. Ann Hum Biol 38, 121–130.CrossRefGoogle Scholar
Hughes, I, Harris, M, Cotterill, A, et al. (2014) Comparison of Centers for Disease Control and Prevention and World Health Organization references/standards for height in contemporary Australian children: analyses of the Raine Study and Australian National Children’s Nutrition and Physical Activity cohorts. J Paediatr Child Health 50, 895–901.CrossRefGoogle ScholarPubMed
Bonthuis, M, Van Stralen, KJ, Verrina, E, et al. (2012) Use of national and international growth charts for studying height in European children: development of up-to-date European height-for-age charts. PLoS One 7, 1–11.CrossRefGoogle ScholarPubMed
NCD Risk Factor Collaboration (NCD-RisC) (2020) Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants. Lancet 396, 1511–1524.CrossRefGoogle Scholar
World Health Organization (2018) Reducing Stunting in Children: Equity Considerations for Achieving the Global Nutrition Targets 2025. Geneva: WHO.Google Scholar
Aristizabal, JC, Barona, J, Hoyos, M, et al. (2015) Association between anthropometric indices and cardiometabolic risk factors in pre-school children. BMC Pediatr 15, 170.CrossRefGoogle ScholarPubMed
Hastuti, J, Rahmawati, NT, Suriyanto, RA, et al. (2020) Patterns of Body Mass Index, percentage body fat, and skinfold thicknesses in 7- to 18-year-old children and adolescents from Indonesia. Int J Prev Med 11, 129.CrossRefGoogle ScholarPubMed
Etchison, WC, Bloodgood, EA, Minton, CP, et al. (2011) Body mass index and percentage of body fat as indicators for obesity in an adolescent athletic population. Sports Health 3, 249–252.CrossRefGoogle Scholar
Moselakgomo, KV & Van Staden, M (2017) Diagnostic comparison of Centers for Disease Control and Prevention and International Obesity Task Force criteria for obesity classification in South African children. Afr J Prim Health Care Fam Med 9, e1–7.CrossRefGoogle ScholarPubMed
El Mouzan, MI, Al Herbish, AS, Al Salloum, AA, et al. (2008) Comparison of the 2005 growth charts for Saudi children and adolescents to the 2000 CDC growth charts. Ann Saudi Med 28, 334–340.CrossRefGoogle Scholar
Kêkê, LM, Samouda, H, Jacobs, J, et al. (2015) Body mass index and childhood obesity classification systems: a comparison of the French, International Obesity Task Force (IOTF) and World Health Organization (WHO) references. Rev Epidemiol Sante Publique 63, 173–182.CrossRefGoogle ScholarPubMed
Eknoyan, G (2008) Adolphe Quetelet (1796–1874) – The average man and indices of obesity. Nephrol Dial Transplant 23, 47–51.CrossRefGoogle ScholarPubMed
De Oliveira, MH, Araújo, J, Severo, M, et al. (2023) Accuracy of the international growth charts to diagnose obesity according to the body composition analysis in US children and adolescents [Unpublished manuscript]. University of São Paulo, 1–25.Google Scholar