Vithanage Pujitha Wickramasinghe, Shabina Ariff, Shane A. Norris, Ina S. Santos, Rebecca Kuriyan, Lukhanyo H. Nyati, Jithin Sam Varghese, Alexia J. Murphy-Alford, Nishani Lucas, Caroline Costa, Kiran D. K. Ahuja, S. Jayasinghe, Anura V. Kurpad, Andrew P. Hills, Multi-center Infant Body Composition Reference Study (MIBCRS)
{"title":"Anthropometric prediction models of body composition in 3 to 24month old infants: a multicenter international study","authors":"Vithanage Pujitha Wickramasinghe, Shabina Ariff, Shane A. Norris, Ina S. Santos, Rebecca Kuriyan, Lukhanyo H. Nyati, Jithin Sam Varghese, Alexia J. Murphy-Alford, Nishani Lucas, Caroline Costa, Kiran D. K. Ahuja, S. Jayasinghe, Anura V. Kurpad, Andrew P. Hills, Multi-center Infant Body Composition Reference Study (MIBCRS)","doi":"10.1038/s41430-024-01501-0","DOIUrl":null,"url":null,"abstract":"Accurate assessment of body composition during infancy is an important marker of early growth. This study aimed to develop anthropometric models to predict body composition in 3–24-month-old infants from diverse socioeconomic settings and ethnic groups. An observational, longitudinal, prospective, multi-country study of infants from 3 to 24 months with body composition assessed at three monthly intervals using deuterium dilution (DD) and anthropometry. Linear mixed modelling was utilized to generate sex-specific fat mass (FM) and fat-free mass (FFM) prediction equations, using length(m), weight-for-length (kg/m), triceps and subscapular skinfolds and South Asian ethnicity as variables. The study sample consisted of 1896 (942 measurements from 310 girls) training data sets, 941 (441 measurements from 154 girls) validation data sets of 3–24 months from Brazil, Pakistan, South Africa and Sri Lanka. The external validation group (test) comprised 349 measurements from 250 (185 from 124 girls) infants 3–6 months of age from South Africa, Australia and India. Sex-specific equations for three age categories (3–9 months; 10–18 months; 19–24 months) were developed, validated on same population and externally validated. Root mean squared error (RMSE) was similar between training, validation and test data for assessment of FM and FFM in boys and in girls. RMSPE and mean absolute percentage error (MAPE) were higher in validation compared to test data for predicting FM, however, in the assessment of FFM, both measures were lower in validation data. RMSE for test data from South Africa (M/F−0.46/0.45 kg) showed good agreement with validation data for assessment of FFM compared to Australia (M/F−0.51/0.33 kg) and India(M/F−0.77/0.80 kg). Anthropometry-based FFM prediction equations provide acceptable results. Assessments based on equations developed on similar populations are more applicable than those developed from a different population.","PeriodicalId":11927,"journal":{"name":"European Journal of Clinical Nutrition","volume":"78 11","pages":"943-951"},"PeriodicalIF":3.6000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41430-024-01501-0.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Clinical Nutrition","FirstCategoryId":"3","ListUrlMain":"https://www.nature.com/articles/s41430-024-01501-0","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
引用次数: 0
Abstract
Accurate assessment of body composition during infancy is an important marker of early growth. This study aimed to develop anthropometric models to predict body composition in 3–24-month-old infants from diverse socioeconomic settings and ethnic groups. An observational, longitudinal, prospective, multi-country study of infants from 3 to 24 months with body composition assessed at three monthly intervals using deuterium dilution (DD) and anthropometry. Linear mixed modelling was utilized to generate sex-specific fat mass (FM) and fat-free mass (FFM) prediction equations, using length(m), weight-for-length (kg/m), triceps and subscapular skinfolds and South Asian ethnicity as variables. The study sample consisted of 1896 (942 measurements from 310 girls) training data sets, 941 (441 measurements from 154 girls) validation data sets of 3–24 months from Brazil, Pakistan, South Africa and Sri Lanka. The external validation group (test) comprised 349 measurements from 250 (185 from 124 girls) infants 3–6 months of age from South Africa, Australia and India. Sex-specific equations for three age categories (3–9 months; 10–18 months; 19–24 months) were developed, validated on same population and externally validated. Root mean squared error (RMSE) was similar between training, validation and test data for assessment of FM and FFM in boys and in girls. RMSPE and mean absolute percentage error (MAPE) were higher in validation compared to test data for predicting FM, however, in the assessment of FFM, both measures were lower in validation data. RMSE for test data from South Africa (M/F−0.46/0.45 kg) showed good agreement with validation data for assessment of FFM compared to Australia (M/F−0.51/0.33 kg) and India(M/F−0.77/0.80 kg). Anthropometry-based FFM prediction equations provide acceptable results. Assessments based on equations developed on similar populations are more applicable than those developed from a different population.
期刊介绍:
The European Journal of Clinical Nutrition (EJCN) is an international, peer-reviewed journal covering all aspects of human and clinical nutrition. The journal welcomes original research, reviews, case reports and brief communications based on clinical, metabolic and epidemiological studies that describe methodologies, mechanisms, associations and benefits of nutritional interventions for clinical disease and health promotion.
Topics of interest include but are not limited to:
Nutrition and Health (including climate and ecological aspects)
Metabolism & Metabolomics
Genomics and personalized strategies in nutrition
Nutrition during the early life cycle
Health issues and nutrition in the elderly
Phenotyping in clinical nutrition
Nutrition in acute and chronic diseases
The double burden of ''malnutrition'': Under-nutrition and Obesity
Prevention of Non Communicable Diseases (NCD)