Isabel Gätjens1, Steffen Christian Ekkehard Schmidt2, Sandra Plachta-Danielzik3, Anja Bosy-Westphal4, Manfred James Müller1. 1. Institute of Human Nutrition and Food Science, Christian-Albrechts University Kiel, Kiel, Germany. 2. Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany. 3. Kompetenznetz Darmerkrankungen e.V., Kiel, Germany. 4. Institute of Human Nutrition and Food Science, Christian-Albrechts University Kiel, Kiel, Germany, abosyw@nutrition.uni-kiel.de.
Abstract
INTRODUCTION: Body composition assessment is superior to the use of body mass index (BMI) to characterize the nutritional status in pediatric populations. For data interpretation, suitable reference data are needed; hence, we aimed to generate age-dependent and sex-specific body composition reference data in a larger population of children and adolescents in Germany. METHODS: This is a cross-sectional study on a representative group of 15,392 5- to 17-year-old children and adolescents. Body composition was assessed by bioelectrical impedance analysis using a population-specific algorithm validated against air displacement plethysmography. Age- and sex-specific percentiles for BMI, fat mass index (FMI), fat-free mass index (FFMI), and a "load-capacity model" (characterized by the ratios of fat mass [FM]/ fatt-free mass [FFM] and FM/FFM2) were modeled using the LMS method. RESULTS: BMI, FMI, FFMI, FM/FFM, and FM/FFM2 curves showed similar shapes between boys and girls with steady increases in BMI, FMI, and FFMI, while FM/FFM2-centiles decreased during early childhood and adolescence. Sex differences were observed in FMI and FM/FFM percentiles with increases in FMI up to age 9 years followed by a steady decrease in FM/FFM during and after puberty with a fast-growing FFMI up to age 17 in boys. The prevalence of low FFM relative to FM reached more than 60% in overweight children and adolescents. CONCLUSION: These pediatric body composition reference data enable physicians and public health scientists to monitor body composition during growth and development and to interpret individual data. The data point out to an early risk of sarcopenia in overweight children and adolescents.
INTRODUCTION: Body composition assessment is superior to the use of body mass index (BMI) to characterize the nutritional status in pediatric populations. For data interpretation, suitable reference data are needed; hence, we aimed to generate age-dependent and sex-specific body composition reference data in a larger population of children and adolescents in Germany. METHODS: This is a cross-sectional study on a representative group of 15,392 5- to 17-year-old children and adolescents. Body composition was assessed by bioelectrical impedance analysis using a population-specific algorithm validated against air displacement plethysmography. Age- and sex-specific percentiles for BMI, fat mass index (FMI), fat-free mass index (FFMI), and a "load-capacity model" (characterized by the ratios of fat mass [FM]/ fatt-free mass [FFM] and FM/FFM2) were modeled using the LMS method. RESULTS: BMI, FMI, FFMI, FM/FFM, and FM/FFM2 curves showed similar shapes between boys and girls with steady increases in BMI, FMI, and FFMI, while FM/FFM2-centiles decreased during early childhood and adolescence. Sex differences were observed in FMI and FM/FFM percentiles with increases in FMI up to age 9 years followed by a steady decrease in FM/FFM during and after puberty with a fast-growing FFMI up to age 17 in boys. The prevalence of low FFM relative to FM reached more than 60% in overweight children and adolescents. CONCLUSION: These pediatric body composition reference data enable physicians and public health scientists to monitor body composition during growth and development and to interpret individual data. The data point out to an early risk of sarcopenia in overweight children and adolescents.
Authors: C S Yajnik; C H D Fall; K J Coyaji; S S Hirve; S Rao; D J P Barker; C Joglekar; S Kellingray Journal: Int J Obes Relat Metab Disord Date: 2003-02
Authors: S Plachta-Danielzik; B Landsberg; D Lange; K Langnäse; M J Müller Journal: Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz Date: 2011-03 Impact factor: 1.513
Authors: Mario Siervo; Carla M Prado; Emily Mire; Stephanie Broyles; Jonathan C K Wells; Steven Heymsfield; Peter T Katzmarzyk Journal: Public Health Nutr Date: 2014-09-15 Impact factor: 4.022
Authors: Milena Kobylińska; Katarzyna Antosik; Agnieszka Decyk; Katarzyna Kurowska; Diana Skiba Journal: Int J Environ Res Public Health Date: 2022-09-14 Impact factor: 4.614