Eva Craig1, John Reilly, Ruth Bland. 1. 1 Section of Human Nutrition, University of Glasgow, Yorkhill Hospitals, QMH Tower 1st Floor, Dalnair Street, Glasgow G3 8SJ, UK.
Abstract
OBJECTIVE: A variety of methods are available for defining undernutrition (thinness/underweight/under-fat) and overnutrition (overweight/obesity/over-fat). The extent to which these definitions agree is unclear. The present cross-sectional study aimed to assess agreement between widely used methods of assessing nutritional status in children and adolescents, and to examine the benefit of body composition estimates. DESIGN: The main objective of the cross-sectional study was to assess underweight, overweight and obesity using four methods: (i) BMI-for-age using WHO (2007) reference data; (ii) BMI-for-age using Cole et al. and International Obesity Taskforce cut-offs; (iii) weight-for-age using the National Centre for Health Statistics/WHO growth reference 1977; and (iv) body fat percentage estimated by bio-impedance (body fat reference curves for children of McCarthy et al., 2006). Comparisons were made between methods using weighted kappa analyses. SETTING: Rural South Africa. SUBJECTS: Individuals (n 1519) in three age groups (school grade 1, mean age 7 years; grade 5, mean age 11 years; grade 9, mean age 15 years). RESULTS: In boys, prevalence of unhealthy weight status (both under- and overnutrition) was much higher at all ages with body fatness measures than with simple anthropometric proxies for body fatness; agreement between fatness and weight-based measures was fair or slight using Landis and Koch categories. In girls, prevalence of unhealthy weight status was also higher with body fatness than with proxies, although agreement between measures ranged from fair to substantial. CONCLUSIONS: Methods for defining under- and overnutrition should not be considered equivalent. Weight-based measures provide highly conservative estimates of unhealthy weight status, possibly more conservative in boys. Simple body composition measures may be more informative than anthropometry for nutritional surveillance of children and adolescents.
OBJECTIVE: A variety of methods are available for defining undernutrition (thinness/underweight/under-fat) and overnutrition (overweight/obesity/over-fat). The extent to which these definitions agree is unclear. The present cross-sectional study aimed to assess agreement between widely used methods of assessing nutritional status in children and adolescents, and to examine the benefit of body composition estimates. DESIGN: The main objective of the cross-sectional study was to assess underweight, overweight and obesity using four methods: (i) BMI-for-age using WHO (2007) reference data; (ii) BMI-for-age using Cole et al. and International Obesity Taskforce cut-offs; (iii) weight-for-age using the National Centre for Health Statistics/WHO growth reference 1977; and (iv) body fat percentage estimated by bio-impedance (body fat reference curves for children of McCarthy et al., 2006). Comparisons were made between methods using weighted kappa analyses. SETTING: Rural South Africa. SUBJECTS: Individuals (n 1519) in three age groups (school grade 1, mean age 7 years; grade 5, mean age 11 years; grade 9, mean age 15 years). RESULTS: In boys, prevalence of unhealthy weight status (both under- and overnutrition) was much higher at all ages with body fatness measures than with simple anthropometric proxies for body fatness; agreement between fatness and weight-based measures was fair or slight using Landis and Koch categories. In girls, prevalence of unhealthy weight status was also higher with body fatness than with proxies, although agreement between measures ranged from fair to substantial. CONCLUSIONS: Methods for defining under- and overnutrition should not be considered equivalent. Weight-based measures provide highly conservative estimates of unhealthy weight status, possibly more conservative in boys. Simple body composition measures may be more informative than anthropometry for nutritional surveillance of children and adolescents.
Authors: Makama Andries Monyeki; Adedapo Awotidebe; Gert L Strydom; J Hans de Ridder; Ramoteme Lesly Mamabolo; Han C G Kemper Journal: Int J Environ Res Public Health Date: 2015-01-22 Impact factor: 3.390
Authors: Theodosia Adom; André Pascal Kengne; Anniza De Villiers; Rose Boatin; Thandi Puoane Journal: Int J Environ Res Public Health Date: 2019-12-19 Impact factor: 3.390