OBJECTIVES: (1) To examine the validity of existing prediction equations (PREE) for estimating resting energy expenditure (REE) in obese Chinese children, (2) to correlate the measured REE (MREE) with anthropometric and biochemical parameters and (3) to derive a new PREE for local use. DESIGN: Cross-sectional study. SUBJECTS: 100 obese children (71 boys) were studied. MEASUREMENTS: All subjects underwent physical examination and anthropometric measurement. Upper and central body fat distribution was signified by centrality and conicity index respectively, and REE was measured by indirect calorimetry. Fat free mass (FFM) were measured by DEXA scan. Thirteen existing prediction equations for estimating REE were compared with MREE among these obese children. Fasting blood for glucose, lipid profile and insulin were obtained. RESULTS: The overall, male and female median MREEs were 7.1 mJ/d (IR 6.2-8.4), 7.3 mJ/d (IR 6.3-9.7) and 6.9 mJ/d (IR 5.6-8.1) respectively. No sex difference was noted in MREE (p=0.203). Most of the equations except Schofield equation underestimated REE of our children. By multiple linear regression, MREE was positively correlated with FFM (p<0.0001), conicity index (p<0.001) and centrality index (p=0.001). A new equation for estimating REE for local use was derived as: REE=(17.4*logFFM)+(11.4*conicity index)-(2.4*centrality index)-31.3. The mean difference of new PREE-MREE was -0.011 mJ/d (SD 1.51) with an interclass correlation coefficient of 0.91. CONCLUSION: None of the existing prediction equations were accurate in their estimation of REE, when applied to obese Chinese children. A new prediction equation has been derived for local use.
OBJECTIVES: (1) To examine the validity of existing prediction equations (PREE) for estimating resting energy expenditure (REE) in obese Chinese children, (2) to correlate the measured REE (MREE) with anthropometric and biochemical parameters and (3) to derive a new PREE for local use. DESIGN: Cross-sectional study. SUBJECTS: 100 obesechildren (71 boys) were studied. MEASUREMENTS: All subjects underwent physical examination and anthropometric measurement. Upper and central body fat distribution was signified by centrality and conicity index respectively, and REE was measured by indirect calorimetry. Fat free mass (FFM) were measured by DEXA scan. Thirteen existing prediction equations for estimating REE were compared with MREE among these obesechildren. Fasting blood for glucose, lipid profile and insulin were obtained. RESULTS: The overall, male and female median MREEs were 7.1 mJ/d (IR 6.2-8.4), 7.3 mJ/d (IR 6.3-9.7) and 6.9 mJ/d (IR 5.6-8.1) respectively. No sex difference was noted in MREE (p=0.203). Most of the equations except Schofield equation underestimated REE of our children. By multiple linear regression, MREE was positively correlated with FFM (p<0.0001), conicity index (p<0.001) and centrality index (p=0.001). A new equation for estimating REE for local use was derived as: REE=(17.4*logFFM)+(11.4*conicity index)-(2.4*centrality index)-31.3. The mean difference of new PREE-MREE was -0.011 mJ/d (SD 1.51) with an interclass correlation coefficient of 0.91. CONCLUSION: None of the existing prediction equations were accurate in their estimation of REE, when applied to obese Chinese children. A new prediction equation has been derived for local use.
Authors: Kiymet Bozaoglu; Chantal Attard; Hemant Kulkarni; Nik Cummings; Vincent P Diego; Melanie A Carless; Katherine A Shields; Matthew P Johnson; Sudhir Kowlessur; Thomas D Dyer; Anthony G Comuzzie; Laura Almasy; Paul Zimmet; Eric K Moses; Harald H H Göring; Joanne E Curran; John Blangero; Jeremy B M Jowett Journal: J Clin Endocrinol Metab Date: 2014-06-10 Impact factor: 5.958
Authors: Jimena Fuentes-Servín; Azalia Avila-Nava; Luis E González-Salazar; Oscar A Pérez-González; María Del Carmen Servín-Rodas; Aurora E Serralde-Zuñiga; Isabel Medina-Vera; Martha Guevara-Cruz Journal: Front Pediatr Date: 2021-12-06 Impact factor: 3.418