Abstract
BackgroundChildhood overweight and obesity remains high, contributing to cardiometabolic risk factors at younger ages. It is unclear which measures of adiposity serve as the best proxies for identifying children at metabolic risk. This study assessed whether DXA-derived direct measures of adiposity are more strongly related to cardiometabolic risk factors in children than indirect measures.MethodsAnthropometric and DXA measures of adiposity and a comprehensive assessment of cardiometabolic risk factors were obtained in 288, 9–12 year old girls, most being of Hispanic ethnicity. Multiple regression models for each metabolic parameter were run against each adiposity measure while controlling for maturation and ethnicity. In addition, regression models including both indirect and direct measures were developed to assess whether using direct measures of adiposity could provide a better prediction of the cardiometabolic risk factors beyond that of using indirect measures alone.ResultsMeasures of adiposity were significantly correlated with cardiometabolic risk factors (p < 0.05) except fasting glucose. After adjusting for maturation and ethnicity, indirect measures of adiposity accounted for 29-34% in HOMA-IR, 10-13% in TG, 14-17% in HDL-C, and 5-8% in LDL-C while direct measures accounted for 29-34% in HOMA-IR, 10-12% in TG, 13-16% in HDL-C, and 5-6% in LDL-C. The addition of direct measures of adiposity to indirect measures added significantly to the variance explained for HOMA-IR (p = 0.04).ConclusionAnthropometric measures may perform as well as the more precise direct DXA-derived measures of adiposity for assessing most CVD risk factors in preadolescent girls. The use of DXA-derived adiposity measures together with indirect measures may be advantageous for predicting insulin resistance risk.Trial registrationNCT02654262. Retrospectively registered 11 January 2016.
Highlights
Childhood overweight and obesity remains high, contributing to cardiometabolic risk factors at younger ages
Of the 288 girls recruited for the study, 269 girls had complete data for all variables and were used in the final analyses except for regression models with HOMA-Homeostatic model assessment of insulin resistance (IR) for which 234 girls made up the total sample due to study budgetary constraints for measuring fasting insulin levels
When comparing the addition of Dual-energy X-ray absorptiometry (DXA)-derived android fat mass, a more precise measure of regional fat to the indirect measures of regional adiposity (WC, waist-to-height ratio (WHtR)), the addition of Android fat mass added significantly to the variance explained for HOMA-IR (p = 0.01) but not to TG, high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C) (p = 0.85, 0.21, and 0.20, respectively)
Summary
Childhood overweight and obesity remains high, contributing to cardiometabolic risk factors at younger ages It is unclear which measures of adiposity serve as the best proxies for identifying children at metabolic risk. BMI has been shown to have low sensitivity for identifying children at risk for health related problems, with 38% of BMIdefined obese children not having metabolic syndrome (MetS) [6, 7]. This leads to the question as to whether BMI is an adequate measure for assessing adiposity in children and if it should continue to be used as a tool for risk stratification
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