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Arm Circumference-to-Height Ratio as a Situational Alternative to BMI Percentile in Assessing Obesity and Cardiometabolic Risk in Adolescents

OBJECTIVE: To determine whether arm circumference-to-height ratio (AHtR) predicts adolescents' cardiometabolic risk and how its predictive statistics compare to those of body mass index (BMI) percentile. METHODS: Pooled data for adolescents (N = 12,269, 12–18 years) from the National Health and...

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Detalles Bibliográficos
Autores principales: Jayawardene, Wasantha, Dickinson, Stephanie, Lohrmann, David, Agley, Jon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6146674/
https://www.ncbi.nlm.nih.gov/pubmed/30258656
http://dx.doi.org/10.1155/2018/7456461
Descripción
Sumario:OBJECTIVE: To determine whether arm circumference-to-height ratio (AHtR) predicts adolescents' cardiometabolic risk and how its predictive statistics compare to those of body mass index (BMI) percentile. METHODS: Pooled data for adolescents (N = 12,269, 12–18 years) from the National Health and Nutrition Examination Survey, U.S., 1999–2014, were analyzed. For each of the eight cardiometabolic variables, borderline-risk and high-risk were considered unhealthy, and being unhealthy on any variable was considered “unhealthy overall” in terms of cardiometabolic risk. Area under the curve and R (2) were used to compare BMI percentile and AHtR for accuracy in predicting risk. RESULTS: Female AHtR ≥ 0.19 and BMI percentile ≥ 94 and male AHtR ≥ 0.16 and BMI percentile ≥ 64 predicted a probability of >0.7 being unhealthy overall. AHtR predicted overall risk and unhealthy levels of six variables more accurately than BMI percentile. Significant differences were overall risk (χ (2) = 4.18; p=0.041), total cholesterol (χ (2) = 8.68; p=0.003), glycated hemoglobin (χ (2) = 5.24; p=0.022), and systolic pressure (χ (2) = 5.10; p=0.024). AHtR had higher accuracy in predicting high-density cholesterol, fasting glucose, glycated hemoglobin, and systolic/diastolic pressures plus higher specificity in predicting all variables except triglycerides. BMI percentile had higher sensitivity for all variables. Sensitivity and accuracy were higher for males. No significant race/ethnicity differences were observed. CONCLUSIONS: Without needing adjustment for age and weight, AHtR can predict some cardiometabolic risk factors of adolescents, especially of males, more accurately than BMI percentile, thus facilitating population risk estimation and early interventions. Further research is required to validate these findings in younger children.