Diabetes & metabolic syndrome · 2016
Maximum accuracy obesity indices for screening metabolic syndrome in Nigeria: A consolidated analysis of four cross-sectional studies.
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Oguoma Victor M, Nwose Ezekiel U, Ulasi Ifeoma I, Akintunde Adeseye A, Chukwukelu Ekene E, Araoye Matthew A, Edo Andrew E, Ijoma Chinwuba K, Onyia Innocent C, Ogbu Innocent I, Onyeanusi Joel C, Digban Kester A, Onodugo Obinna D, Adediran Olufemi, Opadijo Oladimeji G, Bwititi Phillip T, Richards Ross S, Skinner Timothy C
Аннотация
BACKGROUND: In sub-Saharan Africa, there is no precise use of metabolic syndrome (MetS) definitions and risk factors screening indices in many clinical and public health services. Methods proposed and used in Western populations are adopted without validation within the local settings. The aim of the study is to assess obesity indices and cut-off values that maximise screening of MetS and risk factors in the Nigerian population.
METHOD: A consolidated analysis of 2809 samples from four population-based cross-sectional study of apparently healthy persons≥18 years was carried out. Optimal waist circumference (WC) and waist-to-height ratio (WHtR) cut points for diagnosing MetS and risk factors were determined using Optimal Data Analysis (ODA) model. The stability of the predictions of the models was also assessed.
RESULTS: Overall mean values of BMI, WC and WHtR were 24.8±6.0kgm(-2), 84.0±11.3cm and 0.52±0.1 respectively. Optimal WC cut-off for discriminating MetS and diabetes was 83cm in females and 85cm in males, and 82cm in females and 89cm in males, respectively. WC was stable in discriminating diabetes than did WHtR and BMI, while WHtR showed better stability in predicting MetS than WC and BMI.
CONCLUSION: The study shows that the optimal WC that maximises classification accuracy of MetS differs from that currently used for sub-Saharan ethnicity. The proposed global WHtR of 0.50 may misclassify MetS, diabetes and hypertension. Finally, the WC is a better predictor of diabetes, while WHtR is a better predictor of MetS in this sample population.
METHOD: A consolidated analysis of 2809 samples from four population-based cross-sectional study of apparently healthy persons≥18 years was carried out. Optimal waist circumference (WC) and waist-to-height ratio (WHtR) cut points for diagnosing MetS and risk factors were determined using Optimal Data Analysis (ODA) model. The stability of the predictions of the models was also assessed.
RESULTS: Overall mean values of BMI, WC and WHtR were 24.8±6.0kgm(-2), 84.0±11.3cm and 0.52±0.1 respectively. Optimal WC cut-off for discriminating MetS and diabetes was 83cm in females and 85cm in males, and 82cm in females and 89cm in males, respectively. WC was stable in discriminating diabetes than did WHtR and BMI, while WHtR showed better stability in predicting MetS than WC and BMI.
CONCLUSION: The study shows that the optimal WC that maximises classification accuracy of MetS differs from that currently used for sub-Saharan ethnicity. The proposed global WHtR of 0.50 may misclassify MetS, diabetes and hypertension. Finally, the WC is a better predictor of diabetes, while WHtR is a better predictor of MetS in this sample population.