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
School of Psychological and Clinical Sciences, Charles Darwin University, Northern Territory, Australia.
School of Community Health, Charles Sturt University, New South Wales, Australia; Department of Public and Community Health, Novena University Ogume, Delta State, Nigeria.
Diabetes Metab Syndr. 2016 Jul-Sep;10(3):121-7. doi: 10.1016/j.dsx.2016.01.001. Epub 2016 Feb 12.
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.
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.
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.
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.
在撒哈拉以南非洲地区，许多临床和公共卫生服务中对代谢综合征（MetS）定义和危险因素筛查指标的使用并不精确。西方人群中提出并使用的方法未经当地环境验证就被采用。本研究的目的是评估肥胖指标和临界值，以最大限度地筛查尼日利亚人群中的代谢综合征及其危险因素。
对来自四项针对≥18岁明显健康人群的基于人群的横断面研究的2809个样本进行综合分析。使用最优数据分析（ODA）模型确定诊断代谢综合征及其危险因素的最佳腰围（WC）和腰高比（WHtR）切点。还评估了模型预测的稳定性。
BMI、WC和WHtR的总体平均值分别为24.8±6.0kg/m²、84.0±11.3cm和0.52±0.1。区分代谢综合征和糖尿病的最佳WC切点女性为83cm，男性为85cm；区分糖尿病的最佳WC切点女性为82cm，男性为89cm。WC在区分糖尿病方面比WHtR和BMI更稳定，而WHtR在预测代谢综合征方面比WC和BMI表现出更好的稳定性。
研究表明，使代谢综合征分类准确性最大化的最佳WC与目前撒哈拉以南种族使用的不同。提议的全球WHtR为0.50可能会对代谢综合征、糖尿病和高血压进行错误分类。最后，在该样本人群中，WC是糖尿病的更好预测指标，而WHtR是代谢综合征的更好预测指标。
