Mamtani Manju R, Kulkarni Hemant R
Lata Medical Research Foundation, Nagpur, India.
Arch Med Res. 2005 Sep-Oct;36(5):581-9. doi: 10.1016/j.arcmed.2005.03.049.
In spite of several available anthropometric indexes, the relative merit of these indexes for the prediction of type 2 diabetes remains unknown. Considering that obesity and diabetes commonly coexist as co-morbidities, our objective was to directly compare the performance of measures of central and general obesity to predict the risk of type 2 diabetes.
We conducted a case-control study of type 2 diabetes on 150 cases and 150 age- and gender-matched controls. We directly compared the predictive performance of five anthropometric indexes: four related to central obesity--waist circumference (WC), waist/hip ratio (WHR), abdominal volume index (AVI) and conicity index (CI); and one related to general obesity--body mass index (BMI). We used various statistical approaches like area under (AUC) receiver-operating characteristic (ROC) curves, likelihood ratios, logistic regression and Shannon's entropy to compare the performance of the indexes in the study sample as well as bootstrapped samples.
WC had the highest overall predictive accuracy that was gender insensitive (AUC=0.77 in males and 0.74 in females); a comparable information content as that of AVI (Shannon's entropy=1.81 for WC and 1.84 for AVI) and was a better predictor of the risk of type 2 diabetes than all the remaining indexes. WC also correlated strongly with the biochemical markers of diabetes like blood sugar and lipid profile.
WC is a simple, non-invasive and accurate predictor of the risk of type 2 diabetes that can potentially be used in screening programs in developing countries.
尽管有多种可用的人体测量指标,但这些指标在预测2型糖尿病方面的相对优势仍不明确。鉴于肥胖和糖尿病常作为共病同时存在,我们的目的是直接比较中心性肥胖和全身性肥胖测量指标预测2型糖尿病风险的性能。
我们对150例2型糖尿病患者和150例年龄及性别匹配的对照者进行了病例对照研究。我们直接比较了五项人体测量指标的预测性能:四项与中心性肥胖相关——腰围(WC)、腰臀比(WHR)、腹部容积指数(AVI)和锥度指数(CI);一项与全身性肥胖相关——体重指数(BMI)。我们使用了各种统计方法,如受试者操作特征(ROC)曲线下面积(AUC)、似然比、逻辑回归和香农熵,以比较研究样本以及自抽样样本中各指标的性能。
WC具有最高的总体预测准确性,且对性别不敏感(男性AUC = 0.77,女性AUC = 0.74);其信息含量与AVI相当(WC的香农熵 = 1.81,AVI的香农熵 = 1.84),并且比所有其他指标更能预测2型糖尿病风险。WC还与血糖和血脂谱等糖尿病生化标志物密切相关。
WC是一种简单、无创且准确的2型糖尿病风险预测指标,有可能用于发展中国家的筛查项目。