摘要
目的探讨脂质蓄积指数(LAP)相较于腰围(WC)、体重指数(BMI)、腰臀比(WHR)等体脂指标对于代谢综合征(MS)识别的有效性。方法本研究为横断面研究,对重庆市某社区共3467人进行现况调查。根据2009年国际联合标准诊断MS,比较MS组与无MS组WC、TG、BMI、WHR、TG/HDL-C、HOMA-IR、LAP等指标差异,并对MS人群进行受试者工作特征曲线(ROC)分析比较各指标识别MS的差别。结果 (1)MS各亚组分人群中,LAP均显著增高(P<0.01)。(2)MS人群ROC分析,无论男女LAP曲线下面积均最大[男性0.91±0.01(95%CI 0.89~0.92),女性0.93±0.01(95%CI 0.91~0.94)]。男性与女性LAP的最佳界限值分别为39.18和37.89,均具有较好的灵敏度与特异度。(3)年龄分组后的MS人群中,各年龄段男性LAP的ROC曲线下面积均最大,女性LAP在25~40岁及56~70岁年龄段曲线下面积最大。结论 LAP与HOMA-IR、MS及各亚组分均密切相关,且与其他体脂指标相比LAP是MS最佳评价指标。
Objective To explore the efficacy of lipid accumulation product(LAP) in identifying metabolic syndrome(MS),compared with such traditional markers as body mass index(BMI),waist circumference(WC) or waist hip ratio(WHR).Methods This research was a cross-sectional study,including 3467 subjects aged 25 to 85 years from an urban community of Chongqing city.Metabolic syndrome was diagnosed according to international diagnostic criteria 2009.Body fat indexes,including WC,TG,BMI,WHR,TG / HDL-C,HOMA-IR and LAP were compared between the MS group and non-MS group.Receiver operating characteristic curve analysis was conducted to detect the best predictive variable to identify MS.Results(1) LAP was significantly elevated(P < 0.01) among all sub-groups of MS patients.(2) LAP showed the largest area under the curve to identify MS(0.91 ± 0.01[95% CI 0.89-0.92] in males,0.93 ± 0.01[95% CI 0.91-0.94] in females).For both males and females,the cut-off values of LAP exhibited high sensitivity and specificity for MS identification.(3) The subjects stratified according to fifteen years of life,LAP also showed the largest area under the curve in each age group in males,and showed the largest in the 25-40 and 56-70 years of age in females.Conclusion LAP is closely related with HOMA-IR and MS.LAP is proved to be the best body fat marker to identify MS,compared with other body fat indexes.
出处
《中国实用内科杂志》
CAS
CSCD
北大核心
2013年第7期552-555,共4页
Chinese Journal of Practical Internal Medicine
关键词
脂质蓄积指数
代谢综合征
体重指数
胰岛素抵抗
lipid accumulation product
metabolic syndrome
body mass index
insulin resistance