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Prevalence of metabolic syndrome in relation to body mass index and polycystic ovarian syndrome in Indian women

ABSTRACT
OBJECTIVE: To study the prevalence of metabolic syndrome (MBS) in Indian women and to see how does it correlate to body mass index (BMI) and polycystic ovarian syndrome (PCOS) in this population. STUDY DESIGN: Prospective cross sectional observational study. SETTING: Infertility clinic of a tertiary center. MATERIALS AND METHODS: Two hundred women, 120 with PCOs and 80 age-matched controls were enrolled. The prevalence of MBS was studied in the women with and without and was co related to BMI by further subgrouping as team (BMI 23 kg/m2). The sample size was: team controls-40, obese controls-40, team PCOS80. Each subject underwent a physical examination and laboratory evaluation for the diagnosis of MBS, which was defined according to the guidelines of National Cholesterol Education Program Adult Treatment Pamel (NCEP ATP III) 2005. INTERVENTION: None. MAIN OUTCOME MEASURES: Main Outcome Measures: Subjects with and without PCOs were compared with each other for the prevalence of MBS, and similarly team subjects were compared with obese subjects. Receiver operator characteristic (ROC) curves were obtained for both the PCOS and non PCOS population separately, co-relating the prevalence of MBS with BMI. These ROC curves were used to establish the cut off values of BMI, which could best predict the risk of MBS. RESULTS: The prevalence of MBS was significantly higher in the women with PCOS, as compared to age matched controls. Similarly, when BMI was considered, MBS was more prevalent in overweight subjects than in lean subjects with or without PCOS. In subgroup analysis, the presence of PCOS had a lesser impact on the prevalence of MBS as compared to non PCOS controls with higher BMI. The relative risk of MBS increased as follows: lean controls 1, lean PCOS 2.66, obese controls 5.33, and obese PCOS 6.5. The most appropriate cut off level of BMI for predicting the risk of MBS in Indian women without PCOS seems to be 23 kg/m2 , whereas, with PCOS, it was 22.5 kg/m2 . CONCLUSION: MBS is more prevalent in women with PCOS. However, obesity is an independent and stronger risk factor for developing MBS. To reduce the risk of MBS and its related long term health consequences, lifestyle modification is advisable above BMI of 23 kg/m2 in the normal population and 22.5 kg/m2 in women with PCOS.

INTRODUCTION

Polycystic ovarian syndrome (PCOS) is common disorder, affecting approximately 5–10% of the women in reproductive age group.[1,2] It is characterized by chronic anovulation, hyperandrogenism, and polycystic ovaries. The other metabolic abnormalities associated with PCOS are obesity, dyslipidemia, insulin resistance, glucose intolerance, and hypertension, which confer an increased risk of long term health consequences such as type II diabetes mellitus and cardiovascular risk.[3] Most of these metabolic features are also shared by the syndrome X or metabolic syndrome (MBS), which is associated with atherosclerosis, hypertension, dyslipidemia, coronary artery disease, and diabetes. Some of the factors affecting the prevalence of MBS are age,[4,5] obesity,[4] insulin resistance,[6] and underlying PCOS.[7] Till date, there are few studies, mainly from the American population[8 10] and still fewer from the European continent,[11,12] which have addressed the prevalence of MBS in women with PCOS. There is a scarcity of data from Asian population.[13,14] Moreover, in most of these studies, the women with PCOS were found to have a higher body mass index (BMI) and waist circumference, as compared to the controls, which could have confounded in the higher prevalence of MBS. This study was undertaken with an aim of comparing the prevalence and different characteristics of MBS in Indian women with PCOS and age matched controls. To negate the confounding effect of the high BMI associated with PCOS, subgroups of lean and obese women were studied separately for the prevalence of MBS. In order to reduce the serious long term consequences related to MBS, we have attempted to find out the predictors of MBS, and the action points, at which screening for MBS and lifestyle modification would be beneficial, in respect to preventing, or modifying long term morbidity.



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