A Study on Insulin Resistance and Obesity Among Women at High Risk for Breast Cancer Using Cluster Analysis.

OBJECTIVE: The present study to stratify the female population based on their obesity and body fat distributions using cluster analysis without relating to conventional obesity cutoff values. To study insulin response (sensitivity x resistance) using indices of surrogate measures obtained from OGTT data. To identify the hormonal parameters that are significantly altered in obese breast cancer patients and to exploit them as screening markers along with body mass index (BMI) and body fat mass (BFM). To build a comprehensive questionnaire for breast cancer risk prediction using related variables and the symptoms associated with hormonal variations in breast cancer. PURPOSE OF STUDY: According to estimates of the International Obesity Task Force, 1,7 billion people are exposed to health risks related to body weight, while the increase in Body Mass Index (BMI) is responsible for more than 2.5 million deaths annually, which is expected to double by 2030. The aim is to define obesity using anthropometric measures particularly in obese post-menopausal women. Assessment of insulin resistance is of great importance in the study of epidemiology and pathophysiology of major public health problems and in following the clinical course of patients on various therapeutic regimens. It is also of our interest to evaluate the insulin resistance in obese post-menopausal women who are at high risk for breast cancer using a simple oral glucose tolerance test (OGTT). Studying about relevant risk factors of breast cancer and their prevalence is essential in the breast cancer risk prediction among individuals of high risk group.CONCLUSION: Obesity is a chronic disease which has spread all over the world and threatens public global health. Obesity in postmenopausal women was highly correlated with several disorders including type 2 diabetes mellitus, hypertension, coronary heart disease, arthritis, sleep apnea, and certain forms of obesity-related cancers, including breast, prostate, endometrium, colon and gallbladder cancer. However, defining an individual as overweight/obese using widely employed markers is a complex task. Cut-off points of these markers widely vary among the different sections of women population. In order to define obesity on a local level we stratified the female population based on their anthropometric measures using cluster analysis. We also clustered them based on their body fat distribution. Thus, we could identify through an alternative approach, the obese women who may be at high risk for breast cancer