Abstract

Alshaari A. A, Elshaari F. A., Ahmed F. A. and Elshaari M. A*

Obesity related diseases like diabetes and coronary artery disease (CAD) are very much prevalent in local Libyan population at Benghazi. Leptin is one of the adipocytokines implicated in fuel balance as well as a marker of obesity. Leptin resistance is considered to be one of the risk factors associated with CAD. Therefore the present study was undertaken to evaluate the presence of leptin resistance in obese females in local population. The study was undertaken in female obese (measured by Body Mass Index) and non-obese patients. The patients were grouped into two groups of patients; one with BMI< 25(G1) and the other with BMI>30(G2). The results obtained were analyzed according to groups classified as obese and non-obese subjects as well as by cluster analyses. Cluster analysis is an important technique in many research areas such as data mining, information science agriculture technology, and biomedicine. One of the most important issues in cluster analysis is the evaluation of clustering results to find the partitioning that best fits the underlying data. The data obtained was subjected to cluster analysis using Silhouette index: The assumption made was obese people will have more leptin levels or leptin resistance. This assumption generalizes and assumes obesity is the cause or effect of leptin resistance. But when the results are used in adopting cluster analyses there was no assumption or classification of patients based BMI. Rather the results obtained were correlated to bring out the relationship between obesity and leptin resistance. In the present study cluster analyses did bring about similar observations made in the independent variables (biochemical parameters) as observed in groups classified based on BMI. Cluster analyses seem a better approach to say that BMI or obesity could be a risk factor for leptin resistance and will help undertake a prospective cohort studies extended more to patients with obesity, leptin resistance and future coronary artery disease (CAD).