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Evaluation of serum leptin levels in obese local Libyan female subjects at Benghazi- Is cluster analysis a better evaluator method for such a study

机译:在Benghazi评估肥胖的局部利比亚女性受试者的血清瘦素水平-聚类分析是该研究的更好评估方法

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  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 BMI30(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).  
机译:与肥胖相关的疾病,例如糖尿病和冠状动脉疾病(CAD),在班加西的利比亚当地居民中非常普遍。瘦素是与燃料平衡有关的脂肪细胞因子之一,也是肥胖的标志。瘦素抵抗被认为是与CAD相关的危险因素之一。因此,本研究旨在评估当地人群肥胖女性中瘦素抵抗的存在。该研究针对女性肥胖(通过体重指数衡量)和非肥胖患者进行。将患者分为两组。一个BMI <25(G1),另一个BMI> 30(G2)。根据分类为肥胖和非肥胖受试者的组以及聚类分析对获得的结果进行了分析。聚类分析是许多研究领域的重要技术,例如数据挖掘,信息科学农业技术和生物医学。聚类分析中最重要的问题之一是对聚类结果的评估,以找到最适合基础数据的分区。使用Silhouette指数对获得的数据进行聚类分析:假设肥胖者的瘦素水平或瘦素抵抗力更高。这种假设是普遍的,并认为肥胖是瘦素抵抗的起因或结果。但是,当将结果用于聚类分析时,则没有基于患者的BMI的假设或分类。而是将获得的结果进行关联,以得出肥胖与瘦素抵抗之间的关系。在本研究中,聚类分析确实对自变量(生化参数)做出了与基于BMI分类的组中观察到的相似观察。聚类分析似乎是一种更好的方法,可以说BMI或肥胖可能是瘦素抵抗的危险因素,并且将有助于开展一项前瞻性队列研究,其研究范围更多地涉及肥胖,瘦素抵抗和未来冠心病(CAD)的患者。

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