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Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016)

机译:糖尿病风险因素建模(2016年在肯尼亚Kiambu的Focus Medical Center案例研究)

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This study sought to model risk factors of diabetes (A case study of Focus Medical Center in Kiambu, Kenya) for the year 2016. We considered sample of size 181 patients and carried descriptive statistics, bivariate analysis, Chi-Square test and Hosmer and Lemeshow test. The independence test between response variable (diabetes) and predictor variables (age, obesity, alcohol, smoking and hypertension) was carried. The variables age, obesity, alcohol and hypertension were found to be statistically significant at α =0.05 level of significant. A multiple logistic regression model was fitted and the fitted regression model indicated that the predictor variables age, obesity and alcohol were statistically significant. The results of the odds ratios show that age, obesity and alcohol consumption are positively associated with diabetes. The fitted reduced multiple logistic regression model was subjected to an overall goodness-of-fit test and results indicate that there is no significant difference between the observed and predicted probability. Based on the results of this study, we recommend that special attention should be given to individuals advanced in age, consume alcohol or who are obese for screening as there is a high possibility of testing positive for diabetes for health care givers to monitor and manage the condition. Further, healthy lifestyles should be promoted among the general population and in particular, the diabetic patients to increase the chance of properly managing the condition. A further study ought to be conducted to assess treatment interventions of diabetes to ascertain the effectiveness and recommend the best medication for patients suffering from diabetes.
机译:本研究旨在为2016年的糖尿病风险因素建模(以肯尼亚基安布的福克斯医疗中心为例)。我们考虑了181名患者的样本,并进行了描述性统计,双变量分析,卡方检验以及Hosmer和Lemeshow测试。进行了反应变量(糖尿病)和预测变量(年龄,肥胖,酒精,吸烟和高血压)之间的独立性测试。年龄,肥胖,酒精和高血压的变量在α= 0.05的显着水平上具有统计学意义。拟合多元logistic回归模型,拟合的回归模型表明预测变量年龄,肥胖和饮酒有统计学意义。比值比的结果表明,年龄,肥胖和饮酒与糖尿病呈正相关。拟合的简化多元逻辑回归模型经过整体拟合优度检验,结果表明,观察到的概率与预测的概率之间没有显着差异。根据这项研究的结果,我们建议应特别注意年龄稍大,饮酒或肥胖的筛查对象,因为很有可能检测出糖尿病呈阳性反应,以供医护人员监测和管理。健康)状况。此外,应在一般人群中,特别是在糖尿病患者中,提倡健康的生活方式,以增加适当控制病情的机会。应该进行进一步的研究以评估糖尿病的治疗干预措施,以确定其有效性并为患有糖尿病的患者推荐最佳药物。

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