首页> 外文期刊>British Journal of Medicine and Medical Research >Association between Major Non-communicable Diseases Risk Factors and Fasting Blood Glucose in Iran: Comparison of Two Techniques, with and Without Dichotomizing the Response
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Association between Major Non-communicable Diseases Risk Factors and Fasting Blood Glucose in Iran: Comparison of Two Techniques, with and Without Dichotomizing the Response

机译:伊朗主要的非传染性疾病危险因素与空腹血糖之间的关联:两种方法的比较(有无将反应二分法)

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Background: Dichotomizing a continuous outcome variable is a common approach to estimate the odds ratio (OR) as a measure of association. In the present study we aimed to compare a non-dichotomizing technique with logistic regression which exploits dichotomizing the response for estimating OR. Method: Data including a total of 17,152 Iranian individuals aged 25–65 years were derived from the third national survey of non-communicable Diseases Risk Factors in Iran. To measure the associations between fasting blood glucose and attributed risk factors two distinct techniques were used. Using a non-dichotomizing technique, an approach proposed by B.K. Moser and L. Coombs (2004) was employed to estimate odds ratios and associated 95% confidence intervals (CIs); A binary logistic regression model was also applied to fit the data as a common dichotomizing approach. Finally the results of two methods were compared by use of relative efficiencies and relative length of CIs. Results: The odds ratios provided by both approaches are approximately the same, but relative efficiencies and relative length of CIs are greater than 2 which reflected better results for the technique used a non-dichotomizing approach compared to Logistic Regression Model. Conclusions: Dichotomizing continues outcome variable is not necessary to estimate ORs, especially when there is no pre-specified optimal cut-off point for the response variable.
机译:背景:将连续结果变量二等分是估计比值比(OR)作为关联度量的一种常用方法。在本研究中,我们旨在将非二分法技术与逻辑回归进行比较,该方法利用二分法将响应二分法估计OR。方法:数据包括总共17152名25-65岁的伊朗人,这些数据来自于第三次全国非传染性疾病危险因素国家调查。为了测量空腹血糖和相关危险因素之间的关联,使用了两种不同的技术。 B.K.使用非二分法技术提出了一种方法。 Moser和L. Coombs(2004)用来估计比值比和相关的95%置信区间(CI s );二元逻辑回归模型也被应用来拟合数据,这是一种常见的二分法。最后利用CI s 的相对效率和相对长度对两种方法的结果进行了比较。结果:两种方法提供的比值比大致相同,但CI的相对效率和相对长度均大于2,这反映了与Logistic相比,使用非二分法的方法具有更好的结果回归模型。结论:将连续结果变量二分法并不需要估计OR s ,尤其是在没有预先指定响应变量的最佳截止点的情况下。

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