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自2000年以来伊朗成年人肥胖比值比的变化:二次推断函数法

Changes in Obesity Odds Ratio among Iranian Adults, since 2000: Quadratic Inference Functions Method.

作者信息

Bakhshi Enayatollah, Etemad Koorosh, Seifi Behjat, Mohammad Kazem, Biglarian Akbar, Koohpayehzadeh Jalil

机构信息

Department of Biostatistics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.

Center for Diseases Control, Ministry of Health and Medical Education, Tehran, Iran.

出版信息

Comput Math Methods Med. 2016;2016:7101343. doi: 10.1155/2016/7101343. Epub 2016 Oct 10.

Abstract

Monitoring changes in obesity prevalence by risk factors is relevant to public health programs that focus on reducing or preventing obesity. The purpose of this paper was to study trends in obesity odds ratios (ORs) for individuals aged 20 years and older in Iran by using a new statistical methodology. Data collected by the National Surveys in Iran, from 2000 through 2011. Since responses of the member of each cluster are correlated, the quadratic inference functions (QIF) method was used to model the relationship between the odds of obesity and risk factors. During the study period, the prevalence rate of obesity increased from 12% to 22%. By using QIF method and a model selection criterion for performing stepwise regression analysis, we found that while obesity prevalence generally increased in both sexes, all ages, all employment, residence, and smoking levels, it seems to have changes in obesity ORs since 2000. Because obesity is one of the main risk factors for many diseases, awareness of the differences by factors allows development of targets for prevention and early intervention.

摘要

通过风险因素监测肥胖患病率的变化,对于关注减少或预防肥胖的公共卫生项目具有重要意义。本文的目的是运用一种新的统计方法,研究伊朗20岁及以上人群肥胖比值比(OR)的变化趋势。数据来源于伊朗2000年至2011年的全国性调查。由于每个聚类成员的回答具有相关性,因此采用二次推断函数(QIF)方法对肥胖几率与风险因素之间的关系进行建模。在研究期间,肥胖患病率从12%上升至22%。通过使用QIF方法和用于进行逐步回归分析的模型选择标准,我们发现,虽然肥胖患病率在各性别、各年龄段、各就业状况、居住状况和吸烟水平中普遍上升,但自2000年以来肥胖OR似乎有所变化。由于肥胖是许多疾病的主要风险因素之一,了解各因素之间的差异有助于制定预防和早期干预目标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04db/5075634/368d6ddaf8f1/CMMM2016-7101343.001.jpg

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