Validation of the self-reported diagnosis of diabetes mellitus, hypercholesterolemia, and hypertension in Iran; STEPS 2016

伊朗糖尿病、高胆固醇血症和高血压自我报告诊断的验证;STEPS 2016

阅读:1

Abstract

PURPOSE: As a part of STEPwise approach to risk factor Surveillance (STEPS) study, our aim was to evaluate the validity of the self-reported diagnosis of diabetes (DM), hypertension (HTN), and hypercholesterolemia (Hyper-Chol) in the Iranian population. METHODS: Using systematic proportional to size cluster sampling, 27,232 participants were included in our study. We calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) to assess the validity of self-reported diagnoses. Furthermore, logistic regression was employed to examine the relationship between the validity of self-reported diagnoses and sociodemographic and lifestyle factors. All analyses were performed using STATA version 14. RESULTS: The PPV for self-report of DM, HTN, and Hyper-Chol were estimated to be 69%, 74% and 80%, and NPV measured up to 95%, 84%, and 50%, respectively. Positive/negative self-reports were more accurate among older (younger) individuals. Age had a negative correlation with the validity of self-reported Hyper-Chol but a positive correlation with the validity of self-reported DM and hypertension HTN. Additionally, an increase in BMI was associated with an increase/decrease in PPV and a decrease/increase in NPV across all diseases. CONCLUSION: Self-report studies hold value in situations where direct in-person interaction is not feasible, either due to prohibitive costs or restrictions imposed by infectious diseases (COVID-19). Self-report surveys are valuable tools in studying the epidemiology of diseases; however, the type of the disease, the study purpose, either finding sick people or healthy people, the age subgroups, and socioeconomic status should be taken into consideration.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。