چاپ صفحه |  صفحه نخست سامانه |  نویسندگان |  اطلاعات تفضیلی |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده ثبت کننده مقاله | ندا گیلانی |
| مرحله جاری مقاله | تایید نهایی |
| دانشکده/مرکز مربوطه | دانشکده بهداشت |
| کد مقاله | 85383 |
| عنوان فارسی مقاله | Application of Skewed Logistic Modeling for Comparison of Traditional and Novel Anthropometric Indices in Discriminating Diabetes: Results of 5-year Follow up Azar Cohort Study |
| عنوان لاتین مقاله | Application of Skewed Logistic Modeling for Comparison of Traditional and Novel Anthropometric Indices in Discriminating Diabetes: Results of 5-year Follow up Azar Cohort Study |
| نوع ارائه | سخنرانی |
| عنوان کنگره / همایش | the 3rd International and 5th National Conference on Biomathematics |
| نوع کنگره / همایش | بین المللی |
| کشور محل برگزاری کنگره/ همایش | Iran (Islamic Republic) |
| شهر محل برگزاری کنگره/ همایش | Tabriz |
| سال انتشار/ ارائه شمسی | 1403 |
| سال انتشار/ارائه میلادی | 2024 |
| تاریخ شمسی شروع و خاتمه کنگره/همایش | 1403/05/03 الی 1403/05/04 |
| آدرس لینک مقاله/ همایش در شبکه اینترنت | https://biomath3.tabrizu.ac.ir/files_site/files/r_5_240824180937.pdf |
| آدرس علمی (Affiliation) نویسنده متقاضی | 1. Liver and Gastrointestinal Diseases Research center, Tabriz University of Medical Sciences, Tabriz, Iran. 2. Department of Statistics and Epidemiology, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran. Email:gilanin@tbzmed.ac.ir |
| نویسنده | نفر چندم مقاله |
|---|---|
| ندا گیلانی | اول |
| روح اله حق شناس | دوم |
| محمد حسین صومی | سوم |
| الناز فرامرزی | چهارم |
| عنوان | متن |
|---|---|
| خلاصه مقاله | Background: Anthropometric indices (AI) play a crucial role in identifying individuals at risk for various metabolic disorders, including diabetes. The purpose of this study was to identify the diagnostic ability of these indices to discriminate diabetes in the Azar cohort population. Materials and Methods: Subjects who were diabetic in the baseline phase from 15006 participants in study of azar cohort population were excluded and to follow up, a total of 13253 people was included in the analysis. Demographic characteristics and 11 AI were measured. Skewed logistic regression modeling and adjusted risk ratio (aRR) coefficients were used to evaluate the association between the anthropometric indices and diabetes. The receiver operating characteristic (ROC) curve analysis was performed to compare the discrimination of different anthropometric measures. Results: During the follow-up years, a total of 685 participants developed diabetes. The measurements of the AI were significantly higher in subjects with diabetes (P<.001). Body Roundness Index (BRI) and Waist height ratio (WHtR) exhibited the largest AUCs for predicting diabetes onset risk (both AUC=0.6989) among these anthropometric measures. Significant aRR for BRI and WhtR were 3.69 and 7.89, respectively. Conclusions: The BRI and WtHR demonstrated superior efficacy in detecting diabetes within the Azar Cohort population. |
| کلمات کلیدی | Anthropometric, Incidence Diabetes, Modeling |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| paper in booklet.pdf | 1403/06/08 | 268211 | دانلود |
| Booklet.pdf | 1403/06/08 | 16036483 | دانلود |
| IMG_20240901_093148_188.jpg | 1403/06/11 | 30468 | دانلود |
