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Novel anthropometric indices for predicting type 2 diabetes mellitus.
Sadeghi, Erfan; Khodadadiyan, Alireza; Hosseini, Seyed Ali; Hosseini, Sayed Mohsen; Aminorroaya, Ashraf; Amini, Massoud; Javadi, Sara.
Affiliation
  • Sadeghi E; Department of Biostatistics, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Khodadadiyan A; Department of Cardiovascular Research Centre, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Hosseini SA; School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Hosseini SM; Department of Biostatistics & Epidemiology, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Aminorroaya A; Isfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Amini M; Isfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Javadi S; Shiraz University of Medical Sciences, Shiraz, Iran. javadi.stat@gmail.com.
BMC Public Health ; 24(1): 1033, 2024 Apr 13.
Article in En | MEDLINE | ID: mdl-38615018
ABSTRACT

BACKGROUND:

This study aimed to compare anthropometric indices to predict type 2 diabetes mellitus (T2DM) among first-degree relatives of diabetic patients in the Iranian community.

METHODS:

In this study, information on 3483 first-degree relatives (FDRs) of diabetic patients was extracted from the database of the Endocrinology and Metabolism Research Center of Isfahan University of Medical Sciences. Overall, 2082 FDRs were included in the analyses. A logistic regression model was used to evaluate the association between anthropometric indices and the odds of having diabetes. Furthermore, a receiver operating characteristic (ROC) curve was applied to estimate the optimal cutoff point based on the sensitivity and specificity of each index. In addition, the indices were compared based on the area under the curve (AUC).

RESULTS:

The overall prevalence of diabetes was 15.3%. The optimal cutoff points for anthropometric measures among men were 25.09 for body mass index (BMI) (AUC = 0.573), 0.52 for waist-to-height ratio (WHtR) (AUC = 0.648), 0.91 for waist-to-hip ratio (WHR) (AUC = 0.654), 0.08 for a body shape index (ABSI) (AUC = 0.599), 3.92 for body roundness index (BRI) (AUC = 0.648), 27.27 for body adiposity index (BAI) (AUC = 0.590), and 8 for visceral adiposity index (VAI) (AUC = 0.596). The optimal cutoff points for anthropometric indices were 28.75 for BMI (AUC = 0.610), 0.55 for the WHtR (AUC = 0.685), 0.80 for the WHR (AUC = 0.687), 0.07 for the ABSI (AUC = 0.669), 4.34 for the BRI (AUC = 0.685), 39.95 for the BAI (AUC = 0.583), and 6.15 for the VAI (AUC = 0.658). The WHR, WHTR, and BRI were revealed to have fair AUC values and were relatively greater than the other indices for both men and women. Furthermore, in women, the ABSI and VAI also had fair AUCs. However, BMI and the BAI had the lowest AUC values among the indices in both sexes.

CONCLUSION:

The WHtR, BRI, VAI, and WHR outperformed other anthropometric indices in predicting T2DM in first-degree relatives (FDRs) of diabetic patients. However, further investigations in different populations may need to be implemented to justify their widespread adoption in clinical practice.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Diabetes Mellitus, Type 2 Limits: Female / Humans / Male Country/Region as subject: Asia Language: En Journal: BMC Public Health Journal subject: SAUDE PUBLICA Year: 2024 Document type: Article Affiliation country: Iran Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Diabetes Mellitus, Type 2 Limits: Female / Humans / Male Country/Region as subject: Asia Language: En Journal: BMC Public Health Journal subject: SAUDE PUBLICA Year: 2024 Document type: Article Affiliation country: Iran Country of publication: United kingdom