Predictive value of anthropometric indices for incident of dyslipidemia: a large population-based study
The findings from machine learning models were in agreement, highlighting the significance of BMI, WHR, BSA, and BAI as key anthropometric indices for predicting dyslipidemia. These indices consistently emerged as strong predictors underscoring their importance in assessing the risk of dyslipidemia.
Authors
- Atena Ghasemabadi (ORCID: https://orcid.org/0000-0003-2389-6092)
- Negar Soleimani
- Mohammad Hassan Moradi (ORCID: https://orcid.org/0000-0002-3386-4003)
- Rana Kolahi Ahari (ORCID: https://orcid.org/0000-0002-3681-7528)
- Somayeh Ghiasi Hafezi
- Amin Mansoori (ORCID: https://orcid.org/0000-0003-4442-3358)
- Mark Ghamsary (ORCID: https://orcid.org/0000-0002-7867-0405)
- Maryam Allahyari
- Habibollah Esmaily (ORCID: https://orcid.org/0000-0003-4139-546X)
- Gordon Ferns
- Majid Ghayour-Mobarhan
Institutions
- Brighton and Sussex Medical School (GB)
- Mashhad University of Medical Sciences (IR)
- Allameh Tabataba'i University (IR)
- Loma Linda University (US)
- Esfarayen University of Technology (IR)
- Ferdowsi University of Mashhad (IR)
Publication Details
- Journal
- Population Health Metrics
- Published
- 2025-08-19
- DOI
- https://doi.org/10.1186/s12963-025-00410-z
- Primary Topic
- Lipoproteins and Cardiovascular Health
- Type
- article
- Field-Weighted Citation Impact
- 0.00