Association between dietary multi-metal intake and the risk of diabetic retinopathy: a population-based study
ObjectiveTo investigate the association between dietary metals intake and the risk of diabetic retinopathy (DR) in adults with diabetes.MethodsData from 2,822 U. S. adults with diabetes in National Health and Nutrition Examination Survey (NHANES) 2007–2016 were analyzed. Associations between the int...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Nutrition |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnut.2025.1595788/full |
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| author | Chaohua Zhang Haiyang Peng Qin Lang Haoyu Fang Keqin Zhang Andong Zhao |
| author_facet | Chaohua Zhang Haiyang Peng Qin Lang Haoyu Fang Keqin Zhang Andong Zhao |
| author_sort | Chaohua Zhang |
| collection | DOAJ |
| description | ObjectiveTo investigate the association between dietary metals intake and the risk of diabetic retinopathy (DR) in adults with diabetes.MethodsData from 2,822 U. S. adults with diabetes in National Health and Nutrition Examination Survey (NHANES) 2007–2016 were analyzed. Associations between the intake of six dietary metals and DR risk were assessed using multivariable logistic regression, Weighted Quantile Sum (WQS) regression, and Bayesian Kernel Machine Regression (BKMR). Restricted Cubic Spline (RCS) regression examined the dose–response relationship between intake of dietary metal and DR risk. Mediation analysis explored the underlying mechanisms.ResultsLog10-transformed dietary Zinc (Zn) (OR = 0.53, 95% CI 0.35–0.80, p = 0.003) were negatively associated with the DR risk. WQS regression indicated that the combined effects of dietary metals intake were negatively associated with the risk of DR (OR = 0.79, 95% CI 0.61–0.97, p = 0.024), with Zn contributing the most to the reduced risk (36.4%). BKMR model suggested the negative association between the combined intake of 6 metals and DR risk, with Zn receiving the highest posterior inclusion probability (PIP) (0.8574).ConclusionIn American adults with diabetes, elevated dietary metals intake, especially zinc, may be associated with a lower risk of DR. |
| format | Article |
| id | doaj-art-0805a8ba4f7d4b4084930f14c469116a |
| institution | Kabale University |
| issn | 2296-861X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Nutrition |
| spelling | doaj-art-0805a8ba4f7d4b4084930f14c469116a2025-08-20T03:30:44ZengFrontiers Media S.A.Frontiers in Nutrition2296-861X2025-06-011210.3389/fnut.2025.15957881595788Association between dietary multi-metal intake and the risk of diabetic retinopathy: a population-based studyChaohua Zhang0Haiyang Peng1Qin Lang2Haoyu Fang3Keqin Zhang4Andong Zhao5Department of Urinary Nephropathy Center, Second Hospital Affiliated to Chongqing Medical University, Chongqing, ChinaDepartment of Hepatobiliary Surgery, Second Hospital Affiliated to Chongqing Medical University, Chongqing, ChinaDepartment of Clinical Nutrition, Chongqing Red Cross Hospital (People's Hospital of Jiangbei District), Chongqing, ChinaDepartment of Hepatobiliary Surgery, Second Hospital Affiliated to Chongqing Medical University, Chongqing, ChinaDepartment of Urinary Nephropathy Center, Second Hospital Affiliated to Chongqing Medical University, Chongqing, ChinaDepartment of Plastic and Maxillofacial Surgery, Second Hospital Affiliated to Chongqing Medical University, Chongqing, ChinaObjectiveTo investigate the association between dietary metals intake and the risk of diabetic retinopathy (DR) in adults with diabetes.MethodsData from 2,822 U. S. adults with diabetes in National Health and Nutrition Examination Survey (NHANES) 2007–2016 were analyzed. Associations between the intake of six dietary metals and DR risk were assessed using multivariable logistic regression, Weighted Quantile Sum (WQS) regression, and Bayesian Kernel Machine Regression (BKMR). Restricted Cubic Spline (RCS) regression examined the dose–response relationship between intake of dietary metal and DR risk. Mediation analysis explored the underlying mechanisms.ResultsLog10-transformed dietary Zinc (Zn) (OR = 0.53, 95% CI 0.35–0.80, p = 0.003) were negatively associated with the DR risk. WQS regression indicated that the combined effects of dietary metals intake were negatively associated with the risk of DR (OR = 0.79, 95% CI 0.61–0.97, p = 0.024), with Zn contributing the most to the reduced risk (36.4%). BKMR model suggested the negative association between the combined intake of 6 metals and DR risk, with Zn receiving the highest posterior inclusion probability (PIP) (0.8574).ConclusionIn American adults with diabetes, elevated dietary metals intake, especially zinc, may be associated with a lower risk of DR.https://www.frontiersin.org/articles/10.3389/fnut.2025.1595788/fulldiabetic retinopathydietary metals intakeweighted quantile sumBayesian kernel machine regressionNHANES |
| spellingShingle | Chaohua Zhang Haiyang Peng Qin Lang Haoyu Fang Keqin Zhang Andong Zhao Association between dietary multi-metal intake and the risk of diabetic retinopathy: a population-based study Frontiers in Nutrition diabetic retinopathy dietary metals intake weighted quantile sum Bayesian kernel machine regression NHANES |
| title | Association between dietary multi-metal intake and the risk of diabetic retinopathy: a population-based study |
| title_full | Association between dietary multi-metal intake and the risk of diabetic retinopathy: a population-based study |
| title_fullStr | Association between dietary multi-metal intake and the risk of diabetic retinopathy: a population-based study |
| title_full_unstemmed | Association between dietary multi-metal intake and the risk of diabetic retinopathy: a population-based study |
| title_short | Association between dietary multi-metal intake and the risk of diabetic retinopathy: a population-based study |
| title_sort | association between dietary multi metal intake and the risk of diabetic retinopathy a population based study |
| topic | diabetic retinopathy dietary metals intake weighted quantile sum Bayesian kernel machine regression NHANES |
| url | https://www.frontiersin.org/articles/10.3389/fnut.2025.1595788/full |
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