Oxidative balance score predicts chronic kidney disease risk in overweight adults: a NHANES-based machine learning study
BackgroundOxidative stress plays a pivotal role in the pathogenesis of chronic kidney disease (CKD), particularly in overweight and obese populations where adipose tissue dysfunction exacerbates systemic inflammation and metabolic derangements. The oxidative balance score (OBS) is a composite index...
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Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Nutrition |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnut.2025.1641496/full |
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| author | Leying Zhao Leying Zhao Cong Zhao Cong Zhao Yuchen Fu Yuchen Fu Xiaochang Wu Xiaochang Wu Xuezhe Wang Xuezhe Wang Yaoxian Wang Yaoxian Wang Yaoxian Wang Huijuan Zheng |
| author_facet | Leying Zhao Leying Zhao Cong Zhao Cong Zhao Yuchen Fu Yuchen Fu Xiaochang Wu Xiaochang Wu Xuezhe Wang Xuezhe Wang Yaoxian Wang Yaoxian Wang Yaoxian Wang Huijuan Zheng |
| author_sort | Leying Zhao |
| collection | DOAJ |
| description | BackgroundOxidative stress plays a pivotal role in the pathogenesis of chronic kidney disease (CKD), particularly in overweight and obese populations where adipose tissue dysfunction exacerbates systemic inflammation and metabolic derangements. The oxidative balance score (OBS) is a composite index that integrates dietary antioxidants and pro-oxidant exposures, offering a quantifiable surrogate of oxidative burden. However, its utility in CKD prediction among overweight adults remains unclear.MethodsWe analyzed data from 28,377 overweight or obese participants in ten NHANES cycles (1999–2018). OBS was calculated based on 16 dietary components and 4 lifestyle factors. CKD was defined using KDIGO guidelines. Survey-weighted logistic regression models were used to assess the association between OBS and CKD, with multivariable adjustment. Restricted cubic spline regression examined dose–response patterns, and subgroup analyses evaluated effect modifiers. Additionally, 14 machine learning algorithms were trained and validated using SMOTE-balanced data and five-fold cross-validation. Model interpretability was enhanced through SHapley Additive exPlanations (SHAP) analysis.ResultsA higher OBS was inversely associated with CKD risk (fully adjusted OR per unit increase, 0.975; 95% CI, 0.969–0.981; p < 0.0001), with a significant linear dose–response relationship. This protective association was attenuated in morbid obesity (BMI ≥ 40 kg/m2; Pinteraction < 0.001), a finding driven by the abrogation of the dietary score’s effect, while the lifestyle score remained protective in this subgroup. Among 14 machine learning models, GLMBoost was the top performer, achieving an Area Under the Curve (AUC) of 0.833 on the independent test set. SHAP analysis identified age, LDL-C, and SBP as primary predictors, but also revealed the significant protective contributions of OBS components—most notably physical activity and magnesium—and showed that age critically modifies the effects of both clinical and lifestyle factors.ConclusionHigher OBS was associated with lower CKD risk in overweight and obese adults. This may support the role of oxidative balance in kidney health and its potential for early prevention strategies. |
| format | Article |
| id | doaj-art-47d3a87bcdd84c5fa0e4c82c3ce37ba2 |
| institution | Kabale University |
| issn | 2296-861X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Nutrition |
| spelling | doaj-art-47d3a87bcdd84c5fa0e4c82c3ce37ba22025-08-20T03:27:43ZengFrontiers Media S.A.Frontiers in Nutrition2296-861X2025-07-011210.3389/fnut.2025.16414961641496Oxidative balance score predicts chronic kidney disease risk in overweight adults: a NHANES-based machine learning studyLeying Zhao0Leying Zhao1Cong Zhao2Cong Zhao3Yuchen Fu4Yuchen Fu5Xiaochang Wu6Xiaochang Wu7Xuezhe Wang8Xuezhe Wang9Yaoxian Wang10Yaoxian Wang11Yaoxian Wang12Huijuan Zheng13Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, ChinaBeijing University of Chinese Medicine, Beijing, ChinaDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, ChinaBeijing University of Chinese Medicine, Beijing, ChinaDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, ChinaBeijing University of Chinese Medicine, Beijing, ChinaDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, ChinaBeijing University of Chinese Medicine, Beijing, ChinaDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, ChinaBeijing University of Chinese Medicine, Beijing, ChinaDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, ChinaRenal Research Institution of Beijing University of Chinese Medicine, Beijing, ChinaHenan University of Chinese Medicine, Zhengzhou, ChinaDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, ChinaBackgroundOxidative stress plays a pivotal role in the pathogenesis of chronic kidney disease (CKD), particularly in overweight and obese populations where adipose tissue dysfunction exacerbates systemic inflammation and metabolic derangements. The oxidative balance score (OBS) is a composite index that integrates dietary antioxidants and pro-oxidant exposures, offering a quantifiable surrogate of oxidative burden. However, its utility in CKD prediction among overweight adults remains unclear.MethodsWe analyzed data from 28,377 overweight or obese participants in ten NHANES cycles (1999–2018). OBS was calculated based on 16 dietary components and 4 lifestyle factors. CKD was defined using KDIGO guidelines. Survey-weighted logistic regression models were used to assess the association between OBS and CKD, with multivariable adjustment. Restricted cubic spline regression examined dose–response patterns, and subgroup analyses evaluated effect modifiers. Additionally, 14 machine learning algorithms were trained and validated using SMOTE-balanced data and five-fold cross-validation. Model interpretability was enhanced through SHapley Additive exPlanations (SHAP) analysis.ResultsA higher OBS was inversely associated with CKD risk (fully adjusted OR per unit increase, 0.975; 95% CI, 0.969–0.981; p < 0.0001), with a significant linear dose–response relationship. This protective association was attenuated in morbid obesity (BMI ≥ 40 kg/m2; Pinteraction < 0.001), a finding driven by the abrogation of the dietary score’s effect, while the lifestyle score remained protective in this subgroup. Among 14 machine learning models, GLMBoost was the top performer, achieving an Area Under the Curve (AUC) of 0.833 on the independent test set. SHAP analysis identified age, LDL-C, and SBP as primary predictors, but also revealed the significant protective contributions of OBS components—most notably physical activity and magnesium—and showed that age critically modifies the effects of both clinical and lifestyle factors.ConclusionHigher OBS was associated with lower CKD risk in overweight and obese adults. This may support the role of oxidative balance in kidney health and its potential for early prevention strategies.https://www.frontiersin.org/articles/10.3389/fnut.2025.1641496/fulloxidative balance scorechronic kidney diseasemachine learningoverweightprecision nutrition |
| spellingShingle | Leying Zhao Leying Zhao Cong Zhao Cong Zhao Yuchen Fu Yuchen Fu Xiaochang Wu Xiaochang Wu Xuezhe Wang Xuezhe Wang Yaoxian Wang Yaoxian Wang Yaoxian Wang Huijuan Zheng Oxidative balance score predicts chronic kidney disease risk in overweight adults: a NHANES-based machine learning study Frontiers in Nutrition oxidative balance score chronic kidney disease machine learning overweight precision nutrition |
| title | Oxidative balance score predicts chronic kidney disease risk in overweight adults: a NHANES-based machine learning study |
| title_full | Oxidative balance score predicts chronic kidney disease risk in overweight adults: a NHANES-based machine learning study |
| title_fullStr | Oxidative balance score predicts chronic kidney disease risk in overweight adults: a NHANES-based machine learning study |
| title_full_unstemmed | Oxidative balance score predicts chronic kidney disease risk in overweight adults: a NHANES-based machine learning study |
| title_short | Oxidative balance score predicts chronic kidney disease risk in overweight adults: a NHANES-based machine learning study |
| title_sort | oxidative balance score predicts chronic kidney disease risk in overweight adults a nhanes based machine learning study |
| topic | oxidative balance score chronic kidney disease machine learning overweight precision nutrition |
| url | https://www.frontiersin.org/articles/10.3389/fnut.2025.1641496/full |
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