Junfeng Ge, Lin Zhu, Sijie Jiang, Wenyan Li, Rongzhan Lin, Jun Wu, Fengying Dong, Jin Deng, Yi Lu
{"title":"饮食质量、生物老化、心血管-肾脏-代谢综合征进展和死亡率的关联：来自调解和机器学习方法的见解。","authors":"Junfeng Ge, Lin Zhu, Sijie Jiang, Wenyan Li, Rongzhan Lin, Jun Wu, Fengying Dong, Jin Deng, Yi Lu","doi":"10.1186/s12937-025-01175-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>To investigate the association between the Dietary Inflammatory Index (DII), biological aging, and the staging and mortality of cardiovascular-kidney-metabolic (CKM) syndrome.</p><p><strong>Methods: </strong>Data of 7,918 participants were derived from the National Health and Nutrition Examination Survey 2005-2018. Cross-sectional analyses using multivariable logistic regression were conducted to evaluate the relationship between DII and CKM staging. Cox proportional hazards models were employed to assess the impact of DII on mortality in CKM patients. Mediation analyses were performed to determine whether biological aging mediated DII-staging and DII-mortality association. Machine learning models were developed to classify CKM stages 3/4 and predict all-cause mortality, with SHapley Additive exPlanations (SHAP) used to interpret the contribution of DII components.</p><p><strong>Results: </strong>Over a median follow-up of 9.3 years, 819 deaths were recorded. Higher DII were associated with an increased risk of advanced CKM stages [OR (95% CI): tertile 2, 1.39 (1.17, 1.65); tertile 3, 1.85 (1.56, 2.20)], and all-cause mortality [(HR (95% CI): tertile 2, 1.20 (1.01-1.43); tertile 3: 1.45 (1.21-1.73)]. The optimal risk stratification threshold for DII to predict all-cause mortality was 1.93. Mediation analyses revealed that biological aging accounted for 23% (95% CI: 18-28%) of the effect of DII on advanced CKM stages and 13% (95% CI: 8-22%) of the effect of DII on all-cause mortality. Furthermore, the Light Gradient Boosting Machine model showed strong performance in predicting advanced CKM staging (AUC: 0.896, 95% CI: 0.882-0.911), while Logistic regression performed better in predicting all-cause mortality (AUC: 0.857, 95% CI: 0.831-0.884). SHAP analysis revealed that intake of magnesium and n-3 fatty acid were associated with reduced risk of both advanced CKM stages and all-cause mortality.</p><p><strong>Conclusion: </strong>DII, a marker of pro-inflammatory dietary patterns, was significantly linked to CKM syndrome progression and mortality, partly by influencing biological aging. This underscores the importance of diet quality in managing CKM staging and mortality risk.</p>","PeriodicalId":19203,"journal":{"name":"Nutrition Journal","volume":"24 1","pages":"105"},"PeriodicalIF":4.4000,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12235904/pdf/","citationCount":"0","resultStr":"{\"title\":\"Association of dietary quality, biological aging, progression and mortality of cardiovascular-kidney-metabolic syndrome: insights from mediation and machine learning approaches.\",\"authors\":\"Junfeng Ge, Lin Zhu, Sijie Jiang, Wenyan Li, Rongzhan Lin, Jun Wu, Fengying Dong, Jin Deng, Yi Lu\",\"doi\":\"10.1186/s12937-025-01175-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>To investigate the association between the Dietary Inflammatory Index (DII), biological aging, and the staging and mortality of cardiovascular-kidney-metabolic (CKM) syndrome.</p><p><strong>Methods: </strong>Data of 7,918 participants were derived from the National Health and Nutrition Examination Survey 2005-2018. Cross-sectional analyses using multivariable logistic regression were conducted to evaluate the relationship between DII and CKM staging. Cox proportional hazards models were employed to assess the impact of DII on mortality in CKM patients. Mediation analyses were performed to determine whether biological aging mediated DII-staging and DII-mortality association. Machine learning models were developed to classify CKM stages 3/4 and predict all-cause mortality, with SHapley Additive exPlanations (SHAP) used to interpret the contribution of DII components.</p><p><strong>Results: </strong>Over a median follow-up of 9.3 years, 819 deaths were recorded. Higher DII were associated with an increased risk of advanced CKM stages [OR (95% CI): tertile 2, 1.39 (1.17, 1.65); tertile 3, 1.85 (1.56, 2.20)], and all-cause mortality [(HR (95% CI): tertile 2, 1.20 (1.01-1.43); tertile 3: 1.45 (1.21-1.73)]. The optimal risk stratification threshold for DII to predict all-cause mortality was 1.93. Mediation analyses revealed that biological aging accounted for 23% (95% CI: 18-28%) of the effect of DII on advanced CKM stages and 13% (95% CI: 8-22%) of the effect of DII on all-cause mortality. Furthermore, the Light Gradient Boosting Machine model showed strong performance in predicting advanced CKM staging (AUC: 0.896, 95% CI: 0.882-0.911), while Logistic regression performed better in predicting all-cause mortality (AUC: 0.857, 95% CI: 0.831-0.884). SHAP analysis revealed that intake of magnesium and n-3 fatty acid were associated with reduced risk of both advanced CKM stages and all-cause mortality.</p><p><strong>Conclusion: </strong>DII, a marker of pro-inflammatory dietary patterns, was significantly linked to CKM syndrome progression and mortality, partly by influencing biological aging. This underscores the importance of diet quality in managing CKM staging and mortality risk.</p>\",\"PeriodicalId\":19203,\"journal\":{\"name\":\"Nutrition Journal\",\"volume\":\"24 1\",\"pages\":\"105\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2025-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12235904/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nutrition Journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12937-025-01175-9\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NUTRITION & DIETETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nutrition Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12937-025-01175-9","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
Association of dietary quality, biological aging, progression and mortality of cardiovascular-kidney-metabolic syndrome: insights from mediation and machine learning approaches.
Background: To investigate the association between the Dietary Inflammatory Index (DII), biological aging, and the staging and mortality of cardiovascular-kidney-metabolic (CKM) syndrome.
Methods: Data of 7,918 participants were derived from the National Health and Nutrition Examination Survey 2005-2018. Cross-sectional analyses using multivariable logistic regression were conducted to evaluate the relationship between DII and CKM staging. Cox proportional hazards models were employed to assess the impact of DII on mortality in CKM patients. Mediation analyses were performed to determine whether biological aging mediated DII-staging and DII-mortality association. Machine learning models were developed to classify CKM stages 3/4 and predict all-cause mortality, with SHapley Additive exPlanations (SHAP) used to interpret the contribution of DII components.
Results: Over a median follow-up of 9.3 years, 819 deaths were recorded. Higher DII were associated with an increased risk of advanced CKM stages [OR (95% CI): tertile 2, 1.39 (1.17, 1.65); tertile 3, 1.85 (1.56, 2.20)], and all-cause mortality [(HR (95% CI): tertile 2, 1.20 (1.01-1.43); tertile 3: 1.45 (1.21-1.73)]. The optimal risk stratification threshold for DII to predict all-cause mortality was 1.93. Mediation analyses revealed that biological aging accounted for 23% (95% CI: 18-28%) of the effect of DII on advanced CKM stages and 13% (95% CI: 8-22%) of the effect of DII on all-cause mortality. Furthermore, the Light Gradient Boosting Machine model showed strong performance in predicting advanced CKM staging (AUC: 0.896, 95% CI: 0.882-0.911), while Logistic regression performed better in predicting all-cause mortality (AUC: 0.857, 95% CI: 0.831-0.884). SHAP analysis revealed that intake of magnesium and n-3 fatty acid were associated with reduced risk of both advanced CKM stages and all-cause mortality.
Conclusion: DII, a marker of pro-inflammatory dietary patterns, was significantly linked to CKM syndrome progression and mortality, partly by influencing biological aging. This underscores the importance of diet quality in managing CKM staging and mortality risk.
期刊介绍：
Nutrition Journal publishes surveillance, epidemiologic, and intervention research that sheds light on i) influences (e.g., familial, environmental) on eating patterns; ii) associations between eating patterns and health, and iii) strategies to improve eating patterns among populations. The journal also welcomes manuscripts reporting on the psychometric properties (e.g., validity, reliability) and feasibility of methods (e.g., for assessing dietary intake) for human nutrition research. In addition, study protocols for controlled trials and cohort studies, with an emphasis on methods for assessing dietary exposures and outcomes as well as intervention components, will be considered.
Manuscripts that consider eating patterns holistically, as opposed to solely reductionist approaches that focus on specific dietary components in isolation, are encouraged. Also encouraged are papers that take a holistic or systems perspective in attempting to understand possible compensatory and differential effects of nutrition interventions. The journal does not consider animal studies.
In addition to the influence of eating patterns for human health, we also invite research providing insights into the environmental sustainability of dietary practices. Again, a holistic perspective is encouraged, for example, through the consideration of how eating patterns might maximize both human and planetary health.
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