Association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD): data from the NHANES III (1988-1994).
Ying Zhang, Peng-Yu Luo, Yu-Na Tang, Jing Wang, Shuai Gao, Yu-Chen Fan, Kai Wang
{"title":"Association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD): data from the NHANES III (1988-1994).","authors":"Ying Zhang, Peng-Yu Luo, Yu-Na Tang, Jing Wang, Shuai Gao, Yu-Chen Fan, Kai Wang","doi":"10.1186/s12986-025-00942-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The prognostic value of the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) remains unclear. This study aimed to evaluate the associations between the NHHR and all-cause and cause-specific mortality in patients with MASLD.</p><p><strong>Methods: </strong>Data for this study were obtained from the National Health and Nutrition Examination Survey (NHANES III and the National Death Index (NDI). The NHHR was calculated according to the formula. The results of mortality associated with the NDI were recorded as of December 31, 2019. We used a multivariate Cox proportional hazard model and restricted cubic spline (RCS) regression to assess the associations between the NHHR and all-cause and cause-specific mortality. In addition, subgroup analyses were performed to explore the relationships between the NHHR and all-cause and cause-specific mortality.</p><p><strong>Results: </strong>This study included 3155 patients with a definite diagnosis of MASLD. A total of 1,381 (43.8%) patients with MASLD died, and 1,774 (56.2%) survived. Multivariate Cox proportional hazards model analysis showed that NHHR was not significantly associated with all-cause mortality in MASLD patients. The RCS curve showed a significant nonlinear trend between the NHHR and all-cause mortality in patients with MASLD. Subgroup analysis revealed that the NHHR was better suited to predict cardiovascular mortality in patients without advanced fibrosis.</p><p><strong>Conclusions: </strong>Our study revealed the clinical value of the NHHR in the prediction of mortality in the MASLD population. The NHHR can be used as a biomarker for follow-up in people without advanced fibrosis.</p>","PeriodicalId":19196,"journal":{"name":"Nutrition & Metabolism","volume":"22 1","pages":"46"},"PeriodicalIF":4.1000,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12093885/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nutrition & Metabolism","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12986-025-00942-z","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The prognostic value of the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) remains unclear. This study aimed to evaluate the associations between the NHHR and all-cause and cause-specific mortality in patients with MASLD.
Methods: Data for this study were obtained from the National Health and Nutrition Examination Survey (NHANES III and the National Death Index (NDI). The NHHR was calculated according to the formula. The results of mortality associated with the NDI were recorded as of December 31, 2019. We used a multivariate Cox proportional hazard model and restricted cubic spline (RCS) regression to assess the associations between the NHHR and all-cause and cause-specific mortality. In addition, subgroup analyses were performed to explore the relationships between the NHHR and all-cause and cause-specific mortality.
Results: This study included 3155 patients with a definite diagnosis of MASLD. A total of 1,381 (43.8%) patients with MASLD died, and 1,774 (56.2%) survived. Multivariate Cox proportional hazards model analysis showed that NHHR was not significantly associated with all-cause mortality in MASLD patients. The RCS curve showed a significant nonlinear trend between the NHHR and all-cause mortality in patients with MASLD. Subgroup analysis revealed that the NHHR was better suited to predict cardiovascular mortality in patients without advanced fibrosis.
Conclusions: Our study revealed the clinical value of the NHHR in the prediction of mortality in the MASLD population. The NHHR can be used as a biomarker for follow-up in people without advanced fibrosis.
期刊介绍:
Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects.
The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases.
Key areas we wish to encourage submissions from include:
-how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes;
-the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components;
-how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved;
-how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.