Suppr超能文献

基于三种机器学习方法的矿物质摄入与血液同型半胱氨酸水平之间的关系:一项大型横断面研究。

Relationships between minerals' intake and blood homocysteine levels based on three machine learning methods: a large cross-sectional study.

机构信息

Key Laboratory of Public Health Safety of Ministry of Education, School of Public Health, Fudan University, Shanghai, 200032, China.

Department of Clinical Nutrition, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361003, China.

出版信息

Nutr Diabetes. 2024 Jun 1;14(1):36. doi: 10.1038/s41387-024-00293-3.

Abstract

BACKGROUND

Blood homocysteine (Hcy) level has become a sensitive indicator in predicting the development of cardiovascular disease. Studies have shown an association between individual mineral intake and blood Hcy levels. The effect of mixed minerals' intake on blood Hcy levels is unknown.

METHODS

Data were obtained from the baseline survey data of the Shanghai Suburban Adult Cohort and Biobank(SSACB) in 2016. A total of 38273 participants aged 20-74 years met our inclusion and exclusion criteria. Food frequency questionnaire (FFQ) was used to calculate the intake of 10 minerals (calcium, potassium, magnesium, sodium, iron, zinc, selenium, phosphorus, copper and manganese). Measuring the concentration of Hcy in the morning fasting blood sample. Traditional regression models were used to assess the relationship between individual minerals' intake and blood Hcy levels. Three machine learning models (WQS, Qg-comp, and BKMR) were used to the relationship between mixed minerals' intake and blood Hcy levels, distinguishing the individual effects of each mineral and determining their respective weights in the joint effect.

RESULTS

Traditional regression model showed that higher intake of calcium, phosphorus, potassium, magnesium, iron, zinc, copper, and manganese was associated with lower blood Hcy levels. Both Qg-comp and BKMR results consistently indicate that higher intake of mixed minerals is associated with lower blood Hcy levels. Calcium exhibits the highest weight in the joint effect in the WQS model. In Qg-comp, iron has the highest positive weight, while manganese has the highest negative weight. The BKMR results of the subsample after 10,000 iterations showed that except for sodium, all nine minerals had the high weights in the joint effect on the effect of blood Hcy levels.

CONCLUSION

Overall, higher mixed mineral's intake was associated with lower blood Hcy levels, and each mineral contributed differently to the joint effect. Future studies are available to further explore the mechanisms underlying this association, and the potential impact of mixed minerals' intake on other health indicators needs to be further investigated. These efforts will help provide additional insights to deepen our understanding of mixed minerals and their potential role in health maintenance.

摘要

背景

血液同型半胱氨酸(Hcy)水平已成为预测心血管疾病发展的敏感指标。研究表明,个体矿物质摄入与血液 Hcy 水平之间存在关联。混合矿物质摄入对血液 Hcy 水平的影响尚不清楚。

方法

数据来自 2016 年上海郊区成人队列和生物库(SSACB)的基线调查数据。共有 38273 名 20-74 岁符合纳入和排除标准的参与者。使用食物频率问卷(FFQ)计算 10 种矿物质(钙、钾、镁、钠、铁、锌、硒、磷、铜和锰)的摄入量。清晨空腹血样测量 Hcy 浓度。传统回归模型用于评估个体矿物质摄入与血液 Hcy 水平之间的关系。三种机器学习模型(WQS、Qg-comp 和 BKMR)用于评估混合矿物质摄入与血液 Hcy 水平之间的关系,区分每种矿物质的个体效应,并确定它们在联合效应中的各自权重。

结果

传统回归模型显示,钙、磷、钾、镁、铁、锌、铜和锰的摄入量较高与血液 Hcy 水平较低相关。Qg-comp 和 BKMR 结果均表明,混合矿物质的摄入量较高与血液 Hcy 水平较低相关。在 WQS 模型中,钙在联合效应中的权重最高。在 Qg-comp 中,铁具有最高的正权重,而锰具有最高的负权重。经过 10000 次迭代后的子样本 BKMR 结果表明,除了钠之外,所有 9 种矿物质在联合效应中对血液 Hcy 水平的影响均具有较高的权重。

结论

总体而言,较高的混合矿物质摄入量与较低的血液 Hcy 水平相关,且每种矿物质对联合效应的贡献不同。未来的研究可进一步探讨这种关联的机制,以及混合矿物质摄入对其他健康指标的潜在影响需要进一步研究。这些努力将有助于提供更多的见解,加深我们对混合矿物质及其在维持健康方面的潜在作用的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3df6/11144190/b8a4ecd0a995/41387_2024_293_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验