Evidence map›Paper›PMID 39516497›Full record

ArticleScientific reports2024

Using three statistical methods to analyze the associations between a mixture of multi-nutrients and risk of mild cognitive impairment in an elderly population in Northern China.

Xian Gao, Yan Wang, Qingxia Li, Xin Huang, Yan Sun, Yutian Zhou, Huichen Zhu, Shiyao Liu, Yuxia Ma

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Xian Gao *Department of Nutrition and Food Hygiene, School of Public Health, Hebei Province Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang, China.
Yan Wang *Department of Nutrition, The Second Hospital of Hebei Medical University, No. 215 Heping West Road, Shijiazhuang, Hebei, 050000, China.
Qingxia Li *Department of Nutrition and Food Hygiene, School of Public Health, Hebei Province Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang, China.
Xin HuangDepartment of Nutrition and Food Hygiene, School of Public Health, Hebei Province Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang, China.
Yan SunDepartment of Nutrition and Food Hygiene, School of Public Health, Hebei Province Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang, China.
Yutian ZhouDepartment of Nutrition and Food Hygiene, School of Public Health, Hebei Province Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang, China.
Huichen ZhuDepartment of Nutrition and Food Hygiene, School of Public Health, Hebei Province Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang, China.
Shiyao LiuDepartment of Nutrition and Food Hygiene, School of Public Health, Hebei Province Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang, China.
Yuxia MaDepartment of Nutrition and Food Hygiene, School of Public Health, Hebei Province Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang, China. mayuxia@hebmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Few studies have considered nutrients as a mixture and their impact on Mild Cognitive Impairment (MCI). The generalized linear regression (GLM), weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) models are fitted to estimate the association between intake of a mixture of nutrients and MCI. Comparing the results from these three models, vitamin E and vitamin B6 were identified as the most important factors associated with the risk of MCI. Considering the characteristics of BKMR, it may be more advantageous to use BKMR to estimate the combined the joint effects of nutrients mixture. In the future, studies need to move from a "one nutrient at a time" approach to simultaneous analyses of multiple nutrients intakes in order to understand and quantify the joint effect of nutrients mixture on health.

Indexed as

Cognitive DysfunctionModels, StatisticalNutrientsAgedBayes TheoremChinaEatingFemaleHumansLinear ModelsMaleOdds RatioProbabilityRisk FactorsNutrientsBKMR modelGLMMCINutrientsWQS regression model

Identifiers

PMID39516497
PMCPMC11549350

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.