Evidence mapPaperPMID 39275199Full record

ArticleNutrients2024

Dietary Carbohydrates, Genetic Susceptibility, and Gout Risk: A Prospective Cohort Study in the UK.

Baojie Hua, Ziwei Dong, Yudan Yang, Wei Liu, Shuhui Chen, Ying Chen, Xiaohui Sun, Ding Ye, Jiayu Li, Yingying Mao

Abstract read
In one paragraph

Article in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

10 authors.

Baojie HuaDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Ziwei DongDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Yudan YangDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Wei LiuDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Shuhui ChenDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Ying ChenDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Xiaohui SunDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Ding YeDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China.ORCID 0000-0001-6654-7832
Jiayu LiDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Yingying MaoDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China.ORCID 0000-0003-3644-9160

Funding

National Natural Science Foundation of China 81973663National Natural Science Foundation of China 82174208Natural Science Foundation of Zhejiang Province LY22H260005
6 · The paper itself

Abstract

This study aimed to investigate the associations between carbohydrate intake and gout risk, along with interactions between genetic susceptibility and carbohydrates, and the mediating roles of biomarkers. We included 187,387 participants who were free of gout at baseline and completed at least one dietary assessment in the UK Biobank. Cox proportional hazard models were used to estimate the associations between carbohydrate intake and gout risk. Over a median follow-up of 11.69 years, 2548 incident cases of gout were recorded. Total carbohydrate intake was associated with a reduced gout risk (Q4 vs. Q1: HR 0.67, 95% CI 0.60-0.74), as were total sugars (0.89, 0.80-0.99), non-free sugars (0.70, 0.63-0.78), total starch (0.70, 0.63-0.78), refined grain starch (0.85, 0.76-0.95), wholegrain starch (0.73, 0.65-0.82), and fiber (0.72, 0.64-0.80), whereas free sugars (1.15, 1.04-1.28) were associated with an increased risk. Significant additive interactions were found between total carbohydrates and genetic risk, as well as between total starch and genetic risk. Serum urate was identified as a significant mediator in all associations between carbohydrate intake (total, different types, and sources) and gout risk. In conclusion, total carbohydrate and different types and sources of carbohydrate (excluding free sugars) intake were associated with a reduced risk of gout.

Indexed as

Dietary CarbohydratesGenetic Predisposition to DiseaseGoutAdultAgedBiomarkersDietFemaleHumansMaleMiddle AgedProportional Hazards ModelsProspective StudiesRisk FactorsUnited KingdomUric AcidBiomarkersDietary CarbohydratesUric Acidbiomarkerscohort studydietary carbohydratesgenetic riskgoutmediation analysis

Identifiers

PMID39275199
PMCPMC11397129

What Socratic holds

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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 Socratic graph.