Evidence map›Paper›PMID 40200226›Full record

ArticleBMC public health2025

Trends in the burden of chronic kidney disease related to high red meat intake from 1990 to 2021.

Miaofei Dai, Haixu Guo

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 2 pooled it
–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

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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, 2 syntheses or guidelines pooled it.

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  3. Article
4 · The record

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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

2 authors.

Miaofei DaiNephrology Department, Maoming People's Hospital, Maoming, Guangdong, China.
Haixu GuoIntensive Care Unit Section 3, Maoming People's Hospital, Maoming, Guangdong, China. guohaixu@stu.hebmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo systematically examine global trends and spatial distribution of the burden of chronic kidney disease associated with high red meat intake from 1990 to 2021 using data from the Global Burden of Disease 2021 study, providing scientific evidence for targeted prevention strategies.

methodsWe assessed disease burden using age-standardized death rate and age-standardized disability-adjusted life year rate. Disease burden was analyzed by sex, age, region, and Socio-demographic Index level, while estimated annual percentage change was calculated to evaluate temporal trends.For the analysis of future trends in chronic kidney disease burden, we utilized both the Age-Period-Cohort model and the Bayesian Age-Period-Cohort model.

resultsFrom 1990 to 2021, age-standardized death rate and disability-adjusted life year rates of chronic kidney disease linked to high red meat intake increased, with EAPCs of 1.33% and 1.07%, respectively. Males consistently exhibited a higher disease burden than females, with mortality peaking in the 85-89 age group. The age-standardized disability-adjusted life year rate in high-SDI groups (6.59 per 100,000) was significantly higher than in low-SDI groups (2.38 per 100,000). A temporary decline occurred between 2016 and 2018, and disease burden decreased among individuals over 95 years old between 2018 and 2021.

conclusionThe chronic kidney disease burden associated with high red meat intake demonstrated significant demographic and regional disparities, characterized by an overall increasing trend with some period-specific exceptions. These findings suggest the need for targeted public health interventions, particularly dietary guidance for high-risk populations such as males and residents of high-SDI groups. Future research should focus on elucidating the underlying biological mechanisms and social determinants that drive these disparities.

Indexed as

Cost of IllnessRed MeatRenal Insufficiency, ChronicAdultAgedAged, 80 and overDisability-Adjusted Life YearsFemaleGlobal Burden of DiseaseGlobal HealthHumansMaleMiddle AgedYoung AdultChronic kidney diseaseDisease burdenGlobal health trendsRed meat consumption

Identifiers

PMID40200226
PMCPMC11978116

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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.