Meta-analysis: Eating more legumes and soy is linked to lower risk of hypertension, itself a risk factor for cardiovascular disease & related mortality: doi.org/10.1136/bmjn... #Legumes #Beans #Lentils #Chickpeas #Peas #Soybeans #Tofu #Health #Hypertension #CVD #Review #MetaAnalysis

doi.org/10.1136/bmjnph...
Legume and soy consumption and the risk of hypertension: a systematic review and dose–response meta-analysis of prospective studies

Background Several studies have suggested that high intakes of legumes and soy products are associated with a lower risk of hypertension; however, the results have been inconsistent. We conducted a systematic review and meta-analysis to clarify the association between legumes and soy consumption and the risk of hypertension.Methods PubMed and Embase databases were searched up to 14 June 2025. Random effects models were used to calculate summary relative risks (RRs) and 95% confidence intervals (95% CIs) for the association between legume or soy consumption and hypertension risk. Heterogeneity was evaluated using I 2. The likelihood of causality was evaluated using World Cancer Research Fund (WCRF) criteria.Results 12 prospective studies were included in the meta-analysis. The summary RR for high versus low intake of legumes was 0.84 (95% CI 0.77 to 0.93, I 2=65%, pheterogeneity=0.003, n=10 studies, 86 098 cases, 309 853 participants) and for soy was 0.81 (95% CI 0.70 to 0.93, I2=82%, pheterogeneity<0.0001, n=7 studies, 93 934 cases, 278 200 participants). In the linear dose–response analyses, the summary RR per 100 g/day was 0.88 (95% CI 0.80 to 0.97, I2=69%, pheterogeneity=0.001, n=10) for legumes and 0.76 (95% CI 0.60 to 0.96, I2=89%, pheterogeneity<0.0001, n=6) for soy. The test for non-linearity was not significant for legumes (pnon-linearity=0.13), suggesting a linear reduction in risk up to ~170 g/day, while for soy there was indication of non-linearity (pnon-linearity=0.01), and most of the reduction in risk was observed up to an intake around 60–80 g/day. Although there was an indication of publication bias with Egger’s test (p=0.04) for legumes, this was explained by two outlying studies. Using WCRF criteria, the likelihood of causality was considered probable for both legumes and soy in relation to hypertension risk.Conclusion In this meta-analysis of 12 prospective cohort studies, legume and soy intakes were associated with lower risk of hypertension. These findings support dietary recommendations to increase the intake of legumes in the general population.

BMJ Nutrition, Prevention & Health

An update on the CRAN Task View on MetaAnalysis https://cran.r-project.org/view=MetaAnalysis which is still slowly growing. It now has more than 200 packages covering a wide range of situations.

#metaanalysis #Rstats

CRAN Task View: Meta-Analysis

This task view covers packages which include facilities for meta-analysis of summary statistics from primary studies. The task view does not consider the meta-analysis of individual participant data (IPD) which can be handled by any of the standard linear modelling functions but it does include some packages which offer special facilities for IPD.

It's been 84 years... okay, three months, but here's a PhD side quest: a mini meta-analysis.

Analysis & forest plot done in {metafor}, HTML report knitted in RMarkdown, {grateful} for software acknowledgements.

GitHub repo: https://github.com/ale-lazic/vacc_cvrg_meta/

HTML page preview: https://htmlpreview.github.io/?https://github.com/ale-lazic/vacc_cvrg_meta/blob/1d79d6506bc5dca5333fa05cbfb95953817e904b/vacc_cvrg_meta.html

#Rstats #Metaanalysis #Psychology

🔬 Study Review

Effects of berberine on blood glucose in patients with type 2 diabetes mellitus

Researchers combined data from multiple trials to assess berberine for type 2 diabetes. The supplement reduced fasting blood sugar, after-meal glucose, and HbA1c levels. Observed benefits were smaller when taken for more than 90 days, at doses over 2 grams daily, or in participants older than 60.
Meta-analysis

#Type2Diabetes #Berberine #MetaAnalysis

https://s.fitbodyscience.com/EvvYuw

#statstab #531 Effect Size Calculator [Campbell]

Thoughts: A nice place for quick formulas for variance and effect sizes of various designs and data types.

#metaanalysis #effectsize #CohenD #calculator #Variance #Eta #effects

https://www.campbellcollaboration.org/calculator/equations

'Nature' Retracts Paper on the Benefits of ChatGPT in Education
'Nature' 소속 학술지 Humanities & Social Sciences Communications가 ChatGPT가 교육에 긍정적인 영향을 미친다는 내용을 담은 메타분석 논문을 철회했다. 해당 논문은 51개의 연구를 종합해 ChatGPT가 학생들의 학습 성과와 인지 능력에 긍정적 영향을 준다고 주장했으나, 연구의 질이 낮다는 지적을 받았다. 이번 철회는 AI 교육 효과에 대한 신뢰할 만한 데이터와 증거가 필요함을 시사한다.

https://www.404media.co/nature-retracts-paper-on-the-benefits-of-chatgpt-in-education/

#chatgpt #education #researchretraction #aiimpact #metaanalysis

'Nature' Retracts Paper on the Benefits of ChatGPT in Education

“What educators, parents and policy officials really needed was high quality data and evidence to help guide them. What they have had to deal with instead is some substandard research.”

404 Media
Supporting Information for: Fifty years later, and we still don’t know about badges of status

A new version (1.6-0) of the metadat package (https://wviechtb.github.io/metadat/) has been released on CRAN (https://cran.r-project.org/package=metadat). The package provides over 100 meta-analytic datasets, which are useful for teaching and testing purposes.

#RStats #MetaAnalysis

Meta-Analysis Datasets

A collection of meta-analysis datasets for teaching purposes, illustrating/testing meta-analytic methods, and validating published analyses.

#statstab #530 Fisher vs Stouffer

Thoughts: Combining p-values (say in a meta-analysis) is not a straightforward thing. Here are two methods.

#fisher #stouffer #pvalues #metaanalysis #zscores #evidence #falsepositive
#r #simulation

https://timydaley.github.io/FisherVsStouffer.html

Fisher vs Stouffer

Analyzing COVID-19 data reveals:
🔹 Fever in 88.5%
🔹 52% discharge rate
🔹 5% fatality rate
🔹 60% affected were male
#MetaAnalysis #COVID19 #Pub2Post https://dev.https://tnyp.me/BUrL4MuV/m