Evidence map›Paper›PMID 37764694›Full record

ArticleNutrients2023

Coffee Consumption and Incidence of Cardiovascular and Microvascular Diseases in Never-Smoking Adults with Type 2 Diabetes Mellitus.

Yu-Jie Liu, Meng-Yuan Miao, Jia-Min Wang, Quan Tang, Wen-Wen Han, Yi-Ping Jia, Hao-Wei Tao, Yan Zheng, Rob M van Dam, Li-Qiang Qin and 1 more

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
2.9field-weighted citation impact, top 9% of its field
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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. 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

11 authors at 3 institutions in 2 countries.

Yu-Jie LiuDepartment of Nutrition and Food Hygiene, Suzhou Medical College of Soochow University, Suzhou 215127, China.
Meng-Yuan MiaoDepartment of Nutrition and Food Hygiene, Suzhou Medical College of Soochow University, Suzhou 215127, China.
Jia-Min WangDepartment of Nutrition and Food Hygiene, Suzhou Medical College of Soochow University, Suzhou 215127, China.
Quan TangYancheng Center for Disease Control and Prevention, Yancheng 224002, China.
Wen-Wen HanDepartment of Nutrition and Food Hygiene, Suzhou Medical College of Soochow University, Suzhou 215127, China.
Yi-Ping JiaDepartment of Nutrition and Food Hygiene, Suzhou Medical College of Soochow University, Suzhou 215127, China.
Hao-Wei TaoDepartment of Nutrition and Food Hygiene, Suzhou Medical College of Soochow University, Suzhou 215127, China.
Yan ZhengState Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Fudan University, Shanghai 200438, China.ORCID 0000-0003-1129-3147
Rob M van DamDepartment of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University, Washington, DC 20037, USA.ORCID 0000-0002-7354-8734
Li-Qiang QinDepartment of Nutrition and Food Hygiene, Suzhou Medical College of Soochow University, Suzhou 215127, China.ORCID 0000-0002-5231-2562
Guo-Chong ChenDepartment of Nutrition and Food Hygiene, Suzhou Medical College of Soochow University, Suzhou 215127, China.
Soochow University · CNFudan University · CNMilken Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The relationship between coffee consumption and diabetes-related vascular complications remains unclear. To eliminate confounding by smoking, this study assessed the relationships of coffee consumption with major cardiovascular disease (CVD) and microvascular disease (MVD) in never-smokers with type 2 diabetes mellitus (T2DM). Included were 9964 never-smokers with T2DM from the UK Biobank without known CVD or cancer at baseline (7781 were free of MVD). Participants were categorized into four groups according to daily coffee consumption (0, 0.5-1, 2-4, ≥5 cups/day). CVD included coronary heart disease (CHD), myocardial infarction (MI), stroke, and heart failure (HF). MVD included retinopathy, peripheral neuropathy, and chronic kidney disease (CKD). Cox regression models were used to estimate hazard ratios (HRs) and 95% confidential intervals (CIs) of total CVD and MVD and the component outcomes associated with coffee consumption. During a median of 12.7 years of follow-up, 1860 cases of CVD and 1403 cases of MVD were identified. Coffee intake was nonlinearly and inversely associated with CVD (P-nonlinearity = 0.023) and the component outcomes. Compared with no coffee intake, HRs (95% CIs) associated with a coffee intake of 2 to 4 cups/day were 0.82 (0.73, 0.93) for CVD, 0.84 (0.73, 0.97) for CHD, 0.73 (0.57, 0.92) for MI, 0.76 (0.57, 1.02) for stroke, and 0.68 (0.55, 0.85) for HF. Higher coffee intake (≥5 cups/day) was not significantly associated with CVD outcomes. Coffee intake was linearly and inversely associated with risk of CKD (HR for ≥5 vs. 0 cups/day = 0.64; 95% CI: 0.45, 0.91; P-trend = 0.0029) but was not associated with retinopathy or peripheral neuropathy. Among never-smoking individuals with T2DM, moderate coffee consumption (2-4 cups/day) was associated with a lower risk of various CVD outcomes and CKD, with no adverse associations for higher consumption.

Indexed as

Cardiovascular DiseasesCoronary DiseaseDiabetes Mellitus, Type 2Heart FailureMyocardial InfarctionRenal Insufficiency, ChronicStrokeAdultCoffeeHumansIncidenceRisk FactorsSmokingCoffeecardiovascular diseasescoffeemicrovascular diseasestype 2 diabetes mellitus

Identifiers

PMID37764694
PMCPMC10535817
OpenAlexW4386542203

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.