Evidence map›Paper›PMID 36373514›Full record

ArticleThe American journal of clinical nutrition2022

Habitual coffee consumption and subsequent risk of type 2 diabetes in individuals with a history of gestational diabetes - a prospective study.

Jiaxi Yang, Deirdre K Tobias, Shanshan Li, Shilpa N Bhupathiraju, Sylvia H Ley, Stefanie N Hinkle, Frank Qian, Zhangling Chen, Yeyi Zhu, Wei Bao and 3 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The American journal of clinical nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 12% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 10 institutions in 4 countries.

Jiaxi YangGlobal Center for Asian Women's Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
Deirdre K TobiasDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Shanshan LiDepartment of Medicine, Boston University School of Medicine, Boston, MA, USA.ORCID 0000-0001-9177-1385
Shilpa N BhupathirajuDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Sylvia H LeyDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.ORCID 0000-0003-0084-2630
Stefanie N HinkleDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Frank QianDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Zhangling ChenDepartment of Epidemiology, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Yeyi ZhuDivision of Research, Kaiser Permanente Northern California, Oakland, CA, USA.ORCID 0000-0002-7296-738X
Wei BaoDivision of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Jorge E ChavarroDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0002-4436-9630
Frank B HuDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Cuilin ZhangGlobal Center for Asian Women's Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.ORCID 0000-0002-8014-2708
Brigham and Women's Hospital · USHarvard University · USBeth Israel Deaconess Medical Center · USBoston University · USErasmus MC · NLKaiser Permanente · USNational University of Singapore · SGTulane University · USUniversity of Pennsylvania · USUniversity of Science and Technology of China · CN

Funding

Tulane COBRE in Cardiometabolic Diseases Clinical Research CoreP20GM109036 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI Ning Liu · 2016 to 2026
$25.3M
Transgenic CoreP30DK046200 · NIDDK · TUFTS MEDICAL CENTER · PI CORKEY, BARBARA E. · 1992 to 2021
$25.0M
Life Course Cancer Epidemiology Cohort in WomenU01CA176726 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI ELIASSEN, A. HEATHER, WILLETT, WALTER C. · 2018 to 2025
$22.4M
Integrating lifecourse approaches, biologic and digital phenotypes in support of heart and lung disease epidemiologic researchU01HL145386 · NHLBI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI CHAVARRO, JORGE EDUARDO, MANSON, JOANN ELISABETH · 2019 to 2025
$17.8M
Premonopausal Hormone Levels and Risk of Breast CancerR01CA067262 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI HANKINSON, SUSAN E · 2002 to 2011
$11.9M
NCI NIH HHS R01 CA067262NCI NIH HHS U01 CA176726NHLBI NIH HHS U01 HL145386NICHD NIH HHS HHSN275201000020CNICHD NIH HHS HHSN275201100002CNICHD NIH HHS HHSN275201100002GNIDDK NIH HHS P30 DK046200NIGMS NIH HHS P20 GM109036NIH HHS U01 CA176726
6 · The paper itself

Abstract

backgroundFemales with a history of gestational diabetes mellitus (GDM) are at higher risk of developing type 2 diabetes mellitus (T2D) later in life.

objectiveThis study prospectively examined whether greater habitual coffee consumption was related to a lower risk of T2D among females with a history of GDM.

methodsWe followed 4522 participants with a history of GDM in the NHS II for incident T2D between 1991 and 2017. Demographic, lifestyle factors including diet, and disease outcomes were updated every 2-4 y. Participants reported consumption of caffeinated and decaffeinated coffee on validated FFQs. Fasting blood samples were collected in 2012-2014 from a subset of participants free of diabetes to measure glucose metabolism biomarkers (HbA1c, insulin, C-peptide; n = 518). We used multivariable Cox regression models to calculate adjusted HRs and 95% CIs for the risk of T2D. We estimated the least squares mean of glucose metabolic biomarkers according to coffee consumption.

resultsA total of 979 participants developed T2D. Caffeinated coffee consumption was inversely associated with the risk of T2D. Adjusted HR (95% CI) for ≤1 (nonzero), 2-3, and 4+ cups/d compared with 0 cup/d (reference) was 0.91 (0.78, 1.06), 0.83 (0.69, 1.01), and 0.46 (0.28, 0.76), respectively (P-trend = 0.004). Replacement of 1 serving/d of sugar-sweetened beverage and artificially sweetened beverage with 1 cup/d of caffeinated coffee was associated with a 17% (risk ratio [RR] = 0.83, 95% CI: 0.75, 0.93) and 9% (RR = 0.91, 95% CI: 0.84, 0.99) lower risk of T2D, respectively. Greater caffeinated coffee consumption was associated with lower fasting insulin and C-peptide concentrations (all P-trend <0.05). Decaffeinated coffee intake was not significantly related to T2D but was inversely associated with C-peptide concentrations (P-trend = 0.003).

conclusionsAmong predominantly Caucasian females with a history of GDM, greater consumption of caffeinated coffee was associated with a lower risk of T2D and a more favorable metabolic profile.

Indexed as

Diabetes, GestationalDiabetes Mellitus, Type 2BiomarkersCoffeeC-PeptideFemaleHumansPregnancyProspective StudiesRisk FactorsSweetening AgentsBiomarkersCoffeeC-PeptideSweetening Agentscoffee consumptiondietindividuals with a history of gestational diabetes mellitusnutritiontype 2 diabetes risk

Identifiers

PMID36373514
PMCPMC9761754
OpenAlexW4308957542

What OpenQuestion holds

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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.