Evidence map›Paper›PMID 27468925›Full record

Observational studyJournal of the American Heart Association2016

Obesity and Subtypes of Incident Cardiovascular Disease.

Chiadi E Ndumele, Kunihiro Matsushita, Mariana Lazo, Natalie Bello, Roger S Blumenthal, Gary Gerstenblith, Vijay Nambi, Christie M Ballantyne, Scott D Solomon, Elizabeth Selvin and 2 more

Open access · goldAbstract readMulticenter StudyObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Journal of the American Heart Association, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 138 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
138citing papers in PubMed, 3 pooled it
12.8field-weighted citation impact, top 1% 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

138 citing papers in PubMed, 3 syntheses or guidelines pooled it, 243 citations in OpenAlex.

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78 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 5 institutions in 1 country.

Chiadi E NdumeleJohns Hopkins Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD Department of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD cndumel2@jhmi.edu.
Kunihiro MatsushitaDepartment of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Mariana LazoDepartment of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD Department of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Natalie BelloDivision of Cardiology, Columbia University Medical Center, New York, NY.
Roger S BlumenthalJohns Hopkins Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD.
Gary GerstenblithJohns Hopkins Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD.
Vijay NambiMichael E DeBakey Veterans Affairs Hospital, Houston, TX Division of Atherosclerosis and Vascular Medicine, Baylor College of Medicine, and Center for Cardiovascular Disease Prevention, Methodist DeBakey Heart and Vascular Center, Houston, TX.
Christie M BallantyneDivision of Atherosclerosis and Vascular Medicine, Baylor College of Medicine, and Center for Cardiovascular Disease Prevention, Methodist DeBakey Heart and Vascular Center, Houston, TX.
Scott D SolomonDivision of Cardiology, Brigham and Womens' Hospital, Boston, MA.
Elizabeth SelvinDepartment of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Aaron R FolsomDivision of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.
Josef CoreshDepartment of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Johns Hopkins University · USHouston Methodist · USBrigham and Women's Hospital · USColumbia University Irving Medical Center · USMinnesota Department of Health · US

Funding

Diabetes and Prediabetes in Older Adults in ARICR01DK089174 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI SELVIN, ELIZABETH · 2011 to 2020
$6.4M
The Relationship of Obesity with Subclinical Myocardial Injury and Heart FailureK23HL122447 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI NDUMELE, CHIADI E · 2014 to 2018
$919k
Research and Mentoring in the Clinical Epidemiology of Type 2 DiabetesK24DK106414 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI SELVIN, ELIZABETH · 2015 to 2019
$654k
NHLBI NIH HHS HHSN268201100005CNHLBI NIH HHS HHSN268201100006CNHLBI NIH HHS HHSN268201100007CNHLBI NIH HHS HHSN268201100008CNHLBI NIH HHS HHSN268201100009CNHLBI NIH HHS HHSN268201100010CNHLBI NIH HHS HHSN268201100011CNHLBI NIH HHS HHSN268201100012CNHLBI NIH HHS K23 HL122447NHLBI NIH HHS L30 HL129418NIDDK NIH HHS K24 DK106414NIDDK NIH HHS R01 DK089174
6 · The paper itself

Abstract

backgroundObesity is a risk factor for various subtypes of cardiovascular disease (CVD), including coronary heart disease (CHD), heart failure (HF), and stroke. Nevertheless, there are limited comparisons of the associations of obesity with each of these CVD subtypes, particularly regarding the extent to which they are unexplained by traditional CVD mediators. METHODS AND

resultsWe followed 13 730 participants in the Atherosclerosis Risk in Communities (ARIC) study who had a body mass index ≥18.5 and no CVD at baseline (visit 1, 1987-1989). We compared the association of higher body mass index with incident HF, CHD, and stroke before and after adjusting for traditional CVD mediators (including systolic blood pressure, diabetes mellitus, and lipid measures). Over a median follow-up of 23 years, there were 2235 HF events, 1653 CHD events, and 986 strokes. After adjustment for demographics, smoking, physical activity, and alcohol intake, higher body mass index had the strongest association with incident HF among CVD subtypes, with hazard ratios for severe obesity (body mass index ≥35 versus normal weight) of 3.74 (95% CI 3.24-4.31) for HF, 2.00 (95% CI 1.67-2.40) for CHD, and 1.75 (95% CI 1.40-2.20) for stroke (P<0.0001 for comparisons of HF versus CHD or stroke). Further adjustment for traditional mediators fully explained the association of higher body mass index with CHD and stroke but not with HF (hazard ratio 2.27, 95% CI 1.94-2.64).

conclusionsThe link between obesity and HF was stronger than those for other CVD subtypes and was uniquely unexplained by traditional risk factors. Weight management is likely critical for optimal HF prevention, and nontraditional pathways linking obesity to HF need to be elucidated.

Indexed as

AdultAgedAtherosclerosisBody Mass IndexCardiovascular DiseasesCoronary DiseaseFemaleHeart FailureHumansMaleMemory, EpisodicMiddle AgedObesity, MorbidRisk FactorsSedentary BehaviorStrokecoronary heart diseaseepidemiologyheart failureobesitystroke

Identifiers

PMID27468925
PMCPMC5015307
OpenAlexW2480369291

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.