Evidence map›Paper›PMID 30448248›Full record

ArticleDisability and health journal2019

Prevalence of five lifestyle risk factors among U.S. adults with and without stroke.

Ryan R Bailey, Allison Phad, Ryan McGrath, Debra Haire-Joshu

Abstract read
In one paragraph

Article in Disability and health journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 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

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

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Health risk factors in Australian Stroke Survivors: A latent class analysis.Health promotion journal of Australia : official journal of Australian Association of Health Promotion Professionals · 2024
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  17. Impact of Cardiovascular Diseases on Ischemic Stroke Outcomes.Journal of integrative neuroscience · 2022
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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

4 authors.

Ryan R BaileyWashington University in St. Louis, Brown School of Social Work, Campus Box 1196, One Brookings Drive, St. Louis, MO, 63110, USA. Electronic address: baileyr@wustl.edu.
Allison PhadWashington University in St. Louis, Brown School of Social Work, Campus Box 1196, One Brookings Drive, St. Louis, MO, 63110, USA. Electronic address: allisonphad@wustl.edu.
Ryan McGrathNorth Dakota State University, Department of Health, Nutrition, and Exercise Sciences, NDSU Dept. 2620, PO Box 6050, Fargo, ND, 58108, USA. Electronic address: ryan.mcgrath@ndsu.edu.
Debra Haire-JoshuWashington University in St. Louis, Brown School of Social Work, Campus Box 1196, One Brookings Drive, St. Louis, MO, 63110, USA. Electronic address: djoshu@wustl.edu.

Funding

Washington University Center for Diabetes Translation Research P30DK092950 · NIDDK · WASHINGTON UNIVERSITY · PI Ross C Brownson, Debra Haire-Joshu · 2011 to 2026
$11.7M
WUSTL Transdisciplinary Pre- and Postdoctoral Training Program in Obesity and Cardiovascular DiseaseT32HL130357 · NHLBI · WASHINGTON UNIVERSITY · PI WILFLEY, DENISE ELLA · 2016 to 2025
$4.3M
NHLBI NIH HHS T32 HL130357NIDDK NIH HHS P30 DK092950
6 · The paper itself

Abstract

backgroundHistory of stroke increases cardiometabolic risk, which can be exacerbated by the presence of unhealthy lifestyle factors. Population-based estimates of lifestyle risk factors in people with stroke are lacking but could be used to inform research, policy, and healthcare practice.

objectiveTo compare population-based estimates of the prevalence of five lifestyle risk factors-low fruit and vegetable consumption, insufficient physical activity, smoking, heavy alcohol consumption, and overweight/obesity-among U.S. adults with and without stroke.

methodsRepresentative data from noninstitutionalized adults aged ≥18 years (stroke, n = 37,225; no stroke, n = 851,607) from the 2015 and 2017 Behavioral Risk Factor Surveillance System (BRFSS) were used to estimate prevalence of individual and total number of risk factors. Logistic regression models were used to determine the odds of lifestyle risk factors in adults with stroke, adjusting for sex, age, ethnicity, marital status, education, income, and disability.

resultsPrevalence and adjusted odds ratios (AOR) were higher in individuals with stroke compared to those without stroke for insufficient physical activity (56.5% vs. 49.5%, AOR: 1.14) and smoking (30.1% vs. 16.6%, AOR: 1.16), but lower for heavy alcohol consumption (5.4% vs. 6.1%, AOR: 0.76). Prevalence for low fruit and vegetable consumption (51.7% vs. 46.0%) and overweight/obesity (70.2% vs. 64.5%) was higher among adults with stroke, but differences were attenuated by demographic characteristics. Additionally, clustering of 4-5 lifestyle risk factors was higher in adults with stroke (9.0% vs. 5.3%, AOR: 1.12).

conclusionAdditional research and healthcare interventions are needed to improve lifestyle risk factors in adults with stroke.

Indexed as

Health BehaviorLife StylePersons with DisabilitiesAdolescentAdultAgedAged, 80 and overAlcoholismBehavioral Risk Factor Surveillance SystemDietExerciseFemaleHumansLogistic ModelsMaleMiddle AgedBRFSSHealth behaviorsPhysical activityPrevalenceStroke

Identifiers

PMID30448248
PMCPMC6431268

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.