Evidence map›Paper›PMID 38708436›Full record

ArticleJournal of diabetes2024

Clustering of health behaviors and their associations with cardiometabolic risk factors among adults at high risk for type 2 diabetes in India: A latent class analysis.

Gabrielli T de Mello, Sathish Thirunavukkarasu, Panniyammakal Jeemon, Kavumpurathu R Thankappan, Brian Oldenburg, Yingting Cao

Abstract read
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Article in Journal of diabetes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Gabrielli T de MelloResearch Center for Physical Activity and Health, Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil.ORCID https://orcid.org/0000-0002-6745-1901
Sathish ThirunavukkarasuDepartment of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, Georgia, USA.ORCID https://orcid.org/0000-0002-2016-4964
Panniyammakal JeemonAchutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, India.
Kavumpurathu R ThankappanDepartment of Public Health, Amrita Institute of Medical Sciences, Kochi, Kerala, India.
Brian OldenburgBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Yingting CaoBaker Heart and Diabetes Institute, Melbourne, Victoria, Australia.

Funding

Building the Asian NCoD Research Network for Regional Research CapacityD43TW008332 · FIC · MONASH UNIVERSITY · PI FISHER, EDWIN B, KADIR, KHALID · 2010 to 2014
$1.0M
CDC HHS #75D30120P0742FIC NIH HHS D43 TW008332FIC NIH HHS D43TW008332
6 · The paper itself

Abstract

backgroundWe aimed to identify clusters of health behaviors and study their associations with cardiometabolic risk factors in adults at high risk for type 2 diabetes in India.

methodsBaseline data from the Kerala Diabetes Prevention Program (n = 1000; age 30-60 years) were used for this study. Information on physical activity (PA), sedentary behavior, fruit and vegetable intake, sleep, and alcohol and tobacco use was collected using questionnaires. Blood pressure, waist circumference, 2-h plasma glucose, high-density lipoprotein and low-density lipoprotein cholesterol, and triglycerides were measured using standardized protocols. Latent class analysis was used to identify clusters of health behaviors, and multilevel mixed-effects linear regression was employed to examine their associations with cardiometabolic risk factors.

resultsTwo classes were identified, with 87.4% of participants in class 1 and 12.6% in class 2. Participants in both classes had a high probability of not engaging in leisure-time PA (0.80 for class 1; 0.73 for class 2) and consuming <5 servings of fruit and vegetables per day (0.70 for class 1; 0.63 for class 2). However, participants in class 1 had a lower probability of sitting for >=3 h per day (0.26 vs 0.42), tobacco use (0.10 vs 0.75), and alcohol use (0.08 vs 1.00) compared to those in class 2. Class 1 had a significantly lower mean systolic blood pressure (β = -3.70 mm Hg, 95% confidence interval [CI] -7.05, -0.36), diastolic blood pressure (β = -2.45 mm Hg, 95% CI -4.74, -0.16), and triglycerides (β = -0.81 mg/dL, 95% CI -0.75, -0.89).

conclusionImplementing intervention strategies, tailored to cluster-specific health behaviors, is required for the effective prevention of cardiometabolic disorders among high-risk adults for type 2 diabetes.

Indexed as

Cardiometabolic Risk FactorsDiabetes Mellitus, Type 2Health BehaviorLatent Class AnalysisAdultBlood PressureCardiovascular DiseasesCluster AnalysisExerciseFemaleHumansIndiaMaleMiddle AgedRisk FactorsSedentary Behaviorcardiometabolic riskclusteringdiabeteshealth behaviorslatent class

Identifiers

PMID38708436
PMCPMC11070839

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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.