Evidence map›Paper›PMID 41788956›Full record

ArticleJournal of education and health promotion2026

Multifactorial determinants of cardiovascular disease: The role of socio-demographic, lifestyle, and morbidity factors.

Sharada Ashok Jadhav, S V Kakade, Abhijeet B Shelke, Satyajeet Ashok Jadhav, Sheela D Kadam

Abstract read
In one paragraph

Article in Journal of education and health promotion, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Sharada Ashok JadhavDepartment of Community Medicine, Krishna Vishwa Vidyapeeth (Deemed to be University), Karad, Maharashtra, India.
S V KakadeDepartment of Community Medicine, Krishna Vishwa Vidyapeeth (Deemed to be University), Karad, Maharashtra, India.
Abhijeet B ShelkeDepartment of Cardiology, Krishna Vishwa Vidyapeeth (Deemed to be University), Karad, Maharashtra, India.
Satyajeet Ashok JadhavDepartment of Mechanical, Government College of Engineering, Karad, Maharashtra, India.
Sheela D KadamDepartment of Anatomy, Krishna Vishwa Vidyapeeth (Deemed to be University), Karad, Maharashtra, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCardiovascular disease (CVD) development was influenced by various factors, including socio-demographic aspects (age, gender, socioeconomic status, education), lifestyle behaviors (diet, physical activity, smoking, alcohol use), health conditions (hypertension, diabetes, obesity), and genetics. The aim was to examine how these factors relate to the likelihood of CVD confirmation through angiography. Understanding one's CVD risk is essential for several reasons. Predicting CVD risk involves using factors such as age, exercise habits, diabetes, tobacco use, and marital status, along with statistical models. To determine how socio-demographic factors, health conditions, and self-control relate to the likelihood of confirming cardiovascular disease through angiography. MATERIALS AND

methodsAn observational cross-sectional study analyzed angiography reports from 274 participants at Krishna Vishwa Vidhypeeth, Karad, Maharashtra, with CVD complaints from January to May 2023. Statistical analysis was done using Microsoft Excel, Instat, and SPSS version 28. The Chi-Square test assessed the link between demographic parameters, Lifestyle, and Morbidity Factors with CVD, while backward logistic regression was used to create a predictive model.

resultsAngiography revealed several key factors strongly linked to cardiovascular disease (CVD): regular exercise (79.46% of cases), tobacco chewing (69.7%), diabetes (75.45%), and age. The proportion of significant findings increased with age: 20% in the 20-39 age group, 44.7% in the 40-49 group, 65.1% in the 50-59 group, 75.8% in the 60-69 group, 70.3% in the 70-79 group, and 71.4% in the 80-89 group. Backward logistic regression analysis affirmed these factors as the most reliable predictors of CVD, highlighting the importance of lifestyle choices and co-morbidities in the risk of coronary artery disease.

conclusionRecognizing the risk factors for cardiovascular disease enables proactive prevention, timely intervention, and efficient management, which improves individual health and reduces the broader societal effects of CVD. Modifiable risk factors like exercise and tobacco use can be adjusted to significantly lower one's risk of developing the disease.

Indexed as

CVD (MeSH Unique ID: D002318)multicollinearitytolerancevariance inflation factor

Identifiers

PMID41788956
PMCPMC12959545

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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.