Evidence map›Paper›PMID 39462359›Full record

ArticleBMC medical research methodology2024

Office-based risk equation of Globorisk for prediction of ten-years cardiovascular risk among Iranian population: findings from Fasa PERSIAN cohort study.

Amir Baseri, Azizallah Dehghan, Rozhan Khezri, Zahra Montaseri, Dagfinn Aune, Fatemeh Rezaei

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Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Amir BaseriStudent Research Committee, Jahrom University of Medical Sciences, Jahrom, Iran.
Azizallah DehghanNoncommunicable Diseases Research Center, Fasa University of Medical Sciences, Fasa, Iran.
Rozhan KhezriStudent Research Committee, Iran University of Medical Sciences, Tehran, Iran.
Zahra MontaseriNoncommunicable Diseases Research Center, Fasa University of Medical Sciences, Fasa, Iran.
Dagfinn AuneDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Fatemeh RezaeiResearch Center for Social Determinants of Health, Jahrom University of Medical Sciences, Jahrom, Iran. frezaeik@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGloborisk is one of the prediction tools for 10-year risk assessment of cardiovascular disease, featuring an office-based (non-laboratory-based) version. This version does not require laboratory tests for determining the CVD risk. The present study aims to determine the 10-year CVD risk using the office-based Globorisk model and factors associated with the 10-year CVD risk.

methodsIn this study, baseline data from 6810 individuals participating in the Fasa cohort study, with no history of CVD or stroke, were utilized. The risk equation of the office-based Globorisk model incorporates age, sex, systolic blood pressure (SBP), body mass index (BMI), and smoking status. The Globorisk model categorizes the risk into three groups: low risk (< 10%), moderate risk (10% to < 20%), and high risk (≥ 20%). To identify factors associated with the 10-year CVD risk, the predicted risk was categorized into two groups: <10% and ≥ 10%. Multivariable logistic regression analysis was employed to determine factors associated with an increased CVD risk.

resultsAccording to the 10-year CVD risk categorization, 78.3%, 16.4%, and 5.3% of men were in the low, moderate, and high risk groups, respectively, while 85.8%, 10.0%, and 4.2%, of women were in the respective risk groups. Multivariable logistic regression results indicated that in men, the 10-year CVD risk decreases with being an opium user, and increases with being illiterate, having abdominal obesity, and low or moderate physical activity compared to high physical activity. In women, being married, and higher fiber consumption decrease the 10-year CVD risk, while being illiterate, low or moderate physical activity compared to high physical activity, having abdominal obesity, opium use, and being in wealth quintiles 1 to 4 compared to quintile 5 increase the risk.

conclusionsConsidering the factors associated with increased CVD risk, there is a need to enhance awareness and modify lifestyle to mitigate and reduce the risk of CVD. Additionally, early identification of individuals at moderate to high risk is essential for preventing disease progression. The use of the office-based Globorisk model can be beneficial in settings where resources are limited for determining the 10-year CVD risk.

Indexed as

Cardiovascular DiseasesAdultAgedBlood PressureBody Mass IndexCohort StudiesFemaleHeart Disease Risk FactorsHumansIranMaleMiddle AgedRisk AssessmentRisk FactorsSmokingCardiovascular diseasesGloboriskOffice-basedRisk assessment

Identifiers

PMID39462359
PMCPMC11514861

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.