Risk of Incident Cardiovascular Diseases at National and Subnational Levels in Iran From 2000 to 2016 and Projection Through 2030: Insights From Iran Steps Surveys Publisher Pubmed



Ebrahimi H¹ ; Masinaei M¹ ; Aminorroaya A^{1, 2} ; Aryan Z^{1, 3} ; Mehdipour P⁴ ; Rostamabadi Y⁵ ; Ahmadi N¹ ; Saeedi Moghaddam S^{1, 6} ; Pishgar F⁷ ; Ghanbari A¹ ; Rezaei N¹ ; Takian A^{8, 9, 10} ; Farzadfar F^{1, 11} Show Affiliations
Source: PLoS ONE Published:2023

Abstract

Background Cardiovascular Disease (CVD) is the leading cause of death in developing countries. CVD risk stratification guides the health policy to make evidence-based decisions. Aim To provide current picture and future trend of CVD risk in the adult Iranian population. Methods Nationally representative datasets of 2005, 2006, 2007, 2008, 2009, 2011, and 2016 STEPwise approach to non-communicable diseases risk factor surveillance (STEPS) studies were used to generate the 10-year and 30-year risks of CVD based on Framingham, Globorisk, and World Health Organization (WHO) risk estimation models. Trend of CVD risk was calculated from 2000 until 2016 and projected to 2030. Results In 2016, based on Framingham model, 14.0% of the Iranian, aged 30 to 74, were at great risk (≥20%) of CVD in the next 10 years (8.0% among females, 20.7% among males). Among those aged 25 to 59, 12.7% had ≥45% risk of CVD in the coming 30 years (9.2% among females, 16.6 among males). In 2016, CVD risk was higher among urban area inhabitants. Age-standardized Framingham 10-year CVD risk will increase 32.2% and 19%, from 2000 to 2030, in females and males, respectively. Eastern provinces had the lowest and northern provinces had the greatest risk. Conclusions This study projected that CVD risk has increased from 2000 to 2016 in Iran. Without further risk factor modification, this trend will continue until 2030. We have identified populations at higher risks of CVD to guide future intervention. © 2023 Ebrahimi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.