Prevalence of physical inactivity in Iran: a systematic review

• Main Authors: Hossein Fakhrzadeh, Shirin Djalalinia, Mojdeh Mirarefin, Tahereh Arefirad, Hamid Asayesh, Saeid Safiri, Elham Samami, Morteza Mansourian, Mostafa Qorbani
• Format: Article
• Language: English
• Published: Tabriz University of Medical Sciences 2016-09-01
• Series: Journal of Cardiovascular and Thoracic Research
• Subjects: Physical Inactivity; Systematic Review; Iran
• Online Access: http://jcvtr.tbzmed.ac.ir/PDF/JCVTR-8-92.pdf

Introduction: Physical inactivity is one of the most important risk factors for chronic diseases, including cardiovascular disease, cancer, and stroke. We aim to conduct a systematic review of the prevalence of physical inactivity in Iran. Methods: We searched international databases; ISI, PubMed/Medline, Scopus, and national databases Irandoc, Barakat knowledge network system, and Scientific Information Database (SID). We collected data for outcome measures of prevalence of physical inactivity by sex, age, province, and year. Quality assessment and data extraction has been conducted independently by two independent research experts. There were no limitations for time and language. Results: We analyzed data for prevalence of physical inactivity in Iranian population. According to our search strategy we found 254 records; of them 185 were from international databases and the remaining 69 were obtained from national databases after refining the data, 34 articles that met eligible criteria remained for data extraction. From them respectively; 9, 20, 2 and 3 studies were at national, provincial, regional and local levels. The estimates for inactivity ranged from approximately 30% to almost 70% and had considerable variation between sexes and studied sub-groups. Conclusion: In Iran, most of studies reported high prevalence of physical inactivity. Our findings reveal a heterogeneity of reported values, often from differences in study design, measurement tools and methods, different target groups and sub-population sampling. These data do not provide the possibility of aggregation of data for a comprehensive inference.