Multilevel regression modeling for risk factors associated with hypertension

Introduction:Hypertension is one of the most important risk factors for cardiovascular disease with a high prevalence and serious complications. In this regard, the present study aimed to identify factors associated with hypertension using multivariate regression model. Materials and Methods:This cross-sectional study has been conducted in Mashhad since 2008. The study population were individuals within the age range of 35-65 years in Mashhad.The sample was composed of 9365 cases selected using stratified cluster sampling technique. The variables included in the present study were demographic data, anthropometric index, diabetes, anxiety, depression, physical activity level, and dietary patterns. To conduct data analysis, SPSSsoftware (version 23) was used for fitting the two-level regression model of MLwiN2.10. P-value less than 0.05 was considered statistically significant. Results:The results showed that the prevalence of hypertension was 23 (2135), out of which 22 (1230) patients were women with mean age of 47.6±8.0 years. The mean age of male participants(n=905) was 4.8±9.48 years. The obtained results of fitting the multivariate model indicated that there was a significant positive relationship among the variables of type 2 diabetes, cholesterol, body mass index, age with hypertension (P<0.05). Conclusion:The results of this study showed that most of the factors associated with hypertension are controllable lifestyle variables. It is suggested to conduct appropriate interventions to improve screening, control, and even treatment of such a disease.