Incidence and risk factors of cardiovascular disease among population aged 40–70 years: a population-based cohort study in the South of Iran

Abstract

Background Cardiovascular diseases are the main cause of mortality in the world. This study aimed to estimate the incidence and identify the risk factors of these diseases. Methods This prospective cohort study was performed on 9442 individuals aged 40–70 years in Kharameh, a city in the South of Iran, in 2015–2022. The subjects were followed up for 4 years. The demographic information, behavioral habits, biological parameters, and history of some diseases were examined. The density incidence of cardiovascular disease was calculated. The log-rank test was calculated to assess the cardiovascular incidence difference between men and women. Simple and multiple Cox regression with Firth's bias reduction method were used to identify the predictors of cardiovascular disease. Results The mean ± SD age of the participants was 51.4 ± 8.04 years, and the density incidence was estimated at 1.9 cases per 100,000 person-day. The log-rank test showed that men had a higher risk of cardiovascular disease than women. The Fisher's exact test showed a statistically significant difference between the incidence of cardiovascular diseases in different age groups, education levels, diabetes, and hypertension in men and women. The results of multiple Cox regression revealed that with increasing age, the risk of developing CVDs increased. In addition, the risk of cardiovascular disease is higher in people with kidney disease (HRadj = 3.4, 95% CI 1.3 to 8.7), men (HRadj = 2.3, 95% CI 1.7 to 3.2), individuals with hypertension (HRadj = 1.6, 95% CI 1.3 to 2.1), diabetics (HRadj = 2.3, 95%c CI 1.8 to 2.9), and alcohol consumption (HRadj = 1.5, 95% CI 1.09 to 2.2). Conclusions In the present study, diabetes, hypertension, age, male gender, and alcohol consumption were identified as the risk factors for cardiovascular diseases; three variables of diabetes, hypertension and alcohol consumption were among the modifiable risk factors, so if they were removed, the incidence of cardiovascular disease could greatly reduce. Therefore, it is necessary to develop strategies for appropriate interventions to remove these risk factors.

Machine learning models identify micronutrient intake as predictors of undiagnosed hypertension among rural community-dwelling older adults in Thailand: a cross-sectional study

“…The etiology of hypertension depends on non-modifiable (such as sex, age, and genetics) and modifiable factors (such as consumption behaviors, psychological stress, physical activity, tobacco use, and alcohol consumption) ( 13 ). Previous studies suggest that by monitoring and controlling the modifiable risk factors, up to 90% of hypertension-associated cardiovascular diseases (CVDs) can be prevented.…”