Evaluation of the effect of baseline predictors on the incidence of metabolic syndrome: a population-based cohort study

Background Metabolic syndrome (MetS) is a common indicator of non-communicable diseases (NCDs) and mortality, causing health problems in most societies. Our aims were to estimate the incidence rates and to assess the risk factors of MetS among an adult population in content of a prospective cohort study. Methods This population-based cohort study conducted on 10009 adult individuals in southwest Iran. Among the participants of cohort baseline, a total number of 1,781 at risk individuals remained for follow-up, after putting aside the exclusions. Incidence rates (IRs) of metabolic syndrome were calculated by dividing the number of new events, occurred during the follow-up period by the person-years at risk. The effects of various explanatory variables on these incidence rates were assessed using Poisson regression models. Results The overall incidence rate of MetS was 102.23 per 1,000 person-years, with a higher rate in females (122.86) compared to males (83.66) (p-value < 0.001). In the multiple Poisson regression model, higher age, being female, marital status (married-widowed-divorced), higher BMI, having a history of cardiovascular diseases (CVDs) and a family history of diabetes significantly increased MetS incidence (all p-values < 0.05). Conclusion: Targeted public health strategies and lifestyle interventions are crucial for reducing metabolic syndrome incidence, particularly among high-risk groups such as women, older adults, and individuals with cardiovascular history.