Socioeconomic inequality in hypertension and its determinants in people over 60 years in Fasa, southern Iran: a Blinder-Oaxaca decomposition - Reza Tabrizi; Reza Pakzad; Maryam Akbari; Azizallah Dehghan; Mozhan Abdollahi; Sina Bazmi; Sina Kardeh; Yaser Sarikhani (BMC Public Health)
Abstract Background Hypertension (HTN) is well-known as a major risk factor for various noncommunicable diseases. Evidence indicates a link between socioeconomic status and the likelihood of developing HTN. A thorough comprehension of the inequalities in HTN is crucial for implementing evidence-based interventions. This study aimed to assess the socioeconomic disparities in HTN among people aged 60 and older in Fasa County, located in southern Iran. Methods A total of 1,632 seniors, aged 60 and above, were included in the analysis, with data obtained from the Fasa Adults Cohort Study (FACS). Initially, we utilized both simple and multiple logistic regression models to investigate the associations between HTN and the determinant variables. The Blinder‒Oaxaca decomposition method was used to decompose the disparity between the impoverished and the wealthy. Results The research indicated that elderly individuals with a higher risk of developing HTN were notably linked to factors such as socioeconomic status, education level, a history of coronary artery disease, employment status, smoking habits, body mass index (BMI), waist‒hip ratio (WHR), and physical activity (p < 0.05). The decomposition model revealed a significant gap in HTN rate between rich and poor individuals, with those in the lower income bracket having a 7.59% higher rate of HTN (p = 0.001). Additionally, the leading factors contributing to the greatest disparities in HTN among older adults from different socioeconomic backgrounds include education level (33.07%), employment status (12.78%), BMI (12.25%), physical activity (-15.02%), and WHR (-9.22%). Conclusions The decomposition model illustrated a significant disparity in HTN rates among various socioeconomic groups, with a higher rate observed in the lower-income demographic. The analysis revealed that a substantial part of the explained gap can be attributed to factors including education level, employment status, WHR, BMI, and level of physical activity. Nonetheless, a considerable portion of HTN inequality among older adults remains unexplained by the model, highlighting the necessity for additional research that includes a wider variety of factors and variables to gain a deeper insight into the root causes of these disparities.