Assessing socioeconomic inequalities of hypertension among women in Indonesia's major cities

• Published in: Journal of human hypertension Vol. 29; no. 11; pp. 683 - 688
• Main Authors: Christiani, Y, Byles, J E, Tavener, M, Dugdale, P
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01-11-2015; Nature Publishing Group
• Subjects: 692/499; Adolescent; Adult; Aged; Aged, 80 and over; Blood Pressure; Body mass index; Demographic aspects; Developing countries; Diagnosis; Educational Status; Employment; Epidemiology; Female; Health Administration; Health Status Disparities; Humans; Hypertension; Hypertension - diagnosis; Hypertension - economics; Hypertension - epidemiology; Hypertension - physiopathology; Income; Indonesia - epidemiology; Inequality; LDCs; Logistic Models; Medicine; Medicine & Public Health; Middle Aged; Multivariate Analysis; original-article; Prevalence; Public Health; Risk Assessment; Risk Factors; Socioeconomic Factors; Sphygmomanometers; Urban Health; Women's Health; Young Adult; Indonesia
• ISSN: 0950-9240; 1476-5527
• DOI: 10.1038/jhh.2015.8

Although hypertension has been recognized as one of the major public health problems, few studies address economic inequality of hypertension among urban women in developing countries. To assess this issue, we analysed data for 1400 women from four of Indonesia’s major cities: Jakarta, Surabaya, Medan and Bandung. Women were aged ⩾15 years (mean age 35.4 years), and were participants in the 2007/2008 Indonesia Family Life Survey. The prevalence of hypertension measured by digital sphygmomanometer among this population was 31%. Using a multivariable logistic regression model, socioeconomic disadvantage (based on household assets and characteristics) as well as age, body mass index and economic conditions were significantly associated with hypertension (
P
<0.05). Applying the Fairlie decomposition model, results showed that 14% of the inequality between less and more economically advantaged groups could be accounted for by the distribution of socioeconomic characteristics. Education was the strongest contributor to inequality, with lower education levels increasing the predicted probability of hypertension among less economically advantaged groups. This work highlights the importance of socioeconomic inequality in the development of hypertension, and particularly the effects of education level.