Inequalities in the prevalence, diagnosis awareness, treatment coverage and effective control of diabetes: a small area estimation analysis in Iran

Abstract

Objective This study aims to assess geographic inequalities in the prevalence, awareness of diagnosis, treatment coverage and effective control of diabetes in 429 districts of Iran. Methods A modelling study by the small area estimation method, based on a nationwide cross-sectional survey, Iran STEPwise approach to surveillance (STEPS) 2016, was performed. The modelling estimated the prevalence, awareness of diagnosis, treatment coverage, and effective control of diabetes in all 429 districts of Iran based on data from available districts. The modelling results were provided in different geographical and socio-economic scales to make the comparison possible across the country. Results In 2016, the prevalence of diabetes ranged from 3.2 to 19.8% for women and 2.4 to 19.1% for men. The awareness of diagnosis ranged from 51.9 to 95.7% for women and 35.7 to 100% for men. The rate of treatment coverage ranged from 37.2 to 85.6% for women and 24.4 to 80.5% for men. The rate of effective control ranged from 12.1 to 63.6% for women and 12 to 73% for men. The highest treatment coverage rates belonged to Ardebil for women and Shahr-e-kord for men. The highest effective control rates belonged to Sanandaj for women and Nehbandan for men. Across Iran districts, there were considerable differences between the highest and lowest rates of prevalence, diagnosis awareness, treatment coverage, and effective control of diabetes. The concentration indices of diabetes prevalence, awareness of diagnosis, and treatment coverage were positive and significant for both sexes. Conclusion Findings of this study highlight the existence of inequalities in diagnosis awareness, treatment coverage, and effective control of diabetes in all Iran regions. More suitable population-wide strategies and policies are warranted to handle these inequalities in Iran.

Inequality in electricity consumption and economic growth: Evidence from a small area estimation study

“…Small area estimation has gained a lot of attention in recent years due to the growing need for accurate small area estimates from both public and business sectors [24][25][26][27][28][29][30]. Using the small area estimation method, Perseh et alestimated inequality indicators in diabetes care and health outcomes relevant to diabetes management in almost all districts of Iran [26].…”

“…Small area estimation has gained a lot of attention in recent years due to the growing need for accurate small area estimates from both public and business sectors [24][25][26][27][28][29][30]. Using the small area estimation method, Perseh et alestimated inequality indicators in diabetes care and health outcomes relevant to diabetes management in almost all districts of Iran [26]. Reames predicted the mean census block group home heating energy usage intensity (EUI), an energy efficiency proxy, in Kansas City, Missouri, using small area estimates approaches [31].…”