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Sociodemographic and Geographic Inequalities in Diagnosis and Treatment of Older Adults' Chronic Conditions in India: a Nationally Representative Population-based Study

Overview
Publisher Biomed Central
Specialty Health Services
Date 2023 Apr 4
PMID 37013518
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Abstract

Context: Expeditious diagnosis and treatment of chronic conditions are critical to control the burden of non-communicable disease in low- and middle-income countries. We aimed to estimate sociodemographic and geographic inequalities in diagnosis and treatment of chronic conditions among adults aged 45 + in India.

Methods: We used 2017-18 nationally representative data to estimate prevalence of chronic conditions (hypertension, diabetes, lung disease, heart disease, stroke, arthritis, cholesterol, and neurological) reported as diagnosed and percentages of diagnosed conditions that were untreated by sociodemographic characteristics and state. We used concentration indices to measure socioeconomic inequalities in diagnosis and lack of treatment. Fully adjusted inequalities were estimated with multivariable probit and fractional regression models.

Findings: About 46.1% (95% CI: 44.9 to 47.3) of adults aged 45 + reported a diagnosis of at least one chronic condition and 27.5% (95% CI: 26.2 to 28.7) of the reported conditions were untreated. The percentage untreated was highest for neurological conditions (53.2%; 95% CI: 50.1 to 59.6) and lowest for diabetes (10.1%; 95% CI: 8.4 to 11.5). Age- and sex-adjusted prevalence of any diagnosed condition was highest in the richest quartile (55.3%; 95% CI: 53.3 to 57.3) and lowest in the poorest (37.7%: 95% CI: 36.1 to 39.3). Conditional on reported diagnosis, the percentage of conditions untreated was highest in the poorest quartile (34.4%: 95% CI: 32.3 to 36.5) and lowest in the richest (21.1%: 95% CI: 19.2 to 23.1). Concentration indices confirmed these patterns. Multivariable models showed that the percentage of untreated conditions was 6.0 points higher (95% CI: 3.3 to 8.6) in the poorest quartile than in the richest. Between state variations in the prevalence of diagnosed conditions and their treatment were large.

Conclusions: Ensuring more equitable treatment of chronic conditions in India requires improved access for poorer, less educated, and rural older people who often remain untreated even once diagnosed.

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References
1.
. Five insights from the Global Burden of Disease Study 2019. Lancet. 2020; 396(10258):1135-1159. PMC: 7116361. DOI: 10.1016/S0140-6736(20)31404-5. View

2.
Atinga R, Yarney L, Gavu N . Factors influencing long-term medication non-adherence among diabetes and hypertensive patients in Ghana: A qualitative investigation. PLoS One. 2018; 13(3):e0193995. PMC: 5874015. DOI: 10.1371/journal.pone.0193995. View

3.
Ali M, Alemu T, Sada O . Medication adherence and its associated factors among diabetic patients at Zewditu Memorial Hospital, Addis Ababa, Ethiopia. BMC Res Notes. 2017; 10(1):676. PMC: 5715531. DOI: 10.1186/s13104-017-3025-7. View

4.
Prenissl J, Jaacks L, Mohan V, Manne-Goehler J, Davies J, Awasthi A . Variation in health system performance for managing diabetes among states in India: a cross-sectional study of individuals aged 15 to 49 years. BMC Med. 2019; 17(1):92. PMC: 6515628. DOI: 10.1186/s12916-019-1325-6. View

5.
Shaw K, Theis K, Self-Brown S, Roblin D, Barker L . Chronic Disease Disparities by County Economic Status and Metropolitan Classification, Behavioral Risk Factor Surveillance System, 2013. Prev Chronic Dis. 2016; 13:E119. PMC: 5008860. DOI: 10.5888/pcd13.160088. View