# Medication Adherence and its Predictors in Patients With Type 2 Diabetes Mellitus in India: A Systematic Review and Meta‐Analysis of Current Evidence

**Authors:** Saurav Basu, Trina Sengupta, Satyajit Kundu

PMC · DOI: 10.1002/hsr2.71845 · Health Science Reports · 2026-02-17

## TL;DR

This study reviews medication adherence in Indian patients with type 2 diabetes, finding that nearly half are non-adherent, with factors like age and socioeconomic status playing a role.

## Contribution

The study provides a comprehensive meta-analysis of medication adherence predictors in Indian type 2 diabetes patients, highlighting geographic and methodological gaps.

## Key findings

- The pooled prevalence of medication non-adherence among T2DM patients in India was 48%.
- Key predictors of poor adherence include older age, socioeconomic disadvantage, and treatment complexity.
- Geographic diversity in the studies was limited, with most coming from South India.

## Abstract

India has nearly 90 million (10.5%) patients living with type 2 diabetes mellitus (T2DM) with a high burden of suboptimal medication adherence. This systematic review and meta‐analysis aimed to synthesize the determinants of medication adherence in Indian patients with T2DM, estimate the pooled prevalence of adherence, and formulate evidence‐based recommendations for public health policy.

We conducted a systematic review and meta‐analysis of observational and experimental studies from India, published between January 2020 and December 2024. Electronic databases (PubMed, Scopus, Web of Science) were searched for studies reporting the proportion of patients reporting poor adherence to anti‐diabetic medications.

A total of 534 articles were identified after removing duplicates and assessed for eligibility, of which 16 studies were included in this SRMA. The pooled prevalence of medication non‐adherence among MMAS‐8 using studies (n = 4) was 48% (95% CI: 18%–79%), and, overall, among all the studies ranged from 11% to 68%. Predictors of poor adherence included older age, socio‐economic disadvantage, substance use, treatment complexity, psychological distress, polypharmacy, and health‐system access barriers. Information on comorbidity and multimorbidity was sparse. Furthermore, a key limitation was that studies using the Morisky adherence scales (MMAS‐4/8) did not report individual item responses, which precluded a granular analysis of specific reasons for non‐adherence. There were eight studies from South India and six from north and north‐eastern India, indicating a significant lack of geographic diversity.

Medication non‐adherence in patients with T2DM persists as a major public health challenge in India, further exacerbating the country's burgeoning diabetes epidemic. Strengthening primary care can address the primary factors contributing to significant non‐adherence in this population.

## Linked entities

- **Diseases:** type 2 diabetes mellitus (MONDO:0005148), diabetes (MONDO:0005015)

## Full-text entities

- **Genes:** INS (insulin) [NCBI Gene 3630] {aka IDDM, IDDM1, IDDM2, ILPR, IRDN, MODY10}
- **Diseases:** alcohol addiction (MESH:D000437), hyperglycemia (MESH:D006943), OADs (MESH:D000092582), Asthma (MESH:D001249), Diabetes (MESH:D003920), noncommunicable diseases (MESH:D000073296), retinopathy (MESH:D058437), Thyroid 1 (MESH:D013966), death (MESH:D003643), Hypertension (MESH:D006973), hypoglycemia (MESH:D007003), phobia (MESH:D010698), T2D (MESH:D003924), depression (MESH:D003866), nephropathy (MESH:D007674), neuropathy (MESH:D009422)
- **Chemicals:** Anti-Diabetic Medications (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

56 references — full list in the complete paper: https://tomesphere.com/paper/PMC12914141/full.md

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Source: https://tomesphere.com/paper/PMC12914141