Assessment of Medication Compliance among Type 2 Diabetes Patients Attending a Rural Health Centre in Tamil Nadu

Pathy LY et al | DOI: 10.65188/nurexus.1049

Page 9

Journal of MedVerse Research & Practice

ISSN: 3107-4278

Assessment of Medication Compliance among Type 2 Diabetes Patients

Attending a Rural Health Centre in Tamil Nadu

Dr. Lakshmi Pathy Y

, Dr. Suvitha F

Postgraduate, Associate Professor

Department of Community Medicine, Stanley Medical College, Chennai

Email: laskhmipathyss94@gmail.com

Submission Date: 21.9.2025

Accepted Date: 19.10.2025

Published Date: 31.10.2025

DOI: 10.65188/nurexus.1049

article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits

unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Abstract

Background: Diabetes Mellitus (DM) continues to rise in India, with Type 2 DM accounting for the majority of

cases. Medication adherence plays a critical role in achieving optimal glycaemic control and preventing

complications, yet poor compliance remains a challenge, particularly in rural populations.

Objectives: To assess medication compliance among Type 2 DM patients attending a Rural Health Training Centre

(RHTC) in Tamil Nadu and to identify socio-demographic and clinical factors influencing compliance.

Methods: A facility-based cross-sectional study was conducted among 300 adults with Type 2 DM attending the

outpatient clinic of an RHTC. Participants aged ≥30 years with at least six months of treatment history were

included. Data were collected using a pre-tested semi-structured questionnaire. Medication compliance was assessed

using three validated self-report questions. Glycaemic control was evaluated using fasting and post-prandial blood

glucose values from records. Data were analysed using STATA; Prevalence Ratios and adjusted PR (aPR) with 95%

confidence intervals (CI) were calculated.

Results: The prevalence of poor medication compliance was 24%. Poor compliance was significantly higher among

employed (28%) and retired individuals (27%), compared to unemployed participants (14%). Physical inactivity

(aPR = 11.2; p = 0.01), longer distance from health facility (>5 km) (aPR = 2.0; p = 0.03), and absence of

comorbidities (aPR = 0.35; p = 0.03) were significantly associated with poor adherence. Good glycaemic control was

observed in 18% of participants, while 62% demonstrated poor control. Knowledge regarding disease and treatment

was high (86%), yet forgetfulness, lack of awareness, and distance to health center were common barriers. Family

support and motivation were noted as key facilitators.

Conclusion: Nearly one-fourth of patients had poor medication compliance despite high disease awareness.

Employment-related constraints, poor physical activity, and limited access to healthcare facilities were major

determinants of non-adherence. Strengthening counselling, enhancing behavioural support, and improving

accessibility through community-based outreach programs could significantly improve medication adherence among

rural diabetic patients.

Keywords: Ocular ultrasonography, B-scan ultrasound, Ocular complaints, Cataract

Introduction

India is witnessing a fast-growing burden of Diabetes Mellitus (DM), positioning the country as a major

global hotspot for the disease. Current projections indicate that the diabetic population in India will rise to

nearly 69.9 million by 2025 and reach approximately 80 million by 2030 [1]. Present estimates suggest that

about 74.2 million individuals in the country are living with diabetes, making India the nation with the

second-highest number of diabetic cases worldwide, next only to China [1]. The central aim of diabetes

Pathy LY et al | DOI: 10.65188/nurexus.1049

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management is to attain and maintain optimal glycaemic control and reduce the risk of long-term

complications. This requires continuous adherence to treatment components such as pharmacotherapy,

dietary modifications, regular physical exercise, and routine blood glucose monitoring [2].

Sustained glycaemic control can be achieved through healthy lifestyle practices and consistent use of

recommended oral or injectable anti-diabetic medications [2]. Adhering to appropriate therapeutic regimens

plays a crucial role in delaying disease progression, minimizing morbidity, and preventing diabetes-related

complications [2]. However, since the majority of diabetes management relies on patient-initiated daily

practices, adherence remains a significant challenge, with nearly 98 percent of diabetes care depending on

self-management [3]. Several studies have shown suboptimal adherence to both medications and lifestyle-

based self-care behaviours among individuals with Type 2 Diabetes Mellitus [3–7].

Medication adherence has been strongly linked to favourable clinical outcomes, including improved HbA1c

levels, fewer hospital admissions, reduced mortality, and lower healthcare expenditure [6]. Individuals who

consistently follow their treatment plans also tend to report better quality of life and overall well-being [8].

The terms “adherence” and “compliance,” although used interchangeably, differ conceptually: adherence

indicates an active patient-physician partnership in treatment planning, while compliance refers to a more

passive following of medical instructions [9]. Since objective measurement of adherence can be difficult in

community settings, this study focuses on self-reported medication compliance to better understand real-

world patient behaviour in individuals living with Type 2 Diabetes Mellitus [10].

The specific objectives of this study are:

a) To assess the level of compliance with prescribed anti-diabetic medications among individuals with Type

2 Diabetes Mellitus.

b) To determine socio-demographic, behavioural, and clinical factors associated with medication

compliance.

c) To identify reported reasons for both satisfactory and poor compliance with anti-diabetic medications.

Materials & Methods

This facility-based cross-sectional study was carried out at the outpatient department of a Rural Health

Training Centre (RHTC) attached to a tertiary-care teaching institution in Tamil Nadu, South India. Data

collection was conducted over one month, from November to December 2024. All eligible patients visiting

the outpatient clinic during the study period who fulfilled the criteria and provided written informed

consent were included.

Eligibility criteria: Adults aged above 30 years of any gender with a confirmed diagnosis of Diabetes

Mellitus who had been attending the RHTC and receiving treatment there for at least six months.

Individuals excluded from participation included pregnant women with gestational diabetes, those

unwilling to give written consent, and patients in need of urgent or emergency medical attention.

Sample size: The required sample size was determined as 300. This calculation was based on an expected

prevalence of poor medication compliance of 11% among patients with diabetes, as reported in earlier

research, using OpenEpi version 3.0. The calculation assumed a 5% alpha error, 95% confidence level, and

accounted for a 10% non-response rate.

Sampling method: The RHTC diabetes registry included 247 previously registered patients with diabetes.

As the calculated sample size was 300, eligible participants were enrolled consecutively during the study

period until the required number was reached. Trained investigators interviewed the consenting participants

during their scheduled follow-up visits to the center.

Pathy LY et al | DOI: 10.65188/nurexus.1049

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Study procedure: Following approval from the Institutional Ethics Committee on 15.09.2024, participants

who met the inclusion criteria were approached. After obtaining informed consent, data were collected

through a pre-tested semi-structured questionnaire administered by trained investigators under faculty

supervision. Information was gathered regarding socio-demographic factors, clinical characteristics of

diabetes, follow-up practices, and treatment-related factors.

Study variables:

1. Socio-demographic details: participant ID, age, gender, education, occupation, socio-economic

status, family history of diabetes, and comorbid conditions.

2. Diabetes-related characteristics: duration of diabetes, type of treatment, distance to the RHTC,

location of medicine procurement, frequency of follow-up visits, and whether medication adherence

advice was received from health workers.

3. Medication compliance: assessed through three yes/no questions regarding (i) regular availability

of diabetes medicines, (ii) daily intake of prescribed medicines over the preceding two weeks, and

(iii) taking medicines on the day before the interview. Participants answering “yes” to all three were

categorized as having good compliance; any “no” response indicated poor compliance. This tool

was adapted from a validated questionnaire used for quick exit interviews among diabetes patients.

4. Biochemical assessment: Glycaemic status was evaluated using the most recent fasting blood sugar

(FBS) and post-prandial blood sugar (PPBS) values recorded within the previous month. Good

control was defined as FBS 80–130 mg/dL and PPBS <180 mg/dL. Partial control referred to only

one parameter being within the target range. Poor control was defined as FBS >130 mg/dL or PPBS

>180 mg/dL.

The study was approved by the Institutional Ethics Committee of Stanley Medical College, Chennai (Ref

No: SMC/IEC/2023/6219). A detailed Participant Information Sheet was provided to all participants, and

written informed consent was obtained prior to their inclusion in the study.

Statistical analysis: Data entry was performed using Microsoft Excel, and statistical analysis was

conducted using STATA version 12. Categorical data were summarized using frequencies and percentages.

Multivariate logistic regression was applied to explore associations between independent variables and

medication compliance. Prevalence Ratios (PR) and adjusted Prevalence Ratios (aPR) with 95% confidence

intervals (CI) were calculated to identify predictors of poor compliance. A p-value below 0.05 was

considered statistically significant.

Results

Table 1: Socio-demographic characteristics of study participants and their unadjusted association

with diabetes mellitus drug compliance (N=300)

Characteristics

Total

(%)

Poor compliance

95% CI

p-value

Age group (years)

30–49

87 (29.0)

31.03

1.60

0.98–2.61

0.06

50–69

181 (60.3)

19.89

1 (Ref)

—

≥70

32 (10.7)

21.88

1.10

0.43–2.78

0.84

Gender

Male

138 (46.0)

26.81

1.23

0.77–1.97

0.38

Female

162 (54.0)

20.99

1 (Ref)

—

Education

Literate

280 (93.3)

25.00

3.00

0.47–19.12

0.24

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Illiterate

20 (6.7)

10.00

1 (Ref)

—

Occupation

Employed

125 (41.7)

30.40

4.18

1.69–10.35

0.003*

Unemployed

92 (30.7)

7.61

1 (Ref)

—

Retired

83 (27.6)

31.33

4.23

1.70–10.50

0.003*

Socio-economic Status

BPL

257 (85.7)

24.90

1.28

0.60–2.75

0.52

APL

43 (14.3)

18.60

1 (Ref)

—

Marital status

Married

260 (86.7)

23.08

1.14

0.20–6.33

0.89

Unmarried

8 (2.7)

25.00

1 (Ref)

—

Others

32 (10.6)

31.25

1.55

0.26–9.13

0.62

Religion

Hindu

240 (80.0)

26.25

1.46

0.43–4.97

0.54

Christian

42 (14.0)

11.90

1 (Ref)

—

Muslim

18 (6.0)

22.22

0.72

0.16–3.31

0.67

Note: #-column %, ^ row %, PR-unadjusted Prevalence ratio, CI-Confidence Interval, Ref-Reference category, APL-

Above Poverty Line & BPL-Below Poverty Line, * Statistically significant (p<0.05).

This table presents the socio-demographic characteristics of the study participants and their association

with medication compliance among individuals with type 2 diabetes (N = 300). The majority of the

participants were between 50–69 years of age (60.3%), followed by the 30–49 age group (29%). Poor

compliance was highest among those aged 30–49 years (31.03%) compared to the 50–69 years group

(19.89%), although this association was not statistically significant (p = 0.06). Females constituted 54% of

the participants, and while males showed a slightly higher proportion of poor compliance (26.81%) than

females (20.99%), this difference was not statistically significant (p = 0.38).

Most participants were literate (93.3%), and literacy did not show a significant association with compliance

(p = 0.24). Occupational status demonstrated a strong association with compliance, with employed

(30.40%) and retired individuals (31.33%) showing significantly higher poor compliance compared to

unemployed individuals (7.61%), and this association was statistically significant (p = 0.003). Participants

belonging to below-poverty-line families (85.7%) had slightly higher poor compliance (24.90%) than those

above the poverty line (18.60%), but this was not statistically significant (p = 0.52). Regarding marital

status, married individuals had a poor compliance rate of 23.08%, slightly higher than unmarried and

widowed/separated participants, though the association was not significant (p > 0.05). The majority of

participants were Hindus (80%), and religion did not show a significant association with medication

compliance (p = 0.54).

Overall, the findings indicate that younger adults, males, employed and retired individuals, and those from

lower socioeconomic strata tend to have higher poor compliance, with occupational status being the only

statistically significant predictor in this table. These observations highlight the need for targeted counselling

and follow-up strategies, especially for working individuals and younger diabetic patients to improve

adherence to therapy.

Table 2: Facilitating and hindering factors for medication compliance among DM patients (n=300)

Variables

Frequency

(n)

Percentage

(%)

Facilitating factors

Knowledge about disease treatment

260

86.7

Wish to live longer and healthier

3.3

Pathy LY et al | DOI: 10.65188/nurexus.1049

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Financial support

0.7

Motivation and care by family

8.0

Trust in doctors or healthcare

0.7

Motivation by friends

0.7

Hindering factors

Lack of awareness about the

disease and treatment

32.0

Fear of drugs and side effects

3.0

Financial constraints

10.7

Lack of motivation and support by

family

1.0

Lack of trust on doctors or health

care

0.7

Does not know

156

52.0

The most common supportive factor was good knowledge about diabetes and its treatment, reported by

86.7% of participants. This indicates that awareness and understanding play a major role in encouraging

regular medication use. In addition, 8% were motivated by care and support from their family, highlighting

the importance of family involvement in diabetes management. Smaller proportions reported motivation to

stay healthy and live longer (3.3%), trust in healthcare providers (0.7%), financial support (0.7%), and

encouragement from friends (0.7%).

Figure 1: Facilitating and hindering factors (N = 300)

In this study, nearly half of the participants (48%) reported factors that supported their adherence to

diabetes medication, such as adequate knowledge about the disease, motivation to stay healthy, and

encouragement from family and healthcare providers. However, a slightly higher proportion (52%)

experienced hindering factors that adversely affected their medication compliance. These barriers included

lack of awareness about diabetes and its treatment, fear of side effects, financial constraints, limited support

from family, and uncertainty about the importance of regular medication. The predominance of hindering

factors highlights the need for enhanced patient education, continuous counselling, and supportive

interventions to strengthen treatment adherence, particularly in rural healthcare settings.

Discussion

The present study found that the prevalence of poor medication compliance among patients with Type 2

Diabetes Mellitus (T2DM) was 23.9% (95% CI: 17.8–30.9). Employed and retired individuals

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demonstrated a significantly higher prevalence of non-compliance compared with unemployed participants.

Most participants (85.6%) showed adequate knowledge regarding diabetes and its treatment. Key strengths

of this study include the objective assessment of glycaemic control through fasting and postprandial

glucose measurements and the identification of facilitators and barriers influencing medication adherence.

However, a limitation is that compliance was assessed using self-reported recall, and the short two-month

duration may not have captured fluctuations in adherence behavior.

The prevalence of poor medication compliance observed in the present study is comparable to findings

from similar studies conducted in South India. Aravindakshan et al., Jaya et al., Venkatachalam et al.,

Karthik et al., Suguna et al., and Sathish et al. reported medication adherence rates ranging between 49%

and 75% among diabetic patients in various South Indian settings [11,12,20–23]. Furthermore, a systematic

review by Paudel et al. documented an overall adherence rate of 64% (95% CI: 53–74) across South Asian

populations [24]. Poor self-care practices related to diet, physical activity, foot care, and glucose

monitoring have also been widely reported in these studies. The relatively better adherence observed in the

present study may be attributed to higher literacy levels among participants and the implementation of

community-based healthcare initiatives in Tamil Nadu, such as the “Makkalai Thedi Maruthuvam” scheme

described by Thiagesan et al., which facilitates doorstep screening and medication delivery for non-

communicable diseases [25]. Despite a relatively robust public healthcare system, persistent gaps in

adherence highlight the need for targeted behavioral interventions.

The observed association between occupation and poor medication compliance is consistent with earlier

findings. Kotian et al. reported similar challenges among working individuals, likely due to difficulty in

remembering medication schedules during work hours or disruptions in routine following retirement [19].

Additionally, poor compliance was significantly associated with lack of physical activity, a finding

supported by studies conducted by Venkatachalam et al., Suguna et al., Sathish et al., and Srinath et al.,

which collectively suggest an overall deficit in self-care behaviors driven by time constraints and

competing priorities [20,22,23,26]. In contrast, participants with comorbidities demonstrated better

adherence, possibly due to increased disease awareness and more frequent healthcare interactions, as noted

by Shiomi et al. [18]. Moreover, patients residing more than 5 km from healthcare facilities showed higher

odds of non-compliance, reflecting access-related barriers to routine follow-up care.

Non-adherence among rural patients with T2DM is strongly influenced by socioeconomic and healthcare

system challenges. Rajeshwari et al. reported a non-adherence rate of 39.8% in Chidambaram, identifying

financial constraints, fear of side effects, and comorbid conditions as major barriers [27]. Similarly, Deepa

et al. reported a non-adherence rate of 45.4% in rural Tamil Nadu, with illiteracy, poor disease awareness,

dissatisfaction with physician communication, and coexisting hypertension significantly associated with

non-compliance [28]. In rural Bengaluru, Rani PK et al. found that forgetfulness, advancing age, and

complex medication regimens were key contributors to poor adherence [29]. These findings emphasize the

importance of structured diabetes education, simplified drug regimens, and enhanced doctor–patient

communication.

Further insights are provided by a qualitative study conducted in rural Puducherry by Krishnamoorthy et

al., which identified stress, forgetfulness, alcohol use, fear of hypoglycaemia, inadequate family support,

social stigma, and insufficient counselling as major barriers to medication adherence [30]. Conversely,

strong family support, peer motivation, prior adverse illness experiences, and consistent counselling were

found to improve adherence. The authors recommended community-based peer support groups, simplified

medication labeling, and strengthened follow-up by frontline health workers to address these barriers

effectively.

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Limitations: The study was conducted at a single rural health centre, which may limit the generalizability

of findings to urban or diverse healthcare settings. Future longitudinal studies with larger and more

heterogeneous populations are needed to validate these results and to evaluate the long-term impact of

targeted adherence-enhancing interventions.

Conclusion

The present study found that poor medication compliance among diabetic patients was low. Lack of

physical activity was found to be associated with poor medication compliance; hence, behaviour change

communication strategies in this regard can help in improving compliance in this study population. The

presence of comorbidities was associated with good compliance, which might be due to good awareness

about diabetes and its complications. A greater distance to the health centre is associated with poor

compliance, which can be overcome by conducting regular mobile camps in such villages. Overall, there is

a need to develop a structured diabetes self-care education program for people in rural areas to ensure long-

term care.

Conflict of Interest: Nil

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