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Self-care behaviours among people with type 2 diabetes mellitus in South Asia: A systematic review and meta-analysis

Grish Paudel1, Corneel Vandelanotte2, Padam K Dahal1, Tuhin Biswas3, Uday N Yadav4,5, Tomohiko Sugishita6, Lal Rawal1,2,7

1 School of Health, Medical and Applied Sciences, Central Queensland University, Sydney, Australia
2 Appleton Institute, Physical Activity Research Group, Central Queensland University, Rockhampton, Australia
3 The Australian Research Council Centre of Excellence for Children and Families over the Life Course, The University of Queensland, Brisbane, Queensland, Australia
4 National Centre for Epidemiology and Population Health, The Australian National University, Canberra, Australia
5 Centre for Primary Health Care and Equity, University of New South Wales, Sydney, Australia
6 Section of Global Health, Division of Public Health, Department of Public Health, Tokyo Women’s Medical University, Tokyo, Japan
7 Translational Health Research Institute (THRI), Western Sydney University, Sydney Australia

DOI: 10.7189/jogh.12.04056

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Abstract

Background

The burden of Type 2 Diabetes Mellitus (T2DM) in South Asian countries is increasing rapidly. Self-care behaviour plays a vital role in managing T2DM and preventing complications. Research on self-care behaviours among people with T2DM has been widely conducted in South Asian countries, but there are no systematic reviews that assess self-care behaviour among people with T2DM in South Asia. This study systematically assessed the studies reporting self-care behaviours among people with T2DM in South-Asia.

Methods

Adhering to the PRISMA guidelines, we searched six bibliographic databases (Scopus, PubMed, CINAHL, Embase, Web of Science, and PsychInfo) to identify the relevant articles published between January 2000 through March 2022. Eligibility criteria included all observational and cross-sectional studies reporting on the prevalence of self-care behaviours (ie, diet, physical activity, medication adherence, blood glucose monitoring, and foot care) conducted in South Asian countries among people with T2DM.

Results

The database search returned 1567 articles. After deduplication (n = 758) and review of full-text articles (n = 192), 92 studies met inclusion criteria and were included. Forward and backward reference checks were performed on included studies, which resulted in an additional 18 articles. The pooled prevalence of adherence to blood glucose monitoring was 65% (95% CI = 49-80); 64% for medication adherence (95% CI = 53-74); 53% for physical activity (95% CI = 39-66); 48% for diet (95% CI = 38-58); 42% for foot care (95% CI = 30-54). About a quarter of people with T2DM consumed alcohol (25.2%, IQR = 13.8%-38.1%) and were using tobacco products (18.6%, IQR = 10.6%-23.8%).

Conclusions

Our findings suggest that the prevalence of self-care behaviours among people with T2DM in South Asia is low. This shows an urgent need to thoroughly investigate the barriers to the practising of self-care and design and implement interventions to improve diabetes self-care behaviour among people with T2DM in South Asia.

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Diabetes mellitus is a major public health concern worldwide. The number of people with diabetes mellitus has increased from 108 million in 1980 to 422 million in 2014 [1] and 537 million in 2021 [2]. According to the International Diabetes Federation (IDF), this number is likely to reach 643 million by 2030 [2]. Type 2 Diabetes Mellitus (T2DM) constitutes more than 90% of all diabetes cases around the globe [2]. In recent years, the T2DM prevalence has significantly increased in low- and middle-income countries compared to higher-income countries in recent years [3]. The prevalence of T2DM in the South-Asian region specifically has doubled from 4.1% in 1980 to 8.6% in 2014 [3] and is estimated to reach 11.3% by 2045 [2].

South Asia is the southern region of Asia that comprises eight countries: Nepal, India, Bangladesh, Maldives, Sri Lanka, Pakistan, Bhutan, and Afghanistan [4]. South Asians are at higher risk of developing Non-Communicable Disease (NCDs), including T2DM, compared to other ethnic groups [5]. They tend to have more abdominal fat, more insulin resistance, low levels of adiponectin, low high-density lipoproteins, high low-density lipoproteins, and high triglycerides – characteristics which are responsible for the development of T2DM and cardiovascular diseases [5]. The prevalence of T2DM is the highest in Pakistan (26.7%) followed by India (8.3%), Bhutan (8.8%), Sri Lanka (9.8%), Bangladesh (12.5%), Maldives (6.7%), Afghanistan (8.7%) and Nepal (6.3%) [2]. The increased prevalence of T2DM negatively affects the socioeconomic circumstances for South Asian people by increasing diabetes-related health expenditure [6]. Poor knowledge about the disease, delayed diagnosis, poor adherence to self-care behaviours, and administration of harmful alternative medicines are the challenges for the treatment of T2DM among South-Asians [7,8].

The IDF has identified indicators for data collection (at least once in 12-24 months) to monitor the effectiveness of diabetes management, including self-care. The components of self-care are smoking status, alcohol consumption, self-monitoring (glucose, blood pressure, body weight), diet, physical activity, driving risk, medication adherence, insulin techniques, and dental care [9]. Similarly, the American Association of Diabetes Educators (AADE) has identified seven self-care behaviours: healthy eating, being active, monitoring, taking medication, problem-solving, healthy coping, and reducing risks as a framework for delivering patient-oriented diabetes care and education [10]. Adherence to self-care behaviours is essential for controlling adequate metabolism and preventing long-term complications [9,11–13]. Adherence to healthier behaviours significantly reduces the T2DM related complications and the mortality rate [14,15]. Despite this evidence, South-Asians adhere poorly to T2DM self-care behaviours [7,8,16]. To date, the components of self-care for management of T2DM in the South Asian region have not been defined by South Asian or the regional federations on diabetes.

As many South Asian countries have adopted the WHO’s Global Action Plan for the Prevention and Control of Non-Communicable Diseases [17], there is a need for research examining the planning, implementation, and evaluation of NCD prevention, control, and management strategies. Similarly, the higher risks of developing T2DM among South Asians have drawn the attention of policy makers in management and control of T2DM in this region. There are many studies examining the prevalence of self-care behaviours among those with T2DM in South-Asian countries [18–21]. However, a comprehensive systematic review and meta-analysis of this collective body of literature has not yet been conducted; posing challenges for policymakers to act on this. The literature on the prevalence of self-care behaviours among people with T2DM has been systematically analysed in regions other than South Asia [11,22–25] and reported widely varying rates of self-care behaviours. The findings from such reviews improve our understanding on practice of self-care among the people with T2DM across the regions. Because of the increasing burden of T2DM in South Asia [2] and South Asians being at higher risk for developing T2DM [5], there is an urgent need to design and implement effective prevention and management programs for T2DM. Improving our understanding on the practice of self-care behaviours among people with T2DM will help forward this agenda. This systematic review and meta-analysis aim to assess and summarize the findings on self-care behaviours among people with T2DM in South-Asia.

METHODS

This systematic review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [26]. The South Asian countries included in this study were Bangladesh, Bhutan, India, Nepal, Pakistan, Maldives, Sri Lanka, and Afghanistan [4]. The review was registered with PROSPERO, an international prospective register of systematic reviews (Registration number: CRD42021242930).

Search strategy

We systematically searched six bibliographic databases: Scopus, PubMed, CINAHL, Embase, Web of Science, and PsychInfo for articles published between January 2000 through March 2022. This time frame aligns with the launch of the Millennium Development Goals (MDGs) in 2000 [27]. A search strategy for each database was developed with all the possible combinations of three keywords, “Type 2 Diabetes Mellitus”, “Self-care behaviour”, and “South-Asia” (See Appendix S1 in the Online Supplementary Document). Search tools such as PICO, PICOS, or SPIDER were not used because this study only reviewed observational and cross-sectional studies. Medical Subject Headings (MeSH), boolean operators, wildcards, truncation, and field tags were used where appropriate. Both the reference lists (ie, backward search) and articles citing (ie, forwards search) of included studies were checked by two authors (GP, PD) for additional relevant studies.

Inclusion and exclusion criteria

Observational, and cross-sectional studies that quantitatively reported on the practice of self-care behaviours (ie, diet, physical activity, medication adherence, blood glucose monitoring, and foot care) among adults with T2DM from South-Asian countries that were published in the English language were included. These five self-care behaviours were based on the key indicators for self-care behaviour as suggested by the IDF and AADE [9,10]. Furthermore, these domains of self-care were also assessed by several review studies on self-care among people with T2DM in other settings [11,22–25]. Studies not mentioning the type of diabetes examined, studies based on the same data set, and studies without a full-text publication available were excluded.

Screening

One author (GP) performed the online database search in first week of April 2021 (updated on 25 March 2022). Articles identified through the search were exported into the EndNote referencing software and deduplicated. Titles and abstracts were screened independently by two reviewers (GP, PD). The potentially eligible studies underwent full-text screening using the selection criteria. Disagreements between the two reviewers (GP and PD) was discussed in consultation with a third reviewer (LR). Remaining disagreements were discussed within the study team (GP, PD, TB, LR, UNY, TS, and CV) until a consensus was reached. A detailed study selection process is presented in the PRISMA flowchart (Figure 1) [26].

Figure 1.  PRISMA flow diagram (2009) for reporting systematic review and meta-analysis.

Data extraction and quality assessment

A data extraction template similar to the one used in the systematic review of Stephani et al. [24] was developed in Microsoft Excel to collect information from the selected studies for the analysis. Information on the primary author, publication year, country, study design, sample size, demographic characteristics of the population (eg, age, gender, and other contextual information), and reported self-care behaviours were extracted.

The Jonna Briggs Institute (JBI) critical appraisal checklist was used to assess the methodological quality of the selected studies following each study design [28]. Two independent reviewers (GP, PD) critically appraised the selected articles using the JBI critical appraisal checklist. This tool involves assessing the study’s methodological quality in dealing with bias at different study stages. A checklist for analytical cross-sectional studies (with 8 appraising items) and another for prevalence studies (with 9 appraising items) were used. Each response was scored with 1 (if the response to the question was “yes”) and 0 (if the response to the question was “no” or “unclear” or “not applicable”). Based on the score, studies were categorized into high (80% and above), moderate (60%-80%) and low quality (<60%) [29]. Discrepancies between reviewers (GP, PD) on study quality assessment were resolved through discussion and consultation with a third reviewer (LR).

Meta-analysis

A systematic narrative synthesis was performed to describe the characteristics and results of all included studies. The narrative synthesis followed the Guidance of the Conduct of Narrative Synthesis in Systematic Reviews [30]. Data synthesis and analysis were performed by one reviewer (GP) and the findings were discussed with all other team members.

In the meta-analysis, the overall pooled prevalence for each domain of self-care behaviours was conducted. A subgroup analysis of self-care behaviours including diet, physical activity, and foot care was conducted based on studies that either used a standardised tool to assess self-care domains or those that clearly defined the self-care domain and studies that did not clarify either the measure used to assess self-care domain or that did not define self-care domain. Medication adherence was not considered for subgroup analysis as most included studies used standard tools, while some reported regular intake of medication as recommended by their health care providers. Similarly, blood glucose monitoring differs from person to person based on their blood glucose level, so subgroup analysis was based on studies that assessed blood glucose monitoring on monthly basis and studies that assessed blood glucose monitoring at least once in three months. We used the quality effects model (QE) for bias adjustment [31]. The advantage of the QE model is that the between-study variability is adjusted based on the relative quality rank of the studies instead of on random variables assigned by the random effect (RE) model. The heterogeneity of the studies was reported by the I-squared value (I2) which measures the proportion of total variance between studies beyond random error [32]. As significant heterogeneity was detected among the studies (I2>50%) in the meta-analysis, a random-effects model was used. All the analyses were conducted using the MetaXL software version 5.3 [33]. Publication bias was assessed using both a graphical (Doi plot) and quantitative (Luis Furuya-Kanamori (LFK) index) examination for potential small-study effects [32]. LFK indices are defined as no (±1), minor (between ±1 and ±2), and major (>±2) asymmetry, respectively. Sensitivity and subgroup analysis were performed for extreme levels of heterogeneity between studies (I2≥90%) [32].

RESULTS

Study selection

A total of 1585 studies were identified through the database search (n = 1567) and forward and backward reference checking (n = 18). The duplicates (n = 809) were removed, and 758 studies underwent the title and abstract screening. Of these, 260 studies were eligible for full-text retrieval and 192 studies were retrieved with full-text articles. It was not possible to access the full-text of 68 studies, which were conference abstracts or articles published in local paper-based journals. After full text review, 92 studies met the inclusion criteria and were included in the qualitative synthesis, and 70 were eligible to be included in the meta-analysis (22 were excluded due to insufficiently disaggregated data). A detailed process of study screening and selection is presented in the PRISMA flow diagram (Figure 1).

Quality assessment of the included studies

Quality assessment of 92 studies included in this review was done using Jonna Briggs Institute (JBI) Critical Appraisal Tool based on study design. Thirty-five studies (38%) were assessed as high quality, 33 studies (36%) were assessed as moderate quality, and 24 studies (26%) were assessed as poor quality (Appendix S2 in the Online Supplementary Document). The detailed information on quality assessment of individual study is presented in Table 1.

Table 1.  General characteristics of included studies

SMBG – self-monitoring of blood glucose, NR – not reported, IQR – interquartile range, SD – standard deviation

Characteristics of the included studies

Of the total included studies (n = 92), 50 were conducted in India [18,34–82], 15 in Pakistan [19,83–96], 15 in Nepal [20,97–110], 10 in Bangladesh [21,111–119] and two in Sri-Lanka [120,121]. No studies were conducted in the Maldives, Bhutan, and Afghanistan. 78 studies were based on data recorded in health facilities (hospitals, primary health care centres, diabetic clinics, and pharmacies) while 14 studies were based on data collected in community settings. The general characteristics of the studies are summarized in Table 1. The total number of participants in the included studies was 36 180 (16 601 male and 19 559 female) and ranged from 48 participants in the smallest study [51] to 11 917 in the largest study [115]. The mean age of the participants, as reported by 66 studies, ranged from 43 to 64 years. 24 studies reported the length of time participants were living with T2DM, which ranged from 1.5 to 9.7 years. Thirty studies reported on smoking habits (n = 30) while fifteen studies reported on alcohol use (n = 15). The median score for tobacco use (smoke and/or smokeless form) was 18.6% (IQR = 10.6%-23.8%) and 25.2% (IQR = 13.8%-38.1%) for alcohol consumption among the participants.

Domains of T2DM self-care behaviours

Among all the self-care behaviours, physical activity (n = 61) was the most reported self-care behaviour followed by medication intake (n = 57), dietary habits (n = 56), self-monitoring of blood glucose (n = 42), and foot care (n = 30). Studies adopted a wide range of scales (n = 58) to assess the different domains of self-care behaviours. Many studies did not provide information about the tool used (n = 27) and some studies (n = 7) reported using author-developed tools. The Summary of Diabetes Self-Care Activities measure (SDSCA) [122] was used by 16 studies and the Diabetes Self-Management Questionnaire (DSMQ) [123] by seven studies to assess the different domains of self-care behaviours. Similarly, the Morisky Medication Adherence Scale (MMAS) scale was used by 23 studies in assessing the status of medication adherence among the study participants [124,125]. Four studies used the Global Physical Activity Questionnaire (GPAQ) [126] and the International Physical Activity Questionnaire (IPAQ) [127] was used by three studies to measure the physical activity level of the study participants. The findings on self-care behaviours were reported in the form of a percentage, mean and median.

Physical activity

Physical activity was assessed by 61 studies (Table 2). The Summary of Diabetes Self-Care Activities measure (n = 15), the Diabetes Self-Management Questionnaire (n = 7), the Global Physical Activity Questionnaire (n = 4), and the International Physical Activity Questionnaire (n = 3) were the most used tools in assessing the study participants’ physical activity. Two studies reported the mean number of days in a week participants were physically active, ranging from 4.08 to 4.23 days [20,45]. Additionally, four studies reported the mean score for physical activity ranging from 3.74 to 5.1 (scale range of 0-10, where 10 represents the optimal practice of self-care) [73,76,86,95].

Table 2.  Physical activity

SD – standard deviation, IQR – interquartile range

The overall pooled prevalence of adherence to sufficient physical activity was 53% (95% CI = 39-66) and ranged from 9% to 80%. In terms of country-specific pooled prevalence, studies conducted in Sri Lanka (n = 1) reported an adherence of 79% (95% CI = 74-82), followed by Bangladesh (n = 5; 58%, 95% CI = 23-91), Nepal (n = 9; 51%, 95% CI = 39-63), India (n = 27; 45%, 95% CI = 37-52) and Pakistan (n = 5; 35%, 95% CI = 12-59) (Figure 2). Adherence to sufficient physical activity was 54% (95% CI = 38%-69%) for studies that either used a standardised tool to assess physical activity or studies that clearly defined what sufficient physical activity constitutes. Adherence to sufficient physical activity was 47% (95% CI = 34%-59%) for studies that did not clarify either the measure used to assess physical activity or studies that did not define what sufficient physical activity constitutes (Figure S1-S2 in the Online Supplementary Document).

Figure 2.  Pooled estimate of physical activity among people with T2DM.

Medication use

57 studies measured adherence to the medication use (Table 3). The Morisky Medication Adherence Scale (n = 23) and the Summary of Diabetes Self-Care Activities measure (n = 10) were the most used tools in measuring adherence to medication use. A study from Nepal reported a mean of 6.77 number of days per week participants’ adhering to medication [20]. Non-adherence to Oral Hypoglycaemic Agents and Insulin was assessed by a study from Bangladesh [113], where 20% and 6.6% were non-adherence to Oral Hypoglycaemic Agents and Insulin respectively.

Table 3.  Medication adherence

SD – standard deviation, OHA – oral hypoglycaemic agent, d – day

The pooled prevalence of adherence to medication use was 64% (95% CI = 53-74) and ranged between 3% and 98%. Studies conducted in Nepal reported a higher prevalence of adherence to medication use (n = 6; 86%, 95% CI = 64-100), followed by India (n = 19; 64%, 95% CI = 52-75), Pakistan (n = 6; 50%, 95% CI = 21-78), Bangladesh (n = 1; 43%, 95% CI = 34-52) and Sri-Lanka (n = 1; 23%, 95% CI = 17-29) (Figure 3).

Figure 3.  Pooled estimate of medication intake among people with T2DM.

Dietary habits

56 studies explored the study participants’ dietary intake (Table 4) using a range of dietary measurement tools. Summary of the Diabetes Self-Care Activities measure (n = 15) and the Diabetes Self-Management Questionnaire (n = 7) were the most used self-care tools in assessing the dietary practice of the study participants. Some studies reported the mean number of days in a week participant’s adhering to a healthy diet ranging from 4.32 to 5.42 days [20,45,47]. In addition, the reported mean score for dietary control (limiting sweets and carbohydrate-rich foods, consuming recommended diet) varied from 3.9 to 6.6 (scale range of 0-10, where 10 represents the optimal practice of self-care) [73,76,86,95]. Non-adherence to healthy dietary habits was reported by four studies whose values range from 41% to 88% [100,107,112,113].

Table 4.  Dietary habits

SD – standard deviation, IQR – interquartile range, d – days

*General diet: Consumption of generally helpful or prescribed diet.

†Specific diet: Consumption of five or more servings of “fruits and vegetables” and avoiding fat foods.

‡Dietary control: Limiting sweets and carbohydrate rich foods, consuming recommended diet.

The prevalence of adherence to a healthy diet varied widely across studies, from 0% to 95.7%. The overall pooled prevalence of adherence to a healthy diet was 48% (95% CI = 38-58). In terms of country-specific analysis, the studies conducted in India (n = 22) had an adherence to a healthy diet of 51% (95% CI = 39-63), followed by Pakistan (n = 6; 51%, 95%CI: 27-75), Nepal (n = 4; 44%, 95%CI: 10-79) and Bangladesh (n = 2; 24%, 95%CI: 16-31) (Figure 4). Adherence to a healthy diet was 40% (95%CI = 29%-53%) for studies that either used a standardised tool to assess diet or studies that clearly defined what a healthy diet constitutes. Adherence to a healthy diet was 57% (95%CI = 42%-72%) for studies that did not clarify either the measure used to assess diet or studies that did not define what a healthy diet constitutes (Figure S3-S4 in the Online Supplementary Document).

Figure 4.  Pooled estimate of Dietary habit among people with T2DM.

Blood glucose monitoring

42 studies investigated blood glucose monitoring (Table 5). The Summary of Diabetes Self-Care Activities measure (n = 10) and the Diabetes Self-Management Questionnaire (n = 7) were the most used tools in assessing the blood glucose monitoring among the study participants. The mean number of days in a week practicing adequate self-monitoring of blood glucose was reported by two studies and ranged from 0.61 to 1.33 days [20,45]. Similarly, the reported mean scores for glucose management ranged from 3.92 to 6.82 (scale ranging from 0 to 10, where 10 represents the highest practice of self-care behaviour) [73,76,86,95]. However, non-adherence to blood glucose monitoring was reported by a study from Bangladesh [112,113] which ranged from 32% to 37%, while 46.61% of participants did not monitor the glucose level regularly in Nepal [107].

Table 5.  Blood glucose monitoring

IQR – interquartile range, SD – standard deviation, HbA1c – glycated haemoglobin, d – days, mo – months

*Testing blood glucose: Testing of blood glucose and as recommended by health care provider

The overall pooled prevalence of blood glucose monitoring was 65% (95%CI: 49-80), ranging between 18% to 95%. A higher prevalence of adequate blood glucose monitoring among people with T2DM was found in India (n = 14; 68%, 95% CI = 53-82), followed by Pakistan (n = 1; 66%, 95% CI = 61-71), Bangladesh (n = 3; 60%, 95% CI = 42-76), and Nepal (n = 3; 55%, 95% CI: 25-84) (Figure 5). The sub-group analysis for blood glucose monitoring was assessed based on monitoring blood glucose levels at least once a month and/or at least once in three months.

Figure 5.  Pooled estimate of blood glucose monitoring among people with T2DM.

In the sub-group analysis, the pooled prevalence of monthly blood glucose monitoring was 63% (95% CI = 48-77), while it was 67% (95% CI = 53-79) for the at least once in three months interval (Figure S5-S6 in the Online Supplementary Document).

Foot care

Thirty studies investigated the practice of foot care (Table 6). The Summary of Diabetes Self-Care Activities measure tool (n = 10) was most used in assessing the study participants’ foot care. The mean number of days in a week participants practicing foot care ranged between 0.55 and 2.16 days [20,45]. A study from India among 200 people with T2DM reported that the median number of days in the past week inspecting shoes or footwear was “0” [60]. Studies from Bangladesh reported on non-adherence to foot care ranging from 43.2 to 70% [112,113].

Table 6.  Foot care

SD – standard deviation

*Foot care: Checking feet and inside of shoe, and washing, and drying feet.

The overall pooled prevalence of adherence to foot care was 42% (95% CI = 30-54) and ranged between 6% and 92%. Studies conducted in Pakistan reported the highest adherence to foot care (n = 2; 72%, 95%CI = 47-94) followed by Nepal (n = 3; 52%, 95% CI = 19-84), Bangladesh (n = 1; 37%, 95% CI = 32-43) and India (n = 15; 33%, 95% CI = 21-45) (Figure 6). Sufficient adherence to foot care was 37% (95% CI = 18-57) for studies that either used a standardised tool to assess foot care or studies that clearly defined what adequate foot care constitutes. Adherence to sufficient foot care was 29% (95% CI = 8-57) for studies that did not clarify either the measure used to assess foot care or studies that did not define what sufficient foot care constitutes (Figures S7-S8 in the Online Supplementary Document).

Figure 6.  Pooled estimate of foot care among people with T2DM.

DISCUSSION

Adherence to self-care behaviour prevents T2DM-associated morbidities and mortalities [14,15]. The systematic reviews that included studies from Ethiopia [22,23], Sub-Saharan Africa [24], and LMICs [25] reported the poor practice of self-care behaviours among the people with T2DM and stressed the need for developing and implementing interventions to improve self-care behaviour. South Asians are at higher risk of developing NCDs, including type 2 diabetes [5], and the health care resources in this region are limited [128,129]. While previous systematic reviews on self-care behaviours have been conducted in various regions [11,22–25], no reviews have focused on studies conducted in South Asia. To the best of our knowledge, this is the first systematic review and meta-analysis to systematically assess and report the evidence on self-care behaviours among people with T2DM in South Asia countries. We also conducted a meta-analysis to calculate the pooled prevalence of different domains of self-care behaviour reported in 70 studies. The prevalence of T2DM self-care behaviour was highest for blood glucose monitoring, followed by medication adherence, physical activity, diet, and foot care.

Physical activity was the most frequently measured self-care behaviour among included studies. The pooled prevalence of adherence to physical activity was 53%. This shows insufficient participation in physical activity among South Asians with T2DM. Similar findings were observed in reviews from Ethiopia conducted by Dagnew et al. [23] (pooled prevalence = 48.29%) and Katema et al. [22] (pooled prevalence = 49%). In contrast, lower adherence to physical activity was reported in Canadian studies (21%) by Thiel et al. [130] and LMICs (41.2%) by Morge et al. [25]. This discrepancy might be because of the higher presence of manual labour in low-income countries compared to sedentary occupation and personal motorized transportation in high-income countries [131]. However, studies identified that time constraint, unwillingness, poor awareness level, comorbid conditions, social issues, lack of infrastructure and insufficient emphasis by physicians were the barriers to physical activity among South Asians with T2DM [59,100,120,132]. Engaging in sufficient physical activity reduces the risk of T2DM and plays a significant role in reducing the glycaemic level among people with T2DM [133,134]. This illustrates that physical activity is a key self-care behaviour for diabetes management and needs to be improved in South Asians with T2DM by designing culturally acceptable and person-centred interventions to facilitate and encourage people to adopt healthy behaviours.

The pooled prevalence of adherence to medication use in this review was 64%. This finding is consistent with the review from Sub-Saharan Africa conducted by Stephani et al. [24] that reported a mean adherence to medication use of 64% (range = 39%-88%). However, a higher prevalence of adherence to medication use (71%, range = 59%-83%) is reported by Morge et al. [25]. The lower adherence to medication use in South Asia might be the result of a poor understanding of the role of medication use in controlling blood glucose levels and the preference for traditional home remedies [135]. The practice of fasting, a cultural practice observed by people from various faiths, may impede compliance with medication intake [136,137]. Unaffordability, lack of information about prescribed medicines and their importance, ignorance and unwillingness, forgetfulness, poor drug supply from health facilities and poor doctor-patient relationship are significant factors for the lower adherence to medication use among the people with T2DM in South Asian countries [19,46,61,104,107]. Although adherence to medication use has a positive impact in controlling the glycaemic level [138], almost half of the South Asians did not adhere to their prescribed medication use and are at risk of developing acute and long-term complications, consequently leading to an increased hospitalization rate and higher medical costs [138–140]. Interventions aiming to raise awareness of the role of regular use of medication in controlling blood glucose levels are to be designed and implemented to adhere to the treatment regimen, and primary health care facilities need to be equipped with proper infrastructure required for screening of diabetes, provision of regular drug supplies and counselling services.

Less than half (48%) of the study participants adhered to healthy dietary behaviour. This finding is consistent with the reviews from Ethiopia conducted by Dagnew et al. [23] and Katema et al. [22], both reporting a pooled estimate of 50% for good dietary practice. A study by Stephani et al. [24] from Sub-Saharan Africa reported adherence to a healthy diet ranging between 33%-87%, while a study by Morge et al. [25] examining adherence in low- and middle-income countries reported 58%. A study by Coyle et al. [11] examining adherence in high-income countries reported healthy diet adherence ranging between 50% and 80.9%. As such, these studies reported a relatively higher prevalence of adherence to dietary habits than those reported in our study. The differences in study outcomes might be due to differences in foods consumed in other countries and the difference in cultural and traditional values. For example, South Asians often eat certain foods because of their cultural and traditional importance, even if they are known to be unhealthy [135]. In addition, South Asians consume high amounts of white rice, other refined grains, saturated fats, and low amounts of fibre and vegetables; these food patterns increase the risk of T2DM [141,142]. Furthermore, poor quality information on dietary modification and misconceptions on what a healthy diet constitutes might have also restricted adherence to healthy dietary behaviours among South Asians [135]. Cost constraints are also a barrier to consuming the recommended amount of fruits and vegetables among South Asians [143]. Evidence shows that the practice of fasting, a religious belief observed with Hindus (Navratri, Mahashivratri, Janmashtami, Ashtami, Ekadashi), Muslim (Ramadan), and Jain (Ekasana, Digambarupvas), has also impacted the practicing of healthy dietary habits [136]. As diet plays an important role in controlling glycaemic levels and preventing T2DM complications [144,145], there is an need for addressing dietary behaviours among people with T2DM in South Asia. This can be achieved by implementing culturally tailored and contextual interventions on healthy diets, given the importance of diet in maintaining the recommended level of blood glucose.

Regular blood glucose monitoring improves blood glucose level among people with T2DM [146] and its frequency varies from person to person depending on the patient’s needs and health care provider’s advice. We found that the pooled prevalence of blood glucose monitoring was 65%. However, studies by Morge et al. [25] (range = 13%-79%), Ketema et al. [22] (pooled prevalence = 28%), and Dagnew et al. [23] (pooled prevalence = 31.89%) found a lower prevalence of blood glucose monitoring than our study. This might be because we only considered those monitoring the blood glucose level at monthly or at least once in three months intervals as adhering to the blood glucose monitoring, while the above-mentioned studies considered daily, weekly, monthly, three-monthly, bi-annually and other intervals. Unlike other self-care behaviours, it was difficult to compare the practice of blood glucose monitoring among people with T2DM due to varied treatment goals. Also, the access to glucometers at the household level in South-Asia is minimal because of cost constraints, thus contributing to suboptimal blood glucose monitoring. The engagement of community health workers in primary health care centres can ensure comprehensive health care services are delivered and self-management of NCDs is promoted [147]. As such, community health workers can be trained to conduct regular visits to patients with T2DM and provide social prescriptions required for adopting healthy self-care behaviour.

The overall pooled prevalence of adherence to foot care was 42%. A lower prevalence of foot care than in this study was observed in the review by Morge et al. [25] which reported a median adherence to foot care of 36.5% (IQR = 13.6%-59.2%). However, the studies conducted by Dagnew et al. [23] (pooled prevalence = 63.61%) and Ketema et al. [22] (pooled prevalence = 58%) reported higher adherence to diabetic foot-care. The lower prevalence of foot care among people with T2DM in the South-Asian region might be the result of the practice of barefoot walking, use of inappropriate footwear, poor awareness of foot care and its complications, and poor counselling on foot care from service providers [148,149]. Foot problems due to T2DM can have a large economic impact which deteriorates the quality of life and ultimately results in physical impairment [150]. There is a high need for health literacy programs on foot care and its complication among people with T2DM in this region.

Strengths and limitations:

This study has several strengths. This review adhered to the PRISMA guidelines [26] and is registered in the PROSPERO website [151] (Registration number: CRD42021242930). We included cross-sectional and observational studies searching multiple databases and performed forward and backward reference checking to ensure no relevant articles were missed. In addition, this study considered and categorized the studies as those defining the study tool and/or providing a clear definition of self-care domain and those not reporting the study tool and/or not providing a clear definition of self-care domain (reporting only good or poor practice). This allowed for sub-group analyses and pooled prevalence calculation to be done separately. Moreover, this study is the first of its kind to provide comprehensive findings on the practice of self-care behaviours among people with T2DM in South Asian countries.

This study also had some limitations. The findings of the sub-group analysis, specifically among studies not defining study tools and/or not providing a clear definition of self-care domains assessed, should be used with caution. Another limitation was that only “high adherence” to medication intake was categorized as adequate. This is because moderate adherence was unevenly calculated (scoring for moderate adherence differed) among the included studies. In addition, the pooled prevalence of adequate blood glucose monitoring might be over-reported, as we included only those monitoring blood glucose every month or at least once in three months in the meta-analysis. Moreover, the country-specific findings on each domain of self-care should be interpreted with caution, as the number of studies varied between countries, with some countries reporting very low numbers. Finally, outcomes might be biased as most of the included studies only assessed self-reported self-care behaviours.

CONCLUSION

The findings of this meta-analysis suggest that the overall self-care behaviour among people with T2DM in South Asia was low. Of five self-care domains, blood glucose monitoring and medication adherence were relatively common compared to physical activity, diet, and foot care. There is a need for designing and implementing high-quality, community-based, cost-effective, and culturally-tailored interventions to improve self-care among people with T2DM in South Asia.

Additional material

Online Supplementary Document

Acknowledgements

We would like to thank and acknowledge Dr Rashidul Alam Mahumud at Faculty of Medicine and Health, The University of Sydney for his valuable suggestions during the process of conducting the review and drafting the manuscript.

[1] Funding: This research was supported by an Australian Government Research Training Program Scholarship.

[2] Authorship contributions: GP conceptualised the study and designed the protocol under the supervision of LR and CV. GP, LR, and CV identified and finalised the search strategies. GP independently performed the search; GP and PD contributed to screening, data extraction, and quality assessment of studies. TB conducted the meta-analysis and GP drafted the manuscript. LR, CV, UNY, TS, TB, and PD reviewed the draft manuscript, provided critical comments, and approved the final manuscript.

[3] Disclosure of interest: The authors completed the ICMJE Unified Competing Interest Form (available upon request from the corresponding author) and declare no relevant interests.

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Correspondence to:
Grish Paudel
School of Health Medical and Applied Sciences
Central Queensland University
Sydney
Australia
[email protected]