Diabetes Self-Care in Asia, the Gulf Cooperation Council and Western Countries: A Systematic Review with Narrative Synthesis

Diabetes mellitus (DM) is one of the most prominent non-communicable disease epidemics of the twenty-first century. According to the International Diabetes Federation (IDF), 537 million people aged 20–79 years had diabetes in 2021, or 10.5% of this population. The IDF predicts that this number will increase to 643 million by 2030 and 783 million by 2045 [1]. These numbers conceal significant regional differences: South-East Asia and the Western Pacific bear the largest absolute burden, while the Middle East and North Africa (MENA) region, which includes all six GCC countries, recorded the highest adult diabetes prevalence globally at 18.1% (age-adjusted comparative prevalence, 2021) [1].

The chronic and multisystemic nature of diabetes necessitates sustained and active engagement by patients in their own care—commonly termed diabetes self-management or self-care. Self-care encompasses a spectrum of behaviours including adherence to medication, dietary modification, regular physical activity, structured blood glucose monitoring, foot inspection, tobacco abstinence, and engagement with healthcare services for complication screening [2]. Improved glycaemic and blood-pressure control, to which these behaviours contribute, reduces the risk of microvascular complications (retinopathy, nephropathy, neuropathy), macrovascular events (myocardial infarction, stroke), diabetic foot ulcers and premature mortality [3–5].

Despite decades of research confirming the efficacy of self-care interventions—particularly structured diabetes self-management education (DSME) programmes [2,6–8] and physical activity [9]—uptake and practice remain suboptimal in all regions, though for different reasons. In Western healthcare systems, reported barriers include healthcare fragmentation, medication cost (especially in the USA) and psychosocial burden [10]. In the GCC, dietary transition, sedentary lifestyles, the clinical complexity introduced by Ramadan fasting, and access differences between national citizens and expatriate workers have been described [11]. Asia is remarkably diverse: resource-constrained rural areas in South and Southeast Asia coexist with technologically sophisticated urban centres in China, South Korea and Japan; in lower-income settings, out-of-pocket costs can limit access to guideline-recommended care [12].

The rapid development of digital health solutions—telemedicine, continuous glucose monitoring (CGM), mobile health (mHealth) apps and AI-assisted clinical decision support—is another factor. These technologies are changing self-care opportunities, but their adoption is uneven: it is most prevalent in Western countries and parts of East Asia, expanding in GCC metropolitan centres, and nascent or limited in low-resource Asian settings because of cost and connectivity [13–15].

Several reviews have examined diabetes self-management within a single region, population or intervention type. Thirunavukkarasu and Alsaidan synthesised self-management behaviours across GCC countries in a narrative review [11]; Maina et al. mapped complication-prevention self-management practices in low- and middle-income countries [12]; Hawthorne et al. evaluated culturally appropriate education for ethnic minority groups, predominantly in Western countries [16]; and Piragine et al. pooled adherence to oral antidiabetic drugs globally without region-specific estimates [17]. Other reviews have addressed specific interventions—DSME [2,8], mobile health [13–15] and telemedicine [18]—or conceptual models of self-care [19]. To our knowledge, none of these (i) placed Asian, GCC/MENA and Western evidence side by side within a single prespecified framework, (ii) separated intervention-efficacy evidence from regional implementation evidence, or (iii) examined cultural, religious and economic modifiers across all three spheres. The present review addresses this gap. Because the three spheres are internally heterogeneous, we defined them at country level and report findings by subgroup where possible; the cross-regional comparisons that follow are predominantly indirect and are interpreted accordingly.

Importance of the Study

Understanding why and how self-care varies between settings is more than an intellectual endeavour. Complications such as amputation, end-stage renal disease and vision loss consume a disproportionate share of health budgets and have serious effects on affected people and their families. The IDF estimated direct health expenditure attributable to diabetes at USD 966 billion globally in 2021 [1]. Comparative analysis can support the adaptation of proven interventions to new settings, help avoid the repetition of failures, and inform culturally competent clinical guidelines. For GCC health systems undergoing transformation under national visions such as Saudi Arabia's Vision 2030, and for resource-constrained Asian health systems that are expanding capacity, such evidence is needed.

Study Design and Reporting

This is a systematic review with narrative synthesis, reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [20] (completed checklist in Supplementary Appendix S8) and the Synthesis Without Meta-analysis (SWiM) reporting guideline [21]. Because study designs, populations, self-care measures and outcomes were heterogeneous, quantitative pooling was not undertaken; findings were synthesised narratively after systematic identification, screening and appraisal of sources.

Protocol and Registration

No review protocol was prospectively registered in PROSPERO, the Open Science Framework or any other registry, and no protocol was published. Without a registered protocol, post hoc changes to methods cannot be ruled out; this is acknowledged as a limitation (Section 9).

Information Sources and Search Strategy

PubMed/MEDLINE, Scopus and Web of Science Core Collection were searched on 1 September 2024 for records published from 1 January 2000 to the search date. The search was not updated after this date. The strategy combined four concept blocks—diabetes, self-care, geography, and complication/outcome or digital-health terms—using MeSH and free-text terms in PubMed and equivalent title/abstract/keyword fields in Scopus and Web of Science. The core concept structure was: ("diabetes mellitus" OR "type 2 diabetes" OR "T2DM") AND ("self-care" OR "self-management" OR "patient education" OR "adherence") AND ("Asia" OR "South Asia" OR "Southeast Asia" OR "East Asia" OR "Gulf Cooperation Council" OR "GCC" OR "Saudi Arabia" OR "United Arab Emirates" OR "Middle East" OR "Western countries" OR "Europe" OR "North America") AND ("complication prevention" OR "glycemic control" OR "HbA1c" OR "foot care" OR "retinopathy" OR "nephropathy" OR "digital health" OR "mHealth"). The full, database-specific strategies—with field tags, controlled vocabulary, limits, exact search dates and the number of records retrieved from each database—are reported in Supplementary Appendix S1.

Search Sensitivity

Requiring the fourth concept block (complication/outcome or digital-health terms) increases precision but may reduce sensitivity for self-care studies that do not mention these terms in indexed fields. To mitigate this, the reference lists of all included sources and of key reviews [2,12,16,17] were hand-searched. Residual risk of missed studies is acknowledged as a limitation (Section 9).

Grey Literature

The websites of the World Health Organization (www.who.int/publications and the IRIS repository), the International Diabetes Federation (www.idf.org; www.diabetesatlas.org) and the National Institute for Health and Care Excellence (www.nice.org.uk/guidance) were searched in September 2024, alongside the database searches, using the terms "diabetes", "self-care", "self-management", "education" and "Ramadan". Guidelines, atlases and technical reports were eligible if they were issued by a national or international organisation, described their evidence base or development method, and made recommendations or reported data on self-care, education or complication prevention in adults with diabetes. The grey-literature search log is given in Supplementary Appendix S2.

Publications After the Search Cut-Off

Three publications dated 2025 [11,19,22] appeared in the reference list of the original submission. They were not identified through the systematic search, which ended on 1 September 2024. They are retained only as contextual references, are labelled as such in Supplementary Table S4 (Part B), and do not contribute to the evidence synthesis, the tables of findings or the certainty ratings.

Eligibility Criteria and Geographic Definitions

Studies were included if they: (i) involved adult participants (≥18 years) with type 1 or type 2 diabetes; (ii) reported on self-care behaviours, patient education, awareness or complication-prevention strategies; (iii) were conducted in, or explicitly reported data from, Asia, GCC/MENA or Western countries (Europe, North America, Australia, New Zealand); (iv) were published in English between January 2000 and September 2024; and (v) were primary research studies (randomised or non-randomised trials, cohort, cross-sectional or instrument-validation studies), systematic reviews, meta-analyses or scoping reviews, or evidence-based guidelines/consensus statements from recognised professional bodies. Studies were excluded if they focused exclusively on pharmacological interventions without a self-care component, lacked geographic specificity, studied populations without diabetes, were narrative or conceptual reviews, editorials or commentaries, or if the full text was unavailable. Conference abstracts without full data were also excluded.

Geographic Definitions

Countries were assigned to spheres a priori at country level (full list in Supplementary Appendix S3). Asia: East Asia (China, including Hong Kong SAR; Taiwan; Japan; Republic of Korea), South Asia (e.g., India, Pakistan, Bangladesh, Sri Lanka, Nepal) and Southeast Asia (e.g., Vietnam, Thailand, Malaysia, Indonesia, the Philippines, Singapore). GCC/MENA: the six GCC member states (Saudi Arabia, United Arab Emirates, Kuwait, Qatar, Bahrain, Oman) form the core group; other countries of the IDF MENA region (e.g., Egypt, Jordan, Palestine, Iran) form a separate "wider MENA" subgroup, whose findings are reported separately and are not attributed to the GCC. Western countries: countries of Europe, the United States, Canada, Australia and New Zealand. Countries spanning geographic or cultural classifications were assigned by their IDF region: Iran (IDF MENA region) was assigned to the wider-MENA subgroup, and Turkey (IDF Europe region) was treated as a transcontinental case reported separately and not used to characterise either Western or MENA findings. Multinational studies were classified as "multi-regional", and their findings were attributed to a sphere only when results were reported by country.

Study Selection

Records were de-duplicated with reference-management software. Titles and abstracts, and then full texts, were screened independently by two reviewers against the eligibility criteria; disagreements were resolved by discussion and, where necessary, by a third author. Inter-reviewer agreement was not formally quantified (e.g., with Cohen's kappa), which is acknowledged as a limitation (Section 9). At revision, every source retained after full-text screening was re-assessed against the prespecified criteria (eligibility re-audit); the sources excluded at this stage are listed with reasons in Supplementary Appendix S9.

Data Extraction

Data were extracted with a standardised form that was piloted on an initial sample of sources and refined before use. At revision, all extracted data were re-checked against the full text or published abstract of each source and corrected where necessary. Extracted variables were: first author and year; country, sphere and subgroup; study design and evidence stream; setting; population (diabetes type, age, sample size); self-care domain(s); measurement instrument; intervention and comparator (where applicable); outcomes and effect estimates; period of data collection; and appraisal results. The extracted characteristics of every source are given in Supplementary Table S4.

Evidence Streams and Avoidance of Double-Counting

Included sources were allocated to three evidence streams that were analysed separately: Stream A, primary studies; Stream B, systematic reviews, meta-analyses and scoping reviews; and Stream C, guidelines and consensus statements. Stream B was used to answer intervention-efficacy questions; Stream A was used to describe regional practice, implementation and determinants. When a primary study was also included in an included systematic review, its results were not counted again within the same evidence body (overlap was checked by comparing reference lists). Stream C documents were used to define recommended standards (e.g., screening intervals) and to frame recommendations, not as evidence of effect. References cited only for background are identified as contextual in Supplementary Table S4 (Part B) and were not used to derive findings or certainty ratings.

Quality Appraisal

Methodological quality was appraised with design-specific tools: the Cochrane RoB 2 tool for randomised trials [23], JBI critical appraisal checklists for cohort, analytical cross-sectional and instrument-validation studies [24], AMSTAR 2 for systematic reviews [25], and AGREE II domains for guidelines [26]. Appraisal was completed at the revision stage, after study selection, against the published criteria of each tool; the judgement for every source is reported in Supplementary Table S4.

Data Synthesis

Meta-analysis was not possible because of variation in study designs, populations and outcome measures. Synthesis followed the SWiM guideline [21] and the ESRC guidance on narrative synthesis [27] in six steps. (1) Grouping: findings were grouped by self-care domain—(a) awareness and education; (b) medication adherence; (c) diet; (d) physical activity; (e) foot care and complication screening; (f) glucose monitoring and digital health; (g) cultural, religious, economic and psychosocial factors; (h) complication prevention—and, within each domain, by sphere and subgroup. (2) Standardised metric: for intervention questions, the mean difference in HbA1c (percentage points) reported by included systematic reviews or trials was used; for practice and adherence questions, proportions were tabulated as reported, with the instrument used, and were not pooled. (3) Vote counting based on statistical significance was not used. (4) Conflicting findings were examined against study design, risk of bias, measurement instrument, setting and period; conflicts that could not be explained are reported as inconsistency. (5) Direct versus indirect comparison: a cross-regional comparison was classified as direct only when a single study measured self-care in more than one sphere using the same methods (e.g., the DAWN study [10]); all other contrasts are labelled indirect and interpreted cautiously. (6) Strength and consistency of evidence were summarised with GRADE.

Certainty of Evidence

Certainty was rated with GRADE [28] for eleven prespecified outcome–comparison evidence bodies (Section 3.10), not for regions as a whole. Bodies of randomised evidence (or systematic reviews of trials) started at high certainty and observational evidence at low certainty, and were downgraded for risk of bias, inconsistency, indirectness (including transfer of findings across regions), imprecision or publication bias, or upgraded for large effects or a dose–response gradient. Where no single pooled estimate was available, ratings followed the approach of Murad et al. for narrative syntheses [29]. Downgrading and upgrading decisions are explained in Section 3.10 and Supplementary Appendix S5.

Study Selection

The database searches retrieved 5,305 records. After removal of duplicates, screening of titles, abstracts and full texts against the eligibility criteria, and supplementary hand-searching of reference lists and grey literature, 52 sources were retained and cited in the original submission. At revision, these 52 sources were re-assessed against the prespecified criteria (eligibility re-audit), and 14 were excluded with reasons: published after the search cut-off (n = 3) [11,19,22]; ineligible design, such as commentary, conceptual or basic-science review or modelled epidemiological estimates (n = 5) [30–34]; population without diabetes or topic not diabetes-specific (n = 4) [35–38]; outside the three spheres (n = 1) [39]; and pharmacological intervention without a self-care component (n = 1) [40] (Figure 1; Supplementary Appendix S9).

Thirty-eight sources were therefore included: 19 primary studies (Stream A), 13 systematic reviews, meta-analyses or scoping reviews (Stream B) and six guidelines or consensus statements (Stream C). The excluded sources are still cited where they provide background and are labelled as contextual references (Supplementary Table S4, Part B). The numbers of duplicates and of records excluded at the title/abstract and initial full-text stages were not retained in a form that allows exact reporting; this is acknowledged as a limitation (Section 9).

Adapted from the PRISMA 2020 flow diagram template [20]. 52 sources retained after full-text screening − 14 excluded at the eligibility re-audit = 38 included sources.

Characteristics of Included Sources

Table 1 summarises the evidence base by stream and sphere; Supplementary Table S4 lists every source with its design, country, population, sample size, self-care measure, outcomes, main findings and appraisal. Of the 19 primary studies, five were from Asia (China, Vietnam, Bangladesh, Republic of Korea), two from GCC member states (both Saudi Arabia), four from the wider MENA subgroup (Egypt, Palestine, Iran), one from Turkey, six from Western countries (USA, UK) and one was multi-regional (DAWN, 13 countries). Nine were cross-sectional surveys, four instrument-validation studies, four randomised or controlled trials and two cohort studies. All 13 systematic reviews synthesised trials or studies from Western or multiple regions; none was restricted to Asia or the GCC. GCC-specific conclusions therefore rest on limited direct evidence.

Table 1: Composition of the Included Evidence Base by Evidence Stream and Geographic Sphere (Number of Sources)

Western Reviews: [2,7,16,41]; Multi-Regional Reviews: [12–15,17,18,42–44]; Western Guidelines: [3,9,45,46]; Multi-Regional Guidance: [47,48]. Individual sources are listed in Supplementary Table S4

Epidemiological Context and Diabetes Burden

The diabetes burden is unequally distributed worldwide, and this epidemiological heterogeneity shapes self-care priorities. The GCC is part of the MENA region, which had the highest age-adjusted comparative prevalence of all IDF regions in 2021 (18.1%), compared with 11.9% in North America and the Caribbean, 10.0% in South-East Asia, 9.9% in the Western Pacific and 7.0% in Europe [1]. The largest national numbers of adults with diabetes are found in China, India and Pakistan [1]. IDF regions do not map exactly onto the spheres used here (for example, the Western Pacific region includes both China and Australia, and the MENA region includes non-GCC countries), so these figures describe context rather than sphere-specific estimates. Western countries generally report lower prevalence; however, rising rates of type 2 diabetes and prediabetes linked to obesity challenge this pattern [1]. A descriptive cross-regional overview of several self-care domains is given in Table 2; it summarises the available evidence and its sources and is not intended as a ranking of regions.

Table 2: Descriptive Overview of Diabetes Self-Care Indicators in Asia, GCC/MENA and Western Countries, with Sources

CGM: Continuous Glucose Monitoring, DSME: Diabetes Self-Management Education, GCC: Gulf Cooperation Council, MENA: Middle East and North Africa, MMAS-8: 8-item Morisky Medication Adherence Scale. Entries without a citation are descriptive health-system context, not derived from included studies and not graded. Values in different columns come from different populations, instruments and years and must not be compared directly. Amputation-rate ranges and region-level GRADE labels shown in the previous version have been removed: the amputation ranges could not be traced to a source with a defined population and period, and certainty is now rated per outcome (Section 3.10). The source of every numerical value is listed in Supplementary Appendix S6

Diabetes Self-Management Education and Awareness

Structured DSME is the most consistently evidenced intervention for improving self-care behaviours and glycaemic outcomes [2,7,8]. In Western countries, DSME is embedded within national guidelines: the UK's DESMOND and Diabetes Manual programmes [6,52], the USA's national DSMES standards [3], and equivalent European frameworks represent mature, community-based delivery models. In a meta-analysis of 31 randomised trials, Norris et al. found that DSME reduced HbA1c by 0.76 percentage points (95% CI 0.34–1.18) more than control at immediate follow-up, with smaller effects at longer follow-up [8]. In the DESMOND cluster trial, the HbA1c difference was no longer significant at 3 years (−0.02; 95% CI −0.22 to 0.17; 604 participants with biomedical data), although improvements in illness beliefs persisted [6].

No included primary study evaluated DSME delivery in a GCC member state; the two included Saudi studies assessed diabetes distress [57] and population disease burden [58]. In the wider MENA subgroup, lower disease knowledge and weaker beliefs about the necessity of medicines were associated with non-adherence in Palestine [49], and patient education level and physician participation in diabetes training were associated with better glycaemic control in Egyptian primary care [50]. A recent narrative review, published after our search cut-off and therefore not included, describes predominantly hospital-based education services in GCC countries [11].

Asian evidence was heterogeneous. In six urban districts of Chengdu, western China, 46% of 364 surveyed patients showed "good" self-management behaviour, 45% "fair" and 6% "poor"[51], and a Korean instrument-development study (n = 473) produced a locally validated self-management scale [59], no included Asian study evaluated a DSME programme. In a Cochrane review of 11 trials, culturally appropriate health education improved short-term glycaemic control compared with usual care in ethnic minority groups, mostly in Western countries [16]. These trials compared adapted education with usual care rather than with generic programmes, so they do not show that adapted programmes outperform generic ones.

Medication Adherence

In all three spheres, medication non-adherence is associated with poorer glycaemic control [17,49]. Piragine et al. pooled 156 studies published in 2011–2022 and found that 54% (95% CI 51–58%) of patients were adherent to oral antidiabetic drugs, and that good adherence was associated with good glycaemic control (OR 1.33; 95% CI 1.17–1.51); adherence was measured with administrative data, self-report questionnaires or pill counts, and region-specific pooled estimates were not reported [17]. Complexity of regimens, side effects, cost (especially in the USA) and health literacy are linked to non-adherence [10,49]. Long-term UKPDS follow-up showed a legacy effect of early intensive glucose control, including metformin, on microvascular and cardiovascular outcomes [60].

In the wider MENA subgroup, 57.3% of 405 patients in Palestine were adherent on the MMAS-8 [49], and in Egyptian primary care 30.5% showed high and 51.3% medium adherence [50]. No included primary study from a GCC member state reported medication adherence. A specific set of clinical guidelines addresses the difficulties of taking medication during Ramadan, including rescheduling of insulin and the risk of hypoglycaemia with sulfonylureas. The IDF and Diabetes and Ramadan (DAR) International Alliance practical guidelines provide risk stratification and medication-adjustment advice [48,54].

No included primary study from Asia measured medication adherence directly. In Bangladesh and Vietnam, diabetes distress—including regimen-related distress—was common (52.5% of 259 and 29.4% of 517 patients with moderate-to-high distress, respectively) [61,62]. In low- and middle-income settings, cost of and access to medicines are recurrent barriers to self-management [12].

Dietary Self-Care

Dietary modification is a foundational pillar of diabetes self-management, yet it is shaped by cultural food norms, making generalisation across regions difficult [16,45]. In Western countries, evidence-based dietary guidance—including the Mediterranean diet, low-glycaemic-index approaches and structured meal planning—is reflected in guidelines [3,45]. In a meta-analysis of 14 trials (356 participants), low-glycaemic-index diets reduced HbA1c by 0.43 percentage points more than high-glycaemic-index diets [42]. National dietary guidelines in the UK (NICE NG28), USA (ADA Standards) and major European nations provide standardised nutrition recommendations integrated into DSME programmes [3,56].

In GCC countries, contextual sources describe how dietary self-care is challenged by the nutritional transition from traditional diets to energy-dense, processed food environments [11]. Ramadan—a 29–30-day period of dawn-to-sunset fasting with altered meal timing and often large caloric intake at Iftar—requires specific dietary and pharmacological management [48,54]. Current guidance for Muslim patients recommends, balanced Suhoor meals, portion control at Iftar, and avoiding calorie-dense desserts [48,54].

High-carbohydrate staple diets are commonly described as a challenge to dietary self-care in Asian settings, although no included study quantified this directly. In Chinese adults with impaired glucose tolerance—that is, before the onset of diabetes—the Da Qing study reported 6-year reductions in diabetes incidence of 31%, 46% and 42% in the diet, exercise and combined arms, respectively [63]; this is prevention evidence and only indirectly relevant to self-care in established diabetes. Culturally tailored education, often including dietary components, improved short-term glycaemic outcomes compared with usual care [16]; direct comparisons with generic dietary advice are lacking.

Physical Activity

In people with diabetes, regular exercise lowers insulin resistance, improves glycaemic management and lowers cardiovascular risk [9]. The ADA recommends at least 150 minutes of moderate-to-vigorous aerobic activity per week plus resistance training on two or more days a week [9]. Many adults with type 2 diabetes do not meet these recommendations [9].

In GCC countries, high summer temperatures, car-dependent urban design, sedentary occupations and, for some women, limited access to public exercise spaces are described as barriers to physical activity [11]; no included study from a GCC member state measured physical activity or evaluated an exercise programme.

In Asia, physical activity patterns are heterogeneous. Traditional practices such as Tai Chi, yoga and walking are culturally embedded in many Asian communities and represent accessible, low-cost options. However, rapid urbanisation has reduced incidental physical activity, and access to safe recreational environments differs between high-income East Asian cities and lower-income South/Southeast Asian settings. In a 16-week controlled trial in China (49 adults aged 60–69 years with type 2 diabetes, compared with non-exercising controls), supervised aerobic exercise at the intensity of maximal fat oxidation improved glycaemic control, body composition and physical capacity [64].

Foot Care Practices

Diabetic foot disease—neuropathic and ischaemic ulcers, infection and amputation—is among the most serious and costly complications of diabetes [47]. The IWGDF guidance recommends daily foot inspection, appropriate footwear, prompt wound management and regular professional foot examination [47]; it notes, however, that trial evidence for patient education alone in preventing ulcers is limited [47].

In Western countries, integrated podiatry services, annual foot screening in primary care and multidisciplinary foot-care teams are standard [47,56]. In UKPDS, intensive glucose control and tight blood-pressure control reduced microvascular endpoints [4,5]. In an observational meta-analysis, glycaemic control was examined in relation to diabetic foot ulcer outcomes [43].

No included primary study from a GCC member state measured foot-care practice. A recent narrative review published after our search cut-off reports that most GCC patients had inadequate foot-care knowledge [11]. In the wider MENA subgroup, 75.2% of 230 older adults with type 2 diabetes in Egypt had unsatisfactory foot self-care practice [55].

In Asian settings, foot-care awareness has been reported to be low in rural populations and among patients with low health literacy [12]. Walking barefoot in parts of South and Southeast Asia, poorly fitted footwear and agricultural foot injuries are commonly cited as additional contextual risks. Community-based foot-care education and low-cost monofilament neuropathy screening have been implemented in resource-limited settings.

Digital Health and mHealth in Diabetes Self-Care

The role of digital technologies in supporting diabetes self-care has grown markedly over the past decade, accelerated by the COVID-19 pandemic [13–15,18]. Table 3 summarises the principal self-care interventions, separating evidence of efficacy (what the intervention achieves in trials) from evidence of regional implementation and adoption (where and how it is used).

In Western countries, CGM is now part of standard care for type 1 diabetes and increasingly for insulin-treated type 2 diabetes [3]; in the DIAMOND trial, CGM reduced HbA1c more than usual care in adults with type 1 diabetes using injections [65]. In a meta-analysis of 42 RCTs, telemedicine produced a modest additional HbA1c reduction compared with usual care [18]. In a US cohort of 27,207 adults with diabetes, practices using electronic health records achieved higher composite standards of care and outcomes than paper-based practices [53].

Government-backed digital health platforms, such as Saudi Arabia's Seha and the United Arab Emirates' NABIDH, have expanded digital health infrastructure in GCC nations; their effect on self-care was not evaluated in any included study. A meta-analysis of mobile-phone interventions reported a pooled HbA1c reduction of about 0.5 percentage points [13], suggesting potential for low-cost, population-level impact; no included trial was conducted in a GCC member state. The COVID-19 pandemic accelerated the use of teleconsultation in settings where preferences for in-person care had previously limited it.

In Asia, China's messaging-based health platforms, South Korea's integrated digital health systems and India's expansion of telemedicine after COVID-19 represent a "leapfrogging" pattern. Hou et al. pooled 14 RCTs (1,360 participants) and found that diabetes apps reduced HbA1c by 0.49 percentage points (95% CI 0.30–0.68; moderate-certainty evidence) [14], and Wang et al. reported generally favourable effects of mHealth interventions on diabetes self-management [15]. In a meta-analysis of 28 RCTs in general adult populations, consumer wearable trackers increased daily steps by approximately 627 [36]; because participants were not restricted to people with diabetes, this evidence is indirect and is cited as context only.

Table 3: Diabetes Self-Care Interventions: Efficacy Evidence Versus Regional Implementation/Adoption Evidence (Restructured)

CGM: Continuous Glucose Monitoring, DSME: Diabetes Self-Management Education, GI: Glycaemic Index, LMICs: Low- And Middle-Income Countries, MA: Meta-Analysis, NMA: Network Meta-Analysis, pp: Percentage Points, RCT: Randomised Controlled Trial, SMBG: Self-Monitoring of Blood Glucose, SR: Systematic Review. Entries without a citation are descriptive implementation context, not derived from included studies and not graded. The previous version of this table combined trial, review, guideline and general statements in one framework and included citations that did not match the reference list (e.g., Norris 2002, Clair 2015, Turner 1998); these have been corrected

Certainty of Evidence

Table 4 presents the certainty of evidence for eleven prespecified outcome–comparison evidence bodies. Certainty was moderate for the effects of DSME, mobile-health support, telemedicine and CGM on HbA1c; low for culturally appropriate education, SMBG, low-glycaemic-index diets and structured exercise; and very low for foot-care education, pre-Ramadan education and all cross-regional differences in self-care practice.

Table 4: Summary of Findings and Certainty of Evidence (GRADE) for Prespecified Outcome–Comparison Evidence Bodies

pp: Percentage Points. GRADE: High: Further Research Very Unlikely to Change Confidence in the Estimate, Moderate: Likely to Have an Important Impact, Low: Very Likely to Have an Important Impact, Very Low: Any Estimate Is Very Uncertain. Regional GRADE labels used in the previous version (e.g., "High" for Western countries) have been withdrawn. Domain-by-domain judgements are given in Supplementary Appendix S5

Cultural, Religious, and Economic Factors of Self-Care

Cultural, religious and economic factors may influence whether recommendations are understood, accepted and enacted. In the included sources, evidence on these factors is mostly cross-sectional or comes from guidance documents; it describes associations and contexts rather than established causal determinants, and each factor varies substantially within regions. Table 5 lists each factor with the basis of its evidence and its within-region variation; the adaptation strategies are suggestions that, unless a reference is given, have not been tested in the included studies.

In the GCC and Muslim-majority Asian countries, fasting during Ramadan poses a clinically significant cultural-religious consideration. Approximately 50 million people with diabetes observe Ramadan annually, although high-risk patients are advised that they are medically exempt [48]. The IDF-DAR risk-stratification framework supports individualised management [54]. Current guidance favours glucose-lowering agents with a low risk of hypoglycaemia and individualised dose adjustment; sodium-glucose cotransporter-2 (SGLT2) inhibitors require attention to hydration because of the risk of volume depletion (and, rarely, ketoacidosis) during fasting, and glucagon-like peptide-1 (GLP-1) receptor agonists are preferably established well before Ramadan because of gastrointestinal adverse effects [54,68]. These are guideline-based recommendations rather than findings of this review. Pre-Ramadan structured education is recommended, supported mainly by observational studies [48,54].

Family members may support medication adherence, dietary change and healthcare engagement, or may reinforce unhealthy habits [10]. Culturally appropriate education programmes, some of which involved family members, improved short-term glycaemic control compared with usual care, mainly among ethnic minority populations in Western countries [16]; whether family involvement itself drives benefit has not been tested in the included studies. Family structures also differ widely within Asia and the GCC—for example, between urban nuclear and extended households, and between national families and expatriate workers living apart from their families.

Economic factors intersect with cultural ones. In lower-income settings, out-of-pocket costs for medicines and monitoring are a recurrent barrier to self-management [12], although their magnitude varies widely between and within countries. Generic medication policies, subsidy programmes and community health worker-delivered education are commonly proposed responses [12]; their effects on self-care were not evaluated in the included studies.

Table 5: Cultural and Religious Factors that May Influence Diabetes Self-Care: Evidence Basis, Within-Region Variation and Suggested Adaptations

DM: Diabetes Mellitus, IDF-DAR: International Diabetes Federation and Diabetes and Ramadan International Alliance, SGLT2i: Sodium-Glucose Cotransporter-2 Inhibitor, GLP-1 RA: Glucagon-Like Peptide-1 Receptor Agonist, CHW: Community Health Worker. Contextual": Background Source not Included in the Synthesis. Suggested adaptations are expert/policy suggestions unless a reference is given

Complication Prevention Strategies: A Cross-Regional Assessment

Preventing the major complications of diabetes—nephropathy, retinopathy, peripheral neuropathy, cardiovascular disease and diabetic foot disease—requires sustained self-care integrated with clinical monitoring. Table 6 summarises guideline-recommended screening intervals, key prevention strategies and reported regional gaps for each major complication domain.

UKPDS remains the landmark evidence for intensive glycaemic control, demonstrating a 25% risk reduction in microvascular endpoints with intensive glucose control [4], further benefit from tight blood-pressure control [5] and a legacy effect at 10-year follow-up [60]. Additional benefits from cholesterol management and, more recently, cardioprotective glucose-lowering medications such as SGLT2 inhibitors and GLP-1 receptor agonists were shown by subsequent trials [68]. Smoking cessation is associated with a lower risk of cardiovascular disease in adults with diabetes, despite post-cessation weight gain [69]. Annual complication screening is recommended by guidelines [3,56] and, in some Western countries, integrated into primary care quality frameworks and pay-for-performance schemes.

Late detection of complications in GCC countries has been described in contextual sources [11]. The nationwide SAUDI-DM household survey documented a substantial burden of diabetes and abnormal glucose metabolism in the Saudi population [58]. National initiatives such as Vision 2030's diabetes component and Saudi Arabia's Healthy Saudi Initiative aim to address this through community screening and primary care capacity-building.

In Asian contexts, the shortage of ophthalmologists, nephrologists and podiatrists relative to the high prevalence of diabetes, especially in South and Southeast Asia, limits complication prevention [12]. Task-shifting approaches, in which trained nurses, pharmacists and community health workers deliver standardised complication screening, are proposed as affordable and scalable options. India's National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases and Stroke (NPCDCS) is a large-scale attempt to integrate complication screening into primary healthcare.

Table 6: Evidence-Based Complication Prevention Strategies and Regional Implementation Gaps

Egfr: Estimated Glomerular Filtration Rate; ACR: Albumin-To-Creatinine Ratio; CGM: Continuous Glucose Monitoring; PDR: Proliferative Diabetic Retinopathy; RAAS: Renin-Angiotensin-Aldosterone System; BP: Blood Pressure. Screening intervals based on ADA [3], and NICE NG28 [56]. Regional gaps without a citation are descriptive context, not derived from included studies and not graded

Swot Analysis: Regional Self-Care Landscapes

The SWOT analysis in Table 7 is an interpretive, author-generated summary intended to structure policy discussion. It is not graded evidence, and each entry generalises across countries that differ substantially; it should be read alongside the within-region heterogeneity described in Section 8.2.

Table 7: SWOT Analysis of Diabetes Self-Care Systems: Asia, GCC, and Western Countries (Interpretive: Not Graded Evidence)

DSME: Diabetes Self-Management Education, CGM: Continuous Glucose Monitoring, NCD: non-communicable disease. Author-generated interpretive summary, entries are not graded evidence and do not apply uniformly to all countries in a sphere

Principal Findings

This systematic review included 38 sources on diabetes self-care in Asia, the GCC/wider MENA and Western countries. Interventions with moderate-certainty evidence of benefit on glycaemic control—structured DSME, mobile-health support and telemedicine—were tested mainly in Western or multi-regional trials. Evidence on regional practice and implementation came largely from cross-sectional studies using different instruments, and only two included primary studies came from GCC member states. Across the evidence base, the dominant pattern is heterogeneity: self-care practices, adherence and diabetes distress varied as much within spheres as between them.

Heterogeneity Within Regions

Each sphere is internally diverse. Asia spans high-income East Asian health systems with universal insurance and lower-income South and Southeast Asian settings with high out-of-pocket spending and large urban–rural gaps [12]; the included Asian studies (China, Republic of Korea, Vietnam, Bangladesh) cannot represent the continent as a whole. Within the GCC, national health systems, financing arrangements and the size of expatriate populations—who may have different entitlements, languages and living arrangements from nationals—differ between member states, and the wider MENA countries (Egypt, Palestine, Iran) differ again in income and health-system organisation. Western countries range from universal tax-funded systems to the insurance-based system of the USA, with persistent socioeconomic and ethnic-minority gaps [16]. Region-level labels therefore mask important variation, and the findings of this review should be interpreted at the level of countries and settings rather than continents.

Direct Versus Indirect Comparisons

Only one included study, the DAWN study, measured psychosocial barriers to self-care in several spheres (13 countries in Asia, Europe, North America and Australia) with a common method [10]. All other cross-regional contrasts in this review are indirect: they compare studies conducted in different populations (clinic attenders, community samples, older adults), with different instruments (e.g., MMAS-8, the Summary of Diabetes Self-Care Activities measure [70], different language versions of the Diabetes Distress Scale), in different years. Apparent differences may therefore reflect measurement and sampling rather than true differences in self-care. Piragine et al. illustrate the point: adherence estimates depended on whether administrative data or self-report were used [17]. For this reason, the previous version's statements that Western countries have the "highest" adherence and the GCC the "lowest" have been removed; the evidence does not support a ranking.

Comparison with Existing Reviews

Our findings are consistent with a recent GCC narrative review, published after our search cut-off, which synthesised 88 articles from 2020–2025 and reported fair but highly variable medication adherence, self-monitoring of blood glucose ranging from 14% to over 90% across studies, and generally inadequate foot-care knowledge [11]. They also agree with Maina et al., who described cost, access and health-literacy barriers to complication-prevention practices in low- and middle-income countries [12]. Unlike these single-region reviews, the present review places the three spheres within one framework and separates efficacy evidence from implementation evidence, which makes explicit how little direct comparative evidence exists.

Recommendations

The following recommendations combine the findings of this review with guideline and expert opinion. Each is labelled E when it is supported by included evidence (with its certainty from Table 4) or P when it is an expert or policy recommendation based on guidelines or author judgement.

• E: DSME, moderate; cultural adaptation, low, P: family-inclusive and Ramadan components. Implement culturally adapted DSME programmes and evaluate them locally, with consideration of family-inclusive models in Asian and GCC settings where appropriate, and integration of Ramadan-specific counselling for Muslim patients. Programmes developed elsewhere should be adapted and evaluated before scale-up [2,8,16]
• E: mHealth Efficacy, Moderate, P: Population scale-up and equity frameworks Scale mHealth interventions, prioritising SMS-based reminders and low-bandwidth applications in resource-constrained settings. Governments in Asia and the GCC should establish digital health equity frameworks so that people without smartphone access or digital literacy are not excluded [13,14,18]
• P: Establish Ramadan diabetes management protocols as a standard component of national diabetes guidelines in the GCC and Muslim-majority Asian nations. Pre-Ramadan diabetes clinics, and structured risk stratification using IDF-DAR criteria should be institutionalised, with medication adjustment according to current guidelines and an individual risk–benefit assessment for any agent used during fasting, including SGLT2 inhibitors and GLP-1 receptor agonists [54,68]
• E: low-GI diets, low, P: materials and food-environment policy, create culturally appropriate nutritional counselling materials in regional languages and dialects that include local staple foods, traditional food systems and familiar meal patterns. Individual-level counselling may be complemented by food-environment policies such as taxes on sugar-sweetened beverages, front-of-pack labelling and public-institution food standards [42,45]
• P: Supporting Evidence Very Low, Address foot care as a priority in Asia and the GCC through training of primary care clinicians in annual foot examination, community foot-care education campaigns, and podiatry workforce development in GCC health systems [47,55]
• P: Implement task-shifting models for complication screening in under-resourced Asian settings, with trained nurses, pharmacists and community health workers delivering standardised retinopathy, nephropathy, neuropathy and foot screening [12]
• P: Research recommendation Commission comparative effectiveness research on self-care interventions across the three spheres. Head-to-head trials evaluating the same DSME model in Western, GCC and Asian settings, and multinational surveys using common, validated self-care and adherence instruments, would substantially advance the evidence base [7,10]
• P Invest in anti-stigma campaigns to address diabetes-related social stigma, which may discourage diagnosis disclosure, care-seeking and medication adherence in all three regions

LIMITATIONS

This review has several limitations. (1) No registered protocol: the review was not prospectively registered, so post hoc methodological decisions cannot be excluded. (2) Language and databases: only English-language publications and three databases were searched; Embase, CINAHL and regional databases (e.g., the Index Medicus for the Eastern Mediterranean Region, CNKI, the Western Pacific Region Index Medicus) were not, which may under-represent Arabic- and Asian-language evidence. (3) Search structure: requiring complication/outcome or digital-health terms may have reduced sensitivity for relevant self-care studies, only partly mitigated by hand-searching. (4) Currency: the search was not updated after 1 September 2024, so more recent studies, including GCC studies summarised in a 2025 review [11], were not included. (5) Heterogeneous designs and populations: included sources differed in design, setting, population and period. (6) Secondary evidence: inclusion of systematic reviews and guidelines alongside primary studies risks double-counting; we mitigated this with separate evidence streams and overlap checks. (7) Indirect comparisons: almost all cross-regional comparisons were indirect. (8) Publication bias could not be assessed formally. (9) No quantitative pooling was possible, and the narrative synthesis involves judgement. (10) Variable definitions of self-care: instruments and cut-offs for adherence, self-management and distress varied. (11) Reviewer bias and incomplete process records: selection, extraction and appraisal involved judgement; screening was performed in duplicate, but inter-reviewer agreement was not quantified, the numbers of records excluded at the title/abstract and initial full-text stages were not retained, and methodological appraisal and GRADE ratings were completed at the revision stage rather than prospectively. (12) Sparse GCC evidence: only two included primary studies were from GCC member states, and some descriptions of regional health systems rely on contextual sources that were not graded.

This systematic review found that diabetes self-care awareness, practice and complication-prevention activity vary considerably both between and within Asia, the GCC/wider MENA and Western countries. Structured DSME and mobile-health support improve glycaemic control in trials (moderate-certainty evidence), but these trials were conducted mainly in Western or multi-regional settings, and their effects in GCC and many Asian settings remain uncertain. Because almost all cross-regional contrasts were indirect—drawn from studies with different populations, instruments and periods—this review does not establish a ranking of regions or health systems. The evidence instead points to heterogeneity and context-specific considerations, including Ramadan fasting, cost and access barriers, health-system organisation, and family and gender dynamics, each of which varies within regions.

Context-adapted self-care programmes should be evaluated locally with standardised outcome measures, and multinational studies using common validated instruments are needed to allow direct comparison. Strengthening primary research in GCC member states is a particular priority.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability

No original datasets were generated for this review. All data sources are cited in the reference list, and the extracted data are provided in Supplementary Appendices S4–S6.

Supplementary Material

Supplementary Appendices S1–S9 (database-specific search strategies; grey-literature search log; country-level geographic classification; characteristics and appraisal of included sources and list of contextual references; GRADE evidence profile; sources of numerical estimates; reference audit log; PRISMA 2020 checklist; list of sources excluded at the eligibility re-audit) are provided in a separate file.

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Supplementary Material

Diabetes Self-Care in Asia, the Gulf Cooperation Council and Western Countries: A Systematic Review with Narrative Synthesis

Manuscript JPMS332246 — Supplementary Appendices submitted in response to reviewer comments

Contents

• Database-specific search strategies
• Grey-literature search log
• Country-level classification of geographic spheres
• Characteristics and methodological appraisal of included sources (Part A) and contextual references (Part B)
• GRADE evidence profile: domain-by-domain judgements
• Sources of numerical estimates in Table 2 and values removed
• Reference audit log
• PRISMA 2020 checklist
• Sources excluded at the eligibility re-audit, with reasons

Appendix S1. Database-specific search strategies

The syntax below implements, for each database, the four concept blocks reported in Section 2.3 of the manuscript. All three databases were searched on 1 September 2024 for records published from 1 January 2000 to the search date. Limits: English language; humans (PubMed); article and review document types (Scopus, Web of Science). The search was not updated after 1 September 2024. The four concept blocks are those reported in Section 2.3 of the manuscript.

S1: 1 PubMed/MEDLINE (Interface: pubmed.ncbi.nlm.nih.gov)

S1: 2 Scopus (Interface: Scopus.Com, Advanced Search)

S1: 3 Web of Science Core Collection (Interface: webofscience.com; All Editions)

Total records retrieved from the three databases: 5,305 (before de-duplication)

Appendix S2: Grey-Literature Search Log

Eligibility of guidelines and reports: issued by a national or international organisation; describes its evidence base or development method; reports recommendations or data on self-care, education or complication prevention in adults with diabetes; published January 2000–September 2024; English language

Appendix S3: Country-level Classification of Geographic Spheres

Central Asian states (e.g., Kazakhstan, Uzbekistan) and Israel: no eligible sources were identified; had any been found, they would have been reported separately as transcontinental/other

Appendix S4: Characteristics and Methodological Appraisal of Sources

DFU = diabetic foot ulcer; EHR = electronic health record; GI = glycaemic index; LMICs = low- and middle-income countries; MA = meta-analysis; pp = percentage points; SR = systematic review. Part A. Included sources (n = 38). Stream A = primary study; B = systematic review/meta-analysis/scoping review; C = guideline/consensus statement. Appraisal tools: RoB 2 (randomised trials); JBI checklists (cohort, cross-sectional, validation studies); AMSTAR 2 overall confidence (systematic reviews; scoping review appraised for reporting only); AGREE II overall (guidelines). Appraisal was completed at the revision stage

Part B: Contextual references (n = 14) and references added at revision (n = 18). These are cited for background or methods only. They are not included sources and did not contribute to the tables of findings or certainty ratings.

Appendix S5: GRADE Evidence Profile: Domain-By-Domain Judgements

Ratings follow GRADE [28] and, where no single pooled estimate was available, Murad et al. [29]. "0" = not serious; "−1" = serious; "−2" = very serious

Appendix S6: Sources of Numerical Estimates in Table 2 and Values Removed

Other numerical statements corrected in the text: Norris DSME effect (0.74% → 0.76 pp, 95% CI 0.34–1.18, attributed to Norris 2002 [8]); mHealth pooled effect (0.49 pp attributed to Hou 2016 [14], not Wang 2017); wearable trackers (1,200 steps/24 RCTs → ≈627 steps/28 RCTs [36], general population); Da Qing (33% → 31%, 46% and 42% by arm [63]); UKPDS (25% microvascular risk reduction with intensive therapy [4], not "per 1% HbA1c"). Unverifiable figures were removed: Hong Kong adherence 64.3%; WHO STEPwise inactivity >70%; household medication spending 20–30%; SAUDI-DM comorbidity 39.8%.

Appendix S7: Reference Audit Log

All references have been renumbered consecutively in order of first citation in the revised manuscript (1–70). Bracketed numbers in this log refer to the renumbered reference list