Next Article in Journal
Long-Term Exposure to PM2.5, Facemask Mandates, Stay Home Orders and COVID-19 Incidence in the United States
Next Article in Special Issue
Prediction of Cardiorespiratory Fitness in Czech Adults: Normative Values and Association with Cardiometabolic Health
Previous Article in Journal
Analyzing Twitter Data to Evaluate People’s Attitudes towards Public Health Policies and Events in the Era of COVID-19
Previous Article in Special Issue
Classroom Movement Breaks Reduce Sedentary Behavior and Increase Concentration, Alertness and Enjoyment during University Classes: A Mixed-Methods Feasibility Study
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 18
Issue 12
10.3390/ijerph18126273
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Lifestyle Interventions to Improve Glycemic Control in Adults with Type 2 Diabetes Living in Low-and-Middle Income Countries: A Systematic Review and Meta-Analysis of Randomized Controlled Trials (RCTs)

by
Grainne O’Donoghue
1,*,
Cliona O’Sullivan
1,
Isabelle Corridan
1,
Jennifer Daly
1,
Ronan Finn
1,
Kathryn Melvin
1 and
Casey Peiris
2
1
School of Public Health, Physiotherapy and Sports Science, University College Dublin, D04 V1W8 Dublin, Ireland
2
School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, VIC 3086, Australia
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(12), 6273; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18126273
Submission received: 1 April 2021 / Revised: 31 May 2021 / Accepted: 4 June 2021 / Published: 10 June 2021
(This article belongs to the Special Issue Assessment and Management of Lifestyle-Related Risk Factors for the Prevention and Management of Non-communicable Disease in Primary and Community Care)
Browse Figures
Review Reports Versions Notes

Abstract

:
Alongside glucose lowering therapy, clinical guidelines recommend lifestyle interventions as cornerstone in the care of people living with type 2 diabetes (T2DM). There is a specific need for an up-to-date review assessing the effectiveness of lifestyle interventions for people with T2DM living in low-and-middle income countries (MICs). Four electronic databases were searched for RCTs published between 1990 and 2020. T2DM, lifestyle interventions, LMICs and their synonyms were used as search terms. Data codebooks were developed and data were extracted. Narrative synthesis and meta-analysis were conducted using random effects models to calculate mean differences (MD) and standardized mean differences (SMD) and 95% confidence intervals (CI). Of 1284 articles identified, 30 RCTs (n = 16,670 participants) met the inclusion criteria. Pooled analysis revealed significant improvement in HBA1c (MD −0.63; CI: −0.86, −0.40), FBG (SMD −0.35; CI: −0.54, −0.16) and BMI (MD −0.5; CI: −0.8, −0.2). In terms of intervention characteristics, those that included promoted self-management using multiple education components (e.g., diet, physical activity, medication adherence, smoking cessation) and were delivered by healthcare professionals in a hospital/clinic setting were deemed most effective. However, when interpreting these results, it is important to consider that most included studies were evaluated as being of low quality and there was a significant amount of intervention characteristics heterogeneity. There is a need for further well-designed studies to inform the evidence base on which lifestyle interventions are most effective for glycemic control in adults with T2DM living in LMICs.

1. Introduction

Between 1980 and 2014, the global prevalence of diabetes nearly doubled from 4.7% to 8.5%, with most new cases in low-and-middle income countries (LMIC) [1]. South-East Asia has an estimated 96 million people living with diabetes (90% T2DM), a significantly higher prevalence than within the World Health Organization’s (WHO) European (n = 60 million) or American (n = 47 million) regions [2,3]. Furthermore, the WHO 2016 Global Report stated that, since 2012, the lower socioeconomic class of middle-income countries (MIC) had the highest mortality attributed to hyperglycemia and T2DM, which is detrimental to population health in LMICs [4]. It has significant economic consequences, threatening to reverse economic gains in developing countries, which will further limit resources, making them even less equipped to manage this diabetes epidemic [5].
In addition to glucose-lowering therapies, lifestyle management, including nutritional education, physical activity (PA), weight loss and self-efficacy education is recommended as a cornerstone in the care of a patient living with T2DM [6]. Healthcare and community-based lifestyle interventions have been shown to be both clinically and cost-effective ways of curbing the growth of diabetes [7]. A substantial number of systematic reviews that mainly include studies conducted in high income countries provide considerable evidence supporting lifestyle interventions as cost and clinically effective in the prevention [8,9] and management of T2DM by reducing body weight and improving glucose control [10,11,12].
There are a number of reviews exploring the evidence for the prevention [9,13] and lifestyle management [11,12,13] of T2DM in LMICs. Previous reviews of management interventions have focused on specific regions or continent sub-regions, such the Asian Western Pacific (AWP) [11] region and Southeast Asia [12], a specific type of intervention, for example, diabetes self-management education [11] or specific site of delivery [13]. A review published in 2016 [14] that included literature up until 2014 for both prevention and management trials in LMICs concluded that there was a lack of large experimental trials exploring diabetes control. Moreover, the quality of the documented studies was poor and, due to the heterogeneity in the reported interventions, the authors were not able to pool findings; hence, reported results are only based on descriptive data.
Therefore, the aim of this review was to synthesize the most up-to-date evidence in relation to lifestyle interventions that target glycemic control in adults with T2DM living in LMICs. Our specific objectives were:
  • To explore core components of lifestyle interventions, specifically in relation to strategies and intervention characteristics for the management of T2DM (method, context of delivery, by whom, with what intensity and for how long).
  • To complete a quality assessment on included randomized control trials (RCTs).
  • To conduct a meta-analysis to establish the effectiveness of these interventions on improving glycemic control and anthropometry.
  • To compile recommendations for future research on this topic.

2. Materials and Methods

2.1. Registration

This review was registered prospectively on the International prospective register of systematic reviews (PROSPERO 2020: CRD42020151938) and conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. [15].

2.2. Search Strategy

Four electronic databases (PubMed, CINAHL, Embase and CENTRAL) were searched. The search strategy was constructed around the PICOS tool: (P) Population: adults living in LMIC with type 2 diabetes; (I) Intervention: any intervention specifically targeting lifestyle behaviors; (C) Comparator: usual care, wait-list control, placebo; (O) Outcomes: glycemic control; and (S) Study Type: randomized controlled trials (RCTs). A complete list of the search terms is available in Table S1. In addition to the databases, the reference lists of included articles were scanned for additional studies that met the inclusion criteria.

2.3. Inclusion Criteria

RCTs published in English and conducted in LMICs between January 1990 and October 2020 were included. Adults were defined as ≥18 years. T2DM was defined using one or more of the following criteria: fasting blood glucose (FBG) of ≥126 mg/dL (7.0 mmol/L) and/or 2-h FBG ≥ 200 mg/dL (11.1 mmol/L) and/or glycosylated hemoglobin (HbA1c) ≥ 6.5% [16]. LMICs were classified using the World Bank Classifications from 2019 [17]. A lifestyle intervention was any intervention that included a focus on increasing physical activity and/or changing dietary habits.

2.4. Outcome Measures

The primary outcome was change in glycemic control, as measured by glycated hemoglobin (HBA1c). Secondary outcomes were fasting blood glucose (FBG), other measures of metabolic risk (high density lipoproteins (HDL), low density lipoproteins (LDL), systolic and diastolic blood pressure (SBP and DBP), triglycerides (TG)), anthropometry (body weight, body mass index (BMI), waist circumference and percentage body fat) and quality of life.

2.5. Selection Process

All studies were imported into EndNote (Version 9X) and de-duplicated. Two authors independently screened titles, and subsequently abstracts, for potential inclusion (RF, IC). Following a review for accuracy, full texts were retrieved and independently assessed for inclusion in the review (JD, KM). Any disagreement over the eligibility was resolved through discussion with an additional reviewer (GO’D).

2.6. Data Extraction

Microsoft excel was used to develop a comprehensive codebook for data extraction. The following information was recorded: study details, participant demographics, intervention components (coded according to the Template for Intervention Description and Replication Checklist (TIDieR), comparator information, primary and secondary outcomes at baseline and follow-up and quality assessment material. The same authors involved in the screening process extracted data into the codebook.

2.7. Quality Assessment

To assess the risk of bias, the Effective Public Health Practice Project quality assessment tool was used [18]. All articles were assessed by two independent reviewers (RF and IC) and discrepancies were resolved with an additional reviewer (CO’S).

2.8. Data Synthesis

Firstly, the included trials were qualitatively described. The narrative synthesis included sample demographics, primary and secondary outcomes, intervention components and research quality. Quantitatively, meta-analyses were conducted in RevMan (version 5) for the primary outcome (HBA1c) and secondary outcomes of interest (FBG, BMI). Post-intervention means and standard deviations were pooled using random-effects models and inverse variance methods to calculate mean differences (MD), where outcomes were homogenous, or standardized mean differences (SMD) where outcomes were reported in different units and at 95% confidence intervals (CI). Where outcomes were measured at multiple timepoints, the post-intervention data were chosen to be pooled a priori as not all trials had follow-up measurements. For the primary outcome of HbA1c, measurements were only pooled if they were taken at least 12 weeks after baseline testing, as HbA1c is a measure of long-term glycaemic control over 2 to 3 months. Statistical heterogeneity was assessed using the I2 statistic, where I2 values >50% were considered to represent substantial heterogeneity [19]. Sub-group analyses were conducted to explore whether intervention type, delivery or setting, were observed to impact results. Intervention type was defined as either self-management education, consisting of a multifactorial program that focused on providing education around multiple risk factors associated with T2DM, or a structured nutrition/exercise intervention, where the focus was on prescribed or supervised individualized programming. Intervention delivery was categorized as being delivered by a healthcare Professional (HCP) or healthcare multidisciplinary team, or as being delivered by peers. Additionally, setting was based on whether the intervention was delivered in a hospital, community or home environment.

2.9. Assessment of Publication Bias

Where we included at least 10 studies in a meta-analysis, we generated funnel plots of effect estimates against their standard errors (on a reversed scale) using RevMan software. We assessed the potential risk of publication bias through visual analysis of the funnel plots. Roughly symmetrical funnel plots indicated a low risk of publication bias and asymmetrical plots a high risk. As this is a subjective judgement and asymmetry might also arise from other sources, we further attempted to avoid publication bias by not including multiple publications referring to the same data.

2.10. Grading of the Quality of Evidence

To evaluate the quality of the evidence in the subgroup analysis, the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach was used. As all included trials were randomized controlled trials, the quality rating starts at “high”. All studies were allocated five points initially and were downgraded by one point, respectively, if there was evidence of: 1. risk of bias (40% or more of the trials had a global rating of week on the EPHPP tool); 2. unexplained heterogeneity (I2 > 50%); 3. indirectness in outcomes or population; 4. imprecision in results (wide 95% CI >  0.8) for SMD; or 5. publication bias (visual inspection of funnel plots when there were at least 10 trials in the meta-analysis). The quality of these data was then graded as follows: 1 = very low; 2 = low; 3 = medium; and 4 or 5 = high.

3. Results

3.1. Literature Selection

A total of 1284 articles were initially identified. Following review by title and abstract, 75 studies progressed to full manuscript review. Of these, 45 were excluded as they did not fulfill the inclusion criteria. The remaining 30 trials were included in this review. All 30 contributed to the qualitative analysis and 25 contributed to the quantitative analysis. The detailed process is illustrated in Figure 1.

3.2. Study Characteristics

Eighteen trials were conducted in upper middle-income countries [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38], nine in lower middle-income countries [39,40,41,42,43,44,45,46,47] and two in low-income countries [48,49]. The total sample size was 16,670, with individual study participants ranging from 41 [49] to 8120 [40], with 11 of the 30 studies included having a sample size greater than 200. Mean age of participants was 55.4 (SD = 5.6) years and 58% were female (n = 9521). Diabetes duration ranged from 2.3 to 11 years, but was only reported in 12 studies, and diabetes medication was only reported in six studies. Study duration ranged from four weeks [28] to 348 weeks [35], with more than a third of studies exceeding a one-year duration. The most commonly investigated outcome measures were HBA1c (n = 20 studies), FBG (n = 13) and BMI (n = 13). Table 1 provides a detailed account of all study characteristics.

3.3. Lifestyle Intervention Characteristics

Of the 30 included trials, 24 of the interventions were described as diabetes self-management education programs [20,21,22,23,25,26,27,29,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,48], where the focus was on disease management skills including decision making, problem solving, and action planning. These programs were multifactorial in terms of their content. The majority included education relating to physical activity and diet (n = 19) and medication advice (n = 18). Other content covered was foot and skin care (n = 12), glucose monitoring (n = 14), smoking cessation (n = 7), stress control (n = 2) and blood pressure monitoring (n = 1). Of the remaining six trials, three investigated the effectiveness of nutrition/diet interventions [28,30,31], two prescribed exercise programs [47,49] and one was a combined diet and exercise program [24].
In 16 trials, the intervention was delivered by healthcare professionals [21,22,23,24,28,30,32,33,35,37,39,42,44,45,46,47]. Trained educators delivered five programs [23,36,41,43,48] and peer leaders or lay facilitators delivered three [26,38,40]. In one trial, the intervention was delivered by the researchers [25] and, in another, it was delivered online [31]. Five trials did not provide information relating to intervention delivery [20,27,29,34,49].
In terms of where the interventions were delivered, eighteen took place in either a hospital or healthcare setting [20,21,27,29,30,31,32,33,34,35,37,39,41,44,45,46,47,48] but did not differentiate between hospital and clinic settings. Five interventions were conducted in community health centers [24,26,36,38,40], three took place at home [22,40,43], two were reported as being in any location where technology was accessible [25,31] and the remaining two did not report a location for intervention delivery [23,49]. Table S2 provides a complete overview of the interventions and all their characteristics.

3.4. Effects of Lifestyle Interventions on Clinical Outcome Measures

A meta-analysis was conducted on three clinical outcomes—HbA1c, FBG and BMI, as illustrated in Figure 2. Twenty of the 30 included trials provided post-intervention data on HbA1c and data from 19 trials were included in the meta-analysis. One trial was excluded as it measured HbA1c at day 30.
Compared to the control group, in 19 trials with 5428 participants, intervention group participants reduced their HbA1c by 0.63% (95% CI, −0.86 to −0.40). Thirteen trials (n = 3306) were included in the meta-analysis exploring FBG, with results revealing a small reduction in FBG in the intervention group compared to control group (−0.35; 95% CI, −0.54 to −0.16). Finally, when compared to control group participants, intervention group participants reduced their BMI by 0.5 kg/m2 (95% CI −0.8 to −0.2) in 13 trials with 3461 participants. Details of all the other clinical outcomes reported in the studies can be found in Table S3.
A subgroup analysis provided data relating to the effectiveness of the intervention type and its delivery. The self-management education programs that included multi-components demonstrated moderate to large effects on HbA1c, FBG and BMI, while interventions that focused specifically on structured diet/exercise or a combination of both demonstrated no effect or small effects (Table 2). Programs delivered by healthcare professionals demonstrated larger effects on HbA1c and FBG than those that were peer-led. Additionally, in terms of settings, interventions delivered in healthcare or/hospital settings appeared to be more effective at improving glycemic control than those delivered in the community or at home.

3.5. Risk of Bias Assessment

Twelve trials were rated as “weak”, 14 as “moderate,” and four as “strong” on the Effective Public Health Practice Project quality assessment tool. No trial was categorized as strong in all six components. Selection bias was apparent in most studies. Most authors did not report the rationale behind their participant selection. The randomization procedure was described adequately in 20 trials, with the remaining 10 using the word “random”; however, these trials did not describe a randomization process [21,22,23,31,37,44,45,46,48,49]. A major source of bias identified across all trials was blinding. Apart from three trials [30,36,39], it was not stated clearly whether the trial participants were aware of the research question. Data collection was recorded as strong, apart from in four studies; three were classified as weak [22] and one was classified as moderate [31,36,39]. Studies provided a range of detail on participant attrition, with only one providing complete numbers [21] and others not reporting drop-out rates at all [30,36,39]. Further details relating to trial quality are provided in Table S4.

3.6. Publication Bias

As we included ≥10 studies in the meta-analysis of HbA1c, FBG and BMI, we generated funnel plots. The funnel plots were nearly symmetrical and every meta-analysis exhibited negative and positive results, which meant that there is little possibility of publication bias in this study. See Figure S1 for detailed information.

3.7. Strength of the Evidence

There was high quality evidence that lifestyle intervention, using self-management education, resulted in a significant decrease in HbA1c and BMI, with moderate quality evidence for its effectiveness in decreasing FBG. The quality of the evidence in relation to the different subgroups was varied, but mostly deemed to be of moderate or low quality, with 50% (9/18 subgroups) categorized as low or very low. Most subgroups were downgraded due to a high risk of bias in most of the included trials, high heterogeneity between trials and imprecision of results. Table S6 provides details.

4. Discussion

This systematic review analyzed the evidence from 30 RCTs with 16,670 participants, to assess the effect of lifestyle interventions on the management of T2DM in LMICs. Overall, the results are positive, showing these interventions can improve key clinical markers in T2DM, including HbA1c, FBG and BMI. The primary outcome in this review was improvement in glycemic control (HbA1c) and a meta-analysis including 19 trials found a significant reduction in HbA1c (−0.63%; 95%CI, −0.86 to −0.40). Our subgroup analyses further explored core characteristics of included lifestyle interventions. Findings suggest: (1) self-management education programs may be more effective than lifestyle modification that focused specifically on diet and exercise, (2) interventions delivered by healthcare professionals (HCPs) resulted in better outcomes than those delivered by peers or lay educators, and (3) interventions delivered in the clinical environment were superior to those delivered in the community or home settings.
The reduction in HbA1 found in this study is clinically significant [50] and has been shown to have a positive effect on both morbidity and mortality. A systematic review of trials that decreased HbA1c by at least 0.5% found that they were associated with a significant reduction in incident cardiovascular events and myocardial infarction, commonly recognized complications of T2DM [51]. Furthermore, a recent update on the cost effectiveness of interventions to manage T2DM categorized diabetes self-management programs as very cost effective [52], suggesting they are a very worthwhile component of a multipronged approach in the management of T2DM.
With reference to previous research, our findings are both confirming and conflicting. From the perspective of program types, we found that participants in self-management education programs had better clinical outcomes than those availed by an intervention that focused solely on diet and/or exercise. This is contrary to the findings reported by Huang et al. [10], where physical activity and diet modifications yielded a greater reduction in HbA1c and BMI than education programs. Interestingly, though, while we found self-management education programs clinically effective in reducing HbA1 (−8.1% HbA1c), our improvements following diet/exercise modification (−0.3% HbA1c) cannot be classified as clinically effective (minimum change of −0.5% HbA1c) [50] and were less than those reported by Huang et al. (−0.30mmol).
Although the interventions in both our review and that of Huang et al. were categorized as self-management education or exercise/diet modification, there was still significant heterogeneity between programs. For example, Huang et al. only classified a program as an exercise intervention if it was individualized and strictly supervised. Indeed, supervised exercise programs may be superior to unsupervised exercise for glycemic control and weight loss in people with T2DM [53]. Furthermore, they reported exercise and diet as two separate programs. In this current review, we classified an intervention as an exercise intervention if its primary focus was on physical activity or exercise and we did not stipulate supervision or individual programming as inclusion criteria. We also combined exercise and/or diet interventions to conduct the analysis.
A number of other reviews have been published that confirm our findings, illustrating that, irrespective of type, interventions focused on lifestyle change, are effective for the management of T2DM [11,12,54]. When compared to a control group, these reviews, exploring self-management education [11] in the Asian Western Pacific region, diet/exercise modification [12] in a Southeast Asian population and a combination of both (primarily in high-income countries) [54], reported a significant reduction in HbA1c and BMI from the baseline in the lifestyle intervention groups. Specifically with regard to LMICs, a very recent review exploring health system interventions for adults with T2DM with similar cohort selection criteria to ours found diabetes multicomponent self-management education interventions to be successful at improving glycemic control [55].
In clinical practice, intervention setting and by whom the intervention is delivered have been shown to be important influencers of outcomes due to their potential to influence uptake and attrition [56,57]. Our sub-group meta-analyses was designed to explicitly explore the effect of these factors which, to the best of our knowledge, has not previously been conducted in reviews of T2DM lifestyle management in LMICs. Our findings showed that programs delivered by HCPs in a clinical environment were more effective in reducing HbA1c than those delivered by peer educators at home or in a community setting. Previous reviews have reported on the differences between interventions that are delivered by one healthcare professional versus a multidisciplinary team [11,55], showing a team approach to be more effective. A very recent review exploring the effectiveness of peer- and community health worker-led self-management education programs in LMICs showed inconsistent improvements in clinical, behavior and psychological outcomes [58]. Ideally, based on the findings of our current review alongside those previously reported, T2DM lifestyle interventions, be they self-management education or active lifestyle modification using diet and exercise, would be led by HCPs and delivered in a clinical setting.
However, this is perhaps an unrealistic goal, as most LMICs do not have the extensive health systems of high-income countries nor the number of HCPs working in the field of chronic disease management [59]. An alternative may be the use of healthcare–community partnerships. This approach differs from a peer-led process as it ensures the patient has the opportunity to interact with an HCP for initial education/goal setting and again at a number of agreed time points over the intervention duration. In between, patients return to their local communities, where a support mechanism using peer led educators is in place to facilitate and sustain healthy behaviors [60]. This may be a viable option as, while it still includes HCP input, it is less demanding on healthcare personnel and has the potential to reach a much larger number of patients. It has been used successfully in HICs but further research into its feasibility and efficacy in LMICs is required.
This study has several strengths and weaknesses. The review was systematic and exhaustive. A considerable sample size of adults living with T2DM (n = 16,670) was included, thus providing us with the power to detect statistically significant mean differences in glycemic control. Only RCTs, the gold standard for evaluating the effectiveness of an intervention, were included. Our review shares a number of limitations with the studies on which it is based. Although we attempted to limit heterogeneity by using strict inclusion and exclusion criteria, we fully acknowledge that the lifestyle intervention are diverse and, although data were analyzed according to intervention sub-type and delivery, the wide variability in terms of age, sex, and duration of follow-up could have confounded our findings. Due to the observed heterogeneity in terms of intervention duration, we conducted some pre-liminary exploration but found it to be meaningless because of the frequency versus duration issues, i.e., some intense studies may have been short in duration and some studies with a really long follow-up may have only had two hours of intervention. Furthermore, defining lifestyle intervention is challenging and there is no available consensus definition. In terms of outcomes, this review mainly focused on glycemic control (HbA1c and FBG). This was due to the limited availability of secondary clinical outcomes data (other metabolic markers) and the issue of calculating an effect size for outcomes that were reported using several different measurement tools (e.g., quality of life, self-efficacy, diabetes knowledge). Finally, 26 of the included RCTs were recorded as weak or moderate on the Effective Public Health Practice Project quality assessment tool [18]; hence, the results of this present review should be interpreted in a conservative manner.
Future research should consider some of the limitations noted above. Gaining consensus around the definition of a lifestyle intervention, maybe specifically in relation to LMIC, would be useful and could perhaps address some of the homogeneity issues we came across when analyzing the data in this review; for example, in duration to intervention duration and content. In terms of outcomes that should be measured, a recent consensus study identified 18 core outcomes across five domains for randomized effectiveness trials in T2DM [61]. The implementation of such a core outcome set in future trials could help to ensure that outcomes of importance to all stakeholders are measured and reported. This, in turn, will facilitate the comparison of results across trials, allow for pooled analyses in reviews and, inevitably, result in enhanced relevance of reported research findings. Finally, based on the GRADE quality of evidence assessment, the evidence available for lifestyle interventions delivered in the home setting was deemed to be of a low quality. This was, in part, due to a lack of studies conducted in this environment, highlighting the necessity for further exploration.

5. Conclusions

Despite its limitations, this review identified and summarized the available evidence from LMICs regarding the effectiveness of lifestyle interventions in the management of adults living with T2DM. The results suggest that overall lifestyle interventions are associated with clinically significant improvements in glycemic control. Interventions that promote self-management, including multiple education components, delivered by healthcare professionals in a clinical setting appear to be optimal. However, this is perhaps unworkable in terms of population reach in LMICs, due to a shortage of resources and HCPs working in the area of chronic disease management. Exploring the option of a hybrid model using health–community and home delivery might be a more realistic option. There is, however, a need to further investigate such options in well-designed trials to better inform this evidence base.

Supplementary Materials

The following are available online at https://0-www-mdpi-com.brum.beds.ac.uk/article/10.3390/ijerph18126273/s1, Table S1: Search Strategy, Table S2: Lifestyle interventions’ characteristics, Table S3: Outcome measures reported in included trials, Table S4: EPHPP tool quality assessment ratings, Figure S1: Funnel Plots, Table S5: GRADE quality of evidence, Table S6: PRISMA 2020 checklist.

Author Contributions

Conceptualization, G.O. and C.O.; methodology, G.O., C.O. and C.P.; validation, G.O., C.O., I.C., J.D., R.F. and K.M.; formal analysis, G.O. and C.P.; investigation, G.O., I.C., J.D., R.F. and K.M., C.P.; data curation, G.O., I.C., J.D., R.F., K.M. and C.P.; original draft preparation, G.O., I.C., J.D., R.F. and K.M.; writing—review and editing, G.O., C.O., I.C., J.D., R.F., K.M. and C.P.; supervision, G.O. and C.O. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were not required.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data extracted and analyzed are contained within the article or Supplementary Materials.

Acknowledgments

The authors would like to acknowledge Diarmuid Stokes, Liaison Librarian for Health and Science in University College Dublin, for his advice and assistance regarding electronic literatures search.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Unnikrishnan, R.; Mohan, V. Diabetes in the tropics: Prevalent, increasing and a major public health problem. Trans. R. Soc. Trop. Med. Hygeine 2016, 110, 263–264. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. World Health Organization. Diabetes Epidemic in Europe 2014. Available online: https://www.who.int/news-room/fact-sheets/detail/diabetes (accessed on 1 October 2020).
  3. IDF Diabetes Atlas. Federation ofNorth America and Caribbean Diabetes Report 2010–2045. 2019. Available online: https://www.diabetesatlas.org/data/en/region/5/nac.html. (accessed on 1 October 2020).
  4. Owolabi, M.O.; Yaria, J.O.; Daivadanam, M.; Makanjuola, A.I.; Parker, G.; Oldenburg, B.; Vedanthan, R.; Norris, S.; Oguntoye, A.R.; Osundina, M.A.; et al. Gaps in Guidelines for the Management of Diabetes in Low- and Middle-Income Versus High-Income Countries-A Systematic Review. Diabetes Care 2018, 41, 1097–1105. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Moucheraud, C.; Lenz, C.; Latkovic, M.; Wirtz, V.J. The costs of diabetes treatment in low- and middle-income countries: A systematic review. Br. Med. J. Glob. Health 2019, 4, e001258. [Google Scholar] [CrossRef]
  6. Association, A.D. Lifestyle Management: Standards of Medical Care in Diabetes—2018. Diabetes Care 2018, 41, S38–S50. [Google Scholar] [CrossRef] [Green Version]
  7. Jacobs-van der Bruggen, M.A.; Bos, G.; Bemelmans, W.J.; Hoogenveen, R.T.; Vijgen, S.M.; Baan, C.A. Lifestyle Interventions Are Cost-Effective in People With Different Levels of Diabetes Risk: Results from a modeling study. Diabetes Care 2007, 30, 128–134. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Sun, Y.; You, W.; Almeida, F.; Estabrooks, P.; Davy, B. The Effectiveness and Cost of Lifestyle Interventions Including Nutrition Education for Diabetes Prevention: A Systematic Review and Meta-Analysis. J. Acad. Nutr. Diet. 2017, 117, 404–421. [Google Scholar] [CrossRef] [Green Version]
  9. Howells, L.; Musaddaq, B.; McKay, A.J.; Majeed, A. Clinical impact of lifestyle interventions for the prevention of diabetes: An overview of systematic reviews. BMJ Open 2016, 6, e013806. [Google Scholar] [CrossRef]
  10. Huang, X.L.; Pan, J.H.; Chen, D.; Chen, J.; Chen, F.; Hu, T.T. Efficacy of lifestyle interventions in patients with type 2 diabetes: A systematic review and meta-analysis. Eur. J. Intern. Med. 2016, 27, 37–47. [Google Scholar] [CrossRef]
  11. Mohamed, A.; Staite, E.; Ismail, K.; Winkley, K. A systematic review of diabetes self-management education interventions for people with type 2 diabetes mellitus in the Asian Western Pacific (AWP) region. Nurs. Open 2019, 6, 1424–1437. [Google Scholar] [CrossRef] [Green Version]
  12. Wai Htoo, Z.; Hsu, W.-W.; Rosenkranz, R. Syatematic review and meta-anlysis: Is lifestyle modification effectvie for glycemic control among adults with type II daibetes in Southeast Asia? Diabetes Res. Clin. Pract. 2016, 122, 148–153. [Google Scholar] [CrossRef]
  13. Shirinzadeh, M.; Afshin-Pour, B.; Angeles, R.; Gaber, J.; Agarwal, G. The effect of community-based programs on diabetes prevention in low- and middle-income countries: A systematic review and meta-analysis. Glob. Health 2019, 15, 10–23. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Afable, A.; Karingula, N.S. Evidence based review of type 2 diabetes prevnetion and management in low and middle income countries. World J. Diabetes 2016, 7, 209–229. [Google Scholar] [CrossRef] [PubMed]
  15. Mohan, D.; Shamseer, L.; Clarke, M.; Ghersi, D.; Liberati, A.; Petticrew, M.; Shekelle, P.; Stewart, L.A.; PRISMA-P Group. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst. Rev. 2015, 4, 1–9. [Google Scholar]
  16. Association, A.D. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes—2019. Diabetes Care 2019, 42, S13–S28. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Bank, T.W. World Bank Country and Lending Groups 2019. Available online: https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups (accessed on 1 November 2020).
  18. Armijo-Olivo, S.; Stiles, C.R.; Hagen, N.A.; Biondo, P.D.; Cummings, G.G. Assessment of study quality for systematic reviews: A comparison of the Cochrane Collaboration Risk of Bias Tool and the Effective Public Health Practice Project Quality Assessment Tool: Methodological research. J. Eval. Clin. Pract. 2012, 18, 12–18. [Google Scholar] [CrossRef]
  19. Higgins, J.P.T.; Green, S. Cochrane Handbook for Systematic Reviews of Interventions Cochrane Collaboration 2011. Available online: https://training.cochrane.org/handbook/current (accessed on 10 September 2020).
  20. Chaveepojnkamjorn, W.; Pichainarong, N.; Schelp, F.P.; Mahaweerawat, U. A randomized controlled trial to improve the quality of life of type 2 diabetic patients using a self-help group program. Southeast Asian J. Trop. Med. Public Health 2009, 40, 169–176. [Google Scholar]
  21. Chen, S.; Burström, B.; Sparring, V.; Qian, D.; Burström, K. Differential impact of an education-based intervention for patients with type 2 diabetes mellitus in rural China. Int. J. Environ. Res. Public Health 2019, 16, 2676. [Google Scholar] [CrossRef] [Green Version]
  22. Chow, E.P.; Hassali, M.A.; Saleem, F.; Aljadhey, H. Effects of pharmacist-led patient education on diabetes-related knowledge and medication adherence: A home-based study. Health Educ. J. 2016, 75, 421–433. [Google Scholar] [CrossRef]
  23. Gagliardino, J.J.; Lapertosa, S.; Pfirter, G.; Villagra, M.; Caporale, J.E.; Gonzalez, C.D.; Elgart, J.; Gonzalez, L.; Cernadas, C.; Rucci, E.; et al. Clinical, metabolic and psychological outcomes and treatment costs of a prospective randomized trial based on different educational strategies to improve diabetes care (PRODIACOR). Diabet. Med. 2013, 30, 1102–1111. [Google Scholar] [CrossRef]
  24. Goldhaber-Fiebert, J.D.; Goldhaber-Fiebert, S.N.; Tristán, M.L.; Nathan, D.M. Randomized controlled community-based nutrition and exercise intervention improves glycemia and cardiovascular risk factors in type 2 diabetic patients in rural Costa Rica. Diabetes Care 2003, 26, 24–29. [Google Scholar] [CrossRef] [Green Version]
  25. Goodarzi, M.; Ebrahimzadeh, I.; Rabi, A.; Saedipoor, B.; Jafarabadi, M.A. Impact of distance education via mobile phone text messaging on knowledge, attitude, practice and self efficacy of patients with type 2 diabetes mellitus in Iran. J. Diabetes Metab. Disord. 2012, 11, 10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Ju, C.; Shi, R.; Yao, L.; Ye, X.; Jia, M.; Han, J.; Yang, T.; Lu, Q.; Jin, H.; Cai, X.; et al. Effect of peer support on diabetes distress: A cluster randomized controlled trial. Diabet. Med. 2018, 35, 770–775. [Google Scholar] [CrossRef] [PubMed]
  27. Sanaeinasab, H.; Saffari, M.; Yazdanparast, D.; Zarchi, A.K.; Al-Zaben, F.; Koenig, H.G.; Pakpour, A.H. Effects of a health education program to promote healthy lifestyle and glycemic control in patients with type 2 diabetes: A randomized controlled trial. Prim. Care Diabetes 2020, 15, 275–282. [Google Scholar] [CrossRef]
  28. Li, Y.; Xu, M.; Fan, R.; Ma, X.; Gu, J.; Cai, X.; Liu, R.; Chen, Q.; Ren, J.; Mao, R.; et al. The effects of intensive nutrition education on late middle-aged adults with type 2 diabetes. Int. J. Environ. Res. Public Health 2016, 13, 897. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Mohammadi, S.; Karim, N.A.; Talib, R.A.; Amani, R. The impact of self-efficacy education based on the health belief model in Iranian patients with type 2 diabetes: A randomised controlled intervention study. Asia Pac. J. Clin. Nutr. 2018, 27, 546–555. [Google Scholar]
  30. Muchiri, J.W.; Gericke, G.J.; Rheeder, P. Effect of a nutrition education programme on clinical status and dietary behaviours of adults with type 2 diabetes in a resource-limited setting in South Africa: A randomised controlled trial. Public Health Nutr. 2015, 19, 142055. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  31. Ramadas, A.; Chan, C.K.Y.; Oldenburg, B.; Hussein, Z.; Quek, K.F. Randomised-controlled trial of a web-based dietary intervention for patients with type 2 diabetes: Changes in health cognitions and glycemic control. BMC Public Health 2018, 18, 716. [Google Scholar] [CrossRef]
  32. Salahshouri, A.; Alavijeh, F.Z.; Mahaki, B.; Mostafavi, F. Effectiveness of educational intervention based on psychological factors on achieving health outcomes in patients with type 2 diabetes. Diabetol. Metab. Syndr. 2018, 10, 67–79. [Google Scholar] [CrossRef] [Green Version]
  33. Wichit, N.; Mnatzaganian, G.; Courtney, M.; Schulz, P.; Johnson, M. Randomized controlled trial of a family-oriented self-management program to improve self-efficacy, glycemic control and quality of life among Thai individuals with Type 2 diabetes. Diabetes Res. Clin. Pract. 2017, 123, 37–48. [Google Scholar] [CrossRef] [Green Version]
  34. Zheng, F.; Liu, S.; Liu, Y.; Deng, L. Effects of an outpatient diabetes self-management education on patients with type 2 diabetes in China: A randomized controlled trial. J. Diabetes Res. 2019, 2019, 1073131. [Google Scholar] [CrossRef]
  35. Zhang, Y.; Chu, L. Effectiveness of Systematic Health Education Model for Type 2 Diabetes Patients. Int. J. Endocrinol. 2018, 2018, 6530607. [Google Scholar] [CrossRef] [Green Version]
  36. Mash, R.J.; Rhode, H.; Zwarenstein, M.; Rollnick, S.; Lombard, C.; Steyn, K.; Levitt, N. Effectiveness of a group diabetes education programme in under-served communities in South Africa: A pragmatic cluster randomized controlled trial. Diabet. Med. 2014, 31, 987–993. [Google Scholar] [CrossRef] [PubMed]
  37. Wattana, C.; Srisuphan, W.; Pothiban, L.; Upchurch, S.L. Effects of a diabetes self-management program on glycemic control, coronary heart disease risk, and quality of life among Thai patients with type 2 diabetes. Nurs. Health Sci. 2007, 9, 135–141. [Google Scholar] [CrossRef]
  38. Zhong, X.; Wang, Z.; Fisher, E.B.; Tanasugarn, C. Peer Support for Diabetes Management in Primary Care and Community Settings in Anhui Province, China. Ann. Fam. Med. 2015, 13, S50–S58. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Essien, O.; Otu, A.; Umoh, V.; Enang, O.; Hicks, J.P.; Walley, J. Intensive patient education improves glycaemic control in diabetes compared to conventional education: A randomised controlled trial in a nigerian tertiary care hospital. PLoS ONE 2017, 12, e0168835. [Google Scholar] [CrossRef]
  40. Fottrell, E.; Ahmed, N.; Morrison, J.; Kuddus, A.; Shaha, S.K.; King, C.; Jennings, H.; Akter, K.; Nahar, T.; Haghparast-Bidgoli, H.; et al. Community groups or mobile phone messaging to prevent and control type 2 diabetes and intermediate hyperglycaemia in Bangladesh (DMagic): A cluster-randomised controlled trial. Lancet Diabetes Endocrinol. 2019, 7, 200–212. [Google Scholar] [CrossRef] [Green Version]
  41. Gathu, C.W.; Shabani, J.; Kunyiha, N.; Ratansi, R. Effect of diabetes self-management education on glycaemic control among type 2 diabetic patients at a family medicine clinic in Kenya: A randomised controlled trial. Afr. J. Prim. Health Care Fam. Med. 2018, 10, 1–9. [Google Scholar] [CrossRef] [Green Version]
  42. Grillo, M.D.F.F.; Neumann, C.R.; Scain, S.F.; Rozeno, R.F.; Beloli, L.; Perinetto, T.; Gross, J.L.; Leitão, C.B. Diabetes education in primary care: A randomized clinical trial. Cad. Saude Publica 2016, 32, e00097115. [Google Scholar] [CrossRef]
  43. Jain, V.; Joshi, R.; Idiculla, J.; Xavier, D. Community health worker interventions in type 2 diabetes mellitus patients: Assessing the feasibility and effectiveness in Rural Central India. J. Cardiovasc. Dis. Res. 2018, 9, 127–133. [Google Scholar] [CrossRef] [Green Version]
  44. Malathy, R.; Narmadha, M.P.; Jose, M.A.; Ramesh, S.; Babu, N.D. Effect of a diabetes counseling programme on knowledge, attitude and practice among diabetic patients in Erode district of South India. J. Young Pharm. 2011, 3, 65–72. [Google Scholar] [CrossRef] [Green Version]
  45. Ojieabu, W.A.; Saka, S.A.; Ojieabu, C.E. Evaluation of pharmacists’ educational and counseling impact on patients’ clinical outcomes in a diabetic setting. J. Diabetol. 2017, 8, 7–11. [Google Scholar] [CrossRef]
  46. Samtia, A.M.; Rasool, M.F.; Ranjha, N.M.; Usman, F.; Javed, I. A multifactorial intervention to enhance adherence to medications and disease-related knowledge in type 2 diabetic patients in Southern Punjab, Pakistan. Trop. J. Pharm. Res. 2013, 12, 851–858. [Google Scholar] [CrossRef] [Green Version]
  47. Rehman, S.S.U.; Karimi, H.; Gillani, S.A.; Ahmad, S. Effects of supervised structured aerobic exercise training programme on level of exertion, dyspnoea, VO2 max and body mass index in patients with type 2 diabetes mellitus. J. Pak. Med. Assoc. 2017, 67, 1670–1673. [Google Scholar]
  48. Debussche, X.; Besançon, S.; Balcou-Debussche, M.; Ferdynus, C.; Delisle, H.; Huiart, L.; Sidibé, A.T. Structured peer-led diabetes self-management and support in a low-income country: The ST2EP randomised controlled trial in Mali. PLoS ONE 2018, 13, e0191262. [Google Scholar] [CrossRef] [Green Version]
  49. Yan, H.; Prista, A.; Ranadive, S.M.; Damasceno, A.; Caupers, P.; Kanaley, J.A.; Fernhall, B. Effect of Aerobic Training on Glucose Control and Blood Pressure in T2DDM East African Males. ISRN Endocrinology. Int. Sch. Res. Not. 2014, 2014, 864897. [Google Scholar]
  50. Lenters-Westra, E.; Schindhelm, R.K.; Bilo, H.J.; Groenier, K.H.; Slingerland, R.J. Differences in interpretation of haemoglobin A1c values among diabetes care professionals. Neth. J. Med. 2014, 72, 462–466. [Google Scholar]
  51. Mannucci, E.; Monami, M.; Lamanna, C.; Gori, F.; Marchionni, N. Prevention of cardiovascular disease through glycemic control in type 2 diabetes: A meta-analysis of randomized clinical trials. Nutr. Metab. Cardiovasc. Dis. 2009, 19, 604–612. [Google Scholar] [CrossRef]
  52. Siegel, K.R.; Ali, M.K.; Zhou, X.; Ng, B.P.; Jawanda, S.; Proia, K.; Zhang, X.; Gregg, E.W.; Albright, A.L.; Zhang, P. Cost-effectiveness of Interventions to Manage Diabetes: Has the Evidence Changed Since 2008? Diabetes Care 2020, 43, 1557. [Google Scholar] [CrossRef]
  53. Pan, B.; Ge, L.; Xun, Y.Q.; Chen, Y.J.; Gao, C.Y.; Han, X.; Zuo, L.Q.; Shan, H.Q.; Yang, K.H.; Ding, G.W.; et al. Exercise training modalities in patients with type 2 diabetes mellitus: A systematic review and network meta-analysis. Int. J. Behav. Nutr. Phys. Act. 2018, 15, 72. [Google Scholar] [CrossRef]
  54. Chen, L.; Pei, J.H.; Kuang, J.; Chen, H.M.; Chen, Z.; Li, Z.W.; Yang, H.Z. Effect of lifestyle intervention in patients with type 2 diabetes: A meta-analysis. Metabolism 2015, 64, 338–347. [Google Scholar] [CrossRef] [PubMed]
  55. Flood, D.; Hane, J.; Dunn, M.; Brown, S.J.; Wagenaar, B.H.; Rogers, E.A.; Heisler, M.; Rohloff, P.; Chopra, V. Health system interventions for adults with type 2 diabetes in low- and middle-income countries: A systematic review and meta-analysis. PLoS Med. 2020, 17, e1003434. [Google Scholar] [CrossRef]
  56. Horigan, G.; Davies, M.; Findlay-White, F.; Chaney, D.; Coates, V. Reasons why patients referred to diabetes education programmes choose not to attend: A systematic review. Diabet. Med. 2017, 34, 14–26. [Google Scholar] [CrossRef] [PubMed]
  57. Graziani, C.; Rosenthal, M.P.; Diamond, J.J. Diabetes education program use and patient-perceived barriers to attendance. Fam. Med. 1999, 31, 358–363. [Google Scholar] [PubMed]
  58. Werfalli, M.; Raubenheimer, P.J.; Engel, M.; Musekiwa, A.; Bobrow, K.; Peer, N.; Hoegfeldt, C.; Kalula, S.; Kengne, A.P.; Levitt, N.S. The effectiveness of peer and community health worker-led self-management support programs for improving diabetes health-related outcomes in adults in low- and-middle-income countries: A systematic review. Syst. Rev. 2020, 9, 133. [Google Scholar] [CrossRef]
  59. Checkley, W.; Ghannem, H.; Irazola, V.; Kimaiyo, S.; Levitt, N.S.; Miranda, J.J.; Niessen, L.; Prabhakaran, D.; Rabadán-Diehl, C.; Ramirez-Zea, M.; et al. Management of NCD in low- and middle-income countries. Glob. Heart 2014, 9, 431–443. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  60. Plumb, J.; Weinstein, L.C.; Brawer, R.; Scott, K. Community-based partnerships for improving chronic disease management. Prim. Care 2012, 39, 433–447. [Google Scholar] [CrossRef] [Green Version]
  61. Harman, N.L.; Wilding, J.P.H.; Curry, D.; Harris, J.; Logue, J.; Pemberton, R.J.; Perreault, L.; Thompson, G.; Tunis, S.; Williamson, P.R. Selecting Core Outcomes for Randomised Effectiveness trials In Type 2 diabetes (SCORE-IT): A patient and healthcare professional consensus on a core outcome set for type 2 diabetes. BMJ Open Diabetes Res. Care 2019, 7, e000700. [Google Scholar] [CrossRef] [Green Version]
Ijerph 18 06273 g001 550
Figure 1. PRISMA study flow diagram.
Figure 1. PRISMA study flow diagram.
Ijerph 18 06273 g001
Ijerph 18 06273 g002 550
Figure 2. Forest plots illustrating group data from meta-analysis of HbA1c, FBG and BMI.
Figure 2. Forest plots illustrating group data from meta-analysis of HbA1c, FBG and BMI.
Ijerph 18 06273 g002
Table
Table 1. Characteristics of studies included in the review.
Table 1. Characteristics of studies included in the review.
AuthorYear CountryCountry ClassificationIntervention DescriptionIntervnetion CategoryStudy Duration (Weeks)Sample Size (I/C)Age Mean (SD)Gender (% Female)Diabetes Any Diabetes Medication (Insulin)Outcome Measures
Chaveepojnkamjorn [20] 2009ThailandUpper middleSelf-help group program for patients.SME1680/84I: 48.9 (6.9)
C: 49.1 (7.3)		I: 78
C: 76		 QoL
Chen [21]2019ChinaUpper middleEducation-based intervention for patients.SME104245/248I: 63.3 (6.8)
C: 61.5 (9.1)		I: 79
C: 67		 FBG, QoL
Chow [22]2016MalaysiaUpper middleHome based pharmacist led educational intervention for patients.SME1275/7560.31I: 64
C: 63		 HbA1c
Debussche [48]2018MaliLowStructured T2DM Self-management Education by peers for patients.SME5276/75I: 53.9 (9.8)
C: 51.1 (9.6)		I: 75
C: 77		I: 55 (22)
C: 53 (21)		HbA1c, BMI, WC, SBP, DBP
Essien [39]2017NigeriaLower middleIntensive diabetes self-management program for patients.SME2659/59I: 52.6 (10.9)
C: 52.8 (10.1)		I: 52
C: 67		 HbA1c
Fottrell [40]2019BangladeshLower middle1. MHealth educational voice messages.
2. Participatory learning which engages communities to identify and address their own local problems.		1. SME *
2. SME		104* 4093/4079/4108 I 1: 55
I 2: 53
C: 52		 BMI, SBP, DBP, QoL
Gagliardino [23]2013ArgentinaUpper middle1. Education for healthcare professionals.
2. Self-management education for patients.
3. Education for patients and healthcare professionals.		1. SME ^
2. SME ^^
3. SME ^^^		182135/135/135/135I 1: 62.4 (9.1)
I 2: 62.2 (8.4)
I 3: 62.2 (9.0)
C: 62.1 (8.4)		 HbA1c, SBP, TG
Gathu [41]2018KenyaLower middleDiabetes self-management education training for patients.SME2670/70I: 50.2 (9.9)
C: 47.5 (9.5)		I: 41
C: 47		 HbA1c, BMI, SBP, DBP
Goldhaber-Fiebert [24]2003Costa RicaUpper middleCommunity-based nutrition and exercise intervention for patients.SDEP1240/35I: 60 (10)
C: 57 (9)		I: 83
C: 75		 HbA1c, FBG, BW,
BMI, SBP, DBP, TC, HDLc, LDLc, TG
Goodarzi [25]2012IranUpper middleDistance education including exercise, diet, diabetic meds, self-monitoring of blood glucose levels, via mobile phone text messaging.SME1250/50I: 50.1 (10.3)
C: 56.7 (9.7)		I: 79
C: 76		I: 41 (13)
C: 37 (13)		HBA1c, TC, HDLc, LDLc, TG
Grillo [42]2016BrazilLower middleStructured diabetes self-management education course for patients, administered by a generalist nurse trained in diabetes education.SME5269/68I: 61.7 (9.9)
C: 63.2 (9.7)		I: 71
C: 55		I: 69 (4)
C: 68 (3)		BMI, WC, SBP, DPB, HDLc, LDLc
Huimin [49]2014MozmbiqueLowLow to vigorous intensity exercise intervention for patients.SDEP1231/10I: 53.2 (2.5)
C: 55.3 (3)		I: 0
C: 0		 HbA1c, FBG, BW, BMI, WC, SBP, DBP, VO2max
Jain [43]2018IndiaLower middleFace-to-face interaction by community health workers as well as telephonic reminders.SME24153/146I: 55.7 (10.9)
C: 57.4 (10.1)		I: 45
C: 41		 HBA1c, FBG, BW, BMI, WC, SBP, DPB, TC, HDLc, LDLc, TG
Ju [26]2018ChinaUpper middleUsual education of 2 h each month of focused diabetes education and peer support.SME52200/200I: 67.8 (7.4)
C: 68.8 (8)		I: 65
C: 68		 HBA1c, FBG, 2HBG
Li [28]2016ChinaUpper middleIntensive nutrition education classes for patients.SDEP498/98I: 59.1 (4.6)
C: 58.3 (4.1)		I: 52
C: 46		I: 84 (16)
C: 82 (17)		HBA1c, FBG, 2HBG, BW, BMI, HDLc, LDLc, TG
Malathy [44]2011IndiaLower middlePharmacist-led diabetes counseling program for patients.SME12137/70I: 52.1 (9.5)
C: 51.1 (9.8)		I: 73
C: 35		 TC, HDLc, LDLc, TG
Mash [36] 2014South AfricaUpper middleGroup-based diabetes education program for patients.SME52710/860I: 55.8 (11.5)
C: 56.4 (11.6)		I: 72
C: 76		I: 213 (59)
C: 228 (73)		HBA1c, WC, BW, SBP, DBP, TC
Mohammadi [29]2018IranUpper middleSelf-efficacy education for patients, based on health belief model.SME36120/120I: 51.2 (6.2)
C: 51.4 (6.1)		 HBA1c, FBG, BW, BMI, WC, LDLc, HDLc, QoL
Muchiri [30]2015South AfricaUpper middleNutrition education program for patients.SDEP5241/41I: 59.4 (6.9)
C: 58.2 (8)		85 HbA1c, BMI, SBP, DBP, TC, LDLc, HDLc
Ojieabu [45]2017NigeriaLower middlePharmacist-led education and counseling program for patients.SME2075/75 I: 64
C: 60		 FBG, BMI, SBP, DBP
Ramadas [31]2018MalaysiaUpper middleWeb-based dietry intervention program.SDEP5266/66I: 49.6 (10.7)
C: 51.5 (10.3)		I: 41
C:40		I: 56 (7)
C: 51 (7)		HbA1c
Salahshouri [32]2018IranUpper middleEducational sessions for patients, based on psychological factors administered by a group of internal specialists, dieticians, diabetes experts, a psychologist and a religious expert.SME2073/72I: 55.9 (12.4)
C: 54.8 (9.4)		I: 67
C: 69		 HbA1c, FBG
Sanaeinasab [27]2020IranUpper middleGroup face-to-face sessions, 1 × weekly × 6 weeks; health education and promotion program focusing on diabetes self-care.SME640/4050.7 (5.9)I: 55
C: 63		 HBA1c, FBG, BMI, SBP, DBP, TC, HDL, LDL, TG
Samtia [46]2013PakistanLower middlePre-defined, pharmacist-led, multifactorial, specialized care for patients.SME20178/170I: 46.1
C: 42.3		I: 47
C: 52		 HBA1c, FBG, BMI, WC
Ur Rehman [47]2017PakistanLower middleSupervised structured aerobic exercise training (SSAET) program, routine medication, and dietry planning for patients.SDEP2551/5154.7 (8.2)67 BMI
Wattana [37]2007ThailandUpper middleDiabetes self-management program for patients, based on the theories of self efficacy and self-management.SME2479/8256.8 (4.6)76 HbA1c, QoL
Wichit [33]2017ThailandUpper middleFamily oriented self-management intervention program for patients, designed based on the self-efficacy theory.SME1370/70I: 61.3 (11.6)
C: 55.5 (10.5)		I: 76
C: 70		 HbA1c, QoL
Zhang [35]2018ChinaUpper middleA nine-component systematic education intervention for patients.SME348489/489I: 56.8 (14.2)
C: 52.6 (13.2)		I: 51
C: 49		 HbA1c, BMI, SBP, DBP, TC, LDLc, HDLc
Zheng [34]2019ChinaUpper middle2-session diabetes self-management education program for patients with theory and practical elements.SME1230/30I: 52.5 (10.5)
C: 51.9 (12.3)		I: 47
C: 43		 HBA1c, FBG, 2HBG
Zhong [38]2015ChinaUpper middlePeer leader-support program for patients.SME26365/361 55 FBG, 2HBG, BMI, SBP, DBP
I: Intervention. SDEP (Structured diet and/or exercise program): A structured nutrition/exercise/combined intervention, where the focus was on a prescribed and/or supervised individualized program. SME (Self-management education) consists of a multifactorial program focusing on education provision education around multiple risk factors associated with T2DM. C: Control. * mHealth self management education. ^ Self management education delivered to patients, ^^ SME delivered to healthcare practitioners, ^^^ SME delivered to patients and healthcare practitioners. QoL—Quality of life, CV—cardiovascular, BP—blood Pressure, HbA1c—glycated hemoglobin (%), FBG—fasting blood glucose (mmol/L), FBS—fasting blood glucose, BMI—body mass index (kg/m2), WC—waist circumference (cm), SBP—systolic blood pressure (mmHg), DBP—diastolic blood pressure (mmHg), TG—triglycerides (mmol/L), TC—total cholesterol (mmol/L), HDLc—high density lipid cholesterol (mmol/L), LDLc—low density lipid cholesterol (mmol/L), 2HBG—2 h blood glucose (mmol/L), BW—body weight (kg).
Table
Table 2. Subgroup analysis, based on intervention type, delivery and setting.
Table 2. Subgroup analysis, based on intervention type, delivery and setting.
Clinical Outcome Measure
Glycated Hemoglobin (HbA1c)Body Mass Index (BMI)Fasting Blood Glucose (FBG)
OverallMD −0.63 (−0.86 to −0.40),
I2 88%		MD −0.50 (−0.80 to −0.20),
I2 30%		SMD −0.35 (−0.54 to −0.16),
I2 83%
Intervention
Self-management educationMD −0.69 (−0.96 to −0.43),
I2 90%		MD −0.54 (−0.79 to −0.29),
I2 0%		SMD −0.42 (−0.69 to −0.16),
I2 87%
Structured Diet/exercise/combinedMD −0.07 (−0.81 to 0.67),
I2 45%		MD −0.06 (−0.64 to 0.51),
I2 35%		SMD −0.14 (−0.76 to 0.48),
I2 87%
Delivery
Healthcare professional(s)/MDTMD −0.71 (−1.01 to −0.41),
I2 77%		MD −0.48 (−1.11 to 0.15),
I2 57%		SMD −0.37 (−0.70 to −0.05),
I2 84%
Trained peers/lay peopleMD −0.24 (−0.47 to 0.00),
I2 57%		MD −0.51 (−1.10 to 0.09),
I2 30%		SMD −0.11 (−0.33 to 0.12),
I2 77%
Setting
Hospital/clinicMD −0.77 (−1.08 to −0.56),
I2 88%		MD −0.61 (−1.07 to −0.15),
I2 50%		SMD −0.47 (−0.74 to −0.20),
I2 82%
CommunityMD −0.2 (−0.59 to 0.19),
I2 85%		N/ASMD −0.12 (−0.48 to 0.24),
I2 88%
HomeMD −0.48 (−1.44 to 0.49),
I2 83%		N/AN/A
MD = Mean difference; SMD = standardised mean difference; N/A = not applicable, as ≤1 study in analysis.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

O’Donoghue, G.; O’Sullivan, C.; Corridan, I.; Daly, J.; Finn, R.; Melvin, K.; Peiris, C. Lifestyle Interventions to Improve Glycemic Control in Adults with Type 2 Diabetes Living in Low-and-Middle Income Countries: A Systematic Review and Meta-Analysis of Randomized Controlled Trials (RCTs). Int. J. Environ. Res. Public Health 2021, 18, 6273. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18126273

AMA Style

O’Donoghue G, O’Sullivan C, Corridan I, Daly J, Finn R, Melvin K, Peiris C. Lifestyle Interventions to Improve Glycemic Control in Adults with Type 2 Diabetes Living in Low-and-Middle Income Countries: A Systematic Review and Meta-Analysis of Randomized Controlled Trials (RCTs). International Journal of Environmental Research and Public Health. 2021; 18(12):6273. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18126273

Chicago/Turabian Style

O’Donoghue, Grainne, Cliona O’Sullivan, Isabelle Corridan, Jennifer Daly, Ronan Finn, Kathryn Melvin, and Casey Peiris. 2021. "Lifestyle Interventions to Improve Glycemic Control in Adults with Type 2 Diabetes Living in Low-and-Middle Income Countries: A Systematic Review and Meta-Analysis of Randomized Controlled Trials (RCTs)" International Journal of Environmental Research and Public Health 18, no. 12: 6273. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18126273

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop