Research & theory

Integrated Management of Type 2 Diabetes and Gestational Diabetes in the Context of MultiMorbidity in Africa: A Systematic Review

Authors: {'first_name': 'Jean Claude', 'last_name': 'Mutabazi'},{'first_name': 'Mahmoud', 'last_name': 'Werfalli'},{'first_name': 'Angeli', 'last_name': 'Rawat'},{'first_name': 'Ezekiel', 'last_name': 'Musa'},{'first_name': 'Tawanda', 'last_name': 'Chivese'},{'first_name': 'Shane', 'last_name': 'Norris'},{'first_name': 'Katherine', 'last_name': 'Murphy'},{'first_name': 'Helen', 'last_name': 'Trottier'},{'first_name': 'Naomi', 'last_name': 'Levitt'},{'first_name': 'Christina', 'last_name': 'Zarowsky'}


Introduction: Many adults diagnosed with gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM) also have other known or unknown comorbid conditions. The rising prevalence of GDM and T2DM within a broader context of multimorbidity can best be addressed through an integrated management response, instead of stand-alone programs targeting specific infectious and/or chronic diseases.

Aim: To describe GDM and T2DM screening, care and cost-effectiveness outcomes in the context of multimorbidity through integrated interventions in Africa.

Methods: A systematic review of all published studies was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Risk Of Bias in Non-randomised Studies of Interventions (ROBINS-I) was used to assess risk of bias. Data synthesis was conducted using narrative synthesis of included studies.

Results: A total of 9 out of 13 included studies reported integrated diabetes mellitus (DM) screening, 7 included integrated care and 9 studies addressed cases of newly detected DM who were asymptomatic in pre-diabetes stage. Only 1 study clearly analysed cost-effectiveness in home-based care; another 5 did not evaluate cost-effectiveness but discussed potential cost benefits of an integrated approach to DM screening and care. Compared to partial integration, only 2 fully integrated interventions yielded tangible results regarding DM screening, care and early detection of cases despite many that reported barriers to its sustainability.

Conclusion: Though few, integrated interventions for screening and/or care of DM in the context of multimorbidity within available resources in health systems throughout Africa exist and suggest that this approach is possible and could improve health outcomes.

Keywords: integrated carediabetes mellitustype 2 diabetesgestational diabetesmultimorbiditysyndemichealth systems 
 Accepted on 30 Aug 2022            Submitted on 31 Aug 2020


Gestational Diabetes Mellitus (GDM) and Type 2 Diabetes Mellitus (T2DM) are the two types of diabetes commonly identified during adulthood and comprise more than 90% of global diabetes cases [1, 2]. Their prevalence has been rising worldwide, especially in the context of multiple co-morbidities and risk factors in LMICs, despite the history of underdiagnosis and low reporting in these countries [3, 4, 5, 6, 7, 8, 9]. Several factors contribute to this increasing burden. First, some women with T2DM are diagnosed for the first time during their pregnancy and are included among women with GDM [10]. Women with true GDM and not previously undiagnosed T2DM are at high risk of developingT2DM in the long term, and their children are also at risk [10, 11]. Secondly, triggered by genetic and environmental factors through epigenetic mechanisms [12], both GDM and T2DM occur later in life, in a population that increasingly becomes vulnerable to various other risk factors and complications [11, 13, 14, 15]. Thirdly, adults diagnosed with GDM or T2DM may remain unaware that they have diabetes and may also suffer from other known or unknown comorbid conditions. Chronic co-morbid conditions could include cardio-vascular diseases (e.g., hypertension) and/or infectious diseases (e.g., tuberculosis, Hepatitis B, HIV/AIDS) and/or vector borne diseases (e.g., malaria) [16]. Treatment of some of these diseases – such as antiretroviral therapy (ART) for HIV – may increase the likelihood of concomitant metabolic complications, with possible pre-existing opportunistic infections among others [10, 13, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28], necessitating more complex and costly clinical management [16]. The multimorbidity caused by comorbid non-communicable and infectious chronic diseases [29], which include GDM and T2DM, has not been well studied, especially their integrated management into primary health care (PHC) in LMICs including all countries in Africa. Fourthly, the diagnosis of GDM or T2DM among some patients with multiple diseases has to be conducted along with diagnosis of these other multiple diseases, a situation that causes challenges in terms of cost and logistics for adequate testing and management, especially in the context of struggling health systems. Hence, researchers and experts increasingly argue that the rising prevalence and burden of GDM and T2DM [1, 30, 31], can best be addressed through an integrated management response instead of more easily delivered and less costly stand-alone programmes targeting specific diseases [29, 32, 33, 34, 35].

Syndemic theory is increasingly used as a framework not only to understand but also to also design interventions for complex multiple diseases affecting disadvantaged populations, especially in low- and middle-income countries (LMICs). LMICs in Africa and beyond are facing epidemiological transitions [36, 37], that overwhelm already weak health systems dealing with multiple complex health problems rather than a single disease or isolated risk factors [38]. A syndemic framework assesses and addresses interacting population health problems where underlying biological, cultural, socioeconomic and environmental dimensions lead to health inequities [37, 39]. It also goes beyond conventional approaches to co-morbidity and multimorbidity [40] such as disease-specific, stand-alone or vertical programmes for targeted infectious, non-communicable, acute or chronic conditions and specific co-morbidities. It instead suggests that integrated management of multiple conditions, though not simple, is necessary for better health services delivery [41]. In contrast to documented integrated interventions within multimorbidity in the developed world, findings from LMICs are scarce, especially in the context of colliding infectious and chronic diseases including GDM and T2DM in LMICs, especially in Africa [29, 42, 43, 44, 45, 46].

This study aimed to review the literature on integrated management of T2DM and GDM in the context of multimorbidity in Africa and to identify the emerging good practices, lessons and advantages, including cost-effectiveness, of integrated rather than vertical or targeted interventions. Additionally, we identified research gaps related to GDM and T2DM integration within management of other chronic and infectious diseases and propose syndemic theory as a useful conceptual background to this study.

This systematic review answers the following research questions: 1) What are the existing integrated interventions and service delivery models for managing T2DM including GDM in the context of multi-morbidity in Africa? 2) What are the successes and challenges of the existing integrated management of T2DM including GDM in the context of multi-morbidity in Africa?



The protocol for this study was developed based on the Cochrane Handbook for Systematic Reviews [47] and registered with PROSPERO: (, registration no. CRD42016046630. The systematic review methods were described in our previously published protocol [48].

Study design and search strategy

For this study, the PRISMA guideline was followed during the systematic review [49]. Published studies were searched using terms (MeSH: Medical subject heading) and key words. The following databases were searched: Cochrane Library, MEDLINE, PubMed, Embase, SCOPUS, AIDS journal and the Cumulative Index to Nursing and Allied Health Literature (CINAHL). Additionally, a manual search was conducted in Google scholar, ( and relevant journals for additional studies. The target population, the intervention of interest, the comparator intervention, key outcomes and time (PICOT) approach [50] was used as a framework for the identification and selection of studies for inclusion. This study was limited to all fifty-four African countries. Since there were not many articles regarding our review topic in our preliminary search, there were no starting time limits up to the search date in February 2019 but two full papers published later in 2019 were extracted after their conference abstracts were initially included in the selection. The search strategy used is shown in Table 1.

Table 1

Search strategy.

(integrat* OR linkag* OR combin* OR amalgamat* OR coordinat* OR unificat* OR manag* OR comprehensive* OR “co-ordinated” OR “disease control” OR care deliver* OR “healthcare deliver*” OR “health care deliver*” OR “collaborative care” OR “intersectional collaborat*” OR “interagency collaborat*” OR “care partner*”) AND (diabet* OR diabetes mellitus, type 2/OR diabetes, gestational/) AND (comorbid* OR co-morbid* OR multimorbid* OR multi-morbid* OR polymorbid* OR poly-morbid* OR codisease* OR co-disease* OR multidisease* OR multi-disease* OR polydisease* OR poly-disease* OR coillness* OR co-illness* OR multiillness* OR multi-illness* OR polyillness* OR poly-illness* OR copatholog* OR co-patholog* OR multipatholog* OR multi-patholog* OR polypatholog* OR poly-patholog* OR codisorder* OR co-disorder* OR multidisorder* OR multi-disorder* OR polydisorder* OR poly-disorder* OR cocondition* OR co-condition* OR multicondition* OR multi-condition* OR polycondition* OR poly-condition* OR cosyndrom* OR co-syndrom* OR multisyndrom* OR multi-syndrom* OR polysyndrom* OR poly-syndrom* OR ((coexisting OR co-existing OR multiple) W0 (morbidit* OR disease* OR illness* OR patholog* OR disorder* OR condition* OR syndrom*)) OR ((Charlson* OR Elixhauser*) W0 (index* OR score*))) OR OR “noncommunicable disease*” OR “non communicable disease*” OR ncd OR ncds OR “non infectious disease*” OR “non infectious illness*” OR “chronic disease*” OR “chronic illness*” OR “cardiovascular disease*” OR “vascular disease*” OR “heart disease*” OR “heart illness*” OR “cardiac disease*” OR “heart attack*” OR stroke* OR “heart failure” OR “heart rupture” OR “cardiac arrest” OR cancer* OR neoplasm* OR “chronic respiratory disease*” OR “chronic airflow obstruction*” OR “chronic obstructive airway disease*” OR “chronic obstructive lung disease*” OR “chronic obstructed pulmonary disease*” OR asthma OR “lung disease*” OR “communicable disease*” OR “infectious disease*” OR “human immunodeficiency virus” OR hiv OR “acquired immunodeficiency syndrome” OR aids OR “opportunistic infectious disease*” OR tuberculosis OR tb OR malaria OR pneumonia OR “diarrheal disease*”) AND Africa/OR “Africa South of the Sahara”/OR “Sub-Saharan Africa”/OR north Africa/OR Africa, Northern/Egypt or Libya OR Tunisia OR Algeria OR Morocco OR “Western Sahara” OR Angola/OR Benin/OR Botswana/OR Burkina Faso/OR Burundi/OR Cameroon/OR Cape Verde/OR Central African Republic/OR Chad/OR Comoros/OR Congo/OR Brazzaville/OR Cote d’Ivoire/OR Djibouti/OR Equatorial Guinea/OR Eritrea/OR Ethiopia/OR Gabon/OR Gambia/OR Ghana/OR Guinea/OR Bissau/OR Kenya/OR Lesotho/OR Liberia/OR Madagascar/OR Malawi/OR Mali/OR Mauritania/OR Mauritius/OR Mozambique/OR Namibia/OR Niger/OR Nigeria/OR Rwanda/OR Sao Tome e Principe/OR Senegal/OR Seychelles/OR Sierra Leone/OR Somalia/OR South Africa/OR South Sudan/OR Sudan/OR Swaziland/OR Eswatini OR Tanzania/OR Togo/OR Uganda/OR Western Sahara/OR Zaire/OR Zambia/OR Zimbabwe/

Study selection

After systematic searches, the retrieved citations were exported to and managed using Endnote X9. Duplicates were removed automatically and a manual search was conducted to crosscheck and remove any duplicates that escaped the automatic removal. The remaining citations were independently screened for eligibility by two researchers (JCM and EM), in accordance with the inclusion and exclusion criteria of the study. Any disagreements were resolved through discussion between reviewers and with a third author (TC). These citations were assessed in two phases by two researchers (JCM and EM); the titles and abstracts first and then the full-text articles of potential studies for inclusion. Once titles and abstracts were screened, the full text were retrieved and screened for eligibility. The team of three researchers (JCM, EM and TC) discussed and agreed on the final studies included.

Eligibility criteria

Eligible studies were the published and unpublished randomised controlled trials (RCTs), non-RCTs, quasi-randomised controlled trials (QCTs) and observational studies on integrated interventions for management of T2DM and GDM within multi-morbidity conditions in Africa, without language restrictions. Studies that were considered for inclusion were primarily quantitative but also included a limited number of relevant qualitative and mixed methods studies. Because most of the included studies simply used “diabetes mellitus” (DM) as a classification instead of the standardised classification of type 1, type 2, GDM or other specific types of diabetes [51, 52] in the context of multimorbidity, we considered DM instead of T2DM and GDM. To ensure that the DM discussed was either GDM or T2DM and therefore eligible for inclusion (for the reasons explained in the Introduction, above), we first checked whether the screening and/or care of DM or its early case detection were among adult patients without a pre-existing diagnosis of type 1 diabetes. All screenings and subsequent procedures were indicated as conducted for the first time without prior diagnosis which increased our confidence that they would in fact be GDM or T2DM, if standard classifications were applied. The level of integration of the intervention [53, 54] was considered. Included interventions could be: (1) mainstreamed (disease specific programmes that were included into PHC services), (2) partially integrated (through linkage or unstructured interactions of two or more disease-specific programmes and possibly including the coordination of interactions with a committee to oversee work oriented to shared goals but maintaining separate programmatic and administrative structures) or (3) fully integrated (in which two or more disease specific programmes were structurally merged including funds, human resources, information system and functional elements such as strategic planning, resource allocation, intervention delivery)(53,54). The outcomes within the multimorbidity framework that were considered in these integrated interventions with these chronic diseases were: integrated screening, integrated care (preventive, treatment and referral services), cost-effectiveness, and early detection of disease.

Data extraction

Data were extracted using a piloted form. The following information was extracted for each included study: the characteristics of the eligible research reports (author(s), year of publication, country of study, and study setting); study methods (study design, target population, sampling strategy, total number of participants, and response rate); intervention and facility (diagnosis, other co-morbidities, service providers (Doctor, Nurse, Both), and point of entry/type of facility); study outcomes (integrated screening outcome, integrated care outcome (preventive, treatment and referral services), cost-effectiveness outcome, and early detection of disease outcome); and approach and level of integration (integration through co-location of services (same room or same clinic), integration of two services OR integration into PHC-mainstreaming, partial integration (linkages, coordination), and full integration.

Assessment of risk of bias in included studies

MW and JCM assessed the methodological quality and risk of bias of the included studies using the ROBINS-I assessment tool [55].

Data synthesis

We performed a narrative synthesis [56], to summarize and thoroughly compare a variety of included studies. We then presented findings through different outcomes and a tabular summary was used to synthesize individual studies characteristics and outcomes (intervention effects). Heterogeneity of the populations as well as of the included studies made a meta-analysis inappropriate for this systematic review.

Patient and public involvement

No patients were involved in the development of the research question, the design or the conduct of this study.


Description of included studies

A total of 7297 published articles were retrieved; 3772 duplicate records were removed and 3153 records were excluded after screening title and abstract. A total of 372 full-text articles were screened for eligibility. Of those, 322 full-text articles were excluded, because they failed to fulfill prior eligibility criteria and out of 50 potential studies 37 articles were excluded for cited reasons. Finally, 13 studies were included in the final analysis, 3 for narrative synthesis and 10 for quantitative analysis (Figure 1).

Flow diagram of the included studies for the systematic review of integrated management of type 2 diabetes mellitus and gestational diabetes mellitus in the context of multi-morbidity conditions in Africa
Figure 1 

Flow diagram of the included studies for the systematic review of integrated management of type 2 diabetes mellitus and gestational diabetes mellitus in the context of multi-morbidity conditions in Africa.

Characteristics of the included studies

All the included studies were from only seven African countries: eight were from Southern African countries – four from South Africa [57, 58, 59, 60], three from Malawi [61, 62, 63] and one from Angola [64], four were from East African countries; two from Kenya [65, 66], one from Ethiopia [67], one from Uganda [68] and one from Central Africa (Cameroon) [69]. Regarding the study design, most studies (10/13) were cross-sectional [57, 59, 60, 61, 62, 63, 64, 67, 68] and three were cohort studies [58, 65, 69]. A total of 27,772 participants were included in this review and some were purposively sampled [61, 63, 64, 66, 67, 69] while others were on voluntary [58, 62, 65], random [59], quota from an old enrolled cohort [60], convenience [57] and community based campaign [68] sampling bases. Table 2 details the characteristics of the included studies.

Table 2

Study characteristics.


Labhardt N.D et al. 2010 Cameroon To examine the effectiveness of integrating care for HT and T2DM by task shifting to non-physician clinician (NPC) facilities in eight rural health districts in Cameroon. Cohort Purposive

Segafredo G. et al. 2016 Angola To estimate the double burden of DM, HT and TB and to pilot the integration of the screening for DM and HT in the TB national programs in six TB centers in Luanda. Cross-sectional or Interventional Purposive

Wroe E.B. et al. 2015 Malawi To increase access to care for NCD patients, to maximize efficiency given the severe human resource shortages, and to replicate strong HIV outcomes for patients with other chronic conditions. Cross-sectional Purposive

Chamie al. 2012 Uganda To test the feasibility and diagnostic yield of integrating NCD and other communicable disease services into a rapid, high-throughput, community-based HIV testing and referral campaign for all residents of a rural Ugandan parish, and to determine rates and predictors of post-campaign linkage to care by disease. Cross-sectional Community based campaign (census)

Jerene D. et al. 2017 Ethiopia 2017 Ethiopia To demonstrate the feasibility of integrated care for TB, HIV and DM in a pilot project. Cross-sectional Purposive

Almossawi HJ et al. 2019 South Africa To assess the readiness of the PHC system to provide integrated TB and DM services. Cross-sectional Random for patients records, convenience for respondents

Pfaff C. et al. 2018 Malawi 2018 Malawi To describe the experience of this pilot initiative, where all adults accessing care in the HIV clinic are screened and treated for HT and DM during the same visit. Cross-sectional Purposive

Pastakia S.D et al. 2017 Kenya To assess the impact of the implementation of a patient-centered rural NCD care delivery model called Bridging Income Generation through grouP Integrated Care (BIGPIC). Cohort or Interventional Voluntary

Govindasamy D. et al. 2013 2013 South Africa To determine the yield of newly-diagnosed HIV, TB symptoms, DM and HT, and to assess CD4 count testing, linkage to care as well as correlates of linkage and barriers to care from a mobile testing unit. Cohort or Interventional Voluntary

Kachimanga C. et al. 2017 Malawi To increase case detection for NCDs in the community, at the facility for acute outpatient care, and at Integrated Chronic Care Clinic (IC3) itself. Cross-sectional Voluntary

Manne-Goehler J. et al. 2017 South Africa To assess the relationship between ART use and utilization of health care services for DM and HT. Cross-sectional Random

Golovaty I. et al. 2018 South Africa To conduct a cost analysis to determine the per-person incremental costs associated with integrating NCD screening and counseling to a home-based HIV counseling and testing program in KwaZulu-Natal. Cross-sectional Quota from an old enrolled cohort

Venables A. et al. 2016 Kenya To assess patient and health-care worker perceptions and experiences of medicines adherence clubs (MACs) in the urban informal settlement of Kibera. Cross-sectional Purposive

Quality appraisal and risk of bias for included studies

All studies reported the results of nonrandomized studies. Many biases were recorded while analyzing all studies and only one study was considered to have a low risk [69] while the remaining twelve had serious risk of bias [57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68]. Studies with serious risk of bias either lacked or had unclear information on participant selection, classification of interventions, measurement of outcomes, selection of the reported results. Some biases were caused by confounding, deviation from intended interventions or by missing data (Table 3).

Table 3

Results of the assessment of risk of bias in included studies by using the ROBINS-I assessment tool.


Labhardt N.D et al. 2010 Cameroon Low Low Low No information Low information on reasons for missing data provided) Low Low Low

Segafredo G. et al. 2016 Angola Serious Low No information No information No information Serious No information Serious

Wroe E.B. et al. 2015 Malawi Serious Serious No information No information Serious Serious Serious Serious

Chamie al. 2012 Uganda Serious Serious No information No information Serious No information No information Serious

Jerene D. et al. 2017 Ethiopia Serious Serious No information No information Low (information on reasons for missing data provided) No information No information Serious

Almossawi HJ et al. 2019 South Africa Serious Low No information No information Low (information on reasons for missing data provided) No information Low Serious

Pfaff C. et al. 2018 Malawi Serious Low Low No information Low (information on reasons for missing data provided No information No information Serious

Pastakia S.D et al. 2017 Kenya Serious Serious Serious Low No information Serious Serious Serious

Govindasamy D. et al. 2013 South Africa Low Low No information No information No information No information No information Serious

Kachimanga C. et al. 2017 Malawi Serious Serious No information No information No information No information No information Serious

Manne-Goehler J. et al. 2017 South Africa Serious Low No information No information Low (information on reasons for missing data provided Serious No information Serious

Golovaty I. et al. 2018 South Africa Low Low No information No information No information No information No information Serious

Venables A. et al. 2016 Kenya Serious Serious No information No information Serious No information No information Serious

Outcomes from included studies

Included studies have shown that integrated screening and care of DM as well as the early detection of DM cases in the context of multimorbidity is possible, although these studies were few and had significant heterogeneity in their findings. Outcomes regarding the integrated screening, care and early detection of DM cases, as well as the cost-effectiveness and integration level outcomes from the included studies were analyzed, summarized and were subsequently presented in Table 4, under the following themes:

Table 4

Cost effectiveness outcomes and integration levels.


Labhardt et al. 2010 Cameroon Affordable drugs from the national essential drug list were available and used Full

Segafredo et al. 2016 2016 Angola Not measured Partial

Wroe et al. 2015 Malawi All patients were seen in one day, at the nearest health center, for all of their chronic conditions. Full

Chamie al. 2012 Uganda Cost-effectiveness of adding NCD screening was not the aim of the study but the relatively low cost of $2.41/person makes it likely to be cost-effective. Partial

Jerene et al. 2017 Ethiopia Not measured Partial

Almossawi et al. 2019 South Africa Not measured Partial

Pfaff et al. 2018 Malawi Not measured but its advantages discussed and its evaluation recommended Partial

Pastakia et al. 2017 Kenya group care model resulted in 72.4% of screen-positive participants returning for subsequent care, of which 70.3% remained in care through the 12 months of the evaluation period. Partial

Govindasamy et al. 2013 South Africa Not measured Partial

Kachimanga et al. 2017 Malawi Not measured Partial

Manne-Goehler et al. 2017 South Africa Not measured Partial

Golovaty et al. 2018 South Africa Comprehensive home-based HIV-NCD testing and counseling results in a modest increase in costs with the potential to avert NCD death and disability. The additional time burden of NCD screening and testing was the major driver of costs, emphasizing the need for a targeted approach that bridges to an integrated public health model. 20% increase in testing and counseling time was revealed in time assessment Partial

Venables et al. 2016 Kenya MACs allow for the efficient management of co-morbidities and enable large numbers of stable patients to collect their chronic medication efficiently, whilst simultaneously enabling patients to benefit from peer support and health education. Partial

Partial *: Integration through co-location of services (same room or same clinic).

Full **: Integration of services OR integration into PHC-mainstreaming.

Integrated diabetes mellitus screening and care in Africa

One included study clearly mentioned that the type of diabetes was T2DM [69], while the remaining studies used DM as diabetes diagnosed or treated along with other diseases from which patients suffered. Among twelve studies that reported DM screening among other co-morbidities [57, 58, 59, 60, 61, 62, 63, 64, 65, 67, 68, 69], only nine reported the exact number of patients who were screened. As expected, the review found that different criteria were used to diagnose DM in routine screening. Applying different criteria was an additional challenge in Africa where lack of clear protocols, limited resources in health facilities and inadequate training for health workers, especially at primary levels of care, was widely documented [57, 61, 69]. Though integrated DM screening was identified in most retained studies, not all patients who benefited from integrated screening had integrated treatment.

Integrated care including preventive, treatment and referral services was reported in nine studies [57, 58, 59, 61, 62, 63, 66, 68, 69], out of which seven had a known number of patients in care. DM screening in the reviewed studies was conducted at different venues: four at the clinic or PHC facilities exclusively [61, 63, 66, 69], three at home or community based infrastructures [60, 65, 68], five at specialized clinics or clinics in close collaboration with hospitals or at hospitals [57, 59, 62, 64, 67] and one at a mobile clinic [58], and by different teams. Health care workers involved in screening and care of DM within multi-morbidities ranged from expert clients or trained patients [63] and lay counsellors and community health workers [58, 59, 60, 61, 62, 65, 67] playing limited roles, to nurses and clinicians that lead interventions in all 13 included studies. The expertise and available resources, including equipment and medication in the facilities, were highlighted as key factors for the successful implementation of integrated screening and care of DM and other NCDs. This integration was more easily carried-out when conducted within the existing protocols of well-established programmes such as for HIV and these established programmes were seen as of tremendous impact to its success [59, 61, 62, 63]. In fact, nine integrated DM screening and care interventions included in this study were conducted with HIV as one of the multi-morbidities [58, 59, 60, 61, 62, 63, 66, 67, 68]. Tuberculosis [57, 58, 62, 64, 67, 68], malaria [68], hypertension [59, 63, 65, 69] and other NCDs including, depression, cardiovascular disease, and health risks such as tobacco, obesity and alcohol use [58, 60, 61, 62] were other diseases and risk factors screened or treated along with DM.

Early detection of DM cases

Nine studies addressed the cases of newly detected DM who were asymptomatic and those with impaired glucose or in pre-diabetes stage [58, 61, 62, 63, 64, 65, 67, 68, 69]. The remaining four studies did not measure this outcome nor include it as one of its results [57, 59, 60, 66]. One study was not included in the meta-analysis as it only mentioned this particular outcome in their weekly integrated screening at the clinic and during outreach but did not share the number of early detected DM cases [61].

Cost-effectiveness of integrated DM screening and care

The majority of included studies (7/13) did not evaluate cost-effectiveness [57, 58, 59, 62, 63, 64, 67]. Only one study clearly analysed cost-effectiveness of home-based integrated screening and referral to care of HIV and comprehensive NCDs including DM [60]; another five did not evaluate cost-effectiveness but rather discussed potential cost benefits of an integrated approach to DM screening and care [21, 61, 65, 66, 69]. Some of the elements addressed throughout different studies that were highlighted and that could relate to cost-effectiveness were: patients with multi-morbidities being seen in one day for all their health conditions [61], availability and affordability of essential DM/NCDs drugs [68, 69], efficient collection of DM and other NCDs medication, benefiting from peer support and health education [66] and reinforcement of adherence to care [65].

Integration levels for GM screening and care within multimorbidity

Interventions carried out in the included studies were integrated but at different levels based on the study objectives, design or available resources for services delivery. Only two studies were classified as fully integrated but not mainstreamed (i.e., services offered for two or more diseases were merged in structural and functional aspects but were not delivered along with other primary care services). Wroe et al. in Malawi and Labhardt et al. in Cameroon reported services that were fully integrated [61, 69] and provided DM screening and care following a clear protocol within the package of other services available in the health care facility. The other 11 studies were partially integrated [57, 58, 59, 60, 62, 63, 64, 65, 66, 67, 68], which means that the services were offered through coordination or co-location in the same room or same clinic but each programme kept its structures as separate entities within health care services.

Integration approaches and models of DM screening and care

Most studies included in this review did not apply specific approaches or models to integrate DM screening and care in the context of multimorbidity. However, some details emerged from a small number of reviewed studies that gave limited information regarding intervention approaches or models used to achieve the aimed integration of screening or care of DM. Task shifting to non-physician clinicians [69], the integrated Chronic Care Clinic, locally called IC3 or “Ice-Cubed” through task shifting and decentralisation [61, 62], medication adherence clubs [66], mobile testing [58] were the few documented approaches adopted to integrate screening or care DM in the context of multimorbidity. Other studies strived for integration of screening or managing DM along with other services or available protocols in the facility but without a specified model used for this particular purpose.


This was a systematic review that examined: 1) the existing integrated interventions and service delivery models for managing T2DM including GDM in the context of multi-morbidity in Africa; and 2) the successes and challenges of the existing integrated management of T2DM including GDM in the context of multi-morbidity in Africa.

In most high-income countries, patients with multi-morbidities including NCDs like DM have been documented to have access to family doctors or general practitioners and health care facilities equipped to provide appropriate integrated care and address multiple health problems [35, 70, 71, 72]. In contrast, Africa does not generally possess enough facilities and the required resources to offer integrated care models like the Integrated Chronic Disease management (ICDM) model, Innovative Care for Chronic Conditions (ICCC) framework, among others [29, 73, 74, 75] for DM. In the context of multimorbidity and severe resource constraints, few studies included in our review followed well-described integrated care models, as seen in the results. This highlights the urgent need to identify core indicators of integrated care models to allow for comparability and share lessons learned, which is increasingly important as health systems are tasked with caring for multimorbidities in the face of waning resources.

Only one study [69] by Labhardt et al. on the integrated intervention of hypertension and T2DM into PHC clinics conducted by clinical nurses in rural Cameroon (2010) assessed after two years, had a low risk of bias. We did not identify any RCTs.

The Labhart et al. study [69] highlighted that fully integrated management of DM is feasible. The findings demonstrate that with adequate training and supervision for nurses on T2DM prevention, diagnosis and care and the provision of additional needed equipment and drugs to the existing facilities within national health system framework, successful integration into PHC is possible. Another study conducted under the fully integrated chronic care clinic in Malawi by Wroe et al. [61] in 2015 had similar results. With lessons from a previously failed partial integration intervention, existing HIV platforms were used to benefit NCDs including DM in terms of prevention, diagnosis, care and follow-up to trace the defaulters [61]. Both of these fully integrated interventions have shown how tasks to prevent, screen and treat DM and other NCDs could be shifted from doctors to nurses and other health care workers in the clinics and communities. Drawing on the experience of scaling up HIV testing and care in Africa, task-shifting could be seen as a good strategy to increase the availability and accessibility of clinical services that are also cost-effective to deal with the rising burden of DM and other major NCDs at primary care [76, 77, 78, 79, 80, 81]. Other studies included in this review were of partially integrated interventions that did not assess task shifting or task sharing aspect of services integration and were limited to either DM screening, care or both and other components as above shown in the results section. The main finding in relation to our study question was that fully integrated screening and care have been shown to work well within multimorbidity approaches in PHC, although only two studies covered this.

As one the main review outcomes, integrated DM screening conducted has led to early detection of unclassified DM in nine studies, and DM would be T2DM and GDM if it were categorised well in those respective studies. These newly screened patients were asymptomatic when diagnosed for the first time in the integrated package of services and had an opportunity to be initiated on treatment before complications appear, while those found to be in pre-diabetes stage with impaired glucose had time to change their lifestyle in order to prevent or delay DM onset [52, 82, 83]. While arguing that the early detection of T2DM should align with changes in LMICs’ health systems, Narayan et al. recommend an integrated approach to address the rapidly increasing T2DM rates and its associated complications or other NCDs in the most cost-effective way [84].

The last outcome from this review was cost-effectiveness, mentioned in seven studies. Only one study conducted by Golovaty et al. in South Africa in 2018 analysed the cost of the home-based integrated screening of NCDs including DM into HIV testing and counselling [60]. Others neither systematically measured the costs, nor the health outcomes [85] of DM integration as an intervention option within multimorbidity. Desmedt et al. in 2016 did not find any study from African country to include in their research assessing the economic impact of integrated care for patients with NCDs including T2DM [86]. The study by Pfaff et al. in 2018 included in this review did not find any publications with formal cost-effectiveness analysis of integrated management of NCDs and HIV [63]. HIV programs, especially in Africa could present an opportunity for measured integration of NCDs, against the potential cost-savings of integrated NCD screening and treatment [63, 87, 88].

Strengths and Limitations


For this systematic review and meta-analysis, many databases were searched and all identified evidence of integrated management of T2DM and GDM within multimorbidity through-out the continent were analyzed, even though few studies qualified for inclusion. To our current knowledge, no other study has comprehensively assessed integrated management of DM within multimorbidity in Africa.


Many studies that could have enriched this review did not have the integrated DM screening and care interventions but merely focused on prevalence or others aspects that did not meet this study’s inclusion criteria. Lack of RCTs to meet the inclusion criteria reveals paucity of rigorous data and highlights the need for more research in this important health systems domain. The lack of studies from many sub-regions and countries in the continent may limit the generalizability of the findings. GDM as a specific health problem for a particular group of population prone to other diseases or risk factors did not clearly appear in studies included in this review and it would be important to consider it for further integrated services. Integrated care being itself a complex approach, most of included studies did not give information about the levels of integration and they were then classified based on the predefined research terms. With this challenge, it was also obvious that a study could set out to be one type of integration and then whether or not in reality that happens the way that was planned, was the next consideration. Another limitation involved heterogenous study designs, methods and outcomes of included studies which weaken the conclusions of the present study.


All included studies demonstrated the feasibility and benefits of integrated management of DM within multimorbidity and emphasized the importance of integration in Africa. Only two studies reported on fully integrated interventions and both were successful. Some studies suggested that integrated interventions to screen and care for DM in the context of multimorbidity could potentially be cost-effective, although scarce evidence of its formal analysis was noted. More original research and review studies are needed to analyze integrated management of T2DM and GDM practices in the context of multimorbidity in Africa.


AIDS: Acquired Immunodeficiency Syndrome

ANC: Antenatal Care

ART: Antiretroviral Therapy

CCRBT: Cochrane Collaboration Risk of Bias Tool

CI: Confidence Interval

CNCICDs: Comorbid Non-Communicable and Infectious Chronic Diseases

DM: Diabetes Mellitus

EPHPP: Effective Public Health Practice Project

GDM: Gestational Diabetes Mellitus

HINARI: Health InterNetwork Access to Research Initiative

HIV: Human Immunodeficiency Virus

ICCC: Innovative Care for Chronic Conditions

ICDM: Integrated Chronic Disease management

LMICs: Low and Middle-Income Countries

MeSH: Medical subject heading

NCDs: Non-Communicable Diseases

PACTR: Pan African Clinical Trials Registry

PHC: Primary Health Care

PICO: Population, Intervention, Comparator and Outcome

PRISMA: Preferred Reporting Items for Systematic review and Meta-Analysis

QCTs: Quasi-randomised Controlled Trials

RCTs: Randomised Controlled Trial

ROBINS-I: Risk Of Bias In Non-randomized Studies – of Interventions

SE: Standard Error

T2DM: Type 2 Diabetes Mellitus.


Pr. Dr. Geert Goderis, MD, PhD, Professor aan de KU Leuven – ACHG, Maître de Conférence à L’Université Libre de Bruxelles (ULB), Belgium.

Sylwia Szafraniec-Burylo, MD, PhD, Department of Pharmacoeconomics, Institute of Mother and Child, Warsaw, Poland.

One anonymous reviewer.

Funding Information

No funding was received for the study but it was part of a PhD project. The first author, JCM held a PhD scholarship of her supervisor Christina Zarowsky from the Canadian Institutes of Health Research (CIHR) under the “Team Grant – Implementation Research in the Prevention and Treatment of Type II Diabetes in Low- and Middle-Income Countries” competition. This funding was for the following randomized trial: integrated health system intervention aimed at reducing type 2 diabetes risk in women after gestational diabetes in South Africa (IINDIAGO). HT holds a salary award (chercheur-boursier) from the “Fond de la recherche en santé- du Québec (FRQ-S)” and a salary award (New Investigator Salary Award) from Canadian Institutes of Health Research (CIHR).

Competing Interests

The authors have no competing interests to declare.


  1. Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Research and Clinical Practice [Internet]. 2019 Nov 1 [cited 2020 Aug 8]; 157. Available from: DOI: 

  2. Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge AW, et al. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract. 2018 Apr; 138: 271–81. DOI: 

  3. Mendenhall E, Norris SA, Shidhaye R, Prabhakaran D. Depression and Type 2 Diabetes in Low and Middle Income Countries: A Systematic Review. Diabetes Res Clin Pract [Internet]. 2014 Feb [cited 2020 Jun 1]; 103(2): 276–85. Available from: DOI: 

  4. Vellakkal S, Millett C, Basu S, Khan Z, Aitsi-Selmi A, Stuckler D, et al. Are estimates of socioeconomic inequalities in chronic disease artefactually narrowed by self-reported measures of prevalence in low-income and middle-income countries? Findings from the WHO-SAGE survey. J Epidemiol Community Health. 2015 Mar; 69(3): 218–25. DOI: 

  5. McMurry HS, Mendenhall E, Rajendrakumar A, Nambiar L, Satyanarayana S, Shivashankar R. Coprevalence of type 2 diabetes mellitus and tuberculosis in low-income and middle-income countries: A systematic review. Diabetes Metab Res Rev. 2019; 35(1): e3066. DOI: 

  6. Luppens D, Piette C, Radermecker R, Scantamburlo G, Ansseau M, Pitchot W. [Depression and type 2 diabetes: etiopathogenic analysis of a frequent comorbidity]. Rev Med Liege [Internet]. 2014 Nov 1 [cited 2020 Jun 1]; 69(11): 611–7. Available from: 

  7. Leone T, Coast E, Narayanan S, de Graft Aikins A. Diabetes and depression comorbidity and socio-economic status in low and middle income countries (LMICs): a mapping of the evidence. Global Health [Internet]. 2012 Nov 26 [cited 2020 Jun 1]; 8: 39. Available from: DOI: 

  8. Jaacks LM, Siegel KR, Gujral UP, Narayan KMV. Type 2 diabetes: A 21st century epidemic. Best Practice & Research Clinical Endocrinology & Metabolism [Internet]. 2016 Jun 1 [cited 2020 Jun 2]; 30(3): 331–43. Available from: DOI: 

  9. International diabetes federation. IDF Diabetes Atlas. 7th ed. Brussels, Belgium: International Diabetes Federation; 2015. 

  10. Mirghani A, Doupis J. Gestational diabetes from A to Z. World J Diabetes [Internet]. 2017 Dec 15 [cited 2020 May 31]; 8(12): 489–511. Available from: DOI: 

  11. Damm P, Houshmand-Oeregaard A, Kelstrup L, Lauenborg J, Mathiesen ER, Clausen TD. Gestational diabetes mellitus and long-term consequences for mother and offspring: a view from Denmark. Diabetologia [Internet]. 2016 Jul 1 [cited 2020 Jun 2]; 59(7): 1396–9. DOI: 

  12. Unnikrishnan R, Pradeepa R, Joshi SR, Mohan V. Type 2 Diabetes: Demystifying the Global Epidemic. Diabetes [Internet]. 2017 Jun 1 [cited 2020 Jun 2]; 66(6): 1432–42. Available from: DOI: 

  13. Gunderson EP, Chiang V, Pletcher MJ, Jacobs DR, Quesenberry CP, Sidney S, et al. History of gestational diabetes mellitus and future risk of atherosclerosis in mid-life: the Coronary Artery Risk Development in Young Adults study. J Am Heart Assoc. 2014 Mar 12; 3(2): e000490. DOI: 

  14. Kim C, Newton KM, Knopp RH. Gestational diabetes and the incidence of type 2 diabetes: a systematic review. Diabetes Care. 2002 Oct; 25(10): 1862–8. DOI: 

  15. Bellamy, Casas JP, Hingorani AD, Williams D. Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. The Lancet [Internet]. 2009 May 23 [cited 2018 Jul 4]; 373(9677): 1773–9. Available from: DOI: 

  16. Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining Comorbidity: Implications for Understanding Health and Health Services. Ann Fam Med [Internet]. 2009 Jul [cited 2020 Jul 31]; 7(4): 357–63. Available from: DOI: 

  17. Kendir C, van den Akker M, Vos R, Metsemakers J. Cardiovascular disease patients have increased risk for comorbidity: A cross-sectional study in the Netherlands. Eur J Gen Pract [Internet]. 2017 Nov 23 [cited 2020 Jun 3]; 24(1): 45–50. Available from: DOI: 

  18. Archambault C, Arel R, Filion KB. Gestational diabetes and risk of cardiovascular disease: a scoping review. Open Med [Internet]. 2014 Jan 7 [cited 2020 Jun 3]; 8(1): e1–9. Available from: 

  19. Li LJ, Aris IM, Su LL, Chong YS, Wong TY, Tan KH, et al. Effect of gestational diabetes and hypertensive disorders of pregnancy on postpartum cardiometabolic risk. Endocr Connect [Internet]. 2018 Feb 14 [cited 2020 Jun 2]; 7(3): 433–42. Available from: DOI: 

  20. Alexander M, Gupta A, Mathad JS. Is there a connection between gestational diabetes mellitus, human immunodeficiency virus infection, and tuberculosis? Int J Tuberc Lung Dis [Internet]. 2019 Jan 1 [cited 2020 Jun 3]; 23(1): 19–25. Available from: DOI: 

  21. Dunachie S, Chamnan P. The double burden of diabetes and global infection in low and middle-income countries. Trans R Soc Trop Med Hyg [Internet]. 2019 Feb 1 [cited 2020 Jun 2]; 113(2): 56–64. Available from: DOI: 

  22. Lao TT, Chan BCP, Leung WC, Ho LF, Tse KY. Maternal hepatitis B infection and gestational diabetes mellitus. Journal of Hepatology [Internet]. 2007 Jul 1 [cited 2020 Jun 3]; 47(1): 46–50. Available from: DOI: 

  23. Wu D. Correlation of viral load of Hepatitis B with the gestation period and the development of diabetes mellitus. Saudi Journal of Biological Sciences [Internet]. 2019 Dec 1 [cited 2020 Jun 3]; 26(8): 2022–5. Available from: DOI: 

  24. Restrepo BI, Fisher-Hoch SP, Crespo JG, Whitney E, Perez A, Smith B, et al. Type 2 diabetes and tuberculosis in a dynamic bi-national border population. Epidemiol Infect [Internet]. 2007 Apr [cited 2020 Jun 3]; 135(3): 483–91. Available from: DOI: 

  25. Soepnel LM, Norris SA, Schrier VJMM, Browne JL, Rijken MJ, Gray G, et al. The association between HIV, antiretroviral therapy, and gestational diabetes mellitus. AIDS. 2017 Jan 02; 31(1): 113–25. DOI: 

  26. Prioreschi A, Munthali RJ, Soepnel L, Goldstein JA, Micklesfield LK, Aronoff DM, et al. Incidence and prevalence of type 2 diabetes mellitus with HIV infection in Africa: a systematic review and meta-analysis. BMJ Open. 2017; 7(3): e013953. DOI: 

  27. Kalra S, Kalra B, Agrawal N, Unnikrishnan A. Understanding diabetes in patients with HIV/AIDS. Diabetology & Metabolic Syndrome [Internet]. 2011 Jan 14 [cited 2020 Jun 3]; 3(1): 2. DOI: 

  28. American Diabetes Association. 4. Comprehensive Medical Evaluation and Assessment of Comorbidities: Standards of Medical Care in Diabetes—2019. Diabetes Care [Internet]. 2019 Jan 1 [cited 2020 Jun 3]; 42(Supplement 1): S34–45. Available from: DOI: 

  29. Oni T, McGrath N, BeLue R, Roderick P, Colagiuri S, May CR, et al. Chronic diseases and multi-morbidity–a conceptual modification to the WHO ICCC model for countries in health transition. BMC Public Health. 2014; 14(100968562): 575. DOI: 

  30. Ferrara A. Increasing prevalence of gestational diabetes mellitus: a public health perspective. Diabetes care. 2007; 30(Suppl): NaN–NaN. DOI: 

  31. Zhu Y, Zhang C. Prevalence of Gestational Diabetes and Risk of Progression to Type 2 Diabetes: a Global Perspective. Curr Diab Rep [Internet]. 2016 Jan [cited 2020 Aug 8]; 16(1): 7. Available from: DOI: 

  32. Simmons D, Wenzel H, Zgibor JC. Integrated Diabetes Care: A Multidisciplinary Approach. Springer. 2016; 257. DOI: 

  33. Hörnsten Å, Jutterström L, Audulv Å, Lundman B. A model of integration of illness and self-management in type 2 diabetes. Journal of Nursing and Healthcare of Chronic Illness [Internet]. 2011 [cited 2020 Jun 3]; 3(1): 41–51. Available from: DOI: 

  34. Pantalone KM, Hobbs TM, Wells BJ, Kong SX, Kattan MW, Bouchard J, et al. Clinical characteristics, complications, comorbidities and treatment patterns among patients with type 2 diabetes mellitus in a large integrated health system. BMJ Open Diabetes Research and Care [Internet]. 2015 Jul 1 [cited 2020 Jun 3]; 3(1): e000093. Available from: DOI: 

  35. Rijken M, Hujala A, van Ginneken E, Melchiorre MG, Groenewegen P, Schellevis F. Managing multimorbidity: Profiles of integrated care approaches targeting people with multiple chronic conditions in Europe. Health Policy [Internet]. 2018 Jan 1 [cited 2020 Jun 3]; 122(1): 44–52. Available from: DOI: 

  36. Omran AR. The Epidemiologic Transition: A Theory of the Epidemiology of Population Change. The Milbank Quarterly [Internet]. 2005 Dec [cited 2020 May 29]; 83(4): 731. Available from: DOI: 

  37. Mendenhall E, Kohrt BA, Norris SA, Ndetei D, Prabhakaran D. Non-communicable disease syndemics: poverty, depression, and diabetes among low-income populations. Lancet [Internet]. 2017 Mar 4 [cited 2020 May 29]; 389(10072): 951–63. Available from: DOI: 

  38. McKeown RE. The Epidemiologic Transition: Changing Patterns of Mortality and Population Dynamics. Am J Lifestyle Med. 2009 Jul 1; 3(1 Suppl): 19S–26S. DOI: 

  39. Singer. Introduction to syndemics: A critical systems approach to public and community health. John Wiley & Sons; 2009. 

  40. Hart L, Horton R. Syndemics: committing to a healthier future. The Lancet [Internet]. 2017 Mar 4 [cited 2018 Nov 9]; 389(10072): 888–9. Available from: DOI: 

  41. Haldane V, Legido-Quigley H, Chuah FLH, Sigfrid L, Murphy G, Ong SE, et al. Integrating cardiovascular diseases, hypertension, and diabetes with HIV services: a systematic review. AIDS Care. 2017 Jul 5; 1–13. DOI: 

  42. Barr AL, Young EH, Smeeth L, Newton R, Seeley J, Ripullone K, et al. The need for an integrated approach for chronic disease research and care in Africa. Glob Health Epidemiol Genom [Internet]. 2016 Nov 29 [cited 2021 Oct 20]; 1: e19. Available from: DOI: 

  43. Rohwer A, Nicol JU, Toews I, Young T, Bavuma CM, Meerpohl J. Effects of integrated models of care for diabetes and hypertension in low-income and middle-income countries: a systematic review and meta-analysis. BMJ Open [Internet]. 2021 Jul 1 [cited 2021 Oct 20]; 11(7): e043705. Available from: DOI: 

  44. Levitt NS, Steyn K, Dave J, Bradshaw D. Chronic noncommunicable diseases and HIV-AIDS on a collision course: relevance for health care delivery, particularly in low-resource settings—insights from South Africa. The American Journal of Clinical Nutrition [Internet]. 2011 Dec 1 [cited 2021 Oct 20]; 94(6): 1690S–1696S. DOI: 

  45. Nielsen KK, Kapur A, Damm P, de Courten M, Bygbjerg IC. From screening to postpartum follow-up – the determinants and barriers for gestational diabetes mellitus (GDM) services, a systematic review. BMC Pregnancy Childbirth [Internet]. 2014 Jan 22 [cited 2020 Apr 21]; 14: 41. Available from: DOI: 

  46. Nicklas JM, Zera CA, Seely EW, Abdul-Rahim ZS, Rudloff ND, Levkoff SE. Identifying postpartum intervention approaches to prevent type 2 diabetes in women with a history of gestational diabetes. BMC Pregnancy and Childbirth [Internet]. 2011 Mar 24 [cited 2020 Apr 28]; 11(1): 23. DOI: 

  47. Higgins JPT, Wells GA. Cochrane handbook for systematic reviews of interventions; 2011. 

  48. Mutabazi JC, Werfalli MM, Rawat A, Musa E, Norris SA, Murphy K, et al. Integrated management of type 2 diabetes and gestational diabetes within multi-morbidity conditions in Africa: a systematic review protocol. BMJ Open [Internet]. 2019 Mar 1 [cited 2020 May 10]; 9(3): e023684. Available from: DOI: 

  49. Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ [Internet]. 2015 Jan 2 [cited 2018 Sep 6]; 349: g7647. Available from: DOI: 

  50. Thabane L, Thomas T, Ye C, Paul J. Posing the research question: not so simple. Can J Anesth/J Can Anesth [Internet]. 2008 Dec 24 [cited 2020 May 20]; 56(1): 71. DOI: 

  51. Kuzuya T, et al. Report of the Committee on the classification and diagnostic criteria of diabetes mellitus. – PubMed – NCBI [Internet]; 2002 [cited 2019 Jul 24]. Available from: 

  52. American Diabetes Association. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes—2018. Diabetes Care [Internet]. 2018 Jan 1 [cited 2019 Jul 29]; 41(Supplement 1): S13–27. Available from: DOI: 

  53. Shigayeva A, Atun R, McKee M, Coker R. Health systems, communicable diseases and integration. Health Policy Plan. 2010 Nov; 25(Suppl 1): i4–20. DOI: 

  54. Atun, de Jongh T, Secci F, Ohiri K, Adeyi O. Integration of targeted health interventions into health systems: a conceptual framework for analysis. Health Policy Plan [Internet]. 2010 Mar 1 [cited 2018 Mar 30]; 25(2): 104–11. Available from: DOI: 

  55. Sterne JAC, Hernán MA, Reeves BC, Savović J, Berkman ND, Viswanathan M, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ [Internet]. 2016 Oct 12 [cited 2018 Sep 6]; 355: i4919. Available from: DOI: 

  56. Schwarz CM, Hoffmann M, Schwarz P, Kamolz LP, Brunner G, Sendlhofer G. A systematic literature review and narrative synthesis on the risks of medical discharge letters for patients’ safety. BMC Health Services Research [Internet]. 2019 Mar 12 [cited 2020 Jul 2]; 19(1): 158. DOI: 

  57. Almossawi HJ, Matji R, Pillay Y, Singh S, Mvusi L, Mbambo B, et al. Primary Health Care System Readiness for Diabetes Mellitus and Tuberculosis Service Integration in South Africa; 2019. 

  58. Govindasamy D, Kranzer K, van Schaik N, Noubary F, Wood R, Walensky RP, et al. Linkage to HIV, TB and non-communicable disease care from a mobile testing unit in Cape Town, South Africa. PLoS ONE. 2013; 8(11): e80017. DOI: 

  59. Manne-Goehler J, Montana L, Gómez-Olivé FX, Rohr J, Harling G, Wagner RG, et al. The ART advantage: healthcare utilization for diabetes and hypertension in rural South Africa. J Acquir Immune Defic Syndr [Internet]. 2017 Aug 15 [cited 2020 Jun 15]; 75(5): 561–7. Available from: DOI: 

  60. Golovaty I, Sharma M, van Heerden A, van Rooyen H, Baeten JM, Celum C, et al. Cost of Integrating Noncommunicable Disease Screening Into Home-Based HIV Testing and Counseling in South Africa. J Acquir Immune Defic Syndr. 2018; 78(5): 522–6. DOI: 

  61. Wroe EB, Kalanga N, Mailosi B, Mwalwanda S, Kachimanga C, Nyangulu K, et al. Leveraging HIV platforms to work toward comprehensive primary care in rural Malawi: the Integrated Chronic Care Clinic. Healthc (Amst). 2015; 3(4): 270–6. DOI: 

  62. Kachimanga C, Cundale K, Wroe E, Nazimera L, Jumbe A, Dunbar E, et al. Novel approaches to screening for noncommunicable diseases: Lessons from Neno, Malawi. Malawi Med J. 2017; 29(2): 78–83. DOI: 

  63. Pfaff C, Singano V, Akello H, Amberbir A, Berman J, Kwekwesa A, et al. Early experiences integrating hypertension and diabetes screening and treatment in a human immunodeficiency virus clinic in Malawi. Int Health. 2018; 10(6): 495–501. DOI: 

  64. Segafredo G, Kapur A, Robbiati C, Joseph N, de Sousa JR, Putoto G, et al. Integrating TB and non-communicable diseases services: Pilot experience of screening for diabetes and hypertension in patients with Tuberculosis in Luanda, Angola. PLoS One [Internet]. 2019 Jul 5 [cited 2020 Jun 15]; 14(7). Available from: DOI: 

  65. Pastakia SD, Manyara SM, Vedanthan R, Kamano JH, Menya D, Andama B, et al. Impact of Bridging Income Generation with Group Integrated Care (BIGPIC) on Hypertension and Diabetes in Rural Western Kenya. J Gen Intern Med. 2017; 32(5): 540–8. DOI: 

  66. Venables E, Edwards JK, Baert S, Etienne W, Khabala K, Bygrave H. “They just come, pick and go.” The Acceptability of Integrated Medication Adherence Clubs for HIV and Non Communicable Disease (NCD) Patients in Kibera, Kenya. PLOS ONE [Internet]. 2016 Oct 20 [cited 2020 Jun 15]; 11(10): e0164634. Available from: DOI: 

  67. Jerene D, Hiruy N, Jemal I, Gebrekiros W, Anteneh T, Habte D, et al. The yield and feasibility of integrated screening for TB, diabetes and HIV in four public hospitals in Ethiopia. Int Health. 2017; 9(2): 100–4. DOI: 

  68. Chamie G, Kwarisiima D, Clark TD, Kabami J, Jain V, Geng E, et al. Leveraging rapid community-based HIV testing campaigns for non-communicable diseases in rural Uganda. PLoS ONE. 2012; 7(8): e43400. DOI: 

  69. Labhardt ND, Balo JR, Ndam M, Grimm JJ, Manga E. Task shifting to non-physician clinicians for integrated management of hypertension and diabetes in rural Cameroon: a programme assessment at two years. BMC Health Serv Res. 2010; 10(101088677): 339. DOI: 

  70. Rijken M, Struckmann V, van der Heide I, Hujala A, Barbabella F, van Ginneken E, et al. How to improve care for people with multimorbidity in Europe? World Health Organization, Regional Office for Europe; 2017. 

  71. Martínez-González NA, Berchtold P, Ullman K, Busato A, Egger M. Integrated care programmes for adults with chronic conditions: a meta-review. Int J Qual Health Care [Internet]. 2014 Oct 1 [cited 2020 Jun 22]; 26(5): 561–70. Available from: DOI: 

  72. Health Council of Canada. Self-management support for Canadians with chronic health conditions: a focus for primary health care. Health Council of Canada; 2012. 

  73. Mahomed O, Asmall S. Development and implementation of an integrated chronic disease model in South Africa: lessons in the management of change through improving the quality of clinical practice. International Journal of Integrated Care [Internet]. 2015 Oct 12 [cited 2020 Jun 22]; 15(4). Available from: DOI: 

  74. Garrib A, Birungi J, Lesikari S, Namakoola I, Njim T, Cuevas L, et al. Integrated care for human immunodeficiency virus, diabetes and hypertension in Africa. Oxford University Press; 2019. DOI: 

  75. Capelli O, Quattrini B, Abate F, Casalgrandi B, Cacciapuoti I. Integrated Care for Chronic Diseases – State of the Art. Primary Care in Practice – Integration is Needed [Internet]; 2016 May 11 [cited 2020 Jun 22]. Available from: DOI: 

  76. Joshi R, Alim M, Kengne AP, Jan S, Maulik PK, Peiris D, et al. Task Shifting for Non-Communicable Disease Management in Low and Middle Income Countries – A Systematic Review. PLoS One [Internet]. 2014 Aug 14 [cited 2020 Jun 23]; 9(8). Available from: DOI: 

  77. Varghese C, Nongkynrih B, Onakpoya I, McCall M, Barkley S, Collins TE. Better health and wellbeing for billion more people: integrating non-communicable diseases in primary care. BMJ [Internet]. 2019 Jan 28 [cited 2020 Jun 23]; 364. Available from: DOI: 

  78. Heller DJ, Kumar A, Kishore SP, Horowitz CR, Joshi R, Vedanthan R. Assessment of Barriers and Facilitators to the Delivery of Care for Noncommunicable Diseases by Nonphysician Health Workers in Low- and Middle-Income Countries: A Systematic Review and Qualitative Analysis. JAMA Netw Open [Internet]. 2019 Dec 2 [cited 2020 Jun 23]; 2(12): e1916545–e1916545. Available from: DOI: 

  79. Kengne AP, et al. Setting-up nurse-led pilot clinics for the management of non-communicable diseases at primary health care level in resource-limited settings of Africa. Pan Afr Med J. 2009; 3(101517926): 10. DOI: 

  80. Kengne AP, et al. Type 2 diabetes management in nurse-led primary healthcare settings in urban and rural Cameroon. Prim Care Diabetes. 2009 Aug; 3(3): 181–8. DOI: 

  81. Frieden M, Zamba B, Mukumbi N, Mafaune PT, Makumbe B, Irungu E, et al. Setting up a nurse-led model of care for management of hypertension and diabetes mellitus in a high HIV prevalence context in rural Zimbabwe: a descriptive study. BMC Health Serv Res. 2020 Jun 1; 20(1): 486. DOI: 

  82. American Diabetes Association. 4. Prevention or Delay of Type 2 Diabetes. Diabetes Care [Internet]. 2016 Jan 1 [cited 2020 Jun 23]; 39(Supplement 1): S36–8. Available from: DOI: 

  83. American Diabetes Association. Gestational diabetes mellitus. Diabetes care. 2004; 27(suppl 1): s88–90. DOI: 

  84. Narayan KMV, Chan J, Mohan V. Early Identification of Type 2 Diabetes: Policy should be aligned with health systems strengthening. Diabetes Care [Internet]. 2011 Jan 1 [cited 2020 Jun 23]; 34(1): 244–6. Available from: DOI: 

  85. Petitti DB. Meta-Analysis, Decision Analysis, and Cost-Effectiveness Analysis: Methods for Quantitative Synthesis in Medicine. USA: Oxford University Press. 2000; 319. 

  86. Desmedt M, Vertriest S, Hellings J, Bergs J, Dessers E, Vankrunkelsven P, et al. Economic Impact of Integrated Care Models for Patients with Chronic Diseases: A Systematic Review. Value in Health [Internet]. 2016 Sep 1 [cited 2020 Jun 22]; 19(6): 892–902. Available from: DOI: 

  87. Pfaff C, Scott V, Hoffman R, Mwagomba B. You can treat my HIV – But can you treat my blood pressure? Availability of integrated HIV and non-communicable disease care in northern Malawi. Afr j prim health care fam med. 2017; 9(1): e1–8. DOI: 

  88. Hod M, Kapur A, Sacks DA, Hadar E, Agarwal M, Di Renzo GC, et al. The International Federation of Gynecology and Obstetrics (FIGO) Initiative on gestational diabetes mellitus: A pragmatic guide for diagnosis, management, and care. Int J Gynaecol Obstet. 2015 Oct; 131(Suppl 3): S173–211. DOI: