Self-management of diabetes and associated comorbidities in rural and remote communities: a scoping review

Keywords: chronic health conditions, comorbidities, diabetes, rural and remote communities, self-management.

People living in rural and remote areas experience higher levels of chronic diseases than people living in metropolitan areas (Australian Institute of Health and Welfare (AIHW) 2018; Disler et al. 2020). One reason is that people living in rural and remote areas have less access to health services, such as GPs, than people living in urban areas (Glazier et al. 2008; AIHW 2017). Diabetes is one of the most prevalent chronic diseases, currently ranking seventh in the World Health Organization’s (WHO’s) global burden of disease estimation and accounting for 2.8% of all deaths (WHO 2018). Globally, the prevalence of diabetes is slightly higher in urban (10.8%) than rural (7.2%) areas, although this gap is narrowing with increasing urbanisation (Saeedi et al. 2019). However, in some countries like Australia, rates of hospitalisations and deaths due to diabetes are twice as high in remote and very remote areas than in major cities (AIHW 2019). Some of the common risk factors for diabetes, such as poverty and obesity (O’Connor and Wellenius 2012), are also more prevalent in rural and remote areas than in metropolitan areas.

Diabetes is often associated with one or more serious comorbidity; 85% of people in Australia with diabetes have one or more diabetes-related comorbidity (AIHW 2016). Compared with people without diabetes, people living with a diagnosis of diabetes are significantly more likely to experience conditions like blindness, cardiovascular disease, hypertension, kidney failure, overweight/obesity, hyperlipidaemia, amputation and metabolic syndrome (Pambianco et al. 2006; Iglay et al. 2016). The risk of comorbidities can vary depending on location (i.e. rural or urban areas) and ethnicity (Mainous et al. 2004). There are positive associations between diabetes and both depression (Roy and Lloyd 2012; Moulton et al. 2015) and anxiety (Smith et al. 2013; Chaturvedi et al. 2019). Among people aged ≥65 years, hypoglycaemia is associated with dementia and cognitive impairment (Yerrapragada et al. 2019).

Despite general awareness of the high prevalence of comorbidities, policy and practice are often based on evidence about preventing and managing single disease processes, rather than comorbidities (Ording and Sørensen 2013; Iglay et al. 2016).

Barlow et al. (2002, p. 178) define self-management as ‘the individual’s ability to manage the symptoms, treatment, physical and psychological consequences and life style changes inherent in living with a chronic condition’. Self-management of chronic conditions by individuals is believed to be a complex behavioural process that involves individual decision making, which can be affected by multiple social, cognitive and developmental factors, as well as characteristics of the healthcare system (Bodenheimer et al. 2002; Grady and Gough 2015). Managing diabetes requires lifelong self-care, with particular attention required to balance physical activity, food intake and medication such as insulin (American Association of Diabetes Educators 2014). In research not specific to rural and remote-dwelling people, there is inconsistent evidence as to whether having comorbidities impedes the self-management of diabetes (Piette and Kerr 2006; Jowsey et al. 2009) or encourages people to focus more on their diabetes (Beverly et al. 2011; Teljeur et al. 2013). Although self-management can be successfully promoted through education and goal setting, this can be challenging in rural and remote areas, where health services and transport may be limited (Si et al. 2008).

In summary, although substantial research offers important insights into the self-management of diabetes, and other research informs the self-management of comorbidities, it is unclear whether these insights are applicable to people living in rural and remote settings with diabetes and comorbidities.

The first aim of this study was to synthesise the body of evidence examining self-management among adults with a diagnosis of diabetes and comorbidities living in rural and remote communities. The second aim of the study was to describe any barriers and enablers emerging from the systematic search that may underpin self-management among this target population.

A scoping review was identified as the most appropriate methodology to respond to the broad aims described above. Scoping reviews are defined as ‘exploratory projects that systematically map the literature on a topic, identifying key concepts, theories and sources of evidence’ (Levac et al. 2010). The rigorous methodologies used by the systematic review are used to find studies and extract data (Arksey and O’Malley 2005). However, a formal evaluation of methodological quality of included studies is not performed because the aim is to provide a broad overview of the topic and types of evidence available regardless of quality (Colquhoun et al. 2014; Joanna Briggs Institute 2015). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher et al. 2009) were followed to conduct the review and to report the results.

The PsycINFO, Medline Complete, Cumulative Index to Nursing and Allied Health Literature (CINAHL) Complete and EMBASE databases were searched. Keywords were organised into five concepts and combined using the ‘AND’ Boolean operator: diabet* AND comorbid* AND (‘chronic condition’ OR ‘chronic disease’) AND (‘health literacy’ OR ‘self management’ OR ‘self care’) AND (rural OR regional). In addition, we used controlled vocabulary (MeSH and equivalent terms). We applied the English language limiter to all database searches. Box 1 shows the search strategy in EMBASE.

One author (NI), conducted the search under the guidance of a health librarian and exported references to EndNote. Duplicate records were removed. A two-stage screening process was undertaken by two reviewers (BR with NI or KW): records were screened first by title and abstract, and second by full text. Discrepancies at both stages were resolved via discussion between the reviewers.

Reference lists of all included studies, as well as any review papers found in the search, were harvested for additional eligible studies. A search of the Cochrane Database of Systematic Reviews was also conducted.

All searches were conducted on 6 March 2020, searching for literature from the beginning of each database.

Inclusion criteria related to study design, population, intervention or interest and outcomes, as detailed below:

• Study design: any primary research (including cohort, case control and qualitative studies)

• Population: adults aged ≥40 years. Internationally, diabetes prevalence increases to over 10%, with a substantial economic impact, from the age of 45 years (International Diabetes Federation 2019) and comorbidities usually occur in adults over the age of 45 years (AIHW 2016). To capture studies assessing self-management among adults aged ≥45 years, we set our age cut-off point at ≥40 years. In addition, study participants had to be living in rural and remote areas with diabetes (Type 1 or Type 2) and any combination of the following comorbidities: cardiovascular disease, chronic obstructive pulmonary disease, mental health problems or renal failure

• Intervention or interest: effects of interventions on self-management, the experience or effect of living with diabetes and comorbidities, barriers and/or enablers to self-management of diabetes and comorbidities

• Outcomes: self-management i.e. health literacy, emotional management, metabolic control, treatment adherence (medication adherence, appointment compliance) or lifestyle change (physical activity, healthy eating).

• Although studies from any country were eligible for inclusion, they were only included if they were published in English.

Studies that were not primary research, did not include adults aged ≥40 years, did not include subjects living in rural or remote communities, had a sample in which <75% had diabetes and/or no comorbidities were excluded. In addition, studies in which self-management was not the focus and those published in any language other than English were excluded.

Data were extracted into a data extraction form containing the following fields: author names, date of publication, country, setting, study aim, inclusion/exclusion criteria, sampling frame, number of participants, participant characteristics including age (range, mean if available) and comorbidities, study design, description of intervention if relevant, outcome measures, results regarding efficacy of interventions (including statistics where available) and, finally, results regarding any barriers and enablers to self-management that were reported.

Preliminary data synthesis involved summarising results separately for each study design type (e.g. randomised controlled trials (RCTs), feasibility trials, descriptive cohort studies, qualitative studies). Results from RCTs and other trials were then synthesised together, highlighting similarities and differences among findings, to report interventions to improve self-management strategies. Results from all other study designs were then synthesised together to describe comorbidities associated with better or poorer self-management and then barriers and enablers to self-management among people living with diabetes and comorbidities in rural and remote areas.

The PRISMA flowchart is presented in Fig. 1.

Fig. 1.  Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart.

Twelve studies reporting a large range of comorbidities met the inclusion criteria (see Table 1). Ten were conducted in the US (Utz et al. 2006, 2008; Bell et al. 2010; Brown et al. 2011; Ciemins et al. 2011; Schoenberg et al. 2011; Naik et al. 2012, 2019; Magnan et al. 2015; Carpenter et al. 2017), one in Australia (McDermott et al. 2015) and one in Denmark (Kristensen et al. 2018). The mean age of participants ranged from 48 to 62 years, and most had a diagnosis of Type 2 diabetes. The number of participants varied from 8 to 23 430. Among the studies, only two reported on RCTs; three were qualitative studies describing patient experiences, two described cross-sectional studies of associations between variables, two reported on feasibility studies with pre- and post-test control group design, one was a small pre-post study with no control group, one was a quasi-experimental study comparing two different formats of the same intervention and one was a large retrospective analysis of electronic records (see Table 1). Outcomes included the self-management of diabetes and other chronic conditions, depression, diabetes-related distress and experiences of living with diabetes and comorbidities. Six studies assessed the efficacy of interventions to promote self-management, four reported on the impact of specific comorbidities on self-management outcomes and five reported on barriers and enablers to self-management among adults with a diagnosis of diabetes and comorbidities in rural and remote communities (see Table 1).

Table 1.  Summary of included studies and their findings
AQoL, Assessment of Quality of Life; BMI, body mass index; CAHS, Cognitive Appraisal of Health Scale; CES-D, Center for Epidemiological Studies-Depression; DSME, diabetes self-management education; EUC, enhanced usual care; FBG, fasting blood glucose; HDL, high-density lipoprotein cholesterol; HOPE, Healthy Outcomes through Patient Empowerment; LDL, low-density lipoprotein cholesterol; MI, myocardial infarction; MM, multiple morbidity; NCM, nurse care manager; NP, nurse practitioner; OSA, obstructive sleep apnoea; PAID, Problem Areas in Diabetes; PHQ-4, Patient Health Questionnaire for Depression and Anxiety; PHQ-9, Patient Health Questionnaire-9 for Depression; PRISM, Promoting Realistic Individual Self-Management; SDSCA, Summary of Diabetes Self-Care Activities; SMBG, self-monitoring of blood glucose; T1D, Type 1 diabetes; T2D, Type 2 diabetes; TOFHLA, Test of Functional Health Literacy; USA, United States of America

Of the six studies that assessed the efficacy of an intervention to promote self-management among adults with a diagnosis of diabetes and comorbidities in rural and remote communities (Utz et al. 2008; Brown et al. 2011; Ciemins et al. 2011; Naik et al. 2012, 2019; McDermott et al. 2015), only three (Naik et al. 2012, 2019; McDermott et al. 2015) specifically recruited adults with diabetes and comorbidities. One study (McDermott et al. 2015) found that a culturally safe, community-level health worker-led case management approach to the care of Indigenous adults with poorly controlled Type 2 diabetes and comorbidities in Australia resulted in greater HbA1c reductions than in the control group. The other two studies reported on the Healthy Outcomes through Patient Empowerment (HOPE) intervention, with mixed results: small improvements in HbA1c were demonstrated in the feasibility trial (Naik et al. 2012), but not the subsequent study (Naik et al. 2019). A reduction in depression scores was reported in both studies (Naik et al. 2012, 2019).

The other three interventions targeted adults living with diabetes in rural and remote areas; although comorbidities were reported, these were not required for inclusion in the studies (Utz et al. 2008; Brown et al. 2011; Ciemins et al. 2011). No significant differences were reported between trial groups in any of these studies, which included: (1) a study that compared an intensive, interdisciplinary telehealth self-management diabetes education program with face-to-face consultations in rural areas in the US (Ciemins et al. 2011); (2) an investigation of the effect of adding a nurse case manager to a diabetes self-management program among adults with diabetes (some with comorbidities) in a rural community in the US (Brown et al. 2011); and (3) an assessment of the effects of a culturally tailored diabetes self-management education program intervention in a small group of rural-dwelling African Americans with Type 2 diabetes and comorbidities (Utz et al. 2008).

Specific comorbidities were reported to predict poorer outcomes in self-management interventions, namely obesity, depression, anxiety disorders, disorders of the central and peripheral nervous systems, congestive heart failure, skin ulcer, degenerative eye problems and substance use disorders (Magnan et al. 2015). Bell et al. (2010) reported that rural-dwelling older adults with diabetes and depression are less likely to adhere to some aspects of self-management, healthy eating and physical activity, but not others, such as blood glucose self-monitoring and diabetes medication adherence. Similarly, Carpenter et al. (2017) found that higher diabetes-related distress and depressive symptoms negatively affected diet adherence among adults with Type 2 diabetes. In another study, patients with concurrent mental disorders and impaired self-care ability were more attentive to their mental disorder than other conditions such as diabetes (Kristensen et al. 2018).

Particular barriers related to self-management of diabetes and comorbidities while living in rural areas were reported in two studies (Utz et al. 2006; Schoenberg et al. 2011). These barriers included financial costs, shortages of healthcare providers, delays in diagnosis and treatment, lack of access to fresh, healthy food and exercise facilities, and inadequate transportation to healthcare services (Utz et al. 2006; Schoenberg et al. 2011).

Enablers reported to facilitate self-management of diabetes and comorbidities included religion and spirituality, the use of complementary and alternative therapies (Utz et al. 2006) and formal and informal support (Schoenberg et al. 2011). In particular, an ongoing relationship with the same GP was reported as an enabler to self-management among adults with Type 2 diabetes, concurrent chronic diseases and impaired self-care ability (Kristensen et al. 2018). Carpenter et al. (2017) reported that participants’ cognitive appraisal of diabetes acted as both a barrier and an enabler for their self-management of diabetes: higher appraisals of diabetes as a challenge were significantly associated with better medication adherence, whereas higher appraisals of diabetes as a threat and as a harm were both significantly inversely related to better diet adherence.

This scoping review identified only two interventions that specifically aimed to improve self-management of diabetes and comorbidities among people living in rural and remote communities. Only these interventions were associated with statistically significant differences in health outcomes, including HbA1c reduction (McDermott et al. 2015) and improvements in depression scores (Naik et al. 2012, 2019). Given that depression and distress are associated with poorer self-management (Bell et al. 2010; Carpenter et al. 2017; Kristensen et al. 2018), reducing depression levels is an important outcome. Indeed, a promising intervention currently being tested, COMRADE (COllaborative care Management foR distress And depression in rural DiabetEs), involves cognitive and/or behavioural interventions in a primary care setting among rural-dwelling adults with uncontrolled Type 2 diabetes and comorbid depression or distress (Lutes et al. 2018).

No significant differences were identified between the intervention and control groups in the three studies that did not specifically target adults with diabetes and comorbidities (Utz et al. 2008; Brown et al. 2011; Ciemins et al. 2011). Based on qualitative studies that have reported the experience of living with diabetes and comorbidities in rural communities, a focus on self-management of single diseases is likely to be ineffective because it does not account for the nuances and idiosyncrasies of having comorbidities, especially among vulnerable populations (Schoenberg et al. 2011; Corcoran et al. 2013). Thus, interventions may need to explicitly consider and address managing comorbidities in order to demonstrate significant effects on diabetes self-management.

It is notable that the intervention reported by McDermott et al. (2015) was effective in reducing HbA1c among Australian Indigenous adults with poorly controlled Type 2 diabetes and comorbidities. In Australia, diabetes accounts for 7.9% of deaths among Indigenous people, compared with 2.6% among non-Indigenous people, and contributes to a significant life expectancy gap between these groups (AIHW 2015). Indigenous people are also diagnosed at a significantly younger age than non-Indigenous people (McDermott et al. 2004). Given that approximately 65% of Australia’s Indigenous people live in regional remote areas, compared with 29% of non-Indigenous Australians (National Rural Health Alliance 2011), any interventions designed for people with diabetes and comorbidities living in rural and remote areas should be tailored for specific communities living in those areas. This includes ensuring that the interventions are codesigned with community groups so that they are culturally safe.

Some of the barriers and enablers identified in this review are consistent with evidence on the self-management of diabetes in rural or remote communities, regardless of the presence of comorbidities. For example, among rural and remote-dwelling people, informal and formal support facilitates self-management among people with diabetes, with (Schoenberg et al. 2011; Kristensen et al. 2018) or without (Bardach et al. 2011; Grant and Steadman 2016; Vanderlee et al. 2016; Birabwa et al. 2019) comorbidities.

Our review identified a lack of financial resources as a barrier to the self-management of diabetes and comorbidities among rural and remote-dwelling adults (Utz et al. 2006), consistent with evidence among rural- (Grant and Steadman 2016; Vanderlee et al. 2016; Birabwa et al. 2019) and urban-dwelling adults with diabetes (Jeon et al. 2009). Lack of transport and limited access to health services and associated delays in diagnosis and treatment were identified as barriers to the self-management of diabetes and comorbidities in our review (Utz et al. 2006; Schoenberg et al. 2011); these barriers are commonly reported in general studies among rural-dwelling adults with chronic conditions (Jones et al. 2014; McLaren et al. 2014).

One telehealth intervention (Naik et al. 2012, 2019) identified in this review demonstrated that technology can help participants with uncontrolled diabetes and depression to overcome some of the barriers to self-management, such as distance and the availability of health services. A team approach to health care delivered by telehealth (Ciemins et al. 2011) did not result in statistically significant differences in outcomes compared with the face-to-face intervention; however, face-to-face health care is not always possible in rural and remote settings. Positive contributions of technology (including video conferencing and smartphones) to the self-management of diabetes among rural and remote communities have been reported in studies that did not specifically consider comorbidities (Shea et al. 2009; Stuckey et al. 2011; Jaglal et al. 2013; Jeffrey et al. 2019); expanding such interventions to address the self-management of diabetes and comorbidities simultaneously could potentially improve clinical outcomes and health behaviours in rural and remote-dwelling populations with these conditions. A promising protocol has been published of the mWellcare trial, which is testing an Android-based mobile application in India that generates clinical management prompts for treating hypertension and diabetes (Jha et al. 2017).

Through this scoping review a limited number of studies meeting the search criteria were identified. Study limitations include that the review protocol was not published before the review was conducted. The search was limited to the published literature and did not include the grey literature. It is possible that health services are delivering successful programs to improve self-management of diabetes among the target population as part of usual health care delivery; however, these are not documented in current published peer-reviewed journals. Eligible studies were limited to those that included adults aged ≥40 years; this may have excluded relevant studies reporting on self-management interventions targeting Indigenous communities in rural and remote areas of Australia. Among Indigenous Australians, Type 2 diabetes is increasingly prevalent among adolescents and young adults (Haynes et al. 2016). Further study limitations include that only English language papers were assessed for eligibility because we did not have the resources to translate from other languages. We did not search explicitly for keywords such as ‘barriers’ and ‘enablers’; thus, our description of barriers and enablers to self-management among the target population is limited to evidence reported in the papers that met the criteria for inclusion in the present review.

Further research is needed to separate the effects of, or investigate the interactions among, barriers and enablers related to personal resources, health systems, family and community factors and specific comorbidities. Further research is also required to disentangle the effects of interventions that target Indigenous groups in rural and remote areas to determine the key elements that determine the success of these interventions.

A few of the included studies did not specifically seek out people living with diabetes and who have comorbidities; some participants in these studies may have had comorbidities, whereas others may have not, and a range of comorbidities was represented across the studies. Therefore, the relative effect of an intervention on comorbidities and/or how the outcomes were modified by different comorbidities are not known. Similarly, although some studies focused on participants living in rural and remote settings, others included those living in these settings, as well as those living in urban areas. Synthesising results was therefore difficult. Except for the two studies that described RCTs (McDermott et al. 2015; Naik et al. 2019), the methodologies of the papers included in this review do not lend themselves to generalisation of the findings.

This scoping review on the self-management of diabetes and associated comorbidities in people living in rural and remote areas can inform the planning and delivery of health services for this vulnerable population. Our search revealed only two promising interventions targeting this population: (1) a case management diabetes care approach that includes an Indigenous community health worker; and (2) a telephone-delivered goal-setting intervention. We identified numerous barriers and few enablers that affect how people manage their diabetes and comorbidities. Well-documented reported barriers included limited access to health services and travelling long distances to access health services. These barriers may be overcome by the use of telehealth, which can enable people living with comorbidities to become more engaged in their self-management, particularly those who are hundreds of kilometres away from health services and have higher rates of chronic disease. However, any modern technologies rely on the ability of people to be connected with health services and, unfortunately, the least digitally connected areas are all outside metropolitan regions (Australian Government 2018).

This review suggests that interventions to improve self-management among rural and remote-living people with diabetes need to specifically address the management of comorbidities if they are to achieve positive outcomes. The two studies that report robust evidence on telehealth approaches and community-level interventions that take account of the experiences and cultural context of people with diabetes and comorbidities (McDermott et al. 2015; Naik et al. 2019) suggest that these approaches each hold promise to overcome barriers among people with these conditions living in rural and remote areas, particularly if codesigned with participating communities.

The authors declare no conflicts of interest.

This research was funded by a grant from the Centre for Quality and Patient Safety Research (QPS), Deakin University.