Type 2 diabetes is a serious medical condition that is increasingly prevalent in developed countries (International Diabetes Federation, 2013) and the most common variants of the condition are Types I and II. Type I patients have a deficiency in their pancreatic beta cells which leaves them unable to produce insulin. Thus in these individuals, some control over the condition can be achieved using insulin therapy (Schilling, 2007). Type II diabetics, have cells that have become resistant to the effects of insulin resulting in a delayed reduction in blood glucose (Skrha et al., 2010). There are additional types of diabetes; gestational, and a variety of Type III diabetes, however, the overwhelming majority of cases are of Type II with a significant minority of type I cases (Hardt et al., 2008).
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Complications of Diabetes
Regardless of the underlying aetiology, the long-term complications of diabetes are similar. Excess blood glucose is thought to drive increases in oxidative stress both directly and via the derangement of mitochondrial energy pathways (Cade, 2008). Long term macrovascular damage will inevitably increase the risk of coronary heart disease (CHD), and ischaemic heart disease, with diabetics estimated as having a 3 and 5-fold increased risk of CHD mortality for men and women respectively (Loveman et al., 2008). Cerebrovascular disease is also a consequence of the chronic macrovascular damage with similar increases in stroke risk (Naci et al., 2015)
Since each organ has its own microvascular supply, chronic hyperglycaemia also results in diffuse and widespread damage to a variety of body organs. As a result, diabetic complications include visual disability due to diabetic retinopathy; the leading cause of blindness in working age adults in the UK (Fowler, 2008; Kempen et al., 2004). In addition, patients suffer end stage renal disease from diabetic nephropathy (Adler et al., 2003), diffuse impairments of autonomic and somatic neural function, including pain perception, due to diabetic neuropathy (Stirban, 2014; Voulgari et al., 2013). Furthermore, the combination of microvascular damage, and reduced pain sensation, usually in the lower limb, results in many patients developing ulceration and necrosis of the inferior surface of the foot, the most common cause of non-traumatic amputations in the UK (Elraiyah et al., 2016).
Costs of Diabetes
In addition to the significant cost to the individual suffering with diabetes in terms of reduced personal health and quality of life, there are significant financial costs in treating the condition. In 2010-11, the total cost of diabetes to the UK was estimated at £23.7bn (Hex et al., 2012). This was comprised of £9.8bn in direct costs related to treating the disease, and £13.9bn in indirect cost (e.g. lost productivity through absenteeism, early retirement or unemployment, (Hex et al., 2012)). More recently, the direct costs were estimated at £13.7bn in 2012 (Kanavos et al., 2012). Within these direct costs, only around a quarter is directly spent on treating diabetes its self, and the remaining three quarters is spent on treating the complications following from the disease, (e.g. CHD, retinopathy, liver failure, diabetic foot, neuropathy (Kanavos et al., 2012)).
Risk Factors for Diabetes
There are a variety of factors that have been identified that places individuals at risk of developing type II diabetes, these include; having a family history of diabetes, obesity assessed using body-mass index, hypertension, visceral adiposity, adverse blood lipids, smoking, and impaired fasting glucose control (Lyssenko et al., 2008). Notably, several of these risk factors, including blood lipids, BMI, hypertension and visceral adiposity, are shared risk factors for CHD, which may in part explain the elevated risk of CHD in diabetics (Haffner et al., 1998). Indeed the clustering of these risk factors has been shown to be predictive of both CHD and diabetes (Haffner et al., 1998) and are collectively referred to as the metabolic syndrome. Moreover, these risk factors, appear to primarily be related to obesity in general, and excessive visceral adiposity in particular (Wozniak et al., 2009). Early work by West and colleagues (1978) demonstrated a strong positive association between rates of obesity and rates of diabetes with a variety of populations. Since then, the epidemiological link between excess body fat and risk of developing type II diabetes in particular has been repeatedly supported. For example, in the Nurses Health Study (Chan et al., 1994) females who had a BMI of greater than 35 kg.m-2 had a risk of diabetes 95 fold higher than those with a BMI of less than 21 kg.m-2 .
Epidemiology of Diabetes
The incidence and prevalence of diabetes have increased dramatically in the last two decades. Currently, the World Health Organisation estimates that diabetes effects around 9% of the adult global population (International Diabetes Federation, 2013) with variations in prevalence ranging from 26.4% in Kiribati to 1.54% of the population in Manin (International Diabetes Federation, 2013). Overall the UK ranks relatively favourably; in the same data from 2014, the UK had a prevalence of 3.9% (172nd out of 193 countries). Despite this relatively low ranking, the UK, in line with many developed countries, has experienced a rapid growth in the proportion of the population suffering with diabetes. Between 2007 and 2015 the number of patients diagnosed with diabetes increased by 75% from two to three and a half million cases (Diabetes UK, 2015). There are also an estimated half a million undiagnosed individuals at any one time. Indeed, the absence of overt symptoms in the early stages of the disease means that it is not uncommon for patients to have had the disease for several years prior to diagnosis, and confounds attempts to accurately calculate prevalence rates. Scotland has experienced similar increases, with the number of individuals diagnosed with diabetes increasing markedly over the last decade. The Scottish Diabetes survey (2014) demonstrated that the number of individuals with diabetes doubled from approximately 100,000 to 200,000 individuals between 2002 and 2007 despite a stable population of 5 million. Currently estimates for Scotland indicate that there are 276,500 diabetics in Scotland resulting in an overall prevalence that is a third higher than the UK average at 5.2% (NHS Scotland, 2014).
Diabetes and Deprivation
While the reasons that link indices of deprivation to diabetes are likely multifactorial, they undoubtedly exist. Individuals living in the most deprived areas of the UK are 2.5 times more likely to suffer from diabetes than those in the least deprived areas (Diabetes UK, 2006). Moreover the complications arising from diabetes such as CHD and stroke are more than three times higher in the lowest socio-economic groups and those with lowest educational achievement are twice as likely to have heart disease, retinopathy and poor diabetic control (Diabetes UK, 2006; International Diabetes Federation, 2006). The cause of the increased risk is not clear, however many of the risk factors such as obesity, smoking and physical inactivity, are also higher in those areas with the greatest degree of deprivation (Diabetes UK, 2006; International Diabetes Federation, 2006).
From the data outlined above, the development of diabetes is a serious chronic medical condition that can result in early morbidity and mortality and is associated with significant personal and healthcare costs. Despite many of the risk factors for its development being modifiable, it remains a significant and increasing health risk that has a disproportional focus on the areas of greatest deprivation. Given that there is strong evidence that Glasgow has higher rates of both deprivation and type 2 diabetes than the rest of the UK, the aims of this paper are to discuss methods of describing the degree of the problem in Glasgow, as well as identifying, implementing and evaluating initiatives designed to reduce the burden of Type 2 diabetes within that area.
Epidemiological Investigation of Diabetes in Glasgow
The Centre for Disease Control defines public health research as consisting of four phases, public health tracking, public health research, health intervention programmes, and impact and evaluation (CDC, 2015). Thus before designing and implementing a diabetes focused health initiative, it is necessary to first establish that there is a public health need within Glasgow. This can be undertaken using primary or secondary data sources.
Although secondary data sources are repositories of data that have been collected for some purpose other than the investigators main research question, Bailey et al. (2012) suggest that secondary sources also have several advantages. Typically, they are large data sets, and their use is highly cost efficient, as the data collection has already taken place. In terms of this investigation into Diabetes prevalence in Glasgow, there are a number of possible secondary data sources. The most directly relevant data is from the Scottish Diabetes Survey, the most recent data for which covers 2014 (NHS Scotland, 2014). In the most recent report, there is evidence that diabetes is a specific public health concern in Glasgow. For example, while it is not surprising is that Glasgow has the highest number of diabetics, around 22% of Scotland’s diabetic population, since it is also the most densely populated region. However, this also translates to the region having the highest age adjusted prevalence of diabetes within Scotland at 5.8%. Furthermore the Greater Glasgow and Clyde (GGC) NHS board is criticised as falling behind other NHS health boards within Scotland, in its system of managing and screening its diabetic population in order to limit the progression of the disease.
In addition, the Scottish Public Health Observatory (SPHO) provide a number of secondary data sources which may be valuable in triangulating conclusions and include; mortality rates, primary care information from GP practices, the Quality Outcomes Framework (QOF) detailing the performance of GP practices in dealing with key health issues, the Scottish Diet and Nutrition Survey, and the Health Education population survey (Scottish Public Health Observatory, 2015). In addition, both English and Scottish governments produce databases of indices of multiple deprivation (IMD), which can be useful when attempting to standardise the degree of a public health issue by deprivation level.
This secondary data should be supported with primary evidence of the population of interest. While there are a number of research designs that could be used to collect primary data on Glasgow residents with diabetes, in this instance a cross-sectional observational design would be most useful. This method has several advantages, it is cost effective, requires only a single group, and each participant is only required to be assessed at a single time-point. This means that it becomes feasible to assess relatively large numbers of people (Bailey & Handu, 2012). The limitations of this method are that it represents a single point in time and as a result, cannot be used to determine the sequence of events for a given set of exposures and outcomes. Therefore, it is not possible to infer causality from cross-sectional data. This type of research is most useful for determining prevalence rates for a specific condition (Bailey & Handu, 2012)..
An ecological study design might also be used, however, in this case, there are wide variations in income levels and deprivation levels within specific postcodes. Thus the possibility for the data to be affected by unknown confounding variables is significant. Similarly a case control study design has some additional control regarding possible confounders, but is again limited in being retrospective in nature and is predominantly used for rare diseases, which type 2 diabetes is not (Greenfield, 2002).
Experimental designs such as prospective cohort studies or randomised control trials are the most internally valid designs to attribute causation of a condition to a specific exposure. However, they would not be appropriate in this instance, as they time consuming, expensive, and typically include far fewer individuals. Thus in order to use this type of study, the cost would be greater than the cost of any proposed intervention. In addition, while such designs are internally valid, they often lack ecological validity. That is, while the exposure and outcome can be linked in the study, at the population level, individuals may experience exposure to several predicating factors, and several protective factors. Thus, it is not always straightforward to transfer the findings from a highly controlled study to individuals (Peat et al., 2008).
In order to undertake the cross-sectional survey, would require defining a series of areas (e.g. roads or school catchment areas) within specific post-codes to act as the sample frame. The survey data would be collected on these areas. The main problem with collecting this kind of data is a low response rate (Levin, 2006), and the possibility that individuals may responder or not due to the influence of some other factor introducing some systematic bias into the data. The main protection from this is to maximise the response rates. This is best done using face-to-face interviews with individuals in the sample frame (Levin, 2006).
The evidence for the type of behaviours that are useful in limiting the adverse complications of diabetes, have been the subject of several large scale epidemiological studies. In the UK the UK Prospective Diabetes Study (UK Prospective Diabetes Study, 1998) and its 10 year follow up (Holman et al., 2008) evaluated the effect of managing type II diabetes through diet alone, versus aggressive management aimed at restricting blood sugar concentrations. The data from the study indicated that while both the aggressive intervention only lowered blood sugar for one year, this translated into significantly lower rates of complications at the 10-year follow up. In the US, the Diabetes Control and Complications Trial (DCCT, 1993) and its 10 year follow up (the Epidemiology of Diabetes Interventions and Complications EDIC (Nathan et al., 2005)) also demonstrated that limiting increases in blood sugar, by maintaining concentrations within strict individualised limits, reduced the incidence of complications at the 10 year follow up by 57%. Similar reductions in adverse outcomes have also been found when diabetics have measures of blood lipids, blood pressure, nephropathy, retinopathy and diabetic foot complications assessed at regular intervals. It is also noteworthy that the Greater Glasgow and Clyde NHS region regularly performed in the lowest quartile of Scottish NHS authorities for implementing each of these evaluations (Scottish Diabetes Survey 2014).
In long-term conditions such as Type 2 diabetes, the most appropriate strategies to control and manage the condition is for patients, to recognise themselves as stakeholders in their own treatment and to take ownership of the critical aspects of their care such as pharmacological treatment, dietary modifications and physical activity recommendations (National Institute for Health and Care Excellence, 2015). There have been several interventions that have aimed to use patient education to allow for a greater degree of self-management with a resulting closer control of risk factors for diabetic complications. Most recently Minet et al. (2010) evaluated the efficacy of 47 RCT studies aimed at improving diabetic patient education, and found that there was a significant reduction in the degree of hyperglycaemia experienced by the patients at the 6 and 12 month follow up time points. Similar meta analyses have supported the role of education in reducing the incidence of nephropathy and diabetic foot (Elraiyah et al., 2016; Loveman et al., 2008). Given that the UKPDS (1998) demonstrated that even short term reductions in blood glucose can reduce the numbers of patients who progress to sever complications, and given that the majority of the financial burden in treating type 2 diabetes is related to complications rather than the disease its-self. It seems clear that patient education could significantly improve the prognosis of diabetics as well as reduce the costs of future treatment.
Implementing an Intervention in Glasgow
Having identified a suitable educational intervention, the next stage is to ensure its faithful and appropriate replication within patients with Diabetes in Glasgow. A limitation of much of the available research is that interventions are predominantly applied in academic settings, and the effectiveness of interventions in community and primary care settings are frequently lower than anticipated from the scientific literature. This is a continuing challenge for implementing evidence-based strategies for public health issues. Kilbourne et al. (2007) recommend the REP framework, which although originally devised for faithful implementations of HIV educational programmes has been evaluated and found to help improve the effectiveness of other public health interventions.
In order to use the REP framework for educational programmes aimed at Diabetics in Glasgow, the four stages of the REP framework would be developed. Pre-condition requires the identification of a suitable educational intervention. In this phase it is important that the chosen intervention is both feasible and appropriate for the setting in which it will be used. Pre-implementation requires that all staff involved in the intervention undergo training not only in the interventional educational curriculum, but also in the underpinning theories that shaped the original intervention. Implementation requires the educational programme is rolled out to diabetics within Glasgow, and that feedback is sought from stakeholders including patients undergoing the education. In this way it is possible to modify the intervention to better fit the situation, while still remaining faithful to the initial conceptual design. Finally, maintenance and evaluation requires further feedback regarding the effectiveness of the intervention, as well as ongoing support for partners who are delivering or helping ensure the continuation of the intervention.
Monitoring an Evaluation
For the proposed educational intervention, the evaluation would use the RE-AIM framework. This is the most widely adopted model for evaluation of public health interventions originally proposed by Glasgow and Colleagues (1999). This framework proposes the evaluation of five key elements of the intervention. ‘Reach’ assess the number of individuals from the target population who received the interventions. ‘Efficacy’ evaluates the degree to which the education intervention improved patient’s ability to manage their condition (e.g. better control of blood glucose, maintained or lowered blood pressure). ‘Adoption’ would focus on the number of patients receiving the educational intervention whose behaviour was altered as a result. ‘Implementation’ attempts to assess the degree to which the intervention was faithful to the evidence base upon which it was designed or was there pragmatic or other issues that meant the interventions was poorly delivered, or delivered in a manner not originally envisaged. ‘Maintenance’ attempts to quantify the degree to which the intervention becomes self-sustaining. This can be at an institutional level, i.e. does the health authority feel the programme is sufficiently successful to continue its development. However, it can also be at the individual level, were patients value the intervention and it becomes part of the person’s habitual processes.
The aim of this paper was to investigate an intervention aimed at reducing the complications of type 2 diabetes in individuals diagnosed with the condition, living in Glasgow. It has established that in order to implement any such strategy, it is necessary to evaluate the degree of the problem using secondary and if required primary sources of data. In addition, any intervention should be evidence based, and attempt to replicate those interventions that have been demonstrated to be successful. This should be attempted in a strategic and structured manner in order to ensure high fidelity conversion from research evidence to intervention. The intervention its-self needs robust evaluation to determine if it was effective, and if not was it because of a failure of the underpinning theories or a failure in delivery. Unless they are well managed, individuals with Type 2 diabetes are at a significant risk of serious and life threatening complications. Educational interventions may be one way to provide effective strategies to enable better outcomes and reduced personal and financial costs.
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