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Diabetes, Depression, and Cognitive Disorders

  • Richard I. G. Holt
Reference work entry
Part of the Endocrinology book series (ENDOCR)

Abstract

The interactions between diabetes and the mind are complex; physical illness increases the risk of a number of psychiatric disorders, while mental illness and its treatment also alter the risks of diabetes and worsen both acute metabolic and long-term outcomes of diabetes.

The prevalence of depression is approximately 1.5 to 2-fold higher in people with diabetes compared with the general population. Approximately 10% of people with diabetes will have a formal diagnosis of depression and around a quarter have significant depressive symptoms. Microvascular and macrovascular complications and treatment with insulin are associated with higher rates of depressive symptoms. The underlying mechanisms are multifactorial and include genetic and environmental factors as well as disease and treatment effects. The presence of depression adversely affects diabetes outcomes; quality of life and glycemic control are worsened, while the rates of microvascular and macrovascular complications and mortality are increased in people with depression. Screening for depression in people with diabetes and prompt treatment, where necessary, is recommended.

Diabetes has modest effects on certain aspects of cognition, including general intelligence, psychomotor speed, and mental flexibility, particularly when diagnosed in children under the age of 7 years.

Diabetes increases the risk of vascular dementia and Alzheimer’s disease, even after adjustment for traditional cardiovascular risk factors. Approximately 1 in 15 cases of dementia is attributable to diabetes. Insulin directly affects amyloid β formation. Dementia impedes the person with diabetes’ ability to self-manage their diabetes and mandates a change in glycemic targets and management strategies.

Keywords

Diabetes Depression Diabetes-related distress Cognitive function Dementia Alzheimer’s disease 

Introduction

An effect of diabetes on the mind and vice versa has been recognized for many centuries; in the seventeenth century, Thomas Willis discussed how “diabetes is a consequence of prolonged sorrow” (Willis 1675). As the brain is highly vascular and dependent on glucose for its normal functioning, it is perhaps unsurprising that diabetes affects cognitive function and the risk of mental illness. What is surprising is that clinicians looking after people with diabetes frequently ignore this association. Nevertheless, the effects of comorbid mental illness on someone with diabetes may be profound as the comorbidity worsens the clinical outcomes of both conditions. Quality of life across a broad range of domains is worsened, while the individual’s ability to self-manage their diabetes is impaired, ultimately leading to a higher incidence of complications and reduced life expectancy (Holt and Katon 2012).

Despite the pressing clinical need to consider the comorbidity, in many countries, mental and physical health services are not properly integrated; this leaves diabetes services poorly equipped and organized to address both the physical and psychological needs of patients in the same setting (Mitchell et al. 2009). Over the last decade, however, there have been increasing levels of interest in the comorbidity from researchers, who have made considerable progress in understanding the epidemiology and underlying mechanisms explaining the association. This is beginning to change clinical practice with national and international guidelines highlighting the importance of assessing and treating the psychological sequelae of diabetes (International Diabetes Federation 2012; National Institute for Health and Care Excellence 2015a, b).

This chapter will first describe the complex relationship between diabetes and depression before considering the effects of diabetes on cognitive function, with particular reference to the association between diabetes and dementia.

Diabetes and Depression

Depression is a mood disorder , which is characterized by persistent low mood and loss of interest or pleasure in life. Other symptoms include weight loss or gain, change in sleep patterns, agitation or retardation, fatigue or loss of energy, feelings of worthlessness or guilt, diminished ability to think or concentrate, and recurrent thoughts of death including suicidal ideation.

Depressive symptoms are common in the general population and vary considerably in severity. Consequently, a clinical diagnosis of depression is defined by the number, severity, and duration of symptoms; the most widely used diagnostic criteria in current practice are those of the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (American Psychiatric Association 2005) (Table 1). This degree of symptomatology is associated with significant disability and dysfunction, but it is important to recognize that less severe depressive symptoms may still adversely affect diabetes self-care and outcomes.
Table 1

The Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5): definition of a “major” depressive episode

A. Five (or more) of the following symptoms have been present during the same 2-week period and represent a change from previous functioning; at least one of the symptoms is either (1) depressed mood or (2) loss of interest or pleasure

Depressed mood most of the day, nearly every day, as indicated by either subjective report (e.g., feels sad or empty) or observation made by others (e.g., appears tearful)

• Markedly diminished interest or pleasure in all, or almost all, activities most of the day, nearly every day (as indicated by either subjective account or observation made by others)

• Significant weight loss when not dieting or weight gain (e.g., a change of >5% of body weight in a month), or decrease or increase in appetite nearly every day

• Insomnia or hypersomnia nearly every day

• Psychomotor agitation or retardation nearly every day (observable by others, not merely subjective feelings of restlessness or being slowed down)

• Fatigue or loss of energy nearly every day

• Feelings of worthlessness or excessive or inappropriate guilt (which may be delusional) nearly every day (not merely self-reproach or guilt about being sick)

• Diminished ability to think or concentrate, or indecisiveness, nearly every day (either by subjective account or as observed by others)

• Recurrent thoughts of death (not just fear of dying), recurrent suicidal ideation without a specific plan, or a suicide attempt or a specific plan for committing suicide

B. The symptoms cause clinically significant distress or impairment in social, occupational, or other important areas of functioning

C. The symptoms are not due to the direct physiological effects of a substance (e.g., a drug of abuse, a medication) or a general medical condition (e.g., hypothyroidism)

Epidemiology of Diabetes and Depression

Depression within the general population is common and its prevalence is increasing. It is predicted to become the second leading global cause of disability after heart disease by 2020 (Murray and Lopez 1997). The lifetime prevalence varies widely across the globe from 3% in Japan to 17% in the USA, falling between 8% and 12% in most countries. At any one time, approximately 3–5% of men and 8–10% of women have depression. Given the high prevalence of diabetes and depression, one would expect a degree of comorbidity, but the current evidence suggests that depression occurs more frequently in people with diabetes and vice versa than would be expected by chance (Holt et al. 2014).

Recent meta-analyses have demonstrated that significant depressive symptoms affect approximately 1 in 3–4 adults with diabetes, while a formal diagnosis of depressive disorders is made in approximately 10–15%, equivalent to a 1.5–2-fold increased prevalence (Anderson et al. 2001; Ali et al. 2006). Longitudinal cohort studies report the incidence of depression to be 15–24% higher in people with diabetes compared with those without diabetes (Nouwen et al. 2010; Mezuk et al. 2008). On the other hand, the incidence of type 2 diabetes is also increased by 15–37% among people with depression (Mezuk et al. 2008; Knol et al. 2006), indicating the bidirectional nature of the relationship between these conditions. Episodes of depression appear to be more persistent and more likely to relapse among people with diabetes (Nefs et al. 2012), which may in part explain the discrepancy between the relative incidence and prevalence figures.

Although the literature is consistent in showing an increased prevalence of depression in people with diabetes and vice versa, within each of the meta-analyses, there is considerable variation in risk estimates. This variation stems in part from the meaning of the word “depression,” which spans from relatively minor, occasional negative mood symptoms to life-threatening disabling conditions (Holt et al. 2014). More recently, papers have started to differentiate between “depressive symptoms” and “depression” and this change in definition partly explains why current risk estimates of “depression” are lower than former ones. Another reason why earlier studies reported higher prevalence rates is because the studies recruited selected patient populations, often drawing from specialist diabetes clinics, where referral patterns and other differences in demographic characteristics, such as ethnicity, may increase the likelihood of depression.

The gold standard diagnostic procedure is a diagnostic interview, such as the Structured Clinical Interview for DSM-IV-TR Axis I Disorders SCID interview (First et al. 2002) or the Schedule for Clinical Assessment in Neuropsychiatry 2.1 (World Health Organisation 1999), but these are time-consuming and are unfeasible in most large epidemiological studies. Consequently, many studies have relied on self-rating scores, which tend to overestimate the true prevalence of depression and only provide an estimate of true caseness. These questionnaires may further exaggerate the prevalence of depression because of the overlap of the symptoms of diabetes and depression (Roy et al. 2012).

Depression or Distress

Some authors have argued that much of the psychopathology previously identified as depression is in fact “diabetes-related distress” (Fisher et al. 2016). This concept captures the emotional distress associated with living with diabetes (Fisher et al. 2010), with the top most frequently reported problems including:
  • Worries about the future and the possibility of serious complications.

  • Feeling guilty or anxious when you get off track with your diabetes management.

  • Feeling scared when you think about living with diabetes.

  • Feeling discouraged with your diabetes regimen.

  • Feeling depressed when you think about living with diabetes.

These symptoms are recognized in up to 60% of people with type 1 diabetes or insulin-treated type 2 diabetes (Polonsky et al. 1995; Sturt et al. 2015) and are negatively associated with diabetes self-care and optimal glycemic control (Polonsky et al. 1995). Indeed HbA1c correlates more closely with diabetes-related distress than depression. These feelings are more likely to develop in those with long-standing diabetes and in those with recurrent severe hypoglycemia. Given the commonality of some symptoms, e.g., low mood and guilt, it is unsurprising that many people are reported to display both diabetes-related distress and depressive symptoms with ~30% overlapping variance. Nevertheless as well as the distinct association with glycemic control, the association with self-management also differs between distress and depression, strengthening the view that these are two distinct entities.

Specific Populations

Many studies examining the prevalence of depression in people with diabetes have not differentiated between the types of diabetes. This limitation is important because people with type 2 diabetes are generally older and depression prevalence varies with age, the rates of various diabetic complications and other comorbid conditions (e.g., obesity, heart disease) differ and management strategies are different. Because the prevalence of type 1 diabetes is so much lower than type 2 diabetes, people with type 1 diabetes are underrepresented in depression association studies. One review of depression in type 1 diabetes (Barnard et al. 2006), however, reported that depression was present in 12%, compared with 3.2% in people without diabetes. However, if studies without control groups and interview ascertainment were excluded, the estimated prevalence fell to 7.8%, which was no longer statistically significantly different from people without diabetes (OR 2.4, 95% CI −0.7 to 5.4). A recent study of 368 individuals with type 1 diabetes found an unexpectedly low rate of major depressive disorder (3.5%) and highlighted the marked difference in estimated prevalence rates using self-rated questionnaires (11.4%) compared with diagnostic interviews, again perhaps reflecting an effect of the overlap with diabetes-related distress (Fisher et al. 2016).

Although many of the early studies were undertaken in Western Europe and North America, a recent report including 231,797 adults from 47 countries using data from the World Health Organisation World Health Survey found a 2-fold increase in episodes of depressive symptoms in people with diabetes living in South America, Asia, and Europe (Table 2) (Mommersteeg et al. 2013). No increase in depressive symptoms was seen in people living in Africa, but this may reflect less complete case ascertainment because of cultural differences in the understanding of depression.
Table 2

Increased risk of depressive episodes in people with and without diabetes in four continents after adjustment for age, sex, education, BMI, smoking, and physical activity (Mommersteeg et al. 2013)

 

OR

95% CI

World

2.36

1.91–2.92

Africa

0.86

0.54–1.37

South America

1.98

1.46–2.68

Asia

2.16

1.38–3.37

Europe

2.47

1.73–3.52

Although there are few data, depression rates (9–26%) also appear elevated in children and adolescents with diabetes (Holt et al. 2014).

Etiology of Diabetes and Depression

Which People with Diabetes Are at Risk of Depression?

Female sex, marital status, childhood adversity, and social deprivation are all risk factors for depression in otherwise healthy individuals, and these appear to operate equally in people with diabetes. However, in addition, there are a number of diabetes specific and treatment risk factors associated with the development of depression.

Poor glycemic control and recurrent hypoglycemia are risk factors for depression, in part as a direct effect of hypoglycemia and hyperglycemia on brain function as well as the psychological effects of abnormal glucose levels. Animal models of diabetes have loss of hippocampal integrity and neurogenesis (Ho et al. 2013), while hippocampal atrophy has also been shown in MRI studies of people with diabetes (Lyoo et al. 2009). These structural changes are associated with neurotransmitter abnormalities, including increased prefrontal glutamate-glutamine-gamma-aminobutyric acid levels, which have been observed in people with type 1 diabetes in a manner that correlates with mild depressive symptoms.

Diabetes is not the only chronic physical condition associated with the development of depression, which occurs also more commonly in people with cardiovascular disease (Carney and Freedland 2003), cancer (Sellick and Crooks 1999), and inflammatory arthropathies among others (Matcham et al. 2013). As disease burden increases, so does the prevalence of depressive symptoms. It is therefore unsurprising that depressive symptoms are more common in people with diabetes who have developed either macrovascular or microvascular complications (de Groot et al. 2001). In a specialized outpatient clinic, people with two or more diabetes complications had twice the risk of depression, with neuropathy and nephropathy showing the strongest association with depression (van Steenbergen-Weijenburg et al. 2011). Sexual dysfunction and painful peripheral neuropathy also appear to be particularly associated with depression (de Groot et al. 2001).

People with insulin-treated type 2 diabetes have higher rates of depression compared to those treated with lifestyle interventions or noninsulin medications (Hermanns et al. 2005; Li et al. 2008). Exactly why this is the case is uncertain but probably has more to do with the increased treatment demands including intensive self-monitoring of blood glucose, longer duration of disease, and higher rates of diabetes complications than a direct effect of insulin per se (Li et al. 2008).

Why Do People with Diabetes Develop Depression?

The traditional view is that people with diabetes develop depression because of the psychological response to living with a chronic condition that is associated with unpleasant consequences and treatment that places heavy behavioral demands on the individual. There is support for this hypothesis as a meta-analysis indicated that the rates of depression were only increased among people with diagnosed diabetes while those with undiagnosed diabetes or impaired glucose regulation had no difference in depressive symptoms compared to those with normal glucose metabolism (Nouwen et al. 2011). This finding is important for clinicians who have the responsibility of communicating the diagnosis and its implications to people with new onset diabetes in a sensitive and compassionate manner to help people adjust to the diagnosis.

According to one German study, adults with new onset type 1 diabetes were more than twice as likely to develop a major depressive episode (5.8% vs. 2.7%), although the difference was only statistically significant in women (Petrak et al. 2003). By contrast, the situation appears less clear cut in people with type 2 diabetes where several studies have shown that the diagnosis has little impact on well-being (Adriaanse et al. 2004; Pibernik-Okanovic et al. 1996); the higher rates of depression only start to appear as the disease moves from being asymptomatic to one where complications begin to occur and where treatment demands increase.

This psychological model does not preclude other biological mechanisms, and it is important to recognize that acute changes in glucose may lead to a change in mood (Hermanns et al. 2007). Whether long-term changes or glucose variability may trigger depression directly is uncertain but changes in brain structure and function have been seen in the areas responsible for mood in people with type 1 diabetes (Lyoo et al. 2009).

Why Do People with Depression Develop Diabetes?

The low mood and loss of interest in pleasurable activities may lead to changes in behavior that increase the risk of diabetes. People with depression tend to eat less prudent diets (comfort eating is a readily understandable concept), are less likely to undertake regular physical activity and are more likely to be smokers, all of which increase the risk of diabetes (McMartin et al. 2013; Payne et al. 2012; Weyerer 1992).

Depression is associated with poorer self-care management. This has been studied in more depth in people with established diabetes where people with comorbid depression are more likely to miss medical appointments and are less likely to follow advice about medication use, glucose monitoring, and foot care (Gonzalez et al. 2008). In people with established diabetes, this is associated with poorer diabetes outcomes, but if similar patterns of behavior predated the diagnosis of diabetes, this may have contributed to its onset.

Several biological changes occur in depression, including alterations in the hypothalamic pituitary axis (HPA) and inflammatory markers that could lead to increased insulin resistance and consequently risk of diabetes (Champaneri et al. 2010). Subclinical hypercortisolism, blunted diurnal cortisol rhythm, or hypocortisolism with impaired glucocorticoid sensitivity have all been observed in depression while inflammatory changes include elevated concentrations of C-reactive protein, TNF-α, and proinflammatory cytokines, which have been implicated in causing sickness behavior in animal models and depression in humans (Musselman et al. 2003; Dantzer et al. 2008). Disrupted sleep, which is common in depression, may be a further biological mechanism linking to diabetes as poor sleep quality and altered circadian rhythms are associated with an increased risk of diabetes through insulin resistances (Gangwisch 2009).

There have been concerns that the use of at least some antidepressants may worsen the risk of diabetes (Barnard et al. 2013) as substantial weight gain may occur with certain antidepressants, including mirtazapine, amitriptyline, and paroxetine (Serretti and Mandelli 2010). Case reports and early observational studies demonstrated a consistent association between antidepressant usage and risk of diabetes; however, more recent cohort studies have shown much lower odds ratios, to the point where the association could be explained by confounding and the antidepressant use is merely a marker of individuals at high risk of diabetes. Randomized controlled trials have reported both hyperglycemic and hypoglycemic effects suggesting that not all antidepressants are alike (Barnard et al. 2013).

Do Common Antecedents Explain the Association Between Diabetes and Depression?

Both diabetes and depression occur more frequently among people from lower socioeconomic classes raising the possibility that both conditions occur because of shared environmental risk factors. The importance of social status was demonstrated in a recent study from Denmark, which showed that, while all people with diabetes were more likely to develop depression than those without diabetes, those from lower employment and income groups were disproportionately affected (Cleal et al. 2017).

It is uncertain how the adult environment increases the risk of diabetes but poor physical (e.g., traffic, noise, decreased walkability) and social environments (e.g., lower social cohesion, increased violence, decreased residential stability) are associated with worse diet and lower physical activity levels that predispose to obesity, diabetes, and depression (de Vet et al. 2011). Although it is impossible to determine causality from these observational studies, dysfunctional HPA axis activity and disruption of its normal circadian rhythm (i.e., blunted profile) (Skinner et al. 2011; Brenner et al. 2013; Karb et al. 2012; Do et al. 2011; Dulin-Keita et al. 2012) as well as enhanced inflammation have all been observed in people living in adverse neighborhood environments providing a potential biological mechanism to explain the association (Browning et al. 2012; Broyles et al. 2012). Similar mechanisms may also operate in childhood adversity.

An adverse fetal environment may also predispose an individual to both type 2 diabetes and depression. There is a J-shaped relationship between birth weight and plasma glucose, insulin concentrations and type 2 diabetes while some but not all studies have shown that fetal under-nutrition is associated with adult depression (Holt et al. 2014). Again, programming of the HPA axis may be one biological mechanism to explain the association (Champaneri et al. 2010).

Consequences of Depression in Diabetes

People with comorbid depression experience worsened diabetes outcomes and poorer quality of life (Goldney et al. 2004; Jacobson et al. 1997; Carper et al. 2014). While it is clear that those with microvascular complications are more likely to develop depression, recent work has also shown that those with depression are more likely to develop complications. In one 10-year cohort study of individuals with childhood-onset diabetes, in addition to longer duration of diabetes and poor glycemic control, the overall proportion of time that an individual was depressed predicted retinopathy severity (Kovacs et al. 1995). Similarly, in a longitudinal study of people with type 2 diabetes, progression to diabetic retinopathy and to proliferative diabetic retinopathy was more likely in those with high depressive symptom scores at both baseline and 6-year follow-up (Roy et al. 2007). Depression may worsen the pain experienced by those with painful peripheral neuropathy (Katona et al. 2005). Poor glycemic control is not the explanation for the increase in microvascular complications seen in people with comorbid depression as studies have not reported a consistent association between depressive symptoms and HbA1c (Lustman et al. 2000; Hislop et al. 2008; Aikens et al. 2008). Nevertheless, impaired self-care among people with depression may play a role.

Cardiovascular morbidity and mortality is increased in people with comorbid diabetes and depression (Park et al. 2013); in one study those with diabetes and depression has an annual mortality rate of 8%, which was 2.5-fold higher than those without either condition (Egede et al. 2005).

Management of People with Diabetes and Depression

A greater awareness of the link between diabetes and depression have led several national and international guideline bodies to recommend action to improve the psychological well-being of people with diabetes (International Diabetes Federation 2012; National Institute for Health and Care Excellence 2015a, b). There is a responsibility for healthcare professionals caring for those with diabetes to identify depression when it occurs and then institute prompt treatment in order to reduce depressive symptoms and to improve self-care, glycemic control, and diabetes outcomes (Petrak et al. 2015).

Screening and Diagnosis of Depression

It goes without saying that before treatment can be offered, depression must be recognized and diagnosed. A formal diagnosis of depression requires a time-consuming validated interview, and so this is impractical for routine clinical care. Consequently, quicker and cheaper screening methods are needs to identify those in primary and secondary care with depressive symptoms who should then go forward for a diagnostic interview (Holt and van der Feltz-Cornelis 2012).

Many easy-to-use questionnaires that can be self-completed have been developed for routine use in clinical care but because of the overlap between symptoms of diabetes and depression, only validated questionnaires should be used for people with diabetes (Roy et al. 2012). The Patient Health Question-9 (PHQ-9), which contains nine questions, is the most widely used and validated questionnaire in type 2 diabetes but even this overestimates the prevalence of depression (Fisher et al. 2016). A score of ≥10 reliably identifies those with major depression is in community populations but a higher cut-off of ≥12 has been suggested for people with diabetes in order to improve the discrimination between diabetes-related symptoms and depressive symptoms (van Steenbergen-Weijenburg et al. 2010). The Beck Depression Inventory, the Centre for Epidemiologic Studies Depression Scale, and the Hospital Anxiety and Depression Scale (HADS) are other examples of well-validated questionnaires for people with diabetes.

An even simpler approach that can be used by diabetes healthcare professionals is to ask two questions:
  • During the past month, have you been bothered by having little interest or pleasure in doing things?

  • During the past month, have you been bothered by feeling down, depressed, or hopeless?

If the answer to either is “yes,” the healthcare professional should ask the patient if they want help with this problem. If the answer to this is also “yes,” a diagnostic interview should be undertaken followed by appropriate referral and treatment.

Although diagnosis of depression is necessary to instigate treatment, there is debate as to whether screening for depression should be undertaken (Holt and van der Feltz-Cornelis 2012). Depression screening in the general population has little or no impact on the detection and management of depression if used alone and robust clinical pathways are essential to ensure that appropriate treatment can be offered if a diagnosis is made (Gilbody et al. 2008). The importance of this in the context of diabetes was demonstrated in a Dutch randomized controlled trial, which investigated the benefits of depression screening in people with type 2 diabetes (Pouwer et al. 2011). Following screening, although written feedback was provided to both participant and doctor, neither utilization of mental health services nor depression scores improved. A further study from the USA also failed to demonstrate any improvement in depressive symptoms despite a modest increase in mental healthcare utilization (Scollan-Koliopoulos et al. 2012). Low acceptance of screening and subsequent referral to further care by people with diabetes, failure to screen those at highest risk of depression, reluctance by healthcare professionals to undertake screening and treatment, and generally poor quality of depression care in primary care systems may all contribute to these findings (Petrak et al. 2015).

Thus, while there is a strong imperative to identify people with depression, better integration with care pathways is needed, before screening can be wholeheartedly adopted, not least because screening without appropriate follow-up could lead to harm, by increasing the stigma and discrimination associated with depression and the risk of labelling transient distress as illness (Petrak et al. 2015).

Treatment of Depression in People with Diabetes

As depression adversely affects psychological well-being and diabetes outcomes, the best treatment approaches focus on both improving depressive symptoms and diabetes self-management. The aim of depression treatment is to achieve complete remission of symptoms with the further goals of improving health-related quality of life and psychosocial functioning (Petrak et al. 2015). Over the last decade, a number of randomized controlled trials have demonstrated the effectiveness of both psychological and pharmacological treatments of depression in people with diabetes (Petrak et al. 2015). Most of these trials have been undertaken in people with type 2 diabetes, and so there is still a paucity of evidence for type 1 diabetes.

Psychological Treatment

Psychological interventions are heterogeneous incorporating various techniques (e.g., cognitive behavioral therapy, problem-solving, and psychodynamic), different settings (primary and secondary care), and media (face-to-face, group, web-based, and telephone contacts) (Petrak et al. 2015). Given this level of variability, it is perhaps unsurprising that the effectiveness of interventions differs and comparisons between trials are challenging. Nevertheless, meta-analyses suggest psychological interventions improve depressive symptoms, with a moderate to large effect size (standardized mean difference (SMD) ranging from −0.14 to −1.47). The effect on glycemic control, however, is more modest with one systematic review reporting a reduced HbA1c of ~0.6% (6 mmol/mol) (Ismail et al. 2004) and another indicating a nonsignificant improvement (SMDs from 0.40 to −1.40) (Baumeister et al. 2012). Four recent trials on psychological interventions found an improvements in glycemic control (SMD from −0.25 to −0.68) (Petrak et al. 2015). Web-based psychological therapies appear less effective than face-to-face contact, particularly for glycemic outcomes (van der Feltz-Cornelis 2013). The most effective psychological interventions combine diabetes self-management education with psychological support (van der Feltz-Cornelis et al. 2010).

Pharmacotherapy

There are several classes of effective and well-tolerated antidepressants, and these form an integral component of depression management. Randomized clinical trials in people with diabetes have been undertaken for only a relatively small group of antidepressants, including nortriptyline, fluoxetine, bupropion, sertraline, paroxetine, and citalopram (Petrak et al. 2015); however, these trials show that these antidepressants improve depressive symptoms to a similar extent in people with diabetes and the general population. All antidepressants studied appear to have similar efficacy and as long as adequate doses are used, the effect sizes are −0.61 SMD (Baumeister et al. 2012). However, there are gaps in our evidence base, with regards to glycemic control and the medium- and long-term sustainability of pharmacological interventions after treatment cessation. Furthermore, a number of new antidepressants have recently been approved, including vilazodone, vortioxetine, and levomilnacipran, which have not been formally assessed in people with diabetes.

Given the comparable effectiveness, the treatment of choice depends largely on the side effect profile, patient preference, and individual response. Selective serotonin reuptake inhibitors (SSRIs) are widely regarded as first choice agents, because they are less cardiotoxic than the older tricyclic antidepressants and are safer in overdose.

Some antidepressants, including mirtazapine, paroxetine, and some tricyclic antidepressants, may cause unwanted weight gain (Serretti and Mandelli 2010), while bupropion, which is available in the USA but not Europe, is associated with weight loss.

Several antidepressants may interact with oral hypoglycemic agents through inhibition of the cytochrome P450 3A4 and 2C9 isoenzyme. For example, the use of fluoxetine may potentiate the effect of sulfonylureas precipitating hypoglycemia (Musselman et al. 2003).

Antidepressant treatment should be continued at an adequate dose for at least 4–6 months after complete remission of depressive symptoms to reduce the risk of relapse and recurrence. This is particularly important in people with diabetes, in whom the risk of relapse and persistence of symptoms is greater than the general population.

Clinical trials demonstrate that SSRIs lead to a modest improvement in glycemic control (SMD −0.38), but there is a mixed effect on glycemic control with other antidepressants ranging from hyperglycemic effects with tricyclic antidepressant medications to euglycemic or slightly hypoglycemic effects with serotonin–noradrenaline reuptake inhibitors. The diversity of effect implies that any finding of improved glycemic control with individual antidepressants should not be extrapolated to other untried antidepressants (Petrak et al. 2015).

The treatment of depression may lead to a change in the patient’s behavior and routine requiring a change in diabetes self-management. For example, should the patient’s appetite improve, more insulin may be required; by contrast, if the patient becomes more physically active, less may be needed.

Models of Care

Many healthcare systems are poorly equipped to manage comorbidity, particularly where this involves mental and physical illness. The Cartesian split of mind and body affects the delivery of care, leading healthcare professionals to consider one or other illness rather than making holistic decisions. In order to overcome this, the late Wayne Katon and colleagues in Seattle pioneered a model of care, known as “Collaborative Care” (Katon et al. 2010). This model encourages interdisciplinary cooperation between healthcare providers and shared decision making to facilitate appropriate provision of evidence-based treatment options, regular follow-up, self-management training, and support for people with comorbid diabetes and depression. The first study of this model showed improvements in depression symptoms but no change in glycemic control (Katon et al. 2004); however, in later studies, greater attention was paid to diabetes and blood pressure interventions, leading to improved biomedical outcomes as well as improved depressive symptoms (Katon et al. 2010). These models of care are also highly cost-effective (Simon et al. 2001, 2007).

Cognitive Function

Cognitive function can be defined as an intellectual process by which one becomes aware of, perceives, or comprehends ideas. It involves aspects of perception, thinking, reasoning, and remembering. Given the multifaceted nature of cognition, a full assessment of cognitive functioning requires a battery of psychometric tests to obtain an overview of an individual’s thinking skills. These tests assess how a person processes information, reasons, and learns in different ways. Cognitive function may be impaired globally or specific components of cognitive function may be affected.

Diabetes and Cognition

As cognitive and affective processes occur in highly linked regions of the brain, it is unsurprising that people with diabetes also experience cognitive deficits. These are relatively modest in most individuals but particularly affect general intelligence, psychomotor speed, and mental flexibility; on average performance in these domains is 0.3–0.7 standard deviations below the population mean (van den Berg et al. 2009; Brands et al. 2005; Palta et al. 2014) and has been likened to the change in cognitive function experienced after a 6–8 h jetlag (Fig. 1). The effects of diabetes on the brain appear to be age related with children and older adults being most vulnerable, with effects being attributable to both hypoglycemia and chronic hyperglycemia.
Fig. 1

Trajectories of cognitive dysfunction in type 1 and type 2 diabetes. (a) Cognitive dysfunction in people with type 1 diabetes. Cognitive decrements can be detected soon after onset of diabetes, often in childhood. The width of the shaded area indicates the uncertainty of the estimates, which is larger in older age groups (>65 years for type 1, >80 years for type 2 diabetes) because of the small number of studies. In young adults with type 1 diabetes, cognitive decrements are largest in individuals with an early diabetes onset (black arrow E), and smaller in individuals with a later onset (arrow L). Estimates of the diabetes-associated decrements do not clearly increase with age, consistent with slow progression of the decrements over time. However, some individuals, particularly those with severe microvascular complications (arrow C), might show accelerated decline. (b) In people with type 2 diabetes, estimates of mean cognitive decrements are likewise mostly independent of age. By contrast, the incidence of dementia (blue lines), which is increased in people with diabetes, is strongly dependent on age. (Reprinted from Koekkoek et al. (2015). Copyright (2015), with permission from Elsevier.)

Cognitive Dysfunction in Children and Adolescents

The age of onset of diabetes is a major determining factor for its effect on cognitive function in children. In those diagnosed before the age of 7 years, there is an increased risk of developing cognitive impairment across a range of cognitive domains, including attention, mental flexibility, psychomotor efficiency, learning, memory, problem-solving, and overall intelligence, and which start to be apparent within 2–3 years of diagnosis (Biessels et al. 2008; Gaudieri et al. 2008; Northam et al. 2001; Northam et al. 2006; Hershey et al. 2004). For children diagnosed after this age, the effect is much more modest and is confined primarily to overall intelligence and speed-related tasks, particularly those with a visual-perceptual aspect (Gaudieri et al. 2008). The cognitive impairment seen in children diagnosed before the age of 7 years persists into adulthood and manifests as lower IQ scores and slower information processing (Ferguson et al. 2005).

Academic achievement is lower in children with diabetes, irrespective of the age of diagnosis but this could relate to school absences or hypoglycemia interfering with learning as much as a direct effect on the developing brain (McCarthy et al. 2003). However, there is evidence from older studies that severe hypoglycemia causes neuropsychological deficits, particularly in children whose onset of diabetes occurred below the age of 6 years (Ryan et al. 1985; Rovet and Ehrlich 1999). Part of the problem is that younger children may not be able to describe their hypoglycemic symptoms thereby increasing the likelihood of prolonged and severe hypoglycemia. Some support for the hypoglycemia hypothesis comes from a meta-analysis of data from 441 children with recurrent severe hypoglycemia and 560 children without recurrent severe hypoglycemia (Blasetti et al. 2011). This study found that those with recurrent severe hypoglycemia had a modestly reduced performance in the domains of intelligence, language, and memory and learning but motor speed was unaffected (Blasetti et al. 2011). This effect appears to be limited to children, because there was no difference in the cognitive function in adults with type 1 diabetes in the Diabetes Control and Complications Trial with and without a history of severe hypoglycemia after an 18-years follow-up period (Jacobson et al. 2007). Similarly, the ACCORD-MIND study, which recruited adults with type 2 diabetes, found no difference in cognitive function after 20 months and 40 months follow-up between those treated intensively compared with standard care despite a 3-fold increase in the rates of hypoglycemia (Launer et al. 2011).

Cognitive Dysfunction in Adults with Diabetes

Adults with type 1 diabetes show modest nonprogressive cognitive deficits in measures of intelligence, attention, psychomotor speed, cognitive flexibility, and visual perception but measures of language, learning, and memory are unaffected despite long duration of diabetes (Brands et al. 2005, 2006). With the exception of “crystallized intelligence,” the affected domains require a rapid response indicating that diabetes affects mental agility rather than accuracy.

These changes are accompanied by structural changes that are characterized by reduced grey matter volumes in the frontal lobe and the adjacent supramarginal and postcentral gyri (Hughes et al. 2013). These MRI alterations have been linked to disrupted integrity of fiber tracts connecting the main cortical areas of the brain (Koekkoek et al. 2015). Functional studies have demonstrated altered cerebral perfusion with both decrease and increased blood flow (Kodl et al. 2008; Franc et al. 2011; van Duinkerken et al. 2012).

Adults with type 2 diabetes also show mild cognitive deficits affecting memory, processing speed, and executive function, which may lead to the individual to be less able to process unstructured information (van den Berg et al. 2009; Palta et al. 2014). Interestingly similar deficits are also present in people with newly diagnosed type 2 diabetes and impaired glucose regulation as well as those with features of the metabolic syndrome (Crichton et al. 2012; Lamport et al. 2009; Ruis et al. 2009). Type 2 diabetes is also associated with structural changes in the brain, characterized by a loss of grey matter loss in the medial temporal, anterior cingulate, and medial frontal lobes, while white matter is lost in the frontal and temporal regions (Moran et al. 2013).

The mechanisms underlying these changes are not fully understood although studies have not consistently demonstrated an association with cerebral small vessel disease (Koekkoek et al. 2015). The link between glycemic control and cognitive dysfunction in adults with diabetes is less obvious than for children. As previously described, hypoglycemia does not appear to be a major risk factor for cognitive decline in young- and middle-aged adults with diabetes but hyperglycemia appears to be more important, at least in the case of type 1 diabetes. A recent meta-analysis found a weak negative association between HbA1c and cognitive function, with HbA1c explaining at most 10–15% of the variance in cognitive function (Geijselaers et al. 2015).

The presence of microvascular complications, especially retinopathy and nephropathy, is associated with accelerated cognitive decline (Ryan et al. 2003; Jacobson et al. 2011). Cardiovascular disease and its risk factors are also associated with cognitive decline as they are in the general population but whether there is any specific interaction with diabetes is uncertain (Koekkoek et al. 2015; Ryan et al. 2003).

Dementia

The term dementia encompasses a broad category of brain disorders that lead to a gradual and progressive decline in cognitive function to the extent that an individual’s ability to function on a day-to-day is impaired. There are a number of types of dementia of which the most common are Alzheimer’s disease (50–70% of cases) and vascular dementia (up to 25%). Other causes of dementia are shown in Table 3. There has been a rapid increase in the prevalence of dementia in recent years, with a global prevalence of 22.7 million in 2015. The World Alzheimer Report predicts the prevalence of dementia to rise to 38.5 million by 2030 and 131.5 million by 2050. This increase is largely being driven by an ageing population as the prevalence rises from 1.4% in men and 1.9% in women aged 60–64 years to 33.4% in men and 48.3% in women aged >90 years. In 2013, approximately 1.7 million people died as a result of dementia.
Table 3

Causes of dementia in people with diabetes

Alzheimer’s disease

62%

Vascular dementia

17%

Mixed

10%

Lewy body dementia

4%

Parkinson’s disease

2%

Frontotemporal

2%

Other

3%

Diabetes and Dementia

The rate of cognitive decline in older individuals with type 2 diabetes appears to be up to 2-fold quicker than the general population and a number of studies have indicated that the risk of dementia is increased by approximately 50% in people with diabetes (Cheng et al. 2012). The commonest cause of dementia in people with diabetes is Alzheimer’s disease, which is increased by 46%, while vascular dementia is increased 2.38-fold (Cheng et al. 2012). It is estimated that the diabetes-attributable risk of dementia is 6–7%; in other words, 1 in 15 cases of dementia is attributable to diabetes (Koekkoek et al. 2015). An increased risk of dementia has also been reported in people with prediabetes and metabolic syndrome (Crichton et al. 2012). Diabetes worsens the outcome for people with dementia and is associated with 90% increase in mortality compared with those without diabetes (Zilkens et al. 2013).

Part of the explanation for this increased incidence of dementia ris k stems from a higher prevalence of risk factors for dementia among people with diabetes (Table 4). Many of these cardiovascular risk cluster in people with diabetes and those at risk of diabetes. Interestingly, glycemia per se appears to have little impact on the risk (Geijselaers et al. 2015). Only one study has linked elevated HbA1c with the risk of dementia and only in those with markedly elevated levels (10–12%, 86–108 mmol/mol). No association between fasting or postprandial glucose or measures of glucose variability with dementia has been found.
Table 4

Risk factors for Alzheimer’s disease and vascular dementia

Alzheimer’s disease

Vascular dementia

Dyslipidemia

Dyslipidemia

Smoking

Smoking

Hypertension

Hypertension

Obesity

Obesity

Physical inactivity

Atrial fibrillation

Depression

Previous coronary heart disease, stroke of transient ischemic event

Alcohol

 

Head injury

 

Unlike in younger adults, recurrent hypoglycemia is an important risk factor for cognitive decline in those with dementia (Whitmer et al. 2009; Punthakee et al. 2012). In a retrospective study of 16,667 older people with diabetes, a history of one, two, and three or more severe hypoglycemic episodes increased the risk of dementia increased by 26%, 80%, and 94%, respectively independent of glycemic control, medications, and other comorbidities (Whitmer et al. 2009). The relationship, however, appears to be bidirectional as cognitive dysfunction increases risk of hypoglycemia, thereby creating a vicious cycle.

Impaired insulin signalling in the brain may also play a role in the development of Alzheimer’s disease (Li et al. 2015). Briefly, the pathology of Alzheimer’s disease is characterized by the deposition of β-amyloid plaques and tangles in the brain (Turner et al. 2003; Niedowicz et al. 2011). β-amyloid is derived from the cleavage of amyloid precursor protein, an extracellular protein which is critical to neuron growth, survival, and post-injury repair. The formation of β-amyloid is regulated with several genes but is increased in ageing and by obesity and less prudent diet (Niedowicz et al. 2011). Insulin inhibits the production and accumulation of β-amyloid and so in situations where there is insulin deficiency or impaired action, β-amyloid accumulates (Li et al. 2015). Supporting this hypothesis is the observation of reduced brain insulin and its receptor in people with Alzheimer’s disease.

Clinical Implications of Dementia in People with Diabetes

Prevention of Dementia

Several large randomized controlled trials in both type 1 diabetes and type 2 diabetes have investigated whether improved glycemic control can reduce the risk of dementia. To date, no difference in the rate of cognitive decline, cognitive performance, or incidence of dementia has been seen in those with tighter glycemic control (Jacobson et al. 2007; Launer et al. 2011; Koekkoek et al. 2012; de Galan et al. 2009). The ACCORD-MIND study also assessed whether better blood pressure and lipid control could improve cognition but again no benefit was seen in those treated with a combination of statin and fibrate while intensive blood pressure lowering actually accelerated brain atrophy (Williamson et al. 2014).

Diagnosis of Dementia

Once dementia develops, the person’s ability to self-manage their diabetes progressively deteriorates. Exercise and diet appear to be particularly affected but the real danger lies in the increased risk of adverse events in people taking hypoglycemic drugs. The risk of hypoglycemia is exacerbated further because dementia may impair language and lead to disorientation and personality changes, all of which may mimic the symptoms of hypoglycemia (Sinclair et al. 2010). When lack of engagement with self-management occurs in older people, clinicians should consider cognitive dysfunction as a cause.

A risk score which includes age, microvascular disease, diabetic foot, cerebrovascular disease, cardiovascular disease, acute metabolic events, depression, and education has been developed to help predict the risk of developing dementia. In a prospective study over 10 years, the risk of developing dementia was 5.3% in those with the lowest score compared with 73.3% for the top scores (Exalto et al. 2013). Other authors have advocated the use of the easy-to-perform Mini Cog test as a simple screening tool for dementia. This test has a sensitivity of 86.4% and a specificity of 91.1% (Sinclair et al. 2013).

A formal diagnosis of dementia involves a combination of history, examination, including tests of mental investigation and investigation. It is important to obtain corroborating information from a friend or relative who knows the patient well. Unfortunately, the diagnosis is not always straightforward particularly in the early stages and time may be an important diagnostic tool.

Treatment of Dementia

A detailed description of the treatment of Alzheimer’s disease is beyond the scope of this chapter as treatment is usually initiated in specialist memory clinics. The most commonly used drugs are the acetylcholinesterase inhibitors, such as donepezil, which are licensed for the treatment of mild to moderate Alzheimer’s disease (Cummings et al. 2015). This class of agents can cause bradycardia and exacerbate symptoms of gastric and duodenal ulcers, precipitate bronchospasm and may cause convulsions. Dizziness, headache, and nausea are the most common side effects with abdominal disturbance and nightmares also commonly reported. Because of the cardiovascular effects, they should be used with caution in those whose baseline pulse is <60 beats per minute. An ECG is recommended if the pulse is <70 beats per minute or if it is irregular.

Given the relationship between cerebral insulin action and Alzheimer’s disease, the use of several antidiabetes drugs has been examined in people with dementia (Koekkoek et al. 2015; Li et al. 2015). Small studies have suggested that intranasal insulin improves delayed memory and cognitive function (Reger et al. 2008; Craft et al. 2012) but the results of larger on-going trials people with Alzheimer’s disease, with and without diabetes are awaited (Koekkoek et al. 2015). Studies of thiazolidinediones have shown mixed effects on cognitive function but a possible benefit has been reported in those whose genotype is APOE-ε4-negative (Watson et al. 2005; Risner et al. 2006; Gold et al. 2010). As well as insulin, GLP-1 also appears to play an important role in the control of synaptic plasticity and in some forms of memory formation and two trials of GLP-1 receptor agonists are on-going (Li et al. 2015).

Management of Diabetes in Someone with Dementia

As dementia affects self-management, it is important that glycemic targets are adjusted appropriately taking into account overall health and life expectancy. Several guidelines now recommend HbA1c targets of <8.5% (69 mmol/mol) for older dependent people with dementia (Sinclair et al. 2012). In these individuals, avoidance of symptomatic hypoglycemia is more important than tight glycemic control, which may reduce the quality of life. Glycemic targets should be regularly reviewed and medications as appropriate.

Many older people with diabetes and dementia are overtreated with multiple drugs. In a retrospective cohort study of 15,880 people with type 2 diabetes and dementia from the Veterans Affairs Healthcare System, 52% of participants had an HbA1c < 7% (53 mmol/mol) and within this group, 75% were treated either with sulfonylureas, insulin, or both placing them at a high risk of hypoglycemia (Thorpe et al. 2015). Declining weight, malnutrition, and frailty may lead to a reduced need for antidiabetes medications, and these have been safely withdrawn in several studies (Sjoblom et al. 2008) without a deterioration of their glycemic control (Abdelhafiz et al. 2014). Drugs with a lower risk of hypoglycemia should be preferentially used.

Conclusions

This chapter has highlighted some of the many and various ways in which diabetes interacts with the brain. It is clear that these connections can have a major impact on diabetes outcomes, and health professionals who work with people with diabetes require good knowledge and awareness of these issues to be able to provide optimal care. There is clearly also a great need for closer working between diabetes services and mental health services while further research on these topics is also required.

Notes

Acknowledgments

Richard Holt has received fees for lecturing and consultancy from the following companies: Eli Lilly, Janssen, Lundbeck, Novo Nordisk, Novartis, Otsuka, Sanofi, Sunovion, Takeda, and MSD.

References

  1. Abdelhafiz AH, Chakravorty P, Gupta S, Haque A, Sinclair AJ. Can hypoglycaemic medications be withdrawn in older people with type 2 diabetes? Int J Clin Pract. 2014;68(6):790–2.PubMedCrossRefGoogle Scholar
  2. Adriaanse MC, Snoek FJ, Dekker JM, Spijkerman AM, Nijpels G, Twisk JW, et al. No substantial psychological impact of the diagnosis of type 2 diabetes following targeted population screening: the Hoorn Screening Study. Diabet Med. 2004;21(9):992–8.PubMedCrossRefGoogle Scholar
  3. Aikens JE, Perkins DW, Piette JD, Lipton B. Association between depression and concurrent type 2 diabetes outcomes varies by diabetes regimen. Diabet Med. 2008;25(11):1324–9.PubMedGoogle Scholar
  4. Ali S, Stone MA, Peters JL, Davies MJ, Khunti K. The prevalence of co-morbid depression in adults with type 2 diabetes: a systematic review and meta-analysis. Diabet Med. 2006;23(11):1165–73.PubMedCrossRefGoogle Scholar
  5. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed. Washington, DC: American Psychiatric Association; 2005.Google Scholar
  6. Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care. 2001;24(6):1069–78.CrossRefPubMedGoogle Scholar
  7. Barnard KD, Skinner TC, Peveler R. The prevalence of co-morbid depression in adults with type 1 diabetes: systematic literature review. Diabet Med. 2006;23(4):445–8.PubMedCrossRefGoogle Scholar
  8. Barnard K, Peveler RC, Holt RI. Antidepressant medication as a risk factor for type 2 diabetes and impaired glucose regulation: systematic review. Diabetes Care. 2013;36(10):3337–45.PubMedPubMedCentralCrossRefGoogle Scholar
  9. Baumeister H, Hutter N, Bengel J. Psychological and pharmacological interventions for depression in patients with diabetes mellitus and depression. Cochrane Database Syst Rev. 2012;12:CD008381.PubMedGoogle Scholar
  10. Biessels GJ, Deary IJ, Ryan CM. Cognition and diabetes: a lifespan perspective. Lancet Neurol. 2008;7(2):184–90.PubMedCrossRefPubMedCentralGoogle Scholar
  11. Blasetti A, Chiuri RM, Tocco AM, Di GC, Mattei PA, Ballone E, et al. The effect of recurrent severe hypoglycemia on cognitive performance in children with type 1 diabetes: a meta-analysis. J Child Neurol. 2011;26(11):1383–91.PubMedCrossRefPubMedCentralGoogle Scholar
  12. Brands AM, Biessels GJ, de Haan EH, Kappelle LJ, Kessels RP. The effects of type 1 diabetes on cognitive performance: a meta-analysis. Diabetes Care. 2005;28(3):726–35.PubMedCrossRefPubMedCentralGoogle Scholar
  13. Brands AM, Kessels RP, Hoogma RP, Henselmans JM, van der Beek Boter JW, Kappelle LJ, et al. Cognitive performance, psychological well-being, and brain magnetic resonance imaging in older patients with type 1 diabetes. Diabetes. 2006;55(6):1800–6.PubMedCrossRefPubMedCentralGoogle Scholar
  14. Brenner AB, Zimmerman MA, Bauermeister JA, Caldwell CH. The physiological expression of living in disadvantaged neighborhoods for youth. J Youth Adolesc. 2013;42(6):792–806.PubMedCrossRefPubMedCentralGoogle Scholar
  15. Browning CR, Cagney KA, Iveniuk J. Neighborhood stressors and cardiovascular health: crime and C-reactive protein in Dallas, USA. Soc Sci Med. 2012;75(7):1271–9.PubMedCrossRefGoogle Scholar
  16. Broyles ST, Staiano AE, Drazba KT, Gupta AK, Sothern M, Katzmarzyk PT. Elevated C-reactive protein in children from risky neighborhoods: evidence for a stress pathway linking neighborhoods and inflammation in children. PLoS One. 2012;7(9):e45419.PubMedPubMedCentralCrossRefGoogle Scholar
  17. Carney RM, Freedland KE. Depression, mortality, and medical morbidity in patients with coronary heart disease. Biol Psychiatry. 2003;54(3):241–7.PubMedCrossRefGoogle Scholar
  18. Carper MM, Traeger L, Gonzalez JS, Wexler DJ, Psaros C, Safren SA. The differential associations of depression and diabetes distress with quality of life domains in type 2 diabetes. J Behav Med. 2014;37(3):501–10.PubMedCrossRefGoogle Scholar
  19. Champaneri S, Wand GS, Malhotra SS, Casagrande SS, Golden SH. Biological basis of depression in adults with diabetes. Curr Diab Rep. 2010;10(6):396–405.PubMedCrossRefGoogle Scholar
  20. Cheng G, Huang C, Deng H, Wang H. Diabetes as a risk factor for dementia and mild cognitive impairment: a meta-analysis of longitudinal studies. Intern Med J. 2012;42(5):484–91.PubMedCrossRefPubMedCentralGoogle Scholar
  21. Cleal B, Panton UH, Willaing I, Holt RI. Diabetes and depression in Denmark 1996–2010: national data stratified by occupational status and annual income. Diabet Med. 2017;34(1):108–14.PubMedCrossRefPubMedCentralGoogle Scholar
  22. Craft S, Baker LD, Montine TJ, Minoshima S, Watson GS, Claxton A, et al. Intranasal insulin therapy for Alzheimer disease and amnestic mild cognitive impairment: a pilot clinical trial. Arch Neurol. 2012;69(1):29–38.PubMedCrossRefGoogle Scholar
  23. Crichton GE, Elias MF, Buckley JD, Murphy KJ, Bryan J, Frisardi V. Metabolic syndrome, cognitive performance, and dementia. J Alzheimers Dis. 2012;30(Suppl 2):S77–87.PubMedCrossRefPubMedCentralGoogle Scholar
  24. Cummings JL, Isaacson RS, Schmitt FA, Velting DM. A practical algorithm for managing Alzheimer’s disease: what, when, and why? Ann Clin Transl Neurol. 2015;2(3):307–23.PubMedPubMedCentralCrossRefGoogle Scholar
  25. Dantzer R, O’Connor JC, Freund GG, Johnson RW, Kelley KW. From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci. 2008;9(1):46–56.PubMedPubMedCentralCrossRefGoogle Scholar
  26. de Galan BE, Zoungas S, Chalmers J, Anderson C, Dufouil C, Pillai A, et al. Cognitive function and risks of cardiovascular disease and hypoglycaemia in patients with type 2 diabetes: the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial. Diabetologia. 2009;52(11):2328–36.PubMedCrossRefGoogle Scholar
  27. de Groot M, Anderson R, Freedland KE, Clouse RE, Lustman PJ. Association of depression and diabetes complications: a meta-analysis. Psychosom Med. 2001;63(4):619–30.PubMedCrossRefPubMedCentralGoogle Scholar
  28. de Vet E, de Ridder DT, de Wit JB. Environmental correlates of physical activity and dietary behaviours among young people: a systematic review of reviews. Obes Rev. 2011;12(5):e130–42.PubMedCrossRefPubMedCentralGoogle Scholar
  29. Do DP, Diez Roux AV, Hajat A, Auchincloss AH, Merkin SS, Ranjit N, et al. Circadian rhythm of cortisol and neighborhood characteristics in a population-based sample: the Multi-Ethnic Study of Atherosclerosis. Health Place. 2011;17(2):625–32.PubMedPubMedCentralCrossRefGoogle Scholar
  30. Dulin-Keita A, Casazza K, Fernandez JR, Goran MI, Gower B. Do neighbourhoods matter? Neighbourhood disorder and long-term trends in serum cortisol levels. J Epidemiol Community Health. 2012;66(1):24–9.PubMedCrossRefGoogle Scholar
  31. Egede LE, Nietert PJ, Zheng D. Depression and all-cause and coronary heart disease mortality among adults with and without diabetes. Diabetes Care. 2005;28(6):1339–45.PubMedCrossRefGoogle Scholar
  32. Exalto LG, Biessels GJ, Karter AJ, Huang ES, Katon WJ, Minkoff JR, et al. Risk score for prediction of 10 year dementia risk in individuals with type 2 diabetes: a cohort study. Lancet Diabetes Endocrinol. 2013;1(3):183–90.PubMedPubMedCentralCrossRefGoogle Scholar
  33. Ferguson SC, Blane A, Wardlaw J, Frier BM, Perros P, McCrimmon RJ, et al. Influence of an early-onset age of type 1 diabetes on cerebral structure and cognitive function. Diabetes Care. 2005;28(6):1431–7.PubMedCrossRefGoogle Scholar
  34. First MB, Spitzer RL, Gibbon M, Williams JB. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, research version, patient edition. (SCID-I/P). New York: Biometrics Research, New York State Psychiatric Institute; 2002.Google Scholar
  35. Fisher L, Glasgow RE, Strycker LA. The relationship between diabetes distress and clinical depression with glycemic control among patients with type 2 diabetes. Diabetes Care. 2010;33(5):1034–6.PubMedPubMedCentralCrossRefGoogle Scholar
  36. Fisher L, Hessler DM, Polonsky WH, Masharani U, Peters AL, Blumer I, et al. Prevalence of depression in type 1 diabetes and the problem of over-diagnosis. Diabet Med. 2016;33(11):1590–7.  https://doi.org/10.1111/dme.12973.CrossRefPubMedGoogle Scholar
  37. Franc DT, Kodl CT, Mueller BA, Muetzel RL, Lim KO, Seaquist ER. High connectivity between reduced cortical thickness and disrupted white matter tracts in long-standing type 1 diabetes. Diabetes. 2011;60(1):315–9.PubMedCrossRefGoogle Scholar
  38. Gangwisch JE. Epidemiological evidence for the links between sleep, circadian rhythms and metabolism. Obes Rev. 2009;10(Suppl 2):37–45.PubMedPubMedCentralCrossRefGoogle Scholar
  39. Gaudieri PA, Chen R, Greer TF, Holmes CS. Cognitive function in children with type 1 diabetes: a meta-analysis. Diabetes Care. 2008;31(9):1892–7.PubMedPubMedCentralCrossRefGoogle Scholar
  40. Geijselaers SL, Sep SJ, Stehouwer CD, Biessels GJ. Glucose regulation, cognition, and brain MRI in type 2 diabetes: a systematic review. Lancet Diabetes Endocrinol. 2015;3(1):75–89.PubMedCrossRefGoogle Scholar
  41. Gilbody S, Sheldon T, House A. Screening and case-finding instruments for depression: a meta-analysis. CMAJ. 2008;178(8):997–1003.PubMedPubMedCentralCrossRefGoogle Scholar
  42. Gold M, Alderton C, Zvartau-Hind M, Egginton S, Saunders AM, Irizarry M, et al. Rosiglitazone monotherapy in mild-to-moderate Alzheimer’s disease: results from a randomized, double-blind, placebo-controlled phase III study. Dement Geriatr Cogn Disord. 2010;30(2):131–46.PubMedPubMedCentralCrossRefGoogle Scholar
  43. Goldney RD, Phillips PJ, Fisher LJ, Wilson DH. Diabetes, depression, and quality of life: a population study. Diabetes Care. 2004;27(5):1066–70.PubMedCrossRefGoogle Scholar
  44. Gonzalez JS, Peyrot M, McCarl LA, Collins EM, Serpa L, Mimiaga MJ, et al. Depression and diabetes treatment nonadherence: a meta-analysis. Diabetes Care. 2008;31(12):2398–403.PubMedPubMedCentralCrossRefGoogle Scholar
  45. Hermanns N, Kulzer B, Krichbaum M, Kubiak T, Haak T. Affective and anxiety disorders in a German sample of diabetic patients: prevalence, comorbidity and risk factors. Diabet Med. 2005;22(3):293–300.PubMedCrossRefGoogle Scholar
  46. Hermanns N, Scheff C, Kulzer B, Weyers P, Pauli P, Kubiak T, et al. Association of glucose levels and glucose variability with mood in type 1 diabetic patients. Diabetologia. 2007;50(5):930–3.PubMedCrossRefGoogle Scholar
  47. Hershey T, Lillie R, Sadler M, White NH. A prospective study of severe hypoglycemia and long-term spatial memory in children with type 1 diabetes. Pediatr Diabetes. 2004;5(2):63–71.PubMedCrossRefGoogle Scholar
  48. Hislop AL, Fegan PG, Schlaeppi MJ, Duck M, Yeap BB. Prevalence and associations of psychological distress in young adults with type 1 diabetes. Diabet Med. 2008;25(1):91–6.PubMedCrossRefGoogle Scholar
  49. Ho N, Sommers MS, Lucki I. Effects of diabetes on hippocampal neurogenesis: links to cognition and depression. Neurosci Biobehav Rev. 2013;37(8):1346–62.PubMedPubMedCentralCrossRefGoogle Scholar
  50. Holt RI, Katon WJ. Dialogue on diabetes and depression: dealing with the double burden of co-morbidity. J Affect Disord. 2012;142:S1–3.PubMedCrossRefGoogle Scholar
  51. Holt RI, van der Feltz-Cornelis CM. Key concepts in screening for depression in people with diabetes. J Affect Disord. 2012;142:S72–9.PubMedCrossRefGoogle Scholar
  52. Holt RI, de Groot M, Golden SH. Diabetes and depression. Curr Diab Rep. 2014;14(6):491.PubMedPubMedCentralCrossRefGoogle Scholar
  53. Hughes TM, Ryan CM, Aizenstein HJ, Nunley K, Gianaros PJ, Miller R, et al. Frontal gray matter atrophy in middle aged adults with type 1 diabetes is independent of cardiovascular risk factors and diabetes complications. J Diabetes Complicat. 2013;27(6):558–64.PubMedCrossRefGoogle Scholar
  54. International Diabetes Federation. Global guideline for type 2 diabetes. 2012. http://www.idf.org/guideline-type-2-diabetes. Last accessed 17 Sept 2016.
  55. Ismail K, Winkley K, Rabe-Hesketh S. Systematic review and meta-analysis of randomised controlled trials of psychological interventions to improve glycaemic control in patients with type 2 diabetes. Lancet. 2004;363(9421):1589–97.PubMedCrossRefGoogle Scholar
  56. Jacobson AM, de Groot M, Samson JA. The effects of psychiatric disorders and symptoms on quality of life in patients with type I and type II diabetes mellitus. Qual Life Res. 1997;6(1):11–20.PubMedCrossRefGoogle Scholar
  57. Jacobson AM, Musen G, Ryan CM, Silvers N, Cleary P, Waberski B, et al. Long-term effect of diabetes and its treatment on cognitive function. N Engl J Med. 2007;356(18):1842–52.PubMedCrossRefGoogle Scholar
  58. Jacobson AM, Ryan CM, Cleary PA, Waberski BH, Weinger K, Musen G, et al. Biomedical risk factors for decreased cognitive functioning in type 1 diabetes: an 18 year follow-up of the Diabetes Control and Complications Trial (DCCT) cohort. Diabetologia. 2011;54(2):245–55.PubMedCrossRefGoogle Scholar
  59. Karb RA, Elliott MR, Dowd JB, Morenoff JD. Neighborhood-level stressors, social support, and diurnal patterns of cortisol: the Chicago Community Adult Health Study. Soc Sci Med. 2012;75(6):1038–47.PubMedPubMedCentralCrossRefGoogle Scholar
  60. Katon WJ, Von Korff M, Lin EH, Simon G, Ludman E, Russo J, et al. The Pathways Study: a randomized trial of collaborative care in patients with diabetes and depression. Arch Gen Psychiatry. 2004;61(10):1042–9.CrossRefPubMedGoogle Scholar
  61. Katon WJ, Lin EH, Von Korff M, Ciechanowski P, Ludman EJ, Young B, et al. Collaborative care for patients with depression and chronic illnesses. N Engl J Med. 2010;363(27):2611–20.PubMedPubMedCentralCrossRefGoogle Scholar
  62. Katona C, Peveler R, Dowrick C, Wessely S, Feinmann C, Gask L, et al. Pain symptoms in depression: definition and clinical significance. Clin Med. 2005;5(4):390–5.CrossRefGoogle Scholar
  63. Knol MJ, Twisk JW, Beekman AT, Heine RJ, Snoek FJ, Pouwer F. Depression as a risk factor for the onset of type 2 diabetes mellitus. A meta-analysis. Diabetologia. 2006;49(5):837–45.PubMedCrossRefGoogle Scholar
  64. Kodl CT, Franc DT, Rao JP, Anderson FS, Thomas W, Mueller BA, et al. Diffusion tensor imaging identifies deficits in white matter microstructure in subjects with type 1 diabetes that correlate with reduced neurocognitive function. Diabetes. 2008;57(11):3083–9.PubMedPubMedCentralCrossRefGoogle Scholar
  65. Koekkoek PS, Ruis C, van den Donk M, Biessels GJ, Gorter KJ, Kappelle LJ, et al. Intensive multifactorial treatment and cognitive functioning in screen-detected type 2 diabetes – the ADDITION-Netherlands study: a cluster-randomized trial. J Neurol Sci. 2012;314(1–2):71–7.PubMedCrossRefGoogle Scholar
  66. Koekkoek PS, Kappelle LJ, van den Berg E, Rutten GE, Biessels GJ. Cognitive function in patients with diabetes mellitus: guidance for daily care. Lancet Neurol. 2015;14(3):329–40.PubMedCrossRefGoogle Scholar
  67. Kovacs M, Mukerji P, Drash A, Iyengar S. Biomedical and psychiatric risk factors for retinopathy among children with IDDM. Diabetes Care. 1995;18(12):1592–9.PubMedCrossRefGoogle Scholar
  68. Lamport DJ, Lawton CL, Mansfield MW, Dye L. Impairments in glucose tolerance can have a negative impact on cognitive function: a systematic research review. Neurosci Biobehav Rev. 2009;33(3):394–413.PubMedCrossRefGoogle Scholar
  69. Launer LJ, Miller ME, Williamson JD, Lazar RM, Gerstein HC, Murray AM, et al. Effects of intensive glucose lowering on brain structure and function in people with type 2 diabetes (ACCORD MIND): a randomised open-label substudy. Lancet Neurol. 2011;10(11):969–77.PubMedPubMedCentralCrossRefGoogle Scholar
  70. Li C, Ford ES, Strine TW, Mokdad AH. Prevalence of depression among U.S. adults with diabetes: findings from the 2006 behavioral risk factor surveillance system. Diabetes Care. 2008;31(1):105–7.PubMedCrossRefGoogle Scholar
  71. Li X, Song D, Leng SX. Link between type 2 diabetes and Alzheimer’s disease: from epidemiology to mechanism and treatment. Clin Interv Aging. 2015;10:549–60.PubMedPubMedCentralCrossRefGoogle Scholar
  72. Lustman PJ, Anderson RJ, Freedland KE, de Groot M, Carney RM, Clouse RE. Depression and poor glycemic control: a meta-analytic review of the literature. Diabetes Care. 2000;23(7):934–42.PubMedCrossRefGoogle Scholar
  73. Lyoo IK, Yoon SJ, Musen G, Simonson DC, Weinger K, Bolo N, et al. Altered prefrontal glutamate-glutamine-gamma-aminobutyric acid levels and relation to low cognitive performance and depressive symptoms in type 1 diabetes mellitus. Arch Gen Psychiatry. 2009;66(8):878–87.PubMedCrossRefGoogle Scholar
  74. Matcham F, Rayner L, Steer S, Hotopf M. The prevalence of depression in rheumatoid arthritis: a systematic review and meta-analysis. Rheumatology (Oxford). 2013;52(12):2136–48.CrossRefGoogle Scholar
  75. McCarthy AM, Lindgren S, Mengeling MA, Tsalikian E, Engvall J. Factors associated with academic achievement in children with type 1 diabetes. Diabetes Care. 2003;26(1):112–7.PubMedCrossRefGoogle Scholar
  76. McMartin SE, Jacka FN, Colman I. The association between fruit and vegetable consumption and mental health disorders: evidence from five waves of a national survey of Canadians. Prev Med. 2013;56(3–4):225–30.PubMedCrossRefGoogle Scholar
  77. Mezuk B, Eaton WW, Albrecht S, Golden SH. Depression and type 2 diabetes over the lifespan: a meta-analysis. Diabetes Care. 2008;31(12):2383–90.PubMedPubMedCentralCrossRefGoogle Scholar
  78. Mitchell AJ, Malone D, Doebbeling CC. Quality of medical care for people with and without comorbid mental illness and substance misuse: systematic review of comparative studies. Br J Psychiatry. 2009;194(6):491–9.PubMedCrossRefGoogle Scholar
  79. Mommersteeg PM, Herr R, Pouwer F, Holt RI, Loerbroks A. The association between diabetes and an episode of depressive symptoms in the 2002 World Health Survey: an analysis of 231,797 individuals from 47 countries. Diabet Med. 2013;30(6):e208–14.PubMedCrossRefGoogle Scholar
  80. Moran C, Phan TG, Chen J, Blizzard L, Beare R, Venn A, et al. Brain atrophy in type 2 diabetes: regional distribution and influence on cognition. Diabetes Care. 2013;36(12):4036–42.PubMedPubMedCentralCrossRefGoogle Scholar
  81. Murray CJ, Lopez AD. Alternative projections of mortality and disability by cause 1990–2020: global burden of disease study. Lancet. 1997;349(9064):1498–504.PubMedCrossRefGoogle Scholar
  82. Musselman DL, Betan E, Larsen H, Phillips LS. Relationship of depression to diabetes types 1 and 2: epidemiology, biology, and treatment. Biol Psychiatry. 2003;54(3):317–29.PubMedCrossRefGoogle Scholar
  83. National Institute for Health and Care Excellence. Type 1 diabetes in adults: diagnosis and management, NICE guidelines (NG17). 2015a. https://www.nice.org.uk/guidance/ng17. Last accessed 17 Sept 2016.
  84. National Institute for Health and Care Excellence. Type 2 diabetes in adults: management. NICE guidelines (NG28). 2015b. https://www.nice.org.uk/guidance/ng28. Last accessed 17 Sept 2016.
  85. Nefs G, Pouwer F, Denollet J, Pop V. The course of depressive symptoms in primary care patients with type 2 diabetes: results from the Diabetes, Depression, Type D Personality Zuidoost-Brabant (DiaDDZoB) Study. Diabetologia. 2012;55(3):608–16.PubMedCrossRefGoogle Scholar
  86. Niedowicz DM, Nelson PT, Murphy MP. Alzheimer’s disease: pathological mechanisms and recent insights. Curr Neuropharmacol. 2011;9(4):674–84.PubMedPubMedCentralCrossRefGoogle Scholar
  87. Northam EA, Anderson PJ, Jacobs R, Hughes M, Warne GL, Werther GA. Neuropsychological profiles of children with type 1 diabetes 6 years after disease onset. Diabetes Care. 2001;24(9):1541–6.PubMedCrossRefGoogle Scholar
  88. Northam EA, Rankins D, Cameron FJ. Therapy insight: the impact of type 1 diabetes on brain development and function. Nat Clin Pract Neurol. 2006;2(2):78–86.PubMedCrossRefGoogle Scholar
  89. Nouwen A, Winkley K, Twisk J, Lloyd CE, Peyrot M, Ismail K, et al. Type 2 diabetes mellitus as a risk factor for the onset of depression: a systematic review and meta-analysis. Diabetologia. 2010;53(12):2480–6.PubMedPubMedCentralCrossRefGoogle Scholar
  90. Nouwen A, Nefs G, Caramlau I, Connock M, Winkley K, Lloyd CE, et al. Prevalence of depression in individuals with impaired glucose metabolism or undiagnosed diabetes: a systematic review and meta-analysis of the European Depression in Diabetes (EDID) Research Consortium. Diabetes Care. 2011;34(3):752–62.PubMedPubMedCentralCrossRefGoogle Scholar
  91. Palta P, Schneider AL, Biessels GJ, Touradji P, Hill-Briggs F. Magnitude of cognitive dysfunction in adults with type 2 diabetes: a meta-analysis of six cognitive domains and the most frequently reported neuropsychological tests within domains. J Int Neuropsychol Soc. 2014;20(3):278–91.PubMedPubMedCentralCrossRefGoogle Scholar
  92. Park M, Katon WJ, Wolf FM. Depression and risk of mortality in individuals with diabetes: a meta-analysis and systematic review. Gen Hosp Psychiatry. 2013;35(3):217–25.PubMedPubMedCentralCrossRefGoogle Scholar
  93. Payne ME, Steck SE, George RR, Steffens DC. Fruit, vegetable, and antioxidant intakes are lower in older adults with depression. J Acad Nutr Diet. 2012;112(12):2022–7.PubMedPubMedCentralCrossRefGoogle Scholar
  94. Petrak F, Hardt J, Wittchen HU, Kulzer B, Hirsch A, Hentzelt F, et al. Prevalence of psychiatric disorders in an onset cohort of adults with type 1 diabetes. Diabetes Metab Res Rev. 2003;19(3):216–22.PubMedCrossRefPubMedCentralGoogle Scholar
  95. Petrak F, Baumeister H, Skinner TC, Brown A, Holt RI. Depression and diabetes: treatment and health-care delivery. Lancet Diabetes Endocrinol. 2015;3(6):472–85.PubMedCrossRefPubMedCentralGoogle Scholar
  96. Pibernik-Okanovic M, Roglic G, Prasek M, Metelko Z. Emotional adjustment and metabolic control in newly diagnosed diabetic persons. Diabetes Res Clin Pract. 1996;34(2):99–105.PubMedCrossRefPubMedCentralGoogle Scholar
  97. Polonsky WH, Anderson BJ, Lohrer PA, Welch G, Jacobson AM, Aponte JE, et al. Assessment of diabetes-related distress. Diabetes Care. 1995;18(6):754–60.PubMedCrossRefPubMedCentralGoogle Scholar
  98. Pouwer F, Tack CJ, Geelhoed-Duijvestijn PH, Bazelmans E, Beekman AT, Heine RJ, et al. Limited effect of screening for depression with written feedback in outpatients with diabetes mellitus: a randomised controlled trial. Diabetologia. 2011;54(4):741–8.PubMedPubMedCentralCrossRefGoogle Scholar
  99. Punthakee Z, Miller ME, Launer LJ, Williamson JD, Lazar RM, Cukierman-Yaffee T, et al. Poor cognitive function and risk of severe hypoglycemia in type 2 diabetes: post hoc epidemiologic analysis of the ACCORD trial. Diabetes Care. 2012;35(4):787–93.PubMedPubMedCentralCrossRefGoogle Scholar
  100. Reger MA, Watson GS, Green PS, Wilkinson CW, Baker LD, Cholerton B, et al. Intranasal insulin improves cognition and modulates beta-amyloid in early AD. Neurology. 2008;70(6):440–8.PubMedCrossRefPubMedCentralGoogle Scholar
  101. Risner ME, Saunders AM, Altman JF, Ormandy GC, Craft S, Foley IM, et al. Efficacy of rosiglitazone in a genetically defined population with mild-to-moderate Alzheimer’s disease. Pharmacogenomics J. 2006;6(4):246–54.PubMedCrossRefPubMedCentralGoogle Scholar
  102. Rovet JF, Ehrlich RM. The effect of hypoglycemic seizures on cognitive function in children with diabetes: a 7-year prospective study. J Pediatr. 1999;134(4):503–6.PubMedCrossRefPubMedCentralGoogle Scholar
  103. Roy MS, Roy A, Affouf M. Depression is a risk factor for poor glycemic control and retinopathy in African-Americans with type 1 diabetes. Psychosom Med. 2007;69(6):537–42.PubMedCrossRefPubMedCentralGoogle Scholar
  104. Roy T, Lloyd CE, Pouwer F, Holt RI, Sartorius N. Screening tools used for measuring depression among people with type 1 and type 2 diabetes: a systematic review. Diabet Med. 2012;29(2):164–75.PubMedCrossRefPubMedCentralGoogle Scholar
  105. Ruis C, Biessels GJ, Gorter KJ, van den Donk M, Kappelle LJ, Rutten GE. Cognition in the early stage of type 2 diabetes. Diabetes Care. 2009;32(7):1261–5.PubMedPubMedCentralCrossRefGoogle Scholar
  106. Ryan C, Vega A, Drash A. Cognitive deficits in adolescents who developed diabetes early in life. Pediatrics. 1985;75(5):921–7.PubMedPubMedCentralGoogle Scholar
  107. Ryan CM, Geckle MO, Orchard TJ. Cognitive efficiency declines over time in adults with type 1 diabetes: effects of micro- and macrovascular complications. Diabetologia. 2003;46(7):940–8.PubMedCrossRefPubMedCentralGoogle Scholar
  108. Scollan-Koliopoulos M, Herrera I, Romano K, Gregory C, Rapp K, Bleich D. Healthcare technician delivered screening of adults with diabetes to improve primary care provider recognition of depression. J Family Med Prim Care. 2012;1(2):97–102.PubMedPubMedCentralCrossRefGoogle Scholar
  109. Sellick SM, Crooks DL. Depression and cancer: an appraisal of the literature for prevalence, detection, and practice guideline development for psychological interventions. Psychooncology. 1999;8(4):315–33.PubMedCrossRefPubMedCentralGoogle Scholar
  110. Serretti A, Mandelli L. Antidepressants and body weight: a comprehensive review and meta-analysis. J Clin Psychiatry. 2010;71(10):1259–72.PubMedCrossRefGoogle Scholar
  111. Simon GE, Katon WJ, VonKorff M, Unutzer J, Lin EH, Walker EA, et al. Cost-effectiveness of a collaborative care program for primary care patients with persistent depression. Am J Psychiatry. 2001;158(10):1638–44.PubMedCrossRefGoogle Scholar
  112. Simon GE, Katon WJ, Lin EH, Rutter C, Manning WG, Von KM, et al. Cost-effectiveness of systematic depression treatment among people with diabetes mellitus. Arch Gen Psychiatry. 2007;64(1):65–72.PubMedCrossRefGoogle Scholar
  113. Sinclair AJ, Armes DG, Randhawa G, Bayer AJ. Caring for older adults with diabetes mellitus: characteristics of carers and their prime roles and responsibilities. Diabet Med. 2010;27(9):1055–9.PubMedCrossRefGoogle Scholar
  114. Sinclair A, Morley JE, Rodriguez-Manas L, Paolisso G, Bayer T, Zeyfang A, et al. Diabetes mellitus in older people: position statement on behalf of the International Association of Gerontology and Geriatrics (IAGG), the European Diabetes Working Party for Older People (EDWPOP), and the International Task Force of Experts in Diabetes. J Am Med Dir Assoc. 2012;13(6):497–502.PubMedCrossRefGoogle Scholar
  115. Sinclair AJ, Gadsby R, Hillson R, Forbes A, Bayer AJ. Brief report: use of the mini-cog as a screening tool for cognitive impairment in diabetes in primary care. Diabetes Res Clin Pract. 2013;100(1):e23–5.PubMedCrossRefGoogle Scholar
  116. Sjoblom P, Tengblad A, Lofgren UB, Lannering C, Anderberg N, Rosenqvist U, et al. Can diabetes medication be reduced in elderly patients? An observational study of diabetes drug withdrawal in nursing home patients with tight glycaemic control. Diabetes Res Clin Pract. 2008;82(2):197–202.PubMedCrossRefGoogle Scholar
  117. Skinner ML, Shirtcliff EA, Haggerty KP, Coe CL, Catalano RF. Allostasis model facilitates understanding race differences in the diurnal cortisol rhythm. Dev Psychopathol. 2011;23(4):1167–86.PubMedPubMedCentralCrossRefGoogle Scholar
  118. Sturt J, Dennick K, Due-Christensen M, McCarthy K. The detection and management of diabetes distress in people with type 1 diabetes. Curr Diab Rep. 2015;15(11):101.PubMedCrossRefGoogle Scholar
  119. Thorpe CT, Gellad WF, Good CB, Zhang S, Zhao X, Mor M, et al. Tight glycemic control and use of hypoglycemic medications in older veterans with type 2 diabetes and comorbid dementia. Diabetes Care. 2015;38(4):588–95.PubMedPubMedCentralGoogle Scholar
  120. Turner PR, O’Connor K, Tate WP, Abraham WC. Roles of amyloid precursor protein and its fragments in regulating neural activity, plasticity and memory. Prog Neurobiol. 2003;70(1):1–32.PubMedCrossRefGoogle Scholar
  121. van den Berg E, Kloppenborg RP, Kessels RP, Kappelle LJ, Biessels GJ. Type 2 diabetes mellitus, hypertension, dyslipidemia and obesity: a systematic comparison of their impact on cognition. Biochim Biophys Acta. 2009;1792(5):470–81.PubMedCrossRefGoogle Scholar
  122. van der Feltz-Cornelis CM. Comorbid diabetes and depression: do E-health treatments achieve better diabetes control? Diabetes Manag. 2013;3(5):379–88.CrossRefGoogle Scholar
  123. van der Feltz-Cornelis CM, Nuyen J, Stoop C, Chan J, Jacobson AM, Katon W, et al. Effect of interventions for major depressive disorder and significant depressive symptoms in patients with diabetes mellitus: a systematic review and meta-analysis. Gen Hosp Psychiatry. 2010;32(4):380–95.PubMedCrossRefGoogle Scholar
  124. van Duinkerken E, Schoonheim MM, Sanz-Arigita EJ, IJzerman RG, Moll AC, Snoek FJ, et al. Resting-state brain networks in type 1 diabetic patients with and without microangiopathy and their relation to cognitive functions and disease variables. Diabetes. 2012;61(7):1814–21.PubMedPubMedCentralCrossRefGoogle Scholar
  125. van Steenbergen-Weijenburg KM, de Vroege L, Ploeger RR, Brals JW, Vloedbeld MG, Veneman TF, et al. Validation of the PHQ-9 as a screening instrument for depression in diabetes patients in specialized outpatient clinics. BMC Health Serv Res. 2010;10:235.PubMedPubMedCentralCrossRefGoogle Scholar
  126. van Steenbergen-Weijenburg KM, van Puffelen AL, Horn EK, Nuyen J, van Dam PS, van Benthem TB, et al. More co-morbid depression in patients with type 2 diabetes with multiple complications. An observational study at a specialized outpatient clinic. Diabet Med. 2011;28(1):86–9.PubMedCrossRefGoogle Scholar
  127. Watson GS, Cholerton BA, Reger MA, Baker LD, Plymate SR, Asthana S, et al. Preserved cognition in patients with early Alzheimer disease and amnestic mild cognitive impairment during treatment with rosiglitazone: a preliminary study. Am J Geriatr Psychiatry. 2005;13(11):950–8.PubMedGoogle Scholar
  128. Weyerer S. Physical inactivity and depression in the community. Evidence from the Upper Bavarian Field Study. Int J Sports Med. 1992;13(6):492–6.PubMedCrossRefGoogle Scholar
  129. Whitmer RA, Karter AJ, Yaffe K, Quesenberry CP Jr, Selby JV. Hypoglycemic episodes and risk of dementia in older patients with type 2 diabetes mellitus. JAMA. 2009;301(15):1565–72.PubMedPubMedCentralCrossRefGoogle Scholar
  130. Williamson JD, Launer LJ, Bryan RN, Coker LH, Lazar RM, Gerstein HC, et al. Cognitive function and brain structure in persons with type 2 diabetes mellitus after intensive lowering of blood pressure and lipid levels: a randomized clinical trial. JAMA Intern Med. 2014;174(3):324–33.PubMedPubMedCentralCrossRefGoogle Scholar
  131. Willis T. Pharmaceutice rationalis sive diabtriba de medicamentorum operantionibus in humano corpore. Oxford; 1675.Google Scholar
  132. World Health Organisation. Schedule for Clinical Assessment in Neuropsychiatry 2.1. 1999. http://whoscan.org/wp-content/uploads/2014/10/xinterview.pdf. Last accessed 17 Sept 2016.
  133. Zilkens RR, Davis WA, Spilsbury K, Semmens JB, Bruce DG. Earlier age of dementia onset and shorter survival times in dementia patients with diabetes. Am J Epidemiol. 2013;177(11):1246–54.PubMedCrossRefGoogle Scholar

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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Human Development and Health Academic Unit, Faculty of MedicineUniversity of SouthamptonSouthamptonUK

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