Back to Journals » Diabetes, Metabolic Syndrome and Obesity » Volume 17

Barriers and Facilitators of Self-Management in Older People with Type 1 Diabetes: A Narrative Review Focusing on Cognitive Impairment

Authors Fonseca LM , Schmidt JJ, Snoek FJ, Weinstock RS, Chaytor N , Stuckey H, Ryan CM , van Duinkerken E 

Received 22 January 2024

Accepted for publication 30 May 2024

Published 12 June 2024 Volume 2024:17 Pages 2403—2417

DOI https://doi.org/10.2147/DMSO.S410363

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 5

Editor who approved publication: Prof. Dr. Juei-Tang Cheng



Luciana Mascarenhas Fonseca,1,2,* Juliana Janeiro Schmidt,3,* Frank J Snoek,4 Ruth S Weinstock,5 Naomi Chaytor,1 Heather Stuckey,6 Christopher M Ryan,7 Eelco van Duinkerken3,4

1Department of Community and Behavioral Health, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, USA; 2Programa Terceira Idade (PROTER, Old Age Research Group), Department and Institute of Psychiatry, University of São Paulo School of Medicine, São Paulo, Brazil; 3Post-Graduate Program in Neurology, Universidade Federal Do Estado Do Rio de Janeiro, Rio de Janeiro, Brazil; 4Department of Medical Psychology, Amsterdam University Medical Center, Vrije Universiteit, Amsterdam, the Netherlands; 5Department of Medicine, Upstate Medical University, Syracuse, NY, USA; 6Department of Medicine, Penn State University College of Medicine, Hershey, PA, USA; 7Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA

*These authors contributed equally to this work

Correspondence: Eelco van Duinkerken, Amsterdam University Medical Centers, Vrije Universiteit, Department of Medical Psychology, De Boelelaan 1117, Amsterdam, 1081 HV, the Netherlands, Email [email protected]

Abstract: Over the past decades, life expectancy of people with type 1 diabetes has increased considerably, which brings potential challenges due to the process of aging. Cognitive aging and dementia, as well as reductions in visual acuity, hearing and dexterity, can influence the frequency and quality of daily self-management activities, including medication taking and insulin dosing, glucose self-monitoring, and healthy eating. This can increase the risk for hypo- and hyperglycemic events, which, in turn, may contribute to cognitive decline. Because there is a gap in understanding the barriers and facilitators of self-management in older adults with type 1 diabetes and the relationship to cognitive functioning, the authors 1) review the available literature on cognitive aging and type 1 diabetes, 2) describe what self-management in later adulthood entails and the cognitive functions required for effective self-management behaviors, 3) analyze the interaction between type 1 diabetes, cognition, aging, and self-management behaviors, and 4) describe the barriers and facilitators for self-management throughout the life span and how they may differ for older people. Potential evidence-based practices that could be developed for older adults with type 1 diabetes are discussed. There is need for further studies that clarify the impact of aging on T1D self-management, ultimately to improve diabetes care and quality of life.

Keywords: type 1 diabetes, self-management, cognition, aging

Introduction

Life expectancy of people with type 1 diabetes (T1D) has increased significantly in most countries over the past decades due to advances in medical treatments and technological improvements in glucose monitoring and insulin delivery.1,2 Consequently, an increased number of people with T1D reach older age (>65 years),3 and may experience signs of typical aging processes, such as frailty, loss of autonomy, malnutrition, vision and hearing impairments, reduced dexterity, and age-related decline in cognition. All such factors may affect their engagement with, and capacity for managing, T1D-related behaviors (ie, diabetes self–management skills).4–6

Regardless of age, diabetes self-management can be cognitively complex and demanding,7,8 since it requires the measurement and interpretation of glucose levels, the use of algorithms to adjust insulin doses based on current and trending glucose levels, and attention to current eating patterns and activity levels. Newer glucose monitoring and insulin delivery technologies, including continuous glucose monitoring (CGM) devices and advanced hybrid closed-loop (HCL) systems hold promise for automating and simplifying these self-management requirements. However, both traditional and newer technology require interpretation and thoughtful decision-making based on extensive insulin and glucose data that may fluctuate over time, as well as uncaptured lifestyle, personal preferences, and behavioral factors, which can be challenging at any age.7

All aspects of T1D self-management require adequate cognitive function.7,9,10 They include the complex tasks of taking medication, monitoring of glucose levels, reducing risk of hypo- and hyperglycemia and long-term complications, problem solving, and healthy nutrition and physical activity.9 Of these, little is known about healthy nutrition (eg, meal planning, matching insulin with carbohydrate or food intake, adequate protein intake and interpreting nutrition labels),8,11 and physical activity – both of which may promote improved glucose control,12 improved appetite,13 and prevent frailty14 in older adults with T1D. Because T1D is associated with increased risk for cognitive decline, over and above the expected cognitive changes associated with normal aging, this may interfere with self-management, which then may lead to (additional) glycemic dysregulation, potentially further worsening cognitive functioning.

In view of the high cognitive demand needed for T1D self-management, it is imperative to understand the cognitive profile of older adults with T1D in addition to the expected age-related changes in cognition. Recently, the 32-year DCCT/EDIC T1D follow-up study showed that cognitive decline, particularly in psychomotor and mental efficiency, was equivalent to nearly 10 years of advanced cognitive aging,15 with higher lifetime HbA1c, more episodes of severe hypoglycemia, and elevated systolic blood pressure associated with greater cognitive decline.15 In older adults with T1D, the presence of severe hypoglycemia, in particular, can impact cognition.16

This review summarizes the barriers and facilitators of self-management in older individuals with T1D, with a particular focus on the role of cognition. We review the cognitive literature in T1D, discuss the most important aspects of self-management and the cognitive functions that may underly these behaviors, analyze the interaction between cognition, aging, and T1D self-management behaviors, and describe the barriers and facilitators for self-management competencies throughout life and how they may uniquely impact older people with T1D. While type 2 diabetes (T2D) is also related to cognitive alterations with aging, other publications have discussed this in detail, eg, see.17 Therefore, we will focus exclusively on T1D.

Cognition and Aging in T1D

Cognition refers to the conscious and unconscious mental processes by which knowledge is accumulated, including memory, attention, language, executive functions, motor control, sensory perception, and speed of information processing (Table 1).18 To further elaborate, executive function is an umbrella term that includes self-monitoring, problem–solving, impulse control, judgment, and the ability to learn novel behaviors. Throughout life, T1D is associated with small, but significant, cognitive decrements compared to adults without diabetes particularly on measures of attention, psychomotor efficiency, and executive functions.17 This section will briefly address expected age-related changes, as well as pathological cognitive decline and dementia in older adults with T1D.

Table 1 Impact of Cognitive Decline on Self-Management in Older Adults with T1D

Cognitive Changes Expected with Aging and the Role of Cognitive Reserve

With healthy aging, some cognitive functions are expected to decline, such as processing speed and new learning, with minimal impact on the ability to perform daily activities.19 In contrast to normative age-related cognitive decline, pathological cognitive aging is marked by cognitive decline that is greater than expected due to aging alone (ie, Mild Cognitive Impairment; MCI) and impacts daily functioning (ie, dementia). In MCI, cognition is impaired in one or more cognitive domains compared to age-matched normative data, with no or minimal impairment of instrumental activities of daily living.20 MCI can be divided into amnestic and non-amnestic and is associated with a higher risk of conversion to dementia, with amnestic MCI being especially associated with risk for Alzheimer disease.21 In dementia, multiple domains of cognition are impaired, along with impairment in activities of daily living,22 regardless of underlying pathology (eg, Alzheimer’s disease, Lewy Body disease, and vascular disease).

There is substantial heterogeneity in the cognitive aging process (normal and pathological) in the general population, in which inter- and intra-individual risk and protective factors play an important role. Some factors, including level of education, intelligence, socioeconomic status, and lifestyle factors, such as regular exercise and good nutritional habits,23,24 may attenuate the effect of brain aging.24 Collectively these factors have been included within the concept of cognitive reserve. A higher cognitive reserve, or “surplus” in cognitive abilities, may delay the onset of noticeable cognitive decline, which helps explain resilience or susceptibility to aging and pathological cerebral changes.25 Little is known about factors that protect against age-related or accelerated cognitive decline in older adults with T1D.

Aging-Related Changes and Cognitive Decline in T1D

Despite increasing life expectancy, relatively little is known about the profile of cognitive decrements in older people with T1D. A recent cross-sectional study comparing older adults with T1D (n=734; mean age 67.20±6.25 years), T2D (n=232; mean age 68.70±7.04 years) and no diabetes (n=247; mean age 68.70±7.0 years), demonstrated that people with T1D had lower scores on total cognition, language, executive function/psychomotor processing speed, and verbal episodic memory, compared to individuals without diabetes, but not when compared with T2D.26 A 4.1-year follow-up study of those with T1D vs controls (40 T1D/36 controls; T1D mean age at baseline 60.4±6.0 years) did not show an accelerated decline compared to controls.16 It did, however, demonstrate that those with one or more severe hypoglycemic or cardiovascular events during follow-up showed accelerated decline in processing speed and overall cognition, compared to their counterparts without such events.16 The DCCT/EDIC 32-year cognitive follow-up (n=1051; median age 59 years; range 43–75) showed accelerated decline in processing speed and mental efficiency,15 particularly between the 18 year and 32 year visits. The main predictors of decline were a higher lifetime HbA1c, more episodes of severe hypoglycemia, and a higher systolic blood pressure, suggesting an important vascular contribution to decline (Figure 1). Interestingly, those participants with the lowest risk factor exposure (ie, lower HbA1c, no severe hypoglycemic events, normal systolic blood pressure) did not experience any decline in psychomotor efficiency over the 32-year follow-up period, possibly suggesting that controlling these factors can protect individuals from accelerated decline.

Figure 1 A schematic overview of factors related to cognitive impairment in older people with T1D. On top are factors that have been found to be related to cognitive impairment. In the middle, some factors have been added which can be considered a consequence of T1D and may play a mediating role in these factors relating to cognitive impairment.

Risk of MCI and Dementia in T1D

The data discussed in the previous paragraph suggest that at least a subset of older adults with T1D may have accelerated cognitive aging, which could evolve into MCI or dementia. Despite these conditions posing serious implications for self-management, few studies have investigated these conditions in T1D. A study including 201 older participants with T1D (age >65 years; mean age 68.29±6.15 years) showed that clinically significant cognitive impairment (two or more test performances of ≥1.5 standard deviations below the mean based on normative data) was present in 50% of the group,27 with the majority showing a non-amnestic profile. The DCCT/EDIC defined possible MCI as scoring 21 or lower on the Montreal Cognitive Assessment (MoCA), a commonly used cognitive screening test. They showed that 6% of the sample met the criteria for MCI,15 although the chosen cut-off is very conservative and the percentage likely represents an underestimation. Indeed, a reanalysis of the DCCT/EDIC data showed the optimal cut-off for cognitive impairment was 25 and lower, indicating the percentage of participants with cognitive impairment might be higher than 6%.28 In another sample of older adults with T1D, the overall accuracy of the MoCA was low, but a cut-off of <27 was found to be most accurate.29 More studies determining MCI prevalence in older adults with T1D and its effect on self-management tasks are needed. These low rates of MCI may represent an underestimation of cognitive burden in T1D because of “survivor bias”. That is, those with better glycemic control, and less micro- and macroangiopathy may be more likely to survive into older adulthood as well as function better cognitively because they have fewer biomedical risk factors. It is also known that older participants tend to be better educated, have better socioeconomic status, and lower depression scores.

Regarding dementia, a British medical records study including 343,062 people with T1D aged 30 and older, found 10,786 had a diagnosis of any dementia, representing an adjusted relative risk of 1.65 with a 95% confidence interval (CI) ranging from 1.61 to 1.68.30 This was mainly driven by vascular dementia, with a relative risk of 2.21 (95% CI: 2.13–2.28; 3885 cases), while the increase in risk of Alzheimer’s disease was small (1.10 [95% CI: 1.05–1.15]; 2113 cases). This considerably higher hazard ratio of vascular dementia relative to Alzheimer’s disease was corroborated by a smaller Danish national records study in adults 65 and older (1.51 [95% CI: 1.17–1.95] versus 1.11 [95% CI: 0.95–1.32]).31

In summary, there is some evidence that having T1D increases risk of MCI and dementia, likely due to a vascular etiology. This mirrors T1D-related cognitive decrements found across the life-span, which are heavily skewed towards domains that are sensitive to vascular cerebral damage, such as processing speed, attention, and executive functions, with relative sparing of memory.17

Possible Mechanisms Underlying Cognitive Alterations in T1D

Given the limited literature on cognitive functioning and dementia in older adults with T1D, the mechanisms responsible remain unclear. In general, in adolescents and adults with T1D, cognitive dysfunction is associated with early age of T1D onset and chronic hyperglycemia which is associated with the development of microvascular and macrovascular complications.15,17 It is known that chronic and reactive (after hypoglycemia) hyperglycemia can cause a cascade of biomedical reactions, including increased inflammation, oxidative stress, and advanced glycation end products (Figure 1),32–34 which may affect brain structure and functioning. While it is likely that these factors, and specifically chronic hyperglycemia, play a role in older adults, other factors should also be considered. The 32-year DCCT/EDIC study showed that the observed decline in psychomotor speed and mental efficiency was related to higher lifetime HbA1c (chronic hyperglycemia), episodes of severe hypoglycemia, and higher systolic blood pressure (Figure 1).15 In other samples, poorer cognition has also been shown to be associated with these risk factors, as well as microvascular complications and cardiovascular events (Figure 1).16,27 Mechanisms specific to dementia are scarce, but also seem to be related to HbA1c,35 although not to the presence of retinopathy.36 Taken together, these data suggest a strong vascular component, which matches the speed-related profile of cognitive alterations and the significantly increased risk of vascular dementia in T1D, but also points towards a contribution of severe hypoglycemia as an important risk factor that should be prevented. Figure 1 summarizes these mechanisms and details some of their biomedical consequences that could be related to cognitive alterations.

The literature to date suggests that optimal control of vascular disease risk factors, including HbA1c, and minimizing exposure to severe hypoglycemia, across the lifespan will maximize the likelihood of successful cognitive aging in T1D. Of note, EDIC participants with average HbA1c of 6.5%, systolic blood pressure of 100 mmHg and no severe hypoglycemic events, did not experience any cognitive decline over the 32-year follow-up period. Adherence to this level of control, however, requires substantial resources, patient burden and access to optimal health care, and is not possible for all T1D adults.

Type 1 Diabetes-Related Self-Management

According to the Association of Diabetes Care and Education Specialists, there are seven key diabetes self-management behavioral domains that are associated with improved clinical outcomes.8 In no particular order, these competencies include: (1) taking medication, (2) healthy eating, (3) being physically active, (4) problem-solving, (5) monitoring glucose, (6) reducing risk of diabetes complications and (7) healthy coping.8 Several cognitive functions (eg, executive function, memory, attention), and applied skills (eg, numeracy, literacy) may be involved in these competencies (Table 1; Figure 2).7,37,38

Figure 2 A schematic overview of the core competencies for type 1 diabetes self-management, where coping, reducing risk, problem solving, and monitoring were placed at the center. Competencies, including healthy eating, taking medication, and physical activity, in part are dependent on the other competencies.

Taking Medication in T1D

Taking medication is an essential component of T1D self-management and encompasses behaviors like following the daily recommended timing, dosage, and frequency of insulin administration.8 Given the increased risk of hypoglycemia in older adults with T1D,39 the use of CGM is recommended, since wide glycemic excursions, including episodes of hypo- and hyperglycemia, can occur at both high and low HbA1c levels. The HbA1c goals should be individualized, with the recommended HbA1c goal of 7.0–7.5% for cognitively and otherwise healthy older adults, and <8.0% for those with significant cognitive and/or functional impairments.39 For those with moderate to severe cognitive impairment, glucose targets should be guided based on avoiding hypoglycemia and symptomatic hyperglycemia.39

Successful adherence to any insulin regimen (complex or simplified) will require various cognitive abilities and related skills, including numeracy (ability to comfortable work with numbers), health literacy, and executive functioning.8,38 Of these, numeracy is particularly important since many adults with T1D count/estimate carbohydrates and determine insulin doses based on their current blood glucose level and carbohydrate-to-insulin ratio. Smart/connected insulin pens and insulin pumps can perform these calculations. However, because the routine use of complex insulin regimens may become too cognitively demanding for older adults with or without cognitive decline, a simplified regime may be necessary.7,40 This should be based on an individualized decision between the older person with T1D and health care provider, based on actual problems with self-management. Examples include the use of fixed mealtime boluses if eating patterns are established and reliable, or ultrafast–acting insulin up to 20 minutes after each meal to accommodate for fluctuating meal intake, or supervision/assistance by caregiver.41 However, eventually, with progressing cognitive decline, self-management may need to be assumed by caregivers. Depending upon the availability of caregiver support, automated insulin delivery systems can be used, and their use is associated with less time in hypoglycemia.

Healthy Eating and Physical Activity in the Context of Self-Management in Older Adults with T1D

In T1D, a healthy diet and physical activity are fundamental for glycemic control at any age, including regular exercise, choosing healthy foods, and proper meal planning. All of these involve optimal nutrition and protein intake, carbohydrate counting (when possible), portion management and understanding nutrition label information.8,39 In older adults with T1D, healthy eating can become more challenging due to a variety of factors, including cognitive decline, a change in appetite, decreased olfactory and gustatory capacity, poor dentition or vision, polypharmacy, financial limitations, cultural preferences, and problems with access to healthy food.6,42,43

In T1D, changing eating habits can result in altered insulin needs, for which insulin regimens need to be adjusted. Such changes can make blood glucose regulation less predictable and self-management more cognitively demanding, which may lead to more hypo- and (reactive) hyperglycemic events. Changes in diet quality and/or glucose variation may also influence daily cognitive functioning and promote cognitive deterioration, as poor nutrition has been linked to cognitive decline irrespective of the presence of T1D.44 Healthy eating requires planning, numeracy, attention, memory, and inhibition. Indeed, memory and more complex attentional functioning are correlated with T1D self-management skills, such as carbohydrate counting, and calculating insulin-dose adjustments based on serving sizes and nutrition labels.37

Physical activity in relation to diabetes self-management remains understudied in older adults with T1D. However, it has been shown that regular light exercise can improve insulin sensitivity and glycemic control in adults with T1D,12 highlighting the importance of physical activity. With aging, independent of T1D, physical activity can become more difficult, due to many factors, including isolation, malnutrition, overweight/obesity, risk of falls, loss of interest, and general frailty.45,46 In older people with T1D, microvascular complications, such as neuropathy or retinopathy, as well as the risk of hypo- or hyperglycemia can pose barriers to being physically active.47 In older adults without T1D, physical activity has been found to have a bidirectional relationship with cognitive function, including memory and executive functions.48 In older people with T1D, unfortunately, the relationship between cognition and physical activity, especially related to self-management, has not yet been studied.

Problem Solving, Monitoring, Reducing Risk, and Healthy Coping

The four competencies of problem solving, monitoring, reducing risk of complications, and healthy coping strategies are aimed at limiting acute hypo- and hyperglycemia, diabetic ketoacidosis, and long-term complications. Cognitive decrements and accelerated decline in older adults with T1D should also be a focus of risk reduction as long-term exposure to elevated blood glucose is associated with increased cognitive decline and dementia risk.35,49

In T1D, problem solving refers to the knowledge and set of strategies and skills that are necessary to solve acute or long-term problems.8 It involves identifying the problem (eg, hypoglycemia), developing appropriate solutions, acting on a solution, and monitoring.8 For T1D, monitoring involves the examination of glucose levels, blood pressure, nutritional intake, weight, exercise, and medication.8 The results can be used to develop appropriate solutions and action through behavior changes.8 For example, glucose self-monitoring provides data that can be used to evaluate the effectiveness of T1D self-management and guides adjustments in diet, insulin dosage, exercise, and medication use.50 The use of CGM is an essential component of automated insulin delivery systems, which can suspend insulin delivery when hypoglycemia is predicted, thereby reducing time in hypoglycemia. Automated insulin correction doses can also be given to reduce time in serious hyperglycemia. Reducing risks is linked to the previous two competencies, as well as engaging in recommended screening for early signs of complications (eg, eye exams, kidney function tests, foot checks), and treating hypertension and hyperlipidemia. These interventions reduce the risk of long-term complications.8 The ability to mitigate these risks is fundamental for healthy aging, continued effective T1D self-management and overall quality of life. Coping in the context of T1D self-management refers to the individual’s set of mechanisms to deal with all aspects of T1D.8 For example, a study in younger persons with T1D and their caregivers showed a pattern of productive (acceptance, planning ahead, social support) and non-productive (avoidance/disengagement, insulin rationing) coping strategies.51 Non-productive or unhealthy coping can lead to significant increases in diabetes distress and symptoms of depression and anxiety. These, in turn, can influence other aspects of self-management, ultimately leading to reduced glycemic control. In contrast, healthy coping may reduce distress and improve overall self-management. Healthy coping, as a potential protective factor, has not been systematically studied in older people with T1D, despite the fact that they are similarly affected by diabetes-related stress as their younger peers.52

The cognitive skills related to the success of these seven competencies include memory, attention, and executive functions, such as adequate judgement, planning, self-monitoring, problem solving, as well as inhibition of unhealthy behaviors.53 In older adults with T1D, these competencies can be more challenging in the presence of financial difficulties, reduced dexterity, vision and hearing impairment, and cognitive decline.

Recent Advances in Technology to Reduce Cognitive Burden of T1D Self-Management

As stated, self-management in T1D is cognitively demanding and is dependent on the close interplay between memory, attention, executive functions, processing speed, and visual/motor skills. Technologies, such as CGM and automated insulin delivery (HCL) systems, may help improve T1D self-management in older people by reducing its cognitive burden when used appropriately. These technologies, their cognitive burden, and other potential treatment solutions for older adults with T1D and cognitive impairment have been summarized in Table 2.

Table 2 Overview of Treatment Options and Their Cognitive Burden

There is evidence to suggest that regardless of presence or absence of cognitive decline, older people with T1D can successfully use advanced technology,54 albeit potentially with additional device training.55 For example, in a study of people with T1D aged 60–83 years, CGM effectively reduced time spent in hypoglycemia, severe hypoglycemic events and glycemic variability after 6,54 and 12 months,56 with no difference in benefit for those with and without cognitive impairment. Using HCL with 30 older adults (mean age 67±5 years; range 60–75), McAuley et al demonstrated a significant improvement of time in target glucose range (TIR) and a small but significant decrease in hypoglycemia (time below range) compared with sensor augmented pump therapy.35 Boughton et al, in a 16-week HCL versus sensor-augmented pump therapy crossover trial that included 37 older adults with T1D (median age 68 years; IQR 63–70), found clinically significant improvements in TIR and a reduction in HbA1c when using HCL, without increased hypoglycemia.57

HCL systems reduce or suspend insulin delivery when hypoglycemia is predicted to occur, thereby reducing time in hypoglycemia. Many currently available advanced HCL systems also provide “autocorrection” doses when glucose readings are rising, so even in adults who forget to bolus for eating, glycemic control improves. Significant improvements in glycemic control have been reported recently for a commercially available system that requires only the person’s weight and the time and size of the meal (usual, smaller or larger) to be entered. Unfortunately, this has not yet been tested specifically in older adult but seems quite promising, particularly because no carbohydrate counts are required (Table 2).58 In development are fully closed-loop systems that will administer insulin with or without glucagon automatically, including at mealtimes, with the goal of keeping all glucose levels within the target range.59,60

HCL systems are an improvement over multiple daily injections or insulin pump use without automated insulin delivery, as they reduce the cognitive burden of self-management. However, these systems still can be difficult for older adults with cognitive, dexterity and vision problems. Some older adults may have difficulty adopting new technology, may require more time and effort when learning new routines and tasks, and may have increased difficulty trouble-shooting problems that can arise with HCL systems. Further, all available technologies require application of sensors and/or insulin infusion sets, and regular care and maintenance of the devices (eg filling insulin pump cartridges) which can be difficult for those with disabilities. Challenges include software updates, charging devices, changing CGM components, ordering pump and CGM supplies, recognizing occlusions, and the need to rotate sites. While the HCL devices take over several aspects of self-management, competencies including coping, healthy nutrition, and physical activity also remain. Larger trials that include important subgroups (eg, >75 years old, cognitively impaired, frail, lower education/literacy, and greater racial/ethnic diversity) and caregivers, are needed to study training approaches, evaluate the effectiveness and safety of these different devices and examine how competencies, such as coping, healthy eating, and physical activity can be promoted in the aging T1D population to reduce cognitive decline.

Interaction Between Cognition, Aging and Self-Management

Many of the cognitive domains that are most susceptible to aging-related deterioration, such as planning, mental flexibility, inhibition, and memory are fundamental for T1D self-management. Due to the complexity of these activities, even minor cognitive impairment can have a major impact. Indeed, in a study with 201 older adults with longstanding T1D, the severity of cognitive deficits was associated with both diabetes management and performance of instrumental activities of daily living,34 which is similar to findings in T2D,61,62 indicating a relationship between cognition and self-management.

Not only did the DCCT/EDIC study group show 10 years of accelerated cognitive aging by study year 32,15 but neuroimaging showed that people with T1D have structural abnormalities equivalent to 4 to 9 years of accelerated brain aging.63 Even though self-management can be assumed to be a highly overlearned and reinforced skill and older adults with T1D have been “doing it” for decades, older people with T1D are as much affected by diabetes-related stressors as their younger peers.52 Add to this accelerated cognitive and brain aging, and it is conceivable that self-management, including monitoring, insulin injection administration and device control, may become more difficult, and lead to worse glycemic control. How the effects of accelerated aging interact with self-management is largely unknown. Larger studies are needed in diverse international populations that incorporate both cognition and self-management measures. Especially important to include in such studies are assessments of healthy coping, healthy eating and physical activity, as these domains of self-management cannot be controlled by devices.

Importantly, hypoglycemia is known to be dangerous for older individuals, as it can lead to falls, fractures, hospitalizations, vascular complications and mortality, as well as additional cognitive decline.15,27,64 This decline can further complicate self-management and cause deterioration in glycemia, which can increase the risk of pathological cognitive decline.65 Depending on the level of cognitive reserve and care partner support, however, there will be individual variation as to when cognitive aging and neurodegeneration start to affect self-management. Clinical follow-up by providers, involvement and continued monitoring by caregivers will be needed, as well as a proper understanding of each person’s barriers and facilitators of T1D self-management, which will likely change over time. The dynamics of this cycle are shown in Figure 3.

Figure 3 Cycle model of self-management, cognition, and aging in type 1 diabetes. There is a bidirectional relationship between self-management and cognition in T1D: cognitive performance influences the quality of diabetes management, and suboptimal diabetes management may also increase the likelihood of worsening cognitive performance. Both the presence of T1D and aging will affect this relationship between cognition and self-management, enhancing the dependence and strength of this bidirectional association: cognitive difficulties associated with T1D negatively impact the self-management needs generated by the disease; with age-related decline, self-management ability deteriorates and the need for planned self-management increases considerably.

Barriers and Facilitators of Self-Management

Table 1 summarizes barriers and potential facilitators of self-management in T1D, including the development of cognitive, visual and hearing impairments, availability of advanced T1D treatment options, reduction in dexterity and other physical functions, an increased comorbid medical conditions, polypharmacy, an increased risk of malnutrition, and, for many, the need for caregiver support. Some facilitators may offset these potential difficulties, including expertise in T1D self-management, cognitive reserve, preserved cognitive functioning, use of technological advancements, modification of the insulin and glucose monitoring regimen, personalized dietary plans, nutrition assistance programs, and programs to offset medication cost. These are mostly T1D-related or general medical barriers and facilitators. Psychosocial facilitators and barriers may include support from family and friends, personality traits, loneliness, stress of limited financial resources or limited access to food or care, and mood states, such as depression or dysphoria.66

Due to lack of research, barriers and facilitators from the perspective of the older person with T1D are unclear. It is possible that some older adults with T1D may perceive effects of cognitive decline before decline is captured on neuropsychological testing, or before others’ observations. A qualitative study including 29 older participants with T1D (73.4±4.5 years) identified various themes that acted both as a barrier and a facilitator. For example, technology, including CGM, was mentioned as a barrier (challenging to understand, needing to learn to work with the device), but also as a facilitator (improves glycemic control, takes over some aspects of self-care). Self-reliance, self-advocacy and survivors’ mentality were identified as facilitators. On the contrary, worries about declining (cognitive) and physical health and getting help or giving control to a caregiver were described as barriers.67 Another recent study assessed burden and benefits of CGM use in T1D, including 102 participants 65 and older.68 In non-users, relative to users, there was a stronger belief that CGM use was a burden. For example, non-users more frequently reported that CGM information was too hard to understand, and that it causes too much worry. Only 43% reported feeling more secure with CGM, and 20% reported feeling that with CGM they would take better care of their T1D.68 Interestingly, about 59% of the non-users believed that the CGM would make diabetes care easier and that it would take care of their low blood glucose. However, in CGM-uses, these percentages were considerably and statistically significantly higher.68,69

Unfortunately, these studies have included ethnically non-diverse people with higher SES, many using CGM. Barriers and facilitators in people who are non-white, lower educated, and of lower SES, including from developing countries, should be studied. In such studies, progressive cognitive decline should also be included. How do older people with T1D think about having caregivers taking over more self-management tasks, and how can this be done safely are important unanswered questions. Furthermore, caregivers can serve as facilitators, but also as barriers to self-management as they will not have the life experience of the person with T1D, and will need to be trained to provide T1D self-management. They may also develop age-related impairments. More studies are needed to gain a better understanding of the barriers and facilitators of self-management from the perspective of older people with T1D and their families and caregivers.

Future Studies

Given the increasing life-expectancy of people with T1D and the need for complex T1D self-management, there is a need for research that addresses the gap in knowledge in the association between aging, cognition, and self-management behaviors. Future studies characterizing the heterogeneous cognitive profiles in this population will help define personalized target areas for rehabilitation interventions, caregiver involvement, and need for changes in insulin regimens/delivery methods over time. Research should also focus on aging-related planning, and investigating T1D-related cognitive demands and the usability and effectiveness of new technologies, including advanced automated insulin delivery systems, to inform the establishment of self-management support for older adults with T1D and their caregivers. Finally, the role of healthy coping, nutrition, and exercise in older adults with T1D remains largely unexplored. Further research, both qualitative and quantitative, is required to better understand the different and changing needs of this unique population, including identifying those at risk for deteriorating self-management. Also needed is research that identifies facilitators of continued self-management independence, and strategies that can optimize support during transition periods (eg, declining cognition, starting new diabetes technologies, caregiver taking over diabetes management).

Conclusions

Advancements in T1D treatment and self-management technologies have dramatically increased longevity of individuals with T1D. With aging, and specifically with declining cognition, new challenges in self-management often emerge. The usability and effectiveness of new technological devices by older adults with T1D with varying degrees of cognitive and physical impairments needs further study. A greater understanding of the changing barriers and facilitators in the management of T1D in older adults, both qualitative and quantitative, will help lead to better approaches for their diabetes management and, in turn, to improved quality of life.

Acknowledgments

LMF currently receives support from the Alzheimer’s Association (AARFD-21-851373) and the National Institute on Aging of the National Institutes of Health (Award Number K99AG082864). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Alzheimer’s Association.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

FS reports personal fees/grants from Eli Lilly, Sanofi, Abbott, and Roche Diabetes, outside the submitted work. RSW reports participation in multicenter clinical trials, through her institution, sponsored by Insulet, Tandem, Eli Lilly, MannKind, Amgen, Diasome, and DexCom provided devices at reduced cost. NC reports personal fees from Adaptelligence, LLC, outside the submitted work. The authors report no other conflicts of interest in this work.

References

1. Heald AH, Stedman M, Davies M, et al. Estimating life years lost to diabetes: outcomes from analysis of national diabetes audit and office of national statistics data. Cardiovasc Endocrinol Metab. 2020;9(4):183–185. doi:10.1097/XCE.0000000000000210

2. Orchard TJ, Nathan DM, Zinman B, et al. Association between 7 years of intensive treatment of type 1 diabetes and long-term mortality. JAMA. 2015;313(1):45–53. doi:10.1001/jama.2014.16107

3. Norris JM, Johnson RK, Stene LC. Type 1 diabetes-early life origins and changing epidemiology. Lancet Diabetes Endocrinol. 2020;8(3):226–238. doi:10.1016/S2213-8587(19)30412-7

4. Burr D Effects of aging on skeletal fragility. In: Osteoporotic Fracture and Systemic Skeletal Disorders: Mechanism, Assessment, and Treatment; 2022:31–43.

5. Legdeur N, Heymans MW, Comijs HC, Huisman M, Maier AB, Visser PJ. Age dependency of risk factors for cognitive decline. BMC Geriatr. 2018;18(1):187. doi:10.1186/s12877-018-0876-2

6. Clegg ME, Williams EA. Optimizing nutrition in older people. Maturitas. 2018;112:34–38. doi:10.1016/j.maturitas.2018.04.001

7. Taboada Gjorup AL, Snoek FJ, van Duinkerken E. Diabetes self-care in older adults with type 1 diabetes mellitus: how does cognition influence self-management. Front Clin Diabetes Healthc. 2021;2:727029. doi:10.3389/fcdhc.2021.727029

8. American Association of Diabetes Educators. An effective model of diabetes care and education: REVISING the AADE7 self-care behaviors®. Diabetes Educ. 2020;46(2):139–160. doi:10.1177/0145721719894903

9. Sinclair AJ, Dunning T, Dhatariya K. Clinical guidelines for type 1 diabetes mellitus with an emphasis on older adults: an Executive Summary. Diabet Med. 2020;37(1):53–70. doi:10.1111/dme.14135

10. Goshen A, Goldbourt U, Benyamini Y, Shimony T, Keinan-Boker L, Gerber Y. Association of diet quality with longevity and successful aging in Israeli adults 65 years or older. JAMA Network Open. 2022;5(6):e2214916. doi:10.1001/jamanetworkopen.2022.14916

11. Gray A, Threlkeld RJ. Nutritional Recommendations for Individuals with Diabetes. Feingold KR, Anawalt B, Blackman MR, eds.. MDText.com, Inc.Copyright © 2000–2023, MDText.com, Inc; 2000.

12. Basu R, Johnson ML, Kudva YC, Basu A. Exercise, hypoglycemia, and type 1 diabetes. Diabetes Technol Ther. 2014;16(6):331–337. doi:10.1089/dia.2014.0097

13. Hubner S, Boron JB, Koehler K. The effects of exercise on appetite in older adults: a systematic review and meta-analysis. Systematic review. Front Nutr. 2021;8. doi:10.3389/fnut.2021.734267

14. Angulo J, El Assar M, Álvarez-Bustos A, Rodríguez-Mañas L. Physical activity and exercise: strategies to manage frailty. Redox Biol. 2020;35:101513. doi:10.1016/j.redox.2020.101513

15. Jacobson AM, Ryan CM, Braffett BH, et al. Cognitive performance declines in older adults with type 1 diabetes: results from 32 years of follow-up in the DCCT and EDIC Study. Lancet Diabetes Endocrinol. 2021. doi:10.1016/S2213-8587(21)00086-3

16. van Duinkerken E, Brands AMA, van den Berg E, et al. Cognition in older patients with type 1 diabetes mellitus: a longitudinal study. J Am Geriatr Soc. 2011;59:563–565.

17. van Duinkerken E, Ryan CM. Diabetes mellitus in the young and the old: effects on cognitive functioning across the life span. Neurobiol Dis. 2020;134:104608. doi:10.1016/j.nbd.smolin2019.104608

18. Lezak MD. Neuropsychological Assessment. 5th ed. Oxford University Press; 2012.

19. Salthouse TA. Trajectories of normal cognitive aging. Psychol Aging. 2019;34(1):17–24. doi:10.1037/pag0000288

20. Petersen RC, Caracciolo B, Brayne C, Gauthier S, Jelic V, Fratiglioni L. Mild cognitive impairment: a concept in evolution. J Intern Med. 2014;275(3):214–228. doi:10.1111/joim.12190

21. Oltra-Cucarella J, Ferrer-Cascales R, Alegret M, et al. Risk of progression to Alzheimer’s disease for different neuropsychological Mild Cognitive Impairment subtypes: a hierarchical meta-analysis of longitudinal studies. Psychol Aging. 2018;33(7):1007–1021. doi:10.1037/pag0000294

22. Association AP. DSMV Diagnostic and Statistical Manual of Mental Disorder. APA; 2013.

23. Scarmeas N, Stern Y. Cognitive reserve and lifestyle. J Clin Exp Neuropsychol. 2003;25(5):625–633. doi:10.1076/jcen.25.5.625.14576

24. Borenstein AR, Copenhaver CI, Mortimer JA. Early-life risk factors for Alzheimer disease. Alzheimer Dis Assoc Disord. 2006;20(1):63–72. doi:10.1097/01.wad.0000201854.62116.d7

25. Stern Y. Cognitive reserve in ageing and Alzheimer’s disease. Lancet Neurol. 2012;11(11):1006–1012. doi:10.1016/S1474-4422(12)70191-6

26. Lacy ME, Moran C, Gilsanz P, Beeri MS, Karter AJ, Whitmer RA. Comparison of cognitive function in older adults with type 1 diabetes, type 2 diabetes, and no diabetes: results from the Study of Longevity in Diabetes (SOLID). BMJ Open Diabetes Res Care. 2022;10(2).

27. Chaytor NS, Barbosa-Leiker C, Ryan CM, Germine LT, Hirsch IB, Weinstock RS. Clinically significant cognitive impairment in older adults with type 1 diabetes. J Diabetes Complications. 2019;33(1):91–97. doi:10.1016/j.jdiacomp.2018.04.003

28. Chaytor NS, Trapani VR, Braffett BH, et al. Utility of the NIH Toolbox Cognition Battery in middle to older aged adults with longstanding type 1 diabetes: the DCCT/EDIC study. Clin Neuropsychol. 2023:1–21. doi:10.1080/13854046.2023.2266876

29. Choe J, Kudrna R, Fonseca LM, Chaytor NS. Usefulness of the Montreal cognitive assessment in older adults with type 1 diabetes. Diabetes Spectr. 2023;36(4):385–390. doi:10.2337/ds23-0012

30. Smolina K, Wotton CJ, Goldacre MJ. Risk of dementia in patients hospitalised with type 1 and type 2 diabetes in England, 1998–2011: a retrospective national record linkage cohort study. Diabetologia. 2015;58:942–950. doi:10.1007/s00125-015-3515-x

31. Wium-Andersen IK, Rungby J, Jørgensen MB, Sandbæk A, Osler M, Wium-Andersen MK. Risk of dementia and cognitive dysfunction in individuals with diabetes or elevated blood glucose. Epidemiol Psychiatr Sci. 2019;29:e43. doi:10.1017/S2045796019000374

32. Brownlee M. Biochemistry and molecular cell biology of diabetic complications. Nature. 2001;414(6865):813–820.

33. Brownlee M. The Pathobiology of Diabetic Complications: a unifying mechanism. Diabetes. 2005;54:1615–1625. doi:10.2337/diabetes.54.6.1615

34. Suh SW, Gum ET, Hamby AM, Chan PH, Swanson RA. Hypoglycemic neuronal death is triggered by glucose reperfusion and activation of neuronal NADPH oxidase. J Clin Invest. 2007;117(4):910–918.

35. Lacy ME, Gilsanz P, Karter AJ, Quesenberry CP, Pletcher MJ, Whitmer RA. Long-term glycemic control and dementia risk in type 1 diabetes. Diabetes Care. 2018;41(11):2339–2345. doi:10.2337/dc18-0073

36. Rodill LG, Exalto LG, Gilsanz P, Biessels GJ, Quesenberry CPJ, Whitmer RA. Diabetic retinopathy and dementia in type 1 diabetes. Alzheimer Dis Assoc Disord. 2018;32(2):125–130. doi:10.1097/wad.0000000000000230

37. Chaytor NS, Riddlesworth TD, Bzdick S, et al. The relationship between neuropsychological assessment, numeracy, and functional status in older adults with type 1 diabetes. Neuropsychol Rehabil. 2017;27(4):507–521. doi:10.1080/09602011.2015.1116448

38. Munshi MN. Cognitive dysfunction in older adults with diabetes: what a clinician needs to know. Diabetes Care. 2017;40(4):461–467. doi:10.2337/dc16-1229

39. American Diabetes Association Professional Practice Committee. Older Adults: standards of Care in Diabetes-2024. Diabetes Care. 2023;47(Supplement_1):S244–S257. doi:10.2337/dc24-S013

40. Hopkins R, Shaver K, Weinstock RS. Management of adults with diabetes and cognitive problems. Diabetes Spectr. 2016;29(4):224–237. doi:10.2337/ds16-0035

41. Nally LM, Sherr JL, Van Name MA, Patel AD, Tamborlane WV. Pharmacologic treatment options for type 1 diabetes: what’s new? Expert Rev Clin Pharmacol. 2019;12(5):471–479. doi:10.1080/17512433.2019.1597705

42. Churnin I, Qazi J, Fermin CR, Wilson JH, Payne SC, Mattos JL. Association between olfactory and gustatory dysfunction and cognition in older adults. Am J Rhinol Allergy. 2019;33(2):170–177. doi:10.1177/1945892418824451

43. Braun T, Doerr JM, Peters L, et al. Age-related changes in oral sensitivity, taste and smell. Sci Rep. 2022;12(1):1533. doi:10.1038/s41598-022-05201-2

44. Feng L, Chu Z, Quan X, et al. Malnutrition is positively associated with cognitive decline in centenarians and oldest-old adults: a cross-sectional study. EClinicalMedicine. 2022;47:101336. doi:10.1016/j.eclinm.2022.101336

45. Baert V, Gorus E, Mets T, Geerts C, Bautmans I. Motivators and barriers for physical activity in the oldest old: a systematic review. Ageing Res Rev. 2011;10(4):464–474. doi:10.1016/j.arr.2011.04.001

46. Chen M, Yerramalla MS, van Hees VT, et al. Individual barriers to an active lifestyle at older ages among Whitehall II study participants after 20 years of follow-up. JAMA Network Open. 2022;5(4):e226379. doi:10.1001/jamanetworkopen.2022.6379

47. Alobaid AM, Zulyniak MA, Ajjan RA, Brož J, Hopkins M, Campbell MD. Barriers to Exercise in Adults With Type 1 Diabetes and Insulin Resistance. Can J Diabetes. 2023;47(6):503–508. doi:10.1016/j.jcjd.2023.04.016

48. Xu L, Gu H, Cai X, et al. The effects of exercise for cognitive function in older adults: a systematic review and meta-analysis of randomized controlled trials. Int J Environ Res Public Health. 2023;20(2):1.

49. Jacobson AM, Ryan CM, Cleary PA, 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):245–255. doi:10.1007/s00125-010-1883-9

50. Shrivastava SR, Shrivastava PS, Ramasamy J. Role of self-care in management of diabetes mellitus. J Diabetes Metab Disord. 2013;12(1):14. doi:10.1186/2251-6581-12-14

51. Owusu BA, Ofori-Boateng P, Doku DT. Coping and adaptation strategies among young persons living with type 1 diabetes and their caregivers: textual and photovoice analyses. BMC Public Health. 2023;23(1):1684. doi:10.1186/s12889-023-16573-z

52. Berg CA, Helgeson VS, Kelly CS, Tracy EL, Litchman ML, Butner JE. Age differences in reactivity to daily general and Type 1 diabetes stressors. Psychol Aging. 2020;35(8):1115–1126. doi:10.1037/pag0000519

53. Zhao Q, Zhang Y, Liao X, Wang W. Executive Function and diabetes: a clinical neuropsychology perspective. Front Psychol. 2020;11:2112. doi:10.3389/fpsyg.2020.02112

54. Pratley RE, Kanapka LG, Rickels MR, et al. Effect of continuous glucose monitoring on hypoglycemia in older adults with type 1 diabetes: a randomized clinical trial. JAMA. 2020;323(23):2397–2406. doi:10.1001/jama.2020.6928

55. Greenfield M, Stuber D, Stegman-Barber D, et al. Diabetes education and support tele-visit needs differ in duration, content, and satisfaction in older versus younger adults. Telemed Rep. 2022;3(1):107–116. doi:10.1089/tmr.2022.0007

56. Miller KM, Kanapka LG, Rickels MR, et al. Benefit of continuous glucose monitoring in reducing hypoglycemia is sustained through 12 months of use among older adults with type 1 diabetes. Diabetes Technol Ther. 2022;24(6):424–434. doi:10.1089/dia.2021.0503

57. Boughton CK, Hartnell S, Thabit H, et al. Hybrid closed-loop glucose control compared with sensor augmented pump therapy in older adults with type 1 diabetes: an open-label multicentre, multinational, randomised, crossover study. Lancet Healthy Longev. 2022;3(3):e135–e142. doi:10.1016/S2666-7568(22)00005-8

58. Bionic Pancreas Research Group. Multicenter, randomized trial of a bionic pancreas in type 1 diabetes. New Engl J Med. 2022;387(13):1161–1172. doi:10.1056/NEJMoa2205225

59. Blauw H, Onvlee AJ, Klaassen M, van Bon AC, DeVries JH. Fully closed loop glucose control with a bihormonal artificial pancreas in adults with type 1 diabetes: an outpatient, randomized, crossover trial. Diabetes Care. 2021;44(3):836–838. doi:10.2337/dc20-2106

60. Jancev M, Snoek FJ, Frederix GWJ, et al. Dual hormone fully closed loop in type 1 diabetes: a randomised trial in the Netherlands – study protocol. BMJ Open. 2023;13(8):e074984. doi:10.1136/bmjopen-2023-074984

61. Primožič S, Tavčar R, Avbelj M, Dernovšek MZ, Oblak MR. Specific cognitive abilities are associated with diabetes self-management behavior among patients with type 2 diabetes. Diabet Res Clin Pract. 2012;95(1):48–54. doi:10.1016/j.diabres.2011.09.004

62. Sinclair AJ, Girling AJ, Bayer AJ. Cognitive dysfunction in older subjects with diabetes mellitus: impact on diabetes self-management and use of care services. All Wales Research into Elderly (AWARE) Study. Diabet Res Clin Pract. 2000;50(3):203–212. doi:10.1016/s0168-8227(00)00195-9

63. Jacobson AM, Braffett BH, Erus G, et al. Brain Structure Among Middle-aged and Older Adults With Long-standing Type 1 Diabetes in the DCCT/EDIC Study. Diabetes Care. 2022;45(8):1779–1787. doi:10.2337/dc21-2438

64. Lacy ME, Gilsanz P, Eng C, Beeri MS, Karter AJ, Whitmer RA. Severe Hypoglycemia and Cognitive Function in Older Adults With Type 1 Diabetes: the Study of Longevity in Diabetes (SOLID). Diabetes Care. 2020;43(3):541–548. doi:10.2337/dc19-0906

65. Whitmer RA, Gilsanz P, Quesenberry CP, Karter AJ, Lacy ME. Association of type 1 diabetes and hypoglycemic and hyperglycemic events and risk of dementia. Neurology. 2021. doi:10.1212/WNL.0000000000012243

66. Bayliss EA, Ellis JL, Steiner JF. Barriers to self-management and quality-of-life outcomes in seniors with multimorbidities. Ann Fam Med. 2007;5(5):395–402. doi:10.1370/afm.722

67. Cristello Sarteau A, Muthukkumar R, Smith C, et al. Supporting the ‘lived expertise’ of older adults with type 1 diabetes: an applied focus group analysis to characterize barriers, facilitators, and strategies for self-management in a growing and understudied population. Diabet Med. 2024;41(1):e15156. doi:10.1111/dme.15156

68. Divan V, Greenfield M, Morley CP, Weinstock RS. Perceived Burdens and benefits associated with continuous glucose monitor use in type 1 diabetes across the lifespan. J Diabetes Sci Technol. 2022;16(1):88–96. doi:10.1177/1932296820978769

69. Kahkoska AR, Smith C, Thambuluru S, et al. “Nothing is linear”: characterizing the determinants and dynamics of CGM use in older adults with type 1 diabetes. Diabet Res Clin Pract. 2023;196:110204. doi:10.1016/j.diabres.2022.110204

Creative Commons License © 2024 The Author(s). This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.