kelingwang/causation_strength_rating huggingface dataset:
Early-onset type 1 diabetes has been shown to be associated with potential long-term deficits in intellectual abilities, especially in the context of repeated episodes of severe hypoglycemia (513), and is correlated with higher A1C and sensor glucose values (514).
(See Section 14, �Children and Adolescents,� for information on early-onset diabetes and cognitive abilities and the effects of severe hypoglycemia on children�s cognitive and academic performance.)
Thus, for myriad reasons, cognitive capacity should be assessed during routine care to ascertain the person�s ability to maintain and adjust self-management behaviors, such as dosing of medications, remediation approaches to glycemic excursions, etc., and to determine whether to enlist a caregiver in monitoring and decision-making regarding management behaviors.
If cognitive capacity to carry out self-maintenance behaviors is questioned, an age-appropriate test of cognitive capacity is recommended (1).
Cognitive capacity should be evaluated in the context of the person�s age, for example, in very young children who are not expected to manage their disease independently and in older adults who may need active monitoring of treatment plan behaviors.
Cognitive decline is more severe in older adults with type 2 diabetes (515).
Longitudinal epidemiological studies have documented that chronic hyperglycemia, older age, less education, retinopathy, and nephropathy are associated with diabetes-related cognitive dysfunction (516).
Importantly, the risk of cognitive decline can be reduced through improved A1C (517).
Exercise may be a potential nonpharmacological treatment pathway for cognitive impairment in older adults with type 2 diabetes (518,519).
Strong evidence now exists on the benefits of virtual, telehealth, telephone-based, or internet-based DSMES for diabetes prevention and management in a wide variety of populations and age-groups of people with diabetes (44–56).
Technologies such as mobile apps, simulation tools, digital coaching, and digital self-management interventions can also be used to deliver DSMES (57–62).
These methods provide comparable or even improved outcomes compared with traditional in-person care (63).
Greater A1C reductions are demonstrated with increased engagement (64), although data from trials are considerably heterogeneous.
Technology-enabled diabetes self-management solutions improve A1C most effectively when there is two-way communication between the person with diabetes and the health care team, individualized feedback, use of person-generated health data, and education (47).
Continuous glucose monitoring (CGM), when combined with individualized diabetes education or behavioral interventions, has demonstrated greater improvement on glycemic and psychosocial outcomes compared with CGM alone (64,65).
Similarly, DSMES plus intermittently scanned CGM has demonstrated increased time in range (70–180 mg/dL [3.9–10.0 mmol/L]), less time above range, and a greater reduction in A1C compared with DSMES alone (66).
Incorporating a systematic approach for technology assessment, adoption, and integration into the care plan may help ensure equity in access and standardized application of technology-enabled solutions (www.diabeteseducator.org/danatech/home) (8,31,67–70).
The associations between sleep problems and diabetes are complex: sleep disorders are a risk factor for developing type 2 diabetes (520,521) and possibly gestational diabetes mellitus (522,523).
People with diabetes across the life span often experience sleep disruptions and reduced sleep quality (524,525), and sleep problems are also common in parents of youth with diabetes, especially soon after diagnosis (526,527).
Disrupted sleep and sleep disorders, including obstructive sleep apnea (528), insomnia, and sleep disturbances (529), are common among people with diabetes.
In type 1 diabetes, estimates of poor sleep range from 30% to 50% (530), and estimates of moderate to severe obstructive sleep apnea are >50% (531).
In type 2 diabetes, 24–86% of people are estimated to have obstructive sleep apnea (532), 39% to have insomnia, and 8–45% to have restless leg syndrome (i.e., an uncontrollable urge to move legs) (533).
Further, people with type 2 diabetes and restless leg syndrome are more likely to experience microvascular and macrovascular complications (534) as well as depression (535).
Additionally, people with diabetes who perform shift work increase their risk for circadian rhythm disorders, which are associated with higher A1C (536), neuropathy (537), and decreased psychological well-being (537).
Health care professionals should consider a comprehensive evaluation of the daily lifestyles of people with diabetes to decrease risk factors, including low sleep duration, shift work, and days off, given their associations with hyperglycemia, hypertension, dyslipidemia, and weight gain (538).
Sleep disturbances are associated with less engagement in diabetes self-management and may interfere with glucose levels within the target range among people with type 1 and type 2 diabetes (525,529,531,533,539,540).
Risk of hypoglycemia poses specific challenges for sleep in people with type 1 diabetes and may require targeted assessment and treatment approaches (541).
People with type 1 diabetes and their family members also describe diabetes management needs interfering with sleep and experiencing worries about poor sleep (542).
Both helpful and challenging aspects of diabetes technology use have been described in relation to sleep (542), with the greatest perceived benefits being related to automated insulin delivery systems (543–545).
For these reasons, detection and treatment of sleep disorders should be considered a part of standardized care for people with type 1 and type 2 diabetes.
As for the general population, there are evidence-based strategies to improve sleep for people with diabetes.
CBT shows benefits for sleep in people with diabetes (429), including CBT for insomnia, which demonstrates improvements in sleep outcomes and possible small improvements in A1C and fasting glucose (546).
There is also evidence that sleep extension and pharmacological treatments for sleep can improve sleep outcomes and possibly insulin resistance (541,546).
Lastly, sleep education, or sleep hygiene, improves sleep quality, reduces A1C, and decreases insulin resistance in adults with type 2 diabetes (547).
Thus, diabetes care professionals are encouraged to counsel people with diabetes to use sleep-promoting routines and practices, such as establishing a regular bedtime and rise time, creating a dark, quiet area for sleep with temperature and humidity control, establishing a pre-sleep routine, putting electronic devices (except diabetes management devices) in silent/off mode, exercising during the day, avoiding daytime naps, limiting caffeine and nicotine in the evening, avoiding spicy foods at night, and avoiding alcohol before bedtime (548).
For people with diabetes who have significant sleep difficulties, referral to sleep specialists to address the medical and behavioral aspects of sleep is recommended, ideally in collaboration with the diabetes care professional (Fig. 5.1).
Despite the benefits of DSMES, data from the 2017 and 2018 Behavioral Risk Factor Surveillance System of 61,424 adults with self-reported diabetes indicate that only 53% of individuals eligible for DSMES through their health insurance receive it (84).
Medicare reimburses DSMES when that service meets the national standards (2,56) and is recognized by the American Diabetes Association (ADA) through the Education Recognition Program (professional.diabetes.org/diabetes-education) or by the Association of Diabetes Care & Education Specialists (diabeteseducator.org/practice/diabetes-education-accreditation-program).
DSMES is also covered by most health insurance plans.
Ongoing support has been shown to be instrumental for improving outcomes when it is implemented after the completion of education services.
Medicare reimburses remote physiologic monitoring for glucose and other cardiometabolic data if certain conditions are met (89).
For Medicare Part B, the basics of the DSMES benefit include individual encounters reimbursable for the first 10 h (1 h of individual training and 9 h of group training); if special needs that would interfere with effective group participation are identified on the referral order, individual DSMES encounters are reimbursable for the initial 10 h.
For Medicaid, DSMES coverage varies by state.
Although DSMES is frequently reimbursed when performed in person, DSMES can also be provided via telehealth and phone calls (13).
These versions may not always be reimbursed; however, changes in reimbursement policies that increase DSMES access and utilization will result in a positive impact on beneficiaries� clinical outcomes, quality of life, health care utilization, and costs (13,90–92).
During the time of the coronavirus disease 2019 (COVID-19) pandemic, reimbursement policies were revised (professional.diabetes.org/content-page/dsmes-and-mnt-during-covid-19-national-pandemic), and these changes may provide a new reimbursement paradigm for future provision of DSMES through telehealth channels.
Per updated guidance from the Centers for Medicare & Medicaid Services, DSMES telehealth reimbursements remain the same as they were during the public health emergency for most practice settings.
Both ADA-recognized and Association of Diabetes Care & Education Specialists�accredited programs were added to the list of approved telehealth professionals via the Consolidated Appropriations Act, 2023.
The reimbursement of DSMES telehealth services was extended through the end of 2024.
Importantly, DSMES is paid on the physician fee schedule and not the outpatient prospective payment system.
Per the Consolidated Appropriations Act, 2023, distant-site health care professionals may be able to bill DSMES as a Medicare telehealth service through 31 December 2024.
Barriers to DSMES exist at the health system, payer, clinic, health care professional, and individual levels.
Low participation may be due to lack of referral or other identified barriers, such as logistical issues (accessibility, timing, and costs) and the lack of a perceived benefit (85).
Health system, clinic, programmatic, and payer barriers include lack of administrative leadership support, limited numbers of DSMES professionals, not having a referral to DSMES effectively embedded in the health system service structure, and limited reimbursement rates (86).
Thus, in addition to educating referring health care professionals about the benefits of DSMES and the critical times to refer, efforts need to be made to identify and address potential barriers at each level (2).
For example, a multilevel diabetes care intervention that combined clinical outreach, standardized protocols, and DSMES with SDOH screening and referrals to social needs support documented a 15% increase in receipt of DSMES, including among people on Medicaid (87).
Support from institutional leadership is foundational for the success of DSMES.
Expert stakeholders should also support DSMES by providing input and advocacy (56).
Alternative and innovative models of DSMES delivery (58) need to be explored and evaluated, including the integration of technology-enabled diabetes and cardiometabolic health services (8,68).
One potential model is virtual environments, which allow people with diabetes to self-represent as avatars and interact in a world with embedded informational resources accessed using principles of gamification.
An RCT testing DSMES in a virtual environment demonstrated greater weight loss but similar decreases in A1C, blood pressure, cholesterol, and triglycerides compared with DSMES via a standard website (88).
Barriers to equitable access to DSMES may be addressed through telehealth delivery of care, virtual environments, and other digital health solutions (56).
When the first ADA Standards of Care guidelines were published in 1989, nutrition was mentioned in two sentences in the entire 4-page document (93).
Even now, in 2024, the science of nutrition for diabetes continues to evolve.
At the same time, there has been change of emphasis from nutrients (macronutrients and micronutrients) to a focus on foods and, more broadly, dietary patterns.
This integrative approach aligns with the 2021 American Heart Association dietary guidance to improve cardiovascular health (94), the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines (95), the European Association for the Study of Diabetes/ADA type 1 consensus report (96) and type 2 consensus report (97), and the Dietary Guidelines for Americans, 2020–2025 (98).
Simply put, people eat food, not nutrients, and nutrient recommendations need to be applied to what people eat.
Additionally, macronutrients are not interchangeable entities and vary by nutrient type and quality.
As an example, carbohydrates include legumes, whole grains, and fruits and are in the same category as refined grains, but their health effects are very different (99).
For more detailed information on nutrition therapy, please refer to the ADA consensus report on nutrition therapy (73).
Contained in the report is an important and often repeated tenet, i.e., there is not a one-size-fits-all eating pattern for individuals with diabetes, and meal planning should be individualized.
Nutrition therapy plays an integral role in overall diabetes management, and each person with diabetes should be actively engaged in education, self-management, and treatment planning with the health care team, including the collaborative development of an individualized eating plan (73,100).
All health care professionals should refer people with diabetes for individualized MNT provided by an RDN who is knowledgeable and skilled in providing diabetes-specific MNT (101–103) at diagnosis and as needed throughout the life span, similar to DSMES.
MNT delivered by an RDN is associated with A1C absolute decreases of 1.0–1.9% for people with type 1 diabetes (104) and 0.3–2.0% for people with type 2 diabetes (104).
See Table 5.1  for specific nutrition recommendations.
Because of the progressive nature of type 2 diabetes, behavior modification alone may not be adequate to maintain euglycemia over time.
However, after medication is initiated, nutrition therapy continues to be an important component, and RDNs providing MNT in diabetes care should assess and monitor medication changes in relation to the nutrition care plan (73,100).
Obesity is defined by the World Health Organization as an abnormal or excessive fat accumulation that presents a risk to health (25).
BMI (calculated as weight in kilograms divided by the square of height in meters [kg/m2]) has been used widely to diagnose and stage obesity (overweight: BMI 25–29.9 kg/m2; obesity class I: BMI 30–34.9 kg/m2; obesity class II: BMI 35–39.9 kg/m2; obesity class III: BMI =40 kg/m2); however, BMI should not be relied on as a sole diagnostic and staging tool (19).
Despite its ease of measurement, BMI is at most an imperfect measure of adipose tissue mass and does not measure adipose tissue distribution or function, nor does it factor in the presence of weight-related health or well-being consequences (26,27).
BMI is especially prone to misclassification in individuals who are very muscular or frail, as well as in populations with different body composition and cardiometabolic risk (28).
A diagnosis of obesity should be made based on an overall assessment of the individual�s adipose tissue mass (BMI can be used as a general guidance), distribution (using other anthropometric measurements like waist circumference, waist-to-hip circumference ratio, or waist-to-height ratio), or function and, importantly, the presence of associated health or well-being consequences: metabolic, physical, or psychological/well-being (29).
Obesity is a key pathophysiologic driver of diabetes, other cardiovascular risk factors (e.g., hypertension, hyperlipidemia, nonalcoholic fatty liver disease, and inflammatory state), and ultimately cardiovascular and kidney disease (30).
Diabetes can further exacerbate obesity, setting up a vicious cycle that contributes to disease progression and occurrence of microvascular and macrovascular complications.
As such, treatment goals for both glycemia and weight are recommended in people with diabetes to address both hyperglycemia and its underlying pathophysiologic driver (obesity) and therefore benefit the person holistically.
A person-centered communication style that uses inclusive and nonjudgmental language and active listening to elicit individual preferences and beliefs and assesses potential barriers to care should be used to optimize health outcomes and health-related quality of life.
Use person-first language (e.g., �person with obesity� rather than �obese person�) to avoid defining people by their condition (26,31,32).
The nutrition choice should be based on the individual�s health status and preferences, including a determination of food availability and other cultural circumstances that could affect nutrition patterns (59).
Health disparities adversely affect people who have systematically experienced greater obstacles to health based on their race or ethnicity, socioeconomic status, gender, disability, or other factors.
Overwhelming research shows that these disparities may significantly affect health outcomes, including increasing the risk for obesity, diabetes, and diabetes-related complications.
Health care professionals should evaluate systemic, structural, and socioeconomic factors that may impact food choices, access to healthful foods, and nutrition patterns; behavioral patterns, such as neighborhood safety and availability of safe outdoor spaces for physical activity; environmental exposures; access to health care; social contexts; and, ultimately, diabetes risk and outcomes.
For a detailed discussion of social determinants of health, refer to �Social Determinants of Health: A Scientific Review� (79).
People with type 2 diabetes and overweight or obesity who have lost weight should be offered long-term (=1 year) comprehensive weight loss maintenance programs that provide at least monthly contact with trained individuals and focus on ongoing monitoring of body weight (weekly or more frequently) and/or other self-monitoring strategies such as tracking intake, steps, etc.; continued focus on nutrition and behavioral changes; and participation in high levels of physical activity (200–300 min/week) (63,64).
Some commercial and proprietary weight loss programs have shown promising weight loss results; however, results vary across these programs, most lack evidence of effectiveness, many do not satisfy guideline recommendations, and some promote unscientific and possibly dangerous practices (65,66).
Structured, very-low-calorie meals, typically 800–1,000 kcal/day, utilizing high-protein foods and meal replacement products, may increase the pace and/or magnitude of initial weight loss and glycemic improvements compared with standard behavioral interventions (20,21).
However, such an intensive nutritional intervention should be provided only by trained practitioners in medical settings with close ongoing monitoring and integration with behavioral support and counseling, and only for short term (generally up to 3 months).
Furthermore, due to the high risk of complications (electrolyte abnormalities, severe fatigue, cardiac arrhythmias, etc.), such intensive intervention should be prescribed only to carefully selected individuals, such as those requiring weight loss and/or glycemic management before a needed surgery, if the benefits exceed the potential risks (67–69).
As weight recurrence is common, such interventions should include long-term, comprehensive weight maintenance strategies and counseling to maintain weight loss and behavioral changes (70,71).
Despite widespread marketing and exorbitant claims, there is no clear evidence that nutrition supplements (such as herbs and botanicals, high-dose vitamins and minerals, amino acids, enzymes, antioxidants, etc.) are effective for obesity management or weight loss (72–75).
Several large systematic reviews show that most trials evaluating nutrition supplements for weight loss are of low quality and at high risk for bias.
High-quality published studies show little or no weight loss benefits.
In contrast, vitamin/mineral (e.g., iron, vitamin B12, vitamin D) supplementation may be indicated in cases of documented deficiency (76), and protein supplements may be indicated as adjuncts to medically supervised weight loss therapies (77,78).
Measurement of weight and height (to calculate BMI) and other anthropometric measurements... (33).
...should be performed at least annually to aid the diagnosis of obesity and to monitor its progression and response to treatment (33).
Clinical considerations, such as the presence of comorbid heart failure or unexplained weight change, may warrant more frequent evaluation (34,35).
If such measurements are questioned or declined by the individual, the practitioner should be mindful of possible prior stigmatizing experiences and query for concerns, and the value of monitoring should be explained as a part of the medical evaluation process that helps to inform treatment decisions (36,37).
Accommodations should be made to ensure privacy during weighing and other anthropometric measurements, particularly for those individuals who report or exhibit a high level of disease-related distress or dissatisfaction.
Anthropometric measurements should be performed and reported nonjudgmentally; such information should be regarded as sensitive health information.
Health care professionals should advise individuals with overweight or obesity and those with increasing weight trajectories that, in general, greater fat accumulation increases the risk of diabetes, cardiovascular disease, and all-cause mortality and has multiple adverse health and quality of life consequences.
Health care professionals should assess readiness to engage in behavioral changes for weight loss and jointly determine behavioral and weight loss goals and individualized intervention strategies using shared decision-making (38).
Strategies may include nutrition and dietary changes, physical activity and exercise, behavioral counseling, pharmacotherapy, medical devices, and metabolic surgery.
The initial and subsequent therapeutic choice should be individualized based on the person�s medical history, life circumstances, preferences, and motivation (39).
Combination treatment approaches may be appropriate in higher-risk individuals.
Among people with type 2 diabetes and overweight or obesity who have inadequate glycemic, blood pressure, and lipid management and/or other obesity-related metabolic complications, modest and sustained weight loss (3–7% of body weight) improves glycemia, blood pressure, and lipids and may reduce the need for disease-specific medications (7–9,40).
In people at risk, 3–7% weight loss reduces progression to diabetes (2,7,8,41,42).
Greater weight loss may produce additional benefits (20,21).
Mounting data have shown that >10% body weight loss usually confers greater benefits on glycemia and possibly diabetes remission and improves other metabolic comorbidities, including cardiovascular outcomes, nonalcoholic steatohepatitis, nonalcoholic fatty liver disease, adipose tissue inflammation, and sleep apnea, as well as physical comorbidities and quality of life (6,20,21,30,41,43–52).
With the increasing availability of more effective treatments, individuals with diabetes and overweight or obesity should be informed of the potential benefits of both modest and more substantial weight loss and guided in the range of available treatment options, as discussed in the sections below.
Shared decision-making should be used when counseling on behavioral changes, intervention choices, and weight management goals.
For a more detailed discussion of lifestyle management approaches and recommendations, see Section 5, �Facilitating Positive Health Behaviors and Well-being to Improve Health Outcomes.� For a detailed discussion of nutrition interventions, please also refer to �Nutrition Therapy for Adults With Diabetes or Pre-diabetes: A Consensus Report� (53).