A Wearable Technology Delivering a Web-Based Diabetes Prevention Program to People at High Risk of Type 2 Diabetes: Randomized Controlled Trial

Wearable monitoring device based on an internet management platform improves metabolic parameters in type 2 diabetes patients: a prospective pilot study

OBJECTIVES

This pilot study aimed to prospectively investigate the effects of a wearable monitoring device, based on an Internet management platform, on the comprehensive management of type 2 diabetes mellitus (T2DM) patients.

METHODS

A total of 120 hospitalized patients with T2DM were enrolled and randomly divided into the control group and the intervention group. Patients in the control group only received conventional diabetes treatments, while patients in the intervention group were provided with a wearable monitoring device in addition to conventional diabetes treatments. Moreover, the wearable device could connect to an Internet platform for diabetes management and upload self-monitoring data. All patients were followed for 3 months. The changes in parameters representing glucose metabolism, blood lipids, renal function, and patient satisfaction were compared between the two groups. All results were analyzed on an intention-to-treat basis.

RESULTS

One hundred twenty subjects met all criteria and agreed to participate in this study. During the follow-up period, 5 and 4 subjects were lost to follow-up in the intervention and control groups, respectively. Compared with the control group, the blood glucose of the intervention group decreased significantly after 3 months (p < 0.05). Subgroup analysis found that females, those younger than 60 years, with baseline glycated hemoglobin A1c (HbA1c) levels of 8% or greater, and patients with good adherence showed significant improvements in HbA1c (p < 0.05). However, there was no significant difference in blood lipid and renal function. The intervention group showed a better adherence rate to blood glucose, comprehensive adherence rate, and diabetes treatment satisfaction (p < 0.05). One subject in the intervention group and two subjects in the control group reported mild hypoglycemia. No other adverse events such as infections and skin allergies occurred in the two groups.

CONCLUSION

The intervention of a wearable monitoring device based on an Internet management platform significantly improved blood glucose control in T2DM patients, as well as the overall adherence rate and patient satisfaction with treatment.

CLINICAL TRIAL REGISTRATION

NCT04973644.

Smartphone Applications to Prevent Type 2 Diabetes: A Systematic Review and Meta-Analysis

INTRODUCTION

Evidence supporting the use of apps for lifestyle behavior change and diabetes prevention in people at high risk of diabetes is lacking. The aim of this systematic review was to determine the acceptability and effectiveness of smartphone applications (apps) for the prevention of type 2 diabetes.

METHODS

PubMed, Embase, CINAHL and PsychInfo were searched from 2008 to 2023. Included studies involved adults at high risk of developing diabetes evaluating an app intervention with the aim of preventing type 2 diabetes. Random-effects meta-analyses were conducted for weight loss, body mass index (BMI), glycated hemoglobin, and waist circumference. Narrative synthesis was conducted for all studies, including qualitative studies exploring user perspectives.

RESULTS

Twenty-four studies (n=2,378) were included in this systematic review, including 9 randomized controlled trials (RCTs) with an average duration of 6 months, 10 quasi-experimental and 7 qualitative studies. Socially disadvantaged groups were poorly represented. Six RCTs were combined in meta-analyses. Apps were effective at promoting weight loss [mean difference (MD) -1.85; 95% CI -2.90 to -0.80] and decreasing BMI [MD -0.90, 95% CI -1.53 to -0.27], with no effect on glycated hemoglobin and waist circumference. No studies reported on diabetes incidence. Qualitative studies highlighted the need for app personalization.

DISCUSSION

Smartphone apps have a promising effect on preventing type 2 diabetes by supporting weight loss. Future robust trials should include diverse populations in co-design and evaluation of apps and explore the role of artificial intelligence in further personalizing interventions for higher engagement and effectiveness.

Digital interventions for self-management of prediabetes: A scoping review

BACKGROUND

Rates of prediabetes, which can lead to type 2 diabetes, are increasing worldwide. Interventions for prediabetes mainly focus on lifestyle changes to diet and exercise. While these interventions are effective, they are often delivered face-to-face, which may pose a barrier to those with limited access to healthcare. Given the evidence for digital interventions addressing other noncommunicable diseases, these may also be effective for prediabetes self-management. The aim of this scoping review was to assess the breadth of evidence around digital interventions for prediabetes self-management.

METHODS

We developed a targeted search strategy and relevant studies were identified through searches conducted in four bibliographic databases (Medline, Embase, PsycInfo, and Scopus). Published studies were eligible if they included a digital intervention to support adults aged 18+ with prediabetes self-management. Titles and abstracts were first screened for relevance by one researcher. Full texts of selected records were assessed against the review criteria independently by two researchers for inclusion in the final analysis.

RESULTS

Twenty-nine studies were included, of which nine were randomised controlled trials. Most efficacy studies reported significant changes in at least one primary and/or secondary outcome, including participants' glycaemic control, weight loss and/or physical activity levels. About one-third of studies reported mixed outcomes or early significant outcomes that were not sustained at long-term follow-up. Interventions varied in length, digital modalities, and complexity. Delivery formats included text messages, mobile apps, virtually accessible dietitians/health coaches, online peer groups, and web-based platforms. Approximately half of studies assessed participant engagement/acceptability outcomes.

CONCLUSION

Whilst the evidence here suggests that digital interventions to support prediabetes self-management are acceptable and have the potential to reduce one's risk of progression to type 2 diabetes, more research is needed to understand which interventions, and which components specifically, have the greatest reach to diverse populations, are most effective at promoting user engagement, and are most effective in the longer term.

Global trends in the burden of chronic kidney disease attributable to type 2 diabetes: An age-period-cohort analysis

AIM

To assess temporal trends of chronic kidney disease (CKD) attributable to type 2 diabetes (T2D) globally and in five sociodemographic index (SDI) regions.

MATERIALS AND METHODS

We extracted the population data and CKD burden attributable to T2D from the Global Burden of Disease Study 2019. We evaluated the trends of disability-adjusted life years (DALYs), mortality, prevalence and incidence through age-period-cohort modelling, and calculated net drifts (overall annual percentage changes), local drifts (annual percentage changes in each age group), longitudinal age curves (fitted longitudinal age-specific rates), period relative risks (RRs) and cohort RRs.

RESULTS

From 1990 to 2019, the global burden of CKD attributable to T2D showed increasing trends in general. The burden of CKD attributable to T2D was highest in the middle SDI region and lowest in the low SDI region. Age effects increased with age, and peaked at the ages of 75-79 and 80-84 years for incidence and prevalence, respectively. Period RRs in the burden of CKD attributable to T2D increased, with the high SDI being the most remarkable in DALYs and mortality, and the middle SDI being the most notable in incidence. Cohort RRs showed unfavourable trends in incidence and prevalence among recent cohorts.

CONCLUSIONS

After a lengthy period of multi-initiative diabetes management, the high-middle SDI region exhibited improvement. However, unresolved issues and improvement gaps were still remarkable. Future efforts to reduce the burden of CKD attributable to T2D in the population should prioritize addressing the unfavourable patterns identified.

Developing and evaluating the usability of a web-based Diabetic Retinopathy Health Education Program for patients with type 2 diabetes mellitus

OBJECTIVES

To describe the development of a webpage based on the Intervention Mapping (IM) protocol and usability testing of the Diabetic Retinopathy Health Education Profram (DRHEP).

METHODS

The mixed methods pilot feasibility study was carried out between April and September 2021, involving 16 patients with type 2 diabetes mellitus and 5 experts. The usability score was rated according to the System Usability Scale (SUS).

RESULTS

The average SUS score by the experts was 88. The patients gave a higher score of 85 for SUS, with 58 as the lowest. The average SUS score was 72. The findings indicate that the webpage is acceptable, good, and highly usable for users.

CONCLUSION

The outcomes of this study signify the relationship between effective health applications and how their design might hamper their effectiveness in changing patients' behavior.

Is Web-Based Program Effective on Self-Care Behaviors and Glycated Hemoglobin in Patients with Type 2 Diabetes: A Randomized Controlled Trial

Background

Diabetes Self-Management Education and Support (DSMES) as a framework focuses on seven self-care behaviors. Moreover, technology-assisted self-care education is increasingly suggested for patients with Type 2 Diabetes Mellitus (T2DM). Therefore, we examined the effect of a web-based program on self-care behaviors and glycated hemoglobin values in patients with diabetes mellitus.

Materials and Methods

This randomized controlled clinical trial was conducted at Alzahra Hospital in Isfahan, Iran, between April and November 2020 and included 70 patients with T2DM. Data were collected using a questionnaire that included a demographic information section and a diabetes self-management section with 21 questions on a Likert scale. Fasting blood samples (2.50 ml) were collected before and after the interventions to measure HbA1c levels. The study intervention involved a web-based program that included multimedia educational content (such as videos, lectures, educational motion graphics, text files, posters, and podcasts) presented in seven sections based on DSMES over a 21-day period with monitoring by an instructor.

Results

The mean scores for healthy eating (F = 3.48, p = 0.034) and medication adherence (F = 6.70, p < 0.001) significantly increased in the interventional group, while the mean scores for being active, monitoring, reducing risks, problem-solving, and healthy coping did not significantly change. Additionally, the mean differences in HbA1c values significantly improved in the interventional group compared to the control (F = 5,1, p = 0.026).

Conclusions

A web-based program in accordance with DSMES improved HbA1c levels and increased scores for healthy eating and medication adherence in patients with T2DM. However, further research with larger sample sizes and qualitative interviews is needed.

Dietary flavonoids prevent diabetes through epigenetic regulation: advance and challenge

The pathophysiology of diabetes has been studied extensively in various countries, but effective prevention and treatment methods are still insufficient. In recent years, epigenetics has received increasing attention from researchers in exploring the etiology and treatment of diabetes. DNA methylation, histone modifications, and non-coding RNAs play critical roles in the occurrence, maintenance, and progression of diabetes and its complications. Therefore, preventing or reversing the epigenetic alterations that occur during the development of diabetes may reduce the individual and societal burden of the disease. Dietary flavonoids serve as natural epigenetic modulators for the discovery of biomarkers for diabetes prevention and the development of alternative therapies. However, there is limited knowledge about the potential beneficial effects of flavonoids on the epigenetics of diabetes. In this review, the multidimensional epigenetic effects of different flavonoid subtypes in diabetes were summarized. Furthermore, it was discussed that parental flavonoid diets might reduce diabetes incidence in offspring, which represent a promising opportunity to prevent diabetes in the future. Future work will depend on exploring anti-diabetic effects of different flavonoids with different epigenetic regulation mechanisms and clinical trials.Highlights• "Epigenetic therapy" could reduce the burden of diabetic patients• "Epigenetic diet" ameliorates diabetes• Targeting epigenetic regulations by dietary flavonoids in the diabetes prevention• Dietary flavonoids prevent diabetes via transgenerational epigenetic inheritance.

Analyzing the Effectiveness of mHealth to Manage Diabetes Mellitus Among Adults Over 50: A Systematic Literature Review

Purpose

A total of 537 million suffered from diabetes mellitus in 2021, and the aging of the population will not abate this number in the future. Diabetes predisposes people to ailments and doubles the risk of COVID-19 mortality. mHealth has shown promise to help manage diabetes. The aim of this review is to objectively analyze research from the last 2.5 years to assess effectiveness where mHealth has been used as an intervention to help manage diabetes in older patients. We also analyzed patient satisfaction, quality, and barriers to adoption of mHealth to manage diabetes.

Patients and Methods

No human subjects were involved in this review. We queried four research databases for mHealth to manage diabetes in older adults. We conducted the review based on the Kruse Protocol for writing as systematic review and we reported our findings in accordance with PRISMA (2020).

Results

Thirty research articles from 11 countries were analyzed. Five interventions of mHealth were identified. Of these mHealth Short Message service (SMS) helped change behavior and encouraged self-care. mHealth SMS coupled with telemedicine for coaching showed positive effects on weight loss, BMI, diet, exercise, HbA1C, disease awareness, blood pressure, cholesterol, medication adherence, and foot care.

Conclusion

mHealth SMS coupled with telemedicine for coaching shows the greatest promise for educating, changing behavior, and realizing positive outcomes across a broad spectrum of health factors. The largest drawback is the cost of acquiring equipment and training users.

Type 2 diabetes

Type 2 diabetes accounts for nearly 90% of the approximately 537 million cases of diabetes worldwide. The number affected is increasing rapidly with alarming trends in children and young adults (up to age 40 years). Early detection and proactive management are crucial for prevention and mitigation of microvascular and macrovascular complications and mortality burden. Access to novel therapies improves person-centred outcomes beyond glycaemic control. Precision medicine, including multiomics and pharmacogenomics, hold promise to enhance understanding of disease heterogeneity, leading to targeted therapies. Technology might improve outcomes, but its potential is yet to be realised. Despite advances, substantial barriers to changing the course of the epidemic remain. This Seminar offers a clinically focused review of the recent developments in type 2 diabetes care including controversies and future directions.

The Use of Mobile Health Interventions for Outcomes among Middle-Aged and Elderly Patients with Prediabetes: A Systematic Review

BACKGROUND

There are currently limited systematic reviews of mobile health interventions for middle-aged and elderly patients with prediabetes from trial studies. This review aimed to gather and analyze information from experimental studies investigating the efficacy of mobile health usability for outcomes among middle-aged and elderly patients with prediabetes.

METHODS

We conducted a literature search in five databases: Clinicaltrials.gov, the International Clinical Trials Registry Platform (ICTRP), PubMed, ProQuest, and EBSCO, with a date range of January 2007 to July 2022 written in English, following a registered protocol on PROSPERO (CRD42022354351). The quality and possibility of bias were assessed using the Jadad score. The data extraction and analysis were conducted in a methodical manner.

RESULTS

A total of 25 studies were included in the qualitative synthesis, with 19 studies using randomized trial designs and 6 studies with non-randomized designs. The study outcomes were the incidence of diabetes mellitus, anthropometric measures, laboratory examinations, measures of physical activity, and dietary behavior. During long-term follow-up, there was no significant difference between mobile health interventions and controls in reducing the incidence of type 2 diabetes. The findings of the studies for weight change, ≥3% and ≥5% weight loss, body mass index, and waist circumference changes were inconsistent. The efficacy of mobile health as an intervention for physical activity and dietary changes was lacking in conclusion. Most studies found that mobile health lacks sufficient evidence to change hbA1c. According to most of these studies, there was no significant difference in blood lipid level reduction.

CONCLUSIONS

The use of mobile health was not sufficiently proven to be effective for middle-aged and elderly patients with prediabetes.

Effects of Feedback From Self-Monitoring Devices on Lifestyle Changes in Workers with Diabetes: 3-Month Randomized Controlled Pilot Trial

Background

Although lifestyle interventions are useful in the prevention and management of diabetes, they can be expensive and time-consuming. There is some evidence on the effectiveness of automated mobile technology for health self-monitoring; however, few studies have used such devices in the occupational health field.

Objective

We aimed to examine the effectiveness of a digital self-monitoring device on glucose levels and activity of workers with diabetes in Japan. The primary outcomes were changes in blood glucose levels, and the secondary outcomes were changes in weight and BMI.

Methods

A 2-arm randomized controlled pilot trial was conducted with workers from 23 organizations. The intervention group (n=50) wore an armband activity monitor, a body composition monitor, and a blood pressure monitor for 3 months and received semiautomated weekly email messages tailored to their device data. The control group (n=53) engaged in no self-monitoring. Messages were developed by a physician and a dietician. Postintervention changes in blood glucose levels, weight, and BMI were compared between the intervention and control groups, using blood tests and questionnaires.

Results

At the end of 3 months, the intervention group showed significantly lower blood glucose levels (HbA1c: intervention group mean 6.4% (SD 0.3%) vs control group mean 6.6% (SD 0.3%); Cohen d=0.7, 95% CI 0.2-1.1; P=.009). There were no significant between-group differences in weight and BMI.

Conclusions

Mobile digital self-monitoring was effective in improving blood glucose levels in workers with diabetes. The use of digital health devices is a cost-effective way of implementing health self-monitoring for large numbers of individuals in the workplace. However, due to the large volume of missing values in this study, we need to be careful in interpreting the results, and well-designed intervention studies need to be conducted.

Trial Registration

University Hospital Medical Information Network UMIN000023651; https://upload.umin.ac.jp/cgi-open-bin/icdr/ctr_view_cb.cgi?recptno=R000027244&flwp_key=1008PYbOcXKmk7CAg4Th1FWS

Effects of self-care programs on the incidence of diabetes among adults with prediabetes: A systematic review and meta-analysis of randomised controlled trials

OBJECTIVES

To verify the effects of self-care programs among adults with prediabetes, to identify the preferable structure components and to summarise the core content components of self-care programs.

DESIGN

A systematic review and meta-analysis of randomised controlled trials.

METHODS

PubMed, Embase, Cochrane, CINAHL, PsycINFO, Wanfang, CNKI, Chinese Biomedical Database and Open Grey were searched for studies published from January 2002 to December, 2021. Meta-analysis was conducted to verify the effects of self-care programs on diabetes incidence. Subgroup analyses based on structure components were performed to contrast the effects. We made a critical analysis to generalise the core elements of content components. The study was reported according to PRISMA statement.

RESULTS

Totally, 15 studies were included in systematic review, of which 14 studies were eligible for meta-analysis. The results of meta-analysis showed the incidence of diabetes for prediabetic adults receiving self-care programs was significantly lower than those who received usual care (OR 0.58; 95% CI 0.46 to 0.73). The results of subgroup analyses based on delivery mode, intervention implementer, health education brochures provided, and follow-up duration showed statistically significant reduction in incidence compared with control group (p < .05). However, the differences of these pair-wise comparisons (face-to-face or remote, individual or interdisciplinary team, with or without brochures provided, ≤1 year or >1 year) were not statistically significant (p > .05). Three core content elements were generalised: cognitive education, behaviour guidance and psychological support.

CONCLUSIONS

Self-care programs can effectively delay the progression of prediabetes to diabetes. Regardless of the diversified structure components, self-care programs can achieve better effects on the diabetes incidence than usual care, while the optimal structure components still remain unknown. Cognitive education, behaviour guidance and psychological support are core elements for these programs.

RELEVANCE TO CLINICAL PRACTICE

More clinical trials with rigorous study design are needed to provide further evidence.

Effectiveness of Motivational Interviewing in Managing Overweight and Obesity : A Systematic Review and Meta-analysis

BACKGROUND

Motivational interviewing (MI) is potentially useful in management of overweight and obesity, but staff training and increased delivery time are barriers, and its effectiveness independent of other behavioral components is unclear.

PURPOSE

To assess the independent contribution of MI as part of a behavioral weight management program (BWMP) in controlling weight and improving psychological well-being.

DATA SOURCES

6 electronic databases and 2 trial registries, searched from database inception through 24 September 2021.

STUDY SELECTION

Randomized controlled trials in adults or adolescents aimed at weight loss or maintenance and comparing programs incorporating MI versus interventions without MI.

DATA EXTRACTION

Two reviewers independently screened studies, extracted data, and assessed risk of bias. Outcomes included weight, anxiety, depression, quality of life, and other aspects of psychological well-being. Pooled mean differences or standardized mean differences were obtained using random- and fixed-effects meta-analyses.

DATA SYNTHESIS

Forty-six studies involving 11 077 participants, predominantly with obesity, were included. At 6 months, BWMPs using MI were more effective than no/minimal intervention (-0.88 [95% CI, -1.27 to -0.48] kg; I ² = 0%) but were not statistically significantly more effective than lower-intensity (-0.88 [CI, -2.39 to 0.62] kg; I ² = 55.8%) or similar-intensity (-1.36 [CI, -2.80 to 0.07] kg; I ² = 18.8%) BWMPs. At 1 year, data were too sparse to pool comparisons with no/minimal intervention, but MI did not produce statistically significantly greater weight change compared with lower-intensity (-1.16 [CI, -2.49 to 0.17] kg; I ² = 88.7%) or similar-intensity (-0.18 [CI, -2.40 to 2.04] kg; I ² = 72.7%) BWMPs without MI. Studies with 18-month follow-up were also sparse; MI did not produce statistically significant benefit in any of the comparator categories. There was no evidence of subgroup differences based on study, participant, or intervention characteristics. Too few studies assessed effects on psychological well-being to pool, but data did not suggest that MI was independently effective.

LIMITATIONS

High statistical heterogeneity among studies, largely unexplained by sensitivity and subgroup analyses; stratification by comparator intensity and follow-up duration resulted in pooling of few studies.

CONCLUSION

There is no evidence that MI increases effectiveness of BWMPs in controlling weight. Given the intensive training required for its delivery, MI may not be a worthwhile addition to BWMPs.

PRIMARY FUNDING SOURCE

National Institute for Health Research Biomedical Research Centre. (PROSPERO: CRD42020177259).

mHealth prompts within diabetes prevention programs: a scoping review

BACKGROUND

Mobile health (mHealth) prompts (e.g., text messaging, push notifications) are a commonly used technique within behaviour change interventions to prompt or cue a specific behaviour. Such prompts are being increasingly integrated into diabetes prevention programs (DPPs). While mHealth prompts provide a convenient and cost-effective way to reinforce behaviour change, no reviews to date have examined mHealth prompt use within DPPs. This scoping review aims to: (I) understand how mHealth prompts are being used within behaviour change interventions for individuals at risk for developing type 2 diabetes (T2D); and (II) provide recommendations for future mHealth prompt research, design, and application.

METHODS

The scoping review methodology outlined by Arksey and O'Malley were followed. Medline, CINAHL, PsycInfo, Web of Science, and SportDiscus were searched. The search strategy combined keywords relating to T2D risk and mHealth prompts in conjunction with database-controlled vocabulary when available (e.g., MeSH for Medline).

RESULTS

Of the 4,325 publications screened, 44 publications (based on 33 studies) met the inclusion criteria and were included for data extraction. Text messaging was the most widely used mHealth prompt (73%) followed by push notifications (21%). Only 30% of studies discussed the theoretical basis for prompt content and time of day messages were sent, and only 27% provided justification for prompt timing and frequency. Fourteen studies assessed participant satisfaction with mHealth prompts of which only two reported dissatisfaction due to either prompting frequency (hourly) or message content (solely focused on weight). Nine studies assessed behavioural outcomes including weight loss, physical activity, and diabetes incidence, and found mixed effects overall.

CONCLUSIONS

While mHealth prompts were well-received by participants, there are mixed effects on the influence of mHealth prompts on behavioural outcomes and diabetes incidence. More thorough reporting of prompt content development and delivery is needed, and more experimental research is needed to identify optimal content, delivery characteristics, and impact on behavioural and clinical outcomes.

Effectiveness of Wearable Device-based Intervention on Glycemic Control in Patients with Type 2 Diabetes: A System Review and Meta-Analysis

With the development of flexible electronics and chip technology, the application value of wearable devices in lifelong treatment of chronic diseases is increasing. In view of its rapid development and diversified forms, wearable device-based intervention seems to provide a promising option to solve the problems of long-term glycemic control in type 2 diabetes (T2D). However, to date, it is unclear whether the intervention based on wearable device is effective on glycemic control in patients with T2D. In order to explore whether this choice is effective in glycemic control in patients with T2D, after database search and study screening, 6 studies and 1001 patients were selected from 181studies for this meta-analysis. The results guided that the wearable device-based intervention may be more effective than usual care on glycemic control in patients with T2D. Subgroup analysis showed that when the duration of intervention was equal to or less than 12 weeks, the effect of wearable device-based intervention was significantly different from that of usual care, but when the intervention duration greater than 12 weeks, the effect was not significantly different. The intervention effect of wearable devices with goal-setting or encouragement functions was significantly better than that of usual care, and there was no significant difference between automatic drug delivery wearable devices and usual care. In conclusion, the wearable device-based intervention is effective on glycemic control in patients with T2D. In general, this choice of wearable devices for patients with T2D may be effective to some extent.

Using Wearable Activity Trackers to Predict Type 2 Diabetes: Machine Learning-Based Cross-sectional Study of the UK Biobank Accelerometer Cohort

BACKGROUND

Between 2013 and 2015, the UK Biobank collected accelerometer traces from 103,712 volunteers aged between 40 and 69 years using wrist-worn triaxial accelerometers for 1 week. This data set has been used in the past to verify that individuals with chronic diseases exhibit reduced activity levels compared with healthy populations. However, the data set is likely to be noisy, as the devices were allocated to participants without a set of inclusion criteria, and the traces reflect free-living conditions.

OBJECTIVE

This study aims to determine the extent to which accelerometer traces can be used to distinguish individuals with type 2 diabetes (T2D) from normoglycemic controls and to quantify their limitations.

METHODS

Machine learning classifiers were trained using different feature sets to segregate individuals with T2D from normoglycemic individuals. Multiple criteria, based on a combination of self-assessment UK Biobank variables and primary care health records linked to UK Biobank participants, were used to identify 3103 individuals with T2D in this population. The remaining nondiabetic 19,852 participants were further scored on their physical activity impairment severity based on other conditions found in their primary care data, and those deemed likely physically impaired at the time were excluded. Physical activity features were first extracted from the raw accelerometer traces data set for each participant using an algorithm that extends the previously developed Biobank Accelerometry Analysis toolkit from Oxford University. These features were complemented by a selected collection of sociodemographic and lifestyle features available from UK Biobank.

RESULTS

We tested 3 types of classifiers, with an area under the receiver operating characteristic curve (AUC) close to 0.86 (95% CI 0.85-0.87) for all 3 classifiers and F1 scores in the range of 0.80-0.82 for T2D-positive individuals and 0.73-0.74 for T2D-negative controls. Results obtained using nonphysically impaired controls were compared with highly physically impaired controls to test the hypothesis that nondiabetic conditions reduce classifier performance. Models built using a training set that included highly impaired controls with other conditions had worse performance (AUC 0.75-0.77; 95% CI 0.74-0.78; F1 scores in the range of 0.76-0.77 for T2D positives and 0.63-0.65 for controls).

CONCLUSIONS

Granular measures of free-living physical activity can be used to successfully train machine learning models that are able to discriminate between individuals with T2D and normoglycemic controls, although with limitations because of the intrinsic noise in the data sets. From a broader clinical perspective, these findings motivate further research into the use of physical activity traces as a means of screening individuals at risk of diabetes and for early detection, in conjunction with routinely used risk scores, provided that appropriate quality control is enforced on the data collection protocol.

Real-Time Continuous Glucose Monitoring During the Coronavirus Disease 2019 Pandemic and Its Impact on Time in Range

Background: The coronavirus disease 2019 (COVID-19) pandemic disrupted the lives of people with diabetes. Use of real-time continuous glucose monitoring (rtCGM) helped manage diabetes effectively. Some of these disruptions may be reflected in population-scale changes to metrics of glycemic control, such as time-in-range (TIR). Methods: We examined data from 65,067 U.S.-based users of the G6 rtCGM System (Dexcom, Inc., San Diego, CA) who had uploaded data before and during the COVID-19 pandemic. Users associated with three counties that included the cities of Los Angeles, Chicago, and New York or with five regions designated by the Centers for Disease Control and Prevention (CDC) were compared. Public data were used to associate regions with prepandemic and intrapandemic glycemic parameters, COVID-19 mortality, and median household income. Results: Compared with an 8-week prepandemic interval before stay-at-home orders (January 6, 2020, to March 1, 2020), overall mean (standard deviation) TIR improved from 59.0 (20.1)% to 61.0 (20.4)% during the early pandemic period (April 20, 2020 to June 14, 2020, P < 0.001). TIR improvements were noted in all three counties and in all five CDC-designated regions. Higher COVID-19 mortality was associated with higher proportions of individuals experiencing TIR improvements of ≥5 percentage points. Users in economically wealthier zip codes had higher pre- and intrapandemic TIR values and greater relative improvements in TIR. TIR and pandemic-related improvements in TIR varied across CDC-designated regions. Conclusions: Population-level rtCGM data may be used to monitor changes in glycemic control with temporal and geographic specificity. The COVID-19 pandemic is associated with improvements in TIR, which were not evenly distributed across the United States.