Acceptability of Continuous Glucose Monitoring in Free-Living Healthy Individuals: Implications for the Use of Wearable Biosensors in Diet and Physical Activity Research

Innovative solution or cause for concern? The use of continuous glucose monitors in people not living with diabetes: A narrative review

AIMS

Continuous glucose monitors (CGMs) have expanded their scope beyond indicated uses for diabetes management and are gaining traction among people not living with diabetes (PNLD). CGMs track in time glucose levels and are proposed as tools for the early detection of abnormal glucose and a potential solution for its normalisation through behavioural change, particularly, diet personalisation and motivation of physical activity. This becomes relevance given the growing incidence of metabolic conditions, such as type 2 diabetes mellitus (T2DM). Clinical guidelines, however, do not recommend CGMs in contexts outside type 1 diabetes (T1DM) or insulin-treated T2DM. Therefore, there is a visible disconnect between the indicated and real-world usage of these medical devices. While the commercial market for CGMs in PNLD is expanding rapidly, a comprehensive and evidence-based evaluation of the devices' utility in this population has not been done. Therefore, this review aims to formulate a working model for CGM utility in PNLD as proposed by the 'health and wellness' market that advertises and distributes it to these individuals.

METHODS

We aim to critically analyse the available research addressing components of the working model, that is (1) detection of abnormal glucose; (2) behavioural change, and (3) metabolic health improvement.

RESULTS

We find a lack of consistent and high-quality evidence to support the utility of CGMs for these purposes. We identify significantly under-reserved areas including clinical benchmarks and scoring procedures for CGM measures, device acceptability, and potential adverse effects of CGMs on eating habits in PNLD. We also raise concerns about the robustness of available CGM research.

CONCLUSION

In the face of these research gaps, we urge for the commercial claims suggesting the utility of the device in PNLD to be labelled as misleading. We argue that there is a regulatory inadequacy that fuels 'off-label' CGM distribution and calls for the strengthening of post-market clinical follow-up oversight for CGMs. We hope this will help to avert the continued misinformation risk to PNLD and 'off-label' exacerbation of health disparities.

Adding a Brief Continuous Glucose Monitoring Intervention to the National Diabetes Prevention Program: A Multimethod Feasibility Study

The National Diabetes Prevention Program (DPP) promotes lifestyle changes to prevent diabetes. However, only one-third of DPP participants achieve weight loss goals, and changes in diet are limited. Continuous glucose monitoring (CGM) has shown potential to raise awareness about the effects of diet and activity on glucose among people with diabetes, yet the feasibility of including CGM in behavioral interventions for people with prediabetes has not been explored. This study assessed the feasibility of adding a brief CGM intervention to the Arizona Cooperative Extension National DPP. Extension DPP participants were invited to participate in a single CGM-based education session and subsequent 10-day CGM wear period, during which participants reflected on diet and physical activity behaviors occurring prior to and after hyperglycemic events. Following the intervention, participants completed a CGM acceptability survey and participated in a focus group reflecting on facilitators and barriers to CGM use and its utility as a behavior change tool. A priori feasibility benchmarks included opt-in participation rates ≥ 50%, education session attendance ≥ 80%, acceptability scores ≥ 80%, and greater advantages than disadvantages of CGM emerging from focus groups, as analyzed using the Key Point Summary (KPS) method. Thirty-five DPP members were invited to participate; 27 (77%) consented, and 24 of 27 (89%) attended the brief CGM education session. Median survey scores indicated high acceptability of CGM (median = 5, range = 1-5), with nearly all (n = 23/24, 96%) participants believing that CGM should be offered as part of the DPP. In focus groups, participants described how CGM helped them make behavior changes to improve their glucose (e.g., reduced portion sizes, increased activity around eating events, and meditation). In conclusion, adding a single CGM-based education session and 10-day CGM wear to the DPP was feasible and acceptable. Future research will establish the efficacy of adding CGM to the DPP on participant health outcomes and behaviors.

A low-glucose eating pattern is associated with improvements in glycemic variability among women at risk for postmenopausal breast cancer: an exploratory analysis

Background

High glycemic variability (GV) is a biomarker of cancer risk, even in the absence of diabetes. The emerging concept of chrononutrition suggests that modifying meal timing can favorably impact metabolic risk factors linked to diet-related chronic disease, including breast cancer. Here, we examined the potential of eating when glucose levels are near personalized fasting thresholds (low-glucose eating, LGE), a novel form of timed-eating, to reduce GV in women without diabetes, who are at risk for postmenopausal breast cancer.

Methods

In this exploratory analysis of our 16-week weight loss randomized controlled trial, we included 17 non-Hispanic, white, postmenopausal women (average age = 60.7 ± 5.8 years, BMI = 34.5 ± 6.1 kg/m2, HbA1c = 5.7 ± 0.3%). Participants were those who, as part of the parent study, provided 3-7 days of blinded, continuous glucose monitoring data and image-assisted, timestamped food records at weeks 0 and 16. Pearson's correlation and multivariate regression were used to assess associations between LGE and GV, controlling for concurrent weight changes.

Results

Increases in LGE were associated with multiple unfavorable measures of GV including reductions in CGM glucose mean, CONGA, LI, J-Index, HBGI, ADDR, and time spent in a severe GV pattern (r = -0.81 to -0.49; ps < 0.044) and with increases in favorable measures of GV including M-value and LBGI (r = 0.59, 0.62; ps < 0.013). These associations remained significant after adjusting for weight changes.

Conclusion

Low-glucose eating is associated with improvements in glycemic variability, independent of concurrent weight reductions, suggesting it may be beneficial for GV-related disease prevention. Further research in a larger, more diverse sample with poor metabolic health is warranted.Clinical trial registration: ClinicalTrials.gov, NCT03546972.

The Impact of Sex, Body Mass Index, Age, Exercise Type and Exercise Duration on Interstitial Glucose Levels during Exercise

The impact of age, sex and body mass index on interstitial glucose levels as measured via continuous glucose monitoring (CGM) during exercise in the healthy population is largely unexplored. We conducted a multivariable generalized estimating equation (GEE) analysis on CGM data (Dexcom G6, 10 days) collected from 119 healthy exercising individuals using CGM with the following specified covariates: age; sex; BMI; exercise type and duration. Females had lower postexercise glycemia as compared with males (92 ± 18 vs. 100 ± 20 mg/dL, p = 0.04) and a greater change in glycemia during exercise from pre- to postexercise (p = 0.001) or from pre-exercise to glucose nadir during exercise (p = 0.009). Younger individuals (i.e., <20 yrs) had higher glucose during exercise as compared with all other age groups (all p < 0.05) and less CGM data in the hypoglycemic range (<70 mg/dL) as compared with those aged 20-39 yrs (p < 0.05). Those who were underweight, based on body mass index (BMI: <18.5 kg/m2), had higher pre-exercise glycemia than the healthy BMI group (104 ± 20 vs. 97 ± 17 mg/dL, p = 0.02) but similar glucose levels after exercise. Resistance exercise was associated with less of a drop in glycemia as compared with aerobic or mixed forms of exercise (p = 0.008) and resulted in a lower percent of time in the hypoglycemic (p = 0.04) or hyperglycemic (glucose > 140 mg/dL) (p = 0.03) ranges. In summary, various factors such as age, sex and exercise type appear to have subtle but potentially important influence on CGM measurements during exercise in healthy individuals.

Use of Continuous Glucose Monitors by People Without Diabetes: An Idea Whose Time Has Come?

BACKGROUND

Continuous glucose monitor (CGM) systems were originally intended only for people with diabetes. Recently, there has been interest in monitoring glucose concentrations in a variety of other situations. As data accumulate to support the use of CGM systems in additional states unrelated to diabetes, the use of CGM systems is likely to increase accordingly.

METHODS

PubMed and Google Scholar were searched for articles about the use of CGM in individuals without diabetes. Relevant articles that included sufficient details were queried to identify what cohorts of individuals were adopting CGM use and to define trends of use.

RESULTS

Four clinical user cases were identified: (1) metabolic diseases related to diabetes with a primary dysregulation of the insulin-glucose axis, (2) metabolic diseases without a primary pathophysiologic derangement of the insulin-glucose axis, (3) health and wellness, and (4) elite athletics. Seven trends in the use of CGM systems in people without diabetes were idenfitied which pertained to both FDA-cleared medical grade products as well as anticipated future products, which may be regulated differently based on intended populations and indications for use.

CONCLUSIONS

Wearing a CGM has been used not only for diabetes, but with a goal of improving glucose patterns to avoid diabetes, improving mental or physical performance, and promoting motivate healthy behavioral changes. We expect that clinicians will become increasingly aware of (1) glycemic patterns from CGM tracings that predict an increased risk of diabetes, (2) specific metabolic glucotypes from CGM tracings that predict an increased risk of diabetes, and (3) new genetic and genomic biomarkers in the future.

Multimodal, Idiographic Ambulatory Sensing Will Transform our Understanding of Emotion

Emotions are inherently complex - situated inside the brain while being influenced by conditions inside the body and outside in the world - resulting in substantial variation in experience. Most studies, however, are not designed to sufficiently sample this variation. In this paper, we discuss what could be discovered if emotion were systematically studied within persons 'in the wild', using biologically-triggered experience sampling: a multimodal and deeply idiographic approach to ambulatory sensing that links body and mind across contexts and over time. We outline the rationale for this approach, discuss challenges to its implementation and widespread adoption, and set out opportunities for innovation afforded by emerging technologies. Implementing these innovations will enrich method and theory at the frontier of affective science, propelling the contextually situated study of emotion into the future.

AI4FoodDB: a database for personalized e-Health nutrition and lifestyle through wearable devices and artificial intelligence

The increasing prevalence of diet-related diseases calls for an improvement in nutritional advice. Personalized nutrition aims to solve this problem by adapting dietary and lifestyle guidelines to the unique circumstances of each individual. With the latest advances in technology and data science, researchers can now automatically collect and analyze large amounts of data from a variety of sources, including wearable and smart devices. By combining these diverse data, more comprehensive insights of the human body and its diseases can be achieved. However, there are still major challenges to overcome, including the need for more robust data and standardization of methodologies for better subject monitoring and assessment. Here, we present the AI4Food database (AI4FoodDB), which gathers data from a nutritional weight loss intervention monitoring 100 overweight and obese participants during 1 month. Data acquisition involved manual traditional approaches, novel digital methods and the collection of biological samples, obtaining: (i) biological samples at the beginning and the end of the intervention, (ii) anthropometric measurements every 2 weeks, (iii) lifestyle and nutritional questionnaires at two different time points and (iv) continuous digital measurements for 2 weeks. To the best of our knowledge, AI4FoodDB is the first public database that centralizes food images, wearable sensors, validated questionnaires and biological samples from the same intervention. AI4FoodDB thus has immense potential for fostering the advancement of automatic and novel artificial intelligence techniques in the field of personalized care. Moreover, the collected information will yield valuable insights into the relationships between different variables and health outcomes, allowing researchers to generate and test new hypotheses, identify novel biomarkers and digital endpoints, and explore how different lifestyle, biological and digital factors impact health. The aim of this article is to describe the datasets included in AI4FoodDB and to outline the potential that they hold for precision health research. Database URL https://github.com/AI4Food/AI4FoodDB.

Electrochemical biosensors in healthcare services: bibliometric analysis and recent developments

Biosensors are nowadays being used in various fields including disease diagnosis and clinical analysis. The ability to detect biomolecules associated with disease is vital not only for accurate diagnosis of disease but also for drug discovery and development. Among the different types of biosensors, electrochemical biosensor is most widely used in clinical and health care services especially in multiplex assays due to its high susceptibility, low cost and small in size. This article includes comprehensive review of biosensors in medical field with special emphasis on electrochemical biosensors for multiplex assays and in healthcare services. Also, the publications on electrochemical biosensors are increasing rapidly; therefore, it is crucial to be aware of any latest developments or trends in this field of research. We used bibliometric analyses to summarize the progress of this research area. The study includes global publication counts on electrochemical biosensors for healthcare along with various bibliometric data analyses by VOSviewer software. The study also recognizes the top authors and journals in the related area, and determines proposal for monitoring research.

Low carbohydrate high fat ketogenic diets on the exercise crossover point and glucose homeostasis

In exercise science, the crossover effect denotes that fat oxidation is the primary fuel at rest and during low-intensity exercise with a shift towards an increased reliance on carbohydrate oxidation at moderate to high exercise intensities. This model makes four predictions: First, >50% of energy comes from carbohydrate oxidation at ≥60% of maximum oxygen consumption (VO2max), termed the crossover point. Second, each individual has a maximum fat oxidation capacity (FATMAX) at an exercise intensity lower than the crossover point. FATMAX values are typically 0.3-0.6 g/min. Third, fat oxidation is minimized during exercise ≥85%VO2max, making carbohydrates the predominant energetic substrate during high-intensity exercise, especially at >85%VO2max. Fourth, high-carbohydrate low-fat (HCLF) diets will produce superior exercise performances via maximizing pre-exercise storage of this predominant exercise substrate. In a series of recent publications evaluating the metabolic and performance effects of low-carbohydrate high-fat (LCHF/ketogenic) diet adaptations during exercise of different intensities, we provide findings that challenge this model and these four predictions. First, we show that adaptation to the LCHF diet shifts the crossover point to a higher %VO2max (>80%VO2max) than previously reported. Second, substantially higher FATMAX values (>1.5 g/min) can be measured in athletes adapted to the LCHF diet. Third, endurance athletes exercising at >85%VO2max, whilst performing 6 × 800 m running intervals, measured the highest rates of fat oxidation yet reported in humans. Peak fat oxidation rates measured at 86.4 ± 6.2%VO2max were 1.58 ± 0.33 g/min with 30% of subjects achieving >1.85 g/min. These studies challenge the prevailing doctrine that carbohydrates are the predominant oxidized fuel during high-intensity exercise. We recently found that 30% of middle-aged competitive athletes presented with pre-diabetic glycemic values while on an HCLF diet, which was reversed on LCHF. We speculate that these rapid changes between diet, insulin, glucose homeostasis, and fat oxidation might be linked by diet-induced changes in mitochondrial function and insulin action. Together, we demonstrate evidence that challenges the current crossover concept and demonstrate evidence that a LCHF diet may also reverse features of pre-diabetes and future metabolic disease risk, demonstrating the impact of dietary choice has extended beyond physical performance even in athletic populations.

Addressing privacy concerns for mobile and wearable devices sensors: Small-group interviews with healthy adults and cancer survivors

Objective

Mobile and wearable sensor technology is increasingly common and accessible. The aim of this study was to explore individuals' perceptions and acceptability of mobile and wearable sensors, as well as concerns.

Methods

Purposive sampling was used to recruit non-patient adults (n = 22) and cancer survivors (n = 17) for face-to-face and virtual small-group interviews. Reflexive thematic analysis of the data focused on privacy concerns.

Results

Participants reported that privacy was generally not a concern for sensor adoptions for physical activity health interventions except for health insurer access.

Conclusion

The patient perspectives as reported in the findings illustrate the need for transparency between potential adopters and users of mobile and wearable devices and health care practitioners, as well as secure privacy policies for health insurers.

Innovation

Older adults often are perceived as unwilling to adopt mHealth technologies for many reasons, including privacy concerns. This study examined an important patient population, cancer survivors, who are often overlooked yet may benefit from targeted health interventions using mHealth technologies, and compared their responses with a non-patient population for prevention purposes. Our findings suggest that one's lived health experiences (cancer survivorship) are more influential than one's age in adopting mHealth technologies.

A qualitative study to explore the acceptability and usefulness of personalized biofeedback to motivate physical activity in cancer survivors

Objective

Many cancer survivors do not meet recommended levels of exercise, despite the benefits physical activity offers. This study aimed to understand experiences of insufficiently active overweight/obese breast or colorectal cancer survivors, in efforts to (1) examine regular physical activity barriers, and (2) determine perceptions and acceptability of a remotely delivered physical activity intervention utilizing wearable sensors and personalized feedback messages.

Methods

In-person and virtual small group interviews were conducted engaging overweight/obese cancer survivors (n = 16, 94% female, 94% breast cancer survivors) in discussions resulting in 314 pages of transcribed data analyzed by multiple coders.

Results

All participants expressed needing to increase physical activity, identifying lack of motivation centering on survivorship experiences and symptom management as the most salient barrier. They indicated familiarity with activity trackers (i.e., Fitbit) and expressed interest in biosensors (i.e., continuous glucose monitors [CGMs]) as CGMs show biological metrics in real-time. Participants reported (1) personalized feedback messages can improve motivation and accountability; (2) CGM acceptability is high given survivors’ medical history; and (3) glucose data is a relevant health indicator and they appreciated integrated messages (between Fitbit and CGM) in demonstrating how behaviors immediately affect one's body.

Conclusions

This study supports the use of wearable biosensors and m-health interventions to promote physical activity in cancer survivors. Glucose-based biofeedback provides relevant and motivating information for cancer survivors regarding their daily activity levels by demonstrating the immediate effects of physical activity. Integrating biofeedback into physical activity interventions could be an effective behavioral change strategy to promote a healthy lifestyle in cancer survivors.

Continuous Glucose Monitoring in Healthy Adults-Possible Applications in Health Care, Wellness, and Sports

INTRODUCTION

Continuous glucose monitoring (CGM) systems were primarily developed for patients with diabetes mellitus. However, these systems are increasingly being used by individuals who do not have diabetes mellitus. This mini review describes possible applications of CGM systems in healthy adults in health care, wellness, and sports.

RESULTS

CGM systems can be used for early detection of abnormal glucose regulation. Learning from CGM data how the intake of foods with different glycemic loads and physical activity affect glucose responses can be helpful in improving nutritional and/or physical activity behavior. Furthermore, states of stress that affect glucose dynamics could be made visible. Physical performance and/or regeneration can be improved as CGM systems can provide information on glucose values and dynamics that may help optimize nutritional strategies pre-, during, and post-exercise.

CONCLUSIONS

CGM has a high potential for health benefits and self-optimization. More scientific studies are needed to improve the interpretation of CGM data. The interaction with other wearables and combined data collection and analysis in one single device would contribute to developing more precise recommendations for users.

Advancing understanding of dietary and movement behaviours in an Asian population through real-time monitoring: Protocol of the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA)

Background

Modifiable risk factors for non-communicable diseases, including eating an unhealthy diet and being physically inactive, are influenced by complex and dynamic interactions between people and their social and physical environment. Therefore, understanding patterns and determinants of these risk factors as they occur in real life is essential to enable the design of precision public health interventions.

Objective

This paper describes the protocol for the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA). The study uses real-time data capture methods to gain a comprehensive understanding of eating and movement behaviours, including how these differ by socio-demographic characteristics and are shaped by people's interaction with their social and physical environment.

Methods

COBRA is an observational study in free-living conditions. We will recruit 1500 adults aged 21-69 years from a large prospective cohort study. Real-time data capture methods will be used for nine consecutive days: an ecological momentary assessment app with a global positioning system enabled to collect location data, accelerometers to measure movement, and wearable sensors to monitor blood glucose levels. Participants receive six EMA surveys per day between 8 a.m. and 9.30 p.m. to capture information on behavioural risk factors including eating behaviours and diet composition movement behaviours (physical activity, sedentary behaviour, sleep), and related contextual factors. The second wave of ecological momentary assessment surveys with a global positioning system enabled will be sent 6 months later. Data will be analysed using generalised linear models to examine associations between behavioural risk factors and contextual determinants.

Discussion

Findings from this study will advance our understanding of dietary and movement behaviours as they occur in real-life and inform the development of personalised interventions to prevent chronic diseases.

A prospective study of the relationships between movement and glycemic control during day and night in pregnancy

Both disturbed sleep and lack of exercise can disrupt metabolism in pregnancy. Accelerometery was used to objectively assess movement during waking (physical activity) and movement during sleeping (sleep disturbance) periods and evaluated relationships with continuous blood glucose variation during pregnancy. Data was analysed prospectively. 15-women without pre-existing diabetes mellitus wore continuous glucose monitors and triaxial accelerometers from February through June 2018 in Sweden. The relationships between physical activity and sleep disturbance with blood glucose rate of change were assessed. An interaction term was fitted to determine difference in the relationship between movement and glucose variation, conditional on waking/sleeping. Total movement was inversely related to glucose rate of change (p < 0.001, 95% CI (− 0.037, − 0.026)). Stratified analyses showed total physical activity was inversely related to glucose rate of change (p < 0.001, 95% CI (− 0.040, − 0.028)), whereas sleep disturbance was not related to glucose rate of change (p = 0.07, 95% CI (< − 0.001, 0.013)). The interaction term was positively related to glucose rate of change (p < 0.001, 95% CI (0.029, 0.047)). This study provides temporal evidence of a relationship between total movement and glycemic control in pregnancy, which is conditional on time of day. Movement is beneficially related with glycemic control while awake, but not during sleep.

Use of continuous glucose monitoring in obesity research: A scoping review

BACKGROUND

This scoping review provides a timely synthesis of the use of continuous glucose monitoring in obesity research with considerations to adherence to continuous glucose monitor devices and metrics most frequently reported.

METHODS

This scoping review was conducted adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. Eligible studies (n = 31) evaluated continuous glucose monitor use in research on participants, of all ages, with overweight or obesity.

RESULTS

Reviewed studies varied in duration from one to 84 days (mean: 8.74 d, SD 15.2, range 1-84 d) with 889 participants total (range: 11-118 participants). Across all studies, the mean percent continuous glucose monitor wear time (actual/intended wear time in days) was 92% (numerator - mean: 266.1 d, SD: 452, range: 9-1596 d/denominator - mean: 271.6 d, SD: 451.5, range: 9-1596 d). Continuous glucose monitoring was utilized to provide biofeedback (n = 2, 6%), monitor dietary adherence (n = 2, 6%), and assess glycemic variability (n = 29, 93%). The most common variability metrics reported were standard deviation (n = 19, 62%), area under the curve (n = 12, 39%), and glycemic range (n = 12, 39%).

CONCLUSIONS

Available evidence suggests that continuous glucose monitoring is a well-tolerated and versatile tool for obesity research in pediatric and adult patients. Future investigation is needed to substantiate the feasibility and utility of continuous glucose monitors in obesity research and maximize comparability across studies.

Performing nutrition assessment remotely via telehealth

Performing nutrition assessment remotely via telehealth is a topic of significant interest given the global pandemic in 2020 that has necessitated physical distancing and virtual communications. This review presents an evidence-based approach to conducting nutrition assessments remotely. The authors present suggestions for adaptations that can be used to perform a remote nutrition-focused physical exam. Direct-to-consumer technologies that can be used in remote nutrition assessment are discussed and compared. Practice tips for conducting a telehealth visit are also presented. The aim of this publication is to provide interdisciplinary clinicians a set of guidelines and best practices for performing nutrition assessments in the era of telehealth.

Teaching people to eat according to appetite - Does the method of glucose measurement matter?

BACKGROUND

Hunger training teaches people to eat according to their appetite using pre-prandial glucose measurement. Previous hunger training interventions used fingerprick blood glucose, however continuous glucose monitoring (CGM) offers a painless and convenient form of glucose monitoring. The aim of this randomised feasibility trial was to compare hunger training using CGM with fingerprick glucose monitoring in terms of adherence to the protocol, acceptability, weight, body composition, HbA1c, psychosocial variables, and the relationship between adherence measures and weight loss.

METHODS

40 adults with obesity were randomised to either fingerpricking or scanning with a CGM and followed identical interventions for 6 months, which included 1 month of only eating when glucose was under their individualised glucose cut-off. For months 2-6 participants relied on their sensations of hunger to guide their eating and filled in a booklet.

RESULTS

90% of the fingerpricking group and 85% of the scanning group completed the study. Those using the scanner measured their glucose an extra 1.9 times per day (95% CI 0.9, 2.8, p < 0.001) compared with those testing by fingerprick. Both groups lost similar amounts of weight over 6 months (on average 4 kg), were satisfied with the hunger training program and wanted to measure their glucose again within the next year. There were no differences between groups in terms of intervention acceptability, weight, body composition, HbA1c, eating behaviours, or psychological health. Frequency of glucose testing and booklet entry both predicted a clinically meaningful amount of weight loss.

CONCLUSIONS

Either method of measuring glucose is effective for learning to eat according to hunger using the hunger training program. As scanning with a CGM encouraged better adherence to the protocol without sacrificing outcome results, future interventions should consider using this new technology in hunger training programs.

Future Directions for Integrative Objective Assessment of Eating Using Wearable Sensing Technology

Established methods for nutritional assessment suffer from a number of important limitations. Diaries are burdensome to complete, food frequency questionnaires only capture average food intake, and both suffer from difficulties in self estimation of portion size and biases resulting from misreporting. Online and app versions of these methods have been developed, but issues with misreporting and portion size estimation remain. New methods utilizing passive data capture are required that address reporting bias, extend timescales for data collection, and transform what is possible for measuring habitual intakes. Digital and sensing technologies are enabling the development of innovative and transformative new methods in this area that will provide a better understanding of eating behavior and associations with health. In this article we describe how wrist-worn wearables, on-body cameras, and body-mounted biosensors can be used to capture data about when, what, and how much people eat and drink. We illustrate how these new techniques can be integrated to provide complete solutions for the passive, objective assessment of a wide range of traditional dietary factors, as well as novel measures of eating architecture, within person variation in intakes, and food/nutrient combinations within meals. We also discuss some of the challenges these new approaches will bring.

Using Continuous Glucose Monitoring to Motivate Physical Activity in Overweight and Obese Adults: A Pilot Study

BACKGROUND

Regular physical activity (PA) is associated with a lower risk of several types of cancers. However, two-thirds of overweight/obese adults are not sufficiently active; this, in combination with the unfavorable effect of excess body weight, puts them at a greater risk for cancer. One reason that these individuals do not engage in enough PA may be their lack of motivation to change their current behavior due to the perception of putting in effort for possible future gain without obvious short-term benefits. There is a need for innovative ways to help individuals recognize the immediate health benefits of PA and thus increase their motivation.

METHODS

This pilot intervention tested a PA education module that included a one-on-one counseling session highlighting the acute effects of PA on glucose patterns, followed by a 10-day self-monitoring period with a continuous glucose monitor (CGM) and a Fitbit tracker. Participants rated the acceptability of the education module on a 5-point Likert scale and completed surveys assessing stages of change for motivational readiness.

RESULTS

Nineteen overweight/obese adults (84% female) completed the study. Participants gave high ratings to the counseling session for improving their PA-related knowledge (mean = 4.22), increasing motivation (mean = 4.29), and providing personally relevant information (mean = 4.35). The summary acceptability scores for the self-monitoring period were 4.46 for CGM and 4.51 for Fitbit. Participants reported a significant decrease in the precontemplation stage and an increase in the action stage (P < 0.05).

CONCLUSIONS

CGM is a feasible tool for PA interventions.

IMPACT

Information from CGM could be used as biological-based feedback to motivate PA.See all articles in this CEBP Focus section, "Modernizing Population Science."