Wearable technology-delivered lifestyle intervention amongst adults with overweight and obese: A systematic review and meta-regression

The future of healthy ageing: Wearables in public health, disease prevention and healthcare

Wearables have evolved into accessible tools for sports, research, and interventions. Their use has expanded to real-time monitoring of behavioural parameters related to ageing and health. This paper provides an overview of the literature on wearables in disease prevention and healthcare over the life course (not only in the older population), based on insights from the Future of Diagnostics Workshop (Leiden, January 2024). Wearable-generated parameters include blood glucose, heart rate, step count, energy expenditure, and oxygen saturation. Integrating wearables in healthcare is protracted and far from mainstream implementation, but promises better diagnosis, biomonitoring, and assessment of medical interventions. The main lifestyle factors monitored directly with wearables or through smartphone applications for disease prevention include physical activity, energy expenditure, gait, sleep, and sedentary behaviour. Insights on dietary consumption and nutrition have resulted from continuous glucose monitors. These factors are important for healthy ageing due to their effect on underlying disease pathways. Inclusivity and engagement, data quality and ease of interpretation, privacy and ethics, user autonomy in decision making, and efficacy present challenges to but also opportunities for their use, especially by older people. These need to be addressed before wearables can be integrated into mainstream medical and public health strategies. Furthermore, six key considerations need to be tackled: 1) engagement, health literacy, and compliance with personalised feedback, 2) technical and standardisation requirements for scalability, 3) accountability, data safety/security, and ethical concerns, 4) technological considerations, access, and capacity building, 5) clinical relevance and risk of overdiagnosis/overmedicalisation, and 6) the clinician's perspective in implementation.

Umbrella review of social inequality in digital interventions targeting dietary and physical activity behaviors

Digital interventions are increasingly utilized as a lever to promote population health, yet not everyone may equally benefit from them. This umbrella review pooled the insights from available systematic and scoping reviews regarding potential social inequalities in digital intervention uptake, engagement and effectiveness, focusing on the promotion of weight-related behaviors (diet, physical activity, sedentary behavior) and weight loss (maintenance) in adults. Six databases were searched from 1970 to October 2023. Forty-six reviews were included, of which most focused on physical activity and intervention effectiveness. Age and gender/ sex differences were most frequently studied. Most reviews found digital interventions to be effective irrespective of age, while men benefitted more from digital interventions than women. Other inequality indicators (e.g., income, education) were rarely studied, despite them being potential causes of a digital divide. A more systematic and thorough exploration of inequalities in digital health is required to promote health for all.

Effect of wearable activity trackers on physical activity in children and adolescents: a systematic review and meta-analysis

BACKGROUND

Physical inactivity in children and adolescents has become a pressing public health concern. Wearable activity trackers can allow self-monitoring of physical activity behaviour and promote autonomous motivation for exercise. However, the effects of wearable trackers on physical activity in young populations remain uncertain.

METHODS

In this systematic review and meta-analysis, we searched PubMed, Embase, SPORTDiscus, and Web of Science for publications from database inception up to Aug 30, 2023, without restrictions on language. Studies were eligible if they were randomised controlled trials or clustered randomised controlled trials that examined the use of wearable activity trackers to promote physical activity, reduce sedentary behaviours, or promote overall health in participants with a mean age of 19 years or younger, with no restrictions on health condition or study settings. Studies were excluded if children or adolescents were not the primary intervention cohort, or wearable activity trackers were not worn on users' bodies to objectively track users' physical activity levels. Two independent reviewers (WWA and FR) assessed eligibility of studies and contacted authors of studies if more information was needed to assess eligibility. We also searched reference lists from relevant systematic reviews and meta-analyses. Systematic review software Covidence was used for study screening and data extraction. Study characteristics including study setting, participant characteristics, intervention characteristics, comparator, and outcome measurements were extracted from eligible studies. The two primary outcomes were objectively measured daily steps and moderate-to-vigorous physical activity. We used a random-effects model with Hartung-Knapp adjustments to calculate standardised mean differences. Between-study heterogeneity was examined using Higgins I2 and Cochran Q statistic. Publication bias was assessed using Egger's regression test. This systematic review was registered with PROSPERO, CRD42023397248.

FINDINGS

We identified 9619 studies from our database research and 174 studies from searching relevant systematic reviews and meta-analyses, of which 105 were subjected to full text screening. We included 21 eligible studies, involving 3676 children and adolescents (1618 [44%] were female and 2058 [56%] were male, mean age was 13·7 years [SD 2·7]) in our systematic review and meta-analysis. Ten studies were included in the estimation of the effect of wearable activity trackers on objectively measured daily steps and 11 were included for objectively measured moderate-to-vigorous physical activity. Compared with controls, we found a significant increase in objectively measured daily steps (standardised mean difference 0·37 [95% CI 0·09 to 0·65; p=0·013]; Q 47·60 [p<0·0001]; I2 72·7% [95% CI 53·4 to 84·0]), but not for moderate-to-vigorous physical activity (-0·08 [-0·18 to 0·02; p=0·11]; Q 10·26 [p=0·74]; I2 0·0% [0·0 to 53·6]).

INTERPRETATION

Wearable activity trackers might increase daily steps in young cohorts of various health statuses, but not moderate-to-vigorous physical activity, highlighting the potential of wearable trackers for motivating physical activity in children and adolescents. More rigorously designed trials that minimise missing data are warranted to validate our positive findings on steps and to explore possible long-term effects.

FUNDING

The Hong Kong University Grants Committee and Seed Fund for Basic Research of the University of Hong Kong.

Step count and multiple health outcomes: An umbrella review

OBJECTIVE

This study aimed to quantify the association between step count and multiple health outcomes in a healthy population.

METHODS

PubMed, Embase, Web of Science, and The Cochrane Library were systematically searched for systematic reviews and meta-analyses from inception to April 1, 2022. Literature screening, data extraction, and data analysis were performed in this umbrella review. The intervention factor was daily step counts measured based on devices. Multiple health outcomes included metabolic diseases, cardiovascular diseases, all-cause mortality, and other outcomes in the healthy population.

RESULTS

Twenty studies with 94 outcomes were identified in this umbrella review. The increase in daily step count contributed to a range of human health outcomes. Furthermore, the special population, different age groups, countries, and cohorts should be carefully considered. Negative correlation between step counts and the following outcomes: metabolic outcomes, cardiovascular diseases, all-cause mortality, postural balance, cognitive function, and mental health. However, there was no association between participation in the outdoor walking group and the improvement of systolic blood pressure and diastolic blood pressure. Analysis of the dose-response association between increasing daily step count and the risk of cardiovascular disease events and all-cause mortality showed a substantially linear relationship.

CONCLUSION

A wide range of health outcomes can benefit from the right number of steps.

Wearable Devices Beyond Activity Trackers in Youth With Obesity: Summary of Options

Background: Current treatment protocols to prevent and treat pediatric obesity focus on prescriptive lifestyle interventions. However, treatment outcomes are modest due to poor adherence and heterogeneity in responses. Wearable technologies offer a unique solution as they provide real-time biofeedback that could improve adherence to and sustainability of lifestyle interventions. To date, all reviews on wearable devices in pediatric obesity cohorts have only explored biofeedback from physical activity trackers. Hence, we conducted a scoping review to (1) catalog other biofeedback wearable devices available in this cohort, (2) document various metrics collected from these devices, and (3) assess safety and adherence to these devices. Methods: This scoping review was conducted adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. Fifteen eligible studies examined the use of biofeedback wearable devices beyond activity trackers in pediatric cohorts, with an emphasis on feasibility of these devices. Results: Included studies varied in sample sizes (15-203) and in ages 6-21 years. Wearable devices are being used to capture various metrics of multicomponent weight loss interventions to provide more insights about glycemic variability, cardiometabolic function, sleep, nutrition, and body fat percentage. High safety and adherence rates were reported among these devices. Conclusions: Available evidence suggests that wearable devices have several applications aside from activity tracking, which could modify health behaviors through real-time biofeedback. Overall, these devices appear to be safe and feasible so as to be employed in various settings in the pediatric age group to prevent and treat obesity.

Wearable Devices to Improve Physical Activity and Reduce Sedentary Behaviour: An Umbrella Review

BACKGROUND

Several systematic reviews (SRs), with and without meta-analyses, have investigated the use of wearable devices to improve physical activity, and there is a need for frequent and updated syntheses on the topic.

OBJECTIVE

We aimed to evaluate whether using wearable devices increased physical activity and reduced sedentary behaviour in adults.

METHODS

We conducted an umbrella review searching PubMed, Cumulative Index to Nursing and Allied Health Literature, the Cochrane Library, MedRxiv, Rxiv and bioRxiv databases up to February 5th, 2023. We included all SRs that evaluated the efficacy of interventions when wearable devices were used to measure physical activity in adults aged over 18 years. The primary outcomes were physical activity and sedentary behaviour measured as the number of steps per day, minutes of moderate to vigorous physical activity (MVPA) per week, and minutes of sedentary behaviour (SB) per day. We assessed the methodological quality of each SR using the Assessment of Multiple Systematic Reviews, version 2 (AMSTAR 2) and the certainty of evidence of each outcome measure using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations). We interpreted the results using a decision-making framework examining the clinical relevance and the concordances or discordances of the SR effect size.

RESULTS

Fifty-one SRs were included, of which 38 included meta-analyses (302 unique primary studies). Of the included SRs, 72.5% were rated as 'critically low methodological quality'. Overall, with a slight overlap of primary studies (corrected cover area: 3.87% for steps per day, 3.12% for MVPA, 4.06% for SB) and low-to-moderate certainty of the evidence, the use of WDs may increase PA by a median of 1,312.23 (IQR 627-1854) steps per day and 57.8 (IQR 37.7 to 107.3) minutes per week of MVPA. Uncertainty is present for PA in pathologies and older adults subgroups and for SB in mixed and older adults subgroups (large confidence intervals).

CONCLUSIONS

Our findings suggest that the use of WDs may increase physical activity in middle-aged adults. Further studies are needed to investigate the effects of using WDs on specific subgroups (such as pathologies and older adults) in different follow-up lengths, and the role of other intervention components.

Identifying Predictors of Adherence to the Physical Activity Goal: A Secondary Analysis of the SMARTER Weight Loss Trial

INTRODUCTION/PURPOSE

Research is needed to inform tailoring supportive strategies for promoting physical activity (PA) in the context of behavioral treatment of obesity. We aimed to identify baseline participant characteristics and short-term intervention response predictors associated with adherence to the study-defined PA goal in a mobile health (mHealth) weight loss trial.

METHODS

A secondary analysis was conducted of a 12-month weight loss trial (SMARTER) that randomized 502 adults with overweight or obesity to either self-monitoring of diet, PA, and weight with tailored feedback messages ( n = 251) or self-monitoring alone ( n = 251). The primary outcome was average adherence to the PA goal of ≥150 min·wk -1 of moderate- and vigorous-intensity aerobic activities (MVPA) from Fitbit Charge 2™ trackers over 52 wk. Twenty-five explanatory variables were considered. Machine learning methods and linear regression were used to identify predictors of adherence to the PA goal.

RESULTS

The sample ( N = 502) was mostly female (80%), White (82%) with the average age of 45 ± 14.4 yr and body mass index of 33.7 ± 4.0 kg·m -2 . Machine learning methods identified PA goal adherence for the first week as the most important predictor of long-term PA goal adherence. In the parsimonious linear regression model, higher PA goal adherence for the first week, greater PA FB messages opened, older age, being male, higher education, being single and not having obstructive sleep apnea were associated with higher long-term PA goal adherence.

CONCLUSIONS

To our knowledge, this is the first study using machine learning approaches to identify predictors of long-term PA goal adherence in a mHealth weight loss trial. Future studies focusing on facilitators or barriers to PA among young and middle-age adults and women with low PA goal adherence are warranted.

Thirty Obesity Myths, Misunderstandings, and/or Oversimplifications: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2022

Background

This Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) is intended to provide clinicians an overview of 30 common obesity myths, misunderstandings, and/or oversimplifications.

Methods

The scientific support for this CPS is based upon published citations, clinical perspectives of OMA authors, and peer review by the Obesity Medicine Association leadership.

Results

This CPS discusses 30 common obesity myths, misunderstandings, and/or oversimplifications, utilizing referenced scientific publications such as the integrative use of other published OMA CPSs to help explain the applicable physiology/pathophysiology.

Conclusions

This Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) on 30 common obesity myths, misunderstandings, and/or oversimplifications is one of a series of OMA CPSs designed to assist clinicians in the care of patients with the disease of obesity. Knowledge of the underlying science may assist the obesity medicine clinician improve the care of patients with obesity.

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.