The efficacy of wearable activity tracking technology as part of a weight loss program: a systematic review

Cheatham, Scott W.; Stull, Kyle R.; Fantigrassi, Mike; Motel, Ian

doi:10.23736/s0022-4707.17.07437-0

Cited by 91 publications

(63 citation statements)

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“…The dotted lines indicate the Bland limit of agreement 1.96=*SD. The dark grey lines indicate a reasonable limit of agreement(-20; 18) as indicated in a study conducted to validate a Fitbit wearable device on an elderly population[31].…”

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confidence: 74%

“…Given its potential and level of accuracy, a wearable device could be used by health care professionals to monitor the levels of PA in their patients. The application of these devices could be easily adopted in situations where there is a need to perform PA for the maintenance or improvement of patient health-for example, following orthopedic or major surgery or to achieve a beneficial increase in metabolism such as in the presence of diabetes or obesity [31][32][33]. Since these devices are commercially available, inexpensive, specific, and reliable, they could be used in today's health care environment, where the use of technological tools and adoption of telemedicine methods is becoming increasingly widespread.…”

Section: Principal Findingsmentioning

confidence: 99%

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Usability and Accuracy of a Smartwatch for the Assessment of Physical Activity in the Elderly Population: Observational Study

Martinato¹,

Lorenzoni²,

Zanchi³

et al. 2021

JMIR Mhealth Uhealth

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Background Regular physical activity (PA) contributes to the primary and secondary prevention of several chronic diseases and reduces the risk of premature death. Physical inactivity is a modifiable risk factor for cardiovascular disease and a variety of chronic disorders such as diabetes, obesity, hypertension, bone and joint diseases (eg, osteoporosis and osteoarthritis), depression, and colon and breast cancer. Population aging and the related increase in chronic diseases have a major impact on the health care systems of most Western countries and will produce an even more significant effect in the future. Monitoring PA is a valuable method of determining whether people are performing enough PA so as to prevent chronic diseases or are showing early symptoms of those diseases. Objective The aim of this study was to estimate the accuracy of wearable devices in quantifying the PA of elderly people in a real-life setting. Methods Participants aged 70 to 90 years with the ability to walk safely without any walking aid for at least 300 meters, who had no walking disabilities or episodes of falling while walking in the last 12 months, were asked to walk 150 meters at their preferred pace wearing a vívoactive HR device (Garmin Ltd) and actual steps were monitored and tallied by a researcher using a hand-tally counter to assess the performance of the device at a natural speed. A Bland-Altman plot was used to analyze the difference between manually counted steps and wearable device–measured steps. The intraclass correlation coefficient (ICC) was computed (with a 95% confidence interval) between step measurements. The generalized linear mixed-model (GLMM) ICCs were estimated, providing a random effect term (random intercept) for the individual measurements (gold standard and device). Both adjusted and conditional ICCs were computed for the GLMM models considering separately the effect of age, sex, BMI, and obesity. Analyses were performed using R software (R Foundation for Statistical Computing) with the rms package. Results A total of 23 females and 26 males were enrolled in the study. The median age of the participants was 75 years. The Bland-Altman plot revealed that, excluding one observation, all differences across measurements were in the confidence bounds, demonstrating the substantial agreement between the step count measurements. The results were confirmed by an ICC equal to .98 (.96-.99), demonstrating excellent agreement between the two sets of measurements. Conclusions The level of accuracy of wearable devices in quantifying the PA of elderly people in a real-life setting that was found in this study supports the idea of considering wrist-wearable nonmedical devices (widely available in nonspecialized stores) as reliable tools. Both health care professionals and informal caregivers could monitor the level of PA of their patients.

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confidence: 74%

Section: Principal Findingsmentioning

confidence: 99%

Usability and Accuracy of a Smartwatch for the Assessment of Physical Activity in the Elderly Population: Observational Study

Martinato¹,

Lorenzoni²,

Zanchi³

et al. 2021

JMIR Mhealth Uhealth

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“…However, they all showed the effectiveness of mobile-based interventions in weight management compared to pre-intervention. Take physical activity into account, a systematic review [30] including 25 studies suggested that short-term (<6 months) weight loss program combined with wearable trackers may be a better choice than a standard one in middle age or older adults with BMI ≥ 25 kg/m 2 . However, our study showed no statistically significant difference between PG and CG.…”

Section: Discussionmentioning

confidence: 99%

Effect of Mobile-Based Lifestyle Intervention on Weight Loss among the Overweight and Obese Elderly Population in China: A Randomized Controlled Trial

Zhou

Zhang

Yan

et al. 2021

IJERPH

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Background and Objective: Overweight or obesity, as an independent risk factor for chronic diseases, has been on the rise globally. Adopting a healthy lifestyle is positive to weight control. Mobile-based lifestyle interventions have shown potential benefits in weight loss, but most studies were carried out among non-elderly population, so it is necessary to perform well-designed randomized controlled trials among the elderly with overweight or obesity. The purpose of this study is to assess the effect of mobile-based lifestyle intervention on weight loss among the overweight and obese elderly population in China. Methods: This is a prospective, open-labeled, three-month, multicenter, randomized controlled trial involving 750 participants from five cities who were randomly assigned to dietary and physical activity interventions group (DPG; mobile phone with the App and bracelet), physical activity interventions group (PG; mobile phone with the App and bracelet) and control group (CG; no interventions and kept their lifestyle as before). The outcomes evaluated were changes in weight, body mass index (BMI), waist circumference (WC), and hip circumference (HC). Results: In total, 642 (85.6%) participants completed the study, 237 (94.8%), 203 (81.2%), and 202 (80.8%) for DPG, PG, and CG respectively. Comparing with PG and CG, the DPG showed a significant decrease in all outcomes after three months, including body weight (−4.1 kg vs. −1.0 kg; −4.1 kg vs. −0.8 kg; p < 0.05), BMI (−1.6 kg/m2 vs. −0.4 kg/m2; −1.6 kg/m2 vs. −0.3 kg/m2; p < 0.05), WC (−2.8 cm vs. −0.1 cm; −2.8 cm vs. −0.5 cm; p < 0.05), and HC (−3.8 cm vs. −1.3 cm; −3.8 cm vs. −1.3 cm; p < 0.05). Similar effects were seen across sex and BMI subgroups. Conclusions: Mobile-based lifestyle intervention obtained beneficial effect in weight loss among the elderly with overweight or obesity. Nevertheless, further studies are needed to confirm the effectiveness and its sustainability.

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“…They have been employed to monitor both lifestyle habits (physical activity, dietary habits, sleep) and clinical parameters (e.g., heart rate) in both healthy subjects and those affected by acute or chronic diseases [7,8]. It has also been reported that wearable motion detectors are the most promising technology enabling an automatic, continuous, and long-term assessment of subjects in their daily life environments [9,10]. In addition, lifestyle parameters can be shared with healthcare providers and insurance platforms to describe better the behavioral pattern and functional ability in high-risk subjects, thus providing important feedback regarding the overall health status of an individual and even prediction of potential adverse health events.…”

Section: Introductionmentioning

confidence: 99%

Improving Healthy Aging by Monitoring Patients’ Lifestyle through a Wearable Device: Results of a Feasibility Study

Fioranzato

Comoretto

Lanera

et al. 2021

IJERPH

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Population aging is related to a huge growth in healthcare and welfare costs. Therefore, wearable devices could be strategic for minimizing years of disability in old age and monitoring patients’ lifestyles and health. The purpose of this study was to assess the feasibility of using smart devices to monitor patients’ physical activity in a primary care setting. To assess the acceptance of this novel technology from the point of view of both patients and healthcare professionals, two questionnaires (one paper-based and one ex-novo developed) were administered to 11 patients with type 2 diabetes mellitus and a non-compliant behavior towards the therapeutic indications of their general practitioner (GP). Seven participants would continue to use a wearable activity tracker to monitor their health. We observed that 75% of patients reported a device’s characteristics satisfaction level of over 80% of the total score assigned to this dimension. No differences were observed in the questionnaire’s scores between the two professionals categories (GPs and nurses). Three dimensions (equipment characteristics, subjective norm, perceived risks, perceived ease-of-use and facilitating conditions) correlated > 0.5 with the device’s acceptability level. Some weak correlations were observed between healthcare professionals’ perception and patients’ parameters, particularly between the dimensions of collaboration and web interface ease-of-use and patients’ median number of steps and hours of sleep. In conclusion, despite the limited number of subjects involved, a good acceptance level towards these non-medical devices was observed, according to both patients’ and healthcare professionals’ impressions.

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The efficacy of wearable activity tracking technology as part of a weight loss program: a systematic review

Cited by 91 publications

References 0 publications

Usability and Accuracy of a Smartwatch for the Assessment of Physical Activity in the Elderly Population: Observational Study

Usability and Accuracy of a Smartwatch for the Assessment of Physical Activity in the Elderly Population: Observational Study

Effect of Mobile-Based Lifestyle Intervention on Weight Loss among the Overweight and Obese Elderly Population in China: A Randomized Controlled Trial

Improving Healthy Aging by Monitoring Patients’ Lifestyle through a Wearable Device: Results of a Feasibility Study

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