Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1
Hidetaka Hamasaki
 + 1574 word(s) 1574 2021-11-01 04:08:48 |
2 format corrected.
Beatrix Zheng
 + 396 word(s) 1970 2021-11-05 11:58:50 |

Video Upload Options

Do you have a full video?
Send video materials Upload full video

Confirm

Are you sure to Delete?
Yes No
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Hamasaki, H. Preventing Physical Inactivity during Future Pandemics. Encyclopedia. Available online: https://encyclopedia.pub/entry/15747 (accessed on 25 April 2024).
Hamasaki H. Preventing Physical Inactivity during Future Pandemics. Encyclopedia. Available at: https://encyclopedia.pub/entry/15747. Accessed April 25, 2024.
Hamasaki, Hidetaka. "Preventing Physical Inactivity during Future Pandemics" Encyclopedia, https://encyclopedia.pub/entry/15747 (accessed April 25, 2024).
Hamasaki, H. (2021, November 05). Preventing Physical Inactivity during Future Pandemics. In Encyclopedia. https://encyclopedia.pub/entry/15747
Hamasaki, Hidetaka. "Preventing Physical Inactivity during Future Pandemics." Encyclopedia. Web. 05 November, 2021.
Preventing Physical Inactivity during Future Pandemics
Edit
This entry is adapted from the peer-reviewed paper 10.3390/app11219956

Wearable activity trackers are devices that are comfortably worn on the body and are designed to be effective in monitoring daily physical activity and improving physical fitness of the wearer. This review aimed to investigate the impact of the coronavirus disease 2019 (COVID-19) pandemic on physical activity measured using wearable activity trackers and discuss future perspectives on wearable activity trackers during pandemics. Daily physical activity was significantly decreased during the COVID-19 pandemic.

wearable device smartphone application telemedicine physical activity COVID-19

1. Introduction

The coronavirus disease 2019 (COVID-19) pandemic has emerged and become prolonged, significantly affecting the lives of people worldwide. To date (September 2021), over 220,000,000 coronavirus cases and 4,500,000 deaths due to COVID-19 have been confirmed across the globe [1]. New coronavirus variants have been appearing one after another, and some mutated strains, such as the Delta variant, may be more contagious, virulent, and vaccine-resistant, which will make it difficult for humans to manage the pandemic effectively [2]. Several countries took non-pharmaceutical public health measures such as lockdown [3] and social distancing [4] in addition to conventional infection control measures (e.g., handwashing and wearing of face masks); however, the spread of COVID-19 is not currently controlled. People are required to make behavioral and lifestyle changes in this pandemic era. The development of technologies and systems that enable disease prevention, effective healthcare without a risk of infection, and protection of human life is critical [5].

Wearable devices that can comfortably be worn on the body and perform several tasks in conjunction with handheld devices, such as smartphones, play a pivotal role in healthcare [6]. Recent systematic reviews have shown that wearable devices are useful for monitoring heart rate and sleep in hospital settings [7], increasing physical activity in children and adolescents [8], improving health-related outcomes in patients with cancer [9], and reducing body weight in individuals with obesity [10]. In addition, during the COVID-19 pandemic, sleep pattern and duration were accurately and effectively monitored by wearable devices [11][12][13][14][15]. On the other hand, social distancing or self-isolation can decrease daily physical activity [16], and such physical inactivity may increase cardiovascular risks [17]; further, physical inactivity itself was associated with an increased risk of hospitalization due to COVID-19 (relative risk = 1.32; 95% confidence interval [CI], 1.10–1.58) [18]. Physical inactivity is a global health problem responsible for the increasing risk of noncommunicable diseases, such as diabetes, coronary heart disease, and breast and colon cancers, and Lee et al. [19] reported that the life expectancy of humans would increase by 0.68 years by increasing physical activity. Promoting and increasing physical activity are the cornerstone of the management of diabetes and obesity, which are now the risks of severe COVID-19 as well as public health epidemics.

2. Physical Activity during the COVID-19 Pandemic

In this narrative review, the author focuses on the impact of the COVID-19 pandemic on physical activity measured using wearable activity trackers. The author performed a literature search on COVID-19 and wearable devices in PubMed. The search terms were “COVID-19” and “wearable”. The titles and abstracts of the identified articles were reviewed to determine their relevance. The author excluded editorials, commentaries, and letters. The search of PubMed from its inception to August 2021 yielded 253 articles. Of these, nine studies were included in this review (Figure 1).
Applsci 11 09956 g001 550
Figure 1. Review flow chart.
The Remote Assessment of Disease and Relapse–Central Nervous System (RADAR-CNS) Consortium reported that people in Italy, Spain, Denmark, the United Kingdom (UK), and the Netherlands significantly changed their behavior during the COVID-19 pandemic based on the data from wearables and mobile technologies [20]. A total of 1062 subjects were recruited in the RADAR-CNS study, and the following data were collected through a smartphone or a Fitbit device on a 24/7 basis: smartphone location (maximum traveled distance from home and homestay), smartphone Bluetooth (maximum number of nearby devices), Fitbit step count, Fitbit sleep (bedtime and sleep duration), Fitbit heart rate (average heart rate), smartphone user interaction (unlock duration), and smartphone use event (social application use duration). Subjects spent more time on social media (Italy, Spain, the UK, and The Netherlands), had a lower heart rate (Italy, Spain, and Denmark), slept later (Italy, Spain, the UK, and The Netherlands), and slept longer (Italy, Spain, and the UK) during the lockdown than before the lockdown. Young subjects (<45 years) also had fewer daily steps during the lockdown than before the lockdown (Italy, the UK, and The Netherlands). Subjects whose body mass index (BMI) was less than 25 kg/m2 walked more than subjects with a high BMI (≥25 kg/m2). Non-pharmaceutical measures such as lockdown made people inactive, and the health of people with overweight/obesity could be damaged more by lockdown than people with normal weight. Interestingly, there were different results across countries; for example, Denmark showed small behavioral changes in response to the lockdown. Apart from the effectiveness of lockdown for infection control during the pandemic, young people with obesity should be monitored carefully to prevent health problems due to physical inactivity when implementing lockdown and social distancing. Importantly, obesity is significantly associated with the increased risk of susceptibility to COVID-19 (odds ratio (OR), 2.42; 95% CI, 1.58–3.70), severity of COVID-19 (OR, 1.62; 95% CI, 1.48–1.76), hospitalization (OR, 1.75; 95% CI, 1.47–2.09), and death (OR, 1.23; 95% CI, 1.06–1.41) [21].
A small retrospective observational study in Poland showed similar results [22]. Five subjects who self-isolated at home during the COVID-19 pandemic were enrolled in this study, and their daily steps, resting heart rate, and sleep duration were recorded for 464 days. The data were collected through Fitbit Versa smartwatches. The self-isolation period was 50 days. The daily step count (from 7550 ± 4430 to 3230 ± 1910 steps) and resting heart rate (from 63.28 ± 4.36 to 60.23 ± 3.69 beats per minute (bpm)) were significantly decreased during the self-isolation period compared with those before the lockdown, but no significant change was noted in sleep duration. However, sleep duration (from 429.64 ± 66.80 to 371.73 ± 117.19 min) was significantly decreased in subjects aged ≥80 years during the self-isolation period. The cardiovascular and pre-frailty risk assessment score using age, daily steps, resting heart rate, and sleep duration was developed in this study; four out of five subjects increased the score during the self-isolation period, and two out of five subjects were considered to have an increased cardiovascular and pre-frailty risk due to self-isolation. This study suggests that self-isolation is harmful for physical health and increases the risk of cardiovascular disease and frailty. The authors undoubtedly expect that smartwatches or other medical wearables will play an essential role in telemedicine when a public health emergency, such as a pandemic, occurs.
Taylor et al. [23] quantified the effect of lockdown on physical activity in patients with heart failure. Physical activity data were collected from modern cardiac implantable electronic devices (CIEDs) in the Triage HF Plus Evaluation Study in the UK. CIEDs have multiple built-in sensors to monitor real-time physiological data including physical activity, thoracic impedance, heart rate, heart rhythm, and atrial arrhythmias. A total of 311 patients who completed the collection of 8-week activity data (pre-lockdown for 4 weeks and post-lockdown for 4 weeks) were enrolled in this study. Daily physical activity was measured by an accelerometer within the CIED. A total of 246 patients (79.1%) showed a reduction in physical activity post-lockdown. The median physical activity per day was significantly decreased from 134.7 min/day during pre-lockdown to 113.9 min/day during post-lockdown. Daily physical activity was immediately decreased within 2 weeks after the implementation of lockdown. There were no characteristics of patients such as age, sex, BMI, frailty, and severity of heart failure that were clearly associated with the reduction in physical activity due to the lockdown. Table 1 summarizes the studies investigating the change in daily physical activity during the COVID-19 pandemic.
Table 1. Changes in daily physical activity measured by wearable activity trackers during the COVID-19 pandemic.
Authors, Year Subjects
Countries		 Study Design
Study Period		 Wearable Activity Trackers Results
Sun et al., 2020 [20] 1062 patients with major depressive disorder or multiple sclerosis in Italy, Spain, Denmark, the United Kingdom, and Netherlands
Age: No description
BMI: No description		 Prospective cohort study
a part of the RADAR-CNS studies
Between 1 February 2019 and 5 July 2020		 Smartphone
Fitbit		 Daily step count↓ in young subjects
Heart rate↓
Time spent on social media↑
Sleep duration↑
Kańtoch E and Kańtoch A, 2021 [22] 5 adult volunteers (2 men and 3 women, 2 subjects with history of cardiovascular diseases)
Poland
Age: 57 ± 22.38 years
BMI: 27.80 ± 2.95 kg/m2		 Retrospective observational study
Between 22 January 2019 and 30 April 2020		 Fitbit Versa smartwatch Daily step count↓
Resting heart rate↓
Sleep duration→
Mishra et al., 2021 [24] 10 community-dwelling older adults (6 men and 4 women)
United States
Age: 77.3 ± 1.9 years
BMI: 27.5 ± 1.6 kg/m2		 Prospective observational study
Between January-March 2020 and March–September 2020		 ActivePERS/PAMSys pendant Daily step count↓
Standing%↓
Walking%↓
Sitting%↑
Sleep quality→
Woodruff et al., 2021 [25] 121 subjects (23 men, 96 women, 1 cisgender, and 1 unknown)
Canada
Age: 36.2 ± 13.12 years
BMI: No description		 Prospective observational study
Between March 2020 and April 2020		 Various activity trackers, e.g., Apple Watch, Fitbit, Samsung, and Garmin Daily step count↓
Sedentary time↑
Ong et al., 2021 [26] 1824 city-dwelling, working adults (883 men and 941 women)
Singapore
Age: 30.94 ± 4.62 years
BMI: No description		 Prospective cohort study
Between 2 January 2020 and 27 April 2020		 Fitbit Daily step count↓
Time spent on moderate-to-vigorous activity↓
Resting heart rate↓
Sleep duration↑
Sleep efficiency→
Pépin et al., 2020 [27] Approximately 742,000 individuals using wearable activity trackers (proportion of women: 37.8%)
Australia, Canada, China, France, Germany, Ireland, Italy, Japan, Netherlands, Singapore, Switzerland, United Kingdom, and United States
Age: 35–46 years
BMI: No description		 Retrospective observational study
Between 1 December 2019 and 13 April 2020		 Withings The number of steps↓ in countries with lockdown
The number of steps↑ in Sweden without lockdown
Capodilupo and Miller, 2021 [28] 5436 individuals using a wearable activity tracker (3900 men and 1536 women)
United States
Age: 40.25 ± 11.33 years
BMI: No description		 Retrospective observational study
Between 1 January 2020 and 15 May 2020		 WHOOP strap Exercise frequency↑ in all subjects
Exercise frequency↓ in subjects aged 18–25 years
Resting heart rate↓
Heart rate variability↑
Sleep duration↑
Zinner et al., 2020 [29] 14 highly trained athletes (6 men and 8 women)
Germany
Age: 17.1 ± 1.9 years
BMI: 22.9 ± 1.4 kg/m2		 Retrospective observational study
During 4 weeks prior to and after the social distancing and lockdown on 23 March 2020		 Polar M430 Training time↓
Time spent on light- and moderate-intensity physical activity↓
Sitting time↓
Time spent lying down↑
Taylor et al., 2021 [23] 311 patients with heart failure (240 men and 71 women)
United Kingdom
Age: 68.8 years
BMI: <18.5 kg/m2 (0.7%), 18.5–24.9 kg/m2 (22.3%), 25–29.9 kg/m2 (32.8%), >30 (44.3%)		 Prospective observational study
During 4 weeks preceding and following the lockdown on 23 March 2020		 Triage HF Daily physical activity↓
↑, increase; ↓, decrease; BMI, body mass index; RADAR-CNS, Remote Assessment of Disease and Relapse–Central Nervous System.
It is evident that there is heterogeneity among the studies. First, the types of wearable activity trackers differ among the studies. Although there is evidence supporting inter-device validity and reliability between different types of wearable activity trackers [30], the method for measuring physical activity should be standardized. Henriksen et al. [31] developed a system to record data on physical activity from different types of wearable activity trackers (Apple, Fitbit, Garmin, Oura, Polar, Samsung, and Withings) and confirmed that there was a significant reduction in the daily step count and energy expenditure during the lockdown period. However, the development of a more accurate and more reliable device is a challenge for the future. Second, there is a lack of information on the characteristics of subjects in the included studies. For example, five of nine studies do not show the BMI of the study subjects. In addition, most of the study subjects are probably healthy in the large-scale studies [20][26][27][28]; however, it is possible that those studies include subjects with chronic diseases, and the impact of the pandemic on daily physical activity differs between healthy individuals and patients with chronic diseases. Further studies assessing the change in daily physical activity in patients with chronic diseases such as diabetes, chronic kidney disease, and cancers during pandemics are warranted.

3. Conclusions

In conclusion, daily physical activity was significantly decreased during the current COVID-19 pandemic. It depends on the types of non-pharmacological public health measure; however, the reduction in daily physical activity reaches approximately 10–50% of the amount of daily physical activity before the pandemic. After the current pandemic, the world may confront a significant increase in the number of individuals with metabolic disturbances, such as obesity and diabetes. It should be considered that healthcare professionals encourage people to increase (or at least maintain) daily physical activity via wearable technologies such as smartphone applications. If we construct an effective healthcare system involving wearable activity trackers, we will be able to prevent health problems due to physical inactivity and hospitals’ burden during pandemics in the future.

References

  1. Coronavirus Cases–Worldometer. Available online: https://www.worldometers.info/coronavirus/ (accessed on 1 September 2021).
  2. Soh, S.M.; Kim, Y.; Kim, C.; Jang, U.S.; Lee, H.R. The rapid adaptation of SARS-CoV-2-rise of the variants: Transmission and resistance. J. Microbiol. 2021, 59, 807–818.
  3. Alfano, V.; Ercolano, S. The Efficacy of Lockdown Against COVID-19: A Cross-Country Panel Analysis. Appl. Health Econ. Health Policy 2020, 18, 509–517.
  4. Thu, T.; Ngoc, P.; Hai, N.M.; Tuan, L.A. Effect of the social distancing measures on the spread of COVID-19 in 10 highly infected countries. Sci. Total Environ. 2020, 742, 140430.
  5. Ding, X.; Clifton, D.; Ji, N.; Lovell, N.H.; Bonato, P.; Chen, W.; Yu, X.; Xue, Z.; Xiang, T.; Long, X.; et al. Wearable Sensing and Telehealth Technology with Potential Applications in the Coronavirus Pandemic. IEEE Rev. Biomed. Eng. 2021, 14, 48–70.
  6. Hamasaki, H. Efficacy of wearable devices to measure and promote physical activity in the management of diabetes. Eur. Med. J. Diabetes 2018, 6, 62–69.
  7. Patel, V.; Orchanian-Cheff, A.; Wu, R. Evaluating the Validity and Utility of Wearable Technology for Continuously Monitoring Patients in a Hospital Setting: Systematic Review. JMIR Mhealth Uhealth 2021, 9, e17411.
  8. Creaser, A.V.; Clemes, S.A.; Costa, S.; Hall, J.; Ridgers, N.D.; Barber, S.E.; Bingham, D.D. The Acceptability, Feasibility, and Effectiveness of Wearable Activity Trackers for Increasing Physical Activity in Children and Adolescents: A Systematic Review. Int. J. Environ. Res. Public Health 2021, 18, 6211.
  9. Singh, B.; Zopf, E.M.; Howden, E.J. Effect and feasibility of wearable physical activity trackers and pedometers for increasing physical activity and improving health outcomes in cancer survivors: A systematic review and meta-analysis. J. Sport Health Sci. 2021.
  10. McDonough, D.J.; Su, X.; Gao, Z. Health wearable devices for weight and BMI reduction in individuals with overweight/obesity and chronic comorbidities: Systematic review and network meta-analysis. Br. J. Sports Med. 2021, 55, 917–925.
  11. Cellini, N.; Canale, N.; Mioni, G.; Costa, S. Changes in sleep pattern, sense of time and digital media use during COVID-19 lockdown in Italy. J. Sleep Res. 2020, 29, e13074.
  12. Blume, C.; Schmidt, M.H.; Cajochen, C. Effects of the COVID-19 lockdown on human sleep and rest-activity rhythms. Curr. Biol. 2020, 30, R795–R797.
  13. Wright, K.P., Jr.; Linton, S.K.; Withrow, D.; Casiraghi, L.; Lanza, S.M.; Iglesia, H.; Vetter, C.; Depner, C.M. Sleep in university students prior to and during COVID-19 Stay-at-Home orders. Curr. Biol. 2020, 30, R797–R798.
  14. Gao, C.; Scullin, M.K. Sleep health early in the coronavirus disease 2019 (COVID-19) outbreak in the United States: Integrating longitudinal, cross-sectional, and retrospective recall data. Sleep Med. 2020, 73, 1–10.
  15. Lee, P.H.; Marek, J.; Nálevka, P. Crowdsourced smartphone data reveal altered sleep/wake pattern in quarantined Chinese during the COVID-19 outbreak. Chronobiol. Int. 2020, 37, 1181–1190.
  16. Caputo, E.L.; Reichert, F.F. Studies of Physical Activity and COVID-19 during the Pandemic: A Scoping Review. J. Phys. Act. Health 2020, 17, 1275–1284.
  17. Peçanha, T.; Goessler, K.F.; Roschel, H.; Gualano, B. Social isolation during the COVID-19 pandemic can increase physical inactivity and the global burden of cardiovascular disease. Am. J. Physiol. Heart Circ. Physiol. 2020, 318, H1441–H1446.
  18. Hamer, M.; Kivimäki, M.; Gale, C.R.; Batty, G.D. Lifestyle risk factors, inflammatory mechanisms, and COVID-19 hospitalization: A community-based cohort study of 387,109 adults in UK. Brain Behav. Immun. 2020, 87, 184–187.
  19. Lee, I.M.; Shiroma, E.J.; Lobelo, F.; Puska, P.; Blair, S.N.; Katzmarzyk, P.T.; Lancet Physical Activity Series Working Group. Effect of physical inactivity on major non-communicable diseases worldwide: An analysis of burden of disease and life expectancy. Lancet 2012, 380, 219–229.
  20. Sun, S.; Folarin, A.A.; Ranjan, Y.; Rashid, Z.; Conde, P.; Stewart, C.; Cummins, N.; Matcham, F.; Dalla Costa, G.; Simblett, S.; et al. RADAR-CNS Consortium. Using Smartphones and Wearable Devices to Monitor Behavioral Changes During COVID-19. J. Med. Internet Res. 2020, 22, e19992.
  21. Raeisi, T.; Mozaffari, H.; Sepehri, N.; Darand, M.; Razi, B.; Garousi, N.; Alizadeh, M.; Alizadeh, S. The negative impact of obesity on the occurrence and prognosis of the 2019 novel coronavirus (COVID-19) disease: A systematic review and meta-analysis. Eat Weight Disord. 2021, 1–19.
  22. Kańtoch, E.; Kańtoch, A. Cardiovascular and Pre-Frailty Risk Assessment during Shelter-In-Place Measures Based on Multimodal Biomarkers Collected from Smart Telemedical Wearables. J. Clin. Med. 2021, 10, 1997.
  23. Taylor, J.K.; Ndiaye, H.; Daniels, M.; Ahmed, F.; Triage-HF Plus investigators. Lockdown, slow down: Impact of the COVID-19 pandemic on physical activity-an observational study. Open Heart 2021, 8, e001600.
  24. Mishra, R.; Park, C.; York, M.K.; Kunik, M.E.; Wung, S.F.; Naik, A.D.; Najafi, B. Decrease in Mobility during the COVID-19 Pandemic and Its Association with Increase in Depression among Older Adults: A Longitudinal Remote Mobility Monitoring Using a Wearable Sensor. Sensors 2021, 21, 3090.
  25. Woodruff, S.J.; Coyne, P.; St-Pierre, E. Stress, physical activity, and screen-related sedentary behaviour within the first month of the COVID-19 pandemic. Appl. Psychol. Health Well Being 2021, 13, 454–468.
  26. Ong, J.L.; Lau, T.; Massar, S.; Chong, Z.T.; Ng, B.; Koek, D.; Zhao, W.; Yeo, B.; Cheong, K.; Chee, M. COVID-19-related mobility reduction: Heterogenous effects on sleep and physical activity rhythms. Sleep 2021, 44, zsaa179.
  27. Pépin, J.L.; Bruno, R.M.; Yang, R.Y.; Vercamer, V.; Jouhaud, P.; Escourrou, P.; Boutouyrie, P. Wearable Activity Trackers for Monitoring Adherence to Home Confinement During the COVID-19 Pandemic Worldwide: Data Aggregation and Analysis. J. Med. Internet Res. 2020, 22, e19787.
  28. Capodilupo, E.R.; Miller, D.J. Changes in health promoting behavior during COVID-19 physical distancing: Utilizing wearable technology to examine trends in sleep, activity, and cardiovascular indicators of health. PLoS ONE 2021, 16, e0256063.
  29. Zinner, C.; Matzka, M.; Leppich, R.; Kounev, S.; Holmberg, H.C.; Sperlich, B. The Impact of the German Strategy for Containment of Coronavirus SARS-CoV-2 on Training Characteristics, Physical Activity and Sleep of Highly Trained Kayakers and Canoeists: A Retrospective Observational Study. Front. Sports Act. Living 2020, 2, 579830.
  30. Evenson, K.R.; Goto, M.M.; Furberg, R.D. Systematic review of the validity and reliability of consumer-wearable activity trackers. Int. J. Behav. Nutr. Phys. Act. 2015, 12, 159.
  31. Henriksen, A.; Johannessen, E.; Hartvigsen, G.; Grimsgaard, S.; Hopstock, L.A. Consumer-Based Activity Trackers as a Tool for Physical Activity Monitoring in Epidemiological Studies During the COVID-19 Pandemic: Development and Usability Study. JMIR Public Health Surveill. 2021, 7, e23806.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
Upload a video for this entry
Information
Subjects: Primary Health Care
Contributor MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Hidetaka Hamasaki
View Times: 375
Entry Collection: COVID-19
Revisions: 2 times (View History)
Update Date: 10 Nov 2021
Table of Contents
    1000/1000
    Hot Most Recent
    Feedback