Moving Toward the Inclusion of Step-Based Metrics in Physical Activity Guidelines and Surveillance

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Jacqueline L. Mair Future Health Technologies, Singapore-ETH Center, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore
Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore

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Elroy J. Aguiar Department of Kinesiology, College of Education, The University of Alabama, Tuscaloosa, AL, USA

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Emmanuel Stamatakis Charles Perkins Center, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia

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Sarah M. Edney Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore

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Physical activity (PA) is crucial to maintaining good physical and mental health and reducing the risk of chronic diseases. As such, many countries have developed national guidelines to promote PA among their populations, with the World Health Organization (WHO) guidelines1 providing a blanket set of global recommendations. In the 5 years since the launch of the WHO Global Action Plan on Physical Activity,2 there has been progress in the number of countries with national PA guidelines and surveillance mechanisms, but significant surveillance data gaps remain, both nationally and globally. These gaps must be addressed if we are to reduce the burden of physical inactivity.3 One critical data gap is the consistent measurement of PA and sedentary behavior metrics over time, including domain-specific behaviors.

Aligned to innovations in technology and increased adoption of mobile and wearable technology in recent years, there has been growing interest in using step count as a viable measure of ambulatory PA. Smartphones and wearables can continually and passively track steps in free-living settings over long periods of time,4 making them an accessible and scalable tool by which to measure and promote PA behavior. Multiple mass media campaigns and nationwide PA programs advocate for individuals to accumulate 10,000 steps per day, because step counting is relatively simple to monitor and easy to understand. Tracking of step counts is often at the core of digital interventions to promote PA5 because ubiquitous technology allows individuals to receive immediate feedback on their PA levels which in turn can motivate future activity. The aim of this editorial is to explore the reasons why current global and national guidelines on PA and sedentary behavior do not include a daily step count-based recommendation and suggest ways forward for the development of such recommendations.

Evidence-Based Guidelines

The 2020 WHO guidelines on PA and sedentary behavior were informed by evidence syntheses conducted in 20186 and 2020,1 which found insufficient evidence for the dose–response relationship between steps per day and health outcomes. Since then, several studies have been published to address this evidence gap. A recent meta-analysis of 15 international cohort studies using hip-worn accelerometers (totaling 47,471 adults) found that taking 8,000 to 10,000 steps per day for adults younger than 60 years old and 6,000 to 8,000 steps per day for adults over 60 years old was associated with progressively lower risk of all-cause mortality, respectively.7 Further, the 50% to 60% lower risk in the higher versus lower steps per day quartiles is similar to the relationship observed for accelerometer-determined moderate to vigorous PA (MVPA) and all-cause mortality. Another study using wrist-worn accelerometer data from a cohort of 78,500 adults in the United Kingdom reported gradually reduced risk of all-cause, cancer, and cardiovascular disease mortality up to approximately 10,000 steps per day.8 These findings add empirical weight to earlier calls for a move toward step-based PA guidelines.9

The growing evidence linking steps per day to health benefits is promising, but certain limitations must be addressed before step-based guidelines can be implemented. First, step counting is limited to ambulatory movement which raises 3 key issues: (1) other types of aerobic PA, such as cycling and swimming, are not captured or are captured inaccurately; (2) strength- and balance-based aspects of the guidelines are not included; and (3) people who are nonambulatory cannot partake. It is important to note, however, that walking is a commonly reported mode of exercise10 and is a necessity for most activities of daily living. Second, the minimal and optimal number of steps needed for health varies for different population groups such as children, older adults, pregnant women, and people with certain health conditions who may require different step count guidelines. Relying solely on step count may promote a “one-size-fits-all” approach to PA promotion, which may not be appropriate for all groups. Third, step count alone gives a general indication of the total amount of ambulatory activity in a day but does not capture the intensity of PA, which is a critical determinant of health effects.8 Here, step cadence can be used as a proxy for PA intensity.11 For example, studies have reported a strong relationship between cadence and intensity, whereby taking ≥100 steps per minute is approximately equivalent to MVPA,12 with each 10 steps per minute increment up to 130 steps per minute associated with an increase of 1 metabolic equivalent (ie, 100, 110, 120, and 130 steps per minute associated with 3, 4, 5, and 6 metabolic equivalents, respectively).13 Other cadence-based metrics, such as peak 30-minute cadence (average steps per minute for the 30 highest, but not necessarily consecutive, minutes per day), have also been linked to reduced mortality and morbidity.8 In a practical sense, walking cadence can be estimated by simply counting the number of steps accumulated in a certain time window (epoch, eg, 1-min or 15-s epochs multiplied by 4). Some newer consumer-level wearable devices provide instantaneous display of cadence on the watch face, which can facilitate self-regulation of walking cadence to achieve MVPA thresholds or personalized targets. However, in the absence of activity tracking devices, pace-based instruction such as asking people to walk at a “usual” or “fast” pace could also assist people to walk at cadence associated with health benefits. A recent meta-analysis reported that adults who were asked to walk at a self-selected usual or fast pace naturally stepped at cadences averaging 117 and 127 steps per minute, respectively,14 suggesting that this pace instruction helps people to walk at an intensity equivalent to MVPA.

PA Surveillance

Any move toward using consumer device-based measures of PA within surveillance systems that monitor adherence to guidelines has thus far been hampered by concerns over the feedback devices provide that may influence the observed behavior, as well as the representativeness, validity, reliability, and comparability of the data collected from different devices.15 Furthermore, complexities around safe data sharing, access, and storage in line with varying data protection policies around the world cause added anxiety. In-depth discussions of these points can be found elsewhere.4,16 Here, we outline some possible solutions to these challenges. First, remote representative sampling via smartphones could already be possible in some countries given current smartphone penetration rates.17 Considering rising smartphone ownership across the world, opportunities for such will continue to increase in high-income and low- or middle-income countries alike. Second, research conducted in the laboratory18 and in free-living settings Höschsmann supports the validity and reliability of step tracking data from certain consumer-grade devices. These data appear to be comparable with a research-grade accelerometer, which has been shown to underestimate steps by around 20%.19 Assuming these findings are applicable to other consumer- and research-grade devices, estimates of stepping are likely to be conservative, which could be considered when using devices in general for surveillance purposes. Third, with appropriate consent from data owners (ie, individual users) it is already possible to access step count data from smartphones and wearables via application programming interfaces (APIs).4 In summary, opportunities to collect population-level step count data already exist, but we still lack reasonable agreement on how to safely share, access, store, and use these data at scale for population PA surveillance purposes.

Device-based surveillance of stepping is in its infancy, and there are many unknowns. A certain degree of consensus on the above issues is needed for step-based PA surveillance to monitor adherence to any step-based guidelines. Long-term public–private partnerships (involving academics, government, guideline developers, and industry) and an appropriate regulatory framework will be needed to help governments or national nongovernmental organizations implement the safe collection and use of step count data from consumer-grade devices. Indeed, examples of such collaborations are beginning to emerge; Google recently announced Open Health Stack—a suite of open-source building blocks built on an interoperable data standard—developed in partnership with the WHO.20 A standardized and well-coordinated approach to PA surveillance will be a major contributor toward step-based PA guidelines.

Conclusions

Given the popularity of walking and the ease with which steps per day can be measured, step-based PA guidelines could reach a wider audience and aid the promotion of PA. Although several challenges need to be overcome, it is important that key stakeholders (researchers, practitioners, policy makers, and industry) strongly consider the benefits of leveraging existing and future technologies to advance PA surveillance in parts of the world that, to date, are largely unreached, for example, low- or middle-income countries. Despite the challenges, choosing not to take advantage of the masses of data captured by consumer-grade devices is a missed opportunity. Importantly, step-based guidelines should not be seen as a substitute for more comprehensive PA guidelines that include recommendations for strength and balance exercise and limiting sedentary behavior. Rather, step count recommendations should be seen as an adjunct to, or component of, PA guidelines. Ultimately, stepping-based targets offer more options to populations and individuals on how to set PA-related goals and monitor progress. Such tailored approaches to PA promotion, taking into account individual needs and preferences are likely to be the most promising.

References

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  • Collapse
  • Expand
  • 1.

    Bull FC, Al-Ansari SS, Biddle S, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54(24):14511462. PubMed ID: 33239350 doi:10.1136/bjsports-2020-102955

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    World Health Organization. Global Action Plan on Physical Activity 2018–2030: More Active People for a Healthier World. World Health Organization; 2018. Accessed April 27, 2023. https://apps.who.int/iris/bitstream/handle/10665/272722/9789241514187-eng.pdf

    • Search Google Scholar
    • Export Citation
  • 3.

    World Health Organization. Global Status Report on Physical Activity 2022. World Health Organization; 2022. Accessed April 27, 2023. https://www.who.int/publications/i/item/9789240059153

    • Search Google Scholar
    • Export Citation
  • 4.

    Mair JL, Hayes LD, Campbell AK, Sculthorpe N. Should we use activity tracker data from smartphones and wearables to understand population physical activity patterns? J Meas Physical Behav. 2022;5(1):37. doi:10.1123/jmpb.2021-0012

    • Search Google Scholar
    • Export Citation
  • 5.

    Vetrovsky T, Borowiec A, Juřík R, et al. Do physical activity interventions combining self-monitoring with other components provide an additional benefit compared with self-monitoring alone? A systematic review and meta-analysis. Br J Sports Med. 2022;56:13661374. doi:10.1136/bjsports-2021-105198

    • Search Google Scholar
    • Export Citation
  • 6.

    Kraus WE, Janz KF, Powell KE, et al. Daily step counts for measuring physical activity exposure and its relation to health. Med Sci Sports Exerc. 2019;51(6):12061212. doi:10.1249/MSS.0000000000001932

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Paluch AE, Bajpai S, Bassett DR, et al. Steps for health collaborative. Daily steps and all-cause mortality: a meta-analysis of 15 international cohorts. Lancet Public Health. 2022;7(3):e219e228. doi:10.1016/S2468-2667(21)00302-9

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    del Pozo Cruz B, Ahmadi MN, Lee I, Stamatakis E. Prospective associations of daily step counts and intensity with cancer and cardiovascular disease incidence and mortality and all-cause mortality. JAMA Intern Med. 2022;182(11):11391148. doi:10.1001/jamainternmed.2022.4000

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Tudor-Locke C, Aguiar EJ. Toward comprehensive step-based physical activity guidelines: are we ready? Kinesiol Rev. 2019;8(1):2531. doi:10.1123/kr.2018-0065

    • Search Google Scholar
    • Export Citation
  • 10.

    Hulteen RM, Smith JJ, Morgan PJ, et al. Global participation in sport and leisure-time physical activities: a systematic review and meta-analysis. Prev Med. 2017;95:1425. doi:10.1016/j.ypmed.2016.11.027

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Huang BH, Hamer M, Chastin S, Pearson N, Koster A, Stamatakis E. Cross-sectional associations of device-measured sedentary behaviour and physical activity with cardio-metabolic health in the 1970 British Cohort Study. Diabet Med. 2021;38:e14392. doi:10.1111/dme.14392

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Tudor-Locke C, Aguiar EJ, Han H, et al. Walking cadence (steps/min) and intensity in 21–40 year olds: CADENCE-adults. Int J Behav Nutr Phys Act. 2019;16:8. doi:10.1186/s12966-019-0769-6

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Tudor-Locke C, Han H, Aguiar EJ, et al. How fast is fast enough? Walking cadence (steps/min) as a practical estimate of intensity in adults: a narrative review. Br J Sports Med. 2018;52(12):776788. doi:10.1136/bjsports-2017-097628

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Murtagh EM, Mair JL, Aguiar E, et al. Outdoor walking speeds of apparently healthy adults: a systematic review and meta-analysis. Sports Med. 2021;51:125141. doi:10.1007/s40279-020-01351-3

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Strain T, Milton K, Dall P, Standage M, Mutrie N. How are we measuring physical activity and sedentary behaviour in the four home nations of the UK? A narrative review of current surveillance measures and future directions. Br J Sports Med. 2020;54(21):12691276. doi:10.1136/bjsports-2018-100355

    • Search Google Scholar
    • Export Citation
  • 16.

    Strain T, Wijndaele K, Pearce M, Brage S. Considerations for the use of consumer-grade wearables and smartphones in population surveillance of physical activity. J Meas Physical Behav. 2022;5(1):814. doi:10.1123/jmpb.2021-0046

    • Search Google Scholar
    • Export Citation
  • 17.

    Statista. Smartphone ownership penetration in the United Kingdom (UK) in 2012–2022, by age. Accessed April 21, 2023. https://www.statista.com/statistics/271851/smartphone-owners-in-the-united-kingdom-uk-by-age/

    • Search Google Scholar
    • Export Citation
  • 18.

    Mora-Gonzalez J, Gould ZR, Moore CC, et al. A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study. Int J Behav Nutr Phys Act. 2022;19:117. doi:10.1186/s12966-022-01350-9

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Höchsmann C, Knaier R, Infanger D, Schmidt-Trucksäss A. Validity of smartphones and activity trackers to measure steps in a free-living setting over three consecutive days. Physiol Meas. 2020;41(1):015001. PubMed ID: 31851949 doi:10.1088/1361-6579/ab635f

    • Search Google Scholar
    • Export Citation
  • 20.

    Hersch F. New tools to help developers build better health apps. 2023. Accessed April 7, 2023. https://blog.google/technology/health/health-developer-tool-thecheckup/

    • Search Google Scholar
    • Export Citation
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