| Literature DB >> 28005190 |
David R Bassett1, Lindsay P Toth2, Samuel R LaMunion2, Scott E Crouter2.
Abstract
Step counting has long been used as a method of measuring distance. Starting in the mid-1900s, researchers became interested in using steps per day to quantify ambulatory physical activity. This line of research gained momentum after 1995, with the introduction of reasonably accurate spring-levered pedometers with digital displays. Since 2010, the use of accelerometer-based "activity trackers" by private citizens has skyrocketed. Steps have several advantages as a metric for assessing physical activity: they are intuitive, easy to measure, objective, and they represent a fundamental unit of human ambulatory activity. However, since they measure a human behavior, they have inherent biological variability; this means that measurements must be made over 3-7 days to attain valid and reliable estimates. There are many different kinds of step counters, designed to be worn on various sites on the body; all of these devices have strengths and limitations. In cross-sectional studies, strong associations between steps per day and health variables have been documented. Currently, at least eight prospective, longitudinal studies using accelerometers are being conducted that may help to establish dose-response relationships between steps/day and health outcomes. Longitudinal interventions using step counters have shown that they can help inactive individuals to increase by 2500 steps per day. Step counting is useful for surveillance, and studies have been conducted in a number of countries around the world. Future challenges include the need to establish testing protocols and accuracy standards, and to decide upon the best placement sites. These challenges should be addressed in order to achieve harmonization between studies, and to accurately quantify dose-response relationships.Entities:
Mesh:
Year: 2017 PMID: 28005190 PMCID: PMC5488109 DOI: 10.1007/s40279-016-0663-1
Source DB: PubMed Journal: Sports Med ISSN: 0112-1642 Impact factor: 11.136
Number of Fitbit devices sold worldwide from 2010 to 2015. From Statista [4]
| Year | No. of devices sold per year (in thousands) |
|---|---|
| 2010 | 58 |
| 2011 | 208 |
| 2012 | 1279 |
| 2013 | 4476 |
| 2014 | 10,904 |
| 2015 | 21,355 |
Steps-per-day categories and classification system of Tudor-Locke and Bassett [33]
| Steps per day | Classification |
|---|---|
| <5000 | Sedentary lifestyle |
| 5000–7499 | Physically inactive |
| 7500–9999 | Moderately active |
| ≥10,000 | Physically active |
| ≥12,500 | Very active |
Fig. 1Relationship between locomotive speeds and rates of caloric expenditure.
Reproduced from Hatano et al. [34] with permission
Steps-per-day categories and prevalence of metabolic syndrome in Australian men and women.
From Schmidt et al. [41]
| Activity level | Sample | Metabolic syndrome | |||
|---|---|---|---|---|---|
|
| % | % with MetS | PR | 95% CI | |
| Men | |||||
| Sedentary (0–4999) | 69 | 7.8 | 13.0 | 1.00 | Ref |
| Low-active (5000–7499) | 247 | 27.9 | 14.6 | 1.22 | 0.62–2.39 |
| Somewhat active (7500–9999) | 242 | 27.3 | 12.4 | 0.98 | 0.49–1.95 |
| Active (10,000–12,500) | 190 | 21.4 | 10.5 | 0.72 | 0.34–1.51 |
| High-active (≥12,500) | 139 | 15.7 | 4.3 | 0.29 | 0.11–0.79 |
| | <0.01 | <0.001 | |||
| Women | |||||
| Sedentary (0–4999) | 56 | 6.2 | 14.3 | 1.00 | Ref |
| Low-active (5000–7499) | 253 | 27.9 | 5.5 | 0.39 | 0.17–0.86 |
| Somewhat active (7500–9999) | 301 | 33.2 | 4.0 | 0.30 | 0.13–0.70 |
| Active (10,000–12,500) | 193 | 21.3 | 6.2 | 0.48 | 0.21–1.10 |
| High-active (≥12,500) | 103 | 11.4 | 2.9 | 0.22 | 0.06–0.79 |
| | 0.06 | 0.10 | |||
Prospective, longitudinal studies using wearable activity monitors to assess physical activity and examine it in relation to disease endpoints. Reproduced with permission from Dr. I-Min Lee (Wearable Devices and the 24-Hour Activity Cycle, conference held at Stanford University, Palo Alto, 27–28 April 2016)
| Study | Start year | Sample size | Population age | Device | Delivery mode |
|---|---|---|---|---|---|
| REGARDS | 2008 | ~10,000 | 56+ years | Actical | |
| EPIC Norfolk | 2008 | 3892 | 60–80 years | ActiGraph GT1 M | In Person |
| Actife Ulm | 2009 | 1500 | 65–90 years | ActivPAL | In Person |
| BRHS | 2010 | ~2500 | Mean 78 years | ActiGraph GT3X | |
| Maastricht Study | 2010 | ~10,000 | 40–75 years | ActivPAL | In Person |
| WHS | 2011 | ~18,000 | 62+ years | ActiGraph GT3X+ | |
| WHI | 2012 | ~7000 | 63+ years | ActiGraph GT3X+ | In Person/Mail |
| UK Biobank | 2013 | ~100,000 | 40–69 years | Axivity AX3 |
REGARDS reasons for geographic and racial differences in stroke, EPIC European prospective investigation of cancer, BRHS British Regional Heart Study, WHS Women’s Health Study, WHI women’s health initiative
| Steps are a fundamental unit of human locomotion, and thus are a preferred metric for quantifying physical activity. |
| In cross-sectional studies, strong associations between steps per day and health variables have been documented. |
| Many step-counting devices are available for both consumer and research use, but the need for industry standardization is acknowledged and must be addressed in order to harmonize data. |