Original paperAdjusting step count recommendations for anthropometric variations in leg length
Introduction
One of the major limitations of monitoring physical activity with pedometers is their inability to distinguish physical activity of varying intensity. It has been suggested that this limitation might be overcome by using step frequency as a marker of intensity, thus allowing for a determination of the threshold for moderate intensity physical activity (MPA).1, 2 This is based on the notion that step frequency is related to the amount of energy expended. All things equal, walking at 50 steps min−1 would have a lower metabolic equivalent (MET) value than walking at 150 steps min−1. In fact, preliminary evidence indicates that the moderate intensity threshold of 3METs corresponds to 100 steps min−1.1, 3
While 100 steps min−1 provides a practical physical activity recommendation, it varies among people.1 This may partially be accounted for by leg length differences between adults. Leg length largely determines the step frequency which in turn affects the metabolic cost during walking. Therefore, the relationship between step frequency and metabolic cost may differ between people of varying leg length, affecting the step frequency associated with the MPA threshold. Accounting for this in step frequency recommendations is likely to provide a more precise estimate of step frequency required to reach the MPA threshold. The present study, therefore, examined the effect of leg length on the MPA threshold of 100 steps min−1.
Section snippets
Methods
Participants were 20 healthy adults (26.4 ± 4.6 years, 9 males). Their height, body mass, and leg length were measured while wearing shoes and light clothing. Leg length was measured with a tape measure (cm) as the distance from the greater trochanter to the floor with participants wearing shoes and keeping their legs straight. The study was approved by the Institutional Review Board and all participants provided written informed consent.
Participants were instructed to avoid food, caffeine, and
Results
Table 1 shows the participants’ characteristics, steps frequency, and METs across the five walking speeds. The model with the best fit to predict steps min−1 from METs is presented below:
Steps min−1 predicted = −1.88968 + (MET * 82.91132) + ((MET2) * −7.80956) + (BMI * 2.654937) + (Leg Lengthcm * −1.14803) + ((MET * BMI) * −0.51904), SEE 3.49 steps min−1 (R2 = 0.68)
Using this regression equation, the steps min−1 that corresponded to expending 3 METS was estimated. Using the mean values for BMI (23.87 kg m−2) and leg length
Discussion
Developing a threshold based on step frequency that corresponds to expending 3 METs has widespread public health application. Most importantly, it provides the general public with a simple and inexpensive means by which to self-monitor their progress towards reaching physical activity recommendations associated with health (i.e., 150 min wk−1).4 However, the recommended MPA threshold of 100 steps min−1 overlooks between-people differences in leg length, which directly influences both step
Practical Implications
The use of pedometers to monitor moderate and above intensity physical activity has widespread application, both for the research community and general public. The practical importance of the findings is the ability to more specifically define the step frequency threshold for each individual, based on height (i.e., leg length). From this, more accurate prescriptions of moderate physical activity can be provided and progress towards documented for health-related pursuits (e.g., weight
References (4)
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Translating physical activity recommendations into a pedometer-based step goal: 3000 steps in 30 minutes
Am J Prev Med
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Pedometer reliability, validity and daily activity targets among 10- to 15-year-old boys
J Sports Sci
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