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23 sep 2011

Measurement of moderate intensity physical activity via pedometers-lessons learned

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Physical activity has both short and long term benefits including improving cardiovascular, metabolic, skeletal and psychological health of both children and adults.

Autor(es): Thomas Francis Cuddihy
Entidades(es): School of Human Movement Studies
Congreso: VII CONGRESO DE LA ASOCIACIÓN INTERNACIONAL DE ESCUELAS SUPERIORES DE EDUCACIÓN FÍSICA (AIESEP)
A Coruña, 26-29 de Octubre de 2010
ISBN: 978-84-614-9946-5
Palabras claves: pedometers, MVPA, validity

Abstract

Adult Australian national physical activity guidelines mandate achievement of at least 30 minutes of moderate to vigorous physical activity (MVPA) on most days of the week.  Recently, some pedometer manufacturers claim devices that measure MVPA. However, little or no published studies concerning their validity or reliability to do this may be found.  Participants (n = 18, females = 10) were University undergraduate students who walked on three occasions, on a treadmill for 5 minutes at four different step frequencies (100, 110, 120 and 130 steps/minute (spm). This protocol resulted in an exercise intensity of between 3.0-6.0 MET’s. Participants’ data were collected using Walk4Life MVPA_pedometers, heart rate monitors and an accelerometer. MET levels, steps and MVPA(seconds) physical activity duration and Rating of Perceived Exertion (RPE) data were collected.  Repeated measures analysis results indicated that this pedometer does validly and reliably measure accumulated MVPA when the MVPA filter is set at a step frequency of 110spm. Intra class correlations (ICC) of between 0.65 and 0.81 for differing step frequencies when measured over 3 different occasions were registered.  ICC’s for total physical activity duration for the different step frequencies ranged from 0.75 – 0.82.  Consequently this function may provide objective measurement of daily MVPA. 

KEY_WORDS: pedometers, MVPA, validity

Introduction

Physical activity has both short and long term benefits including improving cardiovascular, metabolic, skeletal and psychological health of both children and adults. Additionally, obesity and low physical activity are associated with issues of social acceptance, competence, physical appearance, self-esteem and associated with medical conditions including hypertension, dyslipidaemia, type 2 diabetes and other problems include musculoskeletal discomfort, obstructive sleep apnoea, heat intolerance, asthma and shortness of breath (Dietz, 1998; Freedman, Dietz, Srinivasan and Berenson, 1999).  

The Australia Government’s Department of Health and Ageing’s National Physical Activity Guidelines (1999) for adults mandate that they take at least 30 minutes of  moderate to vigorous physical activity each day i.e in the 3 – 6 METS range. Over half these adults do not reach these recommended levels of physical activity (Armstrong, Bauman and Davies, 2000)   A recent national survey (Commonwealth of Australia, 2008) on nutritional intake and physical activity in Australian children aged 2-16 years (n=4,487), daily physical activity levels measured by pedometer steps/day and activity recall surveys were established and compared to the National Physical Activity Guidelines. Findings indicate that approximately 70% of children were meeting the National Physical Activity Guidelines, however of more concern was the information that ~70% of children were not adhering to the National Guidelines of less than 120 minutes of ‘screen time’ per day indicating higher than recommended levels of sedentary activity (Commonwealth of Australia, 2008).   In a recent paper the term “Active Couch Potatoes” was coined to refer to adults who gain regular physical activity, even as much as 30 minutes of moderate to vigorous physical activity on most days yet they also engage in a trend of long time sitting and screen based activities  (Owen, Healy, Matthews and Dunstan, 2010).  

A range of public health measures and individual strategies have been identified in an attempt to address declining levels of physical activity and increased sedentary activities.  Motion sensors such as accelerometers and pedometers have received increased attention because of their potential as precise physical activity measurement tools and as promising motivational devices (Tudor-Locke et al., 2003). Pedometers are currently the most useful tool for field use due to their established validity (Crouter et al., 2003; Le Masurier and Tudor-Locke, 2003), low cost, accessibility, practical simple interface and low data management requirements. Pedometers also function as effective feedback tools providing immediate information on activity level, act as environmental cues to stimulate physical activity and can be used in combination with record keeping for progressive goal-setting and reflection (Beighle, Pangrazi and Vincent, 2001).

There are currently no nationally recognised guidelines regarding the number of steps to take per day for children, adolescents or adults as measured by pedometers, however two commonly referenced recommendations include 13,000 steps/d and 11,000 steps/d for boys and girls respectively (Presidential Council on Fitness and Sport 2002) and 15,000 steps/d and 12,000 steps/d for boys and girls respectively (Tudor-Locke et al. 2002).  However, in adult Australian population studies 10,000 steps has been trialled with limited success (Brown, Eakin and Mummery et al., 2006).  The study was limited to modest success with changes in physical activity noted only among females.   A criticism of pedometers and the currently held guidelines is that they are not typically designed to capture intensity of activity, an important feature of the Australian national physical activity recommendations due to association with cardio respiratory health (Beighle, Pangrazi and Vincent, 2001; Commonwealth of Australia, 2005; Williams, 2001). Therefore, in order to be useful, guidelines that include activity intensity levels are required for evaluation purposes (Tudor-Locke and Bassett, 2004). Scruggs et al. (2003) recently introduced the concept of utilising step rate expressed as steps/min to infer activity intensity based upon the premise that if step rate (or cadence) is known, a corresponding physical activity intensity may be inferred if specific cut points in terms of steps/min were available to represent meaningful intensity categories.

The National Physical Activity Guidelines express physical activity recommendations as time multiples of ‘Moderate to Vigorous Physical Activity’ intensity, or MVPA. This is currently accepted widely in the literature to correspond to an intensity of 3.0-5.99 METs (Tudor-Locke et al., 2005; Freedson et al., 1998). This can be accurately measured by determining VO2 during exercise, however is impractical due to energy, time and cost requirements and skill intensive equipment. Additionally systematic observation tools (SOFIT, MARCA) have been identified as the most valid criterion measure for assessing children’s physical activity levels within a defined space and time period (Kohl, Fulton and Caspersen, 2000) as they report continual physical activity throughout the day which can be linked to an energy cost. This is also an impractical undertaking for large-scale implementation. Therefore, further efforts to utilise pedometer technology to reach these goals appears promising.

Researchers such as Scruggs et al. (2003) Tudor-Locke et al. (2005) have established pedometer steps/min intensity categories for women and men, determining cut-points for minimal moderate intensity walking (96 steps/min for men and 107 steps/min in women) based upon steady-state VO2 recordings and concurrent pedometer recordings (96-124 steps/min and 107-135 steps/min). Each of these studies therefore based their physical activity recommendations upon measuring the number of pedometer steps taken over a set time period (eg. 2,880 steps in 30 minutes for men) to achieve this intensity goal. A new generation of pedometers recently released have a new function which allows users to set a cadence threshold, which when the user begins to walk at or above this cadence, accumulates time (seconds). This innovation has the potential for use as if step/min cut-points may be used to infer exercise intensity, users of this pedometer may track their ‘moderate to vigorous’ intensity physical activity over the course of a day and compare to the national guidelines (ref Walk4Life). This would prove a more efficient and user-friendly method of tracking MVPA as users of the pedometers can simply read their time tally of MVPA at the end of a day, rather than reading off steps in a specified time period and recording these over a day.  Australia wants to build an evidence base of effective health promotion and prevention strategies (National Health and Hospitals Reform Commission, 2009) consequently, having access to a pedometer which records MVPA would add economic viability and enhanced validity to adult physical activity data collection.

The current study is the first in a series of investigations to assess the accuracy, reliability, and validity of a new line of pedometers (namely the Walk4Life MVPA) in the measuring, monitoring and public health promotion of physical activity in adults. Specifically, this study aims to evaluate the ability of the pedometers to accurately accumulate moderate to vigorous physical activity (minutes and seconds) via the number of steps taken during prescribed treadmill walking at a rate on or above a minimum filter stepping frequency threshold e.g. 110 spm.

Methods

Pre-Test Protocol

Participants (n=18; 10 female) filled in a basic information sheet, appropriate ethics approval was gained and PAR-Q was used to exclude any participants from the study at risk of adverse events from physical activity. Subject’s height (cm) and weight was measured using a stadiometer and weight (kg) was measured using electronic scales and leg length (cm) was measured from the greater trochanter of the femur to the lateral malleolus of the ankle. Step length was measured as the subject’s heel-heel distance (average over 4 steps). Participants were fitted with a heart rate monitor and resting heart rate was recorded.

Subjects also wore a belt of suitable size, on which two pedometers were appropriately attached (one on each hip) directly onto the belt. The pedometers were programmed to set the MVPA threshold (the cadence above which time would accumulate indicating MVPA time) appropriate to the cadence that the participants would be walking at. The pedometer on the right hip had its MVPA threshold set to the metronome speed that the subject would be walking at on the right hip, and the MVPA threshold on the left hip pedometer was set to 10 steps per minute below the right hip setting. For example if the right pedometer was set to record MVPA steps and duration at or above 120 steps/minute (spm) then the left pedometer was set at 110 spm. Once attached to the participant the pedometers were left open so as not to accumulate data until the walking protocol began. At that instant they were closed to the vertical position to accumulate perturbations.  Participants were instructed on how to use Borg’s ‘Ratings of Perceived Exertion’ and were informed they were to report their RPE at the end of each two minute data collection.  MET levels were recorded using two protocols.  Firstly MET’s were recorded directly from the treadmill computer software. In addition MET’s were also generated based on the treadmill speed and the elevation of the treadmill, via calculations regarding the horizontal and vertical component of the oxygen cost of walking (American College of Sport Medicine Guidelines for Exercise Testing and Prescription formulas 8th Edition 2010).

Design

All participants were to complete two minutes of data collections at four different metronome frequencies. The order of frequencies between and within participants was counterbalanced and participants had at least two minutes rest between each set of data collection. The testing protocol was repeated on two more occasions with a similar testing protocol.

Testing Protocol

Participants were instructed to walk on the treadmill (gradient 1%) to the same pace as a metronome sounding from a nearby computer. The metronome was set to one of four possible step frequencies (100, 110, 120, and 130steps/minute). Participants began walking from a stationary position on the treatment and slowly increased the treadmill speed, adjusting it until their step rate coincided with the metronome pace. Once reaching the goal metronome pace, participants were instructed that the two minute test was about to begin, at which time participants closed both pedometers on their hips (thereby starting data collection) and walked for a time of two minutes after which the treadmill immediately stopped. Treadmill speed and equivalent METs were recorded and heart rate was recorded every 30 seconds during the two minute test. Additionally, the numbers of steps taken during the two minute test were manually counted using a hand counter. Participants reported their RPE after completion of the test and the pedometers were opened and total steps recorded, including time in MVPA and total time in physical activity for both pedometers. This protocol was repeated on three further occasions at a range of different step frequencies, with the metronome and pedometer thresholds modified accordingly.

The same protocol was repeated two more times on separate visits to the laboratory. On the second testing session, accelerometers were positioned in the centre of the lumbar spine secured with micro-pore tape. Each session the stepping frequency order was changed based on a Latin square format. The same protocol was repeated in a third session.

Data Analysis

Data collected included the following variables:

  • Baseline data: age, height, weight, leg length, average step length and resting heart rate
  • Pedometer: number of steps taken, total time in physical activity, time in MVPA
  • Accelerometer: acceleration data in the x, y, z planes
  • Treadmill speed, heart rate, METs, RPE, counted steps
  • Acceleration data analysis were made using a Sin analysis

Results

Table 1 is a report of the height, weight and resting heart rates.  Treadmill speeds measured as metres per sec (m/s) are reported for each of the stepping frequencies. One male participant was heavy and tall with a weight of 115 Kgs and a standing height of 207 cms.  It may be seen in Table 2 that when walking at 100 steps per minute that some females and males did not engage in exercise intensity greater than 3.00 METS.

Table 1.  Participant height, weight heart rate and range of treadmill speeds

Sex

Variables

Ht

Weight

Resting HR

Treadmill speed (m/s)
at 100 spm

Treadmill speed (m/s)
at 110 spm

Treadmill speed (m/s)
at 120 spm

Treadmill speed (m/s)
at 130 spm

Female

N

10

10

10

10

10

10

10

Minimum

160.0

53.0

54.0

48.3

63.3

70.0

85.0

Maximum

185.0

75.4

98.0

75.0

91.7

103.3

115.0

Mean

168.2

64.8

71.8

62.5

77.1

90.9

101.9

Std. Dev.

8.1

7.7

12.0

6.2

7.4

8.2

8.1

Male

N

8

8

8

8

8

8

8

Minimum

168.0

65.9

61.0

56.7

65.0

78.3

88.3

Maximum

207.0

115.0

80.0

86.7

108.3

123.3

120.0

Mean

182.6

79.9

71.1

69.7

84.1

101.1

109.5

Std. Dev.

10.5

15.7

5.6

9.0

12.4

12.4

8.6


Table 2.  MET values at the different step frequencies

Sex

N

Minimum

Maximum

Mean

Std. Deviation

Female

Mets @ 100spm

10

2.6

3.5

3.1

.2

Mets @ 110spm

10

3.1

4.1

3.6

.2

Mets @ 120spm

10

3.4

4.6

4.1

.3

Mets @ 130spm

10

3.8

6.2

4.8

.7

Valid N (listwise)

10

 

 

 

 

Male

Mets @ 100spm

8

2.9

3.9

3.3

.3

Mets @ 110spm

8

3.2

5.3

3.9

.6

Mets @ 120spm

8

3.6

7.3

4.9

1.1

Mets @ 130spm

8

4.0

7.0

5.6

.9

Valid N (listwise)

8

 

 

 

 

Data in Table 3 indicate that there were no significant differences for the number of steps determined by the right hand pedometer (RH Ped) among the three visits to the laboratory for testing.  The F values for the four frequencies at each of the three visits were less than 1.5 and the p values ranged from 0.25 to 0.84.  Additionally, there were no significant differences between the hand counted steps at each frequency and the steps registered by the right hand Pedometer.  As indicated by the mean and the size of the standard deviations for the right hand pedometer the greatest variance was evidenced at the slower stepping frequency of 100 steps per minute.  The hand count column indicates that over the two minutes the participants mean step frequency was correct for the designated frequency, precisely where it was meant to be for each two minute period.  According to t test analysis there was no significant difference between the RH Pedometer and the hand count at any step frequency. 

 

Table 3.  Total steps (means) for two minutes measured at 4 different stepping frequencies secured on three occasions

Stepping frequency            Visit

N

RHPed.

Std. Dev

Hand count

Std. Dev

Step/min = 100

1

16

192.9

12.1

198.6

2.6

2

15

195.7

8.4

199.2

1.9

3

16

195.8

8.3

198.9

1.8

Step/min = 110

1

17

219.4

7.9

219.9

2.3

2

18

219.3

6.6

219.4

2.6

3

17

220.9

2.9

220.1

2.8

Step/min = 120

1

18

240.6

4.5

240.1

2.9

2

18

241.1

2.1

240.5

2.8

3

18

242.4

2.9

241.5

3.1

Step/min = 130

1

17

257.2

2.2

259.2

2.7

2

16

257.6

2.2

259.6

2.2

3

16

258.0

2.5

259.9

2.4

Time in Moderate to Vigorous Physical Activity

The ability of the pedometers to record time (seconds) spent at or above a step frequency (i.e. > 110spm) threshold is displayed below.  The results show the average duration that was detected as MVPA by the pedometer when the participant was walking at the different stepping frequencies.  Table 4 provides the mean duration for MVPA which the pedometers detected above the threshold.  The smaller number of contributors to the mean and the size of the large standard deviation associated with the slower step frequency of 100spm are noticeable. 

Table 4.  MVPA accumulation (seconds) descriptives

Step Freq.

N

Minimum

Maximum

Mean

Std. Deviation

100spm

34

74

123

112.4

13.5

110spm

47

80

124

117.5

9.7

120spm

49

110

123

120.2

3.6

130spm

44

120

122

120.8

.7

Figure 1 displays the percentage achievement of MVPA of the possible 120 seconds in which participants engaged when they stepped at or above 110spm.  The figure displays an almost 100% accordance for step frequencies of 110, 120 and 130spm. The data indicate that when stepping at 100spm 87% of the possible time was detected as in MVPA.  For the other 3 step frequencies the average percentage of the possible 120 seconds was within 2.5 % or lower of the possible 100%. 

img01

Figure 1.  Moderate to vigorous accumulation (secs) at the four different step frequencies

Pedometer v Accelerometer

An accelerometer was employed to verify the cadence of the participants to ascertain time spent at or above the defined threshold to determine whether the pedometer was accurately recording  time spent at or above the threshold, or whether the participants were not indeed walking at the metronome speed.

Figure 2. shows an example of one person’s instantaneous cadence as defined by the accelerometer, showing an average cadence of 119.8 and standard deviation of 9.3 steps/minute (7.7% coefficient of variation). This person was set to walk at a step frequency of 120spm.  It may be observed that while they average that frequency each individual instantaneous cadence was wildly variable with a fast step frequency followed immediately by a much slower step frequency.  

img02

Figure 2.  All individual step frequencies taken by one subject during the 120 seconds trial. 

 

Discussion

Key Findings

When walking to an audible cadence for two minutes, the Walk4Life MVPA pedometer, as a measure of steps taken, was found to be reliable and valid for step frequencies at or above 110 steps per minute.  This was consistent for both genders.  The treadmill speeds ranged from 77 – 110 metres per minute.  Stepping frequencies below 110spm resulted in some inability for the pedometers to detect all steps taken. Other studies have found this inability of pedometers to detect vertical perturbations at these slower speeds (Scruggs, Beveridge, Eisenman, Watson, Schultz, and Ransdell. 2003).  The slower step frequency of 100spm resulted in some adult females and males working at a MET level less than 3.0 MET’s. All other step frequencies were associated with MET levels greater than 3.0.  Some pedometer brands including the one investigated in this study, allow “aerobic minute” thresholds between 60 -100spm.  It must be considered that time accumulated at these lower thresholds may not fall into the moderate to vigorous category. 

When the threshold was set to 110spm it detected between 87% and 100% of the actual moderate to vigorous duration associated with the trials.  However as shown in Figure 2 there was a variability associated with the instantaneous step frequency for all participants.  Even though the participant in Figure 2 averaged 119.8spm in accordance with an audible metronome set at 120spm the actual step frequency range was from 104spm to 144spm.  This variability is common in heart rate measurement and has been observed in the Gait literature.

Step Variability

Decades of research into quantitative gait parameters have focused on the participant’s mean values of gait parameters such as step length, stride length, step time, step width ignoring within-subject stride-to-stride fluctuations. Recent attention has been given to variability in step/stride length and time as close examination of gait has revealed complex fluctuations in the gait pattern even under constant environmental conditions and it is believed this information may convey important information. There is insufficient data presented in the recent papers to compare with the current data collected in our study, but basic data analysis allows crude comparisons to be made which show that the step-to-step variability (measured as a standard deviation of co-efficient of variation) detected within this study is within the upper range of normal variability found in other similar studies. Hausdorff (2005) recently evaluated methods for measuring and models for analysing gait variability and established SD and CV to be effective measures of step length variability and accelerometers, gyroscopes, foot-switches and gait mats to be useful for this purpose. Healthy adults (n=64), median values of the co-efficient of variation were < 6% for step length (Gabell and Nayak, 1984). There were few differences found in temporal gait parameters between treadmill and overground walking except for increased step frequency (Lee and Hidler, 2008; Betker et al., 2008) indicating that the results of this study and further studies may be generalised to the greater population on overground walking.

Conclusion

The question of whether the Walk4Life MVPA pedometer itself can accurately measure number of steps or duration in moderate to vigorous physical activity needs further study within the laboratory and with an overground design.  How many steps consecutively above a threshold are required to activate the accumulation function of MVPA must be known as these data indicate that humans do not walk at a steady frequency, rather variability is the norm. Consequently, average steps per minute calculated for a minimum period (e.g. 10 seconds) may be the required in the algorithm utilised. 

The potential exists and has been lightly supported by this study for this technology to greatly assist Public Health researchers to finally get an objective measure of moderate to vigorous physical activity.  This possibility exists at a cost which may be sustained for large population studies.

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