Comparison of pedometer and accelerometer measures of physical activity during preschool time on 3- to 5-year-old children

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1 REGULAR ARTICLE Comparison of pedometer and accelerometer measures of physical activity during preschool time on 3- to 5-year-old children 2 Peter Pagels 1, Cecilia Boldemann 2, Anders Raustorp (anders.raustorp@lnu.se) 1,3 1.School of Sport Sciences, Linnaeus University, Kalmar, Sweden 2.Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden 3 3.Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden Keywords Accelerometer, Pedometer, Physical activity, Preschool children. Correspondence Anders Raustorp, Linnaeus University, School of Sport Sciences, SE Kalmar, Sweden. Tel: Fax: anders.raustorp@lnu.se Received 4 March 2010; revised 21 June 2010; accepted 22 July 2010 DOI: /j x A P A B BACKGROUND The rise in childhood obesity during the past decade has been dramatic. In 2010, worldwide 43 million children under age five are estimated be overweight (1). Decreased physical activity and increased sedentary behaviours are likely to be related to this trend (1,2). In addition to a higher risk of obesity and a range of noncommunicable diseases later in life, affected children experience adverse outcomes such as breathing difficulties, increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance and psychological effects (3 5). To clarify the effects of physical activity on overweight and obesity in preschool children and to identify the relationship between physical activity and other health parameters in children of that age, a valid and reliable measure to detect the frequency, intensity and duration of young children s physical activity is required. For the measurement of activity levels, both subjective (direct observation, self-report) and objective (heart rate monitoring and motion sensors) have been applied (6). Motion sensors (accelerometers and pedometers) are common in field research, as they are unobtrusive and unbiased Dispatch: Journal: APA CE: Ponjesuraj Journal Name Manuscript No. Author Received: No. of pages: 5 PE: Gayathri Acta Pædiatrica ISSN ABSTRACT Aims: To compare pedometer steps with accelerometer counts and to analyse minutes of engagement in light, moderate and vigorous physical activity in 3- to 5-year-old children during preschool time. Methods: Physical activity was recorded during preschool time for five consecutive days in 55 three- to five-year-old children. The children wore a Yamax SW200 pedometer and an Actigraph GTIM Monitor. Results: The average time spent at preschool was 7.22 h day with an average step of 7313 (±3042). Steps during preschool time increased with increasing age. The overall correlation between mean step counts and mean accelerometer counts (r = 0.67, p < 0.001), as well as time in light to vigorous activity (r = 0.76, p < 0.001), were moderately high. Step counts and moderate to vigorous physical activity minutes were poorly correlated in 3 years old (r = 0.19, p < 0.191) and moderately correlated (r = 0.50, p < 0.001) for children 4 to 5 years old. Conclusion: Correlation between the preschool children s pedometer-determined step counts and total engagement in physical activity during preschool time was moderately high. Children s step counts at preschool were low, and the time spent in moderate and vigorous physical activity at preschool was very short. store information, and are convenient to handle (7). Pedometers are cost-effective, valid and reliable, providing summary output of ambulatory activity throughout the day, which is useful for screening, intervention, guiding surveillance and evaluation (8,9). Pedometers do not yield information on intensity, other than steps per measured time period, so when providing standards for daily pedometerdetermined steps per day; it is preferable, if possible, to relate to a health criterion (i.e. body mass index (BMI)). The preliminary health-related criterion reference standard for children ages 6 12 recommends daily steps (girls) and daily steps (boys) for optimal chance of maintaining normal weight (10). Accelerometers are able to discriminate between intensities of physical activity and are crucial for our understanding activity patterns. Activity is measured in epoch lengths. An epoch is the amount of time (i.e. seconds) during which movement data (i.e. activity counts) are summed and stored for processing and analysis. Epochs ranging from 2 60 sec have been applied in children s research (11). Commonly, the accumulated activity counts of each epoch are classified into physical activity intensity categories (e.g. light, moderate, vigorous), applying validated threshold values (cut ª2010 The Author(s)/Journal Compilation ª2010 Foundation Acta Pædiatrica/Acta Pædiatrica 1

2 Comparison of pedometer and accelerometer measures 1 Pagels et al points) for the observed age group. Concurrent cut points for moderate and vigorous physical activity (MVPA), however, are problematic and complicate interpretation of data. One cut-off for all subjects in the 3- to 5- years age range has been applied,(12,13) but age-specific cutoffs identified in a recent study suggest that the use of age-specific count cut-offs for 3-, 4- and 5- year-olds are more adequate (14). Only few studies have compared physical activity levels measured by pedometers and accelerometers in preschool children during one whole day. Cardon and De Bourdeaudhuij (2007) (15) demonstrated a correlation of 0.73 between daily step counts and MVPA minutes in 76 fourand five-year-old children on a daily basis and concluded that daily step counts in preschool children give valid information on physical activity levels. In Sweden, >81% of the 1- to 6-year-old children attend preschool (2008) (16). Preschool children s physical activity level during preschool time is therefore of special interest. Only one study could be identified which used pedometers to evaluate physical activity levels in 197 one- to six-yearold preschool children specifically during preschool time. Boldemann et al. (17) used step counts per minute as outcome measure, and only pedometers were used. In terms of physical activity levels, the aims of this study were to compare pedometer steps with accelerometer counts and to analyse minutes of engagement in light, MVPA in 3- to 5-year-old children during preschool time. METHODS Participants Participants were recruited from four preschools in Southern Sweden and North Carolina State of America with different outdoor environment. Measurements were carried out March 30 April 3 (Raleigh) and May 4 8 (Malmö, Sweden). The parents of the 3-, 4- and 5-year-old children at the participating preschools were invited by an informational letter to sign up their children in the study. After omitting three participants with incomplete data, this study sample consisted of 55 children (28 boys) with mean age 4.5 years, range years. Permission for the study was obtained from the Internal Revision Board at North Carolina State University (NCSU), and the Stockholm Regional Ethics Committee, the involved local authorities (Malmö) and preschools and by parental written informed consent. Objectively measured physical activity The participants wore an elastic belt with an accelerometer and a pedometer side by side to compare step counts with activity minutes. The belt was attached upon arrival and removed before going home. Pedometry Daily step counts were measured with cable tie sealed 4 pedometers (Yamax SW-200 Tokyo, Japan), considered by researchers as the criterion pedometer (18). The pedometers were attached to the waistband and placed in line with the midpoint of the right knee. The participants were instructed to wear the sealed pedometers during the entire preschool time. The number of daily steps was measured during five consecutive days, as recommended to assure reliable results and avoid reactivity (19). Accelerometry The Actigraph GT1M accelerometer (Pensacola, FL, USA) is a uniaxial accelerometer registering volume and pattern of physical activity. The Actigraph has been calibrated in children against heart rate telemetry (20), indirect calometry (21), observational techniques (22) and energy expenditure measured by doubly labelled water (23). Epoch was set at 15 sec. Cut points according to Sirard et al. (2005) (14) were used to classify intensity, for 3-year olds for sedentary, for light, for moderate and >1231 for vigorous activity, for 4-year-olds for sedentary, for light, for moderate, and >1235 for vigorous activity and for 5-year-olds for sedentary, for light, for moderate and >1255 for vigorous activity. Statistical analysis Data were analysed using SPSS for Windows (17.0). Independent t-tests were applied to identify differences in mean 5 step counts and steps per minutes between sexes, and oneway ANOVA to compare mean step counts of different age groups. Linear regression analysis was generated to compare accelerometer counts and pedometer steps during preschool time and to compare intensity levels vs. steps during preschool time. The strength of the correlation was evaluated according to the following interpretation; as poor, as moderate, as moderately high and 0.85 and above as high. The alpha level was set at 0.05 for all analyses. RESULTS In average, the children spent 7.22 h day (+1.2) at preschool. The average daily step count during preschool time was 7313 (±3017), in girls 6202 (±2022) and in boys 8385 (±3442). Descriptive data of the participating preschool children are presented by gender, and data given as mean and standard deviation (SD) are reported in Table 1. Steps during preschool time increased by age, the average step count preschool time being 5124 (±1279) in 3-year-olds, 7287 (±2491) in 4-year-olds, and 9344 (±4414) in 5- yearolds. Steps minutes during preschool time were overall 16.1 (±6.8), with a significant difference (p < 0.004) between boys 18.5 (±7.6) and girls 13.8 (±5.0). Step count minute during preschool time increased by age, with an average step count minute of 12.3 (±3.0) in 3-year-olds, 15.8 (±6.0) in 4-year-olds and 20.9 (±8.8) in 5-year-olds. The difference between 3 and 5 years of age was significant (p = 0.014). The regression analysis resulted in a moderately high correlation between mean step counts and mean accelerometer counts with a r of 0.67, accounting for 45% of the variance (adjusted R 2 ) (standardized beta B = 0.67, p < 0.000) see 2 ª2010 The Author(s)/Journal Compilation ª2010 Foundation Acta Pædiatrica/Acta Pædiatrica

3 Pagels et al. Comparison of pedometer and accelerometer measures LOW RESOLUTION FIG Table 1 Descriptive data of the participating preschool children presented by gender. Data are given as mean and standard deviation (SD) Age (years) SD Height (cm) SD Weight (kg) SD Body mass index (kg m 2 ) SD Waist (cm) SD Boys (n = 28) Girls (n = 27) Figure 1 Relationship between daily mean steps (pedometer) and daily mean 9 counts (accelerometer) in preschool children. Figure 1. For boys and girls, linear regression analysis revealed a moderately high (r = 0.73, R 2 = 0.52, B = 0.73, p = 0.000) and a moderate correlation (r = 0.55, R 2 = 0.30, B = 0.55, p = 0.003). The corresponding figures for each age group revealed in the 3- years old a moderate correlation (r = 0.37, R 2 = 0.13., B = 0.37, p = 0.127) in 4- years old a moderate (r = 0.52, R 2 = 0.27, B = 0 52, p = 0.002) and in 5- years old a moderately high correlation (r = 0.84, R 2 = 0.67, B = 0.84, p = 0.001). Linear regression analysis between step counts and minutes of light to vigourous physical activity resulted in a moderately high correlation (r = 0.76, R 2 = 0.52, B = 0.76, p = 0.001). Analysis between step counts and minutes spent in moderate to vigorous physical activity resulted in 3- years old in a nonsignificant poor correlation (r = 0.19, R 2 = 0.04, B = 0.19, p = 0.191) and for combined 4- to 5- years old a moderate correlation (r = 0.50, R 2 = 0.23, B = 0.50, p = 0.001). The percentage spent in MVPA, as well as sedentary time, had a tendency to decrease, whereas time of light to moderate intensity had a tendency to increase as age increased. The average time spent in light to vigorous PA (i.e not being 6 categorized as sedentary) was 50 (±17) min during preschool time. MVPA had a tendency to decrease with increasing age. The proportion of MVPA was 4% in the 3- year olds and 3.3% in 4- and 5- years old. Accelerometer counts, step counts and light-, moderate- and vigorous physical activity of the participating preschool children presented by gender and age with data given as mean and SD are reported in Table 2. DISCUSSION Moderately high significant correlations between mean step counts and mean accelerometer counts were observed in total and in boys. In girls, a moderately correlation was seen. To our knowledge, this is the first study reporting the correlation between pedometer-determined step counts and accelerometer-determined counts during preschool time. To be able to compare a previous reported study on comparison of pedometer steps and accelerometer-determined minutes in MVPA, we tested the group of 4- to 5- year-old children separately. Mean step counts and MVPA minutes correlated poorly and positively in 3-year-olds and Table 2 Accelerometer counts, step counts and light-, moderate- and vigorous physical activity of the participating preschool children presented by gender and age. Data are given as mean and standard deviation (SD) Variable, 5 days mean values Boys (n = 28) Girls (n = 27) 3-Years (n = 10) 4-Years (n = 32) 5-Years (n = 13) Accelerometer data (counts)sd * Pedometer steps (counts) SD 8385* 3442 Moderate to vigorous PA (minutes) SD Light to vigorous PA (minutes) SD Sedentary (minutes) SD Steps per minutes, SD 18.4* 7.6 * Significant differences between boys and girls, p < * * * ª2010 The Author(s)/Journal Compilation ª2010 Foundation Acta Pædiatrica/Acta Pædiatrica 3

4 Comparison of pedometer and accelerometer measures Pagels et al correlated moderately in the 4- to 5- year (r = 0.50) -old children. This is in contrast to Cardon and DeBourdeaudhuij (2007) (15) who observed a moderately high correlation (r = 0.73) between daily step counts and minutes of engagement in MVPA, using identical instruments in 4- and 5-year-old children. This may be explained by wholeday measurement in which more structured periods and periods of more intensive activities are combined, hence the weaker correlation. Interestingly, the exclusion of 3-yearolds from analysis did increase the correlation in our study. Possibly, the impact of 3- year-old children s step sometimes is not enough to detect a pedometer step, however, is enough to detect an accelerometer count as sensitivity thresholds between the two devices differ, as 0.35 vs g force is reported to be required by pedometer and accelerometers, respectively (24). On the contrary, the correlation of 5- yearold children s steps vs. accelerometer counts (r = 0.84) is almost in line with these reported for older children and adults (19). Steps minutes during preschool time differed significantly between boys and girls. This corresponds well to the study by Boldemann et al. (2006) (17), in which significantly higher step count minute was observed in boys than in girls, averages 20.9 and 18.0, respectively. We found a significant increase in both intensity and step minutes with increasing age. This may partly be explained by decreasing sedentary minutes in 5-year-olds. However, MVPA had a tendency to decrease with increasing age. Furthermore, current results are supported by a recent published review article, which shows that preschool children participate very little in MVPA and exhibit high levels of sedentary behaviour (25). Steps during preschool time were observed to increase with increasing age. These steps were taken during an average of 7 h of preschool time. The total active time during a day was reported to be 11 h, i.e. at an average additional four active hours. Observations in a study by Tudor-Locke et al. (2004) (26) comprising a group of 6- to 12-year-old children state preliminary step per day recommendations ( for girls and for boys). Provided that these recommendations would also be valid for 5-year-old children, a great portion of the activity in terms of recommended step counts per day have to be accomplished during these few remaining hours. There are several limitations in this study. The convenience sample makes it difficult to generalize the results to a national perspective. Secondly, a small study population is vulnerable to division into age groups. Thirdly, the lack of whole-day data complicates comparison with other studies. The strength is the controlled research setting within preschools. The use of both accelerometers and pedometers may also be considered as a strength, as pedometers enable communication of the results in terms of steps per minute or steps during preschool time to the professionals who work with preschoolers activities and in preschooler s environment. The use of accelerometers will help identify the fractions of sedentary behaviour and MVPA. Children s physical activity levels vary depending on season (27). Therefore, measurements were performed in March-April in North Carolina and the beginning of May in Sweden, which is springtime at both sites. CONCLUSION Correlation was moderately high between pedometer-determined step counts and preschool children s total engagement in physical activity during preschool time. Children s step counts at preschool were low. The time spent in MVPA at preschool was very short. Future research is warranted to explore accumulated indoor vs. outdoor physical activity during preschool time and to identify indoor and outdoor sites, which promote physical activity. Further, studying the contribution of preschool activity over a whole day of children s physical activity may be a subject of study. References 1. de Onis M, Borghi E, Blössner M. Global prevalence and trends of overweight and obesity among preschool children (In submission) World Health Organization Action Plan for the Global Strategy for the Prevention and Control of Non-communicable Diseases. Geneva: World Health Organization, Caprio S, Daniels SR, Drewnowski A, Kaufman FR, Palinkas LA, Rosenbloom AL, et al. Influence of race, ethnicity, and culture on childhood obesity: implications for prevention and treatment: a consensus statement of Shaping America s Health and the Obesity Society. Diabetes Care 2008; 31: Choudhary AK, Donnelly LF, Racadio JM, Strife JL. Diseases associated with childhood obesity. Am J Roentgenol 2007; 188: Daniels SR, et al. Overweight in children and adolescents. Pathophysiology, consequences, prevention and treatment. Circulation 2005; 111: Welk GJ. Physical Activity Assessments for Health-Related Research. Champaign, IL: Human Kinetics, Freedson PS, Miller K. Objective monitoring of physical activity using motion sensors and heart rate. Res Q Exerc Sport 2000; 71: Tudor-Locke C, Bassett DR Jr. How many steps day are enough? Preliminary pedometer indices for public health. Sports Med 2004; 34: Welk GJ, Differding JA, Thompson RW, Blair SN, Dziura J, Hart P. The utility of the Digiwalker step counter to assess daily physical activity patterns. Med Sci Sports Exerc 2000; 32: S Tudor-Locke C, Pangrazi RP, Corbin CB, et al. BMI-referenced standards for recommended pedometer determined steps day in children. Prev Med 2004; 38: McClain JJ, Abraham TL, Brusseau TA Jr, Tudor-Locke C. Epoch length and accelerometry outputs in children: comparison to direct observation. Med Sci Sports Exerc 2008; 40: Finn K, Johannsen N, Specker B. Factors associated with physical activity in preschool children. J Pediatr 2002; 140: Reilly JJ, Coyle J, Kelly L, Burke G, Grant S, Paton JY. An objective method for measurement of sedentary behavior in 3- to 4-year olds. Obes Res 2003; 11: ª2010 The Author(s)/Journal Compilation ª2010 Foundation Acta Pædiatrica/Acta Pædiatrica

5 Pagels et al. Comparison of pedometer and accelerometer measures Sirard JR, Trost SG, Pfeiffer KA, Dowda M, Pate RR. Calibration and evaluation of an objective measure of physical activity in preschool children. J Phys Act Health 2005; 3: Cardon G, De Bourdeaudhuij I. Comparison of pedometer and accelerometer measures of physical activity in preschool children. Pediatr Exerc Sci 2007; 19: National Agency for Education, Follow-up Systems, Stockholm, Sweden, 2008 Available at: (accessed on February 22, 2010). 17. Boldemann C, Dal H, Wester U, Blennow M, Mårtensson F, Raustorp A, et al. The impact of outdoor environment upon preschool children s physical activity and sun exposure. Prev Med 2006; 42: Tudor-Locke C, Sisson B, Lee SM, Craig CL, Plotnikoff RC, Bauman A. Evaluation of quality of commercial pedometers. Can J Public Health 2006; 5: Tudor-Locke C, McClain JJ, Abraham TL, Sisson SB, Washington TL. Pedometry methods for assessing free-living youth. Res Q Exerc Sport 2009; 80: Janz KF. Validation of the CSA accelerometer for assessing children s physical activity. Med Sci Sports Exerc 1994; 26: Melanson EL, Freedson PS. Validity of the Computer Science and Applications, Inc. (CSA) activity monitor. Med Sci Sports Exerc 1995; 27: Fairweather SC, Reilly JJ, Grant S, Whittaker A, Paton JY. Using the Computer Scienceand Applications (CSA) activity monitor in preschool children. Pediatr Exerc Sci 1999; 11: Ekelund U, Sjostrom M, Yngve A, et al. Physical activity assessed by activity monitorand doubly labeled water in children. Med Sci Sports Exerc 2001; 33: Tudor-Locke C, Ainsworth BE, Thompson RW, Matthews CE. Comparison of pedometer and accelerometer measures of free-living physical activity. Med Sci Sports Exerc 2002; 34: Oliver M, Schofield G, Kolt G. Physical activity in preschoolers: understanding prevalence and measurement issues. Sports Med 2007; 37: Tudor-Locke C, Pangrazi RP, Corbin CB, et al. BMI-referenced standards for recommended pedometer determined steps day in children. Prev Med 2004; 36: Chan CB, Ryan DA, Tudor Locke C. Relationship between objective measures of physical activity and weather: a longitudinal study. Int J Behav Nutr Phys Act 2006; 7: 21. ª2010 The Author(s)/Journal Compilation ª2010 Foundation Acta Pædiatrica/Acta Pædiatrica 5

6 Author Query Form Journal: APA Article: 1962 Dear Author, During the copy-editing of your paper, the following queries arose. Please respond to these by marking up your proofs with the necessary changes/additions. Please write your answers on the query sheet if there is insufficient space on the page proofs. Please write clearly and follow the conventions shown on the attached corrections sheet. If returning the proof by fax do not write too close to the paper s edge. Please remember that illegible mark-ups may delay publication. Many thanks for your assistance. Query reference Query Remarks Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 AUTHOR: A running head short title was not supplied; please check if this one is suitable and, if not, please supply a short title of up to 40 characters that can be used instead. AUTHOR: Please check and approve the edit made in the title. AUTHOR: Please check if authors names (surnames are in green colour) and affiliations are correctly presented. AUTHOR: Please give manufacturer information for Yamax SW-200: company name. AUTHOR: Please give manufacturer information for SPSS: company name, town, state (if USA), and country. AUTHOR: Please define PA here. AUTHOR: Please provide the name of the publisher, city location of publisher for reference [1]. AUTHOR: If there are fewer than 7 authors for Reference list, please supply all of their names. If there are 7 or more authors, please supply the first 6 author names then et al. AUTHOR: Figure 1 has been saved at a low resolution of 180 dpi. Please resupply at 600 dpi. Check required artwork specifications at

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