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BASIC SCIENCES: Epidemiology

Pedometer-Determined Physical Activity and Body Composition in New Zealand Children


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Medicine & Science in Sports & Exercise: August 2006 - Volume 38 - Issue 8 - p 1402-1409
doi: 10.1249/01.mss.0000227535.36046.97
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The escalation of obesity into a worldwide epidemic raises the prospect of serious health and economic consequences for many countries. Although the prevalence of obesity continues to increase in people of all ages (37), childhood obesity undoubtedly presents the greatest long-term concerns from a population health perspective. In the United States, obesity in children 6-11 yr of age (defined as a body mass index [BMI] at or above the 95th percentile of national growth charts) rose from 6.5% in 1976-1980, to 11.3% in 1988-1994, to 15.3% in 1999-2000 (19). These substantial increases in obesity are not exclusive to young Americans; similar patterns have been observed in other countries, including Australia (2), France (35), and the United Kingdom (3). Using international age- and sex-specific BMI cutoff points (4), a national survey conducted in 2002 found that 9.8% of New Zealand children were classified as obese (17). Furthermore, a recent longitudinal study found that the risk of obesity in 2000 was 3.8 times greater than the risk in 1989 (33), suggesting that the prevalence of childhood obesity in New Zealand is following overseas trends.

Such findings have triggered an upsurge in the promotion of physical activity among young people as a long-term solution to the obesity epidemic. This has coincided with a widespread increase in the availability of step-counting pedometers for monitoring daily activity levels. For researchers, pedometers provide an objective, cost-effective assessment of physical activity that can be easily compared across different time periods, age groups, and locations (27). Pedometers are especially useful for studies of pediatric populations, where the inability of younger children to accurately recall their activity behavior can reduce the efficacy of questionnaires and interviews (23). Although pedometers are unable to detect physical activity intensity, duration, or frequency, there are clear benefits to recording a measurement unit that has direct applications to health promotion. Increasing the number of steps per day encourages the accumulation of physical activity in people of all ages and physical abilities and is less complicated than alternative recommendations based on physical activity intensity and duration. Pedometer-based interventions have already proved effective for increasing physical activity in adults (5,13) and adolescent girls (26).

Numerous descriptive studies have implemented pedometers to assess weekday physical activity in children (16,21,34), yet comparatively few have obtained separate data representing weekend days. The number of steps taken by children on the weekends is of particular interest, given the current evidence that young people are less active when outside the school environment (10,11). To discern step counts for individual days, conventional pedometers (e.g., the Yamax Digiwalker series) require researchers to visit participants at school each morning to record data from the previous day. Naturally, this procedure becomes more difficult during the weekend when children are at home. It is possible to obtain weekend data by relying on self-reported step counts; however, the prevalence of age-related recall bias or deliberate misrepresentation appears high in young people (29). Alternatively, the multiday memory (MDM) pedometer features an internal clock that automatically categorizes data according to the day of the week, enabling researchers to collect both weekday and weekend data while restricting participant contact to before and after the test period.

Although a daily step count target appears to be a promising approach for increasing population physical activity and thus lowering the risk of obesity, limited information describes the association between steps per day and body composition in children. In the only large-scale study of activity and body size in young people, Vincent et al. (34) found few significant relationships between weekday steps and BMI. The latter result is surprising given the growing body of longitudinal evidence supporting the role of physical activity in the prevention of childhood obesity (9,18). One possibility is that pedometers do not provide a suitably accurate estimate of physical activity to enable the detection of a significant association with body size. However, this is unlikely because previous research has established pedometers as a valid measure of activity in children (27). An alternative explanation is that BMI, as a weight-based index, is a simplistic indicator of adiposity. It is noteworthy that physical activity lowers the risk of obesity-related complications by reducing the accretion of body fat rather than decreasing body weight. The natural increases in height and weight that occur during growth may also complicate the relationship between BMI and physical activity. Indeed, several studies have observed stronger associations between activity and body fat than between activity and BMI (1,18). Even waist circumference (WC), a proxy measure of central fat accumulation, appears more closely related to activity levels in young people than BMI (12). We suggest that obtaining more direct measures of body fatness will increase the probability of detecting significant associations between pedometer steps and obesity in children.

It is clear that the association between steps per day and body composition in pediatric populations needs further clarification. Thus, the primary purpose of this study was to investigate pedometer steps in relation to BMI, WC, and percentage body fat (%BF) in a large sample of New Zealand children. A secondary objective was to compare differences in activity between weekdays and weekends, and among European, Polynesian, and Asian children.



A total of 2000 children (1000 boys, 1000 girls) aged 5-12 yr were randomly selected from 27 primary (elementary) schools in Auckland, New Zealand. Participating schools were purposively sampled to replicate the overall geographic and socioeconomic distribution of primary schools in the Auckland region. Consent was obtained for 1251 of the 2000 children selected (68.3%), and 1229 children (603 boys, 626 girls) eventually took part in the study. Of this initial group, 29 participants (2.4%) either lost or damaged their pedometer during testing. A further 85 (6.9%) provided incomplete data and were excluded from analysis, resulting in a final sample size of 1115 (536 boys, 579 girls). The ethnic composition of this sample was 549 European children (49.2%), 334 Polynesian children (30.0%), 184 Asian children (16.5%), and 48 children from other ethnic groups (4.3%). The Polynesian ethnic group was composed of Pacific Island (56.0%) and Maori (44.0%) children, and the Asian ethnic group included Indian (38.0%), Chinese (22.3%), Korean (13.0%), Filipino (9.8%), Sri Lankan (4.3%), and other Asian (12.6%) children. Socioeconomic status (SES) was estimated using the Ministry of Education decile classification system for New Zealand primary schools. For the purposes of this study, participants from schools with a decile rating between 1 and 3 were categorized into the "low" SES group, whereas those from schools rated 4-7 or 8-10 were considered "middle" or "high," respectively. Although this proxy measure of SES may not accurately classify all individuals, it negated the potential parent or caregiver burden associated with a socioeconomic questionnaire. Ethical approval for this study was obtained from the Auckland University of Technology ethics committee. Written informed consent was provided by each participant and his or her legal guardian.

Physical activity.

The New Lifestyles NL-2000 (Lee's Summit, MO) MDM pedometer was used to monitor daily physical activity. Previous research has shown that the NL-2000 offers a degree of accuracy comparable with the widely used Yamax Digiwalker series while providing the added benefits of a MDM function (25). Each NL-2000 pedometer was checked for defects before use in the study by observing the recorded step count after walking 100 paces. Instrumental error did not exceed 3% in any of the pedometers. Testing took place during the spring months between August and December. Each participant was given a short explanation about the study before receiving a demonstration about how to attach a presealed pedometer to the waistline. Participants were then asked to wear the pedometer all day for seven consecutive days (except when sleeping or swimming). On the seventh day of monitoring, researchers visited the participants to collect pedometers and record the number of steps taken on each of the testing days. Pedometers were not available to the participants on the morning of the first testing day or the evening of the last testing day, resulting in a maximum of 5 d of data (three weekdays and two weekend days). Previous research has suggested that 4-5 d of monitoring is sufficient to obtain a reliable (ICC >0.80) estimate of physical activity in children (30).

To assess participant compliance outside of the school environment, parents or caregivers completed a questionnaire the night before the pedometers were collected. This alerted researchers to times during the monitoring period that parents or caregivers were aware their children had removed the pedometer. Although this method is less effective for detecting noncompliance when parents or caregivers are not present, the low reliability of self-report techniques in children (23) precluded their use in this study. Noncompliance during school hours was considered negligible because of active teacher assistance. At present, a standard noncompliance time period above which pedometer data are discarded has yet to be established. Data treatment procedures used in previous studies have ranged from the inclusion of all daily pedometer data regardless of participant compliance (29) to the exclusion of data from participants who removed their pedometer for more than 1 h on any given day (36). Although the latter criterion results in a greater number of exclusions, it likely provides the most accurate estimates of daily steps. Thus, children in the present study who removed their pedometer for more than 1 h on any given day had the steps accumulated on that day omitted from analysis. Participants were excluded from the study if more than one weekday and one weekend were lost because of incomplete data.

Nevertheless, the possibility that noncompliant individuals were overlooked because of inaccurate parent or caregiver questionnaires cannot be ruled out. Of particular concern is the potential for abnormally low or high step counts to be retained in the dataset. To date, limited information exists concerning the treatment of extreme values in pedometry research. The only existing standards for children were developed by Rowe et al. (20), using a combination of percentile analysis and previous experience. It was proposed that daily step counts below 1,000 or above 30,000 were unlikely to be valid and should be regarded as outliers. Five participants (0.4%) from the present study were excluded by these criteria.

Body composition.

The standing height of each participant was measured to the nearest millimeter with a portable stadiometer (Design No. 1013522, Surgical and Medical Products, Seven Hills, Australia), and weight was measured to the nearest 0.1 kg on a digital scale (Model Seca 770, Seca, Hamburg, Germany). BMI was then calculated as weight (kg) divided by squared height (m2). During data analysis, participants were classified as normal weight, overweight, or obese using international age- and sex-specific BMI cutoff points (4). In addition, WC measurements were made at the highest point of the iliac crest at minimal respiration. Children with a central pattern of fat distribution were identified using the WC cutoffs developed for New Zealand children by Taylor et al. (28).

Body fat measurements were obtained using hand-to-foot bioelectrical impedance analysis (BIA). Resistance (R) was measured at 50 kHz using a bioimpedance analyzer (Model BIM4, Impedimed, Capalaba, Australia) with a tetrapolar arrangement of self-adhesive electrodes (Red Dot 2330, 3M Healthcare, St. Paul, MN). After swabbing the skin on the right hand and foot with alcohol, source electrodes were placed on the dorsal surface of the foot over the distal portion of the second metatarsal and, on the hand, on the distal portion of the second metacarpal. Sensing electrodes were placed at the anterior ankle between the tibial and the fibular malleoli, and at the posterior wrist between the styloid processes of the radius and ulna. Testing was initiated after the participants emptied their bladder and had been lying supine with their arms and legs abducted for at least 5 min. Testing was completed when repeated measurements of R were within 1 Ω of each other. Fat-free mass (FFM) was then calculated from R, height, and weight using a prediction equation previously validated with deuterium dilution (R2 = 0.96, SEE = 2.44 kg) in New Zealand children (22). To ensure consistency between samples, preparation procedures in the present study were identical to those implemented by Rush et al. (22). Fat mass (FM) was derived as the difference between FFM and body weight. Percentage body fat was calculated as 100 × FM/weight. Children above the 90th percentile of %BF for each age- and sex-specific group in the sample were classified as having excessive body fatness. Unlike BMI, no generally accepted definitions exist of overweight or obesity in children based on %BF. Given that approximately 10% of New Zealand children are classified as obese using international BMI thresholds (17), the 90th percentile of %BF was chosen as the cutoff point for identifying excessively high levels of body fatness in this sample.

Statistical analyses.

Data were analyzed using SPSS version 12.0.1 for Windows (SPSS Inc., Chicago, IL). Differences in participant characteristics (age, height, weight, BMI, WC, and %BF) between sexes and among ethnic groups were assessed by two-way ANOVA, and significant associations were examined by pairwise comparisons using t-tests. One-way ANOVA and Bonferroni post hoc tests were used to determine where significant differences in step counts existed among ethnic, age, socioeconomic, BMI, WC, and %BF groups. Associations among weekday and weekend step counts, sex, ethnicity, and %BF category were assessed using factorial repeated-measures ANCOVA (sex by ethnicity by %BF by day) with age and SES as covariates. A P value < 0.05 was used to indicate statistical significance.


The physical characteristics of each ethnic group in this study are presented in Table 1. Although no significant effects were found of sex on age, height, weight, BMI, or WC, significant differences in %BF were detected between boys and girls within each ethnic group (excluding other ethnicities). Furthermore, Polynesian children were heavier than European and Asian children and had a greater BMI and WC. Ethnic differences in %BF were also observed, with Polynesian and Asian boys carrying significantly more body fat than their European counterparts. Similar %BF trends were found in girls, although the difference between the European and Asian groups was not significant (P = 0.108).

Participant characteristics (mean ± SD).

Table 2 shows the mean weekday and weekend step counts for the study sample grouped according to sex, ethnicity, age, socioeconomic status, BMI, WC, and %BF. Mean weekday steps were consistently higher and had smaller standard deviations than mean weekend steps across all subgroups. Preliminary analysis revealed significant differences in weekday steps between boys and girls and among the three major ethnic groupings, with Polynesian children the most active and Asian children the least active during weekdays. Weekend activity showed similar patterns between sexes and among ethnicities, although European children averaged the highest weekend step count. Weekend activity decreased with age and increased with socioeconomic status, trends that were not observed for weekday activity.

Pedometer-determined physical activity (steps per day).

The relationships between mean step counts and each of the three body composition variables included in this study were analyzed separately. First, international BMI cutoff points for childhood overweight and obesity (4) were applied to the sample. Overall, 73.5% of participants were classified as "normal" weight, with 17.3% overweight and a further 9.2% obese. Analysis of variance showed a significant difference in weekend, but not weekday (P = 0.291), step counts among the three BMI categories (Table 2). Participants were then grouped according to the WC standards proposed by Taylor et al. (28). Compared with BMI, differences in activity between children with normal fat distribution (78.4%) and those with central fat distribution (21.6%) were larger for weekdays and similar for weekends. Finally, the greatest differences in steps per day were found when participants were categorized into either normal (< 90th percentile) or high (> 90th percentile) %BF groups. Both weekday and weekend activity was significantly lower for children with high %BF (9.5%) when compared with those with normal %BF levels (90.5%).

To investigate the interaction among the key factors associated with activity in this sample, sex (male and female), ethnicity (European, Polynesian, and Asian), %BF (normal %BF and high %BF), and day (weekday and weekend) were entered into a 2 × 3 × 2 × 2 factorial repeated-measures ANCOVA (sex by ethnicity by %BF by day) with age and SES as covariates (Table 3). Mean step counts differed significantly between weekdays and weekends, with significant interactions between day and age, day and socioeconomic status, and day and sex. No significant interactions existed between day and ethnicity, day and %BF, or among any of the higher-level combinations. This indicates that the significant decrease in activity observed on weekend days is affected by age, socioeconomic status, and sex, but not by ethnicity or %BF category. Analysis of the between-subject variance revealed significant associations between overall mean step count and both age and SES. Significant differences between boys and girls, among ethnicities, and between %BF groups were also detected. The latter finding, in addition to the nonsignificance of the interaction between day and %BF, shows that a high level of %BF (> 90th percentile) is associated with a significantly lower number of daily steps on both weekdays and weekends. Furthermore, the nonsignificant interactions among sex, ethnicity, and %BF indicate that the negative association between %BF status and daily steps is similar for boys and girls from all ethnic groups.

Factorial repeated-measures ANCOVA (sex by ethnicity by %BF by day) corrected for age and SES.

Figure 1 shows the differences in weekday and weekend step counts between %BF groups for all ethnicities. On average, boys with normal %BF levels accumulated 1554 more steps each weekday and 1893 more steps each weekend than boys with high %BF. Girls with normal %BF levels achieved 1480 more steps each weekday but only 844 more steps each weekend when compared with those in the high %BF group. The Cohen effect size statistics associated with these differences were 0.40 for boys and 0.47 for girls on weekdays, and 0.40 for boys and 0.19 for girls on weekends. This implies that %BF status had a moderate association with mean weekday and weekend steps in boys, a slightly larger association with mean weekday steps in girls, and a trivial association with mean weekend steps in girls.

Pedometer-determined physical activity during weekdays and weekends grouped by sex and %BF. * Significant (P < 0.05) level. ** Significant (P < 0.005) level.


The results presented in this study represent the only step count data available for young New Zealanders and have enabled us to observe the physical activity patterns of New Zealand children from an international perspective for the first time. Previous research from a large three-country sample found that Swedish children were the most active on weekdays (15,673-18,346 steps per day for boys, and 12,041-14,825 steps per day for girls), followed by Australian children (13,864-15,023 and 11,221-12,322 steps per day), and then American children (12,554-13,872 and 10,661-11,383 steps per day) (34). Comparing these data with findings from the present study suggests that New Zealand children are relatively active, with boys averaging 16,133 steps and girls averaging 14,124 steps each weekday. It should be noted, however, that such comparisons of physical activity levels do not necessarily reflect the overall variation between countries because neither dataset is representative. The potential measurement error between different brands of pedometer may be another confounding factor (15).

The mean step counts recorded on weekends were significantly lower than on weekdays in our sample (boys, 12,702; girls, 11,158), with the extent of the decrease dependent on participant age, sex, and socioeconomic status. This may be a result of greater opportunities to participate in active play, sport, or physical education programs when at school, and suggests that the promotion of activity during out-of-school hours is a priority. However, previous comparisons of weekday and weekend activity using other measures of physical activity in children have been equivocal. Trost et al. (30) found that children accumulated more accelerometer counts on weekends compared with weekdays. In contrast, Gavarry et al. (10) used heart rate monitoring to show a significant decrease in children's activity during free days. The latter authors proposed that social and cultural factors may be responsible for the discrepancies among studies. An understanding of the types of activity occurring at school and at home may help explain such differences. To our knowledge, only one other study used pedometers to investigate weekend activity in children (20). Although the mean weekday step count (9504) was slightly greater than the mean weekend step count (9005), data were collected by the participants using various self-report techniques that have yet to be validated. Consequently, it is difficult to establish whether the difference in weekday and weekend steps demonstrated in the present study is distinctive to New Zealand children.

Significant differences in activity were also observed between sexes, with boys 14.2 and 13.8% more active than girls on weekdays and weekends, respectively. This was not surprising because sex is the most frequent correlate of physical activity identified in previous research (24). Our step count data also showed a negative association with age on weekends but not on weekdays. Although convincing evidence indicates an age-related decline in physical activity during adolescence, data representing preadolescent children are less consistent (24). Trost et al. (31) reported a significant decrease in accelerometer counts during both childhood and adolescence. Conversely, Vincent et al. (34) found little effect of age on weekday step counts in their international cohort of children 6-12 yr of age. This was supported by recent findings suggesting that a significant decline in weekday steps occurs during the transition from elementary school to high school (14). Combining the latter findings with those from the present study, it seems likely that the number of steps accumulated by preadolescent children on weekdays is relatively constant. The divergence from previous accelerometry data may be a result of differences in methodology. For example, an age-related decline in nonambulatory activity (e.g., cycling, swimming, or other upper-body movement) would be detected by accelerometry but not by pedometry. In any case, our results suggest that age-related trends in physical activity behavior may be accentuated in out-of-school environments. Similarly, grouping the sample by socioeconomic status revealed significant differences in weekend steps only. This is of interest because most previous research has found little evidence of an interaction between physical activity and socioeconomic indicators in children (24). A possible explanation is that New Zealand schools are required to maintain a reasonable level of physical activity regardless of socioeconomic rating, whereas children from more privileged backgrounds may be given greater opportunity to be active during weekends. Thus, interventions that focus on promoting out-of-school activity in families from lower socioeconomic regions may be beneficial.

Although the mean weekday step counts in the present study appear higher than current international estimates (34), the prevalence of overweight and obesity in the Australian and Swedish children (15.1 and 16.7%, respectively) was considerably lower than in our sample (26.5%). This apparent paradox may be explained by the relatively weak correlations between BMI and steps per day. Our results showed trends similar to those reported by Vincent et al. (34), with no significant differences in weekday step counts among the three BMI categories. This may be partly attributable to the limitations of BMI as a tool for measuring childhood obesity. Previous research has raised the possibility of interindividual variance in %BF at a given BMI among children from different ethnic backgrounds (8). Consequently, the use of a universal BMI scale for classifying overweight and obesity may not be appropriate for children who differ from the typical European phenotype. Polynesian children, for instance, tend to have more FFM and less FM at a given BMI when compared with European children (22). In contrast, Asian children often show less FFM and more FM than their European counterparts (8). Although the degree of potential misclassification for each ethnic group is uncertain, it is likely that the trivial associations between mean step count and BMI status observed in this study reflect the shortcomings of BMI as a predictor of childhood obesity.

A key objective of this study was to determine whether the implementation of body composition measures other than BMI would enable the detection of an association between steps per day and childhood obesity. It is well established that central adiposity increases the risk of several negative health outcomes in childhood (7). By grouping the sample according to the WC cutoffs proposed by Taylor et al. (28), we were able to compare step counts in children with normal and central patterns of fat distribution. Results showed that children with central adiposity averaged significantly fewer steps on weekdays and weekends than those with normal fat distribution. This is consistent with recent research suggesting that WC has stronger associations with physical activity in young people than BMI (12). As with BMI, however, it remains possible that ethnic variation in body size may contribute to the potential misclassification of Polynesian and Asian children. The development of ethnic-specific cutoffs may address this issue.

Percentage body fat provides a more appropriate gauge of obesity than either BMI or WC. Criterion measures of body fat (e.g., dual-energy x-ray absorptiometry, deuterium dilution, and underwater weighing) are costly and impractical for large-scale research. However, these reference standards can be used to calculate accurate (R2 > 0.95) BIA prediction equations for describing %BF in children. BIA is an ideal technique for pediatric populations because of its portability and short operating time (5-10 min). It is also less invasive and has greater interrater reliability than skinfold testing, a common measure of body fat used in field studies. The main limitation of BIA is that the study sample must be comparable with the reference population from which the prediction equation was derived. Using a BIA equation cross-validated with deuterium dilution in New Zealand children, we found significant associations between the numbers of steps children accumulated each day and their level of body fatness. Boys and girls with excessive body fat averaged 1554 and 1893 fewer steps, respectively, each weekday than children with normal body fat levels. Although the differences were less pronounced on the weekends (1480 and 844 for boys and girls, respectively), the significant association between %BF status and activity was similar across sexes and ethnic groups. This provides new evidence supporting the implementation of population-wide initiatives for increasing daily steps in children. Nevertheless, the cross-sectional design of this study precludes statements of cause and effect. A logical next step is to obtain longitudinal data monitoring trends in steps per day and body fatness during development. This would enable conclusions to be made regarding the causal nature of the relation between steps and body fat in children. The effect of puberty on the association between daily step counts and body fatness also requires investigation. The sharp decline reported previously (14) in steps per day during the transition from childhood to adolescence coincides with distinct changes in body composition. For example, at an equivalent BMI, adolescents who are sexually mature tend to have a lower %BF than those who are less developed (6). Resolving the relationships between pedometer-determined activity and population measures of body composition at various stages of maturation is an important topic for future research.

Given the findings from the present study, we suggest that daily step count targets based on %BF are more relevant than either BMI- or WC-referenced standards. Currently, the only step count recommendations available for young people are based on BMI. Tudor-Locke et al. (32) proposed a target of 15,000 (boys) and 12,000 (girls) steps each weekday to minimize the risk of overweight or obesity as defined by international BMI cutoff points (4). Before these step count standards can be verified using %BF, the levels of body fat that constitute an unhealthy child need to be determined. The development of sex- and age-specific %BF charts identifying increased health risk in young people would ensure that %BF-referenced step count targets are applicable to the population. Prospective recommendations should also allow for the significantly lower step counts on weekends when compared with weekdays. Yet another layer of complexity is added when considering the potential differences in activity and body composition across ethnic groups within a population. Our results indicated that Asian children were the least active of the three ethnic groups in this study, whereas Polynesian children were the most active on weekdays. Interestingly, both Asian and Polynesian groups had relatively high levels of body fat compared with Europeans. The high weekend step counts observed in European children may be related to the larger proportion of this ethnic group with a high socioeconomic rating (51.0%) when compared with Asian (42.3%) and Polynesian (8.4%) children. Such ethnic variation, although an important consideration when tailoring obesity-prevention initiatives, may not be practical to include in population step count recommendations.

In summary, this study provides the first step count data for young New Zealanders, revealing differences in physical activity across sex, age, and socioeconomic groups, and among European, Polynesian, and Asian children. The utilization of MDM pedometers enabled us to detect significantly lower levels of activity during weekends when compared with weekdays. Furthermore, the results of this study offer new evidence of a link between daily steps and body fatness in children. Given that daily steps were more strongly related with body fat than either BMI or WC, we recommend the use of %BF as an indicator of childhood obesity in physical activity research. These findings advance the current state of knowledge regarding physical activity and body composition in children and provide support for the development of strategies to increase the accumulation of daily steps in pediatric populations.

This study was funded by a seeding grant provided by the Auckland University of Technology. The results of the present study do not constitute endorsement of pedometers by the authors or ACSM.


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