The focus on health-related physical activity is tremendous and has in recent years led to its intensive promotion in Norwegian society. Nevertheless, children today are thought to be less physically active than in previous generations. This perception is based on the increased prevalence of overweight and obesity seen from an early age (2,19) as well as the drastic increase in the time that children devote to sedentary activities in recent decades (29). Although several studies show longitudinal decline in physical activity from childhood through adolescence and into adulthood (3,25,35), there are few reliable data obtained from using objective methods assessing changes in physical activity level in children (11,23,27). Moreover, children's physical activity has provided serious measurement challenges for researchers, and there are limitations to existing data. Much of the data provide crude estimates of physical activity that are based on some form of children's self-report (11,25). This may be problematic because assessing physical activity participation in children is challenging because they rarely engage in lengthy sustained bouts of activity but have a physical activity pattern that is typically intermittent and spontaneous (4). Children tend to overestimate high-intensity physical activity behavior and to underestimate moderate physical activity when completing self-report instruments. Moreover, children lack the cognitive ability to accurately recall details of their physical activity patterns (16,33,38).
Some uncertainties surround the associations between socioeconomic status (SES) and physical activity participation in childhood. Although some studies reveal a positive association between SES and physical activity (12,18,21), others find no association (5,6,14,17,30) or an inverse association (22). Furthermore, few studies have examined the extent to which the changes in childhood physical activity vary by SES. A study from Australia (11) revealed that moderate-to-vigorous physical activity (MVPA) increased across all SES tertiles. However, the greatest increase was seen in adolescents from middle- and high-SES areas. The study, however, was based on self-report data and included adolescents only. A study from Denmark using objective methods to assess changes in habitual physical activity among 8- to 10-yr-olds showed that changes in physical activity did not differ among SES groups (23). There is a need to gain a better understanding of how children in different SES groups change their physical activity level over time.
The aim of this study was to describe changes in objectively assessed physical activity over a 5-yr period using representative samples of 9-yr-olds living in Oslo, Norway. In addition, we tested whether there was an interaction between change in mean physical activity level and time spent at MVPA between study periods and SES.
Data were collected in two cross-sectional studies: the European Youth Heart Study carried out from 1999 to 2000 and the Physical Activity among Norwegian Children Study carried out in 2005. In 1999, all elementary schools in Oslo were stratified according to the socioeconomic character of their local area. From each of three socioeconomic strata (low, middle, and high) and at an individual level based on the number of students attending each school, a proportional sample of schools was randomly selected. In 1999-2000, children were recruited from nine elementary schools in Oslo, and the same schools were included in the 2005 study. In 1999-2000, 410 of 578 invited fourth graders participated in the study, giving a participation rate of 70.9%. In 2005, 449 of 491 invited children were included in the study, giving a participation rate of 91.4%. Before participation in the study, written informed consent was obtained from each subject and his or her primary guardian. The Regional Committee for Medical Research Ethics and the Norwegian Social Science Data Services approved the study.
Weight and height were measured while the children were in light clothing and without shoes. Weight was measured to the nearest 0.1 kg with a digital Seca 770 scale. Height was measured to the nearest 0.1 cm, using wall-mounted tapes, with the child standing upright against the wall. Body mass index (BMI) was calculated as weight (kg) divided by the squared height (m2).
Socioeconomic status (SES).
The classification of SES was based on the economic profile of the catchment area of the schools the children attended. On the basis of the average gross income per inhabitant aged between 30 and 66 yr liable to pay taxes within the different school catchment areas, the local authorities calculated the percentage inhabitants who had a gross income considered as high (in 1997 defined as >US $50,000). This calculation was used to divide the catchment areas into three gross income groups: low-, middle-, and high-SES areas. From these three subgroups, we included four schools from low-SES areas, two schools from middle-SES areas, and three schools from high-SES areas. The clustered SES code was assigned to each child within the data set.
Assessment of physical activity.
The uniaxial Actigraph accelerometer (MTI model 7164; Manufacturing Technology Inc, Fort Walton Beach, FL) was used to obtain objective assessment of physical activity. We visited the children at their schools, and each child was fitted with one accelerometer worn for four consecutive days (two weekdays and two weekend days). The children wore the monitor on the right hip, and we instructed them to wear the accelerometer during all waking hours, except during swimming and bathing. Accelerometers were initialized to start recording at 6 a.m. on the day after they were distributed to the children. In 1999-2000, we set the epoch to 60 s, and in 2005, we set the epoch to 10-s intervals, which subsequently were summed to 60-s intervals before further analyses. The physical activity measurements in both studies were undertaken during the same months of the year (February to June), with the exception of one school in 1999 where data were collected in October and November.
A SAS-based software program (SAS Institute Inc., Cary, NC) called CSA analyzer (http://csa.svenssonsport.dk) was used to analyze accelerometer data. In the analyses of accelerometer data, we excluded all night activity (12−6 a.m.) and all sequences of 10 min or more of consecutive zero counts from each subject's recording. The latter implies that the child has not been wearing the accelerometer. A newly published study (20) reported that the single-day intraclass correlation coefficient (ICC) for 600 min of assessment was 0.45, whereas the ICC for 480 min of assessment was 0.44. To avoid loosing statistical power, we chose to specify a valid day as 480 min. In the present study, data were considered valid if a child had at least 3 d of at least 480 min·d−1 recorded.
The primary physical activity variable was the mean number of counts per minute (counts·min−1), and additional outcomes were time spent at different activity intensities. Published cutoffs for different intensity levels in children vary substantially between studies. We defined MVPA as >2000 counts·min−1, whereas vigorous physical activity (VPA) was defined as >3000 counts·min−1. The cutoff for moderate activity (i.e., 2000 counts·min−1) is broadly equivalent to walking at 4 km·h−1 and has also been used elsewhere (1,8). The proportion of children who achieved the recommended levels of 60 min of MVPA each day (24) was established by dividing time spent on MVPA by the number of valid days of recording, giving an average number of minute per day across the assessment period.
With physical activity (counts·min−1) as the primary outcome variable, we used the variability known from the baseline population (SD = 286) to calculate the minimum size of differences we could distinguish between subgroups. With respect to this, 340 children in each group gave us the ability to detect subgroup physical activity differences of 30 counts·min−1 (4%) (α = 0.05) using a two-tailed test (1 − β = 0.80). General linear models were used to assess the changes in physical activity between 1999-2000 and 2005. We found no interaction between sex and study period for any of the physical activity variables; therefore, these analyses are presented by study period, adjusted for sex and school. We used chi-square analyses to study change in the proportions of children meeting the physical activity recommendations.
Two-way ANCOVA was used to study the associations between sex, SES, mean physical activity, and MVPA between the two time points. For mean physical activity, but not MVPA, a trend toward a three-way interaction was found between SES, study period, and sex (P = 0.06). Consequently, the results for the association between mean physical activity and SES are presented, stratified by sex. The patterns of associations were compared among different SES groups by testing interaction terms (study period × SES). Because SES can be confounded by BMI, all analyses are adjusted for BMI. One-way ANOVA with a Bonferroni correction for multiple comparisons was used to compare physical activity across SES groups for each time point. For the latter variables, a P value <0.02 (0.05/3) was required to declare significance. All analyses were conducted using the Statistical Package for the Social Sciences (version 15; SPSS Inc., Chicago, IL).
The 1999-2000 study comprised 340 children, and the 2005 study comprised 378 children with valid physical activity assessments. Descriptive characteristics of the study sample are presented in Table 1.
Mean physical activity level.
In 1999-2000, the participants' mean (SD) physical activity was 779 (255) counts·min−1, whereas the corresponding value was 833 (322) counts·min−1 in 2005. Adjusted mean (SE) physical activity data are presented in Table 2. A significant increase in mean physical activity was observed between the two time points (P = 0.02). The difference in mean physical activity between the children in 1999-2000 and 2005 was 49 counts·min−1, which translates into a 6.2% (95% CI = 4.5-8.0) difference. In 1999-2000, the participants' mean (SD) physical activity level was 815 (279) counts·min−1 during weekdays and 676 (345) counts·min−1 during weekends. The corresponding values were 839 (303) and 829 (480) counts·min−1 in 2005. As can be seen in Table 2, physical activity during weekdays showed no change over time (P = 0.4). However, an increase in physical activity during weekends was observed between the study periods (P < 0.001). Children in 2005 were 20.8% (95% CI = 17.8-23.8) more physically active during weekends than children in 1999-2000.
Time spent in MVPA and VPA (min·d−1).
Between study periods, no difference was seen for mean time spent in MVPA and VPA (Table 2). Changing the cutoff for VPA to >4000 or >4500 counts·min−1 did not alter the results (data not shown). In 1999-2000, 75.4% of girls and 86.7% of boys met the Norwegian physical activity recommendations of 60 min of daily MVPA. In 2005, 79.3% of the girls and 92.8% of the boys met the recommendations; the increase was significant among boys (P = 0.05).
Physical activity and SES.
In 1999-2000, boys from middle-SES groups had significantly lower mean physical activity level than boys from the low- and the high-SES groups (P = 0.001 and <0.001, respectively). In 2005, girls from the high-SES groups were significantly more active than girls from the low-SES groups (P = 0.003). We found a significant interaction between study period and SES for mean physical activity for both girls (P = 0.02) and boys (P = 0.05). Between studies, the physical activity level among girls from low-SES groups remained relatively stable, whereas an increase in mean physical activity was seen among girls from middle- and high-SES groups. The mean physical activity level among boys from low- and high-SES areas remained fairly stable; however, an increase was seen among boys from middle-SES groups (Table 3).
In 1999-2000, children from low-SES groups participated in more MVPA than children from middle- and high-SES groups (P < 0.001 and P = 0.007, respectively). In 2005, there was no association between time spent in MVPA and SES. A significant interaction was found between study period and SES for time spent in MVPA (P = 0.02). Between studies, the MVPA participation among children from low- and high-SES groups remained fairly stable, whereas participation in MVPA increased in children from middle-SES groups (Fig. 1).
Our study has two main findings. First, 9-yr-old children living in Oslo, Norway, have increased both their mean physical activity level and their activity level during weekends between 1999-2000 and 2005, with the patterns being similar for girls and boys. Second, interactions were found between change in physical activity and SES. Although no change was seen in mean physical activity level and MVPA participation among children from low-SES groups, an increase was seen among children from middle-SES groups. Moreover, children from high-SES groups had an increase in mean physical activity level (girls only) between study periods, whereas their MVPA participation remained fairly stable.
Strengths and limitations.
A major strength of this study was the use of an objective assessment of physical activity. Accelerometers are regarded as optimal for quantification of the amount and intensity of physical activity (28), and the use of the device has shown to be both valid and reliable (37). In both studies, we used identical data reduction methods, which should exclude any systematic differences among studies. Furthermore, both studies included large population-based samples with high participation rates.
Some limitations in the study should be noted. First, in 1999-2000, approximately 30% of the invited children chose not to participate, and we cannot completely rule out the issue of selection bias. Because the aim of the study was, among others, to assess physical activity level, aerobic fitness, and body composition, it is likely that the leanest and most physically active children chose to participate. If this is true, there are reasons to believe that our results are underestimated rather than overestimated. Second, we chose to define SES on an area level, which may be biased on the individual level. However, it has been argued that household and neighborhood factors could be important modifiers of physical activity (32). In Oslo, there are strong regional links between socioeconomic background factors and disability and mortality (31). By defining SES on an area level, our study could add significantly to the knowledge of whether neighborhood context affect childhood behavior. Third, data were collected over several months, and it is a possibility that seasonal variation in daily physical activity might influence the results. However, as both studies were conducted during the same months of the year and the months when data were collected in the different SES areas were random in both studies, we do not think that changes in physical activity were caused by seasonal variation.
Changes in physical activity.
Previous self-report data have suggested that US adolescents have had relatively stable MVPA participation during recent decades (25,26), whereas Australian adolescents increased their MVPA participation between 1997 and 2004 (11). At present, few studies have reported on changes in objectively assessed physical activity; however, the few that have been conducted show similar changes as those using self-report measures. A study from Denmark reported a stable physical activity level in 8- to 10-yr-old children between 1997-98 and 2003-04 (23), whereas Swedish 7- to 9-yr-olds increased their weekday physical activity (steps per day) between 2000 and 2006 (27).
One of the most notable findings of the present study was the large increase in physical activity during weekends. Because children in 1999-2000 were 17% less physically active during weekends than during weekdays, the weekend days had the greatest potential for increased physical activity. During weekdays, a lot of the physical activity is connected to school activities and organized activities in the afternoon. On the weekends, however, parents and significant others are primarily responsible for ensuring that children are sufficiently physically active. Our results therefore suggest that the intensive promotion of physical activity has contributed to significant parental investment in increasing physical activity during weekend days.
The recent increases in physical activity found in the present study are likely to have resulted from an interaction of different factors. First, the Norwegian government has developed a national physical activity action plan aimed at increasing and strengthening factors that promote physical activity in the population and reducing the factors that lead to physical inactivity (36). The vision of the action plan is a general improvement in public health through increased physical activity in the population. However, children and adolescents are identified as target group number one. Second, several school interventions have been initiated to increase children's physical activity participation. Third, the mass media have emphasized the positive health benefits associated with regular physical activity, and attention has been given to the prevention of obesity, which may stimulate further interest in physical activity.
Physical activity and SES.
The association between childhood physical activity and SES is still unclear, and results remain inconclusive. Riddoch et al. (30) reported that the mother's and partner's education levels were inversely associated with 11-yr-olds' activity level. However, the association was lost for mother's education and attenuated for partner's education when adjusting for age, sex, season, maternal age, and social class. Hesketh et al. (12) reported that maternal employment was associated with objectively assessed MVPA in Australian 6-yr-olds, whereas no associations were found between Scottish preschoolers' objectively assessed physical activity levels and SES (14). Moreover, a study from the United States revealed that a lower level of parental education was associated with greater physical activity decline when going from childhood through adolescence (15). The reason for the inconsistencies among studies might be that behaviors may be differently related to SES in different cultures or the different classifications of SES used in each study. Whereas some studies use individual-level measures of SES (e.g., parent's education, occupation, and income), others use household-level measures (e.g., combined income earned by all members of the household, occupation of the "main income earner" in the household) or area-level measures (postcode of residence). Each method has its own strengths and weaknesses, making comparisons between studies and countries challenging.
Interactions were found between change in mean physical activity level, MVPA and SES. This indicates that some characteristics of the school environment influence children's opportunities for physical activity. It is possible that schools in high-SES areas have higher-quality and better-maintained physical activity facilities than do schools in less affluent areas. Previous studies have also shown that low-income neighborhoods have fewer facilities for recreational physical activity, and the presence of facilities in neighborhoods is directly correlated with individual physical activity (10). Moreover, studies have found that adults in high-SES groups are more physically active than adults from other SES groups (7,9,39). It might be that parents in high-SES areas are more aware of the health benefits of physical activity and therefore encourage their children to be physically active. Cultural factors may also influence the change in mean physical activity. In 1999-2000, 97% of the children in the high-SES group were of Western origin compared with 78% in the low-SES groups. In 2005, the corresponding numbers were 96% and 68%. It might be that ethnic minority girls experience less encouragement from parents and friends to be physically active and may also have fewer opportunities to be physically active than ethnic Norwegian girls, as the increase in mean physical activity was particularly large among high-SES girls.
Implications for public health.
There is a need to gain a better understanding of how children's physical activity levels change during time. Our results suggest that there has been significant investment in providing children with greater physical activity opportunities. However, because these opportunities are not equal across SES groups, more emphasis should be put on increasing physical activity among children from low-SES groups, especially in girls. It is important that the activities that are offered are inexpensive and convenient to access (13). One solution could be making 60 min of daily physical activity mandatory in school curricula. This can be achieved in a cumulative manner during physical education, recess, and before and after school programs (34) and would give children from all SES groups the opportunity to be physically active. The activities should be of at least moderate intensity and require qualified teachers. Furthermore, policy makers should make an effort to improve accessibility of physical activity programs as well as the number and quality of recreational facilities in lower SES areas (13).
From 1999-2000 to 2005, 9-yr-old girls and boys living in Oslo increased their mean physical activity level as well as their activity level during weekends. The increase in physical activity was, however, not equal across SES groups. The results emphasize the need to increase physical activity level in children from low-SES areas.
The authors thank Professor Ingar Holme for statistical guidance. Financial support was received from the Norwegian Directorate of Health and the Norwegian School of Sport Sciences. The results of the present study do not constitute endorsement by the American College of Sports Medicine.
Competing interests: The authors declare that they have no competing interests.
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