corresponding p -values. We scaled the e ects to interquartile range (IQR) increases in pol- lutant metrics to compare the magnitude of e ect across di erent scales of the pollutant concentrations. The 96-hr school pollutant concentrations (PM 2.5 , PM 10 , and NO 2 ) were negatively associated with MVPA (PM 2.5 and PM 10 : p < .001; NO 2 : p = .04), whereas they were positively associated with sedentary activity (PM 2.5 and PM 10 : p < .001; NO 2 : p = .02). The relationship between 96-hr O 3 and MVPA was not significant ( p = .7). The 72-hr maximum O 3 data, however, were associated with a decreased rate of MVPA ( p = .001). The 96-hr mean ambient PM and NO 2 concentrations at the Ascarate CAMS were significantly associated with physical activity levels, showing consistent patterns of associa- tion with 96-hr school concentrations. The largest percent time spent in MVPA per school pollutant increase in IQR was observed in the association between 96-hr PM 2.5 and MVPA: 3.45% decrease in MVPA (95% CI [-5, -1.9]) as the IQR in PM 2.5 increased. We had a similar amount of percent change in seden- tary activity: 3.43% increase (95% CI [1.78, 5.09]) as the IQR in PM 2.5 increased. Discussion Principal Findings The 96-hr average concentration for each of the pollutants was higher compared with the CAMS (Table 1), indicating a higher exposure at the school. The proximity to a major freeway, as well as air pollutant con- centrations contributed by school-specific traffic, potentially could lead to adverse health outcomes for children attending ele- mentary school and participating in outdoor activities. In addition, as observed from the pollutant concentrations, we can infer that the larger time windows considered (72 or 96 hr) provide a better representation of the current air pollutant exposure for physical activity at the study site. We found negative correlations between the 96-hr means of PM 2.5 , PM 10 , and NO 2 at the school and the amount of time spent in MVPA during school hours. In contrast, sed- entary activity was positively correlated with air pollutant concentrations. This finding is consistent with other studies that have objec- tively measured physical activity using accel- erometers. An increase in ambient PM 2.5 was
TABLE 2
Participant Demographic, Anthropometric, and Physical Activity Data ( N = 12)
Mean ± SD
Range
Age (years) Height (in.) Weight (lb) BMI (kg/m 2 )
8.3 ± 1.5
6–10
54.3 ± 4.4 76.3 ± 27.3 17.9 ± 5.0 49.8 ± 41.2
46.3–70.0 45.8–134 12.3–27.8
BMI (%)
0–99.4
Physical activity (%) MVPA
63.4 ± 8.2 10.1 ± 1.7 26.5 ± 7.9
30.4–77.7
Light
7.1–14.4
Sedentary
13.7–61.7
Note. BMI = body mass index; MVPA = moderate to vigorous physical activity.
TABLE 3
Participant-Specific Factors Compared With Physical Activity Levels
Specific Factor
Participant Frequency ( N = 12)
Moderate to Vigorous Physical Activity
Sedentary Physical Activity
# (%)
%
p -Value
%
p -Value
Gender
.001
.001
Male
7 (58) 5 (42)
65.8 60.0
24.2 29.2
Female
BMI category
.010
<.001
Underweight and normal Overweight and obese
8 (67) 4 (33) 5 (42) 7 (58) 3 (25) 9 (75) 8 (67) 4 (33) 8 (67) 4 (33) 6 (50) 6 (50) 8 (67) 4 (33) 3 (35) 9 (75)
61.9 66.5 63.2 63.6 60.9 64.3 63.4 63.5 62.7 64.8 61.2 65.6 63.0 64.2 66.8 62.2
28.4 22.6 26.1 26.7 28.8 25.7 26.3 26.8 26.9 25.6 28.8 24.1 27.2 25.1 23.2 27.7
Mother with asthma
.895
.503
No
.041
.032
Father with asthma
No
Mother with hay fever
.944
.595
No
Father with hay fever
.305
.511
No
.005
.001
Siblings with asthma
No
Siblings with hay fever
.602
.169
No
.012
.011
Having eczema
No
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