Abstract:Background:The purpose of this study was to conduct a secondary analysis by combining 2 pedometer data sets to describe and analyze pedometer-determined steps/day of children by ethnicity and metropolitan status. Methods: Participants were 582 children (309 girls, 273 boys; 53% Hispanic, 26% Caucasian, 21% African American) age 10 to 11 years (M = 10.37 ± 0.48) attending 1 of 10 schools located in urban, suburban, and rural settings. Participants wore a research grade pedometer for at least 3 week/school days.… Show more
“…Other categorisation variables commonly applied where appropriate include age group or school year/grade and BMI since it has been reported that step counts decline with increasing age 39,46,52,75 and BMI. 50,63 Ethnic differences in step counts have also been reported, 47 therefore where relevant it may also be important to report step count data according to ethnicity.…”
Section: Methods Of Data Treatment Analysis and Reportingmentioning
confidence: 99%
“…A number of researchers have excluded data from a particular day, or all of the data from a participant, if participants have reported removing the pedometer for over an hour. 11,[39][40][41][42][43][44][45][46][47][48][49][50] To enhance comparability between studies it is recommended that future studies apply the same protocol of excluding data from a particular day if participants report removing the pedometer for over one hour on that day.…”
“…Other categorisation variables commonly applied where appropriate include age group or school year/grade and BMI since it has been reported that step counts decline with increasing age 39,46,52,75 and BMI. 50,63 Ethnic differences in step counts have also been reported, 47 therefore where relevant it may also be important to report step count data according to ethnicity.…”
Section: Methods Of Data Treatment Analysis and Reportingmentioning
confidence: 99%
“…A number of researchers have excluded data from a particular day, or all of the data from a participant, if participants have reported removing the pedometer for over an hour. 11,[39][40][41][42][43][44][45][46][47][48][49][50] To enhance comparability between studies it is recommended that future studies apply the same protocol of excluding data from a particular day if participants report removing the pedometer for over one hour on that day.…”
“…(37, 41) Compared to the general youth population, lower
percentages of disadvantaged and urban youth appear to be meeting the
recommendations. (8, 15, 16, 19) The known health benefits of physical
activity support prioritizing the identification and characterization of these and
other subgroups at high risk for inactivity. In addition, the recent Surgeon
General’s Call to Action, titled, “Step it
up!”(38), highlighted the
need to identify factors related to PA levels in these subgroups that may better
inform targeted PA intervention efforts for those most in need of improvement.…”
Section: Introductionmentioning
confidence: 99%
“…(36) Aspects of the built
environment that vary across metropolitan settings have also emerged as factors that
may lead to differences in PA levels across subgroups. (8, 16). In
relation to this, one study reported that urban youth had significantly lower
average (stdev) step counts/day compared to suburban and rural youth (10,856
± 3,706 versus 12,297 ± 3,616 and 11,934 ± 3,374,
P<0.05); with the lowest mean step counts/day in urban females.…”
Section: Introductionmentioning
confidence: 99%
“…In
relation to this, one study reported that urban youth had significantly lower
average (stdev) step counts/day compared to suburban and rural youth (10,856
± 3,706 versus 12,297 ± 3,616 and 11,934 ± 3,374,
P<0.05); with the lowest mean step counts/day in urban females. (16) Furthermore, studies of environmental
factors suggest that differences in opportunities to engage in PA in/outside of
school and neighborhood safety (perceived and objectively recorded) may contribute
to activity level variations across metropolitan settings. (10, 12, 33) Other factors highly correlated with
metropolitan setting that may be related to activity levels include race/ethnicity
and poverty.…”
Purpose
Evidence suggests that female adolescents and those living in urban
environments may have lower physical activity (PA) levels compared to their
peers. Yet, few studies report PA for urban adolescent females and there is
no consensus regarding potential causes for low PA in this subgroup. We
examined PA levels, in a large, diverse cohort of 14–17 year old
urban-dwelling females and assessed the impact of socio-economic, personal,
and neighborhood/environmental factors on PA.
Methods
One week of time-stamped step count data was collected on 926 girls
from the Pittsburgh Girls Study (PGS) at four annual visits. Valid
recordings (worn at least 10 hours on 3+ days) were examined and
compared to normalized step count values from a U.S.
population-representative sample. Relationships between important covariates
and average steps/day were examined with regression models.
Results
Adjusted mean (stdev) step counts/day at baseline were 5,614 (2,434)
after controlling for important covariates with less than 6% of
girls achieving at least 10,000 steps/day. PGS girls accrued
~45% of their steps during school hours. Age specific,
median step counts/day for study participants were similar to the
25th percentile of U.S. population normalized values and did
not significantly change over follow-up. Non-Hispanic African American
race/ethnicity was associated with higher average step counts/day; obesity
and a recent childbirth were associated with lower average step
counts/day.
Conclusions
Step counts in this cohort of urban adolescent girls were
considerably lower than expected for U.S. adolescent females. Targeted
efforts to improve PA levels in urban youth should consider the importance
of school-based activity while increasing PA opportunities outside of
school.
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