household characteristics, symptoms, activ- ity limitation due to symptoms, emergency department visits, and hospital admissions. The children answered questions weekly about medication use and symptoms using the Asthma Control Questionnaire (Juniper et al., 2010). English and Spanish versions were made available for all questionnaires. We measured physical activity rates—cat- egorized by activity intensity as moderate to vigorous physical activity (MVPA), light, and sedentary—using an accelerometer (wGT3X- BT, ActiGraph) placed on the participant’s wrist each week between 9 a.m. and 2 p.m. We used ActiLife software (version 6.13.3) using the children algorithm (Freedson et al., 2005) to distinguish the three levels of activity. Air pollutants were continuously mea- sured using GRIMM Technologies Aerosol Spectrometer 11-A (for PM 10 and PM 2.5 ), 2B Technologies Model 405 NO 2 /NO/NO x (for NO 2 ), and 2B Technologies Model 202 (for O 3 ) placed outdoors between the school building and I-375 highway. We collected temperature and relative humidity data from the nearest weather station located at El Paso International Airport. We used air pollution data recorded by the Texas Commission on Environmental Quality from continuous ambient monitoring stations (CAMS) at Chamizal National Memorial Park in El Paso for comparison of site-specific PM 2.5 , PM 10 , and O 3 data. We used another CAMS site at Ascarate Park, a county park in El Paso, to compare NO 2 (Figure 1). Hourly measure- ments were averaged to calculate values for 24, 48, 72, and 96 hr before the physical activity measurements. Data Analysis We performed all statistical analyses using R version 3.2.2. To explore relationships between physical activity and outdoor pollut- ant concentrations, we used Spearman cor- relations. We compared physical activity out- comes between the subjects (% time spent in sedentary, light, or MVPA) using the Kruskal– Wallis test. We examined longitudinal associa- tions between MVPA/sedentary physical activ- ity measures and air pollution metrics using a generalized estimating equations (GEE) approach (Liang & Zeger, 1986). We assumed the subject-specific cluster and exchangeable correlation structure for the repeated mea- sures of the physical activity data.
FIGURE 1
Location of School and Continuous Ambient Monitoring Stations
Legend
School Continuous Ambient Monitoring Stations
can be controlled well enough for them to perform physical activity and that healthcare professionals can provide additional therapy options if needed (National Heart, Lung, and Blood Institute & National Asthma Educa- tion and Prevention Program, 1998, 2007). Given the benefits of physical activity, it is in the best interest of people with asthma to achieve a balance between controlling their respiratory symptoms and regular exercise. The impact of air pollution on people with asthma, however, can also prevent them from achieving a physically active lifestyle. In controlled studies among groups exposed to higher concentrations of air pollutants, there was a higher risk of asthma attacks (Sharman et al., 2004) and lung diseases (Giles & Koehle, 2014). Furthermore, chil- dren with asthma who live in low-income communities are likely to have increased clinical asthma symptoms when they are exposed to short-term increases in air pol- lutants (Wendt et al., 2014). To our knowledge, there are no studies that have assessed changes in air quality over time that examine how those changes correlate with objectively measured physical activity in children with asthma in a school setting. Our study investigated the relationship between physical activity levels and air pollution in children with asthma, along with other social, demographic, and medical factors. We expect the findings of our study to fill this gap of knowledge and inform the implemen-
tation of policies and health recommenda- tions for communities to reduce the adverse eect of air pollution on physical activity in school settings.
Methods
Setting, Population, and Sampling This study was conducted in El Paso, Texas, from October to December 2017 at an ele- mentary school located within 50 ft of a free- way with heavy trac. Air pollutants and concurrent meteorological data were con- tinuously monitored throughout the study. Physical activity was assessed weekly dur- ing school hours. The institutional review board of The University of Texas at El Paso approved the protocol. Children with asthma were recruited by contacting the school nurse and distributing flyers to students and their parents. The par- ent or legal guardian of each participant pro- vided written consent and the children pro- vided assent. Consent and assent forms were available in English and Spanish. The selec- tion criteria included children between 6 and 12 years with a medical diagnosis of asthma, no other lung disease or major illness, and living in a nonsmoking household. In total, 12 children met the eligibility requirements and participated in the study. At the start of the study, parents completed a questionnaire regarding health status, current allergies, insurance status, medication usage,
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April 2023 • Journal of Environmental Health
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