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. Author manuscript; available in PMC: 2023 Nov 1.
Published in final edited form as: Prev Med. 2022 Oct 14;164:107306. doi: 10.1016/j.ypmed.2022.107306

Are the adverse health effects of air pollution modified among active children and adolescents? A review of the literature

Stephanie DeFlorio-Barker 1, Sarah Zelasky 2, Kevin Park 2, Danelle T Lobdell 1, Susan L Stone 3, Kristen M Rappazzo 1
PMCID: PMC10116489  NIHMSID: NIHMS1887183  PMID: 36244521

Abstract

Air pollution exposure is associated with negative health consequences among children and adolescents. Physical activity is recommended for all children/adolescents due to benefits to health and development. However, it is unclear if physically active children have additional protective benefits when exposed to higher levels of air pollution, compared to less active children. This systematic review evaluates all available literature since 2000 and examines if effect measure modification (EMM) exists between air pollution exposure and health outcomes among children/adolescents partaking in regular physical activity. PubMed, Science Direct, Scopus, Web of Science, and ProQuest Agricultural & Environmental Science databases were queried, identifying 2,686 articles. Title/abstract screening and full-text review eliminated 2,620 articles, and 56 articles were removed for evaluating individuals >21, leaving 10 articles for review. Of the included articles, half were conducted in China, three in the United States, and one each in Indonesia and Germany. Seven articles identified EMM between active children and air-pollution related health outcomes. Five of these indicated that children/adolescents do not experience any additional benefits from being physically active in higher levels of air pollution, with some studies implying active children may experience additional detriments, compared to less active children. However, the remaining two EMM studies highlighted modest benefits of having a higher activity level, even in polluted air. Overall, active children/adolescents may be at greater risk from air pollution exposure, but results were not consistent across all studies. Future studies assessing the intersection between air pollution and regular physical activity among children would be useful.

Introduction

Interactions between physical activity and air pollution have the potential to be complex and multifactorial. Air pollution exposure, whether it be long- or short-term, is associated with several negative health consequences, especially among vulnerable groups such as children and adolescents. Air pollution exposure among children and adolescents can result in several negative health consequences including increased cardiorespiratory effects (Brugha and Grigg 2014; Dong et al. 2019), neurodevelopment effects (Ha 2021), exacerbation or development of asthma (Tiotiu et al. 2020), slowed lung development (Gauderman et al. 2004; Gaurderman et al. 2015), and other detrimental effects (US Environmental Protection Agency 2019). Worldwide, over 90% of children under 15 are exposed to ambient air pollution levels above the 2005 World Health Organization (WHO) air quality guidelines, and air pollution accounts for close to 10% of deaths in children less than five years of age (World Health Organization 2018). Recently, the WHO has updated their air quality guidelines for fine particulate matter from 10μg/m3 to 5μg/m3, resulting in even more children and adults being exposed to levels of air pollution that may have negative health consequences (World Health Organization 2021). Exposure to air pollution at a young age has been tied to increased risk of cardiovascular and immunologic deficiencies into adulthood (Prunicki et al. 2021). Physical activity, on the other hand, is known to have several benefits to overall health, and the WHO currently recommends that children and adolescents (5-17 years) engage in at least 60 minutes per day of moderate to vigorous intensity physical activity along with vigorous intensity aerobic and muscle/bone strengthening activities at least three days per week. Among children and adolescents, physical activity has demonstrated several benefits, including: cardiometabolic health, bone health, cognitive outcomes, mental health, improved cardiorespiratory and muscular fitness , and reduced adiposity (World Health Organization 2020).

Despite known benefits of regular physical activity, it is unclear if these benefits extend to protect children and adolescents against the detrimental effects from exposure to air pollution. Physical activity increases ventilation rate and therefore can increase the number of pollutants that make it deep within the respiratory system (Oravisjaervi et al. 2011), potentially causing more adverse reactions due to higher degree of exposure. Children can be especially vulnerable because they have a higher ventilation rate and a greater lung surface area compared to adults. Taken together, it is estimated that children can intake approximately 50% more air compared to adults (US Environmental Protection Agency 2008). Additionally, the presence of high concentrations of air pollution can also directly impact outdoor physical activity behavior. Recent studies have concluded that increased air pollution is associated with more sedentary behavior and less outdoor exercise frequency, which can further negate the positive impacts of physical activity on a population (An et al. 2019; Yu et al. 2017).

A previous review of the literature examined the interaction between short-term exposure to air pollutants and physical activity, and corresponding acute health endpoints (DeFlorio-Barker et al. 2020). In that review, composed primarily of crossover studies, it was concluded that pollutant levels and the intensity of physical activity were influential in determining whether or not physical activity provided either a detrimental or protective effect in areas of higher verses lower pollution. Additionally, this review noted that studies evaluating sensitive populations, such as those with pre-existing conditions and the elderly, often noted a greater detriment of physical activity in areas of relatively higher air pollution levels. However, no crossover studies in this review included evaluations of children and adolescents 21 years and under, as they are typically conducted among healthy, adult populations.

For the current study, we performed a systematic review of the literature aiming to evaluate and summarize the science published since the year 2000 relating to effect measure modification between air pollution exposure and health outcomes among children and adolescents who regularly participate in physical activity.

Methods

Literature Search, Selection Criteria, and Data Extraction

A search of the literature was done using the methodology outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher et al. 2009), using PubMed, Science Direct, Scopus, Web of Science, and ProQuest Agricultural & Environmental Science databases for articles published between 2000–2021. Search terms included air pollution terms joined with an AND operator with physical activity terms (Table S1). The search was limited to human subjects, peer-reviewed literature, and the English language. A minimum of two investigators (either S.D.B, K.M.R, or S.Z.), independently performed title and abstract screening, using SWIFT-ActiveScreener (https://www.sciome.com/swift-activescreener/). Articles were included in the final systematic review if they estimated air pollution exposure (using a model, from a fixed site monitor, or relied on measurements from a wearable device), evaluated physical activity within the population studied, and either directly evaluated effect measure modification (EMM) between being physically active and air pollution, or had enough critical elements in which EMM could be derived from the information presented. Lastly, articles which studied populations with a mean age >21 years were excluded.

The following data were extracted from each reviewed article: study location, age range of study population, percent of female participants, study design, study time period, sample size, type of physical activity, estimated air pollutant measurements, health endpoint, covariates adjusted, and the presence or absence of EMM. Each article was evaluated directly for EMM. Presence of EMM was indicated if regular physical activity modified the association between exposure to air pollution and a particular health endpoint, demonstrated with an interaction term or stratified analysis. This study was a review of existing published literature and did not require human subjects review.

Risk of Bias

Each study was also critically reviewed for risk of bias. Currently, the U.S. EPA is developing a risk of bias protocol based on the Risk of Bias in Non-Randomized Studies - of Interventions (ROBINS-I) (https://cfpub.epa.gov/ncea/iris_drafts/recordisplay.cfm?deid=345065). The U.S. EPA has modified the ROBINS-I to fit more in line with environmental health, rather than intervention-based epidemiologic studies. This U.S. EPA-derived risk of bias framework was then modified further specifically for this review, by the incorporation of a component in which to evaluate physical activity (see supplemental material). The current review thoroughly evaluated eight distinct domains including: exposure assessment, physical activity assessment, outcome ascertainment, participant selection, confounding, analysis, selective reporting, and sensitivity. Each domain could be evaluated as either: acceptable, adequate, deficient, or critically deficient. Each article was evaluated and scored twice by either S.D.B, S.Z., K.P, or K.M.R. Subsequently, each study was then scored as either: high confidence, medium confidence, low confidence, or uninformative, based on the criteria previously established by U.S. EPA (Table S2), with particular emphasis on the physical activity domain as it was highly relevant to the interpretation of the results and comparability between studies. Instances of disagreement in individual domain scores or the overall score were settled by a third reviewer.

Results

Characteristics of Included Studies

The literature screen identified a total of 2,686 articles, after duplicates were removed (Figure 1). In the title and abstract screening phase, many articles (n=2,305) were excluded for either not jointly evaluating air pollution exposure and exercise/physical activity. The 381 remaining studies underwent full text review. During this phase of the review 315 articles were removed for not specifically evaluating individuals who habitually exercise or engage in regular physical activity, leaving 66 articles. An additional 56 articles were removed for evaluating participants >21 years of age.

Figure 1:

Figure 1:

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Literature flow diagram

A total of ten articles among children and adolescents less than 21 years of age were identified (Table 1), four of which were published since 2020 (Gui et al. 2020; Yu et al. 2020; Zhang et al. 2021a; Zhang et al. 2021b). Half of the included studies (n=5) were conducted in China (Gao et al. 2013; Gui et al. 2020; Yu et al. 2004; Zhang et al. 2021a; Zhang et al. 2021b), three in the U.S. (Lovinsky-Desir et al. 2016; Lovinsky-Desir et al. 2017; McConnell et al. 2002), and one each in Indonesia (Yu et al. 2020) and Germany (Thiering et al. 2016). The majority of the included articles had a cross-sectional design (n=7), two studies had a prospective cohort study design (McConnell et al. 2002; Yu et al. 2004), and one was considered a prospective, double blind randomized intervention trial (Thiering et al. 2016).

Table 1:

Included studies, children aged ≤ 21

Article, Study Population Location Study Design Air pollutant(s) and method of measurement Definition of physically active Health Endpoint Does regular physical activity modify association? Are there benefits to physical activity in areas of high air pollution?
Gao et al 2013
n= 2,048 (48% Female), children aged 8-10, average age: 9		 China Cross-sectional PM10, NO2, SO2, O3 Fixed site monitor Self-reported participation in sports and/or vigorous free play ≥3x/wk, ≥30 min Complete Speed, VO2max Yes No
Gui et al 2020
n=5,028 (46% Female), children aged 6-12, average age: 9		 China Cross-sectional PM10, PM2.5, CO, SO2, O3 Modeled Self-reported frequency of moderate and vigorous intensity physical activity Executive Function Yes* Yes
Lovinsky-Desir et al 2017
n=135 (50% Female), children aged 9-14, median age: 12.7 (non-active), 12.2 (active)		 United States Cross-sectional, within Colombia Center for Children’s Environmental Health Birth Cohort Black Carbon (BC), wearable device Wearable device, ≥60min moderate to vigorous activity Forkhead box p3 (FOXP3) Promotor methylation Yes Yes
Lovinsky-Desir et al 2016
n=129 (50% Female) children aged 9-14, average age: NR		 United States Cross-sectional, within Colombia Center for Children’s Environmental Health Birth Cohort Black Carbon (BC), wearable device Wearable device, ≥60min moderate to vigorous activity Airway inflammation (FeNo) Yes* No
McConnell et al 2002
n=3,535 (%Female NR), children age range: 9-16, average age: NR		 United States Prospective Cohort O3 Fixed site monitors Self-reported number of sports (0, 1, 2, 3+) Incident asthma Yes No
Thiering et al 2016
n=837, birth cohort average age: 15.0 at follow-up		 Germany Prospective, double-blind, randomized intervention trial PM2.5, PM10, NO2, Modeled Self-reported hours of moderate and vigorous activity per week Insulin resistance No No effect
Yu et al 2004
n=821 (51% Female), children aged 8-12, average age: NR		 China Prospective Cohort NO2, SO2, PM10 Fixed site monitor Self-reported participation in sports and/or vigorous free play ≥3x/wk, 30 min VO2max Yes No
Yu et al 2020
n=482 (43% Female), children aged 14-18, average age 16.3		 Indonesia Cross-sectional PM2.5 Modeled International Physical Activity Questionnaire-Short Form (IPAQ-SF) Fasting Plasma Glucose Yes No
Zhang et al 2021 (a)
n=44,718 (50% Female), children aged 7-18, average age: 10.7 (Boys), 11.0 (Girls)		 China Cross-sectional PM10, PM2.5, PM1, NO2 Modeled Self-reported frequency of outdoor exercise Obesity No No effect
Zhang et al 2021 (b)
n=9,897 (50% Female), children aged 10-18, average age: 13.3		 China Cross-sectional PM10, PM2.5, PM1, NO2 Modeled Frequency of outdoor exercise Metabolic Syndrome No No effect
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*

Interaction term not statistically significant, NR=not reported

A range of pollutants and pollutant concentrations were observed among the included studies. Most studies evaluated several different pollutants, including fine particulates (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3), using either ambient concentration data collected from fixed site monitors or estimates of ambient concentrations from air pollution models. In contrast, two of the U.S. based articles (Lovinsky-Desir et al. 2016; Lovinsky-Desir et al. 2017) evaluated personal exposure to black carbon (BC) using a wearable device. Many of the articles measured average PM2.5 concentrations in excess of the current annual U.S. EPA National Ambient Air Quality Standard (NAAQS) of 12μg/m3. Two articles (Zhang et al. 2021a; Zhang et al. 2021b) reported particularly high mean PM2.5 concentrations in excess of 60μg/m3, on an annual basis.

Each included article provided a definition for ‘active’ children and adolescents, yet there was a lack of consistency for that definition between articles. Most studies evaluated physical activity based on a combination of both self-reported frequency and intensity (Gao et al. 2013; Gui et al. 2020; Thiering et al. 2016; Yu et al. 2004). Two articles directly evaluated physical activity using an accelerometer and defined active children as those engaging in at least 60 minutes of moderate to vigorous activity per day. The article by Yu (2020), evaluated frequency and intensity of physical activity based on the International Physical Activity Questionnaire-Short Form (IPAC-SF). The IPAC-SF is a specific tool used to estimate the metabolic equivalent of task (MET), which is a way to approximate the amount of oxygen used during physical activity (National Center for Health Statistics 2017), specifically among those >15 years of age (Lee et al. 2011). The article by McConnell (2002) evaluated physical activity by using the number of sports played, as a proxy for increased physical activity. Lastly, the articles by Zhang et al (2021a) and Zhang et al (2021b) only evaluated self-reported outdoor exercise frequency.

The included articles evaluated a number of health endpoints. Four articles evaluated metabolic outcomes including insulin resistance (Thiering et al. 2016), fasting plasma glucose (Yu et al. 2020), metabolic syndrome (Zhang et al. 2021a), and obesity (Zhang et al. 2021b). Two articles specifically studied cardiopulmonary fitness (measured as VO2max) (Gao et al. 2013; Yu et al. 2004). The remaining four articles evaluated a variety of health endpoints including executive function (Gui et al. 2020), methylation of the forkhead box p3 promotor (Lovinsky-Desir et al. 2017), airway inflammation (Lovinsky-Desir et al. 2016), and incident asthma (McConnell et al. 2002).

Risk of Bias

The majority of studies (n=7) had an overall risk of bias classification of “medium confidence”. Two studies had an overall classification of ‘high confidence’, while one study was considered ‘low confidence’ (Figure 2). Individual domains that received either ‘acceptable or ‘adequate’ ratings included: exposure, physical activity, selective reporting, and sensitivity. Deficiencies in individual domains were often noted due to lack of a clear description and reason for inclusion and exclusion of specific confounders or due to inadequate analyses techniques. Based on the risk of bias results, all 10 articles were screened and included in the full systematic review.

Figure 2:

Figure 2:

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Risk of Bias

Effect Measure Modification

Air Pollution and Physical Activity Interaction: Protective Health Effects

Among the included articles, two indicated potential beneficial EMM between air pollution and physical activity (Table 1, Supplement Table S3), indicating an overall benefit of physical activity, regardless of air pollution exposure. The first article included a cross-sectional study conducted among African American and Dominican children from the Colombia Center for Children’s Environmental Health Birth Cohort (Lovinsky-Desir et al. 2017). This study evaluated forkhead box p3 (FOXP3) promoter methylation, which regulates the suppression of the immune response in the T regulatory pathway, and physical activity. A reduction in FOXP3 promotor 2 methylation was more likely to be observed among active vs. inactive children with higher BC exposures, indicating that physical activity may activate a protective immunologic benefit among children exposed to higher concentrations of BC (Lovinsky-Desir et al. 2017). In addition, an article by Gui et al (2020) evaluated the association between air pollution exposure and executive function in Chinese children. This study reported no statistically significant interactions between air pollution, physical activity, and executive function, but stratified analyses suggested that increased physical activity may be beneficial for improving executive function among children, even for children with relatively higher exposure to environmental pollution.

Air Pollution and Physical Activity Interaction: Detrimental Health Effects

In contrast, five studies noted no increased benefits (n=3), and some evidence of detriments (n=2), from increased physical activity when in areas of higher air pollution. Three articles suggested that the benefits of physical activity were diminished in areas of higher concentrations of air pollutants. Two cohort studies assessing cardiopulmonary fitness (VO2max) (Gao et al. 2013; Yu et al. 2004) and complete speed (Gao et al. 2013) reported that in areas with relatively lower concentrations of air pollution, increased physical activity had a positive association with cardiopulmonary fitness. However, in areas with relatively higher concentrations of air pollution there was no difference in cardiopulmonary fitness with increased physical activity, indicating that higher exposure to air pollutants negated any positive effect of increased physical activity. Similarly, a study evaluating airway inflammation (Lovinsky-Desir et al. 2016) among African American and Dominican children in the US indicated that while increased physical activity was associated with a reduction in airway inflammation in children with personal exposures to lower concentrations of BC, there was no association with a reduction in airway inflammation among children with relatively higher personal exposures to BC (>1,790 ng/m3). However, the interaction between BC, physical activity, and airway inflammation was not statistically significant.

Two studies indicated a detrimental health effect with increased physical activity. A cross-sectional study in Indonesia among overweight and obese adolescents indicated that active adolescents had an increased odds of elevated plasma glucose for each 1 μg/m3 increase in PM2.5 compared to those with less activity (Yu et al. 2020). Additionally, a prospective cohort by McConnell et al (2002) evaluated the relationship between different measures of air pollution and the development of asthma among adolescents, stratified by the number of sports played. This study reported that in communities with lower O3 concentrations, the number of sports played had no impact on incident asthma; however, in higher ozone communities, the odds of incident asthma increased among the most active children (≥3 sports played).

Air Pollution and Physical Activity Interaction: Null Health Effects

While the majority of the studies included in this review (n=7) indicated some form of EMM, there were some studies (n=3) that reported no substantial difference in physical activity level between air pollution and a health outcome among children and adolescents. A study by Thiering et al (2016) evaluated the association between several air pollutants (PM2.5, PM10, NO2) and insulin resistance (HOMA-IR), among German children, stratified by physical activity level. While the study observed an association between NO2 and PM10 exposure and increased insulin resistance, physical activity did not modify this effect. Similarly, a study by Zhang et al (2021b) assessed the association between air pollutant (NO2, PM10, PM2.5, PM1) exposure and obesity among Chinese boys and girls, but did not observe differences in the association when stratified by self-reported outdoor exercise frequency. Another study among Chinese children evaluated air pollution exposure and metabolic syndrome. This study indicated that the association between air pollution (PM10, PM2.5, PM1, NO2) exposure and metabolic syndrome did not differ by outdoor exercise frequency (Zhang et al. 2021a).

Discussion

The aim of this review was to evaluate EMM between physical activity and exposure to air pollutants and to ultimately evaluate if physical activity in polluted air confers additional health benefits among children and adolescents. Several studies indicated that active children tended to have worse health outcomes in locations with relatively higher air pollution (Gao et al. 2013; Lovinsky-Desir et al. 2016; McConnell et al. 2002; Yu et al. 2004; Yu et al. 2020), implying that air pollution effects may overwhelm the benefits of being active among minors. However, a few studies indicated either beneficial effects (Gui et al. 2020; Lovinsky-Desir et al. 2017) of physical activity, while others indicated no difference among active and inactive groups (Thiering et al. 2016; Zhang et al. 2021a; Zhang et al. 2021b), even in high pollution environments. While there were some similarities between studies, many of these studies evaluated air pollution and physical activity differently from one another, making direct comparisons difficult (Table 1, Supplement Table 3).

Previous research has indicated that children may be at greater risk from exposure to particulate matter compared to adults (US Environmental Protection Agency 2019). First, children’s respiratory systems are still developing and exposure to air pollution can negatively impact this period of developmental growth. Second, children have greater ventilation rates and often spend more time outdoors which can increase their exposure to air pollutants. Third, children also tend to be ‘oral breathers’. It has been previously demonstrated that during nasal breathing the nasal passages can help with filtration and therefore reduce air pollutant concentrations that reach the lungs. Oral breathing bypasses the nasal passage, causing a greater amount of pollutants to reach further into the lung (Bateson and Schwartz 2007). Exercise also increases oral breathing which can further lead to pollutants entering the lung (Carlisle and Sharp 2001).

Physical Activity Definition and Location

There are many ways to define physical activity. The WHO recommends that children and adolescents (5-17 years) engage in ≥ 60 minutes per day of moderate to vigorous intensity physical activity along with vigorous intensity aerobic and muscle/bone strengthen activities ≥ 3 days per week. (World Health Organization 2020). Half of the included studies indicated ‘active’ children in accordance with this WHO definition. Those that did not use the WHO definition either considered a lesser frequency of activity (≥ 30 minutes, 3x/week) (Gao et al. 2013; Yu et al. 2004), outdoor exercise frequency (Zhang et al. 2021a; Zhang et al. 2021b), or relied on using the number of sports played per week (McConnell et al. 2002) as a proxy for designating ‘active’ children.

Intensity of physical activity may also play a role in the relationship between air pollution and physical activity. In a previous review of the short-term impacts of physical activity during periods of high air pollution exposure, DeFlorio-Barker et al 2020 indicated there was evidence that high intensity physical activity may neutralize the short-term impacts of air pollution, mainly among healthy adults. This level of information was not consistently provided within the included studies. Therefore, it is unclear if the typical intensity of physical activity has any impact on health outcomes that may be a result of exposure to higher levels of air pollution. However, there are clear indicators that higher intensity, frequency, and duration of physical activity has additional health benefits among children and adolescents (Wu et al.2021).

In addition to considering activity levels among children, some studies specifically evaluated children and adolescents engaged in outdoor activities or sports. Two recent studies conducted in China evaluated outdoor exercise frequency and noted no EMM (Zhang et al. 2021a; Zhang et al. 2021b). These studies specifically aimed at assessing activities where children and adolescents would be more likely exposed to air pollution. While this is an important area of study, our aim was to evaluate EMM between air pollution exposure and health outcomes among children and adolescents regularly participating in physical activity. Since these studies did not consider indoor physical activity, there may have been misclassification of ‘active’ status. Another study by McConnell et al (2002) suggested that an increased number of sports was associated with a greater risk of developing asthma. While this study did not indicate specifically if sports were taking place indoors or outdoors, there is an assumption that the majority of sports played would be outdoors. Therefore, this increase in incident asthma could be the result of a greater exposure to air pollution. It is difficult to disentangle if this increase in incident asthma was based on their increased activity, thus implying EMM, or if these children are simply at a different place on the exposure curve. Additionally, it is unclear if any of the participants in the included studies, changed their physical activity behaviors based on current air quality conditions. In areas of higher pollution, if current air quality is checked and activities were moved to periods of better air quality during the day, that could lead to exposure misclassification.

Health Endpoint Differences

The included studies encompassed a range of health endpoints. In some cases, similar conclusions were drawn from several studies with the same health endpoint. Specifically, two studies evaluating cardiopulmonary fitness indicated that being more physically active does not offer increased benefits in areas of relatively higher polluted air (Gao et al. 2013; Yu et al. 2004). Four studies evaluated metabolic outcomes among children and adolescents, including insulin resistance (Thiering et al. 2016), metabolic syndrome (Zhang et al. 2021a), obesity (Zhang et al. 2021b), and fasting plasma glucose (Yu et al. 2020). Three of these studies, among healthy children and adolescents (Thiering et al. 2016; Zhang et al. 2021a; Zhang et al. 2021b), indicated no evidence of EMM. However, the study by Yu et al (2020) suggested that, among obese or overweight adolescents, more active individuals were more likely to have higher fasting plasma glucose levels, compared to those who were less active. There may be some indication that modifying effects are different for those with underlying health conditions; however, more information in this area would be useful.

Exposure Differences

The 10 included articles considered air pollution exposure in several ways. Two articles by Lovinsky-Desir (2016, 2017) evaluated personal exposures to BC. These studies indicated that physical activity was beneficial in high BC when considering FOXP3 methylation (Lovinsky-Desir et al. 2017), but that physical activity was detrimental when considering airway inflammation as the outcome (Lovinsky-Desir et al. 2016). Rather than evaluating associations between individual pollutants, three studies, all of which identified EMM, considered higher vs. lower pollution districts or communities (Gao et al. 2013; McConnell et al. 2002; Yu et al. 2004). The remaining articles considered associations with individual pollutants. While it is expected that higher air pollution levels would correspond to worsening health outcomes, due to the few studies assessed within this review, it is difficult to ascertain any exposure-response relationships between air pollution and health outcomes among those who regularly exercise.

Strengths and Limitations

Many of the studies included in this review have relatively large sample sizes, which can aid in the detection of true statistical interaction. Almost all of these studies were conducted on healthy populations of children and adolescents, with the exception of a study on obese or overweight adolescents (Yu et al. 2020). Children and adolescents with pre-existing conditions are more likely to suffer negative consequences from exposure to air pollution compared to those without pre-existing conditions. Specifically, the current science suggests that children with asthma are more likely to experience asthma exacerbations when exposed to high levels of air pollutants (Orellano et al. 2017).

While there has been a large influx in publications related to the intersection between air pollution and physical activity (Figure 1), there remains a paucity of studies specific to children and adolescents. The majority of the studies included in the current review have low risk of bias (classified as either ‘High’ or ‘Medium’ overall confidence). Most commonly, studies were downgraded due to lack of sufficient explanation of included or excluded potential confounders. One study was downgraded to ‘Low Confidence’ due to deficiencies in analyses that could bias the reported relationship (inclusion of missing data category in final statistical model).

This systematic review was designed to evaluate EMM or interaction within studies. Identifying potentially stratified results during a literature search can be challenging, especially if stratified results were null or if there was no statistical significance. While our search was thorough, some stratified results could have been missed during our literature search.

The research reviewed herein examines interactions of air pollution and general physical activity in children. There are many questions surrounding this topic that are important to consider, that are not answered within this work. For example, the question of at what level air pollution overwhelms any benefits from being physically active. At this point, there is not enough information to indicate if increases in physical activity would provide additional benefit for children and adolescents in areas of high air pollution. However, the benefits of physical activity should be considered in light of the risks of exposure to air pollution. Relatedly, the question of how physically active children and adolescents fair in extreme air pollution events such, as wildfires and wildfire smoke events, is not addressed in the reviewed literature, but is of increasing importance with the implications of climate change.

Conclusions

The majority of included studies indicates that more active children do not gain additional health benefits in high pollution environments. However, this finding was not consistent across all studies. It appears that active children are more vulnerable to some specific health effects of air pollution, which has the potential to have long-term consequences (Prunicki et al. 2021). Currently, very little research has been conducted on the effect of regular physical activity and outdoor air pollution among children and adolescents with pre-existing conditions. While regular physical activity is beneficial for overall health, extra considerations should be taken for active children and for those with pre-existing conditions, especially in areas with elevated levels of air pollution. Future investigations of the intersection between physical activity, air pollution, and health endpoints would be useful for disentangling the benefit or decrement of exercise in air pollution. Specifically, research that aims to identify how changes or restrictions in physical activity among active children and adolescents during extreme air pollution events can help determine future public health priorities.

Supplementary Material

Supplemental File

Funding source

This research did not receive any external funding.

Footnotes

Disclaimer: The views expressed in this manuscript are those of the individual authors and do not necessarily reflect the views and policies of the U.S. Environmental Protection Agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

Conflicts of interests

The authors indicate there are no conflicts of interest

Availability of data and materials

PDFs of articles included for data extraction and raw extraction data tables can be provided by the authors upon request.

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Associated Data

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Supplementary Materials

Supplemental File
NIHMS1887183-supplement-Supplemental_File.docx (57.5KB, docx)

Data Availability Statement

PDFs of articles included for data extraction and raw extraction data tables can be provided by the authors upon request.

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