Short-Term Exposure to Wildfire Smoke and ${\mathrm{PM}}_{2.5}$ and Cognitive Performance in a Brain-Training Game: A Longitudinal Study of U.S. Adults

Wildfire smoke is a complex mixture of particulate matter (PM) and gases containing many chemical species.¹ Both wildfire smoke and many of its components have been previously associated with significant risks to human health (as reviewed by Reid et al.²). Of wildfire emissions, the primary pollutant of public health concern is fine PM [PM $\le 2.5\mathrm{\mu }\mathrm{m}$ in aerodynamic diameter (${\mathrm{PM}}_{2.5}$)] (as reviewed by U.S. EPA³). In addition to the extensive body of epidemiologic evidence that daily and subdaily (hourly level)⁴ exposure to ${\mathrm{PM}}_{2.5}$ and smoke increases the risk of all-cause mortality and cardiovascular and respiratory morbidity (as reviewed by Atkinson et al.⁵ and Jaffe et al.¹), newer epidemiologic research has found that ${\mathrm{PM}}_{2.5}$ exposure may also adversely impact cognitive function (as reviewed by Clifford et al.,⁶ Delgado-Saborit et al.,⁷ and Xu et al.⁸). The aim of this study was to further investigate the associations between exposure to ${\mathrm{PM}}_{2.5}$ and wildfire smoke and cognitive performance. This is a pressing research question because exposure to ${\mathrm{PM}}_{2.5}$ is ubiquitous, often elevated during wildfire events,¹ and likely to increase with the frequency and intensity of wildfires under climate change.^9–12

Current epidemiologic research has identified ${\mathrm{PM}}_{2.5}$ as a risk factor that can impair cognitive function, accelerate cognitive decline, and increase rates of dementia and Alzheimer’s, especially in younger and older populations (as reviewed by Clifford et al.,⁶ Delgado-Saborit et al.,⁷ and Power et al.¹³). In addition to the epidemiologic literature, there is a growing body of research from animal and human studies that identifies the biological pathways and mechanisms by which air pollution likely impacts neurological health and cognitive function. It shows that ${\mathrm{PM}}_{2.5}$ can cause systematic inflammation, reach the brain via the olfactory nerve, pass through the blood–brain barrier, or modulate the nervous system, leading to brain inflammation and oxidative stress (as reviewed by Delgado-Saborit et al.,⁷ Schikowski and Altuğ,¹⁴ and U.S. EPA³). Although epidemiologic evidence of the relationships between long-term exposure to ${\mathrm{PM}}_{2.5}$ and cognitive function is mounting, evidence for short-term exposure is still scarce. The small number of studies that focused on short-term associations have found ${\mathrm{PM}}_{2.5}$ exposure at the monthly, weekly, and daily level to be associated with increased risk of hospital admissions for neurological disorders^15–18 and poorer performance on cognitive tests measuring attention, memory, and fluid reasoning, as well as language, math, and reading skills.^19–25 However, there is limited epidemiologic evidence of the associations with subdaily exposure²⁶ and the associations in the working-age population,²³ and, to our knowledge, no evidence of the subdaily associations across multiple age groups or at lower level concentrations, which is largely due to limited availability of data on health outcomes and cognitive performance at the hourly timescale.

Although ${\mathrm{PM}}_{2.5}$ is a main component of wildfire smoke, the particles have a different composition from typical ambient ${\mathrm{PM}}_{2.5}$, and smoke also contains toxic chemicals and gases, which may lead to differential health effects compared with typical ambient ${\mathrm{PM}}_{2.5}$.^27,28 Previous research has found agricultural fires and open fire usage indoors to be associated with reduced performance on neurocognitive tests.^29–31 Although these studies indicate a potentially important association with biomass smoke, to our knowledge, no study to date has investigated the relationship between wildfire smoke exposure and cognitive function. Because concentrations of ${\mathrm{PM}}_{2.5}$ and smoke can change rapidly over days and hours during wildfire events and given that wildfires pose a growing threat to air quality and public health,¹ research is needed to assess how daily and subdaily exposure to ${\mathrm{PM}}_{2.5}$ and smoke impact cognitive performance and the populations most at risk.

To address these knowledge gaps, we evaluated the associations between short-term ${\mathrm{PM}}_{2.5}$ and wildfire smoke exposure and cognitive function in a large adult cohort across the contiguous U.S. We measured cognitive performance using data from the Lumosity brain-training platform, which consists of games aimed to measure and improve areas of cognitive function, including memory, attention, flexibility, processing speed, and problem solving. We used a longitudinal repeated measures study design to characterize associations between scores in an attention-oriented Lumosity game, and daily and subdaily ${\mathrm{PM}}_{2.5}$ and wildfire smoke exposures. We evaluated these associations by age, gender, user behavior, and region to identify vulnerable populations. Although many research efforts have identified serious cardiopulmonary effects of short-term ${\mathrm{PM}}_{2.5}$ and wildfire smoke exposure, neurological impacts can be more challenging to study because the time between exposure and outcome is often undefined. To our knowledge, this is one of the first epidemiologic studies to use Lumosity data to investigate the associations between short-term air pollution exposure and cognitive performance. It is also the first to investigate these relationships at both the daily and hourly timescale in a large, longitudinal cohort of adults $\ge 18\text{\hspace{0.17em}years}$ of age.

We found evidence of significant associations between short-term exposure to ${\mathrm{PM}}_{2.5}$ and wildfire smoke and decreased attention in adults, as measured by Lumosity’s Lost in Migration game. Exposure to ${\mathrm{PM}}_{2.5}$ at the daily and hourly level were associated with a reduction of more than 20 points in attention score per $10{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ of ${\mathrm{PM}}_{2.5}$. Likewise, exposure to heavy or medium smoke density at the daily and weekly level were associated with a reduction of $>100$ points in attention score relative to no smoke.

Using the estimated association at lag 0, we can compare users’ predicted scores at the observed ${\mathrm{PM}}_{2.5}$ concentrations with their predicted scores in the absence of ${\mathrm{PM}}_{2.5}$, concentrations of $0{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$. By doing so, we estimate that western U.S. users lost on average a total of 887 (95% CI: 86, 1,688) points over 20 plays, with an average 40- to 50-point loss for each play, due to same-day ${\mathrm{PM}}_{2.5}$ exposure. The estimated loss of 887 points from the average 20th play score of 14,317 points corresponds to a 6.2% (95% CI: 0.6%, 11.8%) reduction in final score associated with ${\mathrm{PM}}_{2.5}$. Further, assuming no multiplier bonus is applied, an 887-point loss is equivalent to $\sim 18$ fewer correct answers over 20 plays. In comparison, we estimate contiguous U.S. users lost on average 529 (95% CI: 98, 960) points [3.7% (95% CI: 0.7%, 6.7%) reduction in 20th play score and $\sim 11$ fewer correct answers] over 20 plays due to ${\mathrm{PM}}_{2.5}$.

The strongest associations with ${\mathrm{PM}}_{2.5}$ were observed within a short exposure window, showing that ${\mathrm{PM}}_{2.5}$ is associated with reduced attention within 3 h of exposure. Although we were unable to evaluate the impacts of subdaily exposure to wildfire smoke, the strongest associations were also observed within a short exposure window of $\le 2\mathrm{d}$. Because the ${\mathrm{PM}}_{2.5}$ associations were driven by hourly and same-day exposure, we hypothesize that the relationships between short-term variations in ${\mathrm{PM}}_{2.5}$ and cognitive performance, such as those experienced during wildfire smoke episodes, may be transient. However, given that we observed associations at ambient concentrations typically experienced in U.S. communities in the absence of extreme air pollution events, it is likely that long-term exposure also has implications for cognitive function. Such associations have been observed in recent epidemiologic studies identifying the chronic cognitive impacts of sustained exposure,^64–67 but further research into the links between extended ${\mathrm{PM}}_{2.5}$ and wildfire smoke exposure and cognitive performance is needed.

In addition to varying by exposure duration, the associations of ${\mathrm{PM}}_{2.5}$ with attention were also more pronounced in the western U.S., with the magnitude of association nearly double that of the contiguous U.S. This may be due in part to geographic differences in the sources and chemical composition of ${\mathrm{PM}}_{2.5}$.⁶⁸ Wildfires are a significant source of ${\mathrm{PM}}_{2.5}$ in the western U.S., which can affect the toxicity of the particles and may modify their associated health effects.^27,28,69 The other physical and mental health effects of wildfire events may also play a role. For example, eye irritation^70,71 could impact the ability of users to effectively interact with mobile devices, and increased anxiety^72,73 could affect the ability to focus. The observed associations with both ${\mathrm{PM}}_{2.5}$ and smoke density in the western U.S. provide evidence that individuals living in wildfire-impacted regions may be more vulnerable to the cognitive impacts of air pollution. This vulnerability may be further exacerbated as ${\mathrm{PM}}_{2.5}$ concentrations in areas affected by wildfires increase under climate change.^9,10,74

Further, although the differences were not statistically significant, habitual users had stronger associations with both smoke and ${\mathrm{PM}}_{2.5}$ exposure than nonhabitual users. This is potentially due to behavioral differences between the groups. Because habitual users train more frequently, their decision to play may be less dependent on environmental conditions and their short-term variations in exposure may be better represented with areal averages when compared with more sporadic users. In addition, the moderate sensitivity of the results to the user inclusion criteria could also be due to differences in user behavior. Prior research has found that Lumosity users who drop out early tend to exhibit poorer performance and shallower learning trajectories, potentially due to lower motivation or less desire to continue playing.⁷⁵ Although it is not fully clear how lower motivation to play impacts the associations between ${\mathrm{PM}}_{2.5}$ and smoke and Lumosity performance, the observed attenuation may be due to stronger exposure misclassification in users with less predictable patterns of behavior or the suppression of scores in users with less desire to play. However, all possibilities for the cause of any user behavior-related differences will be unknown until Lumosity data is used more broadly in a research context.

Our findings are largely consistent with existing epidemiologic research. Prior studies have identified associations between daily ${\mathrm{PM}}_{2.5}$ concentrations and poorer cognitive performance, as measured by Lumosity performance²³ and Mini-Mental State Examination (MMSE),²¹ global cognitive function,²¹ fluid reasoning,²⁴ and standardized test scores.^19,20,22,25 However, this analysis did not have the power to detect a nonlinear association as was reported by some prior studies.^21,23,24 Although there is very limited research on the relationships between cognitive function and subdaily exposure, one study with 63 participants identified an association between hourly exposure to PM via outdoor commuting and candle burning and reduced MMSE performance.²⁶ In addition, although differences between age groups were not statistically significant, younger and older users having stronger associations with exposure aligns with existing research linking ${\mathrm{PM}}_{2.5}$ to reduced academic and cognitive performance in youth and accelerated cognitive decline in older adults (as reviewed by Clifford et al.⁶). The only other study that has used Lumosity data to investigate how daily ${\mathrm{PM}}_{2.5}$ varies with cognitive performance did not report significant associations among older users, but they did find younger users to be more impacted.²³ Finally, although no prior epidemiologic study has examined the association between wildfire smoke density and cognitive performance, our results are generally consistent with other studies that identified associations between agricultural fires and open fire usage and decreased cognitive function, as measured by MMSE,²⁹ word recall,^29–31 and mental intactness^30,31 tests.

Our study has many strengths, the first of which is the repeated measures study design. The Lumosity data set provided detailed, longitudinal measurements for a large adult population, enabling us to conduct one of the first large-scale studies of the links between short-term ${\mathrm{PM}}_{2.5}$ and wildfire smoke exposure and cognitive function. This allowed us to overcome some of the limitations associated with clinical or laboratory studies, which can be time and cost intensive with a limited number of participants. In addition, because the data set provided repeat measures for over 10,000 diverse users across the contiguous U.S., we were able to identify significant associations in the larger working-age population. Another notable strength is our use of BME data fusion to estimate ${\mathrm{PM}}_{2.5}$ concentrations. Most such studies rely solely on data from the closest monitoring station to inform exposure.^19–25 By fusing observations from both FRM/FEM and PurpleAir monitors, we were able to increase the spatial coverage of observations and get more information on ${\mathrm{PM}}_{2.5}$ exposure at the hourly and daily level while still accounting for the uncertainty in the PurpleAir measurements. Further, by population-weighting the ${\mathrm{PM}}_{2.5}$ estimates to the ZIP3 level, we were able to account for the spatial distribution of the population and give proportionally greater weight to the ${\mathrm{PM}}_{2.5}$ experienced in the most densely populated regions. This approach likely generated estimates that were more representative of exposure than taking a simple spatial average. Finally, an important strength of this study was the ability to investigate associations with subdaily ${\mathrm{PM}}_{2.5}$ exposure. Most epidemiologic studies on the health effects of ${\mathrm{PM}}_{2.5}$ and wildfire smoke have focused on 24-h average exposure (as reviewed by Reid et al.² and Atkinson et al.⁵), often because data on health outcomes are only available at the daily timescale.⁴ By identifying how quickly changes in hourly ${\mathrm{PM}}_{2.5}$ concentrations are linked to decreased cognitive performance, our findings may be useful for time-sensitive public health decision-making processes during extreme air pollution events, such as wildfires.

This study is not without limitations. First, performance on the Lumosity platform is not a clinical measure of cognitive function. Use of Lumosity has been associated with improved performance in other neuropsychological tests,^{35,36,76–78} and brain-training games can improve performance on tasks involving similar cognitive domains (as reviewed by Simons et al.⁷⁹ and Smid et al.⁸⁰). In addition, Lost in Migration scores have been used in other studies as a measure of attention,^23,39 and the cognitive focus of Lumosity games has been characterized.³⁴ However, it is unclear whether changes Lumosity scores have generalizable impacts on everyday learning and cognitive tasks. Second, there is the possibility of exposure misclassification. The analyses were conducted at the ZIP3 level, which is a relatively coarse resolution for studying the impacts of ${\mathrm{PM}}_{2.5}$ and smoke given that concentrations and density can change rapidly over short distances. In addition, we assumed that users did not move and completed all plays at their sign-up ZIP3 location. It is very possible that users, especially those using mobile devices, played Lost in Migration in different ZIP3s during their 20 plays, which would lead to nondifferential exposure misclassification and attenuation of the true associations toward the null. This is especially true in regions with higher variability in ${\mathrm{PM}}_{2.5}$ concentrations within a ZIP3, such as in the western U.S. (Figure S5). In addition, the visibility on smoke days may influence a user’s movement and in turn their performance or decision to play. Although this is difficult to verify with the current data, we confirmed that 6,668 plays occurred on 409 smoke days in 96 ZIP3s. In comparison, 6,716 plays occurred on the 508 nonsmoke days in the week prior to a smoke day in same ZIP3s. This leads us to believe that a user’s decision to play is likely not influenced by the presence or visibility of smoke. Third, the inclusion of paid subscribers in the cohort did not constitute a random sample. The Lumosity brain-training games are promoted as tools aimed to improve cognitive abilities and it is unclear how the willingness to pay and motivation to play affects the direction and magnitude of the observed associations. This should be considered in future investigations. Fourth, we were unable to control for all individual-level factors, such as socioeconomic status, leaving the possibility of residual confounding. However, we were able to control for related confounders, such as education at the individual level and socioeconomic status at the ZIP3 level. In addition, given the relatively coarse spatial resolution of the Lumosity data set, we may have been unable to account for all spatial correlation present in the data. Further, although the results of the subgroup analyses are informative, showing more pronounced associations in younger (18–29 y), older ($\ge 70\mathrm{y}$), and male users, the differences between groups were not statistically significant. There was also a lack of precision for some of the subgroup estimates due to small sample sizes. Additional research using a larger study population is needed to clearly identify vulnerable subpopulations. Finally, the generalizability of our findings may be limited to adults with similar demographics to our study population who use brain-training games, such as Lumosity.

Despite these limitations, our findings help expand the knowledge base on the cognitive function risks posed by poor air quality. This is one of the first epidemiologic studies to identify the link between daily and subdaily ${\mathrm{PM}}_{2.5}$ exposure and cognitive performance in the working-age population and to show that ${\mathrm{PM}}_{2.5}$ is associated with reduced attention within hours of exposure. It is also the first to identify an association between wildfire smoke density and decreased cognitive performance. Further, we show that Lumosity data can be a useful tool for investigating the associations between environmental exposures and cognitive function. The platform provides cognitive performance data for a large population using controlled and repeated games that can be combined with appropriate statistics to conduct robust epidemiologic research. Future work could include expanding analyses to Lumosity games beyond Lost in Migration that target cognitive domains other than attention. In addition, research using Lumosity data over a longer duration could enable the investigation of the short- and longer-term impacts of exposure in tandem. Research considering the interaction between wildfire smoke and ${\mathrm{PM}}_{2.5}$ could also be informative given that ${\mathrm{PM}}_{2.5}$ is likely on the causal pathway between smoke exposure and cognitive performance and that prior studies have found PM-health associations to be more pronounced on smoky days,⁸¹ possibly because of very high concentrations, PM composition, or coexposure with gaseous pollutants. Finally, additional research into the associations between short-term ${\mathrm{PM}}_{2.5}$ and wildfire smoke exposure and cognitive function using different measures of cognitive performance and in other wildfire-impacted regions would be valuable to validate our findings and further elucidate these relationships.

We thank Lumos Labs, Inc., for making the deidentified Lost in Migration data set available for research purposes through the Human Cognition Project and for their continued collaboration and guidance. We also thank A. Patil for her assistance with the fine particulate matter (${\mathrm{PM}}_{2.5}$) and meteorological data sets. This project was supported by an appointment (of S.E.C.) to the Research Participation Program at the Center for Public Health and Environmental Assessment, U.S. Environmental Protection Agency (EPA), administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and the U.S. EPA. The Bayesian Maximum Entropy data fusion estimates of daily and hourly average ${\mathrm{PM}}_{2.5}$ at census tract population centers can be downloaded at https://doi.org/10.15139/S3/Z9WSWC. The ZIP3 (first three digits of a ZIP code)-level daily maximum smoke density and population-weighted daily and hourly average ${\mathrm{PM}}_{2.5}$ exposure data can be downloaded at https://doi.org/10.23719/1523337. All results for the primary and sensitivity analyses conducted, as well as maps of the exposure surfaces and additional information on the Lumosity data set, can be viewed online at https://ehs-bccdc.shinyapps.io/PMSmoke_Attention_Dashboard/. Although this work has been reviewed for publication by the U.S. EPA, it does not necessarily reflect the views and policies of the agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

The authors declare they have nothing to disclose.