Faculty Mentor: David Curtis (Family & Consumer Studies, University of Utah)

Exposure to air pollution has been associated with increased risk of respiratory diseases (Xing et al. 2016). However, not all people are affected to the same degree by air pollution. With that in mind, this research project aims to understand whether the health risks of air pollution vary by occupation and occupational factors. Specifically, we examine how occupational group moderates the associations between the fine particulate matter (PM2.5) concentration and the prevalence and incidence of respiratory disease. We also investigate occupational factors (i.e., job strain, outdoor work environment, occupational status) as potential moderators in the associations. We used two waves of data from the MIDUS (Midlife in the U.S.) study, which collected longitudinal information on health and the aging process on a national sample of adults in the U.S. Our sample consisted of employed adults between the ages of 30 and 64. Exposure to PM2.5 concentration was determined based on the annual average of PM2.5 in the census tracts of residence from 2001-2005 and 2006-2010 (data from the Center for Air, Climate and Energy Solutions (CACES)) (Kim et al., 2020). The respiratory disease outcome was a self-reported measure. Occupations, based on participants’ selfreports, were classified as: 1) Professional and Managerial, 2) Administrative, 3) Sales, 4) Services, and 5) Manual. Linear probability models were used to examine the research questions. Our findings indicate that, relative to professionals, participants in administrative occupations had a lower incidence of respiratory diseases. Additionally, the association between PM2.5 and the incidence of respiratory diseases, but not prevalence, was stronger for participants in sales and service occupations compared to professionals. In addition, we found that the effect of PM2.5 on respiratory diseases did not vary by occupational factors. Finally, occupational factors did not predict different levels of respiratory disease outcomes, although greater job strain was associated with increased prevalence.

This research study was part of a larger cohort, HAPPIEST (Health, Air Pollution, and Population Initiative in Education and Science Training), in which different teams and mentors were involved in an air pollution research initiative. Our team’s specific focus was on air pollution, health outcomes, and socio-economic factors. It was amazing to be part of this cohort, as we were able to meet mentors and fellow undergraduate students from different departments, learn together, and support each other in our projects. I also had the chance to learn more about graduate school and academic life from graduate students who were part of the cohort, which was incredibly valuable information as I move forward and get closer to graduating.

Furthermore, this research provided many opportunities to improve research, critical thinking, and communication skills, as well as to get to know different people and make amazing connections. With our project, we also had the chance to walk through the process of doing research and writing a research article step by step—it was an intense experience. One of the challenges that I faced was the time constraint to accomplish everything we aimed to in a short period of 10 weeks. This made all the steps of the process very fast-paced and required a lot of time and effort. Personally, the moment I learned the most from was when we ran our data analysis and found that most of the results were not in agreement with our initial predictions. It was a great opportunity to better understand the research process and how not everything will work the way I expected it to, and that is simply part of the process. Lastly, I also had the chance to connect with my lab partner and my mentors, to whom I am very grateful for all the support and guidance throughout this project.

References

Kim S.-Y., Bechle, M., Hankey, S., Sheppard, L., Szpiro, A. A., Marshall, J. D. (2020). “Concentrations of criteria pollutants in the contiguous U.S., 1979 – 2015: Role of prediction model parsimony in integrated empirical geographic regression.” PLoS ONE 15(2), e0228535. https://doi.org/10.1371/journal.pone.0228535

Xing, Y.-F., Xu, Y.-H., Shi, M.-H., & Lian, Y.-X. (2016). The impact of PM2.5 on the human respiratory system. Journal of Thoracic Disease, 8(1), E69–E74. https://doi.org/10.3978/j.issn.2072-1439.2016.01.19nk