The SPC Online Journal Club is a live, online journal club for SER-SPC members. The journal club provides our members with the opportunity to discuss recent epidemiologic literature. Papers chosen for discussion in the journal club are focused on epidemiologic methods. Journal club sessions are led by one of the authors of the article. Members participate via chat and polls using the Clickmeeting software. Headphones are recommended. Please join us for our next session!
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January 15, 2020
April 15, 2020
July 15, 2020
October 21, 2020
Date: January 15, 2020
Time: 12:00 – 1:00pm EDT
Author: Dr. Erika Garcia
Article: “Association of Changes in Air Quality With Incident Asthma in Children in California, 1993-2014”
Erika Garcia, PhD, is a Postdoctoral Scholar in the Department of Preventive Medicine at the Keck School of Medicine of the University of Southern California. Her research focuses on the role of airborne environmental contaminants in the development of human disease. To better inform understanding of these relations, she applies both traditional epidemiologic as well as causal inference methodologies in her research. Her current research examines how early life exposure to ambient air pollution relates to pediatric respiratory health outcomes, including new-onset asthma, lung function, and fractional exhaled nitric oxide.
- Were you initially surprised that pollutant levels decreased over the study period? Do these trends align with other parts of the state of California or U.S. as a whole?
- How did the authors leverage the design of the Southern California Children’s Health Study and “secular trends in air pollution?” (p. 1907)
- How might assessing incident asthma among the children via first the parent and then self-report around 11 years alter the sensitivity and specificity of outcome ascertainment? Do you believe the associations are in actuality stronger or weaker than observed? Are might available data sources (e.g., medical record) verify diagnoses and inform a quantitative bias analysis?
- Physical activity was evaluated but modeled as a yes/no for participation in team sports. Do you suspect any residual confounding or misclassification driven by lifestyle factors?
- Discuss the heterogeneity of a) participant exposure to regional air pollution, collected by ambient air pollutant monitoring stations, as well as b) exposure to the inputs to the line source dispersion model (page 1908). Explain how effect modification was assessed “comparing nested models using…partial likelihood ratio test[s]” (p. 1908).
- Beyond those discussed (p. 1913) specify some time-varying confounders on the level of the individual (e.g. health behaviors) as well as community (e.g. sociodemographic residential composition) that could not be assessed in the current study.
- Consider the implications of the following on the presented results: a) imputing the asthma diagnosis date, b) having children with missing questionnaires contribute person-time until diagnosis or loss to follow up, and c) using 1994 data to account for unavailable data on temperature, PM2.5 and PM10 (p.1908).
- The authors do well in articulating how nitrogen dioxide may be “serving as a marker for the traffic-related air pollution” (p. 1912) as well as the “plausibility of a [specific] biological mechanism” (p. 1913). Discuss sources of random as well as systematic error that may partially explain the robustness of associations of asthma incidence that was found to be associated with nitrogen oxide but not other pollutants. Is there more potential for exposure misclassification for some pollutants versus others?
- Consider confounders associated with nitrogen dioxide as well as asthma incidence (e.g. low socioeconomic status). How could the biological mechanisms of such factors be assessed and analyzed in future work?
- Discuss the methodological and interpretative tradeoffs between assessing a threshold effect versus continuous levels of each pollutant. How might a mixtures approach be used to operationalize the effect of more than one exposure? Are the following likely: a) effect modification of pollutant effect by temperature or b) synergy between the joint effects of pollutants and temperature?
- The “10 AM to 6 PM mean for ozone [was calculated] due to its marked diurnal variation (1907).” Is peak pollutant exposure more clinically relevant than mean exposure for the development of asthma? Is diurnal variation as marked for the other pollutants? How might more detailed information on timing of exposure and outcomes alter the study findings?
- How might an ‘ideal’ study of this association with unlimited resources be conducted?
- The paper exemplifies several strategies to account for spatial confounding. What are some clinical and policy implications of these strategies in multilevel modeling for population health research?
Registration is now closed
Date: October 16, 2019
Time: 12:00 – 1:00pm EDT
Author: Dr. Sarah MacDonald, ScD, ScM
Senior Consultant Epidemiologist, IQVIA
Article: “Assessment of recording bias in pregnancy studies using health care databases: An application to neurologic conditions.”
MacDonald SC, Hernán MA, McElrath TF, Hernández-Díaz S. Assessment of recording bias in pregnancy studies using health care databases: An application to neurologic conditions. Paediatr Perinat Epidemiol. 2018 May ; 32(3): 281–286. doi:10.1111/ppe.12459. PMID 29569366