Effect Modification of Prenatal Exposure to Ambient Air Pollution and Childhood Asthma Incidence

1. Effect Modification of Prenatal Exposure to Ambient Air Pollution and Childhood Asthma Incidence Éric Lavigne, PhD June 14th, 2017 BC Lung Association Air Quality Webinar

2. State of knowledge • Air pollution affects population subgroups differently • Children, pregnant women and elderly persons represent susceptible groups • Air pollution & pregnancy • During pregnancy, anatomical and physiological changes occur and are necessary for successful gestation • Various studies indicate associations between gestational exposure to air pollution and poor fetal outcomes • Preterm birth • Low birth weight

3. Possible biological mechanisms by which air pollutants may affect birth outcomes Source: Slama et al. Envrionmental Health Perspective, 2008, 116(6):795

4. State of knowledge Prenatal exposure to air pollution and adverse birth outcomes • Consistent for the association with low birth weight • More mixed for premature birth Sources: Dadvand et al., 2013; Stieb et al., 2012; Shah et al., 2011

5. State of knowledge Prenatal exposure to air pollution and chilldhood respiratory morbidity • Air pollution during pregnancy appears to affect lung function measures during childhood • forced expiratory volume 1 second (FEV1) • forced vital capacity (FVC) • peak expiratory flow (PEF) (Korten et al., 2017)

6. State of knowledge Prenatal exposure to air pollution and chilldhood respiratory morbidity • Suggestive evidence regarding the development of asthma during childhood • Investigation of effect modifiers might provide insights into those most susceptible (e.g. maternal asthma) • Lack of information on concentration-response curves

7. POWERPOINT TITLE GOES HERE USING: VIEW > HEADERS AND FOOTERS

8. Objectives Research objectives • To evaluate the associations between exposures during pregnancy to air pollution (NO2 & PM2.5) & childhood asthma incidence • To examine whether these associations were modified by maternal history of asthma

9. Methods Study population & design • Retrospective cohort of pregnant women who gave birth to live born singleton infants in the Province of Ontario, Canada (2006 to 2012) • Data linkage to provincial admin databases (at ICES) • Outcome: childhood asthma < 6 years of age (using OASIS with validated case definition) • Exposures: PM2.5 (satellite-derived estimates at a 1 × 1 km resolution, single year, three-month running interval satellite surfaces) & NO2 (temporally scaled national land use regression (LUR) model)

10. Methods Summary of administrative data linkages

11. POWERPOINT TITLE GOES HERE USING: VIEW > HEADERS AND FOOTERS

12. POWERPOINT TITLE GOES HERE USING: VIEW > HEADERS AND FOOTERS

13. Methods Covariates & statistical analysis • Covariates: birth date, birth weight, infant sex, gestational age, maternal age at delivery, maternal cigarette smoking anytime during pregnancy, parity, maternal intention to breastfeed on discharge, maternal history of asthma, residential exposure to greenness, SES variables at neighborhood level • Statistical analysis: random-effects Cox proportional hazards models (spatial clusters at census division and census tract within census divisions) • effect modification by maternal asthma

14. Selected results: c-r curves Selected descriptive statistics • N = 761,172 • Asthmatic children = 110,981 • Mother’s with asthma = 45,443 (6.0%) • Average time from birth until asthma diagnosis = about 2 years • NO2 (per IQR in ppb) • IQRs = 9.6; 9.7; 9.5; 8.6 • PM2.5 (per IQR in µg/m3) • IQRs = 4.1; 3.9; 3.8; 3.7

15. Selected results: c-r curves

16. Selected results: c-r curves

17. Selected results: overall

18. Selected results: overall, with 1st year of life adjustment

19. Selected results: effect modification by maternal asthma (multiplicative scale)

20. Selected results: effect modification by maternal asthma Multiplicative scale interaction: p-value = 0.43 Relative excess risk due to interaction (95% CI) = -0.04 (-0.16 – 0.08)

21. Selected results: effect modification by maternal asthma Multiplicative scale interaction: p-value = 0.40 Relative excess risk due to interaction (95% CI) = 0.11 (0.02 – 0.21)

22. Discussion • Prenatal exposures to NO2 and PM2.5 were associated with increased risks of developing asthma • Suggestive evidence that children of mothers who have a history of asthma and who were in the upper quartile of exposure to NO2 during prenatal period were 1.7 times more at risk of developing compared to children of mothers without asthma and with NO2 exposure below the 25th percentile.

23. Discussion Air pollution during pregnancy and lung development in the child  Source: Korten et al. Paediatric Respiratory Reviews  , 2017, 21 (38-46

24. Discussion: air pollution & maternal asthma as an effect modifier • Mechanisms not well understood • Exposure to air pollution during pregnancy might lead to exacerbations of maternal asthma that translates into a higher susceptibility for the infant to develop asthma during childhood • inflammation pathway • Genetic susceptibility among those already sensitized

25. Discussion Implications of findings (Regulatory point of view) • These findings suggest that reductions in NO2 and PM2.5 exposure may reduce risk of childhood asthma in children of mothers with AND without asthma • Even at low level concentrations (such as those observed in Canada) effects are being observed

26. Discussion Implications of findings (Clinical point of view) • These findings suggest that maternal asthma modifies the relationship between NO2 and childhood asthma development • Clear advices should be given to pregnant women during pregnancy regarding their exposures to outdoor air pollution

27. Discussion Implications of findings - AQHI

28. Discussion Implications of findings - AQHI

29. Discussion Strengths & limitations • Limitations: • Lack of information on maternal obesity in pregnancy or maternal gestational weight gain • Did not have information on asthma phenotypes and asthma severity (e.g. medications) • High level of correlations between time windows • Stengths: • Large sample size, availability of air pollution exposure across a large geographical area, residential mobility and adjusting for many potential confounders

30. Discussion Nextsteps • Oxidative potential analysis (33 cities across ON) • Ultrafine particles analysis (Toronto) • Recommendations for future studies: • Refining exposure assessment for identifying critical windows

31. Aknowledgements • Marc-André Bélair & Daniel Rodriguez Duque (ICES) • Minh T. Do (PHAC) • David M. Stieb, Richard T. Burnett, Markey Johnson, Sabit Cakmak, (Health Canada) • Scott Weichenthal (McGill) • Perry Hystad (Oregon State University) • Aaron van Donkelaar & Randall V. Martin (Dalhousie U.) • Daniel L. Crouse (University of New Brunswick) • Eric Crighton (University of Ottawa) • Hong Chen (Public Health Ontario) • Paul J. Villeneuve (Carleton University) • Teresa To (Sick Kids & U of T) • Jeffrey R. Brook (Envionment Canada) • Abdool S. Yasseen III. & Mark Walker (BORN & Ottawa Hospital)

32. POWERPOINT TITLE GOES HERE USING: VIEW > HEADERS AND FOOTERS Thank youeric.lavigne@hc-sc.gc.caQuestions?