(Published in International Journal of Environmental Health Research. 2012 Jun;22(3): 249-69)

1. Prevalence of Childhood Asthma in the Haifa bay area and its links to Air Pollution by Particulate Matter: Evidence from GIS Analysis and Bayesian Model Averaging Boris A. Portnov Ph.D., DSc1, Benjamin Reiser2, KhaledKarkabi MD, MMH5,6, Orit Cohen-Castel MD, MMDSc5, and Jonathan Dubnov MD, MPH3,4 1 Department of Natural Resources & Environmental Management, University of Haifa, Israel 2 Department of Statistics, University of Haifa, Israel 3Haifa District Health Office, Ministry of Health, Israel 4School of Public Health, University of Haifa, Israel 5Department of Family Medicine, Haifa and Western Galilee District, Clalit Health Services 6Rappaport Faculty of Medicine, Technion – Israel Institute of Technology, Haifa, Israel (Published in International Journal of Environmental Health Research. 2012 Jun;22(3):249-69) יום עיון בנושא: "בריאות וסביבה: ראייה לאומית, התמודדות מקומית איכות אוויר במפרץ חיפה", 3 בספטמבר 2012, מלון הר הכרמל, דרך הים 103, חיפה

2. Childhood asthma as a major health problem • Asthma is characterized by a variable degree of airflow obstruction, bronchial hyper-responsiveness, and airway inflammation. • Childhood asthma often begins in early life and continues into adulthood, being exacerbated by weather changes, viral infections, and exposure to allergens and airborne pollutants. • High prevalence of childhood asthma is observed in most developed countries: New Zealand - 22.2%, USA 22.3%, Canada -18.2%, UK - 20.9%, Germany - 17.5%, Spain - 9.6%, and Israel - 7%). • Childhood asthma prevalence tend to increase in many developing nations at alarming rates: Poland - 10.2%, Mexico - 11.6%, Chile - 15.5%

3. Previous studies abroad • Several epidemiological studies reported significant health effects of ambient air pollution on children’s health, even at relatively low levels of air pollution exposure • Substantial evidence has been also accumulated to date linking the incidence of childhood asthma with traffic related air pollution and early life exposure to ambient air pollution • Exposure to Nitrogen Dioxide (NO2) and Ozone (O3), resulting from residential proximity to major thoroughfares and interacting with genetic factors, was also found to be associated with childhood asthma incidence in urban areas

4. Study population • Cohort of 3,922schoolchildren of the 1st through 8th grade (6-14 year old) residing in different residential communities of the GHMA, of who 540 children were diagnosed with asthma. • The children’s medical records were retrieved from the ‘Clalit’ Health Services database, which is the largest Health Maintenance Organization (HMO) in Israel that provides health care coverage for more than 54% of the GHMA population. • All schoolchildren in the 6-14 year old age group recorded (as of June 2009) in this database, and living within a radius of less than 500 meters from one of the 14 air quality monitoring stations (AQMSs) located in the study area, were covered by the analysis.

5. Air pollution levels • Air pollution data for the present study were obtained from 14 air quality-monitoring stations measuring half-hour mean concentrations of SO2and from 7AQMSalso measure half-hour concentrations of PM10. • In the analysis, average concentrations of these air pollutants were estimated for the period of 2006-2008, as arithmetic means of the AQMS half-hour measurements, and compared with the children’s health status in the first half of 2009, so as to allow for a latency period.

6. Individual exposure estimates • An indirect approach to estimating air pollution exposure, known as the ‘individual exposure estimates’ or IEE, which has became a popular research tool in recent years, was used in the present study. • According to this approach, the home addresses of children in the study cohort were geo-coded (that is, their home addresses were converted into X, Y coordinates), positioned on the map, and then superimposed upon SO2 and PM10 air pollution surfaces obtained by interpolation (IDW or kriging).

7. Study area and study population

8. Statistical analysis • Descriptive analysis: Childhood asthma prevalence were first compared with several environmental and demographic indicators (viz., air pollution, percent of children from families receiving welfare support, etc.). The analysis was performed separately for individual townships covered by the study. • Ordinary binary logistic regressions were run to identify and measure the relative strength of factors potentially affecting the prevalence of asthma in different loci of GHMA. • Last, Bayesian Model Averaging (BMA) was used to account for uncertainties associated with the model selection.

9. Descriptive statistics - results Country-wide average – 7%

10. Logistic models

11. Bayesian model averaging (Relative to Haifa) All negative except for Q.Yam

12. Sensitivity test 60 µg/m3 - permitted annual maximum Haifa Probability of asthma prevalence, %

13. Conclusions (I) • According to the results of the present analysis, the prevalence of asthma in our study area surpasses the rates of childhood asthma in the country as a whole by more than twofold: 16% vs. 7% (P <0.001). • In addition, the rates of childhood asthma are found to differ across communities forming the study area, ranging from 8.7% in QiryatTivon to 21.4% in Qiryat Yam. • The study also revealed that asthma morbidity is related to air pollution by Particulate Matter (PM10) at the places of the children’s residences (about 10% increase in relative risk per 1 mg/m3).

14. Conclusions (II) • Exposure to airborne particular matter, even at relatively low concentrations (40-50 µg/m3), generally below international air pollution standards (55-70 µg/m3),appears to be a considerable risk factor for childhood asthma in urban areas. This should be a cause for concern for public health authorities and environmental decision-makers.