1. A study of over 300,000 schoolchildren worldwide found an association between self-reported frequent truck traffic near homes and increased symptoms of asthma, rhinitis, and eczema. 2. A study of over 7,500 schoolchildren in Munich, Germany found associations between living near high traffic counts (>30,000 vehicles/day) and increased reports of current asthma, wheezing, and coughing as well as positive skin prick tests. 3. Exposure to traffic air pollution may be linked to adverse respiratory and atopic health effects in children, though results are mixed and confounding factors need accounting.

1. ‫ד"ר חוה פרץ,‬
‫אוניברסיטת תל אביב, החוג לאפידמיולוגיה‬
‫לוסיה ברגובוי-ילין,‬
‫אוני' תל אביב, סטודנטית בבי"ס פורטר ללימודי סביבה‬
‫מתמחה, הקואליציה לבריאות הציבור‬
‫הפורום לבריאות וסביבה: מרחק מוסדות חינוך מכבישים‬
‫המשרד להגנת הסביבה, מפגש 1102.50.71‬

2. ‫במחקרים אפידמיולוגים בעולם המערבי בעבר נמצא:‬
‫שמגורים בסמוך לצירי תחבורה קשורים בעליה בסימפטומים‬
‫נשימתיים ,בעליה בשעורי רגישות ‪ SENSITIZATION‬וירידה‬
‫בתפקודי ראות -- בילדים‬
‫חולשות עיקריות:‬
‫- תוקף הערכת החשיפה , ‪ , outdoor –indoor‬חשיפה אישית?‬
‫מנה‬
‫- תוקף הערכת התחלואה , אוביקטיביות?‬
‫- מחקרי חתך, חד פעמיות המדידה (השתנות עונתית וכד')‬
‫- מדגמים קטנים, ייצוגיות?‬
‫- חשיפות גבוהות, 0‪lag‬‬
‫- משתנים מתערבים- מצב סוציואקונומי, גזע, נגישות לשרותי בריאות .‬
‫- אוכלוסיות רגישות, כגון- אסטמתיים‬
‫- הפרדה בין מזהמים, חומר חלקיקי- גודל ותכולת חלקיקים‬

3. ‫שינויים במרוצת הזמן:‬
‫עליה במערב ב ‪RESIRATORY ALLERGIC DISEASES‬‬ ‫‪‬‬
‫שינויים ברמות החשיפה- תקינה, שפור טכנולוגי ומודעות‬ ‫‪‬‬
‫שינויים בנפח התנועה‬ ‫‪‬‬
‫הבנה של המכאניזם הביולוגי : חשיפה-תחלואה, תמיכה‬ ‫‪‬‬
‫בקשר סיבתי‬

4.  Bibliographic search: articles published 2005-2011 :
◦ PubMed (NLM and NIH), Embase.com (Elsevier).
◦ ScienceDirect, Informaworld, SpringerLink, Science, Scholar Google.
 Key words: short term/acute exposure; traffic-related air
pollution; schoolchildren; health ; health-outcome
 Inclusion: 9 studies on
◦ Exposure to outdoor and indoor air pollution
◦ School children between ages 6-20 years old.
◦ Study design: cross-sectional / cohort studies.
◦ Geographical ascription: (world-wide) Europe; Canada; USA;

5. ◦ Airborne particulates: PM10, PM2.5, PM1.0 (ultra-fine)
◦ Nitrogen oxides (NOX): NO, NO2
◦ Sulfur dioxide (SO2)
◦ Carbon monoxide (CO)
◦ Ozone (O3)
◦ EC (elemental carbon), BC (black carbon) and
OC (optical carbon) fractions (soot)
◦ Benzene

6. ‫מחקרי חתך‬
 Asthma, respiratory outcomes, allergy
 (Nicolai et al 2003)
 symptoms of asthma and allergic sensitisation
(Annesi-Maesano et al 2007, Brunekreef et al
2009).
‫מחקרי עוקבה‬
 Lung function decrements (Dales et al 2009)
 Lung function (Delfino et al 2008)
 Respiratory outcomes
(O’connor et al 2008, Graveland et al 2010,
Patel et al 2010, Spira-Cohen et al 2011)
 Lung function and atopy (Romieu et al 2008),

7. ‫מחקרי חתך‬
 Large studies - the ISAAC (International Study of Asthma and Allergies in
Childhood) protocol:
 Munich, Germany (Phase II): 7,509.children
School beginners (5–7 yrs), Fourth grade (9–11 yrs)
 The French six study (6C): 5,338 elementary children (10.4±0.7 yrs).
 World-wide study (Phase III): 45 developing, 30 developed countries:
315,572 children 13–14 yrs, 110 centers (46 countries)
197,515 children 6–7 yrs, 70 centers (29 countries)
 Netherlands, 9 Dutch schools <400 m of motorways (7-11 yrs): 812 children -
86 asthmatic, 726 non-asthmathic.

8. ‫מחקרי עוקבה‬
 Windsor, Ontario, CA: 182 asthmatic elementary schoolchildren (9-14 yrs).
11.10–11.12/14.11–11.12.2005
 ICAS (the Inner-City Asthma Study) protocol:
 2 regions, Los-Angeles, California: 53 with mild-moderate persistent asthma
(9–18 yrs). a run of 16 10-day periods of follow-up: Jul.-Dec. 2003 (Riverside),
2004 (Whittier)
 7 low-income census tracts, USA: 861 asthmatic children (moderate-severe)
& atopy (5-12 yrs): Aug. 1998-Jul. 2001
 4 high school, urban & suburban communities, NYC: individual-level study, 249
adolescents (13-20 yrs): 57 asthmatics, 192 non-asthmatics. Different dates, 2003-
2005
 4 South Bronx schools (10 children per school): 45 elementary schoolchildren
with asthma (10-12 yrs), Spring 2002, Spring 2004, Fall 2004 & Spring 2005

9.  An environmental questionnaire (EQ(
A question: Frequency of truck traffic on the street of residence.
“How often do trucks pass through the street where you live, on weekdays?”
never, seldom, frequently through the day, and almost the whole day )in
ISAAC phase 3),
 A model : using car-traffic counts and a weighting function, to account for the
distance between measurement point and street, together with street
characteristics (mainly per cent of time with stop-and-go conditions in the
segment), Nicolai et al 2003).

10.  Instruments: At the school level, the inter-variability of PM2.5 and NO2
assessments during the survey span was estimated; concentration values
obtained with our instruments at both proximity and city levels
 Traffic characteristics : such as truck-traffic counts and distances of the
children‟s homes and school addresses from the motorways (GIS) as
markers of long-term personal exposure to traffic.
 Sites of the National Air Quality Monitoring Network
 Personal air monitors: active air samplers worn in a backpack daily over the
10 consecutive days.

11. H-Graveland et al 2007 (cont.)

12.  Age, sex BMI and nationality ethnic group
 Socioeconomic status.
 Time related variables: chronological time, season, month, day of
the week
 Climatic condition: minimum temperature) and daily mean
temperature and relative humidity, Downwind school location
(yes/no) . Previous day minimum temperature
Personal Health
 Corticosteroid (Corticoid) Therapy or antiallergenic medicine use
 Previous FEV1 measurement,
 Family history of relevant diseases:

13. 1. World-wide: Brunekreef et al 2009

14. Methods:
 Sample: 13- to 14-year-old , n=325572
and 6- to 7-year-old children , n=197,515 across the world.
 Exposure: A question about frequency of truck traffic on the street
of residence was included in an additional questionnaire.
 Health: symptoms of asthma, rhinoconjunctivitis, and eczema
 Confounders: sex, region of the world, language, gross national
income, and 10 other subject-specific covariates.

15. Association between self-reported truck traffic on the street of residence and symptoms
in 6- to 7-year-old children

17. Methods:
 Sample: Random samples of schoolchildren (n=7,509, response
rate 83.7%) 5 in Munich Germany
 Exposure: traffic counts and an emission model which predicted
soot, benzene and nitrogen dioxide (NO2), per subject
 Health: Intern. Study of Asthma and Allergies in Childhood
phase-II protocol
with skin-prick tests, measurements of specific immunoglobulin E
and lung function.
 Confounders: age, sex, socioeconomic , family history of disease
.

18. Table 4: Respiratory and atopic outcomes in relation to traffic counts (High exposure tertile) in the area of residence
outcome Crude reference prevalence % (raw numbers) Adjusted OR (95% CI)
Asthma 10.4 (318/3071) 1.194 (0.762–1.871)
Current asthma# 5.0 (157/3124) 1.790 (1.051–3.048)§
Current wheeze# 8.6 (266/3085) 1.663 (1.073–2.578)§
Cough¶ 18.0 (559/3097) 1.622 (1.162–2.266)ƒ
Hay fever 11.7 (360/3082) 1.171 (0.756–1.814)
Skin-prick test (≥3 mm) 19.4 (341/1762) 1.373 (0.857–2.200)
Pollen 13.9 (243/1754) 1.567 (0.940–2.613)+
Specific IgE aeroallergens 36.3 (476/1311) 1.213 (0.755–1.947)
(≥0.7 kU·mL-1)
low: 2600–15000 vehicles·day-1; medium: 15001–30000 vehicles·day-1; high: >30000
vehicles·day-1
in street segment <50 m away from home.
#: with respective symptoms during the last 12 months;
¶: morning cough during the last 12 months. ORs adjusted for age, sex, socioeconomic
status, and family history of asthma, hay fever, or eczema.

19. Table 4: Respiratory and atopic outcomes in relation to traffic counts (High exposure tertile) in the area of residence
outcome Crude reference prevalence % Adjusted OR (95% CI)
(raw numbers)
Asthma 10.4 (318/3071) 1.194 (0.762–1.871)
Current asthma# 5.0 (157/3124) 1.790 (1.051–3.048)§
Current wheeze# 8.6 (266/3085) 1.663 (1.073–2.578)§
Cough¶ 18.0 (559/3097) 1.622 (1.162–2.266)ƒ
Hay fever 11.7 (360/3082) 1.171 (0.756–1.814) OR: odds ratio; CI: confidence
interval; Ig: immunoglobulin;
Skin-prick test (≥3 mm) 19.4 (341/1762) 1.373 (0.857–2.200)
Pollen 13.9 (243/1754) 1.567 (0.940–2.613)+
Specific IgE aeroallergens 36.3 (476/1311) 1.213 (0.755–1.947) low: 2600–15000 vehicles·day-1;
(≥0.7 kU·mL-1) medium: 15001–30000
vehicles·day-1; high: >30000 v
Table 5: Respiratory and atopic outcomes in relation to traffic counts (high exposure tertile) ehicles·day-1 in street segment <50
in the area of residence for children additionally exposed to environmental tobacco smoke m away from home.
#: with respective symptoms during
outcome Crude reference prevalence % Adjusted OR (95% CI)
(raw numbers) the last 12 months;
¶: morning cough during the last 12
Asthma 10.8 (126/1169) 1.343 (0.736–2.452) months. ORs adjusted for age, sex,
Current asthma# 5.2 (62/1193) 2.047 (1.005–4.171)§ socioeconomic status, and family
Current wheeze# 9.1 (107/1178) 1.697 (0.927–3.106)z history of asthma, hay fever, or
Cough¶ 19.1 (226/1186) 1.543 (0.967–2.462)z eczema. Traffic categories
Hay fever 10.4 (123/1179) 1.739 (0.967–3.126)z analysed versus rest of population
(reference).
Skin-prick test (≥3 mm) 15.8 (110/695) 2.670 (1.353–5.268)ƒ +: p=0.05–≤0.10;
Pollen 11.8 (82/694) 3.255 (1.581–6.699)ƒ §: p=0.01–≤0.05; ƒ: p≤0.01.
Specific IgE aeroallergens 33.1 (164/496) 1.761 (0.897–3.458) +
(≥0.7 kU·mL-1)

20. Methods:
 Sample: 5338 school children (10.4 years) attending 108 randomly
chosen schools in 6 French cities
 Exposure: concentrations of PM2.5 (fine particles with aerodynamic
diameter p2.5 mm) assessed in proximity of their homes.
range:1.6-54micm3, NO2 8.1-70.4
 Health: asthma and allergy. Children underwent a medical visit
including skin prick test (SPT) to common allergens, exercise-
induced bronchial (EIB) reactivity and skin examination for flexural
dermatitis. Their parents filled in a standardised health
questionnaire.
 Confounders: sex, socioeconomic , passive smoking, family history
of diseases, ethnic group, NO2
.

21. Table 4: Odds ratios (95% confidence interval) of allergic and respiratory morbidity by high vs. low concentrations of
PM2.5 and NO2 in all (n=5338) and long-term resident (n=1945) children of the French Six Cities Study
The two categories of exposure „„low‟‟ vs. „„high‟‟ were defined with respect to the median value of the distribution of the
concentrations; EIB: exercise-induced bronchial hyperresponsiveness as assessed by PEFin–PEFfin/PEFin X10% (PEF ¼
peak expiratory flow); SPT: skin prick tests. Odds-ratios (ORs) were adjusted for age, sex, family history of allergy and passive
smoking. a8 years at the same address.

22. 3. Annesi-Maesano et al 2007 (cont.)
Table 5: Odds ratios (95% confidence interval) of allergic sensitisation by high vs. low concentrations of PM2.5 and NO2 in all
(n=5338) and long-term resident (n=1945) children of the French Six Cities Study
Odds-ratios (ORs) adjusted for: age, sex, family history of allergy and passive
smoking.
2 categories of exposure „„low‟‟ vs. „„high‟‟ were defined with respect to the median
value of the distribution of the concentrations;
EIB: PEFin–PEFfin/PEFinX10%.
a8 years at the same address.

23. Methods:
 Sample: 812 children from nine Dutch schools within 400 m of
motorways.

 Exposure: Daily levels of PM10, obtained from background
monitoring stations. Long-term exposure was assessed using
specific traffic-related characteristics such as total, car and truck
motorway traffic and the distances of the children’s homes and
schools from the motorway.
 Health: Asthma and Allergies questionnaire, Offline exhaled NO
measurements
 Confounders: sex, age, nationality, socioeconomic , passive smoking
family history of diseases, etc.

24. H-Graveland et al 2007
Figure 2: Adjusted* geometric means ratios with 95% CIs for the associations between traffic characteristics
and PM10 levels and exhaled NO in children with and without asthma.
*All effects were adjusted for individual confounders (sex, age, current parental smoking, current pet
possession, parental education level, non-Dutch nationality, gas cooking, parental allergy, presence of
mould stains in the home) and downwind location. Effects of traffic characteristics were additionally
adjusted for outdoor PM10 on the day of exhaled NO measurements; effects of PM10 were additionally
adjusted for total traffic and distance of the school from the motorway.

25. 5. Dales et al 2009
Methods:
 Sample: 182 elementary schoolchildren with physician-diagnosed
asthma
 Exposure: city monitored ambient hourly air pollution concentrations.
 Health: morning and evening forced expiratory volume in 1 s (FEV1)
for 28 consecutive days; daily symptom diary
 Confounders: sex, time of outdoor activity, temp., RH, week-day

26. 5. Dales et al 2009
Mean (95% confidence interval) for diurnal change in forced expiratory volume in 1 s (FEV1)
associated with interquartile increases of air pollutant concentrations averaged from 08:00 h to 20:00
h on the test day.
adjusted for daily mean temperature, relative humidity, day of the week and time for outdoor activity on
the same day and study period r.

27. Methods:
 Sample: 861 children with persistent asthma in 7 US urban
communities
 Exposure: Daily pollution measurements from the Aerometric
Information Retrieval
 Health: 2-week periods of twice-daily pulmonary function testing
every 6 months for 2 years.
Asthma symptom data were collected every 2 months
 Confounders: site, month, temperature

28. Table 3: Mean (95% CI) change in pulmonary function parameter at the 90th percentile of pollutant concentration relative to
the 10th percentile
Table 4: Risk of asthma-related symptoms and missed school days at the 90th percentile of pollutant concentration
relative to the 10th percentile
Covariates include site, month, site-by-month interaction, temperature, call number, and intervention group. Independent variable is
the 19-day average pollutant concentration.

29. Methods:
 Sample: 249 subjects (57 asthmatics, 192 nonasthmatics)
age- high schools
 Exposure: BC and PM2.5 monitored continuously outside three
NYC high schools and one suburban high school for 4–6 weeks
 Health: daily symptom data using diaries
 Confounders: school, weekend, and daily maximum 8-hr average O3.

30. Table 4: ORsa (95% CI) for respiratory symptoms and use of medication for asthma associated with an IQRb
increase in pollutant concentrations at various lags of exposure
a Models combine data from all schools and adjust for school, weekend, and daily maximum 8-hr average O3.
b IQRs are 1.2 ƒÊg/m3 for BC, 16 ppb for NO2, and 11.3 ƒÊg/m3 for PM2.5.
c Sample sizes vary among pollutant models because of differing patterns of missing pollutant measurements.
*

31. Methods:
 Sample: 53 subjects with asthma, 9-18 y in Los-Angeles
 Exposure: Personal hourly PM2.5 mass, 24-hr PM EC and OC,
24-hr NO2 and the same outdoor central-site exposure
 Health: Spirometry 10 days (*3)
 Confounders:

32. Figure 2: Adjusted single- and two-pollutant models Figure 3: Adjusted single- and two-pollutant models
(coefficient and 95% CIs) for change in FEV1 in relation to (coefficient and 95% CIs) for change in FEV1 in relation to
personal 1-hr maximum PM2.5 the last 24 hr, and 2-day lag day 0 personal 24-hr average NO2 (pNO2) or PM2.5
average NO2 measurements. (pPM2.5), with ambient 24-hr average NO2 (aNO2).
Expected change in FEV1 corresponds to an IQR change Expected change in FEV1 corresponds to an IQR change
in the air pollutant, and estimates are plotted by open in the air pollutant (Table 2), and estimates are plotted by
symbols for single-pollutant models and solid symbols for open symbols for single-pollutant models and solid
models adjusting for the indicated co-pollutant. Single- symbols for models adjusting for the indicated co-pollutant.
pollutant models are for the subset of nonmissing Single-pollutant models are for the subset of nonmissing

33. Methods:
 Sample: 45 grade children with asthma at four South Bronx
schools (10 children per school)
 Exposure: Daily 24-hr personal samples of PM2.5, including the
elemental carbon (EC) fraction during 1 month and outdoor…
 Health: Spirometry and symptom scores were recorded several
times daily during weekdays

34. Table 2: Mixed model estimates of lung function decrements associated with personal and school-site pollutants
a from 5th-95th percentile of pollutant concentration weekdays only, 9am-9am.
b same day afternoon lung function measurements.
* p-value < 0.10 by t-test

35. Figure 1: Relative risks of cough, wheeze, shortness of breath and Figure 2: Relative risks of cough, wheeze, shortness of breath
total symptom severity scores associated with the various personal and total symptom severity scores associated with the school-
and outdoor school-site particle and gas exposure measurements site integrated measurements of Sulfur, EC, and PM2.5.

36.  World-wide: Higher exposure to self-reported truck traffic on the street of
residence is associated with increased reports of symptoms of asthma,
rhinitis, and eczema in many locations in the world.
 In German children: High vehicle traffic was associated with asthma, cough
and wheeze, and in children additionally exposed to environmental tobacco
smoke, with allergic sensitisation. However, effects of socioeconomic
factors associated with living close to busy roads cannot be ruled out.
 In the French 6C suffering from EIB (exercise-induced bronchial) and flexural
dermatitis at the period of the survey, past year atopic asthma and SPT (skin-
prick test) positivity to indoor allergens were significantly increased in
residential settings with PM2.5 concentrations exceeding 10 mg/m3 (WHO
air quality limit values). After adjustment for confounders and NO2 as a potential modifier The
relationships were strengthened in long-term residents (>8 years).
 In Dutch children: Short-term (not long-term) changes in ambient PM10
largely attributable to biomass burning are associated with increased levels
of exhaled NO (marker of airway inflammation)

37.  In Canadian children with asthma: Relatively low concentrations of urban air pollution worsen
lung function over a short period of time, even within a day. (PM2.5 appears to be the most
important pollutant).
 In US inner-city children with asthma: short-term increases in air pollutant concentrations
below the National Ambient Air Quality Standards were associated with adverse respiratory
health effects (reflected in pulmonary function) / absence from school . (The associations with
NO2 suggest that motor vehicle emissions may be causing excess morbidity in this
population).
 In US adolescents: Acute exposures to traffic-related pollutants- DEPs (diesel exhaust
particles- a local driver of urban PM2.5); and/or NO2 may contribute to increased respiratory
morbidity ; urban residents (compared with suburban) and asthmatics may be at increased
risk.
 In NY-Bronx: Significantly elevated same-day relative risks of cough , wheeze ,shortness of
breath and total symptoms were found with an increase in personal EC, but not with personal
PM2.5 mass.
Increased risk of cough and total symptoms was found with increased one-day lag and two-
day average school-site.
Adverse health associations were strongest with personal measures of EC exposure,
suggesting that the diesel “soot” fraction of PM2.5 is most responsible for pollution-related
asthma exacerbations among children living proximal to roadways. Studies that rely on
exposure to particulate mass may underestimate PM health impacts.