, ר חוה פרץ"דהחוג לאפידמיולוגיה, אוניברסיטת תל אביב

, ילין-ברגובוילוסיה ס פורטר ללימודי סביבה "סטודנטית בבי, תל אביב' אוני

הקואליציה לבריאות הציבור, מתמחה

מרחק מוסדות חינוך מכבישים: הפורום לבריאות וסביבה

17.05.2011מפגש , המשרד להגנת הסביבה

: המערבי בעבר נמצאאפידמיולוגים בעולם במחקרים

קשורים בעליה בסימפטומים לצירי תחבורה שמגורים בסמוך

וירידה SENSITIZATIONבעליה בשעורי רגישות ,נשימתיים

בילדים --ראות בתפקודי

:חולשות עיקריות

? חשיפה אישית , outdoor –indoor, תוקף הערכת החשיפה -מנה

?אוביקטיביות, התחלואה תוקף הערכת -

( 'השתנות עונתית וכד)חד פעמיות המדידה , מחקרי חתך-

?ייצוגיות, קטניםמדגמים -

lag0, גבוהותחשיפות -

.בריאות לשרותינגישות , גזע, מצב סוציואקונומי -מתערביםמשתנים -

אסטמתיים -כגון, אוכלוסיות רגישות-

חלקיקיםותכולת גודל -חומר חלקיקי, מזהמיםהפרדה בין -

:שינויים במרוצת הזמן

עליה במערב בRESIRATORY ALLERGIC DISEASES

שפור טכנולוגי ומודעות, תקינה -שינויים ברמות החשיפה

שינויים בנפח התנועה

תמיכה , תחלואה-חשיפה: הביולוגי המכאניזם הבנה שלסיבתיבקשר

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;

◦ 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

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),

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)

Netherland s, 9 Dutch schools <400 m of motorways (7-11 yrs): 812 children -

86 asthmatic, 726 non-asthmathic.

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

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).

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.

H-Graveland et al 2007 (cont.)

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:

1. World-wide: Brunekreef et al 2009

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.

Association between self-reported truck traffic on the street of residence and symptomsin 6- to 7-year-old children

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

.

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

(≥0.7 kU·mL-1)

36.3 (476/1311) 1.213 (0.755–1.947)

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.

Traffic categories analysed versus rest of population (reference).

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

(≥0.7 kU·mL-1)

36.3 (476/1311) 1.213 (0.755–1.947)

OR: odds ratio; CI: confidence

interval; Ig: immunoglobulin;

low: 2600–15000 vehicles·day-1;

medium: 15001–30000

vehicles·day-1; high: >30000 v

ehicles·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. Traffic categories

analysed versus rest of population

(reference). +: p=0.05–≤0.10;§: p=0.01–≤0.05; ƒ: p≤0.01.

Table 5: Respiratory and atopic outcomes in relation to traffic counts (high exposure tertile)

in the area of residence for children additionally exposed to environmental tobacco smoke

outcome Crude reference prevalence %

(raw numbers)

Adjusted OR (95% CI)

Asthma 10.8 (126/1169) 1.343 (0.736–2.452)

Current asthma# 5.2 (62/1193) 2.047 (1.005–4.171)§

Current wheeze# 9.1 (107/1178) 1.697 (0.927–3.106)z

Cough¶ 19.1 (226/1186) 1.543 (0.967–2.462)z

Hay fever 10.4 (123/1179) 1.739 (0.967–3.126)z

Skin-prick test (≥3 mm) 15.8 (110/695) 2.670 (1.353–5.268)ƒ

Pollen 11.8 (82/694) 3.255 (1.581–6.699)ƒ

Specific IgE aeroallergens

(≥0.7 kU·mL-1)

33.1 (164/496) 1.761 (0.897–3.458) +

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

.

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.

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.

3. Annesi-Maesano et al 2007 (cont.)

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.

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 petpossession, parental education level, non-Dutch nationality, gas cooking, parental allergy, presence ofmould stains in the home) and downwind location. Effects of traffic characteristics were additionallyadjusted for outdoor PM10 on the day of exhaled NO measurements; effects of PM10 were additionallyadjusted for total traffic and distance of the school from the motorway.

5. Dales et al 2009Methods:

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

5. Dales et al 2009

) 1s (FEV1 in forced expiratory volume in diurnal change% confidence interval) for 95(Mean

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.

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 testingevery 6 months for 2 years. Asthma symptom data were collected every 2 months

Confounders: site, month, temperature

Table 3: Mean (95% CI) change in pulmonary function parameter 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.

Table 4: Risk of asthma-related symptoms and missed school days at the 90th percentile of pollutant concentration

relative to the 10th percentile

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.

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.

*

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:

Figure 2: Adjusted single- and two-pollutant models

(coefficient and 95% CIs) for change in FEV1 in relation to

personal 1-hr maximum PM2.5 the last 24 hr, and 2-day

average NO2 measurements.

Expected change in FEV1 corresponds to an IQR change

in the air pollutant, and estimates are plotted by open

symbols for single-pollutant models and solid symbols for

models adjusting for the indicated co-pollutant. Single-

pollutant models are for the subset of nonmissing

observations for the other co-pollutant, and thus exclude

Figure 3: Adjusted single- and two-pollutant models

(coefficient and 95% CIs) for change in FEV1 in relation to

lag day 0 personal 24-hr average NO2 (pNO2) or PM2.5

(pPM2.5), with ambient 24-hr average NO2 (aNO2).

Expected change in FEV1 corresponds to an IQR change

in the air pollutant (Table 2), and estimates are plotted by

open symbols for single-pollutant models and solid

symbols for models adjusting for the indicated co-pollutant.

Single-pollutant models are for the subset of nonmissing

observations for the other co-pollutant in 51 subjects with

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

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

Figure 1: Relative risks of cough, wheeze, shortness of breath and

total symptom severity scores associated with the various personal

and outdoor school-site particle and gas exposure measurements

Figure 2: Relative risks of cough, wheeze, shortness of breath

and total symptom severity scores associated with the school-

site integrated measurements of Sulfur, EC, and PM2.5.

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)

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.