THEE”!

l ‘ LIBRARY
zoo; Michigan State
_ University

 

 

This is to certify that the
thesis entitled

PEAK EXPIRATORY FLOW RATES IN GERMAN CHILDREN
EXPOSED TO AMBIENT OUTDOOR AIR POLLUTION,
PARTICULATE MATTER AND TRACE ELEMENTS

presented by

Scott Alan Asakevich

has been accepted towards fulfillment
of the requirements for the

 

 

MS. degree in Epidemiology
L91 // ( ij

 

Major Professor’s Signature
74p)? 2 ‘7’; '2 (CO E,
v r

Date

MS U is an A‘r’rrmatrve Action/Equal ODDOITUU/iy Institution

-—--—~¢-— -,-.-_---

 

PLACE IN RETURN BOX to remove this checkout from your record.
TO AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE DATE DUE DATE DUE

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2/05 p:lCIRC/DaleDue.indd-p.1

 

 

 

PEAK EXPIRATORY FLOW RATES IN GERMAN CHILDREN EXPOSED TO
AMBIENT OUTDOOR AIR POLLUTION, PARTICULATE MATTER AND TRACE
ELEMENTS
By

Scott Alan Asakevich

A THESIS
Submitted to
Michigan State University
In partial fulﬁllment of the requirements
for the degree of
Master of Science

Department of Epidemiology

2006

I IIDII.’III. Ill}

ABSTRACT
PEAK EXPIRATORY FLOW RATES IN GERMAN CHILDREN EXPOSED TO
AMBIENT OUTDOOR AIR POLLUTION, PARTICULATE MATTER AND TRACE
ELEMENTS
By
Scott Alan Asakevich

In light of inconsistencies among existing reports and the continued public health
impact, the Objective of this report is to investigate associations between childhood
exposures to ambient particulate matter, gaseous, and trace metal pollution and
observable decrements in peak expiratory flow.

We longitudinally followed 70 German children. Linear regression analyses of
moving averages of pollution variables and changes in peak ﬂow values were performed
utilizing the mixed procedure of SAS.

Analysis of changes in afternoon peak ﬂow yielded a statistically signiﬁcant
negative association for N05, strong acid aerosol, and antimony concentrations. No
associations were seen for changes in morning peak flow.

In conclusion, this study failed to demonstrate consistent associations between
pollutants and peak expiratory ﬂow rates. The data does provide additional evidence for
reductions in lung function associated with exposures to low level N03’ and strong acid
aerosol concentrations. The signiﬁcant association Observed for antimony suggests
further research into health effects of various transition metal species is warranted. This
inability to demonstrate consistent relationships supports previous assertions that future

research endeavors investigating associations regarding particulate matter and its

speciation should target susceptible children with chronic respiratory complaints.

ACKNOWLEDGMENTS

I would like to express my gratitude to my thesis advisor, Dr. Wilfried Karmaus.
for the countless hours Of encouragement, guidance and patience throughout my graduate
education. As the leader of our “United Nations” you provided me with far more than
you can imagine.

I would also like to express my thanks to Dr. Matthew Reeves and Dr. David
'l‘odem for their service on my committee. I appreciate the investment of your time and
the direction you provided. In addition, I would like to thank Dr. Michael Collins and Dr.
Alka Indurkhya for their contributions to this thesis.

In regards to the entire Fisheater’s group, many of whom have gone on to bigger
and better things: I would like to thank each of you for the years of friendship and
support.

I would also like to thank Kevin Brooks, Alireza Sadeghnejad, and Xiaobei Zhu
for their support, insight, and suggestions. I would like to express my gratitude to
Matthew and Sarah Payok as well as Debra Dalton for their editorial services.

Finally, I would like to express my sincere appreciation for the work and effort of
Lora McAdams and the entire Department of Epidemiology staff who work behind the

scenes to ensure the success of so many graduate students.

iii

TABLE OF CONTENTS

LIST OF TABLES ................................................................................... vi

LIST OF ABBREVIATIONS ...................................................................... vii

INTRODUCTION ...................................................................................... 1

CHAPTER 1

BACKGROUD ....................................................................................... 3
Ozone}
Particulate Matter .............................................................................. 4
Sulfur Dioxide .................................................................................. 6
Nitrogen Dioxide .............................................................................. 7

Current issues regarding health outcomes resulting from air pollution. . . .. . . . . .8
CHAPTER 2

METHODS ............................................................................................ l l
The study population ......................................................................... 1 I
School Site selection ......................................................................... l 1
Determination and speciation of air pollution variables ................................ 15
Questionnaire ................................................................................ I 5
Peak Expiratory Flow Measurements .................................................... 16
Statistical Analysis .......................................................................... 16
Hypertonic saline challenge test .......................................................... 17

CHAPTER 3

RESULTS .......................................................................................................................... 18
Seection and description of the study population ........................................ 18
Outdoor air pollution ......................................................................... 19
Description of outcome and external validity .......................................... 25

CHAPTER 4

DISCUSSION .................................... 32

CHAPTER 5

CONCLUSIONS ....................................................................................... 40

APPENDIX A

Peak ﬂow measurement data sheet (English translation) ........................................ 44

REFERENCES ........................................................................................ 45

TABLE I

TABLE 23

TABLE 2b

TABLE 2b

TABLE 3

TABLE 4

TABLE 5

TABLE 5

TABLE 6

TABLE 7

LIST OF TABLES

Demographics of 70 German children participating in peak ﬂow
measurements....................

Daily daytime mean and maximum concentrations for PM25, 8042',
N03' across seven Southwestern German communities for 26 days
between February and March 1996..............

Daily daytime mean and maximum concentrations for 7 select trace
metals across seven Southwestern German communities for 26 days
between February and March 1996

Daily daytime mean and maximum concentrations for 7 select trace
metals across seven Southwestern German communities for 26 days
between February and March 1996

Spearrnan correlation coefﬁcients for measured mean ambient outdoor
air pollutants .........................................................................

Number of children participating in both morning and afternoon peak
expiratory ﬂow rate measurements by day. . . . .. ........................................

Relationship between peak expiratory flow rates and external measures
Ofbronchial hyperreactivity..................

Relationship between peak expiratory ﬂow rates and external measures
Ofbronchial hyperreactivity...........

APEFam effect-estimates with standard error Of air pollution on peak
expiratory ﬂow

APEFpm effect-estimates with standard error Of air pollution on peak
expiratory ﬂow

24

26

.28

.30

.31

LIST OF FIGURES

FIGURE 1 Map of the seven Southwestern Germany communities with children
participating in peak ﬂow measurements ...................................... 14

vi

LIST OF ABBREVIATIONS

ETS ................................................................. Environmental Tobacco Smoke
SAS .................................................................... Statistical Analysis Software
PM35 ............................................ Particulate Matter smaller than 2.5 micrometers
PM“, .............................................. Particulate Matter smaller than 10 micrometers
SO; ..................................................................................... Sulfur Dioxide
8042’ ........................................................................................ Sulfate Ion
N02 .................................................................................. Nitrogen Dioxide
N03' .......................................................................................... Nitrate Ion
CO ................................................................................................ Cobalt
Cd ............................................................................................. Cadmium
As ................................................................................................ Arsenic
Pb ................................................................................................... Lead
Va ............................................................................................ Vanadium
Sb ............................................................................................. Antimony
Pt ............................................................................................... Platinum
PEF R ..................................................................... Peak Expiratory Flow Rate
F EV. ................................................... Forced Expiratory Ventilation in 1 second
EPA ............................................................. Environmental Protection Agency
NAAQS ................................................................. National Ambient Air Quality Standards

CIConﬁdence Intervals

BHR ...................................................................... Bronchial Ilyperreactivity

vii

INTRODUCTION

Public health concern regarding possible associations between adverse health
outcomes and exposure to air pollutants has been mounting over the last several decades.
The effect increasing levels of air pollution may have on childhood health outcomes has
been of particular concern. This concern has been prompted in part by Observed
increases in the prevalence Of asthma and asthma-like symptoms in children who live in
developed countries. (Peat, van den Berg et al. 1994; Mannino, Homa et al. 1998;
Sullivan 2003) Due to the substantial social and economic cost that is associated with
asthma, researchers have attempted to identify prospective risk factors amenable to
intervention. (Rusznak, Devalia et al. 1994; Zmirou, Deloraine et al. 1999; Zanobetti,
Schwartz et al. 2000; Piecoro, Potoski et al. 2001; Park, Lee et al. 2002; Mo, Robinson et
al. 2003)

Childhood exposure to air pollution warrants special consideration based on a
variety Of factors. Chief among these is the knowledge that a child’s immune system and
lung function are not fully developed. (Dockery, Speizer et al. 1989; Wang. Dockery et
al. 1993; Roth-Kleiner and Post 2003) This physiological immaturity raises the suspicion
that children’s scquelae from environmental exposures that occur during a sensitive target
window may be different from those of adults. (Chew, Goh et al. 1999; Braga. Zanobetti
et al. 2001; Fusco, Forastiere et al. 2001) Furthermore, it is reasonable to assume that
Since children spend more time outdoors during warmer months and evening hours that
have a greater exposure to peak air pollution levels. This temporal trend of childhood

outdoor activity and higher ambient levels of air pollution is made more ominous by the

tendency for childhood outdoor activities to increase ventilatory rate. (Mercier. Varray et
al. 1991; Rowland and Cunningham 1997)

There are a variety of postulated mechanisms mitigating the association between
ambient air pollution and respiratory compromise. The two most prominent include
inﬂammatory processes (Ferin, Oberdorster et al. 1992; Utell and F rampton 2000; Goto.
lshii et al. 2004) and oxidative stress. (Dick, Brown et al. 2003; Hirano, Furuyama et al.
2003) Both of these mechanisms involve chronic exposure to industrial ambient air
pollutants including ozone, nitrogen dioxide, sulfur dioxide, various heavy metals. and

particulate matter. Each Of these pollutants will be examined briefly.

Chapter 1

BACKGROUND

Overview of current research regarding air pollution and childhood lung function
Ozone (03)

Unlike the other listed pollutants, ozone is not directly emitted from an
identiﬁable polluting source. It is readily produced through photochemical thermal
reactions between volatile organic compounds and NO; species, and is the principal
component of smog. The basic requirements of sunlight and heat explain the observed
seasonal and diurnal variations in ozone concentration. (Porter, Rao et al. 2001; Wolff.
Dunker et al. 2001) The organic compound precursors of ozone are emitted from a
variety Of sources including motor vehicles, chemical plants, reﬁneries and factories.
The N02 species are mainly released from motor vehicle exhaust. power plant emissions
and as by-products of various combustion reactions. The Environmental Protection
Agency (EPA) 1997 National Ambient Air Quality Standards (NAAQS) have established
a one hour 03 exposure level of 0.12 ppm. This standard is the threshold exposure level
that individuals should not exceed more than once per year. In addition, the NAAQS has
established an 8-hour 03 exposure limit of 0.08 ppm. This level is the 8-hour 03
exposure averaged over a three year time span.

A variety of studies have established an association between increases in ozone
levels and increases in hospital emergency room admissions for respiratory illness.
(Hajat, Haines et al. 1999; Neas, Schwartz et al. 1999; Sheppard, Levy et al. 1999;

Fauroux, Sampil et al. 2000; Gouveia and Fletcher 2000; Schwela 2000; Atkinson.

Anderson et al. 2001; Braga, Zanobetti et al. 2001; Friedman, Powell et al. 2001; Fusco,
Forastiere et al. 2001; Delﬁno, Zeiger et al. 2002; Martins, Latorre Mdo et al. 2002: Park.
Lee et al. 2002; Peel, Tolbert et al. 2005) In addition, researchers have demonstrated that
exposure to ambient ozone concentrations can lead to respiratory compromise (Gent,
Triche et al. 2003) and reductions in lung ﬁrnction. (Gold, Damokosh et al. 1999;
Jalaludin, Chey et al. 2000; Mortimer, Neas et al. 2002)

Particulate Matter (PM)

Particulate matter is a mixture of solid particles and liquid droplets found in the
air. The particles emitted by an identiﬁable source are commonly referred to as direct
emissions, while those that are formed through atmospheric processes are known as
secondary particles. There are a variety of factors that determine the role particulate
matter has on health outcomes. (Harrison and Yin 2000)

One key determinate is the size of particulate matter. (Harkema. Kceler et al.
2004) PM can be classiﬁed as either large diameter, coarse, ﬁne, or ultraﬁne. Large
diameter particles are those that are greater than 10 micrometers in diameter. These
particles rarely penetrate beyond the upper airways. (Ferin, Oberdorster et al. 1992) They
are readily removed by the body’s main defenses including coughing and transport via
the mucociliary ladder. Particles of this size are generally regarded as having little affect
on the development of respiratory disease and will not be discussed further.

Coarse particles are those that are between 2.5 and 10 micrometers in diameter.
These particles are generally made up of silica, aluminum, and iron, and have been
demonstrated to be deposited high in the endobronchial tree. Various research studies

have linked ambient concentrations of coarse particulate matter, commonly denoted as

PM .0, to a variety of respiratory and other health outcomes. (Pope, Dockery et al. 1991:
Pope and Dockery 1992; Neas, Dockery et al. 1995; Abbey, Nishino et al. 1999; Gold.
Damokosh et al. 1999; Neas, Schwartz et a1. 1999; Sheppard, Levy et al. 1999; Gouveia
and Fletcher 2000; Zanobetti, Schwartz et al. 2000; Anderson, Bremner et al. 2001;
Atkinson, Anderson et al. 2001; Braga, Zanobetti et al. 2001; Lacasana, Esplugues et al.
2005) The studies include large scale epidemiologic studies in both Europe (Pekkanen.
Timonen et al. 1997; Roemer, Clench-Aas et al. 1999; Tiittanen, Timonen et al. 1999;
Samoli, Analitis et al. 2005) and the United States. (Keeler, Dvonch et a1. 2002;
Mortimer, Neas et a1. 2002; Peel, Tolbert et al. 2005)

Similarly, ﬁne particles are the components of PM that are less than 2.5
micrometers in size. These particles are deposited in the terminal bronchioles and
alveoli, and are regarded as the most closely associated with adverse health outcomes
(OsomiO-Vargas, Bonner et al. 2003; ChOi, Kim et al. 2004) such as emergency rooms
admissions (Sheppard, Levy et al. 1999; Anderson, Bremner et al. 2001; Barnett.
Williams et al. 2005), respiratory compromise (Romieu, Meneses et al. 1996; Ostro.
Lipsett et al. 2001; Pino, Walter et al. 2004; Ranzi, Gambini et al. 2004), and decrements
in lung function. (Koenig, Larson et al. 1993; Gold, Damokosh et al. 1999; Neas,
Schwartz et al. 1999; Tiittanen, Timonen et al. 1999; Schwartz and Neas 2000; Delﬁno,
Quintana et al. 2004) They are composed of a mixture of particles formed in the air from
chemical reactions involving gaseous pollutants including sulfates. nitrates and other
organic compounds.

Finally, the subset of PM” that ranges from 0.1 to 1 micrometers is sometimes

referred to as ultraﬁne particles. This range of PM has not been extensively studied.

Particles less than 0.1 nm remain in the air stream and are not believed to settle within the
respiratory tract.

The EPA NAAQS for PM”) sets an annual mean ambient air concentration < 50
rig/m3 averaged over three years. In addition, the NAAQS speciﬁes a standard
concentration of 150 ug/m3 that should not be exceeded more than once per year over a
three year time period. For PM” the standards are 15 ug/m3 and 65 ug/m3 respectively.
Trace Elements

Another recently hypothesized explanation of the relationship between PM and
adverse health outcomes is exposure to trace amounts of heavy metals in the atmosphere.
One Of the leading mechanistic theories explaining these adverse outcomes is based on
the oxidation-reduction capacity Of various metals which leads to the production of free
radicals via the Fenton reaction. (Dick, Brown et al. 2003; Jimenez Del Rio and Velez-
Pardo 2004) The generation of these free radicals results in widespread tissue
inﬂammation. Metals which have been demonstrated to undergo Fenton-type oxidation-
reduction reactions include iron, cobalt, lead, cadmium and mercury. Recent studies have
begun investigating the potential role air particulate metal exposure may have on human
health. (Burnett, Brook et al. 2000; Claibom, Larson et al. 2002)

Sulfur Dioxide (SOz)

Sulfur dioxide is formed primarily from either the burning of fossil fuels that
contain sulfur, including emissions from coal burning electric utilities or as a by-product
during industrial processes such as metal smelting. Reports have linked elevated levels
of 802 with increased mortality (Wichmann and Heinrich 1995; Vigotti 1999;

Wichmann. Spix et al. 2000). asthma exacerbations in children (Chew. Goh et al. 1999;

de Diego Damia. Leon F abregas et al. 1999; Vigotti 1999; Herbarth, Fritz et al. 2001 ).
decrements in lung function (Roemer, Hock et al. 1993; Timonen and Pekkanen 1997;
Roemer, Clench-Aas et al. 1999; van der Zee, Hoek et al. 1999), and aggravation of
cardiovascular disease. (Vigotti 1999; Venners, Wang et al. 2003; Fung. Luginaah et al.
2005) The established NAAQS for SO; include a maximum concentration of 0.14 ppm
over 24 hours that should not be exceeded more than once per year. Additionally. a
speciﬁed annual mean of 0.030 ppm should not be surpassed more than once in any given
yean

Nitrogen Dioxide (NO;)

NO; is a highly reactive gas that is formed via oxidation of nitric oxide.
Anthropogenic sources of NO; include high-temperature combustion processes primarily
via automobile combustion engines, power plants and electric utilities. There are a
variety of natural sources of NO; include lightning, biological processes in the soil and
stratospheric intrusion. Home heaters (Moseler, Hendel-Kramer et al. 1994; Garcia
Algar, Pichini et al. 2004) and gas stoves (Goldstein, Melia et al. 1979; Bruggc, Vallarino
et al. 2003) have been shown to produce signiﬁcant concentrations of indoor NO;
pollution. Various European and American studies have shown childhood health effects
including airway hyperresponsiveness (Boezen, van der Zee et al. 1999; Hirsch. Weiland
et al. 1999), reductions in pulmonary function (Timonen and Pekkanen 1997), and
relative increases in asthmatic symptoms and other respiratory illnesses. (Baldacci,
Carrozzi et al. 1997; Just, Segala et al. 2002; van Strien, Gent et al. 2004) In addition. a

recent study has suggested a positive association between increased respiratory symptoms

in childhood and combined exposure to NO; and ETS. (Emenius, Pershagen et al. 2003)
The NAAQS index for maximum annual mean N02 concentration is 0.053 ppm.
Current issues in air pollution and health impact studies

Although there is a growing body of evidence implicating various components of
ambient air pollution to adverse health outcomes, there continue to be reports published
that yield inconsistent ﬁndings. (Roemer, Hoek et al. 1998; Roemer, Clench-Aas et al.
1999) In light of these inconsistencies as well as the potential impact on public health.
the objective of this report is to further investigate the potential associations between
childhood exposure to ambient ﬁne particulate matter, gaseous pollutants, and trace metal
pollution and observable reductions in peak expiratory ﬂow (PEF).

The likely role of inﬂammation in regard to the adverse respiratory outcomes of
air pollution has led many researchers to evaluate alternate means of assessing airway
inﬂammation. One commonly used test believed to be a reasonable marker of
inﬂammation is bronchial hyperreactivity to a pharmacologic challenge test. (Parker.
Abu-Hijleh et al. 2003) The associated cost and relative invasiveness of these tests limit
their utility as epidemiologic tools. These limitations have led researchers to evaluate
alternative proxies for these pharmacologic challenge tests.

One such commonly proposed surrogate is the peak expiratory ﬂow rate (PEFR).
The diurnal variability in PEF has been shown to be correspond well to the degree of
bronchial hyperresponsiveness following pharmacologic challenge tests, (Ryan, Latimer
et al. 1982; Gem, Eggleston et al. 1994) although some researchers have disputed the
clinical and diagnostic value of this association. (den Otter, Reijnen et al. 1997:

Goldstein, Veza et al. 2001) The physiologic pattern of diurnal variation in PEF has been

well demonstrated. (Hetzel 1981) Subsequently, several studies have identiﬁed a variety
of factors which contribute to the observed variation. These factors include age (Le
Souef I997; Lebowitz, Sherrill et al. 1997), gender (Lebowitz, Sherrill et al. 1997;
Holcroft, Eisen et al. 2003; Ones, Somer et. al. 2004), race (Le Souef 1997; Ones. Somer
et al. 2004), height (Ones, Somer et al. 2004), weight (Ones, Somer et al. 2004). and
smoking exposure. (Holcroft, Eisen et al. 2003).

Peak expiratory ﬂow is obtained from the maximum ﬂow achieved during a
maximal expiratory effort following maximum inspiration. Since PEF is generally
attained within the ﬁrst 0.1 seconds of a forced expiratory maneuver, it has potential
advantages over other pulmonary function determinants for long-term epidemiologic
monitoring in a childhood population. The most likely advantage in measuring PEF is
that it makes the prolonged and challenging expiration maneuvers necessary to calculate
forced expiratory ventilation in 1 second (FEVI) and forced vital capacity unnecessary.

A variety of portable hand-held peak ﬂow monitors have been manufactured to
reliably record PEF. One of the most widespread meters, the mini-Wright ﬂow meter.
has been shown to be reliable after 5 years of continued use. (Douma, van der Mark et al.
1997) In addition, the reproducibility of PEF obtained by the mini-Wright peak ﬂow
meter is also reported to be good. (Enright, Sherrill et al. 1995; Paggiaro. Moscato et al.
1997; Holcroft, Eisen et al. 2003)

Several studies have conﬁrmed that the mini-Wright ﬂow meter over estimates
PEF values in the mid-ﬂow ranges and under records values at the lower and higher ﬂow
ranges. (Miller, Dickinson et al. 1992) Subsequent authors have determined a correction

formula for the Observed non-linearity Of the mini-Wright peak ﬂow meter ( M iles.

Tunnicliffe et al. 1996), although recent studies have conﬁrmed that correction for this
factor does not increase reproducibility. (Douma, Kerstjens et al. 2000) Taking into
consideration the widespread availability, ease of use, good reproducibility, good
reliability and the relative inexpensivenessof hand-held spirometers. it is reasonable to

conclude that they serve as a valuable epidemiologic monitoring tool.

10

Chapter 2

METHODS

Study population

Data was collected in a longitudinal study designed to assess the potential impact
of ambient air pollution on childhood lung function in a cohort of children residing in
seven largely urban Southwestern German communities. Children eligible to participate
were those who had previously been enrolled in a large scale environmental cohort
(Kuehr, F rischer et al. 1992; Kuehr, Frischer et al. 1998) determined to live within one
km of the seven primary schools selected as sites for air pollution monitoring stations.
The communities from which children were recruited include: Crumstadt, Eschollbriiken-
Pfungstandt, Biebesheim, Gemsheim, Bickenbach, Auf Esch-GroB-Gerau. and
Michelstadt (See Figure 1).
School site selection

As the children spent a large proportion of their days at school and all

participating children lived within close proximity of the school, we elected to collect air
pollution measurements on the rooftops of the schools. Due to limited funds, we were
forced to select only seven locations to measure air pollution data. Of the 18 schools
from which children participated, we selected those buildings that provided the best
measurement conditions (ﬂat roof, not more than one story, and readily accessible
electrical power). The selected schools maintained representation of the three regions
from which children were recruited for the larger study.

Determination and speciﬁcation of PM2.5

ll

Air pollution monitoring stations were established on the rooftops of the seven
primary schools as discussed above. All air samples were conducted with a ﬁlter unit
(VDI guideline NO. 2463). Each ﬁlter sample was collected for 24 hr through a Harvard-
Marple impactor (Air Diagnostics, Harrison, ME, USA) with a 50% aerodynamic
diameter cutpoint of 2.5 pm. The selection of PM was based on impactor principle and
required constant ﬂow and volumes during the sampling period. The sampling units were
equipped with volume regulators to ensure a constant ﬂow of 2 m3 per hour.

For the deposition of particulate matter, adhesive-free silica ﬁber ﬁlters
(Munktell, Type MK 360, 47 mm) were utilized. Throughout the study. three ﬁlters
were used per week. The rotation of ﬁlter replacement was coordinated to ensure an
equal distribution of each week day. Therefore, the sampling duration was 24 hours
responding to a volume of 48 m3. In order to maintain adequate quality control measures.
following three sample data collection visits, two unused ﬁlters which had previously
been transported to the sampling unit site were analyzed.

To maximize consistency, we equilibrated each sample ﬁlters at 21 i 2°C and 35
i 5% relative humidity for 24 hr before weighing. We used an analytical balance
designed for weighing ﬁlters with a resolution of 0.1 ug (M5P-000V001; Sartorius.
Goettingen, Germany). We calculated ambient PM;,5 concentrations based on sample
weight and air volume.

Determination of metals and anions required two different preparations. Filters
were divided into equal halves (1% weight difference). For the analyses of metals.
samples were prepared by chemical decomposition with nitric acid and hydrogen ﬂuoride

in encased pressure containers using microwave treatment (VDI guideline NO. 2268').

12

Metals were determined with ICP-MS (inductively coupled plasma - mass spectrometry.
PerkinElmer). For the analyses of ion species, the remaining half of each ﬁlter was used
for aqueous extraction in a microwave bath. Ions were then determined using ion
chromatographic methods. Detection limits based on a sampling volume of 48 m3 were:
0.5 ng/m3 for cobalt, cadmium, antimony and vanadium; 3.3 ng/m3 for lead; 1.0 ng/m3 for
platinum; 0.33 ug/m3 for sulfate; 0.21 ug/m3 for nitrate and 0.06 ug/m3 ‘strong acid‘
(chloride anions).

The mini-Wright peak ﬂow meters (Clement Clarke International Ltd.. London
UK) were distributed to each child. The study was approved by the Data Protection
Agency of the State of Hamburg, Germany, by the Ministry of Cultural Affairs of
Hessen. Germany, and by the local school committees. According to the requirements of
the Ethical Committee of the Board of Physicians and the Data Protection Agency of the
State of Hamburg, informed consent was Obtained from the parents or legal guardians of

all participating children.

13

 

.GroB-Gerau

oCrumstadt oEschollbrticken
oBiebesheim oBickenbach
oGernsheim
Rhein Michelstadt e

 

 

 

Figure 1: Map of the seven Southwestern German communities with children
participating in peak ﬂow measurements

14

Questionnaires

A questionnaire designed to investigate a variety Of environmentally related
health outcomes had previously completed for each child in 1995 as part of the larger
cohort investigation. In addition, a follow-up questionnaire was distributed and
completed by the parents in 1996. A history of physician diagnosed asthma or current
wheezy bronchitis, of asthmatic complaints in the preceding 12 months, and of parental
atopy (ascertained as maternal or parental history of asthma, hay fever, or eczema) were
determined based on the 1995 and 1996 questionnaires. Additional information collected
on the children included gender, birth-date, environmental tobacco smoke exposure
(deﬁned as never, 1 day a week, a couple of times a week, or daily), height (centimeters).
weight (kilograms), as well as any respiratory symptoms experienced during the study
period. Height and weight were recorded directly on the data sheet (see Appendix A)
based upon the child’s height and weight on the ﬁrst day of participation in both February
and March. For February and March three and six children respectively were missing
either height or weight measurements. For these children height and weight information
was obtained either from questionnaire data (7 children) or the preceding month's
measurement (2 children) depending on which date was closer to the child‘s ﬁrst PEFR
trial. All measurements taken from questionnaire data were determined within one week
of the ﬁrst trial. Similarly, the presence of any of the following symptoms were recorded
directly onto the data sheet for each day of participation: coughing or shortness of breath
at night or in the morning, coughing during exertion or upon exposure to cold air, or any

wheezing or whistling sounds. In addition to the respiratory symptoms. parents were

15

instructed to record any use of prescription medication and to specify which medications
had been used each day.
Peak Expiratory Flow Rate

Children and parents were instructed in the correct use of the mini-Wright peak
ﬂow meter, and were instructed to perform all tests in a standing position. Parents were
also instructed to record the best of three readings (Enright, Sherrill et al. 1995; Ilolcroft.
Eisen et al. 2003) achieved by their child twice each day. The morning period, between
7am-9am, was prior to the use of any medications. The evening measurement was to
occur between 4pm-7pm. Measurements were recorded on a sheet that reinforced the
instructions (see Appendix A). The importance of the correct time for measurements was
emphasized and parents were encouraged to insert blanks rather than inaccurate data.
PEFR measurements were recorded over a maximum of 10 consecutive days in February
1996 and again in March 1996.
Statistical analysis

For each child, the APEF was deﬁned as the deviation of each PEFR
measurement from the child’s mean PEFR. This value was calculated for APEFam and
APEFpm separately by subtracting the child’s mean PEFR over the entire study from the
recorded value for that day and subsequently dividing by the child’s mean PEFR. These
child-speciﬁc deviations were then standardized by multiplying each Observation by
199.1, the mean PEFR for the entire population. (Neas, Dockery et al. 1995) Values
determined to be outlier, greater than three standard deviations from the mean. were
removed from analysis. Linear regression analyses of 5 day moving averages of air

pollution variables and the APEF values controlling for gender. age, linear time-trend.

16

BMI. and ETS exposure were performed for each pollutant separately utilizing the mixed
procedure of SAS. For all repeated measurements, an unstructured covariance matrix
was assumed. All analyses were performed using SAS statistical software version 9.1.
(SAS Institute Inc., Cary, NC, USA)

Hypertonic saline challenge test

A pharmacologic hypertonic saline challenge tests was completed to assess bronchial
hyperreactivity (BHR) at the time of the third survey in 1997. Subjects were excluded
from the tests if their baseline F EVI was less than 65% of predicted value. We obtained
a history of respiratory infection that occurred during the week preceding bronchial
hyperreactivity testing. The BHR test was done at a later visit if the child had been
suffering from a respiratory infection in the last 7 days. The bronchial challenge test was
done following standard procedures. The 4.5% hypertonic solution was prepared by
adding 45g of dialysis-grade sodium chloride to 1,000 ml of sterile pyrogen-free water.
The aerosolized solution was delivered using an ultrasonic nebulizer (particle-size
distribution, 0.5-5 mm; mean, 2.8 mm; De Vilbiss Ultraneb 2000, De Vilbiss, Langen.
Germany), connected to 60 cm of corrugated aerosol tubing (inner diameter. 2.2 cm) and
two non-rebreathing valves (Hans Rudolph 1410, Hans Ruldolph, Inc., Kansas City.
MO). The mean output of the nebulizer was 2.14 ml/min. During the test, the dose of
hypertonic saline was increased successively by doubling the aerosol inhalation time.
starting with 30 sec up to 8 min. One minute after each inhalation, a ﬂow-volume curve
was recorded. The challenge test ended when FEVl had fallen >=15%. or after a
cumulative inhalation time of greater than 15.5 min or a cumulative dose of 23 ml of

hypertonic saline had been used. BHR was deﬁned as a fall in FEVl >=15%.

17

Chapter 3

RESULTS

Selection and description of the study population

Of the 84 children eligible to participate in the study 72 (85.7%) agreed to
participate. Of the 72 children who were enrolled in the study, 70 (97%) participated in
both the February and March trial periods. The average morning PEF in February was
294.0 i 62.4 L/min, whereas the average evening PEF was 298.1 :E 62.3 L/min. The
values were similar for March with 303.4 i 53.6 L/min and 306.6 i 53.3 L/min
respectively. The average variation between morning and aftemoon PEF was 4.4 :I: 29.4
L/min and 4.3 :t 25.2 L/min for February and March respectively.

The demographics of the children studied are summarized in Table l. A slightly
higher percentage of girls than boys participated in the study, 54.3% versus 45.7%. The
average age of the children at their ﬁrst PEF measurement was 9.23 i 0.37 years old. All
ages were calculated directly from the child’s birth date. Sixty-one children (87%) had
complete height and weight information for both months. A majority of children (62. %)
had no reported ETS exposure within the previous week. Fifty-nine (84.3%) of the
children had complete ETS exposure information for February and March. For those
children (7) who were missing either February or March data, ETS exposure was
determined based on the value reported in the preceding or subsequent month. For the 3
children who were missing ETS for both February and March, ETS exposure was taken
from a 1997 questionnaire completed by the child’s parents ascertaining the average ETS

exposure of the child per week.

18

Outdoor air pollution

During the study period, the mean air pollution concentration for PM;_5 ranged
from 33.35 ug/m3 in Bickenbach to 41.0 jig/m3 in Gemsheim (Table 2). The mean 24
hour concentrations on PM;,5 exceeded the World Health Organization and the United
States NAAQS recommendation on 11 out Of 55 days between February 4, 1996 and
March 31, I996. The mean concentration for 8042' ranged from 4.55 ug/m3 in
Bickenbach to 5.1 1 ug/m3 in Michelstadt. The mean concentration for NO3' ranged from
3.29 ug/m3 in Bickenbach to 4.02 jig/m3 in Gemsheim. With respect to trace element
speciation, there was a noticeably higher mean cobalt concentration for Michelstadt
compared with the other communities. Similarly, there was a higher mean platinum
concentration in Crumstadt compared to the other Sites.

There was a high degree of inter-correlation between the air pollution variables
(Table3). Twenty-four hour PM;,5 concentrations were found to be statistically correlated
with levels Of 8042' (rgpcmm: 0.69, p<0.001), arsenic (rgpwmm: 0.84, p<0.001), lead

(rgpwmmnz 0.0.76. p<0.001) and antimony (rgpcammn: 0.85, p<0.001).

l9

 

Table 1: Demographics of 70 German Children
Participating in the Human Health Bio-monitoring Program

 

 

Age (years)
Height (cm)

Weight (kg)

Gender

ETS: number of days
within previous week
where child was
exposed

History of physician
diagnosed asthma

Parental atopy

Boys
Girls

Never
One

3.5

Yes
No

Yes
No

9.23 :l: 0.37

137.5 :I: 6.8

31.6 :1: 6.2

Number Percent

64 45.7
76 54.3
44 62.86
23 32.86
3 4.29
3 4.3
67 95.7
24 34.3
46 65.7

 

20

 

 

 

 

 

 

 

 

 

Table 2a: Daily daytime mean and maximum concentrations of PM; 5, 8042'. N03' and

Strong Acid across seven Southwestern German communities for 26 days between
February and March 1996

Location Mean D e122; 0 n Minimum Maximum # mi sgin
CR 37.88 22.66 10.40 98.00 19 7
MI 3928 17.36 9.30 70.20 23 3
CG 37.80 16.89 10.70 69.40 26 O
(537$) PF 35.08 16.20 10.10 62.80 24 2
Bl 37.32 16.73 11.10 69.00 25 1
GE 41.00 19.38 13.30 71.10 24 2
BB 33.35 15.90 10.40 69.40 25 1
CR 4.94 3.612 0.84 13.22 19 7
MI 5.11 3.48 0.79 12.65 24 2
SO 2. GG 4.93 3.32 0.88 12.74 25 1
4 3 PF 4.70 3.26 0.75 12.72 24 2
(“g/m ) Bl 4 81 3 28 0 89 13 22 25 1
GE 5.03 3.49 0.91 13.58 25 1
BB 4.55 3.13 0.73 11.77 25 1
CR 3.34 1.82 0.55 7.06 19 7
MI 3.29 2.04 0.30 9.25 24 2
NO‘ GG 3.34 2.05 0.17 10.15 26 0
(pg/r7313) PF 3.35 1.75 0.16 6.98 24 2
Bl 3.81 1.79 1.27 9.00 25 1
GE 4.02 2.05 1.16 9.19 25 1
BB 3.20 1.89 0.14 6.67 25 1
CR 0.10 0.14 0.02 0.54 17 9
MI 0.09 0.11 0.02 0.41 19 7
3:239 GG 0.08 0.10 0.02 0.40 20 6
Cl" PF 0.13 0.18 0.02 0.66 19 7
(pg/m3) Bl 0.13 0.16 0.02 0.63 18 8
GE 0.10 0.15 0.02 0.58 19 7
BB 0.09 0.12 0.02 0.46 20 6

 

 

 

CR = Crumstadt, M1 = Michelstadt, GG = Auf Esch-GroB-Gerau. PF = Eschollbrijken-
Pfungstandt, B1 = Biebesheim, GE = Gemsheim, BB = Bickenbach

21

 

Table 2b: Daily daytime mean and maximum concentrations of 7 select trace elements
across seven Southwestern German communities for 26 days between February and March
1996

 

 

 

 

 

 

 

. s . . . #
Location Mean Devigfi on Minimum Maxrmum # missin

CR 0.55 0.02 0.51 0.57 18 10

Ml 0.71 0.62 0.55 3.40 21 5

c GG 0.56 0.01 0.55 0.58 23 3

”a"; PF 0.57 0.01 0.56 0.58 21 5
("Q/m )

Bl 0.56 0.01 0.55 0.57 22 4

GE 0.56 0.01 0.55 0.57 22 4

BB 0.56 0.01 0.55 0.58 22 4

CR 2.14 2.34 1.13 9.31 19 7

MI 196 2.33 1.23 10.43 24 2

c . GG 1.83 2.10 1.23 10.39 26 o

adm'gm PF 1.73 1.89 1.24 10.37 24 2
(ng/m )

Bl 1.63 1.85 1.23 10.53 25 1

GE 1.66 1.23 1.22 6.42 25 1

BB 1.58 0.96 1.22 5.04 25 1

CR 2.71 2.88 0.80 10.10 17 9

MI 3.30 3.04 0.88 9.82 23 3

Arsenic GG 3.14 3.09 0.88 10.92 25 1

(”g/m3) PF 2.98 2.95 0.89 9.57 24 2

Bl 2.77 2.90 0.88 10.19 24 2

GE 3.12 3.14 0.88. 10.01 25 1

BB 2.95 2.91 0.87 10.09 25 1

CR 30.58 17.33 8.07 63.37 19 7

MI 33.63 19.07 8.97 72.34 24 2

L d GG 30.30 18.41 7.56 67.70 26 0

(”g/ﬁns) PF 32.58 17.20 11.38 71.32 24 2

Bl 31.79 18.03 8.52 68.75 25 1

GE 33.19 22.09 6.55 97.27 25 1

BB 2772 16.01 6.81 63.07 25 1

 

 

CR = Crumstadt. M1 = Michelstadt, GG = Auf Esch-GroB-Gerau. PF = Eschollbriiken-
Pfungstandt, BI = Biebesheim, GE = Gemsheim, BB = Bickenbach

22

 

Table 2b (continued): Daily daytime mean and maximum concentrations of 7 select trace
elements across seven Southwestern German communities for 26 days between February
and March 1996

 

 

 

 

 

 

Location Mean Deﬁgi on Minimum Mammu misZinL

CR 1.30 0.97 0.12 2.97 16 10

MI 1.36 0.93 0.13 3.23 21 5

Antimony GG 1.36 1.03 0.13 4.23 23 3

3 PF 1.44 0.90 0.13 3.16 21 5
(“g/m )

BI 1.38 0.95 0.12 3.34 22 4

GE 1.36 0.93 0.12 3.05 22 4

BB 1.23 0.79 0.13 2.67 22 4

CR 2.79 1.82 0.48 6.28 14 12

MI 3.13 2.21 0.47 6.80 20 6

Vanadium GG 2.95 2.01 0.48 6.67 22 4

3 PF 2.76 1.86 0.49 6.17 21 5
(rig/m )

BI 2.78 1.81 0.48 6.44 21 5

GE 3.20 2.35 0.47 8.97 22 4

BB 2.94 2.02 0.47 6.24 22 4

CR 0.25 0.50 0.11 2.11 16 10

MI 0.13 0.00 0.12 0.13 21 5

Platinum GG 0.13 0.00 0.12 0.13 23 3

3 PF 0.13 0.00 0.13 0.13 21 5
(ﬁg/m )

BI 0.13 0.00 0.12 0.13 22 4

GE 0.13 0.00 0.12 0.13 22 4

BB 0.17 0.22 0.12 1.18 22 4

 

 

CR = C rumstadt, M1 = Michelstadt, GG = Auf Esch-GroB-Gerau, PF = Eschollbrtiken-
Pfungstandt, B1 = Biebesheim, GE = Gemsheim, BB = Bickenbach

23

 

8E6:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

88W:

83 E
ovmdna

on Pu: on w": 863:

88.8 883 8>
m~v8n8 388.88

82": 88W: 82": ME8
8 3.8- 43.8 888. 3 8m
88888 388.88 388.88

82" 88W: 8W8 8V: 4.58:

:88- 88.8 ~58 83 an.
$488 38.88 388.88 388.88

88": 88W: 82": 82»: 83": ”E88
88.8. 88.8 888.8 83 83 w<
388.88 388.88 88.88 38888 388.88

82": 82": 82": 88.": 88W: 82": ”.58:

-88 88.8. 8~8.8- 88.8- 388- 888. 3 no
5888 888“ 83.88 82.8" 888.88 388.88

83": 88.": 82": 88.": 88W: 83": 82": ME88

58 -88 ~88- 888 88.8 8~v8 888. 3 8
83.88 38888 38488 88.88 58.88 88.88 88.8"8

82": 82": 82" 88W: 88W: 82": 82" 82": sea:

~3 8- 89.8- 88.8- ~8~.8- 88.8- ~88 8. 8- 88.3 22. 8:888
.888 388.88 «888 88.88 mv~8u8 83.8"8 ~88.8u8 388.88

82": 8E. 82": 89": 88W: 82": 82": 83": 83": mean

83.8- 5.8- 883.8 888.8- 383.8 888 83 8- 83.8 883 .62
88.88 38888 388.88 388.88 388.88 38888 :88" 88.88 28.88

88W: 88W: 82": 82": 82": 82": 82" 82": 82": 88.": 4:8:

8888- «9.8 ~88 «88.8 828 8:48. 8.88 88.8- :~.8- 883 A .08
42.88 388.88 388.88 88.88 38.88 8888 3.888 E388 88888 388.88

8 3": 82": 82": 82": 8W8 83": 82": 883": 82": 88W: 82": ”E81

88.8- 88.8 8488 88 88.8 8-.8- 488.8 m: 3.8- 8~8 8888 3 m 828

E m> 8m 88 2 no oo 93 8896 .62 A 40m 8 N28

 

 

9:93:08 Ea .oouSo EmBEm :09: “893888.. .2 956580 8:26:00 cwEmeqw Mm 832.

 

 

24

Description of outcome and external validity

The relative proportion of children completing both morning and afternoon peak
expiratory ﬂow rate maneuvers are presented in Table 4. The participation proportions
ranged from 4.3-87% for February and between 15.7%-100% for March. If the ﬁnal two
days of the study are excluded, the values are between 71.4%-87% and 97.1 %-100%
respectively. p

The relationship between the children’s mean morning PEFR, mean aftemoon
PEFR, APEFam and APEFpm with various external measures of bronchial hyperreactivity
are presented in Table 5. For morning and afternoon PEFR, the mean values coincide
favorably with all three external measures of lung function. Similar results are seen with

APEP,,,., and APEFpm.

25

 

Table 4: Number of children completing both morning and
afternoon PEFR measurements by day

 

 

Feb-96 Mar-96
Day NngZegrgf Percent Ngmlgfésf Percent

1 54 77.1 70 100.0
2 61 87.0 69 98.6
3 52 74.3 68 97.1
4 56 80.0 69 98.6
5 57 81.4 69 98.6
6 55 78.6 69 98.6
7 53 75.7 69 98.6
8 50 71.4 70 100.0
9 4 5.7 1 1 15.7
10 3 4. 3 1 1 15.7

 

26

 

 

Table 5: Relationship between study mean peak expiratory ﬂow rate and external measures of
bronchial hyperreactivity

 

 

 

Measures of # of # of 05% 9598—4
hyperreactivity Outcome children observations Mean Std CL CL
Hyperreactivity

score _,

0 Morning 48 742 303.7 61.0 299.3 30.8
1 PEF 15 232 295.7 49.5 289.2 302.1
22 (Umin) 7 102 268.6 47.3 259.3 277.9
0 Afternoon 48 732 306.8 60.8 30.2 31 1 .2
1 PEF 15 231 300.1 51.5 293.4 306.7
22 (Umin) 7 102 274.9 44.5 266.1 283.6
0 APEF 48 732 0.91 2.89 0.70 1.12
1 (0/0)AM 15 227 0.37 3.15 -0.04 0.78
22 7 104 0.31 3.63 -0.39 1.02
0 APEF 48 732 0.87 2.64 0.68 1.06
1 (°/o)PM 15 231 0.62 3.45 0.17 1.07
22 7 102 0.37 3.77 -0.37 1.11

Hypertonic

saline test

Requnse 7 106 304.7 38.2 297.3 312.0

missing Morning

<15% FEV1

. PEF 53 809 300.2 61.4 295.9 304.4
reduction (Umin)

215% FEV1

reduction 10 161 286.9 52.1 278.8 295.0
Rei‘p‘?“ 7 106 308.9 40.1 301.2 316.6
missing

<15% FEV1 Afternoon

. PEF 53 801 302.4 59.8 298.3 306.6
reduction (Umin)

215% FEV1

reduction 10 158 297.0 60.2 287.6 306.5
Response
missing 7 109 0.42 2.96 -0.14 0.98
<15% FEV1 APEFAM
reduction (%) 53 793 0.81 2.94 0.60 1.01
215% FEV1
reduction 10 161 0.60 3.51 0.06 1.15
Response
missing 7 106 0.65 2.49 0.17 1.13
<15% FEV1 APEFFM
reduction (%) 53 801 0.81 2.78 0.62 1.00
215% FEV1
reduction 10 158 0.62 3.98 -0.01 1.24

 

27

 

 

Table 5: Relationship between study mean peak expiratory flow rate and external measures of
bronchial hyperreactivity

 

 

Measures of

hyperreactivity Outcome
Diagnosed
Asthma
No Morning
Yes PEF
(Umin)
Afternoon
”0 PEF
(Umin)
Yes
NO APEFAM
Yes (°/°)
N0 APEFFM
Yes (%0

# of
children

67
3

67

#of

observations

1 034
42

1 024

41
1018
45
1024
41

Mean

300.3
256.9

303.6

269.0
0.75
0.41
0.77
0.59

Std

58.0
51.9

58.1

51.6
3.02
3.36
2.90
4.16

05%
CL

296.8
240.7

300.1

252.7
0.57

-0.60
0.60

—0.72

95%
CL

303.9
273.1

307.2

285.3
0.94
1.42
0.95
1.91

 

28

 

Estimate coefﬁcients for the APEFam and APEFpm are summarized in tables 6 and
7 respectively. Regarding APEFam, no pollutants attained statistical signiﬁcance.
Analysis Of APEFpm yielded a statistically signiﬁcant adverse association between
increasing levels Of NOg' and aftemoon PEF rates. The estimate corresponds to a 0.1 1
L/min reduction in mean aftemoon PEFR per 1 jig/m3 increase in NO_;' concentration. A
similar adverse association was seen with strong acid concentration. A 1 rig/m3 increase
in mean chloride concentration resulted in a 12.7 L/min reduction in afternoon PEFR. A
borderline signiﬁcant adverse association was also seen for antimony. A l ng/m3
increase in mean antimony concentration resulted in a 3 L/min reduction in afternoon
PEFR. After speciﬁcation of a two-pollutant model with PM2.5 and antimony the effect
estimates no longer showed a clear association. Nitrate ion was the only pollutant to have
an adverse impact on both morning and afternoon PEFR. Increasing levels of cobalt.
8042‘, arsenic, lead and vanadium all had an apparent protective affect with respect to

both morning and aftemoon PEFR.

29

 

Table 6: APEFam effect-estimates with standard error of air
pollution on peak expiratory ﬂow

 

Controlling for site, 1

gender, gge, time trend, ETS and BMI

 

 

 

 

 

 

 

 

 

 

 

 

 

Estimate std error p-value
PM,5 ,,,,,.,3, 0.01835 0.05990 0.7594
so} ,,,g,,,,3, 0.1223 0.2773 0.6594
NO3' ,,._,,m3, 01079 0.4033 0.7892
Stmng Acid: C'- 4.8594 5.1664 0.3472
(tug/m )
Cobalt (ng/ma) 37.6544 64.6885 0.5607
Cadmium (ng/ma) 0.2454 0.4134 0.5529
Arsenic (ng/ma) 0.07751 0.3216 0.8096
Lead (ng/m3) 0.02947 0.05614 0.5998
Vanadium (ng/ma) 0.8732 0.4710 0.0641
Antimony (ng/ma) 0.5774 1.469 0.6944
Platinum (ng/ma) -0.9654 10.4256 0.9262

 

 

 

 

30

 

 

Table 7: APEFpm effect-estimates with standard error of air
pollution on peak expiratory ﬂow

 

Controlling for site, gender, age, time trend, ETS and BMI

 

 

 

 

 

 

 

 

 

 

 

 

 

B Coefficient std error p-value
PM2 5 ,,,g,,,,3, 0.03234 0.06110 0.5968
8042' (“9.3, 0.4837 0.2823 0.0870
N03- noma- -1.1174 0.4103 0.0066
Stmng Acid: C" -12.7643 5.2326 0.0149
(Pg/m )
Cobalt (ng/ma) 123.11 69.6449 0.0775
Cadmium (ng/m3) 01404 0.4224 0.7396
Arsenic (ng/m3) 0.1201 0.3253 0.7120
Lead (ng/m3) 0.003911 0.05633 0.9447
Vanadium (ng/ms) 0.8339 0.4752 0.0797
Antimony (ng/ma) -2.9691 1.4838 0.0458
Platinum (ng/ma) 20.8023 10.9793 0.0585

 

 

 

 

31

 

Chapter 3

DISCUSSION

This study found evidence supporting a relationship between ambient NO3' and
strong acid aerosols air pollution concentration and a reduction in aftemoon peak
expiratory ﬂow rate. We found no clear associations between ambient PM2.5, 8043'. or
trace metals with respect to reductions in PEFR in a cohort of primary school children.
These results support other recent European reports that failed to show clear associations
between these air pollutants and PEF. (Roemer, Hoek et al. 1998; Peacock. Symonds et
al. 2003)

Previous studies have documented reductions in various lung function
determinants in children exposed to increasing levels ofNO;. (Timonen and Pekkanen
1997; Peters, Avol et al. 1999; Peacock, Symonds et al. 2003) In their study. Peters et al.
reported a negative association between NO; and forced vital capacity. FEV ., and
maximal midexpiratory ﬂow rates in girls. No similar effect was seen with respect to
boys. Timonen and Pekkanen demonstrated a signiﬁcant association between NO; levels
and reductions in morning PEFR in a cohort of Finnish school children. They reported
no effect on afternoon PEFR. In another report, Peakcock et al. 2003 reported
statistically signiﬁcant reductions when stratifying for children who experienced large
reduction in PEF R measurements. The results of the current study, showing a signiﬁcant
reduction in afternoon rather than morning PEF rates among school age children, suggest
the possibility that may be differences between this report and previous studies. It is

possible that monitoring NOg' rather than NO; concentrations. contributed to the

32

differences. In addition, since we are unable to control for ozone levels. it is possible that
the affects attributed to NO3' levels in the current study may in fact be due to exposure to
ambient ozone concentrations. (Just, Segala et al. 2002)

The association with strong acid vapor is similar to that reported by Neas et al
1995. (Neas, Dockery et al. 1995) They reported a 2.5 L/min reduction in PEF with
strong acid aerosols measured as H+ ion concentration. The magnitude of the effect
estimate in the current study is surprising given the low levels of acid aerosols detected.
Given that the standard error was large it is likely that the true effect estimate is much
lower.

The Observed effect between antimony and afternoon peak expiratory ﬂow rate
was unexpected. Although previous studies have implicated various transition metals. no
study has indicated antimony speciﬁcally. It is possible that this was a chance
association. It is also possible that the affects attributed to antimony may be confounded
by another metal species such as iron. (Roemer, Hoek et al. 2000) This hypothesis is
supported by the high correlation between various metal species in this study.

The lack of effect for other pollutants in this study cannot be adequately explained
by low levels of exposures. The average PM2.5 and 8042' concentrations for the study
period were similar to or higher than other reported European studies. (Roemer, Hoek et
al. 2000) It is noteworthy that the average NO3' concentrations during this study period
were actually lower than NO; concentrations reported in previous studies. It is
acknowledged that the lack of any additional associations could also be explained by low
power. The study population consisted of only 70 children and a maximum of 1.145

child-day Observations. It is reasonable to conclude that the current study would not have

33

sufﬁcient power to detect the small decrements reported by previous studies. (Neas.
Dockery et al. 1995; Hock, Dockery et al. 1998)

One proposed difference between those studies which have reported a positive
association and those studies which no association was observed concerns the make-up of
the various study populations. In many studies reporting an inconsistent relationship
between air pollutants and various outcomes involving PEF, researchers have operated
under the population average model. This model assumes that all children in the
population will have a similar sensitivity to the effects of air pollutants.

A competing theory which was ﬁrst proposed by Hoek et al. 1998 (Hock,
Dockery et al. 1998) Operates on the assumption that there is a heterogeneous response to
air pollution among the childhood population. In this model, the authors only suggest
that only a small proportion of children will be sensitive to the effects of respiratory
insults. The conclusion based upon the population susceptible model is that overall
effects observed in outcomes based upon continuous variable analyses will be diluted by
the majority of children who are not susceptible. Evidence for this theoretical model is
provided by several studies verifying a positive association betweenlevels of air
pollution and childhood lung function deﬁcits in children with chronic respiratory
complaints. (Neas, Dockery et al. 1995; Yu, Sheppard et al. 2000) Further support has
been provided researchers having demonstrated a more consistent association between
ambient air pollution concentration and large PEFR decrements. (Hoek, Dockery et al.
1998; Peacock, Symonds et al. 2003) As only three of the children in this study were
conﬁrmed to be asthmatic and only four used bronchodilators during the course of the

study, subgroup analysis in the current study was not feasible.

34

In addition. the lack of daily determinations of air pollutants is a potential
limitation of the study. It is possible that the lack of complete measurements obscured
possible associations due to misclassiﬁcation of the actual 5 day average pollutant
exposure. This hypothesis is supported by signiﬁcant ﬂuctuations in pollutant levels for
several of the communities. However, this is unlikely to systematically bias the data
since each center collected data on a similar time schedule and any missing values would
have been unknown to the children or parents.

Similarly, the lack of site-speciﬁc temperature readings could have obscured any
associations. This, however, is also unlikely as all of the communities except Michelstadt
are in the Rhine Valley and therefore. regional climate trends would not be expected to
vary dramatically between sites.

Although the multiple locations of air pollution collection data. the establishment
of schools as the sites of collection, and the restriction of the study population to those
children within one kilometer of the schools, reduces the possibility of exposure
misclassiﬁcation, the possibility remains. The inability to account for time spent
outdoors may have accounted for the observed lack of association. Neas et al. have
reported that accounting for individual time spent outdoors increases the magnitude of
effect estimates and reduced variation in outcomes. (Neas, Dockery et al. 1995)

Furthermore, since the PEFR determinations were made during colder months. it
may be reasonable to assume that children would spend less time outdoors and have had
less exposure to ambient air pollution. With the exception of exposure to N03”. less time
spent outdoors would be expected to bias the results toward a null association. It is

possible that during colder months. the use of home heating oil would increase thereby

35

resulting in increasing indoor concentrations of NO3'. The combination of higher indoor
NO3’ concentrations and children spending more time indoors could drastically alter the
reported association between ambient outdoor NO3' concentrations and peak ﬂow rate
measurements.

Another potential limitation in the current study is the inability to account for
respiratory infections and other infectious outbreaks during the study period. It is
possible that infectious agents may have inﬂuenced the children’s lung function and
biased the effect estimates on PEF. As infectious processes would have varied in time.
severity and location, any potential association between air pollution and PEF
measurements based upon communities may have been biased. Due to the nature of
these infections, it is reasonable to conclude that these biases could have occurred in
either direction. In one scenario, an inﬂuenza outbreak in a community with low average
daily pollution could bias the results toward the null whereas an infectious outbreak in a
community with high daily averages of pollutants could bias the results in a positive
direction.

Similarly, the inability to account for seasonal allergic rhinitis may have
confounded the association between PEF R and air pollution levels in susceptible
children. During data analysis, we attempted to correct for child hay fever by controlling
for parental history of atopy. It is possible that although parental history of atopy has
been shown to be a risk factor for childhood allergic rhinitis, (Graif. Garty et al. 2004) it
was not a sufﬁcient indicator of hay fever in these children.

Another possible contributing factor could result from the use of mini-Wright

peak ﬂow meters to assess PEF. The portable peak ﬂow meters are considered less

36

precise than timed forced expiratory volumes measured by spirometry. (Giannini.
Paggiaro et al. 1997) The absence of complete spirometry is a potential limitation of the
study. however Neas et al. (Neas, Dockery et al. 1995) reported on a similar population
based cohort in Uniontown Pennsylvania. They observed high correlations between
PEFR measurements and FEV1 values Obtained via spirometry. Furthermore. the
correlation between both PEF and APEF with external measures of bronchial
hyperreactivity would suggest reasonable reliability.

The short duration of the measurement periods, prevented controlling for any
potential training effect in the use Of the peak ﬂow meters. Previous researchers have
documented that inconsistencies due to training effect are observed for the ﬁrst 2-3 days
of measurement. (Siersted, Hansen et al. 1994; Enright, Sherrill et al. 1995) The inability
to correct for any potential training effect is an accepted limitation of the study.

A common practice in studies analyzing the relationship between outdoor
pollutants and lung function is to construct multiple statistical models with varying lag
day exposures and to report those associations which are the strongest. While the exact
temporal relationships between exposures to air pollutants and potential physiologic
inﬂammatory responses are not known, this practice increases the potential of detecting a
chance association. Maintaining the relationship as a 5-day moving average minimizes
the risk of Obtaining an erroneous association based upon model selection. Furthermore.
studies have observed a larger and more precise estimate regarding the effect of air
pollution exposure on lung function using the 5-day average instead Of shorter periods of

exposure. (Pope and Dockery 1992; Gold, Damokosh et al. 1999)

37

In addition, the use of APEF may have limited the potential to detect changes
between a child’s morning and afternoon PEF rates. In measuring the effect of maternal
smoking on childhood lung function (Frischer, Kuhr et al. 1993), investigators involved
in the current study employed the percentage ratio of the amplitude above the mean
(AVAM) of daily PEF R. (‘Voamplitude/mean = (abs(PEF pM-PEFAM))/meanX100) as a
measure of bronchial hyperreactivity. The AVAM model is conceptually based on an
asthmatic model where morning peak ﬂow rates are thought to be disproportionately
affected by ambient air pollution levels in comparison to afternoon and evening rates. In
such models, an increase in the calculated PEFR variability (AVAM) is thought to
correspond to increased BHR. This phenomenon is based on a physiologic understanding
of airway hyperreactivity in relation to diurnal variations serum cortisol levels. The end
result of this relationship is an observed increase in susceptibility to airway insults in
morning hours when cortisol levels are at their nadir in the bloodstream. Although this
model has been employed successfully in populations with known BHR (asthmatics). its
applicability to non-asthmatic populations is less clear. In the current study population.
we observed that many of the children had evening PEFR that were consistently lower
than their morning PEFR. The authors concede that the Observed decrements in
aftemoon PEF may simply reﬂect a more accurate response to ambient air pollution
given increased exposure to outdoor environments. Furthermore, there may have been a
greater degree of exposure misclassiﬁcation in regard to morning PEF secondary to the
anticipated increase in time spent indoors during night-time and early morning hours.
Irrespective of the potential etiology, the authors do not feel that the relative decrements

in PEFpM Observed in the current study would accurately be reﬂected in the AVAM

38

model. Given these ﬁndings. we would further caution future researchers who might
consider employing this model in non-asthmatic populations.

Another potential factor which could have limited our ability to detect effects of
air pollution on lung function was the assumption of an unstructured covariance structure
in the statistical models. Given the perceived correlation between each individual child's
daily PEF R measurements, not accounting for this correlation would have resulted in
increased sampling error for the B-coefﬁcients. Typically, this would be expected to bias
the hypothesis toward the null association. We attempted to correct for correlation and
thus improve precision of the B-coefﬁcient estimates by ﬁtting the model to a first order
autoregression structure. Upon analysis, these models did not allow convergence of the
matrix. We suspect this was due to the relatively short time period for the repeated PEFR
measurements and the lack of individual measurement variability with respect to time.

To our knowledge, there are very few epidemiological studies investigating the
adverse health impacts of trace metal exposure. One report investigating the association
of various transition metals with adverse respiratory outcomes indicated a positive
association between ambient iron, nickel, and zinc concentrations with daily mortality
(Burnett, Brook et al. 2000) in adults. Another report studied the association between
trace metal PM“) speciation and PEF. (Roemer, Hoek et al. 2000) The authors reported
no signiﬁcant effect between iron, nickel, zinc, vanadium, sodium, lead or silicon with
APEFpM or APEFAM.

We are unaware of any published study which has attempted to analyze speciﬁc
health outcomes with the individual speciation of PM;,5. In a recent study conducted in

Michigan, Batterman et al. (unpublished) reported that weaker correlations were Observed

39

between two sites for trace metals than for gaseous air pollutants. Their speciation
analysis of PM;.5 also concluded that the contribution of various PM;.5 species was more
dependent on Speciﬁc site location and local pollutant sources than was observed for
other pollutants. The absence of a clear association between various trace metals and
PEF R in the current study could indicate that at the levels reported there is no signiﬁcant
health impact. It is also possible that the variation between communities was insufﬁcient
to detect any potential health impact. With the exception of platinum, this hypothesis is
supported by similar variation between mean PM2.5 concentrations and the mean
concentrations of the transition metals. The large protective association seen for
platinum may be explained by the large discrepancy between Crumstadt and Bickenbach
and the other communities. A similar discrepancy was Observed with cobalt between
Michelstadt and the other communities respectively.

In conclusion, this longitudinal study of 70 children in Southwestern Germany
failed to demonstrate consistent associations between air pollutants and childhood lung
function as measured by changes in morning and aﬁemoon peak expiratory ﬂow rates.
The results provide additional evidence for reductions in childhood lung function
associated with exposures to low level ambient NO3' and strong acid aerosol
concentrations. The inability to demonstrate adverse affects of particulate matter on PEF
support previous studies in which no clear associations were established in a healthy
population. The signiﬁcant association Observed for antimony suggests further research
into health effects of various transition metal species is warranted. The inability to

demonstrate consistent relationships supports previous assertions that future research

40

endeavors investigating associations regarding PM and its speciation should target

susceptible children with chronic respiratory complaints.

41

APPENDICES

42

APPENDIX A

PEAK FLOW MEASUREMENT DATA SHEET ENGLISH TRANSLATION

43

 

 

 

O O O O
o O O o
o o o O
o o o o

LDC/OZ

8:0

.435 8 SE: 36.: <

.888

832:8 3388.85
:88; 2.3.5.8 c: 5 :52 8 E EEO So» v.83
.wESéoEE x35 2: wEE: .cozo 3o:

8.... Wm H_ 8:588 2883
a: L A 7 8.2688286:
E :8 88:

 

 

 

”3:0 :85: 1.3.:

”8:282:22.

O O O O O 0
8.9538 WED-32.5

O O O O O 0
E8 28 8 888896 E:
Co :Ecoxu were: chwon

0 O O O O O
wEEoE 2.: E .5 EE: :8
5885 .8 mmoctosthzwzoO

o o o o o 0

.28: £888 5.. mEoEE>..,. w:_.$o__£ 2: Co .38 38:88:89.8 EEO 56%.: 3:82: 3805
SE 8-8
E< 0-8

8.5

28:28 2: 85 8:28.“ 2: .3 3:882 3 LEE 8:888 2;

.8388 2: :6

m8: :2: 58186:: 8:: 8:08.86 8 848E EoEEﬁPoE 2: 3: E: B: so» .8: E8858 8 .5:

o 8 SEE 882 .88.: £888 .32
wEBoE 8:53 :8888 3885
EBE 8.3 cEEqusm 828:: o: 3803 ”:28:an—

523 .828. 2: E E882 m 85.3 7.8wa 2: Econ: :88 BE: m 8:: o:
3285.58 2: SE 303 827.88 88 7E 88 :58 wcobm m<
328582: 2: “8:888 aim: ma: :5

SEE 53. E 8829:8282: 8.8: :58 5885 new: 8 8.48.8 ”8:28.885

53:52 EEO 8 :5: meENMDmxmei/OALQZMQ

44

References

Abbey, D. E., N. Nishino, et al. (1999). "Long-term inhalable particles and other air
pollutants related to mortality in nonsmokers." Am J Respir Crit Care Med
159(2): 373-82.

Anderson, H. R., S. A. Bremner, et al. (2001). "Particulate matter and daily mortality and
hospital admissions in the west midlands conurbation of the United Kingdom:

associations with ﬁne and coarse particles, black smoke and sulphate." Occup
Environ Med 58(8): 504-10.

 

Atkinson, R. W., H. R. Anderson, et al. (2001). "Acute effects of particulate air pollution
on respiratory admissions: results from APHEA 2 project. Air Pollution and
Health: a European Approach." Am J Respir Crit Care Med 164(10 Pt 1): 1860-6.

 

Baldacci, S.. L. Carrozzi, et al. (1997). "Assessment of respiratory effect of air pollution:

study design on general population samples." J Environ Pathol Toxicol Oncol
16(2-3): 77-83.

Barnett, A. G., G. M. Williams, et al. (2005). "Air Pollution and Child Respiratory
Health: a Case-crossover Study in Australia and New Zealand." Am J Respir Crit
Care Med.

Boezen, H. M., S. C. van der Zee, et al. (1999). "Effects of ambient air pollution on upper
and lower respiratory symptoms and peak expiratory ﬂow in children." Lancet
353(9156): 874-8.

Braga, A. L., A. Zanobetti, et al. (2001). "The lag structure between particulate air
pollution and respiratory and cardiovascular deaths in 10 US cities." J Occup
Environ Med 43(11): 927-33.

Brugge, D., J. Vallarino, et al. (2003). "Comparison of multiple environmental factors for
asthmatic children in public housing." Indoor Air 13(1): 18-27.

Burnett. R. T., J. Brook. et al. (2000). "Association between particulate- and gas-phase
components of urban air pollution and daily mortality in eight Canadian cities."
Inhal Toxicol 12 Suppl 4: 15-39.

 

Chew, F. T., D. Y. Goh, et al. (1999). "Association of ambient air-pollution levels with
acute asthma exacerbation among children in Singapore." Allergy 54(4): 320-9.

Choi. J. H.. .I. S. Kim, et al. (2004). "Comparative study of PM2.5 - and PM10 - induced
oxidative stress in rat lung epithelial cells." J Vet Sci 5(1): 1 1-8.

45

C laibom, C. S., T. Larson, et al. (2002). "Testing the metals hypothesis in Spokane,
Washington." Environ Health Perspect 110 Suppl 4: 547-52.

de Diego Damia, A., M. Leon Fabregas, et al. (1999). "Effects of air pollution and
weather conditions on asthma exacerbation." Respiration 66(1): 52-8.

Delﬁno, R. J ., P. J. Quintana, et al. (2004). "Association of FEV1 in asthmatic children
with personal and microenvironmental exposure to airborne particulate matter."
Environ Health Perspect 112(8): 932-41.

Delﬁno, R. J., R. S. Zeiger, et al. (2002). "Association of asthma symptoms with peak
particulate air pollution and effect modiﬁcation by anti-inﬂammatory medication
use." Environ Health Perspect 110(10): A607-17.

den Otter, J. J ., G. M. Reijnen, et al. (1997). "Testing bronchial hyper-responsiveness:
provocation or peak expiratory ﬂow variability?" Br J Gen Pract 47(421): 48 7-92.

 

Dick, C. A., D. M. Brown, et al. (2003). "The role of free radicals in the toxic and
inﬂammatory effects of four different ultraﬁne particle types." Inhal Toxicol
15(1): 39-52.

Dockery. D. W., F. E. Speizer, et al. (1989). "Effects of inhalable particles on respiratory
health of children." Am Rev Respir Dis 139(3): 587-94.

Douma, W. R.. H. A. Kerstjens, et al. (2000). "Changes in peak expiratory ﬂow indices
as a proxy for changes in bronchial hyperresponsiveness. Dutch Chronic Non-
Speciﬁc Lung Disease study group." Eur Respir J 16(2): 220-5.

 

Douma, W. R.. T. W. van der Mark, et al. (1997). "Mini-Wright peak ﬂow meters are
reliable after 5 years use. Dutch CNSLD Study Group." Eur RespirJ 10(2): 457-
9.

 

Emenius, G., G. Pershagen, et al. (2003). "N02, as a marker of air pollution, and
recurrent wheezing in children: a nested case-control study within the BAMSE
birth cohort." Occup Environ Med 60(11): 876-81.

 

Enright, P. L., D. L. Sherrill, et al. (1995). "Ambulatory monitoring of peak expiratory
ﬂow. Reproducibility and quality control." Chest 107(3): 657-61.

Fauroux, B., M. Sampil, et al. (2000). "Ozone: a trigger for hospital pediatric asthma
emergency room visits." Pediatr Pulmonol 30(1): 41-6.

Ferin, J ., G. OberdorSter, et al. (1992). "Pulmonary retention of ultraﬁne and ﬁne
particles in rats." Am J Respir Cell Mol Biol 6(5): 535-42.

46

F riedman, M. S., K. E. Powell, et al. (2001). "Impact of changes in transportation and
commuting behaviors during the 1996 Summer Olympic Games in Atlanta on air
quality and childhood asthma." Jama 285(7): 897-905.

Frischer, T., J. Kuhr, et al. (1993). "Inﬂuence of maternal smoking on variability of peak
expiratory ﬂow rate in school children." Chest 104(4): 1133-7.

F ung. K. Y., I. Luginaah, et al. (2005). "Air pollution and daily hospital admissions for
cardiovascular diseases in Windsor, Ontario." Can J Public Health 96(1): 29-33.

 

Fusco, D., F. Forastiere, et al. (2001). "Air pollution and hospital admissions for
respiratory conditions in Rome, Italy." Eur RespirJ 17(6): 1 143-50.

 

Garcia Algar, 0., S. Pichini, et al. (2004). "Concentrations and determinants of N02 in
homes of Ashford, UK and Barcelona and Menorca, Spain." Indoor Air 14(4):
298-304.

Gent. J. F., E. W. Triche, et al. (2003). "Association of low-level ozone and ﬁne particles
with respiratory symptoms in children with asthma." Jama 290(14): 1859-67.

Gem. J. E.. P. A. Eggleston, et al. (1994). "Peak ﬂow variation in childhood asthma: a
three-year analysis." J Allergy Clin Immunol 93(4): 706-16.

Giannini, D., P. L. Paggiaro, et a1. (1997). "Comparison between peak expiratory ﬂow
and forced expiratory volume in one second (FEV1) during bronchoconstriction
induced by different stimuli." J Asthma 34(2): 105-1 1.

Gold, D. R., A. I. Damokosh, et al. (1999). "Particulate and ozone pollutant effects on the

respiratory function of children in southwest Mexico City." @idemiology 10(1):
8-16.

 

Goldstein, B. D., R. J. Melia, et al. (1979). "The relation between respiratory illness in
primary schoolchildren and the use of gas for cooking--II. Factors affecting
nitrogen dioxide levels in the home." Int J Epidemiol 8(4): 339-45.

 

Goldstein, M. F ., B. A. Veza, et al. (2001). "Comparisons Of peak diurnal expiratory ﬂow
variation, postbronchodilator FEV(1) responses, and methacholine inhalation
challenges in the evaluation of suspected asthma." Chest 119(4): 1001-10.

Goto. Y., H. Ishii, et al. (2004). "Particulate matter air pollution stimulates monocyte
release from the bone marrow." Am J Respir Crit Care Med 170(8): 891-7.

Gouveia, N. and T. Fletcher (2000). "Respiratory diseases in children and outdoor air
pollution in Sao Paulo, Brazil: a time series analysis." Occup Environ Med 57(7):
477-83.

47

Graif, Y., B. Z. Garty, et al. (2004). "Prevalence and risk factors for allergic rhinitis and

atopic eczema among schoolchildren in Israel: results from a national study." m
Allergy Asthma Immunol 92(2): 245-9.

Hajat. S., A. Haines, et al. (1999). "Association of air pollution with daily GP
consultations for asthma and other lower respiratory conditions in London."
Thorax 54(7): 597-605.

Harkema, J. R., G. Keeler, et al. (2004). "Effects of concentrated ambient particles on

normal and hypersecretory airways in rats." Res Rep Health Eff Inst( 1 20): 1-68;
discussion 69-79.

Harrison, R. M. and J. Yin (2000). "Particulate matter in the atmosphere: which particle
properties are important for its effects on health?" Sci Total Environ 249(1-3): 85-
101.

 

Herbarth, O.. G. Fritz, et al. (2001). "Effect of sulfur dioxide and particulate pollutants on
bronchitis in children--a risk analysis." Environ Toxicol 16(3): 269-76.

 

Hirano. S., A. Furuyama, et al. (2003). "Oxidative-stress potency of organic extracts of
diesel exhaust and urban ﬁne particles in rat heart microvessel endothelial cells."
Toxicology 187(2-3): 161-70.

Hirsch, T., S. K. Weiland, et al. (1999). "Inner city air pollution and respiratory health
and atopy in children." Eur Respir J 14(3): 669-77.

Hoek, G., D. W. Dockery, et al. (1998). "Association between PMlO and decrements in
peak expiratory ﬂow rates in children: reanalysis of data from ﬁve panel studies."
Eur Respir] 11(6): 1307-11.

Holcroft, C. A., E. A. Eisen, et al. (2003). "Measurement characteristics of peak
expiratory ﬂow." Chest 124(2): 501-10.

Jalaludin, B. B., T. Chey, et al. (2000). "Acute effects of low levels of ambient ozone on
peak expiratory ﬂow rate in a cohort of Australian children." Int J Epidemiol
29(3): 549-57.

Jimenez Del Rio, M. and C. Velez-Pardo (2004). "Transition metal-induced apoptosis in
lymphocytes via hydroxyl radical generation, mitochondria dysfunction, and

caspase-3 activation: an in vitro model for neurodegeneration." Arch Med Res
35(3): 185-93.

Just. J ., C. Segala, et al. (2002). "Short-term health effects of particulate and
photochemical air pollution in asthmatic children." Eur Respir J 20(4): 899-906.

 

48

Keeler, G. J, T. Dvonch, et al. (2002). "Assessment of personal and community-level
exposures to particulate matter among children with asthma in Detroit, Michigan.
as part of Community Action Against Asthma (CAAA)." Environ Health Perspect
110 Suppl 2: 173-81.

Koenig, J. Q., T. V. Larson, et al. (1993). "Pulmonary function changes in children
associated with ﬁne particulate matter." Environ Res 63(1): 26-38.

 

Kuehr, J ., T. F rischer, et al. (1992). "Early childhood risk factors for sensitization at
school age." J Allergy Clin Immunol 90(3 Pt 1): 358-63.

Kuehr, J ., T. Frischer, et al. (1998). "Cotinine excretion as a predictor Of peak ﬂow
variability." Am J Respir Crit Care Med 158(1): 60-4.

Lacasana, M., A. Esplugues. et al. (2005). "Exposure to ambient air pollution and
prenatal and early childhood health effects." Eur J Epidemiol 20(2): 183-99.

Le Souef, P. N. (1997). "Paediatric prediction equations for PEF (growth. ageing. gender.
race and health)" Eur Respir J Suppl 24: 75S-79S.

Lebowitz, M. D., D. L. Sherrill, et al. (1997). "Peak expiratory ﬂow from maximum
expiratory ﬂow volume curves in a community population: cross-sectional and
longitudinal analyses." Eur Respir J Suppl 24: 29S-38S.

Mannino, D. M., D. M. Homa, et al. (1998). "Surveillance for asthma--United States.
1960-1995." MMWR CDC Surveill Summ 47(1): 1-27.

Martins, L. C., R. Latorre Mdo, et al. (2002). "Air pollution and emergency room visits
due to chronic lower respiratory diseases in the elderly: an ecological time-series
study in Sao Paulo, Brazil." J Occup Environ Med 44(7): 622-7.

Mercier, J .. A. Varray. et al. (1991). "Inﬂuence of anthropometric characteristics on
changes in maximal exercise ventilation and breathing pattern during growth in
boys." Eur J 23291 PMSIOI Ochp Physiol 63(3-4): 235-41.

Miles, J. F., W. Tunnicliffe, et al. (1996). "Potential effects of correction of inaccuracies
of the mini-Wright peak expiratory ﬂow meter on the use of an asthma self-
management plan." Thorax 51(4): 403-6.

Miller, M. R., S. A. Dickinson, et al. (1992). "The accuracy of portable peak ﬂow
meters." Thorax 47(11): 904-9. *

 

Mo, F., C. Robinson, et al. (2003). "Analysis of prevalence, triggers. risk factors and the
related socio-economic effects of childhood asthma in the Student Lung Health
Survey (SLHS) database, Canada 1996." Int J Adolesc Med Health 15(4): 349-58.

49

Mortimer, K. M., L. M. Neas, et al. (2002). "The effect of air pollution on inner-city
children with asthma." Eur Respir J 19(4): 699-705.

 

Moseler, M., A. Hendel-Kramer, et al. (1994). "Effect Of moderate N02 air pollution on
the lung function of children with asthmatic symptoms." Environ Res 67(2): 109-
24.

 

Neas, L. M., D. W. Dockery, et al. (1995). "The association Of ambient air pollution with

twice daily peak expiratory ﬂow rate measurements in children." Am J Epidemiol
141(2): Ill-22.

 

Neas, L. M., J. Schwartz, et al. (1999). "A case-crossover analysis of air pollution and
mortality in Philadelphia. " Environ Health Perspect 107(8): 629-31.

Ones. U., A. Somer, et al. (2004). "Peak expiratory ﬂow rates in healthy Turkish children
living in Istanbul, Turkey." Allergy Asthma Proc 25(5): 313-20.

Osomio-Vargas. A. R., J. C. Bonner, et al. (2003). "Proinﬂammatory and cytotoxic
effects of Mexico City air pollution particulate matter in vitro are dependent on
particle size and composition." Environ Health Perspect 111(10): 1289-93.

Ostro, B., M. Lipsett, et al. (2001). "Air pollution and exacerbation of asthma in African-
American children in Los Angeles." Epidemiology 12(2): 200-8.

Paggiaro, P. L., G. Moscato, et al. (1997). "Relationship between peak expiratory ﬂow
(PEF) and FEV1." Eur Respir J Suppl 24: 398-418.

Park, H., B. Lee, et al. (2002). "Association of air pollution with school absenteeism due
to illness." Arch Pediatr Adolesc Med 156(12): 1235-9.

Parker, A. L., M. Abu-Hijleh, et al. (2003). "Ratio between forced expiratory ﬂow
between 25% and 75% of vital capacity and F VC is a determinant of airway
reactivity and sensitivity to methacholine." Chest 124(1): 63-9.

Peacock, J. L., P. Symonds, et al. (2003). "Acute effects of winter air pollution on

respiratory function in schoolchildren in southern England." Occup Environ Med
60(2): 82-9.

 

Peat. J. K., R. H. van den Berg, et al. (1994). "Changing prevalence of asthma in
Australian children." EDI 308(6944): 1591-6.

Peel, J. L., P. E. Tolbert, et a1. (2005). "Ambient air pollution and respiratory emergency
department visits." Epidemiology 16(2): 164-74.

50

Pekkanen, J .. K. L. Timonen, et al. (1997). "Effects of ultraﬁne and ﬁne particles in urban

air on peak expiratory ﬂow among children with asthmatic symptoms." Environ
E 74(1): 24-33.

Peters, J. M., E. Avol, et al. (1999). "A study of twelve Southern California communities
with differing levels and types of air pollution. 11. Effects on pulmonary function."
Am J Respir Crit Care Med 159(3): 768-75.

Piecoro, L. T., M. Potoski, et al. (2001). "Asthma prevalence, cost, and adherence with
expert guidelines on the utilization Of health care services and costs in a state
Medicaid population." Health Serv Res 36(2): 357-71.

 

Pino, P.. T. Walter, et al. (2004). "Fine particulate matter and wheezing illnesses in the
ﬁrst year of life." Epidemiology 15(6): 702-8.

Pope. C. A., 3rd and D. W. Dockery (1992). "Acute health effects of PM I 0 pollution on
symptomatic and asymptomatic children." Am Rev Respir Dis 145(5): 1 123-8.

 

Pope. C. A., 3rd, D. W. Dockery, et al. (1991). "Respiratory health and PM10 pollution.
A daily time series analysis." Am Rev Respir Dis 144(3 Pt 1): 668-74.

Porter, P. S., S. T. Rao. et al. (2001). "Ozone air quality over north america: part II--an

analysis of trend detection and attribution techniques." J Air Waste Mantyg Assoc
51(2): 283-306.

Ranzi, A., M. Gambini, et al. (2004). "Air pollution and respiratory status in asthmatic
children: hints for a locally based preventive strategy. AIRE study." Eur J
Epidemiol 19(6): 567-76.

Roemer, W., J. Clench-Aas, et al. (1999). "Inhomogeneity in response to air pollution in
European children (PEACE project)" 00ch) Environ Med 56(2): 86-92.

 

Roemer, W., G. Hoek, et al. (1993). "Effect Of ambient winter air pollution on respiratory

health of children with chronic respiratory symptoms." Am Rev Respir Dis
147(1): 118-24.

Roemer, W., G. Hoek. et al. (2000). "PM10 elemental composition and acute respiratory
health effects in European children (PEACE project). Pollution Effects on
Asthmatic Children in Europe." Eur RespirJ 15(3): 553-9.

Roemer, W., G. Hoek, et al. (1998). "Daily variations in air pollution and respiratory
health in a multicentre study: the PEACE project. Pollution Effects on Asthmatic
Children in Europe." Eur Respir J 12(6): 1354-61.

 

51

Romieu, 1., F. Meneses, et al. (1996). "Effects of air pollution on the respiratory health of
asthmatic children living in Mexico City." Am J Respir Crit Care Med 154(2 Pt
1): 300-7.

Roth-Kleiner, M. and M. Post (2003). "Genetic control of lung development." B_io_l
Neonate 84(1): 83-8.

Rowland, T. W. and L. N. Cunningham (1997). "Development of ventilatory responses to
exercise in normal white children. A longitudinal study." Chest 111(2): 327-32.

Rusznak. C., J. L. Devalia, et al. (1994). "The impact of pollution on allergic disease."
Allergy 49(18 Suppl): 21-7.

Ryan, G., K. M. Latimer, et al. (1982). "Bronchial responsiveness to histamine:
relationship to diurnal variation of peak ﬂow rate, improvement after
bronchodilator, and airway calibre." Thorax 37(6): 423-9.

Samoli, E, A. Analitis, et al. (2005). "Estimating the exposure-response relationships
between particulate matter and mortality within the APHEA multicity project."
Environ Health Perspect 113(1): 88-95.

Schwartz, J. and L. M. Neas (2000). "Fine particles are more strongly associated than
coarse particles with acute respiratory health effects in schoolchildren."
Epidemiology 11(1): 6-10.

Schwela, D. (2000). "Air pollution and health in urban areas." Rev Environ Health 15(1-
2): 13-42.

Sheppard, L., D. Levy, et al. (1999). "Effects of ambient air pollution on nonelderly
asthma hospital admissions in Seattle, Washington, 1987-1994." EfpidemiologyI
10(1): 23-30.

Siersted, H. C., H. S. Hansen, et al. (1994). "Evaluation of peak expiratory ﬂow
variability in an adolescent population sample. The Odense Schoolchild Study."
Am J Respir Crit Care Med 149(3 Pt 1): 598-603.

Sullivan, S. D. (2003). "Asthma in the United States: recent trends and current status." J
Manag Care Pharm 9(5 Suppl): 3-7.

Tiittanen, P., K. L. Timonen, et a1. (1999). "Fine particulate air pollution, resuspended
road dust and respiratory health among symptomatic children." Eur Respir J
13(2): 266-73.

Timonen, K. L. and J. Pekkanen (1997). "Air pollution and respiratory health among
Children with asthmatic or cough symptoms." Am J Respir Crit Care Med 156(2
Pt 1): 546-52.

52

Utell, M. J. and M. W. Frampton (2000). "Acute health effects of ambient air pollution:
the ultraﬁne particle hypothesis." J Aerosol Med 13(4): 355-59.

van der Zee, S., G. Hoek, et al. (1999). "Acute effects of urban air pollution on
respiratory health of children with and without chronic respiratory symptoms."
Occup Environ Med 56(12): 802-12.

van Strien, R. T., J. F. Gent, et al. (2004). "Exposure to N02 and nitrous acid and
respiratory symptoms in the ﬁrst year of life." Epidemiology 15(4): 471-8.

Venners, S. A., B. Wang. et al. (2003). "Particulate matter, sulfur dioxide, and daily
mortality in Chongqing, China." Environ Health Perspect 111(4): 562-7.

Vi gotti, M. A. (1999). "[Short-term effects of exposure to urban air pollution on human
health in Europe. The APHEA Projects (Air Pollution and Health: a European
Approach]." Epidemiol Prev 23(4): 408-15.

Wang. X.. D. W. Dockery, et al. (1993). "Pulmonary function growth velocity in children
6 to 18 years of age." Am Rev Respir Dis 148(6 Pt 1): 1502-8.

Wichmann, H. E. and J. Heinrich (1995). "Health effects of high level exposure to
traditional pollutants in East Gennany--review and ongoing research." Environ
Health Perspect 103 Suppl 2: 29-35.

Wichmann, H. E., C. Spix, et al. (2000). "Daily mortality and ﬁne and ultraﬁne particles

in erfurt. gerrnany part I: role of particle number and particle mass." Res Rep
Health Eff Inst(98): 5-86; discussion 87-94.

Wolff, G. T., A. M. Dunker, et al. (2001). "Ozone air quality over North America: part I--
a review of reported trends." J Air Waste Manag Assoc 51(2): 273-82.

Yu, 0., L. Sheppard, et al. (2000). "Effects Of ambient air pollution on symptoms of
asthma in Seattle-area children enrolled in the CAMP study." Environ Health
Perspect 108(12): 1209-14.

 

Zanobetti, A., J. Schwartz, et al. (2000). "Are there sensitive subgroups for the effects of
airborne particles?" Environ Health Perspect 108(9): 841-5.

Zmirou, D., A. Deloraine, et al. (1999). "Health effects costs of particulate air pollution."
J Occup Environ Med 41(10): 847-56.

53

   

liiiliiiijliiijjiiiijlljijjil