University of Southern California Dissertations and Theses

The impact of the environment on childhood allergic rhinitis: findings from the Children’s Health Study

(USC Thesis Other)

The impact of the environment on childhood allergic rhinitis: findings from the Children’s Health Study

PDF

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content

The Impact of the Environment on Childhood Allergic
Rhinitis: Findings from the Children’s Health Study

by
Hui Zhou

A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Fulfillment of the
Requirements of the Degree

DOCTOR OF PHILOSOPHY
in
EPIDEMIOLOGY

December 2017

Copyright 2017 Hui Zhou

DEDICATION

This is dedicated to my family, especially Serena and
Alyssa. I would not have accomplished this Ph.D. without
their unconditional love and support.

ii

Acknowledgements
This study would not be done without the knowledge, guidance and support of my
supervisor Dr. Frank D. Gilliand. Thank you for always believing in me and giving me the
positive feedback. You make me better than I thought I can be. I would like to thank all my
committee members, Dr. Kiros Berhane, Dr. Anny H.Xiang, Dr.Carrie Breton, Dr. Heather Volk,
and Dr.Louis Dubeau for willing to take time to read the dissertation and provide your
suggestion. Your research experience will guide my way. I would also like to thank the
professors, Dr. Wendy Mack and Dr. Andrea Kovacs, for leading me to the biostatistical and
epidemiological research and help me grow.
A special thanks to my collaborators, Dr. JeongHee Kim and Dr. HyoBin Kim. Your
clinical experience is an invaluable treasure to my study. I enjoyed working with you both. I
would like to thank the current and previous research staff working in the Children Health Study,
Edward B. Rappaport, Dr.Muhammad T.Salam, Feifei Liu, Robert Urman, Iona Li, and
Dr.Robert Mcconnell. Thank you all for answering all my questions and directing me to the right
documents.
I would like to thank my collaborators in Kaiser Permanente Southern California, especially
Wansu Chen, Jeff M.Slezak, Dr. MaryHelen Black, Dr. Stephen F. Derose, Dr.Annette L.Adams
and Jean Q.Chantra, for supporting me to pursue the study and research in the University of
Southern California. It would be impossible for me to complete the dissertation without your
cooperation.
A huge thanks to my family, who has never hesitate to give me the full support, and my
friends who help me to keep balance between work/ study and life. Finally, I want to present the
dissertation as a gift to my lovely daughters, Serena and Alyssa----if you have a dream, pursue it
no matter how hard it is.

iii

Table of Contents

Abstract ...................................................................................................................................... xi
Chapter 1 Introduction ................................................................................................................ 1
1.1 Allergic Rhinitis ................................................................................................................. 1
1.1.1 Clinical Diagnosis and Current Treatment of Allergic Rhinitis ................................... 1
1.1.2 Prevalence and Burden of Disease ................................................................................ 3
1.1.3 Classification of Allergic Rhinitis ................................................................................ 5
1.1.4 Co-morbidities ............................................................................................................. 6
1.1.5 Pathology of Allergic Rhinitis ...................................................................................... 6
1.2 Risk Factors ......................................................................................................................... 9
1.2.1 Genetic Factors ............................................................................................................. 9
1.2.2 Environmental Factors ................................................................................................ 11
1.2.2.1 Hygiene hypothesis .......................................................................................... 11
1.2.2.3 Traffic-related air pollution ............................................................................... 13
1.2.2.4 Indoor environment ............................................................................................ 15
1.2.3 Other Risk Factors ...................................................................................................... 17
1.3 Genetic and Environmental Interaction............................................................................. 19
1.4 Children Health Study in Southern California .................................................................. 21
1.5 Study Population and Data Collection .............................................................................. 23
Chapter 2. Study on the Synergic Effect of Allergen Sensitization and Traffic-Related Air
Pollution on the Development of Allergic Rhinitis during Childhood ..................................... 24
2.1 Introduction ....................................................................................................................... 24
2.2 Materials and methods ...................................................................................................... 26
2.2.1 Study Subjects ............................................................................................................. 26

iv

2.2.2 New Onset Allergic Rhinitis and Covariates. ............................................................ 27
2.2.3 Allergen Sensitization and Air Pollutant Exposure Assessment ................................ 28
2.3 Result ................................................................................................................................. 30
2.4 Discussion ......................................................................................................................... 39
Chapter 3. Cross-Sectional Study on the Association between Environmental Risk Factors and
Prevalent Allergic Rhinitis among Children ............................................................................. 44
3.1 Introduction ....................................................................................................................... 44
3.2 Method .............................................................................................................................. 47
3.2.1 Study Population ......................................................................................................... 47
3.2.2 Prevalent Allergic Rhinitis and Covariates. ................................................................ 48
3.2.3 Indoor Environmental Factors .................................................................................... 48
3.2.4 Ambient Air Pollutants ............................................................................................... 49
3.2.5 Statistical Analysis ...................................................................................................... 50
3.3 Results ............................................................................................................................... 51
3.4 Discussion ......................................................................................................................... 58
3.5 Conclusion ......................................................................................................................... 63
Chapter 4. Effects of Environmental Factors and Family History of Allergic Diseases on
Development of Incident Childhood Allergic Rhinitis ............................................................. 64
4.1 Introduction ....................................................................................................................... 64
4.2 Methods ............................................................................................................................. 65
4.2.1 Study Population ......................................................................................................... 65
4.2.2 Incident Allergic Rhinitis Identification and demographic information collection .... 66
4.2.3 Indoor Environmental Factors .................................................................................... 67
4.2.4 Ambient Air Pollutants ............................................................................................... 67
4.2.5 Statistical Analysis ...................................................................................................... 68
4.3 Results ............................................................................................................................... 69

v

4.4 Discussion ......................................................................................................................... 75
Chapter 5. Fractional Exhaled Nitric Oxide Predicts Risk of Childhood Allergic Rhinitis ..... 77
5.1 Introduction ....................................................................................................................... 77
5.2 Method .............................................................................................................................. 79
5.2.1 Study Population ......................................................................................................... 79
5.2.2 FeNO Measurement .................................................................................................... 80
5.2.3 Incident Allergic Rhinitis Identification and demographic information collection .... 81
5.2.4 Statistical Analysis ...................................................................................................... 81
5.3 Results ............................................................................................................................... 82
5.4 Discussion ......................................................................................................................... 88
5.5 Conclusion ......................................................................................................................... 90
Chapter 6 Discussion and Conclusion ....................................................................................... 91
Reference ................................................................................................................................... 95

vi

List of Tables
Table 1 Characteristics comparison between CHS participants with and without SPT (N=5,277)*
....................................................................................................................................................... 32
Table 2 Sociodemographic, Environmental Exposure and Clinical Characteristics of 67 Children
who Underwent SPT and Who Were Free of Allergic Rhinitis when SPT was Performed ......... 33
Table 3 Association between Allergen Sensitization and Onset of Allergic Rhinitis among 67
Children who Underwent SPT and were Free of Allergic Rhinitis when SPT was Performed.... 35
Table 4 Association between TRAP and Incident Allergic Rhinitis among Study Population
during up to 8 Years of Follow-Up ............................................................................................... 36
Table 5 Joint Effect of Air Pollution Indicated by Proximity to Freeway and Allergen
Sensitization on Onset of AR among Study Population during up to 8 Years of Follow-up ....... 37
Table 6 Joint Effect of Ambient Air Pollutants including PM10, PM2.5, Ozone, and NO2, with
Allergic Sensitization on Onset of Allergic Rhinitis among 67 Children during up to 8 Years
Follow-Up ..................................................................................................................................... 38
Table 7 Ambient air pollutants comparison between measurements at study entry and averaged
during follow-up ........................................................................................................................... 42
Table 8 Characteristics Comparison of CHS Participants by their Answers to Lifetime
Residential History (N=5,111) ...................................................................................................... 53
Table 9 Demographic Characteristics and Medical History Comparison and Single Factor
Analysis among CHS Participants who have Resided in the Same House from Birth to Study
Entry (N=1,611) ............................................................................................................................ 55
Table 10 History of Exposure to Environmental Factors Comparison and Odds Ratio Analysis
on Childhood Allergic Rhinitis among CHS Participants who have Resided in the Same House
since Birth(N=1,611) .................................................................................................................... 56
Table 11 Multivariate Analysis on Association between Socio-Demographic, Medical and
Family History, and Environmental Risk Factors and Allergic Rhinitis among CHS Participants
who have Resided in the Same House since Birth (N=1,611) ...................................................... 59
Table 12 Characteristics comparison by incident allergic rhinitis status and single-factor analysis
among cohort (N=2,892) ............................................................................................................... 72
Table 13 Single-factor effect of air pollutants measured at baseline on incident allergic
rhinoconjunctivitis ........................................................................................................................ 73

vii

Table 14 Correlation between air pollutants in the longitudinal study (N=2,892) ....................... 73
Table 15 Multivariate Analysis on Risk of Allergic Rhinitis between Socio-Demographic,
Medical and Family History, Indoor and outdoor Environmental Risk Factors (N=2,892) ......... 74
Table 16 Competing risk analysis on incident allergic rhinoconjunctivitis (N=2.892) ................ 75
Table 17 Demographic and clinical characteristics comparison between children who developed
incident allergic rhinitis and didn’t have the symptoms during follow-up (N=621) .................... 84
Table 18 Hazard ratio of incident rhinoconjunctivitis with levels of FeNO measured at baseline
....................................................................................................................................................... 85
Table 19 Hazard ratio of incident rhinoconjunctivitis with increasing baseline FeNO level ....... 85
Table 20 Hazard ratio of incident rhinoconjunctivitis with increasing FeNO using time-varying
measurement ................................................................................................................................. 86
Table 21 HR of incident allergic rhinitis by FeNO level .............................................................. 88

Childhood AR: Finding from CHS Study
viii

List of Figures

Figure 1 Mechanism of Treg in the regulation of immunosystem (Palomares O et al. 2010).......... 9
Figure 2. Map of communities that the Southern California Children’s Health Study was
performed ......................................................................................................................................... 22
Figure 3. Flowchart of study population establishment in SPT cohort study .................................. 31
Figure 4. Establishment of eligible population for the cross-sectional study ................................. 52
Figure 5. Establishment of study population in longitudinal study on incident AR ........................ 70
Figure 6 Establishment of cohort study among children with FeNO measurement ........................ 83
Figure 7 Cut-point plot of FeNO for predicting risk of incident AR ............................................... 87

Childhood AR: Finding from CHS Study
ix

List of Abbreviation

AAAAI American Academy of Allergy, Asthma, and Immunology
AhR Aryl hydrocarbon receptor
AR Allergic Rhinitis
ARB Air Resource Board
ARIA Allergic rhinitis and its impact on asthma
ARNT AhR nuclear translocator
CDC Centers for Disease Control and Prevention
CHS Children’s Health Study in southern California
CI confidence intervals
DC dentritic cells
DEP diesel exhaust particles
DOHaD Developmental Origins of Health and Disease
ELISA enzyme-linked immunosorbent assay
ETS environmental tobacco smoking
GWAS genome-wide association study
HDM house dust mites
HR hazard ratio
HRQL Health-Related Quality of Life
IgE Immunoglobulin E
IL interleukin
ISAAC International Study of Asthma and Allergies in Childhood
MAS Multicenter Allergy Study
MONICA
Multinational Monitoring of Trends and Determinants in
C di l Di
NCDs non-communicable diseases
NHANES National Health and Nutrition Examination Survey
NO2 nitrogen dioxide
NOX oxide of nitrogen
OME otitis media with effusion
OR odds ratio
PedsQL Pediatrics Quality of Life
PM10 particular matter with an aerodynamic diameter less than 2.5µm

Childhood AR: Finding from CHS Study
x

PM2.5 particular matter with an aerodynamic diameter less than 2.5µm
QOL-KCAR Quality of Life in Korean Children with Allergic Rhinitis
SNP single nucleotide polymorphism
SPT skin prick test
TCDD 2,3,7,8-tetrachlordibenzo-p-dioxin
Th1 Type 1 helper
Th2 Type 2 helper
TRAP traffic-related air pollution
Treg regulatory T cells
WHO
World Health Organization

Childhood AR: Finding from CHS Study
xi

Abstract
Background: Allergic rhinitis (AR) is a common respiratory disease, especially among children
in the United States. The prevalence of AR has been rising with the increasing industrialization
and urbanization and the economic impact on society becomes a major concern worldwide.
However, limited studies have been done in a large population to test the impact of environment,
indoor and outdoor, on the development of childhood allergic rhinitis. In addition, there was lack
of thorough studies on whether or how the effects of environmental factors on the development of
childhood AR in different age groups.
Objectives: We investigated the risk from exposure to indoor and outdoor environments and other
biological determinants (sensitization, FeNO) for the development of AR in children. We also tested
if the impacts varied by sex or family history of allergic diseases.
Methods: A). Among participants in the CHS study, 67 children who were AR-free and
underwent skin prick test to common allergens were followed for up to 8 years for incident AR.
The individual and joint effects of allergen sensitization and exposure to traffic-related air
pollution (TRAP) on the development of AR in children were assessed by Cox proportional
hazards model. B). Cross-sectional analyses of risk factors for AR was performed among CHS
participants at the entry. Association between environments, outdoor and indoor, and prevalent AR
was assessed by multinomial regression model. C). A longitudinal study of AR incidence was
conducted among 2,892 AR-free participants followed for up to 10 years. The impact of
indoor/outdoor environment on the risk of developing AR was assessed using survival analysis
after adjustment for demographic, socio-economic factors, and family medical history and D). To
Childhood AR: Finding from CHS Study
xii

assess fractional exhaled nitric oxide (FeNO) in prediction of new onset rhinoconjunctivitis, 621
eligible children who had FeNO measurement and were free of AR were followed for 5 years for
the incident rhinoconjunctivitis. Baseline level of FeNO and time-varying levels of FeNO were
included in the proportional cox models separately after adjustment for covariates.
Results: 1). In the cohort study following children with SPT test, it was found that children with
sensitization to multiple allergens had a 4.7 (95% CI: 2.1-10.6) times increased risk for incident
AR. Children who lived within 500m from a freeway were 2.3 (95% CI: 1.1-4.9) times as likely to
develop AR, compared to those living further than 500m. A strong synergism was suggested
between sensitization and TRAP exposure for the development of AR. Sensitized children who
lived ≤ 500m from a freeway had 8.1-fold (95% CI: 2.8-23.5) increased risk of AR compared to
non-sensitized children who lived >500m from a freeway. 2). From the cross-sectional study
performed among kindergarteners and first-graders, we identified that some indoor environmental
factors and air pollutants were significantly related to prevalent AR. Use of a humidifier or
vaporizer was associated with 1.6 (95% CI: 1.2- 2.3) times higher odds of nasal allergy, and 1.7
times (95% CI: 1.3-2.4) higher prevalence of rhinoconjunctivitis. Household mildew increased the
odds of nasal allergy 1.7-fold (95% CI: 1.2-2.4) and rhinoconjunctivitis 1.4-fold (95% CI: 1.0-1.9).
Prevalence of rhinoconjunctivitis was associated with exposure to nitrogen dioxide (NO2) (OR
=1.5; 95% CI: 1.1-1.9 per 17ppb) and particulate matter with aerodynamic diameter <10
micrometer (PM10) (OR: 1.4; 95% CI: 1.0-1.8 per 25 µg/m
3
). 3). In the longitudinal study followed
AR-free children for ten years, it was shown that exposure to secondhand smoke was significantly
related to the risk of new onset rhinoconjunctivitis. After adjustment for demographic, and socio-
economic factors, the risk ratio of developing childhood AR increased 1.4 times (95% CI: 1.0-1. 8)
Childhood AR: Finding from CHS Study
xiii

with the exposure to secondhand smoke. 4). By following 621 children without AR when their
FeNO was measured, it was found that the risk of developing new onset AR in 6 years increased to
1.2 times (95% CI: 1.1 - 1.3) among children whose measured FeNO were 12 ppb higher. Further
analysis identified that children whose baseline FeNO>=20 ppb were 2.1 times (95% CI: 1.3-3.4)
more likely to have new incident AR in next 6 years, comparing to those with lower FeNO. Similar
results were obtained from the model using updated FeNO levels.
Conclusion: There was significant impact of early childhood environment on the development
of allergic rhinitis among children. Indoor and outdoor environment may work independently, or
together on the induction of AR. Exposure to higher levels of air pollutants increases the risk for
new onset AR especially among children with allergic sensitization. In addition, FeNO may be an
early predictor for the development of new onset AR in children.

Childhood AR: Finding from CHS Study
1

Chapter 1 Introduction

1.1 Allergic Rhinitis
1.1.1 Clinical Diagnosis and Current Treatment of Allergic Rhinitis
Allergic rhinitis (AR) is a common condition involving recurrent nasal mucosal irritation or
inflammation as a response to allergen exposure in sensitized individuals. The typical symptoms
include rhinorrhea, sneezing, itching nose and stuffy nose due to blockage or congestion. These
symptoms are similar to non-allergic rhinitis but have different triggering factors. Non-allergic
rhinitis is induced either by a virus or bacteria, medication, hormones or chemical agents (Fokkens
2002) while AR is caused by exposure to perennial or seasonal allergens existing in our indoor and
outdoor environment.
The accurate diagnosis distinguishing AR from non-AR is important since the effective
treatments for one condition might be less or not effective for the other. In 1998, the first clinical
practice guidelines were created by the American Academy of Allergy, Asthma, and Immunology
(AAAAI). Based on the AAAI guideline, the World Health Organization (WHO) developed an
extensive section on the differential diagnosis and management of AR in 2001 (Bousquet et al.
2001). According to the WHO guideline, medical history including the age of onset, family
history, and therapy history serve as indicators for likelihood of AR. Examination of the nose or
detection of cervical lymphadenopathy can provide additional information to confirm the diagnosis
(Quillen and Feller 2006). Allergy testing such as percutaneous skin test and the allergen-specific
Childhood AR: Finding from CHS Study
2

immunoglobulin E (IgE) antibody test is not required but recently has been more commonly used
to provide objective support for the final diagnosis. Non-AR is diagnosed after eliminating allergic
causes of rhinitis.
In epidemiological studies, using the clinical diagnostic methods to define allergic
rhinitis for each individual is logistically difficult especially when the study is performed in
a relatively large population. However, in order to compare the incidence/prevalence of AR
among different studies, a standardized case definition is required. There are several
standardized questionnaires developed for this purpose (Burney et al. 1994; Charpin et al.
1996). Currently, the most common approach for ascertaining AR in epidemiology is using
the International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire. The
AR case identification was based on the confirmative self-report of ‘ever had nasal
symptoms in the absence of a cold’, accompanied by the ocular symptoms. The
performance of this method has been validated in the other studies on asthma and AR
(Braun-Fahrländer et al. 1997b; de Andrade et al. 2008).
Once patients are diagnosed with AR, effective management of the disease is
needed to preserve a high quality of daily life and to prevent exacerbations. The current
therapies include patient education, allergen exposure avoidance, pharmacotherapy and
immunotherapy. Among these, the educational approach is adapted to the characteristics of
the patients, such as age, gender and racial groups. Although completely avoiding exposure
to all allergens is difficult, starting avoidance of exposure to some major allergens early can
greatly improve the symptoms. For more effective control, the combined therapies are
applied together.
Childhood AR: Finding from CHS Study
3

1.1.2 Prevalence and Burden of Disease
Allergic rhinitis is considered as a modern disease, which was first described in the United
States in 1872 and was not widely recognized until 1900. The prevalence of AR has been rising
with increasing industrialization and urbanization. Conservative estimates for current prevalence
indicate that AR affects between 10% and 30% of the population (Pawandar R et al, the WHO
white book) and the risk is rising worldwide(Asher et al. 2006). In addition, due to the milder
symptoms of allergic rhinitis comparing to asthma or other allergic disease, it tends to be
underestimated by parents and doctors in some area (Kim et al. 2014). Because of this potential for
mild symptoms and under diagnosis, the actual prevalence may be higher than that reported.
The prevalence of AR differs by country, age, gender, race/ethnicity, geographic area, and
social-economics levels. The prevalence of AR is the highest in industrialized countries than in
undeveloped or developing countries. According to the ISAAC Phase III reports, prevalence of AR
ranged from 3.6% in Nigeria while 45.1% in Paraguay (Björkstén et al. 2008). This disease is more
common in children than adults, and more common in Caucasians than African Americans. In
2012, estimated annual prevalence of AR was 9.0% among children in the United States while
7.5% among adults (Adams et al. 2013; Bloom et al. 2013; Schiller et al. 2012). Around 10% of
white but only 7% of black children in the U.S. had AR according to a report in 2010 (Bloom et al.
2011). Additionally, the prevalence of allergic rhinitis in children from birth to 4 years is 4% while
increases to 10.7% by the age of 11 (Blackwell et al. 2003; Wright et al. 1994). The AR prevalence
differs between female and male but these sex differences change markedly with age. Among
children who are 6-7 years old, the prevalence of AR among boys is higher than girls (Sánchez-
Lerma et al. 2009) while after age 15, the prevalence becomes higher among females than among
Childhood AR: Finding from CHS Study
4

males (Osman et al. 2007; Pinart et al. 2017). Even in the same country, the prevalence of
AR is different by geographic areas (Asher et al. 2006). For example, in the southern
region of the United States, such as California and Florida, greater prevalence of AR was
found comparing to the other regions (Bloom et al. 2013). In addition to age, gender, and
geography, socio-economic class was reported to be significantly associated with the
prevalence of AR with higher prevalence among families with higher socioeconomic class,
which is consistent with other allergic disease (Borges et al. 2006; Georgy et al. 2006;
Mercer et al. 2004).
During the past decades, the prevalence of AR has increased and is now one of the
most common diseases among children, and it became a larger socio-economic burden
worldwide. Although allergic rhinitis is not life threatening, it is often associated with other
allergic disease such as asthma, eczema and has a considerable effect on the quality of life.
Especially among children, AR interferes with sleep, play and school attendance (Baiardini
et al. 2006). There is evidence showing that allergic rhinitis may impair cognitive
functions in childhood and is related to asthma which can impair social life (Leynaert et al.
2000a). It was emphasized in the ARIA recommendations that the management of upper
and lower airway disorders should consider ‘one airway, one disease’ which involve the
co-morbidities of asthma, rhinitis, otitis media and conjunctivitis(Bachert et al. 2004). The
economic impact on society is also a major concern(Hardjojo et al. 2011). According to the
Centers for Disease Control and Prevention (CDC) report, approximately 11.1 million
ambulatory visits in 2013 were due to AR. The estimated direct costs for AR in the U.S. in
2005 was US $11.2 billion due to expenditure on medications and health care provision,
Childhood AR: Finding from CHS Study
5

with indirect cost up to US $9.7 billion due to the loss of work, social support etc (WAO White
Book on Allergy (World Allergy Organization, 2008).
Comprehensive studies on the risk factors of allergic rhinitis, especially childhood AR, are
in great need to improve the management of this disease and prevention of the development of
asthma in rhinitis patient.
1.1.3 Classification of Allergic Rhinitis
Traditionally, allergic rhinitis was categorized as seasonal or perennial based on the time of
symptoms. If the symptoms only exist in spring, summer, and/or fall, it was classified as
“seasonal”. If the symptoms last year-round, it was considered as “perennial”, which was also
known as hay fever. Pollens from trees, grasses or weeds, or airborne mold spores are the
predominant triggers of the seasonal AR. Perennial AR was generally caused by sensitivity to
house dust mites (HDM), animal dander, pets or/and mold spores. However, this classification is
confusing as: 1). in areas with warm climates such as California and Florida, AR induced by
pollens may become perennial since these allergens are present year-round; 2). many patients may
be sensitized to multiple allergens including pollens and HDM; 3) patients are exposed in different
environments when traveling etc. To avoid the confusion, the report Allergic rhinitis and its impact
on asthma (ARIA) in 2001, coordinated by the WHO, suggested a new classification system to
replace the old terms “seasonal” and “perennial” rhinitis by “intermittent” and “persistent” based
on the duration of symptoms, or “mild” and “moderate-severe” based on the severity of symptoms
and the impact on the social life, school and work

(Bousquet et al. 2001). The new classification
system has been largely adopted for research and clinical practice.
Childhood AR: Finding from CHS Study
6

1.1.4 Co-morbidities
Allergic rhinitis is closely associated with other respiratory diseases. Asthma is the
most common and significant co-existing disease with allergic rhinitis. The prevalence of
asthma in patients with rhinitis is up to 40% while less than 2% among subjects without
rhinitis (Bachert et al. 2004; Linneberg et al. 2002). With the increased severity level of
AR, the risk of suffering from asthma increased as well (Bousquet et al. 2005a). At the
same time, the concomitant allergic rhinitis increases intensity of treatment needed for the
management of asthma. It has been reported that the adults and children with these two
diseases experienced more asthma-related hospitalization visits and more frequent work or
school absences (Bousquet et al. 2005b; Gaugris et al. 2006; Sazonov Kocevar et al. 2005;
Thomas et al. 2005).
In addition to asthma, ocular symptoms, characterized by itching and burning of the
eyes, is considered as “conjunctivitis” of allergic rhinitis. Among patients who suffered
from pollen-triggering allergic rhinitis, 75% also experience ocular symptoms. Some
studies also suggested the correlation between allergic rhinitis and adenoid hypertrophy
(Nguyen et al. 2004), otitis media with effusion (OME) (Caffarelli et al. 1998), Eustachian
tube dysfunction during childhood (Lazo-Sáenz et al. 2005), and chronic cough (Guerra et
al. 2005; Lack 2001; Sherrill et al. 2005).
1.1.5 Pathology of Allergic Rhinitis
With the development of knowledge on the immunologic mechanism of allergic
disease, it was suggested that an imbalance between Type 1 helper (Th1) and Type 2 helper
Childhood AR: Finding from CHS Study
7

(Th2) pathway might be the underlying mechanism of the atopic disease. IgE was identified to
play a central role of triggering the release of mediators which are responsible for allergic
symptoms once an individual becomes sensitized.
The development of allergic symptoms can be divided into two main stages: sensitization
(memory), and effect stage which was further divided into early and late phase responses.
Sensitization may occur in early life after exposure to allergen for a certain time or to the threshold
level. The allergens can be deposited in the mucus layer for a long time (Strachan 1994). In
sensitized individuals, CD4
+
T lymphocytes are activated and result in the release Type 2 helper
(Th2) pro-inflammatory cytokines, such as interleukin (IL)-3, IL-4, IL-5, and IL-13. Activated T
lymphocytes can also interact with B lymphocytes to induce the synthesis of allergen specific IgE
which binds to the IgE receptor on the surface of mast cells. However, in non-sensible individuals,
only Th1 not Th2 immunologic response is activated. Once sensitized, the early response occurs
within minutes when the individuals are re-exposed to the same allergens. By binding to the
allergen specific IgE-binding mast cells, the allergen induces the degranulation of the mast cells
and results in the release of preformed and de novo mediators such as histamine. These mediators
stimulate the mucous glands, and the sensory nerve endings of trigeminal causing sneezing,
rhinorrhea, and congestion (Naclerio 1991) during this early phase. In the late phase, usually 4-6
hours after allergen stimulation, other inflammatory cells such as basophils, eosinophils,
neutrophils and T lymphocytes are recruited to compose a inflammatory cellular influx inducing
additional mediators release (Naclerio 1991). Symptoms in late phase are similar as early phase
with possible increased nasal congestion.
Childhood AR: Finding from CHS Study
8

Recently, more cytokines such as IL-25, IL-31, and IL-33 have been identified to
participate in the Th2 response (Kakkar and Lee 2008); (Wang et al. 2007). Besides
cells, increasing evidence suggested that other T cell subsets, especially Th17 and
cells (Treg), play central roles in controlling and modifying the development of AR
(Albano et al. 2013). By comparing the peripheral blood sample from patients with AR and
healthy individuals using flow cytometry and enzyme-linked immunosorbent assay
(ELISA), it was found that there was significantly higher concentration of Th17 cells while
much lower proportion of Treg cells among AR patients (Huang et al. 2014). These
findings were supported by the experimental study performed in a murine model that
greater level of Th2, Th17 cells were found in allergic rhinitis mice and the Th17 in the
spleen of AR mice were significantly reduced by allergen dosing treatment (Qu et al. 2011;
Shi et al. 2011). In vivo study also suggested that therapy targeting Th17 cells is a potential
pharmacological approach for treating children with allergic rhinitis and asthma (Albano et
al. 2013). With more studies performed in the immunology area, it was suggested that
Treg regulates the immune system through several major pathways: a). Treg minimizes the
production of cytokines including IL-4, IL-5, IL-13 by directly inhibiting the activation of
Th2 cells; b). Treg decreases the inflammatory abilities of dentritic cells (DC) to prime
effector Th1, Th2 and Th17 cells and increase the tolerogenic DC phenotypes (Wing et al.
2008); c). Treg blocks the effector T cells to bind with inflamed tissues (Ring et al. 2006) ;
d). Treg can also have the direct effect on B cells so the production of allergen-specific IgE
was suppressed (Meiler et al. 2008). Due to the importance of Treg, it was considered that
the imbalance of Th17/Treg cells is the trigger in the development and progression of
allergic diseases (Figure 1).
Childhood AR: Finding from CHS Study
9

Figure 1 Mechanism of Treg in the regulation of immunosystem (Palomares O et al. 2010)

1.2 Risk Factors
1.2.1 Genetic Factors
Earlier studies suggested that the genetic background especially the family history of atopic
disease is one of the strongest risk factors for AR. From the twin study in 1971, Edfors-Lubs found
out the potential hereditary character of allergic disease (Edfors-Lubs 1971). More evidence from
the comparison between monozygotic and dizygotic twins was derived to support the genetic effect
in the development of atopy (Hopp et al. 1984). It is commonly found that AR often affects
multiple members in the same family. The persons with strong family history of allergy were more
likely to have allergic disease during childhood or adolescence (Johansson et al. 2004). In addition,
Childhood AR: Finding from CHS Study
10

the findings that the risk of AR varied by gender as well as ethnic background suggested
that the susceptibility of host (sex, age, race /ethnicity) is an important risk factor of AR.
With the development of genetic techniques, such as positional cloning, linkage
analysis, and genome-wide association studies (GWAS), many candidate genes have been
found to be strongly associated with certain phenotypes of allergic disease such as asthma
and/or AR (Moffatt and Cookson 1999; Peden 2002; Toda and Ono 2002). The first
GWAS on allergic rhinitis was performed among a Singapore Chinese population in 2011,
suggesting two new genes, MRPL4 and BCAP, to be related to allergic rhinitis (Andiappan
et al. 2011). From the later GWAS meta-analysis performed in four European adult
cohorts, a single nucleotide polymorphism (SNP) rs2155219 near the region C11orf30 and
LRRC32 which was previously identified to be associated with allergic disorders of skin
was found to be significantly related to AR (Ramasamy et al. 2011). Some of the genes
involved in the immune response such as HlA-D, Toll-like receptor(TLR1, TLR6 and
TLR10), STAT6, and TSLA; genes coding cytokine (ie, IL-4, IL-33) or the total IgE
receptors, IL-4R) and genes in the inflammatory process (ie, TNF-ɤ, IL-3) were reported to
be associated with the phenotypes of AR and asthma (Hinds et al. 2013). In the most
recent published GWAS report, 11 genetic variants were identified to be significantly
related to the combined phenotype of asthma and allergic rhinitis (Ferreira et al. 2014) .
In the candidate gene studies, more than 100 SNPs have been identified to be
associated to AR. Nilsson and his collaborates performed the systematic study for AR in
2013 and identified IL13 as the best candidate for future research and IL33 to be consistent
with the other GWASs results (Ferreira et al. 2014; Hinds et al. 2013; Nilsson et al. 2013).
Childhood AR: Finding from CHS Study
11

However, not all the gene studies showed consistent results. Large sample size with
sufficient statistical power is a common challenge in these studies. Variation of ethnic background
is also responsible for the conflicting results due to the difference in distribution of several allergy-
related alleles. For example, the IL2-330G allele associated with increased IL-2 production is
around 5% among Black, 27% among White, and 34 % in Asian (Hoffmann et al, 2002). In
addition, the different life style, gene-environmental interaction can be the other critical reasons for
the discrepancy.
1.2.2 Environmental Factors
Although family history plays an important role in AR, it cannot account for the increasing
prevalence of the disease in the recent decades. Some of the environmental factors such as life
style change, decrease in viral/bacterial infection, increased air pollution are commonly considered
as the triggering factors for AR (Wang 2005).
1.2.2.1 Hygiene hypothesis
A hypothesis, called hygiene hypothesis of allergy, suggests that exposure to the
environmental factors plays an important role in the development of allergic disease. This
hypothesis considered that the decreasing incidence of infections is responsible for the increased
prevalence of allergic diseases. It was first raised by Strachan who found out that the risk of
developing hay fever was negatively related to the family size, especially the number of children
living in the same house (Strachan 1989). It was supported by the following studies, such as the
prevalence of atopic disease is much higher in developed country than in developing country while
the prevalence of community disease had inverse trend. It was also confirmed by other findings
Childhood AR: Finding from CHS Study
12

that decreased risk of atopic disease was related to increased contact with farm animals or
pets in the early childhood (Radon et al. 2004; von Mutius et al. 1994a).
Pathologically, hygiene hypothesis is supported by the theory that imbalance of
Th1/Th2 pathway is responsible for the development of allergic disease. The exposure to
virus or bacterial, especially during the early childhood, results in constant activation of
Th1 pathway to help the immune system develop and reduce the risk of atopic disease.
However, living in a ‘sterile’ environment leads the balance to Th2 so the risk of allergy
increases (Bousquet et al. 2008).
1.2.2.2 Pollen
Pollen is the primary risk factor of AR. Due to the varied sensitization to pollens from
different sources, symptoms of allergic rhinitis vary in different seasons. Patients who are allergic
to tree pollen may experience that attack of allergic rhinitis in the spring while the persons who are
allergic to grass and weed pollen find their symptoms become worse during the summer time. On
hot, dry and windy days, more susceptible persons were affected by the increased concentration of
pollens in the air. The National Health Interview Survey showed that the prevalence of AR among
children living in southern region of the United States is greater than those living in other regions
(Bloom et al. 2013). One of the putative explanations for this differences may be the existence of
larger amounts of aero-allergens throughout the year including grasses (e.g., bermuda, orchard),
and trees (e.g., oak, olive, elm) in this region (Taborda-Barata and Potter 2012).
In addition to function as the allergen, pollen grain can activate or enhance symptoms of
AR through two other mechanisms: release bioactive lipid mediators to activate AR cascade by
Childhood AR: Finding from CHS Study
13

activating human neutrophils and eosinophils in vitro (Traidl-Hoffman et al. 2003); function as an
adjuvant to enhance nasal responsiveness to other allergens (Takai and Ikeda 2011).
1.2.2.3 Traffic-related air pollution
Pollen cannot explain the higher prevalence of allergic rhinitis nor the higher percentage of
positive skin prick test in urban than rural area of the same geographic region (Cingi et al. 2005).
A cross-sectional study called Multinational Monitoring of Trends and Determinants in
Cardiovascular Disease (MONICA) performed in Germany showed that the significant difference
in risk of AR (OR, 1.5; 95%CI: 1.2-1.9) in urban vs. Rural areas (Filipiak et al. 2001). By
comparing to the different distribution of the potential factors involved in human exposure
pathway of asthma between urban and rural areas, it was suggested that exposures to ambient air
pollutants may also play important roles in the development of allergic airway diseases (Jie et al.
2013; Mugusi et al. 2004).
Air pollutant is a mixture of gaseous compounds and particle matters from various
sources. The strict definition of traffic-related air pollution (TRAP) refers to the primary
emissions from motor vehicles, such as elemental carbon (EC), Nitrogen oxides (NO), and
ultrafine particles (UFP). Ambient air pollutants include more broadly dispersed secondary
pollutants such as ozone (O3), PM with aerodynamic diameters less than 2.5µm (PM2.5) and less
than 10 µm (PM10), and Nitrogen dioxides (NO2) that are derived from the primary emissions.
Traffic-related emissions are the major sources of primary and secondary pollutants and accounts
for the difference of the concentration of air pollutants within and between cities. The direct
measures of traffic itself (such as proximity, or distance, of the residence to the nearest road and
traffic volume within buffers Traffic emissions are the principal source of intra-urban variation
Childhood AR: Finding from CHS Study
14

in the concentrations of air pollutants in many cities; thus, population-oriented central monitors
cannot by themselves capture this spatial variability. Studies that have examined gradients in
pollutants as a function of distance from busy roadways have indicated exposure zones for
traffic-related air pollution (TRAP) in the range of 50 to 1500 m from highways and major roads,
depending on the pollutant and the meteorologic conditions. Because it is not practical or feasible
to measure all the components of the traffic-pollutant mix, surrogates of traffic related pollution
have been used as a reasonable compromise for assessing the contribution of traffic emissions to
ambient air pollution and for estimating traffic exposure. Surrogates can also help in the
assessment of spatial and temporal distributions of ambient pollution related to. Two broad
categories of surrogates have been used in epidemiology studies to estimate traffic exposure: (1)
measured or modeled concentrations of pollutant surrogates and (2) direct measures of traffic
itself (such as proximity, or distance, of the residence to the nearest road and traffic volume
within buffers). The most commonly used traffic pollutant surrogates include CO, elemental
carbon (EC; or black carbon [BC] or black smoke [BS]), PM, benzene, and ultrafine particles
(UFP). Nitrogen oxides, carbon dioxide, carbon monoxide, particulate matter such as PM10 and
PM2.5 were the primary components of traffic-related air pollution. Both epidemiologic and
experimental studies have documented that exposure to TRAP increases the risk of allergen
sensitization and allergic diseases (Annesi-Maesano et al. 2007; Krämer et al. 2000; Nel et al.
1998; Pénard-Morand et al. 2005). Animals and in vitro studies suggest that diesel exhaust
particles (DEP) has the potential to act as adjuvants in de novo IgE responses, induce elevated
IgE production, and result in enhanced immunological response to allergens (Diaz-Sanchez et al.
1999; Gilliland et al. 2004; Liu et al. 2008; Takafuji et al. 1989) . These studies support the
hypothesis that allergens and ambient air pollution have synergistic effects on the development
Childhood AR: Finding from CHS Study
15

of rhinitis (Harley et al. 2009; Kihlström et al. 2002). The proposed underlying mechanism for
the synergic effect of TRAP and aero-allergens is unknown but may involve TRAP pollutants
binding to the surface and change the morphology of aeroallergen such as pollen or fungi to
induce airway inflammation, and potential direct effects on tolerance mediated by Tregs
(D'Amato 2002; Nadeau et al. 2010; Rutherford et al. 2000). However, other studies have shown
conflicting findings. A pooled analysis from 6 birth cohorts consisted from 2 Canadian cohorts,
2 German cohort, 1 Sweden cohort, and 1 Netherland cohort found out that only PM2.5 but no
other TRAPs (NO2 and Ozone) was associated with incident rhinitis (Fuertes et al. 2013a).
Similar result was also reported from another birth cohort by the same group (Fuertes et al.
2013b). The conflicting results suggest the need for additional research on the effects of air
pollution as well as its joint effect with allergens on the development of AR, especially during
childhood.
1.2.2.4 Indoor environment
In addition to the TRAP, indoor allergens also play critical roles in triggering allergic
respiratory disease including asthma and allergic rhinitis. Depending on the life/work style, the
effect of indoor vs. outdoor environmental factors may weight differently on triggering allergic
rhinitis. For example, indoor allergens may play larger roles in the early childhood while TRAP
becomes the predominant risk factor among adults who spend most of time outside. The study on
the newborns identified that the prenatal exposure to dust mite were significantly associated to the
total serum IgE at birth (Schönberger et al. 2005).
Similar to TRAP, house dust is also a heterogeneous mixture which contains allergens from
pets, insects, human skin scales, fungal sports, and so on. House dust mites (HDM) are the
Childhood AR: Finding from CHS Study
16

predominant part among all these indoor allergens, especially in tropical and subtropical
region, or during humid periods (Colloff 1991; Walshaw and Evans 1987). It is the most
important risk factor of allergic disease in Korea where the ‘Ondol’ under-floor heating
systems are used and mites were found in 90% of houses. Around 40% - 60% of patients
with atopic disease in Korean are sensitized to HDM (Jeong et al. 2012). Similar to pollen,
HDM can directly function as an auto-adjuvant by itself, but also binds to other adjuvant-
like substances to activate the Th2 cell response. However, in dry areas such as California,
HDM is not the main risk factor of AR.
Endotoxin of gram-negative bacteria is another component in house dust. It can
induce neutrophil invasion, irritation on the mucus membranes and result in inflammation
of the airways. However, there is debate on the effect of exposure to endotoxin. As a
conflicting result, a dose-dependent relationship between the exposure to endotoxin and
immune disease was found in some studies. According to the hygiene hypothesis, the
endotoxin can play as a switch that affects the balance between the Th1/Th2 cytokine
levels. However, the mechanism of the effect of endotoxin on the risk of atopic disease is
unknown.
Pets at home also show conflicting relationship with AR. It was reported that early
cat exposure can increase the sensitization in the childhood by the German Multi-Center
Allergy Study (MAS) and the Dutch PIAMA study (Lau et al. 2000; Svanes et al. 2003).
However, some other studies on atopic disease supported the protective effect of cats or
dogs exposure in the early childhood (Svanes et al. 2003).
Childhood AR: Finding from CHS Study
17

Other domestic factors such as molds, yeast, insects such as cockroach were also related to
the respiratory allergies by inducing an IgE immune response (Atkinson et al. 2006; Baldo and
Baker 1988; Bush et al. 2006; Lewis et al. 2002). Further discussion is presented in chapter 3.
1.2.3 Other Risk Factors
There are some other factors which can directly or indirectly affect the risk of allergic
rhinitis, such as climates, exposure to secondhand environmental tobacco smoke (ETS). Among
these factors, exposure to tobacco smoking is a potential important risk factor. Although lack of
longitudinal study, the positive relationship between asthma/allergic rhinitis and exposure to
tobacco smoke especially during pre-natal and early post-natal was supported by a few studies
(Butland et al. 1997; Wang et al. 2008). It was found that in utero exposure to mutual tobacco
smoke resulted in epigenetic changes by increasing of DNA methylation(Breton et al. 2014).
Climate is believed to be one of the factors which are indirectly related to the AR through
pollen, air pollutants (Molfino et al. 1992; Williams 2005). With the recent global climate change,
especially the increased average temperature called “greenhouse effect”, the prevalence of atopic
disease is going up and the symptoms are more severe due to the possible reasons as below: the
increased pollen levels, the extended duration of the pollen season, the appearance of some pollen
types in some area which did not exist due to cooler climate (Beggs and Bambrick 2005).
The urbanized “western” life style is also considered to be one of the risk factors of atopic
diseases such as allergic rhinitis, which is also used as support for the hygiene hypothesis. The
relatively higher prevalence of allergic rhinitis in urban than in rural areas were reported in North
America (Gergen and Turkeltaub 1992; von Mutius et al. 1994b), Europe (von Mutius et al.
Childhood AR: Finding from CHS Study
18

1994b), Central America (Soto-Quiros et al. 2002) and South Africa(Crockett et al. 1995).
Before reunification, the prevalence of seasonal allergic rhinitis is lower among East
German children comparing to West German children(von Mutius et al. 1994b). However,
its prevalence became similar in all parts of Germany(von Mutius et al. 1998). Although
the prevalence rate is higher in some industrialized countries, recent ISAAC III reports
showed that there is trend of increase in countries where prevalence of AR was low or
medium during ISAAC phase I while the rates are plateauing or decreasing in the high-
prevalence countries (Asher et al. 2006).
Additionally, obesity was shown to be positively related to the prevalence of
severity of allergic rhinitis (Kellberger et al. 2012). There was a recent study in China
showing that obesity is related to increased prevalent childhood allergic rhinitis, especially
among girls(Lei et al. 2016). Similar results were reported in West Sweden Asthma Study
performed through a questionnaire survey which supported that obesity was a risk factor
for prevalent AR (Rönmark et al. 2016). There were some studies arguing that physical
activity and changes in life style are also related to the increased prevalence of allergic
rhinitis (Kilpeläinen et al. 2006). But more data are needed in this area.

Childhood AR: Finding from CHS Study
19

1.3 Genetic and Environmental Interaction
Although genetic can determine the susceptibility of each individual to certain disease, it
cannot explain the dramatic increase of the prevalence in the recent 100 years. The environmental
exposure on the critical timing is equally, or more influential on promoting a phenotype. However,
it also cannot explain why the great variation of response among people living in the same
environment. Dr Judith Stern from University of California, at Davis claimed that “Genetics loads
the gun, but the environment pulls the trigger”, which is one of the best description of the relationship
among disease, genetic, and environmental.
As a relatively new hypothesis first raised by David Barker in 1986, the Developmental
Origins of Health and Disease (DOHaD) hypothesis has obtained increasing interests when
exploring the potential risk factors of non-communicable diseases (NCDs) including allergy,
asthma, and cancer (Barker and Osmond 1986; Barker 1998; Gluckman et al. 2007). DOHaD
suggested that the exposure during the early life (maternal, perinatal, infancy, and early childhood)
has a long term effects on the future health risk(Barker and Osmond 1986). The hypothesis was
supported by many reports showing that prenatal exposure plays an important role in the risk of
allergic rhinitis. It was found that the prenatal exposure to house dust mite or pet allergens is
related to higher total serum IgE (Schönberger et al. 2005). Data from an established birth cohort
which involved 24,690 children in United Kingdom showed exposure to antibiotics in utero is
associated with an increased risk of allergic rhinitis (McKeever et al. 2002). Research performed in
a subset of Asthma Coalition on Community, Environment, and Social Stress (ACCESS) project
demonstrated the elevated prenatal dust mite levels increased cord blood IgE concentration (Peters
et al. 2009). This hypothesis was also supported by various animal studies showing that DNA
Childhood AR: Finding from CHS Study
20

methylation is directly related to early life exposure including diet, maternal behavior and then
change the risk of disease later (Wadhwa et al. 2009; Weaver et al. 2005). It was also supported by
the biologist who believed that the development and differentiation of stem cells is greatly affected
by its surrounding environment which alters or adjusts the gene expression or functions to promote
disease, especially during the fatal growth.
Specifically, the researchers in the allergy and asthma study area found out the immune
system is highly vulnerable to early environmental changes (dietary, bacterial, pollutants etc),
which is responsible for all the immune disease including allergy and autoimmunity. The studies in
mice identified the significant association between early exposure to environmental factors and
Aryl hydrocarbon receptor (AhR) in the development of allergic diseases (Konkel 2014). AhR is a
ligand-dependent transcription factor present in numerous tissues and cell subsets, involving in
normal cell development and immune regulation. In response to environmental stimuli, such as
dioxins and dioxin-like compounds (Veldhoen et al. 2008), 2,3,7,8-tetrachlordibenzo-p-dioxin
(TCDD) (Fernandez-Salguero et al. 1996), and PM, AhR is activated and translocates to the
nucleus to form heterodimer with AhR nuclear translocator (ARNT) (Beischlag et al. 2008). The
heterodimer results in the changes of gene transcription, ROS generation, cell differentiation, and
inflammatory cytokine production (Stockinger et al. 2014). However, the reports on the role of
AhR in allergic disease are controversial. It was shown that activated AhR suppresses food allergy
to peanut by increasing the percent of Treg (Schulz et al. 2013) while another in vitro study
showed the expression of AhR was elevated in cockroach allergen-induced immune responses
through controlling the active TGFβ1 release (Zhou, 2014). The similar result was found that
increased expression of AhR in patients with allergic rhinitis (Manners et al. 2014; Wei et al.
Childhood AR: Finding from CHS Study
21

2014). More studies are need for the further understanding of underlying interaction between
environment and genetics.

1.4 Children Health Study in Southern California
The Southern California Children’s Health Study (CHS) led by the investigators in the
University of Southern California is one of the largest long-term studies to determine the effects of
air pollutants exposures on the health of children (Künzli et al. 2003). The studies were composed
of more than 11,000 schoolchildren living in up to 16 communities within the Southern California
recruited in five cohorts. The longest follow-up was up to 10 years. The first study initiated in
1992 focused on the children from 4
th
, 7
th
, and 10
th
grade in 12 communities. The most recent one
recruited 5,341 kindergarten and 1
st
grade children from schools in 13 southern California
communities in 2002 and stopped in Dec, 2011. Questionnaire asking about the children’s
respiratory symptoms and disease, physical activity, parental smoking, and many other factors
were collected at baseline and updated annually. Health measurement such as the lung function
was tested every year. The level of air pollutants including Ozone, Nitrogen Dioxide (NO2), Acid
Vapor, and Particulate Matter (PM10, PM2.5) had been continuous measured in each community
throughout the study.
The key findings resulted from this study can be summarized as: Exposure to air pollutants
interferes with lung function development in children and these changes are unlikely to be
reversible (Gauderman et al. 2002; Gauderman et al. 2004); School absences from respiratory
problems increases in the area with high Ozone level (Gilliland et al. 2001); Exposure to traffic-
Childhood AR: Finding from CHS Study
22

related air pollution reduces lung function at age 18 years among children who live within 500m
from a freeway but not the ones living farther away (Gauderman et al. 2007); Children exposed to
higher levels of TRAP have higher risk of new-onset asthma (McConnell et al. 2010); Children
exposed to higher levels of PM have increased active asthma/bronchitis occurrence (McConnell et
al. 1999; McConnell et al. 2006b); Exposure to in utero or environmental secondhand tobacco
smoke or near-roadway air pollution increased the possibility of childhood obesity (McConnell et
al. 2014). These findings provided scientific support to help the Air Resource Board (ARB) and
the US EPA to adjust the California’s ambient air quality standards to protect public health. As one
of the responses, California law prohibits the approval of constructing a new school within 500
feet of a freeway.

Figure 2. Map of communities that the Southern California Children’s Health Study was
performed

Childhood AR: Finding from CHS Study
23

1.5 Study Population and Data Collection
In this dissertation, participants in the CHS were selected to assess the potential risk
factors of prevalent or incident childhood allergic rhinitis. Briefly, 5,341 kindergarteners and 1
st

graders were recruited from schools in 13 southern California communities in 2002 (Fig.2).
Baseline questionnaire such as family history, residential history, respiratory disease history, and
medication use were answered by the parents or guardians. During the10 years follow-up period,
the questionnaire was annually updated in terms of the respiratory disease development. Buccal
cells were collected for DNA samples in the baseline. Pulmonary function test and exhaled NO
measurement (FeNO) had been performed every spring. Data was collected by field teams
consisting of two to six trained members. Similarly to previous cohorts of CHS, ambient air
pollution had been measured during the study period. According to our specific research interests
and data availabilities, different numbers of participants were selected in each of following
chapters. Detailed information will be provided in following chapters.
Childhood AR: Finding from CHS Study
24

Chapter 2. Study on the Synergic Effect of
Allergen Sensitization and Traffic-Related
Air Pollution on the Development of
Allergic Rhinitis during Childhood

2.1 Introduction
Allergic rhinitis is a common chronic upper airway disease, especially among children
residing in urban or industrialized areas. Estimated annual prevalence of AR among children in the
United States ranges from 10-40% (Berger 2004; Meltzer et al. 2009; Wright et al. 1994).
According to the International Study of Asthma and Allergies in Childhood (ISAAC) Phase III
studies, prevalence of AR varies from 3.6% in Nigeria to 45.1% in Paraguay (Björkstén et al.
2008) and is rising worldwide (Asher et al. 2006). The National Health Interview Survey showed
that the prevalence of AR among children living in southern region of the United States is greater
than those living in other regions (Bloom et al. 2013). One of the putative explanations for these
regional differences in the United States and worldwide may be due to the existence of larger
amounts and different types of outdoor allergens throughout the year including pollens from
grasses (e.g., bermuda, orchard), and trees (e.g., oak, olive, elm) in this region leading to a higher
prevalence of sensitization and AR prevalence (Taborda-Barata and Potter 2012). A better
understanding of the role of both outdoor and indoor allergens in the development of AR is needed
to develop effective primary prevention interventions. The need to better define the role of inhaled
Childhood AR: Finding from CHS Study
25

allergens in children’s health is becoming more urgent because the types and levels of pollen are
predicted to increase with climate change in many regions (Lee et al. 2003).
Exposures to air pollutants may also play an important role in the development of allergic
airway diseases. Both epidemiologic and experimental studies have documented that exposure to
TRAP increases the risk of allergen sensitization and allergic diseases (Annesi-Maesano et al.
2007; Krämer et al. 2000; Nel et al. 1998; Pénard-Morand et al. 2005). Animals and in vitro
studies suggest that diesel exhaust particles (DEP) have the potential to act as adjuvants in de novo
IgE responses, induce elevated IgE production, and result in enhanced immunological response to
allergens (Diaz-Sanchez et al. 1999; Gilliland et al. 2004; Liu et al. 2008; Takafuji et al. 1989) .
These studies support the hypothesis that allergens and TRAP have synergistic effects on the
development of rhinitis (Harley et al. 2009; Kihlström et al. 2002). The proposed underlying
mechanism for this synergic effect is unknown but may involve TRAP pollutants binding to the
surface and changing the morphology of aeroallergens such as pollen or fungi to induce airway
inflammation and direct effects on tolerance mediated by regulatory T cells (Tregs) (D'Amato
2002; Nadeau et al. 2010; Rutherford et al. 2000). However, other studies have shown conflicting
findings. A pooled analysis from 6 birth cohorts consisted from 2 Canadian, 2 German, 1 Swedish,
and 1 Dutch cohort found out that only PM2.5 but no other TRAPs such as NO2 was associated
with incident rhinitis (Fuertes et al. 2013a). Similar results were also reported from another birth
cohort by the same group in Germany (Fuertes et al. 2013b). The conflicting results suggest the
need for additional research, particularly in different climatic regions, on the effects of both air
pollutants and allergens on the development of AR, especially during childhood.
Childhood AR: Finding from CHS Study
26

The Southern California Children’s Health Study (CHS) provides a unique opportunity to
investigate both independent and joint effects of allergens and air pollutants in AR development
(McConnell et al. 2006b). The CHS was designed to study the chronic effects of air pollution on
children's respiratory health and has previously found associations between closer residential
proximity to TRAP and increased risk of asthma or wheeze (Gauderman et al. 2005; McConnell et
al. 2010). The aim of this study was to assess the individual and joint effects of ambient air
pollutants (PM2.5, NO2, O3) and TRAP with allergen sensitization on development of AR in
children.

2.2 Materials and methods
2.2.1 Study Subjects
Subjects were participants in the Southern California Children’s Health Study who were
enrolled during 2002-2003. Details about the study design have been described previously (23).
Briefly, 695 children with and without asthma were selected from 5,277 children who were
recruited from 13 Southern California communities when they were in kindergarten or first grade
(5–7 years old) for a sub-study that included allergen sensitization status assessment using skin
prick test (SPT). With parents’ consent, 232 of them received SPT. Parents provided informed
consent and completed a baseline and yearly questionnaire with information about demographic
characteristics, personal and family history of asthma and other respiratory conditions and
symptoms at study entry. To ensure the study cohort was free of prevalent allergic rhinitis,
children with a history of ‘non-cold/flu-related runny or blocked nose’ or with unknown rhinitis
Childhood AR: Finding from CHS Study
27

information before SPT was performed were excluded (n=162). Children who did not provide
information for ‘non-cold/ flu related sneezing or a runny or blocked nose’ in any of the annual
follow-up questionnaires were also excluded (n=3), resulting in 67 children whose parents never
reported symptoms suggestive of AR prior to SPT and thus were deemed eligible for the incidence
study.
2.2.2 New Onset Allergic Rhinitis and Covariates.
Prevalent and incident AR were identified using the ISAAC questionnaire items validated
by other studies on asthma and allergic rhinitis (Braun-Fahrländer et al. 1997b; de Andrade et al.
2008). Prevalent AR was defined by the affirmative answer to question “Has your child ever had a
problem with sneezing or a runny or blocked nose, when he/she DID NOT have a cold or the flu”
at baseline. Incident AR was defined if children without prevalent AR provided affirmative answer
to “In the past 12 months, has your child had a problem with sneezing or a runny or blocked nose
when he/she DID NOT have a cold or flu” during follow-up. The midpoint of the interval between
the date of questionnaire when AR was first reported and the date of previous questionnaire
without report of rhinitis symptoms was defined as the date of new-onset AR since the exact date
of new-onset AR is often clinically uncertain and cannot be accurately defined based on the annual
questionnaires. Children without reported symptoms were followed until they were lost to follow-
up or until the study ended. Demographic characteristics including age, sex, race/ethnicity, and
socio-economic information such as parental education, annual family income and availability of
health insurance for the child, parental history of allergy or asthma, history of exposure to maternal
cigarette smoking in utero and postnatal exposure to secondhand tobacco smoke, residential
information were assessed by questionnaire at baseline and were updated annually.
Childhood AR: Finding from CHS Study
28

2.2.3 Allergen Sensitization and Air Pollutant Exposure Assessment
Sensitization to common indoor and outdoor allergens was evaluated by SPT (Bernstein et
al. 2008; Rönmark et al. 2009). SPT was defined as positive when having ≥ 3 mm wheal.
Histamine was used as the positive control. Pollen sensitization was defined by positive SPT to
one of the following pollens: olive, coast oak, ragweed, thistle, timothy, and bermuda. Indoor
allergen sensitization was defined as sensitization to any one of the following indoor allergens:
dust mite mix, cat, dog, mouse, cockroach, and Aspergillus. Sensitization to any allergen was
defined by positive SPT to any of allergens mentioned above. The subjects were categorized into 3
categories by number of sensitized allergens: none, mono- (1 positive) and poly-sensitization (>1
positive).
Residential distance to the nearest freeway or main road was used as one surrogate of
TRAP. The distance of each participant’s residence to the nearest freeway was estimated using
methods described previously (McConnell et al. 2006b). Briefly, participants’ residences were
geo-coded using the Tele Atlas database 3 and software (Tele Atlas, Inc., Boston, CA,
www.na.teleatlas.com). A major road was defined based on functional classification by the
California Department of Transportation as a freeway (with limited access) or other highway
(typically with heavy traffic volume), or a major or minor arterial thoroughfare. Residential
distance to the nearest freeway was categorized as <500m and ≥500 m, based on recent evidence
for extended increased concentration of fresh traffic pollutants on this scale, and results from a
previous CHS cohort that have shown respiratory health associations on this spatial scale
(Gauderman et al. 2007). The concentrations of residential TRAP NOx, separated for freeway and
non-freeways sources, were estimated using a line source dispersion model as described previously
Childhood AR: Finding from CHS Study
29

(McConnell et al. 2010). Total NOx was the sum of freeway and non-freeway NOx. Community
levels of NO2, particulate matter with aerodynamic diameter <10 micrometer (PM10) and 2.5
micrometer (PM2.5), and O3 were measured continuously at ambient monitor station in each
community and annual average levels for the year prior to SPT was performed were calculated.
Values of IQR of residential TRAP NOx (freeway NOX=15 ppb, non-freeway NOx=6 ppb, total
NOx=18ppb) were used as cut-off points to categorize the air pollutants to binary variables.
follows
(Kim et al. 2004)
. Similarly, median values of community air pollutants (NO2-19.9 ppb; PM2.5-
15.9 µg/m
3
; PM10 - 34.2 µg/m
3
O3; 45.7 ppb) were used as cut-off to grouping the pollutants into
two groups. Comparing the measurements at enrollment, there were very slight differences in
median values in using the average exposure during followup (median of NO2 changed from 19.9
ppb to 19.6ppb; median of PM10 changed from 34.2 to 32.5; and the median of PM2.5 dropped
from 15.9 to 13.9).
2.2.4 Statistical analyses
Descriptive statistics on sociodemographic, environmental exposures, and clinical
characteristics of the study population were first examined. Cox proportional hazards models were
used to investigate the association between allergen sensitization, or/and air pollutants, and the risk
for developing AR. All models were adjusted for age, sex, and asthma status at the time of SPT
assessment. To assess the associations between AR and ambient air pollutants including PM2.5,
PM10, and NO2, the community when children was resided was included in the model as a random
effect. The potential confounders such as indicators of SES (parental education, annual household
income, health insurance, Spanish language questionnaire), BMI, or exposure history such as
second-hand smoke exposure, in utero exposure to maternal smoking, and parental history of atopy
Childhood AR: Finding from CHS Study
30

were tested in the model. The factors which can alter the magnitude of the associations between
sensitization and incident AR more than 10% were considered as confounders to be adjusted.
Interaction of TRAP and allergen sensitization in the association with incident allergic rhinitis on
multiplicative scale using Wald test were tested. For those showing significant interaction, joint
modeling of sensitization and TRAP exposure was further performed. All hypotheses were tested
assuming a 0.05 significance level and a two-sided alternative hypothesis. All analyses were
conducted using SAS software 9.4 (SAS Institute, Cary, NC, USA).

2.3 Result
The study population was identified as described in Figure 3. To assess the potential
selection bias, children who completed skin test was compared to those who didn’t have the test
for their demographic, socio-economic, family medical history (Table 1). Most of the tested factors
were similar between two populations, except asthma status, history of wheeze and family history
of allergic diseases. To adjust for the possible selection bias, asthma status was chosen from these
three highly-correlated factors to be included in all the models as a confounder.

Childhood AR: Finding from CHS Study
31

Figure 3. Flowchart of study population establishment in SPT cohort study

Sociodemographic and clinical characteristics, as well as environmental exposures of the
study population are presented in Table 2. The mean age at SPT assessment was 8.9 years and the
majority of children were male (62.7%). Most of the subjects were non-Hispanic (56.7%) or
Hispanic white (37.3%), and had parents who graduated with a degree from college or above
(62.7%). Among the 67 participants, 17 (25.4%) were identified as sensitized to at least one
allergen in the SPT panel that was tested including 5 sensitized to indoor allergens only, 7
sensitized to pollens only and 5 sensitized to both pollens and indoor allergens. There were 11 of
them sensitized to more than one tested allergens.

Childhood AR: Finding from CHS Study
32

Table 1 Characteristics comparison between CHS participants with and without SPT (N=5,277)*

No skin prick
test
(N=5,045)
Having skin
prick test
(N=232)
p-value
Female, % 48.8 44.8
Race/Ethnicity, %

0.4
Non-Hispanic white 31.6 33.2
Hispanic white 56.5 56.9
Asian 3.8 1.3
African-American 3.1 3.0
Other 5.0 5.6
Parental Education, %

0.02
High school or under 36.7 30.6
Some college or above 58.9 66.4
Annual Household Income, %

0.1
<$15,000 31.5 26.7
$15,000-$49,000 30.1 28.0
≥$50,000 38.5 45.3
Health Insurance, % 84.8 83.2 0.5
Premature, % 11.0 8.2 0.2
BMI status, %

0.1
Underweight 4.2 5.2
Normal 61.3 57.3
Overweight 12.8 10.8
Obese 12.6 17.7
In utero Exposure to Maternal
Smoking, %
8.0 9.0 0.62
Exposure to secondhand smoke, % 8.0 5.6 0.19
Parental history of atopic diseases, % 42.4 54.7 0.0002
Diagnosed Asthma, % 14.9 66.7 <0.0001
Wheeze, % 28.8 43.1 <0.0001
* Numbers do not always add up because of missing data.

Childhood AR: Finding from CHS Study
33

Table 2 Sociodemographic, Environmental Exposure and Clinical Characteristics of 67 Children
who Underwent SPT and Who Were Free of Allergic Rhinitis when SPT was Performed

Variables*
Children
developed
new onset AR
(N=36)
Children didn’t
developed new
onset AR (N=31)
P-value
Mean age ± SD 8.9 ± 1.3 8.9 ± 1.1 0.5
Female 13 (36.1) 12 (38.7) 0.8
Race/Ethnicity

0.05
Non-Hispanic White 25 (69.4) 13 (41.9)

Hispanic 10 (27.8) 15 (48.4)

Other 1 (2.8) 3 (9.7)

Parental Education

0.9
High school or under 12 (33.3) 13 (41.9)

Some college or above 24 (66.7) 18 (48.1)

Annual Household Income

0.6
<$15,000 10 (27.8) 11 (35.5)

$15,000-$49,000 11 (30.6) 6 (19.4)

≥$50,000 15 (41.7) 14 (45.2)

Children with Health Insurance 31 (86.1) 27 (87.1) 0.9
Body Mass Index (BMI)

0.2
Normal or underweight 24 (66.7) 22 (71.0)

Overweight 6 (16.7) 5 (16.1)

Obese 6 (16.7) 4 (12.9)

In utero Exposure to Maternal Smoking 4 (11.1) 1 (3.2) 0.4
Household SHS Exposure
4 (11.1) 2 (6.7) 0.5
Parental history of atopy 16 (44.4) 11 (35.5) 0.5
*
Age when SPT was performed was presented as mean ± SD. All the other categorical variables were presented as N
(%)

During up to 8 years of follow up, 36 (53.7%) children developed AR. Thirteen of 17
(76.5%) sensitized children developed AR. Pollen and indoor allergen sensitization were
identified as important predictors of risk for AR (Table 3). After adjustment for age, sex and
asthma status, children who had sensitization to more than one type of pollens were at a three-
times increased risk of AR (HR = 3.00; 95% CI: 1.20-7.51) compared with children without any
pollen sensitization. Children with sensitization to any indoor allergen were 4.63 (95% CI: 1.86-
11.50) times as likely to develop AR as children who had no sensitization to indoor allergen.
Children who had any allergen sensitization were 2.52 times (95% CI: 1.23-5.15) as likely to
develop AR as those who had no allergen sensitization (Table 3). The risk of AR increased with
the number of allergens to which a child showed sensitization (Ptrend<0.001). Children who were
sensitized to ≥2 allergens were 4.70 times (95% CI: 2.09-10.56) more likely to develop AR than
non-sensitized children.
We found that elevated TRAP exposure was associated with a higher incidence of AR.
Children who lived within 500m from a freeway were 2.27 (95% CI: 1.06-4.88) times as likely
to develop AR as the ones who lived ≥500m (Table 4). In contrast, ambient air pollutants were
not significantly associated with the occurrence of AR. No statistically significant associations
were observed between PM10 (HR=1.21; 95% CI: 0.54-2.71), PM2.5 (HR=1.19; 95% CI: 0.54-
2.59), NO2 (HR=0.95; 95% CI: 0.48-1.89), or O3 (HR=0.93; 95% CI: 0.48-1.81) with new onset
AR (Table 4).

Childhood AR: Finding from CHS Study
35

Table 3 Association between Allergen Sensitization and Onset of Allergic Rhinitis among 67
Children who Underwent SPT and were Free of Allergic Rhinitis when SPT was Performed
Sensitization
Crude Adjusted*
HR (95% CI) P-value HR (95% CI) P-value
Pollen
†
2.85 (1.30, 6.25) 0.009

1.99 (0.92, 4.31) 0.08
Number of pollen

None Reference

Reference

Mono-sensitization 2.09 (0.62, 6.99) 0.23

1.16 (0.34, 3.97) 0.81
Poly-sensitization
||
3.52 (1.40, 8.82) 0.007

3.00 (1.20, 7.51) 0.02
ptrend 0.005

0.03

Indoor allergen‡ 4.03 (1.73, 9.36) 0.001

4.63 (1.86, 11.5) 0.001
Number of indoor allergen

None Reference

Reference

Mono-sensitization 4.03 (1.35, 11.97) 0.01

4.22 (1.36, 13.11) 0.01
Poly-sensitization
||
4.03 (1.34, 12.06) 0.01

5.20 (1.57, 17.2) 0.007
ptrend 0.002

0.001

Any allergen

§
3.45 (1.67, 7.17) 0.001

2.52 (1.23, 5.15) 0.01
Number of allergen

None Reference

Reference

Mono-sensitization 1.67 (0.49, 5.71) 0.41

0.98 (0.29, 3.39) 0.98
Poly-sensitization
||
5.25 (2.34, 11.77) <0.0001

4.70 (2.09, 10.56) 0.0002
ptrend <0.0001 <0.01

*Adjusted for age, sex, and asthma. Pollen and Indoor allergen was not exclusively adjusted.
† Pollen sensitization was defined by positive SPT to one of the following pollens: olive, coast oak,
ragweed, thistle, timothy, and bermuda.
‡

Indoor allergen sensitization was defined as sensitization to any one of the following indoor allergens:
dust mite mix, cat, dog, mouse, cockroach, Aspergillus.
§
Any allergen included positive SPT to any of allergens mentioned in pollen and indoor allergens.
||
Sensitization to more than one allergen in each type was categorized as poly-sensitization

Childhood AR: Finding from CHS Study
36

Table 4 Association between TRAP and Incident Allergic Rhinitis among Study Population
during up to 8 Years of Follow-Up
Sensitization

Crude Adjust
*

HR 95% CI HR 95% CI
Proximity to freeway

>500m Reference Reference

≤500m 2.01 (0.98, 4.11) 2.27 (1.06, 4.88)
Freeway NOx (ppb)

<15 Reference Reference

≥15 1.09 (0.55, 2.19) 1.09 (0.50, 2.37)
PM10
†

1.21 (0.57, 2.59) 1.21 (0.54, 2.71)
PM2.5
†

1.24 (0.59, 2.61) 1.19 (0.54, 2.59)
O3
†

0.92 (0.48, 1.75) 0.93 (0.48, 1.81)
NO2
†

1.02 (0.53, 1.96) 0.95 (0.48, 1.89)
HR: hazard ratio. CI: confidence interval
*
Adjusted for age, sex and asthma.
†
The expected change in HR with 2SD change in each air pollutant level. 2SD for personal
air pollutant measurement were 21 µg/m
3
for PM 10 , 10 µg/m
3
for PM 2.5, 14 ppb for O 3,
12 ppb for NO 2

Exposure to TRAP and allergic sensitization had synergistic effects on the development of
new onset AR. Using the subjects’ residential distance to the nearest freeway as the air pollution
indicator, there was a synergistic effect between allergen sensitization and TRAP on risk of new
onset AR. Joint modeling was performed to evaluate the effect (Table 5). Children with
sensitization to any indoor allergen and who lived within 500m to a freeway were 7.64 times
(95% CI: 2.55-22.87) as likely to have new-onset AR as non-sensitized children who lived more
than 500m from a freeway (Table 5). Children who had any allergen sensitization and lived
within 500m of a freeway were 8.13 times (95% CI: 2.81-23.53) as likely to develop AR as
compared with non-sensitized children residing more than 500m from a freeway. No other
statistically significant interactions on multiplicative scale between allergen sensitization and
Childhood AR: Finding from CHS Study
37

non-freeway NOx or regional air pollutants including PM10, PM2.5 and O3 were found to be
related to incident AR (p>0.05). Joint modeling confirmed no synergic effect between ambient
air pollutants and sensitization on childhood AR (Table 6).
Table 5 Joint Effect of Air Pollution Indicated by Proximity to Freeway and Allergen
Sensitization on Onset of AR among Study Population during up to 8 Years of Follow-up
Sensitization
Residential distance from the nearest freeway
>500m

≤500m
N HR
*
(95% CI) N HR
*
(95% CI)
Any allergen
†

None 41 Reference

9 1.29 (0.45, 3.70)
Yes 11 1.67 (0.68, 4.09)

6 8.13 (2.81, 23.53)
Pollen
‡

None 44 Reference

11 1.68 (0.68, 4.18)
Yes 8 1.32 (0.49, 3.60)

4 10.99 (2.95, 40.94)
Any indoor allergen
§

None 47 Reference

10 1.50 (0.57, 3.94)
Yes 5 3.06 (0.83, 11.26) 5 7.64 (2.55, 22.87)
HR: Hazard Ratio; CI: Confidence Interval
*
Adjusted for age, sex and asthma
†
Any allergen included positive SPT to any of allergens mentioned in pollen and indoor
allergens
‡
Pollen sensitization was defined by positive SPT to one of the following pollens: olive, coast
oak, ragweed, thistle, timothy, and bermuda.
§
. Indoor allergen sensitization was defined as sensitization to any one of the following indoor
allergens: dust mite mix, cat, dog, mouse, cockroach, Aspergillus.
Childhood AR: Finding from CHS Study
38

Table 6 Joint Effect of Ambient Air Pollutants including PM10, PM2.5, Ozone, and NO2, with Allergic Sensitization on Onset of
Allergic Rhinitis among 67 Children during up to 8 Years Follow-Up

PM 2.5

PM 10

Ozone

NO 2

<=median
a

>median
a

<=median
a

>median
a

<=median
a

>median
a

<=median
a

>median
a

HR
e
95% CI HR
e
95% CI

HR
e
95% CI HR
e
95% CI

HR
e
95% CI HR
e
95% CI

HR
e
95% CI HR
e
95% CI
Pollen
b

None Reference

1.02 (0.43, 2.42)

Reference

1.06 (0.48, 2.30)

Reference

1.01 (0.46, 2.25)

Reference

1.29 (0.57, 2.91)
Yes 2.21 (0.26, 18.70)

1.99 (0.71, 5.59)

3.33 (1.08, 10.28)

1.43 (0.44, 4.58)

1.37 (0.43, 4.42)

3.37 (1.07, 10.63)

2.52 (0.31, 20.82)

2.27 (0.89, 5.83)
Indoor allergen
c

None Reference

1.00 (0.42, 2.38)

Reference

0.84 (0.39, 1.82)

Reference

1.33 (0.60, 2.96)

Reference

1.33 (0.59, 3.02)
Yes 7.78 (0.82, 73.66)

4.39 (1.41, 13.71) 6.46 (1.52, 27.54)

3.62 (1.2, 10.94)

5.59 (1.47, 21.16)

5.68 (1.58, 20.40)

4.28 (0.85, 21.58)

6.24 (1.96, 19.83)
Any allergen
d

None Reference

1.05 (0.41, 2.64)

Reference 0.98 (0.42, 2.27)

Reference

1.12 (0.47, 2.70)

Reference

1.44 (0.59, 3.51)
Yes 3.78 (0.72, 19.91) 2.46 (0.89, 6.81) 3.46 (1.18, 10.18) 2.05 (0.76, 5.54) 2.14 (0.73, 6.25) 3.75 (1.26, 11.18) 4.07 (0.98, 16.86) 2.94 (1.14, 7.58)
a
Median PM 10 is 34.24 ppb; Median PM 2.5 is 15.86 ppb; median Ozone is 45.70 ppb; and median NO 2 is 19.93 ppb.
b
Pollen sensitization was defined by positive SPT to one of the following pollens: olive, coast oak, ragweed, thistle, timothy, and bermuda.
c
Indoor allergen sensitization was defined as sensitization to any one of the following indoor allergens: dust mite mix, cat, dog, mouse, cockroach, Aspergillus,
homodendrum, and Alternaria.
d
Any allergen included positive SPT to any of allergens mentioned in pollen and indoor allergens.

e
Adjusted for age, gender and asthma

Childhood AR: Finding from CHS Study
39

2.4 Discussion
The results from this relatively small study indicate that children with allergen sensitization
may be at greater risk of developing AR and those with both allergen sensitization and high
TRAP exposure were at the greatest risk of developing new-onset AR. Both indoor and outdoor
allergen sensitization were important determinants of AR in children living in southern
California. Allergen sensitization is common in the US and among CHS children, but the
prevalence of sensitization alone differs by age, sex, socioeconomic and regional factors. The
overall rate of allergen sensitization in a US population aged 6 years and older was 44.6%
according to National Health and Nutrition Examination Survey (NHANES) 2005-2006 and 30-
50% of the pediatric population in the industrialized world, which indicates a difference in
allergen-specific sensitization rate based on sociodemographic and regional factors (Salo et al.
2014). The worldwide prevalence of sensitization to one or more common allergens is
approaching 40-50% among school children in general population (Schiller et al. 2012). Skin
prick test is a well-accepted approach to demonstrate an individual’s the allergic response to a
specific allergen with relatively high sensitivity and specificity, which has been recommended as
an appropriate method for the diagnosis of allergic sensitization, providing high sensitivity and
specificity (de Vos et al. 2013; de Vos 2014). In our study, SPT was performed to determine
allergic sensitization at baseline. Allergen types were determined from the most prevalent
respiratory allergens in Southern California, which may potentially miss some other types of
allergen sensitization. In our study population, we observed a positive SPT result to common
allergens in 25.4%, which was slightly lower than the other studies, possibly due to the younger
age of our population. The results from our study also confirmed that a positive SPT result is
closely associated with the incidence of AR among children.
Childhood AR: Finding from CHS Study
40

Ambient air pollutants and TRAP have been found to be associated with the development
and exacerbation of respiratory disease, especially among children (Brauer et al. 2002; Gauvin et
al. 2002; Timonen et al. 2002; Zmirou et al. 2002). In vitro and in vivo effects of air pollutants on
cell culture, animal and human volunteers show exposure to ambient particulate matter can
induce airflow obstruction persisting for up to 48 hours, and activate proinflammatory cytokines
including IL-6, COX-2, and NF- κB (Ahmadi-Abhari et al. 2014; Jagielo et al. 1996; Kline et al.
1999; Zhao et al. 2009) . Results from a large number of studies suggest that increasing levels of
TRAP may, in part, be responsible for the global increasing trend of allergic respiratory disease
including asthma and AR. Large-scale, cross-sectional studies from US and Sweden showed the
increasing prevalence of allergic respiratory disease in children exposed to higher levels of air
pollution (Braun-Fahrländer et al. 1997a; Dockery et al. 1996). These findings were also
supported by biological evidence. It was found that DEP enhances the allergen-specific IgE
response in animal studies (Diaz-Sanchez et al. 1997; Riedl and Diaz-Sanchez 2005). In a
randomized clinical trial, it was found that short-term exposure to DEP resulted in decreased NK
cell recruitment and activation and increased allergic inflammation in nasal mucosa among
persons with AR (Pawlak et al. 2016). Air pollutants can also increase allergenicity of pollen via
increasing allergy potency or release of pollen proteins (Chehregani et al. 2004; Motta et al.
2006; Suárez-Cervera et al. 2008). Exposure to pollens in an area with heavy traffic may be more
likely to induce sensitization than exposure the same pollen in an area with low traffic. These
factors may contribute to the increasing prevalence of allergic diseases in recent years.
The strengths of this study include its prospective follow-up and annually updated
information that permitted evaluation for the association of allergen sensitization and TRAP with
new-onset allergic rhinitis. Using data from the CHS, we previously reported that children living
Childhood AR: Finding from CHS Study
41

near a freeway had increased risk of asthma (Gauderman et al. 2005; McConnell et al. 2010) , as
well as significant deficits in lung function growth rate (Breton et al. 2011; Islam et al. 2007)
among children who were exposed to TRAPs including NO2, PM2.5, and elemental carbon. Further,
the protective effect of better lung function on asthma was reduced among adolescents exposed to
high levels of PM2.5 (Gauderman et al. 2002; Islam et al. 2007). Using data on home location with
respect to highway as an indicator of TRAP, we found significant associations between traffic
proximity and risk of respiratory diseases, including wheeze (Venn et al. 2001), respiratory
hospital admission (Buckeridge et al. 2002), and childhood asthma medical care visits (Chen et al.
2015; Eckel et al. 2016; English et al. 1999). The results from the present study further support a
role for allergen sensitization on onset pediatric AR and enhancement by TRAP. In this study, we
found a significant interaction between freeway NOx and allergen sensitization on new-onset AR,
but little evidence for enhancement between non-freeway NOx and allergen sensitization.
Furthermore, regional community central-site measurement of criteria pollutants including NO2,
PM10, PM2.5, and O3 did not show significant interactions with allergen sensitization on onset AR.
These findings suggest that the air pollutants from high volume freeways may be an important risk
factor for new onset AR, especially among respiratory allergen sensitized children. These
associations could not be explained by demographic or socio-economic factors, which are
consistent with the other studies (Chen et al. 2015). In sensitivity analysis, we used the annually
updated information for ambient air pollutants such as PM10, PM2.5 and NO2 and obtain the median
exposure of ambient air pollutants between study enrollment and study ending date for each
participant. From annually completed questionnaire, we have confirmed that all 67 participants
stayed in the same community from start to the end of study. Moves within communities were
used to estimate longer term exposures using time-weighted averages. By comparing the median
Childhood AR: Finding from CHS Study
42

values to the baseline measurement, it was found they were very similar (Table 7). We did not use
yearly variation in concentrations because our hypothesis was that longer-term exposure was
associated with the pathophysiologic process leading to AR. Especially all these ambient pollutants
were used as binomial variables with median levels as the cut-off points. There were very slight
differences between median exposure at study entry with median exposure using time-weighted
averages. For interpretations, we decided to use baseline exposures in our analysis.
We also updated information on TRAP including distance to freeway or main road if children
moved to a new residential address. None of these 67 children moved out of their original
communities during follow-up except 4 moved within a community. Further investigation showed
only 1 of 4 switched the categories of distance to freeway and this move was close to the end of
the study.

Table 7 Ambient air pollutants comparison between measurements at study entry and averaged
during follow-up
Air
pollutants
Baseline measurement used in
analysis
Mean of median exposure during
follow-up
Mean SD Median Mean SD Median
NO2 19.4 6.0 19.9 18.1 5.7 19.6
PM10 37.2 10.4 34.2 34.5 9.0 32.5
PM2.5 14.8 5.0 15.9 14.1 4.0 13.9

However, there were some limitations. In this study, 67 children completed SPT. Due
to the small sample size, further analysis of associations with specific allergens was not feasible.
Childhood AR: Finding from CHS Study
43

However, associations between allergen sensitization and incidence AR were of large enough
magnitude to reach statistical significance using longitudinally collected data.
Because AR was associated with asthma in other studies (Gürkan et al. 2002; Kocabas
et al. 2005; Leynaert et al. 2000b), asthma was a potential confounder or mediator. However, the
association between allergen sensitization and incident AR was robust to adjustment for asthma
status at the time of SPT, suggesting independence of effects of allergy on AR and asthma.
Although there was the potential recall bias for AR when parents answered the questionnaire at
study entry, a broad case definition was used to define AR-free children at enrollment, so recall
was unlikely to be differential or affect the ascertainment of incident AR during follow-up or be
related to exposure. In this study, exposure to air pollutants including ambient air pollutants
(NO2 , PM2.5, etc.) examined in a community level was assigned to individuals instead of
personal measurements. We acknowledge the possible bias coming from misclassification of
these exposures to individual. However, this misclassification was unlikely to be differential by
AR case status.

2.5 Conclusion
This prospective study supports the hypothesis that TRAP and aeroallergen exposure
during childhood may have synergic effects on the risk of new-onset allergic rhinitis. The study
suggests the need for public health policy interventions to reduce TRAP and individually tailored
environmental control of indoor allergen exposures for the primary prevention of allergic
rhinitis.
Childhood AR: Finding from CHS Study
44

Chapter 3. Cross-Sectional Study on the
Association between Environmental Risk
Factors and Prevalent Allergic Rhinitis
among Children

3.1 Introduction
Allergic rhinitis (AR) is a common chronic condition in children affecting 8.4% of
American children (Selnes et al. 2005). Although AR is not a life-threatening condition, it
adversely affects the patients’ social life, school and work performance which also imposes an
economic burden to family and society. According to 2012 Centers for Disease Control and
Prevention (CDC) report, approximately 11.1 million ambulatory visits in 2010 were due to AR.
The estimated direct costs for AR in the U.S. was $11.2 billion in 2005 due to expenditure on
medications and health care provision, with an estimated indirect cost approaching US $9.7
billion due to the loss of work, or social support (WAO White Book on Allergy, World Allergy
Organization, 2008).
Beyond effects on quality of life and economic costs, AR is an important condition to
prevent as it is considered to be part of the “allergic march” during childhood (Kjellman 1994)
and was an independent risk factor for asthma in a 23-year follow up study (Settipane and
Settipane 2000). Children with allergic rhinitis, especially those with troublesome ocular
symptoms, are more likely to have other inflammatory disorders including asthma, atopic
eczema, and other atopic diseases (Greiner et al. 2011). Therefore, effective methods to prevent
Childhood AR: Finding from CHS Study
45

and to manage AR exacerbation in childhood are necessary to reduce the substantial clinical and
public health burden.
Population-based epidemiological studies have identified several host determinants of AR
including age, sex, race/ethnicity, parental, especially maternal, history of allergic disease (Alm
et al. 2011; Marinho et al. 2007; Osman et al. 2007; Sánchez-Lerma et al. 2009). It is estimated
that the prevalence of AR varies from 1.4% ~39.7% of children worldwide (Rosenwasser
2013). The marked international variation is consistent with an important environmental
contribution to AR. Various environmental factors including pollen, air pollutants and indoor
allergens have been reported to play an important role in the occurrence of AR. Pollens from
grass, trees or weeds are the dominant outdoor allergens depending on region while house dust
mites (HDM), pet allergens, and molds are the most common indoor allergens (Codispoti et al.
2015; Zuraimi et al. 2011). These allergens in the indoor or/and outdoor environment may
independently or jointly induce AR among children. Important triggers of AR may differ by
geographic areas with different climates, biological allergen species, or life styles. In Korea,
exposure to mold during infancy is considered to be one of the major risk factors of AR where
children are indoors during the cold winter and mold was found in 90% of houses (Jeong et al.
2012). In Japan, pollen from Cryptomeria japonica is the most important AR trigger (Maeda et
al. 2010). In addition to indoor and outdoor allergens, other environmental exposures, especially
those appearing in the modern/industrialized society such as ambient air pollutants and traffic-
related air pollution (TRAP), may also contribute to the etiology of allergic rhinitis (Wang 2005).
A cohort conducted in China reported that early life exposure to ambient air pollutants,
particularly NO2 and PM10 during the third trimester of pregnancy and during the first-year of
Childhood AR: Finding from CHS Study
46

life, were associated with life-time prevalence of AR in preschool children (Deng et al. 2016). A
pooled analysis of 6 birth cohorts showed that PM2.5 mass was statistically significantly
associated with elevated risk for allergic rhinitis (Fuertes et al. 2013a). Add a summary sentence
for this paragraph
Although evidence for concerning environmental contribution to AR is growing, there are
a number of gaps in the scientific knowledge base for AR. First, there are a limited number
studies focused on AR among children under 7 years old (Marinho et al. 2007; Morgenstern et al.
2008) although rhinitis in this age group is a relatively common problem (Hardjojo et al. 2011).
There is a significant unmet need for prevention and treatment guideline of AR in this age group.
Secondly, the methods used for the classification of rhinitis into non-allergic rhinitis (NAR) and
allergic-rhinitis (AR) are an active area of research. AR is usually characterized with additional
symptoms of itchy eyes while NAR may be induced by triggers including infectious, hormonal
which is not related to IgE-mediated mechanism (Alm et al. 2011; Hardjojo et al. 2011; Mai et
al. 2007). Especially in young children, NAR and AR may co-exist and be hard to differentiate.
In addition, risk factors such as outdoor or indoor environmental exposures have been studied
separately in previous studies (Codispoti et al. 2015; Dong and Cheng 2008; Morgenstern et al.
2008). However, factors from indoor and outdoor environment may work together and have
important synergism in warm areas such as southern California where children spend more of the
year outdoors exposed to ambient air pollutants and outdoor allergens such as pollens.
To address some of these knowledge gaps for early childhood AR, in this study, we
performed a cross-sectional study among 1,611 children from 13 Southern California
communities who were aged 5-7 years and lifetime residents of the same house. We investigated
Childhood AR: Finding from CHS Study
47

important indoor/outdoor environmental exposures (including history of mildew, pests in the
house, ambient NO2, and PM10), socio-economic status, and family medical history separately
and jointly for their association with two types of AR with different symptoms (nasal allergy
only and rhinoconjunctivitis).

3.2 Method
3.2.1 Study Population
Participants in the Southern California Children Health Study (CHS) were enrolled between
2002 and 2003. The study was approved by the IRB committee of University of Southern
California. Details about the study design have been described previously (Bastain et al. 2011;
Berhane et al. 2011). Briefly, 5,487 children in kindergarten or first grade (5–7 years old) were
recruited from 13 communities in southern California. With informed consent, parents completed
a questionnaire at study entry to provide information including demographic characteristics,
socioeconomic status, family medical history, child’s respiratory conditions and symptoms.
Residential history was also collected in the questionnaire. To reduce exposure misclassification
from residential mobility, the primary analysis was performed among the children who lived in
the same residence from birth to study entry (N=1,671). Children who did not provide answer to
the question of “Has your child ever had a problem with sneezing or a runny or blocked nose,
when he/she did not have a cold or the ‘flu’” in the baseline questionnaire were excluded (n=60),
resulting in 1,611 eligible children in final analysis.

Childhood AR: Finding from CHS Study
48

3.2.2 Prevalent Allergic Rhinitis and Covariates.
Cases of AR were identified using the validated ISAAC questionnaire validated (Braun-
Fahrländer et al. 1997b; de Andrade et al. 2008). We classified children based on their AR
symptoms into three groups. Children providing affirmative answers to the questions - “Has
your child ever had a problem with sneezing or a runny or blocked nasal, when he/she DID NOT
have a cold or the flu” and “In the past 12 months, has this nasal problem been accompanied by
itchy-watery eyes” at baseline were classified as “prevalent rhinitis with nasal and ocular
symptom (rhinoconjunctivitis)”. Those only providing affirmative answer to the first question
were identified as “prevalent rhinitis with nasal symptom (nasal allergy)”. Those who did not
provide the affirmative answer to the first question were classified as “No AR symptoms”.
Demographic characteristics including age, sex, race/ethnicity, and socio-economic
information such as parental education, annual household income and availability of health
insurance for the child, medical history such as prematurity, and history of exposure to cigarette
smoking during in utero and postnatal period were collected in questionnaire at study entry.
Family history of allergic disease was also determined from questionnaire responses at study
entry. Specifically, child was identified to have family history of allergic disease if either of his
(her) parents had doctor-diagnosed hay fever, allergies or asthma.
3.2.3 Indoor Environmental Factors
To examine if indoor environment factors were related to prevalent AR, we identified the
children who resided in the same house from birth to study entry. Household characteristics
included types of the house, time and date the house was originally built. Multiple indoor
environmental factors were also assessed using the baseline questionnaire. Specifically, we
Childhood AR: Finding from CHS Study
49

collected information on types of household heating system, fuel used to heat the house, air
conditioning use, carpeting in the home, humidifier or vaporizer use, lifetime history of indoor
pet ownership (including cats, dogs, birds), exposure to pests (including termites, spiders, ants,
cockroaches, mice, rats) and history of exposure to mold/mildew inside the house.
3.2.4 Ambient Air Pollutants
Several metrics of exposure to traffic-related air pollutants at participants’ residences were
considered. First, the residential addresses of participants were standardized and their locations
were geocoded using the TeleAtlas database which is more accurate than the standard files
available from the U.S.Census (Tele Atlas, Inc., Boston, CA, www.na.teleatlas.com), Then the
distance of each residence to the nearest freeways or major roads was estimated using ESRI
ArcGIS Version 9.2 (ESRI, Redlands, CA, www.esri.com) s described previously (McConnell et
al. 2006a). Residential distance to the nearest freeway was categorized as < 500m and ≥ 500 m
while distance to main roads was categorized as < 75m and ≥ 75m based on evidence from
studies of concentrations around freeways (Fruin et al. 2014) and previous CHS studies that have
shown respiratory health associations on this spatial scale (Gauderman et al. 2007). The
concentrations of residential traffic-related air pollutants from freeway and non-freeway sources
were estimated separately using the CALINE4 dispersion model. This Gaussian line-dispersion
model incorporates distance to roads, traffic counts, emissions factors, and local meteorology to
estimate concentrations of traffic-related pollutants, with NOx used as a marker, at the residences
of study participants at study entry (McConnell et al. 2010). Total NOx was calculated as the sum
NOx from freeway and non-freeway sources.

Childhood AR: Finding from CHS Study
50

Regional air pollutants were also considered in this analysis. Individual levels of NO2,
particulate matter with aerodynamic diameter < 10 micrometers (PM10) and with aerodynamic
diameter < 2.5 micrometers (PM2.5), and ozone (O3) were continuously collected with Federal
Reference Method or Federal Equivalent Method instruments in each of the study communities
(Berhane et al. 2014; Gauderman et al. 2007).
The primary exposure metric used in this study was the average air-pollutant
concentrations from individual’s birth year to the study entry based on residency location. Effect
estimates were scaled to two times standard deviations NO2, PM10, PM2.5, O3, and NOx to
facilitate comparison of the effect of different air pollutants on AR.
3.2.5 Statistical Analysis
Descriptive statistics for selected characteristics of the study population including
socioeconomic status, family history of allergic diseases, and residential environmental exposure
were examined and compared among three groups of children who had no symptom, nasal
allergy, or rhinoconjunctivitis. Multinomial logistic regression using PROC GLIMMIX was
performed to investigate independent associations between indoor/outdoor environmental factors
and prevalent AR with different symptoms. Single factor analysis was performed first to
determine potential risk factors for AR. In the model assessing the association between ambient
air pollutants (PM2.5, PM10, O3, and NO2) and AR, indicator of Spanish questionnaire was
included as a default covariate to reduce the potential information bias when people answered
questionnaires in languages. In all other models tested associations of AR with socio-
demographic characteristics, family history of allergic diseases, indoor environmental factors or
TRAP, community where children resided was added as a random effect besides having indicator
Childhood AR: Finding from CHS Study
51

of Spanish questionnaire as a covariate. Exposures and risk factors showing statistically
significant associations in the univariate analysis or those consistently reported in previous
studies were included in final multivariable models. All hypotheses were tested two-sided at a
0.05 significance level. Statistical analyses were conducted in SAS software 9.4 (SAS Institute,
Cary, NC, USA).

3.3 Results
In this study, from 5,264 participants enrolled in the Children’s Health Study (2002-3),
1,611 participants who had resided in the same house since birth were selected in the final
population (Figure 4). Comparison between children whose parents answered ‘Yes’ or ‘No’ to
the question –“Has your child lived in current residence his or her entire life”, showed no
significant difference for all socio-demographic characteristics and most exposure history (Table
8).
Among 1,611 participants, 534 (33.1%) reported any lifetime history of AR at study entry.
As shown in Table 9, single factor analysis suggested the odds of having nasal allergy among
Hispanic was 0.57 times (95% CI: 0.40-0.81) as of non-Hispanic White. More than 70% of
children with rhinoconjunctivitis and approximately 50% of children with nasal allergy had a
family history of allergic disease, compared to only 33% among non-symptomatic children
(Table 9). A higher proportion of children with rhinoconjunctivitis were exposed to maternal
smoking during pregnancy (9.9%) compared to those without symptoms (4.6%). The odds of
rhinoconjunctivitis was 4.3 (95% CI: 5.9 - 3.1) among children with family history of allergic
diseases and 2.0 (95% CI: 3.2-1.2) among those exposed to maternal smoking. The odds of nasal
Childhood AR: Finding from CHS Study
52

allergy also increased to 2.3 (95% CI: 3.2-1.7) when children had a family history of allergic
diseases.

First graders/Kindergarteners were enrolled from 13 communities in
Southern California
N=5,364
Eligible population in this study
N=1,611
Children lived in the same residence since birth
(N=1,671)
Exclude children who didn’t
provided answer to ISAAC
questionnaire at study entry

Figure 4. Establishment of eligible population for the cross-sectional study

Childhood AR: Finding from CHS Study
53

Table 8 Characteristics Comparison of CHS Participants by their Answers to Lifetime
Residential History (N=5,111)

Living in the same residence since
birth*
P-
value
Yes (N=3,500) No (N=1,611)
Age, mean years ± SD 6.57 ± 0.65 6.56 ± 0.66 0.09
Race/ethnicity, N (%)

0.16

White 1,123 (32.1%) 524 (32.5%)

Asian 85 (2.4%) 66 (4.1%)

Black 137 (3.9%) 48 (3.0%)

Hispanic 1,963 (56.1%) 885 (54.9%)

Other 192 (5.5%) 88 (5.5%)

Male, N (%) 1772 (50.6%) 849 (52.7%) 0.18
Mother's education level, N (%)

0.08

High school and lower 1,343 (38.4%) 599 (37.2%)

College and above 1,480 (42.3%) 676 (42.0%)

Unknown 252 (7.2%) 145 (9.0%)

Premature, N (%) 2,975 (85.0%) 1391 (86.3%) 0.1
Parent atopy history, N (%) 1,540 (44.0%) 695 (43.1%) 0.57
Maternal smoking during pregnancy, N (%) 309 (8.8%) 93 (5.8%) 0.0002
Smoke, N (%) 296 (8.5%) 117 (7.3%) 0.15
Home construction year, N (%)

0.02

After 1970's 1,920 (54.9%) 737 (45.7%)

Before 1970's 1,477(42.2%) 819 (50.8%)

Water damage, N (%) 458 (13.1%) 242 (15.0%) 0.06
Mildew, N (%) 761 (21.7%) 396 (24.6%) 0.02
Musty odor, N (%) 155 (4.4%) 59 (3.7%) 0.2
Humidifier, N (%) 746 (21.3%) 397 (24.6%) 0.008
Air conditioner use, N (%) 2,022 (57.8%) 895 (55.6%) 0.14
Pests, N (%) 2,215 (63.3%) 971 (60.3%) 0.05
Pets at home, N (%) 1,808 (51.7%) 867 (53.8%) 0.15

Dog 973 (27.8%) 470 (29.2%) 0.3

Cat 669 (19.1%) 271 (16.8%) 0.05
* 153 children didn't provided answer to this question. The % in some of characteristics doesn’t add up to 1 due
to missing.

Childhood AR: Finding from CHS Study
54

The majority of indoor environmental exposure metrics including residential history of
water damage, musty odor, and pests in the past 12 months were associated with AR in single
risk factor analyses. For example, among children whose parents reported a history of
mildew/mold in the house, the odds of nasal allergy increased 2.0 (95% CI: 1.5-2.8) and the odds
of rhinoconjunctivitis was 1.9 (95% CI: 1.4-2.5) times higher (Table 10).

The mean (SD) level of freeway NOx and non-freeway NOx from birth to study entry
were 16.0 (15.2) ppb and 6.8 (4.3ppb), respectively. The lifetime average (SD) exposure levels
of NO2, O3, PM10, and PM2.5 in the communities were 23.4 (8.49) ppb, 27.6 (9.28) ppb, 36.0
(12.69) µg/m
3
, or 17.9 (5.94) µg/m
3
, respectively. We found that PM10 and NO2 were
significantly associated with rhinoconjunctivitis (Table 10). A two standard increase in PM10
(25.4 µg/m
3
) resulted in an OR of 1.3 (95% CI: 1.1-1.7) and an increase in NO2 (17.0 ppb) led to
an OR of 1.4 (95% CI: 1.1-1.8) for prevalent rhinoconjunctivitis.

Childhood AR: Finding from CHS Study
55

Table 9 Demographic Characteristics and Medical History Comparison and Single Factor Analysis among CHS Participants who have
Resided in the Same House from Birth to Study Entry (N=1,611)

No*
Nasal
Allergy*
Rhinoconjunctivitis* Nasal Allergy Rhinoconjunctivitis
N=1,077 N=240 N=294 OR (95% CI) OR (95% CI)
Mean age

6.52± 0.65 6.42 ± 0.64 6.52 ±0.66 0.78 (0.63-0.98) 0.98 (0.80-1.20)
Male

550 (51.1%) 137 (57.1%) 162 (55.1%) 1.28 (1.70-0.96) 1.17 (1.51-0.90)
Race/ethnicity

White 314 (29.2%) 100 (41.7%) 110 (37.4%) 1

Asian 56 (5.2%) 3 (1.3%) 7 (2.4%) 0.17 (0.05-0.56) 0.35 (0.16-0.80)

Black 30 (2.8%) 4 (1.7%) 14 (4.8%) 0.43 (0.15-1.27) 1.33 (0.68-2.61)

Hispanic 624 (57.9%) 117 (48.8%) 144 (49.0%) 0.57 (0.40-0.81) 0.90 (0.66-1.23)
Mother's education level

High school or lower 452 (42.0%) 79 (32.9%) 68 (23.1%) 1

College 396 (36.8%) 112 (46.7%) 168 (57.1%) 1.73 (1.20-2.49) 2.30 (1.64-3.24)

Graduated 90 (8.4%) 27 (11.3%) 28 (9.5%) 1.82 (1.07-3.10) 1.67 (0.99-2.79)
Insurance

908 (84.3%) 213 (88.8%) 270 (91.8%) 1.41 (0.85-2.32) 1.86 (1.08-3.23)
Annual Household Income

<$15,000 158 (14.7%) 31 (12.9%) 29 (9.9%) 1

$15,000-$49,000 310 (28.8%) 75 (31.3%) 83 (28.2%) 1.17 (0.74-1.87) 1.36 (0.85-2.17)

≥$50,000 425 (39.5%) 99 (41.3%) 151 (51.4%) 1.01 (0.62-1.64) 1.39 (0.87-2.20)
Premature

93 (8.6%) 27 (11.3%) 39 (13.3%) 1.31 (2.07-0.83) 1.49 (2.22-0.99)
History of parental allergic disease 367 (34.1%) 120 (50.0%) 208 (70.8%) 2.30 (3.19-1.66) 4.28 (5.86-3.12)
Maternal smoking during pregnancy 50 (4.6%) 14 (5.8%) 29 (9.9%) 1.26 (2.33-0.68) 1.97 (3.19-1.22)
Home construction after 1970's 527 (48.9%) 132 (55.0%) 160 (54.4%) 1.21 (1.63-0.90) 1.08 1.42-0.82)
*The overall % in some factors didn’t add up to 1 due to missing value
Childhood AR: Finding from CHS Study
56

Table 10 History of Exposure to Environmental Factors Comparison and Odds Ratio Analysis on Childhood Allergic Rhinitis among
CHS Participants who have Resided in the Same House since Birth(N=1,611)
No Nasal Allergy Rhinoconjunctivitis Nasal Allergy Rhinoconjunctivitis
N=1,077 N=240 N=294 OR (95% CI) OR (95% CI)
History of Water damage at home* 138 (12.8%) 46 (19.2%) 58 (19.7%) 1.56 (1.07-2.28) 1.46 (1.04-2.06)
History of Mildew or mold at home* 220 (20.4%) 79 (32.9%) 97 (33.0%) 2.01 (1.46-2.75) 1.87 (1.40-2.51)
Humidifier or vaporizer use* 206 (19.1%) 79 (32.9%) 112 (38.1%) 2.05 (1.48-2.85) 2.21 (1.65-2.96)
Musty Odor* 33 (3.1%) 8 (3.3%) 18 (6.1%) 1.14 (0.52-2.52) 2.45 (1.33-4.49)
Use of air conditioning* 560 (52.0%) 143 (59.6%) 192 (65.3%) 1.34 (0.95-1.88) 1.36 (1.02-1.81)
Carpeting* 963 (89.4%) 224 (93.3%) 270 (91.8%) 1.45 (0.82-2.56) 1.13 (0.69-1.84)
Pests in the past 12 months* 591 (54.9%) 166 (69.2%) 214 (72.8%) 1.81 (1.32-2.49) 2.03 (1.50-2.76)
Pets at home* 558 (51.8%) 135 (56.3%) 174 (59.2%) 1.16 (0.86-1.55) 1.22 (0.93-1.60)
Freeway NOx*,
#
17.10±26.01 13.39±17.12 13.97±17.00 0.76 (0.58-1.00) 0.89 (0.71-1.12)
Non-freeway NOx*,
#
7.07±5.61 6.30±5.19 6.26±5.14 1.07 (0.80-1.45) 0.96 (0.74-1.26)
Total NOx*,
#
24.17±28.37 19.69±20.11 20.23±19.92 0.77 (0.58-1.03) 0.89 (0.69-1.14)
PM 10
#,§
36.19±12.40 36.66±12.67 36.99±12.05 1.12 (0.87-1.45) 1.34 (1.06-1.70)
PM 2.5
#,§
17.87±6.66 18.32±6.70 19.00±6.40 1.09 (0.82-1.45) 1.19 (0.91-1.56)
NO 2
#,§
23.14±8.96 23.59±9.19 25.00±8.90 1.09 (0.84-1.42) 1.41 (1.10-1.82)
O 3
#,§
26.86±8.81 26.92±8.91 26.92±9.09 1.00 (0.74-1.34) 0.92 (0.70-1.22)
Distance from freeway (≤500m) * 265 (24.6%) 56 (23.3%) 52 (17.7%) 0.71 (0.51-1.00) 0.92 (0.66-1.28)
Distance from main road (≤75m) * 203 (18.9%) 44 (18.3%) 49 (16.7%) 0.87 (0.62-1.24) 0.94 (0.66-1.35)
* Using multinomial logistic regression model with indicator of answers in Spanish as confounder and community as random effect.
#
Using multinomial logistic regression model with indicator of answers in Spanish as confounder
§
Per 2SD unit increase. Specifically, per 30ppb freeway NOx increase, per 8 ppb non-freeway NOx increase, per 37 ppb total NOx
increase, per 17 ppb NO 2 increase, per 19 ppb Ozone increase, per 25 µg/m
3
PM 10 increase, or per 12µg/m
3
PM 2.5 increase.
Childhood AR: Finding from CHS Study
57

We next conducted multivariate analysis to investigate the impact of indoor and outdoor
environment on AR after adjustment for risk factors from the single factor models (such as
premature and family history of allergic disease) or supported by the existing literature such as
age, sex, race/ethnicity, parental education status, and history of exposure to maternal smoking
during pregnancy. The indoor and outdoor environmental exposures were selected from single
factor analysis if they were shown as significant factors for AR or if they were supported by
other reports such as pets at home. Mildew and musty odor were highly correlated and mildew
was kept because it was more objective. Because of high correlation between PM10 and NO2, a
model with both of them in was not feasible. Therefore, two models were performed separately
to include PM10 or NO2 with all other risk factors. The odds ratios of demographic, indoor
environmental factors were similar in two models. In a model including PM10 (Table 11), family
history of allergic disease was related to odds of 3.5 (95% CI: 2.5-4.8) for rhinoconjunctivitis
and odds of 1.7 (95% CI: 1.2-2.5) for nasal allergy. History of exposure to maternal smoking
during pregnancy was significantly associated with prevalence of rhinoconjunctivis, but not nasal
allergy. In adjusted models, children living in a house/apartment with history of mildew had 1.7
times (95% CI: 1.2 -2.4) higher prevalence of nasal allergy and 1.4 (95% CI: 1.0- 1.9) higher
odds of rhinoconjunctivitis. Children with humidifier or vaporizer in their bedroom had an
increased prevalence of rhinoconjunctivitis (OR: 1.7; 95% CI: 1.3-2.4) compared with those who
did not use a humidifier. Exposure to PM10 was an independent risk factors for
rhinoconjunctivitis (OR: 1.4; 95% CI: 1.0-1.8) and nasal allergy (OR: 1.3; 95% CI: 1.0-1.9)
(Table 11). Children living in the area with higher level of NO2 had 1.5 times (95% CI: 1.1-1.9)
higher prevalence of rhinoconjunctivitis across 2 SDs of concentrations (17 ppb).
Childhood AR: Finding from CHS Study
58

3.4 Discussion
In the cross-sectional study, we investigated the determinants for allergic rhinitis among
1,611 residentially stable 5-7-year-old children residing in Southern California.
The case definition of AR depends largely on the occurrence of a correlated group of
clinical symptoms. The typical symptoms of AR include rhinorrhea, sneezing, itching and stuffy
nose due to obstruction or congestion. Coexistence of ocular symptoms including itchy and
watery ocular, or/and swollen eyelids is common among patients with AR (Klossek et al. 2012).
In clinical practice, AR diagnosis is based on a consistent medical history including symptoms,
age of onset, family history, therapy history and physical examination of nasal passages (Quillen
and Feller 2006). According to the World Health Organization (WHO) guideline developed in
2008 (Bousquet et al. 2008), allergy test such as percutaneous skin test and the allergen-specific
immunoglobulin E (IgE) antibody test are recommended but not required for a diagnosis of AR.
In large population-based studies, validated questionnaire responses on symptoms have been
used to establish a standardized case definition by International Study of Asthma and Allergies in
Childhood (ISAAC) (Asher et al. 1995). This case definition is based on confirmative self-report
of ‘ever had nasal symptoms in the absence of a cold’, which has been validated in other studies
on asthma and AR (Braun-Fahrländer et al. 1997b; de Andrade et al. 2008). In most recent
studies, it was found that using combined nasal and ocular symptoms in ISAAC questionnaire to
define AR cases can improve the sensitivity compared with a case definition using nasal
symptoms alone (74% vs. 67%) with similar specificity (Kim et al. 2012).
Childhood AR: Finding from CHS Study
59

Table 11 Multivariate Analysis on Association between Socio-Demographic, Medical and Family History, and Environmental Risk
Factors and Allergic Rhinitis among CHS Participants who have Resided in the Same House since Birth (N=1,611)
Nasal allergy Rhinoconjunctivitis Nasal allergy Rhinoconjunctivitis
OR * (95% CI) OR* (95% CI) OR* (95% CI) OR* (95% CI)
Age

0.76 (0.61-0.96) 0.99 (0.80-1.22) 0.76 (0.60-0.96) 0.99 (0.80-1.23)
Male vs. Female

1.35 (1.01-1.82) 1.18 (0.89-1.56) 1.35 (1.01-1.82) 1.18 (0.89-1.56)
Mother's education level

High school and
lower
Reference Reference
College 1.45 (0.98-2.15) 1.84 (1.27-2.68) 1.39 (0.94-2.06) 1.77 (1.22-2.57)
Graduated 1.30 (0.73-2.31) 1.14 (0.65-2.00) 1.24 (0.69-2.20) 1.07 (0.61-1.88)
Premature

1.16 (0.72-1.86) 1.21 (0.79-1.86) 1.17 (0.73-1.88) 1.23 (0.80-1.88)
History of parents' allergy

1.73 (1.22-2.46) 3.45 (2.47-4.80) 1.71 (1.21-2.42) 3.38 (2.42-4.71)
Maternal smoking during pregnancy 0.92 (0.47-1.78) 1.68 (0.99-2.87) 0.92 (0.47-1.78) 1.67 (0.98-2.84)
History of mildew

1.72 (1.23-2.41) 1.41 (1.03-1.93) 1.71 (1.22-2.39) 1.40 (1.02-1.92)
Humidifier or vaporizer use

1.64 (1.16-2.31) 1.73 (1.26-2.36) 1.62 (1.15-2.28) 1.68 (1.23-2.30)
Pests in the past 12 months

1.37 (0.98-1.93) 1.60 (1.14-2.23) 1.39 (0.99-1.95) 1.64 (1.18-2.30)
Pets at home

0.88 (0.64-1.21) 1.00 (0.74-1.35) 0.88 (0.64-1.21) 1.01 (0.74-1.36)
PM10
#

1.34 (0.97-1.86) 1.37 (1.02-1.83)

NO2
#

1.13 (0.82-1.58) 1.45 (1.11-1.90)
*Using multinomial logistic regression model with community as random effect, adjust for age, race/ethnicity, Spanish questionnaire, and all the
variables listed in table.
# PM 10 and NO 2 were exclusively adjusted in the model. Change of 17 ppb NO 2 increase, or 25 µg/m
3
PM 10 increase or tested

Childhood AR: Finding from CHS Study
60

To address heterogeneity in the case definition of AR, we separated AR into nasal
allergy and rhinoconjunctivitis by their reported symptoms. So we performed a multinomial
logistic regression to assess the associations of potential risk factors with nasal allergy or
rhinoconjunctivitis individually. We found that some factors were only significantly related to
rhinoconjunctivitis such as NO2 and exposure to maternal smoking in utero, while some
factors had larger effect on rhinoconjunctivitis such as the history of pests in the house. On
the other hand, some factors showed stronger relationship to nasal allergy alone, such as sex
and residential history of mildew, but weaker with rhinoconjunctivitis.
In this study, we tested the impact of early childhood environment on AR accounting for
the effect from social-demographic and family history factors. Positive associations were found
between use of humidifier, mildew/molds, or pests at home and prevalence of AR but the pets
such as cats and dogs were not independent factors for AR in our population. We also
investigated the impact from outdoor environment at the same time. Ambient factors such as
PM10 or NO2 were identified as independent risk factors. Using the average exposure levels of air
pollutants from birth to study entry, it was found that children living in the community with
consistent higher PM10 or NO2 had higher occurrence of rhinoconjunctivitis. This finding is
consistent with previous studies. A cross-sectional study conducted among 6,672 children aged
9–11 years from six French cities shown that the lifetime AR increased to 1.32 (95% CI: 1.04–
1.68) per increase of 10 μg/m
3
of PM10 (Pénard-Morand et al. 2005). Increased risk of allergic
rhinitis at the age of 4 years with higher exposure levels of traffic-PM10 in first-year was
identified in a prospective birth cohort which was composed of 4089 children living in 4
Swedish municipalities(Nordling et al. 2008).
Childhood AR: Finding from CHS Study
61

More similar findings have been reported in Asia recently where air pollution becomes a
big problem. A study performed among 6,730 kindergarteners in China had found a strong
associations between prevalence of persistent cough and wheeze and air pollutants such as PM10,
SO2, and NO2 among girls (Liu et al. 2013). Another time-series analysis in the city of
Northeastern China from 2013 to 2015 suggested the positive relationship between prevalence of
allergic rhinitis and PM2.5, PM10, SO2 and NO2. The lag effects from same study suggested the
highest Relative Risks (RRs) of AR from NO2, PM10 and PM2.5 were on the same day and the
concentration of air pollutants might contribute to the development of AR (Teng et al. 2017).
These findings were also consistent with characteristics of PM10. PM10 consists of PM2.5 and
larger particles of mainly crustal or biological origin including many aeroallergens such as
fungal spores and pollen (Delfino et al. 1997; Ostro et al. 2001). This size particulate of PM10 is
mainly deposited in the nose and upper airways. Thus, its deposition pattern might contribute to
the findings of increased prevalence of AR with PM10 but not PM2.5. Studies in animals and in
vitro suggested that exposure to PM results in enhanced allergic inflammation with Th2 and
Th17 phenotypic differentiation (van Voorhis et al. 2013; Wang et al. 2011). The proposed
underlying mechanisms include that PM10 increase the deposition of allergens in the airways as
an allergen-carrier and increase the allergenicity as an adjuvant(Guarnieri and Balmes 2014).
NO2 had similar effects on AR. Exposure of higher level of ambient NO2 were found to be
related to higher incidence of respiratory disease in Asia, northern California, and Europe
(Levetin and Van de Water 2001; Liu et al. 2013; Teng et al. 2017). Time-series analysis in
Beijing, China during 2009-2010 found the positive relationship between the daily number of
outpatients for AR and daily concentration of the three air pollutants (Zhang et al. 2011). In vitro
studies on NO2 suggested it can result in acute inflammation in the upper and lower airways by
Childhood AR: Finding from CHS Study
62

triggering epithelial dysfunction and damage (Devalia et al. 1997). Experimental data from
animals showing there was enhanced pulmonary neutrophilic inflammation and the promotion of
a Th2/Th17 phenotype after nitrogen dioxide exposure(Martin et al. 2013). However, no
significant effect of TRAP on AR was observed in this study. There were no significant
interactions between NO2 or PM10 with all indoor environmental factors in our population as
well.
Despite the strengths of this study investigating different case definitions for AR and
examining the joint effects of indoor/outdoor environmental exposure, there were some
limitations for this study. First, prevalent AR was defined using parental responses to the ISAAC
questionnaire, which likely produced some outcome misclassification. However, this
misclassification is not likely to account for the associations as the case identification using this
questionnaire has been compared to the doctor diagnosis and validation by previous studies
(Braun-Fahrländer et al. 1997b; de Andrade et al. 2008). Secondly, to reduce exposure
misclassification, we restricted our analysis to children who lived in the same residence for their
entire life. History of exposure to outdoor environmental factors was collected from birth to
study entry. Lastly, although we included important covariates in our final multivariable models,
there is possibility of uncontrolled confounding by unmeasured confounders.

Childhood AR: Finding from CHS Study
63

3.5 Conclusion
We found that early childhood environmental exposures including pests, mildew/mold,
and high concentration of air pollutants PM10 and NO2 were determinants of AR occurrence
among preschoolers or kindergarteners.

Childhood AR: Finding from CHS Study
64

Chapter 4. Effects of Environmental
Factors and Family History of Allergic
Diseases on Development of Incident
Childhood Allergic Rhinitis

4.1 Introduction
Rhinitis is an inflammation of the upper airways characterized by runny and/or block nose
outside of flu/cold. Sinusitis (itchy/watery eyes) often co-exists with rhinitis and has been
considered as a more severe stage with the term ‘Rhinoconjunctivitis’. The definition and
classification of AR varies slightly with different guidelines including ARIA (World Health
Organization), American Academy of Asthma Allergy and Clinical Immunology Task Force,
and British Society of Allergy and Clinical Immunology (Bousquet et al. 2008; Scadding et al.
2008; Wallace et al. 2008). The most common definition used in epidemiological study have
used the validated ISAAC questionnaire, especially among children for whom endoscopic or CT
scan examination is difficult to perform or may do harm.
In chapter 3, we performed a cross-sectional study to investigate the impact of early life
environment on AR among CHS participants who were 6-7 years old at study entry. We found
that indoor environmental factors (mildew/mold, humidifier use, pests etc) play important roles
in the development of allergic rhinitis (AR) during early childhood. Positive associations
between prevalent AR and lifetime exposure level of ambient air pollutants such as PM10 and
Childhood AR: Finding from CHS Study
65

NO2 were also identified among children who have resided in the same house since birth
although no significant effect from TRAP on prevalent AR was shown in this population. In our
pilot cohort study presented in chapter 2, 67 children free of AR were followed up to 8 years. It
was shown that proximity to freeway was significantly associated with the risk of AR. With
children growing up, their time spending outdoor increased. Based on the above results, we
hypothesized that the indoor environment plays more important role of triggering AR from birth
to early childhood (such as kindergartener/first-grader) while outdoor environment might may be
more important among older children.
To examine our hypothesis, we pursued a cohort study among all CHS participants who
were AR-free at study entry (2002-2003) and followed them up to 10 years. The impacts of
environment on the risk of developing incident AR was assessed after adjustment for social-
demographic, and family history were evaluated in this study.

4.2 Methods
4.2.1 Study Population
Between 2002 and 2003, 5,364 kindergartener or first-graders from 13 communities in
Southern California were enrolled in the Children Health Study. With informed consent, parents
answered a questionnaire regarding children’s demographic, medical history, residential history
at study entry. If the parents provided confirmative answer to either question of “Has your child
ever had a problem with sneezing or a runny or blocked nose, when he/she did not have a cold or
the ‘flu’” or “Has this child ever have Hay fever” in the validated ISAAC questionnaire,
children were identified as prevalent AR (N=2,124). After excluding those with prevalent AR, all
Childhood AR: Finding from CHS Study
66

remaining children were followed for up to 10 years. Those who didn’t provided answers to “In
the past 12 months, has your child had a problem with sneezing or a runny or blocked nose when
he/she DID NOT have a cold or flu” in any of the following years were excluded (N=350),
which results in 2,892 eligible participants for this study (Figure 5).
4.2.2 Incident Allergic Rhinitis Identification and demographic information
collection
Using information provided by parents or children (starting from year 6) (Braun-
Fahrländer et al. 1997b; de Andrade et al. 2008) , we identified incident AR using the co-
existence of nasal and eyes symptoms (rhinoconjunctivitis). Specifically, individuals providing
affirmative answers to both questions- “Has your child ever had a problem with sneezing or a
runny or blocked nasal, when he/she DID NOT have a cold or the flu” and - “In the past 12
months, has this nasal problem been accompanied by itchy-watery eyes” were identified as
incident AR. For incident patients, the midpoint of the interval between the date of questionnaire
when AR was first reported and the date of previous questionnaire without report of rhinitis
symptoms was defined as the date of new-onset AR since the exact date of new-onset AR cannot
be accurately defined based on the annual questionnaires. Those didn’t report affirmative
answers to both questions were followed until loss to follow-up or study ended. In addition, a
sensitivity analysis was performed to examine if the ‘strict’ definition will lead to bias due to
misclassification. In the sensitivity analysis, children who only provided affirmative answer to
“Has your child ever had a problem with sneezing or a runny or blocked nasal, when he/she DID
NOT have a cold or the flu” but no eyes symptoms were defined as nasal allergy and censored at
the time when they first provided the affirmative answer. Children who didn’t provide
Childhood AR: Finding from CHS Study
67

affirmative answer to either question were defined as ‘No event’ and censored when they were
lost to follow up or study end. Nasal allergy was included in the model as competing risk.
Demographic characteristics, socioeconomic information, and family history of allergic
disease were collected in questionnaire at study entry. Children’s medical history especially
respiratory disease and allergic disease were collected at study entry and annually updated during
follow-up.
4.2.3 Indoor Environmental Factors
To investigate if exposure to indoor environment is associated with AR, multiple indoor
environmental factors were assessed from baseline questionnaire. Specifically, we collected
information on residential history including types of household heating system, fuel used to heat
the house, air conditioning use, carpeting in the home, humidifier or vaporizer use in children’s
room, lifetime history of indoor pet ownership (including cats, dogs, birds), exposure to pests
(including termites, spiders, ants, cockroaches, mice, rats) in the past 12 months, and lifetime
history of exposure to mold/mildew inside the house.
4.2.4 Ambient Air Pollutants
In this study, air pollutants were categorized as traffic-related air pollutants (TRAP) and
ambient air pollutants. Distance to nearby freeway or main road, and traffic-related NOx were
used as the indicators of TRAP exposure. Specifically, the standardized participants’ residential
address and locations were geocoded using the TeleAtlas database (Tele Atlas, Inc., Boston, CA,
www.na.teleatlas.com) and the distance of each residence to the nearest freeways or major roads
was estimated using ESRI ArcGIS Version 9.2 (ESRI, Redlands, CA, www.esri.com) as
Childhood AR: Finding from CHS Study
68

described previously. The definition of a freeway (with limited access) or other highway
(typically with heavy traffic volume), or a major or minor arterial thoroughfare was based on
functional classification by the California Department of Transportation(McConnell et al.
2006b). The concentrations of residential traffic-related NOx from freeway and non-freeways
sources were estimated using the CALINE4, a line source dispersion model, as described
previously (McConnell et al. 2010). Total NOx was the sum of freeway and non-freeway NOx.
Ambient air pollutants such as community levels of NO2, ozone (O3), particulate matter
with aerodynamic diameter <10 micrometer (PM10) and 2.5 micrometer (PM2.5), and O3 were
measured at ambient monitor station in each community (Berhane et al. 2014; Gauderman et al.
2007). The exposure to ambient air pollutants were assigned to individuals using the community
where they resided. To test the impact of air pollutants on incident AR, we performed survival
analysis using cox regression with the air pollutants measured at enrollment. Freeway NOx, non-
freeway NOx, and total NOx were estimated monthly and average individual exposure level for
the one year prior to enrollment.
4.2.5 Statistical Analysis
Descriptive statistics for selected characteristics were compared between children with and
without incident AR. Proportional COX regression model was fitted to investigate associations
between incident AR and demographic/socioeconomic factors, indoor environmental factors, and
outdoor air pollutants measured one year prior to enrollment. Spanish questionnaire were
included as covariates in all analysis. In the investigation for association between air pollutants
and AR, community where participants live was included in the model as a random effect. In all
single factor analysis testing effect of risk factors other than ambient outdoor air pollutants,
Childhood AR: Finding from CHS Study
69

community was included in the model as a cofounder. To examine potential bias from case
misclassification, sensitivity analysis was performed using nasal allergy as competing risk.
All hypotheses were tested two-sided at a 0.05 significance level. Statistical analyses were
conducted using SAS software 9.4 (SAS Institute, Cary, NC, USA).

4.3 Results
In this cohort, 2,892 children who were rhinitis free at study entry were followed with 779
(26.9%) participants developed AR within 10 years (Figure 5). Compared to children who did not
developed AR, those with incident AR were more likely to be female (55.7% vs. 49.5%), coming
from the family in which mother graduated from college or had higher degree (53.4% vs. 41.4%)
(Table 12). We found that 42.5% children with incident AR had one or both parents with history
of atopic disease including asthma.
To investigate risk factors from socio-demographic characteristics and indoor
environmental history for AR, we fitted single risk factor models to estimate the associations of
incident AR with community of residence and answers in Spanish questionnaire as covariates in
all models. During the follow-up years, the risk of developing incident AR was 23% higher in
females than male (HR: 1.23; 95% CI: 1.07-1.42). Several indoor environmental factors were
significantly associated with new onset AR. For example, children living in the house with musty
odor were 1.31 (95% CI: 1.09 - 1.56) more likely to have incident AR while carpet use in the
room was not related to risk of AR. In this study, exposure to pets such as dog and cat were not
Childhood AR: Finding from CHS Study
70

triggers of incident AR while history of exposure to household secondhand smoke increased the
risk (HR: 1.30; 95% CI: 1.00-1.69) (Table 12).
First graders/Kindergarteners were enrolled from 13 communities in
Southern California
N=5,364
Exclude children with
prevalent AR (N=2,124)
Eligible population in this study
N=2,892
Exclude children who didn’t
provide answer in following
questionnaire (N=350)
AR-free children at study entry
(N=3,240)
779 (26.9%) developed Allergic Rhinitis (Rhinoconjunctivitis)
during followup

Figure 5. Establishment of study population in longitudinal study on incident AR

We next investigated the effects of outdoor environmental factors including TRAP and
ambient air pollutants on risk of new onset AR. Average concentration of ambient air pollutants
in the year prior to enrollment was calculated. For the single factor analysis of ambient air
pollutants, community of residence was used as random effect and answers in Spanish
questionnaire was included in all models as a covariate. For the single factor analysis of TRAP,
Childhood AR: Finding from CHS Study
71

answers in Spanish questionnaire was included in all models as covariates and community of
residence was included as a random effect for analysis of ambient air pollutants. We found that
new onset AR was not significantly associated with air pollutants including ambient air
pollutants and TRAP (Table 13).
To investigate the independent roles of environment, the association between AR and
indoor/outdoor environmental factors with adjustment for age, sex, mothers’ education level,
family history of atopic diseases, and other potential risk factors identified in single factor
analysis. To decide which air pollutant should be included in multi-pollutant models, we checked
the correlation and found out PM2.5 is highly correlated with PM10 (ρ=0.78) and with NO2
(ρ=0.83) (Table 14). As shown in Table 15, Females had increased risk of incident AR than
males (HR: 1.22; 95% CI: 1.05-1.42). The risk of developing AR decreased with age increasing
(HR: 0.91; 95% CI: 0.83-1.00). The risk of developing new onset AR among children whose
parents had history of allergic diseases increased (HR: 1.42; 95% CI: 1.20-1.69). After
adjustment for demographic, socio-economic factors, most of the effects of indoor environment
factors on the risk of AR were no longer statistically significant. However, exposure of
secondhand smoke was related to 1.35 time (95% CI: 1.03-1.78) increased risk of developing
new onset AR. Residential air pollutant levels including NO2, O3 were not significantly
associated with increased risk for allergic rhinoconjunctivitis. TRAP, indicated by freeway NOx
or distance from freeway, wasn’t found to be an important risk factor after adjustment for sex,
age, PM10, and other factors.

Childhood AR: Finding from CHS Study
72

Table 12 Characteristics comparison by incident allergic rhinitis status and single-factor analysis
among cohort (N=2,892)
No Event Event
HR* (95% CI)
N=2,113 N=779
Female, N(%)

1,046 (49.5) 434 (55.7) 1.23 (1.07-1.42)
Race/Ethnicity, N(%)

White 632 (29.9) 227 (29.1) Reference
Hispanic White 1,265 (59.9) 454 (58.3) 1.27 (1.06-1.51)
Other 216 (4.7) 98 (12.6) 1.43 (1.13-1.82)
Mother's education level, N(%)

High school and lower 882 (41.7) 262 (33.6) Reference
Graduated from college or above 1150 (48.2) 498 (61.4) 1.20 (1.02-1.41)
Insurance, N(%) 1,678 (79.4) 643 (82.5) 0.99 (0.78- 1.24)
Premature, N(%) 173 (8.2) 62 (8.0) 0.93 (0.72-1.21)
Parent history of atopic disease, N(%) 658 (31.1) 331 (42.5) 1.45 (1.24-1.7)
In utero Exposure to Maternal Smoking, N(%) 116 (5.8) 55 (7.4) 1.24 (0.94-1.64)
Household ETS Exposure, N(%) 131 (6.2) 61 (7.8) 1.30 (1-1.69)
Mildew/Mold , N(%) 375 (17.8) 174 (22.3) 1.22 (1.03-1.45)
Humidifier use in child's room, N(%) 309 (14.6) 169 (21.7) 1.31 (1.09-1.56)
Musty odor at home, N(%) 60 (2.8) 30 (3.9) 1.45 (1.01-2.09)
Air conditioner use, N(%) 1,098 (52.0) 434 (55.7) 1.03 (0.88-1.2)
Carpet use in the house, N(%) 1,834 (86.8) 682 (87.6) 0.98 (0.75-1.29)
Pests in the previous 12 months, N(%) 1,176 (57.8) 479 (62.9) 1.14 (0.97-1.34)
Pets inside home, N(%) 1,020 (48.3) 410 (52.6) 1.08 (0.93-1.25)
Dog 560 (26.5) 215 (27.6) 1.00 (0.85-1.17)
Cat 343 (16.2) 147 (18.9) 1.04 (0.86-1.26)
*Adjustment for answers in Spanish and town.

Childhood AR: Finding from CHS Study
73

Table 13 Single-factor effect of air pollutants measured at baseline on incident allergic
rhinoconjunctivitis
Air pollutants* HR
#
95% CI p-value
NO2 0.99 (0.80 -1.24) 0.97
PM 2.5 0.90 (0.72-1.13) 0.37
PM10 0.85 (0.68-1.05) 0.13
O3 1.13 (0.91-1.40) 0.27
Freeway NOx 1.10 (0.93-1.29) 0.27
Non-freeway NOx 1.14 (0.93-1.4) 0.20
Total NOx 1.10 (0.94-1.39) 0.17
Distance to freeway (<300m vs. >=300m) 1.11 (0.90-1.37) 0.33
Distance to main road (<100m
vs. >=100m)
1.07 (0.91-1.26) 0.42
*Per 2SD unit increase expect stated otherwise. Specifically, per 16.98 ppb NO2 increase, per 11.8 ppb PM2.5
increase, per 25.38 ppb PM10 increase, per 18.56 ppb O 3 increase, or per 30 ppb freeway NOx increase, per 8ppb
non-freeway NOx increase, per 37 ppb total NOx increase.
# Adjustment for answer in Spanish. For analysis of NO2, PM2.5, PM10 and O3, town was included as a random
effect

Table 14 Correlation between air pollutants in the longitudinal study (N=2,892)
NO2 PM2.5 PM10 O3
Freew
ay
Nox
non-
Freeway
Nox
Total
Nox
NO2 1.00 0.83 0.52 -0.62 0.29 0.44 0.35
<.0001 <.0001 <.0001 0.001 <.0001 <.0001
PM2.5

1.00 0.78 -0.47 0.22 0.32 0.26

<.0001 <.0001 0.01 0.0002 0.0031
PM10 1.00 -0.36 0.07 0.20 0.11

<.0001 0.40 0.02 0.22
O3

1.00 -0.32 -0.46 -0.38

0.0002 <.0001 <.0001
Freeway Nox 1.00 0.45 0.98

<.0001 <.0001
non-Freeway Nox

1.00 0.61

<.0001

Childhood AR: Finding from CHS Study
74

Table 15 Multivariate Analysis on Risk of Allergic Rhinitis between Socio-Demographic,
Medical and Family History, Indoor and outdoor Environmental Risk Factors (N=2,892)
HR * (95% CI)
Age at baseline 0.91(0.83-1.00)
Female

1.22 (1.05-1.42)
Mother's education
High school or lower
College or above 1.21(1.00-1.45)
Parent history of atopic disease 1.42(1.20-1.69)
Household ETS Exposure 1.35(1.03-1.78)
Mildew/mold 1.17(0.97-1.40)
PM10

0.99(0.98-1.00)
Distance to freeway <500m 1.14(0.90-1.45)
*Adjusted for race/ethnicity, town, Spanish questionnaire, and all
the variables in the table

To avoid the bias from misclassification of incident AR, sensitivity analysis was performed
using different symptoms to define AR. Incident AR was still identified by confirmative answers
to both questions - “Has your child ever had a problem with sneezing or a runny or blocked nasal,
when he/she DID NOT have a cold or the flu” and - “In the past 12 months, has this nasal problem
been accompanied by itchy-watery eyes” (nasal and ocular symptoms). However, the competing
risk was identified when children had first shown nasal symptoms if they only provided
confirmative answers to “Has your child ever had a problem with sneezing or a runny or blocked
nasal, when he/she DID NOT have a cold or the flu” but not having symptoms of itchy-watery
eyes. Consistent with previous results, the effects of age, sex, race/ethnicity, family history of
atopic disease and environmental factors were very similar even though nasal-AR was treated as
the competing risk. (Table 16).
Childhood AR: Finding from CHS Study
75

To test if the impact of the risk factors differs by sex, we tested if the proportional assumption
was invalidated by sex but no obvious interaction between age and other exposure was found. In
addition, we also tested if these effects varied by history of parents’ allergic disease. No
proportional assumption was invalidated by the family history of allergic diseases as well.
Table 16 Competing risk analysis on incident allergic rhinoconjunctivitis (N=2.892)

Treat nasal-AR as censored
Treat nasal-AR as
competing risk
HR* (95% CI) HR* (95% CI)
Age at baseline 0.91(0.83-1.00) 0.93(0.84-1.03)
Female

1.22 (1.05-1,42) 1.25(1.06-1.48)
Mother's education
High school or lower
Reference Reference
College or above 1.21(1.00-1.45) 1.19 (0.96-1.47)
Parent history of atopic disease 1.42(1.20-1.69) 1.50(1.23-1.82)
Household ETS Exposure 1.35(1.03-1.78) 1.41(1.05-1.90)
Mildew/mold 1.17(0.97-1.40) 1.03 (0.84-1.26)
PM10

0.99(0.98-1.00) 0.99(0.99-1.00)
Distance to freeway <500m 1.14(0.90-1.45) 1.08(0.83-1.40)
*Adjusted for race/ethnicity, town, Spanish questionnaire, and all the variables in the table

4.4 Discussion
In this chapter, we performed a longitudinal study to assess the impact of environmental
factors on childhood AR. A loose definition was applied to determine prevalent AR to establish a
clean cohort. On the other hand, to increase specificity for identification of incident AR, a strict
definition in which requirement of co-existence of eyes and nasal symptoms was applied.
Childhood AR: Finding from CHS Study
76

It was found that exposure to secondhand smoke increased the risk of developing
new onset AR in children. The family history of allergic diseases remains as one of the
main risk factors for AR development.
Previous studies suggested that environmental exposure is one of the important
risk factors for AR. History of exposure to secondhand smoke, molds, and TRAP were
found to be potential risk factors for childhood AR (Dong et al. 2008; Johansson et al.
2008). In our previous report from the CHS study, increased risk of asthma was reported
among children living near a freeway (Gauderman et al. 2005). Significant deficits in
lung function growth rate were identified among children who lived in the area with high
levels air pollutants including NO2, PM2.5, and elemental carbon (Gauderman et al. 2002;
Islam et al. 2007). NOx, PM2.5, and O3 have been shown to be associated with the
development and exacerbation of respiratory disease, especially among children (Brauer
et al. 2002; Gauvin et al. 2002; Timonen et al. 2002; Zmirou et al. 2002). However, in
current study following children for up to 10 years, no significant effect of TRAP or
ambient air pollutants on the development of new onset AR was found. One of the
potential reasons is that air pollutants measured at enrollment was used. As a further
exploration, using updated air pollutants level to compare the effect from short-term or
long-term exposure is necessary. However, in the current available COX model, the
frailty function could not take care of residual confounding with community as a random
effect. We are working on to find more appropriate method to test the time-varying air
pollutants effect.

Childhood AR: Finding from CHS Study
77

Chapter 5. Fractional Exhaled Nitric
Oxide Predicts Risk of Childhood Allergic
Rhinitis

5.1 Introduction
Nitric oxide (NO), was known as an atmospheric pollutant, now has been recognized as an
important biological mediator in humans and animals. The fractional concentration of exhaled
nitric oxide (FeNO) was generated through the oxidation of the amino acid ʟ-arginine by three
distinct NO synthases (NOS) in several cell types, such as epithelial cells, airway nerves,
vascular endothelial cells and inflammatory cells (Dweik et al. 2011; Kim et al. 2016). In normal
condition, the epithelial cells of the bronchial wall produce minimal NO while the activated
epithelial cells during inflammation release higher-than-normal levels of NO (van den Toorn et
al. 2001). Evidences from a large number of studies showed the concentration of FeNO was
elevated in patients with airway inflammation such as asthma (Piacentini et al. 1999; Zeidler et
al. 2004) and the level is higher in atopic than non-atopic asthma (Cardinale et al. 2005; Leuppi
et al. 2002; Silvestri et al. 2001). These findings helps physicians to diagnose asthma from other
conditions with similar symptoms such as bronchitis, chronic obstructive pulmonary disease
(COPD) when other evidence is lacking (Dweik et al. 2011). Other finding showed the level of
elevated FeNO decreased after corticosteroid treatment. Repeated measurement of FeNO is
Childhood AR: Finding from CHS Study
78

found to be a useful guide for the adjustment of ICSs treatment in asthma children (Hirano et al.
2013).
As a noninvasive marker, measurement of FeNO is considered to be more reliable than
traditional method in asthma assessment. Most of conventional evaluation methods are either
only indirectly associated with airway inflammation(Smith et al. 2004), or effort dependent and
lack sensitivity(Smith et al. 20). Since 2011, the FeNO measurement has been strongly
recommended to aid in the assessment and long-term monitoring of asthma by the American
Thoracic Society (ATS) (Dweik et al. 2011). A standard breath test has been developed to
measure FeNO (1999) and an official Clinical Practice Guideline is developed to guide
interpretation of FeNO (Society and Society 2005) measurement in clinical practice. Therefore,
FeNO has been widely applied in clinical practice for assessment of airway inflammatory status
in respiratory diseases.
As one of common chronic upper airway diseases among children, allergic rhinitis becomes
a burden to the patients and the society. It is important to successfully prevent and diagnose AR
in early childhood. Previous studies suggested that NO may act as a proinflammatory mediator
predisposing to the development of airway hyperresponsiveness (AHR). Levels of FeNO have
been found to be related to rhinologic disease. Low nasal NO is found in patients with primary
ciliary dyskinesia or patients with nasal ployps, chronic rhinosinusitis and cystic. Elevated nNO
was detected among patients with allergic rhinitis because the inducible NOS( iNOS) production
increases (Lee et al. 2012; Scadding 2007). More studies had supported that FeNO could be a
potential biomarker in allergic rhinitis since the AR adults frequently had high FeNO
values(Ciprandi et al. 2017). There were evidences showing that high levels of FeNO among
Childhood AR: Finding from CHS Study
79

allergic rhinitis children had related to higher incident asthma(Di Cara et al. 2015). However,
there was few study performed among children to assess the function of FeNO in the prediction
or treatment for allergic rhinitis.
In this study, using a subset of participants in Children’s Health Studies in Southern
California (CHS), we performed a longitudinal cohort among children without prevalent AR to
investigate if the FeNO can be potentially used as a predictor for childhood allergic rhinitis.

5.2 Method
5.2.1 Study Population
Children's Health Study is a large population-based longitudinal study in which 5,264
kindergarteners or first graders (5–7 years old) were recruited from 13 communities in southern
California and followed for up to 10 years (Bastain et al. 2011; Berhane et al. 2011). The
protocol was reviewed and approved by the University of Southern California Institutional
Review Board. Informed consents were obtained from all children and their parents. At
enrollment and each of following year, parents or children provided answers to a questionnaire
regarding children’s demographic, medial history, residential history, and family history of
allergic diseases. Among those participants, online FeNO tests were performed on 2,665 children
at 49 schools between October 2006 and June 2007. Using the validated ISAAC questionnaire,
the prevalent AR were identified if the parents provided confirmative answer to either question
of “Has your child ever had a problem with sneezing or a runny or blocked nose, when he/she
did not have a cold or the ‘flu’” or “Has this child ever have Hay fever” before the children
Childhood AR: Finding from CHS Study
80

receiving FeNO tests and excluded (N=1,597). Those who didn’t provide answers to ISAAC
questionnaire in any of the following years were further excluded (N=447). Therefore, 621
children who were AR-free at the measurement of FeNO were included in the final study and
followed for up to 6 years.
5.2.2 FeNO Measurement
Online FeNO measurement was performed as described (Linn et al. 2009a; Linn et al.
2009b). Briefly, according to the manufacturer's instructions and recommendations from
professional societies(Baraldi et al. 1998; Slutsky et al. 1999; Society and Society 2005), the
FeNO were measured at 50 ml/s expiratory flow using EcoMedics CLD-88-SP analyzers, with
DeNOx accessories to provide NO-free inhaled air (EcoPhysics Inc., Ann Arbor, MI,
USA/Duernten, Switzerland). A sampling rate of ~330 ml/min was set before each test. During
each online test maneuver, the subjects took two or more preliminary tidal breaths and a nearly
maximal inspiration from the DeNOx unit, then exhaled near 50 ml/s against the sampling head's
fixed resistance with controlling flow while observing a color-coded analog display on a
computer screen. Five maneuvers were recorded per subject. FeNO was represented by the mean
of three acceptable plateau means with concentrations agreeing within 10%, or two within 5%. If
the median FeNO of all ATS acceptable maneuvers was under 10 ppb., two maneuvers within
10% were accepted.
Childhood AR: Finding from CHS Study
81

5.2.3 Incident Allergic Rhinitis Identification and demographic information
collection
From information provided children (Braun-Fahrländer et al. 1997b; de Andrade et al.
2008), incident AR was identified using the co-existence of nasal and eyes symptoms at same
year (rhinoconjunctivitis). Specifically, children providing affirmative answers to both questions
-“Has your child ever had a problem with sneezing or a runny or blocked nasal, when he/she
DID NOT have a cold or the flu” and -“In the past 12 months, has this nasal problem been
accompanied by itchy-watery eyes” were identified as incident AR. The midpoint of the interval
between the date of questionnaire when AR was first reported and the date of previous
questionnaire without report of rhinitis symptoms was defined as the date of new-onset AR for
incident patients. Those who didn’t develop new-onset AR were followed until loss to follow-up
or study ended.
Demographic including age, gender, race/ethnicity, and socio-economic information such
as parental education, annual household income and availability of health insurance for the child,
medical history such as premature, and history of exposure to cigarette smoking during maternal
and postnatal period were collected in questionnaire at study entry. Children’s medical history
especially respiratory diseases and allergic diseases were collected at study entry and annually
updated during follow-up.
5.2.4 Statistical Analysis
Selected characteristics were compared between children with and without developing
new onset AR. Two proportional COX models were fitted to investigate associations between
Childhood AR: Finding from CHS Study
82

FeNO and incident AR. One was using the FeNO and all cofounders collected at baseline. In
time-varying COX model, annually updated FeNO levels and other cofounders (if they were
available in the annual updated data) were assessed. Age at questionnaire answering date, sex,
race/ethnicity, and Spanish questionnaire were included in all analysis. Other
demographic/socioeconomic factors, family history of allergic diseases, personal medial history
were tested as confounders. The factors which altered the magnitude of the associations between
incident AR and FeNO more than 10% were considered as confounders to be adjusted in the
final model. To find a best cut point of FeNO levels for predicting risk of new onset AR, the
‘findcut’ macro (http://www.mayo.edu/research/documents/findcutsas/doc-20119587) was
applied.
All hypotheses were tested two-sided at a 0.05 significance level. Statistical analyses
were conducted using SAS software 9.4 (SAS Institute, Cary, NC, USA).

5.3 Results
Among 621 AR-free children, 129 (20.8%) developed new onset AR during up to 6 years
follow-up (Figure 6). Comparing to those who didn’t developed incident AR, children who
developed AR had higher prevalence of wheeze (13.6% vs. 7.8%), asthma (5.9% vs. 2.9%) and
higher eNO levels (15.5 ± 14.4 ppb vs. 12.5 ± 11.3 ppb) at baseline (Table 17). It was also found
that the percent of obesity was 33.8% among children with incident AR while was 22.0% among
children who didn’t have event.

Childhood AR: Finding from CHS Study
83

Figure 6 Establishment of cohort study among children with FeNO measurement

Childhood AR: Finding from CHS Study
84

Table 17 Demographic and clinical characteristics comparison between children who developed
incident allergic rhinitis and didn’t have the symptoms during follow-up (N=621)

Children who
didn’t developed
new onset AR
Children who
developed new onset
AR during follow-up
N=492 N=129
Age at baseline, mean years ± SD 10.30 ± 0.65 10.24 ± 0.62
Male, N(%)

230 (46.75) 53 (41.09)
Mother's education, N(%)

High school or lower 177 (35.98) 49 (37.99)
Graduated from college or above 234 (47.56) 66 (51.16)
Unknown 81 (16.46) 14 (10.85)
Parent history of allergic diseases, N(%) 142 (32.2) 39 (34.82)
Income, N(%)

<50,000 189 (38.21) 64 (49.61)
>=50,000 211 (42.89) 48 (37.21)
Unknown 93 (18.9) 17 (13.18)
Insurance, N(%)

407 (89.45) 106 (86.89)
Eczema at baseline, N(%) 37 (8.39) 10 (8.4)
History of Asthma, N(%) 13 (2.87) 7 (5.93)
Exposure to secondhand smoke, N(%) 16 (3.52) 3 (2.52)
Wheeze at baseline (year 5), N(%) 34 (7.76) 16 (13.56)
Weight status, N(%)

Normal 305 (61.99) 69 (53.49)
Overweight 79 (16.06) 19 (14.73)
Obese 108 (21.95) 41 (31.78)
eNO at baseline, mean ppb ± SD 12.46 ± 11.33 15.51 ± 14.41
eNO at baseline, median ppb (q1-q3) 9.03 (6.67 - 13.44) 9.67 (7.31 - 17.54)

Childhood AR: Finding from CHS Study
85

To investigate if level of FeNO among children could be used for the early predictor of
allergic rhinitis, we followed these children with no prevalent AR for up to 6 years. Using the
FeNO measured at baseline, it was found that the risk ratio of developing incident AR was 16%
higher (HR: 1.16; 95% CI: 1.02-1.33) if their FeNO were 12 ppb after adjustment for sex,
race/ethnicity, community where children was residing and the indicator of answers in Spanish
(Table 18). To test if there was significant quantile effect for FeNO levels, the population were
categorized into 4 groups based on their FeNO levels measured at enrollment. Comparing to
children with low FeNO level (<6.85 ppb), those with higher FeNO levels (>=14.23 ppb) had
2.50 times (95% CI: 1.35-4.65) higher chance to have incident AR after adjustment for the
cofounders including weight status and family history of allergic diseases (Table 19).
Table 18 Hazard ratio of incident rhinoconjunctivitis with levels of FeNO measured at baseline
95% CI
HR* Lower CI Upper CI
FeNO per increasing one SD (12 ppb) 1.16 1.02 1.33
*Adjusted for sex, race/ethnicity, town and Spanish questionnaire

Table 19 Hazard ratio of incident rhinoconjunctivitis with increasing baseline FeNO level
HR* (95% CI)
FeNO quantile

1st (2.49-6.85) 1
2nd (6.86-9.13) 1.59 (0.83-3.04)
3rd (9.14-14.22) 1.52 (0.79-2.94)
4th (14.23-) 2.50 (1.35-4.65)
Age

0.79 (0.57-1.09)
Parental history of atopic diseases 1.11 (0.65-1.91)
Weight status

Normal

1
Overweight

1.48 (0.85 - 2.56)
Obese

1.65 (1.01-2.72)
History of wheeze 1.95 (1.09-3.50)
* Adjusted for gender, race/ethnicity, town and span-bq
Childhood AR: Finding from CHS Study
86

To account for the FeNO change in up to 6 years, time-varying cox model was performed
using the levels of FeNO measured during follow-up. After applying the cofounder identification
criteria, age, history of family allergic disease, BMI status, and history of wheeze or asthma were
determined as potential cofounders for association between FeNO and incident AR and were
adjusted in the final model. As shown in Table 20, it was found that the risk of developing new
onset AR increased 1.19 times (95% CI: 1.08 - 1.32) among children whose measured FeNO
were 12 ppb higher. Consistent with other studies, the risk of new onset AR decreased to 0.59
(95% CI: 0.50-0.71) with every 1 year increasing of age. Family history of allergic diseases was
positively related to the risk of AR but not significantly. Interestingly, obese children had higher
risk of developing new onset AR than children with normal weight (HR: 1.73; 95% CI: 1.20-
2.49). Wheeze was believed as one of the early symptoms in ‘Allergic March’, the history of
wheeze in children was found to be positively related to the new incident AR in our population.
Children with history of wheeze in childhood had 2.43 times higher risk of incident AR (95% CI:
1.60-3.68).
Table 20 Hazard ratio of incident rhinoconjunctivitis with increasing FeNO using time-varying
measurement
HR* (95% CI)
FeNO per increasing one SD (12 ppb) 1.19 (1.08 - 1.32)
Age

0.59 (0.50 - 0.71)
History of parents’ allergic disease 1.25 (0.88-1.77)
Weight status

Normal Reference
Overweight 1.33 (0.85-2.07)
Obese 1.73 (1.20- 2.49)
History of wheeze 2.43 (1.60 - 3.68)
* Adjusted for gender, race/ethnicity, town and span-bq

Childhood AR: Finding from CHS Study
87

We also assessed the potential cut points of FeNO level to predict the risk of incident AR
using the macro modified in Mayo Clinic. A plot with maximum hazard ratio/minimum p-value
showed that the 20~25 ppb of FeNO could be the potential cut-point. We chose the 20 ppb as the
point to categorize population to two groups (Figure 7). Comparing to children whose FeNO
were less than 20 ppb at enrollment, children who had higher FeNO were 2.06 times (95% CI:
1.26-3.37) more likely to have new incident AR in next 6 years. Similar results were obtained
from the model using updated FeNO levels (Table 21). There were no significant interactions
between FeNO and asthma (p=0.89), parental history of allergic disease (p=0.67), wheeze
(p=0.82), weight status (p=0.67). To test if the association between FeNO and AR differs by the
status of asthma, interactions between NO2 and physician diagnosed-asthma or history of wheeze
and the stratification analysis were checked. There we no significant interactions.

Figure 7 Cut-point plot of FeNO for predicting risk of incident AR
Childhood AR: Finding from CHS Study
88

Table 21 HR of incident allergic rhinitis by FeNO level
Baseline Value only Time varying model
95% CI 95% CI
HR* Lower CI Upper CI HR* Lower CI Upper CI
FeNO<=20 ppb Reference Reference
FeNO> 20 ppb 2.06 1.26 3.37 2.01 1.40 2.88
* Adjusted for age, sex, race/ethnicity, town, answers in Spanish, family history of allergic
disease, person history of wheeze, and weight status.

5.4 Discussion
In this study, we identified that higher levels of FeNO measured among children aged 10
years were highly correlated with higher risk of developing new onset AR in their puberty.
Consistent results from using levels of baseline or updated FeNO suggested that FeNO could be
potentially used as a predictor for incident AR in childhood. A cut-off of FeNO >20ppb was
suggested to discriminate AR from non-AR children.
Many studies have found the levels of FeNO are related to upper and lower airway disease
and suggested that FeNO can be used as a surrogate biomarker for the Th2-dependent
inflammation. Besides the well-known positive correlation between FeNO and asthma, more
recent studies have found similar relationship between FeNO and allergic rhinitis. Mean FeNO
among children with allergic rhinitis was found to be significant higher than those without
AR(Chawes 2011; Yoon et al. 2017). A prospective cohort study followed 959 adolescents (13-
14 years) for 4 years found that higher FeNO levels at baseline were associated with increased
risk for new-onset and persistent rhinitis(Kovesi et al. 2008).A 2-year cohort study among adults
Childhood AR: Finding from CHS Study
89

identified that patients with a high FeNO had a significantly longer AR duration, impaired lung
function, and more severe symptoms(Ciprandi et al. 2017). Takeno et al. demonstrated
significantly higher oral and nasal FeNO levels in patients with AR compared to controls
(Takeno et al. 2012).
Because of the advantages such as noninvasive nature, ease of repeat measurement and
relatively easy performance, it brought lots of interests in the application of FeNO in the clinical
setting. The American Thoracic Society has approved a standard clinical practice guideline for
interpretation the function of exhaled nitric oxide levels in clinical practice(Society and Society
2005). It was recommended the use of FeNO in asthma, particularly for diagnosis and
monitoring of eosinophilic airway inflammation should account for age and allergen exposure
as factors.
To distinguish asthmatics from nonasthmatics, many groups investigated an optimal
cutoff point for clinical diagnostic decision, usually by calculation of receiving operator
characteristic (ROC) curves with a wide range of sensitivities and specificities. Based on
published materials, the ATS guidelines recommend that cutoff points of FeNO levels at <20 ppb
indicate a decreased likeliness of eosinophilic inflammation and can increase accuracy in the
diagnosis of childhood asthma(Smith et al. 2004). Although there are extensive evidences
suggesting the use of FeNO in diagnosis, treatment control, and early prediction of asthma,
limited studies were available for AR. A cross-sectional and longitudinal study among school
children in southern California showed a significantly larger associations between active rhinitis
and FeNO among children with high FeNO concentrations than those with low concentrations(de
Bot et al. 2013). In our study, it was clearly suggested that children with high FeNO at baseline
Childhood AR: Finding from CHS Study
90

or during follow-up had higher risk of new onset allergic rhinitis within 6 years. The suggested
cut-off points for discriminating AR and non-AR is close to the recommendations used for
asthma and non-asthma differentiation (20 ppb).
In spite of the significance of using FeNO in predicting childhood allergic rhinitis, there
were some limitations related to the technology and standardization difficulty during
measurement. We used chemiluminescence instrument/technology to measure FeNO, and as
with any measurement there is potential for measurement error. However, this instrument has
great detection limits and the measurement error is likely to be minimal and classical in nature.
So we don’t expect a large influence or bias on our results.

5.5 Conclusion
In summary, our study has provided strong evidence supporting the potential use of
FeNO in predicting childhood allergic rhinitis.
Childhood AR: Finding from CHS Study
91

Chapter 6 Discussion and Conclusion

Allergic rhinitis, as a common pediatric disease, impairs the quality of life of patients and
imposes significant economic burden on society. Compared to adults, the prevalence of AR is
higher among children. Children with AR may experience sleep disturbance, fatigue, depression
or cognitive function damage (Meltzer 2001; Varshney and Varshney 2015). To understand the
mechanism or identify the potential risk factors of AR in early childhood is critical for the
prevention and treatment management of this disease. However, there were limited studies
among the population aged 6-14 years. In this dissertation, we performed four studies on AR
among children aged 6~7 years and followed some of them for up to 10 years to investigate the
possible risk factors, or for potential early predictors of AR among children aged 10~11 years.
Firstly, we have assessed the effect of air pollutants, including ambient and TRAP, on the
risk of AR among children with allergic sensitization in a cohort. It was found that there was
potential synergic effect from allergic sensitization and TRAP indicated by proximity to freeway
on the risk of new onset AR. The risk of developing AR among children with any allergic
sensitization and living within 500 m from freeway was 7.64 (95% CI: 2.55 - 22.87) times higher
than those without sensitization to common allergens and living farther. In the second study, we
performed a cross-sectional study to investigate the influence of early childhood environment on
prevalence of AR among 1,611 kindergartener and first-graders who had resided in the same
house since birth. To control for potential misclassification of AR, two types of AR—nasal
allergy and rhinoconjunctivitis were defined using the ISAAC questionnaire. Results showed that
Childhood AR: Finding from CHS Study
92

besides the family history of allergic diseases, several indoor and outdoor environmental factors,
such as the use of a humidifier or vaporizer in the room, household mildew, NO2 and PM10, were
related to higher odds of AR in childhood. In the following prospective cohort, 2,892 children
who were AR-free at enrollment were followed for up to 10 years for new onset
rhinoconjunctivitis. Although the effect of air pollutants using baseline measurement was not
shown significant relationship with development of new onset AR, exposure to secondhand
smoke was found to be positively related to the risk of AR. Lastly, in an effort to identify an
early predictor of childhood AR, we tested the role of FeNO among 621 children who were AR-
free when FeNO was measured. Using the levels of FeNO measured at enrollment or updated
measurement during follow-up, it was found that children with higher level of FeNO were more
likely to develop incident rhinoconjunctivitis. This finding suggested that FeNO could be used as
early predictor for childhood AR. Further analysis showed that 20ppb of FeNO could be
potentially used as a cut-off point for identification of AR from non-AR, which was similar to
the recommended cut-off point for differentiation asthmatic and asthmatic children.
Through those studies, we explored the impact of environment, including early childhood
or puberty environment, on development of AR. We identified some modifiable risk factors
such as humidifier or vaporize use in the room, water damage and mildew in the house, as well
as some non-modifiable factors including TRAP and ambient air pollutants. The children with
family history of allergic diseases, or personal history of allergic sensitization are more
susceptible to those risk factors. The measurement of FeNO at early childhood can potentially
help prevention of AR if children can reduce the exposure to allergens and living in an area with
lower levels of air pollutants.
Childhood AR: Finding from CHS Study
93

In this dissertation, we have included a cross-sectional study among close to 3,000 children
and three prospective cohort studies to follow AR-free children with SPT test, or with FeNO
measurement, or general population. Odds ratio of prevalent and hazard ratio of incident AR
were assessed. Consistent results were found in these studies showing that air pollutants were
significantly related to AR. There were also some inconsistent findings such as indoor
environmental factors played an important role in prevalent AR among children aged between 5-
7 years, but not in the relationship with new incident AR among older children. These findings
provided a thorough evaluation of childhood AR.
On the other hand, there are some limitations in these studies. First, the identification of
AR was based on the questionnaire answered by parents and children (after year 6). Due to the
funding restriction, it is hard to perform skin- testing or allergen-specific IgE test or serum IgE
test for diagnosis of AR in an epidemiologic study involving a large number of subjects. Using
validated ISAAC questionnaire, we identified allergic rhinitis by two categories- nasal allergy or
rhinoconjunctivitis. There was potential misclassification since it is hard to differentiate runny
nose from cold/flu or non from cold/flu. By requiring eyes symptoms, the possibility of
misclassification might be reduced. Secondly, we only collected information on indoor
environment at baseline. There is a possibility that exposure to environment changed during
follow-up. However, our hypothesis focused on exposure during early childhood, or long-term
exposure, so the impact from lack of updated information was minimal. Thirdly, there were only
community levels of ambient air pollutants instead of personal level. The other limitation
included the small sample size in the cohort study among those with SPT test, and the one among
those with FeNO measurement. The synergic effect of allergic sensitization and air pollutants
should be tested among larger population if allowed. The accuracy of using FeNO to predict AR
Childhood AR: Finding from CHS Study
94

should be confirmed from larger population as well. There were some limitations from the nature
of the Epidemiology study using questionnaire as the information source, especially given that
the targeted population is children. Potential information bias from recall and misclassification
exist. However, all these bias was non-differentiate between the children identified with or
without AR, which would not result in our estimates more significant.
In this dissertation, we performed thorough studies on childhood AR and confirmed that
environmental exposure significantly impacts the risk of childhood allergic rhinitis, especially
among those with a family history of allergy. The findings should provide the clinicians, parents
or care-givers insights on preventing the development of AR. The findings can also provide
preliminary data for the future studies. Based on the current results, it suggested that further
studies in a larger cohort would be necessary to investigate the interactions between sensitization
to specific allergen and exposure to air pollutants on the risk for AR, and compare the effect of
sensitization to one allergen vs to more than 2 allergens which may suggest the threshold of
tolerance.

Childhood AR: Finding from CHS Study
95

Reference
Adams PF, Kirzinger WK, Martinez M. 2013. Summary health statistics for the u.S. Population:
National health interview survey, 2012. Vital Health Stat 10:1-95.
Ahmadi-Abhari S, Kaptoge S, Luben RN, Wareham NJ, Khaw KT. 2014. Longitudinal
association of c-reactive protein and lung function over 13 years: The epic-norfolk study. Am J
Epidemiol 179:48-56.
Albano GD, Di Sano C, Bonanno A, Riccobono L, Gagliardo R, Chanez P, et al. 2013. Th17
immunity in children with allergic asthma and rhinitis: A pharmacological approach. PLoS One
8:e58892.
Alm B, Goksör E, Thengilsdottir H, Pettersson R, Möllborg P, Norvenius G, et al. 2011. Early
protective and risk factors for allergic rhinitis at age 4½ yr. Pediatr Allergy Immunol 22:398-
404.
Andiappan AK, Wang dY, Anantharaman R, Parate PN, Suri BK, Low HQ, et al. 2011.
Genome-wide association study for atopy and allergic rhinitis in a singapore chinese population.
PLoS One 6:e19719.
Annesi-Maesano I, Moreau D, Caillaud D, Lavaud F, Le Moullec Y, Taytard A, et al. 2007.
Residential proximity fine particles related to allergic sensitisation and asthma in primary school
children. Respir Med 101:1721-1729.
Asher MI, Keil U, Anderson HR, Beasley R, Crane J, Martinez F, et al. 1995. International study
of asthma and allergies in childhood (isaac): Rationale and methods. Eur Respir J 8:483-491.
Asher MI, Montefort S, Björkstén B, Lai CK, Strachan DP, Weiland SK, et al. 2006. Worldwide
time trends in the prevalence of symptoms of asthma, allergic rhinoconjunctivitis, and eczema in
childhood: Isaac phases one and three repeat multicountry cross-sectional surveys. Lancet
368:733-743.
Atkinson RW, Strachan DP, Anderson HR, Hajat S, Emberlin J. 2006. Temporal associations
between daily counts of fungal spores and asthma exacerbations. Occup Environ Med 63:580-
590.
Bachert C, Vignola AM, Gevaert P, Leynaert B, Van Cauwenberge P, Bousquet J. 2004. Allergic
rhinitis, rhinosinusitis, and asthma: One airway disease. Immunol Allergy Clin North Am 24:19-
43.
Baiardini I, Braido F, Brandi S, Canonica GW. 2006. Allergic diseases and their impact on
quality of life. Ann Allergy Asthma Immunol 97:419-428; quiz 429-430, 476.
Childhood AR: Finding from CHS Study
96

Baldo BA, Baker RS. 1988. Inhalant allergies to fungi: Reactions to bakers' yeast
(saccharomyces cerevisiae) and identification of bakers' yeast enolase as an important allergen.
Int Arch Allergy Appl Immunol 86:201-208.
Baraldi E, Azzolin NM, Carrà S, Dario C, Marchesini L, Zacchello F. 1998. Effect of topical
steroids on nasal nitric oxide production in children with perennial allergic rhinitis: A pilot study.
Respir Med 92:558-561.
Barker DJ, Osmond C. 1986. Infant mortality, childhood nutrition, and ischaemic heart disease in
england and wales. Lancet 1:1077-1081.
Barker DJ. 1998. In utero programming of chronic disease. Clin Sci (Lond) 95:115-128.
Bastain TM, Islam T, Berhane KT, McConnell RS, Rappaport EB, Salam MT, et al. 2011.
Exhaled nitric oxide, susceptibility and new-onset asthma in the children's health study. Eur
Respir J 37:523-531.
Beggs PJ, Bambrick HJ. 2005. Is the global rise of asthma an early impact of anthropogenic
climate change? Environ Health Perspect 113:915-919.
Beischlag TV, Luis Morales J, Hollingshead BD, Perdew GH. 2008. The aryl hydrocarbon
receptor complex and the control of gene expression. Crit Rev Eukaryot Gene Expr 18:207-250.
Berger WE. 2004. Allergic rhinitis in children : Diagnosis and management strategies. Paediatr
Drugs 6:233-250.
Berhane K, Zhang Y, Linn WS, Rappaport EB, Bastain TM, Salam MT, et al. 2011. The effect
of ambient air pollution on exhaled nitric oxide in the children's health study. Eur Respir J
37:1029-1036.
Berhane K, Zhang Y, Salam MT, Eckel SP, Linn WS, Rappaport EB, et al. 2014. Longitudinal
effects of air pollution on exhaled nitric oxide: The children's health study. Occup Environ Med
71:507-513.
Bernstein IL, Li JT, Bernstein DI, Hamilton R, Spector SL, Tan R, et al. 2008. Allergy
diagnostic testing: An updated practice parameter. Ann Allergy Asthma Immunol 100:S1-148.
Björkstén B, Clayton T, Ellwood P, Stewart A, Strachan D, Group IPIS. 2008. Worldwide time
trends for symptoms of rhinitis and conjunctivitis: Phase iii of the international study of asthma
and allergies in childhood. Pediatr Allergy Immunol 19:110-124.
Blackwell DL, Vickerie JL, Wondimu EA. 2003. Summary health statistics for u.S. Children:
National health interview survey, 2000. Vital Health Stat 10:1-48.
Bloom B, Cohen RA, Freeman G. 2011. Summary health statistics for u.S. Children: National
health interview survey, 2010. Vital Health Stat 10:1-80.
Childhood AR: Finding from CHS Study
97

Bloom B, Jones LI, Freeman G. 2013. Summary health statistics for u.S. Children: National
health interview survey, 2012. Vital Health Stat 10:1-81.
Borges WG, Burns DA, Felizola ML, Oliveira BA, Hamu CS, Freitas VC. 2006. Prevalence of
allergic rhinitis among adolescents from distrito federal, brazil: Comparison between isaac
phases i and iii. J Pediatr (Rio J) 82:137-143.
Bousquet J, Van Cauwenberge P, Khaltaev N, Group AW, Organization WH. 2001. Allergic
rhinitis and its impact on asthma. J Allergy Clin Immunol 108:S147-334.
Bousquet J, Annesi-Maesano I, Carat F, Léger D, Rugina M, Pribil C, et al. 2005a.
Characteristics of intermittent and persistent allergic rhinitis: Dreams study group. Clin Exp
Allergy 35:728-732.
Bousquet J, Gaugris S, Kocevar VS, Zhang Q, Yin DD, Polos PG, et al. 2005b. Increased risk of
asthma attacks and emergency visits among asthma patients with allergic rhinitis: A subgroup
analysis of the investigation of montelukast as a partner agent for complementary therapy
[corrected]. Clin Exp Allergy 35:723-727.
Bousquet J, Khaltaev N, Cruz AA, Denburg J, Fokkens WJ, Togias A, et al. 2008. Allergic
rhinitis and its impact on asthma (aria) 2008 update (in collaboration with the world health
organization, ga(2)len and allergen). Allergy 63 Suppl 86:8-160.
Brauer M, Hoek G, Van Vliet P, Meliefste K, Fischer PH, Wijga A, et al. 2002. Air pollution
from traffic and the development of respiratory infections and asthmatic and allergic symptoms
in children. Am J Respir Crit Care Med 166:1092-1098.
Braun-Fahrländer C, Vuille JC, Sennhauser FH, Neu U, Künzle T, Grize L, et al. 1997a.
Respiratory health and long-term exposure to air pollutants in swiss schoolchildren. Scarpol
team. Swiss study on childhood allergy and respiratory symptoms with respect to air pollution,
climate and pollen. Am J Respir Crit Care Med 155:1042-1049.
Braun-Fahrländer C, Wüthrich B, Gassner M, Grize L, Sennhauser FH, Varonier HS, et al.
1997b. Validation of a rhinitis symptom questionnaire (isaac core questions) in a population of
swiss school children visiting the school health services. Scarpol-team. Swiss study on childhood
allergy and respiratory symptom with respect to air pollution and climate. International study of
asthma and allergies in childhood. Pediatr Allergy Immunol 8:75-82.
Breton CV, Salam MT, Vora H, Gauderman WJ, Gilliland FD. 2011. Genetic variation in the
glutathione synthesis pathway, air pollution, and children's lung function growth. Am J Respir
Crit Care Med 183:243-248.
Breton CV, Siegmund KD, Joubert BR, Wang X, Qui W, Carey V, et al. 2014. Prenatal tobacco
smoke exposure is associated with childhood dna cpg methylation. PLoS One 9:e99716.
Buckeridge DL, Glazier R, Harvey BJ, Escobar M, Amrhein C, Frank J. 2002. Effect of motor
vehicle emissions on respiratory health in an urban area. Environ Health Perspect 110:293-300.
Childhood AR: Finding from CHS Study
98

Burney PG, Luczynska C, Chinn S, Jarvis D. 1994. The european community respiratory health
survey. Eur Respir J 7:954-960.
Bush RK, Portnoy JM, Saxon A, Terr AI, Wood RA. 2006. The medical effects of mold
exposure. J Allergy Clin Immunol 117:326-333.
Butland BK, Strachan DP, Lewis S, Bynner J, Butler N, Britton J. 1997. Investigation into the
increase in hay fever and eczema at age 16 observed between the 1958 and 1970 british birth
cohorts. BMJ 315:717-721.
Caffarelli C, Savini E, Giordano S, Gianlupi G, Cavagni G. 1998. Atopy in children with otitis
media with effusion. Clin Exp Allergy 28:591-596.
Cardinale F, de Benedictis FM, Muggeo V, Giordano P, Loffredo MS, Iacoviello G, et al. 2005.
Exhaled nitric oxide, total serum ige and allergic sensitization in childhood asthma and allergic
rhinitis. Pediatr Allergy Immunol 16:236-242.
Charpin D, Sibbald B, Weeke E, Wüthrich B. 1996. Epidemiologic identification of allergic
rhinitis. Allergy 51:293-298.
Chawes BL. 2011. Upper and lower airway pathology in young children with allergic- and non-
allergic rhinitis. Dan Med Bull 58:B4278.
Chehregani A, Majde A, Moin M, Gholami M, Ali Shariatzadeh M, Nassiri H. 2004. Increasing
allergy potency of zinnia pollen grains in polluted areas. Ecotoxicol Environ Saf 58:267-272.
Chen ZH, Salam MT, Eckel SP, Breton CV, Gilliland FD. 2015. Chronic effects of air pollution
on respiratory health in southern california children: Findings from the southern california
children's health study. Journal of Thoracic Disease 7:46-+.
Cingi C, Cakli H, Us T, Akgün Y, Kezban M, Ozudogru E, et al. 2005. The prevalence of
allergic rhinitis in urban and rural areas of eskişehir-turkey. Allergol Immunopathol (Madr)
33:151-156.
Ciprandi G, Gallo F, Ricciardolo FL, Cirillo I. 2017. Fractional exhaled nitric oxide: A potential
biomarker in allergic rhinitis? Int Arch Allergy Immunol 172:99-105.
Codispoti CD, Bernstein DI, Levin L, Reponen T, Ryan PH, Biagini Myers JM, et al. 2015.
Early-life mold and tree sensitivity is associated with allergic eosinophilic rhinitis at 4 years of
age. Ann Allergy Asthma Immunol 114:193-198.e194.
Colloff MJ. 1991. A review of the biology and allergenicity of the house-dust mite euroglyphus
maynei (acari: Pyroglyphidae) [corrected]. Exp Appl Acarol 11:177-198.
Crockett AJ, Cranston JM, Alpers JH. 1995. The changing prevalence of asthma-like respiratory
symptoms in south australian rural schoolchildren. J Paediatr Child Health 31:213-217.
Childhood AR: Finding from CHS Study
99

D'Amato G. 2002. Environmental urban factors (air pollution and allergens) and the rising trends
in allergic respiratory diseases. Allergy 57 Suppl 72:30-33.
de Andrade CR, da Cunha Ibiapina C, Gonçalves Alvim C, Fernandes Fontes MJ, de Lima
Belizário Facury Lasmar LM, Moreira Camargos PA. 2008. Asthma and allergic rhinitis co-
morbidity: A cross-sectional questionnaire study on adolescents aged 13-14 years. Prim Care
Respir J 17:222-225.
de Bot CM, Moed H, Bindels PJ, van Wijk RG, Berger MY, de Groot H, et al. 2013. Exhaled
nitric oxide measures allergy not symptoms in children with allergic rhinitis in primary care: A
prospective cross-sectional and longitudinal cohort study. Prim Care Respir J 22:44-50.
de Vos G, Nazari R, Ferastraoaru D, Parikh P, Geliebter R, Pichardo Y, et al. 2013. Discordance
between aeroallergen specific serum ige and skin testing in children younger than 4 years. Ann
Allergy Asthma Immunol 110:438-443.
de Vos G. 2014. Skin testing versus serum-specific ige testing: Which is better for diagnosing
aeroallergen sensitization and predicting clinical allergy? Curr Allergy Asthma Rep 14:430.
Delfino RJ, Zeiger RS, Seltzer JM, Street DH, Matteucci RM, Anderson PR, et al. 1997. The
effect of outdoor fungal spore concentrations on daily asthma severity. Environ Health Perspect
105:622-635.
Deng Q, Lu C, Yu Y, Li Y, Sundell J, Norbäck D. 2016. Early life exposure to traffic-related air
pollution and allergic rhinitis in preschool children. Respir Med 121:67-73.
Devalia JL, Bayram H, Rusznak C, Calderón M, Sapsford RJ, Abdelaziz MA, et al. 1997.
Mechanisms of pollution-induced airway disease: In vitro studies in the upper and lower airways.
Allergy 52:45-51; discussion 57-48.
Di Cara G, Marcucci F, Palomba A, Milioni M, Pecoraro L, Ciprandi G, et al. 2015. Exhaled
nitric oxide in children with allergic rhinitis: A potential biomarker of asthma development.
Pediatr Allergy Immunol 26:85-87.
Diaz-Sanchez D, Tsien A, Fleming J, Saxon A. 1997. Combined diesel exhaust particulate and
ragweed allergen challenge markedly enhances human in vivo nasal ragweed-specific ige and
skews cytokine production to a t helper cell 2-type pattern. J Immunol 158:2406-2413.
Diaz-Sanchez D, Garcia MP, Wang M, Jyrala M, Saxon A. 1999. Nasal challenge with diesel
exhaust particles can induce sensitization to a neoallergen in the human mucosa. J Allergy Clin
Immunol 104:1183-1188.
Dockery DW, Cunningham J, Damokosh AI, Neas LM, Spengler JD, Koutrakis P, et al. 1996.
Health effects of acid aerosols on north american children: Respiratory symptoms. Environ
Health Perspect 104:500-505.
Childhood AR: Finding from CHS Study
100

Dong GH, Ma YN, Ding HL, Jin J, Cao Y, Zhao YD, et al. 2008. Housing characteristics, home
environmental factors and respiratory health in 3945 pre-school children in china. Int J Environ
Health Res 18:267-282.
Dong Z, Cheng L. 2008. [evidence-based pharmacological management of allergic rhinitis].
Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 43:481-483.
Dweik RA, Boggs PB, Erzurum SC, Irvin CG, Leigh MW, Lundberg JO, et al. 2011. An official
ats clinical practice guideline: Interpretation of exhaled nitric oxide levels (feno) for clinical
applications. Am J Respir Crit Care Med 184:602-615.
Eckel SP, Zhang Z, Habre R, Rappaport EB, Linn WS, Berhane K, et al. 2016. Traffic-related air
pollution and alveolar nitric oxide in southern california children. Eur Respir J 47:1348-1356.
Edfors-Lubs ML. 1971. Allergy in 7000 twin pairs. Acta Allergol 26:249-285.
English P, Neutra R, Scalf R, Sullivan M, Waller L, Zhu L. 1999. Examining associations
between childhood asthma and traffic flow using a geographic information system. Environ
Health Perspect 107:761-767.
Fernandez-Salguero PM, Hilbert DM, Rudikoff S, Ward JM, Gonzalez FJ. 1996. Aryl-
hydrocarbon receptor-deficient mice are resistant to 2,3,7,8-tetrachlorodibenzo-p-dioxin-induced
toxicity. Toxicol Appl Pharmacol 140:173-179.
Ferreira MA, Matheson MC, Tang CS, Granell R, Ang W, Hui J, et al. 2014. Genome-wide
association analysis identifies 11 risk variants associated with the asthma with hay fever
phenotype. J Allergy Clin Immunol 133:1564-1571.
Filipiak B, Heinrich J, Schäfer T, Ring J, Wichmann HE. 2001. Farming, rural lifestyle and
atopy in adults from southern germany--results from the monica/kora study augsburg. Clin Exp
Allergy 31:1829-1838.
Fokkens WJ. 2002. Thoughts on the pathophysiology of nonallergic rhinitis. Curr Allergy
Asthma Rep 2:203-209.
Fruin S, Urman R, Lurmann F, McConnell R, Gauderman J, Rappaport E, et al. 2014. Spatial
variation in particulate matter components over a large urban area. Atmos Environ (1994)
83:211-219.
Fuertes E, Brauer M, MacIntyre E, Bauer M, Bellander T, von Berg A, et al. 2013a. Childhood
allergic rhinitis, traffic-related air pollution, and variability in the gstp1, tnf, tlr2, and tlr4 genes:
Results from the tag study. J Allergy Clin Immunol 132:342-352.e342.
Fuertes E, Standl M, Cyrys J, Berdel D, von Berg A, Bauer CP, et al. 2013b. A longitudinal
analysis of associations between traffic-related air pollution with asthma, allergies and
sensitization in the giniplus and lisaplus birth cohorts. PeerJ 1:e193.
Childhood AR: Finding from CHS Study
101

Gauderman WJ, Gilliland GF, Vora H, Avol E, Stram D, McConnell R, et al. 2002. Association
between air pollution and lung function growth in southern california children: Results from a
second cohort. Am J Respir Crit Care Med 166:76-84.
Gauderman WJ, Avol E, Gilliland F, Vora H, Thomas D, Berhane K, et al. 2004. The effect of
air pollution on lung development from 10 to 18 years of age. N Engl J Med 351:1057-1067.
Gauderman WJ, Avol E, Lurmann F, Kuenzli N, Gilliland F, Peters J, et al. 2005. Childhood
asthma and exposure to traffic and nitrogen dioxide. Epidemiology 16:737-743.
Gauderman WJ, Vora H, McConnell R, Berhane K, Gilliland F, Thomas D, et al. 2007. Effect of
exposure to traffic on lung development from 10 to 18 years of age: A cohort study. Lancet
369:571-577.
Gaugris S, Sazonov-Kocevar V, Thomas M. 2006. Burden of concomitant allergic rhinitis in
adults with asthma. J Asthma 43:1-7.
Gauvin S, Reungoat P, Cassadou S, Déchenaux J, Momas I, Just J, et al. 2002. Contribution of
indoor and outdoor environments to pm2.5 personal exposure of children--vesta study. Sci Total
Environ 297:175-181.
Georgy V, Fahim HI, El-Gaafary M, Walters S. 2006. Prevalence and socioeconomic
associations of asthma and allergic rhinitis in northern [corrected] africa. Eur Respir J 28:756-
762.
Gergen PJ, Turkeltaub PC. 1992. The association of individual allergen reactivity with
respiratory disease in a national sample: Data from the second national health and nutrition
examination survey, 1976-80 (nhanes ii). J Allergy Clin Immunol 90:579-588.
Gilliland FD, Berhane K, Rappaport EB, Thomas DC, Avol E, Gauderman WJ, et al. 2001. The
effects of ambient air pollution on school absenteeism due to respiratory illnesses. Epidemiology
12:43-54.
Gilliland FD, Li YF, Saxon A, Diaz-Sanchez D. 2004. Effect of glutathione-s-transferase m1 and
p1 genotypes on xenobiotic enhancement of allergic responses: Randomised, placebo-controlled
crossover study. Lancet 363:119-125.
Gluckman PD, Hanson MA, Beedle AS. 2007. Early life events and their consequences for later
disease: A life history and evolutionary perspective. Am J Hum Biol 19:1-19.
Greiner AN, Hellings PW, Rotiroti G, Scadding GK. 2011. Allergic rhinitis. Lancet 378:2112-
2122.
Guarnieri M, Balmes JR. 2014. Outdoor air pollution and asthma. Lancet 383:1581-1592.
Childhood AR: Finding from CHS Study
102

Guerra S, Sherrill DL, Baldacci S, Carrozzi L, Pistelli F, Di Pede F, et al. 2005. Rhinitis is an
independent risk factor for developing cough apart from colds among adults. Allergy 60:343-
349.
Gürkan F, Davutoglu M, Bilici M, Dagli A, Haspolat K. 2002. Asthmatic children and risk
factors at a province in the southeast of turkey. Allergol Immunopathol (Madr) 30:25-29.
Hardjojo A, Hadjojo A, Shek LP, van Bever HP, Lee BW. 2011. Rhinitis in children less than 6
years of age: Current knowledge and challenges. Asia Pac Allergy 1:115-122.
Harley KG, Macher JM, Lipsett M, Duramad P, Holland NT, Prager SS, et al. 2009. Fungi and
pollen exposure in the first months of life and risk of early childhood wheezing. Thorax 64:353-
358.
Hinds DA, McMahon G, Kiefer AK, Do CB, Eriksson N, Evans DM, et al. 2013. A genome-
wide association meta-analysis of self-reported allergy identifies shared and allergy-specific
susceptibility loci. Nat Genet 45:907-911.
Hirano T, Matsunaga K, Sugiura H, Minakata Y, Koarai A, Akamatsu K, et al. 2013. Persistent
elevation of exhaled nitric oxide and modification of corticosteroid therapy in asthma. Respir
Investig 51:84-91.
Hopp RJ, Bewtra AK, Watt GD, Nair NM, Townley RG. 1984. Genetic analysis of allergic
disease in twins. J Allergy Clin Immunol 73:265-270.
Huang X, Chen Y, Zhang F, Yang Q, Zhang G. 2014. Peripheral th17/treg cell-mediated
immunity imbalance in allergic rhinitis patients. Braz J Otorhinolaryngol 80:152-155.
Islam T, Gauderman WJ, Berhane K, McConnell R, Avol E, Peters JM, et al. 2007. Relationship
between air pollution, lung function and asthma in adolescents. Thorax 62:957-963.
Jagielo PJ, Thorne PS, Watt JL, Frees KL, Quinn TJ, Schwartz DA. 1996. Grain dust and
endotoxin inhalation challenges produce similar inflammatory responses in normal subjects.
Chest 110:263-270.
Jeong KY, Park JW, Hong CS. 2012. House dust mite allergy in korea: The most important
inhalant allergen in current and future. Allergy Asthma Immunol Res 4:313-325.
Jie Y, Isa ZM, Jie X, Ju ZL, Ismail NH. 2013. Urban vs. Rural factors that affect adult asthma.
Rev Environ Contam Toxicol 226:33-63.
Johansson A, Ludvigsson J, Hermansson G. 2008. Adverse health effects related to tobacco
smoke exposure in a cohort of three-year olds. Acta Paediatr 97:354-357.
Johansson SG, Bieber T, Dahl R, Friedmann PS, Lanier BQ, Lockey RF, et al. 2004. Revised
nomenclature for allergy for global use: Report of the nomenclature review committee of the
world allergy organization, october 2003. J Allergy Clin Immunol 113:832-836.
Childhood AR: Finding from CHS Study
103

Kakkar R, Lee RT. 2008. The il-33/st2 pathway: Therapeutic target and novel biomarker. Nat
Rev Drug Discov 7:827-840.
Kellberger J, Dressel H, Vogelberg C, Leupold W, Windstetter D, Weinmayr G, et al. 2012.
Prediction of the incidence and persistence of allergic rhinitis in adolescence: A prospective
cohort study. J Allergy Clin Immunol 129:397-402, 402.e391-393.
Kihlström A, Lilja G, Pershagen G, Hedlin G. 2002. Exposure to birch pollen in infancy and
development of atopic disease in childhood. J Allergy Clin Immunol 110:78-84.
Kilpeläinen M, Terho EO, Helenius H, Koskenvuo M. 2006. Body mass index and physical
activity in relation to asthma and atopic diseases in young adults. Respir Med 100:1518-1525.
Kim H, Levin L, LeMasters GK, Villareal M, Evans S, Lockey JE, et al. 2012. Validating
childhood symptoms with physician-diagnosed allergic rhinitis. Ann Allergy Asthma Immunol
108:228-231.
Kim HB, Eckel SP, Kim JH, Gilliland FD. 2016. Exhaled no: Determinants and clinical
application in children with allergic airway disease. Allergy Asthma Immunol Res 8:12-21.
Kim JH, Ahn YM, Kim HJ, Lim DH, Son BK, Kang HS, et al. 2014. Development of a
questionnaire for the assessment of quality of life in korean children with allergic rhinitis.
Allergy Asthma Immunol Res 6:541-547.
Kim JJ, Smorodinsky S, Lipsett M, Singer BC, Hodgson AT, Ostro B. 2004. Traffic-related air
pollution near busy roads: The east bay children's respiratory health study. Am J Respir Crit Care
Med 170:520-526.
Kjellman NI. 1994. Natural course of asthma and allergy in childhood. Pediatr Allergy Immunol
5:13-18.
Kline JN, Cowden JD, Hunninghake GW, Schutte BC, Watt JL, Wohlford-Lenane CL, et al.
1999. Variable airway responsiveness to inhaled lipopolysaccharide. Am J Respir Crit Care Med
160:297-303.
Klossek JM, Annesi-Maesano I, Pribil C, Didier A. 2012. The burden associated with ocular
symptoms in allergic rhinitis. Int Arch Allergy Immunol 158:411-417.
Kocabas CN, Civelek E, Sackesen C, Orhan F, Tuncer A, Adalioglu G, et al. 2005. Burden of
rhinitis in children with asthma. Pediatr Pulmonol 40:235-240.
Konkel L. 2014. Focusing on the ahr: A potential mechanism for immune effects of prenatal
exposures. Environ Health Perspect 122:A313.
Kovesi T, Kulka R, Dales R. 2008. Exhaled nitric oxide concentration is affected by age, height,
and race in healthy 9- to 12-year-old children. Chest 133:169-175.
Childhood AR: Finding from CHS Study
104

Krämer U, Koch T, Ranft U, Ring J, Behrendt H. 2000. Traffic-related air pollution is associated
with atopy in children living in urban areas. Epidemiology 11:64-70.
Künzli N, McConnell R, Bates D, Bastain T, Hricko A, Lurmann F, et al. 2003. Breathless in los
angeles: The exhausting search for clean air. Am J Public Health 93:1494-1499.
Lack G. 2001. Pediatric allergic rhinitis and comorbid disorders. J Allergy Clin Immunol
108:S9-15.
Lau S, Illi S, Sommerfeld C, Niggemann B, Bergmann R, von Mutius E, et al. 2000. Early
exposure to house-dust mite and cat allergens and development of childhood asthma: A cohort
study. Multicentre allergy study group. Lancet 356:1392-1397.
Lazo-Sáenz JG, Galván-Aguilera AA, Martínez-Ordaz VA, Velasco-Rodríguez VM, Nieves-
Rentería A, Rincón-Castañeda C. 2005. Eustachian tube dysfunction in allergic rhinitis.
Otolaryngol Head Neck Surg 132:626-629.
Lee KJ, Cho SH, Lee SH, Tae K, Yoon HJ, Kim SH, et al. 2012. Nasal and exhaled nitric oxide
in allergic rhinitis. Clin Exp Otorhinolaryngol 5:228-233.
Lee YL, Shaw CK, Su HJ, Lai JS, Ko YC, Huang SL, et al. 2003. Climate, traffic-related air
pollutants and allergic rhinitis prevalence in middle-school children in taiwan. Eur Respir J
21:964-970.
Lei Y, Yang H, Zhen L. 2016. Obesity is a risk factor for allergic rhinitis in children of wuhan
(china). Asia Pac Allergy 6:101-104.
Leuppi JD, Downs SH, Downie SR, Marks GB, Salome CM. 2002. Exhaled nitric oxide levels in
atopic children: Relation to specific allergic sensitisation, ahr, and respiratory symptoms. Thorax
57:518-523.
Levetin E, Van de Water P. 2001. Environmental contributions to allergic disease. Curr Allergy
Asthma Rep 1:506-514.
Lewis SA, Weiss ST, Platts-Mills TA, Burge H, Gold DR. 2002. The role of indoor allergen
sensitization and exposure in causing morbidity in women with asthma. Am J Respir Crit Care
Med 165:961-966.
Leynaert B, Neukirch C, Liard R, Bousquet J, Neukirch F. 2000a. Quality of life in allergic
rhinitis and asthma. A population-based study of young adults. Am J Respir Crit Care Med
162:1391-1396.
Leynaert B, Neukirch F, Demoly P, Bousquet J. 2000b. Epidemiologic evidence for asthma and
rhinitis comorbidity. J Allergy Clin Immunol 106:S201-205.
Childhood AR: Finding from CHS Study
105

Linn WS, Berhane KT, Rappaport EB, Bastain TM, Avol EL, Gilliland FD. 2009a. Relationships
of online exhaled, offline exhaled, and ambient nitric oxide in an epidemiologic survey of
schoolchildren. J Expo Sci Environ Epidemiol 19:674-681.
Linn WS, Rappaport EB, Berhane KT, Bastain TM, Avol EL, Gilliland FD. 2009b. Exhaled
nitric oxide in a population-based study of southern california schoolchildren. Respir Res 10:28.
Linneberg A, Henrik Nielsen N, Frølund L, Madsen F, Dirksen A, Jørgensen T, et al. 2002. The
link between allergic rhinitis and allergic asthma: A prospective population-based study. The
copenhagen allergy study. Allergy 57:1048-1052.
Liu J, Ballaney M, Al-alem U, Quan C, Jin X, Perera F, et al. 2008. Combined inhaled diesel
exhaust particles and allergen exposure alter methylation of t helper genes and ige production in
vivo. Toxicol Sci 102:76-81.
Liu MM, Wang D, Zhao Y, Liu YQ, Huang MM, Liu Y, et al. 2013. Effects of outdoor and
indoor air pollution on respiratory health of chinese children from 50 kindergartens. J Epidemiol
23:280-287.
Maeda N, Inomata N, Morita A, Kirino M, Ikezawa Z. 2010. Correlation of oral allergy
syndrome due to plant-derived foods with pollen sensitization in japan. Ann Allergy Asthma
Immunol 104:205-210.
Mai XM, Almqvist C, Nilsson L, Wickman M. 2007. Birth anthropometric measures, body mass
index and allergic diseases in a birth cohort study (bamse). Arch Dis Child 92:881-886.
Manners S, Alam R, Schwartz DA, Gorska MM. 2014. A mouse model links asthma
susceptibility to prenatal exposure to diesel exhaust. J Allergy Clin Immunol 134:63-72.
Marinho S, Simpson A, Lowe L, Kissen P, Murray C, Custovic A. 2007. Rhinoconjunctivitis in
5-year-old children: A population-based birth cohort study. Allergy 62:385-393.
Martin RA, Ather JL, Daggett R, Hoyt L, Alcorn JF, Suratt BT, et al. 2013. The endogenous
th17 response in no2-promoted allergic airway disease is dispensable for airway
hyperresponsiveness and distinct from th17 adoptive transfer. PLoS One 8:e74730.
McConnell R, Berhane K, Gilliland F, London SJ, Vora H, Avol E, et al. 1999. Air pollution and
bronchitic symptoms in southern california children with asthma. Environ Health Perspect
107:757-760.
McConnell R, Berhane K, Yao L, Jerrett M, Lurmann F, Gilliland F, et al. 2006a. Traffic,
susceptibility, and childhood asthma. Environ Health Perspect 114:766-772.
McConnell R, Berhane K, Yao L, Jerrett M, Lurmann F, Gilliland F, et al. 2006b. Traffic,
susceptibility, and childhood asthma. Environ Health Perspect 114:766-772.
Childhood AR: Finding from CHS Study
106

McConnell R, Islam T, Shankardass K, Jerrett M, Lurmann F, Gilliland F, et al. 2010. Childhood
incident asthma and traffic-related air pollution at home and school. Environ Health Perspect
118:1021-1026.
McConnell R, Shen E, Gilliland FD, Jerrett M, Wolch J, Chang CC, et al. 2014. A longitudinal
cohort study of body mass index and childhood exposure to secondhand tobacco smoke and air
pollution: The southern california children's health study. Environ Health Perspect.
McKeever TM, Lewis SA, Smith C, Hubbard R. 2002. The importance of prenatal exposures on
the development of allergic disease: A birth cohort study using the west midlands general
practice database. Am J Respir Crit Care Med 166:827-832.
Meiler F, Klunker S, Zimmermann M, Akdis CA, Akdis M. 2008. Distinct regulation of ige, igg4
and iga by t regulatory cells and toll-like receptors. Allergy 63:1455-1463.
Meltzer EO. 2001. Quality of life in adults and children with allergic rhinitis. J Allergy Clin
Immunol 108:S45-53.
Meltzer EO, Blaiss MS, Derebery MJ, Mahr TA, Gordon BR, Sheth KK, et al. 2009. Burden of
allergic rhinitis: Results from the pediatric allergies in america survey. J Allergy Clin Immunol
124:S43-70.
Mercer MJ, Joubert G, Ehrlich RI, Nelson H, Poyser MA, Puterman A, et al. 2004.
Socioeconomic status and prevalence of allergic rhinitis and atopic eczema symptoms in young
adolescents. Pediatr Allergy Immunol 15:234-241.
Moffatt MF, Cookson WO. 1999. Genetics of asthma and inflammation: The status. Curr Opin
Immunol 11:606-609.
Molfino NA, Slutsky AS, Zamel N. 1992. The effects of air pollution on allergic bronchial
responsiveness. Clin Exp Allergy 22:667-672.
Morgenstern V, Zutavern A, Cyrys J, Brockow I, Koletzko S, Krämer U, et al. 2008. Atopic
diseases, allergic sensitization, and exposure to traffic-related air pollution in children. Am J
Respir Crit Care Med 177:1331-1337.
Motta AC, Marliere M, Peltre G, Sterenberg PA, Lacroix G. 2006. Traffic-related air pollutants
induce the release of allergen-containing cytoplasmic granules from grass pollen. Int Arch
Allergy Immunol 139:294-298.
Mugusi F, Edwards R, Hayes L, Unwin N, Mbanya JC, Whiting D, et al. 2004. Prevalence of
wheeze and self-reported asthma and asthma care in an urban and rural area of tanzania and
cameroon. Trop Doct 34:209-214.
Naclerio RM. 1991. Allergic rhinitis. N Engl J Med 325:860-869.
Childhood AR: Finding from CHS Study
107

Nadeau K, McDonald-Hyman C, Noth EM, Pratt B, Hammond SK, Balmes J, et al. 2010.
Ambient air pollution impairs regulatory t-cell function in asthma. J Allergy Clin Immunol
126:845-852.e810.
Nel AE, Diaz-Sanchez D, Ng D, Hiura T, Saxon A. 1998. Enhancement of allergic inflammation
by the interaction between diesel exhaust particles and the immune system. J Allergy Clin
Immunol 102:539-554.
Nguyen LH, Manoukian JJ, Sobol SE, Tewfik TL, Mazer BD, Schloss MD, et al. 2004. Similar
allergic inflammation in the middle ear and the upper airway: Evidence linking otitis media with
effusion to the united airways concept. J Allergy Clin Immunol 114:1110-1115.
Nilsson D, Andiappan AK, Halldén C, Tim CF, Säll T, Wang dY, et al. 2013. Poor
reproducibility of allergic rhinitis snp associations. PLoS One 8:e53975.
Nordling E, Berglind N, Melén E, Emenius G, Hallberg J, Nyberg F, et al. 2008. Traffic-related
air pollution and childhood respiratory symptoms, function and allergies. Epidemiology 19:401-
408.
Osman M, Hansell AL, Simpson CR, Hollowell J, Helms PJ. 2007. Gender-specific
presentations for asthma, allergic rhinitis and eczema in primary care. Prim Care Respir J 16:28-
35.
Ostro B, Lipsett M, Mann J, Braxton-Owens H, White M. 2001. Air pollution and exacerbation
of asthma in african-american children in los angeles. Epidemiology 12:200-208.
Pawlak EA, Noah TL, Zhou H, Chehrazi C, Robinette C, Diaz-Sanchez D, et al. 2016. Diesel
exposure suppresses natural killer cell function and resolution of eosinophil inflammation: A
randomized controlled trial of exposure in allergic rhinitics. Part Fibre Toxicol 13:24.
Peden DB. 2002. Influences on the development of allergy and asthma. Toxicology 181-
182:323-328.
Peters JL, Suglia SF, Platts-Mills TA, Hosen J, Gold DR, Wright RJ. 2009. Relationships among
prenatal aeroallergen exposure and maternal and cord blood ige: Project access. J Allergy Clin
Immunol 123:1041-1046.
Piacentini GL, Bodini A, Costella S, Vicentini L, Mazzi P, Sperandio S, et al. 1999. Exhaled
nitric oxide and sputum eosinophil markers of inflammation in asthmatic children. Eur Respir J
13:1386-1390.
Pinart M, Keller T, Reich A, Fröhlich M, Cabieses B, Hohmann C, et al. 2017. Sex-related
allergic rhinitis prevalence switch from childhood to adulthood: A systematic review and meta-
analysis. Int Arch Allergy Immunol 172:224-235.
Childhood AR: Finding from CHS Study
108

Pénard-Morand C, Charpin D, Raherison C, Kopferschmitt C, Caillaud D, Lavaud F, et al. 2005.
Long-term exposure to background air pollution related to respiratory and allergic health in
schoolchildren. Clin Exp Allergy 35:1279-1287.
Qu SH, Li M, Liang JP, Yuan YL, Lin ZB. 2011. [change of th17 and expression of rorγt in a
murine model of allergic rhinitis after a stimulation of allergen and corticosteroid]. Zhonghua Yi
Xue Za Zhi 91:401-404.
Quillen DM, Feller DB. 2006. Diagnosing rhinitis: Allergic vs. Nonallergic. Am Fam Physician
73:1583-1590.
Radon K, Windstetter D, Eckart J, Dressel H, Leitritz L, Reichert J, et al. 2004. Farming
exposure in childhood, exposure to markers of infections and the development of atopy in rural
subjects. Clin Exp Allergy 34:1178-1183.
Ramasamy A, Curjuric I, Coin LJ, Kumar A, McArdle WL, Imboden M, et al. 2011. A genome-
wide meta-analysis of genetic variants associated with allergic rhinitis and grass sensitization and
their interaction with birth order. J Allergy Clin Immunol 128:996-1005.
Riedl M, Diaz-Sanchez D. 2005. Biology of diesel exhaust effects on respiratory function. J
Allergy Clin Immunol 115:221-228; quiz 229.
Ring S, Schäfer SC, Mahnke K, Lehr HA, Enk AH. 2006. Cd4+ cd25+ regulatory t cells
suppress contact hypersensitivity reactions by blocking influx of effector t cells into inflamed
tissue. Eur J Immunol 36:2981-2992.
Rosenwasser LJ. 2013. World allergy organization journal (wao journal) at five years: Updates
and changes. World Allergy Organ J 6:1.
Rutherford S, Simpson R, Williams G, Mitchell C, McCall B. 2000. Relationships between
environmental factors and lung function of asthmatic subjects in south east queensland, australia.
J Occup Environ Med 42:882-891.
Rönmark E, Bjerg A, Perzanowski M, Platts-Mills T, Lundbäck B. 2009. Major increase in
allergic sensitization in schoolchildren from 1996 to 2006 in northern sweden. J Allergy Clin
Immunol 124:357-363, 363.e351-315.
Rönmark EP, Ekerljung L, Mincheva R, Sjölander S, Hagstad S, Wennergren G, et al. 2016.
Different risk factor patterns for adult asthma, rhinitis and eczema: Results from west sweden
asthma study. Clin Transl Allergy 6:28.
Salo PM, Arbes SJ, Jaramillo R, Calatroni A, Weir CH, Sever ML, et al. 2014. Prevalence of
allergic sensitization in the united states: Results from the national health and nutrition
examination survey (nhanes) 2005-2006. J Allergy Clin Immunol.
Childhood AR: Finding from CHS Study
109

Sazonov Kocevar V, Thomas J, Jonsson L, Valovirta E, Kristensen F, Yin DD, et al. 2005.
Association between allergic rhinitis and hospital resource use among asthmatic children in
norway. Allergy 60:338-342.
Scadding G. 2007. Nitric oxide in the airways. Curr Opin Otolaryngol Head Neck Surg 15:258-
263.
Scadding GK, Durham SR, Mirakian R, Jones NS, Leech SC, Farooque S, et al. 2008. Bsaci
guidelines for the management of allergic and non-allergic rhinitis. Clin Exp Allergy 38:19-42.
Schiller JS, Lucas JW, Ward BW, Peregoy JA. 2012. Summary health statistics for u.S. Adults:
National health interview survey, 2010. Vital Health Stat 10:1-207.
Schulz VJ, Smit JJ, Pieters RH. 2013. The aryl hydrocarbon receptor and food allergy. Vet Q
33:94-107.
Schönberger HJ, Dompeling E, Knottnerus JA, Kuiper S, van Weel C, Schayck CP. 2005.
Prenatal exposure to mite and pet allergens and total serum ige at birth in high-risk children.
Pediatr Allergy Immunol 16:27-31.
Selnes A, Nystad W, Bolle R, Lund E. 2005. Diverging prevalence trends of atopic disorders in
norwegian children. Results from three cross-sectional studies. Allergy 60:894-899.
Settipane RJ, Settipane GA. 2000. Ige and the allergy-asthma connection in the 23-year follow-
up of brown university students. Allergy Asthma Proc 21:221-225.
Sherrill DL, Guerra S, Minervini MC, Wright AL, Martinez FD. 2005. The relation of rhinitis to
recurrent cough and wheezing: A longitudinal study. Respir Med 99:1377-1385.
Shi M, Huangfu H, Zhang C, Huang Q, Zhang M, Jin Y. 2011. [the expression and regulation of
th17 cell in murine modal of allergic rhinitis]. Lin Chung Er Bi Yan Hou Tou Jing Wai Ke Za
Zhi 25:652-655.
Silvestri M, Sabatini F, Spallarossa D, Fregonese L, Battistini E, Biraghi MG, et al. 2001.
Exhaled nitric oxide levels in non-allergic and allergic mono- or polysensitised children with
asthma. Thorax 56:857-862.
Slutsky A, Drazen J, Silkoff P, Gaston B, Holden W, Romero F, et al. 1999. Recommendations
for standardized procedures for the online and offline measurement of exhaled lower respiratory
nitric oxide and nasal nitric oxide in adults and children - 1999. American Journal of Respiratory
and Critical Care Medicine 160:2104-2117.
Smith AD, Cowan JO, Filsell S, McLachlan C, Monti-Sheehan G, Jackson P, et al. 2004.
Diagnosing asthma: Comparisons between exhaled nitric oxide measurements and conventional
tests. Am J Respir Crit Care Med 169:473-478.
Childhood AR: Finding from CHS Study
110

Society AT, Society ER. 2005. Ats/ers recommendations for standardized procedures for the
online and offline measurement of exhaled lower respiratory nitric oxide and nasal nitric oxide,
2005. Am J Respir Crit Care Med 171:912-930.
Soto-Quiros ME, Silverman EK, Hanson LA, Weiss ST, Celedón JC. 2002. Maternal history,
sensitization to allergens, and current wheezing, rhinitis, and eczema among children in costa
rica. Pediatr Pulmonol 33:237-243.
Stockinger B, Di Meglio P, Gialitakis M, Duarte JH. 2014. The aryl hydrocarbon receptor:
Multitasking in the immune system. Annu Rev Immunol 32:403-432.
Strachan DP. 1989. Hay fever, hygiene, and household size. BMJ 299:1259-1260.
Strachan DP. 1994. Is allergic disease programmed in early life? Clin Exp Allergy 24:603-605.
Suárez-Cervera M, Castells T, Vega-Maray A, Civantos E, del Pozo V, Fernández-González D,
et al. 2008. Effects of air pollution on cup a 3 allergen in cupressus arizonica pollen grains. Ann
Allergy Asthma Immunol 101:57-66.
Svanes C, Heinrich J, Jarvis D, Chinn S, Omenaas E, Gulsvik A, et al. 2003. Pet-keeping in
childhood and adult asthma and hay fever: European community respiratory health survey. J
Allergy Clin Immunol 112:289-300.
Sánchez-Lerma B, Morales-Chirivella FJ, Peñuelas I, Blanco Guerra C, Mesa Lugo F, Aguinaga-
Ontoso I, et al. 2009. High prevalence of asthma and allergic diseases in children aged 6 to
[corrected] 7 years from the canary islands. [corrected]. J Investig Allergol Clin Immunol
19:383-390.
Taborda-Barata L, Potter PC. 2012. Socio-epidemiological aspects of respiratory allergic
diseases in southern africa. World Allergy Organ J 5:1-8.
Takafuji S, Suzuki S, Muranaka M, Miyamoto T. 1989. Influence of environmental factors on
ige production. Ciba Found Symp 147:188-201; discussion 201-184.
Takai T, Ikeda S. 2011. Barrier dysfunction caused by environmental proteases in the
pathogenesis of allergic diseases. Allergol Int 60:25-35.
Takeno S, Noda N, Hirakawa K. 2012. Measurements of nasal fractional exhaled nitric oxide
with a hand-held device in patients with allergic rhinitis: Relation to cedar pollen dispersion and
laser surgery. Allergol Int 61:93-100.
Teng B, Zhang X, Yi C, Zhang Y, Ye S, Wang Y, et al. 2017. The association between ambient
air pollution and allergic rhinitis: Further epidemiological evidence from changchun,
northeastern china. Int J Environ Res Public Health 14.
Childhood AR: Finding from CHS Study
111

Thomas M, Kocevar VS, Zhang Q, Yin DD, Price D. 2005. Asthma-related health care resource
use among asthmatic children with and without concomitant allergic rhinitis. Pediatrics 115:129-
134.
Timonen KL, Pekkanen J, Tiittanen P, Salonen RO. 2002. Effects of air pollution on changes in
lung function induced by exercise in children with chronic respiratory symptoms. Occup Environ
Med 59:129-134.
Toda M, Ono SJ. 2002. Genomics and proteomics of allergic disease. Immunology 106:1-10.
van den Toorn LM, Overbeek SE, de Jongste JC, Leman K, Hoogsteden HC, Prins JB. 2001.
Airway inflammation is present during clinical remission of atopic asthma. Am J Respir Crit
Care Med 164:2107-2113.
van Voorhis M, Knopp S, Julliard W, Fechner JH, Zhang X, Schauer JJ, et al. 2013. Exposure to
atmospheric particulate matter enhances th17 polarization through the aryl hydrocarbon receptor.
PLoS One 8:e82545.
Varshney J, Varshney H. 2015. Allergic rhinitis: An overview. Indian J Otolaryngol Head Neck
Surg 67:143-149.
Veldhoen M, Hirota K, Westendorf AM, Buer J, Dumoutier L, Renauld JC, et al. 2008. The aryl
hydrocarbon receptor links th17-cell-mediated autoimmunity to environmental toxins. Nature
453:106-109.
Venn AJ, Lewis SA, Cooper M, Hubbard R, Britton J. 2001. Living near a main road and the risk
of wheezing illness in children. Am J Respir Crit Care Med 164:2177-2180.
von Mutius E, Martinez FD, Fritzsch C, Nicolai T, Reitmeir P, Thiemann HH. 1994a. Skin test
reactivity and number of siblings. BMJ 308:692-695.
von Mutius E, Martinez FD, Fritzsch C, Nicolai T, Roell G, Thiemann HH. 1994b. Prevalence of
asthma and atopy in two areas of west and east germany. Am J Respir Crit Care Med 149:358-
364.
von Mutius E, Weiland SK, Fritzsch C, Duhme H, Keil U. 1998. Increasing prevalence of hay
fever and atopy among children in leipzig, east germany. Lancet 351:862-866.
Wadhwa PD, Buss C, Entringer S, Swanson JM. 2009. Developmental origins of health and
disease: Brief history of the approach and current focus on epigenetic mechanisms. Semin
Reprod Med 27:358-368.
Wallace DV, Dykewicz MS, Bernstein DI, Blessing-Moore J, Cox L, Khan DA, et al. 2008. The
diagnosis and management of rhinitis: An updated practice parameter. J Allergy Clin Immunol
122:S1-84.
Childhood AR: Finding from CHS Study
112

Walshaw MJ, Evans CC. 1987. The effect of seasonal and domestic factors on the distribution of
euroglyphus maynei in the homes of dermatophagoides pteronyssinus allergic patients. Clin
Allergy 17:7-14.
Wang C, Salam MT, Islam T, Wenten M, Gauderman WJ, Gilliland FD. 2008. Effects of in utero
and childhood tobacco smoke exposure and beta2-adrenergic receptor genotype on childhood
asthma and wheezing. Pediatrics 122:e107-114.
Wang DY. 2005. Risk factors of allergic rhinitis: Genetic or environmental? Ther Clin Risk
Manag 1:115-123.
Wang P, Thevenot P, Saravia J, Ahlert T, Cormier SA. 2011. Radical-containing particles
activate dendritic cells and enhance th17 inflammation in a mouse model of asthma. Am J Respir
Cell Mol Biol 45:977-983.
Wang YH, Angkasekwinai P, Lu N, Voo KS, Arima K, Hanabuchi S, et al. 2007. Il-25 augments
type 2 immune responses by enhancing the expansion and functions of tslp-dc-activated th2
memory cells. J Exp Med 204:1837-1847.
Weaver IC, Champagne FA, Brown SE, Dymov S, Sharma S, Meaney MJ, et al. 2005. Reversal
of maternal programming of stress responses in adult offspring through methyl supplementation:
Altering epigenetic marking later in life. J Neurosci 25:11045-11054.
Wei P, Hu GH, Kang HY, Yao HB, Kou W, Liu H, et al. 2014. Increased aryl hydrocarbon
receptor expression in patients with allergic rhinitis. QJM 107:107-113.
Williams R. 2005. Climate change blamed for rise in hay fever. Nature 434:1059.
Wing K, Onishi Y, Prieto-Martin P, Yamaguchi T, Miyara M, Fehervari Z, et al. 2008. Ctla-4
control over foxp3+ regulatory t cell function. Science 322:271-275.
Wright AL, Holberg CJ, Martinez FD, Halonen M, Morgan W, Taussig LM. 1994.
Epidemiology of physician-diagnosed allergic rhinitis in childhood. Pediatrics 94:895-901.
Yoon J, Choi YJ, Lee E, Cho HJ, Yang SI, Kim YH, et al. 2017. Allergic rhinitis in preschool
children and the clinical utility of feno. Allergy Asthma Immunol Res 9:314-321.
Zeidler MR, Kleerup EC, Tashkin DP. 2004. Exhaled nitric oxide in the assessment of asthma.
Curr Opin Pulm Med 10:31-36.
Zhang F, Wang W, Lv J, Krafft T, Xu J. 2011. Time-series studies on air pollution and daily
outpatient visits for allergic rhinitis in beijing, china. Sci Total Environ 409:2486-2492.
Zhao Y, Usatyuk PV, Gorshkova IA, He D, Wang T, Moreno-Vinasco L, et al. 2009. Regulation
of cox-2 expression and il-6 release by particulate matter in airway epithelial cells. Am J Respir
Cell Mol Biol 40:19-30.
Childhood AR: Finding from CHS Study
113

Zmirou D, Gauvin S, Pin I, Momas I, Just J, Sahraoui F, et al. 2002. Five epidemiological studies
on transport and asthma: Objectives, design and descriptive results. J Expo Anal Environ
Epidemiol 12:186-196.
Zuraimi MS, Tham KW, Chew FT, Ooi PL, Koh D. 2011. Home air-conditioning, traffic
exposure, and asthma and allergic symptoms among preschool children. Pediatr Allergy
Immunol 22:e112-118.
[Anonymous]. White book on allergy 2011-2012 executive summary.
[Anonymous]. Wao white book on allergy.
[Anonymous]. 1999. Recommendations for standardized procedures for the on-line and off-line
measurement of exhaled lower respiratory nitric oxide and nasal nitric oxide in adults and
children-1999. This official statement of the american thoracic society was adopted by the ats
board of directors, july 1999. Am J Respir Crit Care Med 160:2104-2117.

Abstract (if available)

Abstract Background: Allergic rhinitis (AR) is a common respiratory disease, especially among children in the United States. The prevalence of AR has been rising with the increasing industrialization and urbanization and the economic impact on society becomes a major concern worldwide. However, limited studies have been done in a large population to test the impact of environment, indoor and outdoor, on the development of childhood allergic rhinitis. In addition, there was lack of thorough studies on whether or how the effects of environmental factors on the development of childhood AR in different age groups. ❧ Objectives: We investigated the risk from exposure to indoor and outdoor environments and other biological determinants (sensitization, FeNO) for the development of AR in children. We also tested if the impacts varied by sex or family history of allergic diseases. ❧ Methods: A). Among participants in the CHS study, 67 children who were AR-free and underwent skin prick test to common allergens were followed for up to 8 years for incident AR. The individual and joint effects of allergen sensitization and exposure to traffic-related air pollution (TRAP) on the development of AR in children were assessed by Cox proportional hazards model. B). Cross-sectional analyses of risk factors for AR was performed among CHS participants at the entry. Association between environments, outdoor and indoor, and prevalent AR was assessed by multinomial regression model. C). A longitudinal study of AR incidence was conducted among 2,892 AR-free participants followed for up to 10 years. The impact of indoor/outdoor environment on the risk of developing AR was assessed using survival analysis after adjustment for demographic, socio-economic factors, and family medical history and D). To assess fractional exhaled nitric oxide (FeNO) in prediction of new onset rhinoconjunctivitis, 621 eligible children who had FeNO measurement and were free of AR were followed for 5 years for the incident rhinoconjunctivitis. Baseline level of FeNO and time-varying levels of FeNO were included in the proportional cox models separately after adjustment for covariates. ❧ Results: 1). In the cohort study following children with SPT test, it was found that children with sensitization to multiple allergens had a 4.7 (95% CI: 2.1-10.6) times increased risk for incident AR. Children who lived within 500m from a freeway were 2.3 (95% CI: 1.1-4.9) times as likely to develop AR, compared to those living further than 500m. A strong synergism was suggested between sensitization and TRAP exposure for the development of AR. Sensitized children who lived ≤ 500m from a freeway had 8.1-fold (95% CI: 2.8-23.5) increased risk of AR compared to non-sensitized children who lived >500m from a freeway. 2). From the cross-sectional study performed among kindergarteners and first-graders, we identified that some indoor environmental factors and air pollutants were significantly related to prevalent AR. Use of a humidifier or vaporizer was associated with 1.6 (95% CI: 1.2- 2.3) times higher odds of nasal allergy, and 1.7 times (95% CI: 1.3-2.4) higher prevalence of rhinoconjunctivitis. Household mildew increased the odds of nasal allergy 1.7-fold (95% CI: 1.2-2.4) and rhinoconjunctivitis 1.4-fold (95% CI: 1.0-1.9). Prevalence of rhinoconjunctivitis was associated with exposure to nitrogen dioxide (NO₂ ) (OR =1.5

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

Genetic variation in inducible nitric oxide synthase promoter, residential traffic related air pollution and exhaled nitric oxide in children

PDF

Airway inflammation and respiratory health in the Southern California children's health study

PDF

Native American ancestry among Hispanic Whites is associated with higher risk of childhood obesity: a longitudinal analysis of Children’s Health Study data

PDF

Air pollution, mitochondrial function, and growth in children

PDF

A cohort study of air-pollution and childhood obesity incidence

PDF

Prenatal air pollution exposure, newborn DNA methylation, and childhood respiratory health

PDF

Air pollution and childhood obesity

PDF

Effects of stress and the social environment on childhood asthma in the children' s health study

PDF

Influences of specific environmental domains on childhood obesity and related behaviors

PDF

Effects of near-roadway air pollution exposure on obesity, obesity-related behavior, and neurobehavioral deficits during peripuberty

PDF

Psychosocial and cultural factors in the primary prevention of melanoma targeted to multiethnic children

PDF

Association of maternal and environmental factors with infant feeding behaviors in a birth cohort study

PDF

Association of traffic-related air pollution and lens opacities in the Los Angeles Latino Eye Study

PDF

Persistence of pollution-induced lung function deficits in early adulthood: evidence from the Children's Health Study

PDF

Sensor-based mobile health approaches for personal air pollution and pediatric asthma studies

PDF

A network analysis of online and offline social influence processes in relation to adolescent smoking and alcohol use

PDF

The Internet activities, gratifications, and health consequences related to compulsive Internet use

PDF

Prenatal and lifestyle predictors of metabolic health and neurocognition during childhood

PDF

Associations of cumulative pollution burden and environmental health vulnerabilities with gestational weight gain in a cohort of predominantly low-income Hispanic women

PDF

The role of depression symptoms on social information processing and tobacco use among adolescents

Asset Metadata

Creator Zhou, Hui (author)

Core Title The impact of the environment on childhood allergic rhinitis: findings from the Children’s Health Study

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Preventive Medicine (Health Behavior Research)

Publication Date 09/25/2017

Defense Date 07/21/2017

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag allergen sensitization,allergic rhinitis,FeNO,OAI-PMH Harvest,traffic-related air pollutants

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Gilliland, Frank D. (committee chair), Breton, Carrie (committee member), Dubeau, Louis (committee member), Xiang, Anny Hui (committee member)

Creator Email zhouhui@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c40-431741

Unique identifier UC11266349

Identifier etd-ZhouHui-5754.pdf (filename),usctheses-c40-431741 (legacy record id)

Legacy Identifier etd-ZhouHui-5754.pdf

Dmrecord 431741

Document Type Dissertation

Rights Zhou, Hui

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA