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A descriptive analysis of medication use by asthmatics in the Children's Health Study, 1993
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A descriptive analysis of medication use by asthmatics in the Children's Health Study, 1993
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Content
A DESCRIPTIVE ANALYSIS OF MEDICATION USE BY ASTHMATICS IN
THE CHILDREN’S HEALTH STUDY, 1993
by
Lisa Giltner Grossman
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(APPLIED BIOSTATISTICS AND EPIDEMIOLOGY)
May 2003
Copyright 2003 Lisa Giltner Grossman
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UMI Number: 1416554
Copyright 2003 by
Grossman, Lisa Giltner
All rights reserved.
®
UMI
UMI Microform 1416554
Copyright 2003 by ProQuest Information and Learning Company.
All rights reserved. This microform edition is protected against
unauthorized copying under Title 17, United States Code.
ProQuest Information and Learning Company
300 North Zeeb Road
P.O. Box 1346
Ann Arbor, Ml 48106-1346
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UNIVERSITY OF SOUTHERN CALIFORNIA
THE GRADUATE SCHOOL
UNIVERSITY PARK
LOS ANGELES, CALIFORNIA 90089-1695
This thesis, written by
Lisa Giltner Grossman________________
under the direction o f h e r thesis committee, and
approved by all its members, has been presented to and
accepted by the Director o f Graduate and Professional
Programs, in partial fulfillment o f the requirements for the
degree of
Master of Science, Applied Biometry and Epidemiology
Director
Date May 16, 2003
Thesis Committee
Chair
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DEDICATION
In memory of my brother, John
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iii
ACKNOWLEDGEMENTS
I thank my committee chair and mentor, Dr. Frank Gilliland, for his patient yet
persistent guidance during all phases of this project. My gratitude also goes to Dr.
Rob McConnell, Dr. Kiros Berhane and Mr. Ed Avol for their careful review of this
work, their helpful comments and words of encouragement. I am indebted to Dr.
John Peters and Dr. Stanley Azen for their vote of confidence when I began the
Applied Biometry and Epidemiology program. I also thank my fellow students and
coworkers who have passed this way before me, Made Wenten, Hita Vora, Towhid
Salam, and Jassy Molitor, for their constant support and helpful tips in seeing this
project through to the end.
This work would not have been possible without the support and encouragement
of my family. My love, admiration, and deep appreciation go to my parents, Bonnie
and Walter Heinz and Robert F. Giltner, for their financial support and guidance
through the years. For their help with childcare while I worked, my heartfelt thanks
go to my mother and father-in-law, Barbara and Arnold Grossman. With loving
gratitude, I thank my children, Marie, Anthony, Teresa, Sandy and Miles, for giving
me the time and space for this effort over the years. Finally, I thank my husband,
Steven D. Grossman, for all of his sacrifices and expressions of love and support
throughout the several years of this project.
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iv
CONTENTS
DEDICATION.................................................................................................. ii
ACKNOWLEDGEMENTS............................................................................ iii
LIST OF TABLES........................................................................................ v
LIST OF FIGURES........................................................................................ vi
ABSTRACT..................................................................................................... vii
Chapter
I. INTRODUCTION............................................................................... 1
II. METHODS........................................................................................... 9
III. RESULTS............................................................................................ 16
IV. DISCUSSION..................................................................................... 34
BIBLIOGRAPHY........................................................................................... 39
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LIST OF TABLES
Table Page
1. Definitions of asthma and symptom severity variables, SAIS 1993................... 13
2. Selected characteristics for SAIS participants vs. all other CHS
participants with doctor-diagnosed asthma, 1993................................................ 17
3. Percent agreement and simple Kappa coefficients for selected questions. . . . 19
4. Medication use, SAIS participants, 1993.............................................................. 20
5. Medication use, SAIS participants with current asthma only, 1993.................. 25
6. Adjusted odds ratios and 95% confidence intervals for current
medication use, 1993............................................................................................... 30
7. By community, predicted probability for current medication use........................31
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LIST OF FIGURES
Figure Page
1. Predicted probability of med use by ozone, 10-6,
current asthmatics, 1993 ...................................................................................... 32
2. Probability of med use by max ozone, current asthmatics, 1993 ..................... 32
3. Probability of med use by nitrogen dioxide, 24 hr,
current asthmatics, 1993......................................................................................... 33
4. Probability of med use by particulate matter, 24 hr,
current asthmatics, 1993......................................................................................... 33
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ABSTRACT
vii
The Supplemental Asthma Information Study (SAIS) gathered data on
asthma medications and symptoms in 1993 as part of the Children’s Health Study
(CHS), a longitudinal study of air pollution and children’s respiratory health. SAIS
and CHS responses for asthma and medication use were compared. The observed
agreement for doctor-diagnosed asthma was 99%, for medication use, 77.6%
(Kappa=0.51), for inhaler, 86.8%, (Kappa=0.73) and for steroid use, 81%
(Kappa=0.17). The relationships of inhaler, beta-agonist, and steroid use with
demographic and symptom variables were assessed. Compared to whites, Hispanics
were 4.2 times (95% Cl: 1.6-11.1) less likely and other minorities were 4.6 times
(95% Cl: 1.5-12.5) less likely to use asthma medications. No statistically significant
relationships were found between community patterns of medication use and
ambient levels air pollutants using predicted probabilities of medication use for each
city.
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1
I. INTRODUCTION
Asthma has become the most frequent chronic disease of childhood
(Martinez 1999; Price 2000), affecting 10% to 15% of children in the United States
(Zeffren, Windom et al. 1996). Asthma is the leading cause of hospitalization and
school absenteeism in children (Williams 1997). Several studies report that the
prevalence of asthma and asthma-related hospitalizations and mortality have
increased or remained stable over the past ten years, despite advances in treatment
(Gem, Schroth et al. 1995; Martinez 1999; Price 2000). Serial studies in the United
Kingdom and data from other countries suggest that prevalence of asthma and
wheezy illness may have doubled over the past 20 years (Wainwright, Isles et al.
1997). The increase has affected children and young adults to the greatest extent and
appears to be due to an increase in asthma incidence during the first 10 years of life
(Martinez 1999; Weisberg 2000). Although some of the trend may be explained by
the increased willingness of doctors to diagnose asthma, there is evidence for the
under treatment of symptoms and a rise in the asthma mortality rate, especially in
minority groups (Williams 1997; Powell and Everard 1998).
One effort to better understand the causes of childhood respiratory illnesses,
including asthma, is the University of Southern California Children’s Health Study
(CHS), a longitudinal study of air pollution and children’s respiratory health in
twelve Southern California communities. Since its inception in 1993, over 6500
students from age 10-17 and their parents have participated at school or at home by
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2
performing tests of lung function and providing information on health history,
outdoor activity levels, respiratory illnesses and both personal and household
characteristics. In addition, air pollution data in the twelve communities have been
collected. To confirm asthma status and to obtain detailed information about asthma
medications and symptoms, parents of children who were ever diagnosed with
asthma, as reported on the CHS entry questionnaire, were interviewed by phone in
summer, 1993.
Information from the Supplemental Asthma Information Study, or SAIS,
was used to describe medication use among asthmatics, to assess the reproducibility
of CHS baseline questionnaire responses for asthma and medication use and to
assess differences in community patterns of medication use. Before describing
results obtained in the SAIS, a brief discussion of salient perspectives of asthma is in
order.
The definition of asthma has changed over recent years as more has become
known about its pathogenesis. Once thought to be primarily a bronchospastic
condition, asthma is now thought to be a predominately inflammatory disease. The
National Heart, Lung, and Blood Institute (NHLBI) expert panel report defines
asthma as a lung disease with the following characteristics: airway obstruction that is
reversible either spontaneously or with treatment, airway inflammation, and
increased airway responsiveness to a variety of stimuli (Zeffren, Windom et al.
1996). On a cellular level, asthma is defined as an immune response characterized
by the local production of a large array of inflammatory mediators and by the
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3
subsequent recruitment of different cells in the airway lumen and airway wall,
predominately eosinophils and mast cells (Martinez 1999). More specifically,
childhood asthma maybe difficult to define because the disease’s chronic nature has
yet to be determined in the very young. Scientists are attempting to identify factors
that are associated with chronic childhood asthma in order to distinguish those young
children who only suffer from asthmatic symptoms at a very early age from those
who will develop persistent asthma. Currently, asthma in young children may be
operatively defined as a chronic wheezy condition frequently associated with atopy
and inflammation, provoked by a number of triggers in addition to viruses, and
carrying a poorer prognosis for an adulthood free of respiratory distress (Gem,
Schroth et al. 1995).
Although childhood asthma is of worldwide concern, its prevalence varies
greatly between countries (Price 2000). Before the international study of asthma and
allergies in children (ISAAC) was organized (Asher, Keil et al. 1995; 1996),
comparisons between countries were difficult because study protocols were not
standardized. The ISAAC report, published in 1998, compared the prevalence rates
of asthma and atopy in 56 countries (1998). Higher rates were found in English-
speaking countries. Prevalence rates of 17-30% were reported in the UK, New
Zealand and Australia, in contrast to rates of 1-7% in Eastern Europe, China, and
Indonesia. Prevalence also varied within countries. Reasons for the variations in
rates were not explained. One theory proposes that differences in hygiene and
healthcare lead to different exposures to infection in early life. This may render the
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4
immune system susceptible to an atopic response. Other factors that may affect the
prevalence rates are differences in diet, socio-economic status, ethnic origin and
allergen exposure (Price 2000). Others postulate that the increased prevalence is a
result of an increase in indoor pollution and multiple factors associated with poverty
and overcrowding: increased exposure to viral infections and allergens, proximity to
sources of pollution, cockroach allergy, low birth weight, and decrease in
breastfeeding, which may be protective (Williams 1997).
Several risk factors for developing asthma have been identified. Asthma
affects more boys than girls at very young ages. Later, it affects more girls than boys
in the teen years. It is more common in African American and Hispanic children.
Other factors that increase asthma risk are passive exposure to tobacco smoke, low
socio-economic class, family history of atopy and asthma, and exposure to high
levels of environmental allergens such as house dust mite (Gem, Schroth et al. 1995;
Giuntini and Paggiaro 1995). In addition, children who exercise heavily in
communities with high levels of ozone have been found to be at increased risk for
developing asthma (McConnell, Berhane et al. 2002).
Asthma is treated with a variety of medications, which fall into three main
groups: bronchodilators, anti-inflammatory agents, and leukotriene inhibitors. The
last type, leukotriene inhibitors, was not available in 1993 when the SAIS was
conducted. Bronchodilators include beta-agonists, theophylline, and
anticholinergics. Epinephrine, the first beta-agonist, was isolated in the early 1900’s.
Until recently it was the first-line therapy for acute asthma. Isoproterenol was the
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5
next major agent developed in the 1940’s for asthma, followed by the first beta2-
selective agent, albuterol, about 30 years ago. Beta-agonists relax airway smooth
muscle, inhibit the release of histamine from mast cells and increase ciliary motility
(Zeffren, Windom et al. 1996). Theophylline has been a popular oral drug for
asthma and chronic obstructive pulmonary disease worldwide despite its complex
pharmacokinetics and numerous side effects. Its use in industrialized countries has
declined significantly in the last decade because of toxicity and the fact that beta-
agonists are more effective. Nevertheless, recent findings have indicated that it can
be effective in managing hard to control asthma cases when used along with inhaled
corticosteroids (Barnes 2003). The third class of bronchodialator, anticholinergics, is
not used for children except in severe cases where beta-agonists, by themselves, are
not effective. Ipratopium bromide is the only form available in the U.S (Zeffren,
Windom et al. 1996).
The other major form of asthma medication is anti-inflammatory agents.
These include corticosteroids, in inhaler and oral form, and cromolyn. Inhaled
corticosteroids are the most widely used of anti-inflammatory agents. They were
developed in the 1970’s and are frequently administered as inhalers (Williams 1997;
Price 2000). Their anti-asthma effect is due, in part, to the suppression of genes for
the cytokines and other mediators involved in directing and propagating the cellular
component of inflammation. Steroids also reduce the numbers of T-lymphocytes,
eosinophils, macrophages and mast cells. Mucus production is reduced as well.
Oral corticosteroids, like prednisone, are likely to be administered in high doses for
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6
acute exacerbations, and thus have a greater effect than inhaled corticosteroids, but
also increased propensity for side effects. Cromolyn is a non-steroid anti
inflammatory agent administered by inhaler that effectively stabilizes mast cells.
There are minimal side effects, but it may take 4-6 weeks of use to see a maximum
response.
As the understanding of the pathophysiology of asthma developed, the
accepted treatment and management of asthma changed. Asthma came to be
understood as a disease of bronchial hyperresponsiveness and inflammation, rather
than a disease ofbronchospasm. Therefore, therapeutic approaches changed from
treatment with bronchodilators alone to the combined use of prophylactic anti
inflammatory drug therapy (usually inhaled corticosteriods) with as-needed use of
bronchodilators (Weisberg 2000). Several controversies arose. Of concern were the
potential side effects of inhaled glucocorticoid therapy, specifically growth
suppression in children, adrenal suppression and osteoporosis. Use of systemic
corticosteroids has been linked to greater risk of hip fracture in elderly women,
although use of inhaled corticosteroids was not found to increase hip fracture risk.
Also debated were issues concerning the use of metered-dose and dry powder
inhalers by children, the unknown equivalency of available anti-inflammatory
medications, the use of theophylline for acute asthma attacks, and the potential for
worsened asthma control and increased risk of death with regular, as opposed to “as
needed”, use of inhaled beta-agonists (Kamada 1994). Sudden epidemics of asthma-
related deaths occurred in six countries in the 1960’s and again in New Zealand in
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7
the 1970’s. These epidemics have been attributed the increased use ofhigh-dose
beta-agonists (Pearce 1998). When the beta-agonists were taken off the market, the
asthma mortality rate declined. In 1995, an editorial was published addressing this
controversy over the regular use of inhaled beta-agonists and its association with
asthma mortality and poor control of asthma symptoms. The authors did not find
evidence of a causal link and recommended that larger studies over longer time
periods be conducted (Giuntini and Paggiaro 1995).
At the start of the CHS in 1993, guidelines for the medical management of
childhood asthma were as follows (Tinkelman and Conner 1994). The
recommendation for mild asthma was to use bronchodilators as needed, inhaled beta-
agonists as first choice, oral beta-agonists, or oral theophylline. Recommendations
for moderate asthma were intermittent use of bronchodilators, prophylactic therapy
in the form of regular doses of cromolyn or nedocromil, and use of low-dose inhaled
steroids only when other medications fail to control symptoms. Finally,
recommendations for severe asthma were intermittent use of bronchodilators, high-
dose inhaled steroids, or oral steroids.
Changes over time in asthma treatment include strides in developing new
drugs for asthma treatment and earlier detection and treatment of asthma in infancy,
resulting in less long-term loss of lung function (Wainwright, Isles et al. 1997). New
drugs include nedocromil sodium, an anti-inflammatory medication, used as a
preventive measure and when high-dose inhaled steroids are ineffective or not
tolerated. Also new is salmeterol xinofoate, a long acting beta-agonist. It works for
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up to 12 hours to prevent nocturnal asthma and exercise-induced asthma. Also
developed recently is a more potent corticosteroid, fluticasone propionate, which
allows a lower dose needed for efficacy (Wainwright, Isles et al. 1997; Price 2000).
Anti-leukotriene agents are the first new class of therapy for asthma to be approved
in nearly three decades. They have bronchodialatory effects as well as some anti
inflammatory effects. They are usually used in addition to other established
medications for asthma and enable dosages of corticosteroids to be reduced. Taken
orally, they can be administered once or twice daily, thus improving compliance
(Weisberg 2000). As stated previously, theophylline has reemerged as an effective
asthma course of therapy. It seems to have anti-inflammatory effects when
administered at low doses and has been effective in managing hard to control asthma
cases when used along with inhaled corticosteroids (Powell and Everard 1998;
Barnes 2003).
Besides the development of new drags, the importance of early treatment of
asthma symptoms is emerging. Some studies have found that earlier use of inhaled
corticosteriods in people with milder asthma may result in better long-term lung
function and lesser disease severity (Wainwright, Isles et al. 1997; Powell and
Everard 1998; Martinez 1999). Studies in children and adults suggest that this
practice may prevent later development of chronic airway obstruction. Early
corticosteriod therapy is now acknowledged to have a disease modifying effect,
reducing symptoms and improving lung function as well as decreasing
hospitalization (Delfino, Zeiger et al. 1998; Price 2000). However, it is desirable to
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9
use the minimum dose required to control symptoms because of the possible side
effects of slowing growth and affecting bone formation (Price 2000). The long-term
benefit of early treatment has led to the development of more diagnostic tools to
distinguish between infants with early-onset asthma and those with “transient
wheeze” in order to plan treatment more effectively (Martinez 1999).
fi. METHODS
1. Study Design and Subject Selection
The 205 parent reported doctor-diagnosed asthmatic subjects in this study
were a subset of the much larger University of Southern California Children’s Health
Study (CHS) (Peters, Avol et al. 1999; Peters, Avol et al. 1999). Initiated in 1993,
the CHS was designed as a ten-year longitudinal investigation of the respiratory
health of school-age children in southern California. Factors of interest were
students’ respiratory health, patterns of physical activity, and exposure to tobacco
smoke and other forms of air pollution. The study is being conducted in twelve
communities across southern and central California: Atascadero, Santa Maria,
Lompoc, Long Beach, Lancaster, Upland, Mira Loma, San Dimas, Riverside, Lake
Gregory, Lake Elsinore, and Alpine. These communities were selected because they
represented a spectrum of air quality profiles, were roughly similar in socioeconomic
level and had cooperative school district personnel.
Subjects were recruited in local schools. Recruitment presentations were
made in fourth, seventh and tenth grade classrooms. The goal was to obtain at least
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10
90% class participation. Upon entry, parents of the children completed a baseline
questionnaire that extensively probed their child’s respiratory health history,
exposure to tobacco smoke and other elements, and demographic information, The
subjects performed yearly lung function tests at school and completed yearly update
questionnaires. To date, there are over 6000 children who have participated in the
study.
The Supplemental Asthma Information Study (SAIS) was primarily created
to confirm baseline questionnaire responses for doctor-diagnosed asthma. It was
also used to obtain further information about medication use and respiratory
symptoms. Those who completed the SAIS were chosen because they had answered
“yes” to the question, “Has your child ever been diagnosed with asthma by a
doctor?” on the CHS baseline questionnaire. There were 517 out of a total of 3681
participants, or 14%, responding “yes” to doctor-diagnosed asthma in the first year
of CHS recruitment. The SAIS was conducted as a phone interview with a parent of
the CHS participant during the summer of 1993, immediately following the school
year of recruitment. Two hundred and five phone interviews were completed in six
of the twelve CHS communities: Alpine, Lake Elsinore, Lancaster, Lompoc,
Atascadero, and Santa Maria. Data was not gathered on asthmatic subjects living in
the six CHS communities closest to the Los Angeles metro area: Lake Gregory,
Long Beach, Mira Loma, Riverside, San Dimas, and Upland. Data collection efforts
were halted after calling parents in only half of the twelve CHS communities because
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11
the central goal of the study had been accomplished: it was determined that
parental report of doctor diagnosed asthma was highly reproducible.
2. Definition of terms
In this analysis, information about medication use was taken from the SAIS
and baseline CHS questionnaire. The SAIS included a list of types of medications
used to treat asthma as well as brand names and forms of the medications (pill,
liquid, inhaled, etc.). Each medication was identified as taken regularly or taken as
needed. For this analysis, we created new variables to group, respectively, all
inhalers, all beta-agonists, and all steroids. In addition, we created new variables to
identify medications by administration: regular use or used as needed.
A binary variable based exclusively on SAIS information to describe disease
(asthma) status in the child, labeled “asthma history,” was compiled. A single
question on doctor-diagnosed asthma was not included in SAIS. Instead, asthma
history was considered to be present if any one of several criteria were met. First, if
medications were currently taken for asthma, then asthma history was positive. If
there were no medications taken currently, asthma history was considered present for
any one of the following five reasons: an age at last asthma episode was given, the
name of a diagnosing doctor was given, the child had sleeping problems in the past
six months because of asthma or wheezing, the child missed school in the past year
because of asthma or wheezing, or the child had ever been hospitalized for asthma.
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12
Participants were classified for asthma severity by their response to the
CHS baseline question, “Which best describes this child’s current level of asthma
symptoms?” (Table 1). Those responding, “The child has not been troubled by
asthma in the past twelve months” were classified as having no current asthma.
Those responding, “The child has had some asthma in the past twelve months, but
did not take any medication for it” were classified as having mild asthma. Those
choosing the response, “The child has had some asthma in the past twelve months,
requiring medication only for occasional episodes” were placed in the moderate
asthma category. Those responding, “The child has had some asthma in the past
twelve months, requiring medication on a routine basis, but did not have any
episodes while on medication” were classified as having persistent asthma. Finally,
those responding, “The child has had some asthma in the past twelve months,
requiring medication on a routine basis and also had one or more episodes requiring
additional treatment” were placed in the severe asthma category.
In addition, information from both the baseline questionnaire and SAIS were
used to place participants in one of four levels of symptom severity (Table 1). Those
responding “none” to all of the following three questions: wheeze in the last year
(from baseline questionnaire), school absences due to asthma in last year (taken from
SAIS), and nighttime awakening due to asthma symptoms in last 6 months (taken
from SAIS) were classified as having no current asthma. Those reporting wheeze in
the last year, but no school absences and no awakenings at night were placed in the
“wheeze only” category. Those missing 1 -5 days from school or awakened at night
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TABLE 1
DEFINITIONS OF ASTHMA AND SYMPTOM SEVERITY VARIABLES, SAIS 1993
13
Asthma severity:
1. none
2. mild
3. moderate
4. persistent
5. severe
Symptom severity:
1. none
2. wheeze only
3. intermittent
4. persistent
Taken from parent response on CHS baseline questionnaire to describe
current level of asthma
“The child has not been troubled by asthma in the past twelve months.”
“The child has had some asthma in the past twelve months, but did not
take any medication for it,”
“The child has had some asthma in the past twelve months, requiring
medication only for occasional episodes.”
“The child has had some asthma in the past twelve months, requiring
medication on a routine basis, but did not have any episodes while on
medication.”
“The child has had some asthma in the past twelve months, requiring
medication on a routine basis and also had one or more episodes requiring
additional treatment.”
Wheeze information taken from CHS baseline questionnaire,
school absences and nighttime awakenings taken from SAIS questionnaire
no wheeze in the last year, no school absences due to asthma in the last
year, and no nighttime awakenings due to asthma in the last 6 months
Wheeze reported in the last year, but no school absences or nighttime
awakenings due to asthma
1-5 days missed from school in the last year due to asthma, and/or
awakened by asthma 2 times per month or less
6 or more days missed from school in the last year due to asthma and/or
awakened at night once per week or more due to asthma
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14
with symptoms 2 times per month or less because of asthma were classified as
having intermittent symptoms. Finally, those missing 6 or more days from school or
awakened at night once per week because of asthma were classified as having
persistent symptoms.
All demographic data was taken from the CHS baseline questionnaire. Three
age groups, ages 9-11 years, 12-14 years, and 15-17 years, were used according to
the age of the child at entrance into the study (1993). The three cohort groups,
Group A (10th grade), Group B (7th grade), and Group C (4th grade) correspond to
grade in school for 1992-1993. The child’s ethnic or racial background as reported
by the parent was defined as being one of the following three groups: non-Hispanic
white, Hispanic or other ethnicity. The community was the city of residence for the
child at recruitment into the study in 1993. The level of parental education indicated
the education level of the parent completing the baseline questionnaire.
3. Statistical Methods
Comparisons were made to determine if the SAIS group was similar to the
group of all other CHS asthmatics with respect to chosen demographic variables and
asthma severity. We conducted chi-square tests of association between asthmatics
who completed the SAIS phone interview (n-205) and those asthmatics who did not
complete the SAIS (n=312). We also conducted chi-square tests of association
within the six SAIS communities between respondents (n=205) and non-respondents
(n=56).
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15
To assess the consistency of responses to questions concerning doctor
diagnosed asthma and types of medications taken for asthma, we calculated the
percent agreement and Kappa coefficients for responses to selected questions found
on both the baseline questionnaire and the SAIS interview. We compared responses
for medication use in general, inhaler use, steroid use, and existence of doctor-
diagnosed asthma. The Kappa coefficient is used when dealing with discrete
variables to correct for the chance agreement that would occur if the two questions
being compared were completely unrelated. A Kappa coefficient has a range of 0 to
1 with a value of 0 reflecting agreement by chance only and a value of 1 reflecting
perfect agreement (Kelsey, Whittemore et al. 1996).
As a first step in developing a multivariate model to predict medication use,
we conducted univariate tests of association between several demographic variables
and the three subgroups of medication types, broken down further by frequency of
administration. These chi-square tests of association were done for all SAIS subjects
and then limited to those having current asthma only.
Logistic regression analyses were conducted to assess association of
medication use with several demographic and symptomatic independent variables.
Both univariate and multivariate analyses were done to determine which independent
variables were important predictors of medication use. These analyses were done for
all SAIS subjects and then limited to those having current asthma only.
Finally, analyses were done to explore the community-level differences in
medication use. It was hypothesized that these differences might bias the
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16
measurements of the effect of air pollution on lung health. The predicted
probabilities of medication use by city were calculated after controlling for all
variables included in the logistic regression models. This was done for all SAIS
subjects, then limited to those with current asthma only. Next, the community
predicted probabilities for medication use were plotted against the community levels
for four measures of air pollutants for 1993: average maximum ozone, average ozone
level for 10 AM- 6 PM, 24-hour average nitrogen dioxide level, and 24-hour
particulate matter (10 micron) level. The slopes and p-values for these relationships
were determined by modeling the predicted probability by each pollutant. To factor
in the differences in each community’s standard error for predicted probability of
medication use, the model was weighted by the inverse of the variance. The slopes
and p-values were also determined by using the same model, but using only subjects
with no regular steroid use. All analyses were done using Statistical Analyses
System software (SAS v6.12) (1997).
III. RESULTS
There were statistically significant (p<0.05) differences between the group of
SAIS participants and all other CHS participants with doctor diagnosed asthma with
respect to race/ethnicity and asthma severity (Table 2). In general, there tended to be
less racial/ethnic diversity in the SAIS group compared to all other asthmatics in the
CHS. A higher percentage of SAIS participants were white. The SAIS participants
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17
TABLE 2
SELECTED CHARACTERISTICS FOR S.A.I.S. PARTICIPANTS vs. ALL OTHER CHS PARTICIPANTS
WITH DOCTOR DIAGNOSED ASTHMA (1993)
SAIS, n (%) Other CHS with asthma in 1993, n (%)
Variable (total = 205) (total=312) P Value
Age (years)
9-11 89(43.4) 151(48.4) 0.36
12-14 52(25.4) 81(26.0)
15-17 64 (31.2) 80(25.6)
Gender
Male 110(53.7) 180(57.7) 0.37
Female 95 (46.3) 132(42.3)
Cohort
Group A 64 (31.2) 80(25.6) 0.38
Group B 52 (25.4) 83(26.6)
Group C 89 (43.4) 149(47.8)
Race/Ethnicity (1 missing) (4 missing)
Non Hispanic White 143(69.8) 171(54.8) 0.003
Hispanic 38(18.5) 83(26.6)
Other 24(11.7) 58(18.6)
Community*
Alpine 35 (87.5) 5(12.5) 0.41
Lake Elsinore 36(73.5) 13(26.5)
Lancaster 28 (71.8) 11(28.2)
Lompoc 30 (79.0) 8(21.0)
Atascadero 47 (83.9) 9(16.1)
Santa Maria 29 (74.4) 10(25.6)
Health Insurance (4 missing) (6 missing)
Yes 177 (88.1) 277(90.5) 0.66
No 22(10.9) 27(8.8)
Don’t know 2(1.0) 2(0.7)
Parental Education (7 missing)
< 12 grades 16 (7.8) 34(11.2) 0.57
12 grades 48 (23.4) 59(19.3)
Some college 101 (49.3) 145(47.5)
College 20 (9.8) 31(10.2)
Some graduate 20 (9.8) 36(11.8)
Income (22 missing) (54 missing)
< $7,500 12(6.6) 10(3.9) 0.09
$7,500-514,999 11(6.0) 27(10.5)
$15,000-529,999 23 (12.6) 47(18.2)
$30,000-$49,999 50 (27.3) 64(24.8)
$50,000-599,999 77(42.1) 88(34.1)
5100,000+ 10 (5.5) 22(8.5)
Asthma Severity (11 missing) (11 missing)
No current asthma 62 (32.0) 85(28.2) 0.03
Mild 20 (10.3) 13(4.3)
Moderate 61 (31.4) 125(41.5)
Persistent 28 (14.4) 36(12.0)
Severe 23 (11.9) 42(14.0)
*Non respondents in these 6 communities were statistically different in race, education and income.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
18
were more evenly distributed among the categories of severity, and had a higher
percentage of subjects with no current asthma than all other CHS participants with
doctor-diagnosed asthma. There were no statistically significant differences between
the group of SAIS participants and all other asthmatic CHS participants with respect
to age, gender, cohort group, health insurance, parental education, and income.
The percent agreement and Kappa coefficients for responses to similar
questions found on both the baseline questionnaire and the SAIS interview
concerning doctor diagnosed asthma and types of medications taken are reported in
Table 3. For report of asthma medication use we found an agreement of 77.6% with
a Kappa coefficient of 0.51. When comparing baseline report of inhaler use in the
past year with SAIS report of current inhaler use, the agreement was 86.8% with a
Kappa coefficient of 0.73. In addition, we compared the baseline report of steroid
use by pill or shot with current steroid use in any form, including inhalers. We found
an agreement of 81% with a Kappa coefficient of 0.17. In the last check for
consistency, we found that 99% of the SAIS responses agreed with the baseline
response for doctor-diagnosed asthma.
The results of tests of association between medication use and demographic
and asthma symptom variables for all SAIS subjects are shown in Table 4. There
were statistically significant associations (p<0.05) between age and inhaler use and
beta-agonist use. There was also a statistically significant association between some
medication use and race/ethnicity (p=0.03). Whites showed a higher percentage of
subjects using medication compared to other race/ethnicity groups. In addition, there
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
19
TABLE 3
PERCENT AGREEMENT AND SIMPLE KAPPA COEFFICIENTS FOR SELECTED QUESTIONS
Variable
Any medication
use
Inhaler use
Steroid use
Baseline question
(completed Fall 1993)
SAIF question
(completed Summer 1993)
Currently has
asthma or ever had
asthma
“In the past twelve
months, has your child
taken any of the
following medications
for asthma?”
(any/none)
“In the past twelve
months, has your child
taken inhaled
medications for
asthma?” (yes/no)
“In the past twelve
months, has your child
taken any steroids by
pill or shot (e.g.
Prednisone) for
asthma?”
(yes/no)
“Has a doctor ever
diagnosed this child as
having asthma?”
A “yes” response to
this question was the
criteria set for inclusion
in SAIF.
Observed
Agreement
%
Kappa
coefficient
“What medications is your 77.6
child currently taking?”
(any/none)
Is your child currently using 86.8
inhaled medications for
asthma? Specific list of
inhalers supplied at interview
(yes/no)
Is your child currently taking 81.0
steroids for asthma? Brand
names of steroids in various
forms supplied at interview.
(yes/no)
Asthma history assumed if any 99.0
medications were currently
taken or age at last trouble
given or name of diagnosing
doctor given or had sleeping
problems, school days missed
or hospitalization because of
asthma.
.51
.73
.20
N/A
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TABLE 4
MEDICATION USE, S.A.I.S. PARTICIPANTS, 1993
Number (% total), n = 205
Variable
All medication types
No current Any
med use meds
As Used
needed regularly
Inhalers
As Used
Any needed regularly
Beta-agonists
As Used
Any needed regularly
Steroids
As Used
Any needed regularly
All
Age (years)
9-11
12-14
15-17
Gender
Male
Female
Cohort
Group A
Group B
Group C
Race/Ethnicity
Non Hispanic
White
Hispanic
Other
63(30.7) 142(69.3)
32(36.0) 57(64.0)
11(21.2) 41(78.8)
20(31.3) 44(68.7)
p value(2 DF) 0.18
39(35.5) 71(64.5)
24(25.3) 71(74.7)
pvalue(lD F) 0.12
20(31.3) 44(68.7)
11(21.2) 41(78.8)
32(36.0) 57(64.0)
p value(2 DF) 0.18
36(25.2)
16(42.1)
11(45.8)
107(74.8)
22(57.9)
13(54.2)
p value(2 DF) 0.03
101(49.3) 41(20.0)
39(43.8) 18(20.2)
30(57.7) 11(21.1)
32(50.0) 12(18.7)
0.28 0.95
49(44.5) 22(20.0)
52(54.7) 19(20.0)
0.15 1.0
32(50.0) 12(18.7)
30(57.7) 11(21.1)
39(43.8) 18(20.2)
0.28
76(53.1)
15(39.5)
10(41.7)
0.24
0.95
31(21.7)
7(18.4)
3(12.5)
0.56
119(58.0) 99(48.3) 20(9.8)
43(48.3) 34(38.2) 9(10.1)
38(73.1) 30(57.7) 8(15.4)
38(59.4) 35(54.7) 3(4.7)
0.02 0.04 0.15
59(53.6) 48(43.6) 11(10.0)
60(63.2) 51(53.7) 9(9.5)
0.17 0.15 0.90
38(59.4) 35(54.7) 3(4.7)
38(73.1) 30(57.7) 8(15.4)
43(48.3) 34(38.2) 9(10.1)
0.02 0.04 0.15
88(61.5) 72(50.4) 16(11.1)
20(52.6) 17(44.7) 3(7.9)
11(45.8) 10(41.7) 1(4.1)
0.27 0.65 0.61
117(57.1) 95(46.3) 22(10.7)
43(48.3) 33(37.1) 10(11.2)
36(69.2) 28(53.8) 8(15.4)
38(59.4) 34(53.1) 4(6.3)
0.05 0.07 0.28
57(51.8) 45(40.9) 12(10.9)
60(63.2) 50(52.6) 10(10.6)
0.10 0.09 0.93
38(59.4) 34(53.1) 4(6.3)
36(69.2) 28(53.8) 8(15.4)
43(48.3) 33(37.1) 10(11.2)
0.05 0.07 0.28
87(60.8) 71(49.7) 16(11.1)
20(52.6) 15(39.5) 5(13.1)
10(41.7) 9(37.5) 1(4.2)
0.18 0.35 0.51
38(18.5) 20(9.8) 18(8.8)
20(22.5) 11(12.4) 9(10.1)
11(21.2) 6(11.6) 5(9.6)
7(10.9) 3(4.7) 4(6.2)
0.17 0.25 0.69
23(20.9) 13(11.8) 10(9.1)
15(15.8) 7(7.4) 8(8.4)
0.35 0.28 0.87
7(10.9) 3(4.7) 4(6.3)
11(21.2) 6(11.5) 5(9.6)
20(22.5) 11(12.4) 9(10.1)
0.17 0.25 0.69
28(19.6) 13(9.1) 15(10.5)
8(21.1) 6(15.8) 2(5.3)
2(8.3) 1(4.2) 1(4.1)
0.38 0.29 0.42
to
o
Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission.
TABLE 4. continued
MEDICATION USE, S.A.I.S. PARTICIPANTS, 1993
Number (% total), n = 205
All medication types Inhalers Beta-agonists Steroids
Variable
No current Any
med use meds
As
needed
Used
regularly
As Used
Any needed regularly
As Used
Any needed regularly
As Used
Any needed regularly
Community
Alpine
Lake Elsinore
Lancaster
Lompoc
Atascadero
Santa Maria
11(31.4)
17(47.2)
8(28.6)
6(20.0)
11(23.4)
10(34.5)
24(68.6)
19(52.8)
20(71.4)
24(80.0)
36(76.6)
19(65.5)
18(51.4)
12(33.3)
15(53.6)
17(56.7)
24(51.1)
15(51.7)
6(17.2)
7(19.5)
5(17.8)
7(23.3)
12(25.5)
4(13.8)
19(54.3)
17(47.2)
17(60.7)
20(66.7)
33(70.2)
13(44.8)
17(48.6)
15(41.7)
16(57.1)
15(50.0)
26(55.3)
10(34.5)
2(5.7)
2(5.5)
1(3.6)
5(16.7)
7(14.9)
3(10.3)
20(57.1)
16(44.4)
17(60.7)
21(70.0)
31(66.0)
12(41.4)
17(48.6)
14(38.9)
14(50.0)
15(50.0)
25(53.2)
10(34.5)
3(8.5)
2(5.5)
3(10.7)
6(20.0)
6(12.8)
2(6.9)
4(11.4)
6(16.7)
2(7.1)
7(23.3)
12(25.5)
7(24.1)
3(8.6)
3(8.3)
1(3.6)
4(13.3)
5(10.6)
4(13.8)
1(2.9)
3(8.3)
1(3.6)
3(10.0)
7(14.9)
3(10.3)
p value(5 DF) 0.18 0.45 0.86 0.16 0.46 0.39 0.11 0.59 0.54 0.27 0.80 0.47
Health Insurance
Yes
No
51(28.8)
12(50.0)
126(71.2)
12(50.0)
89(50.3)
9(37.5)
37(20.9)
3(12.5)
105(59.3)
10(41.7)
17(9.6) 88(49.7)
3(12.5) 7(29.2)
104(58.8)
9(37.5)
83(46.9)21(11.9)
8(33.3) 1(4.2)
35(19.8)
2(8.3)
20(11.3)
0(0.0)
15(8.5)
2(8.3)
p value(l DF) 0.04 0.24 0.33 0.10 0.66 0.06 0.05 0.21 0.26 0.26 0.14 1.0
Parental Education
< 12 grades
12 grades
Some college
College
Some graduate
7(43.8)
13(27.1)
31(30.7)
8(40.0)
4(20.0)
9(56.2)
35(72.9)
70(69.3)
12(60.0)
16(80.0)
7(43.7)
23(47.9)
50(49.5)
9(45.0)
12(60.0)
2(12.5)
12(25.0)
20(19.8)
3(15.0)
4(20.0)
9(56.3)
30(62.5)
55(54.5)
11(55.0)
14(70.0)
8(50.0)
24(50.0)
47(46.6)
10(50.0)
10(50.0)
1(6.3)
6(12.5)
8(7.9)
1(5.0)
4(20.0)
9(56.3)
27(56.3)
56(55.5)
12(60.0)
13(65.0)
7(43.8)
22(45.8)
47(46.6)
10(50.0)
9(45.0)
2(12.5)
5(10.5)
9(8.9)
2(10.0)
4(20.0)
2(12.5)
11(22.9)
20(19.8)
2(10.0)
3(15.0)
1(6.3) 1(6.2)
5(10.4) 6(12.5)
12(11.9) 8(7.9)
1(5.0) 1(5.0)
1(5.0) 2(10.0)
p value(4DF) 0.48 0.86 0.85 0.70 0.99 0.45 0.95 0.99 0.65 0.78 0.92 0.86
Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission.
TABLE 4, continued
MEDICATION USE, S.A.I.S. PARTICIPANTS, 1993
Number (% total), n = 205
Variable
AH medication types
No current Any
med use meds
As Used
needed regularly
Inhalers
As Used
Any needed regularly
Beta-agonists
As Used
Any needed regularly
Steroids
As Used
Any needed regularly
Income
< $7,500
$7,500-514,999
$15,000-529,999
$30,000-549,999
$50,000-599,999
$ 100,000+
Symptom Severity
No symptoms
Wheeze only
Intermittent sympt.
Persistent sympt.
School Days
Missed Last Yr.
For Asthma
Don’t know
0 days
I-5 days
6-10 days
II-20 days
21-30 days
30+ days
3(25.0)
3(27.3)
12(52.2)
12(24.0)
24(31.2)
4(40.0)
9(75.0)
8(72.7)
11(47.8)
38(76.0)
53(68.8)
6(60.0)
p value(5DF) 0.27
27(66.4) 17(38.6)
23(39.7) 35(60.3)
12(19.4) 50(80.6)
1(2.4) 40(97.6)
p value(3DF) <0.001
3(100.0)
51(42.5)
9(17.6)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
4(33.3)
8(72.7)
7(30.4)
29(58.0)
42(54.6)
3(30.0)
0.06
5(41.7)
0(0.0)
4(17.4)
9(18.0)
11(14.2)
3(30.0)
0.24
13(29.5) 4(9.1)
24(41.4) 11(18.9)
42(67.7) 8(12.9)
22(53.7) 18(43.9)
< 0.001 < 0.001
0(0.00)
69(57.5)
42(82.4)
12( 100.0)
11( 100.0)
7(100.0)
1( 100.0)
p value(6DF) <0.001
0(0.0)
50(41.7)
34(66.7)
7(58.3)
6(54.6)
4(57.1)
0(0.0)
0.02
0(0.0)
19(15.8)
8(15.7)
5(41.7)
5(45.5)
3(42.9)
1( 100.0)
0.01
8(66.7) 5(41.7) 3(25.0)
6(54.6) 6(54.6) 0(0.0)
9(39.1) 7(30.4) 2(8.7)
34(68.0) 30(60.0) 4(8.0)
40(52.0) 36(46.8) 4(5.2)
6(60.0) 3(30.0) 3(30.0)
0.24 0.19 0.05
4(9.1) 4(9.1) 0(0.0)
31(53.5) 25(43.1) 6(10.4)
45(72.6) 40(64.5) 5(8.1)
39(95.1) 30(73.1) 9(22.0)
<0.001 <0.001 <0.008
0(0.0)
52(43.3)
37(72.6)
12(100.0)
11( 100.0)
6(85.7)
1( 100.0)
0(0.0)
43(35.8)
32(62.8)
11(91.7)
9(81.8)
4(57.1)
0(0.0)
0(0.0)
9(7.5)
5(9.8)
1(8.3)
2(18.2)
2(28.6)
1( 100.0)
<0.001 <0.001 0.08
7(58.3)
6(54.6)
9(39.1)
4(33.3) 3(25.0)
6(54.6) 0(0.0)
7(30.4) 2(8.7)
41(53.3) 37(48.1) 4(5.2)
6(60.0) 4(40.0) 2(20.0)
0.41 0.44 0.12
5(11.4) 4(9.1) 1(2.3)
30(51.7) 25(43.1) 5(8.6)
43(69.4) 39(62.9) 4(6.5)
39(95.1) 27(65.9) 12(29.2)
< 0.001 < 0.001 < 0.001
4(33.3) 1(8.3) 3(25.0)
1(9.1) 1(9.1) 0(0.0)
5(21.7) 4(17.4) 1(4.3)
8(16.0) 4(8.0) 4(8.0)
10(13.0) 5(6.5) 5(6.5)
3(30.0) 1(10.0) 2(20.0)
0.34 0.60 0.16
5(11.4) 3(6.8) 2(4.6)
7(12.1) 2(3.5) 5(8.6)
9(14.5) 7(11.3) 2(3.2)
17(41.5) 8(19.5) 9(22.0)
0(0.0)
51(42.5)
36(70.6)
12( 100.0 )
11( 100.0)
7(100.0)
0(0.0)
0(0.0)
42(35.0)
32(62.8)
8(66.7)
8(72.7)
5(71.4)
0(0.0)
0(0.0)
9(7.5)
4(7.8)
4(33.3)
3(27.3)
2(28.6)
0(0.0)
<0.001 <0.001 0.03
<0.001 0.054 >0.007
0(0.0) 0(0.0) 0(0.0)
14(11.7) 6(5.0) 8(6.7)
11(21.6) 7(13.7) 4(7.8)
2(16.7) 1(8.3) 1(8.3)
7(63.6) 5(45.5) 2(18.1)
3(42.9) 1(14.3) 2(28.6)
1( 100.0) 0(0 .0) 1( 100.0)
<0.001 0.007 0.055
to
to
Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission.
TABLE 4. continued
MEDICATION USE, S.A.I.S. PARTICIPANTS, 1993
Number (% total), n = 205
All medication types Inhalers Beta-agonists Steroids
Variable
No current Any
med use meds
As
needed
Used
regularly
As Used
Any needed regularly
As Used
Any needed regularly Any
As
needed
Used
regularly
Awakened at
Night (last 6 mo.)
Never
2X/mo. or less
lX/wk.
2-3X/wk.
nightly
59(44.0) 75(56.0)
3(5.9) 48(94.1)
0(0.0) 8(100.0)
1(10.0) 9(90.0)
0(0.0) 2(100.0)
8(43.3)
33(64.7)
3(37.5)
5(50.0)
2(100.0)
17(12.7)
15(29.4)
5(62.5)
4(40.0)
0(0.0)
56(41.8) 48(35.8) 8(6.0)
45(88.2) 39(76.4) 6(11.8)
8(100.0) 3(37.5) 5(62.5)
8(80.0) 7(70.0) 1(10.0)
2(100.0) 2(100.0) 0(0.0)
56(41.8) 48(35.8) 8(6.0)
42(82.4) 35(68.7) 7(13.7)
8(100.0) 4(50.0) 4(50.0)
9(90.0) 6(60.0) 3(30.0)
2(100.0) 2(100.0) 0(0.0)
17(12.7)
12(23.5)
6(75.0)
3(30.0)
0(0.0)
9(6.7)
8(15.7)
1(12.5)
2(20.0)
0(0.0)
8(6.0)
4(7.8)
5(62.5)
1(10.0)
0(0.0)
p value(4DF) <0.001 0.04 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001
to
O J
24
was a statistically significant association between any medication use and beta-
agonist use, in particular, with having health insurance (p=0.04, p=0.05,
respectively). As was expected, there were statistically significant associations
between symptom severity and medication use in general, symptom severity and
inhaler use, symptom severity and beta-agonist use, and symptom severity and
steroid use (all pO.OOOl). There were no statistically significant associations
between medication use and the following demographic variables: gender,
community, parental education and income.
The results of tests of association between medication use and demographic
and asthma symptom variables among current asthmatics only are shown in Table 5.
There were statistically significant (p<0.05) associations between any medication use
and health insurance (p=0.03), and any medication use and symptom severity
(p<0.0012). Also, it should be noted that community and income were close to
statistical significance in their association with any medication use (community,
p=0.07, income, p=0.06). Other statistically significant associations were between
any beta-agonists taken and health insurance (p=0.04), income and regular inhaler
use (p=0.015), and symptom severity with several independent variables:
medications taken as needed (p=0.04), medications taken regularly (p=0.006), any
inhalers used (pO.OOOl), any beta-agonists taken (p=0.001), regular beta-agonist use
(p=0.01), any steroids taken (p=0.005) and regular steroid use (p=0.03). A
marginally significant association was found between any beta-agonists taken and
community (p=.Q5).
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission.
TABLE 5
MEDICATION USE, S.A.I.S. WITH CURRENT ASTHMA ONLY
Number (% total), n = 132
Variable
All medication types Inhalers Beta-agonists Steroids
No current
med use
Any
meds
As
needed
Used
regularly
As Used
Any needed regularly Any
As
needed
Used
regularly
As Used
Any needed regularly
All 19(14.4) 113(85.6) 75(56.8) 38(28.8) 107(81.1) 87(65.9) 20(15.2) 104(78.8) 82(62.1) 22(16.7) 33(25.0) 17(12.9) 16(12.1)
Age (years)
9-11
12-14
15-17
8(15.1)
5(12.5)
6(15.4)
45(84.9)
35(87.5)
33(84.6)
28(52.8)
25(62.5)
22(56.4)
17(32.1)
10(25.0)
11(28.2)
41(77.4)
34(85.0)
32(82.1)
32(60.4)
26(65.0)
29(74.4)
9(17.0)
8(20.0)
3(7.7)
39(73.6)
33(82.5)
32(82.1)
29(54.7) 10(18.9)
25(62.5) 8(20.0)
28(71.8) 4(10.3)
17(32.1)
10(25.0)
6(15.4)
9(17.0)
5(12.5)
3(7.7)
8(15.1)
5(12.5)
3(7.7)
p value 0.92 0.65 0.75 0.64 0.37 0.28 0.49 0.25 0.44 0.19 0.42 0.56
Gender
Male
Female
11(16.2)
8(12.5)
57(83.8)
56(87.5)
37(54.4)
38(59.4)
20(29.4)
18(28.1)
53(77.9)
54(84.4)
42(61.7)
45(70.3)
11(16.2)
9(14.1)
51(75.0)
53(82.8)
39(57.4) 12(17.6)
43(67.2) 10(15.6)
20(29.4) 12(17.7)
13(20.3) 5(7.8)
8(11.7)
8(12.5)
p value 0.55 0.57 0.87 0.35 0.30 0.74 0.27 0.24 0.76 0.23 0.09 0.90
Cohort
Group A
Group B
Group C
6(15.4)
5(12.5)
8(15.1)
33(84.6)
35(87.5)
45(84.9)
22(56.4)
25(62.5)
28(52.8)
11(28.2)
10(25.0)
17(32.1)
32(82.1)
34(85.0)
41(77.4)
29(74.4)
26(65.0)
32(60.4)
3(7.7)
8(20.0)
9(17.0)
32(82.1)
33(82.5)
39(73.6)
28(71.8) 4(10.3)
25(62.5) 8(20.0)
29(54.7) 10(18.9)
6(15.4)
10(25.0)
17(32.1)
3(7.7)
5(12.5)
9(17.0)
3(7.7)
5(12.5)
8(15.1)
p value 0.92 0.65 0.75 0.64 0.37 0.28 0.49 0.25 0.44 0.19 0.42 0.56
Race/Ethnicity
Non Hispanic
White
Hispanic
Other
12(12.6)
4(16.7)
3(23.1)
83(87.4)
20(83.3)
10(76.9)
54(56.8)
13(54.2)
8(61.5)
29(30.6)
7(29.1)
2(15.4)
79(83.2)
18(75.0)
10(76.9)
63(66.3)
15(62.5)
9(69.2)
16(16.9)
3(12.5)
1(7.7)
76(80.0)
18(75.0)
10(76.9)
60(63.2) 16(16.8)
13(54.2) 5(20.8)
9(69.2) 1(7.7)
24(25.3) 11(11.6)
8(33.3) 6(25.0)
1(7.7) 0(0.0)
13(13.7)
2(8.3)
1(7.7)
p value 0.47 0.91 0.53 0.55 0.91 0.79 0.85 0.62 0.64 0.23 0.09 0.91
Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission.
TABLE 5. continued
MEDICATION USE, S.A.I.S. WITH CURRENT ASTHMA ONLY
Number (% total), n = 132
All medication types Inhalers Beta-agonists Steroids
Variable No current Any As Used As Used As Used As Used
med use meds needed regularly Any needed regularly Any needed regularly Any needed regularly
Community
Alpine 2(10.0) 18(90.0) 12(60.0) 6(30.0) 17(85.0) 15(75.0) 2(10.0) 17(85.0) 14(70.0) 3(15.0) 4(20.0) 3(15.0) 1(5.0)
Lake Elsinore 8(36.3) 14(63.6) 8(36.4) 6(27.3) 14(63.6) 12(54.6) 2(9.1) 13(59.1) 11(50.0) 2(9.1) 5(22.7) 3(13.6) 2(9.1)
Lancaster 2(10.5) 17(89.5) 13(68.4) 4(21.1) 16(84.2) 15(79.0) 1(5.3) 16(84.2) 13(68.4) 3(15.8) 1(5.3) 1(5.3) 0(0.0)
Lompoc 1(5.0) 19(95.0) 13(65.0) 6(30.0) 18(90.0) 13(65.0) 5(25.0) 19(95.0) 13(65.0) 6(30.0) 6(30.0) 3(15.0) 3(15.0)
Atascadero 3(8.8) 31(91.2) 19(55.6) 12(35.3) 30(88.2) 23(67.7) 7(20.6) 28(82.4) 22(64.7) 6(17.7) 11(32.4) 4(11.8) 7(20.6)
Santa Maria 3(17.8) 14(82.4) 10(58.8) 4(23.5) 12(70.6) 9(52.9) 3(17.7) 11(64.7) 9(52.9) 2(11.8) 6(35.3) 3(17.7) 3(17.7)
p value 0.07 0.38 0.93 0.19 0.46 0.46 0.05 0.72 0.64 0.22 0.91 0.23
Health Insurance
Yes 14(12.2) 101(87.8) 67(58.2) 34(29.6) 95(82.6) 78(67.8) 17(14.8) 93(80.9) 72(62.6) 21(18.3) 30(26.1) 17(14.8) 13(11.3)
No 5(38.5) 8(61.5) 5(38.5) 3(23.0) 8(61.5) 5(38.5) 3(23.0) 7(53.9) 6(46.2) 1(7.7) 2(15.4) 0(0.0) 2(15.4)
p value 0.03 0.24 0.76 0.13 0.06 0.43 0.04 0.37 0.47 0.52 0.21 0.65
Parental Education
< 12 grades 2(18.2) 9(81.8) 7(63.6) 2(18.2) 9(81.8) 8(72.7) 1(9.1) 9(81.8) 7(63.6) 2(18.2) 2(18.2) 1(9.1) 1(9.1)
12 grades 7(19.4) 29(80.6) 17(47.2) 12(33.3) 27(75.0) 21(58.3) 6(16.7) 24(66.7) 19(52.8) 5(13.9) 10(27.8) 4(11.1) 6(16.7)
Some college 7(11.5) 54(88.5) 37(61.0) 17(27.9) 51(83.6) 43(70.5) 8(6.1) 50(82.0) 41(67.2) 9(14.8) 17(27.9) 11(18.0) 6(9.8)
College 2(15.4) 11(84.6) 8(61.5) 3(23.1) 10(76.9) 9(69.2) 1(7.7) 11(84.6) 9(69.2) 2(15.4) 2(15.4) 1(7.7) 1(7.7)
Some graduate 1(9.1) 10(90.9) 6(54.6) 4(36.4) 10(90.9) 6(54.6) 4(36.4) 10(90.1) 6(54.6) 4(36.4) 2(18.2) 0(0.0) 2(18.2)
p value 0.80 0.73 0.85 0.75 0.66 0.36 0.38 0.61 0.50 0.88 0.61 0.86
to
o \
Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission.
TABLE 5. continued
MEDICATION USE, S.A.I.S. WITH CURRENT ASTHMA ONLY
Number (% total), n = 132
All medication types Inhalers Beta-agonists Steroids
Variable No current Any
med use meds
As
needed
Used
regularly
As Used
Any needed regularly
As Used
Any needed regularly
As Used
Any needed regularly
Income
< $7,500
$7,500-514,999
$15,000-$29,999
$30,000-549,999
$50,000-599,999
$100,000+
1(11.1)
1(16.7)
6(40.0)
3(8.6)
4(9.8)
4(25.0)
8(88.9)
5(83.3)
9(60.0)
32(91.4)
37(90.2)
6(75.0)
3(33.3)
5(83.3)
6(40.0)
23(65.7)
28(68.3)
3(37.5)
5(55.6)
0(0.0)
3(20.0)
9(25.7)
9(22.0)
3(37.5)
8(88.9 5(55.6)
5(83.3) 5(83.3)
9(60.0) 7(46.7)
30(85.7) 26(74.3)
34(82.9) 30(73.2)
6(75.0) 3(37.5)
3(33.3)
0(0.0)
2(13.3)
4(11.4)
4(9.8)
3(37.5)
7(77.8) 4(44.4)
5(83.3) 5(83.3)
9(60.0) 7(46.7)
30(85.7)24(68.6)
33(80.5) 29(70.7)
6(75.0) 4(50.0)
3(33.3)
0(0.0)
2(13.3)
6(17.4)
4(9.8)
2(25.0)
4(44.4)
1(16.7)
5(33.3)
6(17.4)
7(17.1)
3(37.5)
1(11.1) 3(33.3)
1(16.7) 0(0.0)
4(26.7) 1(6.7)
2(5.7) 4(11.4)
4(9.8) 3(7.3)
1(12.5) 2(25.0)
p value 0.06 0.09 0.22 0.39 0.13 .015 0.47 0.29 0.38 0.28 0.31 0.19
Symptom Severity
No symptoms
Wheeze only
Intermittent
Persistent
1(25.0)
12(28.6)
6(12.0)
0(0.0)
3(75.0)
30(71.4)
44(88.0)
36(100.0)
2(50.0)
19(45.2)
36(72.0)
18(50.0)
1(25.0)
11(26.2)
8(16.0)
18(50.00)
2(50.0) 2(50.0)
29(69.1) 23(54.8)
40(80.0) 35(70.0)
36(100.0) 27(75.0)
0(0.0)
6(14.3)
5(10.0)
9(25.0)
2(50.0) 1(25.0)
28(66.7) 23(54.8)
39(78.0) 35(70.0)
35(97.2) 23(63.9)
1(25.0)
5(11.9)
4(8.0)
12(33.3)
1(25.0)
7(16.7)
8(16.0)
17(47.2)
1(25.0)
2(4.8)
6(12.0)
8(22.2)
0(0.0)
5(11.9)
2(4.0)
9(25.0)
p value 0.0012 0.04 0.006 <0.0001 0.19 0.29 0.001 0.19 0.01 0.005 0.08 0.03
N 3
• 'O
Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission.
TABLE 5, continued
MEDICATION USE, S.A.I.S. WITH CURRENT ASTHMA ONLY
Number (% total), n = 132
Variable
All medication types
No current Any
med use meds
As Used
needed regularly
Inhalers
As Used
Any needed regularly
Beta-agonists
As Used
Any needed regularly
Steroids
As Used
Any needed regularly
School Days Missed
Last Yr. For Asthma
Don’t know
0 days
1 -5 days
6-10 days
11-20 days
21-30 days
30+ days
Awakened at Night
(last 6 mo.)
Never
2X/mo. or less
lX/wk.
2-3X/wk.
Nightly
1( 100.0)
13(21.0)
5(12.2)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
p value
18(25.7)
1(2 .2)
0(0.0)
0(0.0)
0(0.0)
p value
0(0.00)
49(79.0)
42(87.8)
11( 100.0)
10(100.0)
6(100.0)
1( 100.0)
0.11
52(74.3)
44(97.8)
8( 100.0)
8( 100.0)
1( 100.0)
0.001
0(0.0)
33(53.2)
28(68.3)
6(54.6)
5(50.0)
3(50.0)
0(0.0)
0.46
0(0.0)
16(25.8)
8(19.5)
5(45.5)
5(50.0)
3(50.0)
1( 100.0)
0.09
38(54.3) 14(20.0)
29(64.4) 15(33.3)
3(37.5) 5(62.5)
4(50.0) 4(50.0)
1( 100.0) 0(0.0)
0.49 0.03
0(0.0) 0(0.0)
47(75.8) 38(61.3)
32(78.1) 27(65.9)
11(100.0) 10(91.0)
10(100.0) 8(80.0)
6(100.0) 4(66.7)
1(100.0) 0(0.0)
0.08 0.19
0(0.0)
9(14.5)
5(12.2)
1(9.1)
2(20.0)
2(33.3)
1( 100.0)
0.29
49(70.0) 41(58.6) 8(11.4)
41(91.1) 35(77.8) 6(13.3)
8(100.0) 3(37.5) 5(62.5)
8(100.0) 7(87.5) 1(12.5)
1( 100.0) 1( 100.0) 0(0 .0)
0.01 0.04 0.02
0(0.0) 0(0.0) 0(0.0)
45(72.6) 36(58.1) 9(14.5)
32(78.1) 28(68.3) 4(9.8)
11(100.0) 7(63.6) 4(36.4)
10(100.0) 7(70.0) 3(30.0)
6(100.0) 4(66.7) 2(33.3)
0(0.0) 0(0.0) 0(0.0)
0.01 0.64 0.17
49(70.0) 41(58.6) 8(11.4)
38(84.4) 31(68.9) 7(15.6)
8(100.0) 4(50.0) 4(50.0)
8(100.0) 5(62.5) 3(37.5)
1( 100.0) 1( 100.0) 0 (0 .0)
0.07 0.70 0.03
0(0.0) 0(0.0) 0(0.0)
10(16.1) 4(6.5) 6(9.7)
10(24.4) 6(14.6) 4(9.8)
2(18.2) 1(9.1) 1(9.1)
7(70.0) 5(50.0) 2(20.0)
3(50.0) 1(16.7) 2(33.3)
1( 100.0) 0(0 .0) 1( 100.0)
0.001 0.03 0.13
12(17.1) 6(8.6) 6(8.6)
12(26.7) 8(17.8) 4(8.9)
6(75.0) 1(12.5) 5(62.5)
3(37.5) 2(25.0) 1(12.5)
0(0.0) 0(0.0) 0(0.0)
<0.001 0.34 0.001
to
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29
Next, a multivariate model to predict medication use was developed. The
three independent variables found to be statistically significant predictors of
medication use in univariate models were race, health insurance, and symptom
severity (Table 6). Adjustment variables included in the multivariate model were
age, symptom severity and community. Community was not a statistically significant
predictor of medication use in a univariate model, but was included because it was
discovered to be a confounder of the effect of race and health insurance on predicting
medication use. Specifically, when community was included in the model, the point
estimates for race and health insurance changed 13% and 16%, respectively. Table 6
shows the odds ratios and 95% confidence intervals for all variables included in the
model. Among all SAIS subjects, after adjusting for age, town, insurance and
symptom severity, Hispanics were 4.2 times less likely to use medication than non-
Hispanic whites (OR 4.2, 95% Cl: 1.6-11.1). Other minorities were 4.6 times less
likely to use medication than non-Hispanic whites (OR 4.6, 95% Cl: 1.5-12.5).
Finally, to further explore the role of community differences in medication
use on the effect air pollution has on children’s respiratory symptoms; a two-stage
model was developed. Using the previously outlined model to predict medication
use on an individual level, the predicted probabilities for medication use for each
town, after adjusting for age, race, insurance and symptom severity were calculated
(Table 7). Next, these probabilities were plotted against two 1993 measures of
ozone, one 1993 measure of nitrogen dioxide and one measure of particulate matter
for the six CHS communities with SAIS data (Figures 1-4). The slopes and p-values
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
30
TABLE 6
ADJUSTED ODDS RATIOS AND 95% CONFIDENCE INTERVALS FOR CURRENT
MEDICATION USE, 1993
All SAIF participants Only participants with
current asthma
Variable* Med use
No/Yes (n)
Current medication
use
OR and 95% Cl
Med use
No/Yes
(n)
Current medication
use
OR and 95% Cl
Race/Ethnicity
Non Hispanic
White
Hispanic
Other
36/107
16/22
11/13
1
0.24 (0.09-0.64)
0.22 (0.08-0.66)
12/83
4/20
3/10
1
0.43 (0.09-2.06)
0.37 (0.06-2.17)
Health Insurance
No
Yes
12/12
51/126
1
2.52 (0.82-7.69)
5/8
14/101
1
2.53 (0.48-13.31)
Age (years)
9-11
12-14
15-17
32/57
11/41
20/44
1
1.57 (0.63-3.96)
1.31 (0.58-2.95)
8/45
5/35
6/33
1
1.15 (0.30-4.37)
1.63 (0.40-6.62)
Community
Alpine
Lake Elsinore
Lancaster
Lompoc
Atascadero
Santa Maria
11/24
17/19
8/20
6/24
11/36
10/19
1
1.06 (.034-3.31)
1.75 (0.48-6.40)
2.96 (0.77-11.48)
2.08 (.067-6.49)
2.58 (0.69-9.69)
2/18
8/14
2/17
1/19
3/31
3/14
1
0.60 (0.09-4.10)
1.40 (0.15-12.66)
2.73 (0.20-37.39)
1.66 (0.24-11.64)
1.24 (0.13-12.24)
Symptom Severity
No current
symptoms or
wheeze only
Asthma symptoms
50/52
13/90
1
7.56 (3.43-16.66)
13/33
6/80
1
4.32 (1.29-14.52)
*A 11 variables are mutually adjusted for each other.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
TABLE 7
BY COMMUNITY, PREDICTED PROBABILITY FOR CURRENT
MEDICATION USE, 1993
Community*
Current medication use
among all SAIF participants
Current medication use
among those with current
asthma only
Alpine 0.25 0.54
Lake Elsinore 0.26 0.41
Lancaster 0.37 0.62
Lompoc 0.50 0.76
Atascadero 0.41 0.66
Santa Maria 0.46 0.59
*adjusted for age, race, insurance, symptom severity, baseline is for age 9-12,
white non-Hispanic, no insurance, no symptoms
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
32
FIGURE 1
PREDICTED PROBABILITY OF MED USE BY OZONE, 10-6
CURRENT ASTHMATICS, 1993
< L >
•S
■ O
e
&
T 3
< U
o
■ f t
K
ft
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
♦
Santa Maria
♦ Lompoc
Atascadero
Lancaster
y = -Q.0G48x + 0.8128
R2 = 0.2305
p>0.29
Alpine
^ Lake Elsinore
20 40 60
1993 average ozone, 10 am-6 pm
80
FIGURE 2
PROBABILITY OF MED USE BY MAX OZONE
CURRENT ASTHMATICS, 1993
0.8 - ]
u ♦
0 0
S
0.7 -
_ Lompoc
-o
♦ Atascadero
1 0.6 -
♦ Lancaster
V h
O
> > 0.5 -
Santa M aria
m i ' Alpine
1
0.4 -
♦
J D
y = -0.0044x + 0.8419
Lake Elsinore
S
cx
0.3 -
"d
0.2 -
R2 = 0.3391
o
'O
0.1 -
p>0.21
4 )
h *
cx
0
0 20 40 60 80
Max o3 for 1993
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
33
FIGURE 3
PROBABILITY OF MED USE BY NITROGEN DIOXIDE, 24 hr
CURRENT ASTHMATICS, 1993
C L h
0.8
0.7
0.6
0.5
0.4 - I
0.3
0.2
0.1
0
0
♦ Lompoc
♦ Atascadero
♦
Santa Maria
y = -0.015x+0.8029
R2 = 0.4762
p>0.15
♦ Lancaster
♦
Lake Elsinore
5 10 15 20
N 02 24 hr. yearly average
25
FIGURE 4
PROBABILITY OF MED USE BY PM10, 24 hr
CURRENT ASTHMATICS, 1993
0.7
3
T 3
H
O
i d
4 3
O
0.5
0.4
0.3
0.2
4 Atascadero
♦ Lancaster
Santa Maria
♦
Lake Elsinore
y=-0.0084x + 0.836
R2 = 0.6174
p>0.17
0.1
10 20 30
PM 10 24 hr. yearly average
40 50
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
34
for these relationships were determined by modeling the predicted probability by
each pollutant. To factor in the differences in each community’s standard error for
predicted probability of medication use, the model was weighted by the inverse of
the variance for each community’s beta value from the first-stage model predicting
medication use. We also did the analysis without a weighted variable. We found no
statistically significant relationship between probability of medication use and
ambient air pollution level of ozone, nitrogen dioxide or particulate matter. Finally,
the two stage analysis was done after omitting subjects reporting regular steroid use.
Delfino, et al reported that regular use of steroids minimizes the effect of ozone
levels on asthma symptoms (Delfino, Zeiger et al. 1998). In this case, sixteen
subjects out of 132 current asthmatics were omitted to determine if the relationship
between ozone level and community predicted probability of asthma medication use
would become statistically significant. Again, the relationship was not statistically
significant.
IV. DISCUSSION
Analysis of the SAIS data was performed to assess the reproducibility of
baseline questionnaire responses for doctor-diagnosed asthma and medication use, to
obtain further information about medication use and respiratory symptoms, and to
assess inter-community variations in medication use. The limitations of this analysis
of medication use in Southern California school children in 1993 are as follows.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
35
Data on medication use was gathered in only six of the twelve communities
in the CHS. The cities closest to the Los Angeles basin were not included. Having
data from all twelve communities would have provided a more complete picture of
medication use in the region and likely would have included more minority
participants. Data collection efforts were halted after calling parents in only half of
the twelve CHS communities because the central goal of the study had been
accomplished: it was determined that parental report of doctor diagnosed asthma was
highly reproducible. Respondents within the six SAIS communities were
significantly different from non-respondents with respect to race, income and
education. More respondents tended to be white, better educated and in higher
income groups than non-respondents in the six SAIS communities.
When comparing responses between the CHS baseline questionnaire and the
SAIS form, we found that parents were consistent in reporting doctor-diagnosed
asthma in their child. There was a ninety-nine percent agreement between the CHS
baseline questionnaire and the SAIS phone interview for ever having asthma. It
must be noted that the selection criteria for inclusion in SAIS was report of doctor-
diagnosed asthma on the baseline questionnaire. A better assessment for the
reproducibility of this response would include subjects that responded “no” to
doctor-diagnosed asthma at baseline. Also, there were some limitations to consider
in evaluating the reproducibility of the other three responses about inhaler use,
steroid use and any medication taken, in general. First, time references were
different between the two sources of data. The baseline questionnaire asked about
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
36
medications taken for asthma in the last 12 months, broken down by general
category. In contrast, the SAIS form asked for medications currently taken for
asthma, listed by brand name and type. We believe differences in time references
between the two questionnaires had minimal impact on the reproducibility of inhaler
use responses because inhalers tend to be used intermittently. They are kept on hand
and used as needed. Also, inhalers are easily recognizable and familiar in families of
asthmatics. Parents were fairly consistent in reporting inhaler use (observed
agreement=86.8%, Kappa=0.73). In contrast, reports for medication use in general
and steroid use, specifically, had relatively low agreements (observed
agreement=77.6, Kappa-0.51 for medication use and observed agreem ent^ 1 %,
Kappa=0.17 for steroid use). We postulate that the low agreement levels could be
caused by differences in time references between the two questionnaires and, in the
case of steroid use, also by differences in the type of information requested on each
source of data. The baseline questionnaire asked only for steroids administered by
pill or shot. The SAIS form asked for steroids taken orally or by an inhaler. Report
of steroid use on the SAIS was almost exclusively from steroid inbalers, a
medication not included on the baseline questionnaire. Therefore, we would expect
a Kappa value close to 0 for steroid use.
Using multivariate analyses, our data show that Hispanics were 4.2 times less
likely to use medication than non-Hispanic whites (95% Cl: 1.6-11.1). Other
minorities were 4.6 times less likely to use medication than non-Hispanic whites
(95% Cl: 1.5-12.5). Among current asthmatics only, Hispanics were 2.3 times less
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
37
likely to use medication (95% Cl: 0.5-11.1), and other minorities were 2.7 times
less likely to use asthma medications than non-Hispanic whites (95% Cl: 0.5-16.7).
In addition, children with health insurance were 2.5 times more likely to be taking
medications, after adjusting for age, race, town, and symptom severity, than those
with no health insurance (95% Cl: 0.82-7.69) (95% Cl: 0.48-6.62). The confidence
limits for our findings that predict medication use for minorities and for having
health insurance prevent us from reporting any statistically significant relationships,
except for the group of all SAIS subjects regarding their minority status. However,
these findings are consistent with several other studies reporting that minorities tend
to be under-treated for asthma symptoms (Gem, Schroth et al. 1995; Giuntini and
Paggiaro 1995; Williams 1997; Powell and Everard 1998).
Next, in our investigations examining the effect of air pollutants on children’s
respiratory health, it appeared that the community-specific predicted probabilities for
medication use was inversely related to community levels of ozone, nitrogen dioxide
and particulate matter, but the relationships were not statistically significant. We
theorize that the differences in community predicted probabilities for medication use
are due to community differences in doctors’ treatment of asthma symptoms.
Delfino, et al reported that regular use of steroids minimizes the effect of ozone
levels on asthma symptoms (Delfino, Zeiger et al. 1998). If this were the case in the
CHS cohort, then we would expect to see a disproportionately strong association
between ozone levels and asthma symptoms. Upon further analyses, including
omission of subjects who regularly use steroids (m=16 of 205), we found that the
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
38
inverse relationships of predicted probability of medication use and ambient air
pollutant levels were all non-significant.
In summary, we conclude that, upon review, questionnaire-based information
from the CHS is reproducible regarding parental report of doctor-diagnosed asthma
and inhaler use. In addition, these data show that Hispanics were 4.2 times less
likely to use medication than non-Hispanic whites (OR 0.24, 95% Cl: 0.09-0.64),
and other minorities were 4.6 times less likely to use medication than non-Hispanic
whites (OR 0.22, 95% Cl: 0.08-0.66). Finally, it appeared that differences existed
between communities with respect to asthma medication use, but we did not see
statistically significant relationships with community air pollution levels.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
39
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Asset Metadata
Creator
Grossman, Lisa Giltner
(author)
Core Title
A descriptive analysis of medication use by asthmatics in the Children's Health Study, 1993
School
Graduate School
Degree
Master of Science
Degree Program
Applied Biostatistics and Epidemiology
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biology, biostatistics,health sciences, public health,OAI-PMH Harvest
Language
English
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Gilliland, Frank (
committee chair
), Avol, Ed (
committee member
), Berhane, Kiros (
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), McConnelll (
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