From the Department of Health Policy and Management, Johns
Hopkins University School of Hygiene and Public Health, Baltimore,
Maryland.
Health status instruments are increasingly used to describe health
states of populations, to measure outcomes in clinical trials, and to
conduct research on quality of care. There is a widespread consensus
that health systems should be held accountable for both traditional
clinical outcomes and individuals' health-related quality of life.
Although there are many measures to assess both generic and
disease-specific aspects of adults' health,1
measurement of health status in pediatric populations is still in the
nascent stages of development.
Conceptually, health status is a multidimensional state of physical
health, mental health, everyday functioning in social and role
activities, and general self-perceptions of well-being.2 The current conceptualization of children's health as the ability to
participate fully in developmentally appropriate physical, psychological, and social activities calls for comprehensive (ie, generic health status measures) instruments that are capable of tapping
all these domains.6 Generic instruments differ from disease-specific instruments in their applicability across disease entities and clinical interventions and their ability to summarize broad conceptualizations of health.9
Because asthma is a common10 and costly11
chronic disease in childhood and adolescence, the need for methods to
describe the health status of and evaluate interventions for these
individuals is acute. Research on the outcomes of pediatric asthma
treatment has been hampered because of an absence of an existing
instrument that can broadly assess all aspects of health for children
with asthma. In general, prior efforts have examined disease-specific effects of asthma.12 The instruments used generally
focus only on physical and emotional symptoms considered to be
attributable to an individual's experiences with asthma. However, both
the disease itself and treatment for it may have impacts that extend beyond specific symptoms. Although it would be possible to develop an
asthma-specific instrument that uses a broad conceptualization of
health, it is unlikely that individuals recognize the manifold health
effects that result because of their disease. Instead, they are more
likely to report on their general health perceptions, health
experiences, and health behaviors, which may or may not be associated
with biomedical conditions. Thus, disease-specific instruments may fail
to capture the diverse effects that a chronic illness, such as asthma,
has on health and may not detect unintended adverse effects of
treatment.
Prior studies on the health effects of asthma suggest that it
influences multiple dimensions of child health. Children with asthma
seem more uncomfortable and report lower perceived well-being, more
limitations in physical activity, and more emotional symptoms than
children without chronic disease.19 Asthma may be
associated with poorer physical fitness, possibly because of
self-imposed inactivity rather than physiologic dysfunction caused by
disease processes.26
It is unclear whether asthma is associated with poorer functioning in
age-appropriate roles, such as school and work performance. Using
nationally representative data, one study found that children with
asthma were significantly more likely to have learning disabilities than those without asthma.27 On the other hand, Gutstadt
and colleagues28 found that children with asthma had
average to above-average academic abilities. In young adults, asthma
has been associated with a small adverse effect on
employment.29
In summary, existing evidence suggests that asthma affects multiple
dimensions of health. There are no studies, however, that measure the
health status of adolescents with asthma using a single instrument with
acceptable psychometric properties that is based on a comprehensive
conceptualization of health. In this study, we use the Child Health and
Illness Profile, Adolescent Edition (CHIP-AE) to describe the health
and functioning of a community sample of adolescents with and without
asthma. The CHIP-AE is the most comprehensive currently available
generic health status tool to measure the health status of
adolescents.29,30 It uses a broadly defined conceptual
framework that recognizes that health includes not only perceptions of
wellness and illness but also participation in developmentally
appropriate tasks and activities. We hypothesized that asthma would
affect multiple dimensions of health (primarily perceived well-being
and physical, emotional, and social functioning), and the magnitude of
these effects would be greatest for individuals whose asthma was
symptomatic, as evidenced by recent wheezing.
METHODS 
Data Collection
This investigation was part of a larger study conducted to
develop and test the CHIP-AE.8 A school sample of 3109 adolescents who completed a self-administered version of the CHIP-AE in
school was used for this study. The adolescents' ages ranged from 11 to 17 years. Details of survey administration are presented
elsewhere.30 Briefly, data for teenagers in this study were
obtained in 1992 from two schools in northern Baltimore City (N = 877), two schools in rural Maryland (N = 1,878), and two schools
in rural Arkansas (N = 354). Additionally, mothers of 225 teenagers (26%) in the northern Baltimore City sample completed a
modified version of the CHIP-AE over the telephone.
Before administration in the schools, parents were sent an explanation
of the survey and consent materials. In the northern Baltimore city
sample, those who did not want their children to participate were given
the opportunity to send a postcard to the project team indicating their
desire to decline. At the request of the school administrators in the
western Maryland and Arkansas samples, we obtained parental written
consent before administration of the questionnaire at these locations.
The survey was conducted in a middle school and a high school at each
of the three sites.
In the northern Baltimore and Arkansas samples, questionnaires were
self-administered and completed in classrooms after a member of the
project team explained the study and gave instructions for completing
the questionnaire to the students. Teachers assisted the project team
for the purposes of monitoring the class. In the western Maryland
sample, the survey was conducted entirely by the teachers in the
schools.
Measurement of Health Status Using the CHIP-AE
The CHIP-AE is a recently developed health status
measure8,30 that has a conceptual framework that includes 6 domains and 20 subdomains (see Table 1). Within the
developmental context of adolescence, the instrument measures perceived
well-being, symptoms, states and behaviors that are known to reduce or
increase the likelihood of future health, burden of morbidity, and
physical, emotional, and social functioning. The satisfaction domain
includes perceptions of well-being and self-esteem as well as the
respondents' overall perceptions of their own health and attitudes
toward it. The discomfort domain includes a variety of symptoms that
would generally interfere with comfort or a sense of well-being as well as positive health perceptions. The resilience domain assesses aspects
of positive health characterized by the existence of resources and
patterns of behavior; it also captures phenomena that are known to be
related to the capacity to resist threats to well-being that inevitably
arise in the course of the life span. The risks domain is the converse
of the resilience domain. The achievement domain reflects the state of
development of the individual and consists of work and school
accomplishments. Last, the disorders domain includes biomedically
defined states of physical and mental ill health.
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Table 1.
Child Health and Illness Profile, Adolescent Edition, Domains and
Subdomains
[View Table]
|
Scales in the instrument have acceptable levels of internal consistency
and test-retest reliability. Construct validity has been documented by
showing that the instrument has moderate to high correlation with other
measures that assess single domains of health and by demonstrating that
it can discriminate "well" adolescents from those with
"illness," as characterized by acute and chronic
disorders.8,30,31
All respondents completed a series of sociodemographic questions. These
responses were used to create age, gender, ethnicity, and socioeconomic
variables. We used four dichotomous indicators obtained from the
sociodemographic section of the CHIP-AE to measure socioeconomic
status: family structure (eg, single-mother family); participation in
Aid to Families With Dependent Children, food stamps, or school lunch
programs; maternal education (high school graduate, yes or no); and
whether the teenager's mother was currently employed.
Data Analysis
Analyses were done using the following three groups: (1) no
asthma, (2) asthma and no recent wheezing, and (3) asthma with recent
wheezing. These groups were formed using two questions in the
questionnaire. In the recurrent disorders subdomain section, teenagers
were asked, "Has a doctor ever said you had asthma?" They could
respond, "No," "Yes
but no problems with it in the past 12 months, or "Yesproblems with it in the past 12 months." The two
groups with asthma were combined, because preliminary analyses
indicated few substantive differences between those with or without
problems with their asthma in the past 12 months. Teenagers with asthma
were further classified by their responses to the following question in
the physical discomfort subdomain of the discomfort domain: "In the
past 4 weeks, on how many days did you have wheezing or trouble
breathing (when you weren't exercising)?" Individuals with asthma
were divided into two groups: those with no wheezing in the past 28 days and those with any wheezing in the past 28 days. Of the 3109 teenagers who completed the CHIP-AE for this study, 106 (3.4%) could
not be categorized into one of the three asthma groups because of
missing data for the asthma or wheezing items.
We calculated the subdomain scores for the recurrent disorders and
physical discomfort subdomain scales excluding the asthma and wheezing
items, respectively. To facilitate interpretation of scale scores, we
standardized all scales to a reference group. The sample of 877 adolescents in northern Baltimore city constituted this reference
group. For that group, scale scores were arbitrarily set to a mean of
20 and an SD of 5. The reference group is used for comparative purposes
only and is not intended to be used as a normative population; none of
the populations on which the CHIP-AE has been tested are representative
of the average population of adolescents in the United States. A
standardized subdomain score of 25 was 1 SD greater than that of the
reference population. Domain scores were computed as the averages of
the subdomain scores for a given domain.
All analyses examined differences between teenagers without asthma
(well group) and the two groups with asthma. Initially, the
sociodemographic characteristics of each of the three groups were
compared. Univariate analyses were done for all domain and subdomain
scales. The 95% confidence intervals (CIs) of the mean scale scores of
the two asthma groups were compared with the 95% CI of the mean score
of the well group. The comparison was considered statistically
significant when the CIs did not overlap.
Because statistical significance does not indicate the magnitude of
differences, we calculated effect sizes for domain scales as a measure
of the relative impact of asthma on each of the six domains of health.
Effect sizes translate changes in health status into standardized
units. They were calculated as the difference in means (well group 
asthma groupi) divided by the SD of the well
group.32 The absolute value of the effect size indicates the relative magnitude of the effect. A positive sign was used to imply
improvement in health, and a negative sign indicates worsening in
health.
Multivariable linear regression was conducted to control for
sociodemographic differences between the groups. Each regression produced an adjusted estimate of the difference in subdomain scores between the asthma groups and the well group. Separate regressions were
done for each subdomain scale and controlled for age, gender, socioeconomic status, and site of data collection. P values
for regression-adjusted parameter estimates were obtained from
t tests of the 
coefficients.
RESULTS
The validity of teenagers' reports of the presence of asthma was
assessed by comparing the responses of 225 individuals in the study
population with those of their mothers. Interrater agreement as
measured by the 
statistic was 0.60, indicating a high level of
agreement. Using maternal reporting as the criterion, the sensitivity of adolescents' reports on the presence of asthma was 82%, and specificity was 94%. These figures exceeded those for other disorders and were comparable with levels of agreement found for sociodemographic data included in the CHIP-AE.
Of the 3003 adolescents in the study population, 12.0% reported that a
physician ever had told them they had asthma, and of these, half
(50.0%) said that they had problems with wheezing in the prior 28 days. Asthma was more commonly reported in the urban sample than the
two rural samples. In the northern Baltimore City sample, 16.7%
reported that they ever had asthma, which compared with 9.9% and
11.3% for the two rural samples in Maryland and Arkansas,
respectively. Of those with asthma, about half reported recent wheezing
in the northern Baltimore (46.1%) and western Maryland (49.4%)
samples, but 65.8% reported recent wheezing in the Arkansas sample.
Table 2 presents personal characteristics of the study
population stratified into three groups based on the presence of asthma and wheezing. Teenagers with symptomatic asthma were more likely to be
in minority ethnic groups and girls than were well adolescents. However, when the association between ethnicity and the presence of
asthma was examined by site of data collection, no significant associations were found in any of the three sites. Whereas 37% of the
adolescents in the study population were in minority ethnic groups, the
proportion of minorities in each of the three geographic sites varied
dramatically: 88.4% in northern Baltimore, 89.4% in Arkansas, and
just 3.1% in western Maryland.
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Table 2.
Personal Characteristics of Study Population Stratified by Presence of
Asthma and Wheezing
[View Table]
|
Presence of asthma was associated with lower socioeconomic status for
two of the four indicators. Teenagers in families with single mothers
were 1.8 times more likely to have symptomatic asthma than teenagers in
two-parent families (95% CI, 1.3 to 2.5). Furthermore, the odds of
symptomatic asthma were increased by 50% for those who received at
least one of three different types of welfare aid versus those without
any welfare aid (odds ratio, 1.5; 95% CI, 1.1 to 2.1).
Adolescents with symptomatic asthma had significantly lower perceived
well-being and were more uncomfortable than those without asthma (Table
3). In the satisfaction domain, teenagers' satisfaction with their health and their self-esteem were significantly lower for
those with recent wheezing but not for those without wheezing. Similarly, adolescents with symptomatic asthma had greater levels of
other physical symptoms, emotional symptoms, and restrictions in their
activity than counterparts without asthma. This finding suggests that
symptomatic asthma is negatively associated with multiple dimensions of
individuals' perceived well-being, experiences with symptoms, and
functional status.
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Table 3.
Child Health and Illness Profile, Adolescent Edition, Subdomain
Standardized Scale Scores for Adolescents by Presence of Asthma and
Wheezing*
[View Table]
|
Teenagers with asthma and wheezing also reported a greater burden of
morbidity (ie, more comorbidities), as measured by each of the six
subdomain scores in the disorders domain. Item level analysis revealed
that within each of the disorder subdomains, teenagers with symptomatic
asthma were more likely to have other conditions of a variety of types
(data not shown). Conditions were not limited to infectious problems.
For example, compared with those without asthma, the odds of reporting
a sprained joint for teenagers with symptomatic asthma were 1.9 times
greater, 1.8 times greater for a broken bone, 3.6 times greater for
anemia, 8.2 times greater for epilepsy, 2.0 times greater for
scoliosis, 2.4 times greater for vision problems, and 5.0 times greater
for an eating disorder. (The 95% CIs between the symptomatic asthma groups and those without asthma did not overlap for any of these comparisons.)
For each of the six domains of health that the CHIP-AE addresses, the
effect sizes for the two asthma groups relative to the no-asthma group
are presented in Table 4. Effect sizes can be used to
draw inferences concerning both the presence of statistical associations and the magnitude of the effect. Table 4 shows that except
for other disorders, individuals with asthma but no recent wheezing
have comparable health and illness patterns as those without asthma.
However, teenagers with asthma and recent wheezing scored 1.5 SD units
higher on the disorders domain scale, 1 SD higher on the discomfort
scale, and 0.5 SD lower on satisfaction. Interestingly, teenagers with
asthma and wheezing also had higher scores on the risk domain scale
than those without asthma. This result is attributable principally to
more negative, externalizing behaviors that threaten to disrupt social
development (ie, a higher score on the threats to achievement subdomain
scale).
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Table 4.
Effect Sizes for Differences in the Domain Scale Scores by Presence of
Asthma and Wheezing Compared With the No-Asthma Group*
[View Table]
|
Because some demographic and socioeconomic characteristics of
respondents differed across the three groups, we conducted
multivariable linear regression to adjust for the effects of these
covariates on the subdomain scale scores (Table 5).
Results indicate that despite adjustment for age, gender, geographic
site of data collection, and socioeconomic status, teenagers with
asthma and wheezing had significantly lower perceived well-being (ie,
satisfaction), higher discomfort, and a greater burden of morbidity
(ie, higher scores on disorders subdomains). These regression analyses
also demonstrated that the group with asthma and no recent wheezing had
similar trends in the various subdomain scores as the wheezing group, but except for the disorders subdomains, the effects were small. Last,
the regression-adjusted differences in subdomain scale scores between
the asthma groups and the no-asthma group indicated a trend for
teenagers with asthma to report more states and behaviors that are
known to heighten the likelihood of subsequent illness (ie, risks
subdomain).
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Table 5.
Regression-adjusted Differences in Subdomain Standardized Scale Scores
for Adolescents With Asthma Versus Those Without Asthma*
[View Table]
|
DISCUSSION
This study is the first, to our knowledge, to measure the health
of teenagers with asthma using a self-administered, generic health
status instrument that operationalizes a comprehensive conceptualization of adolescent health. Compared with teenagers without
asthma, those with asthma and recent wheezing have more emotional and
physical symptoms, poorer functional status, lower perceived
well-being, more negative behaviors that threaten to disrupt social
development, and a greater number of reported comorbidities. These
results demonstrate that, to fully understand how asthma affects their
patients, practitioners should monitor not only clinical and
physiologic responses but also changes in health-related quality of
life, ie, symptoms, functional status, and perceptions of well-being.
Merely having asthma without concomitant exacerbation of the disease,
as manifested by wheezing, was not associated with substantive effects
on health status. Teenagers with asthma but no recent wheezing differed
significantly from well teenagers only in the number of reported
comorbidities. The statistical associations attributed to asthma
reported in this study were found primarily for individuals with
wheezing in the past 28 days. Thus, investigators developing
community-based surveys that include adolescents with asthma should
consider including a question about recent wheezing to identify
individuals who are having the greatest health effects of their
disorder.
One potential limitation of the study's findings is the unknown
validity of teenagers' reports of asthma in comparison with physicians' diagnoses. Although the validity of teenagers' reports on
the disorder is unclear, there is evidence that maternal reports of
asthma in their children strongly agree with medical
records.33 The high level of agreement between teenagers'
responses concerning the presence of asthma and their mothers'
responses serves to minimize concern that there is substantial
overreporting or underreporting of asthma.
Because this was a cross-sectional survey, the directionality of the
statistical associations is unclear. For example, does recent wheezing
lead to poorer perceived well-being, does poorer perceived well-being
lead to more wheezing, or both? The consistency of a negative effect of
asthma across multiple dimensions of the health and functioning is
evidence that suggests a potentially causal relationship between asthma
and poorer health-related quality of life. However, future longitudinal
investigations on the natural history of the effects of asthma on the
health status of teenagers are needed to clarify this temporal
relationship.
Although the results of this study were replicated in three separate
geographic sites, their generalizability may be limited to similar
community-based populations. Because of highly skewed distributions of
ethnicity within each geographic site, the power of our analyses to
detect differences in health status attributable to ethnicity was
limited. Even so, the findings were replicated in each of the sites,
which argues against ethnicity as a principal explanation for the
differences in health status.
We did not sample teenagers for moderate or severe asthma. It is
possible that the health and functioning profiles of teenagers with
more severe asthma may differ from those in this study. However, based
on the trends found across the two asthma groups in this study,
differences attributable to severity may be more quantitative (poorer
health and functioning in the dimensions identified in this study) than
qualitative.
The cumulative prevalence estimate of asthma in this study was similar
to those obtained in prior reports. We found that, of nearly 3000 adolescents, the cumulative prevalence of asthma was 12%. A random
digit-dialing telephone survey of Bronx households found a cumulative
prevalence of 14.3%,34 and a study in a large suburban
health maintenance organization indicated that 12.5% of children of 4 through 11 years of age had a subsequent 6-year cumulative prevalence
of asthma.35 However, data from national surveys in the
United States estimate its point prevalence to be from 3.6% to
9.5%.20,36 These findings suggest that the cumulative
prevalence of asthma may be as much as three times as high as its point
prevalence.
Similar to other investigations,36,37 this study indicated
that asthma was more common and tended to be symptomatic, or more
severe, among adolescents with low socioeconomic status. Because
socioeconomic status may have negative effects on teenagers' health
and functioning, we performed multivariate regression that controlled
for its effects. Results indicated that asthma has a negative effect on
adolescent health status that is independent of socioeconomic status.
In this study, teenagers with symptomatic asthma reported more acute,
recurrent, and chronic comorbidities than teenagers without asthma.
This finding suggests that morbidity clusters in some individuals who
have a disproportionate share of illness. Nonrandom clustering of
morbidity has also been reported in longitudinal studies using claims
data38,39 and a British survey.40 Further work
is need to describe the epidemiologic characteristics of morbidity
clusters in adolescents and to determine the mechanisms by which
morbidity clusters influence the health status of teenagers.
One promising approach to measuring health-related quality of life for
adolescents will be to combine a generic instrument with a
disease-specific supplement. A generic instrument provides comprehensive information on the overall health and functioning of
individuals and in longitudinal study designs allows better understanding of the impact of disorder on health. Generic instruments have the additional advantage of providing comparable data for comparisons across disease entities. On the other hand, a
disease-specific module can potentially give information on
asthma-specific symptoms that may be more responsive to intended
effects of medical interventions. Therefore, we propose that
investigations that describe the health status of or examine the
effects of medical interventions on teenagers with asthma incorporate a
generic health status instrument. Because of the availability of the
CHIP-AE and several newly developed asthma-specific
instruments,12 this approach for teenagers with asthma
is now possible.
Reprint requests to (C.B.F.) Department of Health Policy and
Management, Johns Hopkins School of Public Health, 624 N Broadway, Room
451, Baltimore, MD 21205.
This research was supported in part by Agency for Health Care
Policy and Research grant HS07045 and by Bureau of Maternal and Child
Health, US Department of Health and Human Services, grant MCJ247307.
We thank Kelly Vogel for excellent coordination of this project and
acknowledge important contributions to this project from Bert Green and
Margaret Ensminger.
CHIP-AE, Child Health and Illness Profile,
Adolescent Edition.
CI, confidence interval.
ABSTRACT
