Asthma Symptom Burden: Relationship to Asthma
Severity and Anxiety and Depression Symptoms
Laura P. Richardson, MD, MPHa,b, Paula Lozano, MD, MPHa,c, Joan Russo, PhDd, Elizabeth McCauley, PhDb,d, Terry Bush, PhDc, Wayne Katon, MDd
Departments ofaPediatrics anddPsychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, Washington;bChildren’s Hospital and
Regional Medical Center, Seattle, Washington;cCenter for Health Studies, Group Health Cooperative of Puget Sound, Seattle, Washington
The authors have indicated they have no ﬁnancial relationships relevant to this article to disclose.
OBJECTIVE.The purpose of this work was to examine the relationship between youth-reported asthma symptoms, presence of anxiety or depressive disorders, and objective measures of asthma severity among a population-based sample of youth with asthma.
METHODS.We conducted a telephone survey of 767 youth with asthma (aged 11–17 years) enrolled in a staff model health maintenance organization. The Diagnostic Interview Schedule for Children was used to diagnose Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, anxiety and depressive disorders; the Child Health Status-Asthma questionnaire (modified) was used to assess asthma symptoms; and automated administrative data were used to measure asthma treatment intensity and severity. Analyses of covariance were performed to de-termine whether the number of anxiety and depressive symptoms was related to the number of asthma symptoms. Logistic regression analyses were used to eval-uate the strength of association between individual symptoms of asthma and the presence of an anxiety or depressive disorder and objective measures of asthma severity.
RESULTS.After adjusting for demographic characteristics, objective measures of asthma severity, medical comorbidity, and asthma treatment intensity, youth with ⱖ1 anxiety or depressive disorder (N⫽125) reported significantly more days of asthma symptoms over the previous 2 weeks than youth with no anxiety or depressive disorders. The overall number of reported asthma symptoms was sig-nificantly associated with the number of anxiety and depressive symptoms en-dorsed by youth. In logistic regression analyses, having an anxiety or depressive disorder was also strongly associated with each of the 6 asthma-specific symptoms, as well as the 5 related nonspecific somatic symptoms contained in the Child Health Status-Asthma questionnaire.
CONCLUSIONS.The presence of an anxiety or depressive disorder is highly associated with increased asthma symptom burden for youth with asthma.
anxiety, depression, asthma
ED— emergency department GHC—Group Health Cooperative CHSA-T—Child Health Status-Asthma for Teens
DSM-IV—Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition ANCOVA—analysis of covariance PCDS—Pediatric Chronic Disease Scale CI— conﬁdence interval
OR— odds ratio
HEDIS—Health Plan Employer Data and Information Set
Accepted for publication Mar 19, 2006
Address correspondence to Laura Richardson, MD, MPH, Department of Pediatrics, Box 354920, University of Washington School of Medicine, 6200 NE 74th St, Suite 210, Seattle, WA 98115. E-mail: firstname.lastname@example.org
ASTHMA IS THEmost common chronic medical illness of childhood with a prevalence of 3% to 7%.1–3
Among individuals with asthma, there is considerable variation in asthma symptom burden,4–6 which is an
important measure used by providers to guide the treat-ment of asthma and to assess appropriateness of the treatment regimen. The level of symptoms is strongly associated with increased risk of emergency department (ED) visits and hospitalizations,6 as well as decreased
quality of life.7,8These data suggest that it is important to
understand what factors are associated with higher symptom burden.
Patient demographic characteristics that have been found to be associated with increased symptom burden include age and gender.6 Modifiable risk factors that
have been identified include environmental exposures, exposure to tobacco smoke,6,9treatment factors (use of
inhaled anti-inflammatories10and use of a written care
plan11), and coexisting medical conditions, such as
aller-gic rhinitis and sinusitis.12–18
There is growing evidence that youth with asthma also are at increased risk for anxiety and depressive disorders.19–27Among adults with asthma, the
co-occur-rence of an anxiety disorder has been shown to be associated with increased requests for asthma medica-tion,28 increased ED visits,29 and increased
hospitaliza-tions.30 However, few studies have examined the
asso-ciation of psychological disorders with asthma symptom burden. A recent study showed that inner-city children with asthma who scored higher on a measure of psycho-logical distress had more hospitalizations, more days of wheezing, and lower functional status than those scor-ing lower on distress.31The goal of the current study was
to evaluate the association between asthma symptom-atology and anxiety/depressive disorder presence and asthma severity in a large population-based sample of adolescents with asthma.
The Stress and Asthma Research study was developed by a multidisciplinary team in the Departments of Psychia-try and Pediatrics at the University of Washington and the Center for Health Studies at Group Health Cooper-ative (GHC). GHC is a nonprofit health maintenance organization with 25 primary care clinics in Washington state that GHC owns, as well as 75 clinics that have contracts to care for GHC patients.
Potential study subjects were youth (11–17 years of age) with asthma who were enrolled in a GHC insurance plan for ⱖ6 months. Administrative data from GHC were used to identify youth with asthma based on meetingⱖ1 of the following criteria: (1) hospitalization in the past year with an asthma diagnosis andⱖ1 asthma prescrip-tion during that same time period; (2)ⱖ1 ED or urgent
care visit for asthma in the past year and ⱖ1 asthma prescription during that same time period; (3)ⱖ2 office visits for asthma in the past year and ⱖ1 asthma pre-scription during the same time period; (4)ⱖ1 office visit for asthma in the past year and another in the past 18 months andⱖ1 asthma prescription in the last year; (5) only 1 asthma visit in the past year but ⱖ2 asthma prescriptions filled on different days in that time period; and (6) ⱖ4 prescriptions for asthma medication in the last 12 months.
These criteria were developed to identify youth with active asthma and to screen out patients with very mild asthma, such as mild exercise-induced asthma. Youth with an International Classification of Diseases, Ninth Revision code for bipolar disorder or schizophrenia were excluded from the study. All of the youth meeting in-clusion criteria were invited to participate in the study.
Of the 1458 children/adolescents and parents in the initial sample, 170 were ineligible, leaving an eligible sample of 1288. Reasons for ineligibility included: child did not have asthma (n⫽63), disenrolled from GHC (n
⫽84), language ineligible (n⫽11), parent too ill (n⫽ 6), and other (n⫽6). Of the eligible sample, 833 parents gave consent and permission for us to contact their child/adolescent with asthma. From these, we obtained child consent and completed 781 child/adolescent inter-views for a final recruitment rate of 60.6%. The final sample for the current analysis is 767 youth (12 youth did not give permission for the use of automated data and 2 youth did not complete the entire psychiatric interview).
All of the survey contacts were conducted via telephone. At the time of interview, informed consent was obtained both from a parent and the youth study participant. The telephone interview included a 10- to 15-minute inter-view of the consenting parent and a 45- to 75-minute child/adolescent interview.
The parent interview included questions about the child’s race/ethnicity, education and employment status for both the responding parent and his/her partner, mar-ital status of the responding parent, and number of children in the household. Child age and gender was obtained from administrative data and confirmed with the parent.
Asthma Diagnosis and Symptom Burden
adminis-trative data. Treatment intensity was evaluated based on medication fills identified in the administrative data. Youth were classified as receiving no medications, albu-terol only, 1 controller, orⱖ2 controllers. Asthma dura-tion was assessed via parent quesdura-tionnaire and was de-fined as number of years since diagnosis of asthma.
As a measure of asthma-specific functional status, all of the youth completed a modified version of the Child Health Status-Asthma for Teens (CHSA-T).32The CHSA-T
is a 30-item asthma-specific instrument that has been found to have high reliability and validity in capturing a broad range of asthma experiences.32The main outcome
examined in this article was the number of asthma symptom days reported over the previous 2 weeks. This instrument also includes a 5-point Likert scale, which asks youth to report how much of the time, because of their asthma, they were troubled by each of 11 physical symptoms during the past 2 weeks. Response options ranged from “all of the time” to “none of the time.” These 11 symptoms included 6 that are core symptoms of asthma and 5 that are less specific symptoms. The presence or absence of these 11 symptoms was exam-ined as secondary outcomes in our analysis. For the purpose of this analysis, youth were considered to have a symptom if they reported having a symptom “some of the time,” “most of the time,” or “all of the time” in the previous 2 weeks.
Mental Health Assessment
All of the youth completed the National Institute of Mental Health Diagnostic Interview Schedule for Chil-dren (version 4.0), a structured psychiatric interview that has been shown to be a reliable and valid structured interview to diagnoseDiagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), disorders in children and adolescents.33 After standardized training
and demonstrated competence, trained staff used the computer-assisted version of the Diagnostic Interview Schedule for Children to guide telephone administration of this instrument. Telephone versions of structured psy-chiatric interviews have been shown to have a high correlation with in-person interviews.34,35 Interview
quality was repeatedly assessed via silent monitors in-stalled on all telephones; interviewers received written feedback on errors, as well as corrective instruction.
For our analysis, youth were considered to have an anxiety (panic, generalized anxiety, separation anxiety, social phobia, or agoraphobia) or depressive (major de-pression or dysthymia) disorder if they met DSM-IV criteria forⱖ1 of these disorders. Summed scores of the total number (of 62) of positive symptoms across all of the anxiety and depressive disorders were used in the analyses of covariance (ANCOVAs) examining the asso-ciation between the number of anxiety or depressive symptoms and asthma symptoms.
Because symptoms were the key dependent variable in our analyses, we used administrative data to generate a severity measure that was not dependent on reported symptoms. We first explored the use of the Health Plan Employer Data and Information Set (HEDIS) criteria to identify adolescents who were at high risk for adverse asthmatic events. Youth met these criteria if they had any of the following 4 health care use variables over a 12-month period: (1)ⱖ4 dispensings of asthma medica-tion; (2) ⱖ1 emergency visit for asthma; (3)ⱖ1 hospi-talization for asthma; or (4) ⱖ4 ambulatory visits for asthma.36In preliminary analysis, we found that⬃66%
of our sample met these criteria, with most of them meeting criteria because ofⱖ4 dispensings of the asthma medication, suggesting lack of specificity as a measure of severity. Therefore, we modified these criteria to develop a more restrictive definition for severity based on admin-istrative data. These modified criteria (havingⱖ4 ambu-latory visits for asthma,ⱖ1 ED visit, ⱖ1 hospitalization for asthma, or ⱖ1 oral steroid prescription for asthma over a 12-month period) were used to define high-risk youth for all of the analyses in this article.
The Pediatric Chronic Disease Scale (PCDS) was used to measure health-related medical comorbidity not because of asthma or mental illness.37The PCDS is an algorithm
that classifies children into chronic disease categories by using claims data for prescription fills; studies have shown that it has performed as well as the International Classification of Diseases, Ninth Revision-Clinical Mod-ification-based Ambulatory Care Groups38in predicting
subsequent 1-year health use and health care costs. The PCDS was adapted for our study by removing medica-tions used primarily for asthma, anxiety, and depression.
For the purpose of analysis, youth were categorized as havingⱖ1 DSM-IV anxiety or depression diagnosis or no anxiety or depression diagnoses. Basic descriptive statis-tics were then used to compare the demographic char-acteristics, asthma severity, asthma duration, treatment factors, and chronic disease score between these 2 groups, using2analyses with corrections for continuity for the categorical variables andttests for the continuous variables.
trans-formation of number of symptom days (plus 0.5) as the dependent variable with the same set of explanatory variables.
An ANCOVA was used to examine the association between the number of youth-reported symptoms of asthma and the number of youth-reported symptoms of anxiety and depression. Six groups of approximately equal numbers of adolescents were formed based on the number of anxiety and depressive symptoms they re-ported. This was the independent variable, and the num-ber of asthma symptoms was the dependent variable. Age, gender, parental education, race, ethnicity, asthma duration, asthma treatment intensity, and PCDS were used as covariates.
Because the overall number of symptoms and symp-tom days was found to be statistically significantly re-lated to anxiety and depressive disorders, logistic regres-sion models were used to examine the association between presence of an anxiety or depressive disorder and asthma severity and each of the asthma-related symptoms in the CHSA-T symptom scale. Variables in-cluded in the models were chosen a priori and inin-cluded age, gender, parental education, race, ethnicity, duration of asthma, asthma treatment intensity, and PCDS. For this analysis, the modified HEDIS asthma severity mea-sure was used as described above. We performed sensi-tivity analyses for the severity measure by requiring even more stringent criteria of havingⱖ2 steroid fills in the previous year or 2 ED visits or 1 hospitalization. However, because the results of the regression analysis were not significantly different with more stringent se-verity criteria, results are only presented for the main analysis. Based on the a priori hypothesis that youth on controller medications may be different from those not on controller medications, controller medication use was examined as a potential effect modifier. However, the interaction term for this variable was not significant and was not included in the final model.
Because of the fact that we had a final recruitment rate of 60.6%, analyses were all conducted using pro-pensity score weighting. We estimated response propen-sity scores (probability of being a respondent) as a func-tion of the following variables (all of these within the past year): age, gender, rural-urban commuting area code (defining rural versus urban areas using zip code), being on Medicaid, having state-funded insurance be-cause of low income, PCDS, number of primary care visits, number of asthma-related ED visits and hospital-izations, oral steroid prescription, number of specialty mental health visits, any prescription for antidepressant medication or antianxiety medication, and a diagnosis of depression or anxiety. We predicted response/nonre-sponse status as a function of these variables using PROC logistic (SAS Institute, Cary, NC) and estimated a re-sponse probability for each survey respondent (rere-sponse propensity score). These propensity scores weights were
then applied in all of the analyses (weights inversely proportional to estimated probability of response) after being rescaled to sum to the observed sample size (ie, the number of survey respondents) such that individuals with a low probability of response were given a higher weight in the analysis to represent the larger number of nonrespondents with similar characteristics.
A total of 16.2% (n⫽125) of children/adolescents met DSM-IV criteria forⱖ1 anxiety and depressive disorders in the last 12 months with 68 (8.9%) having an anxiety disorder alone, 21 (2.5%) a depressive disorder alone, and 37 (4.8%) both an anxiety and depressive disorder. Table 1 describes the demographic characteristics of youth without an anxiety or depressive disorder com-pared with those with ⱖ1 anxiety or depressive disor-ders. Compared with youth without an anxiety or de-pressive disorder, youth with a disorder were more likely to be girls, to have a parent with high school education or less, to have a more recent diagnosis of asthma, to be on a single controller and less likely to be on 2 control-lers, and to have a higher PCDS score. There were no differences between the 2 groups in either objective measure of severity or other health services use for asthma.
PCDS (t⫽2.28;P⬍.03) remained significant predictors; however, gender and treatment intensity were no longer significant.
Figure 1 shows the results of the ANCOVA analysis
examining the relationship between mean number of reported asthma symptoms and the number of anxiety-depressive symptoms. Based on this analysis, youth with higher levels of anxiety or depressive symptoms were
TABLE 1 Demographics of Youth With Asthma (Nⴝ767, Unless Otherwise Speciﬁed)
Variable Anxiety or Depressive Disorder (N⫽125)
No Anxiety Disorder (N⫽642)
Test Statistics (2)
Male 45 (36.0) 366 (57) 17.73
Female 80 (64.0) 276 (43) (P⬍.001)
Age, y, mean (SD) 14.2⫾2.0 14.0⫾1.9 1.17
Parental education (N⫽757),n(%)
High school or less 18 (14.8) 43 (6.8) 7.76
At least some college 104 (85.2) 592 (93.2)) (P⫽.005)
Race of parent (N⫽754),n(%)
White 91 (74.6) 514 (81.3)
Black 15 (12.3) 23 (3.6) 9.11
Asian and Paciﬁc Islanders 3 (2.5) 23 (3.6) Degrees of freedom⫽4
Native American 9 (7.4) 42 (6.6) (P⫽.06)
Other 4 (3.3) 20 (3.2)
Hispanic 9 (7.4) 26 (4.1) 1.77
Not Hispanic 113 (92.6) 605 (95.9)
Years since diagnosis of asthma (N⫽753), mean (SD)
6.4⫾4.3 7.4⫾4.3 t751⫽2.27 (P⫽.02)
No medications 2 (1.6) 24 (3.7)
Albuterol only 35 (28.2) 159 (24.8) 8.49
Any 1 controller 70 (56.5) 305 (47.5) Degrees of freedom⫽3
ⱖ2 controllers 17 (13.7) 154 (24.0) (P⬍.04)
PCDS, mean (SD) 794.8⫾934.5 580.5⫾962.5 2.28 (P⫽.02)
HEDIS severity criteria,n(%)a 86 (68.8) 447 (69.6) 0.01
Modiﬁed HEDIS severity criteria,n(%)b 32 (25.6) 138 (21.5) 0.95
ⱖ1 ER visit for asthma 11 (8.8) 52 (8.1) 0.01
ⱖ1 inpatient hospitalization for asthma 4 (3.2) 10 (1.6) 0.80
ⱖ1 oral prednisone course 33 (26.6) 155 (24.1) 0.22
ⱖ4 outpatient visits for asthma 7 (5.6) 38 (5.9) 0.00
ⱖ4 prescriptions for asthma medications,n(%) 83 (66.9) 428 (66.6) 0.00
aHEDIS Severity criteria include havingⱖ1 of the following in the prior 12 months:ⱖ4 dispensings of asthma medication,ⱖ1 emergency visit for asthma,ⱖ1 hospitalization for asthma, orⱖ4
ambulatory visits for asthma.
bModiﬁed HEDIS severity criteria include havingⱖ1 of the following in the prior 12 months:ⱖ1 ER visit for asthma,ⱖ1 inpatient hospitalization for asthma,ⱖ1 oral steroid course, orⱖ4 outpatient
visits for asthma.
TABLE 2 Results of Linear Regression of Number of Asthma Symptom Days in the Previous 2 Weeks
Variable Unstandardized␤ 95% CI for␤ t(P) Partial Correlation
Anxiety-depression group versus not 1.70 0.92 to 2.48 4.30 (⬍.001) 0.15
Age .13 ⫺0.02 to 0.28 1.69 (.09) 0.06
Gendera ⫺.79 ⫺1.37 to⫺0.21 ⫺2.67 (.008) ⫺0.10
White vs nonwhite ⫺.19 ⫺0.92 to 0.55 ⫺0.50 (.62) ⫺0.02
Hispanic vs non-Hispanic ⫺.28 ⫺1.68 to 1.12 ⫺0.40 (.69) ⫺0.01
Duration of asthma .01 ⫺0.06 to 0.08 0.30 (.76) 0.01
PCDS .00 0.000 to 0.001 2.64 (.008) 0.09
Highest education of parents 1.00 ⫺1.36 to 3.37 0.83 (.41) 0.03
None to albuterol 1.35 ⫺0.28 to 2.99 1.62 (.10) 0.06
None to 1 controller 1.20 ⫺0.39 to 2.80 1.48 (.14) 0.05
None toⱖ2 controllers 1.93 0.27 to 3.59 2.28 (.02) 0.08
Modiﬁed HEDIS severity .43 ⫺0.19 to 1.06 1.37 (.17) 0.05
also significantly more likely to report higher levels of asthma symptoms (F5,743⫽16.13;P⬍.001) while ad-justing for covariates. When individual symptoms of asthma were examined, multivariate analyses showed that youth with an anxiety or depressive disorder were significantly more likely to report all of the 6 asthma-specific symptoms when compared with those without an anxiety or depressive disorder (Table 3). They were also significantly more likely to report other physical symptoms from the CHSA-T scale, such as headache or itchy eyes. The odds ratios (ORs) for these associations ranged from 1.74 to 3.44, indicating a strong association between having an anxiety or depressive disorder and asthma and related medical symptom reporting.
Table 4 describes the multivariate analysis that com-pares the percentage of patients reporting each asthma symptom among youth meeting objective criteria for the severity of asthma (having ⱖ1 of the following in the
previous 12 months: asthma hospitalization, ED visit for asthma, a course of oral steroids, and ⱖ4 visits for asthma). Twenty-six percent of youth had ⱖ1 of these measures of severity. After controlling for the presence ofⱖ1 anxiety or depressive disorder and other potential confounders, youth with more severe asthma based on these objective criteria were significantly more likely to report only 2 of the 11 symptoms from the CHSA-T symptom scale: headache and itchy eyes. As a sensitivity analysis, we examined more restrictive severity criteria for asthma (having ⱖ2 ED visits for asthma, ⱖ1 inpa-tient hospitalization, or ⱖ2 oral steroid courses for asthma in the previous 12 months). Ten percent of the sample (n⫽79) met these more stringent severity cri-teria. Youth with the more stringent criteria compared with those with less severe asthma were significantly more likely to report tightness in the chest in the previ-ous 2 weeks (OR: 2.02; 95% CI: 1.20 to 3.39) and itchy eyes (OR: 2.00; 95% CI: 1.16 to 3.44) but were not significantly more likely to report other asthma-specific or less-specific physical symptoms.
In this large population-based sample of adolescents with asthma, we found that youth with an anxiety or depressive disorder reported significantly more asthma symptom days in the past 2 weeks than youth without anxiety or depressive disorders after controlling for asthma severity. The number of asthma symptoms re-ported was also significantly associated with the number of anxiety and depressive symptoms reported indicating that youth with more symptomatic anxiety and depres-sive disorders also had a higher symptom burden for their asthma. Finally, after controlling for objective mea-sures of asthma severity, youth with anxiety and depres-sive disorders were also significantly more likely to re-FIGURE 1
Mean number of asthma symptoms as a function of number of anxiety-depressive symp-toms; 62 possible anxiety-depressive symptoms, all means are adjusted for covariates.
TABLE 3 Relationship of Anxiety or Depressive Disorder to Asthma Symptoms
Symptom Anxiety or Depressive Disorder,
Asthma-speciﬁc symptoms from CHSA-T
Shortness of breath 69 (55.6) 206 (32.1) 2.42 (1.60 to 3.65)
Tightness in the chest 55 (44.0) 164 (25.5) 2.22 (1.46 to 3.37)
Wheezing without a cold 56 (44.8) 155 (24.1) 2.57 (1.69 to 3.90)
Cough 68 (54.8) 239 (37.2) 2.02 (1.34 to 3.03)
A cold that won’t go away 43 (35.0) 144 (22.4) 1.74 (1.12 to 2.70)
Wheezing with a cold 50 (40.0) 142 (22.1) 2.05 (1.34 to 3.14)
Related physical symptoms from CHSA-T
Headache 66 (52.8) 195 (30.4) 2.00 (1.32 to 3.04)
Skin rash 16 (13.0) 38 (5.9) 2.64 (1.35 to 5.16)
Itchy eyes 46 (36.8) 129 (20.2) 2.32 (1.50 to 3.60)
Stuffy nose or congestion 87 (70.2) 358 (55.7) 1.94 (1.25 to 3.00) Difﬁculty sleeping, such as trouble
falling asleep or waking in the night coughing or short of breath
82 (66.1) 220 (34.3) 3.45 (2.25 to 5.29)
aAdjusted for age, gender, parental education, race, ethnicity, modiﬁed HEDIS severity measure, duration of asthma, treatment intensity, and
port each of the 6 individual asthma-specific symptoms, as well as the 5 less-specific physical symptoms on a standardized asthma questionnaire.
To our knowledge, this is the first study examining the association between anxiety/depressive disorders and asthma symptom burden in a population-based sample of youth with asthma and adds to a growing literature describing a strong relationship between phys-ical symptoms and psychologphys-ical distress among persons with chronic medical disorders, such as inflammatory bowel disease, diabetes, and coronary artery disease.39In
a recent study of a small school-based sample of adoles-cents with asthma and other chronic diseases, social phobia was found to be predictive of the number and intensity of respiratory symptoms reported, and other anxiety conditions were found to be associated with the number and intensity of related somatic symptoms.40
These studies suggesting an increase in symptoms for youth with asthma are similar to what has been seen for other chronic diseases. Among adults, the presence of a depressive disorder has been shown to be a stronger predictor of reporting each of 10 diabetes symptoms than the hemoglobin A1C level or the presence of ⱖ2 diabetes complications.41In another study, the presence
of depression was more highly associated with chest pain and fatigue than objective measures of coronary artery disease severity.42
There are many potential reasons that youth with anxiety and depressive disorders may report more symp-toms of asthma. First, asthma is associated with frequent somatic symptoms, such as breathlessness or chest tight-ness. Individuals with comorbid mental health disorders have been shown to have more difficulty adapting to aversive symptoms of their diseases.43Similarly,
depres-sive disorders can be associated with increased focus on
illness episodes and medical symptoms.44This may result
in a higher perception and report of symptoms for youth with depressive and anxiety disorders in the absence of objectively measured differences in severity. Given the similarities of symptoms between asthma and anxiety disorders, it is also possible that youth may have diffi-culty distinguishing between symptoms because of asthma and those because of anxiety. Although youth in our questionnaire were asked specifically about symp-toms that they attribute to their asthma, it is not clear whether individuals with asthma and anxiety disorders can accurately distinguish the different causes of their symptoms. Finally, it is possible that, through physio-logic mechanisms, the stress related to anxiety and de-pressive disorders may trigger airway obstruction result-ing in more symptoms.45Because of the cross-sectional
nature of these data, we are unable to draw conclusions of causality; however, given the observed associations, assessing for anxiety and depression may be an impor-tant part of assessing youth with asthma.
In contrast to the strong association between having an anxiety or depressive disorder and asthma symptom burden, youth meeting objective criteria for more severe asthma were not more likely to report any of the asth-ma-specific symptoms evaluated and were only more likely to report a few of the nonspecific medical symp-toms. Often asthma severity is assessed by frequency of reported symptoms in combination with pulmonary function testing. We did not have pulmonary function testing results on this population. Because symptoms were an outcome for this analysis, we tried to select a measure of severity that was not dependent on symptom reporting. We did explore more stringent measures of severity using administrative data, but they did not sub-stantially change the analysis for anxiety and depression.
TABLE 4 Relationship of Asthma Symptoms to Asthma Severity Adjusted for Presence of Anxiety or Depressive Disorder
Asthma Symptom ⱖ1 Severity Indicator (n⫽232),N(%)a
Adjusted OR (95% CI)b Asthma speciﬁc symptoms from CHSA-T
Shortness of breath 87 (37.3) 190 (35.4) 0.97 (0.69 to 1.37)
Tightness in the chest 78 (33.6) 141 (26.3) 1.28 (0.90 to 1.83)
Wheezing without a cold 75 (32.3) 137 (25.5) 1.32 (0.92 to 1.88)
Cough 94 (40.7) 214 (39.9) 0.99 (0.71 to 1.38)
A cold that won’t go away 56 (24.0) 133 (24.8) 0.82 (0.56 to 1.20)
Wheezing with a cold 67 (28.8) 126 (23.5) 1.23 (0.86 to 1.78)
Related physical symptoms from CHSA-T
Headache 95 (40.8) 166 (31.0) 1.45 (1.02 to 2.05)
Skin rash 17 (7.4) 38 (7.1) 1.11 (0.58 to 2.10)
Itchy eyes 75 (32.3) 99 (18.6) 1.87 (1.29 to 2.71)
Stuffy nose or congestion 151 (65.4) 294 (54.7) 1.38 (0.99 to 1.93) Difﬁculty sleeping, such as trouble
falling asleep, waking in the night coughing or short of breath
108 (46.6) 195 (36.3) 1.38 (0.99 to 1.94)
aSeverity indicators: ER visit, inpatient visit, oral steroids, orⱖ4 outpatient visits.
The lack of association in our study may be because of the fact that our asthma measure is based on health care use, which measures not only disease severity but also individuals seeking treatment for the disease. Treatment seeking may be influenced by many factors other than symptoms, such as ability to cope with symptoms, self-efficacy, and access to care.
It is also possible that youth who had increased health care use for asthma in the previous year were more likely to be treated with a controller medication, which decreased their symptoms at the time of the survey. To assess this possibility, we evaluated whether the associ-ation between asthma severity and symptom reporting was different for youth on controller medications versus those not on controller medications. We did not find a significant difference between these 2 groups, suggesting that the lack of association was not because of improved controller medication use. Another possible reason for the lack of association between our asthma severity measure and symptom reporting is the episodic nature of asthma. Our severity measure was based on use in the previous year, whereas the symptom reporting was based on the previous 2 weeks.
Strengths of this study include the large population-based primary care sample of youth with asthma and the use of automated data to identify objective markers of asthma severity and medical comorbidity. It is possible that pulmonary function testing may have had a higher association with symptom reporting than the measure we used. However, given the strong associations be-tween anxiety and depressive disorders and symptom reporting (both asthma-specific symptoms and more general symptoms) and the fact that anxiety and depres-sive disorders seemed to be only weakly linked to con-troller medication use and other measures of severity in our analysis, the use of pulmonary function tests as a severity measure would be unlikely to substantially change the observed associations for anxiety and depres-sive disorders. It is possible that our severity measure was not precise enough to fully measure confounding. To the degree that misclassification occurred, we may have overestimated or underestimated the association between anxiety and depressive disorders and symptom burden. However, the association that we observed is consistent in direction with the one previous study in this area and numerous other studies of the impact of anxiety and depressive disorders on symptom reporting in other chronic diseases, such as diabetes and coronary artery disease.
The other main limitation of the study is that because this study was conducted in a sample from a Northwest group model health maintenance organization, the re-sults may not generalize to populations in other health care settings or different regions of the country.
Health care providers are often challenged by patients who report higher levels of physical symptoms than
other patients with comparable disease severity. Physi-cians report higher levels of frustration with patients who have high numbers of unexplained symptoms.46,47
Depression has also been shown to be associated with differential views of severity of medical concerns be-tween patients and physicians with patients perceiving their symptoms as more severe than clinicians.48 High
levels of symptoms that do not correlate with physical findings should prompt providers to assess for anxiety and depression. The recognition of anxiety or depression may decrease physician frustration, decrease the use of unnecessary testing and treatments, and allow physi-cians to more appropriately target interventions that meet the needs of the patient.
Irrespective of whether anxiety/depressive disorders are the cause or a consequence of asthma symptoms or because of a common underlying factor, recognition and treatment of these mental health disorders among per-sons with asthma can be expected to improve symptom burden and quality of life. Although this cross-sectional study cannot demonstrate that the treatment of anxiety and depressive disorders will reduce the severity of asthma symptoms, it does suggest that these disorders are associated with a higher likelihood of reporting a broad range of physical symptoms of asthma and medi-cally related symptoms. It will be important to test in future studies whether identifying and treating anxiety and depressive disorders in youth with asthma will re-sult in decreased asthma symptom burden.
This work was supported by a grant from the National Institute of Mental Health (MH 67587). Dr Richardson is funded by a K23 award from the National Institute of Mental Health K23 (3K23 MH069814-01A1).
We give special thanks to Michelle Garrison for her editorial assistance.
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GRADING SURGEONS MAY BE HEALTHY PRACTICE
“In a society that champions consumer choice and market forces as the best ways to do nearly everything, medicine stands out as an exception. Most Americans know very little about choosing, say, a heart surgeon. They simply take their primary-care physician’s advice or blindly pick a surgeon from those covered by their insurance plan. For more than a decade, a handful of states, notably Pennsylvania and New York, have been issuing public report cards on individual surgeons that show the rates of death and complication of their heart-bypass patients. After all, practicing doctors and nurses know which surgeons are good, and which are to be avoided. Shouldn’t the rest of us know, too? But report cards remain surprisingly controversial, and not only among doctors being graded. Daniel Kessler, a Stanford University economist, divides the debate into three camps. One says report cards boost the quality of health care. A second says they don’t have much effect, good or bad, because ordinary patients ignore them. And a third group, to which Mr. Kessler belongs, holds that report cards may have some beneficial effects, but those could be outweighed by unwelcome, unintended consequences— such as encouraging doctors and hospitals to game the system by avoiding sicker patients, thereby reducing the overall quality of health care. (States attempt the tricky technical task of adjusting data so doctors who take tougher cases are compared meaningfully to [those] who take easier cases. Surgeons and other skeptics often criticize the precision of such adjustments.) . . . In Maine, New Hampshire and Vermont, heart surgeons have been sharing performance data privately since 1987. Quality has improved, best practices have been adopted and differences among eight heart centers nar-rowed—without sharing details publicly. The absence of public report cards bred ‘a spirit of collaboration instead of a spirit of paranoia,’ says William Nugent, a heart surgeon at Dartmouth-Hitchcock Medical Center. But seeing the national trend, the consortium plans soon to release results publicly— by hospital, not by surgeon.”
Laura P. Richardson, Paula Lozano, Joan Russo, Elizabeth McCauley, Terry Bush and
Asthma Symptom Burden: Relationship to Asthma Severity and Anxiety and
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