Abstract
Objective
Important differences between men and women with asthma have been demonstrated, with women describing more symptoms and worse asthma-related quality of life (QOL) despite having similar or better pulmonary function. While current guidelines focus heavily on assessing asthma control, they lack information about whether sex-specific approaches to asthma assessment should be considered. We sought to determine if sex differences in asthma control or symptom profiles exist in the well-characterized population of participants in the American Lung Association Asthma Clinical Research Centers (ALA-ACRC) trials.
Methods
We reviewed baseline data from four trials published by the ALA-ACRC to evaluate individual item responses to three standardized asthma questionnaires: the Juniper Asthma Control Questionnaire (ACQ), the multi-attribute Asthma Symptom Utility Index (ASUI), and Juniper Mini Asthma Quality of Life Questionnaire (mini-AQLQ).
Results
In the poorly-controlled population, women reported similar overall asthma control (mean ACQ 1.9 vs. 1.8; p=0.54), but were more likely to report specific symptoms such as nocturnal awakenings, activity limitations, and shortness of breath on individual item responses. Women reported worse asthma-related QOL on the mini-AQLQ (mean 4.5 vs. 4.9; p<0.001) and more asthma-related symptoms with a lower mean score on the ASUI (0.73 vs. 0.77; p=<0.0001) and were more likely to report feeling bothered by particular symptoms such as coughing, or environmental triggers.
Conclusions
In participants with poorly-controlled asthma, women had outwardly similar asthma control, but had unique symptom profiles on detailed item analyses which were evident on evaluation of three standardized asthma questionnaires.
INTRODUCTION
Population studies reveal sex-related differences in asthma that change with age. In children and early adolescents, asthma is more common in boys 1–3. After puberty, asthma becomes more common and more severe in women. Women with asthma describe more symptoms and worse quality of life (QOL) than men despite having comparable or better pulmonary function 4–7. Similarly, women with asthma report greater healthcare utilization 4–6 and more frequent use of short acting beta-agonists (SABA) 5–7 than men. While the reasons for these observed sex-related differences in asthma morbidity and disease expression have not been fully explained, differences in perception of air flow obstruction 5,8, increased bronchial hyper-responsiveness in women as a result of increased susceptibility to tobacco smoke 9–10, and hormonal influences 11–13 have all been proposed as potential hypotheses.
Sex specific treatment approaches to asthma care have been developed, and have shown benefit to women when compared to standard nonspecific approaches 14–15. Despite these findings, current asthma guidelines 16 lack information about whether sex-specific approaches to asthma assessment should be considered. Using detailed evaluation of previously validated questionnaires, we sought to determine if sex differences in asthma control or symptom profiles exist in the population of participants in the American Lung Association Asthma Clinical Research Centers (ALA-ACRC) trials, supporting the need for sex-specific approaches to asthma assessment. Some of the results have been reported previously in the form of an abstract 17. By examining commonly utilized questionnaires in this manner, the ALA-ACRC data offer a unique approach to the evaluation of the potential influence of sex on the assessment of asthma morbidity and quality of life, and take advantage of a large well characterized population of participants.
METHODS
Study design and participants
The ALA-ACRC is a multi-center network of 20 centers dedicated to improving asthma care through clinical research in diverse populations. We evaluated data collected at enrollment from four published trials 18–21 by the ALA-ACRC to evaluate item responses of men and women to three standardized asthma questionnaires. A detailed description of the design and inclusion/exclusion criteria for each study is provided elsewhere 18–21.
The analyses included one trial of participants with well-controlled asthma (the Leukotriene or Corticosteroid or Corticosteroid-Salmeterol [LOCCS] trial 20) and three trials of participants with poorly-controlled asthma (Effectiveness of Low Dose Theophylline as Add-On Therapy In Treatment of Asthma [LODO]18, Study of Acid Reflux and Asthma [SARA]19, and the Trial of Asthma Patient Education [TAPE]21) as determined by criteria for study enrollment. Eligibility criteria for each trial are included in the online supplement (Appendix). Participants 17 years of age or older were included.
Demographic and clinical assessments
Data were obtained from the baseline assessments of participants prior to the initiation of study interventions. Demographic and clinical data including targeted co-morbid conditions were evaluated.
Sex-specific item analysis of standard asthma questionnaires
Asthma control was assessed with the seven-question Juniper Asthma Control Questionnaire (ACQ) 22 (range, 0 to 6, with lower scores indicating less severe asthma and 0.5 units considered a minimal clinically important difference [MID] 23, with scores ≥1.5 defined as poor control). Asthma symptoms were evaluated with the multi-attribute Asthma Symptom Utility Index (ASUI) 24 (range, 0 to 1, with higher scores indicating less severe asthma and 0.09 considered a MID 25). Asthma-related QOL was assessed with the Juniper Mini Asthma Quality of Life Questionnaire (mini-AQLQ) 26 (range, 1 to 7, with higher scores indicating better QOL and 0.5 considered the MID) 19. We examined overall scores and individual item responses for sex-related differences in controlled versus poorly-controlled asthmatics.
Statistical analysis
Data from participants enrolled in more than one trial were included only from the latest trial in which the participant enrolled. Analyses were stratified by control status (controlled vs. poorly-controlled) as defined by the criteria required for trial eligibility 18–21. For continuous variables, analyses were adjusted for trial, and as specified, other characteristics using linear regression models; non-adjusted analyses were based on Wilcoxon Rank Sum Tests. For categorical variables, unadjusted analyses were performed using Chi-square and Fisher’s Exact Tests; analyses including covariate adjustments were performed with logistic regression models. For analysis of specific questionnaire items, responses were categorized by presence or absence of the symptom. Analyses were performed in SAS version 9.2 (SAS Institute).
RESULTS
Demographic and clinical characteristics
We reviewed baseline data of 1612 participants (287 well-controlled asthmatics from LOCCS and 1325 poorly-controlled asthmatics from LODO [n=412], TAPE [n=514], and SARA [n=399] respectively). Ages ranged from 17–85, and the majority (70%) was women. Participants were stratified by asthma control and further compared by sex using baseline demographic and clinical characteristics (Tables 1A and 1B).
Table 1.
| A: Demographic and baseline clinical characteristics of well-controlled asthma population | |||||
|---|---|---|---|---|---|
| Women N=181(63%) |
Men N=106(37%) |
P-value | |||
| Demographic and clinical characteristics | |||||
| N | Mean(SD) | N | Mean(SD) | ||
| Age in years | 181 | 35.7(13.2) | 106 | 33.6(11.2) | 0.36 |
| Race | N | % | N | % | |
| White | 126 | 70 | 71 | 67 | 0.17 |
| Black | 44 | 24 | 22 | 21 | |
| Other | 11 | 6 | 13 | 12 | |
| Hispanic | |||||
| Yes | 14 | 8 | 10 | 9 | 0.62 |
| No | 167 | 92 | 96 | 91 | |
| Smoking status | |||||
| Current | 12 | 7 | 7 | 7 | 0.69 |
| Former | 40 | 22 | 19 | 18 | |
| Never | 129 | 71 | 80 | 75 | |
| N | Mean(SD) | N | Mean(SD) | ||
| BMI (kg/m2) | 181 | 28.7(7.6) | 106 | 27.7(5.7) | 0.85 |
| Other self-reported conditions | N | % | N | % | |
| GERD | 46 | 25 | 22 | 21 | 0.37 |
| Eczema | 27 | 15 | 12 | 11 | 0.39 |
| Chronic sinusitis | 65 | 36 | 19 | 18 | 0.001 |
| Food allergies | 49 | 27 | 21 | 20 | 0.17 |
| Allergic rhinitis | 110 | 61 | 62 | 58 | 0.70 |
| Asthma characteristics | |||||
| Asthma exacerbation in prior year | 60 | 33 | 27 | 25 | 0.17 |
| Allergies reported trigger for asthma | 149 | 82 | 90 | 85 | 0.57 |
| N | Mean(SD) | N | Mean(SD) | ||
| Age of asthma diagnosis in years | 177 | 17.0 (15.0) | 104 | 15.1 (15.1) | 0.18 |
| Pulmonary function | |||||
| Pre-bronchodilator FEV1 % predicted | 181 | 92.4 (10.7) | 106 | 89.4 (9.4) | <0.01 |
| Post-bronchodilator FEV1 % predicted | 180 | 97.6 (11.4) | 103 | 95.9 (11.2) | 0.13 |
| % change FEV1 | 180 | 5.6 (5.9) | 103 | 7.4 (6.8) | 0.06 |
| Pre-bronchodilator FVC% predicted | 181 | 100.3 (12.5) | 106 | 99.8 (12.8) | 0.81 |
| Post-bronchodilator FVC% predicted | 180 | 101.6 (14.2) | 103 | 100.2 (13.7) | 0.62 |
| % change FVC | 180 | 1.3 (9.1) | 103 | 0.6 (5.6) | 0.47 |
| PC20 methacholine (mg/dL) | 35 | 3.7 (3.6) | 23 | 3.7 (4.2) | 0.82 |
| Chronic asthma medications | N | % | N | % | |
| Inhaled SABA | 120 | 66 | 71 | 67 | 0.91 |
| ICS | 38 | 21 | 27 | 25 | 0.38 |
| LABA | 13 | 7 | 4 | 4 | 0.31 |
| LABA/ICS | 68 | 38 | 28 | 26 | 0.05 |
| Leukotriene modifiers | 30 | 17 | 10 | 9 | 0.09 |
| Inhaled anticholinergics | 4 | 2 | 0 | 0 | 0.30 |
| Cromolyn sodium or nedocromil | 5 | 3 | 1 | 1 | 0.42 |
| Oral beta-agonists | 1 | 1 | 0 | 0 | >.99 |
| Methylxanthines | 1 | 1 | 0 | 0 | >.99 |
| Oral corticosteroids | 0 | 0 | 1 | 1 | 0.37 |
| Herbal or natural supplements | 32 | 18 | 9 | 8 | 0.03 |
| B: Demographic and baseline clinical characteristics of poorly-controlled asthma population | |||||
|---|---|---|---|---|---|
| Women N=953(72%) |
Men N=372 (28%) |
P-value* | |||
| Demographic and clinical characteristics | |||||
| N | Mean(SD) | N | Mean(SD) | ||
| Age in years | 953 | 40.9(13.8) | 372 | 39.6(14.2) | 0.09 |
| Race | N | % | N | % | |
| White | 563 | 59 | 217 | 58 | 0.62 |
| Black | 316 | 33 | 120 | 32 | |
| Other | 74 | 8 | 35 | 9 | |
| Hispanic | |||||
| Yes | 81 | 9 | 29 | 8 | 0.68 |
| No | 872 | 92 | 343 | 92 | |
| Smoking status | |||||
| Current | 51 | 5 | 20 | 5 | 0.18 |
| Former | 336 | 35 | 151 | 41 | |
| Never | 566 | 59 | 201 | 54 | |
| N | Mean(SD) | N | Mean(SD) | ||
| BMI (kg/m2) | 951 | 31.4(8.7) | 371 | 28.7(6.1) | <.0001 |
| Other self-reported conditions | N | % | N | % | |
| GERD | 248 | 26 | 76 | 20 | 0.03 |
| Eczema | 111 | 17 | 31 | 12 | 0.04 |
| Chronic sinusitis | 422 | 44 | 107 | 29 | <.0001 |
| Food allergies | 138 | 21 | 54 | 20 | 0.73 |
| Allergic rhinitis | 626 | 66 | 230 | 62 | 0.19 |
| Asthma characteristics | |||||
| Asthma exacerbation in prior year | 440 | 46 | 134 | 36 | <0.001 |
| Allergies reported trigger for asthma | 791 | 83 | 286 | 77 | 0.01 |
| N | Mean(SD) | N | Mean(SD) | ||
| Age of asthma diagnosis in years | 933 | 19.1(16.6) | 365 | 16.4(16.9) | <0.001 |
| Pulmonary function | |||||
| Pre-bronchodilator FEV1 % predicted | 953 | 82.5(15.4) | 371 | 78.0(16.3) | <.0001 |
| Post-bronchodilator FEV1 % predicted | 948 | 89.1(15.0) | 370 | 85.2(15.5) | <.0001 |
| % change FEV1 | 948 | 9.0(11.2) | 370 | 10.4(14.3) | <0.01 |
| Pre-bronchodilator FVC% predicted | 952 | 89.9(14.5) | 371 | 90.5(15.9) | 0.35 |
| Post-bronchodilator FVC% predicted | 948 | 93.5(14.7) | 370 | 95.0()14.5 | 0.03 |
| % change FVC | 948 | 4.5(9.5) | 370 | 5.9(11.7) | 0.01 |
| PC20 methacholine (mg/dL) | 128 | 3.3(4.3) | 47 | 3.3(4.1) | 0.82 |
| Chronic asthma medications | N | % | N | % | |
| Inhaled SABA | 779 | 82 | 323 | 87 | 0.03 |
| ICS | 265 | 28 | 112 | 30 | 0.40 |
| LABA | 90 | 9 | 36 | 10 | 0.90 |
| LABA/ICS | 550 | 58 | 201 | 54 | 0.24 |
| Leukotriene modifiers | 109 | 11 | 32 | 9 | 0.14 |
| Inhaled anticholinergics | 26 | 3 | 7 | 2 | 0.37 |
| Cromolyn sodium or nedocromil | 5 | 1 | 4 | 1 | 0.28 |
| Oral beta-agonists | 4 | <1 | 1 | <1 | >0.99 |
| Methylxanthines | 3 | <1 | 3 | 1 | 0.36 |
| Oral corticosteroids | 17 | 2 | 2 | 1 | 0.12 |
| Herbal or natural supplements | 86 | 13 | 28 | 11 | 0.25 |
SD = standard deviation; BMI = body mass index; GERD = gastroesophageal reflux disease; FEV1 = forced expiratory volume in one second; FVC = forced vital capacity; PC20 = provocative concentration of methacholine; SABA = short-acting beta-agonist; ICS = inhaled corticosteroid; LABA = long-acting beta-agonist
Among poorly-controlled participants, men were diagnosed with asthma at an earlier age (16.4 ± 16.9 vs. 19.4 ± 16.6 years; p<0.001), and had a lower BMI (28.7 ± 6.1 vs. 31.4 ± 8.7 kg/m2; p<0.001). Men reported more frequent use of SABA and had a lower mean % predicted post-bronchodilator forced expiratory volume in one second (FEV1) (85.2 ± 15.5 vs. 89.1 ± 15.0; p<0.01) but no difference in bronchial hyper-responsiveness as defined by methacholine challenge. Women were more likely to report concomitant gastroesophageal reflux disease (GERD) (26% vs. 20%; p=0.03), eczema (17% vs. 12%; p=0.04), and sinusitis (44% vs. 29%; p<0.001), and were more likely to report allergy-exacerbated asthma symptoms (83% vs. 77%; p=0.01) or treatment for an exacerbation in the last year (46% vs. 36%; p<0.001).
For controlled subjects, there were few differences noted between men and women. Men had a lower mean % predicted pre-bronchodilator FEV1 (89.4 ± 9.4 vs. 92.4 ± 10.7; p<0.01), and women were more likely to report concomitant sinusitis (36% vs. 18%; p=0.001).
Item responses to asthma questionnaires
In the poorly-controlled population, women reported similar overall asthma control (mean ACQ 1.9 vs. 1.8; p=0.54), but were more likely to report frequent nocturnal awakenings, more limitations in activities, and more shortness of breath related to their asthma (Table 2) than men on individual item responses. Women also reported worse asthma-related QOL on the mini-AQLQ (mean 4.5 vs. 4.9; p<0.001 respectively) (Table 3) where they were more likely to report feeling bothered by symptoms such as coughing (72% vs. 60%; p<0.001), or environmental triggers for asthma such as dust (85% vs. 73%; p<0.001), cigarette smoke (81% vs. 68%; p<0.001), and weather and air pollution (66% vs. 47%; p<0.0001), and were more likely to report limitations with activities. They were also more likely to report difficulty sleeping related to their asthma (57% vs. 48%; p=0.01). After adjusting for the increased frequency of co-morbid conditions in women, differences in reported shortness of breath noted on the ACQ and reports of interference with sleep or social activities on the mini-AQLQ were no longer significant. However, the rest of the item responses evaluated were unaffected.
Table 2.
Juniper Asthma Control Questionnaire (ACQ) responses for poorly-controlled subjects
| Women N=952 (72%) |
Men N=372 (28%) |
|||||||
|---|---|---|---|---|---|---|---|---|
| Mean | SD | 95% CI | Mean | SD | 95% CI | p | p* | |
| ACQ7 | 1.9 | 0.8 | 1.9,2.0 | 1.8 | 0.8 | 1.8,1.9 | .54 | 0.36 |
| Woken by asthma past week? |
1.5 | 1.3 | 1.4,1.6 | 1.3 | 1.2 | 1.1,1.4 | <0.01 | 0.02 |
| How bad were symptoms? |
1.9 | 1.1 | 1.9,2.0 | 1.8 | 1.1 | 1.7,1.9 | 0.08 | 0.11 |
| How limited in activities? |
1.8 | 1.2 | 1.7,1.9 | 1.5 | 1.2 | 1.4,1.6 | 0.001 | 0.02 |
| How much shortness of breath did you experience? |
2.5 | 1.1 | 2.4,2.5 | 2.3 | 1.1 | 2.1,2.4 | 0.03 | 0.07 |
| How much time did you wheeze? |
2.0 | 1.3 | 1.9,2.1 | 1.9 | 1.2 | 1.8,2.0 | 0.89 | 0.68 |
| How many puffs of short-acting bronchodilator each day? |
1.5 | 1.0 | 1.5,1.6 | 1.5 | 1.1 | 1.4,1.6 | 0.91 | 0.75 |
Individual item responses were analyzed by sex of respondent, and describe the preceding seven days.
ACQ7 = seven question asthma control questionnaire; SD = standard deviation; CI = 95% confidence interval; FEV1= forced expiratory volume in one second;
p = p-value adjusted for trial, age, race and body mass index.
p* = p-value adjusted for trial, age, race, body mass index, gastroesophageal reflux disease, eczema, sinusitis, and rhinitis.
Table 3.
Mini Asthma Quality of Life Questionnaire (AQLQ) in poorly controlled subjects.
| Women | Men | ||||||
|---|---|---|---|---|---|---|---|
| Mean(SD) | Median | Mean(SD) | Median | p | p* | ||
| AQLQ Score | 4.5(1.2) | 4.5 | 4.9(1.1) | 5.0 | <.0001 | 0.001 | |
| Women | % | Men | % | ||||
| Feel short of breath as a result of your asthma? |
No time | 148 | 16% | 76 | 20% | 0.08 | 0.20 |
| Any time | 804 | 84% | 296 | 80% | |||
| Feel bothered by or have to avoid dust in the environment? |
No time | 139 | 15% | 100 | 27% | <0.0001 | <0.0001 |
| Any time | 813 | 85% | 272 | 73% | |||
| Feel frustrated as a result of your asthma? |
No time | 340 | 36% | 147 | 40% | 0.44 | 0.94 |
| Any time | 612 | 64% | 225 | 60% | |||
| Feel bothered by coughing? |
No time | 264 | 28% | 149 | 40% | <0.001 | 0.01 |
| Any time | 688 | 72% | 223 | 60% | |||
| Feel afraid of not having your asthma medication? |
No time | 431 | 45% | 151 | 41% | 0.09 | 0.04 |
| Any time | 521 | 55% | 221 | 59% | |||
| Experience a feeling of chest tightness or chest heaviness? |
No time | 245 | 26% | 113 | 30% | 0.11 | 0.86 |
| Any time | 707 | 74% | 259 | 70% | |||
| Feel bothered by or have to avoid cigarette smoke in the environment? |
No time | 180 | 19% | 118 | 32% | <0.0001 | <0.001 |
| Any time | 772 | 81% | 254 | 68% | |||
| Have difficulty getting a good night's sleep as a result of your asthma? |
No time | 406 | 43% | 193 | 52% | 0.01 | 0.10 |
| Any time | 546 | 57% | 179 | 48% | |||
| Feel concerned about having asthma? |
No time | 343 | 36% | 140 | 38% | 0.98 | 0.58 |
| Any time | 609 | 64% | 232 | 62% | |||
| Experience a wheeze in your chest? |
No time | 276 | 29% | 119 | 32% | 0.62 | 0.68 |
| Any time | 676 | 71% | 253 | 68% | |||
| Feel bothered by or have to avoid going outside because of weather or air pollution? |
No time | 327 | 34% | 198 | 53% | <0.0001 | <0.001 |
| Any time | 625 | 66% | 174 | 47% | |||
| Limitations with strenuous activities? |
No time | 235 | 25% | 139 | 37% | <0.001 | <0.01 |
| Any time | 717 | 75% | 233 | 63% | |||
| Limitations with moderate activities? |
No time | 400 | 42% | 228 | 61% | <.0001 | <0.001 |
| Any time | 552 | 58% | 144 | 39% | |||
| Limitations with social activities? |
No time | 644 | 68% | 282 | 76% | 0.04 | 0.06 |
| Any time | 308 | 32% | 90 | 24% | |||
| Limitations with workrelated activities? |
No time | 631 | 66% | 270 | 73% | 0.17 | 0.46 |
| Any time | 321 | 34% | 102 | 27% | |||
Individual item responses were analyzed by sex of respondent, and describe the preceding two weeks.
p=p-value adjusted for age, race, and body mass index.
p*= p-value adjusted for trial, age, race, body mass index, gastroesophageal reflux disease, eczema, sinusitis, and rhinitis. SD = standard deviation
Among participants with poorly-controlled asthma, women reported more asthma-related symptoms with a lower mean score on the ASUI (0.73 vs. 0.77; p=<0.0001) (Table 4). Compared to men, women were more likely to report feeling bothered by coughing (80% vs. 67%; p<0.001), were more likely to describe symptoms such as coughing, wheezing, and shortness of breath as moderate or severe (p<0.001, p=0.03, and p<0.01 respectively), and were more likely to report nocturnal asthma symptoms (62% vs. 50%; p<0.001). After adjusting for the increased frequency of co-morbid conditions in women, severity of wheezing and shortness of breath were no longer significant but the other item responses were not affected.
Table 4.
Asthma symptom utility index (ASUI) in poorly-controlled subjects
| Women (n= 953, 72%) | Men (n= 372, 28%) | ||||||
|---|---|---|---|---|---|---|---|
| Mean(SD) | Median | Mean(SD) | Median | P | p* | ||
| ASUI Score | 0.73(0.16) | 0.75 | 0.77(0.14) | 0.80 | <.0001 | <0.01 | |
| Women | % | Men | % | ||||
| How many days were you bothered by coughing? |
Not at all | 189 | 20% | 121 | 33% | <.0001 | <0.001 |
| Others | 764 | 80% | 251 | 67% | |||
| On average, how severe was your cough? |
Mild | 452 | 59% | 181 | 72% | <0.001 | 0.01 |
| Moderate | 277 | 36% | 61 | 24% | |||
| Severe | 35 | 5% | 9 | 4% | |||
| How many days were you bothered by wheezing? |
Not at all | 210 | 22% | 72 | 19% | 0.11 | 0.33 |
| others | 743 | 78% | 300 | 81% | |||
| On average, how severe was your wheezing? |
Mild | 497 | 67% | 226 | 75% | 0.03 | 0.08 |
| Moderate | 230 | 31% | 70 | 23% | |||
| Severe | 16 | 2% | 4 | 1% | |||
| How many days were you bothered by shortness of breath? |
Not at all | 79 | 8% | 38 | 10% | 0.47 | 0.83 |
| others | 874 | 92% | 334 | 90% | |||
| On average, how severe was your shortness of breath? |
Mild | 522 | 60% | 235 | 70% | <0.01 | 0.12 |
| Moderate | 326 | 37% | 94 | 28% | |||
| Severe | 26 | 3% | 5 | 2% | |||
| How many days were you awakened at night by your asthma? |
Not at all | 364 | 38% | 186 | 50% | <0.001 | 0.001 |
| Others | 589 | 62% | 186 | 50% | |||
| On average, how much of a problem was being awakened at night? |
Mild | 368 | 62% | 127 | 68% | 0.12 | 0.10 |
| Moderate | 199 | 34% | 54 | 29% | |||
| Severe | 22 | 4% | 5 | 3% | |||
| How many days were you bothered by side effects of asthma medications? |
Not at all | 756 | 79% | 318 | 85% | <0.01 | <0.01 |
| Others | 197 | 21% | 54 | 15% | |||
| On average, how severe were the side effects? |
Mild | 140 | 71% | 36 | 67% | 0.78 | 0.56 |
| Moderate | 53 | 27% | 18 | 33% | |||
| Severe | 4 | 2% | 0 | 0% | |||
Individual item responses were analyzed by sex of respondent, and describe the preceding two weeks.
p= pvalue adjusted for trial, age, race, and body mass index.
p* = p-value adjusted for trial, age, race, body mass index, gastroesophageal reflux disease, eczema, sinusitis, and rhinitis SD = standard deviation.
Similar analyses in the controlled population revealed few differences between men and women. The mean score on the ACQ was similar for men and women (0.7 vs. 0.7; p=0.53) and there were no significant differences noted on sex-specific analyses of the individual item responses (data not shown). Men and women also reported similar asthma-related QOL on the mini-AQLQ with mean scores of 5.9 and 5.7 (p=0.09) respectively. For the individual item responses, women were more likely to report feeling bothered by cigarette smoke (69% vs. 49%; p<0.01) or by weather and air pollution (36% vs. 21%; p=0.02), but there were otherwise no differences noted (data not shown). For the ASUI, women reported more overall asthma-related symptoms with a lower mean score of 0.87 vs. 0.90 (p=0.04), and were more likely to report being bothered by cough (46% vs. 33%; p=0.04). Otherwise, there were no significant differences noted. When adjusted for the presence of co-morbid conditions, there was no effect on the differences noted for individual item responses noted on the AQLQ, but there was no longer a statistical difference noted between men and women who reported coughing in the preceding two weeks on the ASUI (p=0.06).
DISCUSSION
The ALA-ACRC trials provide data on a group of well-characterized participants with asthma. The current analysis focuses on sex-related differences in a subgroup of participants 17 years of age or older enrolled in four clinical trials. Results showed that in participants with poorly-controlled asthma, women had outwardly similar asthma control as measured by the mean score on the seven-question ACQ, but reported more asthma symptoms and poorer asthma-related QOL, compared to men despite having better pulmonary function and similar baseline asthma medications. Interestingly, men reported more frequent use of SABA despite reporting less frequent asthma symptoms, suggesting that men may tend to under-report their asthma symptoms. Although the mean differences noted between poorly-controlled men and women on the ASUI and mini-AQLQ were statistically significant, they did not achieve the MID which has previously been described as important19,25, initially suggesting that there were no important sex differences in asthma symptoms or QOL. However, our data suggest there are sex-related differences for a subset of asthma symptoms that may be disguised when looking at overall scores. The subset of symptoms for which there were notable significant differences included nocturnal awakenings and limitation in activities, which are likely to influence QOL and resultant responses on QOL assessments. These sex-related differences in asthma symptom expression became much less evident in the setting of well-controlled disease.
Previous studies have demonstrated differences between the sexes in asthma symptoms and control 4–7,27. Survey data has shown that women report worse asthma control and greater healthcare utilization 6 despite noting more frequent use of controller medications 27. In addition, women frequently report worse asthma-related quality of life despite demonstrating better pulmonary function 4–5,7,28. In a cluster analysis of the Severe Asthma Research Program, Moore and colleagues described five distinct asthma phenotypes 29 including a group of primarily women with frequent co-morbid conditions and symptoms out of proportion to documented airflow obstruction. This phenotype bears a striking resemblance to the adult women with poorly-controlled asthma in the current study.
The data presented here extend the current understanding of the differences between adult men and women with asthma; we present an objectively characterized group of asthmatics, using a combination of standardized asthma control questionnaires and pulmonary function testing to hone in on those factors that may be contributing to poor asthma control in women, and how they differ from men. Accordingly, this study is the first to examine sex-specific responses to standardized questionnaires in a detailed fashion.
Few have attempted to assess sex-specific differences in asthma symptom profiles and asthma control on standard questionnaires. Lee and colleagues 4 assessed sex-related differences in severe asthmatics, and noted that when women reported more control problems on the Asthma Therapy Assessment Questionnaire (ATAQ) 30 they were more likely to report nocturnal awakenings and missed activities despite having better pulmonary function. In a survey of a managed care population, sex differences were noted in item responses to the mini-AQLQ, with women noting more asthma symptoms and specific triggers such as cigarette smoke, weather, and air pollution 6. Wijnhoven and colleagues 7 noted some sex-specific differences in item responses to the Quality of Life in Respiratory Illness Questionnaire 31 in a survey of patients with asthma in some age groups, but not others.
There are several possible explanations for the sex-specific differences noted in item responses to the questionnaires in this study. Women with poorly-controlled asthma reported more GERD and sinusitis, and were more likely to associate their asthma symptoms with allergies. These findings are similar to other studies 4,6 where women with asthma were more likely to report allergic co-morbidities or sinusitis, and seemed to be more susceptible to environmental triggers 27 than men. These conditions could potentially worsen asthma control, or perhaps more importantly, result in symptoms which mimic asthma and potentially influence the response on the questionnaires evaluated here. In the adjusted analysis, the presence of these factors altered the significance of a few, but not most, responses, suggesting that some differences may be related to their presence, while others may be inherent differences between men and women. Others have suggested that women may have increased bronchial hyper-responsiveness as a result of an increased susceptibility to tobacco smoke 9–10, perhaps contributing to this increased sensitivity to environmental triggers. However, we did not find a sex-related difference in the provocative concentration of methacholine (PC20) at baseline in our patients.
Another possible explanation may be an increased awareness of dyspnea or an increased tendency to manifest symptoms in women. It has been shown that inspiratory muscle strength is significantly greater in men than women with asthma, and is inversely related to dyspnea 8. Similarly, in healthy female nonsmokers, women demonstrate a lower cough reflex threshold associated with a greater urge to cough and a greater sense of dyspnea when compared to males 32. Finally, it is possible that factors such as pre-menstrual worsening of asthma 33–35 or increased anxiety and depression in women with asthma 36 which were not easily accounted for in this analysis could explain some of the sex-related differences we identified.
These findings support the fact that men and women experience asthma differently. As asthma care providers, this information can be used to begin developing sex-specific evaluation and treatment plans which target these differences. There are two major clinical implications of our results. Men may have poorer perception of their disease severity than women, as expressed by poorer pulmonary function and less impairment on standardized asthma questionnaires. This would imply that men need to be carefully screened with testing including lung function to accurately assess impairment. Women may have more severe disease in terms of asthma-related symptoms and impact on QOL despite having more preserved pulmonary function, and co-morbidities such as sinusitis may be particularly important in women. One size does not fit all for asthma assessment, and patients may benefit from sex-specific interventions. Clark and colleagues 14–15 have shown that female-specific asthma management improves asthma-related QOL and results in decreased use of rescue inhalers when compared to usual care.
A few limitations to our study must be noted. First, the cross-sectional study design provided only a single evaluation of each participant’s asthma control. Despite the use of standardized questionnaires, many findings were based on self-report and are subject to recall bias. Finally, the original ALA-ACRC studies were not designed to specifically address the question at hand.
CONCLUSION
Our findings suggest that using the overall score alone on currently available asthma questionnaires may not detect sex-specific differences in asthma symptoms, allowing asthma care providers to miss potential opportunities to develop targeted asthma care plans which may improve asthma control for their patients. In addition to utilizing these tools as a global assessment of asthma control, practitioners should be attentive to the potential differences in symptoms which men and women may experience and their potential impact on asthma-related QOL and functional limitation. While future research explores the need for more focused evaluation tools, providers should examine individual item responses with attention to particular sex-specific patterns which may signal areas of sub-optimal control.
Supplementary Material
Acknowledgments
This work was supported by grants from the National Institutes of Health—National Heart, Lung, and Blood Institute [RO1HL073494, 5U01HL072968]; the American Lung Association; GlaxoSmithKline; the Merck Company Foundation; and AstraZeneca.
ABBREVIATIONS
- ACQ
Asthma control questionnaire
- ALA-ACRC
American Lung Association Asthma Clinical Research Centers
- ASUI
Asthma symptom utility index
- ATAQ
Asthma therapy assessment questionnaire
- BMI
Body mass index
- FEV1
Forced expiratory volume in one second
- GERD
gastroesophageal reflux disease
- LOCCS
Leukotriene or Corticosteroid or Corticosteroid-Salmeterol trial
- LODO
Effectiveness of Low Dose Theophylline as Add-On Therapy In Treatment of Asthma
- MID
minimal clinically important difference
- mini-AQLQ
mini asthma quality of life questionnaire
- PC20
provocative concentration of methacholine
- QOL
quality of life
- SABA
short-acting beta-agonist
- SARA
Study of Acid Reflux and Asthma
- TAPE
Trial of Asthma Patient Education
Footnotes
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Author contributions:
JWM: study design; writing, review, and guarantor of manuscript.
JH: data analysis; review of manuscript.
CW: data analysis.
JP, CB, AD, LG: review of manuscript.
JGM: study design; review of manuscript.
Contributor Information
Jennifer W. McCallister, Email: Jennifer.McCallister@osumc.edu.
Janet T. Holbrook, Email: jholbroo@jhsph.edu.
Christine Y. Wei, Email: cwei@jhsph.edu.
Jonathan P. Parsons, Email: Jonathan.Parsons@osumc.edu.
Cathy G. Benninger, Email: Cathy.Benninger@osumc.edu.
Anne E. Dixon, Email: Anne.Dixon@vtmednet.org.
Lynn B. Gerald, Email: lgerald@email.arizona.edu.
John G. Mastronarde, Email: John.Mastronarde@osumc.edu.
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