BMI and Health Status Among Adults With Asthma

Abstract

Background: A convincing body of literature links obesity with a higher risk for developing adult-onset asthma. The impact of obesity on asthma severity among adults with pre-existing asthma, however, is less clear.

Methods and Procedures: In a prospective cohort study of 843 adults with severe asthma, we studied the impact of BMI on asthma health status.

Results: The prevalence of obesity and overweight were 44% (95% confidence interval (CI) 41–47%) and 28% (95% CI 25–32%). The obese BMI group was associated with a higher risk for daily or near daily asthma symptoms than was the normal BMI group (odds ratio (OR) 1.81; 95% CI 1.10–2.96). Compared to the normal BMI group, generic physical health status was worse in the overweight (mean score decrement −2.42 points; 95% CI −4.39 to −0.45) and the obese groups (−6.31 points; 95% CI −8.14 to −4.49). Asthma-specific quality of life was worse in the underweight (mean score increment 8.66 points; 95% CI 2.53–14.8) and obese groups (4.51 points; 95% CI 2.21–6.81), compared to those with normal BMI. Obese persons also had a higher number of restricted activity days that past month (5.05 days; 95% CI 2.90–7.19 days).

Discussion: It appears that obesity has a substantive negative effect on health status among adults with asthma. Further work is needed to clarify the precise mechanisms. Clinicians should counsel dietary modification and weight loss for their overweight and obese patients with asthma.

Introduction

The burden of asthma, in terms of prevalence and severity, has been increasing in the United States and other developed countries (1,2,3). At the same time, there is an epidemic of obesity, with a marked increase in overweight and obese adults (4,5). Obesity has severe consequences for health, including a higher risk of death (6). Emerging literature suggests that the obesity and asthma epidemics could be linked (7).

A convincing body of literature, which includes both cross-sectional and longitudinal studies, links obesity with a higher risk for developing adult-onset asthma (8,9,10,11,12,13). The impact of obesity on asthma severity among adults with pre-existing asthma, however, is less clear because there have been fewer studies on this and mixed results (10,14,15,16,17,18). In a prospective cohort study of adults with severe asthma, we studied the impact of BMI on asthma health status.

Methods and procedures

Overview

We used data from a prospective cohort study of adult members of a closed panel managed care organization who were hospitalized for asthma during a 4-year period. After hospital discharge, we conducted structured telephone interviews that assessed asthma history and health status. The goal of this analysis was to assess the impact of BMI on asthma severity and asthma-related health outcomes. The study was approved by the University of California, San Francisco Committee on Human Research and the Kaiser Foundation Research Instituteapostrope;s institutional review board.

Subject recruitment

Subject recruitment methods have been previously described in detail (19,20). We studied adult members of Kaiser Permanente (KP), the nationapostrope;s largest non-profit managed care organization. To establish a cohort with more severe asthma, we recruited adults who had been recently hospitalized for asthma (21,22,23,24,25). In order to interview subjects promptly after hospitalization, recruitment was conducted on a rolling monthly basis. Each month, we identified all adult KP members (>18 years) who were hospitalized at any Northern California KP hospital with a principal Ninth International Classification of Diseases (ICD-9) discharge diagnosis code for asthma (codes 493.00–493.99) during a 4-year period beginning in April, 2000. We also included KP members hospitalized with a secondary ICD-9 discharge diagnosis code for asthma and a principal ICD-9 code for acute asthma-related respiratory conditions. Persons with a primary or secondary discharge diagnosis code for chronic bronchitis (491.xx), emphysema (492.xx), or chronic airway obstruction (496.xx) were excluded. In addition, all subjects reported a physician diagnosis of asthma at the time of telephone interview. The diagnosis of asthma was previously validated in a stratified random sample of 100 subjects (19,20,26).

The complete cohort included 865 subjects who underwent structured telephone interviews (53% completion rate); the current report includes 843 subjects who reported height and weight during the interview. There were no differences in age, sex, race, or asthma severity scores in the 843 subjects vs. 22 subjects without height and weight information (data not shown).

BMI

Every subject underwent a structured telephone interview. We computed patientsapostrope; BMI from self-reported height and weight estimates without clothing. Measurements were ascertained in pounds and feet and were converted into meters and kilograms for computation of BMI. We then divided the patients into BMI groupings for normal, overweight, and obese patients based on standard criteria (27). We defined underweight as a BMI of <18.5 kg/m², normal weight as 18.5–24.9 kg/m², overweight as 25–29.9 kg/m², and obese as 30 kg/m² or greater.

Sociodemographic characteristics

Structured telephone interviews ascertained age, sex, race-ethnicity, educational attainment, and marital status. As in previous studies, we defined educational attainment as high school or less, some college, or college/graduate degree (28). Race-ethnicity and marital status were ascertained as previously described (28). Atopic history was defined as a reported history of hayfever or eczema. Cigarette smoking was measured using questions developed for the National Health Interview Survey (29).

Asthma health status

We measured asthma severity using a previously developed and validated 13-item disease-specific severity-of-asthma score based on frequency of current asthma symptoms (daytime or nocturnal), use of systemic corticosteroids, use of other asthma medications (besides systemic corticosteroids), and history of hospitalization and intubation (30,31). Possible total scores range from 0 to 28, with higher scores reflecting more severe asthma. Each of these four components of asthma severity also comprises a separate subscale. Previous work has established the reliability, concurrent validity, and predictive validity of the severity score (30,31,32). In addition, we defined a variable for daily or near-daily asthma symptoms (during the day or night). We assessed asthma-specific quality of life using the Marks Asthma Quality of Life Questionnaire, a 20-item questionnaire that measures the physical, emotional, and social impact of asthma (33). Previous work demonstrates the Asthma Quality of Life Questionnaireapostrope;s validity and responsiveness to change in asthma status (34,35). Higher scores represent worse asthma-specific quality of life. The minimal clinically significant difference is approximately seven points (32). Generic physical health status was measured using the SF-12 questionnaire (36). The physical and mental component summary scores, which were defined from the original eight SF-36 subscales by factor analysis, measure underlying physical and mental dimensions of health. Previous research work demonstrates the SF-12 instrumentapostrope;s validity in the study of adult asthma (37). Higher scores reflect more favorable health status.

As another measure of physical health status, daily activity restriction was ascertained using a question adapted from the National Health Interview Survey (38). Specifically, respondents were asked to indicate how many days during the past month their activity level was limited due to a respiratory condition.

Longitudinal asthma outcomes: emergency health care utilization for asthma

To examine the longitudinal impact of BMI on emergency health care utilization for asthma, we ascertained emergency department (ED) visits and hospitalization for asthma that occurred after index hospitalization and after the baseline study interview. The median duration of follow-up was 1.7 years and went up to 4.3 years. Asthma-related hospitalization was defined as one or more hospitalizations with a principal discharge diagnosis code for asthma (ICD-9 code 493.xx). Asthma-related ED visits were identified as one or more visit with an ICD-9 code for asthma (493.xx). In contrast to hospital discharge diagnoses, ED visits do not distinguish primary or secondary diagnoses in the Kaiser system.

BMI and asthma health outcomes: mediation by depressive symptoms and perceived control of asthma

We reasoned that the relationship between body weight and asthma health status could be mediated by psychological processes such as depression and perceived control of asthma. In previous research work, we have established that these two psychological factors have an important impact on asthma health outcomes (19,39). Potential mechanisms for these psychological factors include differences in preventive care for asthma, self-management behaviors, adherence to asthma therapy, or perception of respiratory symptoms. Depressive symptoms were ascertained using the Center for Epidemiologic Studies Depression Scale, one of the best known survey instruments for identifying symptoms of depression (40). It was originally developed to identify depression in the general population (41). The Center for Epidemiologic Studies Depression Scale has 20 items that measure 6 components of depression during the previous week: depressed mood, feelings of guilt and worthlessness, feelings of helplessness and hopelessness, psychomotor retardation, loss of appetite, and sleep disorders (41). Scores range from 0 to 60 points, with higher scores indicating greater depressive symptoms. Reliability and validity have been established in both the general population and clinical settings (40,41).

Perceived control was measured using the Perceived Control of Asthma Questionnaire, an 11-item instrument that has been previously validated (34). It assesses individualsapostrope; perceptions of their ability to manage their asthma and its exacerbations. Possible scores range from 11 to 55 points, with higher scores reflecting greater perceived control of asthma.

Statistical analysis

We performed statistical analysis using SAS software, version 9.1 (copyright, SAS Institute, Cary, NC). Bivariate analysis was conducted with ANOVA for continuous normally distributed variables and the chi-square test for categorical variables. We used a combination of cross-sectional analyses (asthma health status) and longitudinal analyses (health care utilization).

We used multivariate linear regression analysis to evaluate the cross-sectional impact of BMI category on asthma severity, asthma-specific quality of life, physical health status, and restricted activity days. In these analyses, we controlled for variables that could confound the association between BMI and asthma health outcomes. These variables were chosen based on bivariate analysis and our underlying theoretical model of how body composition and health status may be interrelated.

We used Cox proportional hazards analysis to evaluate the impact of BMI on emergency health care utilization for asthma (ED visits and hospitalizations). Person-time was censored for death or leaving the KP system.

We examined statistical interactions between BMI status and gender. There was no evidence that gender modified the association between BMI and any study outcome (P > 0.20 in all cases). Consequently, the results were not stratified by gender.

To test whether the relation between BMI category and asthma status was mediated by depression and perceived control of asthma, the multivariate models were repeated including these two scale scores. The mediation effect was calculated as the percent reduction in the β coefficient for each BMI group after including the two additional psychological variables compared to the nested model without them.

We compared the prevalence of overweight or obesity in adults with severe asthma in our study to the general population of California adults. To perform this comparison, we used data from the California Work and Health Survey, a population-based study of 3,805 California adults aged 18 years or older conducted in 1998–2000 (28,42). Using California Work and Health Survey data, we developed a multivariate logistic regression model for obesity as the dependent variable and the following independent variables: age, age squared, sex, race, educational attainment, marital status, and smoking history. A quadratic term for age was included because it improved model fit. For each variable, we then substituted the mean values of each characteristic for our sample of adults with asthma into the regression equation to calculate the expected (i.e., predicted) prevalence of overweight or obesity for a comparable general population sample of California adults. The observed prevalence of overweight or obesity among persons with severe asthma was then compared to the expected prevalence.

Results

Subject characteristics and BMI

The prevalence of obesity and overweight was 44% (95% confidence interval (CI) 41–47%) and 28% (95% CI 25–32%), respectively. A small proportion was underweight (2.4%; 95% CI 1.5–3.6%) and the rest were in the normal weight category (25%; 95% CI 22–28%). Age, sex, race-ethnicity, and educational attainment were related to BMI group (Table 1). Obese adults with asthma were more likely to be younger, female, and of non-white race-ethnicity. The relation between educational attainment and the BMI group was U -shaped, with lowest educational attainment in the underweight and obese groups.

Table 1. . Multicolor FACS analysis of SCID-hu-derived transgenic thymocytes

Characteristic	Underweight (n = 20)	Normal (n = 212)	Overweight (n = 240)	Obese (n = 371)	P value
Proportions are column proportions (% of each BMI category).
Age (years)	66.4 (16.9)	63.9 (17.7)	61.3 (16.8)	57.5 (15.5)	<0.0001
Female sex	15 (75%)	145 (68%)	137 (57%)	293 (79%)	<0.0001
Race-ethnicity (white)	16 (80%)	137 (64%)	144 (60%)	206 (56%)	0.035
Educational attainment					0.034
High school or less	4 (20%)	34 (16%)	41 (17%)	88 (24%)
Some college	13 (65%)	114 (54%)	139 (58%)	212 (57%)
College graduate or higher	3 (15%)	64 (30%)	59 (25%)	71 (19%)
Household income					0.17
Low (<$20,000)	1 (5%)	38 (18%)	31 (13%)	65 (18%)
Medium ($20–60,000)	18 (90%)	153 (72%)	173 (72%)	262 (71%)
High (>$60,000)	1 (5%)	21 (10%)	36 (15%)	44 (12%)
Married/cohabitating	12 (60%)	126 (59%)	157 (65%)	221 (60%)	0.47
Atopic history	9 (45%)	123 (58%)	150 (63%)	239 (64%)	0.19
Smoking history					0.85
Never smoker	7 (35%)	77 (36%)	75 (32%)	136 (37%)
Current smoker	3 (15%)	21 (10%)	25 (10%)	35 (9%)
Ex-smoker	10 (50%)	114 (54%)	140 (58%)	200 (54%)

BMI and asthma health status

There was no clear impact of obesity on the severity-of-asthma score after controlling for age, sex, race, smoking status, educational attainment, household income, and atopic status (Table 2). Of the four severity score subscales, the obese BMI category was associated with greater asthma symptoms for subscale scores (P = 0.002). There was no apparent relation between the BMI group and the hospitalization-intubation, asthma medications, and systemic corticosteroid subscales (P > 0.10 in all cases). Moreover, the underweight and obese BMI groups were also associated with a higher risk for daily or near daily asthma symptoms than the normal BMI group (odds ratio (OR) 3.55; 95% CI 1.19–10.5 and OR 1.81; 95% CI 1.10–2.96, respectively) (data not shown in table).

Table 2. . The association between BMI and asthma severity, physical health status, and asthma-specific quality of life

BMI category	Asthma severity	Physical health status	Asthma-specific quality of life	Restricted activity days (past 4 weeks)
Results are mean difference compared to normal weight group (95% confidence intervals) controlling for age, sex, race, smoking status, educational attainment, household income, and atopic status. Higher asthma severity score, asthma-specific quality of life score, and restricted activity days = worse health status, whereas higher physical health status (short form-12 (SF-12)) score = better health status.
Underweight	1.44 (−0.12 to 3.02)	−4.05 (−8.90 to 0.81)	8.66 (2.53–14.8)	5.37 (−0.34 to 11.1)
Normal	Referent	Referent	Referent	Referent
Overweight	0.09 (−0.55 to 0.73)	−2.42 (−4.39 to −0.45)	2.20 (−0.29 to 4.68)	2.08 (−0.23 to 4.40)
Obese	0.45 (−0.14 to 1.04)	−6.31 (−8.14 to −4.49)	4.51 (2.21–6.81)	5.05 (2.90–7.19)

Compared to the normal BMI group, generic physical health status was worse in the overweight (mean score decrement −2.42 points; 95% CI −4.39 to −0.45) and the obese groups (−6.31 points; 95% CI −8.14 to −4.49) after controlling for covariates (Table 2). Asthma-specific quality of life was worse in the underweight (mean score increment 8.66 points; 95% CI 2.53–14.8) and obese groups (4.51 points; 95% CI 2.21–6.81), compared to those with normal BMI. Obese persons also had a higher number of restricted activity days during the previous month (5.05 days; 95% CI 2.90–7.19 days).

BMI and health care utilization for asthma

There was no statistical association between the overweight and obese BMI groups and the risk of ED visits or hospitalization for asthma (Table 3). Underweight BMI was related to a greater risk of hospitalization for asthma after controlling for covariates (hazard ratio 2.31; 95% CI 1.013–5.28).

Table 3. . BMI and the longitudinal risk of emergency health care utilization for asthma

BMI category	Emergency department visits HR (95% CI)	Hospitalization HR (95% CI)
Results are hazard ratios (HRs) compared to normal weight group (95% confidence intervals (CIs)) controlling for age, sex, race, smoking status, educational attainment, household income, and atopic status.
Underweight	1.52 (0.68–3.37)	2.31 (1.013–5.28)
Normal	Referent	Referent
Overweight	0.75 (0.51–1.10)	0.94 (0.59–1.50)
Obese	0.91 (0.65–1.27)	0.93 (0.61–1.41)

Mediation by psychological factors

The BMI group was associated with both Center for Epidemiologic Studies Depression Scale depression and perceived control of asthma scores after controlling for covariates (P < 0.0001 in both cases). In both instances, the obese BMI group was associated with worse depression and perceived control scores compared to the normal BMI group (2.2 points; 95% CI 0.6–3.8 and −0.90 points; 95% CI −0.14 to −1.6).

To test whether the relation between BMI category and asthma status was mediated by depression and perceived control of asthma, the multivariate models were repeated including these two scale scores. The mediation effect was calculated as the percent reduction in the β coefficient for each BMI group after including the two additional psychological variables. As shown in Table 4, the mediation effect was greatest for asthma-specific quality of life (e.g., 51% for obesity), intermediate for restricted activity days, and lowest for physical health status. In all cases, however, the obese group remained strongly associated with asthma health status.

Table 4. . BMI and asthma status: controlling for depressive symptoms and perceived control of asthma

	Physical health status		Asthma-specific quality of life		Restricted activity days (past 4 weeks)
BMI category	Mean (95% CI)	Mediation effect	Mean (95% CI)	Mediation effect	Mean (95% CI)	Mediation effect
Results are mean difference compared to normal weight group (95% confidence intervals (CIs)) controlling for age, sex, race, smoking status, educational attainment, household income, atopic status, plus depressive symptoms and perceived control of asthma. Higher asthma severity score, asthma-specific quality of life score, and restricted activity days = worse health status, whereas higher physical health status (short form-12 (SF-12)) score = better health status. Mediation effect = percent reduction in the β coefficient after adding depressive symptoms and perceived control of asthma scores to the base multivariate model in Table 2. This reflects the proportion of the BMI effect that can be “explained” by depressive symptoms and perceived control of asthma.
Underweight	−3.22 (−7.95 to 1.51)	20%	5.59 (0.98–10.20)	35%	3.93 (−1.46 to 9.31)	27%
Normal	Referent	N/A	Referent	N/A	Referent	N/A
Overweight	−2.18 (−4.11 to −0.25)	10%	1.06 (−0.82 to 2.94)	43%	1.54 (−0.66 to 3.73)	24%
Obese	−5.81 (−7.60 to −4.02)	8%	2.19 (0.45–3.93)	51%	4.00 (1.96–6.04)	21%

Prevalence of overweight or obesity in severe asthma vs. California adults

We compared prevalence of overweight or obesity of adults with severe asthma in this study to persons with similar characteristics who live in California (see Methods and Procedures). Based on age, age squared, sex, race, educational attainment, marital status, and smoking history, the predicted proportion of overweight or obesity for the cohort was 53%. The actual prevalence of overweight or obesity for study participants with severe asthma was substantially higher than predicted (72 vs. 53%), which reflects a 36% increase in the likelihood of having greater than normal weight.

Discussion

We observed a high prevalence of overweight and obesity among adults with severe asthma, which was higher than expected in the California population. In this regard, our findings are concordant with epidemiologic studies linking obesity with a higher risk for developing adult-onset asthma and also the high prevalence of obesity in adult asthmatics seeking ED care for asthma (10,15).

Obesity was associated with worse physical health status, asthma-specific quality of life, and respiratory symptoms in cross-sectional analysis. There was also more activity restriction among obese persons with asthma. There was, however, no relation between obesity and the longitudinal risk of subsequent emergency health care utilization for asthma. Taken together, obesity had a negative impact on health status among adults with asthma, but this was not translated into higher utilization of hospital-based services. The effect of obesity on asthma health status was mediated, only in part, by depression and perceived control of asthma. We infer that other factors must therefore be negatively affecting asthma status.

Our study is consistent with the very limited previous literature showing an association between obesity and worse asthma-specific quality of life (17). Like this prior study, we showed a relatively greater effect of obesity on quality-of-life than on asthma severity. Moreover, our work amplifies the Multicenter Airway Research Collaboration study of ED patients which found no clear impact of elevated BMI on asthma severity (15). Our finding that obesity was associated with greater asthma symptoms despite similar underlying disease severity echoes previous work relating obesity to worse asthma control (16,17,18). The present study differs from an Epidemiological study on the Genetics and Environment of Asthma study report that found a substantial effect of obesity on asthma severity in women (14). Differences in measuring asthma severity between our study (a validated survey-based measure) and the Epidemiological study on the Genetics and Environment of Asthma study may account for these different findings. Taken together, our findings advance the field by further establishing the link between obesity and worse asthma health status, especially quality of life.

A major question is whether obesity worsens asthma via specific respiratory mechanisms, such as airway inflammation, early airway closure, or bronchial hyperresponsiveness (7,43,44,45,46). Alternatively, more general mechanisms, such as increasing demand on the cardiorespiratory system or a higher risk of arthritis, could account for decreased physical function in obese adults with asthma. Other explanations could be obesity-related comorbidites, such as gastroesophageal reflux or sleep disordered breathing, which could interact with asthma to increase respiratory dysfunction (8). In our study, the negative impact of obesity on asthma-specific quality of life and respiratory symptoms suggests an asthma-specific effect, whereas the impact on physical health status or restricted activity could be explained by either a specific or generic effect of obesity. The reason for discordance between the impact of obesity on asthma health status and emergency health care utilization for asthma is not clear, but it may reflect a higher tolerance for respiratory symptoms among obese persons, effects of social stigma on seeking health care among the obese, or diagnostic confusion at the time of the ED visit or hospitalization (i.e., less likely to be diagnosed with asthma exacerbation).

Our results suggest that being underweight may also contribute to additional morbidity among adults with asthma. There is an indication that underweight BMI is related to worse asthma severity, physical health status, and asthma-specific quality of life, although the small number of subjects in this category resulted in lower power and CIs that do not exclude “no association.” The underweight BMI category was also associated with a greater longitudinal risk of hospitalization for asthma. These findings are consistent with a prior report of greater asthma symptoms, worse lung function, and greater bronchial hyperresponsiveness in a general population-based sample of adults (46). In addition, previous studies have linked underweight to a higher risk for developing asthma (47,48). Although the reasons for the impact of being underweight (with a low BMI) on asthma status are unclear, they are consistent with the observed effects of low body weight and poor health outcomes in the general population and among adults with other chronic lung disease, primarily chronic obstructive pulmonary disease (49). Underweight may also be a marker for other severe concurrent disease. This is an intriguing area that requires further study.

Our study is subject to several limitations. We cannot exclude some amount of misclassification of asthma and chronic obstructive pulmonary disease. To mitigate against misclassification with chronic obstructive pulmonary disease, we used a systematic approach that was consistent with previous studies using ICD-9 discharge diagnoses to define persons hospitalized for asthma (50,51,52,53). In addition, all subjects in the interviewed subcohort study reported a physicianapostrope;s diagnosis of asthma, which is a standard epidemiologic tool for identifying asthma cases (54). Our validation study strongly supported the validity of the diagnosis of asthma. Taken together, we believe that our results are applicable to adults with asthma treated in a managed care organization.

Of the eligible participants, more than half participated in the telephone interviews. We have previously reported that there were no substantive differences in age, sex, or race between those who did and did not participate in the interviews (26). We cannot, however, fully exclude selection bias due to lack of response.

Another limitation is that we purposely recruited a cohort with more severe asthma (those who had just undergone hospitalization or intensive care unit admission for asthma) (55). This afforded the opportunity to study BMI and outcomes among adults with severe asthma, which has not been previously examined. The results, however, may not apply to persons with milder disease. Because we recruited our cohort from a source population that is highly similar to the general regional population, we do expect our results to generalize to adults with severe asthma in the general population. Supporting this contention, it has been shown that Northern California KP members are similar to those of the regional population, with some under-representation of income extremes (52,56). There is also no evidence of systematic inclusion or exclusion of healthy persons into the KP system (57).

In addition, we used self-reported height and weight and did not directly measure them. BMI calculated using self-reported measures tends to underestimate the prevalence of obesity (58). Because we have no reason to believe that reporting of height and weight would vary based on asthma severity, misclassification is likely to be non-differential, which would bias our results to the null (i.e., our results may underestimate the true effects of obesity).

The asthma severity score, which includes asthma symptoms, cannot fully distinguish the effect of obesity on airway obstruction from the restrictive effects on lung volumes. The lack of pulmonary function testing is, therefore, a study limitation. Even formal pulmonary function testing, however, has limitations in the obese. Although there is a linear negative relationship between BMI and total lung capacity, it remains normal among the majority of severely obese persons (59).

In sum, it appears that obesity has a substantive negative effect on physical health status, asthma-specific quality of life, and daily activity among adults with asthma. Further work is needed to clarify the precise mechanisms. In the meantime, clinicians should counsel for dietary modification and weight loss for their overweight and obese patients with asthma. Evaluation for comorbid factors, such as gastroesophageal reflux and sleep disordered breathing, may also be warranted.

DISCLOSURE

The authors declared no conflict of interest.

Acknowledgments

M.D.E. was supported by K23 HL04201, National Heart, Lung, and Blood Institute, National Institutes of Health, with co-funding by the Social Security Administration.