1 Department of Epidemiology and Community Medicine, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada.
2 Department of Medicine, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada.
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ABSTRACT |
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asthma; body mass index; incidence; longitudinal studies; lung; obesity; sex
Abbreviations: BMI, body mass index; CI, confidence interval; NPHS, National Population Health Survey
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INTRODUCTION |
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Asthma is an important cause of morbidity and increased health care costs (6). Among the 17,605 subjects who participated in the Canadian National Population Health Survey (NPHS) in 19941995, the prevalence of physician-diagnosed asthma was approximately 10 percent for adolescents and young adults and 5 percent for adults (2
). Asthma is a common cause of hospital admission. During the period from fiscal years 19941995 to 19961997, the hospital separation rate for asthma in Canada among children less than 15 years of age was 3 per 1,000 (7
), and asthma accounted for 3 percent of total hospitalizations of the Canadian population (unpublished data). In 1990, the indirect and direct costs of asthma in Canada totaled an estimated Can $600 million (8
), with the corresponding figure for the United States being approximately US $6.2 billion (9
).
Several recent studies have demonstrated an association between relative body weight and asthma. Using cross-sectional data from the first cycle of the Canadian NPHS, Chen et al. (2) found that BMI was linearly related to the prevalence of asthma in women but not in men. Similarly, for British subjects at least 26 years of age, Shaheen et al. (10
) observed an association between BMI and asthma restricted to females. However, cross-sectional studies do not allow determination of the directionality of the BMI-asthma association. A longitudinal analysis by Camargo et al. (11
) of questionnaire data from the Nurses' Health Study in the United States demonstrated that increased BMI was associated with an increased risk of developing asthma. However, this study, which was confined to women, could not determine whether the effect of BMI on the development of asthma was modified by gender. The present investigation used longitudinal data from the NPHS to address this issue.
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MATERIALS AND METHODS |
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The second cycle of the NPHS was conducted in 19961997 by using similar methodology, including a longitudinal component. The longitudinal panel was defined as every selected household member who had completed at least the general questionnaire in the first cycle (13). Of 17,276 eligible subjects, 16,168 (94 percent) participated, and 15,670 provided both general and in-depth health information for both the 19941995 and 19961997 surveys (14
).
In this analysis, we excluded subjects less than 20 years of age or more than 64 years of age in the baseline survey who were not asked to provide information on body weight. We also excluded those who either had reported having asthma in the first cycle or did not respond to questions about asthma in the first and/or second cycles. The present analysis was then based on 9,149 subjects (4,266 men and 4,883 women).
Respondents who answered the following question affirmatively were considered to have asthma: "Do you have asthma diagnosed by a health professional?" Incident asthma cases were those who reported no asthma in the first cycle but reported having asthma in the second cycle.
Self-reported body weight and height were recorded for subjects aged 2064 years at baseline. For these subjects, BMI values at baseline and at follow-up were calculated from the equation BMI = weight(kg)/height(m)2 and were grouped into the following four categories: <20.0, 20.024.9, 25.029.9, and 30.0. We also calculated odds ratios for persons with a BMI of 28.0 kg/m2 or more, a cutpoint set by Statistics Canada. Weight change (BMI change) during the 2-year study period was determined by subtracting weight (BMI) at baseline from weight (BMI) at follow-up.
In both cycles, current smokers were respondents who reported smoking cigarettes every day at the time of the survey. Former smokers were those who reported smoking cigarettes daily in the past but were not smoking at the time of the survey. Otherwise, subjects were classified as nonsmokers. Smoking status did not change dramatically during the 2-year study period, with a great majority of the subjects (87.6 percent of the men and 88.8 percent of the women) remaining in the same smoking categories (nonsmoking, former smoking, and current smoking) in the 19941995 and 19961997 surveys. The present analysis was based on smoking status at baseline (NPHS 19941995).
Subjects were also grouped according to other baseline variables. Subjects in the low education category had not proceeded beyond secondary school; the high education category included subjects who had been admitted to college or university, as well as those with a postsecondary school certificate or diploma. Subjects were classified into low-, middle-, and high-income groups based on total household income adjusted for number of household members (2). A positive history of allergy was defined by an affirmative response to either of the following questions: "Do you have any food allergies diagnosed by a health professional?" or "Do you have other allergies diagnosed by a health professional?" Other variables included in the analysis were age (2029, 3039, 4049, or 5064 years), immigrant status (yes, no), household size (1, 2, 3, or
4 people), number of bedrooms (<3,
3), any pets at home (yes, no), regular drinking (yes, no), and regular exercise (yes, no). A regular drinker was defined as a person who drank alcoholic beverages at least once a month. A regular exerciser was defined as a person who engaged in physical activities that lasted more than 15 minutes at least 12 times a month.
The relations between the weight variables and asthma were examined for men and women separately. We calculated the 2-year cumulative incidence of asthma and corresponding 95 percent confidence intervals according to various risk factors. Logistic regression models were used to evaluate the associations between weight variables and cumulative incidence of asthma, taking other important variables into consideration. Model parameters were estimated by using the method of maximum likelihood and were tested for significance by using the Wald statistic.
The NPHS used a complex survey design incorporating stratification, multiple stages of selection, and unequal probabilities of selection of respondents. The effect of the complex survey design on variance estimates is represented by the design effect, defined as the ratio of the estimated variance taking into account the nature of the survey design to a comparable estimate of variance based on a simple random sample of the target population (15, 16
). In the present analysis, the Rao-Wu bootstrap method (17
, 18
) was used for variance estimation to take both the population weights and design effects into consideration. First, bootstrap weights were calculated by using the Rao-Wu bootstrap approach provided to us by Statistics Canada. In each stratum, clusters were used as the resampling units, including all observations within each cluster. Within stratum h, nh - 1 of nh clusters were randomly selected with replacement, and the bootstrap weight
was calculated, where mh* denotes the number of times that the hith cluster was selected, and whik denotes the original survey weight. If a cluster was not selected (
), then the bootstrap weight (w*hik) of the observations in the cluster was zero.
A total of 500 bootstrap samples were provided for the 19941996 longitudinal panel, permitting calculation of 500 point estimates of each parameter of interest. The standard error of each parameter estimate is then given by a standard deviation of the values for the 500 bootstrap replications. SAS software macros for the bootstrap approach were developed by Statistics Canada, and the statistical analyses were conducted by using SAS software, release 6.12 (19).
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RESULTS |
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DISCUSSION |
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One limitation of the aforementioned prevalence studies is the inability to determine whether asthma preceded obesity or obesity preceded asthma, thus weakening the argument that asthma causes obesity. A longitudinal analysis of data from a prospective cohort study of female registered nurses in the US Nurses' Health Study provided the first evidence that obesity preceded asthma. Over a 4-year period, Camargo et al. (11) studied 85,911 female registered nurses aged 2646 years and found a strong association between obesity and the risk of developing adult-onset asthma. Both BMI at baseline and weight gain after 18 years of age were strongly associated with an increased risk of asthma. However, the issue of gender specificity could not be addressed since men were not included in the study.
In contrast to the findings for adults, associations between obesity and asthma are inconsistent for children and adolescents (21). Some studies demonstrated that BMI was positively associated with wheezing (22
, 23
) and bronchial hyperresponsiveness (22
) in girls but not in boys, whereas another study found BMI to be associated with asthma in both boys and girls (24
). Some earlier studies found that asthmatic children weigh more than nonasthmatic children (25
, 26
), whereas other studies found no association between BMI and childhood asthma, despite their findings of positive associations for several other respiratory ailments (27
29
).
Apart from a causal association between obesity and asthma, particularly in adults, there are several other explanations. Firstly, a factor associated with both obesity and asthma, such as diet or (sedentary) lifestyle, may confound the obesity-asthma association. Obstructive sleep apnea and gastroesophageal reflux disease can be possible risk factors for asthma development that are related to obesity. Secondly, Stenius-Aarniala et al. (30) elegantly demonstrated the detrimental effects of obesity on respiratory symptoms and function. These effects may increase the risk of asthma being diagnosed. However, these arguments are unable to explain the observed gender specificity.
One plausible hypothesis is that female sex hormones play an important role in the etiology of asthma and that these hormones are influenced by obesity (2,10
,11
). The following observations are consistent with this possibility: Sex hormonal changes begin at puberty, with adult hormone levels being attained by approximately 16 years of age (31
). Although boys are at substantially higher risk of asthma than girls are (32
34
), the incidence of asthma is higher in women than in men (35
37
), and prevalence does not differ markedly between men and women (2
, 36
). Similarly, the rate of hospital admission for asthma is higher for prepubertal males than females but is lower for adult males than females (38
). Airway responsiveness, a defining characteristic of asthma, may be greater in women than in men (39
).
To some extent, these epidemiologic observations are consistent with the documented influence of sex hormones, including progesterone and estrogen, on mechanisms that may influence asthma. Progesterone upregulates beta2 receptors. The luteal phase increase in progesterone and estradiol is associated with an increased density of beta2adrenoreceptors on lymphocytes (40). Forty micrograms of exogenously administered progesterone have been shown to cause an eightfold increase in the bronchorelaxant effect of the catecholamine isoprenaline (41
). One hypothesis is that obesity reduces progesterone levels, which reduces beta2adrenoreceptor function, which in turn reduces bronchial smooth muscle relaxation. In support of this hypothesis is the observation that weight loss increases progesterone level and adrenoreceptor density (42
). After studying 20 obese hyperandrogenic women, Wahrenberg et al. (43
) found that a mean weight loss of 8 pounds (3.63 kg) was associated with a five- to sevenfold increase in noradrenaline and terbutaline sensitivity, with a twofold increase in beta2-receptor density as measured by radioligand binding.
Estrogen may have different effects on asthma. The Nurses' Health Study showed that postmenopausal estrogen use was associated with an increased incidence of asthma and that there was a dose-response relation between asthma incidence and the current dose and duration of use of estrogen (44). BMI has been shown to be positively associated with plasma estrogen and estrone sulfate levels in postmenopausal women (45
). Relevant to the lack of association between BMI and asthma in men, Leenen et al. (46
) reported that visceral fat accumulation, determined by magnetic resonance imaging, was associated with sex hormone alterations in women but not in men. Our analysis was limited by a lack of sex hormone data. The interrelations between asthma, obesity, and sex hormones warrant further study.
One major limitation of the present analysis is the diagnosis of asthma. Although a universally accepted definition of asthma remains to be established, there is no question that bronchial hyperresponsiveness and reversible airway narrowing are key features of the disease. Unfortunately, it is not practical to measure these characteristics in large-scale epidemiologic studies. As in most epidemiologic studies, the asthma definition used here was based on self-reported, physician-diagnosed asthma. The persons who reported having no asthma at baseline but reported having asthma at follow-up were considered incident cases during the 2-year study period, without additional verification.
Identification of incident cases of asthma in this manner may be crude; however, we could not find reasons that this would have an important impact on our conclusions. Firstly, Camargo et al. (11) reported substantially more information on the characteristics surrounding the diagnosis of asthma and found that stricter criteria led to stronger associations between BMI and asthma (11
). Secondly, the disease defi-nition we used contains the components essential to the definition in the original American Thoracic Society (47
) Standardization Project questionnaire, which inquired "Have you ever had asthma?" and "Was it confirmed by a doctor?" These questions have been used in various epidemiologic studies, and they have been validated. In the pres-ent study, our definition was based on self-reported asthma and diagnosis by a health care professional. Thirdly, one study has demonstrated that various definitions of asthma have little influence on the observed incidences, and the data have shown an incidence of 1.2 percent for "ever had asthma," 1.1 percent for "asthma diagnosed by a physician," and 1.3 percent for "current use of asthma drugs." Even if the definition used had a small influence on the observed incidence of asthma, the choice of definition would be less likely to create an observed gender difference in asthma incidence in our study (35
).
In addition, the follow-up period for our study was relatively short. Since the incidence of asthma was lower for men than for women, one could argue that there was insufficient statistical power to detect an association between BMI and asthma incidence in men. However, the data did not show an increasing trend in the incidence of asthma with increasing BMI at baseline for men. Another limitation is a lack of measures of adiposity other than body weight and BMI. BMI may not be an equivalent measure of fatness in men and women. The fact that men tend to have more muscle mass and women more fat mass may also contribute to the apparent gender-specific relation between obesity and asthma.
In summary, we found obesity to be a risk factor for asthma in women but not in men. The reproducibility of these findings in other populations, the lack of known confounding variables, and the existence of a biologically plausible explanatory mechanism all support an argument for a causal association. Evidence for causality would be strengthened by objectively measuring changes in asthma severity and female sex hormone levels during periods of weight gain or loss.
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ACKNOWLEDGMENTS |
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The authors thank Colette Koeune of Statistics Canada for her assistance with remote access to the NPHS longitudinal data.
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NOTES |
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Editor's Note: An invited commentary on this paper appears on page 198, and the authors' response is on page 201.
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REFERENCES |
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