Asthma Diagnosis,Knowledge and Awareness among Recreational Endurance Athletes

Abstract

Objective: Limited research exists on recreational-level competitors regarding asthma and/or comorbidity. The present purpose was to conduct a study in conjunction with the 2008 ING Georgia Marathon and Half-Marathon in Atlanta.

Methods: The authors conducted an online secure survey in winter 2008 using PsychData, using previously validated questions from other research and national surveys. Data were summarized from participating recreational athletes on sociodemographic attributes; training locations; participant and family member diagnosis of asthma; and participant knowledge and awareness of signs, symptoms, and management.

Results: There were 1151 participants (99.4%) who provided informed consent and then answered the survey (more than 10% of initially registered athletes); 7 athletes (0.6%) did not consent. There were complete data for 1138 participants (98%). Most participants were women (56.2%), white (88.2%), and of a relatively higher socioeconomic status than the general population. Most participants (96.2%) were running either a full marathon (29.8%) or half-marathon (66.4%), as opposed to walking or participating as a wheelchair athlete. About 1 in 8 participants (12.1%) reported physician-diagnosed asthma. Clinically, whereas 84.6% correctly knew that an asthma action plan can prevent hospitalizations due to asthma, only 18% reported that they had such a plan. Moreover, only 24.8% had ever been asked to demonstrate medication use (controller and/or rescue inhaler), and only 2 people performed daily peak flow measurements.

Conclusions: In a study of physically active white adults of higher socioeconomic status, 12.1% reported asthma. As such, this study identified the need for potential improvements in asthma management via written asthma action plans and demonstration of peak flow monitoring and medication use.

Keywords

asthma asthma action plan asthma education issues self-management adults endurance athletes recreational runners

Adults have been competing in recreational endurance sports events year-round in increasing numbers. For example, participation in running and walking endurance events such as marathons (26.2 miles [42.2 km) has dramatically increased in the United States.¹ The reasons include personal, family, and society-related goals, such as fitness, overall good health through physical activity, and charity—including fund-raising races for such causes as the reduction or prevention of adverse acute/chronic health outcomes (cancer, cardiovascular diseases, diabetes, respiratory diseases, etc), as well as environmental protection and stewardship.

Research to date regarding athletes and asthma has focused on elite, professional, and collegiate athletes regarding asthma (allergic or exercise-induced)^2-12 and/or comorbidity. These survey- and spirometry-based studies included and sometimes compared land versus water sports and cooling season versus heating season sports (ie, summer vs winter). Few studies have examined respiratory health, including asthma status^12-18 and comorbidity,^19-23 among recreational-level/amateur competitors in controlled laboratories or at endurance running events such as full and half-marathons. These studies were clinical—based on spirometry and survey data or focused on the management of clinical measures—to assess the potential impacts of these diseases on endurance sports characterized by aerobic exercise.

Health and exercise professionals have recently placed increased attention on the training and safety of recreational endurance athletes. Moreover, public health and allied health professionals and primary care physicians have put increasing importance on educating and promoting safe, long-term physical activity, in an effort to reduce population prevalence of overweight and obesity. Among adults, potential associations between overweight/obesity and diagnosis of asthma have been reported (ie, via mechanical weight-based, not allergic, airway inflammation or bronchodilation mechanisms).^24-32

We conducted an interdisciplinary survey in conjunction with events of the second annual ING Georgia Marathon and Half-Marathon, during winter 2008 in Atlanta, Georgia. In this article, we highlight the results of our main online survey related to asthma; other results are presented elsewhere.³³ Specifically, we assessed 3 aims: the sociodemographic attributes of participating recreational athletes to characterize our final, consenting, valid study population; the participants’ diagnoses of asthma, as well as family members’ asthma diagnoses; and the participants’ knowledge and awareness of signs, symptoms, and management of asthma (clinical, environmental, and social and behavioral aspects).

Methods

We received human subjects review approval with a waiver of documentation of informed consent from the Institutional Review Board at Georgia State University.

Participation required completing a questionnaire on a secure website any time during the 5 weeks before and on the weekend of the event: February 21 through March 31, 2008. Georgia Marathon, LLC (the 2007-2008 race events management team) regularly sent e-mail to registered participants via Active.com. It highlighted our study and online survey in e-newsletters on February 21-22, 2008, and March 14, 2008, and on the event website. These communications included direct hyperlinks to the informed consent form and the survey. The former was the first item that a potential volunteer viewed and read; then, the person decided if he or she wanted to participate. If yes, then one clicked on the “Continue” button to indicate consent to participate. Alternatively, one could have clicked on the “No, I do not want to participate” button to end access. After consent, he or she was asked to complete an 87-item main survey in 6 modules in about 15 to 20 minutes. In this article, we focus on data regarding sociodemographic variables, reported doctor diagnosis of asthma, and knowledge and awareness of key indicators of symptoms and proper management (clinical, environmental, and/or behavioral) of this chronic disease, using previously validated survey questions (details presented below). We calculated age as 2007 (December 31, 2007) minus the reported year of birth.

PsychData³⁴ was the software program used for the ING Georgia Marathon and Half-Marathon Study in 2007³⁵ and 2008³³ for our interdisciplinary surveys. PsychData contained validated, built-in security features for the administration, transmission, storage, and delivery of an aggregated summary of completed participant responses. Survey pages were dynamic and database generated—that is, loaded directly from the PsychData server such that participation could be from the participant’s computer of choice. Confidentiality was ensured; each participant’s responses were immediately encrypted to minimize, if not prevent, data interception; and data were accessible only from PsychData with the correct user name and password. We never identified participants by name in the database and subsequent aggregate analyses. Our final database for analysis contained only a unique random identification number per participant as generated by PsychData (see references 33-35 for details).

Survey Questions

Previously validated survey questions on demographic variables, socioeconomic status, and race/ethnicity were identified from national surveys such as the National Health and Nutrition Examination Survey and human exposure assessment research projects and used as previously described.^33,35

Questions to assess self-reported physician diagnosis of asthma (ie, allergic, exercise induced, and the nonallergic/mechanical mechanism), plus knowledge and awareness of the clinical and social/behavioral management aspects of asthma management via a set of true/false questions, were drawn from validated surveys and used as previously described.^36-40

Data Analysis

For data management and analysis, we imported text files from PsychData to Microsoft Excel and then to SPSS 15. We archived completed survey databases and analyses on multiple computers and backup media on and off campus.

Results

Table 1 presents selected demographic and race experience characteristics of the study sample among participants registered for and competing in the 2008 ING Georgia Marathon and Half-Marathon. The majority of the participants were women (56.2%) and white (88.2%). Almost three-quarters (74.7%) had graduated from college or university, had attended some graduate school, or had graduated with a master’s degree. In addition, over half of responding participants earned an annual household income of $100 000 or more. Thus, the study sample comprised a relatively higher socioeconomic status than that of the general population. The majority of the participants (96.2%) were running either a full marathon (29.8%) or a half-marathon (66.4%). The majority of short- to medium-length training workouts (67.7%) and weekly longer workouts (88.8%), critical to marathon and half-marathon training, were reported to have been completed outdoors.

Table 1.

Characteristics of the Study Sample Registered for and Competing in the ING Georgia Marathon and Half-Marathon, 2008

		Participants
Variables	Categories	n	%^a
Valid data	Overall^b	1138	100.0
Demographics
Sex	Male	499	43.8
	Female	639	56.2
Race/ethnicity	White	1004	88.2
	Hispanic^c	34	3.0
	African American / non-Hispanic black	36	3.2
	Asian American / Pacific Islander	32	2.8
	American Indian	3	0.3
	Other	15	1.3
	Nonresponse^d	14	1.3
Socioeconomic status indicators
Education completed	Some secondary school	4	0.4
	Secondary school graduate	24	2.1
	Some university/college or technical/vocational completed	125	11.0
	University/college graduate	384	33.7
	Some graduate school	142	12.5
	Highest graduate degree: Master’s	324	28.5
	Highest graduate degree: Doctorate	130	11.4
	Nonresponse^d	5	0.5
Annual household income	Less than $20 000	49	4.3
	$20 000 to $40 000	79	6.9
	$40 000 to $60 000	129	11.3
	$60 000 to $80 000	124	10.9
	$80 000 to $100 000	116	10.2
	$100 000 or more	526	46.2
	Nonresponse^d	115	10.1
Event
2008 registration	Marathon, run	339	29.8
	Marathon, walk	5	0.4
	Half-marathon, run	756	66.4
	Half-marathon, walk	37	3.3
	Half-marathon, wheelchair athlete	1	0.1
2007 study participation among 2008 registrants^e	Yes	155	44.9
	No	179	51.9
Training^f
Short- to medium-length workouts^g (distance and/or time)	Outdoors	770	67.7
	As member, inside gym or recreation/community center	299	26.3
	At home, inside and/or immediately outside	176	15.5
Longer-length workouts (distance and/or time)	Outdoors	1011	88.8
	Inside gym or recreation center at work or in community	67	5.9
	At home, inside and/or immediately outside	50	4.4

Twenty missing values (1.7%); reported percentages (up to 100%) out of 1138 participants (98.3% of data collected).

The age range for study participants was about 14 to 70 years (based on reported birth year: 1938-1993).

We combined Hispanic ethnic subgroups: white, black, Mexican American, non–Mexican Central America.

Missing values, refused to answer, and/or not applicable.

Denominator was 345 (ie, 793 did not register in 2007 event), plus 11 nonresponding participants (3.2%).

There were 10 nonresponse participants (0.9%) for this set of questions.

Participants reported 2 selections if they believed that they spent equal time in 2 of these locations (n = 117).

Table 2 presents data on self-reported doctor-diagnosed respiratory outcomes. About 1 in 8 participants (12.1%) reported having doctor-diagnosed asthma. Most participants (84.7%) did not have a diagnosis of bronchitis at the time they answered the online survey.

Table 2.

Self-reported Doctor-Diagnosed Respiratory Outcomes for a Sample Registered for and Competing in the ING Georgia Marathon and Half-Marathon, 2008^a

		Participants
Variable	Diagnosis	n	%
Bronchitis: Participant	Yes	154	13.5
	No	964	84.7
Asthma
Participant	Yes	138^b	12.1
	No	977	85.9
Spouse, partner, or significant other	Yes	72	6.3
	No	964	84.7
One or more of participant’s children	Yes	85	7.5
	No	790	69.4

Nonresponses (missing values, refused to answer, not applicable) were as follows: 20 (1.8%) on bronchitis, 23 (2.0%) on asthma–participant, 102 (8.9%) on asthma-spouse, partner or significant other, 263 (23.1%) on asthma-participant’s children.

One of these 138 participants had invalid age data (ie, year born).

Table 3 stratifies data on self-reported doctor-diagnosed asthma and bronchitis by sex, race, and education. Of the 12.1% of participants who were diagnosed with asthma and the 13.5% of participants who were diagnosed with bronchitis, about two-thirds were women, and most were white, had graduated from college or university, had attended some graduate school, or had graduated with a master’s degree. These results were consistent with the overall study sample of participants from the target study population (Table 1). More interesting, 12.6% of marathon runners and 11.8% of half-marathon runners reported an asthma diagnosis. Additionally, 15.9% of marathon runners and 12.2% of half-marathon runners were diagnosed with bronchitis. Also notable, 60% of marathon walkers were asthmatic and/or were diagnosed with bronchitis, and among half-marathon walkers, 13.5% were asthmatic and 18.9% were diagnosed with bronchitis. Chronic disease management is critical for these athletes.

Table 3.

Self-reported Doctor-Diagnosed Asthma and Bronchitis: Overall and by Sex, Race/Ethnicity, and Education—ING Georgia Marathon and Half-Marathon Sample, 2008

		Participants^a
Variables	Subcategories	n	%
Asthma diagnosis for participant
Overall	Overall^b,c,d	138	12.1
		977	85.9
		23	2.0
Sex	Male	46	33.3
	Female	92	66.7
2008 registered event	Marathon, running	42	12.6
	Half-marathon, running	88	11.8
	Marathon, walking	3	60.0
	Half-marathon, walking	5	13.5
	Half-marathon, wheelchair	0	0.0
Race/ethnicity^e	White	121	87.7
	Nonwhite^c	16	11.6
Highest level of education	Secondary school graduate or less	4	2.9
	Some university/college or technical/vocational completed	16	11.6
	University/college graduate	38	27.5
	Some graduate school	22	15.9
	Highest graduate degree: Master’s	39	28.3
	Highest graduate degree: Doctorate	19	13.8
Bronchitis diagnosis for participant
Overall	Overall^d	154	13.5
		964	84.7
		20	1.7
Sex	Male	54	35.1
	Female	100	64.9
2008 registered event	Marathon, running	53	15.9
	Half-marathon, running	91	12.2
	Marathon, walking	3	60.0
	Half-marathon, walking	7	18.9
	Half-marathon, wheelchair	0	0.0
Race/ethnicity^e	White	143	92.9
	Nonwhite^c	10	6.5
Highest level of education	Secondary school graduate or less	3	1.9
	Some university/college or technical/vocational completed	13	8.4
	University/college graduate	55	35.7
	Some graduate school	17	11.0
	Highest graduate degree: Master’s	42	27.3
	Highest graduate degree: Doctorate	24	15.6

Overall, 20 missing values (1.7%); reported percentages (up to 100%) were out of 1138 (98.3% of data collected overall). There were, however, 19 extra missing values for certain other questions; thus, here, reported percentages (up to 100%) were out of 1119 (96.6% of data collected overall).

Average age of asthmatic participants was 36 (range, 18-64); average age of participants without asthma, 38 (15-70). Ages based on reported year born.

Average age of participants with unknown asthma status was 28 (range, 19-41), based on reported year born.

Nonresponse (missing values, refused to answer, not applicable): 23 (2.0%) for asthma, 20 (1.7%) for bronchitis.

One participant refused to provide race/ethnicity.

Table 4 presents data on knowledge and awareness of selected asthma management (clinical control, environmental triggers) and general quality-of-life factors among study participants with self-reported doctor-diagnosed asthma. About 1 in 4 participants (24.1%) stated that their asthma bothered or worried them, but few stated that their asthma caused them to miss doing things they wanted to do (3.0%) or that there were things they wanted to do but could not (3.8%). Additionally, 68.4% stated that there were things in their environment that worsen their asthma symptoms; however, only 40.6% felt as though something inside (not outside) their home, work, or school microenvironments made their asthma symptoms worse. Clinically, whereas 84.6% correctly knew that an asthma action plan can prevent hospitalizations due to asthma, only 18% reported they had such a plan. Moreover, only 24.8% had ever been asked to demonstrate how they take their medications (controller and/or rescue inhaler), and only a few (1.5%) reported that they performed daily peak flow measurements.

Table 4.

Knowledge of Asthma Management (Clinical Control) and Quality-of-Life Factors Among Participants With Self-reported Doctor-Diagnosed Asthma: ING Georgia Marathon and Half-Marathon, 2008

		Participants
Question^a,b	Response^b,c	n	%^d
Does your asthma bother or worry you?	Yes	32	24.1
Does your asthma cause you to miss doing the things you want to do?	Yes	4	3.0
Are there things you want to do but cannot do because of your asthma?	Yes	5	3.8
Are there things in your environment that make your asthma worse?^e	Yes	91	68.4
Have you noticed anything in your home, work, or school that makes your asthma worse?^f	Yes	54	40.6
Going from a cold to a hot environment can trigger your asthma, but going from a hot environment to a cold environment does not trigger asthma.^g	True	110	10.4
	False	748	70.4
Do you have an asthma action plan?^e	Yes	24	18.0
Have you been asked to demonstrate how you take your asthma medications?^h	Yes	33	24.8
An asthma action plan can prevent hospitalizations due to asthma.ⁱ	True	918	86.4
	False	53	5.0
Do you perform daily peak flow measurements?^j	Yes	2	1.5

Sources of clinical control questions.^36,37,39,40 Source of general knowledge questions.³⁸

Correct answers are in bold type.³⁸

For clinical control, 28 (23 + 5) missing values and 977 self-reported nonasthmatics (of 1138).

Overall, 20 missing values (1.7%). For clinical control questions, see above note. Reported percentages (up to 100%) were of 133 of 138 reported diagnosed asthmatics. For general knowledge and awareness questions, see below notes.

Three participants refused to answer this clinical control question, so out of 130.

Two participants refused to answer this clinical control question, so out of 131.

For this general knowledge and awareness question, 204 participants refused to answer (19.2%) and 76 had missing values (6.7%); reported percentages (up to 100%) were of 1062 (93.3% of 1138).

Six participants refused to answer this clinical control question, so out of 127.

For this general knowledge and awareness question, 91 participants refused to answer (8.6%) and 76 had missing values (6.7%); reported percentages (up to 100%) were of 1062 (93.3% of 1138).

One participant refused to answer this clinical control question, so out of 132.

Table 5 presents data on knowledge and awareness of selected asthma management factors among study participants with self-reported doctor-diagnosed asthma stratified by selected demographic factors. The key finding was that most participants understood the value of an asthma action plan, even if only 18% reported having a plan at the time of this study. Another finding worth noting was about 1-in-5 people incorrectly answered that the following statement, “going from a cold to a hot environment can trigger your asthma, but going from a hot environment to a cold environment does not trigger asthma,” is false (note the opposite is true).

Table 5.

Knowledge and Awareness of Selected Asthma Management Factors: Overall and by Sociodemographic Factors—ING Georgia Marathon and Half-Marathon Sample, 2008^a

		Participants^b
Variable	Subcategories or Specific Groups	n	%
An asthma action plan can prevent hospitalizations due to asthma [true].^c
Race/ethnicity^d	White	815	86.2
	Hispanic^e	28	87.5
	African American/non-Hispanic black	28	90.3
	Asian American/Pacific Islander	24	82.8
	American Indian	3	100.0
	Other	14	100.0
Highest level of education	Some secondary school	3	75.0
	Secondary school graduate	19	90.5
	Some university/college or technical/vocational completed	91	80.5
	University/college graduate	306	85.7
	Some graduate school	117	85.4
	Highest graduate degree: Master’s	267	87.8
	Highest graduate degree: Doctorate	115	91.3
	Participant’s self-reported asthma diagnosis	111	88.8
	Participant’s spouse/partner has asthma	65	91.5
	Participant’s child (one or more) has asthma	69	85.2
Going from a cold to a hot environment can trigger your asthma, but going from a hot environment to a cold environment does not trigger asthma [false].^f
Race/ethnicity^d	White	664	70.3
	Hispanic^e	27	84.4
	African American/non-Hispanic black	20	64.5
	Asian American/Pacific Islander	20	69.0
	American Indian	3	100.0
	Other	11	78.6
Highest level of education	Some secondary school	3	75.0
	Secondary school graduate	14	66.7
	Some university/college or technical/vocational completed	71	62.8
	University/college graduate	250	70.0
	Some graduate school	98	71.5
	Highest graduate degree: Master’s	213	70.1
	Highest graduate degree: Doctorate	99	78.6
	Participant’s self-reported asthma diagnosis	103	82.4
	Participant’s spouse/partner has asthma	49	69.0
	Participant’s child (one or more) has asthma	60	74.1

Source of general knowledge questions.³⁸

Sample based on participants answering each question correctly (correct answer in brackets). Overall, 20 missing values (1.7%), so study database reduced to 1138 complete participant records.

For this general knowledge and awareness question, 91 participants refused to answer (8.6%) and 76 had missing values (6.7%); reported percentages (up to 100%) were of 1062 (93.3% of 1138).

Eight participants did not provide race/ethnicity.

Hispanic ethnic subgroups combined: white, black, Mexican American, non–Mexican Central America.

For this general knowledge and awareness question, 204 participants refused to answer (19.2%) and 76 had missing values (6.7%); reported percentages (up to 100%) were of 1062 (93.3% of 1138).

Discussion

In this study, participants reported that the majority of their short- to medium-length training workouts (67.7%) and weekly longer workouts (88.8%), critical to marathon and half-marathon training, were completed outdoors. In addition, although the majority (68.4%) stated that there were things in their environment that worsen their asthma symptoms, only 40.6% felt as though something inside (not outside) their home, work, or school microenvironments made their asthma symptoms worse. Thus, for asthmatics, outdoor environmental triggers in the fall and winter training periods preceding the endurance running race, such as particulate matter and nitrogen dioxide, are likely to be of relatively more concern than indoor environmental asthma triggers, such as dust mites, pet allergens, and cockroach or rodent fecal protein antigens. Moreover, primary triggers that participants may have considered during training (eg, particulate matter) usually change by late March, when events occurred (eg, start of ozone season). This scenario may have led to increased airway irritation, for instance.

This study’s data on self-reported doctor-diagnosed respiratory outcomes were interesting and suggestive of future research questions. For the 12.1% of participants reporting doctor-diagnosed asthma, we do not know if it was due to allergy or was exercise induced. In addition, for the 13.5% of participants reporting bronchitis, among the older participants in particular, we do not know for certain if they were also diagnosed with asthma. We assume that reported bronchitis was likely due to a recent acute episode and not chronic bronchitis.

This study’s data on clinical aspects of asthma management collectively suggested that multiple opportunities exist to improve daily asthma self-management practices among recreational endurance athletes diagnosed with asthma—in particular, those of higher socioeconomic status, as is the case with the present study’s sample. Development of an asthma action plan is the logical starting point. The plan, including peak flow monitoring and medication, is a skill to be demonstrated with a physician, nurse, respiratory therapist, and/or asthma educator.

Randolph et al¹⁷ compared results from previously validated surveys among recreational road runners in 2 consecutive years (2003 and 2004, 11% response rate in 2004) to those of Olympic athletes regarding reported symptoms of asthma and allergy. They also compared reported data on medication use (eg, asthma rescue inhalers before a race) and other prescription and over-the-counter medications for allergy. Reported prevalence was 31% for asthma and 21% for asthma and allergies. These percentages are higher than those in our study. Our data, however, were based on reported physician diagnosis, not just the presence of 1 or more classic asthma and allergy respiratory symptoms (wheezing, coughing, chest tightness, shortness of breath). Furthermore, in the Randolph et al¹⁷ study, those reporting asthma and allergy symptoms or only asthma symptoms were more likely to have prescription medication (allergy and asthma, 32%, P = .0001; asthma, 6%, P = .001) and to take medication before a race (asthma and allergy, 27%, P = .0001; asthma, 5%, P = .007) compared to those with only allergy symptoms. Compared to the Olympic athletes, the recreational athletes reported fewer (ie, a lower prevalence of) asthma and allergy symptoms (P < .01) but were less likely to be taking prescription medication (P = .025). Our study focused on physician diagnosis versus details of daily clinical management of symptoms. Neither study focused on reported severity of diagnosis (mild, moderate, or severe persistent).

A literature review by Lang¹⁶ suggested only a small incremental increased risk of death among mild to moderate persistent asthmatics while playing sports at recreational and elite levels across various types of sports and seasons. In the present study, we did not explicitly ask about severity, nor could we infer this type of information from other data collected—the majority of participants did not have an asthma action plan, even though the majority knew what one was. In addition, research by Storms¹² suggested that exercised-induced asthma is prevalent in 10% to 50% of recreational and elite athletes across types of sports and seasons. In this study, we did not explicitly ask about exercised-induced asthma, only physician diagnosis.

The present study had several strengths. Our findings represent one of the few large studies ever conducted among recreational endurance athletes training and competing in a major urban area. Our online survey was administered for about 1.5 months before the events, given the available resources, institutional review board requirements, and planning and preparations. Nevertheless, this did not cover the entire advanced registration process, which started in midsummer 2007. As a result, it is possible that late registrants—at the expo on race weekend—could not participate and that early registrants were among those neither participating nor racing (a study limitation). But, 99.4% of people who started the informed consent process gave consent and completed the survey in 2008 (1151 of 1158). This high participation rate as suggested PsychData was user-friendly, and questions and response choices were readable and understandable; however, this does still not rule out potential information bias given that our 2008 study sample was predominantly white and of a higher socioeconomic status.

The present study also had limitations. With respect to demographic data in our interdisciplinary survey, no data were collected on marital status and health insurance coverage. With respect to socioeconomic status, no data were collected on family/household size (we did ask for household income and level of education obtained) and occupation by job or industry (the third component). We did not ask doctor-diagnosed asthmatics to specify the type (allergic, exercise induced, nonallergic/mechanical, or weight-related mechanism) or severity classification in terms of persistence of asthma symptoms based on the National Heart, Lung, and Blood Institute’s “Guidelines for the Diagnosis and Management of Asthma.”⁴¹ We note, however, that participants may not have been able to answer the latter, given our data demonstrating that the majority (82%) did not have an asthma action plan (Table 5). Study identification numbers randomly generated by PsychData had no relation to assigned race numbers, which were linked to the electronic timing chips; so, we could neither acquire further primary data to assess relevant race day behaviors—rescue inhaler use, reported symptoms during the events, and so on—nor enhance data management or streamline informed consent processes. Finally, the race management team obtained participants’ birth dates on registration forms to calculate accurate race-day ages. Our institutional review board approval asked participants for their year of birth. Thus, we may have underestimated, by 1 year, the age of those born between January and March.

Conclusion

In this study, of a population comprising physically active adults of higher socioeconomic status, we found that 12.1% reported physician-diagnosed asthma. We also found the need for potential improvements in asthma management via written asthma action plans. These plans should include outdoor environmental asthma triggers and demonstration of peak flow monitoring and medication use. Future research of recreational endurance athletes with asthma—particularly in sports involving sustained aerobic activity with periodic changes in intensity—should strive to obtain more information on the type of physician-diagnosed asthma reported (as characterized by the severity of and frequency of symptoms) and mechanistic information—whether allergic (plus the known indoor/outdoor environmental asthma triggers and social stressors), exercised induced, or weight based (ie, mechanical).

Footnotes

Acknowledgements

We acknowledge the efforts of dozens of undergraduate respiratory therapy and physical therapy students, as well as master’s students in nutrition, who volunteered time to help set up the various events and who assisted in data collection and entry at the events or on campus. We thank Alexandra C. H. Nowakowski and Jennifer Therkorn for internal review. We thank for timely collaboration with race organizers and our team. We thank Georgia State University Research Foundation, Atlanta, Georgia, for our interdisciplinary team research funding for 2007-2008, and the Georgia State University Partnership for Urban Health Research for supporting D. Shendell’s PsychData license for July 2006 to May 2008. Finally, we acknowledge the in-kind support received from the College of Health and Human Sciences, Georgia State University, and Georgia Marathon, LLC.

The authors declare no potential conflicts of interest with respect to the authorship and/or publication of this article.

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