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Abstract #2



Abstract #2. Poster presented at Chest 2013

Prevalence and risk factors for Asthma in adult outpatient population



As of 2011, almost 250 million people worldwide were affected by asthma, 1 and approximately 250,000 people die per year from the disease. 2 It is more common in developed countries as compared to developing countries. 2  Asthma affects approximately 8.4 % of the population of the United States and causes approximately 4,210 deaths per year. 3, 4, 5


Asthma is a common disease and one in 12 adults has asthma 6,7 and in Texas almost 8 -12% of adults suffer from asthma 8. In 2009, there were 479,000 asthma-related hospitalizations and 8.9 million asthma-related doctor visits 9. It is an expensive and deadly disease, and costs our nation $56 billion per year and 9 lives per day 9. Black Americans are 2 to 3 times more likely to die from asthma than any other racial or ethnic group 9. So, there are several known risk factors for example, race, history of allergy. But rare risk factors and especially the interplay among different risk factors are poorly understood.


Purpose: Early risk-identification and dissemination of information to the healthcare providers and patients will result in improved patient outcomes.


Method: This is a retrospective analysis of 400 high risk patients in private practice setup. Data was collected from medical records for early risk assessment and diagnosis in patients seeking health care in a medical clinic at San Angelo, Texas. The outcome variable was presence of Asthma diagnosed by the pulmonologist at the clinic. For each patient, socio-demographic, laboratory and clinical information was obtained. The exposure variables were: demographic characteristics; age, gender, ethnicity,; information about co-morbidity; OSA, hypertension and blood biomarkers. Logistic models with forward selection and backward elimination methods were employed to determine association between different risk factors and the presence of Asthma.


More than half of our study population were aged (above 65 years), 56% female and three fourth were White. Seventy five percent of study subjects (N=297) were diagnosed as asthmatic, almost one third of patient population suffer from obstructive sleep apnea, 69% were overweight or obese while thirteen percent were hypertensive.

Multivariate logistic regression analysis showed that being female, being in age groups <65, smokers, being overweight, having OSA, and higher level of factor 8 level were associated with the presence of Asthma. Females has twice odds of developing asthma (P=0.007) while compared to older adults (>65 years old) younger patients had nine times more likely to be asthmatic (P=0.014) after controlling for all the associated risk factors and co-morbidities.


With every unit increase of BMI, there is about 4% increase in odds of being asthmatic (P=0.045), while compared to normal weight patient who are overweight or obese were 77% more like to be diagnosed with asthma. Smokers were 70% less likely to be associated with asthma (P=0.00). Factor VIII exhibit significant relationship with outcome (P=0.03).


From our model, F8 strongly modify the relationship between OSA and Asthma. Patients with moderately elevated F8, depicted odds of Asthma 2.67 times higher if they have OSA compared to those without OSA. The association (become multiplicative) aggravated in subjects with highly elevated F8. So in highly elevated F-8, the odds of being asthmatic is 16.68 times higher for those with OSA comparing to those without OSA. In general, for each unit of increase in BMI, there is an increase in odds of Asthma in older population but the association reverses in younger population, where BMI is protective and odds reduced 6% for each unit increase in BMI.


Smoking and higher level of factor 8, were negatively associated with asthma while being heavy, high BMI and age were significant risk factors for development of asthma. Identification of uncommon risk factors and their interaction with other risk factors for asthma is very vital to assess the individual risk of asthma and promote more targeted prophylactic and therapeutic options. Based on this new information we can develop and advance policies to improve prevention, early detection, and control of asthma in co-morbid patients. Additional prospective studies and analysis of clinical data are essential for further understanding of the underlying mechanism of disease.


1. “World Health Organization Fact Sheet Fact sheet No 307: Asthma”,2009. Retrieved 2nd Oct,  2013.
2. http://www.ginasthma.org/uploads/users/files/GINA_Report2011_May4.pdf
3. Fanta CH (March 2009). “Asthma”. New England Journal of Medicine 360 (10): 1002–14.
4 Lazarus SC (August 2010). “Clinical practice. Emergency treatment of asthma”. N. Engl. J.  Med. 363 (8): 755–64.
5. Getahun D, Demissie K, Rhoads GG (2005). “Recent trends in asthma hospitalization and mortality in the United States”. Journal of asthma 42 (5): 373–8.
6. http://www.cdc.gov/asthma/impacts_nation/infographic.htm
7. National Health Interview Survey (NHIS) Prevalence Data
8. http://www.cdc.gov/asthma/brfss/2010/brfssdata.htm
9. Asthma’s Impact on the Nation, National Asthma Control Program (NACP),

Centers for Disease Control and Prevention (CDC), http://www.cdc.gov/asthma/impacts_nation/infographic.htm, Retrieved 2nd Oct, 2013.

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