Asthma is a chronic lung disease caused by inflammation of the lower airways and episodes
of airflow obstruction. Asthma episodes or attacks can vary from mild to life-threatening.
In 2007, about 7% percent of the U.S. population was diagnosed with asthma and there
have been a growing number of new cases since that time. There are several known risk
factors identified as triggers of asthma symptoms and episodes, including inhalation of
allergens or pollutants, infection, cold air, vigorous exercise, and emotional upsets. There is
also growing evidence relating body-mass index to asthma in both children and adults.
Design a study to investigate whether there is such an association.
Choose a study design and justify the reasons you chose the design over others.
Select a statistical measure you would use to describe the association (if there is one)
between body mass index and asthma.
In addition, address:
Subject selection
Issues relating to the measurement of both the exposure and the outcome
Potential biases that the study might be prone to, and how they might be handled
Possible confounding factors and effect modifiers and how to overcome their effect
Present the information in a 750-1000-word report, using section headings where each
requirement is described and justified under each of the following headings: Study Design,
Statistical Measures, Subject Selection, and Measurement Issues.
Refer to the “Key Elements of a Research Proposal.”
You are required to use a minimum of three scholarly resources.
Prepare this assignment according to the APA guidelines found in the APA Style Guide,
located in the Student Success Center. An abstract is not required.

Study Design

Asthma, a chronic lung disease, results from the lower airways inflammation as well as
airflow obstruction episodes. Its attacks or episodes vary from life-threatening to mild. In the
year 2007, approximately seven percent of the population in US was diagnosed with the disease
and since that time, the numbers of new cases have been increasing. There are a few recognized
risk factors that are known as triggers of asthma episodes and symptoms. These include inhaling
pollutants or allergens, vigorous exercise, cold air, infection, and emotional upsets. In addition,
there is escalating evidence in relation to asthma and body-mass index in adults and children.
This paper aims at developing a study design through which such an association can be


Study Design

The longitudinal health study will be on respiratory health and it will be essential in
investigating in body mass index (being obese or overweight) is actually an antecedent state
linked to an escalated vulnerability of newly diagnosed asthma. The link between obesity
development and novel physician-diagnosed asthma will be examined through the use of data
that will be gathered during annual assessments. A cohort of three thousand seven hundred and
ninety two asthma- free children at enrollment will be used. The prospective study will aim at
identifying the determinants of respiratory health in children (Taylor, 1999).
The children will be assessed yearly during school visits up until their high school
graduation. Data will be collected from the second cohort group once, five visits for the 7 th and
4 th graders, and three visits for the 10 th graders. During every annual assessment visit, the school
children will be required to complete updated interviews and questionnaires that will include
items regarding physician asthma diagnosis, recent exposure history, and other respiratory
symptoms. An incident asthma case will be defined as a novel physician asthma diagnosis during
the periods between follow-up assessments. Incident asthma cases’ date of diagnosis will be
assigned as the intermediate of the time between the follow-up assessments.
Lung function, weight, and height will be measured yearly using the standard protocols.
Considering the link between obesity and MBI changes with age in addition to varying by sex,
BMI will be categorized into sex- and age- specific percentiles founded on CDC BMI growth
charts (one month age intervals). Overweight will be defined as a MBI larger than the sex- and
age- specific 85 th percentile while obesity will BMI larger that the ninety fifth percentile.

Statistical measure

The new physician- diagnosed asthma cases’ incident rates will be calculated through the
use of; new cases number/ person- years at risk for a four-year follow-up period. Stratified rates
will also be calculated for girls and boys, in addition to sex- and age- specific BMI percentile
categories during entry (Taylor, 1999). The new cases’ numbers as well as person-years at risk in
every stratum will be determined as well as summed during the follow-up period. To investigate
the link between new asthma cases and BMI, while considering the confounding variables’
effects, Cox proportional hazards regression model will be used. All analyses will be conducted
by using the SAS software.

Subject selection

The subjects will be school-age children and they will be drawn from twelve California
communities. The children will be recruited six months before the study begins from 10 th ,
seventh, and fourth- grade classes in twelve Southern California communities’ public schools. A
second cohort constituting of 4 th graders will be recruited three years later (Halloran &
Struchiner, 1991). As the participants entered into the study, their guardians or parents presented
a written informed consent in addition to completing written questionnaires that offered
information regarding sociodemographic factors, history of allergic and respiratory illnesses as
well as their associated risk factors, household characteristics, household members’ smoking,
and exposures. Children with a lifetime asthma history at the study entry will be considered not
at risk and will be excluded. Wheezing will be defined as any lifetime wheezing history at study
entry. Children will the wheezing history but no asthma diagnosis will be regarded as at risk for a
novel asthma diagnosis and will be included. The California population will be selected since
there are many new case of overweight and obesity as well as asthma.
Potential biases- handling

The study might be biased by the fact that children might have moved to other schools
not included in the study or discontinued their education. To counter this, once a child is
identified as a participant, follow-ups will be made to the places they are located, either at home
or new schools (Cardon & Bell, 2001).

Effect modifiers and confounding factors- overcoming

There will be identified through literature review and preliminary analyses. They will
include sex, race/ ethnicity, age, community of residence, health insurance, parental asthma and
allergies history, humidifier use, birth weight, history of allergy, history of wheezing,
engagement in team sports, household ETS (environmental tobacco smoke) exposure, personal
smoking, household pests and pets, lung function level, and puberty. Factors such as parental
history will be considered at entry. However, other factors such as exposure to allergens will be
assessed during the annual school visits so that they are put into consideration.



Cardon, L. R., & Bell, J. I. (2001). Association study designs for complex diseases. Nature
Reviews Genetics, 2(2), 91-99.
Halloran, M. E., & Struchiner, C. J. (1991). Study designs for dependent happenings.
Epidemiology, 2(5), 331-338.
Taylor, D. (1999). Introduction to Research Methods. medicine, 319, 1618.

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