2009 Child Asthma Data: Technical Information
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In 2009, the BRFSS survey was conducted in all 50 states, the District of Columbia and in three US territories (Guam, Puerto Rico and the Virgin Islands).
In each area where interviews were conducted, respondents were randomly selected from non-institutionalized civilian adults (18 years of age or older) living in households with a telephone (Chapter 4, page 7 of the BRFSS User’s Guide Cdc-pdf[PDF – 986 KB]).
Child asthma prevalence data are produced from the responses to questions on BRFSS Random Child Selection and Childhood Asthma optional modules. A randomly selected adult provided responses to the child asthma questions. If the adult reported that one or more children aged 17 years or younger lived in the household, then one of the children was randomly selected as the “Xth” child. Questions on the BRFSS Random Child Selection and Childhood Asthma optional modules were asked of the “Xth” child.
Thirty-seven states or territories used both the BRFSS Random Child Selection and Childhood Asthma optional modules in 2009. These states or territories were
California, Connecticut, Delaware, District of Columbia, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Louisiana, Maine*, Maryland, Massachusetts*, Michigan, Mississippi, Montana, Nebraska, Nevada, New Jersey, New Mexico*, New York, North Dakota, Ohio*, Oklahoma*, Oregon*, Pennsylvania, Rhode Island, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, and Puerto Rico.
* These states used the Random Child Selection & Childhood Asthma optional modules in a multiple questionnaire version (split sample states).
The following two asthma questions pertinent to prevalence estimation were asked on the BRFSS Childhood Asthma Prevalence optional module.
Lifetime asthma: Question number 26.1
“Has a doctor, nurse or other health professional ever said that the child has asthma?”
(Variable name: CASTHDX2 [Yes = 1 / No = 2])
Current asthma: Question number 26.2
“Does the child still have asthma?” (Variable name: CASTHNO2 [Yes = 1 / No = 2])
Subgroup tables are based on data from the following questions on the Random Child Selection optional module.
Survey Questions, Variable Names and Codes Used in Subgroup Tables
|Survey Question||Variable name||Codes used|
|25.1 What is the birth month and year of the “Xth” child?||RCSBIRTH*||Grouped into age categories
(in years):0 – 4, 5 – 9, 10 – 14, 15 – 17
|25.2 Is the child a boy or a girl?||RCSGENDER||1 = Boy
2 = Girl
|25.3 Is the child Hispanic or Latino?||RCHISLAT||1 = Yes
2 = No
|25.4 Which one or more of the following would you say is the race of the child?||_CRACE||Grouped into race categories:White, Black, Other races, Multiracial|
* The child’s age was calculated by (IDATE-RCSBIRTH)/365.25, where IDATE is the interview date and RCSBIRTH is the child’s birth month and year with 15th as the day.
The survey design and the child-weighting methods are described in the technical document, “Overview: BRFSS 2009”, which can be found at the Web location:
The BRFSS 2009 survey dataset was used to calculate prevalence estimates for all states that had the Random Child Selection & Childhood Asthma optional modules included in the common questionnaire. For states that used one or more dual questionnaires for these two modules, questionnaire version specific datasets were used for analysis.
Prevalence and standard error estimates were calculated using SAS callable SUDAAN Release 10.0.0 (Research Triangle Institute, Research Triangle Park, NC).
Responses of “don’t know/not sure,” and “refused” were re-coded as missing values. Children older than 18 years were excluded from further analysis.
Confidence Intervals and Prevalence Numbers:
The 95% confidence intervals were calculated using the following formulas:
Lower 95% confidence interval = % prevalence – tv (sep)
Upper 95% confidence interval = % prevalence + tv (sep)
Where sep is the standard error of the prevalence percent and tv represents the student’s t distribution with v degrees of freedom.
Small Sample Size and Failure of Distributional Assumptions
When sample sizes for a particular state or territory was smaller than 50, the calculated standard error of the prevalence estimate might have been large relative to the point estimate of the prevalence value, which caused a wide 95% confidence interval. This sometimes caused the lower limit of the 95% confidence interval to be negative. In which case, the lower limit of the interval was set to zero.
In situations where the normal distribution approximation to the binomial distribution did not hold, values for the standard error and the 95% confidence interval of estimates were not provided, because these estimates are not reliable.
In the tables, states and territories are listed in Federal Information Processing Standard (FIPS) code order.