2019 Child Asthma Data: Technical Information
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Behavioral Risk Factor Surveillance System (BRFSS)
In 2019, the BRFSS survey was conducted in all 50 states, the District of Columbia (DC), Guam, and Puerto Rico.
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 (The BRFSS Data User Guide: https://www.cdc.gov/brfss/data_documentation/pdf/UserguideJune2013.pdf [PDF – 604 KB]).
Child asthma prevalence data are produced from the responses to questions on BRFSS Random Child Selection and Childhood Asthma Prevalence 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 Prevalence modules were asked of the “Xth” child.
States, and the U.S. territory of Puerto Rico asked both the BRFSS Random Child Selection and Childhood Asthma Prevalence modules questions. The child prevalence tables include data for these 30 states, DC, and Puerto Rico. The included areas were
California, Connecticut, District of Columbia, Florida, Georgia, Hawaii, Illinois, Indiana, Kansas, Maine, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Mexico, Ohio, New York, Oregon, Pennsylvania, Puerto Rico, Rhode Island, Texas, Utah, Vermont, Wisconsin
The following five states were not included in the child asthma prevalence tables because, while they did the Random Child Selection module, they did not do the Childhood Asthma Prevalence module in 2019:
South Carolina, South Dakota, Washington.
The following two asthma questions pertinent to prevalence estimation were asked on the BRFSS Childhood Asthma prevalence module.
Lifetime asthma: Question number M31.01
“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 M31.02
“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 Question | Variable Name | Codes Used |
---|---|---|
M30.1 What is the birth month and year of the “Xth” child? | RCSBIRTH* | Grouped into age categories (in years): 0–4, 5–9, 10–14, 15–7 |
M30.2 Is the child a boy or a girl? | RCSGENDR | 1 = Boy 2 = Girl |
1.01 Child Hispanic, Latino/a, or Spanish origin calculated variable | _CHISPNC | 1 = Yes 2 = No |
1.04 Child non-Hispanic race including multiracial | _CRACE1 | Grouped into race categories: White, Black, Other/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 values for RCSBIRTH are not reported in the public data, but they are in each state’s internal data. The variable of RCSBIRTH is not available at BRFSS public released dataset.
BRFSS Sampling and Weighting Changes
The 2011 BRFSS data collection changed from a landline sample survey to a dual-mode survey: landline and cellphone. The 2019 BRFSS data continues to reflect the changes initially made in 2011 in weighting methodology (raking) and the addition of cell phone only respondents. The aggregate BRFSS combined landline and cell phone dataset is built from the landline and cell phone data submitted for 2019 and includes data for 50 states, DC, Guam, and Puerto Rico. More information about the changes to the 2011 BRFSS can be found at http://www.cdc.gov/surveillancepractice/reports/brfss/brfss.html.
For data analysis, the 2011 BRFSS data should be considered a baseline year. Data are not directly comparable to previous years of data because of the changes in weighting methodology and the addition of the cell phone only respondents. Please see the BRFSS Frequently Asked Questions document for additional information (http://www.cdc.gov/surveillancepractice/reports/brfss/brfss_faqs.html).
Survey Design and Sample Weights
The survey design and the child-weighting methods are described in the technical document, “OVERVIEW: BRFSS 2019,” which can be found at https://www.cdc.gov/brfss/annual_data/2019/pdf/overview-2019-508.pdf [PDF – 304 KB].
Data Analysis
Data Used
The BRFSS 2018 survey dataset (https://www.cdc.gov/brfss/annual_data/annual_2019.html) was used to calculate prevalence estimates for all states that had the Random Child Selection and Childhood Asthma prevalence module included in the common questionnaire.
Prevalence and standard error estimates were calculated using SAS callable SUDAAN Release 11.1 (Research Triangle Institute, Research Triangle Park, NC).
Data Management
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:
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.
Table Conventions
In the tables, states and territories are listed in Federal Information Processing Standard (FIPS) code order.