Adult Asthma Module: Technical information

BRFSS Core Questionnaire

In each area where interviews are conducted, respondents are randomly selected from noninstitutionalized civilian adults (18 years of age or older) living in households with a telephone (BRFSS User’s Guide pdf icon[PDF – 1.7 MB]). Asthma prevalence data are produced from the responses to two asthma questions on the 2007 BRFSS Core Questionnaire.

Lifetime asthma: Question number 9.1
“Have you ever been told by a doctor, nurse, or other health professional that you had asthma?” (Variable name: ASTHMA2)

The calculated variable _LTASTHMA (based on question 9.1) from the public use file was used when creating the tables.

Current asthma: Question number 9.2
If the response to 9.1 was “Yes,” then question 9.2 was asked: “Do you still have asthma?” (Variable name: ASTHNOW)

Adult module tables include only respondents who answered “yes” to both the lifetime and the current asthma question.

Module tables are based on data from the following questions:

Survey Design and Sample Weights

The survey design is described in the technical pages document for each year, for example, “2007 Overview” at http://www.cdc.gov/brfss/technical_infodata/surveydata/2007.htm. Sample weights are assigned, according to BRFSS methodology, to the variable _FINALWT as described in the BRFSS Weighting Formula.

Data Analysis

Data Used:

The BRFSS Survey Datapdf icon files for 2002 to 2007 were used to calculate estimates for states that included the adult asthma module in their BRFSS survey. States for each year are indicated below:

* Used a Dual Questionnaire (split sample).

Software:

Percent and standard error estimates were calculated using the SAS 9.1 PROC SURVEYFREQ procedure to account for survey data from complex sample designs. The BRFSS employs a complex stratified sample design. Therefore, an analysis that ignored the complex design clustering and stratification and the sample weights (for example the SAS PROC FREQ procedure) would result in biased estimators.

Data Management:

Only respondents with values of the variables as described in the table above are included in each table. Responses of “don’t know/not sure,” “refused,” or missing values were excluded.

In the original data sets, those respondents answering “Not at any time” to the question “days of asthma symptoms in the past 30 days” had missing values in the question “days of sleep disturbance in the past 30 days” because of a skip pattern in the interview sequence. Therefore, those answering “Not at any time” to the question days of asthma symptoms in 30 days were recoded to “None” for the question “days of sleep disturbance in the past 30 days.”

For “days of activity limitation in 12 months,” the respondents with a response code of “88” days were excluded. Previous investigations indicated that an “88”represented a coding error resulting from the numerical similarity with the code for no days (888).

In the 2005 data, Delaware data included an unusually large percentage of “Don’t Know/Not Sure” for the questions “age of asthma onset” and “use of rescue inhaler in 30 days.” After BRFSS staff in Delaware was consulted, the data were revised to correct a coding error.

Sample weights for states implementing split sample designs have been adjusted to account for the use of dual questionnaires (Colorado and New Jersey in 2007).

Table Conventions:

The first table in each file is a summary table with data from all the states that implemented the adult module. It excludes any U.S. territories that implemented the module. Individual tables for each state and each territory that conducted the adult module follow the summary table.

The tables examine interrelationships between multiple asthma-control indicators (rows) and a primary variable (columns). For the years 2002 to 2004, separate tables are provided for three primary variables (Sex, Age at Diagnosis, and Medication Status). Each table includes the following indicators: Age at Diagnosis (if not the primary variable), Medication Status (if not the primary variable), Attack, Emergency Department Visits, Urgent Doctor Visits, Routine Doctor Visits, Activity Limitations, Days with Symptoms, and Days with Sleep Disturbance. Beginning with 2005, tables are provided for five primary variables (Sex, Age at Diagnosis, Medication Status, Rescue Inhaler, and Preventive Medication). Each primary variable table includes the following indicators: Age at Diagnosis (if not the primary variable), Preventive Medication (if not the primary variable), Rescue Inhaler (if not the primary variable), Attack, Emergency Department Visits, Urgent Doctor Visits, Routine Doctor Visits, Activity Limitations, Days with Symptoms, and Days with Sleep Disturbance.

The relationship between each indicator variable (rows) and the three primary categorical variables (2002–2004) or the five primary categorical variables (2005 and later) were examined. Indicator variables were categorized in two different ways. First, each indicator was dichotomized to represent any event or no event (visit, days, attack, medication use). Second, the “Any” category was grouped into several sub-categories by collapsing question response categories as shown in the table above.

For each indicator variable for each of the three primary categorical variables (2002–2004) or five primary categorical variables (years since 2005) the proportion estimates and variance estimates were calculated. The Wald test was used to determine if there was a significant relationship between each indicator variable and the primary categorical variables. Tests were done separately for the dichotomized version of the indicator and for the multiple category version of the indicator. The resulting P-values are reported in each table.

Small Sample Size

When sample sizes in cells are less than 50, as they are in some of the state/territory tables, the standard error may be large relative to the estimate value, leading to a wide 95% confidence interval. Caution should be used in interpreting such “imprecise” estimates.