COMPARABILITY OF DATA The BRFSS is a cross-sectional surveillance survey currently involving 52 reporting areas. It is important to note that any survey will have natural variation over sample sites; therefore some variation between states is to be expected. The complex sample design and the multiple reporting areas complicate the analysis of the BRFSS. Although Situs Slot Gacor works with the states to minimize deviations, in 1997 there were some deviations in sampling and weighting protocols, sample size, response rates, and collection or processing procedures. In addition, California's questionnaire had a few minor differences in question wording and a more restrictive age range for the HIV/AIDS questions. This following section identifies variations identified for 1997. A. 1997 Data Anomalies and Deviations from Sampling Frame and Weighting Protocols Alaska Alaska's sample design is made up of three random digit-dialed strata and four listed strata, where phone numbers are selected from a list of putative household numbers. The sampling frame contains all of the household numbers in the random digit-dialed strata and an estimated 45% of all household numbers in the listed strata. This represents an exclusion of approximately 9% of all residential numbers in Alaska. In 3 out of 4 geographic strata, prefixes are assigned to a high (RDD) or low (listed) density stratum depending largely on the number of active household numbers (about 2000 being the threshold) in the exchange (10,000 numbers). All numbers in the fourth geographic stratum are assigned to the listed density stratum. In the RDD strata, the probability that a number is selected depends on the number of active household numbers in its exchange. In the RDD strata, a number of prefixes equal to the target sample size are selected at random in proportion to their number of active HH's. (A prefix can be selected more than once.) Once a prefix is selected into the RDD sample, 48 suffixes are randomly generated. Once the entire sample for the stratum is generated duplicate numbers are deleted without replacement. The final result is h lists of phone numbers per stratum, each containing 48 or fewer unique numbers, where h is the target number of completes per stratum. Phone numbers are called sequentially from each list until one complete per list is obtained. California California's 1997 sample design uses a sampling frame consisting of hundred blocks that contain three or more listed household telephone numbers. Telephone numbers are sampled in direct proportion to the number of listed household numbers in the hundred block from which each is selected. The design also varies probabilities of selection by the county to which a prefix is assigned according to one of various criteria, such as total households or population. The criteria may have varied at the different times sample records were selected. During sample selection, if a known business number is initially selected, it is replaced by the next eligible number on the sampling frame, which increases the probability of selection of numbers preceded by known business numbers. Any number selected within the previous five to six months by any of the clients used by California's vendor is also replaced by the next available number on the sampling frame unless this would result in an insufficient number of sampling units being provided. No adjustment has been made for the differential probabilities associated with selection being made in proportion to hundred block listings, county, or replacement of business or recently selected numbers. Hawaii Hawaii uses a sampling frame obtained from the state's telephone company. The frame purportedly contains all working prefixes in Hawaii. The frame is divided into six strata, corresponding to the major islands of Hawaii. The working prefixes are used to randomly generate telephone numbers with a probability proportional to the number of known household numbers in the hundred block to which a number belongs. Telephone numbers from hundred blocks with no known household numbers have a zero probability of being included in the sample. The percentage of telephone households excluded from the sampling frame is unknown. The numbers generated are subsequently screened by GTE Hawaii, who screens out all but the listed and unlisted household numbers in the sample. Nevada Nevada used two different sample designs in 1997. From January through August, Nevada used a sample design with a sampling frame consisting of hundred blocks that contain five or more listed household telephone numbers. Telephone numbers were sampled in direct proportion to the number of listed household numbers in the hundred block from which each is selected. The design also varied probabilities of selection by the county to which a prefix is assigned according to one of various criteria such as total households or population. The criteria may have varied at the different times sample records were selected. During sample selection, if a known business number was initially selected, it was replaced by the next eligible number on the sampling frame, which increased the probability of selection of numbers preceded by known business numbers. Any number selected within the previous five to six months by any of the clients used by Nevada's vendor was also replaced by the next available number on the sampling frame unless it resulted in an insufficient number of sampling units being provided. No adjustment has been made for the differential probabilities associated with selection being made in proportion to hundred block listings, county, or replacement of business or recently selected numbers. From September through December, Nevada used a disproportionate stratified sample. The differences in designs were taken into account when weighting the data. Texas In 1997, Texas used a sample design in which only phone numbers from hundred blocks with one or more listed household numbers were included in the sampling frame. Such hundred blocks are estimated to contain 97.1% of all household numbers in Texas. Numbers from this frame were selected with an equal probability of selection. Other areas In a few states, a portion of sample records intended for use during one month may have been completed in another month. This deviation should only affect analyses based on monthly, rather than annual, data. B. Other 1997 limitations of the data In addition to departing from the standard for sample designs, California modified the wording of mammography, Papanicolaou (PAP) smear questions and chronic alcohol use. These questions may have limited comparability to those of other reporting areas. California also asked the HIV/AIDS section questions to persons 18-45 years of age rather than to those 18-64 years of age as specified. Oklahoma's sample includes a disproportionate number of persons 65 years or over compared with their state population. An age distribution that differs substantially from the population distribution in the survey may produce biased estimates of risk factor prevalences, particularly since many characteristics of individuals are affected by age. Further information on age distribution is shown in Table 6 of the Summary Quality Control Report avaialbe at the internet web site www.cdc.gov/nccdphp/brfss. Respondent race distribution between the sample and the population differed for some reporting areas, and may produce biased estimates of risk factor prevalences. The discrepancy between the percentage Non-white in the sample and the percentage Non-white in the population is an indicator of racial bias of the sample. The percentage Non-white in the sample is affected by interstate differences in the protocol for coding the race of Hispanics. For example, Texas and Idaho coded Hispanics as Other Race unless the respondent identified themselves as belonging to one of the standard categorical races the first time they were asked the question. New Mexico, by contrast, probed for one of the standard race categories. Finally, California coded the race of Hispanics as White unless they identified themselves as belonging to one of the other standard races the first time they were asked the question. These differences in protocol affect the percentage Non-white in states with large Hispanic populations and may introduce bias in the race-specific risk factor prevalences for these areas. ( See Tables 3-5 in The Summary Quality Control Report for additional information.) Income non-response varies substantially by reporting area. Although the median non-response rate on this item is 6.1%, it ranges from 1.4% to 26.8% across states. Twenty-seven percent of Oklahoma's respondent records were missing income, as were about 25% of the records in South Carolina and Arizona. Compared with other items on the survey, income non-response is relatively high. For example, item non-response for age has a median of less than 0.4%, and a maximum of 3.0%. Other demographic items (not shown in the tables), including education, employment, and marital status have less than 1% item non-response. Telephone coverage averages about 95% for U.S. states as a whole, but ranges from 3.2% non-coverage in North Dakota, to 13.3% in New Mexico. It is estimated that 24% of households in Puerto Rico are without telephones. Dual questionnaires and/or partial year coverage occurred in Illinois, Kentucky, Maryland and Tennessee. Illinois used dual questionnaires, and collected data on core items involving immunization, cholesterol and hypertension and modules concerning fruits and vegetables; exercise and weight control for only 6 months of the interviewing period in 1997. Kentucky used dual questionnaires and collected data on the following modules for only part of the year: fruits and vegetables, exercise, folic acid and smokeless tobacco. Maryland collected data for part of the year for the oral health, fruits and vegetables, social context and sexual behavior modules. Tennessee collected data for the modules on sexual behavior and exercise for only part of the year. Data users will need to alter program code so that the usual "missing/dk/refused" codes are not combined with "9's" appearing in records due to noncoverage in the states mentioned here.