From 1999 to 2001 the Kansas BRFSS was conducted using disproportionate stratified sampling methodology. This method of probability sampling involved assigning sets of one hundred telephone numbers with the same area code, prefix, and first two digits of the suffix and all possible combinations of the last two digits (“hundred blocks”) into two strata. Those hundred blocks that have at least one known household number are designated high density (also called “one-plus blocks”); hundred blocks with no known household numbers are designated low density (“zero blocks”). The high density stratum is sampled at a rate four times higher than the low density stratum, resulting in greater efficiency.

Beginning in 2002, the sampling method changed. The disproportionate stratified sample now consists of three strata: listed one-plus block numbers, not listed one-plus block numbers, and zero block numbers. Not listed one-plus numbers are sampled at two-thirds the rate of listed numbers; zero block numbers are sampled at one-fifth the rate of listed numbers. The sampling was changed to increase survey efficiency.

Approximately the same number of persons are called each month throughout each calendar year to reduce bias caused by seasonal variation of health risk behaviors. Potential working telephone numbers are dialed during three separate calling periods (daytime, evening, and weekends) for a total of 15 call attempts before being replaced. Upon reaching a valid household number, one household member ages 18 years or older is randomly selected. If the selected respondent is not available, an appointment is made to call at a later time or date. Because respondents are selected at random and no identifying information is solicited, all responses to this survey are anonymous.

Weighting Procedure
Weighting is a process by which the survey data are adjusted to account for unequal selection probability and response bias and to more accurately represent the population from which the sample was drawn. The responses of each person interviewed are assigned a weight which accounts for the density stratum, the number of telephone numbers in the household, the number of adults in the household, and the demographic distribution of the sample. Alterations in the weighting formulas are made to arrive at estimates for prevalence of households and among children in specific age groups.

Analysis
On some questions which pertain to a particular topic, only respondents who responded in a specific way [subpopulation] on an initial question continue to the next question. Though the subsequent question is asked from those respondents who responded in a particular manner on initial question, analysis for the subsequent question is based on the denominator that includes all respondents who responded to the initial question (in any manner). Therefore, the presented results are on all respondentents vs. the subpopulation. Questions which have this approach aplied are indicated with the statement "Denominator adjusted to represent the prevalence in the overalll population".

Data Reliability
Telephone interviewing has been demonstrated to be a reliable method for collecting behavioral risk data and can cost three to four times less than other interviewing methods such as mail-in interviews or face-to-face interviews. The BRFSS methodology has been utilized and evaluated by the CDC and other participating states since 1984. Content of survey questions, questionnaire design, data collection procedures, surveying techniques, and editing procedures have been thoroughly evaluated to maintain overall data quality and to lessen the potential for bias within the population sample.

Limitations
Sampling
The BRFSS survey samples the population using a technique which is discussed in the methodology section. Sampling yields results which are an estimate of the true answer for the entire population. The more persons that are interviewed, the greater the precision of the estimate. When the data are subdivided to look at sub-populations (e.g., an age subgroup) these estimates will be less precise; if the number of persons interviewed was small because the subgroup represents a small fraction of the population (e.g., diabetics less than 30 years old), the estimate may become too uncertain to be of value.

Because the survey is conducted by telephone, persons without telephones could not be reached. Since phone ownership is highly correlated to income, persons without a phone are more likely to have low incomes than persons with a telephone. This will potentially affect questions with responses that are highly dependent on income (e.g., health insurance) more than other questions. However, because phone ownership is high in Kansas (greater than 95%), it is unlikely that failing to reach these persons will substantially alter results.

Questionnaire Design and Administration
How a question is written and which questions preceded it in the questionnaire can influence responses in unpredictable ways. Not all the questions used in the survey have been tested to ensure that all persons understand the intended meaning. Those that come from modules created by the Centers for Disease Control and Prevention usually have been tested, while those in state modules may or may not have been tested, depending on the source of the question. Furthermore, not all questions are equally easy for respondents to answer. While it may be easy for a respondent to provide a personal opinion, it may be much harder to recall a past event (last mammogram) or provide factual information (household income).

Interviewers are trained and monitored (see Quality Control Page) to ensure that they administer the survey in a neutral voice and read the written question verbatim and without comment. Nonetheless, it is possible for the interviewer to bias the results through tone of voice or administration technique. Coding errors may also occur if the interviewer types in the wrong response to the question. In addition, the person being interviewed may alter his or her response to give the interviewer the most socially acceptable answer. This may be a problem especially for questions which may have a perceived stigma (e.g., HIV risk).

Response Rate
The following table includes the CASRO* response rates for the Kansas BRFSS for 1996-2007 by survey year:

The CASRO formula is based on the number of interviews completed, the number of households reached, and the number of households with unknown eligibility status (e.g., households that where called 15 times but where no one in the household was reached). The CASRO response rate is used because in addition to those persons who refused to answer questions, lack of response can also arise because household members were not available despite repeated call attempts, or household members refuse to pick up the phone based on what they discern from caller ID. The bias from non-response cannot be removed; it is not possible to know if those who refused to respond would have answered the questions in approximately the same ways as those who responded.

Confounding and Causation
personal characteristics which are presented on this web site are univariate (i.e., examine each risk factor in relationship to only one characteristic at a time); however, the complexity of health associations are not fully represented by examining single relationships. For example, an examination of heart disease and employment status might show a greater prevalence of heart disease among persons who are retired than among persons who are employed. However, persons who are retired are expected to have a greater average age than persons who are employed; consequently, this relationship might entirely disappear if we removed the effects of age. (If this were the case we would say that the relationship between heart disease and employment status was being confounded by age.)

Likewise, this web site does not attempt to explain the causes of the health effects examined. For instance, BRFSS data might show a higher prevalence of heart disease among smokers, but one should not conclude from this that smoking causes heart disease. That smoking is indeed a causal factor for heart disease is apparent from a large body of scientific data, but that is not a conclusion that can be drawn from a cross-sectional survey such as this. Rather this is a “snapshot” of disease, risk factors, and population characteristics for adult residents of Kansas at a point in time.

* Council of American Survey Research Organizations

POPULATION DENSITY STRATIFICATIONS

County Categories& Definitions

Categories	Definition of Designations	Number of Counties
Frontier	Less than 6 persons per square mile	31
Rural	6 to less than 20 persons per square mile	38
Densely-settled rural	20 to less than 40 persons per square mile	19
Semi-urban	40 to less than 150 persons per square mile	12
Urban	150 + persons per square mile	5

Population, Land Area, and Population Density by County Kansas, 2000

County	County Code	2000 Population	Land Area Square Miles	Pop. Density Persons Per Square Mile	Category
Kansas		2,688,418	81,823	32.86	Densely-Settled Rural
Allen	001	14,385	503.1	28.59	Densely-Settled Rural
Anderson	003	8,110	583	13.91	Rural
Atchison	005	16,774	432.4	38.79	Densely-Settled Rural
Barber	007	5,307	1134.2	4.68	Frontier
Barton	009	28,205	894	31.55	Densely-Settled Rural
Bourbon	011	15,379	637.1	24.14	Densely-Settled Rural
Brown	013	10,724	570.7	18.79	Rural
Butler	015	59,482	1428.2	41.65	Semi-Urban
Chase	017	3,030	775.9	3.91	Frontier
Chautauqua	019	4,359	641.7	6.79	Rural
Cherokee	021	22,605	587.2	38.50	Densely-Settled Rural
Cheyenne	023	3,165	1019.9	3.10	Frontier
Clark	025	2,390	974.7	2.45	Frontier
Clay	027	8,822	643.9	13.70	Rural
Cloud	029	10,268	715.7	14.35	Rural
Coffey	031	8,865	630.3	14.06	Rural
Comanche	033	1,967	788.4	2.49	Frontier
Cowley	035	36,291	1126.3	32.22	Densely-Settled Rural
Crawford	037	38,242	593	64.49	Semi-Urban
Decatur	039	3,472	893.6	3.89	Frontier
Dickinson	041	19,344	848.4	22.80	Densely-Settled Rural
Doniphan	043	8,249	392.2	21.03	Densely-Settled Rural
Douglas	045	99,962	457	218.74	Urban
Edwards	047	3,449	622.1	5.54	Frontier
Elk	049	3,261	647.9	5.03	Frontier
Ellis	051	27,507	900	30.56	Densely-Settled Rural
Ellsworth	053	6,525	715.9	9.11	Rural
Finney	055	40,523	1300.2	31.17	Densely-Settled Rural
Ford	057	32,458	1098.6	29.54	Densely-Settled Rural
Franklin	059	24,784	573.9	43.19	Semi-Urban
Geary	061	27,947	384.3	72.72	Semi-Urban
Gove	063	3,068	1071.5	2.86	Frontier
Graham	065	2,946	898.3	3.28	Frontier
Grant	067	7,909	574.9	13.76	Rural
Gray	069	5,904	868.9	6.79	Rural
Greeley	071	1,534	778.1	1.97	Frontier
Greenwood	073	7,673	1139.8	6.73	Rural
Hamilton	075	2,670	996.5	2.68	Frontier
Harper	077	6,536	801.5	8.15	Rural
Harvey	079	32,869	539.4	60.94	Semi-Urban
Haskell	081	4,307	577.4	7.46	Rural
Hodgeman	083	2,085	860	2.42	Frontier
Jackson	085	12,657	656.9	19.27	Rural
Jefferson	087	18,426	536.2	34.36	Densely-Settled Rural
Jewell	089	3,791	909.2	4.17	Frontier
Johnson	091	451,086	476.8	946.07	Urban
Kearny	093	4,531	870	5.21	Frontier
Kingman	095	8,673	863.7	10.04	Rural
Kiowa	097	3,278	722.4	4.54	Frontier
Labette	099	22,835	648.9	35.19	Densely-Settled Rural
Lane	101	2,155	717.3	3.00	Frontier
Leavenworth	103	68,691	463.3	148.26	Semi-Urban
Lincoln	105	3,578	718.9	4.98	Frontier
Linn	107	9,570	598.8	15.98	Rural
Logan	109	3,046	1073.1	2.84	Frontier
Lyon	111	35,935	851	42.23	Semi-Urban
McPherson	113	29,554	899.8	32.85	Densely-Settled Rural
Marion	115	13,361	943.2	14.17	Rural
Marshall	117	10,965	902.6	12.15	Rural
Meade	119	4,631	978.5	4.73	Frontier
Miami	121	28,351	576.8	49.15	Semi-Urban
Mitchell	123	6,932	699.9	9.90	Rural
Montgomery	125	36,252	645.3	56.18	Semi-Urban
Morris	127	6,104	697.4	8.75	Rural
Morton	129	3,496	730	4.79	Frontier
Nemaha	131	10,717	719.1	14.90	Rural
Neosho	133	16,997	571.9	29.72	Densely-Settled Rural
Ness	135	3,454	1074.8	3.21	Frontier
Norton	137	5,953	877.9	6.78	Rural
Osage	139	16,712	703.6	23.75	Densely-Settled Rural
Osborne	141	4,452	892.6	4.99	Frontier
Ottawa	143	6,163	721.2	8.55	Rural
Pawnee	145	7,233	754.2	9.59	Rural
Phillips	147	6,001	886.3	6.77	Rural
Pottawatomie	149	18,209	844.3	21.57	Densely-Settled Rural
Pratt	151	9,647	735	13.13	Rural
Rawlins	153	2,966	1069.7	2.77	Frontier
Reno	155	64,790	1254.5	51.65	Semi-Urban
Republic	157	5,835	716.5	8.14	Rural
Rice	159	10,761	726.6	14.81	Rural
Riley	161	62,843	609.6	103.09	Semi-Urban
Rooks	163	5,685	888.4	6.40	Rural
Rush	165	3,551	718.2	4.94	Frontier
Russell	167	7,370	884.7	8.33	Rural
Saline	169	53,597	719.6	74.48	Semi-Urban
Scott	171	5,120	717.6	7.13	Rural
Sedgwick	173	452,869	1000.2	452.78	Urban
Seward	175	22,510	639.6	35.19	Densely-Settled Rural
Shawnee	177	169,871	549.9	308.91	Urban
Sheridan	179	2,813	896.4	3.14	Frontier
Sherman	181	6,760	1055.9	6.40	Rural
Smith	183	4,536	895.5	5.07	Frontier
Stafford	185	4,789	792.1	6.05	Rural
Stanton	187	2,406	680.1	3.54	Frontier
Stevens	189	5,463	727.6	7.51	Rural
Sumner	191	25,946	1181.9	21.95	Densely-Settled Rural
Thomas	193	8,180	1074.9	7.61	Rural
Trego	195	3,319	888.4	3.74	Frontier
Wabaunsee	197	6,885	797.5	8.63	Rural
Wallace	199	1,749	914.1	1.91	Frontier
Washington	201	6,483	898.5	7.22	Rural
Wichita	203	2,531	718.6	3.52	Frontier
Wilson	205	10,332	573.9	18.00	Rural
Woodson	207	3,788	500.7	7.57	Rural
Wyandotte	209	157,882	151.4	1042.81	Urban

Split Questionnaire
To accommodate increasing data needs, the Kansas BRFSS may use a split questionnaire. CDC optional modules and state added questions are organized by topics into two sections: questionnaire A and questionnaire B. Each telephone number is randomly assigned to questionnaire A and questionnaire B prior to being called. All 8,000 respondents answer questions from the core section. Then, approximately half of the respondents will receive questionnaire A and the remaining will receive questionnaire B, (i.e. approximately 4,000 respondents for each questionnaire).

Advantages of a split questionnaire:

• Collect data on numerous topics within one data year
• Collect in-depth data on one specific topic
• Ability to keep questionnaire time and length to a minimum

Disadvantages of a split questionnaire:

• Complexity of data weighting; additional weighting factors are needed
• Variables on questionnaire A cannot be analyzed with variables on questionnaire B

Analyss of split questionnaire:
The sample size for each split of the questionnaire is approximately half of the total sample size. As mentioned above, each respondent is randomly assigned to questionnaire A or to questionnaire B. The questions regarding certain conditions are included in the core section (e.g., asthma, disability, high blood pressures, etc.). State added questions and optional modules for these conditions are included on questionnaire A or questionnaire B. Therefore, these additional questions ona specific health condition are asked from respondents who are assigned to that particular split questionnaire. This resulted in approximately half of the respondents who were identified with a particular condition from the core section responding to additional questions on the specific condition. Also, the number of adults with the specific health condition may vary on each question due to respondents terminating at various points in the survey.

A split questionnaire was used for the following surveys: 2004 2005 2006 2007

Types of Questions on the BRFSS
The BRFSS questionnaire is designed by the Centers for Disease Control and Prevention, state BRFSS Coordinators, and each individual state’s survey selection committee. The questionnaire has three components: core questions, optional modules, and state added questions.

• Core questions are asked by all states and include approximately 72 questions (though this may vary somewhat from year to year). The order the questions appear and the wording of the question is exactly the same in all states. Types of core questions include fixed, rotating, and emerging health issues.
  o Fixed core: contains questions that are asked every year. Fixed core topics include health status, health care access, healthy days, life satisfaction emotional satisfaction, disability, tobacco use, alcohol use, exercise, immunization, HIV/AIDS, diabetes, asthma, and cardiovascular disease. Total number of fixed core questions is 52.
  o Rotating core: contains questions asked every other year.
  • Odd years (2005, 2007, 2009, etc): fruits and vegetables, hypertension awareness, cholesterol awareness, arthritis burden, and physical activity. Total number of rotating core questions for odd years is 72.
  
  
  • Even years (2006, 2008, 2010, etc): women's health, prostate screening, colorectal cancer screening, oral health and injury. Total number of rotating core questions for even years is 74 for female respondents, and 72 for male respondents.
  o Emerging Health Issues: contains late breaking health issue questions. At the end of the survey year, these questions are evaluated to determine if they should be a part of the fixed core. Total number of questions for emerging health issues is four.
  
  
• Optional Modules include questions on a specific health topic. The CDC provides a pool of questions from which states may select. States have the option of adding these questions to their survey. The CDC's responsibilities regarding these questions include development of questions, cognitive testing, financial support to states to include these questions on their questionnaire, data management, limited analysis and quality control.



• State added questions are based on public health needs of each state. State added questions include questions not available as supported optional modules in that year or emerging health issues that are specific to each state. Any modifications made to the CDC support modules available in that year make the module a state added module. The CDC has no responsibilities regarding these questions.