2005 SMART BRFSS County Methodology

2005 Selected Metropolitan/Micropolitan Area Risk Trends from the BRFSS 
Creation of Metropolitan-level weights

The Behavioral Risk Factor Surveillance System (BRFSS) Selected Metropolitan/Micropolitan Area Risk Trends (SMART) is a documented and verified subset of the 2005 BRFSS, which has been produced to provide some local area estimates.  These local areas are identified counties within metropolitan or micropolitan statistical areas (MMSA) as defined by the Office of Management and Budget.  The data set was produced by adding new analysis weights designed to correspond to the 2005 population estimates for each eligible county within a selected MMSA.  The additional weights were post-stratified to the county-level. The process by which these new weights were obtained is detailed in Appendix C, “Weight Class Collapsing Rules.”

Selected Areas 

Typically, BRFSS data are used to produce state-level estimates.  However, for the SMART project, BRFSS data were used to produce small area-level estimates for MMSAs as defined by the Bureau of the Census.  On June 6, 2003, the Office of Management and Budget (OMB) issued new definitions for metropolitan statistical areas, micropolitan statistical areas, and metropolitan divisions.  OMB periodically updates the list of MMSAs.  The list of areas used for this analysis can be found at http://www.whitehouse.gov/omb/bulletins/fy05/b05-02_appendix.pdf.  For more information about MMSAs, please visit http://www.census.gov/population/www/estimates/metroarea.html.  A respondent was associated with a particular MMSA on the basis of their county code.  Missing county codes were imputed from a value included in the purchased telephone sample that represents the county most likely associated with the telephone number.  There were 153 MMSAs that met the analysis criteria for the 2005 data year.  From within the 153 MMSAs, county-level estimates have been produced from the BRFSS data for 232 counties that have met the weighting criteria (Appendix C) for the 2005 data year.

Appendix A: List of Variables added to the 2005 Data

Data Documentation for the 13 Variables Added to the 2005 BRFSS Data

ADJCNTY	County-level post-stratification weight.  This factor is multiplied by the design weight (_WT2) to get the final County-level weight (_CNTYWT).  

AGE_CNTY 	Age categories used to set up the initial weighting classes for the county-level weights.  
	1 – 18–24 
	2 – 25–34 
	3 – 35–44 
	4 – 45–54 
	5 – 55–64 
	6 – 65+    

AGE_C_F	Age categories used in the final weighting classes for the county-level weights. 
	1 – 18–24 
	2 – 25–34 
	3 – 35–44 
	4 – 45–54 
	5 – 55–64 
	6 – 65+    
	7 – 18–34 
	8 – 35–54 
	9 – 55+    
	10 – 18–44
	11 – 45+
	12 – 18–54
	14 – 45–64
	19 – 35+

RACE_CNT	Race categories used to set up the initial weighting classes for the county-level weights.  
	0 – Race not used 
	1 – White, non-Hispanic 
	2 – Nonwhite or Hispanic 

RACE_C_F	Race categories used in the final weighting classes for the county-level weights.  
	0 – Race not used 
	1 – White, non-Hispanic 
	2 – Nonwhite or Hispanic 

SEX_CNTY	Sex categories used to set up the initial and final weighting classes for the county-level weights (weight classes are never collapsed across sex).  
	1 – Male 
	2 – Female 

_CNTY – FIPS 	County code of the county where the respondent lives. This variable is equivalent to CTYCODE, except for respondents with a CTYCODE of “777” or “999”.  The county code for these respondents was imputed based on information provided by BSB.  

_CNTYNAM	County name of the county where the respondent lives.  

_CNTYWT	The new county-level weight.  This is the weight to use when generating county-level estimates for questions that were asked of the whole sample. 

Appendix B: List of the 232 counties that have COUNTY-level Weights in 2005 BRFSS Data

Metropolitan/Micropolitan Statistical Area or Metropolitan Division Codes and Names

State Name	FIPS State	FIPS County	County Name	
Alabama	1	73	Jefferson County	
Alaska	2	20	Anchorage Municipality	
Alaska	2	90	Fairbanks North Star Borough	
Arizona	4	13	Maricopa County	
Arizona	4	19	Pima County	
Arizona	4	21	Pinal County	
Arizona	4	27	Yuma County	
Arkansas	5	7	Benton County	
Arkansas	5	119	Pulaski County	
Arkansas	5	143	Washington County	
California	6	1	Alameda County	
California	6	37	Los Angeles County	
California	6	59	Orange County	
California	6	65	Riverside County	
California	6	71	San Bernardino County	
California	6	73	San Diego County	
Colorado	8	1	Adams County	
Colorado	8	5	Arapahoe County	
Colorado	8	31	Denver County	
Colorado	8	35	Douglas County	
Colorado	8	41	El Paso County	
Colorado	8	59	Jefferson County	
Connecticut	9	1	Fairfield County	
Connecticut	9	3	Hartford County	
Connecticut	9	9	New Haven County	
Delaware	10	1	Kent County	
Delaware	10	3	New Castle County	
Delaware	10	5	Sussex County	
District of Columbia	11	1	District of Columbia	
Florida	12	11	Broward County	
Florida	12	57	Hillsborough County	
Florida	12	86	Miami-Dade County	
Florida	12	95	Orange County	
Florida	12	99	Palm Beach County	
Florida	12	103	Pinellas County	
Hawaii	15	1	Hawaii County	
Hawaii	15	3	Honolulu County	
Hawaii	15	7	Kauai County	
Hawaii	15	9	Maui County	
Idaho	16	1	Ada County	
Idaho	16	19	Bonneville County	
Idaho	16	27	Canyon County	
Idaho	16	55	Kootenai County	
Idaho	16	69	Nez Perce County	
Illinois	17	31	Cook County	
Illinois	17	43	DuPage County	
Illinois	17	97	Lake County	
Indiana	18	89	Lake County	
Indiana	18	97	Marion County	
Iowa	19	153	Polk County	
Kansas	20	91	Johnson County	
Kansas	20	173	Sedgwick County	
Kansas	20	177	Shawnee County	
Kansas	20	209	Wyandotte County	
Kentucky	21	111	Jefferson County	
Louisiana	22	71	Orleans Parish	
Maine	23	5	Cumberland County	
Maine	23	31	York County	
Maryland	24	3	Anne Arundel County	
Maryland	24	5	Baltimore County	
Maryland	24	15	Cecil County	
Maryland	24	17	Charles County	
Maryland	24	21	Frederick County	
Maryland	24	25	Harford County	
Maryland	24	27	Howard County	
Maryland	24	31	Montgomery County	
Maryland	24	33	Prince George's County	
Maryland	24	43	Washington County	
Maryland	24	510	Baltimore city	
Massachusetts	25	5	Bristol County	
Massachusetts	25	9	Essex County	
Massachusetts	25	13	Hampden County	
Massachusetts	25	17	Middlesex County	
Massachusetts	25	21	Norfolk County	
Massachusetts	25	23	Plymouth County	
Massachusetts	25	25	Suffolk County	
Massachusetts	25	27	Worcester County	
Michigan	26	49	Genesee County	
Michigan	26	65	Ingham County	
Michigan	26	81	Kent County	
Michigan	26	99	Macomb County	
Michigan	26	125	Oakland County	
Michigan	26	163	Wayne County	
Minnesota	27	53	Hennepin County	
Minnesota	27	123	Ramsey County	
Mississippi	28	49	Hinds County	
Missouri	29	95	Jackson County	
Missouri	29	189	St. Louis County	
Missouri	29	510	St. Louis city	
Montana	30	111	Yellowstone County	
Nebraska	31	55	Douglas County	
Nebraska	31	109	Lancaster County	
Nebraska	31	153	Sarpy County	
Nebraska	31	157	Scotts Bluff County	
Nevada	32	3	Clark County	
Nevada	32	31	Washoe County	
New Hampshire	33	5	Cheshire County	
New Hampshire	33	9	Grafton County	
New Hampshire	33	11	Hillsborough County	
New Hampshire	33	13	Merrimack County	
New Hampshire	33	15	Rockingham County	
New Hampshire	33	17	Strafford County	
New Jersey	34	1	Atlantic County	
New Jersey	34	3	Bergen County	
New Jersey	34	5	Burlington County	
New Jersey	34	7	Camden County	
New Jersey	34	9	Cape May County	
New Jersey	34	13	Essex County	
New Jersey	34	15	Gloucester County	
New Jersey	34	17	Hudson County	
New Jersey	34	19	Hunterdon County	
New Jersey	34	21	Mercer County	
New Jersey	34	23	Middlesex County	
New Jersey	34	25	Monmouth County	
New Jersey	34	27	Morris County	
New Jersey	34	29	Ocean County	
New Jersey	34	31	Passaic County	
New Jersey	34	35	Somerset County	
New Jersey	34	37	Sussex County	
New Jersey	34	39	Union County	
New Jersey	34	41	Warren County	
New Mexico	35	1	Bernalillo County	
New Mexico	35	13	Dona Ana County	
New Mexico	35	43	Sandoval County	
New Mexico	35	49	Santa Fe County	
New York	36	5	Bronx County	
New York	36	29	Erie County	
New York	36	47	Kings County	
New York	36	55	Monroe County	
New York	36	59	Nassau County	
New York	36	61	New York County	
New York	36	81	Queens County	
New York	36	103	Suffolk County	
New York	36	119	Westchester County	
North Carolina	37	21	Buncombe County	
North Carolina	37	25	Cabarrus County	
North Carolina	37	35	Catawba County	
North Carolina	37	51	Cumberland County	
North Carolina	37	63	Durham County	
North Carolina	37	67	Forsyth County	
North Carolina	37	71	Gaston County	
North Carolina	37	81	Guilford County	
North Carolina	37	101	Johnston County	
North Carolina	37	119	Mecklenburg County	
North Carolina	37	129	New Hanover County	
North Carolina	37	135	Orange County	
North Carolina	37	151	Randolph County	
North Carolina	37	179	Union County	
North Carolina	37	183	Wake County	
North Dakota	38	15	Burleigh County	
North Dakota	38	17	Cass County	
Ohio	39	35	Cuyahoga County	
Ohio	39	49	Franklin County	
Ohio	39	61	Hamilton County	
Oklahoma	40	19	Carter County	
Oklahoma	40	21	Cherokee County	
Oklahoma	40	27	Cleveland County	
Oklahoma	40	31	Comanche County	
Oklahoma	40	47	Garfield County	
Oklahoma	40	109	Oklahoma County	
Oklahoma	40	115	Ottawa County	
Oklahoma	40	121	Pittsburg County	
Oklahoma	40	125	Pottawatomie County	
Oklahoma	40	131	Rogers County	
Oklahoma	40	135	Sequoyah County	
Oklahoma	40	143	Tulsa County	
Oklahoma	40	145	Wagoner County	
Oklahoma	40	147	Washington County	
Oregon	41	5	Clackamas County	
Oregon	41	29	Jackson County	
Oregon	41	39	Lane County	
Oregon	41	47	Marion County	
Oregon	41	51	Multnomah County	
Oregon	41	67	Washington County	
Oregon	41	71	Yamhill County	
Pennsylvania	42	3	Allegheny County	
Pennsylvania	42	17	Bucks County	
Pennsylvania	42	45	Delaware County	
Pennsylvania	42	51	Fayette County	
Pennsylvania	42	79	Luzerne County	
Pennsylvania	42	91	Montgomery County	
Pennsylvania	42	101	Philadelphia County	
Pennsylvania	42	129	Westmoreland County	
Rhode Island	44	3	Kent County	
Rhode Island	44	5	Newport County	
Rhode Island	44	7	Providence County	
Rhode Island	44	9	Washington County	
South Carolina	45	3	Aiken County	
South Carolina	45	15	Berkeley County	
South Carolina	45	19	Charleston County	
South Carolina	45	45	Greenville County	
South Carolina	45	63	Lexington County	
South Carolina	45	79	Richland County	
South Carolina	45	83	Spartanburg County	
South Carolina	45	91	York County	
South Dakota	46	99	Minnehaha County	
South Dakota	46	103	Pennington County	
Tennessee	47	37	Davidson County	
Tennessee	47	157	Shelby County	
Texas	48	29	Bexar County	
Texas	48	113	Dallas County	
Texas	48	141	El Paso County	
Texas	48	201	Harris County	
Texas	48	439	Tarrant County	
Texas	48	453	Travis County	
Utah	49	11	Davis County	
Utah	49	35	Salt Lake County	
Utah	49	45	Tooele County	
Utah	49	49	Utah County	
Utah	49	57	Weber County	
Vermont	50	7	Chittenden County	
Vermont	50	11	Franklin County	
Vermont	50	17	Orange County	
Vermont	50	21	Rutland County	
Vermont	50	23	Washington County	
Vermont	50	27	Windsor County	
Washington	53	5	Benton County	
Washington	53	7	Chelan County	
Washington	53	11	Clark County	
Washington	53	17	Douglas County	
Washington	53	21	Franklin County	
Washington	53	33	King County	
Washington	53	35	Kitsap County	
Washington	53	53	Pierce County	
Washington	53	61	Snohomish County	
Washington	53	63	Spokane County	
Washington	53	67	Thurston County	
Washington	53	77	Yakima County	
West Virginia	54	39	Kanawha County	
Wisconsin	55	79	Milwaukee County	
Wyoming	56	21	Laramie County	
Wyoming	56	25	Natrona County	

Appendix C:  Weight Class Collapsing Rules

County-level Weighting Methodology

Respondents were assigned to a county on the basis of their FIPS county codes.  Missing county codes were imputed from a value included in the purchased telephone sample that represents the county most likely associated with the telephone number before the respondent identifies a county during data collection.

All respondents in counties were then assigned to age, race, and sex categories.  If a respondent’s age was missing, it was imputed by using the variable _IMPAGE available in the BRFSS public-use 2005 data file.  If a respondent’s race was missing, it was imputed by using the majority race for the county in which the respondent lives.  The six age categories were 18-24, 25-34, 35-44, 45-54, 55-64, and 65+.  The two race categories were white, non-Hispanic, and nonwhite or Hispanic.

Within each county, respondents were assigned to weighting classes on the basis of the age, race, and sex categories described above.  Some states do not use race in post-stratification.  For the county in states that do not use race, only the age and sex groups were used to set up weighting classes.  For the county in states that do use race, all three groups were used to set up weighting classes.  Thus, the counties that use race had 24 initial weighting classes and counties that do not use race had 12 initial weighting classes.  

Weighting classes with fewer than 19 sample members were collapsed in accordance with the following rules:

1.	For those counties that used race in post-stratification, the race categories within a sex category collapse if at least 80% of the age categories in that race /sex cross-classification (i.e. 5 of 6 the age categories) have fewer than 19 members. In counties that used race to create the initial weighting classes, the number of weighting classes was thus reduced from 24 to 12 if race was collapsed for both sexes and from 24 to 18 if race was collapsed for only one sex.

2.	Collapse the two youngest age categories in any age/sex or age/sex/race weighing class if either contains fewer than 19 members.  Do the same for the two middle and the two oldest age categories in each remaining weighting class. 

3.	If either of the age/sex or age/sex/race categories have fewer than 19 members, then the age categories were collapsed until there were 19 members in some combination of the age categories listed in the variable AGE_C_F.

4.	Do not collapse weighting classes across sex.

5.	Do not include a county in the reweighting that still has weighting classes with fewer than 19 sample members after all collapsing rules have been applied. These counties will be excluded from the 2005 SMART BRFSS.  

There were 154 MMSAs that had at least 500 respondents in the 2005 BRFSS and at least 19 sample members in all final weighting classes.  There are 232 counties within the 154 MMSAs that had at least 19 sample members in all final weighting classes. (See Appendix B in the Data Documentation for a list of these counties.)  Only the respondents in these counties were given a county-level weight.  To calculate the new county-level weight, we applied a post-stratification adjustment factor to the design weight (_WT2) and created the adjustment factor by taking the ratio of the total population over the sum of the design weights for each weighting class within each county.  The new county-level weight (_CNTYWT) should be used to generate estimates in these 232 counties.

Example SUDAAN Code:
For example, to estimate for DeKalb County, GA (_STATE=13, _CNTY=89).  The following SAS/SUDAAN code that could be used to do this:

data xxxx;
set yyyy;

if (_STATE=13 & _CNTY=89) then DUMMY=1;
run;

proc sort data=xxxx;
by _STSTR SEQNO;
run;

proc descript data=xxxx filetype=sas design=wr;
nest _STSTR SEQNO / missunit;
weight _CNTYWT;
subpopn DUMMY=1 / name=”DeKalb County, GA”;
var (your analysis variable);
catlevel (the level of your analysis variable for which you want an estimate);
run;