**[200]{#OLE_LINK6}1 Behavioral Risk Factor Surveillance System (BRFSS)
Metropolitan Area Data Weighting Methodology**

**Creation of Metropolitan-Level Weights**

This description of the Behavioral Risk Factor Surveillance System
(BRFSS) 2001 metropolitan area data is based on a report produced for
CDC by RTI International.

A documented and verified subset of the 2001 BRFSS has been produced to
provide some local area estimates. These local areas are identified as
metropolitan statistical areas (MSAs), primary metropolitan statistical
areas (PMSAs), or New England county metropolitan statistical areas
(NECMAs), as defined by the U.S. Office of Management and Budget and
used by the U.S. Census Bureau. In this report, all mentions of
metropolitan area refer to MSAs, PMSAs, and NECMAs. Additional
information on MSA, PMSA, and NECMA designations used by the U.S. Census
Bureau is available at and

. The metropolitan area definitions used for this analysis were those
used by the Census Bureau in 2001, not those used currently.

The BRFSS 2001 metropolitan area data set was produced by adding new
analysis weights designed to correspond to the 2001 population estimates
for each eligible metropolitan area. The additional weights were
post-stratified to the metropolitan area 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 this project, 2001 BRFSS data were used to produce
prevalence estimates for metropolitan areas. Estimates have been
produced for 69 metropolitan areas that have met the analysis criteria
for the 2001 data year. Missing county codes were imputed from a value
included in the purchased telephone sample that represents the county
most likely to be associated with the telephone number.

**Appendix A: Variables Added to 2001 Data**

ANLPMSA---Indicates whether a respondent lived in a metropolitan area
that was included in the re-weighting.

0---Not in a metropolitan area that was re-weighted

1---In a metropolitan area that was re-weighted

\_PMSA---Metropolitan area code of the MSA, PMSA, or NECMA, if
appropriate, in which the respondent lived.

\_PMSANAM---Metropolitan area name of the MSA, PMSA, or NECMA, if
appropriate, in which the respondent lived.

\_PMSAWT---The new metropolitan area-level weight, which should be used
when generating metropolitan area-level estimates for questions that
were asked of the entire sample.

\_PMSWTSS---The new metropolitan area-level weight for the split-sample
questions, which should be used when generating metropolitan area-level
estimates for the split-sample questions. This variable is missing for
respondents who did not live in the Chicago, IL, PMSA.

PMSAFLAG---Indicates whether the metropolitan area in which the
respondent lived was associated with additional weight class collapsing
problems beyond those addressed by the collapsing rules.

1 = Metropolitan area that was post-stratified by sex and age only and
had at least one weighting class group that failed the 80% rule (see
Appendix C for an explanation of the weight class collapsing rules).
After adjacent age categories were collapsed when necessary, weighting
classes with fewer than 19 cases remained.

2 = Metropolitan area that was post-stratified by sex and age only and
had at least one weighting class group that failed the 80% rule. After
adjacent age categories were collapsed when necessary, all weighting
classes had at least 19 cases.

3 = Metropolitan area that was post-stratified by sex and age only and
had no weighting class group that failed the 80% rule. After adjacent
age categories were collapsed when necessary, weighting classes with
fewer than 19 cases remained.

4 = Metropolitan area that was post-stratified by race, sex, and age and
had at least one weighting class group that failed the 80% rule. The
group(s) that were collapsed across race needed additional collapsing
across age categories. After adjacent age categories were collapsed when
necessary, weighting classes with fewer than 19 cases remained.

5 = Metropolitan area that was post-stratified by race, sex, and age and
had at least one weighting class group that failed the 80% rule. The
group(s) that were collapsed across race also needed additional
collapsing across age categories. After adjacent age categories were
collapsed when necessary, all weighting classes had at least 19 cases.

6 = Metropolitan area that was post-stratified by race, sex, and age and
had at least one weighting class group that failed the 80% rule. The
group(s) that were collapsed across race needed no additional collapsing
across age categories, but other groups that were not collapsed across
race did need additional collapsing across age categories. After
adjacent age categories were collapsed when necessary, weighting classes
with fewer than 19 cases remained.

7 = Metropolitan area that was post-stratified by race, sex, and age and
had no weighting class group that failed the 80% rule. After adjacent
age categories were collapsed when necessary, weighting classes with
fewer than 19 cases remained.

**Appendix B: The 69 Areas with Metropolitan Area-Level Weights in the
2001 BRFSS, with MSA, PMSA, or NECMA Codes and Names**

  ------ ---------------------------------------------------------------
  0200   Albuquerque, NM MSA
  0520   Atlanta, GA MSA
  0720   Baltimore, MD PMSA
  0760   Baton Rouge, LA MSA
  0875   Bergen-Passaic, NJ PMSA
  1000   Birmingham, AL MSA
  1080   Boise City, ID MSA
  1123   Boston--Worcester--Lawrence--Lowell--Brockton, MA--NH NECMA
  1303   Burlington, VT NECMA
  1520   Charlotte--Gastonia--Rock Hill, NC--SC MSA
  1600   Chicago, IL PMSA
  1640   Cincinnati, OH--KY--IN PMSA
  1680   Cleveland--Lorain--Elyria, OH PMSA
  1840   Columbus, OH MSA
  1920   Dallas, TX PMSA
  2080   Denver, CO PMSA
  2120   Des Moines, IA MSA
  2160   Detroit, MI PMSA
  2190   Dover, DE MSA
  2520   Fargo--Moorhead, ND--MN MSA
  3120   Greensboro--Winston-Salem--High Point, NC MSA
  3160   Greenville--Spartanburg--Anderson, SC MSA
  3283   Hartford, CT NECMA
  3320   Honolulu, HI MSA
  3360   Houston, TX PMSA
  3400   Huntington--Ashland, WV--KY--OH MSA
  3480   Indianapolis, IN MSA
  3640   Jersey City, NJ PMSA
  3760   Kansas City, MO--KS MSA
  4120   Las Vegas, NV--AZ MSA
  4360   Lincoln, NE MSA
  4400   Little Rock--North Little Rock, AR MSA
  4480   Los Angeles--Long Beach, CA PMSA
  4520   Louisville, KY--IN MSA
  4920   Memphis, TN--AR--MS MSA
  5000   Miami, FL PMSA
  5015   Middlesex--Somerset--Hunterdon, NJ PMSA
  5080   Milwaukee--Waukesha, WI PMSA
  5120   Minneapolis--St Paul, MN--WI MSA
  5190   Monmouth--Ocean, NJ PMSA
  5360   Nashville, TN MSA
  5380   Nassau--Suffolk, NY PMSA
  5483   New Haven--Bridgeport--Stamford--Waterbury--Danbury, CT NECMA
  5523   New London--Norwich, CT NECMA
  5560   New Orleans, LA MSA
  5600   New York, NY PMSA
  5640   Newark, NJ PMSA
  5720   Norfolk--Virginia Beach--Newport News, VA--NC MSA
  5880   Oklahoma City, OK MSA
  5920   Omaha, NE--IA MSA
  6160   Philadelphia, PA--NJ PMSA
  6200   Phoenix--Mesa, AZ MSA
  6280   Pittsburgh, PA MSA
  6440   Portland--Vancouver, OR--WA PMSA
  6483   Providence--Warwick--Pawtucket, RI NECMA
  6640   Raleigh--Durham--Chapel Hill, NC MSA
  6660   Rapid City, SD MSA
  6720   Reno, NV MSA
  7040   St Louis, MO--IL MSA
  7160   Salt Lake City--Ogden, UT MSA
  7600   Seattle--Bellevue--Everett, WA PMSA
  7760   Sioux Falls, SD MSA
  8003   Springfield, MA NECMA
  8280   Tampa--St Petersburg--Clearwater, FL MSA
  8520   Tucson, AZ MSA
  8560   Tulsa, OK MSA
  8840   Washington, DC--MD--VA--WV PMSA
  9040   Wichita, KS MSA
  9160   Wilmington--Newark, DE--MD PMSA
         
  ------ ---------------------------------------------------------------

**Appendix C: Weight Class Collapsing Rules**

**Metropolitan Area-Level Weighting Methodology**

Respondents were assigned to a metropolitan area on the basis of the
county name that they provided during the interview. The county was then
recorded using the Federal Information Processing Standards (FIPS)
county code used by the U.S. Census Bureau. Respondents with unknown or
missing values for the county code were excluded.

All respondents in metropolitan areas were then assigned to age, race,
and sex categories. If a respondent's age was missing, it was imputed
using the variable \_IMPAGE available in the BRFSS public-use 2001 data
file. If a respondent's race was missing, it was imputed using the
majority race for the metropolitan area in which the respondent lived.

Within each metropolitan area, respondents were assigned to weighting
classes on the basis of age (18-24, 25-34, 35-44, 45-54, 55-64, or 65+),
race (white and non-Hispanic, or nonwhite or Hispanic), and sex (male or
female) categories. Some states did not use race in post-stratification;
for the metropolitan areas in these states, only age and sex groups were
used to establish weighting classes. For all other metropolitan areas,
all three groups were used to establish weighting classes. For
metropolitan areas that crossed state lines, the post-stratification
variables used by the state in which the majority of the metropolitan
area's population lived were used to set up weighting classes. Thus,
metropolitan areas that post-stratified by race had 24 initial weighting
classes and metropolitan areas that did not post-stratify by race had 12
initial weighting classes.

Weighting classes with fewer than 19 sample members were collapsed
according to the following rules:

1.  For metropolitan areas that used race in post-stratification, the
    race categories within a sex category were collapsed if at least 80%
    of the age categories (i.e., at least five age categories) in the
    race and sex cross-classification had fewer than 19 members. In
    metropolitan areas 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.  The two youngest age categories in any age-sex or age-sex-race
    weighting class were collapsed if either contained fewer than 19
    members. The two middle and two oldest age categories in each
    remaining weighting class were also collapsed if either had fewer
    than 19 members.

3.  Weighting classes were not collapsed across sex.

4.  Metropolitan area was not included in the re-weighting if weighting
    classes with fewer than 19 sample members remained after all
    collapsing rules had been applied.

In 69 metropolitan areas, at least 500 respondents participated in the
2001 BRFSS and at least 19 sample members remained in all final
weighting classes. A list of these metropolitan areas is available in
Appendix B. The respondents in these metropolitan areas were the only
ones assigned a metropolitan area-level weight. To calculate the new
metropolitan area-level weight, we applied a post-stratification
adjustment factor to the design weight (\_WT2) and created the
adjustment factor based on the ratio of the total population to the sum
of the design weights for each weighting class within each metropolitan
area. The new metropolitan area-level weight (\_PMSAWT) should be used
to generate estimates in these 69 metropolitan areas.

[Example---SUDAAN Code]{.underline}

For example, suppose we want a prevalence estimate for the Atlanta, GA
metropolitan area (PMSA code = 0520). The SAS/SUDAAN code that could be
used to generate this estimate is:

proc sort data=xxxx;

by \_STSTR \_PSU;

run;

proc descript data=xxxx filetype=sas design=wr;

nest \_STSTR \_PSU / missunit;

weight \_PMSAWT;

subpopn \_PMSA=0520 / name=" Atlanta, GA";

var (your analysis variable);

catlevel (the level of your analysis variable for which you want an
estimate);

run;

**Metropolitan Area-Level Split-Sample Weighting Methodology**

In 2001, the state of Illinois used a split sample; the state's sample
was divided in half and a different version of the questionnaire was
administered to each half. The \_PMSAWT is appropriate for analyzing the
responses to questions asked on both versions of the Illinois
questionnaire. An additional weight was created to use with questions
that were asked on only one version of their questionnaire. The
metropolitan area-level split-sample weight (\_PMSWTSS) was created
using the methodology described above, except that respondents in the
Illinois metropolitan areas were separated according to the
questionnaire version they received. Weighting classes were created for
each questionnaire version within each metropolitan area. Adjustment
factors were applied to the design weight (\_WT2) that forced the sum of
the weights for each half of the sample to sum to population totals. The
Chicago, IL metropolitan area was the only metropolitan area with
adequate split-sample sizes to provide metropolitan area-level
split-sample weights.

[Example---SUDAAN Code:]{.underline}

For example, suppose we want a prevalence estimate for a split-sample
question from questionnaire version 1 (\_QSTVER) for the Chicago, IL
metropolitan area (PMSA code = 1600). The SAS/SUDAAN code that could be
used to generate this estimate is:

Data xxxx;

Set yyyy;

If (\_PMSA=1600 & \_QSTVER=1) then DUMMY = 1;

Run;

proc sort data=xxxx;

by \_STSTR \_PSU;

run;

proc descript data=xxxx filetype=sas design=wr;

nest \_STSTR \_PSU / missunit;

weight \_PMSWTSS;

subpopn DUMMY=1 / name=" Chicago, IL -- questionnaire version 1";

var (your analysis variable);

catlevel (the level of your analysis variable for which you want an
estimate);

run;

**Note: In general, estimates for split-sample questions can only be
generated for metropolitan areas that do not cross state lines. For
example, the St. Louis, MO-IL metropolitan area lies in both Illinois
and Missouri. These new metropolitan area-level weights cannot be used
to generate a prevalence estimate for a question that was asked of only
half of the Illinois residents but all of the Missouri residents in the
sample. For metropolitan areas that cross state boundaries, estimates
can only be generated for questions asked of the entire sample
population in each state. **