Connecticut Adult BRFSS
VitalWeb Ajax
Online Help

Introduction

Quick Guide to Using VitalWeb Ajax

Multiple Windows
Basic Table Layout

Main Statistic

Table Axes (Rows and Columns)

Statistic / Axis Conflicts
Data Variables

Overall Question

Categorical Variables

Range Variables

Statistic / Variable Conflicts

Other Settings
Chart Settings

Bar Chart Coloring

Bar Chart Layout

Line Chart Settings #1

Line Chart Settings #2

Pie Chart Coloring

Pie Chart Layout

Tabular Charts / Chart Links
Map Settings

Map Coloring

Map Layout

Map Color Palettes
Producing and Using Results

Getting Results

Viewing Results

Printing Results

Saving Results

When Charts and Maps are Made
Other Information

Glossary

County Groupings

95% Poisson Confidence Limits

Age Adjustment Standards

Statistical Methods

Confidence Intervals

BRFSS Questions

Data Sources and Limitations

Links to Related Resources

Whom to Contact

Legal Information

Quick Guide to Using VitalWeb Ajax

First, select settings from within the Main Window:

• Main Statistic, for example "Interviews (Unweighted)"
• Rows and columns, for example year rows
• Values for data variables, for example race
• Overall Question, for example binge drinking

Next, whenever you are ready:

• Click on "Make Table Now" or "Make Map" to submit your query.
• Results will appear in a separate "Results Window".
• Browse through your results.
• Print your results (if desired).
• Save your results (if desired).

After you have made output:

• Go back to the the Main Window.
• Modify settings as desired.
• Make another map or table.

Multiple Windows

VitalWeb Ajax uses multiple browser windows.

• It does not require full-screen windows.
• You can easily switch between browser windows.
• To switch to another window, simply click on it.
• When you exit the Main Window, the other windows go away.

Main Window ("command center") has the majority of settings and action buttons.

Map Settings Window customizes all map settings.

Other Settings Window:

• Click on "Other Settings" in upper right of Main Window.
• A separate "Other Settings Window" pops up.
• Casual users can mostly ignore the other options.
• Advanced users will appreciate the extra power. Help Window is what you are currently viewing.

Results Window displays any output maps or tables.

• Normally, each new result is appended to the Results Window.
• Review previous results by clicking on browser "Back" button. Chart Setting Windows modify bar, line, and pie chart settings.

Overall Question

Overall Question - Based on one or more BRFSS variables.

Main Statistic

Table Axes (Rows and Columns)

Year	0-19	20-39	40-59	60+
1990	1,032	302	545	79
1991	1,134	317	555	88
1992	1,236	348	602	86

Example Table: Year Rows - Age Columns

• Rows - Horizontal lines of data, such as the row for 1991.
• Row Sort - Rows can be sorted, low to high, or high to low.
• Columns - Go up and down, such as the column for age 0-19.
• By Variable - Also called "Multi-Tables". Makes a series of tables.

Example Row Variable Selector:

Selecting - Click on desired setting, such as "Age" or "Race".

Statistic / Axis Conflicts

If there is a conflict between statistic, rows, or columns:

• Vitalnet alerts you of the conflict (mismatch).
• Vitalnet does not allow a table until the conflict is corrected.

Examples of conflicting settings (mismatches) include:

• Age-adjusted rates, age rows.
• Race rows, race columns.
• Year rows, year columns.

To correct a conflict, select a different Main Statistic, Row Variable, or Column Variable.

Selecting Data Variables

Data variables include - Age, Body Mass Index, Education Level, Emotional Support, Height, Income Level, Year.

Example selector for range variable, such as age or year:

Sample range variable selector

Range variable selector lets you easily:

• Shrink or extend ranges
• Delete highlighted ranges
• Split highlighted ranges
• Apply a standard grouping

Example selector for categorical variable, such as race or sex:

Sample range variable selector

Categorical variable selector lets you easily:

• Add a category as a set
• Merge sets into new set
• Split set into separate sets
• Delete a set

Statistic / Variable Conflicts

Sometimes, a conflict exists between a variable and a population-based rate. Vitalnet automatically prevents this from producing misleading output.

This is best shown with an example: Suppose there are 408,000 births, and the population is 12,000,000 females. Thus, the birth rate is 34 births per 1,000 females (408,000 / 12,000,000).

Now, suppose we try limiting the analysis to women with 12 years education. We know there are 108,000 births to such women. The result would seem to be 9 births per 1,000 such women (108,000/ 12,000,000). But of course this is totally wrong, because the denominator is not adjusted. And we do not have the population denominator data for women with 12 years education, so there is no easy solution.

To resolve this problem, when Vitalnet makes a rate calculation, it automatically prevents spurious results from being produced, by automatically adding all categories to demographic variables that are not included in the population data set.

So, for example, if you try to calculate a birth rate for women with 12 years of education, Vitalnet simply ignores the limitation to 12 years of education. Instead, it includes all levels of education, so the numerator and denominator match up. And it correctly reports that all levels of education were analyzed.

In contrast, if you try to calcuate a cesarean rate for women with 12 years of education, this does not require population data, only requires information on the births, so Vitalnet calculates the cesarean rate, limited to women with 12 years of education.

Other Settings

Other Settings include the following options:

Statistic Modifiers:
• Age-Adjust Standard - Standard Population to Use

Secondary Statistics:
• Cell Confidence Level - Set Level, or Turn Off
• Cell Suppression - Hide Result if Low Count
• Maximum Replicates - Maximum Jackknife Replicates to Use
• Table Percents - Row or Column Percents
• Trend Algorithm - Trend Analysis Method
• Trend Confidence - Set Level, or Turn Off

Miscellaneous Details:
• Decimal Digits - Example: Two in 5.78
• HTML Line Style - Line Style for Output HTML
• HTML Output Font - Text Font for Output HTML
• HTML Padding - Padding for Output HTML Table
• Spreadsheet Format - Spreadsheet Data Format
• Tabular Chart - Chart Width, or Omit Chart
• Unique ID - Put ID on Maps and Charts?

Bar Chart Coloring

• Background color behind the chart.
• Color palette to use for the bars.
• First color in palette to use for bars.

Below are shown the settings, with examples:

Background Color for Chart (20 options)

White

Grey 95

Lemon Chiffon

Light Cyan

Color Palette for Bars (4 options)

Bright Colors

Subdued Colors

Bright + Subdued

Black + White

First Color in Palette to Use (10 options)

A Forward

D Reverse

E Forward

J Reverse

Bar Chart Layout

Vertical or Horizontal Bars

Vertical Bars

Horizontal

Stacked Bars?

Stacked Bars

Not Stacked

Height of Each Bar (9 options)

2 cm High

4 cm High

Width of Each Bar (8 options)

0.2 cm Wide

0.6 cm Wide

Include Grid Lines?

Include Grid

Omit Grid

Font Size for Chart Text (8 options)

10 pt Font

14 pt Font

Line Chart Settings #1

Eight ways to customize Vitalnet line charts:

Background Color for Chart (20 options)

Alice Blue

Light Yellow

Include Data Point Symbols? (2 options)

Include Symbols

Omit Symbols

Radius for Chart Symbols (10 options)

1.0 mm Radius

1.4 mm Radius

Line Chart Height (9 options)

4.0 cm (Not Shown)

7.0 cm (Not Shown)

Line Chart Settings #2

Width of Lines (3 options)

Thin Lines

Thick Lines

Include Grid Lines? (2 options)

Include Grid

Omit Grid

Colored Lines, or Black + White (2 options)

Colored Lines

Black + White Lines

Font Size for Chart Text (8 options)

10 pt Font (Not Shown)

12 pt Font (Not Shown)

Pie Chart Coloring

Three settings for customizing pie chart coloring:

• The background color behind the chart.
• The color palette to use for the pie chart.
• First color in palette to use (for slice #1).

Background Color for Chart (20 options)

Cornsilk Background

Grey Background

Light Cyan

Color Palette for Pie Chart (3 options)

Bright Colors

Subdued Colors

Mixed Colors

Slice #1 Color to Use (10 options)

Color A for #1

I Forward

F Reverse

Pie Chart Layout

Four settings for customizing pie chart layout:

Slice #1 Clock Position (12 options)

Slice #1 at Noon

Slice #1 at 3:00

Slice #1 at 6:00

How to Label Pie Chart (9 options)

Line + Label

Label Only

Use Legend

How to Display Slice Percents (3 options)

Percent After Label

Under Label

Omit Percents

Pie Chart Radius (9 options)

3.0 cm (Not Shown)

4.0 cm (Not Shown)

5.0 cm (Not Shown)

Tabular Charts / Chart Links

A "tabular chart" is a convenient way of making comparisons.

The tabular chart is always made, unless turned off from the "Other Settings" menu. Also, you may specify the width of the columns within the chart.

Chart links: Note the links below the tabular chart. The links connect to additional graphical and data output formats. The example above links to bar chart, text, database, and spreadsheet formats.

Map Coloring

Color Combination (36 options)

Orange-Red

Grey

Red-Blue

Number of Colors (8 options)

3 Colors

5 Colors

7 Colors

How to Set Ranges (3 options)

Equal Ranges

Equal Counts

Natural Breaks

Map Layout

Boundaries to Display (2 options)

County Boundaries

HSR Boundaries

Border Counties

Cell Suppression (1 options)

Suppression Off

Suppress if < 10 Events

Suppress if < 30 Events

Map File Format (PNG, PDF, SVG, GIS)

PNG Map (Imports Best)

SVG Map (Prints Best)

GIS Map (Interesting)

Map Color Palettes

1	2	3	4	5	6	7	8	9	Diverging Palette	BW	CB
									Brown-BlueGreen	-	Y
									Pink-Green	-	Y
									Purple-Green	-	Y
									Purple-Orange	Y	Y
									Red-Blue	-	Y
									Red-Grey	-	-
									Red-Yellow-Blue	-	Y
									Red-Yellow-Green	-	-
									Spectral	Y	-
1	2	3	4	5	6	7	8	9	Sequential Palette	BW	CB
									Blue	Y	Y
									Blue-Green	Y	Y
									Blue-Purple	Y	Y
									Green-Blue	Y	Y
									Green	Y	Y
									Grey	Y	Y
									Orange	Y	Y
									Orange-Red	Y	Y
									Purple-Blue	Y	Y
									Purple-Green	Y	Y
									Purple-Red	Y	Y
									Purple	Y	Y
									Red-Purple	Y	Y
									Red	Y	Y
									Yellow-Green	Y	Y
									Yellow-Blue	Y	Y
									Yellow-Brown	Y	Y
									Yellow-Red	Y	Y

All palettes are OK for color printing. BW - OK for black and white printing? CB - OK for red-green color blindness?

References for Vitalnet map color palettes - • LW Pickle, M Mungiole, GK Jones, AA White, "Atlas of United States Mortality", National Center for Health Statistics, 1997. • CA Brewer, "Color Use Guidelines for Mapping and Visualization", in "Visualization in Modern Cartography", Elsevier, 1994. • ColorBrewer web site showing color palettes.

Getting Results

To produce results:

1. Click on button - Click on "Make Map NOW" or "Make Table NOW". The program sends the query to the server.

2. View Results Window - Output will display in separate window. It takes a few seconds, depending on the analysis, the data set, and how much data.

3. Conflicts prevented - The program does not permit an invalid request. If a problem, such as row / column mismatch, you will be prompted to correct it before submitting request.

Viewing Results

To view results:

1. Scroll results - Use scroll bar, PgUp, PgDn, etc.
2. Print or Save results - Sends to printer or disk.
3. Click on footnote links - Access charts and data files.

If graphics do not display in output, refresh the browser.

Printing Results

To print results from your browser, use one of the following methods:

• Press CTL-P - Hold down Control key, and press 'P' key.
• Use Browser Icon - Click on Print Icon (if available).
• Use Browser Menu - Select "File / Print" (if menu available).

If output table is too wide or long, here are two ways to make it fit:

• Use fewer rows or columns. Also makes it easier to understand.
• Change browser font size. Typical command is: View / Text Size.

How to print from a spreadsheet or word processor:

1. Click on link for desired format in output footnotes.
2. Download and import the data file:
• CSV / TSV / DIF for spreadsheets, such as Excel or StarOffice.
• ASCII for word processor, such as Word or WordPerfect.
3. Format and print from within your spreadsheet or word processor.

Saving Results

To save results displayed in your browser, do one of the following:

• Press CTL-S - Hold down Control key, and press 'S' key.
• Use Browser Menu - Select "File / Save" (or equivalent).

To save an alternate data format, click on a footnote link:

• ASCII text - Import into word processing software.
• CSV/TSV/DIF format - Import into spreadsheet software.
• dBASE III - For database, GIS, mapping, stats software.

To save a map as an image file, minus any surrounding text:

1. Position cursor over map, using your mouse.
2. Press right mouse button to bring up popup menu.
3. Select "Save" option from popup menu.
4. Specify directory (folder) to save file.

Here are some suggestions on naming files:

• Memorable - Select a name that will remind you of the content.
• Organized - Organize files into project directories (folders).
• Linkable - Use provided unique ID for data files, such as "112jdhkm.dbf".

When Charts and Maps are Made

Vitalnet is smart about making output. Whenever you make a table, Vitalnet usually makes one or more accompanying charts. But it only produces the charts that make sense. If a chart would look terrible, or not be epidemiologically valid, the software does not make it.

Vitalnet avoids making misleading or useless charts. To prevent misinterpretation and embarassing results, Vitalnet intelligently decides when it appropriate to make a chart, as explained below:

Bar charts are only made if the following conditions are met:

• 1 to 20 rows (groups of bars).
• 1 to 10 columns (bars per group).
• No suppressed results (for stacked bar chart).

Line charts are only made if the following conditions are met:

• Range rows (such as age or year).
• No breaks in ranges (not 2000, 2002).
• Rows not sorted. No suppressed results.
• No more than 10 lines (10 columns).

Pie charts are only made if the following conditions are met:

• Cumulative data (counts, some rates).
• One set of numbers (one row or column).
• 2 to 9 pie slices. No suppressed results.

Time trend maps (that cycle from map to map) are only produced when all selected year ranges are the same width. For example, 1995-1996, 1997-1998, 1999-2000 is OK. But 1995-1996, 1997-1998, 1999 is not OK. Also, at least two year ranges are required. So if you just have 1995-1996 (a single range) selected, Vitalnet does not make a series of time trend maps.

Time trend analysis, when making a table with year rows, is only carried out when: 1) at least three year ranges are selected, 2) there are no gaps in the ranges, 3) the ranges are the same width, and 4) the rows are not sorted. When these conditions are met, the time trend analysis is epidemiologically valid.

Glossary

Area set - One or more areas combined.

ASCII file - A text file, with only alphabetical, numerical, and punctuation characters, like you would see in normal text. Vitalnet can produce output in ASCII format.

CDC - Centers for Disease Control and Prevention. US federal health agency.

Cell - A space for a single numerical result in a table, at a row-column intersection.

Cell suppression - An asterisk "*" is placed in cells with fewer events (such as deaths) than a limit set by the user. Row / column totals with exactly one suppressed cell in the row / column are also suppressed. If more than one cell in the row / column is suppressed, the row / column total may be displayed.

Columns - Vertical groupings of data in a Vitalnet table, such as a column for each race group.

Confidence interval (confidence limits) - A range of values within which the true value of a variable is thought to lie, with a specified level of confidence. For a result of 23.5, a confidence interval might be (23.1-23.9). The smaller the interval, the more reliable the result, so 23-24 is more reliable than 13-34. If the 95% confidence intervals do not overlap, there is probably a statistically significant difference. Vitalnet uses several methods to calculate confidence intervals. The output table documents which method was used.

Confidence level - The likelihood that the true value of a variable is within a confidence interval. For example, for confidence intervals at the 95% level, we are statistically 95% certain that the actual value of the variable is within the interval.

CSV format - Comma-separated-value format. CSV files are readily imported into spreadsheet software. Each output item is separated by a comma from surrounding items, and each output text item is surrounded by "double quotes". A comma-separated-value file has "csv" extension. Similar to TSV format.

Data warehouse - A software system, such as Vitalnet, making large complex databases readily available for querying and analysis. A related term is "data mining", finding unexpected relationships in a data set, for further study. Data mining is similar to exploratory data analysis. Vitalnet is excellent at data mining. Of course, keep in mind that the more you look, the more unusual events you will find, just by chance.

dBASE III format - A widely used file format originally for the database software of the same name. Files in dBASE III format may be readily imported into almost any data analysis, graphing, mapping, or other presentation software. Uses dbf extension. Suppressed cells are represented as the number "-1".

DIF format - Data interchange format. DIF files are readily imported into spreadsheet software. The DIF format is too complex to explain in this glossary. Has "dif" extension.

Denominator - The number on the bottom of a fraction. Population data are often referred to as "denominator data", as they are used as denominators to calculate population-based rates.

Export - Produce output that can be read into other computer programs. Vitalnet produces ASCII text (txt), comma-separated-value (csv), HTML (htm), and dBASE III (dbf) files for export.

Filter variable - A variable solely used to filter which records are included in the output. For example, for a single table with race rows and sex columns, age 10-19 is a filter variable.

FIPS Code - FIPS = "Federal Information Processing Standards". A five-digit number which uniquely identifies counties, territories, and certain other areas in the United States. States have two-digit FIPS codes.

Footer - Last part of a Vitalnet table. Lists less important details of the analysis, such as the date produced, and data sources. Also contains a unique ID to assist in keeping track of analyses.

Header - First part of a Vitalnet table. Lists key analysis parameters, such as years analyzed.

Import - Read information into a computer program. ASCII text, CSV, TSV, DIF, HTML, and dBASE III files from Vitalnet are easily imported into word processing, spreadsheet, data analysis, mapping, graphing, and other presentation software programs.

Jackknife Method - A method for calculating variances and confidence intervals. Jackknife is accurate for complex survey designs, such as BRFSS. Jackknife will work with any statistic, such as percent, mean, or median. The jackknife method repeatedly calculate a replicate statistic. For each replicate, it leaves out one observation (or group of observations), and reweights the observations left in. The variance of the replicates is the same as that of the original data. It is called "jackknife" because it is so generally useful.

Least-squares - A standard method for fitting the best straight line to a set of points. Produces a Y-intercept and a slope defining the least-squares line.

Multiple age groups - One age group for each table row (or column). Example: 0-19, 20-59, 60-99+.

Natural Breaks - Method for determining map ranges. Minimizes "squared deviations from class means".

NCHS - National Center for Health Statistics. US health statistics agency. Part of the CDC.

Population - The number of people living in an area.

Rows - Horizontal lines in a Vitalnet table, such as a row for each race group.

Row sort settings - Vitalnet rows may be sorted in ascending or descending order.

Set - A combination of one or more things. For example, several areas may be combined into an area set.

Single age group - Only one age group (30-49, for example) is selected. A single age group is used for tables that do not have age columns or age rows.

Statistic (Main Statistic) - The basic type of numerical result displayed in a table, chart, or map. For example, birth rate, death rate, population, pregnancy rate, etc.

Table - A set of results produced by Vitalnet. A table has several parts:

1. Header - basic analysis settings
2. Data section - numerical results
3. Bar graphs - horizontal charts
4. Footer - other analysis settings

Tabular chart - A section of a Vitalnet table. Gives an scaleable graphical representation of the data. May be omitted from the output table.

TSV format - Tab-separated-value format. TSV files are readily imported into spreadsheet software. Each output item is separated by a tab from surrounding items, and each output text item is surrounded by "double quotes". A tab-separated-value file has "tsv" extension. Similar to CSV format.

Unknown Values - Unknowns are automatically inserted into a Vitalnet table. For example, a separate row (or column) for unknown race. The rate is assigned as zero for an unknown category, since there is no population denominator to use. Some fields, such as sex for certain data sets, are never unknown, so unknowns are left off the table. When, such as for age-adjusted rates, the unknown variable (age) is different from the rows or columns, the number of unknowns for age is shown below the table.

Vitalnet / VitalPro / VitalWeb - Vitalnet is data warehouse / data analysis software for analyzing health data sets. VitalPro is a Vitalnet system that runs directly on a PC, for example VitalPro for Win32. VitalWeb is a Vitalnet system that runs over the internet, for example VitalWeb Ajax.

Windows - Microsoft PC operating systems. VitalPro runs under any version of Windows.

World Wide Web (WWW) - A widely used part of the internet that may be easily accessed with a web browser. Vitalnet runs on the WWW.

County Groupings

Northern CT: Hartford County, Litchfield County, Tolland County, Windham County

Southern CT: Fairfield County, Middlesex County, New Haven County, New London County

Age Adjustment Standards

Statistical Methods

The "Main Statistic" (numerical outcome) is the basic type of number in a Vitalnet table. It is best understood by looking at the examples below.

Interviews (Unweighted) - The number of interviews considered valid for inclusion in the BRFSS data set. This number is NOT adjusted for sample weights. It is NOT valid for epidemiological comparisons. Interviews with not sure, refused, do not know, unknown, and missing values are INCLUDED.

Interviews (Weighted) - The number of interviews considered valid for inclusion in the BRFSS data set. This number IS adjusted for sample weights. It IS valid for epidemiological comparisons. This number approximates the population in a category. Interviews with not sure, refused, do not know, unknown, and missing values are INCLUDED.

Number Yes (Unweighted) - The number of interviews with a Yes response for a particular variable. This number is NOT adjusted for sample weights. It is NOT valid for epidemiological comparisons.

Number Yes (Weighted) - The number of interviews with a Yes response for a particular variable. This number IS adjusted for sample weights. It IS valid for epidemiological comparisons. This number approximates the population responding Yes for a variable.

Number No (Unweighted) - The number of interviews with a No response for a particular variable. This number is NOT adjusted for sample weights. It is NOT valid for epidemiological comparisons.

Number No (Weighted) - The number of interviews with a No response for a particular variable. This number IS adjusted for sample weights. It IS valid for epidemiological comparisons. This number approximates the population responding Yes for a variable.

Percent Yes (Weighted) - Percent of interviews responding Yes to a particular variable, with weighting factored in. It IS valid for epidemiological comparisons. The weighting means this is not a simple ratio of Yes / Total. Not sure, refused, do not know, unknown, and missing are EXCLUDED from the denominator.

Percent No (Weighted) - Percent of interviews responding No to a particular variable, with weighting factored in. It IS valid for epidemiological comparisons. The weighting means this is not a simple ratio of No / Total. Not sure, refused, do not know, unknown, and missing are EXCLUDED from the denominator.

Responses - The number of interviews with a valid response for a particular variable. Not sure, refused, do not know, unknown, and missing are EXCLUDED. This number is NOT adjusted for sample weights. It is NOT valid for epidemiological comparisons.

Confidence Intervals

Definition - A "confidence interval" is a range of values within which the true value of a variable is thought to lie, at a certain "confidence level", such as 95%. A larger percentage (such as 99%) is more stringent than a smaller percentage (such as 80%). Use 95% if you are unsure.

Interpretation - The smaller the interval, the more reliable the result. Two results that overlap at the 95% level are less likely to be significantly different than results which do not overlap.

Methods - The method Vitalnet uses to calculate confidence intervals depends on the context. The method is listed in the footnotes to the table.

Z * Rate / Sqrt (Events) - This method is recommended by the NCHS. Technical Appendix of the Vital Statistics of the United States, Vol II, Mortality, Part A

Jackknife Replication - A method for calculating variances and confidence intervals. Jackknife is accurate for complex survey designs, such as BRFSS. Jackknife will work with any statistic, such as percent, mean, or median. The jackknife method repeatedly calculate a replicate statistic. For each replicate, it leaves out one observation (or group of observations), and reweights the observations left in. The variance of the replicates is the same as that of the original data. It is called "jackknife" because it is so generally useful.

Jackknife Replication - The Jackknife procedure for calculating a BRFSS confidence interval has five parts (1-5), as follows:

1) SORTING: Sorting is only needed if more than one observation is removed for each replicate. In other words, sorting is not needed if "unlimited replicates". For the case where more than one observation is removed for a replicate, if the sorting is not done, the observations might be in a different order under different table scenarios, resulting in slightly different CI in different tables. Here is the series of sort operations (A-E): A) Sort cell observations by position within original BRFSS data file. B) Seed LINUX POSIX.1-2001 srand function with 1. C) Sequentially assign RandNdx to cell observations, using LINUX POSIX.1-2001 rand function. D) Sort cell observations by RandNdx. E) Sort all table observations by the cellNdx (table cell).

2) PARTITIONING: Partitioning is only needed if more than one observation is removed for each replicate. In other words, partitioning is not needed if "unlimited replicates". Partitioning divides observations in a cell into groups. Assume there are 1000 observations in a cell. For "replicates = 500", groups would be 1-2, 3-4,..., 999-1000. For "replicates = 999", groups would be 1, 2,..., 998, 999-1000. For "replicates = 998", groups would be 1, 2,..., 996, 997-998, 999-1000. For "replicates = 333", groups would be 1-3, 4-6,..., 994-996, 997-1000. For "replicates = 200", groups would be 1-5, 6-10,..., 996-1000. The same logic can be used to partition groups for any number of replicates. Since the observations have been randomly sorted in the previous step, there is no risk of bias resulting from related records being adjacent. If "unlimited replicates", or "replicates = N" and number of observations in cell is less than N, each observation is a group, and partitioning is not needed.

3) REWEIGHTING: Removes one group of observations. Redistributes total weight among remaining observations in a cell. For example, if "unlimited replicates", remove observation #1. Or if 1000 cell observations and "replicates = 500", remove observations 1-2. The remaining observations are re-weighted, so that the total FINAL_WT for each State remains the same. Subtract FINAL_WT of the omitted observations from State total FINAL_WT. Multiply each remaining (non-omitted) observation by the following factor: (State total FINAL_WT) / (State FINAL_WT after omitting observations). This readjusts the FINAL_WT for remaining observations, so the State total FINAL_WT is the same as before.

4) REPLICATING: Produces one replicate estimate. After a group of observations is omitted, and the remaining observations reweighted, the outcome statistic (% yes, median, or other) is calculated as a "replicate", and stored for later use.

5) CI CALCULATION: Calculates the confidence interval, from the replicates. Each replicate estimate is subtracted from the overall outcome statistic (the value with all observations included), and the difference is squared. The variance is calculated as: sumOfSquares_Cell * (replicate_count - 1) / replicate_count. The replicate_count is the number of replicates done for the cell. The standard error is the square root of the variance. The upper or lower confidence limit is (Student's T Value) * (standard error). The Student's T Value is for a given confidence interval (such as 95%), with degrees of freedom one less than the number of cell observations. If only one observation, degrees of freedom is set to one. Confidence intervals with very few obervations are not reliable in any case. If the confidence interval goes below zero, it is cut off at zero. If the percent confidence interval goes over 100%, it is cut off at 100%.

Brief description of jackknife method, for calculating variance for one BRFSS cell - 1) Put interview records for cell into standard, replicable order. 2) Remove one observation, or a group of observations. 3) Adjust weights for remaining observations. 4) Calculate replicate statistic (mean, median, percent) with remaining observations. 5) Repeat steps 2-4 for each observation or group of observations removed. 6) Calculate deviation of each replicate statistic from overall statistic. 7) Add the squared deviations to produce sum of squares (SS). 8) Variance = SS * (replicateCount - 1) / replicateCount. NOTE: More replicates provide slightly more accuracy, but take longer. 1000 replicates seems more than adequate.

Poisson distribution - This method is valid if events are relatively rare, which usually applies to health events. Scientific Tables, Diem and Lentner (ed), Giegy, 1970, page 189.

95% Poisson Confidence Limits

Events	Lo Factor	Hi Factor	Events	Lo Factor	Hi Factor	Events	Lo Factor	Hi Factor
1	0.025318	5.571647	70	0.779549	1.263440	4,000	0.969250	1.031230
2	0.121104	3.612346	80	0.792938	1.244587	5,000	0.972473	1.027911
3	0.206224	2.922426	90	0.804118	1.229170	6,000	0.974857	1.025464
4	0.272466	2.560398	100	0.813640	1.216268	7,000	0.976711	1.023564
5	0.324697	2.333667	200	0.866209	1.143395	8,000	0.978207	1.022034
6	0.366982	2.176580	300	0.890041	1.116362	9,000	0.979446	1.020767
7	0.402052	2.060382	400	0.904401	1.100401	10,000	0.980496	1.019696
8	0.431729	1.970399	500	0.914267	1.089575	20,000	0.986189	1.013907
9	0.457263	1.898312	600	0.921584	1.081617	30,000	0.988716	1.011348
10	0.479539	1.839036	700	0.927291	1.075453	40,000	0.990224	1.009824
20	0.610826	1.544419	800	0.931904	1.070497	50,000	0.991254	1.008785
30	0.674696	1.427562	900	0.935734	1.066400	60,000	0.992014	1.008018
40	0.714415	1.361716	1,000	0.938980	1.062941	70,000	0.992606	1.007422
50	0.742219	1.318376	2,000	0.956653	1.044307	80,000	0.993082	1.006942
60	0.763105	1.287198	3,000	0.964536	1.036105	90,000	0.993477	1.006544

BRFSS Questions

BRFSS Variable for each Question (Yes / No Variable) Question: 2011

BRFSS Variable	Vitalnet Question
FUT_BF_PERSDOC________NOW_	Access: Has a personal health care provider?
FUT_BF_CHECKUP_____1X_1YR_	Access: Had medical checkup within past year?
FUT_BF_HLTHPLAN_______NOW_	Access: Has health care coverage?
FUT_BF_MEDCOST________1YR_	Access: Lacked health care due to cost?
FUT_BF__RFDRHVY_______30D_	Alcohol: Has recently been a heavy drinker?
FUT_BF_HAVARTH_______EVER_	Arthritis: Doctor made a diagnosis of arthritis?
FUT_BF_ASTHMA________EVER_	Asthma: Told had asthma by doctor or nurse?
FUT_BF__ASTHMST___CURRENT_	Asthma: Told had asthma, and still has?
FUT_BF__ASTHMST____FORMER_	Asthma: Told had asthma, and no longer has?
FUT_BF__BMICAT______25_30_	BMI Category: Is overweight (BMI 25 to 30)?
FUT_BF__BMICAT______GE_30_	BMI Category: Is obese (BMI at least 30)?
FUT_BF__BMICAT______GE_25_	BMI Category: Is overweight or obese (BMI 25+)?
FUT_BF_CELL_1_________NOW_	Cell Phone: Has cell phone for personal use?
FUT_BF_BLOODCHO______EVER_	Cholesterol: Ever had cholesterol checked?
FUT_BF__CHOLCHK_______5YR_	Cholesterol: Had cholesterol check in past 5 years?
FUT_BF__RFCHOL_______EVER_	Cholesterol: Had cholesterol check and told high?
FUT_BF_EMPLOY____EMPLOYED_	Demographics: Is currently employed?
FUT_BF_MARITAL____MARRIED_	Demographics: Is married?
FUT_BF_VETERAN_______EVER_	Demographics: Was ever active duty in US military?
FUT_BF_PDIABTST_______3YR_	Diabetes: Had test for diabetes in past 3 years?
FUT_BF_DIABETES_ANY__EVER_	Diabetes: Ever diabetic (include pregnancy)?
FUT_BF_DIABETES_NP___EVER_	Diabetes: Ever diabetic (exclude pregnancy)?
FUT_BF_DIABEYE_______EVER_	Diabetes: Told eyes were affected by diabetes?
FUT_BF_DOCTDIAB_______1YR_	Diabetes Care: Saw a doctor in past year for diabetes?
FUT_BF_INSULIN________NOW_	Diabetes Care: Is taking insulin?
FUT_BF_DIABEDU_______EVER_	Diabetes Care: Took a class to manage diabetes?
FUT_BF_BLDSUGAR_____DAILY_	Diabetes Exams: Checks blood sugar daily?
FUT_BF_CHKHEMO_____1X_1YR_	Diabetes Exams: Checked Hb A1C in past year?
FUT_BF_CHKHEMO_____2X_1YR_	Diabetes Exams: Checked Hb A1C twice in past year?
FUT_BF_EYEEXAM__DM_1X_1YR_	Diabetes Exams: Had diabetic eye exam in past year?
FUT_BF_FEETCHK_____1X_1YR_	Diabetes Exams: Had diabetic foot exam in past year?
FUT_BF_FEETCHK2_____DAILY_	Diabetes Exams: Does daily diabetic foot self-exam?
FUT_BF__FRTINDX___NOW_GE5_	Diet: At least 5 fruits and vegetables a day?
FUT_BF__FRTINDX___NOW_LT1_	Diet: Less than 1 fruits and vegetables a day?
FUT_BF_QLACTLMT_______NOW_	Disability: Is limited in activities by a disability?
FUT_BF_USEEQUIP_______NOW_	Disability: Special equipment for health problem?
FUT_BF_EXERANY______MONTH_	Exercise: Leisure time exercise in past month?
FUT_BF_GENHLTH________E___	General Health: Has excellent general health?
FUT_BF_GENHLTH________EVG_	General Health: Has good or better general health?
FUT_BF_GENHLTH_________FP_	General Health: Has fair or poor general health?
FUT_BF_GENHLTH__________P_	General Health: Has poor general health?
FUT_BF_PHYSHLTH___30D_GE1_	Healthy Days: Poor physical health recently?
FUT_BF_MENTHLTH___30D_GE1_	Healthy Days: Poor mental health recently?
FUT_BF_POORHLTH___30D_GE1_	Healthy Days: Health limited activities recently?
FUT_BF_CVDCORHD______EVER_	Heart Disease: Ever told had coronary heart disease?
FUT_BF_CVDINFAR______EVER_	Heart Disease: Ever had a heart attack?
FUT_BF__HRTDIS_______EVER_	Heart Disease: Ever had heart disease?
FUT_BF__CVD__________EVER_	Heart Disease: Ever had cardiovascular disease?
FUT_BF_HASYMP1__NECK_PAIN_	Heart Facts: MI symptom? Jaw, neck, or back pain?
FUT_BF_HASYMP2__FEEL_WEAK_	Heart Facts: MI symptom? Feeling weak or faint?
FUT_BF_HASYMP3__CHST_PAIN_	Heart Facts: MI symptom? Chest pain or discomfort?
FUT_BF_HASYMP4_____SEEING_	Heart Facts: MI symptom? Sudden trouble seeing?
FUT_BF_HASYMP5___ARM_PAIN_	Heart Facts: MI symptom? Arm or shoulder pain?
FUT_BF_HASYMP6_SHT_BREATH_	Heart Facts: MI symptom? Shortness of breath?
FUT_BF__HASYMP__GOT_ALL_6_	Heart Facts: Recognizes all heart attack symptoms?
FUT_BF_HIVRISK________1YR_	HIV / AIDS: Has an HIV risk factor?
FUT_BF_HIVTST________EVER_	HIV / AIDS: Has ever been tested for HIV?
FUT_BF_BPHIGH________EVER_	Hypertension: Was ever told has hypertension (HTN)?
FUT_BF_BPEATADV______EVER_	HTN Advice: Advised to change eating habits?
FUT_BF_BPSLTADV______EVER_	HTN Advice: Advised to reduce salt intake?
FUT_BF_BPALCADV______EVER_	HTN Advice: Advised to reduce alcohol use?
FUT_BF_BPEXRADV______EVER_	HTN Advice: Advised to exercise?
FUT_BF_BPMEDADV______EVER_	HTN Advice: Advised to take medicine?
FUT_BF_BPEATHBT_______NOW_	HTN Care: To lower HTN: Changing diet?
FUT_BF_BPSALT_________NOW_	HTN Care: To lower HTN: Reducing salt?
FUT_BF_BPALCHOL_______NOW_	HTN Care: To lower HTN: Reducing alcohol?
FUT_BF_BPEXER_________NOW_	HTN Care: To lower HTN: Exercising?
FUT_BF_BPMEDS_________NOW_	HTN Care: To lower HTN: Taking medicine?
FUT_BF_LMTJOINT_______NOW_	Joint Pain: Is limited by arthritis or joint symptoms?
FUT_BF_PREGNANT_______NOW_	Pregnancy: Is currently pregnant?
FUT_BF_SMOKE100______EVER_	Smoking: Smoked 100 cigarettes in entire life?
FUT_BF__RFSMOKE_______NOW_	Smoking: Smoked 100 and currently smokes?
FUT_BF_STOPSMOK__1DAY_1YR_	Smoking: Quit smoking at least 1 day in past year?
FUT_BF_SCGETCAR_______1YR_	Smoking: Saw doctor for care in past year?
FUT_BF_SCDSCMED_______1YR_	Smoking: Discussed medication to quit smoking?
FUT_BF_SCDSCMTH_______1YR_	Smoking: Discussed other ways to quit smoking?
FUT_BF_SCQITSMK_______1YR_	Smoking: Advised to quit smoking in past year?
FUT_BF_CVDSTROK______EVER_	Stroke: Ever told had a stroke?
FUT_BF_STRSYMP1_CONFUSION_	Stroke Facts: Is a stroke symptom? Confusion?
FUT_BF_STRSYMP2__NUMBNESS_	Stroke Facts: Is a stroke symptom? Numbness?
FUT_BF_STRSYMP3____SEEING_	Stroke Facts: Is a stroke symptom? Trouble seeing?
FUT_BF_STRSYMP4_CHST_PAIN_	Stroke Facts: Is a stroke symptom? Chest pain?
FUT_BF_STRSYMP5_DIZZYNESS_	Stroke Facts: Is a stroke symptom? Dizziness?
FUT_BF_STRSYMP6__HEADACHE_	Stroke Facts: Is a stroke symptom? Bad headache?
FUT_BF__STRSYMP_GOT_ALL_6_	Stroke Facts: Recognizes all stroke symptoms?
FUT_BF_PNEUMVAC______EVER_	Vaccines: Ever had pneumococcal vaccine?

Data Sources and Limitations

VitalWeb Ajax uses data from authoritative sources.

BRFSS data - All BRFSS data were provided by the Centers for Disease Control and Prevention (CDC).

Links to Related Resources

Internet resources related to Adult BRFSS:

• CDC BRFSS Web Site
• Connecticut Department of Public Health

Whom to Contact

For additional assistance with analyzing and interpreting the data, contact:

• TBA

Legal Information

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Connecticut Adult BRFSS VitalWeb Ajax Online Help

Table of Contents

Quick Guide to Using VitalWeb Ajax

Multiple Windows

Overall Question

Main Statistic

Table Axes (Rows and Columns)

Statistic / Axis Conflicts

Selecting Data Variables

Statistic / Variable Conflicts

Other Settings

Bar Chart Coloring

Bar Chart Layout

Line Chart Settings #1

Line Chart Settings #2

Pie Chart Coloring

Pie Chart Layout

Tabular Charts / Chart Links

Map Coloring

Map Layout

Map Color Palettes

Getting Results

Viewing Results

Printing Results

Saving Results

When Charts and Maps are Made

Glossary

County Groupings

Age Adjustment Standards

Statistical Methods

Confidence Intervals

95% Poisson Confidence Limits

BRFSS Questions

Data Sources and Limitations

Links to Related Resources

Whom to Contact

Legal Information

Connecticut Adult BRFSS
VitalWeb Ajax
Online Help