Texas ICD-10 Underlying Cause Deaths
VitalWeb Ajax
Online Help
Table of Contents
Introduction
Quick Guide to Using VitalWeb Ajax
Multiple Windows
Table Settings
Main Statistic
Table Axes (Rows and Columns)
Statistic / Axis Conflicts
Data Variables
Categorical Variables
Range Variables
Statistic / Variable Conflicts
Other Settings
Chart Settings
Bar Chart Coloring
Bar Chart Layout
Line Chart Settings
More Line Chart Settings
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
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 "Age-Adjusted Death Rate"
Rows and columns, for example year rows
Values for data variables, for example race
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.
Main Statistic
Main Statistic
- The basic numerical result in the output.
Main statistics include:
Deaths | Death Rate | Age-Adjusted Death Rate | Mean Age of Death | Standardized Mortality Ratio | Years of Potential Life Lost | Years of Life Lost Rate
Selecting
- Click on desired setting, such as Deaths.
Example Statistic Selector:
Deaths
Death Rate
Age-Adjusted Death Rate
Mean Age of Death
Standardized Mortality Ratio
Years of Potential Life Lost
Years of Life Lost Rate
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:
Age
Cause of Death
Geographic Area
Race
Sex
Year
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.
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, race, sex, year, cause of death, county of residence.
Example selector
for range variable, such as age or year:
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:
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
-
SMR Standard
- Standard for Calculating SMR
-
YPLL Age Limit
- YPLL Cutoff, such as 65
Secondary Statistics:
-
Cell Confidence Level
- Set Level, or Turn Off
-
Cell Suppression
- Hide Result if Low Count
-
Table Percents
- Row or Column Percents
-
Trend Algorithm
- Trend Analysis Method
-
Trend Confidence Level
- Set Level, or Turn Off
Miscellaneous Details:
-
Decimal Place Digits
- For example, two in 5.78
-
HTML Output Font
- Font for Output Text
-
Spreadsheet Format
- Spreadsheet Data Format
-
Tabular Chart
- Chart Width, or Omit Chart
-
Unique ID
- Put ID on Maps and Charts?
Bar Chart Coloring
There are three settings for customizing Vitalnet bar chart colors:
- The background color behind the chart.
- The color palette to use for the bars.
- The first color in the palette to use for the bars.
Below are shown the three settings, with examples for each:
Background Color for Chart
(12 options)
White
Grey 90
Lemon Chiffon
Light Blue
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
There are six ways to customize the layout of Vitalnet bar charts:
- Orientation (horizontal or vertical).
- Stacking (works with either horizontal or vertical bars).
- Bar height. - Bar width. - Grid lines. - Font size.
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
There are eight ways to customize Vitalnet line charts, as shown on this and the next page.
Background Color for Chart
(12 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
- Vitalnet also allows you to set the chart height, eg 3.0 cm (9 height options).
More Line Chart Settings
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
- Vitalnet also allows you to select font size, eg 9 pt (8 font size options).
Pie Chart Coloring
There are three settings for customizing Vitalnet pie chart coloring:
- The background color behind the chart.
- The color palette to use for the pie chart.
- The first color in the palette to use (for slice #1).
Background Color for Chart
(12 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
Color B for #1
Color C for #1
Pie Chart Layout
There are four settings for customizing Vitalnet pie chart layout, as shown below:
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
- Vitalnet also allows you to select the pie chart size, eg 2.0 cm (9 options).
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 Ranges
(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
(6 options)
County Boundaries
HSR Boundaries
Border Counties
Cell Suppression
(14 options)
Suppression Off
Suppress < 10
Suppress < 30
PNG and PDF formats
- Vitalnet always makes both PNG and PDF map output. Access the PDF version by clicking a link at the bottom of the web page with the PNG map. The PDF version is set to 8 1/2 x 11 inches.
Text Font for Map
- There are 9 font options for displaying area labels:
[ Serif Normal ]
[ Sans-Serif Normal ]
[ Monospace Normal ]
[ Serif Bold ]
[ Sans-Serif Bold ]
[ Monospace Bold ]
[ Serif Italic ]
[ Sans-Serif Italic ]
[ Monospace Italic ]
Time Trend Maps
- Finally, Vitalnet can make (not shown here) a series of maps, one map for each selected year range. The map series is cycled within a special interface. The data ranges are the same for each map in the series, so you can directly compare the maps.
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
BW
- OK for black and white photocopying?
CB
- OK for people with red-green color blindness?
All palettes are suitable for desktop color printing.
References and research
used to help design Vitalnet 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 displays tested 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 through the results
- Use scroll bar, PgUp, PgDn, etc.
2.
Print
or
Save
results
- Sends results to printer or disk.
3. Click on footnote links
- Displays or downloads charts and data files.
If graphics do not display in the output, try refreshing 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 the appropriate link in output footnotes.
2. Download and import the data file.
-
CSV / TSV / DIF for spreadsheet
, 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
- For importing into word processing software.
-
CSV/TSV/DIF format
- For importing into spreadsheet software.
-
dBASE III
- For database, GIS, mapping, statistical software.
To save a map as an image file, minus any surrounding text:
1. Position the cursor over the map, using your mouse.
2. Press the right mouse button to bring up a popup menu.
3. Select the "Save" option from the popup menu.
4. Specify the directory (folder) to save the 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 the unique ID for data files, such as "112jdhkm.dbf".
When Charts and Maps are Made
Whenever you make a table, Vitalnet also 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
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 2 year ranges are required. So if you just have 1995-1996 (a single range) selected, Vitalnet does not make a time trend map.
Time trend analysis
, when making a table with year rows, is only carried out when: 1) enough 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
Age-adjusted death rate
- Deaths per 100,000 population, adjusted to a standard population (such as US 1940 or US 2000), by the direct method. Age-adjusted rates are often better for making comparisons than unadjusted rates, because they adjust for differences in age distribution between populations. An age-adjusted rate is a summary synthetic measure. Besides calculating overall age-adjusted rates, it is also recommended to compare age-specific rates.
Age-adjustment standard
- A standard population for calculating an age-adjusted death rate. The 1940 and 2000 US Census population are the most common standards.
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.
Cause of death
- Any condition which leads to or contributes to death, and is classifiable according to the International Classification of Diseases (ICD) system.
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".
Death rate
- Deaths per 100,000 population. May be used to compare the burden of disease between different groups. Also called crude death rate.
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.
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.
ICD
- International Classification of Diseases. A widely used system for classifying diseases and injuries. Each disease or set of diseases has an ICD code or ICD group assigned to it. Vitalnet uses the ICD-9 system, for 1979-1998 mortality data, and the ICD-10 system, for 1999-present mortality data. An "ICD code" is a single ICD number representing a single disease or injury. For example, ICD E10 for insulin-dependent diabetes. An "ICD group" is a range of continuous ICD codes. For example, ICD E10-E14 for diabetes mellitus. An "ICD set" is one or more ICD groups or codes combined, for example ICD C50 (breast cancer) and ICD C53 (cervical cancer).
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.
Leading causes for ICD-10
- The ten causes of death with the highest number of deaths, out of a standard National Center for Health Statistics list of 51 rankable causes. Vitalnet makes it easy to select and rank the 51 cause list.
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.
Mean age of death
- If the ages were 50, 51, and 58, the mean age of death is (50 + 51 + 58) / 3 = 53
Multiple age groups
- One age group for each table row (or column). Example: 0-19, 20-59, 60-99+.
Multiple cause mortality data
- Data which include all causes of death listed on the death certificate. Contrast with underlying cause mortality data.
Multiple causes of death
- All diseases or injuries which led directly to death, or all circumstances of the accident or violence which produced the fatal injury.
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.
Place of occurrence mortality data
- Data compiled by the location the death occurred, without regard to the place of residence of the deceased. Vitalnet does not currently analyze for place of occurrence.
Place of residence mortality data
- Data compiled by the place of residence of the deceased, without regard to the location where the death occurred. Vitalnet analyzes mortality data by place of residence.
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.
Standardized mortality ratio (SMR)
- The ratio of the expected number of deaths to the observed number of deaths. The expected number of deaths is derived by applying a standard set of rates (usually state or national rates) to a population. SMRs help assess whether the mortality in a population is higher than expected.
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 - lists basic analysis settings
2. Data section - numerical results
3. Horizontal bar graphs - graphical representation of the data
4. Footer - lists 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.
Underlying cause
- The disease or injury that initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury. A single underlying cause is assigned to each death.
Underlying cause mortality data
- Data which include only the underlying cause of death listed on the death certificate. Contrast with multiple cause mortality data.
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.
Years of potential life lost (YPLL)
- Sum of the years of life lost by persons who die "early". Early death is usually defined as death occurring before the age of 65 (the YPLL age limit). For example, death at age 40 (40.5) results in 24.5 YPLL to age 65. YPLL is a widely used measure of premature mortality.
YPLL age limit
- The age used for calculating YPLL. The most common YPLL age limit is 65.
YPLL rate
- YPLL per 100,000 population in the appropriate age category. The YPLL rate up to age 65 is calculated as follows: (YPLL up to age 65) / (population for age group 0-64). Not commonly used.
County Groupings
8 Health Service Regions
-
HSR 1:
Armstrong, Bailey, Briscoe, Carson, Castro, Childress, Cochran, Collingsworth, Crosby, Dallam, Deaf Smith, Dickens, Donley, Floyd, Garza, Gray, Hale, Hall, Hansford, Hartley, Hemphill, Hockley, Hutchinson, King, Lamb, Lipscomb, Lubbock, Lynn, Moore, Motley, Ochiltree, Oldham, Parmer, Potter, Randall, Roberts, Sherman, Swisher, Terry, Wheeler, Yoakum
HSR 2 / 3:
Archer, Baylor, Brown, Callahan, Clay, Coleman, Collin, Comanche, Cooke, Cottle, Dallas, Denton, Eastland, Ellis, Erath, Fannin, Fisher, Foard, Grayson, Hardeman, Haskell, Hood, Hunt, Jack, Johnson, Jones, Kaufman, Kent, Knox, Mitchell, Montague, Navarro, Nolan, Palo Pinto, Parker, Rockwall, Runnels, Scurry, Shackelford, Somervell, Stephens, Stonewall, Tarrant, Taylor, Throckmorton, Wichita, Wilbarger, Wise, Young
HSR 4 / 5 North:
Anderson, Angelina, Bowie, Camp, Cass, Cherokee, Delta, Franklin, Gregg, Harrison, Henderson, Hopkins, Houston, Jasper, Lamar, Marion, Morris, Nacogdoches, Newton, Panola, Polk, Rains, Red River, Rusk, Sabine, San Augustine, San Jacinto, Shelby, Smith, Titus, Trinity, Tyler, Upshur, Van Zandt, Wood
HSR 6 / 5 South:
Austin, Brazoria, Chambers, Colorado, Fort Bend, Galveston, Hardin, Harris, Jefferson, Liberty, Matagorda, Montgomery, Orange, Walker, Waller, Wharton
HSR 7:
Bastrop, Bell, Blanco, Bosque, Brazos, Burleson, Burnet, Caldwell, Coryell, Falls, Fayette, Freestone, Grimes, Hamilton, Hays, Hill, Lampasas, Lee, Leon, Limestone, Llano, McLennan, Madison, Milam, Mills, Robertson, San Saba, Travis, Washington, Williamson
HSR 8:
Atascosa, Bandera, Bexar, Calhoun, Comal, DeWitt, Dimmit, Edwards, Frio, Gillespie, Goliad, Gonzales, Guadalupe, Jackson, Karnes, Kendall, Kerr, Kinney, La Salle, Lavaca, Maverick, Medina, Real, Uvalde, Val Verde, Victoria, Wilson, Zavala
HSR 9/10:
Andrews, Borden, Brewster, Coke, Concho, Crane, Crockett, Culberson, Dawson, Ector, El Paso, Gaines, Glasscock, Howard, Hudspeth, Irion, Jeff Davis, Kimble, Loving, McCulloch, Martin, Mason, Menard, Midland, Pecos, Presidio, Reagan, Reeves, Schleicher, Sterling, Sutton, Terrell, Tom Green, Upton, Ward, Winkler
HSR 11:
Aransas, Bee, Brooks, Cameron, Duval, Hidalgo, Jim Hogg, Jim Wells, Kenedy, Kleberg, Live Oak, McMullen, Nueces, Refugio, San Patricio, Starr, Webb, Willacy, Zapata
11 Public Health Regions (Effective 3/1/93)
-
PHR 1:
Armstrong, Bailey, Briscoe, Carson, Castro, Childress, Cochran, Collingsworth, Crosby, Dallam, Deaf Smith, Dickens, Donley, Floyd, Garza, Gray, Hale, Hall, Hansford, Hartley, Hemphill, Hockley, Hutchinson, King, Lamb, Lipscomb, Lubbock, Lynn, Moore, Motley, Ochiltree, Oldham, Parmer, Potter, Randall, Roberts, Sherman, Swisher, Terry, Wheeler, Yoakum
PHR 2:
Archer, Baylor, Brown, Callahan, Clay, Coleman, Comanche, Cottle, Eastland, Fisher, Foard, Hardeman, Haskell, Jack, Jones, Kent, Knox, Mitchell, Montague, Nolan, Runnels, Scurry, Shackelford, Stephens, Stonewall, Taylor, Throckmorton, Wichita, Wilbarger, Young
PHR 3:
Collin, Cooke, Dallas, Denton, Ellis, Erath, Fannin, Grayson, Hood, Hunt, Johnson, Kaufman, Navarro, Palo Pinto, Parker, Rockwall, Somervell, Tarrant, Wise
PHR 4:
Anderson, Bowie, Camp, Cass, Cherokee, Delta, Franklin, Gregg, Harrison, Henderson, Hopkins, Lamar, Marion, Morris, Panola, Rains, Red River, Rusk, Smith, Titus, Upshur, Van Zandt, Wood
PHR 5:
Angelina, Hardin, Houston, Jasper, Jefferson, Nacogdoches, Newton, Orange, Polk, Sabine, San Augustine, San Jacinto, Shelby, Trinity, Tyler
PHR 6:
Austin, Brazoria, Chambers, Colorado, Fort Bend, Galveston, Harris, Liberty, Matagorda, Montgomery, Walker, Waller, Wharton
PHR 7:
Bastrop, Bell, Blanco, Bosque, Brazos, Burleson, Burnet, Caldwell, Coryell, Falls, Fayette, Freestone, Grimes, Hamilton, Hays, Hill, Lampasas, Lee, Leon, Limestone, Llano, McLennan, Madison, Milam, Mills, Robertson, San Saba, Travis, Washington, Williamson
PHR 8:
Atascosa, Bandera, Bexar, Calhoun, Comal, DeWitt, Dimmit, Edwards, Frio, Gillespie, Goliad, Gonzales, Guadalupe, Jackson, Karnes, Kendall, Kerr, Kinney, La Salle, Lavaca, Maverick, Medina, Real, Uvalde, Val Verde, Victoria, Wilson, Zavala
PHR 9:
Andrews, Borden, Coke, Concho, Crane, Crockett, Dawson, Ector, Gaines, Glasscock, Howard, Irion, Kimble, Loving, McCulloch, Martin, Mason, Menard, Midland, Pecos, Reagan, Reeves, Schleicher, Sterling, Sutton, Terrell, Tom Green, Upton, Ward, Winkler
PHR 10:
Brewster, Culberson, El Paso, Hudspeth, Jeff Davis, Presidio
PHR 11:
Aransas, Bee, Brooks, Cameron, Duval, Hidalgo, Jim Hogg, Jim Wells, Kenedy, Kleberg, Live Oak, McMullen, Nueces, Refugio, San Patricio, Starr, Webb, Willacy, Zapata
24 Councils of Government
-
COG 1:
Armstrong, Briscoe, Carson, Castro, Childress, Collingsworth, Dallam, Deaf Smith, Donley, Gray, Hall, Hansford, Hartley, Hemphill, Hutchinson, Lipscomb, Moore, Ochiltree, Oldham, Parmer, Potter, Randall, Roberts, Sherman, Swisher, Wheeler
COG 2:
Bailey, Cochran, Crosby, Dickens, Floyd, Garza, Hale, Hockley, King, Lamb, Lubbock, Lynn, Motley, Terry, Yoakum
COG 3:
Archer, Baylor, Clay, Cottle, Foard, Hardeman, Jack, Montague, Wichita, Wilbarger, Young
COG 4:
Collin, Dallas, Denton, Ellis, Erath, Hood, Hunt, Johnson, Kaufman, Navarro, Palo Pinto, Parker, Rockwall, Somervell, Tarrant, Wise
COG 5:
Bowie, Cass, Delta, Franklin, Hopkins, Lamar, Morris, Red River, Titus
COG 6:
Anderson, Camp, Cherokee, Gregg, Harrison, Henderson, Marion, Panola, Rains, Rusk, Smith, Upshur, Van Zandt, Wood
COG 7:
Brown, Callahan, Coleman, Comanche, Eastland, Fisher, Haskell, Jones, Kent, Knox, Mitchell, Nolan, Runnels, Scurry, Shackelford, Stephens, Stonewall, Taylor, Throckmorton
COG 8:
Brewster, Culberson, El Paso, Hudspeth, Jeff Davis, Presidio
COG 9:
Andrews, Borden, Crane, Dawson, Ector, Gaines, Glasscock, Howard, Loving, Martin, Midland, Pecos, Reeves, Terrell, Upton, Ward, Winkler
COG 10:
Coke, Concho, Crockett, Irion, Kimble, McCulloch, Mason, Menard, Reagan, Schleicher, Sterling, Sutton, Tom Green
COG 11:
Bosque, Falls, Freestone, Hill, Limestone, McLennan
COG 12:
Bastrop, Blanco, Burnet, Caldwell, Fayette, Hays, Lee, Llano, Travis, Williamson
COG 13:
Brazos, Burleson, Grimes, Leon, Madison, Robertson, Washington
COG 14:
Angelina, Houston, Jasper, Nacogdoches, Newton, Polk, Sabine, San Augustine, San Jacinto, Shelby, Trinity, Tyler
COG 15:
Hardin, Jefferson, Orange
COG 16:
Austin, Brazoria, Chambers, Colorado, Fort Bend, Galveston, Harris, Liberty, Matagorda, Montgomery, Walker, Waller, Wharton
COG 17:
Calhoun, DeWitt, Goliad, Gonzales, Jackson, Lavaca, Victoria
COG 18:
Atascosa, Bandera, Bexar, Comal, Frio, Gillespie, Guadalupe, Karnes, Kendall, Kerr, Medina, Wilson
COG 19:
Jim Hogg, Starr, Webb, Zapata
COG 20:
Aransas, Bee, Brooks, Duval, Jim Wells, Kenedy, Kleberg, Live Oak, McMullen, Nueces, Refugio, San Patricio
COG 21:
Cameron, Hidalgo, Willacy
COG 22:
Cooke, Fannin, Grayson
COG 23:
Bell, Coryell, Hamilton, Lampasas, Milam, Mills, San Saba
COG 24:
Dimmit, Edwards, Kinney, La Salle, Maverick, Real, Uvalde, Val Verde, Zavala
32 La Paz Border Counties
- Brewster, Brooks, Cameron, Crockett, Culberson, Dimmit, Duval, Edwards, El Paso, Frio, Hidalgo, Hudspeth, Jeff Davis, Jim Hogg, Kenedy, Kinney, La Salle, McMullen, Maverick, Pecos, Presidio, Real, Reeves, Starr, Sutton, Terrell, Uvalde, Val Verde, Webb, Willacy, Zapata, Zavala (The 32 counties either touching the US - Mexico border or touching a county on the border)
15 Immediate Border Counties
- Brewster, Cameron, El Paso, Hidalgo, Hudspeth, Jeff Davis, Kinney, Maverick, Presidio, Starr, Terrell, Val Verde, Webb, Willacy, Zapata (The 14 counties touching the US - Mexico border, plus Willacy)
Age Adjustment Standards
Age group
1940 US
1970 US
2000 US
Birth-11m
15,343
17,151
13,818
1-4
64,718
67,265
55,317
5-14
170,355
200,508
145,565
15-24
181,677
174,406
138,646
25-34
162,066
122,569
135,573
35-44
139,237
113,614
162,613
45-54
117,811
114,265
134,834
55-64
80,294
91,480
87,247
65-74
48,426
61,195
66,037
75-99+
20,073
37,547
60,350
Total
1,000,000
1,000,000
1,000,000
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.
Deaths
- The number of deaths. Vitalnet analyzes "underlying cause" mortality data. The "underlying cause" is *the disease or injury that initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury*. A single underlying cause is assigned to each death. A separate program, MultiCod, analyzes multiple cause mortality data. Also, Vitalnet uses "place of residence" mortality data. The "place of residence" is the location where the death occurred. The deaths are assigned to the usual county of residence of the deceased, without regard to the location where the death occurred.
Death Rate
- Deaths per 100,000 population. This rate may be used to compare the burden of disease between different groups.
Mean age of death
- Mean (average) age of deceased. A lower mean may indicates more premature mortality. However, a younger population will have a lower mean age of death, even if probabilities of death are the same in all age categories.
Age-Adjusted Rate
- The number of deaths per 100,000 population, adjusted to a standard population (such as US 1940), by the direct method. Age-adjusted rates are often better for making comparisons than crude rates, because they adjust for differences in age distribution between populations. An age-adjusted rate is a single summary measure. Be aware that it may mask trends detectable by examining age-specific rates. Age-adjusted rates are synthetic rates that are only useful in comparison with other age-adjusted rates. Age-adjusted rates are used to compare one area or population to another because age distribution is controlled for in the calculations. Age-adjusted rates are not typically calculated for individual age ranges, such as 40-49, and Vitalnet does not do so.
Standardized Mortality Ratio (SMR)
- The ratio of the number of observed deaths to the number that were expected. Also called indirect adjustment. An SMR greater than 1 indicates more events were observed than expected. The number expected is derived by applying age-specific standard rates for a general population (Texas) to the population in the area under study. The standard rates can include all races, or only the races being studied in the smaller area (race-specific). Similarly, the standard rates can include both male and female, or only the sex being studied in the smaller area (sex-specific). A standardized mortality ratio is a single summary measure. It may mask trends detectable by examining age-specific rates. Standardized mortality ratios are not usually calculated for individual age ranges, such as 40-49, and Vitalnet does not calculate such rates.
Years of Potential Life Lost (YPLL)
- The sum of the years of life lost by persons who suffered early deaths, used to measure premature mortality. Early death is usually defined as death occurring before the age of 65 (the YPLL age limit). For example, death at age 40 (40.5) results in 24.5 YPLL to age 65.
YPLL Rate
- YPLL per 100,000 population in the appropriate age category. For example, the YPLL rate to age 65 is calculated as follows: (YPLL to age 65) / (population for age group 0-64). YPLL rate is seldom used.
Age-Adjusted Rate Methodology
- 1) Determine age-specific rates in the Study population. (Set age-specific rate to zero if age-specific population is zero.) 2) Multiply age-specific rates by Standard age-specific populations, such as 1940 US. 3) Sum the results from the previous step. 4) Divide the sum by the total size of the Standard population.
SMR Methodology
- 1) Determine the age-specific death rate for each age group in the Standard (State) population. The age-specific rates may be based on all races combined, or just on the races that are selected (race-specific). 2) For each age group, multiply the age-specific rate by the number of people in that group in the Study population. 3) Sum the results from the previous step. This is the expected number of deaths. 4) Divide the actual number of deaths observed by the number expected (SMR = observed / expected). For example, if 10 deaths were expected in a county (based on the State rate), and 20 occurred, the SMR is 2.
YPLL Methodology
- 1) For each death, calculate the difference between the age at death and age 65 (or other chosen limit). For example, death at age 40 (40.5) results in 24.5 YPLL to age 65. 2) Sum the results of the previous step.
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
Rothman and Boice
- This method is for SMRs. Rothman KJ and Boice JD (1979): Epidemiologic analysis with a programmable calculator. NIH Publication No. 79-1649, Washington, DC: U.S Department of Health.
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
Data Sources and Limitations
VitalWeb Ajax uses data from authoritative sources.
Mortality data
- All Texas mortality data were provided by the Bureau of Vital Statistics, Texas Department of Health.
Population data
- Pre-1990 population data are from the Center for Health Statistics, Texas Department of Health. Population data for 1990 and subsequent years are from the State Population Center at Texas A&M.
Links to Related Resources
Internet resources related to ICD-10 Underlying Cause Deaths:
Bureau of Vital Statistics
- Texas Department of State Health Services
Center for Health Statistics
- Texas Department of State Health Services
Whom to Contact
For additional assistance with analyzing and interpreting the data, contact:
Mortality data -
Bureau of Vital Statistics
- 512-458-7509
Mortality data -
Center for Health Statistics
- 512-458-7261
Population data -
Center for Health Statistics
- 512-458-7261
Legal Information
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Documentation produced: "Aug 5 2019" -
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