California ICD-10 Underlying Cause Deaths
VitalWeb Wizard
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Table of Contents


  1. Introduction

    Wizard Starts in "Beginner" Mode

    Wizard also Runs in "Expert" Mode

  2. Basic Table Layout

    Main Statistic

    Table Axes (Rows and Columns)

    Statistic / Axis Conflicts

  3. Data Variables

    Categorical Variables

    Range Variables

    Statistic / Variable Conflicts

    Other Settings

  4. 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

  5. Map Settings

    Map Coloring

    Map Layout

    Map Color Palettes

  6. Producing and Using Results

    Getting Results

    Viewing Results

    Printing Results

    Saving Results

    When Charts and Maps are Made

  7. Other Information

    Glossary

    Race Categories

    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





Wizard Starts in "Beginner" Mode


Screenshot of Basic Wizard

Instructions for Using Step-by-Step Mode:

1. Make selections - At each step, make selections.
2. Go to next step - Click "Next Step" to move forward.
3. Make output - At last step, produce output table (or map).
4. View output - Results appears in the same window as the wizard.
5. Return to wizard - Click browser "Back" button after viewing output.
6. Continue - Click "Restart" to start wizard again at first step.

• To go back a step, click "Previous Step" (not browser "Back" button).
• You may switch to Jump-to-Step mode (see next page) at any time.



Wizard also Runs in "Expert" Mode


Screenshot of Advanced Wizard

Instructions for Using Jump-to-Step Mode:

1. Jump - Click on step name from top or right.
2. Select - At the chosen step, make selections.
3. Make Output - When ready, click "Make Table".
4. View Output - Results appear in current window.
5. Return to Wizard - Click browser "Back" button.
6. Continue - Keep making selections and output.

• To go back a step, click step name, not "Back" button.
• You may switch to Step-by-Step mode at any time.
• You may switch to designing a map at any time.



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 (above)



Table Axes (Rows and Columns)


  Age
Year 0-19 20-39 40-59 60-79 80+
1990 100 120 140 160 180
1991 120 140 160 180 200
1992 140 160 180 200 220

Rows - Horizontal lines of data, such as 1991 row.
Sorting - Can sort rows low to high, or high to low.
Columns - Go up and down, such as 0-19 column.
Multi-Tables - "ByVar". Make a series of tables.

Selecting - Click on desired setting, such as "Year".






Example Row, Column, or ByVar Selector (above)



Statistic / Axis Conflicts


If a conflict between Main Statistic and Axis Variable:

• Vitalnet alerts you of the conflict (mismatch).
• Vitalnet prevents contradictory results.

Examples of conflicting settings:

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



Selecting Data Variables


Data variables include - age, race, sex, year, cause of death, county of residence.

Selecting - Click on one or more values.



Example Data Variable Selector (Age) (above)



Selecting Data Variable Groupings


Certain data variables allow different "groupings".
For example, 5-year or 10-year age groups.

To change the grouping in actual interface:

1. Click on desired grouping.
2. Click on "Select" button.







Example Data Grouping Selection (above)



Statistic / Variable Conflicts


No Left Turn Sign 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 - 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


Tabular chart


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 (14 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


Go Sign To produce results:

• Click "Make Map" or "Make Table".
Step-by-Step Wizard - Last step.
Jump-toStep Wizard - Anytime.

• Program sends query to server.
• Results should return in seconds.
• Results appear in window Wizard is running in.



Viewing Results


Binoculars After you click "Make Map" or "Make Table", results are sent to the window where the Wizard is running.

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.
To do another analysis, click browser "Back" button.



Printing Results


Printer 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


File Cabinet 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



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.

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.

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 - 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.

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.



Race Categories


California Race Groupings Used
1999 and earlier 2000 and later
Five Groupings:
- American Indian
- Black
- Hispanic
- White
- Asian / Pacific Islander
Seven Groupings:
- American Indian
- Black
- Hispanic
- White
- Asian
- Pacific Islander
- Two or More Races




County Groupings


Health Service Area 1: Butte, Colusa, Del Norte, Glenn, Humboldt, Lake, Lassen, Mendocino, Modoc, Plumas, Shasta, Siskiyou, Tehama, Trinity
 
Health Service Area 2: El Dorado, Nevada, Placer, Sacramento, Sierra, Sutter, Yolo, Yuba
 
Health Service Area 3: Napa, Solano, Sonoma
 
Health Service Area 4: Marin, San Francisco, San Mateo
 
Health Service Area 5: Alameda, Contra Costa
 
Health Service Area 6: Alpine, Amador, Calaveras, Merced, San Joaquin, Stanislaus, Tuolumne
 
Health Service Area 7: Santa Clara
 
Health Service Area 8: Monterey, San Benito, San Luis Obispo, Santa Cruz
 
Health Service Area 9: Fresno, Kern, Kings, Madera, Mariposa, Tulare
 
Health Service Area 10: Santa Barbara, Ventura
 
Health Service Area 11: Los Angeles
 
Health Service Area 12: Inyo, Mono, Riverside, San Bernardino
 
Health Service Area 13: Orange
 
Health Service Area 14: Imperial, San Diego



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
75-84 17,303 30,112 44,842
85-99+ 2,770 7,435 15,508
Total Million Million Million




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 (California) 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 Wizard uses data from authoritative sources.

Mortality data - All California mortality data were provided by the Department of Health Services / Office of Health Information and Research.

Population data - All California population data were provided by the Department of Finance.



Links to Related Resources


Internet resources related to ICD-10 Underlying Cause Deaths:

Center for Health Statistics - California Department of Health Services



Whom to Contact


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

Center for Health Statistics - 916-552-8096


Legal Information


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Documentation produced: "Apr 1 2023" - Contact EHDP