Community Health Nursing Resources
Health Statistics: Data maintained by the Center for Health Statistics (CHS)
- Births
- Deaths
- Fetal deaths
- Matched infant death-birth data
- Health-related behaviors survey (NJBRFS) data (e.g., seat belt use, cancer screening, smoking)
- Violent death data: death certificate data enhanced by other data sources regarding events leading up to the death. Violent death encompasses homicide, suicide, all firearm-related deaths, and injury deaths of undetermined intent.
Other data sources outside CHS
Datasets are maintained by the office that has programmatic responsibility for that particular topic. While we occasionally report some non-CHS data, CHS does not collect, analyze, or maintain any databases not listed above. To get the most up-to-date data and answers to questions about these data, please visit the responsible programs' websites.
Datasets are maintained by the office that has programmatic responsibility for that particular topic. While we occasionally report some non-CHS data, CHS does not collect, analyze, or maintain any databases not listed above. To get the most up-to-date data and answers to questions about these data, please visit the responsible programs' websites.
Data quality
- Municipality-level death data
Street addresses were not entered into the electronic file of death certificates until 2004. Thus, death data prior to 2004 are not published at the municipality level. - Municipality-level rates
Population estimates for municipalities by age, race, Hispanic ethnicity, and sex are only available in Census years. In non-Census years, estimates are only given for the total population of each municipality. Therefore, age-adjusted rates, teen birth rates, and other kinds of rates cannot be calculated for municipalities. - Rates based on small numbers
In keeping with NCHS guidelines regarding statistical reliability, we do not publish rates based on fewer than 20 events (births, deaths, etc.) for any geographic level. See the Random Variation section of the Technical Notes of the NCHS report Deaths: Final Data for 2009 for a full explanation. Multiple years of data may be combined to compute rates when a single year of data yields fewer than 20 events.
Methods
How to calculate crude rates
A rate is a measure of some event, disease, or condition in relation to a unit of population, along with some specification of time.
Crude rate = # of events (births, deaths, marriages, etc.)
population or # “at risk” for the event
Visit NAPHSIS’s website for definitions of various types of crude rates.
How to calculate age-adjusted death rates
Age-adjusted death rates are computed to eliminate the effect of age on crude death rates for purposes of comparison with other rates. This is done by applying age-specific rates to a standard population. The resulting death rate in the standard population is age-adjusted and can be compared to other death rates age-adjusted to the same standard population. Since 1999, all age-adjusted rates have been calculated using the 2000 standard population. Other common standards that have been in use in the past are the 1940 and 1970 standards. In the following age-adjustment Excel worksheet, enter the appropriate age-specific deaths and population for the year, geographic area, race, sex, and/or cause of death of interest in the gray cells and the resulting age-adjusted rate will appear in the red cell.
Age-adjustment Worksheet based on the 2000 Standard Population (Excel)
How to calculate crude rates
A rate is a measure of some event, disease, or condition in relation to a unit of population, along with some specification of time.
Crude rate = # of events (births, deaths, marriages, etc.)
population or # “at risk” for the event
Visit NAPHSIS’s website for definitions of various types of crude rates.
How to calculate age-adjusted death rates
Age-adjusted death rates are computed to eliminate the effect of age on crude death rates for purposes of comparison with other rates. This is done by applying age-specific rates to a standard population. The resulting death rate in the standard population is age-adjusted and can be compared to other death rates age-adjusted to the same standard population. Since 1999, all age-adjusted rates have been calculated using the 2000 standard population. Other common standards that have been in use in the past are the 1940 and 1970 standards. In the following age-adjustment Excel worksheet, enter the appropriate age-specific deaths and population for the year, geographic area, race, sex, and/or cause of death of interest in the gray cells and the resulting age-adjusted rate will appear in the red cell.
Age-adjustment Worksheet based on the 2000 Standard Population (Excel)
How to calculate YPLL (years of potential life lost)
Years of potential life lost (YPLL) is a measure of the number of years not lived by each individual who died before reaching a predetermined age, usually 65 or 75. (NCHS switched to YPLL before 75 in 1996 and CHS switched in 2000.) This measure weights deaths at younger ages more heavily than deaths at older ages; the younger the age at death, the greater the number of years of potential life lost. The YPLL for a population is computed as the sum of all the individual YPLL for individuals who died during a specific time period. In the following YPLL Excel worksheets, enter the appropriate age-specific numbers of deaths and the population under age 65 or 75 for the year, geographic area, race, sex, and/or cause of death of interest in the gray cells and the resulting YPLL rate will appear in the red cell.
YPLL Before Age 65 YPLL Before Age 75
How to calculate life expectancy
Life expectancy is the average number of years of life remaining to a person at a particular age and is often used as a summary measure of the health status of a population. The most commonly used life expectancy measure is life expectancy at birth, the number of years a person born in a given year is expected to live. Calculation of life expectancy requires birth, death, and population data. It is recommended that there be at least 700 deaths in a given geographic area/race/sex group when calculating life expectancy. If there are fewer than 700 deaths, multiple years of data may be combined to give life expectancy for a range of years. Life expectancy does not change much from year to year and random variation can cause life expectancy to decrease slightly on occasion, therefore the overall trend is key.
In the following life expectancy Excel workbook, there are separate worksheets for all races and both sexes, males, females, whites, blacks, white males, white females, black males, and black females. The k-values in gray in the Qx column (column F) differ for each race and sex as does the value of s (cell D129), therefore the appropriate worksheet must be used for each race/sex combination. These values change annually and are available in the Methodology section of the Technical Notes of the annual United States Life Tables publications.
In the worksheets, input the appropriate age-specific number of deaths (column B) and population (column E) for the geographic area, race, and/or sex of interest in the gray cells. Note that cell B85 is the number of deaths of those aged 85 and over. The worksheet takes into account deaths of unknown age, so enter those in B121. In cells D124-D127, enter the geographic area/race/sex-specific numbers of infant deaths this year, infant deaths born last year, births this year, and births last year, respectively. The resulting life expectancy will appear in the red cell.
Life Tables with 2000 k- and s-values
If single year of age population data are not available for the geographic area of interest, an abridged life table may be used. The abridged life table uses deaths and population in 5-year age groups. Unlike the complete life table, it does not require separate factors for each race and sex, nor does it take into account unknown age, births, or infant deaths. It does, however, require at least one death in each age group and at least 700 total deaths are recommended for accuracy. If there are fewer than 700 deaths or there are no deaths in at least one age group, multiple years of data may be combined to give life expectancy for a range of years. In the following abridged life expectancy Excel worksheet, input the appropriate age-specific number of deaths (column B) and population (column C) for the geographic area, race, and/or sex of interest in the gray cells. The resulting life expectancy will appear in the red cell.
Years of potential life lost (YPLL) is a measure of the number of years not lived by each individual who died before reaching a predetermined age, usually 65 or 75. (NCHS switched to YPLL before 75 in 1996 and CHS switched in 2000.) This measure weights deaths at younger ages more heavily than deaths at older ages; the younger the age at death, the greater the number of years of potential life lost. The YPLL for a population is computed as the sum of all the individual YPLL for individuals who died during a specific time period. In the following YPLL Excel worksheets, enter the appropriate age-specific numbers of deaths and the population under age 65 or 75 for the year, geographic area, race, sex, and/or cause of death of interest in the gray cells and the resulting YPLL rate will appear in the red cell.
YPLL Before Age 65 YPLL Before Age 75
How to calculate life expectancy
Life expectancy is the average number of years of life remaining to a person at a particular age and is often used as a summary measure of the health status of a population. The most commonly used life expectancy measure is life expectancy at birth, the number of years a person born in a given year is expected to live. Calculation of life expectancy requires birth, death, and population data. It is recommended that there be at least 700 deaths in a given geographic area/race/sex group when calculating life expectancy. If there are fewer than 700 deaths, multiple years of data may be combined to give life expectancy for a range of years. Life expectancy does not change much from year to year and random variation can cause life expectancy to decrease slightly on occasion, therefore the overall trend is key.
In the following life expectancy Excel workbook, there are separate worksheets for all races and both sexes, males, females, whites, blacks, white males, white females, black males, and black females. The k-values in gray in the Qx column (column F) differ for each race and sex as does the value of s (cell D129), therefore the appropriate worksheet must be used for each race/sex combination. These values change annually and are available in the Methodology section of the Technical Notes of the annual United States Life Tables publications.
In the worksheets, input the appropriate age-specific number of deaths (column B) and population (column E) for the geographic area, race, and/or sex of interest in the gray cells. Note that cell B85 is the number of deaths of those aged 85 and over. The worksheet takes into account deaths of unknown age, so enter those in B121. In cells D124-D127, enter the geographic area/race/sex-specific numbers of infant deaths this year, infant deaths born last year, births this year, and births last year, respectively. The resulting life expectancy will appear in the red cell.
Life Tables with 2000 k- and s-values
If single year of age population data are not available for the geographic area of interest, an abridged life table may be used. The abridged life table uses deaths and population in 5-year age groups. Unlike the complete life table, it does not require separate factors for each race and sex, nor does it take into account unknown age, births, or infant deaths. It does, however, require at least one death in each age group and at least 700 total deaths are recommended for accuracy. If there are fewer than 700 deaths or there are no deaths in at least one age group, multiple years of data may be combined to give life expectancy for a range of years. In the following abridged life expectancy Excel worksheet, input the appropriate age-specific number of deaths (column B) and population (column C) for the geographic area, race, and/or sex of interest in the gray cells. The resulting life expectancy will appear in the red cell.
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North Jersey Health Collaborative
The North Jersey Health Collaborative is a partnership of approximately 100 organizations sharing data and engaging in health improvement planning for collective impact to improve health in North Jersey- Morris, Union, Warren, and Sussex counties.
The North Jersey Health Collaborative is a partnership of approximately 100 organizations sharing data and engaging in health improvement planning for collective impact to improve health in North Jersey- Morris, Union, Warren, and Sussex counties.
