Cancer is a leading cause of death in the United States. There are many different types of cancers. They affect different people and populations.
This module will review several important terms you learned in EXCITE. These terms and others are also in the EXCITE glossary. (You can find them at http://www.cdc.gov/excite, click on "Glossary" or go to the glossary at the end of this Web site.)
When you have finished this module, you will be ready to study cancer rates in the United States through two Web sites: SEER (http://seer.cancer.gov/) and NPCR (http://www.cdc.gov/cancer/npcr/index.htm).
Epidemiology is the study of populations to learn:
Public health officials and epidemiologists work together. They track disease rates in communities to learn how to best prevent and treat disease.
The National Cancer Institute tracks cancer rates in 14 different places around the country. The program is called Surveillance, Epidemiology, and End Results (SEER). The Centers for Disease Control and Prevention (CDC) also has a cancer tracking program as part of its National Program of Cancer Registries (NPCR). CDC is working with at least 45 states to improve tracking of cancer rates in states that have not been tracked at all or states that have not tracked as well as they could have. Starting in Fall 2002, CDC and the National Cancer Institute will jointly have melanoma statistics for 75 percent of the US population. These statistics will be posted at http://www.cdc.gov/cancer/npcr/index.htm
Understanding the following terms will help you use the SEER and NPCR sites.
Incidence measures the frequency with which a health problem occurs. The health problem could be a new injury or case of illness, for example. Incidence is measured for a given population during a given period of time. It is a rate expressed as a fraction.
Here's how we find incidence: We divide the number of new cases by the total population at risk. So the numerator is the number of new cases occurring in the population during a given period of time. And the denominator is the total population at risk during that time.
For example: Seventeen (17) people out of a community of 1,000 get swine flu in November of 2001. The incidence of swine flu is 17 per 1,000 persons for 2001.
Mortality measures the rate of death in a population during a given period of time. It is expressed as a fraction.
For example: Fifty (50) people out of a community of 1,000 die in 2002. The mortality rate is 50 per 1,000 persons for 2002.
An age-adjusted mortality rate has been changed in order to make a comparison. The change removes the effect of different age distributions when comparing death rates in two or more populations. We age-adjust mortality rates in order to see the effect of factors other than age.
(See the example below under "Mortality Rate, Age-specific" for how we calculate age-adjusted rates.)
"Age distribution" is the proportion of young, middle-aged, and old people in a population. Age-adjusted rates can help when you compare two groups that have different proportions of people in different age groups.
Why does age distribution matter when looking for causes of death? Most health problems do not occur at the same rate in every age group. For example, younger people are more likely to die from accidents and violent causes. Older people are more likely to die from heart disease, cancer, and strokes. For a given health problem, certain age groups have a higher or lower risk.
Let's say we compare the unadjusted, or "crude" mortality rate from heart disease in one area with the crude mortality rate from heart disease in another. Any difference could simply be due to a difference in age distribution. One population may have a larger percentage of older people. Older people have a higher risk for death from heart disease.
We don't want the effect of age distribution to mask other factors when we try to compare rates of a health problem in different groups. One of these other factors may be placing one group at greater risk. (In the case of heart disease, other factors would include things like diet and exercise.)
Look at the "population pyramids" below. They show the age distribution in Country A and Country B.
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Compare the age distributions for Country A and Country B:
Think about what you know about which age groups are at higher risk for heart disease.
Consider how age distribution can affect the health and economics of a given country, now and 20 years from now.
An age-specific mortality rate is the death rate for a particular age group.
Here's how we find the age-specific mortality rate: we divide the number of deaths in the age group by the total number of people in the age group. So the numerator is the number of deaths in the age group. And the denominator is the number of people in that age group.
For example: Fourteen (14) people in our sample community of 1,000 died in the year 2000. Twelve (12) of them were aged 60 or older. There were 300 people aged 60 or older living in the community at the time. The crude death rate for the community is only 14/1,000. But the age-specific death rate for people aged 60 or older is 12/300.
Let's take the example of comparing mortality rates from heart disease in Country A and Country B. The "age-specific mortality rates for individuals 60 and older" would give us a better comparison than the crude mortality rates. That's because the age-specific rates let us compare the risk of death from heart disease in older adults in both countries.
Here is a problem taken from the Injury Prevention website at http://www.injurypreventionweb.org/info/data/ratenote.htm.* This is an example of how we use age-specific rates to find age-adjusted rates:
Age-specific Rates to Calculate Age-adjusted Rates
We have the following information about two communities:
|Age-specific death rates per 1,000 population|
From this information
we can find the crude death rates (CDR), as follows:
CDR in A = (1/2)(4) + (1/2)(16) = 10 per 1,000
CDR in B = (2/3)(5) + (1/3)(20) = 10 per 1,000
Note that the risk of dying is lower for County A in both age groups (4 vs. 5 and 16 vs. 20). But the crude death rates are the same in both counties. This is because County A has an older population than County B.
Here's how we find the age-adjusted rate: We apply each age-specific rate to the age distribution of a third "Standard Population." (Note that we do NOT compare it to the age distribution in the county from which the death rate arose. Nor do we compare it to the comparison county.)
For this example, our
standard population is one-third young and two-thirds old. (We chose this
age distribution randomly.) We calculate the age-adjusted death rate (AADR)
AADR in A = (1/3)(4) + (2/3)(16) = 12 per 1,000
AADR in B = (1/3)(5) + (2/3)(20) = 15 per 1,000
We can now compare the risk of dying for these communities without being influenced by differences in their age distributions. Rates are age-adjusted to remove the effects of age in order to see the effect of other factors. But you should ALWAYS look at the overall crude rates first. Why? Because crude rates represent real events in the population. An adjusted rate gives an accurate COMPARISON, but does not reveal the underlying raw data.
Cause-specific mortality rate is the rate of death from a particular cause.
Here's how we find the cause-specific mortality rate: We divide the number of deaths from a certain cause by the number of people in the population. So the numerator is the number of deaths linked to a certain cause in a population. And the denominator is the size of the population.
For example: Ten (10) people out of our sample community of 1,000 die of heart disease in the year 2000. The cause-specific mortality rate is 10/1,000
Prevalence is how widespread a certain disease, chronic condition, or type of injury is in a population. See below for different ways of expressing prevalence.
Period prevalence is the amount of a certain disease, chronic condition, or type of injury in a population over a specified period of time. For example, the period may be for a year.
Point prevalence is the amount of a certain disease, chronic condition, or type of injury in a population at a single point in time. For example, the prevalence may be for January 1, 2002.
Prevalence rate is the proportion of people in a population who have a certain disease, chronic condition, injury, or attribute. We can calculate prevalence rate:
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This page last reviewed April 24, 2007
United States Department of Health Human Services