Principles of Epidemiology Dona SchneiderDona Schneider, PhD, MPH, FACE E J Bloustein School of...
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Transcript of Principles of Epidemiology Dona SchneiderDona Schneider, PhD, MPH, FACE E J Bloustein School of...
Principles of Epidemiology
Dona Schneider, PhD, MPH, FACE
E J Bloustein School of Planning and Public Policy
Rutgers University, NJ, USA
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About the Author
Dona Schneider
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Known Risk Factors for Cancer
Smoking
Dietary factors
Obesity
Exercise
Occupation
Genetic susceptibility
Infectious agents
Reproductive factors
Socioeconomic status
Environmental pollution
Ultraviolet light
Radiation
Prescription Drugs
Electromagnetic fields
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Preliminary Topics Data sources and limitations for cancer
epidemiology
How much cancer is occurring?
How does occurrence vary within the population?
How do cancer rates in your area compare to that
in other areas?
Data sources and limitations for
cancer epidemiology
Review U.S. Census, U.S. Vital Statistics, SEER and NJCR data
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Some other raceOther
Other Pacific Islander
Other Asian
Samoan
Guamanian or Chamorro
Vietnamese
Native HawaiianHawaiian
KoreanKorean
Asian Indian
FilipinoFilipino
JapaneseJapaneseJapaneseJapanese
American Indian or Alaska NativeIndian (Amer.)IndianIndian
ChineseChineseChineseChinese
QuadroonQuadroon1
Black, African American, or NegroNegro or BlackBlack of Negro decentBlackBlack
WhiteWhiteWhiteWhiteWhite
200021970190018701860
Race Categories in the Census 1860-2000
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Revised racial and ethnic standards (effective as
of the 2000 decennial census) have 5 minimum
categories for data on race and 2 for ethnicity
Other Federal programs should adopt standards
no later than January 1, 2003
Revision of Statistical Policy Directive No. 15, Race and Ethnic Standards for Federal Statistics and Administrative Reporting
Office of Management and Budget (OMB)
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American Indian or Alaska Native
A person having origins in any of the original people of North and South America (including Central America) and who maintain tribal affiliation or community attachment
Asian
A person having origins in any of the original people of the Far East, Southeast Asia of the Indian subcontinent including for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand and Vietnam
OMB Race Categories
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Black or African American
A person having origins in any of the black racial groups of Africa. Terms such as “Haitian” or “Negro” can be used in addition to “Black or African American”
Native Hawaiian or Other Pacific Islander
A person having origins in any of the original peoples of Hawaii, Guam, Samoa or other Pacific Islands
White
Persons having origins in any of the original peoples of Europe, the Middle East or North Africa
OMB Race Categories (continued)
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Census Data Changes to the Race Question in the 2000 Census:
The Asian and Pacific Islander (API) category was split:a) Asiansb) Native Hawaiian and Other Pacific Islanders (NHOPI)
The category American Indian, Eskimo, Aleut (AIEA) was changed to American Indian or Alaskan Native (AIAN)
Respondents could select more than one race.
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U.S. Census Bureau
http://www.census.gov/
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Vital Statistics
Maintained by the National Center for Health Statistics (http://www.cdc.gov/nchs/nvss.htm)
States report the following to NCHS: Birth data (Natality) Death data (Mortality) Marriage data (no longer collected) Divorce data (no longer collected)
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CDC Wonder
http://wonder.cdc.gov/
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Registries for Morbidity Data
New Jersey Cancer Registryhttp://www.state.nj.us/health/cancer/statistics.htm
SEER: Surveillance, Epidemiology, and End Resultshttp://seer.cancer.gov/
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Data Limitations
Little data is available at the local level
Problem of small numbers
Data may not be collected uniformly (race category differences, etc.)
People are mobile
Cancer has a long lag time
How much cancer is occurring?
Understand incidence rates and prevalence
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Measuring Epidemiological Outcomes
A proportion with the specification of time
(e.g. deaths in 2000 / population in 2000)Rate
A ratio where the numerator is included in the denominator (e.g. males / total births)
Proportion
Relationship between any two numbers
(e.g. males / females)Ratio
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Definitions
Incidence is the rate of new cases of a
disease or condition in a population at risk
during a time period
Prevalence is the proportion of the
population affected
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Incidence
Incidence is a rate
Calculated for a given time period (time interval)
Reflects risk of disease or condition
Incidence =
Number of new cases during a time period
Population at risk during that time period
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Prevalence
Prevalence is a proportion
Point Prevalence: at a particular instant in time
Period Prevalence: during a particular interval of time (existing
cases + new cases)
Prevalence =
Number of existing cases
Total number in the population at risk
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Prevalence = Incidence Duration
Prevalence depends on the rate of occurrence (incidence)
AND the duration or persistence of the disease
At any point in time:
More new cases (increased risk) yields more existing cases
Slow recovery or slow progression increases the number of affected individuals
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Incidence/Prevalence Example
For male residents of Connecticut:
The incidence rate for all cancers in 1982
431.9 per 100,000 per year
The prevalence of all cancers on January 1, 1982
1,789 per 100,000 (or 1.8%)
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Proportional cancer incidence by gender, US 2000
How does occurrence vary
within the population?
Understand measures of association and difference
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Outcome Measures Compare the incidence of disease among people who
have some characteristic with those who do not
The ratio of the incidence rate in one group to that in
another is called a rate ratio or relative risk (RR)
The difference in incidence rates between the groups
is called a risk difference or attributable risk (AR)
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Calculating Outcome Measures
Outcome
D
B
No Disease
(controls)
IN = C / (C+D)CNot Exposed
IE = A / (A+B)AExposed
IncidenceDisease
(cases)Exposure
Relative Risk = IE / IN
Attributable Risk = IE - IN
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1,1001,000100
730
370
Total
Lung Cancer
700
300
No
30/730 = 41 per 100030Non-smoker
70/370 = 189 per 100070Smoker
IncidenceYesExposure
Relative Risk = IE / IN = 189 / 41 = 4.61
Attributable Risk = IE - IN = 189 - 41 = 148 per 1000
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Smokers are 4.61 times more likely than nonsmokers to develop lung cancer
148 per 1000 smokers developed lung cancer because they smoked
Relative Risk = IE / IN = 189 / 41 = 4.61
Attributable Risk = IE - IN = 189 - 41 = 148 per 1000
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RR < 1 RR = 1 RR > 1
Risk comparison between exposed and unexposed
Risk for disease is lower in the
exposed than in the unexposed
Risk of disease are equal for exposed and unexposed
Risk for disease is higher in the exposed than in the unexposed
Exposure as a risk factor for the disease?
Exposure reduces disease
risk
(Protectivefactor)
Particular exposure is not a
risk factor
Exposure increases
disease risk(Risk factor)
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Annual Death Rates for Lung Cancer and Coronary Heart Disease
by Smoking Status, Males
1000 – 500 = 500 per 100,000
127.2 – 12.8 = 114.4 per 100,000
AR
1000 / 500 = 2127.2 / 12.8 = 9.9RR
50012.8Non-smoker
1,000127.2Smoker
Coronary Heart DiseaseLung CancerExposure
Annual Death Rate / 100,000
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Summary
The risk associated with smoking is lower for
CHD (RR=2) than for lung cancer (RR=9.9)
Attributable risk for CHD (AR=500) is much higher
than for lung cancer (AR=114.4)
In conclusion: CHD is much more common
(higher incidence) in the population, thus the
actual number of lives saved (or death averted)
would be greater for CHD than for lung cancer