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Principles of Epidemiology

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Title: Principles of Epidemiology


1
Principles of Epidemiology
  • Dona Schneider, PhD, MPH, FACE
  • E J Bloustein School of Planning and Public
    Policy
  • Rutgers University, NJ, USA

2
About the Author
  • Dona Schneider

3
Known Risk Factors for Cancer
  • Reproductive factors
  • Socioeconomic status
  • Environmental pollution
  • Ultraviolet light
  • Radiation
  • Prescription Drugs
  • Electromagnetic fields
  • Smoking
  • Dietary factors
  • Obesity
  • Exercise
  • Occupation
  • Genetic susceptibility
  • Infectious agents

4
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?

5
Data sources and limitations for cancer
epidemiology
  • Review U.S. Census, U.S. Vital Statistics, SEER
    and NJCR data

6
Race Categories in the Census 1860-2000
20002
1970
1900
1870
1860
White
White
White
White
White
Negro or Black
Black
Black
Black of Negro decent
Black, African American, or Negro
Quadroon
Quadroon1
Chinese
Chinese
Chinese
Chinese
American Indian or Alaska Native
Indian (Amer.)
Indian
Indian
Japanese
Japanese
Japanese
Japanese
Filipino
Filipino
Asian Indian
Korean
Korean
Native Hawaiian
Hawaiian
Vietnamese
Guamanian or Chamorro
Samoan
Other Asian
Other Pacific Islander
Some other race
Other
7
Office of Management and Budget (OMB)
Revision of Statistical Policy Directive No. 15,
Race and Ethnic Standards for Federal Statistics
and Administrative Reporting
  • 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

8
OMB Race Categories
  • 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

9
OMB Race Categories (continued)
  • 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

10
Census Data
  • Changes to the Race Question in the 2000 Census
  • The Asian and Pacific Islander (API) category was
    split
  • a) Asians
  • b) 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.

11
U.S. Census Bureau
  • http//www.census.gov/

12
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)

13
CDC Wonder
  • http//wonder.cdc.gov/

14
Registries for Morbidity Data
  • New Jersey Cancer Registry
  • http//www.state.nj.us/health/cancer/statistics.ht
    m
  • SEER Surveillance, Epidemiology, and End Results
  • http//seer.cancer.gov/

15
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

16
How much cancer is occurring?
  • Understand incidence rates and prevalence

17
Measuring Epidemiological Outcomes
Relationship between any two numbers (e.g. males
/ females)
Ratio
A ratio where the numerator is included in the
denominator (e.g. males / total births)
Proportion
A proportion with the specification of time (e.g.
deaths in 2000 / population in 2000)
Rate
18
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

19
Incidence
Number of new cases during a time period
Incidence
Population at risk during that time period
  • Incidence is a rate
  • Calculated for a given time period (time
    interval)
  • Reflects risk of disease or condition

20
Prevalence
Number of existing cases
Prevalence
Total number in the population at risk
  • Prevalence is a proportion
  • Point Prevalence at a particular instant in time
  • Period Prevalence during a particular interval
    of time (existing cases new cases)

21
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

22
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)

23
Proportional cancer incidence by gender, US 2000
24
How does occurrence vary within the population?
  • Understand measures of association and difference

25
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)

26
Calculating Outcome Measures
Outcome
No Disease (controls)
Incidence
Disease (cases)
Exposure
IE A / (AB)
B
A
Exposed
IN C / (CD)
D
C
Not Exposed
Relative Risk IE / IN
Attributable Risk IE - IN
27
Lung Cancer
Total
No
Incidence
Yes
Exposure
370
300
70
Smoker
70/370 189 per 1000
30/730 41 per 1000
730
700
30
Non-smoker
1,100
100
1,000
Relative Risk IE / IN 189 / 41 4.61
Attributable Risk IE - IN 189 - 41 148 per
1000
28
Relative Risk IE / IN 189 / 41 4.61
Attributable Risk IE - IN 189 - 41 148 per
1000
  • Smokers are 4.61 times more likely than
    nonsmokers to develop lung cancer
  • 148 per 1000 smokers developed lung cancer
    because they smoked

29
(No Transcript)
30
Annual Death Rates for Lung Cancer and Coronary
Heart Disease by Smoking Status, Males
Annual Death Rate / 100,000
Coronary Heart Disease
Lung Cancer
Exposure
1,000
127.2
Smoker
500
12.8
Non-smoker
1000 / 500 2
127.2 / 12.8 9.9
RR
AR
127.2 12.8 114.4 per 100,000
1000 500 500 per 100,000
31
Summary
  • The risk associated with smoking is lower for CHD
    (RR2) than for lung cancer (RR9.9)
  • Attributable risk for CHD (AR500) is much higher
    than for lung cancer (AR114.4)
  • 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
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