Transcript PH Surveillance + Basic Survey Methods

Evidence-Based Public Health: A
Course in Chronic Disease
Prevention
MODULE 3:
Quantifying the Issue
Anjali Deshpande
March 2013
Learning Objectives
1. To measure and characterize disease
frequency in defined populations
2. To find and use disease surveillance
data presently available on the Internet
2
Obesity Trends* Among U.S. Adults
BRFSS, 1990, 1999, 2008
(*BMI 30, or about 30 lbs. overweight for 5’4” person)
1999
1990
2008
No Data
<10%
10%–14%
15%–19%
20%–24%
25%–29%
≥30%
3
Percent obese high school students,
USA, 2009
4
Descriptive Epidemiology
How do we determine disease frequency
for a population?
Define disease
acute myocardial
infarction (AMI)
Define population at risk
CO residents
Select time frame
2009
5
Descriptive Epidemiology
How do we determine disease frequency
for a population?
Compute disease rate for year 2007
number with AMI
= 1,204
number at risk of having heart disease
= 4,842,770
6
Descriptive Epidemiology
How do we determine disease frequency
for a population?
Compute disease rate for year 2007
= 1,205 Colorado residents with AMI
4,842,770 Colorado residents
=
.000249 AMI / Coloradoan/ year
7
Descriptive Epidemiology
Rates are usually expressed as whole numbers for
populations at risk during specified periods:
.000249 AMI / Coloradoan/ year x 100,000 =
24.9 AMI / 100,000 Coloradoans/ year
Question: Can we follow every Coloradoan at risk of
developing AMI to identify those who develop AMI
during a one-year period?
8
Descriptive Epidemiology
Problems with estimating the population at risk
• It is difficult to follow each person in a
dynamic population for long periods
• A more precise way to deal with persons
moving in or out of a dynamic population
during the study period is to estimate
“person-time”
9
Descriptive Epidemiology
Actual “Person-years”
J
A
B
C
D
E
F
M
l
l
l
l = enters study
A
M
J
J
A
S
O
N
D
PY
O
1.00
0.75
0.25
0.75
0.25
3.00
X
+
l
O
l
O / + = leaves study
X
X = develops disease
10
Descriptive Epidemiology
Computing “person-time” allows for …
• persons who enter the population after the study
period begins,
•
•
persons who are “lost” during the study period, and
persons who develop the disease during the study
period and are no longer at risk of developing the
disease
11
Descriptive Epidemiology
Person-time can be computed by either ...
• counting the “person-time” contributed by each
person in the population during the study period, or
• multiplying the average size of the population at the
mid-point of the study period times the duration of
the study period.
12
Descriptive Epidemiology
Actual “Person-years”
J
A
B
C
D
E
F
M
l
l
l
l = enters study
A
M
J
J
A
S
O
N
D
PY
O
1.00
0.75
0.25
0.75
0.25
3.00
X
+
l
O
l
O / + = leaves study
X
X = develops disease
13
Descriptive Epidemiology
Estimated “Person-years”
J
A
B
C
D
E
l
l
l
F
M
A
M
J
J
A
S
O
N
D
PY
O
1.00
0.75
0.25
0.75
0.25
3.00
X
+
l
O
l
X
3 persons x 1 year = 3 person-years
l = enters study O / + = leaves study
X = develops disease
14
Descriptive Epidemiology
Question:
Does the heart disease rate for Coloradoans
distinguish between existing and new cases of
AMI for this population?
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Descriptive Epidemiology
Prevalence vs. Incidence
• Prevalence is the number of existing cases of
disease in the population during a defined period
• Incidence is the number of new cases of disease
that develop in the population during a defined
period
16
Descriptive Epidemiology
Question:
Are we measuring prevalence or incidence?
• The number of persons living with HIV in your
community as of December 31, 2008
• The number of persons diagnosed with breast
cancer in your community during 2010
17
Descriptive Epidemiology
Question:
Which data are better for estimating disease
rates?
incidence or mortality data
Descriptive Epidemiology
Mortality rates are used to estimate disease
frequency when…
• incidence data are not available,
• case-fatality rates are high,
• goal is to reduce mortality among screened or
targeted populations
19
Descriptive Epidemiology
Intermediate outcomes may be used…
• when it is not feasible to wait years to see the
effects of a new public health program,
and
• there is sufficient type I evidence supporting the
relationship between modifiable risk factors and
disease reduction.
20
Descriptive Epidemiology
Long-term outcomes
Intermediate outcomes
• cardiovascular disease
• obesity, physical activity
• lung cancer
• cigarette smoking
• breast cancer mortality
• mammography screening
• arthritis
• ?
21
22
Descriptive Epidemiology
Estimating Rates
• often available for national and state-wide
populations
• not always available for smaller geographically
or demographically defined populations
23
Descriptive Epidemiology
Estimating Rates for Smaller Populations
• simple solution is to expand the study period or
other parameters, e.g., single vs. multiple
counties, for the population at risk
• rates are not reliable if fewer than 20 cases in
the numerator
24
Surveillance
relative standard error*
100
90
80
70
60
50
40
30
20
10
0
10
20
30
*RSE = 1 / cases
40
50
60
70
80
90
numerator size
25
100
Descriptive Epidemiology
Disease Rates
• crude
or, unadjusted
• category-specific
or, stratified
• adjusted
or, standardized
26
Descriptive Epidemiology
Crude (or unadjusted) rates
• estimate the actual disease frequency for a
population
• can be used to provide data for allocation of health
resources and public health planning
• can be misleading if compared over time or across
populations
27
Descriptive Epidemiology
Category-specific (or stratified) rates:
• are “crude rates” for subgroups of the total population
• Example: gender-specific AMI death rates for all
Coloradoans during 2007
males
= 28.1AMI deaths / 100,000 / year
females = 21.6 AMI deaths / 100,000 / year
28
Descriptive Epidemiology
Category-specific (or stratified) rates:
• provide more detailed information than crude rates
about patterns of disease frequency in the population
• can be used for valid comparison of populations
• can be cumbersome if there is a large number of
categories to compare
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Acute myocardial infarction death rates
per 100,000 U.S. residents, 1999-2007
Age Group
1999
2000
2001
2002
2003
2004
2005
2006
2007
< 1 year
1.7 **
N/A
1.5**
1.5 **
0.3**
1.5**
N/A
N/A
0.5**
25-34 years
1.2**
0.3**
1.0**
0.7**
0.3**
1.0**
0.4 **
0.4**
2.5**
35-44 years
4.1
4.5
3.8
3.5
3.7
4.6
2.2**
3.9
13.2
45-54 years
17.7
18.1
14.6
13.7
13
12.9
14.9
13.8
33.2
55-64 years
65.9
51.3
44.1
50.6
37.5
42.6
34.9
32.1
79.2
65-74 years
151.5
145.5
127.6
111
106.9
88.5
95.1
92.8
222.2
75-84 years
400.4
375.5
379.1
337.3
297.9
288
266.8
205.4
527.4
85+ years
994.7
886.7
844.6
874
875.3
753.8
599.7
616
24.9
40.9
37.4
35.2
34
31.8
30.4
27.8
25.9
31.8
Total
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** Rates are unreliable due to small number of cases
Descriptive Epidemiology
Category-specific rates can provide
general characteristics of the frequency of
disease in a population, particularly by ...
• person
• place
• time
31
Descriptive Epidemiology
Person: Who has the lowest / highest
disease rates in the population?
• age
• education
• gender
• income
• race / ethnicity
• health insurance status
32
Gender- and age-specific
AMI death rates, CO, 2007
Female
Age Group
Male
Total
Crude Rate
25-34 years
0.9 (Unreliable)
3.2 (Unreliable)
0.05
35-44 years
1.7 (Unreliable)
21.9
2.5
45-54 years
4.6 (Unreliable)
49.2
13.2
55-64 years
17.5
112.8
33.2
65-74 years
49.3
271.4
79.2
75-84 years
186.8
660
222.2
85+ years
463.4
28.1
527.4
Total
21.6
24.9
24.9
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Descriptive Epidemiology
Place: Where are the lowest / highest disease rates
for a population?
• geographic unit
• population density
– state
– county
• migration
– census tract
34
AMI Death Rates, Colorado, 2007
per 100,000
residents
35
AMI Death Rates, Colorado, 2007
County
Crude Rate
County
Crude Rate
County
Crude Rate
Adams
County, CO
23
Jefferson
County, CO
28.4
Larimer
County, CO
16.7
Arapahoe
County, CO
24.7
La Plata
12.1
Mesa
County, CO (Unreliable) County, CO
28.8
Boulder
County, CO
11.1
Larimer
County, CO
16.7
Montezuma
County, CO
79.4
Costilla
212.6
Mesa
County, CO (Unreliable) County, CO
28.8
Pueblo
County, CO
31.7
Denver
County, CO
79.4
Weld
County, CO
21.4
25.2
Montezuma
County, CO
36
Descriptive Epidemiology
Time: Are the disease rates changing
over time for a population?
• short-term trends
• cyclic trends
• long-term or secular
trends
• age, period, and birth
cohort effects
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Gender-specific AMI death rates,
CA, 1999-2007
Female
Year
1999
2000
2001
2002
2003
2004
2005
2006
2007
Total
Deaths
8292
7883
7812
7798
7390
6849
6457
6222
5640
64343
Male
Crude Rate Deaths Crude Rate
49.4
8952
53.6
46.4
8660
51.3
45.2
8289
48.2
44.6
8212
47.1
41.8
7915
44.9
38.4
7432
41.8
36
7065
39.4
34.4
6914
38.3
31
6316
34.7
40.6
69755
44.2
Rates per 100,000
Both Sexes
Deaths
17244
16543
16101
16010
15305
14281
13522
13136
11956
134098
Crude Rate
51.5
48.8
46.7
45.9
43.3
40.1
37.7
36.4
32.9
42.4
38
Gender-specific AMI death rates,
CA, 1999-2007
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Descriptive Epidemiology
Rate per 100,000
Age-specific lung cancer mortality rates in 1970
10
20
30
40
50
Age
60
70
80
40
90
Descriptive Epidemiology
Rate per 100,000
Age-specific lung cancer mortality rates in 1970
1890
1910
10
20
30
40
1880
Birth cohort-specific
lung cancer mortality
rates over many years
1900
50
Age
60
70
80
90
41
Descriptive Epidemiology
Rate per 100,000
Age-specific lung cancer mortality rates in 1970
1890
1910
10
20
30
40
1880
Birth cohort-specific
lung cancer mortality
rates over many years
1900
50
Age
60
70
80
90
42
Descriptive Epidemiology
AMI death rates by age and gender, IL Residents, 1999-2007
Age Group
Female
Deaths
Crude Rate
Male
Deaths
Crude Rate
25-34 years
4
0.5
(Unreliable)
13
1.4
(Unreliable)
35-44 years
19
2.1
(Unreliable)
92
10
45-54 years
129
14
325
35.5
55-64 years
265
39
547
85.2
65-74 years
366
85
697
195
75-84 years
85+ years
Total
823
1262
2869
257
861
773
726
44
6130
Rates per 100,000
410
1038
47.8
43
Descriptive Epidemiology
Female
Male
Age Group
Deaths
Crude Rate
Deaths
25-34 years
4
0.5 (Unreliable)
13
Crude Rate
1.4
(Unreliable)
35-44 years
19
2.1 (Unreliable)
92
10
45-54 years
129
14
325
35.5
55-64 years
265
39
547
85.2
65-74 years
366
85
697
195
75-84 years
823
257
861
410
85+ years
Age-Adjusted
Total
1262
773
726
1038
37,734
47.8
36,367
51
Rates per 100,000
44
Colorado Population Estimates, 2010
45
Descriptive Epidemiology
Adjusted (or standardized) rates:
• are computed in order to remove the effect of age
(or other factors) from crude rates to allow
meaningful comparisons across populations when
age distributions are different for the populations
being compared
46
Descriptive Epidemiology
Two methods can be used when comparing
disease rates across populations
• compare category-specific rates among the
populations that are being compared, or
• adjust crude rates for the populations that are being
compared.
47
Descriptive Epidemiology
Group A
Group B
Age
Deaths
<29
1
100
10
20
1,000
20
25
500
50
50
500
100
>60
100
1,000
100
20
100
200
Total
126
1,600
79
90
1,600
56
30-59
Persons Rate*
Deaths
Persons Rate*
* per 1,000 population per year
48
Descriptive Epidemiology
Group A
Group B
Age
Deaths
<29
1
100
10
20
1,000
25
500
50
50
500
>60
100
1,000
100
20
100 1,000 200
Total
126
79
90
56
30-59
Persons Rate*
* per 1,000 population per year
Deaths
Persons Rate*
100
20
500 100
49
Descriptive Epidemiology
Group A
(reference population)
Age
<29
30-59
Deaths Persons
Rate
Group B
(comparison population)
Persons
Rate
Exp*
1
100
10 /1000
100 x 20 /1000 =
25
500
50 /1000
500 x 100 /1000 = 50
1,000 100 /1000
1,000 x 200 /1000 = 200
>60
100
Total
126
2
252
*exp. number deaths
50
Descriptive Epidemiology
“Age-adjusted” mortality rate for group B
= (expected number of deaths / total population at
risk) x 10n
= (252 deaths / 1,600 persons / year) x 1,000
= 158 deaths / 1,000 persons / year
Mortality rate for group A
=
79 deaths / 1,000 persons / year
51
Surveillance
• Public health surveillance is the ongoing collection
and timely analysis, interpretation, and
communication of health information for public health
action.
• Public health surveillance systems are important
tools for collecting and disseminating descriptive
epidemiologic data.
52
Surveillance
Different surveillance collection methods provide
varying levels of confidence in the data
Method
Example
• population-based
• vital statistics
• representative sample
• BRFSS
• convenience sample
• survey at local mall
53
Surveillance
Vital Statistics
Reportable Diseases
• births
• childhood
• deaths
• Food-borne
• infectious
• sexually transmitted
54
Surveillance
Registries
Surveys
• cancers
• NHIS
• birth defects
• NHANES
• other diseases
• BRFSS
55
Public Health Surveillance Loop
Data
Interpretation
Data
Analysis
Data
Collection
Program
Evaluation
Information
Dissemination
Program
Implementation
Program
Planning
56
Exercise
57
Surveillance
Examples of data sources on the Internet
• CDC WONDER
http://wonder.cdc.gov
• BRFSS
http://www.cdc.gov/brfss
• WISQARS
http://www.cdc.gov/ncipc/wisqars
• MICA
http://www.dhss.mo.gov/MICA
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