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July 22, 2015
Evidence‐Based Public Health:Supporting the New York State
Prevention Agenda
MODULE 3:
QUANTIFYING THE ISSUE
Maria Schymura, PhD
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Learning Objectives
1. To measure and characterize disease frequency in defined populations using principles of descriptive epidemiology and surveillance.
2. To find and use disease surveillance data presently available on the Internet.
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Epidemiology
Study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems
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Public Health Surveillance
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
5
Public Health SurveillanceCollection methods
Provide varying levels of confidence in the data
Population-based
Vital Statistics• Birth and death
Reportable diseases
Registries• Birth defects• Cancer• Immunizations• Trauma
Representative Samples
National Health Interview Survey (NHIS)
National Health and Nutrition Examination Survey (NHANES)
Behavioral Risk Factor Surveillance System (BRFSS)
Youth Risk Behavior Survey (YRBS)
Convenience Samples
Survey at a local mall
Level of confidencehigh low6
4
BRFSS
Monitors modifiable risk factors associated with chronic and communicable diseases
All 50 states and DC participate
Sample based on the state’s population, not the population of smaller geographic areas (e.g., counties)
Adults age 18 yrs and older (non-institutionalized)
Random dial telephone survey – Past: landlines
– Present and future: landlines (80%) and cell phone (20%)7
BRFSS Raking methodology to be introduced (2011 data)
– More precise estimates
– Need to start new trend analyses
SMART BRFSS (Metropolitan or Micropolitan Statistical Areas)– Metro
• Lincoln (Lancaster and Seward)
• Omaha–Council Bluffs (Cass, Douglas, Sarpy, Saunders, Washington, plus IA counties)
• Sioux City (Dakota, Dixon, plus IA and SD counties)
– Micro• Grand Island (Hall, Howard, Merrick)
• Hastings (Adams, Clay)
• Norfolk (Madison, Pierce, Stanton)
• North Platte (Lincoln, Logan, McPherson)
• Scottsbluff (Banner, Scotts Bluff)
County-level prevalence estimates – Diabetes, obesity, physical activity (link below)
– 11 indicators (2014)
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http://apps.nccd.cdc.gov/BRFSS-SMART/index.asp
http://apps.nccd.cdc.gov/DDT_STRS2/CountyPrevalenceData.aspx?StateId=18&mode=DBT
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Obesity Trends* Among U.S. Adults—1990, 1999, 2008
*Body Mass Index (BMI) 30; or about 30 lbs. overweight for 5’4” person
1999
2008
1990
Source: Behavioral Risk Factor Surveillance System
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No data <10% 10%-14% 15%-19% 20%-24% 25%-29% ≥30%
Percent of High School Students Considered Obese, United States, 2013
Source: Youth Risk Behavior Survey10
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Descriptive and Analytic Epidemiology
Descriptive epidemiology– Frequency and distribution of risk factors in
populations
– Frequency and distribution of disease in populations
– Can provide hypotheses for etiologic research
Analytical epidemiology – Study of factors associated with disease
(factors that either increase or decrease risk)11
Descriptive and Analytic EpidemiologyThematic Example: Obesity and Cancer
Cancer site and type Summary RR from comprehensive meta-analysis and (95% CI) per given unit increase in BMI
RR Overweight(BMI 25-29) vs BMI <25)
RR Obese (BMI ≥ 30)
vs BMI <25)
Esophagus (adenocarcinoma) 1.11 (1.07-1.15) per 1 kg/m2 increase in BMI 1.55 2.10
Colorectal 1.18 (1.14-1.21) per 5 kg/m2 increase in BMI 1.18 1.36
Pancreas 1.14 (1.07-1.22) per 5 kg/m2 increase in BMI 1.14 1.28
Kidney 1.42 (1.17-1.72) per 5 kg/m2 increase in BMI 1.42 1.84
Post-menopausal breast 1.05 (1.03-1.07) per 2 kg/m2 increase in BMI 1.13 1.25
Endometrial 1.60 (1.52-1.68) per 5 kg/m2 increase in BMI 1.60 2.20
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Source: Eheman C, et al Annual Report to the Nation on the Status of Cancer, 1975–2008, Featuring Cancers Associated with Excess Weight and Lack of Sufficient Physical Activity. Cancer 2012; 118:2338-66.
Relative Risk (RR) Associated with Excess Weight
7
Descriptive and Analytic Epidemiology
Descriptive epidemiology– Frequency and distribution of risk factors in
populations
– Frequency and distribution of disease in populations
– Can provide hypotheses for etiologic research
Analytical epidemiology – Study of factors associated with disease
(factors that either increase or decrease risk)13
Descriptive EpidemiologyTerminology and uses
Prevalence vs. incidence Incidence vs. mortality Role of intermediate indicators Small number issues Types of rates Estimate error and confidence intervals
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Descriptive EpidemiologyTerminology and uses
Prevalence vs. incidence
Incidence vs. mortality
Role of intermediate indicators
Small number issues
Types of rates
Estimate error and confidence intervals
15
Prevalence vs. Incidence
Prevalence is the number of existingcases of disease in the population during a defined period
Incidence is the number of newcases of disease that develop in the population during a defined period
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Prevalence vs. Incidence
QuestionAre we measuring prevalence or
incidence? The number of persons living with HIV
in your community as of December 31, 2012
The number of persons diagnosed with breast cancer in your community during 2012
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Descriptive EpidemiologyTerminology and uses
Prevalence vs. incidence
Incidence vs. mortality
Role of intermediate indicators
Small number issues
Types of rates
Estimate error and confidence intervals
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10
Incidence vs. Mortality
Question
Which data are better for estimating disease rates?
incidence or mortality data
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Incidence vs. Mortality
Mortality rates are used to estimate disease frequency when Incidence data are not available;
Case-fatality rates are high; or
Goal is to reduce mortality among screened or targeted populations
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11
Descriptive EpidemiologyTerminology and uses
Prevalence vs. incidence
Incidence vs. mortality
Role of intermediate indicators
Small number issues
Types of rates
Estimate error and confidence intervals
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Role of Intermediate Outcomes
Intermediate outcomes may be used
When it is not feasible to wait years to see the effects of a new public health program, or
There is sufficient type I evidence supporting the relationship between modifiable risk factors and disease reduction
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Role of Intermediate Outcomes
Long-term outcomes cardiovascular disease
lung cancer
breast cancer mortality
arthritis
Intermediate outcomes obesity, physical activity
cigarette smoking
mammography screening
?
23
Descriptive EpidemiologyTerminology and uses
Prevalence vs. incidence
Incidence vs. mortality
Role of intermediate indicators
Small number issues
Types of rates
Estimate error and confidence intervals
24
13
Small Number Issues
Rates are often available for national and state-wide populations
Not always available for smaller geographic areas or demographically defined populations– Rates are not considered stable if fewer
than 20 cases in the numerator
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0
10
20
30
40
50
60
70
80
90
100
10 20 30 40 50 60 70 80 90 100
Small Number IssuesRole of standard error
numerator size
rela
tive
stan
dar
der
ror*
*RSE = 1 / cases
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Small Number IssuesPossible solutions, combine…
Years
Groups
– e.g., “other races”
Geographic areas
– Public health department regions
– Congressional districts
– Program regions
– School districts
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Descriptive EpidemiologyTerminology and uses
Prevalence vs. incidence
Incidence vs. mortality
Role of intermediate indicators
Small number issues
Types of rates
Estimate error and confidence intervals
28
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Types of Rates
Crude, or unadjusted
Standardized, or adjusted
Category-specific, or stratified
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Types of Rates
Crude, or unadjusted
Standardized, or adjusted
Category-specific, or stratified
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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
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Crude (or unadjusted) RatesDefining your population
Define disease
Define population at risk
Select time frame
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Crude (or unadjusted) RatesDefining your population
Define disease
Define population at risk
Select time frame
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Breast Cancer• Standard inclusion and exclusion
criteria (e.g., invasive, specific ICD-O-3 codes)
New York Females
2010
Crude (or unadjusted) RatesDefining your population
Define disease
Define population at risk
Select time frame
Breast Cancer• Standard inclusion and exclusion
criteria (e.g., invasive, specific ICD-O-3 codes)
New York Females
2010
Where do you find this data?
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Crude (or unadjusted) Rates—Variability among data sources
New York State Cancer Registry
– Incidence and mortality data• State, NYC, NYS excl. NYC, counties
– Incidence data • Select areas for Nassau, Rockland, Suffolk,
& Westchester Counties• Cities: Albany, Buffalo, Rochester, Syracuse,
& Yonkers • NYC neighborhoods• ZIP codes
– http://www.health.ny.gov/statistics/cancer/registry/
New York State Vital Statistics
– Mortality data, birth data– http://www.health.ny.gov/statistics/vital_statistics/
CDC Wonder
– Incidence and mortality data– National, state, regional and metropolitan
statistical area (4 for NY) levels– wonder.cdc.gov – Cancer statistics:
http://wonder.cdc.gov/cancer.html35
Crude (or unadjusted) Rates—Different options for population figures
U.S. Census– Decennial Census (most current:
2010)– American Community Survey (yearly
estimates)– factfinder2.census.gov
NYS Vital Statistics– http://www.health.ny.gov/statistics/vital
_statistics/
SEER Program(Surveillance, Epidemiology and End Results)
– seer.cancer.gov/popdata
CDC Wonder– wonder.cdc.gov
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Crude (or unadjusted) RatesCalculation methodology
Compute disease rate for year 2010
Number of females
diagnosed with breast cancer
Number of females at risk
for breast cancer
14,409
10,007,823
Sources: New York State Cancer Registry; CDC Wonder37
Crude (or unadjusted) RatesCalculation methodology
Compute disease rate for year 2010
14,409 New York females with breast cancer
10,007,823 female New York residents
= 0.0014398 breast cancer cases / female NY residents / year
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20
Crude (or unadjusted) RatesCalculation methodology
Rates are usually expressed as whole numbers for populations at risk during specified periods:
0.0014398 breast cancer cases / female New York residents / year x 100,000 =
144.0 breast cancer cases / 100,000 female New York residents / year
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Types of Rates
Crude, or unadjusted
Standardized, or adjusted
Category-specific, or stratified
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Standardized (or adjusted) Rates
– Removes the impact of different age distributions (or other factors) among populations
– Allows for direct comparisons of those populations
– Types of age standardization• One population to another
• Using the 2000 U.S. Standard Million or Standard Population [right]
– Multiple age category breakdowns, with 18 and 19 categories being the most common
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Standardized (or adjusted) RatesExample calculation from one population to another
Age (years)
Deaths Persons Rate* Deaths Persons Rate*
≤29 1 100 10 20 1000 20
30–59 25 500 50 50 500 100
≥60 100 1000 100 20 100 200
Total 126 1600 79 90 1600 56
Group A Group B
* per 1,000 population per year
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22
Standardized (or adjusted) RatesExample calculation from one population to another
Age (years)
Deaths Persons Rate* Deaths Persons Rate*
≤29 1 100 10 20 1000 20
30–59 25 500 50 50 500 100
≥60 100 1000 100 20 100 200
Total 126 1600 79 90 1600 56
Group A Group B
* per 1,000 population per year
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Age (years)
Deaths Persons Rate* Deaths Persons Rate*
≤29 1 100 10 20 1,000 100 20
30–59 25 500 50 50 500 500 100
≥60 100 1000 100 20 100 1000 200
Total 126 1600 79 90 1600 56
Group A Group B
Standardized (or adjusted) RatesExample calculation
* per 1,000 population per year
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Age (years)
Deaths Persons Rate* Deaths Persons Rate
≤29 1 100 10 20 100 x 0.02 =
30–59 25 500 50 50 500 x 0.10 =
≥60 100 1000 100 20 1000 x 0.20 =
Total 126 1600 79 90
Group A Group B
*Expected number of deaths based on Group A’s population distribution
Standardized (or adjusted) RatesExample calculation
Exp*
2
50
200
252
45
Standardized (or adjusted) Rates
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 • Crude rate: 56 deaths / 1,000 persons / year
Mortality rate for Group A
= 79 deaths / 1,000 persons / year
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24
Standardized (or adjusted) RatesNumber of cancer cases, by age—New York, 2010
47Source: CDC Wonder
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
Num
ber
of c
ases
Age (years)
Standardized (or adjusted) RatesExample calculation using a standard population; all cancers—New York, 2010
48
Age Group Count Population< 1 year 60 232,3261-4 years 199 922,0945-9 years 148 1,161,832
10-14 years 189 1,210,49715-19 years 319 1,360,44020-24 years 535 1,413,61725-29 years 834 1,381,86730-34 years 1,337 1,284,95835-39 years 1,910 1,247,71340-44 years 3,322 1,356,03345-49 years 5,723 1,453,53750-54 years 8,525 1,422,57655-59 years 11,183 1,244,76360-64 years 13,688 1,076,58365-69 years 13,760 776,84370-74 years 12,520 589,87575-79 years 11,216 473,97680-84 years 9,662 391,91085+ years 9,068 393,766All Ages 104,198 19,395,206
Source: CDC Wonder
25
Age Group Count Population Crude Rate
< 1 year 60 232,326
1-4 years 199 922,094
5-9 years 148 1,161,832
10-14 years 189 1,210,497
15-19 years 319 1,360,440
20-24 years 535 1,413,617
25-29 years 834 1,381,867
30-34 years 1,337 1,284,958
35-39 years 1,910 1,247,713
40-44 years 3,322 1,356,033
45-49 years 5,723 1,453,537
50-54 years 8,525 1,422,576
55-59 years 11,183 1,244,763
60-64 years 13,688 1,076,583
65-69 years 13,760 776,843
70-74 years 12,520 589,875
75-79 years 11,216 473,976
80-84 years 9,662 391,910
85+ years 9,068 393,766
All Ages 104,198 19,395,206 0.005372
0.005372 x 100,000 = 537.2 cases /100,000 people (crude rate)
/ =49
Standardized (or adjusted) RatesExample calculation using a standard population, all cancers—New York, 2010
Source: CDC Wonder
50
Age Group Count Population Crude Rate US Standard Million< 1 year 60 232,326 13,8181-4 years 199 922,094 55,3175-9 years 148 1,161,832 72,533
10-14 years 189 1,210,497 73,03215-19 years 319 1,360,440 72,16920-24 years 535 1,413,617 66,47825-29 years 834 1,381,867 64,52930-34 years 1,337 1,284,958 71,04435-39 years 1,910 1,247,713 80,76240-44 years 3,322 1,356,033 81,85145-49 years 5,723 1,453,537 72,11850-54 years 8,525 1,422,576 62,71655-59 years 11,183 1,244,763 48,45460-64 years 13,688 1,076,583 38,79365-69 years 13,760 776,843 34,26470-74 years 12,520 589,875 31,77375-79 years 11,216 473,976 26,99980-84 years 9,662 391,910 17,84285+ years 9,068 393,766 15,508All Ages 104,198 19,395,206 0.005372 1,000,000
Standardized (or adjusted) RatesExample calculation using a standard population, all cancers—New York, 2010
Source: CDC Wonder
26
Age Group Count Population Crude RateUS Standard
MillionExpected
< 1 year 60 232,326 0.000258 13,818 41-4 years 199 922,094 0.000216 55,317 125-9 years 148 1,161,832 0.000127 72,533 9
10-14 years 189 1,210,497 0.000156 73,032 1115-19 years 319 1,360,440 0.000234 72,169 1720-24 years 535 1,413,617 0.000378 66,478 2525-29 years 834 1,381,867 0.000604 64,529 3930-34 years 1,337 1,284,958 0.001041 71,044 7435-39 years 1,910 1,247,713 0.001531 80,762 12440-44 years 3,322 1,356,033 0.002450 81,851 20145-49 years 5,723 1,453,537 0.003937 72,118 28450-54 years 8,525 1,422,576 0.005993 62,716 37655-59 years 11,183 1,244,763 0.008984 48,454 43560-64 years 13,688 1,076,583 0.012714 38,793 49365-69 years 13,760 776,843 0.017713 34,264 60770-74 years 12,520 589,875 0.021225 31,773 67475-79 years 11,216 473,976 0.023664 26,999 63980-84 years 9,662 391,910 0.024654 17,842 44085+ years 9,068 393,766 0.023029 15,508 357All Ages 104,198 19,395,206 1,000,000 4,821
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Standardized (or adjusted) RatesExample calculation using a standard population; all cancers—New York, 2009
Source: CDC Wonder
Count Crude Rate* Standardized Rate*†All Sites Combined 104,198 537.2 482.1Prostate 14,680 156.4 147.6Female Breast 14,409 144.0 123.6Lung and Bronchus 13,301 68.6 61.5Colon and Rectum 9,311 48.0 42.9Urinary Bladder 4,792 24.7 22.1Non‐Hodgkin Lymphoma 4,519 23.3 21.1Thyroid 3,643 18.8 17.8Melanoma of the Skin 3,487 18.0 16.5Corpus Uteri 3,464 34.6 28.7Kidney and Renal Pelvis 3,387 17.5 15.6
Standardized (or adjusted) RatesComparison between crude and standardized rates for the ten leading cancer
types—New York 2010
* per 100,000 population per year; †Standardized using the 2000 U.S. Standard Million
52
Source: CDC Wonder
27
Standardized (or adjusted) RatesChanges in age distribution—United States and New York
53Source: CDC Wonder
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
Age (years)
New York 2000
New York 2010
US Standard Million
c4
Types of Rates
Crude, or unadjusted
Standardized, or adjusted
Category-specific, or stratified
54
Slide 53
c4 At first glance, I'm not sure what the line graphs represent.cthomaskutty, 5/9/2012
28
Category-specific (or stratified) Rates
Can be used for valid comparison of populations
Can be cumbersome if there is a large number of categories to compare
55
Category-specific (or stratified) RatesTwo general categories
Age-specific: crude rates across different age groups
“Other”-specific: crude or standardized rates across different groups
• Person: sex, race / ethnicity, education, income, health insurance status
• Place: geographic unit (e.g., county), urban / rural, population density
• Time: short or long-term trends, cyclic trends, cohort effects
56
29
Category-specific (or stratified) RatesAge-adjusted Rates for Colorectal Cancer, Both Males and Females, by County,
New York, 2008-2012
57Source: New York State Cancer Registry
Category-specific (or stratified) RatesAge-Adjusted Colorectal Cancer Rates by
Race/Ethnicity and Gender, New York, 2008–2012
0
10
20
30
40
50
60
Male Female
White Non-Hispanic
Black Non-Hispanic
Hispanic
Asian/PI
58Source: New York State Cancer Registry
30
Category-specific (or stratified) RatesTrends in Colorectal Cancer Incidence by Race/Ethnicity, New York, 1990-2012
0
10
20
30
40
50
60
70A
ge-a
djus
ted
rate
Year of diagnosis
Non-Hispanic White Non-Hispanic Black Non-Hispanic Asian/Pacific Islander Hispanics
Category-specific (or stratified) RatesFemale Breast Cancer Rates* for Northeastern States, 2007-2011
60
Crude Age-Adjusted
State Rate Rank Rate Rank
Connecticut 165.2 1 136.6 1
Maine 164.7 2 126.4 9
Massachusetts 159.6 5 135.6 2
New Hampshire 161.8 3 134.1 3
New Jersey 152.4 8 129.6 5
New York 149.0 9 128.5 7
Pennsylvania 158.3 6 126.8 8
Rhode island 156.2 7 130.1 4
Vermont 161.4 4 129.1 6
Source: CDC Wonder & SEER Public Use File
*Rates are per 100,000
31
New York State Community Health Indicator Reports
61
New York State Community Health Indicator Reports
62
32
63Source: 2010-2012 Vital StatisticsData as of February 2014
Source: 2010-2012 SPARCSData as of June, 2014
Cardiovascular Disease Mortality Rate*, 2010-2012 (* per 100,000 Adjusted to 2000 US Population)
Cardiovascular Disease Hospitalization Rate*, 2010-2012 (*per 10,000 Adjusted to 2000 US Population)
64Source: 2010-2012 Vital StatisticsData as of February 2014
Source: 2010-2012 SPARCSData as of June, 2014
Diabetes Mortality Rate*, 2010-2012 (* per 100,000 Adjusted to 2000 US Population )
Diabetes Hospitalization Rate* (primary diagnosis), 2010-2012(* per 10,000 Adjusted to 2000 US Population)
33
Descriptive EpidemiologyTerminology and uses
Prevalence vs. incidence
Incidence vs. mortality
Role of intermediate indicators
Small number issues
Types of rates
Estimate error and confidence intervals
65
Estimate Error and Confidence Intervals (CI)
Population-based
Vital Statistics• Birth and death
Reportable diseases
Registries• Birth defects• Cancer• Immunizations• Trauma
Representative Samples
National Health Interview Survey (NHIS)
National Health and Nutrition Examination Survey (NHANES)
Behavioral Risk Factor Surveillance System (BRFSS)
Youth Risk Behavior Survey (YRBS)
Convenience Samples
Survey at a local mall
Level of confidencehigh low
66
34
Estimate Error and Confidence Intervals (CI)
Population-based Representative Sample
Subject to sampling error? No Yes
Impacted by random variation?
Yes, especially when looking at rates for
rare events or among small geographic areas
Yes
CIs* used to describe the range of that variation?
Yes, random variation Yes, both
*95% CIs are typically calculated to provide a range of values in which if one repeated a study 100 times, 95 of the intervals would include the true rate
67
Category-specific (or stratified) RatesAge-adjusted Rates for Male Stomach Cancer, by County, New York, 2008-2012
68
Source: New York State Cancer Registry
35
Public Health Surveillance Loop
69
Data ProgramInterpretation Evaluation
Data Information Program Analysis Dissemination Implementation
Data ProgramCollection Planning
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