module 3 quantifying the issue - nysacho.org

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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

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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

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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

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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)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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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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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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Small number issues

Types of rates


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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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Small number issues

Types of rates


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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

?

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Small number issues

Types of rates


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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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Small number issues

Types of rates


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Types of Rates

Crude, or unadjusted

Standardized, or adjusted

Category-specific, or stratified

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Types of Rates




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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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Define disease


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


Define disease


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


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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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




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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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Standardized (or adjusted) RatesExample calculation from one population to another

Age (years)


≤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


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Age (years)


≤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


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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

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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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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

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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

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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

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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

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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

x

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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

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Source: CDC Wonder

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Standardized (or adjusted) RatesChanges in age distribution—United States and New York

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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




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c4 At first glance, I'm not sure what the line graphs represent.cthomaskutty, 5/9/2012

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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

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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

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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

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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

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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

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New York State Community Health Indicator Reports

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New York State Community Health Indicator Reports

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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)

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Small number issues

Types of rates


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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

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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

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Category-specific (or stratified) RatesAge-adjusted Rates for Male Stomach Cancer, by County, New York, 2008-2012

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Source: New York State Cancer Registry

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Public Health Surveillance Loop

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Data ProgramInterpretation Evaluation

Data Information Program Analysis Dissemination Implementation

Data ProgramCollection Planning

module 3 quantifying the issue - nysacho.org

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