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

1999 Obesity Trends* Among U.S. Adults BRFSS, 1990, 1999, 2008 (*BMI 30, or about 30 lbs. overweight for 5’4” person) No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30% 3

Percent obese high school students, USA,

Descriptive Epidemiology Define disease Define population at risk Select time frame acute myocardial infarction (AMI) CO residents How do we determine disease frequency for a population?

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 ,205 Colorado residents with AMI 4,842,770 Colorado residents = AMI / Coloradoan/ year 7 =

Rates are usually expressed as whole numbers for populations at risk during specified periods: 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? Descriptive Epidemiology 8

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 10 A l O1.00 B l X 0.75 C l D l O0.75 E l X JFMAMJJASOND Actual “Person-years” PY l = enters studyO / + = leaves studyX = develops disease

Descriptive Epidemiology 11 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

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 13 A l O1.00 B l X 0.75 C l D l O0.75 E l X JFMAMJJASOND Actual “Person-years” PY l = enters studyO / + = leaves studyX = develops disease

Descriptive Epidemiology 14 A l O1.00 B l X 0.75 C l D l O0.75 E l X l = enters studyO / + = leaves study X = develops disease JFMAMJJASOND Estimated “Person-years” PY 3 persons x 1 year = 3 person-years

Question: Does the heart disease rate for Coloradoans distinguish between existing and new cases of AMI for this population? Descriptive Epidemiology 15

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 Descriptive Epidemiology 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

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… 19 incidence data are not available, case-fatality rates are high, goal is to reduce mortality among screened or targeted populations

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 cardiovascular disease lung cancer breast cancer mortality arthritis Intermediate outcomes obesity, physical activity cigarette smoking mammography screening ? 21

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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 25 numerator size relative standard error* *RSE = 1 / cases

Descriptive Epidemiology Disease Rates crudeor, unadjusted category-specificor, stratified adjustedor, 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 29

Acute myocardial infarction death rates per 100,000 U.S. residents, Age Group < 1 year1.7 **N/A1.5** 0.3**1.5**N/A 0.5** years1.2**0.3**1.0**0.7**0.3**1.0**0.4 ** 2.5** years ** years years years years years Total ** Rates are unreliable due to small number of cases

Category-specific rates can provide general characteristics of the frequency of disease in a population, particularly by... person place time Descriptive Epidemiology 31

age gender race / ethnicity Descriptive Epidemiology 32 education income health insurance status Person: Who has the lowest / highest disease rates in the population?

Gender- and age-specific AMI death rates, CO, FemaleMaleTotal Age Group Crude Rate years0.9 (Unreliable)3.2 (Unreliable) years1.7 (Unreliable) years4.6 (Unreliable) years years years years Total

geographic unit – state – county – census tract Descriptive Epidemiology 34 population density migration Place: Where are the lowest / highest disease rates for a population?

AMI Death Rates, Colorado, per 100,000 residents

AMI Death Rates, Colorado, CountyCrude RateCountyCrude RateCountyCrude Rate Adams County, CO 23 Jefferson County, CO 28.4 Larimer County, CO 16.7 Arapahoe County, CO 24.7 La Plata County, CO 12.1 (Unreliable) Mesa County, CO 28.8 Boulder County, CO 11.1 Larimer County, CO 16.7 Montezuma County, CO 79.4 Costilla County, CO (Unreliable) Mesa County, CO 28.8 Pueblo County, CO 31.7 Denver County, CO 25.2 Montezuma County, CO 79.4 Weld County, CO 21.4

short-term trends long-term or secular trends Descriptive Epidemiology 37 cyclic trends age, period, and birth cohort effects Time: Are the disease rates changing over time for a population?

Gender-specific AMI death rates, CA, FemaleMaleBoth Sexes YearDeathsCrude RateDeathsCrude RateDeathsCrude Rate Total Rates per 100,000

Gender-specific AMI death rates, CA,

Rate per 100,000 Age Age-specific lung cancer mortality rates in 1970 Descriptive Epidemiology 40

Descriptive Epidemiology Rate per 100,000 Age Age-specific lung cancer mortality rates in Birth cohort-specific lung cancer mortality rates over many years 41

Descriptive Epidemiology Rate per 100,000 Age Age-specific lung cancer mortality rates in Birth cohort-specific lung cancer mortality rates over many years 42

Descriptive Epidemiology 43 FemaleMale Age GroupDeathsCrude RateDeathsCrude Rate years4 0.5 (Unreliable) (Unreliable) years (Unreliable) years years years years years Total Rates per 100,000 AMI death rates by age and gender, IL Residents,

Descriptive Epidemiology 44 FemaleMale Age GroupDeathsCrude RateDeathsCrude Rate years40.5 (Unreliable) (Unreliable) years192.1 (Unreliable) years years years years years Age-Adjusted Total36, , Rates per 100,000

Colorado Population Estimates,

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

Two methods can be used when comparing disease rates across populations Descriptive Epidemiology 47 compare category-specific rates among the populations that are being compared, or adjust crude rates for the populations that are being compared.

Group A Group B AgeDeathsPersonsRate*DeathsPersonsRate* < , >601001, Total1261, ,60056 * per 1,000 population per year Descriptive Epidemiology 48

Group A Group B AgeDeathsPersonsRate*DeathsPersons Rate* < , >601001, , Total * per 1,000 population per year Descriptive Epidemiology 49

Group A Group B (reference population) (comparison population) AgeDeaths PersonsRate Persons Rate Exp* < / x 20 /1000 = / x 100 /1000 = 50 >601001, /10001,000 x 200 /1000 =200 Total *exp. number deaths Descriptive Epidemiology 50

“Age-adjusted” mortality rate for group B = (expected number of deaths / total population at risk) x 10 n = (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 Descriptive Epidemiology 51

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. Surveillance 52

Surveillance Method population-based representative sample convenience sample Example vital statistics BRFSS survey at local mall 53 Different surveillance collection methods provide varying levels of confidence in the data

Surveillance Vital Statistics births deaths Reportable Diseases childhood Food-borne infectious sexually transmitted 54

Surveillance Registries cancers birth defects other diseases Surveys NHIS NHANES BRFSS 55

Public Health Surveillance Loop 56 Data Program Interpretation Evaluation Data Information Program Analysis Dissemination Implementation Data Program Collection Planning

Exercise 57

Surveillance CDC WONDER BRFSS WISQARS MICA Examples of data sources on the Internet

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