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Learning Objectives

Evidence-Based Public Health: A Course in Chronic Disease Prevention MODULE 3: Quantifying the Issue Anjali Deshpande March 2013. Learning Objectives. To measure and characterize disease frequency in defined populations

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Learning Objectives

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  1. Evidence-Based Public Health: A Course in Chronic Disease Prevention MODULE 3:Quantifying the IssueAnjaliDeshpandeMarch 2013

  2. Learning Objectives To measure and characterize disease frequency in defined populations To find and use disease surveillance data presently available on the Internet

  3. Obesity Trends* Among U.S. AdultsBRFSS, 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%

  4. Percent obese high school students, USA, 2009

  5. Descriptive Epidemiology Define disease Define population at risk Select time frame acute myocardial infarction (AMI) CO residents 2009 How do we determine disease frequency for a population?

  6. 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

  7. 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 =

  8. 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? Descriptive Epidemiology

  9. 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”

  10. Descriptive Epidemiology J F M A M J J A S O N D = enters study l Actual “Person-years” PY A O 1.00 l X B 0.75 l C 0.25 l + D O 0.75 l l E X 0.25 3.00 O / + = leaves study X = develops disease

  11. 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

  12. 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 timesthe duration of the study period.

  13. Descriptive Epidemiology J F M A M J J A S O N D = enters study l Actual“Person-years” PY A O 1.00 l X B 0.75 l C 0.25 l + D O 0.75 l l E X 0.25 3.00 O / + = leaves study X = develops disease

  14. Descriptive Epidemiology J F M A M J J A S O N D = enters study l Estimated “Person-years” PY A O 1.00 l X B 0.75 l C 0.25 l + D O 0.75 l l E X 0.25 3 persons x 1 year = 3 person-years 3.00 O / + = leaves study X = develops disease

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

  16. 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 Descriptive Epidemiology

  17. 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

  18. Descriptive Epidemiology Question: Which data are better for estimating disease rates? incidence or mortality data

  19. 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

  20. 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.

  21. Descriptive Epidemiology Long-term outcomes cardiovascular disease lung cancer breast cancer mortality arthritis Intermediate outcomes obesity, physical activity cigarette smoking mammography screening ?

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

  25. 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

  29. Acute myocardial infarction death rates per 100,000 U.S. residents, 1999-2007 ** Rates are unreliable due to small number of cases

  30. 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 Person:Who has the lowest / highest disease rates in the population? • education • income • health insurance status

  32. Gender- and age-specific AMI death rates, CO, 2007

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

  34. AMI Death Rates, Colorado, 2007 per 100,000 residents

  35. AMI Death Rates, Colorado, 2007

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

  37. Gender-specific AMI death rates,CA, 1999-2007

  38. Gender-specific AMI death rates,CA, 1999-2007

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

  40. Age-specific lung cancer mortality rates in 1970 Rate per 100,000 1880 1890 Birth cohort-specific lung cancer mortality rates over many years 1900 1910 Age Descriptive Epidemiology

  41. Age-specific lung cancer mortality rates in 1970 Rate per 100,000 1880 1890 Birth cohort-specific lung cancer mortality rates over many years 1900 1910 Age Descriptive Epidemiology

  42. Descriptive Epidemiology AMI death rates by age and gender, IL Residents, 1999-2007

  43. Descriptive Epidemiology

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

  47. Group A Group B AgeDeathsPersonsRate* DeathsPersonsRate* <29 1 100 10 20 1,000 20 30-59 25 500 50 50 500 100 >60 1001,000 100 20100 200 Total 126 1,600 79 90 1,600 56 * per 1,000 population per year Descriptive Epidemiology

  48. Group A Group B AgeDeathsPersonsRate* DeathsPersonsRate* <29 1 100 10 20 1,000 100 20 30-59 25 500 50 50 500 500 100 >60 1001,000 100 20 100 1,000 200 Total 126 79 90 56 * per 1,000 population per year Descriptive Epidemiology

  49. Group A Group B (reference population) (comparison population) AgeDeathsPersonsRatePersonsRateExp* <29 1100 10 /1000100x 20 /1000 = 2 30-59 2550050 /1000500x 100 /1000 = 50 >60 1001,000100 /10001,000 x 200 /1000 = 200 Total 126 252 *exp. number deaths Descriptive Epidemiology

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