Measuring Epidemiologic Outcomes

1. Measuring Epidemiologic Outcomes

2. Epidemiological Outcomes • Ratio: Relationship between two numbers • Example: males/females • Proportion: A ratio where the numerator is included in the denominator • Example: males/total births • Rate: A proportion with the specification of time • Example: (deaths in 1999/population in 1999) x 1,000

3. In epidemiology, the occurrence of a disease or condition can be measured using rates and proportions. We use these measures to express the extent of these outcomes in a community or other population. • Rates tell us how fast the disease is occurring in a population. • Proportions tell us what fraction of the population is affected. (Gordis, 2000)

4. Morbidity Measures Number of new events during a time period X 1,000 Incidence Rate = • Incidence is always calculated for a given period of time • An attack rate is an incidence rate calculated for a specific disease for a limited period of time during an epidemic Population at risk

5. Prevalence = Number of existing events, old and new X 1,000 Population at risk Morbidity Measures • Prevalence is not a rate • Point prevalence measures the frequency of all current events (old and new) at a given instant in time • Period prevalence measures the frequency of all current events (old and new) for a prescribed period of time

6. High prevalence may reflect: • High risk • Prolonged survival without cure Low prevalence may reflect: • Low risk • Rapid fatal disease progression • Rapid cure Interrelationship: P  ID Examples: Ebola, Common cold

7. Cancer of the pancreas Incidence low Duration short Prevalence low Adult onset diabetes Incidence low Duration long Prevalence high Roseola infantum Incidence high Duration short Prevalence low Essential hypertension Incidence high Duration long Prevalence high Relationship Between Incidence and Prevalence (cont.)

8. Calculation Practice Skin Cancer on Sunny Beach: Point prevalence on 9/28/1974 Period prevalence for year 1975 Incidence rate for year 1975 What information will you need?

9.                                        Diagnosed cases of Skin Cancer on Sunny Beach, 9/28/1974            # of existing cases = 10 Total population at risk = 450         Point Prevalence (9/28/1974) = (10/450)*1000 = 22 per 1000  

10.                                        Diagnosed cases of Skin Cancer on Sunny Beach, 1975 Average population at risk = 500             # of new cases = 5   Incidence rate (year 1975) = (5/500)*1000 = 10 per 1000           Period prevalence (year 1975) = (15/500)*1000 = 30 per 1000  

11. Number of cases of disease beginning, developing, and ending during a period of time, January 1, 2000 – December 31, 2000. Length of each line corresponds to duration of each case. JAN 2000 DEC 2000 MAY JULY SEPT What is the numerator for incidence in 2000? What is the numerator for point prevalence if a survey was done in May? July? September? December?

12. Risk Versus Rate Risk and rate are often used interchangeably by epidemiologists but there are differences

13. Risk Versus Rate (cont.) • Risk is a probability statement assuming an individual is not removed for any other reason during a given period of time • As such, risk ranges from 0 to 1 (no chance to 100% probability of occurrence) • Risk requires a reference period and reflects the cumulative incidence of a disease over that period • Example: 1 in a million chance of developing cancer in a 70 year lifetime

14. Risk Versus Rate (cont.) • Rates can be used to estimate risk if the time period is short (annual) and the incidence of disease over the interval is relatively constant • If however, individuals are in a population for different periods of time for any reason, then you should estimate risk by incidence density

15. Incidence Density

16. ID Example • In the Iowa Women’s Health Study (IWHS), 37,105 women contributed 276,453 person-years of follow-up • Because there were 1,085 incident cases, the rate of breast cancer using the incidence density method is: 1,085/276,453 = 392.5/100,000 person-years

17. ID Example (cont.) • If each woman had been followed for the entire 8-year period of the study, the total person-years would have been 296,840 and the rate would have been lower (assuming the number of incident cancers was the same) • The incidence density method yielded a higher and more accurate estimate

18. Natality Outcomes • Natality measures are used primarily by demographers for population projection Number of live births for a given time period (year) Crude Birth Rate = X 1,000 Estimated mid-interval total population

19. Concerns About Crude Birth Rates • Definitions of a live birth may vary • U.S. = “any product of conception that shows any sign of life after complete birth (pulse, heartbeat, respiration, crying, pulsation of umbilical cord or movement of the voluntary muscles)” • The denominator used for birth rates is inaccurate because men are not part of the population-at-risk

20. Natality Outcomes (cont.) Number of live births for a given time period (year) X 1,000 General Fertility Rate = Estimated # of women 15-44 years at mid-interval

21. Natality Outcomes (cont.) • Total fertility rate: Same as above, but use women 10-49 years and adjust for age cohorts • Gross reproductive rate: Same as TFR, but use only live births of females in numerator • Net reproductive rate: Same as GRR, but count only births of females who survive to reproductive age in the numerator

22. Net Reproductive Rate (NRR) • If NRR = 1,000, each generation will just replace itself • If NRR < 1,000, indicates a potentially declining population • If NRR > 1,000, indicates a potential population increase

23. Mortality Measures Related to Natality • Fetal Death Rate or Ratio: Used primarily by public health officials to estimate the health of populations Fetal Death Rate = Number of fetal deaths 20 weeks or more gestation in a given interval X 1,000 Fetal deaths plus live births in that interval Estimates risk of death associated with late states of gestation

24. Mortality Measures Related to Natality (cont.) Fetal Death Ratio = Number of fetal deaths 20 weeks or more gestation in a given interval X 1,000 Number of live births reported during the same time interval Measures fetal loss relative to live births

25. Mortality Measures Related to Natality (cont.) Perinatal Mortality Rate = Number of fetal deaths 20 weeks or more gestation plus number of neonatal deaths (28 days or less in age) during a given interval X 1,000 Number of fetal deaths 20 weeks or more gestation plus number of live births during the same interval Reflects events occurring during pregnancy and after birth

26. Mortality Measures Related to Natality (cont.) Number of deaths of neonates (28 days or less) in a given interval Neonatal Mortality Rate = X 1,000 Number of live births during the same interval Estimates events immediately after birth, primarily congenital malformations, prematurity and low birth weight

27. Mortality Measures Related to Natality (cont.) Infant Mortality Rate = Number of deaths under 1 year during a given interval X 1,000 Number of live births during the same interval Used for international comparisons; high rates indicate unmet public health needs and poor socioeconomic and environmental conditions

28. Mortality Measures Related to Natality (cont.) Maternal Mortality Rate = Number of deaths assigned to causes related to pregnancy during a given interval X 1,000 Number of live births during the same interval Rates reflect health care access and socioeconomic factors

29. Chart of Early Life Mortality Measures

30. Mortality Outcomes • Crude rate: • The number of events in a population over a given period of time, usually a calendar year • Crude rates reflect the probability of an event • As the probability of death increases with age, the crude death rate reflects the age structure of the population

31. Mortality Outcomes (cont.) Example: 1980 The larger crude death rate in Florida reflects the larger population of elderly in that state.

32. Mortality Outcomes (cont.) • Specific rate: • Used to construct rates for specific segments of the population so we can compare among strata or between groups (used especially for age, race, ethnicity, gender) • We can also construct cause-specific rates to compare rates among causes

33. Mortality Outcomes (cont.) • Examples • Age-specific rates • Gender-specific rates • Race-specific rates • Cause-specific rates