Measures of Association Intermediate Epidemiology

Objectives To play “name that rate” To discuss case-control study designs To discuss and calculate measures of association To discuss the design and measures of association of a study

Name that Rate What’s the numerator What’s the denominator What is the type of rate

N=0 N=2 N=84 N=237N=58 American Indian/ Alaska Native White Not Hispanic Black Not Hispanic Hispanic Asian/Pacific Islander AIDS Rates per 100,000 Children <13 Years of Age by Race/Ethnicity, Reported in 1998*, United States Race/Ethnicity *US Rate=0.7/100,000 N=382 Rate per 100,000

VI 29.6 PR 44.3 < AIDS Rates per100,000 Population Reported in1998 Rate per 100,000 DE MA RI CT NJ MD DC NH VT 3.4

Year of Report American Indian/ Alaska Native Black, not Hispanic Hispanic Asian/Pacific Islander White, not Hispanic Proportion of AIDS Cases, by Race/Ethnicity and Year of Report, , United States Percent of Cases

AIDS Cases in Adult/Adolescent Women by Race/Ethnicity per 100,000 Population, Reported in 1998, United States Race/Ethnicity White, not Hispanic Black, not Hispanic Hispanic Asian/Pacific Islander American Indian/ Alaska Native Total* Cases 2,031 6,775 2, ,998 Rate *Includes 48 women whose race/ethnicity is unknown.

Born1993-March 1998 in 29 States ‡, United States who Received or whose Mothers Received any ZDV* * Any ZDV=Prenatal, intrapartum, or neonatal receipt of Zidovudine to reduce perinatal HIV transmission Quarter-Year of Birth 1993 N= N= N= N= N= N=281 ‡ Includes 29 areas that have conducted pediatric HIV Surveillance since 1993; data reported through March 1999 Percent of Perinatally HIV Exposed or Infected Children Percent Receiving Zidovudine

Northeast N=14,399 North Central N=4,317 South N=19,474 West N=8,121 Metropolitan area 50, ,999 population Non- metropolitan area AIDS Cases by Region and Size of Place of Residence Reported in 1998, United States % % Metropolitan area 500,000 population

White, not Hispanic Black, not Hispanic Hispanic Asian/Pacific Islander American Indian/ Alaska Native 33% 45% 20% *Includes 211 persons with unknown race/ethnicity <1% 1%1% 1%1% 4%4%

Exposure Category N= N=2, N=7, N=1,150 Injection drug use 9 %% Heterosexual contact Transfusion recipient Other/not identified* Age at Diagnosis (in years) *Includes patients whose medical record review is pending; patients who died, were lost to follow-up, or declined interview; and patients with other or undetermined modes of exposure AIDS in Women, by Exposure Category and Age at Diagnosis, Reported in 1998, United States

Case-control study Persons are categorized by disease status and then compared for their exposure status The odds ratio is the measure of association (an estimate of relative risk) The assumption is that the cases and controls originate from the same hypothetical source cohort. When this assumption is not met, the results are susceptible to selection bias Traditional method is case-based case-control study

Nested case-control or case-cohort When cases are identified within a well defined cohort Also known as a hybrid or ambi- directional study

Alternatives for selection of controls and a case-control study Case-cohort - When the controls are randomly selected from a defined cohort at baseline. Nested case-control – based on incidence density sampling (matching cases and controls on duration of follow-up) or risk-set sampling (or comparison of cases with a subset of the cohort members as risk of being cases at the time when each case occurs)

Case-crossover Compares the exposure status of a case immediately before it’s occurrence with that of the same case at some other prior time Appropriate for the study of acute (brief) exposures that produce transient change in risk of an acute condition (eg, MI and episodes of anger or sexual activity)

Matching Performed to reduce confounding Can be individually matched or frequency matched

Advantages of Matching May be the only way to control some degrees of confounding (especially very strong confounding) Tends to increase the statistical power Logistically straight forward

Disadvantages of Matching May be impossible to find a control When matching is done, the association between the matched variables and the outcome can no longer be assessed Also eliminates the ability to assess additive interaction between the matched variable and the exposure of interest Special statistical tests need to be used By matching you remove the representativeness of your controls Once matching is done, it cannot be undone No statistical power is gained if the matching variables are weak confounders

Relative Risk for a disease exposure RR = 75/100 = /100 C.I. ( )

Relative Risk for preventive intervention RR = 25/100 =.50 50/100 C.I. ( )