Epidemiology Lectures 5 And 6

Front 1

What are the two reasons for making quantitative comparisons in epidemiology?

Back 1

(1) To understand the impact of exposures on population health

(2) To better understand risk factors and causation for public health outcomes

Front 2

What is standardization?

Back 2

A method of comparing risks of disease between two populations who have different distributions of another characteristic that itself affects their risk of disease (e.g., gender)

Front 3

Generally, how does standardization work? [2]

Back 3

It creates fictitious "expected" frequencies for a "fairer" comparison between heterogeneous groups; adjustment involves weighting of category-specific risks

Front 4

Define a crude rate.

Back 4

A "summary measure": divide the total number of cases in the population by total population in a specific time period

Front 5

A category-specific rate is...

Back 5

A crude rate within a specific strata of population (age group, etc.)

Front 6

What is it called when you calculate a summary rate for each population using a procedure designed to minimize or remove the differences in age composition?

Back 6

Age-adjusted or age-standardized rate (fictitious/expected rate, but valid for comparison purposes)

Front 7

What is the equation for age-adjusted rate?

Back 7

AAR = (age-specific rate*weight)

Front 8

What are weights equal to in the AAR equation?

Back 8

The proportion of the standard population in each age category

Front 9

What is the interpretation of the AAR?

Back 9

The age-adjusted rates are the total mortality rates that the populations would have experienced if they each had the same age-distribution as that of the standard population

Front 10

An absolute measure of association calculates... What does it provide information about?

Back 10

The difference in disease frequency between an exposed and unexposed group; provides an attributable risk/measure of excess risk (info on the public health impact of an exposure)

*is only meaningful when exposure is accepted as causal

Front 11

Under absolute measures of association, there are three main types of studies, the first of which is cross sectional. How are subjects classified in a cross-sectional study?

Back 11

According to exposure (Y/N) and outcome (Y/N)

Front 12

How are subjects classified in a cohort study?

Back 12

Into exposed and un-exposed subjects (all have the outcome of interest)

Front 13

What are the main ways in which you can distinguish between an absolute and a relative rate?

Back 13

Absolute is the difference in disease frequency between two populations, while relative is the ratio

Front 14

How are absolute comparisons interpreted?

Back 14

Excess risk in the exposed group compared to the unexposed group that is associated with exposure (preferred interpretation)

Front 15

What does the term "attributable" risk indicate?

Back 15

Acceptance of causality

Front 16

What is the "verbal" interpretation of risk difference in the infant diarrhea scenario?

Back 16

The excess risk of diarrhea among LA infants compared to HA infants is 42%.

The total risk of diarrhea among LA infants is due to both LA and other factors. This formula takes out the risk due to others factors (baseline risk in the unexposed, HA group) so we are left with the amount of risk associated with LA (excess risk in the exposed group).

Front 17

Dual interpretation of radiation and breast cancer?

Back 17

The excess risk of breast cancer among those exposed to radiation is 6.8 cases per 10,000 PY.

If we eliminated radiation exposure, we could reduce the risk of breast cancer among exposed by 6.8 cases per 10,000 PY, assuming that such radiation causes breastcancer

Front 18

Interpretation for population risk difference?

Back 18

In the total population, the excess risk of diarrhea that is associated with LA is 20%.

In the total population, 4 excess breast cancer cases for every 10,000 PY of observation are associated with radiation exposure.

Front 19

Interpretation of attributable proportion among exposed?

Back 19

49% of cases of diarrhea among LA titer infants is associated with LA titer.

46% of cases of breast cancer among those exposed to radiation is associated with radiationexposure.

Front 20

Interpretation of attributable proportion among total population?

Back 20

31% of cases of diarrhea in this total population of infants is associated with LA titer.

31% of cases of diarrhea in this total population of infants is associated with LA titer.

Front 21

Lecture 6: What are the two stated reasons for making comparisons in epidemiology?

Back 21

(1) To understand the impact of exposures on population health, and (2) to better understand risk factors/causation for health outcomes

Front 22

What do measurements such as the prevalence ratio or the CI ratio provide? [2]

Back 22

A measure of the strength of association between an exposure and an outcome (tells you how many times higher or lower the disease outcome is among the exposed compared to the unexposed)

Front 23

Interpretations of RR should always specify...

Back 23

For whom, compared to whom

Front 24

Interpret the results of the CI Relative Risk ratio for infants with diarrhea.

Back 24

Infants whose mothers’ milk had low antibodies had 1.96 times the risk of diarrhea over the 10 day period compared to infants whose mothers’milk had high antibodies

Women who were exposed to radiation had 1.86 times the risk of developing breast cancer compared to women who were notexposed, or 86% increased risk of breast cancer.