10. Association and Causation

Question 1

variable

Answer 1

any observable event that can vary

age weight

Question 2

variables are either

Answer 2

associated or they are not

if not they are independent

if they are they are dependent

Question 3

positively associated

Answer 3

they both increase and decrease together

Question 4

negatively associated

Answer 4

they increase and decrease inversely

Question 5

Types of association

Answer 5

no association = X and Y independent

associated = X does not cause Y (non-causally) X causes Y (causally)

Question 6

independent variable

Answer 6

factor that stands alone and isn’t changed by other factor you are trying to measure

Question 7

dependent variable

Answer 7

factor that is influenced or changed by another factor

Question 8

Independent vs dependent

Answer 8

independent variable causes a change in the dependent variable and it is not passible that dependent variable could cause a change in independent variable

Question 9

confounding variable

Answer 9

is interference bt third factor that distorts the association within a study of two primary variables

Question 10

What are the illustrations of association

Answer 10

scatter plots

dose response curves

epidemic curve

contingency table

Question 11

importan thing about causation

Answer 11

association does not prove causation

Question 12

threshold

Answer 12

to the lowest dose at which a particular response occurs

Question 13

epidemic curve

Answer 13

graphic plotting of the distribution of cases by time of onset

Question 14

contingency table

Answer 14

tabular method of demonstrating association

Question 15

central concern of epidemiology

Answer 15

one of the central concerns of epidemiology is to be able to assert that a causal association exists between an exposure factor and disease

Question 16

causality criteria

Answer 16

consistency

strength

specificity

temporality

coherence

Question 17

consistency

Answer 17

association has been observed repeatedly ideally by different observers

Question 18

strength of association

Answer 18

refers to magnitude of relative risk or odds ratios from observed studies

Question 19

specificity

Answer 19

one particular exposure produces one specific outcome

Question 20

temporality

Answer 20

the exposure or factor must precede the outcome or disease

Question 21

coherence

Answer 21

synonymous with biological plausability

cause and effect should not conflict the generally known facts

Question 22

multifactor causality

Answer 22

many types of causal relationships involve diseases with more than one causal factor

Question 23

two models of multifactorial causality

Answer 23

epidemiological triangle

web of causation

Question 24

web of causation

Answer 24

many points not just the three

smokeing

ethnicity

diet

excersise

lots of factors can cause it and pull it one what or another

Question 25

How can chance be ruled out

Answer 25

we can never completely rule out chance

Question 26

how to minimize chance

Answer 26

minimize bias

work through causality criteria

Question 27

risk factor

Answer 27

exposure that is associated with a disease morbidity mortality or adverse health outcome

Question 28

risk assessment

Answer 28

methodology used to provide quantitative measurements of risk to health

Question 29

probability vs odd

Answer 29

probability = chance or risk of occuring

odds= ration of probability of an event occurring to the probability of an even not occurring

odds= P/(1-p)