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PHM 101 Basic Epidemiology > Ch 1. Understanding Epidemiology > Flashcards

Ch 1. Understanding Epidemiology Flashcards

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1
Q

Define epidemiology

A
  • The study of the distribution and determinants of health or events in specified populations, and the application of this study to control health problems
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2
Q

Purpose of epidemiological methods.

A
  • identify the causes of poor health
  • measure the strength of associations between causes and outcomes
  • evaluate interventions to improve health
  • monitor changes in population health over time.
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3
Q

What are the main uses of epidemiology?

A
  • Answer the 5 W’s
  • identify the causes of poor health
  • measure the strength of associations between causes and outcomes
  • evaluate interventions to improve health
  • monitor changes in population health over time.
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4
Q

What are some examples of health OUTCOMEs of interest?

A

Can be positive or negative: illness, infection, death, disability, survival.

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5
Q

What are the 2 factors that determine who is at risk?

A

Risk factors– predisposes a person to getting the outcome, like poverty.
Protective factors – less likely to get outcome, like vaccination.

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6
Q

What is the difference between EFFICACY and EFFECTIVENESS?

A

EFFICACY– how well an intervention works in a research controlled/ ideal setting
EFFECTIVENESS– how well an intervention work in the real world

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7
Q

What was the Doll and Hill study?

A

In 1950, Richard Doll and Austin Bradford Hill published a large and rigorous case-control study (Doll and Hill, 1950), which together with three other case-control studies highlighted the link between smoking and lung cancer.

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8
Q

What is “genetic epidemiology”

A
  • comparing the risk of disease in groups of relatives to the risk in the GENERAL POPULATION, to identify what PROPORTION could be attributed to genetics.
  • but because social settings are similar in families, focused instead on risk of disease by degree of relatedness
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9
Q

What is “social epidemiology”

A
  • study the effects of the social determinants of health, such as social class, income distribution, ethnicity, gender, and discrimination
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10
Q

What is “health economics”

A
  • study of financing and delivery of health services
  • how access to these services affect the individual and population
  • how best to use limited resources
  • analyse the decision-making processes of individuals and policy-makers that may affect health outcomes
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11
Q

What are current challenges in epidemiology?

A
  • environmental and lifestyle effects on pop health
  • aging population
  • advances in science and tech that allow for big data
  • role of media
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12
Q

What 2 groups are epidemiological studies divided into?

A
  • observational studies

- interventional studies

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13
Q

What 2 groups are epidemiological studies divided into?

A
  • observational studies- exposure already assigned (ex: behavior, nature, circumstance)
  • interventional studies- investigator assigns the exposure
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14
Q

What 2 groups can observational studies be divided into?

A
  • descriptive

- analytical (always has a comparison group)

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15
Q

What is descriptive epidemiology?

A

information on the distribution of health outcomes by age, population type, geography, and/or over time
- examples of sources: birth/ death registries, adverse tx reactions, hospital records

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16
Q

A synonymous term for “exposure” is…

A

risk factor

17
Q

In epidemiology, who represents the “counterfactual alternative reality”?

A
  • counterfactual- a scenario where the exposure (risk factor) did not occur
  • counterfactual group can be represented by folks that are unexposed (or did not have the risk factor)
18
Q

What is causaulity?

A

Relating the exposure/ risk factor to the outcome.

19
Q

For an association to be causal, the exposure must occur before or after the outcome?

A

BEFORE. Inferring causality is a complex process because there may be several risk factors that contribute in different ways to the outcome.

20
Q

Causality can be broken into what 2 types of causes?

A
  • Sufficient cause. The set of factors or conditions that can produce an outcome
  • Component causes. Contribute to the outcome occurring
21
Q

What is “sufficient cause”?

What makes up a “sufficient cause”?

A

The set of factors or conditions that can produce an outcome
- The factors that comprise the sufficient cause are called component causes, and contribute to the outcome occurring. Component causes = Contribute to the outcome occurring

22
Q

What is causality?

A

Relating the exposure/ risk factor to the outcome.

23
Q

What is a “necessary cause”?

A

A component cause that is essential for the outcome to occur is known as a necessary cause, for example tuberculosis cannot occur without Mycobacterium tuberculosis

24
Q

What factors affect a person’s exposure?

A
  • Environmental factors tend to affect exposure and may be physical (e.g. climate, altitude)
  • biological (e.g. vectors that transmit an agent)
  • structural (e.g. crowding, sanitation).
  • Human factors affect both exposure and response and include age, sex, ethnicity, behaviour, genetics, and nutritional and immunological status.
25
Q

What is a hypothesis?

A

A proposed association that can be tested

26
Q

What are four different types of analytical study?

A

Case control-
Cohort-
Ecological-
Cross-sectional-

27
Q

What is an ecological study? What type of study is this?

A

An analytical study. Using population level data to relate total freq of an outcome to avg level of exposure to a population. Ex- alcohol consumption and breast cancer rates by country.

28
Q

What is an ecological study? What type of study is this?

A

An analytical study. Using population level data to relate total freq of an outcome to avg level of exposure to a population. Ex- alcohol consumption and breast cancer rates by country.

29
Q

What is a cross-sectional study? What type of study is this?

A

An analytical study. Collect data on outcome and exposure at one point in time from a random sample of study subjects. For example, the presence of HIV infection in relation to prior male circumcision.

30
Q

What is a cohort study? What type of study is this?

A

An analytical study. Take a group with a shared exposure/ risk factor and follow the occurrence of the outcome over time. For example, occurrence of cervical cancer in relation to human papillomavirus infection.

31
Q

What is a cohort study? What type of study is this?

A

An analytical study. Take a group with a shared exposure/ risk factor and follow the occurrence of the outcome over time. For example, occurrence of cervical cancer in relation to human papilloma virus infection.

32
Q

What is a case- control study? What type of study is this?

A

An analytical study. Take individuals with and without the outcome and analyze the exposure rates. For example, mobile telephone use among people with brain tumours compared with that of people without brain tumours.

33
Q

What is an interventional study?

A

Considered ideal study because investigators allocate one group with a specific exposure, and another not. Then they follow to see the outcome frequencies comparing the two groups. For ex, the incidence of malaria among children using an insecticide-treated mosquito net can be compared with the incidence among those using an untreated mosquito net. Intervention studies may be randomized or non-randomized.

34
Q

What is “chance”?

A

random results or “random error”, like flipping a coin 10 times and 7 times it’s heads up.

35
Q

What is “bias”

A

refers to systematic errors that may misrepresent the association being investigated, such as if a coin had been altered so that it always landed face-up

36
Q

What is “confounding”?

A

caused when another factor, independently associated with both the outcome and exposure of interest, influences the association being investigated. For example, in Farr’s study of the cholera outbreaks, elevation was a confounder in the association between contaminated water and cholera.

37
Q

What are the 3 factors that can explain an association between exposure and outcome when that does not really exist?

A

chance
bias
confounding

PHM 101 Basic Epidemiology (6 decks)

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