Chapter 9 Flashcards

1
Q

Which study provides a snapshot of the health status of a population at one point in time?

A

Cross-sectional survey

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2
Q

Cross-sectional studies are also called:

A

Prevalence studies

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3
Q

Why are cross-sectional studies the most popular study approaches in the health sciences?

A

Because they allow for the rapid collection of new data

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4
Q

What is the goal of a cross-sectional survey?

A

To measure the proportion of the population with a particular exposure and disease

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5
Q

A cross-sectional study should be done over a ____(long/short) period of time based on a representative sample of a population.

A

Short

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6
Q

Cross-sectional surveys are used to:

A

1) Describe communities
2) Assess population needs
3) Support program planning
4) Monitor and evaluate programs
5) Establish baseline data prior to the initiation of longitudinal studies

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7
Q

What is epidemiology?

A

The study of the distribution and determinants of health of populations

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8
Q

Explain a cross-sectional study

A

The researcher asks a few hundred people to complete a short questionnaire, and then the data is analyzed.

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9
Q

What is one important requirement for the participants in a cross-sectional survey?

A

The participants must be reasonably representative of some larger population

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10
Q

What does representativeness mean?

A

The sample population must be as diverse as the source population

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11
Q

When do we do cross-sectional surveys?

A

1) The time is limited

2) The budget is small

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12
Q

What statistical measure do we use for cross-sectional surveys?

A

Prevalence

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13
Q

What is a KAP survey?

A

A commonly used type of cross-sectional study that asks participants about their Knowledge, Attitudes, and Practices.

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14
Q

KAP surveys can be particularly helpful for:

A

Identifying gaps between what people know and how they act on that knowledge.

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15
Q

Give an example on KAP survey.

A

The adults in the survey might demonstrate high knowledge about the benefits of exercise on cardiovascular health but at the same time indicate that they rarely exercise because a variety of perceived barriers prevent them from being as physically active as they know they ought to be for maximum fitness.

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16
Q

What does a repeated cross-sectional study do?

A

Re-samples and re-surveys representatives from the same source population at two or more different time points.

17
Q

Which method is used for large studies conducted by the CDC?

A

Repeated cross-sectional surveys

18
Q

Give three examples of repeated cross-sectional surveys

A

1) Behavioral Risk Factor Surveillance System (BRFSS)
2) National Health and Nutrition Examination Survey (NHANES)
3) U.S. National Health Interview Survey (NHIS)

19
Q

True or false:

A repeated cross-sectional study design tracks the same individuals forward in time.

A

False; A new set of participants is sampled from the source population each time a survey is conducted.

20
Q

Repeated cross-sectional surveys can reveal trends in:

A

Population-level metrics over time (NOT individual level changes)

21
Q

Which study is used to study individual participants over a long period of time?

A

Longitudinal cohort study.

22
Q

Cross-sectional surveys measure the prevalence of various:

A

1) Exposure histories
2) Disease states
3) Demographic characteristics
In one well-defined population at one point in time (or short period of time)

23
Q

What is the most common way to report results for a cross-sectional survey?

A

By reporting the prevalence rate

24
Q

What is the prevalence rate?

A

The percentage of the population with a given trait at the time of the survey.

25
Q

What other ways can you report the results for a cross-sectional survey?

A

By comparative measures, such as prevalence rate ratios.

26
Q

What are prevalence rate ratios?

A

They compare the prevalence of a characteristic in two population subgroups by taking a ratio of their prevalence rates.

27
Q

Can cross-sectional surveys assess causality? Why or why not?

A

No they cannot, because a cross-sectional survey has no time dimension. We can say that an exposure can be “associated” or “related to a disease but we cannot show that an exposure caused a disease.