cross-sectional study Flashcards

1
Q

cross-sectional study aka

cross-sectional

A

prevalence study

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2
Q

we measure

cross-sectional

A

exposure and disease measures obtained at individual level AT SAME TIME

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3
Q

observation

cross-sectional

A

single period of observation

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4
Q

what is cross-sectional study good for

cross-sectional

A

good for hypothesis generation and to estimate magnitude and distribution of a health problem

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5
Q

start with

cross-sectional

A
  1. defined population
  2. gather data on exposure and disease
  3. 4 groups:
    - exposed, have disease
    - exposed, no disease
    - not exposed, have disease
    - not exposed, no disease
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6
Q

cross-sectional calculations use

cross-sectional

A

prevalence

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7
Q

prevalence of disease in exposed formula

cross-sectional

A

a/a+b

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8
Q

prevalence of disease in non-exposed formula

cross-sectional

A

c/c+d

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9
Q

prevalence of exposure in diseased

cross-sectional

A

a/a+c

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10
Q

prevalence of exposure in not diseased

cross-sectional

A

b/b+d

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11
Q

design: finding the sample

cross-sectional

A
  • take sample of ppl. or households in a defined geographic area
  • maybe defined by study question (occupational or regional exposure)
  • random sampling of an area
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12
Q

measuring exposure

cross-sectional

A

questionnaires
records
lab tests
physical measurements

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13
Q

what factors are easily measured by cross-sectional studies

cross-sectional

A

factors that don’t change as a result of disease
EX: blood group

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14
Q

measurement of disease

cross-sectional

A

questionnaire for symptoms/diagnosis
physical exam
other tests (x-ray, mammography)
if possible, determine onset
need established diagnostic criteria

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15
Q

confounder

cross-sectional

A

factor related to risk factor or exposure of interest and to health outcome (disease status)

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16
Q

confounders issues and how to resolve

A

can cause over or under estimate of observed assoication btwn exposure and health outcome

if you collect confounder data during study, you can control for it with statistics

17
Q

pros

cross-sectional

A

based on general population, not only those seeking care

18
Q

cons

cross-sectional

A

no incidence = no risk
can’t study disease with low prevalence
can’t determine temporality of exposure
it’s a snapshot: may not reflect exposure status when disease began