Cross-sectional studies Flashcards
Cross-sectional study - design
Sample (or census) of subjects is obtained from the source population, and the presence/absence of outcome and status with regard to putative risk factors (exposures) is ascertained at that point in time.
Cross-sectional study - sampling
Ideally, representative sample is drawn through a random sampling process (SRS, stratified, cluster, multistage).
Cross-sectional study - types of bias (3)
- Selection bias: a) non-response bias - if questionnaire is used and responders differ to non-responders; b) survival bias - diseased animal must live long enough to be sampled (underrepresent cases that don’t survive)
- Information bias: a) recall bias - if exposures are self-reported
- Confounding bias
Cross-sectional study - analysis
Prevalence of disease in the exposed vs unexposed (prevalence risk ratio). Odds ratios often used as logistic regression is frequently used to model multivariable data
Cross-sectional study - advantages (4), disadvantages (3)
Advantages
- Useful for describing baseline characteristics including prevalence (hypothesis generation)
- Multiple outcomes and exposures can be studied
- Relatively quick
- Relatively cheap
Disadvantages:
- Because cross-sectional studies measure prevalence, and prevalence is related to both incidence and duration of disease, it is impossible to distinguish between those exposures which influnce disease occurance vs disease duration
- Difficult to investigate cause-effect relationships because exposure and outcome are measured at the same time (best for permanent exposures like breed or gender)
- Susceptible to bias due to low response/recall issues
Cross-sectional study - example
KAP of zoonoses in clients of single vet practice - aims to assess knowledge, beliefs and experiences with zoonoses in relation to type of animal owned, gender, immune status etc
- External validity: Non-random sample (not representative of all proactices) - findings can’t be extrapolated to other practices
- Internal validity:
- Selection bias: a) non-response bias could arise if clients chosing to participate differ with regard to exposures vs those who don’t; b) survival bias could arise if certain client groups (e.g. immunocompromised) are underrepresented because they did not survive infection
- Information bias: a) Recall bias - clients who experience a zoonoses might be more likely to recall a particular incident leading to transmission (bite, scratch)
- Confounding bias: age may be a confounder in the association betwen education level and zoonosis knowledge