A local health department is conducting an observational study to investigate the association between residential proximity to a major highway and the incidence of childhood asthma. The investigators identify household income level as a significant potential confounder in this relationship. Which of the following strategies are appropriate to control for the confounding effect of household income in this study? (Select all that apply)
- Matching participants in the exposed and unexposed groups based on their household income.Answer
- Including household income as a covariate in a multivariable regression analysis.Answer
- CCalculating stratum-specific odds ratios to verify they are significantly different from one another.
- DBlinding the researchers to the participants' household income during the data collection process.
- EIncreasing the overall sample size to ensure that household income is naturally balanced between the groups.
Answer
The appropriate strategies are matching participants based on their household income and including household income as a covariate in a multivariable regression analysis.
To control for confounding in an observational study, investigators can use strategies during the design phase or the analysis phase. Matching participants based on the confounding variable (household income) during enrollment ensures that the confounder is equally distributed between the exposed and unexposed groups. During the analysis phase, including the confounder as a covariate in a multivariable regression model allows the statistical software to mathematically adjust for its effect, isolating the true relationship between the primary exposure and the outcome.
Step-by-Step Solution
Key Concept
Confounding can be effectively controlled during the design phase (via matching, restriction, or randomization) or the analysis phase (via stratification or multivariable regression).