Epiville

Confounding

Design Questions

1. Education, a marker of socioeconomic status, was one of the potential confounders considered in the study of pesticide use and breast cancer in Teitelbaum et al. (2007). Please explain why education was considered to be a potential confounder:

  1. Education is associated with high exposure to pesticide use. Those with higher education may have larger homes with more lawns and gardens in need of pesticide application to enhance their landscape's appearance. Further, more advanced education is associated with a higher risk of breast cancer (hypothesized to operate via a host of factors, including older age at having a first child), and is not in the causal pathway of interest between pesticide use and breast cancer (pesticide use is not hypothesized to cause education).
  2. Education is in the causal path between pesticide use and breast cancer. All variables in the causal pathway are potential confounders regardless of their association with exposure and outcome.
  3. Although education is not associated with pesticide use, advanced education is associated with a higher risk of breast cancer (hypothesized to operate via a host of factors, including older age at having a first child). Moreover, it is not in the causal pathway of interest between pesticide use and breast cancer (pesticide use is not hypothesized to cause education).
Answer (a) — correct: For a variable to be a confounder, it must fulfill three basic properties: 1) be associated with the exposure, 2) be a risk factor for the disease, and 3) not in the causal pathway of interest. Education, a marker of socioeconomic status meets these criteria. First, it is associated with pesticide use, hypothesized to operate via home ownership and the accompanying lawn and/or garden in suburban Nassau and Suffolk counties. Second, it is a risk factor for breast cancer, possibly related to delays in child bearing, which is associated with breast cancer. Finally, it is not hypothesized to be in the causal pathway between pesticide use and cancer.
Answer (b) — incorrect: A confounder cannot be an intermediate step in the causal pathway of interest. If a third variable is in the causal pathway of interest, it is not a confounder but a mediator.
Answer (c) — incorrect: A variable must fulfill three basic properties to be considered a confounder- one, that it is associated with the exposure of interest. The remaining criteria include: a risk factor for the disease, and not in the causal pathway of interest.

2. Would confounding due to education still be a problem if the investigators were able to conduct a cohort study instead of a case-control study?

  1. Confounding would not be a problem in a cohort study
  2. Confounding would still pose a problem in a cohort study
  3. Confounding would be minimal in a cohort study compared to a case-control study
Answer (a) — Incorrect: Confounding is a problem in all observational study designs. Remember, confounding is a "mixing of effects" between an exposure, outcome, and a third variable. Confounding results from the fact that risk factors are generally not evenly distributed between comparison populations (i.e., exposed and unexposed groups) in observational studies. In large experimental studies, randomization usually produces comparison populations that have nearly the same distribution of characteristics, thus eliminating (or minimizing) confounding.
Answer (b) — Correct: Confounding is a problem for all observational study designs. Because epidemiology research concerns human populations, we must always consider that certain characteristics (e.g., age, sex, education, income, etc.) may be unevenly distributed in our study populations.
Answer (c) — Incorrect: Confounding can be just as large in a cohort study as it is in a case-control study. Regardless of design, it is important to consider potential confounders in your work, both in the design and analysis stages of your study.

3. How was potential confounding by age handled in the design stage of the study?

  1. Randomization of subjects into cases and controls
  2. Restriction of cases and controls within a narrow age category
  3. Matching controls to cases on age
Answer (a) — incorrect: Subjects were not randomized in this study. Subjects can only be randomized in experimental designs (i.e., RCT's). The behavior of subjects cannot be manipulated by investigators conducting observational studies (e.g., cohort or case-control studies)
Answer (b) — incorrect: In this study cases and controls were not restricted to any specific age category.
Answer (c) — correct: Controls were frequency matched to cases by age (in 5-year intervals). See Ashengrau & Seage, pp. 295-296 for details on frequency matching. Matching in a case-control study is intended to created comparability in the underlying source population by creating "mini-studies" in which all individuals are within the same specific 5-year age range such that age can have no effect on the exposure disease relation in that particular mini-study.