This document outlines the strengths and challenges of cohort studies. The strengths include examining multiple health outcomes and exposures over time without binary classifications. Participants can change exposure levels. Exposures are measured before outcomes, allowing assessment of temporality. Challenges include loss to follow-up, expense of repeated data collection, long time to conduct, inefficiency for rare outcomes, reliance on historical data quality, ensuring blind outcome assessment, challenging exposure classification, requiring sufficient population exposure variation, and loss to follow-up potentially introducing bias if associated with outcomes or exposures.

1. Strengths
• Can assess multiple health outcomes (and do
not have to make binary as in case-control)
• Possible to examine multiple exposures
– May not be possible with double-cohort design (i.e.,
one cohort exposed, one cohort unexposed within the
study)
• Participants can move between exposure groups
over time (with incidence density as measure of
disease)

2. Strengths
• Exposures assessed before outcomes (for
prospective) ensuring temporality
• Direct measurement of disease rates, risks
• Capture changing exposures and outcomes in
time

3. Challenges
• Loss to follow-up
• Expense, feasibility and participant burden of
repeated data collection
• Time to conduct (for concurrent)
• Inefficient for rare outcome (rare in the study
population)
• Non-concurrent relies on availability and quality
of historical data

4. Challenges
• Have to assure assessment of outcomes is not
differential with respect to exposure
– Blinding may be possible
• Exposure classification may be challenging

5. Challenges
• Exposure(s) of interest must to have sufficient
variation in the population chosen
– Example: cannot study effect of lead paint exposure
on child development if all children in the population
live in housing built after 1978
– Example: NHS II established because women were
taking oral contraceptives from much younger ages
(compared to NHS I)

6. Challenges
• Loss to follow-up – one of biggest challenges for cohort
studies and trials
• May introduce bias in measure of association
– Bias = systematic difference between association observed and
causal effect
AR = 45 per 1000 AR = 29 per 1000

7. Challenges
• If loss of participants is associated with outcome,
measurement of rates/risks will be inaccurate (e.
g., more likely to lose people shortly before they
develop the outcome of interest)
• If loss of participants is also associated with
exposure will introduce bias (e.g., more likely to
lose people in the exposed group shortly before
they develop the outcome of interest)