A follow up study (also called cohort study, incident study, prospective study, or longitudinal study),
compares disease in exposed to disease in non-exposed groups after a period of follow-up. It can be prospective (forward),
retrospective (backward), or ambispective (both forward and backward) follow-up. In a nested case control design, a case control
study is carried out within a larger follow up study. The follow-up cohorts may be closed (fixed cohort) or open (dynamic
cohort). Analysis of fixed cohorts is based on CI and that of open cohorts on IR.

DESIGN and DATA COLLECTION

The study population is divided into the exposed and unexposed populations. A sample is taken from
the exposed and another sample is taken from the unexposed. Both the exposed and unexposed samples are followed for appearance
of disease. The study may include matching, (one-to-one or one-to-many), pre and post comparisons, multiple control groups,
and stratification. The study cohort is from special exposure groups, such as factory workers, or groups offering special
resources, such as health insurance subscribers. Information on exposure can be obtained from the following sources: existing
records, interviews/questionnaires, medical examinations, laboratory tests for biomarkers, testing or evaluation of the environment.
The time of occurrence of the outcome must be defined precisely. The ascertainment of the outcome event must be standardized
with clear criteria. Follow-up can be achieved by letter, telephone, surveillance of death certificates and hospitals. Care
must be taken to make sure that surveillance, follow-up, and ascertainment for the 2 groups are the same.

In non-random non-response on exposure, the risk ratio is valid but the distribution of exposure in
the community is not valid. In non-random non-response on outcome, the odds ratio is valid but the disease incidence rate
is not valid. There is a more complex situation when there is non-response on both exposure and outcome. In general random
non-response is better than non-random or differential non-response. Loss to follow-up can be related to the outcome, the
exposure and to both outcome and exposure. The consequences of loss to follow-up are similar to those of non-response. In
cases of regular follow-up, it is assumed that the loss occurred immediately after the last follow-up. If the loss to follow-up
is related to an event such as death, it can be assumed that the loss was half-way between the last observation and the death.

Five types of bias can arise in follow-up studies. Selection bias arises when the sample is not representative
of the population. Follow-up bias arises when the loss to follow-up is unequal among the exposed and the unexposed, when disease
occurrence leads to loss to follow up, when people may move out of the study area because of the exposure being studied, and
when the observation of the two groups is unequal. Information/misclassification bias arises due to measurement error or misdiagnosis.
Confounding bias arises usually due to age and smoking because both are associated with many diseases. Post-hoc bias arises
when cohort data is used to make observations that were not anticipated before.

STATISTICAL PARAMETERS

Both incidence and risk statistics can be computed**. **The
incidence statistics are the incidence rate and the cumulative incidence. The risk statistics are either the risk difference
or the various ratio statistics (risk ratio, the rate ratio, the relative risk, or the odds ratio).

STRENGTHS and WEAKNESSES

The cohort design has 4 advantages: it gives a true risk ratio based on incidence rates, the time sequence
is clear since exposure precedes disease, incidence rates can be determined directly, and several outcomes of the same exposure
can be studied simultaneously. It has 5 disadvantages: loss to subjects and interest due to long follow-up, inability to compute
prevalence rate of the risk factor, use of large samples to ensure enough cases of outcome, and high cost. The cost can be
decreased by using existing monitoring/surveillance systems, historical cohorts, general population information instead of
studying the unexposed population, and the nested case control design. Follow-up studies are not suitable for study of diseases
with low incidence.

SAMPLE SIZE COMPUTATION

Two factors are considered: the estimated proportion of the risk factor in the general unexposed population,
the minimum detectable difference in outcome between the exposed and unexposed groups. Sample size computations are usually
made assuming 95% confidence intervals.