Data extraction
Two reviewers used a custom data abstraction
form to evaluate and summarize
selected articles. Abstracted information
included authors, year, location, source
of participants, sample composition, assessment
of diabetes/depression, and
matching and/or statistical adjustment for
potential confounders. If multiple risk estimates
(with error measurements) were
presented in a given manuscript (e.g.,
nested multivariable models), the estimate
that most closely adjusted for only
demographic characteristics (e.g., age,
sex, race, socioeconomic indicators, and
marital status/household composition)
was selected. We chose this approach because
some studies adjusted for prominent
effect modifiers (i.e., family history,
health behaviors, adiposity) while others
did not, and thus the interpretation of the
cases of either depression (for diabetes
predicting depression onset) or diabetes
(for depression predicting diabetes onset).
In the event of multiple publications,
only the most recent manuscript for a particular
study population was included.