Randomized controlled trials (that carefully control for potential confounders such as diet, physical activity, and body composition) are required to adequately investigate the effects of supplementation with long-chain n-3 PUFA on insulin sensitivity and metabolism.
Studies vary in the number of subjects, cohort characteristics, measurement of exposure and control for potential confounders.
Logistic regression was used to control for potential confounders.
These differences persist in multiple regression models that control for potential confounders.
A logistic regression model was used to calculate odds ratios and 95% confidence intervals and to control for potential confounders.
To control for potential confounders, the RH, long-term and seasonal trends, day of the week (DOW), and holidays were introduced into the model simultaneously.
We conducted a cross-sectional survey of 2,022 residents of historically underserved Appalachian Kentucky, an ideal location due to pervasive low income and our ability to control for potential confounders such as race/ethnicity and residential heterogeneity.
The remaining studies used multivariable methods to control for potential confounders associated with the outcomes.
Multivariate regression models for cognitive measures included control for potential confounders including age, sex, education, income and ancestry admixture.
We also examine the correlation between private sector participation and key background factors (socioeconomic development, business environment and governance) and use multivariate regression to control for potential confounders.
Control for potential confounders is particularly important.
