Association between mixed intake of multi-nutrients and cognitive function among the elderly in northern China: Three statistical models

Abstract Few studies have considered nutrients as a mixture and their impact on MCI. The generalized linear regression (GLM), weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) models are fitted to estimate the association between intake of a mixture of nutrients and MCI. Comparing the results of the three statistical models, we found that there were similarities and differences in the correlation between nutrients and MCI. Considering the advantages and disadvantages, we recommend estimating the joint effects of nutrients mixture by applying diverse statistical methods. Applying multiple methods appropriate for the study questions and data structures may help obtain a more comprehensive picture of the intake-response relationships. In the future, studies need to move from a “one nutrient at a time” approach to simultaneous analyses of multiple nutrients intakes in order to understand and quantify the joint effect of nutrients mixture on health.