Using both principal component analysis and reduced rank regression to study dietary patterns and diabetes in Chinese adults.

ABSTRACT:

Objective

We examined the association between dietary patterns and diabetes using the strengths of two methods: principal component analysis (PCA) to identify the eating patterns of the population and reduced rank regression (RRR) to derive a pattern that explains the variation in glycated Hb (HbA1c), homeostasis model assessment of insulin resistance (HOMA-IR) and fasting glucose.

Design

We measured diet over a 3 d period with 24 h recalls and a household food inventory in 2006 and used it to derive PCA and RRR dietary patterns. The outcomes were measured in 2009.

Setting

Adults (n 4316) from the China Health and Nutrition Survey.

Results

The adjusted odds ratio for diabetes prevalence (HbA1c≥6·5 %), comparing the highest dietary pattern score quartile with th

SUBMITTER: Batis C 

PROVIDER: S-EPMC4721264 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature