Adjusting for energy intake in dietary pattern investigations using principal components analysis

Area of Science:

• Nutritional epidemiology
• Dietary pattern analysis
• Statistical modeling

Background:

• Principal component analysis (PCA) is commonly used to derive dietary patterns.
• The impact of energy adjustment on PCA-derived dietary patterns is not well understood.
• Understanding this impact is crucial for accurate nutritional research.

Purpose of the Study:

• To investigate the effect of energy adjustment on dietary patterns derived via PCA.
• To examine the subsequent impact on associations with nutrient intake and birthweight.

Main Methods:

• Utilized data from 12,053 pregnant women in the Avon Longitudinal Study of Parents and Children.
• Performed PCA on food frequency questionnaire data, both before and after energy adjustment.
• Assessed associations with nutrient intakes and birthweight for different adjustment strategies.

Main Results:

• Minor differences observed in extracted components and factor loadings between adjusted and unadjusted analyses.
• Energy adjustment led to reduced correlation coefficients with nutrient intakes.
• No significant difference in the effect of dietary pattern scores on birthweight regardless of energy adjustment timing.

Conclusions:

• Energy adjustment prior to PCA is not necessary for food frequency questionnaire data.
• Nutrient intake and outcome associations can be evaluated at later analytical stages.
• This simplifies dietary pattern analysis without compromising key findings.