dietaryindex

dietaryindex standardizes dietary pattern analysis in epidemiological and clinical studies by calculating multiple dietary indexes from dietary intake data.

Key Features:

• Generic dietary index calculation functions: Accept any dietary assessment with preprocessed serving sizes of food groups and nutrients as defined by the research group that developed each index.
• 1-step functions for common datasets: Directly reference the National Health and Nutrition Examination Survey (NHANES), the Automated Self-Administered 24-h Dietary Assessment Tool (ASA24), the Diet History Questionnaire III (DHQ3), and the Block Food Frequency Questionnaire without requiring data preprocessing.
• Multiple dietary index calculations: Calculates the Healthy Eating Index (HEI)-2020, the Alternative HEI 2010, the Dietary Approaches to Stop Hypertension Index, the Alternate Mediterranean Diet Score, the Dietary Inflammatory Index, the American Cancer Society 2020 dietary index, and the Planetary Health Diet Index from the EAT-Lancet Commission.
• Validated scoring algorithms: Serving size definitions and scoring algorithms were validated by at least 2 independent researchers, demonstrating full accuracy (100%) in all generic functions with 2-decimal rounding precision compared with hand-calculated results.

Scientific Applications:

• Epidemiological dietary pattern analysis: Enables standardized calculation of dietary indexes across diverse study populations and dietary assessment methods.
• Clinical nutrition research: Supports assessment of diet quality and health-related dietary patterns using validated, comparable scoring methods.
• Cross-dataset comparison: Facilitates harmonized dietary index calculation across NHANES, ASA24, DHQ3, and Block Food Frequency Questionnaire data.

Methodology:

The package uses serving size definitions and scoring algorithms developed by the research groups that created each dietary index, with generic functions accepting preprocessed serving sizes of food groups and nutrients, and 1-step functions directly referencing common datasets and tools.