Rapid, Digital Dietary Assessment in Association with Cardiometabolic Biomarkers

Area of Science:

• Cardiovascular disease research
• Metabolic health studies
• Nutritional science and technology

Background:

• Cardiometabolic health is influenced by diet quality.
• Accurate dietary assessment is crucial for understanding these associations.
• Traditional dietary assessment methods can be time-consuming and prone to recall bias.

Purpose of the Study:

• To investigate the relationship between dietary intake, assessed via a rapid, image-based digital tool, and cardiometabolic health biomarkers.
• To evaluate the utility of a novel digital diet assessment technique in a clinical setting.

Main Methods:

• Retrospective analysis of 546 adults' blood biomarkers and dietary data.
• Dietary intake assessed using the Diet Quality Photo Navigation (DQPN®) technique via Diet ID™ tool.
• Statistical analysis using Pearson and Spearman correlation coefficients.

Main Results:

• Diet quality measures significantly correlated with HDL-C, triglycerides, hs-CRP, HgbA1c, fasting insulin, and HOMA-IR.
• The digital tool's continuous and ordinal diet quality measures showed significant associations with multiple cardiometabolic biomarkers.
• Significant correlations were observed across various sample sizes for different biomarkers.

Conclusions:

• Rapid, digital assessment of diet quality using pattern recognition is significantly associated with key cardiometabolic health biomarkers.
• This technology provides a viable alternative to traditional dietary recall methods.
• Findings support the use of digital tools for efficient and accurate dietary assessment in clinical practice.