Schuchardt · The British journal of nutrition 2023 · Biomarker calibration and cross-sectional cohort study · n=117,358

Estimation and predictors of the Omega-3 Index in the UK Biobank.

Cited 29 times in the scientific literature.

Level 3 - non-randomized controlled study

Biomarker calibration study and large cross-sectional cohort analysis

PubMed 36210531 · doi:10.1017/S0007114522003282 · record verified 2026-08-30

What was done

Researchers developed an equation to estimate the erythrocyte Omega-3 Index (eO3I) using plasma nuclear magnetic resonance (NMR) measurements of total n-3 PUFA% and DHA%. The equation was derived from an inter-laboratory calibration experiment using 250 blood samples with paired erythrocyte gas chromatography and plasma NMR data. The derived formula was then applied to 117,108 participants in the UK Biobank cohort to estimate their O3I and assess multivariable-adjusted cross-sectional correlations with demographic and lifestyle factors.

What was found

In the calibration set (n = 250), DHA% combined with (total n-3 % - DHA%) explained 65% of the variability in erythrocyte O3I (r = 0.832, P < 0.0001). Applied to 117,108 UK Biobank participants, the mean eO3I was 5.58% (SD 2.35%). Several variables significantly correlated with eO3I (all P < 0.0001): oily-fish intake (+), fish oil supplement use (+), female sex (+), older age (+), alcohol use (+), smoking (-), waist circumference and BMI (-), and lower socioeconomic status or less education (-). Evaluated lifestyle and demographic predictors accounted for 20.5% of total eO3I variance, with oily fish consumption explaining 7.0%.

Why it matters

This calibration provides a validated equation to estimate erythrocyte Omega-3 Index from high-throughput plasma NMR data, enabling large-scale epidemiological investigations of omega-3 biostatus and chronic disease risk in the UK Biobank.

Limits

The Omega-3 Index in the UK Biobank was computationally estimated rather than directly measured via erythrocyte gas chromatography. The calibration sample was relatively small (n = 250). Evaluated demographic and dietary predictors explained only ~20.5% of eO3I variance, leaving the majority unexplained, and the cross-sectional design cannot establish causality.

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