Food Predictors of Plasma Carotenoids

Abstract

Empirical prediction models that weight food frequency questionnaire (FFQ) food items by their relation to nutrient biomarker concentrations may estimate nutrient exposure better than nutrient intakes derived from food composition databases. Carotenoids may especially benefit because contributing foods vary in bioavailability and assessment validity. Our objective was to develop empirical prediction models for the major plasma carotenoids and total carotenoids and evaluate their validity compared with dietary intakes calculated from standard food composition tables. 4180 nonsmoking women in the Nurses’ Health Study (NHS) blood subcohort with previously measured plasma carotenoids were randomly divided into training (n = 2787) and testing (n = 1393) subsets. Empirical prediction models were developed in the training subset by stepwise selection from foods contributing ≥0.5% to intake of the relevant carotenoid. Spearman correlations between predicted and measured plasma concentrations were compared to Spearman correlations between dietary intake and measured plasma concentrations for each carotenoid. Three to 12 foods were selected for the α-carotene, β-carotene, β-cryptoxanthin, lutein/zeaxanthin, lycopene, and total carotenoids prediction models. In the testing subset, Spearman correlations with measured plasma concentrations for the calculated dietary intakes and predicted plasma concentrations, respectively, were 0.31 and 0.37 for α-carotene, 0.29 and 0.31 for β-carotene, 0.36 and 0.41 for β-cryptoxanthin, 0.28 and 0.31 for lutein/zeaxanthin, 0.22 and 0.23 for lycopene, and 0.22 and 0.27 for total carotenoids. Empirical prediction models may modestly improve assessment of some carotenoids, particularly α-carotene and β-cryptoxanthin.

Intakes of Lutein, Zeaxanthin, and Other Carotenoids and Age-Related Macular Degeneration During 2 Decades of Prospective Follow-up

“…The primary food sources for measured plasma carotenoid levels in the NHS 31 were cooked and raw spinach for lutein/zeaxanthin, oranges and orange juice for β-cryptoxanthin, oked and raw carrots for both α- and β-carotene, and tomato sauce for lycopene (Figure 2), consistent with the National Health and Nutrition Examination Survey. 33 These foods were generally inversely related to advanced AMD, although with variation for specific forms of these foods (Figure 2).…”

“…We thus used a previously validated empirical prediction model among 4180 nonsmoking women in the NHS that related carotenoid-containing foods directly to the measured plasma carotenoid level using linear regression. 31 The regression coefficient of each food in the model reflected a weighted contribution to the bio-available level. We then derived predicted plasma carotenoid scores for all participants by multiplying the consumption frequency of each food by its regression coefficient and summing across all foods.…”

“…The empirical prediction model demonstrated improved assessment of carotenoid intakes compared with the conventional food composition–based method. 31 …”

Dietary Intakes of Eicosapentaenoic Acid and Docosahexaenoic Acid and Risk of Age-Related Macular Degeneration

“…29 Briefly, among food sources of EPA and DHA, we used stepwise linear regression to select foods that were significantly predictive of EPA and DHA blood measurements (p < 0.05). We used the average of food intake between 1986 and 1990 FFQs in the NHS and between 1990 and 1994 FFQs in the HPFS to correspond with the time of blood draw and to reduce within-person variation.…”

Dietary intake of α-linolenic acid and risk of age-related macular degeneration ,

“…This method has been described previously (27,40). Briefly, we used the average of food intake from the 1986 and 1990 FFQs in the NHS and from the 1990 and 1994 FFQs in the HPFS to reduce the within-person variation of intake and to correspond with the time of blood draw.…”