Evaluation of the odd fatty acids 15:0 and 17:0 in serum and adipose tissue as markers of intake of milk and dairy fat

Brevik, Asgeir; Veierød, Marit B.; Drevon, Christian A.; Andersen, Lene Frost

doi:10.1038/sj.ejcn.1602256

Cited by 141 publications

(133 citation statements)

References 33 publications

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“…However, even this sample size may often be insufficient to estimate validity coefficients precisely 4 . Of the 16 published studies considered in this review, seven of them used sample sizes equal to or greater than 100 6,9,18,20,23,24,25 , while four had sample sizes below 50 10,11,21,26 . Indeed, larger sample sizes will reduce the chances of Heywood case events and the negative correlations between variables 9,12 .…”

Section: Food Consumption Validation Studies Using the Triads Methodsmentioning

confidence: 99%

“…The nutrients investigated in the studies reviewed were: carotenoids (7) 6,9,10,15,18,19,20 , tocopherols (6) 6,9,10,15,18,20 , retinol (1) 9 , folic acid (4) 9,17,21,22 , fatty acids (4) 6,11,23,24 , vitamin B 12 (2) 17,22 , proteins (3) 9,15,25 , potassium (2) 15,20 , cholesterol (1) 20 , dithiocarbamate (1) 26 , phytoestrogens (1) 27 and flavonoids (1) 25 . Table 1 presents a summary of the studies in which the triangulation was used to analyze the correlation between methods of intake, biomarkers and the unknown "true" intake.…”

Section: Food Consumption Validation Studies Using the Triads Methodsmentioning

confidence: 99%

“…Nutrients most studied were carotenoids and tocopherols. The majority of the studies aimed to validate a food intake questionnaire but some intended to test the biomarkers as indicators of food intakes 19,23,25,26 .…”

Section: Food Consumption Validation Studies Using the Triads Methodsmentioning

confidence: 99%

“…The comparison between studies must incorporate these important differences among them. For the intake reference method, studies used multiple 24hR 6,9,18,20,26,27 , weighed food records 10,11,15,19,21,23 or several days food registry 22 as the reference method. Taking the example of carotenoids and tocopherols, shown in Table 1, validity coefficients of the reference method and the questionnaire performed well, ranging from ρ RI of 0.39 to 0.97 and ρ QI from 0.38 to 0.80, respectively.…”

Section: Food Consumption Validation Studies Using the Triads Methodsmentioning

confidence: 99%

“…For carotenoids, tocopherol, folic acid and vitamin B 12 studies, serum and erythrocyte were analyzed. For fatty acid biomarkers analyses, plasma phospholipids 11 , erythrocyte membrane 24 and adipose tissue 6,23 were used. In Kabagambe et al's 6 study, plasma performed better than adipose tissue both for carotenoids and tocopherols.…”

Section: Food Consumption Validation Studies Using the Triads Methodsmentioning

confidence: 99%

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Applying the triads method in the validation of dietary intake using biomarkers

2010

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The triads method is applied in validation studies of dietary intake to evaluate the correlation between three measurements (food frequency questionnaire, reference method and biomarker) and the true intake using validity coefficients (ρ) IntroductionThe food frequency questionnaire (FFQ) is the most widely used instrument for the assessment of habitual food intake of a population. A properly validated FFQ for the intended population allows for stratification according to nutritional intake at the reference time considered 1 . Biomarkers offer the possibility of further validation aiming to improve the accuracy of the instrument 2 .In the process of validating a FFQ, multiple dietary records or 24-hour recalls (24hR) are often used as the method of reference 3 . The application of a reference method is important in order to estimate the errors associated with the FFQ, particularly the attenuation bias caused by random measurement errors of the instrument which will impact in the statistical power of the study 1,3 . The limitations of using dietary measures as the reference method is that both the instrument being tested (FFQ) and the reference method (24hR) are subject to the same random and systematic errors, because they rely on the memory of the interviewee and due to errors related to the estimation of the reported food intake 4,5 .In this scenario, biological markers may offer advantages and be able to improve the estimates of dietary intake assessment, due to the independence of their random errors in relation to the errors inherent to the intake questionnaires 5 . However, the biomarkers do not replace the tradition-REVISÃO REVIEW Yokota RTC et al. 2028 Cad. Saúde Pública, Rio de Janeiro, 26(11

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Section: Food Consumption Validation Studies Using the Triads Methodsmentioning

confidence: 99%

Section: Food Consumption Validation Studies Using the Triads Methodsmentioning

confidence: 99%

Section: Food Consumption Validation Studies Using the Triads Methodsmentioning

confidence: 99%

Section: Food Consumption Validation Studies Using the Triads Methodsmentioning

confidence: 99%

Section: Food Consumption Validation Studies Using the Triads Methodsmentioning

confidence: 99%

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Applying the triads method in the validation of dietary intake using biomarkers

2010

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Dairy intake screener as web‐based application is reliable and valid

Piderit,

White,

Becker

et al. 2024

Food Science & Nutrition

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The “Dairy Diary” is a user‐friendly web‐based dairy intake screener. The reliability and validity are unknown. We aimed to evaluate the screener in terms of test–retest reliability and comparative validity. In a diagnostic accuracy study, a purposefully recruited sample of 79 (age: 21.6 ± 3.8 years) undergraduate dietetics/nutrition students from three South African universities completed 3 non‐consecutive days of weighed food records (reference standard) within a seven‐day period (comparative validity), followed by two administrations, 2 weeks apart, of the screener (index test) (reliability). For the four dairy product serving scores (PSSs) and the summative dairy serving scores (DSSs) of the screener and the food records, t‐tests, correlations, Bland–Altman, Kappa, McNemar's, and diagnostic accuracy were determined. For reliability, mean PSSs and DSSs did not differ significantly (p > .05) between the screener administrations. The mean PSSs were strongly correlated: milk (r = .69; p < .001), maas (fermented milk) (r = .72; p < .001), yoghurt (r = .71; p < .001), cheese (r = .74; p < .001). For DSSs, Kappa was moderate (k = 0.45; p < .001). Non‐agreeing responses suggest symmetry (p = .334). For validity, the PSSs of the screener and food records were moderately correlated [milk (r = .30; p = .0129), yoghurt (r = .38; p < .001), cheese (r = .38; p < .001)], with k = 0.31 (p = .006) for DSS. Bland–Altman analyses showed acceptable agreement for DSSs (bias: −0.49; 95% CI: −0.7 to −0.3). Categorized DSSs had high sensitivity (81.4%) and positive predictive value (93.4%), yet low specificity (55.6%) and negative predictive value (27.8%). The area under the receiver operating characteristic curve (0.7) was acceptable. The “Dairy Diary” is test–retest reliable with moderate comparative validity to screen for dairy intake of nutrition‐literate consumers.

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The Distribution of Fatty Acid Biomarkers of Dairy Intake across Serum Lipid Fractions: The Prospective Metabolism and Islet Cell Evaluation (PROMISE) Cohort

Santaren

Bazinet

Liu

et al. 2019

Lipids

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Circulating fatty acids (FA) derived largely from dairy consumption have most commonly been measured in total human serum or phospholipid (PL) fractions, and have been used as validated biomarkers of dairy intake in a growing number of epidemiological studies. Nevertheless, measurement and characterization of a wider spectrum of FA biomarkers of dairy across the four major serum lipid fractions is lacking. This study aimed to (1) quantify FA biomarkers of dairy in PL, triacylglycerol (TAG), cholesteryl ester (CE), and unesterified fatty acid (FFA) serum lipid fractions; and (2) identify potential demographic and metabolic factors that may modify the proportions of these FA across serum fractions. Baseline data from 444 adults in the PROMISE cohort were analyzed. FA biomarkers, 15:0, t16:1n‐7, 18:2‐c9,t11, and t18:1n‐7 were quantified from serum. Dairy intake was estimated using the validated Canadian Diet History Questionnaire. Our results show that t18:1n‐7 was the most abundant FA biomarker in all fractions except CE, where 18:2‐c9,t11 was the most abundant. Positive correlations within fractions, and across FA in the PL, CE, and FFA fractions were found, however, TAG FA were negatively correlated with the other fractions. PL and CE FA were positively associated with dairy intake, and negatively associated with markers of dysmetabolism while, in contrast, these markers were predictors of higher TAG dairy FA. This study is the first to demonstrate distinct proportions of dairy FA in different serum lipid fractions. PL and CE FA marked dairy intake in this cohort, while TAG FA appeared to be markers of dysmetabolism.

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Evaluation of the odd fatty acids 15:0 and 17:0 in serum and adipose tissue as markers of intake of milk and dairy fat

Cited by 141 publications

References 33 publications

Applying the triads method in the validation of dietary intake using biomarkers

Applying the triads method in the validation of dietary intake using biomarkers

Dairy intake screener as web‐based application is reliable and valid

The Distribution of Fatty Acid Biomarkers of Dairy Intake across Serum Lipid Fractions: The Prospective Metabolism and Islet Cell Evaluation (PROMISE) Cohort

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