Calibration of citrus intake assessed by food frequency questionnaires using urinary proline betaine in an observational study setting
Whether observational study can be employed to establish calibration equations for self-reported dietary intake using food biomarkers is unknown. This study aims to demonstrate the feasibility of obtaining calibration equations based on food biomarkers and 7-d diet records (7DDRs) to correct measure...
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Veröffentlicht in: | The American journal of clinical nutrition 2024-07, Vol.120 (1), p.178-186 |
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creator | Hu, Yang Wang, Molin Willett, Walter C Stampfer, Meir Liang, Liming Hu, Frank B Rimm, Eric Brennan, Lorraine Sun, Qi |
description | Whether observational study can be employed to establish calibration equations for self-reported dietary intake using food biomarkers is unknown.
This study aims to demonstrate the feasibility of obtaining calibration equations based on food biomarkers and 7-d diet records (7DDRs) to correct measurement errors of food frequency questionnaires (FFQs) in an observational study setting.
The study population consisted of 669 males and 749 females from the Women’s and Men’s Lifestyle Validation Studies. In the training set, the biomarker-predicted intake derived by regressing 7DDR-assessed intake on urinary proline betaine concentration was regressed on the FFQ-assessed intake to obtain the calibration equations. The regression coefficients were applied to the test set to calculate the calibrated FFQ intake. We examined total citrus as well as individual citrus fruits/beverages.
Urinary proline betaine was moderately correlated with orange juice intake (Pearson correlation [r] = 0.53 for 7DDR and 0.48 for FFQ) but only weakly correlated with intakes of orange (r = 0.12 for 7DDR and 0.15 for FFQ) and grapefruit (r = 0.14 for 7DDR and 0.09 for FFQ). The FFQ-assessed citrus intake was systematically higher than the 7DDR-assessed intake, and after calibrations, the mean calibrated FFQ measurements were almost identical to 7DDR assessments. In the test set, the mean intake levels from 7DDRs, FFQs, and calibrated FFQs were 62.5, 75.3, and 63.2 g/d for total citrus; 41.6, 42.5, and 41.9 g/d for orange juice; 11.8, 24.3, and 12.3 g/d for oranges; and 8.3, 9.3, and 8.6 g/d for grapefruit, respectively. We observed larger differences between calibrated FFQ and 7DDR assessments at the extreme ends of intake, although, on average, good agreements were observed for all citrus except grapefruit.
Our 2-step calibration approach has the potential to be adapted to correct systematic measurement error for other foods/nutrients with established food biomarkers in a cost effective way. |
doi_str_mv | 10.1016/j.ajcnut.2024.05.011 |
format | Article |
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This study aims to demonstrate the feasibility of obtaining calibration equations based on food biomarkers and 7-d diet records (7DDRs) to correct measurement errors of food frequency questionnaires (FFQs) in an observational study setting.
The study population consisted of 669 males and 749 females from the Women’s and Men’s Lifestyle Validation Studies. In the training set, the biomarker-predicted intake derived by regressing 7DDR-assessed intake on urinary proline betaine concentration was regressed on the FFQ-assessed intake to obtain the calibration equations. The regression coefficients were applied to the test set to calculate the calibrated FFQ intake. We examined total citrus as well as individual citrus fruits/beverages.
Urinary proline betaine was moderately correlated with orange juice intake (Pearson correlation [r] = 0.53 for 7DDR and 0.48 for FFQ) but only weakly correlated with intakes of orange (r = 0.12 for 7DDR and 0.15 for FFQ) and grapefruit (r = 0.14 for 7DDR and 0.09 for FFQ). The FFQ-assessed citrus intake was systematically higher than the 7DDR-assessed intake, and after calibrations, the mean calibrated FFQ measurements were almost identical to 7DDR assessments. In the test set, the mean intake levels from 7DDRs, FFQs, and calibrated FFQs were 62.5, 75.3, and 63.2 g/d for total citrus; 41.6, 42.5, and 41.9 g/d for orange juice; 11.8, 24.3, and 12.3 g/d for oranges; and 8.3, 9.3, and 8.6 g/d for grapefruit, respectively. We observed larger differences between calibrated FFQ and 7DDR assessments at the extreme ends of intake, although, on average, good agreements were observed for all citrus except grapefruit.
Our 2-step calibration approach has the potential to be adapted to correct systematic measurement error for other foods/nutrients with established food biomarkers in a cost effective way.</description><identifier>ISSN: 0002-9165</identifier><identifier>ISSN: 1938-3207</identifier><identifier>EISSN: 1938-3207</identifier><identifier>DOI: 10.1016/j.ajcnut.2024.05.011</identifier><identifier>PMID: 38762186</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Assessments ; Betaine ; Beverages ; Biomarkers ; Calibration ; calibration analysis ; Citrus ; Citrus fruits ; clinical nutrition ; Correlation ; cost effectiveness ; Diet ; diet records ; Dietary intake ; Error analysis ; Error correction ; Feasibility studies ; Food ; Food intake ; Fruit juices ; Fruits ; Grapefruit ; grapefruits ; lifestyle ; measurement error ; NMR-spectroscopy ; Nutrients ; Observational studies ; orange juice ; Oranges ; Population studies ; Proline ; Questionnaires ; Regression coefficients ; Test sets ; urinary food biomarker</subject><ispartof>The American journal of clinical nutrition, 2024-07, Vol.120 (1), p.178-186</ispartof><rights>2024 American Society for Nutrition</rights><rights>Copyright © 2024 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.</rights><rights>Copyright American Society for Clinical Nutrition, Inc. Jul 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c302t-9f476b5fff1a70dab4c20463de18a2fdf26a157a219a2b05da473adb49b5296e3</cites><orcidid>0000-0002-0200-5951 ; 0000-0002-8480-1563</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38762186$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hu, Yang</creatorcontrib><creatorcontrib>Wang, Molin</creatorcontrib><creatorcontrib>Willett, Walter C</creatorcontrib><creatorcontrib>Stampfer, Meir</creatorcontrib><creatorcontrib>Liang, Liming</creatorcontrib><creatorcontrib>Hu, Frank B</creatorcontrib><creatorcontrib>Rimm, Eric</creatorcontrib><creatorcontrib>Brennan, Lorraine</creatorcontrib><creatorcontrib>Sun, Qi</creatorcontrib><title>Calibration of citrus intake assessed by food frequency questionnaires using urinary proline betaine in an observational study setting</title><title>The American journal of clinical nutrition</title><addtitle>Am J Clin Nutr</addtitle><description>Whether observational study can be employed to establish calibration equations for self-reported dietary intake using food biomarkers is unknown.
This study aims to demonstrate the feasibility of obtaining calibration equations based on food biomarkers and 7-d diet records (7DDRs) to correct measurement errors of food frequency questionnaires (FFQs) in an observational study setting.
The study population consisted of 669 males and 749 females from the Women’s and Men’s Lifestyle Validation Studies. In the training set, the biomarker-predicted intake derived by regressing 7DDR-assessed intake on urinary proline betaine concentration was regressed on the FFQ-assessed intake to obtain the calibration equations. The regression coefficients were applied to the test set to calculate the calibrated FFQ intake. We examined total citrus as well as individual citrus fruits/beverages.
Urinary proline betaine was moderately correlated with orange juice intake (Pearson correlation [r] = 0.53 for 7DDR and 0.48 for FFQ) but only weakly correlated with intakes of orange (r = 0.12 for 7DDR and 0.15 for FFQ) and grapefruit (r = 0.14 for 7DDR and 0.09 for FFQ). The FFQ-assessed citrus intake was systematically higher than the 7DDR-assessed intake, and after calibrations, the mean calibrated FFQ measurements were almost identical to 7DDR assessments. In the test set, the mean intake levels from 7DDRs, FFQs, and calibrated FFQs were 62.5, 75.3, and 63.2 g/d for total citrus; 41.6, 42.5, and 41.9 g/d for orange juice; 11.8, 24.3, and 12.3 g/d for oranges; and 8.3, 9.3, and 8.6 g/d for grapefruit, respectively. We observed larger differences between calibrated FFQ and 7DDR assessments at the extreme ends of intake, although, on average, good agreements were observed for all citrus except grapefruit.
Our 2-step calibration approach has the potential to be adapted to correct systematic measurement error for other foods/nutrients with established food biomarkers in a cost effective way.</description><subject>Assessments</subject><subject>Betaine</subject><subject>Beverages</subject><subject>Biomarkers</subject><subject>Calibration</subject><subject>calibration analysis</subject><subject>Citrus</subject><subject>Citrus fruits</subject><subject>clinical nutrition</subject><subject>Correlation</subject><subject>cost effectiveness</subject><subject>Diet</subject><subject>diet records</subject><subject>Dietary intake</subject><subject>Error analysis</subject><subject>Error correction</subject><subject>Feasibility studies</subject><subject>Food</subject><subject>Food intake</subject><subject>Fruit juices</subject><subject>Fruits</subject><subject>Grapefruit</subject><subject>grapefruits</subject><subject>lifestyle</subject><subject>measurement error</subject><subject>NMR-spectroscopy</subject><subject>Nutrients</subject><subject>Observational studies</subject><subject>orange juice</subject><subject>Oranges</subject><subject>Population studies</subject><subject>Proline</subject><subject>Questionnaires</subject><subject>Regression coefficients</subject><subject>Test sets</subject><subject>urinary food biomarker</subject><issn>0002-9165</issn><issn>1938-3207</issn><issn>1938-3207</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNqFkc9qFTEUh4Mo9lp9A5GAm25mzP-Z2QhysVYouGnX4WSSSMa5mZpkCvcFfG4zvdWFiwqBs_l-5-ScD6G3lLSUUPVhamEa41paRphoiWwJpc_Qjg68bzgj3XO0I4SwZqBKnqFXOU-EUCZ69RKd8b5TjPZqh37tYQ4mQQlLxIvHYyhpzTjEAj8chpxdfRabI_bLYrFP7ufq4njEteQtFCEkl_GaQ_yO1xQipCO-S8scosPGFdhqiBhqe5Ndun8YBTPOZbVHnF0pNfkavfAwZ_fmsZ6j28vPN_ur5vrbl6_7T9fNyAkrzeBFp4z03lPoiAUjRkaE4tbRHpi3nimgsgNGB2CGSAui42CNGIxkg3L8HF2c-tYfPmygDyGPbp4humXNmlPJFROcs_-jRCqlBO039P0_6LSsqS65UT3r-aCkqJQ4UWNack7O67sUDvVcmhK9KdWTPinVm1JNpK5Ka-zdY_PVHJz9G_rjsAIfT4Crh7sPLuk8hurI2WpmLNou4ekJvwEaVbbR</recordid><startdate>20240701</startdate><enddate>20240701</enddate><creator>Hu, Yang</creator><creator>Wang, Molin</creator><creator>Willett, Walter C</creator><creator>Stampfer, Meir</creator><creator>Liang, Liming</creator><creator>Hu, Frank B</creator><creator>Rimm, Eric</creator><creator>Brennan, Lorraine</creator><creator>Sun, Qi</creator><general>Elsevier Inc</general><general>American Society for Clinical Nutrition, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QP</scope><scope>7T7</scope><scope>7TS</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>P64</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0002-0200-5951</orcidid><orcidid>https://orcid.org/0000-0002-8480-1563</orcidid></search><sort><creationdate>20240701</creationdate><title>Calibration of citrus intake assessed by food frequency questionnaires using urinary proline betaine in an observational study setting</title><author>Hu, Yang ; Wang, Molin ; Willett, Walter C ; Stampfer, Meir ; Liang, Liming ; Hu, Frank B ; Rimm, Eric ; Brennan, Lorraine ; Sun, Qi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c302t-9f476b5fff1a70dab4c20463de18a2fdf26a157a219a2b05da473adb49b5296e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Assessments</topic><topic>Betaine</topic><topic>Beverages</topic><topic>Biomarkers</topic><topic>Calibration</topic><topic>calibration analysis</topic><topic>Citrus</topic><topic>Citrus fruits</topic><topic>clinical nutrition</topic><topic>Correlation</topic><topic>cost effectiveness</topic><topic>Diet</topic><topic>diet records</topic><topic>Dietary intake</topic><topic>Error analysis</topic><topic>Error correction</topic><topic>Feasibility studies</topic><topic>Food</topic><topic>Food intake</topic><topic>Fruit juices</topic><topic>Fruits</topic><topic>Grapefruit</topic><topic>grapefruits</topic><topic>lifestyle</topic><topic>measurement error</topic><topic>NMR-spectroscopy</topic><topic>Nutrients</topic><topic>Observational studies</topic><topic>orange juice</topic><topic>Oranges</topic><topic>Population studies</topic><topic>Proline</topic><topic>Questionnaires</topic><topic>Regression coefficients</topic><topic>Test sets</topic><topic>urinary food biomarker</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hu, Yang</creatorcontrib><creatorcontrib>Wang, Molin</creatorcontrib><creatorcontrib>Willett, Walter C</creatorcontrib><creatorcontrib>Stampfer, Meir</creatorcontrib><creatorcontrib>Liang, Liming</creatorcontrib><creatorcontrib>Hu, Frank B</creatorcontrib><creatorcontrib>Rimm, Eric</creatorcontrib><creatorcontrib>Brennan, Lorraine</creatorcontrib><creatorcontrib>Sun, Qi</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Physical Education Index</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>The American journal of clinical nutrition</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hu, Yang</au><au>Wang, Molin</au><au>Willett, Walter C</au><au>Stampfer, Meir</au><au>Liang, Liming</au><au>Hu, Frank B</au><au>Rimm, Eric</au><au>Brennan, Lorraine</au><au>Sun, Qi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Calibration of citrus intake assessed by food frequency questionnaires using urinary proline betaine in an observational study setting</atitle><jtitle>The American journal of clinical nutrition</jtitle><addtitle>Am J Clin Nutr</addtitle><date>2024-07-01</date><risdate>2024</risdate><volume>120</volume><issue>1</issue><spage>178</spage><epage>186</epage><pages>178-186</pages><issn>0002-9165</issn><issn>1938-3207</issn><eissn>1938-3207</eissn><abstract>Whether observational study can be employed to establish calibration equations for self-reported dietary intake using food biomarkers is unknown.
This study aims to demonstrate the feasibility of obtaining calibration equations based on food biomarkers and 7-d diet records (7DDRs) to correct measurement errors of food frequency questionnaires (FFQs) in an observational study setting.
The study population consisted of 669 males and 749 females from the Women’s and Men’s Lifestyle Validation Studies. In the training set, the biomarker-predicted intake derived by regressing 7DDR-assessed intake on urinary proline betaine concentration was regressed on the FFQ-assessed intake to obtain the calibration equations. The regression coefficients were applied to the test set to calculate the calibrated FFQ intake. We examined total citrus as well as individual citrus fruits/beverages.
Urinary proline betaine was moderately correlated with orange juice intake (Pearson correlation [r] = 0.53 for 7DDR and 0.48 for FFQ) but only weakly correlated with intakes of orange (r = 0.12 for 7DDR and 0.15 for FFQ) and grapefruit (r = 0.14 for 7DDR and 0.09 for FFQ). The FFQ-assessed citrus intake was systematically higher than the 7DDR-assessed intake, and after calibrations, the mean calibrated FFQ measurements were almost identical to 7DDR assessments. In the test set, the mean intake levels from 7DDRs, FFQs, and calibrated FFQs were 62.5, 75.3, and 63.2 g/d for total citrus; 41.6, 42.5, and 41.9 g/d for orange juice; 11.8, 24.3, and 12.3 g/d for oranges; and 8.3, 9.3, and 8.6 g/d for grapefruit, respectively. We observed larger differences between calibrated FFQ and 7DDR assessments at the extreme ends of intake, although, on average, good agreements were observed for all citrus except grapefruit.
Our 2-step calibration approach has the potential to be adapted to correct systematic measurement error for other foods/nutrients with established food biomarkers in a cost effective way.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>38762186</pmid><doi>10.1016/j.ajcnut.2024.05.011</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-0200-5951</orcidid><orcidid>https://orcid.org/0000-0002-8480-1563</orcidid></addata></record> |
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subjects | Assessments Betaine Beverages Biomarkers Calibration calibration analysis Citrus Citrus fruits clinical nutrition Correlation cost effectiveness Diet diet records Dietary intake Error analysis Error correction Feasibility studies Food Food intake Fruit juices Fruits Grapefruit grapefruits lifestyle measurement error NMR-spectroscopy Nutrients Observational studies orange juice Oranges Population studies Proline Questionnaires Regression coefficients Test sets urinary food biomarker |
title | Calibration of citrus intake assessed by food frequency questionnaires using urinary proline betaine in an observational study setting |
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