Meeting the needs of US dietitians for food composition data

McCabe‐Sellers, Beverly; Chenard, Catherine A.

doi:10.1016/j.jfca.2007.07.002

Cited by 11 publications

(7 citation statements)

References 63 publications

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“…Furthermore, dietary record keeping is an important tool for patients/clients to self-monitor their progress with weight loss or their management of diet-related diseases such as diabetes. The availability of diet assessment methods with low respondent burden coupled with reliable food composition data in nutrient analysis programs is essential for monitoring nutrient intake of groups and individuals, to evaluate nutritional advice compliance and to conduct nutrition research [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Validity of Electronic Diet Recording Nutrient Estimates Compared to Dietitian Analysis of Diet Records: Randomized Controlled Trial

Raatz¹,

Scheett²,

Johnson³

et al. 2015

J Med Internet Res

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BackgroundDietary intake assessment with diet records (DR) is a standard research and practice tool in nutrition. Manual entry and analysis of DR is time-consuming and expensive. New electronic tools for diet entry by clients and research participants may reduce the cost and effort of nutrient intake estimation.ObjectiveTo determine the validity of electronic diet recording, we compared responses to 3-day DR kept by Tap & Track software for the Apple iPod Touch and records kept on the Nutrihand website to DR coded and analyzed by a research dietitian into a customized US Department of Agriculture (USDA) nutrient analysis program, entitled GRAND (Grand Forks Research Analysis of Nutrient Data).MethodsAdult participants (n=19) enrolled in a crossover-designed clinical trial. During each of two washout periods, participants kept a written 3-day DR. In addition, they were randomly assigned to enter their DR in a Web-based dietary analysis program (Nutrihand) or a handheld electronic device (Tap & Track). They completed an additional 3-day DR and the alternate electronic diet recording methods during the second washout. Entries resulted in 228 daily diet records or 12 for each of 19 participants. Means of nutrient intake were calculated for each method. Concordance of the intake estimates were determined by Bland-Altman plots. Coefficients of determination (R 2) were calculated for each comparison to assess the strength of the linear relationship between methods.ResultsNo significant differences were observed between the mean nutrient values for energy, carbohydrate, protein, fat, saturated fatty acids, total fiber, or sodium between the recorded DR analyzed in GRAND and either Nutrihand or Tap & Track, or for total sugars comparing GRAND and Tap & Track. Reported values for total sugars were significantly reduced (P<.05) comparing Nutrihand to GRAND. Coefficients of determination (R 2) for Nutrihand and Tap & Track compared to DR entries into GRAND, respectively, were energy .56, .01; carbohydrate .58, .08; total fiber .65, .37; sugar .78, .41; protein .44, .03; fat .36, .03; saturated fatty acids .23, .03; sodium .20, .00; and for Nutrihand only for cholesterol .88; vitamin A .02; vitamin C .37; calcium .05; and iron .77. Bland-Altman analysis demonstrates high variability in individual responses for both electronic capture programs with higher 95% limits of agreement for dietary intake recorded on Tap & Track.ConclusionsIn comparison to dietitian-entered 3-day DR, electronic methods resulted in no significant difference in mean nutrient estimates but exhibited larger variability, particularly the Tap & Track program. However, electronic DR provided mean estimates of energy, macronutrients, and some micronutrients, which approximated those of the dietitian-analyzed DR and may be appropriate for dietary monitoring of groups. Electronic diet assessment methods have the potential to reduce the cost and burden of DR analysis for nutrition research and clinical practice.Trial RegistrationClinicaltrials.gov NCT01183520; h...

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Section: Introductionmentioning

confidence: 99%

Validity of Electronic Diet Recording Nutrient Estimates Compared to Dietitian Analysis of Diet Records: Randomized Controlled Trial

Raatz¹,

Scheett²,

Johnson³

et al. 2015

J Med Internet Res

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

“…Additionally, the importance of user input can be seen in a study by McCabe-Sellers and Chenard [ 10 ] which investigated the requirements of a FCDB to meet the needs of US dietitians. McCabe-Sellers and Chenard [ 10 ] emphasises the importance of accessibility and availability of data, and suggests that this has been improved by technological advancements. Secondly, improved technology provides dietitians with the opportunity to convert food composition data into formats suitable for dietary planning, assessment and for nutrition information panel development [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

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Food Composition Database Format and Structure: A User Focused Approach

et al. 2015

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This study aimed to investigate the needs of Australian food composition database user’s regarding database format and relate this to the format of databases available globally. Three semi structured synchronous online focus groups (M = 3, F = 11) and n = 6 female key informant interviews were recorded. Beliefs surrounding the use, training, understanding, benefits and limitations of food composition data and databases were explored. Verbatim transcriptions underwent preliminary coding followed by thematic analysis with NVivo qualitative analysis software to extract the final themes. Schematic analysis was applied to the final themes related to database format. Desktop analysis also examined the format of six key globally available databases. 24 dominant themes were established, of which five related to format; database use, food classification, framework, accessibility and availability, and data derivation. Desktop analysis revealed that food classification systems varied considerably between databases. Microsoft Excel was a common file format used in all databases, and available software varied between countries. User’s also recognised that food composition databases format should ideally be designed specifically for the intended use, have a user-friendly food classification system, incorporate accurate data with clear explanation of data derivation and feature user input. However, such databases are limited by data availability and resources. Further exploration of data sharing options should be considered. Furthermore, user’s understanding of food composition data and databases limitations is inherent to the correct application of non-specific databases. Therefore, further exploration of user FCDB training should also be considered.

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“…Através das bases de dados é possível estabelecer uma relação entre alimentação, saúde e doença , realizar educação e orientação alimentar, bem como oferecer subsídios para fortificação de alimentos e o estabelecimento de necessidades nutricionais da população . Desse modo, as bases de dados devem ser precisas, de fácil acesso, confiáveis e constantemente atualizadas, tanto com a introdução de novos alimentos quanto de novos componentes (McCabe-Sellers and Chenard, 2008).…”

Section: Capítulounclassified

Alimentos processados: avaliação comparativa do perfil nutricional e sistematização do processo de categorização de alimentos prioritários para atualização de bases de dados

Prado¹

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Meeting the needs of US dietitians for food composition data

Cited by 11 publications

References 63 publications

Validity of Electronic Diet Recording Nutrient Estimates Compared to Dietitian Analysis of Diet Records: Randomized Controlled Trial

Validity of Electronic Diet Recording Nutrient Estimates Compared to Dietitian Analysis of Diet Records: Randomized Controlled Trial

Food Composition Database Format and Structure: A User Focused Approach

Alimentos processados: avaliação comparativa do perfil nutricional e sistematização do processo de categorização de alimentos prioritários para atualização de bases de dados

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