Dataset Information

Repeat 24-hour recalls and locally developed food composition databases: a feasible method to estimate dietary adequacy in a multi-site preconception maternal nutrition RCT.

ABSTRACT: Background: Our aim was to utilize a feasible quantitative methodology to estimate the dietary adequacy of >900 first-trimester pregnant women in poor rural areas of the Democratic Republic of the Congo, Guatemala, India and Pakistan. This paper outlines the dietary methods used. Methods: Local nutritionists were trained at the sites by the lead study nutritionist and received ongoing mentoring throughout the study. Training topics focused on the standardized conduct of repeat multiple-pass 24-hr dietary recalls, including interview techniques, estimation of portion sizes, and construction of a unique site-specific food composition database (FCDB). Each FCDB was based on 13 food groups and included values for moisture, energy, 20 nutrients (i.e. macro- and micronutrients), and phytate (an anti-nutrient). Nutrient values for individual foods or beverages were taken from recently developed FAO-supported regional food composition tables or the USDA national nutrient database. Appropriate adjustments for differences in moisture and application of nutrient retention and yield factors after cooking were applied, as needed. Generic recipes for mixed dishes consumed by the study population were compiled at each site, followed by calculation of a median recipe per 100 g. Each recipe's nutrient values were included in the FCDB. Final site FCDB checks were planned according to FAO/INFOODS guidelines. Discussion: This dietary strategy provides the opportunity to assess estimated mean group usual energy and nutrient intakes and estimated prevalence of the population 'at risk' of inadequate intakes in first-trimester pregnant women living in four low- and middle-income countries. While challenges and limitations exist, this methodology demonstrates the practical application of a quantitative dietary strategy for a large international multi-site nutrition trial, providing within- and between-site comparisons. Moreover, it provides an excellent opportunity for local capacity building and each site FCDB can be easily modified for additional research activities conducted in other populations living in the same area.

SUBMITTER: Lander RL

PROVIDER: S-EPMC5404420 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Repeat 24-hour recalls and locally developed food composition databases: a feasible method to estimate dietary adequacy in a multi-site preconception maternal nutrition RCT.

Lander Rebecca L RL Hambidge K Michael KM Krebs Nancy F NF Westcott Jamie E JE Garces Ana A Figueroa Lester L Tejeda Gabriela G Lokangaka Adrien A Diba Tshilenge S TS Somannavar Manjunath S MS Honnayya Ranjitha R Ali Sumera A SA Khan Umber S US McClure Elizabeth M EM Thorsten Vanessa R VR Stolka Kristen B KB

Food & nutrition research 20170411 1

<b>Background</b>: Our aim was to utilize a feasible quantitative methodology to estimate the dietary adequacy of >900 first-trimester pregnant women in poor rural areas of the Democratic Republic of the Congo, Guatemala, India and Pakistan. This paper outlines the dietary methods used. <b>Methods</b>: Local nutritionists were trained at the sites by the lead study nutritionist and received ongoing mentoring throughout the study. Training topics focused on the standardized conduct of repeat mult ...[more]

PMID: 28469549

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Project description:BackgroundStatistical methods to model the usual dietary intake of foods in a population generally ignore the additional information on the never-consumers. The objective of this study is to determine the added value of Food Frequency Questionnaire (FFQ) data allowing distinguishing the never-consumers from the non-consumers while modeling the usual intake distribution.MethodsThree food items with a different proportion of never-consumers were selected from the database of the Belgian food consumption survey of 2004 (N = 3200). The usual intake distribution for these food items was modeled with the Statistical Program for Analysis of Dietary Exposure (SPADE) and modeling parameters were extracted. These parameters were used to simulate (a) a new database with two 24-h recalls per respondent and (b) a "true" usual intake distribution. The usual intake distribution from the new database was obtained by modeling the 24-h recalls with SPADE, once without and once with the inclusion of the FFQ data on the never-consumers. Ratios were calculated for the different percentiles of the usual intake distribution: the modeled usual intake (g/day) (for both SPADE with and without the inclusion of FFQ data on never-consumers) was divided by the corresponding percentile of the simulated "true" usual intake (g/day). The closer the ratio is to one, the better the model fits the data.ResultsInclusion of the FFQ information to identify the never-consumers did not improve the estimation of the higher percentiles of the usual intake distribution. However, taking into account this FFQ information improved the estimation of the lower percentiles of the usual intake distribution even when the proportion of never-consumers was low.ConclusionsThe inclusion of FFQ information to identify the never-consumers is beneficial when interested in the whole usual intake distribution or in the lower percentiles only, no matter how low the proportion of never-consumers for that food item may be. However, when interest is only in the higher percentiles of the usual intake distribution, inclusion of FFQ information to identify the never-consumers will have no benefit.

Project description:BackgroundThe Automated Self-Administered 24-hour (ASA24) dietary recall system enhances the feasibility of collecting high-quality intake data in population-based studies.ObjectiveThe aim of this study was to assess the accuracy of portion size reporting in the ASA24 compared with interviewer-administered recalls.MethodsTrue intake for 3 meals was ascertained in 81 adults aged 20-70 y from the Washington, DC area. Participants were randomly assigned to complete an unannounced ASA24 or an interviewer-administered Automated Multiple-Pass Method (AMPM) recall the following day. An adapted Bland-Altman approach was used to assess agreement between true and reported portion sizes. Linear regression was used to assess log-scale differences between true and reported portion sizes by recall mode. The proportions of reported portion sizes within 10% and 25% of truth were estimated. Analyses were conducted for all foods and drinks and predetermined categories.ResultsMean differences between true and reported portion sizes were 3.7 g for the ASA24 and 11.8 g for the AMPM. According to the Bland-Altman-type plots, between 92% and 100% (depending on food or drink category and recall mode) of observations fell within the limits of agreement. After adjustment for multiple testing, the mean ratio of reported to true portion sizes was significantly >1 for the categories of all foods and drinks, all foods excluding liquids, amorphous or soft foods, and small pieces among AMPM respondents. Misestimation in the AMPM was significantly different from that in the ASA24 for all foods and drinks and for all foods excluding liquids. Small proportions of reported portions fell within 10% (16.2% for the ASA24 and 14.9% for the AMPM) and 25% (37.5% for the ASA24 and 33.2% for the AMPM) of truth.ConclusionsThe results raise the possibility that digital images tailored to different types and formats of foods may facilitate improved estimation of amounts eaten but highlight the need for continued work in this aspect of dietary assessment. This trial was registered at clinicaltrials.gov as NCT00978406.

Dataset Information

Repeat 24-hour recalls and locally developed food composition databases: a feasible method to estimate dietary adequacy in a multi-site preconception maternal nutrition RCT.

Publications

Repeat 24-hour recalls and locally developed food composition databases: a feasible method to estimate dietary adequacy in a multi-site preconception maternal nutrition RCT.

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