The influence of recipe disaggregation in dietary assessment: results from the national food consumption survey in Saint Kitts and Nevis

It is not always the case that recipe disaggregation is performed in dietary surveys. This investigation aimed to assess the influence of recipe disaggregation in the 2020-2021 national dietary survey in Saint Kitts and Nevis, and provide recommendations for future assessments. A total of 1,004 individuals provided information on their food consumption obtained using 24-h dietary recalls, and 442 recipes were reported. Some recipes were reported as single ingredients at the data collection stage (<i>n</i> = 65). In most cases, the respondent provided a standard recipe without disaggregation (<i>n</i> = 377). A simple and pragmatic recipe disaggregation methodology was developed. The procedure of recipe disaggregation comprised nine steps, including identifying recipes, ingredients, quantities, conversion factors, and the presence of visible fluid, among others. Seventy-eight non-disaggregated standard recipes were post-disaggregated (21% of recipes) to identify ingredient weights. Either the chi-square or Fisher's exact tests were applied to assess the significance of differences in frequency of food group consumption before and after disaggregation. The proportion of consumers across the different food groups increased dramatically for some food groups after recipe disaggregation, with significant differences (all <i>p</i> < 0.01) for cereals and their products (81.3% before and 94.7% after), eggs and their products (21.7% before and 34.6% after), fats and oils (6.9% before and 44.5% after), fish, shellfish and their products (26.7% before and 38.5% after), meat and meat products (59.7% before and 71.4% after), milk and milk products (30.4% before and 46.1% after), pulses, seeds, nuts and their products (18.6% before and 49.2% after), spices and condiments (34.0% before and 68.5% after, and vegetables and their products (49.9% before and 76.6% after). Consequently, most of the reported intakes in grams were also influenced across all food groups. Recipes are an important source of food consumption, and their disaggregation should be carefully considered in dietary assessment.

Authors

Institutions

Publication Details

Journal
Frontiers in Nutrition
Published
2024-09-05
DOI
https://doi.org/10.3389/fnut.2024.1404932
Citations
1
Primary Topic
Nutritional Studies and Diet
Type
article
Field-Weighted Citation Impact
0.54
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The influence of recipe disaggregation in dietary assessment: results from the national food consumption survey in Saint Kitts and Nevis

Vanessa Cardozo Mendes Elias, Victoria Padula de Quadros, Cláudia Choma Bettega Almeida, Rita Ferreira de Sousa et al.
1 citations
Frontiers in Nutrition
Nutritional Studies and Diet
0.54
article

The influence of recipe disaggregation in dietary assessment: results from the national food consumption survey in Saint Kitts and Nevis

Vanessa Cardozo Mendes Elias, Victoria Padula de Quadros, Cláudia Choma Bettega Almeida, Rita Ferreira de Sousa, Sandra Patrícia Crispim, Sharon D. Hutchinson, Agnieszka Balcerzak, Latoya Matthew-Duncan, Isabella Francis-Grandeson, Fransen Jean, Ariel de Moraes Frauches, U. Ruth Charrondière, Bridget Holmes
article en
1 citations

Abstract

It is not always the case that recipe disaggregation is performed in dietary surveys. This investigation aimed to assess the influence of recipe disaggregation in the 2020-2021 national dietary survey in Saint Kitts and Nevis, and provide recommendations for future assessments. A total of 1,004 individuals provided information on their food consumption obtained using 24-h dietary recalls, and 442 recipes were reported. Some recipes were reported as single ingredients at the data collection stage (<i>n</i> = 65). In most cases, the respondent provided a standard recipe without disaggregation (<i>n</i> = 377). A simple and pragmatic recipe disaggregation methodology was developed. The procedure of recipe disaggregation comprised nine steps, including identifying recipes, ingredients, quantities, conversion factors, and the presence of visible fluid, among others. Seventy-eight non-disaggregated standard recipes were post-disaggregated (21% of recipes) to identify ingredient weights. Either the chi-square or Fisher's exact tests were applied to assess the significance of differences in frequency of food group consumption before and after disaggregation. The proportion of consumers across the different food groups increased dramatically for some food groups after recipe disaggregation, with significant differences (all <i>p</i> < 0.01) for cereals and their products (81.3% before and 94.7% after), eggs and their products (21.7% before and 34.6% after), fats and oils (6.9% before and 44.5% after), fish, shellfish and their products (26.7% before and 38.5% after), meat and meat products (59.7% before and 71.4% after), milk and milk products (30.4% before and 46.1% after), pulses, seeds, nuts and their products (18.6% before and 49.2% after), spices and condiments (34.0% before and 68.5% after, and vegetables and their products (49.9% before and 76.6% after). Consequently, most of the reported intakes in grams were also influenced across all food groups. Recipes are an important source of food consumption, and their disaggregation should be carefully considered in dietary assessment.

Frontiers in NutritionVol. 11
Food and Agriculture Organization of the United Nations (IT), University of the West Indies (TT), Universidade Federal do Paraná (BR)
Openalex Percentile: Top 29%
Nutritional Studies and Diet
0.54
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.