Cargando…

A Brief Tool to Assess Image-Based Dietary Records and Guide Nutrition Counselling Among Pregnant Women: An Evaluation

BACKGROUND: Dietitians ideally should provide personally tailored nutrition advice to pregnant women. Provision is hampered by a lack of appropriate tools for nutrition assessment and counselling in practice settings. Smartphone technology, through the use of image-based dietary records, can address...

Descripción completa

Detalles Bibliográficos
Autores principales: Ashman, Amy M, Collins, Clare E, Brown, Leanne J, Rae, Kym M, Rollo, Megan E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116101/
https://www.ncbi.nlm.nih.gov/pubmed/27815234
http://dx.doi.org/10.2196/mhealth.6469
_version_ 1782468613187305472
author Ashman, Amy M
Collins, Clare E
Brown, Leanne J
Rae, Kym M
Rollo, Megan E
author_facet Ashman, Amy M
Collins, Clare E
Brown, Leanne J
Rae, Kym M
Rollo, Megan E
author_sort Ashman, Amy M
collection PubMed
description BACKGROUND: Dietitians ideally should provide personally tailored nutrition advice to pregnant women. Provision is hampered by a lack of appropriate tools for nutrition assessment and counselling in practice settings. Smartphone technology, through the use of image-based dietary records, can address limitations of traditional methods of recording dietary intake. Feedback on these records can then be provided by the dietitian via smartphone. Efficacy and validity of these methods requires examination. OBJECTIVE: The aims of the Australian Diet Bytes and Baby Bumps study, which used image-based dietary records and a purpose-built brief Selected Nutrient and Diet Quality (SNaQ) tool to provide tailored nutrition advice to pregnant women, were to assess relative validity of the SNaQ tool for analyzing dietary intake compared with nutrient analysis software, to describe the nutritional intake adequacy of pregnant participants, and to assess acceptability of dietary feedback via smartphone. METHODS: Eligible women used a smartphone app to record everything they consumed over 3 nonconsecutive days. Records consisted of an image of the food or drink item placed next to a fiducial marker, with a voice or text description, or both, providing additional detail. We used the SNaQ tool to analyze participants’ intake of daily food group servings and selected key micronutrients for pregnancy relative to Australian guideline recommendations. A visual reference guide consisting of images of foods and drinks in standard serving sizes assisted the dietitian with quantification. Feedback on participants’ diets was provided via 2 methods: (1) a short video summary sent to participants’ smartphones, and (2) a follow-up telephone consultation with a dietitian. Agreement between dietary intake assessment using the SNaQ tool and nutrient analysis software was evaluated using Spearman rank correlation and Cohen kappa. RESULTS: We enrolled 27 women (median age 28.8 years, 8 Indigenous Australians, 15 primiparas), of whom 25 completed the image-based dietary record. Median intakes of grains, vegetables, fruit, meat, and dairy were below recommendations. Median (interquartile range) intake of energy-dense, nutrient-poor foods was 3.5 (2.4-3.9) servings/day and exceeded recommendations (0-2.5 servings/day). Positive correlations between the SNaQ tool and nutrient analysis software were observed for energy (ρ=.898, P<.001) and all selected micronutrients (iron, calcium, zinc, folate, and iodine, ρ range .510-.955, all P<.05), both with and without vitamin and mineral supplements included in the analysis. Cohen kappa showed moderate to substantial agreement for selected micronutrients when supplements were included (kappa range .488-.803, all P ≤.001) and for calcium, iodine, and zinc when excluded (kappa range .554-.632, all P<.001). A total of 17 women reported changing their diet as a result of the personalized nutrition advice. CONCLUSIONS: The SNaQ tool demonstrated acceptable validity for assessing adequacy of key pregnancy nutrient intakes and preliminary evidence of utility to support dietitians in providing women with personalized advice to optimize nutrition during pregnancy.
format Online
Article
Text
id pubmed-5116101
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-51161012016-11-23 A Brief Tool to Assess Image-Based Dietary Records and Guide Nutrition Counselling Among Pregnant Women: An Evaluation Ashman, Amy M Collins, Clare E Brown, Leanne J Rae, Kym M Rollo, Megan E JMIR Mhealth Uhealth Original Paper BACKGROUND: Dietitians ideally should provide personally tailored nutrition advice to pregnant women. Provision is hampered by a lack of appropriate tools for nutrition assessment and counselling in practice settings. Smartphone technology, through the use of image-based dietary records, can address limitations of traditional methods of recording dietary intake. Feedback on these records can then be provided by the dietitian via smartphone. Efficacy and validity of these methods requires examination. OBJECTIVE: The aims of the Australian Diet Bytes and Baby Bumps study, which used image-based dietary records and a purpose-built brief Selected Nutrient and Diet Quality (SNaQ) tool to provide tailored nutrition advice to pregnant women, were to assess relative validity of the SNaQ tool for analyzing dietary intake compared with nutrient analysis software, to describe the nutritional intake adequacy of pregnant participants, and to assess acceptability of dietary feedback via smartphone. METHODS: Eligible women used a smartphone app to record everything they consumed over 3 nonconsecutive days. Records consisted of an image of the food or drink item placed next to a fiducial marker, with a voice or text description, or both, providing additional detail. We used the SNaQ tool to analyze participants’ intake of daily food group servings and selected key micronutrients for pregnancy relative to Australian guideline recommendations. A visual reference guide consisting of images of foods and drinks in standard serving sizes assisted the dietitian with quantification. Feedback on participants’ diets was provided via 2 methods: (1) a short video summary sent to participants’ smartphones, and (2) a follow-up telephone consultation with a dietitian. Agreement between dietary intake assessment using the SNaQ tool and nutrient analysis software was evaluated using Spearman rank correlation and Cohen kappa. RESULTS: We enrolled 27 women (median age 28.8 years, 8 Indigenous Australians, 15 primiparas), of whom 25 completed the image-based dietary record. Median intakes of grains, vegetables, fruit, meat, and dairy were below recommendations. Median (interquartile range) intake of energy-dense, nutrient-poor foods was 3.5 (2.4-3.9) servings/day and exceeded recommendations (0-2.5 servings/day). Positive correlations between the SNaQ tool and nutrient analysis software were observed for energy (ρ=.898, P<.001) and all selected micronutrients (iron, calcium, zinc, folate, and iodine, ρ range .510-.955, all P<.05), both with and without vitamin and mineral supplements included in the analysis. Cohen kappa showed moderate to substantial agreement for selected micronutrients when supplements were included (kappa range .488-.803, all P ≤.001) and for calcium, iodine, and zinc when excluded (kappa range .554-.632, all P<.001). A total of 17 women reported changing their diet as a result of the personalized nutrition advice. CONCLUSIONS: The SNaQ tool demonstrated acceptable validity for assessing adequacy of key pregnancy nutrient intakes and preliminary evidence of utility to support dietitians in providing women with personalized advice to optimize nutrition during pregnancy. JMIR Publications 2016-11-04 /pmc/articles/PMC5116101/ /pubmed/27815234 http://dx.doi.org/10.2196/mhealth.6469 Text en ©Amy M Ashman, Clare E Collins, Leanne J Brown, Kym M Rae, Megan E Rollo. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 04.11.2016. https://creativecommons.org/licenses/by/2.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/ (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Ashman, Amy M
Collins, Clare E
Brown, Leanne J
Rae, Kym M
Rollo, Megan E
A Brief Tool to Assess Image-Based Dietary Records and Guide Nutrition Counselling Among Pregnant Women: An Evaluation
title A Brief Tool to Assess Image-Based Dietary Records and Guide Nutrition Counselling Among Pregnant Women: An Evaluation
title_full A Brief Tool to Assess Image-Based Dietary Records and Guide Nutrition Counselling Among Pregnant Women: An Evaluation
title_fullStr A Brief Tool to Assess Image-Based Dietary Records and Guide Nutrition Counselling Among Pregnant Women: An Evaluation
title_full_unstemmed A Brief Tool to Assess Image-Based Dietary Records and Guide Nutrition Counselling Among Pregnant Women: An Evaluation
title_short A Brief Tool to Assess Image-Based Dietary Records and Guide Nutrition Counselling Among Pregnant Women: An Evaluation
title_sort brief tool to assess image-based dietary records and guide nutrition counselling among pregnant women: an evaluation
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116101/
https://www.ncbi.nlm.nih.gov/pubmed/27815234
http://dx.doi.org/10.2196/mhealth.6469
work_keys_str_mv AT ashmanamym abrieftooltoassessimagebaseddietaryrecordsandguidenutritioncounsellingamongpregnantwomenanevaluation
AT collinsclaree abrieftooltoassessimagebaseddietaryrecordsandguidenutritioncounsellingamongpregnantwomenanevaluation
AT brownleannej abrieftooltoassessimagebaseddietaryrecordsandguidenutritioncounsellingamongpregnantwomenanevaluation
AT raekymm abrieftooltoassessimagebaseddietaryrecordsandguidenutritioncounsellingamongpregnantwomenanevaluation
AT rollomegane abrieftooltoassessimagebaseddietaryrecordsandguidenutritioncounsellingamongpregnantwomenanevaluation
AT ashmanamym brieftooltoassessimagebaseddietaryrecordsandguidenutritioncounsellingamongpregnantwomenanevaluation
AT collinsclaree brieftooltoassessimagebaseddietaryrecordsandguidenutritioncounsellingamongpregnantwomenanevaluation
AT brownleannej brieftooltoassessimagebaseddietaryrecordsandguidenutritioncounsellingamongpregnantwomenanevaluation
AT raekymm brieftooltoassessimagebaseddietaryrecordsandguidenutritioncounsellingamongpregnantwomenanevaluation
AT rollomegane brieftooltoassessimagebaseddietaryrecordsandguidenutritioncounsellingamongpregnantwomenanevaluation