Development and Evaluation of an Automated Algorithm to Estimate the Nutrient Intake of Infants from an Electronic Complementary Food Frequency Questionnaire

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dc.citation.issue4
dc.citation.volume9
dc.contributor.authorManerkar K
dc.contributor.authorHarding J
dc.contributor.authorConlon C
dc.contributor.authorMcKinlay C
dc.date.accessioned2024-06-17T21:48:05Z
dc.date.available2024-06-17T21:48:05Z
dc.date.issued2020-11-25
dc.description.abstractBackground: We previously validated a four-day complementary food frequency questionnaire (CFFQ) to estimate the nutrient intake in New Zealand infants aged 9-12 months. However, manual entry of the CFFQ data into nutritional analysis software was time-consuming. Therefore, we developed an automated algorithm and evaluated its accuracy by comparing the nutrient estimates with those obtained from the nutritional analysis software. Methods: We analysed 50 CFFQ completed at 9- and 12-months using Food Works nutritional analysis software. The automated algorithm was programmed in SAS by multiplying the average daily consumption of each food item by the nutrient content of the portion size. We considered the most common brands for commercially prepared baby foods. Intakes of energy, macronutrients, and micronutrients were compared between methods using Bland-Altman analysis. Results: The automated algorithm did not have any significant bias for estimates of energy (kJ) (MD 15, 95% CI -27, 58), carbohydrate (g) (MD -0.1, 95% CI -1.2,1.0), and fat (g) (-0.1, 95% CI -0.3,0.1), but slightly underestimated intake of protein (MD -0.4 g, 95% CI -0.7,-0.1), saturated fat, PUFA, dietary fibre, and niacin. The algorithm provided accurate estimates for other micronutrients. The limits of agreement were relatively narrow. Conclusion: This automated algorithm is an efficient tool to estimate the nutrient intakes from CFFQ accurately. The small negative bias observed for few nutrients was clinically insignificant and can be minimised. This algorithm is suitable to use in large clinical trials and cohort studies without the need for proprietary software.
dc.description.confidentialfalse
dc.format.pagination148-155
dc.identifier.citationManerkar K, Harding J, Conlon C, McKinlay C. (2020). Development and Evaluation of an Automated Algorithm to Estimate the Nutrient Intake of Infants from an Electronic Complementary Food Frequency Questionnaire. International Journal of Child Health and Nutrition. 9. 4. (pp. 148-155).
dc.identifier.doi10.6000/1929-4247.2020.09.04.1
dc.identifier.eissn1929-4247
dc.identifier.elements-typejournal-article
dc.identifier.urihttps://mro.massey.ac.nz/handle/10179/69877
dc.languageEnglish
dc.publisherLifescience Global
dc.publisher.urihttps://lifescienceglobal.com/pms/index.php/ijchn/article/view/6912
dc.relation.isPartOfInternational Journal of Child Health and Nutrition
dc.rights(c) 2020 The Author/s
dc.rightsCC BY-NC 3.0
dc.rights.urihttps://creativecommons.org/licenses/by-nc/3.0/
dc.titleDevelopment and Evaluation of an Automated Algorithm to Estimate the Nutrient Intake of Infants from an Electronic Complementary Food Frequency Questionnaire
dc.typeJournal article
pubs.elements-id479166
pubs.organisational-groupCollege of Health
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