| Autor: |
Sara Santarossa, Ashley Redding, Mackenzie Connell, Karissa Kao, Laura Susick, Jean M. Kerver |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
BMC Research Notes, Vol 17, Iss 1, Pp 1-8 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1756-0500 |
| DOI: |
10.1186/s13104-024-06697-9 |
| Popis: |
Abstract Objective We aimed to describe preliminary dietary intake results using DietID™ for dietary assessment during pregnancy. A sub-sample of participants in the Research Enterprise to Advance Children’s Health (REACH) prospective birth cohort from Detroit, MI received a unique web link to complete the DietID™ assessment multiple times during pregnancy. We present results for the first dietary assessment completed during pregnancy by each participant. DietID™ uses an image-based algorithm to estimate nutrient intake, dietary patterns, and diet quality and provides immediate results to participants. Descriptive statistics were used to summarize participant characteristics, nutrient intakes, dietary patterns, diet quality, and participant-rated accuracy of individual dietary assessment results. Differences in diet parameters were assessed by participant race with an independent t-test. Results Participants (n = 84) identified as majority Black (n = 47; 56%), reflective of the source population. Mean (SD) maternal age and gestational age at dietary assessment were 32 (5.6) years and 14.3 (4.8) weeks, respectively. Mean dietary quality, as reported in the DietID™ data output as the Healthy Eating Index (HEI), was 68 (range 12–98; higher scores indicate higher diet quality) and varied significantly between Black (mean [SD] 61 [23]) and White (mean [SD] 81 [19]) race (p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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