{"title":"估算婴儿类胡萝卜素摄入量的营养评估方法的相对有效性因评估工具、营养素数据库和牛奶类胡萝卜素调整方法而异","authors":"","doi":"10.1016/j.nutres.2024.06.003","DOIUrl":null,"url":null,"abstract":"<div><p>Validated carotenoid assessment methods are needed to study infant carotenoid nutrition. This is a secondary analysis of repeated diet assessments of healthy participants collected at 4- (n = 21), 6- (n = 12), and 8- (n = 9) months of age in Houston, TX between April 2019 and June 2020. Intake was assessed with 3 assessment tools, analyzed with 3 nutrient databases, and underwent 3 adjustments to account for milk composition variability. We hypothesized that manual adjustment of milk carotenoid intake based on laboratory measurements would improve the validity of all assessment approaches and that using a database with greater coverage of infant food carotenoid compositions would improve accuracy. Generalized linear mixed models assessed associations between tool, nutrient database, age, and milk carotenoid adjustment variables with carotenoid, energy, fruit, and vegetable intakes. The effect of the number of food diary days on intake estimate precision was evaluated by testing the correlation between intake estimates derived from 1, 3, or 5, vs. 7 days. Visit age influenced energy intake estimates (<em>p</em> = .029), along with assessment tool (<em>p</em> = .020). Estimates of vegetable intake were influenced by tool (<em>p</em> = .009). Combined fruit and vegetable intake differed by nutrient database (<em>p</em> = .007). Carotenoid intake differed by age (<em>p</em> =<.0001), tool (<em>p</em> = .002), and nutrient database (<em>p</em> = .004). A minimum of 3 food diary days strongly correlated (rho = 0.79-1) with reference estimates across ages. Milk carotenoid adjustment was most influential in estimating 4-month olds’ carotenoid intake, while nutrient database and tool were important for 6- and 8-month-olds’, highlighting the dynamic nature of infant diet assessment validity across feeding stages.</p></div>","PeriodicalId":19245,"journal":{"name":"Nutrition Research","volume":"128 ","pages":"Pages 38-49"},"PeriodicalIF":3.4000,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The relative validity of nutrition assessment methods for estimating infant carotenoid intake differs by assessment tool, nutrient database, and milk carotenoid adjustment method\",\"authors\":\"\",\"doi\":\"10.1016/j.nutres.2024.06.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Validated carotenoid assessment methods are needed to study infant carotenoid nutrition. This is a secondary analysis of repeated diet assessments of healthy participants collected at 4- (n = 21), 6- (n = 12), and 8- (n = 9) months of age in Houston, TX between April 2019 and June 2020. Intake was assessed with 3 assessment tools, analyzed with 3 nutrient databases, and underwent 3 adjustments to account for milk composition variability. We hypothesized that manual adjustment of milk carotenoid intake based on laboratory measurements would improve the validity of all assessment approaches and that using a database with greater coverage of infant food carotenoid compositions would improve accuracy. Generalized linear mixed models assessed associations between tool, nutrient database, age, and milk carotenoid adjustment variables with carotenoid, energy, fruit, and vegetable intakes. The effect of the number of food diary days on intake estimate precision was evaluated by testing the correlation between intake estimates derived from 1, 3, or 5, vs. 7 days. Visit age influenced energy intake estimates (<em>p</em> = .029), along with assessment tool (<em>p</em> = .020). Estimates of vegetable intake were influenced by tool (<em>p</em> = .009). Combined fruit and vegetable intake differed by nutrient database (<em>p</em> = .007). Carotenoid intake differed by age (<em>p</em> =<.0001), tool (<em>p</em> = .002), and nutrient database (<em>p</em> = .004). A minimum of 3 food diary days strongly correlated (rho = 0.79-1) with reference estimates across ages. Milk carotenoid adjustment was most influential in estimating 4-month olds’ carotenoid intake, while nutrient database and tool were important for 6- and 8-month-olds’, highlighting the dynamic nature of infant diet assessment validity across feeding stages.</p></div>\",\"PeriodicalId\":19245,\"journal\":{\"name\":\"Nutrition Research\",\"volume\":\"128 \",\"pages\":\"Pages 38-49\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nutrition Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0271531724000800\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NUTRITION & DIETETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nutrition Research","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0271531724000800","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
The relative validity of nutrition assessment methods for estimating infant carotenoid intake differs by assessment tool, nutrient database, and milk carotenoid adjustment method
Validated carotenoid assessment methods are needed to study infant carotenoid nutrition. This is a secondary analysis of repeated diet assessments of healthy participants collected at 4- (n = 21), 6- (n = 12), and 8- (n = 9) months of age in Houston, TX between April 2019 and June 2020. Intake was assessed with 3 assessment tools, analyzed with 3 nutrient databases, and underwent 3 adjustments to account for milk composition variability. We hypothesized that manual adjustment of milk carotenoid intake based on laboratory measurements would improve the validity of all assessment approaches and that using a database with greater coverage of infant food carotenoid compositions would improve accuracy. Generalized linear mixed models assessed associations between tool, nutrient database, age, and milk carotenoid adjustment variables with carotenoid, energy, fruit, and vegetable intakes. The effect of the number of food diary days on intake estimate precision was evaluated by testing the correlation between intake estimates derived from 1, 3, or 5, vs. 7 days. Visit age influenced energy intake estimates (p = .029), along with assessment tool (p = .020). Estimates of vegetable intake were influenced by tool (p = .009). Combined fruit and vegetable intake differed by nutrient database (p = .007). Carotenoid intake differed by age (p =<.0001), tool (p = .002), and nutrient database (p = .004). A minimum of 3 food diary days strongly correlated (rho = 0.79-1) with reference estimates across ages. Milk carotenoid adjustment was most influential in estimating 4-month olds’ carotenoid intake, while nutrient database and tool were important for 6- and 8-month-olds’, highlighting the dynamic nature of infant diet assessment validity across feeding stages.
期刊介绍:
Nutrition Research publishes original research articles, communications, and reviews on basic and applied nutrition. The mission of Nutrition Research is to serve as the journal for global communication of nutrition and life sciences research on diet and health. The field of nutrition sciences includes, but is not limited to, the study of nutrients during growth, reproduction, aging, health, and disease.
Articles covering basic and applied research on all aspects of nutrition sciences are encouraged, including: nutritional biochemistry and metabolism; metabolomics, nutrient gene interactions; nutrient requirements for health; nutrition and disease; digestion and absorption; nutritional anthropology; epidemiology; the influence of socioeconomic and cultural factors on nutrition of the individual and the community; the impact of nutrient intake on disease response and behavior; the consequences of nutritional deficiency on growth and development, endocrine and nervous systems, and immunity; nutrition and gut microbiota; food intolerance and allergy; nutrient drug interactions; nutrition and aging; nutrition and cancer; obesity; diabetes; and intervention programs.