Dataset Information

Introducing a Suite of Low-Burden Diet Quality Indicators That Reflect Healthy Diet Patterns at Population Level.

ABSTRACT:

Background

Few low-burden indicators of diet quality exist to track trends over time at low cost and with low technical expertise requirements.

Objective

The aim was to develop and validate a suite of low-burden indicators to reflect adherence to global dietary recommendations.

Methods

Using nationally representative, cross-sectional, quantitative dietary intake datasets from Brazil and the United States, we tested the association of food-group scores with quantitative consumption aligned with 11 global dietary recommendations. We updated the Healthy Diet Indicator (HDI) to include current quantifiable recommendations of the WHO (HDI-2020). We developed 3 food-group-based scores-an overall Global Dietary Recommendations (GDR) score as an indicator of all 11 recommendations composed of 2 subcomponents: GDR-Healthy, an indicator of the recommendations on "healthy" foods, and GDR-Limit, an indicator of the recommendations on dietary components to limit. We tested associations between these scores and the HDI-2020 and its respective subcomponents. We developed 9 dichotomous food-group-based indicators to reflect adherence to the global recommendations for fruits and vegetables, dietary fiber, free sugars, saturated fat, total fat, legumes, nuts and seeds, whole grains, and processed meats. We conducted receiver operating characteristic and sensitivity-specificity analyses to determine whether the dichotomous indicators were valid to predict adherence to the recommendations in both countries.

Results

The GDR score and its subcomponents were moderately to strongly associated with the HDI-2020 and its respective subcomponents (absolute values of rank correlation coefficients ranged from 0.55 to 0.66). Of the 9 dichotomous indicators, 8 largely met the criteria for predicting individual global dietary recommendations in both countries; 1 indicator (total fat) did not perform satisfactorily.

Conclusions

Food-group consumption data can be used to indicate adherence to quantitative global dietary recommendations at population level. These indicators may be used to track progress of countries and populations toward meeting WHO guidance on healthy diets.

SUBMITTER: Herforth AW

PROVIDER: S-EPMC7723758 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Introducing a Suite of Low-Burden Diet Quality Indicators That Reflect Healthy Diet Patterns at Population Level.

Herforth Anna W AW Wiesmann Doris D Martínez-Steele Euridice E Andrade Giovanna G Monteiro Carlos A CA

Current developments in nutrition 20201125 12

<h4>Background</h4>Few low-burden indicators of diet quality exist to track trends over time at low cost and with low technical expertise requirements.<h4>Objective</h4>The aim was to develop and validate a suite of low-burden indicators to reflect adherence to global dietary recommendations.<h4>Methods</h4>Using nationally representative, cross-sectional, quantitative dietary intake datasets from Brazil and the United States, we tested the association of food-group scores with quantitative cons ...[more]

PMID: 33344879

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Project description:Diet quality indicators (DQIns) are tools that aim to assess an individual's overall diet quality. Previous reviews focused mainly on health-related outcomes but did not provide detailed information about components, assessment variables, or important methodological issues for the development and application of DQIns in the pediatric age. The current mapping review aims to provide comprehensive guidance regarding DQIns developed through a priori methodology in children aged ≤14 y that have been applied worldwide. A mapping review was conducted, whereby 1665 original articles describing the development, modifications, and updates of DQIns, published up to June 26, 2020, in English and Spanish, were retrieved. A total of 139 articles were identified and classified into 13 subgroups. There were 10 overall DQIns: Healthy Eating Indexes (n = 25), Dietary Diversity Scores (n = 20), Diet Quality Indexes (n = 16), Food Variety Scores (n = 11), Healthy and Unhealthy Scores (n = 11), Feeding and Eating Indexes (n = 10), Diet Quality Scores (n = 5), Nutritional Adequacy and Micronutrients Indexes (n = 5), Dietary Guidelines Indexes (n = 5), and Other Healthy Diet Indexes (n = 13). Three additional subgroups of dietary and lifestyle indicators found were Mediterranean Diet Indexes (n = 10), Diet-Lifestyle Indexes (n = 5), and Breakfast Quality Indexes (n = 3). This compilation of DQIns will help researchers select the most appropriate tool for future epidemiological studies by considering a careful selection of information about the assessment components, scoring methods, and key methodological issues. The main limitations of this review are that, due to its nature, a risk-of-bias assessment was not performed and the article screening was completed in 2 databases (PubMed/MEDLINE and Scopus). More research is needed to identify health-related outcomes associated with DQIns in the pediatric population, using clearer and more standardized methodological criteria.

Project description:BackgroundFood purchasing is considered a key mediator between the food environment and eating behavior, and food purchasing patterns are increasingly measured in epidemiologic and intervention studies. However, the extent to which food purchases actually reflect individuals' dietary intake has not been rigorously tested. This study examined cross-sectional agreement between estimates of diet quality and nutrient densities derived from objectively documented household food purchases and those derived from interviewer-administered 24-h diet recalls. A secondary aim was to identify moderator variables associated with attenuated agreement between purchases and dietary intake.MethodsPrimary household food shoppers (N = 196) collected and annotated receipts for all household food and beverage purchases (16,356 total) over 14 days. Research staff visited participants' homes four times to photograph the packaging and nutrition labels of each purchased item. Three or four multiple-pass 24-h diet recalls were performed within the same 14-d period. Nutrient densities and Healthy Eating Index-2010 (HEI-2010) scores were calculated from both food purchase and diet recall data.ResultsHEI-2010 scores derived from food purchases (median = 60.9, interquartile range 49.1-71.7) showed moderate agreement (ρc = .57, p < .0001) and minimal bias (-2.0) with HEI-2010 scores from 24-h recalls (median = 60.1, interquartile range 50.8-73.9). The degree of observed bias was unrelated to the number of food/beverage purchases reported or participant characteristics such as social desirability, household income, household size, and body mass. Concordance for individual nutrient densities from food purchases and 24-h diet recalls varied widely from ρc = .10 to .61, with the strongest associations observed for fiber (ρc = .61), whole fruit (ρc = .48), and vegetables (ρc = .39).ConclusionsObjectively documented household food purchases yield an unbiased and reasonably accurate estimate of overall diet quality as measured through 24-h diet recalls, but are generally less useful for characterizing dietary intake of specific nutrients. Thus, some degree of caution is warranted when interpreting food purchase data as a reflection of diet in epidemiological and clinical research. Future work should examine agreement between food purchases and nutritional biomarkers.Trial registrationClinicalTrials.gov, NCT02073643 . Retrospectively registered.

Dataset Information

Introducing a Suite of Low-Burden Diet Quality Indicators That Reflect Healthy Diet Patterns at Population Level.

Background

Objective

Methods

Results

Conclusions

Publications

Introducing a Suite of Low-Burden Diet Quality Indicators That Reflect Healthy Diet Patterns at Population Level.

Similar Datasets

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