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Dairy, especially cheese, is associated with high levels of greenhouse gas emissions. Accurate estimates of dairy consumption are therefore important for monitoring dietary transition targets. Previous studies found that disaggregating the meat out of composite foods significantly impacts estimates of meat consumption. Our objective was to determine whether disaggregating the dairy out of composite foods impacts estimates of dairy consumption in Scotland. Approximately 32% of foods in the UK Nutrient Databank contain some dairy. In the 2021 Scottish Health Survey, mean daily intakes of dairy with and without disaggregation of composite foods were 238.6 and 218.4 g, respectively. This translates into an 8% underestimation of dairy consumption when not accounting for dairy in composite foods. In particular, milk was underestimated by 7% and cheese and butter by 50%, whereas yogurt was overestimated by 15% and cream by 79%. Failing to disaggregate dairy from composite foods may underestimate dairy consumption.

Background: Nonquantitative list-based or open 24-h recalls (24-HRs) have been shown to overestimate the prevalence of Minimum Dietary Diversity for Women (MDD-W), as compared with direct quantitative observations. However, the main sources of error are unknown. Objectives: To assess the measurement agreement of proxy data collection methods for MDD-W, as compared with weighed food records (WFRs). Methods: Applying a noninferiority design, data were collected from 431 nonpregnant females in Ethiopia. MDD-W estimates from both proxy data collection methods were compared with the WFR prevalence by McNemar’s chi-square tests, Cohen’s Kappa, and receiver operator characteristic analyses. Ten-point food group diversity scores (FGDS) were compared by Bland–Altman plots, Wilcoxon matched-pairs tests, and weighted Kappa. Food group misclassifications were partitioned into errors related to respondent biases or the questionnaire development. Results: List-based and open 24-HRs overreported MDD-W by 8 and 4 percentage points, respectively, as compared with WFR (objective MDD-W prevalence: 8%). Furthermore, list-based 24-HRs overestimated FGDS by 0.4 points (limits of agreement [LOA]: −1.1, 2.0), whereas open 24-HRs led to a 0.3 point (LOA: −1.2, 1.7) overestimate. Food groups most likely to be misreported using proxy data collection methods were “pulses,” “nuts and seeds,” “dairy products,” and “other fruits.” Underreporting of consumption occurred among

Dietary Guidelines for Americans (DGA) have become increasingly food-based guidelines. The Healthy United States--Style Eating Pattern features fruits, vegetables, whole grains, and low-fat dairy, with limits placed on added sugar, sodium, and saturated fat. Recent measures of nutrient density have followed suit, incorporating both nutrients and food groups. Most recently, the United States Food and Drug Administration (FDA) has proposed to redefine the concept of a "healthy" food for regulatory purposes. To qualify as healthy, foods will need to contain specific minimum amounts of fruits, vegetables, dairy, and whole grains, with limits placed on added sugar, sodium, and saturated fat. The present concern was that the proposed criteria, formulated by the FDA per Reference Amount Customarily Consumed, were so stringent that few foods would pass. We applied the proposed FDA criteria to foods in the USDA Food and Nutrient Database for Dietary Studies (FNDDS 2017-2018). The criteria were met by 58% of fruits, 35% of vegetables, 8% of milk and dairy products, and 4% of grain products. Many foods commonly considered to be healthy by consumers and the USDA alike did not pass the proposed FDA criteria. Federal agencies seem to define healthy in different ways. Our findings have implications for the formulation of regulatory and public health policies. We recommend that nutrition scientists be involved in the development of federal regulations and policies that affect American consumers and the food industry. [ABSTRACT FROM AUTHOR]

Background The Government of Ethiopia has made a major commitment toward improving food security, diet, nutrition, and health through a series of national nutrition plans. The focus of these plans is on providing both nutrition-specific as well as nutrition-sensitive approaches for achieving national priorities for health and nutrition. The present study conducted a secondary analysis of data provided through a larger birth cohort study conducted in Ethiopia between 2014 and 2016. Objectives The overall objectives of this research were to assess the relation between minimum dietary diversity in women and water, sanitation, and hygiene (WASH), and evaluate the association between midupper arm circumference (MUAC) in women and WASH. Methods In addition to descriptive statistics, the study used mixed effects logistic regression analyses to investigate the relation between dietary diversity, MUAC, and household WASH practices. Results Improved WASH practices were associated with an increased probability (p  = 0.04) that a woman would consume a diet with foods from 5 or more food groups. A beneficial effect was observed for improved WASH practices and a decrease in low MUAC. Improved household WASH practices were successful in contributing to improved dietary diversity in women as well as an improved MUAC. Conclusions Interventions aimed at improving the diet and nutritional status of women during and after pregnancy should include relevant WASH components as essential elements in multisector nutrition programming. [ABSTRACT FROM AUTHOR]

Background: Nonquantitative list-based or open 24-h recalls (24-HRs) have been shown to overestimate the prevalence of Minimum Dietary Diversity for Women (MDD-W), as compared with direct quantitative observations. However, the main sources of error are unknown., Objectives: To assess the measurement agreement of proxy data collection methods for MDD-W, as compared with weighed food records (WFRs)., Methods: Applying a noninferiority design, data were collected from 431 nonpregnant females in Ethiopia. MDD-W estimates from both proxy data collection methods were compared with the WFR prevalence by McNemar's chi-square tests, Cohen's Kappa, and receiver operator characteristic analyses. Ten-point food group diversity scores (FGDS) were compared by Bland-Altman plots, Wilcoxon matched-pairs tests, and weighted Kappa. Food group misclassifications were partitioned into errors related to respondent biases or the questionnaire development., Results: List-based and open 24-HRs overreported MDD-W by 8 and 4 percentage points, respectively, as compared with WFR (objective MDD-W prevalence: 8%). Furthermore, list-based 24-HRs overestimated FGDS by 0.4 points (limits of agreement [LOA]: -1.1, 2.0), whereas open 24-HRs led to a 0.3 point (LOA: -1.2, 1.7) overestimate. Food groups most likely to be misreported using proxy data collection methods were "pulses," "nuts and seeds," "dairy products," and "other fruits." Underreporting of consumption occurred among <4% of females for all food groups. Furthermore, respondent biases were the predominant cause of food group overreporting, except for the "pulses" and "other vegetables" food groups, where food items incorrectly included on the food list were the main source of errors., Conclusions: Food group consumption misclassifications by proxy data collection methods were mainly attributable to females overreporting consumption because of respondent biases or the criterion for foods to be counted, rather than the suboptimal development of the food list in Ethiopia. To obtain precise and accurate MDD-W estimates at the (sub)national level, rigorous context-specific food list development, questionnaire pilot testing, and enumerator training are recommended to mitigate identified biases., (© 2024 Food and Agriculture Organization of the United Nations.)

Dairy, especially cheese, is associated with high levels of greenhouse gas emissions. Accurate estimates of dairy consumption are therefore important for monitoring dietary transition targets. Previous studies found that disaggregating the meat out of composite foods significantly impacts estimates of meat consumption. Our objective was to determine whether disaggregating the dairy out of composite foods impacts estimates of dairy consumption in Scotland. Approximately 32% of foods in the UK Nutrient Databank contain some dairy. In the 2021 Scottish Health Survey, mean daily intakes of dairy with and without disaggregation of composite foods were 238.6 and 218.4 g, respectively. This translates into an 8% underestimation of dairy consumption when not accounting for dairy in composite foods. In particular, milk was underestimated by 7% and cheese and butter by 50%, whereas yogurt was overestimated by 15% and cream by 79%. Failing to disaggregate dairy from composite foods may underestimate dairy consumption., (© 2024 The Authors.)

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. [ABSTRACT FROM AUTHOR]

Background: Dietary diversity is a key element of diet quality, but diets of women of reproductive age (WRA; aged 15-49 y) in resource-poor settings are often deficient in a range of micronutrients. Previous work showed associations between simple food-group diversity indicators (FGIs) and micronutrient adequacy among WRA. For operational and advocacy purposes, however, there is strong demand for a dichotomous indicator reflecting an acceptable level of dietary diversity. Objective: The aim of the study was to develop a dichotomous indicator of dietary diversity in WRA. Methods: We performed a secondary analysis of 9 data sets containing quantitative dietary data from WRA in resource-poor settings (total n = 4166). From the raw dietary data, we calculated an individual "mean probability of adequacy" (MPA) across 11 micronutrients. Several candidate FGIs were constructed. Indicator performance in predicting an MPA >0.60 was assessed within each data set by using receiver-operating characteristic analysis and sensitivity and specificity analysis at various FGI cutoffs. The analysis was performed separately for nonpregnant and nonlactating (NPNL) women and for lactating women. Results: We identified 2 "best candidate" dichotomous indicators on the basis of 9- or 10-point food-group scores (FGI-9 and FGI-10) with a cutoff of ≥5 food groups. Both were significantly correlated to MPA in each site ( P < 0.001). Areas under the curve were moderate, ranging from 0.62 to 0.82 among NPNL women and from 0.56 to 0.90 among lactating women. Comparisons of results slightly favored FGI-10 for all women. Conclusions: When resource-intensive dietary methods are not feasible, a simple dichotomous indicator based on a cutoff of ≥5 of 10 defined food groups reflects "minimum dietary diversity for women of reproductive age." According to the conclusions of a consensus meeting of experts, this indicator is well suited for population-level assessment, advocacy, and possibly also for tracking of change in dietary diversity across time.