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Background The global diet quality score (GDQS) is a simple, standardized metric appropriate for population-based measurement of diet quality globally. Objectives We aimed to operationalize data collection by modifying the quantity of consumption cutoffs originally developed for the GDQS food groups and to statistically evaluate the performance of the operationalized GDQS relative to the original GDQS against nutrient adequacy and noncommunicable disease (NCD)-related outcomes. Methods The GDQS application uses a 24-h open-recall to collect a full list of all foods consumed during the previous day or night, and automatically classifies them into corresponding GDQS food group. Respondents use a set of 10 cubes in a range of predetermined sizes to determine if the quantity consumed per GDQS food group was below, or equal to or above food group-specific cutoffs established in grams. Because there is only a total of 10 cubes but as many as 54 cutoffs for the GDQS food groups, the operationalized cutoffs differ slightly from the original GDQS cutoffs. Results A secondary analysis using 5 cross-sectional datasets comparing the GDQS with the original and operationalized cutoffs showed that the operationalized GDQS remained strongly correlated with nutrient adequacy and was equally sensitive to anthropometric and other clinical measures of NCD risk. In a secondary analysis of a longitudinal cohort study of Mexican teachers, there were no differences between the 2 modalities with the beta coefficients per 1 SD change in the original and operationalized GDQS scores being nearly identical for weight gain (-0.37 and -0.36, respectively, P

Background The prevalence of type 2 diabetes has increased substantially in India over the past 3 decades. Undiagnosed diabetes presents a public health challenge, especially in rural areas, where access to laboratory testing for diagnosis may not be readily available. Objectives The present work explores the use of several machine learning and statistical methods in the development of a predictive tool to screen for prediabetes using survey data from an FFQ to compute the Global Diet Quality Score (GDQS). Methods The outcome variable prediabetes status (yes/no) used throughout this study was determined based upon a fasting blood glucose measurement ≥100 mg/dL. The algorithms utilized included the generalized linear model (GLM), random forest, least absolute shrinkage and selection operator (LASSO), elastic net (EN), and generalized linear mixed model (GLMM) with family unit as a (cluster) random (intercept) effect to account for intrafamily correlation. Model performance was assessed on held-out test data, and comparisons made with respect to area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Results The GLMM, GLM, LASSO, and random forest modeling techniques each performed quite well (AUCs >0.70) and included the GDQS food groups and age, among other predictors. The fully adjusted GLMM, which included a random intercept for family unit, achieved slightly superior results (AUC of 0.72) in classifying the prediabetes outcome in these cluster-correlated data. Conclusions The models presented in the current work show promise in identifying individuals at risk of developing diabetes, although further studies are necessary to assess other potentially impactful predictors, as well as the consistency and generalizability of model performance. In addition, future studies to examine the utility of the GDQS in screening for other noncommunicable diseases are recommended.

Background Key nutrient deficits remain widespread throughout sub-Saharan Africa (SSA) whereas noncommunicable diseases (NCDs) now cause one-third of deaths. Easy-to-use metrics are needed to track contributions of diet quality to this double burden. Objectives We evaluated comparative performance of a novel food-based Global Diet Quality Score (GDQS) against other diet metrics in capturing nutrient adequacy and undernutrition in rural SSA adults. Methods We scored the GDQS, Minimum Dietary Diversity–Women (MDD-W), and Alternative Healthy Eating Index–2010 (AHEI-2010) using FFQ data from rural men and nonpregnant, nonlactating women of reproductive age (15–49 y) in 10 SSA countries. We evaluated Spearman correlations between metrics and energy-adjusted nutrient intakes, and age-adjusted associations with BMI, midupper arm circumference (MUAC), and hemoglobin in regression models. Results Correlations between the GDQS and an energy-adjusted aggregate measure of dietary protein, fiber, calcium, iron, zinc, vitamin A, folate, and vitamin B-12 adequacy were 0.34 (95% CI: 0.30, 0.38) in men and 0.37 (95% CI: 0.32, 0.41) in women. The GDQS was associated (P

Background Evidence on concurrent changes in overall diet quality and weight and waist circumference in women of reproductive age from low- and middle-income countries is limited. Objectives We examined the associations of changes in the Global Diet Quality Score (GDQS) and each GDQS food group with concurrent weight and waist circumference change in Mexican women. Methods We followed prospectively 8967 nonpregnant nonlactating women aged 25–49 y in the Mexican Teachers’ Cohort between 2006 and 2008. We assessed diet using an FFQ of the previous year and anthropometric measures were self-reported. Regression models were used to examine 2-y changes in the GDQS and each food group (servings/d) with weight and waist circumference changes within the same period, adjusting for demographic and lifestyle factors. Results Compared with those with little change in the GDQS (−2 to 2 points), women with the largest increase in the GDQS (>5 points) had less weight (β: −0.81 kg/2 y; 95% CI: −1.11, −0.51 kg/2 y) and waist circumference gain (β: −1.05 cm/2 y; 95% CI: −1.62, −0.48 cm/2 y); likewise, women with the largest decrease in the GDQS (

Background Poor diet quality is a major driver of both classical malnutrition and noncommunicable disease (NCD) and was responsible for 22% of adult deaths in 2017. Most countries face dual burdens of undernutrition and NCDs, yet no simple global standard metric exists for monitoring diet quality in populations and population subgroups. Objectives We aimed to develop an easy-to-use metric for nutrient adequacy and diet related NCD risk in diverse settings. Methods Using cross-sectional and cohort data from nonpregnant, nonlactating women of reproductive age in 10 African countries as well as China, India, Mexico, and the United States, we undertook secondary analyses to develop novel metrics of diet quality and to evaluate associations between metrics and nutrient intakes and adequacy, anthropometry, biomarkers, type 2 diabetes, and iteratively modified metric design to improve performance and to compare novel metric performance to that of existing metrics. Results We developed the Global Diet Quality Score (GDQS), a food-based metric incorporating a more comprehensive list of food groups than most existing diet metrics, and a simple means of scoring consumed amounts. In secondary analyses, the GDQS performed comparably with the Minimum Dietary Diversity - Women indicator in predicting an energy-adjusted aggregate measure of dietary protein, fiber, calcium, iron, zinc, vitamin A, folate, and vitamin B12 adequacy and with anthropometric and biochemical indicators of undernutrition (including underweight, anemia, and serum folate deficiency), and the GDQS also performed comparably or better than the Alternative Healthy Eating Index - 2010 in capturing NCD-related outcomes (including metabolic syndrome, change in weight and waist circumference, and incident type 2 diabetes). Conclusions The simplicity of the GDQS and its ability to capture both nutrient adequacy and diet-related NCD risk render it a promising candidate for global monitoring platforms. Research is warranted to validate methods to operationalize GDQS assessment in population surveys, including a novel application–based 24-h recall system developed as part of this project.

Moderate acute malnutrition (MAM) affects 11% of children −2. The median duration of feeding was 2 wk, with a maximum of 12 wk. The hypothesis tested was that children treated with either RUSF would be more likely to remain well-nourished than those treated with CSB++. The primary outcome, remaining well-nourished, was defined as mid-upper arm circumference ≥12.5 cm or WHZ ≥−2 for the entire duration of follow-up. During the 12-mo follow-up period, only 1230 (63%) children remained well-nourished, 334 (17%) relapsed to MAM, 190 (10%) developed severe acute malnutrition, 74 (4%) died, and 139 (7%) were lost to follow-up. Children who were treated with soy/whey RUSF were more likely to remain well-nourished (67%) than those treated with CSB++ (62%) or soy RUSF (59%) (P = 0.01). A seasonal pattern of food insecurity and adverse clinical outcomes was observed. This study demonstrates that children successfully treated for MAM with soy/whey RUSF are more likely to remain well-nourished; however, all children successfully treated for MAM remain vulnerable.

Women of reproductive age living in resource-poor settings are at high risk of inadequate micronutrient intakes when diets lack diversity and are dominated by staple foods. Yet comparative information on diet quality is scarce and quantitative data on nutrient intakes is expensive and difficult to gather. We assessed the potential of simple indicators of dietary diversity, such as could be generated from large household surveys, to serve as proxy indicators of micronutrient adequacy for population-level assessment. We used 5 existing data sets (from Burkina Faso, Mali, Mozambique, Bangladesh, and the Philippines) with repeat 24-h recalls to construct 8 candidate food group diversity indicators (FGI) and to calculate the mean probability of adequacy (MPA) for 11 micronutrients. FGI varied in food group disaggregation and in minimum consumption required for a food group to count. There were large gaps between intakes and requirements across a range of micronutrients in each site. All 8 FGI were correlated with MPA in all sites; regression analysis confirmed that associations remained when controlling for energy intake. Assessment of dichotomous indicators through receiver-operating characteristic analysis showed moderate predictive strength for the best choice indicators, which varied by site. Simple FGI hold promise as proxy indicators of micronutrient adequacy. J. Nutr. 140: 2059S-2069S, 2010.

Micronutrient malnutrition is one of the most widespread yet largely neglected nutrition challenges faced by women living in the developing world today. An estimated 19 million pregnant women are vitamin A deficient due to poor diets (1), and 500 million women of childbearing age (;40%) are anemic (1, 2). The burden of these and other micronutrient deficiencies, such as zinc, iodine, and vitamin B-12, is particularly high in South Asia and sub-Saharan Africa (3). The consequences of micronutrient deficiencies among women are profound and far reaching; they affect not only the health and survival of women but also have long-term, irreversible effects on their offspring. Poor maternal nutrition and health can also jeopardize the ability of women to care for their children, engage in incomegenerating activities, and protect household food security. One of the most important factors responsible for maternal micronutrient deficiency, along with disease burden, is poor diets lacking diversity. Diets of the poor are largely based on cereal or tuber staples and often lack vegetables, fruits, and animal source foods, which are rich in bioavailable micronutrients. Even in households where micronutrient-rich foods are available, inequities in intra-household distribution may prevent women from having access to a high-quality diet (4). Accurate information on women’s diets and micronutrient intakes, however, is extremely scant due primarily to the challenge and cost of collecting and analyzing dietary data. Dietary intake data are timeand resource-intensive to collect and require careful processing and sophisticated analytic methods. The result is that most large data collection efforts, especially those carried out at the national level, have not included dietary intake data. Without data on women’s dietary, and more specifically micronutrient, intake, however, progress in designing, targeting, and evaluating effective programs to improve women’s micronutrient nutrition will continue to be hampered. The Women’s Dietary Diversity Project (WDDP) was designed in 2005 specifically to respond to the need for generating simple yet valid indicators of women’s dietary quality. This collaborative research initiative used existing dietary intake data from 5 resource-poor settings to document women’s diet quality, defined as micronutrient adequacy, and to test whether food group diversity indicators (FGI) could be a useful tool in large-scale nationally representative surveys to predict women’s dietary quality. This journal supplement begins with a review of the literature on women’s micronutrient intakes in Africa, Asia, and Latin America. This is followed by a presentation of empirical research findings from the WDDP initiative. These include results from analyses of 5 datasets on women’s dietary patterns and nutrient intakes from vastly different settings, including both urban/periurban (Burkina Faso, Mali, Philippines) and rural (Bangladesh, Mozambique) areas. The analyses also document the relationship between simple indicators of dietary diversity and the micronutrient adequacy of women’s diets in these settings. Collectively, the results highlight the nature and extent of the gap between women’s micronutrient requirements and their dietary intakes in the 5 areas represented. They also confirm the potential usefulness of simple dietary diversity indicators as a proxy for women’s poor diet quality in these environments. The results are particularly useful for helping focus attention on the critical problem of poor diet quality among women of reproductive age in resource-poor environments. The systematic literature review by Torheim et al. (5) shows a consistent pattern of generally low micronutrient intakes among women in Africa, Asia, and Latin America, regardless of the 1 Published in a supplement to The Journal of Nutrition. Findings of research carried out under the USAID funded Food and Nutrition Technical Assistance Project’s (FANTA) Women’s Dietary Diversity Project (WDDP). The supplement coordinators for this supplement wereMegan Deitchler, AED, andMarie T. Ruel, International Food Policy Research Institute. Supplement Coordinator disclosures: Megan Deitchler is an employee of AED. Marie T. Ruel declares no conflict of interest. The supplement is the responsibility of the Guest Editor to whom the Editor of The Journal of Nutrition has delegated supervision of both technical conformity to the published regulations of The Journal of Nutrition and general oversight of the scientific merit of each article. The Guest Editor for this supplement was Jennifer Nettleton. Guest Editor disclosure: no conflicts of interest. This publication is made possible by the generous support of the American people through the support of the Office of Health, Infectious Disease, and Nutrition, Bureau for Global Health, United States Agency for International Development (USAID), under terms of Cooperative Agreement No. GHN-A00-08-00001-00, through the Food and Nutritional Technical Assistance II Project (FANTA-2), managed by AED. The opinions expressed herein are those of the authors and do not necessarily reflect the views of USAID or the United States Government. Publication costs for this supplement were defrayed in part by the payment of page charges. This publication must therefore be hereby marked "advertisement" in accordance with 18 USC section 1734 solely to indicate this fact. The opinions expressed in this publication are those of the authors and are not attributable to the sponsors or the publisher, Editor, or Editorial Board of The Journal of Nutrition. 2 Author disclosures: M. T. Ruel and M. Arimond, no conflicts of interest. M. Deitchler is an employee of AED. * To whom correspondence should be addressed. E-mail: m.ruel@cgiar.org. 6 Abbreviations used: FGI, food group diversity indicator; MPA, mean probability of adequacy; NPNL, nonpregnant, nonlactating; WDDP, Women’s Dietary Diversity Project. 7 The Women’s Dietary Diversity Project (WDDP) is a collaboration among researchers from the International Food Policy Research Institute, AED, Fafo Institute for Applied International Studies, FAO, Institute of Research for Development, Iowa State University, London School of Hygiene and Tropical Medicine, University of North Carolina at Chapel Hill, and Wageningen University.