ps of Chinese adults. The finding supports the use of the GDQS in different demographic groups of Chinese adults to assess diet quality and nutritional status.

Nutritionally inadequate diets in Ethiopia contribute to a persisting national burden of adult undernutrition, while the prevalence of noncommunicable diseases (NCDs) is rising.

To evaluate performance of a novel Global Diet Quality Score (GDQS) in capturing diet quality outcomes among Ethiopian adults.

We scored the GDQS and a suite of comparison metrics in secondary analyses of FFQ and 24-hour recall (24HR) data from a population-based cross-sectional survey of nonpregnant, nonlactating women of reproductive age and men (15-49 years) in Addis Ababa and 5 predominately rural regions. We evaluated Spearman correlations between metrics and energy-adjusted nutrient adequacy, and associations between metrics and anthropometric/biomarker outcomes in covariate-adjusted regression models.

In the FFQ analysis, correlations between the GDQS and an energy-adjusted aggregate measure of dietary protein, fiber, calcium, iron, zinc, vitamin A, folate, and vitamin B12 adequacy were 0.32 in men and 0.26 in women. GDe warranted to assess the GDQS’ performance in capturing NCD outcomes in sub-Saharan Africa.

The GDQS performed capably in capturing nutrient adequacy-related outcomes in Ethiopian adults. Prospective studies are warranted to assess the GDQS’ performance in capturing NCD outcomes in sub-Saharan Africa.

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.

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.

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.

Correlations between the GDQS and an energy-adjusted aggregate measure of dietary protein, fiber, calcium, iron, zinc, vitamin A, folate, and vitamin B-1ring nutrient adequacy-related outcomes in rural SSA. Selleck CI-1040 Given limited data on NCD outcomes and the cross-sectional study design, prospective studies are warranted to assess GDQS performance in capturing NCD outcomes in SSA.

We have developed a diet quality metric intended for global use. To assess its utility in high-income settings, an evaluation of its ability to predict chronic disease is needed.

We aimed to prospectively examine the ability of the Global Diet Quality Score (GDQS) to predict the risk of type 2 diabetes in the United States, examine potential differences of association by age, and compare the GDQS with other diet quality scores.

Health, lifestyle, and diet information was collected from women (n=88,520) in the Nurses’ Health Study II aged 27-44 y at baseline through repeated questionnaires between 1991 and 2017. The overall GDQS consists of 25 food groups. Points are awarded for higher intake of healthy groups and lower intake of unhealthy groups (maximum of 49 points). Multivariable HRs were computed for confirmed type 2 diabetes using proportional hazards models. We also compared the GDQS with the Minimum Diet Diversity score for Women (MDD-W) and the Alternate Healthy Eating Index-2010 (AHEI-2010).

sely associated with type 2 diabetes risk in US women of reproductive age or older, mainly from lower intake of unhealthy foods. The GDQS performed nearly as well as the AHEI-2010.

The Global Diet Quality Score (GDQS) is intended as a simple global diet quality metric feasible in low- and middle-income countries facing the double burden of malnutrition.

The aim of this study was to evaluate the performance of the GDQS with markers of nutrient adequacy and chronic disease in nonpregnant nonlactating (NPNL) Mexican women of reproductive age and to compare it with the Alternate Healthy Eating Index-2010 (AHEI-2010) and the Minimum Dietary Diversity for Women (MDD-W).

We included NPNL women aged 15 to 49 y from the Mexican National Health and Nutrition Surveys (2012 and 2016) with 24-h recall (n=2542) or a FFQ (n=4975) (separate samples). We evaluated the correlation of the GDQS with the energy-adjusted intake of several nutrients and evaluated its association with health parameters using covariate-adjusted linear regression models.

The GDQS was positively correlated with the intake of calcium, folate, iron, vitamin A, vitamin B-12, zinc, fiber, protein, and total fat (rho=0.09 to 0ase. The performance of the GDQS was satisfactory with either 24-h recall or FFQ.

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.

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.

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.

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 -0.81kg/2y; 95% CI -1.11, -0.51kg/2y) and waist circumference gain (β -1.05cm/2y; 95% CI -1.62, -0.48cm/2y); likewise, women with the largest decrease in the GDQS (<-5 points) had more weight (β 0.36kg/2y; 95% CI 0.06, 0.66kg/2y) and waist circumference gain (β 0.71cm/2y; 95% CI 0.09, 1.32cm/2y). Increased intake of dark green leafy vegetables, cruciferous vegetables, deep orange vegetables, citrus fruits, and fish and shellfish was associated with less weight gain. In addition, deep orange vegetables, low fat and high fat dairy, whole grains, and fish were associated with less waist circumference gain within the 2-y period.

Improvements in diet quality over a 2-y period reflected by an increase in the GDQS and changes in consumption of specific components of the GDQS were associated with less weight and waist circumference gain in Mexican women.

Improvements in diet quality over a 2-y period reflected by an increase in the GDQS and changes in consumption of specific components of the GDQS were associated with less weight and waist circumference gain in Mexican women.

The global diet quality score (GDQS) is a simple, standardized metric appropriate for population-based measurement of diet quality globally.

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.

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 originalerefore are recommended for use to collect GDQS data in the future.

We have developed a simple and globally applicable tool, the Global Diet Quality Score (GDQS), to measure diet quality.

To test the utility of the GDQS, we examined the associations of the GDQS with weight change and risk of obesity in US women.

Health, lifestyle, and diet information were collected from women (n=68,336) in the Nurses’ Health Study II (aged 27-44 y in 1991) through repeated questionnaires (1991-2015). The GDQS has 25 food groups (maximum=49 points) and scoring higher points reflects a healthier diet. The association between GDQS change in 4-y intervals and concurrent weight change was computed with linear models adjusted for confounders.

Mean±SD weight gain across 4-y periods was 1.68±6.26kg. A >5-point improvement in GDQS was associated with -1.13kg (95% CI -1.19, -0.77kg) weight gain compared with a score change of <±2 points. For each 5-point increase, weight gain was 0.83kg less for age<50y compared with 0.71kg less for age≥50y (P-interaction<0.05). A >5-point scoreon was stronger for women aged less then 50 y. Associations similar in direction and magnitude were observed between the GDQS and obesity across age groups.

In India, there is a need to monitor population-level trends in changes in diet quality in relation to both undernutrition and noncommunicable diseases.

We conducted a study to validate a novel diet quality score in southern India.

We included data from 3041 nonpregnant women of reproductive age (15-49 years) from 2 studies in India. Diet was assessed using a validated food frequency questionnaire (FFQ). The Global Diet Quality Score (GDQS) was calculated from 25 food groups (16 healthy; 9 unhealthy), with points for each group based on the frequency and quantity of items consumed in each group. We used Spearman correlations to examine correlations between the GDQS and several nutrient intakes of concern. We examined associations between the GDQS [overall, healthy (GDQS+), and unhealthy (GDQS-) submetrics] and overall nutrient adequacy, micro- and macronutrients, body mass index (BMI), midupper arm circumference, hemoglobin, blood pressure, high density lipoprotein (HDL), and total cholesterol (TC).

Tounts of unhealthy foods, like refined grains, along with healthy foods included in the GDQS.

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.

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).

The outcome variable prediabetes status (yes/no) used throughout this study was determined based upon a fasting blood glucose measurement ≥100mg/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.