BACKGROUND: Access to high-quality dietary intake data is central to many nutrition, epidemiology, economic, environmental, and policy applications. When data on individual nutrient intakes are available, they have not been consistently disaggregated by sex and age groups, and their parameters and full distributions are often not publicly available. OBJECTIVES: We sought to derive usual intake distributions for as many nutrients and population subgroups as possible, use these distributions to estimate nutrient intake inadequacy, compare these distributions and evaluate the implications of their shapes on the estimation of inadequacy, and make these distributions publicly available. METHODS: We compiled dietary data sets from 31 geographically diverse countries, modeled usual intake distributions for 32 micronutrients and 21 macronutrients, and disaggregated these distributions by sex and age groups. We compared the variability and skewness of the distributions and evaluated their similarity across countries, sex, and age groups. We estimated intake inadequacy for 16 nutrients based on a harmonized set of nutrient requirements and bioavailability estimates. Last, we created an R package-nutriR-to make these distributions freely available for users to apply in their own analyses. RESULTS: Usual intake distributions were rarely symmetric and differed widely in variability and skewness across nutrients and countries. Vitamin intake distributions were more variable and skewed and exhibited less similarity among countries than other nutrients. Inadequate intakes were high and geographically concentrated, as well as generally higher for females than males. We found that the shape of usual intake distributions strongly affects estimates of the prevalence of inadequate intakes. CONCLUSIONS: The shape of nutrient intake distributions differs based on nutrient and subgroup and strongly influences estimates of nutrient intake inadequacy. This research represents an important contribution to the availability and application of dietary intake data for diverse subpopulations around the world.
In contrast to nutrient pro!ling models that evaluate the overall nutritional value of individual foods, food-based diet quality metrics attempt to characterize the collective contribution of foods to health. The two approaches are complementary means of providing a quantitative basis upon which to develop programmatic guidance for improving population diets. In this article, we describe a novel food-based metric of diet quality for global use, and key takeaways of our research to develop and evaluate this metric.
Christopher D. Golden, J. Zachary Koehn, Alon Shepon, Simone Passarelli, Christopher M. Free, Daniel F. Viana, Holger Matthey, Jacob G. Eurich, Jessica A. Gephart, Etienne Fluet-Chouinard, Elizabeth A. Nyboer, Abigail J. Lynch, Marian Kjellevold, Sabri Bromage, Pierre Charlebois, Manuel Barange, Stefania Vannuccini, Ling Cao, Kristin M. Kleisner, Eric B. Rimm, Goodarz Danaei, Camille DeSisto, Heather Kelahan, Kathryn J. Fiorella, David C. Little, Edward H. Allison, Jessica Fanzo, and Shakuntala H. Thilsted. 9/2021. “Aquatic foods to nourish nations.” Nature. Publisher's VersionAbstract
Despite contributing to healthy diets for billions of people, aquatic foods are often undervalued as a nutritional solution because their diversity is often reduced to the protein and energy value of a single food type (‘seafood’ or ‘fish’). Here we create a cohesive model that unites terrestrial foods with nearly 3,000 taxa of aquatic foods to understand the future impact of aquatic foods on human nutrition. We project two plausible futures to 2030: a baseline scenario with moderate growth in aquatic animal-source food (AASF) production, and a high-production scenario with a 15-million-tonne increased supply of AASFs over the business-as-usual scenario in 2030, driven largely by investment and innovation in aquaculture production. By comparing changes in AASF consumption between the scenarios, we elucidate geographic and demographic vulnerabilities and estimate health impacts from diet-related causes. Globally, we find that a high-production scenario will decrease AASF prices by 26% and increase their consumption, thereby reducing the consumption of red and processed meats that can lead to diet-related non-communicable diseases while also preventing approximately 166 million cases of inadequate micronutrient intake. This finding provides a broad evidentiary basis for policy makers and development stakeholders to capitalize on the potential of aquatic foods to reduce food and nutrition insecurity and tackle malnutrition in all its forms.
The Sustainable Development Goals (SDGs) are intricately linked to food systems. Addressing challenges in food systems is key to meeting the SDGs in Africa and South Asia, where undernutrition and micronutrient deficiencies persist, alongside increased nutrition transition, overweight and obesity, and related chronic diseases. Suboptimal diets are a key risk factor for mortality and 3 billion people cannot afford a healthy diet; in addition, food systems are not prioritizing environmental sustainability. Optimizing food systems and increasing agricultural productivity beyond calories, to nutrient-rich vegetables and fruits, legumes, and livestock, and sustainable fishing, are required. Strengthening of research around food systems—on pathways, value chains, and development and validation of metrics of diet quality—is required. The development of new technology in crop management and pest control and addressing natural resource degradation is key. Engaging with the public and private sectors, outreach to donors and policymakers, and strengthening cross-disciplinary collaborations are imperative to improving food systems.
Background: In response to India’s unacceptably high burden of anemia among children aged 6–59 mo, the central government introduced the National Iron Plus Initiative program which recommends an intervention of iron supplementation to mitigate anemia, especially iron deficiency anemia. Objective: The objective of this study was to examine the trend (between 2005–2006 and 2015–2016) in receiving weekly iron supplementation (WIS) among children aged 6–59 mo, and factors associated with receiving WIS during 2015–2016.
Methods: Two waves of the nationally representative cross-sectional National Family Health Survey (NFHS) data collected during 2005–2006 (NFHS-3) and 2015–2016 (NFHS-4) were used. The trend was measured using both rounds of datasets, whereas factors associated with WIS receipt were assessed from NFHS-4. The trend was assessed using a sample of 35,650 children from NFHS-3 and 202,227 children from NFHS-4. After exclusion of 8978 cases, a total of 199,110 children were included to analyze the factors associated with receiving WIS. Using appropriate sample weighting, unadjusted and adjusted (multivariate) logistic regression analyses were deployed. Application of the chi-squared test and checking for multicollinearity were also part of the analysis. The possibility of sample selection bias was tested.
Results: An increase of WIS receipt (from 4.6% in 2005–2006 to 26% in 2015–2016) was observed. Older children, children living in rural areas, children belonging to Scheduled Tribes, children of mothers with secondary education or higher, and children whose mothers had some mass media exposure had higher odds of receiving WIS. Children of fifth or higher birth order, children who were followers of Islam and Christianity, children from the richest economic group, noninstitutional birth of children, and children from high-focus group states were negatively associated with WIS receipt.
Conclusions: Despite improvement (between 2005–2006 and 2015–2016) in receiving WIS, coverage remains unacceptably low (in absolute terms). The suboptimum performance of WIS intervention demands further investigation.
Objective: We assessed the ability of the Prime Diet Quality Score (PDQS) to predict mortality in a United States (U.S.) population and compared its predictiveness with that of the Healthy Eating Index-2015 (HEI-2015).
Design: PDQS and HEI-2015 scores were derived using two 24-hour recalls and converted to quintiles. Mortality data were obtained from the 2015 Public-Use Linked Mortality File. Associations between diet quality and all-cause mortality were evaluated using multivariable Cox proportional hazards models, and predictive performance of the two metrics were compared using a Wald test of equality of coefficients with both scores in a single model. Finally, we evaluated associations between individual metric components and mortality.
Setting: A prospective analysis of the U.S. National Health and Nutrition Examination Survey (NHANES) data.
Participants: 5,525 participants from three survey cycles (2003-2008) in the NHANES aged 40 years and over.
Results: Over the 51,248 person-years of follow-up (mean: 9.2 years), 767 deaths were recorded. In multivariable models, hazard ratios between the highest and lowest quintiles of diet quality scores were 0.70 (95%CI: 0.51, 0.96, p-trend=0.03) for the PDQS, and 0.77 (95%CI: 0.57, 1.03, p-trend=0.20) for the HEI-2015. The PDQS and HEI-2015 were similarly good predictors of total mortality (p-difference=0.88).
Conclusion: Among U.S. adults, better diet quality measured by the PDQS was associated with reduced risk of all-cause mortality. Given that the PDQS is simpler to calculate than the HEI-2015, it should be evaluated further for use as a diet quality metric globally.
Valid and efficient tools for measuring and tracking diet quality globally are lacking.
The objective of the study was to develop and evaluate a new tool for rapid and cost-efficient diet quality assessment.
Two screener versions were designed using Prime Diet Quality Score (PDQS), one in a 24-hour recall (PDQS-24HR) and another in a 30-day (PDQS-30D) food frequency format. Participants completed two 24-hour diet recalls using the Automated Self-Administered 24-hour Dietary Assessment Tool (ASA24) and 2 web-based diet quality questionnaires 7 to 30 days apart in April and May 2019. Both dichotomous/trichotomous and granular scoring versions were tried for each screener.
The study included 290 nonpregnant, nonlactating US women (mean age ± standard deviation 41 ± 11 years) recruited via Amazon Mechanical Turk.
Main outcome measures
The main outcome measures were Spearman rank correlation coefficients and linear regression beta-coefficients between ASA24 nutrient intakes from foods and beverages and PDQS values.
Statistical analyses performed
The Spearman rank correlation and linear regression were used to evaluate associations of the PDQS values with ASA24 nutrient intakes from food, both crude and energy-adjusted. Correlations were de-attenuated for within-person variation in 24-hour recalls. Wolfe’s test was used to compare correlations of the 2 screening instruments (PDQS-24HR and PDQS-30D) with the ASA24. Associations between the ASA24 Healthy Eating Index 2015 and the PDQS values were also evaluated.
Positive, statistically significant rank correlations between the PDQS-24HR values and energy-adjusted nutrients from ASA24 for fiber (r = 0.53), magnesium (r = 0.51), potassium (r = 0.48), vitamin E (r = 0.40), folate (r = 0.37), vitamin C (r = 0.36), vitamin A (r = 0.33), vitamin B6 (r = 0.31), zinc (r = 0.25), and iron (r = 0.21); and inverse correlations for saturated fatty acids (r = –0.19), carbohydrates (r = –0.22), and added sugar (r = –0.34) were observed. Correlations of nutrient intakes assessed by ASA24 with the PDQS-30D were not significantly different from those with the PDQS-24HR. Positive, statistically significant correlations between the ASA24 Healthy Eating Index 2015 and the PDQS-24HR (r = 0.61) and the PDQS-30D (r = 0.60) were also found.
The results of an initial evaluation of the PDQS-based diet quality screeners are promising. Correlations and associations between the PDQS values and nutrient intakes were of acceptable strength and in the expected directions, and the PDQS values had moderately strong correlations with the total Healthy Eating Index 2015 score. Future work should include evaluating the screeners in other population groups, including men, and piloting it across low- and middle-income countries.
Acute respiratory tract infections (ARIs) are a leading cause of ill-health and death globally. Individual or multiple micronutrients have been shown to modulate immune function and affect the risk and severity of a number of infectious diseases. We systematically reviewed the evidence on the impact of micronutrient supplements to reduce the occurrence of ARIs and shorten the duration of ARI symptoms among adults. Random effects meta-analyses were conducted to estimate the pooled effects of vitamin D, vitamin C, zinc and multiple micronutrient supplementation (MMS) on the occurrence of ARIs and the duration of ARI symptoms. Vitamin D supplementation reduced the risk of ARI (risk ratio (RR)=0.97; 95% CI 0.94 to 1.00; p=0.028) and shortened the duration of symptoms (per cent difference: −6% (95% CI −9% to −2%; p=0.003)). The RR of vitamin D to prevent ARI was farther from the null when diagnosis was based on clinical diagnosis or laboratory testing, compared with self-report and when the loading dose was <60 000 IU. Vitamin C supplementation reduced the risk of ARIs (RR=0.96; 95% CI 0.93 to 0.99; p=0.01) and shortened the duration of symptoms (per cent difference: −9% (95% CI −16% to −2%; p=0.014)). The effect of vitamin C on preventing ARI was stronger among men and in middle-income countries, compared with women and high-income countries, respectively. Zinc supplementation did not reduce the risk of ARIs but shortened the duration of symptoms substantially (per cent difference: −47% (95% CI −73% to −21%; p=0.0004)). Our synthesis of global evidence from randomised controlled trials indicates that micronutrient supplements including zinc, vitamins C and D, and multiple micronutrient supplements may be modestly effective in preventing ARIs and improving their clinical course. Further research is warranted to better understand the effectiveness that individual or multiple micronutrients have on SARS-CoV-2 infection and treatment outcomes.
BACKGROUND: While the causes of anemia at an individual level (such as certain nutritional deficiencies, infections, and genetic disorders) are well defined, there is limited understanding of the relative burden of anemia attributable to each cause within populations. OBJECTIVE: To estimate the proportion of anemia cases attributable to nutritional, infectious disease, and other risk factors among women, men, and children in six regions of Ethiopia. METHODS: A population-based cross-sectional study was conducted. Data were obtained from 2520 women of reproductive age (15-49 years), 1,044 adult men (15-49 years), and 1,528 children (6-59 months). Participants provided venous blood samples for assessment of hemoglobin concentration, ferritin, folate, vitamin B12, C-reactive protein, and malaria infection. Stool samples were collected to ascertain helminth infection status. Sociodemographic questionnaires and a 24-hour diet recall were administered. Population-weighted prevalences of anemia and risk factors were calculated. Multivariable-adjusted associations of risk factors with anemia and partial population attributable risk percentages (pPAR%) were estimated using generalized linear models. RESULTS: Anemia prevalence was 17% (95% CI: 13%, 21%) among women, 8% (6%, 12%) among men, and 22% (19%, 26%) among children. Low serum ferritin contributed to 11% (-1%, 23%) of anemia cases among women, 9% (0%, 17%) among men, and 21% (4%, 34%) among children. The proportion of anemia attributable to low serum folate was estimated at 25% (5%, 41%) among women and 29% (11%, 43%) among men. Dietary iron intake was adequate for nearly all participants, while inadequacy was common for folate and vitamin B12. Inflammation and malaria were responsible for less than one in ten anemia cases. CONCLUSIONS: Folate deficiency, iron deficiency, and inflammation appear to be important contributors to anemia in Ethiopia. Folic acid food fortification, targeted iron interventions, and strategies to reduce infections may be considered as potential public health interventions to reduce anemia in Ethiopia.
BACKGROUND: The double burdens of under- and overnutrition are changing the health of individuals and the economic and disease burdens in China. Poor diet plays an important role; however, a valid and easily operationalized metric that could capture the full range of characteristics of the diet that are relevant to both under- and overnutrition is lacking in China. OBJECTIVES: We aimed to examine the application of the Global Diet Quality Score (GDQS) to evaluate nutrient inadequacy and metabolic syndrome in different demographic groups of Chinese adults. METHODS: A total of 35,146 individuals (men 14,978, women 20,168) aged >18 y from the 2010-2012 China National Nutrition and Health Survey were included. We scored the GDQS using average intakes of 25 food groups from 3 d of 24-h dietary recalls. Double burden was defined as coexisting metabolic syndrome and nutrient inadequacy. RESULTS: Diet quality assessed by GDQS was significantly higher in urban than in rural residents (20.8 compared with 18.7), and increased with both educational level and household income (P-trends < 0.0001). A higher GDQS score was inversely associated with metabolic syndrome and nutrient inadequacy, or both (P-trends < 0.0001): multivariate adjusted ORs comparing extreme quintiles of GDQS were 0.79 (95% CI: 0.69, 0.91) for metabolic syndrome, 0.17 (95% CI: 0.14, 0.20) for nutrient inadequacy, and 0.59 (95% CI: 0.50, 0.69) for the double burden. These associations were consistent across different household income levels (P-interaction = 0.26), suggestively stronger in younger (<50 y), females, urban residents, and the more highly educated (P-interaction < 0.05) compared with their counterparts. CONCLUSIONS: A higher GDQS was inversely associated with a double burden of nutrient inadequacy and metabolic syndrome across various subgroups 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.
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 (<-5 points) had more weight (β: 0.36 kg/2 y; 95% CI: 0.06, 0.66 kg/2 y) and waist circumference gain (β: 0.71 cm/2 y; 95% CI: 0.09, 1.32 cm/2 y). 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. CONCLUSIONS: 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.
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.
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: Nutritionally inadequate diets in Ethiopia contribute to a persisting national burden of adult undernutrition, while the prevalence of noncommunicable diseases (NCDs) is rising. OBJECTIVES: To evaluate performance of a novel Global Diet Quality Score (GDQS) in capturing diet quality outcomes among Ethiopian adults. METHODS: 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. RESULTS: 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. GDQS scores were inversely associated with folate deficiency in men and women (GDQS Quintile 5 compared with Quintile 1 OR in women, 0.50; 95% CI: 0.31-0.79); inversely associated with underweight (OR, 0.63; 95% CI: 0.44-0.90), low midupper arm circumference (OR, 0.61; 95% CI: 0.45-0.84), and anemia (OR, 0.59; 95% CI: 0.38-0.91) in women; and positively associated with hypertension in men (OR: 1.77, 95% CI: 1.12-2.80). For comparison, the Minimum Dietary Diversity-Women (MDD-W) was associated more positively (P < 0.05) with overall nutrient adequacy in men and women, but also associated with low ferritin in men, overweight/obesity in women, and hypertension in men and women. In the 24HR analysis (restricted to women), the MDD-W was associated more positively (P < 0.05) with nutrient adequacy than the GDQS, but also associated with low ferritin, while the GDQS was associated inversely with anemia. CONCLUSIONS: 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.
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 < 0.05) with lower odds of low MUAC [GDQS quintile (Q) 5 compared with Q1 OR in men: 0.44, 95% CI: 0.22, 0.85; women: 0.57, 95% CI: 0.31, 1.03] and anemia (Q5/Q1 OR in men: 0.56, 95% CI: 0.32, 0.98; women: 0.60, 95% CI: 0.35, 1.01). The MDD-W correlated better with some nutrient intakes, though associated marginally with low MUAC in men (P = 0.07). The AHEI-2010 correlated better with fatty acid intakes, though associated marginally with low MUAC (P = 0.06) and anemia (P = 0.14) in women. Overweight/obesity prevalence was low, and neither the GDQS, MDD-W, nor AHEI-2010 were predictive. CONCLUSIONS: The GDQS performed comparably with the MDD-W in capturing nutrient adequacy-related outcomes in rural SSA. 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.
BACKGROUND: We have developed a simple and globally applicable tool, the Global Diet Quality Score (GDQS), to measure diet quality. OBJECTIVES: To test the utility of the GDQS, we examined the associations of the GDQS with weight change and risk of obesity in US women. METHODS: 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. RESULTS: Mean ± SD weight gain across 4-y periods was 1.68 ± 6.26 kg. A >5-point improvement in GDQS was associated with -1.13 kg (95% CI: -1.19, -0.77 kg) weight gain compared with a score change of <±2 points. For each 5-point increase, weight gain was 0.83 kg less for age <50 y compared with 0.71 kg less for age ≥50 y (P-interaction < 0.05). A >5-point score decrease was associated with 1.13 kg (95% CI: 1.04, 1.22 kg) more weight gain in women aged <50 y and 0.81 kg more (95% CI: 0.63, 0.98 kg) in women aged ≥50 y. Compared with little change in score, obesity RR was 0.77 (95% CI: 0.74, 0.81) for a >5-point increase and 1.32 (95% CI: 1.26, 1.37) for a >5-point decrease. Risk of obesity did not differ by age. Compared with other diet quality scores, the Alternate Healthy Eating Index-2010 had somewhat stronger associations than the GDQS (P < 0.05) but the GDQS had stronger associations than the Minimum Dietary Diversity for Women score (P < 0.05). CONCLUSIONS: Improvement of diet quality as measured by the GDQS was associated with less weight gain and risk of obesity in US women. The association was stronger for women aged <50 y. Associations similar in direction and magnitude were observed between the GDQS and obesity across age groups.
BACKGROUND: 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. OBJECTIVES: 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. METHODS: 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). RESULTS: We ascertained 6305 incident cases of type 2 diabetes during follow-up. We observed a lower risk of diabetes with higher GDQS; the multivariable HR comparing extreme quintiles of the GDQS was 0.83 (95% CI: 0.76, 0.91; P-trend < 0.001). The magnitude of association was similar between women aged <50 y and those aged ≥50 y. An inverse association was observed with lower intake of unhealthy components (HR comparing extreme quintiles of the unhealthy submetric: 0.76; 95% CI: 0.69, 0.84; P-trend < 0.001) but was not with the healthy submetric. The inverse association for each 1-SD increase in the GDQS (HR: 0.93; 95% CI: 0.91, 0.96) was stronger (P < 0.001) than for the MDD-W (HR: 1.00; 95% CI: 0.94, 1.04) but was slightly weaker (P = 0.03) than for the AHEI-2010 (HR: 0.91; 95% CI: 0.88, 0.94). CONCLUSIONS: A higher GDQS was inversely 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.
BACKGROUND: 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. OBJECTIVE: 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). METHODS: 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. RESULTS: 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 0.38, P < 0.05) and was inversely correlated with the intake of added sugar (rho = -0.37 and -0.38, P < 0.05) using both instruments, and with total fat, SFA, and MUFA only with 24-h recall data (rho = -0.06 to -0.16, P < 0.05). The GDQS was inversely associated with serum ferritin, BMI, waist circumference, and serum total and LDL cholesterol using FFQ data (P < 0.05), and was positively associated with serum folate using 24-h recall data (P < 0.05). Similar correlations and associations were observed with the MDD-W (only with micronutrients) and the AHEI-2010 (only with chronic disease-related nutrients and health markers). CONCLUSIONS: In comparison to other diet metrics, the GDQS can capture both dimensions of nutrient adequacy and health markers related to the risk of chronic disease. The performance of the GDQS was satisfactory with either 24-h recall or FFQ.