Discovery and validation of plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance and diabetes progression or regression among Puerto Rican adults.

AIMS/HYPOTHESIS: Many studies have examined the relationship between plasma metabolites and type 2 diabetes progression, but few have explored saliva and multi-fluid metabolites. METHODS: We used LC/MS to measure plasma (n=1051) and saliva (n=635) metabolites among Puerto Rican adults from the San Juan Overweight Adults Longitudinal Study. We used elastic net regression to identify plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting baseline HOMA-IR in a training set (n=509) and validated these scores in a testing set (n=340). We used multivariable Cox proportional hazards models to estimate HRs for the association of baseline metabolomic scores predicting insulin resistance with incident type 2 diabetes (n=54) and prediabetes (characterised by impaired glucose tolerance, impaired fasting glucose and/or high HbA1c) (n=130) at 3 years, along with regression from prediabetes to normoglycaemia (n=122), adjusting for traditional diabetes-related risk factors. RESULTS: Plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance included highly weighted metabolites from fructose, tyrosine, lipid and amino acid metabolism. Each SD increase in the plasma (HR 1.99 [95% CI 1.18, 3.38]; p=0.01) and multi-fluid (1.80 [1.06, 3.07]; p=0.03) metabolomic scores was associated with higher risk of type 2 diabetes. The saliva metabolomic score was associated with incident prediabetes (1.48 [1.17, 1.86]; p=0.001). All three metabolomic scores were significantly associated with lower likelihood of regressing from prediabetes to normoglycaemia in models adjusting for adiposity (HRs 0.72 for plasma, 0.78 for saliva and 0.72 for multi-fluid), but associations were attenuated when adjusting for lipid and glycaemic measures. CONCLUSIONS/INTERPRETATION: The plasma metabolomic score predicting insulin resistance was more strongly associated with incident type 2 diabetes than the saliva metabolomic score. Only the saliva metabolomic score was associated with incident prediabetes.

Acylcarnitines are associated with lower depressive symptomatology in a mainland puerto rican cohort.

INTRODUCTION: Recent studies have implicated acetyl-L-carnitine as well as other acylcarnitines in depression. To our knowledge, no untargeted metabolomics studies have been conducted among US mainland Puerto Ricans. OBJECTIVES: We conducted untargeted metabolomic profiling on plasma from 736 participants of the Boston Puerto Rican Health Study. METHODS: Using Weighted Gene Co-expression Network Analysis, we identified metabolite modules associated with depressive symptomatology, assessed via the Center for Epidemiologic Studies Depression scale. We identified metabolites contributing to these modules and assessed the relationship between these metabolites and depressive symptomatology. RESULTS: 621 annotated metabolites clustered into eight metabolite modules, of which one, the acylcarnitine module, was significantly inversely associated with depressive symptomatology (ß = - 27.7 (95% CI (- 54.5-0.8); p = 0.043). Several metabolite hub features in the acylcarnitine module were significantly associated with depressive symptomatology, after correction for multiple comparisons. CONCLUSIONS: In this untargeted plasma metabolomics study among mainland Puerto Rican older adults, acylcarnitines, as a metabolite module were inversely associated with depressive symptomatology.

Metabolite Profiles of Plant-Based Diets and Cardiometabolic Risk in the Mediators of Atherosclerosis in South Asians Living in America Study.

BACKGROUND: Healthy plant-based diets have been associated with lower risk of type 2 diabetes (T2D). Metabolomics can be leveraged to identify potential pathways through which diet influences disease risk. OBJECTIVES: This study aimed to identify profiles of serum metabolites reflective of plant-based diets of varying quality and examine associations with cardiometabolic risk and T2D. METHODS: We included data from 687 participants of the Mediators of Atherosclerosis in South Asians Living in America (MASALA) cohort. An overall plant-based diet index (PDI), healthy PDI (hPDI), and unhealthy PDI (uPDI) were estimated from food frequency questionnaires. Serum metabolites were assayed using ultraperformance liquid chromatography mass spectrometry. Elastic net regression was used to identify sets of metabolites predictive of each diet index, and metabolite profile scores were calculated as the weighted sum of the selected metabolites. Cross-sectional associations between metabolite profile scores and cardiometabolic measures and prospective associations with incident T2D were evaluated with multivariable-adjusted linear and logistic regressions. RESULTS: Metabolite profiles for PDI, hPDI, and uPDI consisted of n = 51, 55, and 45 metabolites, respectively. Metabolites strongly positively correlated with diet indices included phosphatidylcholine (16:0/18:3) for PDI, phosphatidylethanolamine (20:1/20:4) and pantothenate for hPDI, and lysophosphatidylglycerol (18:2/0:0), proline, and lauric acid for uPDI. Higher metabolite profile scores for PDI and hPDI were associated with lower glycemia and lipids measures, whereas a higher uPDI metabolite score was associated with higher triglycerides and lower low density lipoprotein cholesterol and high density lipoprotein cholesterol. A higher metabolite score for hPDI was additionally associated with lower adiposity measures, higher liver fat attenuation, higher adiponectin, lower odds of overweight (odds ratio [OR]: 0.64; 95% confidence interval [CI]: 0.51, 0.81) and obesity (OR: 0.59; 95% CI: 0.48, 0.74), and lower odds of incident T2D (OR: 0.66; 95% CI: 0.45, 0.97). CONCLUSIONS: Metabolite profiles of different plant-based diets were identified. Metabolite profiles of overall and healthy plant-based diets were associated with favorable cardiometabolic risk profiles.

The Intersection Between COVID-19, Cardiovascular Disease, and Diet: a Review.

PURPOSE OF REVIEW: Cardiovascular disease (CVD) is one of the top comorbidities associated with COVID-19-both pre- and post-infection. This review examines the relationships between COVID-19 infection and cardiovascular health, with a specific focus on diet as an important modifiable risk factor. RECENT FINDINGS: Pandemic era studies of individuals battling and recovering from COVID-19 infection suggest a strong link between metabolic diseases, such as CVD, and SARS-CoV-2 infection susceptibility and severity. Other studies also demonstrate how COVID-19 lockdown policies and quarantine recommendations led to drastic lifestyle changes associated with increased CVD risk, such as reduced physical activity and lower diet quality. At the same time, new research is emerging that plant-based diets, which have previously been associated with lower CVD risk, may lower COVID-19 infection rates and severity of symptoms. Diet, COVID-19, and CVD intersect through complex biological mechanisms and related behavioral factors evidenced by clinical trials and epidemiological studies. Diet may be a critical tool for modifying risk of communicable and non-communicable conditions in the post-pandemic world.

Stability and reproducibility of proteomic profiles in epidemiological studies: comparing the Olink and SOMAscan platforms.

Limited data exist on the performance of high-throughput proteomics profiling in epidemiological settings, including the impact of specimen collection and within-person variability over time. Thus, the Olink (972 proteins) and SOMAscan7Kv4.1 (7322 proteoforms of 6596 proteins) assays were utilized to measure protein concentrations in archived plasma samples from the Nurses' Health Studies and Health Professionals Follow-Up Study. Spearman's correlation coefficients (r) and intraclass correlation coefficients (ICCs) were used to assess agreement between (1) 42 triplicate samples processed immediately, 24-h or 48-h after blood collection from 14 participants; and (2) 80 plasma samples from 40 participants collected 1-year apart. When comparing samples processed immediately, 24-h, and 48-h later, 55% of assays had an ICC/r ≥ 0.75 and 87% had an ICC/r ≥ 0.40 in Olink compared to 44% with an ICC/r ≥ 0.75 and 72% with an ICC/r ≥ 0.40 in SOMAscan7K. For both platforms, >90% of the assays were stable (ICC/r ≥ 0.40) in samples collected 1-year apart. Among 817 proteins measured with both platforms, Spearman's correlations were high (r > 0.75) for 14.7% and poor (r < 0.40) for 44.8% of proteins. High-throughput proteomics profiling demonstrated reproducibility in archived plasma samples and stability after delayed processing in epidemiological studies, yet correlations between proteins measured with the Olink and SOMAscan7K platforms were highly variable.

Plasma metabolite profiles related to plant-based diets and the risk of type 2 diabetes.

AIMS/HYPOTHESIS: Plant-based diets, especially when rich in healthy plant foods, have been associated with a lower risk of type 2 diabetes. However, whether plasma metabolite profiles related to plant-based diets reflect this association was unknown. The aim of this study was to identify the plasma metabolite profiles related to plant-based diets, and to evaluate the associations between the identified metabolite profiles and the risk of type 2 diabetes. METHODS: Within three prospective cohorts (Nurses' Health Study, Nurses' Health Study II and Health Professionals Follow-up Study), we measured plasma metabolites from 10,684 participants using high-throughput LC MS. Adherence to plant-based diets was assessed by three indices derived from the food frequency questionnaire: an overall Plant-based Diet Index (PDI), a Healthy Plant-based Diet Index (hPDI), and an Unhealthy Plant-based Diet Index (uPDI). Multi-metabolite profiles related to plant-based diet were identified using elastic net regression with a training/testing approach. The prospective associations between metabolite profiles and incident type 2 diabetes were evaluated using multivariable Cox proportional hazards regression. Metabolites potentially mediating the association between plant-based diets and type 2 diabetes risk were further identified. RESULTS: We identified multi-metabolite profiles comprising 55 metabolites for PDI, 93 metabolites for hPDI and 75 metabolites for uPDI. Metabolite profile scores based on the identified metabolite profiles were correlated with the corresponding diet index (Pearson r = 0.33-0.35 for PDI, 0.41-0.45 for hPDI, and 0.37-0.38 for uPDI, all p<0.001). Metabolite profile scores of PDI (HR per 1 SD higher = 0.81 [95% CI 0.75, 0.88]) and hPDI (HR per 1 SD higher = 0.77 [95% CI 0.71, 0.84]) showed an inverse association with incident type 2 diabetes, whereas the metabolite profile score for uPDI was not associated with the risk. Mutual adjustment for metabolites selected in the metabolite profiles, including trigonelline, hippurate, isoleucine and a subset of triacylglycerols, attenuated the associations of diet indices PDI and hPDI with lower type 2 diabetes risk. The explainable proportion of PDI/hPDI-related diabetes risk by these metabolites ranged between 8.5% and 37.2% (all p<0.05). CONCLUSIONS/INTERPRETATION: Plasma metabolite profiles related to plant-based diets, especially a healthy plant-based diet, were associated with a lower risk of type 2 diabetes among a generally healthy population. Our findings support the beneficial role of healthy plant-based diets in diabetes prevention and provide new insights for future investigation.

Fruit and Vegetable Intake and Mortality: Results From 2 Prospective Cohort Studies of US Men and Women and a Meta-Analysis of 26 Cohort Studies.

BACKGROUND: The optimal intake levels of fruit and vegetables for maintaining long-term health are uncertain. METHODS: We followed 66 719 women from the Nurses' Health Study (1984-2014) and 42 016 men from the Health Professionals Follow-up Study (1986-2014) who were free from cardiovascular disease (CVD), cancer, and diabetes at baseline. Diet was assessed using a validated semiquantitative food frequency questionnaire at baseline and updated every 2 to 4 years. We also conducted a dose-response meta-analysis, including results from our 2 cohorts and 24 other prospective cohort studies. RESULTS: We documented 33 898 deaths during the follow-up. After adjustment for known and suspected confounding variables and risk factors, we observed nonlinear inverse associations of fruit and vegetable intake with total mortality and cause-specific mortality attributable to cancer, CVD, and respiratory disease (all Pnonlinear<0.001). Intake of ≈5 servings per day of fruit and vegetables, or 2 servings of fruit and 3 servings of vegetables, was associated with the lowest mortality, and above that level, higher intake was not associated with additional risk reduction. In comparison with the reference level (2 servings/d), daily intake of 5 servings of fruit and vegetables was associated with hazard ratios (95% CI) of 0.87 (0.85-0.90) for total mortality, 0.88 (0.83-0.94) for CVD mortality, 0.90 (0.86-0.95) for cancer mortality, and 0.65 (0.59-0.72) for respiratory disease mortality. The dose-response meta-analysis that included 145 015 deaths accrued in 1 892 885 participants yielded similar results (summary risk ratio of mortality for 5 servings/d=0.87 [95% CI, 0.85-0.88]; Pnonlinear<0.001). Higher intakes of most subgroups of fruits and vegetables were associated with lower mortality, with the exception of starchy vegetables such as peas and corn. Intakes of fruit juices and potatoes were not associated with total and cause-specific mortality. CONCLUSIONS: Higher intakes of fruit and vegetables were associated with lower mortality; the risk reduction plateaued at ≈5 servings of fruit and vegetables per day. These findings support current dietary recommendations to increase intake of fruits and vegetables, but not fruit juices and potatoes.

Diet quality and risk and severity of COVID-19: a prospective cohort study.

OBJECTIVE: Poor metabolic health and unhealthy lifestyle factors have been associated with risk and severity of COVID-19, but data for diet are lacking. We aimed to investigate the association of diet quality with risk and severity of COVID-19 and its interaction with socioeconomic deprivation. DESIGN: We used data from 592 571 participants of the smartphone-based COVID-19 Symptom Study. Diet information was collected for the prepandemic period using a short food frequency questionnaire, and diet quality was assessed using a healthful Plant-Based Diet Score, which emphasises healthy plant foods such as fruits or vegetables. Multivariable Cox models were fitted to calculate HRs and 95% CIs for COVID-19 risk and severity defined using a validated symptom-based algorithm or hospitalisation with oxygen support, respectively. RESULTS: Over 3 886 274 person-months of follow-up, 31 815 COVID-19 cases were documented. Compared with individuals in the lowest quartile of the diet score, high diet quality was associated with lower risk of COVID-19 (HR 0.91; 95% CI 0.88 to 0.94) and severe COVID-19 (HR 0.59; 95% CI 0.47 to 0.74). The joint association of low diet quality and increased deprivation on COVID-19 risk was higher than the sum of the risk associated with each factor alone (Pinteraction=0.005). The corresponding absolute excess rate per 10 000 person/months for lowest vs highest quartile of diet score was 22.5 (95% CI 18.8 to 26.3) among persons living in areas with low deprivation and 40.8 (95% CI 31.7 to 49.8) among persons living in areas with high deprivation. CONCLUSIONS: A diet characterised by healthy plant-based foods was associated with lower risk and severity of COVID-19. This association may be particularly evident among individuals living in areas with higher socioeconomic deprivation.

Metabolite patterns link diet, obesity, and type 2 diabetes in a Hispanic population.

INTRODUCTION: Obesity is a precursor of type 2 diabetes (T2D). OBJECTIVES: Our aim was to identify metabolic signatures of T2D and dietary factors unique to obesity. METHODS: We examined a subsample of the Boston Puerto Rican Health Study (BPRHS) population with a high prevalence of obesity and T2D at baseline (n = 806) and participants (without T2D at baseline) at 5-year follow-up (n = 412). We determined differences in metabolite profiles between T2D and non-T2D participants of the whole sample and according to abdominal obesity status. Enrichment analysis was performed to identify metabolic pathways that were over-represented by metabolites that differed between T2D and non-T2D participants. T2D-associated metabolites unique to obesity were examined for correlation with dietary food groups to understand metabolic links between dietary intake and T2D risk. False Discovery Rate method was used to correct for multiple testing. RESULTS: Of 526 targeted metabolites, 179 differed between T2D and non-T2D in the whole sample, 64 in non-obese participants and 120 unique to participants with abdominal obesity. Twenty-four of 120 metabolites were replicated and were associated with T2D incidence at 5-year follow-up. Enrichment analysis pointed to three metabolic pathways that were overrepresented in obesity-associated T2D: phosphatidylethanolamine (PE), long-chain fatty acids, and glutamate metabolism. Elevated intakes of three food groups, energy-dense takeout food, dairy intake and sugar-sweetened beverages, associated with 13 metabolites represented by the three pathways. CONCLUSION: Metabolic signatures of lipid and glutamate metabolism link obesity to T2D, in parallel with increased intake of dairy and sugar-sweetened beverages, thereby providing insight into the relationship between dietary habits and T2D risk.

Performance of the Global Diet Quality Score with Nutrition and Health Outcomes in Mexico with 24-h Recall and FFQ Data.

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.

Exploration of Machine Learning and Statistical Techniques in Development of a Low-Cost Screening Method Featuring the Global Diet Quality Score for Detecting Prediabetes in Rural India.

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.

Validation of Global Diet Quality Score Among Nonpregnant Women of Reproductive Age in India: Findings from the Andhra Pradesh Children and Parents Study (APCAPS) and the Indian Migration Study (IMS).

BACKGROUND: In India, there is a need to monitor population-level trends in changes in diet quality in relation to both undernutrition and noncommunicable diseases. OBJECTIVES: We conducted a study to validate a novel diet quality score in southern India. METHODS: 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). RESULTS: The mean GDQS was 23 points (SD, 3.6; maximum, 46.5). In energy-adjusted models, positive associations were found between the overall GDQS and GDQS+ and intakes of calcium, fiber, folate, iron, monounsaturated fatty acid (MUFA), protein, polyunsaturated fatty acid (PUFA), saturated fatty acid (SFA), total fat, and zinc (ρ = 0.12-0.39; P < 0.001). Quintile analyses showed that the GDQS was associated with better nutrient adequacy. At the same time, the GDQS was associated with higher TC, lower HDL, and higher BMI. We found no associations between the GDQS and hypertension. CONCLUSIONS: The GDQS was a useful tool for reflecting overall nutrient adequacy and some lipid measures. Future studies are needed to refine the GDQS for populations who consume large amounts of unhealthy foods, like refined grains, along with healthy foods included in the GDQS.

Higher Global Diet Quality Score Is Associated with Less 4-Year Weight Gain in US Women.

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.

Changes in the Global Diet Quality Score, Weight, and Waist Circumference in Mexican Women.

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 (ß: -0.81 kg/2 y; 95% CI: -1.11, -0.51 kg/2 y) and waist circumference gain (ß: -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 (ß: 0.36 kg/2 y; 95% CI: 0.06, 0.66 kg/2 y) and waist circumference gain (ß: 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.

Higher Global Diet Quality Score Is Inversely Associated with Risk of Type 2 Diabetes in US Women.

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.

Application of the Global Diet Quality Score in Chinese Adults to Evaluate the Double Burden of Nutrient Inadequacy and Metabolic Syndrome.

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.

There's an App for That: Development of an Application to Operationalize the Global Diet Quality Score.

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 < 0.001 for linear trend for both models) and of the same clinical order of magnitude for waist circumference (-0.52 and -0.44, respectively, P < 0.001 for linear trend for both models). CONCLUSION: The operationalized GDQS cutoffs did not change the performance of the GDQS and therefore are recommended for use to collect GDQS data in the future.

The Global Diet Quality Score Is Inversely Associated with Nutrient Inadequacy, Low Midupper Arm Circumference, and Anemia in Rural Adults in Ten Sub-Saharan African Countries.

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.

The Global Diet Quality Score is Associated with Higher Nutrient Adequacy, Midupper Arm Circumference, Venous Hemoglobin, and Serum Folate Among Urban and Rural Ethiopian Adults.

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.

Walnut Consumption, Plasma Metabolomics, and Risk of Type 2 Diabetes and Cardiovascular Disease.

BACKGROUND: Walnut consumption is associated with lower risk of type 2 diabetes (T2D) and cardiovascular disease (CVD). However, it is unknown whether plasma metabolites related to walnut consumption are also associated with lower risk of cardiometabolic diseases. OBJECTIVES: The study aimed to identify plasma metabolites associated with walnut consumption and evaluate the prospective associations between the identified profile and risk of T2D and CVD. METHODS: The discovery population included 1833 participants at high cardiovascular risk from the PREvención con DIeta MEDiterránea (PREDIMED) study with available metabolomics data at baseline. The study population included 57% women (baseline mean BMI (in kg/m2): 29.9; mean age: 67 y). A total of 1522 participants also had available metabolomics data at year 1 and were used as the internal validation population. Plasma metabolomics analyses were performed using LC-MS. Cross-sectional associations between 385 known metabolites and walnut consumption were assessed using elastic net continuous regression analysis. A 10-cross-validation (CV) procedure was used, and Pearson correlation coefficients were assessed between metabolite weighted models and self-reported walnut consumption in each pair of training-validation data sets within the discovery population. We further estimated the prospective associations between the identified metabolite profile and incident T2D and CVD using multivariable Cox regression models. RESULTS: A total of 19 metabolites were significantly associated with walnut consumption, including lipids, purines, acylcarnitines, and amino acids. Ten-CV Pearson correlation coefficients between self-reported walnut consumption and the plasma metabolite profile were 0.16 (95% CI: 0.11, 0.20) in the discovery population and 0.15 (95% CI: 0.10, 0.20) in the validation population. The metabolite profile was inversely associated with T2D incidence (HR per 1 SD: 0.83; 95% CI: 0.71, 0.97; P = 0.02). For CVD incidence, the HR per 1-SD was 0.71 (95% CI: 0.60, 0.85; P < 0.001). CONCLUSIONS: A metabolite profile including 19 metabolites was associated with walnut consumption and with a lower risk of incident T2D and CVD in a Mediterranean population at high cardiovascular risk.