Relationship between dietary inflammatory index, plant-based dietary index, and bacterial vaginosis: A case-control study.

OBJECTIVE: Bacterial vaginosis (BV) is a common inflammatory condition affecting the vaginal microbiome. In the present study we aimed to explore the relationship between dietary inflammatory index, plant-based dietary index, and BV. METHODS: In this case-control study, 143 individuals with BV and 151 healthy participants aged 15-45 years were included. Bacterial vaginosis diagnosis was based on the Amsel criteria by a gynecologist. Participants' dietary intakes over the past year were assessed using a 168-item food frequency questionnaire. Logistic regression models were employed to analyze the association between dietary inflammatory index, plant-based dietary index, and BV odds. RESULTS: Our study revealed that elevated dietary inflammatory index scores were strongly associated with higher BV odds in the crude model (odds ratio [OR]: 2.88, 95% confidence interval [CI]: 1.57-5.30, P value <0.001), and even after accounting for potential confounding factors (adjusted OR: 3.52, 95% CI: 1.66-7.46, P value = 0.001). While no significant relationship was observed between total plant-based dietary index and healthy plant-based dietary index scores with BV odds, a clear positive association existed between unhealthy plant-based dietary index and the odds of BV (aOR: 2.13, 95% CI: 1.09-4.15, P value = 0.018). CONCLUSION: A positive correlation may exist between unhealthy plant-based dietary index and the likelihood of BV. Furthermore, the dietary inflammatory index may remain linked to increased BV odds.

Association between plant-based dietary index and disease severity in patients with ulcerative colitis: a cross-sectional study.

BACKGROUND: Plant foods are naturally rich in anti-inflammatory nutrients. In this cross-sectional study, we assessed the association between the plant-based dietary index (PDI) and Mayo score in patients with ulcerative colitis (UC). METHODS: This analytical cross-sectional study included 158 patients with UC. The Mayo score was used to determine disease severity. An expert nutritionist performed the anthropometric assessments. A 168-item quantitative food frequency questionnaire (FFQ) was used to calculate the PDI, healthy PDI (hPDI), and unhealthy PDI (uPDI). To assess the association between the total Mayo score (as a dependent factor) and different indices of PDI (as an independent variable), the linear regression model was used. RESULTS: The mean age of participants was 42.52 ± 12.61 years. There were significant differences in the total Mayo score between tertiles of PDI score (p = 0.02). The result of linear regression showed that in the unadjusted model, compared with the patients in the first tertile of PDI, the patients in the second (-0.21 (-1.89, -0.17)), and third tertile (-0.21 (-1.95, -0.16)) had significantly lower total mayo scores. The inverse association remained significant after adjusting for covariates. However, uPDI and hPDI tertiles were not significantly associated with total Mayo scores in the adjusted and unadjusted models. CONCLUSION: higher PDI was significantly associated with higher UC severity. However, considering the limitations of the study, more cohort studies are needed to confirm these results.

Associations of five dietary indices with metabolic dysfunction-associated steatotic liver disease and liver fibrosis among the United States population.

Background and aims: The role of dietary factors in metabolic dysfunction-associated steatotic liver disease (MASLD)-which represents a new definition of liver steatosis and metabolic dysfunction- remains unclear. This study aimed to explore the relationships between dietary indices and MASLD. Methods: We analyzed data from the United States National Health and Nutrition Examination Survey (NHANES) 2017-2020 cycle, including 4,690 participants with complete vibration-controlled transient elastography (VCTE) data. Multivariate logistic regression models adjusted for covariates were used to assess the association between dietary indices, MASLD, and MASLD-associated liver fibrosis (MASLD-LF). Restricted cubic spline (RCS) models and subgroup analyses were also performed. Results: The Alternative Healthy Eating Index (AHEI), Healthy Eating Index-2020 (HEI-2020), Dietary Approaches to Stop Hypertension Index (DASHI), and Mediterranean Diet Index (MEDI) were found to be negatively associated with MASLD risk, while the Dietary Inflammatory Index (DII) had a positive association. The highest quartile of MEDI was linked to a 44% reduction in MASLD risk [Q1 vs. Q4 odds ratio (OR): 0.56; 95% confidence interval (CI): 0.34-0.94, P for trend: 0.012]. DASHI was uniquely associated with a reduced risk of MASLD-LF (continuous OR: 0.79; 95% CI: 0.64-0.97; p for trend: 0.003). Our RCS curves indicated a nonlinear association with DASHI-MASLD (p-overall: 0.0001, p-nonlinear: 0.0066). Subgroup analyses showed robust associations among the non-Hispanic White and highly educated populations. Conclusion: Specific dietary patterns were associated with reduced risks of MASLD and MASLD-LF. The DASHI, in particular, showed a significant protective effect against MASLD-LF. These findings suggest potential dietary interventions for managing MASLD and MASLD-LF, although large-scale randomized controlled trials are warranted to validate these findings.

Dietaryindex: a user-friendly and versatile R package for standardizing dietary pattern analysis in epidemiological and clinical studies.

BACKGROUND: Few standardized and open-source tools exist for calculating multiple dietary pattern indexes from dietary intake data in epidemiological and clinical studies. OBJECTIVES: The primary aim is to develop and validate dietaryindex, a user-friendly and versatile R package that standardizes the calculation of dietary indexes. METHODS: Dietaryindex can calculate multiple dietary indexes of high interest in research, including the Healthy Eating Index (HEI)-2020, the Alternative HEI 2010, the Dietary Approaches to Stop Hypertension Index, the Alternate Mediterranean Diet Score, the Dietary Inflammatory Index, the American Cancer Society 2020 dietary index, and the Planetary Health Diet Index from the EAT-Lancet Commission. The package includes generic dietary index calculation functions that accept any dietary assessment with preprocessed serving sizes of food groups and nutrients as defined by the research group that developed each index. For ease of use and to eliminate any need for data preprocessing, dietaryindex also offers 1-step functions that directly reference common datasets and tools, including the National Health and Nutrition Examination Survey (NHANES), the Automated Self-Administered 24-h Dietary Assessment Tool (ASA24), the Diet History Questionnaire III (DHQ3), and the Block Food Frequency Questionnaire. At least 2 independent researchers validated the serving size definitions and scoring algorithms of dietaryindex. RESULTS: In our validation process, dietaryindex demonstrated full accuracy (100%) in all generic functions with 2-decimal rounding precision when compared with hand-calculated results. Similarly, using NHANES 2017-2018 data and ASA24 and DHQ3 example data, the HEI-2015 outputs from dietaryindex aligned (99.95%-100%) with results using the Statistical Analysis System codes from the National Cancer Institute. CONCLUSIONS: Dietaryindex is a user-friendly, versatile, and validated informatics tool for standardized dietary index calculations. We have open-sourced all validation files and codes with detailed tutorials on GitHub (https://github.com/jamesjiadazhan/dietaryindex).

The association of dietary indices for hyperinsulinemia and insulin resistance with the risk of metabolic syndrome: a population-based cross-sectional study.

We aimed to investigate the association between an empirical dietary index for hyperinsulinemia (EDIH), empirical dietary index for insulin resistance (EDIR), and MetS and its components in an adult Iranian population. In this cross-sectional study, a total of 6482 participants aged 35-65 years were recruited as part of the MASHAD cohort study. Dietary intakes were assessed using a validated food frequency questionnaire (FFQ). The International Diabetes Federation (IDF) criteria were used to define MetS. Multivariable logistic regression models were applied to determine the association between EDIH, EDIR, and MetS and its components. The mean age and BMI of participants were 48.44±8.20 years, and 27.98±4.73 kg/m2, respectively. Around 59% of the population was female. Of the total population, 35.4% had MetS. According to the full-adjusted model, there was no significant association between higher quartiles of EDIH and EDIR and odds of MetS (Q4 EDIH; OR (95%CI):0.93 (0.74-1.18), Q4 EDIR; OR (95%CI):1.14 (0.92-1.40). Regarding MetS components, EDIR was associated with increased odds of hypertension and diabetes (Q4 EDIR; OR (95%CI):1.22 (1.04-1.44) and 1.22 (1.01-1.47), respectively). EDIH was also associated with decreased odds of hypertriglyceridemia (Q4 EDIH; OR (95%CI): 0.72 (0.60-0.87)). This study showed no significant association between hyperinsulinemia and insulin resistance potential of diet and odds of MetS among Iranian adults. However, EDIR was significantly associated with increased odds of hypertension and diabetes as MetS components.

Development and evaluation of an index assessing adherence to the Norwegian food-based dietary guidelines: the Norwegian Dietary Guideline Index (NDGI).

BACKGROUND: Monitoring adherence to the Norwegian food-based dietary guidelines (FBDGs) could provide valuable insight into current and future diet-related health risks. This study aimed to develop and evaluate an index measuring adherence to the Norwegian FBDGs to be used as a compact tool in nutrition surveillance suitable for inclusion in large public health surveys. METHODS: The Norwegian Dietary Guideline Index (NDGI) was designed to reflect adherence to the Norwegian FBDGs on a scale from 0-100, with a higher score indicating better adherence. Dietary intakes were assessed through 19 questions, reflecting 15 dietary components covered by the Norwegian FBDGs. The NDGI was applied and evaluated using nationally representative dietary data from the cross-sectional web-based Norwegian Public Health Survey which included 8,558 adults.​ RESULTS: The population-weighted NDGI score followed a nearly normal distribution with a mean of 65 (SD 11) and range 21-99. Mean scores varied with background factors known to be associated with adherence to a healthy diet; women scored higher than men (67 vs. 64) and the score increased with age, with higher educational attainment (high 69 vs. low 64) and with better self-perceived household economy (good 67 vs. restricted 62). The NDGI captured a variety of dietary patterns that contributed to a healthy diet consistent with the FBDGs. CONCLUSION: The NDGI serve as a compact tool to assess and monitor adherence to the Norwegian FBDGs, to identify target groups for interventions, and to inform priorities in public health policies.​ The tool is flexible to adjustments and may be adaptable to use in other countries or settings with similar dietary guidelines.

The association between healthy and unhealthy dietary indices with prostate cancer risk: a case-control study.

INTRODUCTION: According to our knowledge, the relationship between dietary patterns such as pro-healthy, pro-vegetarian, and non-healthy dietary patterns and prostate cancer risk has not been clearly investigated in Iranian men. Therefore, we aimed to investigate the relationship between adherence to a pro-healthy (PHDI), pro-vegetarian (PDP), and non-healthy dietary indices (NHDI) and the risk of prostate cancer. METHOD: In this matched case-control study, 125 participants (62 cases and 63 hospital-based controls) were enrolled from April to September 2015. Participants' dietary intakes were evaluated using a valid and reliable 160-item semi-quantitative food frequency questionnaire. Dietary indices calculated based on previous studies. The relationship between dietary indices (PHDI, NHDI and PDP) and prostate cancer risk was assessed using binary regression models. RESULTS: According to adjusted model, significant negative correlations were found between PHDI and PDP with prostate cancer (PHDI: OR = 0.31; 95% CI; 0.11-0.85; P = 0.023 - PDP: OR = 0.34; 95% CI; 0.15-0.75; P = 0.008). Also, a positive association was seen between NHDI and prostate cancer (OR = 3.01; 95% CI; 1.20-7.57; P = 0.019). CONCLUSION: We found that adherence to healthy dietary indices which includes high amounts of fruits, vegetables, and whole grains reduces the risk of prostate cancer. While adherence to a dietary pattern high in red and processed meat, refined grains, and sweetened beverages increases the risk of prostate cancer.

The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota.

The aim of the study was to develop and evaluate a novel dietary index for gut microbiota (DI-GM) that captures dietary composition related to gut microbiota profiles. We conducted a literature review of longitudinal studies on the association of diet with gut microbiota in adult populations and extracted those dietary components with evidence of beneficial or unfavorable effects. Dietary recall data from the National Health and Nutrition Examination Survey (NHANES, 2005-2010, n = 3812) were used to compute the DI-GM, and associations with biomarkers of gut microbiota diversity (urinary enterodiol and enterolactone) were examined using linear regression. From a review of 106 articles, 14 foods or nutrients were identified as components of the DI-GM, including fermented dairy, chickpeas, soybean, whole grains, fiber, cranberries, avocados, broccoli, coffee, and green tea as beneficial components, and red meat, processed meat, refined grains, and high-fat diet (≥40% of energy from fat) as unfavorable components. Each component was scored 0 or 1 based on sex-specific median intakes, and scores were summed to develop the overall DI-GM score. In the NHANES, DI-GM scores ranged from 0-13 with a mean of 4.8 (SE = 0.04). Positive associations between DI-GM and urinary enterodiol and enterolactone were observed. The association of the novel DI-GM with markers of gut microbiota diversity demonstrates the potential utility of this index for gut health-related studies.

[Application of Delphi method in the revision of dietary quality index in the elderly].

OBJECTIVE: To revise the dietary evaluation method of the elderly, and scientifically evaluate the dietary quality. METHODS: Delphi method was used to revise a diet quality evaluation method for the elderly according to expert consultation and statistical analysis. The recommended recipes in The Dietary Guidelines for Chinese Residents(2016) were selected for preliminary verification. RESULTS: Two rounds of expert consultation were conducted, 25 experts in the industry were invited. The withdraw rate of two rounds were 100% and 84%, respectively. The authoritative coefficient were 0.82 and 0.80, the degree of familiarity was 0.92, and the basis for determination were 0.73 and 0.70, respectively. The coordination coefficient W value were 0.095 and 0.098 respectively. CONCLUSION: Delphi method had some advantages in the revision of dietary index for the elderly. Dietary quality index had some practicability, but it still needs further verification and improvement.

Protein-enriched and anti-inflammatory dietary patterns, healthy lifestyle index and depressive symptoms: A cross-sectional study of 287,945 adults in China.

OBJECTIVES: Depressive symptoms have a considerable negative impact on mental health. This study aimed to understand the relationship between the protein-enriched and anti-inflammatory dietary index scores, modified healthy lifestyle index scores (Modified HLIS), and depressive symptoms. METHODS: This study used convenience sampling to conduct a single-center cross-sectional survey. From January 1, 2015 to December 31, 2020, a total of 287,945 Chinese adults from a health management center of a general hospital completed an online self-reported health questionnaire, which included demographic characteristics, the Dietary Diversity Scale, the Modified Healthy Lifestyle Index Scores and the Patient Health Questionnaire-9. RESULTS: The higher anti-inflammatory dietary index scores (POR = 0.87; 95 % CI: 0.86-0.87; p < 0.001), moderate modified healthy lifestyle index scores (POR = 0.76; 95 % CI: 0.75-0.78; p < 0.001) and sufficient modified healthy lifestyle index scores (POR = 0.53; 95 % CI: 0.52-0.54; p < 0.001) were negatively associated with depressive symptoms, while the higher protein-enriched dietary index scores (POR = 1.01; 95 % CI: 1.01-1.02; p < 0.001) was positively correlated with depressive symptoms. CONCLUSIONS: This study demonstrated that protein-enriched and anti-inflammatory dietary index scores, and multiple healthy lifestyles are associated depressive symptoms in adults.

The impact of diet quality on cognitive ability of Chinese older adults: evidence from the China Health and Nutrition Survey (CHNS).

BACKGROUND: Numerous studies have demonstrated a positive correlation between diet quality and cognitive performance, indicating that improving diet quality may be beneficial in preventing cognitive decline in older adults. However, few study has investigated the causal relationship between diet quality and cognitive performance. The purpose of this study is to evaluate the causal effects of diet quality on cognitive performance in Chinese adults aged 55 years and older. Particularly, we utilize the Chinese Diet Quality Index (CHEI), a dietary assessment tool tailored for Chinese populations, as a proxy for older adults' diet quality. METHODS: Data were obtained from the China Health and Nutrition Survey (CHNS) ([Formula: see text], [Formula: see text]55 years old) conducted in 2004 and 2006. Cognitive function was tested by a subset of items from the Telephone Interview for Cognitive Status-Modified (TICS-m). Data on dietary intake was retrieved from three consecutive 24 hour recalls by participants and its quality was assessed by the 17-items Chinese Healthy Eating Index (CHEI). An Instrumental Variable technique was used to deal with the potential endogeneity of dietary quality. The instrumental variable used in our study is the community mean of CHEI. RESULTS: After adjusting for socio-demographic factors (age, gender, education, per capita household income), lifestyle habits (smoking, alcohol consumption, physical activity, BMI), and chronic diseases (hypertension, diabetes), our findings revealed that improving diet quality had a significant positive effect on cognitive performance ([Formula: see text]), particularly in females aged 55-65 years ([Formula: see text]) and females with primary education and below ([Formula: see text]). CONCLUSION: Our study suggests that improving diet quality and adhering to the Dietary Guidelines for Chinese may enhance cognitive performance in Chinese adults aged 55 years and older.

The association between hyperuricemia and insulin resistance surrogates, dietary- and lifestyle insulin resistance indices in an Iranian population: MASHAD cohort study.

BACKGROUND: Previous studies have reported insulin resistance (IR) to be associated with hyperuricemia. In this study, we aimed to assess the possible associations between the empirical dietary index for IR (EDIR), the empirical lifestyle index for IR (ELIR), and non-insulin-based surrogates (triglyceride-glucose (TyG) index, triglyceride-to-high-density-lipoprotein-cholesterol (TG/HDL-C) ratio, metabolic score for insulin resistance (METS-IR) and TyG with body mass index (TyG-BMI)) and hyperuricemia in an Iranian population. METHODS: In this cross-sectional study, 6457 participants aged 35-65 years were recruited as part of the MASHAD cohort study. EDIR and ELIR were calculated using dietary intakes, body mass index, and physical activity information. Insulin resistance surrogates including TyG, TyG-BMI, TG/HDL-C, and METS-IR were calculated for all participants. Hyperuricemia was defined as serum uric acid ≥ 7 mg/dl in men or ≥ 6 mg/dl in women. Multivariable logistic regression models were applied to determine the association between indexes of IR and hyperuricemia. RESULTS: The mean ELIR and IR surrogates (TyG, TyG-BMI, TG/ HDL, and METS-IR) were significantly higher in subjects with hyperuricemia compared to non-hyperuricemic subjects (p < 0.001). After adjusting for confounding variables, the association between hyperuricemia and EDIR was not significant, but ELIR had a significant association in all models (p < 0.001). All four IR surrogates (TyG, TyG-BMI, TG/ HDL, and METS-IR) showed a significant association with hyperuricemia (p < 0.001). CONCLUSION: There was a significant association between indexes of insulin resistance: TyG, TyG-BMI, TG/HDL-c, METS-IR, and ELIR with hyperuricemia, in a population sample from northeastern Iran.

Associations of EAT-Lancet Planetary Health Diet or Finnish Nutrition Recommendations with changes in obesity measures: a follow-up study in adults.

Background: Knowledge on the association between the EAT-Lancet Planetary Health Diet (PHD) or the Finnish Nutrition recommendations (FNR) and anthropometric changes is scarce. Especially, the role of the overall diet quality, distinct from energy intake, on weight changes needs further examination. Objectives: To examine the association between diet quality and weight change indicators and to develop a dietary index based on the PHD adapted for the Finnish food culture. Methods: The study population consisted of participants of two Finnish population-based studies (n = 4,371, 56% of women, aged 30-74 years at baseline). Dietary habits at the baseline were assessed with a validated food frequency questionnaire including 128-130 food items. We developed a Planetary Health Diet Score (PHDS) (including 13 components) and updated the pre-existing Recommended Finnish Diet Score (uRFDS) (including nine components) with energy density values to measure overall diet quality. Weight, height, and waist circumference (WC), and the body mass index (BMI) were measured at the baseline and follow-up, and their percentual changes during a 7-year follow-up were calculated. Two-staged random effects linear regression was used to evaluate ß-estimates with 95% confidence intervals. Results: Adherence to both indices was relatively low (PHDS: mean 3.6 points (standard deviation [SD] 1.2) in the range of 0-13; uRFDS: mean 12.7 points (SD 3.9) in the range of 0-27). We did not find statistically significant associations between either of the dietary indices and anthropometric changes during the follow-up (PHDS, weight: ß -0.04 (95% CI -0.19, 0.11), BMI: ß 0.05 (-0.20, 0.10), WC: ß -0.08 (-0.22, 0.06); uRFDS, weight: ß 0.01 (-0.04, 0.06), BMI: ß 0.01 (-0.04, 0.06), WC: ß -0.02 (-0.07, 0.03)). Conclusion: No associations between overall diet quality and anthropometric changes were found, which may be at least partly explained by low adherence to the PHD and the FNR in the Finnish adult population.

Adapting the Planetary Health Diet Index for children and adolescents.

BACKGROUND: Tools for measuring adherence to sustainable healthy diets among children and adolescents are lacking. OBJECTIVE: To advance methods for measuring adherence to sustainable healthy diets among children and adolescents by adapting an existing index, compare scores obtained using the original and adapted versions of the index in a sample of Chilean children, and describe the adapted index association with diet characteristics. METHODS: The Planetary Health Diet Index (PHDI) was adapted to better reflect children's and adolescents' nutritional requirements. The adapted index (PHDI-C) comprises 16 components with a maximum score of 150 points. PHDI-C was piloted among a sample of 958 Chilean children (3-6 years) using dietary data collected in 2016 through single 24-h recalls. A decision tree and food disaggregation methodology were developed to guide the calculation of scores. Scores obtained using the original and adapted versions of the index were compared. Linear regression models adjusted by child's gender and age were fitted to explore associations between total PHDI-C score, dietary recall characteristics and nutritional composition of children's diets. RESULTS: PHDI accounted for 75.7% of children's total caloric intake, whereas PHDI-C accounted for 99.6%. PHDI & PHCI-C scores were low among this sample of children; however, mean total score was lower when using PHDI compared to PHDI-C [40.7(12.1) vs 50.1(14.6)]. Children's scores were very low for nuts & peanuts, legumes, dark green vegetables, whole cereals, tubers & potatoes, and added sugars components across both indices, but were higher for dairy products and eggs & white meats components when using the PHDI-C due to adjustments made to ensure nutritional adequacy. Mean total PHDI-C score was significantly lower on weekends and special occasions, and significantly higher when children reported having a special diet (e.g., vegetarian). Total PHDI-C score was negatively associated with total sugars, saturated fats, trans fats, and animal-based protein intake, and positively associated with total protein, plant-based protein, total carbohydrates, and total fibre intake. CONCLUSIONS: This study provides a replicable method for measuring adherence to sustainable healthy diets among children and adolescents that can be used to monitor trends and measure the effectiveness of actions targeting improving children's diets.

Plant-Based Dietary Indices in Relation to Nutrient and Food Group Intakes in Preschool-Aged Children.

Dietary guidance promotes plant-based foods, yet minimal research has examined intake in children. This study examined plant-based food intake in preschool-aged children using plant-based dietary index (PDI) metrics and related these metrics to nutrient and food group intakes. Dietary data were collected from preschool-aged children (n = 283, 3.45 ± 1.22 years) from the Guelph Family Health Study at baseline using the Automated Self-Administered 24-Hour Dietary Assessment Tool. Food intake servings were assigned to 16 food groups for calculation of overall PDI (oPDI), healthful PDI (hPDI), and less healthful (lhPDI) scores and summarized into tertiles for energy-adjusted comparisons. For oPDI, participants in the highest vs. lowest tertile had higher intakes of nutrients and food groups to encourage (e.g., dietary fiber, fruits) as well as lower intakes of nutrients to encourage (e.g., calcium, vitamin D). For hPDI, participants in the highest vs. lowest tertile had higher intakes of nutrients and food groups to encourage and lower intakes of those to limit (e.g., saturated fat, sweets and desserts). For lhPDI, participants in the highest vs. lowest tertile had higher intakes of nutrients and food groups to limit and lower intakes of those to encourage. These results can inform dietetic practice for dietary guidance that promotes plant-based foods in children.

Plant-based dietary indices and biomarkers of chronic low-grade inflammation: a cross-sectional analysis of adults in Ireland.

PURPOSE: There is increasing interest in the health benefits of plant-based diets (PBDs). Evidence reports favourable associations with inflammatory profiles and reduced cardiovascular disease risk. However, limited studies have examined relationships between PBD indices (PDIs) and inflammatory biomarkers. We explored overall PDI, healthful PDI (hPDI) and unhealthful PDI (uPDI) associations with inflammatory biomarker profiles. METHODS: This cross-sectional analysis included 1986 middle- to older-aged adults from the Mitchelstown Cohort. PDI scores were calculated using validated food frequency questionnaires. PDI score associations with inflammatory biomarkers were assessed via linear regression analysis, with adjustment for potential confounders. RESULTS: Comparison of quintiles (Q5 vs Q1) revealed lower concentrations of C-reactive protein (CRP), interleukin 6 (IL-6), white blood cells (WBCs), neutrophils and monocytes, and the leptin-to-adiponectin ratio (PDI and hPDI P < 0.05); lower leptin (PDI, P < 0.05), and complement component 3 (C3), tumour necrosis factor alpha (TNF-α), plasminogen activator inhibitor 1, lymphocytes and eosinophils (hPDI, P < 0.05); and higher concentrations of adiponectin (PDI and hPDI, P < 0.05). Conversely, higher concentrations of C3, CRP, IL-6, TNF-α, resistin, WBCs, neutrophils, lymphocytes, monocytes and eosinophils, and the neutrophil-to-lymphocyte ratio, and lower adiponectin concentrations were observed comparing uPDI quintiles (P < 0.05). In fully adjusted regression models, higher hPDI scores were associated with lower concentrations of C3, TNF-α, WBCs, neutrophils and monocytes (all P < 0.01). Higher uPDI scores were associated with higher C3 and TNF-α concentrations (all P < 0.01). CONCLUSION: This study provides evidence that a more healthful PBD is associated with a more favourable inflammatory profile and that a more unhealthful PBD is associated with the reverse.

Dietaryindex: A User-Friendly and Versatile R Package for Standardizing Dietary Pattern Analysis in Epidemiological and Clinical Studies.

Background: Few standardized and open-source tools exist for calculating dietary pattern indexes from dietary intake data in epidemiological and clinical studies. Miscalculations of dietary indexes, with suspected erroneous findings, are occasionally noted in the literature. Objective: The primary aim is to develop and validate dietaryindex, a user-friendly and versatile R package that standardizes the calculation of dietary indexes. Methods: Dietaryindex utilizes a two-step process: an initial calculation of serving size for each food and nutrient category, followed by the calculation of individual dietary indexes. It includes generic functions that accept any preprocessed serving sizes of food groups and nutrients, with the standard serving sizes defined according to the methodologies used in well-known prospective cohort studies. For ease of use, dietaryindex also offers one-step functions that directly reference common datasets and tools, including the National Health and Nutrition Examination Survey (NHANES) and Block Food Frequency Questionnaire, eliminating the need for data preprocessing. At least two independent researchers validated the serving size definitions and scoring algorithms of dietaryindex. Results: Dietaryindex can calculate multiple dietary indexes of high interest in research, including Healthy Eating Index (HEI) - 2020, Alternative Healthy Eating Index 2010, Dietary Approaches to Stop Hypertension Index, Alternate Mediterranean Diet Score, Dietary Inflammatory Index, American Cancer Society 2020 dietary index, and Planetary Health Diet Index from the EAT-Lancet Commission. In our validation process, dietaryindex demonstrated full accuracy (100%) in all generic functions with two-decimal rounding precision in comparison to hand-calculated results. Similarly, using NHANES 2017-2018 data and ASA24 and DHQ3 example data, the HEI2015 outputs from dietaryindex aligned (99.95%-100%) with results using the SAS codes from the National Cancer Institute. Conclusions: Dietaryindex is a user-friendly, versatile, and validated informatics tool for standardized dietary index calculations. We have open-sourced all the validation files and codes with detailed tutorials on GitHub (https://github.com/jamesjiadazhan/dietaryindex).

Interactions Between Genetic Risk Score and Healthy Plant Diet Index on Cardiometabolic Risk Factors Among Obese and Overweight Women.

People with higher genetic predisposition to obesity are more susceptible to cardiovascular diseases (CVDs) and healthy plant-based foods may be associated with reduced risks of obesity and other metabolic markers. We investigated whether healthy plant-foods-rich dietary patterns might have inverse associations with cardiometabolic risk factors in participants at genetically elevated risk of obesity. For this cross-sectional study, 377 obese and overweight women were chosen from health centers in Tehran, Iran. We calculated a healthy plant-based diet index (h-PDI) in which healthy plant foods received positive scores, and unhealthy plant and animal foods received reversed scores. A genetic risk score (GRS) was developed based on 3 polymorphisms. The interaction between GRS and h-PDI on cardiometabolic traits was analyzed using a generalized linear model (GLM). We found significant interactions between GRS and h-PDI on body mass index (BMI) (p = 0.02), body fat mass (p = 0.04), and waist circumference (p = 0.056). There were significant gene-diet interactions for healthful plant-derived diets and BMI-GRS on high-sensitivity C-reactive protein (p = 0.03), aspartate aminotransferase (p = 0.04), alanine transaminase (p = 0.05), insulin (p = 0.04), and plasminogen activator inhibitor 1 (p = 0.002). Adherence to h-PDI was more strongly related to decreased levels of the aforementioned markers among participants in the second or top tertile of GRS than those with low GRS. These results highlight that following a plant-based dietary pattern considering genetics appears to be a protective factor against the risks of cardiometabolic abnormalities.

Scoping review of the association of plant-based diet quality with health outcomes.

Introduction: The association of plant-based dietary patterns with health outcomes has traditionally been assessed without considering nutritional value. The plant-based dietary index (PDI), first published in 2016, overcomes this limitation with both a healthful PDI (hPDI) and an unhealthful PDI (uPDI), based on the quality of plant foods consumed plus the frequency of animal foods. We sought to summarize the breadth of research using the hPDI and uPDI to gain insight into how the quality of plant-based dietary patterns might be associated with health outcomes. Methods: Scoping review of studies that used the PDI, hPDI, or uPDI to report associations with health outcomes. Multiple databases were searched from 2010 through April 2023 with 2 authors independently assessing eligibility and extracting data. In addition to assessing the association of the indices to health outcomes, we determined the frequency of concordant or discordant findings for hPDI versus PDI and for hPDI versus uPDI. Results: We included 95 articles (54% longitudinal, 37% cross-sectional, and 9% case-control) with a median sample size of 3,646. Higher hPDI levels were associated with favorable health outcomes in 36% of comparisons (most often for obesity, mortality, diabetes, cardiovascular disease, and psychiatric disorders), compared to 25% for the PDI and only 2% for the uPDI. Conversely, higher levels of the uPDI were associated with unfavorable health outcomes in 33% of comparisons, in contrast to under 1% for the hPDI and 2% for the PDI. When the hPDI association to an outcome was discordant with the uPDI or PDI, the significance and directionality always favored the hPDI over the uPDI, and nearly always favored the hPDI over the PDI. Discussion: Dietary indices that account for the quality of plant foods can show health benefits that might be missed by a generic plant-based index. A greater focus on the quality of plant foods could improve nutrition guidelines, raise awareness about the benefits of adding unrefined plant foods to the diet, and empower consumers to make incremental additions of such foods to displace unhealthy foods. We anticipate increasing use of indices that address food quality in future research.

Chinese Dietary Indices and Glioma: New Insights of a Case-Control Study in the Chinese Population.

Identifying modifiable factors in primary prevention strategies is a typical goal of glioma epidemiology. Among many glioma risk factors, diet was always considered as one. Most of the relevant studies thus far were concentrated on the West. It was crucial to investigate the connection between the Chinese diet and gliomas given the stark variations between western and eastern diets. A food frequency questionnaire including 114 items was used to investigate the food intake of the study subjects. The Chinese Dietary Quality Index (CDQI), the Chinese Dietary Balance Index (CDBI), the Dietary Antioxidant Index (DAI), the Dietary Inflammation Index (DII), and the Chinese Healthy Eating Index (CHEI) were calculated based on the data provided by the food frequency questionnaire to evaluate dietary quality, dietary balance, dietary antioxidants, dietary inflammation and adherence to the Chinese dietary guidelines in 506 glioma patients and 506 controls, respectively. After adjusting covariates, CHEI (OR = 0.90, 95% CI: 0.88-0.93) and DAI (OR = 0.61, 95% CI: 0.54-0.70) were correlated to a reduced glioma risk, and CDBI-based undernutrition (OR = 1.08, 95% CI: 1.06-1.12) and overnutrition (OR = 1.14, 95% CI: 1.09-1.20) and DII (OR = 2.20, 95% CI: 1.81-2.68) were correlated to an elevated glioma risk. Moreover, restrictive cubic spline analysis showed that there were significant nonlinear dose-response relationships between CHEI, CDBI, DAI, DII, and glioma. Therefore, adhering to the Chinese dietary guidelines was connected with a lower glioma risk, and undernutrition and overnutrition in the Chinese diet were associated with an increased risk of glioma.