Background: The novel Dietary Index for Gut Microbiota (DI-GM) quantifies dietary patterns influencing microbiota health, yet its association with irritable bowel syndrome (IBS) risk remains unexplored. We aim to investigate prospective association of DI-GM with incident IBS in a long-term cohort.
Methods: Participants free of IBS at baseline with at least one record of 24-hour dietary recall from UK Biobank were included (N = 175,103). DI-GM was composed of 14 food/nutrient components known to influence gut microbial health. Each component was scored 0 or 1 based on sex-specific median intakes, and total scores were summed. The primary outcome was incident IBS. Multivariable Cox models were used to estimate associated risk.
Results: Over a 12.56-years of follow-up, 2,980 incident IBS cases were identified. Compared to participants with the lowest DI-GM quartile, those with the highest quartile had a 13% lower IBS risk (HR = 0.87; 95% CI: 0.79-0.97; P-value = 0.009), with significant trend (P-trend = 0.012). Moreover, per 1 score increase in DI-GM was associated with a 3% reduced IBS risk (HR = 0.97; 95% CI: 0.95-0.99; P-value = 0.009). Subgroup and sensitivity analyses consistently supported this inverse association.
Conclusions: Higher baseline DI-GM scores, reflecting dietary patterns supportive of gut microbiota, are associated with lower risk of developing IBS. These findings suggest that the DI-GM score may serve as a useful predictive tool for assessing IBS risk and facilitating the implementation of targeted dietary interventions. Future studies should examine changes in DI-GM scores over time help establish a potential causal link with IBS.
Background: Disruption in gut microbiota has been identified as a contributor to obesity-related inflammation and metabolic disorders. This study investigates the effects of preoperative probiotic supplementation on inflammation, endotoxemia, adipokines, and gastrointestinal peptides after bariatric surgery.
Methods: This randomized, double-blind, placebo-controlled clinical trial included patients undergoing laparoscopic sleeve gastrectomy (LSG) or one anastomosis gastric bypass (OAGB). Participants were randomized to receive a 12-week supplementation of either a probiotic mixture, Sanprobi Barrier, which contained nine strains of bacteria (Bifidobacterium bifidum W23, Bifidobacterium lactis W51 and W52, Lactobacillus acidophilus W37, Levilactobacillus brevis W63, Lacticaseibacillus casei W56, Ligilactobacillus salivarius W24, Lactococcus lactis W19, and Lactococcus lactis W58), or a placebo before surgery. The key outcomes measured at baseline and 6 months postoperatively included serum lipopolysaccharide (LPS), cytokines (interleukin-6 - IL-6, interleukin-2 receptor-IL-2R, and C-reactive-CRP protein), adipokines (leptin, adiponectin, resistin), and gastrointestinal peptides (glucagon-like peptide-1 - GLP-1, ghrelin, and trefoil factor 2). Relative mRNA expression of ghrelin and trefoil family factor 2 in gastric tissues was also analyzed at baseline and on the day of the surgery.
Results: Out of the initial 110 participants, serum samples of 18 individuals in the probiotic group and 24 in the placebo group were analyzed. Both groups showed significant reductions in serum LPS levels six months after surgery; however, no significant differences were observed between the two groups. Adiponectin levels increased significantly in the placebo group (4.2 ± 2.3 vs. 2.2 ± 1.1 pg/mL; p < 0.001), while leptin levels decreased significantly in both groups without intergroup differences. IL-6 levels were significantly lower in the probiotic group compared to the placebo group at 6 months (2.2 ± 1.1 vs 4.2 ± 2.3 pg/mL; p = 0.004). No significant differences were observed in the remaining cytokine levels between the groups. Gastrointestinal peptides showed no significant differences between the groups, although GLP-1 levels improved within both groups. No changes were observed in ghrelin and trefoil factor 2 expression at the mRNA level.
Conclusions: Preoperative probiotic therapy was associated with significantly lower IL-6 levels compared to placebo six months after surgery, suggesting a potential anti-inflammatory effect. However, since the between-group difference in IL-6 changes from baseline was not statistically significant, the observed effect should be interpreted with caution. Other measured markers were not significantly affected, though low statistical power may have limited detection of subtle effects. These findings suggest that while probiotics may reduce
Purpose: This study aimed to examine temporal protein patterns (i.e., protein intake timing across the day) in American adults and their associations with diabetes, BMI and glycaemic measures.
Methods: Total protein intake at eating occasions was estimated from the National Health and Nutrition Examination Survey 2017-2020 one-day dietary recall data (≥ 20 y; n = 7625). Latent variable mixture models were used to identify temporal patterns based on hourly protein intake (g). Adults with fasting glucose ≥ 7.0 mmol/L, poor glycaemic control (HbA1c ≥ 6.5%), diabetic medications, or previous diabetes diagnosis were classified as having diabetes. Regression models were used to examine associations for temporal protein patterns with diabetes prevalence, BMI and glycaemic measures (fasting glucose, HbA1c, insulin, Homeostatic Model Assessment of Insulin Resistance), adjusted for multiple confounders.
Results: Three latent classes for men's and women's temporal protein patterns were identified. Class 1 had higher conditional probabilities of eating protein at 18:00 h, while Class 2 tended to eat protein 1-h later than Class 1 and had higher overall protein intake (p < 0.001). Class 3 was characterised by variable protein intake timing and had lower overall protein intake than other classes (p < 0.001). Men's Class 1 had lower probabilities for poor glycaemic control (5.9%), but associations were attenuated after adjusting for BMI. There were no associations between temporal protein patterns with diabetes, BMI and other glycaemic measures.
Conclusions: Temporal protein patterns were not associated with diabetes and glycaemic measures. Future prospective studies may better examine the effects of temporal protein patterns on diabetes by considering variations in protein sources.
Purpose: This study aimed to translate and culturally adapt the Beverage Intake Questionnaire (BEVQ-15) to the Turkish population and to assess its validity and reproducibillity.
Methods: This cross-sectional study included adults and older residing in Ankara, Turkey. The study process involved the translation of the BEVQ-15 from English into Turkish and its adaptation to the Turkish community. Adaptations to the original BEVQ-15 included separating the black tea and coffee category into distict categories, as well as herbal tea. Additionally, plain mineral water, flavored mineral water, kefir, and turnip juice were presented as individual categories. The adaptation of BEVQ-15 to Turkish preferences resulted in the BEVQ-21. Participants come to three visits, each two weeks apart. The BEVQ-21 was administered at visits 1 and 3, and a three day dietary record was returned during visit 2.. The BEVQ-21 was conducted at visit one (BEVQ-1) and visit three (BEVQ-2). Validity and reproducability statistical analyses were conducted using Wilcoxon signed-rank tests, Bland-Altman plots, and Spearman correlations.
Results: Fifty-one participants completed all study visits. Minimal yet significant differences were identified between the two assessment tools (BEVQ-2 and DR) across various beverage categories, with mean differences ranging from 3 to 82 mL and 0 to 16 kcal. According to Bland-Altman plots between BEVQ-21 and dietary records, differences for water (mL), regular mineral water (mL), whole and flavored milk (mL and kcal), soft drinks (mL and kcal), black tea (mL), herbal teas (mL), and total beverage intake (mL) were found to be approximately consistent within the boundaries (p < 0.05). For reproducibility, sugary beverage and total beverage consumption were significantly associated between the first and second administration of the BEVQ-21 (r = 0.44-0.65, p ≤ 0.05).
Conclusions: The adapted BEVQ-21 for the Turkish population demonstrated validity and reproducibility for most types of beverage intake among adults in Turkey.
Background: Low dietary diversity can contribute to undernutrition, impacting gestational weight gain (GWG) and increasing the risk of low birth weight (LBW).
Objective: This study investigates the relationships between maternal dietary diversity, dietary quality, GWG, and LBW in a cohort of singleton pregnant mothers in Jordan. It was hypothesized that higher dietary diversity and appropriate GWG would correlate with a reduced likelihood of LBW and that "minimum dietary diversity for women (MDD-W)" and "prime diet quality scores (PDQS) " would have both indirect and direct effects on birth weight, mediated by GWG.
Methods: The prospective study involved 198 singleton pregnant mothers aged 19 to 45, segmented into three groups by trimester (66 women per trimester). Dietary diversity was assessed using the MDD-W and the PDQS. GWG was classified as appropriate, excess, or inadequate based on pre-pregnancy body mass index (BMI). Birth weights, lengths, and head circumferences of neonates were measured.
Results: Mothers with MDD-W > 5 and PDQS > 21 had significantly higher average birth weights and lengths compared to those with lower scores (MDD-W: 3.1 ± 0.6 vs. 2.6 ± 0.5 kg; PDQS: 3.0 ± 0.6 vs. 2.6 ± 0.5 kg; MDD-W: 49.8 ± 1.7 vs. 48.1 ± 1.7 cm; PDQS: 49.2 ± 1.8 vs. 48.1 ± 1.8 cm). Significant predictors of LBW included GWG for pre-pregnancy BMI, previous LBW deliveries, PDQS, and family income. Inadequate GWG was significantly associated with LBW. GWG significantly mediated the relationship between MDD-W (B = 0.067, P < 0.001, 95% CI [0.059-0.076]), PDQS (B = 0.069, P < 0.001, 95% CI [0.06-0.077]), and birth weight. Each score increase in MDD-W was associated with a 0.141 kg increase in birth weight (B = 0.141, P < 0.001, 95% CI [0.093-0.189]), compared to a 0.041 kg increase for each PDQS score (B = 0.041, P < 0.001, 95% CI [0.025-0.058]).
Conclusions: Our findings indicated that both MDD-W and PDQS are associated with birth weight, with higher scores correlating with increased GWG and birth weight. Notably, dietary diversity and GWG relative to pre-pregnancy BMI emerged as robust predictors of birth weight at delivery.
Background: The evidence linking dietary indices to Parkinson's disease (PD) risk remains limited. This study investigated the association between the Dietary Index for Gut Microbiota (DI-GM) and PD risk in middle-aged and elderly populations.
Methods: Cross-sectional data were obtained from the 2007-2020 cycles of the National Health and Nutrition Examination Survey (NHANES), including 17,373 participants aged 40 years or older. PD was defined by antiparkinsonian medication use. DI-GM scores were calculated based on 14 dietary components. Multiple logistic regression and a restricted cubic spline model (RCS) were used to test the relationship between DI-GM and PD. Subgroup and sensitivity analyses were conducted to evaluate the robustness of the results.
Results: Among 17,373 participants, those with PD (n = 232) had lower DI-GM scores compared to non-PD individuals. Higher DI-GM scores (≥ 6) were associated with a 49% reduction in PD prevalence. RCS analysis showed a non-linear relationship between DI-GM and PD (P < 0.05). Subgroup and sensitivity analyses confirmed stable associations across demographic groups and after adjusting for comorbidities.
Conclusions: A gut microbiota-friendly diet, as measured by DI-GM, is associated with reduced PD risk, especially in the higher DI-GM score. This finding may inform future dietary guidelines for the prevention of PD.
Background: To determine the demographic and socioeconomic factors associated with self-reported diet and physical activity among women in the U.S.
Methods: Retrospective analysis of the Third U.S. National Health and Nutrition Examination Survey (NHANES III, 1988-1994). Chi-squared analyses were used to compare differences in diet and physical activity (PA) among participants.
Results: Of 3,196 female participants, 87.1% of participants were White, 9.4% were Black, and 3.5% Mexican American. 39.4% measured as not obese and 27.4% obese (BMI ≥ 30 kg/m2). Overall, 8.4% reported a poor diet and 19.5% were inactive. Participants reporting both poor diet and low PA were likely to be younger (28.0% vs. 12.0% p < 0.001), Black (36.0%, p < 0.001), less than 12 years education (26.5%, p < 0.001), lower income (23.6%, p < 0.002). In the obese group, 27% of women reported being physically inactive with few reporting poor diet (9.7%). Among participants with BMI ≥ 30 kg/m2, 44.3% of Black women reported poor diet and low physical activity, compared to 24.1% of Mexican American and 22.1% of White participants (p = 0.005).
Conclusion: Participants who were younger than 55, non-Hispanic Black, had less than 12 years of education, low income, obese (BMI ≥ 30 kg/m2), and current smokers were more likely to report poor diet and low PA. Of obese participants, Mexican American and White women were less likely to report both poorer nutrition and a sedentary lifestyle compared to Black women.
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