FDF-DB: A Database of Traditional Fermented Dairy Foods and Their Associated Microbiota.

BACKGROUND: Fermented foods are attracting increasing interest due to their nutritional and health benefits, including a positive impact on gut microbiota exerted by their associated microbes. However, information relative to traditional fermented dairy products, along with their autochthonous microbiota, is still fragmented and poorly standardized. Therefore, our aim was to collect and aggregate data useful for obtaining a comprehensive overview translated in a classical database interface that can be easily handled by users. METHODS: a preliminary inventory was built up by systematically collecting data from publicly available resources for the creation of a list of traditional dairy foods produced worldwide, including additional metadata useful for stratifying, and collapsing subgroups. RESULTS: we developed the Fermented Dairy Food Database (FDF-DB), a feasible resource comprising 1852 traditional dairy foods (cheeses, fermented milks, and yogurt) for which microbial content and other associated metadata such as geographical indication label, country/region of origin, technological aspects were gathered. CONCLUSIONS: FDF-DB is a useful and user-friendly resource where taxonomic information and processing production details converge. This resource will be of great aid for researchers, food industries, stakeholders and any user interested in the identification of technological and microbiological features characterizing traditional fermented dairy products.

The Effect of Low Glycemic Index Mediterranean Diet and Combined Exercise Program on Metabolic-Associated Fatty Liver Disease: A Joint Modeling Approach.

BACKGROUND: Excessive caloric intake and reduced energy expenditure are associated with the onset of metabolic-associated fatty liver disease (MAFLD). The aim of this study was to probe the benefits of a low glycemic index Mediterranean diet (LGIMD) and a combined exercise program (CEP) on MAFLD by monitoring the clinical process through anthropometric measurement, body mass index (BMI), and specific biomarkers, such as the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). METHODS: The study was conducted at the National Institute of Gastroenterology, 'S. de Bellis', Italy. Subjects were invited to join the study for 12 months. RESULTS: 54 participants were enrolled. Joint modeling of longitudinal and time-to-event data was applied. Overall, a statistically significant direct effect of LGIMD/CEP adherence on ln (BMI), a statistically significant direct effect of LGIMD/CEP adherence on time-to-event and a strong statistically significant direct effect of log (BMI) on time-to-event were observed. In addition, a statistically significant direct effect of LGIMD/CEP adherence on ln(HOMA-IR), a statistically significant direct effect of LGIMD/CEP adherence on time-to-event and a statistically significant direct effect of ln(HOMA-IR) on time-to-event were observed. CONCLUSIONS: LGIMD/CEP significantly improved MAFLD status; in addition, longitudinal BMI and HOMA-IR were good predictors of the disappearance of diagnostic criteria for MAFLD.

A Low Glycemic Index Mediterranean Diet Combined with Aerobic Physical Activity Rearranges the Gut Microbiota Signature in NAFLD Patients.

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease, and its prevalence worldwide is increasing. Several studies support the pathophysiological role of the gut-liver axis, where specific signal pathways are finely tuned by intestinal microbiota both in the onset and progression of NAFLD. In the present study, we investigate the impact of different lifestyle interventions on the gut microbiota composition in 109 NAFLD patients randomly allocated to six lifestyle intervention groups: Low Glycemic Index Mediterranean Diet (LGIMD), aerobic activity program (ATFIS_1), combined activity program (ATFIS_2), LGIMD plus ATFIS_1 or ATFIS2 and Control Diet based on CREA-AN (INRAN). The relative abundances of microbial taxa at all taxonomic levels were explored in all the intervention groups and used to cluster samples based on a statistical approach, relying both on the discriminant analysis of principal components (DAPCs) and on a linear regression model. Our analyses reveal important differences when physical activity and the Mediterranean diet are merged as treatment and allow us to identify the most statistically significant taxa linked with liver protection. These findings agree with the decreased 'controlled attenuation parameter' (CAP) detected in the LGIMD-ATFIS_1 group, measured using FibroScan®. In conclusion, our study demonstrates the synergistic effect of lifestyle interventions (diet and/or physical activity programs) on the gut microbiota composition in NAFLD patients.

Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach.

Dietary behaviour is a core element in diabetes self-management. There are no remarkable differences between nutritional guidelines for people with type 2 diabetes and healthy eating recommendations for the general public. This study aimed to evaluate dietary differences between subjects with and without diabetes and to describe any emerging dietary patterns characterizing diabetic subjects. In this cross-sectional study conducted on older adults from Southern Italy, eating habits in the "Diabetic" and "Not Diabetic" groups were assessed with FFQ, and dietary patterns were derived using an unsupervised learning algorithm: principal component analysis. Diabetic subjects (n = 187) were more likely to be male, slightly older, and with a slightly lower level of education than subjects without diabetes. The diet of diabetic subjects reflected a high-frequency intake of dairy products, eggs, vegetables and greens, fresh fruit and nuts, and olive oil. On the other hand, the consumption of sweets and sugary foods was reduced compared to non-diabetics (23.74 ± 35.81 vs. 16.52 ± 22.87; 11.08 ± 21.85 vs. 7.22 ± 15.96). The subjects without diabetes had a higher consumption of red meat, processed meat, ready-to-eat dishes, alcoholic drinks, and lower vegetable consumption. The present study demonstrated that, in areas around the Mediterranean Sea, older subjects with diabetes had a healthier diet than their non-diabetic counterparts.

Effects of weight change on all causes, digestive system and other causes mortality in Southern Italy: a competing risk approach.

Weight change is associated with all causes of death, cardiovascular, and cancer mortality and a heterogeneous group of other causes of death. We aimed to estimate the effect of weight change on all causes and cause-specific mortality in a cohort with a high prevalence of deaths due to diseases of the digestive system.MethodsIn this prospective cohort study, 2230 subjects aged 30 to 50 years were examined. The study consisted of a 32-year longitudinal study period (January 1985 to December 2017) and mortality follow-up. Outcomes were mortality from all causes and deaths from gastrointestinal disease. Root Mean Squared Error (RMSE) was evaluated to capture individual residual variation in Body Mass Index (BMI) after adjustment for baseline BMI, and the relationship of residual variation with mortality was calculated as cumulative incidence function and cause-specific hazard (CSH) rate.ResultsIn total, 793 participants died during the follow-up, 96 of them due to Digestive system causes. Magnitude of residual variation weight in the last quintile was associated with all-cause mortality (relative risk, 2.00; 95% CI, 1.54-2.59) and Digestive system causes (relative risk, 3.82; 95% CI, 1.86-7.81).ConclusionThe findings suggest an association between weight change and gastrointestinal disease mortality. Epidemiological works studying the correlation between weight change and mortality should consider this aspect.

Modified WCRF/AICR Score and All-Cause, Digestive System, Cardiovascular, Cancer and Other-Cause-Related Mortality: A Competing Risk Analysis of Two Cohort Studies Conducted in Southern Italy.

BACKGROUND: In real life, nutrition goes beyond purely biological domains. Primary prevention is the most efficient approach for reducing the risk of mortality. We aimed to study the association of lifestyle, as measured by a modified World Cancer Research Fund/American Institute for Cancer Research (mWCRF/AICR) scoring system with all-cause, digestive system disease-related (DSD-related), cardiovascular disease-related (CVD-related), cancer-related and other cause-related mortality using data from two population-based cohort studies conducted in Southern Italy. METHODS: A random sample of 5271 subjects aged 18 years or older was enrolled in 2005-2006 and followed up until 2020. Usual food intakes were estimated using a validated dietary questionnaire. Competing risks survival models were applied. RESULTS: High adherence to the mWCRF/AICR score was found to be statistically significant and negatively associated with all-cause mortality (HR 0.56, 95%CI 0.39; 0.82), DSD-related mortality (SHR 0.38, 95%CI 0.15; 0.97) and cancer-related mortality (SHR 0.43, 95%CI 0.19; 0.97) in the male sub-cohort and other-cause mortality (SHR 0.43, 95%CI 0.21; 0.88) only in the female group. CONCLUSIONS: This mWCRF/AICR score can be seen as a simple, easy tool for use in clinical practice to evaluate both qualitative and quantitative aspects of the diet.

Development and validation of a neural network for NAFLD diagnosis.

Non-Alcoholic Fatty Liver Disease (NAFLD) affects about 20-30% of the adult population in developed countries and is an increasingly important cause of hepatocellular carcinoma. Liver ultrasound (US) is widely used as a noninvasive method to diagnose NAFLD. However, the intensive use of US is not cost-effective and increases the burden on the healthcare system. Electronic medical records facilitate large-scale epidemiological studies and, existing NAFLD scores often require clinical and anthropometric parameters that may not be captured in those databases. Our goal was to develop and validate a simple Neural Network (NN)-based web app that could be used to predict NAFLD particularly its absence. The study included 2970 subjects; training and testing of the neural network using a train-test-split approach was done on 2869 of them. From another population consisting of 2301 subjects, a further 100 subjects were randomly extracted to test the web app. A search was made to find the best parameters for the NN and then this NN was exported for incorporation into a local web app. The percentage of accuracy, area under the ROC curve, confusion matrix, Positive (PPV) and Negative Predicted Value (NPV) values, precision, recall and f1-score were verified. After that, Explainability (XAI) was analyzed to understand the diagnostic reasoning of the NN. Finally, in the local web app, the specificity and sensitivity values were checked. The NN achieved a percentage of accuracy during testing of 77.0%, with an area under the ROC curve value of 0.82. Thus, in the web app the NN evidenced to achieve good results, with a specificity of 1.00 and sensitivity of 0.73. The described approach can be used to support NAFLD diagnosis, reducing healthcare costs. The NN-based web app is easy to apply and the required parameters are easily found in healthcare databases.

Physical Activity Reduction and the Worsening of Gastrointestinal Health Status during the Second COVID-19 Home Confinement in Southern Italy.

Due to the COVID-19 pandemic, in December 2020, the Italian government established a second home confinement during the Christmas holidays. These restrictions offered the opportunity to utilize a well-defined model for observing the consequences of lifestyle changes of healthy individuals. This study aimed at estimating in healthy subjects from Southern Italy the physical activity (PA), the presence and the severity of gastrointestinal (GI) symptoms, and the association between the possible worsening of GI health status and the PA levels. An adapted version of the International PA Questionnaire-short form (IPAQ-SF) and the Gastrointestinal Symptom Rating Scale (GSRS) were proposed through Google's online survey platform in three different periods via WhatsAppTM to 499 healthy subjects (62% females) from Apulia (25%), Calabria (37%), and Campania (38%). Our results showed statistically significant changes during the home confinement: reduced energy expenditure (EE) among overweight subjects (-239.82, 95%CI -405.74; -73.89) or those who had high GSRS total score (-1079.54, 95%CI -2027.43; -131.66). An increase in GSRS total score was observed in overweight subjects, reaching statistical significance in those from Campania. Our study supports the importance of PA to reduce health risks, including those related to the possible onset of GI tract diseases.

Decreased levels of physical activity: results from a cross-sectional study in southern Italy during the COVID-19 lockdown.

BACKGROUND: During the COVID-19 pandemic, the Italian government took security measures to try to limit infections. Restrictive measures included social distancing, home confinement and the closure of all public structures like gyms and swimming pools. The impact of these limitations on health and lifestyle was inevitably negative. The purpose of this study was to establish the level of physical activity (PA), expressed as energy expenditure (MET-minute/week) in a Southern Italian population before and during the COVID-19 lockdown. METHODS: An adapted version of the International Physical Activity Questionnaire-short form (IPAQ-SF) was published on the official website of the National Institute of Gastroenterology IRCCS S. de Bellis, Castellana Grotte, Bari, Italy and on several social media in May 2020. RESULTS: Three hundred ten replies (72% women) from Apulia (60%), Calabria (28%), Campania (11%) and Sicily (1%) were included in the study. The COVID-19 lockdown had a negative effect on the vigorous PA intensity level and on walking, but not on the moderate PA intensity level. Additionally, daily time spent sitting down increased by more than 12% during the COVID-19 lockdown. CONCLUSIONS: Isolation changed PA behaviors. The decreased energy expenditure (MET-minute/week) during the lockdown had a negative impact in both genders, especially on the young adults and adults' groups.

The effect of the Mediterranean Diet on lifespan: a treatment-effect survival analysis of a population-based prospective cohort study in Southern Italy.

BACKGROUND: The Mediterranean diet (MedDiet) is associated with good health. We aimed to estimate the effect of levels of adherence to the MedDiet on lifespan by performing treatment effects survival analysis. METHODS: A sample of 5250 subjects aged ≥18 years were randomly selected from the electoral list of Castellana Grotte and Putignano (Apulian Region, Italy). Cohorts were enrolled in 2005-06 and followed-up until December 2018. The adherence to the MedDiet was measured by the relative Mediterranean score (rMED) and categorized as high, medium and low. Time-to-death (all-causes) as estimated by average treatment effect on the treated (ATET), potential outcome mean (POM) and relative efficiency of exposure were the outcomes. RESULTS: A total of 4896 subjects were included. The median follow-up time was 12.82 (inter quartile range (IQR) 12.22-13.05), 12.91 (IQR 12.21-13.27) and 12.84 (IQR 12.19-13.03) years for high, medium and low rMED subjects respectively. By December 2018, 453 (9.25%) had died. There was a strong effect of medium and low rMED {ATET, -5.10 [95% confidence interval (CI) -9.39, -0.80] and -8.91 (95%CI -13.37, -4.45), respectively}. High rMED has an important effect on mean age at death [POM 90.16 (95% CI 86.06, 94.25)]. The relative effect size for medium and low rMED subjects was a lower lifespan of 5.62% (95% CI 1.01, 10.3) and 9.90% (95% CI 5.30, 5.30), respectively. CONCLUSIONS: We observed an important benefit in additional years of survival from adherence to MedDiet in this southern Italian cohort. Further investigation corroborating our findings in other population groups in other geographic regions will be an important contribution to promoting health and longevity.

Physical Activity and Low Glycemic Index Mediterranean Diet: Main and Modification Effects on NAFLD Score. Results from a Randomized Clinical Trial.

BACKGROUND: Non-Alcoholic Fatty Liver Disease (NAFLD) is the most common chronic liver disease worldwide, and lifestyle modification is the current standard treatment. The aim of the study was to estimate the effect of two different physical activity (PA) programs, a Low Glycemic Index Mediterranean Diet (LGIMD), and their combined effect on the NAFLD score as measured by FibroScan®. METHODS: Moderate or severe NAFLD subjects (n = 144) were randomly assigned to six intervention arms during three months. Interventions arms were a control diet, LGIMD, aerobic activity program (PA1), combined activity program (PA2), and LGIMD plus PA1 or LGIMD plus PA2. The data were compared at baseline, at 45 days, and at 90 days. Analysis of variance was performed under the intention-to-treat principle. RESULTS: There was a statistically significant reduction in the NAFLD score after 45 days of treatment in every working arm except for Arm 1 (control diet). After 90 days, the best results were shown by the intervention arms in which LGIMD was associated with PA: LGIMD plus PA1 (-61.56 95% CI -89.61, -33.50) and LGIMD plus PA2 (-38.15 95% CI -64.53, -11.77). CONCLUSION: All treatments were effective to reduce NAFLD scores, but LGIMD plus PA1 was the most efficient.

Selecting the best machine learning algorithm to support the diagnosis of Non-Alcoholic Fatty Liver Disease: A meta learner study.

BACKGROUND & AIMS: Liver ultrasound scan (US) use in diagnosing Non-Alcoholic Fatty Liver Disease (NAFLD) causes costs and waiting lists overloads. We aimed to compare various Machine learning algorithms with a Meta learner approach to find the best of these as a predictor of NAFLD. METHODS: The study included 2970 subjects, 2920 constituting the training set and 50, randomly selected, used in the test phase, performing cross-validation. The best predictors were combined to create three models: 1) FLI plus GLUCOSE plus SEX plus AGE, 2) AVI plus GLUCOSE plus GGT plus SEX plus AGE, 3) BRI plus GLUCOSE plus GGT plus SEX plus AGE. Eight machine learning algorithms were trained with the predictors of each of the three models created. For these algorithms, the percent accuracy, variance and percent weight were compared. RESULTS: The SVM algorithm performed better with all models. Model 1 had 68% accuracy, with 1% variance and an algorithm weight of 27.35; Model 2 had 68% accuracy, with 1% variance and an algorithm weight of 33.62 and Model 3 had 77% accuracy, with 1% variance and an algorithm weight of 34.70. Model 2 was the most performing, composed of AVI plus GLUCOSE plus GGT plus SEX plus AGE, despite a lower percentage of accuracy. CONCLUSION: A Machine Learning approach can support NAFLD diagnosis and reduce health costs. The SVM algorithm is easy to apply and the necessary parameters are easily retrieved in databases.

Remnant cholesterol as a risk factor for cardiovascular, cancer or other causes mortality: A competing risks analysis.

BACKGROUND AND AIMS: Cardiovascular diseases (CVDis) are leading causes of morbidity and mortality. Even after the introduction of pharmacological therapy to lower Cholesterol, there is still a residual risk that may be ascribed to remnant cholesterol (RC). We aimed, by analyzing two prospective cohort studies, to estimate the effect of RC on risk and hazard of cardiovascular deaths (CVDs), while accounting for competing risks such as cancer (CDs) and other-causes deaths (OCDs). METHODS AND RESULTS: Cohorts were enrolled in 1992 and 2005. Personal data history was recorded. A fasting venous blood sample was obtained, and RC was calculated at baseline. Cause of Death was coded by using ICD-10th version. Follow-up ended on December 31, 2017. Flexible parametric competing-risks models were applied, with age at death as time-axis. In total, 5729 subjects were enrolled. There were 861 (15.1%) deaths: 234 CVDs (27.2%), 245 CDs (28.5%), 271 OCDs (31.5%) and 111 unknown causes of death (12.8%). RC exposure was a strong risk factor only for CVDs (Risk 2.54, 95% Confidence Interval 1.21; 5.34; Trend 1.26 (1.00; 1.58) for ≥1.29 mmol/L). CONCLUSIONS: RC is a strong independent risk factor for cardiovascular mortality. Competing risk analysis is demonstrably a useful tool to disentangle associations among different competing events with a common risk factor.

The Effect of Three Mediterranean Diets on Remnant Cholesterol and Non-Alcoholic Fatty Liver Disease: A Secondary Analysis.

BACKGROUND: Elevated fasting remnant cholesterol (REM-C) levels have been associated with an increased cardiovascular risk in patients with metabolic syndrome (Mets) and Non-Alcoholic Fatty Liver Disease (NAFLD). We aimed to estimate the effect of different diets on REM-C levels in patients with MetS, as well as the association between NAFLD and REM-C. METHODS: This is a secondary analysis of the MEDIDIET study, a parallel-arm Randomized Clinical Trial (RCT). We examined 237 people with MetS who underwent Liver Ultrasound (LUS) to assess the NAFLD score at baseline, 3-, and 6-months follow-up. Subjects were randomly assigned to the Mediterranean diet (MD), Low Glycemic Index diet (LGID), or Low Glycemic Index Mediterranean diet (LGIMD). REM-C was calculated as [total cholesterol-low density lipoprotein cholesterol (LDL-C)-high density lipoprotein cholesterol (HDL-C)]. RESULTS: REM-C levels were higher in subjects with moderate or severe NAFLD than in mild or absent ones. All diets had a direct effect in lowering the levels of REM-C after 3 and 6 months of intervention. In adherents subjects, this effect was stronger among LGIMD as compared to the control group. There was also a significant increase in REM-C levels among Severe NAFLD subjects at 3 months and a decrease at 6 months. CONCLUSIONS: fasting REM-C level is independently associated with the grade of severity of NAFLD. LGIMD adherence directly reduced the fasting REM-C in patients with MetS.

Effects of Some Food Components on Non-Alcoholic Fatty Liver Disease Severity: Results from a Cross-Sectional Study.

Background: The high prevalence of non-alcoholic fatty liver disease (NAFLD) observed in Western countries is due to the concurrent epidemics of overweight/obesity and associated metabolic complications, both recognized risk factors. A Western dietary pattern has been associated with weight gain and obesity, and more recently with NAFLD. Methods: This is a baseline cross-sectional analysis of 136 subjects (79 males) enrolled consecutively in the NUTRIATT (NUTRItion and Ac-TiviTy) study. Study subjects had moderate or severe NAFLD diagnosed by using Fibroscan-CAP. Food Frequency Questionnaire was used to obtain information about food intake. Statistical analysis included descriptive statistics and a multivariable logistic regression model. Results: The mean age was 49.58 (±10.18) with a mean BMI of 33.41 (±4.74). A significant inverse relationship was revealed between winter ice-cream intake and NAFLD severity (O.R. 0.65, 95% C.I. 0.95-0.99); chickpeas intake and NAFLD severity (O.R. 0.57, 95% C.I. 0.34-0.97), and not industrial aged-cheeses type (O.R. 0.85, 95% C.I. 0.74-0.98). A statistically significant positive association also emerged between rabbit meat (O.R. 1.23, 95% C.I. 1.01-1.49), industrial type aged cheeses (O.R. 1.17, 95% C.I. 1.01-1.35), milk-based desserts (no winter ice cream) (O.R. 1.11, 95% C.I. 1.01-1.21), fats (O.R. 1.12, 95% C.I. 1.01-1.25), and NAFLD severity. Conclusion: The fresh foods from non-intensive farming and high legume intake that characterize the Mediterranean diet would seem to be beneficial for patients with NAFLD.