Associations between exploratory dietary patterns and incident type 2 diabetes: a federated meta-analysis of individual participant data from 25 cohort studies

Dietary Modulations in Preventing Cardiometabolic Risk in Individuals with Type 2 Diabetes

PURPOSE OF REVIEW

Type 2 diabetes mellitus (T2DM) is a complex health issue include obesity, high cholesterol, high blood pressure, and chronic inflammation that increase the risk of cardiovascular diseases (CVDs). CVDs are of great concern in the disease progression and prognosis of T2DM. This review is a comprehensive examination of the literature on the relationship between T2DM and cardiovascular risk, nutrition-related cardiometabolic risk (CMR) factors, and impact of dietary modulations on CMR.

RECENT FINDINGS

In recent years the researches has been focus on the importance of a comprehensive treatment approach like dietary modulations to address multiple cardiovascular risk reductions, including hypertension and dyslipidemia. Modulation of dietary patterns are the most promising interventions to prevent CMR factors and T2DM via affecting the body weight, glucose control, and microbial diversity of individuals. Current evidence suggests that high-quality dietary patterns such as the Dietary Approaches to Stop Hypertension (DASH) eating plan and the Mediterranean diet is important in the metabolic control processes of T2DM with anti-inflammatory and antioxidant compounds, glucagon-like peptide agonist compounds, and intestinal microbiota changes. Nutrition plays a critical role in preventing and improving CVD outcomes in patients with T2DM. Dietary modulations should be planned considering individual differences in responses to dietary composition and nutritional changes, personal preferences, eating behaviors and gut microbiota differences.

Dietary Intake of (Poly)phenols and Risk of All-Cause and Cause-Specific Mortality in the Mexican Teachers' Cohort Study

BACKGROUND

Observational studies have reported that total (poly)phenol intake is associated with a reduction in all-cause and cardiovascular mortality, but mainly from high-income countries, where (poly)phenol intake may differ from that of low- and middle-income countries.

OBJECTIVES

Our objective was to evaluate the association between the intake of total, all classes, and subclasses of (poly)phenols and risk of all-cause and cause-specific mortality in a Mexican cohort.

METHODS

We used data from the Mexican Teachers' Cohort, which included 95,313 adult females. After a median follow-up of 11.2 y, 1725 deaths were reported, including 674 from cancer and 282 from cardiovascular diseases. (Poly)phenol intake was estimated using a validated food frequency questionnaire and the Phenol-Explorer database. Multivariable Cox models were applied to estimate the association between (poly)phenol intake and all-cause mortality and competitive risk models for cause-specific mortality.

RESULTS

Comparing extreme quartiles, total (poly)phenol intake was associated with lower risk of all-cause [hazard ratio (HR)Q4vs.Q1: 0.88; 95% CI: 0.76, 0.99; P-trend = 0.01] and cancer mortality (HRQ4vs.Q1: 0.81; 95% CI: 0.64, 0.99; P-trend = 0.02). Among (poly)phenol classes, phenolic acids, particularly hydroxycinnamic acids from coffee, showed an inverse association with all-cause (HRQ4vs.Q1: 0.79; 95% CI: 0.69, 0.91; P-trend = 0.002) and cancer mortality (HRQ4vs.Q1: 0.75; 95% CI: 0.61, 0.94; P-trend = 0.03). No associations were observed with flavonoids or with cardiovascular mortality.

CONCLUSION

Our study suggests that high (poly)phenol intake, primarily consisting of phenolic acids such as hydroxycinnamic acids, may have a protective effect on overall and cancer mortality. Null associations for flavonoid intake might be due to the potential underestimation of their intake in this population.

A Federated Database for Obesity Research: An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.

Accessibility of covariance information creates vulnerability in Federated Learning frameworks

MOTIVATION

Federated Learning (FL) is gaining traction in various fields as it enables integrative data analysis without sharing sensitive data, such as in healthcare. However, the risk of data leakage caused by malicious attacks must be considered. In this study, we introduce a novel attack algorithm that relies on being able to compute sample means, sample covariances, and construct known linearly independent vectors on the data owner side.

RESULTS

We show that these basic functionalities, which are available in several established FL frameworks, are sufficient to reconstruct privacy-protected data. Additionally, the attack algorithm is robust to defense strategies that involve adding random noise. We demonstrate the limitations of existing frameworks and propose potential defense strategies analyzing the implications of using differential privacy. The novel insights presented in this study will aid in the improvement of FL frameworks.

AVAILABILITY AND IMPLEMENTATION

The code examples are provided at GitHub (https://github.com/manuhuth/Data-Leakage-From-Covariances.git). The CNSIM1 dataset, which we used in the manuscript, is available within the DSData R package (https://github.com/datashield/DSData/tree/main/data).

MetS Prevalence and Its Association with Dietary Patterns among Chinese Middle-Aged and Elderly Population: Results from a National Cross-Sectional Study

The prevalence of metabolic syndrome (MetS) increased dramatically over the past years among adults in a separate province in China; little is known about newly diagnosed MetS in middle-aged and above residents nationwide. We investigated the prevalence of MetS and its components, the dietary patterns, and their relationship among the middle-aged and above population of China by using data from a national cross-sectional survey. General information involving lifestyles and health stations was collected, and dietary intake using a 3-day 24 h dietary recall and weighing method for edible oil and condiments was conducted. Height, weight, waist circumference, and blood pressure were measured, and fasting serum lipids and glucose were tested by trained clinical staff. Dietary patterns were derived from 23 food categories by using cluster analysis, and a multivariate logistic regression model was used to evaluate the odd ratio of MetS and its component across obtained dietary patterns. The estimated prevalence of MetS was 37.1% among 40,909 middle-aged and older participants in the study. Participants were classified into diversity pattern, northern pattern, and southern pattern that, respectively, accounted for 9.8%, 47.2%, and 43.0% of the total. Compared with those inclined to the northern pattern, participants prone to the southern pattern decreased the risk of MetS (OR = 0.81, 95%CI: 0.75- 0.87; p < 0.001), central obesity (OR = 0.70, 95%CI: 0.65−0.76; p < 0.001), and HDL-C (OR = 0.82, 95%CI: 0.76−0.89; p < 0.001), and elevated BP (OR = 0.86, 95%CI: 0.79−0.93; p < 0.001) respectively. However, participants of the southern pattern tended to have a higher risk of elevated glucose; the OR (95%CI) was 1.13 (1.05, 1.22; p = 0.002) after adjusting for potential confounding factors. Greater adherence to diverse dietary patterns was negatively related to the risk of central obesity and elevated blood pressure with an OR (95%CI) of 0.82 (0.71, 0.94; p = 0.005) and 0.77 (0.67, 0.88; p < 0.001), respectively. We concluded that dietary improvement and health promotion for MetS should be based on the district-specific nutritional status of the Chinese middle-aged and elderly population.