Flavonoids are a key class of polyphenols, i.e., phytochemical compounds present in foods and beverages, which have been described as having health benefits in preventing several chronic diseases. Estimating flavonoid intake has already been conducted in several countries but has yet to be performed in Portugal. This study included 5005 participants aged 3–84 years and aimed to estimate dietary flavonoid intake in the Portuguese population, using data from the National Food and Physical Activity Survey 2015–2016, providing information on intake, main food contributors and the socio-demographic factors associated with the intake. Food intake data from the survey was converted to flavonoid intake using a database built to include the most updated USDA databases on flavonoids, isoflavones and proanthocyanidins and the Phenol-Explorer database. The rationale for combining food consumption data and different flavonoid databases using the FoodEx2 classification system was established. Linear regressions assessed the associations between socio-demographic factors and dietary flavonoid intake. The total flavonoid intake of the Portuguese population was estimated to be 107·3 mg/d. Flavanols were the most representative subclass, followed by flavonols, anthocyanidins, flavanones, flavones and isoflavones. Fruits and vegetables were the primary food contributors, providing 31·5 % and 12·4 % of the total flavonoid intake. Adolescents had the lowest total flavonoid intake, and older adults had the highest. This study provides information on the Portuguese population’s dietary flavonoids, allowing for international comparisons. It can also streamline forthcoming investigations into the link between flavonoid consumption and its impact on health, contributing to the future establishment of dietary reference values.

Introduction: Free sugar (FS) intake is linked to obesity, but most evidence is cross-sectional. Few studies have explored early-life FS intake trajectories with later cardiometabolic risk markers (CRM). Aim: To estimate associations between the trajectories of FS intake and CRM during childhood using a longitudinal and cross-sectional analysis and two dietary assessment methods. Methodology: Participants are from the G21 cohort evaluated at 4, 7, 10, and 13y. Dietary intake was assessed through food diaries and food frequency questionnaries (FFQ). FS was measured using a 10-step adapted methodology based on the WHO definition. CRM analyzed included BMI, waist circumference (WC), HOMA-IR, HDL, triglycerides, and systolic blood pressure. Linear mixed-effect models were used to estimate cross-sectional and longitudinal associations between FS trajectories, and CRM. Two regression models were considered: model 1 (crude) and model 2 (adjusted for parity, mothers’ education, mothers’ weight pre-pregnancy, breastfeeding, physical activity, weight for gestational age, and energy intake). Results: Considering data from food diaries and after adjustment, the longitudinal analysis presented positive significant associations between FS intake(/10 g) and CRM, particularly within adiposity variables: BMI (β = 0.044, 95%CI = 0.000;0.088), WC (β = 0.240 95%CI = 0.093;0.386) and HOMA (β = 0.015, 95%CI = 0.003;0.028). In contrast, cross-sectional analyses showed negative associations for the same variables. When using data from FFQ similar results were observed as in diaries. A sensitivity analysis only in plausible reporters supported the previous results in both epidemiological approaches. Conclusion: This study supports the adverse effects of FS on CRM during childhood, independently of the dietary assessment method. Longitudinal approaches are relevant to obtaining accurate associations.

This study aims to explore the relationship between the Diet Sustainability Score (DSS) and health outcomes, specifically body mass index (BMI) and waist-to-height ratio (WHtR). Using data from 2287 Portuguese adults in the National Food, Nutrition, and Physical Activity Survey (IAN-AF 2015–2016), DSS was calculated based on four dimensions: health-related nutritional attributes, environmental impact, economic affordability, and sociocultural acceptability. Logistic regression models were used to analyse associations between DSS and general adiposity (BMI classes: under/normal weight vs. overweight/obesity) and central adiposity (WHtR classes: healthy vs. unhealthy central adiposity). Models were adjusted for sex, age, education and physical activity level to control for potential confounders. Higher DSS is associated with reduced odds of overweight/obesity (OR = 0.91, 95%CI: 0.88, 0.94), and unhealthy central adiposity (OR = 0.91, 95%CI: 0.87, 0.95), suggesting that more sustainable dietary patterns are associated with more favourable adiposity profiles. This study highlights the importance of promoting sustainable diets as part of public health strategies aimed at addressing obesity and integrating health, environmental, economic, and sociocultural dimensions for more comprehensive, long-term population health improvements.

Luxembourg, known for its immigration history, attracts immigrants to work. This study analyses different immigrant groups in the labour market from 2014 to 2022 by using Labor Force Survey (LFS) data, Symbolic Data Analysis (SDA), and the Monitoring the Evolution of Clusters (MEC) framework. Based on the birthplace and length of residence in Luxembourg, in each year, microdata were aggregated into 21 symbolic objects. They were primarily described by 16 modal variables which are multi-valued variables with a frequency attached to each category. Moreover, clustering using complete linkage and the Chernoff’s distance was applied. The Heuristic Identification of Noisy Variables (HINoV) suggested that with just six variables, objects may be grouped homogeneously. The MEC framework traced temporal relations and transitions between the clusters, revealing some movements across the different years. Results indicate that people from the European Union (EU) and Neighbouring countries have similar profiles while the Portuguese have opposite characteristics. The Luxembourgers are somewhere in between. Profiling people from non-EU countries was challenging. The data and methodology used make it easy to replicate the work in other nations, enabling comparison of results and monitoring to continue in the future.