Prevalence of Type 2 Diabetes, Impaired Fasting Glucose, and Diabetes Risk in an Adult and Older North-Eastern Portuguese Population.

The aims of this study were (1) to evaluate the prevalence of type 2 diabetes (T2D) in a middle-aged north-eastern Portuguese population, (2) to analyze the prevalence of impaired fasting glucose (IFG), and (3) to assess the risk of T2D in this community-based sample. An exploratory, retrospective, and cross-sectional study was conducted from a total of 6570 individuals aged 18-102 years, among which 3865 were women (57.4 ± 18.1 years) and 2705 were men (60.0 ± 16.8 years). T2D diagnosis, IFG, and the diabetes risk score (low to very high risk) were assessed. The prevalence of T2D in this adult and an older north-eastern Portuguese population was 17.4%. A higher prevalence of T2D was reported in men (22.2%) than in women (14.0%); however, this was without significant differences (p = 0.086). Otherwise, the prevalence of T2D was significantly different among the age groups and increased with age (p < 0.001). Regarding IFG, a higher percentage of cases was observed in men (14.1%) than in women (8.4%) (p < 0.001). The risk of developing T2D in the next 10 years showed an association with sex and age group (p < 0.001) with a small-to-moderate effect (V = 0.1-0.3). Men and the elderly had the highest percentage of cases in the moderate-to-very high-risk bands. The current research confirmed a higher prevalence of T2D, IFG, and diabetes risk than previous Portuguese epidemiological reports. The results also suggest potential prediabetes cases, which should be carefully monitored. The current research adds evidence to the worldwide trend of the increasing prevalence of T2D and intermediate hyperglycemia (i.e., prediabetes).

Validation of StepTest4all for Assessing Cardiovascular Capacity in Young Adults.

BACKGROUND: Cardiovascular capacity, expressed as maximal oxygen uptake (VO2max), is a strong predictor of health and fitness and is considered a key measure of physiological function in the healthy adult population. The purpose of this study was to validate a specific step test (StepTest4all) as an adequate procedure to estimate cardiovascular capacity in young adults. METHODS: The sample was composed of 56 participants, including 19 women (aged 21.05 ± 2.39 years, body mass = 57.50 ± 6.64 kg, height = 1.62 ± 0.05 m, body mass index = 22.00 ± 2.92 kg/m2) and 37 men (aged 22.05 ± 3.14 years, body mass = 72.50 ± 7.73 kg, height = 1.76 ± 0.07 m, body mass index = 23.34 ± 2.17 kg/m2). Participants were included in one of the following groups: (i) the group used to predict the VO2max, and (ii) the group used to validate the prediction model. All participants performed the StepTest4all protocol. The step height and the intensity of the effort was determined individually. Heart rate and oxygen uptake were measured continuously during rest, effort, and recovery phases. The validation process included the following three stages: (i) mean data comparison, (ii) simple linear regression, and (iii) Bland-Altman analysis. RESULTS: The linear regression retained, as significant predictors of the VO2max, sex (p < 0.001) and heart rate recovery for one minute (p = 0.003). The prediction equation revealed a high relationship between measurements (R2 = 63.0%, SEE = 5.58). The validation procedure revealed non-significant differences (p > 0.05) between the measured and estimated maximal oxygen uptake, high relationship (R2 = 63.3%), and high agreement with Bland-Altman plots. Thus, VO2max can be estimated with the formula: VO2max = 22 + 0.3 · (HRR1min) + 12 · (sex), where HRR1min is the magnitude of the HR decrease (bpm) in one minute immediately after the step was stopped, and sex: men = 1, women = 0. CONCLUSIONS: The StepTest4all is an adequate procedure to estimate cardiovascular capacity, expressed as VO2max, in young adults. In addition, it is possible to determine the qualitative level of cardiovascular capacity from the heart rate recovery for one minute, more specifically, poor: <20, moderate: 20 to 34, good: 35 to 49, and excellent: ≥50. This procedure has the benefit of being simple to apply and can be used by everyone, even at home, without specialist supervision.

Structural Equation Modelling for Predicting the Relative Contribution of Each Component in the Metabolic Syndrome Status Change.

Understanding the factor weighting in the development of metabolic syndrome (MetS) may help to predict the progression for cardiovascular and metabolic diseases. Thus, the aim of this study was to develop a confirmatory model to describe and explain the direct and indirect effect of each component in MetS status change. A total of 3581 individuals diagnosed with MetS, aged 18−102 years, were selected between January 2019 and December 2020 from a community-representative sample of Portuguese adults in a north-eastern Portuguese region to test the model's goodness of fit. A structural equation modelling (SEM) approach and a two-way ANOVA (age × body composition) were performed to compare the relative contribution of each MetS component using joint interim statement (JIS). Waist circumference (ß = 0.189−0.373, p < 0.001), fasting glucose (ß = 0.168−0.199, p < 0.001) and systolic blood pressure (ß = 0.140−0.162, p < 0.001) had the highest direct effect on the change in MetS status in the overall population and concerning both sexes. Moreover, diastolic blood pressure (DBP), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-c) had a low or non-significant effect. Additionally, an indirect effect was reported for age and body composition involving the change in MetS status. The findings may suggest that other components with higher specificity and sensitivity should be considered to empirically validate the harmonised definition of MetS. Current research provides the first multivariate model for predicting the relative contribution of each component in the MetS status change, specifically in Portuguese adults.