Studies in the alcohol consumption area are mostly related to the (ab)use of alcohol in young people. However, today, a growing number of researchers are emphasizing the clinical and public health significance of alcohol consumption in the elderly. In the WHO reports, harmful alcohol consumption is responsible for 5.3% of the global burden of the disease. The aim of this study was to investigate the prevalence of alcohol consumption among men and women aged 55 and over in Serbia and Hungary, leveraging data from the 2013 Serbian National Health Survey and from the 2014 Hungarian National Health Survey. Respondents aged 55 and over were analysed based on logistic multivariate models. The prevalence of alcohol consumption was 41.5% and 62.5% in Serbia and Hungary, respectively. It was higher among men in both countries, but among women, it was significantly higher in Hungary than in Serbia. The statistically significant predictors affecting alcohol consumption in Serbia included age, education, well-being index, long-term disease and overall health status, with marital status being an additional factor among men. In Hungary, education and long-term disease affected alcohol consumption in both sexes, while age and employment were additional factors among women. In both countries for both sexes, younger age, more significantly than primary education and good health, was associated with a higher likelihood of alcohol consumption.

The aim of our study was to predict the epidemic curves (daily new cases) of COVID-19 pandemic using Artificial Intelligence (AI)-based Recurrent Neural Networks (RNNs), then to compare and validate the predicted models with the observed data. We used the publicly available datasets from the World Health Organization and Johns Hopkins University to create a training dataset, then we used RNNs with gated recurring units (Long Short-Term Memory) to create two prediction models. Information collected in the first t time-steps were aggregated with a fully connected (dense) neural network layer and a consequent regression output layer to determine the next predicted value. We also used Root Mean Squared Logarithmic Errors (RMSLE) to compare the predicted models with the observed data. The result of our study underscores that the COVID-19 pandemic is a propagated source epidemic, therefore repeated peaks on the epidemic curve are to be anticipated. Besides, the errors between the predicted and validated data and trends seems to be low. The influence of this pandemic is significant worldwide and has already impacted our daily life. Decision makers must be aware, that even if strict public health measures are executed and sustained, future peaks of infections are possible.

Screen time among children in most European countries is notably high and is influenced by various sociodemographic and other factors. Our study aimed to explore the associations between parents’ sociodemographic characteristics, socioeconomic status, body mass index (BMI), physical activity, risk status for type 2 diabetes, and their children’s BMI, physical activity, and screen time. The data were sourced from the 2016 Feel4Diabetes study, involving 12,280 parents and 12,211 children aged 6–9 years (average age 8.21 years) in a cross-sectional study design. We used a logistic regression model to identify potential factors associated with children’s screen time. The results showed that mothers with tertiary education (OR = 0.64; 95%CI = 0.49–0.82; p < 0.001), the middle age group (45–54 years) (OR = 0.81 95%CI = 0.66–0.98; p = 0.033), and families with higher incomes (middle–OR = 0.85; 95%CI = 0.75–0.97; p = 0.014; high–OR = 0.8; 95%CI = 0.69–0.93; p = 0.003) were associated with a decreased chance of children spending more than 2 h/day in front of the screen. In contrast, maternal overweight/obesity (OR = 1.15; 95%CI = 1.03–1.29; p = 0.013) and lower physical activity in children were linked to an increased likelihood of more than 2 h of screen time per day. Our findings suggest that targeted interventions should be developed to mitigate excessive screen time, particularly focusing on low-income families and mothers with low educational levels.

Antimicrobial resistance (AMR) is an increasing public health problem worldwide. We studied some patient-related factors that might influence the antimicrobial resistance. and whether the volume of antibiotic prescribing of the primary care physicians correlate with the antibiotic resistance rates of commensal nasal Staphylococcus aureus and Streptococcus pneumoniae. The socio-demographic questionnaires, the antibiotic prescription and resistance data of commensal nasal S. aureus and S. pneumoniae were collected in the 20 participating Hungarian practices of the APRES study. Multivariate logistic regression analyses were performed on the patient-related data and the antimicrobial resistance of the S. aureus and S. pneumoniae on individual, patient level. Ecological analyses were performed with Spearman’s rank correlations at practice level, the analyses were performed in the whole sample (all practices) and in the cohorts of primary care practices taking care of adults (adult practices) or children (paediatric practices). According to the multivariate model, age of the patients significantly influenced the antimicrobial resistance of the S. aureus (OR = 0.42, p = 0.004) and S. pneumoniae (OR = 0.89, p < 0.001). Living with children significantly increased the AMR of the S. pneumoniae (OR = 1.23, p = 0.019). In the cohorts of adult or paediatric practices, neither the age nor other variables influenced the AMR of the S. aureus and S. pneumoniae. At practice level, the prescribed volume of penicillins significantly correlated with the resistance rates of the S. aureus isolates to penicillin (rho = 0.57, p = 0.008). The volume of prescribed macrolides, lincosamides showed positive significant correlations with the S. pneumoniae resistance rates to clarithromycin and/or clindamycin in all practices (rho = 0.76, p = 0.001) and in the adult practices (rho = 0.63, p = 0.021). The age is an important influencing factor of antimicrobial resistance. The results also suggest that there may be an association between the antibiotic prescribing of the primary care providers and the antibiotic resistance of the commensal S. aureus and S. pneumoniae. The role of the primary care physicians in the appropriate antibiotic prescribing is very important to avoid the antibiotic resistance.

Background: In 2020, globally 685,000 people died, and 2.3 million women were diagnosed with breast cancer. The main cause of cancer deaths among women is breast cancer, which account for 15.5% of all cancer deaths. Most of these could have been avoided with timely diagnosis.The aim of our study was to determine the proportion of breast screening participation in Hungary, and to identify possible factors that may influence breast screening attendance.Methods: Our data were gathered from the cross-sectional European Health Interview Surveys conducted in Hungary in 2009, 2014, and 2019. In terms of categorical characteristics, Pearson’s chi-square test was performed to evaluate the differences between people who have attended breast screening within two years and who have only attended more than two years ago. To determine the factors that may have an impact on the uptake of screening, generalized linear model with logit link function regarding binomial probability distribution was executed.Results: The responses of 2626 women between the age 45-65 were included in our study. In 2009 85% (n=741), in 2014 90% (n=851) and in 2019 87% (n=699) of the respondents claimed to have ever attended a breast screening in their life. In 2009 68% (n=594), in 2014 66% (n=630) and in 2019 64% (n=515) said that they have taken part in breast screening within two years (p=0.331). From 2014 to 2019 (AOR=0.72 [0.57-0.89]) the chance of attending breast screening was decreasing. We observed that both secondary (AOR=1.97 [1.60-2.44]) and tertiary educational level (AOR=2.23 [1.67-3.00]), higher perceived income (AOR=1.54 [1.25-1.90]), and more frequent meeting with the doctor (AOR=1.77 [1.39-2.27]) and with the specialist (AOR=1.88 [1.54-2.28]) appeared as protective factors of breast screening attendance.Conclusions: Our results show that the lifetime prevalence of breast screening participation is high, however the recommended biennial rate is relatively low. To increase the participation rate, various initiatives would be needed, especially for women in identified risk groups, which are lower educational level, lower perceived income, and less frequent meeting with the doctor and with the specialist.

The surface roughness, surface free energy (SFE) of composites, and composite wettability by dental adhesives are determining factors in achieving a strong and durable adhesion (e.g., composite repair, luting adhesively bonded indirect restorations). In this study, the SFE of one nanohydrid and two bulk-fill composites was investigated in relation to the wetting ability of five different dental adhesives. The profilometry and scanning electron microscopy (SEM) measurement justified that the sandblasting produced a significantly rough surface in which the different filler amounts, filler distribution, and resin-filler ratio participated. The SFE of the tested composite was between 45.65 and 49.07 mJ/m² regardless of surface treatment. Despite the similarity in SFE, the adhesives wet the surface of the composites in different ways that were between 16.01° and 35.10°. The contact angle of solvent-free dental adhesive was lower due to sandblasting supporting the micromechanical retention. Based on our results, it was found that sandblasting, the most frequently recommended surface treatment, does not change the surface energy but causes a change in the contact angle, which can be explained by the different surface tension of the dental adhesives. It was concluded that the dental adhesive parameters have a more important role in wettability.