The World Health Organization (WHO) has recognized obesity as one of the top ten threats to human health. It is estimated that the number of obese and overweight people worldwide exceeds the number of those who are undernourished. Obesity is not only a state of abnormally increased adipose tissue in the body, but also of increased release of biologically active adipokines. Adipokines released into the circulating blood, due to their specific receptors on the surface of target cells, act as classic hormones affecting the metabolism of tissues and organs. What is more, adipokines and cytokines may decrease the insulin sensitivity of tissues and induce inflammation and development of chronic complications. Certainly, it can be stated that in an era of a global obesity pandemic, adipokines may gain more and more importance as regards their use in the diagnostic evaluation and treatment of diseases. An extensive search for materials on the role of white, brown and perivascular fatty tissue and obesity-related metabolic and chronic complications was conducted online using PubMed, the Cochrane database and Embase.

The term unmanned aerial vehicle (UAV) was post-applied in the 1980s to describe remotely piloted multi-purpose, unmanned, autonomous aircraft. The terms unmanned aircraft systems with data terminal connectivity (UAS) and remotely piloted aircraft systems (RPV, RPAS—military systems) are also used. This review aims to analyze the feasibility of using UAVs to support emergency medical systems in the supply and urgent care ranges. The implementation of drones in the medical security system requires proper planning of service cooperation, division of the area into sectors, assessment of potential risks and opportunities, and legal framework for the application. A systematic literature search was conducted to assess the applicability based on published scientific papers on possible medical drone applications in the field of urgent mode. The widespread applications of UAVs in healthcare are concerned with logistics, scope, and transportability, with framework legal constraints to effectively exploit opportunities for improving population health, particularly for costly critical situations.

The increase in type 1 diabetes mellitus (T1DM) incidence in children is worrying and not yet fully explored. It is suggested that probably air pollution exposure could contribute to the development of T1DM. The aim of the study was to investigate the relationship between the concentration of gaseous pollutants including, nitrogen dioxide (NO₂), nitric oxides (NOx), sulphur dioxide (SO₂), carbon monoxide (CO), and particulate matter (PM) in the air, and the number of new cases of T1DM in children. The number of new cases of T1DM was obtained from the Clinic of Paediatrics, Diabetology, and Endocrinology, Medical University of Gdańsk. The number of children of 0–18 years old in Pomeranian Voivodeship was acquired from the Statistical Yearbook. The concentrations of PM₁₀ absorbance, NO₂, NOx, SO₂, and CO were measured at 41 measuring posts, between 1 January 2015 and 31 December 2016. It was detected that the average annual concentration of PM₁₀ was higher than the value acceptable to the WHO. Furthermore, the average 24‐hour concentration of PM₁₀ was 92 μg/m³ and was higher compared to the acceptable value of 50 μg/m³ (acc. to EU and WHO). Moreover, the number of new cases of T1DM showed a correlation with the annual average concentration of PM₁₀ (β = 2.396, p < 0.001), SO₂ (β = 2.294, p < 0.001), and CO (β = 2.452, p < 0.001). High exposure to gaseous pollutants and particulate matter in ambient air may be one of the factors contributing to the risk of developing T1DM in children. Therefore, it is important to take action to decrease air pollutant emissions in Poland. It is crucial to gradually but consistently eliminate the use of solid fuels, such as coal and wood in households, in favour of natural gas and electricity. The development of new technologies to improve air quality, such as “best available techniques” (BAT) or renewable energy sources (water, wind, and solar generation) is of critical importance as well.

The aim of this study was to analyze the effectiveness of implementing an automated appointment confirmation system in a mental health clinic and to assess its impact on patient attendance, which may indirectly support the patient recovery process. The study was conducted at a mental health outpatient clinic in Gdańsk, Poland, and focused on medical appointments across three affiliated outpatient units. Data from 2019 and 2023 were compared, focusing particularly on the rate of missed appointments (relationship between number of visits that did not take place and total number of visits that were scheduled in the software), form return rates (the relationship between the number of forms returned by patients and the total number sent), and patient opinions regarding the usability of the new system. The results showed a significant reduction in no-show rates—from 18.55% to 7.01%—confirming the high effectiveness of the automated system. The form return rate reached 55.41%, with the highest engagement observed among individuals aged 35–44. Patient evaluation of the system was highly positive—over 93% found it intuitive and meeting their expectations. A proprietary software solution developed in Python, alongside databases and Microsoft Office Access/Excel tools, was used for data collection and analysis. The study demonstrated that a comprehensive approach, combining automated reminders with the ability for quick patient response and telephone support, is an effective tool for improving the accessibility and quality of healthcare services. The analysis also considered limitations related to digital barriers and identified directions for further research, including studies on how patient abstention from appointments affects their recovery process.

Background: The economic slowdown affects the population's health. Based on a social gradient concept, we usually assume that this detrimental impact results from a lower social status, joblessness, or other related factors. Although many researchers dealt with the relationship between economy and health, the findings are still inconsistent, primarily related to unemployment. This study reinvestigates a relationship between the economy's condition and health by decomposing it into macroeconomic indicators. Methods: We use data for 21 European countries to estimate the panel models, covering the years 1995–2019. Dependent variables describe population health (objective measures – life expectancy for a newborn and 65 years old, healthy life expectancy, separately for male and female). The explanatory variables primarily represent GDP and other variables describing the public finance and health sectors. Results: (1) the level of economic activity affects the population’s health – GDP stimulates the life expectancies positively; this finding is strongly statistically significant; (2) the unemployment rate also positively affects health; hence, increasing the unemployment rate is linked to better health – this effect is relatively short-term. Conclusions: Social benefits or budgetary imbalance may play a protective role during an economic downturn.