The study applies the fuzzy approach to measuring material deprivation from a multidimensional perspective. By taking into account the intensity of deprivation this approach goes beyond the conventional research using the deprived/non-deprived dichotomy. The study is based on the European Union Statistics on Income and Living Conditions data including a set of nine-item material deprivation indicators adopted by all European Union countries. In order to examine the effects of social reforms introduced by the Polish government in 2016, it focuses on the situation of Polish households in 2015 and 2017. The study aims to identify correlates of material deprivation in Poland using the zero-inflated beta regression model. This model enables to understand the mechanisms behind the risk and the intensity of material deprivation. Moreover, the study provides evidence that households with at least three children experienced meaningful improvement during the studied period. This is probably due to the introduction of the ‘Family 500+’ programme supporting mainly large families.

The study aims to assess household energy poverty in European Union (EU) countries, comparing them based on the Objective Energy Poverty Index and the Subjective Energy Poverty Index. The Objective Energy Poverty Index is derived from indicators such as energy expenditure share, risk-of-poverty rate, and electricity prices. The Subjective Energy Poverty Index includes indicators such as the inability to keep the home adequately warm, arrears on utility bills, and bad housing conditions. Both indices aggregate the indicators mentioned above using equal and non-equal weighting approaches. The analysis uses country-level data from 2019 to 2023 sourced from Eurostat. The findings indicate considerable variation in household energy poverty across the EU, with more pronounced inequalities in subjective indicators than objective ones. Additionally, the study reveals a weak correlation between the Objective Energy Poverty Index and the Subjective Energy Poverty Index, leading to differing country rankings based on these indices. However, the choice of weights in constructing the energy poverty indices does not significantly impact a country’s energy poverty ranking. The paper also identifies countries where household energy poverty decreased in 2023 compared to 2019 and those where it increased. Regarding the Subjective Energy Poverty Index, Croatia and Hungary showed the most notable improvement in their rankings among European countries, while France, Germany, and Spain deteriorated their positions. According to the Objective Energy Poverty Index, Bulgaria, Croatia, Portugal, and Spain demonstrated the most significant improvement, whereas Greece experienced a considerable decline.

While food insecurity (FI) has been extensively studied in many countries, there have been few empirical contributions in Poland to date. The main objective of our research was to identify the socio-demographic factors affecting the risk of FI in Poland within 2014–2019. Moreover, we aimed to examine the effects of the family-oriented social program “Family 500+” by comparing the situation in various types of households with children a few years before and after the program was launched. The analysis was based on the set of eight-item FI indicators adopted by the Food and Agriculture Organization using the Gallup World Poll nationally representative survey data. Based on our results the most vulnerable groups in the context of FI were identified. We confirmed the importance of education, gender, age, marital status, household composition, status of employment and income in preventing FI. The effectiveness of the support program in reducing FI was demonstrated as households with at least three children experienced significant improvement in the FI status during the studied years. These findings should be especially important in the context of the impact of the COVID-19 pandemic on FI. As FI can affect the quality and quantity of food choices it is associated with a poorer health status, which increases the risk of infection, including COVID-19, and worsens recovery prognosis. Planning an efficient response to the pandemic requires a comprehension of the increased risk of exposure experienced by people, especially those who are food insecure.

Research on household energy poverty is crucial for addressing basic human needs, highlighting the importance of conducting studies across different countries. This study examines energy poverty in the Visegrad Group countries using 2022 data from the EU Statistics on Income and Living Conditions survey, with the ‘inability to keep the home warm’ indicator as a measure. The study aims to identify socio-economic factors influencing energy poverty and examine how their impacts differ across the examined countries. Logistic regression, combined with machine learning techniques, was applied for this purpose. Furthermore, the study evaluates the classification results of logistic regression and three machine learning methods—CatBoost, Balanced Random Forests, and Extreme Gradient Boosting—on imbalanced data. It was found that, among the three machine learning methods used, Balanced Random Forests performed the weakest. Logistic regression, effective for our imbalanced data, complements the results and provides deeper insights into the socio-economic factors influencing energy poverty. The study found that Slovakia had the highest percentage of households vulnerable to energy poverty, while Czechia had the lowest. Income, household type, and the presence of disabled individuals were found to be important across all countries. However, other factors varied in their influence from one country to another, highlighting the need for country-specific analyses. Monitoring households’ exposure to energy poverty is a challenge for future social policy and the use of different methods provides an in-depth view of this complex issue.

Food insecurity (FI) remains a challenge not only in less-developed countries but also worldwide. The literature indicates higher rates of FI for women than men in some regions of the world. Thus, the main objective of this cross-sectional study was to assess differences in experiencing FI according to gender in Central-Eastern Europe—a region that has been little researched in terms of FI. The study analyzes individual-level data on FI from the Gallup World Poll (GWP) for the years 2018–2019, obtained under a license from the Food and Agriculture Organization (FAO). Dataset encompasses representative samples of individuals aged 15 and above for each studied country. Apart from bivariate analysis, the ordered logistic regression, the generalized ordered logistic regression and multinomial logistic regression models were used. It was found that women experienced mild FI more often than men. However, gender differences with respect to moderate or severe FI were not confirmed. Moreover, the significant associations of all severity levels of FI with education, employment status, social capital, social network, age, marital status, household composition and income were observed. The research findings can be used to inform policy and to design targeted assistance programs for those in need.