Association of socioeconomic disadvantage and ethnicity with perinatal neonatal, and infant mortality in Slovakia.

BACKGROUND: Infant mortality rates are reliable indices of the child and general population health status and health care delivery. The most critical factors affecting infant mortality are socioeconomic status and ethnicity. The aim of this study was to assess the association between socioeconomic disadvantage, ethnicity, and perinatal, neonatal, and infant mortality in Slovakia before and during the COVID-19 pandemic. METHODS: The associations between socioeconomic disadvantage (educational level, long-term unemployment rate), ethnicity (the proportion of the Roma population) and mortality (perinatal, neonatal, and infant) in the period 2017-2022 were explored, using linear regression models. RESULTS: The higher proportion of people with only elementary education and long-term unemployed, as well as the higher proportion of the Roma population, increases mortality rates. The proportion of the Roma population had the most significant impact on mortality in the selected period between 2017 and 2022, especially during the COVID-19 pandemic (2020-2022). CONCLUSIONS: Life in segregated Roma settlements is connected with the accumulation of socioeconomic disadvantage. Persistent inequities between Roma and the majority population in Slovakia exposed by mortality rates in children point to the vulnerabilities and exposures which should be adequately addressed by health and social policies.

Medically Attended Injuries among Slovak Adolescents: Relationships with Socio-Economic Factors, Physical Fighting, and Physical Activity.

There is a worrisome increase in the reporting of medically attended injuries in Slovak adolescents. The aim of this study is to examine the relationships between socio-economic factors, physical fighting, and physical activity with frequency of medically attended injuries among this population group. Data from 8902 adolescents participating in the Health Behavior in School-Aged Children study were used (mean age 13.37; 50.9% boys). The effects of family affluence, registered unemployment rate, average nominal monthly earnings of employees, physical fighting, and physical activity on frequency of medically attended injury were explored using linear regression analysis. Pearson's correlation was used to describe the associations between all selected variables. The selected model of linear regression explained 15.8% of the variance in the frequency of medically attended injuries. All variables except the registered unemployment rate showed linear positive relationships with medically attended injuries. The correlation analysis confirmed linear positive associations between medically attended injuries and physical fighting, family affluence, physical activity, and average nominal monthly earnings of employees. Further research on these variables is needed in the Slovak context. This may include analyses of the nature of the relationships between socio-economic factors and medically attended injuries, as well as systematic evaluation of applied physical fighting and physical-activity-related injury interventions to support evidence-based policy making.

Mortality in the Visegrad countries from the perspective of socioeconomic inequalities.

OBJECTIVES: Large socioeconomic inequalities in health are still present in the Central Europe. The aim was to explore socioeconomic inequalities in mortality in Visegrad countries-the Czech Republic, Hungary, Poland and Slovakia (V4), by three different socioeconomic indicators (unemployment, risk of poverty/social exclusion, education). The study was conducted within the H2020 Euro-Healthy project. METHODS: The associations between selected socioeconomic indicators and the standardised mortality rates by four main causes (mortality related to cancer, circulatory, respiratory and digestive system) in the economically active population aged 20-64 years in the 35 NUTS 2 level regions of the V4 in the period 2011-2013 were explored, using linear regression models. RESULTS: Lower education level was the most significant predictor of mortality in the V4. The lowest mortality rates by all causes of death were found in the regions of the Czech Republic, the highest in regions of Hungary. CONCLUSIONS: Despite the common origin, the pathways of the V4 countries in employment, poverty and education seem to be different, also having impact on health equity. Therefore, where you live in the V4 can significantly influence your health.

Regional mortality by socioeconomic factors in Slovakia: a comparison of 15 years of changes.

BACKGROUND: Like most Central European countries Slovakia has experienced a period of socioeconomic changes and at the same time a decline in the mortality rate. Therefore, the aim is to study socioeconomic factors that changed over time and simultaneously contributed to regional differences in mortality. METHODS: The associations between selected socioeconomic indicators and the standardised mortality rate in the population aged 20-64 years in the districts of the Slovak Republic in the periods 1997-1998 and 2012-2013 were analysed using linear regression models. RESULTS: A higher proportion of inhabitants in material need, and among males also lower income, significantly contributed to higher standardised mortality in both periods. The unemployment rate did not contribute to this prediction. Between the two periods no significant changes in regional mortality differences by the selected socioeconomic factors were found. CONCLUSIONS: Despite the fact that economic growth combined with investments of European structural funds contributed to the improvement of the socioeconomic situation in many districts of Slovakia, there are still districts which remain "poor" and which maintain regional mortality differences.

Inequalities in mortality by socioeconomic factors and Roma ethnicity in the two biggest cities in Slovakia: a multilevel analysis.

BACKGROUND: The socioeconomic and ethnic composition of urban neighbourhoods may affect mortality, but evidence on Central European cities is lacking. The aim of this study was to assess the associations between socioeconomic and ethnic neighbourhood indicators and the mortality of individuals aged 20-64 years old in the two biggest cities of the Slovak Republic. METHODS: We obtained data on the characteristics of neighbourhoods and districts (educational level, unemployment, income and share of Roma) and on individual mortality of residents aged 20-64 years old, for the two largest cities in the Slovak Republic (Bratislava and Kosice) in the period 2003-2005. We performed multilevel Poisson regression analyses adjusted for age and gender on the individual (mortality), neighbourhood (education level and share of Roma in population) and district levels (unemployment and income). RESULTS: The proportions of Roma and of low-educated residents were associated with mortality at the neighbourhood level in both cities. Mutually adjusted, only the association with the proportion of Roma remained in the model (risk ratio 1.02; 95 % confidence interval 1.01-1.04). The area indicators - high education, income and unemployment - were not associated with mortality. CONCLUSION: The proportion of Roma is associated with early mortality in the two biggest cities in the Slovak Republic.

Socioeconomic inequalities in mortality in 16 European cities.

AIMS: To explore inequalities in total mortality between small areas of 16 European cities for men and women, as well as to analyse the relationship between these geographical inequalities and their socioeconomic indicators. METHODS: A cross-sectional ecological design was used to analyse small areas in 16 European cities (26,229,104 inhabitants). Most cities had mortality data for a period between 2000 and 2008 and population size data for the same period. Socioeconomic indicators included an index of socioeconomic deprivation, unemployment, and educational level. We estimated standardised mortality ratios and controlled for their variability using Bayesian models. We estimated relative risk of mortality and excess number of deaths according to socioeconomic indicators. RESULTS: We observed a consistent pattern of inequality in mortality in almost all cities, with mortality increasing in parallel with socioeconomic deprivation. Socioeconomic inequalities in mortality were more pronounced for men than women, and relative inequalities were greater in Eastern and Northern European cities, and lower in some Western (men) and Southern (women) European cities. The pattern of excess number of deaths was slightly different, with greater inequality in some Western and Northern European cities and also in Budapest, and lower among women in Madrid and Barcelona. CONCLUSIONS: In this study, we report a consistent pattern of socioeconomic inequalities in mortality in 16 European cities. Future studies should further explore specific causes of death, in order to determine whether the general pattern observed is consistent for each cause of death.

Socioeconomic inequalities in injury mortality in small areas of 15 European cities.

This study analysed socioeconomic inequalities in mortality due to injuries in small areas of 15 European cities, by sex, at the beginning of this century. A cross-sectional ecological study with units of analysis being small areas within 15 European cities was conducted. Relative risks of injury mortality associated with the socioeconomic deprivation index were estimated using hierarchical Bayesian model. The number of small areas varies from 17 in Bratislava to 2666 in Turin. The median population per small area varies by city (e.g. Turin had 274 inhabitants per area while Budapest had 76,970). Socioeconomic inequalities in all injury mortality are observed in the majority of cities and are more pronounced in men. In the cities of northern and western Europe, socioeconomic inequalities in injury mortality are found for most types of injuries. These inequalities are not significant in the majority of cities in southern Europe among women and in the majority of central eastern European cities for both sexes. The results confirm the existence of socioeconomic inequalities in injury related mortality and reveal variations in their magnitude between different European cities.

End-stage renal disease among Roma and non-Roma: Roma are at risk.

OBJECTIVES: Ethnic differences in the occurrence of end-stage renal disease (ESRD) are reported on various populations across the world, but evidence on Roma is lacking. The aim of this study was to explore the relative risk (RR) of ESRD for Roma who constitute a major minority in Slovakia. METHODS: Patients treated by means of hemodialysis during 2005-2008 were questioned for their ethnicity. Rates of ESRD among Roma and non-Roma based on hemodialysis data were calculated as well as the RR of Roma for ESRD. The latter was repeated after standardization for differences in age of both populations. RESULTS: Roma represented 11.6 % of all hemodialyzed patients. The RR of ESRD for Roma was 1.34, compared to the majority population. After age standardization, the RR for Roma was 2.85. CONCLUSION: This study shows that the risk for ESRD is significantly higher for Roma than for non-Roma. A genetic propensity of Roma to renal failure may partially explain the higher risk. Moreover, a poorer control of risk factors for ESRD in Slovak Roma contributes to the increased risk.

Socioeconomic factors, ethnicity and alcohol-related mortality in regions in Slovakia. What might a tree analysis add to our understanding?

Regional differences in alcohol-related mortality might reflect strong socioeconomic differences between regions. The present study examines the contribution of education, unemployment, income and minority proportion on regional differences in alcohol-related mortality for inhabitants aged 20-64 years. Linear regression analysis and a non-parametric regression tree analysis were used separately for males and females. The unemployment rate and low education appeared as important determinants of regional alcohol-related mortality, while the proportion of Roma and income were not significantly associated with alcohol-related mortality among males in Slovak districts. A district's unemployment rate was assumed to be the strongest predictor of the outcome measure.

Regional socioeconomic indicators and ethnicity as predictors of regional infant mortality rate in Slovakia.

OBJECTIVE: Exploring the associations of regional differences in infant mortality with selected socioeconomic indicators and ethnicity could offer important clues for designing public health policy measures. METHODS: Data included perinatal and infant mortality in the 79 districts of the Slovak population in 2004. Linear regression was used to analyse the contribution of education, unemployment, income and proportion of Roma population on regional differences in perinatal and infant mortality rates. RESULTS: All the explored socioeconomic indicators and ethnicity individually contributed significantly to both perinatal and infant mortality, with the exception of income. In the model exploring the influence of all these variables together on perinatal and infant mortality, only the effect of the proportion of Roma population remained significant. This model explained 34.9% of the variance for perinatal and 36.4% of the variance for infant mortality. CONCLUSIONS: Living in Roma settlements indicates an accumulation of socioeconomic disadvantage. Health literacy, health-related behaviour and many other factors might contribute to the explanation of the differences in infant mortality, and a better understanding of these processes might help us to design tailored interventions.

Socioeconomic indicators and ethnicity as determinants of regional mortality rates in Slovakia.

OBJECTIVES: Regional differences in mortality might reflect socioeconomic and ethnic differences between regions. The present study examines the relationship between education, unemployment, income, Roma population and regional mortality in the Slovak Republic. METHODS: Separately for males and females, data on standardised mortality in the Slovak population aged 20-64 years in the year 2002 were calculated for each of the 79 districts. Similarly the proportions of respondents with tertiary education, unemployed status, Roma ethnicity and income data were calculated per district. A linear regression model was used to analyse the data. RESULTS: Socioeconomic differences in regional mortality were found among males, but not among females. While education and unemployment rate significantly contributed to mortality differences between regions, income and the proportion of Roma population did not. The model explained 32.9% of the variance in standardised mortality rate among districts for males and 7.6% for females. CONCLUSION: Low education and high unemployment rate seems to be an indicator of regions with high mortality of male and therefore should be targeted by policy measures aimed at decreasing mortality in productive age.