BACKGROUND: Biological aging reflects a decline in the functions and integrity of the human body that is closely related to chronological aging. A variety of biomarkers have been found to predict biological age. Biological age higher than chronological age (biological age acceleration) indicates an accelerated state of biological aging and a higher risk of premature morbidity and mortality. This study investigated how socioeconomic disadvantages influence biological aging. METHODS: The data from the National Health and Nutrition Examination Survey (NHANES) IV, including 10 nationally representative cross-sectional surveys between 1999-2018, were utilized. The analytic sample consisted of N = 48,348 individuals (20-84 years). We used a total of 11 biomarkers for estimating the biological age. Our main outcome was biological age acceleration, indexed by PhenoAge acceleration (PAA) and Klemera-Doubal biological age acceleration (KDM-A). Poverty was measured as a ratio of family income to the poverty thresholds defined by the U.S. Census Bureau, adjusted annually for inflation and family size (5 categories). The PAA and KDM-A were regressed on poverty levels, age, their interaction, education, sex, race, and a data collection wave. Sample weights were used to make the estimates representative of the U.S. adult population. RESULTS: The results showed that higher poverty was associated with accelerated biological aging (PAA: unstandardized coefficient B = 1.38 p <.001, KDM: B = 0.96, p = .026 when comparing the highest and the lowest poverty level categories), above and beyond other covariates. The association between PAA and KDM-A and age was U-shaped. Importantly, there was an interaction between poverty levels and age (p <.001), as the effect of poverty was most pronounced in middle-aged categories while it was modest in younger and elderly groups. CONCLUSION: In a nationally representative US adult population, we found that higher poverty was positively associated with the acceleration of biological age, particularly among middle-aged persons.

• Klíčová slova
• Aging, Biological age, Biomarkers, Health inequalities, Poverty, Socioeconomic position,
• MeSH
• biologické markery MeSH
• chudoba * MeSH
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• průřezové studie MeSH
• senioři MeSH
• stárnutí * MeSH
• výživa - přehledy MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• senioři MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• biologické markery MeSH

The exposome concept encourages holistic consideration of the non-genetic factors (environmental exposures including lifestyle) that influence an individual's health over their life course. However, disconnect between the concept and practical application has promoted divergent interpretations of the exposome across disciplines and reinforced separation of the environmental (emphasizing exposures) and biological (emphasizing responses) research communities. In particular, while knowledge of biological responses can help to distinguish actual (i.e. experienced) from potential exposures, the inclusion of endogenous processes has generated confusion about the position of the exposome in a multi-omics systems biology context. We propose a reattribution of "exposome" to exclusively represent the totality of contact with external factors that a biological entity experiences, and introduce the term "functional exposomics" to denote the systematic study of exposure-phenotype interaction. This reoriented definition of the exposome allows a more readily integrable dataset for multi-omics and systems biology research.

• Klíčová slova
• Environmental health, Exposure assessment, Omics,
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

The prevalence of inequalities in the general health position of communities can be assessed by using selected determinants. The aims of this article are three-fold: (1) to apply a comprehensive approach to the assessment of inequalities in the general health position of communities, (2) to determine the spatial differentiation of determinants, and (3) to present selected assessment methods and their impact on the results. To present a quantitative assessment of these inequalities in health status in communities, a composite indicator (Health Index) was developed. This Health Index is composed of 8 areas of evaluation and 60 indicators which include, amongst others, determinants of health status and healthcare at district level (LAU 1) in the Czech Republic. The data are evaluated using multicriteria decision-making methods (the WSA and TOPSIS methods). Findings suggest that, when all eight domains are assigned the same weight of one, the spatial differentiation among the districts is similar when using both methods. If different weightings are assigned to the districts, changes occur in both the index values and the rankings of the analyzed districts. For example, the allocation of weightings in both methods results in a rearrangement of the ranking of districts for which the Health Index is around the average.

• Klíčová slova
• composite indicator, districts of the Czech Republic, health determinants and indicators, inequalities in health,
• MeSH
• poskytování zdravotní péče * MeSH
• socioekonomické faktory MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Česká republika epidemiologie   MeSH

Background: The paper aims to analyze the impact of key labor market indicators on the self-assessed health of the population of older workers (aged 55-64). Methods: Authors build the econometric models where the dependent variable is the self-perceived health status (for women and men separately). Explanatory variables are selected key indicators of the labor market, covering unemployment, including long-term, inactivity, or under-employment. The average household income is used to control the effect of wealth. Additionally, the models incorporate the variable describing the proximity of retirement. The research sample consists of nine countries of Central and Eastern Europe: Poland, Czech Republic, Slovakia, Hungary, Lithuania, Latvia, Estonia, Bulgaria, and Romania. Results and Conclusions: The study confirms that in the group of elderly workers, the perceived state of health is influenced by long-term unemployment, inactivity, and, in the case of women, time-related underemployment.

• Klíčová slova
• inactivity, key indicators of the labor market, self-perceived health, social determinants of health, unemployment,
• MeSH
• lidé MeSH
• senioři MeSH
• zdravotní stav * MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Bulharsko MeSH
• Česká republika MeSH
• Estonsko MeSH
• Litva MeSH
• Lotyšsko MeSH
• Maďarsko MeSH
• Polsko MeSH
• Rumunsko MeSH
• Slovenská republika MeSH