From genomes to societies: a holistic view of determinants of human health

A holistic model of health inequalities for health policy and state administration: a case study in the regions of the Czech Republic

BACKGROUND

Health inequities exist within and between societies at different hierarchical levels. Despite overall improvements in health status in European Union countries, disparities persist among socially, economically, and societally disadvantaged individuals. This study aims to develop a holistic model of health determinants, examining the complex relationship between various determinants of health inequalities and their association with health condition.

METHODS

Health inequalities and conditions were assessed at the territorial level of Local Administrative Units (LAU1) in the Czech Republic. A dataset of 57 indicators was created, categorized into seven determinants of health and one health condition category. The necessary data were obtained from publicly available databases. Comparisons were made between 2001-2003 and 2016-2019. Various methods were employed, including composite indicator creation, correlation analysis, the Wilcoxon test, aggregate index calculation, cluster analysis, and data visualization using the LISA method.

RESULTS

The correlation matrix revealed strong relationships between health inequality categories in both periods. The most significant associations were observed between Economic status and social protection and Education in the first period. However, dependencies weakened in the later period, approaching values of approximately 0.50. The Wilcoxon test confirmed variations in determinant values over time, except for three specific determinants. Data visualization identified persistently adverse or worsening health inequalities in specific LAU1, focusing on categories such as Economic status and social protection, Education, Demographic situation, Environmental status, Individual living status, and Road safety and crime. The health condition indices showed no significant change over time, while the aggregate index of health inequalities improved with widened differences.

CONCLUSION

Spatial inequalities in health persist in the Czech Republic, influenced by economic, social, demographic, and environmental factors, as well as local healthcare accessibility. Both inner and outer peripheries exhibit poor health outcomes, challenging the assumption that urban areas fare better. The combination of poverty and vulnerabilities exacerbates these inequalities. Despite the low rates of social exclusion and poverty, regional health inequalities persist in the long term. Effectively addressing health inequalities requires interdisciplinary collaboration and evidence-based policy interventions. Efforts should focus on creating supportive social and physical environments, strengthening the healthcare system, and fostering cooperation with non-medical disciplines.

Impact of a Culturally Grounded Running Program on Four Components of Wellness Among Indigenous Participants: A Pilot Study of the Running Medicine Program

Movement as medicine is the premise behind Running Medicine (RM), a community-based wellness program that began in 2016 in New Mexico. RM is centered in the Indigenous traditions of running and is oriented to improving the four dimensions of wellness-mind, body, spirit, and social. Using retroactive surveys of RM's Spring 2019 participants, we investigated the program's effectiveness in the realms of physical, mental, spiritual, and social wellness. Based on data from participant surveys, RM appears to be effective at improving the four realms of wellness. Indigenous participants improved to a greater degree in mental and social wellness than non-Indigenous participants, while the opposite was true for physical and spiritual wellness. For both groups, the largest effect size among the four domains was seen in social wellness. Among our participants, this culturally grounded approach to wellness appears to be effective at improving the four realms of physical, mental, spiritual, and social wellness.

Deep learning in systems medicine

Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promise in this endeavour. This review paper addresses the main developments of DL algorithms and a set of general topics where DL is decisive, namely, within the SM landscape. It discusses how DL can be applied to SM with an emphasis on the applications to predictive, preventive and precision medicine. Several key challenges have been highlighted including delivering clinical impact and improving interpretability. We used some prototypical examples to highlight the relevance and significance of the adoption of DL in SM, one of them is involving the creation of a model for personalized Parkinson's disease. The review offers valuable insights and informs the research in DL and SM.

Atorvastatin Inhibits Endothelial PAI-1-Mediated Monocyte Migration and Alleviates Radiation-Induced Enteropathy

Intestinal injury is observed in cancer patients after radiotherapy and in individuals exposed to radiation after a nuclear accident. Radiation disrupts normal vascular homeostasis in the gastrointestinal system by inducing endothelial damage and senescence. Despite advances in medical technology, the toxicity of radiation to healthy tissue remains an issue. To address this issue, we investigated the effect of atorvastatin, a commonly prescribed hydroxy-3-methylglutaryl-coenzyme A reductase inhibitor of cholesterol synthesis, on radiation-induced enteropathy and inflammatory responses. We selected atorvastatin based on its pleiotropic anti-fibrotic and anti-inflammatory effects. We found that atorvastatin mitigated radiation-induced endothelial damage by regulating plasminogen activator inhibitor-1 (PAI-1) using human umbilical vein endothelial cells (HUVECs) and mouse model. PAI-1 secreted by HUVECs contributed to endothelial dysfunction and trans-endothelial monocyte migration after radiation exposure. We observed that PAI-1 production and secretion was inhibited by atorvastatin in irradiated HUVECs and radiation-induced enteropathy mouse model. More specifically, atorvastatin inhibited PAI-1 production following radiation through the JNK/c-Jun signaling pathway. Together, our findings suggest that atorvastatin alleviates radiation-induced enteropathy and supports the investigation of atorvastatin as a radio-mitigator in patients receiving radiotherapy.