Our aim is to investigate if sex and gender influence the association of hypertension and their comorbidities. We investigated how gender differences in five socioeconomic factors impact the relation between hypertension and ten comorbidities including diabetes mellitus, renal disease, and chronic pulmonary disease in European countries grouped by their gender inequality index using representative survey data from the European Health Interview Survey. Using logistic regressions, we compute the ratio of odds ratios in females versus males. Therefore, an ORR > 1 is associated with a higher odds ratio for females than for males while an ORR < 1 means the opposite. To account for multiple hypothesis testing, we applied the Bonferroni correction. Hypertension in both sexes was associated with lower educational level, being unemployed, and lower income. In males, being divorced/widowed (OR1.12, p < 0.001) had an association to hypertension, whereas in females, being common-law/married (OR1.30, p < 0.001) and being divorced/widowed (OR1.17, p < 0.001) was associated with a higher risk for hypertension. Moreover, in hypertension, females who worked had an association with myocardial infarction (OR1.39, p < 0.001) and having post-secondary education had an association with arthrosis (OR 1.35, p < 0.001) compared to males. Our findings show that gender variables influence the association of hypertension and comorbidities, especially in females. These results can be used to inform targeted prevention measures taking gender-specific contextual factors into account.

Background: Stroke is a leading cause of long-term disability among survivors. Past literature already investigated the biological sex differences in stroke outcome; still limited work on gender differences is published. Therefore, the study aimed at investigating whether biological sex and sociocultural gender of survivors play a role as determinants of disability and quality of life among stroke survivors across Europe and Canada.Methods: Data were gathered from the European Health Information Survey (EHIS, n = 316,333) and Canadian Community Health Survey (CCHS, n = 127,462) data sets. Main outcomes of interest were disability, assessed through evaluating the impairment of Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (iADL), and inpatient care needs, such as hospitalization or institutionalization. Multivariate logistic regression models were utilized to identify factors independently associated with outcomes. Federated analysis was conducted for cross-country comparisons. Data were adjusted for the country-specific Gender Inequality Index (GII), with higher score corresponding to more gender inequality toward females.Results: Female survivors showed greater impairments in iADL (odds ratio [OR] = 1.73, 95% confidence interval [CI]:1.53-1.96) and ADL (OR = 1.25, 95% CI: 1.09-1.44), without a corresponding increase in inpatient care needs. Socioeconomic factors such as marital status and income level were significant predictors of disability, with low income and being single/divorced associated with higher risks. The impact of sex was more pronounced in countries with higher GII, indicating the influence of gender inequality on stroke outcomes.Interpretation: The findings highlight the significant impact of biological sex and gender-related social determinants on post stroke disability, with female sex and unfavorable socioeconomic conditions being associated with worse outcomes.

Homophily, the tendency of humans to attract each other when sharing similar features, traits, or opinions has been identified as one of the main driving forces behind the formation of structured societies. Here we ask to what extent homophily can explain the formation of social groups, particularly their size distribution. We propose a spin-glass-inspired framework of self-assembly, where opinions are represented as multidimensional spins that dynamically self-assemble into groups; individuals within a group tend to share similar opinions (intra-group homophily), and opinions between individuals belonging to different groups tend to be different (inter-group heterophily). We compute the associated non-trivial phase diagram by solving a self-consistency equation for 'magnetization' (combined average opinion). Below a critical temperature, there exist two stable phases: one ordered with non-zero magnetization and large clusters, the other disordered with zero magnetization and no clusters. The system exhibits a first-order transition to the disordered phase. We analytically derive the group-size distribution that successfully matches empirical group-size distributions from online communities.

Sharing health data for research purposes across international jurisdictions has been a challenge due to privacy concerns. Two privacy enhancing technologies that can enable such sharing are synthetic data generation (SDG) and federated analysis, but their relative strengths and weaknesses have not been evaluated thus far. In this study we compared SDG with federated analysis to enable such international comparative studies. The objective of the analysis was to assess country-level differences in the role of sex on cardiovascular health (CVH) using a pooled dataset of Canadian and Austrian individuals. The Canadian data was synthesized and sent to the Austrian team for analysis. The utility of the pooled (synthetic Canadian + real Austrian) dataset was evaluated by comparing the regression results from the two approaches. The privacy of the Canadian synthetic data was assessed using a membership disclosure test which showed an F1 score of 0.001, indicating low privacy risk. The outcome variable of interest was CVH, calculated through a modified CANHEART index. The main and interaction effect parameter estimates of the federated and pooled analyses were consistent and directionally the same. It took approximately one month to set up the synthetic data generation platform and generate the synthetic data, whereas it took over 1.5 years to set up the federated analysis system. Synthetic data generation can be an efficient and effective tool for enabling multi-jurisdictional studies while addressing privacy concerns.

Roux-en-Y gastric bypass operations (RYGB-OP) and pregnancy alter glucose homeostasis and the adipokine profile. This study investigates the relationship between adipokines and glucose metabolism during pregnancy post-RYGB-OP. (1) Methods: This is a post hoc analysis of a prospective cohort study during pregnancy in 25 women with an RYGB-OP (RY), 19 women with obesity (OB), and 19 normal-weight (NW) controls. Bioimpedance analysis (BIA) was used for metabolic characterization. Plasma levels of adiponectin, leptin, fibroblast-growth-factor 21 (FGF21), adipocyte fatty acid binding protein (AFABP), afamin, and secretagogin were obtained. (2) Results: The phase angle (φ) was lower in RY compared to OB and NW. Compared to OB, RY, and NW had lower leptin and AFABP levels, and higher adiponectin levels. φ correlated positively with leptin in RY (R = 0.63, p < 0.05) and negatively with adiponectin in OB and NW (R = −0.69, R = −0.69, p < 0.05). In RY, the Matsuda index correlated positively with FGF21 (R = 0.55, p < 0.05) and negatively with leptin (R = −0.5, p < 0.05). In OB, FGF21 correlated negatively with the disposition index (R = −0.66, p < 0.05). (3) Conclusions: The leptin, adiponectin, and AFABP levels differ between RY, OB, and NW and correlate with glucose metabolism and body composition. Thus, adipokines might influence energy homeostasis and maintenance of cellular health during pregnancy.

Introduction: Gendered-psycho-socio-cultural factors have been shown to play a significant role in disease manifestation, control and management of hypertension (HTN), and their relationship varies in males and females. We investigated the role of sex and gender in HTN prevalence and country-level differences in Canadian and European populations. Methods: Data from the Canadian Community Health Survey (CCHS, 2015-16, N=109,659, Females:56.6%) and the European Health Interview Survey (E-HIS, 2013-2015, N=316,333, females: 51.3%) were analyzed. Primary endpoint was defined as having a diagnosed HTN made by a health professional in the past 12 months. Relationship between gender variables and HTN prevalence and interaction with sex was assessed in a multivariable model. Federated analysis was conducted using the R package and DataShield which allows international data pooling by only exposing aggregated results. Results: The prevalence of HTN was greater in Canada compared with Europe (CCHS: 30.1% vs EHIS: 22.4%, P<0.001). Amongst European countries, Southern (SEU) and Central East (CEU) region had greater prevalence of HTN and more significant sex-differences (greater prevalence in females) compared to Northern (NEU) and Western (WEU) regions. In the multivariable model for assessing the role of gender variables in prevalence of HTN, female sex, older age, greater BMI, married or divorced/widowed status, and lower income were associated with higher risk of HTN, while greater household size, higher level of education, and living in European countries compared to Canada were associated with lower risk. There was a significant interaction between socioeconomic status (income, education) and sex in country stratified analysis. Within European countries, this was more evident in CEU, and SEU compared to NEU and WEU, where women with lower socioeconomic status had greater risk of HTN. There were significant country-level differences with being an immigrant and risk of having HTN. While living in NEU and SEU was associated with lower risk of having HTN, living in CEU was associated with a greater risk. Conclusion: The findings of the study demonstrate the importance of gender related factors and particularly the differences amongst various countries.

Cardiovascular diseases (CVD) are the leading cause of mortality and morbidity worldwide. Whether sex is associated with outcomes in patients with CVD differently across countries remains unknown. Assessing the interaction between sex and psycho-socio-cultural factors (gender) and country requires merging of country specific databases. Privacy concerns are barriers to data access and sharing. Therefore, we assessed the feasibility of pooling data from Canadian and Austrian populations to assess country-level differences in the role of sex, gender in cardiovascular health (CVH) using federated analysis and data synthesis. The datasets used were from the Canadian Community Health Survey (CCHS), and the Austrian Health Interview Survey (ATHIS) in 2014. Only CCHS dataset was synthesized using sequential classification and regression trees. The privacy of the CCHS synthetic data was assessed using a membership disclosure test and F1 score. The low value means that the dataset can be deemed as having low privacy risks. Once it was deemed to be non-personal information, the synthetic dataset was sent to the Austrian team for pooling and analysis. The analysis was performed on the pooled source ATHIS data and the synthetic CCHS data. The outcome variable was CVH, calculated through a modified CANHEART index in both countries. The utility of the pooled dataset was evaluated by comparing the regression model with the model constructed from federated analysis using DataSHIELD. A significant time elapsed to set-up the necessary servers in multiple locations with the requisite security protocols for the federated analysis. For assessing Privacy Risks of Synthetic Data, the largest membership disclosure F1 score across different attack datasets was 0.001, indicating low privacy risk. A comparison of the marginal distributions between males and females showed consistent results in the federated and pooled analyses of synthetic data. In the multivariate analysis of the main effects, the parameter estimates of the federated and pooled analysis were directionally the same as for the univariate analysis. In the multivariate analyses considering the country interactions to determine whether country moderates the relationship between the other variables and CVH, the impact of several factors differed between countries (Table 1). The result of this secondary analysis of population-based datasets revealed that synthetic data generation methods can be safely and reproducibly used to pool datasets across countries for international studies. There were significant country-level differences in the role of sex, and gender in CVH which demonstrates the importance of pooling datasets from different jurisdictions.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Importance: A male predominance is reported in hospitalised patients with COVID-19 alongside a higher mortality rate in men compared to women. Objective: To assess if the reported sex bias in the COVID-19 pandemic is validated by analysis of a subset of patients with severe disease. Design: A nationwide retrospective cohort study was performed using the Austrian National COVID Database. We performed a sex-specific Lasso regression to select the covariates best explaining the outcomes of mechanical ventilation and death using variables known before ICU admission. We use logistic regression to construct a sex-specific “risk score” for the outcomes using these variables. Setting: We studied the characteristics and outcomes of patients admitted to intensive care units (ICUs) in Austria. Participants: 5118 patients admitted to the ICU in Austria with a COVID-19 diagnosis in 03/2020–03/2021. Exposures: Demographic and clinical characteristics, vital signs and laboratory tests, comorbidities, and management of patients admitted to ICUs were analysed for possible sex differences. Main outcomes and measures: The aim was to define risk scores for mechanical ventilation and mortality for each sex to provide better sex-sensitive management and outcomes in the future. Results: We found balanced accuracies between 55% and 65% to predict the outcomes. Regarding outcome death, we found that the risk score for pre-ICU variables increases with age, renal insufficiency (f: OR 1.7(2), m: 1.9(2)) and decreases with observance as admission cause (f: OR 0.33(5), m: 0.36(5)). Additionally, the risk score for females also includes respiratory insufficiency (OR 2.4(4)) while heart failure for males only (OR 1.5(1)). Conclusions and relevance: Better knowledge of how sex influences COVID-19 outcomes at ICUs will have important implications for the ongoing pandemic’s clinical care and management strategies. Identifying sex-specific features in individuals with COVID-19 and fatal consequences might inform preventive strategies and public health services.

The drivers behind regional differences of SARS-CoV-2 spread on finer spatio-temporal scales are yet to be fully understood. Here we develop a data-driven modelling approach based on an age-structured compartmental model that compares 116 Austrian regions to a suitably chosen control set of regions to explain variations in local transmission rates through a combination of meteorological factors, non-pharmaceutical interventions and mobility. We find that more than 60% of the observed regional variations can be explained by these factors. Decreasing temperature and humidity, increasing cloudiness, precipitation and the absence of mitigation measures for public events are the strongest drivers for increased virus transmission, leading in combination to a doubling of the transmission rates compared to regions with more favourable weather. We conjecture that regions with little mitigation measures for large events that experience shifts toward unfavourable weather conditions are particularly predisposed as nucleation points for the next seasonal SARS-CoV-2 waves.

Structure-forming systems are ubiquitous in nature, ranging from atoms building molecules to self-assembly of colloidal amphibolic particles. The understanding of the underlying thermodynamics of such systems remains an important problem. Here, we derive the entropy for structure-forming systems that differs from Boltzmann-Gibbs entropy by a term that explicitly captures clustered states. For large systems and low concentrations the approach is equivalent to the grand-canonical ensemble; for small systems we find significant deviations. We derive the detailed fluctuation theorem and Crooks' work fluctuation theorem for structure-forming systems. The connection to the theory of particle self-assembly is discussed. We apply the results to several physical systems. We present the phase diagram for patchy particles described by the Kern-Frenkel potential. We show that the Curie-Weiss model with molecule structures exhibits a first-order phase transition.

Due to its high lethality among older people, the safety of nursing homes has been of central importance during the COVID-19 pandemic. With test procedures and vaccines becoming available at scale, nursing homes might relax prohibitory measures while controlling the spread of infections. By control we mean that each index case infects less than one other person on average. Here, we develop an agent-based epidemiological model for the spread of SARS-CoV-2 calibrated to Austrian nursing homes to identify optimal prevention strategies. We find that the effectiveness of mitigation testing depends critically on test turnover time (time until test result), the detection threshold of tests and mitigation testing frequencies. Under realistic conditions and in absence of vaccinations, we find that mitigation testing of employees only might be sufficient to control outbreaks if tests have low turnover times and detection thresholds. If vaccines that are 60% effective against high viral load and transmission are available, control is achieved if 80% or more of the residents are vaccinated, even without mitigation testing and if residents are allowed to have visitors. Since these results strongly depend on vaccine efficacy against infection, retention of testing infrastructures, regular testing and sequencing of virus genomes is advised to enable early identification of new variants of concern.

Boltzmann entropy is defined as the logarithm of state multiplicity. For multinomial multiplicities, it results in the ordinary Boltzmann-Gibbs-Shannon entropy. However, for non-multinomial systems, we obtain different expressions for entropy. This is the case of complex systems, particularly the case of systems with emergent structures. Probably the most prominent examples of such systems are provided by the chemical reactions with long-range interactions, i.e., where every particle can interact with each other. Based on the original ideas of L. Boltzmann, we calculate the entropy of a system with emergent molecule states. It turns out that the corresponding entropy is the Boltzmann-Gibbs entropy plus a correction that can be interpreted as a structural entropic force. The corresponding thermodynamics is an alternative for the grand-canonical ensemble that correctly counts the number of states. We demonstrate this approach on several examples, including chemical reactions of the type 2X <-> X2, phase transitions in a magnetic gas, and the fully connected Ising model. For the fully-connected Ising model, the presence of molecule states shifts the Curie temperature down and changes the order of the phase transition from the second-order to the first order. For systems with short-range interactions, we recover the ordinary Boltzmann-Gibbs entropy and derive the well-known relation between chemical potential and concentration.