scholarly journals Worsening risk profiles of out-of-hospital births during the COVID-19 pandemic

Author(s):  
Amos Grünebaum ◽  
Eran Bornstein ◽  
Adi Katz ◽  
Frank A. Chervenak
2021 ◽  
Vol 151 ◽  
pp. 105947
Author(s):  
Manuela Alcañiz ◽  
Montserrat Guillen ◽  
Miguel Santolino

2020 ◽  
pp. 1-13
Author(s):  
Trenette Clark Goings ◽  
Tianyi Yu ◽  
Gene H. Brody

Abstract African American emerging adults face unique contextual risks that place them at heightened risk for poor psychosocial outcomes. The purpose of this study was to identify profiles of contextual risks among rural African American emerging adults and determine how risk profiles relate to psychosocial outcomes. Our representative sample included 667 fifth graders who live in the rural South and were followed from preadolescence into emerging adulthood. Contextual risks were assessed at ages 19–21 years via six indicators: perceived stress, daily stress, community disadvantage, parent–child conflict, racial discrimination, and childhood trauma. Four psychosocial variables were also assessed at ages 19–21 years: self-regulation, racial identity, parent support, and friend support. Psychosocial outcomes were assessed at age 25 years: education, substance use, future orientation, depressive symptoms, and externalizing behaviors. Latent profile analysis results indicated that the sample could be characterized by three patterns of contextual risk: low contextual risk, high contextual risk, and high contextual risk–childhood trauma. Risk profiles were associated with psychosocial outcomes, with the childhood trauma and high-risk profiles faring worse than the low-risk profile. Further, childhood trauma was particularly predictive of worse outcomes for emerging adults. Findings highlight the need for research and prevention programs that mitigate the effects of contextual risks on psychosocial outcomes for African American emerging adults in rural areas.


Author(s):  
Nicola Giuseppe Castellano ◽  
Roy Cerqueti ◽  
Bruno Maria Franceschetti

AbstractThis paper presents a data-driven complex network approach, to show similarities and differences—in terms of financial risks—between the companies involved in organized crime businesses and those who are not. At this aim, we construct and explore two networks under the assumption that highly connected companies hold similar financial risk profiles of large entity. Companies risk profiles are captured by a statistically consistent overall risk indicator, which is obtained by suitably aggregating four financial risk ratios. The community structures of the networks are analyzed under a statistical perspective, by implementing a rank-size analysis and by investigating the features of their distributions through entropic comparisons. The theoretical model is empirically validated through a high quality dataset of Italian companies. Results highlights remarkable differences between the considered sets of companies, with a higher heterogeneity and a general higher risk profiles in companies traceable back to a crime organization environment.


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