The Role of Socioeconomic Factors in the Survival of Patients with Gastrointestinal Cancers

SERIEs ◽  
2021 ◽  
Author(s):  
Pedro Salas-Rojo ◽  
Juan Gabriel Rodríguez

AbstractThe literature has typically found that the distribution of socioeconomic factors like education, labor status and income does not account for the remarkable wealth inequality disparities between countries. As a result, their different institutions and other latent factors receive all the credit. Here, we propose to focus on one type of wealth inequality, the inequality of opportunities (IOp) in wealth: the share of overall wealth inequality explained by circumstances like inheritances and parental education. By means of a counterfactual decomposition method, we find that imposing the distribution of socioeconomic factors of the USA into Spain has little effect on total, financial and real estate wealth inequality. On the contrary, these factors play an important role when wealth IOp is considered. A Shapley value decomposition shows that the distribution of education and labor status in the USA consistently increase wealth IOp when imposed into Spain, whereas the opposite effect is found for the distribution of income.


2015 ◽  
Vol 105 (4) ◽  
pp. 694-702 ◽  
Author(s):  
Paula A. Braveman ◽  
Katherine Heck ◽  
Susan Egerter ◽  
Kristen S. Marchi ◽  
Tyan Parker Dominguez ◽  
...  

2021 ◽  
pp. 140349482110158
Author(s):  
Marte Kjøllesdal ◽  
Katrine Skyrud ◽  
Abdi Gele ◽  
Trude Arnesen ◽  
Hilde Kløvstad ◽  
...  

Aim: Immigrants in Norway have higher COVID-19 notification and hospitalisation rates than Norwegian-born individuals. The knowledge about the role of socioeconomic factors to explain these differences is limited. We investigate the relationship between socioeconomic indicators at group level and epidemiological data for all notified cases of COVID-19 and related hospitalisations among the 23 largest immigrant groups in Norway. Methods: We used data on all notified COVID-19 cases in Norway up to 15 November 2020, and associated hospitalisations, from the Norwegian Surveillance System for Communicable Diseases and the emergency preparedness register at the Norwegian Institute of Public Health. We report notified COVID-19 cases and associated hospitalisation rates per 100,000 and their correlation to income, education, unemployment, crowded housing and years of residency at the group level. Results: Crowded housing and low income at a group level were correlated with rates of both notified cases of COVID-19 (Pearson`s correlation coefficient 0.77 and 0.52) and related hospitalisations (0.72, 0.50). In addition, low educational level and unemployment were correlated with a high number of notified cases. Conclusions: Immigrant groups living in disadvantaged socioeconomic positions are important to target with preventive measures for COVID-19. This must include targeted interventions for low-income families living in overcrowded households.


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