Arnedo Ajona, Laura
Loading...
Email Address
person.page.identifierURI
Birth Date
Job Title
Last Name
Arnedo Ajona
First Name
Laura
person.page.departamento
Gestión de Empresas
person.page.instituteName
ORCID
person.page.observainves
person.page.upna
Name
- Publications
- item.page.relationships.isAdvisorOfPublication
- item.page.relationships.isAdvisorTFEOfPublication
- item.page.relationships.isAuthorMDOfPublication
3 results
Search Results
Now showing 1 - 3 of 3
Publication Open Access Sex-dependent effect of socioeconomic status on cardiovascular event risk in a population-based cohort of patients with type 2 diabetes(Oxford University Press, 2024) Enguita Germán, Mónica; Tamayo Rodríguez, Ibai; Librero, Julián; Ballesteros-Domínguez, Asier; Oscoz-Villanueva, Ignacio; Galbete Jiménez, Arkaitz; Arnedo Ajona, Laura; Cambra Contin, Koldo; Gorricho Mendívil, Javier; Moreno Iribas, Conchi; Millán-Ortuondo, Eduardo; Ibáñez Beroiz, Berta; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Ciencias de la Salud; Osasun Zientziak; Gestión de Empresas; Enpresen KudeaketaBackground: Socioeconomic status (SES) factors often result in profound health inequalities among populations, and their impact may differ between sexes. The aim of this study was to estimate and compare the effect of socioeconomic status indicators on incident cardiovascular disease (CVD)-related events among males and females with type 2 diabetes (T2D). Methods: A population-based cohort from a southern European region including 24,650 patients with T2D was followed for five years. The sex-specific associations between SES indicators and the first occurring CVD event were modeled using multivariate Fine-Gray competing risk models. Coronary Heart Disease (CHD) and stroke were considered secondary outcomes. Results: Patients without a formal education had a significantly higher risk of CVD than those with a high school or university education, with adjusted hazard ratios (HRs) equal to 1.24 (95%CI: 1.09-1.41) for males and 1.50 (95%CI: 1.09-2.06) for females. Patients with <18 000euro income had also higher CVD risk than those with >= 18 000euro, with HRs equal to 1.44 (95%CI: 1.29-1.59) for males and 1.42 (95%CI: 1.26-1.60) for females. Being immigrant showed a HR equal to 0.81 (95%CI: 0.66-0.99) for males and 1.13 (95%CI: 0.68-1.87) for females. Similar results were observed for stroke, but differed for CHD when income is used, which had higher effect in females. Conclusion: Socioeconomic inequalities in CVD outcomes are present among T2D patients, and their magnitude for educational attainment is sex-dependent, being higher in females, suggesting the need to consider them when designing tailored primary prevention and management strategies.Publication Open Access The role of accounting accruals for the prediction of future cash flows: evidence from Spain(Springer, 2012) Arnedo Ajona, Laura; Lizarraga Dallo, Fermín; Sánchez Alegría, Santiago; Gestión de Empresas; Enpresen Kudeaketa; Gobierno de Navarra / Nafarroako GobernuaThe aim of this study is to determine whether accruals have information value beyond that provided by isolated current cash flows for the prediction of future cash flows. Using a sample of 4,397 Spanish companies (mostly privately held), we estimate in-sample regressions of future cash flows on isolated current cash flows and on accrual-based earnings. We then find that the out-of-sample prediction errors provided by the accrual-based earnings model are significantly lower than those obtained with the cash flows model. We also regress the decrease in prediction errors brought about by the addition of accruals on a set of firm-specific circumstances where accounting manipulation is expected. In all cases the decrease in prediction errors is significantly affected in the hypothesized direction.Publication Open Access Cohort Profile: CArdiovascular Risk in patients with DIAbetes in NAvarra (CARDIANA cohort)(BMJ, 2023) Tamayo Rodríguez, Ibai; Librero, Julián; Galbete Jiménez, Arkaitz; Cambra Contin, Koldo; Enguita Germán, Mónica; Forga, Lluís; Goñi, María José; Lecea, Óscar; Gorricho Mendívil, Javier; Olazarán Santesteban, Álvaro; Arnedo Ajona, Laura; Moreno Iribas, Conchi; Lafita, Javier; Ibáñez Beroiz, Berta; Ciencias de la Salud; Osasun Zientziak; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Gestión de Empresas; Enpresen KudeaketaPurpose The CArdiovascular Risk in patients with DIAbetes in Navarra (CARDIANA cohort) cohort was established to assess the effects of sociodemographic and clinical variables on the risk of cardiovascular events in patients with type 1 (T1D) or type 2 (T2D) diabetes, with a special focus on socioeconomic factors, and to validate and develop cardiovascular risk models for these patients. Participants The CARDIANA cohort included all patients with T1D and T2D diabetes registered in the Public Health Service of Navarra with prevalent disease on 1 January 2012. It consisted of 1067 patients with T1D (ages 2–88 years) and 33842 patients with T2D (ages 20–105 years), whose data were retrospectively extracted from the Health and Administrative System Databases. Findings to date The follow-up period for wave 1 was from 1 January 2012 to 31 December 2016. During these 5 years, 9 patients (0.8%; 95%CI (0.4% to 1.6%)) in the T1D cohort developed a cardiovascular disease event, whereas for the T2D cohort, 2602 (7.7%; 95%CI (7.4% to 8.0%)) had an event. For the T2D cohort, physical activity was associated with a reduced risk of cardiovascular events, with adjusted estimated ORs equal to 0.84 (95% CI 0.66 to 1.07) for the partially active group and 0.71 (95% CI 0.56 to 0.91) for the active group, compared with patients in the non-active group. Future plans The CARDIANA cohort is currently being used to assess the effect of sociodemographic risk factors on CV risk at 5 years and to externally validate cardiovascular predictive models. A second wave is being conducted in late 2022 and early 2023, to extend the follow-up other 5 years, from 1 January 2016 to 31 December 2021. Periodic data extractions are planned every 5 years.