Dementia Risk Score for a Population in Southern Europe Calculated Using Competing Risk Models

Author:

Ibarrondo Oliver12,Huerta José María345,Amiano Pilar256,Andreu-Reinón María Encarnación37,Mokoroa Olatz26,Ardanaz Eva89,Larumbe Rosa8910,Colorado-Yohar Sandra M.34511,Navarro-Mateu Fernando3512,Chirlaque María Dolores34513,Mar Javier1214

Affiliation:

1. Research Unit, Debagoiena Integrated Healthcare Organisation, Basque Health Service (Osakidetza), Arrasate-Mondragón, Spain

2. Epidemiology and Public Health Area, Biodonostia Health Research Institute, San Sebastián, Spain

3. Murcia Biomedical Research Institute (IMIB-Arrixaca), Murcia, Spain

4. Department of Epidemiology. Murcia Regional Health Council, Murcia, Spain

5. CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain

6. Sub-Directorate for Public Health and Addictions of Gipuzkoa, Ministry of Health of the Basque Government, San Sebastián, Spain

7. Section of Neurology, Department of Internal Medicine, Rafael Méndez Hospital, Murcian Health Service, Lorca, Spain

8. Public Health Institute of Navarra, IdiSNA, Pamplona, Spain

9. Neuroepigenetics Laboratory, Navarrabiomed, Public University of Navarre (UPNA), Navarre, Spain

10. Department of Neurology, Complejo Hospitalario deNavarra, Pamplona, Spain

11. Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia

12. Unidad deDocencia, Investigación y Formación en Salud Mental(UDIF-SM), Murcian Health Service, IMIB-Arrixaca, Murcia, Spain

13. Department of Health and Social Sciences, University of Murcia, Murcia, Spain

14. Kronikgune Health Services Research Institute, Barakaldo, Spain

Abstract

Background: Dementia prevention can be addressed if the intervention is applied early. Objective: The objective of this study was to develop and validate competing risk models to predict the late risk of dementia based on variables assessed in middle age in a southern European population. Methods: We conducted a prospective observational study of the EPIC-Spain cohort that included 25,015 participants. Dementia cases were identified from electronic health records and validated by neurologists. Data were gathered on sociodemographic characteristics and cardiovascular risk factors. To stratify dementia risk, Fine and Gray competing risk prediction models were constructed for the entire sample and for over-55-year-olds. Risk scores were calculated for low (the 30% of the sample with the lowest risk), moderate (> 30% –60%), and high (> 60% –100%) risk. Results: The 755 cases of dementia identified represented a cumulative incidence of 3.1% throughout the study period. The AUC of the model for over-55-year-olds was much higher (80.8%) than the overall AUC (68.5%) in the first 15 years of follow-up and remained that way in the subsequent follow-up. The weight of the competing risk of death was greater than that of dementia and especially when the entire population was included. Conclusion: This study presents the first dementia risk score calculated in a southern European population in mid-life and followed up for 20 years. The score makes it feasible to achieve the early identification of individuals in a southern European population who could be targeted for the prevention of dementia based on the intensive control of risk factors.

Publisher

IOS Press

Subject

Psychiatry and Mental health,Geriatrics and Gerontology,Clinical Psychology,General Medicine,General Neuroscience

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