SAT0620 INCIDENCE AND TREND OF HIP FRACTURE IN SPAIN. FACTORS ASSOCIATED WITH THE VARIABILITY OBSERVED. (June 2019)

• Record Type: Journal Article
• Authors: Mazzucchelli, Ramón; Perez-Fernandez, Elia; Tejedor, Miguel Angel; Quirós, Javier; Crespí-Villarías, Natalia; García-Vadillo, Alberto; Almodovar, Raquel; Zarco-Montejo, Pedro
• Is Part Of: Annals of the rheumatic diseases. Volume 78(2019)Supplement 2
• Page Start: 1405
• Page End: 1406
• Publication Date: 2019-06
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2019-eular.2293
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: It is known that in Spain there is a great variability between Autonomous Communities (CCAA) in the incidence and trend of hip fracture, with rates in certain regions that can double those of others. Although it is speculated with different hypotheses that explain it, there are no studies that demonstrate the reasons for this variability. Objectives: 1.- To analyze the incidence and trend of hospital admissions for hip fracture, in Spain, during the period between 1999 and 2015. 2.- Analyze factors/risk markers (genetic, demographic, level and living conditions, health indicators, cohort effect centered on the period of the civil war, climatology and environment) that could explain the variability in incidence and trend between different CCAA. Methods: Part 1: retrospective observational study, nationwide, based on the exploitation of an administrative database (MBDS) that collects hospital admissions from 1/1/1999 to 12/31/2015. Hip fractures were identified through the presence of ICD-9 820.0 to 820.9 as primary or secondary diagnosis. Only those that the patient was 50 or older were selected. The crude rates and adjusted for age of incidence of hip fracture were calculated, by sex, age groups and by CCAA. The population census issued by the National Institute of Statistics (INE) was used to calculate this rate. The trend over the 17 years covered in the study was analyzed using Poisson regression and negative binomial models. Part 2: ecological study, based on the analysis of the results obtained in part 1, with different risk markers obtained from the INE (except the 4), by CCAA. The analyzed factors were: 1.- Genetic; 2.- Demographic; 3.- Level and conditions of life; 4.- Health; 5. Impact of the civil war. 6.- Environment; 7.- Climatological. This analysis was performed using bivariate correlations and univariate and multivariate linear regression. Results: There were 744, 848 patients diagnosed with hip fracture; 182, 205 (24.4%) men and 562, 643 (75.5%) women p <0.001. (Ratio M: V of 3.07). The mean age was 81.7 years (SD 8.9), 79.3 years (SD 10.3) in men and 82.5 years (SD 8.2) (p <0.001). In-hospital mortality was 5.7%, The average of the Charlson Index was 0.71 (SD1.14). The rate adjusted for the age of incidence of global hip fracture at the national level was 315.38/100, 000 inhabitants * year (95% CI 312.36-317.45), 169.56 (95% CI 166.26-172.39).) in men and 434.89 (95% CI 430.66-438.17) in women. By CCAA the incidence of hip fx varied from 213, 97 in the Canary Islands to 363, 13 in Comunidad Valenciana and Cataluña). The trend for both sexes was -0.67% (95% CI 0.9990-0.9957) (p <0.001); in men it was -0.06% (95% CI 0.9975-1.0013) (p = 0.537) and in women -0.82% (95% CI 0.9992-0.9944) (p <0.001). The distribution by CCAA of the incidence and trend is represented in the following figure: In the analysis of risk factors/markers that explain this distribution, we found significant correlations with genetic factors (H and J2 haplotypes), demographic (birth, fecundity, mean age and aging index), climatic factors (precipitation) and the time a region was on the Republican side. The linear regression model that includes the factors that show significant correlation justifies 96% of the variability observed. Conclusion: In Spain, the rate adjusted for age of incidence of hip fracture is decreasing. There is a great variability in the incidence and tendency of hip fracture among the different CCAA. Genetic, demographic, climatological factors and due to the cohort effect of the civil war, explain 96% of this variability. Disclosure of Interests: None declared