| Summary: | Abstract Background Accidental falls in older people are a major public health problem but a relatively limited number of studies have analyzed the mortality trends from this cause. Effective public health interventions have been found to prevent the incidence of falls and their complications. Therefore, characterizing the mortality trends of falls for different subpopulations can help to identify their needs and contribute to develop more appropriate prevention programs for specific target groups. Methods This study was based on a longitudinal analysis of death rates from accidental falls (2000-2015) stratified by sex for the population ≥ 65 years and by age groups (65-74, 75-84, ≥85). A joinpoint regression model was used to identify trend inflection points. The Annual Percent Change (APC) was estimated for each trend. Results Mortality rates per 100,000 person-years increased from 20.6 to 30.1 for men and 13.8 to 20.8 for women between 2000 and 2015. Men presented a relevant trend increase between 2008 and 2015 (APC [95% CI] 7.2% [5.3;9.2]) and women between 2008 and 2013 (7.9% [4.1;11.8]) There were no trend differences between sexes. For 65-74 years old men we found a relevant increase in the last period (2011-2015) (7.8% [1.0;15.1]). Those aged 75-84 years showed a trend increase between 2007 and 2015 (6.4% [4.4;8.4]) and men ≥85 years presented a remarkably high trend between 2008 and 2015 (9.0% [5.2;13]). There were no relevant differences between age groups. Women aged 65-74 had no relevant trend through the period. Those aged 75-84 presented an uniform trend increase for the whole period, 2000-2015, (3.4% [2.3;4.4]) and women ≥85 had and important trend increase between 2008 and 2013 (11.1% [5.3;17.2]), that has reached an stable level in the last 2 years. There were no relevant differences between the 75-84 and ≥85 age groups. Conclusions Recent mortality trends from accidental falls increased in men ≥65 years and women ≥75 years. These results recommend the implementation of specific preventive programs.
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