Femoral fractures in older adults are associated with lethality rates of up to 30% within the first year and significantly compromised quality of life, leading to high levels of disability, institutionalization, and burden on health systems. By 2050, the global population of older adults is projected to exceed 2 billion, leading to an exponential increase in these events. In Brazil, the incidence of fractures is high and often linked to inequalities in access to diagnosis and prevention, particularly in regions with limited infrastructure. This study aimed to analyze the spatiotemporal distribution of femoral fractures in older adults and identify contextual factors associated with their occurrence. This is an ecological and retrospective study using secondary data from 2010 to 2021 on hospitalizations for femoral fractures in older adults (≥ 60 years) in the 399 municipalities of Paraná State, Brazil. Descriptive analyses and nonparametric tests were performed to compare mortality rates according to population size. Spatiotemporal distribution was examined using space–time cubes. Spatial autocorrelation was assessed using global Moran’s I and local indicators of spatial autocorrelation (LISA). Geographically weighted regression (GWR) was applied to explore local associations with contextual variables. A total of 39,226 femoral fractures were recorded during the study period, with a predominance among women (66.8%). Overall lethality was 6%, being significantly higher in men. Space–time cube analysis indicated a persistent increasing trend in fractures (Z = 2.8115, p = 0.0049). Spatial analysis revealed significant positive spatial autocorrelation (I = 0.705, p < 0.001) and identified significant clusters and groupings (p < 0.05). GWR demonstrated a negative association between fracture incidence and access to specialists and osteoporosis medication, and a positive association with falls and densitometry availability in some regions. The findings indicate that the distribution of fractures is not random but rather influenced by factors such as access to diagnosis, medication, and specialized care. This evidence underscores the value of geospatial tools in the planning of health actions, enabling more targeted and equitable interventions in response to population aging.
Gabella et al. (Mon,) studied this question.