Patterns and risk factors of falls among older adults: a systematic review
DOI:
https://doi.org/10.15561/health.2025.0102Keywords:
cognitive impairments, sensorimotor function, gait analysis, fall prevention strategies, systematic review methodologyAbstract
Background and Study Aim. Falls represent a significant health concern for older adults, leading to a decline in quality of life and other adverse consequences. The aim of this systematic review is to identify the key patterns and risk factors of falls among older adults and propose recommendations for their prevention.
Materials and Methods. The Web of Science Core Collection database was selected as the data source. The search included publications from the last 10 years (2014–2024). Bibliographic data of the articles were extracted, revealing a total of 852,909 documents. A refined search reduced the dataset to 32,631 documents, from which a subset of 31,009 documents was formed for analysis. Two algorithms were used for the automatic extraction of the most significant documents from a dataset of 31,009 records. The first algorithm is based on extracting documents with the highest citation metrics. The second algorithm employs an approach that combines keyword analysis, their weighting coefficients, and document abstracts. The Latent Dirichlet Allocation (LDA) thematic model was applied for text data processing using the Python programming language. The model quality was assessed using the Perplexity Score (model prediction accuracy) and Coherence Score (topic coherence). For visualization and in-depth analysis of thematic distributions, the pyLDAvis library and Gephi software were utilized.
Results. The application of two document extraction algorithms enabled the identification of two groups (n = 2 × 25) of the most relevant and high-quality articles, which was confirmed using statistical methods. This approach minimizes subjectivity and randomness in selection, enhancing the accuracy and validity of the analysis. The review identified key themes focused on assessing and preventing fall risks among older adults. Risk factors include cognitive and sensorimotor impairments, changes in gait parameters such as reduced speed, shortened step length, and increased variability. Additionally, fear of falling, physiological changes, and external conditions contributing to fall likelihood were noted. A multifactorial approach incorporating modern technologies and regular monitoring demonstrated effectiveness in reducing fall risk. The analysis results showed that the LDA method effectively identifies significant themes related to fall issues, risk factors, mobility, and prevention strategies. Ten key topics were identified, reflecting two main research algorithms.
Conclusions. The analysis identified key risk factors for falls among older adults, including cognitive impairments, reduced sensorimotor function, changes in gait parameters, as well as physiological and external factors. The findings highlight the diversity of approaches to risk assessment and prevention. A comprehensive strategy that integrates regular monitoring, individualized preventive measures, and modern technologies proves to be the most effective in reducing fall risk and maintaining the quality of life for older adults. The use of advanced algorithmic and statistical approaches enhances the objectivity and quality of systematic reviews, ensuring more accurate and reproducible results.
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