Systematic causality mapping of factors leading to accidental falls of older adults

According to WHO's statistical evidence, accidental falls are the second leading causes of death worldwide. This systematic literature review and meta-analysis aims to provide a holistic view of risk factors and unfold the missing or less addressed but crucial factors that lead to accidental falls of the older adults. It also intends to profile the risk factors at different levels, which helps exhibit the level of consistency relationship between various risk factors and falls.

Systematic literature review.

A systematic review on the risk factors leading to accidental falls of older adults by retrieving English journal papers published starting from 1980 was conducted on April 2018. A method of literature synthesis and causal mapping was adopted to aggregate those fall-leading factors into macro variables and a coherent causal tracing network was thereby built, which can reflect not only the causal relationship of various macro variables but also the "consistency of agreement" between macro variables and falls of the older adults.

A hypothesized causal relationship diagram of 19 aggregated macro variables and their 31 causal relationship suggested by the observational evidences is demonstrated. The consistency relationship between macro variables and elderly accidental fall are summarized and demonstrated. Our analysis reveals that "Time", "Season" and "Weather" are three less-studied factors in the literature. In our comprehensive analysis, our study also indicates neglected countries and senior populations such as Africa and Oceania, which requires more attention from the research community and global funding agencies. It is found that major quantitative tools focus on the traditional statistical analysis.

With the accelerated aging and increase of longevity worldwide, national and regional policies, and public health programs to provide adequate care services for the older people are crucially needed in both industrialized and developing countries. Evidences identified in the research are valuable inputs for policy design and decision makers of different stakeholders and prevention design of risk factors for falls in the older adults. The categorization of research methods in different literature also suggests that more quantitative approaches including simulation, optimization in operational research, and maybe machine learning are needed to enrich the research paradigm. We suggest researchers to consider using our presented causal map and the way of building it and explore the possibility of extending this framework to uncover more research topics in health-related research.