Our study not only demonstrates the decreased prevalence of falls across the three waves of the NHIS, but it also identifies several significant independent risk factors for falls during the previous year. These risk factors including the following: female gender, difficulty in performing one basic ADL, difficulty in performing two or more instrumental ADLs, unclear vision, comorbidities, urinary incontinence, and depressive symptoms. However, there was no significant risk of falling associated with advanced age, use of sleeping pills, and getting exercise on either a regular or irregularly basis. Several insights were gained from our study regarding the paradox between the prevalence of falls, the SMR of accidental falls, and the fall-related hospitalization rates. Furthermore, these risk factors may help dictate the future direction of fall prevention policies.
Although a multifactorial fall risk awareness program was launched in 2004, we cannot attribute the declining trend in the prevalence of falls to it for several reasons. During 2005–2013, there were other overlapping health promotion programs that were initiated at different times and locations in Taiwan. These programs included the Community Health Building (since 1996), Safe Communities (since 2002), Healthy Cities (since 1995), and Health Promotion Programs for the Elderly (with which the multifactorial fall risk awareness program has been integrated since 2009) [17]. Second, these aforementioned programs were spreading, either community by community or county/city by county/city, in a disjointed and fragmented fashion without sufficient participation among the informal and formal caregivers for elderly adults. Successful fall prevention strategies are supposed to encompass the full array of contributing variables or causes over a broad target audience with user design strategies [18], and accomplish a significant risk reduction in falls and fall-related hospitalizations and deaths. Accordingly, we can assume that the previous fall prevention strategies in Taiwan indicate a lot of ground for improvement, judging from two folds. First, there were some discrepancies between the decreasing trend of prevalence of falls and the increasing trend of SMR due to accidental falls from 2009–2016 [15] and for the overall, sex-specific, and age-specific fall-related hospitalization rates from 2003–2009 [16]. It implies that falls and fall-related injuries, even sharing some risk factors for falling, cannot be prevented with one-size-fits-all strategies [19,20]. Second, as the population is rapidly aging, the functional disability status among older Taiwanese accelerates over time, especially among women and the old–old (≥75 years old) population. Women in the older age groups suffer from disproportionately greater levels of disability [21] and are more susceptible to falls and fall-related injuries than their male counterparts. This disparity in fall risk is also apparent in the old–old compared with the young–old (65 years old). Elderly women and the old–old tended to have a higher fall-related hospitalization rate during 2003–2009. These higher rates may be because of a higher risk of frailty, restricted mobility, and being less likely to participate in community-based fall prevention activities (Fig 1).
Regarding the socio-demographic risk factors for falling that were identified using the MLR models, women had a higher risk of falls, which was probably owing to osteoporosis and reduced knee muscle strength [22]. The association between difficulties in performing two or more IADLs and an increased risk of falling is compatible with the findings of preceding reports [11,23]. However, there was no corresponding finding among those older adults with difficulty in performing ADLs. A possible explanation is that they were subject to selective survival [24] and became too small a number to obtain a stable OR across the three waves of survey.
Regarding biological factors, our finding that elderly adults with unclear vision had an OR that was twice as high as elderly adults with clear vision aligns with that in a previous report by Lord [25]. Consistent with the findings of Qin & Baccaglini [26], we observed that having one or two or more comorbidities was also identified as a significant risk predictor of falls because physical functions may be compromised by comorbidities. For example, diabetic patients are more liable to falls because they tend to have a high prevalence of frailty [27] and declined compensation for the pathophysiological and psychological factors associated with chronic pain including reflex inhibition, joint instability, fear of falling, and reduced attention [28]. Stroke survivors are usually more susceptible to falls, probably due to unilateral weakness, hemisensory or visual neglect, impaired coordination, visual field defects, perceptual difficulties, cognitive issues [29], and deficits in gait and balance [30]. The 40% higher risk of falling among respondents with urinary incontinence in 2013 was compatible with the conclusions drawn from a previous systematic review [31]. The fact that depressive symptoms were proven to be a significant risk factor of falls might be explained by an intricate bidirectional and self-perpetuating interaction between depression and falls [32].
It is also noteworthy that taking sleeping pills and getting physical exercise either irregularly or regularly were not independently correlated with falls in the three waves of surveys, and these findings contradict those of two large published studies [33,34] and the updated review of exercise as a single intervention for preventing falls [35]. Further studies are needed to clarify this discrepancy.
Our study has two main strengths. First, it has a comparable fall-related questionnaire administered to a large sample size of elderly adults on a national scale. These factors allow this study to analyze the time-dependent trend in the prevalence of falls and to identify risk factors across three waves of surveys. Second, data quality was assured through the pre-job training of interviewers, standardization of the questionnaire administration process, and auditing. However, several aspects of this study may be improved. First, a cross-sectional survey cannot infer a causal relationship between the outcome and explanatory variables. Second, data regarding the instances of falls and explanatory variables might be subject to recall bias for not verified using medical records. Further studies might make use of data linkage with the longitudinal national health insurance research database to examine the medical records of respondents who had experienced falls. Third, the observation period and interval of data collection of our study are not comparable with those of other fall-related hospitalization [16]. The aforementioned discrepancies awaits further study because the evaluation of health promotion for elderly people was beyond the scope of our study [36]. Finally, extrapolation of our study findings to other cultures or nations should be performed with caution because the definitions of falls and coverage of comorbidities vary across surveys.
The present study suggests that a combination of low-risk and high-risk strategies [37] should be adopted to tailor fall prevention programs to people with several different risk factors for falling. Even though the declining prevalence of falls implies that previous community-based health promotion programs, including multifactorial fall risk awareness, were successful, elderly adults with multiple risk factors are often overlooked. It is recommended to deliver an approach that accounts for adults who have multimorbidity and are prescribed multiple medicines because they are likely to be at a higher risk for adverse events and drug interactions [38]. In the face of the projected 2.7-fold growth in the number of hip fractures between 2010–2035 [39], it is recommended that the fall epidemic must be surveyed regularly, as the identification of risk factors in the elderly may help with developing individualized fall risk assessments [19] among high-risk seniors. Furthermore, this approach could enhance fall prevention programs to be more efficient and effective to reduce fall-related hospitalizations [10] in the future.