Our study showed that among community-dwelling older people, motor function assessed by the FINEA index at baseline was significantly associated with an increased risk of total falls after 2 years of follow-up. Baseline GROSSA scores were borderline significantly associated with total fall risk. When the FINEA and GROSSA indices were combined, the association with falls was more robust.
Predictive factors for the risk of falls have been investigated for decades, and factors including visual deficits, muscle strength, motor function, and postural control have been found to be associated with the risk of falls[16, 17]. Among these factors, motor function, gait and balance have been the most studied and have been shown to be firmly linked to the risk of falls in the elderly. The underlying mechanism lies in gait dysfunction or motor dysfunction that is a failure of sophisticated mechanisms of brain mobility control and becomes apparent in falling, known as “brain failure”[6, 18]. These results have been reinforced by well-established relationships among gait or motor function, cognitive impairment and falling[8, 19–21]. Our previous study showed significant associations between motor function assessed by the FINEA or GROSSA indices and cognitive impairments. Therefore, we are not surprised that both motor indices were likely to be associated with falling in the present study, which further confirmed the firm associations between motor function, cognitive impairments, and falls.
To reduce the risk of falls, relevant training has been widely explored. A meta-analysis that assessed the preventive role of exercise on fall risk among community-dwelling individuals showed that functional and balance exercises could reduce the rate of falls by 24%. Fall prevention trials (both multifactorial and single-factor interventions) among cognitively normal elderly individuals showed significant effectiveness while failing in those with cognitive impairment[23, 24]. Detecting the risk of falls for prevention trials in individuals with normal cognitive function would be more significant. However, risk assessment tools that have been developed for predicting future falls, including the Berg balance scale, timed up and go test, performance oriented mobility assessment, functional reach test, gait speed test, and history of falls, have shown low predictive ability (area under the curve < 0.7). Therefore, more sensitive and specific prediction tools should be further investigated. Our study showed that both FINEA and GROSSA indices could predict the risk of falls, and more robust results were observed with the combined motor index. Both the FINEA and GROSSA are simple, feasible, self-report questionnaires, and they might be an effective tool to screen for and identify community-dwelling older people who are at a high risk of falling.
Based on our prospective cohort study, FINEA and GROSSA scores were significantly associated with accidental falls and unaccidental falls, respectively. Where are there these differences? Beside the difference reflection of muscle dysfunction across the two motor index, deficiencies in FINEA performance (bimanual motor performance) may be associated with changes in the size or structure of the corpus callosum[26, 27]. While impairments in GROSSA performance (primate bipedal locomotion) may be caused by changes in the brainstem, cerebellum, and forebrain. As the brain remains an incompletely understood and mysterious organ, the potential for diverse associations between areas associated with differences in motor and cognitive performance, which could result in distinct predictions regarding falling type, should be further studied.
General speaking, unaccidental fall are associated with more intracranial injury and are more likely due to syncope or underlying cardiovascular disease. One-third of patients admitted to an orthopaedic ward had unaccidental fall. Our results showed GROSSA was associated with risk of unaccidental fall, moreover, the relationship is more robust when combination of FINEA and GROSSA index scores. Participants with dysfunction of motor index seemed to be more appropriate for unaccidental falls prevention interventions.
Our findings may be explained by several possible mechanisms. The effective coordination of the basal ganglia and brainstem systems, regulated muscle tone, and functional processing of sensory information could lead to a normal gait. Therefore, both impairments in muscle tone and neural regulation could cause an increased fall risk. Regarding muscle, decreased strength or power of muscle due to multiple factors (increasing age, alterations in nervous systems, etc.) caused atrophy that could decrease dynamic balance abilities and increase the risk of falling. Paratonia was also found to be associated with a decline in both fine and gross motor performance. Regarding neural impairments, postural and gait stability and adjustments during walking, the harmonious modulation of trunk/ankle flexibility under physiological perturbations, and support in the center of body mass are needed to prevent falls that require attention and executive resources. White matter brain regions are areas connecting cortical and subcortical regions. Pathological changes in these regions could decrease connectivity between different brain areas and cause an increase in fall risk. In patients at risk of falling, magnetic resonance imaging showed abnormal white matter in the genu and splenium of the corpus callosum, medial frontal and parietal subcortical pathways, posterior cingulum, prefrontal, and orbitofrontal pathways, and longitudinal pathways that connect the frontal, parietal, and temporal lobes. Damage in different locations within the central nervous system could cause an increased risk of falling. Therefore, combining assessments of several motor functions that change earlier or more typically with deficiencies in different brain areas or muscle atrophy with different underlying causes could help better detect individuals at a higher risk of falling.
Strengths and limitations
Our study has several strengths. We first introduced fine motor or gross motor index scores as being associated with the risk of falls in community-dwelling adults. This association persisted when adjusted the cognitive impairment, which suggests a role of FINEA/GROSSA on fall in these cognitively normal participants. Second, this research was based on a well-designed study with a large sample size, which makes the results more credible. Third, both the FINEA and GROSSA are simple, feasible, self-report questionnaires that could be used as tools to screen for and identify older patients at high risk of falling.
Our study also has limitations. First, although our sample size was large, the number of individuals with motor dysfunction (FINEA > 0 or GROSS > 0) was limited. This imbalanced dataset might have influenced our results. Second, wave 2 of TILDA did not collect information on gait alterations (such as speed or stability), which have been well established in the association with falls[6, 16, 33, 37]. Third, previous also have shown depression and antidepressant use was independently associated with fall, however, the dataset of our study does not include information of depression diagnosis and antidepressant use. Fourth, our sample was Irish, so further analyses based in other populations, including Americans and Asians, should be further investigated.