Factors associated with falls in older adults: A secondary analysis of a 12-month randomized controlled trial

Future risk of falls induced by ankle-foot sprains history: An observational and mendelian randomization study

Background

Ankle-foot sprains are the most common musculoskeletal injuries, which can impair balance and theoretically increase the risk of falls, but still, there is a lack of evidence supporting the direct association between ankle-foot sprains and the future risk of falls.

Methods

UK Biobank cohort was utilized to measure the association between ankle-foot sprains and fall risk with covariates adjusted. Then, the two-sample Mendelian randomization (MR) analysis was applied based on the genetically predicated ankle-foot sprains from FinnGen to validate causal relationship. Finally, genetically predicated cerebellar neuroimaging features were used to explore the mediating role of maladaptive neuroplasticity between ankle-foot sprains and falls by two-step MR analyses.

Results

Patients with ankle-foot sprains history exhibited a slightly increased risk of falls than the matched controls before and after adjustment for covariates (odd ratio [OR] ranged from 1.632 to 1.658). Two-sample MR analysis showed that ankle-foot sprains led to a higher risk of falls (OR ​= ​1.036) and a lower fractional anisotropy of superior cerebellar peduncle (SCP) (left, β ​= ​-0.052; right, β ​= ​-0.053). A trend of mediating effect was observed for the fractional anisotropy of right SCP in the causal effects of ankle-foot sprains on falls (β ​= ​0.003).

Conclusion

The history of ankle-foot sprains is associated with a slightly increased risk of falls. These findings improve our understanding of the clinical consequences of ankle-foot sprains in terms of fall risk and suggest the importance of adopting more efficient strategies for managing residual functional deficits after the injuries.

Imputation and Missing Indicators for Handling Missing Longitudinal Data: Data Simulation Analysis Based on Electronic Health Record Data

Background

Missing data in electronic health records are highly prevalent and result in analytical concerns such as heterogeneous sources of bias and loss of statistical power. One simple analytic method for addressing missing or unknown covariate values is to treat missingness for a particular variable as a category onto itself, which we refer to as the missing indicator method. For cross-sectional analyses, recent work suggested that there was minimal benefit to the missing indicator method; however, it is unclear how this approach performs in the setting of longitudinal data, in which correlation among clustered repeated measures may be leveraged for potentially improved model performance.

objectives

This study aims to conduct a simulation study to evaluate whether the missing indicator method improved model performance and imputation accuracy for longitudinal data mimicking an application of developing a clinical prediction model for falls in older adults based on electronic health record data.

Methods

We simulated a longitudinal binary outcome using mixed effects logistic regression that emulated a falls assessment at annual follow-up visits. Using multivariate imputation by chained equations, we simulated time-invariant predictors such as sex and medical history, as well as dynamic predictors such as physical function, BMI, and medication use. We induced missing data in predictors under scenarios that had both random (missing at random) and dependent missingness (missing not at random). We evaluated aggregate performance using the area under the receiver operating characteristic curve (AUROC) for models with and with no missing indicators as predictors, as well as complete case analysis, across simulation replicates. We evaluated imputation quality using normalized root-mean-square error for continuous variables and percent falsely classified for categorical variables.

Results

Independent of the mechanism used to simulate missing data (missing at random or missing not at random), overall model performance via AUROC was similar regardless of whether missing indicators were included in the model. The root-mean-square error and percent falsely classified measures were similar for models including missing indicators versus those with no missing indicators. Model performance and imputation quality were similar regardless of whether the outcome was related to missingness. Imputation with or with no missing indicators had similar mean values of AUROC compared with complete case analysis, although complete case analysis had the largest range of values.

Conclusions

The results of this study suggest that the inclusion of missing indicators in longitudinal data modeling neither improves nor worsens overall performance or imputation accuracy. Future research is needed to address whether the inclusion of missing indicators is useful in prediction modeling with longitudinal data in different settings, such as high dimensional data analysis.

Association of lower-limb strength with different fall histories or prospective falls in community-dwelling older people: a systematic review and meta-analysis

BACKGROUND

Fall is a major health threat to older people. The lower-limb power and rate of torque or force development (RTD or RFD) are prominently affected by aging and are crucial for maintaining postural balance. However, there have been inconsistent findings regarding the association of such aspects of lower-limb strength with falls among community-dwelling older adults. Comprehensive synthesis and appraisal are needed to examine what deficits in lower-limb rapid force generation could identify the fallers (i.e., those with a fall history or prospective falls).

METHODS

This systematic review searched six databases, including PubMed, Web of Science, EMBASE, Scopus, CINAHL, and Cochrane CENTRAL. Meta-analysis was conducted to aggregate standardized mean differences (SMD) or odds ratios (OR). The quality of evidence regarding each strength parameter's ability to identify fallers was assessed using the GRADE approach.

RESULTS

Twenty observational studies with 8,231 community-dwelling older adults were included (mean age: 73.5 years; male to female ratio: approximately 6:1). Moderate quality of evidence showed that the lower average leg-press power (SMD & 95% CI: -0.17 [-0.23, -0.12]; OR & 95% CI: 0.84 [0.79, 0.89]) and lower peak sit-to-stand power (Cohen's d = 0.41) could predict prospective falls in older adults, especially the injurious/recurrent falls. Low quality of evidence showed that the lower peak sit-to-stand power could also discern fall history (SMD & 95% CI: -0.58 [-0.96, -0.20]). Conversely, low to very low quality of evidence showed that the RTD of a single muscle group could not predict prospective falls and was generally unable to identify fall history in older adults. DISCUSSIONS AND CONCLUSION: The decline of entire lower-limb power appears a good indicator of prospective falls in community-dwelling older adults. Tests of entire lower-limb power required the cumulative and coordinated contractions of more leg muscles, possibly explaining why they could identify the fallers whereas the RTD or power of a single muscle group could not. Future studies are warranted to determine cut-point values of the entire lower-limb power measurements in fall-risk assessment and explore rapid force generation of a single muscle group in predicting the injurious falls among older adults.

TRIAL REGISTRATION

Registration No.: CRD42021237091.

Risk Factors for Falls in Community-Dwelling Older Adults During the Novel Coronavirus Pandemic in Japan: A Prospective Cohort Study

This study aimed to test the hypothesis that knowledge derived from indirect assessments can be used to identify fall risk factors during a period of social distancing. A baseline survey of 1953 community-dwelling older adults was conducted in May 2020, with a follow-up survey performed in May 2023 to assess the situation 3 years later. In total, 339 individuals were followed from baseline to follow-up. Baseline age, sex, Questionnaire for Change of Life, Frailty Screening Index, and Questionnaire for Medical Checkup of Old-Old (QMCOO) scores and subscales were used to determine fall predictors. In addition, history of falls in the past year was assessed at follow-up (outcome). The participants were categorized into fall (n = 78) and non-fall (n = 261) groups. Using binary logistic regression analysis, items that showed significant differences in a between-group comparison were analyzed, and age and history of falls, which were sub-items of the QMCOO, were identified as predictors of falls. Although special assessments may be required during periods of social distancing, we believe that it is important for these assessments to continue being performed as they are performed during normal times.

Short physical performance battery is not associated with falls and injurious falls in older persons: longitudinal data of the SCOPE project

INTRODUCTION

Falls and fall-related injuries in older persons are a major public health problem. Our objective was to study the predictive value of the Short Physical Performance Battery (SPPB) in the cohort of the SCOPE project on falls, injurious falls, and possible difference of prediction between indoors and outdoors falls.

METHODS

For this sub-study of the SCOPE project participants reporting no falls at baseline, and survey data on falls at the 12-month and 24-month follow-up were included. Participant´s characteristics were assessed during the baseline interview and medical examinations. Falls as well as injurious falls and fall circumstances were obtained self-reported. SPPB and its association with fallers vs. no fallers at 12 and at 24 months were studied with logistic regression models.

RESULTS

The 1198 participants had a median age of 79 years (77-82), and a median SPPB of 10 (8-11), with a 52.5% of female. A total of 227 and 277 falls (12- and 24- month visits, respectively) were reported. In the crude model, the SPPB sum scores (p < 0.001) as well as most single item scores were significant different between fallers and non-fallers over time. However, the association was attenuated in models adjusted for age, sex, marital status, number of medications, quality of life, handgrip strength, and muscle mass [e.g., 12 months; OR 0.94 (0.87-1.02)]. While SPPB fails to differentiate between injurious and non-injurious falls (p = 0.48), a lower SPPB score was associated with falls at home (p < 0.01) after 24 months.

CONCLUSION

SBPP was not able to significantly predict the risk of falling as well as experiencing an injurious fall.

TRIAL REGISTRATION

This study was registered prospectively on 25th February 2016 at clinicaltrials.gov (NCT02691546).

In-Hospital Fall Risk Prediction by Objective Measurement of Lower Extremity Function in a High-Risk Population

OBJECTIVES

Limited data exist regarding association between physical performance and in-hospital falls. This study was performed to investigate the association between physical performance and in-hospital falls in a high-risk population.

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

The study population consisted of 1200 consecutive patients with a median age of 74 years (50.8% men) admitted to a ward with high incidence rates of falls, primarily in the departments of geriatrics and neurology, in a university hospital between January 2019 and December 2021.

METHODS

Short Physical Performance Battery (SPPB) was measured after treatment in the acute phase. As the primary end point of the study, the incidence of in-hospital falls was examined prospectively based on data from mandatory standardized incident report forms and electronic patient records.

RESULTS

SPPB assessment was performed at a median of 3 days after admission, and the study population had a median SPPB score of 3 points. Falls occurred in 101 patients (8.4%) over a median hospital stay of 15 days. SPPB score showed a significant inverse association with the incidence of in-hospital falls after adjusting for possible confounders (adjusted odds ratio for each 1-point decrease in SPPB: 1.19, 95% CI 1.10-1.28; P < .001), and an SPPB score ≤6 was significantly associated with increased risk of in-hospital falls. Inclusion of SPPB with previously identified risk factors significantly increased the area under the curve for in-hospital falls (0.683 vs. 0.740, P = .003).

CONCLUSION AND IMPLICATIONS

This study demonstrated an inverse association of SPPB score with risk of in-hospital falls in a high-risk population and showed that SPPB assessment is useful for accurate risk stratification in a hospital setting.