Open-access Falls in older adults: a practical approach

Queda em idosos: uma abordagem prática

ABSTRACT

Background:  Falls are a major problem in public health since they are an important cause of morbidity and mortality. To evaluate the risk of fall and prescribe preventive interventions may be a challenging task.

Objectives:  The objectives of this study are to summarize the most relevant information on the topic “falls in the elderly” and to give a critical view and practical clinical approach on this topic.

Methods:  In March 2022, a search of Pubmed database was performed, using the terms “fall elderly”, fall prevention”, “fall risk”, with the following parameters: five years, review, systematic review, meta-analysis, practice guidelines.

Results:  There are several risk factors for falls that can be grouped in different areas (psychosocial, demographic, medical, medication, behavioral, environmental). The clinical evaluation of an older adult prone to falls must include identification of risk factors through history and examination and identification of risk of falls through an assessment tool such as gait velocity, functional reach test, timed up and go, Berg balance test, and miniBEST test. Fall prevention strategies can be single or multiple, and physical activity is the most cited. Technology can be used to detect and prevent falls.

Conclusion:  A systematic approach to the older patient in risk of falls is feasible and may impact fall prevention.

Keywords: Accidental Falls; Aged

RESUMO

Antecedentes:  As quedas são um grande problema de saúde pública, uma vez que são uma importante causa de morbidade e mortalidade. A avaliação do risco de queda e a prescrição de intervenções preventivas podem ser tarefas desafiadoras.

Objetivo:  Estudo visa sintetizar as informações mais relevantes sobre o tema “quedas em idosos” e apresentar uma visão crítica e uma abordagem da prática clínica neste tema.

Métodos:  Em março de 2022, foi feita uma revisão bibliográfica no Pubmed, utilizando-se os termos “fall elder”, fall prevention”, “fall risk”, com os seguintes parâmetros s: 5 anos, revisão, revisão sistemática, meta-análise, diretrizes práticas.

Resultados:  Há inúmeros fatores de risco para quedas que podem ser agrupados em diferentes domínios (psicossocial, demográfico, condições clínicas, uso de medicamentos, comportamental, ambiental). A avaliação clínica de um idoso propenso a queda deve incluir a identificação de fatores de risco por meio da história e exame físico e identificação do risco de queda por meio de um instrumento de avaliação como velocidade da marcha, teste de alcance funcional, timed up and go, teste de equilíbrio de Berg, escala miniBEST. As estratégias de prevenção de quedas podem ser únicas ou múltiplas, sendo a atividade física a mais citada. Tecnologias podem ser usadas para detectar e prevenir quedas.

Conclusão:  Uma abordagem sistemática ao paciente idoso em risco de queda é possível, deve ser realizada e pode impactar na prevenção de quedas.

Palavras-chave Acidentes por Quedas; Idoso

INTRODUCTION

Falls are a major problem in public health since they are an important cause of morbidity and mortality. Fall rates vary among older adults according to age, but it is estimated that 30% of people over the age of 65 fall each year, and that this percentage increases up to 50% among people over 801-3, while half of these have recurrent falls4. Added to this, falls lead to mild to severe injuries, are the cause of 10-15% of all emergency department visits, and account for 40% of all injury deaths3. Besides physical consequences, falls also can result in psychological sequelae characterized by fear of falling, insecurity, self-limitation, functional impairment, and social isolation. This situation compromises the quality of life and increases the risk of further falls3.

The maintenance of a good postural balance is a complex task that involves an interaction to the environment, multiple afferences to the central nervous system, a complex integration, an efficient motor postural response and a good biomechanical support (Figure 1). Therefore, it is easy to understand that a fall can be the result of a problem in one or more of any of these stages. On the other hand, since there are several possible problems in this schema, identifying fall risks may be a challenging task. Furthermore, in most cases there are multiple risk factors involved and the fall cannot be attributed to a single cause. To evaluate the risk of fall of a patient may be another challenge, since there are different functional tools, with no consensus in the literature as to which one should be applied.

Figure 1.
Schematic representation of all systems involved in postural balance.

Thus, the aims of this review are to summarize the most relevant information on the topic “falls in the elderly” and to give a critical view and practical clinical approach in these cases. For this, the authors will answer the following questions: (1) Which are the most relevant fall risks in the elderly? (2) What is relevant in the physical and neurological examination? (3) How can one identify the risk of fall? (4) Which are the most important interventions to prevent falls? (5) How can new technologies help the management of older people with risk of fall?

FALL RISKS ASSESSMENT

Publications describe an extensive list of risk factors for falls in the elderly, and there is a great effort to establish those that are most important, although the models are still insufficient to predict those patients at risk. The predictive accuracy of risk factor models for falls is weak compared with models for cardiovascular events, and one of the main risk factors for falls in the elderly is a previous fall, meaning there is no proper primary prevention as yet4. One of the possible explanations for this is that risk factors for falls are not static, they can interact with each other, adding to or multiplying their impact4 (Figure 2).

Figure 2.
Schematic representation of fall risks domains. The arrows show the interaction between domains.

Therefore, screening the patient for risk factors for falls may be exhaustive. Epidemiological studies show dozens of risk factors, and some authors group these in different areas in order to make the analysis easier (Table 1) 3,5,6.

Table 1.
Fall risks factors grouped in different domains according to different authors.

However, a careful analysis shows that some factors are present in the three lists: age and sex, medication, medical conditions such as muscle weakness and visual changes, cognitive changes and depression, lack of physical activity/sedentary lifestyle. Next, we will comment on fall risks that we consider most relevant.

General characteristics

Falls incidence increases with age, a finding easy to understand since many other factors (balance problems, polypharmacy, sensory and muscular impairment) are more common in older people. Women are more prone to falls than men, although fall-related mortality is higher among older men3. Biological difference may contribute to a higher risk in women, as they have a faster muscle mass sarcopenia than men. On the other hand, men may have a higher fatality rate, maybe because they only seek medical assistance when they have a severe condition, and they are more engaged in dangerous and risky activities and behaviors3.

Falls among older people are associated with living alone3,7. A possible link between living alone and falls is depression, since isolation may increase depression, which increases the fear of falling, and vice-versa. Fear of falling can lead to less social interaction, loss of personal contact, and reduction of daily activity. This in turn reduces mobility and increases isolation and depression, and consequently increases the risk of falls7.

Medical conditions

Most authors agree that medical conditions such as stroke, dementia, Parkinson’s disease and peripheral neuropathy increase the risk of fall5,6. This is probably due to motor or cognitive dysfunctions that affect postural control.

There is a close relationship between gait and cognition, and both can be impaired in early stages of neurodegenerative disorders. Cognitive impairment is associated with disturbed gait parameters, falls are more frequent in patients with dementia, and the number of falls increases with the severity of cognitive disturbance8.

Other conditions such as cardiovascular diseases may also increase the risk of falls, although it is not clear if this increase is due to disease itself, or due to the association with other conditions that occur with cognitive decline6. Regarding the association between falls and orthostatic hypotension, this may be difficult to confirm as it is an intermittent condition, and may not be present at the consultation but even so may be related to a fall4,5. Vestibular disease, dizziness, foot problems, and arthritis are also thought to be associated with an increased fall risk, but this has not been proven, probably due to a lack of evidence5,9. However, elderly patients with multisite pain had a 51% higher chance of fall risk6. Pain may cause low balance confidence, reduced self-protection from falls, mobility limitations and difficulties in activities of daily life and thus increases risk of fall6.

Balance, mobility, sensory, neuromuscular, and physical function

Considering the classification of Lord et al, medication and sensory and neuromuscular domains were associated with 50% greater risk for recurrent falls and balance and mobility and psychological domain with 30% greater risk9.

Sensory and neuromuscular domain includes vision problems, peripheral sensation, and muscle weakness, so it is not a surprise that there exists an association with falls.

Reduced visual acuity, contrast sensitivity, stereo-acuity and visual motion perception are all visual problems related to increased fall risk10. Presbyopia, cataracts, glaucoma, and macular degeneration are common causes of these visual problems. Furthermore, the use of bifocal and multifocal lenses worsens depth perception and sensitivity to contrast, increasing the risk of falling mainly when going up and down stairs outdoors11.

In elderly people with no neurological diseases, there may be a decrease of sensory afferences. The proprioceptive change occurs by axonal degeneration and a decrease in sensory fiber density and degeneration of chondrocytes on the cartilaginous surface due to articular degenerative disease. With a loss of proprioceptive sensation, the individual has greater difficulty when walking in environments with insufficient lighting, which increases the risk of falls12.

Elderly people lose 1 to 2% of muscle mass and strength each year. This process, called sarcopenia, is more pronounced in women after the age of 60 and is probably one of the reasons for a higher female incidence of falls12.

Poor balance is one of the most important risk factors for falls, and the more difficult the balance task and the poorer performance of the task, the higher the risk of a fall5. Balance is also a complex ability and may also be linked to mobility and psychological aspects in the fall-risk assessment, as shown above. There is a corresponding relationship between falls, depression, mobility, and balance. The worse the balance and mobility, the higher the chance of depression and falls, while a fall increases the chance of depression, reduced mobility and poor balance13.

Although supplementation of vitamin D may lower the risk of falls (see below), vitamin D deficiency is not included as a risk factor, since it is not a fall risk itself, but rather weakens the musculoskeletal system and thus may be associated with falls6.

Medication

Polypharmacy (four or more drugs) or the use of specific classes of medication are important risk factors for falls5,6,9. Special care should be taken with psychoactive drugs (antidepressants, sedatives, opioids), anti-hypertensives (diuretics, b-blockers, vasodilators), skeletal muscle relaxants and antihistamine medication14,15.

The particular situation of a patient prone to falls and with depression may be challenging, as depression and the use of antidepressants are both fall risks. In this case, if clinical conditions allow, the antidepressant should be withdrawn16.

Behavioral and environmental factors

An important behavioral risk factor is the lack of physical activity. This is easy to understand, as physical activity is important for maintaining good health. It contributes to good muscular power and prevents functional decline3.

Regarding environmental factors, although they are usually included in the list, there is some consensus that they do not cause falls by themselves, rather there is an interaction of external hazardous features and intrinsic risk factors3,5,9. In this context, the most common environmental factors cited are slippery surfaces, loose rugs, insufficient lighting, and inappropriate footwear.

PHYSICAL AND NEUROLOGICAL EXAMINATION AND ASSESSMENT TOOLS

The aims of a physical and neurological examination and the use of assessment tools are different, and the physician should bear this in mind. Through a physical and neurological examination, it is possible to identify the risk factors, and to evaluate the functional status of all systems involved with balance (musculoskeletal, muscle strength, coordination, sensibility, visual and vestibular function, cognition). On the other hand, by using one or more assessment tools the objective is to evaluate the mobility or balance function status and to identify the risk of fall. Thus, a complete evaluation should contemplate both aspects.

Physical and neurological examination

As mentioned above, a physical and neurological examination should focus on a physiological approach, rather than a disease-oriented approach17. As an example, the examiner must evaluate and identify possible visual problems such as poor visual acuity or visual contrast sensitivity rather than making a diagnosis of cataracts or glaucoma. With this in mind, all necessary systems for good balance and mobility must be examined: muscular strength and tonus, coordination, proprioception, visual function, vestibular function and cognition in special executive functions14,17. A simple evaluation of gait can also be helpful, observing velocity, stride length, antalgic movements and balance14.

The examiner must also note that a marked deficit in one of these systems may alone explain a fall or disequilibrium. Nevertheless, most elderly patients have only mild to moderate deficits, and the combination of multiple impairments is in most cases the reason for falling17.

Fall risk assessment tools

Once the patient has been examined and physical and neurological deficit has been identified, the physician can use one or two assessment tools to verify mobility, balance and the fall risk.

Review papers about fall risk assessment list up to 28 different functional measurement tools18,19, and to make an analysis of all these tools is not our objective. Among all these tools, a few are often used and cited and are easy to perform in a practical and clinical approach and will be further discussed (Table 2). Although there is no consensus on which tests should be used, there is some agreement that an ideal evaluation should incorporate more than one test18,20.

Table 2.
Assessment tools frequently used to identify risk of fall.

These assessment tools can be divided into single-performance tests (gait velocity and functional reach test) and multidimensional performance tests (timed up and go, Berg balance test, miniBEST test).

The objective functional reach test (FRT) is intended to evaluate how far the person can lean forward without taking a step or losing balance. Normal values are above 18,5cm 21 and values below that point are associated with an increased risk of fall22.

Although walking may be seen as an easy task, it is quite a complex one and is considered a useful sign of functional mobility, as the slower the gait, the greater the chance of adverse events23. To measure gait velocity is very simple, but a few pitfalls must be mentioned: (1) the distance must be 3-10 meters, and longer distances give more reliable measures, (2) a small distance for acceleration and deceleration can be used, but the velocity must be measured only in a predetermined line; (3) the patient must be specifically instructed to walk at a comfortable, normal speed24. Normal gait speed is different for different ages, and older adults have a slower velocity25, thus cut-off values for risk of fall range from 0.7m/sec to 1.0m/sec20,26.

There is some controversy regarding the usefulness of the Berg balance scale27 for assessing fall risk in the elderly28,29, and a ceiling effect has been reported28, but this is still one of the most cited tools. A recent review and meta-analysis observed that cut-off for risk of fall between 45 and 49 points had a good predictive validity in sensitivity29.

The timed up and go test30 has long been used and a vast number of modifications such as walking as fast as possible, walking distances greater than three meters, additional cognitive or motor tasks have been described18. Normal values increase with age and range from eight seconds in people aged 60-69 to 12 seconds in those aged 80-8925. Thus, the cut-off for fall risk also shows variations from 11-13sec18,20.

Through the mini-Balance Evaluation Systems Test (miniBESTest) scale it is possible to evaluate the performance in 14 tasks related to four aspects of dynamic balance: anticipatory adjustment, compensatory response, sensory organization, and gait. Each of the items can be graded between 0 and 2 points, the highest score being related to a better functional status31. Since older adults have a poorer performance and lower score, the cut-off values for fall risk in adults from 60 to above 90 range from 17 to 25 points32,33.

INTERVENTIONS TO PREVENT FALLS

As falls in older people are multifactorial, relating to behavioral, environmental, socio-economic, and biological factors, efforts to prevent falls in the elderly should not be isolated. The prevention of falls in the elderly is supported by the Active Aging policy. According to the World Health Organization, Active Aging is “the process of optimizing opportunities for health, participation and security in order to enhance quality of life as people age”. The determinant factors of Active Aging are gender, culture, access to health and social services, behavioral determinants, physical environment, personal, social, and economic determinants3. Once functional capacity is impaired in the older age, fall prevention measures should be instituted to reduce falls and the complications resulting from them.

Based on the knowledge of risk factors for falls previously discussed, several studies have analyzed the effectiveness of simple and multiple interventions. Theoretically, for each fall risk factor there would be a prevention intervention. However, many risk factors are non-modifiable and prevention is limited. In this situation, promoting the understanding of these non-modifiable factors that result in falls can help to raise the awareness of older people and care providers that they should be more cautious in hazardous situations5.

The interventions are often based on known modifiable risk factors for falling and many studies have evaluated the effectiveness of different interventions for the prevention of falls in the elderly. Many systematic reviews and meta-analysis studies have analyzed the effectiveness of different intervention programs to reduce the risk of falls, including single, multiple, and multifactorial interventions. Although studies have shown promising results, interventions have varied isolated or combined strategies resulting in data heterogeneity and difficulty in generalizing positive results34.

Therefore, it has been necessary to develop a standardization through a taxonomy and common data collection system. Gillespie et al. categorized the interventions using the fall prevention classification system developed by the Prevention of Falls Network Europe (ProFaNe)35,36 (Table 3).

Table 3.
Components of fall prevention.

The interventions to prevent the fall risk in older people are classified into three major groups37:

  • Single intervention;

  • Multifactorial interventions: two or more interventions are given to a person according to the individual risk factor profile (e.g., the intervention exercise and home-hazard modification is applied to one person, whereas home-hazard modification and medication modification may be performed in another);

  • Multiple interventions: two or more interventions are applied to all individuals participating in the fall prevention program (e.g., supervised exercise and vitamin D supplementation).

Thus, we will discuss the different prevention interventions to be performed alone or in combination (Table 4).

Table 4.
Modifiable and non-modifiable fall risk factors and possible interventions to prevent falls.

Interventions in non-modifiable conditions

For risk factors that have no scope for correction, such as advanced age and female gender, intervention strategies must be performed with the individual and caregivers raising awareness of the increased risk of falls5.

Medical conditions

Many clinical and neurological conditions can contribute to the increased risk of falls. Intervention should be instituted as soon as the fall risk assessment is performed, regardless of a lack of evidence, in order to reduce the number of falls. In systematic review studies, for example, improving the management of chronic diseases, depression, and pain has been shown to potentially have much more effect on quality of life than on reducing falls, although this has not been tested37.

Cognitive training (non-physical practice) can improve physical performance of older adults during single-task and dual-task walking (for example, walking while talking). It can be performed using a computerized version of cognitive training with a suggested session duration of 45 minutes or less. A shorter period of cognitive training helps to improve an acceptance of this intervention38.

A vision assessment and treatment with corrective lenses or surgery, in combination with exercises, is strongly associated with reduction in injurious falls. The same is observed when multiple interventions are combined including exercises, vision assessment and treatment, environmental modification, and vitamin D supplementation2.

Exercises

Interventions with exercises are the most studied in prevention of falls and they have shown a reduction in both the rate of falls and the number of people who have falls. No difference was observed between groups of individuals with a high risk of falling or not. In all types of exercises the outcomes were better in reducing falls when interventions were performed by health professionals compared with interventions by trained instructors who were not health professionals39. The main categories of exercise programs associated with high-certainty evidence of fall reduction are balance and functional exercises. Interventions with multiple categories of exercises, mainly programs including balance and functional exercises plus resistance exercises, probably reduce falls (moderate-certainty evidence) though it was uncertain whether exercises classified as 3D (Tai Chi or similar) using the ProFaNE taxonomy reduced the rate of falls (very low-certainty evidence)40. Despite the latter interventions showing less evidence, the great heterogeneity observed in the systematic review studies does not allow a precise evaluation of these data.

Fall prevention interventions with exercise lasting less than six months were not effective in reducing the risk of falling. When these programs have a longer duration, lasting from six to 12 months or 12 months, the fall risk is reduced in 33% and 36%, respectively41. Similarly, the beneficial effects of different programs of exercises in fall risk in older people are related to the frequency of intervention. These effects were shown with a frequency of three to five times a week42.

Medication

Medication review is a necessary intervention that includes different actions (withdrawal, dose reduction or increase, substitution, provision) targeted to specific classes of drugs, mainly those that cause hypotension, cardiac effects, hypoglycemic medications, skeletal muscle relaxants, antihistamine medications and mainly drugs acting on the central nervous system3,5.

Regarding vitamin D supplementation, randomized controlled trials showed inconsistent findings, positive or negative, according to dosage of vitamin D43,44. However, the effectiveness of vitamin D supplementation for the prevention of falls is related to the basal serum levels of 25(OH)D in the elderly. Trials with vitamin D supplementation in older people with concentrations less than 20ng/mL demonstrated beneficial effects on preventing falls45. Unlike isolated vitamin D supplementation in fall prevention, the combination of vitamin D and calcium showed a 12% reduction in the risk of falls and benefits to musculoskeletal function and bone metabolism45,46.

Behavioral and environmental interventions

Fall prevention education promotes fall risk awareness and knowledge facilitating engagement in behavior and lifestyle changes, such as physical activity. Although the target of this intervention is the elderly, in order that it can attain positive results, it must be applied to both the elderly, caregivers, health professionals and the wider communities in which the older people live3.

Environmental interventions are related to the adaptations of homes, walking aids and aids for personal protection and changes in social environment mobility. Adaptation of homes refers for example to ambient lighting, suitability of beds, chairs, attention to rugs and slippery surfaces, and other factors. Walking-sticks, walking-frames, wheelchairs, orthopedic footwear are some aids for walking assistance and personal protection3.

TECHNOLOGY IN FALL DETECTION AND PREVENTION

With advances in technology, researchers have developed techniques for detecting and preventing falls in the elderly, and some will be briefly discussed.

Fall detection devices

Fall detection systems are used in order to establish whether an older person has had a fall through an alarm sent to health professionals, and so the consequences of falls are minimized. These systems continuously monitor older individuals using devices to find the fall prediction. These can be divided into three categories47,48:

  • wearable devices consist of accelerometers, gyroscopes, magnetometers, etc. The posture and movement sensors process the information and decide if it is a fall or not. The decision is communicated to the pre-selected caregivers. The disadvantages of these devices are that they are intrusive and can be an extra burden to some individuals. Moreover, there is the risk of device displacement during everyday activities and less accurate results;

  • camera-based devices, placed at selected locations around the individual for continuous monitoring. The major disadvantages of these systems are their limited coverage and that they compromise the user’s privacy;

  • ambience devices that are a series of sensors strategically installed close to the individual, such as a wall, floor, bed, etc. The data are processed, and an algorithm decides whether there is a fall or not and then the caregivers are notified.

Fall preventing devices

For the future, there are many machines learning algorithms still under development based on the data collected by sensors and data processing to identify and prevent falls.

Today a system of fall injury prevention is already available: the wearable airbag. This multisensory smart wearable belt detects collision with the ground surface. With a response time of 0.133 second it triggers two large-size airbags that lessen the fall impact. The limiting factors are the high cost and its effectiveness has not been evaluated on a large scale49.

Fall intervention devices

Fall intervention devices are used to improve the knowledge, mobility, and balance in older people. However, there is still no evidence that using these technology-based applications prevent falls49. The main examples of these technologies are: exergame and VR system; robot personal coaching system for fall education and walking-aid cane robot for real-time assessment of mobility and support to the user.

In conclusion, falls are a major problem in public health with physical and psychological consequences, compromising the quality of life and increasing the risk of further falls.

Several risk factors for falls that can be grouped in different domains (psychosocial, demographic, medical, medication, behavioral, environmental) and the clinical evaluation of an older adult prone to falls must include identification of these risk factors through history and examination. Furthermore, identification of risk of fall must be done through an assessment tool such as gait velocity, functional reach test, timed up and go, Berg balance test, miniBEST test. Fall prevention strategies can be single or multiple, and physical activity is the most cited. Technologies can be used to detect and prevent falls. Thus, a systematic approach to the older patient at risk of fall is feasible and may impact fall prevention.

References

  • 1. Bergen G, Stevens MR, Burns ER. Falls and fall injuries among adults ages over 65 years. MMWR Morb Mortal Wkly Rep. 2016 Sep 23;65(37):993-8. https://doi.org/10.15585/mmwr.mm6537a2
    » https://doi.org/10.15585/mmwr.mm6537a2
  • 2. Tricco AC, Thomas SM, Veroniki AA, Hamid JS, Cogo E, Strifler L, et al. Comparisons of interventions for preventing falls in older adults: a systematic review and meta-analysis. JAMA. 2017 Nov 7;318(17):1687-99. https://doi.org/10.1001/jama.2017.15006
    » https://doi.org/10.1001/jama.2017.15006
  • 3. World Health Organization. WHO global report on falls prevention in older age [Internet]. Geneva (CH): World Health Organization; 2014 [cited 2022 Mar 3]. 53 p. Available from: https://extranet.who.int/agefriendlyworld/wp-content/uploads/2014/06/WHo-Global-report-on-falls-prevention-in-older-age.pdf
    » https://extranet.who.int/agefriendlyworld/wp-content/uploads/2014/06/WHo-Global-report-on-falls-prevention-in-older-age.pdf
  • 4. Klenk J, Becker C, Palumbo P, Schwickert L, Rapp K, Helbostad JL, et al. Conceptualizing a dynamic fall risk model including intrinsic risks and exposures. J Am Med Dir Assoc. 2017 Nov 1;18(11):921-7. https://doi.org/10.1016/j.jamda.2017.08.001
    » https://doi.org/10.1016/j.jamda.2017.08.001
  • 5. Lord SR, Menz HB, Sherrington C. Falls in older people: risk factors and strategies for prevention. In: Geusens P, Sambrook PN, Lindsay R. Osteoporosis in clinical practice: a practical guide for diagnosis and treatment. London (UK): Springer; 2004. p. 93-9.
  • 6. Kim J, Lee W, Lee SH. A systematic review of the guidelines and delphi study for the multifactorial fall risk assessment of community-dwelling elderly. Int J Environ Res Public Health. 2020 Aug 21;17(17):6097. https://doi.org/10.3390/ijerph17176097
    » https://doi.org/10.3390/ijerph17176097
  • 7. Petersen N, König H-H, Hajek A. The link between falls, social isolation and loneliness: a systematic review. Arch Gerontol Geriatr. 2020 May-Jun;88:104020. https://doi.org/10.1016/j.archger.2020.104020
    » https://doi.org/10.1016/j.archger.2020.104020
  • 8. Zhang W, Low L-F, Schwenk M, Mills N, Gwynn JD, Clemson L. Review of Gait, Cognition, and Fall Risks with Implications for Fall Prevention in Older Adults with Dementia. Dement Geriatr Cogn Disord. 2019 Dec;48(1-2):17-29. https://doi.org/10.1159/000504340
    » https://doi.org/10.1159/000504340
  • 9. Jehu DA, Davis JC, Falck RS, Bennett KJ, Tai D, Souza MF, et al. Risk factors for recurrent falls in older adults: a systematic review with meta-analysis. Maturitas. 2021 Feb 1;144:P23-8. https://doi.org/10.1016/j.maturitas.2020.10.021
    » https://doi.org/10.1016/j.maturitas.2020.10.021
  • 10. Saftari LN, Kwon O-S. Ageing vision and falls: a review. J Physiol Anthropol. 2018 Apr 23;37(1):11. https://doi.org/10.1186/s40101-018-0170-1
    » https://doi.org/10.1186/s40101-018-0170-1
  • 11. Reed-Jones RJ, Solis GR, Lawson KA, Loya AM, Cude-Islas D, Berger CS. Vision and falls: a multidisciplinary review of the contributions of visual impairment to falls among older adults. Maturitas. 2013 May 1;75(1):P22-8. https://doi.org/10.1016/j.maturitas.2013.01.019
    » https://doi.org/10.1016/j.maturitas.2013.01.019
  • 12. Pasma JH, Engelhart D, Schouten AC, van der Kooij H, Maier AB, Meskers CGM. Impaired standing balance: the clinical need for closing the loop. Neuroscience. 2014 May 16;267:157-65. https://doi.org/10.1016/j.neuroscience.2014.02.030
    » https://doi.org/10.1016/j.neuroscience.2014.02.030
  • 13. Gambaro E, Gramaglia C, Azzolina D, Campani D, Dal Molin A, Zeppegno P. The complex associations between late life depression, fear of falling and risk of falls. A systematic review and meta-analysis. Ageing Res Rev. 2022 Jan;73:101532. https://doi.org/10.1016/j.arr.2021.101532
    » https://doi.org/10.1016/j.arr.2021.101532
  • 14. Cuevas-Trisan R. Balance problems and fall risks in the elderly. Phys Med Rehabil Clin N Am. 2017 Nov;28(4):727-37. https://doi.org/10.1016/j.pmr.2017.06.006
    » https://doi.org/10.1016/j.pmr.2017.06.006
  • 15. Bolding DJ, Corman E. Falls in the geriatric patient. Clin Geriatr Med. 2019 Feb 1;35(1):P115-26. https://doi.org/10.1016/j.cger.2018.08.010
    » https://doi.org/10.1016/j.cger.2018.08.010
  • 16. van Poelgeest EP, Pronk AC, Rhebergen D, van der Velde N. Depression, antidepressants and fall risk: therapeutic dilemmas-a clinical review. Eur Geriatr Med. 2021 Jun;12(3):585-96. https://doi.org/10.1007/s41999-021-00475-7
    » https://doi.org/10.1007/s41999-021-00475-7
  • 17. Lord SR, Menz HB, Tiedemann A. A physiological profile approach to falls risk assessment and prevention. Phys Ther. 2003 Mar 1;83(3):237-52. https://doi.org/10.1093/ptj/83.3.237
    » https://doi.org/10.1093/ptj/83.3.237
  • 18. Gafner SC, Allet L, Hilfiker R, Bastiaenen CHG. Reliability and diagnostic accuracy of commonly used performance tests relative to fall history in older persons: a systematic review. Clin Interv Aging. 2021 Aug 28;16:1591-616. https://doi.org/10.2147/CIA.S322506
    » https://doi.org/10.2147/CIA.S322506
  • 19. Park S-H. Tools for assessing fall risk in the elderly: a systematic review and meta-analysis. Aging Clin Exp Res. 2018 Jan;30(1):1-16. https://doi.org/10.1007/s40520-017-0749-0
    » https://doi.org/10.1007/s40520-017-0749-0
  • 20. Lusardi MM, Fritz S, Middleton A, Allison L, Wingood M, Phillips E, et al. Determining risk of falls in community dwelling older adults: a systematic review and meta-analysis using posttest probability. J Geriatr Phys Ther. 2017 Jan-Mar;40(1):1-36. https://doi.org/10.1519/JPT.0000000000000099
    » https://doi.org/10.1519/JPT.0000000000000099
  • 21. Weiner DK, Duncan PW, Chandler J, Studenski S. Functional reach: a marker of physical frailty. J Am Geriatr Soc. 1992 Mar;40(3):203-7. https://doi.org/10.1111/j.1532-5415.1992.tb02068.x
    » https://doi.org/10.1111/j.1532-5415.1992.tb02068.x
  • 22. Thomas JI, Lane JV. A pilot study to explore the predictive validity of 4 measures of falls risk in frail elderly patients. Arch Phys Med Rehabil. 2005 Aug;86(8):1636-40. https://doi.org/10.1016/j.apmr.2005.03.004
    » https://doi.org/10.1016/j.apmr.2005.03.004
  • 23. Middleton A, Fritz SL, Lusardi M. Walking speed: the functional vital sign. J Aging Phys Act. 2015 Apr;23(2):314-22. https://doi.org/10.1123/japa.2013-0236
    » https://doi.org/10.1123/japa.2013-0236
  • 24. Graham JE, Ostir GV, Fisher SR, Ottenbacher KJ. Assessing walking speed in clinical research: a systematic review. J Eval Clin Pract. 2008 Aug;14(4):552-62. https://doi.org/10.1111/j.1365-2753.2007.00917.x
    » https://doi.org/10.1111/j.1365-2753.2007.00917.x
  • 25. Steffen TM, Hacker TA, Mollinger L. Age- and gender-related test performance in community-dwelling elderly people: Six-Minute Walk Test, Berg Balance Scale, Timed Up & Go Test, and gait speeds. Phys Ther. 2002 Feb 1;82(2):128-37. https://doi.org/10.1093/ptj/82.2.128
    » https://doi.org/10.1093/ptj/82.2.128
  • 26. Montero-Odasso M, Schapira M, Soriano ER, Varela M, Kaplan R, Camera LA, et al. Gait velocity as a single predictor of adverse events in healthy seniors aged 75 years and older. J Gerontol A Biol Sci Med Sci. 2005 Oct 1;60(10):1304-9. https://doi.org/10.1093/gerona/60.10.1304
    » https://doi.org/10.1093/gerona/60.10.1304
  • 27. Berg KO, Wood-Dauphinee SL, Williams JI, Maki B. Measuring balance in the elderly: validation of an instrument. Can J Public Health. 1992 Jul-Aug;83 Suppl 2:S7-11.
  • 28. Lima CA, Ricci NA, Nogueira EC, Perracini MR. The Berg Balance Scale as a clinical screening tool to predict fall risk in older adults: a systematic review. Physiotherapy. 2018 Dec 1;104(4):P383-94. https://doi.org/10.1016/j.physio.2018.02.002
    » https://doi.org/10.1016/j.physio.2018.02.002
  • 29. Park S-H, Lee Y-S. The diagnostic accuracy of the berg balance scale in predicting falls. West J Nurs Res. 2017 Nov 1;39(11):1502-25. https://doi.org/10.1177/0193945916670894
    » https://doi.org/10.1177/0193945916670894
  • 30. Podsiadlo D, Richardson S. The timed "Up & Go": a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991 Feb;39(2):142-8. https://doi.org/10.1111/j.1532-5415.1991.tb01616.x
    » https://doi.org/10.1111/j.1532-5415.1991.tb01616.x
  • 31. Franchignoni F, Horak F, Godi M, Nardone A, Giordano A. Using psychometric techniques to improve the Balance Evaluation Systems Test: the mini-BESTest. J Rehabil Med. 2010 Apr;42(4):323-31. https://doi.org/10.2340/16501977-0537
    » https://doi.org/10.2340/16501977-0537
  • 32. Magnani PE, Genovez MB, Porto JM, Zanellato NFG, Alvarenga IC, Freire RC Jr, et al. Use of the BESTest and the Mini-BESTest for fall risk prediction in community-dwelling older adults between 60 and 102 years of age. J Geriatr Phys Ther. 2020 Oct-Dec;43(4):179-84. https://doi.org/10.1519/JPT.0000000000000236
    » https://doi.org/10.1519/JPT.0000000000000236
  • 33. Marques A, Almeida S, Carvalho J, Cruz J, Oliveira A, Jácome C. Reliability, validity, and ability to identify fall status of the balance evaluation systems test, mini-balance evaluation systems test, and brief-balance evaluation systems test in older people living in the community. Arch Phys Med Rehabil. 2016 Dec 1;97(12):P2166-2173.e1. https://doi.org/10.1016/j.apmr.2016.07.011
    » https://doi.org/10.1016/j.apmr.2016.07.011
  • 34. Senderovich H, Tsai PM. Do exercises prevent falls among older adults: Where are we now? A systematic review. J Am Med Dir Assoc. 2020 Sep 1;21(9):P1197-1206.e2. https://doi.org/10.1016/j.jamda.2020.05.010
    » https://doi.org/10.1016/j.jamda.2020.05.010
  • 35. Gillespie LD, Robertson MC, GIllespie WJ, Sherrington C, Gates S, Clemson LM, et al. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2012 Sep 12;2012(9):CD007146. https://doi.org/10.1002/14651858.CD007146.pub3
    » https://doi.org/10.1002/14651858.CD007146.pub3
  • 36. Skelton DA, Todd CJ; ProFaNE Group. Prevention of Falls Network Europe: a thematic network aimed at introducing good practice in effective falls prevention across Europe. Four years on. J Musculoskelet Neuronal Interact. 2007 Jul-Sep;7(3):273-8.
  • 37. Hopewell S, Adedire O, Copsey BJ, Boniface GJ, Sherrington C, Clemson L, et al. Multifactorial and multiple component interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2018 Jul 23;7(7):CD012221. https://doi.org/10.1002/14651858.CD012221.pub2
    » https://doi.org/10.1002/14651858.CD012221.pub2
  • 38. Marusic U, Verghese J, Mahoney JR. Cognitive-based interventions to improve mobility: a systematic review and meta-analysis. J Am Med Dir Assoc. 2018 Jun 1;19(6):P484-491.e3. https://doi.org/10.1016/j.jamda.2018.02.002
    » https://doi.org/10.1016/j.jamda.2018.02.002
  • 39. Sherrington C, Fairhall NJ, Wallbank GK, Tiedemann A, Michaleff ZA, Howard K, et al. Exercise for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2019 Jan 31;1(1):CD012424. https://doi.org/10.1002/14651858.CD012424.pub2
    » https://doi.org/10.1002/14651858.CD012424.pub2
  • 40. Sherrington C, Fairhall N, Wallbank G, Tiedemann A, Michaleff ZA, Howard K, et al. Exercise for preventing falls in older people living in the community: an abridged Cochrane systematic review. Br J Sports Med. 2020 Aug;54(15):885-91. https://doi.org/10.1136/bjsports-2019-101512
    » https://doi.org/10.1136/bjsports-2019-101512
  • 41. Finnegan S, Seers K, Bruce J. Long-term follow-up of exercise interventions aimed at preventing falls in older people living in the community: a systematic review and meta-analysis. Physiotherapy. 2019 Jun 1;105(2):187-99. https://doi.org/10.1016/j.physio.2018.09.002
    » https://doi.org/10.1016/j.physio.2018.09.002
  • 42. Sun M, Min L, Xu N, Huang L, Li X. The effect of exercise intervention on reducing the fall risk in older adults: a meta-analysis of randomized controlled trials. Int J Environ Res Public Health. 2021 Nov 29;18(23):12562. https://doi.org/10.3390/ijerph182312562
    » https://doi.org/10.3390/ijerph182312562
  • 43. Smith LM, Gallagher JC, Suiter C. Medium doses of daily vitamin D decrease falls and higher doses of daily vitamin D3 increase falls: a randomized clinical trial. J Steroid Biochem Mol Biol. 2017 Oct;173:317-22. https://doi.org/10.1016/j.jsbmb.2017.03.015
    » https://doi.org/10.1016/j.jsbmb.2017.03.015
  • 44. Khaw K-T, Stewart AW, Waayer D, Lawes CMM, Toop L, Camargo CA Jr, et al. Effect of monthly high-dose vitamin D supplementation on falls and non-vertebral fractures: secondary and post-hoc outcomes from the randomised, double-blind, placebo-controlled ViDA trial. Lancet Diabetes Endocrinol. 2017 Jun 1;5(6):P438-47. https://doi.org/10.1016/S2213-8587(17)30103-1
    » https://doi.org/10.1016/S2213-8587(17)30103-1
  • 45. Ling Y, Xu F, Xia X, Dai D, Xiong A, Sun R, et al. Vitamin D supplementation reduces the risk of fall in the vitamin D deficient elderly: an updated meta-analysis. Clin Nutr. 2021 Nov 1;40(11):P5531-7. https://doi.org/10.1016/j.clnu.2021.09.031
    » https://doi.org/10.1016/j.clnu.2021.09.031
  • 46. Murad MH, Elamin KB, Elnour NOA, Elamin MB, Alkatib AA, Fatourechi MM, et al. The effect of vitamin D on falls: a systematic review and meta-analysis. J Clin Endocrinol Metab. 2011 Oct 1;96(10):2997-3006. https://doi.org/10.1210/jc.2011-1193
    » https://doi.org/10.1210/jc.2011-1193
  • 47. Tanwar R, Nandal N, Zamani M, Manaf AA. Pathway of trends and technologies in fall detection: a systematic review. Healthcare (Basel). 2022 Jan 17;10(1):172. https://doi.org/10.3390/healthcare10010172
    » https://doi.org/10.3390/healthcare10010172
  • 48. Usmani S, Saboor A, Haris M, Khan MA, Park H. Latest research trends in fall detection and prevention using machine learning: a systematic review. Sensors (Basel). 2021 Jul 29;21(15):5134. https://doi.org/10.3390/s21155134
    » https://doi.org/10.3390/s21155134
  • 49. Oh-Park M, Doan T, Dohle C, Vermiglio-Kohn V, Abdou A. Technology utilization in fall prevention. Am J Phys Med Rehabil. 2021 Jan 1;100(1):92-9. https://doi.org/10.1097/PHM.0000000000001554
    » https://doi.org/10.1097/PHM.0000000000001554

Publication Dates

  • Publication in this collection
    12 Aug 2022
  • Date of issue
    May 2022

History

  • Received
    15 Mar 2022
  • Accepted
    29 Apr 2022
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