as statistically significant as the present study (p=0.027 OR:1.14 n=116). This discrepancy can be explained by differences in sample size and data collection procedures, as the data in the other study were collected by reviewing patient clinical history (2) . Another study also analyzed the association between the number of drugs taken and risk of falls; however, significant associations were found at ≥ 5 drugs per day, regardless of the type of medication (22) . A study conducted with hospitalized individuals inves- tigated the importance of drug-relatedfalls and reported similar findings, with one out of three individuals suffer- ing recurring falls every year. In that study, 77.1% of the analyzed population took 5 or more drugs, with a mean of 7.4 drugs per day, higher than that in the present study. However, the sample consisted of people of all ages. Of the 214 analyzed individuals, 88.8% were older than 60 (190 individuals), and a direct correlation was found between age and susceptibility to future falls. Significant associations were found between the risk of falls and the occurrence of recurrent falls and greater use of drugs (p=0.0001). In the present study, significant associations were found with the use of ≥ 4 drugs taken per day (23) . The sample consisted of noninstitutionalized functional olderadults above the age of 65, but age was not associated with the risk of falls. The only associated variable was the use of ≥ 4 drugs per day.
The baseline characteristics of transitional frail old- er adults are listed in Table 1. Subjects ranged in age from 71 to 96 years (mean age 83.6) and 39.4% were aged over 85. Eighty-four percent were women. They were taking an average of 5 drugs, and 43.9% took psychoactive drugs. Ninety-three percent of subjects who used psychoactive drugs also took more than 3 drugs per day. The mean score for distance visual acu- ity was 6±2.5, and 56.9% of subjects had a score <6. Abnormal basic mobility was observed in 63.6%, and mean Timed Up & Go time was 23.2±6.6 seconds. The mean MMSE score was 25.1±3.6, and cognitive impairment was present in 37.9%. Frail attributes, as determined by the Speechley and Tinetti criteria (18) were as follows: gait or balance impairment (62.1% of subjects), no walking for exercise (72.7%), no other physical activity (69.7%). Nineteen percent of the sub- jects were taking an antidepressant. Intake of psy- choactive drugs such as benzodiazepines, antidepres- sants or neuroleptics was present in 45.5%. Impaired near vision was observed in 83.3%. Impaired upper or lower extremity strength was present in 6.1% and 4.5%, respectively. Lower extremity disability was found in 24.2%.
The main aim of the current study was to reduce state anxiety in olderadults and measure the consequent changes to stepping performance. Our intended method of reducing anxiety through use of a weeklong course of progressive muscle relaxation and diaphragmatic breathing did not result in significantly lower anxiety than the control group. This may have been due to the relatively short time frame, and less time- intensive method of the intervention when compared to previous research (Dendato & Diener, 1986; Bastani et al., 2005). We did however find a significant reduction in salivary -amylase concentrations between the first and second sessions for all participants. Full statistical analysis was also run on the intervention group alone (n = 8, results not shown). This analysis revealed that there was a significant reduction in salivary -amylase change from baseline from the first session (16.8 ± 12.4U/mL/min) compared to the second (-4.9 ± 13.1U/mL/min, F(1,7) = 5.84, p < .05). However, there were no other significant between session differences in any other anxiety, stepping performance, or gaze related variables. Therefore we collapsed the groups in order to maximise statistical power. During the second session we found a reduction in target box hit frequency, and less mediolateral step variability during the greatest task complexity; the implications of which are discussed further in this section.
Our study demonstrated that patients with musculoskeletal system disease, including musculoskeletal disorder, osteoarthritis (OA), osteoporosis and fracture, were more likely to fall. A previous study  demonstrated an association with OA and fall risk. A study con- ducted by Sturnieks  suggested that elderly patients with lower limb arthritis are at increased risk for falling. Our study demonstrat- ed that there was a correlation between OA and falls (r=0.137, P<0.0001), which can be explained by changes in joint kinematics re- sulting from OA. Additionally, we demonstrated that osteoporosis was correlated (r=0.189, P<0.01) with falls. Seyfizadeh N  repor- ted that there was a significant association between age and osteoporosis. A possible explanation for our result is that reduced flexi- bility, lower bone density, muscular weakness and postural imbalance from osteoporosis pre- dispose patients to falls. Our results also sug- gest that fracture was associated with falls (r=0.188, P<0.0001). Fracture can be both a cause and a consequence of a fall event. Perez- Lopez  reported that fragility fractures are remarkably related to falls, which we found was consistent with a previous study. A possible reason for the correlation between fractures and falls was gait deficit, restricted physical function, and muscle weakness of the lower limb caused by previous fractures.
The ability to control the body’s position in space (postural control) and body’s cen- ter of mass in relation to the base of sup- port( postural stability) are dictated by the efficiency of the individual’s balance mechanism related to anticipatory postural adjustments, as well as compensatory pos- tural adjustment that are initiated by senso- ry feedback signals. The important sensory systems involved in postural control are somatosensory information, vestibular sys- tem and vision (10,11). Patients with visual impairment must place a greater emphasis on somatosensory and vestibular infor- mation to maintain postural stability and control body’s position in space (7,8). When vision is impaired, olderadults expe- rience greater problems with mobility that lead to reduced ability to perform inde- pendent activities of daily living (12,13). Vision allows a person to identify a poten- tial hazard and triggers a motor response in central nervous system. Decreasing visual processing speed reduces the ability of the older adult to detect hazards in the envi- ronment, and increases fallsrisk (14).
associated with falls. In fact a unit increase in this variability measure increased the risk of a previous fall in the past year by 14%. These results suggest that increasing variability in the executive or vigilance aspect of sustained attention is associated with falls in olderadults and may represent a novel marker of fallsrisk. Previous studies have reported significant associations between declining executive function and falls [17-19,23), or low scores/longer reaction times on tests of attention and increasing gait variability or postural instability, both of which are related to falls However reports looking specifically at attention have tended to focus on divided or selective attention during dual tasking or have selected olderadults with cognitive impairment, dementia, stroke and Parkinson’s disease (PD)., [25-28,53]. This paper directly associates reduced levels of sustained attention (and particularly vigilant attention) as measured by the SART) and falls in older community dwelling adults without a history of overt cognitive impairment, dementia, stroke or PD.
The most frequently encountered risk factors include: impaired balance and gait, lower muscle strength, lower psychomotor ability, polytherapy, and therapy with benzodiazepines [6, 9, 10]. Additional, health-related fac- tors include: pain; sense of weakness; chronic diseases – particularly neurological diseases, heart diseases, and diabetes; cognitive disorders, and urinary incontinence [4, 5, 9, 11]. Demographic factors discussed by authors of earlier research papers include: elderly age, female sex, low sociodemographic status . Further function- ing of persons who had previously suffered from falls depends on the consequences of fall, experience learned, and the degree of fear of falling again [12, 13]. Time of fall is also a noteworthy aspect, especially the time of the day, due to the morning or evening sleepiness and fatigue. Some authors report that falls suffered by people staying at their place of residence would usually take place in the morning and in the evening  while others it was during house chores [7, 14]. Scales most fre- quently used to assess gait fluency include Time Up and Go test (TUG) as well as Berg Balance Scale (BBS), and Tinneti test [6, 15]. Aachen Falls Prevention Scale is also being increasingly frequently referred to as a useful tool in independent fall risk monitoring by olderadults themselves .
Data come from the 2010 wave of the Chinese Longitu- dinal Survey on Urban and Rural Elderly, conducted by the Chinese Research Center on Aging (CRCA). Since 2000, the CRCA has started surveying community- dwelling rural and urban elders’ personal characteristics and a variety of issues including retirement and employ- ment after retirement, social welfare and security, hous- ing, community-based service programs and utilization, family networks and social participation, medical insur- ance and health programs, mental health and available psychological consulting services. The 2000 and 2006 waves did not include questions on older people’s fall related information. The 2010 wave is the first one that started collecting information on occurrences, incidence, circumstances, locations as well as consequences of elders’ falls. Based on the distribution of Chinese popula- tion aged 60 and over reported by the 2010 Census data, the survey applied multistage proportional random selection strategy to choose respondents from 20 (out of a total number of 31, excluding Hongkong, Macau and Taiwan areas) provinces, autonomous regions and muni- cipalities in China. The 20 provinces, autonomous regions and municipalities include Beijing, Hebei, Shanxi, Liaoning, Heilongjiang, Shanghai, Jiangsu, Zhe- jiang, Anhui, Fujian, Shandong, Henan, Hubei, Guang- dong, Guangxi, Sichuan, Yunnan, Shaanxi and Xinjiang. According to the 2010 Chinese Census data, 49.7% of the population lived in urban areas and the rest of 50.3% lived in rural areas. Thus, the 2010 Wave of the Chinese Longitudinal Survey on Urban and Rural Elderly sam- pled equivalent numbers of rural and urban elders. In each province, autonomous region and municipality, 500 rural and 500 urban respondents were interviewed. The sampling design is as follows: (1) Randomly choosing 4 cities or 4 counties in each province/autonomous region/municipality (in municipalities, districts are treated as equivalent to cities or counties); (2) In each city or county, randomly selecting 16 streets or villages; (3) In each street or village, randomly choosing 50 neighborhood or village committees; (4) In each neigh- borhood or village committee, randomly choosing 10 households with at least one senior aged 60 and over to participate the survey interview. Please see Fig. 1 for sampling scheme of the 2010 wave of the Chinese Longi- tudinal Survey on Urban and Rural Elderly.
141 4.1.3 Adverse drug reactions in patients with cancer
Polypharmacy (144) and IP (35) contribute to ADRs. ADRs are common, the prevalence in the general older adult population at time of hospital admission being as high as 20% depending on the definitions and methodologies used to identify ADRs. ADRs associated specifically with chemotherapy have been well studied. Indeed, potential toxicities are well documented in medications’ summary of product characteristics (SPCs) e.g. neutropenia can occur in 30% of patients receiving chemotherapy (190). In addition, multiple online educational resources exist e.g. http\\:www.chemocare.com and http\\:www.MacMillan.com. These clearly list, classify and risk stratify potential ADRs of chemotherapy so that patients, and clinical practitioners can be aware of, and vigilant for ADRs prior to and during treatment. However, little is known about the prevalence rates of non-chemotherapy related ADRs in patients with cancer and whether or not older patients with cancer are more vulnerable to ADRs than their younger counterparts.
The results of this population-based study inform us about the nature of the association between atypical antipsychotic drugs and hyponatremia. Our estimate is similar to that obtained in a previous case-control study that used individual case safety reports of hyponatremia to estimate a “reporting odds ratio” of 1.55 (95% CI 1.41 to 1.69). 17 This is a measure of disproportionality that estimates the extent to which hyponatremia is reported in association with an atypical antipsychotic drug relative to reports of hyponatremia with other drugs. The low absolute risk observed in our study is likely influenced by the low sensitivity of the hospital diagnosis code for hyponatremia (~11%), which underestimates the true incidence by up to eight-fold. 28 Currently, UpToDate ® a popular reference widely used by physicians, warns of the possibility of hyponatremia and recommends monitoring the concentration of serum sodium in olderadults upon initiation of an atypical antipsychotic drug. 32–34 Another important physician reference in our region, the Canadian Compendium of Pharmaceuticals and Specialties, does not provide information or recommendations related to hyponatremia with atypical antipsychotic medications. 35–37 Updates to these product monographs are warranted to
Larger delayed declines in blood pressure, and impaired recovery of blood pressure in response to orthostatic stress may be risk factors for falls in olderadults in long-term care. Impairments in the regulation of cerebral blood flow, the final physiological pathway implicated in fainting events, may also be an important risk factor for falling in elderly individuals. Those who were prone to falling had larger declines in systolic CBFV during ortho- static stress, providing a mechanistic link between OH, cerebral hypoperfusion and fall susceptibility. This is im- portant given the high reported incidence of both OH and falls in olderadults, and devastating impact of fall-related injury on quality of life for those affected [2, 3]. These relationships need to be further explored in prospective longitudinal studies that can better account for other fall- ing risk factors.
results may be due to the fact that only five percent of the participants had reported to experience a fall. Moreover, most of the olderadults were leading an active lifestyle, which is among the robust protective factor of falls. However, literature suggests that lower fallsrisk is related to more favourable built environment characteristics, such as having ramps at intersections, painting indicating curbs and well-lit places (Chippendale, Otr & Boltz 2014). Causes of falls are multifactorial, but one of the most common factors is environmental related, followed by balance impairments, muscle weakness and dizziness (Rubenstein 2006). It is also noteworthy that the frequency of outdoor falls was higher compared to indoor falls which was associated with higher leisure-time physical activity (li et al. 2006). thus, a safe and conducive environment for increasing physical activity is vital in promoting physical health status of olderadults.
Strengths and limitations of the study are as follow: The cross-sectional study design with a 12-month follow-up provided baseline information on participants. However, determination of risk factors and their associ- ation with falls was hindered by the cross-sectional data collection and retrospective recall of falls both at base- line and follow-up. A temporality between a fall and a risk factor could not be established within the cross- sectional design. The exclusion of subjects who were un- able to walk or to give consent to participate in the study may have excluded individuals with physical and mental frailty who are at increased risk of falls, and led to an underestimate of the prevalence of falls in this community. Subjects lost to follow-up, may have differed from those who remained in the study and the outcome is likely to be an under-estimate of the actual incidence, although the report of falls prior to baseline was not sig- nificantly different between those lost to follow-up and those who remained in the study. For rare outcomes such as recurrent falls, and risk factors such as drug classes, a larger sample would be required to allow for adequate analyses.
falls and can be considered a mediator between fear of fall- ing and falls . Interestingly, fear of falling has been reported in older people who have not fallen suggesting that factors other than falls history may influence the manifestation of fear of falling amongolder people [12,16]. Several studies have suggested that aspects of cogni- tion, particularly declining executive function, are corre- lated with and predictive of fallsrisk in olderadults without dementia or overt cognitive impairment [17-19]. Since deficits in executive function increase with age, this may impair the ability of the older person to com- pensate for age-related changes in gait and balance. This in turn, may compromise the ability of the older person to negotiate and cope with the complexities of their day to day surroundings [20-22]. This is supported by evi- dence from gait and balance studies, particularly dual tasks, indicating that gait performance and falls are related to executive function, and that falls have been associated with primary ageing of the prefrontal cortex [23,24]. Attention is a specific component of executive functioning. Low scores on tests of attention have been correlated with postural instability and increasing gait variability, both of which are related to falls [25,26]. Additional findings revealed that older people allocate more of their attentional resources toward their gait and that the attention-related changes that occur during aging increase the risk of falls [27,28].
have higher rates of falls compared to healthy olderadults (Deandrea et al., 2010; Lord,
Sherrington, Menz, & Close, 2007). Among chronic diseases, some evidence indicates that heart failure (HF) is an important risk factor for falls (Jansen, Kenny, de Rooij, & van der Velde, 2014; Stenhagen, Ekström, Nordell, & Elmståhl, 2013). Heart failure (HF) is a chronic condition in which an impaired heart is unable to adequately pump blood to the body. Impaired heart function produces various signs and symptoms, such as decreased exercise tolerance, impaired cognitive function, and postural hypotension that predisposes them to falls (Benjamin et al., 2017; Mosterd & Hoes, 2007; Murad & Kitzman, 2012). Some individuals suffering from HF also have physiologic impairments of the brain, especially in the area regulating motor function, which may alter gait and balance, placing them at higher risk for falling. In previous studies, the brain images of HF patients showed a loss of tissue integrity in gray matter and axons in the cerebellar cortices and deep nuclei of the brain, which are related to motor regulation alteration (Kumar et al., 2011; Woo et al., 2015). To alleviate their symptoms, HF patients often take medication such as diuretics, digoxin, or type IA anti-dysrhythmic, which are also recognized as high fall risk medications (Hartikainen, Lönnroos, & Louhivuori, 2007; Leipzig, Cumming, & Tinetti, 1999). Thus, HF patients can be seen as a high-risk population for falls.
prevention . Importantly the taxonomy stipulates the need for individual requirements by drawing on older adult perceptions to ensure simplicity, reliability and effectiveness .
Wearable-based fall detection algorithms rely on inertial sensor data to detect fall events (Table 3, recent examples). Within clinically led research few studies have categorised falls based on fall related activity, e.g. walking, going up/down stairs or transition [79, 80]. This is an opportunity for inertial-based wearables as recent work has highlighted clinically defined falls classifications from (e.g.) macro gait and transitional tasks [81, 82] which can be quantified from existing algorithms [45, 83]. Pragmatic innovation lies in the exploitation and fusion of existing algorithms to better inform fall events and to reduce false positives that might be generated during gait related activities, Figure 1. For example, pilot work used multiple algorithms to reduce false fall detection events (e.g. gait during stair ascent/descent) when tested on younger adults during scripted tests and an older adult with PD during free-living . The addition of automated stair ascent/descent identification , a common location for falls , would enhance efforts and provide free-living segmentation of stair descent which may offer better insight into fall risk compared to straight level gait . Thus, the fusion of existing algorithms can identify discrete gait activities linked to fall risk assessment which may better inform/improve ‘life-space’ , i.e. environment modification for those at risk of falls .
2001). Impaired balance is also related to falls (Lord et al., 1994; Sturnieks et al., 2004) and it is likely that cognitive and motor deficits interact with regard to the risk of falling. Furthermore, the control of gait and posture shifts from sub-cortical pathways to cortical networks in conditions such as Parkinson’s disease (Morris, Iansek, Matyas, & Summers, 1996). A decline in motor function because of old age can lead to a variety of compensatory behaviors (Holt et al., 2013; Raw, Kountouriotis, Mon-Williams, & Wilkie, 2012) that may be strategic, explicit and under conscious cognitive control. Indeed, in dual-task conditions (e.g., speaking while walking) olderadults may not reallocate resources appropriately and therefore fail to compensate adequately (Harley, Wilkie, & Wann, 2009). In support of the idea that motor and cognitive factors interact in fallsrisk, dual-task performance has been found to decline in individuals who have experienced a first fall over a 12-month period (Verghese et al., 2002).
The main limitation of this study is the lack of a follow-up. This prevents us from studying the effect of this intervention on actual rates of falling. In addition, subjects with certain medical conditions, who may have a higher risk of fall, were excluded from the study. We recognize that actual clinical relevance must be demonstrated definitively via future ran- domized controlled trials in high-riskolder populations. In addition, cognitive function was not measured in this study. The positive gait outcomes in our study may suggest that the exercise intervention would benefit the cognitive function in older people. Previous studies have found the positive change in gait ability associated with the improvement in cognitive function, 42 and concluded that regular physical activity is
Information regarding the epidemiology of ADEs in Canadian community settings is sparse. Our objec- tive was to identify high-risk medications in primary care settings. Because no administrative data exist on ADEs in Canadian community settings, we described medication-related adverse events associated with emergency department (ED) visits or hospitalizations amongolderadults using administrative data and com- pared these findings with the drug classes most fre- quently prescribed by primary care physicians. This study was part of a larger project using clinical scenar- ios to examine primary care physicians’ use of drug- laboratory alerts in prescribing decisions.