The Movement Towards Recommending Exercise as Being Beneficial to Cancer Care
Dr Selena Young MBBS, MPallC, FRANZCR Radiation Oncologist www.genesiscare.com/au
In May 2022, the American Society of Clinical Oncology (ASCO) added to the growing chorus of voices recognising exercise as an important part of cancer care.1-4 While the ASCO guidelines mirrored previous recommendations, theirs took a different approach to reviewing the extensive literature describing the benefits of exercise.1 They aimed to provide guidance on exercise, diet and weight management during active treatment.1 This approach helps to clarify the value of exercise during this critical phase of the cancer continuum and offers insight into the value of clinicians incorporating exercise guidance into care.1 The recommendations were based on evidence from 42 systematic reviews and 13 randomised controlled trials (RCTs) that were specific to exercise.1 Breast cancer was one of the most commonly studied cancer types across the literature reviewed.1 The evidence showed exercise offers several benefits for patients undergoing treatment, which may include:1,5
• Decreased fatigue
• Preservation of cardiorespiratory fitness, physical function, and muscular strength
• For some cancers, including breast cancer, increased quality of life and decreased anxiety/depression
There is also emerging evidence from animal models that exercise may enhance treatment effectiveness.6,7 Based on these outcomes, ASCO concluded that oncology providers should provide guidance on exercise during cancer treatment.1 Specifically, to recommend regu-
lar aerobic and resistance exercise during active treatment with curative intent.1
Moving the guidelines into practice
As noted by the ASCO guideline authors, it is important to consider how these guidelines will be implemented into care as exercise is not yet routinely offered in oncology care.1,8
“Facilitating implementation of these recommendations for exercise during cancer treatment will require addressing barriers to this care that exist at the patient, clinician, health system, and policy levels.”1
Previous research has identified a long list of barriers to implementation of exercise recommendations in cancer care.8 These have included organisational issues, such as lack of referral systems and lack of time to provide referrals, a lack of awareness about which patients would benefit from exercise, what to recommend and how to safely prescribe during treatment.8 Clinician assumptions of patient willingness to receive exercise instructions and current fitness were also key barriers to implementation in practice.8
The health benefits of regular exercise and physical activity are compelling. Many people are able to benefit from exercise, regardless of age, sex or physical ability. Every person’s circumstances are unique, and these should be taken into account. Tailored exercise programs designed by an exercise profes-
sional that include both aerobic and resistance training activities have shown to provide benefits.1,5,9
AtGenesisCare in Southport, the team has partnered with Atkins Health, a provider of exercise and rehabilitation services. One of the allied health care services that patients are offered access to is an Exercise Physiologist (with onsite gym at the Southport centre), who is able to design bespoke exercise programs, tailored to support an individual patient's needs during their treatment journey. An achievable exercise plan is designed together with the patient, taking into consideration their baseline cardiovascular fitness and strength, their goals and their limitations. The Exercise Physiologist also follows up on the patient, increasing accountability and lifestyle change.
Learn more about GenesisCare: genesiscare.com
References
1. Ligibel JA, et al. J Clin Oncol 2022;40:2491-2507.Hayes SC, et al. J Sci Med Sport 2019;22:1175–1199.
2. Clinical Oncology Society of Australia. Position statement on exercise in cancer care. Version 3, December 2020.
3. Campbell KL, et al. Med Sci Sports Exerc 2019;51(11):2375-2390.
4. Juvet LK, et al. Breast 2017;33:166-177.
5. Betof AS, et al. J Natl Cancer Inst 2015;107(5).
6. Pedersen L, et al. Cell Metab 2016;23(3):554–562.
7. Kennedy MA, et al. J Cancer Surviv 2022;16:865-881.
8. Buffart LM, et al. Cancer Treat Rev 2017;52:91–104.
medicallink.com.au • 15
Metabolic Syndrome in Samoan Islands
The following article is the work of a student of the Oceania University of Medicine, our partner organisation for our previous medical conference held in Samoa last year, 28-30 September, 2023.
Shaoyu Xu, MPhil & Dr Romal C. Stewart, PhD shaoyu.xu@oum.edu.ws |
16 • Issue 149
Abstract
The Samoan Islands have experienced a dramatic increase in the prevalence of metabolic syndrome, with recent data suggesting that it has reached epidemic proportions. This review examines the epidemiology of metabolic syndrome in Samoa, exploring the underlying causes from genetics to rapid modernisation and subsequent lifestyle changes. A stark contrast in health outcomes is evident between Samoa and American Samoa, with the latter exhibiting significantly higher rates of the syndrome. Lifestyle modifications, shifting dietary patterns influenced by globalisation, and deeply ingrained cultural values have been identified as key contributors. Public health professionals advocate for community-driven interventions and early screenings to address this alarming trend.
Introduction
The prevalence of metabolic syndrome has increased in recent decades, and studies have shown that it has reached epidemic levels in the Samoan Islands. (Wang et al., 2017; DiBello et al., 2009) When four Asia-Pacific countries, namely Samoa, Australia, Japan, and Korea, were assessed using various diagnostic criteria for metabolic syndrome, Samoans consistently ranked the highest, with a prevalence of 17%-60% (Lee et al., 2008). Due to the high prevalence of metabolic syndrome in Samoa, this article aims to review the epidemiology and raise awareness of the causes of metabolic syndrome across the Samoan Islands.
The Samoan Islands
The Samoan Islands are divided into two jurisdictions:
• Samoa comprises four inhabited
islands and several small islands and outcrops. It is located in the northeast of Fiji and is the first Pacific Island nation to gain independence. It currently has a population of 200,010 (Samoa, n.d.).
• American Samoa comprises five islands and two atolls. It is located between New Zealand and Hawaii and is a territory of the United States with a population of 55,000 (American Samoa, n.d.).
What is metablic syndrome?
Metabolic syndrome is a cluster of metabolic disorders, including high serum triglycerides, low high-density lipoprotein (HDL) cholesterol, elevated blood pressure, raised fasting serum sugar, and abdominal obesity. It is associated with a high risk of developing atherosclerotic cardiovascular disease, type 2 diabetes, and cerebrovascular accident (Wang et al., 2017). To meet the diagnosis of metabolic syndrome, a patient must have any three of the following disturbances:
• Abdominal obesity, with a waist circumference of over 102 cm in men and 88 cm in women
• Hypertriglyceridemia, with serum triglycerides 1.7 mmol/L or greater
• Reduced serum HDL, of under 1.0 mmol/L in men and under 1.3 mmol/L in women
• Raised fasting glucose, of 100 mg/ dL or greater
• Elevated blood pressure, with systolic blood pressure of 130 mmHg or higher and/or diastolic blood pressure of 85 mmHg or higher (Wang et al., 2017)
It is important to note that measuring waist circumference for abdominal obesity, rather than body mass index (BMI), plays an important role in the clinical diagnosis of metabolic syndrome.
This is because abdominal fat is a marker of "dysfunctional adipose tissue" and is highly linked to insulin resistance (Després & Lemieux, 2006).
Metabolic syndrome among Samoan islanders
Although geographically close, there are health disparities between Samoans due to the different levels of modernisation present across the islands. American Samoans have a higher prevalence of metabolic syndrome and obesity than Samoans. Approximately 71% of women and 61% of men are obese in American Samoa, whereas close to 30% of men and over 50% of women are obese in Samoa. Correspondingly, 49.4% of American Samoans meet the diagnostic criteria for metabolic syndrome, compared with 30.6% of Samoans. Samoan women have a higher prevalence of metabolic syndrome than Samoan men (Dibello et al., 2009).
Interestingly, a similar pattern is observed in adolescents. With age-relevant cutoff criteria for cardiometabolic disorder, a cluster of three or more risk factors was present in 17.9% of male and 21% of female adolescents from American Samoa, whereas very few adolescents in Samoa exhibit three or more risk factors (1.1% in males and 2.8% in females) (Hawley et al., 2012). The difference in the prevalence of cardiometabolic risk factors among adolescents is due to the varied pace and timing of economic and social transition between the two polities and the different levels of parental socioeconomic status, education, and occupation (Hawley et al., 2012). Interestingly, this study reported that BMI correlates positively with the number of cardiometabolic risk factors and that only obese adolescents exhibit a cluster of three or more risk factors (Hawley et al., 2012).
medicallink.com.au • 17
Risk factors for metabolic syndrome in Samoans
Studies have shown that the following are risk factors for metabolic syndrome in Samoans:
• Older age
• Female sex
• Higher socioeconomic status index
• Higher BMI
• Larger waist circumference
• Lower physical activity
In addition, certain genetic traits make Samoans more susceptible to metabolic syndrome when they eat a modern diet. For example, Barlin et al. (2013) reported that one common variant of the insulin-induced gene 2 was associated with higher triglyceride levels and poorer metabolic control in people who followed a modern dietary pattern.
Lifestyle & dietary patterns in the islands of Samoa
The modernisation of Samoa has led to an increase in risk factors for metabolic syndrome, such as unhealthy diet, reduced physical activity, alcohol consumption, and smoking. In both Samoa and American Samoa, the traditional subsistence culture of farming and fishing is gradually being replaced by a sedentary way of life (Hawley et al., 2012). Samoans overall do more farm work than American Samoans (Baylin et al., 2013). However, physical activity has decreased overall due to improved transportation infrastructure and technological advancements in the mass production and distribution of food and tobacco products (Hawley et al., 2012).
The rapid modernisation and urbanisation of Samoa has also led to a dietary transition over the past four de-
cades (Wang et al., 2017; DiBello et al., 2009). Increased global trade has exposed Samoans to imported foods (Hawley et al., 2012). There has been a significant decline in the intake of traditional foods, such as green leafy vegetables, fruit, soup, and fish. With the popularity of imported and processed foods, the Samoan population has undergone a gradual nutrition transition to a mix of neotraditional and modern dietary patterns (Wang et al., 2017). Neotraditional patterns are characterised by the consumption of mostly local foods, such as coconut products, tropical fruits, taro, and a small amount of processed foods. Modern patterns are characterised by a high intake of processed foods, eggs, milk, and cheese, and a low intake of local foods. It is noteworthy that most Samoans have largely abandoned their neotraditional diet and acquired a modern dietary pattern. Adherence to the modern dietary pattern has been consistently associated with a poorer metabolic profile, including higher fasting serum glucose and triglyceride levels, worse insulin resistance, higher BMI, increased waist circumference, and lower HDL levels (Baylin et al., 2013).
Influence of Samoan culture and “fa’asamoa” (the Samoan way)
Samoan culture and "fa'asamoa" are linked to the development of obesity and metabolic syndrome. Feasts are a very important part of Samoan life and foster social well-being. The phrase "food is life, food is our culture" reflects the importance of food in Samoan culture. The high consumption of high-calorie foods at feasts, church events, and other social gatherings has a detrimental impact on individual health, as the foods that are typically served are high in carbohydrates, fat, and salt. "Fa'asamoa" also influences food preferences, taste, and how resources are used. Abundance is a key
cultural pattern of eating. Additionally, the high rate of obesity has been linked to some cultural factors, such as fat-positive attitudes (e.g., "if you are fat, you are wealthy") and the view that stillness is an embodied mode of wellness that indicates status and therefore influences physical activity (Hardin, 2014).
Changing these cultural behaviours may challenge socially grounded well-being. The saying "it is culture, it is the whole way of life" reflects the importance of culture in Samoan society. Samoans place obligations to family, church, or community over individual health (Hardin, 2014).
Public Health Implications and potential interventions
The increasing prevalence of meabolic syndrome has significant implications for affected individuals, families, and the community healthcare system (Hawley et al., 2012). Public health officials are increasingly concerned about this problem and have developed strategies to address the food environment and structural inequalities (Hardin, 2014). Health practitioners are encouraged to act as health mediators, but they often feel uneasy about doing so, as creating change is perceived as imposing cultural change. They have proposed a society-wide change in food, body, and wealth meanings and have suggested that community leaders, including church pastors, engage publicly with their own health. Leadership-driven cultural change involving health prioritisation and the choice of healthier food options can change the orientations of the community. In terms of adolescents, Hawley et al. (2012) proposed a screening test to identify individuals at risk and to initiate medical interventions using existing standard of care.
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RISK FACTORS
Old age
Female sex
POTENTIAL INTERVENTIONS
Raise awareness of metabolic syndrome
Health practitioners act as health mediators
Higher socioeconomic status Society-wide change in food, body, and wealth
Higher BMI Community leaders engage publicly
Larger waist circumference Health prioritisation
Lower physical activity
Genetic predisposition
Figure 2. Risk factors and potential interventions of metabolic syndrome in Samoa islands
Conclusion
The escalating prevalence of metabolic syndrome in the Samoan Islands highlights the urgent need for intervention. The interplay of modernisation, cultural practices, and genetic predispositions presents unique challenges in addressing this health concern. The disparity between the two main Samoan regions further underscores the complexity of the issue. Targeted public health strategies, community engagement, and a deep understanding of Samoan culture and lifestyle are essential in crafting solutions. Emphasising early detection and prevention, coupled with community-driven health initiatives, can offer a promising pathway towards curbing this health crisis in the Samoan Islands. The increasing prevalence of metabolic syndrome has significant implications for affected individuals, families, and the community healthcare system (Hawley et al., 2012). Public health officials are increasingly concerned about this problem and have developed strategies to address the food environment and structural inequalities (Hardin, 2014). Health practitioners are encouraged to act as health mediators, but they often feel uneasy about doing so, as creating change is perceived as imposing cultural change. They have proposed a society-wide change in food, body, and wealth meanings and have suggested that community leaders, including church
Choice of healthier food options
Screening tests to identify risks in adolescents
pastors, engage publicly with their own health. Leadership-driven cultural change involving health prioritisation and the choice of healthier food options can change the orientations of the community. In terms of adolescents, Hawley et al. (2012) proposed a screening test to identify individuals at risk and to initiate medical interventions using existing standard of care.
References
DiBello, J. R., McGarvey, S. T., Kraft, P., Goldberg, R., Campos, H., Quested, C., Laumoli, T. S., & Baylin, A. (2009). Dietary patterns are associated with metabolic syndrome in adult Samoans. The Journal of nutrition, 139(10), 1933–1943. https://doi.org/10.3945/jn.109.107888
Wang, D., Hawley, N. L., Thompson, A. A., Lameko, V., Reupena, M. S., McGarvey, S. T., & Baylin, A. (2017). Dietary Patterns Are Associated with Metabolic Outcomes among Adult Samoans in a Cross-Sectional Study. The Journal of nutrition, 147(4), 628–635. https://doi. org/10.3945/jn.116.243733
Baylin, A., Deka, R., Tuitele, J., Viali, S., Weeks, D. E., & McGarvey, S. T. (2013). INSIG2 variants, dietary patterns and metabolic risk in Samoa. European journal of clinical nutrition, 67(1), 101–107. https://doi.org/10.1038/ejcn.2012.124
Hawley, N. L., Wier, L. M., Cash, H. L., Viali, S., Tuitele, J., & McGarvey, S. T. (2012). Modernization and cardiometabolic risk in Samoan adolescents. Amer-
ican journal of human biology : the official journal of the Human Biology Council, 24(4), 551–557. https://doi. org/10.1002/ajhb.22269
Saklayen, M. G. (2018). The Global Epidemic of the Metabolic Syndrome. Current Hypertension Reports, 20(2):12. http://doi.org/10.1007/s11906-0180812-z
Hardin, H. (2015) Everyday Translation: Health Practitioners’ Perspectives on Obesity and Metabolic Disorders in Samoa. Critical Public Health, 25:2, 125-138. 10.1080/09581596.2014.909581
Lee, C. M., Huxley, R. R., Woodward, M., Zimmet, P., Shaw, J., Cho, N. H., Kim, H. R., Viali, S., Tominaga, M., Vistisen, D., Borch-Johnsen, K., Colagiuri, S., & Detect-2 Collaboration (2008). Comparisons of metabolic syndrome definitions in four populations of the Asia-Pacific region. Metabolic syndrome and related disorders, 6(1), 37–46. https://doi. org/10.1089/met.2007.0024
American Samoa. (n.d.). Australian Government Department of Foreign Affairs and trade. Retrieved from https://www. dfat.gov.au/geo/american-samoa
Samoa. (n.d.). Australian Government Department of Foreign Affairs and trade. Retrieved from https://www.dfat.gov.au/ geo/samoa
Després, J. P., & Lemieux, I. (2006). Abdominal obesity and metabolic syndrome. Nature, 444(7121), 881–887. https://doi. org/10.1038/nature05488
medicallink.com.au • 19
RUDAS Score & Falls Frequency in the Elderly in WA in an Aged Care Facility
The following article is the work of a student of the Oceania University of Medicine, our partner organisation for our previous medical conference held in Samoa last year, 28-30 September, 2023.
Jonathan Schirripa jonathan.schirripa@oum.edu.ws
20 • Issue 149
Abstract
Background: The purpose of the proposed study is to determine whether a relationship exists between the Rowland Universal Dementia Assessment Scale (RUDAS) score of an elderly person (65 years and above) in a residential aged care facility and their number of falls over of a 1-year period
Methods: A retrospective review of resident medical documentation from an aged care facility within Western Australia was performed to collect data for this study. Participants were grouped based on their RUDAS assessment as either nil impairment, normal, mild, moderate, or severe. Data on falls frequency was collected for each participant and this was analysed for correlation and statistical significance.
Results: ANOVA analysis found that falls frequency was significantly increased with a decreased RUDAS assessment score (correlation coefficient (r) -0.917 and p= 0.0281). This was best evidenced in those with moderate cognitive impairment.
Conclusion: From these findings we were able to establish that a lower score in the RUDAS assessment is negatively correlated with increasing falls frequency in the elderly.
Background
Afall is defined as an event where a person comes to rest inadvertently on the ground or floor or other lower level.1 It is estimated that 1/3 of all people aged greater than 65 years will experience falls and of those individuals 50% will fall more than once.2 Furthermore, of those who fall 1 in 40 will expect to be hospitalised and roughly 50% of those hospitalised will live for 1 year post admission.3
In 2011-2012 in Australia, 96,385 people aged 65 and over were hospitalised for a fall related injury.5 In the same population of people falls are attributable for the leading cause of death secondary to traumatic injury.3 Additionally falls account for 2/3 of all unintentional injuries
resulting in deaths.3 Falls will frequently result in complications such as fracture of femur (2%), fractures of the humerus, pelvis or wrist (5%), head trauma, intracranial hematomas and injury of internal organs (10%).4 These resulting injuries will often have profound impacts on quality of life with many long-term adverse outcomes which will likely require readmission to hospital. This begins a cycle of decline that ultimately results in death.6 There is also a burden on the Australian healthcare system, with up to 1.5% of the health care budget utilised for costs associated with falls.18
Cognitive impairment is defined as confusion or memory loss that is occurring more frequently or is progressively worsening over the past 12 months.7 It is well supported that cognitive impairment is a risk factor for falls in the older people population as evidenced by Inacio et al (2021) which indicated that cognitive impairment was the strongest predictor of falls requiring hospitalisation among 27 different variables.19 Approximately 60-80% of older people with cognitive impairment experience 1 or more unintentional falls which accounts for twice as many as those with intact cognition.8 Chen et al (2011) found that recurrent and single-time fallers had significantly lower Mini-Mental State Examination (MMSE) scores than non-fallers and that a large percentage of recurrent fallers had a MMSE of lower than 18.10 Allali et al (2017) found that 50-64% of older adults with impaired cognitive impairment were experiencing falls compared to 25% for those who are cognitively healthy.11 Furthermore Allan et al (2009) found that those 65 and older with dementia experienced nearly 8 times the incidence of falls than healthy controls.12 The RUDAS is a simple cognitive screening assessment that determines baseline cognitive function. It is advantageous over other cognitive assessments such as the MMSE as it is designed to be less sensitive to cultural and language diversity. This is evidenced by a 2015 meta-analysis by Naqvi et al which concluded that the RUDAS is par-
ticularly useful in patients with diverse backgrounds.22 Furthermore, Rowland et al found the RUDAS to be a reliable and valid assessment that is at least as accurate as the MMSE in diagnosing dementia and less impacted by language, education or gender.9 Storey et al (2004) found that the RUDAS is easily interpreted into other languages and is considered to be culturally fair.21
Even though there is strong evidence to support the association between cognitive impairment and risk of falls in the elderly, far less is known about the specific association between the RUDAS assessment and risk of falls in the elderly in an aged care setting in Western Australia. The purpose of the study is to determine whether a relationship exists between the RUDAS score of an elderly person in a residential aged care facility and their number of falls over of a 1 year period. It is hypothesised that there is a negative correlation between RUDAS score and falls frequency in the elderly population in an aged care facility (As RUDAS score decreases falls frequency increases).
Methodology
The study was approved by the Institutional Review Board of Oceania University of Medicine which included ethics approval. HREC Reference OUMHREC24_013
This pilot study consisted of collecting data from an internal database within a residential aged care facility in Perth, Western Australia. All residents in the age care facility consented for data collection. Data was collected within a 1-year period from April 2021 to March 2022. The participants that were included must have had a RUDAS completed by an appropriate allied health professional as well as a documented history of all falls in the 1 year period following the RUDAS assessment. Any resident that did not fulfil the inclusion criteria was excluded from this study. A total of 15 participants did not meet the eligibility criteria as they did
medicallink.com.au • 21 FEATURE STORY •
not have a RUDAS assessment completed and therefore were not included in the data for this study. The study exceeded the target sample size with a total of 98 participants with at least 10 participants in each group. Participants were split into groups based on their score from the RUDAS assessment (nil impairment, normal, mild, moderate and severe). Nil impairment indicates a perfect score or no cognitive impairment, normal indicates an expected age-related decline in cognition, mild indicates a noticeable decline in cognition, moderate indicates a significant impairment of cognition and severe indicates a profound impairment of cognitive function. With regards to scoring nil impairment achieved a score of 30, normal achieved a score of 26-19/30, mild 20-25/30, moderate 1019/30 and severe 9 or less out of 30. The RUDAS score and number of falls for each of the 98 participants was tallied and documented. Demographic data was also collected.
Nomaterials were required to facilitate the study, simple convenience sampling was utilised for all participants medical documentation within the internal database of the facility unless they did not meet inclusion criteria.
Statistics and frequency data is provided and the ANOVA test has been calculated in order to determine correlations and p values. The number of participants, mean age, gender split, mean RUDAS and mean number of falls was documented for each for the 5 groups. Correlation data and p values were generated for each individual group. All analysis was achieved via use of the ANOVA test.
Results
This study had a total of 98 participants, with 42 males (43%) and 56 females (57%) who’s age ranged from 73 to 99 with an overall mean age of 87.7 years. There were 12 participants in the nil impairment group, 15 in the normal
group, 18 in the mild impairment group, 32 in the moderate impairment group and 21 in the severe impairment group. Data surrounding demographics is provided in Table 1. RUDAS score and corresponding falls frequency data is provided in Table 2.
The hypothesis of this study was to determine whether a relationship exists between the RUDAS score of an elderly person (65 years and above) in a residential aged care facility and their number of falls over of a 1-year period. Statistical analysis of the data revealed that a negative correlation exists between RUDAS score and risk of falls.
In the group with nil impairment, there was an average falls frequency of 0.75 over a 1 year period. The normal group achieved a mean RUDAS score of 27.06 and experienced on average 1.13 falls. The pattern continued with the mildly impaired group achieving an average RUDAS of 21.63 and a falls frequency of 1.39. Moderately impaired group had an average RUDAS score of 15.88 and a falls frequency of 2.5. Lastly, the severely impaired group had an average RUDAS score of 6.48 and an associated falls frequency of 8.14. When analysing the mean RUDAS score and mean falls frequency from each group, a strong negative correlation of -0.917 was established with an associated statistically significant p value of 0.028 (figure 1). When analysing the data in each group individually the only group with a statistically significant p value of 0.014 was the moderate impairment group. This was likely the case as this was the largest group by number of participants and therefore best accounted for outliers in the data.
The age and gender of the participants was analysed against the RUDAS score and falls frequency to expose any additional relationships and therefore bias to the hypothesis however it was found that there was no correlation between age and number of falls and between age and RUDAS as per Table 4. Although
the study had more females(n=56) than males(n=42) there was no correlation between gender and RUDAS score or gender and falls frequency as seen in Table 3. This is evident as the average number of falls over a 1 year period for males and females were 3.19 and 3 respectively.
Discussion
The results of this study reveal that reveal that a relationship does exist between declining cognition via the RUDAS score and an increased falls frequency, most evidently in those with a moderate cognitive impairment in the RUDAS which best reflects the greatest number of participants in this study and likely the target population (elderly in aged care facilities).
Prior research into the topic of cognition and falls frequency is well established in the literature however most of the body of research utilises the MMSE which is the Mini-Mental State Examination. Allali et al (2017) used the MMSE and in their study participants with non-Alzheimer’s dementia and Alzheimer’s dementia were more likely to fall compared to cognitive healthy individuals which supports the findings in this paper.11 Interestingly, those with non-Alzheimer’s dementia were more likely to fall with a prevalence of 64% compared to Alzheimer’s dementia with 50% and cognitively healthy with 25%.11 Seijo-Martinez (2016) used the MMSE to categorise participants into absent, mild, moderate and severe cognitive impairment. The study found that those with no cognitive impairment had a falls frequency of 34% and this increased in each subsequent group with severe cognitive impairment having a falls frequency of 50%.20 In summary the available data shows that with declining MMSE score there is an increased risk of falls.8,10,11,12,20 Despite the frequent use of the RUDAS in the elderly population, the data surrounding its relationship with falls is extremely limited. Nevertheless, our findings are congruent with the available data and consistent
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with the findings that the MMSE shows.
Whenanalysing our data, we concluded various limitations. Being a preliminary study with a simple data analysis, the findings and therefore the applicability to the elderly population must be further explored and scrutinised. More specifically, despite achieving the desired sample size, we were unable to ensure similar number of participants in each group which introduced a possibility of data bias. In contrary, it could also be concluded that the size of each group best reflects the cognition levels of the elderly population in aged care facilities and therefore the data is more applicable. However, as the data is collected from only 1 residential aged care facility, the applicability of the findings is reduced as compared to a methodology whereby participants were selected from across different facilities in Western Australia. Furthermore, in ideal future studies, accounting for other confounding variables such as medications, chronic disease and previous mobility levels should be analysed. An example of the impact of medication on falls is seen in Sharif et al (2018) paper where they looked into the various risk factors of falls and stated the many medications that are associated with increase of falls and they include antipsychotics, antidepressants, hypnotics, sedatives and antihistamines.13 All of which are common in the geriatric population.13 Further studies that account for such variables will expand on and build upon the findings in this study and therefore generate improved data that can be considered more actionable.
Aphysiologicaldecline in cognitive function is expected with age however when cognition deteriorates past the expected age-related decline further challenges arise for the elderly. These challenges are not limited to physical function and extend to virtually all aspects of life. With the high prevalence and morbidity of falls in elderly it is important to establish any relationship between common assessments of cognition
such as the RUDAS and the subsequent likelihood of falls. Generating data as well as highlighting findings will contribute to deepening our understanding of the relationship between cognitive impairment and falls. Subsequently, this may guide and focus therapeutic interventions such as physiotherapy, occupational therapy, pharmacological therapy and provision of equipment. As evidenced by Montero-Odasso (2018) who found mounting evidence supporting the use of cognitive therapies such as cognitive training, virtual reality and dual-task training in improving mobility and therefore reducing falls in older adults with cognitive impairment.16 Frequency and/or intensity of the therapeutic intervention may be altered and adapted for the specific person of interest based on their assessment findings. More broadly, this may guide aged care facilities to more appropriately allocate resources as well as indicate the need for additional funding in order to achieve the best outcomes for their residents and staff.
Additionally, this study highlights the need for accurate cognitive assessment as the result of the cognitive assessment will dictate the level of falls prevention required. However, this conclusion will require more extensive research as echoed by Cuevan-Trisan (2017) who strongly advocates for cognitive assessment for falls prevention but believes the recommendations and evidence for falls prevention in those with cognitive impairment is not well documented.14 This is also supported by the 2019 Cochrane review by Sherington et al which concludes various falls prevention recommendations however the research cited in the review excludes participants with cognitive impairment.15 Furthermore, Montero-Odasso (2022) concluded only two recommendations for falls prevention in cognitively impaired individuals. They recommended routine assessment of cognitive and involvement of the individual and their caregiver in the decision of falls prevention as it showed better adherence.17 This highlights the need for
further research into the assessment of individuals with cognitive impairment in order to guide future falls prevention recommendations and strengthen the body of evidence available.
References
1. WHO Global Report On Falls Prevention In Older Age. Appia: WHO Press; 2007.
2. Tinetti M.
2. Preventing Falls in Elderly Persons. New England Journal of Medicine. 2003;348(1):42-49. doi:10.1056/nejmcp02071
3. Pasquetti P. Pathogenesis and treatment of falls in elderly. Clinical Cases in Mineral and Bone Metabolism. 2014. doi:10.11138/ccmbm/2014.11.3.222
4. Rubenstein L. Falls in older people: epidemiology, risk factors and strategies for prevention. Age Ageing. 2006;35(suppl_2):ii37-ii41. doi:10.1093/ageing/afl084
5. AIHW: Bradley C 2012. Hospitalisations due to falls by older people, Australia 2007–08. Injury research and statistics series no. 61. Cat. no. INJCAT 137. Canberra: AIHW.
6. Boyd C, Landefeld C, Counsell S et al. Recovery of Activities of Daily Living in Older Adults After Hospitalization for Acute Medical Illness. J Am Geriatr Soc. 2008;56(12):2171-2179. doi:10.1111/ j.1532-5415.2008.02023.x
7. Cognitive Impairment. A Call For Action Now. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2011.
8. Lord SR, Sherrington C, Menz HB & Close JCT (2007) Falls in Older People. Risk Factors and Strategies for Prevention. Cambridge University Press, Cambridge.
9. Rowland J, Conforti D, Basic D, Vrantsidis F. A Study To Validate The Rowland Universal Dementia Assessment Scale (RUDAS) In Two Populations Outside The Sydney South West Area Health Service. The Australian Government Department of Health and Ageing through Alzheimer’s Australia; 2007.
10. Chen X, Van Nguyen H, Shen Q, Chan D. Characteristics associated with recurrent falls among the elderly within aged-care wards in a tertiary hospital: The effect of cognitive impairment. Arch Gerontol Geriatr. 2011;53(2):e183-e186. doi:10.1016/j.archger.2010.08.012
11. Allali G, Launay C, Blumen H et al. Falls, Cognitive Impairment, and Gait Performance: Results From the GOOD Initiative. J Am Med Dir Assoc. 2017;18(4):335-340. doi:10.1016/j.jamda.2016.10.008
12. Allan L, Ballard C, Rowan E, Kenny
medicallink.com.au • 23 FEATURE STORY •
R. Incidence and Prediction of Falls in Dementia: A Prospective Study in Older People. PLoS One. 2009;4(5):e5521. doi:10.1371/journal.pone.0005521
13. Sharif, S.I. et al. (2018) ‘Falls in the elderly: Assessment of prevalence and risk factors’, Pharmacy Practice, 16(3), p. 1206. doi:10.18549/pharmpract.2018.03.1206.
14. Cuevas-Trisan, R. (2017) ‘Balance problems and fall risks in the elderly’, Physical Medicine and Rehabilitation Clinics of North America, 28(4), pp. 727–737. doi:10.1016/j.pmr.2017.06.006.
15. Sherrington C, Fairhall NJ, Wallbank GK, Tiedemann A, Michale& ZA, Howard K, Clemson L, Hopewell S, Lamb SE. Exercise for preventing falls in older people living in the community. Cochrane Database of Systematic Reviews 2019, Issue 1. Art. No.: CD012424. doi:10.1002/14651858. CD012424.pub2
16. Montero‐Odasso, M. and Speechley, M.
Tables & Figures
Demographic
(2018) ‘Falls in cognitively impaired older adults: Implications for risk assessment and prevention’, Journal of the American Geriatrics Society, 66(2), pp. 367–375. doi:10.1111/jgs.15219.
17. Montero-Odasso, M. et al. (2022) ‘World guidelines for falls prevention and management for older adults: A global initiative’, Age and Ageing, 51(9). doi:10.1093/ ageing/afac205.
18. Nunan, S. (2023) ‘Evaluating the validity, reliability, and feasibility of a falls risk assessment tool recommended for use in Australian residential aged care facilities. A mixed methods study’, The University of Queensland, School of Nursing, Midwifery and Social Work. doi:10.14264/0ea539d.
19. Inacio, M.C. et al. (2021) ‘The risk of fall-related hospitalisations at entry into permanent residential aged care’, BMC Geriatrics, 21(1). doi:10.1186/s12877-
Demographic Information Participants ( n =98)
Sex
Nil Impairment score (Mean age)
Normal Score (Mean age)
Mild Impairment score (Mean age)
Moderate Impairment score (Mean age)
Severe Impairment score (Mean age)
021-02640-w.
20. Seijo-Martinez, M. et al. (2016) ‘Influence of cognitive impairment on fall risk among elderly nursing home residents’, International Psychogeriatrics, 28(12), pp. 1975–1987. doi:10.1017/s1041610216001113.
21. Storey, J.E. et al. (2004) ‘The rowland universal dementia assessment scale (Rudas): A Multicultural Cognitive Assessment Scale’, International Psychogeriatrics, 16(1), pp. 13–31. doi:10.1017/ s1041610204000043.
22. Naqvi, R.M. et al. (2015) ‘Cognitive assessments in multicultural populations using the Rowland Universal Dementia Assessment Scale: A systematic review and meta-analysis’, Canadian Medical Association Journal, 187(5). doi:10.1503/ cmaj.140802.
are reported
Female = 54, Male = 46
Participants (n = 12)
83.33 ± 6.85
Participants (n= 15)
85.60 ± 7.44
Participants (n=18)
89.11 ± 5.26
Participants (n=32)
88.94 ± 7.78
Participants (n=21)
89.00 ± 3.96
24 • Issue 149 • THE MEDICAL LINK
Table 1
data of study participants. Means ± standard deviations
Table 2
Group Mean RUDAS Mean Falls/1yr (SD) Nil Impairment 30 0.75 ± 0.72 Normal 27.06 1.13 ± 0.88 Mild Impairment 21.63 1.39 ± 0.89 Moderate Impairment 15.88 2.5 ± 3.13* Severe Impairment 6.48 8.14 ± 4.91
RUDAS score and corresponding mean number of falls in each group.
*p <0.05
Table 3
Sex Mean RUDAS Mean number of falls Correlation Females 18.07 3 -0.625 Males 19.26 3.19 -0.703
Correlation between RUDAS and mean number of falls in Males and Females
Table 4
Correlation:
Correlation:
medicallink.com.au • 25
Correlation: P -value Age and RUDAS -0.222 0.088 Age and Falls 0.061 0.551
Correlation between Age and Falls frequency and Age and RUDAS score
r= -0.917 P-value 0.028
Figure 1
r= -0.657
0.021
P-value
Figure 2
"With the property market growing 8% nationally over the past 12 months and over 13-15% in Brisbane and the West, pandemic passes and interest rates steady, now may be a good time to invest in residential property."
26 • Issue 149
New Year, New Practice?
Ben Ryan Senior Associate | Avant Law 1800 867 113 | www.avant.org.au
It’sthe new year, you’ve had some time off to refresh and recharge for the year ahead and you might be thinking about actioning some new goals for the year. If one of those goals is establishing or starting a medical practice, then this is the guide for you!
Ownership & corporate structure
One of the first decisions to be made when establishing a practice is how the business will be owned and structured. This decision will depend on several factors including the number of owners involved and the scale of the business that will be operated. The most typical methods of ownership include:
1. Sole trader
2. Partnership
3. Company
4. Trust (whether Unit, Discretionary or Hybrid) or
5. A company acting as trustee for the trust
Where there is more than one owner in the business, the relationship between the owners should also be governed by an ownership document. The table below shows the typical document and its corresponding business structure.
These documents can record important factors, including:
1. The way the owners make decisions
2. The process that needs to be followed if the owners have a dispute
3. How the owners will be paid or how the profits of the business
BUSINESS STRUCTURE OWNERSHIP DOCUMENT
Partnership Partnership Agreement
Company
Trust (Unit, Discretionary or Hybrid)
Company Constitution Shareholders' Agreement
Unitholders' Agreement Trust Deed
Trust with a Corporate Trustee Share and Unitholders' Agreement Trust Deed Company Constitution will be used and shared
4. How owners can enter and exit the business in the future
Location, location, location
Even in the age of remotely run businesses, the reality is that practices predominately require a practice location. With various factors such as location, demographic and price – it’s easy to be overwhelmed by the options available when choosing your location. However, before you pick your fit-out company, you will need to decide whether you will own or lease your location.
No matter what you decide, securing premises and having a detailed lease outlining the security of your tenure and rent payable is a fundamental step. For leased premises, this often means Terms Sheets/Heads of Agreements and draft leases being negotiated with the landlord. Of course there are agents out there that can assist with finding and negotiating these terms for you. If you are looking to purchase a property, you will need to
ensure the usual due diligence steps are followed and the premises are zoned for your intended purpose. Unsurprisingly, a contract that protects you properly during the purchasing process and lease will be a key aspect of your property plans.
Key employees
Before you hire any employees, it’s important to understand the relevant minimum legal terms of employment that will apply to roles in your practice and to have appropriate employment documentation in place.
You will need solid template employment contracts that reflect the relevant minimum legal terms of employment in accordance with the National Employment Standards (NES) and any applicable award.
Awards are legally binding instruments made under the Fair Work Act 2009 (Cth), which supplement the NES to specify additional minimum legal terms of employment on an industry or occupational basis. The Health Profes-
28 • Issue 149 • THE MEDICAL LINK
ADVERTORIAL
sionals and Support Services Award 2020 and the Nurses Award 2020 are the two awards that commonly cover employees working in a private medical practice.
You will need different template employment contracts for permanent and casual employees.
Generally, less is more when it comes to written workplace policies and procedures. However, some policies are essential to ensure compliance with legislation, including policies dealing with workrelated discrimination, sexual harassment and bullying. All employees should be trained on these policies.
You will need to give all new employees a copy of the Fair Work Information Statement. Casual employees and employees whose contract will terminate at the end of an identifiable period will also need to be given additional information statements.
Plan for the unexpected
As the adage goes in business, ‘expect the unexpected’. While you work hard to ensure that the unexpected is managed properly, it’s important to ensure that this also extends to planning what will happen with the business if you, or other key owners and personnel are not available to undertake the roles you are usually able to perform.
This could involve several matters, including:
1. Ensuring your personal wills and powers of attorney are appropriately configured
2. Ownership documents are appropriately drafted to consider these circumstances
3. Investigating insurance structures which may assist the business to continue being properly managed if unfortunate circumstances unfolded (including the potential for a life insurance or TPD event to occur)
Key contracts
Of course, there are other considerations and agreements required when establishing or joining a practice that will help mitigate risks. These include:
1. Privacy policies and disclaimers – practices have particular obligations under the Privacy Act1998 (Cth) including to have a privacy policy (also sometimes known as privacy statements) which set out the way private and sensitive information will be handled and used by the practice. Subject to where your practice is located, you may also need to comply with additional obligations when dealing with patient records.
2. Facilities and Services Agreement – following recent case law and clarification provided by various state revenue offices across Australia regarding payroll tax, it’s important to ensure the practice is properly documenting the relationship with the doctors and understand what different relationship structures can exist between doctors and the practice.
For more considerations, we’ve created an extensive checklist to help you through-
out the process. Be sure to download your checklist via avantlaw.com.au.
We can help you
Avant Law is here to help with all the legals required when establishing or joining a medical practice. The Avant Law team includes lawyers who specialise in vast areas of law including Corporate & Commercial, Property, Estates & Succession and Employment law. Our team can guide you through the entire process. Please call 1800 867 113, or to organise a confidential discussion at a time that suits you, please click here.
About the Author
Ben Ryan is a Senior Associate in the commercial and corporate law practice at Avant Law, based in Brisbane. Ben has been working with medical practices since 2013. Ben works primarily on commercial structuring and intellectual property matters to help clients achieve strategic and commercially sensible results. He pursued a career in law to provide reliable and honest support to those in need of legal assistance and enjoys working with clients to develop solutions-oriented legal strategy and advice.
Disclaimer: The information in this article does not constitute legal advice or other professional advice and should not be relied upon as such. It is intended only to provide a summary and general overview on matters of interest and it is not intended to be comprehensive. You should seek legal or other professional advice before acting or relying on any of this content. The information in this article is current to 23 January 2024. Liability limited by a scheme approved under Professional Standards Legislation. Legal practitioners employed by Avant Law Pty Limited are members of the scheme. © Avant Mutual Group Limited 2024
medicallink.com.au • 29
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