AIM: To investigate the effects of COVID-19 pandemic on self-management, pain, and physical function in older adults awaiting TKA in Malaysia.
METHODS: This cross-sectional study has the data of participants, who matched the criteria and scheduled for TKA for the first time, extracted from the TKA registry in the Department of Orthopaedics and Traumatology, Hospital Canselor Tuanku Mukhriz. Data on pain status, and self-management, physical frailty, and instrumental activities daily living were also collected. Multiple linear regression analysis with a significant level of 0.05 was used to identify the association between waiting time and pain on physical frailty and functional performance.
RESULTS: Out of 180 had deferred TKA, 50% of them aged 50 years old and above, 80% were women with ethnic distribution Malay (66%), Chinese (22%), Indian (10%), and others (2%) respectively. Ninety-two percent of the participants took medication to manage their pain during the waiting time, while 10% used herbs and traditional supplements, and 68% did exercises as part of their osteoarthritis (OA) self-management. Thirty-six participants were found to have physical frailty (strength, assistance with walking, rising from a chair, climbing stairs, and falls questionnaire score > 4) which accounted for 72%. Increased pain was associated with physical frailty with odds ratio, odds ratio (95% confidence interval): 1.46 (1.04-2.05). This association remained significant even after the adjustment according to age and self-management.
CONCLUSION: While deferring TKA during a pandemic is unavoidable, patient monitoring for OA treatment during the waiting period is important in reducing physical frailty, ensuring the older patients' independence.
METHODS: The Promoting Independence in Seniors with Arthritis (PISA) study is a longitudinal observational study of individuals with and without knee pain and knee OA recruited from the orthopaedics clinic of the Universiti Malaya Medical Centre and the local hospital catchment. Patients were diagnosed with OA based on the American College of Rheumatology (ACR) criteria, the presence of knee pain, and a history of physician-diagnosed knee OA. Psychosocial parameters were measured using validated measures for social participation, independence, and ability to perform activities of daily living, and life satisfaction.
RESULTS: Of the 230 included participants, mean age was 66.9 years (standard deviation: 7.2) and 166 (72.2%) were women. Kappa agreement between ACR criteria and knee pain was 0.525 and for ACR and physician-diagnosed OA it was 0.325. Binomial logistic regression analysis showed that weight, anxiety, and handgrip strength (HGS) were predictive of ACR OA. Knee pain was only predicted by HGS but not weight and anxiety. Physician-diagnosed OA was predicted by weight and HGS but not anxiety. HGS was predictive of ACR OA, knee pain, and physician-diagnosed OA.
CONCLUSION: Our study showed that the characteristics of patients with OA are different, physically and psychosocially, depending on the criteria used. Poor agreement was observed between radiological diagnosis and the other diagnostic criteria. Our findings have important implications for the interpretation and comparison of published studies using different OA criteria.
METHODS: The Promoting Independence in our Seniors with Arthritis study recruited participants aged 65 years and over from orthopedic outpatients and community engagement events. Participants were invited to annual visits during which knee OA symptoms were assessed with the Knee Injury and Osteoarthritis Outcome Score (KOOS), social network using the 6-item Lubben Social Network Scale and anxiety and depression using the Hospital Anxiety and Depression scale. Knee OA worsening was defined by a 5% reduction in mean KOOS scores at the last visit compared to the first visit.
RESULTS: Data were available from 148 participants, mean age 66.2±6.5 years and 74.1% female, of whom 28 (18.9%) experienced OA worsening over a median follow-up period of 29 months. Univariate analyses revealed that age, sex, height, grip strength, and social network were associated with OA worsening. Social network remained statistically significantly associated with OA worsening after adjustment for age and sex difference (odds ratio=0.924; 95% confidence interval, 0.857-0.997). The relationship between social network and OA worsening were attenuated by both depression and handgrip strength at baseline.
CONCLUSION: Psychological status and muscle strength may be modifiable risk factors for social network which may in turn prevent knee OA worsening and should be targeted in future intervention studies.
METHODS: This prospective cohort study utilized stratified simple random sampling to recruit 1614 participants from the Malaysian Elders Longitudinal Research aged above 55 years within the Klang Valley region from 2013 to 2015. Individual items for the frailty tools, alongside baseline physical and cognitive measures were extracted from the initial survey. Mortality data up to 31 December 2020 were obtained through data linkage from the death registry data obtained from the Malaysian National Registration Department.
RESULTS: Data were available for over 1609 participants, age (68.92 ± 7.52) years and 57 % women, during recruitment. Mortality data revealed 13.4 % had died as of 31 December 2020. Five to 25 % of our study population fulfilled the criteria for frailty using all four frailty tools. This study found an increased risk of mortality with frailty following adjustments for potential factors of falls, total number of illnesses and cognitive impairment, alongside moderate to strong correlation and agreement between frailty tools.
CONCLUSION: Frailty was associated with increased mortality. All four frailty assessment tools can be used to assess frailty within the Malaysian older adult population. The four available tools, however, may not be interchangeable.
OBJECTIVES: The aim of this study was to determine the feasibility of virtual data collection for a longitudinal study of aging assessing cognitive frailty in a middle-income Southeast Asian country.
METHODS: The Transforming Cognitive Frailty into Later-Life Self-Sufficiency (AGELESS) longitudinal study of aging involved community-dwelling participants aged 60 years and above. A semi-structured focus group discussion was conducted via videoconferencing with selected representatives from existing participants. The survey instrument was compiled during a hybrid meeting and refined using a virtual Delphi process involving 51 AGELESS investigators. The final draft survey and recruitment strategy were then piloted among selected participants.
RESULTS: Twelve individuals participated in the virtual focus group interview. Smartphone, tablet computer, laptops, and desktop personal computers were used for information gathering, communication, banking, shopping, leisure, religion, and education, within this group. The survey instrument was redacted from 362 items in 18 sections to 141 items in 12 sections through 3 virtual Delphi rounds facilitated by email, social media messaging, and videoconferencing which attracted 213 comments. Of 45 participants selected for the pilot survey, 30 were successfully contacted after one attempt and 18 completed the survey. Cognitive frailty was present in 13%, cognitive impairment in 20%, frailty in 20%, and 47% were robust.
CONCLUSION: A virtual survey instrument was developed for the AGELESS longitudinal survey of aging which was vital for determining the effects of the COVID-19 pandemic on our older population as well as sustaining research into aging despite barriers posed by the pandemic.
METHODS: The Malaysian Elders Longitudinal Research study recruited Malaysians aged at least 55 years from 2013 to 2015. Follow-ups were conducted between September and December 2020. Quality of life was determined using the 12-item Control, Autonomy, Self-Realization, and Pleasure questionnaire. Psychological statuses were assessed using the 21-item Depression Anxiety and Stress Scale, 15-item Geriatric Depression Scale, and 4-item Perceived Stress Scale.
RESULTS: This study included data from 706 individuals (mean age, 73.3±6.8 years). We observed reduced quality of life and increased anxiety among 402 (43.1%) and 144 (20.9%) participants, respectively. Participants felt "out of control," "left out," "short of money," and "life was full of opportunities" less often and could "please themselves with what they did" more often. Multivariate analyses revealed increased depression, anxiety, and stress as independent risk factors for reduced quality of life.
CONCLUSION: Individuals with increased depression, anxiety, and stress levels during the pandemic experienced a worsening quality of life. Thus, the development of effective strategies to address the mental health of older adults is needed to mitigate the effects of the pandemic on their quality of life.
METHODS: This is a cross-sectional study where family caregivers and patients who were diagnosed of cancers within 12 months were recruited. QOL of caregivers were measured using The Caregiver Quality of Life Index-Cancer (CQOLC). Psychological distress was measured using Hospital anxiety and depressive scale. Logistic regression analysis was performed to determine the related factors of QOL of caregivers.
RESULTS: A total of 458 patients/caregiver pairs were included. Symptoms of anxiety and depression reported by caregivers were 24.9% and 24.2% respectively. Caregivers of patients with solid tumors have better CQOLC score compared to those who cared for patients with hematological cancers (91.25 vs 86.75). Caregivers of non-Malay ethnicity, those caring for patients with advanced stage cancer and with hematological cancers had significantly poorer QOL. QOL of caregivers are also significantly affected when patients demonstrated anxiety symptoms.
CONCLUSION: This study provides detailed evaluation of the QOL of caregivers of cancer patients in Malaysia. The significant psychological distress and low caregiver QOL indicate the urgent need for comprehensive supports for caregivers with cancer patients, especially those caring for patients with haematological cancers.
METHODS: Data from the Malaysian elders longitudinal research (MELoR) study were utilised. Baseline data were obtained from home-based computer-assisted interviews and hospital-based health-checks from 2013 to 2015. Protocol of MELoR study has been described in previous study (Lim in PLoS One 12(3):e0173466, 2017). Follow-up interviews were conducted in 2019 during which data on the adverse outcomes of falls, sarcopenia, hospitalization, and memory worsening were obtained. Sarcopenia at follow-up was determined using the strength, assistance with walking, rising from a chair, climbing stairs, and falls (SARC-F) questionnaire.
RESULTS: Follow-up data was available for 776 participants, mean (SD) age 68.1 (7.1) years and 57.1% women. At baseline, 37.1% were robust, 12.8% had isolated cognitive impairment, 24.1% were prefrail, 1.0% were frail, 20.2% were prefrail with cognitive impairment, and 4.8% had CF. Differences in age, ethnicity, quality of life, psychological status, function and comorbidities were observed across groups. The association between CF with hospitalisation and falls compared to robust individuals was attenuated by ethnic differences. Pre-frail individuals were at increased risk of memory worsening compared robust individuals [aOR(95%CI) = 1.69 (1.09-2.60)]. Frail [7.70 (1.55-38.20)], prefrail with cognitive impairment [3.35 (1.76-6.39)] and CF [6.15 (2.35-16.11)] were significantly more likely to be sarcopenic at 5-year follow-up compared to the robust group.
CONCLUSIONS: Cognitive frailty was an independently predictor of sarcopenia at 5-year follow-up. The relationship between CF with falls and hospitalization, however, appeared to be accounted for by ethnic disparities. Future studies should seek to unravel the potential genetic and lifestyle variations between ethnic groups to identify potential interventions to reduce the adverse outcomes associated with CF.
METHOD: Participants aged above 60 years from three ageing cohorts in Malaysia were interviewed virtually. The Fatigue, Resistance, Ambulation, Illness and Loss of Weight scale, blind Montreal Cognitive Assessment, 15-item Geriatric Depression Scale, anxiety subscale of Depression, Anxiety and Stress Scale and four-item Perceived Stress Scale measured frailty, mild cognitive impairment (MCI), depression, anxiety and stress, respectively.
RESULTS: Cognitive frailty data were available for 870 participants, age (mean ± SD) = 73.44 ± 6.32 years and 55.6% were women. Fifty-seven (6.6%) were robust, 24 (2.8%) had MCI, 451 (51.8%) were pre-frail, 164 (18.9%) were pre-frail+MCI, 119 (13.7%) were frail and 55 (6.3%) were frail+MCI. There were significant differences in depression and anxiety scores between the controlled MCO and recovery MCO. Using multinomial logistic regression, pre-frail (mean difference (95% confidence interval, CI) = 1.16 (0.932, 1.337), frail (1.49 (1.235, 1.803) and frail+MCI (1.49 (1.225, 1.822)) groups had significantly higher depression scores, frail (1.19 (1.030, 1.373)) and frail+MCI (1.24 (1.065, 1.439)) had significantly higher anxiety scores and pre-frail (1.50 (1.285, 1.761)), frail (1.74 (1.469, 2.062)) and frail+MCI (1.81 (1.508, 2.165)) had significantly higher stress scores upon adjustments for the potential confounders. The MCO was a potential confounder in the relationship between depression and prefrail+MCI (1.08 (0.898, 1.340)).
CONCLUSION: Frail individuals with or without MCI had significantly higher depression, anxiety and stress than those who were robust. Increased depression and stress were also observed in the pre-frail group. Interventions to address psychological issues in older adults during the COVID-19 pandemic could target prefrail and frail individuals and need further evaluation.
METHODS: Participants were drawn from the EPIC-Norfolk Prospective Population Cohort Study (median follow-up = 16.4 years). Cox models analysed the relationship between BF% and incident fractures (all and hip). Linear and restricted cubic spline (RCS) regressions modelled the relationship between BF% and BUA.
RESULTS: 14,129 participants (56.2 % women) were included. There were 1283 and 537 incident all and hip fractures respectively. The participants had a mean (standard deviation) age of 61.5 (9.0) years for women and 62.9 (9.0) years for men. Amongst men, BF% was not associated with incident all fractures. While BF% 23 % was associated with increased risk of hip fractures by up to 50 % (hazard ratio (95 % confidence interval) = 1.49 (1.06-2.12)). In women, BF% 35 % was not associated with this outcome. Higher BF% was associated with lower risk of incident hip fractures in women. Higher BF% was associated with higher BUA amongst women. Higher BF% up to ~23 % was associated with higher BUA amongst men.
CONCLUSIONS: Higher BF% is associated with lower risk of fractures in women. While there was no association between BF% and all fractures in men, increasing BF% >23 % was associated with higher risk of hip fractures in men. This appears to be independent of estimated bone mineral density. Fracture prevention efforts need to consider wider physical, clinical, and environmental factors.
METHODS: Data from the Malaysian Elders Longitudinal Research subset of the Transforming Cognitive Frailty into Later-Life Self-Sufficiency cohort study was utilized. From 2013-2015, participants aged ≥55 years were selected from the electoral rolls of three parliamentary constituencies in Klang Valley. Risk categorisation was performed using baseline data. Falls prediction values were determined using follow-up data from wave 2 (2015-2016), wave 3 (2019) and wave 4 (2020-2022).
RESULTS: Of 1,548 individuals recruited, 737 were interviewed at wave 2, 858 at wave 3, and 742 at wave 4. Falls were reported by 13.4 %, 29.8 % and 42.9 % of the low-, intermediate- and high-risk groups at wave 2, 19.4 %, 25.5 % and 32.8 % at wave 3, and 25.8 %, 27.7 % and 27.0 % at wave 4, respectively. At wave 2, the algorithm generated a sensitivity of 51.3 % (95 %CI, 43.1-59.2) and specificity of 80.1 % (95 %CI, 76.6-83.2). At wave 3, sensitivity was 29.4 % (95 %CI, 23.1-36.6) and specificity was 81.6 % (95 %CI, 78.5-84.5). At wave 4, sensitivity was 26.0 % (95 %CI, 20.2-32.8) and specificity was 78.4 % (95 %CI, 74.7-81.8).
CONCLUSION: The algorithm has high specificity and low sensitivity in predicting falls, with decreasing sensitivity over time. Therefore, regular reassessments should be made to identify individuals at risk of falling.