Associations between falls and psychosocial factors, self-rated health, disability and sleep among community dwelling older people in Malaysia

Original Article

*Shariff-Ghazali Sazlina, MBBS, MMed (Fam Med), PhD1,2, Yoke Mun Chan, BSc (Dietetics), PhD3, Tengku Aizan Hamid, PhD2,4, Shahar Suzana, PhD5,6, Devinder Kaur Ajit Singh, PhD7
1Department of Family Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia
2Malaysian Research Institute on Ageing, Universiti Putra Malaysia
3Department of Nutrition and Dietetics, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia
4Department of Human Development and Family Studies, Faculty of Human Ecology, Universiti Putra Malaysia
5School of Healthcare Sciences, Faculty of Health Sciences, Universiti Kebangsaan Malaysia
6Community Rehabilitation and Aging Research Centre, Faculty of Health Sciences, Universiti Kebangsaan Malaysia
7School of Rehabilitation Sciences, Faculty of Health Sciences, Universiti Kebangsaan Malaysia
DOI: http://dx.doi.org/10.24816/jcgg.2018.v9i3.03

  • Abstract
  • Full Text
  • References

Abstract

Background/Objective

Falls among older people leads to major consequences, which affects their quality of life. The causes are multifactorial, a combination of intrinsic and extrinsic factors, which include psychosocial and functional factors. This study aimed to determine the association between falls and the psychosocial factors, self-rated health, disability and sleep among community dwelling older people in Malaysia.

Methods

This study utilized the first wave data from the Towards Useful Ageing (TUA) cohort. A total of 1993 adults aged ≥60 years with no diagnosed psychiatric illness; without and with mild or moderate cognitive impairment were included in the analyses. Risk of falls, psychosocial factors (perceived stress, life satisfaction, loneliness, depression, social support, and sleep duration) and functional factors (disability and independence of activities of daily living) were assessed using a pre-tested questionnaire.

Results

The proportion of older people with a history of falls was 18.6%. The results of multiple logistic regression revealed aged between 75-84 years (OR=1.61; 95% CI=1.20, 2.15;  p=0.001), aged  ≥85  years  (OR=3.32; 95%  CI=1.23, 8.65;  p=0.014), women (OR=1.67; 95% CI=1.31, 2.11; p <0.001), and at risk of depression (OR=1.39; 95% CI=1.02, 1.89; p=0.035) were significantly associated with falls. Fewer hours of sleep in a day was associated with increased risk of falls (OR=0.91; 95% CI=0.84, 0.98; p=0.017). The Malays (OR=0.52; 95% CI=0.33, 0.84; p=0.007) and Chinese (OR=0.45; 95% CI=0.27, 0.73; p=0.014) ethnic groups were less likely to falls when compared to Indian and others ethnicity.

Conclusion

Knowing these predictors for falls could facilitate in identifying older people who might benefit from early falls prevention interventions in the community.

Keywords:

accidental falls aged, depression gender, Malaysia

Article Outline

  1. Introduction
  2. Methods
  3. Results
  4. Discussion
  5. Conflicts of interest statement
  6. References

Abstract

Background/Objective

Falls among older people leads to major consequences, which affects their quality of life. The causes are multifactorial, a combination of intrinsic and extrinsic factors, which include psychosocial and functional factors. This study aimed to determine the association between falls and the psychosocial factors, self-rated health, disability and sleep among community dwelling older people in Malaysia.

Methods

This study utilized the first wave data from the Towards Useful Ageing (TUA) cohort. A total of 1993 adults aged ≥60 years with no diagnosed psychiatric illness; without and with mild or moderate cognitive impairment were included in the analyses. Risk of falls, psychosocial factors (perceived stress, life satisfaction, loneliness, depression, social support, and sleep duration) and functional factors (disability and independence of activities of daily living) were assessed using a pre-tested questionnaire.

Results

The proportion of older people with a history of falls was 18.6%. The results of multiple logistic regression revealed aged between 75-84 years (OR=1.61; 95% CI=1.20, 2.15;  p=0.001), aged  ≥85  years  (OR=3.32; 95%  CI=1.23, 8.65;  p=0.014), women (OR=1.67; 95% CI=1.31, 2.11; p <0.001), and at risk of depression (OR=1.39; 95% CI=1.02, 1.89; p=0.035) were significantly associated with falls. Fewer hours of sleep in a day was associated with increased risk of falls (OR=0.91; 95% CI=0.84, 0.98; p=0.017). The Malays (OR=0.52; 95% CI=0.33, 0.84; p=0.007) and Chinese (OR=0.45; 95% CI=0.27, 0.73; p=0.014) ethnic groups were less likely to falls when compared to Indian and others ethnicity.

Conclusion

Knowing these predictors for falls could facilitate in identifying older people who might benefit from early falls prevention interventions in the community.

Keywords:

accidental falls aged, depression gender, Malaysia

1. Introduction

Fall is defined as “an unexpected event in which the participants come to rest on the ground, floor, or lower level”,1 and nearly 30% of older people fall at least once a year. 2 Nationwide studies in Malaysia reported up to 19.1%3,4 of older people reported at least one fall in the previous 12 months. On the other hand, the estimates of fall rates vary widely from 4.1% to 27.3% annually among community dwellers.5,6 This is probably due to discrepancies on the demographics of the older people, living arrangements, presence of diseases and the use of different instruments to ascertain falls. With population ageing, the incidence of falls and falls related injuries among older people are expected  to increase exponentially, which will incur higher health and social care costs.7

Numerous studies have been performed to determine the risk factors associated with falls in older people. These include but are not limited to demographic characteristics such as age8 and gender,9 medications used,10 lifestyles factors9 and environment conditions.4 In the local context, living alone and indigenous ethnic groups had been associated with increased risk of falls.6

In comparison to developed countries where only approximately 20% of fallers will need medical attention, a higher percentage at 60% of fallers in Malaysia experienced resultant injury that needed medical attention in the preceding 12 months.11 Falls is a major medical issue among older people due to its health economic and social burden and require further investigation. Falls are multifactorial, culmination of various combinations of intrinsic and extrinsic factors which also include psychosocial and functioal factors.12 Previous local studies on psychosocial and functional risk factors are scarce, and often limited to either small sample size or institutionalized older people. Hence, this study aimed to determine the association between falls and the psychosocial factors, self-rated health, disability and sleep among community dwelling older people in Peninsular Malaysia.

2. Methods

2.1. Participants

The present study utilized data derived from a national longitudinal study – Towards Useful Ageing (TUA) project, wave I. It was a study on aging that focused on a wide range of neuroprotective factors among a population- based sample of Malaysian older people. Participants were recruited using a multi-stage random sampling method from four states in Malaysia that have the highest numbers of older people aged 60 years and above. The methodology of this study had been described elsewhere.13,14 Briefly, this study recruited older people aged ≥60 years who were either normal or with mild cognitive impairment and was not diagnosed with psychiatric illness. Those with moderately severe or severe cognitive impairment (mini mental state examination scores below 15) were excluded.

2.2. Data collection

The extracted data used for analysis in this study included: 1) socio-demography: age, sex, ethnicity, education, marital status, living arrangement, employment, income; 2) history of falls in the last one year; 3) psychosocial factors (perceived stress, risk of  depression, satisfaction with life, loneliness, social network, social support, self-perceived success, perceived quality of life, self-rated health, duration of sleep; and 4) functional factors (disability and activities of daily living).

The outcome in this present study was history of falls and participants were asked if they have fallen in the past 12 months. The level of stress was measured using the 4-items Cohen’s Perceived Stress Scale15 with responses scored as  0 (never) to 4 (very often). Higher scores suggested greater stress. As for risk of depression, it was measured using the 15-items Geriatric Depression Scale.16 One point was awarded for each question with a total score of 15 with scores of ≥5 suggestive of risk of depression. Satisfaction with Life Scale measures global cognitive judgments of satisfaction with one’s life, which has 5 items.17 Higher scores indicated greater satisfaction.

Loneliness was assessed using 3-item scale and each item had three response categories namely hardly ever, some of the time, and often.18 Higher scores suggested greater loneliness. Satisfaction with social support was assessed using the Lubben Social Support Network Scale19 and Medical Outcome Study of Social Support survey.20 The 6-item Lubben Scale assessed kin and non-kin ties social network to screen for social isolation in older people. The scores ranged from 0 to 30 and scores of less than 12 suggested social isolation. The Medical Outcome Study of Social Support Survey comprised 19 items. It measured perceived availability of social support on a four-point Likert Scale namely 0 (none of the time), 1 (some of the time), 2 (most of the time), and 3 (all the time). Higher score was indicative of greater social support.

Flourishing Scale is an 8-item questionnaire with seven- point Likert Scale (1-strongly agree, 2-agree, 3-slightly agree, 4-neither agree nor disagree, 5-slightly disagree, 6-disagree, 7-strongly disagree).21 It measured human functioning ranging from positive relationships, to feelings of competence, to having meaning and purpose in life. Higher score indicated negative feelings. Quality of life, self-rated health and sleep pattern were ascertained using a closed ended question. Disability was assessed using the WHO Disability Assessment Schedule (WHODAS),22 with higher score suggested greater disability. Assessment of Activities of Daily Living (ADL) emphasized on questions related to personal care such as bathing, dressing, toileting, transferring, feeding and continence. Scores ranged between 0 and 6. Scores of 5-6, 3-4 and ≤2 suggested independence in ADL, moderately dependent and very dependent respectively.

2.3. Data analyses

Data was analysed using SPSS version 22.0. Descriptive data was described as mean and standard deviation or median and interquartile range for continuous data and as frequency and percentages for categorical data. Missing data of the variables in this study ranged from 0.04% to 4.28%. No imputation was done for missing data which explains the differences in denominator for each variables. Univariate approaches of logistic regression was applied to determine factors associated with history of falls and the results are presented as odds ratio and 95% confidence interval (95% CI). We regrouped the Indian and others ethnic groups as one and the secondary and tertiary educations as one for  the purpose of logistic regression analysis in view of the small numerator. Multivariate logistic regression model was developed using a stepwise backward likelihood ratio with 0.100 significant levels for an addition of the variable to predict risk of falls. We included all variables as factors in the logistic regression model to obtain the adjusted odds ratio (OR) for predicting risk of falls. The findings presented were based on the final model selection from the stepwise method. The findings were reported as adjusted odds ratio (OR), 95% confidence interval (CI) and p-value (<0.05) to determine the strength of contribution of each predictor towards history  of falls. We did not adjust for age, gender or other variables since the emphasis in this study was centered on identifying subgroups with highest risk and not on the  identification of causal risk factors. A sub-analysis on the sleeping duration among those with history of falls was performed to determine any association with age, sex and ethnicity, as this has not been explored in the Asian population.

2.4. Ethical conduct

This study was approved by the Medical Research Ethics Committee, Universiti Kebangsaan Malaysia. Study participants provided verbal and written consent prior to participation.

3. Results

A final sample of 1,993 older people were included for the analysis for this study. Among the 1,993 older people, 370 (18.6%) had a history of falls in the last one year (Table 1). Of those who had fallen in the last one year, 166 (44.9%) had fallen two or more times. Among those who fell, 181 (48.9%) did not sustain any injuries. About 24 (6.5%) and 60 (16.2%) reported to have sustained injuries and fractures, respectively but only 41 (11%) required hospitalisation. Most of the participants were in the 60-74 year old age group (82.5%), men (50.3%), of Malay ethnicity (63.6%), of primary education level (59.8%), married (71.8%) and were either living with spouse, family or friends (90.2%) (Table 1). The sociodemographic factors associated with falls were people aged ≥75 years (p=0.003) and women (p <0.001) as shown in Table 1.

Characterisitcs of the participants based on psychosocial and functional factors are as summarised in Table 2. Univariate analysis showed that factors associated with falls were those at risk of depression (p=0.018), lack social support (p=0.042) and reduced hours of sleeping in a day (p=0.027). Table 3 presents the findings of the multivariate logistic regression of factors associated with falls in our study population. The factors associated with falls were: aged between 75-84 years (OR=1.61; 95% CI=1.20, 2.15; p=0.001), aged ≥85 years (OR=3.32; 95% CI=1.23, 8.65; p=0.014), women (OR=1.67; 95% CI=1.31, 2.11; p <0.001), and at risk of depression (OR=1.39; 95% CI=1.02, 1.89; p=0.035). The Malays (OR=0.52; 95% CI=0.33, 0.84; p=0.007) and Chinese (OR=0.45; 95% CI=0.27, 0.73; p=0.014) ethnic groups were less likely to falls when compared to Indian and others ethnicity. The hours of sleep in a day was associated with fall; with every one unit increase in sleeping hours the risk of falls decreased by 9% (OR=0.91; 95% CI=0.84, 0.98; p=0.017). In this study, there was no collinearity between the factors associated with falls. The sub-analysis on sleeping hours among those with history of falls found an association between sleeping hours and ethnicity (p=0.033). The post-hoc LSD analysis showed the Malay (6.13±SD 1.74 hour) had less mean sleeping hours compared to the Chinese (6.72±SD 1.52 hours) (results not shown in table). No association was found between other ethnic groups or for age and gender.

4. Discussion

Our study found that women were significantly more likely to fall. The results also showed older people aged 75 years and older, and those at risk of depression and had shorter sleeping hours have significant risk of falls. This is the first large scale Malaysian study that provides falls prevalence and psychosocial falls predictors among multi-ethnic community dwelling older people.

Table 1. Socio-demographic factors associated with falls (n=1,993)

The prevalence of falls in our study was similar to previous studies in Malaysia among older people in community5 and with dementia.4 These prevalence ranged between 18.8% and 27.3%. Being older than 75 years was found to be a predictor of falls in our present study, similar to previous Malaysian studies among community dwelling older people. Moreover, a positive significant correlation exist between age and physiological falls risk.23 With increasing age, there are multiple physiological functional decline such as slower postural response and coordination, reduced muscle mass and strength and balance, and decline in cognitive function.24 All of these factors have been shown to increase the risk of falls among older people.

Our study found that being women was associated with falls. Previous studies showed mixed findings with regards to the association between falls and gender. In some, the prevalence of women who fell were higher than men.9 However, other studies found no effects on gender.4,5,25

Table 2. Associations between falls and psychosocial factors, self-rated health, disability and sleep

Women have more rapid decline in muscle strength and gait speed compared to men,26 which probably explains why women are more susceptible to falls.

Among the psychosocial factors assessed in our study, older people who were at risk of depression was demonstrated to be associated with falls. Community dwelling older people with depressions are three times more susceptible to falls than those without depression.27 In addition, older people with depression at baseline were more likely to fall in the following one year. Declined physical performance and depression may co-exist among older people, leading to higher risk of falls.28

Fewer hours of sleep in a day was another factor associated with falls in our study. Sleeping hours that are less than 5 hours in a day were associated with increased incidence of falls at least once in a year in previous studies.29 Excessive daytime sleepiness, which could be a result of less hours  of sleep, has been shown to be associated with falls among older people.30 Normal aging is accompanied by  changes in sleep quantity and quality with decreased sleep time and increased sleep fragmentation.31 The disruption of sleep and circadian rhythm may contribute to the impairment of behavioural and neurocognitive functions, which are similar risk factors of falls. We also found the Malay ethnicity slept less hours than the Chinese among those with history of falls. However, the reason for this is not known and require further evaluation in future studies in this region.

Our study found that Malay and Chinese ethnic groups were less likely to fall when compared to combined Indian and others ethnic groups. It is worth to note that in our study others ethnicity included indigenous people. These findings were similar to previous studies in Malaysia found that prevalence of falls was highest among the Indian and indigenous ethnicities.3,6 Further studies looking at the different ethnic groups health status is warranted to understand their risk of falls.

The present study evaluated only psychosocial factors of falls as well as self-rated health, disability and sleep. First, this study used retrospective data and excluded older people with moderately severe and severe dementia, which imposed a limitation to the transferability of the findings into practice. Secondly, history of fall was based on recalling on events over past 12 months. As highlighted in a recent study,32 prospective falls is desirable but requires more resources. In addition, there is good agreement between recalled falls report and prospective falls data, namely with recurrent falls.33 Thirdly, the findings of this study did not explore other falls risk factors such as excessive daytime sleepiness and environmental factors. Other falls risk factors that includes polypharmacy and comorbidities are considered separately in another publication. In the present study, older adults with history of falls were advised to seek further assessment and treatment at their nearest primary health care facilities.

At present, most falls prevention interventions are focused at improving physical wellbeing. Future studies need to explore falls prevention interventions that incorporates psychosocial education. Our study results showed that psychosocial fall risk factors such as at risk of depression and having less hours of sleep in a day contribute to falls among older people. Hence, psychosocial related falls risk factors should be considered in falls assessment and management strategies among older adults.

In conclusion, our present study identified several factors associated with
falls among community dwelling older people. Older people aged 75 and older, women, those at risk of depression and having less hours of sleep in a day were significant psychosocial predictors of falls. Knowing these predictors for falls could facilitate in identifying older people who might benefit from early falls prevention interventions in the community. Further
comprehensive geriatric assessment is also imperative to
identify other intrinsic risk factors of falls.

Conflicts of interest statement

The authors report no conflict of interest related to the work.

Acknowledgments

We would like to acknowledge the financial support under the Longterm Research Grant Scheme (LRGS) provided by Ministry of Education Malaysia (LRGS/ BU/2012/UKM– UKM/K/01). We would like to express our  gratitude to all co-researchers, fieldworkers, staffs, local authorities and subjects for their willingness to cooperate with us to make our study a success.

Table 3. Multivariate logistic regression on factors associated with falls

References

  1. Lamb SE, Jørstad-Stein EC, Hauer K, Becker C, on behalf of the Prevention of Falls Network Europe and Outcomes Consensus Development of a Common Outcome Data Set for Fall Injury Prevention Trials: The Prevention of Falls Network Europe Consensus. Journal of the American Geriatrics Society. 2005;53(9):1618-22.
  2. Gillespie LD, Robertson MC, Gillespie WJ, Lamb SE, Gates S, Cumming RG, et al. Interventions for preventing falls in older people living in the Cochrane Database Syst Rev. 2009;(2):CD007146.
  3. Norhafizah S, Noor Ain A, Mohamad Aznuddin , Chan YY, Sooryanarayana R, S Maria A, et al. Falls among older adults: Findings from screening at the Ministry of Health Malaysia Primary Care Clinics. Malaysian Journal of Medicine. 2015;70(S1).
  4. Eshkoor SA, Hamid TA, Nudin SS, Hassan A, Mun A Research on Functional Status, Environmental Conditions, and Risk of Falls in Dementia. International Journal of Alzheimer’s Disease. 2014;2014:e769062.
  5. Rizawati M, Mas Ayu S. Home Environment and Fall at Home Among.  the Elderly in Masjid Tanah Province. JUMMEC. 2008;11(2):72-82.
  6. Yeong UY, Tan SY, Yap JF, Choo Prevalence of falls among community-dwelling elderly and its associated factors: A cross-sectional study in Perak, Malaysia. Malays Fam Physician. 2016;11(1):7-14.
  7. Tan PJ, Khoo EM, Chinna K, Hill KD, Poi PJH, Tan An individually-tailored multifactorial intervention program for older fallers in a middle-income developing country: Malaysian Falls Assessment and Intervention Trial (MyFAIT). BMC Geriatrics. 2014;14:78.
  8. Chu LW, Chi I, Chiu Incidence and predictors of falls in the chinese elderly. Ann Acad Med Singap. 2005;34(1):60-72.
  9. Chien MH, Guo Nutritional Status and Falls in Community- Dwelling Older People: A Longitudinal Study of a Population-Based Random Sample. PLoS One. 2014;9(3):e91044.
  10. Kwan MM, Close JC, Wong AK, Lord SR. Falls incidence, risk factors, and consequences in Chinese older people: a systematic J Am Geriatr Soc. 2011;59(3):536-43.
  11. Sazlina SG, Krishnan R, Shamsul AS, Zaiton A, Visvanathan Prevalence of falls among older people attending a primary care clinic in Kuala Lumpur, Malaysia. Jurnal ftesihatan Masyarakat. 2008;14(1):11-6.
  12. Tromp AM, Smit JH, Deeg DJ, Bouter LM, Lips Predictors for falls and fractures in the Longitudinal Aging Study Amsterdam. J Bone Miner Res. 1998;13(12):1932-9.
  13. Shahar S, Omar A, Vanoh D, Hamid TA, Mukari SZ, Din NC, et al. Approaches in methodology for population-based longitudinal study on neuroprotective model for healthy longevity (TUA) among Malaysian Older Aging Clin Exp Res. 2016;28(6):1089-104.
  14. Vanoh D, Shahar S, Din NC, Omar A, Vyrn CA, Razali R, et Predictors of poor cognitive status among older Malaysian adults: baseline findings from the LRGS TUA cohort study. Aging Clin Exp Res. 2017;29(2):173-82.
  15. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385-96.
  16. Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, et al. Development and validation of a geriatric depression screening scale: a preliminary J Psychiatr Res. 1982-1983;17(1):37-49.
  17. Diener E, Emmons RA, Larsen RJ, Griffin S. The Satisfaction With Life Scale. J Pers 1985;49(1):71-5.
  18. Hughes ME, Waite LJ, Hawkley LC, Cacioppo A Short Scale for Measuring Loneliness in Large Surveys: Results From Two Population- Based Studies. Res Aging. 2004;26(6):655-72.
  19. Lubben J, Blozik E, Gillmann G,  Iliffe S, Kruse W von R, Beck JC,   et al. Performance of an Abbreviated Version of the Lubben Social Network Scale Among Three European Community-Dwelling Older Adult The Gerontologist. 2006 Aug 1;46(4):503-13.
  20. Sherbourne CD, Stewart AL. The MOS social support Soc Sci Med. 1991;32(6):705–14.
  21. Diener E, New measures of well-being: Flourishing and positive and negative feelings. Social Indicators Research. 2009;39:247-66.
  22. Sousa RM, Dewey ME, Acosta D, Jotheeswaran A t., Castro-Costa E, Ferri CP, et al. Measuring disability across cultures – the psychometric properties of the WHODAS II in older people from seven low- and middle-income countries. The 10/66 Dementia Research Group population-based Int J Methods Psychiatr Res. 2010;19(1):1-17.
  23. Singh DK, Pillai SG, Tan ST, Tai CC, Shahar Association between physiological falls risk and physical performance tests among community-dwelling older adults. Clin Interv Aging. 2015;10:1319-26.
  24. Ambrose AF, Paul G, Hausdorff JM. Risk factors for falls among older adults: A review of the Maturitas. 2013;75(1):51-61.
  25. Leung A, Chi I, Lou VWQ , Chan Psychosocial risk factors associated with falls among Chinese community-dwelling older adults in Hong Kong. Health Soc Care Community. 2010;18(3):272-81.
  26. Auyeung TW, Lee SWJ, Leung J, Kwok T, Woo J. Age-associated. decline of muscle mass, grip strength and gait speed: A 4-year longitudinal study of 3018 community-dwelling older Chinese. Geriatr Gerontol Int. 2014;14 Suppl 1:76-84.
  27. Qader MAA, Amin RM, Shah SA, Isa ZM, Latif KA, Ghazi Psychological risk factors associated with falls among elderly people in Baghdad city, Iraq. Open Journal of Preventive Medicine. 2013;3(7):441-5.
  28. Singh DK, Manaf ZA, Yusoff NA, Muhammad NA, Phan MF, Shahar. Correlation between nutritional status and comprehensive physical performance measures among older adults with undernourishment in residential institutions. Clin Interv Aging. 2014;9:1415-23.
  29. Kim SY, Kim SG, Sim S, Park B, Choi Excessive Sleep and Lack of Sleep Are Associated With Slips and Falls in the Adult Korean Population: A Population-Based Cross-Sectional Study. Medicine (Baltimore). 2016;95(4):e2397.
  30. Hayley AC, Williams LJ, Kennedy GA, Holloway KL, Berk M, Brennan-Olsen SL, et al. Excessive daytime sleepiness and falls among older men and women: cross-sectional examination of a population- based sample. BMC 2015;15:74.
  31. Espiritu Aging-related sleep changes. Clin Geriatr Med. 2008;24(1):1-14.
  32. Ibrahim A, Singh DKA, Shahar S, Omar MA. Timed up and go  test combined with self-rated multifactorial questionnaire on falls risk and sociodemographic factors predicts falls among community- dwelling older adults better than the timed up and go test on its own. J Multidiscip Healthc. 2017;10:409-16.
  33. Kunkel D, Pickering RM, Ashburn AM. Comparison of retrospective interviews and prospective diaries to facilitate fall reports among people with stroke. Age Ageing. 2011 Mar;40(2):277-80.

References

  1. Lamb SE, Jørstad-Stein EC, Hauer K, Becker C, on behalf of the Prevention of Falls Network Europe and Outcomes Consensus Development of a Common Outcome Data Set for Fall Injury Prevention Trials: The Prevention of Falls Network Europe Consensus. Journal of the American Geriatrics Society. 2005;53(9):1618-22.

  2. Gillespie LD, Robertson MC, Gillespie WJ, Lamb SE, Gates S, Cumming RG, et al. Interventions for preventing falls in older people living in the Cochrane Database Syst Rev. 2009;(2):CD007146.


  3. Norhafizah S, Noor Ain A, Mohamad Aznuddin , Chan YY, Sooryanarayana R, S Maria A, et al. Falls among older adults: Findings from screening at the Ministry of Health Malaysia Primary Care Clinics. Malaysian Journal of Medicine. 2015;70(S1).


  4. Eshkoor SA, Hamid TA, Nudin SS, Hassan A, Mun A Research on Functional Status, Environmental Conditions, and Risk of Falls in Dementia. International Journal of Alzheimer’s Disease. 2014;2014:e769062.


  5. Rizawati M, Mas Ayu S. Home Environment and Fall at Home Among.  the Elderly in Masjid Tanah Province. JUMMEC. 2008;11(2):72-82.


  6. Yeong UY, Tan SY, Yap JF, Choo Prevalence of falls among community-dwelling elderly and its associated factors: A cross-sectional study in Perak, Malaysia. Malays Fam Physician. 2016;11(1):7-14.


  7. Tan PJ, Khoo EM, Chinna K, Hill KD, Poi PJH, Tan An individually-tailored multifactorial intervention program for older fallers in a middle-income developing country: Malaysian Falls Assessment and Intervention Trial (MyFAIT). BMC Geriatrics. 2014;14:78.


  8. Chu LW, Chi I, Chiu Incidence and predictors of falls in the chinese elderly. Ann Acad Med Singap. 2005;34(1):60-72.


  9. Chien MH, Guo Nutritional Status and Falls in Community- Dwelling Older People: A Longitudinal Study of a Population-Based Random Sample. PLoS One. 2014;9(3):e91044.


  10. Kwan MM, Close JC, Wong AK, Lord SR. Falls incidence, risk factors, and consequences in Chinese older people: a systematic J Am Geriatr Soc. 2011;59(3):536-43.


  11. Sazlina SG, Krishnan R, Shamsul AS, Zaiton A, Visvanathan Prevalence of falls among older people attending a primary care clinic in Kuala Lumpur, Malaysia. Jurnal ftesihatan Masyarakat. 2008;14(1):11-6.


  12. Tromp AM, Smit JH, Deeg DJ, Bouter LM, Lips Predictors for falls and fractures in the Longitudinal Aging Study Amsterdam. J Bone Miner Res. 1998;13(12):1932-9.


  13. Shahar S, Omar A, Vanoh D, Hamid TA, Mukari SZ, Din NC, et al. Approaches in methodology for population-based longitudinal study on neuroprotective model for healthy longevity (TUA) among Malaysian Older Aging Clin Exp Res. 2016;28(6):1089-104.


  14. Vanoh D, Shahar S, Din NC, Omar A, Vyrn CA, Razali R, et Predictors of poor cognitive status among older Malaysian adults: baseline findings from the LRGS TUA cohort study. Aging Clin Exp Res. 2017;29(2):173-82.


  15. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385-96.


  16. Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, et al. Development and validation of a geriatric depression screening scale: a preliminary J Psychiatr Res. 1982-1983;17(1):37-49.


  17. Diener E, Emmons RA, Larsen RJ, Griffin S. The Satisfaction With Life Scale. J Pers 1985;49(1):71-5.


  18. Hughes ME, Waite LJ, Hawkley LC, Cacioppo A Short Scale for Measuring Loneliness in Large Surveys: Results From Two Population- Based Studies. Res Aging. 2004;26(6):655-72.


  19. Lubben J, Blozik E, Gillmann G,  Iliffe S, Kruse W von R, Beck JC,   et al. Performance of an Abbreviated Version of the Lubben Social Network Scale Among Three European Community-Dwelling Older Adult The Gerontologist. 2006 Aug 1;46(4):503-13.


  20. Sherbourne CD, Stewart AL. The MOS social support Soc Sci Med. 1991;32(6):705–14.


  21. Diener E, New measures of well-being: Flourishing and positive and negative feelings. Social Indicators Research. 2009;39:247-66.


  22. Sousa RM, Dewey ME, Acosta D, Jotheeswaran A t., Castro-Costa E, Ferri CP, et al. Measuring disability across cultures – the psychometric properties of the WHODAS II in older people from seven low- and middle-income countries. The 10/66 Dementia Research Group population-based Int J Methods Psychiatr Res. 2010;19(1):1-17.


  23. Singh DK, Pillai SG, Tan ST, Tai CC, Shahar Association between physiological falls risk and physical performance tests among community-dwelling older adults. Clin Interv Aging. 2015;10:1319-26.


  24. Ambrose AF, Paul G, Hausdorff JM. Risk factors for falls among older adults: A review of the Maturitas. 2013;75(1):51-61.


  25. Leung A, Chi I, Lou VWQ , Chan Psychosocial risk factors associated with falls among Chinese community-dwelling older adults in Hong Kong. Health Soc Care Community. 2010;18(3):272-81.


  26. Auyeung TW, Lee SWJ, Leung J, Kwok T, Woo J. Age-associated. decline of muscle mass, grip strength and gait speed: A 4-year longitudinal study of 3018 community-dwelling older Chinese. Geriatr Gerontol Int. 2014;14 Suppl 1:76-84.


  27. Qader MAA, Amin RM, Shah SA, Isa ZM, Latif KA, Ghazi Psychological risk factors associated with falls among elderly people in Baghdad city, Iraq. Open Journal of Preventive Medicine. 2013;3(7):441-5.


  28. Singh DK, Manaf ZA, Yusoff NA, Muhammad NA, Phan MF, Shahar. Correlation between nutritional status and comprehensive physical performance measures among older adults with undernourishment in residential institutions. Clin Interv Aging. 2014;9:1415-23.


  29. Kim SY, Kim SG, Sim S, Park B, Choi Excessive Sleep and Lack of Sleep Are Associated With Slips and Falls in the Adult Korean Population: A Population-Based Cross-Sectional Study. Medicine (Baltimore). 2016;95(4):e2397.


  30. Hayley AC, Williams LJ, Kennedy GA, Holloway KL, Berk M, Brennan-Olsen SL, et al. Excessive daytime sleepiness and falls among older men and women: cross-sectional examination of a population- based sample. BMC 2015;15:74.


  31. Espiritu Aging-related sleep changes. Clin Geriatr Med. 2008;24(1):1-14.


  32. Ibrahim A, Singh DKA, Shahar S, Omar MA. Timed up and go  test combined with self-rated multifactorial questionnaire on falls risk and sociodemographic factors predicts falls among community- dwelling older adults better than the timed up and go test on its own. J Multidiscip Healthc. 2017;10:409-16.


  33. Kunkel D, Pickering RM, Ashburn AM. Comparison of retrospective interviews and prospective diaries to facilitate fall reports among people with stroke. Age Ageing. 2011 Mar;40(2):277-80.