INTRODUCTION:

Beyond expectation that individual who aged 65 and above has a higher risk of fall. Fall is “an event which result in a person coming to rest inadvertently on the ground or floor or other lower level”¹.

Fracture, strain, sprain, laceration, or persistent pain more than seven days are falls related injury. Injury fall can be fatal or non-fatal. One’s may seek medical care and even emergency department after a fall².

In addition, fall are the second leading cause of accidental or unintentional injury deaths worldwide. Approximately 646,000 individuals worldwide die from fall every year. A great number of fatal falls are from elderly population. About 37.17 million falls have make the faller to sought for medical attention each year¹. 28%-35% of community dwelling elderly worldwide fall every year³. Following to WHO global report on fall prevention, 28%-35% of individual aged 65 and above fall in every year. This proportion increased as age and frailty level increased⁴.

There was 14%-53% of people aged 65 and above fall each year in India. In 2004, about one fifth 424,000 fall related death happen in India⁴. There were one quarter of people aged 65-74 and more than one third of people aged more than 75 years old reported a fall in American⁵.

The prevalence of fall among elderly in Malaysia range from 19.1% to 47%⁶. The prevalence of fall among community dwelling older adult range from 15%-28% in Malaysia⁷. Not to mention, there was 24% of faller having serious injuries and 6% of faller having fracture. There was also one in three of community elderly fall each year. As a result, faller may experience pain, subjected to hospital, surgical intervention, admission to nursing home, decreased overall functional ability, heading to a poor quality of live and developed fear of fall⁸.

Fallers are prone to have difficulties during turning. A study shows among 718,582 turns performed, prospective fallers turned less frequently, took longer to turn, and were less consistent in turn angle (p = 0.007, 0.025, and 0.038, respectively)⁹. Prospective fallers also walked slower and spent less time walking and turning and more time engaged in sedentary behaviour (p = 0.043, 0.012, and 0.015, respectively). Recurrent fallers also show staggering during turning, increased time, and the number of steps to complete turning. Hence older persons may struggle to maintain their stability and to avoid falling during turning¹⁰.

Since elderly has a higher risk of fall compared younger generation and turning is one of their common activities of daily living. Therefore, the primary aim of this study is to investigate the relationship between turning difficulty and fall risk among elderly.

MATERIALS AND METHODS:

Research Design:

A cross-sectional study design was employed to determine the relationship between turning difficulty and fall risk among geriatric population. This study was conducted at Klang Valley, Malaysia. Simple random sampling method was used for the recruitment of participants. This research project was funded by Universiti Tunku Abdul Rahman Research Fund (UTARRF) (IPSR/RMC/UTARRF/2022-C2/P03). This study was approved by Scientific and Ethical Review Committee of Universiti Tunku Abdul Rahman (UTAR).

Procedure:

A total of 138 participants were ascertained as the samples for this research study. The participants were asked to sign up the consent form and data protection form. The aim and procedure of the study were explained to the participants. The inclusion criteria were the aged 65 and above, with or without history of fall and able ambulate with or without walking aid. Subject were excluded if they unable to understand the instruction, has recent fracture of lower extremity, non-ambulatory, deaf, blind and have cognitive impairment were excluded from the study.

Participants were screened with a health status questionnaire for demographic purpose. The questions involved age group, gender, coexist medical condition, medication used, frequency of fall, reason of fall and use of assistive device. Each participant was then assessed with Modified Fall efficacy Scale. The confidence level in performing 14 activities listed in MFES without a fear of fall on a 0-10 scale were rated by each participant. 0 means “not confidence/ not sure at all”, 5 means “fairly confident/ Fairly sure” and 10 means “completely confident/ Completely sure. The MFES score of each subject were calculated by dividing the total rating (0-140) by 14. A score of <8 indicate fear of fall and score of > 8 indicate lack of fear.

Thenceforth, the participants were subjected to Time Up and Go test for turning difficulty. A chair with armrest was placed 3 meters away from the floor. Footwear and walking aid can be used during the test. No physical assistance was given to the participant. The participants were seated with their back against the back of chair and arm on armrest. The participants were stood up and walked toward the floor marker on the command “GO” as fast as possible. Then a turn was made and the participant was returning back to sit on the chair. Timing was started on the command go and stop once the participants back touched the chair. A trial section was given and followed by actual test. A score more than 14 second indicate turning difficulty. Data collected was then analysed using IBM SPSS Statistic for Windows (Version 23.0, IBM Inc, Armonk, NY, USA).

RESULT:

Association between MFES with other variables:

Table 1.1 Association between age group and MFES score

Age group	MFES	95% CI	T	p-value
Age group	Mean(sd)	95% CI	T	p-value
65-75	8.66(1.72)	0.611_3.34	2.96*	0.006
75-85	6.69 (2.89)

*t test was performed, level of significant at p< 0.05. MFES= modified fall efficacy scale

The mean of MFES score for age group 65-75(8.66,1.72) is higher than MFES of age group 75-85(6.69, 2.89). The difference in mean value is statistically significant p value = 0.006, as shown in table.

Table 1.2 Association between gender and MFES score

Gender	MFES Mean (sd)	95% CI	T	p-value
Male	8.63(1.81)	-0.55_2.10	1.17	0.246
Female	7.85(2.45)

*t test was performed, level of significant at p<0.05. MFES= modified fall efficacy scale

As shown in table male 8.63(1.81) has higher MFES score compared to female 7.85(2.45). The difference in mean value is not statistically significant (p>0.05).

Table 1.3 Association between Coexist medical condition and MFES score

Coexist medical condition	MFES Mean (sd)	df	F	p-value
0-1	8.69(2.01)	2	7.18*	0.001
2-3	7.74(2.18)
≥4	5.60(2.67)

*ANOVA test was performed, level of significant at p< 0.05, df= degree of freedom. MFES= modified fall efficacy scale

A one-way ANOVA test was performed to investigate the association between coexist medical condition and MFES score. Participant were divided into three group according to the coexist medical condition (Group 1: 0-1; Group 2: 2-3; Group 3: ≥ 4). There was a statistically significant difference at p <0.05 level in MFES score for the three coexist medical condition group. The post-hoc comparison using Tukey HSD tests indicate that the mean score for Group 1 was significant difference from Group 3. Group 2 do not show a strong significant difference with group 3 as p=0.048. Group 2 also show no significant difference from Group 1.

Table 1.4 Association between medication used and MFES score

Medication used

MFES

Mean(sd)

95%CI

p-value

< 4

8.43(2.02)

1.60_4.60

4.13

0.000

≥4

5.33(2.62)

*t test was performed, level of significant at p<0.05. MFES= modified fall efficacy scale

This shows that participants took less than 4 medications has mean MFES score 8.43(2.02) and participants took more than 4 medications has mean MFES score 5.33(2.62). Participants took less than 4 medications has greater mean MFES score than participant took more than 4 medications. The difference in mean value was statistically significant (p<0.05).

Table 1.5 Association between Frequency of fall and MFES score

Frequency of fall

MFES

Mean(sd)

95% CI

p-value

None

8.5 (1.94)

0.33_2.54

2.59

0.012

Fall in last

12 months

7.1 (2.64)

*t test was performed, level of significant at p<0.05. MFES= modified fall efficacy scale

It showed that the mean MFES score for fall in last 12 months 8.5(1.94) was lower than none fall 7.1(2.64). The different in mean value was statistically significant (p<0.05).

Table 1.6 Association between reason of fall and MFES score

Reason of all	MFES Mean (sd)	df	F	p-value
Indoor	4.22 (3.54)	3	5.950*	0.003
Outdoor	6.78 (1.63)
Slipping	8.44 (1.52)
Tripping	8.37 (1.66)

*ANOVA test was performed, level of significant at p< 0.05, df= degree of freedom MFES= modified fall efficacy scale.

A one-way ANOVA test was performed to investigate the association between reason of fall and MFES score. The mean MFES for fall in indoor (4.22, 3.54) is lower than outdoor (6.78, 1.63) followed by tripping (8.37, 1.66) and slipping (8.44, 1.52). The post-hoc that there was significant mean different between indoor and slipping followed by tripping. There was no significant mean different between outdoor and other reasons of fall.

Table 1.7 Association between use of assistive device and MFES score

Use of assistive device

MFES

Mean (sd)

95% Cl

p-value

Yes

4.81(2.47)

-5.24_-1.92

-4.31

<0.001

8.39(2.04)

*t test was performed, level of significant at p<0.05. MFES = modified fall efficacy scale

Result showed that the mean MFES score for use of assistive device 4.81(2.47) was lower than no use of assistive device 8.39(2.04). The different in mean value was statistically significant (p<0.05).

Association of TUG with other variables:

Table 1.8 Association of gender with TUG

	TUG
Gender	Below 14 seconds n(%)	14 seconds and above n(%)	χ²	df	p-value
Male	28(87.5)	4(12.5)	0.782*	1	0.377
Female	82(77.4)	24(22.6)

* Chi-Square test was performed, level of significant at p < 0.01, df = degree of freedom, TUG= Time up and go test.

The number of participants who done TUG below 14 seconds was higher in female 82(77.4%) than male 28(87.5%). The number of participants who done TUG 14 seconds and above was higher in female 24(22.6%) than male 4(12.5%). The difference between the time taken to complete TUG and gender was not statistically significant as p = 0.337.

Table 1.9 Association of coexist medical conditions with TUG

	TUG
coexist medical conditions	Below 14 seconds n(%)	14 seconds and above n(%)	χ²	df	p-value
0-1	70(89.7)	8(10.3)	11.322*	2	0.003
2-3	34(77.3)	10(22.7)
≥4	6(37.5)	10(62.5)

*Chi-Square test was performed, level of significant at p < 0.05, df = degree of freedom, TUG= Time up and go test.

Result showed that 70(89.7%) participants with 0-1 medical conditions finished TUG below 14 seconds followed participants 34(77.3%) with 2-3 medical conditions and participants 6(37.5%) with ≥4 medical condition. There was lesser number of participants 8(10.3%) with 0-1 medical conditions finished TUG by 14 seconds and above as compared to participants with 2-3 and ≥4 medical conditions. The different between coexist medical condition and TUG was significant (p<0.05).

Table 1.10 Association of medication used with TUG

	TUG
Medication used	Below 14sec n(%)	14 and above n(%)	χ²	df	p-value
<4	104(86.7)	16(13.3)	13.764*	1	<0.001
≥4	6(33.3)	12(66.7)

* Chi-Square test was performed, level of significant at p < 0.01, df = degree of freedom, TUG= Time up and go test.

Participants who consume <4 medication 104(86.7%) completed TUG below 14 seconds followed by participant who consume ≥4 medication 6(33.3%). Most of the participants who consume ≥4 medication completed TUG 14 seconds and above. The different between medication used and TUG was significant (p< 0.01).

Table 1.11 Association of frequency of fall with TUG

	TUG
Frequency of fall	Below 14 seconds N (%)	14 seconds and above n(%)	χ²	df	p-value
None	72(85.7)	12(14.3)	2.392	1	0.122
Fall in last 12 months	38(70.4)	16(29.6)

* Chi-Square test was performed, level of significant at p < 0.01, df = degree of freedom, TUG= Time up and go test.

For completing TUG below 14 seconds, most of the participant do not have a fall 72(85.7%), followed by participants who have fall in last 12 months 38(70.4%). 16(29.6%) participants who have fall in last 12 months done TUG 14 seconds and above compared to 12(14.3%) participants who do not have fall. However, the different between frequency of fall with TUG was not statistically significant p= 0.122.

Table 1.12 Association of reason of fall with TUG

	TUG
Reason of fall	Below 14 seconds n(%)	14 seconds and above n(%)	χ²	df	p-value
Indoor	4(33.3)	8(66.7)	5.528*	3	0.137
Outdoor	8(66.7)	4(33.3)
Slipping	22(78.6)	6(21.4)
Tripping	40(69.0)	18(31.0)

* Chi-Square test was performed, level of significant at p < 0.05, df = degree of freedom, TUG= Time up and go test

Association between reason of fall and TUG was analysed by chi-square as show in table 4.3.9. Number of participants who accomplished TUG below 14 second was higher in participants who fall due to tripping 40(69.0%) followed by slipping 22(78.6%), outdoor 8(66.7%) and indoor 4(33.3%). Outdoor showed the lowest number of participants who complete TUG 14 seconds and above. However, there was no statistically significant between reason on fall and time taken to complete TUG (p >0.05)

Table 1.13 Association between use of assistive device with TUG

	TUG
Use of assistive device	Below 14 seconds n(%)	14 seconds and above n(%)	χ²	df	p-value
Yes	4(28.6)	10(71.4)	12.597*	1	<0.001
No	106(85.5)	18(14.5)

* Chi-Square test was performed, level of significant at p < 0.01, df = degree of freedom, TUG= Time up and go test.

Result revealed that most of the participants 106(85.5%) who do not use assistive device done TUG below 14 seconds compared to participants 4(28.6%) who use assistive device. The different between use of assistive device with TUG was statistically significant (p<0.01).

Association of TUG with MFES:

Table 1.14 Association of TUG with MFES

	MFES
TUG	Mean (sd)	95% CI	t*	p-value
<14 sec	8.95(1.3)	3.290_5.718	7.874	<0.001
≥14 sec	4.44(2.03)

*t test was performed, level of significant at p<0.05. TUG= Time up and go test, MFES = modified fall efficacy scale

Independent T test was performed to analyse the association between TUG and MFES as shown in table 4.4. The result showed that the mean MFES score for participants completed TUG <14 sec was 8.95 (1.3) higher than the mean MFES score 4.42 (2.03) for participants completed TUG ≥14 sec. This show that participant with lower turning difficulty has lower risk of fall. The different in mean value was statistically significant (p<0.05).

DISCUSSION:

A total of 138 participants were recruited for this study with 94 participants aged 65 – 75 and 22 participants age 75 – 85. Female (n=106, 76.8%) constitute most participants. Among them, (78, 56.5%) of them have 0 – 1 medical condition and (44, 31.9%) of them have 2 – 3 medical conditions followed by (16, 11.6%) of them have ≥4 medical conditions. 87% of participant have no polypharmacy. 54 of the participants have fall in last 12 months and most of them fall due to slipping (28, 48.3%). More than half participant (134, 89.9%) able to ambulate independently without the need of assistive devices. 80% of them show no turning difficulty as they complete TUG below 14 second. The mean MFES score for the participants was 8.03.

Finding of the current study showed that association between aged group and MFES score was statistically significant (p<0.05). Participants with age 65 – 75 has MFES score of more than 8 indicating low risk of fall. Previous study also shows that elderly aged 60 – 69 has a MFES score of more than 8 than elderly aged 80 above¹¹. Another study done oversea shows age was negatively correlate with MFES value as p value <0.01¹². This showed as age increased the MFES value will become lower, indicating risk of fall.

Result showed male have higher MFES score 8.63(1.81) than female. However, there was no statistically significant association between gender and MFES score in this study. Finding of current study was supported by two studies that male have higher MFES score than female^13-14. In contrary, two other studies Leung, P. M. et al (2017) found women had higher MFES score than men^15-16.

Current study showed a significant association between coexist medical condition and MFES score (p<0.05). Participants with more coexist medical condition have low MFES score. Most of the previous study found was about the type of medical condition and fall risk. This depicts medical condition such as depression, heart failure and hypertension were associated with high fall risk in the elderly¹⁷.

Current study showed a significant association between medication used and MFES (p<0.05). Taking medication of more than or equal to four medication is considered polypharmacy. Participant with polypharmacy has lower mean MFES score. Outcome of previous study done revealed the rate of fall was 18% higher in elderly with polypharmacy¹⁸. Individual who taking more than 4 medication was correlated with increased risk of fall, injurious fall and recurrent fall. The fall risk also differs with the type of medication consumed¹⁹. Another study depicted that community dwelling elderly with increased number of medications used were exposed to increased fall risk²⁰.

In addition, finding on the current study show a significant association between frequency of fall and MFES score as p < 0.05. Faller has lower mean MFES score (7.1, 2.64) than non-faller (8.5, 1.94). This finding is favour with other related studies claims that frequency of fall was negatively correlated with MFES^21-24.

Present study showed participants who use assistive device has a risk of fall (p<0.05). Other studies also showed individual who used walking aid has low MFES score^25-27.

Data showed aged group has a significant association with the time taken to complete TUG (p<0.01). Participants aged 65 – 75 mostly show less turning difficulty as they complete TUG below 14 seconds. Several studies reported a similar finding that elderly more than aged of 80 need more time to complete TUG than young adult of aged 65-75^27-29. A two-way ANOVA test demonstrated significant association between age group and TUG score with p-value <0.0001. Pearson product moment correlation coefficient also show a significant positive correlation between age group and TUG score (r= 0.25, p < 0.001). Regression analysis showed that age was a significant predictor on time taken to complete TUG (p<0.05)³⁰.

Although females show to have less difficulty in turning, current study showed not statistically significant difference between gender and TUG. In contrary, independent t-test showed the association between gender and TUG was statistically significant as p value <0.001 in previous studies done^27-28,31. Females (11.2 ± 3.2sec) spend longer time to complete time up and go test than males (9.3±2.8sec).

Study found association between coexist medical condition and time taken to complete TUG was statistically significant (p<0.05). Similar result was found in the study done^31-33 where number of comorbidities was significantly associated with time taken for TUG (p<0.05). Besides, a univariable analysis show that number of coexist medical condition able to predict TUG time significantly in research conducted. It mentioned an increase in number of coexist medical condition was able to lengthen the time spent on TUG significantly³³.

On the other hand, current study found that association between medication used and time taken to complete TUG was statistically significant (p<0.01). Most of the participants taking less than 4 medications completed test below 14 seconds. A few other studies show number of medications used was significantly correlated with time to complete TUG (r =0.322, p< 0.001). This showed the time to complete TUG was increased with increasing number of medications used^34-35.

Even though most of the non-faller complete done TUG below 14 seconds, current study found that association between frequency of fall and time taken to complete TUG was not statistically significant as p =0.122. This finding is in line with few other studies that show time taken to complete TUG was almost similar between faller (29.5 ± 9.3 seconds) and non-faller (32.9 ± 10.6 seconds)³⁶. A pilot study done illustrated that faller take more time to done TUG than non-faller (p<0.001)³⁸. Receiver operating curve (ROC) analysis from previous study showed significant different between fall and non-fall on time to complete TUG³⁷.

Study found association between uses of assistive device and time taken to complete TUG was statistically significant as p = 0.001. About 85% of participant who did not used assistive device accomplished the test less than 14 seconds. Similar result was found in another study. It showed time taken to complete TUG was highly correlated (r=0.95) with use of assistive device. Participants who did no used assistive device complete TUG faster than those who use assistive devices³⁷. A regression analysis showed that use of assistive device was a significant predictor on time taken to complete TUG (p<0.05). It showed participant using assistive device spent more time to complete TUG^38,43.

Result of present study have shown turning difficulty was associated with fall risk among the geriatric participants. Several studies favour these findings. These studies proved that turning difficulty during walking predispose an individual to risk of fall and taking more than five steps to turn indicate turning difficulty which in turn correlate with risk of fall in geriatric population³⁹. Previous study showed elderly who spend more time on turning, more step on turning were related to future recurrent fall⁴⁰. Besides, studies also show evidence that elderly with turning difficulty often use simplified movement pattern to reduce the risk of fall. From these studies, we may conclude that turning difficulty was associated with the risk of fall^{41-42, 44-49}.

After all, there are few limitations need to be addressed in this study. First and foremost, cause and causal relationship cannot be exactly determined by cross-sectional study. As elderly with risk of fall might have turning difficulty. Secondly, modified fall efficacy scale use in the study was a self-rated questionnaire. Hence, this may predispose to recall and reporting bias. Recalling the frequency of fall by participants may probably cause recall bias. Thirdly, the participants involve in this study were Chinese and Indians and Chinese compose of the majority. Therefore, the result cannot be generalised to whole population in Malaysia. At last, most of the participants are comparatively healthy and physically active. They do not have history of fall and able complete TUG below the cut-off point.

It is recommended that study on the causal relationship of turning difficulty on fall risk can be done in future. Larger sample size and participant from whole nation in Malaysia are needed so that the result can be generalize to all population in Malaysia. Others examination tool should be used instead of self-rated tool in future study to prevent the recall bias.

CONCLUSION:

In a nutshell, this study has highlighted the relationship between turning difficulty and fall risk among geriatric population. As there was significant mean different of MFES score for participants completed TUG below 14 second and participant completed TUG 14 second and above. Hence, participant with turning difficulty was prove to has fall risk. However, the causal relationship between both variables was not able to show through this cross-sectional study.

CONFLICT OF INTEREST:

The authors have no conflicts of interest regarding this study.

ACKNOWLEDGMENTS:

The authors would like to thank all participants for their kind support during data collection.

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47. Training

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Received on 26.11.2023 Revised on 07.07.2024

Accepted on 20.12.2024 Published on 28.01.2025

Available online from February 27, 2025

Research J. Pharmacy and Technology. 2025;18(2):785-791.

DOI: 10.52711/0974-360X.2025.00116

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