View of Risk of fall and its Contributing Factors among Older adults with Chronic Low Back Pain

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18895 http://annalsofrscb.ro

Risk of fall and its Contributing Factors among Older adults with Chronic Low Back Pain

EmanShokryAbd Allah¹, Mona Gamal Ahmed AbdAlla², Hassanat Ramadan Abdel- Aziz³

1Professor and Head of Gerontological Nursing Department, Faculty of Nursing, Zagazig University, Egypt, Email: [email protected]

2Demonstrator of Gerontological Nursing, Faculty of Nursing, Zagazig University, Egypt

3Lecturer of Gerontological Nursing, Faculty of Nursing, Zagazig University, Egypt, Email:

[email protected]

Corresponding Author: Mona Gamal Ahmed Abdalla, Email:

[email protected]

Abstract

This cross-sectional study aimedto assess risk of fall and its contributing factors among older adults with chronic low back pain (CLBP). A random sample composed of 135 older adults from outpatient clinics at X University Hospitals. Risk of fall was measured byFall Risk Assessment Scale.Contributing factors were identified by investigating the relationship of risk of fall with older adults’ characteristics. Study results revealed that 51.9% and38.5% of older adults were at severe and moderate risk of fall, respectively. Statistically significant relations were found between risk of fall and age, female gender, rural residence, illiteracy, not working, insufficient income,chronic diseases, medication use, CLBP intensity, and numbers of fall.High prevalence ofsevere risk of fall and many contributing factors were identified among older adults with CLBP. So, Continuous fall risk assessment in CLBP patients with special concern for contributing factors assessed in study is recommended.

Keywords: Risk of fall, older adults, chronic low back pain, contributing factors

Introduction

The world's aging population will rise at rate never seen before. Seniors aged 60 and up will rise from 610 million in 2000 to over two billion by 2050(Ng et al., 2020).Egypt's older population number was 6.3 million (3.3 million males, 2.9 million females), representing6.7 percent of the total population (Ahram online, 2019).In most of the developed world, the agreed definition of "elderly" is a chronological age of at least 65 years; there are United Nations (UNs) standard demographic requirements, but the UNs agreed criteria is 60+ years to refer to the elderly population (Agrawal, 2016).Neuromuscular changes, such as reduced force generation power, altered muscle fiber-type proportion, and slower motor unit firing rate, are also correlated with aging. As a result, older adults have weaker, less fatigue- resistant muscles and a higher risk of falling(Da Silva et al., 2015). Chronic low back pain (CLBP) is the most common type of musculoskeletal pain, especially among older adults (Stensland& Sanders., 2018).Risk factors for LBP, including psychological stress, structural defects of the spine, as well as biomechanical and genetic factors.However, imaging or biomechanical analysis cannot identify a particular cause in 85% of CLBP cases, and this form of LBP is known as non-specific CLBP(Kim et al., 2018).LBP has been identified as an independent risk factor for falls. Community-dwelling seniors with CLBPhad significantly increased risk of falling(Wong et al., 2017). More than a third of people aged 65 and up experience at least one falls per year. About 20% and 30% of those who fall experience moderate to serious injuries, such as fractures and head trauma, which may result in disability, early nursing home admission, and even death (Hirase et al., 2020).Multiple risk factors combine to cause the majority of falls. The probability of falling increases as the

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number of risk factors increases. The balance, range of motion, and speed of movement are all influenced by age-related physiological and psychological changes. older adults can be unsteady on their feet because of balance problems; hence, the risk of falling rises significantly(Brahmbhatt&Sheth, 2019).Chronic pain, especially musculoskeletal pain, has been related to risk of falls in community-dwelling older adults.Older people who are in pain are more likely to have fallen in the previous year and are at a greater risk of falling again than those without pain (Cederbom&Arkkukangas, 2019).Gerontological nurses play a vital role in preventing fall risk by identifying the prevalence and risk factors of falls and informing the elderly and their family members about how to cope with and manage these risk factors so that falls are prevented as much as possible.As well as they are responsible for rehabilitation of older adults who have fallen (Elsamahy et al, 2019).

Literature review

The prevalence of severe risk of fall among older adults with CLBP vary whereas, high prevalence was reported in a prospective cohort study carried out in Brazil by ‏Rosa et al.

(2016)who demonstrated that older adults with LBPhad severe risk of fall. Additionally, a study in Japan assessed aged people with LBP at risk of falls reported thatolder people with increases of chronicity and intensity of LBP had a higher risk of fallsKitayuguchi et al.

(2017).A recent study carried out in Alexandria, Egypt by Abd El Ghany et al. (2018) found that among the studied elderly highest percentages of the older adult had moderate risk of fall, about one-quarter had mild risk and almost quarter had severe risk of fall.In the study setting, the fall risk assessment is usually omitted during the examination and treatment of older adults diagnosed with CLBP. Furthermore, studies that assess risk of fallamongolder adult with CLBPin our country are limited; hence this study was conducted to assess risk of fall and its contributing factors among older adults with CLBPat X University Hospitals, X.

Method

Study Design and Ethical Considerations

A cross-sectional study design was utilized to conduct the current study from August 2020 up to the beginning of November 2020 in four outpatient clinics at X University Hospitals. The study was approved by the Research Ethics Committee and Postgraduate Committee of the Faculty of Nursing at X University. Verbal consent was obtained from the older adultsafter a description of the purpose of the study.

Sample

Simple random samplecomposed of 135 older adults aged 60 years or above, diagnosed with CLBP from three months or more, free from traumatic injuries, back surgery and neurological disorders asParkinson disease and stroke, and able to communicate was selected in the recruitment of this study.

Sample size calculation

The sample size was calculated using open EPIinfo software program from CDC. It was based on number of admitted older adults with low back pain in four outpatient clinics (orthopedic, Neurological, Chinese acupressure, and Rheumatology and Rehabilitation clinics) and prevalence of risk of fall in a previous study was 52.5% (Abd El Ghanyet al., 2018), at confidence level 95%, so the sample was 135.

Tool of data collection

Three tools were used to collect necessary data. Tool I: an interview questionnaire that was developed by the researchers based on the literature review. It consisted of three parts;Part one used to assess demographic characteristics which included age, gender, residence, marital status, educational level, and monthly income. Part two involved questions about the history of chronic diseases, medications, numbers of fall, causes of fall, and complication of fall. Part

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three involves questions about daily habits which include smoking, caffeine consumption, and practicing regular exercise.

Tool II: Numeric Pain Rating Scale (NPRS): (McCaffery& Beebe, 1989).

This scale was developed by McCaffery& Beebe (1989) to measure pain. It assesses a patient's pain level over the previous 24 hours, ranging from 0 (no pain) to 10 (severe pain). It is made up of an 11-point self-reporting scale. A score (0) suggested no pain, 1 to 3 suggested mild pain, 4 to 6 suggested moderate pain, and 7 to 10 suggested severe pain.

Tool III: Fall risk assessment scale(Cannard, 1996).

This scale was used to assess the risk factors for falls in older adults with CLBP. It was developed byCannard (1996). It includes sex, age, gait, sensory deficit, history of falls during the past year, medical history, medications, and mobility. An Arabic version of the test was validated by Algameel (2013) was used in the present study. It consists of 8 questions.The sum of theresponses can provide a maximum score of 19; a score of 3-8 indicates low risk of fall, scores that range between 9 and 12 indicate moderate risk of fall, and a score ≥ 13 indicates high risk for falls. In the current study, it’s Cronbach α was 0.85.

Statistical analysis

The collected data were organized, tabulated, and statistically analyzed using the Statistical Package for Social Sciences (SPSS) version 22. Data were presented using descriptive statistics in the form of frequencies and percentages. Chi-square test (X2) was used for comparisons between qualitative variables. Cronbach alpha coefficient was calculated to assess the reliability of fall risk assessment scale through their internal consistency. In order to identify the independent predictors of the scores of fall risk assessment scale, the multiple linear regression analysis was used. Statistical significance was considered at p. value < 0.05.

Results

Among 135 older patients, the mean age was 70.37±5.32 years, 54.1% were females and 85.2% belonged to rural areas. 75.5% of the participants were married, 45.9% were illiterate, and 63% had insufficient monthly income (Table 1).According to falls risk assessment scores, 51.9% were atsevere risk of fall, 38.5% wereat moderate risk of fall, and only 9.6%

were at mild risk of fall. The mean score of risk of falling was 11.16±2.18 (Table2).The study findings also revealed that age,gender, marital status, educational level, current occupation, monthly income, residence, and living conditionwere highly statistically significantly related to the total risk of fall of older adults at P > 0.001. It is clear that the higher percentages of older adults with sever risk of falling were aged 60 to less than 70 years, females, belonged to rural areas, married, illiterate, not working, insufficient income, and living with spouse (Table 1).Regardingto health history of the studied older adults, 89.6% of them had chronic diseases. 72.6% of older adultswere on regular medications. The higher percentages of older adultshad severe pain (65.9%).45.9% of older adultsfell once and93.3% of older adultswere fearof falling again. Also, 93.3% of older adults do not exercise regularly.(Table 3).The studyalso demonstrates that there were highly statistically significant relations between the total risk of fall of older adultsand their chronic diseases,regular medication use, CLBP intensity, numbers of fall, and physical activity at P >

0.001. While there were statistically significant relations between the total risk of fall and fearing of fall (P=0.01). Where, the higher percentages ofolder adultswith severe risk of fall were had chronic diseases, regular medication use, severe CLBP intensity, fallen one time, fearing of fall and had no physical activity. No statistically significant relationships were detected between smoking (p=.846), caffeine consumption (p=.605) and total risk of fall (Table3).Table4 expounds that age (p=.007), marital status (p=.03), chronic diseases

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(p=.000), regular medication use (p=.02), numbers of fall (p=.001), and total pain intensity (p=.000)were statistically significant independent predictors of older adult’srisk of fall.

Discussion

Based on the present study findings, the highest percentages of the studied older adults had severe risk of fall and approximately two-fifth had moderate risk of falland the mean score of risk of falling was 11.16±2.18according to fall risk assessment scale (FRAS). Such result might be due to age-related changes and the consequence of severe low back pain that led to different symptoms that interfere with mobility and balance and the majority of older adults with CLBP don’t exercise regularly to avoid experienced of pain during mobility that result in muscle weakness and then increase risk of fall.Meanwhile, a study conducted in Brazil by Rosa et al. (2016) found that older adults with LBP had a significantly severe risk for falls than those without LBP, and physical therapists in the clinical setting should be aware of severe risk of falling among their older adults. Another a prospective study carried in University of Delaware’s by Knox et al. (2021) revealed that older adults with CLBP had a higher risk offalling. Also, study conducted in Japan byKitayuguchi et al. (2017) found that older peoplewith increases of chronicity and intensity of LBP had a higher risk of falls. At the same time, Abd El Ghany et al. (2018) conducted a study in Alexandria found that the highest percentages of the older adult had moderate risk of fall, about one-quarter had mild risk and almost quarter had severe risk of fall.Concerning relations between demographic characteristic of the studied older adults and risk of fall,the current study results indicated that severe risk of fall was highly associated with age. Furthermore, the age was a highly statistically significant positive independent predictor of the elderly risk of fall in multiple linear regressions. Such results might be due to that there is a decrease in muscle strength and elasticity with increasing age, a decrease in bone density, visual, balance and nervous system disorders. These changes make difficult for the elderly to perform activity of daily living (ADL), and increase risk of fall.Similarly, a study conducted in Brazil by Cruz &Leite (2018) explored that falls are frequent and are associated with increasing age. In agreement with this result, ‏‏Smith et al. (2017) in Brazil who revealed that there were statistically significance relations between risk of fall and age and also revealed that age was significance statistical positive predictors for risk of fall. The highest percentages of severe risk of fall were in the age group 60 to less than 70 years. This might be explained to that the base number in the study sample was greater in the age group from 60-<70 years.Controversy, ‏

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Alshammari et al. (2018) conducted a cross-sectional analytical study in Riyadh revealed that age was strongly associated with the risk of falls, and the prevalence of falls gradually increased with age until the age of 90 then it begins to decrease. This disparity in the result might be due to the base number in the sample is greater in the category from 80-89 years.In respect of the relation between gender and risk of fall, the results of present study showed that there was a high association between female sex and moderate and severe risk of fall.

Such results might be due to physiological characteristics and bone and muscle structure where female have less muscle mass compared to men over the life span, hormonal changes associated with menopause, sedentary lifestyle and low physical activity compare to male.

Similarly, ‏ Joseph et al. (2019) in India who conducted a study found that the risk of fall was higher among female older adults.Another study conducted by‏Chang & Do (2015) in Canada reported that risk of fall was significantly higher among female than in male.

Concerning the relation between residence and risk of fall, the results of the current study indicated that moderate and severe risk of fall was associated with living in rural areas. The explanation of such result is due to low socioeconomic status, low level of knowledge regarding ways of fall prevention and healthy lifestyle and limited health care services in these areas. These finding is consistent with a study conducted in China by Zhang et al.

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(2019) who found that the percentage of fallers is higher among rural than urban groups of older adult. Another study conducted by Huang et al. (2017) in Taiwan reported that the rural group of older people had a significantly higher frequency of fall-related hospitalizations.Regarding educational level, the results of present study showed that higher percentage of older adults with severe risk of fall were illiterate. This result might be due to that older adults with low educational level are less aware of their health status and less concerned about preventive measures and strategies given by the healthcare professional;

thus, they are at greater risk of falls. Likewise, a study conducted in United Arab Emirates by Sharif et al. (2018)demonstrated that illiterate older adults suffered more falls, and the risk of falls seems to decrease as the education level increase. This is consistent with a study conducted in Korea by Kim et al. (2020) who explicated that older age groups with higher risk of falling was identified as less educated.

The current study revealed that severe risk of fall was highly associated with the presence of chronic diseases. Moreover, chronic diseases were statistically significant independent predictor for risk of fall according to multiple linear regressions. The possible explanation of such result is that older adults often suffer from more than one health condition at the same time; and the number of chronic diseases increases with the age ‏(Paliwal et al., 2017), in addition such chronic diseases affect person’s physical abilities including walking and balance, making them more vulnerable to fall. In the same vein, ‏‏Zhou et al. (2019) carried out a study in China and found that the presence of medical condition increased the rate of falls. Similarly, Dhargave&Sendhilkumar (2016) in India conducted a study and found that chronic conditions were statistically significantly associated with risk of fall. The present study found that regular medication use was highly associated with severe risk of fall.

Further, regular medication use was a statistically significant independent predictor of risk of fall. The possible explanation for such result is that more than one-half of the studied older adults were took three or more medications per day related to chronic medical conditions; this may result severe drug interaction and multiple side effects which influence mobility, balance, proprioception, coordination, and causes confusion, dizziness, and daytime somnolence that can increase risk for falls. This result is in harmony with a study carried out in Brazil by ‏Nakagawa et al. (2017) who found that there was an association between the number of drugs taken and the risk of falling. Older adults who take three or more drugs/day are at higher risk of falls. The number of drugs taken daily has been identified as an independent risk factor for falls. In the same context, Callis (2016) carried out a study in USA and reported that medications use was significantly associated with increased risk of falls and older adults who were prescribed numerous medications (polypharmacy) had a statistically significance predictor of risk of fall. Similar results have been found by Seppala et al. (2018) who carried a study in the Netherlands and reported that polypharmacy was significantly positive associated with increased risk of falling in the meta-analyses. Likewise, a study conducted in England by ‏Dhalwani et al. (2017)reported that the rate of falls was higher in older adults with polypharmacy compared with older adults without polypharmacy.

Regarding relation between CLBP intensity and total risk of fall, the present study indicated that higher percentages of severe risk of fall had severe pain. Further, pain intensity was a highly statistically significant independent predictor for risk of fall according to multiple linear regression analysis. Moreover, there was a highly significant positive correlation between total pain intensity and total risk of fall. Such result might be due to older adults with CLBP often avoid physical activities to decrease pain feeling during movement that may result in muscle weakness and functional decline predisposing them for severe risk of fall. In the same line, a study in Alexandria, Egypt, carried out byAbd El Ghany et al. (2018) found a highly statistically significant relationship between total risk of fall and severity of CLBP;

where the risk of fall among the study subjects increased when severity of CLBP increased

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and also found significant positive correlation between total risk of fall and total pain intensity. This is in agreement with‏ The Longitudinal Study of Ageing conducted in England by Gale et al. (2016) who explicated that risk of falls was higher in older adults who had moderate or severe pain. This study also found that severe levels of pain were significant independently associated in multivariable analysis with an increased likelihood of having a history of falls in both women and men. Considering numbers of falls, the current study found that falling once was highly associated with severe risk of fall. Moreover, the numbers of fall were a highly statistically significant independent predictor for risk of fall according to multiple linear regressions. This result might be attributed to normal aging inevitably brings physical, cognitive and affective changes, including sensory, musculoskeletal, neurological, and metabolic changes, also reduced ability to respond rapidly and effectively compared to younger adults that may contribute to increase number of falls. Another plausible explanation, with advanced age, higher consumption of medications and related side effect and poor perception of the health status of the older adults, were factors that predisposed to the falls.In the same vein, a study in Japan conducted by Kato, et al. (2019) reported that history of falling in the previous 12 months have been reported to be significant risk factors for falling among older adults.Concerning relation between fearing of fall and risk of fall, the current study clarified that there was statistically significant association between fearing of fall and moderate and sever risk of fall. This result might be due to fear of fall may result in older adults trying to reduce their daily activities and become less active. Where muscle density decrease and bone become weaker when elderly become less active, which increases their risk of fall. In the same context, Dhargave&Sendhilkumar (2016) carried out a study in India, reported that fear of fall was statistically significantly associated with the risk of falling. Likewise, a study carried out in Netherlands by‏van Schooten et al. (2015) demonstrated that history of falls was significantly associated with the higher fear of falling.

The study findings revealed that physical inactivity was highly statistically significantly associated with risk of fall. Such results might be due to that physical activity in general is positively associated with physical performance and muscle strength. So, decrease or avoid physical activity results in muscle weakness and increase risk of falls. In accordance with this, a study conducted in Amsterdam by Yu Mei & El Fakiri (2015) informed that functional limitations (as defined by ADL limitations) were significantly associated with risk of fall.

Conclusion

High prevalence of severe risk of fall and many contributing factors were identified among older adults with chronic low back pain. Severe risk of fall was more prevalent in older adults aged 60 to less than 70 years, female gender, belonged to rural areas, married, illiterate, not working, insufficient income, and living with spouses. Also, having chronic diseases, using regular medications, CLBP intensity, number of falls, fearing of fall, and physical inactivity were significantly related with severe risk of fall. Further, age,marital status, chronic diseases,regular medication use,number of falls,and total pain intensitywere statistically significant independent predictors of older adult’s risk of fall.

Recommendation

Based on the results of this study, continuous fall risk assessment in older adults with CLBPwith special concern for contributing factors assessed in this study is recommended.

Fall risk assessment must be an essential part of the management of older adults with CLBP.

Developing and conducting educational programs for older adults with CLBP to decrease their risk of fall and pain.Further studies are needed to develop fall-prevention strategies/guidelines and evaluate its effect on decrease risk of fall.

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Declaration of Conflicting Interests

The Author(s) declare(s) that there is no conflict of interest.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sector.

Table1:Total and levels scores of fall risk among older adults with CLBP (n=135) Level of risk of fall N %

Mild risk of fall 13 9.

6 Moderate risk of fall 52 38

.5 Severe risk of fall 70 51 .9 Total score of risk of fall

(Mean± SD)

11.16±2.

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Table2: Demographiccharacteristics of older adults with CLBP and its relation to their risk of fall (n=135)

Items Total

Total risk of falling P-

Value Mild(n=13) Moderate

(n=52)

Severe(n=70)

N % N % N % N %

Age (year) 60-<70 85 63 13 100 24 46.1 48 68.6 .000**

70-<80 28 20.7 0 0.0 24 46.1 4 5.7

≥80 22 16.3 0 0.0 4 7.7 18 25.7

Gender Male 62 45.9 13 100 20 38.5 29 41.4 .000**

Female 73 54.1 0 0.0 32 61.5 41 58.6

Residence Rural 115 85.2 9 69.2 40 76.9 66 94.3 .007**

Urban 20 14.8 4 30.8 12 23.1 4 5.7 Marital

status

Single 4 3 0 .0 0 0.0 4 5.7

.000**

Married 102 75.5 13 100 36 69.2 53 75.7

Divorced 3 2.2 0 0.0 0 0.0 3 4.3

Widowed 26 19.3 0 0.0 16 30.8 10 14.3 Educational

Level

Illiterate 62 45.9 5 38.5 36 69.2 21 30

.000**

Read &write 25 18.5 0 0.0 8 15.4 17 24.3 Basic

education

24 17.8 4 30.8 8 15.4 12 17.1 Secondary 20 14.8 4 30.8 0 0.0 16 22.9 University /

Postgraduate

4 3 0 0.0 0 0.0 4 5.7

Current occupation

Not Working

121 89.6 9 69.2 0 0.0 5 7.1 .000**

Working 14 10.4 4 30.8 52 100 65 92.9 Monthly

income

Not Sufficient

85 63 8 61.5 36 69.2 41 58.6

.000**

Sufficient 45 33.3 0 0.0 16 30.8 29 41.4

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Sufficient &

saving

5 3.7 5 38.5 0 0.0 0 0.0

Living condition

Alone 9 6.7 0 0.0 2 3.9 7 10 .001**

Spouse 99 73.3 9 69.2 40 76.9 50 71.4

Sons 23 17 3 23.1 10 19.2 10 14.3

Relatives 4 3 1 7.7 0 0.0 3 4.3

*significant at p ‹ 0.05.**highly significant at p ‹ 0.01.

Table3:Relations between health history and risk of fall among older adults with CLBP (n=135)

Items Total

Total risk of falling P- Value Mild

(n=13)

Moderate (n=52)

Severe (n=70)

N % N % N % N %

Chronic diseases Yes 121 89.6 4 30.8 52 100 65 92.9 .000**

No 14 10.4 9 69.2 0 0.0 5 7.1

medication use Yes 98 72.6 2 15.4 48 92.3 48 68.6 .000**

No 37 27.4 11 84.6 4 7.7 22 31.4 CLBPintensityaccording

to Numeric Pain Rating Scale

Mild pain 18 13.3 13 100 0 0.0 5 7.1 Moderate

pain

28 20.7 0 0.0 12 23.1 16 22.9 Severe

pain

89 65.9 0 0.0 40 76.9 49 70 Numbers of fall Once 62 45.9 5 38.5 24 46.1 33 47.1

.000**

Twice 17 12.6 4 30.8 0 0.0 13 18.6 3times 24 17.8 4 30.8 12 23.1 8 11.4 4times 32 23.7 0 0.0 16 30.8 16 22.9 Fearing of fall Yes 126 93.3 9 69.2 52 100 65 92.9

.01*

No 9 6.7 4 30.8 0 0.0 5 7.1

Smoking Yes 33 24.4 4 30.8 12 23.1 17 24.3 .846

No 102 75.6 9 69.2 40 76.9 53 75.7 Caffeine consumption Yes 90 66.7 9 69.2 32 61.5 49 70 .605

No 45 33.3 4 30.8 20 38.5 21 30

Physical activity Yes 9 6.7 4 30.8 5 9.6 0 0.0 .000**

No 126 93.3 9 69.2 47 90.4 70 100

*significant at p ‹ 0.05.**highly significant at p ‹ 0.01

Table 4. Best Fitting Multiple Linear Regression Model for risk of fall Score Unstandardized

Coefficients

standardized Coefficients

T P. value

B Β

Age .248 .285 2.738 .007**

Marital status .185 .207 2.372 .03*

Chronic diseases .459 .310 4.128 .000**

Regular medication use -.051 -.096 -1.227 .02*

Numbers of fall .377 .465 3.552 .001**

Total pain intensity .251 .267 3.686 .000**

ANOVA

Model Df. F P. value

Regression 7 9.244 .000**

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*significant at p ‹ 0.05 **highly significant at p ‹ 0.01 References

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