Sage Journals: Discover world-class research

Abstract

Background

Life-space mobility is defined as the spatial area traversed by an individual in daily life, extending from bedroom to locations beyond the individual’s hometown, considering distance, frequency, and required assistance. The Life-Space Assessment (LSA) is used to evaluate life-space mobility. It has been reported that the LSA score after total hip arthroplasty (THA) shows an improvement relative to the preoperative score in patients with hip osteoarthritis. Symptoms and walking function also improve after THA. However, the association between these improvements and an increase in the LSA score after THA remains unclear. The purpose of this study was to identify the factors associated with an increase in the LSA score after THA in females with hip osteoarthritis.

Methods

This retrospective cohort study involved females planning to undergo primary and unilateral THA for hip osteoarthritis. The LSA score, subjective hip symptoms and function (assessed using the modified Harris hip score), and walking speed were assessed preoperatively and at 6 months postoperatively. Factors associated with the postoperative change in the LSA score were investigated using multiple regression analysis.

Results

A total of 120 participants were included. Improvement in walking speed (β = 0.19, P = 0.011) was significantly associated with the postoperative increase in the LSA score. The preoperative LSA score (β = −0.67, P < 0.001), age (β = −0.17, P = 0.011), and contralateral hip osteoarthritis (β = −0.15, P = 0.017) were also associated with the change in the LSA score.

Conclusions

The recovery of maximal walking speed, preoperative life-space mobility, age, and contralateral hip osteoarthritis influenced postoperative expansion of life-space mobility. Improved walking speed may serve as a key factor contributing to the expansion of life-space mobility following THA.

Keywords

life-space mobility osteoarthritis total hip arthroplasty walking speed retrospective cohort study

Introduction

Life-space mobility is defined as the spatial area an individual traverses in daily life, from the bedroom to locations beyond their hometown, considering distance, frequency, and required assistance.^1,2 This metric assesses an individual’s daily mobility access to various community amenities³ and reflects opportunities for participation in external life events. Smaller life-space mobility is associated with limited social interactions,⁴ whereas larger life-space mobility is linked to active social participation.⁵ Therefore, life-space mobility can be conceptualized as a global measure of mobility and social participation.¹

Recently, the Life-Space Assessment (LSA), a self-report questionnaire, has been widely used to assess life-space mobility. It measures the extent and frequency of movement, as well as any assistance required, over the past 4 weeks in the following five areas: outside the bedroom, outside the house, within the neighborhood, outside the neighborhood but within town, and beyond town.¹ The LSA was developed in the United States¹ and has been translated into several languages, including Japanese.⁶ Previous studies have shown its substantial test-retest reliability^1,7,8 and a minimal important change.^1,8-10 Moreover, a decline in the LSA score predicts future health outcomes, such as decreased activities of daily living,¹¹ falls,¹² and reduced quality of life.¹³ Therefore, maintaining and improving the LSA score is crucial for preventing adverse health outcomes and enhancing quality of life.

Osteoarthritis (OA) is a common degenerative disease that causes pain and reduces functional ability in middle-aged and older adults.¹⁴ Total hip arthroplasty (THA) is the standard surgical intervention in patients with end-stage hip OA.¹⁴ Although the LSA score has not been directly compared between patients with hip OA and healthy individuals of the same age, the preoperative LSA score in patients requiring THA was lower than that of community-dwelling adults.^15-17 This suggests that life-space mobility is more restricted in patients with hip OA requiring THA. Kurkis et al¹⁵ also reported an improvement in the LSA score 6 months post-THA in both male and female patients compared with their preoperative scores. This improvement indicates not only an expansion in the physical range of mobility and increased frequency but also a reduced reliance on canes or other assistance. Furthermore, these changes help patients overcome the limitations of hip disability, facilitating a return to active social participation, which is crucial for recovery after THA.

However, the mechanism associated with the increase in LSA score after THA remains unknown. THA can reduce pain and improve walking function, including its speed, and quality of life.^18-21 In particular, the symptoms usually improve within 3 weeks,²² and walking speed improves at approximately 6 weeks.²³ Therefore, symptom relief and improved walking speed may lead to an improvement in the LSA score; however, whether the improvement in symptoms and walking speed is associated with an increase in LSA score after THA remains unknown. Additionally, the LSA score is influenced by sex differences,^2,7,17,24 with lower scores observed in females compared with their male counterparts.¹⁷ Females have a longer life expectancy,²⁵ a higher incidence of hip OA,²⁶ and lifestyle differences related to instrumental activities of daily living, such as meal preparation, laundry, home maintenance, and medication management.²⁷ Therefore, limiting the study participants to females individuals to determine the factors associated with the postoperative LSA score and eliminate the influence of sex differences were necessary.

This study aimed to identify factors associated with LSA scores in female patients post-THA. Understanding associated factors is essential for enhancing mobility, as they can be prioritized during postoperative rehabilitation to optimize outcomes.

Methods

Study Design and Participants

This retrospective cohort study was conducted at a single center, and clinical trial registration was not applicable. The Research Ethics Committee of the Kitasato Institute Hospital approved the study protocol (permit number: 17022). This study adhered to the STROBE checklist and was conducted in accordance with the Declaration of Helsinki and the Japanese Ethical Guidelines for Medical and Health Research with Human Subjects. All patients were clearly verbally informed about this study and also clearly informed that their data could be used in the present study and were given the opportunity to refuse participation via the opt-out method on the hospital’s website.

Participants aged 45-84 years who were scheduled to undergo unilateral and primary THA using an anterolateral approach at an urban hospital in Minato-ku, Tokyo, Japan, between July 2017 and June 2023 were included in this study. This study aimed to investigate the recovery process in female patients undergoing standard THA; the exclusion criteria were: (a) male participants; (b) complications such as deep venous thrombosis requiring treatment, infection, dislocation, fractures, or peripheral nerve disorders occurring during or within 2 weeks after the operation; (c) inability to undergo preoperative walking speed measurements; and (d) severe medical, orthopedic, or psychological conditions that rendered the participants unable to complete questionnaires independently or that could affect their walking speed, including Parkinson’s disease, stroke, dementia, schizophrenia, or those undergoing chemotherapy or hemodialysis.

Postoperative Rehabilitation

Each participant underwent standard rehabilitation with one of four physical therapists. From the first postoperative day, full weight-bearing and ambulatory activities were encouraged. Therapists customized the rehabilitation program, adjusting walking distance, aids, and independence based on each patient’s physical function. The participants were discharged within 1-3 weeks and continued outpatient rehabilitation for 3 months to improve hip range of motion, muscle strength, and aerobic capacity.

Data Collection

Data were collected at the following two-time points: preoperatively (within a few days before surgery) and 6-month follow-up after THA.

Clinical Characteristics

Demographic data of patients, including age, body mass index (BMI), environmental factors such as the living alone status and use of stairs when leaving home; current employment status; and medical and surgical information, were collected from electronic medical records. The medical information evaluated included medication history, comorbidities, the severity grade of the operated hip based on Kellgren–Lawrence radiographic severity (K/L),²⁸ and the conditions of the contralateral hip. Evaluated comorbidities included hypertension and diabetes mellitus. The contralateral hip condition was classified as non-OA (including healthy, post-THA, and post-bipolar hip arthroplasty) or OA, which was defined as K/L grade ≥ 2.²⁹ Surgical information, including the volume of blood loss and duration of the operation, was recorded.

Life-Space Mobility

Life-space mobility was measured using the Japanese version of the LSA.⁶ The participants were asked about their life-space levels using the following questions: “During the past 4 weeks, have you been to (1) other rooms of your home besides the room where you sleep? (Level 1); (2) an area immediately outside your home, such as your porch, deck, patio, hallway of an apartment building, or garage? (Level 2); (3) places in your immediate neighborhood but beyond your own property or apartment building? (Level 3); (4) places outside your immediate neighborhood but within your town? (Level 4); and (5) places outside your immediate town? (Level 5)” For each life-space level, the participants were asked how frequently they traveled to that area and whether they needed assistance from another person or an assistive device. The LSA score was calculated by assigning a value to each of the five levels and summing the five scores. Level scores were obtained by multiplying the level number (1-5), degree of independence (2 = no assistance from persons or equipment, 1.5 = use of equipment alone, and 1 = assistance of personal assistance), and frequency of movement (1 = less than once a week, 2 = 1-3 times weekly, 3 = 4-6 times weekly, and 4 = daily). The LSA score ranged from 0 (mobility confined to one’s bed) to 120 (traveling out of town daily without personal assistance or assistive devices), with higher scores indicating higher life-space mobility. The participants requiring assistance with equipment at any location were categorized as walkers who required walking aids. Similarly, the participants requiring assistance from others at any location were categorized as walkers who required assistance. The number of walkers who required walking aids and those who required assistance from others was determined. The LSA questionnaire was independently completed by the participants without supervision from physical therapists to reduce the potential for social desirability or expectation biases. Any missing responses were identified and addressed by administrative staff who were uninvolved in the study, encouraging the participants to complete these missing items.

Patient-Reported Outcome Measures

Subjective hip symptoms and function were evaluated using the modified Harris hip score (mHHS),³⁰ which comprises eight questions on pain, daily activities, and gait. The scores range from 0 to 100, with higher scores indicating less pain and better functioning. A previous study showed substantial test-retest reliability of mHHS (intraclass correlation = 0.91).³¹ The mHHS questionnaire was independently completed by the participants without supervision from physical therapists.

Walking Function Assessment

Walking speeds were measured to assess walking function using a digital stopwatch, timing patients as they walked at a maximal pace, with any necessary assistive device, over the middle 10 m of a 16-m walkway.³² For the maximal-speed walking trials, participants were instructed to walk as fast as possible without running. The measurement precision was 0.01 s; each participant was measured two times. The highest recorded walking speed was used for analysis. A cane was used during the walking trials by participants who regularly used one in daily life.

Statistical Analysis

The normality of the variables was evaluated using the Shapiro–Wilk test. Non-normally distributed variables are presented as medians and interquartile ranges (IQR), whereas categorical variables are expressed as numbers and percentages. Differences were considered statistically significant for all tests at a 5% significance level. All statistical analyses were conducted using IBM SPSS Statistics for Windows, version 30.0 (IBM Corp., Armonk, N.Y., USA).

Many participants could not be included in the follow-up survey as they dropped out for various reasons. To assess whether a bias existed between the participants analyzed and those who dropped out, we performed statistical analyses to compare the demographics, clinical characteristics, and preoperative outcomes between the two groups. Non-normally distributed variables were compared using a two-trailed Mann–Whitney U test, while categorical variables were analyzed using the chi-squared test.

Outcomes measured preoperatively and 6 months postoperatively were compared using a two-trailed Wilcoxon rank-sum test for continuous variables and McNemar’s test for categorical dependent variables. Multiple regression analysis using the forced entry method was conducted to systematically explore the factors associated with the change in the LSA score. The dependent variable was the change in the LSA score from the preoperative assessment to the 6-month follow-up assessment. Given the close relationships between preoperative functional status and postoperative improvements, as well as their potential effects on the LSA score, we analyzed preoperative factors and changes in measured outcomes separately to avoid multicollinearity. Model 1 was developed to identify preoperative factors associated with postoperative changes in the LSA score included both the preoperative mHHS and maximal walking speed as independent variables. In contrast, Model 2 examined the relationship between changes in measured outcomes and changes in the LSA score. Specifically, this model included changes in mHHS and maximal walking speed as independent variables. This approach allowed us to investigate two distinct but complementary research questions while maintaining the statistical stability and interpretability of the models. All models were adjusted for age, BMI, status of contralateral hip OA, diabetes mellitus, living situation, use of stairs when going out, and preoperative LSA score, which were included as covariates. Independent variables and covariates were selected based on their potential association with the postoperative LSA score, as identified in previous studies.^17,22,23,33 The variance inflation factor (VIF) was assessed to determine whether there were multicollinearities among independent factors in the multivariate regression model. Additionally, the inverse probability weighting (IPW) method³⁴ was applied to analyze the possibility of attrition bias in the multiple regression analysis results. The propensity score for the IPW method was calculated using logistic regression analysis, with “analyzed” or “dropped out” as the dependent variable. All investigated variables, including demographics, clinical characteristics, and preoperative outcomes, were considered independent variables.

Results

A total of 189 patients who underwent THA were enrolled in the study, and 69 of these patients dropped out for various reasons (Figure 1). A comparison of the evaluated participants with those who dropped out revealed no significant differences in any investigated variables (Supplemental Table 1).

Figure 1.

Study Flowchart

A total of 120 participants were included in the study (Figure 1). The mean age and BMI were 66.3 ± 8.8 years and 23.9 ± 3.7 kg/m², respectively. Table 1 presents the characteristics of the participants. As summarized in Table 2, all measured outcomes at 6 months after THA were significantly higher than their preoperative values; the proportion of participants requiring walking aids and assistance from others was significantly lower at 6 months postoperatively than that before surgery.

Table 1.

Demographic and Clinical Characteristics

Parameter	ParticipantsN = 120
Age (years), median (IQR)	66.0 (59.3-73.0)
BMI (kg/cm²), median (IQR)	23.5 (21.3-26.3)
Grade of the hip OA on affected side (II/III/IV), n	0/36/84
Status of contralateral hip OA (non-OA; healthy or post-THA or post-BHA/OA), n	82/48
Comorbidities, n (%)
- Hypertension	43 (37.5)
- Diabetes mellitus	10 (8.3)
Surgical information
- Surgical duration (min), median (IQR)	83.5 (67.0-102.8)
- Volume of blood lost (mL), median (IQR)	216.0 (160.0-300.0)
Living situation, alone, n (%)	27 (22.5)
Use of stairs when leaving home, n (%)	14 (11.7)
Current employment status, n (%)	55 (45.8)

SD, standard deviation; BMI, Body Mass Index; OA, Osteoarthritis; THA, Total Hip Arthroplasty; BHA, Bipolar Hip Arthroplasty.

Table 2.

Comparison Between Preoperative and Postoperative Outcomes

Parameter	Participants N = 120
Parameter	Before surgery	6 months after surgery	P-value^a
LSA score (points), median (IQR)	80.5 (60.0-102.0)	92.0 (76.9-110.0)	<.001
Requiring walking aids, n (%)	42 (35.0)	24 (20.0)	0.006
Requiring assistance, n (%)	22 (18.3)	10 (8.3)	0.031
mHHS (points), median (IQR)	58.3 (47.6-73.7)	95.2 (88.3-100.0)	<.001
Maximal walking speed (m/s), median (IQR)	1.5 (1.2-1.6)	1.7 (1.5-1.9)	<.001

The P-values in bold indicate a statistically significant difference between the groups (P <.05).

LSA, life-space assessment; IQR, interquartile range; mHHS, modified harris hip score.

^aPre- and postoperative values were compared using a two-trailed Wilcoxon rank-sum test and McNemar’s test.

Multiple regression analysis revealed that the preoperative mHHS and walking speed were not significantly associated with the change in the LSA score in Model 1 (Table 3). As shown in Model 2, which included both changes in mHHS and in the maximal walking speed, the change in the maximal walking speed (β = 0.19, P = 0.011) remained independently associated with the change in the LSA score, with an adjusted R² of 0.53. Across all models, age, preoperative LSA score, and contralateral hip OA were significantly associated with the change in the LSA score. In addition, multiple regression analysis adjusted with the IPW method showed results almost identical to those obtained without adjustment using the IPW method (Table 3). There were no multicollinearities among the independent factors, as all VIFs were less than 2.0.

Table 3.

Factors Associated With the Change in the LSA Score After THA

	Multiple regression analysis N = 120						Multiple regression analysis with IPW method adjustments N = 189
	Model 1			Model 2			Model 1			Model 2
	Adjusted R² = 0.47			Adjusted R² = 0.53			Adjusted R² = 0.48			Adjusted R² = 0.54
	(P <.001)			(P <.001)			(P <.001)			(P <.001)
Variable	Standardized coefficient β	P value	VIF	Standardized coefficient β	P value	VIF	Standardized coefficient β	P value	VIF	Standardized coefficient β	P value	VIF
Age (years)	−0.21	0.005	1.26	−0.17	0.011	1.20	−0.21	0.004	1.25	−0.18	0.009	1.19
BMI (kg/m²)	−0.04	0.579	1.28	−0.03	0.640	1.20	−0.02	0.801	1.24	−0.01	0.853	1.18
Status of contralateral hip OA (non-OA = ref, OA = 1)	−0.13	0.048	1.08	−0.15	0.017	1.09	−0.15	0.024	1.09	−0.18	0.006	1.10
Diabetes mellitus (absence = ref, presence = 1)	−0.06	0.375	1.15	−0.08	0.233	1.15	−0.11	0.119	1.16	−0.12	0.070	1.16
Living situation (with someone = ref, alone = 1)	0.05	0.504	1.10	0.02	0.816	1.12	0.08	0.222	1.10	0.05	0.451	1.12
Use of stairs when going out (no = ref, use = 1)	−0.02	0.740	1.05	−0.03	0.639	1.05	−0.03	0.654	1.05	−0.04	0.490	1.06
Preoperative LSA score (points)	−0.71	<.001	1.45	−0.67	<.001	1.33	−0.71	<.001	1.50	−0.66	<.001	1.38
Preoperative mHHS (points)	−0.04	0.594	1.60				−0.05	0.532	1.66
Change in mHHS (points)				0.09	0.206	1.40				0.11	0.136	1.48
Preoperative maximal walking speed (m/s)	−0.05	0.578	1.81				−0.05	0.599	1.84
Change in maximal waking speed (m/s)				0.19	0.011	1.44				0.18	0.017	1.52

The P-values in bold indicate a statistically significant difference between the groups (P <.05).

The change in the LSA score following THA was set as the dependent variable. Multiple regression analysis with and without the adjusted IPW method was performed using the forced entry method.

LSA, life-space assessment; THA, total hip arthroplasty; IPW, inverse probability weighting; VIF; Variance inflation factor, BMI, body mass index; OA, osteoarthritis; Ref, reference; mHHS, modified Harris Hip Score.

Discussion

In this study, we identified factors associated with the postoperative increase in the LSA score after THA. Our findings revealed that improvements in walking speed, the preoperative LSA score, age, and contralateral hip OA were associated with the postoperative increase in the LSA score. We propose that improved walking speed serves as a key factor for enhancing the LSA score in individuals with end-stage hip OA who elect to undergo THA.

Even after adjustment for improvements in subjective hip symptoms and function and other covariates, recovery of the maximal walking speed was found to influence the change in the postoperative LSA score. However, the preoperative maximal walking speed was not associated with the change in the LSA score following THA. Maximal walking speed has been widely used to assess walking function in patients after THA, with speed at 6 months postoperatively typically being faster than preoperative speed.²³ Moreover, the preoperative maximal walking speed has been reported to be associated with the recovery of walking function 5 days after THA.³² Thus, it is possible that the improvement in walking speed after THA is more closely linked to an increase in the LSA score than to the preoperative walking speed. On the other hand, although subjective hip symptoms and function were predicted to be associated with changes in the LSA score, the degree of improvement in the mHHS score was not associated with the increase in the LSA score. One possible reason could be that the distribution of mHHS scores was concentrated, with a median of 95.2 (IQR: 88.3-100) at 6 months. Given that scores of 81 or higher are classified as excellent,³⁵ most participants achieved good subjective hip function. Additionally, the ceiling effect likely contributed to the clustering of scores. Age and contralateral hip OA were also associated with the postoperative change in the LSA score. These irreversible factors should be recognized by clinical staff as potential barriers to the increase in LSA score after THA. In contrast, walking speed is a modifiable factor, clinical interventions aimed at improving walking speed could help mitigate the negative impact of age and contralateral OA on postoperative functional outcomes. Therefore, walking speed may serve as a key element in enhancing life-space mobility following THA. We suggest that clinicians and physiotherapists need to focus on not only the primary goal of THA, which is an improvement in hip symptoms and function, but also improvement in walking speed.

Although both maximal walking speed and LSA score can be used to assess walking activity, they capture different contexts; walking capacity is what a person can do in a standardized, controlled environment, whereas walking performance describes what a person actually does in their daily environment.³⁶ Maximal walking speed measures walking capacity, whereas the LSA score assesses walking performance. The key finding of this study is that improved walking capacity altered the range and frequency of walking performance, thereby changing patients’ lifestyles after THA. Symptom relief and enhanced walking function are standard goals after THA; traditional outcomes showed improvements in subjective hip scores²² and walking speed.²³ However, before this study, both whether these changes were truly meaningful for patients who underwent THA and whether they led to greater engagement in life activities were unclear. Our results demonstrated that enhanced walking speed led to an expansion of life-space mobility, suggesting that these improvements could bring about meaningful lifestyle changes after THA.

The preoperative LSA score was also associated with the postoperative change in the LSA score; individuals with lower preoperative scores exhibited greater changes, while those with higher preoperative scores demonstrated smaller changes. This suggests the presence of a ceiling effect, which might have contributed to the observed negative association. Among the selected independent variables and covariates, the preoperative LSA score was the most influential factor for the change in the postoperative LSA score. This result indicates that even if symptom relief and enhanced walking speed are achieved after THA, preoperative life-space mobility continues to have an impact even 6 months postoperatively. This finding highlights the importance of preoperative assessment of life-space mobility in addition to the assessment of symptoms, imaging findings including severity on X-rays, and walking speed, which are commonly evaluated preoperatively in clinical practice. Life-space mobility varies according to factors such as race³⁷; social environment, including income sufficiency^7,37 and educational attainment⁷; and physical environment, such as barriers in the environment,³⁸ urban and rural settings,^7,39 modes of transportation,⁴⁰ and transportation difficulty.³⁹ Preoperative differences in life-space mobility may result from lifestyle differences due to race, region, or social environment, and they may also reflect challenges in the physical environment. Individuals with restricted preoperative life-space mobility may not experience sufficient improvement in their LSA score even if symptom relief and enhanced walking speed are achieved after THA; this indicates the need for interventions tailored to address the underlying causes for these restrictions.

The participants in the analyzed group represent a highly selective population, as their mean age was 66 years, most of whom were not living alone, and the prevalence of comorbidities was low. In addition, although there was no significant difference in demographic or measured outcomes between analyzed and dropout participants, a substantial number of participants dropped out of the study. However, the results of the multiple regression analysis adjusted using the IPW method suggest that the effect of attrition bias on key outcomes, such as the improvement in mHHS and recovery of maximal walking speed, is likely to be minimal.

This study provides valuable information to clinicians and physiotherapists regarding the factors associated with postoperative LSA scores. However, it has a few limitations. First, the follow-up period was relatively short to capture changes in mobility. A longer observation period could introduce factors such as complications or new health conditions. By limiting the focus to 6 months, this study specifically examined the effects of THA and postoperative rehabilitation, which is one of its strengths. Second, reliance on self-reported questionnaires for the LSA score might have led to overestimation or underestimation, as objective tools such as activity logs, pedometers, or accelerometers, which could provide more accurate data, were not used. Furthermore, whether life-space mobility did not expand because the individual wanted to but was unable or simply because expanding it was unnecessary remains unclear. Nevertheless, a key strength of this study is the use of the LSA score, which can assess what a person actually does in their daily environment. Third, many participants dropped out of the study. Among the 20 individuals (29.0%) who dropped out due to treatment at another hospital, factors such as advanced age, residential area, and transportation access may have played a role, suggesting that these dropouts might not be missing at random. However, regarding the remaining 49 individuals, the dropout reason is considered to have occurred randomly. Furthermore, the demographics, clinical characteristics, and preoperative outcomes of the 69 patients who dropped out showed no significant differences compared to those of the analyzed patients, suggesting that the dropouts likely occurred at random. To address this issue, we performed multiple regression analysis adjusted using the IPW method to estimate the potential impact of the missing data, and this ruled out attrition bias. However, the impact of dropouts on the study’s results remains a concern, because this method cannot fully address unmeasured confounders or latent differences between the groups. Finally, the participants in this study were limited to standard THA cases, and most were urban dwellers. The patients with complications, pre-existing conditions, or those living in rural areas who may face challenges such as limited transportation access and different environmental factors, may experience different recovery trajectories. Therefore, selection bias may have been introduced, and the results may not be generalizable to all female patients undergoing THA. In addition, the adjusted R² of 0.53 in Model 2 implies that nearly half of the variance in postoperative LSA change remains unexplained. Although this study considered environmental factors such as living alone and use of stairs when leaving home, other relevant factors — such as income,^7,37 education level,⁷ or transportation access,^39,40 and psychological variables including fear of falling⁴¹ and depression⁴² — were not assessed. Moreover, a variable identified in previous studies, such as living situation,³³ was not found to be significantly associated with the change in LSA score in the present study. This may be partly attributed to the limited sample size, as a power analysis was not performed. To enhance generalizability and identify broader determinants of life-space mobility, future studies should include larger sample sizes, multiple sites in both urban and rural areas, and a wider range of social, environmental, and psychological factors.

Conclusions

A greater change in the maximum walking speed was associated with greater changes in life-space mobility after THA. Preoperative life-space mobility, age and contralateral hip osteoarthritis were also influencing factors for the postoperative change in life-space mobility. We propose that improved walking speed is a key factor that can lead to significant improvements in the LSA score in individuals with end-stage hip OA who elect to undergo THA.

Supplemental Material

Supplemental Material - Factors Associated With Life-Space Mobility After Total Hip Arthroplasty in Females With Osteoarthritis: A Single-Center Retrospective Cohort Study

Supplemental Material for Factors Associated With Life-Space Mobility After Total Hip Arthroplasty in Females With Osteoarthritis: A Single-Center Retrospective Cohort Study by Ryota Kuratsubo, Hiroyuki Watanabe, Masashi Nagao, Naoto Kamide, Kazuki Kaji1, Naruaki Toda1, Kosuke Mizuno, and Hironori Kaneko, Yuji Takazawa in Geriatric Orthopaedic Surgery & Rehabilitation.

Footnotes

Acknowledgments

The authors thank the staff of the Department of Orthopedics and Rehabilitation for their support, participants of this study, and Editage () for English language editing.

ORCID iD

Ryota Kuratsubo

Ethical Considerations

This retrospective cohort study was conducted at a single center, and clinical trial registration was not applicable. The Research Ethics Committee of Kitasato Institute Hospital approved the study protocol (permit number: 17022). This study adhered to the STROBE checklist and was conducted in accordance with the Declaration of Helsinki and the Japanese Ethical Guidelines for Medical and Health Research with Human Subjects.

Consent to Participate

All patients were clearly verbally informed about this study and also clearly informed that their data could be used in the present study and were given the opportunity to refuse participation via the opt-out method on the hospital’s website.

Authors Contributions

R.K. contributed to the conceptualization, methodology, design, formal analysis, investigation, data curation, manuscript draft, and project administration. H.W. supervised the study. M.N. contributed to the methodology, design, formal analysis, and investigation. N.K. contributed to the conceptualization, methodology, design, and formal analysis. K.K. and N.T. provided resources and contributed to data curation. K.M. contributed to the conceptualization. H.K. provided resources and contributed to data curation and project administration. Y.T. contributed to investigation, supervision, and project administration. All authors read and approved the final manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data supporting the findings of this study are available from the corresponding author, RK, on reasonable request.*

Supplemental Material

Supplemental material for this article is available online.

References

Baker

Bodner

Allman

. Measuring life-space mobility in community-dwelling older adults. J Am Geriatr Soc. 2003;51(11):1610-1614. doi:10.1046/j.1532-5415.2003.51512.x

Peel

Sawyer Baker

Roth

Brown

Brodner

Allman

. Assessing mobility in older adults: the UAB study of aging Life-Space Assessment. Phys Ther. 2005;85(10):1008-1119.

Sawyer

Allman

. Resilience in mobility in the context of chronic disease and aging: cross-sectional and prospective findings from the University of Alabama at Birmingham (UAB) study of aging. In: Keyes

CLM

Fry

, eds. New Frontiers in Resilient Aging: Life-Strengths and Well-Being in Late Life. Cambridge University Press; 2010:310-339.

Murata

Kondo

Tamakoshi

Yatsuya

Toyoshima

. Factors associated with life space among community-living rural elders in Japan. Public Health Nurs. 2006;23(4):324-331.

Barnes

Wilson

Bienias

, et al. Correlates of life space in a volunteer cohort of older adults. Exp Aging Res. 2007;33:77-93. doi:10.1111/j.1525-1446.2006.00568.x

Shimada

Sawyer

Harada

, et al. Predictive validity of the classification schema for functional mobility tests in instrumental activities of daily living decline among older adults. Arch Phys Med Rehabil. 2010;91(2):241-246. doi:10.1016/j.apmr.2009.10.027

Curcio

Alvarado

Gomez

Guerra

Guralnik

Zunzunegui

. Life-Space Assessment scale to assess mobility: validation in Latin American older women and men. Aging Clin Exp Res. 2013;25(5):553-560. doi:10.1007/s40520-013-0121-y

Kammerlind

Fristedt

Ernsth Bravell

Fransson

. Test-retest reliability of the Swedish version of the Life-Space Assessment Questionnaire among community-dwelling older adults. Clin Rehabil. 2014;28(8):817-823. doi:10.1177/0269215514522134

Portegijs

Iwarsson

Rantakokko

Viljanen

Rantanen

. Life-space mobility assessment in older people in Finland; measurement properties in winter and spring. BMC Res Notes. 2014;7:323. doi:10.1186/1756-0500-7-323

10.

Kennedy

Almutairi

Williams

Sawyer

Allman

Brown

. Determination of the minimal important change in the life-space assessment. J Am Geriatr Soc. 2019;67(3):565-569. doi:10.1111/jgs.15707

11.

Bentley

Brown

McGwin

Jr Sawyer

Allman

Roth

. Functional status, life-space mobility, and quality of life: a longitudinal mediation analysis. Qual Life Res. 2013;22(7):1621-1632. doi:10.1007/s11136-012-0315-3

12.

Brown

Sawyer

Kennedy

Allman

. Life-space mobility declines associated with incident falls and fractures. J Am Geriatr Soc. 2014;62(5):919-923. doi:10.1111/jgs.12787

13.

Rantakokko

Portegijs

Viljanen

Iwarsson

Kauppinen

Rantanen

. Changes in life-space mobility and quality of life among community-dwelling older people: a 2-year follow-up study. Qual Life Res. 2016;25(5):1189-1197. doi:10.1007/s11136-015-1137-x

14.

Katz

Arant

Loeser

. Diagnosis and treatment of hip and knee osteoarthritis. JAMA. 2021;325(6):568-578. doi:10.1001/jama.2020.22171

15.

Kurkis

Erwood

Maidman

, et al. Mobility limitation after surgery for degenerative pathology of the ankle, hindfoot, and midfoot vs total hip arthroplasty. Foot Ankle Int. 2020;41(5):501-507. doi:10.1177/1071100720907034

16.

Wadley

Brown

, et al. Life-space mobility: normative values from a national cohort of U.S. older adults. J Gerontol A Biol Sci Med Sci. 2023;79(2):glad176. doi:10.1093/gerona/glad176

17.

Malouka

Mayhew

, et al. Sex-stratified reference values for the life-space assessment in the Canadian longitudinal study on aging. Aging Clin Exp Res. 2023;35(5):1073-1080. doi:10.1007/s40520-023-02382-2

18.

Neuprez

Kaux

, et al. Total joint replacement improves pain, functional quality of life, and health utilities in patients with late-stage knee and hip osteoarthritis for up to 5 years. Clin Rheumatol. 2020;39(3):861-871. doi:10.1007/s10067-019-04811-y

19.

Judd

Dennis

Thomas

Wolfe

Dayton

Stevens-Lapsley

. Muscle strength and functional recovery during the first year after THA. Clin Orthop Relat Res. 2014;472(2):654-664. doi:10.1007/s11999-013-3136-y

20.

Vissers

Bussmann

Verhaar

Arends

Furlan

Reijman

. Recovery of physical functioning after total hip arthroplasty: systematic review and meta-analysis of the literature. Phys Ther. 2011;91(5):615-629. doi:10.2522/ptj.20100201

21.

Jeldi

Deakin

Allen

Granat

Grant

Stansfield

. Total hip arthroplasty improves pain and function but not physical activity. J Arthroplast. 2017;32(7):2191-2198. doi:10.1016/j.arth.2017.02.002

22.

Harold

Butler

Delagrammaticas

Sullivan

Stover

Manning

. Patient-reported outcomes measurement information system correlates with modified Harris hip score in total hip arthroplasty. Orthopedics. 2021;44(1):e19-e25. doi:10.3928/01477447-20201202-02

23.

Bahl

Nelson

Taylor

Solomon

Arnold

Thewlis

. Biomechanical changes and recovery of gait function after total hip arthroplasty for osteoarthritis: a systematic review and meta-analysis. Osteoarthr Cartil. 2018;26(7):847-863. doi:10.1016/j.joca.2018.02.897

24.

Dunlap

Rosso

Zhu

Klatt

Brach

. The association of mobility determinants and life space among older adults. J Gerontol A Biol Sci Med Sci. 2021;77(11):2320-2328. doi:10.1093/gerona/glab268

25.

World Health Organization . World Health Statistics 2024: Monitoring Health for the SDGs, Sustainable Development Goals. World Health Organization; 2024. https://www.who.int/publications/i/item/9789240094703. Accessed 12 October 2024.

26.

Iidaka

Muraki

Oka

, et al. Incidence rate and risk factors for radiographic hip osteoarthritis in Japanese men and women: a 10-year follow-up of the ROAD study. Osteoarthr Cartil. 2020;28(2):182-188. doi:10.1016/j.joca.2019.09.006

27.

Yamada

Teranishi

Suzuki

, et al. Lifestyles of local residents: development of standard values for the Frenchay Activities Index for local residents aged 10–79 years. Fujita Med J. 2018;4(1):23-28. doi:10.20407/fmj.4.1_23

28.

Kellgren

Lawrence

. Radiological assessment of osteo-arthrosis. Ann Rheum Dis. 1957;16(4):494-502. doi:10.1136/ard.16.4.494

29.

Iidaka

Muraki

Akune

, et al. Prevalence of radiographic hip osteoarthritis and its association with hip pain in Japanese men and women: the ROAD study. Osteoarthr Cartil. 2016;24(1):117-123. doi:10.1016/j.joca.2015.07.017

30.

Byrd

Jones

. Prospective analysis of hip arthroscopy with 2-year follow-up. Arthroscopy. 2000;16(6):578-587. doi:10.1053/jars.2000.7683

31.

Kumar

Sen

Aggarwal

Rajnish

. Reliability of modified Harris hip score as a tool for outcome evaluation of total hip replacements in Indian population. J Clin Orthop Trauma. 2019;10(1):128-130. doi:10.1016/j.jcot.2017.11.019

32.

Shibuya

Nanri

Kamiya

, et al. The maximal gait speed is a simple and useful prognostic indicator for functional recovery after total hip arthroplasty. BMC Muscoskelet Disord. 2020;21(1):84. doi:10.1186/s12891-020-3093-z

33.

Mümken

Gellert

Stollwerck

O'Sullivan

Kiselev

. Validation of the German Life-Space Assessment (LSA-D): cross-sectional validation study in urban and rural community-dwelling older adults. BMJ Open. 2021;11(7):e049926. doi:10.1136/bmjopen-2021-049926

34.

Seaman

White

. Review of inverse probability weighting for dealing with missing data. Stat Methods Med Res. 2013;22(3):278-295. doi:10.1177/0962280210395740

35.

Aprato

Jayasekera

Villar

. Does the modified Harris hip score reflect patient satisfaction after hip arthroscopy? Am J Sports Med. 2012;40(11):2557-2560. doi:10.1177/0363546512460650

36.

Holsbeeke

Ketelaar

Schoemaker

Gorter

. Capacity, capability, and performance: different constructs or three of a kind? Arch Phys Med Rehabil. 2009;90(5):849-855. doi:10.1016/j.apmr.2008.11.015

37.

Allman

Sawyer

Roseman

. The UAB Study of aging: background and insights into life-space mobility among older Americans in rural and urban settings. Aging Health. 2006;2(3):417-429. doi:10.2217/1745509X.2.3.417

38.

Rantakokko

Iwarsson

Portegijs

Viljanen

Rantanen

. Associations between environmental characteristics and life-space mobility in community-dwelling older people. J Aging Health. 2015;27(4):606-621. doi:10.1177/0898264314555328

39.

Ahmed

Curcio

Auais

, et al. Falls and life-space mobility: longitudinal analysis from the international mobility in aging study. Aging Clin Exp Res. 2021;33(2):303-310. doi:10.1007/s40520-020-01540-0

40.

Viljanen

Mikkola

Rantakokko

Portegijs

Rantanen

. The association between transportation and life-space mobility in community-dwelling older people with or without walking difficulties. J Aging Health. 2016;28(6):1038-1054. doi:10.1177/0898264315618919

41.

Auais

Alvarado

Guerra

, et al. Fear of falling and its association with life-space mobility of older adults: a cross-sectional analysis using data from five international sites. Age Ageing. 2017;46(3):459-465. doi:10.1093/ageing/afw210

42.

Miyashita

Tadaka

Arimoto

. Cross-sectional study of individual and environmental factors associated with life-space mobility among community-dwelling independent older people. Environ Health Prev Med. 2021;26(1):9. doi:10.1186/s12199-020-00923-0

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.08 MB