|Year : 2018 | Volume
| Issue : 3 | Page : 154-158
Evaluation of gait speed over time in adults with arthritis: Data from the osteoarthritis initiative
Vishal Vennu1, Harsh Misra2
1 Research Scholar, Department of Pharmacy, School of Pharmacy, Lingay's University, Faridabad, India; Department of Rehabilitation Sciences, King Saudi University, Riyadh, Saudi Arabia, Saudi Arabia
2 Department of Pharmacology, Rama Medical College Hospital and Research Centre, Kanpur, Uttar Pradesh, India
|Date of Web Publication||21-Aug-2018|
Mr. Vishal Vennu
Deaprtment of Rehabilitation Sciences, College of Applied Medical Sciences, King Saud University, P.O. Box 10219, Riyadh-11433
Source of Support: None, Conflict of Interest: None
Objective: In this longitudinal study across four clinical sites in the United States, gait speed (GS) over time in adults with arthritis was examined.
Methods: We performed a secondary analysis using data from the osteoarthritis initiative. A sample of 4450 adults aged 45 years and older, regardless of sex or ethnicity, were included in the analysis. Based on the response to self-reported questionnaires about arthritis, adults were classified into two groups: without arthritis and with arthritis. GS in m/s was assessed using the 20-m-walk test at baseline and over time. A general linear mixed model was used to examine the GS over time in adults with arthritis.
Results: The rate of decrease in GS per year was 0.006 m/s after adjusting for age, sex, race, depressive symptoms, and body mass index. In adults, having arthritis was significantly associated with lower GS (β = −0.039, standard error = 0.007, P <.001) compared to those without arthritis. The interaction between arthritis, GS, and time was also significant (β = −0.0013, SE = 0.005, P = 0.017), indicating that the slope changed over time due to the continuous decline in GS (0.006 m/s/year).
Conclusions: In adults, having arthritis is associated with lower GS and declined over time compared to those without arthritis, even after controlling for all covariates.
Keywords: Adults, African American, arthritis, body mass index, depression
|How to cite this article:|
Vennu V, Misra H. Evaluation of gait speed over time in adults with arthritis: Data from the osteoarthritis initiative. Indian J Rheumatol 2018;13:154-8
| Introduction|| |
Arthritis is a type of chronic condition among others, which includes over 100 disorders that primarily affect the joints in all ages, sexes, and races worldwide. The most commonly affected joints include knees, hips, and hands, with typical symptoms of pain and stiffness. Other joint symptoms may also include redness, warmth, swelling, and decreased range of motion. These symptoms often limit functional capacity and the ability to perform activities of daily living, which significantly associated with a lower health-related quality of life., However, the association between arthritis and gait speed (GS) in adults has not been studied.
GS is a sixth vital sign and core indicator of health and function in aging and disease. It is used to establish thresholds in community-based activities, such as crossing a street or ambulating. However, the decline in GS is a universal occurrence with aging in both men and women. A growing body of literature indicates that slow GS is a significant independent risk factor for disability, institutionalization, falls, hospitalization, mortality, and higher annual health-care costs., Previous studies also showed that slow GS had been linked to other chronic diseases, such as cardiovascular events and diabetes mellitus., Given the substantial impact of slow GS, evaluation of the association between arthritis and GS is clinically meaningful.
Several studies investigated the relationship between rheumatoid arthritis, osteoarthritis, and GS., Some large population-based studies examined the association between chronic conditions such as arthritis, disability, and physical function., We aimed to examine the GS over time in adults with arthritis. We hypothesized that arthritis would be associated with slow GS with a decline over time.
| Methods|| |
We performed a secondary analysis using data from the osteoarthritis initiative (OAI), a multicenter, longitudinal, observational study with public and private funding that examined the onset and progression of knee OA. The OAI study enrolled men and women between February 2004 and May 2006 from four clinical sites in the USA (Baltimore, MD; Pittsburgh, PA; Pawtucket, RI; and Columbus, OH).
The sample for the present study was drawn from the following specific dataset versions of the OAI database: 0.2.2, 1.2.1, 3.2.1, 5.2.1, 6.2.1, and 8.2.1. A sample of 4450 adults aged 45 years and older, regardless of sex or ethnicity, were included in this longitudinal study. We excluded participants (n = 122) in the control group, defined as having no pain, aching, or stuffiness in either knee in the prior year, those with no radiographic finding of OA, and those with no eligibility risk factors. Questionnaires with responses of “do not know,” “not sure,” or “refuse to answer” were defined as missing data (n = 224) [Figure 1].
Adults were classified as having arthritis if they responded “yes” to the following question: “Were you told by a doctor in the last 12 months that you have arthritis,” during a 4-year follow-up period. Similar questions have been used in other national surveys, with adequate sensitivity and specificity.
GS was assessed using the 20-m-walk test at baseline and over time. The 20-m-walk pace was calculated as an average over two trials during each clinic visit. If one value was missing, the other value was used. Most epidemiological studies have used the 20-m-walk test as a standard outcome measure for arthritis. The participants walked a comfortable, self-directed pace in a corridor between two cones spaced 20-m apart, and then returned to sit in a chair at the starting point. The time to complete the first 20-m walk was recorded in m/s. GS in m/s was calculated as the distance completed divided by the time, as in other epidemiological studies.
The following potential demographic variables were included in analyses: age (years), sex (female/male), and race (white/African American, Asian, or other nonwhite). Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale, with scores ranging from 0 to 60. Scores of 16 or higher indicated severe depression, consistent with other reports. Body mass index (BMI) was computed as weight in kilograms divided by height in meters squared.
Patient characteristics and outcomes were examined using univariate descriptive statistics. The association between two groups (no arthritis versus arthritis) was analyzed using a Chi-square test for categorical variables of sex, race, depressive symptoms, and BMI, and a two-sample independent t-test was used for continuous variables of age and GS. A general linear mixed model using the MIXED procedure in statistical analysis software (SAS) was used to examine the longitudinal relationship between arthritis and GS. This association was determined using an unstructured covariance matrix. A mixed model enabled inferences regarding follow-up by modeling and estimating the components. Furthermore, this approach made better use of incomplete data, such as data for participants who dropped out or missed scheduled follow-up visits.
Two mixed models were constructed to test the relationship between arthritis and GS over time. Model 1 included time, groups (arthritis versus no arthritis), age, sex, and race, whereas in Model 2 included model 1 plus depressive symptoms and BMI. Both models used an interaction term between groups and time. All data processing and analysis were performed with SAS version 9.3 (SAS Institute Inc., NC, US).
This study received ethical approval from the Committee on Human Research and the Institutional Review Board, University of California, San Francisco, and its affiliates (approval number: FWA00000068). Before enrollment, all participants gave written informed consent.
| Results|| |
Of 4796 adults, 4450 with an average age at baseline of 62.4 years (standard deviation [SD = 9.0]) were analyzed. Most were females (58%), white or Caucasian, (80%), and had an average GS of 1.31 m/s (SD = 0.21). Of 4450 adults, 19% (n = 840) had significant arthritis. The mean age of patients with arthritis was significantly lower (62 years [SD = 9.2]) and these patients had a slower GS (1.27 m/s) than adults without arthritis (age: 62.8, SD = 8.8; GS: 1.35 m/s). Most adults with arthritis were female (64%), African American, Asian, or other nonwhites (83%) [Table 1].
|Table 1: Characteristics of the participants with and without arthritisa|
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[Table 2] presents the general linear mixed models of the association between arthritis and GS over time. The rate of decrease in GS (m/s) per year was 0.0021 in Model 1 and 0.006 in Model 2. In both models, patients with arthritis were significantly associated with lower GS compared to those without arthritis. The interaction between arthritis, GS, and time was also significantly associated with all models, indicating that slope changed over time. This indicates that every year, the average GS among adults with arthritis slowed and declined by 0.006 m/s compared to that in adults without arthritis, even after adjustment for age, sex, race, depressive symptoms, and BMI. Other variables significantly (all P < 0.0001) and independently associated with GS were age, sex, race, depressive symptoms, and obesity.
|Table 2: General linear mixed model of gait speed over time in adults with arthritis|
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The decline in GS score by arthritis status is shown in [Figure 2]. The figure shows that adjusted mean GS was slower in adults with arthritis at baseline through 4-year of follow-up compared to that in adults without arthritis. The figure also shows that the slope of GS declined continuously from baseline through the 4-year follow-up period with increasing age in adults without arthritis.
|Figure 2: Adjusted mean gait speed score over time in adults with and without arthritis|
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| Discussion|| |
We aimed to examine the GS over time in adults with arthritis. The findings support the hypothesis that arthritis would be associated with slow GS with a decline over time. This study found that adults with arthritis were significantly associated with slow GS with a continuous decline over a 4-year period. The association remained significant after adjusting for all covariates, such as age, sex, race, depressive symptoms, and BMI. However, groups both with and without arthritis showed significant GS decline over time.
A recent large population cohort study of adults aged 55 years and older with a chronic health condition showed that symptomatic hip or knee OA was the most significant contributor to gait difficulty. That study also showed that gait difficulty was significantly and independently associated with old age, female sex, and BMI. The current study findings showed that arthritis was significantly associated with slow GS and decline over time, even after adjusting for all covariates. Covariates such as age, sex, race, depressive symptoms, and BMI were also significantly and independently associated with GS decline. These findings are consistent with longitudinal studies,, and others., However, the current study results are based on a longer follow-up (4 years), and the adults with arthritis were aged 45 years and older.
Evidence from an English longitudinal study of aging showed that depressive symptoms were associated with slower GS and the results appeared to be bidirectional. In other words, people with slower GS were currently or in the future more likely to report depressive symptoms, while people who reported increased depressive symptoms had slower GS and were likely to experience a further decrease in GS in the future. Thus, more studies are necessary to clarify the relationship between depressive symptoms and GS decline.
The strengths of our study include the large number of subjects from the OAI, a multicenter, prospective, public and privately funded ongoing study across the USA. We also used a widely accepted and validated measure, the 20-m walk test, to assess GS. However, this study had some limitations. First, self-reported arthritis may have been incorrect. Some participants might have had arthritis, but were not diagnosed at the time of the interview, resulting in misclassification bias. However, some national surveys have used self-reporting of arthritis. Second, we did not have information on the severity of arthritis. Finally, we were unable to control for additional factors that may be associated with GS, such as vision and hearing difficulties.
A better examination of the relationship between arthritis and GS is necessary to develop effective strategies for improving management, especially in older adults. This population with arthritis displayed both reduced physical function and impaired mental function, compared to those without arthritis. Therefore, GS is a useful indicator of disability in this population. However, gait requires energy for movement control and support and places demands on the cardiac, respiratory, circulatory, nervous, and musculoskeletal systems. Slowing gait may reflect both impaired organ systems and the high energy cost of gait. Moreover, GS decline may induce a vicious cycle of reduced physical activity, with a direct effect on health and survival.
Our findings suggest that adults with arthritis had slow GS and decline over time compared to those without arthritis, even after controlling for all covariates. In addition, those without arthritis showed a decline in GS over time with increasing age. Confounders of age, sex, race, depressive symptoms, and obesity were independently associated with GS decline. Future studies are needed to examine the association between arthritis and GS, including assessment of additional confounders of vision, hearing, and severity of arthritis, especially in older adults.
The OAI is a public–private partnership comprised of five contracts (N01-AR-2-2258, N01-AR-2-2259, N01-AR-2-2260, N01-AR-2-2261, and N01-AR-2-2262) funded by the National Institutes of Health, a branch of the Department of Health and Human Services, and conducted by the OAI Study Investigators. This manuscript was prepared using an OAI public use data set and does not necessarily reflect the opinions or views of the OAI investigators, the NIH, or the private funding partners. The author extends his appreciation to the Research Centre, College of Applied Medical Sciences, and the Deanship of Scientific Research at King Saud University for support this research.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2]