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European Journal of Physical and Rehabilitation Medicine logoLink to European Journal of Physical and Rehabilitation Medicine
. 2024 Apr 22;60(3):496–504. doi: 10.23736/S1973-9087.24.08034-1

Diabetes is associated with longitudinal declined physical performance measures in persons with or at risk of knee osteoarthritis: data from the Osteoarthritis Initiative

Aqeel M ALENAZI 1,*, Bader A ALQAHTANI 1
PMCID: PMC11258910  PMID: 38647532

Abstract

BACKGROUND

The primary aim of this study was to longitudinally examine the impact of diabetes mellitus (DM) on physical performance measures including Gait Speed and Chair Stand tests over 8 years of follow-up in people with or at risk of knee osteoarthritis (OA).

DESIGN

A prospective longitudinal study.

SETTING

Multisite community based.

POPULATION

This study included participants with or at risk of knee OA aged from 45 to 79 years from the Osteoarthritis Initiative from baseline to 96 months follow-up.

METHODS

The participants performed physical performance measures using a 20 m Walk Test for Gait Speed and 5 Times Sit To Stand for repeated chair stand test time at baseline and during follow-up visits. Participants were asked about the presence of diabetes mellitus (DM) at baseline and categorized into with or without DM. Generalized estimating equations were utilized with 2 models, one for DM and Gait Speed and the other for DM and Repeated Chair Stand Test after controlling for covariates including age, sex, education, Body Mass Index (BMI), depressive symptoms, physical activity level, baseline number of comorbidities, and baseline Kellgren and Lawrence grades for OA grading for each knee.

RESULTS

A total of 4796 participants were included and categorized into those with DM (N.=362) and without DM (N.=4311) at baseline. Participants with DM at baseline showed significantly declined gait speed (B=-0.048, 95% Confidence Interval [95% CI]: [-0.07, -0.02], P<0.001) and significantly an increased time for repeated chair stand test (B=0.49, 95% CI: [0.08, 0.89], P=0.018) over time when compared to those without DM at baseline, after controlling for covariates.

CONCLUSIONS

DM was associated with negative impact on Gait Speed and Repeated Chair Stand Test time in individuals with or at risk of knee OA. Individuals with knee OA and diabetes who exhibit declining physical performance measures are at risk of functional dependence, reduced quality of life, and complex rehabilitation requirements.

Key words: Walking speed, Metabolic syndrome, Exercise test, Arthritis

Osteoarthritis (OA) and diabetes mellitus (DM) are common coexisted comorbidities that might have a negative impact on symptoms and physical functions. The prevalence of OA was approximately 16% globally,1 and the prevalence of DM was approximately 11% of the general population.2 DM has been shown to be a significant risk factor for the development or progression of OA in previous studies.3, 4

The concurrence of OA and DM can have a synergistically negative impact on an individual’s life due to the combined effects of declined physical functions and hyperglycemia. While both OA and DM can independently contribute to these issues, their coexistence can exacerbate the overall impact on an individual’s well-being. This may create a challenge for individuals with both OA and DM since OA affects joints range of motion and physical functions such as walking and raising from a chair, and DM management requires control through increasing activity levels such as walking.5-7

Physical performance measures are important outcomes in clinical field because of their sensitivity and validity for predicting future outcomes such as disability. Among these measures are gait speed/ walking speed and chair stand tests. Gait Speed and Chair Stands are simple and easy to perform measures in a clinic setting, requiring minimal equipment and training. They are therefore ideal for assessing physical function in a variety of patient populations, including older adults, people with chronic diseases, and people with disabilities. Other physical performance measures, such as a 6-Minute Walk, can be more difficult to perform in a clinic setting. Walking is considered as the sixth vital sign because of its predictive ability for future disability and its sensitivity as an outcome measure with excellent psychometric properties.8-10 Repeated Chair Stand Test Speed is considered as an easy to administer test to measure mobility and lower extremity endurance with good reliability and validity.11, 12 Limited research has examined the association between DM and physical performance measures such as Gait Speed and Repeated Chair Stand Speed among persons with OA. Previous evidence has shown that DM was associated with increased pain severity and decreased walking speed in patients with knee OA.13-19 However, these studies included only gait speed using cross-sectional designs. Therefore, it is crucial to examine the impact of DM on other physical performance measure such as sit to stand.

Diabetes can contribute to declines in physical performance through various potential mechanisms. One mechanism is peripheral neuropathy, which is a common complication associated with diabetes. Peripheral neuropathy refers to damage to the peripheral nerves, leading to symptoms such as numbness, tingling, and weakness in the extremities. This can result in impaired balance, coordination, and muscle strength, ultimately affecting physical performance.20 Another mechanism is muscle weakness, which can be caused by physical inactivity in individuals with diabetes. Physical inactivity can lead to a decline in muscle strength, particularly in patients with diabetes. This muscle weakness can further contribute to declines in physical performance, as it may result in poor muscle strength, functional limitations, and physical disability.21

Chronic inflammation is also a potential mechanism through which diabetes may contribute to declines in physical performance.22 Diabetes is associated with increased levels of inflammatory markers, such as interleukin-6.22, 23 Chronic inflammation can lead to muscle wasting and atrophy, impairing muscle function and overall physical performance.23 Overall, diabetes can contribute to declines in physical performance through mechanisms such as peripheral neuropathy, muscle weakness, and chronic inflammation. These mechanisms can impair balance, coordination, muscle strength, and overall physical function, leading to limitations in physical performance in individuals with diabetes.

DM as a chronic metabolic disease with low-grade inflammation may have a negative impact on body systems including muscles, nerves, and joints that may influence physical functions over time. Since previous work has examined the association between DM and OA with gait speed and found declined gait speed in those with DM and knee OA compared to those with knee OA only.18, 19, 24, 25 However, these studies were cross-sectional designs that may not consider other factors such as aging. Measuring the longitudinal decline in performance measures such as gait speed and sit to stan is crucial for participants with DM and OA to track and monitor changes in functional abilities. Having Both DM and OA can impact an individual’s physical capacity, leading to decreased mobility, impaired balance, and reduced overall functionality. By consistently measuring performance measures, such as gait speed, balance, and mobility, healthcare professionals can gain valuable insights into the progression and management of these conditions that help in guiding appropriate interventional plans. Therefore, the aim of this study was to longitudinally examine the impact of DM on physical performance measures including gait speed and chair stand tests over seven years of follow-up in people with or at risk of knee OA. We hypothesized that DM would have a negative impact including a decline in physical performance measures among individuals with or at risk of knee OA.

Materials and methods

Study design and cohort

This study included data from the Osteoarthritis Initiative (OAI). This cohort included data for participants with or at risk of knee OA. More detailed information regarding the data from the OAI has been published elsewhere (https://nda.nih.gov/oai/). To summarize, the OAI is a multisite longitudinal prospective cohort study including four sites in the United States (i.e., Brown University, Rhode Island, Ohio State University, Columbus, Ohio, University of Maryland/Johns Hopkins University joint center, Baltimore, Maryland, and the University of Pittsburgh, Pittsburgh, Pennsylvania). This study aimed to examine OA onset and progression to develop preventive and interventional strategies for individuals with or at risk of knee OA. A total sample of 4796 individuals (aged 45-70 years) were recruited and their data included if they have knee OA or at risk of knee OA. All clinical data and outcomes were measured over for seven clinical visits over the course of the study, one visit per one to two years. All procedures were in accordance with Helsinki declaration and its later amendments. This study was approved by Institutional Review Board (IRB) for the University of California, San Francisco (UCSF) and its affiliates (approval number: FWA00000068) in addition to the approvals from all four clinical sites. Each participant signed an informed consent prior to the enrollment to the study.

Outcome measures

The primary outcomes for this study were physical performance measures including gait Speed and Repeated Chair Stand tests at baseline and during follow-up. These measures were taken over 7-time points including baseline, 12 months, 24 months, 36 months, 48 months, 72 months, and 96 months follow-up.

A 20-m Walk Test was used for measuring gait speed at baseline and during follow-up. This test was performed in a standardized manner and well tolerated by older adults. This test measures the time it takes to complete a 20-m walk at usual walking speed for participants. This test requires equipment and supplies including two fluorescent orange traffic cones, white cloth tape, and digital stopwatch. The stopwatch was used to measure the time to complete the 20-m walk from the beginning to the conclusion of the test. At the start of the test, the display should read 0.00:00. To start the test, press the button to begin and press it again to stop the time when the walk is completed. The time is displayed as minutes: seconds. hundredths of a second and recorded. To ensure consistency across data collection centers, a standardized walking course of 20 meters was established in a dedicated corridor with no obstructions. To clearly indicate the start and end points of the course, fluorescent orange traffic cones were placed, 20 meters apart, with careful consideration to avoid any potential tripping hazards. Additionally, a 0.5-meter length of white cloth tape was positioned on each side of the cones, marking the beginning of the course. It is important for participants to walk in a clockwise direction following this set-up. The test description included that at the start of the walk, participants should position their toes in light contact with the starting line, ensuring not to extend beyond it. A specific script was used across centers to explain the test for participants: “Now we want to measure your usual walking speed. You will start behind this line. When you have passed the orange cone, I want you to take three more steps and then you may stop.” Then, the participants were instructed to start the test by this script ““Now when I say ‘Go,’ I want you to walk at your usual walking pace. Any questions?”, Ready, Go. The duration of the initial 20-Meter Test should be recorded on the form. Then, the stopwatch should be reset, and the participant should be instructed to repeat the 20-meter walk in the opposite direction. It is important to emphasize that the participant should maintain their regular walking speed during this second phase of the test. Time of completion for the second portion should also be recorded. A specific Script was used for the second trial: “OK, fine. Now turn around and when I say go, walk back the other way at your usual walking pace. Ready, Go.” The time for the second trial was recorded on the form similar to the first trial. Specific description for 20-m Walk Test included that the participants were instructed to walk at their usual speed, using their usual footwear. The participants were allowed to use an assistive device if needed. Two trials were performed, and the average was used for gait speed calculation. The mean of the two trials was used by dividing the distance (20 m) by the time required to complete the test.26 A 20-m Walk Test used gait speed measure as meter/second (m/s).

A repeated chair stand test was used as a physical performance measure using 5 times sit to stand.11 This test outlined in this study encompass various aspects of physiological performance, such as lower extremity strength, balance, coordination, and flexibility. The evaluation techniques utilized in this research are based on previous studies, have demonstrated reliability when executed in a standardized manner, and have been found to be well-tolerated by older individuals. This test has been used to measure functional lower extremity strength, and mobility.11 Specific description for 5 times sit to stand required a digital stopwatch and a chair with a straight back, flat, level, firm seat; seat height 45 cm at front. At the start of the test, the display of the stopwatch should read 0.00:00. To start the test, press the button to begin and press it again to stop the time when the task is completed. The time is displayed as minutes: seconds. hundredths of a second and recorded. Walking aids were not allowed in this test. The Chair Stand Test was explained to the participant by the examiner, followed by a discussion about their ability to attempt the test in consideration of any existing physical limitations or disabilities. If the participant declines or was unable to perform the test, this was recorded. To minimize the influence of footwear variations on test outcomes, it was recommended that participants performed the tests wearing tennis shoes or comfortable walking shoes that have minimal or no elevated heels. In situations where suitable footwear is unavailable, the participant was opted to perform the tests while wearing stocking feet or in bare feet, if deemed appropriate. For optimal stability, the standard chair was positioned on a nonslip surface, preferably one with low pile carpeting. The back of the chair was placed against a wall to ensure additional support. Ample space was available in front and on the sides of the chair, enabling both the examiner and participant to move unrestrictedly during the assessment. The Chair Stand Test was administered by a certified examiner in a specific sequence to ensure standardized and consistent results. The examiner began by providing a detailed explanation of the procedure to the study participant, conveying key points from the suggested script. Following this, a demonstration of the procedure was carried out, also following the suggested script. The participant was given the opportunity to ask any questions they had before a brief reiteration of the procedure was conducted. Subsequently, the participant was asked to perform the Chair Stand Test, and all timed procedures were initiated with the words, “Ready? Go!” By following this structured approach, motivation and comprehension levels were effectively addressed, thereby promoting accurate and reliable test outcomes. Participants were instructed to sit with their backs against the chair, with arms folded over their chests. The timer started when the individual moved his/her back away from the chair and each stand was counted aloud to keep the participant oriented. The examiner used a specific script “This time, I want you to stand up five times as quickly as you can keeping your arms folded across your chest.” The timer was stopped when the participant achieved a standing position on the repetition number 5. Participants with lower recorded time indicate better scores and faster mobility performance. This test was repeated in two trials and the average was used for the current analysis using seconds. Five times sit to stand test has been considered as a reliable and valid measure of mobility performance (Figure 1, 2)11 (Supplementary Digital Material 1, Supplementary Text File 1, Supplementary Digital Material 2, Supplementary Text File 2).

Figure 1.

Figure 1

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—Gait speed observation overtime (year to year) in people with and without DM.

Figure 2.

Figure 2

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—Repeated chair stand observation overtime (year to year) in people with and without DM.

Covariates

Demographic characteristics were included as covariates in the current study including age, sex, education, and Body Mass Index (BMI). In addition, other clinical variables were included as covariates including depressive symptoms, physical activity level, baseline number of comorbidities, and baseline Kellgren and Lawrance grades (KL) for each knee ranging from 0 to 4. These covariate variables have been controlled for in previous research using similar database.27

Age was recorded in years and measured at 7-time points. Educational level was dichotomized as less than high school/high school and some college/graduate using two categories. BMI was obtained by dividing body mass (kg) by the square of height (m2), and it was measured at 7-time points.

Depressive symptoms were measured using self-reported 20-item Center for Epidemiologic Studies-Depression Scale (CES-D) that has shown good validity and reliability, and it was measured at 7-time points.28 Physical Activity in the Elderly Scale (PASE) was used for measuring physical activity level that has shown good validity and reliability, and it was measured at 7-time points.29 Baseline number of comorbidities was calculated using self-reported questionnaire from Charlson Index30, 31 and classified into four categories (i.e., none, one, two, and three or more comorbidities). Baseline KL was measured using radiograph for each knee and the grades range from 0 to 4.

Statistical analysis

Participants were selected based on baseline self-reported DM using Charlson Comorbidity Index (CCI), and they were categorized as DM (N.=362) and no DM (N.=4311). All baseline measures were computed and reported in comparison between participants with DM compared to those without DM. Differences between groups were examined using χ2 for categorical variables or independent t-test for continuous variables.

To examine the impact of DM on longitudinal physical performance measure including gait speed and repeated chair stand, generalized estimating equations (GEE) modeled with linear regression was utilized. The use of GEE allows us not to use multiple imputations as this method not exclude participants with missing data at any time points. GEE is a recommended longitudinal analysis when discrete time points are considered.32 The model was built using all variables added at one time to account for covariates. Accounting for this model being the best model was based on the Quasi likelihood under Independence Criterion (QIC) as this was improved after adding other covariate variables such as KL and PASE. The type of correlation matrix was independent matrix as this assumed independence of observations overtime. Finally, model assumptions were assessed by multicollinearity in the independent variables and correlation structure using QIC.

Two adjusted models were used, one with gait speed as the outcome (dependent variable) and one with repeated chair stand as the outcome (dependent variable). Both models were adjusted for age, sex, educational level, BMI, depressive symptoms, physical activity level using PASE, baseline number of comorbidities, and baseline KL grades for each knee. Sex, educational level, number of comorbidities, and KL grades were used at baseline while age, BMI, depressive symptoms, PASE, and PASE were included as a time-varying covariates over 7 time points. These adjustments were made based on previous literature and clinical relevance to the outcome measures including gait speed and mobility measures.18, 19, 24, 33-36 In addition, these covariates were statistically different between groups with DM and OA when compared to the group with OA only using the explanatory univariable analysis except sex that was added due to its relevance to the study outcomes. Participants without DM were used as a reference category. Alpha level was set at 0.05. All analyses used IBM SPSS for Mac version 25.0 (SPSS Inc. Chicago, IL, USA).

Results

A total of 4796 were included in the current study with 96 months follow-up. Baseline measures and clinical variables are shown in Table I.

Table I. —Baseline demographics and clinical characteristics.

Factors DM
N.=362		 No DM
N.=4311		 P*
Age, years (mean±SD) 63.44±8.5 60.90±9.1 <0.001
Sex, females, (% within DM) 198 (54.7) 2538 (58.9) 0.13
BMI, Kg/m2 (mean±SD) 31.75±4.7 28.29±4.7 <0.001
Education, N., (% within DM) <0.001
Less than high school/high school 99 (27.3) 641 (14.9)
Some college/graduate 263 (72.7) 3666 (85.1)
Depressive symptoms (mean±SD) 8.02±8.5 6.40±6.7 <0.001
PASE (mean±SD) 138±78 162±82 <0.001
Number of comorbidities <0.001
None 49 (13.6) 3459 (80.6)
One 177 (49.3) 529 (12.3)
Two 68 (18.9) 221 (5.2)
Three or more 65 (18.1) 80 (1.9)
KL grades right knee, N., (% within DM) <0.001
0 1655 (40.9) 84 (25.8)
1 701 (17.3) 67 (20.6)
2 1013 (25.0) 105 (32.2)
3 555 (13.7) 56 (17.2)
4 127 (3.1) 14 (4.3)
KL grades for left knee, N., (% within DM) <0.001
0 1562 (38.7) 95 (29.0)
1 706 (17.5) 58 (17.7)
2 1107 (27.4) 93 (28.4)
3 525 (13.0) 69 (21.0)
4 134 (3.3) 13 (4.0)
Gait speed, m/s (mean±SD) 1.20.3±0.20 1.33.7±0.21 <0.001
Repeated chair stand, s (mean±SD) 12.44 ±4.5 10.80 ±3.7 <0.001
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DM: diabetes; OA: osteoarthritis; BMI: Body Mass Index; PASE: Physical Activity Scale for Elderly. KL: Kellgren & Lawrence grades for OA severity; SD: standard deviation. *P value that was based on χ2 for categorical variables or Independent t-test for continuous variables.

Participants were categorized into participants with DM (N.=362) and without DM (N.=4311) at baseline. All baseline measures and demographic characteristics were significantly different between those with DM compared to participants without DM except sex. Baseline gait speed and chair stand tests were significantly slower in individuals with DM compared to those without DM (1.20 m/s vs. 1.33 m/s and 12.44 s vs. 10.8 s, respectively).

The results of longitudinal analysis for the impact of DM on physical performance measures are shown in Table II.

Table II. —GEE with linear regression for the relationship between baseline DM and over time gait speed and over time Chair Stand Test.

Outcomes Number of participants B SE P
Gait speed N.=4318 -0.048 0.01 <0.001
Repeated chair stand test N.=4266 0.49 0.21 0.018
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B: unstandardized coefficient, SE: standard error. The model was adjusted for age, sex, education, BMI, depression, PASE, baseline KL grades for both knees, and baseline number of comorbidities.

Participants with DM at baseline showed significantly declined gait speed over time when compared to those without DM at baseline (B=-0.048, 95% Confidence Interval (95% CI): [-0.07, -0.02], P<0.001) after controlling for covariates including age, sex, education, BMI, depression, physical activity level using PASE, baseline KL grades for both knees, and baseline number of comorbidities.

The results of longitudinal analysis for the impact of DM on repeated chair stand test are shown in Table II. Participants with DM at baseline significantly showed an increased time for repeated chair stand test over time when compared to those without DM at baseline (B= 0.49, 95% CI: [0.08, 0.89], P=0.018) after controlling for covariates including age, sex, education, BMI, depression, physical activity level using PASE, baseline KL grades for both knees, and baseline number of comorbidities.

Discussion

The current study aimed to longitudinally examine the impact of DM on physical performance measures including gait speed and chair stand tests over 8 years of follow-up in people with or at risk of knee OA. The findings may support the hypothesis that DM would have a negative impact including a decline in physical performance measures among individuals with or at risk of knee OA overtime. Although the baseline KL grades were significantly different between participants with DM and knee OA compared to participants with knee OA only, KL was included as a covariate in the longitudinal analysis and DM remained a significant predictor for a decline in physical performance measures. The rate of decline has been compared between those with DM and OA to those with OA only accounting for other covariates including age. For example, in the current study, having DM and knee OA was associated with a decline by approximately 0.05 m/s when compared to those with knee OA only. This decline was accounted for aging overtime in the analysis. Also, having DM and knee OA was associated with approximately 0.5 seconds increase in the performance of 5 times sit to stand when compared to those with knee OA only after accounting for age in the analysis. Therefore, the rate of decline is higher than that in normal aging.

Whilst it is well established in the literature that changes in gait biomechanics typically transpire as a result of aging, these alterations are particularly noticeable and have great negative impact on function capabilities in people with OA.37 Moreover, DM, in particular, has been linked with gait alterations such as decreased walk speed. When these two conditions coexist, they can significantly impair gait speed. In addition, previous studies suggest that DM impacts gait speed in individuals with OA through various mechanisms include lower extremity weakness and atrophy, visual impairment, altered biomechanics, and peripheral sensation impairment.

According to research, people with knee OA may have physical performance measures that are affected by DM,18, 19, 24, 25, 38 mostly due to the condition’s impacts on balance and muscle strength. However, previous research did not specify KL grades for knee OA. Future research should examine the impact of DM on physical functions accounting for specific severity such as moderate and sever knee OA. DM can result in decreased muscle mass and strength, particularly in the lower limbs, which can weaken muscles and make performing functional tasks requiring leg strength difficult. DM can also induce neuropathy, or nerve damage, which impairs lower limb motor or sensory function. The differences in physical performance between people with OA and DM and those with OA alone can have a significant clinical impact. These differences can make it difficult for people with OA and DM to maintain their independence and quality of life. They can also increase their risk of falls, fractures, and other complications. This can impair balance and coordination, making it difficult to perform physical tasks safely and productively. DM is also linked to chronic inflammation, which can increase osteoarthritis-related pain and joint deterioration, as well as impair muscle function, decreasing physical performance capacities.39

The negative impacts of DM on physical performance for people with OA can have many implications for their general well-being and day-to-day activities. For example, slow gait speed can increase the risk of falls, further joint damage, and overall physical deconditioning. It can limit daily activities and social participation, leading to a reduced sense of satisfaction and effects on overall functioning and quality of life. Therefore, it is important to assess gait speed and other measurements related to mobility in individuals experiencing both OA and DM and to offer interventions that can improve mobility and activity levels. According to studies, those with DM and OA perform worse on physical performance tests than those with either one of the disorders or those without any of the conditions.

Declining physical performance measures like gait speed and chair stand tests have significant clinical implications on functional independence, mobility, and rehabilitation outcomes. Difficulty performing chair stands indicates reduced lower body strength and balance, which can lead to mobility limitations and an increased risk of falls.40 In addition, slower gait speed is associated with an increased risk of falls, disability, and mortality.9 Declining physical performance measures can negatively impact other rehabilitation outcomes, as they may indicate underlying muscle weakness, balance impairments, or neurological deficits.41, 42 These factors can hinder progress in rehabilitation programs and may require adjustments to treatment plans.

Monitoring these measures is crucial for identifying patients at risk, adapting treatment plans, and promoting overall well-being and quality of life. Early intervention and ongoing assessment can help mitigate the negative consequences associated with declining physical performance.

Interventions that target both DM and OA may be useful in improving physical performance measures in patients with these conditions. These interventions may include lifestyle changes such as losing weight and physical activity, as well as medications to control DM and minimize joint pain and inflammation associated with osteoarthritis. Furthermore, physical therapy and other rehabilitation measures may assist to improve balance and coordination, resulting in enhanced physical function in patients with both conditions.

Limitations of the study

The present study has some limitations, including not accounting for potential confounding factors such as family history of DM or the duration of DM and diabetic medications. Another limitation is that some missing data related to gait speed and sit to stand that might affect the results. However, GEE has been utilized to overcome missing data at some time points of the follow-up and not excluding these cases with missing data. The results should be interpreted with caution since we only adjusted for KL grade at baseline and did not assess the severity of OA over time. Additionally, DM was self-reported, which could have introduced misclassification bias, although previous research has authenticated the validity and reliability of self-reported DM. Some participants might be classified as not having DM while they had the disease, but they might not know it at baseline. Future research should incorporate objective measures for DM such as fasting glucose level and hemoglobin A1c to ensure accurate classification for participants with DM. The sample from the current study included four different sites and participants were recruited through flyers and contacts. However, participants with poor health might not be interested in site visits and interviews and this might affect the generalizability of the results. Though, the study’s strength is that it depended on a large population cohort study and objectively measured physical performance. Consequently, we believe that the study findings can be extended to people with or at risk for OA.

Conclusions

Diabetes was associated with negative impact on gait speed and repeated chair stand test time in individuals with or at risk of knee OA. This study found that DM was associated with declined gait speed and increased time for preforming repeated chair stand test, and this association was significant at baseline and overtime in this population. The study’s findings, elucidating the deleterious consequences of diabetes on gait speed and chair stand test performance in individuals with or at risk of knee OA, necessitate a comprehensive and multidisciplinary paradigm in clinical practice and rehabilitation interventions. To effectively address this multifaceted issue, an integrated care model predicated on a collaborative team of healthcare professionals is paramount. This approach should prioritize regular physical performance assessments, optimized diabetes management, and tailored rehabilitation programs that emphasize muscle strength, joint mobility, and pain management. These findings underscore the significance of adopting holistic strategies to enhance the quality of life for individuals contending with both diabetes and knee OA. Future research should examine effective management strategies such as exercise programs to improve muscle strength and comprehensive DM management to mitigate the negative impact of DM on physical performance in individuals with or at risk of knee OA.

Supplementary Digital Material 1

Supplementary Text File 1

Operations Manual

Supplementary Digital Material 2

Supplementary Text File 2

Operations Manual

Footnotes

Conflicts of interest: The authors certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.

Funding: This study was supported via funding from Prince Sattam Bin Abdulaziz University project number (PSAU/2024/R/1445). Both authors would like to acknowledge Prince Sattam Bin Abdulaziz University for funding project number (PSAU/2024/R/1445). 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; 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 Investi- gators. Private funding partners include Merck Research Laboratories; Novartis Pharmaceuticals Corporation, GlaxoSmithKline; and Pfizer, Inc. Private sector funding for the OAI is managed by the Foundation for the National Institutes of Health. This manuscript was prepared using an OAI public use dataset and does not necessarily reflect the opinions or views of the OAI investigators, the NIH, or the private funding partners. KK acknowledges support from the National Institute for Health Research Collaboration for Leadership in Applied Health Research and care—East Midlands (NIHR CLAHRC—EM) and the Leicester Biomedical Research Center.

References

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Text File 1

Operations Manual

Supplementary_Digital_Material1.pdf (854.7KB, pdf)

Supplementary Text File 2

Operations Manual

Supplementary_Digital_Material2.pdf (731.7KB, pdf)

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