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Bhore P, Shinde S. Effect of multi-component exercises program on pain-related gait adaptations among individuals with osteoarthritis of the knee joint. JOURNAL OF EDUCATION AND HEALTH PROMOTION 2023; 12:138. [PMID: 37397115 PMCID: PMC10312405 DOI: 10.4103/jehp.jehp_1628_22] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 01/12/2023] [Indexed: 07/04/2023]
Abstract
BACKGROUND Osteoarthritis of the knee causes pain and gait disturbances, as well as a distinct gait pattern. Patients with knee OA have decreased range of motion (ROM) and increased ground reaction force. OA reduces stride length and walking speed. OBJECTIVES To determine the effect of a multi-component exercise program on pain-related gait adaptations among individuals with osteoarthritis of the knee joint and to compare the effect of multi-component exercises with traditional exercises on pain-related gait adaptations among individuals with osteoarthritis of the knee joint. MATERIALS AND METHODS This was an experimental study done between 120 patients having knee OA, of both genders, and between the age group of 50-65 years. These individuals were residents of the city of Karad and they were randomly divided into group A (conventional/traditional) and group B (experimental). A pretest assessment was done and the treatment was given for 6 weeks. The later posttest assessment was done and further statistical tests like paired and unpaired t tests were used. RESULTS Among the 120 subjects with OA knee, the age group of 60-65 years (44%) was found to be commonly affected. Thirty-nine were males (32.5%) and 81 were females (67.5%). Fifty-eight subjects (48%) were found to be commonly overweight. Thirty-two subjects (27%) had Genu Valgum deformity, and 88 subjects (73%) had Genu Varum deformity at the knee joint. The Pvalue within both group A and group B was found to be statistically significant for the entire outcome measures used for assessment. The pretest vs post test values of the WOMAC scale for patients with knee OA within both groups were found to be extremely significant (P < 0.0001). As for the MMT score in these patients, the Knee Flexors of Group A were not significant for right side (P = 0.7088) as well as for left side (P = 0.083) and in Group B they were extremely significant (P < 0.0001) for both sides. For the ROM scores within both groups, Knee Flexion of Group A for both sides was found to be extremely significant (P < 0.0001) for both sides. And for the pretest vs posttest values of within the groups'gait parameters among these patients with OA knees, for cadence both groups B were found to be extremely significant (P < 0.0001). The stride length for Group A was found to be very significant (P = 0.0060) and for Group B it was (P < 0.0001). Also, the P values of the various outcome measures between both groups were found to have statistical significance of their own. CONCLUSION Effect of Multi-Component Exercise Program on Pain-Related Gait Adaptations Among Individuals with Osteoarthritis of the Knee joint was found to be significant in pain reduction, improving strength, range of motion, and the gait parameters such as an increase in cadence, stride length, step length and decrease in the step width.
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Affiliation(s)
- Prachiti Bhore
- Department of Musculoskeletal Sciences, Krishna College of Physiotherapy, Krishna Institute of Medical Sciences Deemed to be University, Karad, Maharashtra, India
| | - Sandeep Shinde
- Department of Musculoskeletal Sciences, Krishna College of Physiotherapy, Krishna Institute of Medical Sciences Deemed to be University, Karad, Maharashtra, India
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Chen H, Wu J, Wang Z, Wu Y, Wu T, Wu Y, Wang M, Wang S, Wang X, Wang J, Yu H, Hu Y, Shang S. Trends and Patterns of Knee Osteoarthritis in China: A Longitudinal Study of 17.7 Million Adults from 2008 to 2017. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18168864. [PMID: 34444613 PMCID: PMC8395063 DOI: 10.3390/ijerph18168864] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 08/19/2021] [Accepted: 08/20/2021] [Indexed: 12/18/2022]
Abstract
Background: Knee osteoarthritis (KOA) provides many challenges on the healthcare system. However, few studies have reported the epidemiology, particularly in a large population. Our study aimed to estimate the prevalence, incidence, trends, and patterns of diagnosed KOA in China. Methods: This was a longitudinal study. We used health insurance claims of 17.7 million adults from 2008-2017 to identify people with KOA. Trends in prevalence and incidence were analyzed using joinpoint regression. Results: We identified 2,447,990 people with KOA in Beijing, 60% of which were women. The 10-year average age-standardized prevalence and incidence of KOA was, respectively, 4.6% and 25.2 per 1000 person-years. Prevalence increased with age, surging after 55 years old. The average crude prevalence was 13.2% for people over 55 years old. The prevalence showed an increasing trend from 2008 to 2017, including a period of rapid rise from 2008 to 2011 (p < 0.05); the increase in prevalence was greatest in people under 35 years old (p < 0.05). Conclusion: Our analyses showed that the annual prevalence rate of KOA increased significantly from 2008 to 2017 in China. We need to increase our attention to women and the elderly over 55 years old, and also be alert to the younger trend of incidence of KOA.
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Affiliation(s)
- Hongbo Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
- School of Nursing, Peking University, No. 38 Xueyuan Road, Beijing 100191, China
| | - Junhui Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
| | - Zijing Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
| | - Yao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
| | - Tao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
| | - Yiqun Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
| | - Mengying Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
| | - Siyue Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
| | - Xiaowen Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
| | - Jiating Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
| | - Huan Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
| | - Yonghua Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China; (H.C.); (J.W.); (Z.W.); (Y.W.); (T.W.); (Y.W.); (M.W.); (S.W.); (X.W.); (J.W.); (H.Y.)
- Medical Informatics Center, Peking University, No. 38 Xueyuan Road, Beijing 100191, China
- Correspondence: (Y.H.); (S.S.)
| | - Shaomei Shang
- School of Nursing, Peking University, No. 38 Xueyuan Road, Beijing 100191, China
- Correspondence: (Y.H.); (S.S.)
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