|Year : 2020 | Volume
| Issue : 1 | Page : 19-21
A Cross-sectional study on screening for knee osteoarthritis and associated factors in a rural area of India
Lakshmi Venkata Simhachalam Kutikuppala1, K Vani Madhavi2, MV Sathvika3
1 Final MBBS Part-1 Student, Konaseema Institute of Medical Sciences and Research Foundation (KIMS&RF), Amalapuram, Andhra Pradesh, India
2 Professor and Head of Department, Department of Community Medicine, Konaseema Institute of Medical Sciences and Research Foundation (KIMS&RF), Amalapuram, Andhra Pradesh, India
3 Final MBBS Part-2 Student, Konaseema Institute of Medical Sciences and Research Foundation (KIMS&RF), Amalapuram, Andhra Pradesh, India
|Date of Submission||03-Feb-2020|
|Date of Decision||13-May-2020|
|Date of Acceptance||27-May-2020|
|Date of Web Publication||30-Jun-2020|
Mr. Lakshmi Venkata Simhachalam Kutikuppala
Final MBBS Part-1, Konaseema Institute of Medical Sciences and Research Foundation, Chaitanya Nagar, NH-216, Amalapuram - 533 201, Andhra Pradesh
Source of Support: None, Conflict of Interest: None
Background: Osteoarthritis (OA) is a degenerative disease that worsens over time after fourth decade of life. It accounts for the decrease in activities of daily living in the elderly population. Hence, early diagnosis and treatment are essential to increase the quality of life. Objectives: The objective is to identify the high risk people for OA in a rural area and to find out the significant factors associated to OA among the rural population. Materials and Methods: Cross-sectional study among rural population with a convenient sample size of 100 in which 50 were male and 50 were female. Institutional ethics committee approval was taken. Informed written consent was obtained from the participants. Data collection procedure employed was Western Ontario and McMaster Universities (WOMAC) OA index. Statistical analysis was done by Epi-info statistical software package version 3.5.4 for data analysis. Results: According to WOMAC Index 38% of the subjects belonged to high risk and 62% belonged to low risk. Age group, gender, and family history were significantly associated with these scores. Conclusion: In a resource poor setting, questionnaire-based tool to detect high risk individuals for OA at an early stage is useful in reducing the morbidity.
Keywords: Activities of daily living, osteoarthritis, rural, western Ontario and Mcmaster universities index
|How to cite this article:|
Kutikuppala LV, Madhavi K V, Sathvika M V. A Cross-sectional study on screening for knee osteoarthritis and associated factors in a rural area of India. J Integr Health Sci 2020;8:19-21
|How to cite this URL:|
Kutikuppala LV, Madhavi K V, Sathvika M V. A Cross-sectional study on screening for knee osteoarthritis and associated factors in a rural area of India. J Integr Health Sci [serial online] 2020 [cited 2020 Oct 21];8:19-21. Available from: https://www.jihs.in/text.asp?2020/8/1/19/288689
| Introduction|| |
Osteoarthritis (OA) is a degenerative disease that worsens over time after fourth decade of life. Globally, over 100 million people worldwide suffer from OA and is the fourth leading cause of year lived with disability. It also accounts for the decrease in activities of daily living in the elderly population. OA of the hip and knee are common conditions that, in many cases necessitate frequent follow-up, medical therapy, and potentially costly treatments such as joint replacement surgery. Age and female sex are the two most important factors for determining the onset of the OA. The prevalence of OA was found to be more in postmenopausal women and as age increases prevalence also increases, which is evident in many of the studies. In rural part of India, accessibility and affordability for these treatments are doubtful. The lack of imaging facilities and specialized orthopedic care in rural India causes a deficit in diagnosis and institutional treatment until late stages of the disease process, hence leading to increased morbidity. Hence, early diagnosis and treatment remains the key in the management. So by screening the general population for early diagnosis will reduce the cost of country's health care system.
- To identify the high risk people for OA in a rural area
- To find out the significant associated factors for OA among the rural population.
| Materials and Methods|| |
Cross-sectional community-based study.
Rural area of India.
Hundred subjects (50 males and 50 females) of age more than 50 years.
Data collection procedure
Western Ontario and McMaster Universities (WOMAC) OA index a five-point Likert version was used to detect patients for OA. It is a 24-item questionnaire focusing on pain, stiffness, and functional limitation.
Epi-info statistical software 3.5.4 for epidemiology (developed by Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States (US)). was used for data analysis and P < 0.05 was considered statistically significant.
Institutional Ethical Committee approval was taken, informed written consent was obtained from the study participants before proceeding into the study.
| Results|| |
Out of the 100 participants, 50 were male and 50 were female. Majority of them (59%) were in the age group of 50–59 years [Table 1]. Religion wise Hindus were 79%. Majority of them (63%) were belongs to low socioeconomic status.
According to WOMAC index, 38% of the subjects belonged to high risk (score >70%) among them majority (57.90%) we were females and 62% belonged to low risk (score <70%), which is in accordance with the study conducted by Joshi and Chopra [Table 2]. Most of the study participants belonged to normal body mass index (BMI) ranges and many of them are at low risk with respect to BMI [Table 3]. This is in accordance with the study conducted by Patil et al. History of OA in family was positive in most of the high risk people than the people at low risk. This is in accordance with study conducted by Ganvir and Zambre [Table 4].
The risk factors for OA were studied to find any association with WOMAC scores. Statistically significant variables (P < 0.05) are depicted in [Table 1], [Table 2], [Table 3], [Table 4]. Chi Square and P values of these study variables were depicted in [Table 5].
| Discussion|| |
It is founded that risk is high among the subjects aged >60 years in other studies also they found increasing age is a risk factor. Females had high incidence compared to males, it is in consistent with other studies. And both these factors were found statistically significant.
Overweight/obesity was found as a risk factor for knee OA and subjects with moderate activity had more WOMAC score which was not statistically significant. There is a significant association between family history and knee OA.
From this study, we found a significant association between OA and advancing age, poor education, lower socioeconomic strata, previous history of knee injury and overweight. This is one of the few studies targeted to evaluate knee OA and its associated factors in rural setting, which can be an addition to existing literature and strengthens the available research.
The limitations of the study include the relatively small sample size, the absence of radiographic confirmation of the findings using the two criteria as also the failure to exclude other possible diagnoses. More emphasis on health education and prior research can be laid down to prevent complications and morbidity in the knee OA patients, especially of rural background.
| Conclusion|| |
In a resource poor setting, questionnaire based tool to detect high risk individuals for OA at an early stage is useful in reducing morbidity. Overweight/obesity was found to be an important risk factor for knee OA in this study. Knowledge on the presence of OA risk factors, and in particular modifiable risk factors, in younger populations could help earlier identification of individuals at high risk of developing OA. This may offer an opportunity to prevent or delay the development of OA.
Financial support and sponsorship
This study was supported by the Department of Community Medicine, Konaseema Institute of Medical Sciences and Research Foundation (KIMS and RF), Amalapuram, Andhra Pradesh, India.
Conflicts of interest
There are no conflicts of interest.
| References|| |
World Health Organization. World Health Report 2002. Reducing Risks, Promoting Healthy Life. Geneva: World Health Organization; 2002.
Melzer D, Guralnik JM, Brock D. Prevalence and distribution of hip and knee joint replacements and hip implants in older Americans by the end of life. Aging Clin Exp Res 2003;15:60-6.
Salve H, Gupta V, Palanivel C, Yadav K, Singh B. Prevalence of knee osteoarthritis amongst perimenopausal women in an urban resettlement colony in South Delhi. Indian J Public Health 2010;54:155-7.
] [Full text]
Chopra A, Patil J, Billempelly V, Relwani J, Tandle HS; WHO-ILAR COPCORD Study WHO International League of Associations from Rheumatology Community Oriented Program from Control of Rheumatic Diseases. Prevalence of rheumatic diseases in a rural population in western India: A WHO-ILAR COPCORD Study. J Assoc Physicians India 2001;49:240-6.
Joshi VL, Chopra A. Is there an urban-rural divide? Population surveys of rheumatic musculoskeletal disorders in the Pune region of India using the COPCORD Bhigwan model. J Rheumatol 2009;36:614-22.
Patil PS, Dixit UR, Shettar CM. Risk factors of osteoarthritis knee – A cross-sectional study. IOSR J Dent Med Sci 2012;2:8-10.
Ganvir SD, Zambre BR. Prevalence of identification of risk factors for knee osteoarthritis among elderly men and women. Sch J Appl Med Sci 2013;1:700-3.
Bellamy N. WOMAC: A 20-year experiential review of a patient-centered self-reported health status questionnaire. J Rheumatol 2002;29:2473-6.
Soerosa J, Dans LF, Amarillo ML. Risk factors of symptomatic osteoarthritis of the Knee at a Hospital in Indonesia. APLAR J Rheumatol 2005;8:106-13.
Felson DT, Zhang Y, Hannan MT, Naimark A, Weissman B, Aliabadi P, et al
. Risk factors for incident radiographic knee osteoarthritis in the elderly: The Framingham study. Arthritis Rheum 1997;40:728-33.
Roos EM, Arden NK. Strategies for the prevention of knee osteoarthritis. Nat Rev Rheumatol 2016;12:92-101.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]