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Record W4404242167 · doi:10.7759/cureus.73452

Exploring the Burden of Knee Osteoarthritis in Rural South India: Community Prevalence, Risk Factors, and Functional Assessment Among Adults Aged 40 and Above

2024· article· en· W4404242167 on OpenAlexaboutno aff
Saravanan Kandasamy, Balaji Mahendran

Bibliographic record

VenueCureus · 2024
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACPhysical therapyOsteoarthritisOdds ratioRheumatologyCross-sectional studyLogistic regressionPopulationRheumatoid arthritisInternal medicineEnvironmental healthAlternative medicinePathology

Abstract

fetched live from OpenAlex

Background The rising prevalence of osteoarthritis (OA) will create significant challenges for low-resource public health systems in countries like India, leading to increased disability and reduced quality of life. Limited access to imaging and specialized orthopedic care in rural areas often delays diagnosis and treatment until the disease has progressed to advanced stages, further burdening the economy. Objectives To estimate the community prevalence and assess the risk factors associated with OA among adults aged 40 and older in rural areas of South India and to determine their functional assessment among OA-diagnosed patients. Methods A community-based cross-sectional study was conducted in rural Tiruvallur district, Tamil Nadu, South India, from September 2017 to August 2018 among 427 people aged 40 and above. People with rheumatoid arthritis, reactive arthritis, old trauma of knee joint, and who have undergone total knee replacement were excluded from the study. A validated semi-structured questionnaire was used which consisted of the socio-demographic profile of the individuals, risk factors of knee OA, American College of Rheumatology (ACR) criteria for diagnosis of knee OA, Western Ontario and McMaster Universities Arthritis Index (WOMAC) scale and Visual Analog Scale (VAS) for functional assessment. A chi-square test and odds ratio were used to determine the significant risk factors and multivariate binomial logistic regression was performed to identify the predictors of knee OA. Results The mean age of the study population was 60 years ranging from 42 to 89 years with 48% males and 52% females. The community prevalence of knee OA was 34.6%. The significant predictors for the development of OA were diabetes, obesity, Indian toilet use, and hypertension in women. The level of pain among OA patients was higher for standing from a sitting position and while climbing upstairs. The mean WOMAC score of OA subjects was 57.38 (± 12.16) ranging from 25 to 78. Conclusion The study reveals a high prevalence of knee OA among over one-third of individuals aged 40 and above in rural South India, with significant risk factors including obesity, diabetes, hypertension, menopause, sedentary lifestyles, and Indian-style toilets. Severe functional impairment, indicated by high WOMAC scores, underscores limited healthcare access, emphasizing the need for community interventions in lifestyle modification and chronic disease management.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.252
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

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