Mapping the intersection of social status and comorbidity in knee osteoarthritis: A WOMAC-based study

TL;DR

This study explores how social factors and health conditions affect the severity of knee osteoarthritis in Bangladesh.

Contribution

The study identifies key predictors of knee OA severity, emphasizing social and comorbid factors in a low-resource setting.

Findings

Age, obesity, and diabetes were the strongest predictors of severe knee OA symptoms.

Women and individuals over 70 years old were more likely to experience severe symptoms.

Low education, obesity, diabetes, and cardiovascular disease were linked to higher OA severity.

Abstract

Knee osteoarthritis (OA) is a disabling joint condition that leads to extreme morbidityand quality of life impairment, particularly among older adults. This study aimed to investigate the socio-demographic factors and comorbid conditions influencing the severity of symptoms of knee OA using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Data were derived from 622 patients across 9 months from the major healthcare facilities of Dhaka. This study found age, sex, educational status, obesity, diabetes mellitus, and cardiovascular disease (CVD) were predictors for the severity of symptoms of OA of the knee. Female participants were more prone to have severe symptoms compared to males, and those who were more than 70-years-old were at greater risk of severe symptoms. Low educational status, obesity, diabetes mellitus, and CVD were also predictors for severe OA of the knee. Age (p < 0.001), obesity (p < 0.001), and diabetes (p < 0.001) were the best predictors of severity of symptoms based on the multinomial logistic regression analysis. The findings from the study highlighted the associated factors of knee OA and the need for integral healthcare measures that address both the socio-economic and the physical determinants. Focused interventions need to be employed, particularly for high-risk groups such as the elderly, women, and the comorbid, to minimize the incidence of OA of the knee and maximize the outcomes for patients in settings such as that of Bangladesh, where resources may not be available.

Figures

Distribution of WOMAC score among the participants (n = 622).

Full text

Introduction

Osteoarthritis (OA) is a degenerative joint disease that gives rise to stiffness, pain, and loss of mobility, which predominantly occurs among older adults [1]. Osteoarthritis is one of the leading contributors to disability worldwide, with an upward increase in incidence due to aging populations and rising obesity rates [2]. The condition poses a huge healthcare burden since it negatively affects the quality of life of an individual, particularly of the knee joints [3].

Articular cartilage degeneration, subchondral bone remodeling, synovial inflammation, and osteophyte formation characterize knee OA [4,5]. Pain, stiffness, and functional disability result from these pathological processes and have a significant effect on physical function and overall quality of life [6,7]. The progression of OA encompasses a multifaceted interaction between mechanical stress, inflammation, and oxidative damage [8], and worsening symptoms and limitations of function [9].

Knee OA among older people leads to pain, reduced mobility, limitation of functions, loss of independence, and also to impaired social participation [10,11]. Estimated prevalence of knee OA among adults is 7.3% for Bangladesh [12,13], and such value raises a significant public health concern. Osteoarthritis (OA) imposes high socio-economic burdens on both people and health care systems via increased consumption of healthcare, disability, and loss of productivity [9,14]. The financial burden imposed by OA not only affect individual economies among the affected patients, but also challenge the integrity of public healthcare services [15,16].

Age is also a significant influence on severity and progression of OA knees, where conditions are more severe and degenerate more quickly among older adults [17]. There is also greater vulnerability to knee OA among women compared to men, where there is greater incidence and more severe conditions, particularly post menopause [18,19]. Hormonal deficiency, for example, estrogen deficiency, is significant in aggravating vulnerability among women, for instance, for OA knees [20]. Also, those who are not literate have greater severity of OA since they are not aware of the condition, or they do not reach healthcare services due to limited literacy [21].

Obesity hugely magnifies knee OA by increasing joint mechanical stress and triggering systemic inflammatory process, speeding disease progression and worsening symptoms [22]. Diabetes mellitus also worsens knee OA by increasing joint pain, impaired function, and inflammation [23]. Diabetic patients also experience more severe symptoms, reduced mobility, and worse outcomes compared to non-diabetic patients [23].

Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) is a widely used and validated measure of pain, stiffness, and physical function among people with OA of the knee [24,25]. Aligning to its three subscalespain, stiffness, and physical functionit reports both severity of symptoms and functional disability [24,25]. WOMAC is an important measure for monitoring follow-up improvement in OA of the knee, and also for assessing outcome of treatment [24,25].

Despite the global abundance of data connecting obesity and age to osteoarthritis, evidence remains limited regarding how these factors intersect with unique socio-economic determinants in low-resource settings like South Asia. In Bangladesh, distinct social stratifiers such as high rates of illiteracy, financial dependence among the elderly, and limited access to primary care create a unique clinical landscape that may alter disease presentation compared to Western populations.

Therefore, the aim of this study was to examine the influence of socio-demographic factors and comorbid conditions on the severity of knee osteoarthritis symptoms in a Bangladeshi clinical population. The output from this study will help to strengthen target interventions in low-resource settings as found in Bangladesh. By applying the WOMAC index in this specific demographic, we aim to move beyond established risk factors to highlight the magnitude of burden imposed by social inequality and unmanaged comorbidities in a developing country context.

Materials and methods

Study population

This research utilized cross-sectional descriptive design, in three prominent healthcare centers in Dhaka, Bangladesh: Dhaka Medical College Hospital (DMCH), National Institute of Traumatology and Orthopaedic Rehabilitation (NITOR), and Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM). As tertiary referral centers, these institutions primarily serve patients with established, symptomatic disease who require specialized management, distinguishing this cohort from community-based populations where mild or early-stage OA is more common. The hospitals have heterogeneous patient populations with specialized services, thus making them suitable for study. Data were collected over 9 months from 21 April 2024–26 January 2025. This research included individuals with knee OA, regardless of gender, older than 60 years at study initiation. This age cutoff was selected to focus on the demographic most vulnerable to advanced osteoarthritis and age-related comorbidities, ensuring the sample represented the population with the highest disease burden. All study participants met diagnostic guidelines for OA in knees by the American College of Rheumatology (ACR), including both clinical and radiographic criteria for OA. Participants who were severely ill, mentally impaired, also subjects lacking ability to provide informed consent were all excluded from the study. Furthermore, subjects having other inflammatory joint diseases like rheumatoid arthritis, ankylosing spondylitis, psoriasis, gout, other type of metabolic or congenital joint diseases were also excluded from the study. Finally, patients with previous history of joint surgery were also excluded from participating in the study.

Sampling process

To ensure a representative sample of the clinical population presenting to the selected tertiary centers, a consecutive sampling technique was employed. Data collectors stationed at the outpatient departments approached eligible patients strictly in the order of their arrival. If a selected patient declined participation, the very next eligible patient in the queue was approached. This method was chosen to minimize selection bias by removing the data collectors’ discretion in choosing participants and to ensure the sample reflected the natural flow of patients seeking care during the study period.”

Survey instruments

The survey instrument consisted of three distinct sections: (1) Socio-demographic details, (2) Comorbidity profile, and (3) The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Data were gathered with a Bengali validated English version of self-administered questionnaires by means of face-to-face interviews with the participants. Reliability of the instrument was confirmed by a Cronbach’s alpha of 0.95, indicating strong internal consistency. Before filling in questionnaires, data collectors informed respondents about the study purpose and that participation is voluntary. The questionnaire included components on socio-demographic and comorbidity information’s, and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). WOMAC is widely applied, validated, and used to measure pain, stiffness, and physical function in individuals with knee osteoarthritis [24,25].

Data analysis

After data collection, an MS excel sheet was developed. All data were handled in the MS excel sheet; thereafter, Stata version 16 was utilized for analytical exploration. Chi-square analysis was used to calculate descriptive statistics of socio-demographic features, comorbidities, and frequency of WOMAC outcome. Further, multinomial logistic regression analysis was used in analytical part to test association between socio-demographic and comorbidities with WOMAC scale. The WOMAC scale was scored on the basis of None (0), Mild (1), Moderate (2), Severe (3), and Extreme (4) on a 0–4 scale. Having a score out of a possible 0–20 for pain, 0–8 for stiffness, and 0–68 for physical function, all the values for the subscales are summed. The WOMAC scale produces a total score ranging from 0 to 96. To streamline the analysis and reflect the clinical presentation of the study population, we recategorized the grading into three distinct severity groups: Moderate (0–48), Severe (49–72), and Extreme (73+). It is important to note that no participants in this tertiary cohort scored within the “Mild” range, a finding consistent with the health-seeking behavior in this setting where patients typically delay hospital visits until symptoms become debilitating.

Statistical analysis was performed at three levels. Univariate analysis (descriptive statistics) was used to summarize the socio-demographic and clinical characteristics of the sample. Bivariate analysis (Chi-square tests) was conducted to test the initial association between independent variables and OA severity. Finally, multivariate analysis (multinomial logistic regression) was performed to identify independent predictors of symptom severity while adjusting for confounders.

Socio-demographic and health related characteristics

The explanatory variables in this study are categorized as follows: Age group (60–69 years vs 70 years and above), Gender (Male vs Female), Marital Status (Married vs Unmarried), Education (Illiterate, Primary, Secondary and above), Monthly family income (25,000 and below, 25,001–49,999, 50,000 and above), Financial independence (Independent vs Dependent), Obesity (Yes vs No), Diabetes (Present vs Absent), and cardiovascular disease (Present vs Absent). The primary outcome variable in this study was the WOMAC score, which was used to assess pain, stiffness, and functional limitations in knee OA patients.

Ethical consideration

Ethical approval for this study was obtained from the Institutional Review Board (IRB) of the National Institute of Traumatology and Orthopaedic Rehabilitation (NITOR/PT/93/lRB/2024/02). Written informed consent was obtained from all participants prior to their inclusion. We chose written consent to ensure clear, documented evidence of voluntary participation, adhering to the strict ethical guidelines required by the Institutional Review Board.

Result

Fig 1 illustrates the distribution of WOMAC scores in the 622 participants with 9.1% reported moderate osteoarthritic pain in their knees, 53.8% reported severe pain, and 36.9% faced extreme symptom in their knees.

Distribution of WOMAC score among the participants (n = 622).

The study also found that there were meaningful relationships between socio-demographic variables and WOMAC scores (Table 1). Age was one such factor, whereby respondents older than 70 years reported higher percentages of severe (55.1%) and extreme (37.3%) symptoms compared with respondents between 60 and 69 years. This implies that older individuals have more severe symptoms of knee osteoarthritis. Gender was also found to have an impact since more extreme symptoms were experienced by women (40.6%) compared to men (31.1%), suggesting that women tend to have more severe symptoms of knee OA.

Table 1: Association of sociodemographic status with WOMAC score (n = 622).

Education level was associated with symptom severity, with the highest percentage of extreme symptoms reported by participants with illiteracy (50%), followed by respondents with primary education (36.8%) and secondary education or higher (26%). This implies that less education is related to more severe symptoms. Marital status bore no association with WOMAC scores. Likewise, monthly income from families showed little relation to WOMAC scores, although poorer respondents (25,000 or less) reported an even higher percentage of extreme symptoms (40.5%). Financial independence was similarly not related to WOMAC scores. However, dependent individuals reported a higher percentage with extreme symptoms (38%) compared to independent individuals (35.6%), indicating that financial independence may have some but limited impact on symptom severity.

Table 2 reflects considerable correlations between diabetes, cardiovascular disease, and obesity with WOMAC scores. Participants with obesity reported higher percentages of extreme (42.3%) and severe (52.3%) symptoms compared to non-obese individuals, who indicated a lower percentage of extreme (26.5%) symptoms. This reflects that obesity considerably augments the severity of symptoms of knee osteoarthritis. In the same manner, diabetes was found to have considerable correlations with WOMAC scores. Participants with diabetes reported higher percentages of extreme (37.2%) and severe (54.7%) symptoms compared to non-diabetic individuals, who indicated a considerably lower percentage of extreme (32.3%) symptoms. This reveals that diabetes considerably enhances the severity of symptoms of knee osteoarthritis. Cardiovascular disease (CVD) was also found to have considerable correlations with WOMAC scores. Participants with CVD reported a higher percentage of extreme (44.7%) symptoms compared to non-CVD, who indicated a smaller percentage (23.7%) of extreme symptoms. This reflects that cardiovascular disease further adds to the severity of symptoms of knee osteoarthritis.

Table 2: Association of comorbidities with WOMAC Score (n = 622).

Table 3 shows the odds ratios (OR) for sociodemographic variables and for comorbidities in relation to severe and extreme knee osteoarthritic pain. Participants aged 70 years and older had more than four times higher odds for experiencing both severe (OR = 4.79, 95% CI: 2.18–10.50, p = 0.000) and extreme (OR = 4.23, 95% CI: 1.84–9.71, p = 0.001) symptoms compared to respondents 60–69 years old. These outcomes were similar in both unadjusted models as well as in adjusted ones, thereby emphasizing that age was a determining factor for symptom severity.

Table 3: Logistic regression analysis of sociodemographic status and comorbidities with WOMAC Score (Multinomial Logistic regression).

Female respondents had 2.75 times higher odds for experiencing extreme symptoms (OR = 2.75, 95% CI: 1.52–4.97, p = 0.001) compared to males, thus pointing towards gender as an influencing factor for severity in OA symptoms. Participants who were illiterate had 7.62 times higher odds for expressing extreme symptoms compared to participants with secondary education and more (OR = 7.62, 95% CI: 2.57–22.60, p = 0.000), which is a very strong relationship between lesser education and severity in OA symptoms in knees.

Individuals earning between 25,001–49,999 had 2.47 times greater odds for extreme symptoms (OR = 2.47, 95% CI: 1.19–5.13, p = 0.015) compared to those earning less than 25,000. This suggests that middle-income participants may face an increased symptom burden. Dependent individuals had 1.78 times greater odds of experiencing severe symptoms (OR = 1.78, 95% CI: 1.01–3.14, p = 0.045) compared to financially independent individuals, highlighting that financial dependence contributes to increased symptoms. Obesity was closely related to both severe and extreme symptoms. Participants with obesity had significantly greater odds for severe (OR = 3.07, 95% CI: 1.61–5.83, p = 0.001) and extreme symptoms (OR = 5.26, 95% CI: 2.65–10.47, p = 0.000). This reaffirms obesity's well-established relationship with aggravated symptoms for knee OA. Diabetes was also significantly related to symptom severity. Participants with diabetes had 6.05 times greater odds for severe symptoms (OR = 6.05, 95% CI: 2.08–17.53, p = 0.001) and 3.16 times greater odds for extreme symptoms (OR = 3.16, 95% CI: 0.97–10.30, p = 0.055), implying that diabetes aggravates symptoms for knee OA. Participants with CVD had 2.5 times greater odds for extreme symptoms (OR = 2.50, 95% CI: 1.27–4.94, p = 0.000) compared to non-CVD participants, suggesting that cardiovascular illnesses further add to symptom severity in knee OA individuals.

The model classifies 57.4% of the cases correctly, which is a reasonable performance. The AIC and BIC values indicate that the model is reasonably efficient. Multicollinearity was not observed. The results of the regression show that the most persistent and significant predictors of severity are age, obesity, and diabetes. The factors have been proven to remain significant in unadjusted and adjusted models, illustrating that they play a dominant role in predicting severity levels in the WOMAC. While other variables such as gender and education showed significant associations in the unadjusted models, their significance diminished or varied in the adjusted models, suggesting that their impact on severity may be mediated by other primary factors like age and diabetes.

Discussion

The key results of this research indicated substantial correlations between socio-demographic variables, comorbidities, and symptom severity of knee osteoarthritis measured with WOMAC scores.

While the association between age, obesity, and OA severity is well-documented in global literature [26,34], our findings provide critical insight into the magnitude of these effects within a South Asian clinical context. Unlike Western cohorts where early intervention is common, our data reveals a population where “mild” OA is absent from clinical presentation. This suggests a pattern of delayed health-seeking behavior, likely driven by the socio-economic barriers identified in this study, specifically illiteracy and financial dependence. Thus, while the risk factors are universal, their impact is amplified by the resource-constrained setting of Bangladesh.

Age was found to be a determinant of symptom severity in knee OA. Participants over 70 years old had 4.79 fold increased chances of severe symptom experiences compared to 60–69 year old participants. This is corroborative of earlier studies that indicated older people reported increased intensity of pain and functional disability related to OA compared to younger individuals [26,27]. Another similar study in Saudi Arabia similarly concluded that age was a better predictor of WOMAC severity than obesity or hypertension. In this research, participants aged ≥50 years had significantly elevated WOMAC index scores, where 15.96% of participants were rated as high-risk with severe knee OA [28].

Gender also played an important role in severity and experience of symptoms of OA of the knee. Female participants of the study were 2.75 times more prone to extreme symptoms compared to their male counterparts, as several studies have concluded that the symptoms of OA of the knee afflicted more women compared to men [29,30]. A study conducted in Saudi Arabia also revealed that 73% of the female patients who had high WOMAC scores also had high clinical OA diagnoses [28]. While unadjusted analysis suggested that female participants were more prone to severe symptoms compared to males, this association lost statistical significance in the adjusted multivariate model. This suggests that the apparent gender disparity may be mediated by other confounding factors prevalent among women in this cohort rather than gender acting as an independent predictor of severity.

The educational status contributed significantly to the severity of the symptoms of OA knees. Participants involved in this study who were illiterate had 7.62 times the opportunities of developing extreme symptoms than those who had an educational status of secondary and above. This was evident using a longitudinal study among 1,499 older adults where those without formal qualification had 4.33 more opportunities for severe functional disability [31]. Poorer educational status was also commonly associated with manual laboring occupations [32], which may amplify knee joint loading, with a corresponding increased severity of symptoms.

Income was also a contributing determinant to the severity of symptoms of OA of the knees. Participants who were of low income had 2.47-fold higher odds of extreme symptoms. The outcome showed similarity to that of a Korean study, where the lowest-income category experienced higher prevalence of knees OA seen on radiographs (34.4%), compared to the high-income category (11.3%) [33]. Economic factors and severity of symptoms showed that considerations were affecting both function and physical impact of OA of the knees. Monthly family income showed associations with symptom severity in descriptive comparisons, but these effects were attenuated in the adjusted regression model. This indicates that income likely acts as a proxy for other determinants. For instance, lower income is often inextricably linked with lower education and higher financial dependence, which were stronger independent predictors in our analysis.

Symptom severity was also related to financial independence. Those that were dependent had 1.78 times increased risk of severe knee OA symptom presence than non-dependent participants. This was in accordance with the English Longitudinal Study of Ageing, where financial dependency partly influenced knee OA symptom presence through obesity, with more obesity found in lower-income individuals. A more intense load on the joints and increased pain were the effects of obesity [31].

Participants with obesity were found to have 5.26 times the odds of extreme knee osteoarthritis symptom development. Several studies have illustrated a direct linear association between body mass index (BMI) and increased WOMAC severity. In a cohort of 79 older adult patients with knee OA, class III obesity was linked to an 178% increased WOMAC symptom score compared to individuals with a normal BMI [34]. Additionally, a cohort study in the UK of 1,499 older patients with symptomatic knee OA also reported that 47.4% of patients were obese [31]. Moreover, a study of Chinese women with a BMI of ≥24 kg/m² and the use of oral contraceptive medications likewise reported twice the risk of knee pain [35].

Diabetes mellitus remained a robust predictor of disease burden. In the adjusted model, participants with diabetes had 6.05 times greater odds of experiencing severe symptoms (p = 0.001) compared to non-diabetics. The association with “extreme” symptoms showed a strong trend (OR = 3.16) but was borderline distinct (p = 0.055), reinforcing the substantial impact of metabolic health on joint pathology. Similar research demonstrated that the incidence of type 2 diabetes in older patients having a total knee arthroplasty due to knee OA increased to 16.1% [36]. A population study in Taiwan demonstrated that patients with type 2 diabetes (T2DM) had a 2.75-fold increased risk of developing knee OA compared to non-diabetic patients [37]. This highlights the worsening effect of diabetes in intensifying OA symptoms in the knee.

In addition, participants with CVD suffered 2.5 more extreme knee OA symptoms than those without CVD. Another study reported that 61.5% of the older population with knee OA had hypertension and 43.3% presented with dyslipidemia, two key cardiovascular risk factors [38]. A South Korean study that included 9,514 adults older than 50 years old found that hypertensive patients showed a 26% higher incidence of knee osteoarthritis [39].

Strengths and limitations

A key strength of this study is its use of the validated WOMAC index to quantify disease burden in a substantial sample of 622 patients. However, the study has limitations that must be considered. First, the recruitment of participants from tertiary healthcare centers inherently introduces selection bias. This hospital-based design captures a population with more advanced disease severity compared to community-based samples. Consequently, our findings are most applicable to clinical populations and may not be generalizable to the broader community where mild OA is more prevalent. Second, the cross-sectional nature of the data limits our ability to establish causal pathways between comorbidities and OA progression. Finally, the absence of “mild” cases in our categorization reflects the specific patient profile of tertiary hospitals in Dhaka, where individuals rarely seek specialized orthopedic care for minor symptoms.

Conclusion

The study provides compelling evidence of the impact of socio-demographic variables and comorbid conditions on the severity of knee osteoarthritis among patients in tertiary care settings in Dhaka. Increased age, female sex, low educational attainment, and the presence of comorbidities were found to significantly exacerbate symptom severity. These findings underscore that in this clinical population, OA is not merely a degenerative condition but one deeply entangled with social determinants of health.

Recommendations

It is essential to embrace an integrated healthcare strategy that integrates medical and socio-economic interventions. Programs need to be developed by policymakers to counter the socio-economic determinants of disease that affect an individual's condition by targeting education, income disparities, and improving healthcare access, particularly for vulnerable groups such as the elderly, women, and poorer and less educated individuals. As these comorbid conditions of obesity, diabetes, and cardiovascular disease substantially affect the severity of osteoarthritis of the knees, there needs to be specific screening for these conditions for particular risk groups.

Early diagnosis and treatment can also slow down the progression of symptoms and provide improved prognosis for the future. There is a requirement to have intense outreach within the community to make people aware of the risk factors related to knee osteoarthritis, especially within disadvantaged areas. Health education programs specifically designed to benefit illiterate people and the poorer population could empower them to take proactive measures to ensure their health and obtain appropriate care in time. Further research will be essential to identify the long-term influence of socio-demographic variables and comorbid conditions upon the progression of knee osteoarthritis. Longitudinal studies have the potential to identify association and influence the development of more efficacious, tailored approaches to managing knee osteoarthritis. The healthcare systems should incorporate integrated care strategies that incorporate physical rehabilitation, obesity and weight loss, diabetes control, and cardiovascular disease monitoring under a unified framework to manage knee osteoarthritis. A multidisciplinary strategy would provide holistic care to patients, enhancing both their physical function and quality of life.

Supporting information

S1 AppendixInformed consent form.The written consent form was administered to the participants.(DOCX)

S2 AppendixQuestionnaire.The included questions comprised the questionnaire administered to the participants.(DOCX)

S3 AppendixData.This file contains research data.(CSV)