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Determinants of health-related quality of life in south indian patients with rheumatoid arthritis: A structural equation modeling approach

1 Department of Community Medicine, Velammal Medical College Hospital and Research Institute, Madurai, Tamil Nadu, India
2 Department of Medicine and Rheumatology, Velammal Medical College Hospital and Research Institute, Madurai, Tamil Nadu, India

Date of Submission26-Mar-2022
Date of Acceptance20-Jun-2022
Date of Web Publication26-Jul-2022

Correspondence Address:
Samir Bele,
Department of Community Medicine, Velammal Medical College Hospital and Research Institute, Madurai - 625 009, Tamil Nadu
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/injr.injr_63_22


Introduction: The burden associated with rheumatoid arthritis (RA) is substantial, leading to pain, suffering, impaired physical function, disability and deterioration in quality of life of the patients. Very few studies evaluating health-related quality of life (HRQOL) and its determinants have been published among RA patients in Southern India. The aim of the present study is to investigate the various dimensions of HRQOL and its relationship with various sociodemographic characteristics, functional status and disease activity using a structural equation modeling (SEM) approach in patients with RA.
Materials and Methods: A cross-sectional study was conducted among 110 patients attending tertiary care teaching hospital. SF 36 was used to assess the HRQOL. Disease activity score-28 (DAS28) was used to measure the disease activity and Health Assessment Questionnaire Disability Index (HAQ-DI) was used for measurement of functional disability. SEM analysis was performed to test and evaluate the structural relationships of the model using R Programming.
Results: The mean age of patients was 44.85 ± 11.25 years and 92 (83.6%) were female. Lower HRQOL scores were obtained in the domain of role functioning/physical 48.86 (±40.55), general health 48.27 (±14.92) and physical functioning 40.45 (±23.76). SEM results showed that HAQ–DI and DAS28 were covariance with each other (r = 0.54, P = 0.039), HAQ-DI was a significant predictor of GenPHYS (P = 0.001) and DAS28 was a significant predictor of GenPHYS (P = 0.001) and GenMENT (0.025).
Conclusions: Impact of RA was substantial in both physical and mental domains of HRQOL. The functional disability was having an impact on physical health, whereas disease activity was associated with physical and mental health domains of HRQOL.

Keywords: Disease activity score 28, HAQ-DI, health-related quality of life, rheumatoid arthritis, structural equation modeling

How to cite this URL:
Bodhare T, Bele S, Nallasivan S, Anto J V. Determinants of health-related quality of life in south indian patients with rheumatoid arthritis: A structural equation modeling approach. Indian J Rheumatol [Epub ahead of print] [cited 2022 Dec 5]. Available from:

  Introduction Top

Rheumatoid arthritis (RA) is a chronic, symmetric polyarthritis causing joint damage that inevitably progressed to disability. The disease takes its toll on functional status of the patient leading to impaired physical function, and deterioration in quality of life. The public health burden associated with RA is substantial, including pain, suffering, increased health care utilization, significantly impacting the patients and their families.[1]

The health-related quality of life (HRQOL) is a multi-dimensional and subjective construct which includes the perception of a person's physical, psychological, social, and spiritual well-being in the context of their health conditions and treatment outcomes.[2] It is one of the powerful predictors of morbidity and mortality and is increasingly recognized as a crucial outcome in clinical practice and research. It has become a valid indicator of measuring the quality of health care delivery and treatment outcomes and shall be an integral part of health surveillance for better monitoring of disease burden especially in chronic diseases like RA. Its evaluation shall become a part of everyday clinical practice assessing the influence of disease and focusing on comprehensive care incorporating the bio-psycho-social aspect of a patient's health.[3],[4]

Several instruments have been developed to assess the quality of life and can broadly be categorized into global, generic, and disease-specific instruments.[5]

Studies have shown that there are several factors like socio-demographic, clinical, and psychosocial factors which affect all the aspects of the HRQOL. Age, gender, level of education, socioeconomic status (SES) showed an association with HRQOL.[6] Similarly, several diseases related factors like articular and extra-articular manifestations, disease activity, and functioning impairment, affect HRQOL adversely. Regular assessment of disease activity is crucial for the management of RA and instrument like disease activity score-28 (DAS28) is available for the assessment. However, the utility of DAS28 in evaluation of the disease activity has been grossly neglected in India.[4],[7]

Globally, around 3.4 million (95% UI 2.6–4.4) DALYs are attributed to RA and there is a significant increase in rates in the recent years.[8] In India, RA is predominantly affecting the rural areas and younger women. Limited data are available on evaluation of the overall burden of RA, and HRQOL significantly impacting the quality of care to such patients.[9]

There is an unmet need to sensitize the healthcare providers to understand the importance of various aspects of quality of life of patients suffering from RA and its correlates which will help them in predicting the course of illness and better monitoring of disease burden to plan and intervene to improve overall wellbeing of patients. Similarly, very few studies evaluating HRQOL among RA patients have been conducted in India especially in the southern part. Considering the epidemiological diversity within the country, the present study was aimed to investigate the various dimensions of HRQOL and its relationship with various demographic and clinical parameters, functional status and disease activity using a structural equation modeling (SEM) approach in RA patients attending the tertiary care hospital in south India.

  Materials and Methods Top

Study design and setting

A hospital based cross-sectional study was conducted during October 2020–September 2021 among patients attending the rheumatology clinic, department of General Medicine of a tertiary care teaching institute.


The study sample consisted of patients having age >18 years, suffering from RA diagnosed by a Rheumatologist as per the American College of Rheumatology/European League Against Rheumatism 2010 criteria for RA classification.[10] Patients having co-morbid conditions, critically ill, pregnant females and patients not willing to participate were excluded from the study. A total of 110 patients participated in the study through convenient sampling. The approval from the Institutional Ethics Committee of the Institute was obtained before the starting the data collection (IEC approval No: VMCIEC/37/2019, Dated: September 18, 2019). The purpose of the study and nature of questions were explained to the patients and written informed consent was obtained.

Data sources/measurement

A semi-structured questionnaire was administered to the patients which consisted of socio-demographic characteristics, clinical parameters and medication details. The Medical Outcomes Study Short-Form Health Survey (SF-36) was used to assess the HRQOL, DAS28 was used to measure the disease activity and Indian version of the HAQ-DI was used for the measurement of functional disability among the patients.

SF 36 is a disease-independent tool used to assess health outcomes among patients suffering from various chronic diseases like RA and has been extensively used in several countries including India. It captures 8 different health concepts viz. physical functioning, bodily pain, role limitations due to physical health problems, role limitations due to personal or emotional problems, emotional well-being, social functioning, energy/fatigue, and general health (GH) perceptions. In SF-36 analysis, the raw scores are converted into transformed score on a 0–100 range for 8 subscales wherein the high score defines a more favorable health state or a better quality of life.[11],[12],[13]

The Stanford Health Assessment Questionnaire is a popular instruments used globally for assessing the patient's level of functional ability in many disease areas, including RA. The current study utilized the Indian version of Health Assessment Questionnaire Disability Index, which has shown to have a very good sensitivity, test-retest reliability and construct validity. It consists of total 12 questions relevant to the Indian population and the total scores obtained divided by 12 gave the disability Index (range 0–3) with the higher score reflecting the greater level of disability.[14],[15]

The DAS28 was utilized to assess the RA disease activity. It is a simple and widely used instrument for monitoring of disease activity in daily clinical practice consisted of measurement of a 28 tender joint count, a 28 swollen joint count, erythrocyte sedimentation rate or C-reactive protein, and a GH assessment on a visual analog scale. The overall range of the scores for DAS28 is 0–9.4. The level of RA disease activity can be interpreted as low if a DAS28 score is ≤3.2, a moderate disease activity if the score is between 3.2 and ≤5.1 and high disease activity for score >5.1. A score <2.6 corresponds with being in remission according to the American Rheumatism Association criteria.[16],[17]

Statistical methods

We analyzed the data using R Programming. The SES of the patient was calculated using the modified BG Prasad's classification and anemia status was determined according to the cutoff values recommended by the World Health Organization. Anemia was considered for males with hemoglobin <13 g/dL and females <12 g/dL.[18],[19] Cause and effect relationship of observed variables such as socio-demographic variables, disability index, DAS28 and HRQOL of RA patients is assessed by multiple linear regression models. The regression model included the various domains of HRQOL as a dependent variable and DAS28, duration of illness, HAQ-DI and SES as independent variables. Invariance and multicollinearity of the endogenous variables and structural relationship of latent variables are dealt with the aid of SEM. The latent variable “GenPHYS” was composed of four subscales of the SF-36 which includes physical functioning, role functioning/physical, bodily pain and role functioning/emotional whereas the latent variable “GenMENT” was composed of the subscales consisting of GH, social functioning, emotional wellbeing and energy/fatigue.[20],[21] HAQ-DI, DAS28, socio-demographic and clinical characteristics of the patients were selected as manifest variables. The relationship between manifest variables and latent variables were assessed using SEM.

  Results Top

Of the 110 patients, 92 (83.6%) were female. The mean age of the patients was 44.85 ± 11.25 years. The majority 81 (73.6%) had completed their education up to school level (higher secondary education). As per BG Prasad classification 75 (68.2%) belonged to the middle class and 2 (1.8%) were belonged to an upper class. The mean body mass index scores of the patients was 25.43 (±4.35) and around 56 (51%) were overweight/obese. The majority of patients were suffering from RA for a period of 1–5 years 58 (52.7%) and more than 5 years 39 (35.5%). The majority of the patients 105 (95.5%) had articular manifestation, 10 (9.1%) of the patients had extra articular manifestation and 74 (67.3%) were anemic [Table 1].
Table 1: Sociodemographic and clinical characteristics of rheumatoid arthritis patients

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[Table 2] shows the HRQOL-SF36, DAS28 and HAQ-DI scores of the patients. Quality of health indicators such as social functioning, role functioning/emotional, emotional well-being, energy/fatigue and pain had the higher scores like 61.82 (±23.39), 60.61 (±42.16), 58.76 (±13.35), 57.14 (±16.30) and 52.14 (±26.99) respectively when compared with the other subscales of SF 36 like role functioning/physical 48.86 (±40.55), GH 48.27 (±14.92) and physical functioning 40.45 (±23.76) which had the lower scores. The mean DAS28 score was 4.82 (±1.05) and the majority of them 75 (68.2%) were having moderate disease activity. The mean HAQ-DI score was 1.63 (±0.91) and a total of 52 (47.3%) were having severe disabilities.
Table 2: Mean scores of Health Assessment Questionnaire-Disability Index, Disease Activity Score-28 and health-related quality of life in rheumatoid arthritis patients

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[Table 3] shows the multiple linear models of HRQOL of RA patients. The model specified that age and gender are the least important independent variables and hence excluded from the model. Physical functioning of the RA patients was significantly associated with duration of illness (1–5 years-β = −16.27; P = 0.001, >5 years -β = −28.05; P = 0.001), DAS28 (β = −12.68; P = 0.000), HAQ-DI (β = −3.66; P = 0.000) scores.
Table 3: Impact of sociodemographic variables, Health Assessment Questionnaire-Disability Index and Disease Activity Score-28 on the Health-related quality of life using multiple linear models

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Role functioning/physical of the RA patients was associated with SES, duration of illness, and HAQ-DI. More than 5 years of duration of illness was negatively associated with role functioning/physical (β = −21.53; P = 0.005). Similarly, upper middle (β = 28.69; P = 0.041), and middle class status (β = 22.82; P = 0.005), were positively associated with role functioning/physical.

Additionally, high DAS28 scores were significant predictors of several HRQOL domains like role functioning/emotional (β = −12.04; P = 0.002), social functioning (β = −5.47; P = 0.021), and GH (β = −3.22; P = 0.002), whereas high HAQ-DI scores were significantly associated with emotional wellbeing (β = −8.32; P = 0.039), and bodily pain (β = −9.33; P = 0.001).

Lower SES was significantly associated with the reduced scores of energy/fatigue (β = −27.95; P = 0.002), emotional well-being (β = −26.52; P = 0.001), social functioning (β = −20.99; P = 0.041) and GH (β = −68.39; P = 0.001), whereas duration of illness was found to be associated with reduced scores in emotional well-being (β = −4.36; P = 0.055).

[Table 4] includes two structural equation models, evaluating the relationship between the various factors and HRQOL. Model 1 has four manifest variables such as HAQ-DI, DAS28, SES and Duration of illness and two latent variables such as GenPHYS and GenMENT. These subscales were significantly associated with the latent variables in both the models.
Table 4: Estimated coefficients from structural equation modeling for health related quality of life among rheumatoid arthritis patient

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In the model 1, SES was significantly associated with HAQ-DI (P = 0.026) and DAS28 (P = 0.020) as well as with GenPHYS (P = 0.008) and GenMENT (P = 0.001). Similarly, duration of illness was also associated with HAQ-DI and DAS28, GenPHYS and GenMENT (P = 0.001, 0.001, 0.001, 0.024 respectively).

HAQ-DI was significantly associated with GenPHYS and GenMENT (P= 0.001, 0.043) and DAS28 was also found to be associated with GenPHYS and GenMENT (P = 0.001, 0.014). The model fit indices of model 1 ( χ2 = 170.07: P = 0.001; Comparative Fit Index (CFI) = 0.853, Tucker-Lewis index (TLI): 0.789; Root Mean Square Error of Approximation (RMSEA) = 0.057) reveal that the model 1 was reasonably fit [Figure 1].
Figure 1: Model 1: Structural equation models of the relationship between HAQ DI, DAS28, and HRQOL in RA Patients. Circles represent latent variables (GenPHYS and GenMENT) and squares represent observed variables (SF 36 scales). Model 2: Structural equation models of the relationship between HAQ DI, DAS28, and HRQOL in RA Patients after controlling for SES and Duration of illness. PF: Physical functioning, RP: Role Physical, BP- Bodily Pain, RE Role emotional, GH: General health, SF: Social functioning, EW: Emotional well being, VT: Vitality, SES: Socioeconomic status, HAQ DI: Health Assessment Questionnaire Disability Index, HRQOL: Health related quality of life, RA: Rheumatoid arthritis

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Model 2 is the nested model of the model 1 in which we controlled the effect of SES and duration of illness which were considered as confounding variables. It is observed that HAQ-DI is a significant predictor of GenPHYS (P = 0.001) whereas DAS28 is a significant predictor of GenPHYS as well as GenMENT (P = 0.001, 0.025). Similarly HAQ–DI and DAS28 were covariance with each other (r = 0.54,P= 0.039).

The model fit indices of model 2 ( χ2 = 104.14: P = 0.001; CFI = 0.869; TLI =0.816 RMSEA = 0.044) reveal that the model 2 was a better fit [Figure 1].

Therefore, HAQ-DI and DAS28 predict the GenPHYS whereas DAS28 predict GenMENT irrespective of SES and duration of illness.

  Discussion Top

In our study, we obtained lower scores in the domain of role functioning/physical, GH and physical functioning as compared with other subscale of the SF 36. This is similar to the findings of the other studies which reported the physical domain as a most affected domain of HRQOL.[4],[12] A systematic review and meta-analysis done by Matcham et al., showed that RA negatively impacts HRQOL and the impact is more severe on physical HRQOL domains as compared with mental well-being[13] A strong social support, especially from the family members may be attributed to the higher scores of social functioning and emotional wellbeing in Indian patients with RA.

We observed moderate disease activity among the majority of the patients (68.2%) and almost half of them (47.3%) presented with a severe functional disability. The intensity of disease activity observed among our patient is lesser as compared with the other Indian studies in which the assessment was done at the initial presentation and this reduction can be attributed to the impact of their treatment over a period of time.[7],[22]

We performed the multiple linear regression analyses to evaluate the impact of various socio-demographic variables, functional disability and disease activity on the HRQOL. High HAQ-DI scores were significant predictors of several HRQOL domains like physical functioning, role functioning/physical and bodily pain, whereas high DAS28 scores were significantly associated with physical functioning, role functioning/emotional, social functioning and GH. Socio-economic status was found to be directly associated with all domains of HRQOL except physical functioning with lower classes reflecting the poorer quality of life among the patients.

In this study, we constructed models to exhibit the relationship between several distinct variables and the domains of HRQOL among patients with RA. Most of the authors have used the correlation analysis for evaluating the various factors affecting HRQOL of RA patient.[23],[24] To our knowledge, this study is first of its kind which focuses on establishing the relationships among these variables using a SEM among south Indian patients suffering from RA. SEM is the better tool for analyzing the latent variables. In addition, through SEM analysis, we can test and evaluate multivariate causal relationships. Through this approach we found SES and duration of illness as well as DAS28 and HAQ-DI are associated with HRQOL. While components of SES (income, education, etc.) act as potential confounders, few studies have investigated and proved the causal effect of SES on HRQOL and its role in disease related outcome should be viewed carefully.[25] People belonging to lower socio-economic status confront several barriers, including availability; accessibility and affordability to health care services leading to detrimental consequences in the long run, which often are reflected in poor self-reported outcomes like disability, quality of life and disease activity indices. Similarly, longer duration of illness was found to be negatively associated with the domains of physical and emotional well being. These findings are similar to the findings of other studies in India as well as other countries.[23],[24],[25]

We obtained an inverse relationship between HAQ-DI and DAS28 with HRQOL with a greater level of disability and high disease activity leading to lower scores in GenPHYS and GenMENT resulting in poor quality of life. Several studies have shown the strong correlation between high disease activity and disability with a physical component, and mental components of HRQOL. Although we have adopted a different methodology of analysis, our finding reaffirms the earlier findings. After controlling the effect of SES and duration of illness the association between DAS28 and GenPHYS and GenMENT persists whereas HAQ-DI found to have no impact on the mental component of HRQOL. In spite of the limitation of mobility and activities, the interplay of variety of factors like social support, coping strategies and disease acceptance plays an important role in psychosocial adjustment among individuals, enabling them to adapt to the demands of the chronically ill disease and disabilities leading to better psychological well-being.[26] In the present study, we obtained better scores in the domain of social functioning, however to substantiate the optimal social support, we need further exploration using a multidimensional measure of social support among RA Patients to understand its effect on the psychological wellbeing of the patients.


The results of the study should be viewed carefully as we sampled the patients from a single hospital with relatively small sample size, which limits the generalisability of its findings to a broader population in the community. Similarly, no causal relationship can be ascertained between various factors and HRQOL by virtue of the observational nature of the study. Further exploratory studies are required to evaluate the factors like concomitant nutritional deficiency, community acquired infections, lower educational status, which are inextricably linked with lower SES.

  Conclusions Top

The substantial impact of RA was observed in both physical and mental domains of HRQOL. The findings of this study are helpful in gaining an insight into the various factors and its inter-relationship using a structural equation model. The level of disability was having an impact on physical health, whereas disease activity was inversely associated with physical and mental health domains of HRQOL after controlling the effect of SES and duration of disease. To improve the overall health of the patient, it is crucial to assess patients and intervene appropriately through a multidisciplinary approach that will improve the long term health of the patients.


We wish to thank all the patients who had spent time and participated in the study.

Financial support and sponsorship


Conflict of interest

There are no conflicts of interest.

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  [Figure 1]

  [Table 1], [Table 2], [Table 3], [Table 4]


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