Clinical variables associated with functional deficits in patients affected by chronic chikungunya arthralgia: A cross-sectional study

Abstract

Background

Chikungunya virus is an endemic arbovirus that affects populations worldwide. Its primary debilitating symptoms include inflammatory arthralgia, functional incapacity, and pain.

Objective

This study aims to identify factors predicting altered functional capacity in patients affected by chronic chikungunya arthralgia.

Methods

This is a cross-sectional study conducted from October 2023 to June 2024. Data were collected using the following instruments: the Health Assessment Questionnaire, the Visual Analogue Scale, the Brief Pain Inventory, the Pittsburgh Sleep Quality Index, and the Short Form-36 Health Survey. Regression analysis was performed to identify associations among the variables.

Results

We included 119 individuals infected by the Chikungunya virus. Regression analysis of VAS scores revealed that age (coefficient: −0.5532, p = 0.016) and BPI Intensity (coefficient: 1.1716, p = 0.002) were significant predictors. Older age was associated with lower VAS scores, while higher BPI Intensity correlated with higher VAS scores. The model explained 25.7% of VAS score variability (R-squared: 0.257). For HAQ scores, age (coefficient: −0.0104, p = 0.039), PSQI (coefficient: 0.2250, p = 0.002), and SF36 Physical Health (coefficient: −0.0118, p = 0.005) were significant predictors, accounting for 31.6% of the variability (R-squared: 0.316).

Conclusion

There is significant complexity in the signs and symptoms exhibited by individuals infected with the chikungunya virus. We highlight the identification of significant associations between pain and disability in individuals affected by the Chikungunya virus.

Keywords

pain chikungunya fever sleep

Introduction

Chikungunya fever, a neglected tropical disease, remains a significant public health concern in the Americas, affecting more than 1,659,167 individuals since 2016 (25.37 per 100,000 people), according to the Brazilian Ministry of Health.^1,2 The chikungunya fever outbreak in Brazil began with confirmed cases in September 2014.³ To date, several regions, particularly in the north and Northeast, continue to report hundreds of cases annually.⁴ Symptoms typically appear between 2- and 12-days post-infection, but more than half of patients develop a chronic phase of the disease that may persist for years.⁴ The acute phase is characterized by high fever, headache, fatigue, nausea, vomiting, and muscle and joint pain. The subacute phase may last up to three months, while the chronic phase is characterized by persistent polyarthralgia, lower limb edema, fatigue, and functional limitations extending beyond three months after the initial infection.⁵ The etiology of the chronic phase remains unclear, and treatment options are limited, with few studies providing robust evidence to guide clinical rehabilitation protocols.⁵

To date, studies have shown that advanced age, comorbidities such as cardiovascular diseases and preexisting rheumatologic conditions, and higher viral loads during the acute phase could be associated with chronification of pain.⁶ The chronicity of pain in patients with chronic chikungunya arthralgia results in sustained public expenditures and decreased productivity among the economically active population over an extended period.⁷ Identifying markers that predict the development of chronic pain could aid in developing policies to reduce the burden of chronic pain conditions, along with the associated costs of medical treatment and rehabilitation.⁸ In this context, sociodemographic factors, such as access to healthcare, health education, and the quality of treatment and rehabilitation can be identified, to inform models aimed at preventing pain chronicity.

Pain is the primary symptom reported during the chronic phase.^5,9,10 Still, other symptoms, such as joint edema, general fatigue, myalgia, synovitis, tendonitis, and morning stiffness, can also contribute to a decrease in functional status.^5,9,10 The chronic phase of chikungunya also leads to significant functional deficits, decreased quality of life, low sleep quality, and, in some cases, anxiety and depression.¹⁰ These disturbances interact to create a bidirectional relationship with pain. Chronic pain impairs sleep quality, which in turn heightens pain sensitivity, further compromising physical function and overall health.^11,12 It is important to note that disruptions in the pain neuromatrix and inflammatory pain, which are linked to the immune system and central inflammatory neurons, can lead to neuroplasticity dysfunctions, thereby altering pain processing in the central nervous system.^13,14 Therefore, addressing pain processing pathways is essential in the evaluation of chronic pain.

Several instruments have been employed to assess chronic dysfunctions in individuals affected by the chikungunya. These tools evaluate various aspects of health, including functional capacity, which is related to the competence of performing daily activities efficiently, pain intensity, sleep quality, and physical and mental well-being. They provide a comprehensive overview of the disease's impact on patients’ lives, allowing for a detailed assessment of physical limitations, pain symptoms, and overall quality of life impairments.^15–19 The use of these scales, which demonstrate high sensitivity and specificity, facilitates the identification of functional disorders and supports the development of targeted rehabilitation strategies to address primary clinical symptoms. Additionally, investigating clinical factors associated with chronic chikungunya arthralgia may provide valuable insights into the associations between clinical markers and disease-related functional impairment.

Understanding the factors contributing to functional capacity in patients with chronic chikungunya arthralgia will help optimize healthcare approaches and improve existing treatment models. This study aims to identify predictors of altered functional capacity in patients affected by chronic chikungunya arthralgia.

Methods

Study design

This is a cross-sectional analysis of patients with chronic chikungunya arthralgia (n = 119) in Natal, Brazil. This study was approved by the Research and Ethical Committee of the Federal University of Rio Grande do Norte (Registration number: 6422063) and followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE),²⁰ Declaration of Helsinki and the Brazilian research ethics regulations according to the Resolution n° 466/2012. We conducted the study at the Department of Physical Therapy at the Federal University of Rio Grande do Norte from October 2023 to June 2024. Participants who agreed to take part in the study provided written informed consent by signing an Informed Consent Form.

Participants

The participants included fulfilled the following inclusion criteria: patients of both sexes, aged 18 to 70 years, with a confirmed diagnosis of chronic chikungunya (at least three months post-infection), as determined by the detection of IgG and IgM antibodies using enzyme-linked immunosorbent assay (ELISA) and/or real-time PCR, along with a clinical diagnosis. Additionally, patients had to report a pain intensity of 3 or higher according to the VAS and be in the subacute or chronic phase of the disease. Patients were excluded if they had a previous medical diagnosis of rheumatic diseases, such as gout, lupus, rheumatoid arthritis, or fibromyalgia; infectious diseases; neurological conditions such as dementia, Alzheimer's, Parkinson's disease, motor neuron diseases, or stroke; or severe cognitive disorders, such as depression or generalized anxiety disorder.

Variables and measurements

During the baseline assessment, two trained physical therapists collected demographic and clinical data from the participants. Sociodemographic variables included sex (female or male), age (years), weight (kilograms), height (meters), time to diagnosis of chikungunya (years), educational level (illiterate, primary, secondary, or tertiary education), marital status (single, married, divorced, widowed, or preferred not to answer), income (1 minimum wage; between 2 and 3 minimum wages; >4 minimum wages; or no answer), and race/ethnicity (white, asian, black, mixed race, indigenous, don’t know, or preferred not to answer), analyzed through a multiple-choice questionnaire developed by the research team.

The Health Assessment Questionnaire (HAQ), which can be self-filled, is an instrument that assesses the level of functional capacity.²¹ Originally developed in 1980, it was one of the earliest instruments within the PRO (Patient-Reported Outcomes) framework. The HAQ became one of the most frequently cited and utilized tools in the management of rheumatic diseases.²¹ The Brazilian version of the HAQ presents good reproducibility (ICC: 0.75), construct, and discriminant validity. The questionnaire presents 20 items, divided into 8 categories: dressing, rising, eating, walking, hygiene, reach, grip, and usual activities assessed over the past week. The questionnaire presents 4 levels and ranges from 0 to 3. The scores are interpreted as follows: 0 = no difficulty, 1 = some difficulty, 2 = much difficulty, and 3 = unable to do. Each category includes 2 to 3 questions, with the highest score within these subcategories determining the total score for the corresponding domain.²¹ Additionally, the use of assistive devices contributed to an increased score, ensuring a more accurate representation of the disability.²¹

The Visual Analogue Scale (VAS) for pain was employed on a horizontal line 100 mm in length, with indications at each end representing pain classifications according to intensity, ranging from ‘No pain’ to ‘Worst unimaginable pain,’ with a score scale from 0 to 100 respectively.²² The VAS was self-filled, with volunteers marking the point that best represented their pain intensity at the moment.²² This instrument, validated for one-dimensional measurement properties, has been translated into Brazilian Portuguese and included in this project to assess the highest pain intensity present at the moment.

The Pittsburgh Sleep Quality Index (PSQI), developed by Buysse, assessed sleep quality over one month. The PSQI is a standardized questionnaire validated in Brazil, presenting high internal consistency (Cronbach’ α: 0.82).²³ This self-assessment questionnaire contains 19 individual items that generate 7 component scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medications, and daytime dysfunction.²³ Each component is scored on a scale that ranges from 0 to 3. The sum of these scores results an overall score ranging from 0 to 21, with higher scores indicating poorer sleep quality.²³ For statistical analysis PSQI was categorize as good sleep quality (<5 points), poor sleep quality (>5 points)¹⁹ and sleep disturbance (>10 points).²⁴

The Brief Pain Inventory short form (BPI) is a self-filled questionnaire consisting of 9 items that evaluate pain intensity (sensory dimension), frequency, and the degree to which pain interferes with the patient's life (reactive dimension).²⁵ Initially validated for patients with cancer pain, it has also been validated for various other populations, such as patients with low back pain and chronic non-malignant pain. The questionnaire assesses pain from multiple dimensions, including pain location, comparison of pain intensity extremes, treatment analysis, relief resulting from treatment, and the impact of pain on daily life.²⁵ The questions are rated on a numerical scale from 0 to 10, with a score of zero indicating “no pain” and a score of ten representing “the worst pain imaginable.” The reactive dimension is assessed using the same scale, where zero signifies “does not interfere” and ten represents “completely interferes”. This dimension includes subdomains such as the ability to walk, work, general activity level (activity subdomain), and aspects like enjoyment of life, mood, and sleep (affective subdomain).²⁵

The questionnaire Short Form (SF-36) assessed the quality of life. The SF-36 was translated into Portuguese language and validated by Ciconelli in 1997, adhering to the required steps outlined by the expert committee.²⁶ The SF-36 is a reliable and valid questionnaire to measure quality of life, with intra-reliability ranging from 0.44 to 0.84 and inter-reliability ranging from 0.55 to 0.81. The SF-36 comprises 36 items grouped into eight scales, evaluating various dimensions of quality of life. These eight domains are scored on a scale that ranges from 0 to 100, including physical functioning, role limitations due to physical health, bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems, and mental health. A higher score reflects better health status.²⁶ Physical and emotional scores of SF-36 were used for statistical analysis.

Sample size

We calculated the sample size using GPower 3.1 (Heinrich-Heine-Universität Düsseldorf). The HAQ was considered the primary outcome, with linear multiple regression as the analytical method. We aimed for a statistical power of 99%, an alpha error of 1%, an effect size of 0.3, and 10 predictors, yielding a required sample size of 76 individuals. However, we included an additional 43 participants to accommodate more variables in the model, resulting in a total sample size of 119.

Statistical methods

The R software (R Foundation for Statistical Computing, Vienna, Austria) analyzed the data. We represented the quantitative and qualitative sample results through mean and standard deviation, and numbers and percentages, respectively. Missing data in the dataset was addressed through two approaches. First, missing values in predictor variables were imputed using the mean of each respective column. Second, for regression analyses performed using the sm.OLS function, the missing = ‘drop’ option was applied, which automatically excluded rows with missing data in either the dependent or independent variables. This ensured that the models were fitted using only complete cases. Prior to the modeling stage, we identified factors previously associated with chronic pain in patients affected by chikungunya in the literature. In the statistical analysis of the dataset, various techniques were employed to explore the relationships and impacts of different variables on pain and health assessment scores. Descriptive statistics provided a foundational understanding of participant characteristics and variable distributions. Additionally, the linear regression analyses for specific pairwise relationships provided insights into the direct effects of individual predictors. Correlation analysis identified key relationships (Figure 1). Multiple regression models were utilized to delve deeper into predictors of VAS scores (Figure 2) and HAQ scores (Figure 3), revealing significant influences from factors like age and BPI Intensity for VAS, and age, PSQI, and SF36 Physical Health for HAQ. The effectiveness of each regression model was evaluated through R-squared and adjusted R-squared values, indicating the proportion of variance each model could explain.

Figure 1.

Correlation matrix. Body mass index (BMI). Health Assessment Questionnaire (HAQ); Visual Analogue Scale for pain (VAS); Pittsburgh Sleep Quality Index (PSQI); Brief Pain Inventory – Short Form (BPD); Short Form 36 Health Survey (SF-36).

Figure 2.

Scatter plot for VAS and age, brief pain inventory short-form (BPI) intensity.

Figure 3.

Scatter plot for health assessment questionnaire (HAQ) with Pittsburgh sleep quality Index (PSQI) and age.

Results

A total of 119 individuals affected by chronic chikungunya arthralgia completed the assessments and were included in the statistical analyses (Table 1). The correlation matrix for the univariate analysis is presented in Figure 1.

Table 1.

Sociodemographic and clinical outcomes of the study population.

Variables	Sample: 119
Age (years)^a	47.8 ± 10.2
IMC (Kg/cm²)^a	28.9 ± 4.79
Sex (female)^b	80.7
Time to diagnosis (years)	3.42 ± 2
VAS	53.35 ± 22.54
HAQ	1.12 ± 0.51
Pittsburgh^b
Good sleep quality	8.47
Poor sleep quality	47.45
Sleep disturbance	44.06
SF-36 Physical	40.66 ± 12.13
SF-36 Emotional	47.26 ± 13.83
Education level^b
Illiterate	3.4
Elementary school	12.1
High school	38.8
Undergraduate degree	45.7
Marital status^b
Single	32.8
Married	51.3
Widowed	5
Divorced	9.2
Not respond	1.7
Ethnicity^b
White	41.2
Yellow	6.7
Brown	40.3
Native	6.7
Income^b
1 minimum wage	27.7
Between 2 and 3 minimum wages	40.3
>4 minimum wages	21.0
No answer	10.9

Continuous data represented as mean and standard deviation.

Categorical data represented as percentage. Health Assessment Questionnaire (HAQ); VAS; Pittsburgh Sleep Quality Index (PSQI); Brief Pain Inventory short-form (BPI); Short Form 36 Health Survey (SF-36).

Regression analysis of VAS scores indicated that age and BPI intensity were significant predictors. Specifically, age showed a negative association with VAS scores (coefficient: −0.5532, p = 0.016), suggesting that older participants tend to report lower pain scores. Conversely, BPI Intensity demonstrated a positive association with VAS scores (coefficient: 1.1716, p = 0.002), indicating that higher intensity of BPI symptoms is associated with higher pain scores (Figure 2). The model accounted for approximately 25.7% of the variability in VAS scores (R-squared: 0.257), with an adjusted R-squared of 0.141, confirming the model's significance with a Prob (F-statistic) of 0.00906.

For HAQ scores, the regression model identified age, PSQI, and SF-36 Physical Health as significant predictors (Figure 3). Age showed a significant negative association with HAQ scores (coefficient: −0.0104, p = 0.039), indicating that increasing age is associated with lower HAQ scores. The PSQI had a positive association (coefficient: 0.2250, p = 0.002), suggesting that poorer sleep quality correlates with higher HAQ scores. Additionally, SF36 Physical Health displayed a negative relationship (coefficient: −0.0118, p = 0.005), indicating better physical health correlates with lower HAQ scores. This model explained about 31.6% of the variability in HAQ scores (R-squared: 0.316), with an adjusted R-squared of 0.209, and the overall model was statistically significant (Prob (F-statistic): 0.000494). The supplementary includes presents the Q-Q plots of the outcomes.

Discussion

This cross-sectional study of 119 individuals with chronic chikungunya arthralgia identified key predictors of pain and functional disability. Our findings highlight those functional scales targeting chikungunya-related symptoms effectively identified significantly predictors including pain intensity, age, sleep quality, and overall quality of life.

VAS pain scores, age, and BPI intensity were identified as significant predictors. Age was inversely related to VAS scores, indicating that older participants reported lower pain levels. In contrast, higher BPI intensity was positively associated with greater pain. The model accounted for 25.7% of the variability in VAS scores. Additionally, the HAQ, age, PSQI, and SF-36 were significant predictors of functional disability. Age was negatively associated with HAQ scores, while poor sleep quality (PSQI) was positively correlated with HAQ. Better physical health (SF-36) was linked to lower HAQ scores. This model explained 31.6% of the variability in HAQ scores, with both models being statistically significant. Supporting our findings, previous studies have reported chikungunya-related signs and symptoms worldwide that closely align with those identified in this study.²⁷ These data may support clinical interventions targeting key predictors to address individuals’ specific needs.

Our study provides valuable insights into the factors associated with pain perception and functional disability in individuals affected by chronic chikungunya arthralgia.⁶ Sociodemographic and clinical variables emerged as significant predictors for both pain and intensity.^6,28,29 The negative association between age and VAS scores suggests that older individuals reported lower pain levels. This finding contrasts with previous studies in chronic pain populations, where older adults typically report higher pain levels.^30,31 However, in a large cohort study conducted in Brazil with 143,787 individuals affected by the chikungunya virus, the relative effect of the disease in individuals aged 60 years or older was lower than the estimated in younger individuals.³² The authors suggest that the interaction measure on the multiplicative scale, with a relative association of 0.42 (95% CI 0.26–0.66), indicates that the relative effect of chikungunya virus disease in individuals aged 60 years and older was smaller than the estimated effect in younger individuals.³² This unexpected finding may be attributed to differences in pain tolerance, or coping mechanisms developed over time in older patients with chikungunya-related chronic arthralgia. Another possibility is that younger individuals may have greater pain sensitivity or experience a more severe progression of disease-related symptoms. Differences in immune system function, inflammatory responses, neurotransmitter activity, and pain processing mechanisms across age groups may also contribute to these findings.^33–35 Further research is needed to elucidate the mechanisms behind this relationship.

In contrast, the positive association between BPI intensity and VAS scores confirms that individuals with higher BPI intensity experience more severe pain. This finding aligns with our expectations, as the intensity of disease-related symptoms such as joint inflammation and stiffness would naturally contribute to greater pain experiences.¹⁹ This reinforces the importance of monitoring symptom progression for effective pain management in this population.¹⁹ The overall model explained 25.7% of the variance in VAS scores, suggesting that additional factors not accounted for in this model may also influence pain perception.

Regarding HAQ scores, which assess functional disability, significant predictors included age, sleep quality (PSQI), and quality of life (SF-36). The negative association between age and HAQ scores suggests that as individuals age, they report lower levels of functional disability. This result may reflect the adaptation mechanisms in older patients, who might have already adjusted to living with pain and disability over a longer period.³² However, it could also indicate that younger individuals may experience more acute functional limitations or have higher expectations of physical function, thus perceiving greater disability when faced with chronic arthralgia.³²

Poor sleep quality, assessed through the PSQI, was positively correlated with HAQ scores, indicating that individuals who report worse sleep quality tend to experience greater functional disability. This is the first study to report the association between sleep quality and physical function in patients affected by chronic chikungunya arthralgia. The finding underscores the association between sleep disturbances and chronic pain, in which poor sleep exacerbates pain perception and limits daily activities.³⁶ The results suggest that patients with chronic chikungunya arthralgia experienced poor sleep quality, and that this disrupted or insufficient sleep may contribute to the severity of arthritis and pain severity.³⁶ Similarly, some authors highlight the integration of affective systems, brain neurotransmitter systems, and sociodemographic factors, emphasizing their association with pain and sleep disturbances.³⁷ This reinforces the need for interventions targeting sleep improvement as part of the comprehensive management of chronic chikungunya arthralgia.

Better physical health, as measured by the SF-36, was associated with lower HAQ scores, further emphasizing the link between overall physical health and functional ability.³⁸ Evidence also suggests a correlation between the gut microbiome, exercise, and chronic pain, allowing us to infer that a healthier lifestyle may contribute to reduced pain by reducing systemic inflammation and neurotransmitter production.³⁹ Therefore, individuals with better physical health may be more capable of performing daily activities, resulting in lower perceived disability.^2,4 This highlights the importance of maintaining physical health through rehabilitation programs and physical activity, even in the context of chronic pain.^2,4,40

It is important to highlight that identifying key predictors, as demonstrated in this study through the associations among poor sleep quality, functional disability, and physical health in individuals with chronic chikungunya arthralgia, provides valuable information for targeted interventions. Cognitive behavioral⁴¹ and sleep therapies,⁴² physical exercise,⁴³ and manual therapy⁴⁴ are specific approaches that have shown significant clinical effects with minimal adverse events. Also, evidence from proprioceptive exercises in osteoarthritis highlights the importance of targeted rehabilitation for improving motor function and alleviating disability, which could similarly benefit patients with chikungunya arthralgia.⁴⁵ Clinical interventions with multidisciplinary approaches could focus on personalized pain management strategies. This may include tailored pharmacological therapies, physical therapy, or transcranial direct current stimulation (tDCS), particularly for patients experiencing severe pain. Screening for high-risk individuals using predictors such as age, sleep quality, and pain intensity could enable early identification and intervention. These interventions could potentially improve some key predictors contributing to chronic chikungunya arthralgia. This study has some limitations that should be acknowledged. Although we identified associations with common signs and symptoms experienced by individuals affected by the chikungunya virus, frequent complications such as neurological, cardiovascular, ocular, and renal issues were not analyzed. Additionally, the reliance on self-reported measures may be a limitation; incorporating polysomnography and physical tests could help mitigate this issue. We also did not perform further analysis to calculate odds ratios for the outcomes. Furthermore, the cross-sectional study design did not allow for causal inferences, emphasizing the need for future longitudinal studies to address this limitation.

Conclusion

This study highlights the complex interaction between sociodemographic and clinical variables in influencing pain and disability in individuals affected by chronic chikungunya arthralgia. These findings have important clinical implications, as they suggest that targeted interventions, such as managing symptom intensity, improving sleep quality, and enhancing physical health, may significantly improve pain and functional outcomes. Future studies should aim to explore additional factors contributing to variability in pain and disability outcomes in this population and further investigate the observed age-related differences in pain perception and functional disability.

Highlights

Inflammatory arthralgia and functional incapacity are the most incapacitating symptoms of chronic chikungunya infection.

Older age presented a significant negative association with pain and functional disability, possibly reflecting adaptation mechanisms.

Higher BPI Intensity was positively correlated with increased pain scores, highlighting the link between symptom severity and perceived pain.

Poorer sleep quality was linked to increased functional disability, emphasizing the role of sleep in chronic chikungunya symptoms.

Footnotes

ORCID iD

Eduarda Fonseca Mendes

Ethical approval (including name of institute and number)

This study was approved by the Research and Ethical Committee of the Federal University of Rio Grande do Norte (Registration number: 6422063).

Informed consent

Initially, the researchers informed the procedures to all participants. Then, if they agreed to participate in the study, they signed the Written Informed Consent Form. This consent was signed to validate their participation in the study.

Author contributions

JSCBH and EFM: conceived and designed the experiments, collected the data, authored or reviewed drafts of the article, and approved the final draft.

ESF, ACQM and SDB: involved in the data analysis, authored or reviewed drafts of the article, and approved the final draft.

RP: conceived and designed the experiments, analyzed the data, authored or reviewed drafts of the article, and approved the final draft.

Funding

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

All data generated or analysed during this study are included in this article. Further inquiries can be directed to the corresponding author.

Supplemental material

Supplemental material for this article is available online.

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