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Comorbidities and health-related quality of life in Koreans with knee osteoarthritis: Data from the Korean National Health and Nutrition Examination Survey (KNHANES)

  • Hyemin Jeong,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Division of Rheumatology, Department of Medicine, Soonchunhyang University Hospital, Bucheon, South Korea

  • Sun Young Baek,

    Roles Data curation, Formal analysis, Investigation, Methodology

    Affiliation Biostatic and Clinical Epidemiology Center, Samsung Medical Center, Seoul, South Korea

  • Seon Woo Kim,

    Roles Data curation, Formal analysis, Investigation, Methodology

    Affiliation Biostatic and Clinical Epidemiology Center, Samsung Medical Center, Seoul, South Korea

  • Yeong Hee Eun,

    Roles Project administration, Resources

    Affiliation Division of Rheumatology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea

  • In Young Kim,

    Roles Project administration, Resources

    Affiliation Division of Rheumatology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea

  • Jaejoon Lee,

    Roles Supervision, Visualization

    Affiliation Division of Rheumatology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea

  • Chan Hong Jeon,

    Roles Supervision, Visualization

    Affiliation Division of Rheumatology, Department of Medicine, Soonchunhyang University Hospital, Bucheon, South Korea

  • Eun-Mi Koh,

    Roles Supervision

    Affiliation Division of Rheumatology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea

  • Hoon-Suk Cha

    Roles Conceptualization, Writing – review & editing

    hoonsuk.cha@samsung.com

    Affiliation Division of Rheumatology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea

Comorbidities and health-related quality of life in Koreans with knee osteoarthritis: Data from the Korean National Health and Nutrition Examination Survey (KNHANES)

  • Hyemin Jeong, 
  • Sun Young Baek, 
  • Seon Woo Kim, 
  • Yeong Hee Eun, 
  • In Young Kim, 
  • Jaejoon Lee, 
  • Chan Hong Jeon, 
  • Eun-Mi Koh, 
  • Hoon-Suk Cha
PLOS
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Abstract

Objectives

This study aimed to evaluate the association of knee osteoarthritis (OA) with comorbidities and health-related quality of life (HRQOL).

Methods

A total of 8,907 (weighted n = 13,687,058) participants aged ≥50 years who had undergone knee radiography were selected from the 2010–2012 Korea National Health and Nutrition Examination Survey. OA was classified into four subgroups based on the presence or absence of pain and radiographic OA (ROA): non-OA (Pain-/ROA-), pain only (Pain+/ROA-), ROA only (Pain-/ROA+), and painful ROA (Pain+/ROA+). ROA was defined as Kellgren–Lawrence grade ≥ 2. HRQOL measurements including EuroQOL visual analogue scale (EQ-VAS) scores and the five dimensions and summary index of the EuroQOL-5 dimension (EQ-5D index) were also analyzed. Multivariable logistic regression and linear regression analyses were performed.

Results

After adjustment for socioeconomic and lifestyle characteristics, cardiovascular disease, malignancy, and other comorbidities were not significantly associated with OA. Pain only and painful ROA were each significantly associated with limitations in physical activity (odds ratio (OR) 2.66, 95% CI 2.07–3.44, p < 0.001 and OR 2.83, 95% CI 2.25–3.58, p < 0.001, respectively), lower EQ-VAS (β-coefficient = -10.95, p < 0.001 and β-coefficient = -9.75, p < 0.001, respectively), and EQ-5D index (β-coefficient = -0.10, p < 0.001 and β-coefficient = -0.13, p < 0.001) compared with the non-OA group, whereas ROA only was not associated with limitations in physical activity or lower HRQOL score.

Conclusions

Comorbidities were not significantly associated with knee OA after adjustment. Knee OA was associated with physical activity and HRQOL. Painful knee OA, with or without ROA, was more strongly associated with decreased physical activity and lower quality of life than ROA without pain.

Introduction

Osteoarthritis (OA) is the most common musculoskeletal disorder and causes disability in elderly populations [1]. As the population ages, the prevalence of OA increases, and this can cause a considerable economic burden on society [2]. Elderly OA patients who have other emerging comorbidities present a challenge to treating clinicians. OA is characterized by cartilage destruction and subchondral bone remodeling, but the etiology and pathogenesis of OA remain poorly understood. Recent studies reported that proinflammatory cytokines and systemic inflammation are associated with the pathogenesis of OA [3,4]. Rheumatoid arthritis (RA) is a chronic inflammatory disease that is associated with increased prevalence of several comorbidities including cardiovascular disease, infection, malignancy, lung disease, and neuropsychiatric disease [58]. In contrast to RA, the precise relationships between OA and these various medical comorbidities remain controversial. In the Framingham Heart Study, symptomatic hand OA was associated with increased risk of coronary heart disease events [9]. In a prospective study, Rahman et al. reported that OA was associated with increased risk of cardiovascular disease [10], and a recent cohort study showed that knee OA was associated with increased risk of all-cause and cardiovascular-specific mortality [11]. Conversely, the Rotterdam study concluded that OA was not associated with increased risk of cardiovascular disease [12]. Several studies on comorbidities other than cardiovascular disease in patients with OA have been published, one of which found that OA was associated with gastritis, obesity, and respiratory infections [13].

OA is the major cause of pain in elderly populations. Arthritic pain causes functional impairment characterized by difficulty with activities of daily living [14]. Depression is associated with reported severity of pain and physical disability in patients with rheumatic disease including OA [15]. Furthermore, the presence of coexistent comorbidities increases the extent of long-term disability in patients with knee OA [16]. Leite et al. reported that OA patients showed a high frequency of metabolic syndrome and depression, which impact both pain and physical function [17]. In addition, higher rates of depression and anxiety cause lower quality of life in patients with OA [18]. Therefore, it is crucial to identify and manage disabilities and pain in patients with OA in routine practice, which will enhance patient quality of life.

However, the data regarding medical comorbidities associated with OA in previous studies were mainly from Western populations. Whether radiographic or symptomatic OA is associated with comorbidities or quality of life remains unclear. The aim of this study was to examine the association of knee OA with comorbidities and health-related quality of life (HRQOL) in a Korean adult population with knee OA compared with those of a corresponding non-OA population after adjustment for socioeconomic and lifestyle characteristics.

Methods

Study population

The Korea National Health and Nutrition Examination Survey (KNHANES) is a nationwide survey that is conducted periodically by the Korea Centers for Disease Control and Prevention to investigate the health and nutritional status of the Korean population [19]. This survey assesses the general health and nutrition status of individuals in South Korea through interviews about health and nutrition and basic health assessments. Participants were selected using the proportional allocation-systematic sampling method with multistage stratification to derive a representative Korean population. Although the individual participants are not generally representative of the Korean population, this survey provides representative estimates of the noninstitutionalized Korean civilian population by using the power of sample weight. Every year, 10,000 to 12,000 individuals in approximately 3,800 households are selected from a panel based on the National Census Data. The participation rates of the selected households in the past several cycles of the KNHANES have been high, ranging from 79% to 84%. Among the 25,534 participants in the 2010–2012 KNHANES, 10,152 participants who were 50 years of age or older were selected. Then, 949 participants for whom knee radiograph data or knee pain were missing were excluded. An additional 296 participants who were diagnosed with RA were also excluded. In total, 8,907 participants were selected for analysis. The frequency of missing data for each item was very low, with a maximum frequency of about 1% (0.97%). Written informed consent was obtained from all participants before completing the survey. This study was approved by the institutional review board of Samsung Medical Center (IRB No. 2017-03-041).

Demographic variables and data collection

The KNHANES was conducted by four special research teams, each composed of eight experts including nurses, nutritionists, and students majoring in public health. The selected professional investigator was placed at the investigation site after completing one month of education and practice. Subsequently, the ability to conduct research was verified through regular education and on-site quality management. A standardized interview was performed in participants’ homes, and an established questionnaire was used to collect information on demographic variables and socioeconomic characteristics. Specifically, data on age, sex, income, region, education, marital status, alcohol consumption, and smoking status were collected. Alcohol consumption was categorized into the following four groups based on the frequency of alcohol consumption during the past year: never, ≤ 1/week, 2-3/week, and ≥ 4/week. Income level was categorized into quartiles based on average individual monthly income. Urban and rural areas were classified by administrative district. Comorbidities were defined in the questionnaire as “Hypertension diagnosed by a physician” through a standardized interview. The question was, “Was your hypertension diagnosed by a physician?” The questionnaire consisted of three responses (1. Yes, 2. No, 3. I have never been sick before). Participants who chose 1 (Yes) were classified as having hypertension. Each interview was conducted individually by a trained professional investigator. Information was also collected on cardiovascular comorbidities including hypertension, dyslipidemia, diabetes, stroke, myocardial infarction, or angina that was diagnosed by a physician. Information was also collected on malignancies including stomach cancer, colon cancer, breast cancer, cervical cancer, lung cancer, and other comorbidities including osteoarthritis, pulmonary tuberculosis, thyroid disease, depression, atopic dermatitis, depression, chronic kidney disease, hepatitis B, hepatitis C, and liver cirrhosis that was diagnosed by a physician. Height and weight were assessed using standardized techniques and equipment. Briefly, height was measured to the nearest 0.1 cm using a portable stadiometer (Seriter, Bismarck, ND, USA). Weight was measured to the nearest 0.1 kg using a Giant-150N calibrated balance-beam scale (Hana, Seoul, Korea). Body mass index (BMI) was calculated by dividing weight by height squared (kg/m2).

Assessment of radiographic OA and knee pain

Radiographic examination of the knee, including the acquisition of bilateral weight-bearing anteroposterior and lateral (30° flexion) plain radiographs, was performed using an SD 3000 Synchro Stand (Accele Ray, Shinyoung Co., Seoul, Korea). Radiographic images were reviewed by two radiologists. The degree of radiographic knee OA was assessed according to the Kellgren-Lawrence (KL) grading system [20]. Radiographs were graded, and concordant grades were accepted by two radiologists. When there was a difference of only one grade between the two radiologists, the higher grade was accepted. If the discrepancy was greater than one grade, a third radiologist was consulted, and the grade concordant with the third grade was accepted. Both sides of the knee were graded, and the higher grade was determined as the KL grade of each participant. The inter-rater agreement between the two radiologists was 95.4%, and the kappa coefficient was 0.74. Participants were classified as having radiographic knee OA if they had a KL grade of 2 or more [21].

Self-reported knee pain (yes/no) was assessed in the standardized interview using the question, “Did you suffer from knee pain for more than 30 days during the last 3 months?” The interview was conducted individually by a trained professional investigator. Knee pain was classified as positive if `yes`was reported.

OA was categorized into four subgroups based on the presence or absence of pain and radiographic OA (ROA) [11]: 1. non-OA (Pain-/ROA-: reference group); 2. Pain only (Pain+/ROA-); 3. ROA only (Pain-/ROA+); and 4. Painful ROA (Pain+/ROA+).

Quality of life measurement

In the KNHANES, HRQOL is measured using the EuroQOL-5 dimension-3 level (EQ-5D-3L) questionnaire, the EQ-5D index, and the EuroQOL-visual analogue scale (EQ-VAS). These are instruments for measuring HRQOL developed by the EuroQOL group and use of the EQ-5D-3L and EQ-VAS was approved by EuroQOL group (http://www.euroqol.org). The EQ-5D-3L questionnaire consists of five questions for self-reported problems in five dimensions (mobility, self-care, usual activities, pain or discomfort, and depression or anxiety) [22]. There are three levels for each item (1 = no problem, 2 = moderate problem, 3 = severe problem). An EQ-5D validation study confirmed its validity and reliability in the Korean population [23]. The EQ-5D was also validated for measurement of HRQOL in patients with various rheumatic diseases [24] and osteoarthritis [25]. A summary index (EQ-5D index) can be calculated by combining all scores for the five dimensions; the summary index ranges from −0.171 to 1 [26]. The maximum score of 1 on the EQ-5D index indicates the best health, with no problems in any of the five dimensions.

Substitute a 1 in the formula if the mobility level is 2 or 3 and a 0 if the mobility level is 1. (M2, mobility level 2; M3, mobility level 3; SC2, self-care level 2; SC3, self-care level 3; UA2, usual activities level 2; UA3, usual activities level 3; PD2, pain or discomfort level 2; PD3, pain or discomfort level 3; AD2, anxiety or depression level 2; AD3, anxiety or depression level 3; N3, any dimension level 3).

Participants scored their subjective health status using the EQ-VAS with a vertical scale whose endpoints were labeled `the best health you can imagine`and `the worst health you can imagine`. Scores ranged from 0 (the worst imaginable health state) to 100 (the best imaginable health state).

Statistical analyses

To reflect representative estimates of the noninstitutionalized Korean civilian population, survey sample weights were applied in all of the analyses. The sample weights were calculated by taking into account the sampling rate, response rate, and age/sex proportions of the reference population (2005 Korean National Census registry). Univariable logistic regression analysis was performed with OA categories as dependent variables and clinical characteristics as independent variables. To analyze the effect of OA on the morbidity and quality of life, multivariable logistic regression models were computed with comorbidities as dependent variables and knee OA categories as independent variables. The models were adjusted for socioeconomic and lifestyle characteristics (age, sex, income, region, marital status, alcohol consumption, smoking status, and BMI). Odds ratios (ORs) with 95% confidence intervals (CIs) of three knee OA categories (pain only, ROA only, painful ROA) were calculated compared with the non-OA category (Pain-/ROA-) for each of the comorbidities. Multivariable linear regression analysis was performed to assess the EQ-VAS score and the EQ-5D index. Overall P-values were provided for the overall effects of clinical characteristics on the OA categories. P–values, ORs, and 95% CIs for the pairwise comparisons between the two OA categories were also presented after correction with Bonferroni`s method for multiple comparisons. Statistical analyses were performed using SAS (SAS version 9.4; SAS Institute, Cary, NC, USA). All P-values were two-sided, and a P value < 0.05 was considered statistically significant.

Results

The weighted (n = 13,687,058) demographics and clinical characteristics of the study population are presented in Table 1. Mean participant age was 62.2 years, and 53.2% of the participants were female. The prevalence of college graduates was 11.1%, and mean BMI was 24.0 kg/m2. The prevalence of non-OA (Pain-/ROA-), pain only (Pain+/ROA-), ROA only (Pain-/ROA+), and painful ROA (Pain+/ROA+) was 59.4%, 7.9%, 20.7%, and 12.0%, respectively.

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Table 1. Weighted baseline characteristics of the study population (unweighted, n = 8,907; weighted, n = 13,687,058).

https://doi.org/10.1371/journal.pone.0186141.t001

The clinical characteristics analyzed according to knee OA category are shown in Table 2. Overall P-values were given for each variable. Age, sex, income, region, education, alcohol consumption, smoking status, BMI, hypertension, dyslipidemia, diabetes, myocardial infarction or angina, asthma, thyroid disease, and depression all had an effect on OA category. Females exhibited increased odds of OA compared with males and had significantly increased risk of having pain only (OR 2.12, 95% CI 1.37–2.69, p < 0.001), ROA only (OR 2.20, 95% CI 1.86–2.59, p < 0.001), and painful ROA (OR 6.59, 95% CI 5.34–8.14, p < 0.001). Subjects who lived in rural areas showed increased risk of having pain only (OR 1.29, 95% CI 1.02–1.64, p = 0.029), ROA only (OR 1.25, 95% CI 1.04–1.50, p = 0.012), and painful OA (OR 1.87, 95% CI 1.50–2.33, p < 0.001) compared with subjects who lived in urban areas. Smoking and alcohol consumption were less common in subjects with OA than in the non-OA group. Current smokers were less likely to have pain only (OR 0.55, 95% CI 0.39–0.79, p < 0.001), ROA only (OR 0.40, 95% CI 0.31–0.53, p < 0.001), and painful OA (OR 0.24, 95% CI 0.17–0.35, p < 0.001) compared with never smokers. Subjects who consumed alcohol more than four days a week were less likely to have pain only (OR 0.48, 95% CI 0.29–0.79, p = 0.004), ROA only (OR 0.64, 95% CI 0.46–0.89, p = 0.002), and painful ROA (OR 0.23, 95% CI 0.15–0.37, p < 0.001) compared with never drinkers. The prevalence of cardiovascular risk factors and cardiovascular disease, including hypertension, dyslipidemia, diabetes, and myocardial infarction or angina, was higher in participants with OA compared with non-OA participants. Subjects with hypertension (OR 2.64, 95% CI 2.16–3.22, p < 0.001), dyslipidemia (OR 1.33, 95% CI 1.01–1.68, p = 0.014), and diabetes (OR 1.45, 95% CI 1.12–1.88, p = 0.002) showed increased risk of painful ROA. There was no significant association between solid malignancy and OA category. Subjects with asthma (OR 2.34, 95% CI 1.54–3.58, p < 0.001) and thyroid disease (OR 1.55, 95% CI 1.04–2.29, p = 0.025) were more likely to have painful ROA than non-OA. Depression was associated with increased risk of pain only (OR 2.07, 95% CI 1.37–3.12, p < 0.001).

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Table 2. Clinical characteristics and comorbidities across knee status categories.

https://doi.org/10.1371/journal.pone.0186141.t002

The physical activity and HRQOL measures, including the weighted proportions of problems of each of the EQ-5 dimensions, the EQ-VAS scores, and the EQ-5D indices, are presented in Table 3. Activity limitation, cause of activity limitation, mobility, self-care, usual activities, pain/discomfort, anxiety/depression, EQ-VAS, and EQ-5D index were significantly associated with OA category. Participants with limited physical activity were more likely to have pain only (OR 3.27, 95% CI 2.43–4.40, p < 0.001) and painful ROA (OR 4.70, 95% CI 3.68–6.00, p < 0.001) compared to those with no physical limitations. Limited physical activity was not significantly associated with ROA only (OR 1.23, 95% CI 0.98–1.54, p = 0.097). Participants who had severe problems with mobility (OR 30.42, 95% CI 13.58–68.14, p < 0.001), self-care (OR 12.20, 95% CI 4.44–33.51, p < 0.001), usual activities (OR 17.76, 95% CI 9.55–33.02, p < 0.001), pain/discomfort (OR 25.49, 95% CI 16.02–40.56, p < 0.001), and anxiety/depression (OR 7.13, 95% CI 3.23–15.75, p < 0.001) were more likely to have painful ROA compared with participants with no such problems. Participants who had severe problems with mobility (OR 9.84, 95% CI 3.75–25.83, p < 0.001), self-care (OR 7.08, 95% CI 1.87–26.80, p < 0.001), usual activities (OR 8.30, 95% CI 4.00–17.23, p < 0.001), pain/discomfort (OR 12.11, 95% CI 7.11–20.62. p < 0.001), and anxiety/depression (OR 8.36, 95% CI 3.71–18.82, p < 0.001) were more likely to have pain only compared with participants with no such problems. There was no association with ROA only and severe problems with mobility (OR 1.15, 95% CI 0.39–3.38, p = 1.000), self-care (OR 1.19, 95% CI 0.26–5.41, p = 1.000), pain/discomfort (OR 1.37, 95% CI 0.80–2.34, p = 0.710), or anxiety/depression (OR 0.98, 95% CI 0.31–3.07, p = 1.000), while there was a significant association with usual activities (OR 2.89, 95% CI 1.40–5.98, p = 0.001). Increased EQ-VAS score was associated with decreased risk of pain only (OR 0.97, 95% CI 0.97–0.98, p < 0.001) and painful ROA (OR 0.97, 95% CI 0.96–0.97, p <0.001). EQ-VAS score was not significantly associated with ROA only (OR 0.99, 95% CI 0.99–1.00, p = 0.055). Increased EQ-5D index showed significantly lower risk of pain only, ROA only, and painful ROA than non-OA (OR 0.001, 95% CI 0.000–0.003, p < 0.001, OR 0.141, 95% CI 0.059–0.336, p < 0.001, and OR 0.001, 95% CI 0.000–0.001, p < 0.001, respectively).

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Table 3. Physical activity and health-related quality of life measures across knee status categories.

https://doi.org/10.1371/journal.pone.0186141.t003

Table 4 shows the adjusted ORs for medical comorbidities by knee OA category compared with non-OA. After adjusting for socioeconomic and lifestyle characteristics (age, sex, income, region, education, marriage, alcohol consumption, smoking status, and BMI), OA was not associated with cardiovascular disease. The prevalence of colon cancer was significantly decreased in subjects with ROA only compared with non-OA subjects. The pain only group was associated with increased prevalence of asthma, thyroid disease, depression, and atopic dermatitis compared with the non-OA group. The prevalence of physical activity limitations was significantly increased in the pain only and painful ROA groups compared with the non-OA group.

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Table 4. Adjusted ORs (95% CIs) for medical comorbidities by knee OA category compared with the non-OA (Pain-/ROA-) group.

https://doi.org/10.1371/journal.pone.0186141.t004

Compared with the non-OA group, the pain only and painful ROA groups were significantly associated with decreased EQ-VAS score and decreased EQ-5D index after adjustment for socioeconomic and lifestyle characteristics (Table 5).

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Table 5. Multivariable linear regression model for EuroQOL score and EQ-5D index by knee OA category compared with the non-OA (Pain-/ROA-) group.

https://doi.org/10.1371/journal.pone.0186141.t005

Discussion

We investigated the comorbidities and HRQOL of patients with knee OA using data from a nationwide survey conducted by the Korean government. We found that cardiovascular disease was not significantly associated with OA. These findings corresponded well with those of a previous study reporting that OA is not a significant predictor of incident cardiovascular disease in elderly Japanese-American males [27]. However, the findings of the present study contrast with the results of the US National Health and Nutrition Examination Survey [28]. The US survey reported that US adults with OA have a high prevalence of cardiovascular risk factors compared with an age- and sex-matched general population without arthritis. In the Canadian Community Health Survey, OA was associated with increased prevalence of cardiovascular disease [29]. Although a recent meta-analysis showed that OA is a significant risk factor for cardiovascular disease [30], this topic remains controversial. In contrast to OA, the incidence of cardiovascular disease is higher among patients with RA [31]. The increased risk of cardiovascular disease observed in patients with RA is comparable to the risk in patients with type 2 diabetes mellitus [32,33]. Autoimmune diseases such as RA and systemic lupus erythematosus increase the risk of cardiovascular morbidity and mortality. Rheumatoid joints and atherosclerotic lesions share common proinflammatory features [34]. Moreover, systemic inflammation in autoimmune disease causes endothelial dysfunction and accelerates atherosclerosis; failure to control this inflammation leads to atherosclerosis [3537]. OA is classified as a non-inflammatory type of arthritis. However, evidence of low-grade systemic inflammation in OA exists [38,39]. Synovitis is present in a significant proportion of patients with primary OA, and inflammation has been implicated in the pathogenesis of OA [40]. Nielen et al. reported that the prevalence of cardiovascular disease is increased to similar levels in patients with inflammatory arthritis and diabetes mellitus, while OA is not associated with cardiovascular disease [41]. Systemic inflammatory load is critical to the development of cardiovascular disease. The findings of the current study suggest that systemic inflammation in OA is insufficient to drive the development of cardiovascular disease.

However, many published studies have reported that musculoskeletal disease causes metabolic syndrome. Metabolic syndrome components include central obesity, hypertension, impaired fasting glucose, and dyslipidemia. The presence of metabolic syndrome is significantly associated with the risk of knee OA [42,43]. The Japanese Research on Osteoarthritis Against Disability (ROAD) study also reported that knee OA is associated with components of metabolic syndrome, and that the number of metabolic syndrome components is significantly associated with the presence of knee OA [44]. Metabolic syndrome was a potential risk factor for disability in the elderly US population in the National Health and Nutrition Examination Survey (NHANES) [45]. In the Framingham osteoarthritis study, metabolic syndrome was associated with the incidence of both radiographic OA and symptomatic OA, but these associations were no longer significant after BMI adjustment [46]. Overweight is a well-known risk factor for knee OA due to abnormal knee joint loading [47]. Also, overweight (especially central obesity) is associated with increased release of adipokines by abdominal adipose tissue, which results in low-grade inflammatory status in many peripheral tissues, including joint tissue [48]. In the Michigan Study of Women's Health Across the Nation, serum leptin level was associated with knee OA [49]. Moreover, adipose tissue in the infrapatellar fat pads has been considered a potential source of adipokines [50]. Inflammation, including synovitis and effusion, is associated with responsiveness of the peripheral nociceptive neurons, resulting in pain sensitization in knee OA [51,52]. Pain in knee OA caused by synovial inflammation is related to decreased morbidity, which leads to obesity. Increased systemic inflammation caused by adipokines leads to metabolic syndrome [53]. Metabolic syndrome is associated with increased risk of cardiovascular disease [54,55], and both metabolic syndrome and increased BMI are risk factors for knee OA. Multiple factors are related to incidence of knee OA, and the interactions between metabolic syndrome, cardiovascular disease, and OA remain unresolved. In the current study, we did not identify an association between knee OA and cardiovascular disease. Also, metabolic syndrome has not been reported to be significantly associated with knee OA in the Korean population [56]. BMI is lower in Asian populations than in Western populations [57]. This suggests that factors other than body weight might be more highly associated with the pathogenesis of knee OA in Korean patients and that lower adipokine level might result in lower cardiovascular disease risk in the Korean population. However, we could not determine causality due to the cross-sectional nature of this study. Further investigation is needed regarding the causality of the relationships between knee OA and cardiovascular comorbidities.

Chronic inflammation is also associated with cancer risk. In the current study, malignancy was not significantly associated with OA, which is similar to the results obtained in a Western study [13]. Subjects in the ROA only group in our study were at lower risk of colon cancer. Nonsteroidal anti-inflammatory drugs (NSAIDs) decrease the risk of colorectal cancer by cyclooxygenase (COX) regulation [58]. Using NSAIDs in the management of OA might result in a low prevalence of colon cancer in patients with OA. However, we have no data on the use of NSAIDs in subjects with OA and thus could not draw conclusions between cancer and OA in the current study. Moreover, only the ROA only group showed a statistical significant relationship between OA and colon cancer; thus, it is difficult to reach any definitive conclusions. Inflammatory cytokines such as IL-6, CRP, and TNF-alpha have been shown to be associated with cancer incidence [59]. Considering that chronic inflammation is also associated with the risk of cancer and the findings of the current study, we suggest that OA is not associated with increased risk of malignancy. In the pain only group, the prevalence of asthma, thyroid disease, depression, and atopic dermatitis was significantly higher than that in the non-OA group. A Western study showed that the prevalence of endocrine disorders, mental disorders, respiratory system diseases, and skin and subcutaneous tissue diseases was elevated in subjects with OA compared with control subjects [13]. Patients with OA had several comorbidities, including cardiovascular disease, diseases of eye, ear, nose, throat, urogenital disease, and endocrine disease. The number and severity of morbidities were associated with limited physical activity and pain [60]. In the current study, many of these comorbidities including asthma, thyroid disease, and atopic dermatitis were significantly different only in the pain only group. Although pain is associated with systemic inflammation leading to an increased incidence of medical comorbidities, comorbidities were not significantly associated with painful ROA. Thus, our data do not directly support an association between OA and medical comorbidity.

We found that HRQOL indices, including EQ-VAS score and EQ-5D index, were significantly lower in subjects with pain only and in subjects with painful ROA. This finding is consistent with those of a previous cross-sectional study, which reported that patients with symptomatic knee OA had significantly lower QOL than patients with radiographic knee OA without pain [61]. Musculoskeletal diseases are the most common cause of pain worldwide, and pain is the primary concern of patients with OA [62]. Pain is the main cause of total knee replacement surgery in patients with OA. However, a few patients experience continued unexplained pain after knee replacement surgery [63]. Many studies have reported that radiological changes in the knee joint are only weakly related to joint pain [64,65]. Various mechanisms are involved in the pain pathogenesis of OA. Changes in the nociceptive process caused by local inflammation of subchondral bone and the synovium as well as peripheral neuronal sensitization contribute to OA pain. Also, central pain sensitization is important in the pathophysiology of pain in OA [66,67]. Therefore, a neuropathic pain component can be a predominant feature in individuals with minor joint changes and high levels of pain. In these patients, centrally oriented medications are recommended rather than analgesic treatment that is involved in peripheral processes. Central pain sensitization is related to psychosocial factors [68]. Psychosocial factors are also key determinants of pain severity [64]. Individuals with OA who require treatment for pain are more likely to have depressive symptoms [69]. This suggests that the lower quality of life observed in subjects with knee pain regardless of the presence of radiographic changes might be related to a central pain sensitization pathway.

Knee OA can lead to considerable functional limitations associated with pain. Limitations in activities of daily living and recreation in patients with OA affect HRQOL as well as pain. Subjects with musculoskeletal disease showed significantly lower HRQOL than those without musculoskeletal disease, and patients with OA reported worse HRQOL patterns compared with patients with other chronic disease [70]. In Japanese elderly women with knee OA, quality of life was associated with physical activity [71]. As OA progresses, HRQOL progressively declines [72]. Progression of knee OA decreases physical activity and activities of daily living and therefore affects mental health and quality of life. Functional independence is associated with higher QOL in patients with OA [73]. Considering the impact of OA on HRQOL, clinicians need to assess and manage both pain and physical activity limitations.

The present study has some limitations. First, comorbidity diagnoses depended on the information self-reported by the participants in an interview. This is a major limitation of this type of nationwide survey because patients might misunderstand the information given by physicians. Although trained researchers asked the study population about diagnoses during face-to-face interviews, the risk of recall bias should be considered. Second, we could not assess medications for OA and were unable to evaluate the potential associations between comorbidities and medications. Third, although we defined OA based on the presence of pain and knee radiographs, no classification criteria were applied for diagnosis of OA. Subjects in the pain only group were defined as having a KL grade < 2 OA with knee pain for 30 days or longer within the past 3 months. Although we excluded subjects with RA, other knee joint pathologies such as trauma could not be excluded. However, considering the prevalence of arthritis in the elderly population [74] and symptom duration, most participants in the pain only group likely had knee OA. Fourth, we could not determine causality with our cross-sectional study design. Fifth, BMI varies by race/ethnicity and sex and does not provide information about muscularity; thus, BMI is not an ideal surrogate marker for joint loading. Adjustment for body composition rather than BMI is more useful in knee OA studies. Finally, we could not use the Western Ontario and MacMaster Universities Osteoarthritis Index (WOMAC) in the assessment of OA. The WOMAC provides detailed information about symptoms of OA including pain, stiffness, and physical function. If WOMAC data had been available in this study, it would have provided more evidence regarding the impact of OA on HRQOL. In addition, KNHANES data provide information on EQ-5D-3L as a measure of quality of life. The EQ-5D-5L is a more recent and updated form of this measure that provides a wider range of information than the EQ-5D-3L. The strength of our study is that we analyzed a large, nationally representative dataset of the Korean elderly population that had undergone knee radiography. Moreover, we analyzed four subgroups to evaluate whether symptomatic or radiographic OA is associated with comorbidities or HRQOL.

In conclusion, we did not identify any association between knee OA and comorbidities after adjustment for various factors. Knee OA was associated with limited physical activity and poor QOL. Painful OA with or without ROA was more significantly associated with a decline in physical activity and lower quality of life than was ROA without pain. Since the incidence of OA in the elderly is rising concomitantly with life expectancy, clinicians should focus on QOL in their daily clinical practice. Our study suggests that interventions to relieve knee pain could be effective for improving HRQOL in patients with OA.

Supporting information

References

  1. 1. Vos T, Flaxman AD, Naghavi M, Lozano R, Michaud C, Ezzati M, et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380: 2163–2196. pmid:23245607
  2. 2. March L, Smith EU, Hoy DG, Cross MJ, Sanchez-Riera L, Blyth F, et al. Burden of disability due to musculoskeletal (MSK) disorders. Best Pract Res Clin Rheumatol. 2014;28: 353–366. pmid:25481420
  3. 3. Kapoor M, Martel-Pelletier J, Lajeunesse D, Pelletier JP, Fahmi H. Role of proinflammatory cytokines in the pathophysiology of osteoarthritis. Nat Rev Rheumatol. 2011;7: 33–42. pmid:21119608
  4. 4. Stannus OP, Jones G, Blizzard L, Cicuttini FM, Ding C. Associations between serum levels of inflammatory markers and change in knee pain over 5 years in older adults: a prospective cohort study. Ann Rheum Dis. 2013;72: 535–540. pmid:22580582
  5. 5. Dougados M, Soubrier M, Antunez A, Balint P, Balsa A, Buch MH, et al. Prevalence of comorbidities in rheumatoid arthritis and evaluation of their monitoring: results of an international, cross-sectional study (COMORA). Ann Rheum Dis. 2014;73: 62–68. pmid:24095940
  6. 6. Maradit-Kremers H, Crowson CS, Nicola PJ, Ballman KV, Roger VL, Jacobsen SJ, et al. Increased unrecognized coronary heart disease and sudden deaths in rheumatoid arthritis: a population-based cohort study. Arthritis Rheum. 2005;52: 402–411. pmid:15693010
  7. 7. Listing J, Gerhold K, Zink A. The risk of infections associated with rheumatoid arthritis, with its comorbidity and treatment. Rheumatology (Oxford). 2013;52: 53–61. pmid:23192911
  8. 8. Smitten AL, Simon TA, Hochberg MC, Suissa S. A meta-analysis of the incidence of malignancy in adult patients with rheumatoid arthritis. Arthritis Res Ther. 2008;10: R45. pmid:18433475
  9. 9. Haugen IK, Ramachandran VS, Misra D, Neogi T, Niu J, Yang T, et al. Hand osteoarthritis in relation to mortality and incidence of cardiovascular disease: data from the Framingham heart study. Ann Rheum Dis. 2015;74: 74–81. pmid:24047870
  10. 10. Rahman MM, Kopec JA, Anis AH, Cibere J, Goldsmith CH. Risk of cardiovascular disease in patients with osteoarthritis: a prospective longitudinal study. Arthritis Care Res (Hoboken). 2013;65: 1951–1958. pmid:23925995
  11. 11. Kluzek S, Sanchez-Santos MT, Leyland KM, Judge A, Spector TD, Hart D, et al. Painful knee but not hand osteoarthritis is an independent predictor of mortality over 23 years follow-up of a population-based cohort of middle-aged women. Ann Rheum Dis. 2016;75: 1749–1756. pmid:26543059
  12. 12. Hoeven TA, Leening MJ, Bindels PJ, Castano-Betancourt M, van Meurs JB, Franco OH, et al. Disability and not osteoarthritis predicts cardiovascular disease: a prospective population-based cohort study. Ann Rheum Dis. 2015;74: 752–756. pmid:24385204
  13. 13. Kadam UT, Jordan K, Croft PR. Clinical comorbidity in patients with osteoarthritis: a case-control study of general practice consulters in England and Wales. Ann Rheum Dis. 2004;63: 408–414. pmid:15020335
  14. 14. Hunter DJ, Riordan EA. The impact of arthritis on pain and quality of life: an Australian survey. Int J Rheum Dis. 2014;17: 149–155. pmid:24267825
  15. 15. Edwards RR, Cahalan C, Mensing G, Smith M, Haythornthwaite JA. Pain, catastrophizing, and depression in the rheumatic diseases. Nat Rev Rheumatol. 2011;7: 216–224. pmid:21283147
  16. 16. Ettinger WH, Davis MA, Neuhaus JM, Mallon KP. Long-term physical functioning in persons with knee osteoarthritis from NHANES. I: Effects of comorbid medical conditions. J Clin Epidemiol. 1994;47: 809–815. pmid:7722594
  17. 17. Leite AA, Costa AJ, Lima Bde A, Padilha AV, Albuquerque EC, Marques CD. Comorbidities in patients with osteoarthritis: frequency and impact on pain and physical function. Rev Bras Reumatol. 2011;51: 118–123. pmid:21584418
  18. 18. Ferreira AH, Godoy PB, Oliveira NR, Diniz RA, Diniz RE, Padovani Rda C, et al. Investigation of depression, anxiety and quality of life in patients with knee osteoarthritis: a comparative study. Rev Bras Reumatol. 2015;55: 434–438. pmid:26198010
  19. 19. Kweon S, Kim Y, Jang MJ, Kim Y, Kim K, Choi S, et al. Data resource profile: the Korea National Health and Nutrition Examination Survey (KNHANES). Int J Epidemiol. 2014;43: 69–77. pmid:24585853
  20. 20. Kellgren JH, Lawrence JS. Radiological assessment of osteo-arthrosis. Ann Rheum Dis. 1957;16: 494–502. pmid:13498604
  21. 21. Schiphof D, Boers M, Bierma-Zeinstra SM. Differences in descriptions of Kellgren and Lawrence grades of knee osteoarthritis. Ann Rheum Dis. 2008;67: 1034–1036. pmid:18198197
  22. 22. Rabin R, de Charro F. EQ-5D: a measure of health status from the EuroQol Group. Ann Med. 2001;33: 337–343. pmid:11491192
  23. 23. Min-Woo Jo S IL. Validity and Reliability of Korean EQ-5D Valuation Study Using the Time-trade off Method. Korean J Health Promot Dis Prev. 2007;7: 96–103.
  24. 24. Kim MH, Cho YS, Uhm WS, Kim S, Bae SC. Cross-cultural adaptation and validation of the Korean version of the EQ-5D in patients with rheumatic diseases. Qual Life Res. 2005;14: 1401–1406. pmid:16047514
  25. 25. Lim NY, Lee Inok, Lee Eun Nam, Lee Kyung-Sook, Cho Kyung-Sook, Rhee Seonja, Kang Hyun Sook, Kim Keum-Soon, Kim Jong Im, Bak Won-Sook, Lee Yoon Kyoung, Chon Mi-Young. A Validation Study of EQ-5D in the Patients with Osteoarthritis. J Muscle Joint Health. 2010;17: 203–211.
  26. 26. Lee YK, Nam HS, Chuang LH, Kim KY, Yang HK, Kwon IS, et al. South Korean time trade-off values for EQ-5D health states: modeling with observed values for 101 health states. Value Health. 2009;12: 1187–1193. pmid:19659703
  27. 27. Kishimoto M, Greenberg J, Lee R, Masaki KH, Chen R, Rodriguez BL, et al. Arthritis as a risk factor for incident coronary heart disease in elderly Japanese-American males—the Honolulu Heart Program. Bull NYU Hosp Jt Dis. 2009;67: 230–235. pmid:19583559
  28. 28. Singh G, Miller JD, Lee FH, Pettitt D, Russell MW. Prevalence of cardiovascular disease risk factors among US adults with self-reported osteoarthritis: data from the Third National Health and Nutrition Examination Survey. Am J Manag Care. 2002;8: S383–391. pmid:12416788
  29. 29. Rahman MM, Kopec JA, Cibere J, Goldsmith CH, Anis AH. The relationship between osteoarthritis and cardiovascular disease in a population health survey: a cross-sectional study. BMJ Open. 2013;3 pmid:23674445
  30. 30. Wang H, Bai J, He B, Hu X, Liu D. Osteoarthritis and the risk of cardiovascular disease: a meta-analysis of observational studies. Sci Rep. 2016;6: 39672. pmid:28004796
  31. 31. Meune C, Touze E, Trinquart L, Allanore Y. High risk of clinical cardiovascular events in rheumatoid arthritis: Levels of associations of myocardial infarction and stroke through a systematic review and meta-analysis. Arch Cardiovasc Dis. 2010;103: 253–261. pmid:20656636
  32. 32. Lindhardsen J, Ahlehoff O, Gislason GH, Madsen OR, Olesen JB, Torp-Pedersen C, et al. The risk of myocardial infarction in rheumatoid arthritis and diabetes mellitus: a Danish nationwide cohort study. Ann Rheum Dis. 2011;70: 929–934. pmid:21389043
  33. 33. Peters MJ, van Halm VP, Voskuyl AE, Smulders YM, Boers M, Lems WF, et al. Does rheumatoid arthritis equal diabetes mellitus as an independent risk factor for cardiovascular disease? A prospective study. Arthritis Rheum. 2009;61: 1571–1579. pmid:19877093
  34. 34. Kerola AM, Kauppi MJ, Kerola T, Nieminen TV. How early in the course of rheumatoid arthritis does the excess cardiovascular risk appear? Ann Rheum Dis. 2012;71: 1606–1615. pmid:22736093
  35. 35. Durante A, Bronzato S. The increased cardiovascular risk in patients affected by autoimmune diseases: review of the various manifestations. J Clin Med Res. 2015;7: 379–384. pmid:25883699
  36. 36. Manzi S, Wasko MC. Inflammation-mediated rheumatic diseases and atherosclerosis. Ann Rheum Dis. 2000;59: 321–325. pmid:10784507
  37. 37. Asanuma Y, Oeser A, Shintani AK, Turner E, Olsen N, Fazio S, et al. Premature coronary-artery atherosclerosis in systemic lupus erythematosus. N Engl J Med. 2003;349: 2407–2415. pmid:14681506
  38. 38. Goldring MB. The role of cytokines as inflammatory mediators in osteoarthritis: lessons from animal models. Connect Tissue Res. 1999;40: 1–11. pmid:10770646
  39. 39. Spector TD, Hart DJ, Nandra D, Doyle DV, Mackillop N, Gallimore JR, et al. Low-level increases in serum C-reactive protein are present in early osteoarthritis of the knee and predict progressive disease. Arthritis Rheum. 1997;40: 723–727. pmid:9125256
  40. 40. Scanzello CR, Goldring SR. The role of synovitis in osteoarthritis pathogenesis. Bone. 2012;51: 249–257. pmid:22387238
  41. 41. Nielen MM, van Sijl AM, Peters MJ, Verheij RA, Schellevis FG, Nurmohamed MT. Cardiovascular disease prevalence in patients with inflammatory arthritis, diabetes mellitus and osteoarthritis: a cross-sectional study in primary care. BMC Musculoskelet Disord. 2012;13: 150. pmid:22906083
  42. 42. Engstrom G, Gerhardsson de Verdier M, Rollof J, Nilsson PM, Lohmander LS. C-reactive protein, metabolic syndrome and incidence of severe hip and knee osteoarthritis. A population-based cohort study. Osteoarthritis Cartilage. 2009;17: 168–173. pmid:18760940
  43. 43. Yoshimura N, Muraki S, Oka H, Tanaka S, Kawaguchi H, Nakamura K, et al. Accumulation of metabolic risk factors such as overweight, hypertension, dyslipidaemia, and impaired glucose tolerance raises the risk of occurrence and progression of knee osteoarthritis: a 3-year follow-up of the ROAD study. Osteoarthritis Cartilage. 2012;20: 1217–1226. pmid:22796312
  44. 44. Yoshimura N, Muraki S, Oka H, Kawaguchi H, Nakamura K, Akune T. Association of knee osteoarthritis with the accumulation of metabolic risk factors such as overweight, hypertension, dyslipidemia, and impaired glucose tolerance in Japanese men and women: the ROAD study. J Rheumatol. 2011;38: 921–930. pmid:21324967
  45. 45. Liaw FY, Kao TW, Wu LW, Wang CC, Yang HF, Peng TC, et al. Components of Metabolic Syndrome and the Risk of Disability among the Elderly Population. Sci Rep. 2016;6: 22750. pmid:26948125
  46. 46. Niu J, Clancy M, Aliabadi P, Vasan R, Felson DT. Metabolic Syndrome, Its Components, and Knee Osteoarthritis: The Framingham Osteoarthritis Study. Arthritis Rheumatol. 2017;69: 1194–1203. pmid:28257604
  47. 47. Segal NA, Yack HJ, Khole P. Weight, rather than obesity distribution, explains peak external knee adduction moment during level gait. Am J Phys Med Rehabil. 2009;88: 180–188; quiz 189–191, 246. pmid:19847127
  48. 48. Berenbaum F. Osteoarthritis as an inflammatory disease (osteoarthritis is not osteoarthrosis!). Osteoarthritis Cartilage. 2013;21: 16–21. pmid:23194896
  49. 49. Karvonen-Gutierrez CA, Harlow SD, Mancuso P, Jacobson J, Mendes de Leon CF, Nan B. Association of leptin levels with radiographic knee osteoarthritis among a cohort of midlife women. Arthritis Care Res (Hoboken). 2013;65: 936–944. pmid:23281224
  50. 50. Klein-Wieringa IR, Kloppenburg M, Bastiaansen-Jenniskens YM, Yusuf E, Kwekkeboom JC, El-Bannoudi H, et al. The infrapatellar fat pad of patients with osteoarthritis has an inflammatory phenotype. Ann Rheum Dis. 2011;70: 851–857. pmid:21242232
  51. 51. Neogi T, Guermazi A, Roemer F, Nevitt MC, Scholz J, Arendt-Nielsen L, et al. Association of Joint Inflammation With Pain Sensitization in Knee Osteoarthritis: The Multicenter Osteoarthritis Study. Arthritis Rheumatol. 2016;68: 654–661. pmid:26554395
  52. 52. Mathiessen A, Conaghan PG. Synovitis in osteoarthritis: current understanding with therapeutic implications. Arthritis Res Ther. 2017;19: 18. pmid:28148295
  53. 53. Stenholm S, Koster A, Alley DE, Visser M, Maggio M, Harris TB, et al. Adipocytokines and the metabolic syndrome among older persons with and without obesity: the InCHIANTI study. Clin Endocrinol (Oxf). 2010;73: 55–65. pmid:19878507
  54. 54. Isomaa B, Almgren P, Tuomi T, Forsen B, Lahti K, Nissen M, et al. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care. 2001;24: 683–689. pmid:11315831
  55. 55. Kaur J. A comprehensive review on metabolic syndrome. Cardiol Res Pract. 2014;2014: 943162. pmid:24711954
  56. 56. Han CD, Yang IH, Lee WS, Park YJ, Park KK. Correlation between metabolic syndrome and knee osteoarthritis: data from the Korean National Health and Nutrition Examination Survey (KNHANES). BMC Public Health. 2013;13: 603. pmid:23800128
  57. 57. WHO expert consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363: 157–163. pmid:14726171
  58. 58. Tsujii M, Kawano S, Tsuji S, Sawaoka H, Hori M, DuBois RN. Cyclooxygenase regulates angiogenesis induced by colon cancer cells. Cell. 1998;93: 705–716. pmid:9630216
  59. 59. Il'yasova D, Colbert LH, Harris TB, Newman AB, Bauer DC, Satterfield S, et al. Circulating levels of inflammatory markers and cancer risk in the health aging and body composition cohort. Cancer Epidemiol Biomarkers Prev. 2005;14: 2413–2418. pmid:16214925
  60. 60. van Dijk GM, Veenhof C, Schellevis F, Hulsmans H, Bakker JP, Arwert H, et al. Comorbidity, limitations in activities and pain in patients with osteoarthritis of the hip or knee. BMC Musculoskelet Disord. 2008;9: 95. pmid:18582362
  61. 61. Muraki S, Akune T, Oka H, En-yo Y, Yoshida M, Saika A, et al. Association of radiographic and symptomatic knee osteoarthritis with health-related quality of life in a population-based cohort study in Japan: the ROAD study. Osteoarthritis Cartilage. 2010;18: 1227–1234. pmid:20633679
  62. 62. Elliott AM, Smith BH, Penny KI, Smith WC, Chambers WA. The epidemiology of chronic pain in the community. Lancet. 1999;354: 1248–1252. pmid:10520633
  63. 63. Elson DW, Brenkel IJ. A conservative approach is feasible in unexplained pain after knee replacement: a selected cohort study. J Bone Joint Surg Br. 2007;89: 1042–1045. pmid:17785742
  64. 64. Dieppe PA, Lohmander LS. Pathogenesis and management of pain in osteoarthritis. Lancet. 2005;365: 965–973. pmid:15766999
  65. 65. van Baar ME, Dekker J, Lemmens JA, Oostendorp RA, Bijlsma JW. Pain and disability in patients with osteoarthritis of hip or knee: the relationship with articular, kinesiological, and psychological characteristics. J Rheumatol. 1998;25: 125–133. pmid:9458215
  66. 66. Dimitroulas T, Duarte RV, Behura A, Kitas GD, Raphael JH. Neuropathic pain in osteoarthritis: a review of pathophysiological mechanisms and implications for treatment. Semin Arthritis Rheum. 2014;44: 145–154. pmid:24928208
  67. 67. Gwilym SE, Pollard TC, Carr AJ. Understanding pain in osteoarthritis. J Bone Joint Surg Br. 2008;90: 280–287. pmid:18310746
  68. 68. Adams LM, Turk DC. Psychosocial factors and central sensitivity syndromes. Curr Rheumatol Rev. 2015;11: 96–108. pmid:26088211
  69. 69. Dexter P, Brandt K. Distribution and predictors of depressive symptoms in osteoarthritis. J Rheumatol. 1994;21: 279–286. pmid:8182638
  70. 70. Picavet HS, Hoeymans N. Health related quality of life in multiple musculoskeletal diseases: SF-36 and EQ-5D in the DMC3 study. Ann Rheum Dis. 2004;63: 723–729. pmid:15140781
  71. 71. Watanabe H, Urabe K, Takahira N, Ikeda N, Fujita M, Obara S, et al. Quality of life, knee function, and physical activity in Japanese elderly women with early-stage knee osteoarthritis. J Orthop Surg (Hong Kong). 2010;18: 31–34. pmid:20427830
  72. 72. Hoogeboom TJ, den Broeder AA, de Bie RA, van den Ende CH. Longitudinal impact of joint pain comorbidity on quality of life and activity levels in knee osteoarthritis: data from the Osteoarthritis Initiative. Rheumatology (Oxford). 2013;52: 543–546. pmid:23204552
  73. 73. Araujo IL, Castro MC, Daltro C, Matos MA. Quality of Life and Functional Independence in Patients with Osteoarthritis of the Knee. Knee Surg Relat Res. 2016;28: 219–224. pmid:27595076
  74. 74. Felson DT, Zhang Y. An update on the epidemiology of knee and hip osteoarthritis with a view to prevention. Arthritis Rheum. 1998;41: 1343–1355. pmid:9704632