- Top of page
- MATERIALS AND METHODS
- AUTHOR CONTRIBUTIONS
- Supporting Information
Osteoarthritis (OA) is the most common type of arthropathy and a leading cause of pain, restricted mobility, and functional decline, particularly in older people. It is estimated that approximately 25% of people ages >55 years have persistent knee pain, 10% of whom report having painful disabling knee OA (1). OA contributes substantially to direct and indirect health costs. Currently, there is no cure and the benefits of pharmacologic treatments commonly used for its management are often outweighed by their side effects (2).
Development of knee OA is associated with heredity, age, sex, obesity, previous knee injury, occupational factors (e.g., kneeling and squatting), physical activity, and knee malalignment (3). Obesity is one of the greatest health risks facing the world today, and the prevalence has increased globally in recent decades. Moreover, populations in developed countries are living longer. As obesity is growing progressively in older age (4), the prevalence of obesity-related symptomatic knee OA is anticipated to increase and is threatening to become a major public health problem worldwide. OA is also a major cause of total joint replacement. More than 450,000 primary total knee arthroplasties were performed in the US in 2004, and the number is projected to increase to 3.48 million by 2030 (5). Consequently, the economic impact of OA on society is anticipated to increase in parallel.
Obesity is one of the most important modifiable risk factors for the development (6–12) and progression (6, 12–15) of knee OA. It is suggested that excess weight increases mechanical loading of joints, leading to increased cartilage degradation and subsequent failure of the entire joint (16). Another proposed mechanism is mediation through metabolic and hormonal factors that disadvantage the health of joint tissues (16). In the Framingham Knee OA study, weight loss of approximately 5.1 kg over a 10-year period was found to reduce the risk of incident knee OA by 54% (odds ratio [OR] 0.46, 95% confidence interval [95% CI] 0.24–0.86) in women (17). Recently, a meta-analysis of randomized controlled trials (RCTs) has shown weight loss to reduce physical disability in obese patients diagnosed with knee OA (18). However, despite convincing evidence from observational studies and RCTs of the causal effect of obesity in knee OA, the benefit of preventing obesity at the population level has yet to be assessed (19). This is of considerable importance in support of public health initiatives aimed at reducing the burden of disease in the population.
We therefore carried out this study to 1) estimate the overall relative risk (RR) of knee OA associated with obesity using a meta-analysis of observational studies, and 2) calculate the risk reduction of knee OA in different populations according to the overall RR estimate and the prevalence of obesity.
Significance & Innovations
Body mass index (BMI) is one of the modifiable risk factors for knee osteoarthritis (OA). However, despite convincing evidence on the causal effect of the elevated BMI in knee OA, the potential risk reduction of knee OA due to the control of overweight/obesity at the population level has not been quantified. This is of considerable importance in support of public health initiatives aimed at reducing the burden of the disease in the general population.
We found risk reduction in knee OA to vary from 8% in China to 60% in the US, depending on the prevalence of obesity. The reduction was greatest in severe symptomatic OA awaiting total joint replacement, followed by symptomatic knee OA and asymptomatic radiographic OA.
- Top of page
- MATERIALS AND METHODS
- AUTHOR CONTRIBUTIONS
- Supporting Information
BMI is a major risk factor for the development of knee OA (3, 71), and it may also accelerate the progression of the disease (72). This meta-analysis of 47 observational studies with more than 446,000 people found an approximately 3-fold increased risk in the development of knee OA in overweight or obese individuals, and the association was dose dependent. A potential risk reduction may be estimated according to these RRs estimated from meta-analysis. For example, in the US, approximately 50% of symptomatic knee OA may be prevented if the current obesity prevalence in the US population could be controlled. The risk reduction in China, in contrast, is only 8% due to the low prevalence of obesity (Table 3). It is predicted, however, that the prevalence of obesity is increasing dramatically (73, 74). The impact of preventing obesity and the resultant risk reduction are substantial, especially when multiple outcomes of obesity are considered (19).
To our knowledge, this is the first calculation of risk reduction using the RR summarized from a meta-analysis. The advantage of this method is that it first establishes the association between exposure and the condition. Second, it produces a powerful and globally generalizable RR estimate for the estimation of risk reduction. Given a country- or population-specific prevalence of exposure (e.g., obesity), users are able to estimate the risk reduction for their own populations. The utility of the RR estimates provided in Table 2 is significant. We have therefore listed all possible ORs in subgroups to accommodate the application. The country-specific PAR% in Table 3 is based on the current prevalence of overweight and obesity in adults. It is important to note that we have used prevalence data of adult obesity that includes young adults. However, since BMI increases with age while OA is associated with older age, PAR% for obesity may be underestimated; therefore, these estimates are for reference only. Moreover, risk reduction due to the prevention of both overweight and obesity may be additive. Therefore, the incidence of knee OA would be greatly reduced if overweight and obesity were eliminated.
This study has several limitations. First, we combined RR estimates from different study designs for the subsequent calculation of PAR%. Yet, the OR from case–control studies is less conservative and can overestimate the RR in common diseases such as knee OA. Moreover, the OR may change with the number of confounding factors being adjusted for. As this was a study-level analysis, we were unable to provide an OR that was adjusted with the same set of confounding factors, and unadjusted ORs were used where adjustment was unavailable. Therefore, the RR may be overestimated. Second, there was a high degree of variation among studies included in the meta-analysis. We carried out a number of subgroup analyses with regard to potential sources of heterogeneity such as study design, setting (hospital versus community), sex, adjustment for confounding factors, disease definition, assessment of BMI (self-reported or measured), and BMI categories. Even so, we were unable to explain some of the heterogeneity found here, but findings from the meta–regression analysis revealed case–control studies and obesity as the main sources. Third, it is conceivable that persons may gain weight after developing knee OA as a consequence of knee pain and physical inactivity. Therefore, cross-sectional BMI assessed in symptomatic knee OA cases may not reflect the body weight prior to the onset of knee OA. This may be a source of bias and may also explain the high pooled risk estimate in case–control studies. Finally, we assessed BMI as a surrogate measure of adiposity. However, BMI neither distinguishes heaviness due to body fat or heaviness due to muscle bulk, nor does it indicate the distribution of body fat. It is speculated that fat distribution may act through metabolic or systematic rather than biomechanical mechanisms to contribute to knee OA. Some epidemiologic studies have demonstrated that certain adiposity measures such as waist circumference and waist to hip ratio or body composition components such as fat mass may be associated with knee OA (31, 34, 43, 75), but not others (36, 76). In spite of these reports, such adiposity measures were beyond the scope of this analysis.
Evidence suggests that excessive body weight may attenuate biomechanical load exerted on weight-bearing joints. It is also plausible that obesity may additionally cause dysfunctional metabolism and joint damage by stimulating adipokines that are known regulators of metabolic homeostasis (77, 78). This may partly explain the different associations between obesity and the incidence of OA in weight-bearing versus non–weight-bearing joints such as hand OA (29, 79). Weight loss has shown significant clinical effects in the treatment of OA in a number of RCTs for weight-bearing joint OA (2). However, to our knowledge there have been no trials to prove whether weight loss can prevent the onset of knee OA. Therefore, we have summarized evidence from the observational studies to examine the potential benefit of preventing knee OA attributable to overweight and obesity. It was not our intention to investigate the effectiveness of weight reduction interventions, but to provide an epidemiologic perspective on the potential risk reduction of knee OA in a general population if overweight/obesity was removed. However, these estimates may carry confounding bias, and further prevention trials on the effect of weight reduction are needed to confirm these results.
In summary, obesity is a common risk factor associated with many conditions, including knee OA. It is one of the few risk factors that may be modified, although effective modification is challenging. The resulting benefits from preventing obesity in the general population are huge, especially in the Western world, where obesity is highly prevalent. Approximately half of symptomatic knee OA, for example, would be prevented in the US if this risk factor was eliminated.