Prevalence of knee osteoarthritis in the Chinese population, 2013–2023: a systematic review and meta-analysis

Abstract

Objective

Knee osteoarthritis (KOA) is the primary cause of lower-limb disability and poses a substantial socio-economic burden. This systematic review and meta-analysis aims to assess the prevalence of KOA in the Chinese population between 2013 and 2023.

Methods

Eight databases were searched, in addition to a grey Literature search and manual retrieval, to comprehensively collect cross-sectional studies on the prevalence of KOA in China. Stata 18.0 was used to perform a meta-analysis of the KOA prevalence data included in this study. Furthermore, a narrative review was conducted to evaluate the impact of gender, age, Body Mass Index (BMI), region, and other factors on the prevalence of KOA.

Results

The meta-analysis demonstrated that the overall prevalence of KOA in China from 2013 to 2023 was 28.0%. Subgroup analysis indicated a prevalence of 33.9% in women and 20.5% in men. The highest prevalence was observed in the 60–69 age group (32.8%), followed by those aged ≥ 80 and 70–79 years. The highest prevalence was observed in individuals with a BMI ≥ 28 kg/m², at 50.5%. Prevalence in northern China was 4.5% higher than in southern regions. Prevalence in high-altitude regions was 22.6% higher than in low-altitude regions. The prevalence rates in rural and urban areas were similar.

Conclusions

Over the past decade, the prevalence of KOA in China has remained high and increased with age, particularly among women. It is strongly associated with BMI and environmental factors. A large-scale KOA survey should be conducted nationwide to monitor the disease's development trends and avoid associated risk factors.

Systematic review registration

PROSPERO, identifier CRD42024590187.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13018-025-06270-5.

Introduction

Knee osteoarthritis (KOA) is a degenerative joint disease primarily characterized by pain and impaired mobility in the knee [1, 2], affecting all components of the joint, including the bones, synovium, and joint capsule [3]. It is a leading cause of lower limb disability [4]. In 2020, there were 595 million people globally diagnosed with osteoarthritis (OA), with the highest proportion, 60.6%, occurring in the knee joints [5]. It is projected that by 2050, the number of KOA cases will increase by 74.9%, and the global total number of patients will reach 642 million [6]. Over the past four decades, China has experienced significant changes in its population structure and epidemiological characteristics [7]. In 2019, the incidence of OA in China had increased by 132.66% compared to 1990, with KOA being the most prominent [8]. The average Life expectancy in China has increased by 8.71 years [9]. By the end of 2023, the proportion of people aged 60 and above in China will reach 21.1%. Given China's large population and the rapid acceleration of its aging process, an enormous patient group is emerging. The public, healthcare institutions, and policymakers must recognize the substantial disease burden and socio-economic impact that KOA will impose.

From 2010 to 2017, musculoskeletal diseases accounted for 16% to 19% of the global disease burden in terms of years lost due to disability (YLDs), with KOA accounting for 83% to 86% of this burden [10, 11]. In 2020, YLDs due to OA increased by 9.5% compared to 30 years ago. From 1990 to 2019, the Disability-Adjusted Life Years (DALYs) in China increased by 153.8% [12]. Currently, nonsteroidal anti-inflammatory drugs (NSAIDs) and local corticosteroid injections are commonly used to alleviate KOA symptoms, but prolonged NSAID use can cause gastrointestinal and cardiovascular side effects [13]. Total knee arthroplasty (TKA) is considered one of the effective treatment options for KOA [14]. In the United States, 50% of symptomatic KOA patients will undergo joint replacement surgery, with the number of surgeries expected to reach 1.26 million by 2030 [15, 16]. In 2013, the cost of TKA in Australia exceeded 900 million AUD, and it is projected to reach 3.4 billion AUD by 2030 [17]. In China, the number of TKA surgeries has rapidly increased, growing 5.9-fold from 2011 to 2019 [18]. Given the large treatment population and high costs, it is crucial to reduce the socio-economic burden of KOA.

Research on the pathogenesis of KOA has led to the development of predictive models that assess the risk of its onset. These models enable early detection and intervention, thereby reducing the disease burden in high-risk populations [19–24]. Studies have found that the primary risk factors for KOA are age, gender, and BMI [25]. The accumulation of senescent cells in the elderly can accelerate the progression of KOA [26]. Moreover, prolonged joint usage and damage in the elderly lead to articular cartilage wear, degenerative changes in joint structures, and the deterioration of muscles and ligaments. Aging leads to quadriceps muscle atrophy and decreased muscle strength, resulting in altered gait and load distribution, which in turn affects the onset and progression of KOA [27]. Increased BMI leads to overweight, thereby increasing the load on the knees [28]. Research has shown that estrogen plays a crucial role in maintaining joint homeostasis, and estrogen deficiency contributes to osteoporosis, a key risk factor for arthritis. Consequently, postmenopausal women are at a higher risk of developing KOA [29]. The prevalence of KOA varies across China due to regional differences in climate, environment, lifestyle, and public awareness.

Currently, there is a lack of data on the prevalence of KOA in China over the past decade. Therefore, this study employs a meta-analysis approach to comprehensively analyze the published literature on KOA in China, with the aim of better understanding its prevalence over the past decade, reducing modifiable risk factors, and alleviating the current and future burden of KOA in China.

Materials and methods

Systematic review protocol and registration

The study was registered on September 24, 2024, with the International Prospective Register of Systematic Reviews (PROSPERO), registration number: CRD42024590187. The reporting was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [30]. The detailed report results can be found in Supplementary Material 1.

Search strategy

This study performed a search across eight databases, with the search period spanning from database inception to October 22, 2024. The four English-language databases include PubMed, EMBASE, The Cochrane Library, and Web of Science. The Chinese databases include: Chinese Biomedical Database (CBM), Chinese National Knowledge Infrastructure (CNKI), Wan Fang Data Knowledge Service Platform, and the Chinese Scientific Journal Database (VIP). A search was conducted using Open Grey [31] with the same keywords as those used in the aforementioned databases to identify grey literature. During the initial screening, we examined the references of previous systematic reviews and meta-analyses on similar topics to supplement the search. During the screening of full-text reports, we manually searched and traced the references of eligible studies to gather additional information. The main search terms used in PubMed were "Knee Osteoarthritis," "Osteoarthritis of the Knee," "KOA," "Prevalence," and "Chinese." The detailed search strategy is provided in Supplementary Material 2.

Inclusion and exclusion criteria

All studies must meet the following inclusion criteria: 1. The study must be a published epidemiological study on KOA conducted in China. 2. The study must employ a sampling method to obtain the study population, with clearly defined sample sizes, case numbers, or prevalence rates. 3. The study design must be cross-sectional. 4. The study must include well-defined diagnostic criteria for KOA. 5. The included articles must be published in English or Chinese. 6. The primary objective of this study is to analyze the changes and trends in KOA prevalence in China over the past decade. Due to the time gap between the study period and publication, the investigation period spans from 2013 to 2023. The exclusion criteria are as follows: 1. Duplicate publications. 2. Studies conducted in specific populations (e.g., studies with only female participants or those focusing on specific occupations). 3. Studies from which the required data cannot be extracted. 4. Randomized controlled trials, animal studies, Literature reviews, case reports, conference abstracts, and other non-epidemiological studies. 5. Studies with a sample size of fewer than 30 cases.

Study selection, data extraction, and quality assessment

Two researchers (CLS and LL) independently screened the retrieved articles by reviewing the titles and abstracts, removed duplicates, and then excluded irrelevant studies. Studies that met the inclusion and exclusion criteria were selected, data were extracted, and verified. Discrepancies were resolved through discussion and consensus. If no consensus was reached, a third researcher (YW) was consulted for arbitration. All excluded studies were documented. If necessary, the original authors of the studies were contacted by email or phone to clarify any unclear but essential information for this research. The specific information to be extracted includes the following: first author, year, research province, altitude, study region, sampling sources, total sample size, total number of cases, number of male and female cases, age, methods of diagnosis, and Agency for Healthcare Research and Quality (AHRQ) (Table 1).

Table 1.

Characteristics of included studies

First author (year)	Research province	Altitude	Study Region	Sampling Resources	NO.of Total	NO.of KOA	NO.of Female KOA	NO.of Male KOA	Age (years)	Methods of Diagnosis	AHRQ
Li et al. (2015) [32]	Hebei	Low altitude area	North China	Urban and rural	3382	1274	712	562	40–70	Guidelines for the diagnosis and treatment of osteoarthritis (2007)	5
Tian et al. (2015) [33]	Shandong	Low altitude area	North China	Urban and rural	1125	165	119	46	62.2 ± 1.5	KL ≥ 2 and ACR	5
Wang et al. (2016) [34]	Hei longjiang	Low altitude area	North China	Urban	400	38	32	6	60.09 ± 9.47	KL ≥ 2 and Symptomatic(pain)	5
Liao et al. (2016) [35]	Guangxi	Low altitude area	South China	Urban	1859	322	247	75	≥ 40	Guidelines for the diagnosis and treatment of osteoarthritis (2007)	5
Wu et al. (2016) [36]	Xinjiang	High altitude area	North China	Urban	584	187	146	41	44–75	KL ≥ 2 and ACR	7
Zhang et al. (2016) [37]	Xinjiang	Low altitude area	North China	Rural	1461	354	267	87	38–75	KL ≥ 2 and ACR	6
Ren et al. (2017) [38]	Zhejiang	Low altitude area	South China	Urban	202	79	44	35	40–85(53.42 ± 7.31)	Guidelines for the diagnosis and treatment of osteoarthritis (2007)	6
Yang et al. (2017) [39]	Inner Mongoria	High altitude area	North China	Urban	1084	231	132	96	59.92 ± 7.87	KL ≥ 2	6
Yu et al. (2018) [40]	Xinjiang	High altitude area	North China	Urban and rural	1498	557	351	206	≥ 40	Doctor-diagnosed	8
Zhang et al. (2018) [41]	Shanghai	Low altitude area	South China	Urban	1000	228	152	76	≥ 50	Guidelines for the diagnosis and treatment of osteoarthritis (2007)	6
Chen et al. (2021) [42]	Shanghai	Low altitude area	South China	Urban	1020	324	234	90	72.40 ± 5.96	KL ≥ 2 and Symptomatic(pain)	6
Wang et al. (2021) [43]	Sichuan	Low altitude area	South China	Urban and rural	1642	246	164	82	≥ 50	KL ≥ 2	6
Li et al. (2022) [44]	Guangdong	Low altitude area	South China	Urban and rural	380	70	48	22	≥ 50	Guidelines for the diagnosis and treatment of osteoarthritis (2018) and KL ≥ 2	6
Duan et al. (2023) [45]	Shandong	Low altitude area	North China	Urban	800	222	138	84	64.1 ± 1.6	ACR	6
Xing et al. (2023) [46]	Hebei	Low altitude area	North China	Urban and rural	1264	279	180	99	≥ 40	Guidelines for the diagnosis and treatment of osteoarthritis (2018)	5
Li et al. (2024) [47]	Qinghai	High altitude area	North China	Urban and rural	600	552	285	267	41–70	KL ≥ 2 and Symptomatic(pain)	4
Liang et al. (2024) [48]	Hubei	Low altitude area	North China	Urban and rural	10,108	1234	886	348	50.3 ± 15.7	ACR	6
Tao et al. (2024) [49]	Guizhou	High altitude area	South China	Urban	1362	466	261	205	63.67 ± 4.27	ACR	6

KOA Knee osteoarthritis, NR Not reported, BMI Body mass index, KL The Kellgren and Lawrence, ACR The American College of Rheumatology classification criteria, AHRQ Agency for Healthcare Research and Quality

This study utilized the AHRQ tool to assess the risk of bias in the included studies [50, 51]. The scale consists of 11 items, with responses categorized as "Yes," "No," or "Unclear." A score of 1 is assigned for "Yes," while "No" and "Unclear" are scored as 0. The final result is categorized as low quality (0–3 points), moderate quality (4–7 points), or high quality (8–11 points). Supplementary Material 3.

Statistical analysis and outcomes

Statistical analysis was conducted using Stata 18.0 software. A fixed-effects or random-effects model was selected based on the level of heterogeneity observed in the analysis results. The degree of heterogeneity was assessed using the I² test. When heterogeneity was high (P < 0.1, I² > 50%), a random-effects model was applied; when heterogeneity was low (P ≥ 0.1, I² ≤ 50%), a fixed-effects model was used. A 95% confidence interval (CI) was used to estimate the effect size. Differences were considered statistically significant if P < 0.05. For I² > 75%, heterogeneity is considered high, and subgroup analysis, sensitivity analysis, and meta-regression are performed to identify the sources of heterogeneity.

The primary outcome measure of this study is the prevalence of KOA. Subgroup analysis and meta-regression were conducted based on sex, age, BMI, sampling resources, study region, and altitude to investigate the effects of different factors on prevalence and the sources of heterogeneity. Age was divided into five subgroups: 40–49, 50–59, 60–69, 70–79, and ≥ 80 years. BMI was categorized into three groups: < 24, 24 ≤ BMI < 28, and ≥ 28 kg/m². Sampling sources were classified as rural, urban, or both rural and urban based on the descriptions in the articles. The study region was classified into southern and northern regions based on the Qinling–Huaihe Line in China. Altitude classification was based on the elevation of the surveyed areas, with altitudes between 1500 and 3500 m considered high-altitude areas.

Results

Description of studies

Based on the search strategy, a total of 4,489 relevant articles were identified. After excluding duplicate articles, randomized controlled trials, animal studies, Literature reviews, case reports, and conference papers, 430 articles were retained. Titles and abstracts were reviewed, resulting in 412 articles being further screened. Ultimately, 18 cross-sectional studies [32–49] meeting the inclusion and exclusion criteria were included (Fig. 1), with a total of 29,771 participants, of whom 6,828 were diagnosed with KOA. The studies spanned 13 provinces in China, with 11 studies [32–34, 36, 37, 39, 40, 45–48, 51] conducted in northern China and 7 studies [35, 38, 41–44, 49] in southern China. Five studies [36, 39, 40, 47, 49] were conducted in high-altitude regions, while 13 studies [32–35, 37, 38, 41–46, 48] were conducted in low-altitude regions. Nine studies [34–36, 38, 39, 41, 42, 45, 49] were conducted in urban areas, one study [37] was conducted in rural areas, and eight studies [32, 33, 40, 43, 44, 46–48] were conducted in both rural and urban areas. Six studies [33, 39, 42, 44, 47, 48] reported BMI data.

Fig. 1.

Study flow diagram

Level of evidence

Two researchers (CLS and LL) independently evaluated the quality of the studies that met the inclusion criteria. The AHRQ scale for evaluating the quality of cross-sectional studies was employed for this assessment. As shown in Supplementary Material 3, no studies were rated as low quality; 18 studies [32–39, 41–49] were rated as moderate quality; and 1 study [40] was rated as high quality. All studies explicitly identified the source of information. Four studies [32, 34, 35, 37] did not specify the inclusion and exclusion criteria for the exposed and unexposed subjects, nor did they refer to previous publications. Three studies [36, 37, 40] provided explanations for excluding any patients from the analysis. One study [33] did not describe how confounding factors were assessed and/or controlled. Only one study included follow-up data [40].

Prevalence of KOA

Given the high heterogeneity (I² = 99.7%, P < 0.001), a random-effects model was applied for the analysis. The results indicated that the overall prevalence of KOA in China from 2013 to 2023 was 28.0% (95% CI: 20.0%−37.0%) (Fig. 2).

Fig. 2.

Forest plot showing prevalence of KOA

Subgroup analyses

Subgroup analyses were performed based on sex, age, BMI, sampling resources, study region, and altitude (Table 2). The prevalence of KOA in women was 33.9% (95% CI: 26.4%−41.9%), which was higher than in men, where the prevalence was 20.5% (95% CI: 13.7%−28.2%). Age-based prevalence analysis showed an initial increase, followed by a decrease, with the highest prevalence observed in the 60–69 age group. The prevalence rates were 19.4% (95% CI: 8.9%−32.7%) for the 40–49 age group, 20.6% (95% CI: 11.7%−31.1%) for the 50–59 age group, 32.8% (95% CI: 21.4%−45.2%) for the 60–69 age group, 29.7% (95% CI: 23.9%−35.8%) for the 70–79 age group, and 32% (95% CI: 20.9%−44.2%) for those aged ≥ 80. Regarding BMI, the highest prevalence was found in individuals with a BMI ≥ 28 kg/m², at 50.5% (95% CI: 29.0%−71.9%), followed by 44.6% (95% CI: 19.2%−71.6%) for those with a BMI between 24 and 28 kg/m², and the lowest prevalence was 23.3% (95% CI: 11.6%−37.5%) in those with a BMI < 24 kg/m². The prevalence in rural and urban areas was similar, at 24.2% (95% CI: 22.1%−26.5%) and 25.5% (95% CI: 20.2%−31.2%), respectively. The prevalence in areas with mixed rural and urban populations was 30.5% (95% CI: 17.2%−45.7%). The prevalence in northern China was slightly higher, at 29.4% (95% CI: 18.9%−41.2%), compared to 24.9% (95% CI: 18.5%−31.8%) in southern China. The prevalence in high-altitude areas was significantly higher than in low-altitude areas, at 44.4% (95% CI: 23.0%−66.9%) and 21.8% (95% CI: 16.4–27.7), respectively.

Table 2.

Subgroup analysis results of included studies

Subgroup	No. of studies	Prevalence% (95% CI)	I2	P
Overall	18	0.28 (0.20, 0.37)	99.7	< 0.001
Sex				< 0.001
Male	18	0.205(0.137,0.282)	99.036
Female	18	0.339(0.264,0.419)	99.002
Age(years)				< 0.001
40–49	8	0.194 (0.089, 0.327)	97.826
50–59	14	0.206 (0.117, 0.311)	98.655
60–69	13	0.328 (0.214, 0.452)	98.643
70–79	6	0.297 (0.239, 0.358)	87.170
≥ 80	7	0.320 (0.209, 0.442)	94.789
BMI				< 0.001
< 24	6	0.233 (0.116, 0.375)	99.025
24 ≤ BMI < 28	6	0.446 (0.192, 0.716)	99.550
≥ 28	6	0.505 (0.290, 0.719)	98.124
Sampling Resources				< 0.001
Rural	1	0.242 (0.221, 0.265)
Urban	9	0.255 (0.202, 0.312)	96.943
Urban and rural	8	0.305 (0.172, 0.457)	99.756
Study Region				< 0.001
North China	11	0.294 (0.189, 0.412)	99.658
South China	7	0.249 (0.185, 0.318)	97.696
Altitude				< 0.001
High altitude area	5	0.444 (0.230, 0.669)	99.630
Low altitude area	13	0.218 (0.164, 0.277)	99.020

BMI Body mass index

Sensitivity analysis and meta-regression

A sensitivity analysis was conducted to assess the impact of individual studies on the results. The results were stable (Fig. 3). We performed a meta-regression on the included studies, using sex, BMI, sampling resources, study region, and altitude as covariates to identify the sources of heterogeneity in the study results (Table 3). The results revealed that sex (P = 0.058), BMI (P = 0.167), sampling resources (P = 0.577), and study region (P = 0.614) were not significantly associated with the prevalence of KOA in the Chinese population. Altitude (P = 0.026) may influence the prevalence of KOA in the Chinese population.

Fig. 3.

Sensitivity analysis

Table 3.

Meta-regression analysis of included studies

Covariates	Coefficient	Prevalence% (95% CI)	P
Sex	−0.1224102	−0.249389 to 0.0045685	0.058
BMI	0.1193532	−0.0552379 to 0.2939443	0.167
Sampling Resources	0.0422022	−0.1150036 to 0.1994079	0.577
Study Region	−0.0464984	−0.2383049 to 0.1453082	0.614
Altitude	0.2072192	0.0288484 to 0.38559	0.026

Publication bias

The statistical evaluation revealed no publication bias in these studies (Egger’s test P = 0.069 and Begg’s test, P = 0.495) (Figs. 4 and 5).

Fig. 4.

Egger’s publication bias plot

Fig. 5.

Begg’s publication bias plot

Discussion

This study is the first to conduct a systematic review and meta-analysis of the prevalence of KOA in China over the past decade. The results showed that the prevalence of KOA in China from 2013 to 2023 was 28.0%. The prevalence in females was 33.9%, while in males it was 20.5%. The age group of 60–69 years had the highest prevalence, at 32.8%. The highest prevalence was observed in individuals with a BMI ≥ 28 kg/m², at 50.5%. The prevalence in northern China was 4.5% higher than that in the southern region. The prevalence in high-altitude areas was 22.6% higher than in low-altitude areas. The prevalence rates in rural and urban areas were similar.

Age-related differences in the prevalence of KOA in China

The analysis revealed that the prevalence of KOA in China is significantly higher than that in the global (22.9%) and Asian populations (19.2%) [52]. After the age of 70, OA becomes the seventh leading cause of disability globally, with the knee being the most affected joint [53, 54]. Xu [55] found in a Longitudinal survey conducted between 2011 and 2012 that the prevalence of KOA in the Chinese population increased with age, stabilizing after 70 years old. This result is consistent with our findings. We speculate that this may be related to the reduction in heavy physical activity among the elderly. As aging intensifies, the prevalence of KOA continues to rise [56, 57]. Cho et al. [58] found that for every 5-year increase, the risk of KOA progression increases by 1.6 times. A cross-sectional study [59] found that individuals aged 65 years or older had a 3.56-fold higher risk of moderate to severe KOA compared to those under 65 years of age.

Changes in the biomechanical characteristics of the knee joint are an important factor in the development of KOA [60]. Due to significant degenerative changes in the knee joint of the elderly, biomechanical instability, increased patellofemoral joint pressure, inflammatory infiltration, and stimulation occur, leading to pain and limited joint movement, further exacerbating muscle contraction disorders and imbalance in the load on lower limb cartilage [61]. Mechanical stress affects the development and maturation of chondrocytes [62]. Studies have found that abnormal mechanical stress significantly increases the number of senescent chondrocytes [63].

Degeneration of articular cartilage is a hallmark of OA [64]. Articular cartilage provides a smooth surface, reduces friction, alleviates pressure, maintains joint morphology, and facilitates joint movement [65]. Its destruction leads to joint pain, stiffness, and functional decline. Aging is closely associated with cartilage degeneration [66]. Studies have shown that chondrocytes in the joint undergo aging with increasing age [67], and their number gradually decreases [68]. Cartilage degeneration leads to cartilage thickening, synovitis, and osteophyte formation [69, 70]. Compared to younger individuals, chondrocytes isolated from elderly cartilage are more sensitive to oxidative stress [71]. In addition, the aging process is associated with low-grade chronic inflammation [72]. In the elderly, the increase in pro-inflammatory cytokines stimulates joint degradation, increases susceptibility to cell death, reduces matrix synthesis, lowers resistance and tensile strength, and alters mechanical properties [73]. Therefore, age is an important factor influencing the prevalence of KOA.

Gender-related differences in the prevalence of KOA in China

We found that the prevalence of KOA in Chinese women (33.9%) is significantly higher than that in men (20.5%). From 40 to 70 years old, the difference in prevalence between men and women increases every decade, with the largest difference of 22.42% observed in the 70–79 age group, followed by 13.9% in those aged ≥ 80 years and 13.43% in the 60–69 age group (Fig. 6). Globally, the prevalence and incidence rate ratios for women compared to men are 1.69 and 1.39, respectively [52]. In Spain, the risk of KOA in women is 2 to 3.5 times higher than in men [74]. In Saudi Arabia, the odds ratio for the prevalence of KOA in women compared to men is 2.146 [75]. A global systematic review and meta-analysis indicated that women are a risk factor for KOA, with a risk 1.04 times higher than that in men [76, 77].

Fig. 6.

The trend of the prevalence of KOA changes with age

In women, low levels of estradiol, progesterone, and testosterone are associated with knee effusion-synovitis and related structural changes, which may contribute to the gender differences in KOA [78]. Estradiol can reduce the expression of intra-articular inflammatory factors, increase pain tolerance, and delay the progression of osteoarthritis [79, 80]. However, after menopause, women's estrogen levels significantly decrease, leading to the loss of estrogen's protective effects and increased subchondral bone remodeling, which in turn increases the risk of arthritis in women [81, 82]. Higher serum testosterone levels can alleviate osteoarthritis pain, provide joint protection, and reduce the disability rate in women [83, 84].

At the same time, muscle strength plays an important role in KOA [85]. Women have lower muscle strength than men, particularly during pregnancy, when rapid weight gain increases the load on muscles and the knee joint. A study in the United States showed [86] that gravity affects walking difficulties in elderly women. Women who have been pregnant six times or more have a significantly higher rate of walking limitations than those who have been pregnant four times or fewer. The more pregnancies a woman has, the greater the likelihood of experiencing walking difficulties. Hussain SM [87] found that pregnancy and the number of births increase the risk of TKA. This may be due to weight gain during pregnancy and postpartum weight retention [88, 89], which increases the risk of KOA in women [90].

Furthermore, it is related to the frequency of squatting among women. Due to traditional societal norms in China, women engage in more household chores than men, and frequent squatting during housework can exacerbate knee joint wear. Additionally, many households in China do not have toilets, requiring women to squat frequently when using the restroom, which further contributes to the onset of KOA. The difference in KOA prevalence between men and women in China may be the result of the long-term combined effects of the various factors mentioned above.

Prevalence of KOA in China and its differences related to BMI

In this systematic review and meta-analysis, the highest prevalence was observed in individuals with a BMI ≥ 28 kg/m², accounting for half of the total number of cases, followed by those with a BMI between 24 and 28 kg/m². This suggests a close relationship between obesity and the onset of KOA [1]. Toivanen [91] conducted a large-scale, 22-year prospective study and found that individuals with a BMI ≥ 30 kg/m² had a seven-fold higher risk of KOA than those with a BMI < 25 kg/m². A study in Japan [92] showed that maintaining a Lighter weight over a 10-year period can reduce the risk of KOA by 27.5%. A systematic review and meta-analysis on the risk factors for KOA [76] pointed out that a BMI ≥ 24 kg/m² has been shown to be a risk factor for the onset of KOA in cohort studies. A recent study on the association between weight gain and KOA [93] found that weight gain in adults is associated with an increased risk of KOA, specifically manifesting as significant adverse effects on pain, stiffness, function, and health-related quality of life, as well as detrimental impacts on cartilage, bone marrow lesions, meniscal injury, and effusion/synovitis. Excessive BMI leads to an increased biomechanical load on the knee joint, causing a shift in the knee’s mechanical axis, uneven pressure distribution on the joint surface, leading to uneven cartilage wear, and further accelerating joint degeneration [94].

It is currently widely believed that obesity is a form of low-grade chronic inflammation [95], with elevated levels of TNF-α, IL-1, and IL-6 found in the synovial fluid, synovium, subchondral bone, and cartilage of arthritis patients [94]. These inflammatory factors also affect the function of insulin receptors, exacerbating insulin resistance, which is positively correlated with KOA [96, 97]. Ayumi Ito et al. [92] found that maintaining a Lighter weight over a period of 10 years could reduce the risk of KOA by 27.5%. Therefore, obesity is a key factor in exacerbating knee joint damage, and weight loss is an effective measure for preventing and treating KOA. However, the symptoms of joint pain and swelling in KOA hinder the patient's ability to lose weight. Therefore, breaking this vicious cycle requires a comprehensive approach, including scientific weight loss, appropriate exercise [98], and suitable treatment.

Prevalence of KOA in China and its geographical differences

The prevalence of KOA in northern China is 4.5% higher than in the south, and in high-altitude areas, it is 22.6% higher than in low-altitude areas (Fig. 7). The geographical environment, climate characteristics, and lifestyle in China have a certain impact on the occurrence and development of knee osteoarthritis. In northern regions, winters are cold and dry, while the southern climate is humid. In plateau areas, both temperature and air pressure decrease as altitude increases. Previous studies have found that the prevalence of KOA in plateau areas is higher than in plain regions [99], which is consistent with our research findings. This may be due to the prolonged exposure to high-altitude environments, where blood oxygen levels decrease, leading to poor blood circulation around the joints, thereby affecting the nutrient supply to the joint soft tissues. Hypoxia may also lead to a decrease in bone density, thereby accelerating the development of KOA. Additionally, these regions have large variations in terrain, and people frequently engage in activities such as hiking and climbing slopes, further increasing the burden on the knee joints. Environmental and climatic factors may also influence the clinical symptoms of KOA [100–102]. Yan et al. [103] found a strong correlation between weather sensitivity and knee pain and dysfunction. This result may be due to patients who are sensitive to weather being more susceptible to external climate changes, which exacerbates symptoms related to KOA. A study in Russia found that climatic factors affect the radiographic severity of OA patients [104]. Wang et al. [105] conducted a meta-analysis on weather conditions and OA pain, finding a negative correlation between temperature and OA pain intensity, and a positive correlation between barometric pressure and OA pain. Similarly, a study by Timmermans et al. [106] demonstrated an interaction between cold and humidity, with humidity having a stronger effect on osteoarthritis under cold conditions. The winter in northern China is cold, which may lead to increased viscosity of synovial fluid under cold conditions, resulting in stiffer joints, more friction between joint tissues, and increased sensitivity to mechanical stress pain [107]. In addition, the dietary structure in northern China mainly consists of meat, with frequent consumption of high-salt and high-fat foods [108]. This may contribute to the higher prevalence in northern China, which is 4.5% higher than in the south, and could also increase the risk of KOA.

Fig. 7.

The prevalence rates of KOA in different provinces included in the literature

Prevalence of KOA in China and its differences based on sampling resources

The results show that the prevalence of KOA is comparable between rural and urban areas, at 24.2% and 25.5%, respectively. The 2011 China Health and Retirement Longitudinal Study [55] found that symptomatic knee OA was more common in rural areas than in urban areas (OR 1.84). A study in South Korea also found [109] that living in rural areas was associated with a higher risk of knee osteoarthritis compared to urban areas (OR 1.26). However, in our study, the prevalence was 1.3% lower in rural areas than in urban areas. We speculate that this may be due to the fact that only one study from rural areas was included. However, in areas where both rural and urban populations were studied, the prevalence was higher at 30.5%. Over the past 30 years, rural areas have generally had Limited resources, including fewer clinics, Limited public transportation, fewer exercise facilities, more physical labor, and insufficient health education. However, with the rapid urbanization in China, the urbanization rate increased from 17.9% in 1978 to over 60% by 2020. People's lifestyles and work habits have also changed, and sedentary behavior and lack of exercise may lead to weakened muscle strength around the knee joint, decreased joint function, and thus an increased incidence of urban KOA.

Therefore, in clinical practice, healthcare professionals should prioritize elderly patients, especially peri-menopausal women, as key screening targets, identifying high-risk populations to enable early detection, prevention, and treatment.For obese patients, a scientifically-based weight loss strategy should be developed, combining diet, exercise, and treatment. At the same time, public health departments can reduce the prevalence of KOA in a comprehensive manner through “prevention-screening-intervention-support.” Strengthening joint health screenings for middle-aged and elderly individuals, and establishing a database for high-risk populations, as well as an epidemiological monitoring system for KOA. In 2025, the National Health Commission will launch a three-year "Weight Management Year" campaign, elevating scientific weight loss from personal health to a national strategy. Strengthening the promotion of healthy eating, developing scientific meal plans according to regional needs, controlling energy intake, and ensuring a balanced distribution. Strengthening public education and health guidance, implementing a national scientific exercise program, and cultivating good exercise habits. For occupations that require long periods of kneeling or weight-bearing, especially for female workers, provide relevant labor protection policies. Overall, establishing comprehensive public health policies is crucial to effectively reducing the incidence and severity of KOA.

This study has some Limitations. The data in this meta-analysis are unevenly distributed across the country, with a lack of data from central China, which results in incomplete findings. These issues warrant further attention and should be addressed in future studies as much as possible. The heterogeneity between studies is large due to differences in the participants, equipment used, and diagnostic criteria for KOA. We estimate that the sources of heterogeneity may be related to factors such as occupation, underlying diseases, and educational level. Although we included 18 papers with a total of 29,771 participants, not all studies provided comprehensive demographic characteristics of the participants. Some subgroups included fewer studies with smaller sample sizes, which may reduce the reliability of the results. Detailed demographic data would be more helpful in assessing the prevalence characteristics of KOA in China. Therefore, future studies need to conduct large-scale prospective cohort studies and more detailed subgroup analyses. As new studies emerge, this research needs to be updated further.

Conclusion

In summary, over the past decade, the prevalence of KOA in China has been relatively high, and it gradually increases with age. The prevalence of KOA is closely related to gender and BMI and shows regional distribution patterns, although the difference between urban and rural areas is relatively small. This indicates the need to develop and implement KOA prevention and control strategies and health education programs for the elderly population, with special attention to women and obese patients. Strengthening the prevention and treatment efforts for the KOA population will help reduce the prevalence and severity of the disease.

Abbreviations

KOA

Knee osteoarthritis

BMI

Body Mass Index

OA

Osteoarthritis

YLDs

Years lost due to disability

DALYs

Disability-adjusted life years

NSAIDs

Nonsteroidal anti-inflammatory drugs

TKA

Total knee arthroplasty

PROSPERO

Prospective Register of Systematic Reviews

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

CBM

Chinese Biomedical Database

CNKI

Chinese National Knowledge Infrastructure

VIP

Chinese Scientific Journal Database

AHRQ

Agency for Healthcare Research and Quality

CI

Confidence interval

COX-2

Cyclooxygenase-2

KL

The Kellgren and Lawrence

ACR

The American College of Rheumatology classification criteria

Authors’ contributions

XC and YW designed the study and drafted the manuscript. CLS and LL systematically retrieved the literature and extracted data. LL reviewed the included studies and performed statistical analyses. CLS and LL independently evaluated the quality of the studies that met the inclusion criteria. YW adjudicates ambiguities. XC and ZZ provided useful suggestions and substantial revisions based on the content of the article. All authors participated in the drafting of the manuscript and approved the final version.

Funding

This study was supported by the National Natural Science Foundation of China (30760102600).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

This study was registered in the International Prospective Register of Systematic Reviews (PROSPERO number CRD42024590187).

Consent for publication

As corresponding author of this manuscript, we hereby explicitly agree to have this manuscript published by Journal of Orthopaedic Surgery and Research. We fully understand and acknowledge all the terms and regulations involved in the publishing process, including but not limited to copyright transfer, manuscript editing and modification, as well as arrangements regarding the publishing format and channels. We promise that the content of the manuscript is authentic, legal and free from any infringement upon the rights and interests of others, and we are willing to assume all legal responsibilities and consequences arising from the content of the manuscript.

Competing interests

The authors declare no competing interests.