# Study on the Influencing Factors of Osteoarthritis in Southern China

Authors: Danqing Lu; Xiaomin Ding; Wenqing Lu
Journal: Emergency Medicine International
 (2022)

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## Abstract

Background. Osteoarthritis (OA) is a common chronic disease with numerous and interacting influencing factors, and current inadequate patient perceptions and behaviors in access to care contribute to the difficulties in the diagnosis, treatment, and management of osteoarthritis. Objective. The purpose of this study was to investigate the influencing factors of osteoarthritis (OA) in a southern Chinese population and to provide a scientific basis for the prevention and treatment of OA. Methods. A 1 : 2 matched case-control study was used to select 160 patients with OA from three hospitals in southern China as a case group. Three hundred and twenty cases of the same sex and similar age (within ± 2 years) were selected as the control group, and relevant data were collected for univariate and multivariate conditional logistic regression analysis. Results. There were no significant differences between the two groups of participants in terms of age, sex, and education (P>0.05). Logistic regression statistical analysis showed that genetic factors (OR = 4.52, 95% CI = 1.56–7.83), body mass index (OR = 2.57, 95% CI = 1.16–5.84), alcohol consumption (OR = 3.81, 95% CI = 1.53–5.87), and a history of external joint limb injury (OR = 3.37, 95% CI = 1.67–5.24) would increase the risk of OA. In contrast, eating more fresh vegetables (OR = 0.08, 95% CI = 0.03–0.31), more fresh fruits (OR = 0.34, 95% CI = 0.12–0.96), more soy products (OR = 0.11, 95% CI = 0.04–0.45), and exposure to sunlight (OR = 0.31, 95% CI = 0.14–0.71) would reduce the OA risk of OA. Conclusion. Obesity, alcohol consumption, and a history of joint trauma all increase the risk of OA in a southern Chinese population, whereas a diet rich in fresh vegetables, fresh fruit, soy products, and sun exposure would reduce the risk of OA. In the future, we should focus on improving patients’ awareness of medical care and developing their self-management skills, improving GPs’ treatment skills, improving negative attitudes of both doctors and patients, and promoting positive patient care.


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## Body

## 1. Introduction

On January 23, 2000, the World Health Organization (WHO) launched a worldwide campaign for the “Decade of Bones and Joints,” which aims to draw the attention of governments, medical research institutions, public, and all sectors of society to bone diseases, including osteoarthritis [1]. On October 12, 2001, the Ministry of Health (MOH) of China also held an awareness campaign for World Arthritis Day and decided to establish the MOH Arthritis Prevention and Control Education Program Fund [2]. Osteoarthritis (OA), also known as osteoarthritis, degenerative osteoarthropathy or proliferative arthritis, is an inflammatory disease characterized by damage to joint cartilage and osteophytes [3]. The etiology and pathogenesis of osteoarthritis are still unclear, and its occurrence is related to age, obesity, inflammation, trauma, and genetic factors, among which age is the main factor [4]. Preliminary surveys at home and abroad have shown that the overall incidence of osteoarthritis is about 15%, 10%–17% in people over 40 years, and 50% in people over 60 years [5]. Currently, there are 16 million patients with osteoarthritis in the United States, and in China, the population over 60 years is over 100 million, and it is estimated that there are more than 50 million patients with osteoarthritis [6]. Osteoarthritis occurs in joints with high load and high activity, such as the knee, spine (cervical and lumbar spine), hip, ankle, hand, and other joints. In Asia, osteoarthritis of the knee is predominant, which may be related to different living habits and living environments. The epidemiological findings show that the peak prevalence of osteoarthritis in men and women can reach 24.7% and 54.6%, respectively, which is one of the diseases that greatly endanger the health of the elderly and seriously affect their quality of life [7]. With the rapid development of social economy, people’s social lifestyle has changed, and the concept of health and medical model is also changing. It is too one-sided to evaluate the health status and treatment effect of patients only by quantitative indicators such as morbidity, mortality, survival rate, and cure rate. Osteoarthritis, as a chronic disease, seriously affects patients’ work, family, and social interactions, so we need to explore the factors influencing osteoarthritis (OA) in southern China more comprehensively to provide a scientific basis for the prevention and treatment of OA.Age is an independent risk factor for the development of osteoarthritis, and the prevalence of osteoarthritis increases with age [8, 9]. The overall prevalence of osteoarthritis is about 15%, 10%–17% in middle-aged and elderly people aged ≥40 years, 50% in those aged ≥60 years, and 80% in those aged ≥75 years [10,11]. OA has become one of the major diseases among the elderly in China, and prevention and reduction of OA has special significance in our current national situation. The study by Farhadian et al. [12] found that with the rising level of population aging in China, the family and socioeconomic burden of osteoarthritis patients has further increased. A study of 195 countries over the past 27 years found that the prevalence, incidence, and years of disability survival (YLDs) of osteoarthritis varied among countries, but with increasing life expectancy and an aging global population, all of these indicators are on the rise, posing a serious challenge to the world public health [13,14]. A study Jin et al. [15] found that nearly 2/3 of patients had poor understanding of the clinical manifestations of the osteoarthritis disease. There is a general lack of disease knowledge related to osteoarthritis basics, risk factors, diagnosis and treatment, and prevention in the middle-aged and elderly population in China [16, 17]. In this study, we selected orthopaedic and general practitioners in general hospitals and community general practitioners and patients to conduct a mixed-method study to understand the current status of patients’ perceptions and behaviors of osteoarthritis, analyze the problems and barriers affecting patients’ access to care and disease management, and provide optimal strategies for improving the access to care and disease prognosis of patients with osteoarthritis.


## 2. Materials and Methods

### 2.1. Participants

#### 2.1.1. Case Group

A total of 160 patients with OA were recruited and investigated from June to December 2019, visits from orthopaedic specialists at 3 hospitals in southern China of OA. The inclusion criteria are as follows: X-ray-diagnosed patients with positive OA. There are typical clinical manifestations of OA. Patients diagnosed with OA by an orthopaedic specialist. The above 3 standards must be met at the same time. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional or national research committee and with the 1964 Helsinki declaration and its later amendments are comparable ethical standards. This study is approved by the Ethics Committee of The Second People’s Hospital of Kunshan.


#### 2.1.2. Control Group

A hospital-based 1 : 2 paired case-control study was used. Patients who did not have OA in other outpatient clinics of the same hospital during the same period were used as a control. The matching conditions are the same sex and the age difference is less than 2 years.


### 2.2. Research Methods and Quality Control

After the written informed consent of the study subjects, a questionnaire survey was conducted in the same way for the case group and the control group. Self-designed questionnaires, including general conditions, living habits, genetic factors, past history, and specialties. Investigate the investigators uniformly before the investigation, and investigate the cases and controls in a unified way. Logically check the data before entering it, and correct any errors in a timely manner.


### 2.3. Statistical Analysis

After the data were collected and sorted, EpiData 3.2 software was used to establish the database. SPSS 23.0 statistical software was used to perform single-factor and multifactor conditional logistic regression analysis. Count data is described byn (%), and measurement data is expressed by mean ± standard deviation. P<0.05 was considered statistically significant.


## 2.1. Participants

### 2.1.1. Case Group

A total of 160 patients with OA were recruited and investigated from June to December 2019, visits from orthopaedic specialists at 3 hospitals in southern China of OA. The inclusion criteria are as follows: X-ray-diagnosed patients with positive OA. There are typical clinical manifestations of OA. Patients diagnosed with OA by an orthopaedic specialist. The above 3 standards must be met at the same time. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional or national research committee and with the 1964 Helsinki declaration and its later amendments are comparable ethical standards. This study is approved by the Ethics Committee of The Second People’s Hospital of Kunshan.


### 2.1.2. Control Group

A hospital-based 1 : 2 paired case-control study was used. Patients who did not have OA in other outpatient clinics of the same hospital during the same period were used as a control. The matching conditions are the same sex and the age difference is less than 2 years.


## 2.1.1. Case Group

A total of 160 patients with OA were recruited and investigated from June to December 2019, visits from orthopaedic specialists at 3 hospitals in southern China of OA. The inclusion criteria are as follows: X-ray-diagnosed patients with positive OA. There are typical clinical manifestations of OA. Patients diagnosed with OA by an orthopaedic specialist. The above 3 standards must be met at the same time. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional or national research committee and with the 1964 Helsinki declaration and its later amendments are comparable ethical standards. This study is approved by the Ethics Committee of The Second People’s Hospital of Kunshan.


## 2.1.2. Control Group

A hospital-based 1 : 2 paired case-control study was used. Patients who did not have OA in other outpatient clinics of the same hospital during the same period were used as a control. The matching conditions are the same sex and the age difference is less than 2 years.


## 2.2. Research Methods and Quality Control

After the written informed consent of the study subjects, a questionnaire survey was conducted in the same way for the case group and the control group. Self-designed questionnaires, including general conditions, living habits, genetic factors, past history, and specialties. Investigate the investigators uniformly before the investigation, and investigate the cases and controls in a unified way. Logically check the data before entering it, and correct any errors in a timely manner.


## 2.3. Statistical Analysis

After the data were collected and sorted, EpiData 3.2 software was used to establish the database. SPSS 23.0 statistical software was used to perform single-factor and multifactor conditional logistic regression analysis. Count data is described byn (%), and measurement data is expressed by mean ± standard deviation. P<0.05 was considered statistically significant.


## 3. Results

### 3.1. General Demographics

A total of 501 questionnaires were returned, excluding 21 incomplete questionnaires, and a total of 480 valid questionnaires were obtained. There were 160 cases in the case group and 320 cases in the control group, of which 204 were male and 276 were female, with a sex ratio of 1 : 1.35. The age of the case group was 78 years, the youngest was 26 years, and the mean age was (57.36± 6.58) years. The age of the control group was 79 years, the youngest was 26 years, and the mean age was (58.06 ± 5.99) years. There was no significant difference between the two groups in terms of age and gender (P>0.05). The education level of the case group was as follows: 39.79% were elementary school and below, 26.04% were junior high school, 22.50% were high school or secondary school, and 11.67% were college and above. The educational level of the control group was 40.31% for elementary school and below, 25.63% for middle school, 23.12% for high school or secondary school, and 10.94% for college and above. There was no significant difference between the two groups in terms of education (P>0.05). The results are shown in Table 1.Table 1
The assignment of each study variable.
VariablesAssignmentsLiving environmentQuiet = 0 and noisy = 1Genetic factors(family with or without a history of OA)None = 0, 1 person = 1, 2 persons = 2, 3 and above = 3Staple foodMainly coarse and coarse grains = 0 and mainly polished rice and flour = 1BMI (kg/m2)<23 = 0, 23∼25 = 1, and >25 = 2Family per capita monthly income (RMB)<2000 = 0, 2000∼5000 = 1, and >5000 = 2Consumption of fresh vegetablesRarely = 0, <400 g/d = 1, and ≥400 g/d = 2Consumption of fresh fruitsRarely = 0, <100 g/d = 1, and ≥100 g/d = 2Egg consumptionRarely = 0, 1∼3 eggs/week = 1, 4∼6 eggs/week = 2, and ≥7 eggs/week = 3Consumption of soy productsRarely = 0, <100 g/d = 1, and ≥100 g/d = 2SmokingNone = 0 and smoking = 1DrinkingNone = 0 and drinking = 1Difficulty in falling asleep, awakening during sleep, or dreaming oftenNone = 0 and yeah = 1Have a nap habitNone = 0 and yeah = 1Sunshine duration (h/d)<4 = 0 and ≥4 = 1Take part in the physical exerciseNone = 0 and yeah = 1History of joint traumaNone = 0 and yeah = 1


### 3.2. Prevalence of OA and Univariate Analysis

The OA patients were mainly affected by the knee joint, accounting for 60.42%, followed by the low and middle lumbar joints (20.21%). The disease involved 54 patients with one joint, 66 with two, 23 with three, and 17 with more than three. Logistic analysis showed that there were statistically significant differences in 16 indicators between the case and the control group (P<0.05). The statistical analysis results are shown in Table 2.Table 2
Logistic analysis of univariate conditions affecting OA.
VariablesBSexWaldPOR (95% CI)Living environment1.3850.26513.57<0.0014.09 (1.99, 8.47)Genetic factors1.9620.58810.920.0017.96 (2.38, 25.43)Staple food0.8960.3169.320.0022.65 (1.38, 5.06)BMI0.7950.2639.410.0012.28 (1.31, 3.97)Family per capita monthly income (RMB)0.3410.1427.420.0061.42 (1.12, 1.86)Consumption of fresh vegetables−1.6580.32225.120.0010.19 (0.10, 0.32)Consumption of fresh fruits−0.6880.21911.16<0.0010.45 (0.29, 0.71)Egg consumption−0.5150.1519.180.0020.65 (0.49, 0.86)Consumption of soy products−1.1020.24817.11<0.0010.34 (0.21, 0.56)Smoking0.7180.3354.250.0411.95 (1.04, 3.82)Drinking1.2070.3729.380.0013.16 (1.56, 6.72)Difficulty in falling asleep, awakening during sleep, or dreaming often1.0550.31712.140.0012.74 (1.54, 4.85)Have a nap habit−0.8510.25910.65<0.0010.45 (0.27, 0.73)Sunshine duration−0.6140.13816.91<0.0010.57 (0.43, 0.76)Take part in the physical exercise−0.7290.2797.410.0060.49 (0.27, 0.83)History of joint trauma1.2090.3987.940.0053.11 (1.39, 6.87)The noisy living environment, the consumption of polished rice and noodles, overweight or obesity, smoking, and drinking are the risk factors for OA. Regular consumption of fresh vegetables, fruits, eggs, soy products, the habit of taking a nap, long sunshine hours, and regular physical exercises are the protective factors.


### 3.3. Multivariate Stepwise Conditional Logistic Regression Analysis

The proposed variables were included in the standardα in = 0.05 and the standard α out = 0.05. The multifactor conditional logistic regression analysis was performed on the above factors. The 16 factors with statistical significance were screened for variables using the backward stepwise method. The factors that were finally selected in the regression equation included genetic factors, body mass index (BMI), consumption of fresh vegetables, consumption of fresh fruits, consumption of soy products, sunshine duration, drinking, and history of joint trauma. Logistic regression statistical analysis results suggest that genetic factors (OR = 4.52, 95% CI = 1.56–7.83), body mass index (OR = 2.57, 95% CI = 1.16–5.84), alcohol consumption (OR = 3.81, 95% CI = 1.53–5.87), and a history of external injury of the joint limb (OR = 3.37, 95% CI = 1.67–5.24) will increase the risk of OA. While taking more fresh vegetables (OR = 0.08, 95% CI = 0.03–0.31), taking more fresh fruits (OR = 0.34, 95% CI = 0.12–0.96), taking more soy products (OR = 0.11, 95% CI = 0.04–0.45), and exposure to the sun (OR = 0.31, 95% CI = 0.14–0.71) will reduce the risk of OA. The results of statistical analysis are shown in Table 3.Table 3
Logistic regression analysis of multivariate conditions influencing factors of OA.
VariablesβSexWaldPOR (95% CI)Genetic factors1.7950.6996.690.0114.52 (1.56, 7.83)BMI0.9740.4294.790.0252.57 (1.16, 5.84)Drinking2.5180.8558.460.0213.81 (1.53, 5.87)Consumption of fresh vegetables−2.6470.71512.810.0010.08 (0.03, 0.31)Consumption of fresh fruits−1.0390.5163.920.0430.34 (0.12, 0.96)Consumption of soy products−2.2710.7628.650.0030.11 (0.04, 0.45)Sunshine duration−1.2050.4257.920.0040.31 (0.14, 0.71)History of joint trauma2.8160.9046.960.0153.37 (1.67, 5.24)


## 3.1. General Demographics

A total of 501 questionnaires were returned, excluding 21 incomplete questionnaires, and a total of 480 valid questionnaires were obtained. There were 160 cases in the case group and 320 cases in the control group, of which 204 were male and 276 were female, with a sex ratio of 1 : 1.35. The age of the case group was 78 years, the youngest was 26 years, and the mean age was (57.36± 6.58) years. The age of the control group was 79 years, the youngest was 26 years, and the mean age was (58.06 ± 5.99) years. There was no significant difference between the two groups in terms of age and gender (P>0.05). The education level of the case group was as follows: 39.79% were elementary school and below, 26.04% were junior high school, 22.50% were high school or secondary school, and 11.67% were college and above. The educational level of the control group was 40.31% for elementary school and below, 25.63% for middle school, 23.12% for high school or secondary school, and 10.94% for college and above. There was no significant difference between the two groups in terms of education (P>0.05). The results are shown in Table 1.Table 1
The assignment of each study variable.
VariablesAssignmentsLiving environmentQuiet = 0 and noisy = 1Genetic factors(family with or without a history of OA)None = 0, 1 person = 1, 2 persons = 2, 3 and above = 3Staple foodMainly coarse and coarse grains = 0 and mainly polished rice and flour = 1BMI (kg/m2)<23 = 0, 23∼25 = 1, and >25 = 2Family per capita monthly income (RMB)<2000 = 0, 2000∼5000 = 1, and >5000 = 2Consumption of fresh vegetablesRarely = 0, <400 g/d = 1, and ≥400 g/d = 2Consumption of fresh fruitsRarely = 0, <100 g/d = 1, and ≥100 g/d = 2Egg consumptionRarely = 0, 1∼3 eggs/week = 1, 4∼6 eggs/week = 2, and ≥7 eggs/week = 3Consumption of soy productsRarely = 0, <100 g/d = 1, and ≥100 g/d = 2SmokingNone = 0 and smoking = 1DrinkingNone = 0 and drinking = 1Difficulty in falling asleep, awakening during sleep, or dreaming oftenNone = 0 and yeah = 1Have a nap habitNone = 0 and yeah = 1Sunshine duration (h/d)<4 = 0 and ≥4 = 1Take part in the physical exerciseNone = 0 and yeah = 1History of joint traumaNone = 0 and yeah = 1


## 3.2. Prevalence of OA and Univariate Analysis

The OA patients were mainly affected by the knee joint, accounting for 60.42%, followed by the low and middle lumbar joints (20.21%). The disease involved 54 patients with one joint, 66 with two, 23 with three, and 17 with more than three. Logistic analysis showed that there were statistically significant differences in 16 indicators between the case and the control group (P<0.05). The statistical analysis results are shown in Table 2.Table 2
Logistic analysis of univariate conditions affecting OA.
VariablesBSexWaldPOR (95% CI)Living environment1.3850.26513.57<0.0014.09 (1.99, 8.47)Genetic factors1.9620.58810.920.0017.96 (2.38, 25.43)Staple food0.8960.3169.320.0022.65 (1.38, 5.06)BMI0.7950.2639.410.0012.28 (1.31, 3.97)Family per capita monthly income (RMB)0.3410.1427.420.0061.42 (1.12, 1.86)Consumption of fresh vegetables−1.6580.32225.120.0010.19 (0.10, 0.32)Consumption of fresh fruits−0.6880.21911.16<0.0010.45 (0.29, 0.71)Egg consumption−0.5150.1519.180.0020.65 (0.49, 0.86)Consumption of soy products−1.1020.24817.11<0.0010.34 (0.21, 0.56)Smoking0.7180.3354.250.0411.95 (1.04, 3.82)Drinking1.2070.3729.380.0013.16 (1.56, 6.72)Difficulty in falling asleep, awakening during sleep, or dreaming often1.0550.31712.140.0012.74 (1.54, 4.85)Have a nap habit−0.8510.25910.65<0.0010.45 (0.27, 0.73)Sunshine duration−0.6140.13816.91<0.0010.57 (0.43, 0.76)Take part in the physical exercise−0.7290.2797.410.0060.49 (0.27, 0.83)History of joint trauma1.2090.3987.940.0053.11 (1.39, 6.87)The noisy living environment, the consumption of polished rice and noodles, overweight or obesity, smoking, and drinking are the risk factors for OA. Regular consumption of fresh vegetables, fruits, eggs, soy products, the habit of taking a nap, long sunshine hours, and regular physical exercises are the protective factors.


## 3.3. Multivariate Stepwise Conditional Logistic Regression Analysis

The proposed variables were included in the standardα in = 0.05 and the standard α out = 0.05. The multifactor conditional logistic regression analysis was performed on the above factors. The 16 factors with statistical significance were screened for variables using the backward stepwise method. The factors that were finally selected in the regression equation included genetic factors, body mass index (BMI), consumption of fresh vegetables, consumption of fresh fruits, consumption of soy products, sunshine duration, drinking, and history of joint trauma. Logistic regression statistical analysis results suggest that genetic factors (OR = 4.52, 95% CI = 1.56–7.83), body mass index (OR = 2.57, 95% CI = 1.16–5.84), alcohol consumption (OR = 3.81, 95% CI = 1.53–5.87), and a history of external injury of the joint limb (OR = 3.37, 95% CI = 1.67–5.24) will increase the risk of OA. While taking more fresh vegetables (OR = 0.08, 95% CI = 0.03–0.31), taking more fresh fruits (OR = 0.34, 95% CI = 0.12–0.96), taking more soy products (OR = 0.11, 95% CI = 0.04–0.45), and exposure to the sun (OR = 0.31, 95% CI = 0.14–0.71) will reduce the risk of OA. The results of statistical analysis are shown in Table 3.Table 3
Logistic regression analysis of multivariate conditions influencing factors of OA.
VariablesβSexWaldPOR (95% CI)Genetic factors1.7950.6996.690.0114.52 (1.56, 7.83)BMI0.9740.4294.790.0252.57 (1.16, 5.84)Drinking2.5180.8558.460.0213.81 (1.53, 5.87)Consumption of fresh vegetables−2.6470.71512.810.0010.08 (0.03, 0.31)Consumption of fresh fruits−1.0390.5163.920.0430.34 (0.12, 0.96)Consumption of soy products−2.2710.7628.650.0030.11 (0.04, 0.45)Sunshine duration−1.2050.4257.920.0040.31 (0.14, 0.71)History of joint trauma2.8160.9046.960.0153.37 (1.67, 5.24)


## 4. Discussion

The degradation of cartilage is a hallmark of osteoarthritis, a joint condition brought on by mechanical, metabolic, inflammatory, and immunological mechanisms [18, 19]. Reduced force absorption caused by damaged articular cartilage and increased wear on the ends of joints contributes to the disease's etiology, which can lead to progressive joint injury and degeneration. Clinical studies have shown that patients with osteoarthritis are commonly found in the joints that bear large amounts of weight, such as the ankle, knee, and hip. Once suffering from osteoarthritis, patients suffer from joint pain and functional impairment in going up and down the stairs, walking or getting off and getting into a car, and the quality of daily life is significantly reduced, and the physical and mental health of patients are compromised [20,21]. With the continuous improvement of the medical level, more and more patients with osteoarthritis choose to perform total knee arthroplasty, however, related studies have concluded that human work and life pressures are increasing, and this situation also causes some people to have psychological disorders, which, together with osteoarthritis disease, is not conducive to the physical recovery of the patients after total knee arthroplasty, and the clinical treatment effect is not good [22,23].The results of this study suggest that long-term consumption of high amounts of vegetables and fresh fruits can reduce the risk of OA, mainly because of the high levels of vitamin C. Studies Janssens et al. [24,25] have shown that the risk of knee OA is three times higher in people with low vitamin C intake than in the high intake group because vitamin C promotes the proliferation of chondrocytes and the synthesis of collagen fibers in the body. In addition, studies Sherwood et al. [26,27] reported that the intake of soy products is a protective factor for OA, which is related to the relatively high amount of calcium and protein in soy products. Studies by Das Gupta et al. [28,29] reported that alcohol consumption is a risk factor for OA, so in daily life, it is recommended to drink less alcohol and eat more fresh vegetables, fruits, and soy products. Studies by McAlindon et al. [30,31] reported that prolonged sunlight exposure is a protective factor for OA, because vitamin D has the activity of regulating bone metabolism in the body, it is mainly synthesized in the skin through sunlight, and prolonged sun exposure results in high levels of active vitamin D synthesized in the body, and active vitamin D can promote bone growth and metabolism, which protects the body from OA.The results of this study suggest that body mass index increases the risk of OA. Studies by Haq et al. [32,33] confirmed that obesity is a risk factor for OA, and that for every 2 units (i.e., 5 kg) an increase in the body mass index, the risk of OA increases by 36%. On the one hand, obesity acts to cause OA by increasing the bioburden; on the other hand, intermediate metabolites produced during lipid metabolism (e.g., arachidonic acid) aggravate local inflammation and accelerate the development of OA. In some specific cases, such as ligament injuries, overweight individuals, and age-related muscle weakening, the subchondral bone undergoes potential changes and eventually the overlying articular cartilage is affected [34].The results of this study suggest that a history of bone trauma is a risk factor for OA, possibly due to degeneration of articular cartilage caused by bone trauma, which induces arthritis through a chronic mechanism of injury. Genetic factors are a risk factor for the development of OA. Studies by Jacobsen et al. [35,36] have identified an inherited, early-onset, polyarticular OA associated with abnormalities in the COL2A1 gene. In the hip joint, congenital developmental malformations are a risk factor for hip osteoarthritis. Studies by Bijlsma et al. [37] have shown that SNP loci increase the risk of knee and hip osteoarthritis in Asians and that OA is the result of a combination of the systemic and local factors. Although the occurrence of OA cannot be completely prevented at present, it can be reduced or delayed by some measures.


## 5. Conclusion

In summary, obesity, alcohol consumption, and a history of joint trauma all increase the risk of OA in southern Chinese population, whereas a diet rich in fresh vegetables, fresh fruits, soy products, and sun exposure reduces the risk of OA. Understanding the sociodemographic characteristics, disease and treatment, community health services, and quality of life of patients with osteoarthritis will further explore possible influencing factors and provide a basis for more comprehensive and targeted interventions for osteoarthritis in the future.


## 6. Outlook

First, due to time and capacity constraints, the sample size collected in this study was small, and the representativeness of patients’ quality of life and each dimension may be insufficient.Second, in the regression analysis, the mean scores of the dimensions of quality of life were classified as good and bad, the rationality of which needs to be further investigated; meanwhile, in the follow-up study, the influence of the three factors on the quality of life of patients with osteoarthritis: sociodemographic characteristics, disease and treatment, and access to health services and preventive care needs to be further analyzed.Third, due to time and capacity constraints, nonosteoarthritis patients were not selected for further comparative analysis in this study. In future studies, nonosteoarthritis patients in the surveyed community could be randomly selected for quality of life assessment to investigate the differences in quality of life between osteoarthritis patients and nonosteoarthritis patients in the same setting.



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*Source: 2482728-2022-09-14.xml*