Global, regional, and national burden of hip osteoarthritis (1992–2021) and predictions of future disease burden trends: a systematic analysis of the global burden of disease study 2021

Abstract

Background

Hip osteoarthritis can lead to significant joint pain and functional impairment, significantly affecting patients' daily life and activity levels. This study presents the latest global, regional, and national estimates for the incidence, prevalence and years Lost due to Disability(YLDs) due to hip OA of the by sex, age, and location, based on the GBD 2021, as well as forecasted incidence to future.

Methods

Comprehensive data on hip OA from 1992 to 2021 in 204 countries and territories was obtained from the Global Burden of Disease public database. This dataset included information on hip OA incidence, prevalence, and YLDs Projections for hip OA incidence, prevalence, and YLDs were generated using the Norpred model and Bayesian age-period-cohort models. Additionally, age-population cohort(APC) model, decomposition analysis, and health inequality analysis were employed to assess trends and disparities in hip OA. The EPAC and AAPC apply only to rates (crude rates or age standardized rates), and decomposition analysis is used to analyze the number of cases.

Results

The Age-standardized Incidence Rate (ASIR), Age-standardized Prevalence Rate (ASPR), and Age-standardized YLDs in regions with high Socio-Demographic Index (SDI) were found to be high. In contrast, the ASIR in low SDI regions was relatively low. During the period from 1992 to 2021, the global incidence, prevalence, and YLDs of hip OA have all shown significant increases over the past three decades. Middle SDI countries and Low-middle SDI countries exhibited the highest growth rates. However, the slowdown in this growth trend is mainly reflected in countries in high SDI regions. The growth trend of incidence, prevalence, and YLDs of hip OA in other four SDI region countries is still increasing. In the APC model, the global incidence of hip OA starts at the age of 30, reaches the first peak at the age of 65, and then slowly decreases. After the age of 80, the incidence rises again. The prevalence and YLDs increased with the age of patients and have a growing trend over time. In the decomposition analysis, the factor of population growth has played a more important role in the increase of incidence, prevalence, and YLDs of hip OA. Compared to 1992, the incidence rate, prevalence, concentration index, and slope index of HIP OA in different SDI regions in 2021 are still increasing. According to the results of the prediction model, the incidence, prevalence and YLDs of hip OA may still increase in the future.

Conclusions

The age-standardized incidence, prevalence, and YLDs of global hip OA have been on the rise from 1992 to 2021. While the trend in regions with low SDI continues to increase, the rise in regions with high SDI is slowing down. Predictions for the future indicate that the ASIR, prevalence, and YLDs may continue to significantly increase. Our study brought to light the significant challenges in the control and management of OA, encompassing both the escalating number of cases and global distributive inequalities, which may provide valuable insights for refining public health policies and equitable allocation of medical resources.

Introduction

Hip OA is one of the most common types of arthritis [1]. TThis disease is a prevalent degenerative joint disorder that primarily affects the cartilage tissue of the hip joint and its surrounding structures [2]. Hip OA is a prevalent joint disease with causes that are not yet fully understood [3]. However, it is recognized that factors such as aging, weight gain, genetics, joint injuries, and inflammation are all associated with the development of OA [4]. The hallmark of this condition is the wear and tear of joint cartilage and the proliferation of bone at the joint edges [5]. Common symptoms of hip OA include joint pain, swelling, stiffness, and limited mobility. These symptoms may worsen as the disease progresses [6]. Hip OA is a progressively worsening condition, with symptoms that may deteriorate over time [7]. Early intervention can help slow the progression of the disease and improve the quality of life for patients [8]. Compared to other joint disorders, hip OA merits specific focus, as it may arise from etiologies such as femoral head osteonecrosis or hip dislocation. Nevertheless, detailed characterization of the global disease burden specific to hip OA has been absent from prior research.

Patients with severe hip OA may be recommended for joint replacement surgery [9]. According to the American Joint Replacement Registry (AJRR), between 2012 and 2018, a total of 557,684 patients underwent their first hip replacement, and 809,494 patients underwent their first hip arthroplasty [10]. This number is expected to explode in the future. By 2040, it is projected that the number of patients undergoing their initial hip replacement in the United States will reach 719,364 (95% uncertainty interval, 624,766 to 828,286) [11]. By 2060, the projections are even more significant, with the number of patients undergoing their initial hip replacement in the United States expected to reach 1,982,099 (95% uncertainty interval, 1,624,215 to 2,418,839).

In addition, some patients with mild hip OA may be recommended for joint-preserving surgeries such as hip arthroscopy [12]. Despite treatments such as hip arthroscopy, some patients with mild hip OA still experience limitations in activity and chronic pain before and after treatment, leading to an increase in the incidence of disease and disability-adjusted life years (DALYs), as well as an increase in mortality rates and Years of Life Lost (YLLs) [13]. Furthermore, while there have been advances in the treatment of hip OA, the diagnosis and treatment of these conditions remain inadequate, and there is an association with an increased risk of mortality and comorbidities. Therefore, it is necessary to quantify the burden and patterns of hip OA cases by age and sex, and to make predictions for the future in order to effectively meet the current and future needs of the population [14]. Our aim is to report the global, regional, and national burden and trends associated with hip OA from 1992 to 2021, including prevalence and age-standardized rates, and predictions up to 2050.

Methods

Materials

The GBD 2021 provides comprehensive estimates of the incidence, prevalence, and YLDs for hip OA. These estimates are based on data from the GBD 2021 study, which can be accessed through the GBD Results Viewer at https://vizhub.healthdata.org/gbd-results/ (last accessed on September 2, 2024). The data sources for hip OA in the GBD 2021 study included a variety of records such as hospital records, emergency room records, insurance claims, surveys, and vital registration systems from different countries [15]. The study utilized de-identified data, which was compiled by the Institute for Health Metrics and Assessment (IHME) at the University of Washington. The University of Washington Institutional Review Board reviewed and approved the informed consent waiver for this study [16].

The GBD 2021 encompasses a wide range of diseases and injuries, totaling 369, along with 87 risk factors, for analysis across 204 countries and regions [17]. The GBD project team has provided a detailed methodology description and published estimates for the Age-standardized incidence rate(ASIR), Age-standardized prevalence rate(ASPR), and YLDs for these conditions [18].

To facilitate comparative analysis, the GBD project has divided all countries and regions into 21 regions, and further categorized them into five groups based on the Social Demographic Index (SDI). The SDI, ranging from 0 to 1, is a comprehensive indicator that reflects the social and economic conditions influencing health, calculated as the geometric mean of three components: per capita income, the average years of schooling of the population aged 15 and over, and the total fertility rate for women under 25. Countries and regions are categorized into five SDI groups: high SDI (> 0.81), medium high SDI (0.70–0.81), medium SDI (0.61–0.69), medium low SDI (0.46–0.60), and low SDI (< 0.46). This classification aids in understanding the epidemiological similarities and differences among countries and regions, considering their social and economic backgrounds [16].

Statistical analysis

For the descriptive analysis, the first step involved screening and downloading data on hip OA under the natural injury category of the GBD. A world map was then created, visualizing the ASIR, ASPR, and YLDs of hip OA in the overall population for both 1992 and 2021.

Estimated Annual Percentage Change (EAPC) is a measure used to describe the average annual change of a certain indicator over a certain period of time [19]. We uses this measure to analyze the trends of three indicators: Incidence, Prevalence, and YLDs over time. The calculation method of EAPC is to first calculate the ratio of the indicator between the last year and the first year, then take the natural logarithm of this ratio, and finally multiply it by 100 to convert it into a percentage. This result is the average annual growth rate of the indicator during the specified time period. The symbol of EAPC represents the direction of indicator change. If EAPC is a positive number, it indicates that the indicator is increasing; If EAPC is negative, it indicates that the indicator is decreasing. The absolute value of EAPC represents the magnitude of indicator changes. The larger the absolute value, the greater the magnitude of the change.

AAPC (Average annual percent chage) is a summary measure of the trend over a pre-specified fixed interval, allowing us to use a single number to describe the annual average change over a period [20]. Joinpoint software from the National Cancer Institute's Surveillance Research Program was used for all AAPC calculations. The age population cohort model, different from the annual percentage change (APC) in the joint point model, is commonly used to decompose the age, period, and cohort effects of popular trends.

Use the age-period-cohort model(APC Model) based on the Intrinsic Estimator method algorithm to analyze the age, period, and cohort effects of hip joint disease trends [21]. Decomposition analysis is used to analyze the impact of aging, population growth, and epidemic trend on the incidence, prevalence, and YLDs of hip OA. To quantitatively analyze the driving factors that lead to the changes in the incidence, prevalence, and YLDs of hip OA [22].

Health inequality refers to the inequality among different groups in terms of health status, access to health services, and health influencing factors. We uses the slope index of absolute health inequity and the concentration index of relative health inequity to judge whether there is health inequity among countries in different SDI regions in terms of the incidence rate, prevalence rate, and YLDs of hip OA [23]. Simultaneously use the ordinary linear regression model (lm) and the robust regression model (iterative weighted linear regression, rlm) to calculate the slope index. Compared to ordinary linear regression models, robust regression models can give appropriate weights to outliers, making it particularly suitable for data with high heteroscedasticity. When the p-value of the ncvTest (Non-constant Variance Test) is greater than 0.05, it can be considered that there is no heteroscedasticity in the data, and the results of the LM model are used; when the p-value of the ncvTest is less than 0.05, it indicates the presence of heteroscedasticity in the data, and the RLM model is used. If multiple groups have inconsistent ncvTest results, the results of the RLM model will be affected. If the value of the slope index is positive, it indicates that the distribution of health indicators between groups is skewed upwards, meaning that the proportion of groups with higher health indicators is higher; if it is negative, it indicates that the distribution of health indicators among groups is skewed downwards, meaning that the proportion of groups with higher health indicators is lower. The larger the value of the slope index, the higher the degree of inequality in health indicators between groups. If the value of the concentration index is positive, it indicates that the distribution of health indicators among groups is concentrated, that is, the proportion of groups with higher health indicators is higher; if it is negative, it indicates that the distribution of health indicators among groups is dispersed, meaning that the proportion of groups with higher health indicators is lower. The larger the value of the concentration index, the higher the degree of concentration of health indicators between groups. The Z-test was used to compare the differences in the incidence rate, prevalence, and YLDs of hip OA in all countries in the world between 1992 and 2021.

The Spearman rank correlation test was employed to investigate the presence of a correlation between SDI values in various regions and countries and the incidence rate, prevalence, and YLDs associated with hip OA. The Spearman correlation coefficient (ρ, rho) varies between −1 and 1. A positive value of ρ signifies a positive correlation, whereas a negative value indicates a negative correlation. The closer the value of ρ is to 1 or −1, the stronger the correlation between the two variables [24]. The Norpred model and the Bayesian age-period-cohort models (BAPC) model were used to predict the future incidence of hip OA. Both Nordred and BAPC models are based on the Age-Period-Cohort (APC) model [25]. The theoretical basis of this model is that incidence or mortality is related to age structure and population size. The predicted data is based on GBD2017 (https://ghdx.healthdata.org/record/ihme-data/global-population-forecasts-2017-2100). All analyses in this study were conducted using R software (R Core Team, version 4.3.3, Vienna, Austria), and a P value less than 0.05 was considered statistically significant.

Results

The global ASIR for a specific condition in 2021 ranged from 10.78 in the Democratic People's Republic of Korea (95% uncertainty interval 8.08–13.87) to 47.32 in the USA (95% uncertainty interval 35.47–60.64). The overall global ASIR range was 20.67 (95% uncertainty interval 15.76–26.19). Figure 1B reveals that 30 years later, in 2021, the ASIR in regions with a high SDI, such as Western Europe, Australia, and the United States, remained relatively high. In contrast, the ASIR in low SDI regions, including East Asia and South Asia, was still relatively low. The incidence of hip OA in the world and in various regions are shown in Table 1 and Fig. 1.

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ASPR for a specific condition varied widely, from 181.67 in Yemen (95% uncertainty interval 140.45–233.73) to 875.60 in Denmark (95% uncertainty interval 34.99–57.23). The overall global ASPR range was 390.40 (95% uncertainty interval 494.84 —303.28). Figure 1C illustrates that in 1992, the ASPR in regions with a high SDI, such as Western Europe, Australia, and the United States, was relatively high. In contrast, the ASPR in low SDI regions, including East Asia and South Asia, was relatively low. The prevalence of hip OA in the world and in various regions are shown in Table 1. The global ASPR for a specific condition in 2021 ranged from 199.17 in the Democratic People's Republic of Korea (95% uncertainty interval 152.23–257.28) to 936.99 in the USA (95% uncertainty interval 706.15–1213.86). The overall global ASPR range was 416.01 (95% uncertainty interval 529.74 —321.23). Figure 1D reveals that 30 years later, in 2021, the ASPR in regions with a high SDI, such as Western Europe, Australia, and the United States, remained relatively high. In contrast, the ASPR in low SDI regions, including East Asia and South Asia, was still relatively low.

The global YLDs range in 2021 was 6.43 in the Democratic People's Republic of Korea (95% uncertainty interval 3.01–12.86) to 29.41 in the USA (95% uncertainty interval 13.96–59.70). The overall global Age-standardized YLDs range was 13.19 (95% uncertainty interval 6.20–26.65). Figure 1F indicates that 30 years later, in 2021, the YLDs in regions with a high SDI, such as Western Europe, Australia, and the United States, were still relatively high. In contrast, the YLDs in low SDI regions, including East Asia and Southeast Asia, were still relatively low.

From 1992 to 2021, five countries (Nigeria, Denmark, Iceland, Northern Mariana Islands, Zimbabwe) experienced a decrease in the incidence of hip OA, while the prevalence rates of other countries showed an increase. Similarly, eight countries (Denmark, Nigeria, Northern Mariana Islands, Iceland, Democratic Republic of the Congo, American Samoa, Samoa, Zimbabwe) observed a decline in their prevalence rates, with the prevalence rates of other countries experiencing growth. Six countries (Denmark, Nigeria, Northern Mariana Islands, Iceland, American Samoa, Zimbabwe) saw a decrease in the YLDs associated with hip OA, while the YLDs of other countries increased. Over the past three decades, the EAPC for the global incidence of hip OA was 0.29 (95% CI 0.27 to 0.31), the EAPC for the prevalence rate was 0.28 (0.25 to 0.30), and the EAPC for YLDs was 0.28 (0.26 to 0.30). Table 1 presents the changes in EAPC values both globally and across different levels of the SDI. It is evident from Table 1 that during the period from 1992 to 2021, the global incidence, prevalence, and YLDs of hip OA have all shown significant increases over the past three decades. Middle SDI countries and Low-middle SDI countries exhibited the highest growth rates.

In all 204 countries, only Denmark (−0.30) and Nigeria (−0.04) have negative AAPC values for the incidence of hip OA, and only Nigeria's P value (0.98) has no statistical significance. The AAPC values of Oman (1.24), Equatorial Guinea (1.16), Nepal (1.07), Saudi Arabia (1.04), and Bhutan (1.02) are greater than 1. The global AAPC value is 0.23.

Among all 204 countries, only Denmark (−0.35) had negative AAPC values for hip OA prevalence. The P-values of AAPC for the Democratic People's Republic of Korea (0.408), Northern Mariana Islands (0.073), and Democratic Republic of the Congo (0.054) countries were not statistically significant. The AAPC values of Oman (1.28), Equatorial Guinea (1.20), Saudi Arabia (1.09), Nepal (1.06), and Sudan (1.02) are greater than 1.

Among all 204 countries, only Denmark (−0.33) had negative AAPC values for hip OA YLDs. Only the Democratic People's Republic of Korea (0.38) and Northern Mariana Islands (0.40) had no statistically significant P-values. The AAPC values of Oman (1.29), Equatorial Guinea (1.22), Nepal (1.07), Saudi Arabia (1.06), Bhutan (1.02), and Sudan (1.02) are greater than 1.

Through the analysis of AAPC in the world and five countries in different SDI regions through visualization technology, it can be found that the growth trend of incidence, prevalence, and YLDs of hip OA has slowed down. However, the slowdown in this growth trend is mainly reflected in countries in high SDI regions. The growth trend of incidence, prevalence, and YLDs of hip OA in other four SDI region countries is still increasing. Figure 2 shows the growth trend of incidence, prevalence rate, and YLDs of hip OA in the world and five countries in different SDI regions.

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In the APC model, from 1992 to 2021, the global incidence of hip OA starts at the age of 30, reaches the first peak at the age of 65, and then slowly decreases. After the age of 80, the incidence rises again. The prevalence and YLDs increased with the age of patients and have a growing trend over time. Figure 3 shows the visualization results of incidence, prevalence and YLDs in APC model.

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In the decomposition analysis, compared with the change of population aging and epidemiological, the factor of population growth has played a more important role in the increase of incidence number, prevalence number, and YLDs number of hip OA. The contribution of population growth to the increase number of incidence, prevalence, and YLDs of hip OA accounted for 79.24%, 73.72%, and 74.29%, respectively. Figure 4 and Table 2 present the results of the decomposition analysis.

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Through the analysis of health inequities, it has been observed that the incidence rate ratio of hip OA globally increased from 13.14 (10.60–15.68) in 1992 to 15.69 (12.97–18.40) in 2021, with the prevalence rate ratio rising from 219.54 (176.62–262.46) in 1992 to 255.21 (208.01–302.40) in 2021. The YLDs rate ratio also increased from 7.03 (5.68–8.37) in 1992 to 8.15 (6.67–9.63) in 2021. Conversely, the concentration index for the incidence rate of hip OA globally decreased from 0.20 (0.17–0.23) in 1992 to 0.14 (0.11–0.17) in 2021, with the prevalence concentration index declining from 0.19 (0.16–0.22) in 1992 to 0.14 (0.11–0.17) in 2021, and the YLDs concentration index dropping from 0.20 (0.17–0.23) in 1992 to 0.14 (0.11–0.17) in 2021. The results of the health inequity analysis are presented in Table 3 and Fig. 5. Compared to the incidence, prevalence, and YLDs of global hip osteoarthritis (OA) in 1992, the concentration index for the incidence, prevalence, and YLDs of global hip OA in 2021 showed a significant reduction, with the differences being statistically significant.

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The Spearman rank correlation analysis reveals a significant positive monotonic relationship between the SDI values in different regions and the incidence rate of hip OA, with a correlation coefficient of ρ = 0.68 and a p-value less than 0.05. Similarly, there is a significant positive correlation between the SDI values in different regions and the prevalence of hip OA, indicated by a correlation coefficient of 0.66 and a p-value less than 0.05. Furthermore, the analysis shows a significant positive correlation between the SDI values and the YLDs associated with hip OA in different regions, with a correlation coefficient of 0.67 and a p-value less than 0.05. In the context of countries, the Spearman rank correlation analysis also indicates a significant positive monotonic relationship between the SDI values and the incidence rate of hip OA, with a correlation coefficient of ρ = 0.63 and a p-value less than 0.05. There is also a significant positive correlation between the SDI values and the prevalence of hip OA in different countries, indicated by a correlation coefficient of 0.66 and a p-value less than 0.05. Additionally, the analysis shows a significant positive correlation between the SDI values and the YLDs associated with hip OA in different countries, with a correlation coefficient of 0.66 and a p-value less than 0.05. Figure 6 shows the results of Spearman rank correlation between SDI values in various regions and countries and the incidence rate, prevalence, and YLDs associated with hip OA.

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Globally, we have observed a significant increase in the age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), and age-standardized years lived with disability (YLDs) of hip osteoarthritis (OA) from 1992 to 2021. In two prediction models, all three indicators are predicted to continue to grow from 2021 to 2040. In the Nordpred model, it is predicted that in 2040, the incidence rate of hip OA may reach 267,6613, the prevalence rate may reach 59,581,504, the YLDs may reach 1,874,487, the ASIR of hip OA may reach 22.05, the prevalence rate may reach 444.89, and the YLDs may reach 14.08. Figure 7 shows the prediction of the two models on the incidence rate, prevalence, and YLDs of hip OA.

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Discussion

As hip OA progresses, damage to the entire hip joint surface ultimately occurs, leading to disability in patients [26]. This disease seriously affects the quality of life of patients, but generally does not directly lead to patient death. Therefore, as the incidence rate of this disease increases, the prevalence and YLDs of this disease will also increase accordingly. Therefore, in areas with a high incidence rate of hip OA, the prevalence and YLDs will also increase. In our study, we first found that the global ASIR, prevalence rate, and YLDs of hip OA were significantly different. Compared with countries with low SDI values, countries with high SDI values have higher incidence rates, prevalence, and YLDs, which may be related to the following factors [27]. Our study found that the incidence rate, prevalence rate, and YLDs of hip OA are related to age. Our research also found that the incidence rate of hip OA starts at the age of 30, reaches its first peak at the age of 65, and then declines slowly, but still higher than that of people before the age of 45. After the age of 80, the incidence rate rises rapidly again. In countries with high SDI values, the problem of population aging will be more serious, so there will be more incidence rate of hip OA. This bimodal pattern may be related to age-associated physiological changes, disease progression, or diagnostic disparities. For example, the peak before age 65 could be due to cumulative joint wear reaching its maximum over a lifetime; the decline between 65–80 years may result from some patients no longer being counted in statistics before progressing to severe stages, or reduced diagnostic rates; the subsequent rise after 80 years might be attributed to surviving individuals in advanced age experiencing reduced underdiagnosis or slower disease progression, leading to more cases being identified. Secondly, the medical care system in countries with high SDI is usually relatively complete, which means that patients with hip OA can be more easily diagnosed and treated, thus increasing the incidence rate of the disease [28]. In addition, obesity is an important cause of hip OA, and in some countries with high SDI values, especially in the United States, Australia, New Zealand, obesity has become a public health issue [29]. Obesity can lead to weight gain, affecting joint stability and flexibility, thereby increasing the burden on the hip joint, exacerbating cartilage wear, and increasing the risk of hip OA [30]. In the decomposition analysis conducted in this study, it was found that population growth was the most significant factor contributing to the increase in the incidence rate of hip OA. This finding indicates that even if incidence rates in specific age groups remain unchanged, more people will still develop the disease simply due to an increase in the total population. It is essential to ensure that the newly added population has access to medical facilities, screening programs, and preventive services, especially in under-served or rapidly growing regions. According to the United Nations Population Division, the world population is projected to continue growing over the next 50 years, from 8.2 billion in 2024 to a peak of 10.3 billion in the mid-2080s [31]. As the population increases, the incidence rate of hip OA is expected to rise as well, resulting in a higher burden on the healthcare system. Based on our research, it is estimated that by 2024, the global incidence rate of hip OA may reach 2,676,613 cases, the prevalence rate may reach 59,581,504 cases, and the YLDs may reach 1,874,487. These numbers indicate the significant impact that hip OA would have on the population and the healthcare system in the coming years.

In our study, we found that the growth trend of age-standardized incidence, prevalence, and YLDs of hip OA in countries with high SDI values has been declining, while the growth trend of incidence rate, prevalence, and YLDs in countries with low SDI values is still rising. This may be related to the following factors. With the development of public health, the healthcare systems of countries with low SDI values have gradually been improved, and many potential patients with hip OA have received timely diagnosis and treatment [32]. Patients in countries with low SDI values may experience malnutrition, including deficiencies in vitamins and minerals [33]. This may lead to poor bone development or osteoporosis, thereby increasing the risk of hip OA. Population aging is a global issue, and when it affects high SDI value countries, it would also have an impact on some low SDI value countries [34]. This may explain why the incidence rate of hip OA continues to rise in countries with low SDI values. In countries with high SDI values and better national healthcare systems, some diseases that can lead to secondary hip OA, including osteonecrosis of the femoral head and developmental dysplasia of the hip, would be detected and treated early and promptly before developing into hip OA [35]. This can prevent these patients from developing hip OA in the future. Hip OA is a progressively worsening condition, with symptoms that may deteriorate over time [7]. Early intervention can help slow the progression of the disease and improve the quality of life for patients.

Based on our analysis using the concentration index, slope index, and Spearman rank correlation analysis, we discovered variations in the incidence rate, prevalence, and YLDs of hip OA across countries and regions characterized by different SDI values. Notably, high SDI value countries exhibited a declining growth trend, while low SDI value countries showed an increasing trend. Considering these findings, it is crucial to implement targeted interventions in low SDI regions to ensure timely diagnosis and treatment of hip OA. This proactive approach aims to prevent future disability caused by this condition. By focusing on early intervention and appropriate medical care, we can alleviate the potential burden posed by hip OA and improve the quality of life for individuals affected by the disease in low SDI areas. We recommend that low-SDI countries prioritize strengthening primary healthcare systems to improve access to early diagnosis and management of hip OA, enhance equitable allocation of healthcare resources to underserved regions, and foster international collaboration for technology transfer and funding support to scale up evidence-based prevention and treatment programs. These measures aim to address structural barriers and reduce disparities in health outcomes across SDI regions.

To optimize the targeting of interventions, we examined the correlation between age and the incidence rate of hip OA. According to our research findings, hip OA typically manifests around the age of 30 and progressively intensifies, reaching its pinnacle at 65 years old. Although the rate of increase diminishes thereafter, it remains elevated in comparison to individuals under the age of 45. Interestingly, a remarkable and swift surge in the rate of increase occurs once again after the age of 80. This pattern highlights the intricate nature of hip OA development across diverse age groups. It is worth mentioning that hip joint OA often arises as a consequence of femoral head necrosis and developmental hip dysplasia. Symptoms tend to present between the ages of 40 and 65 for these patients [36, 37]. However, intervening and treating patients solely during this period may not be the most timely approach. Instead, a broader approach encompassing screening for developmental hip dysplasia in newborns and early diagnosis and treatment of individuals with high-risk factors for femoral head necrosis could prove more effective and advantageous [38, 39]. In addition, conditions such as high BMI and alcohol-related avascular necrosis of the femoral head, which can lead to hip OA, should also be given due attention [40].

Previous studies have utilized the GBD 2019 database to report on the incidence of all OA cases [27]. Additionally, there have been reports on the ASPR and YLDs of OA from 1990 to 2021 [41]. However, these papers focus on all types of OA. In our manuscript, we employ the latest GBD 2021 database to provide a detailed analysis specifically addressing the incidence, prevalence, and YLDs associated with hip OA. Furthermore, we utilize methodologies such as the joinpoint model, APC model, and concentration index to conduct a more thorough analysis of the epidemiological trends, age distribution, and health inequalities related to hip OA—areas that have been infrequently reported in the existing literature. Our manuscript also represents the first attempt to describe the impact of health inequalities on the trends of hip OA at a global level. The findings from our study will significantly enhance the understanding of hip OA. We also employed predictive modeling to forecast the future incidence trends of hip OA. This result provides a foundation for the development of targeted healthcare measures in the future. Obesity is implicated as a contributory factor for hip OA [42]. Alongside the implementation of total hip arthroplasty, evidence-based advocacy for weight control strategies should be integrated into public health initiatives to mitigate the disease burden of hip OA.

This study relies on data from the GBD research. While it benefits from high-quality estimates of hip OA, it also faces certain inevitable limitations. Firstly, the GBD research categorizes data units based on countries and regions, lacking information on racial demographics and potentially overlooking the impact of race on the incidence of hip OA. Consequently, analyzing and comparing global trends and changes in the incidence rate, prevalence, and YLDs of hip OA, as well as examining variations among different SDI levels and age groups within each ethnic group, becomes a challenge.Secondly, early data or data from countries and regions with lower levels of development may be subject to inaccuracies. Moreover, the extended 30-year time span is susceptible to various uncontrollable factors that could potentially influence the predictive results of age-standardized disease rates, prevalence rates, and YLDs. These limitations should be taken into consideration when interpreting the findings of this study.

Conclusion

The age-standardized incidence, prevalence, and YLDs of global hip OA have been on the rise from 1992 to 2021. While the trend in regions with low SDI continues to increase, the rise in regions with high SDI is slowing down. Predictions for the future indicate that the ASIR, prevalence, and YLDs may continue to significantly increase. This study brought to light the significant challenges in the control and management of OA, encompassing both the escalating number of cases and global distributive inequalities, which may provide valuable insights for refining public health policies and equitable allocation of medical resources.

Data availability

To download the data used in these analyses, please visit the Global Health Data Exchange GBD 2021 data-input sources tool at Https://vizhub.healthdata.org/gbd-results/?params = gbd-api-2021-public.

Abbreviations

ASIR:

Age-standardized incidence rate

ASPR:

Age-standardized prevalence rate

CI:

Confidence interval

YLDs:

Years Lived with Disability

EAPC:

Estimated annual percentage change

GBD:

Global Burden of Disease

SDI:

Socio-Demographic Index

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