Global, regional, and national burden of congenital musculoskeletal and limb anomalies, 1990-2021: A systematic analysis of the global burden of disease in 2021

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Limited research has been conducted on the incidence trends of these anomalies. This study aims to investigate the patterns and temporal trends of congenital musculoskeletal and limb anomalies. Methods Detailed data on congenital musculoskeletal and limb anomalies from 1990 to 2021 were sourced from the 2021 Global Burden of Disease Study, stratified by sex, region, and country, and integrated with the Socio-demographic Index (SDI). To quantify the burden of these anomalies, we utilized Age-Standardized Incidence Rates (ASIR), Age-Standardized Mortality Rates (ASMR), Age-Standardized Prevalence Rates (ASPR), and Estimated Annual Percentage Change (EAPC). Additionally, decomposition analysis was conducted to examine the impact of aging, population, and epidemiological change on the burden. The ARIMA model was employed to forecast the burden for the period 2021–2031, while health inequality was assessed using the Slope Index of Inequality and the Concentration Index. Results Brunei Darussalam recorded the highest age-standardized incidence rate (ASIR) for congenital musculoskeletal and limb anomalies globally in 2021, followed by Republic of Guatemala and Argentine Republic. Afghanistan and United Mexican States had the highest mortality and prevalence rates, respectively. India reported the largest number of cases and deaths in absolute terms, while China had the highest number of cases. The ARIMA model forecasts that by 2031, the number of congenital musculoskeletal and limb anomalies will increase from 2,437,890 to 24,711,128, while the number of deaths is projected to decrease from 13,600 to 10,137. The patient population is expected to grow from 18,549,408 to 19,207,414. Decomposition analysis revealed that the rise in the number of congenital musculoskeletal and limb anomalies in moderate SDI regions was primarily driven by population growth, whereas the reduction in mortality was mainly attributed to epidemiological changes and aging. In low and medium SDI areas, both population and epidemiological changes contributed to the increase in case numbers. The EAPC exhibited a significant correlation with ASIR and ASMR. Between 1990 and 2021, inequalities in the incidence and mortality of congenital musculoskeletal and limb anomalies have significantly increased. Lower SDI regions have experienced concentrated incidence and mortality, with respective inequities on the rise. The concentration index for incidence rose from 0.28 in 1990 to 0.35 in 2021, and the concentration index for mortality increased from 0.34 in 1990 to 0.42 in 2021, indicating an escalating burden of congenital musculoskeletal and limb anomalies in lower SDI groups. Conclusion This study estimated temporal trends in the incidence and mortality of Congenital musculoskeletal and limb anomalies from 1990 to 2021 at the global, national, and regional levels. Adverse trends were observed in countries with lower sociodemographic indices. This suggests that some countries should develop more targeted and specific strategies to address the burden of Congenital musculoskeletal and limb anomalies. Congenital musculoskeletal and limb anomalies Incidence Mortality Prevalence Global Burden of Disease Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 7 Introduction Congenital musculoskeletal and limb anomalies are a group of birth defects that are prevalent on a global scale and have a profound impact on children's health and quality of life. In recent years, the global burden of these conditions has exhibited complex trends in response to population growth and advances in medical technology. According to estimates by the World Health Organisation (WHO), congenital anomalies are one of the leading causes of neonatal mortality and long-term childhood disability 1 . The precise prevalence of congenital musculoskeletal and limb anomalies remain to be fully elucidated, exhibiting significant variations across different geographical regions, ethnic groups and socio-economic strata 2 . It is estimated that 6 percent of global infant deaths are attributable to congenital anomalies. Of these cases, 92 percent occur in low- and middle-income countries 3 . Furthermore, a range of factors have been identified as being significantly associated with the development of congenital musculoskeletal and limb anomalies. These factors include genetic factors, environmental exposures and maternal health 4 – 6 . Recent years have seen an increasing number of studies focusing on the role of genetics in congenital musculoskeletal and limb anomalies, largely due to the advancement of molecular biology techniques 7 – 9 . A study conducted in Pakistan revealed that familial factors were implicated in 35 percent of cases of congenital malformations 10 . However, there remains a paucity of in-depth understanding of the aetiology and pathogenesis of many complex malformations, which limits the development of preventive and intervention strategies for such disorders. Congenital musculoskeletal and limb anomalies have a considerable impact on patients and their families. On the one hand, these deformities may result in significant physical dysfunction, impacting the patient's capacity for exercise, daily living and psychological well-being. On the other hand, the long-term medical needs and social support may impose a substantial financial burden on the family and society 2 . It is imperative to comprehend the global epidemiological characteristics and temporal trends of such diseases in order to formulate targeted prevention strategies. The Global Burden of Disease (GBD) study provides detailed data on congenital musculoskeletal and limb anomalies, thereby offering a valuable opportunity to assess their health impacts at global, national and regional levels.Utilising the GBD database, this study systematically analysed the temporal trends of incidence, mortality and prevalence of congenital musculoskeletal and limb anomalies over the period of 1990 to 2021, and further explored their regional variations. The findings of this study are expected to contribute to the existing literature and provide a scientific basis for the development of prevention strategies for congenital anomalies in different countries and regions. Materials and methods Study data The Global Health Data Exchange (GHDx) query tool ( http://ghdx.healthdata.org/gbd-results-tool ) was utilised to collate data on the number of cases of congenital musculoskeletal and limb anomalies from 1990 to 2021, with age-standardised incidence rates, deaths and prevalences by sex, region and country. Anomalies were characterised by number of person-degree incidence cases, age-standardised incidence rates, deaths and prevalences, disaggregated by sex, region, and country. The data set encompasses a total of 204 countries and territories, which were then categorised into five regions based on the socio-demographic index (SDI). These regions include low, low-moderate, moderate, moderate-high and high. Additionally, the world was divided into 21 regions based on geographical area. The aggregated data used in the article are derived from public data and can be downloaded free of charge. Statistical analysis The present study employed age-standardised incidence rates (ASIR), age-standardised mortality rates (ASMR), age-standardised prevalence rates (ASPR), and estimated annual percentage change (EAPC) to quantify the burden caused by congenital musculoskeletal and limb anomalies. The necessity for standardisation arises when comparing populations with different age structures or changes in age over time in the same population. The ASR (per 100,000 population) in accordance with the direct method is calculated by summing up the products of the age-specific rates (a i , where I denotes the i th age class) and the number of persons (or weight) (w i ) in the same age subgroup I of the chosen reference standard population, then dividing the sum of standard population weights, i.e., $$\:ASR=\frac{{\sum\:}_{\left\{i=1\right\}}^{A}{a}_{i}{w}_{i}}{{\sum\:}_{\left\{i=1\right\}}^{A}{w}_{i}}\times\:\text{100,000}$$ The EAPC is defined as the person average change in ASR over a specified time period. The regression line is fitted to the natural logarithm of the rate, i.e. y = α + βx + ε , where y = ln(ASR), x = calendar year. The EAPC is calculated as 100 × (exp(β) – 1), and The 95 percent confidence interval (CI) for the EAPC can be obtained from a linear regression model 11 . If both the EAPC estimate and its 95 percent lower bound of the CI are > 0, then the ASR is considered to be on an upward trend. Conversely, if both the EAPC estimate and the upper limit of its 95 percent CI were < 0, then the ASR was considered to be on a downward trend. In all other instances, the ASR was considered stable over time. In order to explore the factors influencing EAPC, this study assessed the association between EAPC and ASR at the national level. Decomposition analysis was used to visualise the three factors driving changes in the number of morbidities and deaths of Congenital musculoskeletal and limb anomalies between 1990s and 2021s. The study further examined the role of three factors (ageing, population and pidemiology) in driving these changes. Epidemiological changes refer to underlying age- and population-adjusted mortality and morbidity rates 12 . Autoregressive integrated moving average model The autoregressive integrated moving average model (ARIMA) is comprised of two constituent models: the autoregressive (AR) model and the moving average (MA) model. The fundamental assumption of the model is that the data series are time-dependent random variables whose autocorrelation can be characterised by the ARIMA model. The latter is capable of predicting future values based on past values. The equation can be expressed as follows:Y t = φ 1 Y t−1 + φ 2 Y t−2 + … + φ p Y t−p + e t – θ 1 e t−1 - … - θ q e t−q , The AR model part is represented by the following equation: where(φ 1 Y t−1 + φ 2 Y t−2 + … + φ p Y t−p + e t ) is the AR model part, ༈e t – θ 1 e t−1 - … - θ q e t−q ༉ is the MA model part, Y t−1 is the observation of༈t-p༉ period, p and q denote AR and MA, respectively, and e t is the t-period random error 13 . The time series in the ARIMA model is required to be a smooth random series with zero mean. Cross-country inequalities analysis The slope index of inequality and the concentration index are standardised measures of absolute and relative gradient imbalances, respectively. The slope index of inequality is obtained through regression analyses that relate a country's ASIR or ASMR to its relative position on the SDI, defined by the midpoint of the population in the cumulative distribution sorted by SDI 14 . The heteroscedasticity of the data was tested using a weighted regression model. Concentration indices were calculated by numerically integrating the area under the Lorenz curve, with the cumulative proportions of ASIR, ASMR, and ASPR aligned with the cumulative distribution of the population sorted by SDI 15 . The statistical analyses were conducted using R 4.3.0, and P value < 0.05 was considered to indicate statistical significance. Result Global Congenital musculoskeletal and limb anomalies burden ASIR, ASMR and ASPR are known to vary widely around the world in relation to congenital musculoskeletal and limb anomalies (Fig. 1 ; Figure S1 ; Figure S2). In 2021, the highest ASIR was recorded in Brunei Darussalam (76.7 per 100,000), followed by the Republic of Guatemala (75.6 per 100,000) and the Argentine Republic (73.3 per 100,000). In terms of absolute numbers, India recorded the highest incidence of congenital musculoskeletal and limb anomalies in 2021 (339,702.3), followed by China (238,561.2) and Nigeria (170,560.3) (Table S1 ); In contrast, Afghanistan had the highest ASMR (0.9 per 100,000), followed by Commonwealth of Dominica, Sudan and Yemen (0.7 per 100,000). In absolute numbers, India had the highest number of Congenital musculoskeletal and limb anomalies deaths in 2021 (2421.3), followed by Nigeria (1371) and Pakistan (689.1) (Table S2); In 2021, the United Mexican States has the highest ASPR (492.9 per 100,000), followed by Japan (488.3 per 100,000) and Hellenic Republic (474.2 per 100,000). In absolute numbers, China had the highest number of cases (3112683.7), followed by India (2771851.2) and Republic of Indonesia (639780.7) (Table S3). The findings of the ARIMA model demonstrate that the number of congenital musculoskeletal and limb anomalies is projected to rise from 2,437,890.1 in 2021 to 2,471,128.1 in 2022. Thereafter, the number of incidence cases is predicted to remain relatively stable from 2023 to 2031, indicating a stable trend in the overall situation. In contrast, the model predicts that the number of deaths from congenital musculoskeletal and limb anomalies will show a decreasing trend in the future, from 13,599.8 in 2021 to 10,137.0 in 2031. Conversely, the number of congenital musculoskeletal and limb anomalies continues to increase, from 18,549,408.3 in 2021 to 19,207,414.2 in 2031 (Fig. 2 ; Table S4). Decomposition analysis of age-standardized incidence number, age-standardized death number, and age-standardized prevalence number From 1990 to 2021, the transient increase in the global incidence of congenital musculoskeletal and limb anomalies was primarily influenced by population growth (100.27%). The middle SDI quintile region exhibited the most significant increase in congenital musculoskeletal and limb anomalies. The increase in congenital musculoskeletal and limb anomalies in this region was entirely attributable to population growth (131.86%) (Fig. 3 A; Table S5). A similar pattern was observed in the gender quintile, where population growth (97.41%) accounted for the majority of the increase, while ageing contributed only 8.77% (Fig. 3 B; Table S5). It is important to note that the global decline in the number of deaths due to congenital musculoskeletal and limb anomalies is primarily influenced by epidemiological changes (-456.53%), followed by ageing (-235.66%).The mortality of congenital musculoskeletal and limb anomalies was also affected by population growth (592.20%). The middle SDI quintile exhibited the most significant decline in deaths attributable to congenital musculoskeletal and limb anomalies, with epidemiological changes contributing the most (-175.92%), followed by aging (-147.02%) (Fig. 3 C; Table S5). However, when stratified by gender, the decrease in the number of deaths due to congenital musculoskeletal and limb anomalies was only affected by aging (-12.77%) (Fig. 3 D; Table S5). The increase in the number of congenital musculoskeletal and limb anomalies on a global scale was primarily driven by population growth (75.01%), followed by epidemiological changes (45.33%). Congenital musculoskeletal and limb anomalies exhibited the most significant increase in the number of prevalent cases, which was predominantly attributable to population growth (69.98%). This was followed by epidemiological changes, which accounted for 39.68% of the increase.In terms of gender stratification, it was observed that the increase in the number of prevalent cases of congenital musculoskeletal and limb anomalies was primarily influenced by population growth and epidemiological changes, with the respective contributions of 51.40% and 52.76%. The influential factor for EAPC A substantial correlation has been identified between EAPC and ASIR, as well as ASMR (P < 0.05). The EAPC demonstrated a downward trend, transitioning from positive to negative values as ASIR fell below 30. Conversely, as ASIR surpassed 40, the EAPC exhibited a general tendency to decrease, exhibiting a somewhat non-linear relationship (P = 9.6E-06, R 2 = 0.0098). When ASMR < 0.35, the EAPC demonstrates signs of volatility, initially decreasing and subsequently increasing. Concurrently, as the ASMR rises, the EAPC persists in a downward trajectory (P = 5.81E-43, R 2 = 0.0902). Conversely, an absence of correlation was observed between EAPC and ASPR(P = 8.3E-02, R 2 = 0.0015) (Fig. 4 ). The overall incidence of congenital musculoskeletal and limb anomalies was found to be higher in women than in men (Fig. 5 A). Furthermore, the incidence of congenital musculoskeletal and limb anomalies was found to be stable at four-year intervals from 1990 through 2021 (Fig. 5 B). Conversely, among patients with congenital musculoskeletal and limb anomalies of all ages, mortality was higher in men than in women and was concentrated in low SDI and low-middle SDI regions (Fig. 5 C). The mortality rate of congenital musculoskeletal and limb anomalies decreased over time (Fig. 5 D). The prevalence of congenital musculoskeletal and limb anomalies decreases with age. The burden of congenital musculoskeletal and limb anomalies was found to be more significant in low SDI and high middle SDI regions (Fig. 5 E), and the prevalence remained stable across periods (Fig. 5 F). Global health inequality analysis of incidence, mortality and prevalence in congenital musculoskeletal and limb anomalies from 1990 to 2021 The disparity in the incidence and mortality of congenital musculoskeletal and limb anomalies has been observed to diminish across different SDI levels between countries and regions in 2021 in comparison to 1990. The analysis revealed a general tendency for decreasing morbidity rates with increasing SDI levels. In 2021, the Slope index of inequality (SII) values were found to be significantly lower than those of the 1990s, with respective values of 62.17 and 84.02 (Fig. 6 A; Table S6). Furthermore, the absolute values of the SII exhibited a downward trend, as evidenced by regression fitting results that were found to be highly statistically significant (P = 2.62e − 13). This finding suggests that inequalities in the incidence of congenital musculoskeletal and limb anomalies have been decreasing over the past few decades in countries and regions with different levels of social development, and the trend has been very stable (Fig. 6 B). A similar decline has been observed in the SII values for mortality from congenital musculoskeletal and limb anomalies in 2021, with values of -0.39 and − 0.66, respectively (Fig. 6 C; Table S6). The regression fits also show highly statistically significant results(P = 2.97e − 17). The data demonstrate a decline in the disparity in mortality rates for congenital musculoskeletal and limb anomalies across different levels of social development between countries and regions over recent decades (Fig. 6 D). Conversely, there has been an increase in the inequality of prevalence of congenital musculoskeletal and limb anomalies, with the SII value increasing from − 47.44 in 1990 to -55.56 in 2021 (Fig. 6 E; Table S6). The regression fit for SII was not statistically significant (P = 6.13e-02) (Fig. 6 F). As demonstrated in Fig. 7 A, the cumulative curves deviate from the equality line (orange diagonal) in both 1990 and 2021, indicating that the prevalence of congenital musculoskeletal and limb anomalies is more concentrated in areas with lower SDI, with a concentration index (CI ) in 1990 was 0.28 and a CI of 0.35 in 2021, suggesting that inequality in the prevalence of congenital musculoskeletal and limb anomalies has increased in terms of socioeconomic status (Fig. 7 A). A similar increase was observed in the confidence interval (CI) for congenital musculoskeletal and limb anomalies mortality, which rose from 0.34 in 1990 to 0.42 in 2021. This suggests that in 2021, individuals residing in areas with lower SDI levels experienced higher mortality rates due to congenital musculoskeletal and limb anomalies. This finding indicates an increase in inequalities in mortality by socioeconomic status (Fig. 7 B). Conversely, the cumulative curve for the burden of prevalence for congenital musculoskeletal and limb anomalies exhibited a closer proximity to the equality line, with CIs of 0.05 in both 1990 and 2021. This finding suggests that the burden of prevalence for congenital musculoskeletal and limb anomalies was more equitably distributed across diverse SDI levels, and the degree of inequality remained relatively constant over time (Fig. 7 C). Discussion This study provides a comprehensive analysis of temporal trends in the incidence, mortality and prevalence of congenital musculoskeletal and limb anomalies at the global, regional and national levels.The analysis reveals that there have been fluctuations in the incidence of congenital musculoskeletal and limb anomalies from 1990 to 2021, with a decline observed in the overall number. In contrast, the mortality rate has exhibited a downward trend, while the prevalence rate has shown an upward trend. Furthermore, the analysis reveals that the incidence and prevalence of congenital musculoskeletal and limb anomalies are higher in women than in men, while the mortality rate is higher in men than in women, a finding that aligns with the conclusions of several preceding studies 16 , 17 . Males may be more prone to severe complications, which can result in elevated mortality rates. In contrast, females may be more susceptible to genetic and environmental factors that contribute to higher morbidity and prevalence profiles.The morbidity rates of congenital musculoskeletal and limb anomalies in 1990 and 2021 are predominantly concentrated in lower SDI regions. In 1990 and 2021, the incidence of congenital musculoskeletal and limb anomalies is predominantly concentrated in the lower SDI regions, with a CI of 0.28 in 1990 and 0.35 in 2021. A similar distribution is observed in the mortality rate, which exhibits a CI of 0.34 in 1990 and 0.42 in 2021. This suggests that lower SDI regions experience inadequate prenatal healthcare coverage, insufficient capacity to save deliveries and newborns, and challenges in accessing healthcare resources and managing maternal health 17 – 20 . The subject is susceptible to suboptimal intake of essential nutrients and exposure to environmental pollutants 21 , 22 . In addition, lower SDI regions encounter challenges due to inadequate screening technology adoption and insufficient public awareness, compounded by inadequate policy support, which hinders efforts to regulate the progression of the disease 23 . The issue of growing health inequalities in morbidity and mortality between countries and regions at different levels of social development is of significant concern 24 , and trends are more stable. However, the prevalence of the condition was more evenly distributed across areas with different SDI levels, with a confidence interval (CI) of 0.05 for both years, suggesting that the extent of health inequalities in prevalence did not change significantly over time. The results of the ARIMA model demonstrate that the number of congenital musculoskeletal and limb anomalies is projected to increase from 2,437,890.1 in 2021 to 2,471,128.1 in 2022, and then remain more or less unchanged from 2023 to 2031. Meanwhile, the number of deaths shows a decreasing trend, while the number of illnesses continues to increase.The explanation for this phenomenon is that the early detection and documentation of congenital musculoskeletal and limb anomalies has increased significantly with the advancement of medical diagnostic technologies, including prenatal ultrasound and standardised registration systems 25 – 27 . Concurrently, the heightened public cognisance of the condition, alongside the efficacious propagation of preventative measures, namely genetic testing (e.g. COL6A1-3, LAMA2 gene screening) and antenatal counselling, has led to a marked stabilisation in the prevalence of congenital musculoskeletal and limb anomalies. This has led to a marked stabilisation in the number of congenital musculoskeletal and limb anomalies, following a brief period of growth 28 – 30 . In addition, increased public health awareness, widespread use of interventions, reduced socio-economic deprivation and significant improvements in neonatal and paediatric intensive care techniques have enabled many children with congenital musculoskeletal and limb anomalies to be treated effectively at an early stage, reducing the incidence of complications and the risk of death, and ultimately leading to a downward trend in the number of deaths 31 – 33 . However, exposure to pesticides, heavy metals (e.g. mercury) and industrial chemicals during pregnancy is significantly associated with congenital malformations 34 , 35 , and drug use, viral infections can lead to abnormalities in fetal musculoskeletal development 36 in addition to the adverse effects of inadequate folic acid intake 37 and the decline in mortality rates mentioned above is contributing to the continued increase in the number of cases. More research into congenital musculoskeletal and limb anomalies is therefore urgently needed to address this increasing burden of disease. The temporary increase in the global number of cases of congenital musculoskeletal and limb anomalies was mainly influenced by population growth and, to a lesser extent, ageing, with epidemiological changes playing a negative role. In contrast, the global decrease in the number of deaths from congenital musculoskeletal and limb anomalies was mainly influenced by epidemiological changes and ageing, with the largest decrease in the middle SDI quintile regions, but the increase in the number of deaths was influenced by population growth. Finally, the increase in the number of illnesses is mainly influenced by population growth and to a lesser extent by epidemiological changes, a phenomenon that is reflected in the low-middle SDI regions. Population growth directly increases the fertility base, leading to an increase in the absolute number of cases of congenital musculoskeletal and limb anomalies, and thus to a temporary increase in the number of morbidities and an increase in the number of deaths and illnesses. In addition, population expansion may be associated with an increase in genetic diversity and a higher cumulative risk of low-frequency deleterious mutations 38 . The incidence and prevalence of musculoskeletal malformations are significantly higher in developing countries than in developed countries due to high fertility rates 39 , 40 . Childbearing at an advanced age is associated with an increased rate of germ cell mutations and an increased risk of chromosomal aneuploidy. A Norwegian cohort study showed a 0.43 percentage point increase in the risk of foot malformations when the parents were older than 45 years 41 . In addition, metabolic disorders (e.g. diabetes) in older pregnant women further exacerbate the risk of congenital musculoskeletal and limb anomalies. In addition, metabolic disorders (e.g. diabetes) in older pregnant women further exacerbate the risk of congenital musculoskeletal and limb anomalies 42 . Advances in medical technology have prolonged the survival of patients with congenital musculoskeletal and limb anomalies, and as they enter the geriatric stage, the cause of death has shifted from congenital anomalies to age-related diseases, and multi-system complications in the elderly have been managed by surgery and rehabilitation, reducing the risk of direct mortality; and ageing is associated with a decrease in bone density and osteoporosis, gait abnormalities and a risk of falls, but the above symptoms can be alleviated when patients with congenital musculoskeletal and limb anomalies take medication and receive physiotherapy to reduce the risk, so that the number of deaths caused by this disease has decreased 43 – 45 . The reasons why epidemiological changes trigger changes in morbidity, mortality and prevalence have been described previously. In addition, the study observed that the EAPC began to decrease when the baseline ASIR exceeded 40. A possible explanation for this finding is that congenital musculoskeletal and limb anomalies have not yet resulted in a significant public safety hazard that has come to public attention when the baseline ASIR is low, and begin to receive attention and control when they reach a certain impact. In conclusion, we suggest that in the future we continue to pay attention to the early screening and intervention of congenital musculoskeletal and limb anomalies in high-risk groups (e.g. exposure to chemical substances, heavy metals, and older mothers), as well as the promotion of effective treatments to minimise the disease burden of congenital musculoskeletal and limb anomalies. Congenital musculoskeletal and limb anomalies are still not fully understood and their aetiology is complex, mainly related to genetics, environment and maternal health. Currently, congenital musculoskeletal and limb anomalies are often caused by mutations in specific genes or chromosomal abnormalities, for example, RYR1 mutations cause central core disease and fetal ankylosing spondylitis 46 , gene dosage effects in specific regions of partial chromosomal trisomies affect foot development 47 , and there is a Mendelian pattern of inheritance of congenital musculoskeletal and limb abnormalities, with approximately 12% of patients with congenital spinal deformities having a monogenic aetiology, whereas polydactyly is often inherited in an autosomal dominant pattern 48 . Additionally, exposure to opioids and anti-epileptic drugs during pregnancy significantly increases the risk of limb defects, especially in the middle and late stages of life 49 . Similarly, exposure to pesticides and heavy metals during pregnancy was significantly associated with congenital limb deformities 50 , 51 , PM2.5 exposure has the potential to cause musculoskeletal deformities 22 , nicotine and alcohol are also associated with the condition 52 , 53 , and the number of cases also increased during the virus epidemic 36 . Finally, maternal health status is also an important component of aetiology. It has been suggested that gestational diabetes and hyperlipidaemia may affect fetal bone development through oxidative stress mechanisms 54 , and that hypertension is associated with an elevated risk of foetal limb defects 55 . Insufficient maternal folic acid intake linked to neural tube defects: Tanzanian study shows doubled risk of congenital anomalies in areas with low folic acid supplementation rates 37 . In conclusion, the aetiology of congenital musculoskeletal and limb anomalies is complex and requires a comprehensive diagnosis that combines genetic testing, assessment of environmental exposures and maternal health management. Perinatal nutritional interventions and avoidance of teratogenic exposures are important preventive strategies in clinical practice. However, there are several limitations to this study. First, the accuracy and robustness of GBD estimates are highly dependent on the quality and quantity of data used in modelling. Although GBD 2021 provides extensive global data coverage, there is considerable variation in the completeness and consistency of data reporting across countries and regions, and the burden of congenital musculoskeletal and limb anomalies may be underestimated in resource-poor or poor areas due to underreporting or inadequate medical information systems. These factors combine to create data uncertainty. This may have a potential impact on the accurate assessment of the burden of disease. In addition, GBD databases mainly provide population-based summary data and lack detailed clinical and epidemiological information at the individual level. This limitation limits the ability to perform stratified analyses of specific patient subgroups and thus may affect the understanding of the heterogeneity, risk factors and their interacting mechanisms of congenital musculoskeletal and limb anomalies. Finally, the definition, aetiology and types of congenital musculoskeletal and limb anomalies in GBD 2021 still have some limitations that need to be further complemented and refined to improve the accuracy, comparability and reliability of the data. These results could provide a solid basis for further epidemiological studies and assessment of the burden of disease. Conclusion This study estimated temporal trends in morbidity and mortality from congenital musculoskeletal and limb anomalies at global, national and regional levels from 1990 to 2021 and observed unfavourable trends in countries with lower socio-demographic indices, suggesting that some countries should develop more targeted and specific strategies to address the burden of congenital musculoskeletal and limb anomalies. Declarations Acknowledgements All the authors are grateful for the help of Zunyi Medical University, People’s Hospital of Qianxinan Prefecture, and Affiliated Hospital of Zunyi Medical University. Funding This research was funded by the National Natural Science Foundation of China (grant nos. 82260106), the College Students’ Innovation Training Program under project numbers 2024106610965, S2024106612281 and S2024106612233. Availability of data and materials No datasets were generated or analysed during the current study. Ethics approval and consent to participate Not applicable. Consent for publication All authors of this manuscript have read and approved the final version of the article and agree to its publication. There are no conflicts of interest to declare. Competing interests The authors declare no competing interests. Author Contribution Conceptualization, Y.L., Z.B., R.Z., J.C., Z.T., and Z.Z.; methodology, Y.L, J.C., R.Z., Z.B., and Z.T.; validation, R.Z., J.C.; writing—original draft preparation, R.Z., J.C.; data curation, J.C. and M.D. All the authors have read and agreed with the published version of the manuscript. References (WHO) WHO. Congenital disorders. 2025. https://www.who.int/health-topics/congenital-anomalies . Mody KS, Henstenburg J, Herman MJ. The Health & Economic Disparities of Congenital Musculoskeletal Disease Worldwide: An Analysis of 25 Years (1992–2017). Glob Pediatr Health 2021; 8: 2333794x21994998. Higashi H, Barendregt JJ, Vos T. 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LID – 10.3390/genes13071194 [doi] LID – 1194. (2073–4425 (Electronic)). Wen X, Belviso N, Murray E, Lewkowitz AK, Ward KE, Meador KJ. Association of Gestational Opioid Exposure and Risk of Major and Minor Congenital Malformations. (2574–3805 (Electronic)). Felisbino K, Milhorini SDS, Kirsten N, Bernert K, Schiessl R, Guiloski IC. Exposure to pesticides during pregnancy and the risk of neural tube defects: A systematic review. (1879 – 1026 (Electronic)). Ikeda AA-OX, Marsela M, Miyashita C, et al. Heavy metals and trace elements in maternal blood and prevalence of congenital limb abnormalities among newborns: the Japan Environment and Children's Study. (1347–4715 (Electronic)). Kirsch Micheletti JA-O, Bláfoss R, Sundstrup E, Bay H, Pastre CM, Andersen LL. Association between lifestyle and musculoskeletal pain: cross-sectional study among 10,000 adults from the general working population. (1471–2474 (Electronic)). Hackshaw A, Rodeck C Fau - Boniface S, Boniface S. Maternal smoking in pregnancy and birth defects: a systematic review based on 173 687 malformed cases and 11.7 million controls. (1460–2369 (Electronic)). Usategui-Martín R, Pérez-Castrillón JL, Mansego ML, et al. Association between genetic variants in oxidative stress-related genes and osteoporotic bone fracture. The Hortega follow-up study. (1879-0038 (Electronic)). Materna-Kiryluk AA-O, Wisniewska K, Wieckowska BA-O, et al. Maternal Risk Factors Associated with Limb Reduction Defects: Data from the Polish Registry of Congenital Malformations (PRCM). LID – 10.3390/children8020138 [doi] LID – 138. (2227–9067 (Print)). Additional Declarations No competing interests reported. Supplementary Files Supplement.docx Cite Share Download PDF Status: Published Journal Publication published 12 May, 2025 Read the published version in Tropical Medicine and Health → Version 1 posted Editorial decision: Revision requested 06 Mar, 2025 Reviews received at journal 28 Feb, 2025 Reviews received at journal 27 Feb, 2025 Reviewers agreed at journal 24 Feb, 2025 Reviewers agreed at journal 24 Feb, 2025 Reviewers agreed at journal 24 Feb, 2025 Reviewers invited by journal 24 Feb, 2025 Editor assigned by journal 24 Feb, 2025 Submission checks completed at journal 24 Feb, 2025 First submitted to journal 19 Feb, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6063028","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":420434876,"identity":"085fb4b9-05b8-44a1-820f-d6bd120d1541","order_by":0,"name":"Yu Luo","email":"","orcid":"","institution":"Department of Pediatric Orthopedics, The Affiliated Hospital of Zunyi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Luo","suffix":""},{"id":420434877,"identity":"5f7d712a-97e3-4aa8-9385-100cde917f3c","order_by":1,"name":"Rubin Zheng","email":"","orcid":"","institution":"Clinical College, Zunyi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Rubin","middleName":"","lastName":"Zheng","suffix":""},{"id":420434880,"identity":"cb96c1fe-c30e-4511-9b2d-b5b4640a88f9","order_by":2,"name":"Jiaxi Chen","email":"","orcid":"","institution":"Clinical College, Zunyi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiaxi","middleName":"","lastName":"Chen","suffix":""},{"id":420434882,"identity":"84507055-a2dd-402f-8d50-1d75fec624fa","order_by":3,"name":"Miao Deng","email":"","orcid":"","institution":"Department of Nephrology, The Affiliated Hospital of Zunyi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Miao","middleName":"","lastName":"Deng","suffix":""},{"id":420434883,"identity":"338170df-7ab0-4d04-bb5b-56e03d7b5405","order_by":4,"name":"Ziyang Zhang","email":"","orcid":"","institution":"Department of Nephrology, The Affiliated Hospital of Zunyi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ziyang","middleName":"","lastName":"Zhang","suffix":""},{"id":420434884,"identity":"4112c494-b25e-4108-9e1f-1acb2eb9949a","order_by":5,"name":"Zhouke Tan","email":"","orcid":"","institution":"Department of Nephrology, The Affiliated Hospital of Zunyi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhouke","middleName":"","lastName":"Tan","suffix":""},{"id":420434885,"identity":"cbc18497-99cf-4fc7-925a-a8d2af8e7ffb","order_by":6,"name":"Zhixun Bai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYDACCcYGIHmAgY29AcxnbCBeC88BorWASaByiQQitcjPbm6T5t1xR55P8vnTzTwMNrIbDjA/e4BPC+Ocg83GvGeeGbZJJ6Td5mFIM95wgM3cAJ8WZonExse8bYcZgVqOAbUcTtxwgIdNAp8WNonEhsNALfZtkgfbgFr+E9bCA7UlsU2CmQ2o5QBhLRISic2Gc9ueJbfxpLHdnGOQbDzzMJsZXi3yM9KfSbxtu2M7v/34sxtvKuxk+443P8OrBQ2AgoqZBPWjYBSMglEwCrADABZzSO4CEYDEAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Nephrology, People’s Hospital of Qianxinan Prefecture","correspondingAuthor":true,"prefix":"","firstName":"Zhixun","middleName":"","lastName":"Bai","suffix":""}],"badges":[],"createdAt":"2025-02-19 10:08:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6063028/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6063028/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s41182-025-00750-4","type":"published","date":"2025-05-12T15:57:37+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":77618535,"identity":"f49a6a97-92d6-45d1-aa24-c66b05184471","added_by":"auto","created_at":"2025-03-03 15:17:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":564226,"visible":true,"origin":"","legend":"\u003cp\u003eThe global disease burden of congenital musculoskeletal and limb anomalies for both sexes in 204 countries and territories. (A) The ASIR of congenital musculoskeletal and limb anomalies in 2021; (B) The EAPC of congenital musculoskeletal and limb anomalies ASIR from 1990 to 2021. ASIR, age standardized incidence rate; EAPC, estimated annual percentage change.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6063028/v1/d59e260e402a109486fac743.jpg"},{"id":77616061,"identity":"f972b501-2e23-47dd-b4bb-945bbfb4ea24","added_by":"auto","created_at":"2025-03-03 15:01:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":365954,"visible":true,"origin":"","legend":"\u003cp\u003ePredicted trends of congenital musculoskeletal and limb anomalies incident cases (A), deaths (B), and prevalence (C) in the next decade (2021-2031). Red lines represent the true trend during 1990-2021; yellow dot lines and shaded regions represent the predicted trend and its 95% CI.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6063028/v1/a57450921824470fc5474893.jpg"},{"id":77620100,"identity":"b0a0ce78-e72f-44b3-af6c-b2da28562296","added_by":"auto","created_at":"2025-03-03 15:33:57","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":486094,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in congenital musculoskeletal and limb anomalies incidence, mortality and prevalence from 1990 to 2021 according to population-level determinants of population growth, aging, and epidemiological change across different socio-demographic index quintiles and by sex. The black dot represents the overall value of change contributed by all three components. SDI, socio-demographic index.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6063028/v1/dbe282a0bed9e26872104702.jpg"},{"id":77618536,"identity":"e0bdee22-f3f2-480f-8536-5754b9041c65","added_by":"auto","created_at":"2025-03-03 15:17:57","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":665962,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between EAPC and (A) ASIR, (B) ASMR, and (C) ASPR for congenital musculoskeletal and limb anomalies. Circles represent congenital musculoskeletal and limb anomalies cases from 1990 to 2021, with larger circles indicating higher cases. The R\u003csup\u003e2\u003c/sup\u003e and P values were derived from Pearson correlation analysis.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6063028/v1/be08471ea1ecc5766de8079f.jpg"},{"id":77619751,"identity":"a003a715-20f9-4239-9c74-50ceb5504377","added_by":"auto","created_at":"2025-03-03 15:25:57","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1528184,"visible":true,"origin":"","legend":"\u003cp\u003eAge-specific incidence, mortality, and prevalence of congenital musculoskeletal and limb anomalies stratified by sex, SDI levels and periods.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6063028/v1/f974fdf2891463e8c108636a.jpg"},{"id":77618159,"identity":"6074b400-e536-490f-97d7-92a5160716ea","added_by":"auto","created_at":"2025-03-03 15:09:57","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":647563,"visible":true,"origin":"","legend":"\u003cp\u003eConcentration curves of congenital musculoskeletal and limb anomalies incidence, mortality and prevalence by SDI in 1990 and 2021. The orange diagonal line represents perfect equality, where congenital musculoskeletal and limb anomalies incidence, mortality and prevalence would be equally distributed across all SDI levels. Shaded areas represent the 95% confidence intervals of CI. SDI, socio-demographic index; CI, concentration index.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6063028/v1/9bc3cbf9b40e8ca6763db7da.jpg"},{"id":83067935,"identity":"a9764c33-7d61-4bdb-83e4-91a96b528cc0","added_by":"auto","created_at":"2025-05-19 16:08:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5027875,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6063028/v1/eb18aba1-3187-49f7-bc35-af0a9ab60d46.pdf"},{"id":77616065,"identity":"34b339dd-dee0-4b55-aa6d-864f934d6908","added_by":"auto","created_at":"2025-03-03 15:01:57","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1271276,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-6063028/v1/02f73f2c8d8c0fbf1bc63a52.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Global, regional, and national burden of congenital musculoskeletal and limb anomalies, 1990-2021: A systematic analysis of the global burden of disease in 2021","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCongenital musculoskeletal and limb anomalies are a group of birth defects that are prevalent on a global scale and have a profound impact on children's health and quality of life. In recent years, the global burden of these conditions has exhibited complex trends in response to population growth and advances in medical technology. According to estimates by the World Health Organisation (WHO), congenital anomalies are one of the leading causes of neonatal mortality and long-term childhood disability\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe precise prevalence of congenital musculoskeletal and limb anomalies remain to be fully elucidated, exhibiting significant variations across different geographical regions, ethnic groups and socio-economic strata\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. It is estimated that 6 percent of global infant deaths are attributable to congenital anomalies. Of these cases, 92 percent occur in low- and middle-income countries\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Furthermore, a range of factors have been identified as being significantly associated with the development of congenital musculoskeletal and limb anomalies. These factors include genetic factors, environmental exposures and maternal health\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Recent years have seen an increasing number of studies focusing on the role of genetics in congenital musculoskeletal and limb anomalies, largely due to the advancement of molecular biology techniques\u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. A study conducted in Pakistan revealed that familial factors were implicated in 35 percent of cases of congenital malformations\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. However, there remains a paucity of in-depth understanding of the aetiology and pathogenesis of many complex malformations, which limits the development of preventive and intervention strategies for such disorders. Congenital musculoskeletal and limb anomalies have a considerable impact on patients and their families. On the one hand, these deformities may result in significant physical dysfunction, impacting the patient's capacity for exercise, daily living and psychological well-being. On the other hand, the long-term medical needs and social support may impose a substantial financial burden on the family and society\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. It is imperative to comprehend the global epidemiological characteristics and temporal trends of such diseases in order to formulate targeted prevention strategies.\u003c/p\u003e \u003cp\u003eThe Global Burden of Disease (GBD) study provides detailed data on congenital musculoskeletal and limb anomalies, thereby offering a valuable opportunity to assess their health impacts at global, national and regional levels.Utilising the GBD database, this study systematically analysed the temporal trends of incidence, mortality and prevalence of congenital musculoskeletal and limb anomalies over the period of 1990 to 2021, and further explored their regional variations. The findings of this study are expected to contribute to the existing literature and provide a scientific basis for the development of prevention strategies for congenital anomalies in different countries and regions.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy data\u003c/h2\u003e \u003cp\u003eThe Global Health Data Exchange (GHDx) query tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ghdx.healthdata.org/gbd-results-tool\u003c/span\u003e\u003cspan address=\"http://ghdx.healthdata.org/gbd-results-tool\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was utilised to collate data on the number of cases of congenital musculoskeletal and limb anomalies from 1990 to 2021, with age-standardised incidence rates, deaths and prevalences by sex, region and country. Anomalies were characterised by number of person-degree incidence cases, age-standardised incidence rates, deaths and prevalences, disaggregated by sex, region, and country. The data set encompasses a total of 204 countries and territories, which were then categorised into five regions based on the socio-demographic index (SDI). These regions include low, low-moderate, moderate, moderate-high and high. Additionally, the world was divided into 21 regions based on geographical area. The aggregated data used in the article are derived from public data and can be downloaded free of charge.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe present study employed age-standardised incidence rates (ASIR), age-standardised mortality rates (ASMR), age-standardised prevalence rates (ASPR), and estimated annual percentage change (EAPC) to quantify the burden caused by congenital musculoskeletal and limb anomalies. The necessity for standardisation arises when comparing populations with different age structures or changes in age over time in the same population. The ASR (per 100,000 population) in accordance with the direct method is calculated by summing up the products of the age-specific rates (a\u003csub\u003ei\u003c/sub\u003e, where I denotes the i\u003csup\u003eth\u003c/sup\u003e age class) and the number of persons (or weight) (w\u003csub\u003ei\u003c/sub\u003e) in the same age subgroup I of the chosen reference standard population, then dividing the sum of standard population weights, i.e.,\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:ASR=\\frac{{\\sum\\:}_{\\left\\{i=1\\right\\}}^{A}{a}_{i}{w}_{i}}{{\\sum\\:}_{\\left\\{i=1\\right\\}}^{A}{w}_{i}}\\times\\:\\text{100,000}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe EAPC is defined as the person average change in ASR over a specified time period. The regression line is fitted to the natural logarithm of the rate, i.e. \u003cem\u003ey\u0026thinsp;=\u0026thinsp;α\u0026thinsp;+\u0026thinsp;βx\u0026thinsp;+\u0026thinsp;ε\u003c/em\u003e, where y\u0026thinsp;=\u0026thinsp;ln(ASR), x\u0026thinsp;=\u0026thinsp;calendar year. The EAPC is calculated as 100 \u0026times; (exp(β) \u0026ndash; 1), and The 95 percent confidence interval (CI) for the EAPC can be obtained from a linear regression model\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. If both the EAPC estimate and its 95 percent lower bound of the CI are \u0026gt;\u0026thinsp;0, then the ASR is considered to be on an upward trend. Conversely, if both the EAPC estimate and the upper limit of its 95 percent CI were \u0026lt;\u0026thinsp;0, then the ASR was considered to be on a downward trend. In all other instances, the ASR was considered stable over time. In order to explore the factors influencing EAPC, this study assessed the association between EAPC and ASR at the national level. Decomposition analysis was used to visualise the three factors driving changes in the number of morbidities and deaths of Congenital musculoskeletal and limb anomalies between 1990s and 2021s. The study further examined the role of three factors (ageing, population and pidemiology) in driving these changes. Epidemiological changes refer to underlying age- and population-adjusted mortality and morbidity rates\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAutoregressive integrated moving average model\u003c/h3\u003e\n\u003cp\u003eThe autoregressive integrated moving average model (ARIMA) is comprised of two constituent models: the autoregressive (AR) model and the moving average (MA) model. The fundamental assumption of the model is that the data series are time-dependent random variables whose autocorrelation can be characterised by the ARIMA model. The latter is capable of predicting future values based on past values. The equation can be expressed as follows:Y\u003csub\u003et\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;φ\u003csub\u003e1\u003c/sub\u003eY\u003csub\u003et\u0026minus;1\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;φ\u003csub\u003e2\u003c/sub\u003eY\u003csub\u003et\u0026minus;2\u003c/sub\u003e + \u0026hellip; + φ\u003csub\u003ep\u003c/sub\u003eY\u003csub\u003et\u0026minus;p\u003c/sub\u003e + e\u003csub\u003et\u003c/sub\u003e \u0026ndash; θ\u003csub\u003e1\u003c/sub\u003ee\u003csub\u003et\u0026minus;1\u003c/sub\u003e - \u0026hellip; - θ\u003csub\u003eq\u003c/sub\u003ee\u003csub\u003et\u0026minus;q\u003c/sub\u003e, The AR model part is represented by the following equation:\u003c/p\u003e \u003cp\u003ewhere(φ\u003csub\u003e1\u003c/sub\u003eY\u003csub\u003et\u0026minus;1\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;φ\u003csub\u003e2\u003c/sub\u003eY\u003csub\u003et\u0026minus;2\u003c/sub\u003e + \u0026hellip; + φ\u003csub\u003ep\u003c/sub\u003eY\u003csub\u003et\u0026minus;p\u003c/sub\u003e + e\u003csub\u003et\u003c/sub\u003e) is the AR model part, ༈e\u003csub\u003et\u003c/sub\u003e \u0026ndash; θ\u003csub\u003e1\u003c/sub\u003ee\u003csub\u003et\u0026minus;1\u003c/sub\u003e - \u0026hellip; - θ\u003csub\u003eq\u003c/sub\u003ee\u003csub\u003et\u0026minus;q\u003c/sub\u003e༉ is the MA model part, Y\u003csub\u003et\u0026minus;1\u003c/sub\u003e is the observation of༈t-p༉ period, p and q denote AR and MA, respectively, and e\u003csub\u003et\u003c/sub\u003e is the t-period random error\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. The time series in the ARIMA model is required to be a smooth random series with zero mean.\u003c/p\u003e\n\u003ch3\u003eCross-country inequalities analysis\u003c/h3\u003e\n\u003cp\u003eThe slope index of inequality and the concentration index are standardised measures of absolute and relative gradient imbalances, respectively. The slope index of inequality is obtained through regression analyses that relate a country's ASIR or ASMR to its relative position on the SDI, defined by the midpoint of the population in the cumulative distribution sorted by SDI\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The heteroscedasticity of the data was tested using a weighted regression model. Concentration indices were calculated by numerically integrating the area under the Lorenz curve, with the cumulative proportions of ASIR, ASMR, and ASPR aligned with the cumulative distribution of the population sorted by SDI\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe statistical analyses were conducted using R 4.3.0, and P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate statistical significance.\u003c/p\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGlobal Congenital musculoskeletal and limb anomalies burden\u003c/h2\u003e \u003cp\u003eASIR, ASMR and ASPR are known to vary widely around the world in relation to congenital musculoskeletal and limb anomalies (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e; Figure S2). In 2021, the highest ASIR was recorded in Brunei Darussalam (76.7 per 100,000), followed by the Republic of Guatemala (75.6 per 100,000) and the Argentine Republic (73.3 per 100,000). In terms of absolute numbers, India recorded the highest incidence of congenital musculoskeletal and limb anomalies in 2021 (339,702.3), followed by China (238,561.2) and Nigeria (170,560.3) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e); In contrast, Afghanistan had the highest ASMR (0.9 per 100,000), followed by Commonwealth of Dominica, Sudan and Yemen (0.7 per 100,000). In absolute numbers, India had the highest number of Congenital musculoskeletal and limb anomalies deaths in 2021 (2421.3), followed by Nigeria (1371) and Pakistan (689.1) (Table S2); In 2021, the United Mexican States has the highest ASPR (492.9 per 100,000), followed by Japan (488.3 per 100,000) and Hellenic Republic (474.2 per 100,000). In absolute numbers, China had the highest number of cases (3112683.7), followed by India (2771851.2) and Republic of Indonesia (639780.7) (Table S3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe findings of the ARIMA model demonstrate that the number of congenital musculoskeletal and limb anomalies is projected to rise from 2,437,890.1 in 2021 to 2,471,128.1 in 2022. Thereafter, the number of incidence cases is predicted to remain relatively stable from 2023 to 2031, indicating a stable trend in the overall situation. In contrast, the model predicts that the number of deaths from congenital musculoskeletal and limb anomalies will show a decreasing trend in the future, from 13,599.8 in 2021 to 10,137.0 in 2031. Conversely, the number of congenital musculoskeletal and limb anomalies continues to increase, from 18,549,408.3 in 2021 to 19,207,414.2 in 2031 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Table S4).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDecomposition analysis of age-standardized incidence number, age-standardized death number, and age-standardized prevalence number\u003c/h3\u003e\n\u003cp\u003eFrom 1990 to 2021, the transient increase in the global incidence of congenital musculoskeletal and limb anomalies was primarily influenced by population growth (100.27%). The middle SDI quintile region exhibited the most significant increase in congenital musculoskeletal and limb anomalies. The increase in congenital musculoskeletal and limb anomalies in this region was entirely attributable to population growth (131.86%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA; Table S5). A similar pattern was observed in the gender quintile, where population growth (97.41%) accounted for the majority of the increase, while ageing contributed only 8.77% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB; Table S5). It is important to note that the global decline in the number of deaths due to congenital musculoskeletal and limb anomalies is primarily influenced by epidemiological changes (-456.53%), followed by ageing (-235.66%).The mortality of congenital musculoskeletal and limb anomalies was also affected by population growth (592.20%). The middle SDI quintile exhibited the most significant decline in deaths attributable to congenital musculoskeletal and limb anomalies, with epidemiological changes contributing the most (-175.92%), followed by aging (-147.02%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC; Table S5). However, when stratified by gender, the decrease in the number of deaths due to congenital musculoskeletal and limb anomalies was only affected by aging (-12.77%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD; Table S5).\u003c/p\u003e \u003cp\u003eThe increase in the number of congenital musculoskeletal and limb anomalies on a global scale was primarily driven by population growth (75.01%), followed by epidemiological changes (45.33%). Congenital musculoskeletal and limb anomalies exhibited the most significant increase in the number of prevalent cases, which was predominantly attributable to population growth (69.98%). This was followed by epidemiological changes, which accounted for 39.68% of the increase.In terms of gender stratification, it was observed that the increase in the number of prevalent cases of congenital musculoskeletal and limb anomalies was primarily influenced by population growth and epidemiological changes, with the respective contributions of 51.40% and 52.76%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eThe influential factor for EAPC\u003c/h3\u003e\n\u003cp\u003eA substantial correlation has been identified between EAPC and ASIR, as well as ASMR (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The EAPC demonstrated a downward trend, transitioning from positive to negative values as ASIR fell below 30. Conversely, as ASIR surpassed 40, the EAPC exhibited a general tendency to decrease, exhibiting a somewhat non-linear relationship (P\u0026thinsp;=\u0026thinsp;9.6E-06, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0098). When ASMR\u0026thinsp;\u0026lt;\u0026thinsp;0.35, the EAPC demonstrates signs of volatility, initially decreasing and subsequently increasing. Concurrently, as the ASMR rises, the EAPC persists in a downward trajectory (P\u0026thinsp;=\u0026thinsp;5.81E-43, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0902). Conversely, an absence of correlation was observed between EAPC and ASPR(P\u0026thinsp;=\u0026thinsp;8.3E-02, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0015) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe overall incidence of congenital musculoskeletal and limb anomalies was found to be higher in women than in men (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Furthermore, the incidence of congenital musculoskeletal and limb anomalies was found to be stable at four-year intervals from 1990 through 2021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Conversely, among patients with congenital musculoskeletal and limb anomalies of all ages, mortality was higher in men than in women and was concentrated in low SDI and low-middle SDI regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). The mortality rate of congenital musculoskeletal and limb anomalies decreased over time (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). The prevalence of congenital musculoskeletal and limb anomalies decreases with age. The burden of congenital musculoskeletal and limb anomalies was found to be more significant in low SDI and high middle SDI regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE), and the prevalence remained stable across periods (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eGlobal health inequality analysis of incidence, mortality and prevalence in congenital musculoskeletal and limb anomalies from 1990 to 2021\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe disparity in the incidence and mortality of congenital musculoskeletal and limb anomalies has been observed to diminish across different SDI levels between countries and regions in 2021 in comparison to 1990. The analysis revealed a general tendency for decreasing morbidity rates with increasing SDI levels. In 2021, the Slope index of inequality (SII) values were found to be significantly lower than those of the 1990s, with respective values of 62.17 and 84.02 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA; Table S6). Furthermore, the absolute values of the SII exhibited a downward trend, as evidenced by regression fitting results that were found to be highly statistically significant (P\u0026thinsp;=\u0026thinsp;2.62e\u0026thinsp;\u0026minus;\u0026thinsp;13). This finding suggests that inequalities in the incidence of congenital musculoskeletal and limb anomalies have been decreasing over the past few decades in countries and regions with different levels of social development, and the trend has been very stable (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). A similar decline has been observed in the SII values for mortality from congenital musculoskeletal and limb anomalies in 2021, with values of -0.39 and \u0026minus;\u0026thinsp;0.66, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC; Table S6). The regression fits also show highly statistically significant results(P\u0026thinsp;=\u0026thinsp;2.97e\u0026thinsp;\u0026minus;\u0026thinsp;17). The data demonstrate a decline in the disparity in mortality rates for congenital musculoskeletal and limb anomalies across different levels of social development between countries and regions over recent decades (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). Conversely, there has been an increase in the inequality of prevalence of congenital musculoskeletal and limb anomalies, with the SII value increasing from \u0026minus;\u0026thinsp;47.44 in 1990 to -55.56 in 2021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE; Table S6). The regression fit for SII was not statistically significant (P\u0026thinsp;=\u0026thinsp;6.13e-02) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs demonstrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA, the cumulative curves deviate from the equality line (orange diagonal) in both 1990 and 2021, indicating that the prevalence of congenital musculoskeletal and limb anomalies is more concentrated in areas with lower SDI, with a concentration index (CI ) in 1990 was 0.28 and a CI of 0.35 in 2021, suggesting that inequality in the prevalence of congenital musculoskeletal and limb anomalies has increased in terms of socioeconomic status (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). A similar increase was observed in the confidence interval (CI) for congenital musculoskeletal and limb anomalies mortality, which rose from 0.34 in 1990 to 0.42 in 2021. This suggests that in 2021, individuals residing in areas with lower SDI levels experienced higher mortality rates due to congenital musculoskeletal and limb anomalies. This finding indicates an increase in inequalities in mortality by socioeconomic status (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). Conversely, the cumulative curve for the burden of prevalence for congenital musculoskeletal and limb anomalies exhibited a closer proximity to the equality line, with CIs of 0.05 in both 1990 and 2021. This finding suggests that the burden of prevalence for congenital musculoskeletal and limb anomalies was more equitably distributed across diverse SDI levels, and the degree of inequality remained relatively constant over time (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides a comprehensive analysis of temporal trends in the incidence, mortality and prevalence of congenital musculoskeletal and limb anomalies at the global, regional and national levels.The analysis reveals that there have been fluctuations in the incidence of congenital musculoskeletal and limb anomalies from 1990 to 2021, with a decline observed in the overall number. In contrast, the mortality rate has exhibited a downward trend, while the prevalence rate has shown an upward trend. Furthermore, the analysis reveals that the incidence and prevalence of congenital musculoskeletal and limb anomalies are higher in women than in men, while the mortality rate is higher in men than in women, a finding that aligns with the conclusions of several preceding studies\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Males may be more prone to severe complications, which can result in elevated mortality rates. In contrast, females may be more susceptible to genetic and environmental factors that contribute to higher morbidity and prevalence profiles.The morbidity rates of congenital musculoskeletal and limb anomalies in 1990 and 2021 are predominantly concentrated in lower SDI regions. In 1990 and 2021, the incidence of congenital musculoskeletal and limb anomalies is predominantly concentrated in the lower SDI regions, with a CI of 0.28 in 1990 and 0.35 in 2021. A similar distribution is observed in the mortality rate, which exhibits a CI of 0.34 in 1990 and 0.42 in 2021. This suggests that lower SDI regions experience inadequate prenatal healthcare coverage, insufficient capacity to save deliveries and newborns, and challenges in accessing healthcare resources and managing maternal health\u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The subject is susceptible to suboptimal intake of essential nutrients and exposure to environmental pollutants\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In addition, lower SDI regions encounter challenges due to inadequate screening technology adoption and insufficient public awareness, compounded by inadequate policy support, which hinders efforts to regulate the progression of the disease\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The issue of growing health inequalities in morbidity and mortality between countries and regions at different levels of social development is of significant concern\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, and trends are more stable. However, the prevalence of the condition was more evenly distributed across areas with different SDI levels, with a confidence interval (CI) of 0.05 for both years, suggesting that the extent of health inequalities in prevalence did not change significantly over time.\u003c/p\u003e \u003cp\u003eThe results of the ARIMA model demonstrate that the number of congenital musculoskeletal and limb anomalies is projected to increase from 2,437,890.1 in 2021 to 2,471,128.1 in 2022, and then remain more or less unchanged from 2023 to 2031. Meanwhile, the number of deaths shows a decreasing trend, while the number of illnesses continues to increase.The explanation for this phenomenon is that the early detection and documentation of congenital musculoskeletal and limb anomalies has increased significantly with the advancement of medical diagnostic technologies, including prenatal ultrasound and standardised registration systems\u003csup\u003e\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Concurrently, the heightened public cognisance of the condition, alongside the efficacious propagation of preventative measures, namely genetic testing (e.g. COL6A1-3, LAMA2 gene screening) and antenatal counselling, has led to a marked stabilisation in the prevalence of congenital musculoskeletal and limb anomalies. This has led to a marked stabilisation in the number of congenital musculoskeletal and limb anomalies, following a brief period of growth\u003csup\u003e\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. In addition, increased public health awareness, widespread use of interventions, reduced socio-economic deprivation and significant improvements in neonatal and paediatric intensive care techniques have enabled many children with congenital musculoskeletal and limb anomalies to be treated effectively at an early stage, reducing the incidence of complications and the risk of death, and ultimately leading to a downward trend in the number of deaths\u003csup\u003e\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. However, exposure to pesticides, heavy metals (e.g. mercury) and industrial chemicals during pregnancy is significantly associated with congenital malformations\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, and drug use, viral infections can lead to abnormalities in fetal musculoskeletal development\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e in addition to the adverse effects of inadequate folic acid intake\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e and the decline in mortality rates mentioned above is contributing to the continued increase in the number of cases. More research into congenital musculoskeletal and limb anomalies is therefore urgently needed to address this increasing burden of disease.\u003c/p\u003e \u003cp\u003eThe temporary increase in the global number of cases of congenital musculoskeletal and limb anomalies was mainly influenced by population growth and, to a lesser extent, ageing, with epidemiological changes playing a negative role. In contrast, the global decrease in the number of deaths from congenital musculoskeletal and limb anomalies was mainly influenced by epidemiological changes and ageing, with the largest decrease in the middle SDI quintile regions, but the increase in the number of deaths was influenced by population growth. Finally, the increase in the number of illnesses is mainly influenced by population growth and to a lesser extent by epidemiological changes, a phenomenon that is reflected in the low-middle SDI regions. Population growth directly increases the fertility base, leading to an increase in the absolute number of cases of congenital musculoskeletal and limb anomalies, and thus to a temporary increase in the number of morbidities and an increase in the number of deaths and illnesses. In addition, population expansion may be associated with an increase in genetic diversity and a higher cumulative risk of low-frequency deleterious mutations\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. The incidence and prevalence of musculoskeletal malformations are significantly higher in developing countries than in developed countries due to high fertility rates\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Childbearing at an advanced age is associated with an increased rate of germ cell mutations and an increased risk of chromosomal aneuploidy. A Norwegian cohort study showed a 0.43 percentage point increase in the risk of foot malformations when the parents were older than 45 years\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. In addition, metabolic disorders (e.g. diabetes) in older pregnant women further exacerbate the risk of congenital musculoskeletal and limb anomalies. In addition, metabolic disorders (e.g. diabetes) in older pregnant women further exacerbate the risk of congenital musculoskeletal and limb anomalies\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Advances in medical technology have prolonged the survival of patients with congenital musculoskeletal and limb anomalies, and as they enter the geriatric stage, the cause of death has shifted from congenital anomalies to age-related diseases, and multi-system complications in the elderly have been managed by surgery and rehabilitation, reducing the risk of direct mortality; and ageing is associated with a decrease in bone density and osteoporosis, gait abnormalities and a risk of falls, but the above symptoms can be alleviated when patients with congenital musculoskeletal and limb anomalies take medication and receive physiotherapy to reduce the risk, so that the number of deaths caused by this disease has decreased\u003csup\u003e\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. The reasons why epidemiological changes trigger changes in morbidity, mortality and prevalence have been described previously. In addition, the study observed that the EAPC began to decrease when the baseline ASIR exceeded 40. A possible explanation for this finding is that congenital musculoskeletal and limb anomalies have not yet resulted in a significant public safety hazard that has come to public attention when the baseline ASIR is low, and begin to receive attention and control when they reach a certain impact. In conclusion, we suggest that in the future we continue to pay attention to the early screening and intervention of congenital musculoskeletal and limb anomalies in high-risk groups (e.g. exposure to chemical substances, heavy metals, and older mothers), as well as the promotion of effective treatments to minimise the disease burden of congenital musculoskeletal and limb anomalies.\u003c/p\u003e \u003cp\u003eCongenital musculoskeletal and limb anomalies are still not fully understood and their aetiology is complex, mainly related to genetics, environment and maternal health. Currently, congenital musculoskeletal and limb anomalies are often caused by mutations in specific genes or chromosomal abnormalities, for example, RYR1 mutations cause central core disease and fetal ankylosing spondylitis\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, gene dosage effects in specific regions of partial chromosomal trisomies affect foot development\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, and there is a Mendelian pattern of inheritance of congenital musculoskeletal and limb abnormalities, with approximately 12% of patients with congenital spinal deformities having a monogenic aetiology, whereas polydactyly is often inherited in an autosomal dominant pattern\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Additionally, exposure to opioids and anti-epileptic drugs during pregnancy significantly increases the risk of limb defects, especially in the middle and late stages of life\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Similarly, exposure to pesticides and heavy metals during pregnancy was significantly associated with congenital limb deformities\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, PM2.5 exposure has the potential to cause musculoskeletal deformities\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, nicotine and alcohol are also associated with the condition\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, and the number of cases also increased during the virus epidemic\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Finally, maternal health status is also an important component of aetiology. It has been suggested that gestational diabetes and hyperlipidaemia may affect fetal bone development through oxidative stress mechanisms\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, and that hypertension is associated with an elevated risk of foetal limb defects\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Insufficient maternal folic acid intake linked to neural tube defects: Tanzanian study shows doubled risk of congenital anomalies in areas with low folic acid supplementation rates\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. In conclusion, the aetiology of congenital musculoskeletal and limb anomalies is complex and requires a comprehensive diagnosis that combines genetic testing, assessment of environmental exposures and maternal health management. Perinatal nutritional interventions and avoidance of teratogenic exposures are important preventive strategies in clinical practice.\u003c/p\u003e \u003cp\u003eHowever, there are several limitations to this study. First, the accuracy and robustness of GBD estimates are highly dependent on the quality and quantity of data used in modelling. Although GBD 2021 provides extensive global data coverage, there is considerable variation in the completeness and consistency of data reporting across countries and regions, and the burden of congenital musculoskeletal and limb anomalies may be underestimated in resource-poor or poor areas due to underreporting or inadequate medical information systems. These factors combine to create data uncertainty. This may have a potential impact on the accurate assessment of the burden of disease. In addition, GBD databases mainly provide population-based summary data and lack detailed clinical and epidemiological information at the individual level. This limitation limits the ability to perform stratified analyses of specific patient subgroups and thus may affect the understanding of the heterogeneity, risk factors and their interacting mechanisms of congenital musculoskeletal and limb anomalies. Finally, the definition, aetiology and types of congenital musculoskeletal and limb anomalies in GBD 2021 still have some limitations that need to be further complemented and refined to improve the accuracy, comparability and reliability of the data. These results could provide a solid basis for further epidemiological studies and assessment of the burden of disease.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study estimated temporal trends in morbidity and mortality from congenital musculoskeletal and limb anomalies at global, national and regional levels from 1990 to 2021 and observed unfavourable trends in countries with lower socio-demographic indices, suggesting that some countries should develop more targeted and specific strategies to address the burden of congenital musculoskeletal and limb anomalies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors are grateful for the help of Zunyi Medical University, People\u0026rsquo;s Hospital of Qianxinan Prefecture, and Affiliated Hospital of Zunyi Medical University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the National Natural Science Foundation of\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eChina (grant nos. 82260106), the College Students\u0026rsquo; Innovation Training Program under project numbers 2024106610965, S2024106612281 and S2024106612233.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo datasets were generated or analysed during the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors of this manuscript have read and approved the final version of the article and agree to its publication. There are no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, Y.L., Z.B., R.Z., J.C., Z.T., and Z.Z.; methodology, Y.L, J.C., R.Z., Z.B., and Z.T.; validation, R.Z., J.C.; writing\u0026mdash;original draft preparation, R.Z., J.C.; data curation, J.C. and M.D. All the authors have read and agreed with the published version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e(WHO) WHO. 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(1879-0038 (Electronic)).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaterna-Kiryluk AA-O, Wisniewska K, Wieckowska BA-O, et al. Maternal Risk Factors Associated with Limb Reduction Defects: Data from the Polish Registry of Congenital Malformations (PRCM). LID \u0026ndash;\u0026thinsp;10.3390/children8020138 [doi] LID \u0026ndash;\u0026thinsp;138. (2227\u0026ndash;9067 (Print)).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"tropical-medicine-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tmah","sideBox":"Learn more about [Tropical Medicine and Health](https://tropmedhealth.biomedcentral.com/)","snPcode":"41182","submissionUrl":"https://submission.springernature.com/new-submission/41182/3","title":"Tropical Medicine and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Congenital musculoskeletal and limb anomalies, Incidence, Mortality, Prevalence, Global Burden of Disease","lastPublishedDoi":"10.21203/rs.3.rs-6063028/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6063028/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCongenital musculoskeletal and limb anomalies represent a rare and complex condition globally, with multifactorial etiology. Limited research has been conducted on the incidence trends of these anomalies. This study aims to investigate the patterns and temporal trends of congenital musculoskeletal and limb anomalies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eDetailed data on congenital musculoskeletal and limb anomalies from 1990 to 2021 were sourced from the 2021 Global Burden of Disease Study, stratified by sex, region, and country, and integrated with the Socio-demographic Index (SDI). To quantify the burden of these anomalies, we utilized Age-Standardized Incidence Rates (ASIR), Age-Standardized Mortality Rates (ASMR), Age-Standardized Prevalence Rates (ASPR), and Estimated Annual Percentage Change (EAPC). Additionally, decomposition analysis was conducted to examine the impact of aging, population, and epidemiological change on the burden. The ARIMA model was employed to forecast the burden for the period 2021\u0026ndash;2031, while health inequality was assessed using the Slope Index of Inequality and the Concentration Index.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eBrunei Darussalam recorded the highest age-standardized incidence rate (ASIR) for congenital musculoskeletal and limb anomalies globally in 2021, followed by Republic of Guatemala and Argentine Republic. Afghanistan and United Mexican States had the highest mortality and prevalence rates, respectively. India reported the largest number of cases and deaths in absolute terms, while China had the highest number of cases. The ARIMA model forecasts that by 2031, the number of congenital musculoskeletal and limb anomalies will increase from 2,437,890 to 24,711,128, while the number of deaths is projected to decrease from 13,600 to 10,137. The patient population is expected to grow from 18,549,408 to 19,207,414. Decomposition analysis revealed that the rise in the number of congenital musculoskeletal and limb anomalies in moderate SDI regions was primarily driven by population growth, whereas the reduction in mortality was mainly attributed to epidemiological changes and aging. In low and medium SDI areas, both population and epidemiological changes contributed to the increase in case numbers. The EAPC exhibited a significant correlation with ASIR and ASMR. Between 1990 and 2021, inequalities in the incidence and mortality of congenital musculoskeletal and limb anomalies have significantly increased. Lower SDI regions have experienced concentrated incidence and mortality, with respective inequities on the rise. The concentration index for incidence rose from 0.28 in 1990 to 0.35 in 2021, and the concentration index for mortality increased from 0.34 in 1990 to 0.42 in 2021, indicating an escalating burden of congenital musculoskeletal and limb anomalies in lower SDI groups.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study estimated temporal trends in the incidence and mortality of Congenital musculoskeletal and limb anomalies from 1990 to 2021 at the global, national, and regional levels. Adverse trends were observed in countries with lower sociodemographic indices. This suggests that some countries should develop more targeted and specific strategies to address the burden of Congenital musculoskeletal and limb anomalies.\u003c/p\u003e","manuscriptTitle":"Global, regional, and national burden of congenital musculoskeletal and limb anomalies, 1990-2021: A systematic analysis of the global burden of disease in 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-03 15:01:52","doi":"10.21203/rs.3.rs-6063028/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-07T00:38:38+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-28T09:19:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-28T01:35:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"273837175513296702142274623948377604522","date":"2025-02-24T12:46:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"234939241997688783711648869962033278557","date":"2025-02-24T11:50:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"232175840266294703929111475499706444670","date":"2025-02-24T10:11:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-02-24T09:50:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-24T09:29:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-02-24T09:27:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Tropical Medicine and Health","date":"2025-02-19T10:01:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"tropical-medicine-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tmah","sideBox":"Learn more about [Tropical Medicine and Health](https://tropmedhealth.biomedcentral.com/)","snPcode":"41182","submissionUrl":"https://submission.springernature.com/new-submission/41182/3","title":"Tropical Medicine and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"107664ff-2c12-4636-a5e0-d35dce62c372","owner":[],"postedDate":"March 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-19T16:04:07+00:00","versionOfRecord":{"articleIdentity":"rs-6063028","link":"https://doi.org/10.1186/s41182-025-00750-4","journal":{"identity":"tropical-medicine-and-health","isVorOnly":false,"title":"Tropical Medicine and Health"},"publishedOn":"2025-05-12 15:57:37","publishedOnDateReadable":"May 12th, 2025"},"versionCreatedAt":"2025-03-03 15:01:52","video":"","vorDoi":"10.1186/s41182-025-00750-4","vorDoiUrl":"https://doi.org/10.1186/s41182-025-00750-4","workflowStages":[]},"version":"v1","identity":"rs-6063028","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6063028","identity":"rs-6063028","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}