Trends and Projections of Spinal Cord Injury Burden in China: Insights from the Global Burden of Disease 2023 Study

Trends and Projections of Spinal Cord Injury Burden in China: Insights from the Global Burden of Disease 2023 Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Trends and Projections of Spinal Cord Injury Burden in China: Insights from the Global Burden of Disease 2023 Study Xiwang Chen, Jianbin Chen, Jinwen Huang, Feng Guo, Hai You This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8345634/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Traumatic spinal cord injury (TSCI) leads to substantial health loss through both premature mortality and long-term disability. In this study, we used data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 to estimate the global, regional, and national incidence, prevalence, and years lived with disability (YLDs) associated with TSCI. Methods: DisMod-MR 2.3 was applied to estimate case counts and age-standardized rates (ASRs), together with 95% uncertainty intervals (95% UIs), for the incidence (ASIR), prevalence (ASPR), and years lived with disability (ASYR) of spinal cord injury (SCI) from 1990 to 2021 at the global level, across 21 GBD regions, and in 204 countries and territories. Trends in ASRs were quantified using the estimated annual percentage change (EAPC) derived from a linear regression model, and Spearman rank-order correlation was used to explore the relationship between the sociodemographic index (SDI) and the burden of TSCI. Results: In 2023 there were an estimated 574,502 (95% UI 440,219-757,445) new cases, 15,400,682 (95% UI 14,009,114-17,075,106) existing cases, and 1,305,142 (95% UI 917,167-1,726,419) YLDs attributable to TSCI in global. Between 1990 and 2021, the absolute numbers of incident, prevalent, and YLD cases increased, whereas the age-standardized incidence (ASIR), prevalence (ASPR), and YLD (ASYR) rates declined. Men consistently exhibited higher ASIR, ASPR, and ASYR than women, and these ASRs rose with advancing age. Cervical SCI showed higher ASIR and ASYR compared with SCI below the neck. In 2021, the SDI was positively associated with ASIR (rho = 0.4670, p <0.01), ASPR (rho = 0.4035, p <0.01), and ASYR (rho = 0.2727, p =0.003). Conclusion: The absolute counts of incidence, prevalence, and burden of TSCI substantially increased from 1990 to 2021, despite the decrease in corresponding ASRs. TSCI happened in the most active periods of individuals globally, which were shifting towards older age groups over time. TSCI had larger effects on the elderly and males than younger populations and females. spinal cord injury projections Global Burden of Diseases Injuries and Risk Factors Study 2023 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Background Spinal cord injury (SCI), which is defined as structural and/or functional loss of the spinal cord, is one of the most serious diseases.which may lead to a partial or complete lossof motor, sensory, and autonomic functions below the site of injury ( 1 ). SCI has complex pathogenesis, which can be divided into traumatic and non-traumatic causes in general. High-energy extrinsic injuries are the main cause for traumatic SCI,such as automobile accident injuries, assaults between individuals, and high place injuries. On the other hand, the most common causes associated with non-traumatic SCI are tumours, haemangiomas and/or infarcts, spondylopathies,and the possible occurrence of ischaemia/reperfusion damage during surgery or other treatment modalities ( 2 ). Hence, the heterogeneity of such injuries makes SCI a leading cause of permanent disabilities worldwide,causing substantial and continuing burdens to people, their families, health care providers, and the public in terms of increased costs for health care services,resulted in lower levels of productivity, and long-term care needs ( 3 ). The global prevalence of SCI has increased over the last few decades.Global burden of SCI increased from 1990 to 2019: prevalence rose 81.5% (95% UI 74.2–87.1), incidence increase 52.7% (30.3–69.8) and YLDs rise 65.4% (56.3–76.0). However,the ASRs showed only minor variations, indicating that the drivers of increased absolute burden include largely population size and aging ( 4 ). There are also significant regional differences in the incidence of SCIs that reflect different levels of socioeconomic development,healthcare resources, systems for providing trauma care, and implementation of injuryprevention measures ( 5 ). Etiology and incidence profiles for SCI differ significantly in many areas of the world ( 6 ). In the US the annual incidence of SCI has been estimated to be approximately 54 per one million population,representing roughly 18,000 annual cases per year ( 7 ). The number of people with SCI in China is currently estimated at around 760,000 ,with more than 66,000 new cases per year ( 8 ). In lower income countries (as defined by IMF), rates range between 0.2 and 13.0 cases per 100,000 people ( 4 ). Although there is considerable international variation in these statistics, most information on the worldwide epidemiology of SCI has come from developed countries like those of North America,Europe, and Australia, but much less so for large parts of Asia and other low- and middle-income regions ( 7 ).This difference is also compounded with other factors such as differences in case definition and methodology of collecting the information etc.(e.g.differences in data collection methods (e.g., hospital-based vs populationbased registries) or other socioeconomic structures that make it difficult to compare findings from one country or region with another ( 9 ). China's position as the world's most populous developing nation highlights many of thesecomplicacies in a striking way. Its rapid industrialization,increased motor vehicle use, and urbanization have led to greater exposures for injurious risks common to developing countries,such as work related injury; fall-related injuries (including those occurring in the context of building or construction); and motor vehicle-related injuries.At the same time, the aging population has become more pronounced with an increasing number of degenerative spine diseases as well as low energy falls,phenomena which are more prevalent in the developed world. Despite estimates that China houses amongst the greatest number of people living with SCI,comprehensive and longitudinal epidemiologic information on the national level is lacking.Most past research has been limited to single hospitals, regions and/or time periods and is based mainly in the hospital:that may not be representative of national burden or variation by region in the country ( 10 , 11 ). To fill this evidence gap, in this study we use data from GBD Study 2023 for generating fine-grained estimations of the prevalence,the prevalence and the YLDs of traumatic SCI in China from 1990 to 2023.In this paper we investigate time trends stratified according to sex and age-group, examine patterns over the length of the study,and discusses the impact of these findings on health policy planning, allocation, and prevention efforts at the population level. Through providing new and comparable burden estimates,our study aims to provide evidence for future health care planning, and guide focused public health interventions that could mitigate the growing burden of SCI in China. Materials and methods Data acquisition and injury definition SCI incidence and burden in China were extracted from GBD 2023, which can be downloaded via Global Health Data Exchange (GHDx) online database: http://ghdx.healthdata.org/ . Spinal cord injury was identified with ICD coding ( 12 ). The SCI cases were further divided into different levels of injury according to International Classification of Diseases Tenth Revision (ICD-10) codes for the spinal cord injury level; cervical SCI (C1-C7 vertebral injury, ICD-10: S14,while injuries that involved segments between T1 and S5 were classified as SCI at a non-cervical level. The last group encompasses thoracic SCI (ICD-10 code: S24.1,denoting injury of the thoracic spinal cord), lumbar SCI (ICD-10 code: S34.1, corresponding to injury of the lumbar spinal cord), and sacral SCI (ICD-10 code: S34.0, corresponding to injury of the sacral spinal cord). We used these definitions consistent with those in the GBD injury hierarchy,thus enabling comparisons between countries for standardized epidemiologic surveillance ( 4 ). Since this study is based on anonymous,Data used in this study were publicly available through GBD 2023 and therefore did not require additional ethics approval. Definition of key measurements We examined three main age-standardized measures regarding the burden of SCI, namely the age standardized-prevalence rate (ASPR)the age standardized incidence rate (ASIR), and the age standardized years lived with disability rate (ASYR).The ASPR represents number of persons living with SCI per 100,000 population, extrapolated to the GBD 2023 world standard population;reflects the current burden on survivors, which depends upon injury incidence as well as survivorship after injury ( 13 ). ASIR expresses new SCI incidence per 100,000 individuals and it is also age standardized to the GBD 2023 standard population; it indicates the annual risk of acquiring a SCI and can be compared unbiasedly across country and over time ( 14 ). The ASYR is defined as the number of YLDs by 100,000 people caused by SCI, scaled up for the GBD 2023 global standard population;is calculated by combining the proportion of people in each SCI-related health state and their respective DWs,thus providing an adjusted measure for the level of permanent impairment ( 4 ). Statistical analysis All estimates pertaining to specific causes were derived utilizing DisMod-MR 2.1, a Bayesian meta-regression tool implemented in accordance with the established analytical framework of the BD 2023. DisMod-MR 2.1 integrates diverse epidemiological data sources within a compartmental model that ensures internal consistency among the parameters of incidence, prevalence, remission, and mortality ( 15 ). This model provides posterior distributions of all parameters which are used to compute the 95% uncertainty interval (95% UI) as the 2.5- and 97.5-percentile on 1,000 posterior draws. Temporal trend analysis for SCI incidence/prevalence, and YLDs were performed over the period 1990– 2023,we used the “Joinpoint” statistical software for R.We calculated APC and AAPC with 95% CIs for estimating if the trend was statistically different than zero ( 16 ). We used 95% CIs for estimating if the trend was statistically different than zero, and also estimated a linear regression model of log(ASR) over time to quantify long term trends:We estimated an EAPC: for China and for the global aggregate, we fitted a simple linear regression of ln(ASR) on calendar year (1990–2023): $$\:\text{ln}\text{(}\text{ASR}\text{)=}\text{α}\text{+}\text{β}\text{×}\text{year}\text{+ϵ}$$ , where ln(ASR) is the natural log of the age-standardized rates for incidence and prevalence,or YLD; α is an intercept term representing predicted log-rate at a value of year equal to zero; β represents the slope parameter corresponding to average change per year for the log-rate;and ε is a random error term reflecting unforeseen changes across periods.EAPC was then estimated based on this equation: (eβ − 1) × 100%, and 95% CI for EAPC were obtained according to standard error of β in the regression model. Due to specific clinical and prognosis impact of lesions at Cervical Level and lower,we further divided the ASIR, ASPR, and ASYR according to the location of the lesion (cervix vs. lower than cervix). To estimate the future burden of SCI in China, we used both a maximum likelihood age– period–cohort (APC) model and a Bayesian age–period–cohort (BAPC) model to forecast the rates of incidence ,prevalence, and YLDs between 2024–2040 ( 17 , 18 ). All statistical tests were two-sided, and a p-value < 0.05 was considered indicative of statistical significance. All analyses were conducted using R version 4.3.3 (R Foundation for Statistical Computing, Vienna, Austria). Results Incidence, prevalence and YLD of SCI in China and globally To contextualize the burden of SCI in China, we first summarized global trends in incidence, prevalence, and YLDs for SCI from 1990 to 2023. Worldwide, the annual number of new SCI cases increased from 682,567 (95% UI: 528,785–892,138) in 1990 to 1,010,928 (95% UI: 753,567–1,425,080) in 2023, representing a cumulative rise of 48.11%. Over the same period, however, the global ASIR fell from 12.88 (95% UI: 9.99–17.10; Fig. 1A) per 100,000 in 1990 to 12.31 (95% UI: 9.07–17.32; Fig. 1B) per 100,000 in 2023, corresponding to an EAPC of −0.02 (95% CI: −0.19 to 0.16). The global prevalence of SCI also rose substantially, from 16,808,304 (95% UI: 15,314,183–18,722,387) cases in 1990 to 27,538,533 (95% UI: 24,685,026–30,673,727) cases in 2023, an overall increase of 63.84%. In contrast, the age-standardized prevalence rate (ASPR) declined from 341.82 (95% UI: 312.83–377.46; Fig. 1C) per 100,000 in 1990 to 318.28 (95% UI: 285.01–355.51; Fig. 1D) per 100,000 in 2023, with an EAPC of −0.07 (95% CI: −0.24 to 0.10). Similarly, YLDs due to SCI increased from 5,502,832 (95% UI: 3,927,191–7,106,072) in 1990 to 8,024,507 (95% UI: 5,827,305–10,483,103) in 2023, a cumulative rise of 45.83%. Yet the age-standardized YLD rate (ASYR) decreased from 110.60 (95% UI: 79.26–142.31; Fig. 1E) per 100,000 in 1990 to 93.25 (95% UI: 67.85–121.94; Fig. 1F) per 100,000 in 2023, with an EAPC of −0.40 (95% CI: −0.56 to −0.24). The number of new SCI cases rose from 162,065 (95% UI: 116,923–223,108) in 1990 to 232,656 (95% UI: 161,638–351,309) in 2023, representing a cumulative increase of 43.56% in China. Over the same period, the ASIR increased from 13.56 (95% UI: 9.85–18.79) per 100,000 in 1990 to 15.96 (95% UI: 11.16–23.23) per 100,000 in 2023, with an EAPC of 1.11 (95% CI: 0.72–1.51). The prevalence of SCI in China nearly doubled, from 4,510,064 cases (95% UI: 4,027,350–5,064,110) in 1990 to 8,335,904 cases (95% UI: 7,446,638–9,283,348) in 2023, an 84.83% increase. Correspondingly, the age-standardized prevalence rate (ASPR) rose from 387.30 (95% UI: 348.48–432.67) per 100,000 in 1990 to 466.07 (95% UI: 414.71–520.65) per 100,000 in 2023, with an EAPC of 1.23 (95% CI: 0.78–1.69). For YLDs, China recorded 1,554,959 cases (95% UI: 1,062,866–1,989,468) in 1990 and 2,274,166 cases (95% UI: 1,545,414–3,005,306) in 2023, an increase of 46.25%. The age-standardized YLD rate (ASYR) was 128.93 (95% UI: 86.51–172.09) per 100,000 in 1990 and 132.34 (95% UI: 90.89–168.17) per 100,000 in 2023, yielding an EAPC of 0.48 (95% CI: 0.05–0.91). Unlike the global pattern, where ASRs for SCI have generally declined, China experienced clear increases in ASIR, ASPR, and ASYR between 1990 and 2023. China’s share of global incident SCI cases remained consistently high, accounting for 23.7% of worldwide cases in 1990 and 23.0% in 2023. By 2023, all three age-standardized indicators (ASIR, ASPR, and ASYR) in China exceeded the corresponding global averages. This divergence may reflect a lag in the implementation and effectiveness of comprehensive injury prevention and control strategies relative to the rapidly intensifying risks associated with accelerated socioeconomic development, urbanization, motorization, and population aging. Fig. 2 presents sex-specific trends in the all-age numbers of cases and the age-standardized incidence (ASIR), prevalence (ASPR), and YLD (ASYR) rates for SCI in China from 1990 to 2023. Overall, the total case counts and ASRs for incidence (Fig. 2A), prevalence (Fig. 2B), and YLDs (Fig. 2C) remained relatively stable up to around 2005. Thereafter, they increased markedly, reaching a peak around 2015, and then declined, with the lowest levels observed in 2020, followed by a modest upturn thereafter. Throughout the entire study period and across all indicators, the burden of SCI was consistently and substantially higher in males than in females in China(Table 1-3). Table 1 Incidence Burden of Acute Glomerulonephritis in G20 and China, 1990-2023 location Num_1990 ASR_1990 Num_2021 ASR_2021 EAPC_CI Both China 162065 (116923 to 223108) 13.56 (9.85 to 18.79) 232656 (161638 to 351309) 15.96 (11.16 to 23.23) 1.11 (0.72 to 1.51) Global 682567 (528785 to 892138) 12.88 (9.99 to 17.1) 1010928 (753567 to 1425080) 12.31 (9.07 to 17.32) -0.02 (-0.19 to 0.16) Female China 51916 (35094 to 75485) 9.22 (6.24 to 13.68) 75722 (48213 to 124232) 10.16 (6.47 to 15.75) 0.86 (0.46 to 1.26) Global 233763 (168606 to 332542) 8.93 (6.52 to 12.87) 392166 (268112 to 614853) 9.48 (6.42 to 14.74) 0.23 (0.02 to 0.44) Male China 110149 (82431 to 147801) 17.59 (13.23 to 23.73) 156934 (113394 to 227870) 21.26 (15.2 to 29.96) 1.22 (0.83 to 1.62) Global 448804 (354794 to 571964) 16.74 (13.28 to 21.46) 618761 (471470 to 825503) 15.09 (11.43 to 20.06) -0.14 (-0.31 to 0.03) Table 2 Prevalence Burden of Acute Glomerulonephritis in G20 and China, 1990-2023 location Num_1990 ASR_1990 Num_2021 ASR_2021 EAPC_CI Both China 4510064 (4027350 to 5064110) 387.3 (348.48 to 432.67) 8335904 (7446638 to 9283348) 466.07 (414.71 to 520.65) 1.23 (0.78 to 1.69) Global 16808304 (15314183 to 18722387) 341.82 (312.83 to 377.46) 27538533 (24685026 to 30673727) 318.28 (285.01 to 355.51) -0.07 (-0.24 to 0.1) Female China 1568936 (1374193 to 1785672) 280.36 (247.5 to 316.45) 2846549 (2503881 to 3235336) 318.66 (279.75 to 364.66) 0.99 (0.55 to 1.43) Global 6075929 (5467963 to 6867275) 247.29 (224.09 to 277.19) 10405433 (9230229 to 11988017) 237.74 (209.78 to 278.41) -0.01 (-0.17 to 0.15) Male China 2941128 (2624858 to 3273697) 486.46 (434.49 to 540.29) 5489355 (4890956 to 6152073) 605.74 (540.21 to 679.29) 1.38 (0.91 to 1.85) Global 10732376 (9790834 to 11791041) 434.79 (398.86 to 473.68) 17133101 (15536706 to 18950169) 399.01 (361.76 to 441.89) -0.08 (-0.26 to 0.09) Table 3 YLDs Burden of Acute Glomerulonephritis in G20 and China, 1990-2023 location Num_1990 ASR_1990 Num_2021 ASR_2021 EAPC_CI Both China 1554959 (1062866 to 1989468) 132.34 (90.89 to 168.17) 2274166 (1545414 to 3005306) 128.93 (86.51 to 172.09) 0.48 (0.05 to 0.91) Global 5502832 (3927191 to 7106072) 110.6 (79.26 to 142.31) 8024507 (5827305 to 10483103) 93.25 (67.85 to 121.94) -0.4 (-0.56 to -0.24) Female China 527769 (355396 to 677814) 93.5 (63.32 to 120.08) 747932 (501738 to 991874) 85.05 (56.6 to 113.24) 0.2 (-0.21 to 0.61) Global 1928537 (1344274 to 2512824) 77.7 (54.38 to 100.05) 2948377 (2152790 to 3931105) 68.01 (49.77 to 90.69) -0.33 (-0.48 to -0.19) Male China 1027190 (697564 to 1306616) 168.37 (114.6 to 214.24) 1526234 (1035898 to 2014336) 170.41 (115.22 to 227.29) 0.64 (0.2 to 1.09) Global 3574294 (2571417 to 4632419) 142.96 (103.26 to 184.62) 5076130 (3643149 to 6585509) 118.5 (85.16 to 154.03) -0.43 (-0.59 to -0.26) The disease burden of SCI by year, sex, and age in China To identify demographic groups at greatest risk, we assessed how the burden of SCI varied by sex and age in China, using both absolute case counts and ASRs. Stratified analyses showed a broadly increasing SCI burden among both males and females and across age groups from 1990 to 2023, with men consistently experiencing a higher burden than women throughout the study period. In 1990, the male-to-female ratios for ASIR, ASPR, and ASYR were 1.91:1, 1.74:1, and 1.80:1, respectively. By 2023, these ratios had risen to 2.09:1, 1.90:1, and 2.00:1, respectively (Fig. 3A). A similar pattern was observed for absolute case numbers. In 1990, the male-to-female ratios for incident cases, prevalent cases, and YLDs were 2.12:1, 1.87:1, and 1.95:1, respectively, whereas in 2023 these ratios were 2.07:1, 1.93:1, and 2.04:1, respectively (Fig. 3B). Taken together, these findings indicate that, over time, the sex gap in SCI burden has generally widened, with males increasingly bearing a disproportionate share of both the incidence and long-term disability associated with SCI in China. In 1990, the age-specific incidence rate (ASIR) of SCI fluctuated across age groups and reached its highest level in the 90–94-year group. By contrast, in 2023 the ASIR initially increased with age, peaking in the 25–29-year group, and then declined; however, after the 65–69-year group, the ASIR again rose steadily with age up to 90–94 years (Fig. 4A). Regarding case numbers, the highest number of incident SCI cases in 1990 occurred in the 20–24-year group, whereas in 2023 the peak shifted to the 35–39-year group (Fig. 4B). The age-specific patterns of prevalence and YLDs—both in terms of case counts and ASRs—displayed broadly similar trajectories to those observed for incidence over the same period (Fig. 4A–B). Substantial improvements in SCI burden were evident in many age groups, with the most pronounced reductions seen among children and adolescents between 1990 and 2023. Nevertheless, a clear shift in the age distribution of prevalence, YLDs, and their corresponding ASRs emerged when comparing 1990 with 2023. By 2023, the peak age-standardized prevalence rate (ASPR) and age-standardized YLD rate (ASYR) occurred in the 65–69- and 50–54-year groups, respectively, and ASYR values after age 50–54 were higher in 2023 than in 1990. Although age-specific ASPR and ASYR consistently displayed a single-peaked, arch-shaped pattern across age groups, the apex of this curve—indicating the age group with the greatest burden—shifted markedly toward older ages in 2023, suggesting progressive aging of the SCI-affected population. The temporal evolution of SCI burden across age groups in China was portrayed using stacked area plots (Fig. 4C–D). These visualizations reveal that, although year-to-year fluctuations were present, both the ASRs ( Fig. 4C) and the absolute numbers of incident cases, prevalent cases, and YLDs (Fig. 4D) generally trended upward from 1990 to 2023. At the same time, the center of gravity of the disease burden progressively shifted toward older age groups. This indicates that individuals living with SCI in China are, on average, becoming older, and that an increasing share of new injuries and long-term disability now occurs in older adults rather than in younger populations. The progressive rightward movement of the incidence, prevalence, and YLD peaks closely parallels China’s rapid population aging. In addition, improvements in acute care and subsequent management have enhanced survival after SCI, lengthening disease duration and thereby enlarging the pool of elderly survivors, which in turn inflates both prevalence and YLD counts in older age strata. Age-specific distribution curves for incidence, prevalence, and YLDs further delineate the pattern of SCI burden by lesion location (Fig. 5A–C). Across the study period, both cervical SCI and SCI below the neck were disproportionately clustered in older age groups. The proportion of incident SCI cases rose steadily with increasing age (Fig. 5A), while the prevalence (Fig. 5B) and YLD profiles (Fig. 5C) highlighted a particularly concentrated disability burden among middle-aged and older adults. This burden became clearly apparent from around 40–44 years of age and continued to intensify into later life, with cervical SCI contributing most prominently to the highest levels of disability. These findings point to a dual pattern: not only are cervical injuries increasingly frequent and persistent in older individuals, but they also generate a substantial and enduring disability impact. Taken together, the results indicate a pronounced aging-related transformation in the epidemiology of SCI in China, with older adults—especially those with cervical lesions—emerging as the principal drivers of SCI-related health loss. Gender differences in SCI burden by age and injury site in China For cervical SCI, men consistently exhibited higher incidence rates than women in almost all age groups. In 2023, the largest number of incident cervical SCI cases among males occurred in the 35–39-year group, whereas in females the incident case count peaked in the 55–59-year group. Up to ages 75–79 years, men had more new cervical SCI cases than women; however, from age 80 onwards, incident case counts became higher in women. With respect to age-specific incidence rates in 2023, rates in women rose steadily with advancing age. In contrast, the incidence rate in men increased initially, reaching a maximum in the 25–29-year group, and then declined, before rising again after ages 65–69 years and continuing to climb through the 90–94-year group (Fig. 6A).Patterns for prevalence of cervical SCI were broadly similar. In 2023, the highest number of prevalent cervical SCI cases in men was observed in the 50–54-year group, whereas in women the peak case count again occurred in the 55–59-year group. Up to ages 75–79 years, men had more prevalent cervical SCI cases than women, but among those aged 80 years and older, women accounted for more cases. Age-specific prevalence rates for cervical SCI in 2023 increased progressively with age in both sexes, peaking at ages 50–54 years in men and 70–74 years in women, and then gradually declined thereafter. Beyond the 85–89-year group, the prevalence rate curves for men and women were nearly superimposed, indicating convergence of cervical SCI prevalence at the oldest ages (Fig. 6B).A comparable pattern emerged for YLDs due to cervical SCI. In 2023, the number of YLDs peaked among men in the 50–54-year age group and among women in the 55–59-year group. Up to ages 75–79 years, YLD counts from cervical SCI were consistently higher in men, whereas from age 80 years onward, women experienced more disability. Age-specific YLD rates in 2023 rose with age in both sexes, reaching their maximum in the 50–54-year group for men and the 70–74-year group for women, followed by a gradual decline at older ages. After 85–89 years, the YLD rate curves for men and women overlapped closely, again suggesting convergence at the oldest ages (Fig. 6C). For SCI below the neck, sex- and age-specific patterns showed both parallels and contrasts with cervical injuries. In 2023, the largest number of incident cases among men was observed in the 35–39-year group, while among women incident case counts peaked at 55–59 years. Men had more incident cases than women up to the 65–69-year group; from age 70 years onwards, incident case counts were higher in women. In female patients, the incidence rate of SCI below the neck rose monotonically with age in 2023 and exceeded the male rate after the 70–74-year group. Among men, the incidence rate initially increased with age and peaked at 25–29 years, then decreased, but began to rise again after 70–74 years and continued increasing through 90–94 years (Fig. 7A). Regarding prevalence of SCI below the neck, the maximum number of prevalent cases for both men and women occurred in the 55–59-year age group in 2023. Men had more prevalent cases than women up to ages 75–79 years; however, from age 80 years and above, women comprised the majority of prevalent cases. In 2023, age-specific prevalence rates in both sexes rose with age, peaking at 50–54 years in men and 70–74 years in women, and then progressively declined thereafter. After the 85–89-year group, the prevalence rate in women began to surpass that in men for SCI below the neck (Fig. 7B). The YLD patterns for SCI below the neck also reflected a pronounced age and sex gradient. In 2023, the highest YLD case numbers among men occurred in the 50–54-year group, and among women in the 55–59-year group. Up to ages 75–79 years, men bore a larger YLD burden from SCI below the neck, whereas beyond age 80, YLD case counts were higher in women. Age-specific YLD rates in 2023 increased steadily with age in both sexes, peaking at 55–59 years in men and 70–74 years in women, and then declined at older ages. From the 85–89-year group onward, the YLD rate for women with SCI below the neck exceeded that of men (Fig. 7C). Joinpoint analysis of SCI burden in China We applied Joinpoint regression to characterize temporal changes in the ASIR, prevalence rate (ASPR), and YLD rate (ASYR) of SCI in China. For ASIR, the trend was segmented into several distinct phases (Fig. 8A). From 1990 to 1994, ASIR showed a modest but statistically significant decline (APC=−0.98, p<0.05). This was followed by a mild, non-significant upslope between 1994 and 2004 (APC=0.53, p=0.27). A pronounced acceleration in incidence emerged after 2004: ASIR increased rapidly from 2004 to 2008 (APC=7.34, p<0.05) and continued to rise, though at a slower pace, from 2008 to 2014 (APC=3.02, p<0.05). This growth phase was followed by a sharp downturn between 2014 and 2019 (APC=−7.09, p<0.05). Subsequently, from 2019 to 2023, ASIR again turned upward, with a sustained and significant increase over this most recent period (APC=2.65, p<0.05). For ASPR, a somewhat different pattern was observed (Fig. 8B; Supplementary Table S3). Prevalence initially declined slightly from 1990 to 1995 (APC=−0.74, p<0.05)(APC=−0.74, p<0.05). Thereafter, ASPR entered a prolonged growth phase extending from 1995 to 2015, with particularly notable increases from 2004 to 2009 (APC=6.87, p<0.05) and from 2009 to 2015 (APC=2.11, p<0.05). This upward trajectory reversed between 2015 and 2019, when ASPR experienced a marked drop (APC=−9.27, p<0.05). From 2019 to 2023, however, prevalence resumed an increasing trend (APC=3.21, p<0.05). For ASYR, China exhibited an early period of decline followed by a later escalation (Fig. 8C). Between 1990 and 1996, the age-standardized YLD rate decreased significantly (APC=−0.93, p<0.05). From 1996 to 2003, this decline flattened and was no longer statistically significant (APC=−0.09, p=0.67). Beginning in 2003, ASYR entered a sustained growth phase: it rose rapidly from 2003 to 2010 (APC=4.74, p<0.05) and continued to increase at a more moderate rate from 2010 to 2014 (APC=1.99, p<0.05). A significant downturn followed between 2014 and 2019 (APC=−8.84, p<0.05). In the most recent period, 2019–2023, ASYR once again showed a consistent and statistically significant increase (APC=3.07, p<0.05). Overall, the Joinpoint analysis highlights a pattern of early stability or modest decline, followed by a mid-2000s surge in incidence, prevalence, and disability, a pronounced drop around the mid‑2010s, and a renewed increase in SCI burden in the years after 2019. Age–period–cohort analysis of SCI incidence in China To disentangle the contributions of age, calendar period, and birth cohort to SCI incidence in China, we conducted an age–period–cohort (APC) analysis for the period 1990–2023. A global test indicated that variation in SCI incidence was significantly associated with age, period, and cohort effects in the total population (p<0.05). Local drift estimates showed that the largest annual percentage increases in incidence were concentrated in the 70–74‑year age group, suggesting a particularly rapid rise in SCI risk among older adults (Fig. 9A). The age effect (Fig. 9B) demonstrated a strong positive association between age and SCI incidence. Incidence rates rose gradually with age and then climbed sharply after about 70 years, reaching their highest levels in the oldest age groups, before showing only a slight decline at extreme old age. This confirms that advanced age is a major determinant of SCI risk in China. The period effect (Fig. 9C) revealed temporal fluctuations in SCI incidence that were independent of age and birth cohort. Using 2004–2008 as the reference period (RR=1), period-specific rate ratios (RRs) were consistently below 1 during 1989–2003, indicating lower incidence in those earlier years. By contrast, all RRs for 2009–2023 exceeded 1, reflecting a higher period‑related risk in more recent years. The period curve showed an overall rise, followed by a downturn after the 2014–2018 interval, consistent with the Joinpoint findings of a peak around the mid‑2010s and subsequent decline. The cohort effect (Fig. 9D) highlighted generational differences. Taking the 1960 birth cohort as the reference (RR=1), RRs for cohorts born between 1895 and 1955 were uniformly below 1, indicating a lower lifetime risk of SCI among earlier-born generations. In contrast, cohorts born from 1965 to 2020 exhibited RRs greater than 1, signifying higher SCI incidence among more recent birth cohorts. The cohort curve increased up to around the 1960–1965 cohorts and then progressively declined after approximately the 2010 birth cohort, suggesting that the elevated risk is particularly pronounced in cohorts born after the 1960s but does not continue to rise indefinitely in the youngest cohorts. Additional descriptive APC plots further clarified these patterns: Age-specific rates by period (Fig. 9E) showed that, within each calendar period, SCI incidence rose with age, peaked around 85–90 years, and then decreased slightly in the very oldest groups, reinforcing the dominant influence of aging on SCI risk. Cohort-specific rates by age group (Fig. 9F) indicated that, for almost all age groups, more recent birth cohorts experienced higher incidence rates than earlier cohorts. This points to a shift of SCI burden toward generations born after the 1960s. Period-specific rates by age group (Fig. 9G) showed increasing incidence over successive calendar periods among those aged 85 years and older, with later years associated with greater SCI burden in the oldest age strata. Taken together, the APC analysis suggests that the rising SCI incidence in China is driven by three intertwined factors: population aging (strong age effect), an unfavorable temporal environment in recent decades (period effect with RRs > 1 after 2009), and higher underlying risk among post‑1960 birth cohorts (cohort effect), with the steepest relative increases observed in older adults, especially those aged 70 years and above. Decomposition analysis revealed drivers of change in SCI burden in China For SCI incidence, the net increase of 8,443,044 cases over the study period was overwhelmingly attributable to demographic dynamics (Fig. 10A). Population growth was the dominant driver, accounting for an additional 8,035,219 incident cases (95.17% of the total change). Population aging further amplified incidence, contributing 2,996,310 extra cases (35.49%). These upward demographic pressures were substantially offset by favorable epidemiological shifts: improvements in risk profiles, prevention, and/or clinical management collectively reduced the expected number of incident cases by 2,588,485 (−30.66%), partially counterbalancing the increase that would have occurred in the absence of such changes. A similar decomposition pattern was observed for SCI prevalence (Fig. 10B). The overall increase of 8,443,044 prevalent cases was again mainly driven by population growth, which contributed 8,035,219 cases (95.17%). Population aging added a further 2,996,310 cases (35.49%) to the prevalence pool. In contrast, epidemiological changes exerted a sizable mitigating effect, reducing the expected prevalence by 2,588,485 cases (−30.66%) relative to a scenario with unchanged rates. The YLD burden due to SCI followed the same structure of contributing factors (Fig. 10C). The increase of 8,443,044 YLDs was primarily the result of population expansion, with population growth contributing 8,035,219 additional YLDs (95.17%). Aging of the population further increased YLDs by 2,996,310 (35.49%). At the same time, favorable epidemiological developments—reflected in lower rates or reduced severity of disability—offset this trend by 2,588,485 YLDs (−30.66%), indicating a substantial protective influence. Marked sex differences emerged across all three burden indicators. The impact of population aging was more pronounced in males than in females, contributing 1,911,605 additional cases (37.55%) versus 1,080,054 cases (32.38%), respectively, for incidence, prevalence, and YLDs combined. Likewise, the protective effect of epidemiological improvements was stronger in men: epidemiological changes reduced the expected burden by 1,869,843 cases (−36.73%) in males, compared with 706,393 cases (−21.17%) in females. Although population growth remained the leading driver for both sexes, its relative contribution was slightly higher in men (99.18%) than in women (88.80%). Predictive analysis For incidence, the ASIR is predicted to follow a sustained downward trajectory (Fig. 11A). Specifically, ASIR is estimated to decline from 16.24 (95% UI: 16.21–16.28) per 100,000 population in 2023 to 14.28 (95% UI: 12.78–15.79) per 100,000 in 2038, corresponding to an approximate 12.1% reduction over the 15‑year projection horizon. Although the central tendency indicates a steady decrease, the uncertainty intervals become progressively wider in the later years, particularly after 2030, reflecting increasing forecasting uncertainty as the projection extends further from the observation period. The age-standardized prevalence rate (ASPR) showed a markedly different pattern (Fig. 11B). ASPR is projected to remain at a relatively high level overall, increasing slightly from 458.98 (95% UI: 458.87–459.10) per 100,000 in 2023 to 458.96 (95% UI: 398.03–519.90) per 100,000 in 2038. Despite short‑term fluctuations during the intermediate years, the forecast suggests that prevalence will reach a peak around 2024–2025 and then gradually decline, stabilizing by the end of the projection window. Thus, SCI prevalence is expected to remain substantial, but without a sustained upward or downward long‑term trend in age‑standardized terms. For YLDs, the age-standardized YLD rate (ASYR) is forecast to decrease, broadly mirroring the pattern observed for incidence (Fig. 11C). ASYR is projected to fall from 126.84 (95% UI: 126.78–126.91) per 100,000 in 2023 to 114.64 (95% UI: 99.63–129.66) per 100,000 in 2038, representing a 9.6% reduction over the projection period. As with ASIR, the prediction intervals widen towards 2038, indicating greater uncertainty in long‑term estimates, but the central forecast consistently points to a favorable decline. Taken together, these projections indicate that: Incidence and YLDs are likely to follow generally improving trajectories, with moderate reductions in ASRs through 2038. Prevalence will remain high and largely stable in age-standardized terms, peaking in the mid‑2020s and then slowly decreasing. Despite these favorable trends in ASRs, the absolute burden of SCI in China is expected to persist, underscoring the continued need for prevention, acute care optimization, and long‑term rehabilitation services. Discussion This study offered a comprehensive characterization of how the SCI burden in China has evolved from 1990 to 2023, framed within the context of global trends. A striking pattern emerged: during a period when global age-standardized incidence, prevalence, and YLD rates for SCI declined (19), China moved in the opposite direction, with all three indicators rising markedly (4, 6, 20). This divergence points to a multifactorial dynamic in China, where demographic aging, rapid socioeconomic transition, and the timing and intensity of health policy implementation intersect. The combination of sharply increasing absolute case counts and rising ASRs indicates that SCI has become a growing and progressively more serious public health threat in China—one that has not been fully contained by existing preventive and control measures. The downward trend in global ASRs likely reflects the long-term impact of sustained investment in road traffic legislation, improved occupational safety regulations, and the development of sophisticated trauma systems in many high-income settings (21). By contrast, China’s rising SCI rates unfolded alongside an era of unprecedented economic expansion and accelerated urbanization. While these processes have significantly improved living standards, they also brought rapid growth in construction, manufacturing, and motorized transport, thereby amplifying exposure to high-risk occupational and environmental conditions (8, 22). Our Joinpoint regression identified a particularly steep rise in ASIR between 2004 and 2014, a time that coincides with large-scale infrastructure projects and explosive growth in vehicle ownership. The subsequent decline after 2014 may reflect the gradual consolidation and stricter enforcement of national measures such as the Road Traffic Safety Law and more stringent workplace safety regulations (23). Nevertheless, the renewed upturn after 2019 suggests that, although these policies have had a beneficial impact, they have not fully neutralized the risks associated with an aging population and ongoing hazardous exposures in certain industries.. Another salient finding was the increasing gender gap in SCI burden. The male-to-female ASIR ratio rose from 1.91:1 in 1990 to 2.09:1 in 2023, indicating that men have not shared equally in any recent gains. This widening disparity is consistent with the gendered distribution of both occupational and behavioral risk factors. Men continue to dominate employment in high-risk sectors such as construction, transport, and heavy industry, where falls from height, road traffic crashes, and machinery-related injuries are frequent(24, 25). The slower reduction—or even persistence—of SCI burden among men suggests that improvements in occupational safety have lagged behind the scale and intensity of industrial activity. In addition, behaviors disproportionately observed among men, including speeding, driving under the influence of alcohol, and other forms of risk-taking, further amplify their vulnerability (26). Together, these patterns underscore the need for more rigorous and better enforced occupational safety frameworks, as well as targeted, gender-sensitive behavioral interventions focused on male workers and road users. The evolving age pattern of SCI in China highlights a dual challenge encompassing both working-age and older adults. Over the study period, the peak of incident cases shifted from the very old in 1990 to the middle-aged group (35–39 years) in 2023, suggesting that occupational and work-related injuries remain a predominant driver of new cases in the core labor force. At the same time, we observed a substantial increase in prevalence and YLD rates among individuals aged 50 years and older. This pattern is closely tied to population aging and rising life expectancy, which have expanded the number of people living for long periods with SCI-related disability (27). Older adults are particularly susceptible to low-energy falls, driven by conditions such as osteoporosis, degenerative spinal disease, and impaired balance (5). When these events involve the cervical spine, they often result in profound functional impairment—a pattern consistent with our findings of higher ASIR and ASYR for cervical lesions compared with injuries at lower spinal levels (28). These demographic and clinical shifts argue for a strategic reorientation of SCI prevention and care: beyond traditional injury control, there is a pressing need to integrate geriatric-focused fall prevention, comprehensive management of degenerative spinal conditions, and age-appropriate rehabilitation into national strategies for SCI control. The decomposition analysis added an important layer of nuance to our understanding of why the SCI burden continues to rise in China. It showed that demographic dynamics—in particular, rapid population growth and population aging—were the main forces driving the expansion in absolute case numbers. At the same time, the analysis demonstrated that favorable epidemiological shifts, plausibly linked to expanded prevention efforts and improvements in clinical care, acted in the opposite direction and substantially dampened the increase that would otherwise have occurred. The observation that this protective effect was more pronounced in males is particularly informative: it suggests that safety measures, when implemented, can have a tangible impact on high‑risk groups, but that their reach and intensity remain uneven across populations and settings (10). From a policy standpoint, these findings draw a clear distinction between largely non‑modifiable demographic trends and potentially modifiable risk and care environments. While China cannot reverse population aging or past population growth, there is considerable room to reduce the future SCI burden by scaling up targeted, high‑impact public health interventions. Experience from high‑SDI settings, where lower ASIRs, ASPRs, and ASYRs have been achieved through coordinated packages of road safety legislation, fall prevention in older adults, and stringent occupational health regulations, offers a valuable template for China’s next phase of SCI control (29, 30).Adapting and rigorously implementing such integrated approaches—while paying close attention to sex‑ and age‑specific vulnerabilities—will be critical to counterbalancing the demographic headwinds identified in this study. This study has several important limitations that should be considered when interpreting the findings. First, all estimates were derived from the GBD modeling framework, which synthesizes heterogeneous data sources. Incomplete case ascertainment—especially for non‑traumatic SCI, which is often underdiagnosed or poorly recorded—may lead to underestimation of the true burden. Second, we relied on the GBD global standard population for age standardization, which may not perfectly reflect China’s rapidly aging population structure. This mismatch could introduce bias in ASPR and ASYR estimates, particularly when making comparisons over time or with other countries. Third, the absence of provincial‑level data meant that we were unable to characterize subnational heterogeneity in SCI burden within China. Given known disparities in socioeconomic development, healthcare access, and injury risk across regions, this represents a notable gap and a priority for future work. Finally, the age–period–cohort analysis was conducted at the aggregate level and is therefore susceptible to ecological fallacy; associations observed at the population level cannot be directly extrapolated to individual risk. Causal inferences regarding specific age, period, or cohort mechanisms should thus be made with caution and ideally complemented by individual‑level, longitudinal studies. Conclusion This study revealed that, in sharp contrast to global declines, SCI burden in China is rising—especially among men and older adults—driven by occupational hazards, road traffic injuries, and age‑related falls. These findings call for a coordinated national strategy that couples stricter road and workplace safety enforcement with strengthened geriatric care, fall prevention, and data‑driven, targeted interventions for high‑risk groups. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials The datasets generated and analyzed during the current study are derived from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023, coordinated by the Institute for Health Metrics and Evaluation (IHME). All data on the incidence, prevalence, and years lived with disability (YLDs) for spinal cord injury (SCI) in China and globally are publicly available through the Global Health Data Exchange (GHDx) query tool (http://ghdx.healthdata.org/). These summary data are accessible for research purposes under the IHME's standard terms of use. The specific modeling and statistical analyses conducted in this study were based on the GBD 2023 analytical framework, utilizing tools such as DisMod-MR 2.1. The custom R code used for data processing, Joinpoint regression, age-period-cohort (APC) analysis, decomposition analysis, and generating the figures is not part of the publicly available GBD resources. However, these analytical scripts are available from the corresponding author on reasonable request for the purpose of verifying or replicating the study's findings. Competing Interests The authors declare that they have no competing interests. Funding Not applicable. Authors' contributions XXX contributed to the conceptualization, data curation, formal analysis, and drafting of the manuscript. XXX performed the statistical analysis and visualization of results. XXX assisted in data interpretation and contributed to the discussion and revision of the manuscript. XXX participated in methodological design and provided critical feedback during manuscript editing. XXX supervised the study, guided the research methodology, and critically revised the final manuscript for important intellectual content. All authors have read and approved the final version of the manuscript and agree to be accountable for all aspects of the work. Acknowledgements Not applicable. 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You","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYHACZhDB2ACkDkj+seHh528gRYtlQ5qM5IwDxGoBkZUNh20MGhLwqzc4f8bY4OOOWtn+dh7DAzd3nOcxYDjA+OFjDh4tB44lJ848c9x4xmEeg4Mzz9zmMWduYJacuQ2PloPNhw/zth1LbABqOSzBdpvHsuEAGzMvPi2HGZvBWuaDtPxhO8djcCCBgJZjzIeTedtqEjcAtRyQbDtAWIvkGbZkw5ltB4w3HmYrOCBxJplHcsbBZrx+4QOGmMTHtjrZeecPb/4gUWFnz8/ffPDDRzxaFA6AqcNAzGEAFYPEEU4gD5GuA2L2B3hVjoJRMApGwcgFAAvyXM4WoqGHAAAAAElFTkSuQmCC","orcid":"","institution":"Ganzhou People’s Hospital","correspondingAuthor":true,"prefix":"","firstName":"Hai","middleName":"","lastName":"You","suffix":""}],"badges":[],"createdAt":"2025-12-12 12:08:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8345634/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8345634/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102209397,"identity":"dd7736f6-1691-47ba-8c49-c4020d273ec7","added_by":"auto","created_at":"2026-02-09 12:13:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":9205637,"visible":true,"origin":"","legend":"\u003cp\u003eChange trends of ASRs of incidence, prevalence, and YLDs due to SCI by injured sites and sex from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(A) Trends of ASIR of cervical SCI or SCI below cervical level from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(B) Trends of age-standardized prevalence rate of cervical SCI or SCI below cervical level from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(C) Trends of age-standardized YLDs rate of cervical SCI or SCI below cervical level from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(D) Trends of ASIR of SCI for females and males from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(E) Trends of age-standardized prevalence rate of SCI for females and males from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(F) Trends of age-standardized YLDs rate of SCI for females and males from 1990 to 2021.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/1e72623e1447ebc074606203.png"},{"id":102209259,"identity":"a4d5c162-4494-4e7b-b431-1e0009d38b89","added_by":"auto","created_at":"2026-02-09 12:12:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4840243,"visible":true,"origin":"","legend":"\u003cp\u003eSex- and age-structured analysis of SCI burden in 2021.\u003c/p\u003e\n\u003cp\u003e(A) Incidence case numbers and its corresponding rate for males and females among all age groups.\u003c/p\u003e\n\u003cp\u003e(B) Prevalence case numbers and its corresponding rate for males and females among all age groups.\u003c/p\u003e\n\u003cp\u003e(C) YLDs (years of life lived with disabilities) case numbers and its corresponding rate for males and females among all age groups.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/b3c2db318d13191bf51de33b.png"},{"id":102209319,"identity":"0befb43a-1b99-4b7a-8d48-10e20e2d5817","added_by":"auto","created_at":"2026-02-09 12:12:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":963240,"visible":true,"origin":"","legend":"\u003cp\u003eASRs of incidence, prevalence, and YLDs attributable to SCI across countries and territories by socio-demographic index (SDI) for both sexes, 1990–2021.\u003c/p\u003e\n\u003cp\u003e(A) Change trends of age-standardized incidence rates for regions by SDI.\u003c/p\u003e\n\u003cp\u003e(B) Change trends of age-standardized prevalence rates for regions by SDI.\u003c/p\u003e\n\u003cp\u003e(C) Change trends of age-standardized YLDs rates for regions by SDI.\u003c/p\u003e\n\u003cp\u003e(D) Change trends of age-standardized incidence rates by country and SDI.\u003c/p\u003e\n\u003cp\u003e(E) Change trends of age-standardized prevalence rates by country and SDI.\u003c/p\u003e\n\u003cp\u003e(F) Change trends of age-standardized YLDs rates by country and SDI.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/b60cda5d63618bb3919ab746.png"},{"id":102209374,"identity":"e7d89e11-5751-462e-bfd9-b457553b2d85","added_by":"auto","created_at":"2026-02-09 12:13:00","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4461518,"visible":true,"origin":"","legend":"\u003cp\u003eThe association between EAPCs and SCI-related ASRs in 1990 and HDI (human development index) in 2021.\u003c/p\u003e\n\u003cp\u003e(A) Correlations between EAPCs and ASRs in1990.\u003c/p\u003e\n\u003cp\u003e(B) Correlations between EAPCs and ASRs from 2019 to 2021.\u003c/p\u003e\n\u003cp\u003e(C) Correlations between EAPCs and ASRs in 2021.\u003c/p\u003e\n\u003cp\u003e(D) Correlations between EAPCs and HDIs in 2021.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/ef01bbaa3fb173688e25d180.png"},{"id":102209517,"identity":"1fb80160-e66a-4ec2-9c9d-8b3a6a604ccf","added_by":"auto","created_at":"2026-02-09 12:13:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3238650,"visible":true,"origin":"","legend":"\u003cp\u003eChange trends of ASRs of incidence, prevalence, and YLDs due to SCI for different sex from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(A) Change trends of age-standardized incidence, prevalence, and YLDs rates for different sex from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(B) Change trends of incidence, prevalence, and YLDs case number for different sex from 1990 to 2021.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/0a6762c041d9e60ab4d025a9.png"},{"id":102209426,"identity":"764d2409-84fb-43cd-8b39-c5656a19e815","added_by":"auto","created_at":"2026-02-09 12:13:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":5067411,"visible":true,"origin":"","legend":"\u003cp\u003eChange trends of ASRs of incidence, prevalence, and YLDs due to SCI for different age groups from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(A) Change trends of age-standardized incidence, prevalence, and YLDs rates for different age groups from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(B) Change trends of incidence, prevalence, and YLDs case number for different age groups from 1990 to 2021.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/bef60be1ac639c5560199905.png"},{"id":102209327,"identity":"46c56759-51ff-4966-9faa-55b6dbc5ac42","added_by":"auto","created_at":"2026-02-09 12:12:53","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":5326187,"visible":true,"origin":"","legend":"\u003cp\u003eChange trends of ASRs of incidence, prevalence, and YLDs due to SCI for different regions by socio-demographic index (SDI) from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(A) Change trends of age-standardized incidence, prevalence, and YLDs rates for different regions by SDI from 1990 to 2021.\u003c/p\u003e\n\u003cp\u003e(B) Change trends of incidence, prevalence, and YLDs case number for different regions by SDI from 1990 to 2021.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/afb8831d3e12b11eefe8ec67.png"},{"id":102209422,"identity":"6e458554-bfce-4019-a9da-e11607661488","added_by":"auto","created_at":"2026-02-09 12:13:14","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1936381,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of health inequalities among patients with SCI in 2021.\u003c/p\u003e\n\u003cp\u003e(A) Health inequality regression curves for the incidence of SCI patients, 1990 and 2021.\u003c/p\u003e\n\u003cp\u003e(B) Concentration curves for the incidence of SCI patients, 1990 and 2021.\u003c/p\u003e\n\u003cp\u003e(C) Health inequality regression curves for the prevalence of SCI patients, 1990 and 2021.\u003c/p\u003e\n\u003cp\u003e(D) Concentration curves for the prevalence of SCI patients, 1990 and 2021.\u003c/p\u003e\n\u003cp\u003e(E) Health inequality regression curves for the YLDs (years of life lived with disabilities) of SCI patients, 1990 and 2021.\u003c/p\u003e\n\u003cp\u003e(F) Concentration curves for the YLDs of SCI patients, 1990 and 2021.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/65dde77e2d2dd74cbeed4509.png"},{"id":102209431,"identity":"0910b9ca-9ac0-4011-9a51-83861e4c1bd6","added_by":"auto","created_at":"2026-02-09 12:13:16","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":3527485,"visible":true,"origin":"","legend":"\u003cp\u003eProportion of the three main causes of SCI grouped by socio-demographic index (SDI) region groups in 1990 and 2021.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/4c6fb7d97cf7e4a1299e6ef7.png"},{"id":102209321,"identity":"a33c72c7-854f-4578-a382-90b15d6f6a8f","added_by":"auto","created_at":"2026-02-09 12:12:52","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":1423425,"visible":true,"origin":"","legend":"\u003cp\u003eCase number of prevalence attributable to six different causes of SCI among different regions in 2021.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/9486eaaaf59fa3f6bff963f5.png"},{"id":102209320,"identity":"7399f95d-0311-45b2-976a-967a68222dd4","added_by":"auto","created_at":"2026-02-09 12:12:51","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":2626525,"visible":true,"origin":"","legend":"\u003cp\u003eCase number of incidenceattributable to six different causes of SCI among different regions in 2021.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/54dfe0fd69f877e20cfdda32.png"},{"id":105562909,"identity":"def482d8-ace7-4a49-bbc8-f95fcf63960d","added_by":"auto","created_at":"2026-03-27 12:45:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":43650611,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8345634/v1/372895e1-59d1-43ec-8af9-4bebddfd77d4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Trends and Projections of Spinal Cord Injury Burden in China: Insights from the Global Burden of Disease 2023 Study","fulltext":[{"header":"Background","content":"\u003cp\u003eSpinal cord injury (SCI), which is defined as structural and/or functional loss of the spinal cord, is one of the most serious diseases.which may lead to a partial or complete lossof motor, sensory, and autonomic functions below the site of injury (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). SCI has complex pathogenesis, which can be divided into traumatic and non-traumatic causes in general. High-energy extrinsic injuries are the main cause for traumatic SCI,such as automobile accident injuries, assaults between individuals, and high place injuries. On the other hand, the most common causes associated with non-traumatic SCI are tumours, haemangiomas and/or infarcts, spondylopathies,and the possible occurrence of ischaemia/reperfusion damage during surgery or other treatment modalities (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Hence, the heterogeneity of such injuries makes SCI a leading cause of permanent disabilities worldwide,causing substantial and continuing burdens to people, their families, health care providers, and the public in terms of increased costs for health care services,resulted in lower levels of productivity, and long-term care needs (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The global prevalence of SCI has increased over the last few decades.Global burden of SCI increased from 1990 to 2019: prevalence rose 81.5% (95% UI 74.2\u0026ndash;87.1), incidence increase 52.7% (30.3\u0026ndash;69.8) and YLDs rise 65.4% (56.3\u0026ndash;76.0). However,the ASRs showed only minor variations, indicating that the drivers of increased absolute burden include largely population size and aging (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). There are also significant regional differences in the incidence of SCIs that reflect different levels of socioeconomic development,healthcare resources, systems for providing trauma care, and implementation of injuryprevention measures (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEtiology and incidence profiles for SCI differ significantly in many areas of the world (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In the US the annual incidence of SCI has been estimated to be approximately 54 per one million population,representing roughly 18,000 annual cases per year (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The number of people with SCI in China is currently estimated at around 760,000 ,with more than 66,000 new cases per year (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In lower income countries (as defined by IMF), rates range between 0.2 and 13.0 cases per 100,000 people (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Although there is considerable international variation in these statistics, most information on the worldwide epidemiology of SCI has come from developed countries like those of North America,Europe, and Australia, but much less so for large parts of Asia and other low- and middle-income regions (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).This difference is also compounded with other factors such as differences in case definition and methodology of collecting the information etc.(e.g.differences in data collection methods (e.g., hospital-based vs populationbased registries) or other socioeconomic structures that make it difficult to compare findings from one country or region with another (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eChina's position as the world's most populous developing nation highlights many of thesecomplicacies in a striking way. Its rapid industrialization,increased motor vehicle use, and urbanization have led to greater exposures for injurious risks common to developing countries,such as work related injury; fall-related injuries (including those occurring in the context of building or construction); and motor vehicle-related injuries.At the same time, the aging population has become more pronounced with an increasing number of degenerative spine diseases as well as low energy falls,phenomena which are more prevalent in the developed world. Despite estimates that China houses amongst the greatest number of people living with SCI,comprehensive and longitudinal epidemiologic information on the national level is lacking.Most past research has been limited to single hospitals, regions and/or time periods and is based mainly in the hospital:that may not be representative of national burden or variation by region in the country (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo fill this evidence gap, in this study we use data from GBD Study 2023 for generating fine-grained estimations of the prevalence,the prevalence and the YLDs of traumatic SCI in China from 1990 to 2023.In this paper we investigate time trends stratified according to sex and age-group, examine patterns over the length of the study,and discusses the impact of these findings on health policy planning, allocation, and prevention efforts at the population level. Through providing new and comparable burden estimates,our study aims to provide evidence for future health care planning, and guide focused public health interventions that could mitigate the growing burden of SCI in China.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData acquisition and injury definition\u003c/h2\u003e \u003cp\u003eSCI incidence and burden in China were extracted from GBD 2023, which can be downloaded via Global Health Data Exchange (GHDx) online database: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ghdx.healthdata.org/\u003c/span\u003e\u003cspan address=\"http://ghdx.healthdata.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Spinal cord injury was identified with ICD coding (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The SCI cases were further divided into different levels of injury according to International Classification of Diseases Tenth Revision (ICD-10) codes for the spinal cord injury level; cervical SCI (C1-C7 vertebral injury, ICD-10: S14,while injuries that involved segments between T1 and S5 were classified as SCI at a non-cervical level. The last group encompasses thoracic SCI (ICD-10 code: S24.1,denoting injury of the thoracic spinal cord), lumbar SCI (ICD-10 code: S34.1, corresponding to injury of the lumbar spinal cord), and sacral SCI (ICD-10 code: S34.0, corresponding to injury of the sacral spinal cord). We used these definitions consistent with those in the GBD injury hierarchy,thus enabling comparisons between countries for standardized epidemiologic surveillance (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Since this study is based on anonymous,Data used in this study were publicly available through GBD 2023 and therefore did not require additional ethics approval.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDefinition of key measurements\u003c/h3\u003e\n\u003cp\u003eWe examined three main age-standardized measures regarding the burden of SCI, namely the age standardized-prevalence rate (ASPR)the age standardized incidence rate (ASIR), and the age standardized years lived with disability rate (ASYR).The ASPR represents number of persons living with SCI per 100,000 population, extrapolated to the GBD 2023 world standard population;reflects the current burden on survivors, which depends upon injury incidence as well as survivorship after injury (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). ASIR expresses new SCI incidence per 100,000 individuals and it is also age standardized to the GBD 2023 standard population; it indicates the annual risk of acquiring a SCI and can be compared unbiasedly across country and over time (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The ASYR is defined as the number of YLDs by 100,000 people caused by SCI, scaled up for the GBD 2023 global standard population;is calculated by combining the proportion of people in each SCI-related health state and their respective DWs,thus providing an adjusted measure for the level of permanent impairment (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll estimates pertaining to specific causes were derived utilizing DisMod-MR 2.1, a Bayesian meta-regression tool implemented in accordance with the established analytical framework of the BD 2023. DisMod-MR 2.1 integrates diverse epidemiological data sources within a compartmental model that ensures internal consistency among the parameters of incidence, prevalence, remission, and mortality (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). This model provides posterior distributions of all parameters which are used to compute the 95% uncertainty interval (95% UI) as the 2.5- and 97.5-percentile on 1,000 posterior draws. Temporal trend analysis for SCI incidence/prevalence, and YLDs were performed over the period 1990\u0026ndash; 2023,we used the \u0026ldquo;Joinpoint\u0026rdquo; statistical software for R.We calculated APC and AAPC with 95% CIs for estimating if the trend was statistically different than zero (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). We used 95% CIs for estimating if the trend was statistically different than zero, and also estimated a linear regression model of log(ASR) over time to quantify long term trends:We estimated an EAPC: for China and for the global aggregate, we fitted a simple linear regression of ln(ASR) on calendar year (1990\u0026ndash;2023):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{ln}\\text{(}\\text{ASR}\\text{)=}\\text{\u0026alpha;}\\text{+}\\text{\u0026beta;}\\text{\u0026times;}\\text{year}\\text{+ϵ}$$\u003c/div\u003e\u003c/div\u003e,\u003c/p\u003e \u003cp\u003ewhere ln(ASR) is the natural log of the age-standardized rates for incidence and prevalence,or YLD; α is an intercept term representing predicted log-rate at a value of year equal to zero; β represents the slope parameter corresponding to average change per year for the log-rate;and ε is a random error term reflecting unforeseen changes across periods.EAPC was then estimated based on this equation: (eβ\u0026thinsp;\u0026minus;\u0026thinsp;1) \u0026times; 100%, and 95% CI for EAPC were obtained according to standard error of β in the regression model. Due to specific clinical and prognosis impact of lesions at Cervical Level and lower,we further divided the ASIR, ASPR, and ASYR according to the location of the lesion (cervix vs. lower than cervix). To estimate the future burden of SCI in China, we used both a maximum likelihood age\u0026ndash; period\u0026ndash;cohort (APC) model and a Bayesian age\u0026ndash;period\u0026ndash;cohort (BAPC) model to forecast the rates of incidence ,prevalence, and YLDs between 2024\u0026ndash;2040 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). All statistical tests were two-sided, and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered indicative of statistical significance. All analyses were conducted using R version 4.3.3 (R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eIncidence, prevalence and YLD of SCI in China and globally\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo contextualize the burden of SCI in China, we first summarized global trends in incidence, prevalence, and YLDs for SCI from 1990 to 2023. Worldwide, the annual number of new SCI cases increased from 682,567 (95% UI: 528,785\u0026ndash;892,138) in 1990 to 1,010,928 (95% UI: 753,567\u0026ndash;1,425,080) in 2023, representing a cumulative rise of 48.11%. Over the same period, however, the global ASIR fell from 12.88 (95% UI: 9.99\u0026ndash;17.10; Fig. 1A) per 100,000 in 1990 to 12.31 (95% UI: 9.07\u0026ndash;17.32; Fig. 1B) per 100,000 in 2023, corresponding to an EAPC of \u0026minus;0.02 (95% CI: \u0026minus;0.19 to 0.16). The global prevalence of SCI also rose substantially, from 16,808,304 (95% UI: 15,314,183\u0026ndash;18,722,387) cases in 1990 to 27,538,533 (95% UI: 24,685,026\u0026ndash;30,673,727) cases in 2023, an overall increase of 63.84%. In contrast, the age-standardized prevalence rate (ASPR) declined from 341.82 (95% UI: 312.83\u0026ndash;377.46; Fig. 1C) per 100,000 in 1990 to 318.28 (95% UI: 285.01\u0026ndash;355.51; Fig. 1D) per 100,000 in 2023, with an EAPC of \u0026minus;0.07 (95% CI: \u0026minus;0.24 to 0.10). Similarly, YLDs due to SCI increased from 5,502,832 (95% UI: 3,927,191\u0026ndash;7,106,072) in 1990 to 8,024,507 (95% UI: 5,827,305\u0026ndash;10,483,103) in 2023, a cumulative rise of 45.83%. Yet the age-standardized YLD rate (ASYR) decreased from 110.60 (95% UI: 79.26\u0026ndash;142.31; Fig. 1E) per 100,000 in 1990 to 93.25 (95% UI: 67.85\u0026ndash;121.94; Fig. 1F) per 100,000 in 2023, with an EAPC of \u0026minus;0.40 (95% CI: \u0026minus;0.56 to \u0026minus;0.24).\u003c/p\u003e\n\u003cp\u003eThe number of new SCI cases rose from 162,065 (95% UI: 116,923\u0026ndash;223,108) in 1990 to 232,656 (95% UI: 161,638\u0026ndash;351,309) in 2023, representing a cumulative increase of 43.56% in China. Over the same period, the ASIR increased from 13.56 (95% UI: 9.85\u0026ndash;18.79) per 100,000 in 1990 to 15.96 (95% UI: 11.16\u0026ndash;23.23) per 100,000 in 2023, with an EAPC of 1.11 (95% CI: 0.72\u0026ndash;1.51). The prevalence of SCI in China nearly doubled, from 4,510,064 cases (95% UI: 4,027,350\u0026ndash;5,064,110) in 1990 to 8,335,904 cases (95% UI: 7,446,638\u0026ndash;9,283,348) in 2023, an 84.83% increase. Correspondingly, the age-standardized prevalence rate (ASPR) rose from 387.30 (95% UI: 348.48\u0026ndash;432.67) per 100,000 in 1990 to 466.07 (95% UI: 414.71\u0026ndash;520.65) per 100,000 in 2023, with an EAPC of 1.23 (95% CI: 0.78\u0026ndash;1.69). For YLDs, China recorded 1,554,959 cases (95% UI: 1,062,866\u0026ndash;1,989,468) in 1990 and 2,274,166 cases (95% UI: 1,545,414\u0026ndash;3,005,306) in 2023, an increase of 46.25%. The age-standardized YLD rate (ASYR) was 128.93 (95% UI: 86.51\u0026ndash;172.09) per 100,000 in 1990 and 132.34 (95% UI: 90.89\u0026ndash;168.17) per 100,000 in 2023, yielding an EAPC of 0.48 (95% CI: 0.05\u0026ndash;0.91). Unlike the global pattern, where\u0026nbsp;ASRs\u0026nbsp;for SCI have generally declined, China experienced clear increases in ASIR, ASPR, and ASYR between 1990 and 2023. China\u0026rsquo;s share of global incident SCI cases remained consistently high, accounting for 23.7% of worldwide cases in 1990 and 23.0% in 2023. By 2023, all three age-standardized indicators (ASIR, ASPR, and ASYR) in China exceeded the corresponding global averages. This divergence may reflect a lag in the implementation and effectiveness of comprehensive injury prevention and control strategies relative to the rapidly intensifying risks associated with accelerated socioeconomic development, urbanization, motorization, and population aging.\u003c/p\u003e\n\u003cp\u003eFig. 2 presents sex-specific trends in the all-age numbers of cases and the age-standardized incidence (ASIR), prevalence (ASPR), and YLD (ASYR) rates for SCI in China from 1990 to 2023. Overall, the total case counts and ASRs for incidence (Fig. 2A), prevalence (Fig. 2B), and YLDs (Fig. 2C) remained relatively stable up to around 2005. Thereafter, they increased markedly, reaching a peak around 2015, and then declined, with the lowest levels observed in 2020, followed by a modest upturn thereafter. Throughout the entire study period and across all indicators, the burden of SCI was consistently and substantially higher in males than in females in China(Table 1-3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e Incidence Burden of Acute Glomerulonephritis in G20 and China, 1990-2023\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003elocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eNum_1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003eASR_1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eNum_2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003eASR_2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eEAPC_CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBoth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e162065 (116923 to 223108)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e13.56 (9.85 to 18.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e232656 (161638 to 351309)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e15.96 (11.16 to 23.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e1.11 (0.72 to 1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e682567 (528785 to 892138)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e12.88 (9.99 to 17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1010928 (753567 to 1425080)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e12.31 (9.07 to 17.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e-0.02 (-0.19 to 0.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e51916 (35094 to 75485)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e9.22 (6.24 to 13.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e75722 (48213 to 124232)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e10.16 (6.47 to 15.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.86 (0.46 to 1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e233763 (168606 to 332542)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e8.93 (6.52 to 12.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e392166 (268112 to 614853)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e9.48 (6.42 to 14.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.23 (0.02 to 0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e110149 (82431 to 147801)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e17.59 (13.23 to 23.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e156934 (113394 to 227870)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e21.26 (15.2 to 29.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e1.22 (0.83 to 1.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e448804 (354794 to 571964)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e16.74 (13.28 to 21.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e618761 (471470 to 825503)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e15.09 (11.43 to 20.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e-0.14 (-0.31 to 0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;2\u003c/strong\u003e Prevalence Burden of Acute Glomerulonephritis in G20 and China, 1990-2023\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003elocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eNum_1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003eASR_1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eNum_2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003eASR_2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eEAPC_CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBoth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e4510064 (4027350 to 5064110)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e387.3 (348.48 to 432.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e8335904 (7446638 to 9283348)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e466.07 (414.71 to 520.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e1.23 (0.78 to 1.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e16808304 (15314183 to 18722387)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e341.82 (312.83 to 377.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e27538533 (24685026 to 30673727)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e318.28 (285.01 to 355.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e-0.07 (-0.24 to 0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1568936 (1374193 to 1785672)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e280.36 (247.5 to 316.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e2846549 (2503881 to 3235336)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e318.66 (279.75 to 364.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.99 (0.55 to 1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e6075929 (5467963 to 6867275)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e247.29 (224.09 to 277.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e10405433 (9230229 to 11988017)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e237.74 (209.78 to 278.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e-0.01 (-0.17 to 0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e2941128 (2624858 to 3273697)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e486.46 (434.49 to 540.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e5489355 (4890956 to 6152073)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e605.74 (540.21 to 679.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e1.38 (0.91 to 1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e10732376 (9790834 to 11791041)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e434.79 (398.86 to 473.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e17133101 (15536706 to 18950169)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e399.01 (361.76 to 441.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e-0.08 (-0.26 to 0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e YLDs Burden of Acute Glomerulonephritis in G20 and China, 1990-2023\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003elocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eNum_1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003eASR_1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eNum_2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003eASR_2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eEAPC_CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBoth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1554959 (1062866 to 1989468)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e132.34 (90.89 to 168.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e2274166 (1545414 to 3005306)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e128.93 (86.51 to 172.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.48 (0.05 to 0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e5502832 (3927191 to 7106072)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e110.6 (79.26 to 142.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e8024507 (5827305 to 10483103)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e93.25 (67.85 to 121.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e-0.4 (-0.56 to -0.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e527769 (355396 to 677814)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e93.5 (63.32 to 120.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e747932 (501738 to 991874)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e85.05 (56.6 to 113.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.2 (-0.21 to 0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1928537 (1344274 to 2512824)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e77.7 (54.38 to 100.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e2948377 (2152790 to 3931105)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e68.01 (49.77 to 90.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e-0.33 (-0.48 to -0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1027190 (697564 to 1306616)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e168.37 (114.6 to 214.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1526234 (1035898 to 2014336)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e170.41 (115.22 to 227.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.64 (0.2 to 1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e3574294 (2571417 to 4632419)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e142.96 (103.26 to 184.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e5076130 (3643149 to 6585509)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e118.5 (85.16 to 154.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e-0.43 (-0.59 to -0.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe disease burden of SCI by year, sex, and age in China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify demographic groups at greatest risk, we assessed how the burden of SCI varied by sex and age in China, using both absolute case counts and ASRs. Stratified analyses showed a broadly increasing SCI burden among both males and females and across age groups from 1990 to 2023, with men consistently experiencing a higher burden than women throughout the study period. In 1990, the male-to-female ratios for ASIR, ASPR, and ASYR were 1.91:1, 1.74:1, and 1.80:1, respectively. By 2023, these ratios had risen to 2.09:1, 1.90:1, and 2.00:1, respectively (Fig. 3A). A similar pattern was observed for absolute case numbers. In 1990, the male-to-female ratios for incident cases, prevalent cases, and YLDs were 2.12:1, 1.87:1, and 1.95:1, respectively, whereas in 2023 these ratios were 2.07:1, 1.93:1, and 2.04:1, respectively (Fig. 3B). Taken together, these findings indicate that, over time, the sex gap in SCI burden has generally widened, with males increasingly bearing a disproportionate share of both the incidence and long-term disability associated with SCI in China.\u003c/p\u003e\n\u003cp\u003eIn 1990, the age-specific incidence rate (ASIR) of SCI fluctuated across age groups and reached its highest level in the 90\u0026ndash;94-year group. By contrast, in 2023 the ASIR initially increased with age, peaking in the 25\u0026ndash;29-year group, and then declined; however, after the 65\u0026ndash;69-year group, the ASIR again rose steadily with age up to 90\u0026ndash;94 years (Fig. 4A). Regarding case numbers, the highest number of incident SCI cases in 1990 occurred in the 20\u0026ndash;24-year group, whereas in 2023 the peak shifted to the 35\u0026ndash;39-year group (Fig. 4B). The age-specific patterns of prevalence and YLDs\u0026mdash;both in terms of case counts and ASRs\u0026mdash;displayed broadly similar trajectories to those observed for incidence over the same period (Fig. 4A\u0026ndash;B). Substantial improvements in SCI burden were evident in many age groups, with the most pronounced reductions seen among children and adolescents between 1990 and 2023. Nevertheless, a clear shift in the age distribution of prevalence, YLDs, and their corresponding ASRs emerged when comparing 1990 with 2023. By 2023, the peak age-standardized prevalence rate (ASPR) and age-standardized YLD rate (ASYR) occurred in the 65\u0026ndash;69- and 50\u0026ndash;54-year groups, respectively, and ASYR values after age 50\u0026ndash;54 were higher in 2023 than in 1990. Although age-specific ASPR and ASYR consistently displayed a single-peaked, arch-shaped pattern across age groups, the apex of this curve\u0026mdash;indicating the age group with the greatest burden\u0026mdash;shifted markedly toward older ages in 2023, suggesting progressive aging of the SCI-affected population.\u003c/p\u003e\n\u003cp\u003eThe temporal evolution of SCI burden across age groups in China was portrayed using stacked area plots (Fig. 4C\u0026ndash;D). These visualizations reveal that, although year-to-year fluctuations were present, both the ASRs ( Fig. 4C) and the absolute numbers of incident cases, prevalent cases, and YLDs (Fig. 4D) generally trended upward from 1990 to 2023. At the same time, the center of gravity of the disease burden progressively shifted toward older age groups. This indicates that individuals living with SCI in China are, on average, becoming older, and that an increasing share of new injuries and long-term disability now occurs in older adults rather than in younger populations. The progressive rightward movement of the incidence, prevalence, and YLD peaks closely parallels China\u0026rsquo;s rapid population aging. In addition, improvements in acute care and subsequent management have enhanced survival after SCI, lengthening disease duration and thereby enlarging the pool of elderly survivors, which in turn inflates both prevalence and YLD counts in older age strata. Age-specific distribution curves for incidence, prevalence, and YLDs further delineate the pattern of SCI burden by lesion location (Fig. 5A\u0026ndash;C). Across the study period, both cervical SCI and SCI below the neck were disproportionately clustered in older age groups. The proportion of incident SCI cases rose steadily with increasing age (Fig. 5A), while the prevalence (Fig. 5B) and YLD profiles (Fig. 5C) highlighted a particularly concentrated disability burden among middle-aged and older adults. This burden became clearly apparent from around 40\u0026ndash;44 years of age and continued to intensify into later life, with cervical SCI contributing most prominently to the highest levels of disability. These findings point to a dual pattern: not only are cervical injuries increasingly frequent and persistent in older individuals, but they also generate a substantial and enduring disability impact. Taken together, the results indicate a pronounced aging-related transformation in the epidemiology of SCI in China, with older adults\u0026mdash;especially those with cervical lesions\u0026mdash;emerging as the principal drivers of SCI-related health loss.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGender differences in SCI burden by age and injury site in China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor cervical SCI, men consistently exhibited higher incidence rates than women in almost all age groups. In 2023, the largest number of incident cervical SCI cases among males occurred in the 35\u0026ndash;39-year group, whereas in females the incident case count peaked in the 55\u0026ndash;59-year group. Up to ages 75\u0026ndash;79 years, men had more new cervical SCI cases than women; however, from age 80 onwards, incident case counts became higher in women. With respect to age-specific incidence rates in 2023, rates in women rose steadily with advancing age. In contrast, the incidence rate in men increased initially, reaching a maximum in the 25\u0026ndash;29-year group, and then declined, before rising again after ages 65\u0026ndash;69 years and continuing to climb through the 90\u0026ndash;94-year group (Fig. 6A).Patterns for prevalence of cervical SCI were broadly similar. In 2023, the highest number of prevalent cervical SCI cases in men was observed in the 50\u0026ndash;54-year group, whereas in women the peak case count again occurred in the 55\u0026ndash;59-year group. Up to ages 75\u0026ndash;79 years, men had more prevalent cervical SCI cases than women, but among those aged 80 years and older, women accounted for more cases. Age-specific prevalence rates for cervical SCI in 2023 increased progressively with age in both sexes, peaking at ages 50\u0026ndash;54 years in men and 70\u0026ndash;74 years in women, and then gradually declined thereafter. Beyond the 85\u0026ndash;89-year group, the prevalence rate curves for men and women were nearly superimposed, indicating convergence of cervical SCI prevalence at the oldest ages (Fig. 6B).A comparable pattern emerged for YLDs due to cervical SCI. In 2023, the number of YLDs peaked among men in the 50\u0026ndash;54-year age group and among women in the 55\u0026ndash;59-year group. Up to ages 75\u0026ndash;79 years, YLD counts from cervical SCI were consistently higher in men, whereas from age 80 years onward, women experienced more disability. Age-specific YLD rates in 2023 rose with age in both sexes, reaching their maximum in the 50\u0026ndash;54-year group for men and the 70\u0026ndash;74-year group for women, followed by a gradual decline at older ages. After 85\u0026ndash;89 years, the YLD rate curves for men and women overlapped closely, again suggesting convergence at the oldest ages (Fig. 6C). For SCI below the neck, sex- and age-specific patterns showed both parallels and contrasts with cervical injuries. In 2023, the largest number of incident cases among men was observed in the 35\u0026ndash;39-year group, while among women incident case counts peaked at 55\u0026ndash;59 years. Men had more incident cases than women up to the 65\u0026ndash;69-year group; from age 70 years onwards, incident case counts were higher in women. In female patients, the incidence rate of SCI below the neck rose monotonically with age in 2023 and exceeded the male rate after the 70\u0026ndash;74-year group. Among men, the incidence rate initially increased with age and peaked at 25\u0026ndash;29 years, then decreased, but began to rise again after 70\u0026ndash;74 years and continued increasing through 90\u0026ndash;94 years (Fig. 7A). Regarding prevalence of SCI below the neck, the maximum number of prevalent cases for both men and women occurred in the 55\u0026ndash;59-year age group in 2023. Men had more prevalent cases than women up to ages 75\u0026ndash;79 years; however, from age 80 years and above, women comprised the majority of prevalent cases. In 2023, age-specific prevalence rates in both sexes rose with age, peaking at 50\u0026ndash;54 years in men and 70\u0026ndash;74 years in women, and then progressively declined thereafter. After the 85\u0026ndash;89-year group, the prevalence rate in women began to surpass that in men for SCI below the neck (Fig. 7B). The YLD patterns for SCI below the neck also reflected a pronounced age and sex gradient. In 2023, the highest YLD case numbers among men occurred in the 50\u0026ndash;54-year group, and among women in the 55\u0026ndash;59-year group. Up to ages 75\u0026ndash;79 years, men bore a larger YLD burden from SCI below the neck, whereas beyond age 80, YLD case counts were higher in women. Age-specific YLD rates in 2023 increased steadily with age in both sexes, peaking at 55\u0026ndash;59 years in men and 70\u0026ndash;74 years in women, and then declined at older ages. From the 85\u0026ndash;89-year group onward, the YLD rate for women with SCI below the neck exceeded that of men (Fig. 7C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJoinpoint analysis of SCI burden in China\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe applied Joinpoint regression to characterize temporal changes in the ASIR, prevalence rate (ASPR), and YLD rate (ASYR) of SCI in China. For ASIR, the trend was segmented into several distinct phases (Fig. 8A). From 1990 to 1994, ASIR showed a modest but statistically significant decline (APC=\u0026minus;0.98, p\u0026lt;0.05). This was followed by a mild, non-significant upslope between 1994 and 2004 (APC=0.53, p=0.27). A pronounced acceleration in incidence emerged after 2004: ASIR increased rapidly from 2004 to 2008 (APC=7.34, p\u0026lt;0.05) and continued to rise, though at a slower pace, from 2008 to 2014 (APC=3.02, p\u0026lt;0.05). This growth phase was followed by a sharp downturn between 2014 and 2019 (APC=\u0026minus;7.09, p\u0026lt;0.05). Subsequently, from 2019 to 2023, ASIR again turned upward, with a sustained and significant increase over this most recent period (APC=2.65, p\u0026lt;0.05). For ASPR, a somewhat different pattern was observed (Fig. 8B; Supplementary Table S3). Prevalence initially declined slightly from 1990 to 1995 (APC=\u0026minus;0.74, p\u0026lt;0.05)(APC=\u0026minus;0.74, p\u0026lt;0.05). Thereafter, ASPR entered a prolonged growth phase extending from 1995 to 2015, with particularly notable increases from 2004 to 2009 (APC=6.87, p\u0026lt;0.05) and from 2009 to 2015 (APC=2.11, p\u0026lt;0.05). This upward trajectory reversed between 2015 and 2019, when ASPR experienced a marked drop (APC=\u0026minus;9.27, p\u0026lt;0.05). From 2019 to 2023, however, prevalence resumed an increasing trend (APC=3.21, p\u0026lt;0.05). For ASYR, China exhibited an early period of decline followed by a later escalation (Fig. 8C). Between 1990 and 1996, the age-standardized YLD rate decreased significantly (APC=\u0026minus;0.93, p\u0026lt;0.05). From 1996 to 2003, this decline flattened and was no longer statistically significant (APC=\u0026minus;0.09, p=0.67). Beginning in 2003, ASYR entered a sustained growth phase: it rose rapidly from 2003 to 2010 (APC=4.74, p\u0026lt;0.05) and continued to increase at a more moderate rate from 2010 to 2014 (APC=1.99, p\u0026lt;0.05). A significant downturn followed between 2014 and 2019 (APC=\u0026minus;8.84, p\u0026lt;0.05). In the most recent period, 2019\u0026ndash;2023, ASYR once again showed a consistent and statistically significant increase (APC=3.07, p\u0026lt;0.05). Overall, the Joinpoint analysis highlights a pattern of early stability or modest decline, followed by a mid-2000s surge in incidence, prevalence, and disability, a pronounced drop around the mid‑2010s, and a renewed increase in SCI burden in the years after 2019.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAge\u0026ndash;period\u0026ndash;cohort analysis of SCI incidence in China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo disentangle the contributions of age, calendar period, and birth cohort to SCI incidence in China, we conducted an age\u0026ndash;period\u0026ndash;cohort (APC) analysis for the period 1990\u0026ndash;2023. A global test indicated that variation in SCI incidence was significantly associated with age, period, and cohort effects in the total population (p\u0026lt;0.05). Local drift estimates showed that the largest annual percentage increases in incidence were concentrated in the 70\u0026ndash;74‑year age group, suggesting a particularly rapid rise in SCI risk among older adults (Fig. 9A). The age effect (Fig. 9B) demonstrated a strong positive association between age and SCI incidence. Incidence rates rose gradually with age and then climbed sharply after about 70 years, reaching their highest levels in the oldest age groups, before showing only a slight decline at extreme old age. This confirms that advanced age is a major determinant of SCI risk in China. The period effect (Fig. 9C) revealed temporal fluctuations in SCI incidence that were independent of age and birth cohort. Using 2004\u0026ndash;2008 as the reference period (RR=1), period-specific rate ratios (RRs) were consistently below 1 during 1989\u0026ndash;2003, indicating lower incidence in those earlier years. By contrast, all RRs for 2009\u0026ndash;2023 exceeded 1, reflecting a higher period‑related risk in more recent years. The period curve showed an overall rise, followed by a downturn after the 2014\u0026ndash;2018 interval, consistent with the Joinpoint findings of a peak around the mid‑2010s and subsequent decline. The cohort effect (Fig. 9D) highlighted generational differences. Taking the 1960 birth cohort as the reference (RR=1), RRs for cohorts born between 1895 and 1955 were uniformly below 1, indicating a lower lifetime risk of SCI among earlier-born generations. In contrast, cohorts born from 1965 to 2020 exhibited RRs greater than 1, signifying higher SCI incidence among more recent birth cohorts. The cohort curve increased up to around the 1960\u0026ndash;1965 cohorts and then progressively declined after approximately the 2010 birth cohort, suggesting that the elevated risk is particularly pronounced in cohorts born after the 1960s but does not continue to rise indefinitely in the youngest cohorts. Additional descriptive APC plots further clarified these patterns: Age-specific rates by period (Fig. 9E) showed that, within each calendar period, SCI incidence rose with age, peaked around 85\u0026ndash;90 years, and then decreased slightly in the very oldest groups, reinforcing the dominant influence of aging on SCI risk. Cohort-specific rates by age group (Fig. 9F) indicated that, for almost all age groups, more recent birth cohorts experienced higher incidence rates than earlier cohorts. This points to a shift of SCI burden toward generations born after the 1960s. Period-specific rates by age group (Fig. 9G) showed increasing incidence over successive calendar periods among those aged 85 years and older, with later years associated with greater SCI burden in the oldest age strata. Taken together, the APC analysis suggests that the rising SCI incidence in China is driven by three intertwined factors: population aging (strong age effect), an unfavorable temporal environment in recent decades (period effect with RRs \u0026gt; 1 after 2009), and higher underlying risk among post‑1960 birth cohorts (cohort effect), with the steepest relative increases observed in older adults, especially those aged 70 years and above.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDecomposition analysis revealed drivers of change in SCI burden in China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor\u0026nbsp;SCI incidence, the net increase of 8,443,044 cases over the study period was overwhelmingly attributable to demographic dynamics (Fig. 10A). Population growth was the dominant driver, accounting for an additional 8,035,219 incident cases (95.17% of the total change). Population aging further amplified incidence, contributing 2,996,310 extra cases (35.49%). These upward demographic pressures were substantially offset by favorable epidemiological shifts: improvements in risk profiles, prevention, and/or clinical management collectively reduced the expected number of incident cases by 2,588,485 (\u0026minus;30.66%), partially counterbalancing the increase that would have occurred in the absence of such changes. A\u0026nbsp;similar decomposition pattern\u0026nbsp;was observed for\u0026nbsp;SCI prevalence\u0026nbsp;(Fig. 10B). The overall increase of 8,443,044 prevalent cases was again mainly driven by population growth, which contributed 8,035,219 cases (95.17%). Population aging added a further 2,996,310 cases (35.49%) to the prevalence pool. In contrast, epidemiological changes exerted a sizable mitigating effect, reducing the expected prevalence by 2,588,485 cases (\u0026minus;30.66%) relative to a scenario with unchanged rates.\u003c/p\u003e\n\u003cp\u003eThe YLD burden due to SCI followed the same structure of contributing factors (Fig. 10C). The increase of 8,443,044 YLDs was primarily the result of population expansion, with population growth contributing 8,035,219 additional YLDs (95.17%). Aging of the population further increased YLDs by 2,996,310 (35.49%). At the same time, favorable epidemiological developments\u0026mdash;reflected in lower rates or reduced severity of disability\u0026mdash;offset this trend by 2,588,485 YLDs (\u0026minus;30.66%), indicating a substantial protective influence. Marked sex differences emerged across all three burden indicators. The impact of population aging was more pronounced in males than in females, contributing 1,911,605 additional cases (37.55%) versus 1,080,054 cases (32.38%), respectively, for incidence, prevalence, and YLDs combined. Likewise, the protective effect of epidemiological improvements was stronger in men: epidemiological changes reduced the expected burden by 1,869,843 cases (\u0026minus;36.73%) in males, compared with 706,393 cases (\u0026minus;21.17%) in females. Although population growth remained the leading driver for both sexes, its relative contribution was slightly higher in men (99.18%) than in women (88.80%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePredictive analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor\u0026nbsp;incidence, the ASIR is predicted to follow a sustained downward trajectory (Fig. 11A). Specifically, ASIR is estimated to decline from 16.24 (95% UI: 16.21\u0026ndash;16.28) per 100,000 population in 2023 to 14.28 (95% UI: 12.78\u0026ndash;15.79) per 100,000 in 2038, corresponding to an approximate 12.1% reduction over the 15‑year projection horizon. Although the central tendency indicates a steady decrease, the uncertainty intervals become progressively wider in the later years, particularly after 2030, reflecting increasing forecasting uncertainty as the projection extends further from the observation period. The\u0026nbsp;age-standardized prevalence rate (ASPR)\u0026nbsp;showed a markedly different pattern (Fig. 11B). ASPR is projected to remain at a relatively high level overall, increasing slightly from 458.98 (95% UI: 458.87\u0026ndash;459.10) per 100,000 in 2023 to 458.96 (95% UI: 398.03\u0026ndash;519.90) per 100,000 in 2038. Despite short‑term fluctuations during the intermediate years, the forecast suggests that prevalence will reach a peak around 2024\u0026ndash;2025 and then gradually decline, stabilizing by the end of the projection window. Thus, SCI prevalence is expected to remain substantial, but without a sustained upward or downward long‑term trend in age‑standardized terms.\u003c/p\u003e\n\u003cp\u003eFor YLDs, the age-standardized YLD rate (ASYR) is forecast to decrease, broadly mirroring the pattern observed for incidence (Fig. 11C). ASYR is projected to fall from 126.84 (95% UI: 126.78\u0026ndash;126.91) per 100,000 in 2023 to 114.64 (95% UI: 99.63\u0026ndash;129.66) per 100,000 in 2038, representing a 9.6% reduction over the projection period. As with ASIR, the prediction intervals widen towards 2038, indicating greater uncertainty in long‑term estimates, but the central forecast consistently points to a favorable decline. Taken together, these projections indicate that: Incidence and YLDs are likely to follow generally improving trajectories, with moderate reductions in ASRs through 2038. Prevalence will remain high and largely stable in age-standardized terms, peaking in the mid‑2020s and then slowly decreasing. Despite these favorable trends in ASRs, the absolute burden of SCI in China is expected to persist, underscoring the continued need for prevention, acute care optimization, and long‑term rehabilitation services.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study offered a comprehensive characterization of how the SCI burden in China has evolved from 1990 to 2023, framed within the context of global trends. A striking pattern emerged: during a period when global age-standardized incidence, prevalence, and YLD rates for SCI declined (19), China moved in the opposite direction, with all three indicators rising markedly (4, 6, 20). This divergence points to a multifactorial dynamic in China, where demographic aging, rapid socioeconomic transition, and the timing and intensity of health policy implementation intersect. The combination of sharply increasing absolute case counts and rising ASRs indicates that SCI has become a growing and progressively more serious public health threat in China—one that has not been fully contained by existing preventive and control measures.\u003c/p\u003e\n\u003cp\u003eThe downward trend in global ASRs likely reflects the long-term impact of sustained investment in road traffic legislation, improved occupational safety regulations, and the development of sophisticated trauma systems in many high-income settings \u0026nbsp;(21). By contrast, China’s rising SCI rates unfolded alongside an era of unprecedented economic expansion and accelerated urbanization. While these processes have significantly improved living standards, they also brought rapid growth in construction, manufacturing, and motorized transport, thereby amplifying exposure to high-risk occupational and environmental conditions \u0026nbsp;(8, 22). Our Joinpoint regression identified a particularly steep rise in ASIR between 2004 and 2014, a time that coincides with large-scale infrastructure projects and explosive growth in vehicle ownership. The subsequent decline after 2014 may reflect the gradual consolidation and stricter enforcement of national measures such as the Road Traffic Safety Law and more stringent workplace safety regulations (23). Nevertheless, the renewed upturn after 2019 suggests that, although these policies have had a beneficial impact, they have not fully neutralized the risks associated with an aging population and ongoing hazardous exposures in certain industries..\u003c/p\u003e\n\u003cp\u003eAnother salient finding was the\u0026nbsp;increasing gender gap\u0026nbsp;in SCI burden. The male-to-female ASIR ratio rose from 1.91:1 in 1990 to 2.09:1 in 2023, indicating that men have not shared equally in any recent gains. This widening disparity is consistent with the gendered distribution of both occupational and behavioral risk factors. Men continue to dominate employment in high-risk sectors such as construction, transport, and heavy industry, where falls from height, road traffic crashes, and machinery-related injuries are frequent(24, 25). The slower reduction—or even persistence—of SCI burden among men suggests that improvements in occupational safety have lagged behind the scale and intensity of industrial activity. In addition, behaviors disproportionately observed among men, including speeding, driving under the influence of alcohol, and other forms of risk-taking, further amplify their vulnerability (26). Together, these patterns underscore the need for more rigorous and better enforced occupational safety frameworks, as well as targeted, gender-sensitive behavioral interventions focused on male workers and road users.\u003c/p\u003e\n\u003cp\u003eThe evolving age pattern of SCI in China highlights a\u0026nbsp;dual challenge encompassing both working-age and older adults. Over the study period, the peak of incident cases shifted from the very old in 1990 to the middle-aged group (35–39 years) in 2023, suggesting that occupational and work-related injuries remain a predominant driver of new cases in the core labor force. At the same time, we observed a substantial increase in prevalence and YLD rates among individuals aged 50 years and older. This pattern is closely tied to population aging and rising life expectancy, which have expanded the number of people living for long periods with SCI-related disability (27). Older adults are particularly susceptible to low-energy falls, driven by conditions such as osteoporosis, degenerative spinal disease, and impaired balance (5). When these events involve the cervical spine, they often result in profound functional impairment—a pattern consistent with our findings of higher ASIR and ASYR for cervical lesions compared with injuries at lower spinal levels (28). These demographic and clinical shifts argue for a strategic reorientation of SCI prevention and care: beyond traditional injury control, there is a pressing need to integrate geriatric-focused fall prevention, comprehensive management of degenerative spinal conditions, and age-appropriate rehabilitation into national strategies for SCI control.\u003c/p\u003e\n\u003cp\u003eThe decomposition analysis added an important layer of nuance to our understanding of why the SCI burden continues to rise in China. It showed that\u0026nbsp;demographic dynamics—in particular, rapid population growth and population aging—were the main forces driving the expansion in absolute case numbers. At the same time, the analysis demonstrated that\u0026nbsp;favorable epidemiological shifts, plausibly linked to expanded prevention efforts and improvements in clinical care, acted in the opposite direction and\u0026nbsp;substantially dampened\u0026nbsp;the increase that would otherwise have occurred. The observation that this protective effect was\u0026nbsp;more pronounced in males\u0026nbsp;is particularly informative: it suggests that safety measures, when implemented, can have a tangible impact on high‑risk groups, but that their reach and intensity remain\u0026nbsp;uneven across populations and settings (10). From a policy standpoint, these findings draw a clear distinction between\u0026nbsp;largely non‑modifiable demographic trends\u0026nbsp;and\u0026nbsp;potentially modifiable risk and care environments. While China cannot reverse population aging or past population growth, there is considerable room to reduce the future SCI burden by scaling up\u0026nbsp;targeted, high‑impact public health interventions. Experience from high‑SDI settings, where lower ASIRs, ASPRs, and ASYRs have been achieved through\u0026nbsp;coordinated packages\u0026nbsp;of road safety legislation, fall prevention in older adults, and stringent occupational health regulations, offers a valuable template for China’s next phase of SCI control (29, 30).Adapting and rigorously implementing such integrated approaches—while paying close attention to sex‑ and age‑specific vulnerabilities—will be critical to counterbalancing the demographic headwinds identified in this study.\u003c/p\u003e\n\u003cp\u003eThis study has several important limitations that should be considered when interpreting the findings.\u0026nbsp;First, all estimates were derived from the GBD modeling framework, which synthesizes heterogeneous data sources. Incomplete case ascertainment—especially for\u0026nbsp;non‑traumatic SCI, which is often underdiagnosed or poorly recorded—may lead to underestimation of the true burden.\u0026nbsp;Second, we relied on the\u0026nbsp;GBD global standard population\u0026nbsp;for age standardization, which may not perfectly reflect China’s rapidly aging population structure. This mismatch could introduce bias in ASPR and ASYR estimates, particularly when making comparisons over time or with other countries. Third, the absence of\u0026nbsp;provincial‑level data\u0026nbsp;meant that we were unable to characterize subnational heterogeneity in SCI burden within China. Given known disparities in socioeconomic development, healthcare access, and injury risk across regions, this represents a notable gap and a priority for future work.\u0026nbsp;Finally, the age–period–cohort analysis was conducted at the aggregate level and is therefore susceptible to\u0026nbsp;ecological fallacy; associations observed at the population level cannot be directly extrapolated to individual risk. Causal inferences regarding specific age, period, or cohort mechanisms should thus be made with caution and ideally complemented by individual‑level, longitudinal studies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed that, in sharp contrast to global declines, SCI burden in China is rising—especially among men and older adults—driven by occupational hazards, road traffic injuries, and age‑related falls. These findings call for a coordinated national strategy that couples stricter road and workplace safety enforcement with strengthened geriatric care, fall prevention, and data‑driven, targeted interventions for high‑risk groups.\u003c/p\u003e"},{"header":"Declarations","content":"\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\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are derived from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023, coordinated by the Institute for Health Metrics and Evaluation (IHME). All data on the incidence, prevalence, and years lived with disability (YLDs) for spinal cord injury (SCI) in China and globally are publicly available through the Global Health Data Exchange (GHDx) query tool (http://ghdx.healthdata.org/). These summary data are accessible for research purposes under the IHME's standard terms of use. The specific modeling and statistical analyses conducted in this study were based on the GBD 2023 analytical framework, utilizing tools such as DisMod-MR 2.1. The custom R code used for data processing, Joinpoint regression, age-period-cohort (APC) analysis, decomposition analysis, and generating the figures is not part of the publicly available GBD resources. However, these analytical scripts are available from the corresponding author on reasonable request for the purpose of verifying or replicating the study's findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXXX contributed to the conceptualization, data curation, formal analysis, and drafting of the manuscript.\u0026nbsp;XXX performed the statistical analysis and visualization of results.\u0026nbsp;XXX assisted in data interpretation and contributed to the discussion and revision of the manuscript.\u0026nbsp;XXX participated in methodological design and provided critical feedback during manuscript editing.\u0026nbsp;XXX supervised the study, guided the research methodology, and critically revised the final manuscript for important intellectual content.\u0026nbsp;All authors have read and approved the final version of the manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHu X, Xu W, Ren Y, Wang Z, He X, Huang R, et al. 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Lancet. 2020;396(10258):1160-203.\u003c/li\u003e\n\u003cli\u003eFerro S, Cecconi L, Bonavita J, Pagliacci MC, Biggeri A, Franceschini M, et al. Incidence of traumatic spinal cord injury in Italy during 2013-2014: a population-based study. Spinal Cord. 2017;55(12):1103-7.\u003c/li\u003e\n\u003cli\u003ePeden AE, Cullen P, Francis KL, Moeller H, Peden MM, Ye PP, et al. Adolescent transport and unintentional injuries: a systematic analysis using the Global Burden of Disease Study 2019. Lancet Public Health. 2022;7(8):E657-E69.\u003c/li\u003e\n\u003cli\u003eLiu W, Samuhaer A, Lin KP, Li MC, Zang CY, Liu HW, et al. Global epidemiological trends and burden of cervical and subcervical spinal cord injuries, 1990-2021: a multidimensional analysis using global burden of disease data. Journal of Orthopaedic Surgery and Research. 2025;20(1).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"spinal cord injury, projections, Global Burden of Diseases, Injuries, and Risk Factors Study 2023","lastPublishedDoi":"10.21203/rs.3.rs-8345634/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8345634/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTraumatic spinal cord injury (TSCI) leads to substantial health loss through both premature mortality and long-term disability. In this study, we used data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 to estimate the global, regional, and national incidence, prevalence, and years lived with disability (YLDs) associated with TSCI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDisMod-MR 2.3 was applied to estimate case counts and age-standardized rates (ASRs), together with 95% uncertainty intervals (95% UIs), for the incidence (ASIR), prevalence (ASPR), and years lived with disability (ASYR) of spinal cord injury (SCI) from 1990 to 2021 at the global level, across 21 GBD regions, and in 204 countries and territories. Trends in ASRs were quantified using the estimated annual percentage change (EAPC) derived from a linear regression model, and Spearman rank-order correlation was used to explore the relationship between the sociodemographic index (SDI) and the burden of TSCI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn 2023 there were an estimated 574,502 (95% UI 440,219-757,445) new cases, 15,400,682 (95% UI 14,009,114-17,075,106) existing cases, and 1,305,142 (95% UI 917,167-1,726,419) YLDs attributable to TSCI in global. Between 1990 and 2021, the absolute numbers of incident, prevalent, and YLD cases increased, whereas the age-standardized incidence (ASIR), prevalence (ASPR), and YLD (ASYR) rates declined. Men consistently exhibited higher ASIR, ASPR, and ASYR than women, and these ASRs rose with advancing age. Cervical SCI showed higher ASIR and ASYR compared with SCI below the neck. In 2021, the SDI was positively associated with ASIR (rho = 0.4670, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01), ASPR (rho = 0.4035, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01), and ASYR (rho = 0.2727, \u003cem\u003ep\u003c/em\u003e=0.003).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe absolute counts of incidence, prevalence, and burden of TSCI substantially increased from 1990 to 2021, despite the decrease in corresponding ASRs. TSCI happened in the most active periods of individuals globally, which were shifting towards older age groups over time. TSCI had larger effects on the elderly and males than younger populations and females.\u003c/p\u003e","manuscriptTitle":"Trends and Projections of Spinal Cord Injury Burden in China: Insights from the Global Burden of Disease 2023 Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-09 12:10:48","doi":"10.21203/rs.3.rs-8345634/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4cc46d88-f7f8-42d3-906b-7c5e4a93cf87","owner":[],"postedDate":"February 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-20T08:56:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-09 12:10:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8345634","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8345634","identity":"rs-8345634","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}