Temporal changes in the burden of Edentulism across the BRICS, 1990-2023: a comprehensive analysis for the global burden of disease study 2023

Temporal changes in the burden of Edentulism across the BRICS, 1990-2023: a comprehensive analysis for the global burden of disease study 2023 | 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 Temporal changes in the burden of Edentulism across the BRICS, 1990-2023: a comprehensive analysis for the global burden of disease study 2023 Minsheng Zheng, Chi Zhang, Chenxinzi Lin, Chongjie Zhu, Yawen Chen, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7974581/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 Abstract Objective This study analyzed long-term trends (1990–2023) and drivers of edentulism burden in BRICS nations (Brazil, Russia, India, China, South Africa) and projected the burden to 2050. Materials and methods Using GBD 2023 data, Joinpoint regression assessed trend turning points. Age-Period-Cohort (APC) modeling and decomposition analysis quantified contributions from population growth, aging, and epidemiological changes. The Bayesian APC (BAPC) model projected future burden. Result Edentulism burden was heterogeneous. Age-standardized rates (ASRs) were high/increased in Brazil and Russia but declined in China, India, and South Africa. Population aging was the primary driver of absolute burden increases in China, Russia, and Brazil; population growth was key in India and South Africa. APC analysis revealed rising risk in younger Chinese cohorts. Projections suggest continued burden increases for Russia, Brazil, and China. Conclusions The absolute edentulism burden is rising in all BRICS nations, driven by demographic transitions. Divergent epidemiological trends and emerging risk in younger Chinese cohorts necessitate dual strategies: strengthening prevention for the young and preparing health systems for surging geriatric/prosthetic dental care demand. Clinical Relevance Although age-standardized risk is declining in some BRICS nations, the absolute number of edentulous individuals is surging, driven by population aging. Clinicians and health systems must prepare for a rising demand for prosthetic/geriatric dental services. The identified risk in younger Chinese cohorts signals an urgent need to intensify primary prevention, focusing on controlling caries and periodontal disease. BRICS countries Edentulism Disease burden Age-period-cohort model Bayesian age-period-cohort Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Edentulism, the state of complete tooth loss, represents a terminal outcome of oral diseases and stands as a significant global public health challenge[1]. Its consequences extend far beyond mere masticatory dysfunction, profoundly impacting nutritional intake, facial aesthetics, psychological well-being, and overall quality of life[2]. The condition can precipitate difficulties in food consumption, potentially leading to malnutrition, while the associated changes in facial appearance can negatively affect self-esteem, contributing to conditions like anxiety and depression[3]. As an irreversible condition, edentulism serves as a key indicator of a population's oral health status and the effectiveness of its healthcare system. The epidemiological characteristics of edentulism exhibit substantial variation globally, influenced by a confluence of factors including age, socioeconomic status, educational attainment, and access to healthcare[4]. While many high-income regions have witnessed a decline in edentulism prevalence due to advancements in preventive dentistry and public health initiatives, the burden remains disproportionately high in many low- and middle-income countries[5]. Furthermore, with the rapid progression of global population aging, the absolute burden of edentulism is projected to escalate significantly, particularly in societies undergoing demographic transition[6]. This underscores an urgent need to examine the long-term trends of edentulism in greater depth. The BRICS countries—comprising Brazil, the Russian Federation, India, China, and South Africa—represent nearly half of the global population and are a powerful economic alliance characterized by rapid development and societal transformation[7]. Alongside their economic achievements, these nations face common and formidable public health challenges, including the rising burden of non-communicable diseases (NCDs), with oral diseases being a major contributor[8]. Sharing similar healthcare development trajectories and aspirations, the BRICS bloc presents a unique and critical context for studying the dynamics of edentulism, providing valuable insights that may be applicable to other developing nations[9]. Although previous studies leveraging the Global Burden of Disease (GBD) framework have documented the high global burden of edentulism, comprehensive analyses focusing specifically on its long-term epidemiological trends within the BRICS nations remain limited[9]. Descriptive epidemiological studies often fall short of disentangling the intricate contributions of demographic shifts from true changes in disease risk, thus limiting a complete understanding of the disease's temporal evolution[10]. Advanced analytical models are required to deconstruct these trends and identify the underlying drivers, which is essential for evidence-based policymaking. Therefore, this study utilizes data from the GBD 2023 to provide a comprehensive analysis of the temporal trends in the edentulism burden across the BRICS countries from 1990 to 2023. By employing Joinpoint regression analysis, we aim to identify significant turning points in these trends. Furthermore, we apply Age-Period-Cohort (APC) and decomposition analyses to deconstruct the observed changes and quantify the distinct effects of population aging, population growth, and epidemiological shifts. Finally, this study projects the edentulism burden to 2050, seeking to establish a robust scientific basis to inform the formulation of targeted public health strategies and interventions for the prevention and control of edentulism in these influential nations. 2. Materials and Methods 2.1. Data Source This study was a cross-sectional analysis based on publicly available data sourced from the Global Burden of Disease Study 2023 (GBD 2023), accessed via the Global Health Data Exchange (GHDx) query tool ( http://ghdx.healthdata.org/gbd-results-tool ). The GBD 2023 provided a comprehensive and systematic assessment of the burden of 375 diseases and injuries across 204 countries and territories from 1990 to 2023[11]. Annual data on the incidence, prevalence, and Disability-Adjusted Life Years (DALYs) of edentulism for the five BRICS countries (Brazil, the Russian Federation, India, China, and South Africa) was extracted, spanning the period from 1990 to 2023. DALYs are a composite measure of disease burden, calculated as the sum of Years of Life Lost (YLLs) due to premature mortality and Years Lived with Disability (YLDs) [12]. To facilitate comparisons across populations with different age structures, age-standardized rates for incidence (ASIR), prevalence (ASPR), and DALYs (ASDR) were utilized. These rates were computed by direct standardization using the GBD 2023 global standard population [13]. All estimates were presented with their corresponding 95% uncertainty intervals (UIs). As this study utilized aggregated, de-identified data from a public domain repository, no additional ethical approval was required. 2.2. Statistical Analysis 2.2.1. Assessment of Long-Term Trends To provide a general overview of the long-term temporal trends in the burden of edentulism, the ASIR, ASPR, and ASDR for each BRICS country from 1990 to 2023 were first visualized using multi-panel line charts. Additionally, the Estimated Annual Percentage Changes (EAPCs) were calculated to summarize the overall trend direction and magnitude over the entire study period[14]. 2.2.2. Joinpoint Regression Analysis To more precisely identify and quantify significant changes in secular trends, a Joinpoint regression model was employed[15]. This model identifies "joinpoints," which are time points where a statistically significant change in the trend occurs, and fits a series of linear segments to the data. For each segment between joinpoints, the APC and its 95% confidence interval (CI) were calculated to describe the rate of change within that specific period. 2.2.3. Age-Period-Cohort Model Analysis To deconstruct the underlying drivers of the observed trends in edentulism prevalence, an Age-Period-Cohort model was utilized[9]. This analytical framework aimed to disentangle the independent effects of age, period, and birth cohort. The age effect represented the change in risk associated with physiological aging. The period effect captured temporal changes in risk that affect all age groups simultaneously, often reflecting shifts in medical diagnostics, public health interventions, or societal factors. The cohort effect reflected variations in risk among groups of individuals born in different years, which may be linked to differential exposures or lifestyle patterns early in life. Data were arranged into consecutive 5-year periods and 5-year age groups to meet the modeling requirements. 2.2.4. Decomposition Analysis To quantitatively attribute the net change in the total number of edentulism cases (prevalence, incidence, and DALYs) between 1990 and 2023 to its fundamental drivers, a decomposition analysis was performed. Following the methodology of Das Gupta, the total change was partitioned into three components: the contribution of population growth, the contribution of population aging, and the contribution of epidemiological changes[16]. The results were visualized using stacked bar charts to compare the relative impact of these drivers across the BRICS nations. 2.2.5. Trend Forecasting To project the future burden of edentulism, a Bayesian Age-Period-Cohort (BAPC) model was employed[17]. Based on the historical data from 1990–2023, this model was used to forecast the trends of ASIR, ASPR, and ASDR for each country up to the year 2050. The projections were presented as trend lines with 95% uncertainty intervals to provide data-driven insights for long-term public health planning and policy formulation. All statistical analyses and visualizations were conducted using R software (Version 4.2.1) and the Joinpoint Regression Program from the U.S. National Cancer Institute. 3. Result 3.1. Description of the burden of Edentulism in BRICS countries Incidence of Edentulism In Brazil, the ASIR of edentulism remained relatively stable, with a minor decrease from 599.50 (95% UI: 521.50–681.70) in 1990 to 595.20 (95% UI: 532.90–654.70) per 100,000 population in 2023. Conversely, the Russian Federation experienced a notable increase in ASIR from 417.20 (95% UI: 349.10–496.00) to 445.60 (95% UI: 371.40–529.20) per 100,000 population over the same period. China, India, and South Africa all demonstrated significant declines in their ASIRs, highlighting progress in disease control ( Table 1 ) . Table 1 Age-standardized edentulism burden for the BRICS countries Age-standardized DALYs Age-standardized Incidence Age-standardized prevalence Location 1990 (per 100,000 population, 95% UI) 2023(per 100,000 population, 95% UI) EAPCs (95% CI) Location 1990 (per 100,000 population, 95% UI) 2023(per 100,000 population, 95% UI) EAPCs (95% CI) Location 1990 (per 100,000 population, 95% UI) 2023(per 100,000 population, 95% UI) EAPCs (95% CI) Brazil 237.50 (156.70-327.10) 240.10 (158.20-319.90) 0.1 (-0.2,0.3) Brazil 599.50 (521.50-681.70) 595.20 (532.90-654.70) 0.0 (-0.1,0.2) Brazil 8829.70 (7321.90-10493.80) 8930.20 (7780.40-10127.20) 0.1 (-0.2,0.3) People's Republic of China 92.70 (60.90-132.50) 84.60 (57.20-118.30) -0.0 (-0.4,0.3) People's Republic of China 303.60 (242.20-373.70) 285.60 (235.30-338.60) -0.0 (-0.3,0.2) People's Republic of China 3470.50 (2710.40-4416.20) 3161.40 (2616.80-3860.80) -0.1 (-0.4,0.3) Republic of India 98.90 (63.50-136.50) 81.70 (53.80-109.30) 0.3 (-0.6,1.2) Republic of India 291.10 (236.10-361.60) 247.40 (209.60-296.20) -0.0 (-0.7,0.6) Republic of India 3728.70 (2986.40-4698.50) 3065.40 (2613.20-3630.70) 0.2 (-0.6,1.1) Republic of South Africa 206.10 (127.60-296.60) 168.50 (104.10-238.40) -0.6 (-1.1,-0.2) Republic of South Africa 364.40 (306.60-426.50) 321.80 (270.70-379.50) -0.5 (-0.8,-0.2) Republic of South Africa 7448.70 (5774.90-9047.70) 6152.30 (4897.00-7420.70) -0.6 (-1.1,-0.2) Russian Federation 162.60 (104.80-220.30) 181.60 (118.10-241.30) 0.3 (0.2,0.4) Russian Federation 417.20 (349.10–496.00) 445.60 (371.40-529.20) 0.2 (0.1,0.2) Russian Federation 6037.80 (4945.90-7392.90) 6736.20 (5612.90-8006.20) 0.3 (0.2,0.4) Abbreviations: CI, confidence interval; DALYs, disability-adjusted life years; EAPCs, estimated annual percentage changes; UI, uncertainty interval. Prevalence of Edentulism Brazil and the Russian Federation both exhibited a high and increasing prevalence of edentulism. The ASPR in Brazil rose from 8829.70 (95% UI: 7321.90–10493.80) in 1990 to 8930.20 (95% UI: 7780.40–10127.20) in 2023. Compared to 1990, the most significant reductions in ASPR were observed in South Africa, which saw a decrease from 7448.70 (95% UI: 5774.90–9047.70) to 6152.30 (95% UI: 4897.00–7420.70), resulting in a relatively reduced burden of edentulism ( Table 1 ) . DALYs of Edentulism From 1990 to 2023, the ASDR for edentulism increased in Brazil, rising from 237.50 (95% UI: 156.70–327.10) to 240.10 (95% UI: 158.20–319.90), and in the Russian Federation, where it climbed from 162.60 (95% UI: 104.80–220.30) to 181.60 (95% UI: 118.10–241.30). Nations such as China, India, and South Africa each noted considerable declines in their ASDRs. South Africa experienced the steepest decline, with the ASDR falling from 206.10 (95% UI: 127.60–296.60) to 168.50 (95% UI: 104.10–238.40) ( Table 1 ) . Overall Trends Overall, the results of these measures show that Brazil consistently ranks first among the BRICS in terms of the burden of edentulism, followed by the Russian Federation and South Africa ( Table 1 ) . 3.2. Trends of Edentulism from 1990 to 2023 From 1990 to 2023, the age-standardized rates (ASRs) of edentulism among the BRICS countries exhibited varied and dynamic trends. A general overview of the long-term changes reveals significant heterogeneity in the ASPR, ASDR, and ASIR among the five nations (Fig. 1 ). Brazil and the Russian Federation generally demonstrated the highest burden across all metrics, whereas China consistently showed the lowest rates. India and South Africa displayed intermediate and fluctuating trends throughout the period. To more precisely identify and quantify key inflection points, a Joinpoint regression analysis was performed on the temporal trends of ASDR, ASIR, and ASPR. The analysis of ASDR revealed complex, non-linear trajectories. Brazil's trend was characterized by five joinpoints, with a period of sharp increase between 2005 and 2010 (APC = 5.34), followed by a subsequent decline. The trend in India was similarly volatile, with a dramatic surge in burden from 2005 to 2010 (APC = 19.04) before reversing into a steep decrease (APC = -10.53 from 2010 to 2017). In contrast, the Russian Federation exhibited a sustained upward trend across four joinpoints, with the most significant increase occurring between 2010 and 2014 (APC = 3.41). China and South Africa, however, showed a predominantly declining trend, with China's ASDR decreasing at an APC of -3.22 from 1990 to 2000. (Fig. 2 A) Similar complex patterns were observed in the analyses of ASIR and ASPR. In the ASPR analysis, Brazil’s rate peaked between 2005 and 2010 (APC = 6.14), while China’s ASPR demonstrated a consistent decline across five joinpoints, with a significant decrease between 1990 and 2000 (APC = -3.19). For ASIR, India again showed a pronounced peak from 2005 to 2010 (APC = 15.38), and the Russian Federation's rate increased significantly between 2010 and 2014 (APC = 1.10). (Fig. 2 B, 2 C) 3.3. Age, period, and cohort effects on Edentulism incidence rate The longitudinal age curves reveal the age effect (Fig. 3 A). A consistent pattern was observed across all BRICS nations, wherein the risk of edentulism incidence increased substantially and continuously with advancing age. This pattern was particularly pronounced in Brazil, the Russian Federation, and India, where the incidence rate began to accelerate after the age of 40, reaching its peak in the 80–85 age group. While China's incidence followed a similar trajectory, its point of significant increase started later, at approximately 50 years of age. In contrast, the age-effect curve for South Africa, while also trending upward, was comparatively flatter, suggesting a lower peak incidence rate among its older population compared to the other BRICS nations. Figure 3 B illustrates the period effects, revealing considerable heterogeneity in the relative risk (RR) of edentulism incidence across time. Brazil and India exhibited a similar and distinct non-linear pattern, marked by a significant increase in period-related risk that peaked around the 2005–2010 period before subsequently declining. In contrast, South Africa and China both demonstrated a general downward trend in period RR over the three decades, indicating a reduction in risk attributable to period factors. The Russian Federation displayed the most stable pattern, with its period RR remaining relatively constant and close to the reference line throughout the study period. Figure 3 C s hows that the cohort effects on past incidence risk have remained relatively stable in Brazil, India, and the Russian Federation. However, in China, there has been a gradual increase in incidence risk after the reference cohort (1949–1954). In contrast, South Africa has shown a gradual decline in incidence risk after the reference cohort. 3.4. Decomposition of driving factors for the burden of Edentulism The absolute number of DALYs, incident cases, and prevalent cases of edentulism increased across all BRICS nations from 1990 to 2023, with the most substantial increases detected in China and India. For the growth in DALYs, population aging was the primary driver in China, the Russian Federation, and Brazil, accounting for 90.6%, 78.8%, and 66.2% of the increase, respectively. In contrast, population growth was the main contributor in India (67.1%) and South Africa (82.6%). Epidemiological change exerted a mitigating, negative effect on the DALYs increase in India (-27.5%), China (-10.7%), and most notably in South Africa (-34.8%), but contributed positively in the Russian Federation (26.0%). This pattern was largely mirrored in the increase of prevalent cases. Population aging accounted for 91.0%, 79.2%, and 66.3% of the rise in prevalent cases in China, the Russian Federation, and Brazil, respectively. Meanwhile, population growth was the dominant factor in India (66.8%) and South Africa (89.9%). Notably, the Russian Federation was unique in that its population growth provided a negative contribution (-4.7%) to the increase in prevalent cases. A similar dynamic was observed for incident cases, where population aging was the most significant factor in China (86.8%) and the Russian Federation (87.9%), while population growth was the largest contributor in South Africa (89.9%) and India (67.4%) ( Fig. 4 ). 3.5. Future forecasts of the burden of disease in Edentulism Utilizing the BAPC model based on data from 1990–2023, we projected ASIR, ASPR, and ASDR for edentulism in the BRICS countries up to 2050. The projections indicate divergent future trends among these nations ( Fig. 5 A-C ) . Specifically, the burden of edentulism is projected to continue increasing in the Russian Federation, Brazil, and China through 2050. By 2050, the projected ASIR, ASPR, and ASDR are expected to reach 377.3 (95% CI: 330.6–424.0), 5186.2 (95% CI: 4470.9–5901.5), and 138.7 (95% CI: 118.9–158.6) per 100,000 in the Russian Federation, respectively. For Brazil, these rates are projected to be 637.9 (95% CI: 185.7–1090.1), 8280.7 (95% CI: 364.6–16196.8), and 224.0 (95% CI: 13.6–434.3) per 100,000, respectively. China's projected rates are 246.6 (95% CI: 95.8–397.5), 2393.9 (95% CI: 731.8–4056.0), and 65.2 (95% CI: 19.8–110.5) per 100,000, respectively. Conversely, India and South Africa are projected to exhibit stable or declining trends by 2050. India's ASIR, ASPR, and ASDR are projected to be 152.0 (95% CI: -47.1–351.0), 1848.6 (95% CI: -1480.1–5177.3), and 50.4 (95% CI: -40.1–141.0) per 100,000, respectively, with the lowest projected ASDR among the BRICS nations. South Africa is expected to see declines, with projected rates of 198.1 (95% CI: 66.4–329.8), 3861.3 (95% CI: 356.3–7366.2), and 104.2 (95% CI: 9.6–198.9) per 100,000 for ASIR, ASPR, and ASDR, respectively. 4. Discussion This study provides a comprehensive assessment of the edentulism burden across the BRICS nations, revealing a profound heterogeneity in epidemiological trajectories from 1990 to 2023. Our primary finding is a stark divergence: while China and South Africa have made significant strides in reducing their age-standardized burden, Brazil and the Russian Federation continue to face a persistently high and, in some aspects, worsening challenge. Crucially, our analysis reveals that this epidemiological narrative is universally shaped by a powerful undercurrent of demographic change. The inexorable forces of population aging and growth are the principal drivers of the rising absolute number of cases across all five nations, a finding that significantly refashions the public health challenge from one of pure prevention to one of managing a growing, inevitable demand for care. These findings are broadly consistent with research showing a global decline in edentulism in many regions, yet they highlight that this progress is not uniform[18]. The sustained high burden in Brazil and the Russian Federation aligns with literature detailing challenges in their public health systems and significant socioeconomic disparities in access to dental care[19, 20]. Our decomposition analysis adds a critical layer of insight, revealing that Russia’s situation is uniquely compounded by an unfavorable epidemiological shift, suggesting that risk factor control or systemic healthcare access may have deteriorated over the period, beyond the impact of aging alone[20]. In contrast, the success observed in China likely reflects the positive impact of rapid economic development, improved public health infrastructure, and targeted national oral health programs[21]. Also, the results in South Africa may reflect the fact that South African populations tend to have lower consumption of free sugars[22]. Our analysis, however, uncovers a crucial nuance that distinguishes our findings: the Age-Period-Cohort model identified a concerning rise in incidence risk among younger birth cohorts in China. This novel observation suggests that new risk factors, such as dietary shifts towards higher sugar consumption, may be creating a future wave of oral disease that could undermine past public health achievements[23]. Notwithstanding its strengths, this study has several limitations. First and foremost, our analysis is contingent upon the accuracy of GBD-modeled estimates, which are themselves subject to uncertainty based on the quality and availability of primary data from each country[24]. The extreme volatility observed in India's data, for instance, may be a methodological artifact rather than a true epidemiological event, warranting a cautious interpretation of its trends. Second, the GBD framework analyzes data at the national level, which inevitably masks significant sub-national, regional, and socioeconomic disparities that are particularly pronounced in large and diverse nations like the BRICS[25]. Finally, our future projections are based on historical trends and cannot account for the potential impact of future policy shifts, disruptive technological innovations in dentistry, or major economic events. The implications of our findings for public health policy are twofold and demand tailored strategies. For nations with a high and sustained burden like Brazil and Russia, a renewed focus on primary prevention of caries and periodontal disease—the main precursors to tooth loss—is imperative[26]. However, for all BRICS nations, including those succeeding in epidemiological control like China, the demographic reality is inescapable. The dramatic increase in the absolute number of edentulous individuals, driven predominantly by population aging, signals an urgent need to reorient healthcare systems to meet a surging demand for prosthetic and geriatric dental services. This involves planning for infrastructure, workforce training, and financing models capable of managing a large elderly population requiring restorative care. Conclusion In conclusion, despite the progress in reducing age-standardized rates in countries like China and South Africa, the absolute number of people affected by edentulism is projected to increase across the BRICS bloc, driven primarily by demographic transitions. The burden of edentulism is greatest in the elderly populations, with a notable emerging risk among younger birth cohorts in China. The BRICS countries face a substantial and growing absolute burden of edentulism, and public health policies must be adapted to manage both the primary prevention for at-risk younger cohorts and the surging prosthetic and geriatric dental care needs of an aging population. Declarations Funding Declaration This study was supported by grants from School & Hospital of Stomatology, Wuhan University [No. LYZX202002]. Conflicts of interest statement The authors declare that they have no conflicts of interest. Data availability statement Publicly available datasets were analyzed in the present study. The original contributions presented in the study are included in the article and accompanying Supporting information. Further inquiries can be directed to the corresponding authors. Author Contribution Conceptualization: M.Z., C.Z. Methodology: M.Z. Formal Analysis: M.Z., C.Z. Investigation: M.Z., C.Z. Data Curation: M.Z., C.L., B.Y., C.J.Z. Visualization: M.Z., C.L., Y.C., C.J.Z. 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Clin Oral Investig 29:22. doi: 10.1007/s00784-024-06111-5 Bernabe E, Marcenes W, Hernandez CR, Bailey J, Abreu LG, Alipour V, Amini S, Arabloo J, Arefi Z, Arora A, Ayanore MA, Bärnighausen TW, Bijani A, Cho DY, Chu DT, Crowe CS, Demoz GT, Demsie DG, Dibaji Forooshani ZS, Du M, El Tantawi M, Fischer F, Folayan MO, Futran ND, Geramo YCD, Haj-Mirzaian A, Hariyani N, Hasanzadeh A, Hassanipour S, Hay SI, Hole MK, Hostiuc S, Ilic MD, James SL, Kalhor R, Kemmer L, Keramati M, Khader YS, Kisa S, Kisa A, Koyanagi A, Lalloo R, Le Nguyen Q, London SD, Manohar ND, Massenburg BB, Mathur MR, Meles HG, Mestrovic T, Mohammadian-Hafshejani A, Mohammadpourhodki R, Mokdad AH, Morrison SD, Nazari J, Nguyen TH, Nguyen CT, Nixon MR, Olagunju TO, Pakshir K, Pathak M, Rabiee N, Rafiei A, Ramezanzadeh K, Rios-Blancas MJ, Roro EM, Sabour S, Samy AM, Sawhney M, Schwendicke F, Shaahmadi F, Shaikh MA, Stein C, Tovani-Palone MR, Tran BX, Unnikrishnan B, Vu GT, Vukovic A, Warouw TSS, Zaidi Z, Zhang ZJ and Kassebaum NJ (2020) Global, Regional, and National Levels and Trends in Burden of Oral Conditions from 1990 to 2017: A Systematic Analysis for the Global Burden of Disease 2017 Study. J Dent Res 99:362-373. doi: 10.1177/0022034520908533 Pucca GA, Jr., Gabriel M, de Araujo ME and de Almeida FC (2015) Ten Years of a National Oral Health Policy in Brazil: Innovation, Boldness, and Numerous Challenges. J Dent Res 94:1333-7. doi: 10.1177/0022034515599979 Danton C (2007) The health crisis in Russia. Human Rights & Human Welfare 7:41. Liu Y, Rao K and Fei J (1998) Economic transition and health transition: comparing China and Russia. Health Policy 44:103-22. doi: 10.1016/s0168-8510(98)00010-4 Peltzer K, Hewlett S, Yawson AE, Moynihan P, Preet R, Wu F, Guo G, Arokiasamy P, Snodgrass JJ, Chatterji S, Engelstad ME and Kowal P (2014) Prevalence of loss of all teeth (edentulism) and associated factors in older adults in China, Ghana, India, Mexico, Russia and South Africa. Int J Environ Res Public Health 11:11308-24. doi: 10.3390/ijerph111111308 Ladeira LLC, Nascimento GG, Leite FRM, Alves-Costa S, Thomaz E, Alves CMC, Cury JA and Ribeiro CCC (2024) Sugar intake above international recommendations and oral disease burden: A population-based study. Oral Dis 30:615-623. doi: 10.1111/odi.14464 Tamrakar M, Kharel P, Traeger A, Maher C, O'Keeffe M and Ferreira G (2021) Completeness and quality of low back pain prevalence data in the Global Burden of Disease Study 2017. BMJ Glob Health 6. doi: 10.1136/bmjgh-2021-005847 Achoki T, Sartorius B, Watkins D, Glenn SD, Kengne AP, Oni T, Wiysonge CS, Walker A, Adetokunboh OO, Babalola TK, Bolarinwa OA, Claassens MM, Cowden RG, Day CT, Ezekannagha O, Ginindza TG, Iwu CCD, Iwu CJ, Karangwa I, Katoto PD, Kugbey N, Kuupiel D, Mahasha PW, Mashamba-Thompson TP, Mensah GA, Ndwandwe DE, Nnaji CA, Ntsekhe M, Nyirenda TE, Odhiambo JN, Oppong Asante K, Parry CDH, Pillay JD, Schutte AE, Seedat S, Sliwa K, Stein DJ, Tanser FC, Useh U, Zar HJ, Zühlke LJ, Mayosi BM, Hay SI, Murray CJL and Naghavi M (2022) Health trends, inequalities and opportunities in South Africa's provinces, 1990-2019: findings from the Global Burden of Disease 2019 Study. J Epidemiol Community Health 76:471-81. doi: 10.1136/jech-2021-217480 Huang Y, Hao L, Li J, Guan W, Li S, Zhang Y, Xu X, Li J and Xu X (2025) Trends in incidence of untreated caries in permanent teeth in BRICS countries: an age-period-cohort analysis from 1992 to 2021 and projections for the next two decades. Clin Oral Investig 29:267. doi: 10.1007/s00784-025-06343-z Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7974581","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":549136730,"identity":"d40ae667-ded5-4e1d-8c7c-e84e38bc0d94","order_by":0,"name":"Minsheng Zheng","email":"","orcid":"","institution":"School \u0026 Hospital of Stomatology, Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Minsheng","middleName":"","lastName":"Zheng","suffix":""},{"id":549136731,"identity":"77a1a9bf-d014-4bb8-a0d7-91835ab421cf","order_by":1,"name":"Chi Zhang","email":"","orcid":"","institution":"School \u0026 Hospital of Stomatology, 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10:05:41","extension":"xml","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":105689,"visible":true,"origin":"","legend":"","description":"","filename":"2a1a4aaa875a4909ac1c7276e86a5d851structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7974581/v1/ccd37e4b85307d8fc5a0f88f.xml"},{"id":96709345,"identity":"338c61be-5147-4a9b-a626-3de192fc213a","added_by":"auto","created_at":"2025-11-25 10:08:47","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":116663,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7974581/v1/2ca0e929dd83a6bea2a834ac.html"},{"id":96708692,"identity":"20325fce-83c9-438c-bba0-800ba38a1827","added_by":"auto","created_at":"2025-11-25 10:05:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3084581,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trends in the age-standardized rates (ASRs) of edentulism in BRICS countries, 1990–2023. (A) Age-standardized Prevalence Rate (ASPR). (B) Age-standardized DALY Rate (ASDR). (C) Age-standardized Incidence Rate (ASIR).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7974581/v1/93eb3486cb6712262de5fa9a.png"},{"id":96624725,"identity":"10c67595-4de4-425a-bb41-339148d847da","added_by":"auto","created_at":"2025-11-24 11:30:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1312752,"visible":true,"origin":"","legend":"\u003cp\u003eJoinpoint regression analysis of the temporal trends in age-standardized rates (ASRs) for edentulism in BRICS countries, 1990–2023. (A) Trends in age-standardized DALYs rate (ASDR). (B) Trends in age-standardized incidence rate (ASIR). (C) Trends in age-standardized prevalence rate (ASPR).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7974581/v1/7101da1c3f83874f705b4cea.png"},{"id":96624729,"identity":"ab8a638e-23c7-49c5-9b30-1d280b2e6a43","added_by":"auto","created_at":"2025-11-24 11:30:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":456402,"visible":true,"origin":"","legend":"\u003cp\u003eAge, period, and cohort effects on edentulism incidence in the BRICS countries. (A) Age effects are shown by the fitted longitudinal age curves of incidence rate (per 100,000 population) adjusted for period deviations. (B) Period effects are shown by the relative risk of incidence rate (incidence rate ratio) and computed as the ratio of age-specific rates across periods from 1994–1998 to 2019–2023, with the referent period set at 2005–2006. (C) Cohort effects are shown by the relative risk of incidence rate and computed as the ratio of age-specific rates across birth cohorts, with the referent cohort set at 1945–1949.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7974581/v1/c8971277a199331ab2b90528.png"},{"id":96624727,"identity":"8ef9e9da-d03f-45f3-90b5-7249c856c6ba","added_by":"auto","created_at":"2025-11-24 11:30:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":606969,"visible":true,"origin":"","legend":"\u003cp\u003eDecomposition analysis attributing the net change in the burden of edentulism in BRICS countries from 1990 to 2023 to underlying drivers. (A) Decomposition of changes in total DALYs cases. (B) Decomposition of changes in total incident cases. (C) Decomposition of changes in total prevalence cases.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7974581/v1/d8d67278236fb2d23b23e025.png"},{"id":96708784,"identity":"e26f93da-1fce-4e0b-bc87-21ba7455fd69","added_by":"auto","created_at":"2025-11-25 10:05:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1011432,"visible":true,"origin":"","legend":"\u003cp\u003eProjections of the burden of edentulism in the BRICS countries from 2023 to 2050 using the Bayesian age-period-cohort (BAPC) model. (A) Projected age-standardized DALYs rate (ASDR). (B) Projected age-standardized incidence rate (ASIR). (C) Projected age-standardized prevalence rate (ASPR).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7974581/v1/ee0042ced32a01bd4c249bb9.png"},{"id":102748289,"identity":"bf1a5eb8-3dfd-4a8e-abdd-fe50ba9ceebd","added_by":"auto","created_at":"2026-02-16 09:06:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6900579,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7974581/v1/1d116941-baba-4014-b3fc-f02d23345f0a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Temporal changes in the burden of Edentulism across the BRICS, 1990-2023: a comprehensive analysis for the global burden of disease study 2023","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eEdentulism, the state of complete tooth loss, represents a terminal outcome of oral diseases and stands as a significant global public health challenge[1]. Its consequences extend far beyond mere masticatory dysfunction, profoundly impacting nutritional intake, facial aesthetics, psychological well-being, and overall quality of life[2]. The condition can precipitate difficulties in food consumption, potentially leading to malnutrition, while the associated changes in facial appearance can negatively affect self-esteem, contributing to conditions like anxiety and depression[3]. As an irreversible condition, edentulism serves as a key indicator of a population's oral health status and the effectiveness of its healthcare system.\u003c/p\u003e\u003cp\u003eThe epidemiological characteristics of edentulism exhibit substantial variation globally, influenced by a confluence of factors including age, socioeconomic status, educational attainment, and access to healthcare[4]. While many high-income regions have witnessed a decline in edentulism prevalence due to advancements in preventive dentistry and public health initiatives, the burden remains disproportionately high in many low- and middle-income countries[5]. Furthermore, with the rapid progression of global population aging, the absolute burden of edentulism is projected to escalate significantly, particularly in societies undergoing demographic transition[6]. This underscores an urgent need to examine the long-term trends of edentulism in greater depth.\u003c/p\u003e\u003cp\u003eThe BRICS countries\u0026mdash;comprising Brazil, the Russian Federation, India, China, and South Africa\u0026mdash;represent nearly half of the global population and are a powerful economic alliance characterized by rapid development and societal transformation[7]. Alongside their economic achievements, these nations face common and formidable public health challenges, including the rising burden of non-communicable diseases (NCDs), with oral diseases being a major contributor[8]. Sharing similar healthcare development trajectories and aspirations, the BRICS bloc presents a unique and critical context for studying the dynamics of edentulism, providing valuable insights that may be applicable to other developing nations[9].\u003c/p\u003e\u003cp\u003eAlthough previous studies leveraging the Global Burden of Disease (GBD) framework have documented the high global burden of edentulism, comprehensive analyses focusing specifically on its long-term epidemiological trends within the BRICS nations remain limited[9]. Descriptive epidemiological studies often fall short of disentangling the intricate contributions of demographic shifts from true changes in disease risk, thus limiting a complete understanding of the disease's temporal evolution[10]. Advanced analytical models are required to deconstruct these trends and identify the underlying drivers, which is essential for evidence-based policymaking.\u003c/p\u003e\u003cp\u003eTherefore, this study utilizes data from the GBD 2023 to provide a comprehensive analysis of the temporal trends in the edentulism burden across the BRICS countries from 1990 to 2023. By employing Joinpoint regression analysis, we aim to identify significant turning points in these trends. Furthermore, we apply Age-Period-Cohort (APC) and decomposition analyses to deconstruct the observed changes and quantify the distinct effects of population aging, population growth, and epidemiological shifts. Finally, this study projects the edentulism burden to 2050, seeking to establish a robust scientific basis to inform the formulation of targeted public health strategies and interventions for the prevention and control of edentulism in these influential nations.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Data Source\u003c/h2\u003e\u003cp\u003eThis study was a cross-sectional analysis based on publicly available data sourced from the Global Burden of Disease Study 2023 (GBD 2023), accessed via the Global Health Data Exchange (GHDx) query tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ghdx.healthdata.org/gbd-results-tool\u003c/span\u003e\u003cspan address=\"http://ghdx.healthdata.org/gbd-results-tool\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The GBD 2023 provided a comprehensive and systematic assessment of the burden of 375 diseases and injuries across 204 countries and territories from 1990 to 2023[11].\u003c/p\u003e\u003cp\u003eAnnual data on the incidence, prevalence, and Disability-Adjusted Life Years (DALYs) of edentulism for the five BRICS countries (Brazil, the Russian Federation, India, China, and South Africa) was extracted, spanning the period from 1990 to 2023. DALYs are a composite measure of disease burden, calculated as the sum of Years of Life Lost (YLLs) due to premature mortality and Years Lived with Disability (YLDs) [12]. To facilitate comparisons across populations with different age structures, age-standardized rates for incidence (ASIR), prevalence (ASPR), and DALYs (ASDR) were utilized. These rates were computed by direct standardization using the GBD 2023 global standard population [13]. All estimates were presented with their corresponding 95% uncertainty intervals (UIs). As this study utilized aggregated, de-identified data from a public domain repository, no additional ethical approval was required.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Statistical Analysis\u003c/h2\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1. Assessment of Long-Term Trends\u003c/h2\u003e\u003cp\u003eTo provide a general overview of the long-term temporal trends in the burden of edentulism, the ASIR, ASPR, and ASDR for each BRICS country from 1990 to 2023 were first visualized using multi-panel line charts. Additionally, the Estimated Annual Percentage Changes (EAPCs) were calculated to summarize the overall trend direction and magnitude over the entire study period[14].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2. Joinpoint Regression Analysis\u003c/h2\u003e\u003cp\u003eTo more precisely identify and quantify significant changes in secular trends, a Joinpoint regression model was employed[15]. This model identifies \"joinpoints,\" which are time points where a statistically significant change in the trend occurs, and fits a series of linear segments to the data. For each segment between joinpoints, the APC and its 95% confidence interval (CI) were calculated to describe the rate of change within that specific period.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.2.3. Age-Period-Cohort Model Analysis\u003c/h2\u003e\u003cp\u003eTo deconstruct the underlying drivers of the observed trends in edentulism prevalence, an Age-Period-Cohort model was utilized[9]. This analytical framework aimed to disentangle the independent effects of age, period, and birth cohort. The age effect represented the change in risk associated with physiological aging. The period effect captured temporal changes in risk that affect all age groups simultaneously, often reflecting shifts in medical diagnostics, public health interventions, or societal factors. The cohort effect reflected variations in risk among groups of individuals born in different years, which may be linked to differential exposures or lifestyle patterns early in life. Data were arranged into consecutive 5-year periods and 5-year age groups to meet the modeling requirements.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.2.4. Decomposition Analysis\u003c/h2\u003e\u003cp\u003eTo quantitatively attribute the net change in the total number of edentulism cases (prevalence, incidence, and DALYs) between 1990 and 2023 to its fundamental drivers, a decomposition analysis was performed. Following the methodology of Das Gupta, the total change was partitioned into three components: the contribution of population growth, the contribution of population aging, and the contribution of epidemiological changes[16]. The results were visualized using stacked bar charts to compare the relative impact of these drivers across the BRICS nations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.2.5. Trend Forecasting\u003c/h2\u003e\u003cp\u003eTo project the future burden of edentulism, a Bayesian Age-Period-Cohort (BAPC) model was employed[17]. Based on the historical data from 1990\u0026ndash;2023, this model was used to forecast the trends of ASIR, ASPR, and ASDR for each country up to the year 2050. The projections were presented as trend lines with 95% uncertainty intervals to provide data-driven insights for long-term public health planning and policy formulation.\u003c/p\u003e\u003cp\u003eAll statistical analyses and visualizations were conducted using R software (Version 4.2.1) and the Joinpoint Regression Program from the U.S. National Cancer Institute.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3. Result","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Description of the burden of Edentulism in BRICS countries\u003c/h2\u003e\u003cp\u003e\u003cb\u003eIncidence of Edentulism\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn Brazil, the ASIR of edentulism remained relatively stable, with a minor decrease from 599.50 (95% UI: 521.50\u0026ndash;681.70) in 1990 to 595.20 (95% UI: 532.90\u0026ndash;654.70) per 100,000 population in 2023. Conversely, the Russian Federation experienced a notable increase in ASIR from 417.20 (95% UI: 349.10\u0026ndash;496.00) to 445.60 (95% UI: 371.40\u0026ndash;529.20) per 100,000 population over the same period. China, India, and South Africa all demonstrated significant declines in their ASIRs, highlighting progress in disease control \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAge-standardized edentulism burden for the BRICS countries\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"12\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eAge-standardized DALYs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003eAge-standardized Incidence\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c12\" namest=\"c9\"\u003e\u003cp\u003eAge-standardized prevalence\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLocation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1990 (per 100,000 population, 95% UI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2023(per 100,000 population, 95% UI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEAPCs (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eLocation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1990 (per 100,000 population, 95% UI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2023(per 100,000 population, 95% UI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eEAPCs (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003eLocation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1990 (per 100,000 population, 95% UI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e2023(per 100,000 population, 95% UI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eEAPCs (95% CI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBrazil\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e237.50 (156.70-327.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e240.10 (158.20-319.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1 (-0.2,0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eBrazil\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e599.50 (521.50-681.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e595.20 (532.90-654.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0 (-0.1,0.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003eBrazil\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e8829.70 (7321.90-10493.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e8930.20 (7780.40-10127.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.1 (-0.2,0.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePeople's Republic of China\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e92.70 (60.90-132.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84.60 (57.20-118.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0 (-0.4,0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003ePeople's Republic of China\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e303.60 (242.20-373.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e285.60 (235.30-338.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.0 (-0.3,0.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003ePeople's Republic of China\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3470.50 (2710.40-4416.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3161.40 (2616.80-3860.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-0.1 (-0.4,0.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRepublic of India\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e98.90 (63.50-136.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81.70 (53.80-109.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.3 (-0.6,1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eRepublic of India\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e291.10 (236.10-361.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e247.40 (209.60-296.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.0 (-0.7,0.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003eRepublic of India\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3728.70 (2986.40-4698.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3065.40 (2613.20-3630.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.2 (-0.6,1.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRepublic of South Africa\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e206.10 (127.60-296.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e168.50 (104.10-238.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.6 (-1.1,-0.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eRepublic of South Africa\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e364.40 (306.60-426.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e321.80 (270.70-379.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.5 (-0.8,-0.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003eRepublic of South Africa\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e7448.70 (5774.90-9047.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e6152.30 (4897.00-7420.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-0.6 (-1.1,-0.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRussian Federation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e162.60 (104.80-220.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e181.60 (118.10-241.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.3 (0.2,0.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eRussian Federation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e417.20 (349.10\u0026ndash;496.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e445.60 (371.40-529.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.2 (0.1,0.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003eRussian Federation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e6037.80 (4945.90-7392.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e6736.20 (5612.90-8006.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.3 (0.2,0.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003cem\u003eAbbreviations: CI, confidence interval; DALYs, disability-adjusted life years; EAPCs, estimated annual percentage changes; UI, uncertainty interval.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePrevalence of Edentulism\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBrazil and the Russian Federation both exhibited a high and increasing prevalence of edentulism. The ASPR in Brazil rose from 8829.70 (95% UI: 7321.90\u0026ndash;10493.80) in 1990 to 8930.20 (95% UI: 7780.40\u0026ndash;10127.20) in 2023. Compared to 1990, the most significant reductions in ASPR were observed in South Africa, which saw a decrease from 7448.70 (95% UI: 5774.90\u0026ndash;9047.70) to 6152.30 (95% UI: 4897.00\u0026ndash;7420.70), resulting in a relatively reduced burden of edentulism \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDALYs of Edentulism\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFrom 1990 to 2023, the ASDR for edentulism increased in Brazil, rising from 237.50 (95% UI: 156.70\u0026ndash;327.10) to 240.10 (95% UI: 158.20\u0026ndash;319.90), and in the Russian Federation, where it climbed from 162.60 (95% UI: 104.80\u0026ndash;220.30) to 181.60 (95% UI: 118.10\u0026ndash;241.30). Nations such as China, India, and South Africa each noted considerable declines in their ASDRs. South Africa experienced the steepest decline, with the ASDR falling from 206.10 (95% UI: 127.60\u0026ndash;296.60) to 168.50 (95% UI: 104.10\u0026ndash;238.40) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOverall Trends\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOverall, the results of these measures show that Brazil consistently ranks first among the BRICS in terms of the burden of edentulism, followed by the Russian Federation and South Africa \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Trends of Edentulism from 1990 to 2023\u003c/h2\u003e\u003cp\u003eFrom 1990 to 2023, the age-standardized rates (ASRs) of edentulism among the BRICS countries exhibited varied and dynamic trends. A general overview of the long-term changes reveals significant heterogeneity in the ASPR, ASDR, and ASIR among the five nations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Brazil and the Russian Federation generally demonstrated the highest burden across all metrics, whereas China consistently showed the lowest rates. India and South Africa displayed intermediate and fluctuating trends throughout the period.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo more precisely identify and quantify key inflection points, a Joinpoint regression analysis was performed on the temporal trends of ASDR, ASIR, and ASPR.\u003c/p\u003e\u003cp\u003eThe analysis of ASDR revealed complex, non-linear trajectories. Brazil's trend was characterized by five joinpoints, with a period of sharp increase between 2005 and 2010 (APC\u0026thinsp;=\u0026thinsp;5.34), followed by a subsequent decline. The trend in India was similarly volatile, with a dramatic surge in burden from 2005 to 2010 (APC\u0026thinsp;=\u0026thinsp;19.04) before reversing into a steep decrease (APC = -10.53 from 2010 to 2017). In contrast, the Russian Federation exhibited a sustained upward trend across four joinpoints, with the most significant increase occurring between 2010 and 2014 (APC\u0026thinsp;=\u0026thinsp;3.41). China and South Africa, however, showed a predominantly declining trend, with China's ASDR decreasing at an APC of -3.22 from 1990 to 2000. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSimilar complex patterns were observed in the analyses of ASIR and ASPR. In the ASPR analysis, Brazil\u0026rsquo;s rate peaked between 2005 and 2010 (APC\u0026thinsp;=\u0026thinsp;6.14), while China\u0026rsquo;s ASPR demonstrated a consistent decline across five joinpoints, with a significant decrease between 1990 and 2000 (APC = -3.19). For ASIR, India again showed a pronounced peak from 2005 to 2010 (APC\u0026thinsp;=\u0026thinsp;15.38), and the Russian Federation's rate increased significantly between 2010 and 2014 (APC\u0026thinsp;=\u0026thinsp;1.10). (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Age, period, and cohort effects on Edentulism incidence rate\u003c/h2\u003e\u003cp\u003eThe longitudinal age curves reveal the age effect (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). A consistent pattern was observed across all BRICS nations, wherein the risk of edentulism incidence increased substantially and continuously with advancing age. This pattern was particularly pronounced in Brazil, the Russian Federation, and India, where the incidence rate began to accelerate after the age of 40, reaching its peak in the 80\u0026ndash;85 age group. While China's incidence followed a similar trajectory, its point of significant increase started later, at approximately 50 years of age. In contrast, the age-effect curve for South Africa, while also trending upward, was comparatively flatter, suggesting a lower peak incidence rate among its older population compared to the other BRICS nations.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB illustrates the period effects, revealing considerable heterogeneity in the relative risk (RR) of edentulism incidence across time. Brazil and India exhibited a similar and distinct non-linear pattern, marked by a significant increase in period-related risk that peaked around the 2005\u0026ndash;2010 period before subsequently declining. In contrast, South Africa and China both demonstrated a general downward trend in period RR over the three decades, indicating a reduction in risk attributable to period factors. The Russian Federation displayed the most stable pattern, with its period RR remaining relatively constant and close to the reference line throughout the study period.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC \u003cb\u003es\u003c/b\u003ehows that the cohort effects on past incidence risk have remained relatively stable in Brazil, India, and the Russian Federation. However, in China, there has been a gradual increase in incidence risk after the reference cohort (1949\u0026ndash;1954). In contrast, South Africa has shown a gradual decline in incidence risk after the reference cohort.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Decomposition of driving factors for the burden of Edentulism\u003c/h2\u003e\u003cp\u003eThe absolute number of DALYs, incident cases, and prevalent cases of edentulism increased across all BRICS nations from 1990 to 2023, with the most substantial increases detected in China and India. For the growth in DALYs, population aging was the primary driver in China, the Russian Federation, and Brazil, accounting for 90.6%, 78.8%, and 66.2% of the increase, respectively. In contrast, population growth was the main contributor in India (67.1%) and South Africa (82.6%). Epidemiological change exerted a mitigating, negative effect on the DALYs increase in India (-27.5%), China (-10.7%), and most notably in South Africa (-34.8%), but contributed positively in the Russian Federation (26.0%).\u003c/p\u003e\u003cp\u003eThis pattern was largely mirrored in the increase of prevalent cases. Population aging accounted for 91.0%, 79.2%, and 66.3% of the rise in prevalent cases in China, the Russian Federation, and Brazil, respectively. Meanwhile, population growth was the dominant factor in India (66.8%) and South Africa (89.9%). Notably, the Russian Federation was unique in that its population growth provided a negative contribution (-4.7%) to the increase in prevalent cases. A similar dynamic was observed for incident cases, where population aging was the most significant factor in China (86.8%) and the Russian Federation (87.9%), while population growth was the largest contributor in South Africa (89.9%) and India (67.4%) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.5. Future forecasts of the burden of disease in Edentulism\u003c/h2\u003e\u003cp\u003eUtilizing the BAPC model based on data from 1990\u0026ndash;2023, we projected ASIR, ASPR, and ASDR for edentulism in the BRICS countries up to 2050. The projections indicate divergent future trends among these nations \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-C\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSpecifically, the burden of edentulism is projected to continue increasing in the Russian Federation, Brazil, and China through 2050. By 2050, the projected ASIR, ASPR, and ASDR are expected to reach 377.3 (95% CI: 330.6\u0026ndash;424.0), 5186.2 (95% CI: 4470.9\u0026ndash;5901.5), and 138.7 (95% CI: 118.9\u0026ndash;158.6) per 100,000 in the Russian Federation, respectively. For Brazil, these rates are projected to be 637.9 (95% CI: 185.7\u0026ndash;1090.1), 8280.7 (95% CI: 364.6\u0026ndash;16196.8), and 224.0 (95% CI: 13.6\u0026ndash;434.3) per 100,000, respectively. China's projected rates are 246.6 (95% CI: 95.8\u0026ndash;397.5), 2393.9 (95% CI: 731.8\u0026ndash;4056.0), and 65.2 (95% CI: 19.8\u0026ndash;110.5) per 100,000, respectively.\u003c/p\u003e\u003cp\u003eConversely, India and South Africa are projected to exhibit stable or declining trends by 2050. India's ASIR, ASPR, and ASDR are projected to be 152.0 (95% CI: -47.1\u0026ndash;351.0), 1848.6 (95% CI: -1480.1\u0026ndash;5177.3), and 50.4 (95% CI: -40.1\u0026ndash;141.0) per 100,000, respectively, with the lowest projected ASDR among the BRICS nations. South Africa is expected to see declines, with projected rates of 198.1 (95% CI: 66.4\u0026ndash;329.8), 3861.3 (95% CI: 356.3\u0026ndash;7366.2), and 104.2 (95% CI: 9.6\u0026ndash;198.9) per 100,000 for ASIR, ASPR, and ASDR, respectively.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study provides a comprehensive assessment of the edentulism burden across the BRICS nations, revealing a profound heterogeneity in epidemiological trajectories from 1990 to 2023. Our primary finding is a stark divergence: while China and South Africa have made significant strides in reducing their age-standardized burden, Brazil and the Russian Federation continue to face a persistently high and, in some aspects, worsening challenge. Crucially, our analysis reveals that this epidemiological narrative is universally shaped by a powerful undercurrent of demographic change. The inexorable forces of population aging and growth are the principal drivers of the rising absolute number of cases across all five nations, a finding that significantly refashions the public health challenge from one of pure prevention to one of managing a growing, inevitable demand for care.\u003c/p\u003e\u003cp\u003eThese findings are broadly consistent with research showing a global decline in edentulism in many regions, yet they highlight that this progress is not uniform[18]. The sustained high burden in Brazil and the Russian Federation aligns with literature detailing challenges in their public health systems and significant socioeconomic disparities in access to dental care[19, 20]. Our decomposition analysis adds a critical layer of insight, revealing that Russia\u0026rsquo;s situation is uniquely compounded by an unfavorable epidemiological shift, suggesting that risk factor control or systemic healthcare access may have deteriorated over the period, beyond the impact of aging alone[20]. In contrast, the success observed in China likely reflects the positive impact of rapid economic development, improved public health infrastructure, and targeted national oral health programs[21]. Also, the results in South Africa may reflect the fact that South African populations tend to have lower consumption of free sugars[22]. Our analysis, however, uncovers a crucial nuance that distinguishes our findings: the Age-Period-Cohort model identified a concerning rise in incidence risk among younger birth cohorts in China. This novel observation suggests that new risk factors, such as dietary shifts towards higher sugar consumption, may be creating a future wave of oral disease that could undermine past public health achievements[23].\u003c/p\u003e\u003cp\u003eNotwithstanding its strengths, this study has several limitations. First and foremost, our analysis is contingent upon the accuracy of GBD-modeled estimates, which are themselves subject to uncertainty based on the quality and availability of primary data from each country[24]. The extreme volatility observed in India's data, for instance, may be a methodological artifact rather than a true epidemiological event, warranting a cautious interpretation of its trends. Second, the GBD framework analyzes data at the national level, which inevitably masks significant sub-national, regional, and socioeconomic disparities that are particularly pronounced in large and diverse nations like the BRICS[25]. Finally, our future projections are based on historical trends and cannot account for the potential impact of future policy shifts, disruptive technological innovations in dentistry, or major economic events.\u003c/p\u003e\u003cp\u003eThe implications of our findings for public health policy are twofold and demand tailored strategies. For nations with a high and sustained burden like Brazil and Russia, a renewed focus on primary prevention of caries and periodontal disease\u0026mdash;the main precursors to tooth loss\u0026mdash;is imperative[26]. However, for all BRICS nations, including those succeeding in epidemiological control like China, the demographic reality is inescapable. The dramatic increase in the absolute number of edentulous individuals, driven predominantly by population aging, signals an urgent need to reorient healthcare systems to meet a surging demand for prosthetic and geriatric dental services. This involves planning for infrastructure, workforce training, and financing models capable of managing a large elderly population requiring restorative care.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, despite the progress in reducing age-standardized rates in countries like China and South Africa, the absolute number of people affected by edentulism is projected to increase across the BRICS bloc, driven primarily by demographic transitions. The burden of edentulism is greatest in the elderly populations, with a notable emerging risk among younger birth cohorts in China. The BRICS countries face a substantial and growing absolute burden of edentulism, and public health policies must be adapted to manage both the primary prevention for at-risk younger cohorts and the surging prosthetic and geriatric dental care needs of an aging population.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from School \u0026amp; Hospital of Stomatology, Wuhan University [No. LYZX202002].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePublicly available datasets were analyzed in the present study. The original contributions presented in the study are included in the article and accompanying Supporting information. Further inquiries can be directed to the corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: M.Z., C.Z. Methodology: M.Z. Formal Analysis: M.Z., C.Z. Investigation: M.Z., C.Z. Data Curation: M.Z., C.L., B.Y., C.J.Z. Visualization: M.Z., C.L., Y.C., C.J.Z. Writing \u0026ndash; Original Draft: M.Z., C.Z. Writing \u0026ndash; Review \u0026amp; Editing: All authors. Supervision: Q.W. Project Administration: Q.W. Qilong Wan is the guarantor of this work. All authors have read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCunha-Cruz J, Hujoel PP and Nadanovsky P (2007) Secular trends in socio-economic disparities in edentulism: USA, 1972-2001. 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BMJ Glob Health 6. doi: 10.1136/bmjgh-2021-005847\u003c/li\u003e\n\u003cli\u003eAchoki T, Sartorius B, Watkins D, Glenn SD, Kengne AP, Oni T, Wiysonge CS, Walker A, Adetokunboh OO, Babalola TK, Bolarinwa OA, Claassens MM, Cowden RG, Day CT, Ezekannagha O, Ginindza TG, Iwu CCD, Iwu CJ, Karangwa I, Katoto PD, Kugbey N, Kuupiel D, Mahasha PW, Mashamba-Thompson TP, Mensah GA, Ndwandwe DE, Nnaji CA, Ntsekhe M, Nyirenda TE, Odhiambo JN, Oppong Asante K, Parry CDH, Pillay JD, Schutte AE, Seedat S, Sliwa K, Stein DJ, Tanser FC, Useh U, Zar HJ, Z\u0026uuml;hlke LJ, Mayosi BM, Hay SI, Murray CJL and Naghavi M (2022) Health trends, inequalities and opportunities in South Africa\u0026apos;s provinces, 1990-2019: findings from the Global Burden of Disease 2019 Study. J Epidemiol Community Health 76:471-81. doi: 10.1136/jech-2021-217480\u003c/li\u003e\n\u003cli\u003eHuang Y, Hao L, Li J, Guan W, Li S, Zhang Y, Xu X, Li J and Xu X (2025) Trends in incidence of untreated caries in permanent teeth in BRICS countries: an age-period-cohort analysis from 1992 to 2021 and projections for the next two decades. Clin Oral Investig 29:267. doi: 10.1007/s00784-025-06343-z\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":"BRICS countries, Edentulism, Disease burden, Age-period-cohort model, Bayesian age-period-cohort","lastPublishedDoi":"10.21203/rs.3.rs-7974581/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7974581/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAbstract\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eObjective This study analyzed long-term trends (1990–2023) and drivers of edentulism burden in BRICS nations (Brazil, Russia, India, China, South Africa) and projected the burden to 2050.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing GBD 2023 data, Joinpoint regression assessed trend turning points. Age-Period-Cohort (APC) modeling and decomposition analysis quantified contributions from population growth, aging, and epidemiological changes. The Bayesian APC (BAPC) model projected future burden.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResult\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEdentulism burden was heterogeneous. Age-standardized rates (ASRs) were high/increased in Brazil and Russia but declined in China, India, and South Africa. Population aging was the primary driver of absolute burden increases in China, Russia, and Brazil; population growth was key in India and South Africa. APC analysis revealed rising risk in younger Chinese cohorts. Projections suggest continued burden increases for Russia, Brazil, and China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe absolute edentulism burden is rising in all BRICS nations, driven by demographic transitions. Divergent epidemiological trends and emerging risk in younger Chinese cohorts necessitate dual strategies: strengthening prevention for the young and preparing health systems for surging geriatric/prosthetic dental care demand.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Relevance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlthough age-standardized risk is declining in some BRICS nations, the absolute number of edentulous individuals is surging, driven by population aging. Clinicians and health systems must prepare for a rising demand for prosthetic/geriatric dental services. The identified risk in younger Chinese cohorts signals an urgent need to intensify primary prevention, focusing on controlling caries and periodontal disease.\u003c/p\u003e","manuscriptTitle":"Temporal changes in the burden of Edentulism across the BRICS, 1990-2023: a comprehensive analysis for the global burden of disease study 2023","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-24 11:30:24","doi":"10.21203/rs.3.rs-7974581/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":"8add07a7-98c2-47f9-923c-403cf3193a8a","owner":[],"postedDate":"November 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-15T00:08:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-24 11:30:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7974581","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7974581","identity":"rs-7974581","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}