Burden of lip and oral cavity cancer among young people across South, East, and Southeast Asia: trends from 1990 to 2021 and predictions to 2030

Background: Lip and oral cavity cancer (LOC) is a major public health challenge in Asia. Nevertheless, a critical gap remains in understanding the epidemiological burden of LOC among young people (15–44 years) in the region. This study aims to analyze the burden and risk factors of LOC in this age group across the four Global Burden of Disease (GBD) Asian regions from 1990 to 2021 and projects trends to 2030.

Methods: Data on the incidence, deaths, disability-adjusted life years (DALYs), and risk factors of LOC from 1990 to 2021 were obtained from the GBD 2021 study for East, South, Southeast Asia, and High-income Asia Pacific. This study assessed the LOC burden among young people (15–44 years) through age- and sex-stratified analyses, evaluated temporal trends via joinpoint regression, examined risk factor contributions, and projected trends to 2030 using the Nordpred age-period-cohort model.

Results: From 1990 to 2021, the age-standardized incidence rate (ASIR) increased across all subregions, with the largest rise in East Asia. In contrast, age-standardized mortality rate (ASMR) and age-standardized DALYs rate declined everywhere except South Asia. In 2021, South Asia bore the heaviest LOC burden among young people in the four Asian subregions. India reported the highest incident cases, deaths, and DALYs in 2021, and Pakistan had the highest ASR for all three metrics. Taiwan (Province of China) showed the largest increase in ASRs over the period. In 2021, smoking had the highest contribution in East Asia, alcohol use in High-income Asia Pacific, and chewing tobacco in South Asia. Projections to 2030 indicate rising ASIR in East, South, and Southeast Asia but declines in High-income Asia Pacific; decreasing ASMR everywhere except South Asia; and increasing age-standardized DALYs rate in East and South Asia but decreases elsewhere.

Conclusions: LOC imposes a substantial and growing burden on young people in South, East, and Southeast Asia, marked by rising ASIR since 1990 and projected increases through 2030. South Asia faces the most urgent challenge with concurrent rises in incidence, mortality, and DALYs—most notably in the 20–24 age group. Region-specific interventions targeting predominant risk factors are critically needed.

1 Introduction

Lip and oral cavity cancer (LOC) presents a significant and evolving global public health challenge. While traditionally associated with older populations, compelling evidence now confirms an alarming rise in incidence among younger individuals globally (1). A recent study showed that from 1990 to 2021, incidence, mortality, and disability-adjusted life-years (DALYs) rates of LOC and pharyngeal cancers grew among people aged 15–39 worldwide (2). This trend highlights the unique vulnerabilities of adolescence and early adulthood, as well as widening geographic and gender disparities. It signals a distinct clinical entity potentially reflecting complex gene-environment-behavior interactions in modern societies. Notably, the burden is most acute in Asia, where our prior analysis of Global Burden of Disease (GBD) 2021 data indicates that South and East Asian countries carry a disproportionately high LOC burden among younger populations (1). While existing studies, including the aforementioned global analysis of 15–39-year-olds and national or regional reports from China (3), India (4), Iran (5), Brazil (6), and other BRICS nations (7), have described the overall burden, most focus on broader age groups or national-level data, obscuring key subregional differences. For instance, a recent analysis by Lin et al. examined the spatiotemporal patterns and risk factors of LOC across all age groups in Asia (8). While their study provides important insights into the continent’s overall epidemic, it does not isolate the burden on young people—an age group with distinct risk factors and life-course considerations. As a result, the specific burden of early-onset LOC across Asian subregions is poorly understood, hindering the development of targeted prevention strategies.

To fill this gap, we analyzed GBD 2021 data, focusing on individuals aged 15–44 in East Asia, Southeast Asia, South Asia, and the High-income Asia Pacific. We report age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and age-standardized DALYs rate, enabling comparisons across regions and uncovering heterogeneity hidden in aggregate data. In addition to current estimates, we applied Nordpred age-period-cohort (APC) model to project trends through 2030 for this vulnerable group. This combined approach—capturing both current burden and future trajectories—offers novel insights into early-onset LOC in Asia. Our findings provide essential evidence to guide regionally tailored prevention strategies, inform health policy, and optimize resource allocation to reduce the growing burden among young people in high-risk Asian regions.

2 Materials and methods

2.1 Data sources

The GBD 2021 comprehensively evaluates health impairments of 371 diseases and injuries and 88 risk factors. Its methodology for disease burden estimation is detailed in previous studies (9, 10). Data on LOC incidence, deaths, DALYs, their corresponding age-standardized rate (ASR), and risk factors were extracted from the GBD 2021 study (https://vizhub.healthdata.org/gbd-results/). This study focused on young people aged 15–44 years (stratified by 5-year age groups from 15–19 to 40-44) across four Asian subregions: East Asia, South Asia, Southeast Asia, and High-income Asia Pacific. The age range of 15–44, defined as “young people” in recent GBD publications (11), was selected to capture the burden of early-onset LOC and represent the transition from adolescence to adulthood. A complete list of countries in each subregion is provided in Supplementary Table 1.

The Global Cancer Observatory (GLOBOCAN) 2022 project provides estimates for 36 cancer types across 185 countries and regions, including data on cancer incidence, mortality, and mortality-to-incidence ratios. To assess the reliability of the data used in this study, validation and consistency analysis was conducted against the corresponding estimates from GLOBOCAN 2022 (12). All GLOBOCAN 2022 data were sourced from the Cancer Today platform (https://gco.iarc.who.int/today/en/dataviz/tables). The research followed the Guidelines for Accurate and Transparent Health Estimates Reporting (13). As the data employed were publicly available, ethical review and informed consent were waived.

2.2 Definition of LOC

In the GBD 2021, LOC was defined using codes C00 to C08 in alignment with the corresponding International Classification of Diseases and Related Health Problems, Tenth Revision (ICD 10) (9).

2.3 Statistical analyses

2.3.1 Descriptive analysis

The epidemiological burden of LOC among young people (15–44 years) in four Asian subregions was assessed from 1990 to 2021 through analysis of case counts and ASR of incidence, deaths, and DALYs, stratified by sex and age. All rates were expressed per 100,000 population, and the GBD 2021 world standard population was used for age standardization (9).

2.3.2 Trend analysis

Investigating temporal trends in disease burden is crucial to epidemiology, facilitating the development of tailored preventive strategies. Joinpoint regression analysis is commonly employed in epidemiological research to assess such trends in incidence or mortality rates (14). In this study, this method was applied to analyze the temporal trends in the ASIR, ASMR, and age-standardized DALYs rate of LOC from 1990 to 2021. This analysis involved key steps: first, the Grid Search Method (GSM), the default approach in Joinpoint regression, is employed to identify all potential joinpoints for segmented interval functions. In this process, GSM divides the parameter space into grids, calculates the Sum of Squared Errors (SSE) and Mean Squared Error (MSE) for each scenario, and selects the grid point with the minimum MSE as the optimal joinpoint. Subsequently, the optimal number of joinpoints is determined using the Monte Carlo permutation test (see Supplementary Methods) (14). Detailed information on joinpoint regression methodology is available on its official website (https://surveillance.cancer.gov/joinpoint/). The model calculated the average annual percent change (AAPC). An AAPC >0 indicates an increasing trend in ASR, while AAPC <0 reflects a decreasing trend. If the AAPC is not statistically different from zero, the trend is considered stable. The model fit was evaluated through residual analysis, where an average relative error ≤10.00% between observed and fitted values indicated a good fit (15). Additionally, a sensitivity analysis was performed using the lower and upper bounds of the data to test the robustness of the findings against potential fluctuations.

2.3.3 Attributable risk factors

This study further analyzed the proportion of LOC deaths and DALYs attributable to smoking, alcohol use, and chewing tobacco. Within the GBD 2021 framework, the selection of these risk factors was based on their risk-outcome pairs meeting the World Cancer Research Fund grades of convincing or probable evidence. The theoretical minimum risk exposure level was defined as lifelong non-use for smoking and chewing tobacco, while for alcohol use, it was defined as a daily intake distribution ranging from 0 to 10 grams (10). Additionally, the AAPC was employed to assess the temporal trends in the contribution of these risk factors from 1990 to 2021.

2.3.4 Prediction

The Nordpred APC model was used to predict future trends in the burden of LOC among young people across four Asian subregions, including projections of incidence, death, and DALY counts and ASR from 2022 to 2030. Population data for projections were obtained from the 2024 revision of the World Population Prospects (https://population.un.org/wpp/). The reliability of the Nordpred model has been validated in previous studies (16, 17). Sensitivity analysis and residual analysis were performed as described in section 2.3.2 to evaluate model robustness and fit.

2.3.5 Software and statistical tools

Statistical analyses were performed using R software (version 4.4.1) with the “Nordpred” package for age-period-cohort modeling and the “ggplot2” package for data visualization, as well as Joinpoint regression software (version 5.2.0) for trend analysis.

3 Results

3.1 Regional burden and trends of LOC in young people

In 2021, South Asia had the heaviest LOC burden among young populations across the four Asian subregions, with 26,729 incident cases, 11,922 deaths, and 650,469 DALYs, accounting for over half of the corresponding global totals. Its ASIR, ASMR, and age-standardized DALYs rate all exceeded twice the global averages. Conversely, High-income Asia Pacific recorded the lowest case numbers and ASR for deaths and DALYs, and East Asia had the lowest ASIR. From 1990 to 2021, the ASIR demonstrated increasing trends across all subregions, with East Asia exhibiting the most pronounced increase. In contrast, the ASMR and age-standardized DALYs rate showed declining trends in most subregions, except for South Asia (Figure 1, Tables 1–3).

Figure 1

Figure 1. The temporal trends of the age-standardized rate of incidence (A), deaths (B), and DALYs (C) of lip and oral cavity cancer among young people across four Asian subregions. AAPC, average annual percent change; DALYs, age-standardized disability-adjusted life years.

Table 1

Table 1. Number of cases and ASR of LOC incidence among young people in 1990 and 2021, at global, Asian four regional and national level, along with AAPC from 1990 to 2021.

Table 2

Table 2. Number of cases and ASR of LOC mortality among young people in 1990 and 2021, at global, Asian four regional and national level, along with AAPC from 1990 to 2021.

Table 3

Table 3. Number of cases and ASR of LOC DALYs among young people in 1990 and 2021, at global, Asian four regional and national level, along with AAPC from 1990 to 2021.

The residual analysis confirmed an excellent model fit, with average relative errors consistently below 10.00% (Supplementary Table 2). Furthermore, sensitivity analyses using the lower and upper bounds of the data produced similar trend patterns (Supplementary Table 3). These findings confirmed the reliability and robustness of the trend analysis methods.

3.2 National burden and trends of LOC in young people

At the national level across the four Asian subregions, India had the highest case numbers of LOC incidence, deaths, and DALYs among young people in 2021, followed by Pakistan. Seychelles reported the lowest counts for these indicators. Pakistan exhibited the highest ASIR, ASMR, and age-standardized DALYs rate, while Timor-Leste showed the lowest ASIR and Singapore demonstrated the lowest ASMR and age-standardized DALYs rate. From 1990 to 2021, Taiwan (Province of China) experienced the most pronounced increases in ASIR, ASMR, and age-standardized DALYs rate. Conversely, Philippines demonstrated the largest decrease in ASIR, Singapore in ASMR, and Maldives in age-standardized DALYs rate (Tables 1–3). According to GLOBOCAN 2022, India recorded the highest incidence and mortality cases of LOC among young people in 2022 (Supplementary Table 4), followed by Pakistan. The two countries also ranked first and second, respectively, in both ASIR and ASMR. These findings are consistent with the results from GBD 2021. Furthermore, the countries with a relatively low burden were similar across both databases (Supplementary Table 4).

3.3 Regional sex- and age-specific burden and trends

Globally, young men had higher numbers and ASR of LOC incidence, deaths, and DALYs than women. This gender disparity persisted across four Asian subregions, particularly in East Asia, where men’s ASR was more than three-fold higher than women’s (Supplementary Table 5). Temporal trends revealed distinct subregional patterns in gender-specific LOC burden. In East Asia, men showed upward trends in ASIR, ASMR, and age-standardized DALYs rate, while women had declining ASMR and age-standardized DALYs rate. Conversely, in the High-income Asia Pacific, women experienced rising trends in all three metrics, whereas men exhibited decreasing trends in ASMR and age-standardized DALYs rate. In South Asia, both genders exhibited increases in ASR for all three metrics. Uniform trends were observed in Southeast Asia, with rising ASIR but declining ASMR and age-standardized DALYs rate for both sexes.

Across the four Asian subregions, both the number of cases and ASR of LOC incidence, deaths, and DALYs among individuals aged 15–44 years increased with age, consistent with global patterns (Supplementary Tables 6–8). From 1990 to 2021, the ASIR showed a rising trend across all age subgroups in each of the four subregions. For ASMR and age-standardized DALYs rate, East Asia and Southeast Asia exhibited decreasing trends across all age groups, with the most significant decrease in the 15–19 age group. High-income Asia Pacific showed consistent ASMR and age-standardized DALYs rate trends across age groups, with some increasing and others decreasing; the largest rise was in the 35–39 age group and the steepest decrease was in the 15–19 age group. In contrast, South Asia experienced increasing trends in both ASMR and age-standardized DALYs rate across all age groups, with the most pronounced rise in the 20–24 age group.

3.4 Risk factors

From 1990 to 2021, the overall contribution of all risk factors to LOC deaths and DALYs in young people increased in East Asia and Southeast Asia, while decreasing in High-income Asia Pacific and South Asia (Figure 2). Regarding specific risk factors, the contribution of smoking declined in all subregions except East Asia, while alcohol use increased in all subregions except High-income Asia Pacific. Chewing tobacco slightly increased in most regions but declined in South Asia. In 2021, the distribution of risk factor contributions to LOC deaths and DALYs among young populations varied significantly across the four subregions. Smoking had the highest contribution in East Asia, alcohol use in High-income Asia Pacific, and chewing tobacco in South Asia. Notably, alcohol use was the primary attributable risk factor for LOC deaths and DALYs among young populations in East Asia, High-income Asia Pacific, and Southeast Asia, whereas chewing tobacco predominant factor in South Asia. Across most studied countries, the contribution of smoking to LOC deaths and DALYs decreased, while the contributions of alcohol use and chewing tobacco increased. In 2021, smoking accounted for the largest proportion in China and Taiwan (Province of China). Alcohol use contributed over 30% in ten countries, with the highest in the Republic of Korea. Chewing tobacco’s contribution remained below 5% in most countries but reached approximately 30% in Bangladesh, India, and Nepal, peaking in Nepal.

Figure 2

Figure 2. Comparison of attributable risk factors for lip and oral cavity cancer deaths and DALYs among young people, 1990 and 2021. DALYs: age-standardized disability-adjusted life years.

Stratified by age group, from 1990 to 2021, the contributions of all risk factors to LOC deaths and DALYs among young populations increased in most age groups. This increase was most pronounced in the 25–29 age group in East Asia, and in the 15–19 age group in South Asia and Southeast Asia (Figures 3, 4). Regarding smoking, its contribution showed a decreasing trend across most age groups in the four subregions. In contrast, the contributions of alcohol use demonstrated an increasing trend in all age subgroups in East Asia, South Asia, and Southeast Asia. The largest increases were observed in the 25–29 age subgroup in East Asia, the 15–19 age group in South Asia, and the 40–44 age group in Southeast Asia. As for chewing tobacco, its contribution increased across all age groups in East Asia and the High-income Asia Pacific, but decreased in South Asia and Southeast Asia.

Figure 3

Figure 3. AAPC of lip and oral cavity cancer ASMR attributable to each risk factor among young people (1990–2021), by age group. AAPC, average annual percent change; ASMR, age-standardized mortality rate.

Figure 4

Figure 4. AAPC of lip and oral cavity cancer age-standardized DALYs rate attributable to each risk factor among young people (1990–2021), by age group. AAPC, average annual percent change; DALYs, disability-adjusted life-years.

3.5 Prediction to 2030

Nordpred models projected rising LOC incidence, deaths, and DALYs among young people in East, South, and Southeast Asia from 2022 to 2030, with South Asia showing the greatest increase (Figure 5, Supplementary Table 9). In contrast, the High-income Asia Pacific was predicted to exhibit consistent declines across all three indicators. As for the ASR, the ASIR was predicted to increase by 9.00% in East Asia, 7.54% in South Asia, and 6.87% in Southeast Asia, while declining 9.93% in High-income Asia Pacific. The ASMR was predicted to decrease annually in most subregions, except South Asia. Similarly, the age-standardized DALYs rate was projected to increase in East Asia and South Asia, while decreasing in High-income Asia Pacific and Southeast Asia. Sensitivity analyses using the lower and upper bounds of the data showed similar predicted trends, supporting the reliability of the projections (Supplementary Tables 10, 11). Furthermore, residual analysis indicated an excellent model fit, with average relative errors well within the 10.00% threshold (Supplementary Table 12).

Figure 5

Figure 5. The projected global case numbers and ASR of lip and oral cavity cancer among young people to 2030. (1) The predicted case number of incidence (A), deaths (B), and DALYs (C); (2) The predicted ASR of incidence (D), deaths (E), and DALYs (F). ASR, age-standardized rate; DALYs, disability-adjusted life-years.

4 Discussion

South Asia remains the clear epicenter of early-onset LOC among young people (15–44 years) within the Asian subregions studied, with India and Pakistan as key hotspots. This aligns with Lin et al.’s findings, which identified South Asia as having the highest age-standardized DALY rate for LOC across all age groups in Asia (8). However, our age-stratified analysis reveals that the region’s high burden is driven by a distinct, adverse trend among young people: concurrent increases in the ASIR, ASMR, and age-standardized DALY rates—a pattern not observed in other subregions and not discernible in the all-age data. This escalation is particularly pronounced in the 20–24 age group. Furthermore, our application of the Nordpred model predicts a continued rise in these rates through 2030, offering new insights into the future trajectory of the epidemic. These findings indicate that the public health crisis in South Asia is not static but evolving, with a growing burden on young people that calls for targeted interventions.

Among Asian youth, the burden of LOC is heavily concentrated in South Asia—the only subregion exhibiting concurrent increases in ASIR, ASMR, and age-standardized DALYs rate. A global multicenter study supports this, reporting that Manipal, India, had the highest proportion of young oral squamous cell carcinoma (OSCC) patients (13.2%) among all institutions surveyed, highlighting the regional burden (18). Data from India’s National Cancer Registry Programme (NCRP) reaffirm that mouth and tongue cancer is a leading malignancy among adolescents and young adults (30–39 years), underscoring the persistent disease burden (19). India accounted for the highest case numbers of LOC incidence, deaths, and DALYs, attributable to its large population and the widespread consumption of smokeless tobacco (SLT) products, including khaini, gutka, and mawa (20). Our findings further validate chewing tobacco (a major SLT type) as the predominant risk factor for LOC deaths and DALYs among youth in this subregion. Despite a national gutka ban in 2011, illicit sales persist, sustaining high SLT use among youth (21). Regional disparities are marked, with states like Meghalaya and Gujarat showing extreme rates (22). In Pakistan, naswar—a widely used SLT product—accounts for nearly 70% of LOC cases in Khyber Pakhtunkhwa (23). This is supported by a recent hospital-based case-control study, which showed that naswar use significantly increases the risk of oral cancer (AOR = 6.83) (24). Compounding SLT’s impact, delayed diagnosis due to strained healthcare and limited public awareness worsens outcomes, while genetic vulnerabilities (GSTM1 and/or GSTT1 null genotypes and CYP1A1 variants) and HPV co-infection further amplify risks (25, 26).

Conversely, East and Southeast Asia demonstrate divergent epidemiological trends where rising ASIR coexist with declining ASMR and age-standardized DALYs rate. This pattern reflects distinct risk factor profiles and superior healthcare capacity. Particularly concerning is East Asia’s steep ASIR increase from 1990–2021, primarily driven by smoking (per GBD models) and emerging areca nut use—the latter being a major risk factor absent from GBD’s traditional framework. In Hunan, China, youth increasingly chew dried areca husk and swallow the juice—a high-risk behavior (27). In Taiwan (Province of China), youth experienced the steepest global increases in ASIR, ASMR, and age-standardized DALYs rate, despite declining areca nut use. This likely reflects legacy effects, as past chewers still face high risks (up to 137-fold for oral preneoplastic disorders) due to the long latency of oral carcinogenesis (27). Overall, the distribution of LOC in Asian youth closely follows regional patterns of SLT, areca nut, alcohol, and smoking, shaped by healthcare disparities and exacerbated by gene–virus interactions. Early, targeted interventions are urgently needed to curb this preventable burden.

From 1990 to 2021, South Asia showed the most pronounced early-onset LOC increase, particularly in 20–24-year-olds, while the proportion of non-smoking, non-drinking among OSCC cases continued to increase (28). These trends challenge traditional models of carcinogenesis, which assume prolonged exposure to smoking or alcohol. The risk profile of LOC is complex, with distinct regional patterns. While tobacco control has effectively reduced smoking-related burdens, the peak age-group attribution to alcohol varied by subregion (East Asia: 25–29; South Asia: 15–19; Southeast Asia: 40–44), and trends for chewing tobacco diverged (decreasing in South/Southeast Asia but increasing elsewhere). Alongside traditional factors, SLT and areca nut are established key causative agents. In 2022, they accounted for 31% of global LOC cases, primarily in lower-middle-income countries (29). Some products, like naswar, can increase LOC risk over 11-fold, though youth-specific data are scarce (30). Beyond these exogenous risk factors, emerging evidence highlights the role of biological mechanisms, particularly in early-onset and non-habit-related cases. First, HPV is an important causative factor of LOC. A recent systematic review across 11 Asian countries found the highest pooled HPV prevalence in OSCC in South Asia (27.1%), followed by East Asia (19.4%) and Southeast Asia (16.7%). Two subtypes—HPV-16 (9.1%) and HPV-18 (5.1%)—were most common (31). The E6 and E7 genes of high-risk HPV types can integrate into the host genome, disrupting cell proliferation and apoptosis through p53 degradation, retinoblastoma protein binding, and other mechanisms, promoting carcinogenesis (32). Second, genetic susceptibility is crucial. CASP8 mutations linked to impaired apoptosis (33), display widespread CpG island methylation (34), or carry undiagnosed Fanconi anemia (a condition conferring a 500-fold increased LOC risk) (35). Additionally, environmental exposure to tobacco smoke affects young women and is associated with tongue cancers (36). Microbial dysbiosis—marked by increased Fusobacterium, Prevotella, and Alloprevotella in young non-smokers—may drive inflammation, though causality is unclear (37). The coexistence of these diverse risk factors—ranging from substance use to infections and genetic predispositions—requires a multifaceted public health approach. In regions like South and Southeast Asia, where SLT and areca nut are major drivers, enforcing existing product bans is crucial. Globally, there is a pressing need to include areca nut control in cancer prevention policies. At the clinical level, screening protocols should be refined, such as prioritizing FANCA mutation testing in young, non-smoking, non-drinking patients to identify high-risk individuals early.

Globally, while young males exhibit a persistent male predominance in LOC incidence, mortality, and DALYs, females experienced significantly accelerated growth rates from 1990 to 2021 among young people (ASIR: +1.19% vs +0.67%; ASMR: +0.55% vs +0.21%; age-standardized DALYs rate: +0.59% vs +0.25%). Across Asian subregions, however, sex-specific trajectories diverge markedly: South Asia and High-income Asia Pacific mirror this global acceleration with female AAPC exceeding males (ASIR: female +1.13% vs male +1.05% in South Asia; female +1.89% vs male +1.32% in High-income Asia Pacific). Notably, East Asia exhibits the most extreme disparity, where male ASRs are over three times higher than those of females—largely attributable to higher rates of smoking and alcohol use among men (38). This shifting epidemiology within Asia finds parallels in independent global reports. A study of 89,212 tongue squamous cell carcinoma cases across 22 registries worldwide found a higher incidence increase among those under 45 in most regions, with a significant sex-based disparity in half of the registries. This suggests a broader shift toward younger individuals and women (39). Notably, analyses of cancer age distributions have identified oral cavity cancer as the only subsite showing a true increase in the proportion of young patients (0–39 years), strongly linked to rising incidence among young women (40). These external observations provide critical context and support for our region-specific findings, indicating that the rising burden among young women in parts of Asia is part of an emerging, though not universal, global pattern. The exacerbation of this burden in South Asia and high-income Asia-Pacific regions highlights a convergence of biological and structural vulnerabilities, which may be amplified in specific settings. First, hormonal dualism: estrogen can both suppress inflammation and promote tumor growth via ER-α overexpression, which is linked to worse prognosis in young women (41, 42). Second, women’s higher susceptibility to autoimmune disorders may compromise antitumor immunity (43). Third, HPV–sex interactions: although HPV-positive OSCC is more common in men, HPV-negative tumors—which are more frequent in women—tend to have poorer outcomes, suggesting intrinsic vulnerability (44, 45). In addition, diagnostic disparities may compound risk. These findings highlight the urgent need for sex-specific strategies, including routine screening for women regardless of behavioral history, targeted public health messaging on non-traditional exposures, and expanded research into sex-related biological mechanisms.

Nordpred projections show that LOC burden among youth (15–44 years) will rise across Asia from 2022 to 2030, with South Asia facing the steepest increases in incidence, mortality, and DALYs. In contrast, High-income Asia Pacific is expected to see steady declines, reflecting stronger health systems and preventive strategies. Population growth remains a key driver of global LOC burden and is projected to continue contributing to rising cases (46). According to the United Nations’ medium-variant projection (47), South Asia’s youth population (15–44 years) will grow by 7.18% and Southeast Asia’s by 3.51% by 2030, while East Asia’s will decline by 4.69%, potentially curbing its overall case growth. In resource-limited settings, the rising burden is exacerbated by weak screening systems. Although conventional visual and tactile examination (CVTE) is fast, affordable, and effective, screening rates remain under 40% (48), slowed by poor access and provider shortages. This hampers progress toward early detection goals outlined in the Global Strategy and Action Plan on Oral Health 2023–2030 (49), which emphasizes prevention, governance, improved data systems, and research. CVTE is especially valuable in high-incidence regions such as South Asia, where the risk posed by missed cases exceeds that of false positives. Meanwhile, HPV-driven LOC remains largely preventable, but many Asian countries have yet to integrate the HPV vaccine into national immunization programs (50). Barriers such as cost, logistics, regulation, and cultural resistance continue to limit uptake, especially among youth. High-income Asia Pacific’s declining burden likely stems from effective strategies: routine CVTE as part of dental care, supportive billing practices, and strong HPV vaccination programs. South Asia must adopt similar models, as its rising youth population, weak screening, and limited vaccine infrastructure create a perfect storm for a rising burden.

This study has several limitations. First, the accuracy of our estimates depends on the completeness and quality of the underlying source data. Biases may arise from underdiagnosis and variations in cancer registry coverage, especially in resource-limited settings. While the GBD’s modeling approach cannot replace local validation, the strong concordance of our core findings (e.g., regional burden rankings) with the GLOBOCAN database increases confidence that these macro-geographical patterns reflect a robust epidemiological reality. Second, the exclusion of areca nut as a distinct risk factor in GBD modeling limits the precise quantification of its burden in high-consumption regions. Third, the lack of data on anatomical sub-sites restricts deeper etiological analysis. Despite these limitations, our analysis offers a crucial macro-epidemiological perspective. Future research that integrates these high-level trends with localized primary data will be invaluable for validating and contextualizing our findings.

5 Conclusion

This study reveals three critical patterns in early-onset LOC burden among young people (15–44 years) across Asia: 1) South, East, and Southeast Asia carry persistently high burdens with steadily increasing ASIR from 1990 to 2021; 2) Projections indicate continued ASIR growth through 2030; and 3) South Asia exhibits the most concerning trajectory, with concurrent rises in ASIR, ASMR, and age-standardized DALYs rate—particularly in the 20–24 age group—while other subregions show declining mortality and DALYs rates. Within this landscape, India and Pakistan remain key hotspots. Addressing this escalating crisis demands urgent, subregion-specific interventions tailored to dominant risk factors. Simultaneously, the global health community must coordinate action through expanded research on early-onset aetiology, stronger international regulation of tobacco and alcohol targeting youth, and increased investment in surveillance and screening infrastructure.

Data availability statement

Publicly available datasets were analyzed in this study. This data can be found here: https://vizhub.healthdata.org/gbd-results/.

Author contributions

HC: Conceptualization, Data curation, Methodology, Software, Visualization, Writing – original draft. MH: Investigation, Methodology, Software, Validation, Writing – original draft. MF: Investigation, Writing – original draft. XC: Formal analysis, Writing – original draft. XG: Methodology, Writing – review & editing. JG: Conceptualization, Funding acquisition, Supervision, Writing – review & editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This study was funded by the Natural Science Foundation of Hunan Province (No. 2024JJ9532; No. 2025JJ80524), Natural Science Foundation of Changsha City (No. kq2403178; No. kq2502307), The Scientific Research Project of Hunan Health Commission (No. D202313048136), Chinese Medicine Research Project of Hunan Province (No. B2023048), and Joint Fund of Universities and Colleges (No. 2025XYLH236).

Acknowledgments

We appreciate the GBD 2021 collaborators for their excellent work and selfless sharing.

Conflict of interest

The authors declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2025.1680008/full#supplementary-material

References

1. Hu M, Chen H, Wang R, Zhang R, Yao J, Qiu X, et al. Global, regional, and national burden of lip and oral cavity cancer and its attributable risk factors from 1990 to 2021: an analysis of the Global Burden of Disease study 2021. Int J Clin Pharm. (2025). doi: 10.1007/s11096-025-01961-9

PubMed Abstract | Crossref Full Text | Google Scholar

2. Dai R, Zhang Y, Zou H, Li H, and Zhang S. Increased burden of lip, oral, and pharyngeal cancer in adolescents and young adults from 1990 to 2021. BMC Oral Health. (2025) 25:758. doi: 10.1186/s12903-025-06166-0

PubMed Abstract | Crossref Full Text | Google Scholar

3. Yu Z, Ma X, Xiao H, Chen Y, Wu Y, He J, et al. Disease burden and attributable risk factors of lip and oral cavity cancer in China from 1990 to 2021 and its prediction to 2031. Front Public Health. (2024) 12:1419428. doi: 10.3389/fpubh.2024.1419428

PubMed Abstract | Crossref Full Text | Google Scholar

4. Akashanand, Zahiruddin QS, Jena D, Ballal S, Kumar S, Bhat M, et al. Burden of oral cancer and associated risk factors at national and state levels: A systematic analysis from the global burden of disease in India, 1990-2021. Oral Oncol. (2024) 159:107063. doi: 10.1016/j.oraloncology.2024.107063

PubMed Abstract | Crossref Full Text | Google Scholar

5. Roghanizadeh L, Atarbashi-Moghadam S, Masaebi F, and Baghban AA. Lip and oral cavity cancer in Iran from 1990 to 2019 based on the global burden of disease study. Sci Rep. (2025) 15:7389. doi: 10.1038/s41598-025-92090-w

PubMed Abstract | Crossref Full Text | Google Scholar

6. Romagna DV, Oliveira MMD, Abreu LG, Stein C, Hugo FN, Teixeira R, et al. Incidence and mortality rates of lip, oral cavity, and pharynx cancers in Brazil: time-trend and age-period-cohort analysis from the last 30 years, Global Burden of Disease Study. Rev Soc Bras Med Trop. (2022) 55:e0286. doi: 10.1590/0037-8682-0286-2021

PubMed Abstract | Crossref Full Text | Google Scholar

7. Yu Z, Wu Y, Cao Y, and Cheng P. Epidemiological trends and age-period-cohort effects on lip and oral cavity cancer burden across the BRICS from 1992 to 2021. Front Oncol. (2025) 15:1539417. doi: 10.3389/fonc.2025.1539417

PubMed Abstract | Crossref Full Text | Google Scholar

8. Lin D, Lu X, Ma R, and Zeng X. Spatiotemporal dynamics in the burden of lip and oral cavity cancer and attributable risk factors in asia (1990-2021). Healthcare (Basel). (2025) 13(12):1377. doi: 10.3390/healthcare13121377

PubMed Abstract | Crossref Full Text | Google Scholar

9. GBD 2021 Diseases and Injuries Collaborators. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet. (2024) 403:2133–61. doi: 10.1016/S0140-6736(24)00757-8

PubMed Abstract | Crossref Full Text | Google Scholar

10. GBD 2021 Risk Factors Collaborators. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet. (2024) 403:2162–203. doi: 10.1016/S0140-6736(24)00933-4

PubMed Abstract | Crossref Full Text | Google Scholar

11. Tian P, Zhao H, Wang B, Chen Y, Jia Z, Wang C, et al. Global burden of gout among young people from 1990 to 2021, with projections for 2050: A systematic analysis based on the Global Burden of Disease Study 2021. PloS One. (2025) 20:e0333368. doi: 10.1371/journal.pone.0333368

PubMed Abstract | Crossref Full Text | Google Scholar

12. Pan T, Zhang J, Wang X, and Song Y. Global burden and trends of hematologic Malignancies based on Global Cancer Observatory 2022 and Global Burden of Disease 2021. Exp Hematol Oncol. (2025) 14:98. doi: 10.1186/s40164-025-00684-x

PubMed Abstract | Crossref Full Text | Google Scholar

13. Stevens GA, Alkema L, Black RE, Boerma JT, Collins GS, Ezzati M, et al. Guidelines for accurate and transparent health estimates reporting: the GATHER statement. PloS Med. (2016) 13:e1002056. doi: 10.1371/journal.pmed.1002056

PubMed Abstract | Crossref Full Text | Google Scholar

14. Kim HJ, Fay MP, Feuer EJ, and Midthune DN. Permutation tests for joinpoint regression with applications to cancer rates. Stat Med. (2000) 19:335–51. doi: 10.1002/(sici)1097-0258(20000215)19:3<335:aid-sim336>3.0.co;2-z

PubMed Abstract | Crossref Full Text | Google Scholar

15. Yao CZ, Zhang M, Zeng YK, Zhang YY, Wu X, Xiong WJ, et al. Analysis and prediction of thyroid cancer morbidity and mortality trends in China. Zhonghua Liu Xing Bing Xue Za Zhi. (2023) 44:917–23. doi: 10.3760/cma.j.cn112338-20221010-00869

PubMed Abstract | Crossref Full Text | Google Scholar

16. Li S, Chen H, Man J, Zhang T, Yin X, He Q, et al. Changing trends in the disease burden of esophageal cancer in China from 1990 to 2017 and its predicted level in 25 years. Cancer Med. (2021) 10:1889–99. doi: 10.1002/cam4.3775

PubMed Abstract | Crossref Full Text | Google Scholar

17. Wang Y, Wang M, Liu C, Hao M, Wang W, Li Y, et al. Global burden of liver cirrhosis 1990–2019 and 20 years forecast: results from the global burden of disease study 2019. Ann Med. (2024) 56:2328521. doi: 10.1080/07853890.2024.2328521

PubMed Abstract | Crossref Full Text | Google Scholar

18. Ferreira E Costa R, Leão ML, Sant'Ana MS, Mesquita RA, Gomez RS, Santos-Silva AR, et al. Oral squamous cell carcinoma frequency in young patients from referral centers around the world. Head Neck Pathol. (2022) 16:755–62. doi: 10.1007/s12105-022-01441-w

PubMed Abstract | Crossref Full Text | Google Scholar

19. Mathur P, Nath A, and K SK. Adolescent and young adult cancers in India-Findings from the National Cancer Registry Programme. Cancer Epidemiol. (2022) 78:102124. doi: 10.1016/j.canep.2022.102124

PubMed Abstract | Crossref Full Text | Google Scholar

20. Zhao L, Mbulo L, Twentyman E, Palipudi K, and King BA. Disparities in smokeless tobacco use in Bangladesh, India, and Pakistan: Findings from the Global Adult Tobacco Survey, 2014-2017. PloS One. (2021) 16:e0250144. doi: 10.1371/journal.pone.0250144

PubMed Abstract | Crossref Full Text | Google Scholar

21. Dsouza V, Kembhavi PM, Rao SP, P K, and Hebbar PB. How does Indian news media report smokeless tobacco control? A content analysis of the gutka ban enforcement. PloS Glob Public Health. (2023) 3:e0001724. doi: 10.1371/journal.pgph.0001724

PubMed Abstract | Crossref Full Text | Google Scholar

22. Ray CS and Gupta PC. Oral cancer in India. Oral Dis. (2025) 31:1439–54. doi: 10.1111/odi.14974

PubMed Abstract | Crossref Full Text | Google Scholar

23. Khan Z, Dreger S, Shah SM, Pohlabeln H, Khan S, Ullah Z, et al. Oral cancer via the bargain bin: The risk of oral cancer associated with a smokeless tobacco product (Naswar). PloS One. (2017) 12:e0180445. doi: 10.1371/journal.pone.0180445

PubMed Abstract | Crossref Full Text | Google Scholar

24. Shabir A, Kazmi S, Rashid MU, Mubeen I, Jamshed A, Hussain SR, et al. Unveiling oral cancer epidemiology in Pakistan: insights from a case-control study. Glob Health Epidemiol Genom. (2025) 2025:9982580. doi: 10.1155/ghe3/9982580

PubMed Abstract | Crossref Full Text | Google Scholar

25. Zakiullah, Ahmadullah, Khisroon M, Saeed M, Khan A, Khuda F, et al. Genetic susceptibility to oral cancer due to combined effects of GSTT1, GSTM1 and CYP1A1 gene variants in tobacco addicted patients of Pashtun ethnicity of Khyber Pakhtunkhwa province of Pakistan. Asian Pac J Cancer Prev. (2015) 16:1145–50. doi: 10.7314/apjcp.2015.16.3.1145

PubMed Abstract | Crossref Full Text | Google Scholar

26. Sarwar S, Mulla M, Mulla M, Tanveer R, Sabir M, Sultan A, et al. Human papillomavirus, tobacco, and poor oral hygiene can act synergetically, modulate the expression of the nuclear factor kappa B signaling pathway for the development and progression of head and neck cancer in the Pakistani population. Chin Med J (Engl). (2022) 135:1829–36. doi: 10.1097/CM9.0000000000001970

PubMed Abstract | Crossref Full Text | Google Scholar

27. Lee C-H, Ko AM-S, Warnakulasuriya S, Yin B-L, Sunarjo, Zain RB, et al. Intercountry prevalences and practices of betel-quid use in south, southeast and eastern Asia regions and associated oral preneoplastic disorders: an international collaborative study by Asian betel-quid consortium of south and east Asia. Int J Cancer. (2011) 129:1741–51. doi: 10.1002/ijc.25809

PubMed Abstract | Crossref Full Text | Google Scholar

28. Tran Q, Maddineni S, Arnaud EH, Divi V, Megwalu UC, Topf MC, et al. Oral cavity cancer in young, non-smoking, and non-drinking patients: A contemporary review. Crit Rev Oncol Hematol. (2023) 190:104112. doi: 10.1016/j.critrevonc.2023.104112

PubMed Abstract | Crossref Full Text | Google Scholar

29. Rumgay H, Nethan ST, Shah R, Vignat J, Ayo-Yusuf O, Chaturvedi P, et al. Global burden of oral cancer in 2022 attributable to smokeless tobacco and areca nut consumption: a population attributable fraction analysis. Lancet Oncol. (2024) 25:1413–23. doi: 10.1016/S1470-2045(24)00458-3

PubMed Abstract | Crossref Full Text | Google Scholar

30. Khan Z, Suliankatchi RA, Heise TL, and Dreger S. Naswar (Smokeless tobacco) use and the risk of oral cancer in Pakistan: A systematic review with meta-analysis. Nicotine Tob Res. (2019) 21:32–40. doi: 10.1093/ntr/ntx281

PubMed Abstract | Crossref Full Text | Google Scholar

31. Pimolbutr K, Poomsawat S, Na-Ek N, Warnakulasuriya S, and Buajeeb W. Prevalence of human papillomavirus in oral cancer in Asia: A systematic review and meta-analysis. Oral Dis. (2025) 31:1479–89. doi: 10.1111/odi.14979

PubMed Abstract | Crossref Full Text | Google Scholar

32. Pirmoradi Z, Nazari K, Shafiee N, Nikoukar N, Minoo S, Ghasemi H, et al. Oral cancer and HPV. Asian Pacific J Cancer Biol. (2024) 9:87–95. doi: 10.31557/apjcb.2024.9.1.87-95

Crossref Full Text | Google Scholar

33. Hayes TF, Benaich N, Goldie SJ, Sipilä K, Ames-Draycott A, Cai W, et al. Integrative genomic and functional analysis of human oral squamous cell carcinoma cell lines reveals synergistic effects of FAT1 and CASP8 inactivation. Cancer Lett. (2016) 383:106–14. doi: 10.1016/j.canlet.2016.09.014

PubMed Abstract | Crossref Full Text | Google Scholar

34. Brennan K, Koenig JL, Gentles AJ, Sunwoo JB, and Gevaert O. Identification of an atypical etiological head and neck squamous carcinoma subtype featuring the CpG island methylator phenotype. EBioMedicine. (2017) 17:223–36. doi: 10.1016/j.ebiom.2017.02.025

PubMed Abstract | Crossref Full Text | Google Scholar

35. Furquim CP, Pivovar A, Amenábar JM, Bonfim C, and Torres-Pereira CC. Oral cancer in Fanconi anemia: Review of 121 cases. Crit Rev Oncol Hematol. (2018) 125:35–40. doi: 10.1016/j.critrevonc.2018.02.013

PubMed Abstract | Crossref Full Text | Google Scholar

36. Dahlstrom KR, Little JA, Zafereo ME, Lung M, Wei Q, and Sturgis EM. Squamous cell carcinoma of the head and neck in never smoker-never drinkers: a descriptive epidemiologic study. Head Neck. (2008) 30:75–84. doi: 10.1002/hed.20664

PubMed Abstract | Crossref Full Text | Google Scholar

37. Ganly I, Yang L, Giese RA, Hao Y, Nossa CW, Morris LG, et al. Periodontal pathogens are a risk factor of oral cavity squamous cell carcinoma, independent of tobacco and alcohol and human papillomavirus. Int J Cancer. (2019) 145:775–84. doi: 10.1002/ijc.32152

PubMed Abstract | Crossref Full Text | Google Scholar

38. Kruse AL, Bredell M, and Grätz KW. Oral cancer in men and women: are there differences? Oral Maxillofac Surg. (2011) 15:51–5. doi: 10.1007/s10006-010-0253-6

PubMed Abstract | Crossref Full Text | Google Scholar

39. Ng JH, Iyer NG, Tan M-H, and Edgren G. Changing epidemiology of oral squamous cell carcinoma of the tongue: A global study. Head Neck. (2017) 39:297–304. doi: 10.1002/hed.24589

PubMed Abstract | Crossref Full Text | Google Scholar

40. Bajpai S, Zhang N, and Lott DG. Tracking changes in age distribution of head and neck cancer in the United States from 1975 to2016. Clin Otolaryngol. (2021) 46:1205–12. doi: 10.1111/coa.13817

PubMed Abstract | Crossref Full Text | Google Scholar

41. Hashim D, Sartori S, La Vecchia C, Serraino D, Maso LD, Negri E, et al. Hormone factors play a favorable role in female head and neck cancer risk. Cancer Med. (2017) 6:1998–2007. doi: 10.1002/cam4.1136

PubMed Abstract | Crossref Full Text | Google Scholar

42. Egloff AM, Rothstein ME, Seethala R, Siegfried JM, Grandis JR, and Stabile LP. Cross-talk between estrogen receptor and epidermal growth factor receptor in head and neck squamous cell carcinoma. Clin Cancer Res. (2009) 15:6529–40. doi: 10.1158/1078-0432.CCR-09-0862

PubMed Abstract | Crossref Full Text | Google Scholar

43. Valero C, Yuan A, Zanoni DK, Lei E, Dogan S, Shah JP, et al. Young non-smokers with oral cancer: What are we missing and why? Oral Oncol. (2022) 127:105803. doi: 10.1016/j.oraloncology.2022.105803

PubMed Abstract | Crossref Full Text | Google Scholar

44. Abdel-Rahman O. Sex-based differences in outcomes of patients with HPV-positive versus HPV-negative oropharyngeal carcinoma: a population-based study. Expert Rev Anticancer Ther. (2020) 20:813–8. doi: 10.1080/14737140.2020.1810019

PubMed Abstract | Crossref Full Text | Google Scholar

45. Shinn JR, Carey RM, Mady LJ, Shimunov D, Parhar HS, Cannady SB, et al. Sex-based differences in outcomes among surgically treated patients with HPV-related oropharyngeal squamous cell carcinoma. Oral Oncol. (2021) 123:105570. doi: 10.1016/j.oraloncology.2021.105570

PubMed Abstract | Crossref Full Text | Google Scholar

46. Xie L, Huang C-M, Song Y-L, Shao Z, and Shang Z-J. Incidence trends and projections of lip and oral cavity cancer in China 1990-2021: an age-period-cohort and decomposition analysis. BMC Oral Health. (2025) 25:406. doi: 10.1186/s12903-025-05764-2

PubMed Abstract | Crossref Full Text | Google Scholar

47. United Nations. World population prospects 2024: online edition. (2024). https://population.un.org/wpp/ (Accessed June 20, 2025).

Google Scholar

48. Gupta A, Sonis S, Uppaluri R, Bergmark RW, and Villa A. Disparities in oral cancer screening among dental professionals: NHANES 2011–2016. Am J Prev Med. (2019) 57:447–57. doi: 10.1016/j.amepre.2019.04.026

PubMed Abstract | Crossref Full Text | Google Scholar

49. World Health Organization. Global strategy and action plan on oral health 2023–2030. Geneva: World Health Organization. (2024).

Google Scholar

50. Toh ZQ, Licciardi PV, Russell FM, Garland SM, Batmunkh T, and Mulholland EK. Cervical cancer prevention through HPV vaccination in low- and middle-income countries in Asia. Asian Pac J Cancer Prev. (2017) 18:2339–43. doi: 10.22034/APJCP.2017.18.9.2339

PubMed Abstract | Crossref Full Text | Google Scholar