Abstract
Oral cancer is among the most common malignant tumors of the head and neck. However, a comprehensive assessment of the burden of lip and oral cavity cancer (LOC) in adolescents and young adults (AYAs) aged 15 to 39 is still lacking. Using age- and sex-stratified data across global, regional, and national levels from 1990 to 2021, this study aimed to provide a comprehensive estimate of the burden of LOC in the AYAs population and analyzed global data on the incidence, mortality, and disability-adjusted life years (DALYs) linked to AYAs LOC from 1990 to 2021. Age-standardized rate and estimated annual percentage change, were used to assess AYAs LOC trends across gender, age, and socio-demographic index, as well as to evaluate disparities between countries. A Bayesian Age-Period-Cohort (BAPC) model was applied to forecast the disease burden from 2022 to 2041. In 2021, there were 29,223 cases of LOC globally (95% uncertainty interval [UI]: 24,871–33,190), resulting in 9815 deaths (95% UI: 8038–11,421) and 581,394 DALYs (95% UI: 474,111–677,536). At the regional, South Asia has the highest incidence, mortality, DALYs, and age-standardized rate by Global Burden of Disease classification. At the national, India had the highest numbers for incidence, deaths, and DALYs, while Palau recorded the highest age-standardized incidence rate, age-standardized mortality rate, and age-standardized disability-adjusted life year rate. The burden is most pronounced among AYAs aged 35 to 39. Among those aged 15 to 24, women experienced a greater burden than men, while in the 25 to 39 age group, men had a higher burden. Projections indicate that by 2041, the burden of LOC will continue to rise, with a greater impact on men than women. From 1990 to 2021, the global burden of LOC, when adjusted for age, has increased. However, regional variations have been observed, with the burden decreasing in some areas. Consequently, monitoring the condition of young patients with LOC is crucial for reducing this overall burden. Limitations remain in this study: data gaps in low-income countries affect the accuracy of the Global Burden of Disease, and the burden of LOC on AYAs was not stratified. Future work needs to improve data collection.
Keywords: DALYs, GBD, incidence, lip and oral cavity cancer, mortality, temporal trends
1. Introduction
Cancer of the oral cavity is among the most prevalent malignancies globally.[1] This category includes cancers of the lips, tongue, cheeks, floor of the mouth, and hard palate. If undiagnosed, these cancers can be life-threatening. Among them, lip carcinoma is often the most overlooked and understudied, classified variably as oral cancer, skin cancer, or head and neck cancer. While the etiology of lip cancer remains incompletely understood, numerous risk factors associated with its development are being actively researched.[2] Common risk factors for oral cancer include heavy tobacco use (including smokeless forms), betel quid chewing, alcohol consumption, and chronic inflammation.[3–7] The prevalence of HPV-associated oral and oropharyngeal cancers, particularly HPV type 16, has risen in recent decades, predominantly among younger populations.[8–10] Factors including the oral microbiome, mucosal inflammation, and repeated trauma to the oral mucosa from dental and prosthetic devices have garnered growing attention for their potential carcinogenic impact on tumor development.[11] In the case of lip cancer, exposure to actinic ultraviolet radiation, especially ultraviolet-B, is among the most significant risk factors, as ultraviolet-B radiation can directly damage cellular DNA, raising the likelihood of mutations that may lead to cancer.[12] Furthermore, genetic conditions such as xeroderma pigmentosum, Fanconi anemia, and ataxia-telangiectasia elevate risk due to deficiencies in DNA repair mechanisms.[13] Oral cancer generally has a poor prognosis, with 5-year survival rates dropping to around 40%. However, early detection at stages I and II can significantly improve survival, pushing rates above 80%.[14,15] Unfortunately, up to 50% of cases are diagnosed at advanced stages (III and IV), primarily because early-stage oral cancer is often asymptomatic. Many patients delay seeking medical attention until symptoms like pain, bleeding, or detectable masses in the mouth or neck appear, symptoms often associated with lymphatic spread.[16] This delay in diagnosis is critical; a wait time of more than 1 month from symptom onset to diagnosis is associated with a substantially higher risk of advanced-stage oral cancer at presentation.[17] While patients often contribute to diagnostic delays by not recognizing symptoms, delays can also result from healthcare providers failing to suspect or diagnose oral malignancies promptly.[17–19] The standard of care typically involves primary surgical resection, with or without postoperative adjuvant therapy. Improvements in surgical techniques, alongside the routine use of postoperative radiation or chemoradiation, have led to better survival outcomes. Successful treatment relies on multidisciplinary strategies to maximize oncologic control while minimizing the therapy’s impact on form and function. Preventing oral cancer necessitates enhanced education about lifestyle-related risk factors and improved awareness and tools for early diagnosis.[1]
However, differences in the disease burden of lip and oral cavity cancer (LOC) among adolescents and young adults (AYAs) aged 15 to 39 years in different countries, regions, and ethnic groups have not been adequately studied. Therefore, it is crucial to prioritize the prevention, early diagnosis, and effective treatment of LOC among AYAs in this age group. Early intervention strategies can significantly reduce disease incidence and improve health outcomes. Emphasizing preventive measures, such as public health education and lifestyle changes, may help address the risk factors associated with LOC. In addition, improving the diagnostic ability to detect LOC at an early stage could greatly improve survival and quality of life. Finally, ensuring timely access to effective treatment options is critical to managing LOC in AYAs and mitigating its broader impact on individuals and health care systems. Using the Global Burden of Disease (GBD) statistical model, we evaluated the global impact of LOC in 2021, analyzing prevalence, incidence rates, mortality figures, and disability-adjusted life years (DALYs) by age, sex, and temporal trends. We also projected morbidity and mortality for the next 2 decades. Our findings offer crucial insights for clinicians, epidemiologists, and health policymakers, aiding in optimizing resource allocation and developing effective public health strategies.
2. Methods
2.1. Data source
The data for this study were obtained from the GBD 2021 database, covering data from 1990 to 2021. All research data can be accessed publicly via the Global Health Data Exchange (GHDx) query tool (https://vizhub.healthdata.org/gbd-results/).
2.2. Statistical analyses
We analyzed the incidence, mortality, and DALYs by examining the number, percentage, and rate of cases, providing 95% uncertainty intervals (UIs) for each estimate.[20] To assess temporal trends in the burden of LOC in AYAs from 1990 to 2021, we calculated the estimated annual percentage change (EAPC) in age-standardized rate (ASRs) for incidence, mortality, and DALYs. The EAPC is a widely accepted metric for quantifying changes in ASRs over time, calculated using a regression model fitted to the natural logarithm of the rates. This model is defined as: ln(rate) = α + β × (calendar year) + ε, where the EAPC is derived as 100 × (exp(β) −1). An EAPC and its 95% confidence interval (CI) above 0 indicate an upward trend in ASR over time, while values below 0 denote a downward trend. When EAPC values are near 0, this suggests stability in ASR.[21] To explore the impact of socioeconomic factors on LOC burden in AYAs, the Pearson correlation coefficient (ρ) was used to examine the relationship between ASR and socio-demographic index (SDI). In the GBD 2021 study, Pearson correlation calculations were carefully designed to account for significant variations in population size and case frequency across countries and regions. This analysis applied age-standardized methods, converting raw data to age-standardized ratios and utilizing population-weighted averages to ensure each population’s fair representation. Pearson correlation coefficients were calculated using the product–moment correlation formula, carefully considering the statistical power and precision of estimates, while integrating ecological inference to avoid erroneous causal interpretations at the individual level. Additionally, the Bayesian Age-Period-Cohort (BAPC) model was used to project the disease burden from 2022 to 2041.[22] We applied the BAPC model to predict the future incidence burden of LOC among AYAs. The model treats age, period, and cohort effects as random variables with smooth priors (2nd-order random walks) to ensure temporal consistency. Bayesian inference was performed using integrated nested Laplace approximation, avoiding Markov chain Monte Carlo sampling and convergence issues. The model’s probabilistic predictions were validated through time series cross-validation and posterior prediction tests, ensuring well-calibrated uncertainty intervals.[23,24] All analyses were conducted using R statistical software (version 4.4.1; R Foundation for Statistical Computing, Vienna, Austria), with a P-value of < .05 considered statistically significant.
3. Results
3.1. Global burden of LOC in AYAs
The incidence, deaths, and DALYs associated with LOC among AYAs worldwide have increased from 1990 to 2021 (Fig. 1B). In 2021, there were 29,223 cases of LOC (95% UI: 24,871–33,190), 9815 deaths (95% UI: 8038–11,421), and 581,394 DALYs (95% UI: 474,111–677,536) in AYAs globally. The number of cancer cases among AYAs rose from 14,096 in 1990 to 29,223 in 2021, while deaths increased from 5717 in 1990 to 9815 in 2021, and DALYs grew from 338,687 in 1990 to 581,394 in 2021 (Tables 1–3). From 1990 to 2021, the ASR trends for LOC mirrored the trends in incidence, deaths, and DALYs, showing an overall increase year by year (Fig. 1A). The age-standardized incidence rate (ASIR) increased from 0.69 (95% UI: 0.64–0.74) per 100,000 population in 1990 to 0.96 (95% UI: 0.81–1.09) per 100,000 in 2021. The age-standardized mortality rate (ASMR) rose from 0.28 (95% UI: 0.25–0.3) per 100,000 population in 1990 to 0.32 (95% UI: 0.26–0.37) per 100,000 in 2021. Similarly, the age-standardized disability-adjusted life year rate (ASDR) demonstrated an upward trend, increasing from 16.35 per 100,000 (95% UI: 14.93–17.78) in 1990 to 19.12 per 100,000 (95% UI: 15.57–22.3) by 2021 (Tables 1–3).
Figure 1.
Temporal trends of ASIR, ASMR, and ASDR in LOC in AYAs, 1990 to 2021. (A) ASIR, ASMR, and ASDR of LOC in AYAs by sex, globally and in 5 SDI regions. (B) Number of cases of LOC among AYAs, disaggregated by sex, globally and in the 5 SDI regions. ASDR = age-standardized disability-adjusted life year rate, ASIR = age-standardized incidence rate, ASMR = age-standardized mortality rate, AYAs = adolescents and young adults, LOC = lip and oral cavity cancer, SDI = Socio-Demographic Index.
Table 1.
Incidence of lip and oral cavity cancer in 1990 and 2021 for both sexes and all locations, with EAPC from 1990 and 2021.
| Location | Num_1990 | ASR_1990 | Num_2021 | ASR_2021 | EAPC_CI |
|---|---|---|---|---|---|
| Andean Latin America | 34 (27 to 41) |
0.25 (0.2 to 0.3) |
80 (62 to 105) |
0.3 (0.23 to 0.39) |
0.78% (0.61 to 0.95) |
| Australasia | 113 (90 to 139) |
1.34 (1.08 to 1.65) |
169 (136 to 205) |
1.45 (1.17 to 1.76) |
0.24% (0.02 to 0.46) |
| Caribbean | 65 (57 to 74) |
0.49 (0.43 to 0.56) |
72 (57 to 88) |
0.39 (0.31 to 0.48) |
−0.58% (−0.71 to −0.45) |
| Central Asia | 118 (107 to 130) |
0.44 (0.41 to 0.49) |
166 (141 to 195) |
0.42 (0.35 to 0.49) |
−0.14% (−0.35 to 0.07) |
| Central Europe | 270 (252 to 290) |
0.52 (0.49 to 0.56) |
219 (198 to 244) |
0.52 (0.47 to 0.58) |
-0.22% (−0.36 to −0.09) |
| Central Latin America | 165 (155 to 177) |
0.28 (0.26 to 0.3) |
326 (286 to 370) |
0.32 (0.28 to 0.37) |
0.56% (0.43 to 0.69) |
| Central Sub-Saharan Africa | 40 (28 to 56) |
0.23 (0.16 to 0.32) |
120 (82 to 172) |
0.26 (0.18 to 0.37) |
0.36% (0.14 to 0.59) |
| East Asia | 1701 (1458 to 1961) |
0.32 (0.28 to 0.37) |
3227 (2684 to 3823) |
0.57 (0.47 to 0.67) |
2.14% (1.95 to 2.34) |
| Eastern Europe | 725 (685 to 773) |
0.76 (0.72 to 0.81) |
1043 (954 to 1142) |
1.18 (1.07 to 1.29) |
1.67% (1.32 to 2.02) |
| Eastern Sub-Saharan Africa | 270 (225 to 327) |
0.45 (0.37 to 0.54) |
818 (598 to 1072) |
0.54 (0.4 to 0.71) |
0.42% (0.3 to 0.55) |
| Global | 14,096 (13,109 to 15,085) |
0.69 (0.64 to 0.74) |
29,223 (24,871 to 33,190) |
0.96 (0.81 to 1.09) |
1.1% (1.03 to 1.17) |
| High-income Asia Pacific | 442 (392 to 500) |
0.65 (0.58 to 0.74) |
647 (552 to 760) |
1.12 (0.95 to 1.31) |
1.83% (1.42 to 2.24) |
| High-income North America | 1174 (1120 to 1230) |
0.96 (0.91 to 1) |
1234 (1166 to 1309) |
0.94 (0.89 to 1) |
-0.01% (−0.19 to 0.16) |
| High-middle SDI | 2253 (2117 to 2405) |
0.5 (0.47 to 0.54) |
3448 (3114 to 3794) |
0.66 (0.6 to 0.73) |
1.01% (0.77 to 1.25) |
| High SDI | 3139 (2997 to 3287) |
0.85 (0.82 to 0.89) |
3666 (3481 to 3867) |
0.91 (0.87 to 0.96) |
0.29% (0.18 to 0.41) |
| Low-middle SDI | 3987 (3408 to 4600) |
0.99 (0.85 to 1.15) |
10,867 (8267 to 13,443) |
1.41 (1.08 to 1.74) |
1.13% (1.07 to 1.18) |
| Low SDI | 1034 (823 to 1250) |
0.65 (0.52 to 0.78) |
3165 (2399 to 4068) |
0.81 (0.62 to 1.04) |
0.61% (0.52 to 0.71) |
| Middle SDI | 3673 (3375 to 4008) |
0.54 (0.5 to 0.59) |
8066 (6967 to 9150) |
0.81 (0.7 to 0.92) |
1.43% (1.32 to 1.53) |
| North Africa and Middle East | 233 (196 to 285) |
0.2 (0.17 to 0.24) |
755 (635 to 902) |
0.28 (0.24 to 0.34) |
1.42% (1.29 to 1.56) |
| Oceania | 10 (6 to 13) |
0.41 (0.28 to 0.56) |
27 (18 to 38) |
0.5 (0.34 to 0.71) |
0.68% (0.55 to 0.8) |
| South Asia | 5774 (4985 to 6607) |
1.48 (1.28 to 1.69) |
16,126 (12,370 to 19,705) |
2.1 (1.61 to 2.56) |
1.17% (1.11 to 1.22) |
| Southeast Asia | 969 (804 to 1154) |
0.55 (0.46 to 0.65) |
1887 (1572 to 2249) |
0.66 (0.55 to 0.79) |
0.27% (0.12 to 0.42) |
| Southern Latin America | 69 (60 to 81) |
0.38 (0.33 to 0.44) |
107 (90 to 127) |
0.4 (0.34 to 0.47) |
0.55% (0.34 to 0.77) |
| Southern Sub-Saharan Africa | 115 (99 to 135) |
0.63 (0.54 to 0.73) |
181 (143 to 223) |
0.52 (0.41 to 0.64) |
-0.7% (−1.2 to −0.2) |
| Tropical Latin America | 246 (228 to 266) |
0.43 (0.4 to 0.46) |
468 (435 to 504) |
0.49 (0.46 to 0.53) |
0.1% (−0.02 to 0.23) |
| Western Europe | 1475 (1348 to 1611) |
1 (0.91 to 1.09) |
1247 (1160 to 1356) |
0.86 (0.8 to 0.94) |
-0.44% (−0.57 to −0.32) |
| Western Sub-Saharan Africa | 89 (67 to 110) |
0.15 (0.11 to 0.18) |
303 (204 to 414) |
0.19 (0.13 to 0.26) |
0.7% (0.52 to 0.88) |
ASR = age-standardized rate, EAPC = estimated annual percentage change, SDI = Socio-Demographic Index.
Table 3.
DALYs of lip and oral cavity cancer in 1990 and 2021 for both sexes and all locations, with EAPC from 1990 and 2021.
| Location | Num_1990 | ASR_1990 | Num_2021 | ASR_2021 | EAPC_CI |
|---|---|---|---|---|---|
| Andean Latin America | 954 (782 to 1169) |
6.84 (5.6 to 8.38) |
1438 (1124 to 1851) |
5.34 (4.18 to 6.88) |
−0.69% (−0.83 to −0.55) |
| Australasia | 670 (578 to 768) |
8.01 (6.92 to 9.17) |
693 (585 to 818) |
6.01 (5.08 to 7.09) |
−0.93% (−1.12 to −0.74) |
| Caribbean | 1416 (1240 to 1626) |
10.45 (9.16 to 11.99) |
1488 (1154 to 1863) |
8.1 (6.28 to 10.14) |
−0.58% (−0.76 to −0.4) |
| Central Asia | 3516 (3244 to 3825) |
13.1 (12.1 to 14.24) |
3951 (3379 to 4599) |
10.02 (8.57 to 11.66) |
−0.96% (−1.08 to −0.84) |
| Central Europe | 6721 (6327 to 7171) |
13.09 (12.32 to 13.98) |
3765 (3430 to 4126) |
9.01 (8.2 to 9.87) |
−1.44% (−1.59 to −1.29) |
| Central Latin America | 4202 (3983 to 4436) |
6.86 (6.5 to 7.24) |
5781 (5131 to 6483) |
5.73 (5.09 to 6.43) |
−0.48% (−0.64 to −0.33) |
| Central Sub-Saharan Africa | 1363 (954 to 1883) |
7.57 (5.31 to 10.44) |
3536 (2403 to 5019) |
7.45 (5.06 to 10.56) |
−0.07% (−0.21 to 0.06) |
| East Asia | 42,183 (36,052 to 48,519) |
7.9 (6.75 to 9.08) |
39,358 (32,719 to 47,125) |
7.02 (5.82 to 8.4) |
−0.24% (−0.39 to −0.09) |
| Eastern Europe | 12,382 (11,755 to 13,153) |
13.06 (12.4 to 13.87) |
11,997 (10,947 to 13,151) |
13.77 (12.55 to 15.1) |
0.21% (−0.02 to 0.43) |
| Eastern Sub-Saharan Africa | 9278 (7726 to 11,367) |
14.83 (12.39 to 18) |
24,069 (17,554 to 31,534) |
15.46 (11.3 to 20.22) |
−0.04% (−0.12 to 0.04) |
| Global | 338,687 (309,306 to 368,467) |
16.35 (14.93 to 17.78) |
581394 (474,111 to 677,536) |
19.12 (15.57 to 22.3) |
0.53% (0.5 to 0.56) |
| High-income Asia Pacific | 4808 (4416 to 5274) |
7.09 (6.51 to 7.78) |
4241 (3882 to 4690) |
7.44 (6.81 to 8.22) |
−0.02% (−0.33 to 0.28) |
| High-income North America | 8742 (8431 to 9068) |
7.17 (6.91 to 7.43) |
7230 (6855 to 7629) |
5.54 (5.25 to 5.84) |
−0.76% (−0.99 to −0.52) |
| High-middle SDI | 44,179 (41,341 to 47,549) |
9.86 (9.23 to 10.61) |
42,691 (38,509 to 47,125) |
8.34 (7.5 to 9.22) |
−0.5% (−0.64 to −0.35) |
| High SDI | 33,371 (32,103 to 34,683) |
9.13 (8.78 to 9.49) |
26,591 (25,189 to 28,253) |
6.68 (6.33 to 7.1) |
−0.97% (−1.04 to −0.9) |
| Low-middle SDI | 127,646 (108,686 to 147,828) |
31.25 (26.58 to 36.19) |
276,357 (210,118 to 343,079) |
35.64 (27.15 to 44.16) |
0.41% (0.33 to 0.49) |
| Low SDI | 34,289 (27,508 to 41,597) |
21 (16.84 to 25.42) |
87,781 (67,122 to 111,509) |
22.04 (16.9 to 27.89) |
0.04% (−0.05 to 0.14) |
| Middle SDI | 98,970 (90,444 to 108,276) |
14.47 (13.22 to 15.82) |
147,747 (125,690 to 167,752) |
15.05 (12.78 to 17.1) |
0.24% (0.2 to 0.28) |
| North Africa and Middle East | 5838 (4890 to 7178) |
4.88 (4.09 to 6.01) |
12,118 (10,273 to 14,435) |
4.61 (3.9 to 5.49) |
0.03% (−0.05 to 0.12) |
| Oceania | 261 (170 to 365) |
10.9 (7.11 to 15.25) |
719 (482 to 1021) |
13.34 (8.93 to 18.94) |
0.77% (0.67 to 0.87) |
| South Asia | 182,163 (156,876 to 208,503) |
46.05 (39.62 to 52.69) |
395,161 (300,475 to 486,067) |
51.1 (38.91 to 62.78) |
0.35% (0.27 to 0.44) |
| Southeast Asia | 24,304 (20,156 to 28,921) |
13.5 (11.22 to 16.01) |
35,009 (29,227 to 41,459) |
12.32 (10.28 to 14.59) |
−0.61% (−0.75 to −0.46) |
| Southern Latin America | 1298 (1154 to 1468) |
7.03 (6.25 to 7.95) |
1431 (1249 to 1641) |
5.37 (4.69 to 6.16) |
−0.45% (−0.66 to −0.25) |
| Southern Sub-Saharan Africa | 2964 (2543 to 3426) |
15.93 (13.72 to 18.37) |
4322 (3398 to 5348) |
12.44 (9.78 to 15.39) |
−0.86% (−1.38 to −0.35) |
| Tropical Latin America | 6100 (5694 to 6526) |
10.5 (9.79 to 11.23) |
8615 (8077 to 9190) |
9.1 (8.53 to 9.71) |
−0.72% (−0.85 to −0.59) |
| Western Europe | 16,792 (15,738 to 17,852) |
11.36 (10.65 to 12.08) |
8554 (8073 to 9137) |
5.97 (5.63 to 6.38) |
−2.15% (−2.33 to −1.97) |
| Western Sub-Saharan Africa | 2733 (2070 to 3368) |
4.45 (3.38 to 5.47) |
7916 (5387 to 10,688) |
4.87 (3.32 to 6.55) |
0.17% (0.04 to 0.31) |
ASR = age-standardized rate, DALYs = disability-adjusted life years, EAPC = estimated annual percentage change, SDI = Socio-Demographic Index.
Table 2.
Deaths of lip and oral cavity cancer in 1990 and 2021 for both sexes and all locations, with EAPC from 1990 and 2021.
| Location | Num_1990 | ASR_1990 | Num_2021 | ASR_2021 | EAPC_CI |
|---|---|---|---|---|---|
| Andean Latin America | 16 (13 to 19) |
0.12 (0.09 to 0.14) |
24 (19 to 31) |
0.09 (0.07 to 0.12) |
−0.73% (−0.87 to −0.59) |
| Australasia | 11 (9 to 12) |
0.13 (0.11 to 0.14) |
11 (9 to 12) |
0.09 (0.08 to 0.11) |
−1.02% (−1.22 to −0.83) |
| Caribbean | 24 (21 to 27) |
0.18 (0.15 to 0.2) |
25 (20 to 31) |
0.14 (0.11 to 0.17) |
−0.59% (−0.77 to −0.4) |
| Central Asia | 59 (54 to 64) |
0.22 (0.21 to 0.24) |
67 (58 to 78) |
0.17 (0.15 to 0.2) |
−0.95% (−1.08 to −0.83) |
| Central Europe | 119 (112 to 126) |
0.23 (0.22 to 0.24) |
66 (60 to 72) |
0.16 (0.14 to 0.17) |
−1.52% (−1.68 to −1.36) |
| Central Latin America | 70 (66 to 74) |
0.12 (0.11 to 0.12) |
97 (86 to 108) |
0.1 (0.09 to 0.11) |
−0.51% (−0.67 to −0.35) |
| Central Sub-Saharan Africa | 23 (16 to 32) |
0.13 (0.09 to 0.18) |
60 (41 to 85) |
0.13 (0.09 to 0.18) |
−0.07% (−0.21 to 0.06) |
| East Asia | 712 (609 to 819) |
0.13 (0.11 to 0.15) |
668 (555 to 802) |
0.12 (0.1 to 0.14) |
−0.29% (−0.44 to −0.14) |
| Eastern Europe | 216 (205 to 230) |
0.23 (0.22 to 0.24) |
211 (191 to 231) |
0.24 (0.22 to 0.26) |
0.2% (−0.01 to 0.42) |
| Eastern Sub-Saharan Africa | 153 (128 to 186) |
0.25 (0.21 to 0.3) |
398 (290 to 521) |
0.26 (0.19 to 0.34) |
−0.04% (−0.11 to 0.04) |
| Global | 5717 (5217 to 6220) |
0.28 (0.25 to 0.3) |
9815 (8038 to 11,421) |
0.32 (0.26 to 0.37) |
0.5% (0.48 to 0.53) |
| High-income Asia Pacific | 80 (74 to 88) |
0.12 (0.11 to 0.13) |
69 (64 to 76) |
0.12 (0.11 to 0.13) |
−0.12% (−0.43 to 0.18) |
| High-income North America | 144 (139 to 147) |
0.12 (0.11 to 0.12) |
116 (110 to 121) |
0.09 (0.08 to 0.09) |
−0.84% (−1.08 to −0.6) |
| High-middle SDI | 755 (707 to 812) |
0.17 (0.16 to 0.18) |
730 (658 to 806) |
0.14 (0.13 to 0.16) |
−0.54% (−0.69 to −0.39) |
| High SDI | 562 (542 to 582) |
0.15 (0.15 to 0.16) |
438 (417 to 463) |
0.11 (0.1 to 0.12) |
−1.06% (−1.13 to −0.99) |
| Low-middle SDI | 2149 (1828 to 2492) |
0.53 (0.45 to 0.62) |
4660 (3565 to 5767) |
0.6 (0.46 to 0.75) |
0.39% (0.31 to 0.47) |
| Low SDI | 575 (462 to 698) |
0.36 (0.29 to 0.43) |
1466 (1125 to 1859) |
0.37 (0.29 to 0.47) |
0.03% (−0.06 to 0.13) |
| Middle SDI | 1672 (1528 to 1829) |
0.25 (0.23 to 0.27) |
2517 (2141 to 2857) |
0.25 (0.22 to 0.29) |
0.22% (0.17 to 0.26) |
| North Africa and Middle East | 97 (81 to 119) |
0.08 (0.07 to 0.1) |
203 (172 to 242) |
0.08 (0.06 to 0.09) |
−0.01% (−0.1 to 0.07) |
| Oceania | 4 (3 to 6) |
0.18 (0.12 to 0.26) |
12 (8 to 17) |
0.22 (0.15 to 0.32) |
0.76% (0.66 to 0.85) |
| South Asia | 3075 (2645 to 3522) |
0.79 (0.68 to 0.9) |
6674 (5109 to 8160) |
0.87 (0.66 to 1.06) |
0.34% (0.25 to 0.42) |
| Southeast Asia | 408 (338 to 484) |
0.23 (0.19 to 0.27) |
594 (496 to 704) |
0.21 (0.17 to 0.25) |
−0.61% (−0.76 to −0.46) |
| Southern Latin America | 22 (20 to 25) |
0.12 (0.11 to 0.14) |
24 (21 to 28) |
0.09 (0.08 to 0.1) |
−0.52% (−0.72 to −0.32) |
| Southern Sub-Saharan Africa | 50 (43 to 58) |
0.27 (0.24 to 0.32) |
74 (59 to 92) |
0.21 (0.17 to 0.26) |
−0.88% (−1.39 to −0.36) |
| Tropical Latin America | 105 (98 to 113) |
0.18 (0.17 to 0.2) |
148 (139 to 158) |
0.16 (0.15 to 0.17) |
−0.81% (−0.94 to −0.68) |
| Western Europe | 284 (267 to 301) |
0.19 (0.18 to 0.2) |
140 (133 to 148) |
0.1 (0.09 to 0.1) |
−2.28% (−2.47 to −2.09) |
| Western Sub-Saharan Africa | 46 (35 to 57) |
0.08 (0.06 to 0.09) |
134 (92 to 181) |
0.08 (0.06 to 0.11) |
0.18% (0.04 to 0.32) |
ASR = age-standardized rate, EAPC = estimated annual percentage change, SDI = Socio-Demographic Index.
3.2. Regional burden of LOC in AYAs
In the 5 SDI regions, the incidence, deaths, and DALYs for LOC in AYAs increased over time in the middle, low-middle, and low SDI regions. However, the incidence, deaths, and DALYs in the high and high-middle SDI regions remained relatively stable. In 2021, the low-middle SDI region had the highest burden, with 10,867 cases (95% UI: 8267–13,443), 4660 deaths (95% UI: 3565–5767), and 276,357 DALYs (95% UI: 210,118–343,079). We also analyzed the ASIR, ASMR, and ASDR across the 5 SDI regions. Over time, the ASIR increased in all regions. However, ASMR and ASDR decreased in the high and high-middle SDI regions, while they increased in the low-middle, middle, and low SDI regions. In 2021, the low-middle SDI region recorded the highest ASIR (1.41 per 100,000), ASMR (0.6 per 100,000), and ASDR (35.64 per 100,000). The middle SDI region showed the most notable increase in ASIR, with an EAPC of 1.43% (95% CI: 1.32–1.53). In contrast, the low-middle SDI region had the largest rises in both ASMR and ASDR, with EAPCs of 0.39% (95% CI: 0.31–0.47) and 0.41% (95% CI: 0.33–0.49), respectively. Meanwhile, a moderate decline in ASMR and ASDR was observed in the high-middle SDI region, with EAPCs of −0.54% (95% CI: −0.69 to −0.39) and −0.5% (95% CI: −0.64 to −0.35), respectively (Tables 1–3, Fig. 1A and B).
At the regional level, based on GBD classification, South Asia bore the heaviest burden of LOC in 2021, with 16,126 cases (95% UI: 12,370–19,705), 6674 deaths (95% UI: 5109–8160), and 395,161 DALYs (95% UI: 300,475–486,067). South Asia reported the highest ASIR at 2.1 per 100,000, alongside the highest ASMR of 0.87 per 100,000 and ASDR of 51.1 per 100,000. From 1990 to 2021, East Asia saw the sharpest increase in ASIR, with an EAPC of 2.14% (95% CI: 1.95–2.34). Oceania showed the most pronounced rises in both ASMR and ASDR, with EAPCs of 0.76% (95% CI: 0.66–0.85) and 0.77% (95% CI: 0.67–0.87), respectively. Conversely, Southern Sub-Saharan Africa recorded the largest reduction in ASIR, with an EAPC of −0.7% (95% CI: −1.2 to −0.2), while Western Europe exhibited the most significant decreases in both ASMR and ASDR, with EAPCs of −2.28% (95% CI: −2.47 to −2.09) and −2.15% (95% CI: −2.33 to −1.97), respectively (Tables 1–3).
3.3. National burden of LOC in AYAs
Nationally, in 2021, Indian AYAs had the highest incidence, mortality, and DALYs for LOC, with 10,380 cases (95% UI: 8065–12,525), 4151 deaths (95% UI: 3272–5038), and 243,589 DALYs (95% UI: 185,929–296,219). In terms of ASRs, Palau AYAs had the highest ASIR at 10.69 per 100,000, ASMR at 3.49 per 100,000, and ASDR at 214.42 per 100,000. Cabo Verde AYAs showed the most significant increases in ASIR, ASMR, and ASDR, with EAPC of 7.71% (95% CI: 5.32–10.16), 6.7% (95% CI: 4.25–9.22), and 6.7% (95% CI: 4.25–9.2), respectively (Tables S1–S3, Supplemental Digital Content, https://links.lww.com/MD/Q534, Fig. 2A–F).
Figure 2.
These maps illustrate the ASIR (A), ASMR (B), ASDR (C), and the EAPC of ASIR (D), ASMR (E), and ASDR (F) of LOC in AYAs per 100,000 people in 2021 across 204 countries and territories for both sexes. ASDR = age-standardized disability-adjusted life year rate, ASIR = age-standardized incidence rate, ASMR = age-standardized mortality rate, AYAs = adolescents and young adults, EAPC = estimated annual percentage change, LOC = lip and oral cavity cancer.
3.4. Global LOC burden by age and sex in AYAs
A detailed gender-based subgroup analysis in 2021 reveals significant differences in the global burden of LOC between men and women, despite the overall upward trend in AYAs across different age groups. A clear pattern emerges when comparing the 2 genders. In the 15 to 24 age group, the incidence, deaths, and DALYs are higher in females than in males. Conversely, in the 25 to 39 age group, males experience higher incidence, deaths, and DALYs than females. Notably, both men and women show large increases in morbidity, mortality, and DALYs in the 25 to 39 age group, with a peak occurring in the 35 to 39 age group. The ASR for both genders follows this same pattern across age groups. In summary, women bear a greater burden in the 15 to 24 age group, while men bear a greater burden in the 25 to 39 age group (Fig. 3).
Figure 3.
Age-specific rates of incidence (A), mortality (B), and DALYs (C) of LOC by sex, 2021. DALYs = disability-adjusted life years, LOC = lip and oral cavity cancer.
Additionally, we analyzed changes in the burden of LOC among AYAs by sex, globally and within SDI regions, from 1990 to 2021. These changes were based on population-level determinants such as population growth, aging, and epidemiological shifts. Over the past 31 years, population growth has been the most significant factor driving the increase in the global burden of LOC among AYAs, particularly in the low, low-middle, and middle SDI regions. However, in the high-middle and high SDI regions, epidemiological changes have been the primary factor driving changes in the cancer burden among AYAs. When stratified by sex, both globally and within the 5 SDI regions, young men bear a greater burden of LOC than young women. The effect of age-related factors on the cancer burden is more pronounced in young men than in young women (Fig. 4).
Figure 4.
Changes in oral cancer burden among AYAs by sex globally and in SDI regions from 1990 to 2021, based on population-level determinants of population growth, aging, and epidemiological changes. The black dots represent the total value of the changes contributed by all 3 components. AYAs = adolescents and young adults, SDI = Socio-Demographic Index.
3.5. The association between SDI, global inequalities, and the burden of LOC in AYAs
Globally and across 21 regions, the ASIR, ASMR, and ASDR for LOCs exhibited a pattern of increase, followed by a decrease, and then another increase, peaking at an SDI value of 0.38. Specifically, ASIR peaked at SDI 0.38, then declined, before rising again at SDI 0.62. The trends for ASMR and ASDR were similar to ASIR, but when the SDI exceeded 0.75, both ASMR and ASDR consistently decreased as the SDI increased. Regions with lower SDI levels are significantly more likely to have higher LOC burdens among AYAs (Fig. 5A–C). In 2021, the global analysis of 204 countries showed that ASIR (R = 0.156, P = .026) for LOC was positively correlated with SDI, and SDI was significantly correlated with ASIR, indicating that regions with higher SDI tended to have higher ASIR. However, no statistically significant correlation was found between ASMR, ASDR, and SDI (Fig. 6A–C). Further analysis explored the relationship between the 2021 EAPC and ASR in relation to the 2021 SDI across various countries and regions. As ASMR (ρ = 0.21, P = .002) and ASDR (ρ = 0.21, P = .003) increased, EAPCs for ASMR and ASDR also initially increased, but then decreased. Conversely, there was no statistically significant correlation between ASIR and ASIR-related EAPCs. Additionally, with increasing SDI, EAPCs of ASMR (ρ = -0.32, P < .01) and ASDR (ρ = -0.30, P < .01) showed a tendency to first increase and then decrease. While EAPCs of ASIR also followed this trend with rising SDI, the relationship between EAPCs of ASIR and ASIR-related EAPCs was not statistically significant (Fig. 7A–C).
Figure 5.
Trends in ASIR (A), ASMR (B), and ASDR (C) of LOC across 21 geographical regions and globally by SDI for both sexes combined, 1990 to 2021. For each region, the points from left to right depict the estimates from 1990 to 2021. The shaded areas represent 95% UI. ASDR = age-standardized disability-adjusted life year rate, ASIR = age-standardized incidence rate, ASMR = age-standardized mortality rate, LOC = lip and oral cavity cancer, SDI = Socio-Demographic Index, UI = uncertainty interval.
Figure 6.
Correlation between ASIR and SDI quintile (A); correlation between ASMR and SDI quintile (B); and correlation between age-specific DALYs rate and SDI quintile (C). The ρ and P values were derived from Pearson correlation analysis. ASIR = age-standardized incidence rate, ASMR = age-standardized mortality rate, DALYs = disability-adjusted life years, SDI = Socio-Demographic Index.
Figure 7.
Correlation between ASR and EAPC (A), SDI and EAPC (B). The ρ and P values were derived from Pearson correlation analysis. ASR = age-standardized rate, EAPC = estimated annual percentage change, SDI = Socio-Demographic Index.
3.6. Predictions of LOC in AYAs
We applied the BAPC model to analyze the ASIR, ASMR, and ASDR for the burden of LOC.
Globally, from 2022 to 2041, the ASIR for men is projected to rise annually during the 1st decade and then plateau in the 2nd. In contrast, the ASIR for women is expected to increase each year. For men, ASIR increased from 1.11 per 100,000 population in 2022 (95% UI: 1.07–1.15) to 1.18 per 100,000 in 2041 (95% UI: 0.57–1.79). For women, ASIR rose from 0.83 per 100,000 in 2022 (95% UI: 0.81–0.86) to 1.09 per 100,000 in 2041 (95% UI: 0.45–1.73). However, the ASMR is expected to decrease in men and increase in women over the same period. For men, the ASMR is projected to decline from 0.4 per 100,000 in 2022 (95% UI: 0.38–0.41) to 0.38 per 100,000 by 2041 (95% UI: 0.16–0.59). In women, ASMR rose from 0.25 per 100,000 in 2022 (95% UI: 0.24–0.41) to 0.29 per 100,000 in 2041 (95% UI: 0.08–0.59). ASDR followed similar trends to ASMR. In men, ASDR decreased from 23.33 per 100,000 in 2022 (95% UI: 22.65–24.00) to 21.84 per 100,000 in 2041 (95% UI: 10.12–33.56). For women, ASDR increased from 15.37 per 100,000 in 2022 (95% UI: 14.98–15.76) to 17.41 per 100,000 in 2041 (95% UI: 6.53–28.29). These projections highlight a significant gender difference in ASIR, with women expected to experience a more pronounced increase compared to men over the next 2 decades (Fig. 8A–C, Table S4, Supplemental Digital Content, https://links.lww.com/MD/Q534).
Figure 8.
Incidence (A), deaths (B), and DALYs trends of LOC from 1990 to 2021, and projections from 2022 to 2041 (C). DALYs = disability-adjusted life years, LOC = lip and oral cavity cancer.
We also analyzed gender-disaggregated projections for LOC incidence, deaths, and DALYs for 2022 to 2041. Incidence is expected to rise annually for both men and women. In men, incidence increased from 17,623 cases in 2022 (95% UI: (0–983,430)) to 20,210 cases in 2041 (95% UI: 0–6938,838). In women, incidence rose from 12,891 cases in 2022 (95% UI: 0–926,489) to 17,134 cases in 2041 (95% UI: 0–8188,652). DALYs followed a similar trend to incidence, with an increase from 368,398 cases in 2022 (95% UI: 63,972–1031,119) to 389,013 cases in 2041 (95% UI: 0–5138,766) in men, and from 235,394 cases in 2022 (95% UI: 0–970,024) to 294,922 cases in 2041 (95% UI: 0–5515,392) in women. Notably, the rate of increase in incidence and DALYs was greater in females than in males. Although overall deaths for both sexes are projected to decline from 2022 to 2041, a slight increase is expected in the final decade of this period. Male deaths decreased from 6253 (95% UI: 0–994,722) in 2022 to 5506 in 2041 (95% UI: 0–8629,148). Female deaths decreased from 3878 (95% UI: 0–1001,926) in 2022 to 3378 in 2041 (95% UI: 0–9640,701) (Fig. 8A–C, Table S5, Supplemental Digital Content, https://links.lww.com/MD/Q534).
4. Discussion
Cancer of the oral cavity is recognized as one of the most prevalent and widespread malignancies affecting populations worldwide.[25] Among the various types of oral cancers, squamous cell carcinoma stands out as the most common histological type, with its primary etiological factors being the heavy use of tobacco products and the consumption of alcoholic beverages.[26] This specific cancer presents significant, multifaceted challenges to global public health systems, impacting both individual health outcomes and imposing substantial demands on healthcare infrastructure worldwide. The complexities in its management and the corresponding healthcare requirements have driven ongoing discussions within the global health community on strategies to mitigate its extensive impact across regional and international levels.[27–29] Addressing these issues, our study conducted an in-depth analysis of the disease burden associated with LOC in AYAs, examining variations in incidence, mortality, and DALYs across diverse populations over multiple time periods. To ensure precision and relevance, we leveraged the latest, high-quality data from the GBD database, enabling a detailed trend analysis and offering insights into how this burden shifts across socio-demographic and geographic dimensions. Furthermore, we assessed the epidemiological trends in LOC specifically among AYAs over the past 31 years, EAPC calculations to quantify these trends effectively. However, it is important to note that this article also highlights several limitations that should be taken into account when interpreting the results and their implications.
From 1990 to 2021, the incidence of LOC in AYAs rose significantly, from 14,096 cases to 29,223 cases globally. This increase may be related to improvements in LOC diagnostic technology among AYAs. In addition, the number of deaths and DALYs associated with this cancer in AYAs has also increased worldwide. Similarly, ASIR, ASMR, and ASDR reflect the same upward trend. This illustrates the increasing burden of LOC among AYAs worldwide.
In our demographic-specific findings, women in the 15 to 24 age group bear a greater burden of LOC than men, while men in the 25 to 39 age group face a higher burden compared to women. Notably, men in the 35 to 39 age group experience the highest burden, with the highest ASRs. And the reason for this discrepancy may be related to the risk factors that lead to LOC, as mentioned earlier the common risk factors for LOC include smoking, betel chewing, alcohol consumption, ultraviolet radiation, and HPV infection.[30] Among the various oral cancer risk factors, smoking, alcohol consumption, and oral sex (a transmission route for HPV infection) are the top 3 risk factors for oral cancer worldwide.[31,32] Men have a higher LOC burden after the age of 25 years, which may be associated with the high adult smoking prevalence in men, which globally was 32.6% and 6.5% for men and women, respectively, in 2020.[33] In a previous study in Taiwan, more than 80% of male patients were found to be both betel nut chewers and smokers, and both chewers and smokers usually started the habit in their 20s.[34] Secondly, men are 7 times more likely to be infected with oral HPV16 than women, and the prevalence of any oral HPV infection is significantly higher in men than in women.[35] Moreover, men are less able to clear HPV viruses than women and take significantly longer to clear HPV infections,[36] all of which may exacerbate cancer risk and be important factors influencing the burden of LOC in men. Females have a higher LOC burden at 15 to 24 years of age, which may be biologically related to the fact that females are biologically immature in immune regulation around puberty and their cervical epithelium is more susceptible to high-risk HPV types.[37] However, more specific associations remain to be investigated.
There are many risk factors for LOC, and since most can be mitigated, the disease is largely preventable. Primary prevention efforts should prioritize public education on modifiable behavioral risk factors associated with this disease. Key focus areas include discouraging smoking, reducing substance dependence, and raising awareness of the health risks linked to excessive alcohol use. Targeting these lifestyle factors allows public health initiatives to lower disease incidence by empowering individuals to make healthier choices, ultimately decreasing their cancer risk and alleviating the overall strain on healthcare systems.[14]
The burden of LOC in AYAs is clearly associated with regional differences. In 2021, according to the GBD classification, South Asia had the highest ASIR, ASMR, and ASDR at the regional level. In terms of SDI regions, the Low-middle SDI region recorded the highest ASIR, ASMR, and ASDR. These disparities emphasize the impact of socioeconomic factors, such as lifestyle, healthcare access, and environmental exposures, on health outcomes. We also analyzed the relationship between ASIR, ASMR, and ASDR in AYAs with LOC across 5 SDI regions. ASIR increased in all 5 regions, likely reflecting global advances in diagnostic techniques and instruments for these cancers. For ASMR and ASDR, both high and high-middle SDI regions saw declines over time, while middle, low-middle, and low SDI regions experienced increases. This may be closely related to the implementation of more effective health interventions, higher public awareness, and better treatment levels in regions with high and medium-high SDI. In contrast, the rising ASMR and ASDR in the middle, low-middle, and low SDI regions likely reflect a shortage of medical resources in these areas.[38] This may also be related to the dietary habits, oral health and other behaviors of citizens in these regions, the GBD 2019 study estimated that 83.3% (95% UI: 82.2–84.2%) of chewing tobacco users in 2019 lived in South Asia,[39] and previous studies have found that chewing tobacco increases the risk of oral cancer.[40] Secondly consumption of betel leaf and betel nut is a common social practice in South, Southeast and Pacific Asia as well as in North American and European immigrant communities, which has been identified as an important risk factor for oral, head, and neck cancer.[41,42] These results suggest that the problem of high LOC burden may be better mitigated by expanding and strengthening tobacco, betel nut control initiatives in medium, low-middle and low SDI areas. The observed trends emphasize the intricate, interdependent relationship between socioeconomic development and disease burden, especially concerning LOC in AYAs. This connection underscores the need for targeted public health strategies that are attuned to the unique needs of different socioeconomic groups. By aligning resource allocation and interventions with these specific challenges, health systems can more effectively address issues related to AYAs LOC, working to reduce disparities and enhance health outcomes across diverse populations.[43] While these findings provide valuable insights into regional disparities, it is essential to note that the present study is ecological in design, relying on aggregated population-level data. Therefore, the associations observed between SDI and cancer indicators (ASIR, ASMR, and ASDR) should not be interpreted as evidence of direct causality. Ecological studies are inherently limited by the ecological fallacy, which occurs when group-level associations are erroneously assumed to apply to individuals. Additionally, the lack of individual-level data restricts our ability to adjust for confounding variables such as personal behaviors, genetic predispositions, or detailed clinical characteristics. As such, while we report significant population-level patterns, these should be interpreted with caution. Further research using individual-level longitudinal data is needed to investigate the underlying causal mechanisms driving the observed disparities in LOC burden among AYAs.
Based on findings from the GBD 2021 study, this research offers a forward-looking projection of the global burden of LOC in AYAs from 2022 to 2041. The ASIR and ASDR of these cancers are expected to rise, while ASMR is predicted to show an overall decline, with a slight increase during the latter decade of the forecast. Incidence, deaths, and DALYs are anticipated to follow the same trends as the ASRs. Our projections indicate that by 2041, the burden of LOC will continue to rise, affecting men more than women. Addressing the health challenges posed by LOCs in AYAs remains a priority on global public health agendas due to their substantial impact worldwide. Effective management of this burden will require coordinated, sustained efforts targeting high-risk factors such as smoking, alcohol use, and other modifiable behaviors closely associated with LOC in AYAs. Additionally, enhancing prevention strategies, improving access to quality care, and investing in health promotion programs that raise awareness and encourage healthier lifestyles will be essential. These comprehensive approaches are crucial for reducing incidence and improving outcomes for LOCs in AYAs over time.
Our study offers valuable insights but has several limitations that merit acknowledgments. First, the accuracy and robustness of GBD estimates depend heavily on data quality and availability from sources such as vital registries, cancer registries, and autopsy systems. In low-income countries with limited healthcare resources, under-reporting and under-diagnosis may affect the reliability of these estimates.[44,45] This is particularly true in less developed countries, where the lack of high-quality cancer registry data may lead to an underestimation of the risk of adolescent LOC in countries with scarce raw data, thereby affecting our assessment of its burden. Second, despite significant sociocultural differences across regions, our study did not distinguish AYAs LOC burden by histological type or race/ethnicity, potentially overlooking critical variations in disease impact across populations. Third, as this is a population-level study, it is vulnerable to ecological fallacy; therefore, while associations between mortality, DALYs, and socio-demographic indicators are indicative, they should not be interpreted as causal. It is important to note that while we observe significant associations between socio-demographic factors and the burden of LOC, these findings are based on population-level data. Caution should be exercised when interpreting these associations as causal relationships, as ecological fallacy may influence the results. Future studies focusing on individual-level data are necessary to better understand the causal mechanisms. At the same time, there were very wide UIs for DALYs and deaths projected for some of the countries in this study, which mainly stemmed from inadequate data quality uncertainty in the modeling assumptions about future risk factors and significant heterogeneity of epidemiological characteristics of the study populations. Such wide UIs reduce the credibility of precise inferences about the burden of disease in a given country and limit the application of the results to specific policy formulation. Future research needs to improve this problem by strengthening basic data collection, optimizing model parameters introducing dynamic risk factor adjustment, and shortening the forecasting period. Future GBD studies should aim to incorporate this data for a more nuanced understanding of disease determinants.
It is important to note that while we observe significant associations between socio-demographic factors and the burden of LOC, these findings are based on population-level data. Caution should be exercised when interpreting these associations as causal relationships, as ecological fallacy may influence the results. Future studies focusing on individual-level data are necessary to better understand the causal mechanisms.
5. Conclusion
In conclusion, our study indicates that the burden of LOC is significantly higher among individuals aged 35 to 39, particularly men, and those residing in low-middle SDI regions. The global burden of this cancer has risen from 1990 to 2021, establishing it as a persistent global concern. This increasing burden necessitates urgent action and coordinated efforts to enhance early detection and treatment strategies. Our projections suggest that by 2041, the ASIR for men will rise annually in the first decade before plateauing, while for women, it will continue to increase each year. Both the ASMR and ASDR exhibit similar trends for both sexes, with ASMR and ASDR likely declining in men but rising in women. Additionally, our sex-stratified projections indicate that incidence and DALYs will increase, while mortality is expected to decrease among young men and women by 2041. We hope these findings provide valuable insights for policymakers to develop more effective disease control measures and prevention strategies.
Author contributions
Supervision: Xiaofei Zhang, Encun Hou.
Software: Xiaohan Ma, Sheng Chen.
Writing – original draft: Peiling Zuo, Yujia Wei.
Writing – review and editing: Peiling Zuo, Yujia Wei, Xiaohan Ma, Tong Wu, Sheng Chen.
Supplementary Material
Abbreviations:
- DALYs
- disability-adjusted life years
- ASDR
- age-standardized disability-adjusted life year rate
- ASIR
- age-standardized incidence rate
- ASMR
- age-standardized mortality rate
- ASR
- age-standardized rate
- AYAs
- adolescents and young adults
- BAPC
- Bayesian Age-Period-Cohort
- CI
- confidence interval
- EAPC
- estimated annual percentage change
- GBD
- Global Burden of Disease
- LOC
- lip and oral cavity cancer
- SDI
- Socio-Demographic Index
- UI
- uncertainty interval
This research was supported by the Guangxi Science and Technology Program Project (Guike AB21196012; 2021AB11025), funding for a Key Project on the Characteristics and Advantages of Chinese Medicine at Ruikang Hospital (2024), and a project aimed at enhancing the collaborative treatment capacity for malignant tumors using both Chinese and Western medicine.
This article does not contain any studies with human participants or animals performed by any of the authors.
The authors have no conflicts of interest to disclose.
All data generated or analyzed during this study are included in this published article [and its supplementary information files].
Supplemental Digital Content is available for this article.
How to cite this article: Zuo P, Wei Y, Ma X, Wu T, Chen S, Zhang X, Hou E. Global, regional, and national burdens of lip and oral cavity cancer in the adolescents and young adults from 1990 to 2021 and its predictions. Medicine 2025;104:45(e45601).
PZ and YW contributed to this article equally.
Contributor Information
Peiling Zuo, Email: 384287245@qq.com.
Yujia Wei, Email: 361491282@qq.com.
Xiaohan Ma, Email: 903638492@qq.com.
Tong Wu, Email: 1321241464@qq.com.
Sheng Chen, Email: 13005909276@163.com.
Xiaofei Zhang, Email: 631032537@qq.com.
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