Introduction
Africa, a continent abundant in natural resources yet facing economic and cultural challenges, is experiencing a significant rise in noncommunicable diseases (NCDs) such as cancer, diabetes, and heart disease [ 1 – 3 ] . This increasing burden is especially pronounced in sub-Saharan Africa, where healthcare services for chronic conditions like cancer and diabetes remain limited, despite relatively increase over the previous vaccination rates for infectious diseases such as HIV [ 4 – 6 ] . According to data from the World Health Organization, Africa’s healthcare market is projected to grow at an annual rate of 8.3% in the coming years. However, the continent accounts for only 1% of global pharmaceutical consumption, with a heavy reliance on imports for most medicines and over 90% of medical device products [ 7 ] . HIGHLIGHTS The study unveils the change in cancer incidence and mortality across Africa from 1990 to 2021, highlighting urgent healthcare challenges. Breast, cervical, and prostate cancers are identified as the most prevalent and deadliest, with breast cancer leading in both incidence and mortality across the continent. Genitourinary system cancers are the most burdensome, accounting for the highest incidence and mortality among the eight studied systems, especially among females. Significant regional variations exist, with Central and Eastern Africa showing high incidence and mortality of breast cancer, while Northern Africa faces a major burden from tracheal, bronchus, and lung cancer. Socioeconomic disparities, as measured by the Social Demographic Index. The study underscores the critical need for enhanced healthcare infrastructure, better access to diagnostic and treatment services, and comprehensive strategies to address the growing cancer burden in Africa.
Africa is one of the fastest-growing regions in the world in terms of population. Historically, healthcare funding in Africa has primarily relied on government allocations and international donations. Amidst these challenges, the issue of cancer also warrants significant attention. Cancer represents a critical health crisis in Africa, contributing substantially to mortality rates. Despite the predominant focus on infectious diseases, the increasing burden of cancer underscores the necessity for improved healthcare infrastructure, enhanced access to diagnostic and treatment services, and comprehensive strategies to address this complex disease. Cancer is a growing health crisis in Africa, disproportionately affecting individuals across all age groups and socioeconomic statuses [ 8 ] . Despite advancements in global healthcare, many African nations encounter unique challenges, including limited access to early detection, diagnostic facilities, and effective treatments. The health burden of cancer in Africa is profound, impacting not only individuals but also families and communities. Cancers such as cervical, breast, liver, and esophageal malignancies significantly contribute to morbidity and mortality rates [ 8 ] . Moreover, malignancies of the genitourinary, digestive, respiratory, and hematopoietic systems impose severe strains on healthcare infrastructure and economic stability. Delayed diagnosis, inadequate treatment options, and a lack of awareness exacerbate the suffering of countless individuals, highlighting the urgent need for immediate action.
We try to provide critical insights into these challenges by the Global Burden of Disease (GBD) study, shedding light on the distribution and health impact of 32 types of malignancies across eight major organ systems. By focusing on Africa’s cancer burden, this study seeks to emphasize the critical need for collaborative global efforts to address disparities in cancer care.
Methods
Study population and data collection
This study investigates the burden of cancer in Africa by leveraging data from the GBD Study 2021. The study population included individuals of all age groups and sexes diagnosed with cancer across the African continent, from 1990 to 2021. The dataset spans 54 African countries, categorized into eight GBD regions based on geographic and socioeconomic factors. The study population included individuals of all age groups and sexes diagnosed with cancer from 1990 to 2021, covering 54 African countries. The malignancies studied were categorized into eight major organ systems: Genitourinary system cancers (including ovarian, testicular, kidney, bladder, prostate, uterine, breast, and cervical cancers), digestive system cancers (including colon and rectum, esophageal, gallbladder and biliary tract, liver, pancreatic, and stomach cancers), respiratory system cancers (tracheal, bronchus, and lung cancer), head and neck cancers (lip and oral cavity, nasopharynx, other pharynx, larynx, thyroid, and eye cancers), skin and soft tissue cancers (malignant skin melanoma, non-melanoma skin cancer, soft tissue and other extraosseous sarcomas, and mesothelioma), bone and joint cancers (malignant neoplasms of bone and articular cartilage), lymphatic and hematopoietic system cancers (Hodgkin lymphoma, non-Hodgkin lymphoma, leukemia, and multiple myeloma), and nervous system cancers (neuroblastoma and other peripheral nervous cell tumors, brain and central nervous system cancer).
To assess socioeconomic and healthcare access disparities, we used the Social Demographic Index (SDI), which incorporates indicators such as per capita income, educational attainment, and fertility rates to measure regional socioeconomic status.
Statistical analysis
To analyze the data, we first calculated key metrics including cancer incidence, prevalence, mortality rates, and DALYs per 100 000 population. Age-standardized incidence rates (ASIRs) were calculated to compare cancer frequencies across countries with different age distributions. Temporal trends in cancer burden were assessed through joinpoint regression analysis, which identifies significant shifts in cancer incidence, mortality, and DALYs over time. Annual percentage changes (APCs) and magnitude of changes in cancer burden between 1990 and 2021. Our methodology adheres to the strengthened reporting guidelines of cohort, cross-sectional, and case-control studies in epidemiology and the STROCSS guidelines [ 9 , 10 ] . Additionally, Pearson correlation analysis was conducted to investigate the relationship between socioeconomic factors and cancer outcomes. Frontier analysis was used to assess the impact of healthcare access, infrastructure, and other socioeconomic variables on cancer burden across different countries, adjusting for SDI levels. Based on historical data and projected socioeconomic changes. This advanced statistical method integrates age, period, and cohort effects to provide a probabilistic forecast of cancer incidence, prevalence, mortality, and DALYs in Africa. All statistical analyses were performed using R version 4.2.3. Results were reported with 95% confidence intervals, and P values less than 0.05 were considered statistically significant. During preparation of this work the author(s) used ERNIE Bot in order to polish sentences. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication. Our use adheres to the Transparency In The reporting of Artificial Intelligence – the TITAN guideline [ 11 ] .
Ethical considerations
This study utilized publicly available data from the GBD Study ( https://vizhub.healthdata.org/gbd-results/result/c121d96d2fd53001376a8f1154f33b87 ). Since the data used in the analysis were anonymized and aggregated, no ethical approval was required. Patient confidentiality was maintained throughout the study by using de-identified and aggregated data.
Results
Tumor burden in Africa
Based on the data from 2021 regarding cancer incidence and mortality across 32 types of tumors in eight systems, certain trends are evident within the African population. Breast cancer ranks as the most prevalent and deadliest cancer, with an estimated 0.144 million new cases (95% UI: 0.126–0.165 million) and 0.074 million deaths (95% uncertainty interval [UI]: 0.065–0.084 million). Cervical cancer follows as the second most common, with 0.114 million new cases (95% UI: 0.096–0.135 million) and 0.063 million deaths (95% UI: 0.053–0.074 million). Prostate cancer ranks third in incidence, accounting for 0.072 million new cases (95% UI: 0.044–0.087 million). Colon and rectum cancer are fourth, with 0.061 million new cases (95% UI: 0.054–0.068 million). Although tracheal, bronchus, and lung cancer is fifth in incidence (0.053 million cases; 95% UI: 0.046–0.061 million), it ranks third in mortality, with 0.055 million deaths (95% UI: 0.048–0.063 million) (Tables 1 and 2 ). Table 1 Incidence of 32 cancer categories in Africa in 2021 Cancer type Incidence cases Incidence rate (crude, per 100 000) Both sexes Males Females Both sexes Males Females Numbers (95% UI) Rank Numbers (95% UI) Numbers (95% UI) Numbers (95% UI) Numbers (95% UI) Numbers (95% UI) Breast cancer 144 153 (125 915, 164 521) 1 3944 (2740, 6552) 140 210 (121 834, 160 211) 10.42 (9.1, 11.89) 0.58 (0.4, 0.96) 20.1 (17.46, 22.97) Cervical cancer 114 266 (96 326, 134 844) 2 N/A 114 266 (96 326, 134 844) 8.26 (6.96, 9.75) N/A 16.38 (13.81, 19.33) Prostate cancer 71 552 (44 236, 86 826) 3 71 552 (44 236, 86 826) N/A 5.17 (3.2, 6.28) 10.44 (6.45, 12.66) N/A Colon and rectum cancer 61 108 (53 950, 68 248) 4 32 125 (28 455, 36 623) 28 984 (25 149, 32 699) 4.42 (3.9, 4.93) 4.69 (4.15, 5.34) 4.15 (3.61, 4.69) Tracheal, bronchus, and lung cancer 53 398 (46 491, 60 894) 5 39 815 (34 638, 45 510) 13 583 (11 400, 15 638) 3.86 (3.36, 4.4) 5.81 (5.05, 6.64) 1.95 (1.63, 2.24) Liver cancer 49 888 (42 207, 58 696) 6 29 970 (25 052, 35 953) 19 918 (16 746, 23 619) 3.61 (3.05, 4.24) 4.37 (3.65, 5.24) 2.86 (2.4, 3.39) Stomach cancer 42 929 (32 937, 48 977) 7 24 415 (16 352, 28 922) 18 514 (15 789, 21 052) 3.1 (2.38, 3.54) 3.56 (2.38, 4.22) 2.65 (2.26, 3.02) Non-melanoma skin cancer 41 811 (33 513, 50 163) 8 24 095 (19 314, 28 816) 17 716 (14 050, 21 308) 3.02 (2.42, 3.63) 3.51 (2.82, 4.2) 2.54 (2.01, 3.05) Esophageal cancer 39 643 (33 484, 45 529) 9 23 980 (21 196, 27 589) 15 663 (10 256, 20 671) 2.87 (2.42, 3.29) 3.5 (3.09, 4.02) 2.25 (1.47, 2.96) Non-Hodgkin lymphoma 39 426 (32 763, 47 044) 10 22 733 (18 561, 27 969) 16 693 (13 388, 20 370) 2.85 (2.37, 3.4) 3.32 (2.71, 4.08) 2.39 (1.92, 2.92) Leukemia 29 015 (19 700, 35 620) 11 16 655 (9406, 21 860) 12 360 (8049, 14 848) 2.1 (1.42, 2.58) 2.43 (1.37, 3.19) 1.77 (1.15, 2.13) Bladder cancer 24 584 (20 767, 30 774) 12 18 385 (15 006, 24 490) 6199 (5326, 7194) 1.78 (1.5, 2.22) 2.68 (2.19, 3.57) 0.89 (0.76, 1.03) Ovarian cancer 21 805 (16 639, 25 514) 13 N/A 21 805 (16 639, 25 514) 1.58 (1.2, 1.84) N/A 3.13 (2.39, 3.66) Other malignant neoplasms 21 117 (16 714, 25 277) 14 8860 (6760, 11 532) 12 258 (9190, 14 943) 1.53 (1.21, 1.83) 1.29 (0.99, 1.68) 1.76 (1.32, 2.14) Brain and central nervous system cancer 18 537 (13 347, 23 195) 15 9674 (5645, 12 984) 8863 (6407, 10 338) 1.34 (0.96, 1.68) 1.41 (0.82, 1.89) 1.27 (0.92, 1.48) Pancreatic cancer 17 034 (14 794, 19 292) 16 9174 (7974, 10 411) 7860 (6508, 9063) 1.23 (1.07, 1.39) 1.34 (1.16, 1.52) 1.13 (0.93, 1.3) Uterine cancer 15 415 (11 913, 18 580) 17 N/A 15 415 (11 913, 18 580) 1.11 (0.86, 1.34) N/A 2.21 (1.71, 2.66) Lip and oral cavity cancer 15 318 (13 008, 17 710) 18 8803 (7345, 10 224) 6516 (5494, 7703) 1.11 (0.94, 1.28) 1.28 (1.07, 1.49) 0.93 (0.79, 1.1) Thyroid cancer 14 906 (11 771, 19 222) 19 3841 (2972, 4721) 11 065 (8373, 14 989) 1.08 (0.85, 1.39) 0.56 (0.43, 0.69) 1.59 (1.2, 2.15) Kidney cancer 12 378 (9565, 14 936) 20 7333 (5685, 8793) 5045 (3884, 6353) 0.89 (0.69, 1.08) 1.07 (0.83, 1.28) 0.72 (0.56, 0.91) Malignant neoplasm of bone and articular cartilage 12 077 (9533, 16 578) 21 7410 (5756, 10 506) 4667 (3305, 7080) 0.87 (0.69, 1.2) 1.08 (0.84, 1.53) 0.67 (0.47, 1.01) Soft tissue and other extraosseous sarcomas 11 509 (8629, 17 179) 22 6548 (4495, 11 696) 4961 (3593, 7550) 0.83 (0.62, 1.24) 0.95 (0.66, 1.71) 0.71 (0.52, 1.08) Larynx cancer 10 851 (9232, 12 390) 23 9376 (8039, 10 644) 1475 (1011, 1896) 0.78 (0.67, 0.9) 1.37 (1.17, 1.55) 0.21 (0.14, 0.27) Eye cancer 9700 (6413, 14 066) 24 4541 (2411, 7910) 5158 (3207, 7970) 0.7 (0.46, 1.02) 0.66 (0.35, 1.15) 0.74 (0.46, 1.14) Hodgkin lymphoma 9616 (5045, 12 753) 25 5508 (2633, 7696) 4108 (1899, 6002) 0.7 (0.36, 0.92) 0.8 (0.38, 1.12) 0.59 (0.27, 0.86) Nasopharynx cancer 7214 (5801, 8747) 26 4551 (3519, 5767) 2663 (2212, 3469) 0.52 (0.42, 0.63) 0.66 (0.51, 0.84) 0.38 (0.32, 0.5) Malignant skin melanoma 6687 (3558, 8470) 27 2922 (1465, 3948) 3766 (1754, 5176) 0.48 (0.26, 0.61) 0.43 (0.21, 0.58) 0.54 (0.25, 0.74) Multiple myeloma 6082 (3937, 7707) 28 2910 (1774, 3968) 3172 (1756, 4020) 0.44 (0.28, 0.56) 0.42 (0.26, 0.58) 0.45 (0.25, 0.58) Gallbladder and biliary tract cancer 4922 (3581, 5937) 29 1730 (1041, 2192) 3192 (2061, 4058) 0.36 (0.26, 0.43) 0.25 (0.15, 0.32) 0.46 (0.3, 0.58) Other pharynx cancer 3387 (2692, 4197) 30 2337 (1887, 2982) 1049 (680, 1275) 0.24 (0.19, 0.3) 0.34 (0.28, 0.43) 0.15 (0.1, 0.18) Testicular cancer 3135 (2683, 3657) 31 3135 (2683, 3657) N/A 0.23 (0.19, 0.26) 0.46 (0.39, 0.53) N/A Mesothelioma 1794 (1222, 2433) 32 1118 (719, 1664) 676 (442, 1048) 0.13 (0.09, 0.18) 0.16 (0.1, 0.24) 0.1 (0.06, 0.15) Neuroblastoma and other peripheral nervous cell tumors 1691 (861, 2712) 33 1060 (520, 1729) 631 (317, 1081) 0.12 (0.06, 0.2) 0.15 (0.08, 0.25) 0.09 (0.05, 0.15) Table 2 Mortality of 32 cancer categories in Africa in 2021 Cancer type Death cases Death rate (crude, per 100 000) Both sexes Males Females Both sexes Males Females Numbers (95% UI) Rank Numbers (95% UI) Numbers (95% UI) Numbers (95% UI) Numbers (95% UI) Numbers (95% UI) Breast cancer 74 156 (64 997, 84 040) 1 2641 (1845, 4431) 71 514 (62 639, 81 242) 10.69 (9.5, 11.96) 0.91 (0.64, 1.49) 19.58 (17.37, 22.03) Cervical cancer 63 060 (53 318, 73 982) 2 N/A 63 060 (53 318, 73 982) 8.23 (7.02, 9.59) N/A 15.83 (13.5, 18.45) Tracheal, bronchus, and lung cancer 55 451 (48 369, 63 263) 3 41 387 (36 086, 47 474) 14 064 (11 818, 16 156) 8.9 (7.84, 10.15) 14 (12.36, 16.02) 4.32 (3.65, 4.95) Prostate cancer 51 716 (31 419, 63 100) 4 51 716 (31 419, 63 100) N/A 10.93 (6.63, 13.21) 23.74 (14.39, 28.66) N/A Liver cancer 50 894 (43 132, 59 812) 5 30 326 (25 403, 36 386) 20 568 (17 306, 24 374) 7.67 (6.6, 8.88) 9.33 (7.9, 11) 6.14 (5.27, 7.18) Colon and rectum cancer 48 504 (43 150, 54 115) 6 26 256 (23 312, 29 780) 22 248 (19 414, 25 018) 8.29 (7.43, 9.16) 9.47 (8.52, 10.58) 7.25 (6.42, 8.11) Stomach cancer 42 260 (32 525, 48 279) 7 23 580 (15 869, 27 864) 18 680 (15 954, 21 218) 6.85 (5.32, 7.78) 8.03 (5.49, 9.37) 5.79 (5.02, 6.56) Esophageal cancer 40 983 (34 595, 47 142) 8 24 620 (21 762, 28 300) 16 363 (10 726, 21 493) 6.51 (5.54, 7.42) 7.91 (7.03, 9.03) 5.21 (3.42, 6.81) Non-Hodgkin lymphoma 28 779 (23 837, 34 057) 9 16 442 (13 509, 20 122) 12 337 (9909, 15 124) 3.68 (3.1, 4.23) 4.22 (3.54, 5.11) 3.17 (2.62, 3.78) Leukemia 25 622 (17 593, 31 225) 10 14 680 (8635, 19 217) 10 941 (7265, 13 155) 2.86 (2.02, 3.44) 3.41 (2.06, 4.37) 2.37 (1.6, 2.86) Other malignant neoplasms 18 248 (14 562, 21 880) 11 7894 (6105, 10 257) 10 353 (7841, 12 729) 2.36 (1.96, 2.76) 2.09 (1.64, 2.72) 2.61 (2.02, 3.16) Pancreatic cancer 17 646 (15 298, 19 974) 12 9366 (8151, 10 613) 8280 (6862, 9548) 2.92 (2.54, 3.29) 3.15 (2.78, 3.54) 2.7 (2.25, 3.09) Brain and central nervous system cancer 15 646 (11 184, 19 632) 13 8141 (4752, 10 976) 7506 (5396, 8758) 1.72 (1.23, 2.13) 1.87 (1.1, 2.54) 1.59 (1.14, 1.84) Bladder cancer 13 313 (11 414, 16 045) 14 9202 (7659, 11 878) 4112 (3552, 4783) 2.51 (2.17, 3.03) 3.73 (3.13, 4.8) 1.45 (1.27, 1.68) Ovarian cancer 13 062 (10 066, 15 303) 15 N/A 13 062 (10 066, 15 303) 1.89 (1.47, 2.21) N/A 3.62 (2.81, 4.22) Lip and oral cavity cancer 10 252 (8760, 11 831) 16 6122 (5126, 7064) 4130 (3505, 4874) 1.56 (1.35, 1.77) 1.89 (1.62, 2.16) 1.25 (1.07, 1.46) Malignant neoplasm of bone and articular cartilage 8583 (6858, 11 906) 17 5297 (4168, 7496) 3286 (2345, 4999) 0.89 (0.72, 1.21) 1.13 (0.89, 1.58) 0.66 (0.48, 0.98) Larynx cancer 8549 (7265, 9764) 18 7376 (6355, 8359) 1173 (812, 1511) 1.33 (1.15, 1.5) 2.42 (2.11, 2.72) 0.34 (0.24, 0.44) Kidney cancer 7145 (5567, 8539) 19 4695 (3667, 5595) 2450 (1913, 3080) 0.98 (0.8, 1.14) 1.35 (1.11, 1.55) 0.64 (0.52, 0.79) Soft tissue and other extraosseous sarcomas 7079 (5404, 10 682) 20 4020 (2802, 7158) 3059 (2279, 4446) 0.83 (0.65, 1.24) 0.98 (0.69, 1.73) 0.69 (0.53, 1.01) Hodgkin lymphoma 6643 (3464, 8878) 21 3870 (1836, 5412) 2773 (1278, 4126) 0.66 (0.36, 0.87) 0.79 (0.39, 1.1) 0.54 (0.26, 0.79) Nasopharynx cancer 6558 (5261, 7965) 22 4176 (3228, 5291) 2382 (1984, 3130) 0.83 (0.68, 1) 1.11 (0.88, 1.38) 0.58 (0.49, 0.75) Uterine cancer 6038 (4669, 7351) 23 N/A 6038 (4669, 7351) 0.99 (0.76, 1.2) N/A 1.87 (1.43, 2.27) Multiple myeloma 5609 (3604, 7039) 24 2675 (1622, 3616) 2934 (1612, 3709) 0.92 (0.59, 1.14) 0.92 (0.56, 1.24) 0.92 (0.51, 1.15) Gallbladder and biliary tract cancer 4938 (3611, 5986) 25 1714 (1036, 2168) 3224 (2081, 4090) 0.87 (0.64, 1.05) 0.64 (0.39, 0.81) 1.08 (0.69, 1.37) Eye cancer 4538 (3334, 5921) 26 2214 (1278, 3423) 2324 (1583, 3403) 0.49 (0.35, 0.67) 0.49 (0.26, 0.83) 0.49 (0.34, 0.74) Malignant skin melanoma 3986 (2192, 5117) 27 1945 (1004, 2607) 2042 (988, 2885) 0.56 (0.31, 0.71) 0.58 (0.3, 0.77) 0.55 (0.27, 0.75) Thyroid cancer 3171 (2532, 4016) 28 1175 (890, 1455) 1996 (1526, 2725) 0.47 (0.38, 0.59) 0.37 (0.28, 0.45) 0.57 (0.44, 0.76) Other pharynx cancer 2735 (2177, 3395) 29 1932 (1556, 2465) 803 (519, 987) 0.39 (0.31, 0.48) 0.57 (0.46, 0.72) 0.22 (0.15, 0.28) Mesothelioma 1699 (1159, 2308) 30 1071 (690, 1598) 628 (412, 989) 0.26 (0.18, 0.35) 0.35 (0.23, 0.52) 0.18 (0.12, 0.29) Non-melanoma skin cancer 1596 (752, 2135) 31 1023 (339, 1456) 572 (384, 772) 0.3 (0.15, 0.4) 0.39 (0.13, 0.55) 0.22 (0.15, 0.3) Testicular cancer 1017 (851, 1200) 32 1017 (851, 1200) N/A 0.1 (0.08, 0.11) 0.2 (0.17, 0.24) N/A Neuroblastoma and other peripheral nervous cell tumors 761 (440, 1132) 33 468 (268, 699) 293 (169, 469) 0.05 (0.03, 0.07) 0.06 (0.04, 0.08) 0.04 (0.02, 0.06) Other neoplasms 436 (287, 798) 34 217 (85, 593) 219 (167, 262) 0.08 (0.06, 0.15) 0.08 (0.03, 0.23) 0.08 (0.06, 0.1)
Table 1
Incidence of 32 cancer categories in Africa in 2021
| Cancer type | Incidence cases | Incidence rate (crude, per 100 000) | |||||
| Both sexes | Males | Females | Both sexes | Males | Females | ||
| Numbers (95% UI) | Rank | Numbers (95% UI) | Numbers (95% UI) | Numbers (95% UI) | Numbers (95% UI) | Numbers (95% UI) | |
| Breast cancer | 144 153 (125 915, 164 521) | 1 | 3944 (2740, 6552) | 140 210 (121 834, 160 211) | 10.42 (9.1, 11.89) | 0.58 (0.4, 0.96) | 20.1 (17.46, 22.97) |
| Cervical cancer | 114 266 (96 326, 134 844) | 2 | N/A | 114 266 (96 326, 134 844) | 8.26 (6.96, 9.75) | N/A | 16.38 (13.81, 19.33) |
| Prostate cancer | 71 552 (44 236, 86 826) | 3 | 71 552 (44 236, 86 826) | N/A | 5.17 (3.2, 6.28) | 10.44 (6.45, 12.66) | N/A |
| Colon and rectum cancer | 61 108 (53 950, 68 248) | 4 | 32 125 (28 455, 36 623) | 28 984 (25 149, 32 699) | 4.42 (3.9, 4.93) | 4.69 (4.15, 5.34) | 4.15 (3.61, 4.69) |
| Tracheal, bronchus, and lung cancer | 53 398 (46 491, 60 894) | 5 | 39 815 (34 638, 45 510) | 13 583 (11 400, 15 638) | 3.86 (3.36, 4.4) | 5.81 (5.05, 6.64) | 1.95 (1.63, 2.24) |
| Liver cancer | 49 888 (42 207, 58 696) | 6 | 29 970 (25 052, 35 953) | 19 918 (16 746, 23 619) | 3.61 (3.05, 4.24) | 4.37 (3.65, 5.24) | 2.86 (2.4, 3.39) |
| Stomach cancer | 42 929 (32 937, 48 977) | 7 | 24 415 (16 352, 28 922) | 18 514 (15 789, 21 052) | 3.1 (2.38, 3.54) | 3.56 (2.38, 4.22) | 2.65 (2.26, 3.02) |
| Non-melanoma skin cancer | 41 811 (33 513, 50 163) | 8 | 24 095 (19 314, 28 816) | 17 716 (14 050, 21 308) | 3.02 (2.42, 3.63) | 3.51 (2.82, 4.2) | 2.54 (2.01, 3.05) |
| Esophageal cancer | 39 643 (33 484, 45 529) | 9 | 23 980 (21 196, 27 589) | 15 663 (10 256, 20 671) | 2.87 (2.42, 3.29) | 3.5 (3.09, 4.02) | 2.25 (1.47, 2.96) |
| Non-Hodgkin lymphoma | 39 426 (32 763, 47 044) | 10 | 22 733 (18 561, 27 969) | 16 693 (13 388, 20 370) | 2.85 (2.37, 3.4) | 3.32 (2.71, 4.08) | 2.39 (1.92, 2.92) |
| Leukemia | 29 015 (19 700, 35 620) | 11 | 16 655 (9406, 21 860) | 12 360 (8049, 14 848) | 2.1 (1.42, 2.58) | 2.43 (1.37, 3.19) | 1.77 (1.15, 2.13) |
| Bladder cancer | 24 584 (20 767, 30 774) | 12 | 18 385 (15 006, 24 490) | 6199 (5326, 7194) | 1.78 (1.5, 2.22) | 2.68 (2.19, 3.57) | 0.89 (0.76, 1.03) |
| Ovarian cancer | 21 805 (16 639, 25 514) | 13 | N/A | 21 805 (16 639, 25 514) | 1.58 (1.2, 1.84) | N/A | 3.13 (2.39, 3.66) |
| Other malignant neoplasms | 21 117 (16 714, 25 277) | 14 | 8860 (6760, 11 532) | 12 258 (9190, 14 943) | 1.53 (1.21, 1.83) | 1.29 (0.99, 1.68) | 1.76 (1.32, 2.14) |
| Brain and central nervous system cancer | 18 537 (13 347, 23 195) | 15 | 9674 (5645, 12 984) | 8863 (6407, 10 338) | 1.34 (0.96, 1.68) | 1.41 (0.82, 1.89) | 1.27 (0.92, 1.48) |
| Pancreatic cancer | 17 034 (14 794, 19 292) | 16 | 9174 (7974, 10 411) | 7860 (6508, 9063) | 1.23 (1.07, 1.39) | 1.34 (1.16, 1.52) | 1.13 (0.93, 1.3) |
| Uterine cancer | 15 415 (11 913, 18 580) | 17 | N/A | 15 415 (11 913, 18 580) | 1.11 (0.86, 1.34) | N/A | 2.21 (1.71, 2.66) |
| Lip and oral cavity cancer | 15 318 (13 008, 17 710) | 18 | 8803 (7345, 10 224) | 6516 (5494, 7703) | 1.11 (0.94, 1.28) | 1.28 (1.07, 1.49) | 0.93 (0.79, 1.1) |
| Thyroid cancer | 14 906 (11 771, 19 222) | 19 | 3841 (2972, 4721) | 11 065 (8373, 14 989) | 1.08 (0.85, 1.39) | 0.56 (0.43, 0.69) | 1.59 (1.2, 2.15) |
| Kidney cancer | 12 378 (9565, 14 936) | 20 | 7333 (5685, 8793) | 5045 (3884, 6353) | 0.89 (0.69, 1.08) | 1.07 (0.83, 1.28) | 0.72 (0.56, 0.91) |
| Malignant neoplasm of bone and articular cartilage | 12 077 (9533, 16 578) | 21 | 7410 (5756, 10 506) | 4667 (3305, 7080) | 0.87 (0.69, 1.2) | 1.08 (0.84, 1.53) | 0.67 (0.47, 1.01) |
| Soft tissue and other extraosseous sarcomas | 11 509 (8629, 17 179) | 22 | 6548 (4495, 11 696) | 4961 (3593, 7550) | 0.83 (0.62, 1.24) | 0.95 (0.66, 1.71) | 0.71 (0.52, 1.08) |
| Larynx cancer | 10 851 (9232, 12 390) | 23 | 9376 (8039, 10 644) | 1475 (1011, 1896) | 0.78 (0.67, 0.9) | 1.37 (1.17, 1.55) | 0.21 (0.14, 0.27) |
| Eye cancer | 9700 (6413, 14 066) | 24 | 4541 (2411, 7910) | 5158 (3207, 7970) | 0.7 (0.46, 1.02) | 0.66 (0.35, 1.15) | 0.74 (0.46, 1.14) |
| Hodgkin lymphoma | 9616 (5045, 12 753) | 25 | 5508 (2633, 7696) | 4108 (1899, 6002) | 0.7 (0.36, 0.92) | 0.8 (0.38, 1.12) | 0.59 (0.27, 0.86) |
| Nasopharynx cancer | 7214 (5801, 8747) | 26 | 4551 (3519, 5767) | 2663 (2212, 3469) | 0.52 (0.42, 0.63) | 0.66 (0.51, 0.84) | 0.38 (0.32, 0.5) |
| Malignant skin melanoma | 6687 (3558, 8470) | 27 | 2922 (1465, 3948) | 3766 (1754, 5176) | 0.48 (0.26, 0.61) | 0.43 (0.21, 0.58) | 0.54 (0.25, 0.74) |
| Multiple myeloma | 6082 (3937, 7707) | 28 | 2910 (1774, 3968) | 3172 (1756, 4020) | 0.44 (0.28, 0.56) | 0.42 (0.26, 0.58) | 0.45 (0.25, 0.58) |
| Gallbladder and biliary tract cancer | 4922 (3581, 5937) | 29 | 1730 (1041, 2192) | 3192 (2061, 4058) | 0.36 (0.26, 0.43) | 0.25 (0.15, 0.32) | 0.46 (0.3, 0.58) |
| Other pharynx cancer | 3387 (2692, 4197) | 30 | 2337 (1887, 2982) | 1049 (680, 1275) | 0.24 (0.19, 0.3) | 0.34 (0.28, 0.43) | 0.15 (0.1, 0.18) |
| Testicular cancer | 3135 (2683, 3657) | 31 | 3135 (2683, 3657) | N/A | 0.23 (0.19, 0.26) | 0.46 (0.39, 0.53) | N/A |
| Mesothelioma | 1794 (1222, 2433) | 32 | 1118 (719, 1664) | 676 (442, 1048) | 0.13 (0.09, 0.18) | 0.16 (0.1, 0.24) | 0.1 (0.06, 0.15) |
| Neuroblastoma and other peripheral nervous cell tumors | 1691 (861, 2712) | 33 | 1060 (520, 1729) | 631 (317, 1081) | 0.12 (0.06, 0.2) | 0.15 (0.08, 0.25) | 0.09 (0.05, 0.15) |
Table 2
Mortality of 32 cancer categories in Africa in 2021
| Cancer type | Death cases | Death rate (crude, per 100 000) | |||||
| Both sexes | Males | Females | Both sexes | Males | Females | ||
| Numbers (95% UI) | Rank | Numbers (95% UI) | Numbers (95% UI) | Numbers (95% UI) | Numbers (95% UI) | Numbers (95% UI) | |
| Breast cancer | 74 156 (64 997, 84 040) | 1 | 2641 (1845, 4431) | 71 514 (62 639, 81 242) | 10.69 (9.5, 11.96) | 0.91 (0.64, 1.49) | 19.58 (17.37, 22.03) |
| Cervical cancer | 63 060 (53 318, 73 982) | 2 | N/A | 63 060 (53 318, 73 982) | 8.23 (7.02, 9.59) | N/A | 15.83 (13.5, 18.45) |
| Tracheal, bronchus, and lung cancer | 55 451 (48 369, 63 263) | 3 | 41 387 (36 086, 47 474) | 14 064 (11 818, 16 156) | 8.9 (7.84, 10.15) | 14 (12.36, 16.02) | 4.32 (3.65, 4.95) |
| Prostate cancer | 51 716 (31 419, 63 100) | 4 | 51 716 (31 419, 63 100) | N/A | 10.93 (6.63, 13.21) | 23.74 (14.39, 28.66) | N/A |
| Liver cancer | 50 894 (43 132, 59 812) | 5 | 30 326 (25 403, 36 386) | 20 568 (17 306, 24 374) | 7.67 (6.6, 8.88) | 9.33 (7.9, 11) | 6.14 (5.27, 7.18) |
| Colon and rectum cancer | 48 504 (43 150, 54 115) | 6 | 26 256 (23 312, 29 780) | 22 248 (19 414, 25 018) | 8.29 (7.43, 9.16) | 9.47 (8.52, 10.58) | 7.25 (6.42, 8.11) |
| Stomach cancer | 42 260 (32 525, 48 279) | 7 | 23 580 (15 869, 27 864) | 18 680 (15 954, 21 218) | 6.85 (5.32, 7.78) | 8.03 (5.49, 9.37) | 5.79 (5.02, 6.56) |
| Esophageal cancer | 40 983 (34 595, 47 142) | 8 | 24 620 (21 762, 28 300) | 16 363 (10 726, 21 493) | 6.51 (5.54, 7.42) | 7.91 (7.03, 9.03) | 5.21 (3.42, 6.81) |
| Non-Hodgkin lymphoma | 28 779 (23 837, 34 057) | 9 | 16 442 (13 509, 20 122) | 12 337 (9909, 15 124) | 3.68 (3.1, 4.23) | 4.22 (3.54, 5.11) | 3.17 (2.62, 3.78) |
| Leukemia | 25 622 (17 593, 31 225) | 10 | 14 680 (8635, 19 217) | 10 941 (7265, 13 155) | 2.86 (2.02, 3.44) | 3.41 (2.06, 4.37) | 2.37 (1.6, 2.86) |
| Other malignant neoplasms | 18 248 (14 562, 21 880) | 11 | 7894 (6105, 10 257) | 10 353 (7841, 12 729) | 2.36 (1.96, 2.76) | 2.09 (1.64, 2.72) | 2.61 (2.02, 3.16) |
| Pancreatic cancer | 17 646 (15 298, 19 974) | 12 | 9366 (8151, 10 613) | 8280 (6862, 9548) | 2.92 (2.54, 3.29) | 3.15 (2.78, 3.54) | 2.7 (2.25, 3.09) |
| Brain and central nervous system cancer | 15 646 (11 184, 19 632) | 13 | 8141 (4752, 10 976) | 7506 (5396, 8758) | 1.72 (1.23, 2.13) | 1.87 (1.1, 2.54) | 1.59 (1.14, 1.84) |
| Bladder cancer | 13 313 (11 414, 16 045) | 14 | 9202 (7659, 11 878) | 4112 (3552, 4783) | 2.51 (2.17, 3.03) | 3.73 (3.13, 4.8) | 1.45 (1.27, 1.68) |
| Ovarian cancer | 13 062 (10 066, 15 303) | 15 | N/A | 13 062 (10 066, 15 303) | 1.89 (1.47, 2.21) | N/A | 3.62 (2.81, 4.22) |
| Lip and oral cavity cancer | 10 252 (8760, 11 831) | 16 | 6122 (5126, 7064) | 4130 (3505, 4874) | 1.56 (1.35, 1.77) | 1.89 (1.62, 2.16) | 1.25 (1.07, 1.46) |
| Malignant neoplasm of bone and articular cartilage | 8583 (6858, 11 906) | 17 | 5297 (4168, 7496) | 3286 (2345, 4999) | 0.89 (0.72, 1.21) | 1.13 (0.89, 1.58) | 0.66 (0.48, 0.98) |
| Larynx cancer | 8549 (7265, 9764) | 18 | 7376 (6355, 8359) | 1173 (812, 1511) | 1.33 (1.15, 1.5) | 2.42 (2.11, 2.72) | 0.34 (0.24, 0.44) |
| Kidney cancer | 7145 (5567, 8539) | 19 | 4695 (3667, 5595) | 2450 (1913, 3080) | 0.98 (0.8, 1.14) | 1.35 (1.11, 1.55) | 0.64 (0.52, 0.79) |
| Soft tissue and other extraosseous sarcomas | 7079 (5404, 10 682) | 20 | 4020 (2802, 7158) | 3059 (2279, 4446) | 0.83 (0.65, 1.24) | 0.98 (0.69, 1.73) | 0.69 (0.53, 1.01) |
| Hodgkin lymphoma | 6643 (3464, 8878) | 21 | 3870 (1836, 5412) | 2773 (1278, 4126) | 0.66 (0.36, 0.87) | 0.79 (0.39, 1.1) | 0.54 (0.26, 0.79) |
| Nasopharynx cancer | 6558 (5261, 7965) | 22 | 4176 (3228, 5291) | 2382 (1984, 3130) | 0.83 (0.68, 1) | 1.11 (0.88, 1.38) | 0.58 (0.49, 0.75) |
| Uterine cancer | 6038 (4669, 7351) | 23 | N/A | 6038 (4669, 7351) | 0.99 (0.76, 1.2) | N/A | 1.87 (1.43, 2.27) |
| Multiple myeloma | 5609 (3604, 7039) | 24 | 2675 (1622, 3616) | 2934 (1612, 3709) | 0.92 (0.59, 1.14) | 0.92 (0.56, 1.24) | 0.92 (0.51, 1.15) |
| Gallbladder and biliary tract cancer | 4938 (3611, 5986) | 25 | 1714 (1036, 2168) | 3224 (2081, 4090) | 0.87 (0.64, 1.05) | 0.64 (0.39, 0.81) | 1.08 (0.69, 1.37) |
| Eye cancer | 4538 (3334, 5921) | 26 | 2214 (1278, 3423) | 2324 (1583, 3403) | 0.49 (0.35, 0.67) | 0.49 (0.26, 0.83) | 0.49 (0.34, 0.74) |
| Malignant skin melanoma | 3986 (2192, 5117) | 27 | 1945 (1004, 2607) | 2042 (988, 2885) | 0.56 (0.31, 0.71) | 0.58 (0.3, 0.77) | 0.55 (0.27, 0.75) |
| Thyroid cancer | 3171 (2532, 4016) | 28 | 1175 (890, 1455) | 1996 (1526, 2725) | 0.47 (0.38, 0.59) | 0.37 (0.28, 0.45) | 0.57 (0.44, 0.76) |
| Other pharynx cancer | 2735 (2177, 3395) | 29 | 1932 (1556, 2465) | 803 (519, 987) | 0.39 (0.31, 0.48) | 0.57 (0.46, 0.72) | 0.22 (0.15, 0.28) |
| Mesothelioma | 1699 (1159, 2308) | 30 | 1071 (690, 1598) | 628 (412, 989) | 0.26 (0.18, 0.35) | 0.35 (0.23, 0.52) | 0.18 (0.12, 0.29) |
| Non-melanoma skin cancer | 1596 (752, 2135) | 31 | 1023 (339, 1456) | 572 (384, 772) | 0.3 (0.15, 0.4) | 0.39 (0.13, 0.55) | 0.22 (0.15, 0.3) |
| Testicular cancer | 1017 (851, 1200) | 32 | 1017 (851, 1200) | N/A | 0.1 (0.08, 0.11) | 0.2 (0.17, 0.24) | N/A |
| Neuroblastoma and other peripheral nervous cell tumors | 761 (440, 1132) | 33 | 468 (268, 699) | 293 (169, 469) | 0.05 (0.03, 0.07) | 0.06 (0.04, 0.08) | 0.04 (0.02, 0.06) |
| Other neoplasms | 436 (287, 798) | 34 | 217 (85, 593) | 219 (167, 262) | 0.08 (0.06, 0.15) | 0.08 (0.03, 0.23) | 0.08 (0.06, 0.1) |
In males, prostate cancer leads both in incidence and mortality, with 0.072 million new cases (95% UI: 0.044–0.087 million) and 0.052 million deaths (95% UI: 0.031–0.063 million). The next most common cancers in terms of incidence in men are tracheal, bronchus, and lung cancer, followed by colon and rectum cancer. In terms of mortality among men, after prostate cancer, tracheal, bronchus, and lung cancer, along with liver cancer, pose significant risks (Tables 1 and 2 ).
For females, breast cancer is the most prevalent and deadliest, with 0.140 million new cases (95% UI: 0.122–0.160 million) and 0.072 million deaths (95% UI: 0.063–0.081 million). Cervical cancer remains the second most common and deadly cancer among women, with 0.114 million new cases (95% UI: 0.096–0.135 million) and 0.063 million deaths (95% UI: 0.053–0.074 million) (Tables 1 and 2 ).
The analysis of cancer burden across eight major organ systems in Africa reveals significant disparities in incidence rates, with genitourinary system cancers emerging as the most prominent cancer burden. Zimbabwe exhibits the highest ASIR for these cancers at 105.97, followed by Zambia (ASIR = 86.87), Swaziland (ASIR = 86.16), Lesotho (ASIR = 85.26), Uganda (ASIR = 82.28), and South Africa (ASIR = 80.35). Digestive system cancers are the second most significant cancer burden in Africa. Cape Verde reports the highest ASIR of 59.90, with Swaziland (ASIR = 53.87), Zimbabwe (ASIR = 52.21), and Lesotho (ASIR = 50.42) also experiencing notable incidence rates. Skin and soft tissue cancers are most prevalent in South Africa, with an ASIR of 34.53. Namibia (ASIR = 24.14), Lesotho (ASIR = 21.80), Swaziland (ASIR = 21.72), and Botswana (ASIR = 20.74). Respiratory system cancers are predominantly observed in Libya, with an ASIR of 23.34, followed by Lesotho (ASIR = 21.34). Head and neck cancers have the highest incidence in Uganda, with an ASIR of 18.40. Zambia (ASIR = 18.29), Namibia (ASIR = 17.97), and Libya (ASIR = 16.45) also face significant burdens from these cancer types, suggesting the need for increased awareness and early detection efforts. Lymphatic and hematopoietic system cancers are most prevalent in Libya, with an ASIR of 24.32, followed by Zimbabwe (ASIR = 19.36), Uganda (ASIR = 16.73), and Malawi (ASIR = 16.67) (Fig. 1 ). Figure 1. Incidence of malignant tumor across eight systems in Africa in 2021. (A) Incidence of bone and joint cancers in Africa. (B) Incidence of digestive system cancers in Africa. (C) Incidence of genitourinary system cancers in Africa. (D) Incidence of head and neck cancers in Africa. (E) Incidence of lymphatic and hematopoietic system cancers in Africa. (F) Incidence of nervous system cancers in Africa. (G) Incidence of respiratory system cancers in Africa. (H) Incidence of skin and soft tissue cancers in Africa.
Nervous system cancers and bone and joint cancers present comparatively lower burdens across the eight cancer systems in Africa. Egypt shows the highest incidence for nervous system cancers with an ASIR of 6.86, followed by Libya (ASIR = 5.88). Bone and joint cancers are most prevalent in Egypt with an ASIR of 1.70, with Kenya (ASIR = 1.53) and Ethiopia (ASIR = 1.51) also showing higher rates relative to other regions (Fig. 1 ).
Genitourinary system cancers account for the highest proportion of incidence at 44.0%, making it the most significant cancer burden among the eight systems. These cancers also contribute to the highest percentage of deaths, representing 39.4% of all cancer-related mortality within the eight systems. Digestive system cancers follow, accounting for 23.1% of cancer incidence and 30.4% of cancer-related deaths. In male patients, genitourinary system cancers again have the highest incidence, comprising 30.7% of cancers across the eight systems, indicating a substantial health burden. However, they rank second in cancer-related deaths, accounting for 39.4%. Digestive system cancers are the second most common in incidence among males at 27.5%, but they are the leading cause of cancer-related deaths at 32.8%. For female patients, the pattern shifts more prominently toward genitourinary system cancers, which have the highest incidence at 57.2% and the highest mortality rate at 50.8%. Digestive system cancers remain significant, with an incidence of 18.7% and a mortality rate of 27.2%, ranking second in both categories (Fig. 2 ). Figure 2. Proportion of incidence and death of malignant tumor across eight systems in Africa in 2021. (A) Proportion of incidence of malignant tumor across eight systems in Africa. (B) Proportion of death of malignant tumor across eight systems in Africa. (C) Proportion of incidence of malignant tumor across eight systems in Africa in male patients. (D) Proportion of death of malignant tumor across eight Systems in Africa in male patients. (E) Proportion of incidence of malignant tumor across eight systems in Africa in female patients. (F) Proportion of death of malignant tumor across eight systems in Africa in female patients.
Geographically, breast cancer holds the highest incidence and mortality rates in Central and Eastern Africa. In Southern Africa, breast cancer incidence ranks second to prostate cancer, while its mortality ranks third, following tracheal, bronchus, and lung cancer, and esophageal cancer. In Northern Africa, tracheal, bronchus, and lung cancer have the highest incidence and mortality rates. Although in Southern Africa, this type of cancer ranks third in incidence, it leads in terms of mortality. In Western Africa, stomach cancer has the highest incidence rate; however, its mortality ranks fifth. Despite prostate cancer being the tenth most common in terms of incidence in Western Africa, it results in the highest mortality. These regional variations underscore the diverse cancer burden across different areas (Fig. 3 ). Figure 3. The 32 cancer categories were ranked according to the incidence and death rates by African regions.
The SDI and frontiers analysis
The analysis shows a nuanced relationship between SDI levels and cancer incidence, indicating that socioeconomic development impacts health outcomes differently for each cancer category. For nervous system cancers, the incidence shows a slow upward trend with increasing SDI. Egypt, with an SDI of 0.61, and Libya, with an SDI of 0.73, report the highest incidences, suggesting that better socioeconomic conditions may correlate with increased detection. Skin and soft tissue cancers exhibit a relatively flat trend in incidence as SDI increases, with South Africa (SDI of 0.68) experiencing the highest number of cases. Respiratory system cancers’ incidence also gradually rises with higher SDI levels. Libya, having the highest number of patients, reflects this pattern at an SDI of 0.73. Digestive system cancers have an incidence that remains relatively stable across varying SDI regions, primarily concentrated in areas with an SDI between 0.4 and 0.6. Head and neck cancers follow a similar pattern, with a stable incidence across SDI levels. Genitourinary system cancers show high incidence rates predominantly in regions with SDI values between 0.4 and 0.6. Lymphatic and hematopoietic system cancers are more prevalent in areas with SDI values between 0.4 and 0.5. Lastly, bone and joint cancers show a relatively even incidence distribution across different SDI levels, reflecting a consistent impact of socioeconomic variables. In summary, this analysis of the relationship between SDI and cancer incidence highlights the diverse ways socioeconomic factors intersect with health outcomes. Understanding these patterns is crucial for developing targeted interventions and allocating resources efficiently to address cancer burden across different regions in Africa (Figs. 4 and 5 ). Figure 4. The relationship between Social Demographic Index (SDI) and incidence of malignant tumor across eight systems in Africa in 2021. (A) Nervous system cancers. (B) Skin and soft tissue cancers. (C) Respiratory system cancers. (D) Digestive system cancers. (E) Head and neck cancers. (F) Genitourinary system cancers. (G) Lymphatic and hematopoietic system cancers. (H) Bone and joint cancers. Figure 5. Frontier analysis involving SDI and malignant tumor burden in in 2021. (A) Skin and soft tissue cancers. (B) Bone and joint cancers. (C) Genitourinary system cancers. (D) Respiratory system cancers. (E) Digestive system cancers. (F) Nervous system cancers. (G) Lymphatic and hematopoietic system cancers. (H) Head and neck cancers.
Tumor burden trends by age subgroup
In the demographic analysis of cancer burden by age, distinct patterns emerge, highlighting the variations in cancer prevalence and mortality across different age groups. Among patients under the age of 25, lymphatic and hematopoietic system cancers have the highest incidence. This category also leads in cancer-related deaths in this age group, emphasizing the critical need for focused diagnostic and treatment strategies for young patients. These cancers often include conditions like leukemia and lymphoma, which require specialized healthcare resources and early intervention to improve survival rates. For individuals aged 25 and above, the cancer burden shifts significantly. Genitourinary system cancers become the predominant concern, with the highest incidence and associated mortality rates. This indicates a substantial impact on the adult population, necessitating enhanced screening programs and access to effective treatments to manage these conditions. Following genitourinary system cancers, digestive system cancers also represent a significant burden in this age group, both in terms of incidence and mortality. This underscores the importance of addressing lifestyle factors and improving early detection methods to mitigate the impact of these cancers (Fig. 6 ). Figure 6. Proportion of incidence and death of malignant tumor across eight systems in Africa in 2021 by age groups. (A) Proportion of incidence of malignant tumor across eight systems in Africa in 2021 by age groups. (B) Proportion of death of malignant tumor across eight systems in Africa in 2021 by age groups.
In further analysis, the incidence of bone and joint cancers peaks among patients aged 5–20, with a higher prevalence observed in males compared to females across all age groups. Mortality from these cancers is concentrated between the ages of 10 and 25. Digestive system cancers exhibit a predominance in males, with the highest incidence occurring between the ages of 55 and 70, while mortality rates peak between 55 and 75 years. Head and neck cancers are more common in males, with the majority of cases found in individuals aged 50–70. Mortality is also highest within this age range, suggesting a significant impact on the quality of life and survival among older adults. Lymphatic and hematopoietic system cancers display a higher prevalence in males, with cases distributed relatively evenly across age groups. The highest incidence is observed in children under 5 years old, and mortality is similarly distributed, with a slight concentration in younger demographics. Respiratory system cancers are characterized by a significantly higher incidence in males, primarily affecting those aged 50–75, with mortality also most common within this age bracket. Skin and soft tissue cancers predominantly affect males, with the greatest number of cases occurring between the ages of 50 and 75, and mortality is similarly concentrated from 55 to 75 years. Nervous system cancers present a balanced incidence between males and females, peaking in children under 10. While mortality is higher in this young age group, it remains evenly distributed among older patients. In genitourinary system cancers, females exhibit a significantly higher incidence than males, with peak incidence occurring between ages 30 and 65 for women, and mortality primarily affecting those aged 40–75. In contrast, for males, incidence peaks between ages 60 and 80, with the majority of deaths occurring from 65 to 85 years. These patterns reflect distinct gender and age-related vulnerabilities (Figs. 7 and 8 ). Figure 7. Incidence of malignant tumor across eight systems in Africa in 2021 by age groups. (A) Incidence of bone and joint cancers in Africa by age groups. (B) Incidence of digestive system cancers in Africa by age groups. (C) Incidence of head and neck cancers in Africa by age groups. (D) Incidence of lymphatic and hematopoietic system cancers in Africa by age groups. (E) Incidence of respiratory system cancers in Africa by age groups. (F) Incidence of skin and soft tissue cancers in Africa by age groups. (G) Incidence of genitourinary system cancers in Africa. (H) Incidence of nervous system cancers in Africa by age groups. Figure 8. Death of malignant tumor across eight systems in Africa in 2021 by age groups. (A) Death of bone and joint cancers in Africa by age groups. (B) Death of digestive system cancers in Africa by age groups. (C) Death of head and neck cancers in Africa by age groups. (D) Death of lymphatic and hematopoietic system cancers in Africa by age groups. (E) Death of respiratory system cancers in Africa by age groups. (F) Death of skin and soft tissue cancers in Africa by age groups. (G) Death of genitourinary system cancers in Africa. (H) Death of nervous system cancers in Africa by age groups.
Risk factors and death analyses
For patients with tracheal, bronchus, and lung cancer, air pollution, occupational risks, tobacco use, and other environmental factors emerge as significant risk factors, underscoring the need for public health policies aimed at reducing exposure to these hazards. Alcohol use is notably associated with increased mortality and DALYs in liver cancer, nasopharynx cancer, and cancers of the lip and oral cavity. For colon and rectum cancer, esophageal cancer, and tracheal, bronchus, and lung cancer, dietary risks play a prominent role. Drug use is particularly linked to liver cancer mortality and DALYs. Low physical activity is identified as a significant risk factor for colon and rectum cancer (Fig. 9 ). Figure 9. (A) Secondary risk factors of incidence of 32 cancer categories by age and sex with analyses. (B) Secondary risk factors of death of 32 cancer categories by age and sex with analyses.
In female patients, unsafe sex is a major risk factor for cervical cancer mortality and DALYs, pointing to the critical importance of sexual health education. High body-mass index also emerges as a notable risk factor, with gender-specific impacts: in males, it is primarily linked to liver cancer, mesothelioma, pancreatic cancer, and thyroid cancer, while in females, it is associated with breast cancer, liver cancer, and uterine cancer (Fig. 9 ).
Trends and frontiers of tumor burden in Africa
According to the joinpoint regression model, breast cancer has exhibited a consistent upward trajectory, with APC of 1.96 from 2015 to 2021. This trend underscores the urgent need for enhanced screening and treatment programs to address this growing health burden. In contrast, cervical cancer, which experienced an initial increase between 2001 and 2004, has shown an overall decline, with an APC of −0.30 from 2008 to 2021. Prostate cancer also exhibits a rising trend, with an APC of 0.28 from 2019 to 2021, reflecting a growing health challenge for men in the region that demands targeted awareness and healthcare strategies. Similarly, colon and rectum cancer has been increasing gradually, with an APC of 0.53 from 2015 to 2021. The trend for tracheal, bronchus, and lung cancer has remained relatively stable over the years, with periods of slow increase and decrease. Notably, there was a slight decline from 2015 to 2021, with an APC of −0.53. Liver cancer has been declining since 2000, and from 2019 to 2021, the incidence has stabilized with an APC of 0.20 (Fig. 10 ). Figure 10. APC of prevalence for cancers from 1990 to 2021. (A) Breast cancer. (B) Cervical cancer. (C) Prostate cancer. (D) Colon and rectum cancer. (E) Tracheal, bronchus, and lung cancer. (F) Liver cancer.
Discussion
The findings of this study highlight the growing burden of NCDs, particularly cancer, in Africa, underscoring the urgent need for targeted healthcare interventions and policy reforms. The data from 2021 illustrates a significant incidence and mortality associated with various types of cancer across the African continent, with breast cancer emerging as the most prevalent and deadliest among females and prostate cancer leading in males. Africa’s rapid population growth and improving healthcare infrastructure have not kept pace with the increasing burden of NCDs, particularly cancer. The study underscores the urgent need for comprehensive strategies to address the disparities in cancer care across the continent. Breast and cervical cancers are the most prevalent and deadliest cancers among females in Africa, reflecting global trends but exacerbated by limited access to early detection and treatment services in many regions. The rising trend in breast cancer, as indicated by the APC of 1.96 from 2015 to 2021, highlights the need for improved screening programs and public health initiatives. In contrast, the overall decline in cervical cancer incidence, with an APC of −0.30 from 2008 to 2021, suggests potential progress in HPV vaccination and awareness campaigns, though these efforts need to be sustained and expanded. In males, prostate cancer leads both in incidence and mortality. The increasing trend of prostate cancer (APC of 0.28 from 2019 to 2021) signals the necessity for heightened awareness and early screening initiatives tailored for men’s health. This study also highlights the significant burden of digestive system cancers, particularly colon and rectum cancers, which are on a gradual rise (APC of 0.53 from 2015 to 2021). These findings necessitate targeted strategies focusing on lifestyle modification, dietary interventions, and enhanced healthcare access.
The geographic analysis reveals substantial variations in cancer incidence and mortality across African regions, influenced by socioeconomic, environmental, and healthcare access factors. For instance, respiratory system cancers are predominantly observed in Northern Africa, with high rates in Libya, potentially due to environmental factors like air pollution and smoking prevalence. In contrast, genitourinary system cancers have high incidence rates in regions with lower SDI values, indicating disparities in healthcare access and early detection measures. Age-related disparities in cancer burden further emphasize the need for demographic-specific interventions. Lymphatic and hematopoietic system cancers are the most prevalent among young individuals, necessitating specialized diagnostic and treatment strategies. For adults over the age of 25, the focus should shift to addressing the significant burden of genitourinary and digestive system cancers through comprehensive screening and treatment programs. The study highlights a nuanced relationship between socioeconomic development, measured by the SDI, and cancer incidence. While socioeconomic advancements can lead to better healthcare access and early detection, they may also correlate with lifestyle changes increasing cancer risk. For example, respiratory system cancers show a gradual rise in incidence with higher SDI, reflecting potentially increased exposure to risk factors like smoking and air pollution. Understanding these socioeconomic influences is crucial for developing targeted interventions that address both prevention and treatment.
Risk factors such as air pollution, tobacco use, and dietary habits significantly contribute to cancer burden in Africa. Public health policies must prioritize reducing exposure to these risk factors, with initiatives tailored to regional contexts. For instance, addressing dietary risks and promoting physical activity can mitigate the impact of digestive system cancers. In female populations, improving sexual health education and HPV vaccination coverage is vital for reducing cervical cancer incidence and mortality.
The implementation of cancer control strategies in Africa faces multifaceted challenges, many of which stem from systemic resource constraints. First, limited healthcare infrastructure – including shortages of specialized oncology facilities, diagnostic equipment (e.g. mammography and MRI machines), and trained personnel – hinders early detection and treatment. Second, financial barriers exacerbate disparities. Many patients face catastrophic out-of-pocket expenses for cancer care, while underfunded public health systems struggle to subsidize treatments. Third, cultural and educational barriers, such as stigma surrounding cancer diagnosis, distrust in biomedical systems, and low health literacy, delay care-seeking behaviors. For instance, political instability and fragmented health governance in some regions disrupt the continuity of cancer programs. These challenges are compounded by competing health priorities, such as infectious disease outbreaks, which divert attention and resources away from NCDs like cancer.
To address the evolving cancer burden in Africa, targeted research must prioritize closing critical evidence gaps. First, expanding cancer registries and population-based epidemiological studies is essential to improve data granularity, particularly in underrepresented regions such as Central and Western Africa, where cancer trends remain under characterized. Longitudinal studies tracking incidence, survival, and mortality patterns across diverse SDI settings could elucidate the interplay between socioeconomic development and cancer outcomes. Second, etiology-focused research is needed to dissect the drivers of rising cancers like breast and prostate malignancies, including genetic susceptibility, hormonal factors, and lifestyle transitions. Similarly, the paradoxical decline in cervical cancer warrants studies evaluating HPV vaccine coverage, screening adherence, and treatment accessibility. Third, implementation science should evaluate the cost-effectiveness of context-specific interventions – such as mobile screening units for rural populations or telehealth platforms for specialist referrals – to inform scalable policies. Finally, interdisciplinary collaboration is critical to explore innovative solutions, such as AI-assisted diagnostics, and to integrate traditional healing practices with biomedical care in culturally aligned prevention programs. By addressing these priorities, future studies can catalyze equitable cancer control strategies across Africa’s heterogeneous healthcare landscapes.
Despite the comprehensive analysis and significant findings presented in this study, several limitations must be acknowledged. First, the reliance on data from the GBD Study 2021 may introduce potential biases inherent in secondary data sources, including variations in data quality and completeness across different regions. The accuracy of cancer incidence and mortality estimates may be affected by underreporting or misclassification of cancer cases, particularly in countries with limited healthcare infrastructure and diagnostic capabilities. Additionally, while the SDI provides valuable insights into socioeconomic factors, it may not capture all the nuances of healthcare access and quality across diverse African regions. Furthermore, the study’s observational nature precludes establishing causality, and while correlations between risk factors and cancer outcomes are identified, direct causal relationships cannot be confirmed. Lastly, although the study spans a significant timeframe from 1990 to 2021, it may not fully capture the most recent developments and emerging trends in cancer incidence and healthcare advancements post-2021, which could impact current and future cancer burden projections.
Conclusions
In summary, breast and prostate cancers remain the most prevalent and deadly among women and men, respectively, while genitourinary and digestive system cancers also contribute substantially to overall cases and deaths. Marked geographic and socioeconomic variations were observed, influenced by healthcare access and risk exposures. Expanding early detection programs for cancers such as breast, prostate, and colorectal, promoting public awareness, and addressing modifiable risks are critical. Integrating socio-demographic indicators like the SDI into health planning can help address disparities and inform resource allocation. Despite progress, challenges such as data limitations and gaps in healthcare infrastructure persist. Future research should focus on improving cancer surveillance, exploring socio-environmental determinants, and evaluating interventions and policies.
Acknowledgements
During preparation of this work, the author(s) used ERNIE Bot in order to polish sentences. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.
K.L., S.L., J.Z., and J.M. contributed equally to this work and shared first authorship.
Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.
Published online 12 June 2025
Ethical approval
Not applicable.
Consent
Not applicable.
Sources of funding
This work was supported by grants from the Yunnan Provincial Science and Technology Special Program (No. 202302A A310020), the Kunming Medical University Excellence Team Development Program (2024XKTDYS07), and Yunnan Provincial Key Research and Development Projects (No. 202403AC100015 and No. 202303AC100203), the Yunnan Provincial Innovation Team for Thoracic Tumor Prevention and Treatment (No. 202405AS350015), the Yunnan Thoracic Surgery Doctoral Supervisor Team, the Development of a Precision Prevention and Full-Cycle Intelligent Management System for Regional High-Incidence Lung Cancer in Yunnan Province (No. 202303AC100203), the Ministry of Education International Collaborative Laboratory for High-Incidence Tumors in Plateau Regions, the Kunming Medical University Advantageous Discipline Team Program (No. 2024XKTD YS07), the Yunnan Provincial Key Laboratory of Lung Cancer (No. 202205AG070073), the Yunnan Provincial Li Yin Expert Workstation (No. 202405AF140055), Scientific Research Fund Project of Yunnan Provincial Department of Education (2025J0288) and the Academician Zhan Qimin Expert Workstation (No. 202405AF140011), the Innovative Experimental Program for University Students at Kunming Medical University (2024CYD384).
Author contributions
Study concept and design, acquisition, analysis, or interpretation of data, revising the article critically for important intellectual content, final approval of the version to be published: All authors; drafting of the article: Kexun Li; statistical analysis: S.L.; obtained funding: Y.H.; administrative, technical, or material support: Y.H. and L.Y.; study supervision: L.Y. and K.L. K.L., S.L., J.Z., and J.M. had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Conflicts of interest disclosure
The authors declare no conflicts of interest.
Research registration unique identifying number (UIN)
Not applicable.
Guarantor
Kexun Li, Lianhua Ye, Yunchao Huang.
Provenance and peer review
Not commissioned, externally peer-reviewed.
Data availability statement
As this study utilized publicly available data from the Global Burden of Disease study ( https://www.who.int/zh/news-room/fact-sheets/detail/ageing-and-health ), no ethical approval was required for the analysis. All data were anonymized and aggregated, ensuring patient confidentiality.
Purpose and scope of AI use
During preparation of this work, the author(s) employed the AI language model ERNIE Bot specifically for the purpose of polishing and refining sentence structure and language clarity. Generative AI was utilized solely in the writing and revision stages of the manuscript preparation workflow. The author(s) reviewed, verified, and edited all AI-generated content to ensure accuracy, clarity, and integrity, and take full responsibility for the final content of the publication.
AI tool(s) and configuration
The AI tool used was ERNIE Bot, developed by Baidu. The version used corresponds to the deployment available as of January 2025 and April 2025. The tool was accessed via a cloud API service with default parameters; no fine-tuning or plug-ins were applied, and prompt lengths were limited to sentence-level polishing requests. The AI operated entirely through an online platform provided by the vendor.
Data inputs and safeguards
Only de-identified textual content from the manuscript draft was submitted to the AI tool for language refinement. No patient data, images, or sensitive personal information were provided. All data inputs complied with relevant data protection regulations, including GDPR and HIPAA where applicable. No institutional approvals or data-sharing agreements were required due to the nature of input data.
Human oversight and verification
Every output generated by ERNIE Bot was reviewed in detail by the author(s). The authors conducted thorough fact-checking and ensured clinical and technical accuracy throughout the manuscript. Any AI-generated text was edited or discarded as necessary to maintain the highest standards of quality. The limitations of AI in language generation and potential errors or biases are acknowledged by the author(s).
Bias, ethics, and regulatory compliance
The authors took care to detect and mitigate any algorithmic biases by critically evaluating AI-suggested text. The use of ERNIE Bot adhered to ethical guidelines for AI-assisted writing. The author(s) declare no conflicts of interest or financial ties to the AI vendor.
Reproducibility and transparency
Exact prompts used for sentence polishing are available upon reasonable request. As the AI interaction involved short, contextual sentence refinement rather than code generation or data analysis, no extensive code snippets or version-controlled logs are maintained. No AI-generated artifacts requiring repository deposition were produced. This declaration aims to ensure transparency and reproducibility in the use of AI tools in manuscript preparation.
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