Colorectal Cancer Risk Factors in Adults in Nigeria.
Colorectal cancer (CRC) incidence is increasing in sub-Saharan Africa, including Nigeria, where more than half of patients die within 1 year due to late diagnosis and limited treatment. Without ready access to screening, identifying risk factors is critical. However, regional data are scarce, and it is unclear whether risk factors from high-income populations apply to Nigerians, who may have distinct clinicodemographic patterns and tumor characteristics.
To assess whether 13 CRC risk factors identified in high-income populations are associated with CRC in adults in Nigeria.
This multicenter case-control study was conducted in 6 hospitals across 3 of Nigeria's 6 geopolitical zones, with recruitment from April 2020 to September 2024. Participants were patients newly diagnosed with CRC and cancer-free controls matched on age, sex, location, education, and recruitment site. Data were analyzed from April 2023 to November 2025.
Family history of cancer, anthropometric factors (adult height, body mass index [BMI], and somatotype or body size over the life course), physical activity, and dietary and lifestyle factors (processed meat, red meat, fruit, vegetables, fiber, alcohol, smoking, and diabetes).
The associations of risk factors with CRC were assessed using odds ratios (ORs) and 95% CIs, estimated using multivariable unconditional logistic regression.
Among 2063 participants (1103 [53.5%] male; median [IQR] age, 54 [42-64] years) enrolled, most had secondary education or higher (1756 participants [85.2%]), lived in urban areas (1817 participants [88.1%]), and were Yoruba (1524 participants [73.9%]). Cases were older than controls (median [IQR] age, 56 [45-66] vs 52 [41-63] years) but were otherwise similar. Family history of cancer (OR, 1.55; 95% CI, 1.06-2.26), adult height (OR per 5-cm increase, 1.09; 95% CI, 1.00-1.20), body size or type over the life course (tertile 3 vs tertile 1: OR, 1.88; 95% CI, 1.30-2.72), and processed meat intake (lowest vs highest tertile of intake: OR, 1.43; 95% CI, 1.07-1.91) were positively associated with CRC risk, and an inverse U-shaped association was identified between physical activity and CRC risk (OR vs first quartile of activity, quartile 2: 0.63; 95% CI, 0.44-0.88; quartile 3: 0.52; 95% CI, 0.34-0.79; quartile 4: 0.77; 95% CI, 0.58-1.02), consistent with data from high-income populations. BMI was inversely associated with CRC risk (OR vs BMI 18.5-24.9, BMI <18.5: 2.63; 95% CI, 1.79-3.86; BMI ≥30: 0.42; 95% CI, 0.28-0.63), likely reflecting prediagnostic weight loss. No associations with diabetes, smoking, or intakes of red meat, fruit, vegetables, fiber, or alcohol were observed, likely due to low prevalence or variability.
This case-control study of CRC risk factors in adults in Nigeria found CRC risk patterns similar to those observed in high-income populations. These insights offer immediate opportunity to tailor education, prevention, and early detection in the region, especially as economic development leads to lifestyles more similar to high-income populations. These data provide a foundation for prospective research and investigations in other African populations.
To assess whether 13 CRC risk factors identified in high-income populations are associated with CRC in adults in Nigeria.
This multicenter case-control study was conducted in 6 hospitals across 3 of Nigeria's 6 geopolitical zones, with recruitment from April 2020 to September 2024. Participants were patients newly diagnosed with CRC and cancer-free controls matched on age, sex, location, education, and recruitment site. Data were analyzed from April 2023 to November 2025.
Family history of cancer, anthropometric factors (adult height, body mass index [BMI], and somatotype or body size over the life course), physical activity, and dietary and lifestyle factors (processed meat, red meat, fruit, vegetables, fiber, alcohol, smoking, and diabetes).
The associations of risk factors with CRC were assessed using odds ratios (ORs) and 95% CIs, estimated using multivariable unconditional logistic regression.
Among 2063 participants (1103 [53.5%] male; median [IQR] age, 54 [42-64] years) enrolled, most had secondary education or higher (1756 participants [85.2%]), lived in urban areas (1817 participants [88.1%]), and were Yoruba (1524 participants [73.9%]). Cases were older than controls (median [IQR] age, 56 [45-66] vs 52 [41-63] years) but were otherwise similar. Family history of cancer (OR, 1.55; 95% CI, 1.06-2.26), adult height (OR per 5-cm increase, 1.09; 95% CI, 1.00-1.20), body size or type over the life course (tertile 3 vs tertile 1: OR, 1.88; 95% CI, 1.30-2.72), and processed meat intake (lowest vs highest tertile of intake: OR, 1.43; 95% CI, 1.07-1.91) were positively associated with CRC risk, and an inverse U-shaped association was identified between physical activity and CRC risk (OR vs first quartile of activity, quartile 2: 0.63; 95% CI, 0.44-0.88; quartile 3: 0.52; 95% CI, 0.34-0.79; quartile 4: 0.77; 95% CI, 0.58-1.02), consistent with data from high-income populations. BMI was inversely associated with CRC risk (OR vs BMI 18.5-24.9, BMI <18.5: 2.63; 95% CI, 1.79-3.86; BMI ≥30: 0.42; 95% CI, 0.28-0.63), likely reflecting prediagnostic weight loss. No associations with diabetes, smoking, or intakes of red meat, fruit, vegetables, fiber, or alcohol were observed, likely due to low prevalence or variability.
This case-control study of CRC risk factors in adults in Nigeria found CRC risk patterns similar to those observed in high-income populations. These insights offer immediate opportunity to tailor education, prevention, and early detection in the region, especially as economic development leads to lifestyles more similar to high-income populations. These data provide a foundation for prospective research and investigations in other African populations.
Authors
Alatise Alatise, Peeri Peeri, Abdulkareem Abdulkareem, Badejo Badejo, Gali Gali, Oludara Oludara, Okereke Okereke, Olatoke Olatoke, Ademakinwa Ademakinwa, Alabi Alabi, Aderounmu Aderounmu, Adeomi Adeomi, Mohammed Mohammed, Adegboyega Adegboyega, Adisa Adisa, Ajewole Ajewole, Famurewa Famurewa, Agodirin Agodirin, Ariyibi Ariyibi, Nggada Nggada, Babatunde Babatunde, Badmos Badmos, Balogun Balogun, Bamidele Bamidele, Batta Batta, Betiku Betiku, Bojuwoye Bojuwoye, Choonawala Choonawala, Cookey Cookey, Daji Daji, Egberongbe Egberongbe, Esan Esan, Folaranmi Folaranmi, Fasiku Fasiku, Fatusi Fatusi, Fodero Fodero, Francis Francis, Gallagher Gallagher, Habeeb Habeeb, Shittu Shittu, Iasonos Iasonos, Ige Ige, Ikujenlola Ikujenlola, Igetei Igetei, Jackman Jackman, Kahn Kahn, Katung Katung, Koiki Koiki, Komolafe Komolafe, Lawrence Lawrence, Lawal Lawal, Lawal Lawal, Makanjuola Makanjuola, Mobolaji Mobolaji, Omodele Omodele, Na'aya Na'aya, Nganjiwa Nganjiwa, Njokanma Njokanma, Nuhu Nuhu, Nwachukwu Nwachukwu, O'Connell O'Connell, Odunafolabi Odunafolabi, Ogunleye Ogunleye, Olaofe Olaofe, Olcese Olcese, Ologunagba Ologunagba, Olokoba Olokoba, Olasehinde Olasehinde, Olajide Olajide, Osinowo Osinowo, Omoyiola Omoyiola, Omisore Omisore, Onyekwere Onyekwere, Owoade Owoade, Oyesegun Oyesegun, Samson Samson, Sanni Sanni, Sharma Sharma, Sowunmi Sowunmi, Sulaiman Sulaiman, Adebukola Adebukola, Wuraola Wuraola, Adeleye Adeleye, Adewunmi Adewunmi, Zarami Zarami, Kingham Kingham, Du Du
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