Percentage body fat in breast cancer patients at the university college hospital, Ibadan: A case-control study

Abdus-Salam, A A; Babatunde, Olutoye Ogunnorin; Adenipekun, A; Adeniyi, Adedayo Olabumuyi; Olabumuyi, Olayide

doi:10.4103/1115-2613.278592

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“…Breast cancer is the most common female malignancy, and it accounted for about 30% of all cancer diagnoses in women in 2019 [ 1 ]. In Nigeria, it was estimated to be responsible for about 11,500 deaths in 2018 with an age-standardised rate of 18.8/100,000 [ 2 ]. The mortality rate of breast cancer has dipped over the past three decades in the developed world [ 1 ], but unfortunately, mortality rates are disproportionately high especially in sub-Saharan Africa [ 3 , 4 ]; and with Nigeria, Africa’s most populous country having the highest mortality rate [ 5 ].…”

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confidence: 99%

Body composition, energy expenditure and caloric intake among breast cancer patients at a teaching hospital in Nigeria—a cross sectional study

Izuegbuna,

Sodiq,

Olawumi

et al. 2023

ecancer

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Objective This cross-sectional study was conducted on the associations between body composition, energy expenditure and caloric intake among 45 Nigerian breast cancer patients. Methods Forty-five Nigerian breast cancer patients were measured and analysed for their body composition, energy expenditure and caloric intake. Statistical analyses included a chi-square test, Student’s t -test, paired t -test, Spearman correlation and linear regression using Statistical Package for the Social Sciences 23.0. Results The body fat indices (body mass index (BMI), fat mass index (FMI), and body fats percentage) show that more than 50% of breast cancer patients were either overweight or obese. The Spearman correlation showed that fat-free mass (FFM) was the most strongly correlated with energy expenditure ( r = 0.84). BMI and (FMI – fat mass in relation to height) were significantly correlated with the Harris–Benedict equation for energy expenditure ( p < 0.001; p = 0.002), but they were not correlated significantly with the Karnofsky performance status. A paired t -test showed that caloric intake was significantly higher than total energy expenditure ( p < 0.001). FFM was the best predictor of resting energy expenditure (REE). Conclusion In conclusion, FFM remains the best predictor of REE. High body mass and high caloric intake indicate the need for support from nutritional programmes.

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