PREDICTORS OF SERUM ANTIOXIDANT CONCENTRATION IN BREAST CANCER SURVOURS: A RANDOMISED CROSS-SECTIONAL STUDY

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A.D. Ezuma1, S.C. Ibeneme2,3, G. Fortwengel4, H. Myezwa3, T..A. Ajidahun3, O. Onodugo5, A. Nnamani6, N. Lasebikan6, I.J. Okoye6
1University of Nigeria Teaching Hospital, Physiotherapy, Ituku/Ozalla, Enugu, Nigeria, 2University of Nigeria, Medical Rehabiliutation (Physiotherapy), Enugu, Nigeria, 3University of the Witwatersrand, Department of Physiotherapy, Johannesburg, South Africa, 4Hochschule Hannover University of Applied Sciences and Arts, Faculty III, Hannover, Germany, 5University of Nigeria Teaching Hospital, Medicine, Ituku/Ozalla, Enugu, Nigeria, 6University of Nigeria Teaching Hospital, Radiation Medicine, Ituku/Ozalla, Enugu, Nigeria

Background: Physical inactivity distorts body composition [percentage body fat mass (%BFM),waist-hip ratio (WHR) and body mass index (BMI)] resulting in increased adiposity which promotes inflammatory micro-environment, oxidative stress, and consequently depletes antioxidant (i.e. superoxide dismutase-SOD) level. The net effect favours breast cancer (BCA) induction/recurrence. Therefore, physical activity (PA), and body composition are likely predictors of BCA and should be given consideration in prioritizing BCA prevention strategies according to their predictive weights.   

Purpose: To:
1. Explore differences in body composition, PA and serum concentration of SOD between BCA survivors (BCAS) and apparently healthy women (HW), and
2. Explore how these variables [I.e. body composition, and PA] relate to SOD in BCAS and HW.

Methods: A randomized cross-sectional study involving 80 participants, who were consecutively recruited, including 40 BCAS (age range=35–55 years, mean age=48.5±6.9.05 years) and 40 HW(age range=21.50 - 28.80, mean age=23.97±1.67 years) was conducted at the Oncology Clinic.  Six explanatory variables (Age, BMI, WHR,%BFM, PAL and Step count/day) were explored to predict SOD in BCAS and HW. Data collected were analyzed using multiple linear regression, and independent t-test at p<0.05.

Results: HW were younger (p=0.001) and recorded higher step counts/day (p=0.03), PAL (MET-min/week) (p=0.0007), and SOD (p=<.0001) but lower WHR (p=0.0009), %BFM (p=0.008), and BMI (p<.0001) compared to BCAS. The %BFM is the highest predictor (r=-0.62,beta=-0.39,p<.0001) of SOD In BCAS and combined with BMI (r=-0.54;b=-.16,p=0.0002), WHR (r=-0.44;b=-0.20,p=0.002), Step counts/day (r=0.45,b=0.11,p=0.002) and PAL(r=0.51,b=0.18,p=0.0004) to produce R2=0.50;F(5,39)=8.78;p=<0.0001) as the best fit for the predictive model. The variance(R2) change was significant from the %BFM model (R2=0.37;p=<0.0001), %BFM+BMI model (R2=0.40,p=<0.0001), %BFM+BMI+Step count/day model (R2=0.47,p<0.0001), %BFM+BMI model+Step count/day+PAL model(R2=0.47,p=<0.0001) to %BFM+BMI+Step count+PAL+WHR model (R2=0.50,p=<0.0001). The regression equation is given as SOD=22.59+0.13(%BFM)+ -0.06(BMI)+0.0001(Steps)+0.0002(PAL)+ -1.87(WHR). The highest predictor of SOD in HW is WHR (t=-3.87;beta=-0.53) and produced R2=0.26;F(1,39)=14.96;p=0.0004 as the best predictive model. The variance change was significant from PAL+WHR model (R2=0.25;p=0.002) to WHR model (R2=0.26 p=0.0004). The regression model equation for predicting SOD in HW is given as SOD= 24.5435+ -6.61(WHR). 

Conclusion(s): BRCAS are less physically active with higher adiposity and lesser antioxidant concentration than HW. Subcutaneous adiposity(defined by %BFM) is the key determinant of SOD in BRCAS similar to central adiposity(defined byWHR) in HW. Overall, the indices of body composition and PA are associated with SOD and are good predictors of SOD in BCAS, contributing to half of the SOD variance. However, only the WHR is associated with SOD in HW and accounts for only 26% of its variance. 

Implications: There is a plausible role for the subcutaneous and central adiposities in BCA recurrence and induction, respectively, since they are the key negative predictors of SOD but seem amenable to PA whose indices are also positive predictors of SOD. Considering that only 50% and 26% of the variance change were explained by the predictive models in BCAS and HW, respectively, it implies that other factors that improve body composition and boost antioxidant concentration (e.g. nutrition) should be prescribed to complement PA in the prevention of BCA induction/recurrence. Therefore, PA alone may not suffice in preventing BCA induction/recurrence in HW/BCAS.

Funding, acknowledgements: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors

Keywords: Breast cancer recurrence and prevention, Antioxidant concentration, Physical activity and Body composition

Topic: Oncology, HIV & palliative care

Did this work require ethics approval? Yes
Institution: University of Nigeria
Committee: Health Research Ethics Committee
Ethics number: NHREC/05/01/2008B


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