Browsing by Author "Adu, E.A."
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Item Assessment of the performance of haematological and non-invasive fbrotic indices for the monitoring of chronic HBV infection: a pilot study in a Ghanaian populatio(Research Notes, 2023) Nyarko, E.N.Y.; Obirikorang, C.; Owiredu, W. K. B. A.; Adu, E.A.; Acheampong, E.Objective Haematological and liver fbrotic markers could be appreciably utilized for efective monitoring of Chronic Hepatitis B viral (HBV) infection, thereby increasing patient’s treatment outcome. The objective of this study was to assess the applicability of complete blood count (CBC) and non-invasive liver-fbrotic indices as markers of prognostic outcome and monitoring in HBV infections. Results Signifcant diferences in levels of white cell and diferentials counts, red blood cell count, hemoglobin indices, and platelet indices were observed between HBV-infected patients (cases) and uninfected persons (controls). Levels of haemoglobin (Hb), total white blood cells (tWBC), neutrophils, monocytes, platelets, and Platelet Distribution width (PDW) were signifcantly lower (p<0.05) in the cases compared to the controls. Total and indirect bilirubin; De Ritis ratio, Aspartate transaminase to platelet ratio index (APRI) and RDW-to-platelet ratio (RPR) were elevated in cases compared with controls (p-value<0.05). In a multivariate adjusted model to test the signifcance of markers, Hemo globin Index (beta coefcient=− 0.876, p-value<0.001), NLR (beta coefcient=− 0.839, p-value<0.001), MPV_10000 (beta coefcient=− 0.333, p-value<0.001) and Albumin (beta coefcient=− 0.059, p-value=0.014), were associated with HBV infection status. Receiver operative characteristics curve analysis showed Hemoglobin Index (AUC=0.744) and MPV_10000 (AUC=0.730) as better prognostic markers for HBV-infection.Item Prevalence and risk factors of obesity among undergraduate student population in Ghana: an evaluation study of body composition indices(BMC Public Health, 2024) Obirikorang, C.; Adu, E.A.; Nyarko, E.NY.Background Obesity is a classified risk factor for several of the world’s leading causes of death. In this study, we combined information contained in body mass index (BMI), total percentage body fat (TPBF) and relative fat mass (RFM) to estimate obesity prevalence and examine the risk factors associated with obesity. Methods The study recruited 1027 undergraduate students aged between 16 and 25 years using a cross-sectional study design and two-stage stratified random sampling between January and April 2019 from the Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. Demographic, lifestyle, and family history of chronic disease data, were collected using a structured questionnaire. Bioelectrical impedance, along with height, weight, age, and gender, were used to estimate BMI and TPBF. The RFM was calculated using a published equation. The TPBF and RFM ranges were evaluated based on standard BMI thresholds and an informative combined obesity prevalence estimated in a Bayesian framework. Multiple logistic regression analysis was used to evaluate potential risk factors of overweight/ obesity. Results Concordance between BMI, TPBF and RFM for obesity classification was 84% among female and 82.9% among male students. The Bayesian analysis revealed a combined prevalence means of obesity of 9.4% (95%CI: 6.9- 12.2%) among female students and 6.7% (95%CI:4.3-9.5%) among male students. The odds of obesity were increased between 1.8 and 2.5 for females depending on the classification index. A significant increasing trend of obesity was observed with university-level. A family history of obesity was associated with a high estimate of general, central, and high TPBF. Conclusion Using multiple adiposity indicators conjointly in a Bayesian framework offers a greater power to examine obesity prevalence. We have applied this and reported high obesity prevalence, especially among female students. University level and family history of obesity were key determinants for obesity among the student population.