RESUMO
Background:Medicinal plants are now becoming indispensable in the treatment and management of many ailments. The unaffordability, unavailability and adverse effects of conventional therapy in the treatment and management of many diseases have geared keen interest in the use of herbal medicine. This work was carried out to investigate the prophylactic effect of the ethanol extract of Azadirachta indicaleaf in streptozotocin-induced diabetic rats. Methods:A total of one hundred (100) rats were randomized into four (4) groups (n=25) and used for the study. Each group of 25 rats was sub-divided into five (5) groups (n=5). The sub-groups comprise: Group A-normal control that was not treated, group B-100mg/kg body weight of metformin and groups C to E -graded doses (100mg/kg, 200mg/kg and 400mg/kg body weight) of the ethanol leaf extracts of A. indicaleaves. The standard drug and the extracts were consecutively administered to groups B-E for 7, 14, 21 and 28 days before the induction of diabetes. Diabetes was induced intraperitoneally using 50mg/kg bodyweight of streptozotocin. Results: Thegroups thatwere administered 100, 200 and400mg/kg bw of ethanolextract of A. indica showed a significant (p<0.05) increase in their weight after 21 and 28 days of pre-treatment compared with the control group that was not treated. The graded doses of the extract also have a remarkable effect in the fasting blood glucose levels which was made visible by the significant (p<0.05) reduction recorded in the fasting blood glucose levels compared with the control group that was not pre-treated and the group pre-treated with metformin. Conclusion: The results obtained in this research suggest that ethanol extract of A. indicahas the potential to protect against diabetes by delaying its onset. However, the longer the period of pre-treatment, the better the condition of the animals pre-treated as well as the protection as can be seen from the results of the weight and fasting blood glucose levels.
RESUMO
Background: Obesity is a well-established independent risk factor for hypertension and other cardiometabolic disorders. However, the best anthropometric index of obesity that predicts or associates strongly with hypertension and related conditions remains controversial and inconclusive.Objective: This study compared the performance of eight anthropometric indices of obesity: body mass index (BMI), ponderal index (PI), waist circumference (WC), hip circumference (HC), waisthip ratio (WHR), waistheight ratio(WHtR), body adiposity index (BAI) and conicity index (CI) as correlates and potential predictors of risk of hypertension and prehypertension in a Nigerian population, and also the possible effect of combining two or more indices in that regard.Methods: This church-based, cross-sectional study was conducted in Anambra state, south-eastern Nigeria from 2012 to 2013. A total of 912 persons (436 male and 476 female) drawn randomly from three major cities (Awka, Onitsha and Nnewi) in the state participated in the study. Information on demography, medical history and lifestyle were obtained using a well-structured and validated questionnaire. The systolic/diastolic blood pressure and anthropometric measurements were taken by well-trained personnel. The resulting data were analysed using descriptive statistics, logistic regression, Poisson regression and receiver operating characteristic curve analysis.Results: The mean values of all the anthropometric indices studied increased from normotension, through prehypertension to hypertension in both genders. BMI, WC, HC and CI were significantly higher (p < 0.05) in females than males. All the anthropometric indices studied were significantly (p < 0.001 except for CI) correlated with systolic and diastolic blood pressure. BMI, WHtR, WC and PI (with higher correlation coefficients for blood pressure) showed the best potential to predict hypertension and prehypertension in the study: BMI (cut-off = 24.49, AUC = 0.698; cut-off = 23.62, AUC = 0.659), WHtR (cut-off = 0.55, AUC = 0.682; cut-off = 0.5, AUC = 0.636), WC (cut-off = 91.44, AUC = 0.692; cut-off = 82.55, AUC = 0.645), PI (cut-off = 14.45, AUC = 0.670; cut-off = 13.69, AUC = 0.639), in males; and BMI (cut-off = 24.44, AUC = 0.622; cut-off = 28.01, AUC = 0.609), WHtR (cut-off = 0.51, AUC = 0.624; cut-off = 0.6, AUC = 0.572), WC (cut-off = 96.62, AUC = 0.616; cut-off = 96.52, AUC = 0.584), PI (cut-off = 16.38, AUC = 0.619; cut-off = 17.65, AUC = 0.599), in females for hypertension and prehypertension, respectively. In predicting hypertension risk, WC and WHtR did not significantly improve the performance of BMI in the models when included using our decision rule. Overall, CI had a very poor discriminatory power for both conditions in this study.Conclusion: BMI, WHtR, WC and PI emerged the best predictors of hypertension risk, and BMI, WC and PI of prehypertension risk in this study. The combination of high-performing anthropometric indices in a model did not improve their performance. Therefore we recommend the simultaneous but independent use of BMI and either WC or WHtR for predicting hypertension, and BMI and WC for prehypertension risk, bearing in mind that both types of index (abdominal and general obesity) account for different forms of obesity