Objective(s): Ramadan is the Holy month of the Muslims, where they are required to abstain from food and drinks
from dawn till the beginning of night. This study was conducted in Ramadan to investigate the effect of fasting on
hematological incidences, lipid profile, renal and liver function tests among healthy adult males.
Methodology: The present study was carried out in Ramadan – 1431 of Higira (August-September 2010). The study
sample was 56 healthy adult males. Five samples of blood were taken at five intervals (Before, at day 1, 15, 28 and
after Ramadan). Estimation was done for hematological markers, (hemoglobin, white blood cells count, platelet
count); renal function tests (blood urea, serum uric acid, serum albumin, total serum protein); biochemical
parameters, (blood glucose, total serum cholesterol, serum triacylglyceride, high and low density lipoproteins) and
liver function tests (AST, ALT, Alkaline phosphatase, total serum bilirubin).
Results: The mean age of the subjects was 48.4 years (SD 7.15) and mean weight was 79.92 kg (SD 7.94). No
significant changes were observed in weight, hemoglobin, white blood cell count and platelets count, blood urea and
serum albumin values. Whereas, serum uric acid and total serum protein levels were statistically lower during and
aŌer Ramadan (P< 0.05, 0.01).
Blood levels of glucose showed no significant decrease and serum cholesterol and serum triacylglyceride results were
non-significant at first 2 weeks of Ramadan.
The same significant changes (p< 0.05, 0.01) were observed in the lipoprotein at day 15 and 28 of Ramadan. Findings
of liver functions levels showed significant changes. While, total serum bilirubin still with no significant changes during
Ramadan.
Recommendations: The present study recommends performing more studies with both larger groups and in various
categories of healthy and unhealthy subjects.
Abstract
The multiple linear regression model of the important regression models used in the analysis for different fields of science Such as business, economics, medicine and social sciences high in data has undesirable effects on analysis results . The multicollinearity is a major problem in multiple linear regression. In its simplest state, it leads to the departure of the model parameter that is capable of its scientific properties, Also there is an important problem in regression analysis is the presence of high leverage points in the data have undesirable effects on the results of the analysis , In this research , we present some of
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