Objective: to identify the secondary school adolescent's obesity, and to find out the relationship between
adolescents obesity characteristics and their family history.
Methodology: A cross-sectional study was carried out among 537 adolescents (270 boys and 267 girls) aged 12-15
years selected by means of a multistage stratified random sampling technique.
Results: the prevalence of obesity among adolescents was 22.3%. (55.8%) of the obese adolescents were male,
(42.5%) their age is (13) years old, and (79.2%) of them coming from middle level of socio economic status score.
There are a significant relationship between obese adolescents and their family history of obesity which indicated
that obese father, and obese brother /sister (0.000, 0.037, & 0.000) respectively have a highly significant
relationship with adolescents' obesity.
Recommendation: Intervention programs focusing on promoting changes in lifestyles, food habits and increasing
physical activity need to be implemented at the earliest stage of children life
MM Abdulwahhab, kufa Journal for Nursing sciences, 2017 - Cited by 1
In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For
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The methods of the Principal Components and Partial Least Squares can be regard very important methods in the regression analysis, whe
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... Show MoreIn this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe
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This was a cross‐sectional study based on electronic survey data that was collected in Iraq during December first‐19th, 2020. The electronic surve
Chronic Kidney Disease (CKD) is a public health problem and many studies support the link between kidney dysfunction and cardiovascular events. Aldosterone has been shown for decades that a plasma aldosterone concentration is elevated in CKD. Whilst, Osteoprotegerin (OPG), after its capacity to protect bone, also osteoprotegerin is elevated in patients with chronic kidney disease (CKD), where it could predict the deterioration of kidney function, cardiovascular, vascular events and all-cause mortality. On the other hand, fibroblast growth factors (FGFs), in patients with CKD, its levels seem to increase progressively as kidney function worsens. The aim of the present study is to assess the correlations between serum osteoprotegerin
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