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Obesity in kindergarten children and its relation with some variables Family
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Obesity is a common disease that resulted from over-nutrition in adults and children. It rarely causes damage to the centers of food in the brain. Obesity is defined as an increased body weight from its natural limit which is resulted from the accumulation of excessive amounts of fatty tissue incredibly up to 20% in males, 30 % in females unless this increase is not due to an increase in muscles as in athletes or accumulation of water in the body which is resulted from Mesothelioma or the magnitude of the skeleton.Obesity is the increase of the total average of fat in the body compared to other tissues, which causes an increasing body weight, thereby increasing body mass. The fatty child has an increase in the stored fatty layer under the skin, and increased weight 20%more than the normal weight of other children in the same age and height.
This thesis focuses on identifying showing the relationship between obesity and some of the variables. Moreover, the thesis reflects the importance of maintaining the ideal weight of the child and his role in the growth and health. The evidence shows that children who suffer from obesity are more likely to become fat adults, so they are exposed to increased risk of serious health problems. Hence, protecting children from obesity and treating them is possible through changing lifestyle, improving the child's nutrition system, and urging him to exercise to improve their health at the present time and in the future.
Therefore, the thesis aims: to detect significant differences in obesity for kindergarten children depending on certain variables through the testing hypothesis as followed: Statistically there are no significant differences in obesity with kindergarten children that are attributable to the following variables:
(A)Sex variable.
(B) The sequence of the child in the family..
(C) Dietary habits of the family.
To achieve the objectives of this study, 300 children were selected as samples, 166 males and 134 females. One of the most important tools that were used is:
1 - an electronic device for measuring weight.
2 - Length measuring tape.
3 - Measurement of body mass index (BMI)..
The researcher used in data statistical analysis:
(1) One way Anova.
(2) The T- test for two independent samples: Independent Samples Test.
(3) The real bilateral correlation coefficient (Point Bay Cyril).
The most important results that have been reached:
(1) That females suffer from obesity more than males because the body mass index of females is greater than the body mass index (BMI) for males.
(2) There is no statistically significant difference between the averages of body mass index (BMI) scores for kindergarten children due to the variable of the sequence of the child within his brothers.
(3) There is no statistically significant difference between the averages of body mass index (BMI) scores for obese kindergarten children that is attributed to behavioral tendencies variable of the child.

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Publication Date
Thu Jun 20 2024
Journal Name
Ingénierie Des Systèmes D Information
Enabling Technologies for Ultra-Low Latency and High-Reliability Communication in 6G Networks
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Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Concrete strength development by using magnetized water in normal and self-compacted concrete
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Publication Date
Thu Jun 01 2023
Journal Name
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Batch and flow injection spectrophotometric methods for determination of Ceftazidime in pharmaceutical formulations
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Publication Date
Tue Oct 27 2020
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The complex dynamic in three species food webmodel involving stage structure and cannibalism
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Fri Jun 29 2018
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Examining the Values and Principles of Agile Construction Management in Iraqi Construction Projects
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Publication Date
Sun Feb 25 2024
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Natural Language Processing For Requirement Elicitation In University Using Kmeans And Meanshift Algorithm
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Publication Date
Tue Dec 20 2022
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2022 4th International Conference On Current Research In Engineering And Science Applications (iccresa)
Noise Detection and Removing in Heart Sound Signals via Nuclear Norm Minimization Problems
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Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix

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