Background: Obesity represents a clear and
present danger to the health of children and
adolescents. Its prevalence among American
youth has doubled in the past 3 decades, and
there are now more overweight and obese
adults in the United States than adults of
normal weight.
Objectives of the study:
1- Finding whether screen watching among
adolescents has an effect on increasing
prevalence overweight and obesity.
2- The effect of other variables like physical
activity, eating in front of screen, eating under
stress on obesity and overweight among the
subjects sample.
Patients &Methods: During 3 months period a
cross sectional survey was conducted on 4
high schools at Baghdad with total sample of
500 subjects using time table to assess screen
watching hours per week,
Results:Higher percentagesof overweight &
obesity were found among female adolescents
than males, significant associations was
obvious among total sample & male sample
betweenthe level of physical activity &
BMI,while there was no significant
association among female sample for the same
variables , There was obvious significant
association between BMI a time spending in
screen watching, eatingin front of screen, ,
eating under stressin the total & male samples.
Conclusion: Increased levels of physical
activity are associated with a lower BMI and
less time spent on screen watching .in addition
.stress-induced eating may be one factor
contributing to the development of obesity;
furthermore habits like eating in front of
screen could increase BMI of an adolescent.
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In cognitive radio system, the spectrum sensing has a major challenge in needing a sensing method, which has a high detection capability with reduced complexity. In this paper, a low-cost hybrid spectrum sensing method with an optimized detection performance based on energy and cyclostationary detectors is proposed. The method is designed such that at high signal-to-noise ratio SNR values, energy detector is used alone to perform the detection. At low SNR values, cyclostationary detector with reduced complexity may be employed to support the accurate detection. The complexity reduction is done in two ways: through reducing the number of sensing samples used in the autocorrelation process in the time domain and through using the Slid
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