Journal article
A Cross-Sectional Study: Predicting Health Risks Among Female University Students


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Publication Details
Author list: MUAIDI Q, Ahsan M
Publication year: 2020
Journal: The Open Public Health Journal
Volume number: 13
Issue number: 1
Start page: 316
End page: 322
Number of pages: 7
ISSN: 1874-9445
Web of Science ID:
PubMed ID:
Scopus ID: 85088796672
eISSN: 1874-9445
Languages: English-United States



Background:


Good health is very important in our lives and plays a significant
role. Many health risks are associated with an unhealthy lifestyle.
These risks are responsible for raising the risk of chronic heart
diseases and other health complications. Females are not exempted from
these issues.




Objective:


To identify the obesity-associated health risks of female students by using selected anthropometric measurements.




Methods:


A cross-sectional study was conducted including 300 females aged
20.82 ± 5.23 years from the college of applied medical sciences, Imam
Abdulrahman bin Faisal University. The anthropometric measurements (body
mass index, percentage of body fat, visceral fat area, waist
circumference, waist-hip ratio,and waist-height ratio) were taken with
the help of an auto-calibrated bioelectric impedance device. The
waist-height ratio was determined by dividing waist circumference with
height. Cross tabulation was done to scrutinize the participant’s levels
at risk and high risk. Linear regression analysis was done to see the
relationship and prediction between selected anthropometric
measurements.




Results:


The finding showed that BMI level was high in 55% of participants,
Waist-height ratio over the average level was 46.67% and 21% of
participants had a visceral fat area on risk. Linear regression analysis
showed a strong association among body mass index, percentage of body
fat, visceral fat area, waist circumference, waist-hip ratio,and
waist-height ratio and statistically significant to each other at the
0.01 level.




Conclusion:


The selected anthropometric measurements can be used to identify
health-related risks. Though, when any anthropometric measurement
dichotomized as standard or high, BMI is the best measure to predict
health risk.



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Last updated on 2020-26-08 at 10:32