Health and Wellbeing: Analysis of Road Traffic Accidents, Depression, and Obesity

This article analyzes the relationship between road traffic accidents, depression, and obesity in students. It includes statistical analysis of various factors such as gender, age, living arrangement, and more.

Running head: HEALTH AND WELLBEING
Health and Wellbeing
Name
Course Number
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HEALTH AND WELLBEING 2
Health and Wellbeing
1 Introduction
ACU commits it to provide the best to the students by ensuring that they understand the
concerns, health and wellbeing. In a study conducted to measure Road traffic accidents,
depression and obesity, the age distribution of the first years who were entered into the study had
a mean of 20, with the youngest student being 16 years and 59 for the oldest. Due to ethics issues
accompanied by connection of age and informed consent, the analysis had to exclude student
under the age of 18. It was found that 15.2% were below 18 years and 30.7% were exactly 18
years. The study had 38,681 students.
2 Analysis
2.1 Equality of means
After testing for equality of means of drivers’ aggression by their gender, it was found
that the average values were 7.52 and 7.51 for males and females respectively. The p-value for
the independent samples assuming equal variances was 0.934 which indicates that there is no
difference in driver aggression levels based on their gender. Similarly, it was also found that
there was no difference in thrill seeking and risk acceptance by gender – p-values 0.711 and
0.116 respectively. According to the participant's metropolitan background status, there was no
difference in driver aggression, thrill-seeking and risk acceptance. These tests head p-values of
0.475, 0.493 and 0.386 respectively. These variables were also evaluated based on the students’
study mode. It was found that driver aggression and thrill-seeking averages were not
significantly different by comparing full time and part-time students. However, risk acceptance
average for part-time students was significantly greater compared to that of full-time students (p-
value = 0.023). The variation of risk acceptance, thrill-seeking and risk acceptance was
heterogeneous for both students who experienced road traffic accidents and those who did not

HEALTH AND WELLBEING 3
(all p-values < 0.001). On average risk acceptance, driver aggression and thrill-seeking were
significantly different after comparing students who experienced RTA and those who did not.
2.2 Chi-square test of independence
We conducted a chi-square test of independence for depression and gender. Using the
Fisher’s test statistic, we conclude that there is no association between depression and gender (p-
value = 0.598). Likewise, there is no relationship between the metropolitan background status of
the student and depression (p-value = 0.743). We could also conclude that the depression status
is not dependent on whether the fees status of a student is international or domestic and their
study mode (p-values = 0.966 and 0.084 respectively).
2.3 Logistic Regression
2.3.1 Road traffic accidents (RTA) as the dependent variable
Sig. Odds Ratio
95% C.I.for Odds Ratio
Lower Upper
Demographics Ref
Age category .000
Age category(1) .000 3.241 2.680 3.921
Age category(2) .000 1.754 1.450 2.122
Age category(3) .684 1.044 .848 1.285
GENDER .000 .538 .482 .601
LIVING_ARRANGE .356 Ref
LIVING_ARRANGE(1) .151 .910 .799 1.035
LIVING_ARRANGE(2) .652 .963 .816 1.136
FEE_STATUS .000 1.707 1.454 2.005
Driving
Distance driving .271 .944 .852 1.046
Behaviour
Driver aggression .000 1.881 1.788 1.979
thrill .000 1.671 1.414 1.975
Risk acceptance .000 1.838 1.801 1.875
Constant .000 .000
a. Variable(s) entered on step 1: driver aggression, thrill, risk acceptance

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In general, living arrangement is not a significant predictor of whether a student has ever
been involved in a road accident or not. This is because the p-values for all the generated dummy
variables generated are greater than the significance level (0.05). Further, students living in
college or other student residential areas had 9% less chance of having been involved in a road
accident. Similarly, students living independently had 3.7% less chance of having experienced
road accident.
Age, fee status, driver aggression, thrill-seeking and risk acceptance are associated with
increased odds of having experienced road accidents. However, gender, living arrangements and
driving distance are associated with reduced odds. Being a female is associated with 46.2%
fewer odds of having experienced a road traffic accident.
2.3.2 Obesity at 3rd years as the dependent variable
Degree
of
freedo
m
Sig. Odds
Ratio
95% C.I.for Odds
Ratio
Lower Upper
Demographic
Age category 3 .000
Age category(1) 1 .000 1.999 1.733 2.306
Age category(2) 1 .000 1.410 1.220 1.630
Age category(3) 1 .227 1.103 .941 1.294
GENDER 1 .000 .686 .633 .745
LIVING_ARRANGE 2 .000
LIVING_ARRANGE(1) 1 .008 .881 .803 .967
LIVING_ARRANGE(2) 1 .221 1.075 .957 1.207
Baseline characteristics
Obese/Overweight at baseline 1 .329 .962 .891 1.040
depression 1 .000 14.635 12.990 16.487
Parental factors
Parents education 1 .000 .076 .067 .088
Parents Obese/Overweight 1 .000 7.581 5.356 10.730
Constant 1 .000 .037
a. Variable(s) entered on step 1: Parents education, Parents Obese/Overweight.

HEALTH AND WELLBEING 5
The students living arrangements were associated with a lower odds ratio for students
living in the college or other student accommodation and higher odds for those living
independently. Generally, the student accommodation is a significant predictor of the being
obese in their third year of college.
Age, depression, and parents status of obesity is associated with higher odds of being
obese. On the other side, gender, living arrangement, obesity status at baseline, and parents’
education are associated with lower odds of obesity.
3 Conclusion
In conclusion, gender, fee status, driver aggression, risk acceptance and thrill-seeking are
significant predictors of RTA. In addition, students aged 19-21 years and 22 – 25 years
compared to 18 years old significantly predicts the probability of having experienced road traffic
accident. Secondly, age (19 -21 and 22 – 25 categories), gender, living arrangement, depression,
parents education and obese information about students’ parents significantly predicts obesity
status of the students.