Physical Inactivity and Its Associated Factors among University Students

Abstract Background: Undiagnosed depression among university students has an adverse effect on the wellbeing and academic performance of students. This study aimed to assess the prevalence of depression and associated factors among Debre Birhan university students. Methodology: Institutional based cross-sectional study design is conducted in Debre Birhan University from April to June 2013 E.C. Three hundred sixty nine students participated in this study which was selected by simple random sampling technique. Data were collected by using a self-administered PHQ-9 standard depression questionnaire. First the data was entered into in Epidata 3.1 and then was exported to SPSS version 20 for analysis. Associated factors were identified using binary logistic regression and variables with a p-value < 0.05 were declared as statistically significant factors with the outcome variables. Result: All of the study subjects were between ages 18 and 33 with a mean age of 22.65 9 ± 2.78. The overall prevalence of depression is 17.1%. Among this according to PHQ-9 scores cut scores, 161(43.6 %) scored as normal (0–4), 145(39.3%) scored as mild (5–9), 53(14.4%) scored as moderate (10–14), 4(1.1%) scored as moderately severe (15–19) and 6(1.6%) students scored as sever (> 20). In multivariate analysis being female AOR = 9.28[3.47–24.81], academic year AOR = 0.236[0.059–0.936], smoking 26.3[9.33–74.1] and alcohol use AOR of 2.62[0.95–7.21] are significantly associated with depression. Conclusion and recommendation: This study found a considerable proportion of undergraduate students with depression. Higher institutions need to pay special attention to students especially those who are female, junior students, smokers and alcohol users.

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Faculty Opinions recommendation of Quality of life and associated factors among university students during the COVID-19 pandemic: a cross-sectional study.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.740954148.793590592 ◽

2021 ◽

Author(s):

Santosh Kumar

Keyword(s):

Quality Of Life ◽

University Students ◽

Associated Factors ◽

Cross Sectional Study ◽

Sectional Study ◽

Cross Sectional

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Prevalence and Associated Factors of Smartphone Addiction among University Students : A Northern Saudi Cross-Sectional Study

Aljouf University Medical Journal ◽

10.12816/0058987 ◽

2021 ◽

Vol 8 (2) ◽

pp. 33-43

Author(s):

Abouelkheir , Mohamed ◽

Thirunavukkarasu , Ashokkumar ◽

Albalawi , Faisal A. M. ◽

Alruwaili , Sultan H. H. ◽

Almugharriq , Malek M. N. ◽

...

Keyword(s):

University Students ◽

Associated Factors ◽

Cross Sectional Study ◽

Smartphone Addiction ◽

Sectional Study ◽

Cross Sectional

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Health-related Quality of Life and Associated Factors Among Undergraduate University Students

Oman Medical Journal ◽

10.5001/omj.2017.62 ◽

2017 ◽

Vol 32 (4) ◽

pp. 329-334 ◽

Cited By ~ 2

Author(s):

Naim Nur ◽

Ahmet Kıbık ◽

Esma Kılıç ◽

Haldun Sümer

Keyword(s):

Quality Of Life ◽

University Students ◽

Associated Factors ◽

Health Related Quality ◽

Undergraduate University Students ◽

Related Quality ◽

Health Related

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Prevalence of physical inactivity and associated factors among adolescents from public schools in Uruguaiana, Rio Grande do Sul State, Brazil

Cadernos de Saúde Pública ◽

10.1590/0102-311x00077512 ◽

2013 ◽

Vol 29 (11) ◽

pp. 2217-2229 ◽

Cited By ~ 9

Author(s):

Gabriel Gustavo Bergmann ◽

Mauren Lúcia de Araújo Bergmann ◽

Alexandre Carriconde Marques ◽

Pedro Curi Hallal

Keyword(s):

Physical Activity ◽

Public Schools ◽

Physical Education ◽

Physical Inactivity ◽

Associated Factors ◽

Female Gender ◽

Older Children ◽

Cross Sectional ◽

Behavioral Variables ◽

Cross Sectional Design

This study aimed to identify the prevalence of physical inactivity and associated factors in adolescents, using a cross-sectional design with a sample of 1,455 adolescents (741 females). Data were collected using a questionnaire consisting of socio-demographic, perceptual, and behavioral variables. Physical activity was estimated with the Physical Activity Questionnaire for Older Children and Adolescents. Prevalence of physical inactivity was 68% (95%CI: 65.6%-70.4%). The following variables remained associated with physical inactivity in the adjusted analysis (p < 0.05): living in an apartment, female gender, older adolescents, lower self-rated physical activity compared to peers, low perception of maternal physical activity, passive commuting to school, non-participation in physical education at school, non-enjoyment of physical education classes, and limited involvement in other types of physical exercise besides physical education at school. There were a high proportion of inactive adolescents. Strategies to prevent physical inactivity in adolescents should be elaborated with a central role for the school and family.

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