Leisure Time Physical Activity and Risk of Developing Depression among the Youth of Kangra District, Himachal Pradesh, India

Abstract

Background: Physical inactivity during adolescence and youth has been considered as potential risk factor for future mental health problems. The present study was conducted with the aim to examine whether an association exists between leisure-time physical activity (PA) and depression among the youth of Kangra district, studying in professional or degree colleges. Methodology: A cross-sectional study was conducted among the students of Medical College (MC), Central University (CU) and Industrial Training Institute (ITI) of Kangra district. 370 adolescents and youth of age <25 years, who consented to participate, were recruited. The sample size was divided into three parts among all the three institutes. Only one question regarding leisure time PA (LTPA) was asked, as to how many hours spent in the last week; and Center for Epidemiologic Studies Depression Scale for Children (CES-DC) was used. Results: There were 124 participants from ITI, 126 from CU and 120 from MC. The mean score of CES-DC was highest among CU students 22.7 (±11.0) and lowest among MC students; 13.6 (±9.2). Low LTPA (<4 h) was significantly associated with higher depressive symptoms among all students (odds ratio [95% confidence interval]; 3.34 [1.41–7.92]). Conclusion: LTPA was associated with lower rates of depression.

Physical activity and mental health in India: A narrative review

“…The articles included in this review followed either a cross-sectional or intervention study design. A majority of studies were conducted in clinical settings (Behere et al, 2011; Duraiswamy, Thirthalli, Nagendra, & Gangadhar, 2007; Ganesh & Mishra, 2016; Krishnamurthy & Telles, 2007; Manjunath, Varambally, Thirthalli, Basavaraddi, & Gangadhar, 2013; Ramanathan, Bhavanani, & Trakroo, 2017; Roy, Govindan, & Muralidharan, 2018; Telles, Singh, Yadav, & Balkrishna, 2012; Varambally et al, 2012), while other study settings included educational institutions, community, geriatric centres, a park, and a corporate organization (Deb et al, 2016; Ghosh & Datta, 2012; Ghrouz et al, 2019; Godse, Shejwal, & Godse, 2015; Hallam, Bilsborough, & de Courten, 2018; Mukherjee et al, 2017; Nayak, Mohapatra, & Panda, 2019; Ray et al, 2001; Singh et al, 2018; Telles et al, 2018). The recruitment of clinical patients in many of these studies could prevent results from being generalizable to a broader population of mentally ill individuals.…”

“…A few studies used validated measure like the Physical Activity Scale for Individuals With Physical Disabilities (PASIPD), the World Health Organization (WHO) Disability Assessment Schedule 2.0 (WHODAS 2.0), and the International Physical Activity Questionnaire–Short Form (IPAQ) (Ganesh & Mishra, 2016; Ghosh & Datta, 2012; Ghrouz et al, 2019; Mukherjee et al, 2017). The remaining studies measured prevalence by designing their own questionnaires asking participants whether they were active or not (Deb et al, 2016; Ghosh & Datta, 2012; Nayak et al, 2019; Singh et al, 2018). Medical data were not collected except in one study which recorded body mass index (BMI) of the participants and determined cut-off values for obesity according to WHO guidelines (Misra et al, 2009; Singh et al, 2018).…”

“…The remaining studies measured prevalence by designing their own questionnaires asking participants whether they were active or not (Deb et al, 2016; Ghosh & Datta, 2012; Nayak et al, 2019; Singh et al, 2018). Medical data were not collected except in one study which recorded body mass index (BMI) of the participants and determined cut-off values for obesity according to WHO guidelines (Misra et al, 2009; Singh et al, 2018). Using unstandardized tools and questionnaires could have neglected reporting on the nature of the physical activity as well as its intensity and duration.…”

Describing Research Design

“…Singh et al [ 1 ] made a curious observation in an earlier issue of this journal; the gist was that because their study[ 2 ] was cross-sectional in design, it could not be considered prospective. Their observation prompted a discussion in eJCIndia,[ 3 ] during the course of which it became apparent that there are widespread misunderstandings about how research design is described.…”

“…The reader will now immediately see that a study can be classified in many different ways at the same time, as in randomized, double-blind, active- and placebo-controlled, parallel arm superiority trials that are additionally, and almost by definition, empirical, sample-based, prospective, longitudinal, interventional, and hypothesis-driven in nature. The reader will now also understand why the study of Singh et al [ 2 ] was both prospective and cross-sectional. It was prospective because they recruited subjects and collected new data, as different from extracting data that already existed in paper or electronic records (which would have made it a retrospective study).…”