Authors
Vanessa Grout, Elizabeth A. Easley, Sarah H. Sellhorst, William F. Riner, Dept. of Exercise

 

 

Introduction

Sedentary behavior is believed to have increased over the past years due to the popularization of media use (Fountaine, Liguori, Mozumdar, Schuna, 2011; Matthews et al., 2008). According to a systematic review of research, increased sedentary time is linked to lower health-related quality of life among adolescents (Wu et al., 2017). When compared to other age groups, young adults (18-29yrs) have the most increasing rates of overweight and obeseindividuals (Gropper, Simmons, Connell, & Ulrich, 2012; Mokdad et al., 1999). Additional research is necessary in order to develop new interventions that will promote physical activity and reduce sedentary behaviors in college student populations.

Sedentary behavior is any behavior in sitting position that requires little energy expenditure such as 1.0- 1.5 metabolic equivalents or METS (Han, Gabriel & Kohl, 2017; Matthews et al., 2008; Owen, Leslie, Salmon, & Fotheringham, 2000). Examples of sedentary behaviors include television viewing, computer use, and playing video games (Fountaine, Liguori, Mozumdar, & Schuna, 2011; Gabriel, Morrow, & Woolsey, 2012; Han, Gabriel, & Kohl, 2017; Ianotti et al., 2009; Marshall, Gorely, & Biddle, 2006). U.S young adults spend more than 7.5-8.0 hours/day on sedentary behaviors (Han, Gabriel & Kohl, 2017; Matthews et al., 2008). Adverse effects that result from sedentary behaviors include an increased risk of obesity as well as an increased risk of cardiovascular disease (Costigan, Barnett, Plotnikoff, Lubans, 2013; Ianotti et al., 2009; Prentice-Dunn & Prentice-Dunn, 2012; Ussher, Owen, Cook, Whincup, 2007; Wu et al., 2017).

Numerous research-supported health benefits of physical activity include improved blood circulation and increased metabolic energy (Ianotti et al., 2009; Strong et al., 2005). Physical activity is any activity that requires movement, which creates a physiological response that will increase energy expenditure and improve physical fitness (Gabriel, Morrow, & Woolsey, 2012; Han, Gabriel & Kohl, 2017; Ianotti et al., 2009). The U.S Department of Health and Human services recommended daily physical activity guidelines include 150 minutes of moderate-to- vigorous activity per week or 10,000 steps per day. Currently, there is a lack of research literature regarding sedentary behaviors and physical activity patterns in college student populations. In order to increase health awareness in college students, it is important to promote positive health behaviors during young adulthood as well as to prevent chronic disease in later adulthood (Strong et. al., 2005). Early implementation of interventions such as increasing physical activity and reducing sedentary behaviors can improve lifestyle habits. In addition, increasing physical activity levels can help prevent the long lasting effects of obesity, which are often associated with chronic diseases such as cardiovascular disease and Non-insulin dependent diabetes mellitus (Altenburg et al., 2012).

It is important to examine differences between sexes to understand quality of life, physical activity patterns, and motives for exercise (Craft, Carroll, & Lustyk, 2014). The purpose of physical activity may vary depending on sex such as as weight loss, desire to improve self- esteem, overall psychological well-being, to maintain fitness, and/or for enjoyment (Craft, Carroll, & Lustyk, 2014; Tergerson & King, 2002). Also, genetic sex differences require individualized physical activity plans for varying types of exercise including strength, endurance, flexibility, and balance to obtain best health outcomes and achieve maximum benefits.

The purpose of this study was to determine if there were statistically significant sex differences among objectively measured sedentary behaviors and physical activity levels in traditional-aged college students at a small, rural, commuter-based campus. The research goals were to compare leisure-time physical activity measured by accelerometers between male and female students. In addition, this study independently measured sedentary behavior as well as light, moderate, vigorous, and moderate-to-vigorous physical activity at leisure.

 

 

Methods

Ethics Statement

This research study was approved by the Institutional Review Board at the University of South Carolina. All participants completed a written informed consent and voluntarily agreed to participate prior to the commencement of the study.

Design and Population

Body weight was measured to the nearest 0.1 kilogram (kg) in light clothing with shoes removed using a calibrated digital scale (Seca model 869, Hamburg, Germany). Height was measured to the nearest 0.1 centimeter (cm) using a wall-mounted stadiometer without shoes (Seca model 424, Hamburg, Germany). Body weight and height were obtained to calculate body mass index (BMI, kg/m²). Number of steps, sedentary activity, light physical activity, moderate physical activity and vigorous physical activity, very vigorous, and moderate-to-vigorous levels (MVPA) were objectively measured using triaxial accelerometers (Acti-Graph-GT3X, Pensacola, FL). Actigraph accelerometers (Actigraph GT3X, Pensacola, FL) were also used to determine frequency, duration and intensity of sedentary activity as well as physical activity levels. The established cut-point values by Actigraph were used to determine the different intensity levels of the physical activity. The cut-point values for different intensity levels were the following: sedentary, 0-99 counts/min; light, 100-1951 counts/min; moderate, 1952-5724 counts/min; vigorous, 5725-9498 counts/min; and very vigorous, 9499-above counts/min.

Participants wore the sensor-based accelerometers for seven consecutive days during all waking hours to ensure accuracy of a typical day. Data were collected in 10 second long epochs as an established unit and time frame. The minimum required wear time of the accelerometers was at least eight hours for three days (Ruiz et al., 2011). Total wear time was calculated by averaging two weekdays and one weekend day provided by three valid days of accelerometer data. Total sedentary time was calculated by averaging two weekdays and one weekend day provided by three valid days of accelerometer data. Non-wear was determined using paper logs recalling accelerometer wear-time in combination with accelerometers to validate data.

 

Statistical Analyses

 All statistical analyses were performed using SPSS statistics software (IBM, v. 24). A multivariate ANOVA was used to determine significant differences between sexes. The MANOVA determined that there was a significant sex difference in physical activity variables.

 

Results

Table 1. Descriptive anthropometric characteristics

	Males (n = 32)	Females (n = 45)	Total (n = 77)
Age (yrs)	19.31 ± 1.45	19.27 ± 1.40	19.35 ±1.43
Height (cm)	174.32 ± 7.16	164.58 ± 5.46	169.45 ± 6.31
Weight (kg)	76.14 ± 18.47	67.70 ± 15.98	71.92 ± 17.23
BMI	24.87 ± 5.02	24.96 ± 5.60	24.92 ± 5.31

 

 

Table 2. Descriptive Physical Activity and Sedentary Activity Levels and the comparisons between sexes

Dependent   Variable	Male (n = 32)	Female (n = 45)	p-value
Minutes spent in Sedentary	3880.20 ± 167.25	3985.96 ± 141.04	p = 0.630

 

Activity (min/week)
Minutes spent in Light Physical Activity (min/week)	1069.63 ± 198.72	1209.48 ± 167.57	p = 0.592
Minutes spent in Moderate Physical Activity (min/week)	286.41 ± 20.36	194.92 ± 17.17	p = 0.001
Minutes spent in Vigorous Physical Activity (min/week)	21.40 ± 6.46	11.09 ± 5.45	p = 0.226
Minutes spent in Very Vigorous Activity (min/week)	5.68 ± 3.19	5.39 ± 2.69	p = 0.945
Minutes spent in MVPA (min/week)	313.49 ± 23.93	211.41 ± 20.18	p = 0.002
Average Steps	7545.38 ± 539.60	6469.15 ± 455.03	p = 0.132

100 full-time (>12 hours) traditional-aged college students (18-25yrs) at a rural two-year college campus participated in this present study. After exclusions, (n = 50) female and (n = 50) male participants of the population cohort remained in the study. For the purpose of this study, pregnant females and student athletes were excluded from this study. Students were mostly Caucasian (66.7%), followed by African American (21.9%), Other (9.4%), and Native American (2.1%). The students were measured between August 2015 and November 2016. Data collection took place during the academic school year excluding holiday breaks. Due to a limited number of accelerometers students were measured in the fall semester (n = 83) while the remainder of students were measured in the spring semester (n = 14). Since individuals tend to be more physically active in different seasons an analysis was conducted to compare seasonal variation between fall semester participants and spring semester participants. Levene’s test for equality of variances determined that there were no differences in seasonal variances between groups. Of the 100 initial volunteers (males, n = 50 and females, n= 50), 77 (males, n = 32, females, n = 45) participants completed all requirements and remained within the study.

A multivariate test using Wilk’s Lambda showed significant association among sexes (p = 0.009). A significant sex difference was determined for physical activity between groups, Wilks’ lambda = 0.809, F (5, 71) = 3.342, p = 0.009. Pairwise comparisons demonstrated that men spent more time in moderate physical activity than women (286.41 ± 20.36 min/week vs. 194.92 ± 17.17 min/week, p = 0.001). Pairwise comparisons also demonstrated that men spent more time in MVPA than women (313.49 ± 23.93 min/week vs. 211.41 ± 20.18, p = 0.002).

In summary, this study determined that there was a significant difference in moderate physical activity between sexes. Minutes spent in moderate physical activity were greater for men than women (mean difference = 91.49 min/week). Men also spent more time in MVPA than women (mean difference = 102.08 min/week). Overall, there were no additional statistically significant differences in average daily steps, time spent on sedentary activity, light physical activity, and vigorous physical activity in between sexes.

 

Discussion

A study that assessed physical activity patterns in Portuguese university students determined that male students walked more steps, spent less time in sedentary behaviors and light activity and more time in moderate-to-vigorous physical activity during the week days (Clemente, Nikolaidis, Martins, & Mendes, 2016). This study is similar to the results of the present study, which compared varying levels of physical activity between sexes. Despite these results, the present study only found statistically significant differences in moderate physical activity levels and MVPA. Another comparable study conducted by the University of Oklahoma determined that college students were more active during weekdays when compared to weekend days (Dinger & Behrens, 2006). This increase in activity during the week may be due to extracurricular activities other than school requirements and/or employment opportunities. In addition, most participants in that study did not meet the recommended daily physical activity guidelines (Dinger & Behrens, 2006).

The overall decrease in physical activity among young adults is supported by the theory of inverse relationship between physical activity levels and sedentary behaviors. The theory of inverse relationship explains the overall decrease of physical activity levels due to an increase in sedentary behaviors thus decreasing the overall energy expenditure among young adults during the period of transition from high school to college or university (Han, Gabriel, & Kohl, 2017;

Owen et al., 2011). However, other research suggests that sedentary behavior is independent of physical activity suggesting that an individual can be highly physically active but also spend an increased amount of time in sedentary behavior (Han, Gabriel, & Kohl, 2017; Whitfield, Gabriel, & Kohl, 2014). In order to reduce sedentary behaviors in college student populations, individuals must demonstrate motivational readiness and actively take initiatives towards reducing sedentary behaviors (Han, Gabriel, & Kohl, 2017).

The significant difference found in males in regards to moderate physical activity might be related to motivation to participate in leisure-time physical activity. Although the psychosocial aspects of physical activity were not analyzed in this present study, it is believed that there are true differences in physical activity motivation between sexes. Typically, adolescents use physical activity for leisure, socializing, and to improve self-esteem (Tergerson & King, 2002). Current research suggests that leisure physical activity in females declines during adolescence, while declines are not noted for males until the third decade of life (Kimm, et al., 2002; Matthews et al., 2008). The differences in moderate physical activity could prove detrimental for the health risk of female college students and show further decline with age. It is also believed that physical activity rapidly declines from adolescence to adulthood due to the establishment of careers and/or development of families during this time (Bureau of Labor & Statistics, 2005; Matthews et al., 2008). In addition, literature supports that physical inactivity increases with age (Han et al., 2008; Matthews et al., 2008). Recent research shows that increased levels of sedentary activity leads to higher body fat percentage, an increase in weight, and less lean muscle mass in later adulthood (Matthews et al., 2008). 

A study that assessed perceived benefits of physical activity in adolescents determined that females perceived physical activity as leisure exercise to improve physical fitness, stress relief, self-esteem, and/or to promote weight loss (Tergerson & King, 2002). This study also reported that males perceived physical activity as competitive sports to improve muscular strength and/or for peer acceptance during adolescence (Tergerson & King, 2002). Regardless of perception of physical activity, it is important for students that are transitioning from adolescence to young adulthood to continue to engage in physical activity. This is generally achieved by the implementation of an active lifestyle, which can potentially improve future health outcomes.

Strengths of the present study include the use of sensor-based accelerometers as an objective measure of physical activity. Also, the analysis included data based on accelerometer measurements of physical activity and sedentary time. The lack of significant differences among sedentary behaviors and physical activity between female and male college students may be due to several factors. Factors such as a small sample size may have influenced the lack of significant differences among sedentary behaviors and physical activity between sexes.

Limitations of this study also include a lack of diversity in the participants due to the location of a rural college campus setting. Another limitation of the present study is that although accelerometers were used to measure sedentary behavior, they are unable to detect differences in varying types of sedentary activities (Altenburg et al., 2012). This study did not take into account factors such as the impact of diet, lifestyle, and genetics.

 

Conclusion 

This study concluded that there was a statistically significant difference in physical activity patterns among males when compared to females. In addition, this study revealed that male students spent more time in moderate physical activity and MVPA than female students. These results are an indicator of individual’s risk for future health concerns and may be used to increase health awareness in college student populations. Additional research is suggested to further our findings.

 

About the author

Vanessa Grout 

My name is Vanessa Grout and I am originally from Passaic, New Jersey. I am a senior currently enrolled in the Bachelor of Science in Nursing program at USC-Lancaster distance campus. My educational background includes a Bachelor of Science in Health Sciences and Services from Queens University of Charlotte ’15. In April 2018, I had the privilege of being awarded first place in the health sciences category at USC Discover for my undergraduate research work on “the relationship among screen-time, body fat percentage, and measured physical activity in college student populations”.  In May 2018, I completed the Graduation with Leadership distinction program and attained an Associate’s in Science degree at USCL with a concentration in Research. I also have had the opportunity to co-author and earn a Magellan Mini-Grant for an upcoming research study at the Lancaster campus. I have always enjoyed caring for others and love how diverse nursing can be. My two passions include public health and critical care and I hope to one day become a nurse practitioner of my own clinic that specializes in Family Medicine.   

 

  My goals for this project are to disseminate knowledge learned from our research findings and to promote health education in college student populations in addition to raising awareness about the importance of implementing positive health behaviors such as physical activity during young adulthood. I would like to thank my mentors Dr. Elizabeth Easley, Dr. Sarah Sellhorst, and Dr. William “Bill” F. Riner of the Exercise Science Dept. at USC- Lancaster for their guidance and support throughout my academic career. I would also like to thank all of the hardworking student research assistants who worked on data collection and data entry for this study. Lastly, I would like to thank all of the Research Club executive committee members who have dedicated their time to promoting science, research, and higher learning in our community of Lancaster, South Carolina.  

References

Altenburg, T. M., Hofsteenge, G. H., Weijs, P. M., Delemarre-van de Waal, H. A., & Chinapaw, M. M. (2012). Self-Reported Screen Time and Cardiometabolic Risk in Obese Dutch Adolescents. Plos ONE, 7(12), 1-4. doi:10.1371/journal.pone.0053333

Bureau of Labor Statistics, US Department of Labor. (2005). American Time Use Survey— 2004 results announced by BLS. (News release). (USDL publication no. 05- 1766), 2005 Washington, DC. (http://www.bls.gov/news.release/archives/atus_09202005.pdf).

Clemente, F. M., Nikolaidis, P. T., Martins, F. L., & Mendes, R. S. (2016). Physical Activity Patterns in University Students: Do They Follow the Public Health Guidelines?. Plos ONE, 11(3), 1-11. doi:10.1371/journal.pone.0152516

Costigan, S. A., Barnett, L., Plotnikoff, R. C., & Lubans, D. R. (2013). The health indicators associated with screen-based sedentary behavior among adolescent girls: a systematic review. Journal of Adolescent Health, 52(4), 382-392. 

Craft, B. B., Carroll, H. A., & Lustyk, M. K. (2014). Gender Differences in Exercise Habits and Quality of Life Reports: Assessing the Moderating Effects of Reasons for Exercise. International journal of liberal arts and social science, 2(5), 65–76.

Dinger, M. K., & Behrens, T. K. (2006). Accelerometer-determined physical activity of free- living college students. Medicine and science in sports and exercise, 38(4), 774. doi: 10.1249/01.mss.0000210191.72081.43

Fountaine, C. J., Liguori, G. A., Mozumdar, A., & Schuna Jr, J. M. (2011). Physical activity and screen time sedentary behaviors in college students. International Journal of Exercise Science, 4(2), 3.

Gabriel, K. K. P., Morrow Jr, J. R., & Woolsey, A. L. T. (2012). Framework for physical activity as a complex and multidimensional behavior. Journal of Physical Activity and Health, 9(s1), S11-S18.

Gropper, S. S., Simmons, K. P., Connell, L. J., & Ulrich, P. V. (2012). Weight and Body Composition Changes during the First Three Years of College. Journal Of Obesity, 20121-6. doi:10.1155/2012/634048

Han, H., Pettee Gabriel, K., & III Kohl, H. W. (2017). Application of the transtheoretical model to sedentary behaviors and its association with physical activity status. Plos ONE, 12(4), 1-13. doi:10.1371/journal.pone.0176330

Han, J. L., Dinger, M. K., Hull, H. R., Randall, N. B., Heesch, K. C., & Fields, D. A. (2008). Changes in women’s physical activity during the transition to college. American Journal of Health Education, 39(4), 194-199.

Iannotti, R. J., Janssen, I., Haug, E., Kololo, H., Annaheim, B., & Borraccino, A. (2009). Interrelationships of adolescent physical activity, screen-based sedentary behaviour, and social and psychological health. International journal of public health, 54(2), 191-198.

Kimm, S. Y., Glynn, N. W., Kriska, A. M., Barton, B. A., Kronsberg, S. S., Daniels, S. R., ... & Liu, K. (2002). Decline in physical activity in black girls and white girls during adolescence. New England Journal of Medicine, 347(10), 709-715.

Marshall, S. J., Gorely, T., & Biddle, S. J. (2006). A descriptive epidemiology of screen- based media use in youth: a review and critique. Journal of adolescence, 29(3), 333- 349.

Matthews, C. E., Chen, K. Y., Freedson, P. S., Buchowski, M. S., Beech, B. M., Pate, R. R., & Troiano, R. P. (2008). Amount of time spent in sedentary behaviors in the United States, 2003–2004. American journal of epidemiology, 167(7), 875-881.

Mokdad, A. H., Serdula, M. K., Dietz, W. H., Bowman, B. A., Marks, J. S., & Koplan, J. P. (1999). The spread of the obesity epidemic in the United States, 1991-1998. Jama, 282(16), 1519-1522.

Owen, N., Leslie, E., Salmon, J., & Fotheringham, M. J. (2000). Environmental determinants of physical activity and sedentary behavior. Exerc Sport Sci Rev, 28(4), 153-158.

Owen, N., Sugiyama, T., Eakin, E. E., Gardiner, P. A., Tremblay, M. S., & Sallis, J. F. (2011). Adults' sedentary behavior: determinants and interventions. American journal of preventive medicine, 41(2), 189-196. 

Physical Activity Guidelines Advisory Committee. (2008). Physical activity guidelines for Americans. Washington, DC: US Department of Health and Human Services, 15-34.

Prentice-Dunn, H., & Prentice-Dunn, S. (2012). Physical activity, sedentary behavior, and childhood obesity: a review of cross-sectional studies. Psychology, health & medicine, 17(3), 255-273.

Ruiz, J. R., Ortega, F. B., Martínez-Gómez, D., Labayen, I., Moreno, L. A., De Bourdeaudhuij, I., ... & Widhalm, K. (2011). Objectively measured physical activity and sedentary time in European adolescents: the HELENA study. American journal of epidemiology, 174(2), 173-184.

Strong, W. B., Malina, R. M., Blimkie, C. J., Daniels, S. R., Dishman, R. K., Gutin, B., ... & Rowland, T. (2005). Evidence based physical activity for school-age youth. The Journal of pediatrics, 146(6), 732-737.

Whitfield, G., Gabriel, K. K. P., & Kohl III, H. W. (2014). Sedentary and active: self- reported sitting time among marathon and half-marathon participants. Journal of Physical Activity and Health, 11(1), 165-172.

Wu, X. Y., Han, L. H., Zhang, J. H., Luo, S., Hu, J. W., & Sun, K. (2017). The influence of physical activity, sedentary behavior on health-related quality of life among the general population of children and adolescents: A systematic review. PLoS ONE, 12(11), e0187668. http://doi.org/10.1371/journal.pone.0187668

U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division of Nutrition and Physical Activity. Promoting physical activity: a guide for community action. Champaign, IL: Human Kinetics, 1999. (Table adapted from Ainsworth BE, Haskell WL, Leon AS, et al. Compendium of physical activities: classification of energy costs of human physical activities. Medicine and Science in Sports and Exercise1993; 25(1): 71-80.)

Ussher, M. H., Owen, C. G., Cook, D. G., & Whincup, P. H. (2007). The relationship between physical activity, sedentary behaviour and psychological wellbeing among adolescents. Social psychiatry and psychiatric epidemiology, 42(10), 851-856