1. Introduction

Physical activity is defined as “any bodily movement produced by skeletal muscles that requires energy expenditure” ^[1]. Engaging in physical activity is a popular recommendation for improving Health-Related Quality of Life (HRQoL) as adequate levels of physical activity reduce the risk of many diseases, particularly cardiovascular diseases, colon and breast cancer, diabetes and depression. Moreover, physical inactivity is known to be the fourth leading risk factor for worldwide mortality, causing about 3.2 million deaths globally ^[2].

A plethora of studies ^{[3, 4, 5, 6]} have confirmed that physical activity is a good treatment for depression, which is a condition common among workaholics or individuals who work for hours on end without or with little rest ^{[7, 8]}. Depression is nonetheless a psychological and emotional disorder that would counter individuals’ happiness, HRQoL and productivity at work.

Though long hours of work is associated with depression ^[7], anecdotal evidence shows that some jobs require daily engagement in physical activity (PA). Many construction jobs, for instance, require engagement in physical activities such as walking, running and climbing. Therefore, in view of the empirical evidence that physical activity is a treatment for depression, Work-related Physical Activity (WPA) can counteract the adverse impact of hours of work on depression. Invariably, jobs rich in physical activity may result in less depression as compared to those largely associated with sedentary behavior or physical inactivity. No identifiable study has nevertheless been dedicated to assessing whether or not WPA is correlated to depression. To provide a basis for examining causation between WPA and depression in future research, this study ascertains whether or not WPA influences depression.

2. Methods

This study adopts a cross-sectional quantitative research technique to address the research problem. Basically, the levels of depression for three groups of workers having varied physical activity levels were compared to see if depression reduces with increasing physical activity. The three groups compared are described as follows:

Group 1 – the researcher refers to this group as sedentary jobs or SEDJOB. It is made up of individuals whose jobs require that at least 90% of working time is spent ‘sitting or reclining’, which World Health Organization (WHO) recognizes as sedentary behavior.

Group 2 – this is called partially sedentary jobs or PSJOB in this study. It is composed of individuals whose jobs require that between 45 to 50 per cent of working time is spent ‘sitting or reclining’ and the remaining proportion of this time is spent in physical activity.

Group 3 – The researcher calls this group physical jobs or PHYJOB. It is constituted by individuals whose jobs require that at least 90% of working time is spent in some kind of physical activity.

The researcher employed Analysis of Variance to verify the presence of a necessary systematic difference in the physical activity of the three groups. Outcomes of this analysis are shown in the results section of this study.

This study’s participants were volunteers working in various private and public sector organizations in Ho in the Volta Region of Ghana. In the process of selecting participants, the researcher took the list of all organizations in Ho from the Municipal Assembly. Each of the listed organizations was visited to identify, by means of a short interview, workers who were eligible to be included in any of the three groups. An individual could be in only one group.

In the interview, each participant was asked to describe his or her job in terms of how much it involved engagement in PA. Three general categories of responses provided the basis for forming the study groups. The three categories of responses are as follows:

Group 1(SEDJOB) – individuals revealed that their jobs requires sitting idle or by the computer for most of their working hours. They added that walking is the only physical activity they engage in at work, and walking about at work each day takes less than an hour.

Group 2 (PSJOB) – participants in this group agreed that about half of their working time requires participation in field work while the remaining half of this time involves sitting idle or by the computer. The field work they engage in daily involves much of climbing, walking, running, riding of bicycle, and/or other activities that increase the energy expenditure of their body.

Group 3 (PHYJOB) – participants in this group agreed that they engage in field work for most of their working hours, with less than an hour spent each day sitting idle or by the computer. The field work they engage in involves much of climbing, walking, running, riding of bicycle, and/or other activities that increase the energy expenditure of their body.

The researcher afterward used an informed consent form to identify willful participants in each organization. The number of participants reached for each group is as follows: Group 1 – 285; Group 2 – 241; and Group 3 – 260. A number of studies ^{[16, 17]} contend that group comparison using ANOVA yields the best result when all groups have the same number of participants. Based on ^[16] therefore, 47 and 20 participants were randomly taken out of groups 1 and 3 respectively, resulting in all groups having the same number of participants (number = 231).

The Beck Depression Inventory – II (BDI-II) was used to measure depression. BDI-II is a 21-item self-report rating inventory that is used to measure symptoms and characteristic attitudes of depression for the last two weeks ^[9]. It is associated with a 4-point scale that ranges from 0 (i.e. symptom not present) to 3 (i.e. symptom strongly present).The resulting summary scores thus range from 0 to 63, with 21 indicating depression at its lowest level. In this study, the BDI-II was employed because it provides evidence of current depression and it has been used at both clinical and non-clinical levels ^[10]. More importantly, it is largely validated ^[11].

Physical activity, on the other hand, was measured using the second version of WHO’s Global Physical Activity Questionnaire (GPAQ-2). The GPAQ-2 is the most recently validated version of the GPAQ and is much oriented for measuring physical activity relating to work. It also includes items that capture physical activity in days and hours, making it robust and comprehensive. Its first six items (i.e. Q1-Q6) measure work-related physical activity whereas the next nine items (i.e. Q7-Q15) measure physical activity relating to leisure and recreation. The sixteenth item (Q16) measures sedentary behavior. The GPAQ-2 has five questions that are associated with two levels of response, namely “Yes” and “No”. Based on ^[1], “Yes” and “No” were associated with the codes 1 and 2 respectively in this study. Since this study focuses on WPA, only the first six items of the GPAQ-2 were considered in data analysis. Based on ^[1], WPA was computed using the following formula:

WPA = (P2*P3*8) + (P5*P6*4), where the constants 8 and 4 represent the Metabolic Equivalents (METs) of vigorous and moderate WPA respectively, and P2, P3, P5 and P6 are respectively the second, third, fifth and sixth question on the GPAQ-2.

In addition, P2 and P3 measure vigorous WPA in days/week and hours/day respectively, while P5 and P6 measure moderate WPA in days/week and hours/day respectively. With respect to the above equation, the unit of measurement of PA is minutes per week. The GPAQ-2 specifies that the minimum recommended PA level is 600 minutes per week. For only WPA however, this value would be less than 600. Before WPA was computed using the above formula, the researcher identified based on the recommendation of ^[1] the proportion of individuals who did not engage in WPA and those who engaged in moderate and vigorous WPA based on responses to question 1 (P1) and 4 (P4).

Prior to data collection, the management of each organization from which participants were drawn endorsed the study. Each participant also signed an informed consent form, which clearly spelt out the benefits and potential risks to which every respondent was exposed.

Table 1. Study Response Rate

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Data was collected in about twelve (12) weeks through hand delivery of the self-reported questionnaire. The response rate achieved in data collection is shown in Table 1. For each group, almost equal numbers of males and females responded (Group 1: males = 111; females = 107; Group 2: males = 115, females = 106; Group 3: males = 117, females = 105), and the age distribution of the three groups is approximately the same (Group 1: mean = 24.6, SD = 12.2; Group 2: mean = 25.1, SD = 11.7; Group 3: mean = 24.9, SD = 13.4).

Data was analyzed using SPSS 21. Descriptive statistics were used to summarize the data. Normal distribution of the data was also tested and verified for the main dependent variables (i.e. Depression). Data associated with depression, the dependent variable, was normally distributed on the basis of satisfying p > 0.05 criterion recommended in the literature [e.g. 1,16,17] in terms of Shapiro-Wilk test (Statistic = 2.329, p = .601). Moreover, the z-score computed for each value of the dependent variable is within the generally recommended range of -3 to 3. In data analysis, the linear contrasts test was conducted to ascertain whether or not there is a “dose-response” relationship between WPA and depression and to correct the condition of the three groups having unequal variances. Results of the study are presented in the next section.

3. Results

Table 2 shows the number of participants who agreed to have engaged in vigorous and moderate WPA and those who indicated they did not. It can be seen from this table that the number of participants who engaged in vigorous WPA is lowest for SEDJOB (frequency = 4) and highest for PHYJOB (frequency = 117). On the other hand, the number of participants who did not engage in vigorous WPA is largest for SEDJOB (frequency = 214) and smallest for PHYJOB (frequency = 101). The evidence is similar for engagement in moderate WPA and suggests that the number of participants engaging in vigorous and moderate WPA is not the same for the three categories. This evidence is corroborated by results of the Pearson’s Chi-square test of association shown in Table 3.

Table 2. Number of Participants who engaged and did not engage in Vigorous and Moderate WPA

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Table 3. Chi-Square Tests of Association

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Table 4. Descriptive Statistics showing WPA Level of the three Groups

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Table 5. One-Way ANOVA [Testing for a Difference in WPA Level across the three Groups]

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Table 6. Contrasts Tests [Testing for a Difference in WPA Level across the three Groups]

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Table 7. Tamhane Multiple Comparison Test [Testing for a Difference in WPA Level across the three Groups]

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Table 8. Descriptive Statistics showing Depression Level of the three Groups

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Table 9. One-Way ANOVA [Testing for a Difference in Depression across the three Groups]

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Table 10. Contrasts Test [Testing for a Difference in Depression Level across the three Groups]

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Table 11. Tamhane Multiple Comparison Test [Testing for a Difference in Depression across the three Groups]

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With respect to “engagement in vigorous WPA” in Table 3, the Chi-square test is significant at 1% significance level [Chi-square (χ2) = 1151.351; df = 90; p = .000]. This result suggests that there is a positive relationship between group membership and engagement in vigorous WPA. Similarly, engagement in vigorous WPA increases from SEDJOB through PSJOB to PHYJOB. The Chi-square test is also significant at 1% significance level with respect to “engagement in moderate WPA” [Chi-square (χ2) = 1652.452; df = 90; p = .000]. Thus, engagement in moderate WPA increases from SEDJOB through PSJOB to PHYJOB. The respective Eta statistics corresponding to “engagement in vigorous WPA” and “engagement in moderate WPA” are 0.51 and 0.62. Since these statistics are greater than 0.5, the relationship between group membership and engagement in vigorous and moderate WPA is strong.

In Table 4, SEDJOB has the lowest level of WPA (Mean = 25.18, SD = 20.052, 95%CI = 19.99-30.37). PSJOB has a WPA level higher than SEDJOB but lower than PHYJOB (Mean = 426.67, SD = 142.297, 95%CI = 356.36-496.97). PHYJOB produces the highest level of WPA (Mean = 2752.68, SD = 628.99, 95%CI = 2541.50-2963.86). In Table 5, the ANOVA test is significant at 1% significance level [F (2, 690) = 509.52, p = .000]. This result implies that there was a difference in the WPA of the three groups. At the bottom of Table 5, Levene’s test is significant at 5% significance level (Statistic = 535.75, p = .000). Hence, it is assumed that the three groups have unequal variances.

Table 6 shows results of a linear contrasts test. Beneath this table are ANOVA-related statistics of the contrasts test. Of interest is the “Contrast”, which is statistically significant at 1% significance level (F = 226.038; p = 0.000). Moreover, results in this table with respect to “Assume equal variances” show that the three groups significantly differ in terms of WPA at 1% significance level (t = 12.04, df = 651, p = .000). Evidently, there is a “dose-response” relationship between WPA and group membership. In Table 7, the Tamhane Multiple Comparison test shows that the WPA score of PHYJOB is significantly larger than those of the other two groups at 1% significance level. The WPA score of PSJOB is also significantly larger than that of SEDJOB at 1% significance level. So the three groups compared had varied levels of WPA, and this provided a basis for comparing their depression levels as a way of examining the association between WPA and depression.

In Table 8, sedentary jobs have the highest level of depression (Mean = 26.03, SD = 10.24, 95%CI = 25.26-27.80). Partially sedentary jobs produce a depression level higher than SEDJOB but lower than PHYJOB (Mean = 15.867, SD = 7.49, 95%CI = 14.9, 16.9). Physical jobs produce the lowest level of depression (Mean = 11.119, SD = 6.26, 95%CI = 10.3, 12.0). In Table 9, the ANOVA test is significant at 1% significance level [F (2, 651) = 86.91, p = .000]. As a result, there is a significant difference in the depression of the three groups.

At the bottom of Table 9, Levene’s test is significant at 5% significance level (Statistic = 64.70, p = .000). It is thus assumed that the three groups had unequal variances. Below Table 10 are ANOVA-related statistics of the linear contrasts test. The “Contrast” category is statistically significant at 1% significance level (F = 873.997; p = 0.000). Moreover, results in Table 10 with respect to “Assume equal variances” show that the three groups significantly differ in terms of depression at 1% significance level (t = 12.04, df = 651, p = .000). It is therefore confirmed that there is a “dose-response” relationship between depression and group membership. In Table 11, the Tamhane Multiple Comparison test shows that mean score for the PHYJOB group is significantly larger than those of the other two groups at 1% significance level. The mean score of PSJOB is also significantly larger than that of SEDJOB at 1% significance level. So depression decreases across the three groups from SEDJOB through PSJOB to PHYJOB. The analysis thus confirms that depression decreases with increased WPA.

4. Discussion

Data analysis shows that depression reduces as work-related physical activity increases. For this reason, participants in the first group, SEDJOB, had the largest depression score and were as well depressed. The two other groups that more frequently engaged in work-related physical activity had lower depression scores and were not depressed. This result is supported by several studies ^{[3, 4, 5, 6]} conducted in western countries and signifies that engaging in physical activity reduces the level of depression.

The result reached in this study implies that working for long hours does not necessarily lead to depression. Moreover, works involving less physical activity and much of sedentary behavior would often result in depression, while those involving much more physical activity are likely to be associated with less depression. Nonetheless, working beyond a certain limit of time would not necessarily remedy depression owing to fatigue, occupational stress and strain ^[7]. The maximum working time that supports the reducing impact of work-related physical activity on depression is however an important topic that future research and academic debate should embrace.

Based on some studies ^{[13, 14]}, the positive effect of physical inactivity or sedentary behavior on depression could be worse depending on the sector in which an individual works. The services sector is characterized by more sedentary jobs (e.g. jobs requiring long hours of sitting, reclining, etc.). As seen in the data analysis therefore, depression is likely to be higher among people working in service-oriented companies. Employers and companies in this and similar sectors can change this anomaly by introducing a corporate policy that encourages individuals to engage in physical activity, at least on daily basis. A practical step that could be taken in the light of this policy is creating a suitable recreation center (e.g. Gym) where workers can exercise after hours of inactivity on their jobs.

This study suggests that individuals nurturing sedentary jobs are more vulnerable to depression, especially if employers do not provide appropriate interventions (such as the one mentioned above) to work-related sedentary behavior. Needless to say, many previous studies ^{[3, 8, 15]} have recommended non-work related physical activity as a way to reduce depression. Hence, workers have no choice than to resort to this option if employers are not ready to provide corporate systems that support work-related physical activity.

5. Conclusion

It is concluded that depression decreases as WPA increases. Physical jobs are therefore less likely to lead to depression. Unfortunately, many individuals would have the sole option of working in sectors that encourage sedentary behavior. As a consequence, it is incumbent on employers or companies to introduce policies and systems that support engagement in work-related physical activity.

While employers are less likely to provide such systems possibly due to the need to optimize operational cost and focus on core business activities, individual employees may have to get used to engaging in regular physical activity outside the work environment. Individuals could also regularly engage in physical activity at work, provided this step does not conflict with their jobs. For instance, a few minutes of aerobics during lunch time is acceptable and would be helpful.

References

[1]	World Health Organization (2014). Global recommendations on physical activity for health. Accessed [15 October, 2016] from: https://whqlibdoc.who.int/publications/2010/9789241599979_eng.pdf.
	In article
[2]	World Health Organization (2015). Physical activity strategy for the WHO European Region 2016-2025. Accessed [15 October, 2016] from: https://www.euro.who.int/__data/assets/pdf_file/0010/282961/65wd09e_PhysicalActivityStrategy_150474.pdf.
	In article
[3]	Babyak, M., Blumenthal, J.A., Herman, S., Khatri, P., Doraiswamy, M., Moore, K., Craighead, W.E., Baldewicz, T.T., Krishnan, K.R. (2000). Exercise Treatment for Major Depression: Maintenance of Therapeutic Benefit at 10 Months, Psychosomatic Medicine, 62:633-638.
	In article		View Article  PubMed
[4]	Craft, L.L., Perna, F.M. (2004). The Benefits of Exercise for the Clinically Depressed, Journal of Clinical Psychiatric, 6 (3): 104-113.
	In article		View Article
[5]	Baxter, H., Winder, R., Chalder, M., Wright, C., Sherlock, S., Haase, A., Wiles, N.J., Montgomery, A.A., Taylor, A.H., Fox, K.R., Lawlor, D.H., Peters, T.J., Sharp, D.J., Campbell, J., Lewis, G. (2010). Physical activity as a treatment for depression: the TREAD randomized trial protocol, Trials, 11 (105): 1-7.
	In article		View Article
[6]	Blake, H. (2012). Physical activity and exercise in the treatment of depression, Frontiers in Psychiatry, 3 (2): 1-4.
	In article		View Article
[7]	Dembe, A.E., Erickson, J.B., Delbos, R.G., Banks, S.M. (2005). The impact of overtime and long work hours on occupational injuries and illnesses: new evidence from the United States, Occupational Environment Medicine, 62: 588-597.
	In article		View Article  PubMed
[8]	Martinsen, E.W. (2008). Physical activity in the prevention and treatment of anxiety and depression, Nordic Journal of Psychiatry, 62: 25-29.
	In article		View Article  PubMed
[9]	Wang, Y.P., Andrade, L.H., Gorenstein, C. (2005). Validation of the Beck Depression Inventory for a Portuguese-speaking Chinese community in Brazil, Brazilian Journal of Medical and Biological Research, 38: 399-408.
	In article		View Article  PubMed
[10]	Grothe, K.B., Dutton, G.R., Jones, G.N., Bodenlos, J., Ancona, M., Brangtley, P.J. (2005). Validation of the Beck Depression Inventory—II in a Low-Income African American Sample of Medical Outpatients, Psychological Assessment, 17 (1): 110-114.
	In article		View Article  PubMed
[11]	Byrne, B.M, Stewart, S.M., Lee, P.W.H. (2004). Validating the Beck Depression Inventory–II for Hong Kong Community Adolescents, International Journal of Testing, 4(3), 199-216.
	In article		View Article
[12]	Sawilowsky, S. (2005). Misconceptions leading to choosing the t test over the Wilcoxon Mann-Whitney U test for shift in location parameter. Journal of Modern Applied Statistical Methods, 4 (2): 598-600.
	In article
[13]	Akhtar-Danesh, N., Landeen, J. (2007). Relation between depression and sociodemographic factors, International Journal of Mental Health Systems, 1 (4): 1-9.
	In article		View Article
[14]	Schutte, S.N., Malouff, J.M., Hall, L.E., Haggerty, D.J., Cooper, J.T., Golden, C.J., Dornheim, L. (1998). Development and validation of a measure of emotional intelligence. Personality and Individual Differences, 25: 167-177.
	In article		View Article
[15]	Webster, L. (2015). The effectiveness of physical activity as an intervention in the treatment of depression: A systematic review, Journal of Applied Psychology and Social Sciences, 1 (1): 28-40.
	In article
[16]	Kim, H. (2014). Analysis of variance (ANOVA) comparing means of more than two groups, Open Lecture on Statistics, 39(1): 74-77.
	In article		View Article
[17]	Sow, M.T. (2014). Using ANOVA to Examine the Relationship between Safety & Security and Human Development, Journal of International Business and Economics, 2(4): 101-106.
	In article		View Article