|Year : 2019 | Volume
| Issue : 2 | Page : 63-70
Influence of leisure-time physical activity constraints on physical activity participation of working-class individuals: A cross-sectional study
Mannir Kassim1, Musa Sani Danazumi2, Abdulsalam Mohammed Yakasai3, Abdu Lawan4, Usman Usman Zakari5
1 Medical Rehabilitation Therapists (Reg.) Board of Nigeria, North-East Zonal Office, Bauchi State, Nigeria
2 Department of Physiotherapy, Federal Medical Center, Nguru, Yobe State; Department of Physiotherapy, Faculty of Allied Health Sciences, College of Health Sciences, Bayero University, Kano, Nigeria
3 Medical Rehabilitation Therapists (Reg.) Board of Nigeria, North-West Zonal Office, Kano, Nigeria
4 Department of Physical Health Education, Faculty of Education, Bayero University Kano, Kano, Nigeria
5 Department of Physiotherapy, Federal Medical Centre Birnin Kudu, Jigawa State, Nigeria
|Date of Submission||01-Nov-2019|
|Date of Decision||07-Dec-2019|
|Date of Acceptance||27-Dec-2019|
|Date of Web Publication||02-Apr-2020|
Mr. Musa Sani Danazumi
Department of Physiotherapy, Federal Medical Center, Nguru, Yobe State; Department of Physiotherapy, Faculty of Allied Health Sciences, College of Health Sciences, Bayero University, Kano
Source of Support: None, Conflict of Interest: None
Introduction: Constraints to leisure-time physical activity (PA) have been studied by many researchers all over the world. However, these studies were based on prevalence and were not able to determine the impact of these constraints among working-class individuals. The current study was conducted to determine the impact and influence of leisure-time PA constraints (LTPACs) on PA participation of working-class individuals. Materials and Methods: A cross-sectional study of 401 participants was conducted. PA levels were measured using the International PA Questionnaire. LTPACs were measured using the Leisure Constraints Questionnaire. Binomial logistic regression analysis was conducted to determine the influence of the constraint variables on PA. Results: The results indicated that 34.4% of the participants were sufficiently active and 65.6% of the participants were not physically active. The predictor constraints explained 68.1% of the variability in PA (Nagelkerke R2=0.681). The most significant predictors were lack of friends (odds ratio [OR] =8.360, confidence interval [CI] =6.671–10.468), lack of time due to work (OR = 8.313, CI = 6.633–10.419), lack of interest (OR = 2.190, CI = 1.161–4.121), lack of knowledge (OR = 1.360, CI = 1.049–1.764), and inadequate facilities (OR = 1.181, CI = 1.083–1.276). Conclusion: LTPACs were reported to be endemic among working-class individuals. These constraints need to be highly considered when health-care policies are being developed to ensure good health and longevity of workers.
Keywords: Leisure-time constraints, physical activity, working-class
|How to cite this article:|
Kassim M, Danazumi MS, Yakasai AM, Lawan A, Zakari UU. Influence of leisure-time physical activity constraints on physical activity participation of working-class individuals: A cross-sectional study. Niger J Exp Clin Biosci 2019;7:63-70
|How to cite this URL:|
Kassim M, Danazumi MS, Yakasai AM, Lawan A, Zakari UU. Influence of leisure-time physical activity constraints on physical activity participation of working-class individuals: A cross-sectional study. Niger J Exp Clin Biosci [serial online] 2019 [cited 2021 Mar 3];7:63-70. Available from: https://www.njecbonline.org/text.asp?2019/7/2/63/281621
| Introduction|| |
The prevalence of noncommunicable diseases (NCDs) has increased substantially over the last two decades and has become a leading cause of deaths globally. These diseases are attributed to individual behavior and lifestyle habits, which are to a large extent influenced by economic transition, rapid urbanization, and modern lifestyle factors including diet and physical activity (PA).
PA is described as any bodily movement produced by the skeletal muscles that result in energy expenditure above the resting metabolic equivalent (MET). The benefits of involvement in PA and exercise have grown to become a strategic health importance and that have attracted the attention of people of all ages. According to the World Health Organization (WHO), participating in exercise- and recreation-based PA enhances the quality of life and overall well-being. Therefore, promoting active and healthy lifestyle during the working years of life is a key factor for preventing chronic diseases and disability and ensures a healthy retirement.
Physical inactivity levels are rising in many countries including Nigeria, and are implicated in the endemic of NCDs worldwide. Physical inactivity is now identified as the fourth leading risk factor for global mortality. A report by the WHO has shown that physical inactivity is estimated as being the principal cause of approximately 21%–25% of breast and colon cancer burden, 27% of diabetes, and approximately 30% of ischemic heart disease burden. This indicated that work–life PA and fitness program may ensure good health and longevity for a large number of workers. Unfortunately, a considerable number of employees spend much time in workplaces which are not free from debilitating leisure-time PA constraints (LTPACs).
However, this setback in PA or lifestyle can be modified if not completely reversed to ensure good-quality workforce and efficient service through adhering to proper PA guidelines produced by the pertinent authorities. Unarguably, in spite of this development, it is still a worrisome issue to most Nigerian workers because they fall short of the American College of Sports Medicine exercise guidelines due to some very important circumstantial constraints. Nevertheless, knowing these constraints may promote PA advocacy and enlightenment campaigns. Yet, there is no reliable information on the perceived constraints to PA participation among the working class in Nigeria. For these reasons, this study was conducted to examine the influence of LTPACs among Nigerian working-class individuals.
| Materials and Methods|| |
Research design and setting
This study was a descriptive cross-sectional survey conducted to determine the point prevalence of physical inactivity and influence of constraints to leisure-time PA (LTPA) on PA participation of working-class population in a metropolitan Nigerian city.
Ethical approval to conduct this study was sought from the Health Research Ethics Committee of Bauchi State Hospitals' Management Board, Nigeria, according to the Declaration of the Helsinki. Prior to the administration of the questionnaire, verbal consent was obtained from the participants after informing them about the objectives and purpose of the study. The participants were also assured of anonymity and their ability to decline their voluntary response.
Sample size and sampling technique
The sample size was estimated using the following formula for cross-sectional studies: (n = Z2 P [1 − P]/d2) (where n = minimum sample size, Zα/2 set at 5% significant level = 1.96, P = estimate of prevalence of physical inactivity among Nigerian populace which was examined to be 41% =0.41, and d = absolute error or precision [5%]). Adjustment for nonresponse rate (nr/r − 1) of 10% was also calculated, which gave a total sample size of 413 participants for this study.
For the purposes of regression analysis, the estimated sample size also supported the model because it has been suggested that one of the assumptions of regression is that the sample size should be sufficient enough to support the model. The sample size required to support a model depends on both the R- value of the model and the number of variables that are included.,, A simple rule that has been suggested for predictive equations is that the minimum number of cases should be at least 100 or, for step-wise regression, that the number of cases should be at least 40 × m, where m is the number of variables in the model., In the current study, eight predictor variables were identified as the variables that may influence PA. Based on this assumption, the sample size was calculated as 40 × 8 = 320. Therefore, the calculated sample size of 413 using the cross-sectional design formula, very well supported the regression model.
Based on the sample size estimation, a total of 413 healthy working-class individuals who were staff of different establishments (state, federal, and private) in Bauchi State, Nigeria, were recruited for the study using a convenient sampling method.
The criteria for inclusion in the study were (1) working-class individuals with an age of 18 years and above, (2) lack of cognitive impairment, and (3) independence in the activities of daily living. The exclusion criteria were participants (1) with psychiatric or behavioral conditions, (2) with severe cardiorespiratory problems, (3) who have red flags (history of significant trauma, cancer, constitutional symptoms, fever, malaise, weight loss, recent infection, and bladder and/or bowel dysfunction), and (4) unable to provide consent.
Physical activity measure
Information on PA behaviors was collected using the short-form self-administered, last-week version of the International PA Questionnaire (IPAQ). The instrument inquires about the time spent being physically active in the last 7 days and measures vigorous-intensity activities, moderate-intensity activities (walking not included), walking activity, and sitting activity. These activity categories were treated separately to obtain the activity pattern or multiplied by their estimated value in METs and summed up to gain an overall estimate of PA in a week. One MET represents the energy expended while sitting quietly at rest and is equivalent to 3.5 ml/kg/min of maximum oxygen consumption (VO2 max). The MET intensities used to score IPAQ questions in this study were vigorous (8 METs), moderate (4 METs), and walking (3.3 METs).
These three groups were then categorized as sufficiently physically active or physically inactive. The sufficiently physically active group included participants in the moderate- or high-intensity categories who met the WHO PA recommendations. The physically inactive group included participants in the low-intensity category who did not meet the WHO PA recommendations.
The IPAQ has been tested for psychometric properties in both developed and developing countries and has an acceptable test–retest reliability coefficient (r = 0.70–0.97) and criterion validity (r = 0.23) compared with accelerometer monitoring. The IPAQ is considered to have similar measurement properties as other self-report measures of PA.
PA participation constraints among the workers were measured using the Leisure Constraints Questionnaire (LCQ). The questionnaire was adopted and attached to a pro forma containing information on the participants' sociodemographic characteristics. The questionnaire has three parts namely (1) intrapersonal constraints, (2) interpersonal constraints, and (3) structural constraints. Intrapersonal constraints refer to how individual characteristics such as attitudes, values, and beliefs detrimentally affect PA participation. Interpersonal constraints arise from interactions with others, such as lack of social or family support. Structural constraints are any barriers that arise from external conditions in the environment, such as money or accessibility concerns. This self-assessment scale asks participants to rank 32 potential barriers to PA on a 7-point Likert scale (ranging from 1 = very unimportant, to 7 = very important). The questionnaire has an acceptable evidence of reliability (Cronbach's alpha = 0.876, Spearman–Brown correlation = 0.754, and Guttman Split-Half correlation = 0.754).
Demographic and clinical parameters
A short sociodemographic form was used to obtain information on age, gender, marital status, work sector, working years, and level of educational. The height and weight of all the participants were measured before administering the questionnaire. The weight and height were measured in light clothing using a weighing scale and stadiometer. The body mass index of the participants was calculated as body weight divided by the square of height (kg/m2).
The data were analyzed using Statistical Package for the Social Sciences (SPSS) 23.0 (SPSS Inc., Chicago, Illinois, USA). Descriptive statistics such as mean, standard deviation (SD), frequency, and percentage were used to summarize the sociodemographic parameters of the participants. In addition, the point prevalence of PA constraints (PACs) among the working population was computed using frequencies and percentages. Shapiro–Wilk test was used to assess the normality of the data and thereafter, Pearson's product moment correlation was used to determine the relationship between PA and PACs. The bivariate association between PA and its constraints was also assessed using the Fisher's exact Chi-square test.
Multicollinearity check was performed to examine the correlation among the PACs and thereafter, binomial logistic regression was used to determine the predictability of the constraints. Sequential method of entering variables was used to assess the contribution of variables in the models. Model improvement with the addition of each predictor variable, percentage accuracy of each model, P value, and standard error and odds ratios (ORs) was used in assessing the models. In addition, model fitness to the data was obtained in the form of Nagalkerke R2. Statistical analysis was set at 5% probability level (P< 0.05) and 95% confidence interval (CI).
| Results|| |
A total of 413 civil servants were enrolled in to the study. However, 12 questionnaires were not returned and therefore, the results for 401 participants were reported. This indicated that there was 2.9% nonresponse rate in the study. The sociodemographic characteristics of the participants are presented in [Table 1] and [Table 2]. The results indicated that out of the 401 participants (mean age = 38.1, SD = 4.02), 138 (34.4%) were sufficiently active and 263 (65.6%) were not physically active [Table 1] and [Table 2]. In addition, the PACs are presented in [Table 3]. The results indicated that lack of friends to participate with (59.6%) and lack of time due to work (55.1%) were reported to have higher prevalence [Table 3].
|Table 1: Demographic characteristics of the participants (n=401) (frequency/percentages)|
Click here to view
|Table 2: Sociodemographic characteristics of the participants (n=401) (descriptive)|
Click here to view
|Table 3: Prevalence of physical activity constraints and their relationship with physical activity (n=401)|
Click here to view
The relationship between PACs and PA is also presented in [Table 2]. The results indicated that lack of friends to participate with, lack of interest, lack of time due to work, lack of knowledge, tiredness after exercise, lack of money, and inadequate facilities were all negatively related with PA (P = 0.000 each).
The collinearity among the constraint variables is presented in [Table 4]. The outcomes indicated that the tolerance of each variable was high (above 0.5). In addition, the variance inflation factor for each variable was also <4, indicating that there was no significant collinearity among the variables. However, lack of skills and lack of any one were collinear.
The influence of the constraint variables on PA is presented in [Table 5]. The significant constraints explained 68.1% of the variability in PA (Nagelkerke R2 = 0.681 [Table 5]). In addition, the results also indicated that five significant predictors have accounted for not participating in PA. The most significant constraints were lack of friends to participate with (OR = 8.360, CI = 6.671–10.468) and lack of time due to work (OR = 8.313, CI = 6.633–10.419), which accounted for not participating in PA by eight times. Lack of interest is more than twice (OR = 2.190, CI = 1.161–4.121) as likely not to participate in PA as having interest. Lack of knowledge accounted for not participating in PA by 36% (OR = 1.360, CI = 1.049–1.764). Inadequate facilities accounted for not participating in PA by 18.1% (OR = 1.181, CI = 1.083–1.276).
| Discussion|| |
This study investigated the influence of LTPACs on PA participation of working-class individuals in a metropolitan Nigerian city. The findings of this study indicated that lack of friends to participate with and lack of time due to work were reported to have a higher prevalence. In addition, lack of interest, lack of knowledge, and inadequate facilities were also reported by the participants as other important constraints. These constraints were also observed by our study to be inversely related to PA. This indicated that as the constraints increased, participation in PA decreased. This also implied that an increase in PA will reduce these constraints. The findings of the present study are in agreement with that of Justine et al. and Funda Kocak, which reported that these constraints were also endemic among the Singaporean and Turkish populations, respectively.
However, in contrast to our findings, Justine et al. reported other factors (too tired, already active enough, and too lazy) that influence participation in PA. This slight difference in PACs observed in our current study and that of Justin et al. might be attributed to the lifestyle of the participants involved in the two studies. In addition, another factor that could have also led to the difference could have been the different scales used to measure PACs in the two studies. For example, Justin et al.'s study used Barriers in PA and Exercise Participation and our study used LCQ. Moreover, even though these questionnaires have significant levels of validity and reliability, they quite differed in the number of items (LCQ has three subcategories and 32 items and barriers to physical activity (BTPA) has two subcategories and 22 items).
The findings of this study also indicated that the constraint variables explained about 68.1% of the variability in PA, leaving the remaining 31.9% to be accounted for by other unknown factors. In addition, the findings also indicated that one of the most significant constraints to PA was lack of friends to participate with, which accounted for not participating in PA by eight times. This outcome is not surprising because it is a basic fact that group exercise participation is a desirable event which motivates and encourages co-participation. Individuals who found associates to compete with and set goals perform better and exercise on a regular basis than those who have no associates. This indicated that civil servants who work in a network of colleagues to compete for excellence and reward may feel lonely if to exercise alone. Therefore, providing exercise clubs and social institutions for workers may promote their participation in PA.
The findings of this study also indicated that lack of time was another significant constraint of PA among the civil servants because it accounted for not participating in PA by eight times just like the lack of friends. Even though majority of the civil servants work between 8.00 a.m. and 4.00 p.m. within five working days in a week, they still reported time as a significant factor that limits their participation in PA. This is understandable to some extent because workers may be tired after working hours and may therefore, need some period of rest and family life. However, it can still be argued that these workers can exercise at night, at the weekends, or even during work breaks to remain healthy. Therefore, workers may require orientation on work–life and leisure-time balance to explore their opportunities for PA participation.
A similar finding was also observed by Pham et al. who found that the three most crucial barriers among Chinese women aged 30–59 years were insufficient time, inadequate skill and resource, and lack of support from family or friends. In another study, Schutzer and Graves also reported lack of time as an important barrier in 17 inactive older adults aged 50–75 years, who rated exercise as the lowest priority in their life. These findings are indicative of the generally low importance given to exercise by elderly populations; some participants even suggested that they view exercise to be a waste of time. Thus, there may be a need for health-care providers to organize campaigns and educational programs that promote exercise in individuals from these age groups so that participation in exercise and long-term adherence are encouraged. Tips on how to achieve effective time management would also help this group of individuals reduce overlaps with sedentary activities and promote participation in exercise.
The findings of this current study also indicated that lack of interest is also another important constraint to LTPA. Just like in any other situation or life endeavor, lack of interest in anything would normally result in a negative outcome and PA is not an exception. According to Chao et al., self-motivation determines participation in structured PA. The authors pointed out that the motivation to exercise may be altered over time, in association with the individual's commitment. Another study by Andajani-Sutjahjo et al. found that the most common barriers to PA in this group were also associated with a lack of motivation, followed by time constraints and cost. Similarly, lack of motivation was determined to be the most important barrier to PA among young undergraduates from a Turkish university in a study by Arzu et al.
The findings of this study also indicated that lack of knowledge is another constraint to LTPA among the studied population. This indicated that if participants are not very well informed about PA, they may likely not engage in it. This is not surprising because PA is something that is very well guided by certain principles and laws which are necessary if proper body homeostasis is to be maintained. In addition, it is also through this state of balance and body decency that we prevent damages and even sudden death in the worst exercise scenarios. To achieve this, a qualified PA specialist is a prerequisite. Moreover, the specialist should also be able to determine the appropriate conditions and fitness levels of the participating individuals to ensure proper PA participation and progression.
The last constraint to LTPA that was found in the current study was inadequate facilities. Although no effort was made to distinguish between institutionalized and noninstitutionalized LTPA facilities in this study, the participants still agreed to a good extent that lack of exercise facilities is a constraint to their participation in PA. This constraint may seem very significant particularly if the target of the participants is to reduce weight. This is because proper weight reduction requires adequate facilities to help burn out fat mass and build up lean body mass. However, on the contrary, this finding was not reported by most published studies,,,, conducted in the developed countries. The reason for this outcome may likely be that Nigeria is currently battling with malnutrition and poverty and therefore participants cannot afford to buy exercise facilities. On the other hand, developed countries are mostly very well informed about the benefits of PA and are therefore rich enough to buy these exercise facilities.
Limitations of the study
This study was limited to working-class individuals in a metropolitan Nigerian city and therefore, may not be generalized to the entire Nigerian working-class individuals. Other limitations of the study include the cross-sectional nature of the study that makes it difficult to draw definitive conclusions of causality on the constraints found. In addition, the use of self-report measures might have also introduced some measurements biases and inaccurate estimates of PA constraints and intensities.
| Conclusion|| |
LTPACs were reported be endemic among working-class individuals. These findings provide information that could be useful for surveillance and public servants' health planning in Nigeria and have implications for identifying the contexts where working-class PA participation could best be promoted. These findings need to be highly considered when health-care policies are being developed to ensure good health and longevity of workers.
In addition, it is also recommended that further studies need to be conducted on diverse Nigerian populations to determine the influence of LTPACs on PA participation and overall health status of working-class individuals with a view to obtaining sufficient findings that may be truthfully generalizable. Furthermore, future studies may also try to use objective measures of PA such as accelerometers or pedometers to provide better estimates of total PA of different intensities.
MK developed this idea and was conceptualized by MSD and AMY. Other co-authors (UUZ and AL) were equally involved in the data collection, manuscript design, and editing.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Sundell J. Resistance training is an effective tool against metabolic and frailty syndromes. Adv Prev Med 2011;1-7.
Beaglehole R, Bonita R, Horton R, Adams C, Alleyne G, Asaria P, et al
. Priority actions for the non-communicable disease crisis. Lancet 2011;377:1438-47.
Guthold R, Ono T, Strong KL, Chatterji S, Morabia A. Worldwide variability in physical inactivity a 51-country survey. Am J Prev Med 2008;34:486-94.
Guilbert JJ. The World Health Report 2002 – Reducing risks, promoting healthy life. Educ Health (Abingdon) 2003;16:230.
Thyfault JP, Krogh-Madsen R. Metabolic disruptions induced by reduced ambulatory activity in free-living humans. J Appl Physiol (1985) 2011;111:1218-24.
Pahor M, Guralnik JM, Ambrosius WT, Blair S, Bonds DE, Church TS, et al
. Effect of structured physical activity on prevention of major mobility disability in older adults: The LIFE study randomized clinical trial. JAMA 2014;311:2387-96.
World Health Organization. WHO | The Global Strategy on Diet, Physical Activity and Health (DPAS). World Health Organization; 2015. Available from: https://www.who.int/nmh/wha/59/dpas/en/
. [Last accessed on 2019 Oct 28].
Gal DL, Santos AC, Barros H. Leisure-time versus full-day energy expenditure: A cross-sectional study of sedentarism in a Portuguese urban population. BMC Public Health 2005;5:16.
Adegoke BO, Oyeyemi AL. Physical inactivity in Nigerian young adults: Prevalence and socio-demographic correlates. J Phys Act Health 2011;8:1135-42.
Dupont WD, Plummer WD Jr., Power and sample size calculations for studies involving linear regression. Control Clin Trials 1998;19:589-601.
Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al
. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003;35:1381-95.
Pollock ML, Wilmore JH. Exercise in Health and Disease: Evaluation and Prescription for Prevention and Rehabilitation. Philadelphia: W. B. Saunders; 1990. p. 760.
Öztürk MA, Yikilmaz A, Sarikol E. Turkish validity and reliability study of the leisure constraint questionnaire. J Educ Learn 2018;8:150.
Justine M, Azizan A, Hassan V, Salleh Z, Manaf H. Barriers to participation in physical activity and exercise among middle-aged and elderly individuals. Singapore Med J 2013;54:581-6.
Pham KL, Harrison GG, Kagawa-Singer M. Perceptions of diet and physical activity among California Hmong adults and youths. Prev Chronic Dis 2007;4:A93.
Schutzer KA, Graves BS. Barriers and motivations to exercise in older adults. Prev Med 2004;39:1056-61.
Chao D, Foy CG, Farmer D. Exercise adherence among older adults: Challenges and strategies. Control Clin Trials 2000;21:212S-7S.
Andajani-Sutjahjo S, Ball K, Warren N, Inglis V, Crawford D. Perceived personal, social and environmental barriers to weight maintenance among young women: A community survey. Int J Behav Nutr Phys Act 2004;1:15.
Arzu D, Tuzun EH, Eker L. Perceived barriers to physical activity in university students. J Sports Sci Med 2006;5:615-20.
Nelson ME, Rejeski WJ, Blair SN, Duncan PW, Judge JO, King AC, et al
. Physical activity and public health in older adults: Recommendation from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007;39:1435-45.
Lam TH, Ho SY, Hedley AJ, Mak KH, Leung GM. Leisure time physical activity and mortality in Hong Kong: Case-control study of all adult deaths in 1998. Ann Epidemiol 2004;14:391-8.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]