Literature DB >> 34334866

Evaluation of health-related quality of life in physically active and physically inactive students during the COVID-19 pandemic in Iran.

Hamid Reza Sadeghipour1, Abdossaleh Zar1, Ali Pakizeh2, Roger Ramsbottom3.   

Abstract

Covid-19 is an acute respiratory syndrome that can effect on lifestyles. The aim of the present study was to compare the health-related quality of life (HRQoL), physical component summary (PCS) and mental component summary (MCS) scores in physically active (PA) and physically inactive (PI) during the Covid-19 pandemic. Three hundred and twenty-six (182 women; 144 men) studying at the Persian Gulf University participated in the study. The HRQoL Questionnaire (SF-12) was used to collect information. Significant differences in HRQoL score, MCS score and PCS score were observed between physically active and inactive men and women, as well as between physically active and inactive men, and finally between physically active and inactive women (P < 0.01). Data from the present study suggests higher levels of physical activity, even during social restrictions imposed by the current global pandemic, results in significantly greater scores for HRQoL.
© 2021 Published by Elsevier Ltd.

Entities:  

Keywords:  Covid-19; Health-related quality of life (HRQoL); Lifestyles Iran

Year:  2021        PMID: 34334866      PMCID: PMC8302848          DOI: 10.1016/j.cities.2021.103367

Source DB:  PubMed          Journal:  Cities        ISSN: 0264-2751


Introduction

Covid-19, or coronavirus, is an acute respiratory syndrome that spread from China, resulting in a global pandemic (Zhu et al., 2020). Although quarantine may seem reasonable in order to maintain population health, it is considered an unpleasant experience that can lead to a variety of mental health problems, including depression, anxiety, fear, loneliness, and dissatisfaction and can also change lifestyles and significantly affect the quality of life (Bao et al., 2020). A recent study in China showed that female students in initial phase of the Covid-19 symptoms, experienced higher levels of stress and anxiety (Wang et al., 2020). In addition, Pietrobelli et al. (2020) reported that students' lifestyles changed significantly during a Covid-19 quarantine period; namely levels of physical activity showed a significant decrease. ‘Quality of Life’ is a multidimensional concept that is influenced by physical health, personal development, psychological states, level of independence and social relationships and is based on individual perception (Ghafari et al., 2013). Quality of life metrics have been reported for different sections of society (e.g. elderly men and women, solders and smokers), furthermore studies have shown that exercise can improve the quality of life in these populations (Ahmadi et al., 2020; Zar et al., 2018; Zar et al., 2019). Exercise and physical activity are recommended as therapy in both healthy and unhealthy populations (Vina et al., 2012). An increase in ‘Machine’ or ‘Technological’ lifestyles has significantly reduced levels of physical activity (Rind et al., 2014). Individual (home) quarantine due to Covid-19 and decreased levels of physical activity lead to changes in lifestyle across densely populated urban cities. Decreased levels of physical activity is another lifestyle factor (like obesity) which acts to increase the chance of early mortality from Covid-19. Therefore, it is vital that we understand the effect of Covid-19 on quality of life and promote ameliorating strategies globally. Decreased levels of physical activity affects everyone from the person engaging in recreational activities to the elite athlete. Currently the impact of home quarantine during the Covid-19 pandemic, specifically comparing physically active versus inactive individuals has not been investigated, here we seek to address this issue.

Materials and methods

The present study was a cross-sectional post-event study conducted at the Persian Gulf University. Three hundred and twenty-six students volunteered to participate in the present study. Participants were divided into two groups physically active (PA) and physically inactive (PI) (182 women: 80 PA and 102 PI, and 144 men: 68 PA and 76 PI). Individuals who participated in at least 3 sessions (45 min per session) of physical activity or exercise per week were included in the “physically active” group and Physically inactive people – will have to be those people reporting less than 1 sessions per week of PA were included in the inactive group (participants complete a self-report questionnaire) (Zar et al., 2019). Data were collected by The Health Quality of Life Questionnaire (SF-12) and the Demographic Characteristics Questionnaire. The health-related quality of life questionnaire (HRQoL) includes a mental component (MCS) and physical component summary (PCS). Mental Component Summary (MCS) includes Social Function, Vitality, Mental Health and Emotional problems scales. The Physical Component Summary (PCS) includes Body Pain, understanding of one's life, Physical Function and Physical health scales (Zar et al., 2019). It should be noted that in the quality of life and related scales, a higher score denotes a ‘better’ status. This study was performed in accordance with the principles described in the Declaration of Helsinki (2013) and approved by the Research Ethics Committee of Jahrom University of Medical Sciences (ethics code: IR.JUMS.REC.1399.044). The Kalmogorov-Smirnov test was used to evaluate the normality of the distribution of findings and independent t-tests were used to evaluate the research findings. Also SPSS 18 software was used with a significance level of α = 0.05 which was considered significantly different.

Results

The results showed that there was no significant difference in HRQoL score (p = 0.312), MCS score (p = 0.307) and PCS score (p = 0.58) between men and women. Because the HRQoL score for men (20.10 ± 3.44) and women (19.62 ± 3.09) was less than 24; both groups demonstrate poor HRQoL (Table 1 ; Fig. 1A).
Table 1

Comparisons of quality of life and its subscales in men and women subjects.

VariableMenWomenp value
Mental component summary12.53 ± 2.2512.21 ± 2.280.307
 Social function3.26 ± 1.383.19 ± 1.460.718
 Vitality2.75 ± 0.942.57 ± 1.150.199
 Mental health5.32 ± 1.115.23 ± 1.070.601
 Emotional problems1.19 ± 0.861.20 ± 0.940.925
Physical component summary7.56 ± 1.987.41 ± 1.840.587
 Body pain1.11 ± 0.961.38 ± 0.890.004
 Understanding of your life1.88 ± 0.991.65 ± 1.170.126
 Physical function3.06 ± 1.142.78 ± 1.190.087
 Physical health1.65 ± 0.831.59 ± 0.750.585
Health-related quality of life20.10 ± 3.4419.62 ± 3.090.312

Data are presented as the mean ± standard error of the mean.

P-value ≤0.05 considered significant.

Fig. 1

Comparisons of quality of life in different groups. Part A: Comparison between Men and Women; Part B: Comparison between Physically Active and Physically Inactive (men + women); Part C: Comparison between Physically Active Men and Physically Inactive Men; Part D: Comparison between Physically Active Women and Physically Inactive Women. Data are presented as the mean ± standard error of the mean. * P-value ≤0.05 considered significant. - - -: The dotted line indicates a score of 24 that Scores higher than t indicate a desirable quality of life; PA: Physically Active; PI: Physically Inactive; PAM: Physically Active Men; PIW: Physically Inactive Women; PAM: Physically Active Men; PIM: Physically Inactive Men.

Comparisons of quality of life and its subscales in men and women subjects. Data are presented as the mean ± standard error of the mean. P-value ≤0.05 considered significant. Comparisons of quality of life in different groups. Part A: Comparison between Men and Women; Part B: Comparison between Physically Active and Physically Inactive (men + women); Part C: Comparison between Physically Active Men and Physically Inactive Men; Part D: Comparison between Physically Active Women and Physically Inactive Women. Data are presented as the mean ± standard error of the mean. * P-value ≤0.05 considered significant. - - -: The dotted line indicates a score of 24 that Scores higher than t indicate a desirable quality of life; PA: Physically Active; PI: Physically Inactive; PAM: Physically Active Men; PIW: Physically Inactive Women; PAM: Physically Active Men; PIM: Physically Inactive Men. There was a significant difference between physically active and inactive men and women in HRQoL score (p = 0.001), MCS score (p = 0.002), PCS score (p = 0.001), social function score (p = 0.014), mental health score (p = 0.019), emotional problems score (p = 0.009), body pain score (p = 0.024), physical function score (p = 0.001) and physical health score (p = 0.001). Total score of HRQoL of physically inactive (18.49 ± 3.46) and active (20.96 ± 2.47) was less than 24, so both groups possess poor HRQoL (Table 2 ; Fig. 1B).
Table 2

Comparisons of quality of life and its subscales in physically active and physically inactive subjects.

VariablePhysically activePhysically inactivep Value
Mental component summaryTotal12.77 ± 1.9511.82 ± 2.490.002
Men13.48 ± 1.8011.68 ± 2.960.001
Women12.44 ± 1.9411.92 ± 2.630.192
 Social FunctionTotal3.44 ± 1.282.97 ± 1.540.014
Men3.40 ± 1.113.14 ± 1.580.404
Women3.46 ± 1.362.85 ± 1.520.014
 VitalityTotal2.54 ± 1.052.74 ± 1.110.181
Men2.91 ± 0.792.60 ± 1.040.144
Women2.36 ± 1.122.82 ± 1.150.019
 Mental HealthTotal5.43 ± 0.985.08 ± 1.160.019
Men5.62 ± 0.985.04 ± 1.160.021
Women5.34 ± 0.975.11 ± 1.170.214
 Emotional problemsTotal1.35 ± 0.801.02 ± 0.990.009
Men1.54 ± 0.690.87 ± 0.890.001
Women1.26 ± 0.841.12 ± 1.050.397
Physical component summaryTotal8.18 ± 1.636.66 ± 1.840.001
Men8.56 ± 1.596.68 ± 1.870.001
Women8.01 ± 1.636.66 ± 1.830.001
 Body painTotal1.37 ± 1.011.07 ± 0.950.024
Men1.05 ± 1.171.05 ± 0.870.491
Women1.53 ± 0.901.20 ± 0.860.031
 Understanding of your lifeTotal1.69 ± 1.161.77 ± 1.060.592
Men2.05 ± 1.051.73 ± 0.920.157
Women1.53 ± 1.181.80 ± 1.140.160
 Physical functionTotal3.31 ± 0.892.39 ± 1.280.001
Men3.48 ± 0.762.68 ± 1.290.001
Women3.24 ± 0.932.20 ± 1.240.001
 Physical healthTotal1.76 ± 0.631.41 ± 0.870.001
Men1.97 ± 0.641.36 ± 0.880.001
Women1.70 ± 0.621.44 ± 0.870.046
Health-related quality of lifeTotal20.96 ± 2.4718.49 ± 3.460.001
Men22.05 ± 2.2618.34 ± 3.360.001
Women20.45 ± 2.4118.58 ± 3.540.001

Data are presented as the mean ± standard error of the mean.

P-value ≤0.05 considered significant.

Comparisons of quality of life and its subscales in physically active and physically inactive subjects. Data are presented as the mean ± standard error of the mean. P-value ≤0.05 considered significant. There was a significant difference between physically active and inactive male in HRQoL score (p = 0.001), MCS score (p = 0.001), PCS score (p = 0.001) the mental health score (p = 0.021), emotional problems score (p = 0.001), physical function score (p = 0.001), and physical health score (p = 0.001). because the HRQoL score of physically inactive (18.34 ± 3.36) and active (22.05 ± 2.26) men was less than 24, both groups possessed ‘poor’ HRQoL (Table 2; Fig. 1C). There was a significant difference between physically active and inactive women in HRQoL score (p = 0.001), PCS score (p = 0.001), social function score (p = 0.014), vitality score (p = 0.019), and body pain score (p = 0.031), physical function score (p = 0.001) and physical health score (p = 0.046). because the total score of HRQoL of physically active (20.45 ± 2.41) and inactive (18.58 ± 3.54) women was less than 24, both groups demonstrate ‘poor’ HRQoL (Table 2; Fig. 1D).

Discussion

The results of the present study showed that, the quality of life scores of both men and women were less than 24; both groups demonstrating ‘poor’ quality of life. There were no significant differences between the sexes in the scores of total mental and physical health. These results indicated that regardless of physical activity, Covid-19 and its resulting quarantine has led to a significant decline in quality of life in both male and female students. In previous studies in non-coronary conditions, 54.31% of students had a score above 24 and a good quality of life, and a significant relationship was reported between quality of life and health literacy (Khaleghi et al., 2019). Haleem et al. (2020) stated that Covid-19 widely affected the lives of different communities in important areas of health, economy and society, all of which led to a decrease in their quality of life (Haleem et al., 2020). Our results indicate that quarantine significantly affected quality of life in this young population. It seems that, due to the prevalence and mortality as a direct result of Covid-19 pandemic, extensive damage to people's mental health is not unexpected. In a study of more than 7000 students in China, more than 44.9% of them were reported anxiety, mainly due to concerns about the impact of the Covid-19 virus on their future employment status (Cao et al., 2020). In the present study, the quality of life in the general scale of mental health and the general scale of physical health in physically active students was higher compared with inactive students but quality of life scores of both groups were similar. It seems that fear, anxiety and quarantine restrictions have made their overall quality of life score very unsatisfactory. Zhang et al. (2020) reported that an increased prevalence of Covid-19 significantly increased negative emotions. Contrastingly maintaining regular physical activity helped to relieve negative emotions (Zhang et al., 2020). Under the current Covid-19 pandemic being physically active has the potential to improve quality of life. We suggest that the World Health Organization and the Health Services of the different nation states promote physical activity via educational content and other means. For example delivering exercise interventions via telehealth increases levels of support for ‘at risk’ populations (Bland et al., 2020). In our study, physically active female students scored higher only in the physical dimension. Adibelli and Sümen (2020) stated that during the Covid-19 period, more than half of the research samples (children aged 7–13) were overweight and inclined to sleep more (Adibelli & Sümen, 2020). In the present study, any change in body mass as a result of quarantine was not evaluated, but a lack of significant difference in mental health scores between physically active and inactive women may be due to a concern about a weight gain (due to quarantine restrictions). Moreover, it has been shown that lower scores and lowered physical activity among girls is a particular concern - because they show even lower levels of physical activity compared with men outside of school and university (Bann et al., 2019) and this issue can have a direct impact on the overall mental health and quality of life of women.

Conclusion

During the quarantine period of Covid-19, the quality of life in physically active students was higher and physically active men scored higher for both mental and physical health compared with their inactive peers The results of the present study, supports previous research, showing that physical activity during quarantine (imposed by Covid-19) can be an important way to promote mental and physical health. However, this study should be conducted in a wider range of socio-demographic individuals affected by the pandemic. Finally, depending on the length and strictness of containment policies, the type and method of effective intervention in improving the level of physical activity and quality of life of people involved in the Covid-19 epidemic must be carefully designed and promoted.

Confirmation of ethical compliance

The authors of this article, while observing the rules and provisions of ethical regulations, including the Helsinki Declaration and obtaining informed consent from the participants and full assurance of the confidentiality of the collected information and complete freedom to participate in the study as well as leaving the study, conducted the present study. The study approved by the Research Ethics Committee of the Jhrom University of Medical Science (ethics code: IR.JUMS.REC.1399.044).

Funding information

The authors have not received any founds.

Availability of data

The data that support the findings of this study are available from the corresponding author, [author initials], upon reasonable request.

CRediT authorship contribution statement

HS: Conceptualization, Methodology, Investigation, Writing - original draft, Writing - editing, Visualization. A Z: Conceptualization, Methodology, Investigation, Writing - original draft, Writing - editing, Visualization, Project administration, Formal analysis Funding acquisition. AP: Conceptualization, Methodology. RR: Writing- Original draft preparation, Writing – editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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