The Impact of COVID-19 on Lifestyle and Mental Stress of the Kuwait Population

 

Abstract

The outbreak of Covid-19 which occurred towards the end of 2019, marked the start of both a stressful and uncertain period in the existence of human life in the 21st century. The novel virus spread rapidly with millions being infected and losing their lives, destabilizing the work environment, overwhelmed health care systems and lockdowns. The impacts of the pandemic were not without sudden changes in the lives of people around the world. One such change was the change in lifestyles. The purpose of this study is to assess the impacts of Covid-19 on the lifestyle of the Kuwait population. The study objectives include to evaluate the impact of Covid-19 on eating habits, physical activity and on psychological state of the Kuwait population. The study will adopt a cross-sectional research design with the target population being people living in Aseema, Hawalli, Farwaniya, Almadi, Jahra and Mubarak Al Kabeer Governorates. An online structured questionnaire on Google Forms survey platform will be used to collect data. The collected data will be analyzed using SPPS software v27. The response rate was 90% with the total number of participants being 965. The study findings identified several changes in regard to lifestyle, eating habits and mental health. The study established that 38% of the respondents were partially affected in their businesses/jobs and 17% suffered total loss as a result of the pandemic. In regard to physical activity, 25% and 24.2% indicated they participated in physical exercise most of the time and always respectively during the pandemic compared to 18.5% and 18.3% respectively before the pandemic. On physical exhaustion, 27.3% and 18.4% indicated that they most of the time and always respectively experienced physical exhaustion during the pandemic compared to 21.2% and 13.3% respectively before the pandemic. On emotional exhaustion, 27.4% and 22.3% reported that they experienced emotional exhaustion most of the time and always during the pandemic compared to 19.5% and 15.3% respectively before the pandemic. On stress, 27% and 26.8% indicated they were stressed most of the time and always respectively during the pandemic compared to 21% and 14.2% respectively before the pandemic. On irritability, 28.9% and 23.5% indicated they were irritable most of the time and always respectively during the pandemic compared to 21.9% and 15% respectively before the pandemic. The Multinomial logistic model for altered dietary habits and self-reported weight was statistically significant, χ2 (54) = 78.639, p < 0.005; for altered physical activity and self-reported weight was non-statistically significant, χ2 (27) = 19.876, p > 0.005 and for psychological health and food intake was statistically significant, χ2 (72) = 130.705, p < 0.005. The Wilcoxon test indicated that there was a non-statistically significant difference (Z = -1.889, p >0.05) between eating habits before and during the pandemic. The null hypothesis was rejected; a non-statistically significant difference (Z = -0.698, p >0.05) between the physical activity of the Kuwaiti population before and during the pandemic. The null hypothesis was rejected and a statistically significant difference (Z = 130.705, p < 0.005) between the psychological impacts of the Kuwaiti population and thus the null hypothesis was retained. The study contributes to the better understanding of the impacts of Covid 19 on lifestyle and metal health of the Kuwait population. Similar longitudinal studies should be conducted to provide more information on the effects of the pandemic.

Keywords: Covid 19; eating habits; physical activity; mental health; lifestyle; dietary habits

CHAPTER ONE

Introduction

1.1 Introduction

Towards the end of 2019, a novel severe acute respiratory infection was first reported in Wuhan China. The infection and death rates surged in the first two months and by March 11th, 2020, the World Health Organization (WHO) declared it a pandemic. The corona virus proved to be a challenge to scientists and health workers all over the world since much was still unknown on its mode of transmission with no vaccine or cure in sight for the victims. To date, 238 million infections, 215 million recoveries and 4.8 million death cases have been reported. In Kuwait, 412, 079 infections and 2,454 deaths had been reported as of October 11th, 2021 (Worldometer, 2021). Urgent preventative measures were put in place by governments all over the world to contain the pandemic, which included national lockdowns, curfews, safety health protocols and self-isolations. The Kuwait Authorities imposed restrictions ranging from total and partial lockdowns in Khaitan, Nugra, Farwaniya and Hawalli. In an effort to contain virus from spreading, several measures were put in place which included the banning of public gatherings in restaurants, mosques and malls, employees were given paid holidays and studies postponed in all learning institutions (Gasana & Shehab, 2020). 

The protective measures imposed by various governments throughout the world were not without impact. Millions of people lost their livelihoods, some started working from their homes except for those who offered essential services. The impact of the restrictions including lockdowns and quarantines were evident in people’s lives. Among these impacts is a reduction in physical activities because of the restrictions in sporting and travelling. The staying at home results in signficant lifestyle changes which affect the eating habits of the people and as a consequence of the lockdowns, changes were witnessed in food purchases and dietary habits (di Renzo et al., 2020). The lockdowns resulted in a situation where there is limited supplies of fresh foods and food varieties (Hobbs, 2020). The loss of income made it necessary to seek cheaper foods to supplement their diets. According to Latif and Karaman (2021) the stay-at-home restrictions resulted in boredom and sometimes this boredom was aggravated by economic challenges occasioned by job losses and an uncertain future. According to Moynihan et al., (2015) boredom can result to emotional issues, food cravings and overeating. In addition, emotions such as sadness and fear have been linked to a reduced desire of eating and enjoyment of the foods. 

Hence adjustment changes in lifestyle were an expected outcome of the Covid-19 restrictions. Scanty literature is available on the impacts of Covid-19 on lifestyle prior and during the pandemic. This current study will seek to provide a detailed understanding on how the lifestyle in Kuwait have been affected. Thus, the aim of this study is to assess the impact of Covid-19 on the eating habits, physical activity, and psychological state of the Kuwaiti population in the six Governorates: Aseema, Hawalli, Farwaniya, Almadi, Jahra and Mubarak Al Kabeer.  

1.2 Research Statement

The outbreak of the novel virus, Covid-19 and the preventative measures put in place brought about massive changes in the lives of millions of people. Introducing these sudden changes in people’s lives can lead to negative impacts on their mental states and lifestyle behaviour. The changes in eating habits, physical activities and mental states represent a change in lifestyle behaviour. The curtailed freedom and abstention from work have been associated with increased boredom and stress levels which have consequently led to increased food consumption. Alhusseini and Alqahtani (2020) conducted a retrospective study on the impacts of Covid-19 curfews on eating habits and food intakes focusing on Saudi Arabia. Galali (2021) conducted a cross-sectional study to evaluate the impacts of Covid-19 confinements on eating habits in Iraq Kurdistan. Since there is no such investigation has been conducted in Kuwaiti population, an in-depth appreciation of the pandemic's effects on dietary habits can provide a platform to guide physiological and behavioral measures focusing on individuals and communities. Thus, this study aims at assessing the impacts of the Covid-19 pandemic on eating habits, psychological state and physical activities of the Kuwait population. 

1.3 Rationale of the Study

Pandemics and natural disasters have become a common occurrence in the current world and the outbreak of the novel Corona virus was one such incidence. However, the rapid spread, the huge number of infections, the rising number of deaths with an overwhelmed health system across the world caused fear, panic and distress. Pandemics appear unannounced, catching people in unexpected situations. Consequently, individuals are forced to change their lifestyles and adopt new behaviors instantly. Therefore, it is critical to document the changes in eating habits in such situations with the aim of evaluating the overall wellbeing of the population. This study will therefore provide insights on the Kuwaiti population eating habits, physical activity and mental health during the Covid 19 outbreak and assist in ensuring that safe and healthier eating habits, physical activities and psychological state interventions are embraced during pandemics. 

1.4 Hypothesis

The imposed Covid-19 restrictions such as lockdowns and quarantines disrupted the food supply system consequently leading to food shortages in the markets. Panic purchases and stockpiling of foodstuff were witnessed. Against this developing scenario of non-availability of some foods, people had more time at their disposal to prepare and cook their meals. On the contrary, most people were prone to spend more time on entertainment and would rather snack as opposed to cooking proper meals. This study, therefore, hypothesizes that there are substantial differences in the Kuwaiti people’s eating habits as a consequence of the Covid-19 pandemic's lockdowns. The lockdowns to curtail the pandemic called for social distancing and quarantines resulted in limited freedom of movement. Thus, we further hypothesize that there will be a substantial decrease in the physical activity of Kuwaiti people. Furthermore, because of the restrictions, the participants could be prone to psychological problems. The study thus also hypothesizes an increase in the psychological stress of the Kuwait population during the Covid-19 pandemic. 

1.5 Research Aim and Specific Objectives

1. To evaluate the impact of Covid-19 on eating habits of the Kuwaiti population

2. To evaluate the impacts of Covid-19 on physical activity of the Kuwait Population.

3. To evaluate the impacts of Covid-19 on psychological state of the Kuwait Population.

 

1.6 Research Questions

1. Did the extended lockdown affect eating habits of the Kuwaiti population?

2. Did the lockdown affect physical activity of the Kuwait Population?

3. Did Covid-19 lockdown impact mental health of the people?

4. Was altered dietary habit associated with self-reported body weight? 

5. Was altered physical activity associated with self-reported body weight?

6. Was psychological health associated with food intake?

CHAPTER TWO

Literature Review

 

2.1 Eating Habits

The lockdowns imposed in different countries were not without effect on the lives and livelihoods of millions of people in various ways. According to Gupta et al. (2020) migrant workers in South Asian countries like Nepal, India and Pakistan lost their source of income. According to HLPE (2020) the unfolding pandemic impacted food systems hence threatening access to food through multiple sources. The crisis caused by the pandemic resulted in a dynamic and fluid situation marked by greater levels of uncertainty with many health experts predicting that the situation will persist for up to two years (Scudellari, 2020).

During the pandemic, eating habits underwent drastic changes due to the mandatory isolations and lockdowns. The dynamic interactions sparked by the Covid-containment lockdowns created scenarios for disturbances in food systems, resulting in a marked surge in hunger. According to the most current projections, anywhere from 83 to 132 million more persons would face food insecurity as a primary consequence of the pandemic (FAO, 2020) and this includes millions of individuals in developing countries who rely on importation of food (Torero, 2020). According to Hobb (2020) the lockdowns resulted in limited access to food varieties which in turn led to people turning to processed food that they bought from the supermarkets. Most of these foods have high energy levels but low nutrition values. The fact that most people found themselves working from home or without jobs resulted in cases of boredom and stress (Gao et al., 2020). According to Moynihan et al. (2015) boredom can result in overeating coupled with craving for food with high energy level contents. 

Another aspect of changes in eating habits was the increased awareness of the role played by the body immunity against coronavirus infections in terms of protection and overcoming. According to a study carried out by Enriquez-Martinez et al. (2021) on dietary and lifestyle changes in Ibero-American countries during the Covid-19 pandemic, it was observed that higher proportions of residents of Argentina (28.8%), Brazil (26.4%) and Mexicans (22.4%) adopted healthier eating habits during the pandemic. On the other hand, 21.6% of Mexicans and 19.4% of Peruvians adopted less healthy eating habits. 

The disruptions in the food security systems will result in changes in the eating habits of people. This will be the case since most people will not be able to access different food varieties for their nutritional intake. In addition, the reduced food volumes available will be costly which will also have an impact on people’s eating habits. There is paucity of literature on how the eating habits of the Kuwait population changed through the coronavirus pandemic. Accordingly, within this context, the changes in the eating habits of the Kuwait population should be examined.

2.2 Psychological Impacts 

The COVID-19 pandemic has had a significant emotional impact on many millions of people worldwide, resulting in concerns of steadily increasing psychological health burden (Sinyor et al., 2021). The global responses to the outbreak and spread of Covid-19 including lockdowns, restriction of movements, closure of learning institutions and workplaces resulted in significant repercussions on the wellbeing of human beings (Wang et al., 2020). Despite the success of the methods such as quarantine in containing the spread of the virus, they have not been without adverse psychological impacts. The restriction of movements, separations from families and friends, curtailed freedom and fears of unknown future are some of the factors that can exacerbate adverse psychological impacts. Past pandemic outbreaks have been shown to result in depression, increased stress levels, emotional disturbance, symptoms of post-traumatic stress and irritableness.  

The impact of pandemics has also been associated with psychological problems among health care workers and survivors of the 2003 SARs epidemic.  The health workers reported feeling nervous and fearful for their families and colleagues. In 2012, the outbreak of the Middle East respiratory syndrome Coronavirus (MERS-CoV) was linked to increased public anxiety, fear and psychological stress. Extant literature has shown that various stressors such as prolonged quarantine, confinement, distress, scarcity of information, loss of income, fear of contracting the virus and boredom have aggravated poor mental health (Serafini et al., 2020). 

In a study carried out in China during the pandemic, the statistics revealed that people suffered from mental health challenges, with anxiety (28.8%), depression (16.5%) and stress (8.1%) being the major causes (Wang et al., 2020). The coronavirus pandemic with rapid transmission patterns, absence of clear treatment protocols and vaccination programs led to increased panic, depression and anxiety around the world. There is scarcity of literature on how Kuwaiti population is coping through the coronavirus pandemic, and the extent of its effects on mental health and lifestyle as a whole. Consequently, it is within this context that the extent of pandemic outbreaks impacts on mental health and lifestyle in general should be understood. Therefore, the research aims at examining the impact of the coronavirus pandemic.

 

2.3 Physical Activity

The confinements and social distancing measures that were put in place by most countries around the world were not without adverse effects on the wellbeing of different populations. The stressful and sudden circumstances coupled with extended staying at home can result in radical changes in lifestyle behaviours such as physical inactivity. According to Hall et al. (2021), general concerns have been raised on the adverse health implications due to sedentary behaviours and inactivity. According to WHO (2010), adult persons are considered to be moderately or vigorously physically active if they attain 150 minutes or 75 minutes of physical activity each week respectively. As the pandemic ravaged the world, people were forced to stay indoors hence resulting in modification of personal, interpersonal and environmental factors that have an effect on the general population (Bauman et al., 2012). 

Notwithstanding the recommendations that even during the lockdown and quarantines, people should remain physically active, these unusual confinements could result in two scenarios: first, a reduction of physical activity among the physically active and second, the physically inactive becoming more active (WHO, 2020). According to a study by Castañeda-Babarro et al. (2020) to evaluate changes in physical activity among the Spanish population, it was observed that young people, men and students had decreased their physical activity while increasing sedentary times during the confinement period.

As stated by Kohl et al. (2012), physical inactivity is ranked as the fourth cause of death globally, a situation that was further exacerbated with the imposed confinements during the Covid 19 pandemic (Hall et al., 2021). Studies have shown that reduced physical inactivity and sedentary behaviours are correlated to adverse mental and physical effects among the elderly (Jiménez-Pavón et al., 2020; Rezende et al., 2014). On a global scale, Kuwait ranks first with the highest prevalence of physical inactivity with approximately 65% of the adult population being physically inactive (Salman, et al., 2020). This situation can be aggravated by the pandemic related confinements. Therefore, it against this background that this study will seek to evaluate the impacts of the Covid pandemic on lifestyle of the Kuwait population in terms of physical activity.

 

CHAPTER THREE

Materials and Methods

 

3.1 Study design

A cross-sectional study will be conducted on a sample population drawn from Aseema, Hawalli, Farwaniya, Almadi, Jahra and Mubarak Al Kabeer Governorates using questionnaire prepared to assess eating habits, physical activity and psychological stress factors during the Covid-19 pandemic. 

3.2 Recruitment and Ethics

All the study participants will be made aware about the goal of the research and their informed consent will be sought prior to their inclusion and participation. The relevant approvals from the University and the Ethics Committee of Kuwait’s Ministry of Health will be sought.  

3.3 Study Population

The study’s target population consists of adults residing in Kuwait with an estimated total population of 4,328,550 people. The required sample size will be 385 based on a 95% confidence level and 3% margin of error based on an estimated 80% outcome response. 

The sample size was calculated using the Cochran formula:

 

                   no = Z2pq

                             e2

 

         Where n = Sample Size

                     Z = Z score

                       e = Margin of error

                       P = Standard of deviation

                       q = 1- P

                             no = (1.96)2(0.5) (0.5)

                                             (0.5)2

                     

                                  = 385 Respondents

For known population size

 

                 n = no

                           1+ (no – 1)/N

    

                   = 385

                     1+(385-1)/4,328,550

                   = 385 Respondents

 

3.4 Inclusion and Exclusion Criteria

The inclusion criteria will be a) adults aged between 18 and 65 years, b) Kuwait nationals. Participation in the study will be voluntary. Persons not residing in the six Governorates, and those outside the 18-65 years’ age bracket will be excluded from the study.

3.5 Assessment Methods and Instruments

The main instrument for data collection will be a questionnaire which will be divided into four sections. The first part will deal with socio-demographic aspects of the study participants. The second part will deal with the eating habits prior to and during the Covid-19 period. The third section will cover questions on the physical activities prior to and during the Covid 19 period. The fourth section will cover questions on the psychological state of the participants prior and during the Covid 19 period. An online structured questionnaire on Google Forms survey platform will be used to collect data.  

3.6 Data Collection

Data collection will be achieved through the use of self-administered questionnaires. The questionnaire will be translated to Arabic language and validated. A pilot study involving 38 participants (representing 10% of the study sample size) was conducted prior to the actual study to check for content validity and increase the likelihood of collecting the required data from the participants. The validity of the questionnaire was checked through consultations with the supervisor to confirm whether the questionnaire accurately reflected the research objectives. The reliability of the research instrument was evaluated using the Cronbach’s Alpha Coefficient. The acceptable Cronbach’s Alpha Coefficient value for validation purposes is 0.70 at a significance level of α = 0.05 (Garson, 2013). The Cronbach’s Alpha Coefficient value was 0.747 which is greater than 0.70 as shown in Table 3.1.

Table 3.1: Reliability

 

3.7 Statistical Methods

The Statistical Package for Social Sciences (SPSS), version 27 will be used in analyzing the data collected. Descriptive statistics will be used to analyze the categorical variables. The data will be checked for normality; for normal distributed data, a parametric test such as and for non-normally distributed data, a non-parametric test will be applied. The categorical variables will be compared using a Chi-square. The statistical significance level will be p < 0.05.

CHAPTER FOUR

Results

4.1 Socio-Demographic Characteristics

The respondents were asked to provide social demographic information which included their Governorates, gender, age bracket, marital status, number of children, level of education, employment status and the effect of Covid-19 pandemic on their businesses/jobs.

4.1.1 Governorates

The total number of respondents who participated in the study were 963 drawn from different Governorates: Hawalli, 234 (24.3%), Mubarak Al-Kabeer, 164 (17%), Al Asimah, 160 (16.6%), Al Farwaniyah, 143 (14.8%), Al Ahmadi, 140 (14.5%) and Al-Jahra, 121(12.7%) as shown in Figure 1 below

Figure 4.1: Governorates

Based on the findings, all the Governorates of Kuwait were involved and therefore the study was representative of the Kuwaiti population. 

4.1.2 Gender

Analysis of the study respondents by gender was run, with majority of the respondents, 583 (60.5%) being female and 380 (39.5%) were male as shown in Figure 4.2

Figure 4.2: Gender

From the findings, all the genders were represented in the study and this is significant because it will provide a balanced understanding on the impacts of the pandemic on both genders in relation to lifestyle and mental health. 

4.1.3 Age Bracket

The respondent’s socio-demographic characteristics by age bracket were analyzed as shown in Figure 4.3. 

Figure 4.3: Age Bracket

Majority of the participants, 222 (23.1%) indicated that they were in the 18-25 years age bracket, 204 (21.2%) were in the 26-33 years age bracket, 197 (20.5%) were in 34-41 years bracket, 124 (12.9%) in the 42-49 years bracket, 120 (12.5%) in the 50-57 years bracket and 96 (10%) were in the 58-65 years bracket. The findings show that majority of the participants were young and there was representation from all the age brackets selected for the study.

4.1.4 Marital Status

The marital status of the study respondents was analyzed and the results presented in the form of a pie chart as shown in Figure 4.4

Figure 4.4: Marital Status

 

Majority of the respondents, 426 (44.2%) reported that they were single, 390 (40.5%) were married and 147 (15.3%) were widowed. Hence, there was representation from each category that will provide a broad perspective on the impact of the pandemic on their lifestyle and mental well-being.

4.1.5 Number of Children

The study participants were asked to indicate the number of children they had, and their responses presented in Figure 4.5 below

Figure 4.5: Number of Children

 

Majority of the respondents, 370 (38.4%) reported that they had no children, 194 (20.1%) reported they had 3-4 children, 174 (18.1%) indicated 1-2 children, 117 (12.1%) indicated they had more than 6 children and 108 (11.2%) indicated that they had 5-6 children. 

4.1.6 Education Level

In terms of level of education, the respondents were asked to indicate the education level attained and the findings shown in Figure 4.6 

Figure 4.6: Education Level

A large number of the respondents, 395 (41%) indicated that they had a Bachelor’s degree, followed by 183 respondents (19%) who were Diploma Holders, 142 respondents (14.7%) indicated High School education, 140 respondents (14.5%) were holders of Masters/Doctorate degree, 103 respondents representing 10.7% reported that they had no schooling. The findings imply that majority of the respondents had the basic knowledge to understand the questions presented to them in this study. 

4.1.7 Employment Status

The study sought to establish the respondents’ employment status and the findings are presented in Figure 4.7

Figure 4.7: Employment Status

 

Regarding employment status, 388 (40.3%) indicated they were employed for wages, 223 (23.2%) were students, 100 (10.4%) were retired, 87 (9%) were unemployed, 83 (8.6%) were unable to work due to Covid 19, 82 (8.5%) indicated they were self-employed.

4.1.8 Effect of Covid 19 on Business/Job

The study sought to establish the effect of Covid 19 on business/job. The responses are shown in Figure 4.8

Figure 4.8: Effect of Covid 19 on Business/Job

 

From the findings, 433 (45%) reported that they were not affected, 366 (38%) were partially affected and 164 (17%) reported a total loss in terms of business/job being affected. 

4.2 Eating Habits and Covid 19

The impact of Covid 19 on eating habits was assessed by use of questions on various aspects relating to eating behaviors before and during the pandemic. 

 4.2.1 Consumption of Fast Foods (Pizza, burger, hotdog, pasta)

The study assessed the frequency to which the respondents consumed fast foods before and during the pandemic period. The findings are presented in Figure 4.9 below

Figure 4.9: Consumption of Fast Foods (Pizza, burger, hotdog, pasta)

 

The findings revealed that more respondents, 208 (21.6%) indicated that they never consumed fast foods during the pandemic compared to 155 (16.1%) who did. On the contrary, more respondents, 169 (17.5%) indicated that they always consumed fast foods during the pandemic compared to those who those who did, 126 (13.1%) before the pandemic. There was a decrease in the number of respondents who sometimes, 359 (37.3%) and those who most of the time, 227 (23.6%) who consumed fast foods during the pandemic when compared to the numbers, 406 (42.2%) and 276 (28.7%) before the pandemic respectively. The findings imply that the increase in number of respondents who never consumed fast foods during the pandemic and also the decrease in number of those who sometimes and most of the time did during and before the pandemic may be attributed to health and maintaining/losing weight. However, the case is different considering there was an increase in the number of those who always consumed fast foods during the pandemic in comparison to the period before the pandemic. 

 4.2.2 Inclusion of Fruits & Vegetables in Meals

The study sought to assess the inclusion of fruits and vegetables in meals by the participants. The findings are shown in Figure 4.10 below 

Figure 4.10: Inclusion of Fruits & Vegetables in Meals

 

Based on the findings, more respondents, 155 (16.1%) during the pandemic compared to 148 (15.4%) before the pandemic indicated they never included fruits and vegetables in their meals. The findings also indicate a decrease in the number of respondents 265 (27.5%) and 184 (19.1%) who indicated they included fruits and vegetables in their meals most of the time and always compared to those who did before the pandemic, 273 (28.3%) and 191 (19.8%) respectively. This may be attributed to the lockdown and the reduced fruits and vegetables supply during the pandemic. However, the results also indicated an increase in the number of participants who sometimes included fruits and vegetables in their meals during the pandemic, 359 (37.3%) compared to those who sometimes did before the pandemic, 351 (36.4%). This difference may be attributed to the desire to stay healthy during the pandemic period. 

 4.2.3 Eating Out of Control

The study assessed whether there were differences on the frequency of the respondents eating out of control before and during the pandemic. The findings are shown in Figure 4.11 below

Figure 4.11: Eating Out of Control

 

According to the findings, more respondents, 200 (20.8%) indicated they never ate out of control compared to before the pandemic, 196 (20.4%) which may be attributed to staying healthy or the lack of adequate supply of food during the pandemic. The findings also indicate a decrease in the number of respondents who sometimes ate out of control during the pandemic, 346 (35.9%) compared to 424 (44%) before the pandemic. This could also be attributed to staying healthy or scarcity of food. More respondents 261 (27.1%) and 156 (16.2%) reported that they most of the time and always respectively ate out of control during the pandemic. This is in comparison to the period before the pandemic where, 196 (20.4%) and 147 (15.3%) reported eating out of control most of the time and always respectively. This can also be attributed to the respondents finding themselves at home during the lockdown with little or no work hence engaging in frequent eating.

 4.2.4 Snacking Between Meals

The respondents were asked to indicate whether they had the habit of snacking between meals before and during the pandemic. The findings are shown in Figure 4.12 below

Figure 4.12 Snacking Between Meals

 

According to the findings, more respondents, 276 (28.7%) indicated that they never snacked between meals during the pandemic compared to those who snacked before the pandemic, 176 (18.1%). The frequency in snacking between meals decreased during the pandemic. The number of those who snacked sometimes, 293 (30.4%), most of the time, 217 (22.5%) and always, 177 (18.4%) was lower compared to 372 (38.6%), 226 (23.5%) and 191 (19.8%) in that order before the pandemic. The findings may be attributed to a health consciousness or scarcity of food during the pandemic.

 4.2.5 Skipping Meals

The study further explored the frequency of skipping meals before and during the pandemic period. The findings are shown in Figure 4.13 below

Figure 4.13: Skipping Meals

 

Based on the findings, more respondents, 264 (27.4%) indicated they never skipped meals during the pandemic compared to those who skipped before the pandemic, 216 (22.4%). The findings also revealed there was a decline in numbers in the frequency of those respondents who sometimes, 372 (38.6%) skipped meals during the pandemic compared to the period before the pandemic, 426 (44.2%). More respondents, 192 (19.9%) indicated skipping meals most of the time during the pandemic compared to the pre-pandemic period, 185 (19.2%). The findings also showed a slight decrease in number of those respondents who always skipped meals during the pandemic, 135 (14.0%) compared to before the pandemic, 136 (14.1%). The study further explored the reasons for skipping of meals during the pandemic.  More than half of the respondents, 536 (55.7%) cited no reasons, 154 (16%) cited lack of time, 149 (15.5%) indicated lacking/having less income and 124 (12.9%) indicated lack of food as the reasons for skipping meals during the pandemic. 

 4. 2.6 Changes in Weight

The study sought to establish whether the weight of the respondents had changed during the pandemic. The findings are shown in Figure 4.14 below

Figure 4.14: Changes in Weight

 

From the analysis of the responses, 330 respondents representing 34.3% of the respondents indicated that they had gained weight, 293 (30.4%) reported that they had lost weight, 175 (18.2%) reported no changes in their respective weights while 165 (17.1%) indicated that they were not sure. The gain in weight could be attributed to a sedentary life or the various stressors that are associated with lockdown periods.

 4.2.7 Altered Dietary Habits and Self-Reported Weight

The study sought to assess whether the altered dietary habits were associated with changes in self-reported weight. A Multinomial logistic regression was run and the results are presented in Table 4.1, 4.2 and 4.3 below

Table 4.1: Model Fit-Altered Dietary Habits and Self-Reported Weight

Table 4.2: Goodness Fit Altered Dietary Habits

 

Table 4.3: Pseudo R Altered

 

The multinomial logistic regression was performed to ascertain the association between altered dietary habits and self-reported weight. The multiple regression model was statistically significant, χ2 (54) = 78.639, p < 0.005. The altered dietary habits will be able to explain 8.4% (Nagelkerke, R2), of the variance in the self-reported weight.

 4.3 Physical Activity and Covid 19

The impact of Covid 19 on physical activity was assessed by use of questions on various aspects relating to physical activity, exercise and time spent on screen both work and entertainment related before and during the pandemic. 

 4.3.1 Physical Activity

The study sought to establish the frequency of physical activity by the study respondents before and during the Covid 19 pandemic. The findings are shown in Figure 4.15 below

Figure 4.15: Physical Activity

 

Figure 4.15 shows that 223 (23.2%) of the respondents reported that they never engaged in physical exercise before the outbreak of the pandemic and the number increased to 261 (27.1%) during the pandemic.  Also 331 respondents representing 34.4% reported that they sometimes engaged in physical activity before the pandemic compared to 283 (29.4%) who sometimes engaged in physical activity during the pandemic. The findings also revealed that there was an increase in the number of respondents, 241 (25.0%) and 178 (18.5%) who most of the time and always engaged in physical activity during the pandemic. The increase in physical activity can be explained by the desire of the participants to remain fit during the lockdown.

 4.3.1 Motivation for Engaging in Physical Exercise

The study sought to establish the respondents’ motivation for engaging in physical exercise. The reasons included health, maintain/lose weight, releasing stress, wasting time and other reasons. The findings are shown in Figure 4.16 below

 

Figure 4.16: Motivation for Engaging in Physical Exercise

 

According to the findings, majority, 309 (32.1%) indicated that the main motivation for engaging in physical exercise was to maintain/lose weight, 256 (26.6%) indicated health reasons, 191 (19.8%) reported they engaged in exercise as a way of releasing stress, 108 (11.2%) cited other reasons while 99 (10.3%) indicated that they engaged in exercise as a way of wasting time. The findings therefore imply that majority of the respondents, 756 (78.5%) were motivated to engage in exercise because they were conscious of their general wellbeing (health, maintain/losing weight and releasing stress) during the pandemic. 

 4.3.2 Altered Physical Activity and Self-Reported Weight

The study sought to assess whether the altered physical habits were associated with changes in self-reported weight. A multinomial logistic regression analysis was run to investigate the association between altered physical activity and self-reported weight. The results are presented in Table 4.4, 4.5 and 4.6 below

Table 4.4: Model Fit-Altered Physical Activity and Self-Reported Weight

 

Table 4.5: Goodness Fit- Altered Physical Activity and Self-Reported Weight

 

Table 4.6: Pseudo R- Goodness Fit- Altered Physical Activity and Self-Reported Weight

 

According to the results, the model was non-statistically significant, χ2 (27) = 19.876, p > 0.005 suggesting that it could not distinguish between the altered physical activity and the self-reported weight.

 4.3.4 Work-related Hours Spent on Screen

The study sought to establish the number of work-related hours that the respondents spent on the screen before and during the Covid 19 pandemic. The findings are shown in Figure 4.17 below

Figure 4.17: Work-related Hours Spent on Screen

 

The findings indicated that before the pandemic, 277 representing 28.8% reported that they spent less than 1 hour on screen, 243 (25.2%) indicated they spent 1-3 hours, 197 (20.5%) spent 4-6 hours on screen, 124 (12.9%) spent 7-9 hours and 122 (12.7%) spent more than 9 hours on screen on work-related issues. During the pandemic, 212 (22%) of the respondents indicated that the work-related hours they spent on the screen was less than 1 hour, 182 (18.9%) spent 1-3 hours, 212 (22%) spent 4-6 hours, 172 (17.9%) spent 7-9 hours which was work-related on the screen. From the findings, it is evident that most of the respondents increasingly spent more work-related hours on the screen during the pandemic compared to before the pandemic. The spending of longer hours on the screen because of work related issues is due to the direction that people should work from their homes in an effort to contain the spread of the pandemic.  

4.3.5 Entertainment-related Hours Spent on Screen

The study sought to establish the number of entertainment hours that the respondents spent on the screen before and during the Covid 19 pandemic. The findings are shown in Figure 4.18 below

Figure 4.18: Entertainment-related Hours Spent on Screen

 

The findings indicated that before the pandemic, 218 representing 22.6% reported that they spent less than 1 hour on screen, 261 (27.1%) indicated they spent 1-3 hours, 215 (22.3%) spent 4-6 hours on screen, 132 (13.7%) spent 7-9 hours and 137 (14.2%) spent more than 9 hours on screen on entertainment. During the pandemic, 169 (17.5%) of the respondents indicated that the entertainment hours they spent on the screen was less than 1 hour, 187 (19.4%) spent 1-3 hours, 203 (21.1%) spent 4-6 hours, 224 (23.3%) spent 7-9 hours which was entertainment related on the screen. From the findings, it is evident that most of the respondents increasingly spent more hours on the screen being entertained during the pandemic compared to the period before the pandemic. Spending more time on entertainment became necessary because most people found themselves indoors with little or no work and limited company because of the restrictions. 

4.4 Mental Health

The study sought to assess the impact of Covid 19 on mental health of the participants. Experiences of physical and mental exhaustion, stress and irritability before and during the pandemic were examined. 

 4.4.1 Experience of Physical Exhaustion Before and During Covid 19 Pandemic

The respondents were asked to share their experiences in regard to physical exhaustion before and during the Covid 19 pandemic. The findings are shown in Figure 4.19 below

Figure 4.19: Experience of Physical Exhaustion Before and During Covid 19 Pandemic

 

From the findings, before the pandemic, majority of the respondents, 424 (44%) indicated that they sometimes felt physically exhausted, 207 (21.2%) reported never being physically exhausted, 204 (21.2%) indicated most of the time and 128 (13.3%) indicated that they always felt physically exhausted before the pandemic. As to whether the respondents experienced physical exhaustion during the pandemic, 286 (29.7%) indicated sometimes, 263 (27.3%) indicated most of the time, 237 (24.6%) reported that they never experienced physical exhaustion while 177 (18.4%) indicated they always experienced physical exhaustion during the pandemic period.  A closer examination of the findings revealed that more respondents indicated that they experienced physical exhaustion most of the time and always during the pandemic compared to the period before the pandemic. These findings therefore imply the Kuwaiti population from which the study respondents were drawn from were impacted by the pandemic which was manifested in form of physical exhaustion.  

 4.4.2 Experience of Emotional Exhaustion Before and During Covid 19 Pandemic

The study sought to assess the respondents’ emotional experiences before and during the Covid 19 pandemic. The findings are shown in Figure 4.20 below

Figure 4.20: Experience of Emotional Exhaustion Before and During Covid 19 Pandemic

 

According to the findings, before the pandemic, majority of the respondents, 383 (39.8%) reported experiencing emotional exhaustion sometimes, 245 (25.4%) reported that they never experienced emotional exhaustion in the period prior to the pandemic, 188 (19.5%) indicated that most of the time and 147 (15.3%) reported that they always experienced emotional exhaustion before the pandemic. As to whether the respondents experienced emotional exhaustion during the pandemic, 264 (27.4%) participants reported that most of the time they felt emotionally exhausted, 255 (26.5%) indicated sometimes, 229 (23.8%) indicated they did not have the experience and 215 (22.3%) respondents indicated that they always experienced emotional exhaustion during the pandemic. Similar to the experience of physical exhaustion, the findings revealed that most of the study respondents indicated that they experienced emotional exhaustion most of the time and always during the pandemic compared to the period before the outbreak of the Covid 19 pandemic.  

 4.4.3 Experience of Stress Before and During Covid 19 Pandemic

The respondents were asked to indicate whether they experienced stress before and during the Covid 19 pandemic. The findings are shown in Figure 4.21 below

 

Figure 4.21: Experience of Stress Before and During Covid 19 Pandemic

 

Based on the findings, before the pandemic, 422 (43.8%) reported to have experienced stress sometimes, 202 (21%) indicated they never experienced stress most of the time, 202 (21%) indicated they never experienced stress and 137 (14.2%) reported that they always experienced stress before the pandemic outbreak. The study further examined the stress experiences of the respondents during the Covid 19 period. The respondents, 284 (29.5%) reported that they experienced stress sometimes, 260 (27%) indicated most of the time, 258 (26.8%) experienced stress always and 161 (16.7%) stated that they never experienced stress during the pandemic. Analyzing the stress experiences during the pandemic, from the results above, it is evident that more study participants indicated that they experienced stress always and most of the time during the pandemic compared to the number of participants who experienced stress always and most of the time before the outbreak of the Covid 19 pandemic. These findings imply that stress was a challenge during the pandemic when compared to the period before the pandemic.

 4.4.4 Experience of Irritability Before and During Covid 19 Pandemic

Another aspect of mental health that was examined is the experience of irritability among the study respondents before and during the Covid 19 pandemic. The findings are presented in Figure 4.22 below

 

Figure 4.22: Experience of Irritability Before and During Covid 19 Pandemic

 

From the analysis of the respondents’ responses, before the pandemic, majority of the respondents, 431 (44.8%) reported that they sometimes experienced irritability, 211 (21.9%) most of the time, 177 (18.4%) never experienced irritability and 144 (15%) indicated they always experienced irritability before the pandemic. On the other hand, during the pandemic period, 288 (29.9%) reported experiencing irritability sometimes, 278 (28.9%) indicated most of the time, 226 (23.5%) indicated always and 171 (17.8%) reported that they never experienced irritability during the pandemic period. A further analysis of the responses indicated that most of the respondents reported experiencing irritability most of the time and always during the pandemic. 

 4.4.5 Psychological Health and Food Intake

The study sought to assess whether the altered psychological impact was associated with food intake. A multinomial logistic regression analysis was run to investigate the association between altered psychological health and food intake. The results are presented in Table 4.7, 4.8 and 4.9 below.

Table 4.7: Model Fit- Psychological Health and Food Intake

 

Table 4.8: Goodness Fit- Psychological Health and Food Intake

 

Table 4.9: Pseudo R - Psychological Health and Food Intake

 

The multinomial logistic regression was performed to ascertain the association between psychological health and food intake. The multinomial logistic regression model was statistically significant, χ2 (72) = 130.705, p < 0.005. The psychological health will be able to explain 13.6% (Nagelkerke, R2), of the variance in the food intake.

4.5 Hypothesis Testing

This study was based on three hypotheses. First, that there are substantial differences in the Kuwaiti people’s eating habits as a consequence of the Covid-19 pandemic's lockdowns. Second, it was hypothesized that there will be a substantial decrease in the physical activity of Kuwaiti people.  Third, the study hypothesized of an increase in the psychological impacts of the Kuwait population during the Covid-19 pandemic. 

 4.5.1 Hypothesis One

H0:  There is no significant difference between the eating habits of the Kuwaiti population before and during the Covid 19 pandemic period.

The Wilcoxon signed rank test will be used to test the null hypothesis that the median of the differences between the eating habits of the Kuwaiti population before the pandemic and the eating habits during the pandemic is equal to zero. The results are presented in Table 4.10 and 4.11 below.

Table 4.10: Hypothesis One -Hypothesis Test Summary

Table 4.11: Hypothesis One - Related-Samples Wilcoxon Signed Rank Test Summary

 

A Wilcoxon signed rank test revealed that there was a non-significant difference (Z = -1.889, p >0.05) between the eating habits of the Kuwaiti population before the pandemic and the eating habits during the pandemic. The median score for the eating habits before the pandemic was 2.4000 which was equal to the median for the eating habits during the pandemic, 2.4000. Therefore, the null hypothesis was retained.

 4.5.2 Hypothesis Two

H0:  There is no significant difference between the physical activity of the Kuwaiti population before and during the Covid 19 pandemic period.

The Wilcoxon signed rank test will be used to test the null hypothesis that the median of the differences between the physical activity of the Kuwaiti population before the pandemic and the physical activity during the pandemic is equal to zero. The results are presented in Table 4.12 and 4.13 below.

Table 4.12: Hypothesis Two - Hypothesis Test Summary

 

Table 4.13: Hypothesis Two - Related-Samples Wilcoxon Signed Rank Test Summary

 

A Wilcoxon signed rank test revealed that there was a non-significant difference (Z = -0.698, p >0.05) between the physical activity of the Kuwaiti population before the pandemic and the physical activity during the pandemic. The median score for the physical activity before the pandemic was 2.0000 which was equal to the median for the physical activity during the pandemic, 2.0000. Therefore, the null hypothesis was retained.

 4.5.3 Hypothesis Three

H0:  There is no significant difference between the psychological impact on the Kuwaiti population before and during the Covid 19 pandemic period.

The Wilcoxon signed rank test will be used to test the null hypothesis that the median of the differences between the psychological impact on the Kuwaiti population before the pandemic and the psychological impact during the pandemic is equal to zero. The results are presented in Table 4.14 and 4.15 below

Table 4. 14: Hypothesis Three - Hypothesis Test Summary

 

Table 4. 15: Hypothesis Three - Related-Samples Wilcoxon Signed Rank Test Summary

 

A Wilcoxon signed rank test revealed that there was a significant difference (Z = 9.097, p <0.05) between the psychological impacts on the Kuwaiti population before the pandemic and the psychological impacts during the pandemic. The median score for the psychological impacts on before the pandemic was 2.2500 compared to the median for the psychological impacts during the pandemic, 2.5000. Therefore, the null hypothesis was rejected.

CHAPTER FIVE

5.1 Discussion

This research investigated the impacts of Covid 19 on the eating habits, physical activity and mental health of the Kuwait population. The study respondents were drawn from the six Governorates namely Hawalli, Mubarak Al-Kabeer, Al Asimah, Al Farwaniyah, Al Ahmadi and Al-Jahra. On a global scale, the Covid 19 pandemic affected populations in terms of dietary habits, physical and mental health as well as the social life. The study found that 38% of the respondents’ businesses and jobs were partially affected by the pandemic and an additional 17% of the respondents reported that they suffered total loss. This is significant because of the after effects that will be witnessed in terms of food intake, mental health and lifestyle in general. A comparison of the two periods before and during the pandemic revealed a decline in the number of people who sometimes and most of the time consumed fast foods such as pizza, burgers and hotdogs. 

Remarkably, there was an increase in the number of people who never consumed fast foods during the pandemic period. This may be attributed to people becoming more health conscious. These findings concur with studies done earlier which showed that the pandemic had forced people to be more aware of their eating habits. In a study conducted by ben Hassen et al. (2020) in Qatar and Husain & Ashkanani (2020) in Kuwait, it was shown that more people had reduced unhealthy foods from their diets. On the issue of the inclusion of fruits and vegetables in meals, the study provided mixed findings. There was an increase in the number of respondents who indicated they never included fruits and vegetables in their diets. The availability of these foods was affected during the lockdowns. Janssen et al. (2021) concurs with this fact arguing that there was a tendency of people reducing their intake of fresh foods especially fruits and vegetables. According to Bracale and Vaccaro (2020), the decrease in the consumption of fruits and vegetables was attributed to a reduction in the frequency of shopping during the lockdown period.

On the other hand, the increased consumption of fruits and vegetables can be attributed to the desire to stay healthy during the pandemic. Brookie et al. (2018) argues that the consumption of fruits and vegetables has been linked to improved mental health, a much-needed aspect during the lockdown period. On the issue of eating out of control, the study results revealed that majority of the respondents ate out of control, a situation that can be attributed to the respondents finding themselves at home during the lockdown with no work to keep them busy. Cancello et al. (2020) in a study on the determining factors of lifestyle changes during the pandemic showed that 53% of the respondents in that study reported to engaging in overeating during the lockdown. The findings of this study showed that there was a marked decrease in snacking between meals which the study attributed to a health consciousness or scarcity of snacks during lockdown. These findings differ from a study conducted by Sidor and Rzymke (2020) where the participants reported increased snacking and gaining of weight. The study findings revealed that most respondents reported skipping meals during the pandemic. In a study by Cheikh Ismail et al. (2020) it was shown that the skipping of meals was majorly because of lack of time before the outbreak and lack of appetite during the pandemic. In this present study, more than half the respondents indicated they had no reasons while 16% stated they skipped meals because of lack of time. 

In assessing the changes in weight, a slight majority of the respondents, 34.3% indicated they had gained weight while 30.4% indicated they had lost weight. Gaining of weight can be because of a sedentary lifestyle, lack of exercise and overeating. Loss of weight can be due to lack of enough food and stress during the pandemic. A study by Khubchandani et al (2022) on weight gains by the American adults during the pandemic showed that 48% of the respondents in that study had gained weight while 18% had lost weight. One of the lifestyle aspects on a global scale that were affected by the pandemic is physical activity. The findings of this study revealed that there is a general increase in the participation in physical activity by the study respondents. On the contrary, a study by Puccinelli et al. (2021) revealed that the physical activity level of the participants was significantly reduced because of social distancing and lockdown restrictions. 

Engaging in physical exercise during lockdowns and social distancing can be a great challenge with many people fearing contracting the virus. On physical exercise, 25% of the respondents reported that they engaged in physical activity most of the time during the pandemic compared to 24.2% before the pandemic. Another 18.5% reported always engaging in physical exercise during the pandemic compared to 18.3% before the pandemic.  In this study, 26.6% of the respondents cited staying healthy, 32.1% indicated maintaining/losing weight while 19.6% indicated they engaged in physical exercise to release stress. According to Lindsey (2020), the immune system plays a major role in fighting of infections. A person who is physically active has an improved immunity, decreased inflammations and decreases the possibility of contracting viral infections of the respiratory system. However, Lindsay (2020) points out that physical exercise should be done with moderation since extreme exercise is known to temporarily lower down the immune system.

The study also assessed the number of hours spent by the respondents in front of the screen, work-related and for entertainment purposes. The findings revealed that the respondents spent longer hours ranging from 4 hours to over 9 hours on their screens during the pandemic compared to the period before the pandemic. This is because more people were working from home as a consequence of the lockdown and social distancing restrictions. According to Kanekar and Sharma (2020) the Covid 19 restrictions forced people to turn to digital platforms as a means of maintaining social connections. 

Psychological impacts were among the challenges faced by the global population because of the pandemic outbreak, and the Kuwait population was no exception. The findings of the study revealed that more people experienced physical exhaustion during the pandemic compared to the period preceding the pandemic outbreak. On physical exhaustion, 27.3% and 18.4% indicated that they most of the time and always respectively experienced physical exhaustion during the pandemic. This is in comparison to 21.2% and 13.3% who indicated that most of the time and always respectively experiencing physical exhaustion before the pandemic. According to Mollica and Fricchione (2021) more health workers experienced physical and mental exhaustion as they handled the pandemic. According to Australian Psychological Society (2020), the unprecedented and far-reaching disruptions in people’ s normal activities and routines, imminent threats of death and infections can manifest a combination of emotional, mental and physical symptoms. In addition, lockdown related fatigues can be manifested in the form of physical exhaustion, sadness, anxieties among others. The findings of this study reveal that respondents drawn from the Kuwait population were impacted by impacted by the Covid 19 pandemic. 

Similarly, the study findings showed that the majority of the respondents reported experiencing emotional exhaustion. On emotional exhaustion, 27.4% and 22.3% reported that they experienced emotional exhaustion most of the time and always during the pandemic compared to 19.5% and 15.3% respectively before the pandemic. According to Hossain (2021), emotional exhaustion is manifested through feelings of exhaustion and energy depletion. The total lockdown and curfews could have resulted to the respondents feeling emotionally exhausted. Another aspect of psychological impacts of Covid 19 was stress. Based on the study findings, majority of the respondents indicated experiencing stress always and most of the time. On stress, 27% and 26.8% indicated they were stressed most of the time and always respectively during the pandemic compared to 21% and 14.2% respectively before the pandemic. According to Brooks et al. (2020) individuals who are quarantined and placed in isolation were a higher risk of experiencing stress, anxiety, confusion and anger. It then follows that the conditions created by the pandemic which included loss of work, loss of income, the lockdowns and the fear of infection could have contributed to the increased stress levels. 

Similarly, the respondents reported experiencing irritability most of the time and always. The findings revealed that irritability levels were high with 28.9% and 23.5% indicating they were irritable most of the time and always respectively during the pandemic compared to 21.9% and 15% respectively before the pandemic. In a study on self-reported impacts of the Covid 19 pandemic, Grondal et al. (2021), increased irritability levels were linked to severe impacts of the pandemic on finances, work, education and family life. Those individuals who experience more suffering from the impacts of Covid 19 were more exposed to experiencing irritable behaviors. Therefore, the impact of the pandemic might have contributed to the increased irritability among the respondents. 

Multinomial logistic regression was conducted to answer the research questions on: the association between altered dietary habits and self-reported weight; altered physical activity and self-reported weight and psychological health and food intake.  The Multinomial logistic model for altered dietary habits and self-reported weight was statistically significant, χ2 (54) = 78.639, p < 0.005. The Multinomial logistic model for altered physical activity and self-reported weight was non-statistically significant, χ2 (27) = 19.876, p > 0.005. The multinomial logistic regression model for psychological health and food intake was statistically significant, χ2 (72) = 130.705, p < 0.005.

The study further tested the hypotheses that guided the study. The study hypothesized that there was no significant difference between the eating habits of the Kuwait population before and during the pandemic. A Wilcoxon test was used to test the hypotheses. The Wilcoxon test indicated that there was a non-statistically significant difference (Z = -1.889, p >0.05) between eating habits before and during the pandemic. The null hypothesis was rejected.

The second hypothesis hypothesized that there was no significant difference between the physical activity of the Kuwaiti population before and during the pandemic period. The Wilcoxon test indicated a non-statistically significant difference (Z = -0.698, p >0.05) between the physical activity of the Kuwaiti population before and during the pandemic. The null hypothesis was rejected.

The third hypothesis stated that there was a non-significant difference between the psychological impacts of the Kuwait population before and during the pandemic period. A Wilcoxon test indicated a statistically significant difference (Z = 130.705, p < 0.005) between the psychological impacts of the Kuwaiti population and thus the null hypothesis was retained.

5.2 Strengths and Limitations

Based on the restrictions albeit the strict deadline of the study, this method of data collection allowed many respondents to be reached online which would have been difficult. In terms of cost, the online platform provided the researcher will an option of collecting a lot of data from the six Governorates at a very minimal cost. The study was not without limitations. First, the cross-sectional nature of this research makes the study outcomes to be intermittent hence they are not an actual representation of the actual changes during the six months’ total lockdown in Kuwait. In addition, based on its cross-sectional nature, the research is not allowed to ascribe causation and thus the study results should be cautiously interpreted. Third, the study was conducted after more than one and half years after the lockdown, therefore, the responses are reported. This may not present the real situation as the respondents will try to recall which will affect the accuracy of the information provided. Fourth, another limitation is on the self-reported weight, where the respondents were required to provide information on the weight changes, first, post pandemic and the weight changes were not physically measured hence providing approximations.  Fifth, the study was also limited in the sense that it was conducted online, thereby presenting a limitation to those who were not able to access the survey platform. Lastly, the collected data is also subject to biasness of self-reporting.

CHAPTER SIX

6.1 Conclusion

In conclusion, the research findings of this study revealed various impacts as a consequence of the Covid 19 pandemic outbreak. This research demonstrated that the pandemic resulted in the partial and total loss of jobs and businesses a matter that will consequentially have an effect on the lifestyle of the Kuwait population. On eating habits there was an increase in the number of people who never consumed fast foods during the pandemic. Similarly, the number of respondents who never included fruits and vegetables increased which can be attributed to their scarcity during the lockdown period. However, the frequency of the conclusion of vegetables and fruits in another segment of the study population increased. The findings also revealed a remarkable increase in the level of physical activity among the population during the pandemic period. Regarding the psychological impacts of Covid 19 on the Kuwait population under the study, it was established that mental and physical exhaustion, stress and irritability significantly increased among the population under study. Therefore, overall, the psychological impacts had the greatest influence on the Kuwaiti population. 

6.2 Recommendations

The study focused on the Kuwaiti population drawn from the six Governorates. However, this study was conducted online which has its own limitations. The study therefore recommends that with the ease of the Covid 19 restrictions, a further study should be conducted to include a larger population where there will be interaction with the respondents hence providing an opportunity to generate more information on the impacts of the pandemic on the Kuwaiti population. In addition, longitudinal studies should be carried out to provide deeper insights on the long-term impacts of the pandemic on dietary behavior, physical activity and psychological impacts on the Kuwaiti population. In conducting a physical study, the study will provide an opportunity for the actual measurement of parameters such as weight and height for the calculation of Body Mass Index (BMI). This will present an opportunity to collect real data on the weight changes.

 

References

Alhusseini, N., & Alqahtani, A. (2020). COVID-19 pandemic’s impact on eating habits in Saudi Arabia. Journal of Public Health Research, 9(3). https://doi.org/10.4081/jphr.2020.1868

Australian Psychological Society (2020).  Managing lockdown fatigue. The Australian Psychological Society Limited. https://www.psychology.org.au/getmedia/74e7a437-997c-4eea-a49c-30726ce94cf0/20APS-IS-COVID-19-Public-Lockdown-fatigue.pdf. Accessed April 25, 2022.

Bauman, A. E., Reis, R. S., Sallis, J. F., Wells, J. C., Loos, R. J., & Martin, B. W. (2012). Correlates of physical activity: why are some people physically active and others not? The Lancet, 380(9838), 258–271. https://doi.org/10.1016/s0140-6736(12)60735-1

ben Hassen, T., el Bilali, H., & Allahyari, M. S. (2020). Impact of COVID-19 on Food Behavior and Consumption in Qatar. Sustainability, 12(17), 6973. https://doi.org/10.3390/su12176973

Bracale, R., & Vaccaro, C. M. (2020). Changes in food choice following restrictive measures due to Covid-19. Nutrition, Metabolism and Cardiovascular Diseases, 30(9), 1423–1426. https://doi.org/10.1016/j.numecd.2020.05.027

Brookie, K. L., Best, G. I., & Conner, T. S. (2018). Intake of Raw Fruits and Vegetables Is Associated With Better Mental Health Than Intake of Processed Fruits and Vegetables. Frontiers in Psychology, 9. https://doi.org/10.3389/fpsyg.2018.00487

Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., & Rubin, G. J. (2020). The Psychological Impact of Quarantine and How to Reduce It: Rapid Review of the Evidence. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3532534

Cancello, R., Soranna, D., Zambra, G., Zambon, A., & Invitti, C. (2020). Determinants of the Lifestyle Changes during COVID-19 Pandemic in the Residents of Northern Italy. International Journal of Environmental Research and Public Health, 17(17), 6287. https://doi.org/10.3390/ijerph17176287

Castañeda-Babarro, A., Arbillaga-Etxarri, A., Gutiérrez-Santamaría, B., & Coca, A. (2020). Physical Activity Change during COVID-19 Confinement. International Journal of Environmental Research and Public Health, 17(18), 6878. https://doi.org/10.3390/ijerph17186878

Cheikh Ismail, L., Osaili, T. M., Mohamad, M. N., al Marzouqi, A., Jarrar, A. H., Zampelas, A., . . . al Dhaheri, A. S. (2020). Assessment of eating habits and lifestyle during the coronavirus 2019 pandemic in the Middle East and North Africa region: a cross-sectional study. British Journal of Nutrition, 126(5), 757–766. https://doi.org/10.1017/s0007114520004547

-considerations.pdf. Published March 18, 2020.

COVID Live Update: 239,609,701 Cases and 4,884,422 Deaths from the Coronavirus - Worldometer. (2021, October 12). Retrieved October 13, 2021, from https://www.worldometers.info/coronavirus/?utm_campaign=homeAdvegas1?

di Renzo, L., Gualtieri, P., Pivari, F., Soldati, L., Attinà, A., Cinelli, G., . . . de Lorenzo, A. (2020). Eating habits and lifestyle changes during COVID-19 lockdown: an Italian survey. Journal of Translational Medicine, 18(1). https://doi.org/10.1186/s12967-020-02399-5

Enriquez-Martinez, O. G., Martins, M. C. T., Pereira, T. S. S., Pacheco, S. O. S., Pacheco, F. J., Lopez, K. V., . . . Molina, M. C. B. (2021). Diet and Lifestyle Changes During the COVID-19 Pandemic in Ibero-American Countries: Argentina, Brazil, Mexico, Peru, and 

Galali, Y. (2021). The impact of COVID‐19 confinement on the eating habits and lifestyle changes: A cross sectional study. Food Science & Nutrition, 9(4), 2105–2113. https://doi.org/10.1002/fsn3.2179

Gao, J., Zheng, P., Jia, Y., Chen, H., Mao, Y., Chen, S., . . . Dai, J. (2020). Mental Health Problems and Social Media Exposure During COVID-19 Outbreak. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3541120

Gasana, J., & Shehab, M. (2020). Coronavirus Disease (COVID 19): Handling Challenges in Kuwait. Sci, 2(2), 40. https://doi.org/10.3390/sci2020040

Gröndal, M., Ask, K., Luke, T. J., & Winblad, S. (2021). Self-reported impact of the COVID-19 pandemic, affective responding, and subjective well-being: A Swedish survey. PLOS ONE, 16(10), e0258778. https://doi.org/10.1371/journal.pone.0258778

Hall, G., Laddu, D. R., Phillips, S. A., Lavie, C. J., & Arena, R. (2021). A tale of two pandemics: How will COVID-19 and global trends in physical inactivity and sedentary behavior affect one another? Progress in Cardiovascular Diseases, 64, 108–110. https://doi.org/10.1016/j.pcad.2020.04.005

Hobbs, J. E. (2020). Food supply chains during the COVID‐19 pandemic. Canadian Journal of Agricultural Economics/Revue Canadienne d’agroeconomie, 68(2), 171–176. https://doi.org/10.1111/cjag.12237

Hossain, M. G. (2021). Psychological Distress among Bangladeshi Adults during the Covid-19 Pandemic: A Cross-sectional Study. JOURNAL OF LIFE SCIENCES, 13(1–2). https://doi.org/10.31901/24566306.2021/13.1-2.257

Huang, S. M., Chen, K. N., Chen, Y. P., Hong, W. S., & Chen, M. J. (2010). Immunomodulatory properties of the milk whey products obtained by enzymatic and microbial hydrolysis. International Journal of Food Science & Technology, 45(5), 1061–1067. https://doi.org/10.1111/j.1365-2621.2010.02239.x

Husain, W., & Ashkanani, F. (2020). Does COVID-19 change dietary habits and lifestyle behaviours in Kuwait: a community-based cross-sectional study. Environmental Health and Preventive Medicine, 25(1). https://doi.org/10.1186/s12199-020-00901-5

Janssen, M., Chang, B. P. I., Hristov, H., Pravst, I., Profeta, A., & Millard, J. (2021). Changes in Food Consumption During the COVID-19 Pandemic: Analysis of Consumer Survey Data From the First Lockdown Period in Denmark, Germany, and Slovenia. Frontiers in Nutrition, 8. https://doi.org/10.3389/fnut.2021.635859

Jiménez-Pavón, D., Carbonell-Baeza, A., & Lavie, C. J. (2020). Physical exercise as therapy to fight against the mental and physical consequences of COVID-19 quarantine: Special focus in older people. Progress in Cardiovascular Diseases, 63(3), 386–388. https://doi.org/10.1016/j.pcad.2020.03.009

Kanekar, A., & Sharma, M. (2020). COVID-19 and Mental Well-Being: Guidance on the Application of Behavioral and Positive Well-Being Strategies. Healthcare, 8(3), 336. https://doi.org/10.3390/healthcare8030336

Khubchandani, J., Price, J. H., Sharma, S., Wiblishauser, M. J., & Webb, F. J. (2022). COVID-19 pandemic and weight gain in American adults: A nationwide population-based study. Diabetes &amp; Metabolic Syndrome: Clinical Research &amp; Reviews, 16(1), 102392. https://doi.org/10.1016/j.dsx.2022.102392

Kohl, H. W., Craig, C. L., Lambert, E. V., Inoue, S., Alkandari, J. R., Leetongin, G., & Kahlmeier, S. (2012). The pandemic of physical inactivity: global action for public health. The Lancet, 380(9838), 294–305. https://doi.org/10.1016/s0140-6736(12)60898-8

Latif, H., & Karaman, E. (2021). COVID-19: Boredom in the Family. The Family Journal, 29(2), 147–152. https://doi.org/10.1177/1066480720986496

Lindsay, A. R. (2020, May 5). Physical activity is a strong benefit during COVID-19. Retrieved from https://www.unr.edu/nevada-today/news/2020/physical-activity-during-covid

Maares, M., & Haase, H. (2016). Zinc and immunity: An essential interrelation. Archives of Biochemistry and Biophysics, 611, 58–65. https://doi.org/10.1016/j.abb.2016.03.022

Mollica, R. F., & Fricchione, G. L. (2021). Mental and physical exhaustion of health-care practitioners. The Lancet, 398(10318), 2243–2244. https://doi.org/10.1016/s0140-6736(21)02663-5

Moynihan, A. B., Tilburg, W. A. P. V., Igou, E. R., Wisman, A., Donnelly, A. E., & Mulcaire, J. B. (2015). Eaten up by boredom: consuming food to escape awareness of the bored self. Frontiers in Psychology, 6. https://doi.org/10.3389/fpsyg.2015.00369

Puccinelli, P. J., da Costa, T. S., Seffrin, A., de Lira, C. A. B., Vancini, R. L., Nikolaidis, P. T., . . . Andrade, M. S. (2021). Reduced level of physical activity during COVID-19 pandemic is associated with depression and anxiety levels: an internet-based survey. BMC Public Health, 21(1). https://doi.org/10.1186/s12889-021-10470-z

Rezende, L. F. M. D., Rey-López, J. P., Matsudo, V. K. R., & Luiz, O. D. C. (2014). Sedentary behavior and health outcomes among older adults: a systematic review. BMC Public Health, 14(1). https://doi.org/10.1186/1471-2458-14-333

Salman, A., Tolma, E., Chun, S., Sigodo, K. O., & Al-Hunayan, A. (2020). Health Promotion Programs to Reduce Noncommunicable Diseases: A Call for Action in Kuwait. Healthcare, 8(3), 251. https://doi.org/10.3390/healthcare8030251

Scudellari, M. (2020). How the pandemic might play out in 2021 and beyond. Nature, 584(7819), 22–25. https://doi.org/10.1038/d41586-020-02278-5

Serafini, G., Parmigiani, B., Amerio, A., Aguglia, A., Sher, L., & Amore, M. (2020). The psychological impact of COVID-19 on the mental health in the general population. QJM: An International Journal of Medicine, 113(8), 531–537. https://doi.org/10.1093/qjmed/hcaa201

Sidor, A., & Rzymski, P. (2020). Dietary Choices and Habits during COVID-19 Lockdown: Experience from Poland. Nutrients, 12(6), 1657. https://doi.org/10.3390/nu12061657

Sinyor, M., Knipe, D., Borges, G., Ueda, M., Pirkis, J., Phillips, M. R., & Gunnell, D. (2021). Suicide Risk and Prevention During the COVID-19 Pandemic: One Year On. Archives of Suicide Research, 1–6. https://doi.org/10.1080/13811118.2021.1955784

Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., Ho, C. S., & Ho, R. C. (2020). Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China. International Journal of Environmental Research and Public Health, 17(5), 1729. https://doi.org/10.3390/ijerph17051729

Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., McIntyre, R. S., . . . Ho, C. (2020). A longitudinal study on the mental health of general population during the COVID-19 epidemic in China. Brain, Behavior, and Immunity, 87, 40–48. https://doi.org/10.1016/j.bbi.2020.04.028

WHO (2010). Global Recommendations on Physical Activity for Health; WHO: Geneva, Switzerland.

WHO (2020). Stay Physically Active during Self Quarantine. Available online: https://www.euro.who.int/en/healthtopics/health-emergencies/coronavirus-covid-19/technical-guidance/stay-physically-active-during-selfquarantine (accessed on 3rd November 2021).

World Health Organization (WHO). Mental Health and Psychosocial Considerations During the COVID-19 Outbreak.https://www.who.int/docs/default-source/coronaviruse/mentalhealth

World Health Organization. WHO timeline - COVID-19. 2020. https://www.who.int/news-room/detail/27-04-2020-who-timeline---covid-19. Accessed April 27, 2020.

World Health Organization. Novel Coronavirus (2019-nCoV): Situation Report−10 (2020). Available online at: https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200130-sitrep-10-ncov.pdf?sfvrsn=d0b2e480_2 (accessed October 12, 2021).