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Eating Habits and Lifestyle during COVID-19 Lockdown in the United Arab Emirates: A Cross-Sectional Study

Department of Clinical Nutrition and Dietetics, College of Health Sciences, University of Sharjah, Sharjah 27272, UAE
Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford OX1 2JD, UK
Research Institute of Medical and Health Sciences (RIMHS), University of Sharjah, Sharjah 27272, UAE
Department of Nutrition and Food Technology, Faculty of Agriculture, Jordan University of Science and Technology, Irbid 22110, Jordan
Department of Nutrition and Health, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain 15551, UAE
Department of Health Services Administration, College of Health Sciences, University of Sharjah, Sharjah 27272, UAE
Department of Food Science and Human Nutrition, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece
College of Natural and Health Sciences, Zayed University, Dubai 19282, UAE
Nutrition Section, Ministry of Health and Prevention, Dubai 1853, UAE
Institute for Health and Sport, Victoria University, Melbourne 14428, Australia
Author to whom correspondence should be addressed.
Nutrients 2020, 12(11), 3314;
Received: 5 October 2020 / Revised: 24 October 2020 / Accepted: 27 October 2020 / Published: 29 October 2020
(This article belongs to the Special Issue Mediterranean Diet and Metabolic Diseases)


The coronavirus disease is still spreading in the United Arab Emirates (UAE) with subsequent lockdowns and social distancing measures being enforced by the government. The purpose of this study was to assess the effect of the lockdown on eating habits and lifestyle behaviors among residents of the UAE. A cross-sectional study among adults in the UAE was conducted using an online questionnaire between April and May 2020. A total of 1012 subjects participated in the study. During the pandemic, 31% reported weight gain and 72.2% had less than eight cups of water per day. Furthermore, the dietary habits of the participants were distanced from the Mediterranean diet principles and closer to “unhealthy” dietary patterns. Moreover, 38.5% did not engage in physical activity and 36.2% spent over five hours per day on screens for entertainment. A significantly higher percentage of participants reported physical exhaustion, emotional exhaustion, irritability, and tension “all the time” during the pandemic compared to before the pandemic (p < 0.001). Sleep disturbances were prevalent among 60.8% of the participants during the pandemic. Although lockdowns are an important safety measure to protect public health, results indicate that they might cause a variety of lifestyle changes, physical inactivity, and psychological problems among adults in the UAE.

1. Introduction

The novel coronavirus disease (COVID-19) pandemic has added various challenges and changes to human life worldwide, causing an unprecedented impact on human health, lifestyle, and social life, and has affected the local and international economy [1]. Following its first emergence in December 2019, in the city of Wuhan in China and its subsequent outbreak throughout the world in the following months it was characterized as a global pandemic by the World Health Organization (WHO) on 11 March 2020 [2]. On 28 September 2020, over 32.7 million confirmed cases of novel coronavirus and around 991,000 deaths worldwide were reported by the WHO [3]. In the United Arab Emirates (UAE) a total of 90,618 confirmed cases were reported in the same period [3]. In response to the rapid spread of the disease governments all around the world had to implement strict measures such as complete or partial lockdowns, isolation, quarantine and social distancing [4,5].
In the UAE, as a response to this outbreak, the government had to act quickly to contain the spread of the virus. Parallel with measures taken by most countries worldwide, complete and partial lockdowns were implemented, non-essential public places were closed, telework and distance learning was initiated, delivery services like delivering drugs to chronically ill patients were provided and sanitizing cities during night as part of the National Disinfection Program was implemented [6]. According to the World Bank, the total population of the UAE in 2019 was about 9.8 million [7]. However, nearly 75% of the population is concentrated in Abu Dhabi and Dubai as they have more than 3 million residents each. Moreover, the UAE is a multicultural country with expatriates and immigrants accounting for about 88% of the population [8]. Thus, this study provides unique opportunities to examine the impact of COVID-19 on lifestyle behaviors in the UAE.
There is no doubt that during times of confinement, food accessibility and availability may be affected, which in turn affects diet quality [9]. The imposed possibility of reduced income, job losses and anxiety about an uncertain future might lead the population to cut down expenditure including their expenses for food, making them go for more palatable, affordable and possibly unhealthy options [10]. Diet can affect many areas, but most importantly it can affect immune status [11] in the short term, a time during which heightened activity should be at its best. Available literature, however, has shown trends toward unfavorable dietary behaviors during the lockdown such as increased caloric intake, more frequent snacking, reduced consumption of fresh fruits and vegetable, and weight gain [10,12]. Traditionally, the diet in the UAE consists of fruits (such as dates), vegetables and fish and it is characterized by a high-fiber content and low fat and cholesterol content [13]; foods that characterize the Mediterranean diet and that are rich in vitamins A, D, C, folate, E and B-complex, required for an optimal immune response. Moreover, a large portion of UAE residents are from Arab countries in which fruits, vegetables and olive oils constitute key components of their diets. Therefore, it would be of interest to assess any shift in dietary habits during the COVID-19 situation.
Levels of physical activity were also negatively affected during quarantine [10,14,15]. Factors like complete lockdowns, closure of sport facilities and parks, and overall movement restrictions have reduced the ability to engage in physical activity. This was accompanied with an increase in sedentary behaviors related to quarantine, including distance learning and telework [16]. A meta-analysis on physical activity prior to COVID-19 pandemic revealed that a quarter of the population residing in the UAE had a sedentary lifestyle and were not engaged in any type of physical activity [17].
The emergence of infectious diseases reaching pandemic levels induces a huge psychological impact and distressed mental health symptoms in the population with anxiety being the most common as was shown following the Middle East respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [18,19]. Anxiety and uncertainty along with food insecurity and restricted healthcare access might also impact individuals with eating disorders and obesity [20,21]. Multiple factors influence the extent of psychological impact of outbreaks including unknown means of virus transmission, future unpredictability, media misinformation, and quarantine [19,22]. Consequently, such stressful events strongly aggravate disturbed sleep patterns and insomnia, poor eating habits along with decreased levels of physical activity and increased sedentary behaviors [23,24].
This study aimed to investigate the effect of quarantine on eating habits, physical activity, stress and sleep behaviors among adult UAE residents using a formulated online survey. A comparison of lifestyle and dietary behaviors before and during the lockdown was also conducted to allow better understanding of the effects of Covid-19-induced confinement policies on lifestyle changes among the UAE residents. Dietary intake was examined during the lockdown to evaluate potential risks of nutritional inadequacies.

2. Materials and Methods

2.1. Study Design and Participants

To assess the effect of the coronavirus pandemic and the effect of lockdown on eating habits and lifestyle of residents of the UAE, a population-based (cross-sectional) study was conducted in the UAE between April and May 2020. Although cross-sectional studies are rarely used to compare before and after, since there is no temporal sequence, it is the best design to use when previous information is not available, in order to draw inferences. Considering the sudden outbreak of COVID-19, this study aimed to evaluate the effect of the pandemic by examining highly modifiable factors including lifestyle and dietary.
The target population included all adults ≥18 years and from all seven emirates, residing in UAE. These were invited to participate in an online survey using snowball sampling methods in order to guarantee a large-scale distribution and recruitment of participants. A total of 1012 participants (24.1% males) were included in this study.
A web link was retrieved for the survey and was distributed using e-mail invitations and social media platforms, e.g., LinkedIn™ (Mountain View, CA, USA), Facebook™ (Cambridge, MA, USA), and WhatsApp™ (Menlo Park, CA, USA). The first page of the survey included an information sheet and consent form indicating the participants’ right to withdraw at any time. Consenting participants then chose their desired language and proceeded to complete and submit their responses. All data were collected anonymously with no indication of any personal information and participants were not rewarded. The study protocol was approved by the Research Ethics Committee at the University of Sharjah (REC-20-04-25-02) and the Social Sciences Research Ethics Committee at United Arab of Emirates University (ERS_2020_6106).

2.2. Survey Questionnaire

A multicomponent, self-administrated online survey was designed using Google document forms in English, Arabic, and French. This survey contained questions on dietary and lifestyle habits prior to and during the COVID-19 confinement. A researcher from the College of Health Sciences at the University of Sharjah (UAE) and a researcher from the College of Food and Agriculture at United Arab Emirates University (UAE) developed the draft of the survey in English. Questions were developed based on a previous national nutrition survey [25], the International Physical Activity Questionnaire Short Form (IPAQ-SF) [26] and the Copenhagen Psychosocial Questionnaire (COPSOQ-II) [27]. It was then translated and culturally adapted following an internationally accepted methodology [28,29]. The survey was later reviewed by the research team and was pilot tested with 25 people from the UAE. Following the pilot-testing, slight modifications were made to the survey. The online survey included 37 questions and was divided into seven sections: (1) socio-demographic background (10 questions): gender, age, marital status, number of children the participant has, education level, employment status, whether they were working or studying from home during the lockdown, weight change, perceived health status, and emirate of residence; (2) sources of information (2 questions): where do they obtain health and nutrition related information; (3) eating habits (8 questions): meal type, meal frequency, eating breakfast, skipping meals, reasons for skipping meals, water intake, and food frequency of specific foods; (4) shopping habits (5 questions): preparing a grocery list, stocking up on foods, using online shopping, reading food labels, and cleaning/sanitizing groceries; (5) physical activity (4 questions): exercising frequency, household chores frequency, computer time for work or study, and screen time for entertainment; (6) stress and irritability (4 questions): physical exhaustion, emotional exhaustion, irritability, and tension; (7) sleep (4 questions) sleep duration, sleep quality, sleep disturbances, and energy level. The full version of the questionnaire is available as a Supplementary File.
Questions on eating habits, physical activity, stress and irritability, and sleep were asked twice, once regarding the period before the pandemic (pre-COVID-19) and the other regarding the period during lockdown (during COVID-19).

2.2.1. Dietary Assessment

A total of 10 specific dietary questions were included in the questionnaire to assess frequency of specific food groups only during COVID-19 pandemic [30]. Food groups were included based on usual intakes of the population residing in the United Arab Emirates [31,32]. These characterize the basic Mediterranean type diet but also include food high in sugar and fat, observed to be recently trending in the UAE [25]. Specifically, the questionnaire included the following food groups: fruit, vegetables, milk and milk products, meat and meat products (red meat, chicken and fish), grains (bread, rice pasta), sweets, sugar sweetened beverages (ssbs), coffee and tea, and energy drinks. Response options included never; 1–4 times per week; once a day; 2–3 times a day; 4 or more times a day. Internal consistency of the food added in the food frequency questionnaire was evaluated using Cronbach’s alpha for this section of the questionnaire specifically, to decrease false high internal consistency, since this test is affected by the length of the test [33]. A value of 0.81 was derived showing strong inter-relatedness of the food items, ensuring validity (Cronbach’s alpha = 0.81, from a scale of 0 to 1.0; small cohort error variance of 0.34).

2.2.2. Physical Activity Assessment

A modified version of the International Physical Activity Questionnaire Short Form (IPAQ-SF) was used to assess frequency of physical activity pre-COVID-19 and during COVID-19 among surveyed participants [26]. Participants were asked to indicate “how many days per week did they engage in moderate to vigorous physical activity”, and “how many days per week did they engage in household chores”. They were also asked to indicate “how many hours per day did they spend on the computer for work or study”, and “how many hours per day did they spend on screens for fun and entertainment”.

2.2.3. Stress, Irritability and Sleep Assessment

Questions on stress and sleep were adopted from the second version of the Copenhagen Psychosocial Questionnaire (COPSOQ-II) with modifications [27]. Regarding stress and irritability, participants were asked to provide the frequency of experiencing physical exhaustion; emotional exhaustion; irritability; and tension. The same questions were asked once regarding the period before the pandemic (pre-COVID-19) and once during the pandemic. The response options included all the time; a small part of the time; part of the time; a large part of the time; all the time.
With regard to sleep, participants were asked if they experienced sleep disturbances including sleeping badly and restlessly; having difficulty to go to sleep; waking up too early and not being able to get back to sleep; waking up several times and found it difficult to get back to sleep; or none of the options. The questionnaire also included the following questions: “number of sleeping hours per night”, “rating sleep quality”, and “describing energy level during the day”. The repose options for rating sleep quality were very good; good; poor. The repose options for describing energy level were energized; neutral; lazy. Questions were repeated twice, once about the period pre-COVID-19 and the second regarding the period during COVID-19.

2.3. Statistical Analysis

Categorical variables are presented as counts and percentages. The chi square test was used to determine the association between categorical variables, and the McNemar test was used to investigate the difference between categorical variables before and during the COVID-19 pandemic. A sub-analysis was also performed for weight and specific behavioral variables’ differences between groups. Specifically, data were stratified (i) by sex, (ii) by age group (18–35 and ≥36 years), and (iii) level of education. Principal component analysis (PCA) was used to group related dietary practice into components [34]. The correlation of each food group with the underlying component was calculated with component loadings. In this analysis, values >0.3 were considered as having an effect in the component construction. Each participant was given a score based on the sum of the component loadings of each food group. The identified components were rotated (varimax rotation) to retrieve orthogonal, uncorrelated factors, decreasing variance errors. The Kaiser–Meyer–Olkin (KMO) measure of sample adequacy was used to assess PCA adequacy. Results were significant for p value < 0.05. Statistical analysis was performed using Statistical Package for the Social Sciences (SPSS) version 26.0 (IBM, Chicago, IL, USA).

3. Results

3.1. Demographic Characteristics

The survey was completed by 1012 participants. The sample distribution from different emirates was representative of the population distribution in the UAE. With the highest number of participants residing in Abu Dhabi and Dubai. More specifically, local coverage spreads over all regions in the UAE: 33.9% of participants live in the capital Abu Dhabi, 32.5% in Dubai, and 33.6% in Sharjah and northern Emirates. The majority of the participants completed the survey in Arabic (60.4%), followed by English (39.3%), and only 0.3% chose the French language. Comprehensive information relating to demographic characteristics of the study population is presented in Table 1. The majority of participants were females (75.9%), aged 26–35 years (29.1%), were married (56.4%), had no children (50%), completed a bachelor’s degree (54.1%), worked full-time (53.3%), and were working or studying from home during quarantine (61.6%). Almost one third of the participants reported weight gain since the start of the lockdown (31%). However, 20.9% reported weight loss, 40.1% maintained their weight, and 7.9% did not know if there was a change in their weight. The majority of participants described their health status during the outbreak as very good (39.7%) and only 0.7% indicated poor health status.

3.2. Source of Information

When asked about the most common source of information for health and nutrition updates, 69.1% and 67.8% of participants reported relying on social media applications, respectively (Table 2). Local and international health authorities were selected as the second source of information for both health and nutrition updates (65.4% and 48.7%, respectively).

3.3. Eating Habits

Table 3 presents the eating habits of the study participants pre- and during the COVID-19 pandemic. Results showed a significant increase in the percentage of participants consuming mostly homemade meals during the pandemic and a significant reduction in those mainly consuming fast-food (p < 0.001). Moreover, the percentage of participants consuming five or more meals per day increased from 2.1% before the pandemic to 7% during the pandemic (p < 0.001). Also, the percentage of participants consuming breakfast increased from 66% to 74.2%, and the percentage of those skipping meals decreased from 64.5% to 46.2% during the pandemic (p < 0.001). Participants reported skipping meals mainly due to lack of time before the pandemic (62.3%), however, the main reason behind that was lack of appetite (36%). With regards to water intake, only 24.1% of participants consumed eight or more cups per day before the pandemic, and the percentage increased to 27.8% during the pandemic (p = 0.003).
The frequency of consumption for particular food products during the COVID-19 pandemic among residents of the UAE are presented in Table 4. Over half of the participants (51.2%) did not consume fruits daily, 37% did not consume vegetables daily, and 46.2% did not consume milk and dairy products on daily basis. However, 46.1% of the participants consumed sweets and desserts at least once per day, and 37.1% reported consuming salty snacks (chips, crackers, and nuts) every day.
Additionally, 69.2% had tea or coffee at least once per day. Sweet drinks such as fruit juices and beverages were less popular among the study participants, as 44.2% reported never consuming them and an even higher percentage (86.5%) reported never consuming energy drinks during the pandemic.
A total of two components from the PCA output were derived, based on eigenvalue (at least 1) and scree plots obtained (Table 5). These two components explained 47% of the variance in eating behavior and were named based on the interpretation of the component loadings. The first pattern explained 31% of eating variation and was named “Western-type diet” since it was characterized by significantly positive loadings in dairy, meat, sweets, salted foods and vegetables. The second pattern explained 16% of the variance and loaded positively with ssbs and energy drinks and negatively on fruits and vegetables. Therefore, it was named “Free Sugars diet”. A KMO of 0.78 was obtained, which is considered substantial.

3.4. Shopping

The results revealed that the majority of participants prepared a shopping list beforehand (80.3%), started stocking up on foods during the pandemic (43.9%), did not order their groceries online (58.0%), read the food label before purchasing products (52.4%), and sanitized or cleaned groceries before storing them (71.9%) (Table 6).

3.5. Physical Activity

Figure 1a shows that 32.1% of the participants reported not engaging in any physical activity before the coronavirus pandemic, and the percentage increased to 38.5% during the pandemic (p < 0.001). Moreover, Figure 1b shows that there was a significant association between the frequency of performing physical activity during the pandemic and the reported change in weight among participants (p < 0.001). Of those who reported performing physical activity more than three times per week, 29.9% lost weight and 49.5% maintained their weight (p < 0.001). Furthermore, 40.3% of people who did not perform physical activity reported weight gain.
A significantly higher percentage of participants spent more than five hours per day on the computer for study or work purposes during the pandemic (47.6%) compared to before the pandemic (32%) (p < 0.001). Similarly, the percentage of participants spending more than five hours per day on screens for fun increased from 12.9% before the lockdown to 36.2% during the lockdown (p < 0.001) (Table 7).

3.6. Stress

Participants were asked to indicate the frequency of experiencing physical exhaustion; emotional exhaustion; irritability; and tension before and during the pandemic. Figure 2 presented the response distribution in percentages for each of the four stress parameters.
The results indicate a significant increase in the percentage of participants reporting all four stress parameters “all the time” during the coronavirus pandemic compared to before the pandemic (13.3% vs. 7.7% for physical exhaustion; 14.1% vs. 6.3% for emotional exhaustion; 13.5% vs. 6.9% for irritability; and 17.8% vs. 6.3% for tension) (all p < 0.001).

3.7. Sleep

Results showed a significant decrease in the percentage of participants who reported sleeping less than seven hours per night from 51.7% before the pandemic to 39% during the pandemic (p < 0.001) (Table 8). However, a higher percentage of participants reported poor sleep quality during the pandemic (28.1%) compared to before the pandemic (17.3) (p < 0.001), and sleep disturbances were also more common during the pandemic (60.8%) compared to before (52.9%). Consequently, 30.9% of the surveyed participants reported feeling lazy and less energized during the pandemic, compared to only 4.7% before the pandemic (p < 0.001) (Table 8).
An analysis of weight and behavioral factors by sex and age groups is depicted in Table 9. Significantly more males reported decreased engagement in physical activity (50% vs. 39.3%; p = 0.013) and increased screen time (54.5% vs. 51%; p = 0.002). Sleep disturbances increase was, however, significantly higher in females (p = 0.011). Moreover, those aged over 36 years reported a higher weight gain as well as an increase in the number of meals consumed per day (p = 0.042 and p = 0.024, respectively). Sleep duration and quality was most affected among participants aged 18–35 (p < 0.001). There was no significant association between different education levels and lifestyle changes (Table 9).

4. Discussion

This population-based, cross-sectional study assessed eating habits and lifestyle behaviors among residences of the UAE, via an online survey during the COVID-19 pandemic between April and May 2020. The results indicate that the COVID-19 pandemic and the subsequent lockdown resulted in weight gain in about one-third of the respondents with changes in important and highly modifiable dietary and lifestyle behaviors that are considered essential for optimal somatic and psychological health. Specifically, participants also reported an increase in the number of meals consumed per day and a reduction in the percentage of skipping meals particularly breakfast during the pandemic. The present study also indicated that dietary habits were distanced from the Mediterranean diet principles and closer to “unhealthy” dietary patterns, characterized as high in energy but with low nutrient density; viewed as a detrimental combination for immune status. Although more homemade meals were prepared, a factor associated with healthy weight status, at the same time more non-nutritious foods were chosen, as well as being more frequently consumed (since an increase was also seen among frequency of meals per day). These data, therefore, are informative on the potential alterations of food prepared and consumed although at home.
In agreement with our study, the results from Kuwait, United States, Italy and France revealed an increase in caloric intake and indicated weight gain during the current COVID-19 home confinement [10,35,36,37]. Data from Kuwait, a close Gulf country to UAE, showed a significant increase in weight of respondents during the quarantine and the weight gain was 4.5 times higher among those consuming unhealthy diets [38]. The actual weight increase was not assessed in this study considering the short time interval of COVID-19 lockdown, however, the large percentage of the population that reported an increase in weight can be used as a proxy pertaining to changes in eating behavior and activity level. It has been suggested that the negative alterations in eating behaviors could be due to anxiety or boredom [39], lack of motivation to maintain healthy habits [40], or reduced availability of goods and limited access to food due to restricted store opening hours [41]. The prevalence of overweight and obesity in the UAE even before COVID-19 was high and has increased over time [42]. It is estimated that over one third of the population in the UAE is living with obesity with higher rates among females [43]. Thus, extra efforts are needed to reduce the burden of obesity and its risk factors especially during the COVID-19 pandemic.
Over half of the surveyed participants in this study did not consume fruits daily and about one third did not consume vegetables and dairy products on daily basis. Instead, almost half of the same population reported consuming sweets and desserts at least once per day and over one third consumed salty snacks daily. This transition towards a Westernized diet in the UAE was reported in 1998, where the consumption of fresh fruit and vegetables and of milk and dairy products was found low [32]. Moreover, in 2003, 77.5% of males and 75.7% of females in the UAE had less than five servings of fruit and vegetables per day [44]. Likewise, a recent study among Emirati adolescents revealed that only 28% of them met the recommended daily fruit and vegetable intake [45]. This is concerning especially as fruits and vegetables are an important source of fiber, vitamins, minerals, and antioxidants. Diets rich in antioxidants (such as the Mediterranean diet and Dietary Approaches to Stop Hypertension (DASH) diet) are vascular protective. The Mediterranean diet is recognized as an anti-inflammatory dietary pattern, focusing on high consumption of plant foods, low red meat and dairy and moderate consumption of monounsaturated fat sources such as olive oil [46]. Evidence suggests that the Mediterranean diet is associated with better health status, lower risk of chronic disease and inflammation as well as increased immunity [47,48,49]. The Mediterranean diet is not only a healthy dietary pattern, but is also a sustainable diet that has a lower environmental impact than the typical Western diet [50]. Moreover, mounting evidence indicates that the Mediterranean diet has a favorable effect on diseases related to chronic inflammation, including visceral obesity, type 2 diabetes mellitus and the metabolic syndrome [51,52,53,54,55]. Knowing that the prevalence of cardiovascular disease incidence is high in the UAE (40%) [56] and rates of dyslipidemia are strikingly elevated (72.5%) [57] makes it imperative that diets such as the Mediterranean diet should be encouraged to prevent the potentially negative effect of quarantine on dietary habits and overall health [41].
Due to the increase in obesogenic behaviors related to the COVID-19 pandemic, two dietary patterns were revealed among the studied population, named the “Western-type diet” and the “Free Sugars diet”. These patterns indicate unhealthy eating behaviors during the period of the pandemic. This is in agreement with previous studies reporting a transformation of the diet in Eastern Mediterranean countries from a traditional Mediterranean diet to a more Westernized diet which is high in energy, saturated fat, cholesterol, salt, and refined carbohydrates, and low in fruits, vegetables, fiber, and polyunsaturated fats [25,58,59,60]. Therefore, current dietary behaviors in the UAE may not be effective against the COVID-19 virus since it can adversely affect the immune system response among other health factors. Furthermore, it is unclear whether these dietary patterns were due to the lockdown that followed the COVID-19 outbreak; however, the implications can be detrimental considering an adequate supply of macro- and micro-nutrients are essential for optimal immune function and response [11,61].
Amidst these passive changes in food behavior, some beneficial aspects emerged from this study, such as a significant increase in home-made food preparations, regular breakfast consumption and lower intakes of fast foods. Similarly, a consumer online based survey conducted by Ipsos across the Middle East and North Africa (MENA) region revealed that 57% out of the 5000 consumers who took part in the survey were preparing their own meals, and 79% were eating less often at restaurants [62].
Among the surveyed participants, more than one third reported a non-engagement in any physical activity during coronavirus pandemic lockdown. This was mostly observed among males in this study, with a simultaneously greater likelihood of increased sedentary time, compared to females. The findings of this questionnaire are in accordance with other studies indicating that the current COVID-19 pandemic had a dramatic impact on lifestyle behaviors globally, including diminished engagement in sports and physical activity in general [63,64,65]. Moreover, the “Effects of home Confinement on multiple Lifestyle Behaviours during the COVID-19 outbreak (ECLB-COVID-19)” international survey revealed that the COVID-19 pandemic had a negative effect on all levels of physical activity (vigorous, moderate, walking and overall) and increased daily sedentary time by more than 28% [14]. Similarly, in the current study the proportion of participants who spent more than five hours per day on screens for entertainment increased by 23.3%. Together with the unhealthy diet, the reduction of physical activity would not only contribute to weight gain, but also to an increase in cardiovascular risk during quarantine. Thus, awareness about the importance of regular physical activity and its benefits on overall health is necessary during such times [66,67]. It is also important to identify groups at a higher risk of unhealthy lifestyle behaviors during the COVID-19 pandemic to design interventions targeted towards these groups.
During the COVID-19 pandemic higher levels of anxiety, stress and depression have been observed among individuals [68,69,70]. In this study, the percentage of participants experiencing exhaustion, irritability, and tension more often during the coronavirus pandemic increased significantly. Sleep was mostly affected in females and needs to be further evaluated since it is linked with multiple endocrine functions, as well risk for obesity and depression. The risk of obesity is underlined by the significant increase in daily meal frequency among participants over 36 years with the majority being female. Also, despite WHO recommendations to minimize listening to unreliable news that could cause anxiety or distress and to seek information only from trusted sources [71], over two thirds of participants in this survey used social media as a main source for health updates. Studies have shown the negative and harmful effect of misinformation overload “infodemic” on the mental health of individuals [72,73]. Moreover, stress and anxiety could disrupt sleep quality during the night and energy levels during the day. Results of the current survey indicated a 10.8% increase in participants reporting poor sleep quality and 26.2% increase in those feeling lazy during the pandemic. Xiao and his co-workers found a significant negative correlation between anxiety levels and sleep quality and suggested the use of telepsychiatry consultation as an important therapeutic strategy [74]. The use of telehealth has been shown to be useful in providing support to patients and is appropriate for the delivery of mental health services [75]. Additionally, the Mediterranean diet does not only have a protective effect on the risk of cardiovascular diseases and certain types of cancer [54,76], but also an increased compliance with it could be associated with lesser mental distress, better sleep quality, and higher scoring for self-perceived health status [77,78,79].
It is acknowledged that this study has limitations related to the use of self-reported questionnaire, snowball sampling method and the cross-sectional study design. The study information was acquired after lockdown, and although comparisons are critical to be made in order to draw inferences, no conclusive remarks can be drawn. Results stratified by sex should be interpreted with caution, since the majority of the participants were females. Furthermore, in order to minimize selection bias that may arise with snowball sampling (including interrelated-similar individuals), each individual could refer a maximum of three people who were not family members, and only one individual per age group (young adults, older adults, elderly) was enrolled from a household. Moreover, the change in dietary pattern was not assessed in this study, since data on food frequency were only obtained during COVID-19 pandemic, although these can be used as a reference for further studies performed, in these uncertain times. This was done to reduce the probability of including recall bias, since the participants had to respond to multiple questions on food frequency and quantity during COVID-19 lockdown and for a prolonged period prior to that. Also, the presence of obesity and eating disorders were not determined in the study, nor was information on infection with COVID-19 reported. Such analysis would require a longer questionnaire, hence may have decreased the compliance and response rate, but also would have required a larger sample size based on the prevalence of all factors to acquire adequate study power. Another potential limitation of the study was that respondents were mostly females. Although this is usual in online questionnaires [80], it should be considered when generalizing the results. However, using an online survey facilitated data collection during COVID-19 pandemic from all seven emirates. It also guaranteed the anonymity of the participants, thus reducing the social desirability bias. The strengths of this research include data collection timing one month after lockdown which minimizes memory failure for previous habits. In addition, the survey provided was in multiple languages in a multilingual environment like UAE.
The results of the study indicate that individuals in the UAE experienced negative lifestyle changes, unbalanced food choices, a reduction in physical activity, and psychological problems during the COVID-19 pandemic. Although quarantine is an essential measure to protect public health and control the transmission of the virus, these findings should be taken into consideration for future regulations in the UAE.

Supplementary Materials

The following are available online at, Eating Habits and Lifestyle during COVID-19 Lockdown in the United Arab Emirates: A Cross-Sectional Study.

Author Contributions

Conceptualization, L.C.I., T.M.O. and A.S.A.D.; methodology, L.C.I., T.M.O., A.S.A.D., M.N.M., M.H., and S.T.S.; validation, L.C.I., T.M.O., A.S.A.D., M.N.M. and E.M.; formal analysis, L.C.I., M.N.M., S.T.S., E.M. and H.H.; investigation, L.C.I., T.M.O., M.N.M., A.S.A.D., A.A.M., A.H.J., D.O.A.J., H.I.A., H.A.S., H.H., L.M.R.A., L.S., M.H., R.R.S.O., and S.T.S.; writing—original draft preparation, L.C.I., M.N.M., A.S.A.D. and S.T.S.; writing—review and editing, L.C.I., T.M.O., M.N.M., A.S.A.D., A.A.M., A.H.J., D.O.A.J., E.M.,H.I.A., H.A.S., H.H., L.M.R.A., L.S., M.H., R.R.S.O., and S.T.S. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Barro, R.J.; Ursúa, J.F.; Weng, J. The Coronavirus and the Great Influenza Pandemic: Lessons from the “Spanish flu” for the Coronavirus’s Potential Effects on Mortality and Economic Activity; 0898-2937; National Bureau of Economic Research: Cambridge, MA, USA, 2020. [Google Scholar]
  2. WHO. WHO Director-General’s Opening Remarks at the Media Briefing on COVID-19—11 March 2020. Available online: (accessed on 16 August 2020).
  3. WHO. Coronavirus Disease (COVID-19) Weekly Epidemiological and Operational Updates September 2020. Available online: (accessed on 29 September 2020).
  4. Wilder-Smith, A.; Freedman, D. Isolation, quarantine, social distancing and community containment: Pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak. J. Travel Med. 2020, 27, taaa020. [Google Scholar] [CrossRef] [PubMed]
  5. Koh, D. COVID-19 lockdowns throughout the world. Occup. Med. 2020. [Google Scholar] [CrossRef]
  6. Bloukh, S.H.; Shaikh, A.; Pathan, H.M.; Edis, Z. Prevalence of COVID-19: A Look behind the Scenes from the UAE and India. Preprints 2020. [Google Scholar] [CrossRef][Green Version]
  7. Bank, T.W. United Arab Emirates: Data Source: United Nations World Population Prospects. Available online: (accessed on 16 August 2020).
  8. De Bel-Air, F. Demography, Migration, and the Labour Market in the UAE; Migration Policy Center, Gulf Labour Markets and Migration (GLMM): Firenze, Italy, 2015. [Google Scholar]
  9. Scarmozzino, F.; Visioli, F. Covid-19 and the Subsequent Lockdown Modified Dietary Habits of Almost Half the Population in an Italian Sample. Foods 2020, 9, 675. [Google Scholar] [CrossRef] [PubMed]
  10. Deschasaux-Tanguy, M.; Druesne-Pecollo, N.; Esseddik, Y.; Szabo de Edelenyi, F.; Alles, B.; Andreeva, V.A.; Baudry, J.; Charreire, H.; Deschamps, V.; Egnell, M.; et al. Diet and physical activity during the COVID-19 lockdown period (March-May 2020): Results from the French NutriNet-Sante cohort study. medRxiv 2020. [Google Scholar] [CrossRef]
  11. Calder, P.C. Nutrition, immunity and COVID-19. BMJ Nutr. Prev. Health 2020, 3, 74. [Google Scholar] [CrossRef]
  12. Zachary, Z.; Brianna, F.; Brianna, L.; Garrett, P.; Jade, W.; Alyssa, D.; Mikayla, K. Self-quarantine and Weight Gain Related Risk Factors During the COVID-19 Pandemic. Obes. Res. Clin. Pract. 2020. [Google Scholar] [CrossRef]
  13. Musaiger, A.O. Diet and Prevention of Coronary Heart Disease in the Arab Middle East Countries. Med. Princ. Pract. 2002, 11, 9–16. [Google Scholar] [CrossRef]
  14. Ammar, A.; Brach, M.; Trabelsi, K.; Chtourou, H.; Boukhris, O.; Masmoudi, L.; Bouaziz, B.; Bentlage, E.; How, D.; Ahmed, M. Effects of COVID-19 Home Confinement on Eating Behaviour and Physical Activity: Results of the ECLB-COVID19 International Online Survey. Nutrients 2020, 12, 1583. [Google Scholar] [CrossRef]
  15. Lippi, G.; Henry, B.M.; Sanchis-Gomar, F. Physical inactivity and cardiovascular disease at the time of coronavirus disease 2019 (COVID-19). Eur. J. Prev. Cardiol. 2020. [Google Scholar] [CrossRef]
  16. Hall, G.; Laddu, D.R.; Phillips, S.A.; Lavie, C.J.; Arena, R. A tale of two pandemics: How will COVID-19 and global trends in physical inactivity and sedentary behavior affect one another? Prog. Cardiovasc. Dis. 2020. [Google Scholar] [CrossRef] [PubMed]
  17. Yammine, K. The prevalence of physical activity among the young population of UAE: A meta-analysis. Perspect. Public Health 2017, 137, 275–280. [Google Scholar] [CrossRef] [PubMed]
  18. Wu, P.; Fang, Y.; Guan, Z.; Fan, B.; Kong, J.; Yao, Z.; Liu, X.; Fuller, C.J.; Susser, E.; Lu, J. The psychological impact of the SARS epidemic on hospital employees in China: Exposure, risk perception, and altruistic acceptance of risk. Can. J. Psychiatry 2009, 54, 302–311. [Google Scholar] [CrossRef]
  19. Pfefferbaum, B.; North, C.S. Mental health and the Covid-19 pandemic. N. Engl. J. Med. 2020. [Google Scholar] [CrossRef] [PubMed]
  20. Todisco, P.; Donini, L.M. Eating disorders and obesity (ED&O) in the COVID-19 storm. Eat. Weight Disord. 2020, 1. [Google Scholar] [CrossRef]
  21. Touyz, S.; Lacey, H.; Hay, P. Eating disorders in the time of COVID-19. J. Eat. Disord. 2020, 8, 19. [Google Scholar] [CrossRef] [PubMed][Green Version]
  22. Rajkumar, R.P. COVID-19 and mental health: A review of the existing literature. Asian J. Psychiatry 2020, 52, 102066. [Google Scholar] [CrossRef]
  23. Holmes, E.A.; O’Connor, R.C.; Perry, V.H.; Tracey, I.; Wessely, S.; Arseneault, L.; Ballard, C.; Christensen, H.; Silver, R.C.; Everall, I. Multidisciplinary research priorities for the COVID-19 pandemic: A call for action for mental health science. Lancet Psychiatry 2020. [Google Scholar] [CrossRef]
  24. Torales, J.; O’Higgins, M.; Castaldelli-Maia, J.M.; Ventriglio, A. The outbreak of COVID-19 coronavirus and its impact on global mental health. Int. J. Soc. Psychiatry 2020. [Google Scholar] [CrossRef][Green Version]
  25. Ng, S.W.; Zaghloul, S.; Ali, H.; Harrison, G.; Yeatts, K.; El Sadig, M.; Popkin, B.M. Nutrition transition in the United Arab Emirates. Eur. J. Clin. Nutr. 2011, 65, 1328–1337. [Google Scholar] [CrossRef][Green Version]
  26. Lee, P.H.; Macfarlane, D.J.; Lam, T.H.; Stewart, S.M. Validity of the international physical activity questionnaire short form (IPAQ-SF): A systematic review. Int. J. Behav. Nutr. Phys. Act. 2011, 8, 115. [Google Scholar] [CrossRef] [PubMed][Green Version]
  27. Pejtersen, J.H.; Kristensen, T.S.; Borg, V.; Bjorner, J.B. The second version of the Copenhagen Psychosocial Questionnaire. Scand. J. Public Health 2010, 38, 8–24. [Google Scholar] [CrossRef]
  28. Wild, D.; Grove, A.; Martin, M.; Eremenco, S.; McElroy, S.; Verjee-Lorenz, A.; Erikson, P. Principles of good practice for the translation and cultural adaptation process for patient-reported outcomes (PRO) measures: Report of the ISPOR task force for translation and cultural adaptation. Value Health 2005, 8, 94–104. [Google Scholar] [CrossRef] [PubMed][Green Version]
  29. Beaton, D.E.; Bombardier, C.; Guillemin, F.; Ferraz, M.B. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine 2000, 25, 3186–3191. [Google Scholar] [CrossRef][Green Version]
  30. Osler, M.; Heitmann, B.L. The Validity of a Short Food Frequency Questionnaire and its Ability to Measure Changes in Food Intake: A Longitudinal Study. Int. J. Epidemiol. 1996, 25, 1023–1029. [Google Scholar] [CrossRef] [PubMed]
  31. Cooper, R.; Al-Alami, U. Food consumption patterns of female undergraduate students in the United Arab Emirates. West Afr. J. Med. 2011, 30, 42–46. [Google Scholar] [CrossRef] [PubMed][Green Version]
  32. Musaiger, A.O.; Abuirmeileh, N.M. Food consumption patterns of adults in the United Arab Emirates. J. R. Soc. Promot. Health 1998, 118, 146–150. [Google Scholar] [CrossRef]
  33. Streiner, D.L. Starting at the Beginning: An Introduction to Coefficient Alpha and Internal Consistency. J. Personal. Assess. 2003, 80, 99–103. [Google Scholar] [CrossRef]
  34. Panagiotakos, D.B.; Pitsavos, C.; Stefanadis, C. Dietary patterns: A Mediterranean diet score and its relation to clinical and biological markers of cardiovascular disease risk. Nutr. Metab. Cardiovasc. Dis. 2006, 16, 559–568. [Google Scholar] [CrossRef]
  35. Bhutani, S.; Cooper, J.A. COVID-19 related home confinement in adults: Weight gain risks and opportunities. Obesity 2020. [Google Scholar] [CrossRef]
  36. Di Renzo, L.; Gualtieri, P.; Pivari, F.; Soldati, L.; Attinà, A.; Cinelli, G.; Leggeri, C.; Caparello, G.; Barrea, L.; Scerbo, F.; et al. Eating habits and lifestyle changes during COVID-19 lockdown: An Italian survey. J. Transl. Med. 2020, 18, 229. [Google Scholar] [CrossRef] [PubMed]
  37. Husain, W.; Ashkanani, F. Does COVID-19 Change Dietary Habits and Lifestyle Behaviours in Kuwait? Environ. Health Prev. Med. 2020. [Google Scholar] [CrossRef] [PubMed]
  38. ALMughamis, N.S.; AlAsfour, S.; Mehmood, S. Poor Eating Habits and Predictors of Weight Gain During the COVID-19 Quarantine Measures in Kuwait: A Cross Sectional Study. Res. Sq. 2020. [Google Scholar] [CrossRef]
  39. Moynihan, A.B.; Van Tilburg, W.A.; Igou, E.R.; Wisman, A.; Donnelly, A.E.; Mulcaire, J.B. Eaten up by boredom: Consuming food to escape awareness of the bored self. Front. Psychol. 2015, 6, 369. [Google Scholar] [CrossRef] [PubMed]
  40. Gardner, B.; Rebar, A.L. Habit Formation and Behavior Change. In Oxford Research Encyclopedia of Psychology; Oxford University Press: Oxford, UK, 2019. [Google Scholar]
  41. Mattioli, A.V.; Puviani, M.B.; Nasi, M.; Farinetti, A. COVID-19 pandemic: The effects of quarantine on cardiovascular risk. Eur. J. Clin. Nutr. 2020. [Google Scholar] [CrossRef]
  42. Sulaiman, N.; Elbadawi, S.; Hussein, A.; Abusnana, S.; Madani, A.; Mairghani, M.; Alawadi, F.; Sulaiman, A.; Zimmet, P.; Huse, O. Prevalence of overweight and obesity in United Arab Emirates Expatriates: The UAE national diabetes and lifestyle study. Diabetol. Metab. Syndr. 2017, 9, 88. [Google Scholar] [CrossRef][Green Version]
  43. Razzak, H.A.; El-Metwally, A.; Harbi, A.; Al-Shujairi, A.; Qawas, A. The prevalence and risk factors of obesity in the United Arab Emirates. Saudi J. Obes. 2017, 5, 57. [Google Scholar] [CrossRef]
  44. Belal, A.M. Nutrition-related chronic diseases Epidemic in UAE: Can we stand to STOP it? Sudan. J. Public Health 2009, 4, 383–392. [Google Scholar]
  45. Makansi, N.; Allison, P.; Awad, M.; Bedos, C. Fruit and vegetable intake among Emirati adolescents: A mixed methods study. East. Mediterr. Health J. 2018, 24. [Google Scholar] [CrossRef]
  46. Díez, J.; Bilal, U.; Franco, M. Unique features of the Mediterranean food environment: Implications for the prevention of chronic diseases Rh: Mediterranean food environments. Eur. J. Clin. Nutr. 2019, 72, 71–75. [Google Scholar] [CrossRef]
  47. Martínez-González, M.A.; Gea, A.; Ruiz-Canela, M. The Mediterranean diet and cardiovascular health: A critical review. Circ. Res. 2019, 124, 779–798. [Google Scholar] [CrossRef]
  48. Becerra-Tomás, N.; Blanco Mejía, S.; Viguiliouk, E.; Khan, T.; Kendall, C.W.; Kahleova, H.; Rahelić, D.; Sievenpiper, J.L.; Salas-Salvadó, J. Mediterranean diet, cardiovascular disease and mortality in diabetes: A systematic review and meta-analysis of prospective cohort studies and randomized clinical trials. Crit. Rev. Food Sci. Nutr. 2020, 60, 1207–1227. [Google Scholar] [CrossRef] [PubMed]
  49. Godos, J.; Zappala, G.; Bernardini, S.; Giambini, I.; Bes-Rastrollo, M.; Martinez-Gonzalez, M. Adherence to the Mediterranean diet is inversely associated with metabolic syndrome occurrence: A meta-analysis of observational studies. Int. J. Food Sci. Nutr. 2017, 68, 138–148. [Google Scholar] [CrossRef] [PubMed]
  50. Germani, A.; Vitiello, V.; Giusti, A.M.; Pinto, A.; Donini, L.M.; del Balzo, V. Environmental and economic sustainability of the Mediterranean Diet. Int. J. Food Sci. Nutr. 2014, 65, 1008–1012. [Google Scholar] [CrossRef] [PubMed]
  51. Giugliano, D.; Esposito, K. Mediterranean diet and metabolic diseases. Curr. Opin. Lipidol. 2008, 19, 63–68. [Google Scholar] [CrossRef] [PubMed]
  52. Hassapidou, M.; Tziomalos, K.; Lazaridou, S.; Pagkalos, I.; Papadimitriou, K.; Kokkinopoulou, A.; Tzotzas, T. The Nutrition Health Alliance (NutriHeAl) Study: A Randomized, Controlled, Nutritional Intervention Based on Mediterranean Diet in Greek Municipalities. J. Am. Coll. Nutr. 2020, 39, 338–344. [Google Scholar] [CrossRef] [PubMed]
  53. Sánchez-Villegas, A.; Bes-Rastrollo, M.; Martínez-González, M.A.; Serra-Majem, L. Adherence to a Mediterranean dietary pattern and weight gain in a follow-up study: The SUN cohort. Int. J. Obes. 2006, 30, 350–358. [Google Scholar] [CrossRef][Green Version]
  54. Serra-Majem, L.; Roman-Vinas, B.; Sanchez-Villegas, A.; Guasch-Ferre, M.; Corella, D.; La Vecchia, C. Benefits of the Mediterranean diet: Epidemiological and molecular aspects. Mol. Asp. Med. 2019, 67, 1–55. [Google Scholar] [CrossRef]
  55. Martínez-González, M.A.; Salas-Salvadó, J.; Estruch, R.; Corella, D.; Fitó, M.; Ros, E. Benefits of the Mediterranean Diet: Insights From the PREDIMED Study. Prog. Cardiovasc. Dis. 2015, 58, 50–60. [Google Scholar] [CrossRef][Green Version]
  56. Turk-Adawi, K.; Sarrafzadegan, N.; Fadhil, I.; Taubert, K.; Sadeghi, M.; Wenger, N.K.; Tan, N.S.; Grace, S.L. Cardiovascular disease in the Eastern Mediterranean region: Epidemiology and risk factor burden. Nat. Rev. Cardiol. 2018, 15, 106–119. [Google Scholar] [CrossRef]
  57. Mahmoud, I.; Sulaiman, N. Dyslipidaemia prevalence and associated risk factors in the United Arab Emirates: A population-based study. BMJ Open 2019, 9, e031969. [Google Scholar] [CrossRef][Green Version]
  58. Taha, Z.; Eltom, S.E. The Role of Diet and Lifestyle in Women with Breast Cancer: An Update Review of Related Research in the Middle East. Biores. Open Access 2018, 7, 73–80. [Google Scholar] [CrossRef] [PubMed]
  59. Musaiger, A.O.; Al-Hazzaa, H.M. Prevalence and risk factors associated with nutrition-related noncommunicable diseases in the Eastern Mediterranean region. Int. J. Gen. Med. 2012, 5, 199–217. [Google Scholar] [CrossRef][Green Version]
  60. Galal, O. Nutrition-related health patterns in the Middle East. Asia Pac. J. Clin. Nutr. 2003, 12, 337–343. [Google Scholar]
  61. Gombart, A.F.; Pierre, A.; Maggini, S. A review of micronutrients and the immune System–Working in harmony to reduce the risk of infection. Nutrients 2020, 12, 236. [Google Scholar] [CrossRef] [PubMed][Green Version]
  62. Ipsos. 5 Ways COVID-19 Has Impacted MENA’s Food Habits. Available online: (accessed on 16 August 2020).
  63. Ammar, A.; Brach, M.; Trabelsi, K.; Chtourou, H.; Boukhris, O.; Masmoudi, L.; Bouaziz, B.; Bentlage, E.; How, D.; Ahmed, M. Effects of COVID-19 home confinement on physical activity and eating behaviour Preliminary results of the ECLB-COVID19 international online-survey. medRxiv 2020. [Google Scholar] [CrossRef]
  64. Abbas, A.M.; Fathy, S.K.; Fawzy, A.T.; Salem, A.S.; Shawky, M.S. The mutual effects of COVID-19 and obesity. Obes. Med. 2020. [Google Scholar] [CrossRef] [PubMed]
  65. Burtscher, J.; Burtscher, M.; Millet, G.P. (Indoor) isolation, stress and physical inactivity: Vicious circles accelerated by Covid-19? Scand. J. Med. Sci. Sports 2020. [Google Scholar] [CrossRef]
  66. Jiménez-Pavón, D.; Carbonell-Baeza, A.; Lavie, C.J. Physical exercise as therapy to fight against the mental and physical consequences of COVID-19 quarantine: Special focus in older people. Prog. Cardiovasc. Dis. 2020. [Google Scholar] [CrossRef] [PubMed]
  67. Czosnek, L.; Lederman, O.; Cormie, P.; Zopf, E.; Stubbs, B.; Rosenbaum, S. Health benefits, safety and cost of physical activity interventions for mental health conditions: A meta-review to inform translation efforts. Ment. Health Phys. Act. 2019, 16, 140–151. [Google Scholar] [CrossRef][Green Version]
  68. Shigemura, J.; Ursano, R.J.; Morganstein, J.C.; Kurosawa, M.; Benedek, D.M. Public responses to the novel 2019 coronavirus (2019-nCoV) in Japan: Mental health consequences and target populations. Psychiatry Clin. Neurosci. 2020, 74, 281–282. [Google Scholar] [CrossRef] [PubMed]
  69. Wang, C.; Pan, R.; Wan, X.; Tan, Y.; Xu, L.; Ho, C.S.; Ho, R.C. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int. J. Environ. Res. Public Health 2020, 17, 1729. [Google Scholar] [CrossRef][Green Version]
  70. Zandifar, A.; Badrfam, R. Iranian mental health during the COVID-19 epidemic. Asian J. Psychiatry 2020, 51. [Google Scholar] [CrossRef] [PubMed]
  71. World Health Organization. Mental Health and Psychosocial Considerations during the COVID-19 Outbreak, 18 March 2020; World Health Organization: Geneva, Switzerland, 2020. [Google Scholar]
  72. Cinelli, M.; Quattrociocchi, W.; Galeazzi, A.; Valensise, C.M.; Brugnoli, E.; Schmidt, A.L.; Zola, P.; Zollo, F.; Scala, A. The covid-19 social media infodemic. arXiv 2020, arXiv:2003.05004. [Google Scholar] [CrossRef] [PubMed]
  73. Gao, J.; Zheng, P.; Jia, Y.; Chen, H.; Mao, Y.; Chen, S.; Wang, Y.; Fu, H.; Dai, J. Mental health problems and social media exposure during COVID-19 outbreak. PLoS ONE 2020, 15, e0231924. [Google Scholar] [CrossRef]
  74. Xiao, H.; Zhang, Y.; Kong, D.; Li, S.; Yang, N. The effects of social support on sleep quality of medical staff treating patients with coronavirus disease 2019 (COVID-19) in January and February 2020 in China. Med. Sci. Monit. Int. Med. J. Exp. Clin. Res. 2020, 26, e923549. [Google Scholar] [CrossRef]
  75. Zhou, X.; Snoswell, C.L.; Harding, L.E.; Bambling, M.; Edirippulige, S.; Bai, X.; Smith, A.C. The role of telehealth in reducing the mental health burden from COVID-19. Telemed. e-Health 2020, 26, 377–379. [Google Scholar] [CrossRef][Green Version]
  76. Rosato, V.; Temple, N.J.; La Vecchia, C.; Castellan, G.; Tavani, A.; Guercio, V. Mediterranean diet and cardiovascular disease: A systematic review and meta-analysis of observational studies. Eur. J. Nutr. 2019, 58, 173–191. [Google Scholar] [CrossRef]
  77. Salvatore, F.P.; Relja, A.; Filipčić, I.Š.; Polašek, O.; Kolčić, I. Mediterranean diet and mental distress:“10,001 Dalmatians” study. Br. Food J. 2019, 121, 1314–1326. [Google Scholar] [CrossRef]
  78. Godos, J.; Ferri, R.; Caraci, F.; Cosentino, F.I.I.; Castellano, S.; Galvano, F.; Grosso, G. Adherence to the mediterranean diet is associated with better sleep quality in Italian adults. Nutrients 2019, 11, 976. [Google Scholar] [CrossRef][Green Version]
  79. Muñoz, M.A.; Fíto, M.; Marrugat, J.; Covas, M.I.; Schröder, H. Adherence to the Mediterranean diet is associated with better mental and physical health. Br. J. Nutr. 2008, 101, 1821–1827. [Google Scholar] [CrossRef][Green Version]
  80. Smith, G. Does Gender Influence Online Survey Participation: A Record-Linkage Analysis of University Faculty Online Survey Response Behavior; ERIC Document Reproduction Service No. ED 501717; San Jose State University, ScholarWorks: San Jose, CA, USA, 2008. [Google Scholar]
Figure 1. Physical activity pre- and during COVID-19 pandemic (a) Frequency; (b) Change in weight. The p values indicate the statistical significance of McNemar test. The p values indicate the statistical significance of chi-square test.
Figure 1. Physical activity pre- and during COVID-19 pandemic (a) Frequency; (b) Change in weight. The p values indicate the statistical significance of McNemar test. The p values indicate the statistical significance of chi-square test.
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Figure 2. Stress and irritability pre- and during COVID-19 pandemic (a) Physical exhaustion; (b) Emotional exhaustion; (c) Irritability; (d) Tension. The p values indicate the statistical significance of McNemar test.
Figure 2. Stress and irritability pre- and during COVID-19 pandemic (a) Physical exhaustion; (b) Emotional exhaustion; (c) Irritability; (d) Tension. The p values indicate the statistical significance of McNemar test.
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Table 1. Demographic characteristics of study participants (n = 1012).
Table 1. Demographic characteristics of study participants (n = 1012).
Age (years)
Marital status
Number of children
≥ 327627.3
Education level
Less than high school80.8
High school11111.0
Bachelor’s degree54754.1
Higher than bachelor’s degree 24424.1
Employment status
Working/studying from home
Not applicable807.9
Weight change during pandemic
Lost weight21220.9
Gained weight31431.0
Maintained weight40640.1
Do not know807.9
Perceived health state during pandemic
Very good40239.7
Emirate of residence
Abu Dhabi34333.9
Ras al Khaimah202.0
Umm al Quwain80.8
Table 2. Source of health and nutrition information during COVID-19 pandemic (n = 1012).
Table 2. Source of health and nutrition information during COVID-19 pandemic (n = 1012).
Source of Information *Health-Related Information, n (%)Nutrition-Related Information, n (%)
Local and international health authorities662 (65.4)493 (48.7)
Social media699 (69.1)686 (67.8)
Healthcare professionals409 (40.4)462 (45.7)
Television231 (22.8)172 (17.0)
Newspapers75 (7.4)51 (5.0)
Friends and family339 (33.5)386 (38.1)
* As multiple responses were allowed, the total number of responses is greater than the number of surveyed participants and the percent of cases is displayed.
Table 3. Eating habits pre- and during COVID-19 pandemic (n = 1012).
Table 3. Eating habits pre- and during COVID-19 pandemic (n = 1012).
n (%)
During COVID-19
n (%)
Most consumed meals during the week *
Homemade838 (82.8)974 (96.2)<0.001
Frozen ready-to-eat meals119 (11.8)97 (9.6)0.032
Fast food270 (26.7)80 (7.9)<0.001
Restaurants 1289 (28.6)58 (5.7)<0.001
Healthy restaurants 298 (9.7)46 (4.5)<0.001
Number of meals per day
1–2 meals470 (46.4)369 (36.5)<0.001
3–4 meals521 (51.5)572 (56.5)0.009
≥5 meals21 (2.1)71 (7.0)<0.001
Eating breakfast on most days
Yes668 (66.0)751 (74.2)<0.001
No344 (34.0)261 (25.8)
Skipping meals
Yes663 (65.5)468 (46.2)<0.001
No349 (34.5)544 (53.8)
Reasons for skipping meals (If the answer was yes) *
To reduce food intake143 (21.7)136 (29.1)0.011
Lack of time410 (62.3)143 (30.6)<0.001
To lose weight122 (18.5)110 (23.6)0.001
Lack of appetite182 (27.7)168 (36.0)0.016
Fasting68 (10.3)120 (25.7)<0.001
Amount of water consumed per day
1–4 cups410 (40.5)337 (33.3)<0.001
5–7 cups358 (35.4)394 (38.9)0.036
≥8 cups244 (24.1)281 (27.8)0.003
* As multiple responses were allowed, the total number of responses is greater than the number of surveyed participants and the percent of cases is displayed. 1 Restaurants: included all ethnic restaurants (Asian, Middle Eastern, International, etc.), casual dining and family style restaurants; 2 healthy restaurants: included food outlets with the “Weqaya logo”, restaurants categorized as “healthy” on food mobile apps (such as Zomato, Talabat, and Uber Eats) or catering services providing meal plan services based on nutritional needs (such as Kcal, right bite, Eat Clean ME, etc.).
Table 4. The frequency of consumption of particular foods during COVID-19 pandemic (n = 1012).
Table 4. The frequency of consumption of particular foods during COVID-19 pandemic (n = 1012).
Food Items≥4 Times/Day2–3 Times/DayOnce/Day1–4 Times/WeekNever
n (%)
Fruits20 (2.0)133 (13.1)341 (33.7)462 (45.7)56 (5.5)
Vegetables32 (3.2)244 (24.1)362 (35.8)356 (35.2)18 (1.8)
Milk and milk products17 (1.7)167 (16.5)361 (35.7)374 (37.0)93 (9.2)
Meat/fish/chicken32 (3.2)133 (13.1)440 (43.5)383 (37.8)24 (2.4)
Bread/rice/pasta43 (4.2)263 (26.0)350 (34.6)311 (30.7)45 (4.4)
Sweets/desserts29 (2.9)106 (10.5)331 (32.7)437 (43.2)109 (10.8)
Salty snacks14 (1.4)85 (8.4)276 (27.3)500 (49.4)137 (13.5)
Coffee/tea80 (7.9)321 (31.7)300 (29.6)222 (21.9)89 (8.8)
Sweetened drinks 18 (1.8)51 (5.0)156 (15.4)340 (33.6)447 (44.2)
Energy drinks4 (0.4)11 (1.1)35 (3.5)87 (8.6)875 (86.5)
Table 5. Component loading for the two major dietary patterns of the participants during COVID-19.
Table 5. Component loading for the two major dietary patterns of the participants during COVID-19.
Food GroupsWesternFree Sugars
Salted Foods0.33560.2776
Sweet Drinks0.26780.4929
Energy Drinks0.15750.4433
KMO: Kaiser–Meyer–Olkin (KMO) test. The unique characteristics of each component (dietary pattern) are presented in bold. Marginally unique dietary characteristic for each component. Loadings ≥0.30 and ≤−0.30.
Table 6. Shopping practices during COVID-19 pandemic (n = 1012).
Table 6. Shopping practices during COVID-19 pandemic (n = 1012).
Prepare shopping list
Start stocking up on foods
Already stocking up15615.4
Online grocery shopping
Reading food labels
Sanitizing/cleaning groceries
Table 7. Daily activities pre- and during COVID-19 pandemic (n = 1012).
Table 7. Daily activities pre- and during COVID-19 pandemic (n = 1012).
n (%)
During COVID-19
n (%)
Doing household chores
Never302 (29.8)207 (20.5)<0.001
1–3 times/week404 (39.8)333 (32.9)<0.001
4–5 times/week62 (6.1)114 (11.3)<0.001
Everyday244 (24.1)358 (35.4)<0.001
Screen time for study or work
None188 (18.6)160 (15.8)0.004
1–2 h/day282 (27.9)136 (13.4)<0.001
3–5 h/day218 (21.5)234 (23.1)0.375
>5 h/day324 (32.0)482 (47.6)<0.001
Screen time for entertainment
Less than 30 min/day113 (11.2)62 (6.1)<0.001
1–2 h/day456 (45.1)231 (22.8)<0.001
3–5 h/day312 (30.8)353 (34.9)0.053
>5 h/day131 (12.9)366 (36.2)<0.001
Table 8. Sleep pre- and during COVID-19 pandemic (n = 1012).
Table 8. Sleep pre- and during COVID-19 pandemic (n = 1012).
n (%)
During COVID-19
n (%)
Hours of sleep per night
<7 h523 (51.7)395 (39.0)<0.001
7–9 h459 (45.4)499 (49.3)0.057
>9 h30 (3.0)118 (11.7)<0.001
How would you rate your sleep quality
Very good308 (30.4)282 (27.9)0.134
Good529 (52.3)446 (44.1)<0.001
Poor175 (17.3)284 (28.1)<0.001
Did you experience any of the following *
Slept badly and restlessly251 (24.8)285 (28.2)0.057
Hard to go to sleep199 (19.7)358 (35.4)<0.001
Woken up too early and not been able to get back to sleep232 (22.9)147 (14.5)<0.001
Woken up several times and found it difficult to get back to sleep187 (18.5)334 (33.0)<0.001
None477 (47.1)397 (39.2)<0.001
Describe your energy level
Energized369 (36.5)189 (18.7)<0.001
Neutral596 (58.9)510 (50.4)<0.001
Lazy47 (4.7)313 (30.9)<0.001
* As multiple responses were allowed, the total number of responses is greater than the number of surveyed participants and the percent of cases is displayed.
Table 9. Lifestyle changes during COVID-19 pandemic by demographic factors (n = 1012).
Table 9. Lifestyle changes during COVID-19 pandemic by demographic factors (n = 1012).
n = 1012
GenderAge Group (Year)Education Level
n = 768
n = 244
p Value18–35
n = 574
n = 438
p ValueHigh School
n = 119
Higher Degree
n = 893
p Value
Weight, n, (%)
Decreased212 (20.9)166 (21.6)46 (18.9)0.143131 (22.8)81 (18.5)0.04219 (16.0)193 (21.6)0.350
Same as before486 (48.0)376 (49.0)110 (45.1)273 (47.6)213 (48.6)62 (52.1)424 (47.5)
Increased314 (31.0)226 (29.4)88 (36.1)170 (29.6)144 (32.9)38 (31.9)276 (30.9)
Meals per day, n (%)
Decreased124 (12.3)96 (12.5)28 (11.5)0.14084 (14.6)40 (9.1)0.02413 (10.9)111 (12.4)0.352
Same as before628 (62.1)464 (60.4)164 (67.2)342 (59.6)272 (61.9)69 (58.0)559 (62.6)
Increased260 (25.7)208 (27.1)52 (21.3)148 (25.8)127 (29.0)37 (31.1)223 (25.0)
Physical activity, n (%)
Decreased424 (41.9)302 (39.3)122 (50.0)0.013226 (39.4)198 (45.2)0.17142 (35.3)382 (42.8)0.169
Same as before438 (43.3)346 (45.1)92 (37.7)258 (44.9)180 (41.1)61 (51.3)377 (42.2)
Increased150 (14.8)120 (15.6)30 (12.3)90 (15.7)60 (13.7)16 (13.4)134 (15.0)
Screen time (entertainment), n (%)
Decreased72 (7.1)67 (8.7)5 (2.0)0.00246 (8.0)26 (5.9)0.1508 (6.7)64 (7.2)0.984
Same as before415 (41.0)309 (40.2)106 (43.4)222 (38.7)193 (44.1)49 (41.2)366 (41.0)
Increased525 (51.9)392 (51.0)133 (54.5)306 (53.3)219 (50.0)62 (52.1)463 (51.8)
Sleep (h), n (%)
Decreased148 (14.6)124 (16.1)24 (9.8)0.051100 (17.4)48 (11.0)<0.00123 (19.3)125 (14.0)0.302
Same as before534 (52.8)397 (51.7)137 (56.1)270 (47.0)264 (60.3)59 (49.6)475 (53.2)
Increased330 (32.6)247 (32.2)83 (34.0)204 (35.5)126 (28.8)37 (31.1)293 (32.8)
Sleep disturbances, n (%)
Decreased157 (15.5)119 (15.5)38 (15.6)0.01190 (15.7)67 (15.3)<0.00116 (13.4)141 (15.8)0.135
Same as before552 (54.5)401 (52.2)151 (61.9)285 (49.7)267 (61.0)58 (48.7)494 (55.3)
Increased303 (29.9)248 (32.3)55 (22.5)199 (34.7)104 (23.7)45 (37.8)258 (28.9)
p value was based on chi-square test at 5% level.
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Cheikh Ismail, L.; Osaili, T.M.; Mohamad, M.N.; Al Marzouqi, A.; Jarrar, A.H.; Abu Jamous, D.O.; Magriplis, E.; Ali, H.I.; Al Sabbah, H.; Hasan, H.; et al. Eating Habits and Lifestyle during COVID-19 Lockdown in the United Arab Emirates: A Cross-Sectional Study. Nutrients 2020, 12, 3314.

AMA Style

Cheikh Ismail L, Osaili TM, Mohamad MN, Al Marzouqi A, Jarrar AH, Abu Jamous DO, Magriplis E, Ali HI, Al Sabbah H, Hasan H, et al. Eating Habits and Lifestyle during COVID-19 Lockdown in the United Arab Emirates: A Cross-Sectional Study. Nutrients. 2020; 12(11):3314.

Chicago/Turabian Style

Cheikh Ismail, Leila, Tareq M. Osaili, Maysm N. Mohamad, Amina Al Marzouqi, Amjad H. Jarrar, Dima O. Abu Jamous, Emmanuella Magriplis, Habiba I. Ali, Haleama Al Sabbah, Hayder Hasan, and et al. 2020. "Eating Habits and Lifestyle during COVID-19 Lockdown in the United Arab Emirates: A Cross-Sectional Study" Nutrients 12, no. 11: 3314.

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