Comparative Study on Nutrition and Lifestyle of Information Technology Workers from Romania before and during COVID-19 Pandemic

The study aimed to evaluate lifestyle factors among Information Technology (IT) workers from Romania before and during the pandemic. We used an online applied questionnaire, filled in by 1638 respondents, that assessed nutrition status-Body Mass Index (BMI), weight and diet change, physical activity, alcohol consumption, number of hours working in front of the computer, stress, and sleep. Multivariate logistic regression was used to establish the lifestyle factors that lead to weight gain. Although the level of physical activity (PA) was low before the pandemic, the results of our study showed a further decrease in physical activity. In total, 61.1% of men and 71.1% of women performed PA for less than 30 min per day. Weight gain was reported in 50.5% of men and 45.3% of women (mean weight gain was 5.11 ± 3.52 kg) as a result of increased screen time (with a mean of 3.52 ± 4.29 for females and 3.05 ± 2.09 for males, p > 0.05 h per day) and the reported changes in diet. Despite the popularity of home-cooked foods, the intake of vegetables and fruit remained low. The quality of sleep was poor for 55.7% of the respondents. Public health and corporation policies are required to encourage a healthy lifestyle and avoid chronic diseases.


Introduction
It is well known that Information Technology (IT) workers are a category of the population with a highly sedentary lifestyle [1]. Sedentary behavior will lead to different pathologies (obesity, cardiovascular diseases, diabetes, cancers) [1]. Sedentary lifestyles are

Study Sample and Data Collection
To achieve the objectives of the study, we used a cross-sectional survey. The questionnaires were administered online using Google Docs. The link to the questionnaire was distributed using the emails taken from the websites of different IT institutions from all over the country; the IT companies who agreed to participate shared the link on their internal groups. To obtain more participants, we also emailed the link to friends working in IT with the same request to share the questionnaire. Inclusion criteria were: individuals working in the IT domain and aged over 18 years because all these participants graduated at least high school, and the majority had a university degree. One thousand six hundred eighty-three persons from Information Technology (IT) participated in this survey. From these 715 were selected before the pandemic and 923 were selected during the pandemic with SARS-CoV-2. We collected the data for the pre-pandemic sample in September-November 2019 and for the pandemic respondents from October 2020 to January 2021.

Questionnaire and Variables
We used a self-administered questionnaire. The questionnaire was elaborated/developed based on previous studies and based on international recommendations for a healthy lifestyle [21,22]. We tested and re-tested the questionnaire on a sample of 30 respondents and calculated Spearman's correlation coefficient to assess the reliability (r = 0.766). The time required to fill the questionnaire in the survey was 15-20 min.
The questionnaire included the following: a. Demographic data: sex, age, studies, marital status; b. Number of hours of working in front of the computer (screen time) or other sedentary behaviors like driving a car, watching television, using other electronic devices. During the pandemic, the questionnaire comprised additional questions like "did you work more hours during the pandemic" "did you work at home" (remote work)?
Diet was assessed as follows: c. Diet as the numbers of meals per day, fast food consumption, vegetables, and fruit consumption. In the case of vegetables and fruits, we investigated how many portions were eaten per day. A portion of fruits or vegetables was considered to be 80 g of a medium-size fruit or a 1/2 cup of chopped/cooked vegetables, 30 g of dried fruits, or 150 mL of fruit or vegetable juice.
The respondents were asked if they changed their diet during the pandemic, with possible answers yes or no. The questionnaire investigated if the food was homemade during the pandemic ("The food was homemade? -possible answers yes or no"); d. Alcohol consumption.
The questionnaire also estimated alcohol consumption as the number of drinks per week. We defined a standard drink as 500 mL beer with 5% alcohol or 150 mL wine with 12.5% alcohol or 50 mL of distillate beverage (40% alcohol); e. Physical activity Physical activity was assessed as the duration and frequency, and the place where the physical activity was performed. As an alternative, the number of steps recorded by devices for those who had bracelets, fitness watches, or other devices. The answers were divided into 3000-4000 steps, between 4001-8999 steps, 9000-10,000, and over 10,000 steps; f.
Sleep was assessed as quantity (How many days per week do you sleep less than six hours?) and as quality ("How do you wake up in the morning? Tired or rested"); g. Stress was investigated by self-assessment, using the following question and answer categories: low, moderate, or high. The study also investigated the social need of meeting other persons using a scale from 1 to 10 points; h. Weight and height were reported as self-assessment. We calculated the body mass index using the formula BMI = Weight (kg)/Height 2 (m 2 ). We divided the sample according to WHO guidelines as: underweight -BMI<18.5; normal weight: BMI = 18.5-24.9; overweight was defined as BMI= 25-29 kg/m 2 and obesity as BMI >30 kg/m 2 . The questionnaire also investigated the weight gain or weight loss of the respondents.

Statistical Analysis
Data were statistically analyzed using the Statistical Package for the Social Sciences, version 20. Descriptive statistics (means and standard deviations for continuous variables or frequencies and percentages for categorical variables) were calculated. A chi-square (χ 2 ) statistical test was conducted to examine the significant differences for categorical variables between two periods of time (before and during the COVID-19 outbreak). We used ANOVA to compare the respondent's weight gain depending on their Body Mass Index.
Multiple regression was run to predict the weight gain due to lifestyle change after the COVID-19 outbreak from gender, age, BMI, diet change, and more hours of work in front of the computer. All reported p values were 2-tailed, and p < 0.05 was considered to be statistically significant.

Ethical Issues
The study was approved by the Bioethics Committee of the University of Medicine and Pharmacy Iuliu Hatieganu, Cluj-Napoca, No 254/2019. No personal data were collected, and the questionnaires were anonymous and voluntary. The participants were informed about the aim of the study, and by completing the questionnaire, they agreed to participate in the study.

Results
The mean age of the participants was 26.58 ± 6.33 years for the respondents during the pandemic period and 27.02 ± 6.42 (p = 0.06) in the pre-pandemic period. Of the investigated sample, 57.4% (941) were males, and 42.6% (697) were females. There was no statistically significant distribution depending on sex between the samples of the two periods (p = 0.078).

Assessment of Nutrition Status and Weight Gain
Regarding the body mass index, the present study revealed that about a half of males 53.4% of the pre-pandemic sample and 50.4% from the pandemic sample, were normal weight. However, a large percentage of males were overweight or obese, 44.6% and 47.9%, respectively. The majority of the females were normal weight (69.9% both samples, pre-and pandemic), and 21.1% and 21.8% were overweight or obese, respectively ( Table 1). The mean BMI was 26.81 ± 6.17 kg/m 2 , higher in males (25.37 ± 4.03 kg/m 2 ) than females (22.58 ± 3.88 kg/m 2 ) (p = 0.59). Regarding the weight gain during the pandemic, the vast majority of the men (50.5%, n = 277) and almost half of the women (45.3%, n = 170) reported a weight gain (p = 0.123). The mean weight gain was 5.16 ± 4.07 kg for males and 4.14 ± 3.97 kg for females (p = 0.006) (mean weight gain of the sample was 5.11 ± 3.52 kg. 27% of the respondents reported a weight loss. The weight loss was 4.29 ± 4.12 kg in males and 3.84 ± 2.98 in females (p = 0.003) (mean weight loss 4.01 ± 4.17 kg). We calculated the respondents' weight gain depending on their body mass index. The results revealed that IT workers who were overweight or obese gained more weight than normal weight workers ( Table 2).

Diet and Changes
Diet was estimated as the number of meals consumed per day, intake of vegetables and fruit, and fast-food intake. In addition, the respondents were asked if they changed their diet during the pandemic.
The majority of the computer workers ate three meals per day as recommended. However, the study results showed that a significant percentage of respondents had only two meals per day, a higher percentage in the pandemic period (Table 3). The main meal was eaten at home, during the pandemic period, as a result of remote work. However, in the pre-pandemic period, a significant percentage of computer workers, especially men (48.3%), ate the main meal in town ( Figure 1). The main meal was eaten at home, during the pandemic period, as a result of remote work. However, in the pre-pandemic period, a significant percentage of computer workers, especially men (48.3%), ate the main meal in town ( Figure 1).

Figure 1. Where did you eat the main meal
Vegetables were eaten in small amounts in both periods. Apparently, the results of our study showed no increase in vegetable intake (Table 4). Fruits were consumed in a higher amount than vegetables. Most of the workers ate 1-2 fruits per day regardless of the investigated period. The present study revealed a higher fast-food intake among males than females (p < 0.001) during the pre-pandemic period. A high percentage of males consumed fast food 2 or 3 times per week. During the pandemic, the results of our study showed an increase in fast food consumption both in males and females (p = 0.228) ( Table 5).  Vegetables were eaten in small amounts in both periods. Apparently, the results of our study showed no increase in vegetable intake (Table 4). Fruits were consumed in a higher amount than vegetables. Most of the workers ate 1-2 fruits per day regardless of the investigated period. The present study revealed a higher fast-food intake among males than females (p < 0.001) during the pre-pandemic period. A high percentage of males consumed fast food 2 or 3 times per week. During the pandemic, the results of our study showed an increase in fast food consumption both in males and females (p = 0.228) ( Table 5). Furthermore, the respondents were asked if they changed their diet during the pandemic, to which 52.9% (n = 290) of males and 62.4% (n = 234) of females IT workers (p = 0.005) answered affirmatively. The majority of the pandemic sample of computer workers (80%, n = 740) declared that the food was homemade, and the rest (19.8%, n = 183) of the respondents answered that the main meal was ordered.

Alcohol Consumption
We estimated alcohol consumption. Our results showed that alcohol consumption decreased during the pandemic. The majority of men (77.6%) did not drink during the pandemic, and 9.9% drank 3-5 times per week in comparison with 24.4% in the prepandemic period ( Table 6). Most of the females were abstainers (84.8% in the pre-pandemic period versus 87.5% during the pandemic period)

Physical Activity
Males performed a higher amount of physical activity than females in both the studied periods (pre-pandemic and pandemic). The study revealed a high percentage of males (30.5% during the pre-and 61.2% during the pandemic) that were not meeting the physical activity recommendations. Females had a higher level of sedentary behaviors, both in pre-pandemic (71.1%) and in remote working periods (70.45%) ( Table 7). In addition, the study estimated the level of physical activity depending on the number of steps in those who had devices or applications on the smartphone. In the pandemic period, the study revealed a low interest in step counting, a higher percentage of respondents did not/have or did not count their steps, and a decrease in the number of the steps, both in males and females (Table 8).

Hours Spent in Front of the Computer (Screen Time)
The results of our study showed that over half of the males (52.7%) and females (52.5%) IT workers stayed more than 8 h in front of the computer or driving a car before the pandemic. During the pandemic, the percentage increased, 84.7% of males and 85.1% of females were involved in teleworking and sedentary behaviors (Figure 2).
In addition, during the pandemic, the present study results showed that IT workers spent more hours in front of computers, more males than females (p < 0.001). In total, 27.9 % (n = 153) of the male and 17.6% (n = 66) of the female respondents reported that they had exceeded the regular program during this pandemic period, with an average of hours of 3.52 ± 4.29 for females and of 3.05 ± 2.09 for males, (p > 0.05).
Teleworking was the method of work applied during the pandemic. The majority of the respondents, 90.5% (n = 496) males and 89.1% (n = 334) females, worked from home during the pandemic (p = 0.505).

Hours Spent in Front of the Computer (Screen Time)
The results of our study showed that over half of the males (52.7%) and females (52.5%) IT workers stayed more than 8 h in front of the computer or driving a car before the pandemic. During the pandemic, the percentage increased, 84.7% of males and 85.1% of females were involved in teleworking and sedentary behaviors (Figure 2). In addition, during the pandemic, the present study results showed that IT workers spent more hours in front of computers, more males than females (p < 0.001). In total, 27.9 % (n = 153) of the male and 17.6% (n = 66) of the female respondents reported that they had exceeded the regular program during this pandemic period, with an average of hours of 3.52 ± 4.29 for females and of 3.05 ± 2.09 for males, (p > 0.05).
Teleworking was the method of work applied during the pandemic. The majority of the respondents, 90.5% (n = 496) males and 89.1% (n = 334) females, worked from home during the pandemic (p = 0.505).

Stress and Social Isolation
Social isolation was estimated during the pandemic period. The majority of the male respondents -89.4%, and 90.4% of the female respondents (p = 0.659) declared that they needed to see their friends during the pandemic. On a scale from 1 to 10, males suffered

Stress and Social Isolation
Social isolation was estimated during the pandemic period. The majority of the male respondents -89.4%, and 90.4% of the female respondents (p = 0.659) declared that they needed to see their friends during the pandemic. On a scale from 1 to 10, males suffered less than females from social isolation (5.29 ± 2.37 in males vs. 6.01 ± 2.17 in females, p < 0.001).
Regarding the self-assessment of stress due to the job assignment, the majority of the respondents perceived their stress as moderate during both periods (Table 9).

Sleep
The results of our study showed that only 34.5% of the respondents before the pandemic period and 35.4% during the pandemic had the recommended amount of sleep. More workers slept less than six hours during the pandemic, at least once per week. In addition, more than half of the IT workers felt tired in the morning, meaning they had poor sleep quality (Table 10).

Factors Associated with Weight Gain
We ran a multiple regression to predict the weight gain of the computer workers during the pandemic period depending on gender, age, BMI, diet change, and more hours of work in front of the computer. These variables significantly predicted the weight gain F (5.917) = 42.965, p < 0.000, R 2 = 42.965. According to our results, age, BMI, diet change, and more hours of work were statistically significantly associated with the weight gain of the respondents (p < 0.05) ( Table 11).

Discussion
The study aimed to estimate the lifestyle of computer workers, such as the number of hours spent on work using the computers, nutrition status, physical activity, diet, sleep, perceived stress, stress isolation before the pre-pandemic period and during the pandemic period. Sedentary lifestyles are spreading worldwide because of a lack of available spaces for exercise, increased occupational sedentary behaviors such as office work, and the increased penetration of television and video devices. Consequently, associated health problems are on the rise. A sedentary lifestyle increases all-cause mortality and the risks of cardiovascular diseases (CVD), diabetes mellitus (DM), hypertension (HTN), and cancers (breast, colon, colorectal, endometrial, and epithelial ovarian cancer). This has been consistently documented in the literature [1,23]. The present study showed that more men (50.5%) during the pandemic than women gained weight (45.3%). The results are consistent with other studies that showed an increase in body weight during the pandemic [24]. The weight gain was associated with an increase in screen time and decreased physical activity [25]. Less IT workers in the present study lost weight (4.01 ± 4.17 kg). Other studies from literature evidenced that weight loss during the pandemic was associated with healthy eating changes (increased consumption of vegetables, fruits, cereals, fish, water, and a decrease in the intake of discretionary foods during the quarantine compared to other respondents [26]. Our study showed a low intake of vegetables and fruits and an increase in fast food intake. However, future studies are needed to better estimate other food groups' consumption during the pandemic and the relationship with the nutrition status among Romanian IT workers.
Studies from the literature showed that the pandemic had a negative effect on physical activity by decreasing it and increasing screen time [27]. The present study revealed that 84.7% of male and 85.1% of female IT workers during the pandemic spent more than 8 h in front of the computers in comparison with 52.7% of the males and 52.5% of the females in the pre-pandemic period. The multivariate analyses showed that the increased time spent in front of the computers was a risk factor for weight gain.
As our results showed, the reduced amount of physical activity among IT workers before the pandemic was also recorded during the pandemic. We estimated the physical activity as time spent; counting the steps; the percentage of the sample; comparison with pre-pandemic IT workers. These results are similar to other studies that showed a decreased level of physical activity [28,29]. Besides the reduction in PA, the study revealed an increased time in sedentary behaviors, like working at the computer.
The WHO/FAO report recommends 400 g edible fruit and vegetables per day as a population-wide intake goal for the prevention of non-communicable diseases (NCDs) and the prevention and alleviation of several micronutrient deficiencies. This translates to roughly five portions per day (two portions of fruits and three portions of vegetables (potatoes, sweet potatoes, cassava, and other starchy roots are not classified as fruits or vegetables) [30]. In European countries, the level of fruit and vegetable intake is still poor. The results of our study showed that over 70% of the IT workers in the pre-pandemic period consumed 1-2 portions of fruits (72.8% for males and 72.1% for females). However, during the pandemic period, the fruit intake was lower (51% for males and 56% for females). The present study revealed that vegetable consumption was insufficient during both periods (44.3 vs. 39.6% for males and 46.6% vs. 44.5% for females). However, these intakes were higher than in other young Romanian populations, as previous studies showed [31]. Other studies undertaken during the pandemic on different European populations showed either an increase in vegetable and fruit intake (18.5% and 15.2%) [32] or a decrease in these food groups.
The intake of fast-food increased during the pandemic period, consumption twice per week, from 15.7% (in pre-pandemic) to 20.0% (in pandemic) of the respondents (p < 0.001). Data from the literature are inconsistent. Some studies from the literature showed that fast-food consumption was increased [31]. Most studies however showed a decrease in fastfood intake [33]. Fast food, processed food, and junk food contribute to obesity, diabetes, heart attacks, strokes, dementia, and cancer. However, many do not realize the strong causative role of an unhealthy diet in mental illness [34].
Both alcohol consumption and smoking can potentially increase vulnerability to SARS-CoV-2 infection and worsen the clinical course of COVID-19. Chronic alcohol exposure has a complex and adverse effect on host response [35]. Stress is a prominent risk factor for the onset and maintenance of alcohol misuse. The reported stress among computer workers was moderate in both studied periods. The results of our study showed that the majority of IT workers did not consume alcohol, before and during the pandemic. A decrease in alcohol consumption was seen in the men, 24.4% of male IT workers drank 3-5 times per week before the pandemic versus 9.9% of male IT workers during the pandemic period (p = 0.004). These results are inconsistent with other studies that showed an increase in alcohol consumption, with a higher tendency to drink among alcohol addicts [24]. Another study revealed a decrease in alcohol consumption associated with the Mediterranean diet during the lockdown [36,37].
Poor sleep quality may lead to weight gain, worsened mood, increased stress, depression and anxiety, daytime fatigue, and poor concentration [19,38]. The recommended amount of sleep per night is 7-9 h for adults. The present study revealed that 33.6 % before the pandemic and 41.7% IT workers during the pandemic slept once or twice per week less than six hours, and over a half reported poor quality of sleep during both periods (they felt Nutrients 2022, 14, 1202 12 of 14 tired in the morning). Studies from the literature showed that excessive screen time could lead to poor sleep quality [39,40].
The present study was the first research that assessed the lifestyle of computer workers from Romania and is an essential study in a lacking data field; consequently, conclusions can be drawn.
Given the fact of the increased demand for computer workers, the study emphasized the need for the implementation of educational and public health measures among this population group to prevent chronic diseases. Public health policies and benefits offered by companies (flexible hours, gym memberships, financial support, catering contracts with nutritional restaurants, healthy "in office" kitchens) are necessary to encourage an active lifestyle. An active lifestyle can prevent weight gain and improve sleep and mood. Dietary changes are recommended, increasing the intake of vegetables, seeds, and fruits, with the assistance of professional nutritional support (training and nutritional specialists' appointments).

Limitation
The main limitation of the study was the self-reported questionnaire. Given the data collection period, during the pandemic, and the population group, we considered remote data collection on specific professional social network sites of computer workers as feasible. Due to this data collection method, we succeeded in having a large sample of respondents. Another limitation of our study was that we could not reach the same sample of IT workers during the pandemic as before the pandemic (the questionnaires were anonymous). However, the two samples were comparable, without statistical differences regarding the age and sex distribution. Regardless of the interest of IT workers in counting their steps, future studies are necessary to use an objective measurement of physical activity (accelerometer, pedometer) and with standardized tools for stress. Future studies are needed to understand better the outcomes of home confinement during the pandemic.

Conclusions
The present study investigated the lifestyle of computer workers from Romania, an important population group with high sedentary behaviors. As a consequence of the pandemic, teleworking further increased screen time and decreased physical activity, leading to weight gain in some of the respondents. The study also revealed poor sleep quality among the majority of respondents, with at least one weeknight with less than 6 h of sleep.
Regardless of the significant number of working hours in front of computers, most IT workers perceived their work stress as only moderate. Moreover, our study revealed that almost all workers suffered from social isolation during the pandemic, especially women.
In addition, diet changes have occurred, with a considerable growth in the consumption of homemade food; however, the intake of vegetables and fruit remained low. Public health and corporation policies and interventions are required to encourage a healthy lifestyle and avoid workers' chronic diseases.