Next Article in Journal
Choline Intake as Supplement or as a Component of Eggs Increases Plasma Choline and Reduces Interleukin-6 without Modifying Plasma Cholesterol in Participants with Metabolic Syndrome
Next Article in Special Issue
Alteration, Reduction and Taste Loss: Main Causes and Potential Implications on Dietary Habits
Previous Article in Journal
Socio-Demographic Characteristics and Body Weight Perceptions of Study Participants Benefitting Most from the Feel4Diabetes Program Based on Their Anthropometric and Glycaemic Profile Changes
Previous Article in Special Issue
Impacts of the COVID-19 Pandemic on Food Security and Diet-Related Lifestyle Behaviors: An Analytical Study of Google Trends-Based Query Volumes
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Associations between Changes in Health Behaviours and Body Weight during the COVID-19 Quarantine in Lithuania: The Lithuanian COVIDiet Study

Faculty of Public Health, Medical Academy, Lithuanian University of Health Sciences, 44307 Kaunas, Lithuania
Department of Nutrition and Food Science, Campus of Melilla, University of Granada, 52001 Melilla, Spain
Biomedical Research Centre, Institute of Nutrition and Food Technology (INYTA) ‘José Mataix’, University of Granada, 18071 Granada, Spain
Author to whom correspondence should be addressed.
Nutrients 2020, 12(10), 3119;
Original submission received: 15 September 2020 / Revised: 2 October 2020 / Accepted: 9 October 2020 / Published: 13 October 2020
(This article belongs to the Special Issue Nutrition within and beyond Corona Virus)


The COVID-19 quarantine has caused significant changes in everyday life. This study aimed to evaluate the effect of the quarantine on dietary, physical activity and alcohol consumption habits of Lithuanians and the association between health behaviours and weight changes. An online cross-sectional survey was carried out among individuals older than 18 years in April 2020. The self-administered questionnaire included health behaviour and weight change data. Altogether 2447 subjects participated in the survey. Almost half of the respondents (49.4%) ate more than usual, 45.1% increased snacking, and 62.1% cooked at home more often. Intake of carbonated or sugary drinks, fast food and commercial pastries decreased, while consumption of homemade pastries and fried food increased. A decrease in physical activity was reported by 60.6% of respondents. Every third (31.5%) respondent, more often those already with overweight, gained weight. Multivariate logistic regression analysis showed that the higher odds of weight gain were associated with females, older age, increased consumption of sugary drinks, homemade pastries and fried food, eating more than usual, increased snacking, decreased physical activity and increased alcohol consumption. Our data highlighted the need for dietary and physical activity guidelines to prevent weight gain during the period of self-isolation, especially targeting those with overweight and obesity.

1. Introduction

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease (COVID-19), first appeared in December 2019 in Wuhan, China, and quickly spread worldwide. On 30 January 2020, the Director-General of the World Health Organization (WHO) declared the outbreak of COVID-19 to be a public health emergency of international concern and a set of recommendations was issued [1]. In Lithuania, the first case of COVID-19 was diagnosed on 28 February 2020. As the number of cases was increasing rapidly, the Lithuanian Government decided to declare quarantine from 16 to 30 March [2]. This was extended several times and ended on 16 June. All public indoor and outdoor gatherings were prohibited. Educational institutions began to work remotely. Shops excluding grocery shops and pharmacies were closed. Restaurants and bars were also closed, leaving the option for food takeaway. This situation forced people to cook at home. Social isolation disrupted daily routine. Increased sedentary behaviour and screen time, and limited food availability and choice could lead to changes in nutrition habits and weight gain [3]. Quarantine caused many economic, social and health problems. Some workers were forced to take unpaid vacation. They lost income and felt uncertain [4]. Stress is related to higher energy intake, ‘food craving’, unhealthy dietary patterns high in fat and sugar and higher alcohol consumption, which can lead to weight gain and increased risk of obesity [5,6]. Physical inactivity may also contribute to weight and body fat gain, causing various cardio-metabolic disorders [7]. Recent studies showed that obesity is associated with more severe COVID-19 illness and outcomes [8,9]. Existing evidence suggests that an unhealthy diet leads to chronic inflammation and impaired defence against viruses [10]. WHO experts developed specific recommendations on nutrition and physical activity for quarantine isolation [11]. However, in this unprecedented time with many economic, social, and psychological problems, it could be complicated to follow such recommendations. Our study aimed to investigate the effect of the COVID-19 quarantine on dietary, physical activity and alcohol consumption habits of Lithuanians and the association between health behaviour and weight changes.

2. Materials and Methods

2.1. Study Sample and Data Collection

This study is a part of the international COVIDiet project led by researchers from the University of Granada, Spain [12]. The data collected in Lithuania were analysed. The online cross-sectional survey was carried out among individuals older than 18 years. Age was the only inclusion/exclusion criterion. The survey began on 14 April, a month after COVID-19 quarantine started in Lithuania, and lasted two weeks. A self-administered anonymous web-based questionnaire was developed to collect data. The link to the questionnaire was distributed using social media such as Facebook, web-pages of some institutions, which agreed to participate, social networking sites, and emails with the aim of reaching the greatest number of participants from all municipalities of Lithuania. In total, 2447 individuals (2149 females and 298 males) participated in the Lithuanian survey.

2.2. Questionnaire and Variables

The study questionnaire included 44 questions regarding various sociodemographic criteria, the Mediterranean Diet Adherence Screen (MEDAS) [12,13], and changes in eating behaviours during the quarantine: snacking and intake of some foods with possible answers: ‘Higher’, ‘Lower’ or ‘As usual’; perception of eating more during the quarantine with possible answers ‘Yes’ or ‘No’; changes in physical activity with possible answers: ‘It has increased’, ‘It has decreased’, ‘It remains as usual’, ‘I do not practice physical activity’; and changes in alcohol consumption with possible answers: ‘Yes, my intake of alcoholic beverages is higher’, ‘No, my intake of alcoholic beverages is lower’, ‘My intake of alcoholic beverages remains as usual’. The question about weight change was: ‘Have you gained weight during the quarantine’ with possible answers: ‘Yes’, ‘No’, ‘I don’t know’. By weight change, the respondents were grouped in those who gained weight (‘Yes’) and others (‘No’ or ‘I don’t know’). Self-reported current weight and height were used to calculate body mass index (BMI) as weight in kilograms divided by height in meters squared. According to WHO guidelines, overweight was defined as BMI 25–29 kg/m2 and obesity as BMI ≥ 30 kg/m2 [14].
The respondents were grouped into three age groups: 18–35 years, 36 50 years and 51 years and older. By education level, respondents were categorized into two groups: with university education and lower level of education.

2.3. Data Analysis

Data analysis was performed using the statistical package IBM SPSS Statistics for Windows, Version 20.0 (IBM Corp.: Armonk, NY, USA, released 2011). The categorical variables were presented as percentages and compared using the chi-square test and z test with Bonferroni correction. Univariate and multivariate logistic regression analysis was used to evaluate the associations between weight gain during COVID-19 quarantine (dependent variable) and social factors, nutrition, physical activity and alcohol consumption habits.

2.4. Ethical Issues

The international COVIDiet study was approved by the Research Ethics Committee of the University of Granada (1526/CEIH/2020) and was registered in ( Additionally, the Lithuanian study was approved by the Bioethics Centre of the Lithuanian University of Health Sciences. No personal data was collected and participation was voluntary and anonymous. The participants were informed about the objectives of the study.

3. Results

The main characteristics of the study population are presented in Table 1. The majority of the participants were females, 18–35 years old and having a university education. Prevalence of overweight was 27.8% and obesity 12.4%. Every third respondent (31.5%) gained weight during the quarantine.
A considerable number of participants reported that they changed their eating habits during the quarantine (Table 2). Almost half of the respondents (49.4%) answered that they ate more than usual. A similar proportion of participants (45.1%) increased snacking. However, 62.1% of respondents replied that they cooked at home more often than before quarantine. Every fifth participant (20.6%) increased consumption of fried food. Fast food became less popular, as 41.3% of respondents decreased its consumption. More than one-third of participants (37.7%) reported that they increased consumption of homemade pastries. Intake in carbonated and sugary drinks was decreased by 19.4% of respondents and consumption of commercial pastries by 26%. More people reduced read meat and fish consumption than increased, while a higher proportion of participants increased fruit and vegetable consumption than decreased.
Most of the participants (69.9%) declared that their intake of alcoholic beverages (wine, beer, strong alcoholic drinks) remained the same as before the COVID-19 quarantine. The proportion of those who increased (14.2%) and decreased (15.9%) consumption of alcohol was similar. A large number of participants (60.6%) reported that they reduced physical activity (Table 2).
The changes in health behaviours differed according to changes in body weight (Table 3). Diet of those who gained weight changed in a more negative direction compared to those who reported no changes or did not notice the increase in body weight. More weigh-gaining respondents reduced fruit and vegetable consumption and increased red meat, carbonated or sugary drinks, pastries, fast food and fried food consumption. The majority of participants (84.3%) whose weight increased declared that they ate more compared to 33.4% of individuals without changes in body weight. More weigh-gaining people increased snacking and cooked more often than before quarantine. Increase in alcohol consumption was reported by every fifth participant (20.9%) who gained weight, and every tenth (11.2%), who did not. A large proportion of weight-gaining respondents (85.2%) decreased their physical activity during quarantine (Table 3).
The weight gain was associated with BMI of participants. Those with higher BMI gained weight more often compared to those having normal BMI (Figure 1).
The binary univariate logistic regression showed that women were more likely to gain weight compared to men (Table 4). No associations were found with the age and education of respondents. The odds of weight gain were higher for those who decreased consumption of fresh fruits and vegetables and increased consumption of red meat, carbonated or sugary drinks, pastries, snacks, fast or fried food and ate more than usual. Increased alcohol consumption and decreased physical activity were also related to higher odds of weight gain. In multivariate logistic regression analyses, the association of weight gain with increased intake of carbonated or sugary drinks, homemade pastries and fast food, increased snacking, eating more than usual, decreased physical activity and increased alcohol consumption remained statistically significant. The odds of weight gain also increased with age.

4. Discussion

Our study demonstrated that Lithuanians changed their eating habits during the quarantine. Almost half of the respondents reported that they ate more than usual, increased snacking and cooked more often at home. The intake of foods changed in positive and negative directions. More respondents increased than reduced fruit and vegetable consumption. The intake of carbonated and sugary drinks, fast food, and commercial pastries decreased; however, the consumption of homemade pastries and fried food increased. Negative changes in eating, physical activity, and alcohol consumption habits were associated with weight gain which was reported by one third of respondents.
Our data support previous findings showing that restrictions during COVID-19 increased the number of main meals, frequency of cooking, and snacking [12,15,16,17,18]. Spending more time on cooking offers the possibilities to eat healthier, try new recipes and enjoy food without rushing. To remind people of the most important principles of healthy nutrition, WHO experts developed recommendations on food and nutrition during self-quarantine [1]. However, restrictions during COVID-19 pandemic decreased the availability of some foods. People were urged to stay at home, all restaurants and bars were closed, and only some of them offered food takeaway. Ordering food online was overloaded [12]. The variety of food products in grocery stores has declined [12,19]. A Spanish study highlighted that people reported difficulties of finding meat in the supermarkets and grocery stores, which could be related to a decrease in consumption of meat during quarantine [12]. At the beginning of the quarantine, people experienced panic and uncertainty, which led to extra buying of all long-lasting food products and caused a shortage of grain and some other products in grocery stores [19].
Social isolation with or without loneliness and boredom can be associated with a negative impact on nutrition habits, obesity, physical activity, and poor physical and mental health [6,15,18,20,21]. Some authors showed that high-level of depression was related to poor diet, increased intake of saturated fat, energy-dense and salty foods [6,22]. Women who tended to act impulsively in a stressing environment were more likely to eat more candies [23]. People with anxiety consumed snacks 2.45 times more often [24]. The studies performed during the COVID-19 pandemic revealed more frequent and increased consumption of sweets, biscuits and cakes, decreased intake of fruits and vegetables and increased consumption of frozen and canned foods, more frequent cooking and eating out of control [15,16,17,18,24,25]. On the other hand, some positive changes such as decreased consumption of processed meat, carbonated or sugary drinks and increased consumption of fresh fruits and vegetables, fish, legumes and white meat were identified [12,16]. Our data support the previous findings that both positive and negative changes in dietary habits were observed during the quarantine.
It is well documented that physical activity has many positive health effects [26]. Together with the changes in diet, a strong impact of quarantine on physical activity was observed. Many studies showed that all levels of physical activity decreased and sitting or screen time increased [12,15,16,17,18,22,24]. Few studies found opposite results, showing an increase of physical activity during COVID-19 crisis [16,27]. These differences may be related to different governmental policy on movement restrictions during this period.
The data on alcohol consumption is controversial. Some studies reported an increase in alcohol consumption and higher drinking tendency among alcohol addicts [17,25], while other studies reported decrease in binge drinking and alcohol consumption [12,15,16,22]. A British study found decreased alcohol consumption only in the younger cohort [27]. Our study demonstrated similar proportions of those who increased and decreased alcohol consumption.
Evidence suggests that even a small positive energy balance over time is sufficient to cause weight gain in many individuals [28]. Our data showed that those respondents who gained weight were more likely to change their diet in an unhealthy direction, decrease physical activity, and increase alcoholic beverages consumption than those who did not report changes in body weight. Furthermore, more respondents with higher BMI at the beginning of quarantine gained weight compare to those having a normal weight.
Previous studies have also reported weight gain during the quarantine [16], providing estimated weight changes from 1.6 kg to 2.07 kg in different countries [16,17,18,24,25]. People following an unhealthy diet had 4.5 times higher odds of weight increase [24]. Weight gain was associated with higher consumption of most foods: meat, dairy, fast foods, and even fruits, vegetables and legumes [25]. An Italian study found no associations between BMI and healthy food intake, while higher consumption of junk food such as snacks, dressings, sweet beverages and sweets was associated with higher BMI [16]. Lower exercise, consumption of snacks, unhealthy foods, cereals, and sweets were associated with significant weight gain in adults with obesity a month after the beginning of the quarantine [18].
The latest studies report that patients with obesity are at increased risk of complications of COVID-19 infection and higher mortality rates [8,29]. As there is not yet effective treatment and vaccination against COVID-19 and there may be new virus outbreaks, healthy eating and physical activity promotion should be incorporated in government initiatives to reduce the negative effects of the COVID-19 pandemic [30]. Encouraging people to follow a balanced diet, especially targeting those with obesity, could help to maintain an effective immune system and may provide protection against infections and other diseases.
The strengths of our study include the online survey, which allowed us quickly to reach a sufficiently large sample of the population from different municipalities of the whole country during the quarantine. Additionally, we used the COVIDiet questionnaire prepared by researchers from the University of Granada for the international study so we will be able to compare our data with other countries in the future. Several limitations of our study should be mentioned for the accurate interpretation of its results. First, we used non-random sampling to reach participants. The majority of respondents were women and people with higher education. The higher participation of women was also reported by other researchers [12,18]. However, our study covered all municipalities of Lithuania and a large age interval. Furthermore, we used self-reported online survey data which may be less reliable and biased. BMI was calculated from self-reported data on weight and height, which could lead to underestimation of overweight and obesity. A question about weight loss was not included in the questionnaire. Finally, we did not collect data on employment status and stress during the quarantine. Stress could impact eating and alcohol consumption habits.

5. Conclusions

COVID-19 quarantine caused both positive and negative changes in nutrition, physical activity, and alcohol consumption habits in the Lithuanian population. Weight gain was associated with unhealthy dietary changes, decreased physical activity, and increased alcohol consumption. Our data highlighted the need for investigations into which dietary and physical activity guidelines might be appropriate to help counteract potentially negative impacts of COVID-19 on health behaviour and body weight.

Author Contributions

V.K. and J.P. made substantial contributions to conception and design of the manuscript. V.K. and L.B. carried out statistical analysis. V.K., L.B. and J.P. were involved in drafting of the manuscript. C.R.-P. reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.


We thank the administrative team of the international COVIDiet survey-the AGR-141 research group: Celia Rodríguez-Pérez, Esther Molina-Montes, Vito Verardo, Reyes Artacho, Belén García-Villanova, Eduardo Jesús Guerra-Hernández and Maria Dolores Ruíz-López, Department of Nutrition and Food Science, University of Granada, Spain, for sharing COVIDiet questionnaire.

Conflicts of Interest

The authors declare no conflict of interest.


  1. World Health Organization: Coronavirus Disease (COVID-19) Advice for the Public. 2020. Available online: (accessed on 14 August 2020).
  2. Government of the Republic of Lithuania: Quarantine Announced throughout the Territory of the Republic of Lithuania (Attached Resolution). 2020. Available online: (accessed on 18 August 2020).
  3. Balanzá-Martínez, V.; Atienza-Carbonell, B.; Kapczinski, F.; De Boni, R.B. Lifestyle behaviours during the COVID-19—Time to connect. Acta Psychiatr. Scand. 2020, 141, 399–400. [Google Scholar] [CrossRef] [PubMed]
  4. Enterprise Lithuania. COVID-19 News for Business: Impact on Business. 2020. Available online: (accessed on 14 August 2020).
  5. Yau, Y.H.C.; Potenza, M.N. Stress and eating behaviors. Minerva Endocrinol. 2013, 38, 255–267. [Google Scholar] [PubMed]
  6. Anton, S.D.; Miller, P.M. Do negative emotions predict alcohol consumption, saturated fat intake, and physical activity in older adults? Behav. Modif. 2005, 29, 677–688. [Google Scholar] [CrossRef] [PubMed]
  7. Wiklund, P. The role of physical activity and exercise in obesity and weight management: Time for critical appraisal. J. Sport Health Sci. 2016, 5, 151–154. [Google Scholar] [CrossRef][Green Version]
  8. Kalligeros, M.; Shehadeh, F.; Mylona, E.K.; Benitez, G.; Beckwith, C.G.; Chan, P.A.; Mylonakis, E. Association of obesity with disease severity among patients with COVID-19. Obesity 2020, 28, 1200–1204. [Google Scholar] [CrossRef]
  9. Lighter, J.; Phillips, M.; Hochman, S.; Sterling, S.; Johnson, D.; Francois, F.; Stachel, A. Obesity in patients younger than 60 years is a risk factor for COVID-19 hospital admission. Clin. Infect. Dis. 2020, 71, 896–897. [Google Scholar] [CrossRef][Green Version]
  10. Rogero, M.M.; Calder, P.C. Obesity, inflammation, toll-like receptor 4 and fatty acids. Nutrients 2018, 10, 432. [Google Scholar] [CrossRef][Green Version]
  11. WHO. Food and Nutrition Tips during Self-Quarantine. 2020. Available online: (accessed on 16 August 2020).
  12. Rodríguez-Pérez, C.; Molina-Montes, E.; Verardo, V.; Artacho, R.; García-Villanova, B.; Guerra-Hernández, E.J.; Ruíz-López, M.D. Changes in dietary behaviours during the COVID-19 outbreak confinement in the Spanish COVIDiet Study. Nutrients 2020, 12, 1730. [Google Scholar] [CrossRef]
  13. Martínez-González, M.A.; García-Arellano, A.; Toledo, E.; Salas-Salvado, J.; Buil-Cosiales, P.; Corella, D.; Covas, M.I.; Schröder, H.; Arós, F.; Gómez-Gracia, E.; et al. A 14-item Mediterranean diet assessment tool and obesity indexes among high-risk subjects: The PREDIMED trial. PLoS ONE 2012, 7, e43134. [Google Scholar] [CrossRef][Green Version]
  14. World Health Organization. Obesity: Preventing and Managing the Global Epidemic. Report on a WHO Consultation; Report No. 894; WHO: Geneva, Switzerland, 2000. [Google Scholar]
  15. Ammar, A.; Brach, M.; Trabelsi, K.; Chtourou, H.; Boukhris, O.; Masmoudi, L.; Bouaziz, B.; Bentlage, E.; How, D.; Ahmed, M.; et al. 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]
  16. 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]
  17. Deschasaux-Tanguy, M.; Druesne-Pecollo, N.; Esseddik, Y.; de Edelenyi, F.S.; 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. Available online: (accessed on 16 August 2020).
  18. Pellegrini, M.; Ponzo, V.; Rosato, R.; Scumaci, E.; Goitre, I.; Benso, A.; Belcastro, S.; Crespi, C.; De Michieli, F.; Ghigo, E.; et al. Changes in weight and nutritional habits in adults with obesity during the “lockdown” period caused by the COVID-19 virus emergency. Nutrients 2020, 12, 2016. [Google Scholar] [CrossRef] [PubMed]
  19. Vallianatos, M.; Azuma, A.M.; Gilliland, S.; Gottlieb, R. Food access, availability, and affordability in 3 Los Angeles communities, project CAFE, 2004–2006. Prev. Chronic Dis. 2010, 7, A27. [Google Scholar]
  20. Leigh-Hunt, N.; Bagguley, D.; Bash, K.; Turner, V.; Turnbull, S.; Valtorta, N.; Caan, W. An overview of systematic reviews on the public health consequences of social isolation and loneliness. Public Health 2017, 152, 157–171. [Google Scholar] [CrossRef][Green Version]
  21. Cacioppo, J.T.; Hawkley, L.C.; Norman, G.J.; Berntson, G.G. Social isolation. Ann. N. Y. Acad. Sci. 2011, 123, 17–22. [Google Scholar] [CrossRef]
  22. Rolland, B.; Haesebaert, F.; Zante, E.; Benyamina, A.; Haesebaert, J.; Franck, N. Global changes and factors of increase in caloric/salty food, screen, and substance use, during the early COVID-19 containment phase in France: A general population online survey. J. Med. Internet Res. 2020, 6, e19630. [Google Scholar] [CrossRef]
  23. Becker, K.D.; Fischer, S.; Smith, G.T.; Miller, J.D. The influence of negative urgency, attentional bias, and emotional dimensions on palatable food consumption. Appetite 2016, 100, 236–243. [Google Scholar] [CrossRef]
  24. AlMughamis, N.; AlAsfour, S.; Mehmood, S. Poor eating habits and predictors of weight gain during the COVID-19 quarantine measures in Kuwait: A cross sectional study. F1000Research 2020, 9, 914. Available online: (accessed on 18 August 2020). [CrossRef]
  25. Sidor, A.; Rzymski, P. Dietary choices and habits during COVID-19 lockdown: Experience from Poland. Nutrients 2020, 12, 1657. [Google Scholar] [CrossRef]
  26. Daskalopoulou, C.; Stubbs, B.; Kralj, C.; Koukounari, A.; Prince, M.; Prina, A.M. Physical activity and healthy ageing: A systematic review and meta-analysis of longitudinal cohort studies. Ageing Res. Rev. 2017, 38, 6–17. [Google Scholar] [CrossRef][Green Version]
  27. Bann, D.; Villadsen, A.; Maddock, J.; Hughes, A.; Ploubidis, G.; Silverwood, R.; Patalay, P. Changes in the Behavioural Determinants of Health during the Coronavirus (COVID-19) Pandemic: Gender, Socioeconomic and Ethnic Inequalities in 5 British Cohort Studies. MedRxiv 2020. Available online: (accessed on 18 August 2020).
  28. Hills, A.P.; Byrne, N.M.; Lindstrom, R.; Hill, J.O. ‘Small changes’ to diet and physical activity behaviors for weight management. Obes. Facts 2013, 6, 228–238. [Google Scholar] [CrossRef] [PubMed]
  29. Simonnet, A.; Chetboun, M.; Poissy, J.; Raverdy, V.; Noulette, J.; Duhamel, A.; Labreuche, J.; Mathieu, D.; Pattou, F.; Jourdain, M.; et al. High prevalence of obesity in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) requiring invasive mechanical ventilation. Obesity (Silver Spring) 2020, 28, 1195–1199. [Google Scholar] [CrossRef] [PubMed]
  30. Naja, F.; Hamadeh, R. Nutrition amid the COVID-19 pandemic: A multi-level framework for action. Eur. J. Clin. Nutr. 2020, 4, 1117–1121. [Google Scholar] [CrossRef] [PubMed][Green Version]
Figure 1. Association between body mass index (BMI) of the participants and weight gain during the quarantine (%). * p < 0.05 compared with normal BMI (z test with Bonferroni correction).
Figure 1. Association between body mass index (BMI) of the participants and weight gain during the quarantine (%). * p < 0.05 compared with normal BMI (z test with Bonferroni correction).
Nutrients 12 03119 g001
Table 1. Characteristics of the study population (%).
Table 1. Characteristics of the study population (%).
 Male 29812.2
Age groups
Body mass index
 <25 kg/m2145859.8
 25–29 kg/m267927.8
 ≥30 kg/m230312.4
Weight changes during the quarantine
 No changes/didn’t know 167668.5
Table 2. Changes in health behaviours during the quarantine (%).
Table 2. Changes in health behaviours during the quarantine (%).
Health BehavioursChanges
IncreasedDecreasedRemains as Usual
Food intake
 Red meats, hamburgers, sausages12.217.969.9
 Carbonated and/or sugary beverages (soda, cola, tonic, bitter)8.519.472.0
 Commercial (non-homemade) pastries such as cookies, custards, sweets18.926.055.2
 Homemade pastries such as cookies, custards, sweets or cakes37.711.550.8
 Fast food6.741.351.9
 Fried food20.68.371.1
Eating habits
 Cooking more often than before the quarantine62.1 (yes)1.3 (no, less often)36.5 (as usual)
 Eat more than usual49.4 (yes)-50.6 (as usual)
Other lifestyle habits
 Alcoholic beverages consumption14.215.969.9
 Physical activity14.360.619.3
Table 3. The proportion of participants who reported changes in health behaviours by changes in weight (%).
Table 3. The proportion of participants who reported changes in health behaviours by changes in weight (%).
Changes in Health BehavioursWeight Changep-Value *
GainedNo Changes/Doesn’t Know
Food intake
 Vegetables decreased16321.120312.10.001
 Fruits decreased14418.721612.90.001
 Red meats, hamburgers, sausages increased15720.41418.40.001
 Carbonated and/or sugary beverages increased11615.0935.50.001
 Commercial pastries increased24131.322113.20.001
 Homemade pastries increased40552.551730.80.001
 Fast food increased9512.3704.20.001
 Fried food increased25132.625315.10.001
Eating habits
 Snacking increased56673.453732.00.001
 Cooking more often than before the quarantine54871.197258.00.001
 Eat more than usual65084.356033.40.001
Other lifestyle habits
 Alcoholic beverages consumption increased16120.918711.20.001
 Physical activity decreased65785.296757.70.001
* z test with Bonferroni correction was used for multiple comparisons.
Table 4. Odds Ratios (OR) for the likelihood of weight gain by socio-demographic variables and changes in health behaviours during the quarantine.
Table 4. Odds Ratios (OR) for the likelihood of weight gain by socio-demographic variables and changes in health behaviours during the quarantine.
VariablesUnivariate AnalysisMultivariate Analysis
OR (95% CI)p-ValueOR (95% CI)p-Value
 Male 1 1
 Female1.37 (1.04–1.80)0.0251.52 (1.08–2.14)0.015
Age groups
 18–351 1
 36–501.14 (0.94–1.39)0.1731.36 (1.06–1.73)0.014
 ≥511.08 (0.86–1.35)0.4831.80 (1.35–2.39)0.001
 University1 1
 Lower1.18 (0.93–11.42)1.1721.20 (0.96–1.51) 0.113
 Intake of vegetables decreased *1.94 (1.55–2.44)0.0011.12 (0.82–1.53)0.484
 Intake of fruits decreased *1.55 (1.23–1.95)0.0011.12 (0.81–1.52)0.530
 Intake of red meat increased *2.78 (2.17–3.56)0.0011.03 (0.75–1.40)0.871
 Intake of carbonated or sugary drinks increased *3.01 (2.26–4.02)0.0011.44 (1.01–2.06)0.049
 Intake of commercial pastries increased *2.99 (2.43–3.68)0.0011.20 (0.92–1.56)0.184
 Intake of homemade pastries increased *2.48 (2.08–2.95)0.0011.56 (1.25–1.95)0.001
 Intake of fast food increased *3.22 (2.33–4.44)0.0011.62 (1.09–2.43)0.018
 Intake of fried food increased *2.71 (2.22–3.32)0.0011.15 (0.89–1.50)0.287
 Snacking increased *5.85 (4.84–7.08)0.0011.55 (1.20–2.01)0.001
 Eating more than usual *10.70 (8.60–13.23)0.0015.68 (4.30–7.51)0.001
 Physical activity decreased *4.22 (3.38–5.27)0.0013.24 (2.53–4.16)0.001
 Alcohol consumption increased *2.10 (1.66–2.64)0.0011.47 (1.11–1.95)0.008
* Reference variable – no change in respective health behaviour or change in the opposite direction; OR—odds ratio; CI—confidence interval.

Share and Cite

MDPI and ACS Style

Kriaucioniene, V.; Bagdonaviciene, L.; Rodríguez-Pérez, C.; Petkeviciene, J. Associations between Changes in Health Behaviours and Body Weight during the COVID-19 Quarantine in Lithuania: The Lithuanian COVIDiet Study. Nutrients 2020, 12, 3119.

AMA Style

Kriaucioniene V, Bagdonaviciene L, Rodríguez-Pérez C, Petkeviciene J. Associations between Changes in Health Behaviours and Body Weight during the COVID-19 Quarantine in Lithuania: The Lithuanian COVIDiet Study. Nutrients. 2020; 12(10):3119.

Chicago/Turabian Style

Kriaucioniene, Vilma, Lina Bagdonaviciene, Celia Rodríguez-Pérez, and Janina Petkeviciene. 2020. "Associations between Changes in Health Behaviours and Body Weight during the COVID-19 Quarantine in Lithuania: The Lithuanian COVIDiet Study" Nutrients 12, no. 10: 3119.

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop