How Can Lockdown Influence Eating Habits? The Spanish Case During the COVID Pandemic
Faculty of Psychology and Health Sciences, Madrid Open University (UDIMA), Ctra. de la Coruña, km 38.500, 28400 Collado Villalba, Madrid, Spain
*
Author to whom correspondence should be addressed.
Obesities 2025, 5(4), 84; https://doi.org/10.3390/obesities5040084
Submission received: 10 October 2025
/
Revised: 21 November 2025
/
Accepted: 25 November 2025
/
Published: 27 November 2025
Abstract
Background and Objectives: Previous research shows that stress can alter eating habits. This study analyzed the impact of COVID-19 confinement on eating behaviors and weight in Spanish adults, as well as related factors. Methods: A total of 2834 adults (69.3% women, Mean age: 41.36) completed an online questionnaire assessing eating habits, weight, and sociodemographic variables. Results: Strict lockdown in Spain was linked to a general worsening of eating habits, particularly increased food intake and weight gain. Risk factors for less healthy eating and weight gain included being female (p < 0.001), under 35 years old (p < 0.001), overweight or obese (p < 0.001), caring for minors (p = 0.002), and experiencing nervousness or anxiety (p < 0.001). Conversely, maintaining pre-confinement eating habits and weight was more common among men (p < 0.001), individuals aged 50 years or older (p < 0.001), those with normal or underweight BMI (p < 0.001), those working outside the home (p < 0.013), and those without minors in their care (p = 0.001). Conclusions: Prolonged lockdowns associated with high stress may negatively influence diet and weight. Prevention strategies should therefore promote healthy eating during such periods, particularly targeting groups at higher risk of worsening habits and weight gain.
1. Introduction
The COVID-19 pandemic required an extraordinarily rapid process of adaptation for both individuals and governments. Since the detection of the first cases, the World Health Organization has estimated that more than 1.1 billion people worldwide have contracted the disease and over 6.9 million have died as a result, although these figures may be underestimated due to variations in testing strategies, reporting criteria, and delays in surveillance systems [1]. The sheer scale and speed of the pandemic forced countries to implement unprecedented containment measures. In Spain, strict home confinement became a central strategy to slow transmission, leading to profound and immediate changes in daily routines, mobility, and lifestyle behaviors.
Given the rapid transmission of COVID-19 and the difficulties in preventing and treating this type of virus, strict containment measures were adopted in Spain to curb its spread, transforming the lives of citizens in many ways. Although confinement proved effective during the first wave of the pandemic, people’s response to such a stressful and prolonged situation has been linked to multiple physical and psychological consequences, such as increased levels of stress and anxiety [2,3]. Likewise, it appears to have modified lifestyle and daily eating habits, which led various organizations to recommend maintaining a healthy diet during confinement [4,5]. This change in eating habits as a consequence of confinement has been observed in adult populations in various countries [6,7], due in part to overeating, which led to weight gain [8,9], especially among those who were previously obese [10,11], who seem to show hypersensitivity to non-nutritive cues and desensitization to normal satiety processes [12].
A growing body of international research has shown that lockdown periods significantly affected dietary patterns and body weight across diverse populations. Studies conducted in Italy, Denmark, Poland, Tunisia, and the United States reported declines in diet quality, higher consumption of ultra-processed foods and snacks, greater snacking frequency, and alterations in meal timing during confinement [8,9,11,13,14]. These shifts were frequently accompanied by weight gain, particularly among individuals with pre-existing overweight or obesity, who may have been more reactive to external eating cues and less responsive to physiological satiety signals [6,10,15,16]. Reduced opportunities for physical activity, increased sedentary time, and disruptions in food access likely contributed to this pattern.
In addition to dietary changes, sociodemographic and psychological factors appear to have shaped the impact of lockdowns across countries. Younger adults tended to experience more substantial alterations in their eating habits, including irregular meal schedules and increased intake, whereas older adults were more likely to maintain stable routines [12,13]. Caregiving duties further intensified these challenges: individuals caring for dependent children reported more disorganized routines, higher stress, and greater changes in food consumption [17]. At the same time, psychological distress increased sharply worldwide. Systematic reviews identified anxiety levels ranging from 6.3% to 50.9% and depression from 14.6% to 48.3% [18], while a large meta-analysis reported combined prevalences of 28% for anxiety, 27% for stress, 22% for depression, and 33% for post-traumatic stress symptoms [19]. Stress- and anxiety-related eating—characterized by increased intake of palatable, carbohydrate-rich foods—was widely observed [20,21,22].
Given this background, the aim of the present study was threefold: (a) to examine the impact of confinement due to the COVID-19 pandemic on the eating habits of the adult Spanish population—specifically, whether eating habits were modified in general, as well as the nutritional quality and quantity of intake, and whether mealtimes were modified; (b) to analyze the impact of confinement on participants’ weight; and (c) to study which variables were related to possible changes in eating habits during confinement.
2. Materials and Methods
2.1. Participants
The sample consisted of 2834 adults aged 19 to 76 years (mean: 41.36; SD: 10.5), of whom 69.3% were women. A total of 32.5% were up to 35 years old, 44.7% were between 36 and 49 years old, and 22.8% were 50 years old or older. Likewise, 59.1% of the participants were normal weight, 28% overweight, 9% obese, and 3.9% underweight. Participation in the study was voluntary and anonymous, as participants were not asked to provide any identifying information on the form that they completed.
2.2. Instruments
An online questionnaire developed ad hoc for the present study was administered to collect information about participants’ weight and modifications in eating habits during the period of confinement (variety and nutritional quality of intake, quantity eaten, mealtimes, and the influence of anxiety on these habits), as well as sociodemographic data (age, sex, weight and height for calculating the body mass index (BMI), experiencing symptoms compatible with COVID-19 or living with people presenting such symptoms, having worked outside the home during the study period, and having children in their care). The presence of anxiety was assessed through a specific item asking participants whether they had felt nervous or anxious during the confinement period (yes/no).
2.3. Procedure
After obtaining authorization from the Ethics Committee of the Faculty of Health Sciences and Education of the Madrid Open University, an online form was sent to the entire educational community. It was expressly stated that participation was voluntary and that the information collected would be confidential, in accordance with Organic Law 3/2018, of December 5, on the Protection of Personal Data and Guarantee of Digital Rights, as responses would be coded using an identification number and therefore remain anonymous. Only those who provided informed consent were able to access the form. No participants were paid or received any academic benefit for their participation. The participation period covered 19–31 May 2020.
2.4. Data Analysis
Descriptive and inferential analyses were performed using cross-sectional methodology. To determine the distribution of the sample according to the sociodemographic variables evaluated, as well as their behavior during confinement with respect to health habits, percentages were calculated. Likewise, to analyze relationships between the variables under study, the chi-square statistic was used, as well as Cramer’s V to determine the strength of the relationships found. The analysis was carried out using version 20.0 of the SPSS software package.
3. Results
3.1. Eating Habits and Weight of Participants During Confinement
A total of 73.7% of the participants maintained their eating habits or reported that these had changed toward more positive habits during confinement. The same trend was observed regarding the quality and nutritional variety of the food consumed, which appeared to have been maintained or even improved in 81.4% of participants. With respect to mealtimes, these were maintained during confinement in 63.1% of the sample. Conversely, 43.8% of respondents increased the amount of food they ate, which may explain why 37.6% of those who checked their weight on a scale after confinement found that their weight had increased. The extent of the weight increase during confinement is shown in Table 1. In addition, 45% of those who reported having experienced anxiety during confinement considered that their eating habits had worsened as a result.
3.2. Factors Associated with General Eating Habits During Confinement
As shown in Table 2, several variables appeared to be related to individuals’ overall eating habits during confinement (amount and type of food consumed, eating style, etc.). Specifically, men and those over 50 years of age maintained their pre-confinement eating habits to a greater extent (p < 0.001), whereas younger individuals and women showed a greater tendency to worsen these habits (p < 0.001). Regarding BMI, participants who maintained or even improved their eating habits were primarily those with normal weight or underweight, whereas those who were obese or overweight worsened their habits to a greater extent (p < 0.001). Likewise, those who did not work outside the home during confinement, those with children in their care, and those who experienced nervousness or anxiety during this period reported that they maintained or worsened their eating habits to a greater extent than those not in these circumstances, who more frequently reported maintaining or improving their eating habits.
3.3. Factors Associated with Dietary Variety and Nutritional Quality During Confinement
When specifically assessing the variety and nutritional quality of participants’ diets during confinement, males (p < 0.001), individuals over 50 years of age (p < 0.001), those who did not experience anxiety (p < 0.001), and participants with normal weight or underweight (p < 0.001) reported the highest percentage of maintained diet quality during this period. In contrast, females (p < 0.001), younger participants (p < 0.001), those experiencing anxiety (p < 0.001), and overweight or obese individuals (p < 0.001) were more likely to report a worsening of their diet during confinement, as shown in Table 3. Additionally, participants who worked outside the home (p < 0.001) or experienced symptoms compatible with COVID-19 (p < 0.048) were more likely to report improvements in diet quality, compared with those who did not have such symptoms or did not leave home for work, who tended to maintain their diet quality.
3.4. Factors Associated with the Amount of Food Consumed During Confinement
When specifically analyzing the amount of food ingested during confinement, men (p < 0.001), participants over 50 years of age (p < 0.000), and those who were normal-weight or underweight (p < 0.001), as well as individuals who did not leave home for work (p < 0.013) or did not experience anxiety (p < 0.001), were more likely to maintain their usual intake. In contrast, women (p < 0.001), younger participants (p < 0.001), those who worked outside the home (p < 0.013), caregivers of minors (p < 0.001), overweight and obese participants (p < 0.001), and those experiencing anxiety (p < 0.001) were more likely to increase their intake, as shown in Table 4. Although only a small proportion of participants decreased their intake, this group included a higher percentage of men, individuals under 35 years of age, underweight participants, and those without minors in their care.
3.5. Factors Associated with Mealtime Changes During Confinement
Confinement affected not only participants’ eating habits, including what and how much they ate, but also their mealtimes, as shown in Table 5. Women (p < 0.001), participants under 35 years of age (p < 0.001), caregivers of minors (p < 0.031), and those experiencing anxiety during confinement (p < 0.001) were the most likely to change their mealtime schedules during this period.
3.6. Factors Associated with Weight During Confinement
Confinement also affected participants’ weight. Women (p < 0.001), older participants (p < 0.001), individuals who were overweight or obese (p < 0.000), those who experienced anxiety (p < 0.001), participants who reported symptoms compatible with COVID-19 (p < 0.004), those who lived with someone showing such symptoms (p < 0.001), and caregivers of minors (p < 0.001) were more likely to report weight gain during this period. In contrast, underweight and normal-weight participants were more likely to maintain their weight (p < 0.001). Likewise, although only a small proportion of participants lost weight, this group included a higher percentage of men (p < 0.001), individuals under 35 years of age (p < 0.001), those who did not experience anxiety, and those without children in their care (p < 0.001), as shown in Table 6.
4. Discussion
The aim of this study was to examine the impact of confinement due to the COVID-19 pandemic on the eating habits and weight of the adult Spanish population, and to analyze the variables related to possible changes in eating habits during this period.
First, regarding the impact on eating habits, the results reflect a general worsening of the nutritional quality of the diet in the Spanish population during confinement, as observed in other countries [6], but contrary to findings from another study in Spain based on the consumption of different foods [23]. There was also a significant increase in food intake during meals, with percentages similar to those found in studies conducted in other countries [9,11,13,14], perhaps due to the increased practice of snacking between meals detected during confinement [11]. In addition, there was a greater tendency to store food, especially canned and ultra-processed products, due to their ease of storage and preparation [16]. This may partly explain the changes in the quality and quantity of intake detected, although a study suggests that variables such as sex, age, and changes in income are associated with higher consumption of sugary drinks and fast foods during the COVID-19 pandemic [24].
Second, with regard to the impact on weight, the results indicate that the modifications in eating behavior observed during confinement translated into a noticeable increase in body weight in a substantial proportion of participants, a pattern consistent with findings reported in studies conducted during the same period [8,25]. This agreement with previous research reinforces the idea that prolonged restrictions on mobility and changes in daily structure tend to generate similar behavioral responses across different populations. The increase in weight may not only reflect the rise in intake observed in the sample but also the reduction in opportunities for physical activity resulting from staying at home, the closure of public spaces and sports facilities, and the difficulty in maintaining pre-pandemic routines [16,26,27]. Such disruptions have been widely associated with a progressive decline in energy expenditure and a greater likelihood of weight gain [20,22,25,28]. In addition, confinement may have intensified sedentary behaviors —including increased screen time, teleworking, and prolonged indoor stays— which previous research has linked to adverse metabolic consequences and higher susceptibility to weight gain. Psychological factors may also have contributed: heightened stress, uncertainty, and emotional vulnerability during the pandemic are known to influence appetite regulation, preference for high-calorie foods, and the frequency of snacking.
Taken together, these findings suggest that the observed weight increase was likely the result of an interaction between dietary changes, reduced physical activity, emotional responses, and environmental constraints inherent to lockdown conditions. This multifactorial explanation highlights the importance of integrated public health strategies that simultaneously address eating behaviors and physical activity during future scenarios involving prolonged restrictions.
Third, in relation to variables associated with changes in eating habits and weight, several sociodemographic and personal factors were identified. As in other populations [7], the youngest participants—those under 35 years of age—were the ones whose overall eating habits worsened and whose mealtimes changed to a greater extent, although the quality of their diet improved, perhaps due to the greater adherence to the Mediterranean diet observed in this age group in other countries [8]. Likewise, their intake and weight were reduced to a greater extent than in other age groups. In contrast, older participants were those who maintained all the eating habits analyzed to a greater extent, showing a lesser impact of confinement on their diet, although those over 36 years of age experienced greater weight gain, as reported in other studies [11]. Although the overall trend was toward a decline in dietary quality, there are distinct profiles whose eating habits were able to improve due to specific protective conditions during confinement, such as increased time available to plan and cook, heightened health awareness, more structured family routines, and greater control over the food environment [8,11].
In relation to BMI, obese participants worsened their eating habits during confinement to a greater extent than the other groups, as found in other studies in the Spanish population [21]. They also increased their intake and modified their mealtimes more markedly, followed by overweight participants. Consequently, these groups showed the greatest increase in weight, consistent with previous findings [10,11].
Emotional factors were also relevant. As expected from the literature, participants who experienced nervousness or anxiety during confinement saw their eating habits worsen and their weight increase to a greater extent, in line with studies linking higher intake with greater anxiety during this period [29]. Numerous studies have corroborated how emotions influence eating behavior [21,30]; indeed, psychosocial stress appears to affect body weight through biological, behavioral, and psychological mechanisms [31,32]. In particular, stress- or anxiety-induced eating can lead to increased food intake —especially of palatable, high-glycemic foods—as well as more frequent snacking [20,22,28], a pattern observed in various populations during the pandemic [16,33,34]. Similarly, studies conducted with individuals with eating disorders show that patients with restrictive eating disorders exhibited poorer family functioning and greater eating psychopathology after the pandemic compared to previous periods, although results differed by age and diagnosis [35,36]. Overall, anxiety appears to function as a vulnerability factor that shapes dietary responses in situations of prolonged stress.
Having experienced symptoms compatible with COVID-19 during confinement also seems to have influenced eating habits and weight, as those who reported symptoms were more likely to improve their eating habits and the nutritional quality of their intake, and to lose weight. This could be related to the gastrointestinal symptoms associated with the disease [37] and the specific diets recommended to address them. The only differences between those who lived with someone with COVID-19 symptoms and those who did not were related to weight, which was reduced in the former and maintained or increased in the latter, possibly because those living with symptomatic individuals may also have contracted the disease.
Likewise, participants who had children in their care during confinement—a situation likely to increase stress, especially when combined with teleworking—reported greater deterioration in their eating habits, including increased intake, later mealtimes, and irregular schedules, which may have contributed to weight gain [17]. By contrast, those without childcare responsibilities maintained or even improved their eating habits and weight status. Furthermore, anxiety experienced during the confinement period was significantly associated with poorer dietary quality, particularly among individuals with low physical activity, supporting the idea that emotional distress and caretaking burden can combine to worsen eating behaviors [38].
Work circumstances also impacted eating habits and weight. Participants who continued working outside the home and were able to preserve pre-pandemic daily routines tended to exhibit better overall eating habits and higher nutritional quality of the diet, suggesting that structured schedules and external time cues may help to maintain more stable lifestyle patterns. However, in our sample, this more favorable profile coexisted with an increase in intake, which could be partly explained by stress related to the risk of contagion outside the home and longer or more demanding workdays. Recent studies have shown that changes in work arrangements during the pandemic, including working from home, were associated with both perceived improvements in diet and, paradoxically, higher caloric intake, weight gain, and diet-related health problems, largely mediated by increased sedentary time and psychological strain [39,40].
This study allowed us to explore the impact of COVID-19 confinement on eating habits and body weight in the Spanish adult population. It also examined the sociodemographic and personal factors that may have influenced the differential effects of confinement, some of which had not been studied previously. The results are consistent with previous research on the impact of lockdown on eating habits, which has been associated with mental health, gender, and socioeconomic status [24].
These findings support the development of prevention strategies for future prolonged confinements or periods of high stress. Public health campaigns should specifically promote healthy eating among populations most affected by confinement, discouraging overeating and informing about the risks of excessive consumption of hypercaloric foods during periods of reduced physical activity and challenges in weight management [14]. Overall, these results underscore the importance of implementing social and communication strategies that promote healthy eating, particularly during health emergency scenarios [14,24].
Among the limitations of the present study are a possible social desirability bias and recall bias related to health habits. These were partly mitigated by requesting anonymous participation and using objective measures, such as body weight assessed with a scale. Although the data reflect participants’ subjective experiences, these perceptions are valuable because they influence self-assessed quality of life and, consequently, the promotion or maintenance of healthy habits. The use of a convenience sample limits the generalizability of the results to the Spanish population, and international comparisons must consider cultural and contextual factors. Additionally, the sample included a disproportionately higher number of women and participants with overweight or obesity, which may limit the applicability of findings to more gender-balanced or weight-diverse populations. The cross-sectional design of the study does not allow causal inferences or the assessment of the temporal stability of the observed changes. Future research should employ longitudinal designs to evaluate whether dietary changes during confinement are maintained, intensified, or reversed over time. Data collection was conducted online and relied on retrospective self-reports, potentially introducing recall bias and affecting the accuracy of the information. Furthermore, the ad hoc questionnaire included data on anxiety status without using a validated measure, which may reduce the reliability of anxiety-related results. Finally, this study did not examine the effects of socioeconomic variables such as education, income, and employment status, which can influence eating habits, access to healthy food, and stress management during lockdown. As the study focused on demographic, psychological, and contextual variables, future research should incorporate socioeconomic variables to explore their modulating role in the relationship between stress, diet, and weight changes in crisis situations.
5. Conclusions
Strict COVID-19 confinement in Spain was associated with a general worsening of eating habits, particularly an increase in food intake and a consequent rise in weight among a considerable proportion of the population. The findings indicate that certain demographic and personal characteristics acted as risk factors for these changes, particularly being female, being under 35 years of age, being overweight or obese, caring for dependent children, and experiencing nervousness or anxiety during this period. In contrast, protective variables that favored the maintenance of pre-confinement habits included being male, being 50 years of age or older, having a normal or low weight, working outside the home, and not having dependent minors. These results underscore the heterogeneity of responses to confinement and highlight how specific circumstances modulated its impact on diet, routines, and weight.
Based on these results, several avenues for future research can be proposed. First, longitudinal studies are needed to determine whether the changes observed during confinement were temporary or whether they persisted once mobility restrictions were lifted. Such studies could clarify the temporal stability of the dietary patterns identified and help determine the factors that predict their maintenance or reversal. Second, it would be useful to incorporate validated instruments to assess psychological variables—particularly anxiety and stress—to more precisely determine their relationship with eating behaviors and weight trajectories during prolonged stress situations. Third, future research should include socioeconomic factors such as education level, income, and employment conditions to better understand how inequalities shape access to healthy foods, the ability to maintain routines, and the adoption of coping strategies during crises.
More detailed analyses of family composition, work arrangements, and the interaction between caretaking responsibilities and psychological strain could also provide a better understanding of which subgroups are most vulnerable to lifestyle deterioration during lockdowns. Finally, experimental and intervention studies could help design and evaluate targeted strategies aimed at preventing overeating and weight gain during periods of reduced mobility, particularly in those groups identified as being at higher risk. Taken together, the present findings reinforce the need to develop prevention plans for future health emergencies that integrate nutritional, psychological, and social components, with special attention to the populations most affected by confinement.
Author Contributions
Conceptualization, J.I.B., M.J.G.-C., M.F.R.-A. and E.I.-S.; methodology, J.I.B. and M.J.G.-C.; validation, J.I.B. and M.J.G.-C.; formal analysis, J.I.B. and M.J.G.-C.; investigation, J.I.B., M.J.G.-C., M.F.R.-A. and E.I.-S.; data curation, J.I.B. and M.J.G.-C.; writing—original draft preparation J.I.B., M.J.G.-C. and M.F.R.-A.; writing—review and editing, J.I.B., M.J.G.-C., M.F.R.-A. and E.I.-S.; supervision, J.I.B., M.J.G.-C., M.F.R.-A. and E.I.-S. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the Ethics Committee of the Faculty of Health Sciences and Education of the Madrid Open University (protocol code PSI18052025 and 18 May 2020)” for studies involving humans.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper.
Data Availability Statement
The data presented in this study are openly available in OSF Registries at https://doi.org/10.17605/OSF.IO/HJCDQ.
Conflicts of Interest
The authors declare no conflicts of interest.
Abbreviations
The following abbreviations are used in this manuscript:
| ns | Non-significant difference |
| df | Degree of freedom |
References
- World Health Organization. WHO Coronavirus (COVID-19) Dashboard. Geneva: World Health Organization. 2024. Available online: https://covid19.who.int/ (accessed on 13 November 2025).
- Brooks, S.K.; Webster, R.K.; Smith, L.E.; Woodland, L.; Wessely, S.; Greenberg, N.; Rubin, G.J. The psychological impact of quarantine and how to reduce it: Rapid review of the evidence. Lancet 2020, 395, 912–920. [Google Scholar] [CrossRef]
- Tracy, M.; Norris, F.H.; Galea, S. Differences in the determinants of posttraumatic stress disorder and depression after a mass traumatic event. Depress. Anxiety 2011, 28, 666–675. [Google Scholar] [CrossRef]
- Aranceta-Bartrina, J.; Partearroyo, T.; López-Sobaler, A.M.; Ortega, R.M.; Varela-Moreiras, G.; Serra-Majem, L.; Pérez-Rodrigo, C.; Collaborative Group for the Dietary Guidelines for the Spanish Population (SENC). Updating the Food-Based Dietary Guidelines for the Spanish Population: The Spanish Society of Community Nutrition (SENC) Proposal. Nutrients 2019, 11, 2675. [Google Scholar] [CrossRef]
- Sociedad Española de Nutrición Comunitaria. Compra Saludable y Comprometida Durante el Periodo de Pandemia y Recuperación. Available online: http://www.nutricioncomunitaria.org/es/noticia/comprar-productos-de-proximidad (accessed on 27 October 2020).
- Alhusseini, N.; Alqahtani, A. COVID-19 Pandemic’s Impact on Eating Habits in Saudi Arabia. J. Public Health. Res. 2020, 9, 1868. [Google Scholar] [CrossRef]
- Huber, B.C.; Steffen, J.; Schlichtiger, J.; Brunner, S. Altered nutrition behavior during COVID-19 pandemic lockdown in young adults. Eur. J. Nutr. 2020, 60, 2593–2602. [Google Scholar] [CrossRef]
- 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]
- 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]
- de Luis Román, D.A.; Izaola, O.; Primo Martín, D.; Gómez Hoyos, E.; Torres Torres, B.; López Gómez, J.J. Effect of lockdown for COVID-19 on self-reported body weight gain in a sample of obese patients. Nutr. Hosp. 2020, 37, 1232–1237. [Google Scholar] [CrossRef]
- Sidor, A.; Rzymski, P. Dietary Choices and Habits during COVID-19 Lockdown: Experience from Poland. Nutrients 2020, 12, 1657. [Google Scholar] [CrossRef]
- López-Moreno, M.; López, M.T.I.; Miguel, M.; Garcés-Rimón, M. Physical and Psychological Effects Related to Food Habits and Lifestyle Changes Derived from COVID-19 Home Confinement in the Spanish Population. Nutrients 2020, 12, 3445. [Google Scholar] [CrossRef]
- Giacalone, D.; Frøst, M.B.; Rodríguez-Pérez, C. Reported Changes in Dietary Habits During the COVID-19 Lockdown in the Danish Population: The Danish COVIDiet Study. Front. Nutr. 2020, 7, 592112. [Google Scholar] [CrossRef]
- Hasni, Y.; Nouira, S.; El Fekih, H.; Saafi, W.; Bedhiafi, S.; Karrai, Y.; Hammami, R.; Alouan, L.; Chaieb, M. Impact of COVID-19 lockdown on dietary habits and weight among Tunisian adults. Tunis. Med. 2025, 103, 152–157. [Google Scholar] [CrossRef]
- 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, 14, 210–216. [Google Scholar] [CrossRef]
- 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, 19, 100250. [Google Scholar] [CrossRef]
- Loezar-Hernández, M.; Briones-Vozmediano, E.; Ronda-Pérez, E.; Otero-García, L. Juggling during Lockdown: Balancing Telework and Family Life in Pandemic Times and Its Perceived Consequences for the Health and Wellbeing of Working Women. Int. J. Environ. Res. Public Health 2023, 20, 4781. [Google Scholar] [CrossRef]
- Xiong, J.; Lipsitz, O.; Nasri, F.; Lui, L.M.W.; Gill, H.; Phan, L.; Chen-Li, D.; Iacobucci, M.; Ho, R.; Majeed, A.; et al. Impact of COVID-19 pandemic on mental health in the general population: A systematic review. J. Affect. Disord. 2020, 277, 55–64. [Google Scholar] [CrossRef]
- Arora, T.; Grey, I.; Östlundh, L.; Lam, K.B.H.; Omar, O.M.; Arnone, D. The prevalence of psychological consequences of COVID-19: A systematic review and meta-analysis of observational studies. J. Health Psychol. 2020, 27, 805–824. [Google Scholar] [CrossRef]
- Block, J.P.; He, Y.; Zaslavsky, A.M.; Ding, L.; Ayanian, J.Z. Psychosocial stress and change in weight among US adults. Am. J. Epidemiol. 2009, 170, 181–192. [Google Scholar] [CrossRef]
- Braden, A.; Musher-Eizenman, D.; Watford, T.; Emley, E. Eating when depressed, anxious, bored, or happy: Are emotional eating types associated with unique psychological and physical health correlates? Appetite 2018, 125, 410–417. [Google Scholar] [CrossRef]
- Torres, S.J.; Nowson, C.A. Relationship between stress, eating behavior, and obesity. Nutrition 2007, 23, 887–894. [Google Scholar] [CrossRef]
- Pérez-Rodrigo, C.; Gianzo Citores, M.; Hervás Bárbara, G.; Ruiz-Litago, F.; Casis Sáenz, L.; Aranceta-Bartrina, J.; Val, V.A.; López-Sobaler, A.M.; Martínez de Victoria, E.; Ortega, R.M.; et al. Cambios en los hábitos alimentarios durante el periodo de confinamiento por la pandemia COVID-19 en España. Rev. Esp. Nutr. Comunitaria 2020, 26, 17. [Google Scholar]
- Horna-Campos, O.; Gómez, N.; Mazzei Pimentel, M.; Anigstein, M.S.; Gongora-Jercic, G.; Cid-Vera, J.; Jacques-Aviño, C.; Villegas Ríos, R. Factors associated with the increased consumption of sugary beverages and fast-food during Chile’s first COVID-19 lockdown. Medwave 2025, 25, e3022. [Google Scholar] [CrossRef]
- Zupo, R.; Castellana, F.; Sardone, R.; Sila, A.; Giagulli, V.A.; Triggiani, V.; Cincione, R.I.; Giannelli, G.; De Pergola, G. Preliminary Trajectories in Dietary Behaviors during the COVID-19 Pandemic: A Public Health Call to Action to Face Obesity. Int. J. Environ. Res. Public Health 2020, 17, 7073. [Google Scholar]
- Martinez-Ferran, M.; de la Guía-Galipienso, F.; Sanchis-Gomar, F.; Pareja-Galeano, H. Metabolic Impacts of Confinement during the COVID-19 Pandemic Due to Modified Diet and Physical Activity Habits. Nutrients 2020, 12, 1549. [Google Scholar] [CrossRef]
- Rodgers, R.F.; Lombardo, C.; Cerolini, S.; Franko, D.L.; Omori, M.; Fuller-Tyszkiewicz, M.; Linardon, J.; Courtet, P.; Guillaume, S. The impact of the COVID-19 pandemic on eating disorder risk and symptoms. Int. J. Eat. Disord. 2020, 53, 1166–1170. [Google Scholar]
- Isasi, C.R.; Parrinello, C.M.; Jung, M.M.; Carnethon, M.R.; Birnbaum-Weitzman, O.; Espinoza, R.A.; Penedo, F.J.; Perreira, K.M.; Schneiderman, N.; Sotres-Alvarez, D.; et al. Psychosocial stress is associated with obesity and diet quality in Hispanic/Latino adults. Ann. Epidemiol. 2015, 25, 84–89. [Google Scholar] [CrossRef]
- Sinisterra Loaiza, L.I.; Vázquez Belda, B.; Miranda López, J.M.; Cepeda, A.; Cardelle Cobas, A. Hábitos alimentarios en la población gallega durante el confinamiento por la COVID-19. Nutr. Hosp. 2020, 37, 1190–1196. [Google Scholar]
- Macht, M. How emotions affect eating: A five-way model. Appetite 2008, 50, 1–11. [Google Scholar] [CrossRef]
- Harvey, T.; Troop, N.A.; Treasure, J.L.; Murphy, T. Fear, disgust, and abnormal eating attitudes: A preliminary study. Int. J. Eat. Disord. 2002, 32, 213–218. [Google Scholar] [CrossRef]
- Sahle, B.W.; Breslin, M.; Sanderson, K.; Patton, G.; Dwyer, T.; Venn, A.; Gall, S. Association between depression, anxiety and weight change in young adults. BMC Psychiatry 2019, 19, 398. [Google Scholar] [CrossRef]
- Sánchez-Sánchez, E.; Ramírez-Vargas, G.; Avellaneda-López, Y.; Orellana-Pecino, J.I.; García-Marín, E.; Díaz-Jimenez, J. Eating Habits and Physical Activity of the Spanish Population during the COVID-19 Pandemic Period. Nutrients 2020, 12, 2826. [Google Scholar] [CrossRef]
- Díaz-Ureña, G.; Renghea, A.; Hernández, S.; Crespo, A.; Fernández-Martínez, E.; Iglesias-López, M.T. Nutritional habits and eating attitude in university students during the last wave of COVID-19 in Spain. Sci. Rep. 2024, 14, 25114. [Google Scholar] [CrossRef]
- Marchetto, C.; Criscuolo, M.; Croci, I.; Bucci, M.E.; Caramadre, A.; Castiglioni, M.C.; Vicari, S.; Zanna, V. Family functioning and eating psychopathology in developmental restrictive eating disorders after COVID-19 lockdown. Eat. Weight Disord. 2025, 30, 36. [Google Scholar] [CrossRef]
- Schlissel, A.C.; Richmond, T.K.; Eliasziw, M.; Leonberg, K.; Skeer, M.R. Anorexia nervosa and the COVID-19 pandemic among young people: A scoping review. J. Eat. Disord. 2023, 11, 122. [Google Scholar] [CrossRef]
- Aguila, E.J.T.; Cua, I.H.Y.; Fontanilla, J.A.C.; Yabut, V.L.M.; Causing, M.F.P. Gastrointestinal Manifestations of COVID-19: Impact on Nutrition Practices. Nutr. Clin. Pract. 2020, 35, 800–805. [Google Scholar] [CrossRef]
- Christofaro, D.G.D.; Tebar, W.R.; Silva, G.C.R.; Lofrano-Prado, M.C.; Botero, J.P.; Cucato, G.G.; Malik, N.; Hollands, K.; Correia, M.A.; Ritti-Dias, R.M.; et al. Anxiety is more related to inadequate eating habits in inactive than in physically active adults during COVID-19 quarantine. Clin. Nutr. ESPEN 2022, 51, 301–306. [Google Scholar] [CrossRef]
- Tiboni-Oschilewski, O.; Quispe-Lagos, L.A.; Hoffmann, R.; Wronski, J.; Roverso, T.; Bithas, G. Dietary habits during the COVID-19 pandemic: Are work arrangements part of the problem? Front. Sustain. Food Syst. 2022, 6, 961908. [Google Scholar] [CrossRef]
- Coşkun, M.G.; Öztürk, R.İ.; Tak, A.Y.; Sanlier, N. Working from home during the COVID-19 pandemic and its effects on diet, sedentary lifestyle, and stress. Nutrients 2022, 14, 4006. [Google Scholar] [CrossRef]
Table 1.
Participants’ eating habits and weight during confinement (n = 2834).
| Question About Eating Habits and Weight | Answer | (%) |
|---|---|---|
| Do you think your eating habits (type of food consumed, quantity, way of eating, etc.) have changed? | No, I think they have remained the same. | 41.4% |
| Yes, I think they have improved. | 32.3% | |
| Yes, I think they have worsened. | 26.3% | |
| Do you think the variety and nutritional quality of the food you have eaten have changed compared with before confinement? | No, I think the variety and quality have remained the same. | 45.6% |
| Yes, I think they have improved. | 35.8% | |
| Yes, I think they have gotten worse. | 18.6% | |
| Do you think that the amount of food you have eaten has changed compared with before confinement? | No, I think I have eaten the same amount as usual. | 39.3% |
| Yes, I think it has increased. | 43.8% | |
| Yes, I think it has decreased. | 16.9% | |
| Have your pre-confinement mealtimes changed substantially? | Yes. | 36.9% |
| No. | 63.1% | |
| Have you checked your weight on a scale to see whether it has changed compared with before confinement? | No, I have not checked. | 27.7% |
| Yes, and it has remained the same. | 26.4% | |
| Yes, and it has increased. | 29.0% | |
| Yes, and it has decreased. | 16.9% | |
| If you checked your weight on a scale, what change did you observe after confinement? | It decreased by more than 5 kg. | 5.4% |
| It decreased by 2 to 5 kg. | 8.0% | |
| It decreased by up to 2 kg. | 13.7% | |
| My weight did not change. | 35.3% | |
| It increased by up to 2 kg. | 22.0% | |
| It increased by 2 to 5 kg. | 15.6% | |
| It increased by more than 5 kg. | 0% | |
| What effect do you think the nervousness or anxiety you experienced had on your eating habits (amount of food eaten, number of daily meals, quality of food consumed, way of eating, etc.)? | I think my habits were not affected by it. | 33% |
| I think my habits worsened. | 33% | |
| I think my habits improved. | 6% | |
| I did not feel nervous or anxious. | 28% |
Table 2.
Factors associated with general eating habits during confinement (n = 2834).
| Variable | Category | Maintained (%) | Improved (%) | Worsened (%) | p | Cramer’s V |
|---|---|---|---|---|---|---|
| Sex | Male | 46.8 | 30.5 | 22.8 | 0.000 | 0.075 |
| Female | 39.1 | 33.0 | 27.9 | |||
| Age | 35 or younger | 35.7 | 35.0 | 29.3 | 0.000 | 0.077 |
| 36–49 | 42.2 | 30.1 | 27.6 | |||
| 50 or older | 48.1 | 32.5 | 19.5 | |||
| BMI | Underweight | 41.1 | 43.0 | 15.9 | 0.000 | 0.099 |
| Normal weight | 44.0 | 32.8 | 23.2 | |||
| Overweight | 39.0 | 31.2 | 29.9 | |||
| Obese | 29.1 | 29.1 | 41.7 | |||
| Work outside the home | Yes | 40.4 | 34.1 | 25.5 | 0.000 | 0.082 |
| No | 46.0 | 24.2 | 29.7 | |||
| Had COVID-19 symptoms | Yes | 33.9 | 40.3 | 25.8 | 0.004 | 0.063 |
| No | 42.3 | 31.3 | 26.4 | |||
| Cohabitant with COVID-19 sympt. | Yes | 38.2 | 35.4 | 26.4 | 0.427 | ns |
| No | 41.8 | 31.9 | 26.3 | |||
| With dependent children | Yes | 39.9 | 30.0 | 30.2 | 0.002 | 0.066 |
| No | 42.3 | 33.5 | 24.2 | |||
| Anxiety presence | Yes | 37.8 | 29.1 | 33.1 | 0.000 | 0.203 |
| No | 47.7 | 37.7 | 14.6 |
Note. ns = non-significant difference. BMI = body mass index. Values are expressed as percentages unless otherwise indicated.
Table 3.
Factors associated with the variety and nutritional quality of dietary intake during confinement (n = 2834).
Table 3.
Factors associated with the variety and nutritional quality of dietary intake during confinement (n = 2834).
| Variable | Category | Maintained (%) | Improved (%) | Worsened (%) | p | Cramer’s V |
|---|---|---|---|---|---|---|
| Sex | Male | 51.1 | 31.7 | 17.1 | 0.000 | 0.074 |
| Female | 43.2 | 37.6 | 19.2 | |||
| Age | 35 or younger | 41.2 | 38.3 | 20.5 | 0.000 | 0.069 |
| 36–49 | 45.5 | 34.4 | 20.0 | |||
| 50 or older | 52.1 | 35.1 | 12.8 | |||
| BMI | Underweight | 44.9 | 44.9 | 10.3 | 0.000 | 0.077 |
| Normal weight | 46.9 | 36.3 | 16.8 | |||
| Overweight | 44.7 | 34.8 | 20.5 | |||
| Obese | 38.9 | 31.2 | 30.0 | |||
| Work outside the home | Yes | 44.8 | 37.5 | 17.6 | 0.000 | 0.078 |
| No | 49.1 | 28.4 | 22.5 | |||
| Had COVID-19 symptoms | Yes | 40.9 | 42.3 | 16.8 | 0.048 | 0.046 |
| No | 46.2 | 35.1 | 18.8 | |||
| Cohabitant with COVID-19 symptoms | Yes | 43.6 | 37.9 | 18.6 | 0.723 | ns |
| No | 45.8 | 35.6 | 18.6 | |||
| With dependent children | Yes | 44.6 | 35.7 | 19.6 | 0.516 | ns |
| No | 46.2 | 35.9 | 18.0 | |||
| Anxiety presence | Yes | 41.8 | 34.1 | 24.1 | 0.000 | 0.188 |
| No | 52.2 | 38.8 | 9.0 |
Note. ns = non-significant difference. BMI = body mass index. Values are expressed as percentages unless otherwise indicated.
Table 4.
Factors associated with the amount of food consumed during confinement (n = 2834).
| Variable | Category | Maintained (%) | Increased (%) | Decreased (%) | p | Cramer’s V |
|---|---|---|---|---|---|---|
| Sex | Male | 41.4 | 38.5 | 20.1 | 0.000 | 0.077 |
| Female | 38.3 | 46.1 | 15.5 | |||
| Age | 35 or younger | 34.6 | 44.6 | 20.9 | 0.000 | 0.068 |
| 36–49 | 39.8 | 45.2 | 15.0 | |||
| 50 or older | 45.0 | 39.9 | 15.1 | |||
| BMI | Underweight | 47.7 | 29.9 | 22.4 | 0.000 | 0.085 |
| Normal weight | 42.4 | 41.1 | 16.5 | |||
| Overweight | 34.7 | 47.3 | 18.1 | |||
| Obese | 28.7 | 56.7 | 14.6 | |||
| Work outside the home | Yes | 38.0 | 44.6 | 17.4 | 0.013 | 0.055 |
| No | 44.9 | 40.2 | 15.0 | |||
| Had COVID-19 symptoms | Yes | 36.6 | 42.6 | 20.8 | 0.160 | ns |
| No | 39.6 | 43.9 | 16.5 | |||
| Cohabitant with COVID-19 symptoms | Yes | 37.9 | 41.1 | 21.1 | 0.148 | ns |
| No | 39.4 | 44.1 | 16.5 | |||
| With dependent children | Yes | 38.5 | 48.4 | 13.1 | 0.000 | 0.087 |
| No | 39.7 | 41.2 | 19.1 | |||
| Anxiety presence | Yes | 33.6 | 50.1 | 16.4 | 0.000 | 0.174 |
| No | 49.1 | 32.9 | 18.0 |
Note. ns = non-significant difference. BMI = body mass index. Values are expressed as percentages unless otherwise indicated.
Table 5.
Factors associated with mealtime changes during confinement (n = 2834).
| Variable | Category | Modified (%) | Maintained (%) | p | Cramer’s V |
|---|---|---|---|---|---|
| Sex | Male | 31.0 | 69.0 | 0.000 | 0.081 |
| Female | 39.6 | 60.4 | |||
| Age | 35 or younger | 41.7 | 58.3 | 0.001 | 0.072 |
| 36–49 | 35.5 | 64.5 | |||
| 50 or older | 32.9 | 67.1 | |||
| BMI | Underweight | 43.9 | 56.1 | 0.063 | ns |
| Normal weight | 35.1 | 64.9 | |||
| Overweight | 36.9 | 63.1 | |||
| Obese | 42.1 | 57.9 | |||
| Work outside the home | Yes | 36.9 | 63.1 | 0.995 | ns |
| No | 36.9 | 63.1 | |||
| Had COVID-19 symptoms | Yes | 39.6 | 60.4 | 0.316 | ns |
| No | 36.6 | 63.4 | |||
| Cohabitant with COVID-19 symptoms | Yes | 38.6 | 61.4 | 0.552 | ns |
| No | 36.8 | 63.2 | |||
| With dependent children | Yes | 39.6 | 60.4 | 0.031 | 0.041 |
| No | 35.5 | 64.5 | |||
| Anxiety presence | Yes | 41.0 | 59.0 | 0.000 | 0.110 |
| No | 29.9 | 70.1 |
Note. ns = non-significant difference. BMI = body mass index. Values are expressed as percentages unless otherwise indicated.
Table 6.
Factors associated with weight during confinement (n = 2834).
| Variable | Category | Maintained (%) | Increased (%) | Decreased (%) | p | Cramer’s V |
|---|---|---|---|---|---|---|
| Sex | Male | 36.0 | 35.4 | 28.6 | 0.000 | 0.086 |
| Female | 36.6 | 42.2 | 21.2 | |||
| Age | 35 or younger | 35.7 | 35.1 | 29.1 | 0.001 | 0.069 |
| 36–49 | 36.7 | 42.8 | 20.5 | |||
| 50 or older | 36.9 | 41.8 | 21.3 | |||
| BMI | Underweight | 53.2 | 19.5 | 27.3 | 0.000 | 0.142 |
| Normal weight | 42.5 | 36.2 | 21.3 | |||
| Overweight | 24.1 | 47.0 | 28.9 | |||
| Obese | 26.4 | 50.6 | 23.0 | |||
| Work outside the home | Yes | 35.5 | 40.8 | 23.8 | 0.164 | ns |
| No | 40.6 | 37.5 | 21.9 | |||
| Had COVID-19 symptoms | Yes | 30.6 | 36.8 | 32.5 | 0.004 | 0.073 |
| No | 37.1 | 40.5 | 22.4 | |||
| Cohabitant with COVID-19 symptoms | Yes | 29.1 | 35.7 | 35.2 | 0.000 | 0.086 |
| No | 37.2 | 40.6 | 22.2 | |||
| With dependent children | Yes | 35.8 | 46.5 | 17.7 | 0.000 | 0.122 |
| No | 36.8 | 36.3 | 26.9 | |||
| Anxiety presence | Yes | 35.4 | 43.3 | 21.4 | 0.000 | 0.088 |
| No | 38.3 | 34.7 | 26.9 |
Note. ns = non-significant difference. BMI = body mass index. Values are expressed as percentages unless otherwise indicated.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Baile, J.I.; González-Calderón, M.J.; Rabito-Alcón, M.F.; Izquierdo-Sotorrío, E. How Can Lockdown Influence Eating Habits? The Spanish Case During the COVID Pandemic. Obesities 2025, 5, 84. https://doi.org/10.3390/obesities5040084
AMA Style
Baile JI, González-Calderón MJ, Rabito-Alcón MF, Izquierdo-Sotorrío E. How Can Lockdown Influence Eating Habits? The Spanish Case During the COVID Pandemic. Obesities. 2025; 5(4):84. https://doi.org/10.3390/obesities5040084
Chicago/Turabian StyleBaile, José I., María J. González-Calderón, María F. Rabito-Alcón, and Eva Izquierdo-Sotorrío. 2025. "How Can Lockdown Influence Eating Habits? The Spanish Case During the COVID Pandemic" Obesities 5, no. 4: 84. https://doi.org/10.3390/obesities5040084
APA StyleBaile, J. I., González-Calderón, M. J., Rabito-Alcón, M. F., & Izquierdo-Sotorrío, E. (2025). How Can Lockdown Influence Eating Habits? The Spanish Case During the COVID Pandemic. Obesities, 5(4), 84. https://doi.org/10.3390/obesities5040084
