1. Introduction
The health crisis caused by COVID-19 significantly impacted multiple aspects of daily life worldwide, particularly and unprecedentedly altering nutritional habits and lifestyle during both the lockdown periods and the post-pandemic era.
On 11 March 2020 [1], the World Health Organization (WHO) declared the public health emergency caused by the SARS-CoV-2 virus as a global pandemic, and therefore, the majority of European governments [2,3,4,5], including the Spanish government [6], adopted various immediate measures such as lockdowns, mobility restrictions, and social distancing to address the health crisis and control the spread of the disease, which led to unprecedented changes in the way people carried out their daily activities, including those related to health, nutrition, and lifestyle [7]. The effects of the pandemic have not only been physically visible, but they also have had profound psychological, social, and economic consequences, altering health and well-being behaviors in different contexts [8,9,10].
A great impact was noticed on the so-called active lifestyle, as the measures implemented led many people to significantly decrease their physical activities, fostering increased sedentary behavior in the population [11,12]. Additionally, changes were observed in sleeping patterns, with greater difficulty falling asleep and a decrease in sleep quality compared to data from the pre-pandemic era [11,12,13]. Furthermore, nutrition and eating habits were highly affected areas by restrictions, experiencing a major impact both in terms of supply and production [14,15], as well as in the intake of highly processed foods, snacks, and sugary drinks [16,17,18], as unhealthy eating behaviors emerged as a way to cope with isolation, stress, or anxiety [9,13,19,20,21,22].
Studies conducted in various European countries show a widespread increase in the intake of processed products; a reduction in physical exercise; and changes in traditional eating patterns, such as the Mediterranean diet in southern Europe. These well-established eating habits were impacted by economic and availability factors, leading to a reduction in the intake of fresh and more nutritious foods [7,23]. In Spain, the existing literature describes how daily routines and eating patterns were disrupted, with an increase in the consumption of nutritionally poor products [24], alongside a decrease in physical activity [8], particularly during the stricter lockdown periods, all together with alterations in sleeping patterns [13,25,26].
As we can see, there are already numerous studies published worldwide on the effects of the pandemic during the lockdown period; however, few have assessed post-pandemic health behaviors and the long-term effects of the pandemic on the general well-being of the population [27,28,29,30,31,32,33,34,35,36], highlighting key areas where intervention is needed to promote healthier lifestyle and eating habits.
This study aims to address these gaps by analyzing changes in dietary patterns and lifestyle among the adult Spanish population during and after the COVID-19-related restrictions. To achieve this, we utilized the validated Nutritional and Social Healthy Habits (NutSo-HH) scale [37], specifically designed to comprehensively assess both nutritional behaviors and social health-related habits. The application of this tool in the context of evaluating the long-term effects of the pandemic is not only innovative but also provides a more holistic and accurate perspective on the dynamics of lifestyle changes. This novel approach enables the identification of key areas for intervention to promote healthy habits in the post-pandemic era, contributes to mitigating the negative effects of future confinement measures, and enhances the development of evidence-based public health policies.
2. Materials and Methods
2.1. Study Design and Sampling
A descriptive cross-sectional survey was conducted during two different time periods among adults (aged 18 and older) living in Spain. Participants were excluded from the study if, at the time of completing the survey, they had any medical condition or restriction that could potentially alter their dietary habits, such as hospitalization or confinement.
2.2. Ethical Approval
Approval for the study was obtained from the Research Ethics Committee of the Catholic University of Valencia under the approval code UCV/2019-2020/152. Informed consent was obtained from all participants prior to their involvement in the study, and the ethical recommendations contained in the Declaration of Helsinki [38] were followed at all times.
Moreover, before the participants could fill in the questionnaire, they were provided with information about the research which was placed on the initial page of the Google Forms document that hosted the survey. All were asked whether they understood the purpose of the study, whether they agreed to answer the questionnaire voluntarily, and whether they gave their consent for the collected data to be used for the research.
If a participant answered no, the Google Forms page was automatically closed and the participant could not progress in answering the questionnaire.
2.3. Instrument
The validated NutSo-HH scale was used for data collection [37] and is divided into several sections: a section on diet that includes the type of diet followed, consumption of various food groups and drinking habits; a section that explores the presence of diagnosed eating disorders or their symptoms; a section on physical activity and health-relevant lifestyle habits; and, finally, a part where anthropometric data such as weight, height, and socio-demographic variables are collected.
2.4. Data Collection
Data collection took place during two different time periods. The first occurred during the COVID-19 pandemic in Spain, between August 2020 and November 2021, a time when various preventive measures were still in place. The second data collection period occurred between December 2023 and May 2024, when no more restrictions were implemented.
The survey was distributed using non-probability snowball sampling [39]. A Google Forms questionnaire was created and shared primarily through online channels, with collaborators helping to disseminate the link. The initial dissemination was carried out via the Instagram account @elretonutricional, as well as through the researchers’ personal social media platforms (WhatsApp, LinkedIn, Facebook, and Twitter) and email distributions to various associations. Additionally, to reach individuals less familiar with digital platforms, physical flyers were distributed in shops and businesses frequented by people from various socio-demographic backgrounds.
2.5. Variables
For the nutritional analysis, the IASE index (Índice de Alimentación Saludable para la población Española) was chosen, which was modified to create a condensed version [40]. This adapted index allows a maximum score of 73 points, measuring adherence to the Spanish Society of Community Nutrition (SENC) guidelines [41]. Based on the score obtained, dietary habits are categorized into three levels:
Healthy: IASE score between 58.4 and 73.
Needs changes: IASE score between 36.5 and 58.4.
Unhealthy: IASE score below 36.5.
This classification provides a clear structure to evaluate dietary patterns in the population based on their alignment with national dietary recommendations. A summary table of the variables used in this adapted version of the IASE index can be found in detail in previous articles [42,43].
The other variables related to the frequency of specific food or beverage intake, which have not been used for the IASE index, such as consumption of water, sugary drinks, coffee or energy drinks, and juice and the consumption of fast, fried, or ultra-processed food have been categorized using a 4-point Likert scale, where 1 was assigned to the lowest and 4 to the highest frequency of consumption (for specific details on the score assigned to each of the responses, see Table A1, Appendix A).
The socio-demographic variables considered in the study were categorized as follows:
-. Sex: analyzed in a binary manner as male and female.
-. Age: divided into four age groups (18–25 years old, 26–40 years old, 41–65 years old, and over 65 years old).
-. Level of education: grouped into two categories, basic education (including no formal education, primary or secondary education, vocational training, or baccalaureate) and higher education (bachelor’s, master’s, and PhD).
-. Income level: classified as low (household income less than EUR 2200/month), medium–high (household income greater than EUR 2200/month), and no answer.
-. Municipality size: based on population size, with three categories established, small municipalities (less than 2000 inhabitants), medium-sized towns (between 2000 and 10,000 inhabitants), and cities (more than 10,000 inhabitants).
-. Living arrangements: classified as living alone and not living alone.
-. Family life: classified as living with family and living without family.
-. Place of residence: categorized based on the various regions of Spain.
Following the same criteria used in previous articles [44,45], variables related to health habits were also categorized using a 4-point Likert scale, with responses ranging from 1 = none or low frequency and 4 = highest frequency. This scale was used to capture the frequency of various health habits such as exercise, smoking, resting, and other lifestyle behaviors. For variables specifically related to eating disorders, a 6-point Likert scale was used to capture a wider range of responses and nuances in behavior (details can be found in Table A1 Appendix A). Finally, body mass index (BMI) and minutes of exercise were treated as numerical variables and not categorized.
2.6. Data Analysis
The sample was initially tested for normality using the Shapiro–Wilk test, which revealed that none of the studied variables adhered to normality. This finding was further validated through Q-Q plots, confirming the hypothesis of non-normality [46]. Consequently, ordinal or numeric variables were assessed with the non-parametric Mann–Whitney U test for independent samples. The significance level was set at 0.05. In a second step, we applied a Kendall’s Tau B correlation test to our most important health and behavioral variables to check for correlations between them.
Additionally, to enhance the interpretation of the statistical significance in a large sample, the effect size r (Rank-biserial correlation coefficient) for the Mann–Whitney U test was incorporated [47]. These measures provided a more nuanced view of the relationships between variables. Specifically, an r value less than 0.3 indicates a small effect [46], while values above this suggest a larger effect [48]. For large samples, effect sizes larger than these thresholds were classified as statistically significant, meaning the relationships between the variables were stronger than what would be expected from random error [47]. All analyses were conducted using Jamovi Version 2.3.28.0.
3. Results
Table 1 shows the characteristics of the sample analyzed, contrasting the sample collected during the COVID-19 period with the sample collected afterwards. In the former, N = 22,181 surveys were collected; 4251 were men (19.2%) and 17,930 women (80.8%), with an average age of 34.9 years. In the second set, N = 3907 answers were collected, 585 from men (15%) and from 3322 women (85%), with an average age of 37.1 years.
Regarding almost all socio-demographic factors, as can be seen for example in the educational level, where the majority of both samples (around two thirds) have a higher level of education, the two samples present with very similar characteristics, which undoubtedly facilitates their comparison.
The only exception is in the income level, which presents differences between the two samples: while the sample collected during COVID-19 is fairly uniform (43.9% low income and 47.9% medium–high income), in the post-pandemic sample, the majority of respondents (76.8%) had a low income compared to 16.4% who had an medium–high income.
Table 2 shows a comparison of the nutritional and health variables studied during and after the COVID-19 period. It can be seen that after the COVID-19 period there was a noticeable increase in physical activity (6.61%), from an average of 158.20 min per week to 168.66 min per week, as well as an increase in the consumption of sugary drinks (6.47%) and ultra-processed food (2.16%), while sedentary behavior (−4.46%), sleep quality (−3.24%), smoking (−4.06%), alcohol consumption (−9.66%), and juice consumption (−6.45%) have decreased, and perhaps somewhat surprisingly, the frequency of going out at night has also decreased (−6.72%), but all these differences, as seen by the effect size, are not statistically significant and can therefore be interpreted as noticeable tendencies which still indicate interesting differences in the samples. With regard to the variables related to possible eating disorders, all have experienced a tendency to decrease in the period after COVID-19. On the other hand, the consumption of coffee and energy drinks experienced a statistically significant increase (38.95%) as seen by an effect size over 0.3.
Table 3 analyzes the correlations between the main health and behavioral variables during the third wave of COVID-19 and after the restrictions were lifted. For most of the variables, there is no clear correlation (red cells) both during and after COVID-19.
Predictably, it is observed that the behavioral variables related to eating disorders (no control, body image, and obesophobia) correlate with each other in a medium–strong way (green cells) in the two data sets.
Finally, a moderate to low correlation (yellow cells) is observed, in a similar way both during and after COVID-19, between BMI and the variables of ED, self-perceived health, and weekly minutes of physical activity and sleep quality. The values range from a maximum of 0.3302 obtained between BMI and obesophobia after COVID-19 to a minimum value of −0.2023 between self-perceived health and no control during COVID-19.
4. Discussion
The aim of this research was to examine the relationship between characteristics associated with nutrition, health, and behavioral habits, with a particular focus on those related to eating disorders and self-perceived health among Spanish adults. Previous studies have already confirmed that COVID-19 had a negative impact on physical and mental health as well as on health habits worldwide [14,49].
The findings in Table 1 indicate that the regional distribution of the collected answers during and after the lockdown was not homogeneous. As indicated by the percentages, while it was possible to collect more data in regions like Navarre and Catalonia in the post-COVID-19 era, less answers were obtained in Galicia and the Valencian Community, which indicate a regional shift towards these first communities. These differences may be related to variations in the perception of the importance of the study, increased awareness of public health after the lockdown, or specific outreach campaigns in different regions. The likely impact of geographical and demographic variations inside Spain on the observed changes in health and dietary behavior is a crucial factor that has been studied by the authors previously [50]. Amuzu et al. [51] state that the place of residence and the environmental conditions in which an individual resides can influence their health behaviors, including diet, smoking, and physical activity. On the other hand, Carrillo Álvarez et al. [52] claim that differences among rural and urban residents could be due to differences in the overall food-related culture, the ability and competence to actually acquire, conserve, prepare, and eat a varied diet. Rural areas may have shown a reduced inclination to acquire bad habits during and after the lockdown since they depend more on fresh and local foods and have more limited access to these ultra-processed products or sugary beverages [53]. Regarding demographic variations, young people may have been more prone to engage in bad habits including higher energy and sugary drink consumption because of stressors like academic pressure, the social impact of restrictions, and marketing especially aimed at this age range. In contrast, older people may have changed their behavior towards a more mediterranean diet [13].
To achieve the objective of the study, it was decided to use the scale validated for the Spanish population NutSo-HH because it is a multifactorial instrument that allows detailed information to be collected on a wide range of variables that influence health. This scale provides information on the nutritional status of the population as well as on lifestyle aspects such as physical activity, sedentary lifestyles, and rest habits. It also analyzes psychological variables such as those that influence behaviors related to eating disorders or social habits such as smoking or going out at night. Specifically, the NutSo-HH scale has six first-order factors (Mediterranean foods, healthy and unhealthy foods, meats and dairy products, eating disorders, rest habits, and alcohol consumption) and two second-order factors (NUTRI, which includes the factors healthy and unhealthy foods, and meats and dairy products, and HH, which includes the factors eating disorders and rest habits). All these factors are interrelated and have a direct impact on health and well-being; the analysis of these during the lockdown period and afterwards can provide interesting information on how the pandemic has affected the health of the Spanish population.
Our study showed a slight decrease in the BMI post-pandemic (see Table 2); however, this difference was not statistically significant. Similarly, a Lithuanian research study found no changes in BMI among women aged 26 or older [54], as people tended to eat less excessively. In contrast, a study conducted on the Bangladeshi population [49] observed an increase in the prevalence of overweight among both women and men during the COVID-19 pandemic.
Another relevant finding to highlight is that, following the COVID-19 lockdown, the Spanish population noticeably increased the weekly minutes dedicated to physical exercise, as can be seen in Table 2. This result is interesting because, following the lockdown, a global campaign promoting healthy eating and physical activity would have otherwise been crucial in motivating people to return to a healthy lifestyle, while reducing cardiovascular risk [18,55,56,57]. Lockdown, with its negative psychological repercussions, led to unhealthy behaviors such as physical inactivity and increased sedentarism [24,25], even if the more flexible management of free time involved in smart working and home office allowed people to exercise more frequently in the morning [58]. The data from the post-COVID-19 era indicate a positive change in this unhealthy mid-COVID-19 behavior.
From a psychological and social perspective, we can also analyze the observed changes in sedentary behaviors, sleep quality, and nightlife in the population (Table 2), comparing the restriction period and upon returning to the “new normal”. On the one hand, as already stated, the uncertainty and traumatic experiences during lockdown periods led to mood changes, such as anxiety, stress, depression, or boredom, which were associated with reduced physical activity [59] and unhealthy dietary practices [18], prompting people to consume sugary foods and alcohol as coping mechanisms [60,61]. Additionally, lockdown significantly disrupted the circadian rhythms of many individuals, as new habits were established, including irregular sleep–wake schedules, increased screen time, and a more sedentary lifestyle [62,63,64,65]. As a consequence, upon returning to a new normal, many people found it difficult to readjust their natural rhythms, resulting in trouble falling asleep and reduced sleep quality [66,67].
Regarding nutritional habits, the results show that the consumption of unhealthy food, sugary drinks, energy drinks, and coffee did not decrease after the period of restrictions; in fact, their consumption increased (Table 2). These findings are similar to those found in Cyprus [27], China [35], Brazil [36], Latin America [68], Poland [69], Lithuania [70], Germany [71], France [72], Norway [73], and the United Kingdom [74]. Causes attributed to these unhealthy habits include increased stress levels and a decline in well-being [75], along with the tendency to choose food based on mood [76]. Although we see these similar patterns, it is important to consider the cultural and food policy differences between these contexts and Spain. For example, in the United Kingdom, the implementation of a sugar tax (soft drinks industry levy—SDIL) has shown positive results in reducing the consumption of sugary drinks [77]. Spain could also benefit from greater investment in post-pandemic nutritional education strategies, such as campaigns aimed at reducing the consumption of sugary drinks, especially among young people and vulnerable populations. Meanwhile, the consumption of fried foods, tobacco, water, and alcohol decreased in the post-lockdown period, indicating that these products were consumed more frequently during lockdown. Similar results are observed in studies conducted in Poland [78], Denmark [79], Belgium [80], and Bahrain [81]. However, it is important to take into account the contextual differences that may influence these trends. For example, changes in alcohol and tobacco consumption could be influenced by price regulation and public health campaigns, which vary between countries [82].
Compared to the post-lockdown period, lockdown was associated with higher levels of body image dissatisfaction, fear of gaining weight, and lack of control over food quantity consumed. These findings align with a study on the physical, mental, and psychosocial aspects that reported significant negative changes in mental well-being and psychosocial health in the Western Australian community [10]. Another study from the USA concludes that population-based interventions on mental health improvement are recommended given the high prevalence of depression and anxiety [83] and a study conducted in 12 countries of Latin America and the Caribbean reports on the impact of cognitive, emotional, and behavioral variables on subjective well-being [84]. Several European studies have also evaluated these emotional eating disorders associated with the COVID-19 pandemic [85,86], identifying psychological distress as the main cause [87].
As can be seen in Table 3, in our study, a positive correlation was observed between sleep quality and self-perceived health, both during lockdown (in the third wave restriction period) and post-lockdown, highlighting the importance of sleep in health perception and overall well-being. In the pandemic context, changes in routines affected sleep quality for many people, leading to insomnia and disrupted sleep cycles, which increased stress levels and negatively impacted general well-being perception [26]. In the post-pandemic context, it is recommended that sleep habits should be improved by promoting sleep hygiene practices, such as reducing the use of electronic devices before bed and maintaining a consistent sleep routine, as these are crucial for enhancing health perception and reducing stress in affected populations [88].
The positive correlation between physical activity and self-perceived health status (Table 3), measured in minutes, indicates that physical exercise is a key predictor of positive health perception [89], with its impact manifesting differently in periods of lockdown or restriction [24]. During the pandemic, many people experienced a reduction in physical activity due to the lockdown or restrictions, which negatively affected their overall well-being [90,91]. Physical activity also appears to act as a protective factor against stress, especially in the pandemic context, and is considered essential for maintaining a positive perception of health and mental well-being [49].
On the other hand, and continuing with self-perceived health status, we found that it is negatively related to the lack of control over food quantity consumed, indicating that people with a less favorable perception of health tend to struggle with food intake control. In our study, this correlation was found to be significant in the pandemic context due to imposed limitations and routine changes that led to compulsive eating patterns, where food consumption served as a response to stress or negative emotions—a phenomenon commonly observed during the pandemic [70,78].
The positive correlation between BMI and feelings of lack of control over food intake, body image, and obesophobia (Table 3) suggests that individuals who are overweight or obese may struggle to moderate food intake or tend to experience greater body dissatisfaction and fear of weight gain [85,87]. All of these emotional eating disorders associated with COVID-19 have been exacerbated by stress, anxiety, and sedentary lifestyles—factors that have increased the risk of overeating and choosing unhealthy foods, contributing to a perceived loss of control and unhealthy behavioral patterns, such as the avoidance of social activities [92,93].
The positive correlations among the three eating disorder-related factors studied (obesophobia, lack of control, and body image) indicate a significant psychological connection. This suggests that individuals’ relationships with body image and control over eating habits were impacted both during and after the pandemic [94,95]. Research exploring the differences in eating behaviors and body image as confinement measures were lifted will be essential for understanding the full psychological impact of this pandemic and for improving future public health and service planning [96].
Finally, we can conduct a more detailed examination of studies specifically related to the Spanish population to better frame the research within existing national studies. In the study by Rodriguez-Perez et al. [24], the authors emphasize that adherence to the Mediterranean diet increased significantly during the lockdown and an improvement in dietary behaviors was observed. These conclusions are in line with other studies from Italy [97], Croatia [98], Romania [99], Mexico [100], Peru [101], and India [102]. On the contrary, in the studies by Casas et al. [13] and Sanchez-Sanchez et al. [25], it is concluded that even though the adherence to the Mediterranean diet slightly increased during lockdown, the consumption of “unhealthy” food also increased, a statement that was confirmed by authors from France [103], the United Kingdom [104], the USA [105], Brazil [106], and Colombia [107].
Strengths and Limitations
Among the research’s limitations is that obtaining an identical sample size as in the first survey for the second one was not feasible. This could potentially be attributed to the fact that during the third state of alarm, which occurred between August 2020 and November 2021, people typically had more free time and were more inclined to participate in this type of research. These big differences (N = 22,181 for the COVID-19 period vs. N = 3.907 for the post-COVID-19 period) could limit the liability of the conclusions taken in the discussion. For that reason, the effect size played an important role in the interpretation because it is not as influenced by the sample size as the p-value and therefore provides a better measurement tool. On the other hand, N = 3907 is still a noticeable sample size and therefore, taking into account the mathematical law of big numbers, the calculated values for mean and standard deviation should approximate the ones found in the population itself quite well and, in conclusion, give our comparison the needed credibility.
Another limitation of this study is related to the sampling method, which primarily utilized snowball sampling and relied heavily on social media for dissemination. While snowball sampling allows for a broader range of responses, it carries the risk of self-selection bias, as the sample depends on initial participants recommending further participants. On social networks, influencers play a significant role in spreading content related to specific topics, attracting followers with similar interests and behaviors. It is possible that the survey reached some of these communities through influencers, potentially influencing respondents’ behaviors and preferences. Another bias found is related to the age and education of the respondents, with the sample being mostly young and highly educated. This may be due to the dissemination of the questionnaire through social networks where young people have easier access and more familiarity. To minimize those biases, substantial efforts were made to disseminate the questionnaire outside of social networks. In concrete terms, the questionnaire was also distributed physically. Different shops and establishments throughout Spain (chosen for their varied clientele) were contacted and asked to display in their premises a poster explaining the research with a QR code that would send the questionnaire form which allowed customers to participate if they wished to. In addition, an email was also sent to different associations operating in Spain (such as housewives’ associations, scout associations, or charities) asking them to disseminate the survey among their members.
Among the most notable biases in the sample is the gender bias (about 80% of the respondents were female). Despite the authors’ efforts to achieve a balanced sample, this bias could not be avoided, probably because it is structural to this type of research. In fact, it is in line with other studies on the same topic, where a greater predisposition of women to participate in nutrition and health studies has been observed [108,109,110].
In order to try to obtain results that are less influenced by these biases, the authors are currently carrying out a new dissemination of the survey with the specific objective of obtaining a sample with a higher average age and with more people with a basic level of education, and in which the percentage of male participation is higher.
As for the strengths of the study, long-term analyses are essential tools for understanding the impacts the pandemic has had on living patterns over time, particularly regarding dietary and lifestyle changes. Observing how behavioral and health variables evolve over time allows us not only to identify abrupt changes but also to understand if these behaviors remain stable or reverse once the pandemic subsided, thereby enhancing the applicability of the results to other countries and populations, increasing their relevance. This study provides an in-depth analysis of changes in physical activity and their impact on self-perceived health. It thoroughly explores the relationship between physical activity, body mass index (BMI), and perceived well-being, underscoring the importance of these factors on participants’ mental and physical health, particularly within quarantine contexts. This study highlights how psychological factors, such as weight concern and control over eating, influence health perception and lifestyle habits. Including elements such as body image, fear of weight gain, lack of control over food intake, and the impact of stress on eating offers a more holistic understanding of lifestyle changes. This comprehensive perspective adds depth to the findings and enriches the discussion about the effects of the pandemic on the overall health of individuals.
This study not only offers observational data but also provides a broad and well-supported interpretive framework, encompassing the physical, psychological, and social aspects of well-being during times of crisis. Nevertheless, it is essential to continue investigating post-pandemic behaviors to mitigate long-term negative health impacts and strengthen our society’s resilience in facing similar situations in the future. Specific interventions are needed to curb the increasing consumption of ultra-processed foods and sugary drinks while promoting overall well-being.
Future studies should investigate regional and demographic disparities in health behaviors across Spain, emphasizing urban versus rural distinctions and specific cohorts such as younger individuals or those from lower socioeconomic backgrounds. Furthermore, examining the psychological underpinnings underlying habits like stress or emotional eating, together with performing cross-cultural comparisons, may reveal useful public health initiatives. Longitudinal studies are crucial for determining the persistence or evolution of observed patterns, while evaluations of specific interventions, such as educational campaigns or taxes on some products, offer practical insights for permanent enhancements in public health.
5. Conclusions
The healthcare crisis triggered by COVID-19 exposed the fragility of our health habits in the face of global emergencies, highlighting the importance of psychological and social factors during this crisis period. We must be prepared to address the negative impact on nutritional and lifestyle habits that the pandemic left behind, including an increased reliance on unhealthy foods that, among other effects, heighten cardiovascular risk. During lockdown, it was crucial to promote healthy eating and physical activity at home, addressing the challenges of sedentary behavior and the use of unhealthy foods as coping strategies for stress and anxiety. Once lockdown was over, a comprehensive reevaluation of the population’s health status was necessary, focusing on both biometric parameters, such as BMI, and psychological factors to enable early identification of persistent anxiety and stress symptoms, thus preventing progression towards potential post-traumatic stress syndrome.
It is essential to implement a global initiative to promote a return to a healthy lifestyle that incorporates a balanced diet and regular physical activity, as these are protective factors that ensure physical and mental well-being, thereby reducing the risk of cardiovascular diseases and other health issues. Such interventions should be holistic, considering both physical and psychological aspects, with the aim of facilitating full recovery and fostering sustainable, healthy lifestyles.
E.S.: Conceptualization, data curation, investigation, methodology, validation, writing—original draft, writing—review and editing. L.U.W.: Data curation, formal analysis, visualization, writing—review and editing. V.B.M.: Conceptualization, methodology, writing—original draft, writing—review and editing. All authors approved the final manuscript. All authors have read and agreed to the published version of the manuscript.
The research strictly followed ethical principles outlined in the Declaration of Helsinki and received approval from the Ethics Research Committee of the Catholic University of Valencia (approval code UCV/2019-2020/152, date of approval 18 June 2020).
Prior to participating, explicit informed consent was obtained from all individuals, ensuring they were fully informed about the study’s objectives, procedures, and potential risks and emphasizing the voluntary nature of their participation.
The data presented in this study are available upon reasonable request to the corresponding author.
The authors sincerely appreciate the collaboration of all individuals who contributed to this research. Special thanks to those who played a role in sharing the questionnaire and to those who devoted their time to participate in and provide responses to the survey. The authors also thank the Universidad Católica de Valencia San Vicente Martir for the support in paying for publication in this open access journal.
The authors declare no conflicts of interest.
Footnotes
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.
Characteristics of the sample.
| During COVID-19 Mean (SD) or N (%) | Post-COVID-19 Mean (SD) or N (%) | ||
|---|---|---|---|
| Sex | Male | 4251 (19.2%) | 585 (15%) |
| Female | 17,930 (80.8%) | 3322 (85%) | |
| Age in years | Age total (years) | 34.9 (11.7) | 37.7 (10.8) |
| Age male (years) | 36.5 (13.4) | 36.14 (12.4) | |
| Age female (years) | 34.5 (11.2) | 38.0 (10.4) | |
| Age divided by | 18–25 years | 5952 (26.8%) | 484 (12.0%) |
| categories | 26–40 years | 9644 (43.5%) | 2006 (51.0%) |
| 41–65 years | 6390 (28.8%) | 1380 (35.0%) | |
| >65 years | 195 (0.9%) | 37 (1.0%) | |
| Exercise in min. | Exercise in min. | 158.20 (177.1) | 168.66 (179.9) |
| Education level | Basic education | 7027 (31.7%) | 1137 (29.1%) |
| Higher education | 15,154 (68.3%) | 2770 (70.9%) | |
| Income level | Low | 9727 (43.9%) | 3002 (76.8%) |
| Medium–high | 10,616 (47.9%) | 640 (16.4%) | |
| No answer | 1839 (8.3%) | 265 (6.78%) | |
| Municipality size | <2000 | 1014 (4.6%) | 186 (4.8%) |
| 2000–10,000 | 3587 (16.2%) | 734 (18.8%) | |
| >10,000 | 17,580 (79.3%) | 2987 (76.4%) | |
| Living arrangement | Living alone | 2202 (9.9%) | 408 (10.4%) |
| Not living alone | 19,979 (90.1%) | 3499 (89.6%) | |
| Family life | Living with family | 16,732 (75.4%) | 3065 (78.5%) |
| Living without family | 5449 (24.6%) | 842 (21.5%) | |
| Diet | Mediterranean diet | 17,573 (79.2%) | 2990 (76.5%) |
| Vegetarian diet | 1425 (6.4%) | 220 (5.6%) | |
| Vegan diet | 365 (1.6%) | 57 (1.5%) | |
| Intermittent fasting | 1018 (4.6%) | 229 (5.9%) | |
| Raw diet | 252 (1.1%) | 61 (1.56%) | |
| Other | 1548 (7.0%) | 350 (9.0%) | |
| Eating disorder | Diagnosed ED | 780 (3.5%) | 176 (4.5%) |
| No diagnosed ED | 21,401 (96.5%) | 3731 (95.5%) | |
| Living area | North of Spain | 9602 (43.3%) | 1772 (45.4%) |
| South of Spain | 12,579 (56.7%) | 2135 (64.6%) | |
| Place of residence | Andalusia | 2617 (11.8%) | 504 (12.9%) |
| Aragon | 652 (2.9%) | 126 (3.2%) | |
| Asturias | 661 (3.0%) | 99 (2.5%) | |
| Balearic Islands | 488 (2.2%) | 78 (2.0%) | |
| Basque Country | 925 (4.2%) | 175 (4.5%) | |
| Canary Islands | 637 (2.9%) | 105 (2.7%) | |
| Cantabria | 217 (1.0%) | 37 (1.0%) | |
| Castilla-La Mancha | 729 (3.3%) | 136 (4.5%) | |
| Castile and León | 1276 (5.8%) | 168 (4.3%) | |
| Cataluña | 3540 (16.0%) | 693 (17.7%) | |
| Ceuta and Melilla | 28 (0.1%) | 8 (0.2%) | |
| Community of Madrid | 3882 (17.5%) | 694 (17.8%) | |
| Extremadura | 395 (1.8%) | 56 (1.4%) | |
| Galicia | 1404 (6.3%) | 172 (4.4%) | |
| La Rioja | 115 (0.5%) | 51 (1.3%) | |
| Navarre | 324 (1.5%) | 173 (4.43%) | |
| Region of Murcia | 417 (1.9%) | 98 (2.5%) | |
| Valencian Community | 3874 (17.5%) | 534 (13.7%) |
Relationship between habit variables in the during COVID-19 and post-COVID-19 groups.
| During COVID-19 | Post-COVID-19 | Change | p-Value * (Effect Size r) | |
|---|---|---|---|---|
| Health values | ||||
| BMI | 23.88 (4.03) | 23.82 (4.25) | −0.25% | p = 0.52 (0.0064) |
| IASE | 53.78 (9.86) | 53.95 (9.93) | +0.32% | p = 0.11 (0.0156) |
| Exercise in min. | 158.20 (177.1) | 168.66 (179.9) | +6.61% | p < 0.0001 (0.0429) † |
| Fried food consumption | 2.24 (0.81) | 2.16 (0.78) | −3.57% | p < 0.0001 (0.0538) † |
| Fast food consumption | 2.37 (0.77) | 2.37 (0.76) | +/−0% | p = 0.82 (0.0021) |
| Ultra-processed food consumption | 2.32 (0.95) | 2.37 (0.97) | +2.16% | p = 0.0013 (0.0305) |
| Water consumption | 3.40 (0.64) | 3.39 (0.63) | −0.29% | p = 0.11 (0.0142) |
| Soft drink consumption | 1.39 (0.67) | 1.48 (0.54) | +6.47% | p < 0.0001 (0.1282) † |
| Juice consumption | 1.24 (0.53) | 1.16 (0.45) | −6.45% | p < 0.0001 (0.0639) † |
| Coffee and energy drink consumption | 1.72 (0.71) | 2.39 (1.03) | +38.95% | p < 0.0001 (0.3743) †† |
| Self-perceived health | 3.82 (0.84) | 3.80 (0.87) | −0.52% | p = 0.22 (0.0112) |
| Sedentary lifestyle | 1.57 (0.83) | 1.50 (0.78) | −4.46% | p < 0.0001 (0.0468) † |
| Sleeping hours | 2.52 (0.73) | 2.48 (0.75) | −1.59% | p = 0.0188 (0.0215) † |
| Getting up rested | 2.54 (0.58) | 2.54 (0.60) | +/−0% | p = 0.7440 (0.0029) |
| Sleeping quality | 3.39 (1.02) | 3.28 (1.06) | −3.24% | p < 0.0001 (0.0531) † |
| Smoking | 1.23 (0.63) | 1.18 (0.55) | −4.06% | p < 0.0001 (0.03) † |
| Alcohol consumption | 1.76 (0.87) | 1.59 (0.79) | −9.66% | p < 0.0001 (0.1015) † |
| Getting drunk | 1.06 (0.29) | 1.05 (0.27) | −0.95% | p = 0.13 (0.0055) |
| Nightlife | 1.19 (0.43) | 1.11 (0.34) | −6.72% | p < 0.0001 (0.0661) † |
| Obesophobia | 3.45 (1.44) | 3.24 (1.41) | −6.09% | p < 0.0001 (0.0836) † |
| No control | 2.78 (1.29) | 2.71 (1.25) | −2.52% | p = 0.007 (0.0263) † |
| Body image | 3.61 (1.29) | 3.44 (1.26) | −4.70% | p < 0.0001 (0.0723) † |
* Mann–Whitney U test. Comparison between the during COVID-19 and post-COVID-19 groups. † Tendencies noticeable but not significant, as shown by effect size r < 0.3. †† Significant differences indicated by effect size r > 0.3.
Correlations between the most important health and behavioral variables in the during and post-COVID-19 samples.
| Value | IASE | BMI | Exercise in min. | Sedentary Lifestyle | Sleep Quality | Self-Perceived Health | No Control | Body Image | Obesophobia |
|---|---|---|---|---|---|---|---|---|---|
| During third wave of COVID-19 | |||||||||
| IASE | - | −0.041 | 0.087 | −0.0122 | 0.0556 | 0.1224 | −0.0663 | −0.0615 | −0.0588 |
| BMI | - | −0.079 | 0.0193 | −0.0632 | −0.1530 | 0.2546 | 0.1845 | 0.3076 | |
| Sport in min. | - | −0.1123 | 0.0775 | 0.2204 | −0.0765 | −0.0404 | −0.0827 | ||
| Sedentary lifestyle | - | 0.0026 | −0.0601 | 0.0579 | 0.0566 | 0.0714 | |||
| Sleep quality | - | 0.2609 | −0.1478 | −0.1408 | −0.1343 | ||||
| Self-perceived health | - | −0.2023 | −0.1811 | −0.1889 | |||||
| No control | - | 0.5252 | 0.6057 | ||||||
| Body image | - | 0.6628 | |||||||
| Obesophobia | - | ||||||||
| Post-COVID-19 | |||||||||
| IASE | - | −0.0405 | 0.0698 | −0.0007 | 0.0422 | 0.1265 | −0.0641 | −0.0712 | −0.0658 |
| BMI | - | −0.0575 | 0.0053 | −0.0577 | −0.0872 | 0.2405 | 0.2089 | 0.3302 | |
| Sport in min. | - | −0.0889 | 0.1115 | 0.2203 | −0.1025 | −0.0638 | −0.0865 | ||
| Sedentary lifestyle | - | 0.0335 | −0.0599 | 0.0284 | 0.0493 | 0.0536 | |||
| Sleep quality | - | 0.2502 | −0.1706 | −0.1630 | −0.1380 | ||||
| Self-perceived health | - | −0.1924 | −0.1814 | −0.1671 | |||||
| No control | - | 0.5074 | 0.5881 | ||||||
| Body image | - | 0.6533 | |||||||
| Obesophobia | - |
Kendall’s Tau B. NOTE: Red = No correlation; Yellow = Low correlation; Green = Medium-high correlation.
Appendix A
Categorization of the health and lifestyle variables and of the variables of eating disorders.
| Variable | Category | Score |
|---|---|---|
| Sleeping hours | Less than 6 h | 1 |
| Between 6 and 7 h | 2 | |
| Between 7 and 8 h | 3 | |
| More than 8 h | 4 | |
| Getting up rested | Never | 1 |
| Very seldom and sometimes | 2 | |
| Frequently and almost always | 3 | |
| Always | 4 | |
| Sleep quality | 0 and 1 | 1 |
| 2 | 2 | |
| 3 | 3 | |
| 4 and 5 | 4 | |
| Water | Never, very rarely (2 max. per month), 1 glass/cup/week, and 2 or more glasses/cups/week | 1 |
| 2 glasses/cups or less every day | 2 | |
| 3 to 5 glasses every day | 3 | |
| More than 5 glasses every day | 4 | |
| Sugary soft drinks, coffee, and energy drinks | Never and very rarely (2 glasses max. per month) | 4 |
| One glass per week, and two or more glasses per week | 3 | |
| 2 glasses or less every day | 2 | |
| 3 to 5 glasses and more than 5 glasses every day | 1 | |
| Juice | Never and very rarely (2 glasses max. per month) | 1 |
| One glass per week, and two or more glasses per week | 2 | |
| 2 glasses or less every day | 3 | |
| 3 to 5 glasses and more than 5 glasses every day | 4 | |
| Fish consumption | Never or very seldom | 1 |
| Between 1 and 2 times a week | 2 | |
| Three or more times a week | 3 | |
| Every day | 4 | |
| Consumption of fast food, fried, and ultra-processed dishes | Never | 1 |
| Very seldom (2 times a month maximum) | 2 | |
| Once a week | 3 | |
| Several times a week | 4 | |
| Getting drunk | Never or less than once a month | 1 |
| Monthly | 2 | |
| Weekly | 3 | |
| Daily or almost daily | 4 | |
| Alcohol consumption | Never or once a month | 1 |
| 2–4 times a month | 2 | |
| 2–3 times a week | 3 | |
| 4–5 times a week or every day | 4 | |
| Smoking | Non-smoker | 1 |
| Light smoker (less than 5 cigarettes per day) | 2 | |
| Moderate smoker (6–15 cigarettes per day) | 3 | |
| Severe smoker (more than 16 cigarettes per day) | 4 | |
| Night outings | Never and sporadically | 1 |
| Between 1 and 2 times a week | 2 | |
| More than 3 times a week | 3 | |
| Every day | 4 | |
| Sedentary lifestyle | Less than 7 h | 1 |
| Between 7 and 9 h | 2 | |
| Between 9 and 11 h | 3 | |
| More than 11 h | 4 | |
| Obesophobia, no control, and body image | Never | 1 |
| Rarely | 2 | |
| Occasionally | 3 | |
| Frequently | 4 | |
| Very frequently | 5 | |
| Always | 6 |
References
1. Boletín Oficial del Estado. Real Decreto 926/2020, de 25 de Octubre, por el que se Declara el Estado de Alarma Para Contener la Propagación de Infecciones Causadas por el SARS-CoV-2 [Internet]; 2020 October 25. Available online: https://www.boe.es (accessed on 24 November 2024).
2. Federal Ministry of Health. Gesetz zum Schutz der Bevölkerung bei Einer Epidemischen Lage von Nationaler Tragweite. Bundesgesetzblatt [Internet]; 2020 May 27. Available online: https://www.bgbl.de/xaver/bgbl/start.xav?startbk=Bundesanzeiger_BGBl&start=//*%5b@attr_id=%27bgbl120s0587.pdf%27%5d#__bgbl__%2F%2F*%5B%40attr_id%3D%27bgbl120s0587.pdf%27%5D__1733650311854 (accessed on 24 November 2024).
3. Journal Officiel de la République Française. Loi n° 2020-290 du 23 mars 2020 D’urgence Pour Faire Face à L’épidémie de COVID-19 [Internet]; 2020 March 24. Available online: https://www.legifrance.gouv.fr/download/pdf?id=kdRvwoE6LswOjQsxQYyZiWtc_Fh71x9KoG_z3damffY= (accessed on 24 November 2024).
4. Dei Ministri, I.C. Dichiarazione dello stato di emergenza in conseguenza del rischio sanitario connesso all’insorgenza di patologie derivanti da agenti virali trasmissibili. Gazz. Uff. Della Repubb. Ital.; 2020; 161, pp. 7-8.
5. The Health Protection (Coronavirus, Restrictions) (Self-Isolation) (England) Regulations 2020, SI 2020/350. Available online: https://www.legislation.gov.uk/uksi/2020/350/contents (accessed on 29 October 2024).
6. Boletín Oficial del Estado. Real Decreto 463/2020, de 14 de Marzo, por el que se Declara el Estado de Alarma Para la Gestión de la Situación de Crisis Sanitaria Ocasionada por el COVID-19 [Internet]; 2020 March 14. Available online: https://www.boe.es/diario_boe/txt.php?id=BOE-A-2020-3692 (accessed on 24 November 2024).
7. Wiśniewski, O.W.; Czyżniewski, B.; Żukiewicz-Sobczak, W.; Gibas-Dorna, M. Nutritional behavior in European countries during COVID-19 pandemic—A review. Nutrients; 2023; 15, 3451. [DOI: https://dx.doi.org/10.3390/nu15153451]
8. Navarro-Pérez, C.F.; Fernández-Aparicio, Á.; González-Jiménez, E.; Montero-Alonso, M.Á.; Schmidt-RioValle, J. Effects of COVID-19 lockdown on the dietary habits and lifestyle in a population in southern Spain: A cross-sectional questionnaire. European Journal of Clinical. Nutrition; 2021; 76, pp. 883-890. [DOI: https://dx.doi.org/10.1038/s41430-021-01034-w]
9. Cecchetto, C.; Aiello, M.; Gentili, C.; Ionta, S.; Osimo, S.A. Increased emotional eating during COVID-19 associated with lockdown, psychological and social distress. Appetite; 2021; 160, 105122. [DOI: https://dx.doi.org/10.1016/j.appet.2021.105122]
10. Bhoyroo, R.; Chivers, P.; Millar, L.; Bulsara, C.; Piggott, B.; Lambert, M.; Codde, J. Life in a time of COVID-19: A mixed method study of the changes in lifestyle, mental and psychosocial health during and after lockdown in Western Australians. BMC Public Health; 2021; 21, 1947. [DOI: https://dx.doi.org/10.1186/s12889-021-11971-7]
11. Soe, P.P.; Hnin, Z.L.; Hlaing, T.; Min, H. Changes in physical activity, dietary and sleeping pattern among the general population in COVID-19: A systematic review protocol. PLoS ONE; 2022; 17, e0269202. [DOI: https://dx.doi.org/10.1371/journal.pone.0269202] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35657947]
12. Pérez-Rodrigo, C.; Citores, M.G.; Bárbara, G.H.; Ruiz-Litago, F.; Sáenz, L.C.; Arija, V.; López-Sobaler, A.M.; De Victoria, E.M.; Ortega, R.M.; Partearroyo, T. et al. Patterns of change in dietary habits and physical activity during lockdown in Spain due to the COVID-19 pandemic. Nutrients; 2021; 13, 300. [DOI: https://dx.doi.org/10.3390/nu13020300] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33494314]
13. Casas, R.; Raidó-Quintana, B.; Ruiz-León, A.M.; Castro-Barquero, S.; Bertomeu, I.; Gonzalez-Juste, J.; Campolier, M.; Estruch, R. Changes in Spanish lifestyle and dietary habits during the COVID-19 lockdown. Eur. J. Nutr.; 2022; 61, pp. 2417-2434. [DOI: https://dx.doi.org/10.1007/s00394-022-02814-1]
14. Żurek, J.; Rudy, M. Impact of the COVID-19 pandemic on changes in consumer purchasing behavior in the food market with a focus on meat and meat products—A comprehensive literature review. Foods; 2024; 13, 933. [DOI: https://dx.doi.org/10.3390/foods13060933]
15. Rabbi, M.F.; Oláh, J.; Popp, J.; Máté, D.; Kovács, S. Food security and the COVID-19 crisis from a consumer buying behaviour perspective—The case of Bangladesh. Foods; 2021; 10, 3073. [DOI: https://dx.doi.org/10.3390/foods10123073]
16. Brizi, A.; Biraglia, A. “Do I have enough food?” How need for cognitive closure and gender impact stockpiling and food waste during the COVID-19 pandemic: A cross-national study in India and the United States of America. Personal. Individ. Differ.; 2020; 168, 110396. [DOI: https://dx.doi.org/10.1016/j.paid.2020.110396] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32982000]
17. 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. [DOI: https://dx.doi.org/10.1186/s12967-020-02399-5] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32513197]
18. Mattioli, A.V.; Sciomer, S.; Cocchi, C.; Maffei, S.; Gallina, S. Quarantine during COVID-19 outbreak: Changes in diet and physical activity increase the risk of cardiovascular disease. Nutr. Metab. Cardiovasc. Dis.; 2020; 30, pp. 1409-1417. [DOI: https://dx.doi.org/10.1016/j.numecd.2020.05.020] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32571612]
19. Prieto, D.C.; Lanza-León, P.; Moreno, P.; Blázquez-Fernández, C.; Lera, J.; Gonzalez-Diego, F.; Rodríguez, I.G. Change in eating habits during the Spanish COVID-19 pandemic lockdown: Evidence for a sample of university community. PeerJ; 2023; 11, e14244. [DOI: https://dx.doi.org/10.7717/peerj.14244]
20. Reyes-Olavarría, D.; Latorre-Román, P.A.; Guzmán-Guzmán, I.P.; Jerez-Mayorga, D.; Caamaño-Navarrete, F.; Delgado-Floody, P. Positive and negative changes in food habits physical activity patterns and weight status during COVID-19 confinement: Associated factors in the Chilean population. Int. J. Environ. Res. Public Health; 2020; 17, 5431. [DOI: https://dx.doi.org/10.3390/ijerph17155431]
21. Dijksterhuis, G.B.; Van Bergen, G.; De Wijk, R.A.; Zandstra, E.H.; Kaneko, D.; Vingerhoeds, M. Exploring impact on eating behaviour exercise and well-being during COVID-19 restrictions in the Netherlands. Appetite; 2021; 168, 105720. [DOI: https://dx.doi.org/10.1016/j.appet.2021.105720]
22. Di Renzo, L.; Gualtieri, P.; Cinelli, G.; Bigioni, G.; Soldati, L.; Attinà, A.; Bianco, F.F.; Caparello, G.; Camodeca, V.; Carrano, E. et al. Psychological aspects and eating habits during COVID-19 home confinement: Results of EHLC-COVID-19 Italian Online Survey. Nutrients; 2020; 12, 2152. [DOI: https://dx.doi.org/10.3390/nu12072152]
23. Mignogna, C.; Costanzo, S.; Ghulam, A.; Cerletti, C.; Donati, M.B.; De Gaetano, G.; Iacoviello, L.; Bonaccio, M. Impact of nationwide lockdowns resulting from the first wave of the COVID-19 pandemic on food intake eating behaviors and diet quality: A systematic review. Adv. Nutr.; 2021; 13, pp. 388-423. [DOI: https://dx.doi.org/10.1093/advances/nmab130]
24. 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 COVID-19iet study. Nutrients; 2020; 12, 1730. [DOI: https://dx.doi.org/10.3390/nu12061730]
25. 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. [DOI: https://dx.doi.org/10.3390/nu12092826]
26. 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. [DOI: https://dx.doi.org/10.3390/nu12113445] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33182816]
27. Kyprianidou, M.; Chrysostomou, S.; Christophi, C.A.; Giannakou, K. Change of Dietary and Lifestyle Habits during and after the COVID-19 Lockdown in Cyprus: An Analysis of Two Observational Studies. Foods; 2022; 11, 1994. [DOI: https://dx.doi.org/10.3390/foods11141994]
28. Bifolco, G.; Cardinali, L.; Mocini, E.; Duradoni, M.; Baldari, C.; Ciampi, M.; Migliaccio, S.; Cianferotti, L. Long-term effects of COVID-19 pandemic on physical activity and eating behaviour of the Italian population: A longitudinal study. Endocrine; 2024; 86, pp. 1003-1013. [DOI: https://dx.doi.org/10.1007/s12020-024-03950-w]
29. Covelli, V.; Camisasca, E.; Manzoni, G.M.; Crescenzo, P.; Marelli, A.; Visco, M.A.; Cafagna, D.; Marsicovetere, V.; Pesce, M.; Cantoia, M. After the first lockdown due to the COVID-19 pandemic: Perceptions, experiences, and effects on well-being in Italian people. Front. Psychol.; 2023; 14, 1172456. [DOI: https://dx.doi.org/10.3389/fpsyg.2023.1172456] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37333603]
30. Scozzafava, G.; Contini, C.; Gerini, F.; Casini, L. Post-lockdown changes in diet in Italy and the USA: Return to old habits or structural changes?. Agric. Food Econ.; 2022; 10, 26. [DOI: https://dx.doi.org/10.1186/s40100-022-00234-7] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36267441]
31. Sung, J.; Davis, W.; Qiu, Q. The effects of COVID-19 lockdown on the body weight and lifestyle behaviors of U.S. adults. South. Econ. J.; 2024; 90, pp. 900-948. [DOI: https://dx.doi.org/10.1002/soej.12679]
32. Al-Tannir, M.; AlFayyad, I.; Altannir, M.; Alosaimi, A.; Alonazi, A.; Alqarni, A. Long-term impact of post COVID-19 pandemic quarantine on eating habits changes among adult residents of Riyadh, Saudi Arabia. Front. Nutr.; 2023; 10, 1243288. [DOI: https://dx.doi.org/10.3389/fnut.2023.1243288]
33. Alhusseini, N.; Alammari, D.; Ramadan, M.; Ziadeh, N.; Zyadeh, Z.; Alshamrani, J.; Qasim, H.; Alamri, N.; Alqahtani, S.A. The impact of COVID-19 pandemic on lifestyle among the Saudi population. J. Public Health Res.; 2022; 11, 22799036221123156. [DOI: https://dx.doi.org/10.1177/22799036221123156]
34. Ochi, S.; Mirai, S.; Hashimoto, S.; Hashimoto, Y.; Sekizawa, Y. Impact of the COVID-19 pandemic on exercise habits and overweight status in Japan: A nation-wide panel survey. PLoS Glob. Public Health; 2023; 3, e0001732. [DOI: https://dx.doi.org/10.1371/journal.pgph.0001732]
35. Li, H.; Song, Y.; Wang, Y.; Feng, X.; Li, C.; Peng, J.; Yu, H. Impact of the COVID-19 pandemic lockdown on Body Mass Index: A three-year follow-up study in 6,156 Chinese college students. Front. Endocrinol.; 2024; 15, 1387151. [DOI: https://dx.doi.org/10.3389/fendo.2024.1387151]
36. Paris, J.M.G.; Lima, E.M.F.; Finger, J.D.A.F.F.; Isidorio, W.R.; Heinzel, C.; Falkenberg, T.; Borgemeister, C.; Pinto, U.M.; Nöthlings, U. Changes in eating habits and lifestyle during the first year of the COVID-19 pandemic across metropolitan regions in Brazil and Germany: A survey-based cross-sectional study. Food Sci. Nutr.; 2024; 12, pp. 2783-2798. [DOI: https://dx.doi.org/10.1002/fsn3.3960] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/38628226]
37. Sandri, E.; Piredda, M.; De Maria, M.; Mancin, S.; Sguanci, M.; Cabo, A.; Cerdá Olmedo, G. Development and Psychometric Testing of the Nutritional and Social Health Habits Scale (NutSo-HH): A Methodological Review of Existing Tools. MethodsX; 2024; 12, 102768. [DOI: https://dx.doi.org/10.1016/j.mex.2024.102768] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/38883583]
38. World Medical Association Declaration of Helsinki. Ethical Principles for Medical Research Involving Human Subjects. JAMA; 2013; 310, pp. 2191-2194. [DOI: https://dx.doi.org/10.1001/jama.2013.281053]
39. Biernacki, P.; Waldorf, D. Snowball Sampling: Problems and Techniques of Chain Referral Sampling. Sociol. Methods Res.; 1981; 10, pp. 141-163. [DOI: https://dx.doi.org/10.1177/004912418101000205]
40. Norte Navarro, A.I.; Ortiz Moncada, R. Quality of the Spanish Diet According to the Healthy Eating Index. Nutr. Hosp.; 2011; 26, pp. 330-336. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21666971]
41. Grupo Colaborativo de la Sociedad Española de Nutrición Comunitaria (SENC). Guías Alimentarias Para la Población Española; La Nueva Pirámide de la Alimentación Saludable. Nutr. Hosp.; 2016; 33, pp. 1-48.
42. Sandri, E.; Pardo, J.; Cantín Larumbe, E.; Cerdá Olmedo, G.; Falcó, A. Analysis of the Influence of Educational Level on the Nutritional Status and Lifestyle Habits of the Young Spanish Population. Front. Public Health; 2024; 12, 1341420. [DOI: https://dx.doi.org/10.3389/fpubh.2024.1341420]
43. Sandri, E.; Modesto i Alapont, V.; Cantín Larumbe, E.; Cerdá Olmedo, G. Analysis of the Influence of Socio-Demographic Variables and Some Nutrition and Lifestyle Habits on Beverage Consumption in the Spanish Population. Foods; 2023; 12, 4310. [DOI: https://dx.doi.org/10.3390/foods12234310]
44. Sandri, E.; Cantín Larumbe, E.; Capoferri, M.; Cerdá Olmedo, G.; Werner, L.U.; Vega-Bello, M.J. Socio-Demographic Determinants of Dietary Choices and Their Impact on Health in Spanish Adults. Front. Public Health; 2024; 12, 1417925. [DOI: https://dx.doi.org/10.3389/fpubh.2024.1417925]
45. Sandri, E.; Borghesi, D.; Cantín Larumbe, E.; Cerdá Olmedo, G.; Vega-Bello, M.J.; Bernalte Martí, V. Intermittent Fasting: Socio-Economic Profile of Spanish Citizens Who Practice It and the Influence of This Dietary Pattern on the Health and Lifestyle Habits of the Population. Nutrients; 2024; 16, 2028. [DOI: https://dx.doi.org/10.3390/nu16132028]
46. Statistics Software|DATAtab. Available online: https://datatab.net/statistics-software (accessed on 12 October 2024).
47. Tomczak, M.; Tomczak, E. The Need to Report Effect Size Estimates Revisited. An Overview of Some Recommended Measures of Effect Size. Trends Sport Sci.; 2014; 21, pp. 19-25.
48. López-Martín, E.; Ardura, D. The Effect Size in Scientific Publication. Educ. XX1 Rev. Fac. Educ.; 2023; 26, pp. 9-17.
49. Akter, T.; Zeba, Z.; Hosen, I.; Al-Mamun, F.; Mamun, M.A. Impact of the COVID-19 pandemic on BMI: Its changes in relation to socio-demographic and physical activity patterns based on a short period. PLoS ONE; 2022; 17, e0266024. [DOI: https://dx.doi.org/10.1371/journal.pone.0266024] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35325012]
50. Elena, S.; Eva, C.L.; Germán, C.O. Changes experienced in the nutritional pattern and in some health habits by the Spanish young adult population according to place of residence. J. Public Health; 2023; [DOI: https://dx.doi.org/10.1007/s10389-023-02134-6]
51. Amuzu, A.; Carson, C.; Watt, H.C.; Lawlor, D.A.; Ebrahim, S. Influence of area and individual lifecourse deprivation on health behaviours: Findings from the British Women’s Heart and Health Study. Eur. J. Prev. Cardiol.; 2009; 16, pp. 169-173. [DOI: https://dx.doi.org/10.1097/HJR.0b013e328325d64d] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/19242356]
52. Carrillo-Álvarez, E.; Costa-Tutusaus, L.; Milà-Villaroel, R.; Krishnan, N.S.; Salinas-Roca, B. Food insecurity and dietary diversity among food aid recipients in urban and rural areas at the COVID-19 outbreak: An exploratory study. World Food Policy; 2024; 10, pp. 33-47. [DOI: https://dx.doi.org/10.1002/wfp2.12070]
53. Rivero-Jiménez, B.; Conde-Caballero, D.; Mariano-Juárez, L. Health and Nutritional Beliefs and Practices among Rural Elderly Population: An Ethnographic Study in Western Spain. Int. J. Environ. Res. Public Health; 2020; 17, 5923. [DOI: https://dx.doi.org/10.3390/ijerph17165923]
54. Skurvydas, A.; Lisinskiene, A.; Lochbaum, M.; Majauskiene, D.; Valanciene, D.; Dadeliene, R.; Fatkulina, N.; Sarkauskiene, A. Did COVID-19 pandemic change people’s physical activity distribution, eating, and alcohol consumption habits as well as body mass index?. Int. J. Environ. Res. Public Health; 2021; 18, 12405. [DOI: https://dx.doi.org/10.3390/ijerph182312405]
55. Ricci, F.; Izzicupo, P.; Moscucci, F.; Sciomer, S.; Maffei, S.; Di Baldassarre, A.; Mattioli, A.V.; Gallina, S. Recommendations for physical inactivity and sedentary behavior during the coronavirus disease (COVID-19) pandemic. Front. Public Health; 2020; 8, 199. [DOI: https://dx.doi.org/10.3389/fpubh.2020.00199]
56. Mattioli, A.V.; Nasi, M.; Cocchi, C.; Farinetti, A. COVID-19 outbreak: Impact of the quarantine-induced stress on cardiovascular disease risk burden. Future Cardiol.; 2020; 16, pp. 539-542. [DOI: https://dx.doi.org/10.2217/fca-2020-0055]
57. World Health Organization. Global Action Plan on Physical Activity 2018–2030: More Active People for a Healthier World [Report]; 2018. Available online: https://iris.who.int/bitstream/handle/10665/272722/9789241514187-eng.pdf?sequence=1&isAllowed=y (accessed on 24 November 2024).
58. Lombardo, M.; Guseva, E.; Perrone, M.A.; Müller, A.; Rizzo, G.; Storz, M.A. Changes in eating habits and physical activity after COVID-19 pandemic lockdowns in Italy. Nutrients; 2021; 13, 4522. [DOI: https://dx.doi.org/10.3390/nu13124522] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34960077]
59. 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, pp. 677-688. [DOI: https://dx.doi.org/10.1177/0145445503261164] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/15911688]
60. Steffen, J.; Schlichtiger, J.; Huber, B.C.; Brunner, S. Altered alcohol consumption during COVID-19 pandemic lockdown. Nutr. J.; 2021; 20, 44. [DOI: https://dx.doi.org/10.1186/s12937-021-00699-0] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33975597]
61. Tebar, W.R.; Christofaro, D.G.D.; Diniz, T.A.; Lofrano-Prado, M.C.; Botero, J.P.; De Almeida Correia, M.; Cucato, G.G.; Ritti-Dias, R.M.; Prado, W.L.D. Increased screen time is associated with alcohol desire and sweetened foods consumption during the COVID-19 pandemic. Front. Nutr.; 2021; 8, 630586. [DOI: https://dx.doi.org/10.3389/fnut.2021.630586]
62. Ingram, J.; Maciejewski, G.; Hand, C.J. Changes in diet, sleep and physical activity are associated with differences in negative mood during COVID-19 lockdown. Front. Psychol.; 2020; 11, 588604. [DOI: https://dx.doi.org/10.3389/fpsyg.2020.588604]
63. Ramos-Padilla, P.; Villavicencio-Barriga, V.D.; Cárdenas-Quintana, H.; Abril-Merizalde, L.; Solís-Manzano, A.; Carpio-Arias, T.V. Eating habits and sleep quality during the COVID-19 pandemic in adult population of Ecuador. Int. J. Environ. Res. Public Health; 2021; 18, 3606. [DOI: https://dx.doi.org/10.3390/ijerph18073606] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33807140]
64. Giustino, V.; Parroco, A.M.; Gennaro, A.; Musumeci, G.; Palma, A.; Battaglia, G. Physical activity levels and related energy expenditure during COVID-19 quarantine among the Sicilian active population: A cross-sectional online survey study. Sustainability; 2020; 12, 4356. [DOI: https://dx.doi.org/10.3390/su12114356]
65. De Oliveira Neto, L.; Elsangedy, H.M.; De Oliveira Tavares, V.D.; La Scala Teixeira, C.V.; Behm, D.G.; Da Silva-Grigoletto, M.E. #TrainingInHome—Home-based training during COVID-19 (SARS-CoV2) pandemic: Physical exercise and behavior-based approach. Rev. Bras. Fisiol. Exerc.; 2020; 19, pp. 9-19. [DOI: https://dx.doi.org/10.33233/rbfe.v19i2.4006]
66. Munteanu, I.; Marc, M.; Gheorghevici, C.; Diaconu, G.A.; Feraru, N.; Sion, D.; Nemes, R.M.; Mahler, B. Sleep quality aspects in post-COVID-19 patients. J. Pers. Med.; 2023; 13, 1125. [DOI: https://dx.doi.org/10.3390/jpm13071125]
67. Pudlo, R.; Jaworska, I.; Szczegielniak, A.; Niedziela, J.; Kułaczkowska, Z.; Nowowiejska-Wiewióra, A.; Jaroszewicz, J.; Gąsior, M. Prevalence of Insomnia in the Early Post-COVID-19 Recovery Period. Int. J. Environ. Res. Public Health; 2022; 19, 14224. [DOI: https://dx.doi.org/10.3390/ijerph192114224]
68. Durán-Agüero, S.; Ortiz, A.; Pérez-Armijo, P.; Vinueza-Veloz, M.F.; Ríos-Castillo, I.; Camacho-Lopez, S.; Cavagnari, B.M.; Nava-González, E.J.; Carpio-Arias, V.; Cordón-Arrivillaga, K. et al. Quality of the diet during the COVID-19 pandemic in 11 Latin-American countries. J. Health Popul. Nutr.; 2022; 41, 33. [DOI: https://dx.doi.org/10.1186/s41043-022-00316-8] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35927689]
69. Błaszczyk-Bębenek, E.; Jagielski, P.; Bolesławska, I.; Jagielska, A.; Nitsch-Osuch, A.; Kawalec, P. Nutrition Behaviors in Polish Adults before and during COVID-19 Lockdown. Nutrients; 2020; 12, 3084. [DOI: https://dx.doi.org/10.3390/nu12103084] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33050404]
70. 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 COVID-19iet Study. Nutrients; 2020; 12, 3119. [DOI: https://dx.doi.org/10.3390/nu12103119]
71. Palmer, K.; Bschaden, A.; Stroebele-Benschop, N. Changes in lifestyle, diet, and body weight during the first COVID-19 19 ‘lockdown’ in a student sample. Appetite; 2021; 167, 105638. [DOI: https://dx.doi.org/10.1016/j.appet.2021.105638] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34388592]
72. Garcia, A.; Higgs, S.; Lluch, A.; Darcel, N.; Davidenko, O. Associations between Perceived Social Eating Norms and Initiation and Maintenance of Changes in Dietary Habits during the First COVID-19 Lockdown in France. Foods; 2021; 10, 2745. [DOI: https://dx.doi.org/10.3390/foods10112745]
73. Bemanian, M.; Mæland, S.; Blomhoff, R.; Rabben, Å.K.; Arnesen, E.K.; Skogen, J.C.; Fadnes, L.T. Emotional Eating in Relation to Worries and Psychological Distress Amid the COVID-19 Pandemic: A Population-Based Survey on Adults in Norway. Int. J. Environ. Res. Public Health; 2020; 18, 130. [DOI: https://dx.doi.org/10.3390/ijerph18010130]
74. Robinson, E.; Boyland, E.; Chisholm, A.; Harrold, J.; Maloney, N.G.; Marty, L.; Mead, B.R.; Noonan, R.; Hardman, C.A. Obesity, eating behavior and physical activity during COVID-19 lockdown: A study of UK adults. Appetite; 2020; 156, 104853. [DOI: https://dx.doi.org/10.1016/j.appet.2020.104853]
75. Rolland, B.; Haesebaert, F.; Zante, E.; Benyamina, A.; Haesebaert, J.; Franck, N. Global Changes and Factors of Increase in Caloric/Salty Food Intake, Screen Use, and Substance Use During the Early COVID-19 Containment Phase in the General Population in France: Survey Study. JMIR Public Health Surveill.; 2020; 6, e19630. [DOI: https://dx.doi.org/10.2196/19630]
76. Marty, L.; De Lauzon-Guillain, B.; Labesse, M.; Nicklaus, S. Food choice motives and the nutritional quality of diet during the COVID-19 lockdown in France. Appetite; 2020; 157, 105005. [DOI: https://dx.doi.org/10.1016/j.appet.2020.105005]
77. Rogers, N.T.; Cummins, S.; Forde, H.; Jones, C.P.; Mytton, O.; Rutter, H.; Sharp, S.J.; Theis, D.; White, M.; Adams, J. Associations between trajectories of obesity prevalence in English primary school children and the UK soft drinks industry levy: An interrupted time series analysis of surveillance data. PLoS Med.; 2023; 20, e1004160. [DOI: https://dx.doi.org/10.1371/journal.pmed.1004160]
78. Sidor, A.; Rzymski, P. Dietary Choices and Habits during COVID-19 Lockdown: Experience from Poland. Nutrients; 2020; 12, 1657. [DOI: https://dx.doi.org/10.3390/nu12061657] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32503173]
79. 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. [DOI: https://dx.doi.org/10.3389/fnut.2020.592112] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33364250]
80. Vandevijvere, S.; De Ridder, K.; Drieskens, S.; Charafeddine, R.; Berete, F.; Demarest, S. Food insecurity and its association with changes in nutritional habits among adults during the COVID-19 confinement measures in Belgium. Public Health Nutr.; 2020; 24, pp. 950-956. [DOI: https://dx.doi.org/10.1017/S1368980020005005]
81. Ahmed, J.; AlSaleh, A.; Almarabheh, A.J.; Ismail, L.C.; Almuqahwi, A.a.M.; AlOmer, H.W.A.; AlAlhareth, I.M.; Albader, S.J.M.; Alhajeri, S.S.; Dhaheri, A.S.A. Lifestyle and Dietary Patterns during the COVID-19 Lockdown in Bahrain: A Web-Based Cross-Sectional Study. Nutrients; 2023; 15, 2543. [DOI: https://dx.doi.org/10.3390/nu15112543]
82. Papadaki, Š. The amount of excise tax and its effect on the consumption of alcohol and cigarettes in European countries. Adiktologie; 2022; 22, pp. 234-243. [DOI: https://dx.doi.org/10.35198/01-2022-004-0005]
83. Khubchandani, J.; Sharma, S.; Webb, F.J.; Wiblishauser, M.J.; Bowman, S.L. Post-lockdown depression and anxiety in the USA during the COVID-19 pandemic. J. Public Health; 2020; 43, pp. 246-253. [DOI: https://dx.doi.org/10.1093/pubmed/fdaa250] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33426559]
84. Caycho-Rodríguez, T.; Tomás, J.M.; Valencia, P.D.; Ventura-León, J.; Vilca, L.W.; Carbajal-León, C.; Reyes-Bossio, M.; White, M.; Rojas-Jara, C.; Polanco-Carrasco, R. et al. COVID-19 anxiety, psychological well-being and preventive behaviors during the COVID-19 pandemic in Latin America and the Caribbean: Relationships and explanatory model. Curr. Psychol.; 2022; 43, pp. 13159-13173. [DOI: https://dx.doi.org/10.1007/s12144-022-03389-0]
85. Madalı, B.; Alkan, Ş.B.; Örs, E.D.; Ayrancı, M.; Taşkın, H.; Kara, H.H. Emotional eating behaviors during the COVID-19 pandemic: A cross-sectional study. Clin. Nutr. ESPEN; 2021; 46, pp. 264-270. [DOI: https://dx.doi.org/10.1016/j.clnesp.2021.09.745]
86. McAtamney, K.; Mantzios, M.; Egan, H.; Wallis, D.J. Emotional eating during COVID-19 in the United Kingdom: Exploring the roles of alexithymia and emotion dysregulation. Appetite; 2021; 161, 105120. [DOI: https://dx.doi.org/10.1016/j.appet.2021.105120]
87. Ramalho, S.M.; Trovisqueira, A.; De Lourdes, M.; Gonçalves, S.; Ribeiro, I.; Vaz, A.R.; Machado, P.P.P.; Conceição, E. The impact of COVID-19 lockdown on disordered eating behaviors: The mediation role of psychological distress. Eat. Weight Disord.—Stud. Anorex. Bulim. Obes.; 2021; 27, pp. 179-188. [DOI: https://dx.doi.org/10.1007/s40519-021-01128-1]
88. Zagaria, A.; Serena, S.; Musetti, A.; Rapelli, G.; De Gennaro, L.; Plazzi, G.; Franceschini, C. Poor sleep hygiene practices are associated with a higher increase in sleep problems during the COVID-19 pandemic: A latent change score model. J. Sleep Res.; 2023; 33, e14057. [DOI: https://dx.doi.org/10.1111/jsr.14057] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37776031]
89. An, H.; Chen, W.; Wang, C.; Yang, H.; Huang, W.; Fan, S. The Relationships between Physical Activity and Life Satisfaction and Happiness among Young, Middle-Aged, and Older Adults. Int. J. Environ. Res. Public Health; 2020; 17, 4817. [DOI: https://dx.doi.org/10.3390/ijerph17134817]
90. Castañeda-Babarro, A.; Arbillaga-Etxarri, A.; Gutiérrez-Santamaría, B.; Coca, A. Physical Activity Change during COVID-19 Confinement. Int. J. Environ. Res. Public Health; 2020; 17, 6878. [DOI: https://dx.doi.org/10.3390/ijerph17186878] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32967091]
91. McDowell, C.P.; Herring, M.P.; Lansing, J.; Brower, C.; Meyer, J.D. Working From Home and Job Loss Due to the COVID-19 Pandemic Are Associated With Greater Time in Sedentary Behaviors. Front. Public Health; 2020; 8, 597619. [DOI: https://dx.doi.org/10.3389/fpubh.2020.597619] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33224922]
92. 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, pp. 1166-1170. [DOI: https://dx.doi.org/10.1002/eat.23318]
93. Salari, N.; Hosseinian-Far, A.; Jalali, R.; Vaisi-Raygani, A.; Rasoulpoor, S.; Mohammadi, M.; Rasoulpoor, S.; Khaledi-Paveh, B. Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: A systematic review and meta-analysis. Glob. Health; 2020; 16, 57. [DOI: https://dx.doi.org/10.1186/s12992-020-00589-w]
94. Ji, X.; Zhan, T.; Zhu, T. Impact of COVID-19 on negative body image: Evidence based on social media data. Soc. Sci. Med.; 2023; 340, 116461. [DOI: https://dx.doi.org/10.1016/j.socscimed.2023.116461]
95. Corno, G.; Paquette, A.; Monthuy-Blanc, J.; Ouellet, M.; Bouchard, S. The Relationship Between Women’s Negative Body Image and Disordered Eating Behaviors During the COVID-19 Pandemic: A Cross-Sectional Study. Front. Psychol.; 2022; 13, 856933. [DOI: https://dx.doi.org/10.3389/fpsyg.2022.856933] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35401386]
96. Robertson, M.; Duffy, F.; Newman, E.; Bravo, C.P.; Ates, H.H.; Sharpe, H. Exploring changes in body image, eating and exercise during the COVID-19 lockdown: A UK survey. Appetite; 2020; 159, 105062. [DOI: https://dx.doi.org/10.1016/j.appet.2020.105062]
97. Ruggiero, E.; Mignogna, C.; Costanzo, S.; Persichillo, M.; Di Castelnuovo, A.; Esposito, S.; Cerletti, C.; Donati, M.B.; De Gaetano, G.; Iacoviello, L. et al. Changes in the consumption of foods characterising the Mediterranean dietary pattern and major correlates during the COVID-19 confinement in Italy: Results from two cohort studies. Int. J. Food Sci. Nutr.; 2021; 72, pp. 1105-1117. [DOI: https://dx.doi.org/10.1080/09637486.2021.1895726]
98. Pfeifer, D.; Rešetar, J.; Kljusurić, J.G.; Krbavčić, I.P.; Bender, D.V.; Rodríguez-Pérez, C.; Ruíz-López, M.D.; Šatalić, Z. Cooking at home and adherence to the Mediterranean diet during the COVID-19 confinement: The experience from the Croatian COVID-19iet Study. Front. Nutr.; 2021; 8, 617721. [DOI: https://dx.doi.org/10.3389/fnut.2021.617721] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33869262]
99. Mititelu, M. The impact of COVID-19 lockdown on the lifestyle and dietary patterns among Romanian population. Farmacia; 2021; 69, pp. 1-11. [DOI: https://dx.doi.org/10.31925/farmacia.2021.1.1]
100. Martínez-Vázquez, S.E.; Ceballos-Rasgado, M.; Posada-Velázquez, R.; Hunot-Alexander, C.; Nava-González, E.J.; Ramírez-Silva, I.; Aguilar-López, D.K.; Quiroz-Olguín, G.; López-Jara, B.; Delgado-De-La-Cruz, C. et al. Perceived diet quality, eating behaviour, and lifestyle changes in a Mexican population with internet access during confinement for the COVID-19 pandemic: ESCAN-COVID-1919Mx survey. Nutrients; 2021; 13, 4256. [DOI: https://dx.doi.org/10.3390/nu13124256]
101. Huancahuire-Vega, S.; Newball-Noriega, E.E.; Rojas-Humpire, R.; Saintila, J.; Rodriguez-Vásquez, M.; Ruiz-Mamani, P.G.; Morales-García, W.C.; White, M. Changes in eating habits and lifestyles in a Peruvian population during social isolation for the COVID-19 pandemic. J. Nutr. Metab.; 2021; 2021, 4119620. [DOI: https://dx.doi.org/10.1155/2021/4119620] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34868677]
102. Singh, B.; Jain, S.; Rastogi, A. Effects of nationwide COVID-19 lockdown on lifestyle and diet. J. Fam. Med. Prim. Care; 2021; 10, pp. 1246-1250. [DOI: https://dx.doi.org/10.4103/jfmpc.jfmpc_2046_20]
103. Deschasaux-Tanguy, M.; Druesne-Pecollo, N.; Esseddik, Y.; De Edelenyi, F.S.; Allès, B.; Andreeva, V.A.; Baudry, J.; Charreire, H.; Deschamps, V.; Egnell, M. et al. Diet and physical activity during the coronavirus disease 2019 (COVID-19) lockdown (March–May 2020): Results from the French NutriNet-Santé cohort study. Am. J. Clin. Nutr.; 2020; 113, pp. 924-938. [DOI: https://dx.doi.org/10.1093/ajcn/nqaa336]
104. Buckland, N.J.; Swinnerton, L.F.; Ng, K.; Price, M.; Wilkinson, L.L.; Myers, A.; Dalton, M. Susceptibility to increased high energy dense sweet and savoury food intake in response to the COVID-19 lockdown: The role of craving control and acceptance coping strategies. Appetite; 2020; 158, 105017. [DOI: https://dx.doi.org/10.1016/j.appet.2020.105017]
105. Cummings, J.R.; Ackerman, J.M.; Wolfson, J.A.; Gearhardt, A.N. COVID-19 stress and eating and drinking behaviors in the United States during the early stages of the pandemic. Appetite; 2021; 162, 105163. [DOI: https://dx.doi.org/10.1016/j.appet.2021.105163] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33587985]
106. Malta, D.C.; Szwarcwald, C.L.; De Azevedo Barros, M.B.; Gomes, C.S.; Machado, Í.E.; De Souza Júnior, P.R.B.; Romero, D.E.; Lima, M.G.; Damacena, G.N.; De Fátima Pina, M. et al. A pandemia da COVID-19 e as mudanças no estilo de vida dos brasileiros adultos: Um estudo transversal, 2020. Epidemiol. Serv. Saúde; 2020; 29, e2020407. [DOI: https://dx.doi.org/10.1590/s1679-49742020000400026]
107. Pertuz-Cruz, S.L.; Molina-Montes, E.; Rodríguez-Pérez, C.; Guerra-Hernández, E.J.; De Rangel, O.P.C.; Artacho, R.; Verardo, V.; Ruiz-Lopez, M.D.; García-Villanova, B. Exploring dietary behavior changes due to the COVID-19 confinement in Colombia: A national and regional survey study. Front. Nutr.; 2021; 8, 644800. [DOI: https://dx.doi.org/10.3389/fnut.2021.644800]
108. Sun, Y.H. Health concern, food choice motives, and attitudes toward healthy eating: The mediating role of food choice motives. Appetite; 2008; 51, pp. 42-49. [DOI: https://dx.doi.org/10.1016/j.appet.2007.11.004] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/18187232]
109. Karam, J.; Haddad, C.; Sacre, H.; Serhan, M.; Salameh, P.; Jomaa, L. Financial wellbeing and quality of life among a sample of the Lebanese population: The mediating effect of food insecurity. Front. Nutr.; 2022; 9, 906646. [DOI: https://dx.doi.org/10.3389/fnut.2022.906646] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35967774]
110. Urhan, M.; Okut Aysin, E. Nutritional and health behaviour predictors of the weight gain during the COVID-19 pandemic. Eur. J. Nutr.; 2022; 61, pp. 2993-3002. [DOI: https://dx.doi.org/10.1007/s00394-022-02862-7] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35322334]
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
© 2024 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/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Abstract
The aim of this study was to investigate the changes in habits regarding the health and lifestyle of the Spanish population during and after the COVID-19 pandemic. A cross-sectional design was used. Data were collected during the pandemic from 22,181 participants and after the pandemic from 3907 participants using the NutSo-HH Scale, assessing demographic, nutritional, and lifestyle variables. Key findings reveal a slight increase in exercise duration (+6.61%) post-pandemic, along with reductions in fried food (−3.57%), juice (−6.45%), and alcohol consumption (−9.66%). Conversely, there were notable increases in the consumption of ultra-processed foods (+2.16%), soft drinks (+6.47%), and coffee/energy drinks (+38.95%). Sleep quality, body image, and self-perceived health showed minor declines. These findings indicate that despite some positive behavioral changes, there is still a significant dependence on unhealthy dietary choices, negatively impacting both mental and physical health. The results highlight the need for public health strategies which encourage healthier eating, increased physical activity, and better sleep quality to reduce the long-term effects of lifestyle changes brought on by the pandemic. Focused interventions are necessary to curb the rising consumption of ultra-processed foods and sugary beverages while fostering overall well-being. This study underscores the vital role of ongoing surveillance and customized public health initiatives to enhance general health in the post-pandemic era.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details
; Werner, Lisa Ursula 2
; Martí, Vicente Bernalte 3
1 Faculty of Medicine and Health Sciences, Catholic University of Valencia San Vicente Mártir, c/Quevedo, 2, 46001 Valencia, Spain
2 Faculty of Teaching and Science of Education, Catholic University of Valencia San Vicente Mártir, c/Quevedo, 2, 46001 Valencia, Spain;
3 Predepartmental Nursing Unit, Faculty of Health Sciences, Jaume I University, Avda. Sos Baynat, s/n, 12071 Castellón de la Plana, Spain;