Abstract
Background and aims
The coronavirus disease 2019 (COVID‐19) outbreak has led to an unprecedented public health crisis. In Peru, although the quarantine is no longer mandatory, it was during the first months of 2020. To date, no studies have assessed the impact of the COVID-19 on the eating patterns and lifestyle context in the country. We aimed to describe the eating habits, lifestyle behaviors and stress during the COVID-19 pandemic quarantine among Peruvian adults.
Methods
We conducted a cross-sectional study. We used an online survey to collect information regarding eating habits, self-perceived stress and sedentary lifestyle among adults over 18 years of age residing in Lima-Peru and who complied with strict home quarantine. We presented our data according to the weight variation of the participants.
Results
A total of 686 were finally included in the study. The 82.9% were female, the median BMI was 25.97 kg/m2 (IQR: 23.37–29.41) and 68.2% reported a significant variation in their weight (38.9% increased and 29.3% lost weight). All bad habits were significantly associated with weight gain, except for prolonged fasting. Additionally, a sitting time longer than usual (p = 0.001), being in front of a screen for more than five hours in the last week (p = 0.002), and most of the stressful scenarios were significantly associated with weight gain.
Conclusion
Almost four out of ten participants gained weight during the quarantine. This was associated with unhealthy eating habits, physical inactivity, and stressful scenarios.
Keywords: Life style, Eating behavior, COVID-19, Quarantine, Peru
Introduction
The ongoing coronavirus disease 2019 (COVID-19) outbreak has led to an unprecedented public health crisis and a global health emergency (Arshad Ali et al., 2020). By the end of October 2020, more than 42 million cases and more than 1.1 million deaths had been reported worldwide (World Health Organization, 2020a). America is the continent with the highest rate of reported COVID-19 cases, with USA, Brazil and Peru as the most affected countries (Acosta, 2020; Rodriguez-Morales et al., 2020).
Due to the rapid widespread and severe public health disruption, the World Health Organization (WHO) recommended various strategies to reduce the COVID-19 transmission. For example, physical distancing, home quarantine, closure of schools, universities and non-essential businesses, among others (World Health Organization, 2020b). Regarding quarantine, although it has had a positive impact on reducing the transmission of COVID-19 (Sen, Karaca-Mandic & Georgiou, 2020; Pan et al., 2020), some studies have reported that it could trigger high levels of anxiety, depressive symptoms and post-traumatic stress disorders (Brooks et al., 2020; Fawaz & Samaha, 2020; Guo et al., 2020). Naturally, this could also predispose to changes in lifestyles and unhealthy nutritional habits (Papandreou et al., 2020; Di Renzo et al., 2020; Górnicka et al., 2020; Ruiz-Roso et al., 2020b).
In Peru, the state of emergency became official on March 16 (Presidencia del Consejo de Ministros, 2010). Since then, physical distancing measures and home quarantine were promoted, and although the quarantine is no longer mandatory (there are only some restriction hours), it was during the first months. To date, few studies have described some lifestyles during the quarantine in Latin America (Werneck et al., 2020; Ruíz-Roso et al., 2020c). However, none of them have been conducted in Peru, which is one of the countries with the highest number of cases and deaths due to COVID-19 worldwide (World Health Organization, 2021).
This study aimed to describe the eating habits, lifestyle behaviors and stress during the COVID-19 pandemic quarantine among Peruvian adults.
Methods
Study design
We conducted a cross-sectional study in July, during the mandatory quarantine in Peru.
Study population and context
We included individuals aged 18 years and over who were in Lima at the survey time and with a good precision of the self-reported weight and height (≥8 points on a 0–10 scale). For the latter, participants were asked on a scale of 0 (no accuracy) to 10 (total accuracy) to report how accurate they felt when answering the questions regarding their anthropometric values. Surveys with incomplete information were not considered for analysis.
Lima is the capital of Peru and is the department with the largest population in the country. According to the National Institute of Statistics and Informatics, by 2018, it had a total population of 9 million 320,000 inhabitants(Instituto Nacional de Estadística e Informática, 2018).
Variables and instruments
We developed a self-administered web-based four-section survey. The first section collected sociodemographic and self-reported anthropometric data (age, sex, self-reported height and weight and precision of the self-report, marital status and self-report of weight variation from the beginning of the quarantine until the moment of the survey). Weight variation was further categorized in “lost weight” (if the participant lost at least 2.5 kg), “weight stable” (no changes or a variation less than 2.5 kg) and “gained weight” (if the participant gained at least 2.5 kg). The second section consisted of an eating habits questionnaire previously validated in a Spanish-speaking population (Reséndiz Barragán et al., 2015). This questionnaire had 17 items with Likert-type responses ranging from 0 to 6 (0 = never, 1 = less than once a month, 2 = once a month, 3 = two or three times a month, 4 = once or twice per week, 5 = three or four times a week, and 6 = every day). For the present study, we categorized the responses as: never, one to three times a month, one to four times a week, every day.
For the third and fourth sections, we used some questions from the Spanish versions of the “Last 7 days sedentary behavior questionnaire” (SIT-Q) (Felez-Nobrega et al., 2019) and the “Perceived Stress Scale” (PSS) (Baik et al., 2019; Remor, 2006). Both instruments have been used in different studies during the quarantine in the context of COVID-19 (Zachary et al., 2020; Gallè et al., 2020; Iasevoli et al., 2020). It is important to mention that, since the present study’s objective was mainly descriptive, we opted to only select some questions from each questionnaire.
Procedures
The survey link was distributed using social media (Facebook and other social networking sites) to reach the highest number of participants from all the districts in Lima, Peru. The informed consent was at the beginning of the online (Google® form) survey, including the estimated time needed to complete the survey (15–20 min). If a participant wanted to receive his/her detailed results in a personalized way, he/she was asked to enter his/her e-mail. It is important to mention that all participants voluntarily opted for this option. This also allowed us to check and drop duplicates before the analysis.
Statistical analysis
We presented the descriptive results for numeric variables as means with their standard deviation (SD) or medians with interquartile range (IQR). Categorical variables were presented as frequencies and percentages. According to the weight variation, each of the eating habits, sedentary behaviors, and stressful scenarios items were compared using the one-way ANOVA or the Kruskal Wallis test as appropriate for continuous variables, and the Chi2 or Fisher exact test for categorical variables. We used STATA v16.0 for our analyses.
Ethics
The Impacta Institutional Review Board, Lima, Peru (RCEI-17) approved the present study (00110-2020-CE). We did not collect personal data, and participation was voluntary and anonymous. The first page of the survey had the consent form. The participants that agreed had to mark the option “I have read the consent form, and I agree with it. I would like to start the survey”. Only the participants who marked this option were able to continue with the following survey questions.
Results
A total of 1,031 adults completed the survey, and 686 considered that they could report their weight with an accuracy of eight points or more. The 82.9% were female, 66% were single, and the median age was 31 (IQR: 25-41). The median BMI was 25.97 kg/m2 (IQR: 23.37–29.41) and 68.2% reported a significant variation in their weight (38.9% increased and 29.3% lost weight) from the start of quarantine to the date of the application of the survey.
Tables 1–3 reports absolute and relative frequencies of eating habits, sedentary behavior, stressful scenarios and weight variation during the quarantine. Relative frequencies were calculated by rows variables (Questions). Table 1 shows significant differences in most of the eating habits. All bad habits were significantly associated with weight gain, except for prolonged fasting (that was associated with weight loss, p = 0.028). Almost 50% of the participants who reported gaining weight answered that they had snacks between meals (p = 0.030) or had sugar cravings every day (p = 0.001). Similarly, these participants were the ones who reported having significantly more snacks between meals (p = 0.002). Additionally, a sitting time longer than usual (p = 0.001), being in front of a screen for more than five hours in the last week (p = 0.002), and most of the stressful scenarios were significantly associated with weight gain (Tables 2 and 3). Some of these scenarios included being upset because of something that happened unexpectedly (p = 0.001), felt nervous and stressed (p = 0.001), found that they could not cope with all the things that they had to do (p = 0.024), and felt difficulties were piling up so high that they could not overcome them (p = 0.020).
Table 1. Eating habits and weight variation during quarantine.
| Question | Lost weight (n = 201) | Weight stable (n = 218) | Gained weight (n = 267) | p |
|---|---|---|---|---|
| “How often do you…” | ||||
| Snack between meals? | 0.030* | |||
| Never | 24 (42.9) | 15 (26.8) | 17 (30.4) | |
| One to three times a month | 32 (33.3) | 35 (36.5) | 29 (30.2) | |
| One to four times a week | 85 (27.6) | 106 (34.4) | 117 (38.0) | |
| Everyday | 60 (26.6) | 62 (27.4) | 104 (46.0) | |
| Have long fasting periods? | 0.028* | |||
| Never | 99 (27.1) | 106 (29.0) | 160 (43.8) | |
| One to three times a month | 43 (29.3) | 56 (38.1) | 48 (32.7) | |
| One to four times a week | 40 (29.9) | 45 (33.6) | 49 (36.6) | |
| Everyday | 19 (47.5) | 11 (27.5) | 10 (25.0) | |
| Eat until you feel uncomfortable? | 0.001* | |||
| Never | 79 (30.7) | 98 (38.1) | 80 (31.1) | |
| One to three times a month | 90 (31.4) | 97 (33.8) | 100 (34.8) | |
| One to four times a week | 28 (23.7) | 19 (16.1) | 71 (60.2) | |
| Everyday | 4 (16.7) | 4 (16.7) | 16 (66.7) | |
| Eat without feeling physical hunger? | 0.001* | |||
| Never | 56 (30.0) | 77 (41.2) | 54 (28.9) | |
| One to three times a month | 81 (31.9) | 89 (35.0) | 84 (33.1) | |
| One to four times a week | 55 (29.7) | 41 (22.2) | 89 (48.1) | |
| Everyday | 9 (15.0) | 11 (18.3) | 40 (66.7) | |
| Feel guilty or sad after eating? | 0.001* | |||
| Never | 72 (31.4) | 103 (45.0) | 54 (23.6) | |
| One to three times a month | 83 (34.3) | 78 (32.2) | 81 (33.5) | |
| One to four times a week | 32 (26.2) | 23 (18.8) | 67 (54.9) | |
| Everyday | 14 (15.1) | 14 (15.1) | 85 (34.3) | |
| Stressed by the way you eat? | 0.001* | |||
| Never | 85 (34.3) | 111 (44.8) | 52 (21.0) | |
| One to three times a month | 54 (27.6) | 71 (36.2) | 71 (36.2) | |
| One to four times a week | 43 (34.1) | 20 (15.9) | 63 (50.0) | |
| Everyday | 19 (16.4) | 16 (13.8) | 81 (69.8) | |
| Drink sodas, processed juices or shakes? | 0.001* | |||
| Never | 47 (32.2) | 57 (39.0) | 42 (28.8) | |
| One to three times a month | 119 (32.0) | 115 (30.9) | 138 (37.1) | |
| One to four times a week | 31 (20.7) | 39 (26.0) | 80 (53.3) | |
| Everyday | 4 (22.2) | 7 (38.9) | 7 (38.9) | |
| Drink water? | 0.001* | |||
| Never | 3 (15.8) | 3 (15.8) | 13 (68.4) | |
| One to three times a month | 9 (34.6) | 3 (11.5) | 14 (53.9) | |
| One to four times a week | 26 (21.9) | 33 (27.7) | 60 (50.4) | |
| Everyday | 163 (31.2) | 179 (34.3) | 180 (34.5) | |
| Have sugar cravings? | 0.001* | |||
| Never | 11 (36.7) | 11 (36.7) | 8 (26.7) | |
| One to three times a month | 75 (36.6) | 70 (34.2) | 60 (29.3) | |
| One to four times a week | 74 (28.7) | 90 (34.9) | 94 (36.4) | |
| Everyday | 41 (21.24) | 47 (24.4) | 105 (54.4) | |
| Have salt cravings? | 0.001* | |||
| Never | 20 (31.8) | 26 (41.3) | 17 (27.0) | |
| One to three times a month | 86 (34.4) | 88 (35.2) | 76 (30.4) | |
| One to four times a week | 65 (24.9) | 75 (28.7) | 121 (46.4) | |
| Everyday | 30 (26.8) | 29 (25.9) | 53 (47.3) | |
| Have cravings for fatty foods? | 0.001* | |||
| Never | 21 (25.92) | 39 (48.2) | 21 (25.9) | |
| One to three times a month | 123 (33.8) | 125 (34.3) | 116 (31.9) | |
| One to four times a week | 47 (24.1) | 44 (22.6) | 104 (53.3) | |
| Everyday | 10 (21.7) | 10 (21.7) | 26 (56.5) | |
| Drink natural juices? | 0.007* | |||
| Never | 30 (43.5) | 16 (23.2) | 23 (33.3) | |
| One to three times a month | 72 (28.8) | 82 (32.8) | 96 (38.4) | |
| One to four times a week | 71 (29.3) | 66 (27.3) | 105 (43.4) | |
| Everyday | 28 (22.4) | 54 (43.2) | 43 (34.4) | |
| Leave the plate “empty” when you finish eating? | 0.538* | |||
| Never | 10 (38.5) | 10 (38.5) | 6 (23.1) | |
| One to three times a month | 9 (25.0) | 10 (27.8) | 17 (47.2) | |
| One to four times a week | 41 (29.1) | 40 (28.4) | 60 (42.6) | |
| Everyday | 141 (29.2) | 158 (32.7) | 184 (38.1) | |
| Have breakfast in the week? | 0.016* | |||
| One to two days | 24 (39.3) | 18 (29.5) | 19 (31.2) | |
| Three to five days | 32 (25.4) | 30 (23.8) | 64 (50.8) | |
| Six to seven days | 145 (29.1) | 170 (34.1) | 184 (36.9) | |
| Have lunch in the week? | 0.756* | |||
| One to two days | 5 (25.0) | 6 (30.0) | 9 (45.0) | |
| Three to five days | 10 (23.8) | 12 (28.6) | 20 (47.6) | |
| Six to seven days | 186 (29.8) | 200 (32.1) | 238 (38.1) | |
| Have dinner in the week? | 0.016* | |||
| One to two days | 29 (40.9) | 19 (26.8) | 23 (32.4) | |
| Three to five days | 37 (21.8) | 52 (30.6 ) | 81 (47.7) | |
| Six to seven days | 135 (30.3) | 147 (33.0) | 163 (36.6) | |
| “How many…” | ||||
| Main meals do you have per day? | 3 (2-3) | 3 (2-3) | 3 (2-3) | 0.198† |
| Snacks between meals do you have per day? | 1.30 (0.88) | 1.25 (0.79) | 1.51 (0.82) | 0.002†† |
| D. you… | ||||
| Skip meals to take care of your figure? | 0.001* | |||
| No | 53 (21.0) | 88 (34.8) | 112 (44.3) | |
| Yes | 148 (34.2) | 130 (30.02) | 155 (35.8) |
Notes:
Chi2 test.
Kruskal Wallis.
ANOVA.
Table 3. Stressful scenarios and weight variation during quarantine.
| Question: “In the last month, how often have you…” | Lost weight (n = 201) | Weight stable (n = 218) | Gained weight (n = 267) | p |
|---|---|---|---|---|
| Been upset because of something that happened unexpectedly | 0.001* | |||
| Never or almost never | 57 (32.8) | 64 (36.8) | 53 (30.5) | |
| Sometimes | 90 (28.0) | 113 (35.1) | 119 (37.0) | |
| Fairly often or very often | 54 (28.4) | 41 (21.6) | 95 (50.0) | |
| You felt that you were unable to control the important things in your life? | 0.051* | |||
| Never or almost never | 83 (31.9) | 89 (34.2) | 88 (33.9) | |
| Sometimes | 78 (29.1) | 88 (32.8) | 102 (38.1) | |
| Fairly often or very often | 40 (25.3) | 41 (26.0) | 77 (48.7) | |
| Felt nervous and "stressed"? | 0.001* | |||
| Never or almost never | 39 (37.5) | 32 (30.8) | 33 (31.7) | |
| Sometimes | 74 (28.2) | 102 (38.9) | 86 (32.8) | |
| Fairly often or very often | 88 (27.5) | 84 (26.3) | 148 (46.3) | |
| Felt confident about your ability to handle your personal problems? | 0.263* | |||
| Never or almost never | 14 (26.4) | 19 (35.9) | 20 (37.7) | |
| Sometimes | 51 (25.1) | 61 (30.1) | 91 (44.8) | |
| Fairly often or very often | 136 (31.6) | 138 (32.1) | 156 (36.3) | |
| Felt that things were going your way? | 0.001* | |||
| Never or almost never | 13(33.3) | 9 (23.1) | 17 (43.6) | |
| Sometimes | 49 (20.6) | 75 (31.5) | 114 (47.9) | |
| Fairly often or very often | 139 (34.0) | 134 (32.8) | 136 (33.3) | |
| Found that you could not cope with all the things that you had to do? | 0.024* | |||
| Never or almost never | 87 (34.1) | 81 (31.8) | 87 (34.1) | |
| Sometimes | 85 (27.8) | 104 (34.0) | 117 (38.2) | |
| Fairly often or very often | 29 (23.2) | 33 (26.4) | 63 (50.4) | |
| Been able to control irritations in your life? | 0.034* | |||
| Never or almost never | 3 (14.3) | 9 (42.9) | 9 (42.9) | |
| Sometimes | 44 (26.7) | 42 (25.5) | 79 (47.9) | |
| Fairly often or very often | 154 (30.8) | 167 (33.4) | 179 (35.8) | |
| Felt that you were on top of things? | 0.056* | |||
| Never or almost never | 13 (21.5) | 24 (36.9) | 27 (41.5) | |
| Sometimes | 60 (24.8) | 75 (31.0) | 107 (44.2) | |
| Fairly often or very often | 127 (33.5) | 119 (31.4) | 133 (35.1) | |
| Felt difficulties were piling up so high that you could not overcome them? | 0.020* | |||
| Never or almost never | 108 (32.2) | 115 (34.3) | 112 (33.4) | |
| Sometimes | 69 (27.4) | 79 (31.4) | 104 (41.3) | |
| Fairly often or very often | 24 (24.2) | 24 (24.2) | 51 (51.5) |
Notes:
Chi2 test.
Table 2. Sedentary behavior and weight variation during quarantine.
| Question: “In the last week, how long…” | Lost weight (n = 201) | Weight stable (n = 218) | Gained weight (n = 267) | p |
|---|---|---|---|---|
| Have you been sitting or lying down? | 0.001* | |||
| Less than normal | 36 (43.9) | 25 (30.5) | 21 (25.6) | |
| About the same | 45 (35.7) | 50 (39.7) | 31 (24.6) | |
| More than usual | 120 (25.1) | 143 (29.9) | 215 (45.0) | |
| Did you sit for breakfast, lunch, or dinner? | 0.940* | |||
| <30 min | 129 (29.5) | 142 (32.5) | 166 (38.0) | |
| 30–60 min | 51 (30.0) | 51 (30.0) | 68 (40.0) | |
| >1 h | 21 (26.6) | 25 (31.7) | 33 (41.8) | |
| Did you sit or lie down in front of a screen? | 0.002* | |||
| <60 min | 51 (33.1) | 54 (35.1) | 49 (31.8) | |
| 1–3 h | 60 (35.1) | 55 (32.2) | 56 (32.8) | |
| 3–5 h | 30 (29.4) | 38 (37.3) | 34 (33.3) | |
| >5 h | 60 (23.2) | 71 (27.4) | 128 (49.4) | |
| Did you sit while reading a book? | 0.469* | |||
| <60 min | 171 (29.7) | 183 (31.8) | 221 (38.4) | |
| 1–3 h | 26 (28.9) | 25 (27.8) | 39 (43.3) | |
| 3–5 h | 4 (19.1) | 10 (47.6) | 7 (33.3) | |
| Did you sit while playing cards or solving puzzles? | 0.244† | |||
| <60 min | 177 (29.1) | 187 (30.8) | 244 (40.1) | |
| 1–3 h | 18 (28.6) | 27 (42.9) | 18 (28.6) | |
| 3–5 h | 6 (40.0) | 4 (26.7) | 5 (33.3) | |
| Did you sit while listening to music? | 0.333* | |||
| <60 min | 134 (28.4) | 157 (33.3) | 181 (38.4) | |
| 1–3 h | 47 (34.8) | 39 (28.9) | 49 (36.3) | |
| 3–5 h | 20 (25.3) | 22 (27.9) | 37 (46.8) |
Notes:
Chi2 test.
Fisher exact test.
Discussion
Before describing the eating behaviors during quarantine, it is important to note that it is expected that the availability of food would be restricted during this period. This already makes it difficult to eat healthy foods (Díez, Bilal & Franco, 2019; Bilal et al., 2018). Also, quarantine itself reduces the possibility of physical activity, promoting a sedentary lifestyle (Fernández-Sanjurjo et al., 2018), which can also generate a significant neuropsychiatric burden (Troyer, Kohn & Hong, 2020). This has been evidenced by our results, as the participants manifested different stressful situations during the quarantine. This, in turn, may be related to the excessive intake of “comfort foods” (such as pizzas, fried chicken, burgers, French fries, among others) (Moynihan et al., 2015), which naturally leads to weight gain. These foods, mainly rich in sugar and carbohydrates, can reduce stress as they stimulate serotonin production with a positive effect on mood (Lima et al., 2020). However, this food-craving effect of carbohydrates is proportional to the glycemic index of these “comfort foods”, associated with an increased risk of developing obesity and cardiovascular disease, which increase the risk of more severe complications from COVID-19 (Yannakoulia et al., 2008).
COVID-19 has had a negative psychological impact worldwide, not only due to the risk of infection but also due to the different measures implemented to contain the outbreak spread (Guo et al., 2020; Lal et al., 2020). During the COVID-19 outbreak, several studies have reported an increase in the prevalence of eating disorders (Cooper et al., 2020; Baenas et al., 2020; Phillipou et al., 2020). Similarly, lower psychological health has been associated with higher body shape and weight concerns (Haddad et al., 2020). In this sense, this quarantine can be defined as an unprecedented stressful event that has negatively affected individuals’ eating patterns (Bin Zarah, Enriquez-Marulanda & Andrade, 2020). In our study, many participants frequently reported unhealthy eating habits, such as eating until feeling uncomfortable, eating without feeling physical hunger, and feeling guilty or sad after eating. Our results agree with current evidence that suggests a strong relationship between unhealthy eating behaviors and stress, anxiety and other mental disorders (Yau & Potenza, 2013).
Regular physical activity can be beneficial not only for weight loss but also for strengthening the immune system (Zheng et al., 2015). In fact, low–moderate exercise has proven to be beneficial for the innate immune response against respiratory infections (Matricardi, Dal Negro & Nisini, 2020) and could improve some clinical conditions related with severe COVID-19 (Dwyer et al., 2020). However, this has been limited in some cases due to the closure of gyms and public open spaces. We found a high frequency of sedentary lifestyles and too much time in front of screens during the quarantine. Similar results have been reported in other studies worldwide (Meyer et al., 2020; Zheng et al., 2020; Ruiz-Roso et al., 2020a). We also found that this sedentary behavior was related to weight gain among the study participants.
Our study had some limitations. First, the weight variation was self-reported. However, we do not consider this as a continuous variable but rather as an ordinal scale variable. Additionally, participants were asked -on a scale of 1 to 10- to report how accurate they felt they could be answering this question. Only the reliable answers (defined as a score ≥8) were chosen. Second, the study was conducted using an online survey. Thus, the population included was the one that responded on social networks or via e-mail. This could limit the extrapolation of our results to the adult population that has access to social media platforms.
Some strengths should also be highlighted. The current study provides valuable information on eating habits and lifestyle behaviors in the context of an unprecedented event worldwide. Moreover, it is the first published study that have addressed this topic in Peru, which is one of the countries with the highest number of cases and deaths due to COVID-19 worldwide. Our results may be useful for implementing public policies to promote healthy lifestyles during the pandemic. In addition, our study provides insight for future research to implement and evaluate different coping strategies to avoid comorbidities associated with weight gain, especially for future circumstances that will again require self-quarantine.
In conclusion, almost 4 out of 10 participants reported an increase of 2.5–5 kg in their weight. This was related to some unhealthy eating behaviors and a sedentary lifestyle. The awareness of these factors could be an opportunity to promote nutrition and physical activity programs across the country, especially since most of them are potentially modifiable. Additionally, we recommend implementing community-based strategies to promote coping skills and support resilience during the COVID-19 pandemic.
Supplemental Information
Acknowledgments
To Marilyn Espantoso and Erick Piskulich for their support in data collection.
Funding Statement
The authors received no funding for this work.
Additional Information and Declarations
Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Hellen S. Agurto conceived and designed the experiments, performed the experiments, authored or reviewed drafts of the paper, and approved the final draft.
Ana L. Alcantara-Diaz performed the experiments, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.
Eduardo Espinet-Coll performed the experiments, authored or reviewed drafts of the paper, and approved the final draft.
Carlos J. Toro-Huamanchumo performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.
Human Ethics
The following information was supplied relating to ethical approvals (i.e., approving body and any reference numbers):
Impacta Institutional Review Board (Lima, Peru) approved this research (00110-2020-CE).
Ethics
The following information was supplied relating to ethical approvals (i.e., approving body and any reference numbers):
The Impacta Institutional Review Board, Lima, Peru (RCEI-17) approved the present study (approval 00110-2020-CE).
Data Availability
The following information was supplied regarding data availability:
The data and codebook are available in the Supplemental File.
References
- Acosta (2020).Acosta LD. Capacidad de respuesta frente a la pandemia de COVID-19 en América Latina y el Caribe. Revista Panamericana de Salud Pública. 2020;44:e109. doi: 10.26633/RPSP.2020.109. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Arshad Ali et al. (2020).Arshad Ali S, Baloch M, Ahmed N, Arshad Ali A, Iqbal A. The outbreak of coronavirus disease 2019 (COVID-19)—an emerging global health threat. Journal of Infection and Public Health. 2020;13(4):644–646. doi: 10.1016/j.jiph.2020.02.033. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Baenas et al. (2020).Baenas I, Caravaca-Sanz E, Granero R, Sánchez I, Riesco N, Testa G, Vintró-Alcaraz C, Treasure J, Jiménez-Murcia S, Fernández-Aranda F. COVID-19 and eating disorders during confinement: analysis of factors associated with resilience and aggravation of symptoms. European Eating Disorders Review. 2020;28(6):855–863. doi: 10.1002/erv.2771. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Baik et al. (2019).Baik SH, Fox RS, Mills SD, Roesch SC, Sadler GR, Klonoff EA, Malcarne VL. Reliability and validity of the perceived stress scale-10 in Hispanic Americans with English or Spanish language preference. Journal of Health Psychology. 2019;24(5):628–639. doi: 10.1177/1359105316684938. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bilal et al. (2018).Bilal U, Jones-Smith J, Diez J, Lawrence RS, Celentano DD, Franco M. Neighborhood social and economic change and retail food environment change in Madrid (Spain): the heart healthy hoods study. Health & Place. 2018;51:107–117. doi: 10.1016/j.healthplace.2018.03.004. [DOI] [PubMed] [Google Scholar]
- Bin Zarah, Enriquez-Marulanda & Andrade (2020).Bin Zarah A, Enriquez-Marulanda J, Andrade JM. Relationship between dietary habits, food attitudes and food security status among adults living within the united states three months post-mandated quarantine: a cross-sectional study. Nutrients. 2020;12(11):3468. doi: 10.3390/nu12113468. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Brooks et al. (2020).Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, Rubin GJ. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet. 2020;395(10227):912–920. doi: 10.1016/S0140-6736(20)30460-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cooper et al. (2020).Cooper M, Reilly EE, Siegel JA, Coniglio K, Sadeh-Sharvit S, Pisetsky EM, Anderson LM. Eating disorders during the COVID-19 pandemic and quarantine: an overview of risks and recommendations for treatment and early intervention. Eating Disorders. 2020 doi: 10.1080/10640266.2020.1790271. Epub ahead of print 9 July 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Di Renzo et al. (2020).Di Renzo L, Gualtieri P, Pivari F, Soldati L, Attinà A, Cinelli G, Leggeri C, Caparello G, Barrea L, Scerbo F, Esposito E, De Lorenzo A. Eating habits and lifestyle changes during COVID-19 lockdown: an Italian survey. Journal of Translational Medicine. 2020;18:229. doi: 10.1186/s12967-020-02399-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Dwyer et al. (2020).Dwyer MJ, Pasini M, De Dominicis S, Righi E. Physical activity: benefits and challenges during the COVID-19 pandemic. Scandinavian Journal of Medicine & Science in Sports. 2020;30(7):1291–1294. doi: 10.1111/sms.13710. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Díez, Bilal & Franco (2019).Díez J, Bilal U, Franco M. Unique features of the Mediterranean food environment: implications for the prevention of chronic diseases Rh—mediterranean food environments. European Journal of Clinical Nutrition. 2019;72(1):71–75. doi: 10.1038/s41430-018-0311-y. [DOI] [PubMed] [Google Scholar]
- Fawaz & Samaha (2020).Fawaz M, Samaha A. COVID-19 quarantine: post-traumatic stress symptomatology among Lebanese citizens. International Journal of Social Psychiatry. 2020;66(7):666–674. doi: 10.1177/0020764020932207. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Felez-Nobrega et al. (2019).Felez-Nobrega M, Bort-Roig J, Dowd KP, Wijndaele K, Puig-Ribera A. Validation study of the Spanish version of the Last-7-d sedentary time questionnaire (SIT-Q-7d-Sp) in young adults. PLOS ONE. 2019;14(5):e0217362. doi: 10.1371/journal.pone.0217362. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Fernández-Sanjurjo et al. (2018).Fernández-Sanjurjo M, De Gonzalo-Calvo D, Fernández-García B, Díez-Robles S, Martínez-Canal Á, Olmedillas H, Dávalos A, Iglesias-Gutiérrez E. Circulating microRNA as emerging biomarkers of exercise. Exercise and Sport Sciences Reviews. 2018;46(3):160–171. doi: 10.1249/JES.0000000000000148. [DOI] [PubMed] [Google Scholar]
- Gallè et al. (2020).Gallè F, Sabella EA, Ferracuti S, De Giglio O, Caggiano G, Protano C, Valeriani F, Parisi EA, Valerio G, Liguori G, Montagna MT, Spica VR, Da Molin G, Orsi GB, Napoli C. Sedentary behaviors and physical activity of Italian undergraduate students during lockdown at the time of CoViD−19 pandemic. International Journal of Environmental Research and Public Health. 2020;17(17):6171. doi: 10.3390/ijerph17176171. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Guo et al. (2020).Guo Y, Cheng C, Zeng Y, Li Y, Zhu M, Yang W, Xu H, Li X, Leng J, Monroe-Wise A, Wu S. Mental health disorders and associated risk factors in quarantined adults during the COVID-19 outbreak in China: cross-sectional study. Journal of Medical Internet Research. 2020;22(8):e20328. doi: 10.2196/20328. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Górnicka et al. (2020).Górnicka M, Drywień ME, Zielinska MA, Hamułka J. Dietary and lifestyle changes during COVID-19 and the subsequent lockdowns among polish adults: a cross-sectional online survey PLifeCOVID-19 study. Nutrients. 2020;12(8):2324. doi: 10.3390/nu12082324. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Haddad et al. (2020).Haddad C, Zakhour M, Bou kheir M, Haddad R, Al Hachach M, Sacre H, Salameh P. Association between eating behavior and quarantine/confinement stressors during the coronavirus disease 2019 outbreak. Journal of Eating Disorders. 2020;8(1):40. doi: 10.1186/s40337-020-00317-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Iasevoli et al. (2020).Iasevoli F, Fornaro M, D’Urso G, Galletta D, Casella C, Paternoster M, Buccelli C, De Bartolomeis A, COVID-19 in Psychiatry Study Group Psychological distress in patients with serious mental illness during the COVID-19 outbreak and one-month mass quarantine in Italy. Psychological Medicine. 2020 doi: 10.1017/S0033291720001841. Epub ahead of print 19 May 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Instituto Nacional de Estadística e Informática (2018).Instituto Nacional de Estadística e Informática Nota de Prensa N° 007—18 Enero 2018: Lima alberga 9 millones 320 mil habitantes al 2018 [Internet] 2018. https://www.inei.gob.pe/media/MenuRecursivo/noticias/nota-de-prensa-n-007-2018-inei-2.pdf https://www.inei.gob.pe/media/MenuRecursivo/noticias/nota-de-prensa-n-007-2018-inei-2.pdf Lima, Peru: INEI.
- Lal et al. (2020).Lal A, Sanaullah A, Saleem MKM, Ahmed N, Maqsood A, Ahmed N. Psychological distress among adults in home confinement in the midst of COVID-19 outbreak. European Journal of Dentistry. 2020;14(S01):S27–S33. doi: 10.1055/s-0040-1718644. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lima et al. (2020).Lima CKT, De Carvalho PMM, De Lima IAAS, De Nunes JVAO, Saraiva JS, De Souza RI, Da Silva CGL, Neto MLR. The emotional impact of coronavirus 2019-nCoV (new coronavirus disease) Psychiatry Research. 2020;287:112915. doi: 10.1016/j.psychres.2020.112915. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Matricardi, Dal Negro & Nisini (2020).Matricardi PM, Dal Negro RW, Nisini R. The first, holistic immunological model of COVID-19: implications for prevention, diagnosis, and public health measures. Pediatric Allergy and Immunology. 2020;31(5):454–470. doi: 10.1111/pai.13271. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Meyer et al. (2020).Meyer J, McDowell C, Lansing J, Brower C, Smith L, Tully M, Herring M. Changes in physical activity and sedentary behavior in response to COVID-19 and their associations with mental health in 3052 US adults. International Journal of Environmental Research and Public Health. 2020;17(18):6469. doi: 10.3390/ijerph17186469. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Moynihan et al. (2015).Moynihan AB, Van Tilburg WAP, Igou ER, Wisman A, Donnelly AE, Mulcaire JB. Eaten up by boredom: consuming food to escape awareness of the bored self. Frontiers in Psychology. 2015;6:369. doi: 10.3389/fpsyg.2015.00369. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Pan et al. (2020).Pan A, Liu L, Wang C, Guo H, Hao X, Wang Q, Huang J, He N, Yu H, Lin X, Wei S, Wu T. Association of public health interventions with the epidemiology of the COVID-19 outbreak in Wuhan, China. JAMA. 2020;323(19):1–9. doi: 10.1001/jama.2020.6130. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Papandreou et al. (2020).Papandreou C, Arija V, Aretouli E, Tsilidis KK, Bulló M. Comparing eating behaviours, and symptoms of depression and anxiety between Spain and Greece during the COVID-19 outbreak: cross-sectional analysis of two different confinement strategies. European Eating Disorders Review. 2020;28(6):836–846. doi: 10.1002/erv.2772. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Phillipou et al. (2020).Phillipou A, Meyer D, Neill E, Tan EJ, Toh WL, Van Rheenen TE, Rossell SL. Eating and exercise behaviors in eating disorders and the general population during the COVID-19 pandemic in Australia: Initial results from the COLLATE project. International Journal of Eating Disorders. 2020;53(7):1158–1165. doi: 10.1002/eat.23317. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Presidencia del Consejo de Ministros (2010).Presidencia del Consejo de Ministros Decreto Supremo N° 044-2020-PCM. 2010. https://www.gob.pe/institucion/pcm/normas-legales/460472-044-2020-pcm https://www.gob.pe/institucion/pcm/normas-legales/460472-044-2020-pcm Peru: PCM.
- Remor (2006).Remor E. Psychometric properties of a European Spanish version of the perceived stress scale (PSS) Spanish Journal of Psychology. 2006;9(1):86–93. doi: 10.1017/s1138741600006004. [DOI] [PubMed] [Google Scholar]
- Reséndiz Barragán et al. (2015).Reséndiz Barragán AM, Hernández Altamirano SV, Sierra Murguía MA, Torres Tamayo M. Hábitos de alimentación de pacientes con obesidad severa. Nutricion Hospitalaria. 2015;31(2):672–681. doi: 10.3305/nh.2015.31.2.7692. [DOI] [PubMed] [Google Scholar]
- Rodriguez-Morales et al. (2020).Rodriguez-Morales AJ, Gallego V, Escalera-Antezana JP, Méndez CA, Zambrano LI, Franco-Paredes C, Suárez JA, Rodriguez-Enciso HD, Balbin-Ramon GJ, Savio-Larriera E, Risquez A, Cimerman S. COVID-19 in Latin America: the implications of the first confirmed case in Brazil. Travel Medicine and Infectious Disease. 2020;35:101613. doi: 10.1016/j.tmaid.2020.101613. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ruiz-Roso et al. (2020a).Ruiz-Roso MB, De Carvalho Padilha P, Mantilla-Escalante DC, Ulloa N, Brun P, Acevedo-Correa D, Peres WAF, Martorell M, Aires MT, De Oliveira Cardoso L, Carrasco-Marín F, Paternina-Sierra K, Rodriguez-Meza JE, Montero PM, Bernabè G, Pauletto A, Taci X, Visioli F, Dávalos A. Covid-19 confinement and changes of adolescent’s dietary trends in Italy, Spain, Chile, Colombia and Brazil. Nutrients. 2020a;12(6):1807. doi: 10.3390/nu12061807. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ruiz-Roso et al. (2020b).Ruiz-Roso MB, Knott-Torcal C, Matilla-Escalante DC, Garcimartín A, Sampedro-Nuñez MA, Dávalos A, Marazuela M. COVID-19 lockdown and changes of the dietary pattern and physical activity habits in a cohort of patients with type 2 diabetes mellitus. Nutrients. 2020b;12(8):2327. doi: 10.3390/nu12082327. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ruíz-Roso et al. (2020c).Ruíz-Roso MB, De Carvalho Padilha P, Matilla-Escalante DC, Brun P, Ulloa N, Acevedo-Correa D, Peres WAF, Martorell M, Carrilho TRB, De Oliveira Cardoso L, Carrasco-Marín F, Paternina-Sierra K, De Las Hazas MCL, Rodriguez-Meza JE, Villalba-Montero LF, Bernabè G, Pauletto A, Taci X, Cárcamo-Regla R, Martínez JA, Dávalos A. Changes of physical activity and ultra-processed food consumption in adolescents from different countries during covid-19 pandemic: an observational study. Nutrients. 2020c;12(8):2289. doi: 10.3390/nu12082289. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sen, Karaca-Mandic & Georgiou (2020).Sen S, Karaca-Mandic P, Georgiou A. Association of stay-at-home orders with COVID-19 hospitalizations in 4 states. JAMA. 2020;323(24):2522–2524. doi: 10.1001/jama.2020.9176. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Troyer, Kohn & Hong (2020).Troyer EA, Kohn JN, Hong S. Are we facing a crashing wave of neuropsychiatric sequelae of COVID-19? Neuropsychiatric symptoms and potential immunologic mechanisms. Brain Behavior and Immunity. 2020;87:34–39. doi: 10.1016/j.bbi.2020.04.027. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Werneck et al. (2020).Werneck AO, Silva DR, Malta DC, Souza PRB, Jr, Azevedo LO, Barros MBA, Szwarcwald CL. Changes in the clustering of unhealthy movement behaviors during the COVID-19 quarantine and the association with mental health indicators among Brazilian adults. Translational Behavioral Medicine. 2020;11(2):323–331. doi: 10.1093/tbm/ibaa095. [DOI] [PMC free article] [PubMed] [Google Scholar]
- World Health Organization (2020a).World Health Organization COVID-19 weekly epidemiological update [Internet] 2020a. https://www.who.int/publications/m/item/weekly-epidemiological-update---27-october-2020 https://www.who.int/publications/m/item/weekly-epidemiological-update---27-october-2020 Geneva: WHO.
- World Health Organization (2020b).World Health Organization Public health considerations while resuming international travel [Internet] 2020b. https://www.who.int/news-room/articles-detail/public-health-considerations-while-resuming-international-travel https://www.who.int/news-room/articles-detail/public-health-considerations-while-resuming-international-travel Geneva: WHO.
- World Health Organization (2021).World Health Organization WHO Health Emergency Dashboard [Internet] 2021. https://covid19.who.int https://covid19.who.int Geneva: WHO.
- Yannakoulia et al. (2008).Yannakoulia M, Panagiotakos DB, Pitsavos C, Tsetsekou E, Fappa E, Papageorgiou C, Stefanadis C. Eating habits in relations to anxiety symptoms among apparently healthy adults: a pattern analysis from the ATTICA study. Appetite. 2008;51(3):519–525. doi: 10.1016/j.appet.2008.04.002. [DOI] [PubMed] [Google Scholar]
- Yau & Potenza (2013).Yau YHC, Potenza MN. Stress and eating behaviors. Minerva Endocrinologica. 2013;38(3):255–267. [PMC free article] [PubMed] [Google Scholar]
- Zachary et al. (2020).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. Obesity Research & Clinical Practice. 2020;14(3):210–216. doi: 10.1016/j.orcp.2020.05.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Zheng et al. (2015).Zheng Q, Cui G, Chen J, Gao H, Wei Y, Uede T, Chen Z, Diao H. Regular exercise enhances the immune response against microbial antigens through up-regulation of toll-like receptor signaling pathways. Cellular Physiology and Biochemistry. 2015;37(2):735–746. doi: 10.1159/000430391. [DOI] [PubMed] [Google Scholar]
- Zheng et al. (2020).Zheng C, Huang WY, Sheridan S, Sit CH-P, Chen X-K, Wong SH-S. COVID-19 pandemic brings a sedentary lifestyle in young adults: a cross-sectional and longitudinal study. International Journal of Environmental Research and Public Health. 2020;17(17):6035. doi: 10.3390/ijerph17176035. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The following information was supplied regarding data availability:
The data and codebook are available in the Supplemental File.