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Article

Impact of COVID-19 Lockdown in Eating Disorders: A Multicentre Collaborative International Study

by
Isabel Baenas
1,2,3,†,
Mikel Etxandi
1,†,
Lucero Munguía
1,2,3,
Roser Granero
2,3,4,
Gemma Mestre-Bach
5,
Isabel Sánchez
1,2,3,
Emilio Ortega
6,7,
Alba Andreu
6,
Violeta L. Moize
6,7,
Jose-Manuel Fernández-Real
2,8,9,
Francisco J. Tinahones
2,10,
Carlos Diéguez
2,11,
Gema Frühbeck
2,12,
Daniel Le Grange
13,
Kate Tchanturia
14,
Andreas Karwautz
15,
Michael Zeiler
15,
Hartmut Imgart
16,
Annika Zanko
16,
Angela Favaro
17,
Laurence Claes
18,19,
Ia Shekriladze
20,
Eduardo Serrano-Troncoso
21,
Raquel Cecilia-Costa
21,
Teresa Rangil
22,23,
Maria Eulalia Loran-Meler
22,
José Soriano-Pacheco
24,25,
Mar Carceller-Sindreu
24,25,
Rosa Navarrete
26,
Meritxell Lozano
27,
Raquel Linares
27,
Carlota Gudiol
28,29,30,31,
Jordi Carratala
28,29,30,31,
Maria T. Plana
25,32,33,
Montserrat Graell
25,34,
David González-Parra
35,
José A. Gómez-del Barrio
25,36,37,
Ana R. Sepúlveda
38,
Jéssica Sánchez-González
1,
Paulo P. P. Machado
39,
Anders Håkansson
40,41,
Ferenc Túry
42,
Bea Pászthy
43,
Daniel Stein
44,
Hana Papezová
45,
Jana Gricova
45,
Brigita Bax
46,
Mikhail F. Borisenkov
47,
Sergey V. Popov
47,
Denis G. Gubin
48,49,
Ivan M. Petrov
50,
Dilara Isakova
51,
Svetlana V. Mustafina
52,
Youl-Ri Kim
53,
Michiko Nakazato
54,
Nathalie Godart
55,56,57,
Robert van Voren
58,
Tetiana Ilnytska
59,
Jue Chen
60,
Katie Rowlands
14,
Ulrich Voderholzer
61,
Alessio M. Monteleone
62,
Janet Treasure
14,
Susana Jiménez-Murcia
1,2,3,30,* and
Fernando Fernández-Aranda
1,2,3,30,*
add Show full author list remove Hide full author list
1
Department of Psychiatry, Bellvitge University Hospital-IDIBELL, 08907 Barcelona, Spain
2
CIBER Fisiopatología Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, 28029 Barcelona, Spain
3
Psychoneurobiology of Eating and Addictive Behaviors Group, Neurosciences Programme, Bellvitge Biomedical Research Institute (IDIBELL), 08908 Barcelona, Spain
4
Department of Psychobiology and Methodology, School of Psychology, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
5
Facultad de Ciencias de la Salud, Universidad Internacional de La Rioja, 26006 La Rioja, Spain
6
Endocrinology and Nutrition Division, Hospital Clinic and Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), 08036 Barcelona, Spain
7
Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
8
Unit of Diabetes, Endocrinology and Nutrition, Hospital de Girona Dr. Josep Trueta-Institut d’Investigació Biomèdica de Girona (IDIBGI), 17007 Girona, Spain
9
Department of Medical Sciences, School of Medicine, University of Girona, 17004 Girona, Spain
10
Department of Endocrinology and Nutrition, Virgen de la Victoria University Hospital-Instituto de Investigación Biomédica de Málaga (IBIMA), 29010 Málaga, Spain
11
Department of Physiology, CIMUS, University of Santiago de Compostela-Instituto de Investigación Sanitaria, 15782 Santiago de Compostela, Spain
12
Metabolic Research Laboratory, Clínica Universidad de Navarra, University of Navarra-IdiSNA, 31008 Pamplona, Spain
13
Eating Disorders Program, Department of Psychiatry, University of California, San Francisco, CA 94143, USA
14
Section of Eating Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London WC2R 2LS, UK
15
Eating Disorders Unit, Department of Child and Adolescent Psychiatry, Medical University of Vienna, 1090 Vienna, Austria
16
Parkland Klinik, 34537 Bad Wildungen, Germany
17
Department of Neuroscience, University of Padua and Neuroscience Center (PNC), 35122 Padua, Italy
18
Clinical Psychology, Faculty of Psychology and Educational Sciences, KU Leuven, 3000 Leuven, Belgium
19
Clinical Psychology, Faculty of Medicine and Health Sciences, University Antwerp, 2000 Antwerp, Belgium
20
D. Uznadze Institute of Psychology, Ilia State University, 0162 Tbilisi, Georgia
21
Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu- Institut de Recerca Sant Joan de Déu, 08950 Esplugues de Llobregat, Spain
22
Department of Psychiatry, Germans Trias i Pujol University Hospital-IGTP, 08916 Barcelona, Spain
23
Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
24
Department of Psychiatry, Hospital de la Santa Creu i Sant Pau-Institut d’Investigació Biomèdica Sant Pau (IIB-Sant Pau)-Universitat Autònoma de Barcelona (UAB), 08041 Barcelona, Spain
25
Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), ISCIII, 28029 Madrid, Spain
26
Centro de Diagnóstico de Enfermedades Moleculares, Universidad Autónoma de Madrid, 28049 Madrid, Spain
27
FITA Foundation, 08006 Barcelona, Spain
28
Infectious Diseases Department, Hospital Universitari Bellvitge-Institut de Investigació Biomedica de Bellvitge (IDIBELL)-Institut Català d’Oncologia-Hospitalet, 08908 Barcelona, Spain
29
REIPI (Spanish Network for Research in Infectious Disease), Instituto de Salud Carlos III, 28029 Madrid, Spain
30
Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, 08907 Barcelona, Spain
31
CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, 28029 Madrid, Spain
32
Institute of Neuroscience, Hospital Clínic de Barcelona, 08036 Barcelona, Spain
33
Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neurosciences, Hospital Clinic de Barcelona, 08036 Barcelona, Spain
34
Child and Adolescent Psychiatry and Psychology Service, Child Hospital Niño Jesus, 28009 Madrid, Spain
35
Psychiatry Service, University of Salamanca Healthcare Complex (USHC)-Institute of Biomedicine of Salamanca (IBSAL)-University of Salamanca, 37008 Salamanca, Spain
36
Unidad de Trastornos de la Conducta Alimentaria, Hospital Universitario “Marqués de Valdecilla”, Avda, Valdecilla s/n, 39011 Santander, Spain
37
Instituto de Investigación Valdecilla (IDIVAL), 39011 Santander, Spain
38
Facultad de Psicología, Universidad Autónoma de Madrid, 28049 Madrid, Spain
39
Psychotherapy and Psychopathology Research Unit—Psychology Research Center, School of Psychology, University of Minho, 4710-057 Braga, Portugal
40
Department of Clinical Sciences Lund, Psychiatry, Faculty of Medicine, Lund University, 221 00 Lund, Sweden
41
Gambling Disorder Unit, Malmö Addiction Center, 205 02 Malmö, Sweden
42
Institute of Behavioral Sciences, Semmelweis University, 1085 Budapest, Hungary
43
1st Department of Paediatrics, Semmelweis University, 1085 Budapest, Hungary
44
Safra Children’s Hospital, Chaim Sheba Medical Center, Tel Hashomer 52 621, Israel
45
Department of Psychiatry, 1st Medical Faculty of Charles University, 11000 Prague, Czech Republic
46
Eating Disorders Center, Vilnius University Vilnius, 01513 Vilnius, Lithuania
47
Institute of Physiology of Komi Science Centre of the Ural Branch of the Russian Academy of Sciences, 167982 Syktyvkar, Russia
48
Laboratory for Chronobiology and Chronomedicine, Department of Biology, Tyumen State Medical University, 625023 Tyumen, Russia
49
Tyumen Cardiology Research Institute, Tomsk Research Medical Center, 634009 Tyumen, Russia
50
Department of Biological & Medical Physics UNESCO, Tyumen State Medical University, 625023 Tyumen, Russia
51
Department of Therapy and Endocrinology, Tyumen State Medical University, 625023 Tyumen, Russia
52
Institute of Internal and Preventive Medicine–Branch of the Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 630090 Novosibirsk, Russia
53
Department of Psychiatry, Seoul Paik Hospital-Inje University, Seoul 01757, Korea
54
Department of Psychiatry, School of Medicine, International University of Health and Welfare, Narita 286-8686, Japan
55
CESP, Université Paris-Saclay, UVSQ, INSERM U 1178, 94805 Villejuif, France
56
Department of Psychiatry, Institut Mutualiste Montsouris, School of Medicine, Université Paris Descartes, 75006 Paris, France
57
UFR des Sciences de la Santé Simone Veil (UVSQ), Praticienne Hospitalière, Fondation Santé des Etudiants de France, 78180 Paris, France
58
Department of Political Science, Vytautas Magnus University, 44248 Kaunas, Lithuania
59
Institute of Psychiatry of Taras Shevchenko, National University of Kyiv, 01033 Kyiv, Ukraine
60
Department of Clinical Psychology, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 280, Shanghai 200030, China
61
Schön Klinik Roseneck, 83209 Prien am Chiemsee, Germany
62
Dipartimento di Salute Mentale e Fisica e Medicina Preventiva, Universitá degli Studi della Campania “Luigi Vanvitelli”, 80138 Naples, Italy
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Nutrients 2022, 14(1), 100; https://doi.org/10.3390/nu14010100
Submission received: 29 October 2021 / Revised: 17 December 2021 / Accepted: 20 December 2021 / Published: 27 December 2021
(This article belongs to the Special Issue Eating Disorders and Obesity: Through the Life Course)

Abstract

:
Background. The COVID-19 lockdown has had a significant impact on mental health. Patients with eating disorders (ED) have been particularly vulnerable. Aims. (1) To explore changes in eating-related symptoms and general psychopathology during lockdown in patients with an ED from various European and Asian countries; and (2) to assess differences related to diagnostic ED subtypes, age, and geography. Methods. The sample comprised 829 participants, diagnosed with an ED according to DSM-5 criteria from specialized ED units in Europe and Asia. Participants were assessed using the COVID-19 Isolation Scale (CIES). Results. Patients with binge eating disorder (BED) experienced the highest impact on weight and ED symptoms in comparison with other ED subtypes during lockdown, whereas individuals with other specified feeding and eating disorders (OFSED) had greater deterioration in general psychological functioning than subjects with other ED subtypes. Finally, Asian and younger individuals appeared to be more resilient. Conclusions. The psychopathological changes in ED patients during the COVID-19 lockdown varied by cultural context and individual variation in age and ED diagnosis. Clinical services may need to target preventive measures and adapt therapeutic approaches for the most vulnerable patients.

1. Introduction

The COVID-19 pandemic has been a challenge for governments and health care professionals. The lockdown has been a worldwide response to control the spread of the disease. Although the measures taken have been effective in reducing the transmission of the infection, health professionals have expressed concerns about the mental health consequences that can result from social isolation and restrictions to daily life [1,2,3].
The psychological impact of lockdown in history and in the current context has been considered [4]. Higher levels of negative emotions such as anxiety, depression, anger, guilt or even posttraumatic stress symptoms have been reported [4,5]. A more profound impact has been observed in individuals with chronic diseases and mental illness [1,6,7]. Patients with eating disorders (ED) have been found to be at risk of adverse psychological consequences in the context of the COVID-19 pandemic [8,9].
Several studies have highlighted the emotional distress due to lockdown in patients with an ED, reporting high levels of anxiety, depression, and post-stress traumatic symptoms that may persist after lockdown [10,11,12]. Social distancing might obstruct adaptive strategies to deal with psychological distress [3,9,13] and maladaptive coping strategies, such as engaging in substance abuse and potentially addictive behaviors (e.g., gaming), may be adopted [14,15].
Changes in eating behaviors, exercise and weight/body mass index (BMI) have been detected both in the general population and in patients with an ED [16,17]. Emotional disturbances secondary to environmental changes and “food insecurity” have been considered as some possible explanatory factors [17,18,19]. Reduced social support, low self-direction, childhood trauma, and insecure attachment or difficulties in emotion regulation are vulnerability factors leading to psychological distress in lockdown, which can be associated with disturbed eating patterns [11,20,21,22,23].
Increased dietary restriction and physical activity in patients with anorexia nervosa (AN) or higher frequency of binge episodes among patients with bulimia nervosa (BN) and binge eating disorder (BED) have been reported during lockdown [10,11,21,24,25]. However, there are few studies focusing on the evolution of ED symptoms after lockdown and these have yielded mixed results [10,11]. A differential impact on eating and general psychopathology has been assessed in patients with an ED when compared with the general population [11,16]. This may vary with the ED subtype [26]. Moreover, age may be a possible factor to consider when evaluating clinical changes in the context of lockdown. In this line, younger age [1,7], together with cultural and socio-demographic factors may modulate them [27,28].
In order to assess the global effect of lockdown due to the COVID-19 pandemic in patients with a current diagnosis of ED, an international group of clinical and research experts developed the COVID Isolation Eating Scale (CIES), which has been translated in nineteen languages [26]. The study by Fernandez-Aranda, Munguía et al. [26] provided evidence of the psychometric robustness of the Spanish version of the CIES, with an adequate goodness-of-fit for the confirmatory factor analysis and good to excellent Cronbach alpha values. Preliminary data suggested that the effects of lockdown differed between ED subtypes, whereby patients with other specified feeding and eating disorders (OSFED) reported the highest global impairment [26].
To the best of our knowledge, this is the first observational study to analyze clinical changes in patients with ED longitudinally during lockdown, from a multicenter and international perspective. Both child/adolescent and adult populations were assessed using the CIES. The aims of the present study were: (1) to explore eating symptoms and behavioral changes, as well as other psychopathological features in the context of lockdown, and (2) to examine whether ED subtypes, age and geography moderated this effect.

2. Materials and Methods

2.1. Participants

The sample comprised N = 829 participants, from European (Spain, n = 300; Austria, n = 43; Germany, n = 103; Russia, n = 119; Portugal, n = 28; Lithuania, n = 23; Czech Republic, n = 50; Ukraine, n = 10) and Asian (China, n = 92; Korea, n = 50; Japan, n = 11) private and public ED units. Participants were diagnosed according to DSM-5 criteria [29] by expert clinical psychologists and psychiatrists using a semi-structured clinical interview (SCID-5) [30].

2.2. Assessment

The COVID Isolation Eating Scale (CIES) [26] is a self-report questionnaire that assesses the impact of lockdown on patients with ED and/or obesity and has been translated in 19 languages [26]. Supplementary Material contains the English version of the scale. It is composed of 4 subscales:
I.
Circumstances of the lockdown (eight items).
II.
Effects of the lockdown on eating symptoms (thirteen items): it evaluates symptomatology of AN, BN, BED and OSFED, according with the DSM-5. Comorbidity with other psychiatric disorders or diabetes is assessed.
III.
Reaction to the lockdown (34 items): it evaluates the effects of the confinement on eating behaviors, attitudes and habits, anxious-depressive symptoms, emotion dysregulation, and other symptomatology associated with substance use disorders and behavioral addictions.
IV.
The evaluation of remote interventions (thirteen items) assesses acceptance, general satisfaction, and motivation for virtual interventions.
The last three subscales are answered in a five-point Likert scale. Section 2 and Section 3 consider two moments of time, before confinement and the current moment of time.
According to the factorial analysis [26], five factors were identified. Factor 1 was defined by the items measuring eating related symptoms; Factor 2 by the items measuring the effects of lockdown on the eating-related style; Factor 3 by the items assessing anxiety and depressive symptoms; Factor 4 was defined by the items related to emotion regulation; and Factor 5 by those that evaluate telemedicine.
Only the subscales I, II and III (that correspond to the factor 1, 2, 3 and 4) were used in this study. Therefore, no results referring to the acceptance of virtual are reported (subscale 4, factor 5).

2.3. Additional Assessment

Socio-demographic and clinical information (i.e., age, ED subtype, and variables related to COVID-19 and lockdown) were also obtained through the CIES questionnaire.

2.4. Procedure

All the participants were already involved in outpatient ED treatment in specialized units of the different countries. The subjects were asked by therapists from each center to voluntarily complete the study questionnaire (i.e., CIES), translated into participants’ languages [26]. Data collection took place retrospectively between August 2020 and January 2021.
The study was approved by the Clinical Research Ethics Committee of the leading University Hospital (Bellvitge University Hospital) (PR239/20), and informed written consent was obtained from all participants.

2.5. Statistical Analysis

Statistical analysis was performed with Stata17 for Windows [31]. The assessment of the pre-post changes in the quantitative measures was carried out through repeated measures analysis of variance (repeated-ANOVA), while the McNemar test was used for paired nominal data.
Additionally, the differences post-pre values were generated for the scores registered in the CIES, and for the weight (kg) and the BMI (kg/m2) (values equal to zero in these new variables indicate absence of change; negative values indicate a decreasing pre-post change; and positive values indicate an increasing pre-post change). Next, ANOVA procedures compared the mean differences between the diagnostic subtypes, the groups of age, and the continent.
In this study, the statistical analyses were adjusted by the sociodemographic sex and age, due to the differences between the groups (defined by the diagnostic subtypes and the origin of the samples).The effect size was estimated with Cohen’s-h coefficient for the differences between the proportions and with Cohen’s-d for the differences between the means (null effect size was considered for |h| < 0.20 or |d| < 0.20, low-poor for |h| > 0.20 or |d| > 0.20, moderate-medium for |h| > 0.50 or |d| > 0.50 and large-high for |h| > 0.80 or |d| > 0.80) [32,33]. Finner’s method controlled the increase in the Type-I error due the use of multiple significance tests [34].

3. Results

3.1. Characteristics of the Participants

Table S1 (Supplementary Material) displays sociodemographic and clinical characteristic of the sample during the lockdown, as well as the comparison between the diagnostic types, the age groups, and the different continents. For the total sample, the mean age was 27.9 years old (SD = 12.3). Most participants were women (70.4%), lived with other people during the lockdown (78.9%), did not have to take care of others (73.8%), were not infected with COVID-19 (92.8%), did not know anyone close to them who was infected with COVID-19 (84.8%), were working (53.8%), and reported a minimal financial loss (73.5%).

3.2. Comparison between Diagnostic Subtypes of Changes Pre to Post Lockdown

Table 1 contains the changes in the CIES subscales scores between the pre- and post-lockdown within each diagnostic subtype. After adjusting by sex and age, patients with AN reported a significant worsening in eating style and alcohol use. Patients with BN had an increase in weight, and a decrease in ED symptoms, but emotion dysregulation and alcohol use were increased. Individuals with BED reported increased weight, an impaired eating style and had an increase in anxiety-depression symptoms. The group with OSFED reported an increase in anxiety-depression symptoms and emotion dysregulation.
Table 2 shows the comparison between the diagnostic ED subtypes for post-pre changes (defined as the difference between the measures at the end of the follow-up and the post lockdown versus the pre lockdown). The first line-plot displayed in Figure 1 also contains the mean changes within each measure (mean values close to the horizontal line at value 0 represent absence of pre-post changes). After adjusting by sex and age, compared with other groups, patients with BED were characterized by the highest increase in weight, BMI, and the CIES-F1 ED symptoms. For the CIES-F2 eating style, BED and BN achieved statistically equal changes, which represented a higher decrease compared with AN, and OSFED. For CIES-F3 anxiety-depression and CIES-F4 emotional dysregulation, OSFED registered the highest increase compared with the other diagnostic conditions.

3.3. Comparison between the Groups of Age for the Changes during the Lockdown

Table 3 contains the results of the repeated-ANOVA assessing the changes between the pre- and post-lockdown within each age group (young/adolescents versus adults). These analyses were adjusted by the ED subtype and sex. Among young/adolescents, a significant decrease was observed for the CIES-F2 eating style. Adult patients reported increased weight, BMI and CIES-F3 anxiety-depression symptoms, decreased CIES-F2 eating style, and the likelihood of alcohol and other illegal drug use.
The results of the ANOVA procedures comparing between the age group the differences generated between the values measured at post- and pre-lockdown are shown in Table 4 (ANOVA procedures adjusted by the ED subtype and sex) (see also the second line-plot of Figure 1). Statistical differences were achieved by comparing the mean changes in the CIES-F2 eating style and the CIES-F3 anxiety-depression symptoms.

3.4. Comparison between Continents for the Changes during the Lockdown

Table 5 contains the results of the repeated-ANOVA (adjusted by the ED subtype, sex, and age) assessing the changes between the pre- and post-lockdown in the weight, the BMI and the CIES scores. Separated/stratified analyses have been performed within each continent (Europe and Asia). Among the European patients, a significant increase was observed in weight, BMI and the CIES-F3 anxiety-depression symptoms. Besides, a significant decrease in the CIES-F2 eating style and in the likelihood of alcohol and other illegal drug use was reported. In Asian patients, while an increase in weight and BMI was obtained, a decrease in the CIES-F1 ED symptoms was found.
Finally, the results of the ANOVA comparing the differences post- and pre-lockdown between the geographical area are shown in Table 6 (results adjusted by the ED subtype, sex, and age) (see also the third line-plot of Figure 1). Statistical differences were achieved comparing the mean changes in the CIES-F1 ED symptoms (higher decrease for Asian patients).

4. Discussion

The aim of this study was to compare the psychopathological effects in the context of lockdown due to the COVID-19 pandemic in patients with ED from different continents (i.e., Europe and Asia). Secondly, we examined if these differences pre/post lockdown varied by ED subtype, age, and continental provenance.

4.1. ED Subtypes and Changes during Lockdown

In line with previous studies [26] the findings highlight a differential psychopathological impact during lockdown according to the ED diagnosis. Patients diagnosed with BN and BED reported weight gain after lockdown, the BED group experiencing the greatest weight changes when comparing by ED subtypes. It is possible that a sedentary lifestyle favored by “stay-at-home” measures and mobility restrictions during lockdown [35] may play a pivotal role in these weight changes [36,37]. Some of the increased eating behaviors related to “food insecurity” or boredom, such as snacking [35], could also lead to weight gain [16,17]. In this line, individuals with BED and BN showed a higher impairment in their eating style in comparison with the other ED subtypes. Moreover, previous studies have recognized an increased vulnerability to weight gain in individuals with overweight and obesity [38], conditions that are usually presented in individuals with BN and BED [39,40].
Eating behaviors have been described as maladaptive strategies to cope with emotional distress [13,18,22]. However, ED symptoms and emotion dysregulation were reduced in BN, which aligns with other findings [10,41]. The continued presence of other people at home and maintaining daily routines [4] are two significant socio-demographic features that characterized our sample, and may have allowed patients with BN to reduce binge episodes and purging. Moreover, the observed decrease in other maladaptive behaviors after lockdown (i.e., alcohol consumption) has been previously described in an international non-clinical study [35].
Individuals with BED reported the highest impact on ED symptoms when comparing ED subtype groups, although no significant changes in ED symptoms pre- and post-lockdown were individually reported in this group. A greater illness perception among these patients together with a higher motivation for change [42], and the weight gain during lockdown, could encourage them to improve their eating style (e.g., non abuse of certain palatable foods).
Changes in eating style have also been described in patients with AN, which may suggest an increased control over food intake during lockdown. Changes in diet habits have been observed both in general and clinical populations during lockdown [16], the restricting pattern being commonly mentioned [24]. Surprisingly, and in contrast to other studies [12,43], they did not report significant modification in weight/BMI, ED symptoms nor other psychological features. Furthermore, a reduction in alcohol use was described in this ED subtype after lockdown.
Regarding OSFED group, both psychopathology and emotion regulation worsened during lockdown. This aligns with previous research which found that individuals with OSFED deteriorated in adverse situations [44,45]. Not only they did experience a greater psychological impairment than subjects from other ED groups but this impairment also persisted after lockdown [10,11,23].

4.2. Age Differences Regarding Changes during Lockdown

Overall young/adolescent patients had a significant improvement in eating habits in comparison to older individuals. The adult group reported significant weight/BMI changes and higher psychological impact than the former one. These results differed from those described in the general population in which younger people had a poorer adjustment to lockdown [1,7]. One possible explanation for our results could be that older age is linked to patients with BED, who in our study reported a greater psychopathological impact than other ED subtypes. Besides, younger people may be supervised and accompanied more frequently by others, constituting a possible protective factor [4]. Furthermore, young people are usually more familiar with the use of social media, which might imply a better adaptation to the online modality, promoting therapeutic adherence and the maintenance of academic/work routines, as well as social contact [4,13].

4.3. Influence of Continental Provenance on the Changes during Lockdown

Both European and Asian patients experienced weight gain during lockdown, as has been described in clinical and general populations [36,37,46], without significant differences between groups. In comparison with European patients, participants from Asia reported an improvement of their ED symptoms. These findings were not in line with other studies exploring the impact of lockdown on the Asian population [46]. Individual differences in personality and coping features have been reported between countries [27,28] which might lead to a differential adjustment to stress such as the COVID-19 pandemic [47].

4.4. Strengths and Limitations

The large sample size with international participation using a validated and homogeneous method of evaluation is a strength of this study. Moreover, the analysis related to age and provenance were adjusted for the ED subtype. However, the observational design of the study and the voluntary nature of participation in it could be some of the limitations of the present work. Furthermore, the presence of memory bias due to the retrospective nature of the assessment and the heterogeneity of the sample must be mentioned. Even though initial evidence regarding clinical changes in ED patients during lockdown has been measured by the CIES, future studies should consider involving other ED severity questionnaires.

5. Conclusions

In this international study of the adjustment of patients with an ED during lockdown, we observed differences that varied according to ED subtype, age, and provenance. Individuals with BED showed higher worsening of eating symptoms and change in weight during lockdown than those from other ED subtypes. The greatest psychological impairment was described in the OSFED group. Finally, young and Asian patients appeared to be more resilient. These findings may enhance preventive and therapeutic approaches in similar future circumstances.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nu14010100/s1, Table S1. Descriptive for the age, sex, and the confinement context/ Covid Isolation Eating Scale (CIES)-English version.

Author Contributions

Conceptualization, F.F.-A. and S.J.-M.; Data curation, I.B., M.E., L.M., R.G., G.M.-B., I.S. (Isabel Sánchezand), E.O., A.A., V.L.M., J.-M.F.-R., F.J.T., C.D., G.F., D.L.G., K.T., A.K., M.Z., H.I., A.Z., A.F., L.C., I.S. (Ia Shekriladze), E.S.-T., R.C.-C., T.R., M.E.L.-M., J.S.-P., M.C.-S., R.N., M.L., R.L., C.G., J.C. (Jordi Carratalaand), M.T.P., M.G., D.G.-P., J.A.G.-d.B., A.R.S., J.S.-G., P.P.P.M., A.H., F.T., B.P., D.S., H.P., J.G., B.B., M.F.B., S.V.P., D.G.G., I.M.P., D.I., S.V.M., Y.-R.K., M.N., N.G., R.v.V., T.I., J.C. (Jue Chen), K.R., U.V., A.M.M., J.T., S.J.-M. and F.F.-A.; Formal analysis, R.G.; Methodology, R.G.; Writing–original draft, I.B., M.E., L.M., R.G., G.M.-B., S.J.-M. and F.F.-A.; Writing–review & editing, I.B., M.E., L.M., R.G., G.M.-B., I.S. (Isabel Sánchezand), E.O., A.A., V.L.M., J.-M.F.-R., F.J.T., C.D., G.F., D.L.G., K.T., A.K., M.Z., H.I., A.Z., A.F., L.C., I.S. (Ia Shekriladze), E.S.-T., R.C.-C., T.R., M.E.L.-M., J.S.-P., M.C.-S., R.N., M.L., R.L., C.G., J.C. (Jordi Carratalaand), M.T.P., M.G., D.G.-P., J.A.G.-d.B., A.R.S., J.S.-G., P.P.P.M., A.H., F.T., B.P., D.S., H.P., J.G., B.B., M.F.B., S.V.P., D.G.G., I.M.P., D.I., S.V.M., Y.-R.K., M.N., N.G., R.v.V., T.I., J.C. (Jue Chen), K.R., U.V., A.M.M., J.T., S.J.-M. and F.F.-A. All authors have read and agreed to the published version of the manuscript.

Funding

Fondo Investigación Sanitario-FIS, Grant/Award Numbers: FIS, INT19/00046, PI17/01167; Ministerio de Economía y Competitividad, Grant/Award Number: PSI2015-68701-R; Portuguese Foundation for Science and Technology grant, Grant/Award Number: POCI-01-0145-FEDER-028145; Consejo Nacional de Ciencia y Tecnología; Generalitat de Catalunya; European Regional Development Fund.

Institutional Review Board Statement

The present study was conducted in accordance with the latest version of the Declaration of Helsinki and was approved by the Clinical Research Ethics Committee of Bellvitge University Hospital (PR239/20).

Informed Consent Statement

Written and signed informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Individuals may inquire with Fernández-Aranda regarding availability of the data as there is ongoing studies using the data. To avoid overlapping research efforts, Fernández-Aranda will consider a request on a case-by-case basis.

Acknowledgments

We thank CERCA Programme/Generalitat de Catalunya for institutional support. This manuscript and research was supported by grants from the Department of Health of the Generalitat de Catalunya by the call Pla estratègic de recerca i innovació en salut (PERIS, SLT006/17/00077), the Ministerio de Economía y Competitividad (PSI201568701R), Fondo de Investigación Sanitario (FIS) (INT19/00046, PI17/01167, PI20/132), CIBERINFEC (CB21/13/00009) and co-funded by FEDER funds /European Regional Development Fund (ERDF), a way to build Europe (Eat2beNICE/ H2020-SFS-2016-2; Ref 728018; and PRIME/ H2020-SC1-BHC-2018-2020; Ref: 847879). CIBEROBN, CIBERSAM, CIBERINFEC and CIBERDEM are all initiatives of Instituto de Salud Carlos III (ISCIII). GMB is supported by a postdoctoral grant from FUNCIVA. PPM was supported, in part, by a Portuguese Foundation for Science and Technology grant (POCI-01-0145-FEDER-028145). IB was partially supported by a Post-Residency Grant from the Research Committee of the University Hospital of Bellvitge (HUB; Barcelona, Spain) 2020–2021. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Conflicts of Interest

FFA received consultancy honoraria from Novo Nordisk and editorial honoraria as EIC from Wiley. The rest of the authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. González-Sanguino, C.; Ausín, B.; Castellanos, M.Á.; Saiz, J.; López-Gómez, A.; Ugidos, C.; Muñoz, M. Mental health consequences during the initial stage of the 2020 Coronavirus pandemic (COVID-19) in Spain. Brain Behav. Immun. 2020, 87, 172–176. [Google Scholar] [CrossRef] [PubMed]
  2. Wang, C.; Pan, R.; Wan, X.; Tan, Y.; Xu, L.; Ho, C.S.; Ho, R.C. Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China. Int. J. Environ. Res. Public Health 2020, 17, 1729. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Rodgers, R.F.; Lombardo, C.; Cerolini, S.; Franko, D.L.; Omori, M.; Fuller-Tyszkiewicz, M.; Linardon, J.; Courtet, P.; Guillaume, S. The impact of the COVID-19 pandemic on eating disorder risk and symptoms. Int. J. Eat. Disord. 2020, 53, 1166–1170. [Google Scholar] [CrossRef] [PubMed]
  4. Chew, Q.H.; Wei, K.C.; Vasoo, S.; Chua, H.C.; Sim, K. Narrative synthesis of psychological and coping responses towards emerging infectious disease outbreaks in the general population: Practical considerations for the COVID-19 pandemic. Singap. Med. J. 2020, 61, 350–356. [Google Scholar] [CrossRef] [PubMed]
  5. Cao, W.; Fang, Z.; Hou, G.; Han, M.; Xu, X.; Dong, J.; Zheng, J. The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Res. 2020, 287, 112934. [Google Scholar] [CrossRef] [PubMed]
  6. De Girolamo, G.; Cerveri, G.; Clerici, M.; Monzani, E.; Spinogatti, F.; Starace, F.; Tura, G.; Vita, A. Mental Health in the Coronavirus Disease 2019 Emergency—The Italian Response. JAMA Psychiatry 2020, 77, 974–976. [Google Scholar] [CrossRef] [PubMed]
  7. Ozamiz-Etxebarria, N.; Dosil-Santamaria, M.; Picaza-Gorrochategui, M.; Idoiaga-Mondragon, N. Stress, Anxiety, and Depression Levels in the Initial Stage of the COVID-19 Outbreak in a Population Sample in the Northern Spain. Cad. Saúde Pública 2020, 36, e00054020. [Google Scholar] [CrossRef]
  8. Todisco, P.; Donini, L. Eating disorders and obesity (ED&O) in the COVID-19 storm. Eat. Weight. Disord. Stud. Anorex. Bulim. Obes. 2021, 26, 747–750. [Google Scholar] [CrossRef]
  9. Branley-Bell, D.; Talbot, C.V. Exploring the impact of the COVID-19 pandemic and UK lockdown on individuals with experience of eating disorders. J. Eat. Disord. 2020, 8, 44. [Google Scholar] [CrossRef]
  10. Nisticò, V.; Bertelli, S.; Tedesco, R.; Anselmetti, S.; Priori, A.; Gambini, O.; Demartini, B. The psychological impact of COVID-19-related lockdown measures among a sample of Italian patients with eating disorders: A preliminary longitudinal study. Eat. Weight. Disord. Stud. Anorex. Bulim. Obes. 2021, 26, 2771–2777. [Google Scholar] [CrossRef]
  11. Castellini, G.; Cassioli, E.; Rossi, E.; Innocenti, M.; Gironi, V.; Sanfilippo, G.; Felciai, F.; Monteleone, A.M.; Ricca, V. The impact of COVID-19 epidemic on eating disorders: A longitudinal observation of pre versus post psychopathological features in a sample of patients with eating disorders and a group of healthy controls. Int. J. Eat. Disord. 2020, 53, 1855–1862. [Google Scholar] [CrossRef]
  12. Msc, J.D.T.; Watson, H.J.; Thornton, L.M.; Borg, S.; Ma, R.E.F.; Ba, C.M.M.; Bs, L.E.H.; van Furth, E.; Peat, C.M.; Bulik, C.M. Early impact of COVID-19 on individuals with self-reported eating disorders: A survey of ~1000 individuals in the United States and the Netherlands. Int. J. Eat. Disord. 2020, 53, 1780–1790. [Google Scholar] [CrossRef]
  13. Fernández-Aranda, F.; Casas, M.; Claes, L.; Bryan, D.C.; Favaro, A.; Granero, R.; Gudiol, C.; Jiménez-Murcia, S.; Karwautz, A.; Le Grange, D.; et al. COVID-19 and implications for eating disorders. Eur. Eat. Disord. Rev. 2020, 28, 239–245. [Google Scholar] [CrossRef]
  14. Håkansson, A.; Fernández-Aranda, F.; Menchón, J.M.; Potenza, M.N.; Jiménez-Murcia, S. Gambling During the COVID-19 Crisis – A Cause for Concern. J. Addict. Med. 2020, 14, e10–e12. [Google Scholar] [CrossRef]
  15. King, D.L.; Delfabbro, P.H.; Billieux, J.; Potenza, M.N. Problematic online gaming and the COVID-19 pandemic. J. Behav. Addict. 2020, 9, 184–186. [Google Scholar] [CrossRef]
  16. Phillipou, A.; Meyer, D.; Neill, E.; Tan, E.J.; Toh, W.L.; Van Rheenen, T.E.; Rossell, S.L. Eating and exercise behaviors in eating disorders and the general population during the COVID -19 pandemic in Australia: Initial results from the COLLATE project. Int. J. Eat. Disord. 2020, 53, 1158–1165. [Google Scholar] [CrossRef]
  17. Christensen, K.A.; Forbush, K.T.; Richson, B.N.; Thomeczek, M.L.; Perko, V.L.; Bjorlie, K.; Christian, K.; Ayres, J.; Wildes, J.E.; Chana, S.M. Food insecurity associated with elevated eating disorder symptoms, impairment, and eating disorder diagnoses in an American University student sample before and during the beginning of the COVID-19 pandemic. Int. J. Eat. Disord. 2021, 54, 1213–1223. [Google Scholar] [CrossRef]
  18. Touyz, S.; Lacey, H.; Hay, P. Eating disorders in the time of COVID-19. J. Eat. Disord. 2020, 8, 19. [Google Scholar] [CrossRef] [Green Version]
  19. Weissman, R.S.; Bauer, S.; Thomas, J.J. Access to evidence-based care for eating disorders during the COVID-19 crisis. Int. J. Eat. Disord. 2020, 53, 639–646. [Google Scholar] [CrossRef]
  20. 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. Eur. Eat. Disord. Rev. 2020, 28, 855–863. [Google Scholar] [CrossRef]
  21. Machado, P.P.P.; Pinto-Bastos, A.; Ramos, R.; Rodrigues, T.F.; Louro, E.; Gonçalves, S.; Brandão, I.; Vaz, A. Impact of COVID-19 lockdown measures on a cohort of eating disorders patients. J. Eat. Disord. 2020, 8, 57. [Google Scholar] [CrossRef] [PubMed]
  22. Vuillier, L.; May, L.; Greville-Harris, M.; Surman, R.; Moseley, R.L. The impact of the COVID-19 pandemic on individuals with eating disorders: The role of emotion regulation and exploration of online treatment experiences. J. Eat. Disord. 2021, 9, 10. [Google Scholar] [CrossRef] [PubMed]
  23. Monteleone, A.M.; Cascino, G.; Marciello, F.; Abbate-Daga, G.; Baiano, M.; Balestrieri, M.; Barone, E.; Bertelli, S.; Carpiniello, B.; Castellini, G.; et al. Risk and resilience factors for specific and general psychopathology worsening in people with Eating Disorders during COVID-19 pandemic: A retrospective Italian multicentre study. Eat. Weight. Disord. Stud. Anorex. Bulim. Obes. 2021, 26, 2443–2452. [Google Scholar] [CrossRef]
  24. Schlegl, S.; Maier, J.; Meule, A.; Voderholzer, U. Eating disorders in times of the COVID-19 pandemic—Results from an online survey of patients with anorexia nervosa. Int. J. Eat. Disord. 2020, 53, 1791–1800. [Google Scholar] [CrossRef] [PubMed]
  25. Schlegl, S.; Meule, A.; Favreau, M.; Voderholzer, U. Bulimia nervosa in times of the COVID -19 pandemic—Results from an online survey of former inpatients. Eur. Eat. Disord. Rev. 2020, 28, 847–854. [Google Scholar] [CrossRef]
  26. Fernández-Aranda, F.; Munguía, L.; Mestre-Bach, G.; Steward, T.; Etxandi, M.; Baenas, I.; Granero, R.; Sánchez, I.; Ortega, E.; Andreu, A.; et al. COVID Isolation Eating Scale (CIES): Analysis of the impact of confinement in eating disorders and obesity—A collaborative international study. Eur Eat Disord Rev. 2020, 28, 871–883. [Google Scholar] [CrossRef] [PubMed]
  27. Hamamura, T.; Heine, S.J.; Paulhus, D.L. Cultural differences in response styles: The role of dialectical thinking. Pers. Individ. Differ. 2008, 44, 932–942. [Google Scholar] [CrossRef]
  28. English, T.; Chen, S. Culture and self-concept stability: Consistency across and within contexts among Asian Americans and European Americans. J. Pers. Soc. Psychol. 2007, 93, 478–490. [Google Scholar] [CrossRef]
  29. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders; American Psychiatric Association: Washington, DC, USA, 2013. [Google Scholar]
  30. First, M.B.; Williams, J.B.W.; Karg, R.S.; Spitzer, R.L. Structured Clinical Interview for DSM-5 Disorders, Clinician Version (SCID-5-CV); American Psychiatric Association: Arlington, TX, USA, 2015. [Google Scholar]
  31. Stata-Corp Stata Statistical Software: Release 17; Statacorp: College Station, TX, USA, 2021.
  32. Cohen, J. Statistical Power Analysis for the Behavioral Sciences, 2nd ed.; L. Erlbaum Associates: Hillsdale, NJ, USA, 1988; ISBN 978-0-8058-0283-2. [Google Scholar]
  33. Kelley, K.; Preacher, K.J. On effect size. Psychol. Methods 2012, 17, 137–152. [Google Scholar] [CrossRef]
  34. Finner, H.; Roters, M. On the false discovery rate and expecte type I errors. J. Am. Stat. Assoc. 2001, 88, 920–923. [Google Scholar] [CrossRef]
  35. Ammar, A.; Brach, M.; Trabelsi, K.; Chtourou, H.; Boukhris, O.; Masmoudi, L.; Bouaziz, B.; Bentlage, E.; How, D.; Ahmed, M.; et al. Effects of COVID-19 Home Confinement on Eating Behaviour and Physical Activity: Results of the ECLB-COVID19 International Online Survey. Nutrients 2020, 12, 1583. [Google Scholar] [CrossRef]
  36. Sánchez, E.; Lecube, A.; Bellido, D.; Monereo, S.; Malagón, M.M.; Tinahones, J.F. Leading Factors for Weight Gain during COVID-19 Lockdown in a Spanish Population: A Cross-Sectional Study. Nutrients 2021, 13, 894. [Google Scholar] [CrossRef]
  37. Bhutani, S.; Cooper, J.A. COVID-19–Related Home Confinement in Adults: Weight Gain Risks and Opportunities. Obesity 2020, 28, 1576–1577. [Google Scholar] [CrossRef]
  38. Stevenson, J.L.; Krishnan, S.; A Stoner, M.; Goktas, Z.; A Cooper, J. Effects of exercise during the holiday season on changes in body weight, body composition and blood pressure. Eur. J. Clin. Nutr. 2013, 67, 944–949. [Google Scholar] [CrossRef] [Green Version]
  39. Agüera, Z.; Lozano-Madrid, M.; Mallorquí-Bagué, N.; Jiménez-Murcia, S.; Menchón, J.M.; Fernández-Aranda, F. A review of binge eating disorder and obesity. Neuropsychiatrie 2021, 35, 57–67. [Google Scholar] [CrossRef]
  40. Villarejo, C.; Fernández-Aranda, F.; Jiménez-Murcia, S.; Peñas-Lledó, E.; Granero, R.; Penelo, E.; Tinahones, F.J.; Sancho, C.; Vilarrasa, N.; Montserrat-Gil de Bernabé, M.; et al. Lifetime Obesity in Patients with Eating Disorders: Increasing Prevalence, Clinical and Personality Correlates. Eur. Eat. Disord. Rev. 2012, 20, 250–254. [Google Scholar] [CrossRef] [Green Version]
  41. Monteleone, A.M.; Marciello, F.; Cascino, G.; Abbate-Daga, G.; Anselmetti, S.; Baiano, M.; Balestrieri, M.; Barone, E.; Bertelli, S.; Carpiniello, B.; et al. The impact of COVID-19 lockdown and of the following “re-opening” period on specific and general psychopathology in people with Eating Disorders: The emergent role of internalizing symptoms. J. Affect. Disord. 2021, 285, 77–83. [Google Scholar] [CrossRef]
  42. Agüera, Z.; Riesco, N.; Valenciano-Mendoza, E.; Granero, R.; Sánchez, I.; Andreu, A.; Jiménez-Murcia, S.; Fernández-Aranda, F. Illness perception in patients with eating disorders: Clinical, personality, and food addiction correlates. Eat. Weight. Disord.—Stud. Anorex. Bulim. Obes. 2021, 26, 2287–2300. [Google Scholar] [CrossRef]
  43. Bryan, D.C.; Macdonald, P.; Ambwani, S.; Cardi, V.; Rowlands, K.; Willmott, D.; Treasure, J. Exploring the ways in which COVID-19 and lockdown has affected the lives of adult patients with anorexia nervosa and their carers. Eur. Eat. Disord. Rev. 2020, 28, 826–835. [Google Scholar] [CrossRef]
  44. Claes, L.; Boekaerts, E.; Verschueren, M.; Boukaert, W.; Luyckx, K. Identity statuses in prebariatric patients with obesity: Associations with eating disorder symptoms, psychological complaints, and coping behaviour? Eur. Eat. Disord. Rev. 2019, 27, 410–420. [Google Scholar] [CrossRef]
  45. Riesco, N.; Agüera, Z.; Granero, R.; Jiménez-Murcia, S.; Menchón, J.M.; Fernández-Aranda, F. Other Specified Feeding or Eating Disorders (OSFED): Clinical heterogeneity and cognitive-behavioral therapy outcome. Eur. Psychiatry 2018, 54, 109–116. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. He, M.; Xian, Y.; Lv, X.; He, J.; Ren, Y. Changes in Body Weight, Physical Activity, and Lifestyle During the Semi-lockdown Period After the Outbreak of COVID-19 in China: An Online Survey. Disaster Med. Public Heal. Prep. 2021, 15, e23–e28. [Google Scholar] [CrossRef] [PubMed]
  47. Rajkumar, R.P. COVID-19 and mental health: A review of the existing literature. Asian J. Psychiatry 2020, 52, 102066. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Differences (post-pre changes) for the weight, the BMI and the CIES factors.
Figure 1. Differences (post-pre changes) for the weight, the BMI and the CIES factors.
Nutrients 14 00100 g001
Table 1. Assessment of the post-pre changes stratified by ED subtype.
Table 1. Assessment of the post-pre changes stratified by ED subtype.
PrePost
Anorexia (n = 370)MeanSDMeanSDp|d|
Weight (kg)48.299.0248.278.230.9540.00
BMI (kg/m2)17.923.0617.943.000.8620.01
CIES-F1 ED symptoms13.946.9313.327.460.0890.09
CIES-F2 Eating style10.968.759.988.710.005 *0.11
CIES-F3 Anxiety-depression17.209.6217.939.850.0890.07
CIES-F4 Emotion dysregulation8.515.098.275.260.2470.05
n%n%p|h|
Tobacco5214.1%5214.1%1.000.00
Alcohol5715.4%3810.3%0.001 *0.15
Other illegal drugs338.9%267.0%0.1430.07
Behavioral addictions24465.9%24265.4%0.8750.01
Bulimia (n = 148)MeanSDMeanSDp|d|
Weight (kg)61.0914.5262.2613.890.026 *0.08
BMI (kg/m2)22.275.0722.704.840.025 *0.09
CIES-F1 ED symptoms19.786.8218.397.160.048 *0.20
CIES-F2 Eating style21.9610.1520.2810.790.0730.16
CIES-F3 Anxiety-depression20.369.0220.849.610.4670.05
CIES-F4 Emotion dysregulation9.914.839.225.280.045 *0.14
n%n%p|h|
Tobacco4228.4%4631.1%0.3880.06
Alcohol6241.9%4530.4%<0.001 *0.24
Other illegal drugs3020.3%2214.9%0.1150.14
Behavioral addictions10873.0%10671.6%0.8390.03
BED (n = 113)MeanSDMeanSDp|d|
Weight (kg)95.2733.7999.1831.49<0.001 *0.12
BMI (kg/m2)33.6310.3835.089.63<0.001 *0.14
CIES-F1 ED symptoms14.107.2614.576.720.4490.07
CIES-F2 Eating style20.8811.3018.8611.600.010 *0.18
CIES-F3 Anxiety-depression17.6610.3719.4511.370.004 *0.16
CIES-F4 Emotion dysregulation8.995.918.885.870.7450.02
n%n%p|d|
Tobacco2925.7%2824.8%1.000.02
Alcohol3631.9%3127.4%0.4050.10
Other illegal drugs1815.9%1311.5%0.3320.13
Behavioral addictions7364.6%7969.9%0.2630.11
OSFED (n = 198)MeanSDMeanSDp|d|
Weight (kg)81.6825.8682.2526.290.2800.02
BMI (kg/m2)28.588.0628.778.130.3400.02
CIES-F1 ED symptoms13.745.9513.355.700.2660.07
CIES-F2 Eating style13.949.1413.999.120.9240.00
CIES-F3 Anxiety-depression13.9910.0316.1710.90<0.001 *0.21
CIES-F4 Emotion dysregulation6.735.087.805.86<0.001 *0.20
n%n%p|h|
Tobacco5829.3%6532.8%0.0920.08
Alcohol5728.8%5125.8%0.2860.07
Other illegal drugs136.6%168.1%0.6290.06
Behavioral addictions12362.1%13166.2%0.1520.08
BMI: body mass index. BED: binge eating disorder. OSFED: other specified feeding eating disorders. SD: standard deviation. * Bold: significant comparison. Results adjusted by sex and age.
Table 2. Comparison of the post-pre differences by the ED subtype.
Table 2. Comparison of the post-pre differences by the ED subtype.
Anorexia (AN)Bulimia (BN)BEDOSFEDSignificant
n = 370n = 148n = 113n = 198Pairwise
MeanSDMeanSDMeanSDMeanSDComparisons
Weight (kg)−0.326.661.106.324.2211.581.027.43BED ≠ (AN = BN = OSFED)
BMI (kg/m2)−0.092.540.402.311.554.130.352.71BED ≠ (AN = BN = OSFED)
CIES-F1 ED symptoms−0.437.03−1.328.520.266.54−0.674.90BED ≠ (AN = BN = OSFED)
CIES-F2 Eating style−0.606.72−1.5811.34−2.428.12−0.526.69(BED = BN) ≠ (AN = OSFED)
CIES-F3 Anxiety-dep.1.198.280.658.281.286.531.477.04OSFED ≠ (AN = BN = BED)
CIES-F4 Emot.dysreg.−0.034.06−0.624.25−0.343.730.753.94OSFED ≠ (AN = BN = BED)
BMI: body mass index. BED: binge eating disorder. OSFED: other specified feeding eating disorders. SD: standard deviation.
Table 3. Assessment of the post-pre changes stratified by groups of age.
Table 3. Assessment of the post-pre changes stratified by groups of age.
PrePost
Age: young/adolescents (n = 172)MeanSDMeanSDp|d|
Weight (kg)63.4913.5265.4413.510.0730.14
BMI (kg/m2)22.744.0023.373.970.1190.16
CIES-F1 ED symptoms14.836.7313.327.520.2130.21
CIES-F2 Eating style16.549.2312.758.600.003 *0.43
CIES-F3 Anxiety-depression symptoms15.968.8915.468.830.7010.06
CIES-F4 Emotion dysregulation8.845.248.395.330.5370.09
n%n%p|h|
Tobacco149.6%1611.1%0.5660.05
Alcohol189.7%93.1%0.1180.28
Other illegal drugs96.0%85.8%0.9450.01
Behavioral addictions12579.7%12780.1%0.9480.01
Age: adults (n = 657)MeanSDMeanSDp|d|
Weight (kg)72.1827.8273.6227.96<0.001 *0.05
BMI (kg/m2)25.799.0026.329.10<0.001 *0.06
CIES-F1 ED symptoms15.547.1415.226.960.2370.04
CIES-F2 Eating style17.1710.6016.3210.520.008 *0.08
CIES-F3 Anxiety-depression symptoms17.6910.1319.2610.57<0.001 *0.15
CIES-F4 Emotion dysregulation8.615.278.705.530.5460.02
n%n%p|h|
Tobacco16726.2%17527.4%0.2350.03
Alcohol19431.4%15625.4%<0.001 *0.13
Other illegal drugs8513.9%6911.0%0.025 *0.09
Behavioral addictions42365.0%43166.6%0.2720.03
BMI: body mass index. SD: standard deviation. * Bold: significant comparison. Results adjusted by ED subtype and sex.
Table 4. Comparison of the post-pre differences by the groups of age.
Table 4. Comparison of the post-pre differences by the groups of age.
Young/AdolescentsAdults
n = 172n = 657
MeanSDMeanSDp|d|
Weight (kg)0.997.161.507.860.4800.07
BMI (kg/m2)0.362.660.562.890.4710.04
CIES-F1 ED symptoms−1.307.94−0.396.500.1540.13
CIES-F2 Eating style−2.718.17−0.937.850.017 *0.22
CIES-F3 Anxiety-depression symptoms−0.138.551.437.520.030 *0.19
CIES-F4 Emotion dysregulation−0.374.770.033.840.2890.09
BMI: body mass index. SD: standard deviation. * Bold: significant comparison. Results adjusted by ED subtype and sex.
Table 5. Assessment of the post-pre changes stratified by continent.
Table 5. Assessment of the post-pre changes stratified by continent.
PrePost
Europe (n = 676)MeanSDMeanSDp|d|
Weight (kg)72.9927.7874.2028.240.001 *0.04
BMI (kg/m2)26.068.9526.499.140.001 *0.05
CIES-F1 ED symptoms14.946.6115.097.060.5870.02
CIES-F2 Eating style16.299.7315.039.82<0.001 *0.13
CIES-F3 Anxiety-depression symptoms17.009.6518.5110.34<0.001 *0.15
CIES-F4 Emotion dysregulation8.545.138.585.460.8050.01
n%n%p|h|
Tobacco16628.2%17329.3%0.3060.02
Alcohol17230.8%13222.9%<0.001 *0.18
Other illegal drugs7514.5%5810.2%0.003 *0.13
Behavioral addictions44066.9%45268.4%0.2090.03
Asia (n=153)MeanSDMeanSDp|d|
Weight (kg)56.1915.4158.0114.990.038 *0.12
BMI (kg/m2)20.794.9521.514.910.030 *0.15
CIES-F1 ED symptoms17.918.1415.557.530.006 *0.30
CIES-F2 Eating style19.7812.4418.6112.150.3140.10
CIES-F3 Anxiety-depression symptoms19.0210.7419.1310.590.8990.01
CIES-F4 Emotion dysregulation9.135.758.615.730.2410.09
n%n%p|h|
Tobacco1512.0%1814.6%0.1670.08
Alcohol4028.6%3325.6%0.3540.07
Other illegal drugs1913.6%1914.4%0.7360.02
Behavioral addictions10868.0%10673.0%0.2840.11
BMI: body mass index. SD: standard deviation. * Bold: significant comparison. Results adjusted by ED subtype, sex, and age.
Table 6. Comparison of the post-pre differences by continent.
Table 6. Comparison of the post-pre differences by continent.
EuropeAsia
n = 676n = 153
MeanSDMeanSDp|d|
Weight (kg)1.277.472.378.730.1380.13
BMI (kg/m2)0.462.730.913.280.1000.15
CIES-F1 ED symptoms−0.046.32−2.408.43<0.001 *0.32
CIES-F2 Eating style−1.376.90−0.9511.480.5830.04
CIES-F3 Anxiety-depression symptoms1.407.540.228.620.1130.15
CIES-F4 Emotion dysregulation0.023.94−0.374.470.3090.09
BMI: body mass index. SD: standard deviation. * Bold: significant comparison. Results adjusted by ED subtype, sex, and age.
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Baenas, I.; Etxandi, M.; Munguía, L.; Granero, R.; Mestre-Bach, G.; Sánchez, I.; Ortega, E.; Andreu, A.; Moize, V.L.; Fernández-Real, J.-M.; et al. Impact of COVID-19 Lockdown in Eating Disorders: A Multicentre Collaborative International Study. Nutrients 2022, 14, 100. https://doi.org/10.3390/nu14010100

AMA Style

Baenas I, Etxandi M, Munguía L, Granero R, Mestre-Bach G, Sánchez I, Ortega E, Andreu A, Moize VL, Fernández-Real J-M, et al. Impact of COVID-19 Lockdown in Eating Disorders: A Multicentre Collaborative International Study. Nutrients. 2022; 14(1):100. https://doi.org/10.3390/nu14010100

Chicago/Turabian Style

Baenas, Isabel, Mikel Etxandi, Lucero Munguía, Roser Granero, Gemma Mestre-Bach, Isabel Sánchez, Emilio Ortega, Alba Andreu, Violeta L. Moize, Jose-Manuel Fernández-Real, and et al. 2022. "Impact of COVID-19 Lockdown in Eating Disorders: A Multicentre Collaborative International Study" Nutrients 14, no. 1: 100. https://doi.org/10.3390/nu14010100

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