Changes in Population Health-Related Behaviors During a COVID-19 Surge: A Natural Experiment.


Journal

Annals of behavioral medicine : a publication of the Society of Behavioral Medicine
ISSN: 1532-4796
Titre abrégé: Ann Behav Med
Pays: England
ID NLM: 8510246

Informations de publication

Date de publication:
05 04 2023
Historique:
medline: 6 4 2023
pubmed: 18 11 2022
entrez: 17 11 2022
Statut: ppublish

Résumé

The study of impact of lockdowns on individual health-related behaviors has produced divergent results. To identify patterns of change in multiple health-related behaviors analyzed as a whole, and their individual determinants. Between March and August 2020, we collected data on smoking, alcohol, physical activity, weight, and sleep in a population-based cohort from Catalonia who had available pre-pandemic data. We performed multiple correspondence and cluster analyses to identify patterns of change in health-related behaviors and built multivariable multinomial logistic regressions to identify determinants of behavioral change. In 10,032 participants (59% female, mean (SD) age 55 (8) years), 8,606 individuals (86%) modified their behavior during the lockdown. We identified five patterns of behavioral change that were heterogeneous and directed both towards worsening and improvement in diverse combinations. Patterns ranged from "global worsening" (2,063 participants, 21%) characterized by increases in smoking, alcohol consumption, and weight, and decreases in physical activity levels and sleep time, to "improvement" (2,548 participants, 25%) characterized by increases in physical activity levels, decreases in weight and alcohol consumption, and both increases and decreases in sleep time. Being female, of older age, teleworking, having a higher education level, assuming caregiving responsibilities, and being more exposed to pandemic news were associated with changing behavior (all p < .05), but did not discriminate between favorable or unfavorable changes. Most of the population experienced changes in health-related behavior during lockdowns. Determinants of behavior modification were not explicitly associated with the direction of changes but allowed the identification of older, teleworking, and highly educated women who assumed caregiving responsibilities at home as susceptible population groups more vulnerable to lockdowns. Lockdowns implemented during the first surge of the COVID-19 pandemic created highly disruptive scenarios impacting many aspects of life, including health-related behaviors. While early studies on isolated health-related behaviors partly aid in the understanding of changes in some of these behaviors, there is robust evidence supporting the idea that health-related behaviors and their changes often co-occur and should be studied and analyzed as a whole. Hence, in this study, we used hypothesis-free methods to identify inter-dependent patterns of change in health-related behaviors including tobacco smoking, alcohol consumption, physical activity, sleep, and weight in a population-based sample of 10,032 adults from Catalonia, Spain. We found that 86% of participants modified their health-related behavior during the lockdown as we identified five patterns of behavioral change, ranging from general worsening to improvement, in diverse combinations. Additionally, we found that being female, older age, teleworking, highly educated, assuming caregiving responsibilities, and having a high exposure to pandemic news were main the determinants of patterns characterized by changing behaviors (both worsening and improving). Overall, our results highlight the heterogeneity, co-occurrence, and inter-play between health-related behaviors under a natural experiment, and identify common demographic, socio-environmental and behavioral factors that might predict changes in behavior.

Sections du résumé

BACKGROUND
The study of impact of lockdowns on individual health-related behaviors has produced divergent results.
PURPOSE
To identify patterns of change in multiple health-related behaviors analyzed as a whole, and their individual determinants.
METHODS
Between March and August 2020, we collected data on smoking, alcohol, physical activity, weight, and sleep in a population-based cohort from Catalonia who had available pre-pandemic data. We performed multiple correspondence and cluster analyses to identify patterns of change in health-related behaviors and built multivariable multinomial logistic regressions to identify determinants of behavioral change.
RESULTS
In 10,032 participants (59% female, mean (SD) age 55 (8) years), 8,606 individuals (86%) modified their behavior during the lockdown. We identified five patterns of behavioral change that were heterogeneous and directed both towards worsening and improvement in diverse combinations. Patterns ranged from "global worsening" (2,063 participants, 21%) characterized by increases in smoking, alcohol consumption, and weight, and decreases in physical activity levels and sleep time, to "improvement" (2,548 participants, 25%) characterized by increases in physical activity levels, decreases in weight and alcohol consumption, and both increases and decreases in sleep time. Being female, of older age, teleworking, having a higher education level, assuming caregiving responsibilities, and being more exposed to pandemic news were associated with changing behavior (all p < .05), but did not discriminate between favorable or unfavorable changes.
CONCLUSIONS
Most of the population experienced changes in health-related behavior during lockdowns. Determinants of behavior modification were not explicitly associated with the direction of changes but allowed the identification of older, teleworking, and highly educated women who assumed caregiving responsibilities at home as susceptible population groups more vulnerable to lockdowns.
Lockdowns implemented during the first surge of the COVID-19 pandemic created highly disruptive scenarios impacting many aspects of life, including health-related behaviors. While early studies on isolated health-related behaviors partly aid in the understanding of changes in some of these behaviors, there is robust evidence supporting the idea that health-related behaviors and their changes often co-occur and should be studied and analyzed as a whole. Hence, in this study, we used hypothesis-free methods to identify inter-dependent patterns of change in health-related behaviors including tobacco smoking, alcohol consumption, physical activity, sleep, and weight in a population-based sample of 10,032 adults from Catalonia, Spain. We found that 86% of participants modified their health-related behavior during the lockdown as we identified five patterns of behavioral change, ranging from general worsening to improvement, in diverse combinations. Additionally, we found that being female, older age, teleworking, highly educated, assuming caregiving responsibilities, and having a high exposure to pandemic news were main the determinants of patterns characterized by changing behaviors (both worsening and improving). Overall, our results highlight the heterogeneity, co-occurrence, and inter-play between health-related behaviors under a natural experiment, and identify common demographic, socio-environmental and behavioral factors that might predict changes in behavior.

Autres résumés

Type: plain-language-summary (eng)
Lockdowns implemented during the first surge of the COVID-19 pandemic created highly disruptive scenarios impacting many aspects of life, including health-related behaviors. While early studies on isolated health-related behaviors partly aid in the understanding of changes in some of these behaviors, there is robust evidence supporting the idea that health-related behaviors and their changes often co-occur and should be studied and analyzed as a whole. Hence, in this study, we used hypothesis-free methods to identify inter-dependent patterns of change in health-related behaviors including tobacco smoking, alcohol consumption, physical activity, sleep, and weight in a population-based sample of 10,032 adults from Catalonia, Spain. We found that 86% of participants modified their health-related behavior during the lockdown as we identified five patterns of behavioral change, ranging from general worsening to improvement, in diverse combinations. Additionally, we found that being female, older age, teleworking, highly educated, assuming caregiving responsibilities, and having a high exposure to pandemic news were main the determinants of patterns characterized by changing behaviors (both worsening and improving). Overall, our results highlight the heterogeneity, co-occurrence, and inter-play between health-related behaviors under a natural experiment, and identify common demographic, socio-environmental and behavioral factors that might predict changes in behavior.

Identifiants

pubmed: 36394497
pii: 6832140
doi: 10.1093/abm/kaac054
pmc: PMC10074031
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

216-226

Informations de copyright

© The Author(s) 2022. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.

Références

J Sleep Res. 2020 Aug;29(4):e13074
pubmed: 32410272
J Affect Disord. 2020 Dec 1;277:55-64
pubmed: 32799105
Foods. 2020 May 25;9(5):
pubmed: 32466106
Int J Environ Res Public Health. 2020 Jun 10;17(11):
pubmed: 32532013
Curr Opin Psychol. 2015 Oct;5:78-84
pubmed: 26213711
J Behav Med. 2017 Feb;40(1):194-202
pubmed: 27785652
Prev Med. 2000 Feb;30(2):146-54
pubmed: 10656842
Obesity (Silver Spring). 2020 Aug;28(8):1382-1385
pubmed: 32352652
J Transl Med. 2020 Jun 8;18(1):229
pubmed: 32513197
Int J Behav Nutr Phys Act. 2011 Oct 21;8:115
pubmed: 22018588
BMC Public Health. 2016 Jul 29;16:657
pubmed: 27473458
Nutrients. 2020 Jul 30;12(8):
pubmed: 32751721
Lancet. 2020 Oct 17;396(10258):1204-1222
pubmed: 33069326
Front Nutr. 2021 Mar 04;8:626432
pubmed: 33748175
BMJ Open. 2018 Mar 27;8(3):e018324
pubmed: 29593016
Int J Environ Res Public Health. 2021 Apr 20;18(8):
pubmed: 33924056
Eur J Public Health. 2021 Oct 26;31(5):1076-1083
pubmed: 33826721
Nutrients. 2020 May 28;12(6):
pubmed: 32481594
Public Health. 2021 Oct;199:20-24
pubmed: 34534885
Nutrients. 2020 Jun 10;12(6):
pubmed: 32531892
Med Clin (Barc). 1998 Sep 12;111(7):267-76
pubmed: 9789243
J Epidemiol Community Health. 2021 Mar;75(3):224-231
pubmed: 32978210
Sci Rep. 2020 Dec 11;10(1):21780
pubmed: 33311526
Soc Sci Med. 2006 Apr;62(7):1650-71
pubmed: 16198467
Children (Basel). 2021 Feb 02;8(2):
pubmed: 33540824
Soc Psychiatry Psychiatr Epidemiol. 2022 Dec;57(12):2457-2468
pubmed: 35633398
Lancet. 2018 Nov 10;392(10159):1923-1994
pubmed: 30496105
Ann Behav Med. 2013 Oct;46(2):157-68
pubmed: 23609341
Am J Clin Nutr. 2021 Apr 6;113(4):924-938
pubmed: 33675635
J Epidemiol Community Health. 2021 Dec;75(12):1136-1142
pubmed: 34039660
Sleep Med. 2020 Oct;74:81-85
pubmed: 32841849
Appetite. 2021 Jan 1;156:104853
pubmed: 33038479
Sci Rep. 2021 Nov 3;11(1):21571
pubmed: 34732749
Nat Hum Behav. 2020 Dec;4(12):1303-1312
pubmed: 33199859
Can J Public Health. 2020 Oct;111(5):654-657
pubmed: 32700231
Int J Environ Res Public Health. 2020 Jun 07;17(11):
pubmed: 32517294
Int J Public Health. 2022 Sep 08;67:1604978
pubmed: 36158782
Nutrients. 2020 Jun 06;12(6):
pubmed: 32517210
Int J Environ Res Public Health. 2021 Jan 06;18(2):
pubmed: 33418907
JMIR Public Health Surveill. 2021 Nov 24;7(11):e28317
pubmed: 34665759
Prev Med. 2015 Dec;81:16-41
pubmed: 26190368
Int J Environ Res Public Health. 2020 May 31;17(11):
pubmed: 32486380
Environ Health Perspect. 2021 Nov;129(11):117003
pubmed: 34787480

Auteurs

Laura Delgado-Ortiz (L)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.

Anne-Elie Carsin (AE)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.
IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.

Jordi Merino (J)

Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Medicine, Harvard Medical School, Boston, MA, USA.

Inés Cobo (I)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.

Sarah Koch (S)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.

Ximena Goldberg (X)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.

Guillaume Chevance (G)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.

Magda Bosch de Basea (M)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.

Gemma Castaño-Vinyals (G)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.
IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.

Ana Espinosa (A)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.
IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.

Anna Carreras (A)

Germans Trias i Pujol Research Institute (IGTP), Genomes for Life-GCAT, Badalona, Spain.

Beatriz Cortes Martínez (B)

Germans Trias i Pujol Research Institute (IGTP), Genomes for Life-GCAT, Badalona, Spain.

Kurt Straif (K)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
Global Public Health and the Common Good Program, Boston College, MA, USA.

Rafael de Cid (R)

Germans Trias i Pujol Research Institute (IGTP), Genomes for Life-GCAT, Badalona, Spain.

Manolis Kogevinas (M)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.
IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.

Judith Garcia-Aymerich (J)

Non-Communicable Diseases and Environment Program, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH