TY - JOUR
T1 - Sociodemographic determinants of intraurban variations in COVID-19 incidence
T2 - The case of Barcelona
AU - López-Gay, Antonio
AU - Spijker, Jeroen
AU - Cole, Helen V.S.
AU - Marques, Antonio G.
AU - Triguero-Mas, Margarita
AU - Anguelovski, Isabelle
AU - Marí-Dell'Olmo, Marc
AU - Módenes, Juan A.
AU - Álamo-Junquera, Dolores
AU - López-Gallego, Fernando
AU - Borrell, Carme
N1 - Funding Information:
Funding This project has been funded by the following programmes: H2020 European Research Council (GREEN LULUs SG/GA678034 and HEALIN CoG/ GA864616); Ministerio de Ciencia e Innovación (CSO2016-79142-R; GLOBFAM/ RTI2018-096730-B-I00I3; ’Maria de Maeztu’ Program/CEX2019-000940-M; ’Ramón y Cajal’ Program/RYC-2013-14851; ’Juan de la Cierva’ Program/FJCI-2017-33842 and IJC2018-035322-I); Agència de Gestió d’Ajuts Universitaris i de Recerca (DEMFAMS/2017 SGR 1454); Talent Research Program, Universitat Autònoma de Barcelona.
Publisher Copyright:
© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - Background: Intraurban sociodemographic risk factors for COVID-19 have yet to be fully understood. We investigated the relationship between COVID-19 incidence and sociodemographic factors in Barcelona at a fine-grained geography. Methods: This cross-sectional ecological study is based on 10 550 confirmed cases of COVID-19 registered during the first wave in the municipality of Barcelona (population 1.64 million). We considered 16 variables on the demographic structure, urban density, household conditions, socioeconomic status, mobility and health characteristics for 76 geographical units of analysis (neighbourhoods), using a lasso analysis to identify the most relevant variables. We then fitted a multivariate Quasi-Poisson model that explained the COVID-19 incidence by neighbourhood in relation to these variables. Results: Neighbourhoods with: (1) greater population density, (2) an aged population structure, (3) a high presence of nursing homes, (4) high proportions of individuals who left their residential area during lockdown and/or (5) working in health-related occupations were more likely to register a higher number of cases of COVID-19. Conversely, COVID-19 incidence was negatively associated with (6) percentage of residents with post-secondary education and (7) population born in countries with a high Human Development Index. Conclusion: Like other historical pandemics, the incidence of COVID-19 is associated with neighbourhood sociodemographic factors with a greater burden faced by already deprived areas. Because urban social and health injustices already existed in those geographical units with higher COVID-19 incidence in Barcelona, the current pandemic is likely to reinforce both health and social inequalities, and urban environmental injustice all together.
AB - Background: Intraurban sociodemographic risk factors for COVID-19 have yet to be fully understood. We investigated the relationship between COVID-19 incidence and sociodemographic factors in Barcelona at a fine-grained geography. Methods: This cross-sectional ecological study is based on 10 550 confirmed cases of COVID-19 registered during the first wave in the municipality of Barcelona (population 1.64 million). We considered 16 variables on the demographic structure, urban density, household conditions, socioeconomic status, mobility and health characteristics for 76 geographical units of analysis (neighbourhoods), using a lasso analysis to identify the most relevant variables. We then fitted a multivariate Quasi-Poisson model that explained the COVID-19 incidence by neighbourhood in relation to these variables. Results: Neighbourhoods with: (1) greater population density, (2) an aged population structure, (3) a high presence of nursing homes, (4) high proportions of individuals who left their residential area during lockdown and/or (5) working in health-related occupations were more likely to register a higher number of cases of COVID-19. Conversely, COVID-19 incidence was negatively associated with (6) percentage of residents with post-secondary education and (7) population born in countries with a high Human Development Index. Conclusion: Like other historical pandemics, the incidence of COVID-19 is associated with neighbourhood sociodemographic factors with a greater burden faced by already deprived areas. Because urban social and health injustices already existed in those geographical units with higher COVID-19 incidence in Barcelona, the current pandemic is likely to reinforce both health and social inequalities, and urban environmental injustice all together.
KW - COVID-19
KW - neighbourhood/place
KW - public health
KW - social inequalities
KW - spatial analysis
UR - http://www.scopus.com/inward/record.url?scp=85108535323&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/702fc3f9-41fb-3494-848e-c9d51e20faa6/
U2 - 10.1136/jech-2020-216325
DO - 10.1136/jech-2020-216325
M3 - Article
C2 - 34158409
AN - SCOPUS:85108535323
SN - 0143-005X
VL - 76
SP - 1
EP - 7
JO - Journal of Epidemiology and Community Health
JF - Journal of Epidemiology and Community Health
IS - 1
M1 - jech-2020-216325
ER -