Community Risk Factors in the COVID-19 Incidence and Mortality in Catalonia (Spain). A Population-Based Study

Quim Zaldo-Aubanell, Ferran Campillo i López, Albert Bach, Isabel Serra, Joan Olivet-Vila, Marc Saez, David Pino, Roser Maneja

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8 Citations (Scopus)


The heterogenous distribution of both COVID-19 incidence and mortality in Catalonia (Spain) during the firsts moths of the pandemic suggests that differences in baseline risk factors across regions might play a relevant role in modulating the outcome of the pandemic. This paper investigates the associations between both COVID-19 incidence and mortality and air pollutant concentration levels, and screens the potential effect of the type of agri-food industry and the overall land use and cover (LULC) at area level. We used a main model with demographic, socioeconomic and comorbidity covariates highlighted in previous research as important predictors. This allowed us to take a glimpse of the independent effect of the explanatory variables when controlled for the main model covariates. Our findings are aligned with previous research showing that the baseline features of the regions in terms of general health status, pollutant concentration levels (here NO 2 and PM 10 ), type of agri-food industry, and type of land use and land cover have modulated the impact of COVID-19 at a regional scale. This study is among the first to explore the associations between COVID-19 and the type of agri-food industry and LULC data using a population-based approach. The results of this paper might serve as the basis to develop new research hypotheses using a more comprehensive approach, highlighting the inequalities of regions in terms of risk factors and their response to COVID-19, as well as fostering public policies towards more resilient and safer environments.

Original languageEnglish
Article number3768
JournalInternational Journal of Environmental Research and Public Health
Issue number7
Publication statusPublished - 4 Apr 2021


  • Agri-food industry
  • Air pollutants
  • COVID-19
  • Cancer
  • Cardiovascular diseases
  • Land use and land cover data
  • Psychological disorders


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