Selected article for: "employment status and sex age"

Author: Calderon-Larranaga, A.; Vetrano, D. L.; Rizzuto, D.; Bellander, T.; Fratiglioni, L.; Dekhtyar, S.
Title: High excess mortality during the COVID-19 outbreak in Stockholm Region areas with young and socially vulnerable populations
  • Cord-id: p5dr7fij
  • Document date: 2020_7_8
  • ID: p5dr7fij
    Snippet: Background: We aimed to describe the distribution of excess mortality (EM) during the first weeks of the COVID-19 outbreak in the Stockholm Region, Sweden, according to individual age and sex, and the sociodemographic context Methods: Weekly all-cause mortality data were obtained from Statistics Sweden for the period 01/01/2015 to 17/05/2020. EM during the first 20 weeks of 2020 was estimated by comparing observed mortality rates with expected mortality rates during the five previous years (N=2,
    Document: Background: We aimed to describe the distribution of excess mortality (EM) during the first weeks of the COVID-19 outbreak in the Stockholm Region, Sweden, according to individual age and sex, and the sociodemographic context Methods: Weekly all-cause mortality data were obtained from Statistics Sweden for the period 01/01/2015 to 17/05/2020. EM during the first 20 weeks of 2020 was estimated by comparing observed mortality rates with expected mortality rates during the five previous years (N=2,379,792). EM variation by socioeconomic status (tertiles of income, education, Swedish-born, gainful employment) and age distribution (share of 70+ year-old persons) was explored based on Demographic Statistics Area (DeSO) data. Findings: An EM was first detected during the week of March 23-29 2020. During the peaking week of the epidemic (6-12 April 2020), an EM of 160% was observed: 211% in 80+ year-old women; 179% in 80+ year-old men. During the same week, the highest EM was observed for DeSOs with lowest income (171%), lowest education (162%), lowest share of Swedish-born (178%), and lowest share of gainfully employed (174%). There was a 1.2 to 1.7-fold increase in EM between those areas with a higher vs. lower proportion of young people. Interpretation: Living in areas with lower socioeconomic status and younger populations is linked to COVID-19 EM. These conditions might have facilitated the viral spread. Our findings add to the well-known biological vulnerability linked to increasing age, the relevance of the sociodemographic context when estimating the individual risk to COVID-19.

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