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10.1111/jir.12739

http://scihub22266oqcxt.onion/10.1111/jir.12739
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suck abstract from ncbi


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pmid32458565      J+Intellect+Disabil+Res 2020 ; 64 (7): 482-488
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  • Mortality of people with intellectual disabilities during the 2017/2018 influenza epidemic in the Netherlands: potential implications for the COVID-19 pandemic #MMPMID32458565
  • Cuypers M; Schalk BWM; Koks-Leensen MCJ; Nagele ME; Bakker-van Gijssel EJ; Naaldenberg J; Leusink GL
  • J Intellect Disabil Res 2020[Jul]; 64 (7): 482-488 PMID32458565show ga
  • BACKGROUND: Data on the development of Covid-19 among people with intellectual disabilities (IDs) are scarce and it is uncertain to what extent general population data applies to people with ID. To give an indication of possible implications, this study investigated excess mortality patterns during a previous influenza epidemic. METHODS: Using Dutch population and mortality registers, a historical cohort study was designed to compare mortality during the 2017-2018 influenza epidemic with mortality in the same period in the three previous years. People with ID were identified by entitlements to residential ID-care services as retrieved from a national database. RESULTS: Data covered the entire adult Dutch population (12.6 million; GenPop), of which 91 064 individuals were identified with an ID. During the influenza epidemic, mortality among people with ID increased almost three times as much than in the GenPop (15.2% vs. 5.4%), and more among male individuals with ID (+19.5%) than among female individuals with ID (+10.6%), as compared with baseline. In both cohorts, comparable increases in mortality within older age groups and due to respiratory causes were seen. Particularly in the ID-cohort, excess deaths also occurred in younger age groups, due to endocrine diseases and ID-specific causes. CONCLUSIONS: During the 2017-2018 influenza epidemic, excess mortality among people with ID was three times higher than in the general Dutch population, appeared more often at young age and with a broader range of underlying causes. These findings suggest that a pandemic may disproportionally affect people with ID while population data may not immediately raise warnings. Early detection of diverging patterns and faster implementation of tailored strategies therefore require collection of good quality data.
  • |Adolescent[MESH]
  • |Adult[MESH]
  • |Aged[MESH]
  • |COVID-19[MESH]
  • |Cohort Studies[MESH]
  • |Comorbidity[MESH]
  • |Coronavirus Infections/epidemiology[MESH]
  • |Epidemics/*statistics & numerical data[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Influenza, Human/*mortality[MESH]
  • |Intellectual Disability/*epidemiology[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Netherlands/epidemiology[MESH]
  • |Pandemics/statistics & numerical data[MESH]
  • |Pneumonia, Viral/epidemiology[MESH]
  • |Registries/*statistics & numerical data[MESH]


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