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3.
J Gerontol A Biol Sci Med Sci ; 76(8): e133-e141, 2021 07 13.
Article in English | MEDLINE | ID: covidwho-1120179

ABSTRACT

BACKGROUND: Age and disease prevalence are the 2 biggest risk factors for Coronavirus disease 2019 (COVID-19) symptom severity and death. We therefore hypothesized that increased biological age, beyond chronological age, may be driving disease-related trends in COVID-19 severity. METHODS: Using the UK Biobank England data, we tested whether a biological age estimate (PhenoAge) measured more than a decade prior to the COVID-19 pandemic was predictive of 2 COVID-19 severity outcomes (inpatient test positivity and COVID-19-related mortality with inpatient test-confirmed COVID-19). Logistic regression models were used with adjustment for age at the pandemic, sex, ethnicity, baseline assessment centers, and preexisting diseases/conditions. RESULTS: Six hundred and thirteen participants tested positive at inpatient settings between March 16 and April 27, 2020, 154 of whom succumbed to COVID-19. PhenoAge was associated with increased risks of inpatient test positivity and COVID-19-related mortality (ORMortality = 1.63 per 5 years, 95% CI: 1.43-1.86, p = 4.7 × 10-13) adjusting for demographics including age at the pandemic. Further adjustment for preexisting diseases/conditions at baseline (ORM = 1.50, 95% CI: 1.30-1.73 per 5 years, p = 3.1 × 10-8) and at the early pandemic (ORM = 1.21, 95% CI: 1.04-1.40 per 5 years, p = .011) decreased the association. CONCLUSIONS: PhenoAge measured in 2006-2010 was associated with COVID-19 severity outcomes more than 10 years later. These associations were partly accounted for by prevalent chronic diseases proximate to COVID-19 infection. Overall, our results suggest that aging biomarkers, like PhenoAge may capture long-term vulnerability to diseases like COVID-19, even before the accumulation of age-related comorbid conditions.


Subject(s)
Aging/physiology , Biological Specimen Banks , COVID-19 Testing/statistics & numerical data , COVID-19/epidemiology , Mortality/trends , Severity of Illness Index , Aged , Biomarkers , Chronic Disease , Humans , Middle Aged , Models, Statistical , Preexisting Condition Coverage/statistics & numerical data , SARS-CoV-2/isolation & purification , Time Factors , United Kingdom/epidemiology
4.
J Gerontol A Biol Sci Med Sci ; 75(11): 2224-2230, 2020 10 15.
Article in English | MEDLINE | ID: covidwho-657110

ABSTRACT

BACKGROUND: Hospitalized COVID-19 patients tend to be older and frequently have hypertension, diabetes, or coronary heart disease, but whether these comorbidities are true risk factors (ie, more common than in the general older population) is unclear. We estimated associations between preexisting diagnoses and hospitalized COVID-19 alone or with mortality, in a large community cohort. METHODS: UK Biobank (England) participants with baseline assessment 2006-2010, followed in hospital discharge records to 2017 and death records to 2020. Demographic and preexisting common diagnoses association tested with hospitalized laboratory-confirmed COVID-19 (March 16 to April 26, 2020), alone or with mortality, in logistic models. RESULTS: Of 269 070 participants aged older than 65, 507 (0.2%) became COVID-19 hospital inpatients, of which 141 (27.8%) died. Common comorbidities in hospitalized inpatients were hypertension (59.6%), history of fall or fragility fractures (29.4%), coronary heart disease (21.5%), type 2 diabetes (type 2, 19. 9%), and asthma (17.6%). However, in models adjusted for comorbidities, age group, sex, ethnicity, and education, preexisting diagnoses of dementia, type 2 diabetes, chronic obstructive pulmonary disease, pneumonia, depression, atrial fibrillation, and hypertension emerged as independent risk factors for COVID-19 hospitalization, the first 5 remaining statistically significant for related mortality. Chronic kidney disease and asthma were risk factors for COVID-19 hospitalization in women but not men. CONCLUSIONS: There are specific high-risk preexisting comorbidities for COVID-19 hospitalization and related deaths in community-based older men and women. These results do not support simple age-based targeting of the older population to prevent severe COVID-19 infections.


Subject(s)
Chronic Disease/epidemiology , Coronavirus Infections , Hospitalization/statistics & numerical data , Mortality , Noncommunicable Diseases/epidemiology , Pandemics , Pneumonia, Viral , Age Factors , Aged , Betacoronavirus/isolation & purification , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques/methods , Cohort Studies , Comorbidity , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/mortality , Coronavirus Infections/therapy , Female , Humans , Male , Pneumonia, Viral/epidemiology , Pneumonia, Viral/mortality , Pneumonia, Viral/therapy , Preexisting Condition Coverage/statistics & numerical data , Risk Assessment/methods , Risk Assessment/statistics & numerical data , Risk Factors , SARS-CoV-2 , Sex Factors , United Kingdom/epidemiology
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