Nationwide health, socio-economic and genetic predictors of COVID-19 vaccination status in Finland.
Nat Hum Behav
; 7(7): 1069-1083, 2023 07.
Article
em En
| MEDLINE
| ID: mdl-37081098
Understanding factors associated with COVID-19 vaccination can highlight issues in public health systems. Using machine learning, we considered the effects of 2,890 health, socio-economic and demographic factors in the entire Finnish population aged 30-80 and genome-wide information from 273,765 individuals. The strongest predictors of vaccination status were labour income and medication purchase history. Mental health conditions and having unvaccinated first-degree relatives were associated with reduced vaccination. A prediction model combining all predictors achieved good discrimination (area under the receiver operating characteristic curve, 0.801; 95% confidence interval, 0.799-0.803). The 1% of individuals with the highest predicted risk of not vaccinating had an observed vaccination rate of 18.8%, compared with 90.3% in the study population. We identified eight genetic loci associated with vaccination uptake and derived a polygenic score, which was a weak predictor in an independent subset. Our results suggest that individuals at higher risk of suffering the worst consequences of COVID-19 are also less likely to vaccinate.
Texto completo:
1
Coleções:
01-internacional
Temas:
Atencao_primaria_forma_integrada
Contexto em Saúde:
2_ODS3
/
4_TD
Base de dados:
MEDLINE
Assunto principal:
COVID-19
Tipo de estudo:
Health_economic_evaluation
/
Prognostic_studies
/
Risk_factors_studies
Aspecto:
Determinantes_sociais_saude
Limite:
Humans
País/Região como assunto:
Europa
Idioma:
En
Revista:
Nat Hum Behav
Ano de publicação:
2023
Tipo de documento:
Article