Age, gender, and 11 comorbidities as risk factors associated with COVID-19 mortality: A retrospective cohort including 1.8 million individuals

ABSTRACT

The aim of this study was to investigate the risk factors age, gender, and 11 comorbidities for mortality attributed to COVID−19 among Brazilians. An observational, retrospective cohort study with 1,804,151 individuals was performed using the São Paulo State Statistics Portal database for COVID−19 monitoring. Multivariate binary logistic regression was conducted to estimate the influence of odds ratio (OR) for asthma, diabetes, obesity, Down’s syndrome, puerperal, hematological, hepatic, neurological, pulmonary, immunological, kidney, and other diseases contributing to mortality attributed to COVID−19. An additional analysis was undertaken using age-stratified data including children, adults, and seniors. Our findings demonstrated that cardiac diseases (9.37%) and diabetes (6.26%) were the most prevalent disorders in therapeutically managed and deceased patients. Multivariate regression model found that male individuals (OR = 1.819, CI 1.783 to 1.856, p < 0.001), older age (OR per year = 1.081, CI 1.081 to 1.082, p < 0.001) and presenting comorbidities (OR varying from 1.84–5.47) were at a higher risk of death. The age-stratified analysis also indicates disparities in the impact of the comorbidities between children, adults, and seniors. Our comprehensive findings indicate the primary risk factors for mortality attributed to COVID−19 in the entire population examined, provide a broader perspective than investigations focused solely on hospitalized patients. This study may be utilized as a valuable tool for decision-making during the COVID−19 outbreak.

KEYWORDS:

• comorbidity
• mortality
• risk factors
• cohort
• COVID-19
• SARS-CoV-2

Acknowledgments

The authors thank Mr. Romulo Mendes for the consultation about COVID-19 reporting in private institutions.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data generated or analyzed during this study are with the corresponding author, and, if necessary, he is available for taking any questions about the datasets and these can be requested by reasonable request.

Additional information

Funding

This study was supported in part by the Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq), CAPES Foundation (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) and Sao Paulo Research Foundation (FAPESP—process numbers 2018/24069–3, 2019/07161–6, and 2021/03633–0)