Related Experiment Video

Updated: Jun 26, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

Risk factors for developing COVID-19: a population-based longitudinal study (COVIDENCE UK)

Hayley Holt1, Mohammad Talaei1, Matthew Greenig1

  • 1Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

Thorax
|December 1, 2021
PubMed

Insights

Asian/Asian British ethnicity and raised body mass index (BMI) increase COVID-19 odds, while atopic disease decreases them. These findings clarify susceptibility factors beyond severe disease risk.

Area of Science:

  • Epidemiology
  • Infectious Disease Research
  • Public Health

Background:

  • Known risk factors for severe COVID-19 include older age, male sex, obesity, certain ethnicities, and pre-existing medical conditions.
  • The influence of these factors on initial susceptibility to developing COVID-19 remains uncertain.
  • Understanding susceptibility factors is crucial for targeted prevention strategies.

Purpose of the Study:

  • To investigate potential risk factors associated with the odds of developing COVID-19.
  • To differentiate between risk factors for susceptibility and those for disease severity.
  • To provide evidence-based insights into COVID-19 transmission dynamics.

Main Methods:

  • Prospective, population-based cohort study (COVIDENCE UK) conducted from May 2020 to February 2021.
  • Baseline and monthly follow-up questionnaires collected data on potential risk factors and incident COVID-19 cases.
  • Logistic regression models were used to calculate multivariable-adjusted odds ratios (aORs) for identified associations.

Main Results:

  • Asian/Asian British ethnicity (aOR 2.28) and raised body mass index (BMI) (aOR 1.50 for BMI 25.0-30.0; aOR 1.39 for BMI >30.0) were independently associated with increased odds of developing COVID-19.
  • Household overcrowding, social contact frequency, indoor public place visits, and frontline occupations also increased COVID-19 odds.
  • Atopic disease showed an independent association with decreased odds of developing COVID-19 (aOR 0.75).

Conclusions:

  • After adjusting for exposure factors, specific ethnicities (Asian/Asian British) and raised BMI are linked to higher COVID-19 susceptibility.
  • Atopic disease appears to be a protective factor against developing COVID-19.
  • Age, sex, and other medical conditions did not show independent associations with COVID-19 susceptibility in this cohort.
Abstract

Keywords:
COVID-19allergic lung diseaseasthma epidemiologyclinical epidemiology

More Related Videos

Development of Multiplex Real-Time RT-qPCR Assays for the Detection of SARS-CoV-2, Influenza A/B, and MERS-CoV03:53

Development of Multiplex Real-Time RT-qPCR Assays for the Detection of SARS-CoV-2, Influenza A/B, and MERS-CoV

Published on: November 10, 2023

COVID-19 Seroprevalence Test for IgG Antibody Levels Among Healthy Donors Across Different Pandemic Phases in Jeddah04:43

COVID-19 Seroprevalence Test for IgG Antibody Levels Among Healthy Donors Across Different Pandemic Phases in Jeddah

Published on: June 24, 2025

Related Concept Videos

Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
Factors Affecting Illness01:18

Factors Affecting Illness

When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness, disability,...
Factors Affecting the Risk of Infection01:26

Factors Affecting the Risk of Infection

The hosts' susceptibility to infection depends on several factors. The integrity of the skin and mucous membranes helps protect the body against microbial attacks. When the skin is altered, the chance of infection, limb loss, and even death increases.
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin create...
Prevalence and Incidence01:08

Prevalence and Incidence

In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health condition at a...
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
Longitudinal Studies01:26

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...