Impact of COVID-19 on health and lifestyle: multidimensional network analyses by generation
The COVID-19 pandemic affected population segments in various ways. Using data from the Health Monitor COVID-19, we examine across different age groups (youth, young adults, adults and elderly) whether people who experienced high versus low negative impact of the COVID-19 pandemic differ demographically. We then analyse associations between physical health, mental health and lifestyle by age and impact group. Consequently, we identify generational-unique key factors that provide clues for future prevention/intervention strategies in crisis situations.
Goal
The aim is to compare demographic characteristics within age groups (youth, young adults, adults, elderly) between people who experienced high versus low negative impact from the COVID-19 pandemic (goal 1). We also examine, within each age group, the multidimensional associations between physical health, mental health, and lifestyle in both impact groups (goal 2). Finally, we compare these multidimensional associations across age groups between the 2 impact groups (goal 3).
Approach
We will use cross-sectional survey data from the Health Monitor COVID-19 for youth (n≈168,000), young adults (n≈70,000), adults (n≈185,000), and elderly (n≈171,000). These surveys include questions on the impact of the COVID-19 pandemic, demographic factors, physical health, mental health, and lifestyle. For goal 1, we use descriptive statistics. For goals 2 and 3, we conduct 2 network analyses per age group (1 for each impact group). These analyses allow us to examine relationships between indicators of physical health, mental health, and lifestyle at one point in time, and compare network structures across age and impact groups.
Collaboration partners
The study is being conducted by researchers at Radboud University's Behavioural Science Institute.
(expected) Results
This project provides insight into demographic differences between people who experienced high versus low negative impact from the COVID-19 pandemic, across different age groups. This knowledge supports targeted assistance for at-risk groups in future crises. We also examine the multidimensional relationships between indicators of physical health, mental health, and lifestyle across age and impact groups, enabling the identification of generation-specific key factors. Policymakers can use this knowledge to tailor their measures to each age group. In doing so, future crisis responses can more effectively address the most relevant factors per group, helping to minimize negative impact for all age groups.