Abstract

Older people have been identified as a particularly vulnerable group during the COVID-19 pandemic. However, the question of how older people actually fared during the COVID-19 pandemic has only been sporadically addressed. This article aims to partly fill this gap by classifying subgroups of older people using Latent Class Analysis. Indicators used are: risk perception, safety behavior, and well-being. To predict subgroup membership, age, gender, living arrangement, children, chronic illness, conflict, socioeconomic status, and migration history are controlled for. The data analyzed stem from a phone survey among 491 older people (75–100 years) in Germany conducted in September/October 2020. Results show that three subgroups of older people – the least, the more and the most affected – can be formed based on their risk perception, safety behavior, and well-being, indicating the usefulness of these three constructs for identifying and studying older people particularly affected by the COVID-19 pandemic and the measures taken to contain it.

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