{"title":"2019冠状病毒病大流行期间的德国老年人:受影响最小、最多和最严重。","authors":"Vincent Horn, Malte Semmler, Cornelia Schweppe","doi":"10.1007/s12062-021-09352-4","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s12062-021-09352-4.</p>","PeriodicalId":45874,"journal":{"name":"Journal of Population Ageing","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8666192/pdf/","citationCount":"5","resultStr":"{\"title\":\"Older People in Germany During the COVID-19 Pandemic:The Least, the More, and the Most Affected.\",\"authors\":\"Vincent Horn, Malte Semmler, Cornelia Schweppe\",\"doi\":\"10.1007/s12062-021-09352-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s12062-021-09352-4.</p>\",\"PeriodicalId\":45874,\"journal\":{\"name\":\"Journal of Population Ageing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8666192/pdf/\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Population Ageing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s12062-021-09352-4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Population Ageing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s12062-021-09352-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GERONTOLOGY","Score":null,"Total":0}
Older People in Germany During the COVID-19 Pandemic:The Least, the More, and the Most Affected.
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.
Supplementary information: The online version contains supplementary material available at 10.1007/s12062-021-09352-4.
期刊介绍:
The Journal of Population Ageing examines the broad questions arising from global population ageing. It provides a forum for international cross-disciplinary debate on population ageing, focusing on theoretical and empirical research and methodological innovation and development.
This interdisciplinary journal publishes editorials, original peer reviewed articles, and subject and literature reviews. It offers high quality research of interest to those working in the fields of demography, bio-demography, development studies, area studies, sociology, geography, history, social gerontology, economics, and social and health policy.