Data quality in centenarian research: The proxy-centenarian relationship and item nonresponse in the SWISS100 study.

Background: In recent years, there has been a growing interest in the investigation of very old individuals. However, various challenges arise when collecting data from this age group. Given potential health and cognitive impairments and the difficulty of retrieving accurate self-reported data, involving individuals knowledgeable of the target person as proxy respondents are an invaluable solution. The primary goal of this study is to explore the association between proxy-centenarian relationship and item nonresponse, a pivotal data quality measure.

Data And Methods: We used data from the phone study conducted within SWISS100, a study on centenarians in Switzerland, focusing on a subsample of 94 centenarians and 75 proxy respondents. We compared characteristics of centenarians who provided self-reports with those interviewed through proxy respondents using descriptive analyses, and Firth's regression models to investigate the association of different types of proxies (children, other relatives, and non-relatives) with item nonresponse.

Results: We noted differences between centenarians participating themselves in interviews and those represented by proxies, observing higher proportions of men and private home residents in the self-report group. There was a low prevalence of item nonresponse among proxy respondents. Proxy type significantly impacted item nonresponse, particularly with non-relatives showing notably higher unanswered question rates. A robust association between non-relatives as proxies and increased item nonresponse persisted even when controlling for potential confounding factors.

Discussion And Conclusions: This study enhances the understanding of data quality, particularly item nonresponse, and highlights the impact of the proxy-centenarian relationship when studying the oldest-old. The findings stress the importance of carefully choosing proxy respondents, preferably children, to improve data quality and inclusivity for those individuals hard to reach or to interview. Future research should investigate various data quality indicators and rely on larger samples to enhance the representation and methodological rigour in the study of the oldest-old.