When we know more than our respondents do… Evaluating health of SHARE respondents based on self-reports and dried blood spot samples

Mitarbeiter in diesem Projekt:

In times of population ageing health inequalities are of major concern to researchers and policy makers. In many surveys, differences in health status are assessed based on self-reported health information. One difficulty in this context is that different biases might influence the results. On the one hand, people may evaluate their own health status differently even when having the same objective conditions. On the other hand, people might not always know about their true health status and prevalent diseases may pass unobserved in self-reported data, especially if symptoms are only mild or unspecific. Using SHARE data including information derived from dried blood samples, this project aims at answering the question whether there’s the same socio-economic gradient in health, when using blood sample analyses to evaluate the health status as compared to self-reported health conditions. Our analyses reveal a considerable amount of respondents showing blood parameter values out of the norm while at the same time not reporting the respective health status, i.e. suffering from diabetes or high levels of cholesterol. Thus, the second question this project focuses on is which factors drive the probability of knowing about prevalent disorders such as diabetes or risk factors like a high cholesterol level. Is this knowledge, for example, related to gender, education, age, income or working status? Looking at diabetes mellitus, first results suggest that surprisingly the highest educated show the highest risk of passing undiagnosed. Is this because these people are more used to have the control over everything that happens to them in their lives? Do they transfer this feeling even to chronic diseases like diabetes? There are several questions included in SHARE covering such feelings and the answers to these questions show a correlation to the fact of passing undiagnosed. These project uses preliminary data from a pilot DBS collection in SHARE Wave 4. It is planned to be repeated with biomarker data from Wave 6, which have not been published yet.

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