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Comparison of data donors in the substudy on 'Tests, symptoms and living situation' with other reference studies

Introduction

In this blog post, we will give you further insight into the socio-demographic characteristics and the health situation of the data donors in the sub-study “Tests, Symptoms and Living Situation” (hereafter referred to as “sub-study”). This time we compare the educational level, the subjectively assessed health status and the utilization of general medical services of the participants in the sub-study with reference data. This brings us another step closer to the goal of describing data donors more precisely. Data donors in the sub-study are not representative of the general population, they registered themselves with the data donation app without having been randomly selected. This means that differences between the data donors and the general population are to be expected. We would like to further investigate in this blog post how strong these differences are with regard to the indicators mentioned.

Why do we compare the data donors in the sub-study with reference data? What does this have to do with Covid-19?

The comparison tells us whether the results of the questionnaire or the fever monitoring can be generalized to the overall population. Or, to put it another way, whether the effects that we record in the fever monitor would be expected to be less pronounced or more pronounced compared with the general population.

Educational status

To assess the educational background of the participants in the sub-study, we choose the Microcensus 2017 as a reference (source: FDZ der Statistischen Ämter des Bundes und der Länder, DOI: 10.21242/12211.2017.00.00.1.1.1, own calculations). For this purpose, we classify the educational and vocational training into three categories (low, medium, high education) according to the standards of ISCED11. When comparing educational status between participants of the sub-study and the Microcensus 2017, large differences can be seen in all three educational groups. As known from other surveys (i.e. survey study of the general population), we also see here that participants of the sub-study with low education are strongly underrepresented compared to the Microcensus 2017. This means that fewer people with low education participated in the sub-study than you would find in the general population. Also, from the group of those with a medium education, fewer people participated in the sub-study than would have been expected according to the Microcensus 2017. In contrast, significantly more people with a high level of education took part in the sub-study than would be expected in the general population. If we look at the distribution of education according to gender and age groups, we see similar results. There are stronger differences among women than among men. Moreover, the difference increases with age.

Limitation: The distribution from the Microcensus 2017 refers to the population aged 18 and over. The data donors, on the other hand, can participate from the age of 16. In the 16-18 age group, a large proportion has not yet completed their school education. This proportion was assigned to the low education category. The proportion in the low education category would therefore actually be even larger if the distribution of the population aged 16 and over were considered. Unfortunately, we do not have this distribution. 16 (0.08 %) data donors did not provide any information on school-leaving qualifications and vocational training out of a total of 20,924 participants in the questionnaire “Living situation” (Last updated: 20.12.2021).

Figure 1: Educational distribution of the data donors of the sub-study with Microcensus 2017

Subjective health status/general health status

For the evaluation of the subjectively assessed health status of the participants in the sub-study, we use the current population-representative health survey GEDA 2019/2020-EHIS of the Robert Koch Institute as a reference for comparison. Compared to the participants in GEDA 2019/2020-EHIS, the participants in the sub-study rate their subjective health status more frequently as very good or good and less frequently as moderate, poor or very poor. This observation is also reflected in the analysis according to gender, whereby the difference is more pronounced among women than among men.

If we look at the subjectively assessed state of health according to age groups, a somewhat different picture emerges. Participants in the sub-study aged 16 to 29 are less likely than participants in GEDA 2019/2020-EHIS to report a very good self-assessed health state. In contrast, they are more likely to report a moderately good self-rated health status than those taking part in GEDA 2019/2020-EHIS. Proportionally, participants in the sub-study aged 16 to 29 also report a subjective state of health rated as very poor slightly more often than participants in GEDA 2019/2020-EHIS, although these proportions are very low in both studies.

In the 60+ age group, a moderate, poor or very poor subjective health status is much less frequently reported among participants in the sub-study than in GEDA 2019/2020-EHIS. 171 (0.82 %) data donors did not provide any information on subjective health status out of a total of 20,924 participants in the questionnaire “Living situation” (Last updated: 20.12.2021).

Figure 2: Distribution of the subjectively assessed health status of the data donors of the sub-study with GEDA 2019/2020-EHIS

Utilization of outpatient medical services

With regard to the utilization of general practitioner services, participants in the sub-study have consulted general practitioners less frequently within the last 12 months, but more frequently 12 months or longer ago than participants in GEDA 2019/2020-EHIS. The proportion of those without general practitioner consultation is also somewhat higher in the sample of the sub-study.

According to gender, the difference among those who have seen a general practitioner within the last 12 months can be observed mainly among women: Participants in the sub-study were less likely to have used these medical services within the past 12 months than participants in GEDA 2019/2020-EHIS. In contrast, a larger proportion of female participants in the sub-study compared to GEDA 2019/2020-EHIS had visited a general practitioner in the past 12 months or more or had never used them. For men, there was no clear difference between the sub-study and GEDA 2019/2020-EHIS.

According to age group, participants in the 16-29 age group of the sub-study had visited a general practitioner less often in the past 12 months than participants in GEDA 2019/2020-EHIS in the same age group. Sub-study participants in this age group also report that they have never visited a general practitioner. In contrast, participants aged 60 and over in both studies have visited a general practitioner about equally often in the past 12 months. The proportions of participants aged 60 and over who had consulted a general practitioner past 12 months or more are also about the same in both studies. 208 (0.99 %) data donors did not provide any information on the last visit to a general practitioner or family doctor out of a total of 20,924 participants in the questionnaire “Living situation” (Last updated: 20.12.2021).

Figure 3: Distribution of the use of general practitioner services of the data donors of the sub-study with GEDA 2019/2020-EHIS

Conclusion

The willingness to donate data to science depends on various factors. We have examined the three characteristics, education, subjective health status and utilization of primary health care services. We see that the sample structure of data donors differs from the overall population, especially with regard to education. How the selection of the sample affects the interpretation of the results of the fever monitoring is still being investigated.

Outlook

The next blog post is about the assessment of further indicators of health status and health behaviour.