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Healthy donor effect and satisfaction with health

The role of selection effects related to blood donation behavior

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Abstract

The objective of this paper is to quantify selection effects related to blood donation behavior and their impact on donors’ perceived health status. We rely on data from the 2009 and 2010 survey waves of the German socio-economic panel (N = 12,000), including information on health-related, demographic and psychographic factors as well as monetary donation behavior and volunteer work. We propose a propensity score matching approach to control for the healthy donor effect related to the health requirements for active blood donations. We estimate two separate models and quantify selection biases between (1) active and inactive blood donors and (2) active donors and non-donors. Our results reveal that active donors are more satisfied with their health status; after controlling for selection effects, however, the differences become non-significant, revealing selection biases of up to 82 % compared with non-donors. These differences also exist between active and inactive donors, but the differences are less distinct. Our methodological approach reveals and quantifies selection biases attributable to the healthy donor effect. These biases are substantial enough to lead to erroneous statistical artifacts, implying that researchers should rigorously control for selection biases when comparing the health outcomes of different blood donor groups.

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Notes

  1. http://www.redcrossblood.org/donating-blood/eligibility-requirements. Accessed August 2014.

  2. http://www.americanredcrossblood.org/faq.html. Accessed on 10 June 2014.

  3. For a mathematical description of PSM see Mithas and Krishnan [29].

  4. Detailed documentation for the SOEP data is open to the public via the project’s homepage; (www.diw.de/soep).

  5. See e.g., http://www.blutspende-ost.de/infos-zur-blutspende/spenderinformationen/blutspender-gesucht.php.

  6. See http://www.diw.de/en/diw_02.c.222729.en/questionnaires.htmlfor the complete questionnaires.

  7. The positive effect of drinking more alcohol on the probability of being an active donor as compared to being a non-donor is somehow inconsistent with the healthy donor effect. While we can only speculate regarding the causes for this effect, we assume that the effect is inverted U-shaped; i.e., that very high levels of drinking alcohol influence the probability of being an active blood donor negatively. A robustness check shows indeed that the squared effect for drinking alcohol is significantly negative (p < 0.05) in the model comparing active donors and non-donors (and not significant in the model comparing active and inactive donors). The squared effect does not influence the PSM results and the estimates can be provided by the authors upon request.

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Author information

Authors and Affiliations

  1. Institute for Marketing and Research Center for Health Marketing, University of Hamburg, Welckerstr. 8, 20354, Hamburg, Germany

    Edlira Shehu, Michel Clement & Ann-Christin Langmaack

  2. Hamburg Institute for Risk and Insurance, HSBA Hamburg School of Business Administration, Alter Wall 38, 20457, Hamburg, Germany

    Annette Hofmann

Authors
  1. Edlira Shehu
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  2. Annette Hofmann
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  3. Michel Clement
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  4. Ann-Christin Langmaack
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Correspondence to Edlira Shehu.

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Appendices

Appendix 1

See Table 4.

Table 4 Operationalization of variables
Full size table

Appendix 2

The SOEP survey contained self-stated information related to hospital admissions of the respondents. Specifically, respondents were asked to state the number of nights spent in hospitals assessed by the open question “How many nights altogether did you spend in hospital last year?” We used the variable “number of nights spent in hospitals” as an alternative outcome of our PSM models for investigating the robustness of our results (Table 5).

Table 5 Comparison of the hospitalized nights as indication of the health status
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The results are consistent with those displayed in Table 3 (see Table 5). We find significant differences between active and inactive donors and between active donors and non-donors regarding the number of nights spent in hospitals before matching. Active donors spent significantly fewer nights in hospitals, indicating a better health status. However, after considering the selection biases related to the healthy donor effect, the differences become non-significant (see Table 5).

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Shehu, E., Hofmann, A., Clement, M. et al. Healthy donor effect and satisfaction with health. Eur J Health Econ 16, 733–745 (2015). https://doi.org/10.1007/s10198-014-0625-1

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