Social Capital and Blood Donation in the Netherlands

René BekkersVU

University Amsterdam

November 17, 2011 140th Arnova Conference, Toronto

Ingrid Veldhuizen

Sanquin Blood Bank

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Proportion of the population registered as a blood donor per municipality, 2005.

Source: R. Bekkers & I. Veldhuizen (2008). ‘Geographical Differences in Blood Donation and Philanthropy in the Netherlands – What Role for Social Capital?’ Journal of Economic Geography, 99 (4): 483-496.

Our question

• What is the influence of social capital on philanthropy, viz. blood donation?

• Does the level of social capital explain geographical differences in blood donation?

• Does the likelihood of donating blood increase with the level of social capital in the area where you live?

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Why this matters

• Since Coleman (1990) and Putnam (1993, 2000), social capital has become a core concept in the social sciences.

• By analogy to human capital, social capital stands for the resources you get from their social environment (Lin, 2001).

• As social capital dwindles, so might the proportion of blood donors in the population.

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Measuring social capital

• Some measures have included blood donation as an indicator of social capital.

• Along with measures of the level of participation in elections, associations, volunteering, donations, and the level of (generalized) trust.

• Note: here we look at the influence of social capital on blood donation.

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How it might work

• As there are more blood donors in your environment….– You are more likely to know about the

possibility and to be asked to donate blood.[>80% of current blood donors were asked.]

– You are more likely to say yes to become a blood donor because this seems like a good thing to do.[Piliavin: normative / personal expectations]

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The context

• In the Netherlands, there is only one blood collection agency, Sanquin.

• Sanquin operates blood collection points in the major cities, and some mobile units.

• Only about 400,000 individuals (2.5% of the Dutch population) give blood. This makes it difficult to study blood donors using a random sample.

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Data on non-donors

• We took the respondents from the Giving in the Netherlands Panel Survey (GINPS) from the 2008 and 2010 waves and excluded those who reported they had donated blood in the past year (n=2,050).

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Data on blood donors

• The blood collection agency Sanquin selected a random sample of 50,000 blood donors for the prospective cohort study ‘Donor InSight’ in 2008.

• Here we use data from 28,759 blood donors located in 443 different municipalities who responded (57.5%).

• The questionnaire included many questions from GINPS.

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Two levels

• The individual: deciding whether or not to donate blood.

• The municipality: the environment in which individuals make this decision.

• There is social capital at both levels.• We need data on both levels to sort

out where the effect of social capital (if any) comes from.

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Variables at the two levels

• Individual level variables:– Sociodemographics: gender, age,

education, income, work status, working hours

– Social capital: trust and altruistic values.

• Context level (municipality): – Sociodemographics: aggregate measures– Social capital: Voter turnout; voluntary

association membership, helping and volunteering intentions

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Nesting: ni=30,809; nj=433

• Multiple individuals are nested within the same municipality.

• Intraclass coefficient (rho): how similar are two individuals from the same municipality?

• We matched the data from individual respondents to the municipality level data using the zipcode of the respondents.

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Statistical model

• You need a statistical model that decomposes the variance at the individual level and the context level.

• OLS does not do that. It assumes observations are ‘independent’.

• ‘Hierarchical’ or ‘multilevel’ regression models the dependency between individuals nested in the same context.

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Individual levelSociodemographics Social capital

Age 18-30 1.211*** 1.051

Female 1.829*** 1.324***

Secondary education 0.808*** 0.718***

Tertiary education 0.938 0.669***

Catholic 3.807*** 3.240***

Protestant 4.331*** 2.903***

Other religion 0.716*** 0.472***

Generalized trust 1.006

Altruistic values 19.057***

Volunteer 0.449***

Rho/intraclass coefficient 6.89%*** 7.46%***

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Coefficients are odds ratios in logistic regression including age 70+, work status, income, home ownership, full time / part time work

Municipality levelSociodemo Social capital

% Age <30 0.978 0.969 0.969

% Secondary education 1.017 1.004 0.993

% Tertiary education: higher vocational 1.089** 1.083** 1.058

% Tertiary education: university 1.023 1.020 1.018

% Catholic 0.928*** 0.987*** 0.986***

% Protestant: Reformed 0.989 0.991 0.991

% Protestant: Rereformed 0.977 0.976 0.973*

% Muslim 0.932*** 0.930*** 0.933***

Blood collection point 1.044 1.065 1.005

Election turnout 1.041** 1.018

Civic-mindedness 1.075 1.072

% Blood donors 1.404***

Rho/intraclass coefficient 5.32%*** 5.02%** 3.50%***November 17, 2011 40th Arnova Conference, Toronto 15

Blood donation increases with voter turnout

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Turnout

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Conclusions

• Only about 7% of the variance in blood donation is at the municipality context.

• About half of this variance is explained by election turnout, civic-mindedness and the presence of other blood donors.

• Turnout affects blood donation through the presence of other blood donors.

• Probably through social influence.

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Two levels

• Effects of the same characteristics at the two levels are often markedly different.

• E.g., 30.1% of blood donors are Catholic vs. only 15.5% of non-donors; a higher % of Catholics in the municipality, however, actually lowers the likelihood of being a blood donor.

• Higher education also has opposite effects at the individual and context level.

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Thanks, says

• René Bekkers, r.bekkers@vu.nl• Blog: renebekkers.wordpress.com• Twitter: @renebekkers• ‘Giving in the Netherlands’, Center

for Philanthropic Studies, Faculty of Social Sciences, VU University Amsterdam: www.geveninnederland.nl

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