Abstract
The social support an individual receives is a phenomenon of growing interest, since it influences his or her state of physical and mental health. Intimate relationships (family and friends) are the greatest source of social support and, among them, the partner plays a critical role in providing aid. In contrast to previous studies, this paper focuses on people in couples and analyzes whether there are international differences in the role of the partner as provider of support. The analysis applies Esping-Andersen’s classification of welfare regimes to study to whom one turns when one needs domestic, economic, or emotional help. Using data on 13 countries from the ISSP (2001), we confirm that people in more defamiliarized countries, where individuals are less dependent on the family (liberal and social democratic welfare regimes), turn more to elective relationships such as partner and friends, while people in conservative and Mediterranean countries seek support in parents, children and siblings.
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Notes
The most frequently cited response for where to turn if one needed money was the bank (a third of the respondents), but this response is not taken into account since our study analyzes only informal social support.
It is worth mentioning that informal support is primarily provided by women: respondents turn more to their mother, sisters, and daughters than to their father, brothers, and sons except in the case of economic aid, in which respondents ask brother before sister. These data confirm previous research that shows that women are the primary sources of emotional support at home and are more likely to aspire to employment in work that requires social abilities and provides emotional support (England et al. 1982; House et al. 1988; Rossi and Rossi 1991).
We performed the same analysis with five categories for each dependent variable (excluding “others” and “none” in the three dependent variables, as well as “bank” in the case of economic help). The patterns established between the significant variables were quite similar. Further, Pseudo-R2 was almost identical in the case of emotional and economic aid and worse in the case of domestic help. For these two reasons, we decided to use only three categories in order to gain parsimony.
We do not find significant differences between the age distribution in the total population surveyed and the sample of members of couples: average age of the sample of respondents in couples is 48.5 years, with a standard deviation of 15.2, and that of the total sample 47.5, with a standard deviation of 17.2. The greatest homogeneity in the sample of members of couples is due to biological factors, as both younger cohorts and the older ones are less likely to have a stable partner.
Primary education includes no formal education, incomplete primary education and completed primary education; secondary education includes incomplete secondary education and completed secondary education; university study includes incomplete university study and completed university study.
We can assume that most people who live in the place where they were born will have at least part of their family network nearby, whereas those who have moved recently will probably have few family members nearby. Intermediate values are harder to interpret, since the respondents’ change of residence may have occurred during the period when they lived with their parents or once they reached adulthood.
The spouse’s occupational status influences the likelihood of asking for support, since people not employed in paid work may be more available to care for a sick partner but will have more difficulty giving him or her money. The survey includes the respondent’s spouse’s occupational status, but we decided not to include this, since data were only available for Austria and France.
The questionnaire asks how many siblings the respondent has but does not ask the frequency with which they visit. They only ask about the sibling with whom the respondent has the most contact.
The questions on the questionnaire specify that respondents mention friends who are neither family members nor their partner. We tried recodifying the variable excluding the 20 cases in the sample who declared over 100 friends, as these are extreme values, but the results were very similar, so we decided to keep the survey in its original form.
The third hypothesis assumes that the data are structured hierarchically, since individuals (level 1) are nested in countries (level 2). In a previous version of this research, we performed a multilevel analysis with the two most frequent providers of each type of support, using the program ML-WIN (Snijders and Bosker 1999). The first step in the analysis was to analyze the so-called baseline model, which contained only the estimate for the intercept. This model is used to corroborate the part of the variance that each level of analysis explains: individual and between countries. For the six dependent variables studied, the model is significant; that is, whom one asks first for support differs both by individual and between countries. In the second step, we introduced, progressively and step by step, the independent variables, both sociodemographic variables and variables of network composition, measured at the individual level (level 1). For each step, we compared the results of a model that included change in the first level only (fixed effects) with another model that permitted the variance to change by country for the explanatory variable in question (random coefficients by country). The results show that, although many of the variables in level 1 were significant, they did not behave differently between countries; that is, the effect of being a man or a woman, for example, or of having frequent contact with one’s mother, varied in similar ways in all of the countries studied, thereby confirming our assumption. This multilevel analysis clarified that there are important differences between countries as to whom one asks for help and that these differences do not depend on sociodemographic variables. Rather, we must look for the explanation of these differences in other kinds of variables, probably more contextual ones. The coefficients estimated by the multilevel models for the explanatory variables differ only slightly from those obtained with logistic models.
The higher or lower probability of turning to one’s partner in the different countries may also be related to marriage law in each country.
For an analysis of the similarities and differences in informal social support between Spain and Italy, see García Faroldi (2011).
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Acknowledgments
I wish to thank Ainhoa de Federico for her suggestions on a previous version of this paper, and Carlos Gamero for providing useful information on methodological issues. Special thanks to Verónica de Miguel for her generosity and help throughout the process of developing this research. I also wish to thank the anonymous reviewer for his/her useful comments. This project was developed within the framework of research project PSI2008-01937, financed by the Spanish Ministry of Science and Innovation under the National Plan for Research, Development, and Innovation 2008–2011.
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García-Faroldi, L. Welfare States and Social Support: An International Comparison. Soc Indic Res 121, 697–722 (2015). https://doi.org/10.1007/s11205-014-0671-1
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DOI: https://doi.org/10.1007/s11205-014-0671-1