Promoting Breastfeeding in Bolivia: Do Social Networks Add to the Predictive Value of Traditional Socioeconomic Characteristics?

By Fonseca-Becker, Fannie; Valente, Thomas W. | Journal of Health Population and Nutrition, March 2006 | Go to article overview

Promoting Breastfeeding in Bolivia: Do Social Networks Add to the Predictive Value of Traditional Socioeconomic Characteristics?


Fonseca-Becker, Fannie, Valente, Thomas W., Journal of Health Population and Nutrition


INTRODUCTION

This study tested whether the prediction of health-related knowledge (correct breastfeeding practices in this case) could be improved by including information about the composition of an individual's personal network above and beyond that predicted by his/her socioeconomic or demographic characteristics. Few studies have tested the predictive value of social networks, especially for population-based studies, despite an increased use of social networks in the past few years in several fields of health research, especially in research relating to prevention of HIV/AIDS (1-8) and design of HIV/AIDS programmes (9).

The field of network analysis has emerged from the disciplines of social anthropology, social psychology, and sociometry and has progressed rapidly over the past two decades (10-14). Network analysis is a "technique used to analyze the pattern of interpersonal communication in a social system by determining who talks to whom" (15). Individual beliefs and actions are shaped by the influence--whether by persuasion, constraint, or example--exerted by the social relationship structures and networks that individuals are embedded in (16).

A social network is a group of nodes linked together by different types of ties (17). These nodes could be groups, individuals, or other units. Personal network refers to an individual and his/her direct contacts, while a whole network refers to an entire group of persons and their links in a specific population (18,19). A population can be a single social network comprising as many personal networks as there are individuals (17).

Valente notes that these individual connections are not random and that, therefore, rather than concentrating on individual characteristics (such as age, educational level, and income) and on relations, researchers may identify the community or social structure which then can be used for understanding health-related behaviours (15). This statement reflects the polarization of approaches used for analyzing aspects of the social world: whether through attributes or characteristics which belong to an individual apart from relations with other individuals; or through relationships which are not derived from any intrinsic characteristics of the individuals involved but are instead a property generated by the linkage or connection between individuals (12,20,21). In support of the pro-relational position, Rogers and Kincaid reported on results of different types of studies on the effect of network variables versus individual characteristics on behaviour (22). They concluded that, in some instances as in the case of acquisition of knowledge about social agencies by Korean immigrants in Honolulu, the personal network characteristics of the immigrants (connectedness and density) predicted 'information acquisition' better than demographic variables, such as education, age, and occupation.

In addition, Phillips et al., in a case-control study of family-planning acceptance, showed that characteristics of the individual were not significant determinants of contraceptive innovation, but that, on the other hand, network indicators of husband's support, spousal communication, and social interaction about family planning were significant determinants of method adoption (23). Behrman, Kohler, and Watkins, in a longitudinal study in rural Kenya, found that the effect of social networks on attitudes and behaviour regarding family planning and AIDS were significant even when controlling for unobserved factors that might also determine the social network itself (24). Similar results for family planning were reported in a 2001 longitudinal study in Ghana (25).

To further test the theory that by simply aggregating the individual attributes of its members, it is not possible to capture the properties of social systems, the present research studied whether the prediction of breastfeeding knowledge can be improved by the composition of an individual's personal network above that predicted by his/her socioeconomic or demographic characteristics. …

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Promoting Breastfeeding in Bolivia: Do Social Networks Add to the Predictive Value of Traditional Socioeconomic Characteristics?
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