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 and design of HIV/AIDS programmes. Promotion of breastfeeding practices that enhance child survival is important in Bolivia because of high infant morbidity and mortality in the country. Data on a cross-sectional urban probability sample of 2,354 women and men aged 15-49 years were collected from seven urban areas in Bolivia. Model building and the log likelihood ratio criteria were used for assessing the significance of variables in a logistic model. Results showed that the network variables added significantly to the predictive power of the socioeconomic variables. These results may also hold for other health research areas, increasingly using social network analysis, such as that of HIV/AIDS.

Journal of Health, Population and Nutrition, 24(1):71-80