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

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... ealth 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 (p<0.05 for knowledge of breast-feeding only with no other liquids and for knowledge of breastfeeding only with no solids p<0.01) 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.