Second , we show that network composition , individual network central ity , and network structure are associated with important health behaviors and health and development outcomes in different context s across multiple levels of analysis and across distinct network types .
Lastly , we highlight the opportunities for health research ers and practitioners in LMICs to 1 ) design effective studies and interventions in LMICs that account for the sociocentric network positions of certain individuals and overall network structure , 2 ) measure the spread of outcomes or intervention externalities , and 3 ) enhance the effectiveness and efficiency of aid based on knowledge of social structure .
In low- and middle-income countries ( LMICs ) , naturally occurring social networks may be particularly vital to health outcomes as extended webs of social ties often are the principal source of various re sources .
Food-Sharing Networks in Lamalera, Indonesia
Exponential r and om graph modeling ( ERGM ) is used here to test hypotheses derived from human behavioral ecology about the adaptive nature of human food sharing . Respondents in all ( n = 317 ) households in the fishing and sea-hunting village of Lamalera , Indonesia , were asked to name those households to whom they had more frequently given ( and from whom they had more frequently received ) food during the preceding sea-hunting season . The responses were used to construct a social network of between-household food-sharing relationships in the village . The results show that kinship , proximity , and reciprocal sharing all strongly increase the probability of giving food to a household . The effects of kinship and distance are relatively independent of each other , although reciprocity is more common among residentially and genealogically close households . The results show support for reciprocal altruism as a motivation for food sharing , while kinship and distance appear to be important partner-choice criteria
Second , we show that network composition , individual network central ity , and network structure are associated with important health behaviors and health and development outcomes in different context s across multiple levels of analysis and across distinct network types .
Lastly , we highlight the opportunities for health research ers and practitioners in LMICs to 1 ) design effective studies and interventions in LMICs that account for the sociocentric network positions of certain individuals and overall network structure , 2 ) measure the spread of outcomes or intervention externalities , and 3 ) enhance the effectiveness and efficiency of aid based on knowledge of social structure .
In low- and middle-income countries ( LMICs ) , naturally occurring social networks may be particularly vital to health outcomes as extended webs of social ties often are the principal source of various re sources .