Social Network Characteristics and Body Mass Index in an Elderly Korean Population

Lee, Won Joon; Youm, Yoosik; Rhee, Yumie; Park, Yeong-Ran; Chu, Sang Hui; Kim, Hyeon Chang

This study has several limitations. First, because of the crosssectional design, this study could not establish a temporal relationship between BMI and social network characteristics. Second, the survey data were open to measurement error. In particular, the reported relationships among alters might differ from actual relationships. It is important to determine not only the association between an ego's health behavior and an actual social network, but the perceived social network as well. Third, we assumed an inverse linear relationship between BMI and health. However, an increased risk of death has been observed to be associated with a low BMI in other studies [37, 38] . Inadequate or incomplete control for confounding or reverse-causation bias could in part explain the increased risk [39] . A low BMI can be an indicator of certain other chronic medical conditions [40] . We adjusted for comorbidities, such as hypertension, diabetes, stroke, and arthritis, in order to overcome this unintended effect. This study population was dwelling in the community, not institutions, and they completely responded to the long survey (mean response time: 70 minutes). It can thus be concluded that they were not unhealthy enough to induce a reverse-causation bias. Fourth, the questionnaires did not measure diet and physical activity. These factors are determinants for obesity, and taking them into account may be necessary to identify the behavioral process (indirect effect) of social networks on BMI [26] . We could not distinguish behavioral processes from psychological processes in this study. Fifth, external validity could be limited because all of the subjects in the study population resided in a single rural community. Accordingly, further longitudinal studies in urban and rural areas are needed.