Modeling Social Network Influences on Oral Health Outcomes among Women Living in Public Housing

Research into the influence and role of social networks on oral health outcomes has been limited. This study aims to demonstrate via explanatory modeling the influence of social networks on oral health outcomes among women in who live in public housing in Boston, Massachusetts.

Individual- and network-level data were obtained from a cross-sectional survey of adult female residents of 2 public housing developments in Boston, Massachusetts. Participants responded to close-ended questions about sociodemographic characteristics, oral and general health status, and health-related behaviors for themselves as well as their named social contacts. Based on this information, network-level variables were calculated for each participant, including the proportion of the social network with certain characteristics or attributes. To assess the salience of network measures in explaining the variability in self-reported oral health status, overall health status, use of dental services within the last year, and current dental treatment needs, logistic regression models with individual-level covariates were compared with corresponding models that additionally included network-level variables with McFadden R² for comparison purposes.

Model comparisons for each outcome of interest demonstrated that adding network-level covariates significantly improved model fit. Additionally, network-level covariates displayed strong independent associations with the outcomes of interest. The network proportion needing dental treatment was positively associated with participants' odds of reporting current dental treatment needs (odds ratio, 4.71; 95% CI, 1.47 to 15.05). An individual's odds of reporting no dental visit within the past year decreased with increasing exposure to social contacts with reported dental visits within the past year (odds ratio, 0.26; 95% CI, 0.07 to 0.89).

The salience of specific network attributes depended on the outcome under study. Interventions aimed at reducing the poor oral health burden in this and similar population groups may benefit from integrating information on social networks, including tailoring intervention delivery and/or messaging to account for the potential influence of social networks.

This work may be beneficial to those developing policy solutions and interventions aimed at reducing the burden of poor oral health outcomes in socioeconomically disadvantaged populations, such as women who reside in public housing developments. The potential for leveraging social networks to seed messaging about oral health, for example, may enhance efforts to reduce oral health disparities.