Kayo Fujimoto

Adolescent Affiliations and Adiposity: A Social Network Analysis of Friendships and Obesity

Friendship choices and BMI were measured for 617 adolescents 11-15 years of age. Overweight youth were twice as likely to have overweight friends. There was a weak association between social position and weight status. Overweight youth nominated more friends but were nominated as friends less frequently than their normal weight peers.

Bridging: Locating Critical Connectors in a Network.

This paper proposes several measures for bridging in networks derived from Granovetters (1973) insight that links which reduce distances in a network are important structural bridges. Bridging is calculated by systematically deleting links and calculating the resultant changes in network cohesion (measured as the inverse average path length). The average change for each nodes links provides an individual level measure of bridging. We also present a normalized version which controls for network size and a network level bridging index. Bridging properties are demonstrated on hypothetical networks, empirical networks, and a set of 100 randomly generated networks to show how the bridging measure correlates with existing network measures such as degree, personal network density, constraint, closeness centrality, betweenness centrality, and vitality. Bridging and the accompanying methodology provide a family of new network measures useful for studying network structure, network dynamics, and network effects on substantive behavioral phenomenon.

Global Tobacco Control Diffusion: The Case of the Framework Convention on Tobacco Control

OBJECTIVES We analyzed demographic and social network variables associated with the timing of ratification of the Framework Convention on Tobacco Control (FCTC). METHODS We compiled a 2-mode data set that recorded country participation in FCTC negotiations, as well as the number of individuals per country per year who joined an online tobacco control network. We used logistic regression analysis of these 2 data sets along with geographic location to determine whether exposure to prior FCTC adoptions was associated with a countrys likelihood of adoption. RESULTS In the logistic regression analysis, higher income and more nongovernmental organizations (NGOs) involved in the Framework Convention Alliance (a network dedicated to the FCTC) were associated with being among the earliest adopters (for income, adjusted odds ratio [AOR] = 2.41; 95% confidence interval [CI] = 1.55; for NGOs, AOR = 1.66; 95% CI = 1.26, 2.17) or among early adopters (for income, AOR = 1.42; 95% CI = 1.09, 1.84; for NGOs, AOR = 1.23; 95% CI = 1.03, 1.45). Network exposure and event history analysis showed that in addition to income, the likelihood of adoption increased with increasing affiliation exposure to FCTC adopters through GLOBALink (an online network facilitating communication between tobacco control advocates). CONCLUSIONS Public health programs should include a plan for creating opportunities for network interaction; otherwise, adoption and diffusion will be delayed and the investments in public health policy greatly diminished.

A comparison of peer influence measures as predictors of smoking among predominately Hispanic/Latino high school adolescents

PURPOSE Consistent evidence has shown that one of the most significant influences on adolescent smoking is peer influence. There is considerable variation, however, in how peer influence is measured. This study constructs social network influence and selection variables from egocentric and sociometric data to compare their associations with smoking, with considerations of perceived smoking norms and adolescent popularity. METHODS Longitudinal data were collected in the 9th and 10th grades in October 2006 and 2007 from predominantly Hispanic/Latino adolescents in seven Southern California schools; among these adolescents, 1,950 completed surveys at both waves. Both cross-sectional (separately for 9th and 10th graders) and longitudinal models were estimated. RESULTS An egocentric measure of perceived friend smoking was strongly and consistently associated with individual smoking (adjusted odds ratio [AOR] ≈ 1.80, p < .001), whereas its sociometric counterpart of friend self-report smoking was only associated with smoking in the 9th-grade cross-sectional models (e.g., AOR = 1.56, p < .001) and rarely in longitudinal models. Popularity, measured by proportion of nominations received by class size, was associated with smoking and becoming a smoker (AOR = 1.67, p < .001), whereas perceived norms were not, in longitudinal models. Friend selection was also associated with becoming a smoker (AOR = 1.32, p = .05). CONCLUSIONS This study illustrates the utility of egocentric data for understanding peer influence and underscores the importance of perceptions and popularity as mechanisms that influence adolescent smoking.

The Network Autocorrelation Model using Two-mode Data: Affiliation Exposure and Potential Bias in the Autocorrelation Parameter

Abstract The network autocorrelation model has been a workhorse for modeling network influences on individual behavior. The standard network approaches to mapping social influence using network measures, however, are limited to specifying an influence weight matrix (W) based on a single mode network. Additionally, it has been demonstrated that the estimate of the autocorrelation parameter ρ of the network effect tends to be negatively biased as the density in W matrix increases. The current study introduces a two-mode version of the network autocorrelation model. We then conduct simulations to examine conditions under which bias might exist. We show that the estimate for the affiliation autocorrelation parameter (ρ) tends to be negatively biased as density increases, as in the one-mode case. Inclusion of the diagonal of W, the count of the number of events participated in, as one of the variables in the regression model helps to attenuate such bias, however. We discuss the implications of these results.

Variations in network boundary and type: A study of adolescent peer influences

Abstract This study compares variation in network boundary and network type on network indicators such as degree and estimates of social influences on adolescent substance use. We compare associations between individual use and peer use of tobacco and alcohol when network boundary (e.g., classroom, entire grade in school, and community) and relational type (elicited by asking whom students: (a) are friends with, (b) admire, (c) think will succeed, (d) would like to have a romantic relationship with, and (e) think are popular) are varied. Additionally, we estimate Exponential Random Graph Models (ERGMs) for 232 networks to obtain a homophily estimate for smoking and drinking. Data were collected from a cross-sectional sample of 1707 adolescents in five high schools in one school district in Los Angeles, CA. Results of logistic regression models show that associations were strongest when the boundary condition was least constrained and that associations were stronger for friendship networks than for other ones. Additionally, ERGM estimations show that grade-level friendship networks returned significant homophily effects more frequently than the classroom networks. This study validates existing theoretical approaches to the network study of social influence as well as ways to estimate them. We recommend researchers use as broad a boundary as possible when collecting network data, but observe that for some research purposes more narrow boundaries may be preferred.

Venue-based affiliation networks and HIV risk-taking behavior among male sex workers.

Background This study examined venue-based networks constituted by affiliation with gay bars and street intersections where male sex workers (MSWs) congregate to find their sexual/drug-sharing partners and network influence on risky sexual behavior (e.g., unprotected anal intercourse [UAI]) and HIV infection. Methods Data collected in 2003 to 2004 in Houston, Texas, consists of 208 MSWs affiliated with 15 gay bars and 51 street intersections. Two-mode network analysis was conducted to examine structural characteristics in affiliation networks, as well as venue-based network influence on UAI and HIV infection. Results Centralized affiliation patterns were found where only a few venues were popular among MSWs, and these were highly interdependent. Distinctive structural patterns of venue-based clustering were associated with UAI and infection. Individuals who shared venue affiliation with MSWs who engage in UAI were less likely to have UAI themselves. This suggests a downhill effect; that is, individuals compensate for their risk of infection by adjusting their own risk-taking behavior, based on their perceptions of their venue affiliates. Conclusions Venue-based HIV/AIDs interventions could be tailored to specific venues so as to target specific clusters that are more likely to engage in risky sexual behavior.

A Network Assessment of Community-Based Participatory Research: Linking Communities and Universities to Reduce Cancer Disparities

OBJECTIVES We sought to determine whether a community-based initiative designed to reduce cancer disparities among Pacific Islanders in Southern California increased communications between community-based organizations and university researchers. METHODS We conducted network analysis among 11 community-based organizations (CBOs) and 5 universities by interviewing 91 and 56 members of these organizations, respectively, at 2 points in time. We estimated random effects probit regression and stochastic actor-oriented network dynamic models. RESULTS We found that, during the 2-year study period, CBOs increased their connectedness with one another (b= 0.44; P < .05) and to the universities (b = 0.46; P < .05), but that university researchers did not increase their connectedness to each other or to CBOs. CONCLUSIONS Cancer awareness, cancer education, and access to cancer services are low among Pacific Island groups, and this study provides an initial attempt to reduce these disparities. Community-based initiatives can strengthen a CBO network, creating the potential for increased community-informed cancer research and improved community access to cancer research resources.

Network structural influences on the adoption of evidence-based prevention in communities†‡

This study examined the impact of key variables in coalition communication networks, centralization and density, on the adoption of evidence-based substance abuse prevention. Data were drawn from a network survey and a corresponding community leader survey that measured leader attitudes and practices toward substance abuse prevention programs. Two types of coalition networks were measured: advice-seeking and discussion relations. For each community, we computed network-level measurements (n = 20), and then used multiple linear regression. Results showed that adoption outcomes were associated with a decrease in centralization for the advice network and an increase in centralization for the discussion network, controlling for density. This suggests that community coalitions might consider decreasing their network density in such a manner that distributes power and influence among a broader base of coalition members to seek advice about programs while simultaneously discussing these programs in a more concentrated group to facilitate decisions about which programs to adopt.

Content-Driven Analysis of an Online Community for Smoking Cessation: Integration of Qualitative Techniques, Automated Text Analysis, and Affiliation Networks

OBJECTIVES We identified content-specific patterns of network diffusion underlying smoking cessation in the context of online platforms, with the aim of generating targeted intervention strategies. METHODS QuitNet is an online social network for smoking cessation. We analyzed 16 492 de-identified peer-to-peer messages from 1423 members, posted between March 1 and April 30, 2007. Our mixed-methods approach comprised qualitative coding, automated text analysis, and affiliation network analysis to identify, visualize, and analyze content-specific communication patterns underlying smoking behavior. RESULTS Themes we identified in QuitNet messages included relapse, QuitNet-specific traditions, and cravings. QuitNet members who were exposed to other abstinent members by exchanging content related to interpersonal themes (e.g., social support, traditions, progress) tended to abstain. Themes found in other types of content did not show significant correlation with abstinence. CONCLUSIONS Modeling health-related affiliation networks through content-driven methods can enable the identification of specific content related to higher abstinence rates, which facilitates targeted health promotion.