A prospective examination of online social network dynamics and smoking cessation

<div><p>Introduction</p><p>Use of online social networks for smoking cessation has been associated with abstinence. Little is known about the mechanisms through which the formation of social ties in an online network may influence smoking behavior. Using dynamic social network analysis, we investigated how temporal changes of an individual’s number of social network ties are prospectively related to abstinence in an online social network for cessation. In a network where quitting is normative and is the focus of communications among members, we predicted that an increasing number of ties would be positively associated with abstinence.</p><p>Method</p><p>Participants were N = 2,657 adult smokers recruited to a randomized cessation treatment trial following enrollment on BecomeAnEX.org, a longstanding Internet cessation program with a large and mature online social network. At 3-months post-randomization, 30-day point prevalence abstinence was assessed and website engagement metrics were extracted. The social network was constructed with clickstream data to capture the flow of information among members. Two network centrality metrics were calculated at weekly intervals over 3 months: 1) in-degree, defined as the number of members whose posts a participant read; and 2) out-degree-aware, defined as the number of members who read a participant’s post and commented, which was subsequently viewed by the participant. Three groups of users were identified based on social network engagement patterns: non-users (N = 1,362), passive users (N = 812), and active users (N = 483). Logistic regression modeled 3-month abstinence by group as a function of baseline variables, website utilization, and network centrality metrics.</p><p>Results</p><p>Abstinence rates varied by group (non-users = 7.7%, passive users = 10.7%, active users = 20.7%). Significant baseline predictors of abstinence were age, nicotine dependence, confidence to quit, and smoking temptations in social situations among passive users (<i>p</i>s < .05); age and confidence to quit among active users. Among centrality metrics, positive associations with abstinence were observed for in-degree increases from Week 2 to Week 12 among passive and active users, and for out-degree-aware increases from Week 2 to Week 12 among active users (<i>p</i>s < .05).</p><p>Conclusions</p><p>This study is the first to demonstrate that increased tie formation among members of an online social network for smoking cessation is prospectively associated with abstinence. It also highlights the value of using individuals’ activities in online social networks to predict their offline health behaviors.</p></div

Distributions of Week 1 degrees for all users in the network.

<p>Distributions of Week 1 degrees for all users in the network.</p

Baseline characteristics by group.

<p>Baseline characteristics by group.</p

Distributions of Week 1 degrees for the 2,657 users in the analytic sample.

<p>Distributions of Week 1 degrees for the 2,657 users in the analytic sample.</p

Website utilization and social network metrics by cluster at 3 months^a.

<p>Website utilization and social network metrics by cluster at 3 months<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0183655#t003fn001" target="_blank">^a</a>.</p

Social network utilization patterns and smoking outcomes among 3 utilization groups.

<p>Social network utilization patterns and smoking outcomes among 3 utilization groups.</p

Odds Ratio (OR) estimates of 3 month abstinence from the gee logistic regression model for active participants (N = 483).

<p>Odds Ratio (OR) estimates of 3 month abstinence from the gee logistic regression model for active participants (N = 483).</p

Odds Ratio (OR) estimates of 3 month abstinence from the GEE logistic regression model for passive participants (N = 812).

<p>Odds Ratio (OR) estimates of 3 month abstinence from the GEE logistic regression model for passive participants (N = 812).</p

Patterns, Variability, and Predictors of Urinary Bisphenol A Concentrations during Childhood

We examined the patterns, variability, and predictors of urinary bisphenol A (BPA) concentrations in 337 children from the Cincinnati, Ohio HOME Study. From 2003 to 2014, we collected two urine samples from women at 16 and 26 weeks of pregnancy and six urine samples from children at 1–5 and 8 years of age. We used linear mixed models to calculate intraclass correlation coefficients (ICCs) as a measure of within-person BPA variability and to identify sociodemographic and environmental predictors. For the 8-year visit, we used multivariable linear regression to explore associations between urinary BPA concentrations and exposure-related factors. We calculated daily intakes using equations estimating creatinine excretion rates and creatinine-standardized BPA concentrations. Urinary BPA concentrations, which decreased over childhood, had a low degree of reproducibility (ICC < 0.2). Estimated daily intakes decreased with age and were below the reference dose of 50 μg/kg body weight/day. BPA concentrations were positively associated with consuming food stored or heated in plastic, consuming canned food and beverages, and handling cash register receipts. Our results suggest that there are multiple sources of BPA exposure in young children. Etiological studies should collect serial urine samples to accurately classify BPA exposure and consider sociodemographic and environmental factors as possible confounders