Myong-Hyun Go

Peer influence and selection effects on adolescent smoking

BACKGROUND Studies showing that adolescents are more likely to smoke if they have friends who smoke typically infer that this is the result of peer influence. However, it may also be due to adolescents choosing friends who have smoking behaviors similar to their own (i.e., selection). One of the most influential studies of influence and selection effects on smoking concluded that these processes contribute about equally to peer group homogeneity in adolescent smoking (Ennett and Bauman, 1994). The goal of this study was to conduct a partial replication of these findings. METHODS Data are from 1223 participants in the National Longitudinal Study of Adolescent Health. Spectral decomposition techniques identified friendship cliques, which were then used as the unit of analysis to examine influence and selection effects over a one-year period. RESULTS Non-smokers were more likely to become smokers if they initially belonged to a smoking (vs. non-smoking) group, and smokers were more likely to become non-smokers if they initially belonged to a non-smoking (vs. smoking) group, indicating an influence effect on both initiation and cessation. Further, group members who changed groups between waves were more likely to select groups with smoking behavior congruent to their own, providing evidence of a selection effect. CONCLUSIONS While our results generally replicate the group analyses reported by Ennett and Bauman (1994), they suggest that peer influence and selection effects on adolescent smoking may be much weaker than assumed based on this earlier research.

The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?

Mathematical models are useful tools for understanding and predicting epidemics. A recent innovative modeling study by Stehle and colleagues addressed the issue of how complex models need to be to ensure accuracy. The authors collected data on face-to-face contacts during a two-day conference. They then constructed a series of dynamic social contact networks, each of which was used to model an epidemic generated by a fast-spreading airborne pathogen. Intriguingly, Stehle and colleagues found that increasing model complexity did not always increase accuracy. Specifically, the most detailed contact network and a simplified version of this network generated very similar results. These results are extremely interesting and require further exploration to determine their generalizability.Please see related article BMC Medicine, 2011, 9:87

Adolescent romantic relationships and change in smoking status

Although smoking rates have decreased, smoking among adolescents continues to be a problem. Previous research has shown the importance of peer influences on adolescent smoking behavior but has mostly neglected the impact of adolescent romantic relationships. This study examines the influence of romantic relationships with smokers and non-smokers on smoking initiation and cessation over a one-year period using data from the National Longitudinal Study of Adolescent Health (Add Health). For initial non-smokers, we examined whether the total length of time in romantic relationships with smokers and non-smokers at Wave I, as well as amount of exposure to smoking through romantic partners, predicted smoking initiation at Wave II. Among initial regular smokers, we examined whether these same relationship characteristics predicted smoking cessation at Wave II. These analyses were conducted separately for respondents in any type of romantic relationship, as well as just those respondents in close romantic relationships. Results indicated that, for close romantic relationships, cessation was more likely among smokers with more time in relationships with non-smoking partners. Greater exposure to smoking through romantic partners at Wave I significantly decreased the likelihood of cessation among initial smokers and increased the likelihood of initiation among initial non-smokers. For all relationships, greater exposure to smoking through romantic partners at Wave I significantly reduced the likelihood of cessation. These associations held when controlling for best friend smoking, as well as demographic factors and school-level smoking, suggesting that peer-based smoking programs aimed at adolescents should incorporate a focus on romantic relationships.

Cost Implications to Health Care Payers of Improving Glucose Management among Adults with Type 2 Diabetes

Objective. To assess the cost implications to payers of improving glucose management among adults with type 2 diabetes. Data Source/Study Setting. Medical-record data from the Community Quality Index (CQI) study (1996-2002), pharmaceutical claims from four Massachusetts health plans (2004-2006), Medicare Fee Schedule (2009), published literature. Study Design. Probability tree depicting glucose management over 1 year. Data Collection/Extraction Methods. We determined how frequently CQI study subjects received recommended care processes and attained Health Care Effectiveness Data and Information Set (HEDIS) treatment goals, estimated utilization of visits and medications associated with recommended care, assigned costs based on utilization, and then modeled how hospitalization rates, costs, and goal attainment would change if all recommended care was provided. Principal Findings. Relative to current care, improved glucose management would cost U.S.

Romantic attraction and adolescent smoking trajectories

327 (U.S.

What impact will reducing concurrency have on decreasing the incidence of HIV in heterosexual populations

192-711 in sensitivity analyses) more per person with diabetes annually, largely due to antihyperglycemic medications. Cost-effectiveness to payers, defined as incremental annual cost per patient newly attaining any one of three HEDIS goals, would be U.S.

Friendship networks and trajectories of adolescent tobacco use.

1,128; including glycemic crises reduces this to U.S.

Social distance and homophily in adolescent smoking initiation

555-1,021. Conclusions. The cost of improving glucose management appears modest relative to diabetes-related health care expenditures. The incremental cost per patient newly attaining HEDIS goals enables payers to consider costs as well as outcomes that are linked to future profitability.

Cost Implications of Improving Blood Pressure Management Among U.S. Adults

Research on sexual orientation and substance use has established that lesbian, gay, and bisexual (LGB) individuals are more likely to smoke than heterosexuals. This analysis furthers the examination of smoking behaviors across sexual orientation groups by describing how same- and opposite-sex romantic attraction, and changes in romantic attraction, are associated with distinct six-year developmental trajectories of smoking. The National Longitudinal Study of Adolescent Health dataset is used to test our hypotheses. Multinomial logistic regressions predicting smoking trajectory membership as a function of romantic attraction were separately estimated for men and women. Romantic attraction effects were found only for women. The change from self-reported heterosexual attraction to lesbian or bisexual attraction was more predictive of higher smoking trajectories than was a consistent lesbian or bisexual attraction, with potentially important differences between the smoking patterns of these two groups.

Adolescent Friendship Networks and Trajectories of Binge Drinking

The importance of concurrency (i.e., multiple over lapping sexual partnerships) in driving HIV epidemics has been hotly debated in the past 20 years. Some have hypothesized that concurrency is an extremely important driver of HIV epidemics and may explain the high prevalence of HIV in the general population of many Sub-Saharan African countries. Notably, proponents of this hypothesis acknowledge a host of other factors, such as multiple sex partners, core groups and the presence of other sexually transmitted infections are also very important. A substantial amount of data have been collected on sexual behavior (e.g., the number of sex partners individuals’ acquire each year), but there are only very limited data on the level and/or degree of concurrency in any population [1](Lurie and Rosenthal 2010). Consequently, it has been impossible to use empirical data to evaluate whether - or not - concurrency is a major driver of HIV epidemics. This lack of empirical evidence has led others to dispute the idea that concurrency is an important driver. Mathematical modelers, unconstrained by empirical data, have been investigating the potential impact of concurrency on HIV epidemics since the early 1990s [2] (Watts and May 1992). Modeling by Morris and Kretzschmar [3-4](1997; 2000) has shown that if levels of concurrency in heterosexual populations are high (i.e., 50%), the prevalence of HIV could be ~10 times higher than if individuals were serially monogamous. In an article in this issue, McCreesh and colleagues [5] present a new model representing heterosexual transmission of HIV. They use their model to evaluate the potential epidemiological impact of hypothetical public health interventions that focus on reducing concurrency in heterosexual populations. McCreesh and colleagues have developed a stochastic network model of sexual partnerships, some of which can be concurrent, in a heterosexual population where HIV is being transmitted. They used data on demography, sexual behavior, and HIV prevalence collected in 2008 in Uganda to parameterize their model. The sexual behavior data they used contained information on both the number of sex partners and the level of concurrency. These data were from the Masaka General Population Cohort study, which is a longitudinal study that has been running since 1989. Study participants are ~7,000 residents of 25 villages in the rural south-west of Uganda. Each year face-to-face interviews are conducted; blood samples are collected and tested for HIV. Concurrency data were collected from 1,214 men and 1,470 women, a subset of the cohort study. Concurrency was defined as “overlapping sexual partnerships where sexual intercourse with one partner occurs between two acts of intercourse with another partner.” Concurrency was further classified into two types: i) sex with spouses and exspouses, defined as concurrent partnership of long duration and ii) sex with others, defined as concurrent partnership of short duration. The survey data, used to parameterize the model, shows that 9.6% of men in these rural villages in Uganda reported having engaged in a concurrent partnership of either type, but only 0.2% of women reported doing so. McCreesh and colleagues assumed that the concurrency level reported by women was significantly lower than the actual value. Consequently in their modeling, they increased the level of concurrency for women from the reported level of 0.2% to 2.4%, a twelve-fold increase. They then used their stochastic network model to evaluate the potential impact of hypothetical public health interventions that focus on reducing concurrency. The authors found that when concurrency was reduced by 20%, the incidence of HIV (over a 10 year period) decreased by 9.2% in women, but only by 4.1% in men. When concurrency was reduced by 50%, the incidence of HIV (over a 10 year period) decreased by 16.2% in women, but only by 6.0% in men. Notably, if the authors had not inflated the level of concurrency in women the reductions in incidence would have been substantially lower. The authors’ results show that the impact of reducing concurrency on decreasing HIV incidence, and hence the importance of concurrency in driving HIV epidemics, is fairly minimal given the specified levels of concurrency in these communities. Notably, the results of McCreesh et al. are in line with a recently published empirical study by Tanser et al. [6] in a rural area in the South African Province of KwaZulu-Natal. Tanser and colleagues estimated the effect of community level concurrency on a woman’s risk of becoming infected with HIV. They found that the number of sex partners, but not concurrency, was a major risk factor for HIV infection. Both the modeling study by McCreesh et al. and the recent empirical study by Tanser et al. make a significant contribution to the debate regarding the importance of concurrency in driving HIV epidemics. Results from both of these studies indicate that concurrency is not a major driver of HIV epidemics in Sub-Saharan Africa. We note that in order for concurrency to be an important driver in generalized HIV epidemics driven by heterosexual transmission three conditions would need to be met: first, there should be many concurrent partnerships in the population; second, the number of concurrent partners should be fairly high for the average individual; and finally, the duration over which the partnerships overlap should be fairly long. To date, no heterosexual community has been identified where these conditions are met. Since the beginning of the HIV epidemic the number of sex partners that individuals in the population acquire each year has been identified to be the major factor driving HIV epidemics and the major risk factor for an individual; the greater the number of sex partners an individual has, the greater their risk of acquiring HIV. If an individual has a high level of sex partners it does not mean that they have a high level of concurrency, however if an individual has a high level of concurrency they have to have a high number of sex partners. Therefore we recommend ending the debate on the importance of concurrency as a driver of HIV epidemics in Sub-Saharan Africa. Rather than trying to reduce concurrency, which is likely to have only a modest impact, we recommend concentrating on designing interventions that focus on decreasing the number of sex partners and/or increasing in condom usage. If concurrency is important, its’ impact on transmission will also be decreased by these interventions.