The Social Context of Adolescent Smoking: A Systems Perspective

 
FRAMING HEALTH MATTERS

The Social Context of Adolescent Smoking:
A Systems Perspective
 Cynthia M. Lakon, PhD, MPH, John R. Hipp, PhD, and David S. Timberlake, PhD

                                                                                                              Furthermore, such models do not provide spe-
      We used a systems science perspective to examine adolescents’ personal
                                                                                                              cific guidance about mechanisms through which
   networks, school networks, and neighborhoods as a system through which
   emotional support and peer influence flow, and we sought to determine whether                              levels of influence relate to outcomes such as
   these flows affected past-month smoking at 2 time points, 1994–1995 and 1996.                              adolescent smoking. There is a need for theo-
   To test relationships, we employed structural equation modeling and used                                   retical models that more specifically and holis-
   public-use data from the National Longitudinal Study of Adolescent Health                                  tically elaborate features of the social context of
   (n = 6504). Personal network properties affected past-month smoking at both                                adolescent smoking and how they act in concert.
   time points via the flow of emotional support. We observed a feedback loop from
   personal network properties to emotional support and then to past-month                                    A SYSTEMS MODEL OF THE
   smoking. Past-month smoking at time 1 fed back to positively affect in-degree                              CONTEXT OF ADOLESCENT
   centrality (i.e., popularity). Findings suggest that networks and neighborhoods
                                                                                                              SMOKING
   in this system positively affected past-month smoking via flows of emotional
   support. (Am J Public Health. 2010;100:1218–1228. doi:10.2105/AJPH.2009.
                                                                                                                 In this study, we incorporate valuable in-
   167973)
                                                                                                              sights from ecological models that theoretically
                                                                                                              partition the environment into levels of influ-
Adolescent cigarette smoking remains a com-            information about linkages among individ-              ence to frame the social context of adolescent
plex public health problem in the United States.       uals, and positional characteristics indicate the      smoking as a complex social system. We
Although lifetime smoking and current fre-             significance of occupying different network            employed a systems science14 approach in
quency of smoking among adolescents de-                positions. In general, studies find that isolated      conceptualizing the social context of adolescent
creased between the late 1990s and 2003,               youths are likely to smoke, although some              smoking, which emphasizes interdependence in
prevalence remained unchanged from 2003                studies have found that popular youths are             complex relationships among people or organi-
through 2005.1 Smoking prevalence among                likely to smoke.3–5,9–12 Implicit in each study is     zations.15 The defining features of systems are
adolescents is currently estimated to be around        the notion that adolescents’ social context of         (1) parts or components yielding a whole that is
23%,1 posing ongoing challenges for tobacco-           friends and peers plays a critical role in their own   greater than the sum of the parts, (2) inputs and
control efforts.                                       smoking behavior.                                      flows coursing through a system, and (3) feed-
   Several streams of literature suggest that             Given the relevance of adolescents’ social          back loops linking parts of a system. Such system
adolescent smoking is inextricably connected           context to their smoking behavior, it is impor-        features hold promise for informing theoretical
to the social context in which it occurs. Liter-       tant to understand how to conceptualize and            models that elaborate adolescents’ social net-
ature shows that an adolescent’s smoking be-           measure this context. Previous research has            works, the dimensionality of their social rela-
havior will tend to be similar to that of his or       used ecological models to inform the theoret-          tionships, and the interdependence among levels
her peers.2–6 There is a longstanding debate           ical specification of the context of adolescent        of influence within their social context.
over why this similarity occurs; some studies          smoking and other substance-use behaviors.13              We conceptualized 3 key structures in the
suggest that it is caused by peer influence on an      Ecological models allow this context to be theo-       social environment of adolescent smoking as
individual adolescent’s smoking,7,8 whereas            retically partitioned into levels of influence.        structural components defining the system un-
others suggest that it is caused by the individual’s   Although there are valuable insights yet to be         der study: (1) personal networks of friends, (2)
selection of smoking peers,8 and still others          gained from such models, more theoretically            school networks, and (3) neighborhoods.
attribute the cause to both influence and selec-       informed research is necessary to elaborate the        School networks were defined as whole net-
tion.2 Some of the literature implicating adoles-      complexity of the social context of adolescent         works of all students in a school and the social
cents’ social contexts in their smoking behavior       smoking. Moreover, because various theories are        ties among them. These networks were con-
examines youths’ social networks of friends and        often integrated at different levels in such           structed from adolescents’ nominations of up to
peers from a structural perspective. Such studies      models, it is difficult to ensure that conceptual      10 friends from a roster listing all names of
focus on how structural and positional charac-         coherence is achieved across and within levels,        adolescents in their own high school and
teristics of these networks relate to adolescent       given the possibility that the theories applied        a geographically proximal ‘‘sister’’ junior or
smoking. Structural characteristics reflect            at each level make incongruous assumptions.            senior high school. Adolescents’ personal

1218 | Framing Health Matters | Peer Reviewed | Lakon et al.                                         American Journal of Public Health | July 2010, Vol 100, No. 7
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    FIGURE 1—Systems model of contextual structures and flows of social processes influencing adolescent smoking.

networks were subsets of whole school net-             network level, conceptualized at the level of the     Having reciprocated friendships may facilitate
works and comprised friends nominated within           adolescent, we focused on (1) adolescents’ popu-      the flow of network resources throughout a net-
their schools and their friends’ ties. The neigh-      larity, or their in-degree centrality; (2) whether    work, as resources are likely exchanged in
borhoods under study were the physical areas           their friendships are mutually reciprocated; (3)      mutual friendships, both in personal networks
where the adolescents lived. We investigated           personal network density, or the extent to which      and in school networks. One study found that
how characteristics of these 3 structural com-         those named in adolescents’ networks know one         adolescents with reciprocated ties with a best
ponents influenced adolescent smoking via              another; (4) the social distance between adoles-      friend were less likely to smoke at age 11 and 13
flows of 2 social processes: emotional support         cents in their networks or the number of path         years than those without such ties.4
and peer influence (Figure 1). We hypothesized         lengths between them, which are relationship ties         Personal network density reflects the extent
that these social processes were mechanisms            linking individuals in a network16; and (5) the       to which those in an adolescent’s personal
through which the structural components un-            number of people they nominated as friends            network know one another. The density of ties,
der study influenced smoking.                          outside of their schools.                             either in personal networks or whole networks,
   In this introduction, we focused on the paths           At the school network level, we focused on        likely plays a role in the flow of resources
of main theoretical interest depicted in this          the network properties of size, density, and the      throughout a network by binding people to-
model; we refer to the other constructs in the         mutuality of ties, all of which may affect            gether and strengthening adherence to pervasive
Methods section only. Throughout this article,         smoking behavior.17 Size refers to the number of      norms and beliefs. Dense ties can also limit the
we present the model, findings, and discussion         students in a school, density is the extent to        inflow of resources from outside a network.
of the results in terms of the causal direction-       which students know one another in a school,          Adolescents aged 15 years who had dense local
ality assumed in our model, but only for ease of       and mutuality is the extent to which youths’          networks were found to have lower odds of
exposition and not for the purpose of making           relationships are mutually reciprocated within        recent smoking.4 If adolescents are close to one
any causal claims.                                     the broader school context. School-level network      another in a network—that is, if path length is
                                                       characteristics may affect the structure and po-      low—then social influences and network re-
THE ROLES OF NETWORKS AND                              sitional attributes of personal networks as larger-   sources may be easily transmitted because the
NEIGHBORHOODS                                          scale versions of these constructs.                   probability of transmission decreases over longer
                                                           The theoretical intuition underlying each of      path lengths.18 Previous research has found that
   For this study, we focused on properties of         the aforementioned network properties is what         adolescents who were socially proximal to
personal and school networks that are relevant to      makes them relevant to adolescent smoking             a smoker had increased odds of smoking.4 Lastly,
the flow of network resources throughout the           from a systems perspective. Popular youths are        the number of people youths nominated as
larger system under study and that have been           directly connected to many others and can             ‘‘friends’’ outside of their schools captures re-
related to adolescent smoking. Network ties carry      quickly and disproportionately transmit and           lationships that either reinforce or attenuate the
resources that flow through a network and are          receive network resources, such as support.           effect of social influences from in-school friends,
exchanged by network members, such as social           Being central or popular in networks is posi-         depending on the types of influences exerted
influence and social support. At the personal          tively related to smoking among youths.11,12          by each of these friends. There is evidence that

July 2010, Vol 100, No. 7 | American Journal of Public Health                                      Lakon et al. | Peer Reviewed | Framing Health Matters | 1219
FRAMING HEALTH MATTERS

having ties to friends from outside one’s school is     generally extends to feelings of closeness, en-       structural components have on smoking is peer
positively related to adolescent smoking.4              couragement, and belonging32—and peer influ-          influence. In this study, peer influence was
   Although previous research offers insight            ence, narrowly defined as the influence exerted       conceptualized as the influence exerted by an
into how each of these network properties               by adolescents’ friends who smoke, as mecha-          adolescent’s friends’ smoking behavior on the
relates to adolescent smoking, smoking behav-           nisms linking social network ties and adolescent      adolescent’s own smoking behavior. The posi-
ior may affect the structure and position of            smoking. Although more inclusive conceptuali-         tive relationship between peer influence and
individuals in a network via network processes          zations of peer influence exist, we focused only      smoking is well-documented.39,40 Peer influ-
such as influence, social support, and selection.       on the influence derived from adolescents’            ence processes have been measured in relation
We explored this notion in our study by                 friends who smoke because they may be partic-         to smoking in numerous ways, including the
positing feedback pathways from smoking to              ularly proximal to and relevant for adolescents’      number of friends who smoke.41,42 Furthermore,
the network characteristics under study.                smoking behavior.                                     studies have found that network characteristics
   Finally, we took adolescents’ neighborhoods             Studies have found that emotional support is       affect the number of friends who smoke. For
into account, utilizing insights from social dis-       positively associated with smoking.33 Perhaps         example, studies have found that reciprocity43
organization theory.19,20 This ecological theory        the closeness generated from an emotionally           and density of network ties are associated with
posits that the key structural characteristics of       supportive tie reinforces social bonding as friends   greater peer influence, arguably through tightly
economic disadvantage, racial/ethnic heteroge-          smoke together. An analogous finding comes            binding people together in a network and am-
neity, and residential instability lead to an overall   from the injection drug use literature, which has     plifying social influence.44,45 It is also likely
milieu of social disorganization within certain         shown that the provision of emotional support in      that peer influence is positively related to
neighborhoods, giving rise to higher levels of          relationships mediated the association between        being central in networks, because highly central
delinquency. In such neighborhoods, this disor-         closeness of ties and needle sharing.34 Among         individuals can quickly receive and transmit
ganization limits residents’ ability to provide the     injection drug users, needle sharing behavior was     influence, and to path length in networks, be-
informal social control that would otherwise            likely a symbolic act of solidarity, exclusivity,     cause social influences may be quickly trans-
reduce adolescents’ delinquent behavior. Al-            and bonding. For adolescents, smoking behavior        mitted if individuals are close to one another in
though the bulk of research using this theory has       may carry a similar symbolic meaning related to       a network.
focused on the generation of criminal forms of          social bonding, especially in the context of             Although there is likely an influence effect of
delinquency,21–23 recent research has tested            emotionally supportive and valued friendships.        friends’ smoking behavior on adolescent
whether these structural characteristics also in-       Moreover, in some friendships receipt of emo-         smoking, there is also likely a selection effect, in
crease the delinquent behavior of cigarette             tional support may be contingent upon engaging        which persons who smoke are more likely to
smoking.24–26                                           in a delinquent behavior because failure to           choose friends who also smoke. To the extent
                                                        smoke and being different from a friend on this       that having friends who smoke then affects
EMOTIONAL SUPPORT AND PEER                              dimension might be perceived as a strike against      one’s position in the network, we suggest that
INFLUENCE AS SYSTEM FLOWS                               the friendship. It is not surprising that emotional   there will be a feedback loop from personal
                                                        support has potential to compromise health            network properties, to friends’ smoking be-
   To study how the structural components of            because previous research has indicated that          havior, to smoking at wave 1 (Figure 1).
interest exert influence on adolescent smoking,         social support can reinforce delinquent behav-           In sum, we examined direct, mediated, and
we hypothesized that 2 social processes—                iors among youths and their network members           feedback pathways through which these
emotional support and peer influence—may be             via modeling processes.35,36                          structural components influenced smoking at 2
mechanisms through which properties of these               Beyond the effect of emotional support on          time points approximately 1 year apart via flows
structural components influence adolescent              smoking behavior, there is reason to expect           of emotional support and peer influence.
smoking. Emotional support relates to health            that the network characteristics under study          Given the systems nature of the study, we
through both direct effects and buffering ef-           increase emotional support. It is likely that         examined a number of pathways in 2 categories:
fects.27 Social support may be a pathway linking        more central individuals are in a position to         (1) direct pathways indicating how properties of
social networks and health indicators; studies          provide support to others or may be connected         personal and school networks and neighbor-
have related structural network characteristics to      to others who could also provide support.37           hoods influenced smoking and (2) indirect
health via emotional support and social influence       Likewise, mutually reciprocated ties, as well as      pathways through which properties of networks
processes.28 The findings of previous research          the density of ties,38 likely increase emotional      and neighborhoods influenced smoking via
highlight the need for future work to focus on          support through increased closeness. Also,            emotional support and peer influence exerted
how social influence mechanisms may mediate             shorter path lengths in networks likely increase      by friends’ smoking behavior. Last, we investi-
the relationship between social networks and            emotional support because being proximal to           gated 2 feedback loops: (1) a loop from network
health,28–30 particularly the association between       others may lead to the provision or receipt of        properties to emotional support, to smoking, and
certain types of supportive networks and                more emotional support.                               back to the network variables and (2) a loop
health-compromising behavior.31 Therefore,                 The second social process hypothesized to          from personal network characteristics to past-
we focused on emotional support—which                   potentially mediate the effect that properties of     month smoking via friends’ smoking.

1220 | Framing Health Matters | Peer Reviewed | Lakon et al.                                         American Journal of Public Health | July 2010, Vol 100, No. 7
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METHODS                                                Structural Equation Modeling                           models with varying starting values.42 We
                                                          We specified the 10 equations in our system         also used the Sargan test to determine whether
   The data for this study were taken from the         as a series of simultaneous equations using            our instrumental variables were appropriate,
first wave of the National Longitudinal Study of       structural equation modeling. Structural equa-         and the test’s nonsignificant results confirmed
Adolescent Health (i.e., Add Health), a school-        tion modeling is ideal for our approach because        that these instrumental variables were indeed
based longitudinal study consisting primarily of       it allows the equations to be estimated simul-         independent of the error term in these equa-
in-school and at-home surveys. We also in-             taneously with a maximum likelihood estima-            tions, as hypothesized. These instrumental
cluded a measure of smoking from the second            tor, and it allows reciprocal effects and feedback     variables explained a reasonable amount of the
wave of Add Health, which occurred 1 year              loops to be specified while appropriately              partial variance in the first-stage equation,
after the first wave. The Add Health wave 1            accounting for possible endogeneity. We                which is an important indicator of their
surveys were administered to a nationally rep-         accounted for clustering within schools by             strength.
resentative sample of students in grades 7             computing robust standard errors. Although                 Note that we cannot estimate the reciprocal
through 12 (and their parents) from September          hierarchical linear models handle clustering,          effect of the selection-influence relationship
1994 through December 1995; wave 2 sur-                they cannot handle reciprocal relationships and        between friends’ smoking behavior and ado-
veys were administered from April 1996 to              feedback loops, given current software con-            lescent’s past-month smoking because we do
August 1996. We used Add Health’s public-use           straints. We estimated the model displayed in          not have any plausible instrumental variables to
data, which comprise a random sample of                Figure 1. Note that the exogenous variables are        estimate both of these paths. Thus, having
6504 individuals from the full study. Social           depicted on the left-hand side of the figure and       friends who smoke likely increases an adoles-
network measures are based on a network                are not predicted by any other variables. The          cent’s past-month smoking, but those who
elicitation item asking a respondent to nomi-          other variables displayed in this figure are           smoke are also more likely to associate with
nate up to 5 male friends and 5 female friends;        endogenous variables in our system (i.e., each         friends who also smoke. Rather than simply
respondents could name persons outside of              is predicted by some other variable or vari-           assuming that the degree of association between
their school. We also used contextual data from        ables). Each of these endogenous variables is          these 2 constructs is entirely attributable to an
the 1990 US Census based on the 2407 block             represented by an equation based on our                influence effect, we adopted a novel technique
groups of residence in the sample (block groups        theoretical discussion above. For instance, in-        to test the robustness of our system, assuming
had an average population of about 1100                degree centrality is a function of the following       various values for the relative proportion of this
persons in 1990). The design sampled first on          equation:                                              relationship attributable to the selection ef-
schools and then on students within schools;                                                                  fect.46 We estimated models in which we fixed
the neighborhoods under study simply arose as          ð2Þ in-degree centrality ¼                             the selection effect at various values: (1) zero
a byproduct of this sample design because they             b1 friends’ smoking behavior þ b2 past             selection effect, (2) selection effect one third the
were defined by where adolescents in the                   -month smoking ðwave1Þ                             size of the influence effect, (3) equal selection and
sample lived.                                              þC1 neighborhood þ C2 demographics                 influence effects, and (4) selection effect 3 times
                                                           þC3 school network þ f1 ;                          the size of the influence effect. This technique
Measures                                                                                                      has only occasionally been employed.46
   The measures used in the analyses are               where b1 shows the effect of friends’ smoking              Another advantage of structural equation
described in Table 1, along with their summary         behavior on the in-degree centrality of the            modeling is that it allows us to test the overall
statistics and the levels at which they were           respondent, b2 shows the effect of the respon-         fit of the model. Structural equation modeling
measured. To aid in identifying the model              dent’s past-month smoking on their own pop-            allows the specification of a causal model,
(described next), we also included 4 measures          ularity, C1 is a vector capturing the effects of the   and it can then test how well the model rep-
of smoking risk (measured at the individual            neighborhood variables on respondent popu-             resents the observed data as a test of causality,
level) that likely affected smoking behavior but       larity, C2 is a vector capturing the effects of        as has been described elsewhere.47–49 This
not network characteristics. We included de-           the respondent’s demographics on his or her            tests the similarity of the model’s implied co-
mographic characteristics that were likely re-         own popularity, C3 is a vector capturing the           variance matrix to the sample covariance matrix.
lated to our endogenous variables. We mea-             effects of the school network variables on             Although a good model fit would be consistent
sured racial/ethnic heterogeneity on the basis         respondent popularity, and f1 is an error term.        with our theorized model, it is possible that other
of a dispersion formula:                               Analogous equations can be written for the             models that might be specified could fit these
                                                       other endogenous variables.                            data equally well. Therefore, the causal conclu-
                   P                                      We allowed for correlated errors among the          sions must necessarily be tempered, despite the
          K ðN 2  fk2 Þ
ð1Þ D ¼                  ;                             personal network variables and between emo-            fact that the specified model is inherently causal.
            N 2 ðK  1Þ
                                                       tional support and friends’ smoking behavior.          The comparative fit index of 0.998, the Tucker-
where K is the number of groups, N2 is the             We used various techniques to confirm that             Lewis index of 0.991, and the root mean square
number of persons squared, and fk is the               our model was identified (i.e., there are unique       error approximation of 0.008 suggest an excel-
frequency of group k (D ranges from 0 to 1).           values for the parameters), including estimating       lent fit for our model.49

July 2010, Vol 100, No. 7 | American Journal of Public Health                                       Lakon et al. | Peer Reviewed | Framing Health Matters | 1221
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    TABLE 1—Descriptions and Summary Statistics of Study Variables: National Longitudinal Study of Adolescent Health, 1994–1996

                         Variable                                    How Variable Was Measured                                      Range of Values                Mean (SD) or %

    Smoking and support (individual level)
      Past-month smoking (days, logged), wave 1    Number of days the respondent smoked cigarettes                    0 = no days to 30 = 30 days                   4.921 (10.082)
                                                      during the previous month (log transformed)
       Past-month smoking (days, logged), wave 2   Number of days the respondent smoked cigarettes                    0 = no days to 30 = 30 days                   5.182 (10.299)
                                                      during the previous month (log transformed)
       Emotional support (proportion)              Proportion of friends in the respondent’s personal                 0–1                                           0.347 (0.327)
                                                      network with whom they discussed a problem
                                                      in the previous 7 days
       Friends’ smoking behavior                   Respondent’s perception of how many of their 3 best                0 = no friends to 3 = 3 friends               0.817 (1.066)
                                                      friends smoked
    Personal network measures (individual level)
       In-degree centrality                        The number of persons in the network who nominated                 1–31 people                                   5.551 (3.692)
                                                      the respondent as a friend
       Personal network density                    The number of existing ties in a respondent’s network              Theoretically from 0 to 1; actually           0.412 (0.203)
                                                      divided by the total possible number of ties                       from 0.09 to 1
       Mean distance to reachable people           This is computed by (1) determining all the people the             1–21.39                                       5.284 (1.620)
                                                      respondent could reach in the network either directly
                                                      or indirectly, (2) computing the minimum number of
                                                      path lengths to reach each person, and (3) computing
                                                      the mean of those distances
       Ties outside the school                     Number of people nominated as friends who were not                 0–10                                          1.406 (2.144)
                                                      members of the respondent’s school
       Best male friend reciprocates               Whether the respondent’s best male friend reciprocated             0 = did not reciprocate,                          54.4
                                                      their tie choice                                                   1 = reciprocate
       Best female friend reciprocates             Whether the respondent’s best female friend reciprocated           0 = did not reciprocate,                          62.7
                                                     their tie choice                                                    1 = reciprocated
    School network measures (school level)
       School network density                      The proportion of existing ties to the number of possible          Theoretically from 0 to 1; actually           0.017 (0.037)
                                                      ties in a school                                                   from nearly 0 to 0.35
       Size of school network                      Number of persons in the school network                            30–2559 students                              671.5 (488.5)
       Mutuality index                             The tendency for ties to be reciprocated relative to               Theoretically from 0 to 1; actually           0.377 (0.052)
                                                      expectations on the basis of chance; higher values                 from 0.23 to 0.53
                                                      indicate more mutuality
    Neighborhood measures (block group level)
       Median home value                           Median value of homes in block group, 1990                         $15 000–$300 000                             95 407 (62 950)
       Racial/ethnic heterogeneity                 Based on a dispersion formula                                      0–1                                           0.340 (0.294)
       Residential stability                       The proportion of residents who moved into their housing unit      Low, medium, high                             1.996 (0.562)
                                                      between 1985 and 1990, categorized into 3 groups, with 1
                                                      standard deviation above and below the mean as the cutoffs
    Demographic characteristics and smoking
     risk variables (individual level)
       Age                                         Age of the respondent at the time of the survey                    10–19 y                                      14.871 (1.729)
       Mother’s education                          Highest level of mother’s educational achievement                  1 = eighth grade or less, 2 = ninth to        5.275 (2.344)
                                                                                                                         12th grade, 3 = high school graduate
                                                                                                                         or GED, 4 = vocational school, 5 = some
                                                                                                                         college, 6 = graduated from college,
                                                                                                                         7 = professional or graduate training

                                                                                                                                                                         Continued

1222 | Framing Health Matters | Peer Reviewed | Lakon et al.                                                       American Journal of Public Health | July 2010, Vol 100, No. 7
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    TABLE 1—Continued

       Parent smoking                                   Number of parents who smoked                                     0 = none, 1 = 1 parent smokes, 2 = both    1.050 (0.781)
                                                                                                                            parents smoke
       Wear seatbelts                                   Frequency of wearing seatbelts when riding in a car              0 = never, 1 = rarely, 2 = sometimes,      3.071 (1.190)
                                                                                                                            3 = most of the time, 4 = always
       Motorcycle riding                                Frequency of riding a motorcycle in the previous 12 months       0 = never, 1 = once or twice, 2 = about    0.363 (0.863)
                                                                                                                            once a month, 3 = about once a
                                                                                                                            week, 4 = almost every day
       Cigarettes in home                               Whether cigarettes are easily available in the home              0 = no, 1 = yes                           30.5
       African American                                 Self-reported race/ethnicity                                     1 = African American, 0 = not             24.6
       Asian                                            Self-reported race/ethnicity                                     1 = Asian, 0 = not                         4.4
       Latino                                           Self-reported race/ethnicity                                     1 = Latino, 0 = not                       13.5
       Other race                                       Self-reported race/ethnicity                                     1 = other race, 0 = not                    3.3
       White (Ref)                                      Self-reported race/ethnicity                                     1 = White, 0 = not                        54.2
       Female                                           Self-reported gender                                             1 = Female, 0 = male                      38.2

    Note. Data are from the public-use version of the National Longitudinal Study of Adolescent Health (n = 6504).

RESULTS                                                               The results for our full simultaneous equa-                with more economic resources had more ties
                                                                   tions model are displayed in Table 2. Given the               outside the school (Table 2 equation 5) and
   The summary statistics for the variables used                   complexity of the results, we will now focus on               higher mean distance to reachable people
in the analyses are shown in Table 1. At wave 1,                   key findings based on our theoretical discus-                 (Table 2 equation 4). Neighborhood economic
70.5% of the entire sample had not smoked,                         sion, beginning with the system component of                  resources had a curvilinear relationship with
whereas this figure was 67% by wave 2. The                         school network measures. School networks                      the density of personal networks and friends’
mean days of smoking per month for the entire                      with greater density and mutuality increased                  smoking behavior: the peak density of personal
sample increased from 4.9 to 5.2 over the 2                        the likelihood that the respondents’ personal                 networks occurred in neighborhoods with
waves. We performed bivariate analyses on                          network would have greater density and reci-                  median home values of approximately
our key outcome measures and found that                            procity (P < .01; Table 2 equations 1 through 3).             $151000, which were somewhat above aver-
Whites smoked significantly more, on average,                      Respondents in school networks with more                      age (value = –[0.106/(–0.035*2)] =1.514).
than did other groups (5.65 days per month),                       density (b = 0.289; P < .01) and mutuality                    By contrast, the number of smokers in adoles-
whereas Blacks and Latinos smoked signifi-                         (b = 0.714; P < .10) had greater in-degree cen-               cents’ networks was lowest in middle-class
cantly less (1.81 and 3.97 days per month,                         trality. Results for equation 6 in Table 2 show               neighborhoods. Residential stability had a di-
respectively; for all P values in this paragraph,                  that adolescents in the largest and smallest                  rect negative effect on in-degree centrality
P < .01). We also found that females smoked                        schools received the fewest nominations.                      (b = –0.081; P < .01) and increased past-month
fewer days per month than did males (4.16                          When we took the first derivative and set it                  smoking (b = 0.120; P < .05; in Table 2
vs 5.39), as did those whose mothers had                           equal to zero, we found that students in                      equation 9).
higher levels of education (3.11). The pattern is                  schools with about 1580 students had the                         Regarding the role that emotional support
similar for friends’ smoking behavior: Whites                      largest in-degree centrality (size = –[0.766/                 plays in the system, results for Table 2 equation
had more friends who smoked (0.87 friends                          (–0.243*2)] =1.576), whereas students in                      8 show that several personal network charac-
who smoked), whereas Blacks (0.53), females                        smaller and larger schools had fewer nomina-                  teristics affect the amount of emotional support.
(0.74), and those with more educated mothers                       tions. Although there was no evidence that                    A 10% increase in in-degree centrality led to
(0.62) had fewer friends who smoked. For                           these school network measures directly af-                    a 0.087 proportionate increase in persons
emotional support, we found that Whites and                        fected adolescents’ past-month smoking (on the                providing emotional support. Likewise, those
females had more (38% and 44% of their                             basis of ancillary models not presented, in                   with more ties outside the school, and those
friends provided emotional support, respec-                        which we added these variables to Table 2                     with reciprocation from the best friend (espe-
tively), whereas Latinos (30%) and Blacks                          equations 9 and 10), adolescents in larger                    cially females), received an increased amount
(31.5%) had less. Finally, Whites had higher in-                   school networks did have fewer friends                        of emotional support. Only personal network
degree centrality (named by 5.95 ties), as did                     who smoked (b = –0.251; P < .01; Table 2                      density showed a negative effect on emotional
females (5.73 vs 5.35 for males), whereas                          equation 7).                                                  support.
Blacks (5.06) and Latinos (4.77) had fewer                            For the structural component of neighbor-                     There is also evidence that adolescents with
social ties.                                                       hood properties, adolescents from block groups                more emotional support engaged in more

July 2010, Vol 100, No. 7 | American Journal of Public Health                                                        Lakon et al. | Peer Reviewed | Framing Health Matters | 1223
TABLE 2—Simultaneous Equations Model Testing Pathways Among Characteristics of Social Networks and Neighborhoods, Emotional Support,
                                                                Peer Influence, and Smoking: National Longitudinal Study of Adolescent Health, 1994–1996

                                                                                                                               Equation 2:         Equation 3:
                                                                                                           Equation 1:        Best Female           Best Male          Equation 4:         Equation 5:         Equation 6:         Equation 7:          Equation 8:           Equation 9:         Equation 10:
                                                                                                            Personal             Friend               Friend           Distance to         Ties Outside         In-Degree            Friends’            Emotional            Past-Month           Past-Month
                                                                                                             Network          Reciprocates,       Reciprocates,         Reachable          the School,          Centrality,         Smoking               Support,             Smoking,             Smoking,
                                                                                                          Density, b (SE)        b (SE)              b (SE)           Others, b (SE)          b (SE)              b (SE)         Behavior, b (SE)    Proportion, b (SE)     Time 1, b (SE)       Time 2, b (SE)

                                                                Past-month smoking                        0.005 (0.005)      0.002 (0.007)       0.007 (0.008)       0.034 (0.021)        0.009 (0.021)       0.023*** (0.007)   0.085 (NA)                                                      0.553*** (0.018)
                                                                Emotional support (proportion)                                                                                                                                                                              0.381** (0.155)      0.660*** (0.169)
                                                                Friends’ smoking behavior                –0.047 (0.039)      0.012 (0.052)       –0.106** (0.054)    –0.169 (0.158)       0.139 (0.171)      –0.153*** (0.057)                                              0.765*** (0.050)     0.323*** (0.045)
                                                                Personal network measures
                                                                     In-degree centrality                                                                                                                                         0.233** (0.118)      0.087*** (0.010)
                                                                     Ties outside the school                                                                                                                                     –0.019 (0.035)        0.032*** (0.003)
                                                                     Mean distance to reachable people                                                                                                                            0.046 (0.066)        0.001 (0.004)
                                                                     Best male friend reciprocates                                                                                                                                0.188 (0.225)        0.022 (0.015)
                                                                     Best female friend reciprocates                                                                                                                             –0.324 (0.232)        0.050*** (0.018)

1224 | Framing Health Matters | Peer Reviewed | Lakon et al.
                                                                     Personal network density                                                                                                                                     0.083 (0.199)       –0.052*** (0.015)
                                                                School network measures
                                                                     School network density               0.117*** (0.025)   0.058*** (0.022)    0.051** (0.023)     –0.899*** (0.153)    0.019 (0.161)       0.289*** (0.064)   –0.137* (0.080)      –0.009 (0.015)
                                                                     Size of school network               0.024 (0.036)      0.040 (0.038)       0.035 (0.038)       0.138 (0.184)        0.096 (0.247)       0.766*** (0.208)   –0.251*** (0.071)     0.019 (0.018)
                                                                     Size of school network squared                                                                                                          –0.243*** (0.063)
                                                                     Mutuality index                      0.467* (0.244)     0.582** (0.238)     0.947*** (0.232)    0.365 (1.682)        1.542 (1.437)       0.714** (0.354)     0.164 (0.511)        0.229* (0.123)
                                                                Neighborhood (block group) measures
                                                                     Median home value                    0.106*** (0.031)   0.029 (0.026)       0.015 (0.025)       0.399*** (0.132)     0.217** (0.102)    –0.005 (0.036)      –0.125** (0.055)     –0.010 (0.011)       –0.002 (0.125)       –0.009 (0.096)
                                                                     Median home value squared           –0.035* (0.019)                                                                                                          0.080*** (0.028)
                                                                     Racial/ethnic heterogeneity          0.063** (0.031)    0.077** (0.036)     –0.035 (0.051)      0.138 (0.137)       –0.098 (0.207)      –0.008 (0.057)       0.014 (0.060)        0.040** (0.020)      0.099 (0.126)       –0.208 (0.165)
                                                                     Residential stability                0.001 (0.016)      –0.032* (0.018)     –0.002 (0.021)      –0.069 (0.060)       0.016 (0.067)      –0.080*** (0.023)    0.019 (0.025)       –0.008 (0.011)        0.120** (0.055)     –0.111* (0.061)
                                                                                                                                                                                                                                                                                                                    FRAMING HEALTH MATTERS

                                                                Demographic characteristics
                                                                     African American                    –0.060** (0.024)    –0.115*** (0.034)   –0.091** (0.036)    0.023 (0.108)        0.489*** (0.153)   –0.110*** (0.038)   –0.218*** (0.056)    –0.062*** (0.013)    –0.967*** (0.115)    –0.790*** (0.119)
                                                                     Asian                                0.000 (0.033)      0.028 (0.049)       –0.004 (0.054)      0.327* (0.174)      –0.132 (0.226)      –0.094 (0.064)      –0.044 (0.067)       –0.036 (0.026)       –0.438** (0.198)     –0.184 (0.242)
                                                                     Latino                               0.031 (0.032)      –0.074** (0.036)    –0.075* (0.044)     0.088 (0.082)       –0.026 (0.126)      –0.104** (0.042)    –0.036 (0.058)       –0.052*** (0.013)    –0.460** (0.190)     –0.305 (0.203)
                                                                     Other race                          –0.035 (0.030)      –0.070* (0.038)     –0.063 (0.040)      0.039 (0.063)        0.188 (0.123)      –0.101*** (0.036)    0.031 (0.053)        0.008 (0.013)        0.072 (0.134)       –0.362*** (0.138)
                                                                     Age                                  0.026*** (0.006)   0.025*** (0.007)    0.029*** (0.008)    0.056*** (0.021)     0.098*** (0.032)    0.001 (0.010)       0.087*** (0.013)     0.023*** (0.003)     0.213*** (0.029)     0.019 (0.029)
                                                                     Female                               0.048*** (0.015)   0.315*** (0.020)    –0.156*** (0.021)   –0.013 (0.078)       0.495*** (0.068)    0.111*** (0.025)    0.068 (0.082)        0.164*** (0.011)    –0.131 (0.090)       –0.058 (0.076)
                                                                     Mother’s education                                                                                                                                          –0.028*** (0.007)                         –0.027 (0.019)       –0.029 (0.021)
                                                                     Parent smoking                                                                                                                                               0.101*** (0.015)                          0.270*** (0.041)     0.209*** (0.043)
                                                                     Wear seatbelts                                                                                                                                              –0.092*** (0.013)                         –0.259*** (0.037)    –0.091** (0.037)
                                                                     Motorcycle riding                                                                                                                                            0.094*** (0.012)                          0.323*** (0.050)     0.062 (0.041)
                                                                     Cigarettes in home                                                                                                                                           0.207*** (0.037)                          0.729*** (0.096)    –0.032 (0.101)
                                                                R2                                             0.050               0.134               0.033               0.324               0.035               0.048               0.254                0.338                0.437                0.313

                                                                Note. Selection effect of friends’ smoking on individual smoking is fixed at same size as influence effect on individual smoking. Models were estimated using maximum likelihood estimation, with standard errors corrected for clustering within
                                                                schools. c258 = 79.6; P = .03. Data are from the public-use version of the National Longitudinal Study of Adolescent Health (n = 6504).
                                                                *P < .05 (1-tail test); **P < .05 (2-tail test); ***P < .01 (2-tail test).

American Journal of Public Health | July 2010, Vol 100, No. 7
FRAMING HEALTH MATTERS

past-month smoking. This effect was positive           selection. For example, the effect of adolescent      influence from friends’ smoking behavior was
(0.381) in the equation predicting past-month          past-month smoking on in-degree centrality            not affected by personal or school-level net-
smoking at the same time point (Table 2                was 0.014 if we assumed no selection effect,          work characteristics, it did affect past-month
equation 9), and in Table 2 equation 10 for            0.018 if 25% of the relationship was attribut-        smoking. Findings pertaining to the school
past-month smoking at the next time point              able to selection, 0.023 if 50% was attributable      component indicate that school-level density
(0.66), even after control for past-month              to selection, and 0.030 if 75% was attributable       and size affected personal network character-
smoking at the previous time point. This im-           to selection (for all effects, P < .05). Likewise,    istics, density, reciprocation of ties from best
plies that emotional support plays a long-term         the effect of friends’ smoking behavior on in-        female friend, mean distance to reachable
role in mediating the relationship between the         degree centrality ranged from –0.128 to               people, in-degree centrality, and number of
various personal network measures and                  –0.171 (for all effects, P < .05). The other          nominations outside of respondents’ schools.
smoking the following year. For example, those         parameters in the model showed even more              Findings related to the neighborhood compo-
with more social ties inside and outside the           stability over these various parameterizations,       nent of the system indicate that median home
school, and those with reciprocated ties with          indicating that our results are robust regardless     value negatively affected past-month smoking
their best friend, had more emotional support,         of the portion of the relationship that was           at time 1. Neighborhood characteristics also
which led to more smoking 1 year later.                attributable to selection and the portion at-         affected network characteristics, including
   There is little evidence that friends’ smoking      tributable to influence.                              density, reciprocation, and ties outside the
behavior mediated the relationship between                We also assessed whether emotional support         school. Findings indicate a feedback loop from
personal network measures and past-month               and friends’ smoking worked multiplicatively at       personal network characteristics, to emotional
smoking. On the one hand, friends’ smoking             the level of social ties. We tested this by           support, to past-month smoking, and then
behavior increased past-month smoking (Table           constructing a measure that multiplied the            back to personal network characteristics, in-
2 equation 9) and past-month smoking at the            emotional support score and the smoking               cluding the provocative finding that past-month
next wave, after control for time 1 smoking            behavior for each of an individual’s friendship       smoking affected in-degree centrality.
(Table 2 equation 10). Each additional friend          ties and then computing the average of these              Our finding that personal network charac-
who smoked increased the number of days                values among the ties of an individual. In            teristics increased emotional support, which
smoked per month by 77%. On the other hand,            ancillary models including personal and school        then increased past-month smoking, supports
there is evidence in Table 2 equation 7 that           network measures and demographics, we                 previous research identifying emotional sup-
those who were more popular (i.e., those with          tested the effect of this variable on past-month      port as a mechanism through which networks
high in-degree centrality) had more friends            smoking behavior at time 1 and time 2 and             relate to health and to risk behavior.29,34 These
who smoked. The other network measures had             found no significant effects (results not pre-        findings were not surprising because being
no effect on friends’ smoking behavior.                sented; available upon request). Finally, we          central in a network likely affords opportunities
   Although there is little evidence that these        estimated a school-level fixed-effects model to       for giving and receiving emotional support.
personal network measures increased friends’           control for unobserved differences across             Second, having friendships outside of school may
smoking behavior, there is evidence in Table 2         schools, and the substantive results were very        increase the number of friends an adolescent
equation 6 that the popularity of adolescents          similar to those presented in the text (results       has, thus increasing the probability of receiving
(in-degree centrality) was affected both by their      available upon request).                              support from any one friend, and may also
own past-month smoking and by their friends’                                                                 suggest that friends outside of school are close
smoking behavior. A 1% increase in past-               DISCUSSION                                            friends who provide emotional support. Third,
month smoking increased in-degree centrality                                                                 having a female friend reciprocate friendship
by 2.3% (b = 0.023: P < .01). However, there              Our findings indicate that when a system of        may increase the emotional support exchanged
was a countervailing effect if one had friends         pathways between characteristics of personal          in a mutually reciprocated friendship tie, given
who smoked: each additional friend who                 networks, school networks, and neighborhoods          that females may often be viewed as sources of
smoked reduced in-degree centrality by 15.3%           is taken into account, together with its constit-     emotional support. Last, the negative effect of
(b = –0.153; P < .01). There is little evidence        uent flows of emotional support and the influ-        density on emotional support may be explained
that past-month smoking or friends’ smoking            ence exerted through friends’ smoking behavior,       by the numerous relationship obligations and
behavior affected the other personal network           important insights into the complexity of the         constraints that densely connected ties can im-
measures (Table 2 equations 1 through 5).              social context of adolescent smoking can be           pose, constituting a great demand on one’s
   We performed sensitivity tests of our model.        gained. Personal network characteristics—being        personal resources. Moreover, if density of ties
As described already, we set the parameter for         central in a network, having ties outside the         limits the resources entering from outside the
the effect of adolescents’ past-month smoking          school, having a best female friend reciprocate       network, this can further limit the amount and
on friends’ smoking behavior to various values         friendship, and the density of ties—influenced        diversity of personal resources to expend as
and assessed the robustness of the system. In          the flow of emotional support, which in turn          emotional support to others.
short, the system appeared to be relatively            influenced past-month smoking at both time                It is notable that the only school-level char-
robust, regardless of the ratio of influence to        points. We found that although the flow of            acteristic to increase emotional support was the

July 2010, Vol 100, No. 7 | American Journal of Public Health                                      Lakon et al. | Peer Reviewed | Framing Health Matters | 1225
FRAMING HEALTH MATTERS

mutuality index. Perhaps a whole network              in-degree centrality and best male friend recip-       they smoked, but did not hang out with fellow
structure with a large proportion of mutually         rocation suggest that having friends who smoke         smokers—were the most popular, based on in-
reciprocated ties increases the possibility that      actually decreases popularity and the reciproca-       degree centrality. Alternatively, smokers who
emotional support will be exchanged in any            tion of friendship ties. Overall, such findings        affiliated with friends who smoked were gener-
one of these close ties. We observed that             suggest that having friends who smoke was not          ally no more popular than average adolescents.
neither school-level density nor size had an          well received among the greater social milieu of          Our findings suggest the need to examine
effect on the flow of emotional support; the          youths in our study.                                   how the pathways represented in the systems
former finding is consistent with the idea that           Our findings suggest evidence of a feedback        model under study might differ across gender
density may limit support in a network. The           loop: personal network characteristics in-             and racial/ethnic groups, given the possible
latter finding may indicate that larger schools       creased the emotional support received by              group differences. Also, future studies should
promote anonymity and consequently fewer              adolescents, which then appears to have led to         examine how other types of social support,
support resources, leading to more diffuse            more smoking at both waves. In addition,               such as confidant support, might function in
networks and fewer close and supportive ties.         adolescent smoking at time 1 flowed back in the        lieu of emotional support in our study model.
   Our finding that emotional support influ-          other direction through the system by bringing         Confidant support has been associated with
ences past-month smoking at both time points          about more friends who smoked (through                 positive health outcomes50,51and is relevant
is consistent with previous work showing that         a selection effect) and then leading to greater        given the notable effects of reciprocated ties and
emotional support positively relates to smok-         in-degree centrality. This greater in-degree           emotional support, both likely characteristics of
ing.33 Perhaps the effect between emotional           centrality and greater distance to reachable           a confidant relationship, on adolescent smoking
support and smoking is more likely to occur           people then led to more emotional support, and         in this study.
between close friends in emotionally supportive       thus the loop begins again. Our findings are
relationships. The persistence of this relation-      indicative of a feedback process that encom-           Limitations
ship at the second time point may indicate its        passes the amplifying effects of personal net-            Our study has some limitations. First, the
strength and stability over time.                     work characteristics on emotional support, the         network elicitation items were limited in the
   Although we found modest effects for our           reinforcing effect of emotional support on             number of friendship nominations. Capping
neighborhood component, findings of note              smoking, and the effect of smoking on popu-            friendship nominations is a common strategy,
were the curvilinear relationships that neigh-        larity and distance to reachable others. Such          though it is a potential drawback among studies
borhood economic resources had with the               a ‘‘reinforcing’’ loop might suggest that smoking      utilizing network generator items. It remains
density of personal networks and with friends’        brings social gains in the way of emotional            unclear how social position and network
smoking behavior. Adolescents living in mid-          support and popularity in the social system            structure would differ if the number of nomi-
dle-income neighborhoods had networks with            under study.                                           nations were not capped at this level. Second,
the highest density, suggesting a relative co-            Our findings also have implications for ex-        network data were not collected for the full
hesion among their personal ties. At the same         tant and future studies that employ the general        national sample at wave 2; therefore, we could
time, adolescents in middle-income neighbor-          strategy of examining relationships between            not account for network variables at time 2
hoods had the fewest smokers in their net-            network characteristics and smoking among              in our models. It is unclear how the inclusion of
works, suggesting a relatively low effect from        youths. Previous research found a positive             these variables might have changed our results.
influence of friends’ smoking behavior. It is         association between the popularity of students         Future studies should include network vari-
notable that adolescents in both low- and high-       (as measured by in-degree centrality) and              ables at multiple time points, to permit obser-
income neighborhoods had networks with                adolescent smoking, and it has been assumed            vation of the evolution of the system. Third,
more smokers than adolescents in middle-in-           conceptually that the direction proceeded from         because we conducted a secondary analysis, we
come neighborhoods.                                   popularity to smoking,12 but we have specified         were restricted in the types of network vari-
   Friends’ smoking behavior was not affected         a system that allows this directionality to proceed    ables, social processes, and outcomes available
by any of the network characteristics under           in either direction. As a consequence, we were         for study. Nevertheless, we investigated theo-
study, but it did increase past-month smoking         able to detect more evidence that smoking              retically informed pathways composing a larger
at the first time point. The lack of any effects of   behavior and peers who smoked affected one’s           system of adolescent smoking. Lastly, what
network characteristics on friends’ smoking           popularity, rather than the reverse. This finding      constitutes a friendship tie is of note here
behavior suggests that although these charac-         has the potential to inform future models used to      because it is unclear whether there was uni-
teristics may be important for promoting              investigate the relationship between in-degree         formity in the strength, duration, and fre-
smoking behavior among youths,11,12 they are          centrality and smoking among youths. More              quency of contact in friendship ties.
not important for the smoking behavior of             broadly, this finding suggests that a social
youths’ friends. This finding runs counter to the     behavior—cigarette smoking—could alter an im-          Implications for Prevention
many studies indicating homogeneity in the            portant positional attribute of a social network. It      In spite of these limitations, our findings
smoking status of friends. The findings that          is notable that the individuals who showed             provide insight into the importance of the
friends’ smoking behavior reduced both                a relatively high degree of autonomy—in that           strength of reciprocated friendships and the

1226 | Framing Health Matters | Peer Reviewed | Lakon et al.                                        American Journal of Public Health | July 2010, Vol 100, No. 7
FRAMING HEALTH MATTERS

emotional support they can transact to help            behavior was not. We found evidence of                           4. Ennett ST, Bauman KE, Hussong A, et al. The peer
                                                                                                                        context of adolescent substance use: findings from
adolescents support each other in remaining            a feedback process, as past-month smoking had
                                                                                                                        social network analysis. J Res Adolesc. 2006;16(2):
nonsmokers or in quitting smoking. These               a direct effect on the popularity of students                    159–186.
friendship pairs could be targeted for a school-       (in-degree centrality). Overall, our findings                    5. Pearson M, West P. Drifting smoke rings: social
based intervention, either to help both adoles-        suggest complexity in the social context of                      network analysis and Markov processes in a longitudinal
                                                                                                                        study of friendship groups and risk-taking. Connections.
cents in a pair remain nonsmokers or so that           adolescent smoking and the need for theory to
                                                                                                                        2003;25:59–76.
they could help each other stop smoking.               account for it. j
                                                                                                                        6. Kirke DM. Chain reactions in adolescents’ cigarette,
This could be done by teaching youths in these                                                                          alcohol and drug use: similarity through peer influence or
pairs how to use emotional support as re-                                                                               the patterning of ties in peer networks? Soc Networks.
inforcement for helping one another remain             About the Authors                                                2004;26(1):3–28.
                                                       Cynthia M. Lakon and David S. Timberlake are with the            7. Flay BR, Hu FB, Siddiqui O, et al. Differential
nonsmokers (among nonsmoking pairs) and for            Department of Population Health and Disease Prevention,          influence of parental smoking and friends’ smoking on
considering quitting (among smoking pairs).            Program in Public Health, University of California, Irvine.      adolescent initiation and escalation and smoking. J Health
Second, adolescents could learn self-regulatory        John R. Hipp is with the Department of Criminology, Law          Soc Behav. 1994;35(3):248–265.
                                                       and Society and the Department of Sociology, University
techniques (e.g., journaling) to help one another      of California, Irvine.
                                                                                                                        8. Hoffman BR, Monge PR, Chou CP, Valente TW.
                                                                                                                        Perceived peer influence and peer selection on adoles-
identify cues in the social environment that              Correspondence should be sent to Cynthia Lakon, De-
                                                                                                                        cent smoking. Addict Behav. 2007;32(8):1546–1554.
elicit interest in smoking or smoking associa-         partment of Population Health and Disease Prevention,
                                                       Program in Public Health, University of California, Irvine,      9. Abel G, Plumridge L, Graham P. Peers, networks or
tions. All participating adolescent pairs could        101 Theory Drive, Suite 250, Irvine, CA 92697-3957               relationships: strategies for understanding social dynam-
form task forces in schools and lead smoking           (e-mail: clakon@uci.edu). Reprints can be ordered at             ics as determinants of smoking behaviour. Drugs Educ
                                                       http://www.ajph.org by clicking the ‘‘Reprints/Eprints’’ link.   Prev Policy. 2002;9(4):325–338.
awareness campaigns. Reciprocated relation-
                                                          This article was accepted November 30, 2009.                  10. Fang X, Li X, Stanton B, Dong Q. Social network
ship pairs would become a channel through
                                                                                                                        positions and smoking: experimentation among Chinese
which antismoking messages permeate per-                                                                                adolescents. Am J Health Behav. 2003;27(3):257–267.
                                                       Contributors
sonal and school networks.                             C. M. Lakon conceptualized the study, interpreted the            11. Alexander C, Piazza M, Mekos D, Valente T. Peers,
   Findings suggest the need to target adoles-         findings, and led the writing of the article. J. R. Hipp         schools, and adolescent cigarette smoking. J Adolesc
                                                       conducted the statistical analyses, wrote the Methods            Health. 2001;29(1):22–30.
cents who smoke, have nonsmoking friends,
                                                       section, and reviewed drafts of the article. D. S. Timber-       12. Valente TW, Unger JB, Johnson CA. Do popular
and are not yet popular. Research suggests that        lake assisted with modeling tobacco use outcomes.                students smoke? The association between popularity and
popular youths can set norms in a school                                                                                smoking among middle school students. J Adolesc Health.
context.12 A corollary is that if popular youths       Acknowledgments                                                  2005;37(4):323–329.
smoke, others will emulate them. Building on           This research uses data from Add Health, a program               13. Bronfenbrenner U. Toward an experimental ecology
previous research12 suggesting that popular            project directed by Kathleen Mullan Harris and designed          of human development. Am Psychol. 1977;32(7):513–
                                                       by J. Richard Udry, Peter S. Bearman, and Kathleen               531.
youths will need to adopt antismoking norms in         Mullan Harris at the University of North Carolina at             14. Midgley G. Systems Thinking. Vol 1–4. Thousand
order for programs to become effective, we             Chapel Hill and funded by grant P01-HD31921 from the             Oaks, CA: Sage; 2003.
suggest that interventions should target youths        Eunice Kennedy Shriver National Institute of Child
                                                                                                                        15. Leischow SJ, Milstein B. Systems thinking and
                                                       Health and Human Development, with cooperative
who smoke before they become popular. Perhaps          funding from 23 other federal agencies and foundations.
                                                                                                                        modeling for public health practice. Am J Public Health.
these youths are not yet frequent smokers,                                                                              2006;96(3):403–405.
                                                       Special acknowledgment is due Ronald R. Rindfuss and
given that they affiliate with nonsmoking friends,     Barbara Entwisle for assistance in the original design of        16. Wasserman S, Faust K. Social Network Analysis:
                                                       the Add Health Study. Information on how to obtain the           Methods and Applications. New York, NY: Cambridge
and thus may be tolerant of antismoking norms.         Add Health data files is available on the Add Health Web         University Press; 1994.
Such adolescents could be educated about the           site (http://www.cpc.unc.edu/addhealth). No direct sup-          17. Ennett ST, Faris R, Hipp JR, et al. Peer smoking,
risks of smoking with the hope that they would         port was received from grant P01-HD31921 for this                other peer attributes, and adolescent cigarette smoking:
                                                       analysis.                                                        a social network analysis. Prev Sci. 2008;9(2):88–98.
adopt antismoking norms, which their non-
smoking friends might reinforce. This interven-                                                                         18. Moody J. The importance of relationship timing for
                                                       Human Participant Protection                                     diffusion. Soc Forces. 2002;81(1):25–56.
tion would be disseminated through adolescents’        No protocol approval was necessary because data were             19. Shaw C, McKay HD. Juvenile Delinquency and Urban
personal networks and would have the potential         obtained from publicly available secondary sources.              Areas. Chicago, IL: University of Chicago Press; 1942.
to solidify antismoking norms over time, as                                                                             20. Sampson RJ, Groves WB. Community structure and
these messages spread from personal to school          References                                                       crime: testing social-disorganization theory. Am J Sociol.
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July 2010, Vol 100, No. 7 | American Journal of Public Health                                                Lakon et al. | Peer Reviewed | Framing Health Matters | 1227
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