Social Network Characteristics and Substance Use:

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Social Network Characteristics and Substance Use

• Findings from a Longitudinal Study of Adolescent
  Health Risk Behaviors

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Susan T. Ennett,1 Karl E. Bauman,1 Andrea
Hussong,2 Robert Faris,3 Vangie A. Foshee,1
Patrick Curran,2 Rob DuRant4

• 1Department of Health Behavior and Health
  Education
• 2Department of Psychology
• 3Department of Sociology
• The University of North Carolina at Chapel Hill
• 4Departments of Pediatrics and Public Health
  Sciences
• Wake Forest University

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Background Adolescent Friendships and Substance
Use
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Hypothesis 1

• Adolescents with a) more peer network prominence,
  b) stronger peer network integration, and c)
  further distance to substance users will be less
  likely to have used substances recently than
  adolescents with less peer network prominence,
  weaker peer network integration, and closer
  distance to substance users
• Substances cigarettes, alcohol, or marijuana

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Hypothesis 2

• Adolescents with a) more peer network prominence,
  b) stronger peer network integration, and c)
  further distance to substance users will increase
  recent substance use less with time than
  adolescents with less prominence, weaker
  integration, and closer proximity to substance
  users
• Substances cigarettes, alcohol, or marijuana

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Data

• The Public School Systems in 3 Central North
  Carolina Counties (Vance, Person, Moore)
• Wave 1 6th, 7th, and 8th Graders, Spring 2002
• Surveyed again every 6 months until Spring 2004
  when in grades 8 - 10 (total of 5 waves)
• Present analyses 1st 3 waves

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Data (cont.)

• Eligible N (Wave 1) 5906
• Wave 1 88.4 (N 5220) completed 1 hour
  questionnaires, most in classrooms
• _______________________________
• Ineligible exceptional children in
  self-contained classrooms and students without
  English proficiency

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Data (cont.)

• Sample in present analyses Age 11 through 15
  and followed through Wave 3 (84 of eligible,
  N4961, Observations12,135)
• Dropped 259 Wave 1 respondents
• Alternative school students (N65)
• Outside age range (N24)
• Missing information (N170)

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Data for Network Measures

• Write first names of up to 5 closest friends,
  starting with best friend
• Assign unique number to each friend from school
  directory
• Not in directory assign 0000

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Network Boundaries

• School and Grade (N26)

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Recent cigarette use in a 6th grade network
(bluenonuser, yellowuser, graymissing info)
12
Recent alcohol use in a 6th grade network
(bluenonuser, yellowuser, graymissing info)
13
Recent marijuana use in a 6th grade network
(bluenonuser, yellowuser, graymissing info)
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Prominence in Network

• 1. Normed indegree No. of nominations received
  by ego divided by no. of possible nominations
  (UCINET)
• 2. Betweeness centrality Extent to which ego
  links unlinked pairs of friends (UCINET)

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Network Integration

• 3. Social position group member, bridge, or
  isolate (SAS IML, James Moody)
• 4. Density of network neighborhood No. of
  friendship ties among alters divided by total
  number of possible ties (UCINET)
• 5. Number of out-of-network (grade) nominations
  (UCINET)

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Proximity to User

• 6. Number of users in adolescents neighborhood,
  excluding ego (UCINET)
• 7.Number of links to nearest substance user
  (UCINET)

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Also measured

• Recent (within 3 months) cigarette, alcohol, and
  marijuana use. Binary.
• Demographics grade in school, sex,
  race/ethnicity (white vs. other), family
  structure (2 parent vs. other)

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Sample Characteristics

• Grade in school
• 6.5 35.6
• 7.5 33.3
• 8.5 31.1
• Sex 50.8 female
• Race/ethnicity 52.5 white
• 2 parent families 67.8

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Analysis Strategy

• Cohort sequential design
• 12,135 observations (4961 respondents,
• 3 waves)
• Age rather than wave of data collection
• to indicate time

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Recent substance use ( )(Observations)
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Analysis Strategy (cont.)

• 3-level (time, school, individual) Hierarchical
  Generalized Linear Models
• Nested repeated measures within adolescents
• and adolescents within schools
• Separate for each network variable and substance
• Always control for demographic variable when
  significantly related to substance use

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Slopes
Intercepts
Age
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Hypothesis 1

• Adolescents with a) more peer network prominence,
  b) stronger peer network integration, and c)
  further distance to substance users will be less
  likely to have used substances recently than
  adolescents with less peer network prominence,
  weaker peer network integration, and closer
  distance to substance users
• Substances cigarettes, alcohol, or marijuana

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Tests of Hypothesis 1

• Intercept (age 11) association between network
  variable and age 11 substance use

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Hypothesis 1 Findings Social network variables
by substance use Beta(SE)

• Cigarettes Alcohol Marijuana
• Prominence
• Normed 3.94 9.030 6.07
• indegree (1.27) (3.43)
  (5.16)
• Betweeness .01 .020 .03
• centrality (.02) (.01)
  (.02)
• plt.05, plt.01, 0opposite to hypothesized
  direction

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Hypothesis 1 Findings (cont.)

• Cigarettes Alcohol Marijuana
• Integration
• Social Position
• Isol. vs. Gp. 1.99 2.57
  1.44
• (1.01) (.92) (1.34)
• Brid. vs. Gp. .40 -.12
  .65
• (.34) (.30) (.46)
• Density -1.28 -1.77 -2.37
• (1.06) (.95) (1.53)
• Out-of-network .29 .30
  -.14
• nominations (.14) (.13) (.19)
• plt.05, plt.01

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Hypothesis 1 Findings (cont.)

• Cigarettes Alcohol Marijuana
• Proximity
• No. of friend .93 .29 1.29
• users (.17) (.15) (.23)
• Distance to -.63 -.23
  -1.19
• nearest user (.27) (.20) (.32)
• plt.001

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Hypothesis 2

• Adolescents with a) more peer network prominence,
  b) stronger peer network integration, and c)
  further distance to substance users will increase
  recent substance use less with time than
  adolescents with less prominence, weaker
  integration, and closer proximity to substance
  users
• Substances cigarettes, alcohol, or marijuana

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Tests of Hypothesis 2

• Hypothesis 2 Network variables predict
  different slopes of substance use
• Social network variable by substance use by time

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Hypothesis 2 Findings

• 24 interactions tested, 2 significantly different
  slopes
• Position (isolate vs. group member) and
  alcohol use
• Beta - 1.25, SE.40, plt.001 (opposite to
• hypothesized direction)
• Number of marijuana using friends and
  marijuana use
• Beta -0.18, plt.05)

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Conclusions

• Integration (social position and out-of-network
  nominations) and proximity (number of users and
  distance to users) are implicated in substance
  use.
• Prominence (normed indegree and betweeness
  centrality) are less implicated in substance use.
• Intercept and slope findings can yield
  substantially different impressions

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Conclusions (cont.)

• Three statistically significant findings opposite
  to hypothesized direction
• Findings vary by substance No hypothesis
  accepted for all substances
• No corrections for multiple statistical tests
• Findings could change as the cohort ages
• Findings could differ for other network measures,
  later-measured network measures, and for other
  substances

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End
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Network variables(Prominence)

• Variable Mean SD Min Max
• 1.Normed
• indegree .06 .04 0 .29
• 2.Betweeness 9.96 11.95 0 140.07
• centrality

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Network variables(Integration)

• Variable
• 3.Social position 53 Gp, 44 Brid, 3 Isol
  (N4961)
• Mean SD Min Max
• 4. Density .18 .17 0 1.00
• 5. Out-of-network
• nominations .80 1.16 0 5

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Network variables(Proximity to user)

• Variable Mean SD Min Max
• 6.No. users
• Cigarette .75 1.03 0 7
• Alcohol .83 1.02 0 7
• Marijuana .67 1.02 0 8
• 7. Distance
• Cigarette 1.71 .82 1 5
• Alcohol 1.63 .80 1 5
• Marijuana 1.84 .91 1 6

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Recent substance use by age ( )

• Age Cigarette Alcohol Marijuana N (Obs)
• 11 6 7 2 808
• 12 11 11 5 3306
• 13 17 18 11 3947
• 14 23 27 18 3116
• 15 29 31 23 958

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Correlations between Network Variables

• Prominence
• Normed Indegree
• x Betweeness Centrality .51
• Integration
• Social Position x Density .36
• Social Position x No.
• Out-of network Nominations .13
• Density x No. out of network
• Nominations -.32

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Correlations between Network Variables (cont.)

• Proximity
• No. Users x Distance
• Cigarettes -.64
• Alcohol -.64
• Marijuana -.61

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Analysis Strategy (cont.)

• Age No. of Observations
• 11 808
• 12 3306
• 13 3947
• 14 3116
• 15 958
• Total 12135