slides - Curry School of Education

advertisement

Adolescent Social

Networks, Physical

Activity and Other Health

Behaviors

John R Sirard

10.20.2011

Overview

1. Background

2. Social factors related to physical activity (PA)

3. Social Networks, PA and Screen Time (crosssectional results)

4. Future Directions (Social Network Analysis and

Health – NIH FOA)

1. Background

Physical Activity: Any bodily movement

produced by the contraction of skeletal muscle that increases energy expenditure above a basal level.

Not just sports and planned exercise

A behavior (not fitness or other physiological outcomes)

20

15

10

5

0

% meeting PA recommendation: > 60 min of moderatevigorous physical activity per day

30

25

Males

Females

9th 10th

Grade

11th 12th

PA Prevalence - A New Challenge

( Troiano et al. 2008 )

2009 YRBSS : 18.4% (Males: 24.8%; Females: 11.4%)

Measured by accelerometer…

% meeting PA recommendation: > 60 min of moderatevigorous physical activity per day

PA and Health in Youth

Lipid profile

Blood Pressure

Overweight and obesity

Metabolic Syndrome

CVD risk factors

Bone health

Depression, anxiety, mood, self-esteem

QOL and fatigue of cancer survivors

PA and Other Health Behaviors

Trost SG. Physical Education,

Physical Activity and

Academic Performance. Fall

2007 Research Brief. Active

Living Research (RWJF)

“Students whose time in PE or school-based physical activity was increased maintained or improved their grades and scores on standardized achievement tests, even though they received less classroom instructional time than students in control groups”.

2. Social Factors Related to PA

Attributes of Self

Genetics.

Self Efficacy impacts motivation and attempts to alter, modify, and maintain health behaviors.

Diet

Unhealthy dietary behaviors; low intake of fruits and vegetables

Physical

Activity

Lack of PA and excess sedentary activities

Inter-personal

Core

Relationships

Family, peers, authority figures offering different types of support for healthy behaviors

Policy

Behavior settings

Intra-personal &

Behaviors

Technology

Labor saving devices, automobiles, communication technology

Systemic & Policy Factors

Unhealthy foods easily accessible, heavily marketed to children

Healthy foods are more costly and difficult to obtain.

Urban sprawl, lack of pedestrian infrastructure

Environment

Extreme climates, walking or biking trails, public gyms and pools, public transportation,

School/work environments

Cultural, Religious & Family Values

Reasons for eating; the quantity, quality, and types of foods eaten; gender roles

Social Factors and PA

Social Support for Physical Activity

Emotional Support (encourages you to do physical activity)

Informational Support

Tangible Support (do physical activities with you, pay for equipment / fees)

Perceived support for PA from family and friends positively associated with adolescent PA

– typically

Social Networks

Social Networks and Obesity

Christakis and Fowler

(NEJM 2007)

Framingham Cohort Study with 30 years of followup

“…obesity appears to spread through social ties”.

National Longitudinal Study of Adolescent Health

Strauss 2003, Trogdon 2008

Challenges to analysis and interpretation

(Lyons

2011)

3. Social Networks, PA and Screen

Time (cross-sectional results)

Project EAT 2010

Eating and Activity among Teens

New cohort of 2,793 middle and high school students from 20 Mpls/St. Paul middle schools and high schools (2009-2010)

Weight-related behaviors (PA, screen time, diet, weight control practices, disordered eating) and

Related multi-level correlates (individual, peer, family, school, neighborhood)

Main “outcome”: weight status

Social Networks and PA in Project EAT 2010

Purpose: To examine how friends’ PA and screen time is related to an individual adolescent’s PA and screen time by using data from nominated friends

Best

Male friend

Male friend 2

Male friend 3

Hyp: Associations between ego and friend PA and screen time would be strongest between same gender and weakest for opposite gender associations.

Best

Female friend

Female friend 2

Hyp: Associations between ego and friend behaviors would be stronger for high school versus middle school students.

Female friend 3

Example of network connections at one middle school. Triangles indicate Girls, Circles indicate Boys, the numbers in the symbol represent the grade level.

How many friends are enough?

Sensitivity Analyses

1. Data from all 6 nominated friends (n=251)

From smaller, lower income, more ethnically diverse schools – not representative of larger Project EAT sample

2. Data from all but one nominated friend (n=585)

Also not representative of larger sample

3. Data from at least 1/3 of nominated friends

(n=1655)

4. Data from at least one nominated friend (n=2126)

Table 1: Sample characteristics for n= 2126 Egos with any friends in dataset.

Values are mean+SD or n (percent)

Males (n=983)

14.29

±2.01

Females (n=1143) p-value

14.11

±1.88

0.03

Age

(years)

Grade

Middle School (n=1114)

High School (n=1012)

Ethnicity group

White (n=426)

African American/Black (n=567)

Latino/Hispanic (n=373)

Asian American (n=409)

Native American (n=87)

Mixed/Other (n=264)

Socioeconomic Status

Missing (n= 64)

Low (n=611)

Low-middle(n=526)

Middle(n=717)

Upper-Middle + High (n=208)

504 (51.3)

479 (48.7)

224 (

22.8

260 (26.5)

164 (16.7)

195 (19.8)

40 (4.1)

100 (

10.2

31 (3.2)

286 (29.1)

249 (25.3)

320 (32.6)

97 (9.8)

)

)

610 (53.4)

533 (46.6)

202 (

164 (

17.7

307 (26.9)

209 (18.3)

214 (18.7)

47 (4.1)

14.4

33 (2.9)

325 (28.4)

277 (24.2)

397 (34.7)

111 (9.7)

)

)

0.34

0.01

0.61

Table 1 (cont’d): Sample characteristics for n= 2126 Egos with any friends in dataset. Values are mean+SD or n (percent)

Males (n=983) Females (n=1143) p-values

Weight Status *

Not overweight (n=1272)

Overweight (n=854)

Physical Activity

(hrs/wk)

Screen Time

(hrs/wk)

566 (57.6)

417 (42.4)

6.83

45.15

±4.84

±28.85

706 (61.8)

437 (38.2)

4.98

36.51

±4.40

±23.92

0.67

<.001

<.001

Number of friends

Number of Male friends

2.64+

1.49+ sd sd

2.62+

1.01+ sd sd

0.XX

0.XX

Number of Female friends

Overweight status is defined as > 85 th

1.15+ sd 1.61+ sd 0.XX

percentile on the Centers for Disease Control and

Prevention’s age and gender specific Body Mass Index curves

BMI = kg / m 2

Table 2. Estimated change in male’s physical activity or screen time for every 1 hour increase in friends’ mean (or best friend’s) physical activity or screen time

Male Ego

Physical Activity

p-value

Male

Friends

Female

Friends

Male Best

Friend

Female Best

Friend

n=838 n=668 n=483 n=389

0.059 (.037) 0.114 (.042)

0.111

0.007 *

?

0.061 (.042) 0.034 (.045)

0.149

0.448

Screen Time

0.024 (.042) 0.111 (.054) -0.025 (.043) 0.110 (.072) p-value 0.559

0.038

0.558

0.129

Adjusted for Ego’s age, SES, race/ethnicity, BMI, and number of friends available

* Significant interaction with school level (middle vs. high school)

Table 3. Estimated change in female’s physical activity or screen time for every 1 hour increase in friends’ mean (or best friend’s) physical activity or screen time

Female Ego

Physical Activity

p-value

Male

Friends

n=723

Female

Friends

n=1007

0.122 (.025) .182 (.0439)

<.0001

<.0001

Male Best

Friend

n=404

.086 (.026)

0.0009

Female Best

Friend

n=612

.128 (.052)

0.0142 *

Screen Time .097 (.039) .091 (.043)

-.010 (.032) .022 (.056) p-value

0.012

0.032

0.75

0.696

Adjusted for Ego’s age, SES, race/ethnicity, BMI, and number of friends available

* Significant interaction with school level (middle vs. high school)

Strengths and Limitations

Strengths

Large, diverse sample

Novel method and analyses

Limitations

Cross-sectional

Incomplete network data

Conclusions

Several associations between adolescent and friend PA and screen time

Consistent associations for female PA support previous research on youth PA and sports participation

Limited associations between Male’s PA and screen time vs. friends’ PA and screen time

4. Future Directions

NIH Funding Opportunity

Announcement

PAR-10-145, “Social Network Analysis and

Health”

Mechanism: R01

Due: May 11, 2012

Start: April 2013

Overall Research Goal

Do changes in friend networks from 8 th through 10 th grade predict changes in weight-related behaviors of individuals as well as sub-networks (cliques) within a school?

Longitudinal, multiple time points

More complete network data

Include multi-level predictors of PA and screen time as mediators of the hypothesized behavior changes

– individual-level psychosocial factors, family/home environment, school, social and physical environments of neighborhood.

Possible Research Questions

How are these weight-related behaviors transmitted within schoolbased peer networks?

If an active person in 8 th inactive individuals in 9 th grade becomes friends with a group of grade, does this individual become less active themselves or do they maintain their activity level?

Does the network become more like the new friend or is there no effect?

Why?

What role do PA, sport, TV viewing, video games play in selecting new friend(s)

What are the characteristics of the individual and those in the network and how do those factors mediate behavior change of the individual or the network?

poorly written

Specific Aims

1. To determine if changes in an individual’s social network

(to a network with different weight-related behaviors) results in changes in the individual’s weight-related behavior that is similar to the network’s behavior

2. To determine if changes in the weight-related behaviors of an individual(s) within a clique influences the behaviors of others in the clique.

3. To identify the…

A.

B.

Individual and network characteristics that promote, maintain, or increase PA within the network

Individual and network characteristics that promote, maintain, or increase screen time within the network

Additional Research Questions

(School-level Analysis)

Does the “spread” of student athletes within non-sports clubs/organizations and across sub-networks (cliques) affect the overall physical activity level of the school?

Collect rosters for school-based sports teams and selected formal non-sports clubs (e.g., student government, newspaper, yearbook, band).

Hyp: School-level physical activity will be greater in schools with a greater “spread” of student athletes within non-sport groups/clubs, and across cliques due to the added exposure of other students to those student athletes, compared to schools where student athletes stay within limited insular cliques.

Download