The Adolescent Obesity Epidemic:

Micro and Macro Perspectives for Health Communication Practitioners

Overview:

My Health Communication Philosophy A general picture of obesity Adolescent obesity (National vs. Local) Strategic Campaign Example

My Health Communication Philosophy

A behavior change intervention should be grounded in theory, strategy, epidemiological research; however, even more importantly, it should first start where the people are.

Ecological Considerations

Obesity in general

What is considered Obese?

Source: Utah Nutrition and Physical Activity Plan 2010 to 2020, Version 2.0. (2012) Salt Lake City, Utah: Utah Department of Health.

Centers for Disease Control and Prevention, Division of Nutrition, Physical Activity, and Obesity (CDC). (2011). About BMI for children and teens. Retrieved from http://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childrens_bmi.html

Risk Factors Obesity is associated with

Myocardial infarction Stroke Type 2 diabetes Hypertension Osteoarthritis Asthma Depression Etc.

Mayo Foundation for Medical Education and Research (MFMER). (2013). Risk factors. Retrieved from http://www.mayoclinic.com/health/obesity/DS00314/DSECTION=risk-factors

J.B. Dixon The effect of obesity on health outcomesMolecular and Cellular Endocrinology, 316 (2010), pp. 104–108

F.B. Hu Obesity Epidemiology Oxford University Press, New York (2008)

Economic Consequences

National Cost In 2006 Finkelstein et al. (2009)

estimated the impact of obesity on national medical costs at

$147 billion In 2012, Cawley and

Meyerhoefer (2012) argued that previous literature underestimated the cost, and found that the cost may actually be closer to

$209 billion

Utah Cost Estimated to be near $485

million

With the future cost estimated at $2.4 billion

E.A. Finkelstein, J.G. Trogdon, J.W. Cohen, W. Dietzannual medical spending attributable to obesity: payer- and service-specific estimatesHealth Affairs (2009) Web Exclusive. July 27, 2009

Thrope KE. The Future Cost of Obesity: National and State Estimates of the Impact of Obesity on Direct Health Care Expenses. A collaborative report from United Health Foundation, the American Public Health Association, and Partnership for Prevention. 2009. http://www.nccor.org/downloads/CostofObesityReport-FINAL.pdf

Utah Nutrition and Physical Activity Plan 2010 to 2020, Version 2.0. (2012) Salt Lake City, Utah: Utah Department of Health. Available for download at www.choosehealth.utah.gov

Narrowing the focus on adolescent obesity

Priority Populations

Children Elderly Clinically depressed

children, youth, and People with disabilities Socioeconomically

disadvantaged people

People who live in rural and frontier areas

Ethnic minorities Refugees Etc.

Source: Utah Nutrition and Physical Activity Plan 2010 to 2020, Version 2.0. (2012) Salt Lake City, Utah: Utah Department of Health.

An Increase in Obesity Rates – especially among adolescents

133% increase among adults aged 20-74 150% increase among children aged 2-5 years 177% increase among children aged 6-11 years 268% increase for adolescents aged 12-19 years

Sources: Ogden, C.L., Carroll, M.D., Curtin, L.R., Lamb, M.M., & Flegal, K.M. (2010) Prevalence of high body mass index among U.S. children and adolescents, 2007-2008. Journal of the American Medical Association, 303(3), 242-249.

Ogden, C.L., Carroll, M.D., Curtin, L.R., Lamb, M.M., & Flegal, K.M. (2010) Prevalence of high body mass index among U.S. children and adolescents, 2007-2008. Journal of the American Medical Association, 303(3), 242-249.

Increases over the last decade

Eaton, D.K, Kann, L., Kinchen, S., Shanklin, S., Ross, J., Hawkins, J., & …Wechsler, H. (2010). Youth Risk Behavior Surveillance – United States, 2009. MMWR SurveillanceEaton, D.K., Kann, L., Kinchen, S., ShanklinS., Flint, K. H., Hawkins, J., & …Wechsler, H. (2012). Youth Risk Behavior Surveillance – United States, 2011. MMWR Surveillance

Percentage of obese adolescents

Source: Eaton, D.K., Kann, L., Kinchen, S., ShanklinS., Flint, K. H., Hawkins, J., & …Wechsler, H. (2012). Youth Risk Behavior Surveillance – United States, 2011. MMWR Surveillance

No Data

7.3% - 10.8%

10.9% - 11.9%

12.0% - 14.6%

14.7% - 17.0%

Micro vs. Macro:

Utah Adolescents 9% were obese

(students who were > 95th percentile for body mass index, based on sex and age-specific reference data from the 2000 CDC growth charts)

U.S. Adolescents 13% were obese

(students who were > 95th percentile for body mass index, based on sex and age-specific reference data from the 2000 CDC growth charts)

Over 56.9% of Utah adults are overweight and 22.5% obese (CDC, 2010).

Research has found that obese children are more susceptible to becoming obese adults (Freedman, Khan, Dietz, Srinivasan, and Berenson, 2001).

CDC. Behavioral Risk Factor Surveillance System: Prevalence and Trend Data–Overweight and Obesity, U.S. Obesity Trends, Trends by State

Seo, D., & Sa, J. (2010). A meta-analysis of obesity interventions among U.S. minority children. Journal of Adolescent Health, 46, 309-323.

And, in recent years, obesity trends reflect the national trend: Obesity has nearly doubled since 1989

Incidentally, overtime, Utah’s southwest region is the least impacted by the epidemic

Utah Nutrition and Physical Activity Plan 2010 to 2020, Version 2.0. (2012) Salt Lake City, Utah: Utah Department of Health. Available for download at www.choosehealth.utah.gov

So, what can be done about adolescent obesity?

CDC’s recommended target areas for state intervention plans Increase physical activity Increase consumption of fruits and vegetables Decrease consumption of sugar-sweetened beverages Increase breastfeeding initiation, exclusivity, and duration Reduce the consumption of high-energy-dense foods Decrease television viewing

Physical Activity Defined

The operational definition of moderate-to-vigorous physical activity is established as any activity which requires the same exertion that it would take to walk briskly, which may include: jogging, stair climbing, dance, soccer, swimming laps, strenuous housework, cross-country skiing and cycling (Sallis and Patrick, 1994).

Physical activity should increase the individual’s heart rate and breathing (Eaton et al., 2009).

Eaton, D.K, Kann, L., Kinchen, S., Shanklin, S., Ross, J., Hawkins, J., & …Wechsler, H. (2010). Youth Risk Behavior Surveillance – United States, 2009. MMWR SurveillanceSallis, J.F., & Patrick, K. (1994). Physical Activity Guidelines for Adolescents: Consensus statement. Pediatric Exercise Science, 5, 302-314

An multi-component (individual-level) intervention designed to increase physical activity

This hypothetical case example was designed to increase physical activity among adolescents in two at-risk wards in the District of Columbia will briefly demonstrate four areas related to campaign planning.

Formative Evaluatio

n

Audience Segment

ation

Process Evaluatio

n

Impact and

Outcome Evaluation

Audience SegmentationWhat at-risk population is most effective to target?

Target audience: African American female students (grades 9-12)

African American female minorities (grades 9-12) in five D.C. area high schools (located in wards 7 & 8) who are currently statistically at the greatest risk of becoming obese adults with obesity related health problems; as well as report low physical activity levels

Why this target audience? Higher BMI

• A comprehensive study of BMI levels by Ogden et al.(2010) found that female minorities were more likely to have a higher BMI when compared to white adolescent females

Sedentary Lifestyle• African American females have been found to be increasingly sedentary as they enter

their late teen years (Freedman, et al., 2001).

Media Consumption Habits• Research found that 57.4% African American female students spend 3 or more hours

watching television daily ( Eaton, 2010, p.26).

Establish Healthy Habits• Research indicates that establishing healthy activity levels in the teen years may

encourage more positive behaviors into adulthood (Robbins et al., 2013)Sources: Eaton, D.K, Kann, L., Kinchen, S., Shanklin, S., Ross, J., Hawkins, J., & …Wechsler, H. (2010). Youth Risk Behavior Surveillance – United States, 2009. MMWR Surveillance

Freedman, D.S., Khan, L.K., Dietz, W.H., Srinivasan S.A., and Berenson, G.S. (2001) Relationship of childhood obesity to coronary heart disease risk factors in adulthood: The Bogalusa heart study. Pediatrics, 108, 712–718.

Ogden, C.L., Carroll, M.D., Curtin, L.R., Lamb, M.M., & Flegal, K.M. (2010) Prevalence of high body mass index among U.S. children and adolescents, 2007-2008. Journal of the American Medical Association, 303(3), 242-249.

Robbins, L. B., Pfeiffer, K. A., Vermeesch, A., Resnicow, K., You, Z., An, L., & Wesolek, S. M. (2013). “Girls on the Move” intervention protocol for increasing physical activity among low-active underserved urban girls: A group randomized trial. BMC Public Health [serial online]

Why Washington D.C.?

Overall 17.8% of students grades 9-12 are overweight and 17.7% obese, which equals over a third of all high school students (BRFSS, 2010).

We will focus specifically two geographic regions in Washington D.C. :

Ward 7= 70,540 residents with 97% African American

Ward 8 = 70,914 residents with 92% African American

The obesity rates in Wards 7 and 8 (40% and 42%, respectively) are the highest compared to all demographic subgroups

Ward 8 has the highest rates of obesity (41.9%) and the

lowest rates of physical activity (69.1%).

Obesity & Inactivity

Target Audience Segments

I chose to segment the target audience into two distinct groups:

Segment 1 Inactive (Not attending P.E.): African American females (grades 9-12) who report NO physical activity in the previous week

Segment 2 Somewhat Inactive (Attending P.E.): African American females (grades 9-12) who report LIMITED physical activity in the previous week

Health Objectives What measurable goals can guide the intervention?

Health Objective: Increase Physical Activity The overall health objective is to decrease by 2.2 % (over 1 academic year)

the proportion of African American female students (grades 9-12) who report not participating in some form of moderate-to-vigorous physical activity at least one 60 minute period each week. *

Geographic Target: 12 Washington D.C. area high schools

Baseline: 43.6 % of African American female students currently do not participate in any physical activity for 60 minutes on any day (Eaton, et al. 2010)**

Target: 41.4 %

Improvement Percentage: 5 percent

Timeframe: 1 academic year

Sources: *Based on Healthy People 2020 ObjectiveInitiative U.S. Department of Health and Human Services (HHS) (2013). Healthy People 2020. Retrieved from http://healthypeople.gov/2020/topicsobjectives2020/objectiveslist.aspx?topicId=33**Eaton, D.K, Kann, L., Kinchen, S., Shanklin, S., Ross, J., Hawkins, J., & …Wechsler, H. (2010). Youth Risk Behavior Surveillance – United States, 2009. MMWR Surveillance

Behavioral Objective: Increase P.E. Attendance

Our overall behavioral objective is to increase by 6.8% the proportion of adolescent African American females (grades 9-12) who attend physical education classes on a daily basis.

Geographic Target: 12 Washington D.C. area high schools

Baseline: 34 % of African American female students currently attend 5 days a week (Eaton et al., 2010)

Target: 40.8%

Improvement Percentage: 20 %

Timeframe: 1 academic year

Theory ImplementationWhat best practices can guide the overall strategy?

A Social Cognitive Framework

SCT’s main construct, reciprocal determinism, asserts that personal factors, environment and human behavior all exert influence on each other (National Cancer Institute, 2005).

As a result, African American adolescent females may be more heavily influenced by their environment, social interactions and observations of others, than they are by a static curriculum that simply increases their knowledge about exercise.

Source: National Cancer Institute. (2005). Theory at a glance: A guide for health promotion practice. Retrieved from http://www.cancer.gov/cancertopics/cancerlibrary/theory.pdf

A multi-component intervention

In one study, conducted by Pate et al. (2005), they found it extremely effective to add an environmental component (based on SCT) in addition to the P.E. curriculum. Further, they provided positive role models that helped female students with observational learning, skill training, self-efficacy, helping them form realistic expectations about exercise, and encouraging them to identify alternative physical activity opportunities outside of school and regular P.E. classes.

Pate, R.R., Ward, D.S., Saunders, R.P., Felton, G., Dishman, R.K., & Dowda, M. (2005). Promotion of physical activity among high-school girls: A randomized controlled trial. American Journal of Public Health, 95(9), 1582-1587.

Why P.E. class attendance? Research supports schools as “a critical setting for prevention and

intervention programming where health status indicators – such as BMI and chronic disease risk factors – can be positively impacted” (Wilson and Meyers, 2009, p.66).

Wilson, D.K., & Meyers, D.C. (2009). Innovations in preventing and treating obesity in children and adolescents: The role of physical activity interventions. In L. James, J. Linton (Eds.), Handbook of Obesity Intervention for the Lifespan (pp.65-82). New York, NY: Spring Science+Business Media, LLC.

In a study of physical exercise among 248 high school students it was found that perceived self-efficacy to overcome barriers to exercise, social environment and outcome expectations, and the ability to self-regulate by setting and meeting goals, all had a significant effect on the students’ regular exercise habits (Winters, Petosa, & Charlton, 2003).

Research supports that building self-efficacy through face-to face activities with role models who demonstrate successful exercise techniques (observational learning and expectations), skill-building activities to improve technique (behavioral capability), and provide self-initiated reinforcements (rewards) through realistic goal-setting, will have a greater chance of encouraging self-efficacy to accomplish substantive behavior change (National Cancer Institute, 2005). Sources: Winters, E.R., Petosa, R.L., & Charlton, T.E. (2003). Using social cognitive theory to explain

discretionary, “leisure-time” physical exercise among high school students. Journal of Adolescent Health, 32(6), 436-442.

National Cancer Institute. (2005). Theory at a glance: A guide for health promotion practice. Retrieved from http://www.cancer.gov/cancertopics/cancerlibrary/theory.pdf

Confidence, Attitude, Knowledge/Skill Objectives

3 Specific Skills ObjectivesConfidence Objective

A 20% improvement (above baseline) among African American females (grades 9-12) who report having confidence in increasing their physical activity levels during the campaign timeframe.

Attitude Objective

A 20% improvement (above baseline) among African American females (grades 9-12) who report positive attitudes (expectations) toward regular physical activity.

Knowledge and Skill Objective

A 20% increase (above baseline) among Somewhat Active African American females (grades 9-12) who report new skills in one or more physical activities or sports.

Dissemination What channels will successfully reach our target?

Interpersonal channels and an interactive approach to a (face-to-face) intervention

Inactive Segment

4 Afterschool workshops

School wide assemblies

Role Models

Motivational brochures, wristbands and posters

Poster campaign

Somewhat Active Segment

Bi-weekly intervention sessions with new curriculum

Personal Goal-Setting journals will be distributed with link to online tracking tools

Skill building activities

Exercise technique modelling

Exposure Objectives

Exposure: For the somewhat active segment this campaign aims for widespread, repeated weekly exposure to (1 of the 2 intervention P.E. class sessions per week) over a time period of one academic year in the treatment schools.

Exposure: For the inactive segment this campaign aims for 80% of our target audience to have attended one motivational event (assembly) or after-school activity; with 90% recalling some aspect of the motivational curriculum or promotional material posted throughout the schools.

Logic Model

Exposure Objectives:

- Somewhat Active - weekly exposure to fitness curriculum

- Inactive – exposure to motivational event and

materials

Behavior Objective:

Increase P.E.

Attendance

Knowledge Objective(Observational

Learning): Role Models demonstrate skills in

physical activities

Health ObjectiveDecrease

proportion of target audience who report not participating in daily physical

activity.

Health ProblemDecrease

obesity among African

American females

(grades 9-12)

Attitude Objective

(Self-Efficacy): The confidence

to engage in regular physical

activities

Self-Regulation(Reinforcements or

Rewards) Set and review self-initiated fitness goals

Outcome ExpectanciesAnticipated positive

attitude about outcomes of physical activity

increase

ProcessObjectives

Somewhat Active- Bi weekly intervention session in P.E. class- Goal-setting journals

Inactive Segment-school assemblies-after-school workshops-poster campaign

Measurement and EvaluationHow do we measure the outcomes to provide evidence of substantive results?

Quasi-Experimental Design

“Designs that do not use random assignment but are more robust than non-experimental designs are quasi-experimental designs” (Issel, 2014).

DESIGN: Nonequivalent, Two-group

Pretest/Posttest

UNIT OF ANALYSIS: Enrolled students at school

Issel, L. M. (2014). Health program planning and evaluation: A practical, systemic approach for community health. Burlington, MA: Jones & Bartlett Learning.

Triangulation of Data

Focus Groups

Survey Data

Quantitative Content Analysis

Informal Feedback

Participants’

Environment

Focus groups

Content Analysis

Informal Feedbac

k

Survey

Pre-testing and Post-testing

Two pre-tests will be conducted, one 6 months before implementation of the intervention, and the other 1 month prior to the intervention.

One post-test will be conducted immediately following the intervention, with the other 6 months later

Intervention2

Academic Semester

s

Posttest 6

months after

Posttest 1 week after

Pretest 1 month

prior

Pretest6

months prior

Control Group

10 Treatment Schools (Ward7&8)

Control School (Ward 7&8)

Statistical Power

Our main concern is that we have enough participants from the somewhat active segment attending our intervention sessions on regular basis.

2,500 students, with an estimated 1,200 females in 9-12th grade

= approx. 400 students registered for P.E. per school in any given 2 terms

Confounding Variables

- Truancy/dropout Rates

- Access to recreational exercise space and equipment

- Pre-established family and cultural traditions

- Smoking Habits

- Homework

- Socioeconomic Status

- Influence of similar national school Campaigns (e.g., Let’s Move)

- Team sport programs that conflict with P.E. schedule

- Negative parental/family influences

Thank you for your time and interest!