Session # G1cOctober 16, 2015

Childhood Obesity Prevention and Treatment: Behavioral Health and

Medical Providers Partnering in Research and Practice

Jerica Berge, Ph.D., Associate Professor, University of Minnesota

Keeley J. Pratt, Ph.D., Assistant Professor, The Ohio State University

Faculty Disclosure

The presenters of this session• have NOT had any relevant financial

relationships during the past 12 months.

Learning Objectives

At the conclusion of this session, the participant will be able to:

• Describe the prevalence of childhood obesity and obesity disparities and discuss how family medicine/primary care clinics are a natural environment for childhood obesity prevention and treatment interventions.

• Describe interdisciplinary childhood obesity intervention research approaches and clinical care models currently being carried out in family medicine/primary care clinics.

• Discuss clinical recommendations and best practices for working with families who have an overweight or obese child in family medicine/primary care clinics.

Bibliography / References1. Berge, J.M., Meyer, C., MacLehose, R., Crichlow, R., Neumark-Sztainer, D. (in press). All in the family: Associations between parents’ and siblings’ weight and weight-related behaviors and adolescents’ weight and weight-related behaviors. Obesity.

2. Berge, J.M., Everts, J. (2011). Family-based interventions targeting childhood obesity: A meta-analysis. Childhood Obesity, 7(2), 110-121.

3. Sherwood, N.E., French, S.A., Veblen-Mortenson, S., Crain, A.L., Berge, J., Kunin-Batson, A., Mitchell, N., Senso, M. (2013). NET-Works: linking families, communities and primary care to prevent obesity in preschool-age children. Contemporary Clinical Trials, 36(2): 544-554.

4. Berge, J.M., Law, D.D., Johnson, J., Wells, M.G. (2010). Effectiveness of a psychoeducational parenting group on child, parent and family behavior: a pilot study in a family practice clinic with an underserved population. Families, Systems and Health, 28, 224-235.

5. Stovitz, S., Berge, J.M., Wetzsteon, R.J., Sherwood, N., Hannan, P.J., Himes, J. (2014). Stage 1 treatment of pediatric overweight and obesity: A pilot and feasibility randomized controlled trial. Childhood Obesity, 10(1):50-57.

Learning Assessment

• A learning assessment is required for CE credit.

• A question and answer period will be conducted at the end of this presentation.

Overview of Presentation

o Agenda• Introduction to presenters, topic, and

prevalence• Family Systems Theory and it’s application to

Childhood Obesity• Research and Clinical Applications for family-

based obesity intervention• Prevention• Treatment

• Questions

Introduction to the topic and prevalence

Prevalence of Childhood Overweight/Obesity

• Worldwide– Approx. 1.6 billion adults (age 15+) are overweight – At least 20 million children under the age of 5 years are overweight

• Nationally: USA (ages 2-19)– 31.8% Overweight ≥ 85th percentile– 16.9% Obese ≥ 95th percentile– 12.3% Severely Obese ≥ 97th percentile – Highest among Hispanics (22.4) and non-Hispanic Black

youth (20.2)– 2-5 years old least obese group vs 6-11 and 12-19 age

groups

(Crawford, 2008; IOM, 2005; Federal Interagency Forum on Child and Family Statistics, 2007; National Survey of Children’s Health, 2007; Ogden et al., 2012)

BMI Trends in Families

• BMI between youth and parents is highly correlated (especially mothers)– 1 parent and 2 parent obesity risks

• BMI between partners/spouses is highly correlated

• Mixed findings before, during, and after marital disruption (divorce/separation) and child BMI

(Arkes, 2012; Bralic, Vrdoijak, & Kovacic, 2005; Safer et al., 2001; Yannakoulia et al., 2008)

Diverse Settings

• Obesity may be treated in several contexts depending on the severity and availability of specialty care– Inpatient – Outpatient– Specialty Clinic/Tertiary Care– School, church, or other community-based

interventions

Stages of Treatment – Childhood Obesity

• Stage 1: Prevention Plus (Primary Care)– Family visits with MD or health professional for lifestyle/behavioral treatment

• Stage 2: Structured Weight Management (Primary or Specialty Care)– More structure and support with individual or group follow-ups with a

dietician and exercise therapist– Included self-monitoring, goal setting and rewards, and monthly

individualized treatment• Stage 3: Comprehensive and multidisciplinary approach (Specialty Care)

– Structured behavioral program with diet and physical activity goals– Weekly group sessions for 8-12 weeks plus follow-up

• Stage 4: Tertiary Care for Severely Obese Youth (Specialty Care)– Medication– Very low-calorie diets– Surgical approaches

(NICHQ, 2007; Barlow, 2007; AAP, 2007; NHLBI, 2007)

*Differences based on age.

Davison & Birch, 2001, Ecological Model of Predictors of Child Overweight

Differences in Age

• The Expert Committee Recommendations (Barlow, 2007) directs healthcare providers to focus their approach based on the developmental and chronological age of the youth:– Youth ages 2–5: focus the discussion on parenting

behavior – Youth ages 6–11: equally target caregiver(s) and youth – Adolescents: discuss health behaviors directly with the

adolescent, and parents/caregivers should be encouraged to make the home environment as healthy as possible and provide support to their teen

Family Systems Theory and Application to Childhood Obesity

Family Systems Theory (FST)

• Families are complex systems where multiple reciprocal interactions occur simultaneously between members

• Members of a family are connected, and must be viewed as a whole

• Families resist change, and strive to stay in homeostasis

• Families have rules, boundaries and rituals• Family subsystems (i.e. parent-child) can influence

the whole family’s functioning (Bertalanffy, 1952)

Family Systems Approach to Childhood Obesity

Sibling Domain:

1. Weight Teasing2. Modeling healthful behaviors

Family Functioning Domain:

1. Family Functioning2. Emotional Closeness and Connectedness3. Family Weight Teasing4. Availability & Accessibility of Healthful Food5. Resources for Physical Activity6. Family Meal Frequency

Parental Domain:

1. Parenting Style2. Parenting Practices (e.g., modeling of health behaviors and conversations about health behaviors)3. Parental Perceptions 4. Personal Behaviors

Obesity & OtherWeight-Related Outcomes

Among Children & Adolescents:

1. Weight Status2. Dietary Intake3. Physical Activity4. Unhealthy Weight Control Behaviors

(Berge, 2009)

Childhood Obesity & Family

• Involving the family system promotes more sustainable

diet and physical activity behavioral changes in the youth • Including parents as active participants in habit change

and weight loss was effective for weight control among children at 5-year follow-up

• Positive outcomes have included: • Reductions in BMI (z-score)• Increases in QOL • Decreases in depression• Reductions in sedentary behavior

(Barlow, 2007; Denzer et al., 2004; Epstein et al., 1990, 1994; Pratt et al., 2013; Robertson et al., 2011)

Systematic Reviews of RCTs• Parent-only vs parent-child (family-focused) approaches for weight loss in

obese and overweight children– 4 RCTs meet inclusion criteria– No significant differences in BMI z-score from baseline to end of treatment

or follow-up

• Family-based models for childhood-obesity intervention: a systematic review of RCTs– 15 RCTs of family-based lifestyle intervention for youth (2-19) were included

• Family-based behavioral interventions achieved better results than family systems theory for treatment effectiveness

– 20 family-based RCT treatment interventions focused on lifestyle with children (2-12 yrs.) and families (some multiple family members)

• Significant effects for family-based treatment; opposite-sex parent/child dyads experienced more weight loss

(Jull & Chen, 2013; Sung-Chan, Sung, Zhao, & Brownson, 2013; Berge & Everts, 2011)

Systematic Review of RCTs cont.

• Family-focused physical activity, diet and obesity interventions in African-American girls– 27 obesity prevention or treatment studies with family– Most targeted parent–child dyads – Effects on weight-related behaviors and outcomes were

generally promising but often non-significant– Data did not detail whether or how best to involve family

members in obesity prevention and treatment interventions with African–American girls

(Barr-Anderson, Adams-Wynn, DiSantis, & Kumanyika, 2013)

Parenting and Home Environment Factors Associated with Childhood

Overweight and Obesity

• Parenting Practices– Feeding practices– Modeling and Encouraging

• Parenting style• Combination of Parenting Practices & Style• Family Meals• Family Functioning• Family Weight Talk

Prevention

Prevention• NET-Works Study:

– Multi-level, multi-setting interventions are needed to address the complex childhood obesity problem (Ecological Model)

– NIH and other expert committees have recommended using primary care as an entry point for family-based interventions

– Need for reducing obesity disparities in racial/ethnic groups

– U01 NIH Center grant; 7-years

NET-Works Specific Aims

• Evaluate three-year parent-targeted multi-level (i.e., home, community, primary care) intervention for preschool children

• Primary outcome change in child BMI z-score

• Randomized two-group design (N = 500)

NET-Works Intervention Components

Primary care message Family Medicine doctors

Family Connector (9 home visits per year) Home visiting

Parenting class (12 weeks x 2 semesters) Family Life Educators

Community food retail and recreation Connecting to pre-existing resources such as farmers markets,

green space/community gyms, libraries

Sample

N=500 families (10 community clinics)SomaliHispanicHmongAfrican AmericanWhite

Randomized two-group design (N = 500) – Standard Care Control Group (safety message); n=250– Experimental Group; n=250

3 year duration in order to increase the likelihood of seeing significant BMI changes

Treatment

• To describe the changes from youth baseline variables in QOL, caregiver and teen depression status, and child/teen BMI z-score from baseline through two follow-up visits

• Longitudinal panel descriptive• Analyzed the relationships over time using linear mixed

models with time as a covariate, considering a model with random intercepts and slopes, and having the unstructured covariance structure

• Patient trajectories are shown together with the estimated mean function (bold curve) obtained using a kernel smoother (a nonparametric function estimation procedure) with bandwidth chosen via the GCV procedure implemented in PACE package in Matlab

QOL and BMI Changes in an Integrated Pediatric Obesity Treatment Program

(Pratt, Lazorick, Lamson, Ivanescu, & Collier, 2013; Fitzmaurice, Laird, & Ware, 2004 ; Yao, Muller & Wang, 2005 )

Table 1. Baseline and Longitudinal CharacteristicsChild Background n(%)

Visit 1 267 Visit 2 113 Visit 3 48Sex

Male 122 (45.7%) 44 (38.9%) 20 (41.7%)Female 145 (54.3%) 69 (61.1%) 28 (58.3%)

RaceWhite 80 (30%) 39 (34.5%) 20 (41.7%)Black 169 (63.3%) 70 (61.9%) 28 (58.3%)Other 18 (6.7%) 4 (3.6) 0

Anthropometric Data mean (SD)BMI 37.8 (12.2) 38.2 (8.7) 38.9 (9.3)BMI z-score 2.50 (.34) 2.52 (.33) 2.53 (.40)BMI Category

Overweight 5 (1.9%) 0 1 Obese 68 (25.5.%) 39 (26.5%) 11 (22.9%)

Severely Obese 194 (72.7%) 83 (73.5%) 36 (75%)Baseline Family Background n(%)

Family StructureTwo-parent 128 (47.9%)

Single parent 95 (35.6%)Single parent +

Grandparent27 (10.1%)

Other 17 (6.4%)

Figure 1. Quality of Life for all youth (age 8-18) participants (n=266)

The average QOL intercept was 74.28 (t (260) = 78.9, p < .001), and slope was .034 (t (61) = 4.9, p < .001).

The mean QOL increased by .034 points, from the average QOL at the first visit, for each additional day all youth participants continue in the study.

The average BMI z-score intercept was 2.49 (t (264.0) = 120.1, p < .001), the slope was -0.00011 (t (66.3) = -2.54, p = .013).

Compared to the average BMI z-score at the first visit, the mean BMI z-score decreased by .00011 for each additional day the participants continue in the study.

Figure 2: Body Mass Index z-score for all youth

Figure 3: Patient Healthcare Questionnaire (nine item) for all teen (age 13-18) participants

The average PHQ9 intercept was 5.35 (t (121) = 14.2, p < .001), and the slope was -.01 (t (56) = -4.2, p < .001).

Compared to the average PHQ of 5.35 for teens at the first visit, the mean PHQ decreased by .01 points for each additional day the participants continue in the study.

Discussion

• Overall, across three visits, our results indicated youth’s BMI z-score decreased slightly, their QOL significantly increased, and teen depression level improved.

• Interestingly, youth had significant improvements in their QOL, despite their BMI z-score and the majority of our sample being either obese or severely obese– Researchers have reported that QOL is inversely related

to weight; suggesting that the most overweight youth have the most significantly impaired QOL

• Limitations: treatment seeking sample, no significant predictors of follow-up, only dyads assessed

Who are our patients?

• Statistics highlight growing rate of overweight individuals & families in the US

• Co-occurrence of mental health issues in conjunction with increased weight

• Providers will undoubtedly work with patients & families struggling with weight and potential biases

• Providers must become aware of their biases about body type & weight

What is Weight-bias?

• Weight bias includes the negative attitudes, stereotypes, and overt or covert actions and expressions that affect our interpersonal relationships and interactions

• Negative stigma attributed to overweight individuals includes labeling them as lazy, unmotivated, lacking in self-discipline, or less competent overall

(Puhl & Brownell, 2007; Puhl & Heuer, 2009)

Weight-bias and Providers

• Weight bias has been documented among:– Physicians– Medical students– Dieticians– Nurses– Mental health providers

(Campbell, Engle, Timperio, Cooper, & Crawford, 2000; Wigton & McGaphie, 2001; Berryman, Dubale, Manchester, & Mittelstaedt, 2006; Hoppe & Ogden, 1997; Puhl & Brownell, 2006)

Trainees & Weight Bias

Purpose: to determine measures of explicit weight bias among MFT graduate students in COAMFTE accredited programs

(Pratt & Cravens, 2014; Pratt, Palmer, Cravens, Ferriby, Balk & Cai, 2015)

Method• Students in CFT programs at Universities around the

country were invited to take a Qualtrics Survey addressing weight-bias

• There was a basic demographics investigator-created questionnaire and three weight-bias questionnaires:

1. Beliefs about Obese Persons (BOAP), scale range 0-24; M=17.2 (SD = 5.5), range 3-24, α = .64

2. Antifat Attitudes Questionnaire (AFA), scale range 0-117; M=38.0(SD=17.0), range 10-75, α = .85

3. Attitudes Towards Obese Persons (ATOP),scale range 43-111; M=70.0(SD=9.3), range 55.0-92.0, α = .50

Method cont.

• Note: On all scales, except for the ATOP, higher totals indicate more weight bias or negative attitudes/beliefs towards obese persons

• Descriptive analyses were done for all demographic and weight-related variables

• Correlations between our continuous variables were calculated using Pearson’s r

• Independent samples t-tests were calculated to determine the differences on the four weight-bias questionnaires based on participant demographic or weight-related variables

• Multiple regression was performed to determine predictors of explicit weight-bias

Independent t-test analyses yielded significant results for the BAOP, ATOP, and AFA scale totals (next slide).

There were also significant results on the AFA Willpower subscale between Master’s (m=12.74, sd=5.93) and Doctoral students in MFT Programs (m=9.07, sd=5.50, t(160)= 3.01, p=.003).

Discussion

• We were surprised to see that participants who were female,overweight (via BMI), and identified as overweight (via self-report) had more fear of gaining weight than their peers

Intervention Take Homes

• Address with families!• Systemic and Ecological approach

– All domains overlap and will help individual and family functioning (e.g., child with ADHD)

• Motivational Interviewing Skills Essential• Now more common to have Medical Family Therapist in

Primary Care/Family Medicine and Pediatrics– Joint visits with physicians=Integrated Care;

Collaborative Care (Warm hand-offs), Co-located care (referrals)

• Some states are reimbursing for “behavioral codes”

Evidence-based Topics to Discuss

• Parenting Practices (feeding, modeling healthful eating and physical activity patterns)– Help families redefine family-level physical activity

• Parenting Style• Family Functioning• Weight Conversations in the Home

Environment• Family Meals

QUESTIONS?Contact Information:

Jerica –

jberge@umn.edu

612-626-3693

Keeley –

pratt.192@osu.edu

614-247-7883

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