Evidence-based obesity management for primary care
As attested to by popular media and epidemiological surveys alike, pediatric obesity and overweight have reached epidemic levels in the United States and much of the developed world. The most recent National Health and Nutrition Evaluation Survey indicates that approximately 17 percent of children and adolescents in the United States are obese and about 32 percent are overweight (Ogden, Carroll, Kit & Flegal, 2012) — a three-fold increase over rates estimated in 1980.
In addition to increased risk of persistent obesity through adulthood, children and adolescents who are overweight or obese are at increased risk for a number of physical and mental health conditions, including insulin resistance, hypertension, abnormal glucose intolerance, sleep apnea, peer victimization, decreased health-related quality of life and increased risk for internalizing problems (for reviews, see Jelalian & Hart, 2009, Vivier & Tomkins, 2008 and Zeller & Modi, 2008). Some of these conditions (e.g., decreased subjective quality of life, internalizing problems) have been associated with further decreases in positive health behaviors (e.g., moderate/vigorous physical activity), thereby resulting in a feedback loop of decreasing health quality, increasing distress and increasing risk for obesity (see Luppino et al., 2010 for a review).
The epidemiological patterns suggest that risk for overweight in the U.S. varies across social, economic, and racial/ethnic groups. Specifically, individuals with lower household incomes, those from rural communities and those who are African-American or Latino/a are at increased risk for obesity and overweight (e.g., Lutfiyya, Lipsky, Wisdom-Behounek, & Inpanbutr-Martinkus, 2007; Singh, Siahpush, Kogan, 2010; Voss, Masuoka, Webber, Scher & Atkinson, 2013).
Although there are likely genetic vulnerabilities for the development of obesity, environmental, economic, cultural and behavioral factors are also important contributors to the risk. For example, foods high in caloric density (e.g., fast food) are frequently less expensive than those of higher nutritional value, increasing risk in low-income families. Similarly, the risk of obesity is increased for children who live in poorly resourced communities and therefore have fewer opportunities for safe physical activity. Regardless of economic or environmental conditions, children who receive modeling of unhealthy diets or patterns of physical activity are at increased risk.
In 2007, the Expert Committee on Pediatric Obesity (Barlow et al., 2007) recommended a sequence of graded stages of obesity care, with more intensive treatment components for children and adolescents with higher degrees of obesity, or those for whom other treatments did not produce adequate results. At each recommended stage of care, the committee noted specific treatment components with consistent evidence supporting their efficacy in structured and comprehensive care. These treatment components included dietary and physical activity changes, a program of behavior modification to support these changes, involvement of the whole family in lifestyle changes and frequent contact with the treatment team.
Given their central role in managing children's health, primary care clinicians (including primary care pediatric psychologists; PCPPs ) are vital contributors to the multifaceted solutions necessary to curb pediatric obesity. PCPPs benefit from: 1) an established and trusting relationship with families that extends beyond a focus on health behavior, 2) a large number of reimbursable opportunities for follow-up, 3) decreased stigma for receiving treatment (as opposed to treatment in a mental health setting) and 4) opportunities for multidisciplinary collaboration and medical monitoring. Below we highlight some of the specific tasks that comprise competent evidence-based management of pediatric obesity.
Evidence-based treatment of pediatric overweight and obesity begins with accurate assessment of the child or adolescent's age, height and weight. These anthropometric data can yield Body Mass Index (BMI) percentiles for age and sex via the Center for Disease Control and Prevention's BMI calculator. Although not a direct measure of adiposity (i.e., amount of fat or adipose tissue), BMI percentile provides an empirically-validated measure of health risk for children and adolescents (e.g., Mei et al., 2002; Must & Anderson, 2003). Children at or above the 85th percentile for age and sex are considered “overweight”; children at or above the 95th percentile are considered “obese” (Ogden et al., 2012). Additional assessments of adiposity or endocrine functioning (e.g., skin-fold measurement, serum lipid levels, glucose tolerance) may be ordered by medical staff and can be used to help assess risk and tailor the treatment plan.
In addition to the collection of anthropometric data, it is important to assess both energy balance behaviors (e.g., physical activity and diet) and psychosocial variables. For the PCPP targeting obesity, this assessment will be both process- and outcome-oriented. Due to the process orientation, it is necessary to use assessments that can be easily reported by patients, such as daily logs of foods eaten and activity performed. These assessments form the foundation for managing energy balance (discussed in the Treatment section below).
Arguably, the most important and most overlooked clinical consequences of obesity are its psychosocial sequelae. These variables are of critical importance because psychosocial consequences commonly precede, and exacerbate, medical co morbidities. Moreover, discussing psychosocial co morbidities with parents can help to motivate health behavior change. For example, in a recent study of treatment-seeking children with obesity, parents' perception of their child's quality of life was the only meaningful predictor of concern for their child's weight and subsequent desire for an intervention (Cushing, Bishop-Gilyard, Boles, Reiter-Purtill, & Zeller, 2013). In other words, parental concern was spurred by the perceived suffering of the child — not the child's excess adiposity.
Clinicians with time to administer a full quality of life assessment are encouraged to use obesity-specific measures such as Sizing Me Up (Child report; Zeller, & Modi, 2009), Sizing Them Up (Parent report; Modi & Zeller, 2008), and the Impact of Obesity on Quality of Life — Kids (Adolescent report; Kolotkin et al., 2006). If these measures are not available, simply using the prompt, “ How is your child doing day-to-day with regard to weight?” followed by questions about: 1) physical, 2) emotional, 3) social, and 4) school functioning may be sufficient to start a dialogue with parents about qualitative impairments. Although quality of life is the psychosocial variable most closely tied to obesity, mood symptoms and poor peer relations also can serve as barriers to weight reduction. Brief, validated screening measures that have been used with overweight populations, such as the Children's Depression Inventory (Kovacs, 2001, 2011) and the Perceptions of Teasing Scale (Thompson, Cattarin, Fowler & Fisher, 1995) can be easily incorporated into clinical practice.
At a fundamental level, treatment of pediatric obesity amounts to helping the family adjust physical activity and dietary choices to achieve a “negative energy balance” (i.e., calories expended > calories consumed) until the child's BMI is within the “healthy” range — either as a result of the child using stored energy for growth or as a result of weight loss. Energy balance is a key concept to teach patients. During these discussions it is essential to communicate that the most effective strategy for creating an energy deficit is calorie control. Although increased energy expenditure (e.g., via increased physical activity) is very important, many families erroneously believe that they can begin an exercise program that will yield changes in adiposity on its own — when, in fact, caloric overconsumption is usually the key factor that leads to obesity. As discussed below, the focus of treatment at the primary care level is education on self-management and brief interventions targeting motivation and behavior modification, as needed.
Dietary Changes
Recommendations for dietary consumption should be presented in plain language that is easy for families to understand. The Stoplight Diet, developed by Leonard Epstein (Epstein & Squires, 1988), teaches families to categorize foods as Green, Yellow, or Red. Green (or “Go”) foods (most fruits and vegetables) are appropriate for relatively unrestricted consumption (including snacks). Yellow (or “Caution”) foods (e.g., grains, lean meats, low-fat dairy) are reserved for meal times (not snacks). It is important to teach families to carefully monitor portion sizes of “yellow” foods to maintain negative energy balance. Red (or “Stop”) foods (those with high fat and sugar content) should be used very sparingly. Families are encouraged to eat at least 35 servings of “green” foods and 5 or fewer servings of “red” foods each week. The remaining calories are recommended to come from a balanced diet that adheres to the Choose My Plate (www.choosemyplate.gov) guidelines of the United States Department of Agriculture.
Physical Activity
As noted above, physical activity is valuable for increasing caloric output and helping achieve a negative energy balance. Primary care providers also should be aware that regular moderate/vigorous physical activity improves cognitive functioning (Hillman, Kamijo & Scudder, 2011), which may lead to better decision-making regarding dietary choices.
Behavior modification
PCPPs may be uniquely suited to work with families on strategies of behavior modification in the home. Stimulus control, modeling, and positive reinforcement are techniques within the PCPP's bailiwick and can be extremely effective in helping establish and maintain positive health behaviors that lead to negative energy balance (Kitzmann et al., 2010). In the context of weight counseling, PCPPs should: 1) encourage families to remove all “ red” foods (see above) from the home and make green foods easily available and visible (i.e., stimulus control); 2) encourage parents to perform the behaviors they desire to see in their children (i.e., modeling or the “do as I do” principle); 3) remind parents that healthy habits must be learned (i.e., they are not innate) and must be positively reinforced. Once healthy behaviors are routine, positive reinforcement can be faded gradually.
Motivational strategies
A consistent finding in the literature, and a recommendation of the Expert Panel, relates to the importance of a whole-family approach (Kitzman et al., 2010; Xanthopoulos et al., 2013). Within the primary care clinic, the PCPP may be well-positioned to help motivate the whole family to improve health behavior. Motivational interviewing strategies have been shown to be effective in improving diet and physical activity, both alone and in combination with other strategies (Erickson, Gerstle, & Feldstein, 2005; Gayes & Steele, under review; Suarez & Mullins, 2008). A key principle of motivational interviewing approaches is the use of techniques to help an individual make a decision to change, rather than having change prescribed by the provider. This process typically involves exploring the advantages and disadvantages of a decision to change (generated by the patient), directing the conversation toward “change talk,” and requesting the patient's permission to provide feedback.
Problem solving
After families have achieved adequate motivation for a healthier lifestyle and understand the actions necessary to achieve a negative energy balance, the PCPP can be instrumental in helping the family identify and overcome barriers to behavior change. As noted above, economic, environmental, cultural and behavioral factors may not be conducive to increased physical activity or improved dietary decision-making. Beyond economics, many families struggle with making time to prepare foods at home (generally healthier than eating out) or to be more physically active. There are sometimes cultural factors that present challenges to achieving improved diets (e.g., specific foods that are hard to avoid within a cultural niche). The PCPP can use general problem-solving strategies (D'Zurilla & Nezu, 2007) to help motivated families find ways to overcome barriers to increased physical activity and improved diets (Epstein, Paluch, Gordy, Saelens & Ernst, 2000).
Pediatric obesity has become a significant problem in much of the developed and developing world. Genetic, environmental, economic, cultural and behavioral factors (and their interactions) have been shown to contribute to the risk for development of pediatric overweight and obesity. Because of the potential for longer-term relationships with families, the availability of interdisciplinary care in a medical home, and their unique training as behavioral health specialists, primary care psychologists are uniquely positioned to help families make the behavioral changes necessary to curb or reverse excessive weight gain and establish behaviors that will contribute to improved quality of life (Steele, Aylward, Jensen, Cushing, Davis & Bovaird, 2012). In particular, PCPPs can provide evidence-based assessment of health-related psychosocial issues that both contribute to, and result from, obesity. Further, PCPPs can provide behavioral, motivational and problem-solving therapies that can help families establish healthier habits.
References
Barlow, S. E., and the Expert Committee (2007). Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescents overweight and obesity: Summary report. Pediatrics, 120 (s4), s164-s192.
Cushing, C. C., Bishop-Gilyard, C. T., Boles, R. E., Reiter-Purtill, J., & Zeller, M. H.
(2013). Caregiver concern in adolescents with persistent obesity: The importance of
quality of life assessment. Journal of Developmental and Behavioral Pediatrics, 34( 1), 9-14. doi: 10.1097/DBP.0b013e31827c1345
D'Zurilla, T.J., & Nezu, A.M. (2007). Problem-solving therapy: A positive approach to clinical intervention (3rd ed.). New York: Springer.
Epstein, L. H., Paluch, R. A., Gordy, C. C., Saelens, B. E., & Ernst, M. M. (2000). Problem solving in the treatment of childhood obesity. Journal of Consulting and Clinical Psychology, 68 (4), 717-721.
Epstein, L. H., & Squires, S. (1988). The stoplight diet for children: An eight-week program for parents and children . Boston, MA: Little, Brown, & Co.
Erickson, S. J., Gerstle, M., & Feldstein, S. W. (2005). Brief interventions and motivational interviewing with children, adolescents, and their parents in pediatric health care settings. Archives of Pediatric Adolescent Medicine, 159 , 1173-1180. doi: 10.1001/archpedi.159.12.1173
Gayes, L. A., & Steele, R. G. ( 2013 ). A meta-analysis of motivational interviewing interventions for pediatric health behavior change. Manuscript submitted for publication.
Hillman, C. H., Kamijo, K., & Scudder, M. (2011). A review of chronic and acute physical activity participation on neuroelectric measures of brain health and cognition during childhood. Preventive Medicine, 52 , S21-28. doi: 10.1016/j.ypmed.2011.01.024
Jelalian, E., & Hart, C.N. (2009). Pediatric obesity. In M.C. Roberts & R.G. Steele (Eds.), Handbook of pediatric psychology (4th ed; pp. 446-463). New York: Guilford.
Kitzmann, K. M., Dalton, W. T., III, Stanley, C. M., Beech, B. M., Reeves, T. P., Buscemi, J., . . . Midgett, E. L. (2010). Lifestyle interventions for youth who are overweight: A meta-analytic review. Health Psychology, 29 (1), 91-101. doi:http://dx.doi.org/10.1037/a0017437
Kolotkin R. L., Zeller, M., Modi, A. C., Samsa, G. P., Quinlan, N. P., Yanovski, J. A.,... Roehrig,
H. R. (2006). Assessing weight-related quality of life in adolescents. Obesity, 14, 448-457. doi:10.1038/oby.2006.59
Kovacs, M. (2001). Children's depression inventory (CDI): Technical manual . North Tonawanda, NY: Multi-Health Systems, Inc.
Kovacs, M. & MHS Staff (2011). Children's depression inventory (Second Edition) (CDI 2): Technical manual . North Tonawanda, NY: Multi-Health Systems, Inc.
Luppino, F.S., de Wit, L.M., Bouvy, P.F., Stijnen, T., Cuijper, P., Penninx, B.W.J.H., & Zitman, F.G. (2010). Overweight, obesity, and depression: A systematic review and meta-analysis of longitudinal studies. Archives of General Psychiatry, 67 (3), 220-229. doi:
Lutfiyya, M. N., Lipsky, M. S., Wisdom-Behounek, J., Inpanbutr-Martinkus, M. (2007). Is rural residency a risk factor for overweight and obesity for U.S. children? Obesity, 15 (9), 2348-2356 doi: 10.1038/oby.2007.278
Mei, Z., Grummer-Strawn, L.M., Pietrobelli, A., Goulding, A., Goran, M.I., & Dietz, W.H. (2002). Validity of body mass index compared with other body-composition screening indexes for the assessment of body fatness in children and adolescents. American Journal of Clinical Nutrition, 75 (6), 978–985.
Modi, A. C., & Zeller, M. H. (2008). Validation of a parent-proxy, obesity-specific quality-of-life measure: Sizing Them Up. Obesity, 16 , 2624-2633. doi: 10.1038/oby.2008.416
Must, A. & Anderson, S.E. (2003). Effects of obesity on morbidity in children and adolescents. Nutrition in Clinical Care, 6 (1), 4–12.
Ogden, C. L., Carroll, M. D., Kit, B. K., & Flegal, K. M. (2012). Prevalence of obesity and trends in body mass index among US children and adolescents, 1999-2010. JAMA, 307 (5) 483-490. doi:10.1001/jama.2012.40
Singh, A. S., Mulder, C., Twisk, J. W., van Mechelen, W., & Chinapaw, M. J. M. (2008). Tracking of childhood overweight into adulthood: A systematic review of the literature. Obesity Reviews, 9 (5), 474–88. doi: 10.1111/j.1467-789X.2008.00475.x
Singh, G. K., Siahpush, M., & Kogan, M. D. (2010). Rising social inequalities in US childhood obesity, 2003-2007. Annals of Epidemiology, 20 (1), 40-52. doi:10.1016/j.annepidem.2009.09.008
Steele, R. G ., Aylward, B. S., Jensen, C. D., Cushing, C. C., Davis, A. M., & Bovaird, J. A. ( 2012 ). Comparison of a family-based group intervention for youths with obesity to a brief family intervention: A practical clinical trial of Positively Fit . Journal of Pediatric Psychology, 37 (1), 53-63. doi: 10.1093/jpepsy/JSR057
Suarez, M., & Mullins, S. (2008). Motivational interviewing and pediatric health behavior interventions. Journal of Developmental and Behavioral Pediatrics, 29, 417-428. doi: 10.1097/DBP.0b013e31818888b4
Thompson, J. K., Cattarin, J., Fowler, B., & Fisher, E. (1995). The Perception of Teasing Scale (POTS): A revision and extension of the Physical Appearance-Related Teasing Scale (PARTS). Journal of Personality Assessment, 65, 146–157.
Vivier, P. & Tompkins, C. (2008). Health consequences of obesity in children and adolescents. In E. Jelalian & R. G. Steele (Eds.), Handbook of childhood and adolescent obesity (pp. 11-24). New York: Springer.
Voss, J. D., Masuoka, P., Webber, B. J., Scher, A. I., & Atkinson, R. L. (2013). Association of elevation, urbanization, and ambient temperature with obesity prevalence in the United States. International Journal of Obesity . Advance online publication, 29 January 2013; doi:10.1038/ijo.2013.5
Xanthopoulos, M. S., Moore, R. H., Wadden, T. A., Bishop-Gilyard, C. T., Gehrman, C. A., Berkowitz, R. I. (2013). The association between weight loss in caregivers and adolescents in a treatment trial of adolescents with obesity. Journal of Pediatric Psychology, 38 , 766-774. doi: 10.1093/jpepsy/jst024
Zeller, M. H. & Modi, A. C. (2008). Psychosocial factors related to obesity in children and adolescents. In E. Jelalian & R. G. Steele (Eds.), Handbook of childhood and adolescent obesity (pp. 25-42). New York: Springer.
Zeller, M. H., & Modi, A. C. (2009). Development and initial validation of an obesity-specific quality-of-life measure for children: Sizing Me Up. Obesity, 17, 1171-1177. doi:10.1038/oby.2009.47
Christopher C. Cushing is an assistant professor of Psychology at Oklahoma State University. Cushing earned his PhD in clinical child psychology from the University of Kansas, and completed a residency in behavioral medicine and clinical psychology at Cincinnati Children's Hospital Medical Center. Cushing's research interests center around pediatric health behavior. Specifically, he is interested in using eHealth approaches to assess and promote health behaviors in children and adolescents. Cushing serves on the board of editors for the Journal of Pediatric Psychology and Health Psychology.
Ric G. Steele is a professor of Psychology and Applied Behavioral Science and Director of the Clinical Child Psychology Program at the University of Kansas. He earned his doctorate from the University of Georgia in clinical psychology, completed a clinical internship at the University of Tennessee (Memphis) Professional Psychology Internship Consortium, and completed a Post-Doctoral Fellowship at the St. Jude Children's Research Hospital (Memphis, Tenn.). Steele's research is focused on the promotion of weight-related health in children and adolescents. His grant-funded work includes the development and evaluation of behaviorally based intervention programs for children with obesity and their families. He is an associate editor for the Journal of Pediatric Psychology, and is a co-editor of several professional handbooks, including the Handbook of Childhood and Adolescent Obesity, the Handbook of Pediatric Psychology, and the Handbook of Evidence-Based Therapies for Children and Adolescents.