Randomized Controlled Trial to Improve Primary Care to Prevent and Manage Childhood Obesity:  The High Five for Kids Study FREE

In the United States, approximately 21.2% of children aged 2 to 5 years are overweight (age- and sex-specific body mass index [BMI] in the 85th-94th percentile) and 10.4% are obese (BMI ≥ 95th percentile).¹ Preschool-aged children who are overweight, especially those with overweight parents, tend themselves to become obese as adults² and are at high risk of short-term³ and long-term adverse outcomes.^4- 8 The pediatric primary care team is well positioned to provide effective interventions to promote healthful behaviors among families of young children. Well-child visits occur at least annually from ages 2 through 6 years and additional problem-oriented visits provide other opportunities to develop a relationship with the child and family. The continuity of the relationship between pediatricians and families, embodied in the concept of the “medical home,”⁹ promotes receptivity to suggestions for changes in health-related behaviors.¹⁰

Few interventions to prevent childhood obesity have been conducted in the primary care setting.^11- 23 Only 1 primary care–based randomized controlled trial²³ and 2 nonrandomized trials have focused on children younger than 6 years.^19- 20 In the Live, Eat, and Play (LEAP) randomized controlled trial of 2112 children aged 5 to 9 years in Australia,²³ consultations with general practitioners on obesity-related behaviors did not result in significant BMI reduction at 9 or 15 months postenrollment. In a nonrandomized study of 1128 children aged 3 to 6 years who attended primary care clinics in Singapore, Ray et al¹⁹ found that nurse-led counseling sessions were effective in reducing obesity prevalence. In another nonrandomized trial conducted within US-based primary care pediatric offices, motivational interviewing by pediatricians and dietitians was effective in reducing BMI percentile among 91 overweight children aged 3 to 7 years.²⁰ Although each of these studies showed the feasibility and, in some, the effectiveness of primary care–based interventions for obesity management, none of these trials involved the entire primary health care team; 2 were further limited by their nonrandomized design; and the 1 US-based study had a small sample size.

The purpose of this study was to assess the extent to which a primary care–based intervention, compared with the usual care control condition, resulted in a smaller increase in BMI and improvement in obesity-related behaviors among children aged 2 through 6 years at elevated risk of obesity.

High Five for Kids is a cluster randomized controlled trial in 10 primary care pediatric offices of Harvard Vanguard Medical Associates, a multisite group practice in Massachusetts. The intervention duration is 2 years and includes an intensive 1-year intervention period followed by a less intensive maintenance period. This article reports the results after the first year of intervention. To pair practices in preparation for blocked, or stratified, randomization, we first divided the practices into the biggest 4 and smallest 6, then matched within those groups as closely as possible on racial/ethnic composition. Within each of 5 pairs, a computerized routine randomly allocated one practice to the intervention group and one to the usual care control group.

Participants comprised children aged 2.0 to 6.9 years whose BMI (calculated as weight in kilograms divided by height in meters squared) was in the 95th percentile or higher or whose BMI was in the 85th to less than 95th percentile if at least 1 parent was overweight (BMI ≥ 25) and who received their pediatric care at Harvard Vanguard Medical Associates between August 2006 and October 2008. We excluded (1) children whose parent or guardian could not respond to interviews in English or Spanish, (2) children whose families were planning to leave Harvard Vanguard Medical Associates, (3) families for whom the primary care clinician thought the intervention was not appropriate, and (4) children with chronic medical conditions.

Using the electronic medical records, we identified 3253 children who had a BMI in the 85th percentile or higher sometime within the year prior to their index well-child care visit. After each pediatric provider offered medical clearance, and approximately 1 month prior to the child's scheduled well-child care visit, we mailed a letter to each parent introducing the study. The letter included an opt-out telephone number to call if the family did not want to participate. We telephoned those individuals who did not opt out within 7 days after mailing the letter. During the telephone call, research staff conducted a baseline interview and mailed a written informed consent to parents. Research assistants assessed parental BMI by interview. Participants were enrolled once we confirmed their BMI at the scheduled well-child care visit and we received written informed consent.

At 1 year, participants completed a telephone interview with research staff and had their heights and weights measured as part of their annual well-child care visit. We offered all participants $20 for completing each telephone interview. We also reimbursed intervention participants for the co-pay incurred at each visit with the nurse practitioners. All study procedures were approved by the human subjects committee of Harvard Pilgrim Health Care.

Participants randomized to usual care received the current standard of care offered by their pediatric practice. This included well-child care visits and follow-up appointments for weight checks with their pediatrician or a subspecialist (eg, nutritionist). Visits for families in the usual care group included the baseline and annual well-child care visits.

The overarching model for this intervention was the Chronic Care Model,²⁴ which posits that changes in primary care to produce functional patient outcomes require changes for all members of the practice team (Figure 1). Major components of the intervention involved changes to the health care system. We trained all members of the practice team to play an active role in the intervention. We enhanced the electronic medical record system to assist clinicians with decision support, patient tracking, follow-up, scheduling, and billing (Figure 1). After reorganization of the delivery of primary and acute care, the pediatric nurse practitioners conducted chronic disease management visits with intervention participants. Prior to the start of the intervention, we negotiated with the regional insurance companies to pay for up to 4 visits for both overweight and obese patients in the first year of the study.

We trained the pediatric nurse practitioners to be the key intervening clinicians and to use motivational interviewing during four 25-minute, in-person chronic disease management visits and three 15-minute telephone calls in the first year of the intervention. Motivational interviewing is a communication technique that enhances self-efficacy, increases recognition of inconsistencies between actual and desired behaviors, teaches skills for reduction of this dissonance, and enhances motivation for change.^25- 28 Components include de-emphasizing labeling, giving the parent responsibility for identifying which behaviors are problematic, encouraging parents to clarify and resolve ambivalence about behavior change, and setting goals to initiate the change process.^25,27- 28 We trained the primary care pediatricians in the intervention practices to use brief, focused negotiation skills²⁹ at all routine well-child care visits to endorse family behavior change. Brief, focused negotiation is based on the concepts of motivational interviewing but tailored for brief sessions such as the clinical encounter. To ensure accurate measurements of heights and weights, we trained all medical assistants in intervention and usual care practices on conducting research-standard anthropometric measurements. We also trained the medical receptionists to schedule initial and follow-up visits with the nurse practitioners based on the study protocol.

We developed several resources to assist the physicians and nurse practitioners in supporting participants and their family in behavior change. For the patient waiting rooms, we created posters highlighting our targeted behaviors to encourage dialogue during well-child care visits (Figure 2). For the chronic disease management visits with the nurse practitioners, we developed educational modules targeting television viewing and fast food and sugar-sweetened beverage intake that were matched to a family's stage of readiness to change²⁷; printed and electronic tools for self-management support; lists of local resources for physical activity; and an interactive Web site with educational materials, recipes, and other features. To further support behavior change, the nurse practitioners provided small incentives such as water bottles, books, and snack containers. In addition, the nurse practitioners offered interested families an electronic television monitoring device to assist with the goal of reducing television viewing.

Our primary outcome was change in BMI from baseline to 1 year. Medical assistants measured children's weight, without shoes, using an electronic, calibrated scale (Seca, Birmingham, United Kingdom) and height using a stadiometer. We calculated BMI and age- and sex-specific BMI z scores and percentiles.³⁰

The behavioral goals for children in the intervention were less than 1 h/d of television and video viewing, removing the television from or avoiding putting a television in the room where the child sleeps, 1 serving/wk or less of fast food, and 1 serving/d or less of sugar-sweetened beverages. To assess average daily television and video viewing, we used previously validated questions.³¹ We also asked if the child had a television in the room where he or she sleeps. We measured daily sugar-sweetened beverage intake using questions from a validated semiquantitative child food frequency questionnaire³² and we measured fast food intake using a single question shown to be associated with BMI in an adolescent cohort.³³ We also measured the child's daily fruit and vegetable intake³⁴ and outdoor physical activity time.³⁵ During interviews with research staff, the parent who brought the child to his or her well-child care visit reported his or her height and weight range, from which we estimated his or her BMI. Research assistants asked the parent to report the height and weight of the child's other parent. Parents also reported their educational attainment, marital status, annual household income, and their child's race/ethnicity.

We culled data from the electronic medical record on completed visits and telephone calls. To assess parents' acceptance of and satisfaction with the intervention components, we asked parents in the intervention group during the 1-year interview to rate how satisfied they were with the program. We also asked parents if they would recommend the program to their family or friends and whether they had chosen to work on specific behaviors.

We first examined baseline distributions of child and parent characteristics by intervention status. In intent-to-treat analyses, we used crude and adjusted multivariate regression models, corrected for clustering by practice, to examine differences from baseline to 1 year between the intervention and usual care groups. For continuous outcomes, we used linear regression models, and for dichotomous outcomes, we used logistic regression models. For all models, to account for intraclass correlation, we performed generalized linear mixed models that accounted for clustering by practices (PROC GLIMMIX in SAS version 9.2; SAS Institute Inc, Cary, North Carolina).

Figure 3 shows the participant flow in the High Five for Kids study. We enrolled 271 children in the intervention group and 204 in usual care. Two hundred fifty-three participants in the intervention group (93% of those enrolled) and 192 participants in usual care (94% of those enrolled) completed a 1-year telephone interview and well-child care visit for BMI measurement. Table 1 shows characteristics of our study sample overall and by intervention assignment. At baseline, mean (SD) BMI was 19.2 (2.6) among intervention children and 19.1 (2.0) among usual care children and BMI z scores were 1.88 (0.69) and 1.82 (0.56), respectively. Fifty-three percent of intervention children had a BMI in the 95th percentile or higher vs 60% of usual care children. Children randomized to the intervention group were more likely to be racial/ethnic minorities, have an obese parent, and live in lower-income households (Table 1). There were no group differences at baseline in health behaviors (Table 1).

Table 2 shows participants' BMI at baseline and at 1 year by intervention assignment. At 1 year, BMI had increased by a mean of 0.31 in the intervention group and 0.49 in the usual care group, yielding a crude difference of −0.19. After multivariable adjustment, compared with usual care, intervention participants had a smaller, nonsignificant change in mean BMI from baseline to 1 year than usual care participants (−0.21; 95% confidence interval [CI], −0.50 to 0.07; P = .15). We observed similar results using change in age- and sex-specific BMI z score as the outcome (−0.05 unit; 95% CI, −0.14 to 0.04; P = .28). In post hoc stratified analyses, we observed statistically significant intervention effects on BMI among girls (−0.38; 95% CI, −0.73 to −0.03; P = .03) but not boys (0.04; 95% CI, −0.55 to 0.63; P = .89) and among participants in households with annual incomes of $50 000 or less (−0.93; 95% CI, −1.60 to −0.25; P = .01) but not in higher-income households (0.02; 95% CI, −0.30 to 0.33; P = .92).

Table 3 shows baseline and 1-year levels of our behavioral outcomes. In adjusted models, intervention participants decreased their television and video viewing more than usual care participants (−0.36 h/d; 95% CI, −0.64 to −0.09; P = .01). We also observed greater decreases in fast food intake (−0.16 serving/wk; 95% CI, −0.33 to 0.01; P = .07) and sugar-sweetened beverage intake (−0.22 serving/d; 95% CI, −0.52 to 0.08; P = .15), though the confidence intervals for these effects did not exclude a null effect. For the dichotomous outcome of television in the room where the child sleeps, we did not observe an intervention effect (Table 3).

Over their multiple visits and telephone calls, participating families could choose to work on 1 or more behavioral targets. Of the 253 participants in the intervention group, 68% chose to work on decreasing their child's sugar-sweetened beverage intake, 62% chose to work on decreasing their child's fast food intake, 63% chose to work on decreasing their child's television and video viewing, but only 9% chose to work on removing the television from or avoiding putting a television in the room where their child sleeps. We stratified models by whether the family chose to work on the behavior and used usual care as the comparison for each model. In these stratified analyses, we observed greater intervention effects among participants who chose to work on specified behaviors (Figure 4).

We aimed for intervention participants to complete 6 intervention activities with the nurse practitioner by 1 year. Among the 253 intervention participants, 141 (56%) had completed at least 2 of 6 activities. Compared with usual care, intervention participants who completed 2 or more activities by 1 year had greater decreases in television and video viewing (−0.58 h/d; 95% CI, −0.92 to −0.24; P = .001) and sugar-sweetened beverage intake (−0.31 serving/d; 95% CI, −0.74 to 0.12; P = .15). Intervention participants with fewer than 2 activities by 1 year had only minimal decreases in their television and video viewing (−0.04 h/d) and sugar-sweetened beverage intake (−0.02 serving/d). There was no difference in BMI or fast food intake change based on adherence to the intervention protocol.

Based on follow-up questions of the 253 intervention participants, 97% reported being “somewhat” or “very satisfied” with the High Five for Kids program and 91% reported they would recommend the program to their family and friends.

In this 1-year follow-up of a primary care–based, cluster randomized controlled trial we found that a multicomponent obesity intervention based on the Chronic Care Model improved television and video viewing particularly among families who chose to work on reducing television time and removing or avoiding putting a television in the room where the child sleeps. Children in the High Five for Kids intervention group had a smaller, but nonsignificant, increase in BMI overall. In addition, in post hoc analyses, the intervention significantly improved BMI among girls and those living in lower-income households.

To our knowledge, the High Five for Kids study is the first randomized controlled trial in a primary care setting aimed at reducing obesity among preschool-aged children. A recent review of primary care–based interventions for treating overweight and obese children and adolescents²² identified no moderate- to high-intensity interventions for children younger than 6 years and only the LEAP trial,²³ a low-intensity intervention that involved consultations with general practitioners on nutrition, physical activity, and sedentary behavior, included children 5 years and older. Our intervention was also innovative in that we attempted to effect sustainable changes in the health care system to prevent and manage childhood obesity. We recognized that the complexity of childhood obesity as a chronic medical problem required a new paradigm to improve obesity-related outcomes. Thus, based on the Chronic Care Model, the High Five for Kids intervention involved changes in the roles and responsibilities for the entire practice team and retraining of clinicians to support family behavior change, as well as updating clinical information systems and providing families links to their community for physical activity. We designed intervention components to be sustainable in a “real-world” primary care setting by training existing clinical staff to deliver the intervention. The intervention was also designed to be of moderate to high intensity requiring 6 intervention activities over a 1-year period.

In our intervention, the overall adjusted mean difference (intervention vs usual care) in BMI was −0.21 at 1 year. This magnitude of effect is very similar to that of the LEAP study²³ in which the adjusted mean difference in BMI was −0.20 (95% CI, −0.6 to 0.1) at 9 months. Several factors could have contributed to the lack of a statistically significant intervention effect on BMI. First, our intervention involved only the primary care setting and not children's communities or environment. It is possible that primary care–based interventions alone will not effect change in BMI but could complement and potentially enhance more comprehensive efforts in multiple settings. Second, adherence to intervention activities was relatively low; a little more than half of the participants completed at least 2 of the 6 visits/telephone calls. It is possible that the intervention “dose” delivered was not sufficient in effecting changes in BMI. Third, we taught the nurse practitioners to use motivational interviewing to structure their visits and telephone calls. Parents were provided a choice of behaviors to work on in a nonprescriptive style and this could have led to parents choosing behaviors that could have had a lower impact on BMI, eg, fruit and vegetable intake. Fourth, it is possible that BMI changes might lag behind the behavioral changes we observed in our intervention. Thus, we will evaluate the effect of the intervention after the planned 2-year intervention period.

Cross-sectional,^36- 38 longitudinal,^39- 40 and experimental^41- 43 evidence suggest that television viewing and televisions in bedrooms are associated with obesity risk in children. Although several interventions have attempted to reduce television viewing, only 3 published studies have included children younger than 6 years,^41- 42,44 only 2 of which successfully decreased television viewing.^41- 42 Using intervention strategies similar to Dennison et al⁴¹ and Epstein et al,⁴² we found that children in the intervention group decreased their television and video viewing by 0.36 h/d. The magnitude of effect was higher (−0.58 h/d) if parents chose to work on reducing their child's television and video viewing. This magnitude of effect was similar to the 2 published interventions that included preschool-aged children. Our results lend support to multimodal interventions to reduce television viewing among young children.

We observed greater intervention effects among female participants and among those living in lower-income households. It is possible that the sex differences we observed could be due to parents of girls being more attuned to issues of weight, diet, and activity and could have been more responsive to the intervention. A similar sex difference in intervention effect has been shown in other childhood obesity intervention studies.⁴⁵ Participating children living in lower-income households had higher BMIs at baseline. It is possible the intervention was more effective among these children because they had more “room to move.” These findings deserve further investigation.

This intervention had several limitations. First, although we attempted to match the pediatric sites to obtain similar participant characteristics in intervention and usual care, unbalanced participant characteristics at baseline occurred. This imbalance may have also affected differences in parent obesity and household income. However, adjusted and unadjusted results were similar, suggesting that any imbalance in observed (or unobserved) characteristics did not affect inferences. Second, electronic medical records, which we used for decision support and recruiting and tracking of intervention participants, are not available in all pediatric practices. Thus, our intervention may not generalize to all pediatric settings. Third, although we used validated measures to assess our behavioral outcomes, we used parental report of behaviors rather than objective measures. Thus, it is possible that parents could exaggerate self-reported improvements in behaviors. For this reason, our primary outcome was BMI, a more objective measure. Fourth, because our intervention was not a factorial design, we are not able to specifically say which components were more effective. However, our results indicate that participants with more fidelity to protocol had greater improvement in their behaviors, possibly indicating that with greater fidelity to protocol, we could have had greater magnitudes of effects.

In summary, after 1 year, we found that the High Five for Kids study improved television-viewing behaviors among preschool-aged children but did not have significant effects on BMI or diet-related behaviors. We plan further follow-up to evaluate the intervention effects over a longer period and examine the components of such an intervention that are maximally effective, scalable, and cost-effective.