There is a growing body of literature on the efficacy of clinical interventions to address child and adolescent obesity. Consistent with what has been reported, we demonstrate an improvement in weight status in response to a multidisciplinary intervention aimed at changing diet and physical activity behaviors. Recent studies suggest that clinic-based interventions such as the WATCH clinic that focus on lifestyle modification can decrease BMI z-score by 0.03-0.05 over approximately 1 year of follow-up13,21
Improvements in weight status, such as those demonstrated herein, have been associated with improvements in lipid profiles21
. However, larger decreases in BMI z-score may be necessary for additional cardiovascular benefit, particularly improved insulin sensitivity. In a follow-up study among 7-15 year-old obese children. and adolescents, Reinehr et al.
found that only patients who decreased their BMI z-score by 0.5 units improved insulin sensitivity22
. Interventions that have achieved this magnitude of improvement in weight status have involved more frequent visits, structured family programs, and delivery of a group exercise component10,23,24
. These programs represent best-practice for the treatment of severe obesity in youth and are consistent with the current guidelines, which recommend weekly visits for a minimum of 8-12 weeks with subsequent monthly visits25
. However, they have required NIH funding for enactment10,23,24
and are difficult to replicate in the clinical setting. Interventions such as the WATCH clinic would be more easily replicated but, because they are constrained by clinical revenues that limit follow-up to every 1-3 months13,15,21
, are likely to show more modest improvements in weight status. Further research will be needed to assess the impact of lower-intensity clinics on measures of cardiovascular risk.
Given what can be accomplished in ‘real-life’ clinic-based obesity programs, it is important to determine which patients will require more intensive treatment. While many studies have attempted to identify baseline characteristics that predict response, most have dichotomized patients into responders versus non-responders (generating odds ratios for predictors). Instead, we used a linear regression model for two reasons. First, a continuous outcome variable better represents the spectrum of response seen in pediatric obesity clinics, in which many patients make small changes; dichotomizing is more appropriate when dealing with a cohort of patients with extreme responses. Second, when both predictor and outcome are naturally continuous, correlations are the preferred method for determining the amount of variance in the outcome that can be explained by the predictor. This is particularly important when examining predictors from a clinical practice perspective. A variable may significantly predict response, but still explain only a small portion of it.
We found that response at the first visit was the strongest predictor of response at the ultimate visit, accounting for approximately 20% of the variance. This is similar to studies with follow-up ranging from 1 to 10 years23,26-28
, demonstrating that initial response was a strong predictor of long-term success. Initial success may generate some self-confidence and beget greater self-efficacy for adhering to clinic recommendations, as was seen by Braet in an in-patient treatment program27
. Alternatively, environmental, familial, or behavioral factors may preclude some patients from adhering to recommendations at the first visit, and such barriers are likely to continue to exert an effect at subsequent visits. Our data suggest that the first follow-up visit is an important visit at which to re-examine strategy and consider moving to more aggressive therapy, such as pharmacotherapy or compUlsory physical activity, particularly for adolescents who were severely overweight at baseline.
Unlike information available at the first follow-up, baseline characteristics are much less consistent in the literature in their ability to predict response. We found that greater obesity at baseline was associated with poorer response at first and ultimate follow-up, explaining up to 10% of response to the intervention. While Eliakim et al.29
and Pinhas-Hameil et al.13
also found greater baseline obesity predicted poor response to a lifestyle intervention, other investigators found the opposite23,27
. Among these studies, no single feature related to study participants (such as age, race, or obesity severity) or the intervention itself (such as visit frequency or intervention components) appears unique to either those showing a positive or negative impact of baseline weight status on response. Therefore, it is unclear what factor might modify the effect of baseline weight status on response, and thereby explain the inconsistency of these results.
Our study also implicates insulin resistance in poor initial response to the lifestyle intervention. While insulin resistance was no longer predictive at ultimate follow-up, two other studies have suggested that greater insulin resistance may predict poorer response13,14
. Conversely, a recent study found greater insulin resistance predicted better
response; however, this study was short (12 weeks) and overall, patients tended to increase their BMI z-score15
. While further research may confirm the relationship between greater insulin resistance and poor response, insulin alone explained only 6% of the variance in response in our diverse cohort, similar to results from another clinic-based intervention13
. From the clinician's perspective, knowing a patient's insulin resistance is unlikely to change recommended treatment at the outset. As the new Endocrine Society guidelines suggest, although obtaining fasting insulin is optional, it is an expensive test that is not necessary to establish the need for weight loss30
. Further, while insulin resistance has been proposed as a means of identifying children at high-risk for diabetes mellitus and cardiovascular disease, its use as a screening tool for therapy will require the development of effective options specific to insulin resistant youth.
Our diverse population allowed us to explore differences in response by race. While each subgroup was relatively small, African-American patients tended to show a lesser response to the intervention at both initial and ultimate follow-up than did their peers. This may suggest that our intervention lacks cultural relevance for African-Americans, or that these adolescents face greater barriers to adherence. Alternatively, the differential response by race may reflect underlying physiological differences, as some research suggests31-34
. Further work should be done to design and evaluate culturally appropriate therapies to ensure that children and adolescents of all ethnic backgrounds receive the best possible care.
We report modest correlations between behavioral variables, such as sugared beverage and breakfast consumption, and response to this intervention. Actual correlations might well be higher; behaviors were generally assessed using single questions at the intake clinic, which likely decreases response accuracy and underestimates the relationship between behaviors and response. Unfortunately, behavioral variables are difficult to assess in the clinical setting, as most measures of behavior are self-reported and prone to social desirability bias35
We recognize additional limitations of our study. Poor follow-up is a common problem in weight management programs36
, and while duration of follow-up did not predict response, it is likely that patients with no follow-up are different from those who return for follow-up. Additionally, our average follow-up time of 10 months is inadequate to describe the persistence of short-term treatment effects. Some data exist on the long-term impact of high-intensity obesity treatment programs23,26
, but to our knowledge, none currently exist for ‘real-life’ obesity clinics. Longer follow-up will be essential to better elucidate the comparative efficacy of different approaches to obesity treatment.
The current study may have lacked the statistical power to identify other predictors of response, such as interactions between race and other potential predictors of therapeutic response. Further, we did not directly assess socio-economic status, nor did we examine other potential predictors, such as degree or compartment of adiposity, or leptin level.
Our findings demonstrate that response at first follow-up visit is likely to be a valuable means of identifying children in need of more intensive therapy. Severely overweight youth who did not respond to the initial lifestyle counseling in the present study were unlikely to change their trajectory. While evidence is mounting to describe the most efficacious interventions, identifying funding mechanisms for these strategies in the real-world will be critical to addressing the problem of pediatric obesity.