Loss to follow-up in a randomized controlled trial study for pediatric weight management (EPOC)

Attrition is a serious problem in intervention studies, which can threaten reliability and validity for several reasons: First, when participants drop out of a study, analyses are limited to a smaller sample, which can lead to insufficient statistical power. Second, although participants may drop out for various reasons, some of these can be related to the outcome. Third, the drop-out pattern may differ between treatment groups, altering the random composition of the groups and leading to confounding influences. Therefore, high attrition rates can cause a significant bias in the study. Such a bias might alter the characteristics of a sample and impede the comparability to the original sample. Moreover, the bias might alter the covariance of the variables included, possibly affecting outcomes or other correlated variables (as reviewed by Ahern [1]).

Reviewing the attrition rates in randomized controlled studies of chronic illness in childhood, Karlson and Rapoff [2] reported that on average, 37 % (range 0–75 %) refused to take part in the study at the beginning, 4 % (range 0–35 %) provided no baseline data, 20 % (range 0–54 %) no initial follow-up data, and 32 % (range 0–59 %) no long-term follow-up data. The majority of the studies did not analyze differences between completers and non-completers. Collins et al. [3] assessed the efficacy of dietetic interventions for children with obesity. From the 37 randomized controlled trials (RCT) they extracted, 26 included follow-up data (1 month to 10 years). Attrition rates during follow-up varied from 5 to 37 %. Only 9 studies reported efficacy data on the basis of an intention-to-treat analysis.

In general, only a small number of studies have reported explicit loss at follow-up. In a recent family-focused intervention study [4], approximately 20 % of participants dropped out at the follow-up assessments. These children were significantly older and had a higher body mass index (BMI) z-score at baseline. This is in line with the findings of van den Aker et al. [5]_, who reported an attrition rate of 33 % at the 1-year follow-up, with drop-outs being older and less successful during treatment. McCallum et al. [6] stated that the children lost in follow-up were slightly heavier, and that their parents reported a lower quality of life for their children. Unfortunately, it was not reported whether these differences were statistically significant. Hughes et al. [7] observed a 34.9–36.9 % loss during follow-up 12 months after the start of treatment, and did not report any demographic differences between completers and non-completers. This is in line with the data of Savoye et al. [8], who found no differences between completers and non-completers with respect to baseline characteristics (BMI, age, gender).

Other studies examined the determining factors for drop-out during treatment [9], with fairly inconclusive results, as almost no overlap was found between the indicators analyzed. Although some studies reported a higher attrition rate for those with a higher BMI z-score [10–13], others did not find a significant effect (n.s. [14, 15]), older age [10, 11, 13] (n.s. [14–16]), ethnic minority status [10, 14, 15] (n.s. [11, 16]), lower socioeconomic status (SES)/education (trend [17]; n.s. [12, 16]) or psychological problems [10, 13, 17] (n.s. [11, 12]). Consistently, no study reported gender effects [11–13, 15–17].

To be able to adequately interpret study results, it is crucial to achieve high retention rates in intervention research. Participants’ motivation to devote time and effort to filling in questionnaires or attending medical check-ups will decrease over time, and this may be particularly true when treatment takes place in inpatient facilities that are far from patients’ homes. Hence, knowledge regarding predictors of attrition during follow-up in clinical trials is limited. Therefore, we analyzed the data of a large randomized controlled study (Empowering Parents of Obese Children – EPOC study) in order to examine which factors predicted failure to provide objective weight-related measurements. We hypothesized that parents with a lower educational background and children experiencing less success during treatment and higher psycho-social strain would return objective weight data less frequently.

At the end of the intervention, the data of one child could not be obtained. Therefore, only the data from 522 children were available. Complete weight and height data were available for 259 (49.6 %) children at the 6-month follow-up and for 350 (67.0 %) at the 12-month follow-up.

Attrition is a highly relevant and prevalent problem in pediatric weight management trials. In the current study, we observed an attrition rate of 33.0 % at the 12-month follow-up. Our results are in line with those reported in the literature [3, 5, 7]. A recent review reported higher attrition rates in studies that focused on children with overweight or obesity (79.6 %) as well in long-term studies (74 %) [28]. Based on the results of a previous study assessing parental factors which might impede or facilitate their participation [29],⁸ we assumed time and financial constraints to be important. Therefore, we used an expensive and time-consuming method (re-sending questionnaires and reminder postcards, repeated telephone calls, offering home visits and financial incentives). These strategies were considered as successful retention strategies to facilitate parents’ participation and receive the long-term data [30]. We assume that this strategy did at least pay off a little, since we invested the greatest efforts before the second follow-up and the attrition rate at 12 months was slightly lower than that at the 6-month follow-up. Nevertheless, the attrition rate was high, and retention rates fell below our expectations. Further studies are needed to indicate empirically validated retention strategies. In order to enhance study commitment and decrease attrition, the study by Germann et al. [31] used an orientation session to give information about achievable and healthy weight loss. We agree that this might be helpful in decreasing the number of unsuccessful weight loss attempts, but it also excludes many individuals with weight problems and focuses only on highly motivated patients. Further research is needed on how to increase the retention rate in clinical trials, especially when not only self-reports but also physiological measurements are required [28].

BMI at baseline and weight loss during intervention are often reported to influence the drop-out in obesity interventions. With respect to the baseline BMI, we observed a higher drop-out rate in families whose children were heavier at baseline [4, 6]. In line with other reports [4, 5, 10], a lower initial weight loss increased the risk of not returning the follow-up assessments in our study. However, analyzing the variables in a multivariate model, only weight loss during intervention remained significant in terms of predicting drop-out at the 6-month follow-up, whereas at the 12-month follow-up, neither the baseline weight status nor the initial weight loss was relevant for individual attrition. Moreover, only at the short-term follow-up did drop-out rates differ between treatment groups, with parents in the intervention group seemingly more willing to return the follow-up data. This group took part in a weekend seminar, which stressed the important role of the parents in supporting their child. Since the two treatment groups did not differ in terms of BMI-SDS, this observation is not merely an effect of treatment effectiveness.

Previous research results concerning the socio-demographic data were controversial. We observed no influence from the child’s age, which contradicts the results of two other studies [4, 5]. Consistent with the literature, no effects of gender were observed [4, 5, 7, 8]. In our study, parents’ age influenced the retention rate for the short-term follow-up, an effect that was no longer visible 6 months later. Only at the 12-month follow-up was a higher level of parents’ education associated with a higher retention rate. We are aware of only one study in the field of pediatric weight management that reported similar results, even if only as tendencies [17]. With regard to psychological characteristics, the available evidence is sparse. In line with our observation regarding the differences between completers and non-completers, McCallum et al. [6] indicated that those who dropped out reported a lower quality of life for children. In addition, we found more psychological problems reported by the parents in the drop-out group. This concurs with the findings, with respect to prematurely stopping the intervention [10, 13, 17]. However, the reported differences in psychological characteristics in this study were not independent predictors in the multivariate logistic regression.

Further aspects that differ between the groups were the eating environment, in which a low degree of family meal structure remained a significant predictor for attrition at 12 months after intervention. The influence of the family eating environment may be interpreted as sign of a successful change in family habits – a major goal in pediatric weight loss interventions [32, 33]. In addition, studies from family-oriented intervention approaches suggest that parents play a key role in sustaining the treatment effect at the long-term follow-up [34, 35]. Our results are further supported by the data of other reports that stress parental influence in treatment adherence [10, 17].

Our study is limited in several ways. First, we could not assess any data at the follow-up measurements concerning the reasons for discontinuing the study. Some participants reported that when called by phone, they lost interest and that completing the questionnaires was too time-consuming. This is in line with the data reported by Savoye et al. [8]. and with our previous study [29]. In addition, our analyses were exploratory and we included many variables. We decided to take that path in order to not miss relevant features, and were willing to accept the increased risk of overestimating the clinical significance of the results. Furthermore, we also ran multivariate analyses in order to combat alpha error inflation. When interpreting our results in terms of comparing the pattern of short- and long-term follow-up data, it should be noted that we invested much more effort in gathering long-term data. Especially at the 12-month follow-up, we successfully contacted those parents who had simply forgotten to fill in the questionnaires due to time constraints or other priorities. Thus, we were able to observe differences otherwise obscured by organizational problems reported by the majority of parents [8].

An important strength of our study is that we collected data from a highly diverse and representative sample of participants, rather than only including those families with a higher level of education or income. Moreover, the weight data were based on blind assessment, thus decreasing the risk of underreporting weight status (see self-reported measurements) [36].

Our study results suggest that the strategies to reduce the attrition rate, which we employed after the first follow-up, were successful, but still could not prevent a final attrition rate of over 33 % for the second follow-up.

We were able to replicate differences between completers and non-completers found in previous studies. However, we observed a different pattern of predictors between the short-term (6 months) and long-term (12 months after intervention) follow-ups. De Niet et al. [10] also found different predictors for attrition at different stages of treatment. Whereas at the 6-month follow-up, mainly aspects associated with the intervention (randomization in the intervention group and initial weight loss) predicted the retention, at the 12-month follow-up, only family aspects such as educational level and family eating environment remained predictive. These differences indicate the risks inherent in only including a short-term follow-up, which might be biased in terms of success rates – especially when drop-out rates are high. Taking into account that in particular, short-term success in weight management does not necessarily imply positive long-term results, intervention studies should include longer follow-up periods and report their results on the basis of intention-to-treat analyses.