Comment on Calugi et al. The Role of Weight Suppression in Intensive Enhanced Cognitive Behavioral Therapy for Adolescents with Anorexia Nervosa: A Longitudinal Study. Int. J. Environ. Res. Public Health 2023, 20, 3221

Calugi and colleagues [...].

Weight suppression and body mass index at admission interactively predict weight trajectories during inpatient treatment of anorexia nervosa

OBJECTIVE

Weight suppression refers to the difference between an individual's current and highest body weight at their current height. Higher weight suppression has been found to predict weight gain in both non-clinical samples and patients with eating disorders. Few studies also have reported interactive effects between weight suppression and current body mass index when predicting weight gain.

METHODS

In this retrospective study, we analyzed clinical records of inpatients with anorexia nervosa (N = 2191, 97% female) and tested whether weight suppression and body mass index at admission would interactively predict different weight trajectories during treatment.

RESULTS

Body weight increased non-linearly during treatment. Higher weight suppression predicted larger weight gain but the nature of this effect depended on body mass index at admission. In patients with a relatively low body weight at admission, those with high weight suppression started at a lower weight and showed a nearly linear and steeper weight gain than those with low weight suppression. In patients with a relatively high body weight at admission, those with high weight suppression started at a similar weight and showed a non-linear and larger weight gain than those with low weight suppression.

CONCLUSION

Findings further support that weight suppression is a robust predictor of weight gain in addition to-and in interaction with-current body weight. As weight suppression can easily be assessed at admission, it may help to anticipate treatment course and outcome in patients with anorexia nervosa.

Relationship between impulsivity, uncontrolled eating and body mass index: a hierarchical model

BACKGROUND

Impulsivity increases the risk for obesity and weight gain. However, the precise role of impulsivity in the aetiology of overeating behavior and obesity is currently unknown. Here we examined the relationships between personality-related measures of impulsivity, Uncontrolled Eating, body mass index (BMI), and longitudinal weight changes. In addition, we analyzed the associations between general impulsivity domains and cortical thickness to elucidate brain vulnerability factors related to weight gain.

METHODS

Students (N = 2318) in their first year of university-a risky period for weight gain-completed questionnaire measures of impulsivity and eating behavior at the beginning of the school year. We also collected their weight at the end of the term (N = 1177). Impulsivity was divided into three factors: stress reactivity, reward sensitivity and lack of self-control. Using structural equation models, we tested a hierarchical relationship, in which impulsivity traits were associated with Uncontrolled Eating, which in turn predicted BMI and weight change. Seventy-one participants underwent T1-weighted MRI to investigate the correlation between impulsivity and cortical thickness.

RESULTS

Impulsivity traits showed positive correlations with Uncontrolled Eating. Higher scores in Uncontrolled Eating were in turn associated with higher BMI. None of the impulsivity-related measurements nor Uncontrolled Eating were correlated with longitudinal weight gain. Higher stress sensitivity was associated with increased cortical thickness in the superior temporal gyrus. Lack of self-control was positively associated with increased thickness in the superior medial frontal gyrus. Finally, higher reward sensitivity was associated with lower thickness in the inferior frontal gyrus.

CONCLUSION

The present study provides a comprehensive characterization of the relationships between different facets of impulsivity and obesity. We show that differences in impulsivity domains might be associated with BMI via Uncontrolled Eating. Our results might inform future clinical strategies aimed at fostering self-control abilities to prevent and/or treat unhealthy weight gain.

A systematic review of the methodology used to study weight change among young adults attending college

INTRODUCTION

Young adulthood is a sensitive developmental period that is high-risk for weight gain. Ample research has focused on weight gain among college students; however meta-analyses report <2 kg pooled estimates of weight gain, which is in the range of normal weight fluctuation, and there is disagreement in the literature regarding common predictors of weight gain. These limitations pose a major barrier to targeted obesity prevention efforts. The present study reviewed the literature assessing college weight gain with a focus on three methodological factors that could contribute to variability in the literature: 1) use of an evidence-supported definition of weight gain (>2 kg or ≥3%); 2) weight measurement protocols; and 3) including weight/BMI in analyses of predictors of weight change.

METHODS

Three databases were systematically searched. Studies were included in the review if the primary goal was to determine magnitude of weight change and/or test predictors of weight change during the academic year, and they reported weight at 2+ time points.

RESULTS

A total of 81 studies were included in the review. Most studies (90%; 73/81) did not use an evidence-supported definition of weight gain. Studies that used an evidence-supported definition reported estimates of gain among students who gained weight to be beyond the range of normal weight fluctuation (4.0-7.5 kg), and occurred in a subset (<32%) of participants. Studies that did not use an evidence-supported definition reported weight gain to be 2.0-4.5 kg, and occurred in the majority >50% of students. Most studies that measured height and weight (71%; 42/59) did not use a fasting protocol and the majority (63%; 37/59) did not conduct measurements at the same time of day. A higher percentage of studies that used a standardized measurement protocol reported weight change >2 kg (44% vs 20%). A lower percentage of studies that used a standardized measurement protocol had substantial variability in weight change estimates (50% vs 69%). The majority of studies that tested predictors of weight gain (74%; 42/57) included weight/BMI as a covariate in analyses.

CONCLUSIONS

The body of literature examining weight change among college students suffers from limitations that may have contributed to overestimations in the percent of students who gain weight, and simultaneous underestimations of the magnitude of weight gain among those who gain weight. Weight gain may be limited to approximately 30% of students in a sample, and weight gain among this subset of students may be substantial (>4 kg). Going forward, use of both an evidence-supported weight gain definition and fasting measurement protocol will likely enhance accuracy in characterizing weight gain among college students, as well as improve researchers' ability to detect important predictors of weight gain.