Citations

Abstract Anorexia nervosa (AN) and atypical AN are distinguished by the presence or absence of a significantly low body weight. In children and adolescents, the population-based age- and sex-adjusted weight characteristics, BMI centile, BMI z-score (BMIz), and percentage of median BMI (%mBMI) are used to diagnose underweight. Whereas BMI centile and BMIz are interconvertible, %mBMI is not. We extend previous analyses to illustrate a) age- and sex-dependent discrepancies between %mBMI and BMIz and b) the non-linear relationship between BMIz and absolute body weight. Based on Centers for Disease Control growth charts, BMIz corresponding to the 65, 75, and 85%mBMI were determined for males and females aged 10 to 18 years. Body weights (in kg) corresponding to BMIz ranging from 0 to -7 (based on average heights) were also calculated and compared. Throughout the age span, BMIz corresponding to 65%mBMI ranged from − 5.0 to -6.9 in males and − 4.5 to -5.2 in females; at 75%mBMI, from − 2.9 to -3.6 in males and − 2.6 to -2.9 in females; and at 85%mBMI, from − 1.4 to -1.7 in males and − 1.3 to -1.4 in females. Body weight increments (in kg) per 1 BMIz were non-linear and dependent on reference BMIz. Transformations between %mBMI and BMIz are not linear, and these characteristics cannot be used interchangeably. Use of both BMIz and %mBMI in eating disorder research limits meta-analyses. Field consensus for universal weight-related assessment in adolescents is necessary.

ABSTRACT Introduction In hospitalised patients with both anorexia nervosa (AN) and atypical AN, premorbid body mass index (BMI; kg/m 2 ), estimated from premorbid weight (i.e., weight at the onset of weight loss preceding eating disorder development) and admission height, strongly predicts admission weight loss (i.e., premorbid weight minus admission weight). We hypothesised that maximal weight loss (i.e., maximal historical weight minus minimal weight since eating disorder onset) is also correlated with maximal BMI. Methods In 520 female adolescents with AN ( n = 503) and atypical AN ( n = 17), relationships between admission age, admission and maximal weight loss, and maximal and minimal BMI were analysed with non‐parametric Spearman’s correlation coefficients. Results Like premorbid BMI in previous studies, maximal BMI was strongly correlated with maximal weight loss. Discussion Maximal BMI appears to be a sound substitute for premorbid BMI in correlations with admission weight loss in hospitalised adolescents with AN and atypical AN. Consistent use of maximal (vs. premorbid) BMI and admission (vs. maximal) weight loss in research would align with the metric weight suppression (derived from both maximal and current weight), thus facilitating cross study comparisons. Additional studies should assess correlations between both premorbid and maximal BMI and admission or maximal weight loss to attempt to identify the variables with the highest predictive value.

ABSTRACTBackgroundBecause premorbid BMI strongly predicts the amount of weight loss in anorexia nervosa (AN)/atypical AN, we hypothesize that weight loss triggers both disorders by inducing the endocrine adaptation to starvation.MethodWe propose research to capture the onset of AN/atypical AN following intentional, otherwise behaviorally motivated, or unintentional weight loss in relationship to premorbid weight.ResultsWe propose retrospective and prospective studies to examine the temporal development of symptoms in AN/atypical AN. Given a greater frequency of weight loss behaviors in individuals with high BMIs, patients with intentionally driven weight loss should demonstrate a higher mean weight loss and greater premorbid weight and shape concerns. Practice guidelines necessitate weight gain for AN recovery, yet how weight gain induces improvements is unspecified and warrants systematic elucidation. Finally, we highlight implications for the current conceptualization of genetic and environmental contributors of AN/atypical AN in twin and molecular genetic studies.ConclusionWe propose separating the starvation‐induced mechanisms relevant for AN/atypical AN development from the reasons/mechanisms inherent to weight loss.

ABSTRACTObjectivePost‐operative development of restrictive eating disorders can occur in patients after bariatric surgery. In children and adolescents with anorexia nervosa (AN) or atypical AN, premorbid body mass index (BMI) has recently been shown to predict total weight loss. We hypothesized that pre‐operative BMI similarly predicts weight loss and the development of a restrictive eating disorder in adult bariatric patients.MethodA PubMed search identified case studies/series of 29 adult females who developed AN or atypical AN/eating disorder not otherwise specified following bariatric surgery. Non‐parametric Spearman's correlation (r s ) between pre‐operative BMI and total weight loss was calculated; a scatterplot was used to illustrate the relationship between pre‐operative/premorbid BMI and weight loss in kg for 29 bariatric patients and 460 children and adolescents with AN or atypical AN as published previously.ResultsThe correlation between pre‐operative BMI and weight loss among bariatric patients was r s = 0.65 (p = 0.0001). Scatterplot data of this relationship fit the previously identified pattern in children and adolescents with AN or atypical AN.DiscussionThe prediction of weight loss by pre‐operative/premorbid BMI appears applicable across the weight spectrum, from underweight to severe obesity, thus strengthening our hypothesis of underlying regulatory mechanisms for the development of AN and atypical AN. Such data may guide the determination of critical weight loss thresholds that trigger eating disorder development in predisposed individuals.

Abstract Objective For adolescents, DSM‐5 differentiates anorexia nervosa (AN) and atypical AN with the 5th BMI‐centile‐for‐age. We hypothesized that the diagnostic weight cut‐off yields (i) lower weight loss in atypical AN and (ii) discrepant premorbid BMI distributions between the two disorders. Prior studies demonstrate that premorbid BMI predicts admission BMI and weight loss in patients with AN. We explore these relationships in atypical AN. Method Based on admission BMI‐centile < or ≥5th, participants included 411 female adolescent inpatients with AN and 49 with atypical AN from our registry study. Regression analysis and t ‐tests statistically addressed our hypotheses and exploratory correlation analyses compared interrelationships between weight loss, admission BMI, and premorbid BMI in both disorders. Results Weight loss in atypical AN was 5.6 kg lower than in AN upon adjustment for admission age, admission height, premorbid weight and duration of illness. Premorbid BMI‐standard deviation scores differed by almost one between both disorders. Premorbid BMI and weight loss were strongly correlated in both AN and atypical AN. Discussion Whereas the weight cut‐off induces discrepancies in premorbid weight and adjusted weight loss, AN and atypical AN overall share strong weight‐specific interrelationships that merit etiological consideration. Epidemiological and genetic associations between AN and low body weight may reflect a skewed premorbid BMI distribution. In combination with prior findings for similar psychological and medical characteristics in AN and atypical AN, our findings support a homogenous illness conceptualization. We propose that diagnostic subcategorization based on premorbid BMI, rather than admission BMI, may improve clinical validity. Public significance Because body weights of patients with AN must drop below the 5th BMI‐centile per DSM‐5, they will inherently require greater weight loss than their counterparts with atypical AN of the same sex, age, height and premorbid weight. Indeed, patients with atypical AN had a 5.6 kg lower weight loss after controlling for these variables. In comparison to the reference population, we found a lower and higher mean premorbid weight in patients with AN and atypical AN, respectively. Considering previous psychological and medical comparisons showing little differences between AN and atypical AN, we view a single disorder as the most parsimonious explanation. Etiological models need to particularly account for the strong relationship between weight loss and premorbid body weight.

Abstract Objective Anorexia nervosa (AN) and atypical AN are conceptualized as distinct illnesses, despite similar characteristics and sequelae. Whereas DSM‐5 differentiates youth with AN and atypical AN by the presence of clinical ‘underweight’ (i.e., 5th BMI percentile for age‐and‐sex (BMI%)), we hypothesized that using this weight cut‐off to discern diagnoses creates a skewed distribution for premorbid weight. Method Participants included hospitalized youth with AN ( n = 165, 43.1%) and atypical AN ( n = 218, 56.9%). Frequency analyses and chi‐square tests assessed the distribution of premorbid BMI z ‐scores (BMIz) for diagnosis. Non‐parametric Spearman correlations and Stepwise Linear regressions examined relationships between premorbid BMIz, admission BMIz, and weight loss in kg. Results Premorbid BMIz distributions differed significantly for diagnosis ( p < .001), with an underrepresentation of ‘overweight/obesity’ (i.e., BMI% ≥ 85th) in AN. Despite commensurate weight loss in AN and atypical AN, patients with premorbid ‘overweight/obesity’ were 8.31 times more likely to have atypical AN than patients with premorbid BMI% < 85th. Premorbid BMIz explained 57% and 39% of the variance in admission BMIz and weight loss, respectively. Discussion Findings support a homogenous model of AN and atypical AN, with weight loss predicted by premorbid BMI in both illnesses. Accordingly, premorbid BMI and weight loss (versus presenting BMI) may better denote the presence of an AN‐like phenotype across the weight spectrum. Findings also suggest that differentiating diagnoses with BMI% < 5th requires that youth with higher BMIs lose disproportionately more weight for an AN diagnosis. This is problematic given unique treatment barriers experienced in atypical AN. Public significance Anorexia nervosa (AN) and atypical AN are considered distinct conditions in youth, with differential diagnosis hinging upon a presenting weight status of ‘underweight’ (i.e., BMI percentile for age‐and‐sex (BMI%) < 5th). In our study, youth with premorbid ‘overweight/obesity’ (BMI% ≥ 85th) disproportionately remained above this threshold, despite similar weight loss. Coupled with prior evidence for commensurate characteristics and sequelae in both diagnoses, we propose that DSM‐5 differentiation of AN and atypical AN inadvertently reinforces weight stigma and may contribute to treatment disparities in atypical AN.

Abstract Eating disorders and substance use disorders frequently co‐occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [ r g ], twin‐based = 0.23‐0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome‐wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance‐use‐related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism‐based genetic correlations between eating disorder‐ and substance‐use‐related phenotypes. Significant positive genetic associations emerged between AUD and AN ( r g = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN ( r g = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating ( r g = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating ( r gs = −0.19 to −0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co‐varying for major depressive disorder loci. The patterns of association between eating disorder‐ and substance‐use‐related phenotypes highlights the potentially complex and substance‐specific relationships among these behaviors.