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Search: WFRF:(Herle M)

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  • Abdulkadir, M, et al. (author)
  • Polygenic Score for Body Mass Index Is Associated with Disordered Eating in a General Population Cohort
  • 2020
  • In: Journal of clinical medicine. - : MDPI AG. - 2077-0383. ; 9:4
  • Journal article (peer-reviewed)abstract
    • Background: Disordered eating (DE) is common and is associated with body mass index (BMI). We investigated whether genetic variants for BMI were associated with DE. Methods: BMI polygenic scores (PGS) were calculated for participants of the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 8654) and their association with DE tested. Data on DE behaviors (e.g., binge eating and compensatory behaviors) were collected at ages 14, 16, 18 years, and DE cognitions (e.g., body dissatisfaction) at 14 years. Mediation analyses determined whether BMI mediated the association between the BMI-PGS and DE. Results: The BMI-PGS was positively associated with fasting (OR = 1.42, 95% CI = 1.25, 1.61), binge eating (OR = 1.28, 95% CI = 1.12, 1.46), purging (OR = 1.20, 95% CI = 1.02, 1.42), body dissatisfaction (Beta = 0.99, 95% CI = 0.77, 1.22), restrained eating (Beta = 0.14, 95% CI = 0.10, 1.17), emotional eating (Beta = 0.21, 95% CI = 0.052, 0.38), and negatively associated with thin ideal internalization (Beta = −0.15, 95% CI = −0.23, −0.07) and external eating (Beta = −0.19, 95% CI = −0.30, −0.09). These associations were mainly mediated by BMI. Conclusions: Genetic variants associated with BMI are also associated with DE. This association was mediated through BMI suggesting that weight potentially sits on the pathway from genetic liability to DE.
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  • Ferreira, DLS, et al. (author)
  • Associations between Blood Metabolic Profile at 7 Years Old and Eating Disorders in Adolescence: Findings from the Avon Longitudinal Study of Parents and Children
  • 2019
  • In: Metabolites. - : MDPI AG. - 2218-1989. ; 9:9
  • Journal article (peer-reviewed)abstract
    • Eating disorders are severe illnesses characterized by both psychiatric and metabolic factors. We explored the prospective role of metabolic risk in eating disorders in a UK cohort (n = 2929 participants), measuring 158 metabolic traits in non-fasting EDTA-plasma by nuclear magnetic resonance. We associated metabolic markers at 7 years (exposure) with risk for anorexia nervosa and binge-eating disorder (outcomes) at 14, 16, and 18 years using logistic regression adjusted for maternal education, child’s sex, age, body mass index, and calorie intake at 7 years. Elevated very low-density lipoproteins, triglycerides, apolipoprotein-B/A, and monounsaturated fatty acids ratio were associated with lower odds of anorexia nervosa at age 18, while elevated high-density lipoproteins, docosahexaenoic acid and polyunsaturated fatty acids ratio, and fatty acid unsaturation were associated with higher risk for anorexia nervosa at 18 years. Elevated linoleic acid and n-6 fatty acid ratios were associated with lower odds of binge-eating disorder at 16 years, while elevated saturated fatty acid ratio was associated with higher odds of binge-eating disorder. Most associations had large confidence intervals and showed, for anorexia nervosa, different directions across time points. Overall, our results show some evidence for a role of metabolic factors in eating disorders development in adolescence.
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  • Herle, M, et al. (author)
  • A longitudinal study of eating behaviours in childhood and later eating disorder behaviours and diagnoses
  • 2020
  • In: The British journal of psychiatry : the journal of mental science. - : Royal College of Psychiatrists. - 1472-1465. ; 216:2, s. 113-119
  • Journal article (peer-reviewed)abstract
    • Eating behaviours in childhood are considered as risk factors for eating disorder behaviours and diagnoses in adolescence. However, few longitudinal studies have examined this association.AimsWe investigated associations between childhood eating behaviours during the first ten years of life and eating disorder behaviours (binge eating, purging, fasting and excessive exercise) and diagnoses (anorexia nervosa, binge eating disorder, purging disorder and bulimia nervosa) at 16 years.MethodData on 4760 participants from the Avon Longitudinal Study of Parents and Children were included. Longitudinal trajectories of parent-rated childhood eating behaviours (8 time points, 1.3–9 years) were derived by latent class growth analyses. Eating disorder diagnoses were derived from self-reported, parent-reported and objectively measured anthropometric data at age 16 years. We estimated associations between childhood eating behaviours and eating disorder behaviours and diagnoses, using multivariable logistic regression models.ResultsChildhood overeating was associated with increased risk of adolescent binge eating (risk difference, 7%; 95% CI 2 to 12) and binge eating disorder (risk difference, 1%; 95% CI 0.2 to 3). Persistent undereating was associated with higher anorexia nervosa risk in adolescent girls only (risk difference, 6%; 95% CI, 0 to 12). Persistent fussy eating was associated with greater anorexia nervosa risk (risk difference, 2%; 95% CI 0 to 4).ConclusionsOur results suggest continuities of eating behaviours into eating disorders from early life to adolescence. It remains to be determined whether childhood eating behaviours are an early manifestation of a specific phenotype or whether the mechanisms underlying this continuity are more complex. Findings have the potential to inform preventative strategies for eating disorders.
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  • Herle, M, et al. (author)
  • Identifying typical trajectories in longitudinal data: modelling strategies and interpretations
  • 2020
  • In: European journal of epidemiology. - : Springer Science and Business Media LLC. - 1573-7284 .- 0393-2990. ; 35:3, s. 205-222
  • Journal article (peer-reviewed)abstract
    • Individual-level longitudinal data on biological, behavioural, and social dimensions are becoming increasingly available. Typically, these data are analysed using mixed effects models, with the result summarised in terms of an average trajectory plus measures of the individual variations around this average. However, public health investigations would benefit from finer modelling of these individual variations which identify not just one average trajectory, but several typical trajectories. If evidence of heterogeneity in the development of these variables is found, the role played by temporally preceding (explanatory) variables as well as the potential impact of differential trajectories may have on later outcomes is often of interest. A wide choice of methods for uncovering typical trajectories and relating them to precursors and later outcomes exists. However, despite their increasing use, no practical overview of these methods targeted at epidemiological applications exists. Hence we provide: (a) a review of the three most commonly used methods for the identification of latent trajectories (growth mixture models, latent class growth analysis, and longitudinal latent class analysis); and (b) recommendations for the identification and interpretation of these trajectories and of their relationship with other variables. For illustration, we use longitudinal data on childhood body mass index and parental reports of fussy eating, collected in the Avon Longitudinal Study of Parents and Children.
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