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Research has emphasized the genetic basis of individual differences in body mass index (BMI); however, genetic factors cannot explain the rapid rise of obesity. Eating behaviors have been stipulated to be the behavioral expression of genetic risk in an obesogenic environment. In this study, we decompose variation and covariation between three key eating behaviors and BMI in a sample of 698 participants, consisting of 167 monozygotic, 150 dizygotic complete same-sex female twins and 64 incomplete pairs from a population-based twin registry in the southeast of Spain, The Murcia Twin Registry. Phenotypes were emotional eating, uncontrolled eating and cognitive restraint, measured by the Three Factor Eating Questionnaire and objectively measured BMI. Variation in eating behaviors was driven by nonshared environmental factors (range: 56%−65%), whereas shared environmental and genetic factors were secondary. All three eating behaviors were correlated with BMI (r = .19–.25). Nonshared environmental factors explained the covariations (Emotional eating–Uncontrolled eating: rE = .54, 95% CI [.43, .64]; BMI–Cognitive restraint: rE = .15, 95% CI [.01, .28]). In contrast to BMI, individual differences in eating behaviors are mostly explained by nonshared environmental factors, which also accounted for the phenotypic correlation between eating behaviors and BMI. Due to the sample size, analyses were underpowered to detect contributions of additive genetic or shared environmental factors to variation and covariation of the phenotypes. Although more research is granted, these results support that eating behaviors could be viable intervention targets to help individuals maintain a healthy weight.
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.
We 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.
Data 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.
Childhood 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).
Our 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.
This study investigated the genetic and environmental contributions to emotional overeating (EOE) and depressive symptoms, and their covariation, in a Sri-Lankan population, using genetic model-fitting analysis. In total, 3957 twins and singletons in the Colombo Twin and Singleton Study-Phase 2 rated their EOE behaviour and depressive symptoms, which were significantly associated (men: r = 0.11, 95% confidence interval (CI) 0.06–0.16, women: r = 0.12, 95% CI 0.07–0.16). Non-shared environmental factors explained the majority of variance in men (EOE e2 = 87%, 95% CI 78–95%; depressive symptoms e2 = 72%, 95% CI 61–83%) and women (EOE e2 = 76%, 95% CI 68–83%; depressive symptoms e2 = 64%, 95% CI 55–74%). Genetic factors were more important for EOE in women (h2 = 21%, 95% CI 4–32%) than men (h2 = 9%, 95% CI 0–20%). Shared-environmental factors were more important for depressive symptoms in men (c2 = 25%, 95% CI 10–36%) than women (c2 = 9%, 95% CI 0–35%). Non-shared environmental factors explained the overlap between depressive symptoms and EOE in women but not in men. Results differed from high-income populations, highlighting the need for behavioural genetic research in global populations.
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