Social influence shifts valuation of appetitive cues in early adolescence and adulthood

Food intake and eating behaviour during a real-life Snack Scenario in childhood obesity-An experiment using a hidden camera

OBJECTIVE

To compare food intake and eating behaviour in children and adolescents with obesity (OBE) undergoing weight loss intervention and normal weight (NW) in a real-life Snack Scenario.

METHODS

Sixty OBE were examined before (T0) and after weight loss (T1) and compared to a single measurement comparison group of 27 NW. Participants watched a 20-min film and were encouraged to snack from a variety of foods ad libitum. Food intake was measured and eating behaviour assessed via a hidden camera and a validated questionnaire.

RESULTS

The food and energy intake did not differ between NW (155 ± 83 g, 1067 ± 732 kJ) and OBE at T0 (144 ± 106 g, 1088 ± 883 kJ) but increased in OBE at T1 (187 ± 91 g, 1544 ± 845 kJ). Latency of food intake was significantly shorter in NW (0 m:07 s ± 0 m:08 s) compared to OBE (T0: 1 m:11 s ± 2 m:57 s). After weight loss, latency decreased in OBE (0 m:26 s ± 1 m:00 s). NW touched food more often (49 ± 24) than OBE (T0: 29 ± 23), but takes from plate were similar. The questionnaire revealed differences between OBE and NW, not correlating with Snack Scenario observations.

CONCLUSION

Eating behaviours differed in NW versus OBE at T0 but food intake was similar. Therefore, behaviour while eating may be an underestimated factor in the considerations for childhood obesity.

CLINICAL TRIAL REGISTRATION

German Clinical Trials Register (DRKS) with the trial number DRKS00005122.

Time-Restricted Eating in Community-Dwelling Adults: Correlates of Adherence and Discontinuation in a Cross-Sectional Online Survey Study

BACKGROUND

Time-restricted eating (TRE), a type of intermittent fasting in which all daily calories are consumed within a window of ≤12 hours, is hypothesized to promote long-term weight management because of its relative simplicity.

OBJECTIVE

This study reports correlates of adherence among community-dwelling adults currently or formerly following a TRE dietary strategy.

DESIGN

A 25-minute cross-sectional online survey was developed, including questions about TRE perceptions, behaviors, motivators and drivers, and demographics. The survey was administered in February 2021 via Prolific, an online platform for sample recruitment and survey dissemination.

PARTICIPANTS

Eligibility criteria included US adult ages 18+ who currently or formerly (past 3 months) followed TRE (ie, consumed all daily calories within a window of ≤12 hours) for a minimum of 1 week.

STATISTICAL ANALYSES

χ2 tests and analysis of covariance (ANCOVA; adjusting for sex and age) compared responses between current and former followers.

RESULTS

Current followers (n = 296, mean [SD]: 34.2 ± 12.2y) were older than former followers (n = 295, mean [SD]: 31.1 ± 10.9 y) and practiced TRE for longer (median: 395 vs 90 days, P < 0.001). Current followers reported more success with meeting TRE goals (P ≤ 0.015), were less likely to report TRE concerns (P < 0.001), and more likely to report TRE satisfaction (P < 0.001). Four TRE motivators were more important among current (vs former) followers: weight maintenance, health (not weight), improved sleep, and preventing disease (P ≤ 0.017); weight loss was more important among former (vs current) followers (P = 0.003). Among adherence drivers, ability to work from home and the impact of COVID-19 were reported as more helpful for TRE adherence among current compared with former followers (P ≤ 0.028).

CONCLUSIONS

TRE motivators and drivers differed between current and former followers; interventions tailored to individuals' preferences and circumstances may benefit TRE adherence.

Confirmatory reinforcement learning changes with age during adolescence

Understanding how learning changes during human development has been one of the long-standing objectives of developmental science. Recently, advances in computational biology have demonstrated that humans display a bias when learning to navigate novel environments through rewards and punishments: they learn more from outcomes that confirm their expectations than from outcomes that disconfirm them. Here, we ask whether confirmatory learning is stable across development, or whether it might be attenuated in developmental stages in which exploration is beneficial, such as in adolescence. In a reinforcement learning (RL) task, 77 participants aged 11-32 years (four men, mean age = 16.26) attempted to maximize monetary rewards by repeatedly sampling different pairs of novel options, which varied in their reward/punishment probabilities. Mixed-effect models showed an age-related increase in accuracy as long as learning contingencies remained stable across trials, but less so when they reversed halfway through the trials. Age was also associated with a greater tendency to stay with an option that had just delivered a reward, more than to switch away from an option that had just delivered a punishment. At the computational level, a confirmation model provided increasingly better fit with age. This model showed that age differences are captured by decreases in noise or exploration, rather than in the magnitude of the confirmation bias. These findings provide new insights into how learning changes during development and could help better tailor learning environments to people of different ages. RESEARCH HIGHLIGHTS: Reinforcement learning shows age-related improvement during adolescence, but more in stable learning environments compared with volatile learning environments. People tend to stay with an option after a win more than they shift from an option after a loss, and this asymmetry increases with age during adolescence. Computationally, these changes are captured by a developing confirmatory learning style, in which people learn more from outcomes that confirm rather than disconfirm their choices. Age-related differences in confirmatory learning are explained by decreases in stochasticity, rather than changes in the magnitude of the confirmation bias.

Obesity and polycystic ovary syndrome

The increased global prevalence of obesity over the last 40-years has driven a rise in prevalence of obesity-related co-morbidities, including polycystic ovary syndrome (PCOS). On a background of genetic susceptibility, PCOS often becomes clinically manifest following weight gain, commonly during adolescence. A common endocrinopathy affecting between 6%-10% of reproductive-age women, PCOS presents with the cardinal features of hyperandrogenism, reproductive and metabolic dysfunction. PCOS associates with insulin resistance, independently of (but amplified by) obesity. Insulin resistance in PCOS is characterized by abnormal post-receptor signalling within the phosphatidylinositol-kinase (PI3-K) pathway. Multiple factors (including most notably, weight gain) contribute towards the severity of insulin resistance in PCOS. Compensatory hyperinsulinaemia ensues, resulting in over-stimulation of the (intact) post-receptor mitogen-activated protein kinase (MAP-K) insulin pathway, with consequent implications for steroidogenesis and ovarian function. In this concise review, we explore the effects of weight gain and obesity on the pathogenesis of PCOS from the perspective of its three cardinal features of hyperandrogenism, reproductive and metabolic dysfunction, with a focus on the central mediating role of the insulin pathway. We also consider key lifestyle strategies for the effective management of obese and overweight women with PCOS.

Obesity: novel and unusual predisposing factors

To tackle the complexity of the global obesity epidemic, it is important to consider the many predisposing factors that underlie progressive and sustained weight gain. Some of the biological drivers for weight gain following initial weight loss include persistent changes in appetite hormones [including ghrelin and postprandial plasma peptide YY (PYY)], and 'persistent metabolic adaptation'. However, many factors within our busy, stressful modern-day environment seem to conspire towards promotion of weight gain. These include the effects of sleep deprivation on appetite regulation, and the effects of modern-day technology on 'attention competition'. These factors, combined with cultural and societal factors can result in a 'mindless' attitude regarding eating-related behaviour that is likely to predispose to weight gain. In addition to the external environment, our internal environment within the gut has also changed radically within the last few decades, resulting from changes in fibre intake, and increased ingestion of highly refined, sterilised and processed foods. Although contentious, these dietary changes have implications for our gut microbiota, and possible downstream effects on control of appetite and metabolism. In this brief review, we consider some of the novel predisposing factors for weight gain within our modern-day 21st century environments (both external and internal), and explore how legal terminology can help to conceptualise the numerous factors that contribute towards weight gain, and, ultimately the global obesity epidemic.