Rhiannon Mae Armitage

Long working hours can negatively affect workers' health, wellbeing, and work performance. Previous trials reducing working time have found improvements in multiple aspects of wellbeing, including sleep, job satisfaction, and reduced burnout, while maintaining performance. However, the potential psychological and biological mechanisms underlying these improvements, including immune function and brain function, remain unexplored. Therefore, the aim of this study is to understand the bidirectional relationship between working patterns and physical and mental health, and how workplace performance is affected. We aim to test at least 150 working-age adults in the UK (approximately half with a working time reduction and no loss of salary, and half controls with no change in working patterns) in a 14-week trial, including a 2-week baseline period, with additional participants completing questionnaires only. The primary outcome measure is the difference in physical and mental health from baseline to the end of the trial among participants undergoing a reduction in working time, compared with the control group. Data collection is currently underway, and while the majority of employers in the working time reduction group adopt a 4-day week format, the specific change in working patterns is flexible and varies between employers according to their operational need, including a 9-day fortnight, two half-days and shorter working days. Core variables include brain structure and function, sleep, immune function, interoception (perception of bodily sensations), time use, diet, mental health, and workplace performance and engagement. Secondary outcomes include weekly monitoring of self-reported wellbeing changes to identify key inflection points and assess whether these are maintained at a 6-month follow-up. Overall, this study aims to generate highly novel multimodal data on the psychological and biological implications of working time reduction, including observed changes in health, wellbeing, and performance.

Working longer hours is associated with negative outcomes in health and wellbeing. While effects of occupational stress on the brain have been observed, there have been no investigations into the effect of amount of time spent at work on brain function to date. We examined the effect of length of working week (in hours) on task-based and resting-state functional magnetic resonance imaging (fMRI) in 8,528 and 7,589 participants, respectively, from the UK Biobank. Analyses were conducted to treat working hours as both a continuous and a categorical (lower versus higher hours groups) variable. Covariates relevant to length of working week were selected using random forest machine learning and were systematically adjusted for in a sequential manner. No association with length of working week was found for task-based fMRI, as reflected by activation in the amygdala, fusiform face area, and insula during an emotional face matching task. For resting-state fMRI, greater continuous length of working week was found to be positively associated with within-network connectivity in the somatomotor network, but did not predict connectivity within or between any other network. The observed association may suggest compensatory or adaptive somatomotor connectivity changes in the face of increased job demands. All other within- and between-network connectivity metrics showed no significant relationship with working hours, following optimal model selection and correction for multiple statistical tests. When looking at uncorrected p-values, significant statistical associations with resting-state fMRI tended to become non-significant once demographic factors were adjusted for, suggesting that associations between length of working week and brain function are frequently accounted for by these covariates, with the sole exception of somatomotor connectivity. Overall, this suggests that length of working week, as just one employment factor, does not show strong associations with fMRI metrics, when related variables are adjusted for. Interventional studies, and analysis of additional factors such as burnout and shift work may shed further light on neural markers of occupational wellbeing.

Reducing sugar intake is a key component of global health policies and dietary guidelines. However, individuals vary substantially in sweet-liking, commonly characterized by sweet-liking status (extreme sweet-likers, moderate sweet-likers, and sweet-dislikers), yet the heritability of these categories remains unexplored. Monozygotic and dizygotic twins from Finland (FinnTwin12; n = 468; 60% female, aged 21–24) and the UK (TwinsUK; n = 967; 90% female, aged 18–81) rated their liking and perceived intensity of a 20% (w/v) sucrose solution, reported their liking and consumption-frequency of food and beverages and completed additional behavioral, eating and personality measures. We estimated the contribution of additive genetic (A), nonadditive genetic (D), shared (C), and unshared environmental factors (E) in the variance and covariance of sweet-liking (defined ordinally through sweet-liking status and continuously) with related traits to see if they share similar proportions of genetic and environmental factors. Model-fitting indicated 30–48% of the variability in sweet-liking was attributed to (A) additive genetic factors and 52–70% to (E) environmental exposures not shared by siblings. Importantly, such AE models consistently fit best, regardless of sex, cohort, or sweet-liking assessment method. Broadly, correlations between sweet-liking and behavioral, eating, and personality measures were modest (–0.19 to 0.21), mostly positive and largely driven by shared genetic rather than environmental factors, with the strongest relationship seen for reported liking, consumption-frequency and craving for sweet foods. We demonstrate that unshared environment modulates individual differences in sweet-liking alongside a substantial genetic component that is partly shared with reported liking, consumption-frequency and craving for sweet foods.

Background: Individuals exhibit substantial variability in sweet-liking, best characterized by three distinct hedonic phenotypes (extreme sweet-likers, moderate sweet-likers, and sweet-dislikers). However, the underlying genetic and environmental contributions to these phenotypes remain unexplored.Objective: We investigated the heritability of sweet-liking through phenotyping and as a continuous variable, using twin modelling and examined whether correlations between sweet-liking assessment method and related behavioral, eating and personality traits share similar proportions of genetic and environmental factors.Method: Monozygotic and dizygotic twins from Finland (FinnTwin12; n = 468; 60% female, aged 21-24) and the UK (TwinsUK; n = 967; 90% female, aged 18-81) rated their liking and perceived intensity of a 20% (w/v) sucrose solution, reported their liking and consumption-frequency of a range of food and beverages and completed additional behavioral, eating and personality measures. Using linear structural equation modelling, we estimated the contribution of additive genetic (A), nonadditive genetic (D), shared (C), or factors (E) in the variance and covariance of sweet-liking and related traits.Results: Model-fitting indicated 30-48% of the variability in sweet-liking in this population was due to additive genetic factors, with environmental exposures and experiences not shared by siblings and measurement error accounting for the rest (52-70%). Importantly, an AE model consistently fit best, regardless of sex, cohort, or sweet-liking. Broadly, correlations between sweet-liking and behavioral, eating, and personality measures were modest (–0.19 to 0.21), mostly positive and largely driven by shared genetic factors rather than environmental. Notably, the strongest relationship was between sweet-liking and reported liking of sweet foods, and, to a lesser extent, their consumption-frequency and craving for sweet foods.Conclusion: We demonstrate that unshared environment modulates the expression of individual differences in sweet-taste liking alongside a substantial genetic component, which is partly shared with the reported liking, consumption-frequency and craving for sweet foods.

Background: Legislation aimed at reducing sugar intake assumes that sweet-liking drives overconsumption. However, evidence that a greater liking for sweet taste is associated with unhealthier body size is mixed and complicated by relatively small samples, an overreliance on body mass index (BMI) and lack of classification using sweet-liking phenotypes. Methods: We first examined body size data in two larger samples with sweet-liking phenotyping: extreme sweet-likers, moderate sweet-likers and sweet-dislikers. Adults (18-34yrs), attended a two-session lab-based experiment involving phenotyping for sweet-liking status and a bioelectrical impedance body composition measurement (Experiment One: N = 200; Experiment Two: N = 314). Secondly, we conducted an individual participant data (IPD) meta-analysis: systematic searches across four databases identified 5736 potential articles. Of these, 53 papers met our search criteria: a taste assessment that measured liking using sucrose (>13.7% w/v), which allowed sweet-liking phenotyping and included either BMI, body fat percentage (BF%), fat-free mass (FFM) or waist-circumference. Results: A significant effect of sweet-liking phenotype on FFM was found in both Experiment One and Two, with extreme sweet-likers having significantly higher FFM than sweet-dislikers. In Experiment One, sweet-dislikers had a significantly higher BF% than extreme sweet-likers and moderate sweet-likers. However, as these data are from one research group in a young, predominantly westernised population, and the results did not perfectly replicate, we conducted the IPD meta-analyses to further clarify the findings. Robust one-stage IPD meta-analyses of 15 studies controlling for sex revealed no significant differences in BF% (n = 1836) or waist-circumference (n = 706). For BMI (n = 2368), moderate sweet-likers had slightly lower BMI than extreme sweet-likers, who had the highest overall BMI. Most interestingly, for FFM (n = 768), moderate sweet-likers and sweet-dislikers showed significantly lower FFM than extreme sweet-likers. Conclusion: The higher BMI often seen in sweet-likers may be due to a larger FFM and questions the simple model where sweet liking alone is a risk factor for obesity.

The vicious cycle model of obesity suggests that repeated habitual intake of a diet high in fat and sugar (HFS) results in impairment in hippocampal function which in turn increases impulsive behaviours, making it harder to resist unhealthy diet choices. Evidence from studies with rodents consistently show switching to a HFS diet impairs performance on hippocampally-sensitive memory tasks. The limited literature in humans also suggest impaired memory and increased impulsivity related to higher habitual HFS intake. However, these changes in memory and impulsivity have been looked at independently. To investigate how these effects are inter-related, three experiments were conducted where relative HFS intake was related to measures of memory and impulsivity. In Experiment 1 (90 female participants), HFS was associated with higher scores on the Everyday Memory Questionnaire-revised (EMQ), and higher scores on the total, Attention (BISatt) and Motor (BISmot) sub-scales of the Barratt Impulsiveness Scale (BIS11). Experiment 2 (84 women and 35 men), replicated the association between HFS and EMQ, and also found HFS related to poorer performance on the hippocampally-sensitive 4 mountain (4MT) memory task. The association between HFS intake and the BISatt replicated, but there were no significant associations with other BIS11 measures or delay-discounting for monetary rewards. Experiment 3 (199 women and 87 men) replicated the associations between DFS and 4MT and EMQ, and also found an association with overall recall, but not response inhibition, from a Remembering Causes Forgetting task: HFS was also significantly associated with BIS total, BISatt and BISmot. In all three studies these associations remained when potential confounds (BMI, age, gender, hunger state, restrained and disinhibited eating) were controlled for. Mediation analysis found that the effect of HFS on memory at least part mediated the relationship between HFS and impulsivity in Experiments 1 and 3, but not 2. Overall these data provide some support for the vicious cycle model, but also suggest that trait impulsivity may be a risk factor for poor dietary choice.