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While negative affect reliably predicts binge eating, it is unknown how this association may decrease or ‘de-couple’ during treatment for binge eating disorder (BED), whether such change is greater in treatments targeting emotion regulation, or how such change predicts outcome. This study utilized multi-wave ecological momentary assessment (EMA) to assess changes in the momentary association between negative affect and subsequent binge-eating symptoms during Integrative Cognitive Affective Therapy (ICAT-BED) and Cognitive Behavior Therapy Guided Self-Help (CBTgsh). It was predicted that there would be stronger de-coupling effects in ICAT-BED compared to CBTgsh given the focus on emotion regulation skills in ICAT-BED and that greater de-coupling would predict outcomes.
Adults with BED were randomized to ICAT-BED or CBTgsh and completed 1-week EMA protocols and the Eating Disorder Examination (EDE) at pre-treatment, end-of-treatment, and 6-month follow-up (final N = 78). De-coupling was operationalized as a change in momentary associations between negative affect and binge-eating symptoms from pre-treatment to end-of-treatment.
There was a significant de-coupling effect at follow-up but not end-of-treatment, and de-coupling did not differ between ICAT-BED and CBTgsh. Less de-coupling was associated with higher end-of-treatment EDE global scores at end-of-treatment and higher binge frequency at follow-up.
Both ICAT-BED and CBTgsh were associated with de-coupling of momentary negative affect and binge-eating symptoms, which in turn relate to cognitive and behavioral treatment outcomes. Future research is warranted to identify differential mechanisms of change across ICAT-BED and CBTgsh. Results also highlight the importance of developing momentary interventions to more effectively de-couple negative affect and binge eating.
IMPaCT is a five-year project funded by the Department of Health, UK. Running in the UK and now Sweden, the IMPACT Project aims to target the poor physical health and excessive substance use seen in people with SMI. There is evidence that behavioural interventions may be associated with an improvement in physical health and substance use in this population.
IMPaCT is a randomised controlled trial of a health promotion intervention which consists of a manualised modular approach to working with people with severe mental illness to empower them to improve their physical health and substance use habits. It consists of The Manual, The Reference Guide and The Better Health Handbook which make up a therapy package to support clients to become healthier.
The therapy is provided by care coordinators (mental health practitioners) over a 6–9 month period and combines Cognitive Behavioural Therapy (CBT) with Motivational Interviewing (MI) principles. The aim is to work with clients to help them identify their own problem health behaviours, e.g. smoking, diet, exercise, drug and alcohol use. Realistic goals are set and revised with the client, and individual and group sessions are used to develop personal motivation to change. Information, workbooks and diaries are provided to record progress and give helpful hints, while meaningful alternative activities are introduced to replace problem health behaviours.
The increased prevalence of metabolic syndrome in people with severe mental illness (SMI) is well documented. The International Diabetes Federation (IDF) criteria for metabolic syndrome are three or more of the following: waist circumference ( 80 cm (females), (94 cm (males) OR BMI (30, triglycerides >1.7 mmol/l or on treatment, raised blood pressure (systolic >130 mg Hg or diastolic >85 mm Hg, OR on treatment for hypertension), raised fasting blood glucose (.5.6 mmol/l) OR diagnosed type II diabetes) and reduced HDL cholesterol (< 1.03 mmol/l) OR on treatment.
The IMPACT RCT is a Department of Health funded trial of a health promotion intervention (HPI) delivered by care co-ordinators to people with SMI across South London, Kent and Sussex. The intervention is focussed on improving health by addressing modifiable lifestyle factors such as diet, physical activity, obesity, cigarette smoking, alcohol and substance use.
We investigated the prevalence of metabolic syndrome in a sample of 212 patients for whom we had relevant baseline measures.
Data (weight, BMI, waist circumference, blood pressure, fasting HDL cholesterol, triglycerides and glucose levels) were analysed on 212 patients.
45% of the sample met IDF criteria for metabolic syndrome. Mean BMI was 30.6, glucose 6.4 mmol/L, triglycerides 2.0 mmol/L, HDL 1.2 (mmol/L), waist circumference 105.8 cm, and BP 122/82 mm Hg.
Metabolic syndrome was highly prevalent in this sample, significantly increasing the risk of physical morbidity and potentially lowering life expectancy. There is an unmet need for health promotion interventions in order to lower morbidity and mortality risk in these populations.
Rules of thumb (RoTs) are proposed as a means of promoting higher levels of Defined Contribution (DC) pension saving and to help stimulate debate about the high and uncertain cost of pension provision, leading to the development of solutions. The Lifetime Pension Contribution (LPC) tells young people what pension contribution is required over a full working life to achieve a decent retirement income, calculated as 23% of average UK earnings. Another RoT is that each 1% of earnings provides a pension of 1.5% of earnings. Other RoTs show how costs vary by retirement age and if the saverʼs retirement planning is on track. The current high cost of pensions is partly due to low interest rates and the inefficiencies of the DC market, with inadequate bulk purchasing power and risk sharing. RoTs might help encourage higher employer contributions, either through automatic enrolment or on a voluntary basis.
Effective management of uncertainty can lead to better, more informed decisions. However, many decision makers and their advisers do not always face up to uncertainty, in part because there is little constructive guidance or tools available to help. This paper outlines six Uncertainty Principles to manage uncertainty.
Face up to uncertainty
Deconstruct the problem
Don’t be fooled (un/intentional biases)
Models can be helpful, but also dangerous
Think about adaptability and resilience
Bring people with you
These were arrived at following extensive discussions and literature reviews over a 5-year period. While this is an important topic for actuaries, the intended audience is any decision maker or advisor in any sector (public or private).
Smoking prevalence is higher amongst individuals with schizophrenia and depression compared with the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS).
We conducted two-sample MR to explore the bi-directional effects of smoking on schizophrenia and depression. For smoking behaviour, we used (1) smoking initiation GWAS from the GSCAN consortium and (2) we conducted our own GWAS of lifetime smoking behaviour (which captures smoking duration, heaviness and cessation) in a sample of 462690 individuals from the UK Biobank. We validated this instrument using positive control outcomes (e.g. lung cancer). For schizophrenia and depression we used GWAS from the PGC consortium.
There was strong evidence to suggest smoking is a risk factor for both schizophrenia (odds ratio (OR) 2.27, 95% confidence interval (CI) 1.67–3.08, p < 0.001) and depression (OR 1.99, 95% CI 1.71–2.32, p < 0.001). Results were consistent across both lifetime smoking and smoking initiation. We found some evidence that genetic liability to depression increases smoking (β = 0.091, 95% CI 0.027–0.155, p = 0.005) but evidence was mixed for schizophrenia (β = 0.022, 95% CI 0.005–0.038, p = 0.009) with very weak evidence for an effect on smoking initiation.
These findings suggest that the association between smoking, schizophrenia and depression is due, at least in part, to a causal effect of smoking, providing further evidence for the detrimental consequences of smoking on mental health.
Meal timing may influence food choices, neurobiology and psychological states. Our exploratory study examined if time-of-day eating patterns were associated with mood disorders among adults.
During 2004–2006 (age 26–36 years) and 2009–2011 (follow-up, age 31–41 years), N = 1304 participants reported 24-h food and beverage intake. Time-of-day eating patterns were derived by principal components analysis. At follow-up, the Composite International Diagnostic Interview measured lifetime mood disorder. Log binomial and adjacent categories log-link regression were used to examine bidirectional associations between eating patterns and mood disorder. Covariates included sex, age, marital status, social support, education, work schedule, body mass index and smoking.
Three patterns were derived at each time-point: Grazing (intake spread across the day), Traditional (highest intakes reflected breakfast, lunch and dinner), and Late (skipped/delayed breakfast with higher evening intakes). Compared to those in the lowest third of the respective pattern at baseline and follow-up, during the 5-year follow-up, those in the highest third of the Late pattern at both time-points had a higher prevalence of mood disorder [prevalence ratio (PR) = 2.04; 95% confidence interval (CI) 1.20–3.48], and those in the highest third of the Traditional pattern at both time-points had a lower prevalence of first onset mood disorder (PR = 0.31; 95% CI 0.11–0.87). Participants who experienced a mood disorder during follow-up had a 1.07 higher relative risk of being in a higher Late pattern score category at follow-up than those without mood disorder (95% CI 1.00–1.14).
Non-traditional eating patterns, particularly skipped or delayed breakfast, may be associated with mood disorders.
Weed management is a major challenge in organic crop production, and organic farms generally harbor larger weed populations and more diverse communities compared with conventional farms. However, little research has been conducted on the effects of different organic management practices on weed communities and crop yields. In 2014 and 2015, we measured weed community structure and soybean [Glycine max (L.) Merr.] yield in a long-term experiment that compared four organic cropping systems that differed in nutrient inputs, tillage, and weed management intensity: (1) high fertility (HF), (2) low fertility (LF), (3) enhanced weed management (EWM), and (4) reduced tillage (RT). In addition, we created weed-free subplots within each system to assess the impact of weeds on soybean yield. Weed density was greater in the LF and RT systems compared with the EWM system, but weed biomass did not differ among systems. Weed species richness was greater in the RT system compared with the EWM system, and weed community composition differed between RT and other systems. Our results show that differences in weed community structure were primarily related to differences in tillage intensity, rather than nutrient inputs. Soybean yield was lower in the EWM system compared with the HF and RT systems. When averaged across all four cropping systems and both years, soybean yield in weed-free subplots was 10% greater than soybean yield in the ambient weed subplots that received standard management practices for the systems in which they were located. Although weed competition limited soybean yield across all systems, the EWM system, which had the lowest weed density, also had the lowest soybean yield. Future research should aim to overcome such trade-offs between weed control and yield potential, while conserving weed species richness and the ecosystem services associated with increased weed diversity.