The social defeat hypothesis posits that low status and repeated humiliation increase the risk for psychotic disorders (PDs) and psychotic experiences (PEs). The purpose of this paper was to provide a systematic review of studies on risk of PDs and PEs among lesbian, gay, or bisexual (LGB) people and a quantitative synthesis of any difference in risk. PubMed, PsycINFO, Embase, and Web of Science were searched from database inception until January 30, 2024. Two independent reviewers assessed the eligibility and quality of studies, extracted effect sizes, and noted the results of mediation analyses. Using a random effects model we computed pooled odds ratios (ORs). Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. The search identified seven studies of PDs and six of PEs. As for PDs, the unadjusted (2.13; 95% confidence interval 0.72–6.34) and covariate-adjusted pooled OR (2.24; 1.72–3.53) were not significantly increased for LGB individuals. After exclusion of a study of limited quality, both the unadjusted pooled OR (2.77; 1.21–6.32) and the covariate-adjusted pooled OR (2.67; 1.53–4.66) were significantly increased. The pooled ORs were increased for PEs: unadjusted, pooled OR = 1.97 (1.47–2.63), covariate-adjusted, pooled OR = 1.85 (1.50–2.28). Studies of PE that examined the mediating role of several variables reported that the contribution of drug abuse was small compared to that of psychosocial stressors. The results of a study in adolescents suggested a protective effect of parental support. These findings suggest an increased psychosis risk for LGB people and support the social defeat hypothesis.

Food insecurity, poised to increase with burgeoning concerns related to climate change, may influence sleep, yet few studies examined the food security-sleep association among racially/ethnically diverse populations with multiple sleep dimensions. We determined overall and racial/ethnic-specific associations between food security and sleep health. Using National Health Interview Survey data, we categorised food security as very low, low, marginal and high. Sleep duration was categorised as very short, short, recommended and long. Sleep disturbances included trouble falling/staying asleep, insomnia symptoms, waking up feeling unrested and using sleep medication (all ≥3 d/times in the previous week). Adjusting for socio-demographic characteristics and other confounders, we used Poisson regression with robust variance to estimate prevalence ratios (PRs) and 95 % confidence intervals (95 % CIs) for sleep dimensions by food security. Among 177 435 participants, the mean age of 47⋅2 ± 0⋅1 years, 52⋅0 % were women, and 68⋅4 % were non-Hispanic (NH)-White. A higher percent of NH-Black (7⋅9 %) and Hispanic/Latinx (5⋅1 %) lived in very low food security households than NH-White (3⋅1 %) participants. Very low v. high food security was associated with a higher prevalence of very short (PR = 2⋅61 [95 % CI 2⋅44–2⋅80]) sleep duration as well as trouble falling asleep (PR = 2⋅21 [95 % CI 2⋅12–2⋅30]). Very low v. high food security was associated with a higher prevalence of very short sleep duration among Asian (PR = 3⋅64 [95 % CI 2⋅67–4⋅97]) and NH-White (PR = 2⋅73 [95 % CI 2⋅50–2⋅99]) participants compared with NH-Black (PR = 2⋅03 [95 % CI 1⋅80–2⋅31]) and Hispanic/Latinx (PR = 2⋅65 [95 % CI 2⋅30–3⋅07]) participants. Food insecurity was associated with poorer sleep in a racially/ethnically diverse US sample.

We sought to examine the effects of daily consumption of macadamia nuts on body weight and composition, plasma lipids and glycaemic parameters in a free-living environment in overweight and obese adults at elevated cardiometabolic risk. Utilising a randomised cross-over design, thirty-five adults with abdominal obesity consumed their usual diet plus macadamia nuts (~15 % of daily calories) for 8 weeks (intervention) and their usual diet without nuts for 8 weeks (control), with a 2-week washout. Body composition was determined by bioelectrical impedance; dietary intake was assessed with 24-h dietary recalls. Consumption of macadamia nuts led to increased total fat and MUFA intake while SFA intake was unaltered. With mixed model regression analysis, no significant changes in mean weight, BMI, waist circumference, percent body fat or glycaemic parameters, and non-significant reductions in plasma total cholesterol of 2⋅1 % (−4⋅3 mg/dl; 95 % CI −14⋅8, 6⋅1) and low-density lipoprotein (LDL-C) of 4 % (−4⋅7 mg/dl; 95 % CI −14⋅3, 4⋅8) were observed. Cholesterol-lowering effects were modified by adiposity: greater lipid lowering occurred in those with overweight v. obesity, and in those with less than the median percent body fat. Daily consumption of macadamia nuts does not lead to gains in weight or body fat under free-living conditions in overweight or obese adults; non-significant cholesterol lowering occurred without altering saturated fat intake of similar magnitude to cholesterol lowering seen with other nuts.

Clinical Trial Registry Number and Website: NCT03801837 https://clinicaltrials.gov/ct2/show/NCT03801837?term = macadamia + nut&draw = 2&rank = 1

Complete nutrition drinks with a low glycemic index (GI) provide nutritional support and prevent hyperglycaemia. The present study identified GI and factors predicting individual glucose response to a new complete nutrition drink. A randomised cross-over controlled trial was conducted in eighteen healthy volunteers (FPG < 100 mg/dl). Complete nutrition drinks containing retrograded starch, glucose solution and white bread were assigned in a random sequence with 14-day wash-out intervals. Plasma glucose and insulin levels were measured from baseline to 180 min after consuming each food. Results show the adjusted GIs of the drink was 48.2 ± 10.4 and 46.7 ± 12.7 with glucose and white bread as the reference, respectively. While the drink has low GI (<55), the individual glucose responses varied (GI: 7–149). Comparing characters in individual GI < 55 (n = 12) and GI ≥ 55 (n = 6) groups revealed significantly higher baseline insulin in the low GI group (14.86 ± 16.51 μIU/ml v. 4.9 ± 3.4 μIU/ml, P < 0·05). The correlation matrix confirms only two predictive factors for having individual GI <55 were baseline insulin (r = 0·5, P = 0·03) and HOMA-IR (r = 0·55, P = 0·02). ROC curve reveals fasting insulin above 1.6 μIU/ml and HOMA-IR above 1.05 as the cut-off values. The findings suggest that the complete nutrition drink has a low GI, but there was wide variability in individual responses partly explained by fasting insulin levels and HOMA-IR. Screening for fasting insulin and HOMA-IR may be encouraged to maximise the functional benefit of the drink.

Stress is the most important proximal precipitant of depression, yet most large genome-wide association studies (GWAS) do not include stress as a variable. Here, we review how gene × environment (G × E) interaction might impede the discovery of genetic factors, discuss two examples of G × E interaction in depression and addiction, studies incorporating high-stress environments, as well as upcoming waves of genome-wide environment interaction studies (GWEIS). We discuss recent studies which have shown that genetic distributions can be affected by social factors such as migrations and socioeconomic background. These distinctions are not just academic but have practical consequences. Owing to interaction with the environment, genetic predispositions to depression should not be viewed as unmodifiable destiny. Patients may genetically differ not just in their response to drugs, as in the now well-recognised field of pharmacogenetics, but also in how they react to stressful environments and how they are affected by behavioural therapies.

This reflection presents a discussion of some common measures of variability and how they are appropriately used in descriptive and inferential statistical analyses. We argue that confidence intervals (CIs), which incorporate these measures, serve as tools to assess both clinical and statistical significance.

ANOVA, one of the most common statistical methods applied in agronomy, offers a variety of results we can report when analyzing designed experiments. The focus, of course, is on treatment means, but what should we report to characterize precision? Should we choose treatment standard deviations (SDs) or standard errors of the mean or standard errors of the difference (SEDs)? We discuss why treatment raw SDs should not be reported as the result of ANOVA, and point out that most of the time it is SEDs that should be provided.

Sustainable invasive weed management must address treatment effects on desired vegetation. Our objective was to determine the influence of clopyralid plus 2,4-D, glyphosate, and fosamine, at various application rates and timing, on the density and biomass of Russian knapweed and desired plant groups growing in association with this invasive weed. In a randomized complete block design with four replications, three herbicides by three herbicide rates by three herbicide application timings and a nontreated control were factorially applied to two sites located along the Missouri River riparian corridor in Montana. Clopyralid plus 2,4-D, glyphosate, and fosamine were applied during the spring rosette stage of Russian knapweed (June), the bud to bloom stage of Russian knapweed (July), or the flowering stage of Russian knapweed (August). Herbicide rates were considered low, medium, and high based on label rates of clopyralid plus 2,4-D, glyphosate, or fosamine. Density and biomass of all species were sampled 3 yr after treatment. Russian knapweed biomass decreased from 125 to about 25 g/m2 using clopyralid plus 2,4-D, irrespective of rate or timing of application. Russian knapweed density was reduced by about half by this mixture of herbicides. Nonnative grass density and biomass were maintained, whereas native grasses increased using clopyralid plus 2,4-D at medium or high rates. Neither glyphosate nor fosamine provided substantial Russian knapweed control or increases in grasses. Too few forbs were present to analyze their response to the treatments. We believe that herbicides must be combined with revegetation in areas lacking a diverse mixture of desired species capable of capturing resources made available by controlling Russian knapweed.

We introduce a stochastic model for the development of attritional and large claims in long-tail lines of business and present a corresponding “chain ladder-like” IBNR method which allows the use of claims payment data for attritional and claims incurred data for large losses. We derive formulas for the mean squared error of prediction and apply the method to a German motor third party liability portfolio.

A claims reserving method is reviewed which was introduced by Gunnar Benktander in 1976. It is a very intuitive credibility mixture of Bornhuetter/Ferguson and Chain Ladder. In this paper, the mean squared errors of all 3 methods are calculated and compared on the basis of a very simple stochastic model. The Benktander method is found to have almost always a smaller mean squared error than the other two methods and to be almost as precise as an exact Bayesian procedure.

In Mack (1993), a formula for the standard error or chain ladder reserve estimates has been derived. In the present communication, a very intuitive and easily programmable recursive way of calculating the formula is given. Moreover, this recursive way shows how a tail factor can be implemented in the calculation of the standard error.

A distribution-free formula for the standard error of chain ladder reserve estimates is derived and compared to the results of some parametric methods using a numerical example.