Comparing body composition between the sweet-liking phenotypes: experimental data, systematic review and individual participant data meta-analysis.

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.

Footprint of publication selection bias on meta-analyses in medicine, environmental sciences, psychology, and economics.

Publication selection bias undermines the systematic accumulation of evidence. To assess the extent of this problem, we survey over 68,000 meta-analyses containing over 700,000 effect size estimates from medicine (67,386/597,699), environmental sciences (199/12,707), psychology (605/23,563), and economics (327/91,421). Our results indicate that meta-analyses in economics are the most severely contaminated by publication selection bias, closely followed by meta-analyses in environmental sciences and psychology, whereas meta-analyses in medicine are contaminated the least. After adjusting for publication selection bias, the median probability of the presence of an effect decreased from 99.9% to 29.7% in economics, from 98.9% to 55.7% in psychology, from 99.8% to 70.7% in environmental sciences, and from 38.0% to 29.7% in medicine. The median absolute effect sizes (in terms of standardized mean differences) decreased from d = 0.20 to d = 0.07 in economics, from d = 0.37 to d = 0.26 in psychology, from d = 0.62 to d = 0.43 in environmental sciences, and from d = 0.24 to d = 0.13 in medicine.

Meta-analyses in psychology often overestimate evidence for and size of effects.

Adjusting for publication bias is essential when drawing meta-analytic inferences. However, most methods that adjust for publication bias do not perform well across a range of research conditions, such as the degree of heterogeneity in effect sizes across studies. Sladekova et al. 2022 (Estimating the change in meta-analytic effect size estimates after the application of publication bias adjustment methods. Psychol. Methods) tried to circumvent this complication by selecting the methods that are most appropriate for a given set of conditions, and concluded that publication bias on average causes only minimal over-estimation of effect sizes in psychology. However, this approach suffers from a 'Catch-22' problem-to know the underlying research conditions, one needs to have adjusted for publication bias correctly, but to correctly adjust for publication bias, one needs to know the underlying research conditions. To alleviate this problem, we conduct an alternative analysis, robust Bayesian meta-analysis (RoBMA), which is not based on model-selection but on model-averaging. In RoBMA, models that predict the observed results better are given correspondingly larger weights. A RoBMA reanalysis of Sladekova et al.'s dataset reveals that more than 60% of meta-analyses in psychology notably overestimate the evidence for the presence of the meta-analytic effect and more than 50% overestimate its magnitude.

Estimating the change in meta-analytic effect size estimates after the application of publication bias adjustment methods.

Publication bias poses a challenge for accurately synthesizing research findings using meta-analysis. A number of statistical methods have been developed to combat this problem by adjusting the meta-analytic estimates. Previous studies tended to apply these methods without regard to optimal conditions for each method's performance. The present study sought to estimate the typical effect size attenuation of these methods when they are applied to real meta-analytic data sets that match the conditions under which each method is known to remain relatively unbiased (such as sample size, level of heterogeneity, population effect size, and the level of publication bias). Four-hundred and 33 data sets from 90 articles published in psychology journals were reanalyzed using a selection of publication bias adjustment methods. The downward adjustment found in our sample was minimal, with greatest identified attenuation of b = -.032, 95% highest posterior density interval (HPD) ranging from -.055 to -.009, for the precision effect test (PET). Some methods tended to adjust upward, and this was especially true for data sets with a sample size smaller than 10. We propose that researchers should seek to explore the full range of plausible estimates for the effects they are studying and note that these methods may not be able to combat bias in small samples (with less than 10 primary studies). We argue that although the effect size attenuation we found tended to be minimal, this should not be taken as an indication of low levels of publication bias in psychology. We discuss the findings with reference to new developments in Bayesian methods for publication bias adjustment, and the recent methodological reforms in psychology. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

First case of systemic phaeohyphomycosis due to Cladophialophora bantiana in Slovakia.

INTRODUCTION: Melanized or dematiaceous fungi are associated with a wide variety of infectious syndromes. Cladophialophora bantiana is one of the most common and dangerous neurotropic fungi, able to cause brain abscess and disseminated infection. CASE PRESENTATION: We report a new case of phaeohyphomycosis brain abscesses caused by C. bantiana in Slovakia. The patient was a 63-year-old man having undergone heart transplantation, with dyspnoea, left-sided bronchopneumonia and fevers. CT (computed tomography) and MRI (magnetic resonance imaging) of the brain revealed numerous abscesses. Bacterial infection was proven by neither the growth of bacteria in culture nor the presence of bacterial antigens. Direct microscopy of the pus from the brain abscess showed Gram-positive hyphae. The isolate was finally identified as C. bantiana based on morphological and physiological features, and on DNA sequence analysis. CONCLUSION: In spite of appropriate therapy, neurological complications and accelerated respiratory insufficiency resulted in the patient's death. Concerning clinical manifestation of the brain phaeohyphomycosis that can sometimes be a problem to distinguish from malignancy, physicians should also assume infection caused by this serious pathogen.