To Örebro University

INTRODUCTION: Irritable bowel syndrome (IBS) is a common condition that should be diagnosed using the Rome criteria and limited laboratory testing. The aim of this retrospective, medical record-based study was to evaluate the adherence of Swedish primary health care practitioners to diagnostic guidelines for IBS.

METHODS: Using the electronic patient register in primary care, we identified 1943 new IBS cases in patients aged 18-65 between January 2015 and December 2019 in Region Örebro County. A random sample of 400 patients was selected and their medical records were scrutinized to evaluate diagnostic methods.

RESULTS: Of the 309 eligible medical records, only 36.2% of patients met the Rome III or IV criteria. The criteria were explicitly documented in 4.9% of cases, and subclassification was noted in 5.5%. There were no significant differences in diagnostic practices between GPs and other physicians. Only 9.4% were diagnosed without laboratory testing, although 69.9% did not undergo all recommended tests according to local guidelines. Rectoscopy was performed in 14.2%, while 9.7% and 5.8% of patients were referred for colonoscopy or CT, respectively, with significantly higher referral rates in patients over 40 years. Men were more frequently referred for colonoscopy while other diagnostic procedures showed no significant sex differences.

CONCLUSIONS: Adherence to IBS diagnostic guidelines in Swedish primary care seems to be limited among both GPs and non-GPs. The documented use of Rome criteria is minimal, and guideline-compliant laboratory testing is insufficient. Increased awareness and structured implementation of IBS diagnostic criteria are warranted.

Growing evidence indicates a link between diet and depression risk. We aimed to examine the association between an inflammatory diet index and depression utilising extensive data from UK biobank cohort. The energy-adjusted dietary inflammation index (E-DII) was calculated to quantify the potential of daily diet, with twenty-seven food parameters utilised. The E-DII scores were classified into two categories (low v. high) based on median value. To mitigate bias and ensure comparability of participant characteristics, propensity score matching was employed. To ascertain the robustness of these associations, sensitivity analyses were conducted. Subgroup analyses were performed to evaluate the consistency of these associations within different subpopulations. Totally, 152 853 participants entered the primary analyses with a mean age of 56·11 (sd 7·98) years. Employing both univariate and multivariate logistic regression models, adjustments were made for varying degrees of confounding factors (socio-demographics, lifestyle factors, common chronic medical conditions including type 2 diabetes and hypertension). Results consistently revealed a noteworthy positive correlation between E-DII and depression. In the context of propensity score matching, participants displaying higher E-DII scores exhibited an increased likelihood of experiencing incident depression (OR = 1·12, 95 % CI: 1·05, 1·19; P = 0·000316). Subgroup analysis results demonstrated variations in these associations across diverse subpopulations. The E-value for the point-estimate OR calculated from the propensity score matching dataset was 1·48. Excluding individuals diagnosed with type 2 diabetes or hypertension, the findings consistently aligned with the positive association in the primary analysis. These findings suggested that consumption of a diet with higher pro-inflammatory potential might associated with an increase of future depression risk.

The Climate Change Anxiety Scale (CCAS) is an emerging psychometric instrument designed to assess climate change anxiety (CCA). This study aimed to preliminarily identify reference cutoff scores and core items of the CCAS in a Chinese adult population. We conducted an online cross-sectional survey in China between May and June 2024, recruiting 653 Chinese adults (mean age = 32.62 ± 7.40 years; 53.8% female) via Wenjuanxing. CCA was assessed using the CCAS. External variables included generalized anxiety (Chinese GAD-7), self-rated sleep quality (single-item, past week), and self-reported experience of meteorological disasters (yes/no). Latent profile analysis (LPA) and receiver operating characteristic (ROC) analyses were used to derive reference cutoff scores, and network analysis was applied to identify core items. LPA supported a two-profile solution and yielded an overall reference cutoff score of 27.5, above which participants were categorized as having elevated CCA risk. Participants classified as high risk reported higher generalized anxiety, poorer sleep quality, and a higher likelihood of meteorological disaster experience. Sex-stratified analyses indicated different optimal cutoffs: 28.5 for males (sensitivity = 1.000; specificity = 0.982) and 26.5 for females (sensitivity = 0.986; specificity = 0.986). Network analysis further suggested that the item 'My concerns about climate change undermine my ability to work to my potential' exhibited the highest centrality, with statistical significance observed only among females. Overall, these findings provide practical, research-oriented evidence for using CCAS-based stratification in Chinese adults and offer preliminary guidance for future subgrouping and sensitivity analyses, while underscoring the need for further validation in broader and more representative samples.

Sleep disorders are highly comorbid with depression. Impaired sleep quality aggravates depressive symptoms, delays recovery, and increases the risk of additional physical and mental disorders. Although mind-body exercises (MBEs) can improve sleep quality, the comparative effects of different types and doses in depressive populations remain unclear. This study evaluated the effects of various MBE modalities and doses on sleep quality in adults with depressive symptoms through pairwise, network, and dose-response meta-analyses to inform the current mental health interventions. Randomized controlled trials (RCTs) assessing MBEs for sleep quality in adults with depressive symptoms were searched across seven major databases from inception to July 2025. Two reviewers independently screened and extracted data. Pairwise, network, and dose-response meta-analyses using R software examined intervention effects and dose-response associations between exercise volume and sleep improvement. Twenty-seven RCTs involving 2,718 participants were included in the systematic review. Yoga and mindfulness significantly improved sleep quality in the pairwise meta-analysis. Network meta-analysis ranked yoga as most effective (SUCRA = 85.64%), followed by Qigong (64.46%) and mindfulness (47.45%). Dose-response analysis revealed a nonlinear relationship between exercise volume and sleep improvement, with an optimal range of similar to 270-650 METs-min/week. Each MBE showed a distinct optimal range. MBEs effectively improve sleep quality in adults with depressive symptoms. Yoga showed the highest SUCRA value, followed by Qigong and mindfulness. A nonlinear dose-response pattern was observed, warranting further studies to validate and refine optimal exercise prescriptions.

The health consequences associated with exercising in polluted air are not fully understood. Therefore, we synthesized controlled trials that compared exercise performed under higher air-pollution exposure with a corresponding lower-exposure condition (e.g., filtered air or a lower concentration) in healthy participants, and explored potential effect modifiers. We searched PubMed, Embase, the Cochrane Library, Web of Science Core Collection, and Scopus for studies published between 2000 and 2024, and included 35 eligible controlled trials. Risk of bias was assessed using RoB 2 for randomized crossover trials and ROBINS-E for non-randomized studies, and the overall certainty of evidence using the GRADE framework. Random-effects meta-analyses using Hedges' g as a pooled effect size were conducted, with subgroup and meta-regression analyses exploring moderators. Results for pulmonary function showed that FEF25-75 declined significantly (g = -0.323, 95% CI -0.633 to -0.014, I2 = 19%, k = 5, certainty of evidence (CoE)), with smaller reductions in FEV1 (g = -0.183, 95% CI -0.334 to -0.032, I2 = 0%, k = 15, high CoE) and FVC (g = -0.131, 95% CI -0.280 to 0.018, I2 = 0%, k = 14, moderate CoE). For cardiovascular function, there was a modest rise in systolic blood pressure (g = 0.279, 95% CI 0.093 to 0.464, I2 = 0%, k = 9, high CoE), while diastolic pressure and heart rate were largely unaffected. Results for hematological outcomes showed that white blood cells (g = 0.479, 95% CI -0.002 to 0.960, I2 = 73%, k = 6, very low CoE) increased, and red blood cells (g = -0.791, 95% CI -1.353 to -0.230, I2 = 74%, k = 5, very low CoE) decreased, whereas results for inflammatory cytokines were inconsistent. Findings for hematological and inflammatory markers should be interpreted cautiously given heterogeneity and generally low certainty of evidence. Overall, these modest but consistent changes suggest that repeated exposure during exercise may accumulate respiratory and cardiovascular risks, underscoring the need to promote activity in cleaner environments to safeguard health benefits.

Background: The COVID-19 pandemic compelled governments worldwide to adopt diverse public health and economic policies. However, the relative efficiency of these interventions across European countries has not been comprehensively evaluated. This study assessed the efficiency of COVID-19 policy responses in 27 European countries of the Organization for Economic Co-operation and Development (OECD), with the aim of identifying factors associated with effective pandemic management. The time period of this study is from January 1, 2020 to December 31, 2022.

Methods: A data envelopment analysis (DEA) framework was applied to evaluate the efficiency of national responses. Policy inputs, including healthcare resources, economic support, and stringency indices, were assessed against outputs reflecting adverse outcomes, namely COVID-19 cases, mortality, and virus transmission. Data were obtained from the Oxford COVID-19 Government Response Tracker and other publicly available international databases.

Results: Marked heterogeneity in policy efficiency was observed. Countries that implemented early, stringent, and adaptive measures demonstrated superior efficiency scores. Italy, Greece, and Austria consistently ranked among the most efficient, while nations with delayed or inflexible strategies performed less effectively despite comparable resource availability. Importantly, policy flexibility and dynamic adjustment to epidemiological trends emerged as critical determinants of sustained efficiency.

Conclusions: This study provides a robust comparative evaluation of COVID-19 policy efficiency across European OECD countries. The findings emphasize that timeliness of interventions, adaptability of policy measures, and judicious resource allocation were more influential than absolute resource capacity. Incorporating efficiency assessments into pandemic preparedness strategies may enhance resilience and inform evidence-based decision-making for future global health emergencies.

Parental feeding practices play a crucial role in preventing childhood obesity and promoting healthy eating habits. However, few interventions are specifically designed to improve these practices. We aimed to assess the feasibility and preliminary effects of a novel psychoeducational intervention, Empower Parents to Optimise Feeding Practices (EPO-Feeding), tailored to enhance parental feeding practices in China. A parallel-arm feasibility randomised controlled trial (RCT) was conducted in two public kindergartens in Yangzhou, China. Participants were randomly assigned to the intervention group (EPO-Feeding programme plus usual care) or control group (usual care). Data were collected at baseline, post-intervention, and 1 month after intervention. Descriptive statistics assessed feasibility and acceptability, while analysis of variance for repeated measures and generalised estimating equations analysed continuous and categorical outcomes across time points, respectively. Within 2 weeks, 131 parents expressed interest, and 84 eligible participants were randomly assigned. Module attendance and retention rates were high, with 83.3% (n = 35) completing all sessions and 97.6% (n = 82) completing all measurements. Satisfaction surveys indicated high acceptability. Statistically significant improvements were observed in the intervention group, including increased encouragement of healthy eating and monitoring, reduced pressure to eat and food as rewards, improved weight accurate perception, and enhanced parenting efficacy (p < 0.05). However, no significant effects were found in long-term outcomes, including children's eating behaviours and weight status. This study demonstrates high feasibility and acceptability of the EPO-Feeding programme and suggests its potential to support Chinese parents' feeding strategies. A full-scale RCT is recommended. Trial registration. It was registered with ClinicalTrials.gov (NCT06181773), 20/11/2023.

BACKGROUND: Epidemiological studies that rely on biomarkers of exposure typically estimate each subject's exposure from measurements on that individual. If repeated measurements of biomarkers of exposure are obtained on an individual, they are typically averaged. This averaging helps to reduce error from within-person variability if average exposure is a better measure of the biologically effective dose than the instantaneous one. However, these analyses then often ignore the residual within-person variation in the averages of measurements. Not considering this variation can bias effect estimates and lead to inaccurate risk assessment.

METHODS: We developed software ("calculators") that help design studies of continuous and binary outcomes that rely on biomarkers of exposure. An independent panel of experts was employed to peer review the models and answer questions regarding their use and best practices for the design of epidemiology studies that utilize biomonitoring data for the exposure assessment.

RESULTS: Web-based tools were developed to estimate the required sample sizes, number of repeated measurements, and the trade-offs between power and bias in simple linear and logistic regression models under classical (independent, additive, normally distributed, homogeneous variance) measurement error assumptions. Application of the calculators was illustrated in case studies of investigation of the associations between urinary levels of bisphenols during pregnancy and fetal growth, and urinary levels of triclosan and neurodevelopment in children. Best practices are recommended for the design of epidemiology studies that utilize biomonitoring data for the exposure assessment.

CONCLUSIONS: Calculators have been developed and vetted by a panel of experts. They are designed to estimate sample size (number of individuals sampled and number of samples per individual), power and bias in epidemiological studies that use biomonitoring to assess each subject's exposure in the presence of classical measurement errors. These user-friendly tools account for measurement error and allow researchers to design more accurate and appropriately powered studies, ultimately improving quality of public health research.

AIMS: Low-energy diet (LED) plus cognitive-behavioural therapy (CBT) produces substantial short-term weight loss in obesity, but long-term maintenance remains difficult. We evaluated whether adding intragastric balloon (IGB) treatment to group-based CBT improves weight maintenance after initial weight loss using LED.

MATERIALS AND METHODS: In this open-label randomized controlled trial, adults aged 30-65 years with BMI 32.5-45 kg/m2 underwent a 6-month run-in period combining LED and group-based CBT and were subsequently randomized to CBT and 1-year IGB or CBT alone. The primary endpoint was weight change in percent between randomization (6 months from enrollment) and 18 months (from enrollment), compared to total body weight (TBW) at enrollment. Secondary outcomes included the proportion of participants achieving weight loss thresholds, metabolic parameters and health-related quality of life (HRQoL).

RESULTS: Of 126 enrolled (mean 43.7 years; BMI 38.0 kg/m2), 107 were randomized 6 months after enrollment (IGB n = 51; CBT n = 56) and lost -18.7% (SE: 0.64) of TBW. At 18 months, the mean weight change from randomization was 5.2% with IGB versus 10.1% with CBT (p < 0.001). A significantly greater proportion of IGB recipients achieved ≥ 5% (84.3% vs. 63.6%; p = 0.021) and ≥ 10% (70.6% vs. 45.5%; p = 0.013) weight loss after 18 months, compared to the CBT group. Improvements in metabolic parameters and HRQoL showed no between-group differences.

CONCLUSIONS: As an adjunct to group-based CBT and after LED-induced weight loss, IGB treatment provided a modest advantage in weight maintenance for up to 18 months, although safety concerns remain and long-term studies are warranted.

OBJECTIVES: European countries implemented highly diverse mitigation policies during the COVID-19 pandemic, ranging from strict nationwide lockdowns to more voluntary approaches. This study aims to understanding how timing, stringency, and comprehensiveness of policy responses influenced epidemic trajectories by applying machine learning-based counterfactual analysis.

METHODS: Data from 27 European OECD countries between January 2020 and December 2022 were analysed. Daily epidemiological data, including COVID-19 cases, deaths, effective reproduction number were linked with government response indicators, demographics, vaccination, testing, and mobility data. Temporal Fusion Transformer (TFT) models were applied for multi-horizon time series forecasting by capturing nonlinear relationships between policy response indicators and COVID-19 outcome variables. Simulations were conducted under eight hypothetical response scenarios, ranging from the loosest to the strictest policy bundles. The impacts of policy responses on COVID-19 outcomes were assessed by comparing the counterfactual scenarios with the factual outcomes.

RESULTS: TFT models achieved excellent predictive accuracy (percentage mean absolute error <10%). The strictest responses were associated with reduced daily COVID-19 cases by over 10% in several countries, notably Hungary, Switzerland, and Turkey, while the loosest responses were associated with increased incidence by 10-20%, with the highest value observed in Poland. Associations with mortality were smaller and heterogeneous, with potentially maximum reductions of 7-10% in Belgium, Portugal, and Switzerland under strict scenarios. Over early relaxation from the restrictions might lead to outcomes as adverse as those under continuously loose policies. Feature importance analyses highlighted restrictions on mobility and gatherings, vaccination, testing, and fiscal measures as dominant drivers, alongside country-level factors such as age structure and chronic disease burden.

CONCLUSIONS: The TFT-based machine learning framework demonstrated favourable feasibility and interpretability, reinforcing its value in guiding policy decisions. Comprehensive, multi-domain interventions outperformed partial or short-lived restrictions. Lifting measures before achieving sufficient immunity and epidemic control posed substantial risks. Stringent policies reduced transmission, but their impact on mortality was constrained, which might be due to demographic and systemic vulnerabilities. Adaptive, data-driven strategies integrating epidemiology, policy, and structural context are essential to strengthen policy responses against future pandemics.