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Objective: To investigate the association between visceral fat area (VFA) and metabolic syndrome (Mets) among normal weight Japanese. Design: A cross-sectional study. Setting: The health check-up centre of the Takeda Hospital group in Kyoto, Japan. Methods: This study involved 1674 men and 1448 women aged 30-74 years who underwent medical check-ups in 2012 in the health check-up centre. They were stratified by Body Mass Index (BMI cut-off for obesity is set at 23.0 kg/m² for Asians): normal weight 18.5-22.9 kg/m² or higher weight ≥23.0 kg/m². The age-adjusted ORs of the 2nd to 4th groups of sex-specific VFA quartiles compared with the 1st quartile for a Mets component clustering were estimated. The clustering was having two or more of the following factors: high blood pressure, high fasting blood glucose (FBG), low high-density lipoprotein cholesterol (HDL-C) and high triglycerides. Statistical analyses were conducted in 2016. Results: Participants in the 2nd to 4th VFA quartiles had significantly higher clustering risks; ORs were 3.4 (1.5 to 8.0), 6.3 (2.8 to 14.2) and 9.3 (4.2 to 20.7) for normal weight participants, and 1.7 (1.2 to 2.6), 2.6 (1.8 to 3.9) and 6.0 (4.1 to 8.8) for higher weight participants, respectively. The ORs of the 4th VFA quartile for Mets components were significantly higher; ORs for normal weight participants were 2.1 (1.5 to 3.0) (high blood pressure), 2.4 (1.4 to 4.2) (high FBG), 5.2 (2.1 to 12.9) (low HDL-C) and 12.0 (5.7 to 25.3) (high triglycerides), and higher weight participants were 3.9 (2.8 to 5.5), 4.1 (2.8 to 6.2), 3.9 (2.2 to 6.9) and 5.0 (3.4 to 7.4), respectively. Conclusions: Among participants with normal weight, as well as those of higher weight, dose-dependent responses were observed between VFA and risk for Mets components and the clustering among Japanese adults. VFA may be useful information for interventions to improve metabolic risk factors in people with normal weight. [ABSTRACT FROM AUTHOR]

Objectives Nationwide lifestyle intervention—specific health guidance (SHG) in Japan—employs counselling and education to change unhealthy behaviours that contribute to metabolic syndrome, especially obesity or abdominal obesity. We aimed to perform a model-based economic evaluation of SHG in a low participation rate setting.Design A hypothetical population, comprised 50 000 Japanese aged 40 years who met the criteria of the SHG, used a microsimulation using the Markov model to evaluate SHG’s cost-effectiveness compared with non-SHG. This hypothetical population was simulated over a 35-year time horizon.Setting SHG is conducted annually by all Japanese insurers.Outcome measures Model parameters, such as costs and health outcomes (including quality-adjusted life-years, QALYs), were based on existing literature. Incremental cost-effectiveness ratios were estimated from the healthcare payer’s perspective. Deterministic and probabilistic sensitivity analyses (PSA) were conducted to evaluate the uncertainty around the model input parameters.Results The simulation revealed that the total costs per person in the SHG group decreased by JPY53 014 (US$480) compared with that in the non-SHG group, and the QALYs increased by 0.044, wherein SHG was considered the dominant strategy despite the low participation rates. PSA indicated that the credibility intervals (2.5th–97.5th percentile) of the incremental costs and the incremental QALYs with the SHG group compared with the non-SHG group were −JPY687 376 to JPY85 197 (−US$6226 to US$772) and −0.009 to 0.350 QALYs, respectively. Each scenario analysis indicated that programmes for improving both blood pressure and blood glucose levels among other risk factors for metabolic syndrome are essential for improving cost-effectiveness.Conclusions This study suggests that even small effects of counselling and education on behavioural modification may lead to the prevention of acute life-threatening events and chronic diseases, in addition to the reduction of medication resulting from metabolic syndrome, which results in cost savings.

Introduction Heart failure (HF) is increasingly common and associated with excess morbidity, mortality, and healthcare costs. Treatment of HF can alter the disease trajectory and reduce clinical events in HF. However, many cases of HF remain undetected until presentation with more advanced symptoms, often requiring hospitalisation. Predicting incident HF is challenging and statistical models are limited by performance and scalability in routine clinical practice. An HF prediction model implementable in nationwide electronic health records (EHRs) could enable targeted diagnostics to enable earlier identification of HF.Methods and analysis We will investigate a range of development techniques (including logistic regression and supervised machine learning methods) on routinely collected primary care EHRs to predict risk of new-onset HF over 1, 5 and 10 years prediction horizons. The Clinical Practice Research Datalink (CPRD)-GOLD dataset will be used for derivation (training and testing) and the CPRD-AURUM dataset for external validation. Both comprise large cohorts of patients, representative of the population of England in terms of age, sex and ethnicity. Primary care records are linked at patient level to secondary care and mortality data. The performance of the prediction model will be assessed by discrimination, calibration and clinical utility. We will only use variables routinely accessible in primary care.Ethics and dissemination Permissions for CPRD-GOLD and CPRD-AURUM datasets were obtained from CPRD (ref no: 21_000324). The CPRD ethical approval committee approved the study. The results will be submitted as a research paper for publication to a peer-reviewed journal and presented at peer-reviewed conferences.Trial registration details The study was registered on Clinical Trials.gov (NCT 05756127). A systematic review for the project was registered on PROSPERO (registration number: CRD42022380892).

Objective Risk-guided atrial fibrillation (AF) screening may be an opportunity to prevent adverse events in addition to stroke. We compared events rates for new diagnoses of cardio-renal-metabolic diseases and death in individuals identified at higher versus lower-predicted AF risk.Methods From the UK Clinical Practice Research Datalink-GOLD dataset, 2 January 1998–30 November 2018, we identified individuals aged ≥30 years without known AF. The risk of AF was estimated using the FIND-AF (Future Innovations in Novel Detection of Atrial Fibrillation) risk score. We calculated cumulative incidence rates and fit Fine and Gray’s models at 1, 5 and 10 years for nine diseases and death adjusting for competing risks.Results Of 416 228 individuals in the cohort, 82 942 were identified as higher risk for AF. Higher-predicted risk, compared with lower-predicted risk, was associated with incident chronic kidney disease (cumulative incidence per 1000 persons at 10 years 245.2; HR 6.85, 95% CI 6.70 to 7.00; median time to event 5.44 years), heart failure (124.7; 12.54, 12.08 to 13.01; 4.06), diabetes mellitus (123.3; 2.05, 2.00 to 2.10; 3.45), stroke/transient ischaemic attack (118.9; 8.07, 7.80 to 8.34; 4.27), myocardial infarction (69.6; 5.02, 4.82 to 5.22; 4.32), peripheral vascular disease (44.6; 6.62, 6.28 to 6.98; 4.28), valvular heart disease (37.8; 6.49, 6.14 to 6.85; 4.54), aortic stenosis (18.7; 9.98, 9.16 to 10.87; 4.41) and death from any cause (273.9; 10.45, 10.23 to 10.68; 4.75). The higher-risk group constituted 74% of deaths from cardiovascular or cerebrovascular causes (8582 of 11 676).Conclusions Individuals identified for risk-guided AF screening are at risk of new diseases across the cardio-renal-metabolic spectrum and death, and may benefit from interventions beyond ECG monitoring.