Coffee, including caffeinated and decaffeinated coffee, and the risk of hepatocellular carcinoma: a systematic review and dose–response meta-analysis by Paul Roderick, Peter Clive Hayes, Julie Parkes, Ryan Buchanan, Oliver John Kennedy, Jonathan Andrew Fallowfield

“…There was evidence that the association was not significantly altered by stage of liver disease or the presence/absence of high alcohol consumption, high body mass index, type 2 diabetes mellitus, smoking, or hepatitis B and C viruses. …”
Get full text

High Body Roundness Index Is Associated With Unhealthy Sleep Patterns: Insights From NHANES (2007–2014) by Pingchuan Liu, Yuding Luo, Xing He, Jiali Zhang, Fanzhou Ren, Bingyang Zhang, Bo Zheng, Jian Wang

“…Receiver operating characteristic (ROC) analysis was used to compare the diagnostic performance of BRI and body mass index (BMI) in identifying unhealthy sleep patterns. …”
Get full text

The Role of Probiotics in Managing Glucose Homeostasis in Adults with Prediabetes: A Systematic Review and Meta-Analysis by Chao Sun, Qingyin Liu, Xiaona Ye, Ronghua Li, Miaomiao Meng, Xingjun Han

“…However, no significant difference was observed in fasting blood glucose, insulin, total cholesterol, triglycerides, low-density lipoprotein cholesterol, interleukin-6, tumor necrosis factor-α, and body mass index. Subgroup analyses showed that probiotics significantly reduced HbA1c in adults with prediabetes in Oceania, intervention duration of ≥3 months, and sample size <30. …”
Get full text

Diagnoses of postpartum urinary retention using next-generation non-piezo ultrasound technology: assessing the accuracy and benefits by Ruben Plöger, Charlotte Behning, Adeline Walter, Ulrich Gembruch, Brigitte Strizek, Florian Recker

“…Intraclass correlation coefficients, Bland-Altman plots, and Pearson correlation coefficients were used for analyzing the reliability and agreement between the measurements of these devices and were calculated for subgroups as body mass index, mode of delivery and timepoint of delivery. …”
Get full text

Obesity prevalence among healthcare professionals in England: a cross-sectional study using the Health Survey for England by Richard G Kyle, Jane Wills, Catherine Mahoney, Louise Hoyle, Muireann Kelly, Iain M Atherton

“…Objective To estimate obesity prevalence among healthcare professionals in England and compare prevalence with those working outside of the health services.Design Cross-sectional study based on data from 5 years (2008–2012) of the nationally representative Health Survey for England.Setting England.Participants 20 103 adults aged 17–65 years indicating they were economically active at the time of survey classified into four occupational groups: nurses (n=422), other healthcare professionals (n=412), unregistered care workers (n=736) and individuals employed in non-health-related occupations (n=18 533).Outcome measure Prevalence of obesity defined as body mass index ≥30.0 with 95% CIs and weighted to reflect the population.Results Obesity prevalence was high across all occupational groups including: among nurses (25.1%, 95% CI 20.9% to 29.4%); other healthcare professionals (14.4%, 95% CI 11.0% to 17.8%); non-health-related occupations (23.5%, 95% CI 22.9% to 24.1%); and unregistered care workers who had the highest prevalence of obesity (31.9%, 95% CI 28.4% to 35.3%). …”
Get full text

Modifiable Risk Factors for Stroke in Syria: A Nationwide Multi-centre Case-Control Study by Mhd Mustafa Albitar, Subhia Maya, Khaled Kalalib Al Ashabia, Ghassan Hamzeh, Ameer Kakaje

“…IS was significantly associated with multiple chronic conditions including atrial fibrillation AF [AOR 5.04 (2.64–9.62)], high body mass index (overweight [AOR 2.09 (1.28–3.40)], obesity [AOR 4.17 (2.32–7.50)]), hypercholesterolemia [AOR 2.10 (1.34–3.28], hypertension HTN [AOR 1.83 (1.23–2.73)], and diabetes mellitus DM [AOR 1.79 (1.18–2.71)]. …”
Get full text

A Novel Oxidative Stress Mediator in Acute Appendicitis: Thiol/Disulphide Homeostasis by Sefa Ozyazici, Faruk Karateke, Umit Turan, Adnan Kuvvetli, Huseyin Kilavuz, Burak Karakaya, Pınar Ozaltun, Murat Alısık, Ozcan Erel

“…In this study, seventy-one (43 male and 28 female) patients diagnosed with AA and 71 (30 male and 41 female) healthy volunteers were included. Age, gender, body mass index (BMI), haemoglobin (Hb), white blood cell (WBC), c-reactive protein (CRP), and thiol/disulphide homeostasis parameters (native thiol, total thiol, disulphide, disulphide/native thiol, native thiol/total thiol, and disulphide/total thiol ratios) were compared between the groups. …”
Get full text

Risk Factor Analysis in Vascular Access Complications for Hemodialysis Patients by Cristian Dan Roşu, Sorin Lucian Bolintineanu, Bogdan Florin Căpăstraru, Roxana Iacob, Emil Robert Stoicescu, Claudia Elena Petrea

“…Demographic data, comorbidities, and lifestyle factors, including age, gender, body mass index (BMI), smoking status, hypertension, diabetes, and cardiovascular disease (CVD), were recorded and analyzed. …”
Get full text

Association of Body Fat Percentage with Time in Range Generated by Continuous Glucose Monitoring during Continuous Subcutaneous Insulin Infusion Therapy in Type 2 Diabetes by Yuting Ruan, Jiana Zhong, Rongping Chen, Zhen Zhang, Dixing Liu, Jia Sun, Hong Chen

“…Body composition was measured using bioelectrical impedance analysis (BIA) and overfat was defined as an amount of body fat of at least 25% of total body mass for men or at least 30% for women. Multiple linear regression models were used to evaluate the independent association of body fat percentage with TIR after adjusting for confounding factors. …”
Get full text

Impact of Different Metabolic Indicators on Ventricular Repolarization Indices in Obese Children: A Case Control Study by Asmaa A El Sehmawy, Rasha Abd El Samad Fawaz, Nadia Ahmed Agiba, Eman Aziz Elsherbiny, Nglaa Fathi Agaba, Doaa Sayed Mohammed, Haidy Mahmoud Nasr, Fatma Elzhraa AE Diab, Amal M Ahmed, Shorouk Issa Mahfouz, Heba T Okda, Doaa Sadek Ahmed

“…A significant positive correlation was detected between QTc and JTc dispersion and the following variables: waist circumference, body mass index (BMI), blood pressure, fasting insulin, HOMA-IR index, and LDL. …”
Get full text

Clinical characteristics of hospitalized male adolescents and young adults with avoidant/restrictive food intake disorder (ARFID) by Jason M. Nagata, Anita V. Chaphekar, Patrick Low, Ruben Vargas, Kyle T. Ganson, Anthony Nguyen, Sara M. Buckelew, Andrea K. Garber, Amanda E. Downey

“…Compared to all youth with AN, youth with ARFID had lower body mass index (BMI, 15.7 vs. 17.0 kg/m2, p = .001) and lower vitamin D (26.5 vs. 33.0 ng/mL, p = .003). …”
Get full text

Advancing Alzheimer’s disease risk prediction: development and validation of a machine learning-based preclinical screening model in a cross-sectional study by Yanfei Chen, Bing Wang, Yankai Shi, Wenhao Qi, Shihua Cao, Bingsheng Wang, Ruihan Xie, Jiani Yao, Xiajing Lou, Chaoqun Dong, Xiaohong Zhu, Danni He

“…An oversampling method was applied to balance the data set.Interventions This study has no interventions.Participants The study included 2379 participants, of whom 507 were diagnosed with AD.Primary and secondary outcome measures Including accuracy, precision, recall, F1 score, etc.Results 11 variables were critical in the training phase, including educational level, depression, insomnia, age, Body Mass Index (BMI), medication count, gender, stenting, systolic blood pressure (sbp), neurosis and rapid eye movement. …”
Get full text

Ability of Different Measures of Adiposity to Identify High Metabolic Risk in Adolescents by Carla Moreira, Rute Santos, Susana Vale, Paula C. Santos, Sandra Abreu, Ana I. Marques, Luísa Soares-Miranda, Jorge Mota

“…This study aimed to evaluate the screening performance of different measures of adiposity: body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) for high metabolic risk in a sample of adolescents. …”
Get full text

Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches by Nafiseh Hosseini, Hamid Tanzadehpanah, Amin Mansoori, Mostafa Sabzekar, Gordon A. Ferns, Habibollah Esmaily, Majid Ghayour-Mobarhan

“…Result After feature selection analysis and assessing multicollinearity, six factors (Mid-arm Circumference (MAC), Waist Circumference (WC), Body Roundness Index (BRI), Body Adiposity Index (BAI), Body Mass Index (BMI), age) were used in the final model. …”
Get full text

Evaluation of placental growth factor, Vitamin D, and systemic inflammatory index as predictive biomarkers for preeclampsia severity: a retrospective cohort study by Xiaoyan Han, Hua Yang

“…The regression models adjusted for potential confounders, including maternal age, body mass index (BMI), and parity. Results In the training cohort, significant differences were observed among control, mild, and severe preeclampsia groups, with severe cases showing elevated PIV (515.8 ± 126.7) and reduced levels of PlGF (12.5 ± 5.8 pg/mL) and Vitamin D (8.4 ± 1.9 ng/mL) compared to controls (P < 0.001). …”
Get full text

Association between neutrophil-to-high-density lipoprotein cholesterol ratio and non-alcoholic fatty liver disease or metabolic dysfunction-associated steatotic liver disease: evid... by Na Zhu, Yanyan Li, Yingying Lin, XinYu Cui, Xin Li, Xin Li

“…Additionally, we performed stratified analyses based on gender, age, body mass index, diabetes, hypertension, smoking status, and history of cardiovascular disease to evaluate the consistency of these associations across different subgroups.ResultsA total of 6,526 participants were included in the study. 2,839 (weighted 44.1%) participants were diagnosed with NAFLD and 2,813 (weighted 43.7%) participants were diagnosed with MASLD. …”
Get full text

Sodium-Glucose Cotransporter-2 (SGLT-2) Attenuates Serum Uric Acid (SUA) Level in Patients with Type 2 Diabetes by Mazhar Hussain, Asim Elahi, Abid Hussain, Javed Iqbal, Lubna Akhtar, Abdul Majid

“…The changes in SUA level were primary end points while changes in body weight and body mass index (BMI) from baseline to end point were secondary end points. …”
Get full text

Evidence for a Specific Diabetic Cardiomyopathy: An Observational Retrospective Echocardiographic Study in 656 Asymptomatic Type 2 Diabetic Patients by Isabelle Pham, Emmanuel Cosson, Minh Tuan Nguyen, Isabela Banu, Isabelle Genevois, Patricia Poignard, Paul Valensi

“…SMI was independently associated with hypokinesia (odds ratio 14.7 [2.7–81.7], p<0.01) and systolic dysfunction (OR 114.6 [1.7–7907], p<0.01), while HbA1c (OR 1.9 [1.1–3.2], p<0.05) and body mass index (OR 1.6 [1.1–2.4], p<0.05) were associated with systolic dysfunction. …”
Get full text

Incorporating low haemoglobin into a risk prediction model for conversion in minimally invasive gynaecologic oncology surgeries by Kevin H. Nguyen, Hyundeok Joo, Solmaz Manuel, Lee-may Chen, Lee-lynn Chen

“…Multivariable logistic regression was used to study the effects of older age, higher body mass index (BMI), higher American Society of Anaesthesiologist (ASA) physical status, and lower preoperative haemoglobin (Hb) on odds of converting from minimally invasive to open surgery. …”
Get full text

Association between Chinese visceral adiposity index and lower urinary tract symptoms suggestive of benign prostatic hyperplasia (LUTS/BPH): a national cohort study by Kunhui Chang, Bo Li, Gang Wang, Hao Zhou, Yonghao Chen, Hongbing Gu

“…Eight obesity-related indices—namely Body mass index (BMI), Waist-height ratio (WHtR), Triglyceride-glucose.BMI (TyG.BMI), TyG. …”
Get full text