Impact of noninsulin-dependent diabetes mellitus (level of control) on sex hormone profile and erectile function by Abdullah A. Khawaji, Hossam S. El-Tholoth, Muath A. Albarakati, Bander A. Binjabaan, Abdulaziz Alzahrani, Abdulmajeed Althobity, Abdulmalik Almardawi, Khaled Bedaiwi, Mussa AlNuami

“…Retrieved data include patient’s demographics, body mass index (BMI), hormonal profile, Complete Blood Count (CBC), lipid profile, prostate-specific antigen (PSA), urate, Vitamin D level, and the severity of ED as assessed by the International Index of Erectile Function (IIEF) scores. …”
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Pilates exercise in pregnancy: a systematic review and meta-analysis by Yuxuan Li, Heran Lu, Liuwei Zhang, Yijia Ren, Xiaotong Dai, Lin Lin

“…Among these, 3 studies exhibited a low risk of bias, while 8 studies presented an unclear risk of bias. (2) The meta-analysis results indicated that Pilates exercise resulted in non-significant changes in the Body Mass Index (BMI) of pregnant women (SMD 0.02; 95% CI, -0.27 to 0.31; P = 0.887), the body weight of pregnant women (SMD 0.25; 95% CI, -0.52 to 1.02; P = 0.519), the mode of delivery (RR 1.41; 95% CI, 0.95 to 2.09; P = 0.093), and the Low-density lipoprotein (LDL) levels of pregnant women (SMD − 1.182; 95% CI, -2.443 to 0.079; P = 0.066). …”
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Establishing of a risk prediction model for metabolic dysfunction-associated steatotic liver disease: a retrospective cohort study by Nan Li, Chenbing Liu, Zhangfan Lu, Wenjian Wu, Feng Zhang, Lihong Qiu, Chao Shen, Di Sheng, Zhong Liu

“…Results Our study indicated that male, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG), serum uric acid to creatinine ratio (SUA/Cr) and white blood cell (WBC) were associated with MASLD incidence. …”
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Coronary Atherosclerotic Plaque Vulnerability Rather than Stenosis Predisposes to Non-ST Elevation Acute Coronary Syndromes by Mohamed Laimoud, Farouk Faris, Helmy Elghawaby

“…The Syntax score was significantly higher in group I compared to group II (18.7 ± 7.8 vs. 8.07 ± 2.5, p=0.001). Body mass index (BMI) was significantly higher in group II while triglycerides levels were higher in group I (P=0.01 & P=0.04, respectively). …”
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Optimization of surgical methods for the treatment of gynecomastia by A.G. Ihnatieva, S.M. Yurchyshyn

“…A total of 132 patients (mean age 31.5 ± 2.8 years, body mass index 25.2 ± 3.4, I–II ASA) were operated for gynecomastia. …”
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General medical comorbidities in psychotic disorders in the Finnish SUPER study by Johan Ahti, Tuula Kieseppä, Willehard Haaki, Jaana Suvisaari, Solja Niemelä, Kimmo Suokas, Minna Holm, Asko Wegelius, Olli Kampman, Markku Lähteenvuo, Tiina Paunio, Jari Tiihonen, Jarmo Hietala, Erkki Isometsä

“…In addition, we examined whether body mass index (BMI) and smoking as risk factors for GMCs explain differences between diagnostic groups. …”
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Sagittal Inclination Angle of the Graft Affects Graft Maturity and Knee Stability After Anterior Cruciate Ligament Reconstruction by Ming Li, Fangang Meng, Dianbo Long, Dorje Wencheng, Yanlin Zhong, Yan Kang, Peihui Wu, Aishan He

“…A multivariate stepwise regression analysis showed that SIA and body mass index were significant influencing factors associated with the graft SNQ. …”
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The association between eight complete blood count-derived inflammatory markers and muscle health by Jingyuan Zhang, Yuqi Wang, Heng Liu, Zhuolin Lei, Shouquan Cheng, Hong Cao

“…In the stratified analysis by body mass index (BMI), only the SII, NLR, and NMLR were unaffected by BMI. …”
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Role of Age, Comorbidity, and Frailty in the Prediction of Postoperative Complications After Surgery for Vulvar Cancer: A Retrospective Cohort Study with the Development of a Nomog... by Giovanni Delli Carpini, Francesco Sopracordevole, Camilla Cicoli, Marco Bernardi, Lucia Giuliani, Mariasole Fichera, Nicolò Clemente, Anna Del Fabro, Jacopo Di Giuseppe, Luca Giannella, Enrico Busato, Andrea Ciavattini

“…A logistic regression model for the rate of Clavien-Dindo 2+ 30-days complications was run, considering the age-adjusted Charlson Comorbidity Index (AACCI), body mass index (BMI), and frailty as exposures. Lesion characteristics and surgical procedures were considered as confounders. …”
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Factors influencing malnutrition among adolescent girls in The Gambia: a mixed-methods exploratory study by Haddy Jallow-Badjan, Tanefa A. Apekey, Maria J. Maynard

“…FGD data were analysed using thematic analysis. Body mass index (BMI)-for-age and height-for-age z-scores, mid-upper arm circumference, and waist: hip ratios were assessed and descriptive statistics used to explore the data obtained. …”
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Weight Change and Predictors of Weight Change Among Patients Initiated on Darunavir/Cobicistat/Emtricitabine/Tenofovir Alafenamide or Bictegravir/Emtricitabine/Tenofovir Alafenamid... by Bruno Emond, Carmine Rossi, Aurélie Côté-Sergent, Keith Dunn, Patrick Lefebvre, Marie-Hélène Lafeuille, Prina Donga

“…**Objectives:** To describe demographic and clinical characteristics of insured patients with HIV-1 in the United States initiating darunavir/​cobicistat/​emtricitabine/​tenofovir alafenamide (DRV/c/FTC/TAF) or bictegravir/FTC/TAF (BIC/FTC/TAF), assess the differences in weight and body mass index (BMI) change between cohorts up to one year after treatment initiation, and identify the predictors of weight gain associated with each treatment. …”
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Machine learning model and nomogram to predict the risk of heart failure hospitalization in peritoneal dialysis patients by Liping Xu, Fang Cao, Lian Wang, Weihua Liu, Meizhu Gao, Li Zhang, Fuyuan Hong, Miao Lin

“…Baseline moderate or severe renal disease, systolic blood pressure (SBP), body mass index (BMI), age, Charlson Comorbidity Index (CCI) score were strongly associated with HF hospitalization, whereas age, CCI score, creatinine, age, high-density lipoprotein cholesterol (HDL-C), total cholesterol, baseline estimated glomerular filtration rate (eGFR) were the most significant predictors of mortality. …”
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Distribution and Related Influencing Factors of AMH Level in Family-Planning Women of Childbearing Age: A Cross-Sectional Study from Beijing, China by Song J, Gao S, Zhao L, Tong X

“…Collected data included age, education level, ethnicity, height, weight, and systolic and diastolic blood pressure. We calculated the body mass index (BMI) of each participant. The collected blood test results included AMH, fasting blood glucose (FBG), thyroid-stimulating hormone (TSH), creatinine (Cr), and alanine aminotransferase, and hemoglobin levels and platelet count. …”
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Prevalence of and factors associated with symptoms consistent with a diagnosis of irritable bowel syndrome among resident physicians in standardised training in China: a cross-sect... by Xin Wang, Ning Li, Xia Li, Zhigang Li, Jun Zhao, Xuefei Wang, Xin Hao, Jiayi Yang, Junjian Tian

“…Univariate and multivariate logistic regression models were constructed to assess the associations of age, sex, body mass index, stress, depression, anxiety, sleep quality and IBS.Results Of the included resident doctors, 77.2% were female, 20.4% were obese or underweight and 8.6% had symptoms consistent with a diagnosis of IBS. …”
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Impact of obesity, overweight and underweight on life expectancy and lifetime medical expenditures: the Ohsaki Cohort Study by Shinichi Kuriyama, Miyuki Kawado, Shuji Hashimoto, Ichiro Tsuji, Atsushi Hozawa, Toshimasa Sone, Masato Nagai, Masako Kakizaki, Kaori Ohmori-Matsuda

“…We examined the association between body mass index, life expectancy and lifetime medical expenditure.Design Prospective cohort study using individual data from the Ohsaki Cohort Study.Setting Miyagi Prefecture, northeastern Japan.Participants The 41 965 participants aged 40–79 years.Primary and secondary outcome measures The life expectancy and lifetime medical expenditure aged from 40 years.Results In spite of their shorter life expectancy, obese participants might require higher medical expenditure than normal weight participants. …”
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Assessment of Exercise-Induced Dehydration Status Based on Oral Mucosal Moisture in a Field Survey by Gen Tanabe, Tetsuya Hasunuma, Yasuo Takeuchi, Hiroshi Churei, Kairi Hayashi, Kaito Togawa, Naoki Moriya, Toshiaki Ueno

“…Receiver operating characteristic curves were constructed to ascertain whether variations in oral mucosal moisture content could discern body mass losses (BMLs) of 1.5% and 2%. <b>Results:</b> A significant correlation was observed between the sweat rate during exercise and the change in oral mucosal moisture content before and after exercise (Spearman’s rank correlation coefficient: ρ = −0.58, <i>p</i> < 0.001). …”
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Vasoreactive testing prevalence and characteristics in patients with idiopathic pulmonary arterial hypertension by Goncharova Natalia, Kirill Lapshin, Aelita Berezina, Irina Zlobina, Anton Ryzhkov, Zhaneta Matakaeva, Elizaveta Andreeva, Olga Moiseeva

“…Patients with ND VRT due to the physicians decision were often older than 60 years, had higher body mass index, symptoms of right heart failure, hemoptysis, arrhythmias, high NT-proBNP, and hemodynamic criteria of high risk in comparison with patients with done VRT. …”
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Association of Obesity and Socioeconomic Status among Women of Childbearing Age Living in Urban Area of Morocco by Fatima Barich, Fatima Ezzahra Zahrou, Fatima Zahra Laamiri, Nisrine El Mir, Manelle Rjimati, Amina Barkat, El Arbi Rjimati, Hassan Aguenaou

“…At recruitment, socioeconomic status (SES) of each participant was assessed, anthropometric parameters were recorded, and body mass index (BMI), waist circumference, and waist-to-hip ratio (WHR) were measured to assess overweight and obesity. …”
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Association between weight-adjusted waist-index and symptoms of sleep apnea in US adults: results from 2015–2018 national health and nutrition examination survey by Edmore Madondo, Paddington T. Mundagowa, Ayesha Mukhopadhyay, Debra Bartelli, Yu Jiang, Fawaz Mzayek

“…Abstract Background Literature shows that traditional measures of obesity such as body mass index (BMI), waist-to-height ratio (WtHR), waist-to-hip ratio (WHR), and waist circumference (WC) may not be precise measures of obesity compared to weight-adjusted waist-index (WWI), a relatively new obesity index. …”
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The obesity paradox in osteoporosis risk among older adults is mostly driven by women: a population-based prospective study by Qingfeng Luo, Shiyong Zhang, Zixin Liang, Danni Wang, Yanlin Zhong, Bin Xia, Peng Xie, Can Wang, Jinqiu Yuan, Ziji Zhang, Xingsheng Li

“…Methods A cross-sectional and prospective study was conducted using data from 177,734 participants in the UK Biobank. The association of body mass index (BMI), waist circumference (WC), and fat percentage with BMD was examined using Spearman correlation analysis with baseline BMD data. …”
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