Chronic disease risk factors among hospital employees: A cross-sectional study in Türkiye. by Volkan Medeni, Vildan Topcu, Fatma Bozdağ, İrem Medeni

“…Dependent variables were smoking, alcohol use, physical inactivity, and body mass index (BMI) categories. Data on participants' characteristics, habits, and behaviors were obtained from the hospital system or with open-ended questions. …”
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Korelasi Kadar Adiponektin dengan Kadar Kolesterol High Density Lipoprotein pada Penyandang Obes by Fiona Septi Mulya, Efrida Efrida, Zelly Dia Rofinda

“…Research subjects were grouped into two groups based on WHO Asia Pacific body mass index (BMI) classification. First-degree obesity group (25.0 £ BMI <30.0 kg/m2) and second-degree obesity group (BMI ≥ 30.0kg/ m2). …”
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Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review by Yihun Mulugeta Alemu, Sisay Mulugeta Alemu, Dan Chateau, Nasser Bagheri, Kinley Wangdi

“…Laboratory predictors (eg, cholesterol and diabetes) had strong HRs, while body mass index in non-laboratory models showed limited effect. …”
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Impacts of stigma and discrimination on people with obesity who smoke cigarettes by Liza A. Kolbasov, Arryn A. Guy, Cara M. Murphy

“…This study examined associations between stigma, discrimination, and health for people with overweight or obesity (body mass index [BMI] ≥ 25) who smoke cigarettes (cigarettes smoked/day ≥ 5) who reported interest in quitting smoking and minimizing weight gain. …”
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PLZF Expression during Colorectal Cancer Development and in Normal Colorectal Mucosa according to Body Size, as Marker of Colorectal Cancer Risk by Francesco Mariani, Paola Sena, Giulia Magnani, Stefano Mancini, Carla Palumbo, Maurizio Ponz de Leon, Luca Roncucci

“…Strong association was found between CD56+ colonic mucosa cell infiltration and body mass index. Interestingly, an increased stromal PLZF-reactivity was present in NM of obese subjects. …”
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Total Antioxidant Status in Type 2 Diabetic Patients in Palestine by Akram T. Kharroubi, Hisham M. Darwish, Mutaz A. Akkawi, Abdelkareem A. Ashareef, Zaher A. Almasri, Khaldoun A. Bader, Umaiyeh M. Khammash

“…Only 9.8% of the subjects had normal body mass index (BMI) levels (<25), 29% were overweight (≥25 to <30), and 61.2% were obese (≥30). …”
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Yogic Practices as a Complementary Approach to Physical Fitness: An Intervention Study by Tarak Nath Pramanik, Aminur Rahaman, Gopal Chandra Saha, Anupam Roy, Punam Pradhan

“…Yoga is an ancient practice that has gained attention for its potential benefits on muscular strength and endurance, flexibility, power, agility, balance, reaction time, and body mass index (BMI), making it an effective complementary approach for improving overall health and physical fitness. …”
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Electrochemical skin conductance to assess peripheral neuropathy in rheumatic diseases with or without type 2 diabetes using sudoscan by Osama M. I. Mohamed, Nagwa M. M. Ali, Mohammed O. Ibrahim, Dana Sarmini, Farah Ibrahim, Mariam Al Hosany

“…The mean glycated haemoglobin A1c (HBA1c) was 7.4% in diabetic patients and 5.8% in non-diabetic patients Additionally, all patients had a mean blood pressure of 134/72 and a mean Body Mass Index (BMI) of 31.40 kg/m2. Among the study patients, the most common RD was osteoarthritis, which affected 56.8% of the patients. …”
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Isotemporal substitution of sedentary time with different physical activity intensities and sleep in obesity parameters across eight latin American countries by Eduardo Rossato de Victo, Diego Sales, Diego G. D. Christofaro, Mauro Fisberg, Irina Kovalskys, Pablo del Val Martín, Gerson Ferrari

“…The parameters of obesity were defined using body mass index (BMI) and waist circumference (WC). Regression analyses were conducted for isotemporal analysis of the association between substituting 30 min/day of ST with light physical activity (LPA), moderate to vigorous physical activity (MVPA) and sleep in relation to BMI and WC. …”
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Association between the aromatase (CYP19A1) gene variant rs10046 and cardiovascular risk in postmenopausal women by Betânia Rodrigues dos Santos, Gislaine Casanova, Thais Rasia da Silva, Karen Oppermann, Poli Mara Spritzer

“…Results: The participants had a mean age of 56.07 ± 5.58 years and a mean body mass index (BMI) of 27.73 ± 5.41 kg/m². The 10-year ASCVD risk was estimated to be low, borderline, intermediate, and high in 64.7%, 12.8%, 19.8%, and 2.7% of the participants, respectively. …”
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Physical functioning trajectories over statutory retirement: a finnish occupational cohort study by Pauliina Saha, Jatta Salmela, Aapo Hiilamo, Anna Liisa Aho, Tea Lallukka

“…Our aim was to identify distinct developmental trajectories of physical functioning over statutory retirement and to examine how social- (age, gender, marital status, education) and health-related (physical workload, self-reported sleep problems, alcohol consumption, smoking, fruit and vegetable (F&V) consumption, leisure-time physical activity (LTPA), and body mass index (BMI)) factors before retirement were associated with the identified trajectories. …”
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Self-reported dyspareunia and outcome satisfaction after spontaneous second-degree tear compared to episiotomy: A register-based cohort study. by Mette L Josefsson, Sara Sohlberg, Cecilia Ekéus, Eva Uustal, Maria Jonsson

“…Logistic regression was used and results are presented by Odds Ratios (OR) with 95% confidence intervals (CI) after adjustment for age, body mass index and mode of delivery.<h4>Results</h4>30.0% of women with a spontaneous tear and 29.1% of women with an episiotomy reported mild or moderate dyspareunia, while 2.4% of women with a spontaneous tear compared to 3.8% of women with an episiotomy reported strong or unbearable dyspareunia (aOR 1.5; CI 0.9-2.4). 73.4% of women with a spontaneous tear and 67.1% with episiotomy were satisfied or very satisfied with their outcome, while 6.7% with an episiotomy compared to 3.7% with a spontaneous tear were dissatisfied (aOR 1.8; CI 1.2-2.6). …”
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Long‑term outcomes of adjustable gastric banding: a 15‑year prospective randomized trial comparing 2 band types in 103 patients by Žygimantas Juodeikis, Gintautas Brimas

“…Results: Baseline characteristics were similar between the groups, with a mean (SD) patient age of 45.9 (11.7) years and a mean (SD) preoperative body mass index of 47.5 (7.3) kg/m2. Of the 103 patients, 55 (53.3%) completed the 15-year follow-up. …”
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Body image in women participants of strength training: association with sociodemographic factors and practice time by Manoela Vieira Sousa, Cilene Rebolho Martins, Morgana Lunardi, Grazieli Maria Biduski, Elisa Pinheiro Ferrari, Cíntia de la Rocha Freitas

“…This group of women are typically in search for an ideal body pattern stipulated by society. e purpose of the present study was to identify in the women the perception with BI, classify then as satisfied or dissatisfied, and association this information whit age group, anthropometric indicators (body mass index and perimeter of waist), and variables related to the practice of ST (purpose and time of the practice). …”
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Risk Factors for Worsening of Bone Loss in Patients Newly Diagnosed with Inflammatory Bowel Disease by Yi Yin, Xiaofeng Lu, Zhun Li, Song Liu, Lihua Shao, Lei Cao, Rui-Qing Liu, Liang-Yu Huang, Zhen-Xing Zhu, Zhen Guo, Yi Li, Wei-Ming Zhu

“…Age at diagnosis, body mass index, and serum phosphorus were identified as independent factors associated with bone loss at baseline. …”
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Effectiveness of Anthropometric Measurements for Identifying Diabetes and Prediabetes among Civil Servants in a Regional City of Northern Ethiopia: A Cross-Sectional Study by Ataklti Gebertsadik Woldegebriel, Kiros Ajemu Fenta, Asfawosen Berhe Aregay, Abraham Desta Aregay, Nega Bezabih Mamo, Tewolde Woldearegay Wubayehu, Alemayehu Bayray, Afework Mulugeta

“…Waist-to-hip ratio was better identifying diabetes (AUC = 0.67) while waist circumference-to-height ratio was better identifying prediabetes (AUC = 0.63) in men compared to body mass index. The optimal cut-off point with maximum sensitivity and specificity of waist circumference for identifying diabetes and prediabetes was 83.5 cm and 82.9 cm in women, respectively. …”
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Effect of “Time To Surgery” on the Endometrial Cancer Prognosis by Engin Celik, Harika Yumru Celiksoy, Hamdullah Sozen, Hale Goksever Celik, Semen Onder, Mehmet Yavuz Salihoglu, Samet Topuz

“…Clinical characteristics of the patients were comparable between the groups, except for comorbid conditions and body mass index. Using cox-regression analysis, time to operation did not have a significant effect on both recurrence and cancer-associated death risk. …”
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Comparison of Tools for Nutritional Assessment and Screening of Hospitalized Patients: A study on Surgical Patients by Susetyowati SUSETYOWATI, Amalia Sarah SHOLIKHATI, Dinda Krisma CAHYANINGRUM, Azizah Isna RACHMAWATI, Adeodatus Yuda HANDAYA

“…Patients were assessed during the first 24 h of admission in the ward from January to July 2022 using the NRI, NRS-2002, SNST, body mass index (BMI), mid-upper arm circumferences (MUAC), albumin serum, hemoglobin level, total lymphocyte count (TLC), and SGA. …”
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Moderate Weight Reduction in an Outpatient Obesity Intervention Program Significantly Reduces Insulin Resistance and Risk Factors for Cardiovascular Disease in Severely Obese Adole... by J. Grulich-Henn, S. Lichtenstein, F. Hörster, G. F. Hoffmann, P. P. Nawroth, A. Hamann

“…Mean standard deviation score of the body mass index (SDS-BMI) in the study group dropped significantly from +2.5 ± 0.5 to 2.3 ± 0.6 (P<0.0001) after participation in the program. …”
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Association between serum albumin levels and erectile dysfunction in American Adults: A cross-sectional study from NHANES 2001-2004. by Haibin Wen, Zhenyu Lan, Xueming Liang, Huabin Su, Yuqi Qin

“…The association between serum albumin and erectile dysfunction was evaluated using weighted logistic regression models across four models: (1) Crude model (unadjusted); (2) Model 1: Adjusted for age, race, poverty-to-income ratio (PIR), marital status, education level, and body mass index (BMI); (3) Model 2: Adjusted for factors in Model 1 plus physical activity, smoking status, drinking status, and Healthy Eating Index (HEI-2015); (4) Model 3: Adjusted for factors in Model 2 plus remaining potential covariates. …”
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