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189 results for “body mass index”
Relations between access to sport and green spaces and Body Mass Index in the canton of Geneva
<p>README.txt</p> <p>-------------------------------------------------<br> Science et Ingénierie de l'Environnement (SIE)<br> Bâtiment GR<br> EPFL ENAC SSIE-GE<br> CH-1015 Lausanne<br> *<br> *<br> ------------------------------------------------.<br> *<br> *<br> "Envdata.csv" contains the data used in the study entitled:<br> "Relations between access to sport and green spaces and Body Mass Index in the canton of Geneva", <br> (C. El Khoury,Y. Frischholz, B. Heutte, V. Remy, M. Schornoz, 2020)<br> *<br> *<br> -------------------------------------------------<br> *<br> *<br> Variables : Description [unit]<br> *<br> ID : Bus Santé participant's ID [-]<br> x_lv03, y_lv03 : Coordinates of participants residence (LV03) [m]<br> year_survey : Bus Santé participation year [-]<br> #SPORT10min : Density of sport infrastructures within a buffer of 10 minutes walk around residences [-]<br> dist_1SPORT : Direct distance to first sport infrastructure from residences [m]<br> meanNDVI10min : Mean NDVI within a buffer of 10 minutes walk (to remove biases due to large water bodies, the lake area was removed from the 10 minutes buffer) [m]<br> BMI_randorder : Values of BMI used in a randomized order for confidentiality reasons [kg/m2]<br> *<br> *<br> -------------------------------------------------</p>
Data from: Intestinal microbiota is influenced by gender and body mass index
Intestinal microbiota changes are associated with the development of obesity. However, studies in humans have generated conflicting results due to high inter-individual heterogeneity in terms of diet, age, and hormonal factors, and the largely unexplored influence of gender. In this work, we aimed to identify differential gut microbiota signatures associated with obesity, as a function of gender and changes in body mass index (BMI). Differences in the bacterial community structure were analyzed by 16S sequencing in 39 men and 36 post-menopausal women, who had similar dietary background, matched by age and stratified according to the BMI. We observed that the abundance of the Bacteroides genus was lower in men than in women (P<0.001, Q = 0.002) when BMI was > 33. In fact, the abundance of this genus decreased in men with an increase in BMI (P<0.001, Q<0.001). However, in women, it remained unchanged within the different ranges of BMI. We observed a higher presence of Veillonella (84.6% vs. 47.2%; X2 test P = 0.001, Q = 0.019) and Methanobrevibacter genera (84.6% vs. 47.2%; X2 test P = 0.002, Q = 0.026) in fecal samples in men compared to women. We also observed that the abundance of Bilophila was lower in men compared to women regardless of BMI (P = 0.002, Q = 0.041). Additionally, after correcting for age and sex, 66 bacterial taxa at the genus level were found to be associated with BMI and plasma lipids. Microbiota explained at P = 0.001, 31.17% variation in BMI, 29.04% in triglycerides, 33.70% in high-density lipoproteins, 46.86% in low-density lipoproteins, and 28.55% in total cholesterol. Our results suggest that gut microbiota may differ between men and women, and that these differences may be influenced by the grade of obesity. The divergence in gut microbiota observed between men and women might have a dominant role in the definition of gender differences in the prevalence of metabolic and intestinal inflammatory diseases.
Data from: Association of body mass index and age with incident diabetes in Chinese adults: a population-based cohort study
Objective. Type 2 diabetes mellitus is increasing in young adults, and greater adiposity is considered a major risk factor. However, whether there is an association between obesity and diabetes and how this might be impacted by age is not clear. Therefore, we investigated the association between body mass index (BMI) and diabetes across a wide range of age groups (20-30, 30-40, 40-50, 50-60, 60-70, ≥70 years old). Design. We performed a retrospective cohort study using healthy screening program data. Setting. A total of 211,833 adult Chinese persons > 20-years-old across 32 sites and 11 cities in China (Shanghai, Beijing, Nanjing, Suzhou, Shenzhen, Changzhou, Chengdu, Guangzhou, Hefei, Wuhan, Nantong) were selected for the study; these persons were free of diabetes at baseline. Primary and secondary outcome measures. Fasting plasma glucose levels were measured and information regarding the history of diabetes was collected at each visit. Diabetes was diagnosed as fasting plasma glucose ≥ 7.00 mmol/L and/or self-reported diabetes. Patients were censored at the date of diagnosis or the final visit, whichever came first. Results. With a median follow-up of 3.1 years, 4,174 of the 211,833 participants developed diabetes, with an age-adjusted incidence rate of 7.35 per 1,000 persons. The risk of incident diabetes increased proportionally with increasing baseline BMI values, with a 23% increased risk of incident diabetes with each kg/m2 increase in BMI (95%CI: 1.22, 1.24). Across all age groups, there was a linear association between BMI and the risk of incident diabetes, although there was a stronger association between BMI and incident diabetes in the younger age groups (age × BMI interaction, P < 0.0001). Conclusions. An increased BMI is also independently associated with a higher risk of developing diabetes in young adults and the effects of BMI on incident diabetes were accentuated in younger adults.
Comparative Evaluation of Body Mass Index, Waist Circumference and Waist-To-Hip Ratio as Correlates of Glucose Intolerance among Rural Dwellers in Nigeria
<p>This research investigates the comparative efficacy of Body Mass Index (BMI), Waist Circumference (WC), and Waist-to-Hip Ratio (WHR) as correlates of glucose intolerance among rural dwellers in Nigeria. Conducted as a descriptive cross-sectional study in Oyo State, Nigeria, the research involved adults aged 18 years and above. The study employed a multi-stage cluster sampling technique, selecting participants from rural communities. Exclusion criteria included pregnant women and those with known diabetes or medications affecting glucose metabolism. Anthro-pometric indices and blood glucose levels were determined using Hanson's weighing scale, a meter rule, and biochemical auto-analyzers. The BMI, WC, and WHR were utilized to assess obesity and abdominal adiposity. Blood glucose levels were measured for fasting and 2-hour post-prandial samples. Data analysis involved descriptive statistics and chi-square tests using SPSS version 26. Results from the study revealed demographic characteristics and medical history of participants. Findings indicated a significant association between anthropometric parameters and gender. Notably, WHR exhibited a strong correlation with glucose intolerance, emphasizing its potential as a predictor. The study also presented the correlation of BMI, WC, and WHR with blood glucose levels, categorizing participants into different risk groups based on these indices. This research contributes valuable insights into the effectiveness of BMI, WC, and WHR in predicting glucose intolerance among rural dwellers in Nigeria. The findings underscore the importance of tailored interventions for specific populations, considering regional variations in health determinants. Future research can build upon these results to develop targeted strategies for diabetes prevention and management in rural communities.</p>
Supplemental material for "Statins, type 2 diabetes and body mass index: a univariable and multivariable Mendelian randomization study"
<p>Supplemental material for "Statins, type 2 diabetes and body mass index: a univariable and multivariable Mendelian randomization study" by Guoyi Yang and C Mary Schooling.</p>
Phase Angle, Lean Body Mass Index and Tissue Edema and Immediate Outcome of Cardiac Surgery Patients
ClinicalTrials.gov study NCT03644030. IPD Sharing: NO. Countries: 1. Publications: 12.
Growth Parameters & Body Mass Index in Children With Chronic Diseases
ClinicalTrials.gov study NCT05801718. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
The Relationship Between Body Mass Index and Patient Outcomes in Low Flow Anaesthesia
ClinicalTrials.gov study NCT06636448. IPD Sharing: NO. Countries: 1. Publications: 3.
Measuring the Impact of Dietary Supplementation With a High Fiber, High Antioxidant Aleurone on Biomarkers of Cardiovascular Disease and Gut Microbiota in Adults With High Body Mass Index
ClinicalTrials.gov study NCT02067026. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Improvement of Physical Activity and Correction of Body Mass Index in School Children
ClinicalTrials.gov study NCT00176371. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Ultra-Processed Foods and Appetite Regulation: Acute Effects Across Body Mass Index Categories
ClinicalTrials.gov study NCT06798220. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Body Mass Index (BMI) and Quality of Life (QoL) in Cancer Patients
ClinicalTrials.gov study NCT03873064. IPD Sharing: UNDECIDED. Countries: 1. Publications: 8.
Association Between Body Mass Index and HFNC Therapy Success
ClinicalTrials.gov study NCT04799132. IPD Sharing: Not stated. Countries: 1. Publications: 17.
New Body Mass Index (BMI) Cut-offs for the Diagnosis of Obesity and Comorbidities
ClinicalTrials.gov study NCT01055626. IPD Sharing: NO. Countries: 1. Publications: 4.
Comparison of Body Mass Index and Metabolic Score for Visceral Adiposity in Evaluation of Visceral Adiposity
ClinicalTrials.gov study NCT05648409. IPD Sharing: NO. Countries: 1. Publications: 1.
Prospective Survey of Body Mass Index in People With Spinal Cord Injury.
ClinicalTrials.gov study NCT03369080. IPD Sharing: NO. Countries: 1. Publications: 1.
Correlation of Preoperative Gastric Residual Volume With Body Mass Index and Aspiration Risk in Laparoscopic Bariatric Surgery
ClinicalTrials.gov study NCT07032207. IPD Sharing: NO. Countries: 1. Publications: 11.
Correlation of Irisin and Adipokine Levels With Body Mass Index and Risk Factors for Metabolic Syndrome in Hispanic Children
ClinicalTrials.gov study NCT02320110. IPD Sharing: Not stated. Countries: 1. Publications: 20.
Planter Pressure and Body Mass Index Affect Balance in Normal Children
ClinicalTrials.gov study NCT06478836. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effects of a Lifestyle Intervention on Body Mass Index in Patients With Bipolar Disorder
ClinicalTrials.gov study NCT00980863. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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