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Janssen waist circumference
Waist Circumference, supplied by Janssen, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/waist+circumference/circumference+waist/10__2147_slash_ijgm__s584966-32-67-62
Average 86 stars, based on 1 article reviews
waist circumference - by Bioz Stars, 2026-09
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Article Title: Beyond BMI.
Article Snippet: When comparing BMI and waist circumference as markers of cardiometabolic risk, Janssen et al. found that “ .

Article Title: GA-Net: A geographical attention neural network for the segmentation of body torso tissue composition.
Article Snippet: Purpose: Body composition analysis (BCA) of the body torso plays a vital role in the study of physical health and pathology and provides biomarkers that facilitate the diagnosis and treatment of many diseases, such as type 2 diabetes mellitus, cardiovascular disease, obstructive sleep apnea, and osteoarthritis.. In this work, we propose a body composition tissue segmentation method that can automatically delineate those key tissues, including subcutaneous adipose tissue, skeleton, skeletal muscle tissue, and visceral adipose tissue, on positron emission tomography/computed tomography scans of the body torso.. Methods: To provide appropriate and precise semantic and spatial information that is strongly related to body composition tissues for the deep neural network, first we introduce a new concept of the body area and integrate it into our proposed segmentation network called Geographical Attention Network (GA-Net).

Article Title: Association between accelerometer-measured physical activity, glucose metabolism, and waist circumference in older adults.
Article Snippet: [12] Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk.

Article Title: Association Between Sarcopenia Index and Central Obesity: Age- and Gender-Specific Patterns and Clinical Implications
Article Snippet: According to the Global Burden of Disease Obesity Collaborators, the worldwide population of obese individuals reached 603.7 million, with obesity prevalence doubling in over 70 countries since 1980.1 Obesity, particularly central obesity, is associated with an elevated risk of several chronic diseases, such as diabetes, hypertension, hyperlipidemia, non-alcoholic fatty liver disease, obstructive sleep apnea, cardiovascular disease (CVD), and chronic renal failure.2 Ian Janssen et al reported that waist circumference, not body mass index (BMI), represents obesity-related risk.3 Therefore, people with abdominal obesity (central obesity) have a higher risk of comorbidities, even at a normal BMI.

Article Title: Financial health and obesity.
Article Snippet: We use individual-level panel data from the English Longitudinal Survey of Ageing over the period 2004–2013 to investigate the links between financial health and obesity.. We find that having no debt (high savings) is associated with a 3.6 (1.6) percentage point lower probability of having a Body Mass Index in excess of 30.. Our results are robust to using different estimation methods, to measuring financial health with a subjective indicator, and adiposity with waist circumference.

Article Title: Altered neural correlates of episodic memory for food and non-food cues in females with overweight/obesity.
Article Snippet: Episodic memory formation is fundamental to cognition and plays a key role in eating behaviors, indirectly promoting the maintenance and acceleration of weight gain.. Impaired episodic memory function is a hallmark of people with overweight/obesity, nevertheless, little research has been conducted to explore the effects of overweight/obesity on neural networks associated with episodic memory.. The current study aimed to unravel the behavioral responses and neurocognitive mechanisms underlying the episodic memory for food and non-food cues in females with overweight/obesity.

Article Title: GA-Net: A geographical attention neural network for the segmentation of body torso tissue composition
Article Snippet: Other anthropometric measurements are also widely used in practice, including, for example, waist circumference, which measures body fat as a predictor of obesity-related health risk ( Janssen et al., 2004 ).

Metabolic Labelling:

Article Title: Obesity and eating behavior from the perspective of twin and genetic research.
Article Snippet: .. Since visceral fat is metabolically more active and more strongly associated with metabolic diseases than subcutaneous fat (Wajchenberg, 2000), it has been suggested that other anthropometric indicators, especially waist circumference as it is considered a measure of visceral fat located in the abdominal cavity, should be used (Janssen et al., 2004). ..



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Waist <t>circumference</t> across the four weight-status groups (A–D). Boxplots display the median and interquartile range, with whiskers indicating the minimum and maximum values. Crosses (+) represent mean values, and dots indicate outliers. Statistically significant between-group differences are indicated in the figure ( p < 0.05). Data were analysed using the Kruskal–Wallis test followed by Dunn's post-hoc test with correction for multiple comparisons.
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Waist circumference across the four weight-status groups (A–D). Boxplots display the median and interquartile range, with whiskers indicating the minimum and maximum values. Crosses (+) represent mean values, and dots indicate outliers. Statistically significant between-group differences are indicated in the figure ( p < 0.05). Data were analysed using the Kruskal–Wallis test followed by Dunn's post-hoc test with correction for multiple comparisons.

Journal: Frontiers in Pediatrics

Article Title: Fair Play a Tavola: a school-based framework integrating nutrition education and anthropometric screening for early identification of excess weight in preschool children

doi: 10.3389/fped.2026.1802064

Figure Lengend Snippet: Waist circumference across the four weight-status groups (A–D). Boxplots display the median and interquartile range, with whiskers indicating the minimum and maximum values. Crosses (+) represent mean values, and dots indicate outliers. Statistically significant between-group differences are indicated in the figure ( p < 0.05). Data were analysed using the Kruskal–Wallis test followed by Dunn's post-hoc test with correction for multiple comparisons.

Article Snippet: Anthropometric screening was conducted with parental consent to measure weight, height, and waist circumference using standardized equipment (SECA scales, stadiometers, and non-elastic measuring tapes).

Techniques: