China
Africa
Explore chapters and articles related to this topic
Coronary Heart Disease Risk Factors
Published in Mark C Houston, The Truth About Heart Disease, 2023
Body weight and body mass index (BMI) correlate with CHD and MI. However, the total body fat and especially belly fat (visceral fat) correlates with CVD, CHD, and MI much better. Body fat and regional fat can be measured with a machine called body impedance analysis (BIA) (Figure 18.1). Normal body fat is 22% or less for women and 16% or less for men. At a total body fat (TBF) of 29%, most men will have metabolic syndrome. At a TBF of 37%, most women will have metabolic syndrome.
Diabetes Mellitus, Obesity, Lipoprotein Disorders and other Metabolic Diseases
Published in John S. Axford, Chris A. O'Callaghan, Medicine for Finals and Beyond, 2023
Body weight is determined by genetic, environmental, cultural and psychosocial factors. Obesity is a condition in which excess body fat accumulates, such that health may be affected. In healthy adult men of average weight, body fat = 15–20% and for women = 25–30% of total body weight. It is difficult to measure body fat directly, so the body mass index (BMI) is usually used as an indirect measure.
Weight Concerns
Published in Carolyn Torkelson, Catherine Marienau, Beyond Menopause, 2023
Carolyn Torkelson, Catherine Marienau
There are two kinds of body fat: subcutaneous fat and visceral (intra-abdominal) fat.Subcutaneous fat is the belly fat you can feel if you pinch excess skin and soft tissue around your middle. In most people, about 90% of body fat is subcutaneous, the kind that lies in a layer just beneath the skin.Visceral fat accumulates in your abdomen in the spaces surrounding the liver, intestines, and other organs. It’s also stored in the omentum, an apron-like flap of tissue that lies under the belly muscles and covers the intestines. Although visceral fat makes up only 10% of body fat, it is linked more strongly than subcutaneous fat to greater risk of serious health problems such as type 2 diabetes and heart disease. No matter what your body shape or BMI, excess belly fat isn’t good for your health.
Why is nutrition vital for advancing ALS care and clinical research?
Published in Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 2023
Edward J. Kasarskis, Rup Tandan
How can we practically achieve this in the clinic and in the research setting? We developed a simple approach to serially measure body fat (6) and provide guidelines for maintaining energy balance (7) and hydration (8). Why is fat an important measure of nutritional adequacy? Body fat has been termed a “precious resource” when viewed from the perspective of its primary purpose, namely, ensuring survival during times of nutritional inadequacy such as war, famine or disaster. This is usually considered in the context of malnutrition of an entire population. However, in ALS net energy insufficiency in the face of abundant available calories is primarily the end result of weakness of the upper extremities and bulbar musculature. Hence, serial measurement of body fat is an indicator of the success of current nutritional approaches adopted by patients. Stable or increasing body fat provides prima facie evidence for adequate energy intake. Whereas decreasing body fat indicates that, however valiant the effort, energy intake is outpaced by energy expenditure, resulting in chronic energy inadequacy. Simply put: this is starvation and in ALS results in more severe disease (9), rapid progression (6), and earlier death (6). As with caloric deficiency, dehydration in ALS shortens survival (8). We must move beyond the outdated concept that merely getting through a meal without choking equates with adequate nutritional and water intake. It does not. This concept is a recipe for starvation and dehydration, and all their negative consequences.
Improvement of body composition in 8- to 11-year-old schoolboys: effects of a 6-months lifestyle intervention A retrospective evaluation of the “EDDY-Kids” prevention study
Published in Child and Adolescent Obesity, 2022
Paula Moliterno, Julia Matjazic, Kurt Widhalm
At baseline, participants in the control group had a lower body fat percentage than those assigned to the intervention group. This baseline difference could be attributed to the fact that the control group (3rd-grade students) was approximately one year younger than the intervention group (4th-grade students); therefore, being the older children closer to puberty can accentuate increases in body fat percentage. Moreover, boys in the intervention group had a median body fat percentage corresponding to excessive body fat (Lobstein and Brinsden 2019). According to Mc Carthy et al., normal body fat percentage is ranked between the 2nd and 85th percentile, representing in a 10-year-old boy a range between 12.8% and 22.8% (Lobstein and Brinsden 2019). Boys classified with obesity in the intervention group almost doubled the number of boys in the control group (16/36 versus 8/33). Therefore, the intervention promoting healthier diet habits and increasing physical activity may have had a greater impact on this group’s reduction of body fat. Nevertheless, the BMI classification at baseline and after the intervention showed no positive effect on nutritional status categories; the children with excessive body weight for age remained in these categories.
Comparing the performance of body mass index, waist circumference and waist-to-height ratio in predicting Malaysians with excess adiposity
Published in Annals of Human Biology, 2022
Nie Yen Low, Chin Yi Chan, Shaanthana Subramaniam, Kok-Yong Chin, Soelaiman Ima Nirwana, Norliza Muhammad, Ahmad Fairus, Pei Yuen Ng, Nor Aini Jamil, Noorazah Abd Aziz, Norazlina Mohamed
Body fat accumulation is associated with numerous health consequences. However, tools for direct measurement of body fat, such as DXA and computed tomography, are not easily accessible (Duren et al. 2008), thus necessitating surrogate tools to identify patients at risk for excess adiposity. These tools could aid in the timely management of patients with a high cardiometabolic risk profile. However, inaccurate cut-off values of a screening tool would lead to misdiagnosis of excess adiposity, subsequently delaying further risk assessment and management. The current study is important because it showed that at the current cut-offs, WC performed better than BMI and WHtR in detecting excess adiposity. Besides, a lower BMI and WC cut-offs are better in identifying Malaysians at risk of excess adiposity.