Normal weight obesity is a condition of having normal body weight, but high body fat percentages with the same health risks of obesity.
Contents
Introduction
Obesity represents a global public health problem and is associated with cardiovascular disease (CVD) and reduced lifespan. The BMI-based classification of obesity do not adequately reflect the degree of adiposity so percentage body fat (PBF) is a better predictor of risk of obesity. New and more accurate formulas for epidemiological studies are of interest to the scientific community. The outdated BMI formula developed by Quetelet, is not an accurate measurement of adiposity but represents an imprecise mathematical estimate. Use of BMI is more simple for its convenience, safety, and minimal cost, but it does not take into account several important factors affecting adiposity. Since BMI does not measure body fat directly and not distinguishes fat from lean or bone mass, its use could be inaccurate. At the same BMI level either individuals with a large proportion of total body fat mass (TBFat)or subjects with a considerable muscle mass (weight-lifter) can be classified as "obese". Greater loss of muscle mass leading to sarcopenic obesity in women occurs increasingly with age. Moreover, men’s BMI does not consider the inverse relationship between muscular strength and mortality. These are the reasons why it is useful to re-evaluate how body fat is determined.
Percentage body fat (PBF), which is calculated as total body fat (TBFat) divided by total mass multiplied by 100, is a direct measure to know body fat and a better predictor of risk of obesity-related diseases than BMI.
In 1995, the World Health Organization (WHO) defined obesity based on a PBF >25% for men and PBF >35% for women. However, more accurate measures of adiposity uses levels of body fat >25% for men and >30% for women. De Lorenzo A. et al. ,revealed a false negative classification of obesity obtained through BMI. ‘’Nearly 25% of normal weight individuals display abnormal metabolic profiles associated with obesitysistance and hsCRP are associated with PBF in a large population of BMI- defined normal weight individuals’’
Who is a metabolically obese normal weight (MONW) subject ?
A metabolically obese normal weight subject (MONW) is a person who has normal weight and BMI, but display some metabolic characteristics that may increase the possibility of developing the metabolic syndrome, in the same way of obese individuals. MONW subjects are not obese but they have an excess of visceral fat and so are predisposing to insulin resistance, hypertension and CVD. The identified metabolically obese, normal weight individuals (MONW) had benefits when they went through programs of energy restriction and weight loss. If patients were challenged to a 4- to 12-week period of diet and exercise, there was metabolic improvement Some studies suggested that the main issue to explain the metabolic abnormalities in individuals not particularly overweight was fat distribution. On the basis of these studies, it was proposed a scoring method to identify a metabolically obese normal weight individual. Depending on the presence of associated diseases or biochemical abnormalities related to insulin resistance, individuals would be assigned a score to base the diagnosis of metabolically obese normal weight. Karelis et al and Dvorak et al realized that insulin sensitivity was related to body composition and that body composition could be a major determinant for the metabolic behavior of individuals.
De Lorenzo syndrome
In 2006, De Lorenzo A. et al. have identified the Normal Weight Obese (NWO)syndrome, characterized by normal body weight and BMI, but high TBFat accumulation. The frequency of NWO syndrome is typically found in females. A study was conducted at the University of Rome Tor Vergata, Human Nutrition Unit, on a sample of Caucasian women from Centre-South of Italy. In the study was included a complete and clear medical history of women. The subjects were also categorized into BMI subgroups according to World Health Organization (WHO) criteria, other study parameters were: gender, age, anthropometric measurements, Dual-energy X-ray absorptiometry(DXA),statistical analysis. The following predictive equation of PBF was derived: PBF= 0.920 x weight (Kg) – 0.004 x (weight (Kg))2 - 0.326 x height (cm)+ 0.263 x hip (cm) + 147.110 x log (waist (cm)) – 32.309 x sqrt (waist (cm)) - 332.116 This equation allows the prediction of individual PBF on the base of easily available measures: height, weight, hip and waist circumference. Based on BMI levels and predicted values of PBF women were classified into underweight, normal, pre-obese and obese. All the 10 obese women incorrectly classified by predicted values of PBF were considered pre-obese. Among the 62 obese women incorrectly classified by BMI, 29 were identified as pre-obese but 33 were regarded as normal. The majority of women misclassified as normal by BMI were found to be pre-obese or obese by PBF. Moreover, it is important to recognize that some subjects, while having a BMI of up to 26 kg/m2, actually had a PBF of <30%, probably due to a greater percentage of muscular mass seen in athletic individuals. In post-menopausal women was reported that both BMI and WC (waist circumference, it reflects abdominal fat levels ) were associated with mortality. In the Nurses’ Health Study, waist circumference were also strongly associated with increased risk of coronary heart disease among women with a BMI of <25 kg/m2. Waist and hip measurements are useful to know different physical and metabolic characteristics of these two regions and therefore the diverse clinical outcomes in subjects with a gynoid or android body conformation. Early inflammation and genetic predisposition characterizes the syndrome. A cross-sectional study carried out to assess the prevalence of NWO in Switzerland. The classical perception of adipose tissue and skeletal muscle as an energy storage has been replaced by the notion that these tissues have a role in lipid and glucose metabolism by producing a large number of adipokines (that have a great role in the pathogenesis of obesity, insulin resistance, hypercholesterolaemia , hypertriglyceridaemia, low levels of HDL cholesterol, hypertension, glucose intolerance and CVD) and myokines. .
Metabolic risk and oxidative stress
After years of studies the adipose tissue, which was considered an energy storage organ, is now considered as an endocrine organ. TBFat distribution may be different in subjects with the same BMI, and lean and obese subjects share different metabolic characteristics. It has been estimated that normal weight individuals could have abnormal metabolic profiles and be at increased risk of developing obesity associated diseases. To valuate the NWO condition, body composition (by dual-energy X-ray absorptiometry), plasma levels of some cytokines, GSH, lipid hydroperoxide, nitric oxide, (NO2−/NO3−), were measured and compared between groups. The study clearly indicates that NOW are contextually exposed to an oxidative stress related to metabolic. In obese and NWO women subjects an inflammatory status is accompanied by oxidative stress.
Connection between obesity and systemic inflammation
Obesity and glucose metabolism are related to systemic inflammation, involving a number of proinflammatory cytokines produced by many cell types that also appear to be major regulators of adipose tissue metabolism. Obesity and diabetes are also related with a low activation of the immune system. Adipokines and myokines appear to be involved in local autocrine/paracrine interactions within adipose tissue and muscle, respectively. Adipocytokines and proinflammatory factors, such as TNF-α, interleukin IL-6 and IL-1, have been demonstrated to play an important role in obesity-related comorbidities.