Diagnosis and Classification of Obesity


2
Diagnosis and Classification of Obesity


Brijesh Madhok


The World Health Organisation (WHO) defines obesity as abnormal or excessive accumulation of fat that presents a risk to health. This simple definition coverts a chronic and complex disease, which can manifest metabolically causing debilitating and life‐threatening conditions. Obesity affects over a third of the world’s population, and the prevalence is on the rise particularly in children and adolescents. The consequences of obesity are a significant increase in serious diseases, such as type 2 diabetes, obstructive sleep apnoea, hypertension, cardiovascular disease, hepatic steatosis, certain cancers as well as a profoundly negative effect on psychosocial well‐being and functional ability. As a result, the socioeconomic impact of obesity particularly on medical services is huge.


Diagnostic Criteria for Obesity


The first hurdle for professionals treating obesity comes with the difficulty in diagnosing obesity. The most common way to diagnose obesity is to calculate one’s body mass index (BMI), which is not ideal. A person’s BMI is derived by a simple formula of weight in kilograms divided by the individual’s height in metres squared (BMI = kgm‐2). The normal range of BMI is considered to be 18.5–24.9 kgm‐2, and greater than 30 kgm‐2 is classed as being obese. This may be a very simple measure of adiposity and is not the most accurate one. Body mass index does not differentiate fat from muscle, as it is not a direct measure of adiposity. Thus, the high BMI of a muscular person does not translate to him or her being obese. Secondly, BMI does not take into consideration a person’s sex or age. It is well known that the body fat composition increases with age, and females have higher percentage of body fat compared to males of the same weight and height. Nonetheless, BMI is the most commonly used measure in the clinical assessment of patients suffering from obesity and also in the published literature. In addition, BMI has been shown to be equivalent to more advanced methods such as measuring skinfold thickness and bioelectrical impedance in identifying the risk of cardiovascular diseases and other obesity‐related medical conditions.


When assessing adiposity, the distribution of fat is thought to be of more relevance than the actual presence of it. A clinically relevant measure of adiposity can be the person’s waist circumference, which indicates the distribution of body fat. Perhaps further assessment of visceral obesity can be obtained by measuring the waist‐to‐hip ratio. Patients suffering from central obesity are at much higher risk of developing obesity‐related medical conditions. The cut‐off values of waist circumference are considered to be more than 40 in. (102 cm) in men, and >35 in. (88 cm) in women with possibly lower values in Asian patients. Similarly, men with the waist‐to‐hip ratio of more than 1 and women with more than 0.8 are considered to be at risk of developing obesity‐related co‐morbid diseases. However, there can be limitations in taking these measurements in clinical practice. The correct site to measure waist circumference is mid‐way between the costal margin and iliac crests. It can be difficult to palpate these landmarks in morbidly obese patients, and this can limit the application of measuring waist circumference and hence the waist‐to‐hip ratio in the assessment of these patients. As such in individuals with BMI > 35 kgm‐2, measuring waist circumference has limited role in adding to the predictive value of risk of developing obesity‐related medical conditions. Nonetheless, in patients with BMI < 35 kgm‐2, recording their waist circumference can be a very useful clinical tool to assess their risk of developing metabolic syndrome and particularly cardiovascular complications. Evidence from large cohort studies indicates that measuring the waist‐to‐hip ratio may be a more accurate assessment of cardiovascular disease mortality risk than waist circumference or BMI.

Only gold members can continue reading. Log In or Register to continue

Stay updated, free articles. Join our Telegram channel

May 14, 2023 | Posted by in GENERAL SURGERY | Comments Off on Diagnosis and Classification of Obesity

Full access? Get Clinical Tree

Get Clinical Tree app for offline access