Obesity

 

Table Of Contents


Thesis Abstract

Abstract
Obesity is a complex and multifaceted public health issue that has reached epidemic proportions globally. This research aims to explore the various factors contributing to the rise in obesity rates, including changes in dietary patterns, sedentary lifestyles, genetic predisposition, and environmental influences. The impact of obesity on individual health, as well as its broader implications for healthcare systems and society as a whole, is also examined. The study will investigate the role of diet in obesity, focusing on the consumption of high-calorie, low-nutrient foods that have become increasingly prevalent in modern diets. Additionally, the sedentary nature of many modern lifestyles, characterized by desk jobs, screen time, and decreased physical activity, will be analyzed for its contribution to the obesity epidemic. Genetic factors that influence metabolism, fat storage, and appetite regulation will be explored to understand the interplay between genetics and the environment in the development of obesity. The influence of environmental factors such as food availability, marketing, urban design, and socioeconomic status on obesity rates will also be examined. The health consequences of obesity, including an increased risk of chronic diseases such as diabetes, cardiovascular disease, and certain types of cancer, will be highlighted. The economic burden of obesity on healthcare systems, due to increased healthcare costs and productivity losses, will be analyzed to underscore the broader societal implications of this public health crisis. The research will also investigate current strategies and interventions aimed at preventing and managing obesity, including dietary guidelines, physical activity recommendations, behavioral therapy, and medical treatments. The effectiveness of these interventions in different population groups and settings will be evaluated to identify best practices for obesity prevention and treatment. Overall, this research aims to provide a comprehensive overview of the complex factors contributing to the obesity epidemic and its impact on individual health and society. By shedding light on the causes and consequences of obesity, as well as potential strategies for prevention and management, this study seeks to inform public health efforts to address this critical issue and improve the health and well-being of populations worldwide.

Thesis Overview

1.0 INTRODUCTION

1.1 OBESITY

Obesity can be defined as an excess of Body Fat (BF). There is no consensus on a cutoff point for excess fatness of overweight or obesity in children and adolescents. Obesity is now so common within the world’s population that it is beginning to replace undernutrition and infectious diseases as the most significant contributor to ill health. In particular, obesity is associated with diabetes mellitus, coronary heart disease, certain forms of cancer, and sleep-breathing disorders (Caterson and Gill, 2002).

Obesity is defined by a body-mass index (weight divided by square of the height) of 30 kg m–2 or greater, but this does not take into account the morbidity and mortality associated with more modest degrees of overweight, nor the detrimental effect of intra-abdominal fat (Chan, 1994). The global epidemic of obesity results from a combination of genetic susceptibility, increased availability of high-energy foods and decreased requirement for physical activity in modern society. Obesity should no longer be regarded simply as a cosmetic problem affecting certain individuals, but an epidemic that threatens global well-being  (Caterson and Gill, 2002).

Obesity causes or exacerbates many health problems, both independently and in association with other diseases. In particular, it is associated with the development of type 2 diabetes mellitus, coronary heart disease (CHD), an increased incidence of certain forms of cancer, respiratory complications (obstructive sleep apnoea) and osteoarthritis of large and small joints (Styne et al., 2005).

There are also several methods to measure the percentage of body fat. In research, techniques include underwater weighing (densitometry), multi-frequency bioelectrical impedance analysis (BIA) and magnetic resonance imaging (MRI). In the clinical environment, techniques such as body mass index (BMI), waist circumference, and skin fold thickness have been used extensively. Although, these methods are less accurate than research methods, they are satisfactory to identify risk (Caterson and Gill, 2002; Styne et al., 2005).

Table 1 – Cut-off points proposed by a WHO expert committee for the

classification of overweight

BMI* (kg m–2)

WHO classification

Popular description

<18.5

Underweight

Thin

18.5–24.9

_____

‘Healthy’, ‘normal’, ‘acceptable’

25.0–29.9

Grade 1 overweight

Overweight

30.0–39.9

Grade 2 overweight

Obesity

≥40.0

Grade 3 overweight

Morbid obesity

*BMI is the weight in kilograms divided by the square of the height in metres.

The data presented in Tables 1 and 2 reflect knowledge acquired largely from epidemiological studies in developed countries. Preliminary information from developing nations indicates that lower cut-off levels for both BMI and waist circumference (see Table 2) are necessary for certain populations who are at particular risk from comparatively modest degrees of overweight.

Source: Peter, 2000

Table 2 – Waist circumference predicts risk of metabolic complications

Increased risk

Substantially increased risk

Men

≥94 cm

≥102 cm

Women

≥88 cm

≥88 cm

Gender-specific waist circumferences are presented that denote ‘increased risk’ (level 1) and ‘substantially increased risk’ (level 2) of metabolic complications associated with obesity in Caucasians. Level 1 is intended to alert clinicians to potential risk for CHD whereas level 2 should initiate therapeutic action

Source: Peter, 2000

While BMI seems appropriate for differentiating adults, it may not be as useful in children because of their changing body shape as they progress through normal growth. In addition, BMI fails to distinguish between fat and fat-free mass (muscle and bone) and may exaggerate obesity in large muscular children (Eckel and Krauss, 1998). While health consequences of obesity are related to excess fatness, the ideal method of classification should be based on direct measurement of fatness. Although methods such as densitometry can be used in research practice, they are not feasible for clinical settings (Chan, 1994).


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