ABSTRACT

TABLE OF CONTENTS

CHAPTER 1

INTRODUCTION

1.1     Statement of the Problem

1.2     Objectives of the Project

1.2.1  The General Objective of this Study

1.2.2   The Specific Objective of this Study

1.3     Significance of the Study

CHAPTER 2

LITERATURE REVIEW

2.1     Diabetes Mellitus

2.1.1 Type of diabetes

2.1.1.1  Type 1 diabetes

2.1.1.2 Type 2 diabetes

2.1.2 Impaired glucose tolerance (IGT) and impaired fasting glycaemia (IFG)

2.1.3 Gestational diabetes (GDM)

2.2     Complications of Diabetes

2.3     Prevalence of Diabetes and Associated Risk Factors

2.4     Preventing Diabetes in People at High Risk

2.5     Management of Diabetes

2.6     Obesity in Adults

2.6.1 Social determinants of obesity

2.6.2 Physical determinants of obesity

2.7     Prevalence of Obesity and Risk Factors

2.8     Health Belief Model

2.8.1 The major concepts and definitions of the health promotion model

CHAPTER 3

MATERIALS AND METHODS

3.1     Study Design

3.2     Area of Study

3.3     Population of the Study

3.4     Sampling and Sampling Technique

3.4.1 Sample size determination

3.4.2 Sampling procedure

3.5     Preliminary Activities

3.5.1 Preliminary visits

3.5.2  Training of research assistants

3.5.3  Informed Consent

3.6     Data Collection

3.6.1  Questionnaire Design

3.6.2  Questionnaire administration 

3.6.3 Anthropometric measurement

3.6.3.1 Weight Measurement

3.6.3.2 Height measurement

3.6.3.3 Hip circumference measurement

3.6.3.4 Waist circumference measurement

3.6.4 Blood glucose assessment

3.7     Data Analysis

3.7.1 Body Mass Index (BMI)

3.7.2 Diagnosis of Diabetes Mellitus

3.7.3 Waist hip ratio (WHR)

3.8     Statistical Analysis

CHAPTER 4

RESULT AND DISCUSSION

4.1     Socio-economic and Demographic Characteristics of the Adults studied.

4.2     Background Information of the Adults Studied on Obesity and diabetes mellitus.

4.3     Health belief determinants of obesity and Diabetes Mellitus

4.4     Anthropometric and random blood glucose status of the adults

4.5     Relationship between health belief determinants, body mass index and waist to hip ratio of the adults.

4.6     Relationship between health belief determinants and random blood sugar of the adults.

4.7     Comparison of mean response between the health belief determinants of obesity and diabetes mellitus.

4.8     Relationship between health belief determinants of the adults on obesity and diabetes mellitus

4.9     Relationship between socio demographic characteristics of the adults and health belief determinants of obesity.

4.10   Relationship between socio demographic characteristics of the adults and health belief determinants of diabetes mellitus.

CHAPTER 5

CONCLUSION AND RECOMMENDATIONS

5.1     Conclusion

5.2.    Recommendation           

References  

                                                                     CHAPTER 1

                                                               INTRODUCTION

The Health Belief Model is a theoretical model that can be used to guide health promotion and disease prevention programs. It is used to explain and predict individual changes in health behaviors. It is one of the most widely used models for understanding health behaviors (Scarinci et al., 2012). Key elements of the Health Belief Model focus on individual beliefs about health conditions, which predict individual health-related behaviors. The model defines the key factors that influence health behaviors as an individual's perceived threat to sickness or disease (perceived susceptibility), belief of consequence (perceived severity), potential positive benefits of action (perceived benefits), perceived barriers to action, exposure to factors that prompt action (cues to action), and confidence in ability to succeed (self-efficacy), (Li et al., 2019).

Originally formulated to model the adoption of preventive health behaviors in the United States, the HBM has been successfully adapted to fit diverse cultural and topical contexts (e.g., Griffin, 2012; Scarinci et al., 2012). Widely used in other fields, the HBM would seem to be ideal for communication research. Surprisingly, the HBM is utilized less frequently by communication scholars. Communication researchers are primarily interested in explicating communication processes, an objective that favors explanatory frameworks (Slater and Gleason, 2012). As an explanatory framework, the HBM has significant limitations. Notably, researchers have argued that the HBM fails to specify variable ordering (Champion and Skinner, 2008). This limitation is significant for researchers interested in utilizing the HBM to understand communication processes, as numerous process-oriented questions are raised by the model that currently have no answer. For example, it is possible that all six variables serve as equivalent mediators (Champion et al., 2008), that some variables form sequential or serial chains (Janz and Becker, 1984), or that variables are hierarchically situated so that some moderate the mediational influence of others (Champion and Skinner, 2008). Unfortunately, these different models are rarely examined or compared in the literature.

Overweight and obesity are defined as abnormal or excessive fat accumulation that presents a risk to health. A body mass index (BMI) over 25 is considered overweight, and over 30 is obese. The issue has grown to epidemic proportions, with over 4 million people dying each year as a result of being overweight or obese in 2017 according to the global burden of disease (WHO, 2020). Tappy and Le (2010) opined that Obesity is caused by a continuing imbalance between energy intake and disbursement. World Health Organization (WHO) (2005) stated that Obesity is evolving as a major nutritional problem in developing countries, resulting in increased burden of chronic disease. The global prevalence of overweight including obesity in children aged 5– m 17 years is estimated by the WHO and International Obesity Task Force to be approximately 10% (WHO, 2005).

Swinburn et al., (2004) reported that the prevalence of obesity is increasing throughout the world’s population. They further stated that the distribution varies greatly between and within countries. WHO (2000) reported that in the US, over the past 30 years, the prevalence of obesity rose from about 12–20% of the population from 1978 to 1990. Furthermore, according to the organization the UK has experienced an increase in the prevalence of obesity from 7% in 1980 to 16% in 1995 and other countries, such as The Netherlands, have experienced much smaller increases from a low baseline of about 5% in the 1980s to about 8% in 1997. Bell et al., (2001) in their study stated that, in Asia, the prevalence of obesity has rapidly increased. In the last 8 years the proportion of Chinese men with a body mass index (BMI) .25 kg/m² has tripled from 4 to 15% of the population and the proportion in women has doubled from 10 to 20% (Bell, et al., 2001a). Pacific populations have some of the world’s highest prevalence rates of obesity. Bell et al. (2001b) pointed out that the proportion of men and women with a BMI .30 kg/m2 in Nauru was 77% in 1994 and for Pacific people living in New Zealand in the early 1990s the prevalence rates were about 65–70% (Bell, et al., 2001b). Obesity in adulthood is suggested by Goran (2011) to be a result of obesity during childhood and adolescence. Lobstein et al., (2004) reported that the rapid increase over the past three decades in the prevalence of childhood obesity in developed countries across the world (Lobstein, et al., 2004), Nicklas et al., (2001) and Nicklas et al., (2003) in relation to the above reported that it has led to increased concern about the diets of adolescents and children. Although increased levels of sedentary behaviour are likely to be associated with this increase in obesity, changes in food consumption patterns are also likely to play an important role. Obesity is increasing as one of the risk factors of CVD among high classes in developing countries.

Diabetes is a common metabolic disorder and the fourth leading cause of death in western countries. Over 300 million people suffer from diabetes around the world. It is one of the major problems for human health which is related to urbanization and lifestyle changes such as inactivity and poor nutrition (Azizi et al., 2010). Changes in lifestyle, industrialization, demographic and nutrition transition, obesity, inactivity and aging are considered among factors which are possible risk of diabetes in modern population (Landim et al., 2011). It is expected the numbers of patients increase over 500 million people during next 30 years (Javadi et al., 2010).

Lack of self-care was identified as the most important reason of death in diabetics Baquedano et al., 2010. Lack of diabetes self-care behaviors can lead to increased complications of the disease (Jordan and Jordan, 2010). Self-care measures such as following a healthy diet, regular use of medications, regular exercise, and monitoring the blood glucose are proposed by International Diabetes Federation for optimal control of blood glucose (Peyrot and Rubin, 2007).

1.1                   STATEMENT OF THE PROBLEM

Obesity and diabetes mellitus is a non-communicable medical disorder that affects Nigerians greatly. It is evident from the literature that the incidence of diabetes mellitus is increasing and that although there is evidence that the complications of diabetes can be prevented, there are still patients who lack the required knowledge and skills to manage and control their condition. It is generally accepted that diabetics must take responsibility for their own care and treatment. Patients therefore have to acquire the relevant knowledge, skills and attitudes for successful diabetes management. This implies adequate diabetes education of patients as well as family members as a support group. Several studies have revealed that the Igbos still hold on to their traditions, including the belief that traditional medicines can cure all kinds of illnesses. There are no data on the incidence and prevalence of diabetes among the Igbos except the national prevalence rate of 3.9 %, as estimated by the International Diabetes Federation (2009) for Nigeria.

Four meta-analyses have been conducted to assess the viability of the HBM and its constructs in predicting behavior, but their findings have been inconsistent. The first analysis was conducted between 1974 and 1984 (Janz and Becker, 1984). However, the failure of health believe determinant to diagnose obesity and diabetes morbidities by clinicians leads to missed opportunities to counsel patients on lifestyle modification and screen them for obesity and diabetes mellitus related morbidities.

1.2                   OBJECTIVES OF THE PROJECT

1.2.1    The general objective of this study:

was to assess the health belief determinants of obesity and diabetes mellitus among adults in Obingwa LGA and Umuahia South LGA areas of Abia State.

1.2.3      The Specific objective of this study were to:

i.      Assess the socio-demographic/economic characteristics of adults in the study areas;

ii.     Determine the health belief determinants of obesity and diabetes mellitus among adults in the study areas using the health belief model;

iii.   Assess the blood glucose status of adults in the study areas;

iv.   Determine the anthropometric status of adults in the study areas using Body Mass Index and Waist - Hip ratio Indicators; and

v.     Identify the relationship between the socio-demographic/economic characteristics, blood glucose and anthropometric status of the adults and their health belief determinants.

1.3                   SIGNIFICANCE OF THE STUDY

The outcome of this study as well as the implementation, will be of immense benefit for the application in Nigeria, since it will help to independently monitor patients diagnosed with obesity and diabetes mellitus.

However, the implementation of this health belief model has many advantages in terms of:

      i.         Effectively implementing health education which mainly focuses on diseases prevention.

     ii.         In this study, health belief model was used for determining the relationship between health belief and behavior in diabetes and obesity patients.

   iii.         Previous studies had shown that the successful application of HBM in explanation and prediction of preventive health behavior and also health related non communicable diseases.

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