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1.1 Background of Study. 1

1.2 The concept of risk assessment 3

1.3 Justification for the study. 4

1.4 Objectives of the Study. 5

1.4.1 Specific Objectives. 5



2.1 Cardiovascular disease occurrence and risk factors. 6

2.2 Plasma lipids and coronary heart disease risk. 6

2.3 Diabetes and coronary heart disease risk. 13

2.4 Hypertension and cardiovascular disease risk. 18

2.5 Homocysteine and coronary heart disease risk. 24

2.5.1 Homocysteine and lifestyle. 30

2.6 C-reactive protein and cardiovascular disease risk. 31

2.7 Lifestyle (physical activity and exercise, smoking, alcohol, diet) and cardiovascular disease risk  39

2.7.1 Physical activity and exercise and cardiovascular disease risk. 39

2.7.2 Smoking and cardiovascular disease risk. 41

2.7.3 Alcohol consumption and cardiovascular disease risk. 45

2.7.4 Diet and cardiovascular disease risk. 49



3.1 Reagents/Chemicals. 55

3.2 Site of the study. 55

3.3 The subjects for the study. 55

3.4 The sample size. 55

3.5 Ethical consideration. 55

3.6 Exclusion and inclusion criteria: 55

3.7        Sample Collection. 56

3.8        Anthropometric Measurements. 56

3.9        Blood pressure measurements. 56

3.10     Determination of Fasting plasma glucose of Subjects. 56

3.11     Determination of Lipid Profile of Subjects. 56

3.11.1      Cholesterol Assay. 57

3.11.2      Triglyceride Assay. 57

3.11.3      High Density Lipoprotein Cholesterol (HDL-C) Assay. 58

3.11.4      Low Density Lipoprotein Cholesterol (LDL-C) 58

3.12     Determination of Antioxidant Status of Subjects. 58



4.1Body Weight and Cardiovascular Risk Factors among Working Class Women. 60

4.2Blood Pressure trends and Cardiovascular Risk Factors of Working Class Women. 60

4.3Obesity, Hypertension and Cardiovascular Risk Factors of Working Class Women. 63

4.4.Physical activity and Cardiovascular Risk Assessment in Working Class Women. 63

4.5 Correlates of Some Anthropometric and Biochemical Cardiovascular Risk Factors. 66

4.6   Prevalence of Cardiovascular Risk Factors among Working Class Women. 66



5.1 Discussion. 72

5.2 Conclusion. 78

5.3 Recommendation. 79



Table 4.1:        Effects of BMI Variability on Cardiovascular Risk Factors in Working

Class Women………………………………………………………………….61

Table 4.2:        Effects of Blood Pressure Variability on Cardiovascular Risk Factors in

Working Class Women……………………………………………………….62

Table 4.3:        Cardiovascular Risk Factors in Obese and Hypertensive Working Class Women ……………………………………………………………………………………….64

Table 4.4:        Effects of Physical Activity on Cardiovascular Risk Factors in Working

Class Women…………………………………………………………….……65

Table 4.5:        Correlation Matrix of Some Anthropometric and Biochemical

Cardiovascular Risk Factors…………………………………………………………………..67

Table 4.6:        Prevalence of Cardiovascular Risk Factors in Working Class Women………68

Table 4.7:        Prevalence of Cardiovascular Risk Factors in Active and Less active

Working Class Women…………………………………………………………69












Figure 2.1: Progression of atherosclerosis. 8

Figure 2.2: Potential mechanisms linking obesity to hypertension. 24

Figure 2.3: Structure of homocysteine. 25

Figure 2.4: Methionine-Homocysteine metabolism and related pathways. 26

Figure 2.5: CRP in the pathogenesis of atherosclerosis and atherothrombosis. 33

Figure 4.1: Prevalence of cardiovascular risk factors in working class women……..………………………….70

Figure 4.2: Prevalence of cardiovascular risk factors in active and less active working class women.71




ABP                            Ambulatory blood pressure

ACS                            Acute coronary syndrome

AI                                Atherogenic Index (LDL–C/HDL–C ratio)

AMI                            Acute myocardial infarction

AP                               Angina pectoris

AT-1                            Angiotensin type-1 receptor

BMI                            Body Mass Index (kg/m2)

BNP                            b-type natriuretic peptide

BP                               Blood pressure

CBS                            Cystathionine-beta-synthase

CETP                          Cholesteryl ester transfer protein

COPD                                     Chronic obstructive pulmonary disease

CRI                             Coronary Risk Index (TC/HDL–C ratio)

CRP                            C-reactive protein

CV                              Cardiovascular

CVD                           Cardiovascular Disease

CVRF                         Cardiovascular Risk Factor

DBP                            Diastolic blood pressure

DM                              Diabetes Mellitus

DPPH                          2,2-Diphenyl-1-picrylhydrazyl

ECM                           Extracellular matrix

eNOS                          Endothelial nitric oxide synthase

FPG                             Fasting plasma glucose

GFR                            Glomerular filtration rate

HC                               Hip Circumference (Inches)

HDL-C                        High density lipoprotein cholesterol

HT                               Height (m)

IHD                             Intermittent heart disease

IL-6                             Interleukin-6

LDL-C                        Low density lipoprotein cholesterol

LVH                            Left ventricular hypertrophy

LVM                           Left ventricular mass

MI                               Myocardial infarction

MS                              Methionine synthase

NCD’s                         Non-communicable diseases

NCEP                          National Cholesterol Education Program

NF-κB                       Nuclear factor kappa B

NO                              Nitric oxide

NOS                            Nitric oxide synthase

OxLDL                       Oxidized LDL

PUFAs                        Polyunsaturated fatty acids

RAAS                          Renin-angiotensin-aldosterone system

ROS                            Reactive oxygen species

SAH                            S-adenosyl homocysteine

SAM                           S-adenosyl methionine

SBP                             Systolic blood pressure

TC                               Total cholesterol

TF                                Tissue factor

TG                               Triglyceride

tHcy                            Total homocysteine

TNF-α                       Tumor necrosis factor- α

VSMCs                       Vascular smooth muscle cells

WC                              Waist Circumference (Inches)

WCHT                        White-coat hypertension

WHR                            Waist to Hip Ratio

WT                              Weight (kg)






Cardiovascular disease is one of the leading cause of mortality and morbidity globally, and it is caused by interaction of several risk factors collectively described as cardio-metabolic syndrome. Consequently,cardio-metabolic syndrome have transformed from a mere physiological curiosity to a major focus of research, clinical and public health interests. The purpose of this study therefore, was to evaluate the relationship between some anthropometric and metabolic variables that reflect the existence of cardio-metabolic syndrome among working class women. Ninety (90) working class women were recruited for this cross sectional study. Descriptive statistics and Pearson moment correlation analysis were used to determine the relationship between anthropometric data and metabolic variables. Anthropometric indices, blood pressure, fasting glucose, lipid profile and total antioxidant status were among the variables assessed using standard procedures. Weight significantly correlated with height (r = .452), WC (r = .865), HC (r = .855) and BMI (r = .933). WC significantly correlated positively with HC (r = .831), BM I (r = .876) and WHR (r = .641).  HC also significantly correlated positively with BMI (r = .859), AI (r = .277) and CRI (r = .289). WHR significantly correlated positively with HDL-C (r = .260).  TC significantly correlated positively with LDL-C (r = .931), AI (r = .494) and CRI (r = .459).  LDL-C significantly correlated positively with AI (r= .689) and CRI (r = .644). AI significantly correlated positively with CRI (r = .993). Significant negative correlation were seen between FPG and DPPH (r = -.345), HDL-C and LDL-C (r = -.281), HDL-C and AI (r= -.688), AI and CRI (r = -.696).  The prevalence of cardiovascular risk factors (CVRFs) wasgenerally high in the study population.Furthermore, the less active subjects showed a higher prevalence of CVRFs than the active subjects,hence it is necessary that the subjects adopt and sustain healthy life stylesto improve their cardiovascular wellbeing.




1.1 Background of Study

Today, the study about lipoproteins is very important because the mortality and morbidity due to metabolism disorders has increased. Research interest in lipids and lipoprotein metabolism has increased due to the establishment of the roles played by lipids, lipoproteins and Apo lipoproteins in the development of cardiovascular disease (CVD) (Durstine et al., 2001; Booth et al., 2002; Asikainen et al., 2004; Coelho et al., 2005; Brown et al., 2007). Suboptimal levels of lipids and lipoproteins represent a major risk factor for cardiovascular disease (CVD), the number one cause of mortality in the United States (American College of Sports Medicine, 1998).

Coronary heart disease (CHD) is the most important cause of mortality in developed countries. All heart attacks, with rare exceptions, are caused by atherosclerosis, or a narrowing and “hardening” of the coronary arteries resulting from fatty deposits called plaque. This process, by which the wall of the artery is infiltrated by deposits of cholesterol and calcium, narrows the lumen (the internal orifice) of the artery. When the degree of narrowing reaches a critical level, blood flow to the portion of the heart supplied by that artery is stopped and this causes injury to the heart muscle, thus, a heart- attack occurs. If the reduction in blood flow is not total and is only temporary, relative to muscle needs, permanent damage does not result but the individual may experience angina pectoris – chest pain as a result of too little blood and oxygen to a portion of the heart in response to its needs (a process called ischemia) (Münzel et al., 2010).

According to Bimenya et al. (2006), public servants, who were mainly University graduates, were found to have abnormally high levels of plasma lipids. Plasma lipid and lipoprotein levels have been shown to be influenced by age, sex, socioeconomic status, genetics, race, diet, cigarette smoking coffee and alcohol intake, and medication as well as habitual and leisure time physical  activity. Increased physical activity has been reported to produce favorable changes in the lipid and lipoprotein profiles (Kraus et al., 2002; Nieman et al., 2002). Apo lipoprotein B is combined with heparin and glucose amino glycan; this chemical interaction leads to atherosclerosis (LeMura et al., 2000; Meilahn et al., 1988; Lakshman et al., 1996).

An increasing number of studies focus on the role of reactive oxygen species (ROS) in the pathogenesis of premature ageing as well as of numerous civilization diseases, such as cardiovascular diseases (Karaouzene et al., 2011). It has been suggested that higher antioxidant potential can protect the organism against undesirable ROS activity and thus prevent disease incidence (Briasoulis et al., 2009).

Relationship of CHD to antioxidant defenses may be modified not only by many demographic, anthropometric, physiological, and biochemical confounders but also by different exogenic substances such as applied medications or cigarette smoking (Hutcheson and Rocic, 2012; Ndrepepa et al., 2013). Total antioxidant capacity (TAC) assessment is an established methodology to measure different elements of antioxidant defense system together (Cervellati et al., 2014).

Coronary heart disease can be classified as “typical” CVD such as fatal myocardial infarction(MI) and sudden death, and “atypical” CVD, such as fatal heart failure and chronic arrhythmias. When further explored, the etiologies of these coronary diseases in relation to major cardiovascular risk factors are different. Death rates from typical and atypical CVD are inversely related, with mean age at death for atypical being significantly higher than typical.

The relationship of risk factors with typical CVD is direct and significant for age, systolic blood pressure, serum cholesterol and smoking habits (Menotti et al., 2006). Atherosclerosis, being a chronic process, undergoes a series of changes in the arterial walls before the clinical endpoints set in. Rupture of the plaque is the final event that results in a clinical endpoint, often stroke or MI (Kanjilal et al., 2008). The increasing pressure on health resources has led to risk stratification as a primary prevention effort to accurately determine and intervene early in the natural history of disease by moving closer to the proximal direct causes of disease and improving prediction (Stampfer et al., 2004).

1.2 The concept of risk assessment

Risk factors are traits and life-style habits that increase a person’s chances of having cardiovascular diseases. Some risk factors cannot be changed or modified, while other risk factors are modifiable (Münzel et al., 2010). The most important risk factors for cardiovascular disease are high blood pressure, high blood cholesterol and cigarette smoking. Other factors that may increase the risk for cardiovascular disease are diabetes, obesity, being physically inactive and having an unhealthy reaction to stress. The concept of risk factors has evolved only over the past 45 years or so, and new factors are periodically added to the list as our comprehension of the disease process grows

Although risk-scoring systems that evaluate conventional risk factors greatly improve risk prediction, multiple studies demonstrate that 20% to 25% of all future events occur in individuals with only one of these factors (Ridker et al., 2004). With evolving understanding of the pathophysiology of CVD, it is more than likely that other risk factors may greatly influence an individual’s overall risk burden (Hemann et al., 2007). As a result, a series of biomarkers such as Hcy and CRP reflecting inflammation, hemostasis, thrombosis, and oxidative stress have been evaluated as potential clinical tools in an effort to improve risk prediction (Ridker et al., 2004).

The close association between traditional risk factors, atherosclerotic burden, and risk for clinical CVD has allowed multivariate risk prediction equations to be developed to better estimate CVDrisk. The Framingham Risk Score calculates the absolute risk of CVD events for patients with no known previous history of CVD, stroke, or peripheral vascular disease (Sheridan et al., 2003). What is apparent is that the Framingham equation may not accurately estimate the risk of vascular disease in some ethnic groups (Cappuccio et al., 2002). However, given the lack of prospective data in large ethnically mixed populations including Nigeria, these risk equations are the best available tools to guide the decision making process of prevention in general practice.

1.3 Justification for the study

There is a dramatic increase in incidence of CVD in the developing world as earlier predicted by World Health Organization (Murray and Lopez, 1996). It is increasingly recognized that developing countries are undergoing an epidemiologic transition, accompanied by an increasing burden of CVD linked to urbanization and lifestyle modifications (Dominguez et al., 2006). The health transition is occurring at an increased pace in urban societies widely exposed to lifestyle modernization, sedentary occupation, and to lipid- and sugar-rich foods often poor in fiber and micronutrients.

In Nigeria the extent of most CVD’s and risk factors at population level remains largely unknown. For the past 25 years, high blood pressure has become established in Nigeria. This has been attributed to consumption of sodium salt and alcohol, psychological stress, obesity, physical inactivity and other dietary factors (Trowell, 1980; Lowe, 1993).   Although the exact genetic markers of CVD remain unknown in Nigeria, different environmental mediators contribute to the development of this disease.   It therefore essential to identify the risk factors involved in order to develop preventive strategies.

To understand who is at risk and what risk actually means to an individual, one first needs to understand how diseases of the heart and circulatory system—particularly heart attacks-develop (Münzel et al., 2010).    However, the present state of knowledge on such dependence is still not complete (Münzel et al., 2010): while numerous discrepancies have been observed in studies and no unequivocal answer has been reached on the appropriate cluster of thesefactors for the incidence of metabolic syndrome among Nigerians.    Furthermore, the impact of occupational demand on civil servant in Nigeria has not received much attention. In addition, that the incidence of CVD is related to antioxidant potential is an issue of current debate in literature, and information on Nigerian population   is especially limited. This underscores the following aim and objectives of this study.

1.4 Objectives of the Study  

The overall aim of this study is to assess the cardiovascular and antioxidant status of some working class women in Ambrose Alli University, Ekpoma; with major focus on the effect of the activity patterns.

1.4.1 Specific Objectives

  1. To obtain data on the prevalence of dyslipidemia.


  1. To obtain data on the prevalence of obesity.
  • To obtain data on the prevalence of diabetes.
  1. To obtain data on the prevalence of hypertension.
  2. To obtain data on prevalence of oxidative stress.


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