CHAPTER ONE
INTRODUCTION
Background of the study
Diabetes Mellitus (DM) describes a group of metabolic diseases in which the person has high blood glucose (blood sugar), either because insulin production is inadequate, or because the body’s cells do not respond properly to insulin, or both (Nordqvist, 2013). Globally, the number of patients with diabetes is expected to increase from 285 million to 439 million by 2030 (Shaw, Sicree, & Zimmet, 2009). Currently, DM affects 246 million people worldwide (Levitt, 2008). According to Nwankwo, Nandy and Nwankwo (2010), the major part of this numerical increase will occur in developing countries. There will be an increase from 51-72 million in the developed countries and 84-228 million in the developing countries. Thus by the year 2025, greater than 75% of people with DM with will reside in developing countries.
The disease was previously thought to be rare in Africa, the population regarded as low and middle income; however, as a result of changes in the lifestyle, feeding patterns, and levels of physical activity among other factors, the prevalence has increased in many African countries over the past few decades. For example, the diabetic population in Uganda, estimated at about 98,000 in 2000, increased more than fifteen times (1.5 million) in a decade. Based on the country’s estimated population of 30 million people in 2010 (Nyanzi, Wamala & Atuhaire, 2014), the figure implies that about five percent of the country’s population was diabetic.
 Nwankwo,et al (2010), posited that while it is estimated that 92% of Nigerians live under $2 a day, studies have shown that there has been a progressive increase in the prevalence of diabetes in Nigeria and the burden is expected to increase even further. According to World Health Organization, there are 1.71 million People living with diabetes in Nigeria and this figure is projected to reach 4.84 million by the year 2030 (WHO, 2009). Current prevalence rate estimates of diabetes in Nigeria have been tagged at 2.5% compared to its 2.2% rate in 2003, ( Nwankwo,et al,2010) .
Diabetes is associated with long-term complications that affect almost every part of the body (National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), 2014). The disease often leads to blindness, heart and blood vessel disease, stroke, kidney failure, amputations, and nerve damage. Uncontrolled diabetes can complicate pregnancy, and birth defects are more common in babies born to women with diabetes. According to Nwankwo, et al (2010), diabetes and its complications impose significant economic consequences on individuals, families, health systems and countries.
 The threat is growing. The number of people, families and communities afflicted are increasing. This growing threat is an under-appreciated cause of poverty and hinders the economic development of many countries (WHO, 2009) and the economic burden is heavy. The upward trend in the number of diabetic patients points to the need for improved treatment and care for the disease. The fact that treatment for the disease and its associated complications are highly complex, a considerable patient education and medical monitoring are required. Thus, the patient is required to regulate blood sugars amidst required changes in lifestyle factors and the unpleasant medication that usually accompanies the disease in order to maintain a correct degree of metabolic control. The fact that these changes make the patients vulnerable to stress, their quality of life is highly bound to be affected.
Quality of life is a scientifically proven indicator of the quality of health experienced by a patient (Eckert, 2012). Due to insufficiency of traditional end points (which are mainly focused on the biologic and physiologic outcomes) in capturing the effects of interventions on patients’ health-related quality of life (HRQoL), a growing interest has emerged during the past decades for assessing determinant factors of patients HRQoL, especially in chronic diseases. Six studies, which examined the effect of diabetes on HRQoL, compared HRQoL in people with and without diabetes and reported negative effects of both type 1 and type 2 diabetes on HRQoL (Aliasghar, Baharak, & Mirmalek-Sani, 2013)
According to Nyanzi, et al (2014) the predictors of quality of life of diabetic patients are identified by Imayama et al (2011)’s study as personal, medical, and lifestyle factors. Particularly, the study noted that old age, higher income, higher score on activity (personality) trait, not using insulin, having fewer comorbidities, lower body mass index (BMI), being a nonsmoker, and a higher physical activity level were significantly associated with better health related quality of life in adults with type 2 diabetes. . The findings of Aliasghar et al (2013) showed that people with diabetes had a lower HRQoL than healthy people. The findings also indicated that better socioeconomic status and better control of cardiovascular risk factors were associated with better HRQoL among patients with diabetes.
In line with these studies, there has been a resurgence of interest in the relation between health and socioeconomic position (SEP). SEP encompasses two important notions: the influence of the structural location of individuals and groups in a society and the cumulative effects of time. It addresses the context in which health-damaging exposures and health-protective resources act at different stages of the life course to influence adult health. Such an approach provides a broad framework in which to think about and understand how both recent and remote socioeconomic factors interact to affect adult health. A substantial body of literature demonstrates that in the general population, material and social deprivation are directly related to disease incidence and prevalence and inversely related to health status. According to Brown, (2014) various studies have addressed the relationship between lower SEP and mortality or the development of chronic conditions such as diabetes mellitus, cardiovascular disease, and cancer. Research on the relationship between SEP and health has often focused on individual characteristics such as income, wealth, education, and occupation. However, SEP encompasses not only current individual socioeconomic status but also social relationships and community-level characteristics (Brown, 2014).
Brown, (2014) further stated that although effective therapies are available for managing diabetes and preventing or treating its complications, these therapies are underutilized, particularly among persons of low socioeconomic status. For someone with diabetes, socioeconomic status such as educational level, income and culture may influence access to and quality of care, social support, and community resources. It may also influence diabetes-related knowledge, communication with providers, ability to adhere to recommended medication, exercise, and dietary regimens, and treatment choices. Socio-economic factors such as income, education and neighborhood culture determine how people are born, live grow and progress in life .They determine how people maintain good health. When an individual is poor and ignorant it creates barrier in accessing health care because the individual cannot afford the cost . Besides an ignorant person would not be aware of the ill health and would not seek for help at the proper time and place when the need arises.
The social status of persons with diabetes and the characteristics of their communities or culture may determine their risk of mortality and diabetes-related complications as well as their quality of life. Lower individual SEP, as measured by individual or household income, education, employment, occupation, or living in an underprivileged area, has been associated with poorer physical or emotional health, all-cause mortality or poor quality of life. In order words, poor socioeconomic factors affect the quality of life of an individual because he may not be able to meet up with required need. At the same time with good socioeconomic status there is the need to use it properly as it may positively or negatively affect the quality of life of an individual.
In the light of the foregoing, the following question was posited: What role does socioeconomic status such as education, occupation; culture and income play in the quality of life of diabetic patients? This study is aimed at assessing how socioeconomic factors are determinant of the quality of life of diabetic patients in Nnamdi Azikiwe University Teaching Hospital.
Statement of the problem
