Health Related Quality Of Life Among Patients Living With Diabetes Mellitus

Health Related Quality Of Life Among Patients Living With Diabetes Mellitus

Abstract

This study was a hospital based cross- sectional study done to assess the health related Quality of life of type 2 diabetes mellitus patients attending the Braithwaite Memorial Specialist Hospital (BMSH), Port Harcourt. A systematic random sampling was used and a total of 267 patients were recruited after a written and informed consent was obtained from the patients.

The study participants were given appointment for laboratory investigation (fasting blood glucose). The samples taken were properly labelled and taken to the chemical pathology laboratory for analysis.

The result of this study showed that close to half of the patients were of the age group 55- 64years, Forty three percent of the patients were of the social class 4.
Majority of the patients (71.9%), were married. A little above half (54.3%) were of the Ijaw ethnic group. Close to

half (43.7%) earned a salary range of N 18000- N 100000. A little above half as assessed using BMI were obese. A little above half (58.8%) had poor blood glucose control level. The relationship between age, occupation, marital status, education and salary range and Quality of life were statistically significant with values of 0.023, 0.005, 0.001, 0.001, 0.001 respectively.

The level of blood glucose control did not show any definite trend. More of the older age group scored their Quality of life as poor in the constructs of overall Quality of life (61.8%), HRQuality of life (48.7%), and physical domain (60.5%). The relationship between age and Quality of life were statistically significant in the constructs of overall Quality of life, HRQuality of life, health satisfaction, psychological domain, and social relationship domain with p-values of 0.001, 0.007, 0.001, 0.001, and 0.010 respectively. More of the male gender rated their Quality of life as poor, in the constructs of overall Quality of life, health satisfaction, physical, social relationship, and environmental domains with scores of 44.7%, 52.6%, 31.1%, 40.3%, and 42.1% respectively. The relationship between gender and Quality of life were statistically significant for the constructs of overall Quality of life, HRQuality of life, health satisfaction, psychological, and environmental domains, with p-values of 0.020, 0.001, and 0.001 respectively. More of those in social class 4 rated their Quality of life as poor and the relationship between social class and Quality of life was statistically significant in the constructs of overall Quality of life, health satisfaction, physical, psychological and social relationship domains with p- values of 0.001, 0.001, 0.010, 0.016, and 0.050 respectively.
In all the Quality of life constructs, those separated rated their Quality of life as poor. The relationship between marital status and Quality of life was statistically significant in the constructs of overall Quality of life, HRQuality of life, health satisfaction and social relationship domain with p- values of 0.001, 0.001, 0.001, 0.001, and 0.035 respectively.

Those earning below N 4,999 rated their Quality of life poor only in the HRQuality of life construct. The relationship between income and Quality of life was statistically significant in the constructs of HRQuality of life, health satisfaction, social relationship domain, and overall Quality of life with p- values of 0.001 for each of the constructs.
More of those with poor glycaemic control rated their Quality of life as poor. The relationship between level of blood glucose control and Quality of life rating was statistically significant in the constructs of overall Quality of life, HRQuality of life, health satisfaction and social relationship domains.

More of those with illness duration > 15 years rated their Quality of life as poor, and the relationship between illness duration and overall Quality of life, social relationship, and environmental domains were statistically significant with p- values of 0.022, 0.034, and 0.001 respectively.

Type 2 diabetes mellitus has a negative impact on the Quality of life of the patient. The poor, less educated, separated, obese, and those with poor glucose control assess their Quality of life as being more negatively affected than those who fare better in all these variables.

Chapter One

Introduction

1.1 Background of the Study

Chronic non-communicable diseases are a major contributor to the burden of disease in developed countries, and are increasing rapidly in developing countries. This is mainly due to demographic transition and changing life style of populations, associated with urbanization.1

Chronic non-communicable disease are largely due to preventable and modifiable risk factors such as; physical inactivity, unhealthy diet and inappropriate use of alcohol. These factors result in various long term disease processes, culminating in high mortality rate. The high mortality rate are attributable to stroke, obstructive lung disease, diabetes and many other chronic no communicable diseases2. There is also a surge in sedentary life style and reduced energy expenditure with utilization of labour saving devices like motorized transportation2. The most significant non-communicable diseases are cardiovascular disease (CVD), chronic respiratory diseases, cancer and diabetes mellitus.

The term ‘diabetes mellitus’ describes a metabolic disorder of multiple etiologies, characterized by chronic hyperglycemia.3 This is associated with disturbances of carbohydrate, fat and protein metabolism, resulting from defective insulin secretion, action or both.5 The effects of the disease include; long-term damage, dysfunction and failure of various organs.5 Type 2 diabetes mellitus is the most common form of diabetes and is characterized by disorder of insulin action and insulin secretion, either of which may be the predominant feature. 5 Both are usually present at the time this form of diabetes is clinically manifest.5, 6 People are typically diagnosed with type 2 diabetes after the age of 40 years;6 however, there is an increasing prevalence of type 2 diabetes mellitus in children worldwide.1 Diagnosis of diabetes mellitus is made using the World Health Organization (WHO) guidelines which stipulates a fasting plasma glucose level of ≥ 7.0 mmol/1 (126mg/d1) or 2 hour post prandial plasma glucose level of ≥ 11.1mmo1/1 (200mg/d1).

In 2007, the International Diabetes Federation estimated that approximately 246 million people worldwide had diabetes mellitus. The number is projected to rise to 266 million in 2030.6,7 According to the International Diabetes Federation, diabetes is the fourth leading cause of global death in the world by the disease. 6,7 Hospital based cross-sectional studies done at Jos University Teaching Hospital, Plateau State of Nigeria, Port Harcourt University Teaching Hospital South-South Nigeria and Lagos University Teaching Hospital, South-West Nigeria showed prevalences of 24.7%, 38.1% and 11.1% respectively. It is also noted that developing countries are least prepared for this emerging world epidemic.

Diabetes is expected to reach epidemic proportions in many regions throughout the world as life spans extend and societies adopt increasingly urban and modern lifestyles.

Patients’ perceived overall well being (quality of life) is hinged on the patients’ perceived functional capacity and the level of the patients’ psychological and social health. How satisfied the patient is with the level of care is now viewed as a major clinical index of success in medical interventions. The World Health Organization Quality of Life group defines quality of life as an individual’s perception of their position in life in the context of the culture and value system in which they live and in relation to their goals, expectations, standards and concerns. Hence, the concept is broad, encompassing the patient’s physical health, psychological state, level of independence, social relationship and relationship with the salient features in the environment.

The determinants of quality of life in diabetes mellitus are broadly classified into two sub headings. These are the socio-demographic determinants such as age, gender, marital status, income, level of education and occupation.13The other; disease specific determinants are level of blood glucose control, duration of illness, presence and type of complication.13 However, the presence and type of complication is the most important disease specific determinant of quality of life.13 Health related quality of life in diabetes mellitus has been measured with instruments including WHOQUALITY OF LIFEBref.

1.2 Statement of the Problem

Non-communicable diseases are the leading cause of disability and death world-wide and type 2 diabetes mellitus is among the four most prominent of these chronic non -communicable diseases.1 Diabetes mellitus particularly type 2, also serves as a trigger factor for cardiovascular disease which is the number one killer disease among non-communicable diseases.1 It has debilitating and serious end organ damages of important organs of the body including the renal system, central nervous system and the eye.2,9 Illiteracy is prevalent in developing countries and patients’ knowledge of diabetes mellitus and the associated risk factors may be inadequate. This ignorance fuels the devastating effects of diabetes mellitus.5,6

There is a global epidemic in diabetes mellitus and the developing world will be hit the hardest by the escalating diabetic epidemic.17 Diabetes mellitus management has regimens that interfere with the desired life style of the patient.17

Current recommendations for ideal risk factors targets and specific therapy to improve glycaemic control, do generate significant benefits. Nevertheless, this tends to focus on the disease rather than the patient.18,19

Consequently, diabetic management should go beyond achieving improved clinical characteristics to include how satisfied the patient is with the care; that is the social and psychological status of the patient in relation to care.13,14 This has an important bearing on whether the patient will continue to adhere to the treatment including modifying his lifestyle. Hence, the impact of diabetes mellitus on the patient, including its complications and treatment outcome that is his quality of life, affects adherence to drug therapy and life style modification.19 This is a very important aspect of diabetes mellitus care particularly by primary care physicians, who see more than 70% of type 2 diabetes mellitus patients in most settings worldwide.13,14 This work was to articulate this fact.

1.3 Aim of the Study

To assess the health related quality of life of type 2 diabetes mellitus patients attending Braithwaite Memorial Specialist Hospital, Port Harcourt.

1.4 Objectives of the Study

1. To determine the socio-demographic characteristics of type 2 diabetic patients in Braithwaite Memorial Specialist Hospital, Port Harcourt.
2. To assess anthropometric indices and fasting blood glucose of type 2 diabetic patients in Braithwaite Memorial Specialist Hospital.
3. To determine the health related quality of life of type 2 diabetic patients attending Braithwaite Memorial Specialist Hospital using the World Health Organization Quality of life Bref on mental health of diabetes mellitus patients.

1.5 Significance of the Study in Family Medicine

There is a global epidemic in type 2 diabetes mellitus.2 People with diabetes mellitus require not just medical treatment from their healthcare providers but also need support in mustering and sustaining complex behaviours. These behaviors include; adhering to drug therapy and lifestyle modifications that make them live as healthy as possible. This study was aimed at highlighting the independent association between type 2 diabetes mellitus and Quality of life and could help articulate how to strengthen provider- patient interaction in diabetes mellitus management.

The result of this work was expected to stress the need to add, discuss and monitor Quality of life in routine practice by family physicians. This could help improve patient’s perceived ability to control the progression of their disease, hence leading to improved psychosocial wellbeing and satisfaction with care.

1.6 Scope / Delimitation of the Study

The study is delimited topatients in Braithwaite Memorial Specialist Hospital (BMSH), Port Harcourt.

1.7 Organization of the Study

This study is organized into five chapters. Chapter one included the background of the study, research problem, research objectives and questions as well as limitation of the study. Chapter two contains the literature review. Chapter three includes the methodology and study area. Chapter Four contains the results and discussion of key findings of the study. Chapter Five finally looks at the summary, conclusions, and recommendations based on the findings.

1.8 Definition of Terms

Diabetes Mellitus:

Diabetes mellitus is a disorder in which the body does not produce enough or respond normally to insulin, causing blood sugar (glucose) levels to be abnormally high. Urination and thirst are increased, and people may lose weight even if they are not trying to.

Quality of Life:

The degree to which an individual is healthy, comfortable, and able to participate in or enjoy life events.

1.9 Limitations of the Study

The design of this study was cross-sectional, hence conclusions on cause and effect could not be drawn. The study was a hospital–based study, in an urban centre, and a public institution. Hence, the result could not be generalized for patients in private medical institutions and those for a community-based study in the rural areas.

The researchers relied on the respondents giving accurate answers to questions posed in the questionnaire. Also, patients with major life events just before the study could be affected in their assessment of their quality of life.

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Chapter Five

Discussion, Conclusion and Recommendation

This study was done to assess the socio-demographic, clinical and anthropometric characteristics of type 2 diabetes mellitus patients attending the general outpatient clinic of the Department of Family Medicine BMSH Port –Harcourt. It was also done to determine the relationship between these characteristics and the Quality of life of the patients using the WHO Bref on mental health.

5.1 Socio-Demographic Characteristics

5.1.1 Age

Close to half of the patients 43.0% had their ages between 55-64years age range. The reason for this is that for more than three decades prior to this study, the Rivers State Government had been running a free medical service for the elderly. This free medical service (s) is anchored in BMSH, which is the study centre for this work.

In this work also, 28.4% of the patients were over 65 years of age. In a work done in Singapore 37% of the patients had their ages over 65years. The researchers did not give the reason for their finding.164 It is also noted that the patients in this age group are still in their productive age. The disease was likely to affect their productive capacity and hence this will in turn affect their ability to cater for their families. The relationship between age and gender was statistically significant with p-value of 0.023.

5.1.2 Gender

The result of the study showed that there were more females with diabetes mellitus 55.4% compared to the males 44.6% with a male to female ratio of 1:1.2.The female preponderance in this study could be explained by the health seeking behaviour of the female gender compared to the male gender.

In a work in Atlanta Georgia, USA, the result showed a female preponderance of 65% compared to male 45% and a male to female ratio of 1:1.4.97

In the work done in Calabar, South-South Nigeria, 57.2% of the patients were females and 42.8% were males.3 In a multinational study involving several countries including UK, USA, and Sweden that enrolled 1922 respondents, the male respondents with diabetes mellitus were 46.9% while females were 57.1%118 Researchers have also suggested that the reason for high female preponderance could be due to their being more obese.84,122 Exceptionally, in a cross sectional study in Singapore, they had a male preponderance of 58%.11

Even in children with type 2 diabetes mellitus, a preponderance of female respondents was found in Aurora United States with a ratio, males to females, 1:1.7 respectively.165 The researchers however, noted that the ratios were based on studies. They opined that the result of that work could
be said to have a weak validity.166

Furthermore, they noted that the high females ratio might be due to high undiagnosed cases among the boys, due to their low frequency of medical visit compared to their female counterparts.166

5.1.3 Education

The patients in this study were mostly literate, 78.7% had one type of education or the other. The result also showed that close to half of the patients had secondary education 43.4%. The patients were mostly literate because for up to 4 decades prior to the study, the Rivers State Government had ran a free education programme for both indigenes and non-indigenes residing in the state. At the moment, every child who resides in the State is entitled to free education up to secondary school level. These include free text books and lunch for those in the Government primary schools.

Besides, various Oil Companies in the State such as Shell, EIfetc and the Niger Delta Development Commission also have one type of Scholarship or the other for residents of the State. In the work done in Saudi Arabia 51.5% of the study population were literate.141.However in another work done in Riyadh Province of Saudi Arabia, 88.6% of the patients were literate.120 Being educated is important as it enhances the ability to understand, appreciate and utilize diabetic education. This in turn is important in enhancing self efficacy and coping skill of the diabetic patients.

5.1.4 Ethnicity

The result also showed that the Ijaw ethnic group was in the majority 54.3%. The reason for this could be because the Ijaw ethnic group includes other sub ethnic groupings. Apart from this, the Ijaws abuse alcohol, which is a risk factor in developing diabetes mellitus (This was not assessed by the work). Their women also observe the fattening room ceremony, this predisposes to obesity, while obesity is a risk factor in developing diabetes mellitus.84
A cross sectional study that enrolled 701 adult patients in Chicago, USA also witnessed ethnic variation in the respondents. In that study, 38.0% of the respondents with diabetes mellitus were African-American, 31.0% were white while 24.0% were of the Latino group.167 However, they noted that the preferences of this particular patient population may not be representative of a general population 167 with type 2 diabetes mellitus.

Even in children, it has been noted that type 2 diabetes mellitus has an ethnic predisposition. Children from the minority group were affected more than the white children, with the Pina Indian children having the highest reported rates. However the rates were not quoted. The same study also noted that type 2 diabetes mellitus was more common in African-American children when compared with the Caucasian children.38

It was noted that this ethnic variation was not only due to their genetic predisposition, but also due to their adopted life style.38 Ethnic consideration is important because in a culturally diverse community like the study population, the development of diabetic education programme must overcome barriers of the sub-culture for it to be clinically relevant. It has to target the predisposing factors in the life style and culture of the particular ethnic group.

5.1.5 Marital Status

In this study majority of the patients were married 71.9%, as has already been noted the patients were mostly above 35years. At this age most people would have married.

The percentage of those who were married in this study was similar to the work done in Riyadh province in Saudi Arabia, where 81.3% of the patients in the study were married. Another study done in Turkey had the percentage of those married as 87.76%.125 Marital status in diabetes mellitus is important because the family could assist the patients in managing the disease. This support could be morally or financially.

5.1.6 Salary

Close to half of the patients earned a salary range of between N18, 000 – N100,000 ($112.5-$625) Rivers State Government pays her public servants more than most states in the Federation. The oil companies also pay well.
In a cross sectional population based study in Chicago area USA, 20% had a monthly income of less than $833, while 26% earned between $833 and $2083, 34% had a monthly income between $2083 and $4166.167 Those who earned good income were likely to have lived in plenty without a day of famine, with the attendant probable obesity which is a risk factor for diabetes mellitus.

However, now that they are diabetic, they were likely to be able to fund the disease.

5.1.7 Occupation

Close to half of the patients 46.0% were in Social Class 4 (Unemployed). The reason for this was that the study population were elderly patients, many of whom had retired from the State Civil Service. Also 27.7% were in Social Class 3 (Unskilled and semi-skilled persons). Apart from those whose jobs were pensionable it will be difficult for them to fund their care. This included their prescribed diet, and their transportation to the hospital, they were on free medical services of the State, nevertheless, the hospital pharmacy, did not stock most of their drugs.
Researchers in Saudi Arabia noted in their study that 60.2% of the study population were unemployed.120 They were of the opinion that this fact was a determinant factor in the life style of the diabetic patients because unemployment status was sequential to the amount of income earned by the patients; this also affected the life style adopted by the patients with regards to the illness.
120

5.2 Anthropometric Characteristics

5.2.1 Obesity

Most of the patients in this study were obese using the BMI, 54.6% and the waist circumference
74.9%. More of the females were obese compared to the males when measured with the BMI and WC, 58.8% and 76.5% respectively.The association between obesity and gender was also statistically significant as assessed by the BMI p-value 0.009. It is noted that Rivers State is a relatively wealthy state; being the treasure base of Nigeria with oil industries and related firms hence the average patient in Rivers State has more money for food. The female gender is also more obese as they also practice fattening room rituals which are sedentary life styles with much food. Comparing these results with the works in other centers, a study done in the US had 56.3% of the patients being obese.157 In Manisa Turkey, more than 43.0% of the respondents had a BMI > 30kg/m.2 125 However, the sample size was very small; only 98 patients.125 Obesity has been noted in various studies to be a risk factor in developing diabetes mellitus.168, 169, 170, 171

5.2.2 Blood Glucose Level

The older age groups 55- 64 years and 65 – 74 years had more patients with poor glucose control 47.8%, and 32.3% respectively, while the youngest age group 35 -44 years had the least number of patients with poor blood glucose control 5.1%. The reason for this could be that more elderly patients were likely to have also had longer duration of the illness, with smaller pancreatic cell reserve and hence less insulin production and poorer blood glucose control. In a work in Singapore, 31.3% of the respondents had abnormal glycaemic control.117More of the female gender had their blood glucose poorly controlled 52.9%. The lower social class 4, also had more patients with poor glycaemic control, 48.3%. Obviously they had less money to fund the disease, including the prescribed diabetic diet, their drugs, and logistics including transportation to the hospital. The relationship between blood glucose control and age, occupation, educational level and marital status were statically significant with P-values of 0.003, 0.003, 0.001, and 0.003 respectively. In the work done by Gorien et al in Turkey, men had better glycaemic control when compared with the female gender. Nevertheless they did not find any statistically significant relationship between glucose control and gender 99, The same was found in the present work with P-value of 0.070. In Singapore, males also had better glucose control when compared with the female gender 26. But, the researchers did not find any statistically significant relationship between gender and level of blood glucose control 26. More of the obese patients also had poorly controlled blood glucose level.
Poor glycaemic control also means more complications.

5.3 Socio-Demographic Characteristics in Relation to Quality of Life

5.3.1 Quality of Life Rating in Relation to the Age of the Patients

More patients in the age group 65-74 years scored their Quality of life poor in the constructs of overall Quality of life, HRQuality of life and physical domain with scores of 61.8%, 48.7% and 60.5% respectively. While the patients in the age group 55-64 years rated their Quality of life poor in the constructs of health satisfaction, psychological and environmental domains 46.1%, 50.5%, 56.5%. The older age groups were more likely to be in the empty nest of their family cycle. They were also supposed to be frailer due to increased co-morbidities occasioned by the declining functional capacity of their vital organs. They also were supposed to have longer disease durations with more complications. These were likely to have made more of them rate their Quality of life as poor. In this study, the younger age group 3544 years had more of their Quality of life rated poor in the social relationship domain 56.5%. Social relationship domain assesses Personal relationship, Social support and Social functioning.15,16 The younger age group was supposed to have a more active sexual life, and more important social relationships. More patients in this age group were hence likely to have rated their Quality of life poor in the social relationship domain. The younger age group may also be more worried of how the disease will affect their social relationship, which may in turn negatively affect their productive capacity. That is obviously distressful to them. That may explain why more of the young people scored their Quality of life poor in the social relationship domain.

In a study in Germany it was noted that increase in age resulted in a decreased Quality of life, hence age was found to be a determinant of health related Quality of life.148 The work in Kuwait that looked at young diabetics also found out that increasing age was correlated with poor health related quality of life.150 In a cross-sectional study in Latfi Kirdar Kartal Turkey, those of the age group >40years were reported to have better Quality of life.10 .They did not give reasons for their result. Similarly, in a cross sectional survey in Manisa Turkey that enrolled only 98 patients, the researchers noted that age was significant only in the environmental domain.125

In a population based longitudinal study in Glasgow UK, more of the older patients scored poor in the physical domain while more of the younger age group scored poor in the psychological domain.137 The researchers noted that the older respondents were more frail, while the younger patients had more commitments. Hence with increasing age, the Quality of life of the patient tended to deteriorate.137

The relationship between age and Quality of life was statistically significant for the constructs of overall Quality of life, HRQuality of life, health satisfaction, psychological and social relationship domains with p-values of ≤0.001,
0.007, 0.001, 0.001, and 0.010 respectively.

5.3.2 Quality of Life Rating in Relation to the Gender of the Patients

The result of this study shows that more of the male gender rated their Quality of life poor in overall Quality of life 50.9%, health satisfaction 52.6% physical domain 35.1% social relationship and environmental domain 40.3% and 42.1% respectively. Exceptionally, more of the females scored their Quality of lifepoor in the psychological domain compared to the male gender. To explain this result, the male gender were older than the females. Other published works in this respect showed that females with diabetes mellitus had worse HRQuality of life.172,173

The male gender was also more in the lower social class 1&2 (33.4%), compared to the female 20.9%. Older age group and lower social class are both associated with poor score in Quality of life. This result is different from that obtained in the Al-Khobar area of Saudi Arabia which had more females rating the Quality of life as poor in the overall quality of life.141

In Saudi Arabia, more of the female gender scored poor in the HRQuality of life construct.122 The relationship between gender and Quality of life was statistically significant in the overall Quality of life P-value 0.021, HRQuality of lifePvalue 0.010, health satisfaction p-value 0.005, psychological and environmental domains P-value 0.024 and 0.035 respectively..InKortal Turkey, a statistically significant relationship was found between gender and Quality of life.99 The same result was found in Germany 106. The female gender had more patients scoring their Quality of life poor in the psychological domain, 34.0%. The reason is that the female gender may have more difficulty adjusting to the disease compared to the male122

However, in a longitudinal hospital based study in Turkey that enrolled 344 out-patients, the male patients had better Quality of life scores in all domains compared to the females.122 Also in Manisa Turkey, gender was statistically significant for all the domains except the environmental domain.125 In Turkey, more of the female gender scored their Quality of life as poor.109 The same result was obtained in Kuwait.131 Women have more difficulty adjusting to illness psychologically that could explain why more females rated their Quality of life poor in the psychological domain. The social relationship domain assesses inter-personal relationships including sexual life, hence it is not surprising that more males perceived their Quality of life poor in this domain.

5.3.6 Quality of Life Rating in Relation to the Occupation of the Patients

The result of this study showed that more of the patients in the social class 4 rated their Quality of life poor in the overall Quality of life and the physical domain 50.4% and 43.9% respectively. More of the patients in social class 3 rated their Quality of life poor in the psychological, social relationship, and environmental domains; 45.9%, 41.9% and 60.8% respectively. The relationship between social class and Quality of life were statistically significant for the constructs of overall Quality of life, health satisfaction, physical, psychological and social domains 0.001, 0.001, 0.010, 0.001, 0.005 respectively. The trend therefore was that more of those in the lower social class scored their Quality of life as poor. It is already noted that diabetes mellitus is an age long and expensive disease to treat. People in the lower social class most likely had difficulty funding their treatment (this was not assessed by the work) in an expensive city such as Port Harcourt, South South, Nigeria. They were supposedly those who do miniature job which was also more tasking. These factors were likely to be the reason for their low Quality of life scores. They also were probably more worried of developing complications in the future, and may have wondered how they would cope financially. In the work done in Ilorin South-west Nigeria, the relationship between occupation and Quality of life was statistically significant. The value was not stated. In the same work, more patients with (elementary) occupations rated their Quality of life as poor. 96 Lindsay and co-workers, in a community-based study in the UK also found the same result; those in the lower social class scored their Quality of life as poor.137

5.3.2 Quality of Life Rating in Relation to the Education of the Patients

More of those with primary education rated their Quality of life poor 50.0%, followed by those with no formal education 44.1% in overall QoI. The same trend was observed for the HRQuality of life with 60.8% of those with primary education rating their Quality of life as poor. This was followed by those with no formal education 47.5%.

For the health satisfaction constructs, more of those with no formal education 64.4% rated their Quality of life as poor. For the domains, the trend was not consistent. In the physical domain more of those with secondary education 51.7% rated their Quality of life as poor. In the psychological domain more of those with no formal education 42.4% rated their Quality of life as poor. For the social relationship domain more of those with secondary education rated their Quality of life as poor with a score of 45.7%. For the environmental domain it was more of those with secondary education and tertiary education that rated their Quality of life as poor 50.0% in either case. Education has been noted to be an essential tool in understanding self care and illness management as well as perception of self worth.174 This could explain why more of those with lower education rated their Quality of life as poor.

In a hospital based cross sectional study done in Ilorin, South-west Nigeria, more of those who had lower education scored their quality of life as poor.96 In Saudi Arabia, the result also showed that more of the less educated patients scored their Quality of life poorer.141 Researchers in Turkey also noted that a higher educational level had a positive effect on the Quality of life of patients.122

In the Mexico-Texas border, the researchers noted that the respondents with education status above high school scored better Quality of life scores 61.6% compared to those who had below high school, 38.4%
in the physical domain.101

The relationship between the level of education and the Quality of life ratings was statistically significant for the overall Quality of life and HRQuality of life with P-values of 0.001 in either case.

5.3.3 Quality of Life Rating in Relation to the Marital Status of the Patients

In all the constructs, more of those separated rated their Quality of life as poor 46.0%, 54.7%, 58.7% 54.6%, 42.7%, 42.7%, and 50.7% for the overall Quality of life, HRQuality of life health satisfaction, physical domain, psychological domain, social domain and environmental domain respectively.

To explain this result, it has been noted that support from other family members especially spouse can facilitate recovery from physical illness and enhance the ability to cope with and adopt to consequences of chronic illnesses like diabetes mellitus. Being with one’s family positively impacted the Quality of life of the patient.122, 101

The Quality of life rating in relation to the marital status variable was statistically significant for the constructs of overall Quality of life, HRQuality of life, health satisfaction and social relationship domain with p-values of 0.001, 0.001, 0.001, and 0.035 respectively.

This result agrees with a longitudinal hospital based study done in Turkey although they did not state the percentage of the respondents that had better Quality of life, they also noted that the quality of marriage was not investigated.122 In a hospital based cross sectional study in Turkey, married patients were noted to have higher HRQuality of life score (t =2.15; p<0.05) compared to separated respondents.10

5.3.4 Quality of Life Rating in Relation to the Income of the Patients

More of those earning below N4,999 rated their Quality of life poor in the constructs of HRQuality of life 58%. While more of those earning between N18,000- N100,000 rated their Quality of life poor in the constructs of overall Quality of life and all the domains; physical, psychological, social relationship and environmental domains with scores of 56.8%. 55.4%, 50.0%, 54.1% and 50.0% respectively. The relationship between income and Quality of life were statistically significant in the constructs of overall Quality of life, HRQuality of life, health satisfaction and social relationship domain with P-values of 0.001, 0.023, 0.007,and 0.045 respectively. The result of this present work therefore, showed that those who earned higher income also scored better in their Quality of life rating. The same trend was found in Turkey 99,.Also in Ilorin, South west Nigeria, those who earmed better income also scored higher in Quality of life rating. Just as in this present work, the relationship between income and Quality of life was statistically significant in Turkey 99 and Ilorin Nigeria96. The explanation for the result is that HRQuality of life assesses the health state of the patient. These include; paying for their medication, the side effect of the treatment and the complication of the disease. Those of the lower social class were likely not to be able to fund the disease and hence were likely to score their HRQuality of lifepoor.177,178 More of social class 1 (N18,000-N100,000) scored their Quality of life poor in the physical and psychological domains 55.4% and 50.0% respectively.

5.3.5 Quality Of Life Rating In Relation To The Ethnicity Of The Patients

The Ikwerre ethnic group rated their Quality of life poor in overall Quality of life 48.4%, HRQuality of life 43.6%, physical domain 45.2%, psychological domain 37.1% and environmental domain 45.2%. More of the Ijaws rated their Quality of life poor in the constructs of health satisfaction 60.0% and social relationship domain 40.0%. The relationship between Quality of liferating and ethnicity was statistically significant in the constructs of overall Quality of life P- value 0.015, HRQuality of life 0.001, health satisfaction P-value 0.001. Similarly, a review of diabetes self care interventions for adults with varying cultural backgrounds, showed that cultural differences affected diabetic quality of life.155,175,176 Researchers have identified ethnic differences in quality of life measures amongst Chinese, Malaysians and Indians residing in Singapore.11 The Indian participants in the study reported higher psychological scores, while the Chinese participants scored higher in physical as well as independent scores.155 They noted that the Indio-Asians had lower Quality of life scores for both physical health as well as mental health scores compared to their White European counterparts.155 However, in the study of type 2 diabetes mellitus in the Texas-Mexico border which reviewed a total of 199 respondents on the US side and 200 respondents in the Reynosa Mexico side. There was no statistically significant difference in physical and mental health status score between Valley and Reynosa (Border) study participants.157 This similarity they attributed to the fact that the US- Mexico border is the melting point of culture and behaviour.157 It is noted that the two tribes that had more patients scoring poor were the indigenous tribes; Ikwerre and the Ijaws. This may mean that by their cultural disposition for instance the fattening room ceremonies of the Ijaws, they have difficulty in adjusting to the disease.

5.4 Anthropometric Characteristics in Relation to Quality of Life

5.4.1 Clinical Characteristics in Relation to Quality of Life

5.4.1.2 Duration of Illness In Relation to Quality of Life

More of those with illness duration > 15 years rated their Quality of life poor with scores of 53.8%, 46.2%, 61.5%, 38.5%, 53.9%, 61.5% for the constructs of overall Quality of life, HRQuality of life, physical domain, psychological domain, social relationship domain and environmental domain respectively.

Exceptionally, more of those with illness duration 5-15years rated their Quality of life poor with a score of 49.1% in the health satisfaction construct. The relationship between the Quality of life rating and duration of illness was only statistically significant for the constructs of overall Quality of life P-value 0.022, social relationship domain P-value 0.034, and environmental domain P-value 0.001. Those with longer duration of illness were likely to have poorer glyceamic control. This is due to dwindling pancreatic B-cell reserve as the illness lasted. It is already noted that poor glyceamic control is associated with more complications.6 Complications negatively impact the Quality of life of the patients.

Again, longer duration of illness means more co-morbidity due to aging with failing vital organs.6 These explain why those with longer duration of illness rated their Quality of life as poor. Nevertheless, most of the constructs did not show statistically significant relationship between the Quality of life rating and the duration of illness, expect for overall Quality of life, social relationship domain and environmental domain with P-values of 0.022, 0.034 and 0.001 respectively. In Iran, Alvi and Co did not find any statistically significant relationship between duration of illness and Quality of life109.Gorien et al in Turkey did not also find any statistically significant relationship between duration of illness and Quality of life99. The study done in Saudi Arabia also did not find any statistically significant association between the HRQuality of life of type 2 diabetic patients and duration of the disease.133Also in relation to the findings of the study, researchers in a longitudinal epidemiological study in Mauritus, noted that there was no significant relationship between duration of disease and Quality of life.116

In a case series health centre based study in Mosul, it was noted that the longer the duration of illness the poorer the perceived quality of life for the patient.165 Also in the work done in Turkey, longer duration of illness was associated with poorest Quality of life, however the researchers did not give figures of their findings. 122 A cross – sectional study that enrolled 376 respondents in Latfi Kirdar Kartal Turkey, also reported better Quality of life for patients with duration of disease <8 years.10 This was also the case in a survey carried out in Manisa Turkey where researchers noted that duration of illness was only significant in the physical domain and not significant in psychological, social and environmental domains.125

5.4.1.3 Quality of Life Rating in Relation to the Bmi of the Patients

The result of this study shows that in almost all the constructs, more of the obese patients scored their Quality of life poor. 49.3%, 52.8%, 43.2%, 50.5%, 46.6% and 48.0% for the constructs of overall Quality of life, HRQuality of life, health satisfaction, physical, psychological and social relationship domains respectively using BMI. In assessing obesity with the waist circumference more of the obese patients rated their Quality of life poor in all the constructs; HRQuality of life, health satisfaction and in all the domains, physical psychological, social relationship and environmental domains with scores of 48.0%, 47.0%, 41.5%, 52.0% and 51.0% respectively.

It is already noted that the diabetic patients that are obese are prone to more complications and comorbidities.179 They also eat a lot and find dietary restriction most disgusting. Their size also makes mobility difficult for them179. Hence, it is not surprising that more of them scored their Quality of life poor in all facets of the Quality of life evaluation.

The obese scored poorly not only because of complications but because of difficulty in relation to mobility, pain and discomfort.18 Several studies have shown that obesity negatively impacts Quality of life in type 2 diabetes mellitus patients.

Researchers in Mexico-Texas survey noted that respondents with severe obesity had poorest scores in the physical and psychological domains, 43.5% and 41.4% respectively.101 However, they noted that during the survey, dependent and independent variables were measured using a self reporting instrument that carries intrinsic respondents’ biases. 101

The relationship betweenQuality of life and obesity as assessed by waist circumference was statistically significant for HRQuality of life, health satisfaction, physical, social relationship domains and overall Quality of life with p-values of 0.001 for every of the constructs.

5.4.2 Quality of Life Rating in Relation to the Blood Glucose of the Patients

The Quality of life of the patients with poorly controlled blood glucose was rated as poor by most of them compared to those who had good blood glucose control, 49.1%, 47.2%, 42.7%,43.3%,44.6% for the constructs of overall Quality of life, health satisfaction, psychological domain, social relationship domain and environmental domain respectively. The Quality of life rating in relation to blood glucose was statistically significant for the constructs of overall Quality of life, HRQuality of life, Health satisfaction, physical and social relationship domains with p-values of 0.001, 0.010, 0.001, 0.025 and 0.045 respectively. Alvi and Co. in Iran did not find any statistically significant relationship between glucose control and overall Quality of life109.Abnormal glucose level is a pointer to difficulty in adapting to the diabetes mellitus disease. The poorer the glyceamic control, the more the complications of diabetes mellitus.180,181,182

Complications are strong predictors of Quality of life; this explains the poor Quality of life of the diabetic patients in this work who had poor glycaemic control.183 In a cross sectional survey in Manisa, Turkey that enrolled only 98 patients, it was noted that the better the glyceamic control, the higher the Quality of life. The same result was observed in a longitudinal hospital –based study in Turkey. In that work,
those who had better glycaemic control also had better Quality of life.183

5.5 Conclusion

This study was undertaken to investigate the relationship between diabetes mellitus and Quality of life. The result of the study showed that close to half of the patients were of the age group 55-64years, (43.0%), were of the social class 4 (46.0%). Majority of the patients were married 71.9%, a little above half were from the Ijaw ethnic group 54.3%, close to half (43.7%) earned a salary of (N18,000-N100,000). A little above half of the patients as assessed by BMI, and W/C were obese 54.6% and 74.9% respectively.

A little above half of the female gender had poorly controlled blood glucose of 52.9%.

Most of the patients had poor blood glucose control and the relationship between level of blood glucose control and age, occupation, level of education and marital status were statistically significant.

Most of those obese also had poorly controlled blood glucose level. The relationship between poorly controlled blood glucose and obesity was statistically significant. More of the older patients scored their Quality of life as poor; the older age groups 65-74yrs and 55-64yrs rated their Quality of life poor in all the constructs except the social relationship domain where more of those of the age group 30-45 years rated their Quality of life as poor.

The Quality of life rating in this study is almost similar to the Quality of life rating of diabetic patients in other centres. The prevalence and socio-demographic characters of the diabetic patients in this study was also similar to those of other centres, particularly those of the developed countries. This lays credience to the fact that developing countries are closing rank with the developed world in the disease burden of chronic non-communicable diseases. Unfortunately, the developing countries are least prepared, and have other diseases that are pandemic particularly infectious diseases like human immune deficiency disease, more than the developed countries.

There was statistically significant relationship between the Quality of life of the patients and their age, occupation, marital status, education and salary range. More male gender perceived their Quality of life as poor compared to the females. More of those of the lower income and those of the lower social class scored their Quality of life as poor.
More of those separated rated their Quality of life as poor compared to those married.

The relationship between Quality of life and marital status was statistically significant in all the constructs except for those of physical, psychological and environmental domains.

More of those who earned more salary rated their Quality of life poor when compared with those who earned poor salary. This is rather surprising, except for the fact that the rich has more money to spend on food, and would feel the most unhappy with the dietary restrictions as obtained in diabetes mellitus. The relationship between salary and Quality of life was statistically significant for all the constructs except for physical domain.

More of the Ikwerre ethnic group rated their Quality of life as poor in almost all the constructs except for the health satisfaction and social relationship domain. The relationship between Quality of life and ethnicity was statistically significant for the overall Quality of life and health satisfaction.

The more the duration of illness the more the patients rated their Quality of life as poor. The relationship between Quality of life rating and duration of illness was statistically significant for only the overall Quality of life, social relationship and environmental domains.

More of the obese patients rated their Quality of life as poor, and the relationship between Quality of life and obesity was statistically significant. More of those with poor glyceamic control also rated their Quality of life as poor and the relationship between Quality of life and glyceamic control was statistically significant for only the constructs of overall Quality of life, HRQuality of life and health satisfaction.

5.6 Recommendations

The age group 65-74; the female gender, those in the lower social class (4,5), the uneducated, the seperated, those with longer duration of illness, the obese and those with poor blood glucose control need special attention as regards their glyceamic control and their psycho-social adjustment to the illness.

Patients should be made active participants in their illness management. The role of the patient should be emphasized (patient – centred care).

The family physician should be educated on sociology and psychology, so that he can properly assess the psycho-social life of his patient in relation to their adjustment to illnesses particularly diabetes mellitus, that is their Quality of life.

The patient should be given diabetes education with emphasis on the need for his blood glucose control to be tight. This will delay the development of complications. Ethnicity, age and gender variations in response to the disease, point to a need for flexibility and adaptive approach in the management of diabetes mellitus.

Ways of improving the self efficacy and coping skill of the patient should be sought which include, improving his education, including organizing evening school if need be, advocating for better living conditions of the patient by the government. These include the provision of jobs. Life style modifications including avoidance of diets with high glycaemic index should be discouraged. This will lead to the prevention of diabetes mellitusat the primary, secondary and tertiary levels.

The high level of obesity in this study population calls for the campaign for increased physical exercise to be intensified.

The family physician should be able to identify barriers to weight reduction, and seek ways of removing them. The mass media should be used to discourage the consumption of obesogenic diet, instead of its current role in promoting same. This will reduce the prevalence of diabetes mellitus with improved Quality of life of the general population.

Though the family physician is an educator and counselor, managing diabetes mellitus is obviously multi-disciplinary. He could therefore have psychologist and social workers in his diabetic management team.

Family physicians should make their consultation with diabetes mellitus patients interactive so as to educate and empower the patients. This will help achieve and maintain good glyceamic control and better Quality of life. Quality of life issues should be assessed during consultation so as to effectively monitor the same for appropriate and timely intervention. Consultation should take a little longer time, so that the primary care physician will get to know the patient better. This will enable him attend to the health related Quality of life that affects daily living.

The result of this study showed that diabetes mellitus affects the Quality of life of the patients. Assessing the Quality of life of a diabetes mellitus patient could form part of a comprehensive management of a diabetic patient. This assessment should be culturally sensitive to accommodate different ethnic groups. Different cultures rate the impact of diabetes mellitus on the Quality of life differently. Also from this result, tight glycaemic control should be ensured in diabetic patients as this will reduce not only the rate of developing complications but also the impact of the disease on the Quality of life of the patients. The treatment of diabetes mellitus by the family physician must address mental stress (Quality of life) brought about by the life-long management of diabetes mellitus, the fear of complication and the economic burden of the disease on the patients and their families.

The Institute of Medicine in the United States of America in their report titled, “Food Marketing To Children And Youths; Threat or Opportunity’, concluded that marketing of food and beverages to children should be regulated with the intervention targeting individuals, families, government, restaurants, and the food and advertising industries.64

The Nigerian Government should adopt the same strategy so as to improve healthy living and reduce the prevalence of diabetes mellitus, with improved Quality of life.

The age group 55-64years need special attention in terms of care, since increased well being in this age group will translate to increased productivity and consequently, an enhanced ability to cater for their families. The Rivers State Government should consider retaining those of retirement age on contract. This will enable these patients who are mostly retired to be re-employed. By this they will be able to fund their disease and cater for their families.
Further studies on the quality of marriage and the quality of life of diabetes mellitus patients in BMSH should be carried out in order to assess the effect of family support on diabetes mellitus patients. A study could as well be done to compare the quality of life of diabetes mellitus patients in private health institutions and that of those attending public health institutions as in this study.