ABSTRACT
Although there have been studies on prevalence of obesity and diabetes among the elderly in Nigeria, there is a paucity of information on the health belief determinants of obesity and diabetes among the elderly in rural and urban settings. It is in this view that this study seeks to assess the health belief determinants of obesity and diabetes mellitus among the elderly in Umuahia metropolis in Umuahia North LGA and UmuikeaIsialaNgwa South LGA.A cross-sectional survey design was used. The study population consisted of older persons from 60 years and above residing in Umuahia metropolis and Umuikea region of Abia State.Multi-stage sampling technique was used. In the first stage two (2) two Local Government Areas from the 17 LGAs in Abia State were selected by balloting based on the criteria of been an urban or rural settlement. In the second stage two communities each were selected by balloting in each of the selected LGAs.Data collection was done using a closed ended questionnaire and interview structured in line with the questionnaires was used. The questionnaire was sectioned into four (4) section A assessed the socioeconomic and demographic data, section B assessed the health beliefs determinants of obesity, section C assessed the health beliefs determinants of diabetes mellitus, section D assessed the anthropometric and blood glucose measurements of the respondents.Descriptive statistics (frequency and percentage, mean and standard deviation) was obtained for objective 1, 2, 3 and 4 respectively and inferential statistics was obtained for objective 5 while significance was judged at p<0.05. Result showed that many (65.3%) of the subjects were between the ages of 60-65 years while few (2%) of them were above 90 years of age. more than half (65.3%) of the subjects were females while some (34.7%) of them were males.The BMI result revealed that some (30.6%) of the subjects were overweight (pre-obese 28.23±1.70), 24.5% of them had normal weight (22.99±1.02) while the various classes of obesity were also prevalent (class 1 (16.3%) 32.34±0.74, class 2 (14.3%) 37.09±0.41) and class 3 (14.3%).The random blood glucose result showed that majority (79.6%) of the subjects had a normal blood glucose level (112.15±15.13), 8.2% of the subjects were pre-diabetic (155.75±6.44), while few (6.1%) of the subjects had diabetics (315.67±46.19) and had low blood glucose (67.00±0.00) respectively. No significant relationship was observed between the health belief determinants, the body mass index and the waist hip ratio of the subjects.This study recommends a multi-sectoral approach in the intervention to curb the incidence of malnutrition among the elderly population in the study area which will involve both the education, media and health sectors.
TABLE OF CONTENTS
TITLE PAGE i
CERTIFICATION ii
DEDICATION iii
ACKNOWLEDGEMENTS iv
TABLE OF CONTENTS v
LIST OF TABLES vi
LIST OF FIGURES
vii
ABSTRACT viii
CHAPTER 1
INTRODUCTION 1
1.1
Statement of Problem 3
1.2
Objective of the Study 5
1.3
Significance of the Study 6
CHAPTER
2
LITERATURE
REVIEW 7
2.1 Health belief model 7
2.2 Prevalence of obesity in
Nigeria
9
2.2.1what
is obesity 9
2.2.2cause
of obesity 11
2.2.3consequences
of obesity 12
CHAPTER
3
MATERIALS
AND METHODS 17
3.1Study Design 17
3.2Area
of Study 18
3.3Population of
the Study 18
3.4 Sampling and
Sampling Techniques 18
3.4.1Sample Size 18
3.4.2 Sampling
procedure 19
3.5 Preliminary Activities 19
3.5.1Preliminary Visits 19
3.5.2 Training of Research Assistants 20
3.6 Data Collection 20
3.6.1Questionnaire Administration 20
3.8
Statistical Analysis 21
CHAPTER 4
RESULTS AND DISCUSSION 22
4.1 Socio-economic/demographic
characteristic 22
4.2The
health belief determinants of obesity and diabetes among the
elderly 27
4.3
Blood glucose status and anthropometric status of the elderly 28
4.4 relationship
between the socio- demographic/economic characteristics, blood glucose and anthropometric
status of the elderly and their health belief determinants 31
CHAPTER
5
CONCLUSION
AND RECOMMENDATION 44
5.1 Conclusion 44
5.2Recommendation 45
REFERENCES
46
LIST OF TABLES
Table 4.1 Socio-economic and Demographic
Characteristics of the elderly 23
Table
4.2 Background Information of the
elderly studied On Obesity
and
diabetes mellitus 26
Table
4.3 Health Belief Determinants of
Obesity and Diabetes mellitus 27
Table 4.4 Anthropometric
and Random Blood Glucose Status of the elderly 30
Table 4.5 Relationship
between Health Belief Determinants of obesity, BMI and
WHR of
the elderly studied 32
Table 4.6 Relationship
between Health Belief Determinants of diabetes and
Random Blood Sugar of
the elderly studied 34
Table
4.7 Comparison of Mean Response
between the Health Belief Determinants
of
Obesity and Diabetes Mellitus of the elderly studied 36
Table
4.8 Relationship between Mean
Response on the Health Belief
determinants
of Obesity and Diabetes Mellitus, BMI, WHR and
RBG of the elderly
studied
39
Table
4.9 Relationship between Socio
Economic Characteristics and mean
response
on Health Belief Determinants of Obesity and Diabetes
mellitus
of the elderly studied
41
Table
4.10 Relationship between Socio
Economic Characteristics and mean
response on Health Belief
Determinants of Obesity and Diabetes
mellitus of the elderly
studied
43
CHAPTER 1
INTRODUCTION
It is believed that an individual’s behaviors are the results of
psychological activities, and the most direct psychological activities that
determine people to take certain behaviors are perception, attitude, and belief
(Li et al., 2019).
The health belief model (HBM), defines the key
factors that influence health behaviors as an individual’s perceived threat to
sickness or disease (perceived susceptibility), belief of adverse consequence (perceived
severity), potential positive benefits of action (perceived benefits), perceived
barriers to action, exposure to factors that prompt action (cues to action),
health motivation, and confidence in ability to succeed (self-efficacy) (Li et
al., 2019). Health belief model
(HBM) is used to reveal the reasons for showing or not showing health-related
behaviours, the behaviours to be protected from the disease, the motivating
factors and the behaviours of individuals related to care and treatment (Harvey
and Lawson, 2009; Hayden, 2009; Heiss, 2013).
Nearly
600 million of the world population is comprised of the elderly 60 years and
above and it is estimated that by 2050 this figure will reach about two billion
mainly living in developing countries (Shaghi et al., 2009). Globally the sharp increase in the number of the
elderly population is due to decline in birth rate, a rise in life expectancy,
development of urbanization, higher education, high income and accessibility to
health care (McCutcheon and Pruchno, 2011). On the other hand there has been an
increase in the prevalence of non-communicable diseases like coronary heart
disease, cancer, cerebrovascular diseases, diabetes mellitus, osteoporosis and
pulmonary diseases. Most of such chronic diseases have risk factors such as
high blood pressure, smoking, high cholesterol, obesity, physical inactivity
and unhealthy diet (Hosseini-Esfahani et
al., 2010).
Older persons are usually at risk for several medical and
nutritional problems as a result of obesity or under nutrition (www.healthinaging.org, 2015). Out
of the three vulnerable groups (pregnant women, infants, and the elderly
persons) that face nutritional and public health threats, the elderly
population has been somewhat neglected
(Ojofeitimi et
al., 2002). Vellas and Anthony (2006), reported
that malnutrition is very common among elderly people, predominantly in the
frail or sick and that poor nutritional status appears to be a major
contributing factor of poor prognosis during illness in these individuals. Little
is known about predictors of overweight and obesity in old age. These might
differ from younger population groups as in old age changes occur in body
composition, height, food intake and energy expenditure (Chapman, 2008). Old
adults have more body fat which, in addition, is distributed differently.
Likewise, a decrease in muscle mass and height is associated with ageing. Old
adults tend to have a lower food intake and become less hungry. Furthermore,
the degree of physical activities decreases in old age. Eventually, old adults
frequently lose weight for reasons of frailty, morbidity and imminent death. There
is a close association between obesity and type 2 diabetes. The likelihood and
severity of type 2 diabetes are closely linked with body mass index (BMI).
There is a seven times greater risk of diabetes in obese people compared to
those of healthy weight, with a threefold increase in risk for overweight
people (Abdullah et al., 2010).
Whilst it is known that body fat distribution is an important determinant of
increased risk of diabetes, the precise mechanism of association remains
unclear.
Diabetes
among the elderly is related to an increased risk of premature death, a greater
association with other comorbidities, and especially been with major geriatric
syndromes, including a decline in functional capacity, autonomy and quality of
life, making it a high-impact disease, which affects the health system, the
family and the elderly person themselves (Francisco et al., 2010; Sociedade Brasileira de Diabetes, 2014). It is a
highly limiting disease, with long-term consequences that include the damage
to, dysfunction and failure of various organs, especially the kidneys, eyes,
nerves, heart and blood vessels. People with diabetes are at increased risk of
hypertension and coronary, peripheral arterial and cerebrovascular disease, and
may also develop neuropathy, arthropathy and autonomic dysfunction, including sexual
dysfunction, which more frequently affect the elderly (Silva et al., 2014). In addition, the diabetic
elderly, when compared to non-diabetics, are more likely to be polymedicated,
suffer functional loss (difficulty in locomotion, for example), cognitive
problems, depression, falls and fractures, urinary incontinence and chronic
pain, and should, therefore, be treated in an individualized manner (Sociedade
Brasileira de Diabetes, 2014).
1.1
Statement
of problem
Obesity is no longer prevalent only among young people, obesity
among the elderly is also increasing globally and has significant public health
consequences (Case and Menendez, 2009; Han et al., 2011; Amarya et al.,
2014). Although the effects of obesity on mortality
and morbidity are well-studied and do point to diabetes and cardiovascular illnesses
as common mediating risk factors, the effects on elderly populations could be
more devastating. The impacts of elderly obesity include heart failure,
impaired physical functionality, arthritis, cancers, and hypertension (Calle
et al., 2005; Dixon, 2010; Han et al., 2011; Daïen and Sellam, 2015). In the West African countries of Ghana and
Republic of Benin, obesity is found in 13.6% and 18% respectively among adults
(Amoah, 2003; Sodjinou et al., 2008),
while Abubakari et al. (2008) reported
a prevalence of 10% in the West African sub-region with the odd of being obese
being 3.2 among urban women compared to men. Elderly
obesity also increases the risk of dementia and diabetes (Whitmer et al.,
2005; Salihu et al., 2009).
Approximately 1.9% of the global disability adjusted life years
is attributed to diabetes having doubled since 1990 (Murray
et al., 2012).
The International Diabetes Federation (IDF) estimates that 450 million people
are living with diabetes, with 5.1 million dying from it annually worldwide
(WHO, 2011; International Diabetes Federation,
2013). The prevalence of diabetes is expected to double by 2030 from 8.3 to
17.6% globally, excluding the high numbers of undiagnosed cases estimated at
175 million (Whiting et al.,
2011; International Diabetes Federation, 2013; Guariguata
et al., 2014; Beagley et al., 2014).
In sub-Saharan Africa, 21.5 million people are living with diabetes leading to
approximately half a million diabetes-related deaths in 2013 (International
Diabetes Federation, 2013). The prevalence of
diabetes varies in different age groups with the older population being at a
higher risk compared to the young population (Ayah et al., 2013).
For instance, the prevalence of diabetes has been estimated to be between 7.7
to 20% and 5 to 8.8% for adults aged 45 years and more in Kenya and South
Africa respectively (Motala et al.,
2008; Ayah et
al., 2013). In addition as identified by literatures, more diabetic people
live in urban than in rural areas (Motala et al., 2008; Mbanya., et al.,
2010).
Although
there have been studies on prevalence of obesity and diabetes among the elderly
in Nigeria, there is a paucity of information on the health belief determinants
of obesity and diabetes among the elderly in rural and urban settings. It is in
this view that this study seeks to assess the health belief determinants of
obesity and diabetes mellitus among the elderly in Umuahia metropolis in
Umuahia North LGA and Umuikea Isiala Ngwa South LGA.
1.2
OBJECTIVES OF THE STUDY
1.2.1 General
objective of the study
The
general objective of this study is to assess the health belief determinants of
obesity and diabetes mellitus among the elderly in selected rural Isiala Ngwa
South and urban Umuahia North Local Government Areas of Abia State.
1.2.2 Specific
objectives of the study
The specific
objectives of the study include to;
1. Assess
the socio demographic/ economic characteristics of the elderly in study areas.
2. Determine
the health belief determinants of obesity and diabetes among the elderly in the
study areas using health belief model
3. Assess
the blood glucose status of the elderly in the study areas.
4. Determine the anthropometric status of the
elderly in the study areas using Body Mass Index and Waist-Hip Ratio indicators
5. Identify
the relationship between the socio- demographic/economic characteristics, blood
glucose and anthropometric status of the elderly and their health belief
determinants.
1.3 SIGNIFICANCE OF THE STUDY
Findings
will be useful to the elderly population as it expose their health belief
determinants of obesity and diabetes mellitus creating room for adequate policy
formulation and programme development to suit the vulnerability of this age
group.
Both government and non-governmental
organizations, policy makers, the general public, nutrition educators, health
professionals as establishment of determinants will be potentially useful in
the holistic approach to the prevention of the rising prevalence of obesity,
diabetes and other non-communicable diseases. Findings will benefit future
researchers as it will also contribute the existing body of knowledge and serve
as a reference material.
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