Diabetes patients took part in both quantitative and qualitative strands; therefore, the results are presented accordingly, including mixed method results which involved the integration of both quantitative and qualitative patients results through merging using joint display for comparison.
4.3.1 Quantitative results and discussion of diabetes patients
The quantitative results of diabetes patients are presented according to subsection of the questionnaire which are (1) Socio-demographic profile, (2) Anthropometric measurements, (3) Knowledge, (4) Attitudes and (5) Practices related to nutrition and exercise diabetes care. Therefore, results of diabetes patients are as follows:
4.3.2 Socio-demographic profile of diabetes patients
Figure 4.1: Age groups of patients
Figure 4.1 shows that over a third (37%) of the participants were between the age of 61 and 70 years, followed by those above the age of 70 years (27%), and the least of the participants were those below the age of 50 years (11%).
Type-2 Diabetes Mellitus (T2DM) is most prevalent type of Diabetes Mellitus worldwide and affect mostly older people (International Diabetes Federation (IDF), 2014). This study shows that close to two-third of diabetes patients (65%) were of the age of 60 years and above, which confirms that diabetes mellitus is most prevalence among the elderly (Herman, Schmitt, Gahr et al., 2015).
0%
5%
10%
15%
20%
25%
30%
35%
40%
<50yrs 51-60yrs 61-70yrs ≥71yrs 11%
25%
37%
27%
Percentages
Age ranges
Age Distribution of Patients
Figure 4.2: Gender of the patients
Figure 4.2 shows that an overwhelming majority of participants were females (81%) and only 19% were males.
This study surpassed a Tanzanian study regarding prevalence of diabetes which showed that 61.4% of participants were females (Chiwanga et al., 2016). Moreover, this study findings are also similar to a study which showed higher prevalence of diabetes mellitus amongst females than males which could be due to a high rate of physical inactivity and bad eating habits amongst females (Azimi-Nezhad, et al., 2008).
Figure 4.3: Education of patients
Figure 4.3 shows that an overwhelming majority of participants had primary or no schooling (81%), followed by those who had secondary schooling (17%) and only 1%
had tertiary education.
19%
81%
Gender of Patients
Males Females
81%
17%
2%
Education of Patients
Primary school or less
Secondary school
Tertiary
This study surpassed Statistics South Africa (Stats SA) (2013) report which indicated that highest percentages of adults with no formal schooling among African women and men at 14,8% and 10,8%, respectively. This could additionally be ascribed to the fact that most of the participants were over the age of 60 years, who could have had no access to education during apartheid South Africa (SA).
Figure 4.4: Marital status of patients
Figure 4.4 shows that most of the participants were married (74%), and only 26% were single.
This study affirms Stats SA (2013), that only smaller proportions of persons aged 30–
59 years are married compared to the older persons. Spousal support has been found to positively influence diabetes outcomes (Baig et al., 2015), implying that patients in this study would benefit from spousal support.
26%
74%
Marital Status of Patients
Single Married
Figure 4.5: Religious affiliation of patients
Figure 4.5 shows that over half of the participants were Christians (58%), followed by those who affiliate to other religions (31%) such as traditional African religion, Hinduism, etc and least were none affiliated (11%).
This study is in accordance with the 2001 census data on religion which reported that almost 80% of South Africa’s are Christians (Erasmus & Hendriks, 2005).
Table 4.1: Income of patients
Income of patients Frequency
(n=200)
Percentages (100%)
Income No income 48 24%
≤R1000 11 5,5%
>R1000 141 70,5%
0%
10%
20%
30%
40%
50%
60%
Christianity None Other
58%
11%
31%
Percentages
Types of religion
Religious Affiliation of Patients
Other person with income in the family
Yes 107 53,5%
No 93 46,5%
Number of family members with income
None 93 46,5%
1-2 98 49%
3-4 9 4,5%
Number of family members at home
2-6 154 77%
7-12 46 23%
Table 4.1 shows that most of the participants have a monthly income of over R1000 (70,5%), over half of the participants have other family members with income (53,5%), and close to half of the participants have between one and two family members with income (49%). Also, most of participants stays with a family size of between two and six individuals (77%).
According to Stats SA (2013) more African women than men are receiving old-age social grants, which is above R1000. Therefore, this study is in accordance with a report highlighting that most of the females are beneficiaries of old-age social grant.
Over half of the participants had other family members with income, which was expected since most participants were elderly, female and married, which could mean their partners are also above the age of 60 years and also earning old-age social grant.
Close to half of the participants had between 1 and 2 of other family members with income, it could also imply that the participants had children who are either working, engaged in market-activities or having children with kids receiving child support grant, which is provided by South African government (Department of Social Development (DSD), 2012).
Various studies detailed that men strongly influence couples’ childbearing behaviour (Ezeh, 1993; Speizer, 1999). Another study additionally detailed that African men’s
ideal number of children tends to be higher than women’s (Gebreselassie, 2008). Most of the participants stays with a family of between two to six people, which could be attributed to males’ influence of bigger family sizes. Likewise, it could be ascribed to the fact that the majority of the participants in this study were elderly with children, who could have given participants grandchildren. Research by Brody Kogan, Murry, Chen, and Brown (2008) has shown that self-care is compromised when individuals live alone without people to provide emotional or physical support. Participants in this study have a support base since the majority live with family members.
Table 4.2: Family prevalence, knowledge of status and support in diabetes care of patients
Family prevalence, knowledge of status and support in diabetes care of patients
Frequency (n=200)
Percentages (100%)
Does your family know you have diabetes?
Yes 192 96%
No 8 4%
Do you have any family member with diabetes
Yes 39 19,5%
No 161 81%
Other family member with diabetes
None 161 80,5%
1 37 18,5%
2 2 1%
Did a family member accompany you to consult dietitian in the past 6 months?
Yes 12 6%
No 188 94%
Did a family member accompany you to consult physiotherapist in the past 6 months?
Yes 7 3,5%
No 193 96,5%
Table 4.2 shows that an overwhelming majority of participants reported that they families know about their diabetes diagnosis (96%); only 19,5% of participants have other family members with diabetes, and most of the participants have 1 family member with diabetes (18,5%). An overwhelming majority of participants were not accompanied to both dietitian (94%) and physiotherapist (96,5%) in the past 6 months respectively.
This study concurs with cross-sectional study which indicated that families of diabetes patients know about their diagnosis and are being supported and cared for by their families (Shilubane & Potgieter, 2007). An Indian study by Anjana et al. (2011), reported that around 60% diabetes mellitus patients had family members suffering from diabetes affirming heredity as an important risk factor of developing Diabetes Mellitus. This study showed only few diabetes patients had family members with diabetes, of which the majority of them had 1 family member with the disease.
Therefore, this study differs with the Indian study reporting 60% of diabetes patients having family members with diabetes but does not differ on heredity being important risk factor. Also, most of the participants pointed that their families never accompanied them to either consult dietitian or physiotherapists in the past 6 months. Family is underutilized resource for continuous support and often battle on best support (Kovacs, Burns, Nicolucci, et al., 2013). Therefore, this study confirms that indeed family remains underutilized resources by healthcare and patients to help in providing continuous support to patients.
Figure 4.6: Diabetes control of participants
Figure 4.6 shows that an overwhelming majority of participants control their diabetes through oral medication (92%), followed by those using insulin injection (7%), and least being those who use other forms (1%).
This study showed that an overwhelming majority of participants controls diabetes through oral medication (92,5%), which confirms that T2DM is most prevalent among the elderly and that it is mostly controlled through medication (Herman et al., 2015).
Figure 4.7: Period at which participants lived with diabetes
Figure 4.7 shows that over a third of participants lived with diabetes for over 10 years (37%), followed by those with 2-5 years (35%), and least being those with 1 years or less (11%).
According to Shilubane, Netshikweta and Ralineba (2016), the prevalence of diabetes among South Africans aged 30 years or more has expanded by half since 2009,
92%
7%
1%
Diabetes Control of Patients
Oral medication (pills) Insulin injection Other
0%
5%
10%
15%
20%
25%
30%
35%
40%
≤1yrs 2-5yrs 6-10yrs >10yrs
11%
35%
17%
37%
Percentages
Years
Period of living with Diabetes
therefore, it is not surprising that over a third of participants lived with diabetes for more than 10 years, since they could have had diabetes at their early ages considering also that most participants are above 60 years.
Table 4.3: Co-morbidities of diabetes patients
Co-morbidities of diabetes patients Frequency(n=200) Percentage (100%)
Do you suffer from any other diseases besides diabetes?
Yes 151 75,5%
No 49 24,5%
How many additional diseases do you have?
None 48 24%
1 126 63%
2 24 12%
3 2 1%
Types of additional diseases
Hypertension (n=200)
Yes 135 67,5%
No 65 32,5%
Arthritis (n=200)
Yes 27 13,5%
No 173 86,5%
Heart (n=200) Yes 4 2%
No 196 98%
Asthma (n=200)
Yes 2 1%
No 198 99%
HIV (n=200) Yes 4 2%
No 196 98%
Cancer (n=200)
Yes 2 1%
No 198 99%
Table 4.3 shows that most of the participants suffer from additional diseases besides diabetes (75,5%), of which close to two-third had 1 additional disease (63%), and over two-third of the participants besides diabetes had hypertension (67,5%).
Presence of comorbid conditions influences health and Quality of Life (QoL) of patients (Nguyen, Tran & Nguyen, 2019). The results of this study indicated infers that diabetes mellitus patients are in danger of health deterioration, diseases and death, if measures are not taken to improve their self-care practices. Moreover, over two-third of the participants had hypertension as a leading comorbid condition, which is not surprising since diabetes patients are often obese, of which obesity has been linked with rates of hypertension among diabetes patients (Gus et al., 2009). Comorbidity is common and connected with unfavorable clinical outcomes and higher healthcare costs, contrasted with single chronic disease (Parekh, Goodman, Gordon et al., 2011).
Therefore, the results of this study place a risk to the Department of Health (DOH) ’s budget considering the cost burden of managing diabetes worsens in the presence of comorbidity condition.
4.3.1.2 Anthropometric assessment for diabetes patients
Objective 1: To determine anthropometric measurements i.e., Body Mass Index &
Waist Circumference.
Figure 4.8: BMI of patients
Figure 4.8 shows that over half of participants are obese (57%), followed by over a third of overweight (34%) and least having normal weight (9%).
This study differs with Tanzanian study which detailed that less than half of the diabetes patients in rural areas were either overweight or obese (Chiwanga et al., 2016). Obesity increases chances of poor diabetes outcomes by disturbing diabetes control (James, Rigby & Leach, 2004). Likewise, poor diabetes control leads to diabetes complications and expands the dangers of diabetes associated health problems (James et al., 2004). Again, prevalence of obesity among over half of the participants in this study could be responsible for prevalence of comorbid condition among participants, thereby confirming that obesity increases chances of poor diabetes control and complications.
0%
10%
20%
30%
40%
50%
60%
Normal weight Overweight Obese
9%
34%
57%
Percentages
BMI Classification
BMI of Patients
Table 4.4: BMI patients by sociodemographic profile
BMI of patients by socio- demographic profile
BMI P-values
Normal weight
Overweight Obesity
Age ≤50yrs 1 4 16 X2 = 3.527
P = 0.171
>50yrs 17 64 98
Gender Male 6 18 13 X2 = 9.300*
P = 0.010
Female 12 50 101
Education Primary or less
17 55 90 X2 = 2.427
P = 0.297 Secondary
or more
1 13 24
Marriage Single 6 10 35 X2 = 6.376*
P = 0.041
Marriage 12 58 79
*signifies statistical significance @ 95% CI
Table 4.4 shows that there was no significant association between BMI and age (p- value=0.171), and also education (p-value=0.297) respectively. However, there was significant association between BMI and gender (p-value=0.010), and also marriage (p-value=0.041).
United States (US) study involving school children discovered that an individual socio- demographic characteristic such as age, and gender were associated with obesity among participants (Rundle et al., 2012). Similar results were highlighted by the
Nigerian study involving school children which also found out that gender, age and socio-economic factors influences abnormal BMI among the participants (Akinsola et al., 2018). This study found no significant association between Body Mass Index (BMI) and age, yet there was significant association between BMI and gender. Therefore, this study differs with the studies on the significant association between BMI and age, however, concurs on significant association between BMI and gender.
Figure 4.9: Waist circumference of patients
Figure 4.9 shows that most of the participants had abdominal obesity (75%) and only 25% does not have abdominal obesity.
This study further differs with Tanzanian study which revealed that only 20,6% of diabetes patients had abdominal obesity in rural areas (Chiwanga et al., 2016).
Abdominal obesity has been associated with hypertension (Gus et al., 2009).
Therefore, this study also confirms association between abdominal obesity and hypertension, since most participants had hypertension as the most prevalent comorbidity.
13%
5%
Waist Circumference of Patients
Abdominal Obesity No Abdominal Obesity
Figure 4.10: Waist circumference of patients by gender
Figure 4.10 shows that most of participants with abdominal obesity are females (71%) and compared to 5% of males.
An Iranian population cohort study detailed that abdominal obesity was most prevalent among male diabetic patients as compared to females (Haghighatdoos et al., 2017), which differs with the findings of this study which in contrast showed prevalent of abdominal obesity among females.
4.3.1.3 Knowledge of diabetes patients
Objective 2: To determine knowledge regarding nutrition and exercise in the management of diabetes.
Overall knowledge of diabetes patients regarding nutrition and exercise in diabetes management
13%
71%
5% 11%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Male Female
Percentages
Gender of Participants
Waist Circumference of Patients by Gender
Abdominal Obesity No Abdominal Obesity
Figure 4.11: Overall knowledge of patients regarding diabetes care through nutrition and exercise
Figure 4.11 shows that close to half of the participants had excellent knowledge (45%), followed by about a third with good knowledge (31%), and the least were those with fair knowledge (5%).
This study affirms various studies which indicated that patients are found deficit with diabetes knowledge (Breen et al., 2015; Fitzgerald, Damio, Segura-Pérez & Pérez- Escamilla, 2008), notwithstanding growing diabetes prevalence (IDF, 2015). Adequate knowledge of diabetes can prevent chronic comorbidities and other complications of diabetes, which has significant impact on the quality of life (Nagar, Prasad, Mitra, Kale, Yadav & Shukla, 2018). Most of the participants in this study had comorbid conditions which could be attributed to lack or inadequate knowledge of participants. Therefore, in a way this study confirms that adequate knowledge prevents against comorbidity.
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Poor knowledge
Fair knowledge Good knowledge
Excellent Knowledge 19%
5%
31%
45%
Percentages
Knowledge Classification
Overall Knowledge of Patients
Table 4.5: Overall knowledge of patients by socio-demographic profile
Knowledge of patients by socio- demographic profile
Overall knowledge P-
value s Poor
knowledg e
Fair knowledg e
Good knowledg e
Excellent knowledg e
Age ≤50yrs 3 2 4 12 X2 =
7.223 P = 0.614
51-60yrs 9 1 13 26
61-70yrs 16 5 27 27
>70yrs 9 3 18 25
Gender Male 10 2 12 13 X2=
2.797 P = 0.424
Female 27 9 50 77
Educatio n
Primary or less
31 11 54 66 X2=
8.943 P = 0.177 Secondar
y or less
6 0 8 20
Marriage Single 6 4 16 25 X2 =
2.611 P = 0.456
Married 31 7 46 65
Table 4.5 shows that there is no significant association between levels of knowledge and sociodemographic profile i.e., Age (p-value =0.614), gender (p-value =0.424), education (p-value= 0.177), and marriage (p-value= 0.546) respectively.
A Zimbabwean cross-sectional study highlighted that low diabetes knowledge was associated with female gender and could be a risk factor for the development of diabetes-related complications (Mufunda et al., 2012). An overwhelming majority of participants in this study were females and only about a third of participants had excellent diabetes nutrition and exercise knowledge, therefore, lack of significant association between overall knowledge and sociodemographic profile in this study affirm the association of inadequate knowledge with females. A study by Malathy et al., (2011) reported that “educated diabetes patients lacked knowledge on how to manage their disease because of their ignorance and laziness to seek information regarding how exercises improve their condition”. This is supported by (Okonta, 2014) who also “reported that low levels of education led to poor knowledge on benefits of exercises on lowering blood glucose level.”
Knowledge of diabetes patients regarding nutrition in diabetes management Table 4. 6: Knowledge of patients regarding diabetes care through nutrition, % in rows; n=200
Knowledge of patients regarding diabetes care through nutrition
Yes Not sure No
Nutrition plays an important part in diabetes management.
162(81%) 3(1,5%) 35(17,5%)
Fruits and vegetables must be eaten because they are good in managing blood sugar.
177(88,5%) 1(0,5%) 22(11%)
It is good to eat small, frequent meals regularly to manage blood sugar.
165(82,5%) 5(2,5%) 30(15%)
Whole-grains high in fibre are recommended as a healthy source of carbohydrate.
159(79,5%) 2(1%) 39(19,5%)
When overweight and diabetes, it is good to skip meals to lose weight.
134(76%) 11(5,5%) 55(27,5%)
When preparing meat, it is recommended to remove visible fats from red meat, and also to eat chicken without skin.
174(87%) 6(3%) 20(10%)
Eating a large portion size of food at once may lead to increased blood sugar.
163(81,5%) 6(3%) 31(15,5%)
High fat dairy products including high animal proteins must be avoided.
163(81,5%) 4(2%) 33(16,5%)
It is good to cut back on salty food including high sodium food such as processed food.
172(86%) 2(1%) 26(13%)
It is good to cut back on sugary food including avoiding added sugar in drinks and food.
177(88,5%) 5(2,5%) 18(9%)
Fried food and other food high in fats must be avoided.
168(84%) 5(2,5%) 27(13,5%)
Table 4.6 shows that an overwhelming majority of participants know that nutrition plays important part in diabetes care (81%); fruits and vegetables must be eaten because they are good in managing blood sugar (88,5%); eating small frequent meals is recommended (82,5%), including eating whole grains high in fibre (79,5%), as well as removing visible fats from red meat and eating skinless chicken (87%). Less than a third of the participants believe overweight diabetes patients should skip meals to lose weight (27,5%). Also, an overwhelming majority of participants reported that eating large portion sizes at once will increase blood sugar (81,5%); it is good to cut back on both salty food (86%), and sugary food (88,5%), including avoiding high fat dairy products (81,5%) and fried food (84%).
The findings of the study impressively revealed that an overwhelming majority of participants know that nutrition is important in diabetes care, and that fruits and vegetables, whole-grains high in fibre should be eaten. This gives hope that diabetes patients will begin to eat healthy diet which includes consumption of vegetables and fruits and whole-grains, leading to improved glycaemic control (Ronquest-Ross, Vink
& Sigge, 2015). “This is because knowledge can lead individuals pursue healthy eating (Spronk, Kullen, Burdon, & O’Connor, 2014), anyway this is not an assurance that diabetes patients will consume healthy diet, since there are factors such as food availability and affordability which determine or affect intake (Campbell, King-Shier, Hemmelgarn et al., 2014).”
“Food preparation and serving are important in diabetes care, since diabetes patients should not be eating large portion sizes since it may prompt increased glucose levels”
(Mahan & Escott-Stump, 2008). An overwhelming majority of participants indicated that it is important to eat small frequent meals and that visible fats in red meat including chicken skin should be removed during preparation. Also, the results impressively show that an overwhelming majority of participants know that it is good to cut back on both salty and sugary food, including avoiding high fat dairy products and fried food.
This gives hope that diabetes patients will use healthy food preparation method and consume healthy food in small portion for good diabetes control. However, it is assumed that the majority of diabetes patients do not cook or prepare food for themselves, their food is often prepared by their families who may not know these food preparations and serving of small portion sizes and continue to serve patients large