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Introduction. Diabetes mellitus remains one of the most complex disorders worldwide impacting Quality of life (QOL). Because of the chronic nature of diabetes, the goal of medical treatment and lifestyle modifications. is not only to prolong life but also to maintain a high level of QOL The aims of the present study are ; (i) to assess the QOL and glycemic control (GC) among diabetic patients at king Abdulaziz Medical City (KAMC), KSA, and (ii) to determine the significant predictors of QOL and GC. Methods. A cross sectional survey was conducted to assess the Qol and glycemic control in 420 Saudi adult diabetics at outpatient clinics of KAMC using a previously validated Arabic version of Diabetes QoL Brief Clinical Inventory. Personal characteristics (age, gender, education, occupation, etc.), disease characteristics (age at onset, duration, type of diabetes, treatment regimen, complications) and lifestyle characteristics (dietary habits, smoking behavior, exercising) were obtained. Medical chart data of the duration of diabetes, and most recent HbA1c levels were extracted. Logistic regression analysis was applied to identify the significant predictors of good QOL. Significance limits were set at P <0.05. Results. The overall percentage mean score of Qol was 74.1+11.6, with good Qol in 29.8% of all patients. Diabetics reported lack of satisfaction of exercise (49.1%), burden on family (31%), and sex-life (28%) due to diabetes, and reported worry of : physical illness (31%), bad night sleep (26%), pain by treatment (24%), and limitation of career (22%) due to diabetes. After adjusting for possible confounders, higher QOL score was significantly associated with male gender (t=3.26,p=0.001), treatment with oral pills (2.14, p=0.03), healthy diet (t=2.63,p=0.009), physical inactivity (t=2.28,p=0.023) and absence of diabetic complications (t=3.47,p=0.001). Two-thirds (68.8%) of all patients showed poor glycemic control (PGC). Presence of diabetic complications was the only significant predictor of PGC (OR=1.66, p=0.024). Conclusion. Changing the lifestyle of Saudi diabetics is necessary to improve their QOL. Avoidance of complications is a safeguard against possible deterioration in Qol and glycemic control. Future research on transcultural aspects, and effects of lifestyle interventions is recommended.
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Predictors of Quality of Life and Glycemic Control
Among Saudi Adults with Diabetes
Mostafa A. Abolfotouh
King Abdullah International Medical Research Center (KAIMRC), King Saud bin-Abdulaziz University for Health
Sciences, Riyadh, Saudi Arabia
Mahmoud Salam
King Abdullah International Medical Research Center (KAIMRC)
Deema Alturaif
King Abdullah International Medical Research Center (KAIMRC)
Wijdan Suliman
King Abdullah International Medical Research Center (KAIMRC)
Noran A Al-Essa
King Saud bin-Abdulaziz University for Health Sciences, College of Medicine, Riyadh, Saudi Arabia
Hadeel Al-Issa
King Saud bin-Abdulaziz University for Health Sciences, College of Medicine, Riyadh, Saudi Arabia
Mohamed A. AlRowaily
King Saud bin-Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
Corresponding author Email: mabolfotouh@gmail.com
ABSTRACT
Introduction. Diabetes mellitus remains one of the most
complex disorders worldwide impacting Quality of life
(QOL). Because of the chronic nature of diabetes, the goal
of medical treatment and lifestyle modifications. is not
only to prolong life but also to maintain a high level of
QOL The aims of the present study are ; (i) to assess the
QOL and glycemic control (GC) among diabetic patients
at king Abdulaziz Medical City (KAMC), KSA, and (ii) to
determine the significant predictors of QOL and GC.
Methods. A cross sectional survey was conducted to
assess the Qol and glycemic control in 420 Saudi adult
diabetics at outpatient clinics of KAMC using a previously
validated Arabic version of Diabetes QoL Brief Clinical
Inventory. Personal characteristics (age, gender, education,
occupation, etc.), disease characteristics (age at onset,
duration, type of diabetes, treatment regimen,
complications) and lifestyle characteristics (dietary habits,
smoking behavior, exercising) were obtained. Medical
chart data of the duration of diabetes, and most recent
HbA1c levels were extracted. Logistic regression analysis
was applied to identify the significant predictors of good
QOL. Significance limits were set at P <0.05.
Results. The overall percentage mean score of Qol was
74.1+11.6, with good Qol in 29.8% of all patients.
Diabetics reported lack of satisfaction of exercise (49.1%),
burden on family (31%), and sex-life (28%) due to
diabetes, and reported worry of : physical illness (31%),
bad night sleep (26%), pain by treatment (24%), and
limitation of career (22%) due to diabetes. After adjusting
for possible confounders, higher QOL score was
significantly associated with male gender
(t=3.26,p=0.001), treatment with oral pills (2.14, p=0.03),
healthy diet (t=2.63,p=0.009), physical inactivity
(t=2.28,p=0.023) and absence of diabetic complications
(t=3.47,p=0.001). Two-thirds (68.8%) of all patients
showed poor glycemic control (PGC). Presence of diabetic
complications was the only significant predictor of PGC
(OR=1.66, p=0.024).
Conclusion. Changing the lifestyle of Saudi diabetics is
necessary to improve their QOL. Avoidance of
complications is a safeguard against possible deterioration
in Qol and glycemic control. Future research on
transcultural aspects, and effects of lifestyle interventions
is recommended.
1. INTRODUCTION
Diabetes mellitus is a major public health problem
globally with an increasing disease trend. A total of 366
million (8.3%) people lived with diabetes in 2011 and 4.6
million deaths were attributed to diabetes[1]. The
incidence is estimated to increase to double the 2011 data
to 552 million in 2030[2], if no action is taken. The
diabetes epidemic is worse in developing Asian countries.
Asian people are at significant risk of diabetes in
comparison to western societies, because of their changing
life style and consumption of white rice[3]. The overall
prevalence of DM in the kingdom of Saudi Arabia is
23.7% among people with age between 30 and 70
years[4]. According to the global estimates of the
prevalence of diabetes for 2010 and 2030[5], 5 of the 10
world’s highest national prevalences occur in the Middle-
East, Saudi Arabia (18.7%) is one of these. Other
countries are UA Emirates (21.4%), Bahrain (17.3%),
Kuwait (16.9%) and Oman (14.9%).
Diabetes has a strong impact on the quality of life - which
is defined as a multidimensional concept that encompasses
the physical, emotional, social perception associated with
an illness or its treatment[6]. People with no chronic
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illness have a better quality of life (QOL) than people with
diabetes. Numerous demographic and psychosocial
determinants affect QOL such as medical factors such as;
treatment, complications, and duration and onset of
diabetes, and social factors like age and gender [7].
Complications of diabetes are the most important disease
specific determinant of QOL[7]. In terms of psychosocial
correlates, several studies have shown that social support,
self-care behaviors, acceptance of the disease, depression,
anxiety, social assistance, stress, sense of belonging, and
knowledge about diabetes were associated with QOL[8]-
[12].
The overall goal for the treatment of all diabetes is to
prevent acute and chronic complications, while preserving
a good quality of life for the patient. Thus, knowledge
concerning HRQoL in diabetic patients, as well as the
determinants of this, is crucial. Studies on QOL of diabetic
patients are numerous using a number of generic[13]-[15].
and disease-specific measures, such as DQOL
questionnaire[16]. The 15-item Diabetic QOL Brief
Clinical Inventory was recommended by Burroughs et
al.[17] to provide a total Health Related QOL score that
predicts self-reported diabetes care behaviors and
satisfaction with diabetes control as effectively as the full
version of the instrument. Thus, the aims of the present
study are (i) to assess the QOL and glycemic control (GC)
of diabetic patients in the outpatient clinic of King
Abdulaziz Medical City (KAMC), Riyadh, Saudi Arabia,
using this 15-item QOL brief version, as a quick screening
tool, and (ii) to determine the independent predictors of
QOL and GC in Saudi diabetics.
2. MATERIALS AND METHODS
2.1 Study design
This is an observational cross-sectional study of the QOL
and glycemic control of diabetic outpatients in the diabetes
clinics at King Abdulaziz Medical City, Riyadh, Saudi
Arabia.
2.2 Study setting
This study was conducted at King Abdulaziz Medical City
(KAMC), which is located in Riyadh, Kingdom of Saudi
Arabia. KAMC is a tertiary hospital with a 690-bed
capacity, including 25 beds for expected surgical
procedures and 132 beds for emergency admissions. King
Abdulaziz Medical City (KAMC) in Riyadh was
established in May 1983. Since then, it has continued
expanding, while providing services for a rapidly growing
patient population in all of its catchment areas. The
Department of Medicine is composed of eleven divisions
which provide specialized high-standard medical
care. One of these divisions is the endocrinology
department where diabetic clinic is the most important
outpatient clinics. The diabetic outpatient clinic has 3
consultants, and 4 health educators. The system of the
clinic is scheduled to 2 clinics a day, one in the morning
and the other is in the afternoon. The capacity of the clinic
is about 25 patients per clinic the study subjects were all
adult patients (ie, age 18 years or older) who visited the
KAMC diabetic clinics between July 16, 2010 and
October 15, 2010 who were willing to participate in the
study. Inclusion criteria were as follows; patients initially
diagnosed with diabetes mellitus by one of the consultant
endocrinologists and met the WHO criteria of diagnosis,
patients with stable disease without need for hospital
admission for 3 months prior to assessment, and those who
established disease for at least one year.
2.3 Sampling
The main goal of this study was to assess QoL in Saudi
Arabian patients with diabetes. Based on previous studies,
the expected prevalence of good QOL in these patients
was 20.7%[18]. Assuming a statistical significance level
of 5% and a margin of error of 4%, the estimated sample
size needed was 394 subjects. All of the patients attending
the KAMC diabetes clinics during the 3-month study
period who fulfilled the inclusion criteria and were willing
to participate in the study were enrolled in the study until
the required sample size was obtained. The questionnaire
takes about 10-15 minutes to be completed, so about 5-6
patients were interviewed in one hour according to the
clinic hours which is 4 hours for the morning clinic and 2
hours for the afternoon clinic. Thus, about 30 patients
were interviewed per day at random. systemic random
method of sampling was applied to include every 2nd
patient.
2.4 Data collection
1. QOL of adult diabetics. Following approval by
our institutional review board and informed verbal consent
from the patients, a previously validated and pretested
Arabic version of the QOL brief clinical inventory
questionnaire[17] was administered to measure the QOL
of diabetic patients. It contains questions that explains self
care behavior and satisfaction with diabetes control, that
combine a set of 15 questions that are related to type 1 or
type 2 diabetes[17]. It is simple and brief and focuses on
two domains, satisfaction domain (questions 18), and
worry domain (questions 915). For the satisfaction
domain, the patients responded to each question with
“very satisfied”, “moderately satisfied”, “neither”,
“moderately dissatisfied”, or “very satisfied”. For the
worry domain, the patients responded to each question
with “all the time”, “often”, “sometimes”, “very seldom”,
or “never”. A five-point Likert scale (from 0 to 4 points)
was used to score the questions. The scores for each
domain were summed over the patients, and the percent
score was calculated. A higher score reflects a better QOL
of the diabetic patient with the disease. The QOL range for
each domain and the overall QOL were categorized as
follows: poor QOL (<60%), moderate QOL (60%80%),
and good QOL (>80%).
2. Patient’s characteristics. These include age, sex,
education level completed, current employment and
marital status.
3. Disease characteristics. Data were collected on
age type of diabetes (T1DM & T2DM), age at onset,
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disease duration, type of medication, , glycemic control as
measured by HbA1c (controlled diabetes <8 and
uncontrolled diabetes >8), and complications. The major
types of microvascular complications such as retinopathy,
neuropathy, nephropathy, and foot and leg ulcer and major
types of macrovascular complications such as myocardial
infarction, heart failure, and stroke were based on a
patient’s self report- in addition to the review of patients
records. The distinction between co-morbidities and
complications of diabetes was based on medical records of
the patient. Exclusion criteria included obvious damage to
the brain or nervous system or any other concomitant
disease that could affect the functions of the nervous
system and independently affect reported or measured
QOL.
4. Healthy lifestyle habits (HLHs). This includes the
following: (a) Dietary habits: Consumption of 5 or more
servings of fruit and vegetable daily (FVC5) was
considered as healthy dietary habit, according to the
national objective in Healthy People 2010[19], (b)
Physical activity: physically active ( regular or irregular) or
non-active. Physical activity was assessed by asking
participants two questions: “ How many days per week do
you do moderate activities for at least 10 min at a time?”
and “ On days when you do moderate activities for at least
10 min at a time, how much total time per day do you
spend doing these activities?[20] (c) Smoking: regular
smoker/nonsmoker. Only daily and weekly smokers were
considered as regular smokers. Daily smokers were those
who, at the time of the survey, smoked cigarettes every
day. Weekly smokers were those who smoked less than
once a day but at least once a week. Physically active
adolescents were those who reported practicing exercise
more than one hour at least 3 times per week[21].
2.5 Ethical considerations
Participation in the study was completely voluntary. The
investigators explained the purpose of the research and
how the survey would be conducted. Each patient was able
to withdraw from the study at any time. Confidentiality
was maintained throughout the study, and the subjects
were assured that the results would be used only for the
stated scientific research purposes. The patients knew that
their responses would not be available to the dermatologist
and would not influence the treatment they received.
Approval by the institutional review board of the National
Guard Health Affairs was obtained before conducting the
study (RR010/041).
2.6 Data analysis
SPSS software (version 17.0, SPSS Inc, Chicago, IL) was
used for data analysis. The χ2 test was used to compare the
categorical data. The Student’s t-test was used to compare
the numerical data. Multiple regression analyses were used
to determine the significant predictors of the QoL scores
for each domain and for the overall score, and logestic
regression analysis was used to determine the significant
predictors of glycemic control. For all of the statistical
analyses, a P < 0.05 was considered to be statistically
significant.
3. RESULTS
The sample included 420 adult diabetics, of whom 192
(45.7%) were males and 228 (54.3%) were females. The
majority of diabetics were aged 40 years or more (83.6%),
married (94.3%)less than secondary educated (81.9%), and
not currently employed (85.47%). With regard to disease
characteristics, the majority of patients were of T2DM
(77.9%), with a mean duration of 10.36±8.34 years and
age of onset of 42.95±14.51 years. Diabetic complications
were prevalent in almost one-half (49.52%) of diabetics.
Retinopathy ranked first (42.7%), followed by
hyperlipidemia (8.7%), neuropathy (5.8%), renal problems
(4.9%), and diabetic foot (3.9%). Those with two or mor
complications constituted 24.3% of all diabetics with
complications. With regard to lifestyles, more than one-
half (57%) showed non-healthy dietary behaviours, 42%
were physically inactive and only 6.9% were current
smokers.
3.1. QoL of adults with diabetes and glycemic control
Table 1 shows the QoL of Saudi adults with diabetes by
sex and QoL domain. The percentage mean score of total
QoL for all diabetics was 74.1+11.6. This percentage
mean score was 74.4+13.5 and 73.8+15.8 for the
satisfaction and worry domains respectively. Patients with
a good total QoL constituted 29.8% of all diabetics. This
percentage was the same for the satisfaction and worry
domains (31.1%,). Male diabetic adults showed
significantly better QoL in all domains (P <0.05).
Diabetics reported lack of satisfaction of: exercise
(49.1%), burden on family (31%), and sex-life (28%) due
to diabetes, and reported worry of : physical illness (31%),
bad night sleep (26%), pain by treatment (24%), and
limitation of career (22%) due to diabetes.(Table 2)
Table 3 shows the glycemic control and QOL of adults
with diabetes by sex. About two-thirds (68.8%) of
diabetics had PGC according to the HbA1c level, and only
31.2% were controlled. However, this figure was
significantly higher for females than for males (36%
versus 25.5%, p=0.021). The mean score of HbA1c for all
adults with diabetes was 10.53±1.90, with statistically
significant sex difference (Z=2.32, p=0.021). There was
no significant association between glycemic control and
QOL scores (t=0.63, p=0.53).
3.2. Predictors of QoL and Qlycemic control
In the bivariate analysis (table 4), QoL was significantly
associated with sex (p=0.001), presence of complications
((p=0.001), type of treatment (p=0.003), dietary behavior
(p=0.004) and exercising ((p=0.0001). After adjustment
for all potential confounders (table 5), all these variables
remained as significant predictors of QoL. Poorer QoL
was significantly associated with male sex (P= 0.001),
presence of diabetic complications (p=0.001), treatment
with insulin injections (p=0.033), unhealthy dietary
behavior (p=0.009) and physical inactivity (p=0.023).
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With regard to glycemic control, in bivariate analysis
(table 4), it was significantly associated with gender
(p=0.04), age (p=0.001), current employment (p=0.017),
age at onset of diabetes (p=0.02), presence of
complications (p=0.007) and type of treatment (p=0.041).
However, after adjustment for all these significant
variables (table 5), presence of complications was the only
significant predictor of glycemic control. Diabetics with
complications were 1.7 more likely to have uncontrolled
diabetes (OR=1.66, p=0.024). Figure 1 shows that the Qol
mean score decrease significantly from 77.2% for those
with no unhealthy behavior to 75.5% among those with
one unhealthy behavior, with further decrease to 70.1%
and 60.5% among those with two and three unhealthy
behaviours respectively (F=11.63, p<0.001). Figure 2
shows that the QOL mean score decreased significantly
from 78.3% among regular exercisers to 76.2% and 70.9%
among irregular- and non-exercisers respectively
(F=13.82, p<0.001).
Table1.Distribution of Saudi adult diabetics according to the level of quality of life (QoL) in different domains by sex
Higher scores denote lower worry and higher satisfaction, and better total QoL
*: P-value < 0.05 significant
QoL Domains
Good Qol
N (%)
Average Qol
N (%)
Poor Qol
N (%)
%Mean score
+ SD
Total QoL
Male
Female
Total
76.1+10.8
72.5+12.0
74.1+11.6
χ2 = 13.622, p=0.001*
t=0.316, p=0.001*
Total Satisfaction
Male
Female
Total
74.4+13.5
76.5+11.2
72.6+14.9
χ2 = 12.164, p=0.002*
t= 3.05, p=0.001*
Total Worry
Male
Female
Total
75.6+13.9
72.3+16.05
73.8+15.8
χ2 = 3.910, p=0.142
t= 2.21, p=0.027*
Table2. Responses of Saudi adults with diabetes to the QOL brief clinical inventory questionnaire.
Satisfaction domain
Very
Satisfied
N (%)
Moderately
Satisfied
N (%)
Neither
N (%)
Moderately
dissatisfied
N (%)
Very
Dissatisfied
N (%)
1. How satisfied are you
with your current
diabetes treatment?
239 (56.9)*
115 (27.8)
14 (3.3)
41 (9.8)
11 (2.6)
2. How satisfied are you
with amount of time it
takes to manage your
diabetes?
191 (45.5)*
94 (22.4)
67 (16)
52 (12.4)
16 (3.8)
3. How satisfied are you
with the time it takes to
determine your sugar
level?
200 (47.6)*
115 (27.4)
30 (7.1)
61 (14.5)
14 (3.3)
4. How satisfied are you
with time you spend
exercising?
69 (16.4)*
76 (18.1)
69 (16.4)
141 (33.6)
65 (15.5)
5. How satisfied are you
with your sex life?
81 (19.3)*
46 (11.0)
176 (41.9)
76 (18.1)
41 (9.8)
6. How satisfied are you
with burden your
diabetes is placing on
150 (35.7)*
100 (23.8)
40 (9.5)
97 (23.1)
33 (7.9)
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*---denotes higher satisfaction and lower worry.
Table3. Distribution of Saudi adults with diabetes according to the glycemic control and QOL by sex.
Glycemic
control
Males
Females
Total
QOL % mean
Score
No.
%
No.
%
No.
%
Controlled
49
25.5
82
36.0
131
31.2
74.71±11.09
Uncontrolled
143
74.5
146
64.0
289
68.8
73.94±11.83
Total
192
100.0
228
100.0
420
100.0
74.10±11.60
X± SD
10.03±1.75
8.58±3.17
10.53±1.90
t=0.63, p=0.53
χ2=5.30 p= 0.021 t=2.32 p=0.021*
2---- Pearson Chi-squared test was applied.
t------ Student-t test was applied.
your family?
7. How satisfied are you
with the time spent
getting checkups for
diabetes?
239 (56.9)*
89 (21.2)
13 (3.1)
59 (14.0)
20 (4.8)
8. How satisfied are you
with your knowledge
about your diabetes?
191(45.5)*
117 (27.9)
16 (3.8)
71 (16.9)
25 (6.0)
Worry domain
Never
N (%)
Very
seldom
N (%)
Sometimes
N (%)
Often
N (%)
All the time
N (%)
9. How often do you find
that you eat something
you shouldn't rather than
tell someone that you
have diabetes?
164 (39.0)*
84 (20.0)
88 (21.0)
41 (9.8)
43 (10.2)
10. How often do you worry
about whether you will
miss work?
274 (65.2)*
34 (8.1)
59 (14.0)
25 (6.0)
28 (6.7)
11. How often do you have
a bad night's sleep
because of diabetes?
151 (36.0)*
39 (9.3)
119 (28.3)
62 (14.8)
49 (11.7)
12. How often do you feel
diabetes limits your
career?
185 (44.0)*
53 (12.6)
87 (20.7)
52 (12.4)
43 (10.2)
13. How often do you have
pain because of the
treatment for your
diabetes?
193 (46.0)*
49 (11.7)
77 (18.3)
58 (13.8)
43 (10.2)
14. 14) How often do you
physically ill?
66 (15.7)*
42 (10.0)
181 (43.1)
65 (15.5)
66 (15.7)
15. How often do you worry
about whether you will
pass out?
287 (68.3)*
30 (7.1)
52 (12.4)
18 (4.3)
33 (7.9)
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Table 4. Bivariate analysis for predictors of Glycemic control and Qol % mean score among Saudi Diabetics
N(%)
Quality of life
Glycemic control (HbA1c)
420 (100.00)
% mean score
( 74.17+11.59)
Controlled
131(31.19)
Uncontrolled
289(68.81)
OR
(95%CI)
[A] Personal Characteristics
Gender
Female
Male
228 (54.3)
192 (45.7)
72.52+12.00
76.13+10.79
82 (35.96)
49 (25.52)
146 (64.04)
143 (74.48)
1
1.63 (1.07-2.50)
t= -3.22, p=0.001*
χ2 =5.297, P=0.04*
Age group (yrs)
Less than 40
More than 40
69 (16.40)
351 (83.60)
73.66+11.76
74.27+11.57
33 (47.82)
98 (27.92)
36 (52.18)
253 (72.08)
1
2.36(1.39-4.00)
t=-0.404, p=0.686
χ2 =10.646, P=0.001*
Educational
level
Secondary
&above
Under
secondary
76 (18.10)
344 (81.90)
73.71+12.53
74.27+11.39
27 (35.52)
104(30.23)
49 (64.48)
240 (69.77)
1
1.27( 0.74-2.13)
t=0.381, p=0.704
χ2 =0.813, p=0.367
Marital Status
Single
Married
24 (5.70)
344 (94.30)
73.44+12.25
74.67+11.52
27 (35.52)
104(30.23)
49 (64.48)
240 (69.77)
1
1.27(0.75-2.14)
t=-0.504, p=0.615
χ2 = 0.813, p= 0.367
Current
employment
Employed
Non employed
61 (14.53)
359 (85.47)
73.42+11.51
74.30+11.61
27 (44.26)
104 (28.96)
34 (55.74)
255 (71.04)
1
1.94 ( 1.11- 3.38)
t=0.551, p=0.582
χ2 =5.68, p=0.017*
[B] Disease Characteristics
Type of
Diabetes
DM II
DM I
327 (77.90)
93 (22.10)
73.92+11.51
75.05+11.87
102(31.19)
29 (31.18)
225 (68.81)
64 (68.82)
1
1(0.60-1.64)
t=0.825, p=0.410
χ2 =0.0001, p=0.999
Age at
onset(yrs)
<20
20 to 40
Above 40
34 (8.10)
136 (32.10)
250 (59.80)
72.27+13.49
72.72+11.89
75.22+11.07
13 (38.20)
53 (39.00)
65 (26.00)
21 (61.80)
83 (61.00)
185 (74.00
1
0.96 (0.44-2.10)
1.76 (0.83-3.71)
F=2.567, p=0.078
χ2 =7.760, p=0.021*
Complications
No
Yes
212 (50.48)
208 (49.52)
76.07+12.00
72.24+10.85
79(37.26)
52(25.00)
133(62.74)
156(75.00)
1
1.78(1.17-2.71)
t=3.430, p=0.001*
χ2 =7.358, p=0.007*
Type of
treatment
Insulin only
Pills only
Diet
Insulin & pills
139 (33.00)
227 (54.20)
19 (4.50)
35 (8.30)
73.42+12.05
75.58+10.90
74.38+11.46
67.92+12.24
54 (38.80)
67 (29.50)
4 (21.10)
6 (17.10)
85 (61.20)
160 (70.50)
15 (79.90)
29 (82.90)
1
1.51 (0.97-2.36)
2.38 (0.75-7.55)
3.07 (1.19-7.88)
F=4.830, p=0.003*
χ2 =8.223, p=0.042*
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*---denotes significance at p<0.05
Table 5. Significant predictors of Qol percentage mean scores and Glycemic control
@---Multiple linear regression analysis was applied. B---- Logistic regression analysis was applied.
aOR--- adjusted odds ratio, SE--- standard error, *----Statistical significance.
[C] Lifestyle Characteristics
Smoking
Non smoker
Smoker
391 (93.10)
29 (6.90)
74.32+11.36
72.13+14.45
124(31.71)
7 (24.13)
267 (68.29)
22 (75.87)
1
1.46 ( 0.60- 3.50)
t=-0.982, p=0.327
χ2 =0.722, p=0.396
Diet
Healthy
Non healthy
180 (42.85)
240 (57.15)
76.05+11.21
72.77+11.69
63 (35.00)
68 (28.33)
117 (65.00)
172 (71.67)
1
1.36( 0.89- 2.06)
t= 2.894, p=0.004*
χ2 =2.130, p=0.144
Exercising
None
Irregular
Regular
179 (42.61)
200 (47.61)
41 (9.79)
63.6±14.8
70.2±13.7
72.7±12.9
52 (29.3)
67 (33.5)
12 (29.3)
127 (70.9)
133 (66.5)
29 (70.7)
1
0.81 (0.52-1.25)
0.98 (0.46-2.08)
F=13.13,,p=0.0001*
χ2=0.950 , p=0.6224
Total Quality of life (Score)@
Glycemic controlB
Beta
S.E.
t-value
adjP-
value
Beta
S.E.
adj P-
value
aOR (95% CI)
Gender
Female 0
Male 1
3.683
1.129
3.263
0.001*
0.411
0.228
0.072
1.50 (0.97 -2.36)
Age (yrs)
less 40 yrs 0
more than 401
-1.027
1.801
-0.570
0.569
0.374
0.339
0.271
1.45 (0.75 -2.83)
Employment
Nonemployed 0
Employed 1
-0.454
1.657
-0.274
0.784
-0.408
0.314
0.194
0.66 (0.36 -1.23)
Age of onset (yrs)
Less than 40 0
Above 40 1
1.493
1.386
1.077
0.282
0.237
0.276
0.392
1.3 (0.74 -2.18)
Complications
No 0
Yes 1
-3.862
1.113
-3.471
0.001*
0.507
0.225
0.024*
1.7 (1.07 -2.58)
Treatment type
Oral (pills) 0
Insulin (injections)1
-2.596
1.212
-2.142
0.033*
-0.103
0.244
0.673
0.90 (0.56-1.46)
Diet
Not follow diet 0
Follow diet 1
2.894
1.103
2.625
0.009*
-0.346
0.221
0.117
0.71 (0.46 -1.09)
Exercising
No 0
Yes 1
4.184
1.839
2.275
0.023*
0.201
0.372
0.588
1.22 (0.59 -2.53)
Constant
73.869
1.767
41.802
<0.00001
0.177
0.335
0.598
1.193
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Figure1 QOL mean score according to number of unhealthy behaviours among Saudi adult diabetics
Figure 2. Qol mean score according to level of physical activity among Saidi adult diabetics
4. DISCUSSION
In evaluating outcomes of diabetes care, it is essential to
assess the impact of diabetes on QOL. It informs us not
only about the patients’ experience of living with the
condition, but also shows us ways in which we could
improve diabetes care. If QOL is made a target of clinical
and research efforts and seen as at least as important as the
target of improved health, we are more likely to achieve
both[22]. In this study of the QOL and its determinants in
diabetic adults in central Saudi Arabia, we found that the
mean total QOL score was 74.1%+11.6%. This figure is
similar to that from a study conducted by Abdel-Gawad
(75.36%)[23] in Riyadh, Saudi Arabia, who reported an
overall QOL of mild to moderate range. It was higher than
figures of 36.7% and 34.8% for physical and
psychological domains in a study of diabetic refugees in
the Gaza strip[24].Good quality of life in the present study
was reported by around 30% of all diabetics, a figure that
is similar to that reported by diabetics in A Nigerian
teaching hospital (20.7%)[18]. However, It is difficult to
compare results from different questionnaires, as these are
presented in different ways.
66
68
70
72
74
76
78
80
none irrigular exercise regular exercise
70.86
76.2
78.34
Total QOL %
mean score
Level of Physical Activity
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Numerous demographic and psychosocial determinants
affect QOL of diabetics. Some demographic variables
associated with quality of life in people with diabetes
parallel those in the general population. Specifically, men
seem to report better quality of life than women;
increasing age seems to be associated with decrements in
some domains of functioning and well-being; and those
with more education or income generally report better
quality of life than those who have less of either of these
attributes[24]. In the present study, women with diabetes
appeared to have worse QOL and mental well-being
compared with men with diabetes. Meanwhile, poor
glycemic control (PGC) was more prevalent in men than
in women (74% vs 64%) - This finding was in agreement
with the finding of a previous studies[24]-[27]. Whereas
this finding could be partly explained by the worse
situation of female patients in respect to the disease in our
sample, this may be a reflection of gender inequalities[24].
This underlines the burden of disease on women and the
importance of diabetes prevention. Factors that
disadvantage women with Type 2 diabetes need to be
researched more thoroughly. Therefore, identifying
strategies to improve QoL among diabetic patients,
especially among women, is of great importance.
Lifestyle and behavioral factors have been less
emphasized in the diabetic population than in the general
population. However, the prevalence of lifestyle and
behavioral factors seems to be different in the diabetic
population from that in the general population in that
people with diabetes have a lower prevalence of smoking
but a higher prevalence of physical inactivity compared to
those without diabetes[28][29]. In the present study, QOL
of diabetics was significantly associated with physical
inactivity and unhealthy diet but not with smoking. This
might be attributed to the low prevalence of smoking
among the study sample. In addition, several studies
reported that a higher level of physical activity was related
to increased vigor and physical functioning [8][10][30]. In
the present study, a significant correlation between QOL
score and the level of exercising was detected, with the
lowest score among non-exercisers and the highest among
regular exercisers. One study found that current smoking
was associated with decreased mental health[31].
(Camacho et al.,2002). Furthermore, Li et al[28] showed
that the accumulation of multiple healthy lifestyle habits
was significantly associated with increased QOL. In the
present study, a significant positive association was
detected between the QOL score and the number of
unhealthy habits, with the lowest score among those with
three unhealthy behaviours, and highest score among those
without any of these unhealthy behaviours.
Diabetes is a major contributing factor for overall health
status, morbidity, mortality and QoL[32]. Uncontrolled
diabetes increases the number of serious health problems
such as heart attack, stroke, blindness, kidney and
peripheral blood vessel disease. Diabetes leads to a high
risk of kidney disease[33], pneumonia[34], heart disease,
high blood pressure and a higher death rate occurs in
diabetes patients than non-diabetic patients[32]. All these
health conditions result in reduced QOL. In the present
study, diabetic complications were prevalent in almost
one-half (49.52%) of diabetics, Retinopathy ranked first
(42.7%), followed by hyperlipedimia (8.7%), neuropathy
(5.8%), renal problems (4.9%), and diabetic foot (3.9%).
Those with two or mor complications constituted 24.3% of
all diabetics with complications.
The strongest correlates of HRQOL found in all reviewed
studies are diabetic complications[20]. In a review of 19
articles from Finland and Sweden on health-related quality
of life (HRQoL)[7], macrovascular diseases, especially
coronary heart disease, and non-vascular diseases were
reported as the most consistently found and strongest
predictors of poor QOL among diabetics. In the present
study, the presence of complications was a significant
predictor of both QOL and glycemic control, even after
controlling for all significant variables in bivariate
analyses. Patients with diabetic complications were 66%
more likely to have PGC as compared to those with no
complications. Our understanding of the pathophysiology
of diabetes--particularly, the dysmetabolic changes seen in
type 2 diabetes--includes abnormalities in lipid
metabolism, fuel flux, and endothelial function. Diabetes
control, therefore, can no longer be viewed exclusively as
glucose management. Rather, a more global approach is
necessary to minimize risks of both microvascular and
macrovascular complications[35].
Results of research on the association between treatment
regimen and quality of life in people with diabetes are
mixed, It has been reported [36] that patients taking oral
medications had more QOL-assessed diabetes-related
worries than those controlling their diabetes with diet and
exercise only, and that those taking insulin reported less.
QOL assessed satisfaction with treatment and more burden
of illness than those taking oral blood-glucose-lowering
medication or none at al[37][38]. This was in agreement
with the findings of the present study, where poor QOL
was significantly associated with insulin therapy, even
after controlling for all possible confounders. QOL score
was highest among those who were on diet only or on oral
medications, while it was lower among those on insulin
alone , with further reduction among those on combined
insulin and oral therapy. It has been reported that Insulin
treatment increased the perception of disease severity[39].
5. LIMITATIONS
Our study has some limitations. First, because we
analyzed self-reported measures of healthy lifestyle habits,
recall bias may be present. Second, because our study was
cross-sectional, we cannot establish a temporal
relationship between exposure and outcome. It is clear that
the true causal relationships among all of the identified
variables are complex and often reciprocal, For example,
quality of life may affect lifestyle habits and behavior,
glycemic control and complications, just as each of these
latter variables may affect each other and quality of life.
Third, the association of QOL and GC with their correlates
under the present study might be confounded by some
other correlates such as; body composition and obesity,
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patient’s knowledge about diabetes and psychosocial
factors as social support and self-care behaviours and
others[8]-[12]. Lastly, complications were identified based
on self report- in addition to the review of patients’
records, which could have affected the validity of results
due to the possible recall bias. However, in most of the
studies reviewed, the major types of microvascular
complication such as retinopathy, neuropathy,
nephropathy, and foot and leg ulcer and major types of
macrovascular complications such as myocardial
infarction, heart failure, and stroke were based on a
patient’s self-report[20].
6. CONCLUSION
QOL of diabetics was significantly associated with
physical inactivity and unhealthy diet but not with
smoking. To benefit from recent advances, patients with
diabetes must understand the treatment goals and strive to
attain not only excellent glycemic control, but also healthy
lifestyle behaviours such as; dietary habits and physical
exercise. Education intervention for diabetes could be a
safeguard against possible deterioration in QOL and
glycemic control over time[40]. The accumulation of
multiple healthy lifestyle habits was significantly
associated with increased QOL. Thus, future research
should control for or explicitly assess the effects of
multiple factors and not simply ignore them or treat them
as an undesirable source of variance.
Healthy life style may best be achieved through public
private partnerships involving government, partners
organizations, health services providers, community and
people living with diabetes. Effective strategies to reduce
the incidence of diabetes globally and assist in managing
the disease are urgently required.
Complications appear to be the most influential correlates
for QOL and the only independent predictor of glycemic
control.. Therefore, early intervention strategies aimed at
preventing or delaying the occurrence of these diabetes-
related complications may lead to the improvement of
QOL.
Poor QOL was significantly associated with insulin
therapy, even after controlling for all possible
confounders. QOL score was highest among those who
were on diet only or on oral medications, while it was
lower among those on insulin alone, with further reduction
among those on combined insulin and oral therapy. This
issue needs to be considered when shifting the patient to
insulin therapy.
Women with diabetes appeared to have worse QoL
compared with men with diabetes Future research should
focus attention on gender-specific approaches to
healthcare delivery to improve quality and access to care.
Identifying strategies to improve QoL among diabetic
patients, especially among women, is of great importance.
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... As the quality of life is specific and limits to psychological factors, expectations of discontent, indignation and civil disobedience are increased, but also emerge social skills such as creativity and innovation of minority groups against ideological or pragmatic imposition of the majority ( Abolfotouh et al., 2013). ...
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Resumen: este trabajo se propuso establecer un modelo correlativo para discutir la importancia de otras variables en la investigación de la calidad de vida. Una vez que se especificaron las relaciones entre los factores derivados de la revisión de la literatura. Se realizó un estudio de corte transversal con una muestra no probabilística de 245 estudiantes. Cuando se obtuvo la validez y confiabilidad del instrumento medido: satisfacción con la vida, capacidades esperadas, expectativas de oportunidad, relaciones de confianza, percepción de la justicia, evaluación del entorno, estándares de contexto y recursos percibidos, se probó un modelo estructural en el que se evaluó Disponibilidad de recursos correlacionados indirectamente con la satisfacción con la vida a través del contexto de estándares. Los resultados fueron comparados con los hallazgos reportados en el estado de conocimiento. Palabras clave: calidad de vida, satisfacción con la vida, normas grupales, disponibilidad de recursos, capacidades percibidas. Abstract-This work was proposed to establish a correlative model to discuss the importance of other variables in the investigation of the quality of life. Once the relationships between the factors derived from the literature review were specified, it conducted a cross sectional study with a non-probabilistic sample of 245 students. When the validity and reliability of the instrument measured was obtained: life satisfaction, expected capabilities, expectations of opportunity, trust relationships, perception of justice, assessment of the environment, standards of context and perceived resources, a structural model was tested in which the perceived availability of resources indirectly correlated to life satisfaction through standards context. The results were compared with findings reported in the state of knowledge. Keywords-Quality of life, life satisfaction, group norms, availability of resources, perceived capabilities. Resumo-Este trabalho foi proposto para estabelecer um modelo correlativo para discutir a importância de outras variáveis na investigação da qualidade de vida. Estabelecidas as relações entre os fatores derivados da revisão da literatura, realizou-se um estudo transversal com uma amostra não probabilística de 245 estudantes. Quando se obteve a validade e confiabilidade do instrumento medido: satisfação com a vida, capacidades esperadas, expectativas de oportunidade, relações de confiança, percepção de justiça, avaliação do ambiente, padrões de contexto e recursos percebidos, testou-se um modelo estrutural em que a percepção disponibilidade de recursos indiretamente correlacionados à satisfação com a vida através do contexto dos padrões. Os resultados foram comparados com os achados relatados no estado do conhecimento.
... Wändell [27] in his study found that poor glycemic control (HbA1c>7%) was only associated with impaired cognitive function but not the other components of quality of life in the elderly diabetic patients compared to the patients with good control (HbA1c<7%). Abolfotouh et al. [28] found no significant association between glycemic control and QoL scores. Moreover, as QoL is a subjective measure, and indeed Choi et al. [29] found that in diabetic patient's subjective factors such as depressive symptom and psychological stress affected HRQoL, but objective factors related to diabetic status did not appear to affect HRQoL. ...
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Objective This study aimed to determine the impact of hypoglycemia on health-related quality of life from a patient perspective. Materials and Methods A cross-sectional study was conducted in 164 type 2 diabetes patients admitted due to severe hypoglycemia from August 2015 to October 2016 at Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders, in Dhaka. Impact of severe hypoglycemia on health-related quality of life in diabetic patients was evaluated using the disease-specific questionnaire audit of diabetes-dependent quality of life-19 (ADDQOL-19). Results The median ADDQOL score was calculated at −3.31. Totally, 88 (53.7%) patients reported an ADDQOL score of − 3.31 or more, and 76 (46.3%) patients had an ADDQOL score of less than −3.31 (lower quality of life [QoL]). After considering weighting, “Freedom to eat” (mean Weighted Impact Score-6.32 ± 1.94) was the most and “Holidays” (mean Weighted Impact Score-0.96 ± 0.19) was the least affected QoL domains, respectively. In multivariate logistic regression analysis, severe hypoglycemia impact on ADDQOL was related with age (odds ratio [OR] 0.932, 95% confidence intervals [CIs] 0.897–0.969, P < 0.001), sex (OR 0.088, 95% CIs 0.023–0.338, P < 0.001), glycated hemoglobin (%) (OR 0.613, 95% CIs 0.422–0.890, P = 0.010), and marital status (OR 9.264, 95% CIs 2.467–34.790, P = 0.001). Conclusions The results of this analysis suggest hypoglycemia impacts heavily on the well-being and quality of life of people with diabetes, and every effort should be made to minimize hypoglycemia while aiming for good glycemic control.
... As the quality of life is specific and limits to psychological factors, expectations of discontent, indignation and civil disobedience are increased, but also emerge social skills such as creativity and innovation of minority groups against ideological or pragmatic imposition of the majority ( Abolfotouh et al., 2013). ...
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This work was proposed to establish a correlative model to discuss the importance of other variables in the investigation of the quality of life. Once the relationships between the factors derived from the literature review were specified, it conducted a cross sectional study with a non - probabilistic sample of 245 students. When the validity and reliability of the instrument measured was obtained: life satisfaction, expected capabilities, expectations of opportunity, trust relationships, perception of justice, assessment of the environment, standards of context and perceived resources, a structural model was tested [X 2 = 12,35 (12 gl); p = 0.000; GFI = 0.975; RMR = 0.000] in which the perceived availability of resources indirectly correlated to life satisfaction through standards context (γ = 0.52). The results were compared with findings reported in the state of knowledge
... Es el caso de los nuevos movimientos sociales lésbico-gay o ecologistas, los cuales al formar grupos de auto-ayuda, generan un bienestar subjetivo mayor a quienes sólo perciben abundancia de recursos (Aristegui y Vázquez, 2013). A medida que la calidad de vida se específica y delimita a factores psicológicos, se incrementan las expectativas de inconformidad, indignación y desobediencia civil, pero también afloran habilidades sociales como la creatividad e innovación de grupos minoritarios, frente a la imposición ideológica o pragmática de las mayorías (Abolfotouh et al, 2013). En síntesis, la calidad de vida en términos económicos, políticos, sociales, sanitarios, educativos, laborales y tecnológicos es un constructo multidimensional (Quiceno y Vinaccia, 2013) ...
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Es indudable la importancia de la gobernanza, sobre todo por la evidente crisis (económica, política, social, de valores; notoria corrupción de la clase política, violencia e inseguridad, etc.). Frente a ello, una de las evidentes alternativas es la gobernanza.
Article
This work was proposed to establish a correlative model to discuss the importance of other variables in the investigation of the quality of life. Once the relationship between the factors derived from the literature review were specified, a cross-sectional study was carried out with a nonrandom sample of 245 students. When the validity and reliability of the instrument measured was obtained: life satisfaction, expected capacities, expectations of opportunity, trust relationships, perceptions of fairness, valuing the environment, rules of context and perceived resources, a structural model was contrasted [X² = 12,35 (12 gl) p = 0.000; GFI = 0.975; RMR = 0.000] in which the perceived availability of resources indirectly correlated to life satisfaction through context rules (γ = 0.52). The results were compared with the findings reported in the state of knowledge.
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Resumen La calidad de vida ha sido abordada desde aproximaciones socioeconómicas que resaltan sus dimen-siones de bienestar y capacidad como dos ejes preponderantes de discusión teórica y conceptual. Em-pero, desde una visión más psicosocial, el presente trabajo estableció la confiabilidad y validez de un instrumento que midió ocho factores indicativos de la dimensión sociopolítica de la calidad de vida. Para tal propósito, se llevó a cabo un estudio transversal con una muestra no probabilística de 245 estudiantes. Por consiguiente, satisfacción de vida (alfa = 0,72; 45% de la varianza explicada), capaci-dades esperadas (alfa = 0,74; 37%), relaciones de confianza (alfa = 0,79; 33%), percepción de justicia (alfa = 0,74; 31%), expectativas de oportunidad (alfa = 0,78; 27%), valoraciones del entorno (alfa = 0,75; 25%), normas de contexto (alfa = 0,71; 23%) y recursos percibidos (alfa = 0,75; 21%) fueron establecidos como factores indicativos de la dimensión sociopolítica de la calidad de vida [KMO = 6,25; chi cuadrada = 14,25 (23 gl) p = 0,000]. En relación con el estado del conocimiento que ha ponderado directamente la calidad de vida desde el bienestar subjetivo y las capacidades económicas, los hallazgos del presente trabajo fueron discutidos para explicitar un escenario de crisis económica y social ante el cual gobernantes y gobernados reaccionan asimétricamente. Palabras clave: calidad de vida, bienestar subjetivo, capacidades económicas, percepciones socia-les, dimensión sociopolítica.
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Diabetes mellitus (DM) is a major public health problem worldwide, and it is a known risk factor for coronary artery disease (CAD). New recommendations for the diagnosis of diabetes have changed the epidemiology of DM. Therefore, we designed this study with the objective to determine the prevalence of DM among Saudis of both sexes, between the ages of 30-70-years in rural as well as urban communities. This work is part of a major national project: Coronary Artery Disease in Saudis study (CADISS) that is designed to look at CAD and its risk factors in Saudi population. This study is a community-based national epidemiological health survey, conducted by examining Saudi subjects in the age group of 30-70-years of selected households over a 5-year period between 1995 and 2000. Data were obtained from history, fasting plasma glucose levels, and body mass index. The data were analyzed to classify individuals as diabetic, impaired fasting glucose and normal, using 1997 American Diabetes Association (ADA) criteria, which was adopted by the World Health Organization (WHO) in 1998, to provide prevalence of DM in the Kingdom of Saudi Arabia (KSA). A total of 17232 Saudi subjects were selected in the study, and 16917 participated (98.2% response rate). Four thousand and four subjects (23.7%), out of 16917 were diagnosed to have DM. Thus, the overall prevalence of DM obtained from this study is 23.7% in KSA. The prevalence in males and females were 26.2% and 21.5% (p<0.00001). The calculated age-adjusted prevalence for Saudi population for the year 2000 is 21.9%. Diabetes mellitus was more prevalent among Saudis living in urban areas of 25.5% compared to rural Saudis of 19.5% (p<0.00001). Despite the readily available access to healthcare facilities in KSA, a large number of diabetics 1116 (27.9%) were unaware of having DM. The overall prevalence of DM in adults in KSA is 23.7%. A national prevention program at community level targeting high risk groups should be implemented sooner to prevent DM. We further recommend a longitudinal study to demonstrate the importance of modifying risk factors for the development of DM and reducing its prevalence in KSA.
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Objective. To design and test the reliability and validity of a brief, treatment-focused version of the Diabetes Quality of Life (DQOL) questionnaire for use with both type 1 and type 2 diabetes. Research design and methods. Questionnaire packets including the DQOL, measures of current diabetes self-care behaviors, and demographic and health characteristics were mailed to 1,080 adults with type 1 or type 2 diabetes. A total of 498 patients returned completed packets. A three-stage statistical process was used to understand the underlying structure of the DQOL and to identify items most predictive of self-care behaviors and satisfaction with diabetes control. Results. Principal components analysis, conducted on 26 items predictive of the main criteria, identified five key underlying factors. For each component, best subset regression analysis was conducted to identify nonredundant questions that best explained self-care behaviors and satisfaction with diabetes control. A combined set of 15 questions was reliable (alpha = 0.85) and valid, though several questions were more relevant to type 1 or type 2 diabetes. For patients with type 1 diabetes, the 15-item brief inventory was equally or more effective at predicting self-care behaviors (shortened scale R2 = 0.360; full scale R2 = 0.254) and satisfaction with diabetes control (shortened scale R2 = 0.562; full scale R2 = 0.580) than the original 60-item DQOL. For type 2 diabetic patients, only satisfaction with diabetes control was well-predicted, but the 15-item inventory accounted for as much variance as the original 60-item DQOL (shortened scale R2 = 0.513; full scale R2 = 0.492). Conclusions . The 15-item DQOL Brief Clinical Inventory provides a total health–related quality of life score that predicts self-reported diabetes care behaviors and satisfaction with diabetes control as effectively as the full version of the instrument. In addition, it provides a vehicle for quickly screening patients for readiness and specific treatment-related concerns. It takes about 10 minutes to administer and can be used to identify quality of life issues that might not arise during the typical patient-provider encounter.
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Objective: To assess the quality of life of patients with diabetes mellitus and to determine the clinical and sociodemographic factors that affect the quality of life of these patients. Patients and Methods: This was a cross-sectional study of 251 patients with diabetes mellitus attending the University of Ilorin Teaching Hospital, Nigeria. The World Health Organization quality of life instrument, short version and a sociodemographic questionnaire was adminis- tered to assess quality of life. Results: Most of the respondents performed fairly well on the World Health Organization quality of life instrument, short version. Poor quality of life was associated with some of the physical compli- cations of diabetes mellitus, lower income, lower educational status, and type 2 diabetes mellitus. Conclusions: Lower income, lower education, low-rated employment, and physical complica- tions adversely affect the quality of life of patients with diabetes mellitus. Such factors need to be addressed by caregivers and physicians managing these patients.
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The aim of this review is to examine diabetes and quality of life improvements through modifying life style. The data was collected by reviewing published articles from PubMed, Medline, Web of Science, and Google open access publications. The review identified prevention strategies can reduce the risk and complications of diabetes. Life style modification in relation to obesity, eating habit, and physical exercise can play a major role in the prevention of diabetes. Nowadays, there has been progress in the development of behavioural strategies to modify these life style habits and it is not easy to accept for long term basis. If people maintain a balanced diet and physical exercise this can have real and potential benefits for their prevention and control of complications from chronic diseases particularly for cardiovascular risk and diabetes. Healthy life style may best be achieved through public private partnerships involving government, partners organizations, health services providers, community and people living with diabetes. Effective strategies to reduce the incidence of diabetes globally and assist in managing the disease are urgently required.
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To assess quality of life (QoL) and glycemic control in adolescents with type 1 diabetes and to investigate the impact of an educational program. A quasiexperimental study with nonrandomized experimental and control groups was conducted in which a total of 503 adolescents with type 1 diabetes completed a questionnaire using the Diabetes Quality of Life Instrument for Youth. Adolescents were then assigned to experimental and control groups. The experimental group was subjected to four 120-minute sessions of an educational program over a period of 4 months. Extracted medical chart data included the duration of diabetes, insulin dosage, and most recent hemoglobin A1c levels. Analysis of covariance was used to detect the impact of intervention. The overall mean QoL score (%) was 76.51 ± 9.79, with good QoL in 38% of all adolescents. Poorer QoL was significantly associated with older age (P < 0.001), more hospital admissions in the last 6 months (P = 0.006), higher levels of depression (P < 0.001), poor self-esteem (P < 0.001), and poor self-efficacy (P < 0.001). There was significant deterioration in all domains of QoL in the experimental group after intervention. However, this deterioration was significantly less severe than in the control group. Between-group effects on total knowledge, adherence to exercise, glucose monitoring, treatment, self-efficacy, family contribution to management, glycemic control, and satisfaction with life were significantly in favor of the experimental group. Education intervention for adolescents with type 1 diabetes could be a safeguard against possible deterioration in QoL and glycemic control over time.
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The aim of this research was to characterize the experience of living with diabetes mellitus (DM) and identify patients' opinions of the quality of care received and the results of interventions. A descriptive, exploratory evaluation study using qualitative methodology was performed. Participants consisted of 40 adult patients diagnosed with DM and followed up in a public hospital in Barcelona, Spain. A semistructured interview and a focus group were used and a thematic content analysis was performed. Patients described DM as a disease that is difficult to control and that provokes lifestyle changes requiring effort and sacrifice. Insulin treatment increased the perception of disease severity. The most frequent and dreaded complication was hypoglycemia. The main problems perceived by patients affecting the quality of care were related to a disease-centered medical approach, lack of information, limited participation in decision-making, and the administrative and bureaucratic problems of the health care system. The bureaucratic circuits of the health care system impair patients' quality of life and perceived quality of care. Health professionals should foster patient participation in decision-making. However, this requires not only training and appropriate attitudes, but also adequate staffing and materials.
Chapter
The prevalence of diabetes has continued to rise in the Unites States. Diabetes has significant impact on health-related quality of life (HRQOL). Thus, improving HRQOL has been an important aspect of health care management in the diabetic population. In this chapter, we systematically reviewed 20 studies on the correlates of HRQOL in diabetes published between 1998 and 2008. Diabetes-related complications, older age, female sex, black or Native American race/ethnicity, longer duration of diabetes, insulin therapy, obesity, smoking, and physical inactivity are associated with the impairment of HRQOL in diabetes. Micro- and macro-vascular complications appear to be the strongest correlates of HRQOL. Therefore, intervention strategies aimed at preventing or delaying the occurrence of these complications may lead to improvement of HRQOL. Healthy lifestyle habits have been associated with improvement of HRQOL. Because people with diabetes are more likely to be non-smokers and to consume more fruits and vegetables but less likely to reach the recommended level of physical activity than those without diabetes, efforts are needed to promote the adoption of healthy lifestyle habits in order to improve HRQOL in diabetes. As an illustration, we provide updated prevalence estimates of impaired HRQOL among people with diabetes and demonstrate how the healthy lifestyle habits are associated with HRQOL using a large population-based sample.
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The Roka Listeria Detection Assay was compared to the reference culture methods for nine select foods and three select surfaces. The Roka method used Half-Fraser Broth for enrichment at 35 +/- 2 degrees C for 24-28 h. Comparison of Roka's method to reference methods requires an unpaired approach. Each method had a total of 545 samples inoculated with a Listeria strain. Each food and surface was inoculated with a different strain of Listeria at two different levels per method. For the dairy products (Brie cheese, whole milk, and ice cream), our method was compared to AOAC Official Method(SM) 993.12. For the ready-to-eat meats (deli chicken, cured ham, chicken salad, and hot dogs) and environmental surfaces (sealed concrete, stainless steel, and plastic), these samples were compared to the U.S. Department of Agriculture/Food Safety and Inspection Service-Microbiology Laboratory Guidebook (USDA/FSIS-MLG) method MLG 8.07. Cold-smoked salmon and romaine lettuce were compared to the U.S. Food and Drug Administration/Bacteriological Analytical Manual, Chapter 10 (FDA/BAM) method. Roka's method had 358 positives out of 545 total inoculated samples compared to 332 positive for the reference methods. Overall the probability of detection analysis of the results showed better or equivalent performance compared to the reference methods.
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Objective: This paper describes and examines conceptually relevant correlates of health-related quality of life (HRQL) in overweight or obese persons with type 2 diabetes. Research Design and Procedures: The investigation was a cross-sectional study of 5145 overweight or obese adults with type 2 diabetes between the ages of 45 and 74 years. Analyses examined the relationship that demographic characteristics, disease burden, and cardiovascular fitness had with HRQL: the Short Form 36 (SF-36) and the Beck Depression Inventory (BDI) II. Results: Means for the SF-36 physical component summary (PCS) scores, the mental component summary scores, and the BDI-II were as follows: 47.0, 54.0, and 5.7. Less desirable PCS scores were related to several comorbidities, insulin use, physical complaints, a high BMI, low metabolic equivalent (MET) capacity, and lower education. Interactions between categories of obesity and MET capacity revealed that greater BMI was related to lower PCS scores when individuals had lower MET capacities yet was absent for those individuals who had higher MET capacities. In addition, although greater BMI was associated with more severe depressive symptomatology, this association was the most dramatic for those with class III obesity who had low MET capacity. Discussion: Although participants in Look AHEAD had a favorable profile on the SF-36 and the BDI-II at baseline, lower PCS scores were related to disease severity and the presence of other comorbidities. More important, although the temporal ordering of associations cannot be determined in a cross-sectional design, the interactions between obesity class and MET capacity suggest that the adverse effect of BMI on PCS and BDI-II scores may be buffered by higher MET capacities.