Keywords
diabetes - middle–aged adults - cognitive functioning - well-being
Introduction
Diabetes is a chronic disease that occurs when the pancreas is no longer able to make
insulin or when the body cannot make good use of the insulin it produces. Over the
long term, the effects of diabetes mellitus include long-term harm, dysfunction, damage,
and failure of various organs and tissues.[1]
The impact of diabetes is not only on body organs, rather it also affects psychological
health. Stress reaction could be easily the most common psychological sequel upon
diagnosis of diabetes. However, in long term, the psychological consequences may manifest
in terms of anxiety and or depression. Anticipation of hypoglycemia is also a common
concern.[2]
[3] Also, the fear related to self-care behavior related to diabetes could enhance the
anxiety in the patients.[4] Comorbid conditions such as mental health disorders and diabetes are linked with
each other. Thomas Willis proposed the connection between the affective symptoms and
diabetes and how it is important to manage psychiatric conditions in patients with
diabetes.[5] Short- and long-term complications of psychiatric conditions negatively affect the
treatment adherence in diabetes.
Patients with diabetes mellitus have shown mild-to-moderate level of deficits in different
cognitive domains of varied degrees, specifically visuospatial abilities, motor speed,
attention, and psychomotor abilities, compared with nondiabetic individuals.[6]
[7]
[8]
[9] Type 2 diabetes has also been associated with decreases in executive function, verbal
memory, complex motor functioning, working memory immediate recall, delayed recall,
verbal fluency, visual retention, and attention.[10]
[11]
[12] It has been found that the prevalence of cognitive dysfunction is more in nontreated
patients of diabetes than treated patients. Several studies suggest that cognitive
dysfunction in diabetes is more prominent when the total duration of diabetes is 5
or more years. Studies suggest that long-term or chronic diabetes mostly impacts recent
memory, attention, and concentration, as compared with the control group.[13]
[14]
[15]
However, there are many contrasting studies in the literature in this domain and few
are from India. The middle-aged population, especially those above 50 years of age,
is already at risk of age-appropriate cognitive decline.[16] Identification of cognitive domains affected due to diabetes would help in formulating
a better diagnosis and intervention plan. With this background, this study explored
and compared the cognitive functioning and psychological well-being of middle-aged
adults with diabetes with healthy controls. The relationship between duration of illness,
cognitive functions, and psychological well-being of the patients was also explored.
Methods
Participants and Procedure
Purposive sampling was used for this study to explore cognitive functioning and psychological
well-being in middle-aged adults with diabetes. The total sample consisted of 60 middle-aged
adults of both sexes (including 30 diagnosed with diabetes and 30 healthy controls).
Inclusion criteria for the patients with diabetes (n = 30) were as follows: (1) within the age range of 40 to 60 years, (2) diagnosed
with diabetes type 2, (3) a minimum duration of 5 years or more after diagnosis, and
(4) minimum education level of eighth grade. Patients with a history of major psychiatric
illness or mood disorders prior to diagnosis of diabetes, any other major medical
illness, or neurologic disorder were excluded from the sample.
Inclusion criteria for the healthy controls (n = 30) were as follows: (1) healthy individuals of both sexes within the age range
of 40 to 60 years and (2) minimum education level of eighth grade. Any patient with
a history of psychiatric, medical, or neurologic disorders was excluded.
Data were collected from the outpatient department of specialty clinics and residential
areas of Kolkata. Informed consent was taken from participants.
Measures
Semistructured sociodemographic and clinical data sheet was used to obtain details
regarding age, sex, education level, occupation, and duration of illness.
Cognitive functions and psychological well-being of the sample was assessed using
the following tools:
-
Verbal Working Memory N Back Test: this 1 back and 2 back versions of Verbal Memory
N back test was used to assess verbal working memory of the sample. The verbal 1 N
back test requires verbal storage and rehearsal, whereas the 2 N back version requires
manipulation of information. The Indian norms[17] for the test were used.
-
Digit Symbol Substitution Test: this test was used to assess visuomotor coordination,
motor persistence, sustained attention, and response speed of the patients. The test
consists of four rows, with each row containing 25 blank squares. Each square is randomly
assigned a number from 1 to 9. A key of symbols corresponding to each number is provided
on the top of the sheet. Following a practice trial of seven squares, the patient
is required to fill in the blank spaces with the corresponding symbol as quickly as
possible. The Indian norms[17] for the test were used.
-
Trail Making Test[18]: this test is a reliable measure of visual attention and task switching. The test
can provide information regarding visual search speed, scanning, speed of processing,
mental flexibility, and executive functioning.
-
Stroop Test[19]: this test measures the ease with which a perceptual set can be shifted both to
conjoin demands and suppressing a habitual response in favor of an unusual one. In
this test, the color names “blue,” “green,” “red,” and “yellow” are printed in capital
letters on a paper. The color of the print occasionally corresponds with the color
designated by the word. The words are printed in 16 rows and 11 columns, and the patient
is required to name the “color” rather than the print word. Test–retest reliability
of the Stroop Test was assessed and the correlation of the Color-Word Scores from
the first and second administration was 0.90, suggesting a high degree of temporal
stability.
-
Psychological Well-Being Index[20]: The Psychological General Well-Being Index is a measure of the level of subjective
psychological well-being. It assesses self-representations of intrapersonal affective
or emotional states reflecting a sense of subjective well-being or distress and thus
captures what we could call a subjective perception of well-being. Consisting of 22
standardized items, the tool produces a single measure of psychological well-being
under six subscale domains: anxiety, depression, positive well-being, self-control,
general health, and vitality. Higher scores on the scale indicate a greater sense
of well-being.
Statistical Analysis
In this study, all the scales were scored and quantitative analysis was performed
through descriptive statistics. Student’s t-test was used to differentiate between the groups. Pearson’s correlation was used
to correlate between variables.
Results
Mean age of the participants in both groups was 52 years. Sexwise they were equally
distributed in healthy controls, with a slightly higher representation of females
in the diabetic group. Majority of the patients in both the groups were educated up
to graduation level. In-service and homemakers constituted majority of the sample
([Tables 1]
[2]).
Table 1
Sociodemographic details of the sample
|
With diabetes
|
Healthy controls
|
|
Age
|
Mean
|
SD
|
Mean
|
SD
|
|
52.76
|
7.19
|
52.07
|
6.9
|
|
N
|
Percent
|
N
|
Percent
|
|
Education
|
Graduate
|
19
|
63.33
|
22
|
73.3
|
|
Postgraduate
|
11
|
36.67
|
8
|
26.67
|
|
Sex
|
Male
|
14
|
46.67
|
15
|
50
|
|
Female
|
16
|
53.33
|
15
|
50
|
|
Occupation
|
Business
|
5
|
16.67
|
8
|
26.67
|
|
Service
|
12
|
40
|
10
|
33.33
|
|
Homemaker
|
13
|
43.33
|
12
|
40
|
Table 2
Difference between the groups on cognitive functions
|
Healthy controls
|
With diabetes
|
|
|
Mean
|
SD
|
Mean
|
SD
|
t-Value
|
p-Value
|
|
Abbreviations: DSST, Digit Symbol Substitution Test; SD, standard deviation; TMT,
Trail Making Test.
a
p < 0.01 level. b
p < 0.05 level.
|
|
Working memory (N back 1)
|
8.22
|
1.251
|
7.69
|
1.644
|
1.324
|
0.191
|
|
Working memory (N back 2)
|
6.33
|
2.019
|
5.77
|
1.773
|
1.079
|
0.564
|
|
Processing speed (DSST) (time)
|
251.56
|
91.723
|
350
|
161.872
|
–2.737
a
|
0.009
|
|
Attention (TMT 1) (time)
|
64.59
|
25.938
|
63.88
|
21.161
|
0.109
|
0.914
|
|
Attention (TMT 2) (time)
|
114.33
|
47.232
|
134.54
|
48.297
|
1.540
|
0.130
|
|
Response inhibition (Stroop effect)
|
107.67
|
6.171
|
99.50
|
16.384
|
2.419
b
|
0.019
|
The groups differed significantly in terms of processing speed and response inhibition,
with healthy controls having better performance on the variables compared with patients
with diabetes. No significant difference was found between the groups in domains of
working memory and attention though.
Comparison of psychological well-being of the groups yielded expected results, with
healthy controls having overall better psychological well-being compared with patients
with diabetes. Domainwise, healthy individuals had lower subjective anxiety and depression
levels compared with those with diabetes. Patients with diabetes had better self-control
though. No difference was found in the domain of general health.
Duration of illness was further analyzed for relationship if any with cognitive functions
and psychological well-being in patients with diabetes ([Table 3]). Duration of illness was found to have a significantly negative relationship with
response inhibition, indicating longer duration of illness to be related to poorer
response inhibition. It was similarly related to processing speed and working memory
functions in patients with diabetes.
Table 3
Relationship between cognitive functioning and psychological well-being with duration
of illness in subjects with diabetes
|
Cognitive functions
|
Duration of illness
|
|
p-Value
|
Significance
|
|
Abbreviations: DSST, Digit Symbol Substitution Test; SD, standard deviation; TMT,
Trail Making Test.
a
p < 0.01 level. b
p < 0.05 level.
|
|
Response inhibition (Stroop effect)
|
–0.695
a
|
0.000
|
|
Working memory (N back 1)
|
–0.130
|
0.494
|
|
Working memory (N back 2)
|
–0.503
a
|
0.005
|
|
Attention (TMT 1) (time)
|
0.254
|
0.175
|
|
Attention (TMT 2) (time)
|
0.344
|
0.063
|
|
Processing speed (DSST) (time)
|
–0.415
b
|
0.022
|
|
Processing speed (DSST) (error)
|
0.210
|
0.264
|
|
Psychological well-being
|
|
Positive well-being
|
–0.146
|
0.442
|
|
Self-control
|
0.089
|
0.64
|
|
Anxiety
|
0.361
b
|
0.050
|
|
Depression
|
–0.055
|
0.773
|
|
Vitality
|
0.122
|
0.521
|
|
General health
|
–0.063
|
0.742
|
In domains of psychological well-being, duration of illness was found to have a significant
relationship with subjective anxiety symptoms. Relationship with other subdomains
of psychological well-being was not significant.
Discussion
There was relatively a higher percentage of women with diabetes (53%) compared with
men (47%) in the sample. Conventionally, men are likely to have a higher prevalence
of diabetes type 2 compared with women.[21] Other risk factors associated with diabetes were beyond the scope of this study
and thus not explored.
The study findings suggest the healthy middle-aged controls had significantly better
response inhibition and processing speed compared with patients with diabetes. This
is in concurrence with the study by Ishizawa et al,[22] which also states that patients with type 2 diabetes show significantly decreased
response inhibition. Patients with diabetes are known to have complexities in visuomotor
coordination, motor persistence, sustained attention, and response speed. Visual-motor
integration, which is related to executive function in activities of daily living,
is demonstrated to be associated with diabetes in male older adults.[23]
[24]
[25]
The groups, however, did not differ in the domain of working memory. Available literature
has studies with different opinions on memory functions in diabetes, with some suggesting
a significant difference in memory functions in healthy individuals compared with
individuals with diabetes[26] and some suggesting no significant difference.[27] The difference though could be due to different methodology adopted by the studies.
Psychological well-being is a unique construct where quantification may vary depending
on subjective or objective perception. The assessment of well-being in this study
was subjective and based on a Psychological Well-Being Index, a self-rated scale,
and the results ([Table 4]) suggest that middle-aged adults with diabetes had poor psychological well-being
in domains of subjective anxiety and depression compared with healthy controls. This
is in concurrence with existing literature. It is suggested that due to poor glycemic
control complications in diabetes, anxiety symptoms are very prominent in patients
with diabetes.[28] Similarly, psychological burden of the illness, hypothalamic–pituitary–adrenal axis
activation, sleep disturbance, inactive lifestyle, poor dietary habits, and environmental
and cultural risk factors can lead to depressive symptoms in patients with diabetes.[29] The finding was shared with the consulting team of the patients for further psychological
intervention. However, the results also suggest a significant difference between the
groups of self-control and vitality domains of the psychological well-being. Adults
with diabetes were found to have higher self-control and vitality. This is in contrast
to previous studies,[30] which suggest that positive well-being, such as optimism, self-control, vitality,
positive affect, and gratitude, are low in patients with diabetes than normal controls.
Table 4
Difference between the groups on psychological well-being
|
Domains
|
Healthy controls
|
With diabetes
|
t-Value
|
|
Mean
|
SD
|
Mean
|
SD
|
|
Abbreviation: SD, standard deviation.
a
p < 0.01 level. b
p < 0.05 level.
|
|
Positive well-being
|
10.11
|
1.867
|
10.35
|
2.607
|
–0.378
|
|
Self-control
|
10.78
|
2.172
|
8.54
|
2.121
|
3.796
a
|
|
Anxiety
|
8.48
|
3.837
|
14.77
|
4.590
|
–5.419
a
|
|
Depression
|
5.63
|
2.420
|
9.27
|
2.765
|
–5.105
a
|
|
Vitality
|
12.26
|
1.318
|
9.62
|
2.021
|
5.661
a
|
|
General health
|
8.89
|
2.486
|
9.08
|
1.719
|
– 0.319
|
Vitality includes spiritedness, energy, and the state of being strong and active,
which was relatively less in healthy individuals. It is expected that the psychological
well-being of any individual with some morbid condition could be lower than disease-free
healthy individuals. However, the nature of illness may have a bearing on the subjective
well-being perception as well as resilience and coping of the individuals. It might
be a possibility that adults with diabetes engaged in a more structured and prescribed
health routine as they were under treatment and thus the possible reason of the finding.
Furthermore, a long duration of diabetes was found to have a significantly negative
impact on response inhibition, processing speed, and working memory of middle-aged
adults with diabetes ([Table 3]). Prior researches revealed that working memory, psychomotor and motor integration,
and inhibitory control are also very susceptible to the long-term effects of hypoglycemia
or diabetes mellitus.[31]
Duration of illness was related only to the anxiety domain of psychological well-being
in the patient sample. People with diabetes have a greater likelihood of developing
mental health problems such as anxiety. It is possible that biological changes induced
by diabetes alongside lifestyle limitations and feelings related to living with a
serious chronic illness could all be linked with anxiety symptoms.[32]
It could be concluded that middle-aged adults with diabetes significantly differ than
healthy individuals in cognitive functions of response inhibition and processing speed.
No difference was found in working memory and attention though. Psychological well-being
in middle-aged adults with diabetes was lower in terms of subjective anxiety and depression
only. Adults with diabetes were found to have better self-control in the study. Overall,
the presence of chronic illness such as diabetes has a detrimental impact on patients’
cognitive functioning and psychological well-being in general. The implications of
the study lies in the understanding of cognitive functioning of the middle-aged patients
and how it differs from healthy controls and possible inclusion of appropriate cognitive
rehabilitation programs and psychotherapeutic interventions for the affected domains.
