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Advances in Aging Research, 2014, 3, 142-151
Published Online May 2014 in SciRes. http://www.scirp.org/journal/aar
http://dx.doi.org/10.4236/aar.2014.32022
How to cite this paper: Amer, M.S., et al. (2014) Relationship of Cognition, Depression and Anxiety to Glycemic Control in
Older Adults with Diabetes. Advances in Aging Research, 3, 142-151. http://dx.doi.org/10.4236/aar.2014.32022
Relationship of Cognition, Depression and
Anxiety to Glycemic Control in Older Adults
with Diabetes
Moatassem Salah Amer1, Tomader Taha Abdel Rahman1, Salma Mohamed Samir El Said1,
Nermien Naim Adly1*, Shaimaa Nabil Rohaiem1, Randa Abdel Wahab Reda2
1Geriatrics and Gerontology Department, Cairo, Egypt
2Clinical Pathology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt
Email: shooterof81@yahoo.com *nano2661978@yahoo.com
Received 5 April 2014; revised 5 May 2014; accepted 15 May 2014
Copyright © 2014 by authors and Scientific Research Publishing Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY).
http://creativecommons.org/licenses/by/4.0/
Abstract
Objective: This study aimed to assess the relationship of cognition, depression and anxiety to gly-
cemic control in elders with diabetes. DM is a chronic medical condition. Its control depends on
adherence to medical therapy and making decisions related to lifestyle changes. This decision
making capacity is affected by many factors including cognition and psychological status. Design:
It was a case control study. Setting: It was done in Ain Shams University Hospital inpatients and
DM outpatient clinic, Cairo, Egypt. Participants: Of the one hundred diabetic patients aged ≥ 60
years, 50 had Hemoglobin A1c (HbA1c) ≥ 7.5 (cases) and 50 had Hb A1c < 7.5 (controls). Mea-
surements: Cognition was assessed using minimental status examination (MMSE) test, Mattis Or-
ganic Mental Syndrome Screening Examination (MOMSSE) and Cambridge Cognitive Examination
(CAMCOG) test. Geriatric depression scale-15 (GDS-15) was performed for depression assessment,
while anxiety was assessed by DSM IV criteria. Laboratory investigations included: fasting blood
sugar (FBS), post-prandial blood sugar (PPBS), glycated haemoglobin (Hb A1c), low density lipo-
protein (LDL), high-density lipoprotein (HDL), total cholesterol, and triglycerides (TG). Results:
Significant difference was found between the two groups regarding scores of cognitive tests: MMSE
score (p = 0.004); below average (p = 0.02) and average scores (p = 0.05) of MOMSSE; CAMCOG
score (p = 0.015); and CAMCOG divided items score including orientation (p = 0.003), comprehen-
sion (p = 0.005), expression (p = 0.020), attention (p = 0.002), and abstraction (p = 0.008) as well
as depression screening scores (P = 0.002). Using Receiver Operating Characteristic, CAMCOG had
better sensitivity and MOMSSE had better specificity. Conclusion: Cognitive impairment was asso-
ciated with poor glycemic control, and impairment in attention and abstraction, related to execu-
tive function, functions were found to be associated with poor glycemic control. These functions
may be more needed in self management of DM and hence affected glycemic control. Depression
was associated with poor glycemic control but anxiety was not.
*
Corresponding author.
M. S. Amer et al.
143
Keywords
Diabetes Mellitus, Cognition, Depression, Anxiety, Hb A1c, Elders
1. Introduction
Diabetes mellitus (DM) is a group of metabolic diseases characterized by hyperglycemia. The chronic hypergly-
cemia of diabetes is associated with long-term damage, dysfunction, and failure of various organs, especially the
eyes, kidneys, nerves, heart, and blood vessels. Several pathogenic processes are involved in the development of
diabetes. These range from autoimmune destruction of the cells of the pancreas with consequent insulin defi-
ciency to abnormalities that result in resistance to insulin action. Impairment of insulin secretion and defects in
insulin action frequently coexist in the same patient, and it is often unclear which abnormality, if either alone, is
the primary cause of the hyperglycemia. Symptoms of marked hyperglycemia include polyuria, polydipsia,
weight loss, sometimes with polyphagia, and blurredvision. Susceptibility to certain infections may also accom-
pany chronic hyperglycemia. Acute, life-threatening consequences of uncontrolled diabetes are hyperglycemia
with ketoacidosis or the nonketotic hyperosmolar syndrome [1].
DM in older adults has become a major public health problem affecting an increasing number of individuals
worldwide. Glycemic control is an essential element of DM management. It is failed to be achieved or maintain-
ed by many older adults [2]. Effective glycemic control involves many steps including proper nutrition, regular
exercise, self monitoring of blood glucose, and medication management [3].
Previous studies have confirmed that both old age & DM are independently associated with an increased risk
of cognitive dysfunction; the risk is even greater for older adults with DM [4]. Cognitive deficits in areas of
psychomotor efficiency, global cognition, episodic memory, semantic memory, and working memory were no-
ted in both young and older patients with DM [5]. Abnormalities in executive functions, including problem sol-
ving, planning, organization, insight, reasoning, and attention, were noted in diabetics [6]. Diabetic patients are
expected to suffer from difficulty in managing their disease due to cognitive dysfunction [6].
Not only cognitive dysfunction, but also previous studies reported significant association between psychiatric
illnesses and poor glycemic control. Data on the relation between depression and anxiety and glycemic control
in diabetic elderly patients are scarce. Depression comorbidity with DM has many hazards as it is a risk factor
for poor metabolic control, decreased physical activity, and potentially more complications and functional im-
pairment [7].
In addition, some authors suggest that anxiety comorbidity with DM has been associated with poor glycemic
control, regimen adherence, and with accelerated rates of coronary heart disease [8].
Therefore, the aim of the current study was to assess the relationship of cognition, depression and anxiety to
glycemic control in elders with diabetes.
2. Materials and Methods
2.1. Study Design and Setting
The study was a case control study. The study was carried out on diabetic elderly patients, aged 60 years or more,
visiting the geriatric hospital inpatient and DM outpatient clinic of Ain Shams University Hospital, Cairo, Egypt.
However, patients with impaired Minimental Status Examination (MMSE) screening test, with a score less than
24 [9], delerium or hypoglycemia were excluded. One hundred patients were included in this study; 50 had Hemo-
globin A1c (Hb A1c) ≥ 7.5 (cases) and 50 had Hb A1c < 7.5 (controls) [10]. Both cases and controls groups
were cross matched regarding age and gender. The research was conducted over the period from October 2011 to
October 2013. It was approved by the ethical Committee of Ain shams University. Informed written or oral con-
sent was taken from each participant and full confidentiality of the data collected was ensured to all participants.
2.2. Data Collection
All participants were subjected to complete medical history taking (including age, DM history, and history of
M. S. Amer et al.
144
other co-morbidities). Each patient then underwent cognitive assessment by MMSE [9], its validated Arabic
version was used [11], Mattis Organic Mental Syndrome screening Examination (MOMSSE) [12] and Cambri-
dge Cognitive Examination (CAMCOG) [13], using its Arabic version [14], tests. Assessment of depression was
done using geriatric depression scale-15 (GDS 15), normal GDS score is <5, [15] the Arabic version of the test
was applied [16]. Assessment of anxiety was done using DSM-IV criteria [17]. Functional assessment was done
by Activities of daily living (ADL) [18], Arabic version was used [19], and Instrumental activities of daily living
(IADL) [20].
2.3. Laboratory Investigations
Each patient was instructed to fast 12 hours, venous blood sample was drawn from each participant into potas-
sium EDTA tube; 5 ml was collected of venous blood by venipuncture. Serum was separated by centrifugation
and was divided into 2 samples:
The first sample was used for measurement of fasting blood sugar.
The second sample was frozen at −20˚C until assayed in the laboratory of clinical pathology department; Ain
Shams University, Faculty of medicine. Serum level of low density lipoprotein (LDL), high-density lipoprotein
(HDL), total cholesterol (TC), and triglycerides (TG) were measured by enzymatic hydrolysis and oxidation.
A third sample of 2 ml was withdrawn by venipuncture 2 hours after eating. Centrifugation was done and se-
rum was used for measurement of 2 hour postprandial blood sugar. Hb A1c was measured spectrophotometri-
cally at the central laboratories of Ain Shams university hospital using (Biosystem, BTS-330, S.A. Costa Brava,
Barcelona, Spain) spectrophotometer. Lipid profile was done in the central laboratory in Ain Shams University
teaching hospital.
2.4. Statistical Analysis
Data were collected and analytical statistics were done using the 16th version of statistical package for social
sciences (SPSS, Chicago, IL, USA). Qualitative data were presented in the form of frequency tables (number
and percent). Quantitative data were presented in the form of means and SD.
Normality distribution of the variables was tested using one sample Kolmogorov Smirnov test. Regarding
Quantitative data, differences between two groups were assessed using the Student’s t test for parametric data or
Mann Whitney U test for non-parametric data. Regarding qualitative data, the chi-square test or Fisher’s Exact
test was used to compare between the two groups.
Receiver operator curve (ROC) analysis was used to test the discriminatory power of anxiety, depression and
cognitive tests in prediction of uncontrolled DM, with calculation for sensitivity, specificity, positive predictive
value (PPV), and negative predictive value (NPV). MedCalc 9.6.2.0 package (MedCalc Software, Mariakerke,
East-Flanders, Belgium) was used to compare between area under the curves (AUCs) of cognitive tests for the
prediction of uncontrolled DM.
The level of significance was taken at P value < 0.05.
3. Results
The mean age of all participants was 67.12 ± 6.36 years, the mean duration of DM was 9.96 ± 6.9 years, and the
mean HbA1c was 8.2 ± 1.7. Forty four percent of participants were males. A significant difference was found
between ADL score, application of treatment, follow up status and glycemic control (p < 0.001 for all) (Table 1).
There was no significant difference between the two groups regarding age and education adjusted MMSE (p =
0.091), but a significant difference exits regarding CAMCOG, MOMSSE below average and average status, and
depression (p = 0.015, 0.02, 0.05, and 0.002 consecutively) but no significant relation was found regarding an-
xiety (p = 0.096) (Table 2). Table 3 showed significant difference between the two groups regarding orientation,
comprehension, expression, attention and abstraction items of CAMCOG (p = 0.003, 0.005, 0.020, 0.002 and
0.008 consecutively). By ROC curve, the discriminatory power of adjusted MMSE and anxiety in prediction of
uncontrolled DM was of poor accuracy (AUC = 0.58 and 0.57 consecutively), while other tests had AUCs > 0.60
(Table 4). Using MedCalc program to compare (AUCs) of MOMSSE versus CAMCOG revealed no significant
difference (P = 0.66). However, CAMCOG had better sensitivity and MOMSSE had better specificity.
M. S. Amer et al.
145
Table 1. Comparing studied groups as regard the age, gender, education, functional status and treatment status.
Variables
Controlled
Uncontrolled
P
Age
66.5 ± 5.6
67.7 ± 7
0.332
Male gender
25 (50%)
19 (38%)
0.227
Education
Illiterate
19 (38%)
24 (48%)
0.31
Below high school 11 (22%) 13 (26%) 0.63
High school 4 (8%) 1 (2%) 0.15
Above high school 16 (32%) 12 (24%) 0.33
Functional status
ADL 5.6 ± 1.4 4.1 ± 2.4 <0.001
IADL 7 ± 2.1 5.2 ± 3.2 0.001
Treatment
Duration of diagnosis of diabetes
*
9.8 ± 5.7 10.1 ± 7.9 0.818
Type of treatment Oral tab N(%) 28 (56%) 28 (56%) 0.548
Insulin 22 (44%) 25 (50%)
Application of treatment Self 47 (94%) 32 (64%) <0.001
Other person 3 (6%) 18 (36%)
Follow up status YES 40 (80%) 22 (44%) <0.001
No 10 (20%) 28 (56%)
Values were expressed in form of mean +/− SD for quantitative data and number (%) for qualitative data. ADL = activities of daily living, IADL =
instrumental activities of daily living.
Table 2. Comparing the studied groups as regard cognitive and psychological status.
Variables Controlled Uncontrolled P
Cognitive assessment
Adjusted MMSE score Not impaired 37 (74%) 29 (58%) 0.091
Impaired 13 (26%) 21 (42%)
CAMCOG 76.3 ± 18.1 66.7 ± 20.1 0.015
MOMSSE
Below average 10 (20%) 25 (50%) 0.02
Average 22 (44%) 13 (26%) 0.05
Above average 18 (36%) 12 (24%) 0.19
Psychological assessment
GDS15 (depressed) 7 (14) 21 (42) 0.002
Anxiety (anxious)
6 (10)
12 (24)
0.096
Laboratory results
HbA1c 6.9 ± 0.5 9.5 ± 1.5 <0.001
FBS 116.7 ± 32.9 167.4 ± 49 <0.001
PPBS 161.1 ± 46.9 230 ± 45.8 <0.001
TC 145 ± 44.3 182.4 ± 56.1 <0.001
TG 122.3 ± 47.8 150.4 ± 66.4 0.017
LDL 88.2 ± 34.6 125.9 ± 47.9 <0.001
HDL 34.1 ± 11.3 31.2 ± 14.0 0.264
Values were expressed in form of mean +/− SD for quantitative data and number (%) for qualitative data. CAMCOG = Cambridge Cognitive Exami-
nation; FBS = Fasting Blood Sugar; GDS 15 = Geriatric depression scale-15; HbA1c = Glycated Hemoglobin; HDL = High density lipoprotein; LDL
= Low density lipoprotein; MMSE = Minimental Status examination test; MOMSSE = Mattis Organic Mental Syndrome Screening Examination;
PPBS = Post Prandial Blood Sugar; TC = Total Cholesterol; TG = Triglycerides.
There was no significant association between education and follow up status (P = 0.052) (data were not pre-
sented).
M. S. Amer et al.
146
Table 3. Comparing studied groups as regard the CAMCOG divided items score.
CAMCOG
Groups
P-value
Controlled Uncontrolled
Mean
±
SD
Mean
±
SD
Orientation 9.5 ± 1.2 8.4 ± 2.0 0.003
Comprehension 7.8 ± 1.5 6.9 ± 1.6 0.005
Expression 14.1 ± 2.9 12.5 ± 3.7 0.020
Recall 8.6 ± 2.0 8.0 ± 2.2 0.177
Recent memory 2.8 ± 1.1 2.6 ± 1.4 0.604
Remote memory 3.7 ± 2.1 3.3 ± 2.0 0.303
Attention 5.8 ± 1.7 4.4 ± 2.6 0.002
Praxis 9.1 ± 2.8 8.0 ± 3.0 0.065
Calculation 1.9 ± 0.2 2.0 ± 0.0 0.320
Perception 8.4 ± 2.1 7.8 ± 2.3 0.184
Abstraction 4.2 ± 3.1 2.5 ± 3.3 0.008
Values were expressed in form of mean +/− SD; CAMCOG = Cambridge Cognitive Examination.
Table 4. Sensitivity, specificity, positive predictive value (PPV), negative predicative vale (NPV) and accuracy of depres-
sion, anxiety and cognitive tests (adjusted MMSE, MOMSSE, CAMCOG).
Sensitivity Specificity PPV NPV Accuracy (%)
Depression 42 86 75 59.72 64
Anxiety
---
----
----
----
57
MOMSSE 50 80 71.43 61.54 65
Adjusted MMSE --- --- --- --- 58
CAMCOG score 66 56 60 62.22 61
CAMCOG = Cambridge Cognitive Examination, MMSE = Minimental Status examination test; MOMSSE = Mattis Organic Mental Syndrome
Screening Examination.
4. Discussion
Current results showed that there was no significant differences between the two groups as regard the age,
gender or education. This was consistent with the findings of another study [21] which showed lack of relation-
ship between glycemic control and either age or gender.
On the other hand, this was not consistent with the findings of another study [22] which demonstrated that
poor glycemic control was least common among those aged ≥65 years (6.8%) and most common among adults
aged 18 - 39 years. They explained the sub-optimal glycemic control observed among young people by the pos-
sible reflection of less interaction with the health system among young people. In the current study the insignifi-
cant association between age and DM control could be attributed to the insignificant age difference between
both groups.
The absence of significant difference between both groups in education could be attributed to the insignificant
association between education and follow up status.
In the current work, comparison of the duration of DM diagnosis between the two groups was not significant.
This might be due to the difficulty of estimating DM duration, especially in older adults as patients usually have
longer duration of DM. DM is frequently diagnosed after a long period of its occurrence. The international DM
foundation overall estimates that, across all the surveys, approximately 50% of all people with DM were un-
diagnosed [23]. This implies that 50% of persons with DM are not diagnosed.
Regarding cognition, our study showed that there was no significant difference between the two groups as re-
gard the age and education adjusted MMSE total score. On the other hand, other batteries, CAMCOG and
MOMSSE which assess a wide range of mental abilities, for cognitive assessment showed significant difference
between the 2 groups.
There was a significant difference between the two groups as regard the MOMSSE below average and aver-
M. S. Amer et al.
147
age scores, as the below average score was more common in uncontrolled group, while the average score was
more common in the controlled group.
These findings are supported by the findings of van Harten, et al. [24] who show a negative relation between
HbA1C (chronic exposure to hyperglycemia) and cognition in Type 1 [25] and Type 2DM. Similarly Munshi, et
al. [6] have demonstrated an inverse relationship between HbAlc and executive functioning and complex psy-
chomotor performance in patients with Type 2DM.
Furthermore, our study showed that there was a highly significant difference between the two groups as re-
gard CAMCOG score which was significantly higher in the controlled group. This could be attributed to the fact
that CAMCOG contains more items on memory, language, and construction and allows a more differentiated
judgment about these functions than the MMSE.
Our study revealed that CAMCOG had better sensitivity and MOMSSE had better specificity for the predic-
tion of uncontrolled DM.
The better specificity of MOMSSE could be linked to its testing of certain cognitive functions that could be
affected by DM, as most of its items namely memory, executive functions (digit span backward in the attention
item using working memory, verbal abstraction item), language, visuospatial (construction skills), insight into
illness, which is affected by memory, as verbal memory had an effect on total insight and all dimensions of in-
sight, [26] and general fund of information which is also related to memory [13]. These functions are known to
be affected in DM as reported by different studies. For instance, a study found ineffective top-down control of
the prefrontal cortex which is involved in executive functions in Type 1DM. Furthermore, inter-network con-
nections between the strategic/executive control system (in prefrontal cortex) and systems subserving other cor-
tical functions including language were also less integrated in Type 1DM patients than in healthy individuals
[27]. Moreover, another study suggests that the hippocampus and parahippocampal gyrus may be particularly
vulnerable to the deleterious effects of Type 2DM. The parahippocampal gyrus in particular may play a crucial
role in the memory impairments frequently reported in Type 2DM [28].
On the other hand, CAMCOG was more sensitive to assess cognitive functions as it includes more items that
assess wider variety of cognitive functions not included in MOMSSE as praxis involved in parietal region of the
brain [29], tactile perception also involved in the parietal region [30], visual perception involved in occipital re-
gion [31]. Whereas DM is known to affect areas in the brain that involve some cognitive functions as reported
by different studies [27] [28].
As regards Depression, our study found a significant difference between the two groups as regard the pres-
ence of depression. This was not consistent with the finding of Munshi, et al. [6] who reported that glycemic
control was not associated with the presence of depression as assessed by the GDS. This can be due to the smal-
ler size of sample used in their study and also that it was conducted at a tertiary care specialty setting. Although
the severity of depression was not disclosed by authors, they considered that the collected patients tend to be
highly motivated, educated, and have excellent support systems. Therefore we might suggest less severe depres-
sion in their population, as it is known that depression is negatively correlated with education along with their
excellent support system [32].
On the other hand, our study was consistent with finding of Lustman & Clouse [33] who reported that De-
pression has been shown to have a significant positive association with HbA1c.
In the current study, there was no significant difference between the two groups as regard the anxiety diag-
nostic criteria. This was not consistent with the findings of Masmoudi, et al. [34] who found that subjects with
uncontrolled DM had a higher average anxiety score than those having a good glycemic control. This might be
due to the difference in the tests as we used DSM-IV criteria [17] and they used the Hopital Anxiety and De-
pression Scale (HADS), which is a psychometric scale used as a screening tool. Masmoudi et al. [34] considered
that using a screening psychometric scale, rather than a structured interview, to evaluate anxiety is a limitation to
their study. This might basically pick up cases with severe anxiety.
On the other hand, our findings were supported by the findings of Gois et al. [35] who found that anxiety
symptoms and vulnerability to stress on their own were not predictive of glycemic control.
As regards functional status, in the current study ADL showed a highly significant difference between the two
groups where the controlled group was more independent than the uncontrolled group. Similarly, the IADL
showed significant difference between the two groups as the controlled group was more independent than the
uncontrolled group.
This can be supported by Kalyani et al. [36] who found that uncontrolled HbA1C and comorbidities ac-
M. S. Amer et al.
148
counted for up to 85% of the excess risk of disability, largely due to cardiovascular disease and obesity, whereas
poor glycemic control alone only accounted for up to 10% of the excess risk of disability. Also, other studies re-
ported a 2 - 3 times greater risk of difficulty in performing ADL, and IADL tasks among older adults with DM
compared with adults without DM [37] [38]. Also, Waidyatilaka et al. [39] found that physical activity was ne-
gatively correlated with HbA1c and sedentary behavior was positively correlated with HbA1c levels.
Regarding ability of self application of treatment; our study showed a significant difference between the two
groups as the majority of the uncontrolled were those who received treatment by caregiver rather than by self.
This was convenient with our findings that the uncontrolled group was more dependent in ADL & IADL. This is
consistent indirectly with the ideas discussing the association between dependency and poor glycemic control
[36].
Also, there was a significant difference between the two groups as regard the follow up status, where those
who used to follow up their blood glucose were found to be more in the controlled group.
Our findings was not consistent with the findings of Harris [39] who found that follow-up frequency by self
screening was not related to glycemic control, as measured by HbA1c level. This difference could be attributed
to that subjects of our study were following up at outpatient clinic, so they received useful medical advice.
Meanwhile, our findings were supported by a study of Deiss et al. [40] that demonstrated that real-time con-
tinuous glucose monitoring (a method to measure glucose levels in real-time throughout the day and night. It al-
so sends the information to a monitoring and display device to the patient and clinicians to make proper inter-
vention) gradually improved glycemic control over 3 months, resulting in a reduction in HbA1c by at least 1%
in half of the patients and at least 2% in one-quarter.
In the current study, there was no significant difference between the two groups as regard the type of treat-
ment used. This was supported by the findings of the United Kingdom prospective DM study, in which subjects
were randomized to four groups: insulin, sulfonylurea, metformin, or continued diet therapy. Only 50 percent of
the patients in any group had HbA1C levels of less than 7% after three years [41].
In addition, the current study showed that there was a highly significant difference between the two groups as
regard the levels of the TC, LDL and TG. However, there was no significant difference between the two groups
as regard the HDL. This was supported by Petitti et al. [42] who found that there were significant trends of
higher levels of TC, LDL, TG, (but not HDL) with higher HbA1c concentrations for both DM types.
5. Conclusion
Cognitive impairment was associated with poor glycemic control. Impairment in attention and abstraction, relat-
ed to executive function, functions were found to be associated with poor glycemic control. These functions may
be more needed in self management of DM and hence affected glycemic control. Also, depression was associ-
ated with poor glycemic control but anxiety was not. Poor functional state, application of treatment by other
person and poor follow up of glucose were all associated with poor glycemic control.
6. Recommendation
Causal relation between poor glycemic control and both cognition and depression is suggested to be studied in a
follow up study.
Funding
This paper was partially funded by Ain Shams University, there were no sponsors.
Acknowledgements
The authors would like to thank Ain Shams University, faculty of medicine for the partial funding of this paper.
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List of Abbreviations
ADL: Activities of Daily Living
AUC: Area under the Curve
CAMCOG: Cambridge Cognitive Examination
DM: Diabetes Mellitus
DSM-IV TR: Diagnostic & Statistical Manual 4th Edition Text Revision
FPG: Fasting Plasma Glucose
GDS: Geriatric Depression Scale
Hb-A1C: Hemoglobin A1c = Glycated Hemoglobin
HDL: High Density Lipoprotein
IADL: Instrumental Activities of Daily Living
LDL: Low Density Lipoprotein
MMSE: Mini Mental-State Examination
MOMSSE: Mattis Organic Mental Syndrome Screening Examination
P Value: Probability
PPG: Postprandial Plasma Glucose
ROC: Receiver Operating Characteristic
SD: Standard Deviation
SPSS: Statistical Package for Social Science
TC: Total Cholesterol
TG: Triglycerides
