![](3D"ImarhiagbeNMJ64No4Page545_files/image002.png")
Sociodemographic Fac=
tors
Associated with Depression Among Persons with Type 2
Diabetes Mellitus in The Family Medicine Clinic of a Tertiary
Hospital in Southern Nigeria. Comfort Oritseweyimi
Imarhiagbe1, *Christian Ibe Dickson1, Titi Precious-<=
span
class=3DSpellE>Ibiye Owen1, Modupeoluwa Omotunde Soroye![3D"Text](3D"ImarhiagbeNMJ64No4Page545_files/image003.png")
![](3D"ImarhiagbeNMJ64No4Page545_files/image005.png")
1
![](3D"ImarhiagbeNMJ64No4Page545_files/image007.png")
Background=
: Diabetes Mellitus (DM) is a chronic Non-Communicab=
le
Disease (NCD) with rising prevalence worldwide. DM increases the risk for d=
epression
as the prevalence of depression has been reported to be three times more in
diabetics than in non-diabetics. Though depressive symptoms are more common=
in
diabetes, they are not usually recognized and treated. Little is known about the predictors of depression in th=
is
group of people, especially among the Nigerian population. This study explored the sociodemographic facto=
rs
associated with depression in patients with type 2 DM without prior psychia=
tric
history.
Methodology: This was a cross-sectional study conducted among =
two
hundred and sixty-four patients using structured questionnaires. Data were =
analyzed using the Statistical Package for Social Sci=
ences version 20. Chi-square te=
sts
were performed to compare associations between categorical variables. A
probability (p) value less than 0.05 was taken as statistically significant=
.
Results:
Females [176 (66%)] were three t=
imes
more than males [88 (33.3%)] respectively. The prevalence of depression was
49.2%. Level of education (p=3D 0.008), occupation (p=3D 0.014), and social=
class
(p=3D 0.040) were significantly associated with depression among the respon=
dents.
Depression was higher among the older age group, females, and the widowed.<=
span
style=3D'color:red'>
Conclusions:
Females and older adults were mo=
re
affected by depression. The predictors of depression were level of educatio=
n,
occupation, and social class. Thus, there is a need to screen those who have
been diagnosed with T2DM for depression, especially females and older adult
patients.
Keywords: <=
/b>Sociodemographic, Depression,
Diabetes, Family Medicine
=
= *Correspondence: Dr. Dickson Christian Ibe Department of Family Medicine, Faculty of Clinical Sciences, College of Medical Sciences, Rivers State University, Port Harcourt, Rivers State, Nigeria. Email: = Dickov82@Gmail.Com
Thi=
s is
an open access journal, and articles are distributed under the terms of the
Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which
allows others to remix, tweak, and build upon the work non-commercially, as
long as appropriate credit is given and the new creations are licensed under
the identical terms.
=
How
to cite this article: Imarhiagbe CO, Dickson CI, Owen TP, Soroye MO, Okocha AN, Dienye PO.
Sociodemographic Factors Associated with Depression Among Persons with Type=
2
Diabetes Mellitus in The Family Medicine Clinic of a Tertiary Hospital in
Southern Nigeria.<=
span
lang=3DEN-GB style=3D'font-size:9.0pt;font-family:"Times New Roman",serif;
mso-ansi-language:EN-GB;mso-bidi-font-weight:bold'> Niger Med J 2023; 63(4)=
:545-555. Accepted: August
24, 2023. Published: September 21, 2023.
![](3D"ImarhiagbeNMJ64No4Page545_files/image009.png")
Diabetes mellitus is a major threat to human health. Like many other chro=
nic
medical conditions, it is complicated by emotional and psychological disord=
ers,
yet the psychological dimension of this condition is often overlooked when
caring for those affected by the disease.[1] Furthermore, improv=
ing
the quality of life for adult diabetics requires knowledge and management of
psychological disorders such as depression.
Depression is a common mental disorder characterized by sadness, los=
s of
interest or pleasure, guilt or low self-worth, disturbed sleep and appetite,
tiredness, and poor concentration which could be long-lasting or recurrent.=
[2]
It is a mood disorder ranked by the World Health Organization (WHO) as a
leading cause of disability worldwide and a major contributor to the overall
global burden of disease.[3]
Studies worldwide have report=
ed
the prevalence of depression among Type 2 diabetes mellitus (T2DM) patients
ranging from 11% to 60%.[4],[5] In Nigeria, the prevalence of clinical depression was reporte=
d as
30% among those who have diabetes mellitus compared to 9.5% in the apparent=
ly
healthy control groups.[5]
The presence of depression in patients with diabetes mellitus is of =
vast
importance, as it is usually associated with poor disease control, adverse
health outcomes, and impairment of quality of life.[6] A chronic
disease like diabetes encourages co-morbidity with mood disorders. The depr=
ession
rates in primary care patients are between 5% and 10%, whereas prevalence r=
ates
of depression in patients with diabetes have been estimated to be 12% to 18=
%.[7]
The more serious the disease is, the more probable it will be accompa=
nied
by mood symptoms of variable severity. Thus, the co-existence of depression
among people with diabetes worsens the disease outcome.[8] In developed countries, depressi=
on and
diabetes are the 4th and 8thcauses of Disability Adju=
sted
Life Years (DALYs). Different literature reviews and meta-analyses conducted
worldwide showed that depression is a common co-morbid condition among pati=
ents
with diabetes, with Nouwen et al in the United Kingdom and Teshoma
et al in Ethiopia reporting prevalence rates of 24% and 39-75% respectively=
.[9],[10]
A recent five-year prospective study examined factors associated with
major depression at a five-year follow-up in approximately three thousand
patients with diabetes.[7] Baseline minor and major depression, =
the
number of diabetes symptoms, among others, were independent predictors of m=
ajor
depression in this 5-year time point.[7] Being a chronic medical
condition, diabetes mellitus necessitates several adjustments in patient
aspiration, lifestyle, and even employment, and adaptation is difficult and
complex. Some patients grieve about their predicament before adjusting to it
while others have protracted distress which may lead to psychiatric disorde=
rs
most commonly, depression and anxiety.[1] However, little is known about the sociodemographic fact=
ors
associated with depression in diabetics, especially among the primary care
population without previous psychiatric illness in the Nigerian population.=
[11],[12]
In diabetic patients, depression has been linked w=
ith
multiple factors, like female sex, younger age, not having a spouse, poor
social support, and low socioeconomic status.[7],[13],[14] Furth=
ermore,
being underweight or overweight has been found to influence the development=
of
depression, with high Body Mass Index, poor glycaemic control, diabetic
complications, and lower educational level being risk factors for depressio=
n in
diabetics.[1] The
present study assessed the magnitude of depression and its potential
sociodemographic associations among type 2 diabetes mellitus patients without prior
psychiatric history attending the family medicine clinic at Rivers State
University Teaching Hospital. The
results are expected to provide more precise measures of the prevalence of
depression in Type 2 diabetics in primary family medicine settings and help
identify the risk factors for depression in these patients.
Materials and Meth=
ods
This cross-sectional study=
was
conducted at the Family Medicine Clinic of the Rivers State University Teac=
hing
Hospital, Port Harcourt. The hospital serves as a referral centre for most
peripheral hospitals and health centres in the state.
Using a 19.4% prevalence of
depression from a study done at a tertiary health institution in Jos, North
Central Nigeria, a minimum sample size of 264 was obtained using the formula
for cross-sectional studies.[15] Two hundred and sixty-four pati=
ents
who met the inclusion criteria were recruited by systematic random sampling
technique, within a period of two and half months using structured
questionnaires. Patients living with Type 2 DM, diagnosed using the
criteria laid down by the American Diabetes Association, and attending the
family medicine clinic, were evaluated for depression using <=
span
lang=3DEN-GB style=3D'font-size:12.0pt;font-family:"Times New Roman",serif;
color:black;mso-themecolor:text1;mso-ansi-language:EN-GB'>the Patient Health
Questionnaire 9 (PHQ- 9).[16] Anthropometric and blood pressure
measurements of participants were measured using a
Inclusion
criteria
All consenting adult patie=
nts
(aged above 18 years), with type 2 diabetes mellitus, who had been on treat=
ment
for diabetes for a minimum of three months.
Exclusion criteria
Patients who were seriously/critically ill or had a
history of previous psychiatric history were excluded from the study.
Ethical
permission
Ethical approval for this
study was obtained from the Ethical Committee of Rivers State Hospital
Management Board. Informed written consent was obtained from each study par=
ticipant
before recruitmentData
collection procedure
On each study day, type 2
diabetic patients who met the study criteria were approached and the study
procedure was explained to them. Those that gave consent for the study were
enrolled in the study. For each study participant, the researcher and resea=
rch
assistant administered the questionnaire. The researcher collected the blood
samples and carried out the anthropometric measurements. The assays for glu=
cose
levels were analysed and the results were cross-checked by a consultant
pathologist in RSUTH
Statistical
analysis
The results we=
re
coded and entered into an Excel worksheet and subsequently transferred into
Statistical Package for the Social Sciences (SPSS) Version 20 and cleaned.<=
/span> Frequency tables and charts were constructed for =
the
presentation of the results. Means and standard deviation were calculated f=
or
continuous variables and categorical variables were expressed in counts and
percentages. Chi-square tests were carri=
ed out
to compare the degree of association between categorical variables. Statist=
ical
significance was set at a 95% confidence interval (p< 0.05).
Results
Two hundred and sixty-four
respondents were involved in the study with a 100% response rate.
The prevalence of depression
regarding age and gender is described in Table 2.=
The
prevalence of depression was found to be 44.3% in males and 51.7% in female
patients. Among th=
ose between the age group of 60–69 =
and
≥70 years, the prevalence of depression was found to be 52.2% and 54.3% respectively.
From the PHQ-9 tool used to evaluate for
depression among t=
he
study participants, it was observed that 130 (49.2%) of them had
depression as shown in Figure 1.=
Table 3 describes the association=
of
depression with the sociodemographic and economic characteristics of the
respondents. Level of education (<=
i>P
=3D 0.008), occupation (P =3D 0.014), and social class (p=3D 0.040) =
were found
to be associated with depression among T2DM patients. There was a=
trend
of decreasing depression rates as the level of education increased. Depress=
ion
was most prevalent among respondents with no formal education [17 (68.0%)] =
and
least among respondents with university education [11 (27.3%)]. There was a
statistically significant association between depression and level of educa=
tion
(p =3D 0.008). For occupation, the highest rate of depression was among the=
skilled
artisans (55.7%), the professionals had a depression rate of 32.8% while the
lowest rate was among the unemployed (30.0%). There was a statistically
significant association between depression and occupation (p=3D 0.014). Als=
o,
respondents in the low social class had the highest prevalence of depression
(57%) compared to those in the middle (47.0%) and high (28.6%) social class.
There was a statistically significant association between social class and
depression (p=3D 0.040).
Table
1: Sociodemographic/Economic Characteristics of
Respondents (n=3D264)
|
Variable =
|
Frequency (n =3D =
264) |
Percentage |
|
Age (year) |
|
|
|
<4=
0 |
15 |
5.7 |
|
40-49=
|
41 |
15.5 |
|
50-59=
|
70 |
26.5 |
|
60-69=
|
92 |
34.9 |
|
Ͱ=
5;70 |
46 |
17.4 |
|
Mean age |
58.5 ± 11.4 |
|
|
Sex |
|
|
|
Male |
88 |
33.3 |
|
Female |
176 |
66.7 |
|
Marital Status |
|
|
|
Single |
17 |
6.4 |
|
Married |
181 |
68.6 |
|
Separated/Divorced |
6 |
2.3 |
|
Widowed |
60 |
22.7 |
|
Ethnicity |
|
|
|
Ikwerre |
44 |
16.7 |
|
Ogoni |
25 |
9.5 |
|
Ijaw |
50 |
18.9 |
|
Igbo |
54 |
20.5 |
|
Others * Education No formal education |
91 25 <=
/span> |
34.4 9.5 |
|
Primary education |
57 |
21.6 |
|
Secondary |
91 |
34.5 |
|
Tertiary non-University |
51 |
19.3 |
|
Social class ** |
|
|
|
High (I) |
21 |
8.0 |
|
Middle (II-III) Low (IV=3DV) =
|
149 94 |
56.4 35.6 |
*Yoruba, Edo,
Ibibio. ** Olusanya`s social class
classification is from I-V with I as the highest and V as the lowest
Table 2: Gender and age group distribution of depression among
respondents
|
Variable |
Depressed |
||
|
Yes |
No |
Total |
|
|
n =3D 130 |
n =3D 134 |
n =3D 264 |
|
|
Age (year) |
|
|
|
|
<=
40 |
5 (3=
3.3) |
10 (66.7) |
15 |
|
40-4=
9 |
18
(43.9) |
23 (56.1) |
41 |
|
50-5=
9 |
34
(48.6) |
36 (51.4) |
70 |
|
60-6=
9 |
48
(52.2) |
44 (47.8) |
92 |
|
≥7=
0 |
25 (54.3=
) |
21 (45.7=
) |
46 |
|
Sex |
|
|
|
|
Male |
39 (44.3=
) |
49 (55.7=
) |
88 |
|
Female |
91 (51.7=
) |
85 (48.3=
) |
176 |
![](3D"ImarhiagbeNMJ64No4Page545_files/image011.png")
Figure 1: Preval=
ence
of depression according to PHQ-9 among the respondents
Table
3: Association=
s BetweenSociodemographic/Economic Characteristics and Depression
|
Variable |
Depressed |
χ2 |
Df |
p-value |
||
|
Yes |
No |
Total |
|
|
|
|
|
n =3D 130 |
n =3D 134 |
n =3D 264 |
|
|
|
|
|
Age (years) |
|
|
|
|
|
|
|
<=
40 |
5 (3=
3.3) |
10 (66.7) |
15 |
2.795 |
4 |
0.593 |
|
40-4=
9 |
18
(43.9) |
23 (56.1) |
41 |
|
|
|
|
50-5=
9 |
34 (=
48.6) |
36 (51.4) |
70 |
|
|
|
|
60-6=
9 |
48
(52.2) |
44 (47.8) |
92 |
|
|
|
|
≥7=
0 |
25 (54.3=
) |
21 (45.7=
) |
46 |
|
|
|
|
Sex |
|
|
|
|
|
|
|
Male |
39 (44.3=
) |
49 (55.7=
) |
88 |
1.281 |
1 |
0.258 |
|
Female |
91 (51.7=
) |
85 (48.3=
) |
176 |
|
|
|
|
Marital
status |
|
|
|
|
|
|
|
Single |
6 (35.3)=
|
11 (64.7=
) |
17 |
2.349 |
3 |
0.503 |
|
Married<= o:p> |
90 (49.7=
) |
91 (50.3=
) |
181 |
|
|
†=
0.527 |
|
Separate=
d/Divorced |
2 (33.3)=
|
4 (66.7)=
|
6 |
|
|
|
|
Widowed<= o:p> |
32 (53.3=
) |
28 (46.7=
) |
60 |
|
|
|
|
Ethnicit=
y |
|
|
|
|
|
|
|
Ikwerre |
20 (45.5=
) |
24 (54.5=
) |
44 |
0.836 |
4 |
0.934 |
|
Ogoni |
12 (48.0=
) |
13 (52.0=
) |
25 |
|
|
|
|
Ijaw |
23 (46.0=
) |
27 (54.0=
) |
50 |
|
|
|
|
Igbo |
28 (51.9=
) |
26 (48.1=
) |
54 |
|
|
|
|
Others |
47 (51.6=
) |
44 (48.4=
) |
91 |
|
|
|
|
Religion=
|
|
|
|
|
|
|
|
Christia=
nity |
130 (49.=
4) |
133 (50.=
6) |
263 |
0.974 |
1 |
0.324 |
|
Islam |
0 (0) |
1 (100)<= o:p> |
1 |
|
|
1.000 |
|
|
|
|
|
|
|
|
|
Educatio=
n |
|
|
|
|
|
|
|
No forma=
l |
17 (68.0=
) |
8 (32.0)=
|
25 |
13.763 |
4 |
0.008* |
|
Primary<= o:p> |
33 (57.9=
) |
24 (42.1=
) |
57 |
|
|
|
|
Secondar=
y |
47 (51.6=
) |
44 (48.4=
) |
91 |
|
|
|
|
Tertiary
(non-university) |
22 (43.1=
) |
29 (56.9=
) |
51 |
|
|
|
|
Universi=
ty |
11 (27.5=
) |
29 (72.5=
) |
40 |
|
|
|
|
Occupation |
|
|
|
|
|
|
|
Unemploy=
ed |
3 (30.0)=
|
7 (70.0)=
|
10 |
10.569 |
3 |
0.014* |
|
Retired<= o:p> |
25 (53.2=
) |
22 (46.8=
) |
47 |
|
|
|
|
Skilled
artisans |
83 (55.7=
) |
66 (44.3=
) |
149 |
|
|
|
|
Professi=
onal |
19 (32.8=
) |
39 (67.2=
) |
58 |
|
|
|
|
Social class |
|
|
|
|
|
|
|
High |
6 (28.6)=
|
15 (71.4=
) |
21 |
6.427 |
2 |
0.040* |
|
Middle |
70 (47.0=
) |
79 (53.0=
) |
149 |
|
|
|
|
Low |
54 (57.4=
) |
40 (42.6=
) |
94 |
|
|
|
* Statistically significant † Fisher exact p
Discussion
The present =
study
was conducted to ascertain the prevalence of depression among type 2 diabetes mellitus patients without prior psychiatric history and to identify the sociodemographic =
factors associated with it.
Conversely, t=
he
depression prevalence found in the index study was much higher than the
findings by James et al in a comparative hospital-based study in a tertiary
institution in Benin City, Southern Nigeria.[5] They reported a =
30%
prevalence of depression among diabetic patients and a significantly lower =
9.5%
(p< 0.001) in the control group. In that study, they used the depression
module, Schedule for Clinical Assessment in Neuropsychiatry (SCAN) to diagn=
ose
depression, and the Beck Depression Inventory (BDI) to measure depression a=
nd
its severity. On the BDI score, 39.5% of the diabetic patients met the
depression criteria compared with 13.5% among the control group.[5] Their
findings although as the index study, supported the fact that depression ra=
tes
were higher among diabetic patients than in the general population, they
however found a prevalence lower than the index study. The lower prevalence
could be due to the difference in assessment tools used as well as the
difference in study designs. Similarly, Agbir e=
t al
in a cross-sectional descriptive study among patients in a tertiary hospita=
l in
Northern Nigeria reported a prevalence of 19.4%.[12] In that stu=
dy,
the depressive module used was the Structured Clinical Interview for DSM an=
d Axis
Disorder (SCID). Subsequently, Hamilton Depression Rating Scale (HDRS) was =
used
to determine the severity of symptoms among respondents diagnosed with
depression according to the DSM IV criteria. Agbir et
al concluded that depression was common among diabetes mellitus subjects in
their environment.[12] The prevalence of 19.4% compared to other
studies could be due to the fact that SCID is used for the diagnosis of maj=
or
depression and cases of mild and moderate depression were not accounted for.
Other international studies also reported a lower prevalence of depression
among diabetics.[21],[22] Wang et al reported a depression
prevalence range of between 15-17% among diabetics in different out-patient
specialties in Turkey.[21] Meanwhile, in a systematic review by
Rezia et al in South East Asia, a depression prevalence range of 14 – 41% w=
as
found among diabetics.[22]
These findings have been irrespective of the urban=
or
rural location as Dienye et al in a rural
clinic-based study in Nigeria reported a higher prevalence of depression
(61.54%) among participants with co-morbid physical illness than a 15.38%
prevalence in those without physical illness while Adiari et al in a study =
in
cosmopolitan Lagos found a 14.4% prevalence of depression among patients wi=
th a
chronic illness as compared to 5.5% in the general population. [23], [=
24],
[25]
The variation=
s in
prevalent figures of these studies and the index study could thus be attrib=
uted
to demographic, biological, and socioeconomic heterogeneity as well as the
difference in instruments used to assess depression in diabetic patients.
In the curren=
t study
More female respondents in the current study were depressed (51.7%) compared to<=
span
lang=3DEN-US style=3D'font-size:12.0pt;font-family:"Times New Roman",serif;
mso-bidi-font-family:Arial;mso-bidi-theme-font:minor-bidi'> male respondents
(44.3%). This is similar to what was found in various studies.[18],[30=
] In
the study by Agbir et al depression was found t=
o be
significantly correlated with sex, with a female-to-male ratio of 3:1, and =
was
also significantly associated with unmarried patients and those who had a p=
oor
relationship with their partners.[12] This higher prevalence in
women could have been influenced by the sociocultural role of women in our
environment, including responsibilities at home and child care as well as
physiologic cyclical hormonal changes in women and their social vulnerabili=
ty.[27]
In contrast, Ganasegeran in Malaysia found a hi=
gher
prevalence of depression in males than females reporting 58.6% in males and
41.4% in females.[26] The higher male prevalence in their study
could be due to the sociocultural practice in that geographic area.
Respondents who were widows had a hig=
her
prevalence of depression. This could be because the study population was ma=
inly
in the aged stage of the family developmental cycle and one of the issues of
this stage is spousal loss.
In this study, the highest prevalence=
of
depression was found among respondents with no formal education. Similar
findings have been reported by various studies.[1],[5] Igwe et a=
l reported in a similar study that no formal education was associated w=
ith
depression.[1] The study by James et al in Benin, Southern Niger=
ia
also reported an association between a low level of education and depressio=
n.[5]
These findings could be because less educated people are more likely to have
low socioeconomic status as they may earn less as they are likely to get po=
orly
paid jobs. With low earning power, patients face the burden of maintaining
lifestyle changes that could sustain the cost of medication adherence. Also,
lack of education is a strong impediment to understanding the dynamics of
chronic medical conditions and the complexities involved in good glycemic
control for subjects with diabetes mellitus.[1] Furthermore, the=
se
patients may not be able to source information for their health, thus ignor=
ance
and poor health-seeking behaviour could predisp=
ose
them to depressive illness. Local studies report poor educational backgroun=
d as
a strong risk for depression.[5],[27]
With regards to occupation and social
class in the index study, the highest rate of depression was among the skilled artisans
(55.7%) and respondents with a low social class had the highest prevalence =
of
depression (57%). There was a statistically significant association between
depression and occupation (p=3D0.014), and depression and social class (p=
=3D0.040).
This is similar to reports from various studies.[18],[30] The hi=
gh
rate of depression among skilled artisans could be due to the current gener=
al
economic downturn as skilled artisans depend on patronage from others to ea=
rn a
living.[31] Many had come to the metropolitan city believing the=
re
were business opportunities but the economic downturn has negatively affect=
ed
this. In the index study, respondents in the low social class had the highe=
st
prevalence of depression (57%). This is consistent with the report by Leone=
et
al who in a systematic mapping of evidence reported the occurrence of
depression among diabetic patients to be associated with lower social class=
.[32]
This could be because diabetics in the low social class do not only have to
contend with the burden of the physiologic chronic disease condition but al=
so
the financial and psychological stress of unavailable means to manage the
condition. Additionally, it was also found in a study =
that
patients with diabetes and depression have a higher frequency of cardiovasc=
ular
risk factors.[7]
current study's findings indicate the importance of patients
Strength and limitations
It was a cross-sectional and hospital-based study limiti=
ng
the ability to make causal inferences and extrapolate to the general commun=
ity.
As little is known about the predictors of depression in the Nigerian diabe=
tic
population, this study contributes essential data to depression as an emerg=
ent
need of diabetic patients as well as serves as a reference for the need for
larger population-based research on depression and its predictors in diabet=
ic
patients.
Conclusions
Findings revealed a high prevalence of depression among =
T2DM
patients, and among these, females and older adult patients were more affec=
ted
by depression. This study also concluded that patients’ level of education,
occupation, and socioeconomic status were also significantly associated with
depression. Further large-scale research is required to explore the predict=
ors
of depression among type 2 DM patients. It is needed to screen patients of =
type
2 DM, especially females, older adults, and less educated patients, for
depression, at regular intervals as per clinical demand. The occupation and
socioeconomic status of these patients should also be considered as predict=
ors
for depression.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
References
1. Igwe
MN, Uwakwe P, Ahanoto CA,O=
nyeama
GM, Bakare MO, Ndukuba AC. Factors associated w=
ith
depression and suicide among patients with diabetes mellitus and hypertensi=
on
in a Nigerian tertiary hospital. Afr Health Sci.
2013; 13(1): 68 – 77.
2. American Psychiat=
ric
Association. Diagnostic and Statistical Manual of Mental Disorders.5th Edit=
ion.
Washington, DC: American Psychiatric Association;2013.
3.&n=
bsp;
World Health Organization.
Depression-fact sheet.2018. Available at:
4.&n=
bsp;
https://www.who.int/news-room/fac=
t-sheets/detail/depression.
Accessed April 2018
5. Hussain S, Habib =
A,
Singh A, Akhtar M, Najmi AK. Prevalence of depression among type 2 diabetes
mellitus patients in India: A meta-analysis. Psychiatry research.2018;270:264-273.
6. James BO, Omoaregba JO, EzeG, Morakinyo O. Depression among patients with diabetes
mellitus in Nigeria tertiary hospital. S.Afr J Psychiatr.2010; 16 (2): 61 – 64.
7. Andreoulakis E, <=
span
class=3DSpellE>Hyphantis T, Kandylis D, =
Lakovides A. Depression in diabetes mellitus: a
comprehensive review. Hippocratia.
2012; 16 (3) 205-214.
8.&n=
bsp;
Katon WJ, Lin EH, Russ=
o J,
Von Korff M, Ciechanowski P, Simon G, et al. Cardiac risk factors in patien=
ts
with diabetes mellitus and major depression. J Gen Intern Med. 2004;19
9. International
Diabetes Federation. IDF Diabetes Atlas, 10th edition. Brussels, Belgium: 2=
021.
Available at: https://www.diabe=
tesatlas.org. Accessed April =
2022
10. Nouwen A, Winkley=
K
and Twist J. Type 2 diabetes mellitus as a risk factor for the onset of
depression: a systematic review and meta-analysis. =
Diabetologia
2010; 53(12): 2480-2486.
11. Teshome HM, Ayalew
GD, Shiferaw FW, Leshargie CL and Boneya DJ. The
prevalence of Depression among Diabetic patients in Ethiopia; A Systemic Re=
view
and Meta-Analysis 2018 Depress Res Treat. 2018; 2018. Available at <=
span
lang=3DEN-US>https://doi.org/10.1155/2018/=
6135460 Accessed June 20=
18
12. Asian J Psychiatr.2017;=
27:85–100. <=
/span>
13.&=
nbsp; Agbir TM, Adebowale TO,
Audu MD, Goar SG. Clinical correlates of depression among diabetics in Jos,
Nigeria. J Med Trop. 2010; 12:37-41
14.
Tol A, Baghbanian A, Mohebbi B, Shojaei=
zadeh
D, Azam K, Shahmirzadi SE, et al. Empowerment
assessment and influential factors among patients with type 2 diabetes. J Diabetes MetabDisord.2013;12
15.
Chowdhury SH, Kar=
im
MN, Selim S, Ahmed F, Azad AK, Maksud SA, et al. Risk of depression among
Bangladeshi type 2 diabetic patients. Diabe=
tes
MetabSyndr.2017;=
11(2):1009–1012.
16.&=
nbsp; Araoy=
e MO. Sample size calculation. Research
methodology with statistics for health and social sciences. Ilorin: Nathadex Publishers; 2004:115-121.
17. Miller CD, Phillips LS, Tate MK, Porwoll JM, Rossman SD, Cronmiller N et al. Meeting
American Diabetes Association guidelines in endocrinologist practice. Diabetes Care. 2000;23(4):444-448.
18. Gupta S, Jain U,
Chauhan N. Laboratory diagnosis of HbA1c: a review. J Nanomed Res. 2017;5(4):00120.
19. El-Mahalli AA. Prevalence and predictors of depression a=
mong
type 2 diabetes mellitus out-patients in Eastern Province, Saudi Arabia. International Journal of Health Scienc=
es,
2015; 9(2): 119-126
20.&=
nbsp; Ofori SN, Adiukwu FN. Screening for depressive symptoms among
patients attending Specialist Medical Outpatient in a Tertiary Hospital in
South Nigeria. Psychiatry J. 20=
18;
2016: 1-6
22. Wang J, Wu X, Lai W,
Long E, Zhang Y, Li W et al. Prevalence of depression and depressive symptoms a=
mong
outpatients: a systematic review and meta-analysis. BMJ Open. 2017; 7(8): e
017173. Doi: 10.1136/bmjopen.2017-017173
23. Rezia R, Islam A,
Islam SMS, Depressive symptoms among participants with type 2 diabetes in S=
outh
east Asia. A systematic review. J <=
span
class=3DSpellE>Diabetol 2018; 9(1):
19-24
24. Dienye PO, Gbeneol PK, Akani=
AB.
Association Between Giant Hydrocele and Depression in a Rural Clinic in
Nigeria. Am J Men Health.
2011; 5 (5): 438-443
25.&=
nbsp; Adiari O, Cambell=
PC.
Prevalence and severity of Depression among people living with HIV/AIDS in a
Tertiary Hospital.Nigeria Hospital Practice. 2014; 14(1-2):3-15
26. Obadeji A, Olow=
oin
LO, Dada MU, Ajiboye AS, Kumolalo BF, Solomon O=
A.
Assessment of depression in a primary care setting in Nigeria using the PHQ=
-9.Family Practice. 2015;4(1):10-34
27. Genasageren K, Renganathan P, Manf RA,
Al-Dubai SAR. Factors associated with anxiety and depression among type 2
diabetes out patients in Malaysia; a descriptive cross sectional single cen=
tre
study, BMJ Open journal of Clinical Pathology. 2014; 4: 1-7
28. Onya ON, Stanley =
PC.
Risk Factor for depressive illness among elderly GOPD<=
/span>
Attendees at UPTH.Int Res. J Medical Sci. 2013; 1=
(6):
1-9
29.&=
nbsp; Salihu AS, Udofia=
O.
Prevalence and Associated Factors of Depression among general outpatients i=
n a
tertiary Institution in Kano North Western Nigeria. O J Psych. 2016;6(=
3):
228-236.
30.&=
nbsp; Berg LL, Ruse T,
Knudsen KA. Depression in persons with by age and antidiabetic treatment; a
cross sectional analysis with Data from Hondaland
Health Survey.PloS one 2015
31. Ichibuzo FMUO.
Influence of social support, age and religious commitment on depressive
symptoms among cancer patients 2013. Available from www.Unn.edu.ng>RpositiryAccessed June 201=
7
32. Adofu I, Al Hassan A. Insecurity and economic developme=
nt
in Nigeria. Journal of Economic and
Sustainable Development. 2018; 9(18):
101-111
33.&= nbsp; Leone T, Coast E, Narayanan S, Aikins A. Diabetes and Depression comorbidity and socio-economic status in = low- and middle-income countries (LMICs): a mapping of evidence. Global Health. 2012; 8:39