Akpalu et al. BMC Psychiatry          (2018) 18:357 
https://doi.org/10.1186/s12888-018-1933-2
RESEARCH ARTICLE Open Access
Depression and glycaemic control among
type 2 diabetes patients: a cross-sectional
study in a tertiary healthcare facility in
Ghana
Josephine Akpalu1, Ernest Yorke1, Joana Ainuson-Quampah2, Williams Balogun3 and Kwame Yeboah4*
Abstract
Background: Diabetes and depression are both chronic debilitating conditions, and their coexistence has been
associated with adverse outcomes. In this study, we investigated the association between glycaemic control and
depression in type 2 diabetes (T2DM) patients attending a tertiary healthcare facility in Ghana.
Methodology: In a cross-sectional study design, Patient Health Questionnare-9 (PHQ-9) was used to assess
depression in 400 T2DM, aged 30–65 years. Anthropometric characteristics and blood pressure were measured. Venous
blood was collected to measure the levels of glycated haemoglobin (HbA1c).
Results: The prevalence of depression was 31.3% among T2DM patients. Female gender, being unmarried, frequent
intake of alcohol, previous smoking status and insulin use were associated with increased odds of depression, whereas
being educated above basic school level was associated with a decreased odds of depression. In a multivariable
logistic regression model, being unmarried and poor glycaemic control were associated with an increase in odds of
depression after adjusting for age, gender, and social factors. The association between depression and glycaemic
control was attenuated when clinical factors were introduced into the model.
Conclusion: In our study population, we found that depression is common among Ghanaians with T2DM, and not
associated with poor glycaemic control in a fully multivariable-adjusted model.
Keywords: Depression, Type 2 diabetes mellitus, Glycaemic control, Ghana
Background developing diabetes, whereas diabetes patients are twice
The prevalence of diabetes mellitus has reached epi- as likely to be depressed, compared to non-diabetes in-
demic levels globally resulting in enormous human, dividuals [3–5].
economic and social cost worldwide. Currently, 415 The presence of depressive symptoms may affect
million people are living with diabetes, 75% of whom T2DM patient’s adherence to diabetes self-care regimen,
live in low and middle-income countries; this number particularly diabetic medications, dietary modifications
has been projected to increase to 642 million by 2040 and exercise [6]. Compared to non-depressed T2DM
[1]. Depression is also a chronic disease that affects patients, depressed T2DM patients have relatively higher
about 340 million people at any given time worldwide glycated haemoglobin (HbA1c) and increased prevalence
[2]. The temporal relationship between diabetes and de- of microvascular and macrovascular complications [7–
pression has been found to be bi-directional; patients 9]. Screening and treatment of depression in diabetes
with depression have an increased risk of 1.6 fold of patients have been reported to favourably improve gly-
cemic control, as well as prevent or delay diabetes-re-
lated complications [4]. However, the recognition and
* Correspondence: kyeboah@ug.edu.gh; melvinky@gmail.com
4Department of Physiology, School of Biomedical and Allied Health Sciences, treatment of depression among patients with diabetes
University of Ghana, Accra, Ghana have been found to be less than optimum [10]. Moreover,
Full list of author information is available at the end of the article
© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Akpalu et al. BMC Psychiatry          (2018) 18:357 Page 2 of 7
in low and middle-income countries including Ghana, using the formula: weight in kilogrammes divided by
there is a dearth of data on the burden of depression the height in metres squared.
among diabetes patients [11, 12]. Venous blood was drawn from each participant for
In this study, we investigated the association between the measurement of glycated haemoglobin (HbA1c)
glycaemic control and depression among T2DM patients using the boronate affinity chromatography method on
attending a tertiary care facility in Ghana. We hypothe- PDQ Plus HPLC autoanalyzer (Primus Diagnostics,
sized that compared to non-depressed diabetes patients, Trinity Biotech, Ireland). Good glycaemic control was
diabetes patients with depression will have poor gly- defined as HBA1c of less than 7% [19]. Ethical approval
caemic control. was sought and obtained from the Ethical and Protocol
Review Committee of the College of Health Sciences,
University of Ghana (Protocol ID MS-Et/M.6-P4.4/
Methodology 2012–13) and each patient provided written voluntary
The study was a cross-sectional design, conducted at the informed consent after the rationale and procedure of
National Diabetes Management and Research Centre, the study were thoroughly explained. Patients found to
Korle Bu Teaching Hospital, Accra, Ghana. The mini- be depressed we referred to the Psychiatry department
mum sample size was calculated based on the hypothet- for further assessment and possible management.
ical prevalence rates of depression and glycaemic control
to be 26% and 15% [13] respectively; 340 patients were Statistical analysis
required to achieve a power of 80% and α of 0.05. In all, Data was analysed using SPSS version 18. Data was pre-
400 T2DM patients, aged between 30 and 65 years, were sented as mean with standard deviation for continuous
enrolled into the study by systematic random sampling variables and as proportions for categorical variables.
of every fourth consenting patient visiting the clinic. Pa- The study subjects were dichotomized based on the
tients with type 1 diabetes, pregnant women and those presence or absence of depression. Differences between
aged less than 30 years at diagnosis or patients older the two groups with regards to their socio-demographic
than 65 years were excluded from the study. In addition, and clinical variables as well as HbA1c were assessed.
patients with other causes of depression such as loss of a The chi-squared (χ2) test was used for the comparison
close family member within past 4 months and medica- of categorical variables and Students t-test for continu-
tion/history of depression or manic/hypomanic episode ous measures. Logistic regression models were per-
were excluded from the study. The socio-demographic formed to determine the change in odds of depression
characteristics such as age, gender, education, employ- and glycaemic control after adjusting for confounding
ment, alcohol & smoking status, as well as clinical data variables. The level of significance was set at p < 0.05.
like duration of diabetes, diabetes medication, hyperten-
sion and antihypertensive medication were collected Results
using structured questionnaires. In our study population with a high representation of
Depression was screened using Patient Health females (male: female = 1:4), 125 (31.3%) of the partici-
Questionnaire-9 (PHQ-9). The PHQ-9 is an instrument pants were found to have depression. Age, duration of
that has been validated in sub-Saharan Africans [14, 15] diabetes and BMI were comparable for T2DM patients
and in diabetes patients [16] for the detection of gen- with or without depression (T-test, p-values> 0.05).
eral depressive symptoms. The PHQ-9 assesses how Female gender, marital status, educational level, alcohol
often the respondent has experienced specific symp- intake and smoking status were associated with depres-
toms over the past 2 weeks, assigning values of 0 to 3 sion (χ2, p-values< 0.05). T2DM patients with depression
points (0 - not at all, 1 - several days, 2 - more than half had higher systolic blood pressure and glycated haemo-
of the days, 3 - nearly every day) [17]. Major depressive globin level than T2DM patients without depression
disorder was defined as the presence of at least five (T-test, p < 0.05; Table 1).
symptoms, reported for more than half the days in the In unadjusted logistic regression models, being female
past 2 weeks, including depressed mood or anhedonia, (OR = 2.84), unmarried (OR = 1.63), regular alcohol con-
as well as the thought of suicide or better dead [18]. sumer (OR = 5.47), former smoker (OR = 1.28), using in-
Blood pressure was measured after 5 min rest using sulin (OR = 1.3) and having poor glycaemic control (OR =
an automated digital blood pressure monitor (Omron 1.82) were associated with an increased odds of depression
907XL pro, Healthcare, Inc., Vernon Hills, IL), with the (Table 2). Multivariable logistic regression models were
patients seated comfortably with a back support and constructed to analyze the relationship between depres-
arm resting on a table. Body weight and height were sion versus glycaemic control status and marital status,
measured with a Seca 740 scale and a stadiometer with sequential adjustments for social and clinical factors.
respectively, and the body mass index (BMI) computed Poor glycaemic control was associated with an increase in
Akpalu et al. BMC Psychiatry          (2018) 18:357 Page 3 of 7
Table 1 General characteristics of participants by depression status
T2DM without depression T2DM with depression All Patients Test statistic P
N (%) 275 (68.7) 125 (31.3) 400
Age 52.9 ± 8.5 52.2 ± 9 52.7 ± 8.7 t (0.79) 0.48
Duration of diabetes, yrs 9.1 ± 7.3 9.5 ± 6.3 9.2 ± 7 t (0.56) 0.57
Females, n (%) 208 (75.6) 106 (84.6) 314 (78.5) Χ2 (6.72) 0.01
Married n (%) 190 (69.1) 72 (57.6) 262 (65.5) Χ2 (5.02) 0.02
Employed n (%) 194 (70.5) 83 (66.4) 277 (69.2) Χ2 (0.69) 0.41
Education Χ2 (5.04) 0.02
Primary or less 68 (24.7) 41 (32.8) 109 (27.3)
Junior grade 119 (43.3) 55 (44) 174 (43.5)
High school 50 (18.2) 19 (15.2) 69 (17.3)
Tertiary 38 (13.8) 10 (8) 48 (12)
Alcohol consumption Χ2 (4.86) 0.035
Doesn’t drink 212 (77.1) 92 (73.6) 304 (76)
Occasional 61 (22.2) 21 (16.8) 90 (22.5)
Always 2 (0.7) 3 (2.4) 5 (1.3)
Smoking status Χ2 (5.48) 0.04
Never 260 (94.5) 116 (92.8) 376 (94)
Previous 14 (5.1) 8 (6.4) 22 (5.5)
Current 1 (0.4) 1 (0.8) 2 (0.5)
BMI (mean ± SD) 30.2 ± 6.6 29.4 ± 5.6 29.9 ± 6.3 t (1.18) 0.24
Obesity classification Χ2 (3.99) 0.076
Normal 56 (20.4) 24 (19.2) 80 (20.1)
Overweight 89 (32.4) 41 (32.8) 130 (32.7)
Obese 128 (46.5) 60 (48) 188 (47.2)
Waist circumferece 99.9 ± 13 99.2 ± 11.7 99.7 ± 12.6 t (0.54) 0.58
WHR 0.93 ± 0.11 0.94 ± 0.09 0.94 ± 0.1 t (0.96) 0.34
Hypertension n (%) 219 (79.6) 99 (79.2) 318 (79.5) 0.39
Systolic BP, mmHg 126 ± 26 133 ± 21 132 ± 23 t (2.16) 0.03
Diastolic BP, mmHg 81 ± 12 80 ± 12 81 ± 12 t (0.77) 0.44
Heart rate, bpm 80 ± 15 81 ± 12 80 ± 14 t (0.71) 0.48
FPG, mol/l 9.2 ± 5.5 9.9 ± 4.3 9.4 ± 5.1 t (1.38) 0.17
HbA1c, % 9.4 ± 2.8 10.2 ± 3 9.9 ± 2.9 t (2.52) 0.013
WHR waist-hip ratio, BMI body mass index, BP blood pressure, FPG fasting plasma glucose, HbA1c glycated haemoglobin, t T-test statistic, Χ2 chi-square statistic
odds of depression, even after adjustment for age and with diabetes have twice the odds of developing de-
gender (AOR = 1.4, p = 0.037), as well as social factors pression compared with those without diabetes [4, 5].
(AOR = 1.25, p = 0.047); the association was however Depression in T2DM patients has been studied exten-
not significant after the introduction of clinical factors sively in populations from high-income countries,
into the model (AOR = 1.04, p = 0.286). Being unmar- however, data from lower-income countries such as
ried was associated with increased odds of depression Ghana are sparse [11, 12].
in the fully adjusted model (AOR = 1.47, p = 0.046; The prevalence of depression among T2DM patients in
Table 3). our study was similar to that reported in other studies. In
a meta-analysis of 42 studies involving over 21,000 adult
Discussion patients, clinically significant depression was diag-
Our study has shown that depression is present in about nosed in 31% of T2DM patients [5]. Comparable re-
one-third of T2DM patients after screening, and depres- sults have also been reported among adult patients
sion was associated with poor glycaemic control. Patients with diabetes in Greece (33.4%) [20], rural Bangladesh
Akpalu et al. BMC Psychiatry          (2018) 18:357 Page 4 of 7
Table 2 Unadjusted logistic regression of depression with socio-demographic and clinical factors
OR (95% CI) Wald’s p
Female gender (Ref: Males) 2.84 (1.67–4.07) 4.59 < 0.001
Age (per 1 year change) 1.303 (0.84–1.68) 1.5 0.13
Duration of diabetes ≥10 years (Ref < 10 yrs) 1.05 (0.81–1.46) 0.32 0.76
Unmarried (Ref: Married) 1.63 (1.05–2.54) 2.17 0.003
Above basic school education (Ref: Basic school) 0.64 (0.4–0.93) 2.07 0.037
Alcohol status (Ref: Never)
Occasional 1.1 (0.66–1.74) 0.39 0.711
Always 5.47 (1.56–13.03) 3.14 0.002
Former Smokers (Ref: Non-smokers) 1.28 (1.05–3.84) 0.75 0.041
BMI (ref: Nornal)
Overweight 1.07 (0.55–2.1) 0.2 0.851
Obese 0.9 (0.47–1.76) 0.3 0.761
Hypertension (ref: Non-hypertensive) 1.13 (0.87–1.85) 0.63 0.536
Insulin use (Ref: Oral Hypoglycaemic drugs) 1.3 (1.18–1.62) 3.24 0.001
Poor glycaemic control (Ref: HbA1c < 7%) 1.82 (1.32–2.48) 3.72 < 0.001
(30%) [21] and in the UK (25%) [22]. In contrast to patients within the range of 19.4% to 30%. [27–29]. De-
our findings, relatively lower prevalence of depression pression in the general population in Ghana was
was found in studies from rural Pakistan (14.7%) [23] reported to be rare decades ago, [30] however, in recent
and Brazil (18.6%) [24], with a much lower rate in years the prevalence has been shown to be comparable
the United States (8.3%) [25]. On the other hand, to that in western countries [30]. The WHO reported a
using different depression assessment tools, higher population-based prevalence of mild depression to be
rates of depression were reported in urban centers in 6.7% among Ghanaian adults > 50 years of age, far
Iran (71.8%) and Pakistan (43.5%) [11, 26]. The wide lower than the findings of the current study [31]. In-
variation in depression across various studies may be deed different studies have reported the prevalence of
attributed to the difference in the socio-cultural back- depression in different Ghanaian populations to be
ground of the participants. In screening for depres- within the range of 3.8 to 9.9% [31–33], and whereas
sion in the various these studies, different assessment 24.5% of patients referred to a psychiatry clinic were di-
tools with varying sensitivity and specificity to detect agnosed with depression [34].
depression were used [16]. In general, the co-existence of diabetes and depression
Very few studies in Africa have evaluated the occur- worldwide has been shown to vary by type of diabetes
rence of depression and its effects among patients with and the socio-economic status of populations studied
diabetes [12]. However available studies from Nigeria [35]. Depression and other psychological problems tend
reported the prevalence of depression among T2DM to be more common in developing countries compared
Table 3 Multivariable regression of depression with marital status, medication adherence and glycaemic control
Unmarried Wald’s (p) Poor glycaemic control Wald’s (p)
Model 1 1.63 (1.15–2.54) 2.42 (0.016) 1.82 (1.32–2.48) 3.72 (< 0.001)
Model 2 1.54 (1.1–2.41) 2.16 (0.031) 1.4 (1.27–2.39) 2.09 (0.037)
Model 3 1.48 (1.09–2.33) 2.02 (0.042) 1.25 (1.17–2.04) 1.98 (0.047)
Model 4 1.46 (1.12–2.31) 2.05 (0.04) 1.04 (0.85–2.29) 0.56 (0.286)
Model 5 1.47 (1.11–2.37) 1.99 (0.046) –
This Table represents multivariable logistic regression analyses with depression status as dependent variable, and either marital status, medication adherence or
glycaemic control as an independent variable in separate models (Model 1). Further adjustments to the models were performed by introducing variables sequentially as
indicated below:
Model 1: Unadjusted
Model 2: Model 1 + age & gender
Model 3: Model 2 + social factors (education, employment, alcohol & smoking status)
Model 4: Model 3 + clinical factors (duration of diabetes, diabetes medication & hypertension)
Model 5: Model 4 + Glycaemic control
Akpalu et al. BMC Psychiatry          (2018) 18:357 Page 5 of 7
with developed countries [36–38]. Possible explanations the ailing spouse to adhere to diabetes medication and
for this observation include higher level of gender self-management practices. Even with married patients,
inequalities, social insecurity, lower level of education, Katz [50] reported that the self-management behavior of
greater level of poverty and financial constraints among husbands with diabetes often deteriorates when conflict
others [37, 38]. Female gender, unmarried status and a exists with their wives. In addition, the belief of a spouse
lower level of education, all of which have socio-eco- in the importance of glycemic control predicts such con-
nomic implications, were associated with depression in trol better than the patient’s beliefs [49]. However, in this
this study. These results are supported by similar find- study, we did not investigate in the quality of intimacy
ings in both the general population [37, 38] as well as in married participants, as well as the beliefs of the
among people with diabetes [22, 39]. spouse on diabetes management practices.
Contrary to various study reports, we did not find sig-
nificant association between poor glycaemic control and Limitation of the study
depression. Some studies have reported that depressed The major limitation of our study is that the results may
T2DM patients have higher HbA1c levels compared not reflect the true burden of depression in the general
with non-depressed individuals [25, 40, 41]. The coexist- T2DM population since patients were selected from a
ence of depression with diabetes has been reported to be specialized tertiary hospital in urban Ghana. Possible
significantly associated with poor glycaemic control [42]. replication of this study in a primary health care setting
However, this association has not been demonstrated in in suburban or rural communities to confirm these
all studies [43]. In systematic reviews and meta-analysis, findings will be vital. Our study did not include non-dia-
depression was found to be weakly correlated with gly- betes controls for comparison, limiting the interpretation
caemic status [44]. In type 1 diabetes patients, the asso- of the possible role of diabetes in depression. Also, being
ciation between depression and glycaemic control exist a cross-sectional study by design, we cannot deduce the
in younger patients, and not in adult patients [45]. The ‘cause-effect’ relationship between diabetes and depres-
findings of our study indicate that, clinical factors like sion from our findings; a longitudinal study design will
diabetes duration, medication and hypertension status be needed to investigate this relationship.
are important factors that link depression to glycaemic
status. It must be noted also that predictors of depres- Conclusions
sion in non-diabetes population in Ghana has not been The findings of our study have shown that depression is
well studied. However, it is worth noting that there is quite common among Ghanaian patients with T2DM.
evidence that remission of depression can result in the Poor glycaemic control was not associated with depres-
improvement of glycaemic control [7]. In addition, sion among T2DM patients in our study. Marriage was
depression is said to impair good self-care practices found to be protective against depression. Future studies
resulting in poor adherence to medication, as well as may investigate the role of quality of marital intimacy
other diabetes management regimens [46]. Diabetes pa- and spousal beliefs on depression.
tients with comorbid depression have been found to
have fewer days adherence to dietary, exercise and self- Abbreviations
HbA1c: Glycated haemoglobin; MMAS: Morisky Medication Adherence Scale;
monitoring recommendations, with a 2.3 fold increased PHQ-9: Patient Health Questionnaire-9; T2DM: Type 2 diabetes mellitus;
odds of missing medication doses compared with those WHO: World Health Organization
without depression [47].
Acknowledgements
The findings of this study indicate that, compared to The authors wish to acknowledge Prof Albert G.B, Amoah, Prof Richard
unmarried participants, currently married participants Adanu and Prof Olugbenga Ogedegbe and his team for their tremendous
had lower risk prevalence of depression. Studies have support before, during and after this project. We also wish to acknowledge the
contributions of Margaret Reynolds and Naa in the acquisition of data.
shown marriage is strongly and positively associated
with psychological well-being for men and women. On Funding
average, the currently married report higher levels of No funding was available for the study.
psychological well-being (measured by lower rates of
Availability of data and materials
depression, substance abuse, and alcoholism) than Data supporting the conclusion of this study is available for systematic review
never-married, divorced, widowed, or separated individ- and meta-analysis upon request.
uals [48, 49]. Spousal support is among the important
Authors’ contributions
sources of psychological fortitude during chronic illness JA was involved in the conception, design, acquisition of data, interpretation
like diabetes, although there is a possibility of disrup- of data and initial drafting of the manuscript. EY participated in conception,
tions in the marital relationship during chronic illness design, acquisition of data and interpretation of data. KY was involved in the
conception, design, analysis and interpretation of data. JAQ participated in
[48]. The importance of marital support in diabetes the conception, design, acquisition of data and interpretation of data.
management might stem from the other spouse helping WB participated in the conception, design and interpretation of data. All
Akpalu et al. BMC Psychiatry          (2018) 18:357 Page 6 of 7
authors critically reviewed the manuscript for important intellectual 15. Adewuya AO, Ola BA, Afolabi OO. Validity of the patient health
content and agreed on the version to be published. questionnaire (PHQ-9) as a screening tool for depression amongst Nigerian
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Competing interests
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The authors declare that they have no competing interests.
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