Received: 15 May 2023 | Revised: 27 July 2023 | Accepted: 17 August 2023
DOI: 10.1002/hsr2.1539
OR I G I NA L R E S E A R CH
The mediating role of quality of life on depression and
medication adherence among patients with type 2 diabetes
mellitus: A cross‐sectional study
Ernest Yorke1 | Vincent Boima1 | Vincent Ganu2 | John Tetteh3 |
Louisa Twumasi4 | George Ekem‐Ferguson4,5,6 | Irene Kretchy4 |
Christopher C. Mate‐Kole4,6,7
1Department of Medicine & Therapeutics,
University of Ghana Medical School, College Abstract
of Health Sciences, University of Ghana, Background and Aim: Patients living with diabetes mellitus have a high burden of
Accra, Ghana
2 psychological distress such as depression and anxiety as well as impaired quality ofDepartment of Medicine and Cardiothoracic
Unit, Korle‐Bu Teaching Hospital, Accra, life, which may negatively impact their adherence to medications, glucose control,
Ghana
and health‐related costs.
3Department of Community Health,
University of Ghana Medical School, College This study assessed the impact of quality of life and depression on medication
of Health Sciences, University of Ghana, adherence among patients with type 2 diabetes (type 2 diabetes mellitus [T2DM]) in
Accra, Ghana
a tertiary care setting in Ghana
4Department of Psychology, University of
Ghana, Accra, Ghana Methods: The study was a cross‐sectional study involving 238 patients with
5National Cardiothoracic Center, Korle Bu diabetes aged 18 years and above. Validated tools were used to assess medication
Teaching Hospital, Accra, Ghana adherence, depressive symptoms, and quality of life. Structural Equation Modeling
6Department of Psychiatry, University of was adopted to examine the mediation effect of quality of life on the relationship
Ghana Medical School, College of Health
Sciences, University of Ghana, Accra, Ghana between depression and medication adherence among participants.
7Center for Ageing Studies, College of Results: The mean age of the participants was 58.82 ± 13.49, and 169 (71.0%) out of
Humanities, University of Ghana
a total of 238 respondents were females. Depression had a significant direct
Correspondence relationship with the quality of life of respondents [aβ (95% confidence interval,
Ernest Yorke, Department of Medicine and CI) = −0.20 (−0.03, −0.00), p < 0.05; −0.21 (−0.41, −0.01) p < 0.05, respectively] and
Therapeutics, School of Medicine and
Dentistry, College of Health Sciences, indirect relationship with quality of life [aβ (95% CI) = −0.01 (−0.02, −0.004)
University of Ghana, Legon, Accra, Ghana. p < 0.001]. Educational status and religion both showed a significant indirect
Email: pavlovium@yahoo.com
relationship with quality of life [aβ (95% CI) = 0.06 (0.07, 0.12), p < 0.05; 0.18 (0.01,
Funding information 0.35) p < 0.05, respectively]. The mediating effect of quality of life on the
Office of Research, Innovation and
Development (ORID) of the University of relationship between depression and medication adherence was significant
Ghana Research Grant, Grant/Award Number: (Sobel = −3.19, p < 0.001).
Award no. UGRF/13/MCG‐002/2019‐ 2020
Conclusion: Depression, medication adherence, and quality of life were higher
among older adults withT2DM. Depression was also found to have a strong negative
association with both medication adherence and quality of life. Interventions to
screen for depression and to improve the quality of life in patients living with
This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any
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© 2023 The Authors. Health Science Reports published by Wiley Periodicals LLC.
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https://doi.org/10.1002/hsr2.1539
2 of 12 | YORKE ET AL.
diabetes are also recommended and this should go beyond the provision of standard
treatments to explore further the mechanisms of this relationships.
K E YWORD S
depression, medication adherence, quality of life, type 2 diabetes
1 | INTRODUCTION
Key points
Diabetes mellitus has reached epidemic proportions globally and in
Africa. The current global prevalence is estimated to be 537 million • Patients living with diabetes mellitus have a high burden
and is projected to reach 783 million by 2045. This will largely be of psychological distress and impaired quality of life,
driven by type 2 diabetes with associated complications expected to which may negatively impact their adherence to medica-
increase.1 tions, glucose control, and health‐related costs.
Adherence to medications relates to the extent to which patients • The study found out that depression had a strong
comply with the prescribed dosing regimen (i.e., the dose and negative association with both medication adherence
intervals that prescribed medications are supposed to be taken).2 In and quality of life.
chronic conditions such as diabetes, because medications must be • Interventions to screen for depression and to improve
taken for a long time, adherence is especially important. The World the quality of life which impact on medication adherence
Health Organization acknowledges medication nonadherence as a in patients living with diabetes are also recommended.
widespread problem in chronic conditions.3 Medication adherence This should go beyond the provision of standard
rates in chronic diseases are estimated between 20% and 80%.3,4 The treatments to explore further the mechanisms of this
causes of medication nonadherence are multifactorial, including relationships.
social, economic, health care system, disease‐specific, medication
specific, and personal factors.4 Moreover, patients living with chronic
diseases such as diabetes mellitus tend to have a high burden of from within and outside the hospital. The daily outpatient attendance
psychological distress such as depression and anxiety as well as is about 80 persons.
impaired quality of life, which in turn may negatively impact their
adherence to medications.5,6
The impact of medication nonadherence is manifold. It may be 2.2 | Study population
associated with increased morbidity and higher rates of mortality in
cardiovascular diseases and diabetes.7 These ultimately lead to increased We recruited patients with type 2 diabetes aged 18 years and above
health‐related costs which impact negatively on the already over- attending NDMRC who had been diagnosed as diabetic and on
burdened resources in developing countries such as Ghana.8,9 Improved medication for at least 6 months. Acutely ill patients, patients who
medication adherence is also associated with improved glycaemic control had known neuropsychiatric illnesses, pregnant women, and those
and less hospitalization for newly diagnosed diabetes patients.10 aged less than 18 years were excluded from the study.
This study examined the impact of quality of life and depression
on medication adherence among type 2 diabetes patients in a tertiary
care setting in Ghana. 2.3 | Sample size calculation
In a recently published study conducted in a similar setting in
2 | MATERIALS AND METHODS northern Ghana, the prevalence of medication nonadherence among
patients with type 2 diabetes was 15.5%.11 The minimum sample size
2.1 | Study design and setting calculated using Cochran's formula (N = z2p(1‐P)/d2) was 201. Where
N—minimum sample size; z—Z score at 95% confidence level = 1.96;
A cross‐sectional study was conducted at the National Diabetes p—prevalence of medication nonadherence in diabetes (15.5%) and
Management and Research Center (NDMRC), Korle‐Bu Teaching d—level of significance = 0.05. Also, in a systematic review of the
Hospital (KBTH), Accra, Ghana. KBTH is a tertiary referral center epidemiology of depression and diabetes, the prevalence of depres-
located in the capital city of Ghana with 1600 bed capacity and 12 sion among over 5000 patients with type 2 diabetes was 11.7%.12
different departments. The NDMRC is the largest Diabetes Center in Computing for the minimum sample size using this prevalence is 159.
Ghana and is a national resource center for diabetes care, training, The larger sample size of 201 was chosen. In all, a total of 238
research and offers out‐patient services. Patients are received both participants were recruited to cater for a 10% nonresponse rate.
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YORKE ET AL. | 3 of 12
2.4 | Sampling technique scores are then normalized to a range of 0–100 by multiplying the
mean score by four according to the WHOQOL‐BREF scoring
A systematic random sampling method was used to recruit patients. manual.17 The scale demonstrated good internal consistency, with
Fifteen patients were selected daily for 4 weeks (16 clinic days) using Cronbach alpha of 0.89 for the whole scale and a Cronbach alpha
a sampling interval of 3. This was done daily except on weekends above 0.70 for all domains except social relationships with a
until all cases were selected. Cronbach alpha of 0.53 among Serbian medical students.18
2.5 | Outcome measures 2.5.4 | Explanatory variables
2.5.1 | Depression The explanatory variables including sociodemographic variables such
as age (≥40 years), gender (male or female), educational status,
Depression was measured using the Brief Symptom Inventory employment status, monthly income (≤GHs 500‐GHs 2000+), marital
Depression subscale (BSI‐DS) of the brief symptom inventory (BSI‐ status, and religion were collected using a pretested questionnaire. A
18). The depression subscale consists of six items from the BSI‐18, an self‐rated questionnaire was used to assess the level of help patients
18‐item self‐report inventory describing three primary dimensions: received from family and friends. Clinical variables such as weight and
somatization (SOMA), anxiety (ANX), depression (DEPR), and the height were measured with a Seca 740 scale and a stadiometer,
Global Scale Global Severity Index (GSI).13 The items are rated on a respectively, and the body mass index (BMI) was computed using the
5‐point scale ranging from 0 (not at all) to 4 (extremely). Loneliness, formula: weight in kilogrammes divided by height in meters squared.
feeling blue, loss of interest, hopelessness about the future, suicidal The BMI scores were categorized as underweight, normal, over-
thoughts, and feelings of worthlessness are rated on the degree of weight, and obese. Blood pressure was measured after a 5min rest
symptoms experienced over the past 2 weeks. The BSI‐DS scores using an automated digital blood pressure monitor (Omron 907XL,
were calculated by summing the scores of the six items and dividing pro Healthcare, Inc.), with the patient seated comfortably with a back
them by six to obtain an average rating that ranges between 0 and 4. support and arms resting on a table.
The subscale cut‐off point of 0.28 or higher indicates the presence of
depressive symptoms.13,14 The BSI‐DS has good internal consistency,
with Cronbach's alpha of 0.87 in a large sample of 2516 2.5.5 | Statistical analysis
nonpatients15 and an alpha that ranged from 0.82 to 0.87 in patients
with Heart failure with and without comorbid renal function.14 Sociodemographic characteristics were summarized in tables by
reporting the proportion and medians. The Skew and kurtosis
coupled with the Shapiro–Wilk test were used to check for normality.
2.5.2 | Medication adherence The Wilcoxon signed rank and Kruskal–Wallis test was used to
compare medians depending on the category of the explanatory
Medication nonadherence was measured using the Medication variable. Quantile regression was used to assess factors associated
Adherence Rating Scale (MARS). MARS is a ten‐item, self‐reported, with the outcomes.
comprehensive scale developed to measure two aspects of medica- In line with the main objective of the study, the mediation
tion nonadherence: the extent or frequency of nonadherence and analysis assumed depression as the exposure outcome while QoL and
reasons for nonadherence.16 For questions 1–6 and 9–10, a no medication adherence were considered as immediate and primary
response is indicative of adherence and is coded as 1, while for outcomes, respectively. Structural equation modeling (SEM) was used
questions 7 and 8, a yes response is indicative of adherence and is to ascertain the mediation effect of QoL on the relationship between
coded as 1. The total MARS score is the sum of 10 items (ranging depression and medication adherence among participants. SEM
from 1 to 10), with higher scores indicating better attention. analysis is a form of path analysis to quantify the relationships
between multiple variables.19,20 The Sobel and Monte Carlo test of
significance was used to test for significant mediation. STATA
2.5.3 | Quality of life software version 16.1 was used to perform all analyses and
p < 0.05 was deemed significant.
The World Health Organization Quality of Life—BREF (WHOQOL‐
BREF) is a self‐report questionnaire that assesses 4 domains of
quality of life (QoL): physical health (7 items), psychological health (6 2.5.6 | Ethical considerations
items), social relationships (3 items) and environment (8 items). In
addition, 2 items measure overall QoL and general health. Items are Ethical approval was obtained from College of Health Sciences
scored on a 5‐point Likert scale which ranges from 1 to 5, and the Ethical and Protocol Review Committee with protocol number (CHS‐
raw domain score is the sum of the respective item scores. All domain Et/M.4‐P4.1/2020‐2021). The study complied with the Helsinki
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4 of 12 | YORKE ET AL.
Declaration on Human Experiments in 1964 (revised in 2000). 120–139mmHg and 45.29 for 140mmHg and above. Further details
Participants were fully informed of the nature of the study. They are set out in Table 1.
were assured that participation in this study was voluntary and that FromTable 2, it was found that being within 60–69 years old and
they are at liberty to withdraw from the study at any time with no 70 years plus were significantly positively related to the quality of life
consequence. COVID‐19 preventive protocols were observed: each as compared to age groups of less or equal to 39 years [aβ (95%
research assistant was involved in data collection and respondents confidence interval, CI) = 0.08 (0.00, 0.15) p < 0.05; 0.08 (0.00, 0.16)
were provided with face masks and alcohol‐based sanitizers and p < 0.05, respectively]. Moreover, being female and single were
interviews and procedures were carried out at the prescribed social positively related to depression as compared to male and married [aβ
distance of at least 1 m. (95% CI) = 0.13 (0.05, 0.20), p < 0.001; 0.13 (0.02, 0.23) p < 0.05,
respectively]. The study further found that being unemployed had a
negative statistically significant relationship with quality of life as
3 | RESULTS compared to respondents who were in full‐time employment [aβ
(95% CI) = −0.11 (−0.16, −0.05) p < 0.001]. Receiving help from at
The mean age of the participants was 58.82 ± 13.49 with 169 out of least three (3) friends was significantly negatively related to
the 258 (71.01%) being females and 69 (29.0%) males. The results medication adherence as compared to receiving no help from friends
(Table 1) showed that 85 (35.86%) of the respondents who were [aβ (95% CI) = −0.08 (−0.15, −0.01) p < 0.05].
depressed, had good quality of life, or adhered to medications were The hypothesized mediating effects of QoL on the relationships
within 60–69 years of age. Moreover, females were more depressed, between depression and medication adherence are presented in the
have good quality of life, and adhered to medications. Majority of the structural equation model displayed in Figure 1. The domains of QoL
respondents were married 148 (62.18%), or attained primary/junior include physical, psychological, social, and environmental. Through
high school (JHS) level of education, 112 (47.06%), and were either these domains, the indirect effect of depression on medication
depressed, had good quality of life, or adhered to medications. In adherence increased with a regression coefficient of 0.024, 0.014,
addition, most of the respondents, 120 (50.42%) were in full‐time 0.13, and 0.14, respectively (model χ2 was 314.94, p < 0.000).
employment (Table 1). A Kruskal–Wallis H test showed that there Meanwhile, the direct effect of depression on medication adherence
was a statistically significant difference in depression and quality of showed a decreased regression coefficient of 0.017 (Figure 1).
life scores between the male and female, [χ2 = 11.06 and 9.32 The results in Table 3 showed that depression and help from
respectively; p < 0.001 each], with a mean depression and quality of friends had a statistically significant negative direct relationship with
life rank score of 42.5, 92 for male and 48.06, 86 for female the quality of life of respondents [aβ (95% CI) = −0.20 (−0.03, −0.00)
respectively. Moreover, the Kruskal–Wallis H test showed that there p < 0.05; −0.21 (−0.41, −0.01) p < 0.05, respectively]. It was further
was a statistically significant difference in depression scores between found that depression had a statistically significant negative indirect
the different marital status scores of married, single, widowed, and relationship with quality of life [aβ (95% CI) = −0.01 (−0.02, −0.004)
divorced [χ2 = 14.55, p < 0.001], with a mean depression rank score of p < 0.001]. On the other hand, educational status and religion both
45.29 for married, 48.06 for single, 50.83 for widowed and 49.44 for showed a statistically significant positive indirect relationship with
divorced. In addition, the Kruskal–Wallis H test showed that there quality of life [aβ (95% CI) = 0.06 (0.07, 0.12) p < 0.05; 0.18 (0.01,
was a statistically significant difference in QOL scores between the 0.35) p < 0.05, respectively]. Overall, depression was found to have a
different educational level scores of no formal education through statistically significant negative relationship with quality of life [aβ
tertiary [χ2 = 8.95, p < 0.05], with a mean quality of life rank score of (95% CI) = −0.03 (−0.05, −0.01), p < 0.001].
88 each for no formal education and SHS/vocational, 86.5 for In addition, the results also showed that the mediating effect of
primary/JHS, and 93.5 for tertiary. quality of life on the relationship between depression and medication
The results further showed that there was a statistically adherence was negatively statistically significant (Sobel = −3.19,
significant difference in depression and GSI scores between the p < 0.001). Furthermore, the Monte Carlo test showed a greater
different employment status scores for full‐time, unemployed, and negative significant value of −3.16 and p < 0.001 of the mediating
retired [χ2 = 10.36, 7.80, and 7.28, p < 0.001]. There was a statistically effect of quality of life on the relationship between depression and
significant difference in QoL score between the different religions of medication adherence.
Christian and Islam [χ2 = 5.67, p < 0.05], with a mean quality of life
rank score of 87 for Christian and 93 for Islam. Moreover, there was a
statistically significant difference in quality‐of‐life scores for the 4 | DISCUSSION
support received from friends with scores of none, 1–2, and 3 or
more [χ2 = 13.78, p < 0.001], with a mean quality of life rank score of This study sought to assess the medication role of quality of life on
87 for none, 83 for 1–2 and 93 for 3 and above. Finally, there was a the association between depression and medication adherence
statistically significant difference in depression score between the among type 2 diabetes patients in Ghana. The findings revealed
different systolic pressure scores [χ2 = 7.54, p < 0.05], with a mean statistically significant median differences in the relationship between
systolic rank score of 50.83 for ≤119mmHg, 48.06 for sociodemographic factors such as sex, marital status, employment,
 23988835, 2023, 9, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1539 by University of Ghana - Accra, Wiley Online Library on [19/09/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
YORKE ET AL. | 5 of 12
TABLE 1 Demographic characteristics and the median difference of psychological domain, quality of life, and medication adherence.
Variable Frequency Depression Quality of life Medication adherence
n (%) Median (LQ, UQ) Median (LQ, UQ) Median (LQ, UQ)
Overall 48.05 (42.52, 56.36) 88 (80, 95) 9 (8, 10)
Age
40–49 53 (22.36) 48.06 (42.52, 53.59) 89 (82, 97) 9 (8, 10)
50–59 52 (21.94) 48.06 (42.52, 59.13) 87 (75, 95) 9 (8, 10)
60–69 85 (35.86) 48.05 (42.52, 56.36) 87 (79, 94) 9 (7, 10)
70+ 47 (19.83) 48.06 (42.52, 56.36) 90 (82, 99) 9 (8, 10)
Test statistic 0.27 5.52 3.56
Sex
Male 69 (28.99) 42.5 (42.52, 50.83) 92 (85, 98) 9 (8, 9)
Female 169 (71.01) 48.06 (42.52, 59.13) 86 (79, 94) 9 (7, 10)
Test statistic 11.06*** 9.32*** 0.07
Marital status
Married 148 (62.18) 45.29 (42.52, 53.59) 89 (81.5, 95.5) 9 (8, 10)
Single 33 (13.87) 48.06 (42.52, 61.90) 86 (79, 94) 9 (8, 10)
Widowed 45 (18.91) 50.83 (42.52, 59.13) 85 (79, 92) 9 (8, 10)
Divorced 12 (5.04) 49.44 (45.29, 60.52) 90.5 (81.5, 95) 9 (8, 10)
Test statistic 14.55*** 3.96 1.10
Educational level
No formal education 25 (10.50) 45.29 (42.52, 50.83) 88 (79, 95) 9 (8, 10)
Primary/JHS 112 (47.06) 49.44 (42.52, 59.13) 86.5 (78, 93) 9 (8, 10)
SHS/vocational 75 (31.51) 45.29 (42.5, 53.59) 88 (81, 96) 9 (8, 10)
Tertiary 26 (10.92) 48.06 (42.52, 53.59) 93.5 (88, 99) 9 (8, 10)
Test statistic 6.72 8.95* 1.97
Employment
Full time 120 (50.42) 48.06 (42.52, 56.36) 88 (80.5, 95.5) 9 (8, 10)
Unemployed 66 (27.73) 48.06 (42.52, 59.13) 86 (79, 94) 9 (8, 10)
Retired 52 (21.85) 42.52 (42.52, 50.83) 89.5 (80.5, 95) 9 (7, 9)
Test statistic 10.36*** 1.67 1.87
Monthly income
less than 500 77 (28.33) 48.06 (42.52, 59.13) 86 (79, 93) 9 (8, 10)
500–900 31 (23.48) 45.29 (42.52, 59.13) 87 (80, 95) 9 (8, 10)
1000–1999 16 (12.12) 48.06 (42.52, 59.13) 91.5 (87, 98) 9 (6, 10)
2000+ 8 (6.06) 48.06 (42.52, 53.59) 94.5 (90.5, 97.5) 9 (8, 9.5)
Test statistic 2.05 9.40 1.64
Religion
Christian 213 (89.50) 48.06 (42.52, 56.36) 87 (79, 95) 9 (8, 10)
Islam 25 (10.50) 48.06 (42.52, 53.59) 93 (90, 98) 9 (8, 10)
Test statistic 0.001 5.67* 0.23
(Continues)
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6 of 12 | YORKE ET AL.
TABLE 1 (Continued)
Variable Frequency Depression Quality of life Medication adherence
Help from friends
None 107 (47.14) 48.06 (42.52, 59.13) 87 (79, 93) 9 (8, 10)
1–2 63 (27.75) 48.06 (42.52, 53.59) 83 (79, 95) 9 (7, 10)
3+ 57 (25.11) 48.06 (42.52, 53.59) 93 (86, 97) 8 (8, 9)
Test statistic 1.88 13.78*** 3.09
Help from family
None 107 (47.14) 48.06 (42.52, 59.13) 87 (79, 93) 9 (8, 10)
1–2 63 (27.75) 48.06 (42.52, 53.59) 83 (79, 95) 9 (7(10)
3+ 57 (25.11) 48.06 (42.52, 53.59) 93 (86, 97) 8 (8, 9)
Test statistic
BMI
Underweight 2 (1.31) 45.29 (42.52, 48.06) 86 (79, 93) 9 (9, 9)
Normal 47 (30.72) 42.52 (42.52, 53.59) 92 (83, 96) 9 (8, 10)
Overweight 53 (34.64) 48.06 (42.52, 56.36) 90 (81, 95) 9 (8, 10)
Obesity 51 (33.33) 45.29 (42.52, 53.59) 88 (83, 95) 9 (8, 10)
Test statistic 3.16 1.51 1.42
Systolic
≤119 45 (19.82) 50.83 (42.52, 56.36) 87 (79, 95) 8 (7, 10)
120–139 88 (38.77) 48.06 (42.52, 59.13) 88 (79, 94.5) 9 (7, 10)
140+ 94 (41.41) 45.29 (42.52, 50.83) 90 (84, 95) 9 (8, 10)
Test statistic 7.54* 3.20 4.58
Diastolic
≤80 114 (50.22) 48.06 (42.52, 56.36) 88.5 (80, 95) 9 (8, 10)
80–89 59 (25.99) 45.29 (42.52, 56.36) 89 (83, 94) 9 (7, 10)
90+ 54 (23.79) 45.29 (42.52, 53.59) 88 (81, 95) 9 (8, 10)
Test statistic 2.39 0.01 0.39
Note: p value notation: *p < 0.05, ***p < 0.001.
Abbreviations: BMI, body mass index; GSI, global severity index; JHS, junior high school; QoL, quality of life; ref, reference category; SHS, senior high
school.
systolic blood pressure, and depression among type 2 diabetes associated with depression among type 2 diabetes mellitus (T2DM)
patients. This finding is congruent with a study that also found marital patients. Surprisingly, the current study found no significant differ-
status to be correlated with depression among type 2 diabetes ences in all sociodemographic factors and medication adherence
patients.21 among type 2 diabetes patients. This is parallel to other studies which
Sociodemographic factors such as sex, educational level, religion, found statistically significant mean differences in some sociodemo-
and help from friends also showed a statistically significant graphic factors and medication adherence amongT2DM patients25,26
relationship with QoL. This finding is partially conforms with a study
that found statistically significant median differences in sex and
educational level but insignificant means for moral and social support 4.1 | Factors associated with depression,
(help from others).22 However, the change in demographic factors quality of life, and medication adherence
such as age, monthly income, help from family, BMI, and diastolic BP
was not statistically significant for both depression and QOL. This is Various factors have been associated with depression, quality of life,
not consistent with other studies that indicate that age, poor and medication adherence among type 2 diabetes patients. Quite
economic status,23 help from family,24 BMI, and diastolic BP are surprisingly, our study found that being between 60 and 69 years old
 23988835, 2023, 9, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1539 by University of Ghana - Accra, Wiley Online Library on [19/09/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
YORKE ET AL. | 7 of 12
TABLE 2 Quantile regression showing factors associated with depression, quality of life, and medication adherence.
Variable Depression QoL Medication adherence
aβ [95% CI] aβ [95% CI] aβ [95% CI]
Age
≤39 Ref ref ref
50–59 0.03 [−0.05, 0.11] 0.04 [−0.03, 0.12] 0.01 [−0.08, 0.09]
60–69 0.03 [−0.06, 0.13] 0.08 [0.00, 0.15]* −0.01 [−0.10, 0.08]
70+ −0.05 [−0.17, 0.06] 0.08 [0.00, 0.16]* 0.01 [−0.09, 0.11]
Sex
Male Ref ref ref
Female 0.13 [0.05, 0.20]*** −0.02 [−0.05, 0.02] −0.02 [−0.08, 0.05]
Marital status
Married Ref ref ref
Single 0.13 [0.02, 0.23]* 0.02 [−0.04, 0.08] 0.01 [−0.09, 0.10]
Widowed 0.02 [−0.06–0.11] 0.02 [−0.02, 0.06] 0.02 [−0.05, 0.09]
Divorced 0.07 [−0.07–0.20] −0.02 [−0.08, 0.05] 0.00 [−0.19, 0.20]
Educational level
No formal education Ref ref ref
Primary/JHS 0.03 [−0.05, 0.11] −0.03 [−0.11, 0.05] −0.08 [−0.17, 0.00]
SHS/vocational 0.01 [−0.08, 0.10] 0.03 [−0.04, 0.10] −0.01 [−0.09, 0.09]
Tertiary 0.09 [−0.05, 0.24] 0.07 [−0.01, 0.14] −0.01 [−0.10, 0.09]
Employment
Full time Ref ref ref
Unemployed 0.06 [−0.02, 0.13] −0.11 [−0.16, −0.05]*** 0.03 [−0.04, 0.00]
Retired 0.01 [−0.09, 0.09] −0.03 [−0.08, 0.02] 0.03 [−0.05, 0.11]
Religion
Christian Ref ref ref
Islam 0.07 [−0.01, 0.15] −0.03 [−0.08, 0.02] 0.07 [−0.02, 0.15]
Help from friends
None ref ref ref
1–2 −0.03 [−0.09, 0.03] 0.02 [−0.03, 0.07] −0.2 [−0.09, 0.05]
3+ −0.01 [0.08, 0.06] −0.01 [−0.05, 0.03] −0.08 [−0.15, −0.01]*
BMI
Underweight ref ref ref
Normal 0.11 [−0.06, 0.28] −0.01 [−0.15, 0.12] −0.01 [−0.10, 0.08]
Overweight 0.16 [−0.01, 032] −0.01 [−0.14, 0.12] −0.02 [−0.11, 0.07]
Obesity 0.13 [−0.04, 0.31] −0.03 [−0.16, 0.11] −0.02 [−0.12, 0.08]
Systolic
≤119 ref ref ref
120–129 0.07 [−0.02, 0.16] −0.01 [−0.06, 0.04] 0.01 [−0.07, 0.01]
130+ −0.001 [−0.10, 0.09] −0.02 [−0.16, 0.11] 0.06 [−0.04, 0.15]
(Continues)
 23988835, 2023, 9, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1539 by University of Ghana - Accra, Wiley Online Library on [19/09/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
8 of 12 | YORKE ET AL.
TABLE 2 (Continued)
Variable Depression QoL Medication adherence
Diastolic
≤80 ref ref ref
81–89 −0.03 [−0.12, 0.05] 0.01 [−0.03, 0.05] −0.04 [−0.12, 0.03]
90+ −0.03 [−0.11, 0.05] 0.01 [−0.04, 0.06] −0.01 [−0.09, 0.07]
Note: p value notation: *p < 0.05, ***p < 0.001.
Abbreviations: aβ, adjusted coefficient estimate; BMI, body mass index; CI, confidence interval; JHS, junior high school; QoL, quality of life; ref, reference
category; SHS, senior high school.
F IGURE 1 Path analysis showing the mediating effect of quality of life on the relationship between depression and medication adherence.
Dep: Depression; Med‐Adh: Medication Adherence; Phy: Physical; Psy: Psychological; Env: Environmental; Soc: Social; QoL: Quality of Life.
and 70 years plus was significantly positively related to quality of life be other confounding variables such as access to social support
amongT2DM as compared to age groups of less or equal to 39 years. networks, resilience, and coping that may influence that association
This implies that as patients with T2DM grew older, their quality of which was not explored in the current study.28
life significantly improves. This finding is inconsistent with other Moreover, being female and single were positively related to
studies which found that older age, poor glycaemic control, longer depression as compared to male and married. This implies that being
duration of diabetes, insulin usage, obesity, and having diabetes‐ female and single increases depression among T2DM patients. This
related complications were significant negative predictors of QoL.27 finding is consistent with another study that found that depression
Similarly, another study by Gebremedhin et al.26 also found an was high among females29 and singles.30 Similarly, Akpalu et al.31 also
inverse association among age, disease duration, and fasting glucose found in their study among Ghanaian patients withT2DM that female
level, and all levels of QoL among patients. These variations may be gender, being unmarried, frequent intake of alcohol, previous
because older patients may not be burdened with family responsibili- smoking status, and insulin use were associated with increased odds
ties or aspire for better career opportunities compared to younger of depression. The findings of the current study, however, are
patients who have large responsibilities of building families and incongruent with another study among T2DM patients in Qatar
having career aspirations in addition to their health conditions. Their which found that male patients were at higher risk for developing
inability to actively perform these functions may trigger sequelae of depression when compared to females.32 Asefa33 and colleagues also
depressive symptoms that affect their quality of life. Again, there may reported that being male and single was associated with increased
 23988835, 2023, 9, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1539 by University of Ghana - Accra, Wiley Online Library on [19/09/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
YORKE ET AL. | 9 of 12
TABLE 3 Direct, indirect, and total effects of QoL on the relationship between depression and medication adherence.
Effect size
Endogenous variable Exogenous Direct Indirect Total
Quality of life aβ [95% CI] aβ [95% CI]
Depression −0.20 [−0.03, ‐0.00]* −0.01 [−0.02, −0.004]** −0.03 [−0.05, −0.01]**
Age −0.03 [−0.19, 0.13] −0.001 [−0.04, 0.03] −0.04 [−0.20, 0.13]
Sex 0.10 [−0.30, 0.49] −0.07 [−0.16, 0.02] 0.03 [−0.38, 0.43]
Marital status −0.01 [−0.19, 0.17] 0.002 [−0.36, 0.04] −0.01 [−0.19, 0.17]
Education −0.13 [−0.35, 0.08] 0.06 [0.07, 0.12]* −0.07 [−0.29, 0.15]
Employment 0.10 [−0.05, 0.26] −0.02 [−0.05, 0.02] 0.09 [−0.07, 0.24]
Religion 0.13 [−0.56, 0.83] 0.18 [0.01, 0.35]* 0.31 [−0.40, 1.02]
Help from −0.21 [−0.41, ‐0.01]* 0.01 [−0.03, 0.06] −0.20 [−0.40, 0.01]
BMI 0.09 [−0.12, 0.30] −0.003 [−0.05, 0.04] 0.08 [−0.13, 0.30]
Systolic BP −0.08 [−0.36, 0.20] 0.06 [−0.01, 0.13] −0.02 [−0.30, 0.26]
Diastolic BP −0.06 [0.31, 0.19] −0.04 [−0.10, 0.04] −0.10 [−0.36, 0.15]
Test of significance
Sobel −3.19**
Monte Carlo −3.16**
Note: p value notation: *p < 0.05, **p < 0.01.
Abbreviations: aβ, adjusted coefficient estimate; BMI, body mass index.
odds of depression among DM patients whereas Mushtaque et al.34 that T2DM patients received social support from family and
found no significant association between depression, gender, and significant others but not friends. Social Support buffered the
marital status. These differences can be attributed to the assessment relationship between depression and T2DM, which indirectly have
tools used and the different populations assessed. an association with medication adherence.24
Unsurprisingly, our study further found that being unemployed
had a negative statistically significant relationship with quality of life
as compared to respondents who were in full‐time employment. This 4.2 | Mediating role (direct, indirect, and total
is consistent with another study which found that females, patients effects) of QoL on the relationship between
above 75 years old, and those who are in low socioeconomic income, depression and medication adherence
unemployed, and widowed had lower QOL.22 Having diabetes and
being unemployed may trigger some psychosocial challenges, The study found that depression had both direct and indirect effects
especially among younger adults, which can affect your QOL. The on medication adherence. The indirect effect of depression on
inability to afford medical bills because of financial difficulties may medication adherence showed an increase in the regression model,
affect treatment adherence and ultimately increase the risk of while the direct effect of depression on medication adherence
complications and reduced QOL. showed a decrease in the regression model. Interestingly, this implies
Receiving help from at least three (3) friends was significantly that the indirect effect of depression leads to an improvement in
negatively related with medication adherence as compared with medication adherence, whereas the direct effect has a negative
receiving no help from friends. This finding supports findings from impact on medication adherence. This finding is in line with other
another study that reported that social support presented a studies that have found that depression contributes negatively to
positive effect on medication adherence, and that support medication adherence among patients with T2DM.5,36 Similarly, in a
utilization and the subscale of social support exhibited a study to assess the impact of incident depression on medication
significantly strong influence on medication adherence in patients adherence in patients with T2DM, Lunghi et al.37 found that
with T2DM. Although medication adherence was influenced by depression was associated with nonadherence to antidiabetic
multiple factors, this finding confirmed that social support must be medications after accounting for baseline adherence and other
recognized as a core element in interventions aimed at improving confounders. Loss of interest in activity, forgetfulness, and low
the management of patients with T2DM.35 Contrary to this, in a energy levels which are associated with depression could explain
related study in Ghana, Ekem‐Ferguson24 and colleagues found these findings.
 23988835, 2023, 9, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1539 by University of Ghana - Accra, Wiley Online Library on [19/09/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
10 of 12 | YORKE ET AL.
The results showed that help from friends had a statistically quality of life such as resilience, coping, self‐care behaviors, and self‐
significant negative direct relationship with the quality of life of efficacy, which were not explored in the current study and may have
respondents. It was further found that depression had a statistically improved our model to better explain the mediators.
significant negative indirect relationship with quality of life. Overall,
depression was found to have a statistically significant negative
relationship with quality of life. This finding is not surprising as it is 4.4 | Implications and future directions
consistent with findings from a systematic review that reported a
negative association between depressive symptoms and at least one The higher prevalence of depression and medication nonadherence
aspect of quality of life in people with diabetes.38 Diabetic individuals among older T2DM patients calls for a change in the approach to
with depressive symptoms also had a severely lower diabetes‐specific managing these patients. Clinicians should consider routinely
quality of life. Generic and domain‐specific quality of life were found to screening for psychological disorders and distress among these
be mildly to moderately lower in the presence of depressive symptoms.39 group of patients. Patients must be educated to recognize early, the
Another study also observed that depression was the major factor that symptomatology of these conditions and seek timeous treatment.
decreased the quality of life in patients with diabetes.40 Policy makers must be engaged to support these initiatives and also
On the other hand, educational status and religion both showed a provide the necessary resources to support these initiatives.
statistically significant positive indirect relationship with the quality We recommend that future researchers should consider the use
of life of T2DM patients. This finding is consistent with other studies of Online Photovoice (OPV) as a qualitative or part of a mixed
which report similar findings that patients with higher levels of method approach to conduct research on the same or similar topics
education may have an appreciable knowledge of their health and are to explore the interrelationships between depression, medication
more likely to follow through on their medication regimen and self‐ adherence, physical health, psychological health, social support, and
care behaviors hence the improved QOL.41,42 Similarly, religiosity or other environmental factors among persons living with T2DM.45–47
spirituality has been reported to be a valuable tool for coping with OPV is emerging as one of the most recent and effective innovative
chronic illness conditions and has been associated with positive qualitative research methods. It gives opportunities to the partici-
health outcomes. In line with our finding, a study performed on pants to express their own experience with as little manipulation as
Iranian patients with T2DM revealed a positive association between possible, compared to traditional quantitative methods. Educators
the components of health‐related QOL and spirituality, with patients can also use OPV for experiential activities to increase group and
who have higher levels of spiritual well‐being showing better QOL.43 organizational synergy and improve the mental and psychological
In addition, the results also showed that quality of life played a health of T2DM patients.45–47
mediating role and had a negative relationship with both depression and
medication adherence. Thus, quality of life significantly reduced the
effect of depression on medication adherence, which may improve 5 | CONCLUSION
treatment outcomes. Previous studies have investigated the potential
factors affecting depression and medication adherence among type 2 In this study, we showed that depression, medication adherence, and
diabetes patients and reported the need for an intervention to improve quality of life were high among older adults with T2DM and poorer
quality of life beyond the provision of standard treatments and explore for younger adults. Again, depression was found to have a strong
further the mechanisms of this relationship. negative association with both medication adherence and quality of
Seligowski44 and colleagues explored the relationship between life. There is a need for thorough screening for early detection and
the fear of hypoglycemia and psychological well‐being in veterans management of depressive symptoms as part of protocols for the
with type 2 diabetes. Using the mediation effect of specific health‐ management of diabetes, particularly among younger adults. Quality
related quality of life (HRQoL), they found significant indirect effects of life was seen as a mediating factor that improved the rate of
on the relationship between depressive symptoms and diabetes medication adherence among T2DM patients with depression. There
quality of life and between anxiety symptoms and diabetes quality of is a need for an intervention to improve the quality of life in patients
life. However, the mediating role of QoL on depression and with diabetes beyond the provision of the standard treatment and
medication adherence has scarcely been explored. Our finding is explore further the mechanisms of this relationship.
therefore novel, hence the need to explore further the mechanisms
through which these associations operate in future studies. AUTHOR CONTRIBUTIONS
Ernest Yorke: Conceptualization; Data curation; Formal analysis;
Funding acquisition; Investigation; Methodology; Project administra-
4.3 | Limitations tion; Resources; Supervision; Validation; Visualization; Writing—
original draft; Writing—review & editing. Vincent Boima: Concep-
The current study was a cross‐sectional study, hence may not draw tualization; Data curation; Formal analysis; Investigation; Methodol-
conclusions based on cause‐and‐effect relationships. Again, there may ogy; Project administration; Resources; Supervision; Writing—review
be other factors associated with depression, medication adherence, and & editing. Vincent Ganu: Conceptualization; Data curation; Funding
 23988835, 2023, 9, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1539 by University of Ghana - Accra, Wiley Online Library on [19/09/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
YORKE ET AL. | 11 of 12
acquisition; Investigation; Methodology; Resources; Supervision; 4. DiMatteo MR. Variations in patients’ adherence to medical
Validation; Visualization; Writing—review & editing. John Tetteh: recommendations: a quantitative review of 50 years of research.
Med Care. 2004;42(3):200‐209. doi:10.1097/01.mlr.0000114908.
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Project administration; Resources; Supervision; Validation; Visualiza- Maciel‐Hernández EA. Anxious depression in patients with type 2
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tion; Resources; Supervision; Validation; Visualization; Writing— 9. Ho PM, Magid DJ, Masoudi FA, McClure DL, Rumsfeld JS.
review & editing. Adherence to cardioprotective medications and mortality among
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ACKNOWLEDGMENTS
10. Lin L‐K, Sun Y, Heng BH, Chew DEK, Chong P‐N. Medication
We are exceedingly indebted to all participants who made time to adherence and glycemic control among newly diagnosed diabetes
participate in this study. The study could not have been accomplished patients. BMJ Open Diabetes Res Care. 2017;5(1):e000429. doi:10.
without their participation. This work was supported by the Mid‐ 1136/bmjdrc-2017-000429
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