
==== Front
Medicine (Baltimore)
Medicine (Baltimore)
MD
Medicine
0025-7974
1536-5964
Lippincott Williams & Wilkins Hagerstown, MD

39029074
MD-D-23-10846
00076
10.1097/MD.0000000000038868
3
6200
Research Article
Observational Study
Assessment of depression in children and adolescents with Type 1 diabetes mellitus: Impact and intervention strategies
https://orcid.org/0000-0002-9103-602X
Alqahtani Youssef A. MD a*
https://orcid.org/0000-0003-0444-5595
Shati Ayed A. MD a
Alhawyan Fatimah S. MD b
Alhanshani Ahmad A. MD a
Al-Garni Abdulaziz M. MD c
Al-Qahtani Saleh M. MD a
Alshehri Mohammed A. MD a
a Department of Child Health, College of Medicine, King Khalid University, Abha, Saudi Arabia
b Department of Internal Medicine, Armed Forces Hospital Southern Region, Khamis Mushayt, Saudi Arabia
c Department of Internal Medicine, College of Medicine, King Khalid University, Abha, Saudi Arabia.
* Correspondence: Youssef Ali Alqahtani, Department of Child Health, College of Medicine, King Khalid University, Abha, Saudi Arabia (e-mail: Yal-qahtani@kku.edu.sa).
19 7 2024
19 7 2024
103 29 e3886804 12 2023
03 6 2024
19 6 2024
Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

Depression is a common comorbidity in children and adolescents with type 1 diabetes mellitus (T1DM), yet its prevalence, impact, and intervention strategies remain underexplored. This study aims to assess the prevalence of depression among children and adolescents with T1DM, investigate its impact on health outcomes, and explore potential intervention strategies. A convenient sampling method was employed to recruit 229 participants aged 6 to 18 years from a single center. Data collection involved validated assessments, demographic surveys, and diabetes-related factor examinations during routine clinic visits. The patient health questionnaire-9 was utilized to evaluate the severity of depressive symptoms. Associations between depression and sociodemographic variables, diabetes management factors, and health behaviors were analyzed using chi-squared tests and logistic regression analysis. The prevalence of depression among participants was 43.23%. Older age, lower parental education levels, lower household income, smoking, and comorbidities were identified as significant risk factors for depression. Associations were found between depression and diabetes management factors, including glycemic control and frequency of glucose monitoring. Depression is highly prevalent among children and adolescents with T1DM and is associated with sociodemographic factors, health behaviors, and diabetes management. Integrated approaches to care that address both physical and mental health aspects are crucial for improving outcomes in this population.

depression
type 1 diabetes
children
adolescents
prevalence
OPEN-ACCESSTRUE
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pmc1. Introduction

Type 1 diabetes mellitus (T1DM) is an autoimmune disease that is chronic and lifelong, typically detected in childhood or adolescence. It is characterized by the death of cells that produce insulin and necessitates lifelong insulin management.[1] The significant psychological burdens that children and adolescents with type 1 diabetes must bear are becoming increasingly recognized, despite the well-documented physical difficulties associated with the condition.

A distinct vulnerability to mental health issues, especially depression, is created by the combination of chronic illness, the need for self-care, and the natural psychosocial stressors of adolescence.[2] Due to the paucity of research in this area, a critical knowledge gap regarding the prevalence and consequences of depression in children and adolescents with T1DM needs to be filled in order to fully understand this population’s holistic well-being.

Depression, when co-occurring with T1DM, extends beyond the typical challenges associated with chronic illness and can impede adherence to treatment, compromise glycemic control, and diminish overall quality of life.[3,4] This study aims to systematically assess the prevalence of depression in this population, delve into its impact on mental health, and explore intervention strategies to alleviate the psychological burden.

The Centres for Disease Control and Prevention released a report in 2013 that emphasized the critical role that mental health plays in young school-age children’s well-being.[5] It has been demonstrated that among children between the ages of 6 and eleven, diagnosed mental disorders rank among the most common chronic health conditions. Parent reports indicated that 4.3% of children had been diagnosed with anxiety disorder, 2.9% with phobias or fears, 2.3% with depression, and 8.4% of children with attention-deficit hyperactivity disorder (ADHD).[5]

Kids’ risk of developing depression sharply increases during adolescence.[6] Of the adolescents aged 13 to 18, 11.7% fulfilled the criteria for a lifetime major depressive disorder or dysthymia in the US National Comorbidity Survey (NCS)-Adolescent Supplement from 2001 to 2004.[6] Before the FDA’s 2003 black-box warning, reports of rising adolescent use of antidepressant medications concerning rising adolescent depression prevalence have been raised,[7] and indirect evidence of increased lifetime prevalence of major depressive disorder in successive birth cohorts.[8]

Age-related variations and heterogeneity in the metabolic, genetic, and immunogenetic aspects of T1DM necessitate a customized strategy for every patient. Insulin secretion loss may happen suddenly or gradually. While diabetic ketoacidosis is more common in young people with T1DM, residual insulin production (detectable or higher c-peptide) is more common in adults with T1D than in children.[9] Greater glycemic control is linked to detectable c-peptides.[10] Variables include the emergence of complications related to diabetes such as depression, obesity, comorbidities, and the existence of additional autoimmune diseases.[11] This study seeks to advance our understanding of depression in children and adolescents with T1DM by assessing its prevalence, impact, and intervention strategies. By identifying effective interventions, healthcare providers can better support the mental health and well-being of children and adolescents with T1DM, ultimately improving their overall health outcomes and quality of life.

2. Methods

2.1. Study design and participants

This single-center study was conducted at Diabetic Centre Clinics in Abha, Saudi Arabia. Participants were recruited using a convenient sampling method from the pediatric diabetes clinic at the institution. The sample included children and adolescents aged 6 to 18 years diagnosed with type 1 diabetes mellitus according to the established criteria.

2.2. Data collection

Data collection involved administering validated assessments, demographic surveys, and diabetes-related factor examinations during routine clinic visits. The following tools and instruments were utilized:

The patient health questionnaire-9 (PHQ-9) was employed to evaluate the severity of depressive symptoms. The PHQ-9 has been validated for use in adolescents aged 12 to 18 years; however, for participants below 12 years old, a modified version suitable for younger age groups was utilized. The questionnaire was administered in Arabic, with a validated translation ensuring linguistic and cultural appropriateness.

A structured demographic survey was utilized to collect information on participants’ age, gender, socioeconomic status, and family medical history. The survey was available in both Arabic and English and was adapted from previously validated instruments.

Additional measures included assessments of glycemic control using hemoglobin A1c (HbA1c) levels, blood glucose monitoring methods (continuous glucose monitoring system, CGM), presence of eating disorders, and quality of life metrics. These measures were obtained through medical records review and participant self-report.

2.3. Statistical analysis

Descriptive statistics were used to summarize the demographic and clinical characteristics of the study sample. The prevalence of depressive symptoms was calculated based on the PHQ-9 scores, with scores ≥ 10 indicating moderate to severe depression. Bivariate and multivariate analyses were conducted to explore associations between depressive symptoms and diabetes-related factors. All statistical analyses were performed using SPSS 22.0, with significance set at P < .05.

2.4. Ethical considerations

This study was approved by the Institutional Review Board (IRB) at King Khalid University. Informed consent was obtained from all participants and their legal guardians prior to enrollment in the study. Confidentiality and anonymity of participants’ data were ensured throughout the study.

2.5. Limitations

Limitations of this study include its cross-sectional design, which precludes causal inferences, and the use of a convenient sampling method, which may limit the generalizability of the findings. Additionally, the reliance on self-report measures for assessing depressive symptoms and other variables may introduce response bias. Furthermore, the study’s single-center nature may limit the diversity of the study population and the generalizability of the findings to other settings.

3. Results

3.1. Participant characteristics

Table 1 presents the demographic characteristics of the participants. The sociodemographic characteristics of the sample population revealed that 55.02% of participants are between the ages of 6 and 11 years, while 44.98% are between the ages of 12 and 18 years; 56.33% of participants are female, and 43.67% of participants are male; parental education varies, with the highest percentage having a secondary school education (18.78%); most participants earn an average monthly income of between SR10,000 and SR15,000 (36.24%); there are a variety of comorbidities, with the most common one being arthritis (19.21%); the distribution of glucose levels over the previous 3 months is varied; 36.24% of participants use an insulin pump, 34.57% use an insulin injection, and 29.26% use other treatments.

Table 1 Demographic characteristics of participants.

Sociodemographic variables	N	%	
Age (yr)	6 to 11	126	55.02	
12 to 18	103	44.98	
Gender	Female	129	56.33	
Male	100	43.67	
Parent educational qualification
	PhD degree	40	17.47	
Master’s degree	33	14.41	
Bachelor’s degree	34	14.85	
Diploma	38	16.59	
Secondary school	43	18.78	
Below Secondary school	41	17.9	
Parent average monthly income (SR)	More than 15,000	56	24.45	
10,000 to 15,000	83	36.24	
5000 to 10,000	37	16.16	
<5000	53	23.14	
Health Issues	Smoking	51	22.27	
Nonsmoking	78	34.06	
Ex-smoker	100	43.67	
Comorbidity	Hypertension	34	14.85	
Cardiac conditions	35	15.28	
Arthritis	44	19.21	
Asthma	31	13.54	
	Autoimmune disease	30	13.1	
None	28	12.23	
Other	27	11.79	
Glucose level over the past 3 mo	>12	41	17.9	
8 to 12	47	20.52	
6 to 8	64	27.95	
<6	77	33.62	
DM treatment	Insulin injection	79	34.5	
Insulin pump	83	36.24	
Other	67	29.26	
Total		229	100	
N: frequency; %: percentage.

3.2. Prevalence of depressive symptoms

Table 2 and Figure 1 show the prevalence of depression among children and adolescents diagnosed with T1DM. There is a considerable percentage of the sample population that is depressed, with 43.23% of study participants having depression and 56.77% not exhibiting any signs of depression. This underscores the significance of mental health considerations in the context of the study.

Table 2 Prevalence of depression among children and adolescents diagnosed with T1DM.

Depression	N	%	
Has depression	99	43.23	
Has no depression	130	56.77	

Figure 1. Prevalence of depression among study participants. This figure illustrates the percentage of study participants exhibiting depression (43.23%) versus those not showing signs of depression (56.77%). The high prevalence underscores the importance of mental health considerations in this population.

3.3. Associations with sociodemographic variables

Table 3 displays the associations between depression and sociodemographic variables. The chi-squared test was used to assess the association between each variable and the presence of depression. The results indicate that there is no significant association between gender and depression (P value = 0.7329). However, significant associations were found between depression and age (P value = 8.3055e − 20), parental education (P value = 2.3316e − 19), and average monthly income (P value = 2.1370e-23). These findings suggest that age, parental education, and average monthly income may be influential factors in understanding and addressing depression in the study population.

Table 3 Association between depression and sociodemographic variables.

Variable	Has depression	Chi-squared test	P value	
Yes	No	
Gender
	Female	54	75	0.1164	.7329	
Male	45	55	
Age	1 to 11	20	106	82.9760	8.3055e − 20	
12 to 18	79	24	
Parent educational qualification	PhD degree	4	36	96.9401	2.3316e − 19	
	Master’s degree	9	24	
	Bachelor’s degree	6	28	
	Diploma	9	29	
Secondary school	33	10	
Below Secondary school	38	3	
Parent average monthly income	More than 15,000	8	48	108.6547	2.1370e − 23	
10,000 to 15,000	14	69	
5000 to 10,000	33	4	
<5000	44	9			

3.4. Association between depression and diabetes and other health-related factors

Table 4 presents the association between depression and diabetes-related and other health-related factors. A marginally significant correlation has been found between DM treatment and depression (P value = .0992), indicating a potential relationship. A strong correlation has been observed between the last 3 months’ HbA1c levels and depression (P value = 2.3284e − 22), suggesting that certain HbA1c levels may predispose people to depression. Depression and health problems, especially smoking, are significantly correlated (P value = 5.4987e − 22). Comorbidities like autoimmune disease, hypertension, heart problems, arthritis, asthma, and none or others, however, do not significantly correlate with depression (P value > .05). These results point to particular health indicators or risk factors for depression in the population under study.

Table 4 Association between depression and diabetes and other health-related factors.

Variable	Has depression	Chi-squared test	P value	
Yes	No	
DM treatment
	Insulin injections	41	38	4.6203	.0992	
Insulin pump	35	48	
Other	23	44	
HbA1c level (Last 3 mo)	>12	35	6	103.8334	2.3284e − 22	
8 to 12	40	7	
6 to 8	14	50	
<6	10	67	
Health issues	Smoking	47	4	97.9047	5.4987e − 22	
Nonsmoking	15	63	
Ex-smoker	37	63	
Comorbidity	Hypertension	16	18	4.8779	.5595	
Cardiac conditions	14	21	
Arthritis	20	24	
Asthma	13	18	
Autoimmune disease	9	21	
None	16	12	
Other	11	16	

3.5. Logistic regression analysis of various factors and health behaviors/conditions in children and adolescents with T1DM

Table 5 provides the results of logistic regression analysis examining various factors and health behaviors/conditions associated with depression among children and adolescents with T1DM. Significant associations were found for several factors, including unhealthy habits, household income, educational level, and glucose level over the past 3 months. These results provide information about how various variables relate to particular health outcomes within the population under study.

Table 5 Logistic regression analysis of various factors and health behaviors/conditions in children and Adolescents with T1DM.

Variable	Reference level	Comparison level	P value	Odds ratio	95% Confidence interval	
Unhealthy habits (Ref: ex-smoker)	Ex-smoker	Nonsmoker	.0155	2.4543	[1.1766, 5.3216]	
Unhealthy habits (Ref: ex-smoker)	Ex-smoker	Smoker	3.4108e − 10	0.0510	[0.0124, 0.1556]	
Average monthly household income (Ref: SR10,000–SR15,000)	SR10,000 to SR15,000	SR5,000 to SR10,000	3.0355e − 13	0.0258	[0.0057, 0.0876]	
Average monthly household income (Ref: SR10,000–SR15,000)	SR10,000 to SR15,000	>SR15,000	.8633	1.2157	[0.4353, 3.6215]	
Average monthly household income (Ref: SR10,000–SR15,000)	SR10,000 to SR15,000	<SR5,000	1.0907e − 13	0.0430	[0.0148, 0.1126]	
Educational level (Ref: Bachelor’s degree)	Bachelor’s degree	Master’s degree	.5145	0.5762	[0.1459, 2.1214]	
Educational level (Ref: Bachelor’s degree)	Bachelor’s degree	PhD degree	.5367	1.9114	[0.4077, 10.1405]	
Educational level (Ref: Bachelor’s degree)	Bachelor’s degree	Secondary school	8.6047e − 07	0.0680	[0.0176, 0.2252]	
Educational level (Ref: Bachelor’s degree)	Bachelor’s degree	Diploma	.7346	0.6940	[0.1781, 2.5220]	
Educational level (Ref: Bachelor’s degree)	Bachelor’s degree	Less than secondary school	2.3911e − 10	0.0186	[0.0028, 0.0846]	
When were you diagnosed with T1DM (Ref: after reaching 18 years old)	After reaching 18 years old	Before reaching the age of 18	.9406	0.9063	[0.3984, 2.0127]	
Sex (Ref: feminine)	Feminine	Male	.7330	0.8805	[0.5025, 1.5428]	
Cumulative glucose level over the past 3 mo (Ref: 6–8)	6 to 8	8 to 12	1.6215e − 10	0.0509	[0.0156, 0.1449]	
Cumulative glucose level over the past 3 mo (Ref: 6–8)	6 to 8	>12	7.2038e − 10	0.0499	[0.0141, 0.1499]	
Cumulative glucose level over the past 3 mo (Ref: 6–8)	6 to 8	<6	.2408	1.8675	[0.7049, 5.1225]	
Frequency of daily glucose testing (Ref: Frequently)	Frequently	Never	1.1775e − 10	0.0486	[0.0147, 0.1409]	
Frequency of daily glucose testing (Ref: Frequently)	Frequently	Seldomly	1.0788e − 13	0.0314	[0.0089, 0.0930]	
Frequency of daily glucose testing (Ref: Frequently)	Frequently	Sometimes	.6075	1.4164	[0.5141, 4.0679]	
What do you use to treat diabetes (Ref: Insulin injection)	Insulin injection	Insulin pump	.2788	1.4761	[0.7602, 2.8834]	
What do you use to treat diabetes (Ref: Insulin injection)	Insulin injection	Other	.0494	2.0537	[1.0033, 4.2715]	
The age (Ref: 6–11)	6 to 11	12 to 18	8.3055e − 20	0.0583	[0.0280, 0.1163]	

4. Discussion

The current study aimed to assess the prevalence of depression in children and adolescents with type 1 diabetes (T1D), explore its impact, and discuss intervention strategies. The findings revealed a concerning prevalence rate of depression among this population, with 43.23% of participants meeting the criteria for depression according to standardized assessments. This prevalence aligns with previous research indicating elevated rates of depression in youth with T1D.[12,13] Additionally, a significant association between depression and various sociodemographic factors, such as parental educational qualification and household income were observed, consistent with prior studies.[14,15]

The impact of depression on glycemic control and diabetes management cannot be overstated. This study found a significant association between depression and higher HbA1c levels, indicating poorer glycemic control among depressed individuals. This finding corroborates the results of longitudinal studies highlighting the bidirectional relationship between depression and glycemic control in youth with T1D.[16,17] Moreover, logistic regression analysis conducted identified several factors and health behaviors associated with depression, including unhealthy habits, household income, educational level, and frequency of glucose testing, underscoring the multifaceted nature of depression in this population.[18,19]

Intervention strategies for addressing depression in children and adolescents with T1D are essential for improving both mental health outcomes and diabetes management. This research findings underscore the importance of implementing targeted interventions, such as cognitive-behavioral therapy (CBT), mindfulness-based interventions, and family-based approaches, to address depression and enhance coping skills among youth with T1D.[20] Collaborative care models that integrate mental health services into routine diabetes care have also shown promise in improving depression outcomes and diabetes-related outcomes simultaneously.[21]

This study highlights the high prevalence of depression among children and adolescents with T1D and its significant impact on glycemic control and health outcomes. By identifying sociodemographic factors associated with depression and elucidating potential intervention strategies, our findings contribute to the development of targeted interventions aimed at improving mental health and diabetes management in this vulnerable population.

5. Conclusion

The current study provides valuable insights into the prevalence, impact, and intervention strategies for depression among children and adolescents diagnosed with T1DM. Our findings underscore the significant burden of depression in this population, with over 40% of participants experiencing depressive symptoms.

The study highlights the complex interplay between sociodemographic factors, health behaviors, diabetes management, and mental health outcomes in children and adolescents with T1DM. Older age, lower parental education levels, lower household income, smoking, and comorbidities were identified as significant risk factors for depression in this population.

Furthermore, the analysis revealed associations between depression and diabetes management factors, emphasizing the importance of comprehensive care that addresses both physical and mental health aspects. Higher levels of depression were associated with poorer glycemic control and less frequent glucose monitoring, highlighting the need for integrated approaches to diabetes management and mental health care.

Intervention strategies should target modifiable risk factors such as unhealthy habits, socioeconomic disparities, and suboptimal diabetes management practices. Tailored interventions that address the unique needs of children and adolescents with T1DM are essential for improving mental health outcomes in this population.

In conclusion, this study underscores the importance of routine mental health screening and integrated care for children and adolescents with T1DM. By addressing depression and its risk factors, healthcare providers can enhance the overall health and well-being of this vulnerable population. Further research is needed to develop and evaluate targeted interventions that optimize mental health outcomes in children and adolescents living with T1DM.

Author contributions

Conceptualization: Youssef A. Alqahtani, Ayed A. Shati, Fatimah S. Alhawyan, Ahmad A. Alhanshani, Abdulaziz M. Al-Garni.

Data curation: Ahmad A. Alhanshani, Abdulaziz M. Al-Garni, Saleh M. Al-Qahtani, Mohammed A. Alshehri.

Formal analysis: Youssef Ali Alqahtani, Ayed Abdullah Shati, Fatimah S. Alhawyan, Saleh M. Al-Qahtani, Mohammed Alshehri.

Funding acquisition: Youssef Ali Alqahtani, Ayed Abdullah Shati.

Investigation: Youssef Ali Alqahtani, Ayed Abdullah Shati, Mohammed Alshehri.

Methodology: Youssef Ali Alqahtani, Ayed Abdullah Shati, Fatimah S. Alhawyan, Ahmad A. Alhanshani.

Project administration: Youssef Ali Alqahtani, Ayed Abdullah Shati.

Resources: Youssef Ali Alqahtani, Ayed Abdullah Shati, Fatimah S. Alhawyan, Ahmad A. Alhanshani.

Software: Youssef Ali Alqahtani, Ayed Abdullah Shati, Abdulaziz M. Al-Garni, Saleh M. Al-Qahtani, Mohammed Alshehri.

Supervision: Youssef Ali Alqahtani, Ayed Abdullah Shati, Fatimah S. Alhawyan.

Validation: Youssef Ali Alqahtani, Ayed Abdullah Shati.

Visualization: Youssef Ali Alqahtani, Fatimah S. Alhawyan, Ahmad A. Alhanshani, Saleh M. Al-Qahtani, Mohammed Alshehri.

Writing – original draft: Youssef Ali Alqahtani, Ayed Abdullah Shati, Fatimah S. Alhawyan, Ahmad A. Alhanshani, Abdulaziz M. Al-Garni.

Writing – review & editing: Youssef Ali Alqahtani, Ayed Abdullah Shati.

Abbreviations:

CGMS Continuous Glucose Monitoring System

HbA1c Hemoglobin A1c

PHQ-9 Patient Health Questionnaire-9

SMBG Self-Monitoring of Blood Glucose

SR Saudi Riyal

T1DM Type 1 Diabetes Mellitus.

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through large group Research Project under Grant No. RGP2/378/44.

The study was conducted in accordance with the Research Ethics Committee at King Khalid University (HAPO-06-B-001) approved on March 10, 2021 with Approval No. ECM#2021-4703. Informed consent was obtained from the study participants prior to study commencement using a written consent form.

The author have no conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

How to cite this article: Alqahtani YA, Shati AA, Alhawyan FS, Alhanshani AA, Al-Garni AM, Al-Qahtani SM, Alshehri MA. Assessment of depression in children and adolescents with Type 1 diabetes mellitus: Impact and intervention strategies. Medicine 2024;103:29(e38868).

YAA, AAS, FSA, AAA, AMA, SMA, and MA contributed equally to this work.
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