Expecting factors for inadequate glycemic control in children and adolescents with type 1 diabetes mellitus: a single center experience

Abstract

Objectives

Achieving an ideal glycemic control in children and adolescents with type 1 diabetes mellitus (T1DM) is both a difficult and challenging process. We aim to highlight the expected factors contributing to inadequate glycemic control in children and adolescents with T1DM in a sample of Iraqi children and adolescents.

Methods

This was a descriptive cross-sectional study that recruited 247 T1DM patients aged < 18 years & disease duration ≥ 1 year. Data collected included socio-demographic & clinical characteristics with recent HbA1c value. Each patient was examined for signs of puberty and any lipodystrophy at insulin injection sites. Factors studied using Independent-Samples T-Test, One way ANOVA & Multivariable logistic regression.

Results

Of the 247 patients, 108 (43.7%) were males, and 139 (56.3%) were females. The mean & SD of the age of patients was 10.13 ± 3.85 years. The Mean & SD of the recent HbA1c level was 9.43 ± 2.56. HbA1c ≤ 7.5 was achieved in 27.1% of patients. Using Multivariable logistic regression to study the association between variable factors and inadequate glycemic control, showed a significant association with higher odds in terms of the older age of the patient, maternal illiteracy, presence of recurrent diabetic ketoacidosis (DKA) episodes, absence of carb counting, and presence of lipodystrophy. Higher HbA1c was also associated significantly with puberty, rural residency, poor socioeconomic status, DKA presentation, and using regular + NPH insulin regimen.

Conclusions

In the current study, inadequate glycemic control was induced by many factors, Strategies should be applied to control these factors to minimize the prospective risks of macro-vascular complications linked to T1DM in children & adolescents.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-024-01442-2.

Introduction

Type 1 diabetes is an autoimmune disease, caused by the destruction of pancreatic islet cells. hence, absolute insulin deficiency [1]. Affected individuals have hyperglycemia and are susceptible to acute complications from hypoglycemia and ketoacidosis [2]. Long-term morbidity caused by Vascular complications as well as mortality are real challenges for young people with type 1 diabetes mellitus (T1DM) that need early detection for better outcomes [3].

Type 1 diabetes mellitus is the most common chronic childhood disease worldwide [4]. In 2021, It was estimated that approximately 108,300 new cases of type 1 diabetes aged less than 15 years were diagnosed globally, and there were 651,700 existing cases of type 1 diabetes in children and adolescents worldwide [4, 5]. The reported prevalence of type 1 diabetes among school-age children in Baghdad, Iraq, was 159 per 100,000 in 2020 [6]. This high prevalence of type 1 diabetes places a considerable burden on the healthcare system & associated with long-term health complications and economic implications.

Glycated hemoglobin, also known as HbA1c, serves as a biomarker used to evaluate long-term glycemic control in diabetic patients, and it correlates directly with the appearance of future complications [7].

HbA1c represents the portion of hemoglobin that is attached non-enzymatically to glucose in the bloodstream. HbA1c is influenced by the interaction between the blood glucose concentration and the lifespan of the erythrocyte (RBC) [8]. As the mean RBC life span is approximately 120 days, HbA1c acts as a representative marker of glucose concentration during the preceding 8–12 weeks [7].

According to the American Diabetes Association (ADA) 2024, HbA1c levels or glycemic target in children should be less than 7.5% (58.5 mmol/mol) is recommended to reduce long-term diabetic complications [9].

The effective management of glycemic control in children with type 1 diabetes is substantial for their well-being. The recent recommendation is to assess glycemic status using HbA1c or other measurements like time in range at least twice / year in patients who are maintaining glycemic goals [9]. Alternatively, at least quarterly in patients who have recent changes in their therapy and /or have not maintained glycemic goals [9].

The importance of optimization of glycemic targets for diabetic children is to reduce short and long-term diabetic complications [10]. As well as to protect against micro- and macro-vascular complications. Moreover, there is a negative association between hyperglycemia and hypoglycemia on cognitive and brain function in children [11]. Owing to the wider impact of diabetes mellitus on health economics and the healthcare system in general, keeping adequate glycemic control will alleviate the burden on healthcare resources in the future.

Despite advancements in diabetes care, achieving optimal glycemic control remains challenging for any pediatric endocrinologist. Achieving a target glycemic control is a multidisciplinary approach involving the parent and the patient himself. Nevertheless, data from T1DM records across nineteen countries in Europe, North America & Australasia, reported that 84% of patients exhibited HbA1c above this target [12].

Extensive researches had focused on the factors that influence glycemic control in pediatric populations including maternal education level, socioeconomic status, carbohydrate counting, and the onset of puberty [12–17]. However, achieving a comprehensive understanding of the specific factors continues to be challenging.

Due to the paucity of studies that focus on agents influencing glycemic control in children and adolescents diagnosed with T1DM, especially in Iraq, this manuscript aims to highlight the expected factors contributing to inadequate glycemic control in T1DM young patients. Understanding these factors is crucial for tailoring targeted interventions, optimizing management plans, and improving prognosis. Exploring these factors will enhance the setting of therapeutic strategies and ultimately elevate the standard of care for those patients.

Methodology

Study design

This was a descriptive cross-sectional study. It was conducted at the pediatric Endocrinology and Diabetes Clinic in Al-Khansaa Teaching Hospital in Mosul City, northern Iraq, in the period from November 2022 to June 2023. We aim to explore the expected factors contributing to inadequate glycemic control in children and adolescents with T1DM in a sample of Iraqi children and adolescents.

Participants, inclusion, and exclusion criteria

Patients eligible for the study were children and adolescents aged < 18 years diagnosed with type 1 diabetes mellitus & duration of disease for one year or more (to avoid the risk of biasing the results because many patients with type 1 diabetes encounter transient improvements in HbA1c levels during the honeymoon period, which, in some cases, can extend for up to one year). Exclusion criteria were those who were newly diagnosed with diabetes or those with a duration of less than one year.

Data collection

Data was collected by interviewing each patient and their parents using a comprehensive questionnaire after obtaining their consent. The data were collected by the researcher himself with the assistance of a qualified staff member of the endocrinology center trained in research protocol & ethics, ensuring data accuracy & privacy. The Data included socio-demographic characteristics, family history, associated comorbidity like celiac ( proved by serology and duodenal biopsy) or thyroid disease (autoimmune hypothyroidism), type of presentation at the diagnosis whether diabetes ketoacidosis or hyperglycemia, type of insulin regimen used ( basal-bolus or regular + NPH or premixed insulin), duration of disease, who involved mainly in the care of the patient at home, no. of diabetes ketoacidosis episodes in the last year, dietary control& whether the patient is compliant to carb counting or no, education of the mother and father & their marital status. Each patient was examined for any signs of lipodystrophy at the insulin injection site & for signs of puberty( signs of appearance of breast bud in females & testicular enlargement of ≥ 4 ml). All participants underwent an HbA1c test using high-performance liquid chromatography. The entirety of the collected data had been systematically submitted and organized within an SPSS sheet, to be ready for thorough statistical analysis. Total number of collected patients was 266. However, due to missing some data and patients, the final number of participants was 247 patients.

Ethical consideration

This study was conducted in compliance with the ethical principles according to the Declaration of Helsinki. The study was approved by the Medical Research Ethics Committee of the College of Medicine, University of Mosul, Mosul, Iraq (No. UOM/COM/MREC/22–23 (2) on 09.10.2022. Written informed consent was obtained from the parents of all patients included in the study.

Statistical analysis

It was done by SPSS version 27 (IBM Co., Armonk, NY, USA). Categorical variables were presented as frequency and percentage (%) and analyzed using the Chi-square test. Numerical data were presented as mean and SD, analyzed using Independent-Samples T-Test and One way ANOVA.

Based on recent HbA1c levels, participants were classified as having good control and inadequate control. Those who had HbA1c levels ≤ 7.5% had good control, and those who had > 7.5% HbA1c levels were considered as having inadequate control [9]. Multiple logistic regression was used to study the factors associated with having inadequate control. The backward selection method was used for the selection of the variables. P-value < 0.05 was considered statistically significant.

Results

Of the 247 patients, 108 (43.7%) were males, and 139 (56.3%) were females. The socio-demographic characteristics of our cohort are shown in Table 1. Mean & SD of the age of patients at the diagnosis was 6.99 ± 3.49 years. While the Mean & SD of the age of the patients was 10.13 ± 3.85 years. The optimum glycemic control HbA1c ≤ 7.5 was achieved in 27.1% of our cohort.

Table 1.

Socio-demographic & clinical characteristics of the patients (N = 247)

		N (%)	Mean ± SD
Sex	Male	108 (43.7%)
	Female	139 (56.3%)
Age at the diagnosis	1–5 years	71 (28.7%)	6.99 ± 3.49
	5–10 years	106 (42.9%)
	10–15 years	67 (27.1%)
	> 15 years	3 (1.2%)
Age of the patient	1–5 years	23 (9.3%)	10.13 ± 3.85
	5–10 years	85 (34.4%)
	10–15 years	102 (41.3%)
	> 15	37 (15%)
Residence	Rural	56 (22.7%)
	Urban	191 (77.3%)
Maternal education level	Illiterate	39 (15.8%)
	Primary	79 (32%)
	Secondary school	59 (23.9%)
	High education	68 (27.5%)
	Died	2 (0.8%)
Paternal education level	Illiterate	26 (10.5%)
	Primary	62 (25.1%)
	Secondary	70 (28.3%)
	Higher education	76 (30.8%)
	Died	13 (5.3%)
Socioeconomic status	Poor	81 (32.8%)
	Moderate	120 (48.6%)
	Good	46 (18.6%)
Person who administer insulin at home	Mother	164 (66.4%)
	Father	30 (12.1%)
	Both	44 (17.8%)
	Other	9 (3.6%)
Marital status of the parents	Married	232 (93.9%)
	Divorced or death of one parent	15 (6.1%)
Puberty	Yes	91 (36.8%)
	No	156 (63.2%)
Family history of type 1 DM		33 (13.4%)
Associated celiac disease		32 (13%)
Associated hypothyroidism		10 (4%)
Presentation at the diagnosis	DKA	87 (35.2%)
	Hyperglycemia	160 (64.8%)
Duration of the disease	1–5	191 (77.3%)	3.15 ± 2.51
	5–10	51 (20.6%)
	10–20	5 (2%)
Type of insulin regimen	Premixed insulin	45 (18.2%)
	Regular + NPH	78 (31.6%)
	Basal-bolus	124 (50.2%)
No. of DKA episodes during the last year	None	181 (73.3%)
	One or more	66 (26.7%)
Carb counting	Yes	45 (18.2%)
	No	202 (81.8%)
Presence of lipodystrophy	Yes	98 (39.7%)
	No	149 (60.3%)
HbA1c level at the diagnosis	5-7.5	23 (9.3%)	10.93 ± 2.44
	7.5–8.5	15 (6.1%)
	8.5–9.5	33 (13.4%)
	9.5–10.5	45 (18.2%)
	10.5–18	131 (53%)
Current HbA1c level	≤ 7.5	67 (27.1%)	9.43 ± 2.56
	7.6–8.5	37 (15%)
	8.6–9.5	30 (12.1%)
	9.6–10.5	34 (13.8%)
	10.6–18	79 (32%)

A comparison of recent HbA1c levels with patients’ characteristics is shown in Table 2. There was a statistically significant difference in recent HbA1c level in terms of age of the patient, age at the diagnosis, residence, parental education level, socioeconomic status, Person who administers insulin at home, and onset of puberty. likewise, There was a statistically significant difference in recent HbA1c level in terms of presentation at the diagnosis, duration of the disease, type of insulin regimen used, No. of DKA events during the last year, carb counting, and the presence of lipodystrophy.

Table 2.

Comparison of recent HbA1c level across patients’ characteristics

		N	Mean ± SD		P-value
Sex	Male	108	9.23 ± 2.4		0.284
	Female	139	9.58 ± 2.68
		N	Pearson Correlation		P-value
Age at the diagnosis		274	0.204		0.001*
Age of the patient	1–5 5–10 10–15 > 15	274	0.279 8.5 ± 1.9 8.9 ± 2.4 10.1 ± 2.7 10.0 ± 2.6		< 0.001*
		N	Mean ± SD		P-value
Residence	Urban	191	8.98 ± 2.26		< 0.001*
	Rural	56	10.97 ± 2.94
Maternal education level	Illiterate	39	11.03 ± 2.44		< 0.001*
	Primary	79	10.28 ± 2.46
	Secondary school	59	8.69 ± 2.42
	High education	68	8.15 ± 2.01
Paternal education level	Illiterate	26	10.95 ± 2.47		< 0.001*
	Primary	62	10.06 ± 2.29
	Secondary	70	9.34 ± 2.68
	Higher education	76	8.28 ± 2.19
	Died	13	10.56 ± 2.61
Socioeconomic status	Poor	81	10.64 ± 2.59		< 0.001*
	Moderate	120	8.75 ± 2.26
	Good	46	9.07 ± 2.53
Person who administer insulin at home	Mother	164	9.25 ± 2.44		0.002*
	Father	30	10.29 ± 2.58
	Both	44	9 ± 2.6
	Other	9	11.97 ± 2.77
Marital status of the parents	Married	232	9.36 ± 2.56		0.085
	Divorced or death of one parent	15	10.53 ± 2.43
Puberty	Yes	91	10.29 ± 2.73		< 0.001*
	No	156	8.93 ± 2.32
Family history of type1 DM	Yes	33	9.5 ± 2.6	0.872
	No	214	9.42 ± 2.56
Associated celiac disease	Yes	32	9.62 ± 2.49	0.656
	No	215	9.4 ± 2.57
Associated hypothyroidism	Yes	10	9.64 ± 1.71	0.792
	No	237	9.42 ± 2.59
Presentation at diagnosis	DKA	87	10.45 ± 2.71	< 0.001*
	Hyperglycemia only	160	8.88 ± 2.3
		N	Pearson Correlation	P-value
Duration of the disease		274	0.139	0.029*
		N	Mean ± SD	P-value
Type of insulin regimen	Basal-bolus	124	8.21 ± 1.79	< 0.001*
	Regular-NPH	78	10.81 ± 2.39
	Premixed insulin	45	10.38 ± 3.03
No. of DKA episodes in the last year	None	181	9.11 ± 2.37	< 0.001*
	One or more	66	10.32 ± 2.86
Carb counting	Yes	45	7.09 ± 0.96	< 0.001*
	No	202	9.95 ± 2.51
Presence of lipodystrophy	Yes	98	10.86 ± 2.64	< 0.001*
	No	149	8.49 ± 2.02
		N	Pearson Correlation	P-value
HbA1c level at the diagnosis		274	0.083	0.194

* significant as P-value ≤ 0.05, DKA = diabetic ketoacidosis

Studying the Association of characteristics of the patients with inadequate glycemic control (HbA1c ≥ 7.5) is shown in Table 3. There was a statistically significant association with inadequate glycemic control in terms of age at the diagnosis, current age of the patient, residence, maternal education level, paternal education level, socioeconomic status, and onset of puberty. In addition, There was a statistically significant association with inadequate glycemic control in terms of DKA presentation at the diagnosis, regular + NPH type of insulin regimen, one or more DKA events in the last year, absence of carb counting during each meal intake, and the presence of lipodystrophy at insulin injection sites.

Table 3.

Association of characteristics of the patients with inadequate glycemic control

		Good control (N = 67)	Inadequate control (N = 180)
		N (%)	N (%)	P-value
Sex	Male	29 (26.9%)	79 (73.1%)	0.932
	Female	38 (27.3%)	101 (72.7%)
		Mean ± SD	Mean ± SD	P-value
Age at diagnosis		6.04 ± 3.59	7.34 ± 3.4	0.009*
Current age of the patient		8.79 ± 3.78	10.63 ± 3.77	< 0.001*
		N (%)	N (%)	P-value
Residence	Urban	60 (31.4%)	131 (68.6%)	0.005*
	Rural	7 (12.5%)	49 (87.5%)
Maternal education level	Illiterate	3 (7.7%)	36 (92.3%)	< 0.001*
	Primary	10 (12.7%)	69 (87.3%)
	Secondary school	24 (40.7%)	35 (59.3%)
	High school education	30 (44.1%)	38 (55.9%)
	Died	0 (0%)	2 (100%)
Paternal education level	Illiterate	2 (7.7%)	24 (92.3%)	< 0.001*
	Primary	7 (11.3%)	55 (88.7%)
	Secondary school	22 (31.4%)	48 (68.6%)
	High school education	34 (44.7%)	42 (55.3%)
	Died	2 (15.4%)	11 (84.6%)
Socioeconomic status	Poor	8 (9.9%)	73 (90.1%)	< 0.001*
	Moderate	41 (34.2%)	79 (65.8%)
	Good	18 (39.1%)	28 (60.9%)
Who take care of patient	Mother	45 (27.4%)	119 (72.6%)	0.110
	Father	6 (20%)	24 (80%)
	Both	16 (36.4%)	28 (63.6%)
	Other	0 (0%)	9 (100%)
Marital status of the parents	Married	65 (28%)	167 (72%)	0.252
	Divorced or death of one parent	2 (13.3%)	13 (86.7%)
Puberty	Yes	15 (16.4%)	76 (83.5%)	0.010*
	No	49 (31.4%)	107 (68.9%)
Family history of Type1 DM	Yes	9 (27.3%)	24 (72.7%)	0.984
	No	58 (27.1%)	156 (72.9%)
Associated celiac disease	Yes	7 (21.9%)	25 (78.1%)	0.474
	No	60 (27.9%)	155 (72.1%)
Associated hypothyroidism	Yes	2 (20%)	8 (80%)	0.733
	No	65 (27.4%)	172 (72.6%)
Presentation at diagnosis	DKA	15 (17.2%)	72 (82.8%)	0.010*
	Hyperglycemia	52 (32.5%)	108 (67.5%)
		Mean ± SD	Mean ± SD	P-value
Duration of disease		2.78 ± 2.42	3.29 ± 2.53	0.151
		N (%)	N (%)	P-value
Type of insulin regimen	Basal-bolus	52(41.9%)	72 (58.1%)	< 0.001*
	Regular + NPH	6 (7.7%)	72 (92.3%)
	Premixed insulin	9 (20%)	36 (80%)
No. of DKA episodes	None	58 (32%)	123 (68%)	0.004*
	One or more	9 (13.6%)	57 (86.4%)
Carb counting	Yes	29 (64.4%)	16 (35.6%)	< 0.001*
	No	38 (18.8%)	164 (81.2%)
Presence of lipodystrophy	No	56 (37.6%)	93 (62.4%)	< 0.001*
	Yes	11 (11.2%)	87 (88.8%)
		Mean ± SD	Mean ± SD	P-value
HbA1c level at the diagnosis		10.6 ± 2.83	11.06 ± 2.27	0.243

Multivariable logistic regression was used to study the factors associated with factors associated with inadequate glycemic control in children with type 1 diabetes as shown in Table 4. Higher odds of having inadequate glycemic control were associated with older age of the patient, maternal illiteracy, one or more DKA events during the last year, absence of carb counting before meal & the presence of lipodystrophy at insulin injection sites.

Table 4.

Factors associated with inadequate glycemic control in children with type 1 diabetes using Multivariable logistic regression

	OR	P-value	95% C.I. for OR
			Lower	Upper
Age of the patient	1.11	0.022*	1.02	1.22
Maternal education level
Illiterate	Ref.
Primary	0.72	0.651	0.18	2.94
Secondary school	0.17	0.009*	0.04	0.63
High education	0.34	0.134	0.08	1.39
No. of DKA events during the last year
None	Ref.
One or more	2.85	0.019*	1.19	6.84
Carb counting
Yes	Ref.
No	4.66	< 0.001*	1.99	10.91
Presence of lipodystrophy
No	Ref.
Yes	2.27	0.043*	1.03	5.04

OR: Odds ratio, CI: Confidence interval, *: significant as P-value ≤ 0.05

Discussion

Type 1 diabetes mellitus is of chronic illness that affects children and adolescents worldwide with rising incidence. The global annual rise is approximated to be 3%, leading to an expected worldwide 70,000 new cases of T1DM in children each year [18]. In children and adolescents with T1DM, poor glycemic control is a crucial problem and linked to future micro-vascular complications [19]. Worldwide, there are a few studies that examined the predictors for poor glycemic control in pediatric patients with T1DM [13, 20–24]. To the best of our knowledge, this is the first study on this subject conducted in Iraq.

In the current study, we found that the most common age group at presentation of T1DM was between 5 and 10 years, that was the same finding in two studies conducted in Iran [25, 26]. Celiac disease was seen in 13% of patients in our study group, a prevalence closely similar to findings reported in a study conducted in Saudi Arabia [1]. However, it was higher than the global report in the US (1.9%) and Australia (7.7%) [27]. Possibly attributed to genetic factors. Similarly, thyroid disease was observed in 4% of our cohort, aligning with results reported in a study in Saudi Arabia [1].In the same way, this is may be explained by the closer genetic factors in the region.

As per clinical practice consensus guidelines of the ISPAD, it is recommended that HbA1c levels or glycemic targets in children should be below 7.5% (58.5 mmol/mol) to reduce the risks of long-term diabetic complications [28]. In this study, we found that 27.1% of our cohort had achieved optimal glycemic control. This finding was slightly higher than the results reported in other studies [1, 13, 14, 24, 25, 27]. This means that there were 72.9% of patients under the study failed to achieve adequate glycemic control which was in alignment with results in other studies in Arabian Gulf countries, Sudan, Iran, Cameroon, and Africa [15, 25, 29–31]. Thus, this study aims to explore the influencing factors for poor glycemic control in Iraqi children and adolescents with T1DM.

In this study we found that the older age of the patients & older age at the diagnosis of T1DM were significantly associated with poor glycemic target, this finding was also reported by several studies [26, 32, 33]. This can be explained by the loss of the parental observation and control on diet and insulin intake as the child gets older, associated with the effect of environment and friends at the school to consume non-healthy foods rich in carbs and sugar. However, this result contrasts with observation in a study by Niba et al. [30].

In the present study, we found that patients who lived in rural areas were more likely to develop poor glycemic control compared to patients who lived in urban areas. This can be explained by the fact that rural areas often face challenges in terms of limited access to healthcare services, poor healthcare infrastructure, limited education, and lower socioeconomic status. All of these factors may result in less awareness and adherence to proper diabetes care practices. However, this finding did not show significance in a study conducted in Egypt [32]. The discrepancies in the results may also arise from variations in demographic characteristics, socioeconomic status, dietary patterns, and the availability of organized diabetes education initiatives or not.

On the other hand, parental education level especially of the mother significantly had a direct effect on glycemic control and HbA1c level in our cohort. The higher maternal education the lower the odds of having inadequate glycemic control, that also reported in other studies [13, 14, 34].Maternal illiteracy may lead to gaps in understanding of the importance of diabetes care. This can result in poor adherence to treatment plans, missed insulin doses, and challenges in recognizing and responding to signs of hypo- or hyperglycemia.

In our study, we found that poor socioeconomic status was linked to inadequate glycemic control which aligns with other studies [14, 15, 29, 31]. Poor socioeconomic status influences the provision of essential diabetes medications, monitoring equipment supplies, access to healthcare resources, nutritional choices& educational opportunities that eventually have a negative effect on the glycemic control of young diabetic patients.

Carb counting is an essential strategy for maintaining glycemic control as reported in our study. Using Multivariable logistic regression, patients who don’t count carbs had four times the odds of having inadequate glycemic control compared to patients who do. This finding was in line with four studies in children & six studies in adults with final improvement of HA1c level [13, 16, 17, 35–41].

Similarly, in our study, puberty was another influencing factor for inadequate glycemic control that was again observed in a study by Alassaf et al., Al-Agha et al. & Holl RW et al. [1, 13, 42]. This finding can be attributed to various physiological and behavioral changes associated with puberty like hormonal changes, increased independence, increased nutritional requirements & changes in fat distribution that can influence insulin sensitivity eventually impacting glycemic control.

According to ISPAD Clinical Practice Consensus Guidelines 2022 report, a basal-bolus regimen of insulin administration is close to the physiologic pattern of insulin secretion by the pancreas & considered an ideal regimen for achieving adequate glycemic control [43]. This was evident in the results of the current study, where the mean HbA1c levels of patients on a basal-bolus regimen were lower compared to those of patients on premixed or regular + NPH insulin regimens [44, 45]. Sharplin et al., observed that patients with T1DM had achieved effective glycemic control following a transition from a premixed insulin regimen to a glargine-based insulin regimen [45]. However, this observation contrasts with findings from a study conducted in Cameroon, which could be attributed to the small sample size in the latter study [30].

One of the striking findings in our study is the number of DKA episodes during the last year before the study, those patients with one or more DKA episodes had higher odds of having inadequate glycemic control exhibited by multivariable logistic regression. Likewise, patients who had DKA as first presenting signs of T1DM. This may be attributed to a state of severe insulinopenia in those patients.

In the same way, through the application of multivariable logistic regression, we report that patients experiencing lipodystrophy at the insulin injection site were about twice as liable to exhibit inadequate glycemic control comparing those without lipodystrophic changes. This finding was also reported by a study in Southern Ethiopia [46]. Subcutaneous fat is a common site for insulin injection, when there are dystrophic changes, insulin absorption will be slow, erratic, and delayed leading to suboptimal glycemic control in those particular patients.

The main limitation of this study was a single-center experience with a limited number of patients & cross-sectional design, all precluding the establishment of generalizability of the study. However, the present study was the first study on this topic in Iraq. Further studies are recommended in the future, involving multi-centers in Iraq or other countries with larger sample sizes, time-in-range data from continuous glucose monitoring devices & using patients ‘anthropometric measures and other lab studies.

Conclusions

Glycated hemoglobin, also known as HbA1c serves as a biomarker used to evaluate long-term glycemic control in diabetic patients. In the current study, the expected factors for poor glycemic control include older age at the diagnosis, rural residence, illiterate mother, poor socioeconomic state, approaching puberty, using regular + NPH insulin regimen, history of recurrent DKA during the last year, absence of carb counting before meal, and presence of lipodystrophy at insulin injection sites. Understanding the association between all those studied factors in our study & glycemic control is a crucial issue for tailoring suitable interventions that address specificchallenges faced by children & adolescents with T1DM. Hence, Implementing a targeted strategies & guidelines that can help to bridge gaps and promote optimal diabetes care for all young diabetic patients.

Electronic supplementary material

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Funding

Note applicable.

Data availability

The data supporting the conclusions of this study can be obtained from the corresponding author upon a reasonable request.

Declarations

Conflict of interest

the named author declare that there was no conflict of interest associated with this article.