Riesgo de trastornos alimentarios en pacientes pediátricos con Diabetes Mellitus tipo 1

Riesgo de trastornos alimentarios en pacientes pediátricos con Diabetes Mellitus tipo 1

Autora principal: Iris Victoria Pastrana-Quintanilla

Vol. XVII; nº 9; 353

Risk of eating disorders in pediatric patients with type 1 Diabetes Mellitus

Fecha de recepción: 06/04/2022

Fecha de aceptación: 06/05/2022

Incluido en Revista Electrónica de PortalesMedicos.com Volumen XVII. Número 9 – Primera quincena de Mayo de 2022 – Página inicial: Vol. XVII; nº 9; 353

Autores:

Iris Victoria Pastrana-Quintanilla¹, MD,

Airam Regalado-Ceballos², MD,

Ana Ramírez-Meléndez²,

Víctor Hugo Monsiváis-Almaguer²,

Melanie Susset Cisneros-González²,

Manuel Enrique de la O-Cavazos¹, PhD,

Leonor Hinojosa-Amaya¹, MD

Centro de Trabajo actual

1Department of Pediatrics, University Hospital “Dr. José Eleuterio González”, U.A.N.L., Monterrey, Nuevo León, México.

2Faculty of Medicine and University and Hospital “Dr. José Eleuterio González”, U.A.N.L., Monterrey, Nuevo León, México.

Resumen:

Antecedentes: la diabetes mellitus tipo 1 (DM1) representa del 5 al 10% de todos los casos de diabetes en el mundo. Al mismo tiempo, la DM1 es el tipo de diabetes más común que se presenta en los niños. Los pacientes con DM1 tienen riesgo de presentar un trastorno alimentario (TA), pero las herramientas de detección de TCA para la población general no son adecuadas para los pacientes con DM1 por varias razones. Nuestro estudio busca identificar la prevalencia de los factores de riesgo para la disfunción eréctil. Diseño del estudio: se trató de un estudio observacional, descriptivo y transversal. Participantes: la población de estudio incluyó a todos los pacientes de 8 a 20 años con diagnóstico de DM1 y tiempo de evolución mayor a 1 año. Intervenciones: solo estudio observacional. Resultados: riesgo de disfunción eréctil. Para la comparación de variables categóricas se aplicó la prueba de χ2 y se utilizó una regresión lineal simple para probar si el número de años desde el diagnóstico de DM1 tenía una correlación significativa en el puntaje de la encuesta aplicada con un modelo de regresión ajustado. Resultados: encontramos que más de la mitad de los pacientes encuestados (65,7%) presentaron test positivo para tener riesgo de padecer una DE. No se encontró asociación entre la edad o el género con una mayor probabilidad de tener un TCA. Sin embargo, se demostró una asociación significativa entre los niveles de HbA1c superiores al 7,5 % y el riesgo de DE. Conclusión: los pacientes con un nivel más alto de HbA1c tienen más probabilidades de tener riesgo de DE. Parece que los pacientes pediátricos mexicanos con DMT1 pueden presentar riesgo de sufrir una DE.

Palabras clave: diabetes mellitus tipo 1, desórdenes alimentarios, DEPS-R

Declaración de buenas prácticas:

Los autores de este manuscrito declaran que:

Todos ellos han participado en su elaboración y no tienen conflictos de intereses

La investigación se ha realizado siguiendo las Pautas éticas internacionales para la investigación relacionada con la salud con seres humanos elaboradas por el Consejo de Organizaciones Internacionales de las Ciencias Médicas (CIOMS) en colaboración con la Organización Mundial de la Salud (OMS) https://cioms.ch/publications/product/pautas-eticas-internacionales-para-la-investigacion-relacionada-con-la-salud-con-seres-humanos/

El manuscrito es original y no contiene plagio

El manuscrito no ha sido publicado en ningún medio y no está en proceso de revisión en otra revista.

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Han preservado las identidades de los pacientes.

ABSTRACT

Background: Type 1 diabetes mellitus (T1DM) accounts to 5-10% of all cases of diabetes in the world. At the same time, T1DM is the most common type of diabetes presented in children. Patients with T1DM are at risk of presenting an eating disorder (ED), but ED screening tools for the general population are not suitable for T1DM patients for several reasons. Our study seeks to identify prevalence of risk factors for ED. Study design: this was an observational, descriptive, and cross-sectional study.  Participants: the study population included all patients aged 8-20 years with a diagnosis of T1DM and an evolution time greater than 1 year. Interventions: observational study only. Outcomes: risk for ED. For the comparison of categorical variables, the χ2 test was applied and a simple linear regression was used to test whether the number of years since the diagnosis of T1DM had a significant correlation in the score of the survey applied with an adjusted regression model. Results: we found that more than half of the patients surveyed (65.7%) presented a positive test for having risk of suffering an ED. No association was found between age or gender with a higher probability of having an ED. However, a significant association was shown between HbA1c levels greater than 7.5% and the risk of ED. Conclusion: patients with a higher HbA1c level are more likely to be at risk for ED. It seems that Mexican pediatric patients with DMT1 may present risk of suffering an ED.

Keywords: diabetes mellitus, pediatric, DEPS-R, survey

INTRODUCTION

Diabetes mellitus (DM) is a chronic degenerative condition with multifactorial causes. According to the World Health Organization (WHO), the number of patients who live with diabetes increased from 108 million to 422 million in 2014.¹ In Mexico, the National Institute of Public Health has named DM as the leading cause of death in women and the second cause of death in men since 2000.² T1DM accounts to 5-10% of all cases of diabetes in the world. At the same time, T1DM is the most common type of diabetes presented in children.^3,4 According to the International Diabetes Federation, approximately 542,000 children are currently living with T1DM, and annually 78,000 children are diagnosed with T1DM.⁵

The health of patients with diabetes is affected by the demands of treatment, which requires commitment and perseverance for life, and which encompasses a set of changes in their lifestyles, especially in reference to dietary habits. This conditioning of eating patterns, added to insulin treatment, can lead patients to become obsessed with their diet, sometimes developing alterations in eating behavior.^6,7

Patients with DM 1 are at risk of presenting an eating disorder (ED)⁸, but ED screening tools for the general population are not suitable for T1DM for several reasons. Firstly, T1DM patients must be aware of their diet and carbohydrate count, and this could come back as a false positive result in screening tests designed for the general population. Secondly, there are certain behaviors that patients with T1DM exhibit, and the general population does not, such as the restriction of insulin application.⁹

Due to the differences between the general population and those with T1DM, the Diabetes Eating Problem Survey (DEPS-R) was developed and validated in 2010 by Markowitz et al.⁹ as a tool for screening for ED, specifically in young patients (13-19 years) living with T1DM. DEPS-R is a questionnaire of that features 16 questions, measured by the 6-point scale, in which a higher the score, translates to a greater the risk of ED (> 20 points). The questionnaire was translated and validated into Spanish in 2017¹⁰ and validated for children and adolescents from 8 to 20 years old.¹¹ The DEPS-R seems to more cases of ED compared to physicians.¹² And could help identify patients at an earlier stage. Timely detection and intervention could help to reduce diabetes complications such as retinopathy, neuropathy, and diabetic ketoacidosis.¹³ This study aims to determine the prevalence of risk of ED in pediatric patients with type 1 Diabetes Mellitus with the DEPS-R tool, as well to identify a clinical characteristic in these patients.

MATERIAL AND METHODS

This observational, descriptive, and cross-sectional study was carried out by conducting surveys in the Pediatric Endocrinology Department in our hospital. The study population included all patients aged 8-20 years with a diagnosis of T1DM and an evolution time greater than 1 year.

The research ethics committee and the Institution’s research committee of the Universidad Autónoma de Nuevo León approved the study procedures (PE21-00007). Because the research study is without risk and considering our local regulations, the informed consent form was exempted, obtaining only verbal consent. Patients with a positive survey were sent to pediatric psychology for evaluation and follow up.

Patients were divided by age into two groups corresponding to children and adolescents, from 7 to 11 years old and 12 to 18 years old, respectively. Demographical and clinical data, such as glycemic control with HbA1c, date of diagnosis, insulin units per day, insulin dose per kg, type of insulins used, number of daily injections, comorbidities, microalbuminuria, number of episodes of hypoglycemia, and number of ketoacidosis events in the last year was collected. Patients with type 2 diabetes mellitus, patients with another type of diabetes, and patients who did not want to take the survey were excluded from the study. Patients who didn’t complete the survey or answered it correctly were also excluded.

The 16-question DEPS-R questionnaire was offered to all eligible patients, result greater than 20 points in the DEPS-R was considered at risk of presenting an ED.

SPSS 25.0 statistical software was used to analyze the study data. In terms of demographic patterns, continuous data were stated as median and range. The conformity of the data with the non-parametric distribution for the age of the sample was evaluated using the Kolmogorov-Smirnov test. For the comparison of categorical variables, the χ2 test was applied and a simple linear regression was used to test whether the number of years since the diagnosis of T1DM had a significant correlation in the score of the survey applied with an adjusted regression model. A value of p ≤ 0.05 was considered statistically significant.

RESULTS

A total of 131 patients (54 female and 77 male) completed the survey. The median age was 14 years with a range of 7 to 18 years. The median number of years with T1DM was 6 with a range of 1 to 13 years. The result of the last glycated hemoglobin was available from 86 patients, with a median of 8 and a range of 5.7 – 12.1. A total of 86 patients (65.6%) presented a risk of having an EA.

The frequency of the group of age and questions is shown in Table 1. The relationship between gender and risk was not significant, (x2 (1) = 0.042, p = 0.837).

Similarly, a significant association was not shown between age and an ED risk, (x2 (1) = 2.474, p = 0.12). However, a significant association was shown between HbA1c levels greater than 7.5% and the risk of ED, (x2 (1) = 10.997, p = <0.001).

The comparison for categorical variables in terms of risk of AT is shown in Table 2.

Correlation between the evolution of T1DM and risk of ED: Among the variables, years of diagnosis with T1DM and risk of ED, a null correlation was presented, considering the linear R2 value of 0.034.

DISCUSSION

Of the 131 patients surveyed, 86 (65.6%) were at risk of presenting ED, according to the DEPS-R survey. These results are similar to those in the meta-analysis carried out by Pinquart in 2013.¹⁴  In our study, patients with T1DM had a greater degree of dissatisfaction with their own bodies, which could trigger risk habits to develop ED. There is no information regarding the prevalence of the risk of ED in patients with T1DM in Mexico, thus a subsequent study to determine it could be useful. Likewise, it is important to consider the North American influence on our state’s lifestyle and the impact of this influence on body perception in children and adolescents.

According to the literature consulted, girls and women with T1DM are more likely to have two or more risk habits to develop ED compared to the healthy population and to boys and men with diabetes as well.¹⁵ However, in our results, the relationship between these variables were not significant (p = 0.837).

Similarly, this study did not find a significant relationship (p = 0.12) between age and the risk of developing an ED. These results are consistent with similar studies, such as the one by Tokalty et al. published in 2018¹⁶, in which no relationship was found with age and risk of developing ED.

Regarding the relationship between the years with the diagnosis of T1DM and the risk of suffering from an ED, it presents a null correlation. This can be compared with the results of the study by Tokalty et al. (2018)¹⁶ who mention that there is no significant relationship between these two variables.

The well-being of patients with T1DM can be affected by the demands of treatment, which requires a commitment and constancy for life, and includes a set of modifications in their lifestyles, especially about eating habits. Nutrition is one of the main pillars of T1DM treatment, so an ED can translate into poor glycemic control, which in turn can lead to an early onset of chronic complications of the disease.

The DEPS-R has been used in several studies as a tool for ED screening in patients with T1DM. For example, Cherubini et al. in 2018¹⁷ identified a clinical profile for positive DEPS-R: overweight, little physical activity, low socioeconomic status, poor metabolic control, and skipping insulin doses. They also showed that there was an increase in the probability of positive DEPS-R with the increase of HbA1c, as well as with the number of omissions of insulin doses in a week, and with a decrease in probability with each hour of exercise per week. DEPS-R was correlated with HbA1c, the latter being commonly reported to be associated with diabetes eating problems. ¹⁸ These findings might be explained by the fact that the DEPS and the DEPS-R can identify diabetes eating problems, such as insulin omission to lose weight, which is a core feature of diabetes eating problems in T1DM. Such diabetes-specific behaviors are not likely to be detected using generic screening tools, indicating the risk of false negatives associated with these measures.

This conditioning of eating patterns, added to insulin treatment, can lead patients to become obsessed with their diet, altering their eating behavior. Therefore, it is important to have information on the subject to consider a change in the disease management guidelines and the development of timely nutrition programs.

We must consider some limitations. The survey was done during the pandemic COVID-19, which may have exacerbated ED. In addition, the group of children was very small compared to the adolescents.

In the current study, we found that more than half of the patients surveyed (65.7%) presented a positive test for having a higher risk of suffering an ED. No association was found between age or gender with a higher probability of having an ED. However, a significant association was shown between HbA1c levels greater than 7.5% and the risk of ED. Patients with a higher HbA1c level are more likely to be at risk for ED. Based on the results obtained and the hypothesis presented, it is established that the DEPS-R survey is useful in the Mexican population with T1DM for the screening of ED in children and adolescents.

References

1. World Health Organization. Diabetes [Internet]. 2021. Available from: https://www.who.int/news-room/fact-sheets/detail/diabetes
2. Instituto Nacional de Salud Pública. Diabetes en México. 2020.
3. Diabetes DOF. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2009;32(SUPPL. 1).
4. Maahs DM, West NA, Lawrence JM, Mayer-Davis EJ. Epidemiology of type 1 diabetes. Endocrinology and Metabolism Clinics of North America. 2010;39(3):481–97.
5. International Diabetes Federation. Diabetes Atlas. 2013;
6. Rodin G, Olmsted MP, Rydall AC, Maharaj SI, Colton PA, Jones JM, et al. Eating disorders in young women with type 1 diabetes mellitus. Journal of Psychosomatic Research. 2002 Oct;53(4):943–9.
7. Ismail K. Eating disorders and diabetes. Psychiatry. 2008 Apr;7(4):179–82.
8. Young V, Eiser C, Johnson B, Brierley S, Epton T, Elliott J, et al. Eating problems in adolescents with Type 1 diabetes: a systematic review with meta-analysis. Diabetic Medicine. 2013 Feb;30(2):189–98.
9. Markowitz JT, Butler DA, Volkening LK, Antisdel JE, Anderson BJ, Laffel LMB. Brief Screening Tool for Disordered Eating in Diabetes: Internal consistency and external validity in a contemporary sample of pediatric patients with type 1 diabetes. Diabetes Care. 2010 Mar 1;33(3):495–500.
10. Sancanuto C, Jiménez-Rodríguez D, Tébar FJ, Hernández-Morante JJ. Traducción y validación de un cuestionario para la detección de trastornos del comportamiento alimentario en pacientes con diabetes mellitus. Medicina Clínica. 2017 Jun;148(12):548–54.
11. Sancanuto C, Tébar FJ, Jiménez-Rodríguez D, Hernández-Morante JJ. Factores psicosociales en la diabetes mellitus tipo1 y su relación con el riesgo de desarrollar trastornos alimentarios en la infancia y la adolescencia. Avances en Diabetología. 2014 Sep;30(5):156–62.
12. Saßmann H, Albrecht C, Busse-Widmann P, Hevelke LK, Kranz J, Markowitz JT, et al. Psychometric properties of the German version of the Diabetes Eating Problem Survey-Revised: additional benefit of disease-specific screening in adolescents with Type 1 diabetes. Diabetic Medicine. 2015 Dec;32(12):1641–7.
13. Atik Altınok Y, Özgür S, Meseri R, Özen S, Darcan Ş, Gökşen D. Reliability and Validity of the Diabetes Eating Problem Survey in Turkish Children and Adolescents with Type 1 Diabetes Mellitus. Journal of Clinical Research in Pediatric Endocrinology. 2017 Dec 14;323–8.
14. Pinquart M. Body image of children and adolescents with chronic illness: A meta-analytic comparison with healthy peers. Body Image. 2013 Mar;10(2):141–8.
15. Araia E, Hendrieckx C, Skinner T, Pouwer F, Speight J, King RM. Gender differences in disordered eating behaviors and body dissatisfaction among adolescents with type 1 diabetes: Results from diabetes MILES youth-Australia. International Journal of Eating Disorders. 2017 Oct;50(10):1183–93.
16. Tokatly Latzer I, Rachmiel M, Zuckerman Levin N, Mazor-Aronovitch K, Landau Z, Ben-David RF, et al. Increased prevalence of disordered eating in the dual diagnosis of type 1 diabetes mellitus and celiac disease. Pediatric Diabetes. 2018 Jun;19(4):749–55.
17. Cherubini V, Skrami E, Iannilli A, Cesaretti A, Paparusso AM, Alessandrelli MC, et al. Disordered eating behaviors in adolescents with type 1 diabetes: A cross-sectional population-based study in Italy. International Journal of Eating Disorders. 2018 Aug;51(8):890–8.
18. Jones JM, Lawson ML, Daneman D, Olmsted MP, Rodin G. Eating disorders in adolescent females with and without type 1 diabetes: cross sectional study. BMJ. 2000 Jun 10;320(7249):1563–6.

Figure legends and tables

Table 1. Frequency comparison between children and adolescents.

Question	Age groups	n (%)						p
		never	rarely	sometimes	often	usually	always
Losing weight is an important goal to me	children	33 (80.5)	2 (4.9)	2 (4.9)	0	0	4 (9.8)	0.003
	adolescents	38 (42.2)	12 (13.3)	8 (8.9)	3 (3.3)	10 (11.1)	19 (21.1)
I skip meals and/or snacks	children	31 (75.6)	3 (7.3)	6 (14.6)	1 (2.4)	0	0	0.032
	adolescents	41 (45.6)	24 (26.7)	22 (24.4)	1 (1.1)	1 (1.1)	1 (1.1)
Other people have told me that my eating is out of control	children	32 (78)	2 (4.9)	6 (14.6)	0	1 (2.4)	0	0.039
	adolescents	53 (58.9)	19 (21.1)	11 (12.2)	4 (4.4)	0	3 (3.3)
When I overeat, I don’t take enough insulin to cover the food	children	26 (63.4)	6 (14.6)	3 (7.3)	1 (2.4)	0	5 (12.2)	0.095
	adolescents	53 (58.9)	17 (18.9)	12 (13.3)	0	5 (5.6)	3 (3.3)
I eat more when I am alone than when I am with others	children	32 (78)	3 (7.3)	2 (4.9)	1 (2.4)	2 (4.9)	1 (2.4)	0.39
	adolescents	56 (62.2)	16 (17.8)	8 (8.9)	1 (1.1)	3 (3.3)	6 (6.7)
I feel that it’s difficult to lose weight and control my diabetes  at the same time	children	33 (80.5)	2 (4.9)	4 (9.8)	0	1 (2.4)	1 (2.4)	0.48
	adolescents	56 (62.2)	9 (10)	16 (17.8)	1 (1.1)	4 (4.4)	4 (4.4)
I avoid checking my blood sugar when I feel like it is out of range	children	32 (78)	4 (9.8)	0	0	3 (7.3)	2 (4.9)	0.302
	adolescents	58 (64.4)	12 (13.3)	8 (8.9)	0	6 (6.7)	6 (6.7)
I make myself vomit	children	39 (95.1)	1 (2.4)	0	0	1 (2.4)	0	0.18
	adolescents	89 (98.9)	0	1 (1.1)	0	0	0
I try to keep my blood sugar high so that I will lose weight	children	38 (92.7)	1 (2.4)	2 (4.9)	0	0	0	0.179
	adolescents	87 (96.7)	0	1 (1.1)	2 (2.2)	0	0
I eat in a way to get ketones	children	40 (97.6)	0	1 (2.4)	0	0	0	0.168
	adolescents	87 (96.7)	3 (3.3)	0	0	0	0
I feel fat when I take all of my insulin	children	39 (95.1)	1 (2.4)	0	0	1 (2.4)	0	0.479
	adolescents	83 (92.2)	2 (2.2)	3 (3.3)	1 (1.1)	0	1 (1.1)
Other people tell me to take better care of my diabetes	children	20 (48.8)	7 (17.1)	3 (7.3)	0	1 (2.4)	10 (24.4)	0.003
	adolescents	18 (20)	25 (27.8)	11 (12.2)	6 (6.7)	15 (16.7)	15 (16.7)
After I overeat, I skip my next insulin dose	children	40 (97.6)	1 (2.4)	0	0	0	0	0.18
	adolescents	76 (84.4)	10 (11.1)	3 (3.3)	1 (1.1)	0	0
I feel that my eating is out of control	children	28 (68.3)	8 (19.5)	3 (7.3)	0	0	2 (4.9)	0.235
	adolescents	50 (55.6)	18 (20)	17 (18.9)	2 (2.2)	2 (2.2)	1 (1.1)
I alternate between eating very little and eating huge amounts	children	29 (70.7)	9 (22)	2 (4.9)	0	0	1 (2.4)	0.667
	adolescents	55 (61.1)	19 (21.1)	12 (13.3)	1 (1.1)	1 (1.1)	2 (2.2)
I would rather be thin than to have good control of my diabetes	children	34 (82.9)	2 (4.9)	0	0	2 (4.9)	3 (7.3)	0.537
	adolescents	74 (82.2)	2 (2.2)	5 (5.6)	0	3 (3.3)	6 (6.7)

Table 2. Comparison table between the two groups, for categorical variables, in terms of risk of EA.

	Without EA risk (n =  45)	With EA risk (n = 86)
Sex
female	18 (40%)	36 (41.9%)	p = 0.837
male	27 (60%)	50 (58.1%)
Age
children	18 (40%)	23 (26.7%)	p = 0.12
adolescents	27 (60%)	63 (73.3%)
HbA1c
< 7.5%	18 (66.7%)	17 (28.8%)	p = 0.001
> 7.5%	9 (33.3%)	42 (71.2%)