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Publicly Available Published by De Gruyter December 20, 2016

The prevalence of dyslipidemia and associated factors in children and adolescents with type 1 diabetes

Tuba Bulut, Fatma Demirel and Ayşe Metin

Abstract

Background:

Dyslipidemia increases the frequency and severity of micro and macrovascular complications of type 1 diabetes (T1D). The present study aims to determine the prevalence of dyslipidemia and its association with clinical and laboratory findings in diabetic children and adolescents.

Methods:

The study included 202 children and adolescents with T1D. Demographic data and laboratory findings were obtained from patients files.

Results:

Dyslipidemia prevalence was found to be 26.2%. Hypercholesterolemia (15.8%) and hyperglyceridemia (12.9%) were most common findings. Age, body mass index (BMI), hemoglobin A1c (A1C) and poor metabolic control were significantly higher in cases with dyslipidemia. Smoking rate was 14.1% in the pubertal group. Poor metabolic control and dyslipidemia was found higher among smokers (p<0.05).

Conclusions:

Blood lipid levels should be monitored regularly and nutrition education should be repeated periodically to prevent and control dyslipidemia in patients with T1D. Smoking-related risks should be a part of patient education in the pubertal period.

Introduction

In patients with type 1 diabetes mellitus (T1DM), chronic complications including nephropathy, neuropathy, retinopathy, cardiovascular conditions and peripheral vascular diseases directly affect life expectancy and quality of life in the long term [1], [2]. The presence of dyslipidemia increases the frequency and severity of these complications [3].

Dyslipidemia is defined as abnormal plasma lipid levels [4], [5]. Diabetic dyslipidemia is characterized by decreased levels of high-density lipoprotein cholesterol (HDL-C) and increased low-density lipoprotein cholesterol (LDL-C) and triglycerides (TGs) [5]. It significantly increases the risk of cardiovascular diseases [6]. Good metabolic control is essential in treatment. Some adolescents may require lipid-lowering medications [4], [7].

Our study aims to determine the frequency of dyslipidemia and its association with demographic characteristics and clinical and laboratory findings in children and adolescent patients followed up for T1DM in the Pediatric Endocrinology Outpatient Clinic in our hospital.

Materials and methods

Study group

Our study included 202 patients, 3–18 years old, followed up for T1DM in the Pediatric Endocrinology Outpatient Clinic of a tertiary care children’s hospital.

Inclusion criteria

  1. Patients aged 3–18 years

  2. Patients who have been under follow-up for at least 2 years

Exclusion criteria

  1. Patients aged below 3 and above 18 years

  2. Patients with other types of diabetes [syndromic diabetes, maturity onset diabetes of the young (MODY), type 2 diabetes mellitus (T2DM)]

  3. Patients with irregular follow-up visits or inadequate dossiers and laboratory data

  4. Patients receiving lipid-lowering medication

Patients’ demographics (age, gender, age at the time of diabetes diagnosis, diabetes duration, smoking habits) were noted down.

For the assessment of smoking experience, they were asked “have you ever smoked cigarette?” If the answer was “Yes”, they were asked “how often you smoked cigarette in the last 30 days?” Smoking one or more cigarettes a day was considered as daily smoking habit [8], [9].

Physical examination findings [weight, height, body mass index (BMI), blood pressure, pubertal stage], diabetes complications (retinopathy, neuropathy, nephropathy), laboratory investigations (most recent fasting lipid profile, thyroid and celiac antibodies, microalbuminuria, renal ultrasonography findings) and familial history of diabetes, dyslipidemia and premature cardiac death were recorded.

Patients’ body weights were measured by a Barimed® Electronic Body Scale SC–105, accurate to 0.1 kg, on an empty stomach and with the children wearing their casual clothes. Height was measured barefoot using a Ayrton® Stadiometer Model S100, accurate to 0.1 cm. BMI was calculated by the kg/square of height (m2) formula. Obesity was defined as a BMI at or above the 95th percentile according to age and gender. In determining BMI percentile, “Reference Values for Body Mass Index in Turkish Children” issued by Neyzi et al. were used and BMI standard deviation score (SDS) values were calculated [10].

Tanner staging was used to evaluate puberty development. According to Tanner staging, 4 mL testicular volume in boys and breast development in girls were considered as Tanner stage II onset of puberty [11], [12].

Patients’ metabolic control state was determined based on the average of the last four A1C levels. Mean A1C levels of 6.5%–7.9% were considered as good metabolic control, 8%–8.9% moderate and ≥9% poor metabolic control.

Blood pressure measurements were performed after a 10-min rest in a sitting position, using aneroid sphygmomanometers with age-appropriate sleeves in all patients. For patients with high blood pressure readings with the first measurement, a second measurement was performed following a 30-min rest. Patients with values above the 95 percentile according to percentile charts based on age and gender were considered hypertensive and were investigated further [13].

Laboratory investigations

Blood samples were collected after a 8–10 h fasting period and analyzed by Roche Modular P800 using standard methods. Total cholesterol (TC), TG and HDL-C levels were measured. LDL-C levels were calculated by the Friedewald formula using the available lipid data [14]. Serum TC levels above 200 mg/dL, TG levels above 150 mg/dL, LDL-C levels above 130 mg/dL or HDL-C levels below 40 mg/dL were considered as dyslipidemia [13].

Hemoglobin A1c (A1C) measurement was performed using the turbidimetric immunoassay method on a Roche Modular P800 device. The results were expressed as percentages.

Fasting insulin, thyroid-stimulating hormone (TSH) and free T4 (fT4) were assayed on Beckman Coulter DxI 800 with two-section and two-step enzymatic immunoassay methods. According to the reference values of the Beckmann Coulter TSH and fT4 kits, the upper and lower values were 0.34 and 5.6 mIU/mL for TSH and 0.6 and 1.2 ng/dL for fT4, respectively.

Renal ultrasonography was performed using Toshiba Xarioi Style ultrasonography in the radiology department of our hospital.

Statistical analysis

Statistical analysis of the data was performed using the Statistical Package for the Social Sciences 17.0 (SPSS, Inc. Chicago IL, USA, Microsoft). Values were expressed as mean±SD (minimum-maximum). A student’s t-test was used to compare the mean values of the numeric variables, and a χ2 test was used to compare the mean values of the non-numeric variables. Comparison of multiple numeric analyses was performed using a oneway Anova test (Post hoc: Bonferroni). Statistical significance was set at p<0.05.

The study protocol was approved by the decision of our hospital Ethics Committee (decision number: 2013-147).

Results

The study included 114 girls (56.4%) and 88 boys (43.6%) and the mean age was 12.8±3.86 years (3–18 years).

Patients’ demographics and physical examination findings by gender are listed in Table 1.

Table 1:

Demographic data of patients with type 1 diabetes.a

TotalFemaleMalep-Value
n (%)202 (100.0)114 (56.4)88 (43.6)
Age, years12.8±3.813.2±3.812.3±3.9NS
Age at diagnosis, years6.9±3.77.2±3.96.7±3.9NS
Diabetes duration, years5.6±3.15.8±3.25.2±0.4NS
BMI, kg/m220.1±3.720.9±3.918.9±2.90.0001
BMI SDS0.1±1.10.3±1.10.2±1.040.001
Puberty (prepubertal/pubertal), n54/14821/9333/550.04
Metabolic control
 Good33 (16.3)17 (14.9)16 (18.2)NS
 Moderate104 (51.5)55 (48.2)49 (55.7)
 Poor65 (32.2)42 (36.8)23 (26.1)
Hypertension7 (3.5)6 (5.3)1 (1.1)NS
Daily smoking21 (10.4)7 (6.1)14 (15.9)0.035

aResults are presented as mean±standard deviation or n (%). NS, not significant; BMI, body mass index; BMI SDS, body mass index standard deviation score.

Girls and boys in our study did not differ with respect to age, age at diagnosis, diabetes duration, metabolic control or hypertension. Higher proportions of the girls were pubertal compared to boys and they had significantly higher BMI and BMI SDS values (p<0.05). Smokers’ ratio was 10.4% in the whole group. Smoking was significantly more common among boys (p<0.05) (Table 1).

Patients’ demographic findings by puberty status are listed in Table 2.

Table 2:

Demographics by pubertal status of patients with type 1 diabetes.a

TotalPrepubertalPubertalp-Value
n (%)202 (100)54 (26.7)148 (73.3)0.0001
Age, years12.8±3.97.9±2.314.5±2.50.0001
Age at diagnosis, years6.9±3.73.73±2.48.2±3.30.0001
Diabetes duration, years5.6±3.163.88±1.76.2±3.30.0001
Gender (female/male), n114/8819/3494/540.004
BMI, kg/m220.1±3.7016.8±1.721.2±3.50.0001
BMI SDS0.1±1.10.18±0.70.07±1.2NS
Metabolic control
 Good33 (16.3)11 (20.4)22 (14.9)0.001
 Moderate104 (51.5)36 (66.7)68 (45.9)
 Poor65 (32.2)7 (13.0)58 (39.2)
Hypertension7 (3.5)1 (1.9)6 (4.1)NS
Daily smoking21 (10.4)0 (0)21 (14.2)0.0001

aResults are presented as mean±standard deviation or n (%). NS, not significant; BMI, body mass index; BMI SDS, body mass index standard deviation score.

Poor control ratio was significantly higher in puberty (p<0.05). The majority of hypertensive subjects were in the pubertal group. All smokers were pubertal (p<0.05) (Table 2).

Distribution of laboratory data by gender and puberty and differences between the groups are presented in Table 3.

Table 3:

Laboratory data by gender and pubertal status of patients with type 1 diabetes.a

TotalFemaleMalep-ValuebPrepubertalPubertalp-Valuec
n (%)202 (100)114 (56.4)88 (43.6)53 (26.2)148 (73.3)
A1Cmean, %8.6±1.68.8±1.68.5±1.5NS8.1±0.98.8±1.70.003
TC, mg/dL168.8±36.2172.2±38.5164.3±32.6NS161.7±26.3171.4±38.90.046
TG, mg/dL93.3±58.194.7±57.791.4±58.9NS69.1±27.7102.1±63.60.001
LDL-C, mg/dL91.5±28.793.8±30.488.5±26.3NS88.6±23.192.6±30.6NS
HDL-C, mg/dL57.7±13.658.7±14.356.4±12.4NS57.5±13.157.8±13.8NS
Dyslipidemia53 (26.2)30 (26.3)23 (26.1)NS10 (18.5)43 (29.1)NS
 Hypercholesterolemia32 (15.8)19 (16.7)13 (14.8)NS5 (9.3)27 (18.2)NS
 Hyperglyceridemia26 (12.9)15 (13.2)11 (12.5)NS1 (1.9)25 (16.9)0.04
 Increased LDL-C21 (10.4)15 (13.2)6 (6.8)NS3 (5.6)18 (12.2)NS
 Decreased HDL-C11 (5.4)4 (3.5)7 (8.0)NS6 (11.1)5 (3.4)NS
TSH, mIU/mL2.4±1.72.3±1.82.6±1.6NS2.7±1.82.3±1.7NS
fT4, ng/dL0.9±0.10.9±0.20.9±0.1NS0.9±0.10.8±0.10.01
Autoimmune thyroiditis (+)48 (23.8)31 (27.2)17 (19.3)NS10 (18.5)38 (25.7)NS
Celiac disease (+)15 (7.4)9 (7.9)6 (6.8)NS6 (11.1)9 (6.1)NS
Microalbuminuria11 (5.4)7 (6.1)4 (4.5)NS1 (1.9)10 (6.8)NS

aResults are presented as mean±standard deviation or n (%). bComparison results of laboratory data by gender and cpuberty are given. NS, not significant; TC, total cholesterol; TG, triglycerides; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TSH, thyroid-stimulating hormone; fT4, free thyroxin.

Our study group was in the moderate metabolic control group according to the mean A1C level. Dyslipidemia rate in the whole group was 26.2%, and the most frequent types of dyslipidemia were hypercholesterolemia (15.8%) and hyperglyceridemia (12.9%). Of the patients, 23.8% had autoimmune thyroiditis, 7.4% had celiac disease and 5.4% had microalbuminuria. Retinopathy or neuropathy was not detected in our patients. Laboratory parameters did not vary significantly between the two genders (p>0.05). Total cholesterol and TG and A1C levels were higher in puberty (p<0.05). Prepubertal cases had higher fT4 levels (p<0.05) (Table 3).

In the families of the patients, the frequencies of dyslipidemia, T2D and cardiac death were 20.8%, 24.3% and 7.4%, respectively. No relationship was observed between dyslipidemia frequency of our patients and familial history of dyslipidemia, diabetes or premature death (p>0.05).

The relationship between dyslipidemia and clinical/laboratory findings and familial history is shown in Table 4.

Table 4:

The association between dyslipidemia and clinical/laboratory findings.

Dyslipidemia (+)Dyslipidemia (−)p-Value
n, %53 (26.2)149 (73.8)
Age, years13.7±3.412.4±3.90.032
Gender (female/male)30/2384/65NS
Puberty (prepubertal/pubertal)10/4344/105NS
BMI, kg/m221.0±3.719.6±3.60.026
BMI SDS0.3±1.20.3±1.1NS
Obesity frequency5 (9.4)10 (6.7)NS
Diabetes duration6.1±3.45.4±3.05NS
Mean A1C, %9.2±1.88.4±1.40.005
Hypertension4 (7.5)3 (2.0)NS
TSH, mIU/mL2.6±2.32.3±1.4NS
fT4, ng/dL0.9±0.10.9±0.1NS
Celiac disease5 (9.4)10 (6.7)NS
Autoimmune thyroiditis15 (28.3)33 (22.1)NS
Microalbuminuria3 (5.7)8 (5.4)NS
Metabolic control
 Good7 (21.1)26 (78.8)0.043
 Moderate22 (21.2)82 (78.8)
 Poor24 (36.9)41 (63.1)
Daily smoking12 (22.6)9 (6.0)0.003
Familial dyslipidemia12 (22.6)30 (20.1)NS
Familial diabetes13 (24.5)36 (24.2)NS
Familial cardiac death2 (3.8)13 (8.7)NS

aResults are presented as mean±standard deviation or n (%). NS, not significant; BMI, body mass index; BMI SDS, body mass index standard deviation score; TSH, thyroid-stimulating hormone; fT4, free thyroxin.

Mean age, mean A1C levels and BMI were found to be significantly higher in patients with dyslipidemia (p<0.05). The ratio of poor metabolic control and smoking was also higher in dyslipidemia (+) group (p<0.05) (Table 4).

Twenty-one (14.2%) of the 148 pubertal patients were smokers. The results of the comparison between smokers and non-smokers are presented in Table 5.

Table 5:

Differences between the clinical and laboratory findings of smoking and non-smoking adolescents with type 1 diabetes.

SmokerNon-smokerp-Value
n (%)21 (14.1)127 (85.8)
Age, years16.7±1.114.2±2.40.001
Gender (female/male)7/1486/410.035
BMI, kg/m220.4±2.621.3±3.6NS
BMI SDS−0.55±1.30.18±1.10.021
Obesity frequency0 (0)15 (11.8)0.0001
Diabetes duration, years6.9±2.96.1±3.4NS
Mean A1C, %11.05±1.78.4±1.40.00
Hypertension1 (4.8)5 (3.9)NS
Dyslipidemia12 (57.1)31 (24.4)0.003
 Hypercholesterolemia6 (28.6)21 (16.5)0.005
 Hyperglyceridemia10 (47.6)15 (11.8)0.01
 Increased LDL-C2 (9.5)3 (2.4)NS
 Decreased HDL-C4 (19)14 (11)NS
Microalbuminuria2 (9.5)8 (6.3)NS
Metabolic control
 Good22 (17.3)0.001
 Moderate2 (9.5)66 (52)
 Poor19 (90.5)39 (30.7)

aResults are presented as mean±standard deviation or n (%). NS, not significant; BMI, body mass index; BMI SDS, body mass index standard deviation score; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol.

Smoking rate in male adolescent diabetics was found as much as twice as the female ones. Dyslipidemia was significantly more frequent among smokers (57.1%), especially the frequencies of hypercholesterolemia and hyperglyceridemia that were higher in cases with dyslipidemia (p<0.05). Pubertal patients who smoked had significantly poorer metabolic control than non-smokers (90.5%). Mean age and mean A1C level were higher and BMI SDS was lower among smokers (Table 5).

Discussion

Dyslipidemia prevalence was found in 26.2% of the 202 children and adolescents with T1DM and hypercholesterolemia and hyperglyceridemia were the most common types in our patients. Dyslipidemia frequency in diabetic children varies between 3.8% and 72.5% in different studies [14], [15], [16], [17], [18], [19], and hypercholesterolemia was reported as the most frequent finding [16], [19], [20], [21]. Redondo et al. found a dyslipidemia prevalence of 3.8% in the US with 11,348 T1D patients aged 2–18 years. The authors attributed this low ratio of dyslipidemia to the facts that the patients included in the study were mostly younger and highly active children and that the number of obese subjects was low [18]. In a study from Brazil, the ratio of dyslipidemia among 239 patients with T1DM was 72.5% and it was shown that dyslipidemia developed most frequently due to hypercholesterolemia and less frequently due to hyperglyceridemia. The authors described that the high frequency of dyslipidemia was due to the broad age range of participants and the increased frequency of sedentary lifestyles, carbohydrate-rich dietary habits and obesity with increasing age [17]. In a study from Turkey, the rate of dyslipidemia in patients with T1D was found to be 30.3% [22]. Local dietary habits, selected age range and different reference ranges for dyslipidemia are some of the reasons for different dyslipidemia frequencies from different studies.

In our study, age, A1C and BMI were higher in patients with dyslipidemia compared to those without dyslipidemia and the number of patients with poor metabolic control was found to be significantly higher. Dyslipidemia frequency was not different between genders. A1C, TC and TG levels and hypercholesterolemia and hyperglyceridemia frequencies were higher in pubertal subjects. Girls in the study group had higher BMI and BMI SDS and their pubertal stages were advanced although the girls and boys had similar mean ages in our study group. Previous studies have also reported that girls had higher BMI than boys [17], [23], [24], [25]. Girls reaching puberty earlier than boys may explain the more advanced pubertal stage in the same age group. Increasing estrogen effect in girls may result in a tendency for weight gain. Due to the altered psychological and hormonal balance and adaptation difficulties in puberty, metabolic control of diabetes is harder and the rate of poor metabolic control is higher in these cases [26], [27], [28]. In addition to all these factors, changing dietary habits with poor treatment compliance are associated with increased frequency of dyslipidemia. Regular and more frequent A1C and lipid monitoring during puberty is recommended [26], [27], [28].

There is a relationship between dyslipidemia and high A1C levels. Increased lipid levels as a characteristic of patients with poor metabolic control have been shown by many studies [14], [29], [30], [31], [32]. A study by Maahs et al. evaluated lipid changes during the follow-up of patients with T1D over a period of about 2 years. The authors found an association between high BMI and lipid levels independent of glycemic control and demonstrated that uncontrolled and unhealthy diets lead to increases in BMI and lipid levels and consequently to poor metabolic control [33]. Perez et al. found a higher frequency of dyslipidemia among girls. Hypercholesterolemia is reported to be more common among diabetic compared to non-diabetic males [34]. Another study determined that girls had higher lipid levels, among which hypercholesterolemia was the most common, and that age, diabetes duration, increased BMI and A1C levels were associated with lipid anomalies [24], [35]. Polak et al. investigated abnormal lipid profiles in children with T1D during puberty and described that cholesterol levels were not associated with metabolic control, while triglyceride levels could have a weak correlation with metabolic control [19]. Heyman et al. studied the relationship among diet, physical activity and metabolic control in adolescent girls late in puberty and reported that unhealthy diets and low physical activity lead to impaired metabolic control and increased lipid levels [27].

Autoimmune comorbidities, micro and macrovascular complications and positive familial history for cardiovascular risk factors were not found to be associated with dyslipidemia frequency in our patients. There are many studies in the literature which determined a positive relationship between microalbuminuria and especially dyslipidemia in T1D [22], [36], [37], [38], [39]. Marcovecchio et al. found no difference between genders with respect to family history of dyslipidemia [40]. Likewise, another study found that total cholesterol levels and parental cholesterol levels were associated in patients with T1D [38]. The number of patients in our study may be inadequate to demonstrate such a relationship. The low level of knowledge and awareness of families about the existing risk factors might be a handicap for the collection of reasonable data.

In this study, 21 (14.2%) of 148 adolescent cases were smokers. A recent study with high school students in Ankara demonstrated that 43% of the boys and 15% of the girls were smokers [41]. In our patient group, the ratio of smokers was lower compared to the corresponding age groups based on the current data, but is still considerably high, especially in male adolescent diabetics. Smoking was generally observed to be much more common among males in studies performed with patients with T1D [23], [25]. We found a significantly higher frequency of dyslipidemia among smokers (57.1%). Increased hypercholesterolemia and hyperglyceridemia rates in this group were remarkable. Smokers had poorer metabolic control, higher mean age and higher mean A1C levels. Schwab et al. similarly reported higher A1C, total cholesterol and LDL-C levels in T1D adolescent smokers [42]. A study from Brazil investigating poor metabolic control and endothelial dysfunction in patients with T1DM determined a positive relationship between age, smoking and dyslipidemia and hypertension [44]. Smoking and dyslipidemia are major risk factors for chronic complications of T1DM [44], [45], [46], [47], [48], [49]. Another study emphasizes that smoking is one of the most influential factors for atherosclerosis [50].

In conclusion, the frequency of dyslipidemia is high among children and adolescents with T1DM and increases further with age. Smoking was also found to be an important risk factor for dyslipidemia in T1D adolescents. Therefore, lipid levels should be monitored closely and healthy diet education should be repeated in patients with T1D. Adolescents and families should be informed and their awareness increased about the risks of smoking. This should particularly be a part of diabetes education.


Corresponding author: Fatma Demirel, MD, Department of Pediatrics, Yıldırım Beyazıt University, Medical School, Ankara, Turkey; and Department of Pediatric Endocrinology, Ankara Children’s Hematology and Oncology Training Hospital, Ankara, Turkey, Phone: +9 0533 635 4895, Fax: +9 0312 347 2330

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

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Received: 2016-3-20
Accepted: 2016-8-29
Published Online: 2016-12-20
Published in Print: 2017-2-1

©2017 Walter de Gruyter GmbH, Berlin/Boston