Abstract: Hyperbetalipoproteinemia is a risk of atherosclerosis and thrombosis, whichlead to
a risk factor for coronary artery disease, hypertension, and stroke - the main causes of
mortality globally. This study aimed to determine environmental factors associated with
hyperbetalipoproteinemia in children in Hanoi. A case-control study was conducted with a
sample of 420 children (41 children with hyperbetalipoproteinemia and 379 children without
hyperbetalipoproteinemia) aged 6 to 11 years from primary schools in Hanoi. The results
obtained by multi-variate logistic regression and Bayesian Model Averaging (BMA) analysis
showed that the optimal predictive model of hyperbetalipoproteinemia in 6 - 11 year-old
children in Hanoi included ‘appetite of eating eggs’, ‘caesarean delivery’, and ‘eating slowly’
factors. These findings suggested a reduction in consumption of eggs (less than 5 eggs/week),
avoidance of caesarean delivery, and maintaining the ‘eating slowly’ habit to reduce the risk
of hyperbetalipoproteinemia for 6 - 11 year-old children.
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JOURNAL OF SCIENCE OF HNUE DOI: 10.18173/2354-1059.2016-0072
Natural Sci. 2016, Vol. 61, No. 9, pp. 185-192
This paper is available online at
185
RELATIONSHIP BETWEEN SOME ENVIRONMENTAL FACTORS
AND HYPERBETALIPOPROTEINEMIA IN 6 - 11 YEAR-OLD CHILDREN IN HANOI
Nguyen Thi Hong Hanh
1
, Bui Thi Nhung
2
, Le Thi Hop
2
and Tran Quang Binh
3
1
Faculty of Biology, Hanoi National University of Education
2
National Institute of Nutrition
3
National Institute of Hygiene and Epidemiology
Abstract: Hyperbetalipoproteinemia is a risk of atherosclerosis and thrombosis, whichlead to
a risk factor for coronary artery disease, hypertension, and stroke - the main causes of
mortality globally. This study aimed to determine environmental factors associated with
hyperbetalipoproteinemia in children in Hanoi. A case-control study was conducted with a
sample of 420 children (41 children with hyperbetalipoproteinemia and 379 children without
hyperbetalipoproteinemia) aged 6 to 11 years from primary schools in Hanoi. The results
obtained by multi-variate logistic regression and Bayesian Model Averaging (BMA) analysis
showed that the optimal predictive model of hyperbetalipoproteinemia in 6 - 11 year-old
children in Hanoi included ‘appetite of eating eggs’, ‘caesarean delivery’, and ‘eating slowly’
factors. These findings suggested a reduction in consumption of eggs (less than 5 eggs/week),
avoidance of caesarean delivery, and maintaining the ‘eating slowly’ habit to reduce the risk
of hyperbetalipoproteinemia for 6 - 11 year-old children.
Keywords: Environmental factors, hyperbetalipoproteinemia, 6 - 11 year-old children.
1. Introduction
Hyperbetalipoproteinemia, elevated low density lipoprotein-cholesterol (LDL-C), is one of
components of dyslipidemia. Hyperbetalipoproteinemia is the risk of atherosclerosis and
thrombosis - leading risk factors for coronary artery disease, hypertension, and stroke - the main
cause of mortality globally [1]. Nowadays, hyperbetalipoproteinemia is a great challenge for
public health not only in developed but also in developing countries. It is alarming that the rate of
hyperbetalipoproteinemia in children has been rising in recent years. This is proportional to the
percentage of children with over-weight or obesity. In 2013, according to the results of the
research on over-weight and obesity children at age of 4 - 9 years in Hanoi, the
hyperbetalipoproteinemia prevalence was 12.6% [2]. Hyperbetalipoproteinemia in childhood can
progress till adulthood and causes premature damage to children such as fatty liver,
atherosclerosis [3]. Therefore, early detection of hyperbetalipoproteinemia in children will help
prevent complications and reduce cardio-vascular risk in the future.
Received June 27, 2016. Accepted November 26, 2016.
Contact Nguyen Thi Hong Hanh, e-mail address: hanhphucmauhong111@yahoo.com
Nguyen Thi Hong Hanh, Bui Thi Nhung, Le Thi Hop and Tran Quang Binh
186
Hyperbetalipoproteinemia is well-known as a multi-factorial disease which is influenced by
gene-gene and gene-environment interactions. There are many environmental factors related to the
plasma lipid profile, such as socio-economic status, diet and physical activity, and especially
obesity [4]. However, in Vietnam, studies on the relationship between environmental factors and
hyperbetalipoproteinemia in children are still limited. Therefore, this study aimed to determined
which environmental factors related to hyperbetalipoproteinemia in 6 - 11 year-old children in
Hanoi. An understanding of this relationship may provide new insights into target preventive
intervention for coronary artery disease.
2. Content
2.1. Subjects and methods
* Study subjects
The study subjects aimed for primary school children in Hanoi, despite having no evidence of
diseases related to atherosclerosis, CAD, diabetes and mental disorder. None of them was using
lipid-lowering medication when their blood sample was taken.
* Study design
A case-control study was carried out from 2011 to 2012. Case group included 41 children
with hyperbetalipoproteinemia, and control group included 379 children without
hyperbetalipoproteinemia. The research protocol was approved by the Ethics Committee of the
National Institute of Nutrition of Vietnam. Written consent to participate in the study was given
by the parents of all subjects.
Hyperbetalipoproteinemia was diagnosed according to the criteria of the National Cholesterol
Education Program (NCEP) [5]. Hyperbetalipoproteinemia was defined as LDL-C 130 mg/dL.
Children in control group had all lipid component levels in the normal ranges (TG < 70 mg/dL
with children age under 10 years or TG 90 mg/dL with children age uper 10 years; TC < 170
mg/dL; HDL-C > 45 mg/dL; LDL-C < 110 mg/dL).
* Measurements
Blood lipids and lipoproteins were measured fast on samples obtained after an overnight.
Blood samples were collected in EDTA containing tubes. Serum TC and TG were determined
with enzymatic method. Serum HDL-C and LDL-C were measured through a direct assay. All
determinations were performed with Auto-Analyzer (Type Architect C8000; Abbott Ltd., United
States of America) in Medlatec Hospital of Hanoi City.
A questionnaire was provided along with consent forms and parents were asked to provide
information regarding their child’s general health, socio-economic status (food costs per person
per month), neo-natal characteristics (babies delivery type, birth weight, weaning time, beginning
time to take a punch, drinking formula milk during the first six months), dietary behaviors
(gluttonous, eating fast/slowly, gorge, having sub- meal, appetite of eating eggs/sweet food/fatty
food/fruits and vegetables), physical activity (exercises, means of transport to the school, total
time forwatching television and playing computer games, nap time, night sleep duration).
Relationship between some environmental factors and hyperbetalipoproteinemia
187
The body weight of participants was measured to the nearest 0.1 kg with standardized
medical scales. Subjects were weighed without shoes and minimum of clothing. The height was
measured to the nearest 0.1 cm. Body mass index (BMI) was calculated as weight divided by
height squared (kg/m
2
). Waist circumference was measured at the end of a normal expiration to
the nearest 0.1 cm at the mid-point between the last floating rib and the top of the iliac crest. Hip
circumference was measured at the level of the symphysis pubis and the greatest gluteal
protuberance. Waist-to-hip ratio was calculated as waist circumference (in cm) divided by hip
circumference (in cm).
* Statistical analysis
Qualitative variables were expressed as percentages. Quantitative variables were expressed as
means ± SD if variables were normal distribution or median (inter-quartile range) if variables
were not normal distribution. Chi-square test or independent-sample T test or Mann-Whitney U
test were used when appropriate. The relationship between risk factors and
hyperbetalipoproteinemia was tested by binary logistic regression analysis. Age, gender, and BMI
were adjusted for the statistical analysis. Risk factor probability set for predictive models was
calculated by Bayesian Model Averaging (BMA) analysis. The statistical analyses were done with
the statistical software package SPSS 16.0 (SPSS Inc., Chicago, Illinois), and R 3.2.3
(https://www.r-project.org). A P-value of less than 0.05 was considered statistically significant.
2.2. Results and discussion
2.2.1. Characteristics of the study subjects
Lipid profile and anthropo-metric characteristics of the subjects in case and control groups
are presented in Table 1. There were significant differences between case and control groups in
obese status, TG, TC, LDL-C, and TC/HDL-C (P < 0.05). There was no difference of gender, age,
weight, height, BMI, waist circumference, waist to hip ratio, blood pressure, and HDL-C level
between the two groups (P > 0.05).
Table 1. Characteristics of the study subjects
Parameter
Controls
(n = 379)
Cases
(n = 41)
P
Male (%) 73.4 71.4 0.870
Age (years)
b
8.0 (7.1 - 9.1) 8.2 (7.4 - 9.0) 0.365
Weight (kg)
b
30.6 (23.6 - 37.6) 34.9 (27.1 - 38.9) 0.394
Height (cm)
a
127.3 ± 9.2 127.9 ± 7.0 0.819
Obesity (%) 34.3 61.5 0.027
BMI (kg/m
2
)
b
17.3 (15.0 - 22.0) 21.9 (16.3 - 23.1) 0.065
Waist circumference (cm)
b
58.0 (51.8 - 69.6) 68.3 (55.5 - 72.8) 0.141
Waist to hip ratio
a
0.89 ± 0.07 0.90 ± 0.72 0.548
Systolic blood pressure 110.6 ± 14.7 117.6 ± 9.4 0.206
Nguyen Thi Hong Hanh, Bui Thi Nhung, Le Thi Hop and Tran Quang Binh
188
(mmHg)
a
Diastolic blood pressure
(mmHg)
a
71.1 ± 12.7 78.4 ± 11.3 0.133
Triglyceride (mmol/L)
b
62.8 (49.6 - 77.9) 89.8 (63.7 - 123.9) 0.001
Total cholesterol (mmol/L)
a
144.7 ± 22.8 222.8 ± 30.6 < 0.0001
HDL-C (mmol/L)
b
54.3 (47.2 - 63.0) 50.8 (46.3 - 55.2) 0.575
LDL-C (mmol/L)
b
80.8 (71.9 - 94.4) 138.1 (134.4 - 174.5) < 0.0001
TC/HDL-C
b
2.62 (2.33 - 3.06) 3.70 (3.27 - 4.11) < 0.0001
a
Data are mean ± SD.
b
Data are median (interquartile range). P-values obtained by Student
T test or Mann-Whitney U test or Chi-square test. Bold values indicate significant differences
between cases and controls. BMI, body mass index; HDL-C, high-density lipoprotein-cholesterol;
LDL-C, low-density lipoprotein-cholesterol; TC, total cholesterol
2.2.2. The relationship between some environmental factors and hyperbetalipoproteinemia
in 6 - 11 years old children in Hanoi using logistic regression analysis
All variables collected from the questionnaire were analyzed using logistic regression
adjusted for age, gender and BMI. The variables related significantly to hyperbetalipoproteinemia
are presented in Table 2.
The analyzed results of relationship between some factors and hyperbetalipoproteinemia
showed that ‘caesarean delivery’ and ‘appetite of eating eggs’ increased the
hyperbetalipoproteinemia risk, and ‘eating slowly habit’ tended to reduce the
hyperbetalipoproteinemia risk (Table 2).
Table 2. The relationship between some environmental factors
and hyperbetalipoproteinemia in 6 - 11 year-old children in Hanoi
Characteristics OR (95%CI) P OR
*
(95%CI) P
* ± SE
Neonatal characteristics
Vaginal delivery 1
Caesarean delivery 3.4 (1.3 - 4.9) 0.049 3.3 (1.0 - 10.7) 0.046 1.19 ± 0.06
Dietary behaviors
Eating normally 1 1
Eating slowly 0.1 (0.1 - 1.0) 0.065 0.2 (0.1 - 1.0) 0.052 -1.53 ± 0.07
Appetite of eating eggs
(> 5 eggs/week)
5.2 (1.7 - 15.5) 0.003 7.5 (2.3 - 24.1) 0.001 2.01 ± 0.05
OR, P obtained after adjusted for age, gender and BMI. OR
*
, P
*
, obtained by multi-variate
logistic regression. 95% CI (95% confidence interval)
Our findings are consistent with the theory that caesarean delivery disrupts the normal
bacterial colonization of the newborn. During vaginal delivery, the fetus is coated by and
Relationship between some environmental factors and hyperbetalipoproteinemia
189
swallows bacterial strains from the maternal vaginal and gastro-intestinal tracts. Children who are
delivered by caesarean section miss this normal source of bacterial colonization. Their intestines
are colonized by micro-biota derived from contact with mothers’ skin, and from other sources [6, 7].
Therefore, caesarean delivery may affect the child's digestive system. Several studies have
demonstrated that caesarean delivery is associated with increased body mass in childhood and
adolescence [6]. Besides, caesarean delivery also affect the activities of endocrine glands,
especially the thyroid hormone in children, which is related to dyslipidemia [8].
Eggs contains a natural source of folate, riboflavin, selenium, choline, vitamin B12, and fat-
soluble vitamins A, D, E, and K. Eggs also provide high-quality, bio-available protein [9]. Thus,
evidences suggest that eating less than 3 eggs/week results in a protective factor for cardiovascular
disease [10]. In addition, some studies didn’t show the association between egg consumption with
dyslipidemia [11]. However, egg, a concentrated source of cholesterol (one yolk provides ~215
mg of cholesterol), had been widely known as a risk factor of dyslipidemia and heart disease [12].
Data from some studies showed that consumption of more than 3 eggs per day adversely affect the
lipid profile [13]. So, WHO recommended that children and adolescents should eat an average of
3 - 4 eggs/week to help provide essential protein and cholesterol for the children’s development.
In our study, there was no relationship between residence, number of persons living in a
household, food costs and hyperbetalipoproteinemia. Neo-natal characteristics including: birth
weight, weaning time, beginning time to take a punch, and drinking formula milk during the first
six months did not associate with hyperbetalipoproteinemia (P > 0.05). Some dietary behaviors
(gluttonous, eating fast, gorge, having sub-meal, appetite of sweet food/fatty food/fruits and
vegetables); physical activity (exercise, transport means to the school, total time of watching
television and playing computer games, nap time, night sleep duration), and obesity-related traits
(normal weight/obesity, BMI, waist circumference, hip circumference, waist to hip ratio, having
overweight-obesity parents) did not associate with hyperbetalipoproteinemia (P > 0.05). The
limitations of our study were that some simple and easily-collected variables used for primary
school children may not accurately reflect the level of physical activity and diets of children. Thus,
the association of these variables with hyperbetalipoproteinemia in primary school children in
Hanoi was not found.
Model
Number
of risk
factor
Age Gender
Caesarean
delivery
Eating
slowly
Appetite
of eating
eggs
PH-L
test
AUC
1 5 X X X X X 0.772 0.803
2 4 X X X X 0.768 0.822
3 3 X X X 0.253 0.814
Figure 1. Multi-variate logistic regression analysis model of the relationship
between some environmental factors and hyperbetalipoproteinemia
in 6 - 11 year-old children in Hanoi using backward conditional method
Note. X: Yes; P obtained by Hosmer-Lemeshow test
H-L: Hosmer-Lemeshow; AUC: Area Under the Curve
Nguyen Thi Hong Hanh, Bui Thi Nhung, Le Thi Hop and Tran Quang Binh
190
To select the environmental factors associated to hyperbetalipoproteinemia for optimal
prediction model, a backward conditional method was used. The results are show in Figures 1 and 2.
Three models were selected when using backward conditional method. These three models
had PH-L test > 0.05. Predictability of the three models was good with AUC range from 0.803 to 0.822.
Figure 2. ROC graph in the model predictions of the relationship between some environmental
factors and hyperbetalipoproteinemia in 6 - 11 year-old children in Hanoi
In three selected models, predictability of the model 3 was 81.4% with three factors
(caesarean delivery, appetite of eating eggs and ‘eating slowly’ habit). Therefore, this model is the
optimal prediction for hyperbetalipoproteinemia in 6 - 11 year-old children in Hanoi.
2.2.3. The relationship between some environmental factors and hyperbetalipoproteinemia
in 6 - 11 years old children in Hanoi using Bayesian Model Averaging analysis
To evaluate the probability that risk factors set for the predictive models of
hyperbetalipoproteinemia in 6 - 11 year-old children in Hanoi, we used Bayesian Model
Averaging (BMA). BMA offers a coherent approach to accounting for model uncertainty. BMA
has also been demonstrated to improve predictive performance, and to avoid the problem of over-
statement of the strength of evidence - a problem when P-values are computed after traditional
variable selection [14]. BMA is useful after a careful scientific analysis of the problem at hand.
BMA offers one more tool in the toolbox of applied statisticians for improved data analysis and
interpretation [15].
Figure 3. Predictive hyperbetalipoproteinemia models selected by BMA in children
Blue: protective factor; Red: risk factor; right column: probability of factor in the predictive models
Relationship between some environmental factors and hyperbetalipoproteinemia
191
Results of BMA analysis showed that probability that ‘appetite of eating eggs’, ‘caesarean
delivery’ and ‘eating slowly’ factors were set for the predictive hyperbetalipoproteinemia models
in children in Hanoi was 94.5%, 39.6% and 26.1%, respectively (Figure 3). This result showed
that ‘appetite of eating eggs’, ‘caesarean delivery’, and ‘eating slowly’ factors were valuable in
predicting hyperbetalipoproteinemia in 6 - 11 year-old children in Hanoi.
3. Conclusion
The results obtained by multi-variate logistic regression and BMA analysis showed that the
optimal predictive models of hyperbetalipoproteinemia in 6-11 year-old children in Hanoi
included ‘appetite of eating eggs’, ‘caesarean delivery’ and ‘eating slowly’ factors.
These findings suggest a reduction in consumption of eggs (less than 5 eggs/week),
avoidance of caesarean delivery, and maintaining the ‘eating slowly’ habit to reduce the risk of
hyperbetalipoproteinemia and heart disease for 6-11 year-old children.
Acknowledgements. The authors would like to thank colleagues at the National Institute of
Nutrition, and Hanoi National University of Education for their kind help and support. This study
was supported by grant No. 01C-08/05-2011-2 from Hanoi Department of Science and Technology.
REFERENCES
[1] Tziomalos K., Athyros V.G., Karagiannis A., Mikhailidis D.P., 2009. Dyslipidemia as a
risk factor for ischemic stroke. Curr. Top. Med. Chem., 9, No. 14, pp. 1291-1297.
[2] Truong T.M., Le T.H., Nguyen T.H., Ngo T.H., 2013. Prevalence of overweight, obesity
and hyperlipidemia among children 4-9 years old at some schools in Hoan Kiem district,
Hanoi. Journal of Food and Nutrition Sciences, 9, No. 3 (in Vietnamese).
[3] Tikkanen E., Tuovinen T., Widén E., Lehtimäki T., Viikari J., Kähönen M., Peltonen L.,
Raitakari O.T., Ripatti S., 2011. Association of known loci with lipid levels among children
and prediction of dyslipidemia in adults. Circ. Cardiovasc. Genet., 4, pp. 673-680.
[4] Heller D.A., de Faire U., Pedersen N.L., Dahlén G., McClearn G.E., 1993. Genetic and
environmental influences on serum lipid levels in twins. N. Engl. J. Med., 328, pp. 1150-1156.
[5] National Cholesterol Education Program, American Academy of Pediatrics, 1992. National
Cholesterol Education Program: Report of the Expert Panel on Blood Cholesterol Levels in
Children and Adolescents. Pediatrics, 89, No. 3, pp. 525.
[6] Blustein J., Attina T., Liu M., Ryan A.M., Cox L.M., Blaser M.J., Trasande L., 2013.
Association of caesarean delivery with child adiposity from age 6 weeks to 15 years.
International journal of obesity, 37, No. 7, pp. 900-906.
[7] Dominguez-Bello M.G., Costello E.K., Contreras M., Magris M., Hidalgo G., Fierer N.,
1010. Delivery mode shapes the acquisition and structure of the initial microbiota across
multiple body habitats in newborns. Proc Natl Acad Sci USA, 107, pp. 11971-11975.
[8] Herbstman J.B., Sjödin A., Apelberg B.J., Witter F.R., Halden R.U., Patterson Jr D.G.,
Goldman L.R., 2008. Birth delivery mode modifies the associations between prenatal
polychlorinated biphenyl (PCB) and polybrominated diphenyl ether (PBDE) and neonatal
thyroid hormone levels. Environmental Health Perspectives, 116, No. 10, pp. 1376-1382.
Nguyen Thi Hong Hanh, Bui Thi Nhung, Le Thi Hop and Tran Quang Binh
192
[9]