Występowanie oraz czynniki ryzyka rozszczepu kręgosłupa u dzieci

Mariana O. Ryznychuk1, Mariana I. Kryvchanska2, Irina V. Lastivka1, Roman Ye. Bulyk2

1 Pediatrics and Medical Genetics Department, Higher State Educational Establishment of Ukraine
“Bukovinian State Medical University”, Chernivtsi, Ukraine

2 Medical Biology and Genetics Department, Higher State Educational Establishment of Ukraine
Bukovinian State Medical University”, Chernivtsi, Ukraine

Abstract

Introduction: The pathogenesis of spina bifida depends on time, region, race and ethnicity. It is found in 4.7 per 10.000 of live born children worldwide.

The aim: The incidence in children of Northern Bukovina was analyzed. The spina bifida incidence for 2007-2016 in this region, as well as, compared to some countries according to EUROCAT data was studied.

Materials and methods: A retrospective study to analyze the risk factors for spina bifida was carried out. A case-control study was conducted using clinical records of 34 children with this pathology (16 boys and 18 girls) aged 0-18 years living in Northern Bukovina. 44 case records of healthy children (26 boys and 18 girls) were compared.

Results: According to EUROCAT, the prevalence of spina bifida in the studied countries varied in the range of 0.13-0.50‰. The spina bifida incidence in Northern Bukovina
(0.22 ‰) does not exceed the statistics for Ukraine (0.29 ‰) throughout the study period.

Conclusions: This study provides a comprehension overview of a number of factors determining spina bifida risks: third pregnancy, miscarriage, high emotional stress during pregnancy, TORCH infection in pregnant, poor housing, maternal age, co-habiting, residence near contaminated lands, hard physical work preconceptionally, smoking habits, military service, etc. The most probable spina bifida preventive factors in children are: high school education of parents and using folic acid during the first trimester of pregnancy. Nevertheless, our data present new factual material, which requires further in-depth study, it is already clear that all the above indicators are associated with increased risk for spina bifida-complicated pregnancies.

Wiad Lek 2018, 71, 2 cz. II, -344

 

Introduction

Practical relevance of the epidemiology of congenital anomalies (CA) study is their relation to the Eco-affiliated diseases group used as the quality indicators of the environment; WHO. Observing the dynamics and prevalence of CA contributes to the prevention of this pathology and its effectiveness [1, 2].

The most important preventive measures is the clinical examination system of the CA and the risk factors identification; which can be used for the preconception care [3, 4]. For the genome-based prediction it is important to know which factors generate the abnormal development: genetic or exogenous. According to data, it was found that 23.2% of the CA resulting with hereditary factors, 50.8% have a multi-factorial nature and approximately 2% is related to the influence of teratogenic factors. At the same time, the cause of CA in 24-33% of cases remains unclear [5, 6].

Myelocele is the most common defect of the CNS. The number of infants with this defect is steadily increasing. In particular, severe forms of spinal hernia (rachistis, meningomyelocystocet), as well as in combination with other defects, became more frequent [7]. The adverse effects of cerebrospinal hernia include severe disablement, progressive hydrocephalus, paresis and paralysis of the lower extremities and gatism in children.

It is known that the incidence of neural tube defects (NTDs) is from 1: 500 to 1: 2000 live births in different regions and ethnic groups, averaging 1: 1000. However, if in the family parents or close relatives had cases of NTDs, the probability of this defect in infants increases to 2-5%. This is subject to the second child, if the first one was born with this defect (incidence approx. 5%). Also, the presence of spontaneous abortion (miscarriage), premature birth, infant mortality in the family and relatives is also a safety signal [8]. It should be noted that in some parts of Ukraine the reproduction dynamics was investigated, and the trends are of a great concern [9].

The spina bifida incidence depends on time, region, race and ethnicity [10]. Across the globe, this disease was found to be 4.7/10.000 live births [11]. A higher incidence was reported in Northern China, Eastern Ireland, Norway and Egypt [12]. Thus, in Ireland, the occurrence of this pathology is 3-4/1000 live births, in the British Isles – 2-3.5/1.000 live births, and in Eastern Europe and the USA – 0.1-0.6/1000 births [13, 14]. K. Airede has reported the following incidence in the middle belt of Nigeria: 7/1.000 infants [15]. It should be noted that Ukraine is a multiethnic country [16], with a high proportion of interethnic marriages [17, 18, 19], and in general this is inherent in the Slavic population [20, 21], so in the nearest future such comparative evaluations are necessary to be done in different regions of the country.

The genetic predisposition to NTDs is a major indicator for the inclusion of a pregnant woman in a high-risk group. A large number of physical (radiation, thermal, mechanical), chemical (hypoxia, teratogenic poisons, hormones, malnutrition) and biological (viruses, protozoa, bacteria) factors which may be the cause of this congenital malformation have also been found implicated in the etiology of the formation of the spine in fetus [22, 23].

Most authors consider embryopathy at the stage of prenatal development of the nervous and osseous systems from the 16th day after fertilization to the end of the 8th week among possible etiological factors [24].

Among the risk factors of NTDs are the health history of parents, their harmful habits, social conditions, etc., which in different regions may have varying degrees of incidence are of great importance [25, 26].

To date, have been found the various risk factors from mother and fetus (threatened miscarriage, fetal chronic hypoxia, general medical condition of the mother, etc.) of a spinal hernia in infants [27, 28]. In recent years, the instability of the socio-economic environment among women of reproductive age, growing prevalence of somatic pathology and sexually transmitted diseases, increasing the number of women who drink alcohol and smoke during pregnancy, changes in their reproductive behavior – late pregnancy (over 35 years) is the basis for improvement, systematizing and identifying the most significant risk factors for spinal hernia in newborn babies [29]. It should be noted that in different regions of Ukraine there is a tendency to increase the variance of the age of getting married and this indicator depends on the degree of urbanization of a particular population [30, 31, 32]. All mentioned above is a ground for a detailed research in the field of clinical genetics, epidemiology and preventive medical programs and genetics services development in the country [33, 34].

The Aim

To study the risk factors and the prevalence of spina bifida in children of Northern Bukovina.

Materials and methods

The medical genetic center-based study of the spina bifida incidence was conducted in the Chernivtsi region (Northern Bukovina). The reports of the Chernivtsi Regional Diagnostic Center of the Ministry of Health of Ukraine were used – Form No. 49-zdorov. “Report on the provision of medical genetic care”, approved by the Order of the Ministry of Health of Ukraine of June 16, 1993 No. 141 (2007-2016). Also the data on the number and morbidity of the total population children in the region is contained in the statistical yearbooks of Chernivtsi region (2007-2016).

A retrospective data analysis using the registration genetic cards (f. No. 149/o), approved by the Order of the Ministry of Health of Ukraine of December 13. 1999 (2000-2016) was carried out to determine the risk factors of spina bifida. A case-control study was conducted using clinical records of 34 children with this pathology (16 boys and 18 girls) aged 0-18 years living in Northern Bukovina. The diagnosis of spina bifida for all examined children is exposed at the time of newborn birth. To identify risk factors, 44 case records of healthy children (26 boys and 18 girls) were compared. The control group was formed on a population basis, as only children whose parents were habitually resident in the territory of Northern Bukovina were subject to registration.

From the parents was collected the following data: maternal age, social class, birth order, social habits, education level, place of residence, family annual income, general medical condition, fetoplacental insufficiency, miscarriage threat, polyhydramnios/oligohydramnios, nuchal cord and gestational age. Premature/mature birth. Gynecological history, presence of abortions and miscarriages in anamnesis. Planned/unplanned pregnancy. Consumption of folic acid during first trimester of pregnancy and high emotional stress. TORCH infection in pregnant. Consumption of contraceptives and other drugs (medicines).

We calculated spina bifida incidence as the ratio of the cases registered by the medical genetic service during this period of time to the number of infants and multiplied by 1000:

The measure of association of the analyzed attributes was determined using the Odds Ratio (OR), expressed by the formula:

where A – the presence of spina bifida and the risk factor;

B – presence of spina bifida and the absence of the risk factor;

C – the the healthy children and the risk factor;

D – the healthy children and and the absence of the risk factor.

The confidence interval (CI) for OR was calculated at significance level 95%. If the odds ratio was less than 1. then the risk was reduced; if = 1. then there was no risk, if more than 1. then the risk was present.

For the assertion about the difference predicate, generally accepted probability level (p) <0.05 in medical and biological studies was taken into consideration. With such values of “p”, the observed changes in the studied features are true for 95 or more cases out of 100.

All data was analyzed by nonparametric methods of variation statistics using the MedCal software (2006) [35].

Results

The spina bifida incidence for 2007-2016 in this region, as well as, compared to some countries according to EUROCAT data was studied (Table І).

According to EUROCAT, spina bifida incidence in the population of studied countries varied in the range of 0.13-0.50 ‰.

Table І shows, that the spina bifida incidence in Northern Bukovina does not exceed the data for Ukraine throughout the studied period. Among the analyzed countries, the highest overall prevalence rate for the analyzed years was in Ireland (0.50 ‰), and the lowest in Portugal (0.11 ‰). In the Northern Bukovina (0,22 ‰), spina bifida was found 1.7 times less frequent than in Ukraine (0.29 ‰). According to Table 1. the spina bifida incidence was compared to data from the Netherlands (0.17 ‰) and Norway (0.17 ‰). Incidence in the republic of Malta was 2.1 times higher than in Northern Bukovina (0.46 ‰). Low inidence of spina bifida was observed in Portugal (0.13 ‰).

Table ІІ reports the most strong spina bifida risk factors. The analysis of risk factors has identified, that the female sex of a child is a risk factor for the development of spina bifida (OR = 1.63). In the analysis of the birth order it was found that the third pregnancy is a possible risk factor for the development of this pathology (OR = 5.63). History of preterm birth, unintended pregnancy, abortion, miscarriage and anemia in pregnant women are also risk factors of spina bifida.

According to Burmeister R. et al., 21% of mothers who gave birth to children with spinal anomalies suffered from toxicosis in the I trimester of pregnancy, and 24.1% of them had infectious diseases. The risk of miscarriage at 7-14 weeks was reporetd in 21% of pregnant women, and in most of them the previous pregnancies ended with miscarriage. 23% of women had a medical abortion procedure [36].

Consumption of folic acid in the I trimester of pregnancy is a spina bifida-preventive factor. Additional folic acid intake in the near-conception period reduces the risk of developing this pathology by approx. 70% [37].

To study the factors associated with the spinal cord diseases incidence, V.S. Polunin et al. studied the health status of 569 children with disabilities in the development of the spinal cord and their parents and found that the most significant are the factors affecting the body of a woman during pregnancy, especially in the I trimester. The authors cite the latest figures according to which in 69.4% of mothers the course of pregnancy and childbirth was accompanied by various acute diseases (acute respiratory viral infections, flu, angina, nasopharyngitis, bronchitis, acute gastritis, enteritis, etc.). The analysis of the health status of parents of children with myelodysplasia has shown that they have higher general and chronic morbidity, as well as TORCH infection detection [22]. In our study TORCH infection in pregnant women is a possible risk factor of congenital hydrocephalus (OR = 6.16).

In 2004, the work of A. Vieira was published, where using meta-analysis of data from various studies, it was not possible to detect the relationship between NTDs with the birth order; however, based on the calculations there was made a conclusion on the increased risk of spina bifida in infants with the birth order [38].

Overview of amniotic fluid analysis found that in the presence of both polyhydramnios and small veins in pregnant women there is a risk of development of the mentioned CNS pathology in a child (OR = 2.80 and OR = 1.31. respectively).

The collation of the frequency of social risk factors in the study- and comparison group showed the most significant factors for the prognosis of spina bifida in newborns, such as: residence near contaminated lands (OR = 6.16), multi-national marriage (OR = 1.34), socially disadvantaged marital status (single women) (OR = 2.41), maternal (>35 years) (OR = 2.59) and paternal age (OR = 6.54), lifestyle habits (smoking, drinking), high emotional stress of a pregnant (OR = 13.23).

A U-shaped relationship between maternal age and spina bifida risk was has been found in analyzing the results of CNS disorders dynamic monitoring in China [39]. According to this study, the incidence is higher among children of women < 20 years and > 30 years; the association of defects from the group of defects of the neural tube with low birth weight was reported. J. Nazer et al. [40], based on the analysis of the 30-year investigation of the risk factors in the etiology of congenital anomalies in Latin American hospitals shows a statistically significant increase in the incidence of these defects in infants weighing less than 1500 g, which also corresponds to the results obtained in our work.

Social class of the spouses plays an important role in this pathogeny. Thus, with the social status of a “worker” as a mother and father, as well as in the presence of severe physical labor, there is a significant risk factor of spina bifida. The probable risk factor is father’s military service before conception; due to chronic stress and hard physical work connected with it.

Educational level is also important in this pathogeny. This can be explained by the attitude of the spouses to pregnancy, planned parenthood, prevention of various physical and chemical factors impact, as well as a negative attitude to bad habits. Thus, it has been shown that higher education of parents is a preventive factor of this pathology, however, father’s incomplete secondary and specialized secondary education can be risk factors for spina bifida.

The impact of chemical factors on a father before pregnancy is a possible risk factor for this CNS pathology.

Conclusions

1. The incidence of spina bifida in children of Northern Bukovina is low, compared to Ukraine, and is on average 0.22 ‰ per study period.

2. A large number of risk factors involved in the formation of the embryology were studied, such as: third pregnancy, miscarriage, high emotional stress during pregnancy, TORCH infection in pregnant, poor housing, maternal age, co-habiting, residence near contaminated lands, hard physical work preconceptionally, smoking habits, military service, etc.

3. Possible preventive of spina bifida incidence in a child is higher education and consumption of folic acid in the I trimester of pregnancy. On the basis of the exploratory study, further studies on larger cohorts of participants based on the development of a questionnaire addressing specific questions will throw further light on the association between some maternal factors and spina bifida and provide information for public health strategies.

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ADDRESS FOR CORRESPONDENCE

Mariana Riznychuk

Department of Pediatrics and Medical Genetics

Higher State Educational Establishment of Ukraine

“Bukovinian State Medical University”,

Teatralna sq., 2, 58001, Chernivtsi, Ukraine

e-mail: rysnichuk.mariana@gmail.com

Received: 30.10.2017

Accepted: 10.03.2018

Table I. The spina bifida incidence among newborn infants of Northern Bukovina and according to EUROCAT (per 1000 live births, ‰)

Region

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

Total

Northern Bukovina

0.00

0.30

0.00

0.09

0.27

0.17

0.26

0.17

0.00

0.29

0.22

Ukraine

0.24

0.52

0.32

0.55

0.41

0.34

0.29

0.42

0.39

Ireland

0.40

0.61

0.38

0.52

0.52

0.40

0.55

0.56

0.00

0.50

Republic of Malta

1.28

0.71

1.20

0.25

0.23

0.23

0.48

0.45

0.00

0.46

Netherlands

0.28

0.17

0.22

0.23

0.23

0.12

0.13

0.06

0.13

0.17

Norway

0.22

0.16

0.19

0.18

0.15

0.15

0.11

0.17

Portugal

0.00

0.16

0.05

0.19

0.00

0.18

0.07

0.07

0.19

0.13

Table II. The most strong spina bifida risk factors in children of Northern Bukovina

Risk factor

OR

СІ

Difference probability

Female sex of a child

1.63

0.66-4.01

 

Birth order:

І pregnancy

0.50

0.20-1.25

 

ІІ pregnancy

0.41

0.14-1.22

 

ІІІ pregnancy

5.63

1.89-16.80

р<0.05

Abortions

2.93

0.68-12.70

 

Miscarriage

23.45

2.86-49.25

р<0.05

Prematurity

1.33

0.31-5.77

 

Unintended pregnancy

1.66

0.64-4.30

 

Consumption of folic acid during I trimester of pregnancy

0.50

0.20-1.23

 

Stress during pregnancy

13.23

1.56-51.91

р<0.05

Anemia

1.01

0.41-3.49

 

Miscarriage threat

0.57

0.23-1.40

 

Gestosis during I trimester of pregnancy

1.17

0.38-3.61

 

TORCH infection in pregnant

6.16

1.95-19.47

р<0.05

Chronic fetoplacental insufficiency

1.90

0.63-5.78

 

Polyhydramnios

2.80

0.48-16.29

 

Oligohydramnios

1.31

0.18-9.83

 

Social factors:

Residence with parents

0.37

0.13-1.05

р<0.05

Low income

0.59

0.22-1.63

 

Residence near contaminated lands

6.16

1.59-19.47

р<0.05

Multi-national marriage

1.34

0.36-5.08

 

Age at delivery:

< 18 years

1.30

0.08-21.62

 

26-35 years

1.02

0.39-2.67

 

> 35 years

2.59

0.69-9.72

 

Father’s age before conception:

< 18 years

0.09

0.01-0.74

р<0.05

26-35 years

1.44

0.53-3.86

 

> 35 years

6.54

1.65-25.85

р<0.05

Mother’s educational level:

Secondary

1.08

0.38-3.00

 

Incomplete secondary

9.21

1.05-80.69

р<0.05

Specialized secondary

1.17

0.45-3.01

 

Higher

0.31

0.11-0.89

р<0.05

Impact of physical factors during pregnancy

1.05

0.41-2.70

 

Unregistered marriage

2.41

0.88-6.59

р<0.05

Social status of a worker

1.86

0.67-5.19

 

Hard physical work during pregnancy

5.44

1.05-28.18

р<0.05

High emotional stress

1.22

0.43-3.46

 

Impact of chemical factors during pregnancy

0.63

0.11-3.63

 

Smoking

2.81

0.84-9.35

р<0.05

High coffee intake

1.05

0.36-3.02

 

High alcohol intake

1.35

0.54-3.35

 

Father’s educational level:

 

Secondary

1.08

0.38-3.00

 

Incomplete secondary

9.21

1.05-80.69

 

Specialized secondary

1.17

0.45-3.01

р<0.05

Higher

0.31

0.11-0.89

р<0.05

Social status of a worker

17.59

5.57-55.55

р<0.05

Hard physical work during pregnancy

2.41

0.88-6.59

р<0.05

High emotional stress

55.88

3.18-98.91

р<0.05

Impact of chemical factors during pregnancy

4.50

1.62-12.47

р<0.05

Social status of a worker

1.13

0.34-3.75

 

Hard physical work during pregnancy

35.00

9.59-72.63

р<0.05

Smoking

3.66

1.42-9.42

р<0.05

High coffee intake

1.01

0.33-3.05

 

High alcohol intake

0.59

0.23-1.54