Keywords
congenital anomalies - ultrasound - prenatal - prenatal diagnosis - risk factors
Palavras-chave
anomalias congênitas - ultrassom - pré-natal - diagnóstico pré-natal - fatores de
risco
Introduction
Congenital anomalies (CAs) are among the main causes of death in children under 5
years of age.[1] It is estimated that between 3 and 7% of children are born with birth defects worldwide,[2] and that ∼ 270,000 newborns die during the first 28 days of life every year.[2]
[3] In developed countries, CA is the leading cause of death in children, while in developing
countries, mortality by CA is still not considered a public health problem.[4] However, with the control of infections and diseases of nutritional deficiency,
there is a tendency to reduce infant mortality for these reasons; thus, congenital
malformations have become important causes of perinatal mortality in countries such
as Brazil.[5]
[6] Currently, ∼ 60% of the etiology of CAs in human beings are not elucidated. However,
in around 25% of CAs, the causes seem to be multifactorial, reflecting a complex interaction
of known and unknown genetic and environmental factors, including sociocultural, racial,
and ethnic variables.[7] In Brazil, there is a shortage of data on the incidence of CA and the associated
maternal risk factors. The absence of comprehensive studies on CAs in Brazil justifies
a prospective study case control that aims to describe the frequency of structural
CAs and the characteristics of pregnant women to determine possible risk factors associated
with the structural CA. The results presented herein can help in the development of
strategies to improve the management, genetic counseling, and rehabilitation of patients
with CA as well as the taking of public health measures to determine risk factors.
Methods
This was a prospective, observational, case-control study based on a hospital population.
Pregnant women attended at a fetal medicine service in Brazil were analyzed in the
period from October 2014 to February 2016.The research ethics committee of the institution
approved the research with the number 808.377. Participants who responded to the questions
asked during the interview and performed all the prenatal follow-up at the institution
were included in the study. The collection of data was obtained through interview
of the pregnant women, using a preform that contained personal and family history
(maternal age, maternal ethnicity, previous children with CA, CA family history, and
consanguinity) data. Data on previous obstetric history (number of previous pregnancies
and prior abortions) were also verified. The presence of structural CA and its classification
was confirmed by prenatal ultrasound evaluation by a fetal medicine specialist in.
After the monitoring of ultrasounds, the pregnant women were categorized in the case
or control groups. The case group was made up of pregnant women of fetuses with structural
anomalies, and the control group by pregnant women whose fetuses did not have structural
abnormalities. The pregnant women in the case group were accompanied by the main researcher
in all the consultations performed after the diagnosis of CA. Thus, it was possible
to update the information concerning the development of the fetus. The results of
childbirth and newborns with structural anomaly were obtained by telephone contact
with the pregnant women, in the computerized reports system, and, in the cases of
childbirth performed in the hospital where the study was conducted, by consulting
the medical file. The data were analyzed through descriptive statistics (average,
standard deviation [SD], absolute frequency, relative frequency, median, confidence
interval [CI]), Chi-squared tests, odds ratio, and the IBM SPSS Statistics for Windows
version 22.0 software (IBM Corp., Armonk, NY, USA). Values of p < 0.05 were considered statistically significant.
Results
In the investigation period, 357 pregnant women were sent for attendance at the institution.
Of these, 62.46% (223/357) were pregnant with fetuses with structural anomalies (case
group), and 37.54% (134/357) were pregnant with structurally normal fetuses (control
group). The average age of pregnant women in the case group was 25.73 years, and,
in the control group, it was 25.39 years. [Table 1] describes the study population in detail.
Table 1
Description of sociodemographic and obstetric data of pregnant women
|
Variables
|
Population
|
|
Case
|
Control
|
|
n
|
%
|
n
|
%
|
|
Maternal age
|
|
≤ 18
|
32
|
14.34%
|
19
|
14.18%
|
|
19–24
|
70
|
31.40%
|
46
|
34.33%
|
|
25–30
|
69
|
30.94%
|
34
|
25.37%
|
|
31–36
|
41
|
18.39%
|
26
|
19.40%
|
|
≥ 37
|
11
|
4.93%
|
9
|
6.72%
|
|
Ethnicity
|
|
White
|
46
|
20.62%
|
45
|
33.58%
|
|
Brown
|
128
|
57.40%
|
62
|
46.27%
|
|
Black
|
45
|
20.20%
|
27
|
20.15%
|
|
Indigenous
|
4
|
1.80%
|
0
|
–
|
|
Nr. of gestations
|
|
Primigravida
|
92
|
41.26%
|
46
|
34.33%
|
|
Multigravida
|
131
|
58.74%
|
88
|
65.67%
|
|
One previous gestation
|
68
|
51.91%
|
42
|
47.73%
|
|
Two previous gestations
|
38
|
29.00%
|
33
|
37.50%
|
|
≥ Three previous gestations
|
25
|
19.09%
|
13
|
14.77%
|
|
History of abortion
|
|
No
|
180
|
80.72%
|
120
|
89.55%
|
|
Yes
|
43
|
19.28%
|
14
|
10.45%
|
|
Previous gestation
|
12
|
27.91%
|
5
|
35.72%
|
|
In one of two previous pregnancies
|
18
|
41.86%
|
2
|
14.28%
|
|
In one of ≥ three previous pregnancies
|
13
|
30.23%
|
7
|
50.00%
|
|
Children with CA
|
|
No
|
205
|
91.93%
|
131
|
97.76%
|
|
Yes
|
18
|
8.07%
|
3
|
2.24%
|
|
Previous gestation
|
2
|
11.11%
|
2
|
66.67%
|
|
In one of two previous pregnancies
|
10
|
55.56%
|
0
|
–
|
|
In one of ≥ three previous pregnancies
|
6
|
33.33%
|
1
|
33.33%
|
|
Family history of CA
|
|
No
|
148
|
66.37%
|
124
|
91.94%
|
|
Yes
|
75
|
33.63%
|
10
|
8.06%
|
|
Parents with CA
|
7
|
9.33%
|
1
|
10.00%
|
|
Brothers or grandmothers with CA
|
23
|
30.67%
|
4
|
40.00%
|
|
Uncles and grandmothers with CA
|
10
|
13.33%
|
0
|
-
|
|
Uncles, grandmothers, and cousins with CA
|
22
|
29.33%
|
5
|
50.00%
|
|
CA in several relatives
|
13
|
17.33%
|
0
|
-
|
|
Consanguinity
|
|
No
|
209
|
93.72%
|
132
|
98.51%
|
|
Yes
|
14
|
6.28%
|
2
|
1.49%
|
|
Total
|
223
|
100%
|
134
|
100%
|
Abbreviations: %, frequency; CA, congenital anomaly; mean, arithmetic mean; n, sample.
The most frequently diagnosed CAs were anomalies of the central nervous system (CNS)
(30.94%; n = 69), followed by anomalies of the genitourinary system (GUSs) (23.80%; n = 53), and, finally, by multiple congenital anomalies (MCAs) (16.60%; n = 37). [Table 2] demonstrates the distribution of major structural CAs, according to topography and
type of lesion. In addition, other abnormalities, such as abdominal (8.52%; n = 19), cardiovascular (6.30%; n = 14), and lymphatic system (5.82%; n = 13), among others (8.02%; n = 18), were observed.
Table 2
Distribution of main structural congenital anomalies according to topography and type
of lesion
|
Congenital anomalies
|
n
|
%
|
|
Central nervous system
|
|
Hydrocephalus
|
23
|
33.33%
|
|
Anencephaly
|
16
|
23.20%
|
|
Meningocele
|
7
|
10.14%
|
|
Others
|
23
|
33.33%
|
|
Total
|
69
|
100%
|
|
Genitourinary system
|
|
Renal dysplasia
|
20
|
37.73%
|
|
Hydronephrosis
|
13
|
24.53%
|
|
Pyelectasis
|
12
|
22.64%
|
|
Others
|
8
|
15.10%
|
|
Total
|
53
|
100%
|
|
Multiple anomalies
|
|
Craniofacial and limbs
|
13
|
35.14%
|
|
Craniofacial and cardiac
|
9
|
24.32%
|
|
Craniofacial and digestive
|
6
|
16.22%
|
|
Others
|
9
|
24.32%
|
|
Total
|
37
|
100%
|
Abbreviations: %, frequency; n, sample.
When comparing the case group with the control group, the data analysis revealed a
statistically significant difference in relation to the CA family history (p < 0.001, CI: 3.12–12.67), indicating that pregnant women with relatives who have
structural CAs have 6.03 more chance of develop fetuses with structural CAs. Patients
with previous children with CAs (p = 0.022) and consanguinity (p = 0.034) also showed a statistically significant difference between the groups ([Table 3]).
Table 3
Distribution of cases of fetal evaluation according to the characteristics of pregnant
women attended at a fetal medicine service
|
Variables
|
Population
|
|
Case
|
Control
|
OR
|
95%CI
|
p-value
|
|
n
|
%
|
n
|
%
|
|
Maternal age
|
|
< 35
|
21
|
90.42%
|
12
|
80.96%
|
–
|
0.50–2.22
|
0.884
|
|
≥ 35
|
202
|
90.58%
|
122
|
91.04%
|
|
Nr. of gestations
|
|
Primigravida
|
92
|
41.26%
|
46
|
34.33%
|
–
|
0.86–2.10
|
0.193
|
|
Multigravida
|
131
|
58.74%
|
88
|
65.67%
|
|
Previous children with CA
|
|
Yes
|
18
|
8.07
|
3
|
2.24%
|
3.85
|
1.11–13.27
|
0.022
|
|
No
|
205
|
91.93
|
131
|
97.76%
|
|
Family history of CA
|
|
Yes
|
75
|
33.63%
|
10
|
8.06%
|
6.03
|
3.12–12.67
|
< 0.001
|
|
No
|
148
|
66.37%
|
124
|
91.94%
|
|
Consanguinity
|
|
Yes
|
14
|
6.28%
|
2
|
1.49%
|
4.43
|
0.99–19.76
|
0.034
|
|
No
|
209
|
93.72%
|
132
|
98.51%
|
|
Total
|
223
|
100%
|
134
|
100%
|
Abbreviations: %, frequency; 95%CI, 95% confidence interval; CA, congenital anomaly;
n, sample; OR, odds ratio.
Discussion
During the investigation period, a frequency of 62.46% of pregnant women with fetuses
carrying structural anomalies was observed. The CNS, GUS, and MC anomalies were the
most frequent ones. Indian studies showed similar results.[8]
[9]
[10]
Differently, other studies report higher frequency of CAs of the cardiovascular system.[5]
[11]
[12]
[13] On the other hand, the higher frequency of CNS has been reported in several studies
in Iran,[14] Japan,[15] Pakistan,[16]
[17] China,[18] Nigeria,[19] Tanzania,[20] and India.[8]
[9]
[10]
The etiology of CNS anomalies is multifactor and involves complex interactions between
genetic and environmental factors, constituting one of the most common congenital
defects.[9]
[21]
[22] Among the anomalies of the CNS observed in this study, hydrocephalus and anencephaly
were the most reported changes, which is similar to other studies that also reported
hydrocephalus[8]
[14]
[17]
[23] and the anencephaly[8]
[15]
[17]
[24] among the most common malformations.
The data in this study indicated that the occurrence of fetal malformation in one
or more family members is associated with the development of CAs in the current gestation.
Pregnant women who have a family history of CAs are 6.03 times more likely to develop
fetuses with some structural anomaly. the literature data already highlighted this
association.[8]
[23] Correia et al[25] revealed that 16% of families with registered cases of fetal malformations in Portugal
had one or more family members with CAs. In addition, studies indicate that some specific
CAs, such as those of the kidney and heart, have the potential to aggregate into families.[26]
[27]
In this study, the pregnant women who have had children with some CA presented 3.85
times more chance of having other children with malformations. These data are similar
to the results of Lie et al,[28] which showed that mothers who already had a child with CA would have a 2.4 times
greater risk of having a second gestation affected when compared with a pregnant woman
without a history of CA occurrence. Marwah et al[8] observed higher frequency of malformations in pregnant women who had already had
children with CA. Thus, possibly, there is a strong tendency of recurrence of specific
defects in the same family, indicating the persistence of a causal factor.
Regarding consanguinity, it was verified that consanguineous parents presented 4.43
times more chance of having children with anomalies than parents with no degree of
kinship. These data are concordant with other studies that show a positive association
between CA and consanguineous parents.[8]
[9]
[11]
[23]
[29] However, Hatibaruah and Hussain[30] found no relation between consanguinity and CA, and Neira et al[31] did not observe cases of consanguinity among the parents of malformed newborns.
Maternal age is considered an important parameter in the birth of a fetus with CA
and patients aged <20 or >40 years old may showed increased risk of having children
with certain birth defects.[32] However, in our study, the correlation between maternal age and CA was not evident
(p = 0.884). Similar to our findings, the study by Francine et al.[11] et al also did not report the occurrence of this association. Despide, some studies
have reported the association of increased maternal age and the occurrence of CA.[8]
[15]
There are few studies in the literature that evaluate number of pregnancies as a risk
factor for the occurrence of CA. Our study found no differences between the occurrence
of AC between and multigravida and primigravida. But, we can verify a higher frequency
of CA in multigravida and this result is in agreement with other data in the literature.[8]
[16]
[30] While, other studies have reported a higher frequency of CA in primigravida.[9]
[30]
[31]
[32]
[33] Thus, the data still do not conclude how parity can influence the occurrence of
CA.
The differences between studies can be reflected in different racial, ethnic, and
social factors in various regions of the world. Other justifications for these variations
include the different study methodologies used for sampling, accessibility, and use
of advanced diagnostic techniques, which improve the early and correct detection of
CAs.[14]
The current study presents some limitations. First of all, the collected data were
from a fetal medicine service, and the prevalence showed may be greater than that
of the general population. Because genetic tests are not offered by the institution,
tests such as karyotype, that could prove the influence of parental genetics in the
occurrence of structural CA, were not performed. However, we recognize the importance
of such tests. Despite the aforementioned limitations, we emphasize the importance
of this work, mainly because it is prospective and because it presents the reality
from the midwest of Brazil.
Conclusion
In the present study's population, a higher frequency of CNS, GUS, and MC anomalies
was observed. The maternal risk factors that may have influenced the occurrence of
structural CAs were previous children with CA, family history, and consanguinity.
The results related here are important for the development of strategies to improve
the management, genetic counseling, and rehabilitation of patients with CA as well
as for the taking of public health measures for risk factors.
