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TRENDS IN THE PREVALENCES OF CONGENITAL ANOMALIES

AND AGE AT MOTHERHOOD IN A SOUTHERN EUROPEAN

REGION

Journal: BMJ Open

Manuscript ID: bmjopen-2013-004244

Article Type: Research

Date Submitted by the Author: 18-Oct-2013

Complete List of Authors: Cambra, Koldo; Navarrabiomed-Fundación Miguel Servet- Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC)., Ibañez, Berta; Navarrabiomed-Fundación Miguel Servet- Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC)., Urzelai, Deiene; Gobierno Vasco, Departamento de Salud Portillo, Isabel; Osakidetza- Servicio Vasco de Salud, Montoya, Imanol; Osakidetza-Servicio Vasco de Salud, Esnaola, Santiago; Gobierno Vasco, Departamento de Salud Cirarda, Francisco; Gobierno Vasco, Departamento de Salud

<b>Primary Subject Heading</b>:

Epidemiology

Secondary Subject Heading: Public health, Reproductive medicine

Keywords: Congenital anomalies, Birth defects, Chromosomal anomalies, Trends, Maternal age

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TRENDS IN THE PREVALENCES OF CONGENITAL ANOMALIES AND AGE AT MOTHERHOOD IN A SOUTHERN EUROPEAN REGION

List of authors:

Cambra K(1), Ibañez B(1), Urzelai D(2), Portillo I(3), Montoya I(2), Esnaola S(2), Cirarda FB(2)

(1) Navarrabiomed-Fundación Miguel Servet- Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC). Pamplona, Spain

(2) Departamento de Salud. Gobierno Vasco. Vitoria, Spain

(3) Osakidetza- Servicio Vasco de Salud. Vitoria, Spain

Corresponding author:

Koldo Cambra Navarrabiomed-Fundación Miguel Servet Complejo Hospitalario de Navarra C/ Irunlarrea s/n 31008 Pamplona. Spain Tfno: 34 848428292 Fax: 34 848422200 e-mail: [email protected]

KEYWORDS:

Congenital anomalies, trends, maternal age, chromosomal anomalies, birth defects

Word count: 2735

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Abstract

Objectives. To estimate the prevalences of the main groups of congenital anomalies

and to assess their evolution from 1999 to 2008.

Design. Population-based study of prevalences.

Setting. The Basque Country, Spain.

Partipants. All births and all congenital anomalies diagnosed in the entire population from 1999 to 2008.

Main outcomes measures. Total diagnosed prevalences and prevalences at birth of all chromosomal and non chromosomal anomalies, Down’s syndrome, anomalies of the nervous system, urinary, limbs, digestive system and congenital heart defects.

Results. Mean age (SD) of women at childbirth and the proportion of them over 35 years and over 40 years shifted from 32,1(4.5) years, 18.3% and 1.4% in 1999-2001, to

32.3(4.7) years, 23.9% and 2.9% in 2006-2008.

Between 1999 and 2008, 991 cases of chromosomal anomalies and 3090 of non chromosomal anomalies were diagnosed, which yields, respectively, prevalences of 5.2‰ and 16.2‰. Among chromosomal anomalies Down’s syndrome is the most frequent (2.9‰). With marginal statistical significance, the results point at an increasing trend in diagnosed chromosomal anomalies, but a decreasing one in prevalences at birth. Among nonchromosomal congenital anomalies, congenital heart defects are the most frequent (5.2‰). Rates of all non chromosomal, urinary and limb anomalies grew during the study period with different evolutions in time, whereas those of congenital heart defects and anomalies of the digestive system did not change significantly.

Conclusion. In the Basque Country, rates of chromosomal anomalies are higher than the overall estimated prevalence in European Countries, and still keep slightly increasing, which can be related to the rise in maternal age. Rates of non chromosomal anomalies are within the European frequent range of values, and the increases observed need to be checked in the following years.

Article summary

Strengths and limitations of the study

� This study analyses the evolution of the prevalences of congenital anomalies

using highly reliable data from population-based registries.

� The study provides insight into the occurring changes in mother age, the extent of the use of antenatal diagnosis and its impact on the prevalences of congenital anomalies at birth.

� Improvements in quality and accessibility of diagnostic tests can lead to an

apparent increase in prevalences.

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INTRODUCCION

Congenital anomalies (CA) affect around 2% of births in Europe.[1] They account for a great part of neonatal mortality and morbidity, and may be an important source of distress for parents and families. In the majority of cases the aetiology of CA remains unknown. Some increasing trends have been detected by EUROCAT in the Pan-Europe analysis for several CA, such as hypospadias, abdominal wall anomalies, gastroschisis, trisomy 18 and renal dysplasia.[2] Local trends have been more frequently detected but, in general, they need further verification. Women’s age at childbirth has been on the rise in all European countries included in Eurostat during the last decades. From 2001 to 2008 the average maternal age in 17-UE

inched up from 29.5 to 30.3 years, but geographical differences remained important, with greater values in West Europe and differences between countries up to 5 years. Spain, in the fifth position of the European ranking of 2008, with a mean age of women at childbirth of 30.8 years, climbed to the top in 2011 with a mean of 31.5 years.[3] Changes in demographics and in the perception of risks, along with a generalized extension and improvement of antenatal diagnosis, have increased, in Spain and other countries, the public awareness on reproductive health issues. Improvements in antenatal diagnosis as well as in case registrations enable presently to conduct more reliable population-based studies on congenital anomalies.

The Basque Country is an industrialized, urban type community, situated in north Spain, with around 2.2 million inhabitants. Demographic changes in the last decades have been dramatic, greater than in other Spanish regions. The synthetic index of fecundity fell from 2.67 in 1975 to 1.24 in 1985, 0.97 in 1990 and 1.03 in 2000, while the average of maternity age rose from 28.6, to 29.1, 30.0, 31.3 and 32.4 years in the same calendar years.[4] Medical care and antenatal diagnosis are widely available to all pregnant women, and they are provided by the Basque Health Service to the entire population. The detection of trends is an essential component of epidemiological surveillance of congenital anomalies, valuable for care and genetic advice planning and also for

warning of environmental risk factors. Its interest actually grows in places where changes in reproductive health determinants may be occurring. This report analyses the evolution of maternal age and prevalences of congenital anomalies in a ten year period in the Basque Country, focusing on total and on specific subgroups of chromosomal and non chromosomal anomalies.

METHODS

The study period has been 1999-2008. We used data from the population based Registry of Neonatal Screening and Congenital Anomalies of the Basque Country, integrated in EUROCAT project and operating since the early 1990s. All anomalies diagnosed prenatally, at birth or during the first year of age, in all hospitals of the country are included. The registry covers affected live births, foetal births with gestational age 22 weeks or greater, and terminations of pregnancy for foetal anomaly following prenatal diagnosis.

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We estimated the prevalences and 95% confidence intervals (CI) related to mothers with residence in the Basque Country, of total chromosomal anomalies (CIE 10, Q90-93, Q96-99), total non chromosomal anomalies (Q chapter excepting chromosomal

anomalies, D215, D821, D1810, P350, P351, P371) and by subgroups, anomalies of the nervous system (Q00-07), urinary (Q60-64, Q794), limbs (Q65-74), digestive system (Q38-Q45, Q790), congenital heart defects (CHD)(Q20-26), and Down (Q90), Patau (Q914-917), Edward (Q910-913), Turner (Q96) and Klinefelter’s (Q980-984) syndromes. Other major organ subgroups of non chromosomal anomalies were not included in the analysis because their average prevalences, lower than one case per 1000 births, are too low to be assessed on a yearly basis. One case with several non- chromosomal anomalies can be assigned to more than one group but it is counted only once within each one. Minor anomalies were excluded.[1] We estimated total prevalence rates (CA in liveborns, foetal deaths and induced abortions divided by the

total number of births) and prevalence rates at birth (CA in liveborns and foetal deaths divided by the total number of births). Data related to denominators (number of births per year, place of residence and age of the mother) were obtained from the Registry of Newborns of the Basque Country. To explore the functional relationship between prevalences and time, we fitted Generalized Additive Models (GAM), for they are flexible models with no restrictions that can properly reflect the true relationship between the variables. We included the annual number of cases as a Poisson response variable, the number of births (live and still) as the offset, and the calendar year as independent variable using thin plate

regression splines. To further assess time trends, we fitted binomial regression models using a logarithmic link function, including the same former variables and adding as explanatory variable mother age group (under 30, 30-34, 35-39 and over 40 years). We also conducted Chi square tests for trends in proportions, whose p-value results are virtually identical to those from the binomial regression models. In the case of Down’s Syndrome, we also tested trends in the estimated prevalence at birth that would have occurred in the absence of antenatal diagnosis (and subsequent terminations), using for that diagnosed prevalences adjusted for the natural foetal loss risks reported by Savva.[5] Adjusting for natural foetal losses is aimed at controlling the

potential bias in the estimation of time trends in periods in which there is an increase in the number of prenatal diagnoses and, consequently, in the number of cases diagnosed prenatally that would not have survived to term and remained undiagnosed in absence of prenatal diagnosis. This study was approved by the Clinical Research Ethics Committee of the Basque Country.

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RESULTS

The number of births grew in the Basque Country during the study period, rising from 51,771 in 1999-2001 to 62,329 in 2006-2008. Concurrently, age of motherhood moved into later ages (Fig 1). Mean age of women at childbirth and the proportion of them over 35 years shifted from 32.1 years and 18.3% in 1999-2001 to 32.3 years and 23.9% in 2006-2008 (Table 1). This shift is greater among chromosomal anomalies cases, with an increase of 0.7 years in the mean age and an increase of 9% in the proportion of mothers above 35 years. Among non-chromosomal anomalies cases, mother age indicators keep closer to those of all births. Table 1. Mean age of women at childbirth and proportion of them above 35 and 40

years, in all births and in cases of congenital anomalies (CA) of the Basque Country, in 1999-2001 and 2006-2008

1999-2001 2006-2008

Mean(SD) >35 y >40 y Mean (SD) >35 y >40 y

All births 32,1(4.5) 18.3% 1.4% 32.3(4.7) 23.9% 2.9% Chromosomal CA 34.6(4.5) 42.6% 7.4% 35.3(5.0) 51.5% 12.0% Non-chromsomal CA 32.1(4.6) 21.1% 3.6% 32.3(5.1) 27.2% 3.2%

Between 1999 and 2008, 991 cases of chromosomal anomalies and 3090 of non chromosomal anomalies were diagnosed, which yields, respectively, prevalences of 5.2‰ and 16.2‰ (Table 2). Diagnosis was antenatal in 83% of chromosomal and in 43% of non-chromosomal anomalies. Among chromosomal anomalies, Down’s Syndrome (DS) is the most frequent, accounting for 55% of all diagnosed chromosomal anomalies. The total prevalence of DS is 2.9‰, the estimated prevalence at birth adjusted for natural foetal losses is 2.3‰, and the actual prevalence of DS at birth is 0.7‰. Other chromosomal syndromes are much less frequent. From 1999 to 2008 Edward syndromes diagnosed were 121, Turner

syndromes 81, Klinefelter 52 and Patau 42, resulting respectively in 0.7(95%IC:0.5-0.8), 0.4(95%IC:0.4-0.5), 0.3(95%IC:0.2-0.3) and 0.2(95%IC:0.2-0.3) diagnosed cases per 1000 births. The results point at certain increasing trend in total chromosomal anomalies and certain decreasing trend in prevalences at birth (Table 2 and Fig 2). For Down’s Syndrome, we found, with marginal statistical significance, annual relative increases in the total prevalence of around 3% (p=0.079) and annual relative reductions of 5% in the prevalence at birth (p=0.098). When adjusting regression models for mother age, increasing trend in diagnosed chromosomal anomalies disappear but decreasing trends

in prevalences at birth remain unchanged, both for all chromosomal anomalies and for DS. Mother age group is strongly associated with the prevalence of chromosomal anomalies (p<0.001), with prevalence rates 1.3, 3.2 and 8.3 times greater in women of 30-34, 35-39 and over 40 years than in women under 30 years, respectively. Among non-chromosomal anomalies, CHD are the most frequent (5.0‰), followed by urinary (3.5‰), nervous system (2.4‰) and limb anomalies (2.4‰). Prevalences at

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birth are around 80% of total diagnosed prevalences, excepting the subgroup of nervous system anomalies, for which the prevalence at birth (0.9‰) is a third of the total diagnosed one.

Prevalences of all non chromosomal, urinary and limb anomalies grew during the study period with different evolutions in time (Fig 3). Deviations from linearity are negligible in all studied subgroups of anomalies, except for the urinary ones, which grew from 1999 to 2003 and then plateaued, and for limb anomalies which sharply mounted from 2004 to 2008. The estimated annual relative increment of prevalence rates of all non-chromosomal anomalies is 3% and that of nervous system anomalies 5%. When models are adjusted for mother age, trend estimates and statistical significances remain unchanged (Table 2). In fact, mother age only turned out to be statistically significant for all non-chromosomal anomalies and for anomalies of the nervous system, in both

cases with the highest prevalence in women over 40 and the lowest prevalence in women between 30 and 34 years, and with differences in prevalence rates between these groups below 30%.

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Table 2. Trends in congenital anomalies in the Basque Country (Spain), from 1999 to 2008

Prevalences(cases/1.000) Crude change/yr Age adjusted change/yr

n 1999-2008 1999-2001 2006-2008 %(95%CI) p %(95%CI) p

Total diagnosed anomalies

Chromosomal All 991 5.2(4.9,5.5) 4.9(4.4,5.6) 5.4(4.8,6.0) 1.01(0.99,1.04) 0.174 1.00(0.98,1.02) 0.878 DS* 548 2.9(2.6, 3.1) 2.8( 2.3, 3.3) 3.1( 2.7, 3.6) 1.03(1.00,1.06) 0.079 1.01(0.98,1.04) 0.669 DS adjusted foetal loss 435 2.3(2.1, 2.5) 2.2( 1.9, 2.7) 2.5( 2.1, 2.9) 1.02(0.99,1.06) 0.161 1.00(0.97,1.04) 0.843

Non-chromosomal

All 3090 16.2(15.6,16.7) 13.8(12.8,14.8) 17.8(16.7,18.8) 1.04(1.02,1.05) <0.001 1.04(1.03,1.05) <0.001 Nervous system 456 2.4(2.2, 2.6) 2.0( 1.6, 2.4) 2.8( 2.4, 3.3) 1.05(1.01,1.08) 0.007 1.05(1.01,1.08) 0.007 Urinary 670 3.5(3.2, 3.8) 2.4( 2.0,2.9) 3.6( 3.2, 4.2) 1.04(1.02,1.07) 0.002 1.04(1.01,1.07) 0.003 Digestive 304 1.6(1.4, 1.8) 1.3( 1.0, 1.7) 1.8( 1.5, 2.2) 1.03(0.99,1.08) 0.101 1.03(0.99,1.08) 0.105 Limbs 460 2.4(2.2, 2.6) 1.6( 1.3, 2.0) 4.1( 3.6, 4.6) 1.17(1.13,1.21) <0.001 1.17(1.13,1.21) <0.001 Heart 962 5.0(4.7, 5.4) 4.9( 4.3, 5.5) 4.8( 4.3, 5.4) 1.00(0.98,1.02) 0.876 1.01(0.98,1.03) 0.619

Congenital anomalies at birth

Chromosomal All 238 1.2(1.1,1.4) 1.5(1.2,1.9) 1.2(0.9,1.5) 0.97(0.93,1.01) 0.160 0.96(0.92,1.00) 0.080 DS 139 0.7( 0.6, 0.9) 1.0( 0.8, 1.4) 0.7( 0.5, 0.9) 0.95(0.9 ,1.01) 0.098 0.95(0.89,1.01) 0.076

Non-chromosomal All 2442 12.8(12.3,13.3) 10.7( 9.9,11.7) 14.1(13.2,15.0) 1.04(1.03,1.06) <0.001 1.04(1.03,1.06) <0.001 Nervous system 166 0.9( 0.7, 1.0) 0.6( 0.4, 0.9) 1.2( 0.9, 1.5) 1.10(1.04,1.16) 0.001 1.10(1.04,1.16) 0.001 Urinary 564 3.0( 2.7, 3.2) 1.9( 1.5, 2.3) 3.1( 2.7, 3.6) 1.05(1.02,1.09) <0.001 1.05(1.02,1.09) <0.001 Digestive 276 1.4( 1.3, 1.6) 1.2( 0.9, 1.5) 1.7( 1.4, 2.0) 1.03(0.99,1.08) 0.115 1.03(0.99,1.08) 0.127 Limbs 360 1.9( 1.7, 2.1) 1.3( 1.0, 1.7) 3.2( 2.8, 3.7) 1.17(1.13,1.22) <0.001 1.17(1.13,1.22) <0.001 Heart 873 4.6( 4.3, 4.9) 4.7( 4.2, 5.4) 4.1( 3.6, 4.6) 0.98(0.96,1.01) 0.176 0.99(0.97,1.01) 0.340

* DS: Down’s Syndrome

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DISCUSION

During 1999-2008 the age of women at childbirth shifted towards later ages, and there was an increase in diagnosed prevalences of chromosomal and non chromosomal anomalies in the Basque Country. Among non-chromosomal anomalies, the evolution of prevalences is particular of each subgroup, with no common pattern and in some cases with notable relative rises in magnitude. Data used in this study come from the Registry of Neonatal Screening and Congenital Anomalies of the Basque Country. The registry follows the EUROCAT project guides and it was launched several years before the initial date of this project. This makes data highly reliable and improves comparability with results from other registries.[6]

Surveillance of the evolution in time of congenital anomalies conceivably allows detecting changes in risk that may occur locally or on a greater scale. However, antenatal diagnosis leads to detect more non-viable cases that otherwise would have been miscarriages and remained undiagnosed, and therefore, improvements in quality and accessibility of diagnostic test can make the estimation of trends in congenital anomalies rates more prone to bias than in other health outcomes. This is an important issue to take into account when interpreting changes in rates of diagnosed congenital anomalies. Prevalence of chromosomal anomalies in the Basque Country are higher than the overall

estimated prevalence for Europe, 5.2‰ vs. 3.8‰ in all chromosomal anomalies, and 2.9‰ vs. 2.1‰ in the case of Down’s Syndrome.[2, 7] It is well known that older mothers are at higher risk of chromosomal anomalies, and that risk increases exponentially from the age of 30, not only for Down Syndrome, but also for other less prevalent chromosomal syndromes, such as trisomies 13 and 18.[8] The high maternal age of Basque mothers, in fact, at the top of the European ranking, can explain why prevalences of chromosomal anomalies are higher in the Basque Country. Likewise, the increase in maternal age from 1999 to 2008 would be the primary reason to explain the observed positive trend in all chromosomal anomalies and Down’s syndrome prevalences. Our findings support this view, as trends are not longer statistically

significant when adjusting for maternal age. A secondary explanation, both for trends and for the differences with other European regions, may be differences in case ascertainment derived from the increasingly frequent use of prenatal diagnoses in the Basque Country, which, in turn, is partially provoked by the rise in maternal age. Increases in prevalences of chromosomal anomalies have been also reported in other European regions.[2] Prevalences at birth of chromosomal anomalies show certain decreasing trend, which is related to the extension and use of antenatal diagnosis and the decision that most of women make after receiving a positive diagnose. On average 80% of all chromosomal

anomalies were diagnosed antenatally, 74% in 1999-2001 and 85% in 2006-2008. In the Basque Country, 90% of the women who received an antenatal diagnose of chromosomal anomaly decided to terminate the pregnancy. This proportion is similar to that found in England and Wales where, as Morris et al reported, dramatic changes in demography have been offset by improved antenatal diagnosis and have resulted in no substantial changes in birth prevalences of Down’s syndrome.[9]

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The prevalence of non chromosomal congenital anomalies in the Basque Country, contrary to chromosomal anomalies, is lower than overall rates reported in Europe, 12.8‰ vs. 20.2‰.[2] By subgroups, those of nervous system, digestive and urinary

anomalies, with deviations smaller than 10%, can be considered similar to the overall European rate; CHD rates are 20% smaller in the Basque Country. The relationship between maternal age and the prevalence of some subgroups of non chromosomal anomalies has been reported to be U-curves or J-curves, younger and older mothers showing increased risk.[10-12] Our findings are in agreement with this type of relationship. Loane et al performed a population based prevalence study, covering a total of 1.75 million births form 2000 to 2004, and they found teenage mothers to have the highest prevalence of all non-chromosomal congenital anomalies.[13] The prevalence decreased as maternal age increased, until a slight

increase was observed in mothers 40-44 years of age and a further increase in mothers above 45 years. They also reported that the maternal age pattern of risk differs between countries, and concluded that, unlike chromosomal anomalies, it is not biological age that is associated with risk of non chromosomal congenital anomalies, but reproductive, social, ethnic, exposure of lifestyle factors that have a different relationship with maternal age in different countries. They concluded that the increase of risk due to mother age can be considered negligible, especially when compared to chromosomal anomalies. Association of paternal age and risk of certain birth defects has been reported for younger paternal ages, also with relatively low increases in risk as age grows.[14]

All non chromosomal anomalies are a very broad and heterogeneous group of anomalies with different aetiology that can hardly be related to a common true change in risk. Taking into account that during the first years of the study period global prevalences were low, below 20‰, it cannot be rule out improvements in case ascertainment to be an explanation of the observed increase. For limbs and urinary anomalies, this explanation is also feasible because prevalences before the observed sudden rise are clearly below the average prevalences reported from other registries. We did not find any change in CHD prevalences, which is in line with what has been

observed in Europe, where after an increase in the early 90s due to improvements in echocardiographic investigations, rates have remained stable.[2, 15] Prevalences of congenital anomalies of nervous and digestive systems show a slight steady increase from 1999 to 2008. Decreasing trends in neural tube defects (NTD) have been reported in some parts of Europe [2], but in others places no significant decrease has been found. [16, 17] NTD risk has been associated with socioeconomic status. This has raised the issue if periconceptual folic acid recommendations are being followed. Spanish data about folic supplementation in pregnancies, coming from INMA project, point at extensive compliance of recommendations in the 3rd month of pregnancy (94% of women), lower compliance in the 2nd one (66% of women) and scarce preconceptual

compliance (19%), suggesting that folic supplementation in Spain is still an area of improvement for NTD reductions.[18] Difference between diagnosed anomalies and prevalences at birth are slight for digestive, limbs and urinary anomalies, while is notable for the nervous system, reflecting differences in severity and in the proportion of antenatal diagnosis, much

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more frequent for anomalies of the nervous system (in 82% of the diagnosed cases) than in limbs (57%), digestive (28%) and urinary anomalies (22%).

Maintaining the surveillance of non chromosomal anomalies is essential. It is necessary to check if the observed trends continue or disappear in the following years, and complementary data analysis are needed in order to assess if, associated or not with the increasing trends, there are spatial clustering of cases that can share the same aetiology.

CONCLUSION

In the Basque Country chromosomal anomalies rates are high and still keep slightly increasing, which can be related to the rise in maternal age. Rates of non chromosomal anomalies are within the European frequent range of values, and the increases observed

in some of them need to be checked in the following years.

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FUNDING

This study was partially funded by Instituto de Salud Carlos III (FIS PI 08/1392)) of The Spanish Ministry of Economy and Competitiveness

CONFLICT OF INTERESTS

The authors declare that they have no conflict of interest.

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REFERENCES

1. Boyd PA, Haeusler M, Barisic I, et al. Paper 1: The EUROCAT network--organization and processes. Birth Defects Res A Clin Mol Teratol 2011;91 Suppl 1:S2-

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2. Loane M, Dolk H, Kelly A, et al. Paper 4: EUROCAT statistical monitoring: identification and investigation of ten year trends of congenital anomalies in Europe. Birth Defects Res A Clin Mol Teratol 2011;91 Suppl 1:S31-43.

3. EUROSTAT. Mean age of women at childbirth (code: tps00017). In: http://goo.gl/8Lzfk. Accessed 4 Jun 2013

4. EUSTAT. Synthetic index of fecundity and average materity age according to year.In: http://goo.gl/jlBXf. Accessed 4 Jun 2013

5. Savva GM, Morris JK, Mutton DE, et al. Maternal age-specific fetal loss rates in Down syndrome pregnancies. Prenat Diagn 2006;26:499-504.

6. Loane M, Dolk H, Garne E, et al. Paper 3: EUROCAT data quality indicators for population-based registries of congenital anomalies. Birth Defects Res A Clin Mol Teratol 2011;91 Suppl 1:S23-30.

7. Khoshnood B, Greenlees R, Loane M, et al. Paper 2: EUROCAT public health indicators for congenital anomalies in Europe. Birth Defects Res A Clin Mol Teratol 2011;91 Suppl 1:S16-22.

8. Savva GM, Walker K, Morris JK. The maternal age-specific live birth prevalence of trisomies 13 and 18 compared to trisomy 21 (Down syndrome). Prenat Diagn 2010;30:57-64.

9. Morris JK, Alberman E. Trends in Down's syndrome live births and antenatal

diagnoses in England and Wales from 1989 to 2008: analysis of data from the National Down Syndrome Cytogenetic Register. Bmj 2009;339:b3794.

10. Reefhuis J, Honein MA. Maternal age and non-chromosomal birth defects, Atlanta--1968-2000: teenager or thirty-something, who is at risk? Birth Defects Res A Clin Mol Teratol 2004;70:572-9.

11. Ooki S. Maternal age and birth defects after the use of assisted reproductive technology in Japan, 2004-2010. Int J Womens Health 2013;5:65-77.

12. Gill SK, Broussard C, Devine O, et al. Association between maternal age and birth defects of unknown etiology: United States, 1997-2007. Birth Defects Res A Clin Mol Teratol 2012;94:1010-8.

13. Loane M, Dolk H, Morris JK. Maternal age-specific risk of non-chromosomal anomalies. Bjog 2009;116:1111-9.

14. Green RF, Devine O, Crider KS, et al. Association of paternal age and risk for major congenital anomalies from the National Birth Defects Prevention Study, 1997 to 2004. Ann Epidemiol 2010;20:241-9.

15. Oyen N, Poulsen G, Boyd HA, et al. National time trends in congenital heart defects, Denmark, 1977-2005. Am Heart J 2009;157:467-73 e1.

16. Poretti A, Anheier T, Zimmermann R, et al. Neural tube defects in Switzerland from 2001 to 2007: are periconceptual folic acid recommendations being followed? Swiss Med Wkly 2008;138:608-13.

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17. Abeywardana S, Bower C, Halliday J, et al. Prevalence of neural tube defects in Australia prior to mandatory fortification of bread-making flour with folic acid. Aust N Z J Public Health 2010;34:351-5.

18. Sanfélix-Gimeno G FI, Librero J, Peiró S. Caracterization of folate supplementation in pregnancy, based on a combination of health information systems. Gac Sanit 2012;26:7.

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Fig 1. Age of women at childbirth and at diagnosis of a chromosomal anomaly in the

Basque Country (Spain), in 1999-2001 and 2006-2008 Fig 2. Estimated prevalences in each calendar year (error bars) and GAM fits (lines) of chromosomal congenital anomalies in the Basque Country (Spain), from 1999 to 2008 Fig 3. Estimated prevalences in each calendar year (error bars) and GAM fits (lines) of non chromosomal congenital anomalies in the Basque Country (Spain), from 1999 to 2008.

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131x202mm (300 x 300 DPI)

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197x141mm (300 x 300 DPI)

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133x198mm (300 x 300 DPI)

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STROBE Statement—checklist of items that should be included in reports of observational studies Item

No Recommendation

Title and abstract 1√

(a) Indicate the study’s design with a commonly used term in the title or the

abstract

(b) Provide in the abstract an informative and balanced summary of what

was done and what was found

Introduction

Background/rationale 2√ Explain the scientific background and rationale for the investigation being

reported

Objectives 3√ State specific objectives, including any prespecified hypotheses

Methods

Study design 4 √ Present key elements of study design early in the paper

Setting 5 √ Describe the setting, locations, and relevant dates, including periods of

recruitment, exposure, follow-up, and data collection

Participants 6

√

(a) Cohort study—Give the eligibility criteria, and the sources and methods

of selection of participants. Describe methods of follow-up

Case-control study—Give the eligibility criteria, and the sources and

methods of case ascertainment and control selection. Give the rationale for

the choice of cases and controls

Cross-sectional study—Give the eligibility criteria, and the sources and

methods of selection of participants. (Data come from a population-based

registry)

(b) Cohort study—For matched studies, give matching criteria and number

of exposed and unexposed

Case-control study—For matched studies, give matching criteria and the

number of controls per case

Variables 7√ Clearly define all outcomes, exposures, predictors, potential confounders,

and effect modifiers. Give diagnostic criteria, if applicable

Data sources/

measurement

8* For each variable of interest, give sources of data and details of methods of

assessment (measurement). Describe comparability of assessment methods

if there is more than one group

Bias 9√ Describe any efforts to address potential sources of bias

Study size 10√ Explain how the study size was arrived at (It is a population based study;

we use data of the entire population)

Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If

applicable, describe which groupings were chosen and why (Not applicable)

Statistical methods 12√ (a) Describe all statistical methods, including those used to control for

confounding

(b) Describe any methods used to examine subgroups and interactions

(c) Explain how missing data were addressed

(d) Cohort study—If applicable, explain how loss to follow-up was

addressed

Case-control study—If applicable, explain how matching of cases and

controls was addressed

Cross-sectional study—If applicable, describe analytical methods taking

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account of sampling strategy

(e) Describe any sensitivity analyses

Results

Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially

eligible, examined for eligibility, confirmed eligible, included in the study,

completing follow-up, and analysed (Not applicable)

(b) Give reasons for non-participation at each stage

(c) Consider use of a flow diagram

Descriptive data 14*√

(a) Give characteristics of study participants (eg demographic, clinical, social) and

information on exposures and potential confounders

(b) Indicate number of participants with missing data for each variable of interest

(c) Cohort study—Summarise follow-up time (eg, average and total amount)

Outcome data 15*

√

Cohort study—Report numbers of outcome events or summary measures over time

Case-control study—Report numbers in each exposure category, or summary

measures of exposure

Cross-sectional study—Report numbers of outcome events or summary measures

Main results 16√ (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and

their precision (eg, 95% confidence interval). Make clear which confounders were

adjusted for and why they were included

(b) Report category boundaries when continuous variables were categorized

(c) If relevant, consider translating estimates of relative risk into absolute risk for a

meaningful time period

Other analyses 17√ Report other analyses done—eg analyses of subgroups and interactions, and

sensitivity analyses

Discussion

Key results 18√ Summarise key results with reference to study objectives

Limitations 19√ Discuss limitations of the study, taking into account sources of potential bias or

imprecision. Discuss both direction and magnitude of any potential bias

Interpretation 20√ Give a cautious overall interpretation of results considering objectives, limitations,

multiplicity of analyses, results from similar studies, and other relevant evidence

Generalisability 21√ Discuss the generalisability (external validity) of the study results

Other information

Funding 22√ Give the source of funding and the role of the funders for the present study and, if

applicable, for the original study on which the present article is based

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and

unexposed groups in cohort and cross-sectional studies.

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and

published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely

available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at

http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is

available at www.strobe-statement.org.

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REGION

Journal: BMJ Open

Manuscript ID: bmjopen-2013-004244.R1


Date Submitted by the Author: 19-Dec-2013



Epidemiology






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TRENDS IN THE PREVALENCES OF CONGENITAL ANOMALIES AND AGE AT

MOTHERHOOD IN A SOUTHERN EUROPEAN REGION

List of authors:

Cambra K(1), Ibañez B(1), Urzelai D(2), Portillo I(3), Montoya I(2), Esnaola S(2),

Cirarda FB(2)

(1) Navarrabiomed-Fundación Miguel Servet- Red de Investigación en Servicios de

Salud en Enfermedades Crónicas (REDISSEC). Pamplona, Spain




Koldo Cambra

Navarrabiomed-Fundación Miguel Servet

Complejo Hospitalario de Navarra

C/ Irunlarrea s/n

31008 Pamplona. Spain

Tfno: 34 848428292

Fax: 34 848422200

e-mail: [email protected]

KEYWORDS:


Word count: 2891

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Abstract


and to assess their trend over time.



Partipants. All births and all congenital anomalies diagnosed prenatally, at birth or

during the first year of age, in all hospitals of the country, from 1999 to 2008.

Main outcomes measures. Total diagnosed prevalences and prevalences at birth of all

chromosomal and non-chromosomal anomalies, Down’s syndrome, anomalies of the

nervous system, urinary, limbs, digestive system and congenital heart defects.

Results. Mean age (SD) of women at childbirth and the proportion of them over 35

years and over 40 years shifted from 32.1(4.5) years, 18.3% and 1.4% in 1999-2001, to

32.3(4.7) years, 23.9% and 2.9% in 2006-2008.

Between 1999 and 2008, 991 cases of chromosomal anomalies and 3090 of non-

chromosomal anomalies were diagnosed, which yields, respectively, total prevalences

of 5.2‰ and of 16.2‰. Among chromosomal anomalies Down’s syndrome is the most

frequent (2.9‰). With marginal statistical significance, the results point at an increasing

trend in total diagnosed chromosomal anomalies, but a decreasing one in prevalences at

birth. Among non-chromosomal congenital anomalies, congenital heart defects are the

most frequent (5.2‰). Rates of all non-chromosomal, urinary and limb anomalies grew

during the study period with different evolutions in time, whereas those of congenital

heart defects and anomalies of the digestive system did not change significantly.

Conclusion. In the Basque Country, rates of chromosomal anomalies are higher than

the overall estimated prevalence in European Countries, and continue to increase

slightly, which may be related to the rise in maternal age. Rates of non-chromosomal

anomalies are within the European frequent range of values, and the increases observed

need to be checked in the following years.

Article summary




� The study provides insight into the occurring changes in maternal age, the extent

of the use of antenatal diagnosis and its impact on the prevalences of congenital

anomalies at birth.



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INTRODUCTION

Congenital anomalies affect around 2% of births in Europe.[1] They account for a great

part of neonatal mortality and morbidity, and may be an important source of distress for

parents and families. In the majority of cases the aetiology of congenital anomalies

remains unknown. Some increasing trends have been detected by EUROCAT in the

Pan-Europe analysis for several CA, such as hypospadias, abdominal wall anomalies,

gastroschisis, trisomy 18 and renal dysplasia.[2] Local trends have been more frequently

detected but, in general, they need further verification.

Women’s age at childbirth has been on the rise in all European countries included in

Eurostat during the last decades. From 2001 to 2008 the average maternal age in EU-17

inched up from 29.5 to 30.3 years, but geographical differences remained important,

with greater values in West Europe and differences between countries of up to 5 years.

Spain, in the fifth position of the European ranking of 2008, with a mean age of women

at childbirth of 30.8 years, climbed to the top in 2011 with a mean of 31.5 years.[3],

along with a generalized extension and improvement of antenatal diagnosis, have

increased (in Spain and other countries) the public awareness on reproductive health

issues. Improvements in antenatal diagnosis as well as in case registrations allow for

more reliable population-based studies on congenital anomalies.

The Basque Country is an industrialized, urban type community, situated in north Spain,

with around 2.2 million inhabitants. Demographic changes in the last decades have been

dramatic, greater than in other Spanish regions. The synthetic index of fecundity (an

estimation of the number of children a hypothetical woman would have at the end of her

fertile life if her fecundity corresponded to the age-specific fecundity rates of the

population) fell from 2.67 in 1975 to 1.24 in 1985, 0.97 in 1990 and 1.03 in 2000, while

the average of maternity age rose from 28.6, to 29.1, 30.0, 31.3 and 32.4 years in the

same calendar years.[4] Medical care and antenatal diagnosis are widely available to all

pregnant women, and they are provided by the Basque Health Service to the entire

population.

The detection of trends is an essential component of epidemiological surveillance of

congenital anomalies, valuable for care and genetic advice planning and also for

warning of environmental risk factors. Its interest actually grows in places where

changes in reproductive health determinants may be occurring.

This report analyses the evolution of maternal age and prevalences of congenital

anomalies in a ten year period in the Basque Country, focusing on total and on specific

subgroups of chromosomal and non-chromosomal anomalies.

METHODS

The study period was 1999-2008. We used data from the population based Registry of

Neonatal Screening and Congenital Anomalies of the Basque Country, integrated in

EUROCAT project and operating since the early 1990s. All anomalies diagnosed

prenatally, at birth or during the first year of age, in all hospitals of the country are

included. The registry covers affected live births, foetal births with gestational age 22

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weeks or greater, and terminations of pregnancy for foetal anomaly following prenatal

diagnosis. The staff of the Registry routinely check Hospital Discharge Databases and

the Registry of Terminations of Pregnancies searching for new cases, review medical

reports of prenatal diagnosis (sonography, genetic test and pathology) and code all

congenital anomalies.

We estimated the prevalences and 95% confidence intervals (CI) related to mothers with

residence in the Basque Country, of total chromosomal anomalies (ICD-10, Q90-93,

Q96-99), total non-chromosomal anomalies (Q chapter excluding chromosomal

anomalies, D215, D821, D1810, P350, P351, P371) and of the following subgroups:

anomalies of the nervous system (Q00-07), urinary (Q60-64, Q794), limbs (Q65-74),

digestive system (Q38-Q45, Q790), congenital heart defects (CHD)(Q20-26), and

Down (Q90), Patau (Q914-917), Edward (Q910-913), Turner (Q96) and Klinefelter’s

(Q980-984) syndromes. Other major organ subgroups of non-chromosomal anomalies

were not included in the analysis because their average prevalences, lower than one case

per 1000 births, are too low to be assessed on a yearly basis. The cases with several

non-chromosomal anomalies count as one case for calculating total or subgroup

prevalences, but they can be assigned to more than one subgroup. More details about

the anomalies included in each subgroup can be found somewhere else.[1] We

estimated total prevalence rates (congenital anomalies in liveborns, foetal deaths and

induced abortions divided by the total number of births) and prevalence rates at birth

(congenital anomalies in liveborns and foetal deaths divided by the total number of

births). Data related to denominators (number of births per year, place of residence and

age of the mother) were obtained from the Registry of Newborns of the Basque

Country.

To explore the functional relationship between prevalences and time, we fitted

Generalized Additive Models (GAM), as they are flexible unrestricted models that can

properly reflect the true relationship between the variables. We included the annual

number of cases as a Poisson response variable, the number of births (live and still) as

the offset, and the calendar year as independent variable using thin plate regression

splines. To further assess time trends, we fitted binomial regression models using a

logarithmic link function, including the same former variables and adding as

explanatory variable maternal age group (under 30, 30-34, 35-39 and over 40 years).

We also conducted Chi square tests for trends in proportions, whose p-value results are

virtually identical to those from the binomial regression models.

In the case of Down’s Syndrome, we also tested trends in the estimated prevalence at

birth that would have occurred in the absence of antenatal diagnosis (and subsequent

terminations), using for that diagnosed prevalences adjusted for the natural foetal loss

risks reported by Savva.[5] Adjusting for natural foetal losses is aimed at controlling the

potential bias in the estimation of time trends in periods in which there is an increase in

the number of prenatal diagnoses and, consequently, in the number of cases diagnosed

prenatally that would not have survived to term and remained undiagnosed in absence

of prenatal diagnosis.

This study was approved by the Clinical Research Ethics Committee of the Basque

Country.

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RESULTS

The total number of births in the 1999-2008 period was 191,171, rising from 51,771 in

the 1999-2001 period to 62,329 in 2006-2008. Concurrently, age of motherhood

increased (Fig 1). Mean age of women at childbirth and the proportion of them over 35

years shifted from 32.1 years and 18.3% in 1999-2001 to 32.3 years and 23.9% in 2006-

2008 (Table 1). This shift is greater among chromosomal anomalies cases, with an

increase of 0.7 years in the mean age and an increase of 9% in the proportion of mothers

above 35 years. Among non-chromosomal anomalies cases, maternal age indicators are

similar to those of all births.

Table1. Mean age of women at childbirth and proportion of them above 35 and 40

years, in all births and in cases of congenital anomalies (CA) of the Basque Country, in

1999-2001 and 2006-2008

1999-2001 2006-2008


All births 32.1(4.5) 18.3% 1.4% 32.3(4.7) 23.9% 2.9%

Chromosomal CA 34.6(4.5) 42.6% 7.4% 35.3(5.0) 51.5% 12.0%

Non-chromosomal CA 32.1(4.6) 21.1% 3.6% 32.3(5.1) 27.2% 3.2%


chromosomal anomalies were diagnosed, which yields, respectively, prevalences of

5.18 and 16.16 per 1000 births (Table 2). Diagnosis was antenatal in 83% of

chromosomal and in 43% of non-chromosomal anomalies.

Among chromosomal anomalies, Down’s Syndrome (DS) is the most frequent,

accounting for 55% of all diagnosed chromosomal anomalies. The total prevalence of

DS is 2.87‰, the estimated prevalence at birth adjusted for natural foetal losses is

2.27‰, and the actual prevalence of DS at birth is 0.73‰. Other chromosomal

syndromes are much less frequent. From 1999 to 2008 Edward syndromes diagnosed

were 121, Turner syndromes 81, Klinefelter 52 and Patau 42, resulting respectively in

0.63 (IC95%:0.52, 0.75), 0.42 (IC95%:0.33, 0.52), 0.27 (IC95%:0.20, 0.35) and 0.22

(IC95%:0.15, 0.29) diagnosed cases per 1000 births.

The results point at certain increasing trend in total chromosomal anomalies and certain

decreasing trend in prevalences at birth (Table 2 and Fig 2). For Down’s Syndrome, we

found, with marginal statistical significance, annual relative increases in the total

prevalence of around 3% (p=0.079) and annual relative reductions of 5% in the

prevalence at birth (p=0.098). When adjusting regression models for maternal age,

increasing trend in diagnosed chromosomal anomalies disappear but decreasing trends

in prevalences at birth remain unchanged, both for all chromosomal anomalies and for

DS. Maternal age group is strongly associated with the prevalence of chromosomal

anomalies (p<0.001), with prevalence rates 1.3, 3.2 and 8.3 times greater in women of

30-34, 35-39 and over 40 years than in women under 30 years, respectively.

Among non-chromosomal anomalies, CHD are the most frequent (5.0‰), followed by

urinary (3.5‰), nervous system (2.4‰) and limb anomalies (2.4‰). Prevalences at

birth are around 80% of total diagnosed prevalences, with the exception of the subgroup

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of nervous system anomalies, for which the prevalence at birth (0.9‰) is a third of the

total diagnosed one.

Prevalences of all non-chromosomal, urinary and limb anomalies grew during the study

period with different evolutions in time (Fig 3). Deviations from linearity are negligible

in all studied subgroups of anomalies, except for the urinary subgroup, which increased

between 1999 to 2003 and then plateaued, and for limb anomalies which sharply

mounted from 2004 to 2008. The estimated annual relative increment of prevalence

rates of all non-chromosomal anomalies is 3% and that of nervous system anomalies

5%. When models are adjusted for maternal age, trend estimates and statistical

significances remain unchanged (Table 2). With respect to mothers under 30 years,

prevalence rates of all non-chromosomal anomalies were 0.93 (IC95%:0.85, 1.02) for

mothers between 30 and 34, 1.0 (IC95%:0.90, 1.10) for mothers between 35 and 39, and

1.30 (IC95%:1.06, 1.51) for those over 40.

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Prevalences(cases/1.000 births) Crude change/yr Age adjusted change/yr

n 1999-2008 1999-2001 2006-2008 %(95%CI) p %(95%CI) p


Chromosomal

All 991 5.18(4.87,5.52) 4.95(4.37,5.60) 5.36(4.81,5.97) 1.01(0.99,1.04) 0.174 1.00(0.98,1.02) 0.878

DS* 548 2.87(2.63,3.12) 2.76(2.34,3.26) 3.10(2.68,3.57) 1.03(1.00,1.06) 0.079 1.01(0.98,1.04) 0.669

DS adjusted foetal loss 435 2.27(2.07,2.50) 2.24(1.86,2.70) 2.46(2.09,2.88) 1.02(0.99,1.06) 0.161 1.00(0.97,1.04) 0.843

Non-chromosomal

All 3090 16.2(15.6,16.7) 13.7(12. 8,14.8) 17.8(16.7,18.8) 1.04(1.02,1.05) <0.001 1.04(1.03,1.05) <0.001

Nervous system 456 2.38(2.17,2.62) 1.99(1.63,2.42) 2.84(2.44,3.30) 1.05(1.01,1.08) 0.007 1.05(1.01,1.08) 0.007

Urinary 670 3.50(3.25,3.78) 2.41(2.02,2.89) 3.64(3.19,4.16) 1.04(1.02,1.07) 0.002 1.04(1.01,1.07) 0.003

Digestive 304 1.59(1.42,1.78) 1.31(1.03,1.68) 1.83(1.52,2.21) 1.03(0.99,1.08) 0.101 1.03(0.99,1.08) 0.105

Limbs 460 2.41(2.19,2.64) 1.62(1.30,2.02) 4.09(3.61,4.63) 1.17(1.13,1.21) <0.001 1.17(1.13,1.21) <0.001

Heart 962 5.03(4.72,5.36) 4.87(4.29,5.51) 4.81(4.29,5.40) 1.00(0.98,1.02) 0.876 1.01(0.98,1.03) 0.619


Chromosomal

All 238 1.25(1.09,1.42) 1.49(1.18,1.87) 1.16(0.91,1.46) 0.97(0.93,1.01) 0.160 0.96(0.92,1.00) 0.080

DS 139 0.73(0.61,0.86) 1.02(0.77,1.35) 0.66(0.48,0.90) 0.95(0.9 ,1.01) 0.098 0.95(0.89,1.01) 0.076

Non-chromosomal

All 2442 12.8(12.3,3.29) 10.7(9.9,11.65) 14.1(13.2,15.0) 1.04(1.03,1.06) <0.001 1.04(1.03,1.06) <0.001

Nervous system 166 0.87(0.74,1.01) 0.64(0.45,0.91) 1.17(0.92,1.48) 1.10(1.04,1.16) 0.001 1.10(1.04,1.16) 0.001

Urinary 564 2.95(2.71,3.21) 1.87(1.53,2.30) 3.11(2.70,3.59) 1.05(1.02,1.09) <0.001 1.05(1.02,1.09) <0.001

Digestive 276 1.44(1.28,1.63) 1.20(0.93,1.55) 1.65(1.36,2.01) 1.03(0.99,1.08) 0.115 1.03(0.99,1.08) 0.127

Limbs 360 1.88(1.70,2.09) 1.33(1.04,1.70) 3.23(2.80,3.71) 1.17(1.13,1.22) <0.001 1.17(1.13,1.22) <0.001

Heart 873 4.57(4.27,4.88) 4.73(4.17,5.37) 4.08(3.60,4.62) 0.98(0.96,1.01) 0.176 0.99(0.97,1.01) 0.340


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DISCUSSION

During 1999-2008 the age of women at childbirth shifted towards later ages, and there

was an increase in diagnosed prevalences of chromosomal and non-chromosomal

anomalies in the Basque Country. Among non-chromosomal anomalies, the evolution

of prevalences is particular of each subgroup, with no common pattern and in some

cases with notable relative rises in magnitude.

Data used in this study come from the Registry of Neonatal Screening and Congenital

Anomalies of the Basque Country. The registry follows the EUROCAT project guides

and it was launched several years before the initial date of this project. As a

consequence, the data are highly reliable and have improved comparability with results

from other registries.[6] Surveillance of the evolution in time of congenital anomalies

conceivably allows detecting changes in risk that may occur locally or on a greater

scale. However, antenatal diagnosis leads to detect more non-viable cases that otherwise

would have been miscarriages and remained undiagnosed, and therefore, improvements

in quality and accessibility of diagnostic test can make the estimation of trends in

congenital anomalies rates more prone to bias than in other health outcomes. This is an

important issue to take into account when interpreting changes in rates of diagnosed


Prevalence of chromosomal anomalies in the Basque Country are higher than the overall

estimated prevalence for Europe, 5.2‰ vs. 3.8‰ in all chromosomal anomalies, and

2.9‰ vs. 2.1‰ in the case of Down’s Syndrome.[2, 7] It is well known that older

mothers are at higher risk of chromosomal anomalies, and that risk increases

exponentially from the age of 30, not only for Down Syndrome, but also for other less

prevalent chromosomal syndromes, such as trisomies 13 and 18.[8] The high maternal

age of Basque mothers, in fact, at the top of the European ranking, can explain why

prevalences of chromosomal anomalies are higher in the Basque Country. Likewise, the

increase in maternal age from 1999 to 2008 would be the primary reason to explain the

observed positive trend in all chromosomal anomalies and Down’s syndrome

prevalences. Our findings support this view, as trends are no longer statistically

significant when adjusting for maternal age. A secondary explanation, both for trends

and for the differences with other European regions, may be differences in case

ascertainment derived from the increasingly frequent use of prenatal diagnoses in the

Basque Country, which, in turn, is partially provoked by the rise in maternal age.

Increases in prevalences of chromosomal anomalies have been also reported in other

European regions.[2]

Prevalences at birth of chromosomal anomalies show certain decreasing trend, which is

related to the extension and use of antenatal diagnosis and the decision that most of

women make after receiving a positive diagnosis. On average 80% of all chromosomal

anomalies were diagnosed antenatally, 74% in 1999-2001 and 85% in 2006-2008. In the

Basque Country, 90% of the women who received an antenatal diagnosis of

chromosomal anomaly decided to terminate the pregnancy. This proportion is similar to

that found in England and Wales where, as Morris et al reported, dramatic changes in

demography have been offset by improved antenatal diagnosis and have resulted in no

substantial changes in birth prevalences of Down’s syndrome.[9]

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The prevalence of non-chromosomal congenital anomalies in the Basque Country,

contrary to chromosomal anomalies, is lower than overall rates reported in Europe,

12.8‰ vs. 20.2‰.[2] By subgroups, those of nervous system, digestive and urinary

anomalies, with deviations smaller than 10%, can be considered similar to the overall

European rate; CHD rates are 20% lower in the Basque Country.

The relationship between maternal age and the prevalence of some subgroups of non-

chromosomal anomalies has been reported to be U-curves or J-curves, younger and

older mothers showing increased risk.[10-12] Our findings for total non-chromosomal

anomalies, with the lowest prevalence in mothers between 30 and 34 years, are in

agreement with this type of relationship. Loane et al performed a population based

prevalence study, covering a total of 1.75 million births form 2000 to 2004, and they

found teenage mothers to have the highest prevalence of all non-chromosomal

congenital anomalies.[13] The prevalence decreased as maternal age increased, until a

slight increase was observed in mothers 40-44 years of age and a further increase in

mothers above 45 years. They also reported that the maternal age pattern of risk differs

between countries, and concluded that, unlike chromosomal anomalies, it is not

biological age that is associated with risk of non-chromosomal congenital anomalies,

but reproductive, social, ethnic, exposure of lifestyle factors that have a different

relationship with maternal age in different countries. They concluded that the increase

of risk due to maternal age can be considered negligible, especially when compared to

chromosomal anomalies. Association of paternal age and risk of certain birth defects

has been reported for younger paternal ages, also with relatively low increases in risk as

age grows.[14]

All non-chromosomal anomalies increased during the study period, but this result needs

to be treated with caution. All non-chromosomal anomalies are a very broad and

heterogeneous group of anomalies with different aetiology that can hardly be related to

a common true change in risk. Besides, in two of the subgroups, limbs and urinary

anomalies, improvements in case ascertainment cannot be completely ruled out, as

prevalences before the observed sudden rise were clearly below the average prevalences

reported from other registries.

We did not find any change in CHD prevalences, which is in line with what has been

observed in Europe, where after an increase in the early 90s due to improvements in

echocardiographic investigations, rates have remained stable.[2, 15] Prevalences of

congenital anomalies of nervous and digestive systems show a slight steady increase

from 1999 to 2008. Decreasing trends in neural tube defects (NTD) have been reported

in some parts of Europe [2], but in others places no significant decrease has been found.

[16, 17] NTD risk has been associated with socioeconomic status. This has raised the

issue if periconceptual folic acid recommendations are being followed. Spanish data

about folic supplementation in pregnancies, coming from INMA project, point at

extensive compliance of recommendations in the 3rd month of pregnancy (94% of

women), lower compliance in the 2nd one (66% of women) and scarce preconceptual

compliance (19%), suggesting that folic supplementation in Spain is still an area of

improvement for NTD reductions.[18]

Difference between diagnosed anomalies and prevalences at birth are slight for

digestive, limbs and urinary anomalies, while is notable for the nervous system,

reflecting differences in severity and in the proportion of antenatal diagnosis, much

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more frequent for anomalies of the nervous system (in 82% of the diagnosed cases) than

in limbs (57%), digestive (28%) and urinary anomalies (22%).

Maintaining the surveillance of non-chromosomal anomalies is essential. It is necessary

to check if the observed trends continue or disappear in the following years, and

complementary data analysis are needed in order to assess if, associated or not with the

increasing trends, there is spatial clustering of cases that can share the same aetiology.

CONCLUSION

In the Basque Country chromosomal anomalies rates are high and continue to increase




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FUNDING

This study was partially funded by Instituto de Salud Carlos III (FIS PI 08/1392)) of

The Spanish Ministry of Economy and Competitiveness

CONTRIBUTORSHIP STATEMENT

KC designed the project, checked the data, interpreted the results, and drafted and

revised the manuscript. BI participated in the study design, conducted the statistical

analysis, interpreted the results and reviewed the manuscript. FC, DU and IP

participated in the study design, collected the data, created the databases and reviewed

the manuscript. SE and IM took part in the study design and reviewed the manuscript.



DATA SHARING STATEMENT

No additional data

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REFERENCES

1. Boyd PA, Haeusler M, Barisic I, et al. Paper 1: The EUROCAT network--

organization and processes. Birth Defects Res A Clin Mol Teratol 2011;91 Suppl 1:S2-

15.

2. Loane M, Dolk H, Kelly A, et al. Paper 4: EUROCAT statistical monitoring:

identification and investigation of ten year trends of congenital anomalies in Europe.

Birth Defects Res A Clin Mol Teratol 2011;91 Suppl 1:S31-43.

3. EUROSTAT. Mean age of women at childbirth (code: tps00017). In:

http://goo.gl/8Lzfk. Accessed 4 Jun 2013

4. EUSTAT. Synthetic index of fecundity and average materity age according to

year.In: http://goo.gl/jlBXf. Accessed 4 Jun 2013

5. Savva GM, Morris JK, Mutton DE, et al. Maternal age-specific fetal loss rates in

Down syndrome pregnancies. Prenat Diagn 2006;26:499-504.

6. Loane M, Dolk H, Garne E, et al. Paper 3: EUROCAT data quality indicators for

population-based registries of congenital anomalies. Birth Defects Res A Clin Mol

Teratol 2011;91 Suppl 1:S23-30.

7. Khoshnood B, Greenlees R, Loane M, et al. Paper 2: EUROCAT public health

indicators for congenital anomalies in Europe. Birth Defects Res A Clin Mol Teratol

2011;91 Suppl 1:S16-22.

8. Savva GM, Walker K, Morris JK. The maternal age-specific live birth prevalence of

trisomies 13 and 18 compared to trisomy 21 (Down syndrome). Prenat Diagn

2010;30:57-64.


diagnoses in England and Wales from 1989 to 2008: analysis of data from the National

Down Syndrome Cytogenetic Register. Bmj 2009;339:b3794.

10. Reefhuis J, Honein MA. Maternal age and non-chromosomal birth defects, Atlanta--

1968-2000: teenager or thirty-something, who is at risk? Birth Defects Res A Clin Mol

Teratol 2004;70:572-9.

11. Ooki S. Maternal age and birth defects after the use of assisted reproductive

technology in Japan, 2004-2010. Int J Womens Health 2013;5:65-77.

12. Gill SK, Broussard C, Devine O, et al. Association between maternal age and birth

defects of unknown etiology: United States, 1997-2007. Birth Defects Res A Clin Mol

Teratol 2012;94:1010-8.

13. Loane M, Dolk H, Morris JK. Maternal age-specific risk of non-chromosomal

anomalies. Bjog 2009;116:1111-9.

14. Green RF, Devine O, Crider KS, et al. Association of paternal age and risk for major

congenital anomalies from the National Birth Defects Prevention Study, 1997 to 2004.

Ann Epidemiol 2010;20:241-9.

15. Oyen N, Poulsen G, Boyd HA, et al. National time trends in congenital heart

defects, Denmark, 1977-2005. Am Heart J 2009;157:467-73 e1.

16. Poretti A, Anheier T, Zimmermann R, et al. Neural tube defects in Switzerland from

2001 to 2007: are periconceptual folic acid recommendations being followed? Swiss

Med Wkly 2008;138:608-13.

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17. Abeywardana S, Bower C, Halliday J, et al. Prevalence of neural tube defects in

Australia prior to mandatory fortification of bread-making flour with folic acid. Aust N

Z J Public Health 2010;34:351-5.

18. Sanfélix-Gimeno G FI, Librero J, Peiró S. Caracterization of folate supplementation

in pregnancy, based on a combination of health information systems. Gac Sanit

2012;26:7.

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Basque Country (Spain), in 1999-2001 and 2006-2008

Fig 2. Estimated prevalences in each calendar year (error bars) and GAM fits (lines) of

chromosomal congenital anomalies in the Basque Country (Spain), from 1999 to 2008


non-chromosomal congenital anomalies in the Basque Country (Spain), from 1999 to

2008.

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1



List of authors:


Cirarda FB(2)






Koldo Cambra



C/ Irunlarrea s/n


Tfno: 34 848428292

Fax: 34 848422200


KEYWORDS:


Word count: 2891

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2

Abstract












32.3(4.7) years, 23.9% and 2.9% in 2006-2008.








during the study period with different evolutions in time, whereas those of congenital

heart defects and anomalies of the digestive system did not change significantly.






Article summary






anomalies at birth.



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INTRODUCTION





Pan-Europe analysis for several CA, such as hypospadias, abdominal wall anomalies,

gastroschisis, trisomy 18 and renal dysplasia.[2] Local trends have been more frequently

detected but, in general, they need further verification.






at childbirth of 30.8 years, climbed to the top in 2011 with a mean of 31.5 years.[3]

Changes in demographics and in the perception of risks, along with a generalized

extension and improvement of antenatal diagnosis, have increased (in Spain and other

countries) the public awareness on reproductive health issues. Improvements in

antenatal diagnosis as well as in case registrations allow for more reliable population-

based studies on congenital anomalies.










population.








METHODS





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the anomalies included in each subgroup can be found somewhere else.[1] We

estimated total prevalence rates (congenital anomalies in liveborns, foetal deaths and

induced abortions divided by the total number of births) and prevalence rates at birth

(congenital anomalies in liveborns and foetal deaths divided by the total number of

births). Data related to denominators (number of births per year, place of residence and

age of the mother) were obtained from the Registry of Newborns of the Basque

Country.









We also conducted Chi square tests for trends in proportions, whose p-value results are

virtually identical to those from the binomial regression models.










Country.

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RESULTS










years, in all births and in cases of congenital anomalies (CA) of the Basque Country, in

1999-2001 and 2006-2008

1999-2001 2006-2008


All births 32.1(4.5) 18.3% 1.4% 32.3(4.7) 23.9% 2.9%

Chromosomal CA 34.6(4.5) 42.6% 7.4% 35.3(5.0) 51.5% 12.0%

Non-chromosomal CA 32.1(4.6) 21.1% 3.6% 32.3(5.1) 27.2% 3.2%











0.63 (IC95%:0.52, 0.75), 0.42 (IC95%:0.33, 0.52), 0.27 (IC95%:0.20, 0.35) and 0.22









DS. Maternal age group is strongly associated with the prevalence of chromosomal

anomalies (p<0.001), with prevalence rates 1.3, 3.2 and 8.3 times greater in women of

30-34, 35-39 and over 40 years than in women under 30 years, respectively.




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period with different evolutions in time (Fig 3). Deviations from linearity are negligible

in all studied subgroups of anomalies, except for the urinary subgroup, which increased








1.30 (IC95%:1.06, 1.51) for those over 40.

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n 1999-2008 1999-2001 2006-2008 %(95%CI) p %(95%CI) p


Chromosomal

All 991 5.18(4.87,5.52) 4.95(4.37,5.60) 5.36(4.81,5.97) 1.01(0.99,1.04) 0.174 1.00(0.98,1.02) 0.878

DS* 548 2.87(2.63,3.12) 2.76(2.34,3.26) 3.10(2.68,3.57) 1.03(1.00,1.06) 0.079 1.01(0.98,1.04) 0.669


Non-chromosomal

All 3090 16.2(15.6,16.7) 13.7(12. 8,14.8) 17.8(16.7,18.8) 1.04(1.02,1.05) <0.001 1.04(1.03,1.05) <0.001

Nervous system 456 2.38(2.17,2.62) 1.99(1.63,2.42) 2.84(2.44,3.30) 1.05(1.01,1.08) 0.007 1.05(1.01,1.08) 0.007

Urinary 670 3.50(3.25,3.78) 2.41(2.02,2.89) 3.64(3.19,4.16) 1.04(1.02,1.07) 0.002 1.04(1.01,1.07) 0.003

Digestive 304 1.59(1.42,1.78) 1.31(1.03,1.68) 1.83(1.52,2.21) 1.03(0.99,1.08) 0.101 1.03(0.99,1.08) 0.105

Limbs 460 2.41(2.19,2.64) 1.62(1.30,2.02) 4.09(3.61,4.63) 1.17(1.13,1.21) <0.001 1.17(1.13,1.21) <0.001

Heart 962 5.03(4.72,5.36) 4.87(4.29,5.51) 4.81(4.29,5.40) 1.00(0.98,1.02) 0.876 1.01(0.98,1.03) 0.619


Chromosomal

All 238 1.25(1.09,1.42) 1.49(1.18,1.87) 1.16(0.91,1.46) 0.97(0.93,1.01) 0.160 0.96(0.92,1.00) 0.080

DS 139 0.73(0.61,0.86) 1.02(0.77,1.35) 0.66(0.48,0.90) 0.95(0.9 ,1.01) 0.098 0.95(0.89,1.01) 0.076

Non-chromosomal

All 2442 12.8(12.3,3.29) 10.7(9.9,11.65) 14.1(13.2,15.0) 1.04(1.03,1.06) <0.001 1.04(1.03,1.06) <0.001

Nervous system 166 0.87(0.74,1.01) 0.64(0.45,0.91) 1.17(0.92,1.48) 1.10(1.04,1.16) 0.001 1.10(1.04,1.16) 0.001

Urinary 564 2.95(2.71,3.21) 1.87(1.53,2.30) 3.11(2.70,3.59) 1.05(1.02,1.09) <0.001 1.05(1.02,1.09) <0.001

Digestive 276 1.44(1.28,1.63) 1.20(0.93,1.55) 1.65(1.36,2.01) 1.03(0.99,1.08) 0.115 1.03(0.99,1.08) 0.127

Limbs 360 1.88(1.70,2.09) 1.33(1.04,1.70) 3.23(2.80,3.71) 1.17(1.13,1.22) <0.001 1.17(1.13,1.22) <0.001

Heart 873 4.57(4.27,4.88) 4.73(4.17,5.37) 4.08(3.60,4.62) 0.98(0.96,1.01) 0.176 0.99(0.97,1.01) 0.340


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DISCUSSION




of prevalences is particular of each subgroup, with no common pattern and in some

cases with notable relative rises in magnitude.







































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age grows.[14]
























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CONCLUSION





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FUNDING





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REFERENCES



15.















2011;91 Suppl 1:S16-22.



2010;30:57-64.






Teratol 2004;70:572-9.





Teratol 2012;94:1010-8.










Med Wkly 2008;138:608-13.

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2012;26:7.

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2008.

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131x202mm (300 x 300 DPI)

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Error bars: Annual prevalences and 95% confidence intervals. Lines: GAM fits

197x141mm (300 x 300 DPI)

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133x198mm (300 x 300 DPI)

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No Recommendation



abstract



Introduction


reported


Methods




Participants 6

√








registry)







Data sources/

measurement










confounding




addressed




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Results











Outcome data 15*

√













Discussion







Other information










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REGION

Journal: BMJ Open

Manuscript ID: bmjopen-2013-004244.R2


Date Submitted by the Author: 05-Feb-2014



Epidemiology






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List of authors:


Cirarda FB(2)






Koldo Cambra



C/ Irunlarrea s/n


Tfno: 34 848428292

Fax: 34 848422200


KEYWORDS:


Word count: 2836

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Abstract












32.3(4.7) years, 23.9% and 2.9% in 2006-2008.








during the study period, whereas those of congenital heart defects and anomalies of the

digestive system did not change significantly.






Article summary


� This study analyses the trend over time of the prevalences of congenital

anomalies using highly reliable data from population-based registries.



anomalies at birth.



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3

INTRODUCTION





Pan-Europe analysis for several congenital anomalies such as hypospadias, abdominal

wall anomalies, gastroschisis, trisomy 18 and renal dysplasia.[2] Local trends have been

more frequently detected but, in general, they need further verification.





















population.








METHODS





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the anomalies included in each subgroup can be found elsewhere.[1] We estimated total

prevalence rates (congenital anomalies in liveborns, foetal deaths and induced abortions

divided by the total number of births) and prevalence rates at birth (congenital

anomalies in liveborns and foetal deaths divided by the total number of births). Data

related to denominators (number of births per year, place of residence and age of the

mother) were obtained from the Registry of Newborns of the Basque Country.









Also, we used these age groups to conduct complementary age-stratified analyses for

chromosomal anomalies.










Country.

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RESULTS










years, in all births and in cases of congenital anomalies of the Basque Country, in 1999-

2001 and 2006-2008

1999-2001 2006-2008


All births 32.1(4.5) 18.3% 1.4% 32.3(4.7) 23.9% 2.9%

Chromosomal CA* 34.6(4.5) 42.6% 7.4% 35.3(5.0) 51.5% 12.0%

Non-chromosomal CA* 32.1(4.6) 21.1% 3.6% 32.3(5.1) 27.2% 3.2%

*CA: Congenital Anomalies











0.63 (IC95%:0.52, 0.75), 0.42 (IC95%:0.33, 0.52), 0.27 (IC95%:0.20, 0.35) and 0.22









DS. In the age-stratified analysis, the decreasing trend in the prevalence of

chromosomal anomalies at birth is more clearly observed in women between 30 and 34

years (p=0.031). Maternal age is strongly associated with the prevalence of

chromosomal anomalies (p<0.001), with prevalence rates 1.3, 3.2 and 8.3 times greater

in women of 30-34, 35-39 and over 40 years than in women under 30 years,

respectively.

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period with different time patterns (Fig 3). Deviations from linearity are negligible in all

studied subgroups of anomalies, except for the urinary subgroup, which increased








1.30 (IC95%:1.06, 1.51) for those over 40.

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n 1999-2008 1999-2001 2006-2008 %(95%CI) p %(95%CI) p


Chromosomal

All 991 5.18(4.87,5.52) 4.95(4.37,5.60) 5.36(4.81,5.97) 1.01(0.99,1.04) 0.174 1.00(0.98,1.02) 0.878

DS* 548 2.87(2.63,3.12) 2.76(2.34,3.26) 3.10(2.68,3.57) 1.03(1.00,1.06) 0.079 1.01(0.98,1.04) 0.669


Non-chromosomal

All 3090 16.16(15.61,16.74 13.75(12.78,14.80) 17.76(16.75,18.84) 1.04(1.02,1.05) <0.001 1.04(1.03,1.05) <0.001

Nervous system 456 2.38(2.17,2.62) 1.99(1.63,2.42) 2.84(2.44,3.30) 1.05(1.01,1.08) 0.007 1.05(1.01,1.08) 0.007

Urinary 670 3.50(3.25,3.78) 2.41(2.02,2.89) 3.64(3.19,4.16) 1.04(1.02,1.07) 0.002 1.04(1.01,1.07) 0.003

Digestive 304 1.59(1.42,1.78) 1.31(1.03,1.68) 1.83(1.52,2.21) 1.03(0.99,1.08) 0.101 1.03(0.99,1.08) 0.105

Limbs 460 2.41(2.19,2.64) 1.62(1.30,2.02) 4.09(3.61,4.63) 1.17(1.13,1.21) <0.001 1.17(1.13,1.21) <0.001

Heart 962 5.03(4.72,5.36) 4.87(4.29,5.51) 4.81(4.29,5.40) 1.00(0.98,1.02) 0.876 1.01(0.98,1.03) 0.619

Anomalies at birth

Chromosomal

All 238 1.25(1.09,1.42) 1.49(1.18,1.87) 1.16(0.91,1.46) 0.97(0.93,1.01) 0.160 0.96(0.92,1.00) 0.080

DS 139 0.73(0.61,0.86) 1.02(0.77,1.35) 0.66(0.48,0.90) 0.95(0.9 ,1.01) 0.098 0.95(0.89,1.01) 0.076

Non-chromosomal

All 2442 12.77(12.29,13.29) 10.72(9.86,11.65) 14.07(13.17,15.03) 1.04(1.03,1.06) <0.001 1.04(1.03,1.06) <0.001

Nervous system 166 0.87(0.74,1.01) 0.64(0.45,0.91) 1.17(0.92,1.48) 1.10(1.04,1.16) 0.001 1.10(1.04,1.16) 0.001

Urinary 564 2.95(2.71,3.21) 1.87(1.53,2.30) 3.11(2.70,3.59) 1.05(1.02,1.09) <0.001 1.05(1.02,1.09) <0.001

Digestive 276 1.44(1.28,1.63) 1.20(0.93,1.55) 1.65(1.36,2.01) 1.03(0.99,1.08) 0.115 1.03(0.99,1.08) 0.127

Limbs 360 1.88(1.70,2.09) 1.33(1.04,1.70) 3.23(2.80,3.71) 1.17(1.13,1.22) <0.001 1.17(1.13,1.22) <0.001

Heart 873 4.57(4.27,4.88) 4.73(4.17,5.37) 4.08(3.60,4.62) 0.98(0.96,1.01) 0.176 0.99(0.97,1.01) 0.340


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8

DISCUSSION




of prevalences is particular of each subgroup, with no common pattern.







































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age grows.[14]
























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CONCLUSION





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FUNDING



CONTRIBUTORSHIP STATEMENT

KC designed the project, checked the data, interpreted the results, and drafted and

revised the manuscript. BI participated in the study design, conducted the statistical

analysis, interpreted the results and reviewed the manuscript. FC, DU and IP

participated in the study design, collected the data, created the databases and reviewed

the manuscript. SE and IM took part in the study design and reviewed the manuscript.



DATA SHARING STATEMENT

No additional data

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12

REFERENCES



15.















2011;91 Suppl 1:S16-22.



2010;30:57-64.






Teratol 2004;70:572-9.





Teratol 2012;94:1010-8.










Med Wkly 2008;138:608-13.

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2012;26:7.

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2008.

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1



List of authors:


Cirarda FB(2)






Koldo Cambra



C/ Irunlarrea s/n


Tfno: 34 848428292

Fax: 34 848422200


KEYWORDS:


Word count: 2836

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2

Abstract












32.3(4.7) years, 23.9% and 2.9% in 2006-2008.








during the study period, whereas those of congenital heart defects and anomalies of the

digestive system did not change significantly.






Article summary


� This study analyses the trend over time of the prevalences of congenital

anomalies using highly reliable data from population-based registries.



anomalies at birth.



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3

INTRODUCTION





Pan-Europe analysis for several congenital anomalies such as hypospadias, abdominal

wall anomalies, gastroschisis, trisomy 18 and renal dysplasia.[2] Local trends have been

more frequently detected but, in general, they need further verification.





















population.








METHODS





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4



















the anomalies included in each subgroup can be found elsewhere.[1] We estimated total

prevalence rates (congenital anomalies in liveborns, foetal deaths and induced abortions

divided by the total number of births) and prevalence rates at birth (congenital

anomalies in liveborns and foetal deaths divided by the total number of births). Data

related to denominators (number of births per year, place of residence and age of the

mother) were obtained from the Registry of Newborns of the Basque Country.









Also, we used these age groups to conduct complementary age-stratified analyses for

chromosomal anomalies.










Country.

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5

RESULTS










years, in all births and in cases of congenital anomalies of the Basque Country, in 1999-

2001 and 2006-2008

1999-2001 2006-2008


All births 32.1(4.5) 18.3% 1.4% 32.3(4.7) 23.9% 2.9%

Chromosomal CA* 34.6(4.5) 42.6% 7.4% 35.3(5.0) 51.5% 12.0%

Non-chromosomal CA* 32.1(4.6) 21.1% 3.6% 32.3(5.1) 27.2% 3.2%

*CA: Congenital Anomalies











0.63 (IC95%:0.52, 0.75), 0.42 (IC95%:0.33, 0.52), 0.27 (IC95%:0.20, 0.35) and 0.22









DS. In the age-stratified analysis, the decreasing trend in the prevalence of

chromosomal anomalies at birth is more clearly observed in women between 30 and 34

years (p=0.031). Maternal age is strongly associated with the prevalence of

chromosomal anomalies (p<0.001), with prevalence rates 1.3, 3.2 and 8.3 times greater

in women of 30-34, 35-39 and over 40 years than in women under 30 years,

respectively.

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period with different time patterns (Fig 3). Deviations from linearity are negligible in all

studied subgroups of anomalies, except for the urinary subgroup, which increased








1.30 (IC95%:1.06, 1.51) for those over 40.

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n 1999-2008 1999-2001 2006-2008 %(95%CI) p %(95%CI) p


Chromosomal

All 991 5.18(4.87,5.52) 4.95(4.37,5.60) 5.36(4.81,5.97) 1.01(0.99,1.04) 0.174 1.00(0.98,1.02) 0.878

DS* 548 2.87(2.63,3.12) 2.76(2.34,3.26) 3.10(2.68,3.57) 1.03(1.00,1.06) 0.079 1.01(0.98,1.04) 0.669


Non-chromosomal

All 3090 16.16(15.61,16.74 13.75(12.78,14.80) 17.76(16.75,18.84) 1.04(1.02,1.05) <0.001 1.04(1.03,1.05) <0.001

Nervous system 456 2.38(2.17,2.62) 1.99(1.63,2.42) 2.84(2.44,3.30) 1.05(1.01,1.08) 0.007 1.05(1.01,1.08) 0.007

Urinary 670 3.50(3.25,3.78) 2.41(2.02,2.89) 3.64(3.19,4.16) 1.04(1.02,1.07) 0.002 1.04(1.01,1.07) 0.003

Digestive 304 1.59(1.42,1.78) 1.31(1.03,1.68) 1.83(1.52,2.21) 1.03(0.99,1.08) 0.101 1.03(0.99,1.08) 0.105

Limbs 460 2.41(2.19,2.64) 1.62(1.30,2.02) 4.09(3.61,4.63) 1.17(1.13,1.21) <0.001 1.17(1.13,1.21) <0.001

Heart 962 5.03(4.72,5.36) 4.87(4.29,5.51) 4.81(4.29,5.40) 1.00(0.98,1.02) 0.876 1.01(0.98,1.03) 0.619

Anomalies at birth

Chromosomal

All 238 1.25(1.09,1.42) 1.49(1.18,1.87) 1.16(0.91,1.46) 0.97(0.93,1.01) 0.160 0.96(0.92,1.00) 0.080

DS 139 0.73(0.61,0.86) 1.02(0.77,1.35) 0.66(0.48,0.90) 0.95(0.9 ,1.01) 0.098 0.95(0.89,1.01) 0.076

Non-chromosomal

All 2442 12.77(12.29,13.29) 10.72(9.86,11.65) 14.07(13.17,15.03) 1.04(1.03,1.06) <0.001 1.04(1.03,1.06) <0.001

Nervous system 166 0.87(0.74,1.01) 0.64(0.45,0.91) 1.17(0.92,1.48) 1.10(1.04,1.16) 0.001 1.10(1.04,1.16) 0.001

Urinary 564 2.95(2.71,3.21) 1.87(1.53,2.30) 3.11(2.70,3.59) 1.05(1.02,1.09) <0.001 1.05(1.02,1.09) <0.001

Digestive 276 1.44(1.28,1.63) 1.20(0.93,1.55) 1.65(1.36,2.01) 1.03(0.99,1.08) 0.115 1.03(0.99,1.08) 0.127

Limbs 360 1.88(1.70,2.09) 1.33(1.04,1.70) 3.23(2.80,3.71) 1.17(1.13,1.22) <0.001 1.17(1.13,1.22) <0.001

Heart 873 4.57(4.27,4.88) 4.73(4.17,5.37) 4.08(3.60,4.62) 0.98(0.96,1.01) 0.176 0.99(0.97,1.01) 0.340


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DISCUSSION




of prevalences is particular of each subgroup, with no common pattern.







































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age grows.[14]
























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CONCLUSION





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FUNDING





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12

REFERENCES



15.















2011;91 Suppl 1:S16-22.



2010;30:57-64.






Teratol 2004;70:572-9.





Teratol 2012;94:1010-8.










Med Wkly 2008;138:608-13.

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2012;26:7.

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2008.

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58x90mm (300 x 300 DPI)

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125x90mm (300 x 300 DPI)

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60x90mm (300 x 300 DPI)

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No Recommendation



abstract



Introduction


reported


Methods




Participants 6

√








registry)







Data sources/

measurement










confounding




addressed




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Results











Outcome data 15*

√













Discussion







Other information










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