# Assessing sociodemographic differences (or lack thereof) in prenatal diagnosis of congenital heart defects: a population-based study

Babak Khoshnood, Nathalie Lelong, Thibaut Andrieu, Lucile Houyel, Damien Bonnet, Jean-Marie Jouannic, François Goffinet

► To cite this version:

Babak Khoshnood, Nathalie Lelong, Thibaut Andrieu, Lucile Houyel, Damien Bonnet, et al.. Assessing sociodemographic differences (or lack thereof) in prenatal diagnosis of congenital heart defects: a population-based study. BMJ Open, 2016, 6 (3), pp.e009353. 10.1136/bmjopen-2015-009353. hal-01315373

HAL Id: hal-01315373

https://hal.sorbonne-universite.fr/hal-01315373

Submitted on 13 May 2016

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# BMJ Open Assessing sociodemographic differences (or lack thereof) in prenatal diagnosis of congenital heart defects: a population-based study

Babak Khoshnood,¹ Nathalie Lelong,¹ Thibaut Andrieu,¹ Lucile Houyel,² Damien Bonnet,³ Jean-Marie Jouannic,⁴ François Goffinet,¹,⁵ on behalf of the EPICARD Study Group

**To cite:** Khoshnood B, Lelong N, Andrieu T, et al. Assessing sociodemographic differences (or lack thereof) in prenatal diagnosis of congenital heart defects: a population-based study. *BMJ Open* 2016;6:e009353. doi:10.1136/bmjopen-2015-009353

► Prepublication history and additional material is available. To view please visit the journal (http://dx.doi.org/10.1136/bmjopen-2015-009353).

Received 10 July 2015

Accepted 17 December 2015

<figure><img src="image_2.png" /></figure>

CrossMark

For numbered affiliations see end of article.

**Correspondence to**
Dr Babak Khoshnood;
babak.khoshnood@inserm.fr

## ABSTRACT

**Objectives:** Our main objective was to assess sociodemographic differences in the probability of prenatal diagnosis of congenital heart defects (CHD); we also looked at differences in termination of pregnancy for fetal anomaly (TOPFA).

**Design:** Prospective cohort observational study.

**Setting:** Population-based cohort of CHD (live births, TOPFA, fetal deaths) born to women residing in the Greater Paris area (Paris and its surrounding suburbs, N=317 538 total births).

**Participants:** 2867 cases of CHD, including 2348 (82%) live births, 466 (16%) TOPFA and 53 (2%) fetal deaths.

**Primary and secondary outcome measures:**

Differences in the probability of prenatal diagnosis by maternal occupation, geographic origin and place of residence; differences in the probability of TOPFA.

**Results:** 29.1% (95% CI 27.5% to 30.8%) of all CHD were prenatally diagnosed. Probability of prenatal diagnosis was similar by maternal occupation, geographic origin and place of residence. In contrast, there were substantial differences in the probability of TOPFA by maternal geographic origin; differences by maternal occupation and place of residence were generally smaller and not statistically significant.

**Conclusions:** Our findings suggest that an appropriate health system organisation aimed at providing universal, reimbursed specialised services to all women can provide comparable access to prenatal diagnosis for all sociodemographic groups. In contrast, we found substantial differences in TOPFA for women of different geographic origins, which may reflect women's preferences that should be respected, but that can nonetheless lead to the situation where families with fewer resources will be disproportionately responsible for care of newborns with more severe forms of CHD.

## INTRODUCTION

Congenital heart defects (CHD) are the most frequent group of major congenital

## Strengths limitations of this study

- Our analyses were based on data from a large, prospective, population-based cohort study of congenital heart defects (CHD).

- There is paucity of information on sociodemographic differences in prenatal diagnosis of CHD, which constitute an important group of congenital anomalies. This limitation in data is particularly true in case of population-based data.

- We report an absence of disparities in prenatal diagnosis of CHD; this constitutes an exception rather than the rule in the studies of disparities in health service use. This, in turn, suggests that such disparities are not inevitable in the setting of an appropriate healthcare organisation and financing.

- We only examined a limited set of sociodemographic factors: maternal occupation, geographic origin and department of residence. We lacked data on maternal education, paternal education, family income and other important individual-level characteristics, as well as data on small area-level indicators of socioeconomic context.

- We were not able to examine women's knowledge or preferences, including whether or not the practices or outcomes of prenatal diagnosis reflected their informed decision-making.

anomalies, accounting for almost 1% of all births.¹ ² Despite considerable progress in the medical and surgical management of CHD,³⁻⁷ they remain the most important cause of infant mortality due to congenital anomalies. Moreover, survivors may have considerable short-term morbidity and long-term adverse neurodevelopmental outcomes.⁸⁻¹⁶

Sociodemographic differences in use of health services and outcomes are ubiquitous and amply documented.¹⁷⁻²⁰ This includes the case of congenital anomalies²¹⁻²⁵ even if much of this literature is concerned with the specific case of Down syndrome.²³ ²⁶⁻²⁹ Little
population-based data exist on sociodemographic differ-
ences in the prevalence, diagnosis, management or out-
comes of CHD. In a retrospective population-based
cohort study, Pinto et al³⁰ looked at census as well as
detailed clinical data in a state-wide surveillance pro-
gramme and found that the probability of prenatal diag-
nosis was not associated with census data. In another
study in the USA, using centre-based data for infants
who underwent surgery or catheter intervention, Peiris
et al³¹ found that individual-level sociodemographic
factors and medical insurance were associated with the
probability of prenatal diagnosis.

Prenatal diagnosis and optimal postnatal manage-
ment of CHD can result in secondary prevention of
mortality and improved long-term outcomes for
CHD. ³⁻⁵ ⁹ ¹⁶ Sociodemographic disparities in prenatal
diagnosis of CHD could therefore lead to poorer out-
comes for groups with less access to prenatal diagnosis.
In addition, prenatal diagnosis can allow the opportun-
ity for women to make an informed decision regarding
their pregnancy, including the option of termination of
pregnancy for fetal anomaly (TOPFA) in case of severe,
incurable CHD.

France pursues an active policy of prenatal surveil-
lance with egalitarian intentions and well-codified rules
and regulations that aim at providing universal, reim-
bursed specialised services to all women. Three ultra-
sound examinations are recommended as part of the
programme for prenatal surveillance; one at the first tri-
mester (11-14 weeks of gestation), a second one at the
second trimester (20-25 weeks) and a third around
34 weeks of gestation. In practice, a substantial number
of women have more than three ultrasound examina-
tions and only a small minority less than three.³²
Prenatal diagnosis of structural congenital anomalies is
done for the most part at the second trimester ultra-
sound; only a small minority are detected either at the
first or the third trimester (in particular, those associated
with intrauterine growth restriction) ultrasound examin-
ation. In case of severe, incurable anomalies, TOPFA is
authorised with no limit of gestational age after certifica-
tion by two experts in dedicated centres for prenatal
diagnosis.

Using data from a population-based prospective
cohort study of CHD, we sought to assess any differences
in the probability of prenatal diagnosis of CHD by
maternal occupation, geographic origin and place of
residence; we did so for all CHD combined and, separ-
ately, for ‘isolated’ cases of CHD (ie, CHD excluding
those cases associated with chromosomal or other anom-
alies). We also looked at sociodemographic differences
in the probability of TOPFA.

MATERIALS AND METHODS

Data source

We used data from the EPICARD (EPIdémiologie des
CARDiopathies congénitales) study, which is a

population-based prospective cohort study with long-
term follow-up of all children with a CHD born to
women in the Greater Paris area (Paris and its surround-
ing suburbs). All cases (live births, TOPFA, fetal deaths)
diagnosed in the prenatal period or up to 1 year of age
in the birth cohorts between 1 May 2005 and 30 April
2008 born to women residing in Greater Paris were eli-
gible for inclusion. Diagnoses were confirmed in specia-
lised paediatric cardiology departments and for the
majority of TOPFA and fetal deaths by a standardised
pathology examination. When a pathology examination
could not be done, the diagnoses were confirmed by a
paediatric cardiologist (LH) and a specialist in echocar-
diography (J-MJ) in the EPICARD study group, using
the results of prenatal echocardiography examination.

Multiple sources of data including all maternity units, paediatric cardiology and cardiac surgery centres, fetal and neonatal pathology departments, neonatal and paediatric intensive units, infant units and outpatient clinics in Greater Paris and a neighbouring tertiary care centre were regularly consulted to attain completeness of case registrations. Informed consent was obtained from study participants. The last cases included in the study were those in the 2008 birth cohort who were diagnosed in 2009. Follow-up of children in the EPICARD cohort is ongoing and will include assessment of children's health and neurodevelopmental outcomes until at least 8 years of age.

Details of coding and classification of cases for the EPICARD study are given elsewhere.³³ Briefly, two paediatric cardiologists in the EPICARD study group (LH, DB) attributed by consensus to each case, one, or in <20% of cases, two or more six-digit code(s) of the long list of the International Paediatric and Congenital Cardiac Code (IPCCC).³⁴ The IPCCC is a comprehensive coding system (the long list of IPCCC includes >10 000 individual codes) and its use in most clinical and epidemiological studies requires regrouping of individual anomalies. A newly proposed classification, the anatomic and clinical classification of CHD (ACC-CHD), accomplishes this regrouping on the basis of anatomic and clinical criteria.³³

Each case was classified into 1 (and only one) of the
10 main categories of the ACC-CHD. This classification
scheme is based on a multidimensional approach
encompassing anatomy, echocardiography, clinical and
surgical management criteria. ACC-CHD includes 10
main categories, ordered in accordance with the direc-
tion of blood flow, and 23 subcategories. It is designed
to use the code numbers of the long list of IPCCC but
can accommodate International Classification of
Diseases, 10th Revision (ICD-10) codes.

Study population

Our initial study population included 2867 cases of
CHD (including live births, fetal deaths and TOPFA).
Information on prenatal diagnosis and TOPFA was avail-
able for all cases. In total, 274 (9.6%) cases had missing
data for maternal occupation and 16 (0.6%) had missing data for geographic origin of the mother; of the latter, 13 (0.5%) cases had missing data on both maternal profession and geographical origin. Overall, 277 (10%) cases had missing data on maternal profession and/or geographical origin. The proportion of cases with a prenatal diagnosis was comparable for cases with complete information on maternal occupation and geographic origin (28.6%) versus for all cases (29.1%) combined (ie, including those with missing data on maternal occupation and/or geographic origin). The probability of TOPFA after prenatal diagnosis was lower, 36.4%, for cases with complete information on maternal occupation and geographic origin vs 41.4% for the overall study population.

The maternal occupation data in our study come from medical records. They reflect women's 'usual' occupation at the time or right before pregnancy. On the basis of occupation categories devised by the French National Institute of Statistics and Economic Studies (INSEE), we used the following maternal occupation categories, which generally represent the order of highest to lowest occupation categories in France: Professional (N=613), Intermediate (N=492), Administrative/Public service (N=309), Other (N=442) and None (N=737). The Administrative/Public service category includes clerical workers and lower echelon public service employees. The group Other included the following categories that comprised a relatively small number of women in each category in our population: artisan, small business owner, shopkeeper, shop assistant, service worker, skilled worker and unskilled worker.

Data on geographic origin were based on women's declaration as noted in their medical records. In many (most) cases, this reflects women's place of birth. However, this is not necessarily the case and geographic origin in our data ultimately reflects how women define their geographic origin. It is important to note that, in France, it is in general illegal to obtain and record race or ethnicity data. Hence, geographic origin should not be equated with ethnicity. Moreover, women of the same geographic origin may very well be of different ethnicity.

We classified the geographical origin of the mother into four categories representing the major groups in France: France (N=1370), North Africa (N=526), Other (sub-Saharan) Africa (N=393) and Other origins (N=562). The latter group mostly comprises women of European origin other than France.

In total, 972 women in the study population were residents of Paris, 702 residents of Hauts-de-Seine, 684 of Seine-Saint-Denis and 509 of Val-de-Marne; the latter three are the adjoining suburbs of Paris. Even if important heterogeneities exist in the sociodemographic characteristics of both residents of Paris and its suburbs, particularly in case of Seine-Saint Denis, those residing in the suburbs tend to have on average a lower sociodemographic status as compared with residents of Paris.

## Statistical analysis

We calculated the proportion of cases with a prenatal diagnosis and TOPFA after a prenatal diagnosis with 95% binomial exact CIs overall and by maternal occupation, geographic origin and place of residence for: (1) all cases of CHD combined, (2) 'isolated' cases of CHD, excluding those associated with chromosomal or other anomalies; 'isolated' cases of CHD could include one or more types of CHD but no other anomalies. We used logistic regression models to estimate the adjusted effects associated with maternal occupation, geographic origin and place of residence on the odds of prenatal diagnosis and TOPFA in models that also included maternal age. We also estimated logistic models that included all of the above plus categories of ACC-CHD in order to take into account any variations that may exist in the distribution of categories of CHD across socioeconomic groups; this was done as the probability of prenatal diagnosis and TOPFA is known to vary substantially across different groups of CHD.¹ ⁶ ³⁵

## RESULTS

### Study population

Table 1 shows the characteristics of the study population. The majority (60%) of women were 25–34 years of age and approximately 30% were 35 years of age or older. Almost half of all women were of French origin, 18% from North Africa and 14% from other African origins. Overall, 24% of women were in the Professional (highest occupation) category and 28% declared no maternal occupation. One-third of women resided in Paris and the remaining were, in relatively similar proportions, residents of the three surrounding suburbs of Paris.

### Prenatal diagnosis

Table 2 shows the proportion of all fetuses (live births, stillbirths and TOPFA combined) which had a prenatal diagnosis of CHD. Overall, 29% of all cases and 23% of 'isolated' cases of CHD were prenatally diagnosed. The probability of prenatal diagnosis for all CHD was somewhat higher (adjusted OR 1.4, 95% CI 1.1 to 1.9) for women aged 38 years and older; however, for 'isolated' CHD, there were no statistically significant differences by maternal age.

We also found essentially no significant disparities in the probability of prenatal diagnosis by maternal occupation, geographic origins or place of residence. This was true both for all and 'isolated' cases of CHD. Moreover, the adjusted ORs of prenatal diagnosis for all and isolated cases of CHD estimated using a model that included maternal occupation, geographic origin and place of residence, as well as maternal age and categories of ACC-CHD, were close to one and the differences were not statistically significant (table 2). Additional detailed descriptive data on the probability of prenatal diagnosis by maternal characteristics as well as
<table><caption>**Table 1** Characteristics of study population in the EPICARD study</caption><thead><tr><th></th><th>N</th><th>Per cent</th></tr></thead><tbody><tr><td>Age (year)</td><td></td><td></td></tr><tr><td>&lt;25</td><td>313</td><td>11.0</td></tr><tr><td>25-34</td><td>1692</td><td>59.4</td></tr><tr><td>35-37</td><td>408</td><td>14.3</td></tr><tr><td>&gt;37</td><td>435</td><td>15.3</td></tr><tr><td>Occupation</td><td></td><td></td></tr><tr><td>Professional</td><td>613</td><td>23.6</td></tr><tr><td>Intermediate</td><td>492</td><td>19.0</td></tr><tr><td>Administrative/Public service</td><td>309</td><td>11.9</td></tr><tr><td>Other</td><td>442</td><td>17.1</td></tr><tr><td>None</td><td>737</td><td>28.4</td></tr><tr><td>Geographic origin</td><td></td><td></td></tr><tr><td>France</td><td>1370</td><td>48.1</td></tr><tr><td>North African</td><td>526</td><td>18.4</td></tr><tr><td>Other African</td><td>393</td><td>13.8</td></tr><tr><td>Other origins</td><td>562</td><td>19.7</td></tr><tr><td>Department of residence</td><td></td><td></td></tr><tr><td>Paris</td><td>972</td><td>33.9</td></tr><tr><td>Hauts-de-Seine</td><td>702</td><td>24.5</td></tr><tr><td>Seine-Saint-Denis</td><td>684</td><td>23.9</td></tr><tr><td>Val-de-Marne</td><td>509</td><td>17.7</td></tr><tr><td>Congenital heart defects</td><td></td><td></td></tr><tr><td>Isolated</td><td>2031</td><td>70.8</td></tr><tr><td>Associated with chromosomal anomalies</td><td>397</td><td>13.9</td></tr><tr><td>Associated with anomalies of other systems</td><td>439</td><td>15.3</td></tr><tr><td>Pregnancy outcome</td><td></td><td></td></tr><tr><td>Live births</td><td>2348</td><td>81.9</td></tr><tr><td>TOPFA</td><td>466</td><td>16.3</td></tr><tr><td>Fetal deaths</td><td>53</td><td>1.8</td></tr></tbody></table>

EPICARD, EPIdémiologie des CARDiopathies congénitales; TOPFA, termination of pregnancy for fetal anomaly.

ACC-CHD groups are provided in online supplementary annex 1.

Table 3 shows the proportion of prenatal diagnosis for live births only. Overall, approximately 20% of all cases and 18% of 'isolated' cases of CHD among live births were prenatally diagnosed. Older women had higher proportions of prenatal diagnosis for all CHD but not for 'isolated' CHD only.

The proportions of prenatal diagnosis across the socio-demographic groups examined were generally similar and there was no evidence of lower odds of prenatal diagnosis for women in lower occupation groups or those from different geographic origins (table 3).

## Terminations of pregnancy for fetal anomaly (TOPFA)

Table 4 shows the proportion of all and 'isolated' cases of CHD with TOPFA following prenatal diagnosis of the CHD. Overall, approximately 41% of all cases and 28% of 'isolated' cases of CHD that were prenatally diagnosed had a TOPFA. We found no statistically significant differences in the probability of TOPFA by maternal age,

occupation or place of residence. However, the proportion of cases with TOPFA was substantially lower for women of African origin and those without a profession. In the logistic regression models that adjusted the effects for a given sociodemographic factor for its association with others, there remained statistically significant and substantial differences in the adjusted odds of TOPFA by geographic origin but not by maternal occupation or place of residence. Women of African origin were less than half as likely to opt for a TOPFA after prenatal diagnosis of an 'isolated' CHD. Additional detailed descriptive data on the probability of TOPFA by maternal characteristics as well as ACC-CHD groups are provided in online supplementary annex 2.

## DISCUSSION

In summary, using population-based data from 2867 cases of CHD, we found no evidence of socioeconomic differences, by maternal occupation, geographic origin or place of residence, in the probability of prenatal diagnosis of CHD. The likelihood of prenatal diagnosis was similar across the sociodemographic groups both for the total number of cases of CHD and for live births only. We did, however, find substantial differences in the probability of TOPFA after a prenatal diagnosis of CHD, particularly for women of different geographic origins. In particular, women of African origin were more likely to continue their pregnancy after prenatal diagnosis of CHD. These findings were robust to adjustment for maternal age and the spectrum of severity of CHD, accounted for by an ACC-CHD.³³

In general, absence of sociodemographic disparities in health service utilisation and outcomes is the exception rather than the rule.¹⁷⁻²⁰ This is also the case in the field of congenital anomalies, although relatively little data exist for anomalies other than Down syndrome.²²⁻²⁵ ²⁸ To the best of our knowledge, this is the first population-based study to specifically assess individual-level sociodemographic differences in prenatal diagnosis and TOPFA of CHD. Our results imply that the potential advantage of prenatal diagnosis, which can lead to both a more informed decision regarding the pregnancy and a more optimal postnatal management of newborns with CHD, is equally shared across sociodemographic groups in our population.

France pursues an active policy of prenatal surveillance with egalitarian intentions. In spite of this policy, previous studies have shown sociodemographic differences in prenatal screening, diagnosis and live birth prevalence of Down syndrome in France.²⁸ ³⁶ However, it appears that disparities in prenatal diagnosis of Down syndrome have decreased substantially over time,³⁷ suggesting that changes in practice and implementation of policies aimed at universal reimbursed access to prenatal diagnosis services have resulted in widespread diffusion of prenatal screening services for Down syndrome for all women. Our results further suggest that in the case of
<table><caption>Table 2 Prenatal diagnosis of CHD according to maternal characteristics in the EPICARD study</caption><thead><tr><th rowspan="3"></th><th colspan="10">Prenatal diagnosis</th><th colspan="10">Isolated CHD*</th></tr><tr><th colspan="4">All CHD</th><th rowspan="2">p Value†</th><th rowspan="2">Adjusted OR‡</th><th rowspan="2">p Value†</th><th colspan="4">N</th><th colspan="4">OR</th><th colspan="4">p Value†</th></tr><tr><th>N</th><th>Per cent</th><th>OR</th><th>95% CI</th><th>N</th><th>Per cent</th><th>OR</th><th>95% CI</th><th>N</th><th>Per cent</th><th>OR</th><th>95% CI</th><th>N</th><th>Per cent</th><th>OR</th><th>95% CI</th><th>N</th><th>Per cent</th><th>OR</th><th>95% CI</th></tr></thead><tbody><tr><td>Age (year)</td><td>2867</td><td>29.1</td><td></td><td>27.5 to 30.8</td><td></td><td></td><td></td><td></td><td></td><td>2031</td><td>23.0</td><td></td><td></td><td>21.2 to 24.9</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;25</td><td>313</td><td>29.7</td><td>1.1</td><td>0.8 to 1.4</td><td>0.09</td><td>1.0</td><td>0.7 to 1.4</td><td>0.09</td><td>222</td><td>23.9</td><td>1.0</td><td>0.7 to 1.5</td><td>0.86</td><td>0.9</td><td>0.6 to 1.4</td><td>0.53</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>25–34</td><td>1692</td><td>28.2</td><td>Ref</td><td></td><td></td><td>Ref</td><td></td><td></td><td>1284</td><td>23.2</td><td>Ref</td><td></td><td></td><td>Ref</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>35–37</td><td>408</td><td>27.9</td><td>1.0</td><td>0.8 to 1.3</td><td></td><td>1.0</td><td>0.8 to 1.4</td><td></td><td>280</td><td>21.4</td><td>0.9</td><td>0.7 to 1.2</td><td></td><td>1.1</td><td>0.7 to 1.6</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&gt;37</td><td>435</td><td>34.3</td><td>1.3</td><td>1.1 to 1.7</td><td></td><td>1.4</td><td>1.1 to 1.9</td><td></td><td>229</td><td>24.5</td><td>1.1</td><td>0.8 to 1.5</td><td></td><td>1.3</td><td>0.9 to 1.9</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Occupation</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Professional</td><td>613</td><td>26.9</td><td>Ref</td><td>Ref</td><td>0.11</td><td>Ref</td><td>Ref</td><td>0.39</td><td>467</td><td>20.8</td><td>Ref</td><td>Ref</td><td>0.05</td><td>Ref</td><td>Ref</td><td>0.34</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Intermediate</td><td>492</td><td>28.3</td><td>1.1</td><td>0.8 to 1.4</td><td></td><td>1.2</td><td>0.9 to 1.7</td><td></td><td>385</td><td>23.1</td><td>1.1</td><td>0.8 to 1.6</td><td></td><td>1.1</td><td>0.8 to 1.7</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Administrative/ Public service</td><td>309</td><td>23.6</td><td>0.8</td><td>0.6 to 1.2</td><td></td><td>0.8</td><td>0.6 to 1.2</td><td></td><td>236</td><td>16.5</td><td>0.8</td><td>0.5 to 1.1</td><td></td><td>0.7</td><td>0.4 to 1.1</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Other</td><td>442</td><td>29.6</td><td>1.1</td><td>0.9 to 1.5</td><td></td><td>1.0</td><td>0.7 to 1.4</td><td></td><td>295</td><td>24.4</td><td>1.2</td><td>0.9 to 1.7</td><td></td><td>1.1</td><td>0.7 to 1.7</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>None</td><td>737</td><td>31.3</td><td>1.2</td><td>1.0 to 1.6</td><td></td><td>1.0</td><td>0.7 to 1.5</td><td></td><td>500</td><td>25.8</td><td>1.4</td><td>1.0 to 1.8</td><td></td><td>1.1</td><td>0.7 to 1.7</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Geographic origin</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>France</td><td>1370</td><td>27.7</td><td>Ref</td><td>Ref</td><td>0.12</td><td>Ref</td><td>Ref</td><td>0.62</td><td>1030</td><td>21.8</td><td>Ref</td><td>Ref</td><td>0.24</td><td>Ref</td><td>Ref</td><td>0.90</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>North African</td><td>526</td><td>28.1</td><td>1.0</td><td>0.8 to 1.3</td><td></td><td>0.9</td><td>0.7 to 1.3</td><td></td><td>360</td><td>21.9</td><td>1.0</td><td>0.8 to 1.3</td><td></td><td>0.9</td><td>0.6 to 1.3</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Other African</td><td>393</td><td>33.6</td><td>1.3</td><td>1.0 to 1.7</td><td></td><td>1.2</td><td>0.8 to 1.6</td><td></td><td>251</td><td>25.5</td><td>1.2</td><td>0.9 to 1.7</td><td></td><td>1.1</td><td>0.7 to 1.7</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Other origins</td><td>562</td><td>30.6</td><td>1.1</td><td>0.9 to 1.4</td><td></td><td>1.1</td><td>0.8 to 1.4</td><td></td><td>380</td><td>26.3</td><td>1.3</td><td>1.0 to 1.7</td><td></td><td>1.0</td><td>0.7 to 1.4</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Department of residence</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Paris</td><td>972</td><td>28.8</td><td>Ref</td><td>Ref</td><td>0.31</td><td>Ref</td><td>Ref</td><td>0.13</td><td>702</td><td>21.1</td><td>Ref</td><td>Ref</td><td>0.39</td><td>Ref</td><td>Ref</td><td>0.44</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Hauts-de-Seine</td><td>702</td><td>29.5</td><td>1.0</td><td>0.8 to 1.3</td><td></td><td>1.1</td><td>0.8 to 1.4</td><td></td><td>523</td><td>23.3</td><td>1.1</td><td>0.9 to 1.5</td><td></td><td>1.2</td><td>0.9 to 1.7</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Seine-Saint-Denis</td><td>684</td><td>31.3</td><td>1.1</td><td>0.9 to 1.4</td><td></td><td>0.9</td><td>0.7 to 1.2</td><td></td><td>428</td><td>25.5</td><td>1.3</td><td>1.0 to 1.7</td><td></td><td>1.0</td><td>0.7 to 1.5</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Val-de-Marne</td><td>509</td><td>26.3</td><td>0.9</td><td>0.7 to 1.1</td><td></td><td>0.8</td><td>0.6 to 1.0</td><td></td><td>378</td><td>23.5</td><td>1.2</td><td>0.9 to 1.6</td><td></td><td>0.9</td><td>0.6 to 1.3</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

*Isolated CHD: excluding chromosomal or other anomalies.

†p Value of the Wald test.

‡Adjusted OR for age, geographic origin, occupation, department of residence and categories of CHD (ACC-CHD³³).

ACC, anatomic and clinical classification; CHD, congenital heart defects; EPICARD, EPIdémiologie des CARDiopathies congénitales.
<table><caption>Table 3 Prenatal diagnosis of live births with CHD according to maternal characteristics in the EPICARD study</caption><thead><tr><th rowspan="3"></th><th colspan="10">Prenatal diagnosis</th><th colspan="10">Isolated CHD*</th></tr><tr><th colspan="4">All CHD</th><th rowspan="2">p Value†</th><th rowspan="2">Adjusted OR‡</th><th rowspan="2">p Value†</th><th colspan="4">Isolated CHD*</th><th rowspan="2">p Value†</th><th rowspan="2">Adjusted OR‡</th><th rowspan="2">p Value†</th></tr><tr><th>N</th><th>Per cent</th><th>OR</th><th>95% CI</th><th>N</th><th>Per cent</th><th>OR</th><th>95% CI</th></tr></thead><tbody><tr><td>Age (year)</td><td>2348</td><td>19.5</td><td></td><td>17.9 to 21.1</td><td></td><td></td><td></td><td></td><td>1885</td><td>17.5</td><td></td><td>15.8 to 19.2</td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;25</td><td>264</td><td>20.8</td><td>1.2</td><td>0.9 to 1.7</td><td>0.004</td><td>1.0</td><td></td><td></td><td>204</td><td>17.7</td><td>1.0</td><td>0.7 to 1.5</td><td>0.62</td><td>0.8</td><td></td><td>0.5 to 1.4</td><td>0.44</td></tr><tr><td>25–34</td><td>1409</td><td>18.0</td><td>Ref</td><td></td><td></td><td>Ref</td><td></td><td></td><td>1183</td><td>17.1</td><td>Ref</td><td></td><td></td><td>Ref</td><td></td><td></td><td></td></tr><tr><td>35–37</td><td>334</td><td>18.0</td><td>1.0</td><td>0.7 to 1.4</td><td></td><td>1.1</td><td></td><td></td><td>265</td><td>17.0</td><td>1.0</td><td>0.7 to 1.4</td><td></td><td>1.1</td><td></td><td>0.7 to 1.6</td><td></td></tr><tr><td>&gt;37</td><td>322</td><td>26.7</td><td>1.7</td><td>1.3 to 2.2</td><td></td><td>1.6</td><td></td><td></td><td>217</td><td>20.7</td><td>1.3</td><td>0.9 to 1.8</td><td></td><td>1.3</td><td></td><td>0.9 to 2.0</td><td></td></tr><tr><td>Occupation</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Professional</td><td>524</td><td>17.6</td><td>Ref</td><td>Ref</td><td>0.07</td><td>Ref</td><td></td><td></td><td>441</td><td>16.3</td><td>Ref</td><td>Ref</td><td>0.09</td><td>Ref</td><td></td><td>Ref</td><td>0.33</td></tr><tr><td>Intermediate</td><td>426</td><td>20.4</td><td>1.2</td><td>0.9 to 1.7</td><td></td><td>1.2</td><td></td><td></td><td>367</td><td>19.4</td><td>1.2</td><td>0.9 to 1.8</td><td></td><td>1.1</td><td></td><td>0.8 to 1.7</td><td></td></tr><tr><td>Administrative/</td><td>268</td><td>15.7</td><td>0.9</td><td>0.6 to 1.3</td><td></td><td>0.8</td><td></td><td></td><td>225</td><td>12.4</td><td>0.7</td><td>0.5 to 1.2</td><td></td><td>0.7</td><td></td><td>0.4 to 1.1</td><td></td></tr><tr><td>Public service</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Other</td><td>366</td><td>21.0</td><td>1.3</td><td>0.9 to 1.8</td><td></td><td>1.1</td><td></td><td></td><td>273</td><td>19.1</td><td>1.2</td><td>0.8 to 1.8</td><td></td><td>1.1</td><td></td><td>0.7 to 1.7</td><td></td></tr><tr><td>None</td><td>621</td><td>22.9</td><td>1.4</td><td>1.0 to 1.9</td><td></td><td>1</td><td></td><td></td><td>465</td><td>20.4</td><td>1.3</td><td>0.9 to 1.8</td><td></td><td>1.0</td><td></td><td>0.7 to 1.7</td><td></td></tr><tr><td>Geographic origin</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>France</td><td>1129</td><td>17.5</td><td>Ref</td><td>Ref</td><td>0.03</td><td>Ref</td><td></td><td></td><td>958</td><td>16.3</td><td>Ref</td><td>Ref</td><td>0.44</td><td>Ref</td><td></td><td>Ref</td><td>0.96</td></tr><tr><td>North African</td><td>455</td><td>21.8</td><td>1.3</td><td>1.0 to 1.7</td><td></td><td>1.1</td><td></td><td></td><td>342</td><td>17.8</td><td>1.1</td><td>0.8 to 1.5</td><td></td><td>1.0</td><td></td><td>0.6 to 1.5</td><td></td></tr><tr><td>Other African</td><td>315</td><td>24.1</td><td>1.5</td><td>1.1 to 2.0</td><td></td><td>1.3</td><td></td><td></td><td>232</td><td>20.3</td><td>1.3</td><td>0.9 to 1.9</td><td></td><td>1.1</td><td></td><td>0.7 to 1.8</td><td></td></tr><tr><td>Other origins</td><td>437</td><td>19.2</td><td>1.1</td><td>0.8 to 1.5</td><td></td><td>1.0</td><td></td><td></td><td>343</td><td>19.0</td><td>1.2</td><td>0.9 to 1.7</td><td></td><td>1.0</td><td></td><td>0.7 to 1.5</td><td></td></tr><tr><td>Department of residence</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Paris</td><td>794</td><td>18.6</td><td>Ref</td><td>Ref</td><td>0.04</td><td>Ref</td><td></td><td></td><td>657</td><td>16.1</td><td>Ref</td><td>Ref</td><td>0.34</td><td>Ref</td><td></td><td>Ref</td><td>0.50</td></tr><tr><td>Hauts-de-Seine</td><td>598</td><td>20.2</td><td>1.1</td><td>0.8 to 1.4</td><td></td><td>1.1</td><td></td><td></td><td>487</td><td>17.7</td><td>1.1</td><td>0.8 to 1.5</td><td></td><td>1.2</td><td></td><td>0.8 to 1.7</td><td></td></tr><tr><td>Seine-Saint-Denis</td><td>544</td><td>22.8</td><td>1.3</td><td>1.0 to 1.7</td><td></td><td>1.0</td><td></td><td></td><td>399</td><td>20.3</td><td>1.3</td><td>1.0 to 1.8</td><td></td><td>1.1</td><td></td><td>0.8 to 1.6</td><td></td></tr><tr><td>Val-de-Marne</td><td>412</td><td>15.5</td><td>0.8</td><td>0.6 to 1.1</td><td></td><td>0.7</td><td></td><td></td><td>342</td><td>16.4</td><td>1.0</td><td>0.7 to 1.5</td><td></td><td>0.9</td><td></td><td>0.6 to 1.3</td><td></td></tr></tbody></table>

*Isolated CHD: excluding chromosomal or other anomalies.

†p Value of the Wald test.

‡Adjusted OR for age, geographic origin, occupation, department of residence and categories of CHD (ACC-CHD³³).

ACC, anatomic and clinical classification; CHD, congenital heart defects; EPICARD, EPIdémiologie des CARDiopathies congénitales.
<table><caption>Table 4 Association between termination of pregnancy (TOPFA) and maternal characteristics in fetuses with prenatal diagnosis in the EPICARD study</caption><thead><tr><th rowspan="3"></th><th colspan="4">TOPFA</th><th colspan="4">Isolated CHD*</th></tr><tr><th colspan="3">All CHD</th><th rowspan="2">p Value†</th><th rowspan="2">Adjusted OR‡</th><th rowspan="2">p Value†</th><th colspan="3">All CHD</th><th rowspan="2">p Value†</th><th rowspan="2">Adjusted OR‡</th><th rowspan="2">p Value†</th></tr><tr><th>N</th><th>Per cent</th><th>OR</th><th>95% CI</th><th>N</th><th>Per cent</th><th>OR</th><th>95% CI</th></tr></thead><tbody><tr><td>Age (year)</td><td>835</td><td>41.4</td><td></td><td>38.1 to 44.9</td><td></td><td></td><td>468</td><td>27.6</td><td></td><td>23.6 to 31.9</td><td></td><td></td></tr><tr><td>&lt;25</td><td>93</td><td>40.9</td><td>0.9</td><td>0.6 to 1.4</td><td>0.05</td><td>0.8</td><td>53</td><td>32.1</td><td>1.1</td><td>0.6 to 2.0</td><td>0.08</td><td>1.0</td></tr><tr><td>25–34</td><td>477</td><td>43.8</td><td>Ref</td><td></td><td></td><td>Ref</td><td>298</td><td>30.2</td><td>Ref</td><td></td><td></td><td>Ref</td></tr><tr><td>35–37</td><td>114</td><td>45.6</td><td>1.1</td><td>0.7 to 1.6</td><td></td><td>1.2</td><td>60</td><td>23.3</td><td>0.7</td><td>0.4 to 1.3</td><td></td><td>1.0</td></tr><tr><td>&gt;37</td><td>149</td><td>31.5</td><td>0.6</td><td>0.4 to 0.9</td><td></td><td>0.7</td><td>56</td><td>14.3</td><td>0.4</td><td>0.2 to 0.8</td><td></td><td>0.5</td></tr><tr><td>Occupation</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Professional</td><td>165</td><td>43.0</td><td>Ref</td><td>Ref</td><td>0.08</td><td>Ref</td><td>97</td><td>24.7</td><td>Ref</td><td>Ref</td><td>0.61</td><td>Ref</td></tr><tr><td>Intermediate</td><td>139</td><td>33.8</td><td>0.7</td><td>0.4 to 1.1</td><td></td><td>0.8</td><td>89</td><td>19.1</td><td>0.7</td><td>0.4 to 1.4</td><td></td><td>1.2</td></tr><tr><td>Administrative/ Public service</td><td>73</td><td>41.1</td><td>0.9</td><td>0.5 to 1.6</td><td></td><td>1.1</td><td>39</td><td>28.2</td><td>1.2</td><td>0.5 to 2.8</td><td></td><td>2.2</td></tr><tr><td>Other</td><td>131</td><td>38.9</td><td>0.8</td><td>0.5 to 1.3</td><td></td><td>1.2</td><td>72</td><td>27.8</td><td>1.2</td><td>0.6 to 2.3</td><td></td><td>2.5</td></tr><tr><td>None</td><td>231</td><td>30.3</td><td>0.6</td><td>0.4 to 0.9</td><td></td><td>0.8</td><td>129</td><td>20.9</td><td>0.8</td><td>0.4 to 1.5</td><td></td><td>1.1</td></tr><tr><td>Geographic origin</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>France</td><td>380</td><td>46.1</td><td>Ref</td><td>Ref</td><td>&lt;0.0001</td><td>Ref</td><td>225</td><td>29.8</td><td>Ref</td><td>Ref</td><td>0.08</td><td>Ref</td></tr><tr><td>North African</td><td>148</td><td>26.4</td><td>0.4</td><td>0.3 to 0.6</td><td></td><td>0.4</td><td>79</td><td>16.5</td><td>0.5</td><td>0.2 to 0.9</td><td></td><td>0.2</td></tr><tr><td>Other African</td><td>132</td><td>34.9</td><td>0.6</td><td>0.4 to 0.9</td><td></td><td>0.6</td><td>64</td><td>25.0</td><td>0.8</td><td>0.4 to 1.5</td><td></td><td>0.4</td></tr><tr><td>Other origins</td><td>172</td><td>48.8</td><td>1.1</td><td>0.8 to 1.6</td><td></td><td>1.1</td><td>100</td><td>33.0</td><td>1.2</td><td>0.7 to 1.9</td><td></td><td>0.7</td></tr><tr><td>Department of residence</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Paris</td><td>280</td><td>42.1</td><td>Ref</td><td>Ref</td><td>0.25</td><td>Ref</td><td>148</td><td>25.7</td><td>Ref</td><td>Ref</td><td>0.14</td><td>Ref</td></tr><tr><td>Hauts-de-Seine</td><td>207</td><td>38.7</td><td>0.9</td><td>0.6 to 1.2</td><td></td><td>0.9</td><td>122</td><td>27.1</td><td>1.1</td><td>0.6 to 1.8</td><td></td><td>1.2</td></tr><tr><td>Seine-Saint-Denis</td><td>214</td><td>38.8</td><td>0.9</td><td>0.6 to 1.3</td><td></td><td>0.9</td><td>109</td><td>22.9</td><td>0.9</td><td>0.5 to 1.5</td><td></td><td>0.5</td></tr><tr><td>Val-de-Marne</td><td>134</td><td>48.5</td><td>1.3</td><td>0.9 to 2.0</td><td></td><td>1.1</td><td>89</td><td>37.1</td><td>1.7</td><td>1.0 to 3.0</td><td></td><td>1.2</td></tr></tbody></table>

<footnote>*Isolated CHD: excluding chromosomal or other anomalies.</footnote>

<footnote>†p Value of the Wald test.</footnote>

<footnote>‡Adjusted OR for age, geographic origin, occupation, department of residence and categories of CHD (ACC-CHD³³).</footnote>

<footnote>ACC, anatomic and clinical classification; CHD, congenital heart defects; EPICARD, EPIdémiologie des CARDiopathies congénitales; TOPFA, termination of pregnancy for fetal anomaly.</footnote>
CHD there may be little if any important sociodemographic barriers to effective access to prenatal diagnostic services. It is possible, however, that these results may not necessarily be representative of other settings in France, as the wide availability of specialised services in our population is not always the case elsewhere.

In France, three ultrasound examinations are recom-
mended as part of the programme for prenatal surveil-
lance; one at the first trimester (11–14 weeks of
gestation), a second at the second trimester (20–
25 weeks) and a third around 34 weeks of gestation. In
practice, a substantial number of women have more
than three ultrasound examinations and only a small
minority less than three.³² Prenatal diagnosis of struc-
tural congenital anomalies is done for the most part at
the second trimester ultrasound; only a small minority
are detected either at the first (in particular neural tube
defects) or the third trimester (in particular those asso-
ciated with intrauterine growth restriction) ultrasound
examination. In 2005, the National Technical
Committee for Ultrasound Examinations issued recom-
mendations for a minimum of two images of the heart,
including the four-chamber and the short-axis views.
This guideline for fetal ultrasound examination has
come to be legally recognised and is likely to have con-
tributed to a generally higher quality of ultrasound
examination of the heart in our population.

In addition, the organisation of prenatal diagnostic
services is well codified and includes in particular the
constitution of 48 multidisciplinary centres for prenatal
diagnosis across the country, including four in Paris and
five in its surrounding suburbs. By law, the severity of
the fetal anomaly must be certified by two experts from
these centres in order for the TOPFA to be authorised.
For cases in which either TOPFA is not an appropriate
decision ('curable' or not sufficiently severe anomalies)
or for which women opt to continue their pregnancy
even if the experts consider that TOPFA is an acceptable
option, the centres play an important role in the peri-
natal management of cases to optimise care for mothers
and their affected newborns. Mandates for the exclusive
coordination of prenatal diagnosis services by these
multidisciplinary centres are likely to have contributed
to a wider availability of high-quality prenatal diagnostic
services in our population.

With regard to the sociodemographic differences
observed in the probability of TOPFA, to the extent that
these may reflect true differences in women's prefer-
ences, they do not constitute a 'problem' to be remed-
ied. The primary objective of prenatal diagnosis,
including the option of TOPFA in case of severe, incur-
able anomalies, should be the opportunity for women to
make an informed choice³⁸ regarding their pregnancy.
Hence, if women with certain sociodemographic
characteristics are more likely than others to opt for con-
tinuing their pregnancy after prenatal diagnosis of a
severe CHD, such differences in women's decisions
should be respected. However, the possibility that such

apparent differences in preferences may in fact be in
part related to factors associated with healthcare provi-
ders, particularly miscommunication between providers
and pregnant women from different cultural back-
grounds, should also be considered.³⁹

Approximately 10% of cases had missing information for maternal occupation and/or geographic origin. However, the proportion of cases with prenatal diagnosis for those with complete information and the overall study (including those with missing data) was essentially the same, whereas the probability of TOPFA was somewhat (5%) lower for the cases with complete information on sociodemographic characteristics versus the overall study population. We have no à priori or empirical reason to believe that this relatively small difference may have biased our estimates of sociodemographic differences in the probability of TOPFA. Although we cannot be certain, it is likely that cases with TOPFA may overall have less information available on sociodemographic characteristics of women and this is not necessarily, or at least not predominantly, the case for some sociodemographic groups more than others.

Another limit of our study is that we only assessed
sociodemographic differences across maternal occupa-
tion, geographic origin and place of residence using
broad categories. Certainly, sociodemographic status and
its possible effects on prenatal testing cannot be repre-
sented comprehensively using the characteristics
included in our study.⁴⁰ In addition, we did not evaluate
women's knowledge or preferences regarding prenatal
diagnosis and TOPFA for CHD. Hence, we cannot know
to what extent our results may reflect women's effective
access to information and the possibility for informed
decision-making. Finally, despite the large number of
cases included in the cohort, we may have had relatively
limited power to assess the independent effects asso-
ciated with different dimensions of sociodemographic
status. Therefore, the absence of statistically significant
differences in TOPFA for certain groups of maternal
occupation or by place of residence may have been in
part due to limited power in the adjusted models.

Our study leaves several questions unanswered. An
important set of questions relates to the possible existence,
and thereby potential implications of any sociodemo-
graphic differences that might exist in the prevalence and
the distribution of various types of CHD, which may in
turn affect the overall severity of CHD across sociodemo-
graphic groups. CHD represent a heterogeneous group of
anomalies³³ ⁴¹ ⁴² that may affect various aspects of the
normal cardiac anatomy or function. Hence, a major chal-
lenge in evaluating clinical management and outcomes of
CHD relates to the great heterogeneity that exists in CHD
in terms of their prevalence, modalities of diagnosis, clin-
ical severity and treatment options among others.

In the case of our study, the notion of ‘severity’ of
CHD and how it should be defined, particularly when
one is interested in sociodemographic differences in the
prenatal diagnosis of (or pregnancy termination for)
CHD, does not seem obvious. The two well-established scores of severity (Risk Adjustment for Congenital Heart Surgery-1 method (RACHS-1) and Aristotle) are concerned with surgical cases only. In addition, these scores or any other classifications of CHD have not been formally evaluated in terms of their ability to predict the probability of prenatal diagnosis (or pregnancy termination).

In a previous study, we found that prenatal diagnosis, pregnancy termination and infant mortality differed greatly across the categories of this classification (ACC-CHD⁶). Therefore, in the present study, we adjusted our estimates of the associations between socio-demographic factors and probabilities of prenatal diagnosis and pregnancy terminations for ACC-CHD. However, the ACC-CHD classification needs to be further evaluated in terms of its predictive ability of probability of prenatal diagnosis and terminations of CHD. Moreover, it is not known whether or to what extent the prevalence of different types of CHD (whether in categories or for individual defects) may vary in relation to sociodemographic factors, or how any such variabilities may be correlated with clinical severity or probability (ease/modalities) of prenatal diagnosis (eg, possibility of prenatal diagnosis by a four-chamber view or not). We have undertaken a study to examine some of these questions, which are beyond the scope of the present one.

In conclusion, our results imply that the potential advantage of prenatal diagnosis, which can lead to both a more informed decision regarding pregnancy and a more optimal postnatal management of newborns with CHD, is equally shared across the sociodemographic groups in our population. This is at least in part the result of the active policy aimed at providing reimbursed universal access to prenatal diagnostic services for residents of France. In addition, the wide availability of specialised services in our population, as well as the well-codified organisation of prenatal diagnostic services by multidisciplinary centres for prenatal diagnosis, is likely to facilitate access to high-quality services in our population. The sociodemographic differences we found in the probability of TOPFA, particularly across categories of geographic origin, may represent true differences in women's preferences, but the role of healthcare providers, particularly communication issues between providers and pregnant women from different cultural backgrounds, should also be taken into account. In any case, these differences in TOPFA can result in disparities in the spectrum of severity of CHD at birth and thereby in the risk of adverse outcomes. Hence, families with fewer resources may become disproportionately responsible for the care of newborns with more severe forms of CHD.

### Author affiliations

¹INSERM UMR 1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Center for Epidemiology and Statistics, Sorbonne Paris Cité (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, France

²Service de chirurgie des cardiopathies congénitales, Hôpital Marie Lannelongue, Le Plessis Robinson, France

³Centre de référence M3C-Necker, Université Paris Descartes, Paris, France

⁴Hôpital Trousseau, AP-HP, Centre pluridisciplinaire de diagnostic prénatal, UPMC, Paris, France

⁵Maternité de Port-Royal, Groupe Hospitalier Cochin-Broca-Hôtel Dieu, Université Paris Descartes, Assistance Publique-Hôpitaux de Paris, Paris, France

### Acknowledgements
BK and NL had full access to the data and take responsibility for the integrity of the data and the accuracy of the data analysis.

### Collaborators
EPICARD Study Group—principal investigators: François Goffinet, Babak Khoshnood. Steering Committee: Damien Bonnet (Hôpital Necker Enfants Malades, AP-HP, Centre de référence M3C, Université Paris Descartes, Paris); Johanna Calderon (INSERM U953); Drina Candilis (Université Paris-Diderot, Paris); Anne-Lise Delezoide (Hôpital Robert Debré, AP-HP, Service de biologie du Développement, Université Paris-Diderot, Paris); Catherine De Vigan (INSERM U953, Paris); François Goffinet (Groupe Hospitalier Cochin-Hôtel Dieu, AP-HP, Maternité Port-Royal et INSERM U953, Université Paris Descartes, Paris); Lucile Houyel (Hôpital Marie Lannelongue, Service de chirurgie des cardiopathies congénitales, Le Plessis-Robinson); Jean-Marie Jouannic (Hôpital Trousseau, AP-HP, Centre pluridisciplinaire de diagnostic prénatal, UPMC, Paris); Babak Khoshnood (INSERM U953, Paris); Nathalie Lelong (INSERM U953, Paris); Suzel Magnier (Hôpital Robert Debré, AP-HP, Service de cardiologie, Paris); Jean-François Magny (Institut de Puériculture et de périmatologie, Service de néonatologie, Paris); Caroline Rambaud (Hôpital Raymond Poincaré, AP-HP, Service d'anatomie et cytologie pathologiques—Médecine légale, UVSQ, Garches); Dominique Salomon (INSERM U953, Paris); Véronique Vodovar (INSERM U953, Paris). Project Coordination and Data Analysis Committee: François Goffinet, Babak Khoshnood, Nathalie Lelong, Anne-Claire Thieulin, Thibaut Andrieu, Véronique Vodovar; Independent Data Monitoring Committee (URC Paris Centre et CIC Cochin Necker Mère Enfant): Maggy Chausson, Anissa Brinis, Laure Faure, Maryline Delattre, Jean-Marc Treluyer (Groupe Hospitalier Cochin-Hôtel Dieu, AP-HP, Université Paris Descartes, Paris). External Scientific Committee: Gérard Bréart, Dominique Cabrol, Alain Sérraf, Daniel Sidi, Marcel Voyer. Participating Centers: The Greater Paris area (Paris and its surrounding suburbs) public (AP-HP) and private maternity units, Departments of Pediatric Cardiology and Pediatric Cardiac Surgery, pediatric cardiologists in private practice, Neonatal Intensive Care Units, Pediatric Intensive Care Units, Emergency Transfer Services (SMUR), Departments of Pathology, Sudden Death Centers, Departments of Family and Infant Protection (DFPE).

### Contributors
BK conceived the study in consultation with NL. TA conducted the statistical analysis under the supervision of NL and BK. LH and DB devised the classification of CHD. BK wrote the first draft of the article. FG, NL and J-MJ made substantial contributions to the interpretation of results and revisions of the manuscript. All the coauthors were part of the EPICARD Study Group and participated in the design and conduct of the study and contributed to the interpretation of results and critical revision of the manuscript.

### Funding
This work was supported by two grants from the French Ministry of Health (PHRC 2004 and 2008). Additional funding was provided by the AREMCAR (Association pour la Recherche et l'Etude des Maladies Cardiovasculaires) association.

### Disclaimer
The funding sources had no role in the study design, data collection, data interpretation or the writing of the manuscript.

### Competing interests
None declared.

### Ethics approval
The EPICARD study was approved by the French National Committee of Information and Freedom (*Commission nationale de l'informatique et des libertés*).

### Provenance and peer review
Not commissioned; externally peer reviewed.

### Data sharing statement
No additional data are available.

### Open Access
This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license,
which permits others to distribute, remix, adapt, build upon this work non-
commercially, and license their derivative works on different terms, provided
the original work is properly cited and the use is non-commercial. See: http://
creativecommons.org/licenses/by-nc/4.0/

REFERENCES

1. Dolk H, Loane M, Garne E, European Surveillance of Congenital Anomalies (EUROCAT) Working Group. Congenital heart defects in Europe: prevalence and perinatal mortality, 2000 to 2005. *Circulation* 2011;123:841-9.

2. Hoffman JI, Kaplan S. The incidence of congenital heart disease. *J Am Coll Cardiol* 2002;39:1890-900.

3. Blyth M, Howe D, Gnanapragasam J, et al. The hidden mortality of transposition of the great arteries and survival advantage provided by prenatal diagnosis. *BJOG* 2008;115:1096-100.

4. Bonnet D, Coltri A, Butera G, et al. Detection of transposition of the great arteries in fetuses reduces neonatal morbidity and mortality. *Circulation* 1999;99:916-18.

5. Khoshnood B, De Vigan C, Vodovar V, et al. Trends in prenatal diagnosis, pregnancy termination, and perinatal mortality of newborns with congenital heart disease in France, 1983–2000: a population-based evaluation. *Pediatrics* 2005;115:95–101.

6. Khoshnood B, Lelong N, Houyel L, et al. Prevalence, timing of diagnosis and mortality of newborns with congenital heart defects: a population-based study. *Heart* 2012;98:1667-73.

7. Lee K, Khoshnood B, Chen L, et al. Infant mortality from congenital malformations in the United States, 1970–1997. *Obstet Gynecol* 2001;98:620–7.

8. Calderon J, Bonnet D, Courtin C, et al. Executive function and theory of mind in school-aged children after neonatal corrective cardiac surgery for transposition of the great arteries. *Dev Med Child Neurol* 2010;52:1139–44.

9. Calderon J, Angeard N, Moutier S, et al. Impact of prenatal diagnosis on neurocognitive outcomes in children with transposition of the great arteries. *J Pediatr* 2012;161:94–8.

10. Calderon J, Jambaqué I, Bonnet D, et al. Executive functions development in 5- to 7-year-old children with transposition of the great arteries: a longitudinal study. *Dev Neuropsychol* 2014;39:365-84.

11. Mahle WT, Clancy RR, McGaum SP, et al. Impact of prenatal diagnosis on survival and early neurologic morbidity in neonates with the hypoplastic left heart syndrome. *Pediatrics* 2001;107:1277-82.

12. Mahle WT, Wernovsky G. Long-term developmental outcome of children with complex congenital heart disease. *Clin Perinatol* 2001;28:235-47.

13. Mahle WT, Tavani F, Zimmerman RA, et al. An MRI study of neurological injury before and after congenital heart surgery. *Circulation* 2002;106(12 Suppl 1):I109-14.

14. Mahle WT, Visconti KJ, Freier MC, et al. Relationship of surgical approach to neurodevelopmental outcomes in hypoplastic left heart syndrome. *Pediatrics* 2006;117:e90-7.

15. Wernovsky G, Newburger J. Neurologic and developmental morbidity in children with complex congenital heart disease. *J Pediatr* 2003;142:6-8.

16. Wernovsky G, Shillingford AJ, Gaynor JW. Central nervous system outcomes in children with complex congenital heart disease. *Curr Opin Cardiol* 2005;20:94-9.

17. Hart JT. The inverse care law. *Lancet* 1971;1:405-12.

18. Feinstein JS. The relationship between socioeconomic status and health: a review of the literature. *Milbank Q* 1993;71:279-322.

19. Fiscella K, Franks P, Gold MR, et al. Inequality in quality: addressing socioeconomic, racial, and ethnic disparities in health care. *JAMA* 2000;283:2579-84.

20. Gortmaker SL, Wise PH. The first injustice: socioeconomic disparities, health services technology, and infant mortality. *Annu Rev Sociol* 1997;23:147-70.

21. Leck I, Lancashire RJ. Birth prevalence of malformations in members of different ethnic groups and in the offspring of matings between them, in Birmingham, England. *J Epidemiol Community Health* 1995;49:171-9.

22. Vrijheid M, Dolk H, Stone D, et al. Socioeconomic inequalities in risk of congenital anomaly. *Arch Dis Child* 2000;82:349-52.

23. Kuppermann M, Gates E, Washington AE. Racial-ethnic differences in prenatal diagnostic test use and outcomes: preferences, socioeconomics, or patient knowledge? *Obstet Gynecol* 1996;87(5 Pt 1):675-82.

24. Rowe RE, Garcia J, Davidson LL. Social and ethnic inequalities in the offer and uptake of prenatal screening and diagnosis in the UK: a systematic review. *Public Health* 2004; 118:177-89.

25. Smith LK, Budd JL, Field DJ, et al. Socioeconomic inequalities in outcome of pregnancy and neonatal mortality associated with congenital anomalies: population based study. *BMJ* 2011;343: d4306.

26. Dolk H, Loane M, Garne E, et al. Trends and geographic inequalities in the prevalence of Down syndrome in Europe, 1980–1999. *Rev Epidemiol Sante Publique* 2005;53 No 2):2S87-95.

27. Khoshnood B, Pryde P, Wall S, et al. Ethnic differences in the impact of advanced maternal age on birth prevalence of Down syndrome. *Am J Public Health* 2000;90:1778-81.

28. Khoshnood B, De Vigan C, Vodovar V, et al. Advances in medical technology and creation of disparities: the case of Down syndrome. *Am J Public Health* 2006;96:2139-44.

29. Muggli EE, McCloskey D, Halliday JL. Health behaviour modelling for prenatal diagnosis in Australia: a geodographic framework for health service utilisation and policy development. *BMC Health Serv Res* 2006;6:109.

30. Pinto NM, Keenan HT, Minich LL, et al. Barriers to prenatal detection of congenital heart disease: a population-based study. *Ultrasound Obstet Gynecol* 2012;40:418-25.

31. Peiris V, Singh TP, Tworetzky W, et al. Association of socioeconomic position and medical insurance with fetal diagnosis of critical congenital heart disease. *Circ Cardiovasc Qual Outcomes* 2009;2:354-60.

32. Blondel B, Lelong N, Kermarrec M, et al., National Coordination Group of the National Perinatal Surveys. Trends in perinatal health in France from 1995 to 2010. Results from the French National Perinatal Surveys. *J Gynecol Obstet Biol Reprod (Paris)* 2012;41: e1-15.

33. Houyel L, Khoshnood B, Anderson RH, et al, EPICARD Study group. Population-based evaluation of a suggested anatomic and clinical classification of congenital heart defects based on the International Paediatric and Congenital Cardiac Code. *Orphanet J Rare Dis* 2011;6:64.

34. Franklin RC, Jacobs JP, Krogmann ON, et al. Nomenclature for congenital and paediatric cardiac disease: historical perspectives and The International Pediatric and Congenital Cardiac Code. *Cardiol Young* 2008;18(Suppl 2):70-80.

35. Garne E. Prenatal diagnosis of six major cardiac malformations in Europe—a population based study. *Acta Obstet Gynecol Scand* 2001;80:224-8.

36. Khoshnood B, Blondel B, De Vigan C, et al. Socioeconomic barriers to informed decisionmaking regarding maternal serum screening for Down syndrome: results of the French National Perinatal Survey of 1998. *Am J Public Health* 2004;94:484-91.

37. Khoshnood B, De Vigan C, Blondel B, et al. Long-term trends for socio-economic differences in prenatal diagnosis of Down syndrome: diffusion of services or persistence of disparities? *BJOG* 2008;115:1087-95.

38. Marteau TM. Prenatal testing: towards realistic expectations of patients, providers and policy makers. *Ultrasound Obstet Gynecol* 2002;19:5-6.

39. Browner CH, Preloran HM, Casado MC, et al. Genetic counseling gone awry: miscommunication between prenatal genetic service providers and Mexican-origin clients. *Soc Sci Med* 2003;56:1933-46.

40. Duncan GJ, Daly MC, McDonough P, et al. Optimal indicators of socioeconomic status for health research. *Am J Public Health* 2002;92:1151-7.

41. Jacobs JP, Mavroudis C, Jacobs ML, et al. Nomenclature and databases—the past, the present, and the future: a primer for the congenital heart surgeon. *Pediatr Cardiol* 2007;28:105-15.

42. Jacobs ML, Jacobs JP, Jenkins KJ, et al. Stratification of complexity: the Risk Adjustment for Congenital Heart Surgery-1 method and the Aristotle Complexity Score—past, present, and future. *Cardiol Young* 2008;18(Suppl 2):163-8.
BMJ Open

# Assessing sociodemographic differences (or lack thereof) in prenatal diagnosis of congenital heart defects: a population-based study

Babak Khoshnood, Nathalie Lelong, Thibaut Andrieu, Lucile Houyel, Damien Bonnet, Jean-Marie Jouannic and François Goffinet

BMJ Open 2016 6: doi: 10.1136/bmjopen-2015-009353

Updated information and services can be found at: http://bmjopen.bmj.com/content/6/3/e009353

These include:

**References**

This article cites 42 articles, 10 of which you can access for free at: http://bmjopen.bmj.com/content/6/3/e009353#BIBL

**Open Access**

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

**Email alerting service**

Receive free email alerts when new articles cite this article. Sign up in the box at the top right corner of the online article.

**Topic Collections**

Articles on similar topics can be found in the following collections

- Epidemiology (1503)

- Health services research (943)

- Obgyn (248)

- Public health (1527)

**Notes**

To request permissions go to: http://group.bmj.com/group/rights-licensing/permissions

To order reprints go to: http://journals.bmj.com/cgi/reprintform

To subscribe to BMJ go to: http://group.bmj.com/subscribe/