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What about the mothers? An analysis ofmaternal mortality and morbidity in perinatalhealth surveillance systems in EuropeM-H Bouvier-Colle,a AD Mohangoo,b M Gissler,c Z Novak-Antolic,d C Vutuc,e K Szamotulska,f

J Zeitlina for The Euro-Peristat Scientific Committee*a Institut National de la Sante et de la Recherche medicale-Unite 953 Recherche epidemiologique en sante perinatale et sante des femmes

et des enfants—INSERM, UMR S953 Epidemiological Research Unit on Perinatal Health and Women’s and Children’s Health, UPMC

University Paris, Paris, France b Netherlands Organization for Applied Scientific Research TNO, Leiden, the Netherlands c National Institute

for Health and Welfare, Helsinki, Finland and Nordic School of Public Health, Gothenburg, Sweden d Department of Obstetrics and

Gynaecology, Division of Perinatology, University Medical Centre, Ljubljana, Slovenia e Leiter der Abteilung fur Epidemiologie Zentrum fur

Public Health der Med. Univ. Wien, Austria f Department of Epidemiology National Research Institute of Mother and Child, Warsaw, Poland

Correspondence: Dr M-H Bouvier-Colle, Institut National de la Sante et de la Recherche medicale-Unite 953 recherche epidemiologique en

sante perinatale et sante des femmes—82, av Denfert-Rochereau, 75014 Paris, France. Email [email protected]

* Members of the Euro-Peristat Scientific Committee are in the Appendix.

Accepted 27 January 2012.

Objective To assess capacity to develop routine monitoring of

maternal health in the European Union using indicators of

maternal mortality and severe morbidity.

Design Analysis of aggregate data from routine statistical systems

compiled by the EURO-PERISTAT project and comparison with

data from national enquiries.

Setting Twenty-five countries in the European Union and Norway.

Population Women giving birth in participating countries in 2003

and 2004.

Methods Application of a common collection of data by selecting

specific International Classification of Disease codes from the

‘Pregnancy, childbirth and the puerperium’ chapter. External

validity was assessed by reviewing the results of national

confidential enquiries and linkage studies.

Main outcome measures Maternal mortality ratio, with

distribution of specific obstetric causes, and severe acute maternal

morbidity, which included: eclampsia, surgery and blood transfusion

for obstetric haemorrhage, and intensive-care unit admission.

Results In 22 countries that provided data, the maternal

mortality ratio was 6.3 per 100 000 live births overall and

ranged from 0 to 29.6. Under-ascertainment was evident from

comparisons with studies that use enhanced identification of

deaths. Furthermore, routine cause of death registration systems

in countries with specific systems for audit reported higher

maternal mortality ratio than those in countries without audits.

For severe acute maternal morbidity, 16 countries provided

data about at least one category of morbidity, and only three

provided data for all categories. Reported values ranged widely

(from 0.2 to 1.6 women with eclampsia per 1000 women

giving birth and from 0.2 to 1.0 hysterectomies per 1000

women).

Conclusions Currently available data on maternal mortality and

morbidity are insufficient for monitoring trends over time in

Europe and for comparison between countries. Confidential

enquiries into maternal deaths are recommended.

Keywords European Union, hospital data, maternal mortality

ratio, severe obstetric complications.

Please cite this paper as: Bouvier-Colle M, Mohangoo A, Gissler M, Novak-Antolic Z, Vutuc C, Szamotulska K, Zeitlin J for The Euro-Peristat Scientific Committee.

What about the mothers? An analysis of maternal mortality and morbidity in perinatal health surveillance systems in Europe. BJOG 2012;119:880–890.

Introduction

During the 1970s and the 1980s, maternal and child health

policies focused more attention on infants than on moth-

ers. For instance, antenatal care has focused more on the

prevention of health problems for the fetus or infant rather

than on the organisation of obstetric and intensive care for

the mothers in case of severe maternal complications. At

the end of the 1980s, maternal mortality was labelled ‘a

neglected tragedy’.1,2 In 1987, a plea for safe motherhood

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880 ª 2012 The Authors BJOG An International Journal of Obstetrics and Gynaecology ª 2012 RCOG

DOI: 10.1111/j.1471-0528.2012.03330.x

www.bjog.orgEpidemiology

worldwide was launched. This led to a greater international

focus on maternal health because of high maternal mortal-

ity ratios in low-income countries. In Europe, as in other

high-income countries, specific surveys were carried out on

maternal mortality and initiatives for severe maternal mor-

bidity were taken.3–7 An important question is therefore

the extent to which these initiatives have improved the

capacity to analyse and to develop public-health strategies

for maternal health in Europe.

Five million women give birth each year in the European

Union. Another million women have failed pregnancies

with first-trimester losses. Overall in the European Union,

between 335 and 1000 women are estimated to die during

or because of pregnancy, delivery or the puerperium.8 The

EURO-PERISTAT group, a European collaboration estab-

lished to develop an information system on perinatal health

in Europe, recommends the maternal mortality ratio

(MMR) and the causes of maternal death as two principal

indicators of maternal health.5 Maternal mortality is con-

sidered to be an important indicator of health system per-

formance4 even in high-income countries where maternal

deaths are very rare but are considered sentinel events that

raise questions about the effectiveness and quality of care.

Vital registration and healthcare information systems exist

in all member states, and provide an opportunity to pro-

duce direct estimates of MMR using a common classifica-

tion of causes of death.

In addition to maternal mortality, EURO-PERISTAT rec-

ommends an indicator of severe maternal morbidity. The

difficulties involved in establishing common definitions of

maternal morbidity have been apparent for some time. In

the 1990s, the European Concerted Action on Maternal

Mortality and Severe Morbidity (the MOMS study) with

collaborators from 15 countries studied three types of severe

maternal morbidity complications (severe postpartum

haemorrhage, eclampsia/pre-eclampsia and sepsis) for which

the participants drew up common definitions.6 Special epi-

demiological surveys were carried out in the participating

countries to estimate the prevalence of these maternal mor-

bidities. These showed wide differences between the morbid-

ity rates. The study concluded that these were probably the

result of differences in the data survey procedures (prospec-

tive or retrospective for example). After a review of the liter-

ature and based on studies performed in Europe, the

EURO-PERISTAT group proposed in 2004 a series of severe

maternal conditions linked to pregnancy and childbirth,

which might be generated using data from routine systems

(hospital discharge registers and medical birth registers).

This article reports on the results of data collection on

maternal health indicators (mortality and morbidity) in 25

European Union member states and Norway to produce

the European Perinatal Health Report. Our aim was to

analyse current capacity to monitor trends and differences

in maternal mortality and morbidity in Europe and to

compare the MMR with information from other sources—

notably confidential enquiries.

Methods

We used data from the EURO-PERISTAT project, the

methods for which are described below and elsewhere,8,9 as

well as data from published reports of national enquiries or

specific studies into maternal deaths.

Definitions

Maternal mortalityInternationally accepted definitions for indicators of mater-

nal mortality and obstetric causes of death have been pub-

lished by the World Health Organization.10 Maternal death

is defined as the death of a woman while pregnant or

within 42 days of the termination of pregnancy irrespective

of the duration and site of the pregnancy for any cause

related to or aggravated by the pregnancy or its manage-

ment, but not from accidental or incidental causes. Mater-

nal deaths are subdivided into direct and indirect obstetric

causes of death (Chapter O, digits from O 00 to O 99) of

the 10th revision of the International Classification of

Diseases (ICD-10), which defines the classification of pathol-

ogies related to pregnancy, childbirth and the puerperium.

Currently all national cause-of-death registries in the study

countries record deaths coded according to ICD-10.

For the EURO-PERISTAT project we compiled data

about all maternal deaths and deaths attributed to the main

causes: ectopic pregnancy or abortion, complications of

hypertension, antepartum and postpartum haemorrhage

(PPH), uterine rupture, amniotic fluid embolism or throm-

boembolism, sepsis or chorioamnionitis, other direct obstet-

ric causes, indirect obstetric causes and unknown causes.

These causes were then aggregated into nine major cate-

gories, haemorrhages and uterine ruptures, amniotic fluid

embolism, thromboembolism, complications of hyperten-

sion, ectopic pregnancies and abortions, anaesthetic compli-

cations, other direct obstetric causes, indirect causes, and

unknown causes.4

As a consequence of the very small number of deaths

each year in most countries, we requested data covering at

least 2 years (2003 and 2004). Small countries provided

data for longer periods to provide a more reliable estimate

for their MMR. For example, Luxembourg provided data

for 5 years. Two large countries, Germany and Italy, pro-

vided data for only 1 year.

The MMR is defined as the number of all maternal

deaths from direct and indirect obstetric causes per

100 000 live births. We did not calculate MMRs by cause

of death because of the small number of deaths.

Maternal health in European surveillance systems

ª 2012 The Authors BJOG An International Journal of Obstetrics and Gynaecology ª 2012 RCOG 881

We calculated the percentage of deaths in each group of

causes, as the number of the deaths reported (numerator)

by the total number of maternal deaths (denominator).

Severe acute maternal morbidityThe EURO-PERISTAT working group conducted an exten-

sive review of potential maternal morbidity indicators. We

identified four possible sources for morbidity data used in

the scientific literature: (i) hospital discharge registers and

databases, (ii) financial data about hospital care, (iii)

obstetric quality registers, and (iv) medical birth registers

and databases. Because the most frequently used sources of

data are hospital discharge registers and databases, we

selected indicators that could be generated using data usu-

ally included in these databases. Our hypothesis was that

all women with severe acute maternal morbidity (SAMM)

would receive hospital care and so be included in hospital

databases.

The EURO-PERISTAT maternal morbidity indicators

included both management-based criteria and clinical diag-

noses. The choice of indicators was agreed upon in a meet-

ing of the EURO-PERISTAT committee, based on results

from EURO-PERISTAT I5 and our literature review. Four

indicators, had been suggested in the first phase of the pro-

ject (eclampsia, surgery, blood transfusion, and intensive-

care unit admission). Embolisation was added as a fifth

indicator. Our initial intent was to present each indicator

separately and also to combine them in a composite indica-

tor of SAMM. Appendix S2 (see Supporting Information)

gives the exact definitions for each indicator. The indicators

were defined as the number of women experiencing the

condition or procedure as a rate (per 1000) of all women

giving birth to one or more live or stillborn babies.

Data collectionMembers of the EURO-PERISTAT Scientific Committee

were responsible for organising data collection in their

own country. They either compiled the data themselves

from data published by national organisations or provided

the names of people to whom the data collection instru-

ments should be sent. The aim of EURO-PERISTAT was

to gather population-based data at a national level. If

these were not available, regional data were accepted if

they covered a geographically defined population. Only

data from existing routine data sources—including vital

registration systems, hospital administrative data, systems

or regular surveys—were used. The Scientific Committee

member for each participating country was responsible for

selecting the most appropriate data source. Appendix S1

(see Supporting Information) gives the data source used

in each country.

Aggregated data were collected using an excel-based sys-

tem. We asked for data for 2004 or the latest available year

before 2004, except for maternal mortality for which data

for two or more years were requested. TNO Quality of Life

in the Netherlands was responsible for developing the data

collection instrument and overseeing the collection process.

The second source of data was publications of national

results from countries that studied maternal deaths using

enhanced systems of registration by confidential enquiries

into maternal deaths and/or data linkage. We drew on

published reports from Austria,11 Denmark,12 Finland,13

France,14 Italy (five regions),15 the Netherlands,16 Norway,17

Slovenia18 and the UK.19 These sources are listed in Appen-

dix S1 (see Supporting Information). We also included

comparison data from a recent international study using

routinely collected medical causes of death data, which were

corrected for under-reporting.20 Data from these studies

were used for external validation of national MMR. In

addition, for those countries that carry out routine surveil-

lance of maternal deaths using enhanced systems (Finland,

France, the Netherlands, Slovenia and the UK), we

compared national MMR with MMR from other countries

with similar infant mortality rates, but no enhanced system

for ascertaining maternal deaths.

Results

Maternal mortality ratiosAll countries contributed data on maternal deaths except

Cyprus, Ireland and Slovakia. Belgium, Denmark, Greece,

Norway, Portugal and Sweden provided only the total

number of deaths without information about their causes.

The total number of maternal deaths reported by country

and by year varied from 0 in Malta, in both years and in

Norway and Slovenia in 2004, to 55 in both France and

the UK in 2003.

The total number of deaths per country ranged from 0

to108; the total number of live births ranged from <8000

to over 1.5 million. The highest ratio was reported in Esto-

nia, with 29.6 per 100 000 live births and the lowest was 0

in Malta, as shown in Table 1. Austria, Belgium, France

and Hungary had rates around the EU average (of 6.2 per

100 000 live births). Sweden and Greece reported low ratios

of 2.0 per 100 000.

Causes of maternal deathsThe profile of causes varied substantially from country to

country (Table 1) because of differences in the proportions

of deaths attributed to unknown causes: seven countries did

not use this category at all, whereas in other countries many

deaths had no cause stated. This problem was greatest in

the Netherlands and in Germany where, respectively, 19

and 47% had no reported cause. Nevertheless, the general

European profile of stated direct obstetric causes of death

shows that all obstetric haemorrhages, including a majority

Bouvier-Colle et al.


of PPH by atony, accounted for the highest proportion

of maternal deaths in participating countries (13%). In

countries that reported it as a direct cause of maternal

death, the proportion of haemorrhages ranged from 7% in

Germany to 67% in Slovenia. Three other direct causes each

accounted for around 9–11% of maternal deaths: thrombo-

embolisms (10% in the European Union, ranging from 3%

in Poland to 33% in Slovenia), complications of hyperten-

sion (9% in the European Union, ranging from 2% in Ger-

many to 25% in Spain), and amniotic fluid embolism (11%

in the European Union, ranging from 5% in Germany to

20% in Latvia and Estonia).

In nine countries that provided data to the EURO-PERI-

STAT project, we were able to check the completeness for

routinely collected data about maternal deaths by compar-

ing ratios with other published studies on maternal deaths:

in Austria, Denmark, Finland, France, Italy, the Nether-

lands, Norway, Slovenia and the UK. Table 2 shows that

Table 1. Live births, maternal deaths, maternal mortality ratios, repartition (%) of the maternal deaths according to the obstetric causes, by

country in 2003/04

Countries* Live births (n) Maternal

deaths (n)

MMR per 100 000

live births

Causes of maternal deaths (%)**

H AFE OTE CHT OD AI UK

Austria1 155 912 10 6.4 0 10 10 20 10 50 0

Belgium2 156 167 7 4.5

Cyprus No data

Czech Republic 191 349 19 9.9 11 16 21 0 26 21 5

Denmark2 129 466 12 9.3

Estonia3 27 028 8 29.6 0 20 0 20 60 0 0

Finland 114 018 9 7.9 11 11 0 11 44 22 0

France 1 529 280 107 7.0 18 14 14 14 28 8 4

Germany4 1 320 820 67 5.1 7 5 7 2 16 16 473

Greece5,2 104 355 2 1.9

Hungary 190 274 14 7.4 14 0 14 0 36 29 7

Ireland No data

Italy4,6 539 066 17 3.2 18 6 6 6 53 6 63

Latvia 41 340 5 12.1 0 20 20 0 0 60 0

Lithuania 61 017 6 9.8 0 0 17 17 67 0 0

Luxembourg7 27 252 2 7.3 0 0 0 0 100 0 0

Malta 7923 0 0.0

The Netherlands 362 012 32 8.8 9 0 13 13 13 34 19

Norway2 113 409 4 3.5

Poland 707 203 31 4.4 39 13 3 6 39 0 0

Portugal2 221 945 17 7.7

Slovakia No data

Slovenia7 34 907 4 11.5 50 0 25 0 0 25 0

Spain 896 472 41 4.6 0 0 0 25 75 0 0

Sweden2 200 316 4 2.0

United Kingdom 1 411 545 108 7.7 6 14 8 9 41 22 0

All countries 8 308 853 519 6.2 13 11 10 9 32 17 8

Countries with <10% of

unknown causes

6 626 021 420 6.3

AFE, amniotic fluid embolism; AI, all indirect; CHT, complications of hypertension; H, obstetric haemorrhage; OD, other direct (other direct obstet-

ric causes: chorioamnionitis/sepsis, abortion/ectopic pregnancy; anaesthetic; uterine rupture and others); OTE, Other thromboembolisms; UK,

unknown.

*:1In Austria indirect causes of maternal death are registered since 2004. 2Belgium, Denmark, Greece, Norway, Portugal and Sweden provided no

data on maternal mortality by cause of death. 3Estonia provided data for the years 2004 and 2005, and Slovenia provided data for the years

2001 and 2002. 4Germany and Italy provided data on maternal mortality by cause of death for 1 year only, respectively 2004 and 2002. 5Greece

provided data for 1 year, 2003. 6Italy provided data on maternal mortality by cause of death based on ICD-9 codes. 7Luxembourg provided data

on maternal death for the years 2000–2004 and Slovenia for the years 2001 and 2002.

**We are very concerned by the fact that calculating percentages with so small numbers sometimes is not pertinent, but we need to have the

same presentation for all the members of the EU.



the official MMRs under-ascertained maternal mortality in

all the European countries where it was possible to make

comparisons. For Norway and Denmark, the confidential

enquiries were performed at earlier dates and cannot be

compared with the EURO-PERISTAT data. Slovenia pub-

lished a first report on its systematic audit from national

registries resulting in an MMR of 9.8 per 100 000 for the

period 1985–94. This is equal to the rate included in the

EURO-PERISTAT report, but covers a longer period. The

under-ascertainment was generally between 20 and 50%.

Often, underestimation was higher in countries with a

lower official rate. We also compared the official MMRs in

countries that routinely monitor maternal deaths using

audits or linkages or confidential enquiries (Finland,

France, the Netherlands, Slovenia and the UK) with the

official MMR in countries that do not, but that have a sim-

ilar level of infant mortality (Austria, Belgium, Czech

Republic, Denmark, Germany, Italy, Luxembourg, Poland,

Portugal, Spain, Sweden). In all five countries with specific

audits, linkage or enquiries, MMRs were at least seven per

100 000 live births, whereas seven of the 11 other countries

(63%), had MMRs <7.

Maternal morbiditySixteen member states provided data for at least one of the

indicators of SAMM but only three provided data about all

Table 2. Maternal mortality data according to different sources, numbers, ratios per 100 000 live births and percentage of underestimation, in

France, Finland, Italy, Netherlands and UK around 2000–04

Countries

Years

(a) Confidential

enquiries n

maternal deaths

(b) Civil

registration

causes of death

(c) Under-estimation*

(%)

MMRs according to different sources

Confidential

enquiries

Vital data

(last period)

Hogan**

estimates 2000

Austria

1980–98 191 119 38.0 NA NA 5 (4–7)

2003/04*** 10 6.4

Denmark

1985–94 60 9.8 7 (5–9)

2003/04 12 9.3

Finland

1999 6 3 50.0 5.3 2.6 7 (5–9)

2003/04 9 7.9

France

1999 58 47 19.0 NA 7.4 11 (10–13)

2001–06 463 384 17.1 9.6 8.0

2003/04 107 7.0

Italy

2000–07 118 NA 74.6 11.8 NA 5 (4–6)

2003/04 17 3.2

The Netherlands

1993–2005 309 208 32.7 12.1 8.1 8 (10–11)

2003/04 32 8.8

Norway

1976–95 61**** 5.5** 7 (5–10)

2003/04 4 3.5

Slovenia

2003–05 8***** 1 87.5 9.4 1.9 21 (15–29)

2003/04 4 11.5

United Kingdom

2000–02 261 136 47.9 13.1 6.8

2003–05 295 149 49.5 13.9 7.0 8 (7–10)

2003/04 108 7.7

Sources, EURO-PERISTAT, Confidential enquiries and specific surveys.

*Underestimation : c = (a) ) (b)/(a) · 100, except for Austria.

**Hogan estimations are based on modelling of vital data.

***All 2003/04 data are taken from EURO-PERISTAT.

****Norway recorded direct obstetric causes of deaths only.

*****Slovenia among the eight deaths, three were late maternal deaths (‡42 days).



the categories, including admission into intensive-care units

(Table 3).

Hysterectomy for PPH and eclampsia were the two com-

plications for which data were most often available. There

was a five-fold country difference in the estimates of

incidence, but the range was moderate at 0.2–1.0 per 1000

women giving birth, as was the range for eclampsia:

0.2–1.6 per 1000. In contrast, data on intensive-care unit

admission were not generally available and the between-

country differences were large (six-fold); There were very

wide variations in blood transfusion data, most probably

because of differences in inclusion criteria. Data on emboli-

sation of uterine arteries were available for only seven

countries and the rates varied between 0.0 and 0.3 per

1000.

Discussion

This attempt to gather data on SAMM and maternal mor-

tality at a European level using routine national systems

show that currently available data are insufficient. Fortu-

nately, some countries have data from enhanced systems

for identification of maternal death and these make it pos-

sible to quantify the shortfalls in data from national statis-

tical offices. This is a crucial issue because the absence of

good data on maternal mortality and morbidity under-

mines national and European capacity to monitor maternal

health in Europe, and to permit comparisons between

countries or surveillance of trends over time. Our results

suggest that calls for a greater focus on mothers are still

highly relevant for European countries and may also be for

Table 3. Severe maternal morbidity rates per 1000 women by pathologies or interventions, according to the countries

Countries No. of

women

Eclampsia ICU

admission

Blood transfusion

whatever the

number of units*

Hysterectomy Embolisation

Austria**

Belgium Flanders 59 956 NA NA 11.5 NA NA

Cyprus**

Czech Republic 96 771 0.2 NA NA 0.8 NA

Denmark 63 781 0.3 NA 11.0 0.3 0.0

Estonia 13 879 0.6 NA NA 0.9 NA

Finland 56 878 0.2 NA 0.1 0.2 0.2

France 774 870 1.1 0.5 2.1 0.3 0.3

Germany–Bavaria 105 490 0.7 3.1 10.7 1.0 0.0

Greece

Hungary 93 913 0.5 NA NA 1.0 0.0

Ireland**

Italy 534 568 1.6 NA 4.6 0.9 0.0

Latvia 20 256 0.4 NA 0.8 NA

Lithuania**

Luxembourg

Malta 3838 1.3 NA 5.2 0.5 NA

The Netherlands 187 910 0.7 2.2 6.4 0.3 0.3

Norway**

Poland 213 190 0.2 NA NA NA NA

Portugal**

Scotland only 53 342 0.6 NA NA 0.2 NA

Slovakia**

Slovenia 17 629 1.1 NA 10.6 0.6 NA

Spain–Valencia 38 389 0.3 NA 6.5 0.3 NA

Sweden**

United Kingdom

(Wales and Scotland)

82 911 0.67*** NA NA 0.13*** NA

*The number of transfusion units provided by the countries were so heterogeneous (three units or more, five units or more, other amount, no

units specified) that we summarised the data in only one category.

**No data provided; Norway did not participate in the data collection.

***The rates were estimated from two nations only, Wales and Scotland.



other high-income countries, as recently affirmed in the

USA.7

For the measure of maternal mortality, there are two

problems, completeness of ascertainment and quality of

coding. The comparison of data from routine cause of

death certificates with enhanced systems for studying

maternal deaths identified substantial underestimation of

between 20 and 50% in MMRs. Furthermore, countries

with continuous audits had higher reported MMR than

countries that have not implemented these initiatives, prob-

ably because of increased awareness of maternal deaths,

which improves the routine reporting of these deaths.

From this perspective, the very low mortality ratios in

some countries are highly suggestive of a failure to ade-

quately count maternal deaths. It would be interesting to

study why these systems are missing maternal deaths and

in particular, whether this is associated with the complete-

ness of ascertainment or the procedures for coding. The

absence of deaths from indirect obstetric causes in some

countries, for example Poland or Spain, might be the result

of under-ascertainment, or coding procedures, or both. A

further issue that affects completeness of ascertainment and

comparability is whether migrant or foreign citizens are

included in official mortality statistics: for example, in

France they are, but in Austria they are not. Migrant

women have been found to have higher MMR than non-

migrant women in the countries to which they migrate.21,22

These routinely reported data are those regularly used at

the international level instead of the results from enhanced

systems of maternal death recording. The recent paper by

Hogan et al.,20 an attempt at the international level to rec-

tify the well-known under-ascertainment of MMRs by

using models based on vital statistics data in industrialised

countries, was based on national statistical office data. Con-

sequently, their estimates were consistently below the true

values in the countries where alternative data sources were

available. Nevertheless, in other countries, such as Greece,

Malta and Sweden, their corrections led to values that were

two or three times higher than ratios reported in national

statistics.

There are validated methods for improving statistics on

maternal mortality, including setting up systems of enqui-

ries. Adding a pregnancy check box to the national medical

death certificate is a first step, as shown recently in a study

from the USA,23 but this is not sufficient, as witnessed by

continued under-reporting in countries, such as France

since 2000 and others where pregnancy check boxes have

been implemented. To insure the completeness of registra-

tion, more comprehensive solutions involve data linkage of

cause of death registers with medical birth registers or birth

registration records (Denmark, England and Wales, Fin-

land, Norway and Slovenia), abortion records (Finland)

and hospital records (Denmark and Finland). National sys-

tems of confidential enquiries into maternal deaths exist in

France, the Netherlands, Slovenia and the UK and these

also rely in part on linkage systems for identifying

cases.14,16,18,19 Implementing data linkage and especially

confidential enquiries in all European countries would sub-

stantially improve the ascertainment of maternal death.

There are also major differences between countries in

reporting causes of death. This problem is more difficult to

resolve because of the small number of deaths and the

complexity of the multiple complications that lead to a

maternal death. Many women die in an intensive-care unit,

often days or weeks after delivery, and the certifying physi-

cian may not always be aware of the details of the preg-

nancy. A previous European study showed that the

differences in coding the underlying cause of death by the

national statistical offices can lead to underestimation or

overestimation of the MMR compared with standardised

coding by a European panel of experts;24 these discrepan-

cies were confirmed in a subsequent study comparing

Europe with the USA.13,25

Another important issue that limits the use of maternal

mortality indicators for surveillance of maternal health in

pregnancy is the small number of deaths. For example, the

relatively high MMR for Estonia is based on only eight

maternal deaths; On the other hand, one maternal death in

Malta would have increased its MMR from 0.0 to 12.6 per

100 000. Given this degree of variation, we would recom-

mend that future international data collection and report-

ing be based on averages over 5 years instead of 2 years to

reduce the effects of variations in the MMRs caused by the

small number of maternal deaths, in medium-sized as well

as small countries. This issue highlights the importance of

developing valid indicators of severe maternal morbidity

which have a higher incidence and therefore have a greater

potential to measure trends in maternal health over time.

Our results show, however, that data on maternal mor-

bidity are scarce and their quality is inadequate. We had

expected that the incidence of embolism, eclampsia, blood

transfusion and surgery for PPH would be readily derived

from the data files compiled at hospital level. We know

that the majority of the European countries have hospital

discharge registers or databases that are used to monitor

hospital activity and to allocate resources to hospitals. As

the morbidity outcomes and procedures we chose take

place in hospital at or shortly after delivery, the cases

should be included in these systems. Many countries were

not able to report the number of women; these data may

exist, but they were not currently available for this purpose.

The EURO-PERISTAT project compiled data that are cur-

rently used to evaluate perinatal health outcomes.

A future line of research would be to request data on

hospital stays associated with childbirth from hospital

discharge databases and validate the accuracy of reporting



of some specific and crucial diagnoses for which there are

commonly accepted definitions, including eclampsia,

thromboembolism and sepsis. Results from new national

and international initiatives should be taken into consider-

ation when refining these definitions of severe maternal

morbidity.26–28

Retrospective studies have been conducted in the USA,

Canada and Australia on hospital databases or discharge

summaries, according to a definition of SAMM that com-

bines codes of procedures and diagnoses and that therefore

depends on the available information.29–31 This type of

study has the advantage of feasibility, immediately available

data and a large sample size. Limitations include use of

codes from the ICD of the World Health Organization to

identify SAMM events; although the ICD has a section on

direct and indirect maternal complications, it does not

define their severity. There is also significant variation in

the reporting of diagnoses that are not the main diagnoses.

Moreover, hospital data are not able to distinguish morbid-

ity associated with pregnancy (temporal association) from

maternal morbidity directly caused by pregnancy (temporal

and causal association). In some systems also there is a risk

of counting the same woman in the same pregnancy several

times unless there is a unique identifier and admissions are

linked. The validity and accuracy of the reported conditions

in the hospital data may be not checked32 in a detailed

manner because of the large numbers of records involved.

Using hospital discharge data would also make it possi-

ble to record admission to intensive-care units, to which

we are strongly favourable. Even though intensive-care

admission depends in part on the way health care is organ-

ised, it can mark a critical event, a so called ‘near miss’.33

This identifies a situation in which resuscitation by an

intensive-care specialist was required, as confirmed by

recent studies.34,35 Since 2006, the intensive-care national

audit and research centre (ICNARC) has analysed admis-

sions of women of reproductive age among the admissions

to adult general intensive-care units, in England and Wales

and Northern Ireland.36 The LEMMoN Study in the Neth-

erlands included a chapter about obstetric intensive-care

unit admissions.28 In France, these admissions are well

recorded in hospital discharge data.32

Epidemiological studies focusing on specific aspects of

SAMM are more informative and provide an essential com-

plement to routine reporting and some are already under

way. They are usually population-based surveys giving bet-

ter estimates of the severe maternal morbidity rates. The

Scottish confidential audit of severe maternal morbidity is

the oldest survey since 200326 and allows calculation of

SAMM indicators annually. The United Kingdom Obstetri-

cal Surveillance System (UKOSS) covering the UK36 is an

ongoing system that focuses in turn on specific types of

rare severe maternal morbidity. Other studies, such as the

LEMMoN28 study in the Netherlands, the recently started

Nordic project (NOSS) or the French Severe maternal

morbidity: measurement, determinants and quality of

care project (EPIMOMS), are prospective but transversal

approaches limited to a specific time period. Neither the

UK study nor the others are designed to enable routine fol-

low up over time.

Conclusion and recommendations

Despite the existence of longstanding cause of death regis-

tration systems and hospital morbidity registers in Euro-

pean countries, currently available data for surveillance of

maternal morbidity and mortality associated with preg-

nancy, childbirth and the postpartum period are inade-

quate. All countries should be encouraged to use validated

methods to improve the ascertainment of maternal deaths

and in particular confidential enquiries and data linkage.

Better use of data available in hospital discharge databases

should make it possible to identify indicators of morbidity

that can be validly compared.

Disclosure of interestsThe authors have no competing interests to declare.

Contribution to authorshipMHBC and JZ conceived and designed the study, wrote the

first draft of the paper and revised the second version;

AMM, MG, ZNA, CV and KS provided input on the analy-

sis and revised the initial draft of the manuscript; The

EURO-PERSTAT scientific committee participated in the

interpretation of the results and commented on the paper’s

second and final drafts.

Details of ethics approvalNo specific ethics approval for this study was required

because outcome data were routinely collected at the aggre-

gate level by countries.

FundingThe EURO-PERISTAT project received funding from the

European Commission of, Directorate General for Health

and Consumers Protection and Public Health Programme

(no. 20101301). The funders had no role in the collection

of the data, the writing of the manuscript or the decision

to submit for publication.

AcknowledgementsWe acknowledge the following contributors to the EURO-

PERISTAT perinatal health report: Austria Christian Vutuc,

Abteilung fur Epidemiologie Zentrum fur Public Health der

Med. Univ. Wien; Jeannette Klimont, Statistics Austria;

Belgium Sophie Alexander, Wei-Hong Zhang, Universite Libre



de Bruxelles, School of Public,Health, Reproductive Health

Unit; Guy Martens SPE (Study Centre for Perinatal Epidemiol-

ogy), Edwige Haelterman, Myriam De Spiegelaere Brussels

Health and Social Observatory; Cyprus Pavlos Pavlou, Maria

Athanasiadou Ministry of Health, Health Monitoring Unit;

Andreas Hadjidemetriou, Christina Karaoli, Neonatal Intensive

Care Unit, Makarios III Hospital; Czech Republic Petr Velebil,

Institute for the Care of Mother and Child, Vit Unzeitig,

Department of Obstetrics & Gynecology, Masaryk University

Brno Denmark Jens Langhoff Roos, Obstetrics Clinic, Rigshos-

pitalet, Copenhagen University; Steen Rasmussen, Sundheds-

styrelsen National Board of Health; Estonia Gleb Denissov,

Statistics Estonia, Luule Sakkeus, Kati Karelson, Mare Ruuge,

National Institute for Health Development, Department of

Health Statistics, Avi Tellmann, Estonian Medical Birth Regis-

try; Finland Mika Gissler, National Research and Development

Centre for Welfare and Health (STAKES); Anneli Pouta

National Public Health Institute (KTL), Department of Child

and Adolescent Health; France Beatrice Blondel, Marie-Helene

Bouvier-Colle, Gerard Breart, Jennifer Zeitlin, Meagan Zim-

beck INSERM U953; Christine Cans, SCPE Service d’Informa-

tion et d’Informatique Medicale (SIIM) Germany Nicholas

Lack, Bavarian Working Group for Quality Assurance, Klaus

Doebler, Federal Quality Assurance Office BQS; Greece Aris

Antlaklis, Peter Drakis, Athens University Department of

Obstetrics & Gynecology, Division of Maternal & Fetal Medi-

cine; Hungary Istvan Berbik, Vaszary Kolos Teaching Hospital,

Department of Obstetrics & Gynecology, Istvan Szabo, Depart-

ment of Obstetric and Gynaecology, Medical Faculty, Scientific

University of Pecs Ireland Sheelagh Bonham, Jacqueline

O’Reilly, Economic and Social Research Institute (ESRI), Italy

Marina Cuttini, Pediatric Hospital of Baby Jesus, Unit of

Epidemiology; Sabrina Prati, Cinzia Castagnaro, Silvia Bruzz-

one, Marzia Loghi Istituto Nazionale di Statistica, ISTAT;

Latvia Jautrite Karaskevica, Irisa Zile, Health Statistics and

Medical Technologies State Agency; Ilze Kreicberga, Riga

Maternity Hospital; Lithuania Aldona Gaizauskiene, Kotryna

Paulauskiene, Lithuanian Health Information Centre; Luxem-

bourg Yolande Wagener, Ministere de la Sante, Direction de la

Sante, Division de la Medecine Preventive et Sociale; Malta

Miriam Gatt, Kathleen England, Department of Health Infor-

mation and Research; Raymond Galea Department of Obstet-

rics & Gynecology, University of Malta; the Netherlands

Simone Buitendijk, Ashna D Mohangoo, Sabine Anthony, Ab

Rijpstra TNO Quality of Life, Prevention and Care, Section

Reproduction and Perinatology, Leiden; Jan Nijhuis, Maas-

tricht University Medical Centre, Department of Obstetrics &

Gynecology; Chantal Hukkelhoven, The Netherlands Perinatal

Registry; Norway Lorentz Irgens, Kari Klungsoyr Melve,

University of Bergen, Medical Birth Registry of Norway; Jon

Gunnar Tufta Medical Birth Registry of Norway; Poland Kat-

arzyna Szamotulska, Department of Epidemiology, National

Research Institute of Mother and Child; Bogdan Chazan, Holy

Family Hospital; Portugal Henrique Barros, Sofia Correia Uni-

versity of Porto Medical School, Department of Hygiene and

Epidemiology; Slovakia Jan Cap, Jarmila Hajnaliova, National

Health Information Centre; Slovenia Ziva Novak-Antolic, Ivan

Verdenik, University Medical Centre Division for Perinatology,

Polonca Truden-Dobrin, Centre for Health and Health Care

Research, Institute of Public Health of the Republic of Slove-

nia, Spain Francisco Bolumar, Universidad de Alcala Facultad

de Medecina; Ramon Prats, Department de Salut Direccio

General Salut Publica, Carmen Barona Perinatal Health Unit

Public Health Board, Isabel Rıo, CIBER Epidemiologıa y Salud

Publica (CIBERESP); Sweden Gunilla Lindmark, IMCH, Aka-

demiska sjukhuset; Milla Bennis, National Board of Health

and Welfare; United Kingdom Gwyneth Lewis, Department of

Health, Alison Macfarlane, Nick Drey, Department of Mid-

wifery, City University; Angela Bell,Health Promotion Agency

for Northern Ireland; Jim Chalmers, Etta Shanks, Information

Services Division, NHS National Services Scotland; Di Good-

win, Vital Statistics Output Branch, Office for National Statis-

tics; Clara Mmata, Information Centre for Health and Social

Care, England; Kath Moser, Office for National Statistics;

Gwyneth Thomas Health Statistics and Analysis Unit, Statisti-

cal Directorate, Welsh Assembly Government.

Supporting Information

Additional Supporting Information may be found in the

online version of this article:

Appendix S1. Data sources used for maternal mortality

and morbidity statistics in the EURO-PERISTAT project.

Appendix S2. Definitions used for maternal morbidity

indicators.

Please note: Wiley-Blackwell are not responsible for the

content or functionality of any supporting information

supplied by the authors. Any queries (other than missing

material) should be directed to the corresponding author.

Keypoints

• The first comparison of official data compiled on mater-

nal health data in the European countries, with data

from enhanced systems of collecting maternal deaths.

• The majority of maternal mortality ratios extracted from

vital data registration are almost certainly underesti-

mated. Confidential enquiries into maternal deaths

should be implemented to improve surveillance.

• There are potential sources of information in hospital

databases on maternal morbidity requiring further study. j

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Appendix

The Euro-Peristat Scientific CommitteeChristian Vutuc (Austria), Sophie Alexander (Belgium), Pavlos

Pavlou (Cyprus), Petr Velebil (Czech Republic), Jens Langhoff

Roos (Denmark), Luule Sakkeus (Estonia), Mika Gissler (Fin-

land), Beatrice Blondel (France), Nicholas Lack (Germany),

Aris Antlaklis (Greece), Istvan Berbik (Hungary), Sheelagh

Bonham (Ireland), Marina Cuttini (Italy), Jautrite Karaskevica

(Latvia), Jone Jaselioniene (Lithuania), Yolande Wagener (Lux-

embourg), Miriam Gatt (Malta), Jan Nijhuis (The Nether-

lands), Lorentz Irgens (Norway), Katarzyna Szamotulska

(Poland), Henrique Barros (Portugal), Maria Chmelova

(Slovakia), Ziva Novak-Antolic (Slovenia), Francisco Bolumar

(Spain), Gunilla Lindmark (Sweden), Alison Macfarlane (Uni-

ted Kingdom).



Commentary on ‘What about the mothers? An analysis of maternalmortality and morbidity in perinatal health surveillance systems in

Europe’

This important paper from EURO-PERISTAT concludes correctly that routine registration data on maternal mortality

are insufficient to monitor trends over time and for comparing countries. Unfortunately the World Health Organiza-

tion relies solely on such data when producing maternal mortality estimates worldwide (Hogan et al., Lancet

2010;375:1609–23). More sophisticated systems such as confidential enquiries reveal substantial under-reporting, with

rates of almost 20% in France, 33% in the Netherlands, 38% in Austria, almost 50% in the UK, 50% in Poland, 75%

in Italy and 87% in Slovenia. This makes routinely collected vital statistics less useful and comparison between coun-

tries meaningless. Sweden will soon publish data from active surveillance, which will illuminate the extremely low offi-

cial maternal mortality ratio in that country.

Under-reporting has several causes, including incomplete ascertainment or misclassifications of maternal deaths as

non-maternal. When immigrant deaths are not included (as in Austria) or indirect maternal deaths are left out (as in

Norway), comparison between different countries becomes meaningless, especially as we know that immigrants are

often disproportionally represented and indirect deaths comprise a high proportion. In this study, five countries

reported zero indirect deaths. That may be understandable when the total numbers are low (Luxembourg, four;

Lithuania, six and Estonia, eight). It is, however, likely that Spain with 41 and Poland with 31 deaths, did not (like

Norway) report their indirect deaths.

Substantial differences within countries exist, with large variations between regions, cities, provinces and even

neighbourhoods (Saucedo et al., BJOG 2012;119:573–81; de Graaf et al., BJOG 2012;119:582–8). Higher maternal mor-

tality ratios in deprived areas (as detected by postal codes) point to the socio-economic and multi-ethnic determi-

nants of health, indicating that serious health inequalities still exist within our welfare states.

The relatively short period of data collection leading to few maternal deaths being recorded, e.g. Luxembourg

(n = 2 for 2000–04), Slovenia, Sweden and Norway (n = 4), Greece (n = 2) is a limitation.

Causes of maternal deaths vary substantially between countries, although obstetric haemorrhage remains the most fre-

quent cause. Deaths from haemorrhage range between 0 and 50% of all maternal deaths, and those from amniotic fluid

embolism are between 0 and 20%. Amniotic fluid embolism often involves serious haemorrhage, so classifications are

bound to overlap. As maternal deaths tend to become litigation cases, clinicians sometimes may prefer the ‘less avoid-

able’ cause of amniotic fluid embolism to obstetric haemorrhage. Unknown causes differed between 0 and 47% of the

deaths. In ten of the 16 countries no maternal deaths of ‘unknown origin’ were reported. This gives rise to doubts about

the figures, because documentation is often a problem, even in a confidential enquiry. Moreover, maternal deaths are

often complex. Recently, when 25 experts from the International Network of Obstetric Survey Systems (INOSS) at their

second annual INOSS meeting in Leiden tried to classify cases of maternal mortality from France and the Netherlands,

consensus could not easily be reached, and an underlying cause could not always be assigned. Such differences can only

be resolved by in-depth audit of every case of maternal death, with prospective data collection. This can be achieved

when countries have national enquiries in place, and that is the most important recommendation from this study. j

J van RoosmalenDepartment of Obstetrics, Leiden University Medical Centre, the Netherlands

Bouvier-Colle

890 ª 2012 The Author BJOG An International Journal of Obstetrics and Gynaecology ª 2012 RCOG

European Journal of Public Health, 1–7

� The Author 2013. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

doi:10.1093/eurpub/cks176

. . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .

Reporting of perinatal health indicators forinternational comparisons—enhancing theappearance of geographical plots

Nicholas Lack1, Beatrice Blondel2, Ashna D. Mohangoo3, Luule Sakkeus4, Christine Cans5,Marie H. Bouvier-Colle2, Alison Macfarlane6, Jennifer Zeitlin2

1 BAQ, Bavarian Institute for Quality Assurance, Department of Methods and Perinatology, Munich, Germany2 Epidemiological Research Unit on Perinatal and Women’s and Children’s Health, INSERM UMRS 953, Universite Pierre-

et-Marie Curie Paris6, Paris, France3 TNO Behavioral and Societal Sciences, Department Child Health, Leiden, The Netherlands4 Estonian Institute for Population Studies, Tallinn University, Tallinn, Estonia5 Laboratoire TIMC-IMAG, ThEMAS, Universite Grenoble 1, CHU, Grenoble, France6 Maternal and Child Health Research Centre, City University London, UK

Correspondence: Nicholas Lack, BAQ, Westenriederstrasse 19, 80331 Munich, Germany, tel: 0049 89 211 590 0,fax: 0049 89 211 590 20, e-mail: [email protected]

Background: Tabulating annual national health indicators sorted by outcome may be misleading for two reasons.The implied rank order is largely a result of heterogeneous population sizes. Distinctions between geographicallyadjacent regions are not visible. Methods: Regional data are plotted in a geographical map shaded in terms ofpercentiles of the indicator value. Degree of departure is determined relative to control limits of a correspondingfunnel plot. Five methods for displaying outcome and degree of departure from a reference level are proposed forfour indicators selected from the 2004 European Perinatal Health Report. Results: Spread of indicator values wasgenerally largest for small population sizes, with results for large populations lying mostly close to respectiveEuropean medians. The high neonatal mortality rate for Poland (4.9 per 1000); high low-birthweight rates forEngland and Wales (7.8%), Germany (7.3%) and Estonia (4.5%); and high caesarean section rates for Italy (37.8%),Poland (26.3%), Portugal (33.1%) and Germany (27.3%) were statistically significant exceptions to this pattern.Estonia also showed an extreme result for maternal mortality (29.6 per 100 000). Conclusion: Extreme deviationsfrom EU reference levels are either correlated with small population sizes or may be interpreted in terms ofdiffering medical practices, as in the case of caesarean section rate. EURO-PERISTAT has now decided to use5-year averages for maternal mortality to reduce the variance in outcome. Use of two colours in three intensitiesand solid fill versus crosshatching is best suited to display rate and significance of difference.. . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .

Introduction

The chief objective of any collection of indicators of health for anumber of countries will be to highlight and interpret differences

found between countries, with the ultimate aim of suggestingpossible causes associated with risk factors or health care. Currentapplications of international comparisons of health and health careare published on the websites of EUROSTAT1 and WHO2 and inthe European Community Atlas of Avoidable Death.3 In addition,a wide range of commercially available databases and programs canbe found on the Internet.

In the perinatal field, each country collects data used to deriveindicators through civil registration, hospital discharge systems orspecialist registers. The indicators include mothers’ and children’shealth, clinical practices and maternal risk factors. Thus, in theEuropean Union, all countries produce sufficient data to constructat least 10 core indicators, to describe their situation.4 Comparisonof these indicators across countries is an essential tool for definingnational policy priorities, or generating hypotheses on factors thatmight explain differences such as risk factors or health policies. Toachieve this aim, it is essential to display data in a way that is sim-ultaneously accurate as well as informative without being toocumbersome and voluminous to digest.

The recent claim that the validity of international comparisons iscompromised by variations in the registration of births at theborderline of viability5 may hold for some publications, althoughnot so for the European Perinatal Health Report,6 as care was takento ensure comparability by appropriate censoring of indicators at the

lower end of the gestational age distribution.7 After due consider-ation and suitable adjustment for methodological difficulties8

and availability and comparability issues,9 however, there remainquestions of presentation of these data, e.g. how to order a tableor what to display on a geographical map.

A tabular presentation is attractive because it can provide a largeamount of numerical information such as rates for each country orpopulation size and because of its naturally inherent ranking option.An alphabetical ordering such as adopted in the European PerinatalHealth Report6 may be considered objective, as reporting sequence issolely a function of lexical ordering. However, this objectivity is atthe expense of any form of structured data display that might helpinterpretation. On the other hand, the ranks of countries in termsof observed rates will be instable10,11 because absolute differencesbetween observed rates are frequently small. An instable rankingmay lead to misinterpretation of observed raw outcome rates.

Longitudinal variation is best displayed graphically. Althoughgraphs of temporal trends can reveal valuable additional informa-tion, we cannot always expect data to be available for long timeseries. This is so especially for the more sophisticated perinatalindicators. These may not be available for all countries on a yearlybasis.

Funnel plots of rates against population size, as pioneered byMacfarlane12 and later adopted for the National Health Servicemore generally by Spiegelhalter,11 are increasingly used in per-formance monitoring. A major advantage is the inclusion of aformal assessment of degree of departure from specified referencelevels with simultaneous display of outcome–volume relationships.

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Funnel plots were recently proposed for monitoring and assessingimprovements13,14 in surgical interventions in Germany.

The plotting of performance indicators for countries in a geo-graphical context is possible because of the availability of graphicalinformation software. This encourages and facilitates regional inter-pretation. Correlations between rates in adjacent states are immedi-ately apparent3,15. Holland3 suggests a number of steps that might betaken in studying geographical variation. One is to see how thesedifferences change over time; another is to map individual deathsand to investigate clustering.

In this article, we take these ideas one step further and suggestmoving the information contained in funnel plots into choroplethmaps to improve their legibility and enhance their interpretability.The proposed method is applied to perinatal health indicators fromthe European Perinatal Health Report.7

Methods

EURO-PERISTAT data

The EURO-PERISTAT6 data are available for 25 European Union(EU) member states plus Norway. Data to construct a number ofindicators were compiled for the year 2004, in most cases at nationalpopulation–based level. In the absence of population-based data,data were provided on a survey basis for the province of Valenciain Spain and for France. Population-based data for the Brussels andFlanders regions of Belgium, for the countries of Northern Ireland,Scotland and England and Wales jointly were available separately,thus yielding 25 European countries/regions for analysis. The datawere mainly obtained from civil registration based on birth anddeath certificates or from other national sources, including specificperinatal databases.

Selection of indicators

To explore the effects of various forms of presentation, fourindicators were chosen from the EURO-PERISTAT set of ‘core’indicators for 2004. They were chosen because they differed withrespect to their average rate and with the further requirement thatcomparable observations were available for the majority ofcountries. In ascending order of mean incidence, these arematernal mortality (ratio of number of pregnancy and childbirth-related maternal deaths to live births) with a ratio of �4–6 per100 000 live births, crude neonatal mortality (deaths at 0–27 daysafter live birth) with a rate of �3–5 per 1000 live births, birthweightbelow 2500 g among all live and stillbirths with a rate of �6% andcaesarean sections (all elective and emergency caesarean sectionscombined) with a rate of �15% per total number of births.

Owing to its low overall incidence, maternal mortality wascompiled for the years 2003–2004 combined, except for Germany(2004), Italy (2002) and Luxembourg (2000–2004), to increase thestability of these estimates. For countries with extremely smallpopulation sizes such as Estonia and Malta, only 2-year averageswere available. No data were available on maternal deaths fromCyprus, Ireland and Slovakia. No data were available for neonatalmortality for Ireland, which only provided data on early neonatalmortality (deaths at 0–6 days after birth), whereas Cyprus providedno data on the distribution of birthweight, and no data wereavailable on mode of delivery for Greece.

Throughout, the data sets are defined by observations (ci, ri andni) denoting country, number of cases in the numerator anddenominator, respectively, with the subscript i running throughall 25 countries/regions. The raw rates are computed as yi = ri/ni

with 0 < yi < 1.

Presentation

In addition to a tabular summary, standard choropleth maps andfunnel plots were constructed for these four selected indicators of

perinatal health. An enhanced choropleth map was constructedfor caesarean section rates. This indicator was chosen because ofits status as a core indicator, its availability in all but one countryand its good quality of documentation.

Tabular summary

A table of denominators ni, observed rates yi and p-values indicatingsignificance of departure from respective EU medians y0 was con-structed in alphabetical order of country. The median was selectedto prevent large countries from dominating the comparisons.The p-values are computed as pi = ��1(zi) from the inversenormal distribution function where

zi ¼yi � y0ffiffiffiffiffiffiffiffiffiffiffiffiffiffi

y0 1�y0ð Þn

q

Standard choropleth maps

We plot the observed rates using colour coding derived from sixpercentiles of the distributional characteristics of the outcomemeasures and with upper limits at 10, 25, 50, 75, 90 and 100. Wechose shades of the neutral colour blue, with dark shades corres-ponding to high rates, in keeping with the examples in the EuropeanPerinatal Health Report.6

The maps were constructed with the SAS GMAP16 procedure. Theperimeters of country boundaries were extracted from the SAS/MAPS16 database and linked to observed rates through thecountry identifiers ci. Version 9.1 of SAS16 provides data atnational level. Subsets of the database corresponding to thecountry of Scotland and the Flanders and Brussels region ofBelgium were generated by straight-line dissection of existingnational coordinate files. Countries for which no data wereavailable are left blank.

Funnel plots

Funnel plots were constructed using R17 by plotting the observedoutcome against population size as a proxy measure of precision.Control limits were drawn vertically around the median rate for allcountries. To assess degree of departure from the median rate y0,statistical control limits were computed from the standard normalapproximation to the binomial distribution as

y0 � z1��=2� �

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiy0 1� y0

� �ni

s

for � levels of 5.0 and 0.1% and 0 < y0 < 1.

Enhanced choropleth maps

Two basic options for indicating significance of difference from areference level were considered, either by superimposing suitablesymbols or by application of different shading patterns. The fivevariants of these two approaches are listed in table 1 and figure 1.Whereas colouring schemes A, B and C use a neutral colouring ofpercentile bands, schemes D and distinguish deviations above andbelow the reference by different colours. Schemes A and B usesuperimposed symbols, schemes C and E differentiate by patternand scheme D uses bold perimeters to indicate significant differ-ences. A significance level of 0.001 was used throughout.

Results

Table 2 shows denominators, rates and significance of departurefrom respective EU medians for the four selected indicators atregional or country level. The denominators vary considerablyaccording to the demographic characteristics. The population of

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Table 2 Denominators (n), regional rates and P-values for EU member states for maternal deaths (MD) per 100 000 live births, birthweightunder 2500 g (LBW) as percentage of total births, neonatal deaths (NND) per 1000 live births and caesarean sections (CS) as percentage oftotal births

Country Code n MD P n LBW P n NND P n CS P

Austria AT 155 912 6.4 0.34 79 229 7.0 0.00 78 934 2.7 0.48 79 229 23.5 0.00

Belgium-Brussels BE.b 32 400 6.2 0.41 15 842 6.7 0.48 16 200 3.1 0.14 15 561 17.2 0.00

Belgium-Flanders BE.f 119 167 4.2 0.11 60 921 6.8 0.21 60 672 2.4 0.07 60 921 18.9 0.00

Czech Republic CZ 191 349 9.9 0.09 98 056 6.9 0.00 97 664 2.3 0.01 96 098 16.3 0.00

Denmark DK 129 466 9.3 0.20 64 585 5.4 0.00 64 521 3.6 0.00 63 767 20.5 0.50

England and Wales UK.ew 1 261 190 7.2 0.47 642 050 7.8 0.00 639 721 3.4 0.00 612 888 23.1 0.00

Estonia EE 27 028 29.6 0.00 14 017 4.5 0.00 13 990 4.2 0.00 14 020 17.7 0.00

Finland FI 114 018 7.9 0.40 57 734 4.3 0.00 57 569 2.4 0.11 57 752 17.1 0.00

France FR 1 529 280 7.0 0.34 14 534 7.2 0.01 767 816 2.6 0.01 14 696 20.2 0.20

Germany DE 692 802 5.3 0.03 648 667 7.3 0.00 705 622 2.7 0.30 647 685 27.3 0.00

Hungary HU 190 274 7.4 0.48 95 537 8.6 0.00 95 137 4.4 0.00 95 613 25.6 0.00

Italy IT 539 066 3.2 0.00 541 270 6.8 0.00 539 066 2.8 0.05 539 235 37.8 0.00

Latvia LV 41 340 12.1 0.13 20 492 5.4 0.00 20 355 5.7 0.00 20 256 19.6 0.00

Lithuania LT 61 017 9.8 0.23 29 633 5.1 0.00 29 480 4.6 0.00 29 595 17.4 0.00

Luxembourg LU 27 252 7.3 0.50 5300 4.8 0.00 5469 2.0 0.16 5422 25.3 0.00

Malta MT 7923 0.0 0.22 3899 8.0 0.00 3887 4.4 0.02 3902 28.3 0.00

Netherlands NL 362 012 8.8 0.14 182 263 6.7 0.44 181 006 3.5 0.00 182 135 15.1 0.00

Northern Ireland UK.n 43 786 9.1 0.32 22 503 6.0 0.00 22 362 3.0 0.25 22 378 27.6 0.00

Norway NO 113 409 3.5 0.07 57 356 5.0 0.00 57 111 2.1 0.00 57 368 15.6 0.00

Poland PL 707 203 4.4 0.00 358 381 6.4 0.00 356 697 4.9 0.00 350 048 26.3 0.00

Portugal PT 221 945 7.7 0.42 109 444 7.8 0.00 109 356 2.6 0.17 107 195 33.1 0.00

Scotland UK.s 106 389 12.2 0.03 53 255 7.5 0.00 52 911 3.0 0.07 52 893 24.7 0.00

Slovenia SI 34 907 11.5 0.18 17 946 6.2 0.00 17 846 2.6 0.42 17 937 14.4 0.00

Spain ES 896 472 4.6 0.00 435 748 7.6 0.00 454 591 2.6 0.16 38 290 24.6 0.00

Sweden SE 200 316 2.0 0.00 100 219 4.3 0.00 100 158 2.1 0.00 100 081 17.4 0.00

The p-values indicate significance of difference from respective EU medians.

Figure 1 Colouring schemes for enhanced choropleth maps: Schemes A, B and C use three darker intensities of blue shading above andthree lighter intensities (two of which are shown) of blue below the median. Significance is indicated by appropriate symbols superimposedin schemes A and B, by solid colouring in schemes C and E and by bold perimeters in scheme D

Table 1 Choices of colouring schemes for enhanced choropleth maps

Attribute A B C D E

Percentile bands Shades of blue Shades of blue Shades of blue Shades of red and green Shades of red and green

Significance Plus and minus symbols Up and down arrows Solid fill Bold contours Solid fill

Intensity of shading corresponds to respective percentile band. Darker shades of blue and red colours indicate values above the median,lighter shades of blue and green colours indicate values below the median. Extreme shadings correspond to values below the 10th or abovethe 90th percentile.

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England and Wales is �160 times that of Malta and �50 times thatof Estonia and Luxembourg. The median rates are 7.3 per 100 000for maternal deaths, 6.7% for the proportion of births below 2500 g,2.7 per 1000 live born for neonatal deaths and 20.5% for caesareansections.

Figure 2 shows a corresponding panel of standard choroplethmaps, with intensity of blue corresponding to percentile band forall four indicators. Countries for which no data were available areleft blank. The percentile grading is reflected in the broader ranges atthe extremes of the distributions. Some of the subranges are notcontiguous owing to their automatic generation by SAS/GRAPHsoftware16 based on the actual distribution of observed rates.

Figure 3 shows the corresponding panel of funnel plots. In thecase of maternal mortality, most countries fall within the controllimits. Estonia stands out with eight maternal deaths in 27 028 livebirths between 2003 and 2004 (29.6 per 100 000 live births vs. 0.0–12.2 for the remaining countries/regions). For neonatal mortalityrates, the majority of smaller countries (with <150 000 births) liewithin the limits. Although there are several other countries withhigh neonatal mortality rates, all new member states of the EuropeanUnion as well as Poland stand out due to its large population. Thedistribution of low birthweight shows countries largely falling eitherbelow, within or above the control limits, irrespective of populationsize. In the case of caesarean sections, only one, Denmark (DK)alone, lies close to the European median rate. All other countries

deviate considerably from the median, again seemingly irrespectiveof population size. Italy stands out due to its high caesarean sectionrate and its large population size.

Figure 4 shows an enhanced choropleth plot for caesarean sectionsusing scheme E from figure 1. The width of the upper percentileband is �5 times that of the lower band as a result of the skeweddistribution, with Italy and Portugal showing comparatively highcaesarean section rates. All countries except Denmark, Latvia andFrance show significant differences from the EU median rate of20.5% (table 2). Twenty-two countries deviate significantly fromthe EU median, 11 above and 11 below.

Discussion

Standard choropleth maps

The chief advantage of choropleth maps lies in making regionalpatterns transparent. At a glance, one can discern the strongcontrast in neonatal mortality rates between the Eastern Europeanstates and Nordic states or the high caesarean section rates in Italy,Germany and Portugal (figure 2). Displays such as these were usedfor reporting perinatal indicators,7 and joint inspection may help togenerate hypotheses about possible common causes for rates inselected regions.

Figure 2 Choropleth panel plot of selected EURO-PERISTAT indicators. Colour grading is by quintiles of outcome rate. Maternal mortality isbased on the period 2003–2004 for the majority of countries (see text)


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Panel plots are also well suited for comparisons across differentperformance indicators, which are highly correlated. For instance,one may see that the Nordic states have lower rates for caesareansections, for low birthweight and, with the exception of Finland, formaternal mortality. A further advantage lies in the informationcontained in geographical size of the region. This, albeit rough,proxy measure of population size can be of help in interpretingthe results.

Six categories were chosen for grading the outcome rates in terms ofdistribution percentiles for all performance indicators to differentiatecountries with respect to the median. Although this indicates distinctcategories of absolute rates, it allows no conclusion about the signifi-cance of departure of this rate from a reference value. This can bemisleading, especially for small countries. It must be borne in mindthat although identically coloured regions imply identical percentilesacross different choropleth maps, this will not in itself indicate how faran individual rate differs from the mean or median.

Funnel plots

This shortcoming is remedied with funnel plots. They reveal a con-siderable heterogeneity in spread not only between countries but

also between selected indicators of perinatal health (figure 3). Thisstrongly suggests non-random causes for the differences in perinatalhealth, which is particularly marked for low birthweight andcaesarean sections. Presenting indicators of perinatal health ina panel facilitates the generation of hypotheses about differencesin the provision and effectiveness of health care. This form of pres-entation also makes the fact that population size differs betweenunits more visible. EURO-PERISTAT has now decided to collectmaternal mortality for a 5-year period because of the difficultiesassociated with low sample sizes. This is expected to result in alower maternal death ratio for Estonia and conversely a higherratio for Malta, where data were available only for 2 successiveyears. When data are presented as rates, it is easy to forget howfew maternal deaths there are.

Choice of pattern

Although initially favoured due to their widespread use, quintilegrading was not considered, as this would lead to ambiguouscolouring and shading in the case of countries within the centralquintile deviating significantly in opposite directions. Symmetricallyarranged percentiles were selected, with a focus on extreme lower

Numbers of live births, 100,000s

Dea

ths

per 1

00,0

00 li

ve b

irths

Maternal Mortality

ATBE.bBE.f

CZDKUK.ew

EE

FI FRDE

HU

IT

LVLT

LU

MT

NLUK.n

NO PLPT

UK.sSI

ESSE

0 5 10 15

010

2030

Numbers of total births, 100,000s

Perc

enta

ge o

f tot

al b

irths

Low birth weight 2004

ATBE.bBE.fCZ

DK

UK.ew

EEFI

FR DE

HU

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LVLT

LU

MT

NL

UK.n

NO

PL

PTUK.s

SI

ES

SE

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56

78

Numbers of live births, 100,000s

Neo

nata

l dea

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,000

live

birt

hs Neonatal Mortality 2004

ATBE.b

BE.fCZ

DK UK.ew

EE

FI FRDE

HU

IT

LV

LT

LU

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UK.n

NO

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45

Numbers of total births, 100,000s

Perc

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AT

BE.bBE.f

CZ

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DEHU

IT

LVLT

LU

MT

NL

UK.n

NO

PL

PT

UK.s

SI

ES

SE

0 2 4 6

1520

2530

35

Figure 3 Funnel plots of indicators shown in figure 2 against total number of deliveries for European countries and regions with controllimits drawn at 95.0 and 99.9%. Some of the axes exclude zero to enhance readability. For maternal mortality, the x-axis is on a wider scaledue to the inclusion of the period 2003–2004 for the majority of countries (see text)


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and upper 10%. The use of superimposed symbols may lead to dis-tortions and graphical difficulties for small countries such asLuxembourg. In scheme A, there is an inherent bias towardshigher rates because of the larger appearance of the ‘plus’ sign,which is not present in scheme B. Although initially appealing, thediscrimination of significance in terms of thickness of countryperimeters has the serious disadvantage that bold black bordersare less distinct for regions with darker shadings. To avoid thisbias and also because of obvious problems for small regions,scheme D was dropped. In the trade-off between colour bias(scheme E) and difficulty in readily identifying countries abovefrom those below the median (scheme C), the final choice fell onscheme E.

Interpreting an enhanced choropleth map

Figure 4 illustrates the advantage of enhancing a standardchoropleth map with colouring scheme E applied to caesareansection rates. The distribution of caesarean section rates isnoteworthy, as one observes that most countries have either sig-nificantly high or significantly low rates, with only Denmark,Latvia and France in between, reflecting a bimodal distribution.It is attractive to use these data to entertain a hypothesis aboutpatterns of mode of delivery across Europe. Local choices madeby pregnant women and clinical custom varying across countriesas well as interactions between these factors may well account forthe observed pattern.

Supplementary data

Supplementary data are available at EURPUB online.

Acknowledgements

The EURO-PERISTAT Scientific Committee: Gerald Haidinger(Austria), Sophie Alexander (Belgium), Pavlos Pavlou (Cyprus),Petr Velebil (Czech Republic), Jens Langhoff Roos (Denmark),Luule Sakkeus (Estonia), Mika Gissler (Finland), Beatrice Blondel(France), Nicholas Lack (Germany), Aris Antsaklis (Greece), IstvanBerbik (Hungary), Sheelagh Bonham (Ireland), Marina Cuttini(Italy), Janis Misins (Latvia), Jone Jaselioniene (Lithuania),Yolande Wagener (Luxembourg), Miriam Gatt (Malta), JanNijhuis (The Netherlands), Kari Klungsoyr (Norway), KatarzynaSzamotulska (Poland), Henrique Barros (Portugal), MariaChmelova (Slovak Republic), Ziva Novak-Antolic (Slovenia),Francisco Bolumar (Spain), Karin Gottvall (Sweden) and AlisonMacfarlane (United Kingdom). Further acknowledgements to con-tributors to the 2008 European Perinatal Health Report can befound in the accompanying supplementary file.

Funding

The EURO-PERISTAT project is funded by the Public HealthProgramme of the European Commission, Directorate General ofPublic Health (Agreement 2010 13 01). The Directorate General of

Figure 4 Enhanced choropleth plot for caesarean section rates using colouring scheme E. Regions with solid-fill patterns differ significantlyfrom the EU median rate of 20.5%. The abundance of such countries indicates a bimodal distribution with evident grouping of rates belowand above the median


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Public Health had no role in the collection of the data, the writing ofthe manuscript or the decision to submit for publication. Datacollection for Estonia was supported by grant numbers EE ESFSF0130018s11 and EE ESF 8325.

Conflicts of interest: None declared.

Key points

� Tabular summaries of rates, population sizes and z-scoresprovide a maximum of statistical information, while beingunwieldy and not easy to read.� Funnel plots also contain most of this information and

enable rapid identification of outliers; however, they donot provide information on regional patterns.� Choropleth plots with enhanced patterns where colour

reflects polarity of a country from a reference level,intensity of colouring to indicate size of deviation andsolid fill versus crosshatching to indicate significance ofdifference can add valuable additional information andfacilitate the interpretation of regional data.� As customary geographical maps of indicators of perinatal

health tend to exaggerate differences between regions, theindication of significance of such differences is expected toimprove monitoring and assessment of public health policyand practice.

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The second European Perinatal HealthReport: documenting changes over6 years in the health of mothersand babies in EuropeJ Zeitlin,1 A D Mohangoo,2 M Delnord,1 M Cuttini,3

the EURO-PERISTAT Scientific Committee

The second European Perinatal HealthReport from the EURO-PERISTAT projectwas released on May 27 of this year.1

Thirty indicators, compiled from routinestatistics in 29 countries, are analysed andgrouped into four main areas: fetal, neo-natal and child health, maternal health,characteristics of the populations andhealthcare. The report results from a 3-yearcollaboration between researchers, clini-cians and official statisticians in Europe. Italso contains data from two otherEuropean projects: Surveillance of CerebralPalsy in Europe (SCPE) and EuropeanSurveillance of Congenital Anomalies(EUROCAT).

Common definitions and inclusion cri-teria make it possible to overcome some ofthe differences between countries in therecording of births and deaths and improvethe comparability of the data presented.2 3

Both results for the year 2010 and compari-sons with the 2004 data published in thefirst European Perinatal Health Report areincluded.3

Between 2004 and 2010, fetal, neonataland infant mortality decreased almosteverywhere. Denmark, Italy and theNetherlands experienced the largest abso-lute declines in fetal mortality rates (areduction of 1.4 per 1000 total births).Absolute declines in neonatal mortalitywere greatest in countries where rates werehigher in 2004 such as some of the EasternEuropean countries. However, declineswere also observed in countries with lowrates in 2004 such as Finland and Sweden,showing that further decreases are stillpossible.

In some cases, these improvements fol-lowed public health actions deliberatelyundertaken at national level. In theNetherlands, the public debate followingthis country poor ranking in fetal andneonatal mortality with 2000 and 2004data led to a series of policy efforts,including audits of perinatal deaths interm babies and establishing a nationalcommission on perinatal care.4 Also, in2007 prenatal screening for congenitalanomalies was implemented nationwide.As a consequence, between 2004 and2010 fetal mortality at or after 28 weeksof gestation declined from 4.3 to 2.9 per1000 births, and neonatal mortality at orafter 24 weeks declined from 2.8 to 2.2per 1000 live births, while the country’slow caesarean rates were maintained.Relating improvements in outcomes to

changes in distributions of risk factors ismore problematic. The prevalence of somerisk factors has increased in European coun-tries, while others have become less preva-lent. The proportion of mothers aged 35and older has increased in all countriesexcept Finland, but the negative impact ofthis change on the health of pregnantwomen and neonates may have been moder-ated by better maternal general health andcare. Multiple birth rates have also increased,probably as a result of rising maternal ageand more widespread use of assisted repro-duction techniques. In contrast, smokingduring pregnancy declined in almost allcountries where data were available.Trends in the rates of preterm live births

vary between European countries (figure 1).Many countries experienced declines inoverall rates, as seen in an earlierEURO-PERISTAT analysis of singletonbirths,5 while elsewhere rates remainedalmost constant. Overall, these findingssuggest that the much quoted increase inoverall preterm birth rates over the past15 years may now be coming to an end. Insome countries, however, preterm birth ratesdid increase. Understanding the reasons forthese diverse trends could help shape effect-ive preventive public health policies.

The changes since 2004 have not elimi-nated the wide differences in perinatalhealth outcomes in Europe, however. Fetalmortality rates at or after 28 weeks of gesta-tion still range from under 2.0 per 1000total births in the Czech Republic andIceland to 4.0 or more in France, Latvia,the region of Brussels in Belgium andRomania. The countries of the UK alsohave relatively high fetal mortality rates, 3.8in England and Wales and 3.6 in Scotland.Neonatal mortality is lower than 2 per1000 live births in Iceland, Finland andSweden but over 4 in Malta and over 5 inRomania. Infant mortality ranges fromabout 2 per 1000 in Iceland and Finland tomore than 5 in Malta and Latvia, andreaches 9.8 in Romania. Documentingthese differences is important because itraises important questions about differencesbetween populations, the effectiveness ofnational maternity care policies and the roleof evidence in maternity care.

Healthcare indicators continue to revealmarked variations in the approach tochildbirth in Europe. Caesarean sectionrates range from 14.8% in Iceland to52.2% in Cyprus, instrumental deliveryrates range from 0.5% in Romania to16.4% in Ireland, and episiotomy ratesrange from under 7% in Denmark andSweden to over 70% in Cyprus andPortugal. The sizes of the maternity unitsvary as well: from no births in maternityunits with 5000 or more deliveries in theregion of Flanders in Belgium andSlovenia to 55.1% in Ireland. There were,however, some common trends: caesareanrates rose in all countries apart fromSweden and Finland where rates declined.Episiotomy rates also tended to declineover this period, although not in countrieswith already low rates in 2004 such asEngland, Latvia and Norway.

The EURO-PERISTAT network has nowbeen in place for over 10 years, showingthat long-lasting multidisciplinary inter-national collaboration can be achieved.Over the years, the number of participatingcountries has increased from 15 in 2000 tothe current 27 out of 28 European Union(EU) member states plus Norway,Switzerland and Iceland. Data were col-lected for three different years, 2000, 2004and 2010 with the first results from theyear 2000 having been published as aspecial issue of the European Journal ofObstetrics and Gynaecology in 2003.6

Thus, time trends in population characteris-tics and outcomes can now be explored.

Yet to build a truly informativesystem, further actions are needed toensure that each country can provide the

1UMRS 953, Epidemiological Research Unit onPerinatal and Women’s and Children’s Health, INSERM,Paris, France; 2Department Child Health, TNO,Netherlands Organization for Applied ScientificResearch, Leiden, South Holland, The Netherlands;3Unit of Epidemiology, Bambino Gesù Children’sHospital, Roma, Italy

Correspondence to Dr Marina Cuttini, Unit ofEpidemiology, Bambino Gesù Children’s Hospital,Viale Ferdinando Baldelli 41, Roma 00146, Italy;[email protected]

Zeitlin J, et al. J Epidemiol Community Health December 2013 Vol 67 No 12 983

Editorial

full set of EURO-PERISTAT indicatorsusing common definitions and agreed eli-gibility criteria. For instance, valid com-parisons of mortality rates for extremelypreterm neonates are still not possiblebetween European countries due to differ-ences in registration criteria for births andin practices for recording late terminationsof pregnancy in routine data systems.2

Agreements about common recordingguidelines as well as wider linkage of datafrom different sources, building onmethods already in use in some parts ofEurope, could enable fuller use of dataalready being collected and yield

immediate gains in many countries. Theuse of individually linked records, anon-ymised to protect confidentiality, wouldprovide opportunities for a better under-standing of the relationship betweenchanges in risk factors, healthcare pro-vided and outcomes.The biggest question, however, con-

cerns the long-term sustainability of thisinitiative so far based on nationalresources, with central funding providedby a series of ad hoc projects under theHealth Programme of the EuropeanUnion. Should perinatal data monitoringbe included in the European Statistical

System run by Eurostat? Should theEuropean Centre for Disease Controlexpand its scope, following the exampleof its US counterpart, traditionally incharge of monitoring perinatal risk factorsand outcomes? Or should a specific pro-gramme linking the various perinatalmonitoring initiatives be created underthe EU Directorate for Health? A solutionis urgently needed to sustain long-termroutine projects like this and otherimportant European public health initia-tives, as this would build on successfulexperiences and on a considerable amountof expertise and dedicated humanresources.

Collaborators EURO-PERISTAT Scientific Committee:Gerald Haidinger (Austria), Sophie Alexander;(Belgium), Pavlos Pavlou (Cyprus), Petr Velebil (CzechRepublic), Jens Langhoff Roos (Denmark), LuuleSakkeus (Estonia), Mika Gissler (Finland), BéatriceBlondel (France), Nicholas Lack (Germany), ArisAntsaklis (Greece), István Berbik (Hungary), Helga SólÓlafsdóttir (Iceland), Sheelagh Bonham (Ireland),Marina Cuttini (Italy), Janis Misins (Latvia), JoneJaselioniene (Lithuania), Yolande Wagener(Luxembourg), Miriam Gatt (Malta), Jan Nijhuis (theNetherlands), Kari Klungsøyr (Norway), KatarzynaSzamotulska (Poland), Henrique Barros (Portugal),Mihai Horga (Romania), Ján Čáp (Slovakia), ŽivaNovak-Antolic (Slovenia), Francisco Bolúmar (Spain),Karin Gottvall (Sweden), Sylvie Berrut (Switzerland) andAlison Macfarlane (UK). Writing committee for the2010 European Perinatal Health Report: Jennifer Zeitlin,Ashna Mohangoo, Marie Delnord (Editors); SophieAlexander, Béatrice Blondel, Marie-HélèneBouvier-Colle, Nirupa Dattani, Mika Gissler, AlisonMacfarlane, Karin van der Pal, Katarzyna Szamotulskaand Wei Hong Zhang.

Contributors JZ, ADM and MD were editors of theEuropean Perinatal Health Report 2010. JZ and MCproduced a first draft of this editorial. ADM and MDcarried out analyses of submitted data and providedsubstantive comments to the manuscript. Members ofthe EURO-PERISTAT Group contributed to analyses andinterpretation of data.

Funding The EURO-PERISTAT project is co-financed bythe Health Programme of the European UnionDirectorate General for Health and Consumers whichalso provides funding for SCPE and EUROCAT (grantnumber 2003131).

Competing interests None.

Provenance and peer review Commissioned;internally peer reviewed.

To cite Zeitlin J, Mohangoo AD, Delnord M, et al.J Epidemiol Community Health 2013;67:983–985.

Received 22 August 2013Accepted 26 August 2013Published Online First 19 September 2013

J Epidemiol Community Health 2013;67:983–985.doi:10.1136/jech-2013-203291

Figure 1 Percentage of preterm live births in 2004 and difference between 2010 and 2004.NOTES: Countries ranked according to increasing differences between 2010 and 2004. Rate in2010 can be computed by adding 2004 rate and difference between 2010 and 2004.

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Editorial

REFERENCES1 Euro-Peristat project with SCPE and Eurocat. European

Perinatal health report. The health of pregnant womenand babies in Europe in 2010. 2013. http://www.europeristat.com

2 Mohangoo AD, Buitendijk SE, Szamotulska K, et al.Gestational age patterns of fetal and neonatalmortality in Europe: results from the Euro-PeristatProject. PLoS ONE 2011;6:e24727.

3 Euro-Peristat project in collaboration SCPE, EUROCATand EURONEOSTAT. Better statistics for better healthfor pregnant women and their babies in 2004.European Perinatal Health Report 2008. http://www.europeristat.com

4 Stuurgroep zwangerschap en geboorte. Een goedbegin. Veilige zorg rond zwangerschap engeboorte. Utrecht: Stuurgroep zwangerschap engeboorte, 2009.

5 Zeitlin J, Szamotulska K, Drewniak N, et al. Pretermbirth time trends in Europe: a study of 19 countries.BJOG 2013;120:1356–65.

6 Zeitlin J, Wildman K, Breart G, et al. Selecting anindicator set for monitoring and evaluating perinatalhealth in Europe: criteria, methods and results fromthe PERISTAT project. Eur J Obstet Gynecol ReprodBiol 2003;111(Suppl 1):5–14.

Zeitlin J, et al. J Epidemiol Community Health December 2013 Vol 67 No 12 985

Editorial







International Comparisons of Fetal and NeonatalMortality Rates in High-Income Countries: ShouldExclusion Thresholds Be Based on Birth Weight orGestational Age?Ashna D. Mohangoo1*, Beatrice Blondel2, Mika Gissler3,4, Petr Velebil5, Alison Macfarlane6,

Jennifer Zeitlin2,7, the Euro-Peristat Scientific Committee"

1 Department of Child Health, TNO, Netherlands Organization for Applied Scientific Research, Leiden, The Netherlands, 2 Epidemiological Research Unit on Perinatal and

Women’s and Children’s Health, INSERM UMRS 953, Universite Pierre-et-Marie Curie Paris6, Paris, France, 3 Information Department, National Institute for Health and

Welfare, Helsinki, Finland, 4 Nordic School of Public Health, Gothenburg, Sweden, 5 Institute for the Care of Mother and Child; Perinatal Centre, Prague, Czech Republic,

6 Maternal and Child Health Research Centre; City University London, London, United Kingdom, 7 UPMC University Paris 06, Paris, France

Abstract

Background: Fetal and neonatal mortality rates are essential indicators of population health, but variations in recording ofbirths and deaths at the limits of viability compromises international comparisons. The World Health Organizationrecommends comparing rates after exclusion of births with a birth weight less than 1000 grams, but many analyses ofperinatal outcomes are based on gestational age. We compared the effects of using a 1000-gram birth weight or a 28-weekgestational age threshold on reported rates of fetal and neonatal mortality in Europe.

Methods: Aggregated data from 2004 on births and deaths tabulated by birth weight and gestational age from 29European countries/regions participating in the Euro-Peristat project were used to compute fetal and neonatal mortalityrates using cut-offs of 1000-grams and 28-weeks (2.8 million total births). We measured differences in rates between andwithin countries using the Wilcoxon signed rank test and 95% confidence intervals, respectively.

Principal Findings: For fetal mortality, rates based on gestational age were significantly higher than those based on birthweight (p,0.001), although these differences varied between countries. The use of a 1000-gram threshold included 8823fetal deaths compared with 9535 using a 28-week threshold (difference of 712). In contrast, the choice of a cut-off madelittle difference for comparisons of neonatal deaths (difference of 16). Neonatal mortality rates differed minimally, by under0.1 per 1000 in most countries (p = 0.370). Country rankings were comparable with both thresholds.

Conclusions: Neonatal mortality rates were not affected by the choice of a threshold. However, the use of a 1000-gramthreshold underestimated the health burden of fetal deaths. This may in part reflect the exclusion of growth restrictedfetuses. In high-income countries with a good measure of gestational age, using a 28-week threshold may provideadditional valuable information about fetal deaths occurring in the third trimester.

Citation: Mohangoo AD, Blondel B, Gissler M, Velebil P, Macfarlane A, et al. (2013) International Comparisons of Fetal and Neonatal Mortality Rates in High-Income Countries: Should Exclusion Thresholds Be Based on Birth Weight or Gestational Age? PLoS ONE 8(5): e64869. doi:10.1371/journal.pone.0064869

Editor: Linda Wright, National Institute of Child Health and Human Development, United States of America

Received August 16, 2012; Accepted April 19, 2013; Published May 0, 2013

Copyright: � 2013 Mohangoo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The results from this study are based on data from the Euro-Peristat project, a European project for monitoring and evaluating perinatal outcomes onthe European level. The Euro-Peristat project was co-financed by the European Commission (DG-SANCO), grant numbers 2003131 and 20101301. The funders hadno role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding was received for thisstudy.

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: [email protected]

" Membership of the Euro-Peristat Scientific Committee is provided in the Acknowledgments.

Introduction

There is an ongoing debate about the value of international

comparisons of fetal and neonatal mortality rates, given differences

between countries in recording of births and deaths at borderline

viability [1,2]. Fetal and neonatal mortality rates are highly

sensitive to these inclusion criteria [1,3,4]. Differences in recording

criteria are most acute for fetal deaths [5]. These deaths are

recorded from as early as 16 completed weeks of gestation in

Norway or 20 completed weeks in the United States to 26

completed weeks in Italy and Spain [3,5]. Denmark and Sweden

recorded fetal deaths beginning at 28 completed weeks until 2004

and 2008, respectively. While only a small proportion of births

occur before 24 completed weeks of gestation (about 1 per 1000)

[6], survival is rare and most of them are either fetal deaths or live

births followed by a neonatal death. These births have a

substantial impact on perinatal mortality statistics [3]. Valid

analyses of fetal and neonatal mortality across countries thus

PLOS ONE | www.plosone.org 1 May 2013 | Volume 8 | Issue 5 | e64869

2

require specifying common inclusion limits. These criteria are

based either on gestational age, or on birth weight or on a

combination of these.

The World Health Organization (WHO) recommends the use

of a 1000-gram threshold for international comparisons of

perinatal mortality rates [7]. This limit makes it possible to

provide a measure of the health burden of third trimester perinatal

deaths, since 1000 grams corresponds approximately to the birth

weight at 28 completed weeks of gestation, the beginning of the

third trimester. This measure provides only a partial view of

overall mortality, since a large proportion of deaths in high-

income countries (between 25–60%) occur to babies born in the

second trimester [3,6], but using this threshold has the benefit of

enabling greater comparability between countries. Participants in

a recent international collaboration on stillbirths agreed that an

analysis of third trimester deaths has public health relevance for

international comparisons in high-income countries [8].

The aim in international comparisons is to maximise both

comparability and scientific and policy relevance. The primary

aim of using a birth weight threshold for international comparisons

is to ensure comparability because birth weight measures are

considered to be less prone to error than calculations of gestational

age. When the date of the last menstrual period (LMP) is used

alone to calculate gestational age, the results can be inaccurate [9],

especially if the woman has no antenatal care or if antenatal care

starts late in pregnancy. However, most high-income countries use

a clinical estimate of gestational age that incorporates information

from dating ultrasounds and is therefore of better quality [10].

Birth weight data also have limitations since babies who are

stillborn or die before they can be transferred to a neonatal unit

may not be systematically weighed [11].

Gestational age is generally considered to be a more relevant

variable than birth weight for studying perinatal outcomes. Recent

European cohorts have analysed the outcome for very preterm

rather than very low birth weight babies, as gestational age has a

better prognostic value [12–16]. Furthermore, when obstetricians

are making decisions during pregnancy, they have reasonably

precise information about gestational age but not about birth

weight. Finally, birth weight distributions differ between and

within populations and European comparisons have found that

the birth weight at which mortality is lowest varies between

European countries [17]. Using birth weight cut-offs will exclude

relatively more births and deaths in countries where average birth

weights are lower and this may introduce bias.

While the hypothesis underlying the current WHO recommen-

dation is that the 1000-gram threshold provides a good

approximation for the 28th week of gestation or the beginning of

the third trimester, this hypothesis has not been tested. The aim of

this analysis was therefore to compare the use of a 1000-gram birth

weight threshold with a 28-week gestational age threshold in terms

of their impact on reporting of fetal and neonatal mortality rates

within European countries and on comparisons between Europe-

an countries.

Methods

This study was embedded within Euro-Peristat, which devel-

oped a list of valid and reliable indicators for monitoring and

evaluating perinatal health in the European Union (EU) [18].

Twenty-five EU member states and Norway participated. Detailed

information on the design and methods is available elsewhere

[5,19,20]. National population-based data for each indicator for

the year 2004 were requested in aggregated form from members of

the Euro-Peristat Scientific Committee. If national data were not

available, population-based regional data could be provided

instead.

The Euro-Peristat core indicator list includes fetal and neonatal

mortality. The fetal mortality rate is defined as the number of

deaths before or during birth in a given year per 1000 live and

stillbirths in the same year. The neonatal mortality rate is defined

as the number of deaths at 0 to 27 days after live birth in a given

year per 1000 live births in the same year. Euro-Peristat collects

data on births and deaths at or after 22 weeks of gestation,

regardless of birth weight. Aggregated data on the number of live

births, fetal and neonatal deaths by each week of gestation and by

birth weight intervals of 500 grams were collected. These data

were used to calculate fetal and neonatal mortality rates for births

and deaths weighing 1000 grams and over and for those born at or

after 28 completed weeks.

Twenty-seven countries were able to provide data to calculate

fetal mortality rates with birth weight and gestational age

thresholds. Germany, Hungary, Ireland and Italy did not have

data on neonatal deaths by birth weight or gestational age. Some

countries could only provide data on some regions (Valencia in

Spain, Brussels and Flanders in Belgium). Data from France came

from a one-week national perinatal survey in October 2003, vital

registration, and neonatal death certificates. Data on neonatal

deaths from England and Wales related to 2005 and data from

Italy were for 2003. Table S1 presents additional information

about the data sources. These constraints reflect the diversity of

sources for perinatal health data in Europe [5].

Missing DataMost countries had fewer than 5% of data missing for fetal and

neonatal deaths by birth weight and gestational age, as presented

in Table S2. However, there were some exceptions. The

percentages of fetal deaths with birth weights missing were

30.7% in Denmark, 25.0% in Italy, 22.7% in Brussels, 13.9% in

Valencia, 6.4% in Portugal, 5.9% in Luxembourg, and 5.1% in

France. Gestational age was missing for 17.0% of fetal deaths in

Brussels, 11.7% in Valencia and 9.5% in Portugal. We excluded

countries where the proportion of fetal deaths with missing birth

weight was significantly different from the proportion with missing

gestational age. These were Denmark (30.7% of birth weights vs.

4.2% of gestational ages) and Italy (25.0% of birth weights and 0%

for gestational age). These divergent proportions of missing data

would have biased our ability to compare rates.

For neonatal deaths, fewer countries had high proportions of

data missing. Over 5% of birth weights were missing for Denmark

(14.8%), Luxembourg (9.1%), Sweden (7.1%), Scotland (6.8%),

and Valencia (5.8%). Gestational ages were missing for over 5% in

Luxembourg (9.1%), Denmark (7.0%), Portugal (6.8%), and

Valencia (6.8%). As with fetal deaths, we excluded countries with

highly divergent proportions of missing birth weights and

gestational ages. We therefore excluded Denmark (14.8% of birth

weights vs. 7.0% of gestational ages) and Sweden (7.1% of birth

weights and 0% for gestational age). Live birth data were missing

for less than 5% with the exception of Brussels and Valencia where

6.3% and 5.5% of gestational ages were missing respectively.

For countries included in the analyses, we excluded missing data

from our primary analyses as this would reflect the reality if these

cut-offs were used, but we also did a second set of analyses with

missing data distributed according to observed birth weight and

gestational age distributions for live births, and fetal and neonatal

deaths separately.

Comparisons of Fetal and Neonatal Mortality Rates


Statistical AnalysisWe calculated fetal and neonatal mortality rates with 95%

confidential intervals, using both birth weight and gestational age

thresholds. We also computed differences between rates with

confidence intervals to test whether these were significant within

countries. To test whether there was a systematic difference

between countries in rates based on birth weight versus gestational

age we used the non-parametric Wilcoxon signed rank test. In

addition, we used the Wilcoxon rank sum test to assess whether

rates based on a 28-week threshold minus a 1000-gram threshold

differed significantly across countries. Finally, we tested the

correlation between these two rates using the Spearman rank test

to assess how these affected country rankings. These statistical tests

were repeated on recalculated rates after imputation of missing

observations, as described above, to ensure that the addition of

these data would not change our results. Analyses were done with

SPSS version 17.0 for Windows (SPSS Inc, Chicago, IL, USA).

Results

Table 1 presents fetal and neonatal mortality rates using a birth

weight cut-off of 1000 grams. The range for fetal deaths was 1.6 to

4.7 per 1000 live and stillbirths and the range of neonatal deaths

was 1.1 to 4.3 per 1000 live births. Also shown are the same rates

with a gestational age cut-off of 28 weeks. They ranged from 1.7 to

4.9 per 1000 for fetal deaths and 1.3 to 4.0 per 1000 for neonatal

deaths.

Except for the Czech Republic (0.16%) and Estonia (0.21%),

where rates were 0.2 per 1000 higher with a birth weight cut-off,

most countries had higher rates of fetal deaths when a gestational

age cut-off was used, as illustrated in Figure 1. For seven out of 25

countries/regions, the two rates were very similar with minimal

differences of 0.1 per 1000 or less. The widest differences were

0.8 per 1000 in Brussels (0.82%) and France (0.76%). At an

individual country level, differences between fetal mortality rates

based on gestational age and those based on birth weight were not

significantly different from zero, except in the Netherlands where

the difference was 0.50 per 1000 with 95% confidence interval

0.09–0.91 (p = 0.018) and England and Wales where the rate

difference was 0.45 per 1000 with 95% confidence interval 0.23–

0.66 (p,0.001).

In contrast, differences between neonatal mortality rates were

minimal, with 15 out of 21 countries/regions having differences

between 20.1 and +0.1 per 1000 (Figure 1). Rates calculated with

a gestational age cut-off were not significantly higher or lower than

those with a birth weight cut-off, although in Latvia (20.35%),

Brussels (+0.27%) and Malta (+0.25%) differences were 0.25 per

1000 or more.

Differences between countries in fetal mortality rates based on

gestational age compared with those based on birth weight were

significant (p,0.001 for Wilcoxon signed rank test). The corre-

sponding neonatal mortality rates did not differ significantly

between countries (p = 0.370), however twelve countries had a

positive difference while eight had a negative and there was one

tie. In total, 8823 fetal deaths were included when a 1000-gram

threshold was used compared with 9535 with a 28-week threshold,

a difference of 712 fetal deaths (7.5% of all fetal deaths). In

contrast, the difference in neonatal deaths was minimal, 4710

using a 1000-gram threshold versus 4726 using a 28-week

threshold (a difference of 16).

Results did not change when the observed birth weight and

gestational age distributions for fetal and neonatal deaths and live

births were used to include births and deaths with missing birth

weights and gestational ages in the analyses. Fetal mortality rates

based on gestational age were still significantly higher than those

based on birth weight (p = 0.002); while the choice of a cut-off

made no difference for comparisons of neonatal mortality rates

(p = 0.380).

Fetal and neonatal mortality rates computed using a birth

weight threshold were highly correlated with rates computed using

a gestational age threshold, with Spearman rank correlations of

r= 0.952 (p,0.001, n = 25) for fetal mortality and r= 0.963

(p,0.001, n = 21) for neonatal mortality. Country rankings were

therefore similar with a few exceptions such as Brussels which

ranked sixth for birth weight and thirteenth for gestational age.

Even for the Netherlands and England and Wales, where

differences in fetal mortality rates calculated using the two

definitions were significantly different, their ranks only differed

by two places (19 and 18 out of 25 for birth weight to 21 and 20

out of 25 for gestational age, respectively (data not shown in table).

Discussion

Our analysis showed that fetal mortality rates in European

countries were higher when based on a 28-week gestational age

threshold compared with a 1000-gram birth weight threshold,

whereas the choice of a threshold made little difference for

neonatal mortality rates. These results suggest that a substantial

proportion of fetal deaths occurring at or after 28 weeks of

gestation have a birth weight under 1000-grams. Despite this

difference, however, the selection of a cut-off did not change

countries’ relative positions. The small differences between

neonatal mortality rates calculated using birth weight and

gestational age cut-offs and the similarity in rankings suggest that

differences in average birth weight between populations do not

create a bias when rates are computed using a birth weight cut-off.

There are a number of limitations to this study. Most notably its

reliance on aggregated data meant we could not cross tabulate the

birth weight and gestational age distributions of the excluded

births and deaths. Our data also date from 2004 and practices in

registration and care of very preterm infants may have changed

since this time. However, these changes most likely occurred for

births with a birth weight under 1000 grams or before 28

completed weeks of gestation which are excluded from our

analysis. At the time these data were compiled, a widespread

consensus in Europe existed about the importance of active care

for infants born at or after 28 weeks of gestation or 1000 grams or

more [21]. Furthermore, in all countries live and stillbirths born at

these thresholds were included in routine data collection systems

[5–7].

Another limitation relates to missing data; many countries had

some birth weight and gestational age data missing and this will

have affected absolute rates. While we excluded countries with

highly divergent proportions of birth weight and gestational age

data missing, some countries still had more data missing among

deaths than among live births. Missing data could be more

prevalent among extremely preterm or very low birth weight

babies, which would limit their influence on analyses of rates using

28 weeks or 1000 grams thresholds. Because we were using

aggregated data, we were limited in our ability to investigate this

further. However, even if this were not the case, these missing data

are unlikely to change our conclusions. This was shown when we

repeated our analyses including missing data based on observed

distributions of birth weight and gestational age for fetal and

neonatal deaths and live births. Nonetheless, this analysis showed

that proportions of missing gestational age and birth weight varied

between countries and this may have an impact on the comparison

of mortality rates when these thresholds are used, regardless of the



choice of threshold. These proportions should be reported in

comparative analyses.

Finally, while the Euro-Peristat project requests data based on

the best obstetric estimate of gestational age in weeks from clinical

records, it was not possible to evaluate differences in the ways in

which participating countries actually measure gestational age. In

most European countries, however, dating ultrasounds are a

standard component of care during pregnancy and most women

have their first antenatal visit in the first trimester [22–24].

Using a birth weight cut-off of 1000 grams resulted in 712 fewer

fetal deaths overall compared with using a cut-off of 28 completed

weeks of gestation leading to systematically lower fetal death rates.

A previous review also suggested that stillbirth rates were higher

using gestational age limits based on Norwegian data showing that

a 500 grams cut-off point excluded more stillbirths than a 22 week

cut-off point; neonatal deaths were not included in this study [4].

By comparing neonatal deaths with fetal deaths, our results show

that this effect specifically relates to stillbirths and does not reflect

the gestational age and birth weight distribution of all births.

There are several possible explanations for this finding. First,

using a birth weight cut-off may exclude growth restricted fetuses.

As concluded by a recent review of stillbirths in high-income

countries, small for gestational age is the pregnancy condition with

the highest population attributable risk (measured at one out of

four for stillbirths) [25]. Fetal growth restriction is a particularly

important risk factor for antepartum deaths, which constitute over

80% of fetal deaths in high-income countries [4]. Second, fetal

weight loss after antepartum death may also contribute to lower

birth weights, although the extent of this phenomenon is still

unknown [26]. Finally, some deaths may predate delivery and this

would lead to lower average birth weights for stillbirths. More

detailed analysis of stillbirths with a gestational age of 28 weeks

and over, but birth weights under 1000 grams is needed to better

understand the relative contribution of these different explana-

tions.

While growth restriction is also a risk factor for neonatal death,

the magnitude of the association may be less strong, especially in

the gestational age and birth weight bands considered in this

analysis. Recent studies in France and New Zealand found that

17% and 13% of all neonatal deaths were below the tenth

percentiles of national standards [27,28]. This compared to studies

of stillbirth where between 40% and 60% are associated with

Table 1. Fetal mortality rates per 1000 total births and neonatal mortality rates per 1000 live births with 95% confidence intervals[CI].

Fetal mortality Neonatal mortality

Birth weight $1000 grams Gestational age $28 weeks Birth weight $1000 grams Gestational age $28 weeks

Country/region Total births Rate [95% CI] Total births Rate [95% CI] Live births Rate [95% CI] Live births Rate [95% CI]

Austria 78820 2.33 [2.0–2.7] 78794 2.49 [2.1–2.8] 78636 1.44 [1.2–1.7] 78598 1.39 [1.1–1.6]

Belgium: Brussels 15752 2.54 [1.8–3.3] 15176 3.36 [2.4–4.3] 15712 1.91 [1.2–2.6] 15125 2.18 [1.4–2.9]

Belgium: Flanders 60642 2.67 [2.3–3.1] 60679 2.85 [2.4–3.3] 60480 1.37 [1.1–1.7] 60506 1.39 [1.1–1.7]

Czech Republic 97544 2.56 [2.2–2.9] 97480 2.40 [2.1–2.7] 97294 1.12 [0.9–1.3] 97365 1.25 [1.0–1.5]

Estonia 13945 3.37 [3.3–4.3] 13939 3.16 [2.2–4.1] 13898 2.52 [1.7–3.4] 13895 2.66 [1.8–3.5]

Finland 57482 1.97 [1.6–2.3] 57407 2.04 [1.7–2.4] 57369 1.20 [0.9–1.5] 57290 1.29 [1.0–1.6]

France 14551 4.12 [3.1–5.2] 14540 4.88 [3.8–6.0] 761290 1.50 [1.4–1.6] 765752 1.48 [1.4–1.6]

Germany 644654 2.39 [2.3–2.5] 645401 2.55 [2.4–2.7]

Hungary 94801 3.55 [3.2–3.9] 94900 3.73 [3.3–4.1]

Ireland 62077 3.82 [3.3–4.3] 62097 4.28 [3.8–4.8]

Latvia 20393 4.71 [3.8–5.6] 20382 4.86 [3.9–5.8] 20297 4.34 [3.4–5.2] 20283 3.99 [3.1–4.9]

Lithuania 29510 3.83 [3.1–4.5] 29502 3.93 [3.2–4.6] 29397 2.89 [2.3–3.5] 29386 2.93 [2.3–3.5]

Luxembourg 5296 2.45 [1.1–3.8] 5384 2.79 [1.4–4.2] 5283 1.51 [0.5–2.6] 5369 1.30 [1.7–5.5]

Malta 3889 3.86 [1.9–5.8] 3894 3.85 [1.9–5.8] 3874 3.36 [1.5–5.2] 3879 3.61 [1.7–5.5]

The Netherlands 181014 3.77 [3.5–4.1] 178710 4.27 [4.0–4.6] 180332 1.96 [1.8–2.2] 177947 1.93 [1.7–2.1]

Norway 57450 2.75 [2.3–3.2] 57004 2.84 [2.4–3.3] 56911 1.32 [1.0–1.6] 56925 1.35 [1.1–1.7]

Poland 356571 3.54 [3.3–3.7] 356734 3.77 [3.6–4.0] 355307 2.92 [2.7–3.1] 355389 3.00 [2.8–3.2]

Portugal 108948 2.64 [2.3–2.9] 109136 2.69 [2.4–3.0] 108660 1.51 [1.3–1.7 108842 1.45 [1.2–1.7]

Slovenia 17840 3.48 [2.6–4.3] 17849 3.53 [2.7–4.4] 17778 1.29 [0.8–1.8] 17786 1.35 [0.8–1.9]

Slovak Republic 52301 1.63 [1.3–2.0] 52332 1.66 [1.3–2.0] 52216 1.63 [1.3–2.0] 52245 1.70 [1.3–2.1]

Spain: Valencia 49505 2.95 [2.5–3.4] 48279 3.11 [2.6–3.6] 49359 1.22 [0.9–1.5] 48129 1.25 [0.9–1.6]

Sweden 99928 2.87 [2.5–3.2] 100111 3.16 [2.8–3.5]

UK: England and Wales 637653 3.68 [3.5–3.8] 637521 4.13 [4.0–4.3] 640374 1.59 [1.5–1.7] 637521 1.59 [1.5–1.7]

UK: Northern Ireland 22351 3.62 [2.8–4.4] 22355 3.76 [3.0–4.6] 22270 1.53 [1.0–2.0] 22271 1.44 [0.9–1.9]

UK: Scotland 52907 4.06 [3.5–4.6] 52860 4.58 [4.0–5.2] 52692 1.54 [1.2–1.9] 52618 1.48 [1.2–1.8]

Cyprus and Greece (no data on fetal and neonatal death by birth weight and gestational age), Germany, Hungary, Ireland and Italy (no data on neonatal death by birthweight and gestational age), Denmark and Italy (excluded from fetal death comparisons, because of highly divergent missing data on birth weight versus gestationalage), Denmark and Sweden (excluded from neonatal death comparisons, because of highly divergent missing data on birth weight versus gestational age).doi:10.1371/journal.pone.0064869.t001



growth restriction [29]. Growth restriction in this context reflects a

wide range of underlying pregnancy complications which contrib-

ute to poor growth and adverse perinatal outcomes.

ConclusionsIn the European countries included in our analysis, fetal

mortality rates calculated using a threshold of 28 weeks of

gestation were higher than those based on birth weight cut-offs of

1000 grams, probably due in part to the role of intra-uterine

growth restriction in antepartum fetal deaths. Assessing the health

burden of third trimester fetal deaths using a cut-off based on

gestational age provides valuable additional information. Com-

parisons based on this cut-off are possible in countries where a

clinical estimate of gestational age is recorded in routine data

sources and where women have access to early antenatal care and

dating ultrasound as is the case in European and other high-

income countries.


Table S1 Data sources used for data on live births, fetaland neonatal deaths in Europe in 2004.

(DOCX)

Table S2 Percentage of missing birth weights (BW) andgestational ages (GA). *Denmark (fetal and neonatal mortal-

ity), Italy (fetal mortality) and Sweden (neonatal mortality) were

excluded from analysis because of substantial difference in missing

data by birth weight and gestational age. Proportions of 5% and

over missing data are presented in bold.

(DOCX)

Acknowledgments

The members of the Euro-Peristat Scientific Committee are: Gerald

Haidinger, Department of Epidemiology, The Medical University of

Vienna (Austria); Sophie Alexander, School of Public Health, Universite

Libre de Bruxelles (Belgium); Pavlos Pavlou, Health Monitoring Unit,

Ministry of Health (Cyprus); Petr Velebil, Institute for the Care of Mother

and Child, Perinatal Centre Prague (Czech Republic); Jens Langhoff Roos,

Obstetrics Clinic Rigshospitalet, Copenhagen University (Denmark); Luule

Sakkeus, Estonian Institute for Population Studies, Tallinn University

(Estonia); Mika Gissler, THL National Institute for Health and Welfare

(Finland); Beatrice Blondel, Epidemiological Research Unit on Perinatal

and Women’s and Children’s Health, INSERM UMRS 953, Universite

Pierre-et-Marie Curie Paris6 (France); Nicholas Lack, Bavarian Working

Group for Quality Assurance (Germany); Aris Antsaklis, Department of

Obstetrics and Gynaecology, Athens University (Greece); Istvan Berbik,

Department of Obstetrics and Gynaecology, Vaszary Kolos Teaching

Hospital (Hungary); Sheelagh Bonham, National Perinatal Reporting

Scheme, Economic and Social Research Institute (Ireland); Marina

Cuttini, Unit of Epidemiology, Pediatric Hospital of Baby Jesus (Italy);

Janis Misins, Center for Disease Prevention and Control (Latvia); Jone

Jaselioniene, Department Epidemiology and Biostatistics, Institute of

Hygiene (Lithuania); Yolande Wagener, Department of Health, Ministry

of Health (Luxembourg); Miriam Gatt, Department of Health Information

and Research, National Obstetric Information Systems (NOIS) Register

(Malta); Jan Nijhuis, Department Obstetrics and Gynaecology, Maastricht

University Medical Centre (The Netherlands); Kari Klungsoyr, Medical

Birth Registry of Norway, University of Bergen (Norway); Katarzyna

Szamotulska, Department of Epidemiology, National Research Institute of

Mother and Child (Poland); Henrique Barros, Department of Hygiene and

Epidemiology, University of Porto Medical School (Portugal); Maria

Chmelova, National Health Information Centre (Slovak Republic); Ziva

Novak-Antolic, Perinatology Unit, University Medical Center (Slovenia);

Francisco Bolumar, Department of Health Sciences and Social Medicine,

University of Alcala (Spain); Karin Gottvall, Department of Statistics,

Monitoring and Evaluation, The National Board of Health and Welfare,

(Sweden); Alison Macfarlane, Maternal and Child Health Research

Centre, City University London (United Kingdom).

Figure 1. Differences in mortality rates based on gestational age $28 weeks minus birth weight $500 grams. Austria (AT), Brussels (BE:BR), Flanders (BE: FL), Cyprus (CY), Czech Republic (CZ), Denmark (DK), Estonia (EE), Finland (FI), France (FR), Germany (DE), Greece (GR), Hungary (HU),Ireland (IE), Italy (IT), Latvia (LV), Lithuania (LT), Luxembourg (LU), Malta (MT), the Netherlands (NL), Norway (NO), Poland (PL), Portugal (PT), Slovenia(SI), Slovak Republic (SK), Valencia region of Spain (ES), Sweden (SE), and the United Kingdom (UK): England and Wales combined (UK: EW), NorthernIreland (UK: NI), and Scotland (UK: SC).doi:10.1371/journal.pone.0064869.g001



The authors acknowledge the following contributors to the 2008

European Perinatal Health Report: Austria Christian Vutuc, Abteilung

fur Epidemiologie Zentrum fur Public Health der Med. Univ. Wien;

Jeannette Klimont, Statistics Austria; Belgium Sophie Alexander, Wei-

Hong Zhang, Universite Libre de Bruxelles, School of Public Health,

Reproductive Health Unit; Guy Martens, Study Center for Perinatal

Epidemiology (SPE), Edwige Haelterman, Myriam De Spiegelaere,

Brussels Health and Social Observatory; Cyprus Pavlos Pavlou, Maria

Athanasiadou, Ministry of Health, Health Monitoring Unit; Andreas

Hadjidemetriou, Christina Karaoli, Neonatal Intensive Care Unit,

Makarios III Hospital; Czech Republic Petr Velebil, Institute for the

Care of Mother and Child, Vit Unzeitig, Department of Obstetrics and

Gynecology, Masaryk University Brno; Denmark Jens Langhoff Roos,

Obstetrics Clinic, Rigshospitalet, Copenhagen University; Steen Rasmus-

sen, Sundhedsstyrelsen National Board of Health; Estonia Luule Sakkeus,

Kati Karelson, Mare Ruuge, National Institute for Health Development,

Department of Health Statistics; Finland Mika Gissler, National Research

and Development Centre for Welfare and Health (STAKES); Anneli Pouta

National Public Health Institute (KTL), Department of Child and

Adolescent Health; France Beatrice Blondel, Marie-Helene Bouvier-

Colle, Gerard Breart, Jennifer Zeitlin, Meagan Zimbeck, INSERM U953;

Christine Cans, SCPE Service d’Information et d’Informatique Medicale

(SIIM); Germany Nicholas Lack, Bavarian Working Group for Quality

Assurance, Klaus Doebler, Federal Quality Assurance Office BQS;

Greece Aris Antlaklis, Peter Drakakis, Athens University, Department

of Obstetrics and Gynecology, Division of Maternal and Fetal Medicine;

Hungary Istvan Berbik, Vaszary Kolos Teaching Hospital, Department

of Obstetrics and Gynecology; Istvan Szabo, Department of Obstetrics and

Gynaecology, Medical Faculty, Scientific University of Pecs; IrelandSheelagh Bonham, Jacqueline O’Reilly, Economic and Social Research

Institute (ESRI); Italy Marina Cuttini, Pediatric Hospital of Baby Jesus,

Unit of Epidemiology; Sabrina Prati, Cinzia Castagnaro, Silvia Bruzzone,

Marzia Loghi, Istituto Nazionale di Statistica, ISTAT; Latvia Jautrite

Karaskevica, Irisa Zile, Health Statistics and Medical Technologies State

Agency; Ilze Kreicberga, Riga Maternity Hospital; Lithuania Aldona

Gaizauskiene, Kotryna Paulauskiene, Lithuanian Health Information

Centre; Luxembourg Yolande Wagener, Ministere de la Sante, Direction

de la Sante, Division de la Medecine Preventive et Sociale; Malta Miriam

Gatt, Kathleen England, Department of Health Information and

Research; Raymond Galea, Department of Obstetrics and Gynecology,

University of Malta; The Netherlands Sabine Anthony, Simone

Buitendijk, Ashna Mohangoo, Ab Rijpstra, TNO Quality of Life,

Department Prevention and Care, Section Reproduction and Perinatology,

Leiden; Jan Nijhuis, Maastricht University Medical Center, Department of

Obstetrics and Gynecology; Chantal Hukkelhoven, The Netherlands

Perinatal Registry; Norway Lorentz Irgens, Kari Klungsoyr Melve,

University of Bergen, Medical Birth Registry of Norway; Jon Gunnar

Tufta, Medical Birth Registry of Norway; Poland Katarzyna Szamo-

tulska, Department of Epidemiology, National Research Institute of

Mother and Child; Bogdan Chazan, Holy Family Hospital; PortugalHenrique Barros, Sofia Correia, University of Porto Medical School,

Department of Hygiene and Epidemiology; Slovak Republic Jan Cap,

Jarmila Hajnaliova, National Health Information Center; Slovenia Ziva

Novak-Antolic, Ivan Verdenik, University Medical Centre, Perinatology

Unit, Polonca Truden-Dobrin, Center for Health and Health Care

Research, Institute of Public Health of the Republic of Slovenia; SpainFrancisco Bolumar, Universidad de Alcala Facultad de Medecina; Ramon

Prats, Departament de Salut Direccio General Salut Publica; Carmen

Barona, Perinatal Health Unit Public Health Board, Isabel Rıo, CIBER

Epidemiologıa y Salud Publica (CIBERESP); Sweden Gunilla Lindmark,

IMCH, Akademiska sjukhuset; Milla Bennis, National Board of Health and

Welfare; United Kingdom, Alison Macfarlane, Nick Drey, City

University London; Angela Bell, Health Promotion Agency for Northern

Ireland CEMACH; Jim Chalmers, Etta Shanks, Information Services

Division, NHS National Services Scotland; Di Goodwin, Kath Moser,

Nirupa Dattani, Office for National Statistics; Gwyneth Thomas, Health

Statistics and Analysis Unit, Statistical Directorate, Welsh Assembly

Government.

Author Contributions

Conceived and designed the experiments: ADM JZ. Performed the

experiments: ADM JZ. Analyzed the data: ADM JZ. Contributed

reagents/materials/analysis tools: ADM JZ Euro-Peristat Scientific

Committee Members. Wrote the paper: ADM JZ. Substantially comment-

ed on the manuscript: BB MG PV AM. Provided the data and commented

on the final draft of the manuscript: Euro-Peristat Scientific Committee

Members.

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Gestational Age Patterns of Fetal and Neonatal Mortalityin Europe: Results from the Euro-Peristat ProjectAshna D. Mohangoo1*, Simone E. Buitendijk1, Katarzyna Szamotulska2, Jim Chalmers3, Lorentz M.

Irgens4, Francisco Bolumar5, Jan G. Nijhuis6, Jennifer Zeitlin7,8, the Euro-Peristat Scientific Committee"

1 Department Child Health, TNO Netherlands Organization for Applied Scientific Research, Leiden, The Netherlands, 2 Department of Epidemiology, National Research

Institute of Mother and Child, Warsaw, Poland, 3 Information Services Division, NHS National Services Scotland, Edinburgh, Scotland, 4 Department of Public Health and

Primary Health Care, University of Bergen and Medical Birth Registry of Norway, Norwegian Institute of Public Health, Norway, 5 Department of Public Health Sciences,

University of Alcala, Madrid, Spain, 6 Maastricht University Medical Center, GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands,

7 INSERM, UMRS 953, Epidemiological Research Unit on Perinatal and Women’s and Children’s Health, Paris, France, 8 UPMC Univ Paris 06, Paris, France

Abstract

Background: The first European Perinatal Health Report showed wide variability between European countries in fetal (2.6–9.1%) and neonatal (1.6–5.7%) mortality rates in 2004. We investigated gestational age patterns of fetal and neonatalmortality to improve our understanding of the differences between countries with low and high mortality.

Methodology/Principal Findings: Data on 29 countries/regions participating in the Euro-Peristat project were analyzed.Most European countries had no limits for the registration of live births, but substantial variations in limits for registration ofstillbirths before 28 weeks of gestation existed. Country rankings changed markedly after excluding deaths most likely to beaffected by registration differences (22–23 weeks for neonatal mortality and 22–27 weeks for fetal mortality). Countries withhigh fetal mortality $28 weeks had on average higher proportions of fetal deaths at and near term ($37 weeks), whileproportions of fetal deaths at earlier gestational ages (28–31 and 32–36 weeks) were higher in low fetal mortality countries.Countries with high neonatal mortality rates $24 weeks, all new member states of the European Union, had highgestational age-specific neonatal mortality rates for all gestational-age subgroups; they also had high fetal mortality, as wellas high early and late neonatal mortality. In contrast, other countries with similar levels of neonatal mortality had varyinglevels of fetal mortality, and among these countries early and late neonatal mortality were negatively correlated.

Conclusions: For valid European comparisons, all countries should register births and deaths from at least 22 weeks ofgestation and should be able to distinguish late terminations of pregnancy from stillbirths. After excluding deaths mostlikely to be influenced by existing registration differences, important variations in both levels and patterns of fetal andneonatal mortality rates were found. These disparities raise questions for future research about the effectiveness of medicalpolicies and care in European countries.

Citation: Mohangoo AD, Buitendijk SE, Szamotulska K, Chalmers J, Irgens LM, et al. (2011) Gestational Age Patterns of Fetal and Neonatal Mortality in Europe:Results from the Euro-Peristat Project. PLoS ONE 6(11): e24727. doi:10.1371/journal.pone.0024727

Editor: Philippa Middleton, The University of Adelaide, Australia

Received March 18, 2011; Accepted August 19, 2011; Published November 16, 2011

Copyright: � 2011 Mohangoo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The results from this study are based on data from the Euro-Peristat project, a European project for monitoring and evaluating perinatal outcomes onthe European level. The Euro-Peristat project was co-financed by the European Commission (DG-SANCO), grant number 2003131. The funders had no role in studydesign, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding was received for this study.

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: [email protected]

" For a list of Euro-Peristat Scientific Committee members, please see the Acknowledgments.

Introduction

In December 2008, the Euro-Peristat network produced the first

European Perinatal Health Report (EPHR) with data from 25

participating EU member states and Norway [1]. This report

showed great variations between European countries in fetal and

neonatal mortality rates in 2004 [1–3]. The highest mortality rates

were approximately 3.5 times higher than the lowest. Fetal

mortality rates ranged from 2.6 to 9.1 per 1000 total births, and

neonatal mortality rates from 1.6 to 5.7 per 1000 live births. The

EPHR also showed that, despite efforts of the World Health

Organization (WHO) to promote the use of common inclusion

criteria, there were still substantial differences in limits for

registration of live and stillbirths in Europe in 2004, especially

stillbirths [4]. These registration differences could be one

explanation for the observed variability between countries.

Preterm birth is an important risk factor for mortality during the

perinatal period and a key to understanding the etiology of both

fetal and neonatal deaths. One of the recommendations of the

Euro-Peristat project was therefore to collect and present data on

fetal and neonatal mortality by gestational age to allow for

exclusion of gestational age groups when differences in registration

are most marked and to permit more meaningful analysis of

variations between countries by comparing gestational age-specific

mortality rates. Differences in health care policies and practices

may contribute to the variation in observed fetal and neonatal

mortality rates by gestational age, including, for instance, policies

related to screening and terminations for congenital anomalies [5–

PLoS ONE | www.plosone.org 1 November 2011 | Volume 6 | Issue 11 | e24727

6]. In countries where terminations are not legal, some babies with

severe congenital anomalies probably die at later gestational ages

either during pregnancy or during the neonatal period. In other

countries, these pregnancies are more likely to be terminated at

earlier gestational ages. Furthermore, prevention strategies for

reducing mortality may differ for very preterm versus at and near

term births between European countries. For instance, programs

to improve the regionalization of perinatal care can contribute to

reduced mortality in the very preterm population [7].

The aim of this study was to analyze gestational age-related

differences in fetal and neonatal mortality between countries in

order to assess which part of inter-country variation is due to

variations in registration of births and deaths and which part is due

to real differences in health and quality of care. We also sought to

improve our understanding of differences between low versus high

mortality countries by identifying patterns of mortality by

gestational age. The following research questions will be

addressed: (i) How did preterm deaths, and in particular early

preterm deaths, contribute to differences in the variability of fetal

and neonatal mortality rates? (ii) Were absolute mortality rates

associated with a specific pattern? That is, did countries with low

mortality rates have higher proportions of preterm deaths (which

might be considered less preventable) and did high mortality

countries have higher proportions of at and near term deaths? (iii)

How did the timing of mortality (fetal/early neonatal/late

neonatal) differ in countries with high versus low mortality?

Methods

This study was embedded within the Euro-Peristat project,

which developed a list of valid and reliable indicators for

monitoring and evaluating perinatal health in the European

Union [8]. Twenty-five EU member states and Norway partici-

pated. Detailed information on the design and methods of the

Euro-Peristat project is available elsewhere [4,9–10].

Data collection was coordinated in the Netherlands. Data about

29 countries/regions for the year 2004 were analyzed: Austria (AT),

Belgium (BE): regions Brussels (BE.BR) and Flanders (BE.FL),

Cyprus (CY), Czech Republic (CZ), Denmark (DK), Estonia (EE),

Finland (FI), France (FR), Germany (DE), Greece (GR), Hungary

(HU), Ireland (IE), Italy (IT), Latvia (LV), Lithuania (LT),

Luxembourg (LU), Malta (MT), the Netherlands (NL), Norway

(NO), Poland (PL), Portugal (PT), Slovenia (SI), Slovakia (SK),

Spain or the Valencia region of Spain (ES), Sweden (SE), and the

United Kingdom (UK): England and Wales combined (UK.EW),

Northern Ireland (UK.NI), and Scotland (UK.SC).

Euro-Peristat definitionsWithin Euro-Peristat the fetal mortality rate is defined as the

number of deaths before or during birth at or after 22 completed

weeks of gestation in a given year per 1000 live and stillbirths in

the same year. The neonatal mortality rate is defined as the

number of deaths during the neonatal period (day 0 to 27) at or

after 22 completed weeks of gestation in a given year expressed per

1000 live births in the same year. Early preterm deaths were

defined as deaths that occurred at 22–27 weeks of gestation, and at

and near term deaths as deaths at 37 weeks and above.

Availability of fetal and neonatal mortalityIf participating countries/regions were unable to provide

numbers on fetal and neonatal mortality according to the Euro-

Peristat definition, the local definition was used. Cyprus provided

no data on fetal mortality, and the data from Greece and Italy

were for 2003. Information on fetal deaths with and without TOP

was collected afterwards, when it appeared that TOP were not

systematically included as fetal deaths.

All countries/regions provided data on neonatal mortality.

Ireland provided data only on early neonatal mortality and

Germany only on early neonatal mortality by gestational age.

Cyprus, the Czech Republic, Greece, Hungary, and Italy provided

no data on neonatal mortality by gestational age.

Spanish data by gestational age came only from the Valencia

region. Data from France by gestational age was based on several

sources: a one-week national perinatal survey that was conducted

in October 2003, vital registration, and neonatal death certificates.

Data on the gestational age distribution for live births from

England and Wales related to 2005, since these data were not

available at a national level before. Detailed information on the

data sources used is presented in Table S1.

Statistical analysisThe annual number of births ranged from 3902 to 774 870.

France, Germany, England and Wales, and Italy were among the

countries with more than 500 000 births, while Malta, Luxem-

bourg, and Cyprus had less than 10 000. We therefore calculated

confidence intervals using the binomial distribution to deal with

statistical variation of observed mortality rates between countries.

Rates were not calculated if there were fewer than 10 births. Rates

based on fewer than 10 deaths are noted in the tables.

Low and high mortality countries were defined by choosing the

25th and 75th percentiles respectively as cut-off levels. Differences in

the proportions of fetal/neonatal deaths between low versus high

mortality countries were tested with the x2-test. We used the non-

parametric Spearman test to assess correlations and thus minimize

the effects of outliers. Spearman’s rho (r) was used to interpret the

strength of correlations. All analyses were performed with SPSS

version 17.0 for Windows (SPSS Inc, Chicago, IL, USA).

Results

Registration of live and stillbirthsTable 1 shows that most European countries had no limits for

registration of live births in 2004, but that the legal limits for

registration of stillbirths varied substantially. In some countries

stillbirths weighing less than 500 grams were not registered, while

other countries had a legal gestational age limit of 24 or even 28

weeks. Because of this Hungary and Sweden could not adhere to the

Euro-Peristat definition of 22 completed weeks of gestation for

stillbirths in 2004. Voluntary notification of late fetal deaths at 22–

23 weeks existed in the United Kingdom and Portugal and therefore

Portugal, Northern Ireland, and Scotland were able to include these

deaths in their data. Italy and Luxembourg had a legal limit for

registration of 180 days of pregnancy, but late fetal deaths starting at

22 weeks were available in the register of spontaneous abortions and

were included. Table 1 also indicates that most countries did not

include TOP as fetal deaths. Exceptions were France, the Nether-

lands and Scotland. Elsewhere TOP were registered separately and

not included in national mortality statistics.

Variation in fetal and neonatal mortality ratesA large range was observed for overall fetal (2.6–9.1%) and

neonatal (1.6–5.7%) mortality rates in the 28 participating

countries/regions, as shown in Table 2. In these countries/

regions, 25 360 fetal deaths and 4 733 268 births, and 14 212

neonatal deaths and 4 713 200 live births were registered. The

proportion of fetal deaths represented by TOP varied between

countries, as measured by supplemental data provided by a few

countries (data not shown in table). If TOP were included as fetal

Patterns of Fetal and Neonatal Mortality in Europe


deaths, the fetal mortality rate would have increased from 5.7% to

5.9% in England and Wales (3.3% were TOP), from 3.2% to

3.7% in Finland (16% were TOP), and from 5.4% to 6.9% in

Italy (28% were TOP). After excluding TOP, the fetal mortality

rate in Scotland would have declined from 6.7% to 6.6% (2.5%

were TOP), and the Netherlands estimated that their fetal

mortality rate would have declined from 7.0% to 6.8% after

excluding TOP (2.9% were TOP).

Exclusion of early preterm deathsFigure 1 illustrates fetal and neonatal mortality rates by

gestational-age subgroups and ranks countries by their mortality

rate at 28 weeks and over. Excluding early preterm deaths reduced

the range of fetal mortality rates quite substantially, while a

moderate reduction was observed for neonatal mortality rates. For

many countries, deaths before 28 weeks of gestation accounted for

a substantial proportion of all deaths. Countries with the highest

overall fetal mortality rates did not necessarily have the highest

fetal mortality rates at or after 28 weeks of gestation, and not all

countries with the highest neonatal mortality rates had the highest

neonatal mortality rates at or after 28 weeks of gestation. The fetal

mortality rate declined dramatically for France when fetal deaths

at 22–27 weeks were excluded and removing neonatal deaths at

22–23 weeks led to a large decline in neonatal mortality rates in

the Netherlands, Northern Ireland, and England and Wales.

Adjusted proportions of fetal and neonatal deathsFigure 2 presents the percentage of fetal and neonatal deaths in

each gestational age subgroup after excluding fetal deaths at 22–27

weeks and neonatal deaths at 22–23 weeks. The percentage of fetal

Table 1. Criteria for registration of live births and stillbirths and inclusion of terminations of pregnancy in Europe in 2004.

Live births Stillbirths TOP included

TOP included in aseparate datasystem

Austria No limit $500 grams No No

BE: Brussels No limit $22 weeks or $500 grams No No

BE: Flanders No limit $500 grams No No

Cyprus No limit No data available No data available

Czech Republic $500 grams or any birth weightsurviving the first 24 hours

$22 weeks No Yes

Denmark No limit $22 weeks No Yes

Estonia No limit $22 weeks or $500 grams No Yes

Finland No limit $22 weeks or $500 grams No Yes

France $22 weeks or $500 grams $22 weeks or $500 grams Yes No

Germany No limit $500 grams No Yes

Greece No limit legal limit of $28 weeks No No

Hungary No limit $24 weeks or $500 grams No Yes

Ireland No limit $24 weeks or $500 grams TOP is not legal and not performed

Italy No limit 180 days No Yes

Latvia No limit $22 weeks No Yes

Lithuania $22 weeks $22 weeks No Yes

Luxembourg No limit 180 days No No

Malta No limit $22 weeks or $500 grams TOP is illegal and not performed

The Netherlands $22 weeks or $500 grams $24 weeks for civil registration$16 weeks for perinatal registry

Yes Yes

Norway $12 weeks $12 weeks No Yes

Poland $500 grams $500 grams No Yes

Portugal No limit $24 weeks No No

Slovakia No limit $22 weeks or $500 grams No Yes

Slovenia No limit $500 grams No Yes

Spain No limit $26 weeks (national)$22 weeks (region Valencia)

No Yes

Sweden No limit $28 weeks No Yes

UK: England and Wales No limit legal limit of $24 weeks voluntarynotification at 22–23 weeks

Yes Yes

UK: Northern Ireland No limit legal limit of $24 weeks voluntarynotification at 22–23 weeks

TOP is not legal*

UK: Scotland No limit legal limit of $24 weeks voluntarynotification at 22–23 weeks

Yes Yes

*The legislation which legalised abortion in the rest of the United Kingdom does not cover Northern Ireland, but TOP are occasionally done there under case law.doi:10.1371/journal.pone.0024727.t001



deaths in each gestational age subgroup differed significantly

between low and high fetal mortality countries (p,0.001). On

average, low fetal mortality countries had higher percentages of

their fetal deaths at earlier gestational ages (at 28–31 weeks 24.5%

vs. 22.9%, at 32–36 weeks 36.3% vs. 32.9%), while high fetal

mortality countries had higher percentages at and near term (44.2%

vs. 39.2%). In contrast, the percentage of neonatal deaths in each

gestational age subgroup did not differ significantly between low

and high neonatal mortality countries (p = 0.112): at 24–27 weeks

(30.0% vs. 31.7%), at 28–31 weeks (17.4% vs. 19.5%), at 32–36

weeks (18.5% vs. 19.6%), and at 37+ weeks (34.1% vs. 29.2%).

Indeed, on average, high neonatal mortality countries had lower

percentages of neonatal deaths at and near term.

Gestational age-specific neonatal mortality ratesTable 3 provides data on gestational age-specific neonatal

mortality for those countries that could provide both numerator

and denominator data for the gestational age distribution.

Substantial variation existed within all gestational age subgroups,

even when rates based on small denominators were excluded.

Countries with high neonatal mortality rates at or after 24 weeks of

gestation (Latvia, Poland, Malta, Lithuania, and Estonia) often had

the highest gestational age-specific neonatal mortality rates for all

gestational age subgroups, except at 22–23 weeks. Some countries

stood out in some subgroups. The Netherlands, for instance, had

high rates at 22–23 weeks and at 24–27 weeks, while Denmark

had high rates at 22–23 weeks and at 37+ weeks.

Correlation between fetal and neonatal mortality ratesAlthough fetal mortality rates at or after 28 weeks and neonatal

mortality rates at or after 24 weeks were significantly correlated

(r= 0.646; p = 0.001), different patterns were observed for low

versus high neonatal mortality countries. Figure 3 shows that high

neonatal mortality countries had high fetal mortality rates, but

countries with low and moderate neonatal mortality rates had

varying levels of fetal mortality. Finland, Czech Republic,

Table 2. Fetal and neonatal mortality rates in Europe in 2004.

Country/regionNumber oftotal births

Number offetal deaths

Fetal Mortality Ratesper 1000 total births

Number of livebirths

Number ofneonatal deaths

Neonatal MortalityRates per 1000 livebirths

Austria 79 229 295 3.7 [3.3–4.1] 78 934 215 2.7 [2.4–3.1]

BE: Brussels 16 288 88 5.4 [4.3–6.5] 16 200 51 3.4 [2.3–4.0]

BE: Flanders 60 921 249 4.1 [3.6–4.6] 60 672 146 2.4 [2.0–2.8]

Cyprus NA NA NA 8 309 13 1.6 [0.7–2.4]

Czech Republic 98 051 387 3.9 [3.6–4.3] 97 671 224 2.3 [2.0–2.6]

Denmark 64 853 332 5.1 [4.6–5.7] 64 521 230 3.6 [3.1–4.0]

Estonia 14 053 63 4.5 [3.4–5.6] 13 990 59 4.2 [3.1–5.3]

Finland 57 759 190 3.3 [2.8–3.8] 57 569 141 2.4 [2.0–2.9]

France 774 870 7 054 9.1 [8.9–9.3] 767 816 1968 2.6 [2.5–2.7]

Germany 648 860 2 261 3.5 [3.3–3.6] 705 622 1892 2.7 [2.6–2.8]

Greece 104 858 503 4.8 [4.4–5.2] 104 355 282 2.7 [2.4–3.0]

Hungary 95 594 476 5.0 [4.5–5.4] 95 137 423 4.4 [4.0–4.9]

Ireland 62 400 334 5.4 [4.8–5.9] 62 066 NA NA

Italy 542 003 2 937 5.4 [5.2–5.6] 539 066 1526 2.8 [2.7–3.0]

Latvia 20 492 137 6.7 [5.6–7.8] 20 355 116 5.7 [4.7–6.7]

Lithuania 29 633 153 5.2 [4.3–6.0] 29 480 136 4.6 [3.8–5.4]

Luxembourg 5 486 17 3.2 [1.6–4.6] 5 469 11 2.0 [0.8–3.2]

Malta 3 902 15 3.8 [1.9–5.8] 3 887 17 4.4 [2.3–6.4]

The Netherlands 182 279 1 273 7.0 [6.6–7.4] 181 006 631 3.5 [3.2–3.8]

Norway 57 368 257 4.5 [3.9–5.0] 57 111 118 2.1 [1.7–2.4]

Poland 358 440 1 743 4.9 [4.6–5.1] 356 697 1731 4.9 [4.6–5.1]

Portugal 109 778 422 3.8 [3.5–4.2] 109 356 280 2.6 [2.3–2.9]

Slovak Republic 52 522 134 2.6 [2.1–3.0] 52 388 134 2.6 [2.1–3.0]

Slovenia 17 946 100 5.6 [4.5–6.7] 17 846 47 2.6 [1.9–3.4]

Spain 456 029 1 438 3.2 [3.0–3.3] 454 591 1199 2.6 [2.5–2.8]

Sweden 100 474 316 3.1 [2.8–3.5] 100 158 210 2.1 [1.8–2.4]

UK: England and Wales 643 407 3 686 5.7 [5.5–5.9] 639 721 2185 3.4 [3.3–3.6]

UK: Northern Ireland 22 504 142 6.3 [5.3–7.3] 22 362 66 3.0 [2.2–3.7]

UK: Scotland 53 269 358 6.7 [6.0–7.4] 52 911 161 3.0 [2.6–3.5]

Cyprus provided no data on fetal death. Ireland only provided data on early neonatal death.Data for countries that did not adhere to the Euro-Peristat definition are presented in italics.High mortality rates (.75th quartile) are presented in bold.doi:10.1371/journal.pone.0024727.t002



Luxembourg, Norway, Spain, and Sweden, for example, all had

neonatal mortality rates of 2.0%, but their fetal mortality ranged

from 2.0% through 3.5%. The correlation between fetal and

neonatal mortality increased with increasing gestational age and

was closest when all preterm deaths were excluded (r= 0.758;

p,0.001), see Figure S1.

Correlation between early and late neonatal mortalityrates

Early and late neonatal mortality were related in different ways

in countries with high (r= 0.261; p = 0.618) versus low and

moderate (r= 20.302; p = 0.184) neonatal mortality, as Figure 4

shows. Countries with high neonatal mortality had high rates of

both early and late neonatal mortality, while different patterns

were observed in other countries: some countries had high early

neonatal mortality, but low late neonatal mortality (e.g. the

Netherlands and Denmark) and several other countries had low

early neonatal mortality and high late neonatal mortality. Early

neonatal mortality was related to total neonatal mortality in all

countries (r= 0.915; p,0.001), but late neonatal mortality was

related to total neonatal mortality only in countries with high

neonatal mortality (r= 0.812; p = 0.05), see Figure S2.

Discussion

Our analysis shows that early preterm deaths, most strongly

influenced by registration differences, contributed substantially

to the variation in fetal and neonatal mortality rates in Europe

in 2004. But even after these early preterm deaths were

excluded, fetal and neonatal mortality rates varied notably and

in all gestational age subgroups, including those at and near

term. In addition, patterns of mortality differed for the

gestational age at which highest mortality was observed and

for the association between fetal and neonatal mortality

rates.

Our study has several limitations linked to measurement and

data availability, despite efforts within Euro-Peristat to ensure

comparability in definitions and sources. The first limitation is

related to our ability to assess the completeness of registration of

early preterm births, especially stillbirths [11]. Although we were

able to describe registration rules, our lack of knowledge about the

extent to which these were applied uniformly in all countries limits

our ability to assess real fetal mortality at 22–27 weeks and real

neonatal mortality at 22–23 weeks. A related issue is the

registration of TOP, which is managed very differently from one

country to another and terminations are not always included as

fetal deaths. TOP varied from 3 to 28% of total fetal deaths in

those countries where this proportion could be computed. In

France an even larger proportion of early fetal deaths are

estimated to be TOP [12–13]. To our knowledge, this limitation

affects all stillbirth data routinely reported to international

agencies. This issue has not previously been highlighted, even

though the influence of TOP on fetal mortality rates has been

discussed in previous studies [14–15].

Figure 1. Impact of different inclusion criteria on fetal and neonatal mortality rates. Countries were sorted by mortality rate at or after 28weeks of gestation with low mortality countries listed first.doi:10.1371/journal.pone.0024727.g001



The different sources of data used by each country may also

affect comparability [4,16]. Some countries provided mortality

data from civil or perinatal registries or both, by linkage. These

differences in methods may lead to differences in coverage [4].

The number of annual births in each country also varied greatly

throughout Europe, from 3902 to 774 870, and random variability

from year to year is high when rates are based on small numbers.

In Malta, for example, the relatively high gestational age-specific

neonatal mortality rate at 28–31 weeks of 238% (5 out of 21

babies died) in 2004 fell drastically to 59% in the two subsequent

years (1 out of 17 babies died in both 2005 and 2006) [17]. In

addition, not all countries were able to provide national data;

instead, some used either representative samples or regional

population-based data. We addressed the question of small sample

sizes by calling attention to rates based on fewer than 10 deaths,

not reporting those based on fewer than 10 births, and presenting

confidence intervals.

A final limitation is related to the comparability of reported

gestational ages. Euro-Peristat requested data in completed weeks

of gestation based on the best obstetrical estimate available, but we

were unable to assess or evaluate differences in the measurement

of gestational age. Preterm birth rates may differ depending to

whether they are measured by last menstrual period or by

ultrasound [18–19]. Use of ultrasound measurements, by shifting

the entire gestational age distribution to the left, can increase the

preterm birth rate [18], but it can also decrease the rate by

Figure 2. Fetal deaths at or after 28 weeks of gestation (A) and neonatal deaths at or after 24 weeks (B) by gestational agesubgroups. Countries were sorted by fetal (A) and neonatal (B) mortality rates with low mortality countries listed first. Fetal mortality rate at or after28 weeks of gestation was calculated as follows: [(number of fetal deaths $28 weeks)/(number of total births $28 weeks)]61000. France, Latvia,Scotland, Ireland and The Netherlands had rates in the top quartile (.75th). * Percentages of fetal deaths were based on fewer than 10 events forLuxembourg and Malta, and for Estonia (at 28–31 and 32–36 weeks). Neonatal mortality rate at or after 24 weeks of gestation was calculated asfollows: [(number of neonatal deaths $24 weeks)/(number of live births $24 weeks)]61000. Latvia, Poland, Malta, Lithuania, and Estonia hadmortality rates in the top quartile (.75th). * Percentages of neonatal death were based on less than 10 events for Luxembourg and Malta, forBrussels, Estonia, and Slovenia (at 28–31 weeks and at 32–36 weeks), and for Northern Ireland (at 28–31 weeks).doi:10.1371/journal.pone.0024727.g002

Table 3. Gestational age-specific neonatal mortality rates per 1000 live births.

Country/region Gestational age in weeks

22–23 24–27 28–31 32–36 $37

Luxembourg – – * 76.9 [0.0–222] * 9.7 [0.0–20.7] * 0.6 [0.0–1.3]

Czech Republic 546 [337–754] 218 [170–266] 52.1 [36.2–68.0] 5.9 [3.9–7.9] 0.5 [0.4–0.7]

Norway 556 [326–785] 185 [126–243] 46.6 [26.1–67.0] 4.3 [2.1–6.5] 0.8 [0.6–1.1]

ES: Valencia – 302 [215–389] 67.4 [41.4–93.5] 3.5 [1.7–5.4] 0.5 [0.3–0.7]

Sweden 485 [314–655] 167 [121–212] 33.4 [19.3–47.4] 8.9 [6.4–11.4] 0.9 [0.7–1.1]

Finland 867 [745–988] 293 [216–371] 52.6 [29.0–76.3] 6.0 [3.0–8.9] 0.7 [0.5–1.0]

BE: Flanders 1000 [1000–1000] 311 [237–385] 51.5 [29.5–73.5] 7.2 [4.7–9.8] 0.6 [0.4–0.8]

Austria 867 [767–966] 230 [182–279] 37.4 [24.0–50.7] 4.1 [2.7–5.5] 0.7 [0.5–0.9]

Slovenia – 308 [182–433] * 36.5 [5.1–67.9] * 7.6 [2.4–12.9] 0.7 [0.3–1.1]

Portugal 338 [285–391] 54.9 [38.2–71.7] 6.7 [4.7–8.8] 0.7 [0.6–0.9]

France – – – – 0.8 [0.8–0.9]

UK: Northern Ireland – 244 [151–337] * 30.3 [4.1–56.5] 9.0 [3.7–14.3] 0.8 [0.4–1.2]

Slovakia 600 [352–848] 281 [203–359] 86.0 [56.6–115.4] 11.8 [7.8–15.8] 0.5 [0.3–0.7]

UK: England andWales{

903 [880–926] 237 [220–254] 36.6 [31.7–41.4] 6.1 [5.3–6.9] 0.9 [0.9–1.0]

UK: Scotland – 301 [234–367] 47.3 [27.6–67.0] 4.7 [2.4–7.0] 0.8 [0.6–1.1]

The Netherlands 976 [950–1000] 325 [282–368] 54.5 [42.2–66.7] 7.5 [5.9–9.1] 1.1 [1.0–1.3]

Denmark 947 [847–1000] 289 [220–358] 38.2 [21.3–55.0] 8.2 [5.3–11.1] 1.6 [1.3–2.0]

BE: Brussels – 320 [191–449] * 84.9 [31.8–138] * 6.6 [1.3–11.8] 1.3 [0.7–1.9]

Estonia – 321 [195–446] * 47.1 [2.0–92.1] * 8.8 [1.8–15.8] 2.1 [1.3–2.8]

Lithuania 786 [571–1000] 488 [378–597] 90.9 [49.7–132] 13.2 [6.9–19.4] 1.9 [1.4–2.4]

Malta – – * 238 [55.9–420] * 15.9 [0.4–31.3] * 1.4 [0.2–2.6]

Poland 875 [822–928] 457 [428–486] 125 [112–137] 16.2 [14.5–17.9] 1.2 [1.1–1.4]

Latvia – 477 [356–598] 82.9 [42.7–123] 15.3 [7.3–23.2] 2.7 [2.0–3.4]

Cyprus, Germany, Greece, Hungary, Ireland, and Italy had no data on neonatal death by gestational age. { Data from 2005.Countries were sorted by neonatal mortality rate at or after 24 weeks of gestation with low mortality countries listed first.High mortality rates are presented in bold (.75th quartile). Rates based on fewer than 10 deaths were denoted with *.Rates were not computed for cells with fewer than 10 births and were denoted with –.For France the number of term live births was estimated from the national perinatal survey and totals from the vital statistics data.doi:10.1371/journal.pone.0024727.t003



Figure 3. Correlation between fetal and neonatal mortality rates, after exclusion of deaths most likely influenced by registrationdifferences. High mortality countries are presented in bold. Correlation for fetal and neonatal mortality: r= 0.646 (p = 0.001).doi:10.1371/journal.pone.0024727.g003

Figure 4. Correlation between early and late neonatal mortality rates. High neonatal mortality countries are presented in bold. r= 0.261(p = 0.618) in high neonatal mortality countries versus r= 20.302 (p = 0.184) in other countries.doi:10.1371/journal.pone.0024727.g004



reducing errors in gestational age estimates [20]. In most

European countries, however, dating ultrasounds are now part

of standard care during pregnancy, and most women have their

first prenatal visit in the first trimester [1].

The Euro-Peristat project chose to collect mortality data using a

cut-off point of 22 completed weeks of gestation without a birth

weight limit, although data were also collected by birth weight to

permit calculation of rates with a lower limit of 1000 grams as

recommended by WHO for international comparisons. While the

WHO definition of the perinatal period is based on gestational age

(starting at 22 weeks of gestation), recommendations for data

collection are based primarily on birth weight (death of a fetus that

has reached a birth weight of 500 grams or if the birth weight is

unavailable, a gestational age of 22 completed weeks or a crown-

to-heel length of 24 cm is used) [21]. These international

recommendations are understandable because in many countries

valid data on gestational age simply do not exist, although it is not

clear that stillbirths are systematically weighed [22]. In Europe,

however, legislation for registering stillbirths is based largely on

gestational age. Regulations governing TOP are also specified with

respect to the length of gestation [13].

It is important to note that gestational age-specific mortality

data are not produced routinely by any international or European

agency (including EUROSTAT, OECD or WHO) and have not,

to our knowledge, ever been published in this way from routine

data. Our analyses require the collection of fetal and neonatal

(both early and late) deaths by individual week of gestation and

these are not routinely provided, even in many national

publications. A further strength of our analysis is the number of

countries that contributed.

From an analytic perspective, gestational-age based analyses are

important because they distinguish premature birth from fetal

growth restriction. Recent European cohorts of very preterm

infants are based on gestational age because of its superior

prognostic value [23] and because information on gestational age,

and not on birth weight, is available to obstetricians when making

decisions during pregnancy and delivery [24–27]. Gestational age

comparisons across Europe avoid biases related to population

differences in birth weight; European comparisons have found that

optimum birth weight, defined as the birth weight at which

mortality is lowest, varies between European countries [28].

Our analyses showed that it was necessary to exclude stillbirths

at 22–27 weeks and neonatal deaths at 22–23 weeks from

European comparisons to minimize the effect of differences in

registration requirements and TOP legislation on mortality rates.

As survival is rare for babies at 22–23 weeks, including this

gestational age group adds nearly as many deaths as births and

gives this subgroup a large weight in mortality statistics, although

they only represent about 1 in 1000 live births. These infants make

up a high proportion of fetal and neonatal deaths in some

countries. Although registration limits primarily affect fetal deaths,

fetal death registration is known to affect the completeness of live

birth registration, especially, for example, for those weighing less

than 500 grams. The limit of 500 grams primarily concerns infants

at 22–23 weeks, so excluding these infants also resolves the

problems of comparability presented by birth weight limits. By 24

weeks of gestation, most babies have a birth weight above 500

grams [29]. Some countries had substantially lower gestational

age-specific neonatal mortality at 22–23 weeks than reported in

specific studies of this population [30–31] suggesting that in some

countries many immediate neonatal deaths are simply not

registered as live births in birth registers. For fetal mortality, a

higher cut-off point was necessary to include Sweden, which only

registered fetal deaths starting at 28 weeks, as well as to deal with

problems of comparability raised by TOP notification. For valid

European comparisons of gestation-specific fetal and neonatal

mortality, all member states should aim to register fetal deaths

from 22 completed weeks of gestation, regardless of birth weight.

In July 2008, Sweden changed its limit for registration of stillbirths

from 28 to 22 completed weeks of gestation. This change will make

it possible to compare their stillbirth rates with other European

countries at earlier gestational ages in future studies.

Use of these exclusion criteria had a substantial impact on the

ranking of countries. Not all countries with the highest or lowest

mortality rates also had the highest or lowest fetal mortality rates at

or after 28 weeks or the highest or lowest neonatal mortality rates

at or after 24 weeks. It is thus very important for international

agencies to collect gestational age to allow like-with-like compar-

isons. In this light, EUROSTAT’s updated directives, which

makes provision of fetal and neonatal mortality by birth weight

voluntary for EU member states and does not even request

voluntary collection by gestational age, is a matter for concern

[32].

After exclusion of the early preterm deaths most likely to be

influenced by registration differences, the levels and patterns of

mortality still varied significantly between countries. The clearest

pattern observed was among countries with highest neonatal

mortality rates, all new member states of the European Union

(Latvia, Poland, Malta, Estonia, Lithuania, and Hungary). These

countries had high fetal mortality and high early and high late

neonatal mortality rates. This finding suggests that some of the

causes may be related to overall standards of living and resources

available to the health care system. For Poland and Malta, the

restricted availability (Poland) and illegality of TOP (Malta) may

also contribute to higher rates.

In contrast, we observed different levels of fetal mortality in

other countries with the same overall level of neonatal mortality.

Medical advances, such as antenatal steroids and surfactant for

very preterm babies, have been very successful in decreasing

neonatal mortality, perhaps contributing to more convergent

trends in neonatal mortality in countries with similar access to

these technologies. In contrast, preventing stillbirths may be more

complex. Stillbirths are strongly related to maternal social

characteristics, high body mass index and smoking [33–34]. The

prevalence of these risk factors and health system programs to

reduce their impact may differ across countries. Factors suggesting

sub-optimal care are associated with a substantial proportion of

stillbirths, especially for intrapartum deaths [35].

We also found that some countries had higher mortality in some

gestational age subgroups. Denmark, for example, had both high

proportions of fetal and neonatal deaths at 37+ weeks, and a high

gestational age-specific neonatal mortality rate at 37+ weeks, but

was not defined as a high mortality country when comparing rates

at earlier gestational ages. France, on the other hand, had the

highest fetal mortality rate at or after 28 weeks, but did not have a

high proportion of fetal deaths at and near term.

Differences in policies and practices may explain these varying

patterns of mortality. For instance, policies related to screening

and terminations for congenital anomalies differ in Europe and

can have a large impact on both fetal and neonatal mortality rates

[5–6]. TOP could be performed legally around 2004 in most

European countries, although the maximum gestational age limit

varied and the notification procedures differed. Exceptions were

Ireland, Northern Ireland and Malta, where TOP are not legal

and cannot be performed. It is possible that some pregnancies that

were found to have lethal congenital anomalies from these

countries were terminated elsewhere or that fewer of these

pregnancies were terminated; in the latter cases, these babies,



who died from the anomaly before, during or after birth, were

included in their mortality statistics. Policies related to TOP may

explain the relatively high proportion of fetal deaths at and near

term in the Netherlands, which, unlike most other European

countries in 2004, had no system for systematic early detection of

congenital anomalies through prenatal screening. On the other

hand, countries that systematically screened at earlier gestational

ages and terminated more before the registration limit necessarily

have lower mortality rates, both fetal and neonatal [13–14]. In

contrast, countries that practice terminations at or after 22 weeks

may end up with high stillbirth rates explained primarily by

terminations. France is one example [13]. Late terminations for

fetal anomalies are rare in Europe, and prevalence rates vary

between European countries [13]. Ideally, it should be possible to

remove TOP from fetal death statistics and to calculate rates with

and without TOP.

Another area where European countries differ is in policies and

attitudes to withdrawing and withholding care for preterm infants

at the limit of viability. This affects the types of care babies receive,

their survival probabilities and the timing of death [36–37].

Countries that are more likely to withhold care will have higher

mortality rates at early gestational ages; for example the Nether-

lands had high gestational age-specific neonatal mortality rates at

22–23 and at 24–27 weeks, because its active interventions for

these early preterm live births were much more limited than in

other European countries [36–37]. These policies may also affect

the proportion of infants that are live born at early gestational ages

after medically indicated cesareans [38]. Cesarean delivery rates

for infants born between 24 and 25 weeks, excluding cesareans for

maternal indications, varied from 0–78% between European

regions in 2003, for instance [39]. Without active intervention,

neonatal deaths also occur earlier. In the Netherlands, for

example, high early neonatal mortality rates but low late neonatal

mortality rates could reflect the lack of active intervention before

26 weeks of gestation [36]. Several other countries had low early

neonatal mortality rates, but high late neonatal mortality rates,

which may indicate that babies were living longer and dying in the

late neonatal period.

Finally, high mortality at and near term may reflect policies

related to the care of term pregnancies, including policies to

induce delivery for post-term infants, which may differ substan-

tially [40] and the organization of maternity services for low-risk

pregnancies which also varies greatly within Europe [41]. Having

data on causes of death and on timing of death (intrapartum or

antepartum) would add to Euro-Peristat’s capacity to explain

differences in levels and patterns of gestational age-specific

mortality and this will be a goal for future phases.

ConclusionsRegistration differences contributed notably to the variability in

fetal and neonatal mortality rates between countries. All European

countries should use common inclusion criteria for the registration

of live and stillbirths. To allow a common analysis of gestation-

specific mortality, it is important to have data starting from at least

22 completed weeks of gestation. To comply with WHO

recommendations, this would require countries to collect data

using both gestational age (22 weeks) and birth weight (500 grams)

limits, as is already done in several European countries. Countries

should also be able to calculate fetal mortality rates with and

without late TOP. Nonetheless, differences in registration criteria

do not explain the variability in mortality rates between European

countries. Routine reporting of fetal and neonatal deaths by

gestational age improves the usefulness of these data for

surveillance and policy. Providing countries with international

references for neonatal and fetal mortality by gestational age

makes it possible for them to assess their specific weaknesses and

generate ideas about how to improve outcomes. These data also

raise important questions for future research about the tradeoffs

between fetal and neonatal mortality in many countries and the

reasons for differing gestational age-specific patterns in neonatal

mortality.


Table S1 Data sources used for the Euro-Peristatproject data.

(DOC)

Figure S1 Correlation between gestation-specific fetaland neonatal mortality rates. Correlation for fetal and

neonatal mortality $22 weeks: r= 0.502 (p = 0.010). Correlation

for fetal and neonatal mortality $28 weeks: r= 0.612 (p = 0.002).

Correlation for fetal and neonatal mortality $37 weeks: r= 0.758

(p,0.001).

(TIF)

Figure S2 Correlation of early and late neonatalmortality with total neonatal mortality. High neonatal

mortality countries are presented in bold. Correlation for early

and total neonatal mortality: r= 0.915 (p,0.001). Correlation for

late and total neonatal mortality: r= 0.812 (p = 0.05) in high

neonatal mortality countries versus r= 20.210 (p = 0.362) in other

countries.

(TIF)

Acknowledgments

The Euro-Peristat Scientific Committee: Christian Vutuc (Austria), Sophie

Alexander (Belgium), Pavlos Pavlou (Cyprus), Petr Velebil (Czech

Republic), Jens Langhoff Roos (Denmark), Luule Sakkeus (Estonia), Mika

Gissler (Finland), Beatrice Blondel (France), Nicholas Lack (Germany), Aris

Antlaklis (Greece), Istvan Berbik (Hungary), Sheelagh Bonham (Ireland),

Marina Cuttini (Italy), Jautrite Karaskevica (Latvia), Jone Jaselioniene

(Lithuania), Yolande Wagener (Luxembourg), Miriam Gatt (Malta), Jan

Nijhuis (The Netherlands), Lorentz Irgens (Norway), Katarzyna Szamo-

tulska (Poland), Henrique Barros (Portugal), Maria Chmelova (Slovakia),

Ziva Novak-Antolic (Slovenia), Francisco Bolumar (Spain), Gunilla Lind-

mark (Sweden), Alison Macfarlane (United Kingdom).

The authors acknowledge the following contributors to the European

Perinatal Health Report: Austria Christian Vutuc, Abteilung fur Epide-

miologie Zentrum fur Public Health der Med. Univ. Wien; Jeannette

Klimont, Statistics Austria; Belgium Sophie Alexander, Wei-Hong Zhang,

Universite Libre de Bruxelles, School of Public Health, Reproductive

Health Unit; Guy Martens, SPE (Study Center for Perinatal Epidemiol-

ogy), Edwige Haelterman, Myriam De Spiegelaere, Brussels Health and

Social Observatory; Cyprus Pavlos Pavlou, Maria Athanasiadou, Ministry of

Health, Health Monitoring Unit; Andreas Hadjidemetriou, Christina

Karaoli, Neonatal Intensive Care Unit, Makarios III Hospital; Czech

Republic Petr Velebil, Institute for the Care of Mother and Child, Vit

Unzeitig, Department of Obstetrics and Gynecology, Masaryk University

Brno; Denmark Jens Langhoff Roos, Obstetrics Clinic, Rigshospitalet,

Copenhagen University; Steen Rasmussen, Sundhedsstyrelsen National

Board of Health; Estonia Luule Sakkeus, Kati Karelson, Mare Ruuge,

National Institute for Health Development, Department of Health

Statistics; Finland Mika Gissler, National Research and Development

Centre for Welfare and Health (STAKES); Anneli Pouta National Public

Health Institute (KTL), Department of Child and Adolescent Health;

France Beatrice Blondel, Marie-Helene Bouvier-Colle, Gerard Breart,

Jennifer Zeitlin, Meagan Zimbeck, INSERM U953; Christine Cans, SCPE

Service d’Information et d’Informatique Medicale (SIIM); Germany

Nicholas Lack, Bavarian Working Group for Quality Assurance, Klaus

Doebler, Federal Quality Assurance Office BQS; Greece Aris Antlaklis,

Peter Drakakis, Athens University, Department of Obstetrics and

Gynecology, Division of Maternal and Fetal Medicine; Hungary Istvan



Berbik, Vaszary Kolos Teaching Hospital, Department of Obstetrics and

Gynecology; Istvan Szabo, Department of Obstetric and Gynaecology,

Medical Faculty, Scientific University of Pecs; Ireland Sheelagh Bonham,

Jacqueline O’Reilly, Economic and Social Research Institute (ESRI); Italy

Marina Cuttini, Pediatric Hospital of Baby Jesus, Unit of Epidemiology;

Sabrina Prati, Cinzia Castagnaro, Silvia Bruzzone, Marzia Loghi, Istituto

Nazionale di Statistica, ISTAT; Latvia Jautrite Karaskevica, Irisa Zile,

Health Statistics and Medical Technologies State Agency; Ilze Kreicberga,

Riga Maternity Hospital; Lithuania Aldona Gaizauskiene, Kotryna

Paulauskiene, Lithuanian Health Information Centre; Luxembourg Yolande

Wagener, Ministere de la Sante, Direction de la Sante, Division de la

Medecine Preventive et Sociale; Malta Miriam Gatt, Kathleen England,

Department of Health Information and Research; Raymond Galea,

Department of Obstetrics and Gynecology, University of Malta; The

Netherlands Sabine Anthony, Simone Buitendijk, Ashna Mohangoo, Ab

Rijpstra, TNO Quality of Life, Deparment Prevention and Care, Section

Reproduction and Perinatology, Leiden; Jan Nijhuis, Maastricht Univer-

sity Medical Center, Department of Obstetrics and Gynecology; Chantal

Hukkelhoven, The Netherlands Perinatal Registry; Norway Lorentz Irgens,

Kari Klungsoyr Melve, University of Bergen, Medical Birth Registry of

Norway; Jon Gunnar Tufta, Medical Birth Registry of Norway; Poland

Katarzyna Szamotulska, Department of Epidemiology, National Research

Institute of Mother and Child; Bogdan Chazan, Holy Family Hospital;

Portugal Henrique Barros, Sofia Correia, University of Porto Medical

School, Department of Hygiene and Epidemiology; Slovakia Jan Cap,

Jarmila Hajnaliova, National Health Information Center; Slovenia Ziva

Novak-Antolic, Ivan Verdenik, University Medical Centre, Perinatology

Unit, Polonca Truden-Dobrin, Center for Health and Health Care

Research, Institute of Public Health of the Republic of Slovenia; Spain

Francisco Bolumar, Universidad de Alcala Facultad de Medecina; Ramon

Prats, Departament de Salut Direccio General Salut Publica; Carmen

Barona, Perinatal Health Unit Public Health Board, Isabel Rıo, CIBER

Epidemiologıa y Salud Publica (CIBERESP); Sweden Gunilla Lindmark,

IMCH, Akademiska sjukhuset; Milla Bennis, National Board of Health and

Welfare; United Kingdom, Alison Macfarlane, Nick Drey, Department of

Midwifery, City University London; Angela Bell, Health Promotion

Agency for Northern Ireland CEMACH; Jim Chalmers, Etta Shanks,

Information Services Division, NHS National Services Scotland; Di

Goodwin, Kath Moser, Office for National Statistics; Gwyneth Thomas,

Health Statistics and Analysis Unit, Statistical Directorate, Welsh Assembly

Government.

Author Contributions

Conceived and designed the experiments: ADM JZ. Performed the

experiments: ADM JZ. Analyzed the data: ADM. Contributed reagents/

materials/analysis tools: Euro-Peristat Scientific Members. Wrote the

paper: ADM JZ. Revised the manuscript: SEB KS JC LMI FB JGN.

Reviewed the manuscript: Euro-Peristat Scientific Members.

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Preterm birth time trends in Europe: a study of19 countriesJ Zeitlin,a,b K Szamotulska,c N Drewniak,a,b AD Mohangoo,d J Chalmers,e L Sakkeus,f L Irgens,g,h

M Gatt,i M Gissler,j,k B Blondel,a,b The Euro-Peristat Preterm Study Group*a INSERM, UMRS 953, Epidemiological Research Unit on Perinatal and Women’s and Children’s Health, Paris, France b UPMC, Paris, Francec Department of Epidemiology, National Research Institute of Mother and Child, Warsaw, Poland d Department Child Health, TNO

Netherlands Organization for Applied Scientific Research, Leiden, the Netherlands e Information Services Division, NHS National Services

Scotland, Edinburgh, UK f Estonian Institute for Population Studies, Tallinn University, Tallinn, Estonia g Department of Public Health and

Primary Health Care, University of Bergen, Bergen, Norway h Medical Birth Registry of Norway, Norwegian Institute of Public Health,

Bergen, Norway i Department of Health Information and Research, National Obstetric Information Systems (NOIS) Register, G’Mangia, Maltaj Department of Information, THL National Institute for Health and Welfare, Helsinki, Finland k Nordic School of Public Health,

Gothenburg, Sweden

Correspondence: J Zeitlin, INSERM, UMRS 953, Epidemiological Research Unit on Perinatal and Women’s and Children’s Health, 53 avenue

de l’Observatoire, 75014 Paris, France. Email [email protected]

Accepted 17 April 2013. Published Online 24 May 2013.

Objective To investigate time trends in preterm birth in Europeby multiplicity, gestational age, and onset of delivery.

Design Analysis of aggregate data from routine sources.

Setting Nineteen European countries.

Population Live births in 1996, 2000, 2004, and 2008.

Methods Annual risk ratios of preterm birth in each country wereestimated with year as a continuous variable for all births and bysubgroup using log-binomial regression models.

Main outcome measures Overall preterm birth rate and rate bymultiplicity, gestational age group, and spontaneous versus non-spontaneous (induced or prelabour caesarean section) onset of labour.

Results Preterm birth rates rose in most countries, but themagnitude of these increases varied. Rises in the multiple birthrate as well as in the preterm birth rate for multiple births

contributed to increases in the overall preterm birth rate. Abouthalf of countries experienced no change or decreases in the ratesof singleton preterm birth. Where preterm birth rates rose,increases were no more prominent at 35–36 weeks of gestationthan at 32–34 weeks of gestation. Variable trends were observedfor spontaneous and non-spontaneous preterm births in the 13countries with mode of onset data; increases were not solelyattributed to non-spontaneous preterm births.

Conclusions There was a wide variation in preterm birth trends inEuropean countries. Many countries maintained or reduced ratesof singleton preterm birth over the past 15 years, challenging awidespread belief that rising rates are the norm. Understandingthese cross-country differences could inform strategies for theprevention of preterm birth.

Keywords Europe, indicated preterm births, multiple births,

preterm births, time trends.

Please cite this paper as: Zeitlin J, Szamotulska K, Drewniak N, Mohangoo A, Chalmers J, Sakkeus L, Irgens L, Gatt M, Gissler M, Blondel B. Preterm birth

time trends in Europe: a study of 19 countries. BJOG 2013;120:1356–1365.

Introduction

Infants born preterm, defined as births at <37 completed

weeks of gestation, are at higher risk of mortality, morbidity,

and impaired motor and cognitive development in child-

hood than infants born at term. In high-income countries,

between two-thirds and three-quarters of neonatal deaths

occur in the 6–11% of infants born alive before 37 weeks of

gestation.1 Infants born before 32 weeks of gestation are at

particularly high risk of adverse outcomes, with rates of

infant mortality at 10–15% and of cerebral palsy at 5–10%,2,3 but moderate preterm birth (at 32–36 weeks of ges-

tation) is also associated with poor outcomes at birth and in

childhood.4–6 Being born preterm predisposes infants to

higher risks of chronic diseases and mortality later in life.7,8

Many countries have reported increased preterm birth

rates over the past two decades,9–15 and this general trend

*Euro-Peristat Preterm Study Group: C Vutuc (Austria); E Martens

(Flanders); P Velebil (Czech Republic); L Sakkeus (Estonia); M Gissler

(Finland); B Blondel (France); N Lack, B Misselwitz, P Wenzlaff (Ger-

many); S Bonham (Ireland); J Jaselioniene (Lithuania); M Gatt (Malta);

A Mohangoo, J Nijhuis (the Netherlands); L Irgens, K Klungsøyr (Nor-

way); K Szamotulska (Poland); H Barros (Portugal); Z Novak (Slovenia);

F Bolumar (Spain); K Gottvall (Sweden); James Chalmers (UK).

1356 ª 2013 The Authors. BJOG: An International Journal of Obstetrics & Gynaecology published by John Wiley and Sons on behalf of theRoyal College of Obstetricians and Gynaecologists

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License,which permits use, distribution and reproduction in any medium, provided the original work is properly cited

and is not used for commercial purposes.

DOI: 10.1111/1471-0528.12281

www.bjog.orgEpidemiology


was recently confirmed by a WHO global survey.16 There

are many reasons to expect preterm birth rates to rise. One

reason is increasing multiple pregnancy rates, associated

with the use of subfertility treatments and later maternal

age at childbirth.17,18 The preterm birth rate for multiples

is 40–60%, compared with 5–10% for singletons.19 Second,

the survival of very preterm infants has improved markedly

over recent decades because of medical advances in neona-

tal care, such as antenatal corticosteroids and surfactants,20

and their improved prognosis has changed perceptions of

the risk associated with prematurity versus other pregnancy

complications. This has lowered the threshold for indicated

(alternatively termed non-spontaneous or provider-initi-

ated) preterm births, and has led to the rise in number of

these births.21–23 Other risk factors for spontaneous and

non-spontaneous preterm birth, such as in vitro fertilisation

(IVF), older maternal age, and higher maternal body mass

index (BMI), have also become more prevalent among

childbearing women.10,15,24 Finally, progress in the preven-

tion of preterm birth has been limited: the 2006 Institute

of Medicine report on preterm birth and other reviews

have concluded that the efforts for prevention have been

largely unsuccessful.25,26

In contrast to this general trend, however, recent studies

from Finland and the Netherlands have reported decreasing

rates of preterm birth for singleton births.24,27 Data on pre-

term birth rates from the Euro-Peristat project, a collabora-

tion to monitor perinatal health in the European Union, also

raise the question of whether rates are rising in all countries.

Preterm birth rates in 2004 ranged from 5 to 11%, and it is

possible that differences in trends over time explain some of

this variation.1 This study was thus designed to investigate

time trends in preterm birth rates in the Euro-Peristat coun-

tries, and how these trends differ for singleton versus multi-

ple pregnancies, as well as preterm deliveries with a

spontaneous versus a non-spontaneous onset of labour.

Methods

DataThe scientific committee members of the countries partici-

pating in the Euro-Peristat II project (25 European mem-

ber states and Norway) were invited to take part in this

study.1 Aggregate data from routine population-based

sources were requested on number of births by gestational

age (in completed weeks), by multiplicity, mode of delivery

(vaginal or caesarean), and mode of onset of labour (cae-

sarean section before labour, induction, or spontaneous),

in 1996, 2000, 2004, and 2008. The definition of gestational

age was the final estimate in the obstetrical records. We

requested data on all live births, starting at 22 weeks of

gestation. Stillbirths were excluded because registration cri-

teria differ in routine sources across EU countries.28

The time intervals were selected in order to allow com-

parisons with other Euro-Peristat data collected in 2000

and 2004. Countries that were unable to provide data for

these years were asked to provide data from the closest

available time point. If data were not available nationally,

we requested population-based data from geographically

defined regions. Appendix S1 describes data sources and

geographical coverage.

Nineteen countries participated in the study. In Belgium,

data came from Flanders, and in Germany, data came from

three L€ander. Data from the UK came from Scotland (ges-

tational age was added to routine birth registers in North-

ern Ireland, England, and Wales in 2005 only). In France,

data came from a routine nationally representative survey

of all births. Spain and Portugal could only provide data

by gestational age groups. The Czech Republic, the German

L€ander, Ireland, and Malta had no data from 1996. Malta

and Sweden provided data from 2009 instead of 2008. Data

from the French survey were available for 1995, 1998, 2003,

and 2010. Most countries reported only minimal rates of

missing data for gestational age, with the exception of

Spain, where missing data were 11–19% depending on the

period. Missing data were minimal for other variables.

Missing data were excluded from analyses.

Austria, Ireland, Poland, Portugal, and Spain could not

provide data on the onset of labour, and Slovakia only had

this data for the last time point. Estonia, Lithuania, Malta,

and Scotland collected data by whether the caesarean was

planned/elective or an emergency. For these latter coun-

tries, planned caesarean sections were considered to occur

before the onset of labour, although Estonia used data on

the presence of labour to recode elective caesarean sections

that followed the onset of labour.

AnalysisWe computed preterm birth rates for all births and for sin-

gleton and multiple births for each time point. We also

computed rates of multiple birth (multiple births/all births)

and rates of spontaneous and non-spontaneous preterm

birth separately, by multiplicity. We estimated risk ratios

(RRs) of preterm birth with year as an independent contin-

uous variable in each country separately for all births, and

by subgroup, using log-binomial regression models.29 Risk

ratios were then transformed into percentage increases (risk

ratio �1) for presentation in graphs and tables. We used

the exact time points available in each country. Random

effects meta-analysis was used to test for heterogeneity in

annual RRs across countries and to compute pooled mea-

sures. We also redid analyses after excluding births at 22–23 weeks of gestation because of concerns about cross-

country differences in the recording of these infants, and

confirmed that the results were similar. Correlations

between country-level variables were assessed with Spear-

ª 2013 The Authors. BJOG: An International Journal of Obstetrics & Gynaecology published by John Wiley and Sons on behalf of theRoyal College of Obstetricians and Gynaecologists 1357

Preterm birth time trends in Europe

man’s rank tests. Finally, we computed population-attribut-

able risks to assess the contribution of multiple births to

the overall preterm birth rate; confidence intervals were

computed using Walter’s limits.30 Data were analysed using

STATA 10.0 (StataCorp LP, College Station, TX, USA).

Results

Rates and trends in preterm birthIn 2008, preterm birth rates across Europe ranged from 5.5

to 11.1% for all live births, from 4.3 to 8.7% for singleton

births, and from 42.2 to 77.8% for multiple births

(Table 1). The annual percentage increases in preterm birth

were significantly >0 in 13 out of the 19 countries included

in the study for all live births (Figure 1). For singleton

births, the percentage increases were positive for eight

countries and negative in three countries. Thirteen coun-

tries experienced significant increases in preterm birth for

multiple births, and no countries had significant decreases,

although four countries had percentage changes <0

(Finland, the Netherlands, Sweden, and France). Meta-anal-

ysis found highly significant heterogeneity for all three

measures using the Q–test; pooled RRs were over 1, but

given the extensive heterogeneity between countries, they

are of limited value (pooled measures: 0.7 (0.7–1.8), 0.2

(0.1–0.3), and 1.3 (1.2–1.4) for all, singleton, and multiple

births, respectively). Country-level trends by year for multi-

ples and singletons were not significantly associated,

although the Spearman’s correlation coefficient was positive

(q = 0.37, P = 0.12).

Some countries experienced fluctuations in rates from

one period to another, in particular for singletons. For

instance, in Austria the rate increased over the period, but

then declined slightly between 2004 and 2008. Furthermore,

not all countries could provide data for all time points. We

estimated annual trends for the period 2000–2008 in order

to assess the sensitivity of our results to the selection of time

points. Results were similar for all countries (Figure S1).

To test whether countries with lower initial rates of pre-

term birth experienced greater increases, we correlated pre-

term birth rates in the first time period with annual trends.

The Spearman’s correlation coefficients were negative, but

the associations were not significant (all births, –0.266,

P = 0.27; singleton births, –0.244, P = 0.31; and multiple

births, –0.321, P = 0.18).

Time trends in multiple births and population-attributable risksMultiple births as a proportion of all live births ranged

from 2.4 to 4.0% in 2008 (Table 2). Over the study period,

Table 1. Rates of preterm birth from 1996 to 2008 in 19 European countries

Country: region/

area

All live births Singleton live births Multiple live births

n

(2008)

1996

%

2000

%

2004

%

2008

%

n

(2008)

1996

%

2000

%

2004

%

2008

%

n

(2008)

1996

%

2000

%

2004

%

2008

%

Austria 77 720 9.1 10.0 11.4 11.1 75 066 7.9 8.4 9.4 8.7 2654 58.2 67.5 74.6 77.8

Belgium: Flanders 69 187 7.0 7.8 8.1 8.0 66 672 5.2 6.0 6.3 6.2 2515 51.7 55.9 60.4 57.3

Czech Republic 119 455 5.4 7.7 8.3 114 722 4.2 6.0 6.3 4733 42.3 52.7 57.5

Estonia 16 031 5.5 5.9 5.9 6.2 15 506 4.9 5.1 4.9 4.6 525 38.5 46.2 47.6 51.0

Finland 59 486 5.8 6.1 5.6 5.5 57 767 4.5 4.7 4.4 4.3 1719 46.5 49.4 44.5 47.5

France* 14 696 5.4 6.2 6.3 6.6 14 261 4.5 4.7 5.0 5.5 435 40.5 48.2 44.3 42.1

Germany: 3 L€ander 215 634 8.8 9.2 9.0 208 383 7.0 7.2 7.0 7251 61.7 61.8 64.2

Ireland 75 246 5.4 5.5 5.9 72 589 4.5 4.4 4.3 2657 41.8 42.3 49.9

Lithuania 31 287 5.3 5.3 5.3 5.9 30 510 4.5 4.6 4.5 4.7 777 41.3 42.6 42.7 49.4

Malta** 4152 6.0 7.2 6.7 4020 5.0 5.8 5.3 132 39.5 51.7 50.0

the Netherlands 175 160 7.8 7.7 7.4 7.4 168 829 6.2 6.0 5.7 5.7 6331 51.1 47.5 48.2 50.6

Norway 60 744 6.4 6.8 7.1 6.7 58 674 5.3 5.4 5.5 5.3 2070 43.4 43.9 49.2 48.3

Poland 414 480 6.8 6.3 6.8 6.6 404 452 6.1 5.5 5.8 5.5 10 028 43.1 44.0 50.2 51.2

Portugal 103 597 7.0 5.9 6.8 9.0 100 705 6.1 4.9 5.4 7.4 2892 45.9 49.6 54.9 63.5

Slovakia 53 624 5.1 5.4 6.3 6.8 52 227 4.4 4.5 5.2 5.6 1397 40.3 46.3 49.8 52.2

Slovenia 21 816 6.0 6.8 7.0 7.4 21 050 4.8 5.1 5.2 5.4 766 54.1 57.4 55.4 62.3

Spain 417 094 7.1 7.7 8.0 8.2 400 474 6.2 6.3 6.4 6.3 16 620 42.2 50.4 53.0 53.9

Sweden** 108 865 6.1 6.4 6.3 5.9 105 799 5.0 5.2 5.2 4.8 3066 44.1 43.4 45.2 43.3

UK: Scotland 58 275 7.0 7.4 7.6 7.7 56 423 5.8 6.1 6.3 6.1 1852 53.1 51.6 55.5 55.0

*Data from France come from a nationally representative sample of births, and the years are 1995, 1998, 2003, and 2010.

**2009, instead of 2008 data.


Zeitlin et al.

All live births

Singleton live births

Mul ple live births

–0.6–0.6–0.3–0.1

0.20.40.70.80.91.01.11.11.11.21.71.82.52.65.1

The NetherlandsFinland

SwedenPoland

Germany: 3 Länder*Norway

UK: ScotlandLithuania

EstoniaFrance

Belgium: FlandersIreland*

SpainMalta*

SloveniaAustria

PortugalSlovakia

Czech Republic*

0 2 4 6 8 10

–0.7–0.7–0.5–0.5–0.4–0.3–0.0

0.10.10.30.50.71.01.01.31.31.92.24.6

The NetherlandsPolandFinlandEstoniaIreland*SwedenNorway

Germany: 3 Länder*Spain

LithuaniaUK: Scotland

Malta*Austria

SloveniaFrance

Belgium: FlandersPortugalSlovakia

Czech Republic*

0 2 4 6 8 10

–0.3–0.1–0.1–0.1

0.40.50.91.11.11.41.61.62.02.02.32.32.52.83.6

FranceFinland

The NetherlandsSweden

UK: ScotlandGermany: 3 Länder*

Belgium: FlandersSloveniaNorway

LithuaniaPolandSpain

EstoniaSlovakia

Malta*Austria

Ireland*Portugal

Czech Republic*

0 2 4 6 8 10

Figure 1. Average annual percentage change for preterm birth by country, 1996–2008.* Data series begins in 2000.



this proportion was stable or decreasing in Belgium, Fin-

land, the Netherlands, and Sweden, and increased steeply

in Austria, the Czech Republic, Estonia, Ireland, and Spain.

There was a significant association between the increase in

the proportion of multiple births and the increase in pre-

term birth (Spearman’s q = 0.66, P = 0.021). The propor-

tion of the overall preterm birth rate attributable to

multiples in 2008 ranged from about 17% in France,

Poland, and Portugal, to 27% in Ireland and Slovenia.

Time trends by gestational age groupFigure 2 displays annual trends by gestational age group

for singletons and multiples. Countries are ordered as in

Figure 1. Although there was more variability in our esti-

mates because of the smaller samples, this figure shows that

increases in preterm birth were less marked for births at

<32 weeks of gestation, in particular for multiples.

Increases were not greatest for the 35–36 weeks of gestation

group, and in many countries the largest proportional

changes were observed between 32 and 34 weeks of gesta-

tion. Although many countries had similar trends for all

gestational age groups, patterns could vary: the Netherlands

experienced increases for singleton births at <32 weeks of

gestation (0.9), but decreases for the two other groups (–

0.8 and –0.1). Divergent time trends are also observed in

Poland, where decreases were larger for earlier preterm

births. The group at 35–36 weeks of gestation represented

a median of 60% of preterm births in participating

countries (interquartile range, 57–62%; range, 55–66%).

Time trends in spontaneous and non-spontaneouspreterm birthFor singletons, the rates of non-spontaneous preterm births

ranged from 1.1 to 3.0% in 2008, whereas spontaneous

onset births ranged from 2.8 to 4.8% (Table 3). For multi-

ples, the rates of non-spontaneous preterm birth ranged

from 12.0 to 34.4%, and spontaneous onset births from

15.1 to 38.2%. In each country, spontaneous preterm births

were more frequent than non-spontaneous preterm births,

with a few exceptions (Germany and Norway for singleton

and multiple births, France and Malta for singleton births,

and Belgium, Czech Republic, and Lithuania for multiple

births).

Countries had differing time trends for non-spontaneous

and spontaneous births for singleton births (Figure 3). In

some countries both types of preterm birth increased (Bel-

gium and Czech Republic), in others non-spontaneous pre-

term births increased, whereas spontaneous preterm births

either remained unchanged or declined (France, Norway,

and Sweden). Finally, some countries had increases in

spontaneous preterm births with no change in non-sponta-

neous preterm births (Scotland and Germany). For multi-

ples, in contrast, non-spontaneous preterm births increased

in almost all countries. In Sweden and the Netherlands,

where rates of multiple preterm births were stable, these

increases were offset by the decline in spontaneous preterm

births.

Discussion

Time trends in preterm births in Europe between 1996 and

2008 were highly heterogeneous, although the overall pre-

term birth rate and the multiple preterm birth rate

increased in most countries. In contrast, singleton preterm

birth rates were stable or decreased in about half of the

countries in this analysis, challenging a widespread belief

that rising rates have been the norm. In countries with rate

increases, these were observed for all gestational age groups,

not just the births closest to term.

Our study is limited by the data available from national

systems: for instance, several countries did not have data

for all the requested time points. We estimated annual

trends using the available data points to compare across

countries despite this limitation; a sensitivity analysis com-

puting trends from 2000 to 2008 showed that our results

were robust to the choice of period. Because our question

was whether rates were rising, we tested for linear trends.

Table 2. Rates of multiple births per 100 live births, population-

attributable risks, and average annual increases, 1996–2008

Multiple birth

rate 2008

Annual

increase

Population-

attributable

risk 2008

Austria 3.4 3.2 21.3 (19.6–23.1)

Belgium: Flanders 3.6 –0.6* 23.2 (21.1–25.2)

Czech Republic 4.0 3.3* 24.5 (22.9–26.0)

Estonia 3.3 5.5* 24.7 (20.2–29.2)

Finland 2.9 –0.9* 22.5 (20.1–25.0)

France** 3.0 0.4 16.5 (11.6–21.4)

Germany: 3 L€ander 3.4 0.3 21.5 (20.3–22.7)

Ireland 3.5 3.9* 27.2 (25.2–29.2)

Lithuania 2.5 1.8* 18.9 (15.3–22.6)

Malta*** 3.2 0.8 21.1 (12.1–30.1)

the Netherlands 3.6 –0.3 22.1 (20.8–23.4)

Norway 3.5 1.2* 21.7 (19.4–24.0)

Poland 2.4 1.8* 16.8 (15.8–17.9)

Portugal 2.8 2.5* 17.4 (15.5–19.3)

Slovakia 2.7 2.7* 17.8 (15.0–20.5)

Slovenia 3.5 2.6* 26.9 (23.2–30.5)

Spain 3.8 3.2* 23.1 (22.3–24.0)

Sweden*** 2.8 –0.6* 18.4 (16.5–20.2)

UK: Scotland 3.2 1.2* 20.2 (17.8–22.6)

*Confidence interval does not include 0.

**Data from France come from a nationally representative sample

of births, and the years are 1995, 1998, 2003, and 2010.

***2009, instead of 2008 data.


Zeitlin et al.

Rate fluctuations occurred in some countries, but no con-

sistent patterns could be discerned, and we chose not to

model these rises and falls.

Some countries could not provide data on the mode of

the onset of labour, and among those that did, definitions

differed (‘elective’ versus ‘pre-labour’ caesareans), although

they were stable over the study period. Questions also exist

about the measure of gestational age. We requested gesta-

tional age based on a common definition, the best obstetri-

cal estimate, but we were unable to assess how clinicians

assigned this estimate.31 Dating pregnancies using ultra-

sound shifts the gestational age distribution to the left, and

can increase the preterm birth rate,32 but it can also

decrease the rate by reducing errors in gestational age esti-

mates.31 We cannot exclude the possibility that the rates of

preterm birth were affected by an increased use of ultra-

sound for the dating of pregnancies over time, but in many

European countries ultrasound dating was already widely

used in the mid-1990s,11,13,27 and it is not clear whether

this would lead to systematic upward or downward trends.

A part of the wide variation in preterm birth rates across

countries (5–11%) may result from differences in how ges-

tational age is estimated; however, the fact that we

observed substantial changes in the preterm birth rate over

the study period in some countries also confirms that large

variations of this indicator are plausible.

More generally, it was not possible to assess the quality

of data collection and case ascertainment; previous work in

the Euro-Peristat group has found significant heterogeneity

in routine data systems in Europe with respect to organisa-

tion and scope.33 However, this study was restricted to

population-based reporting systems with high coverage,33

and used a pre-established protocol with common defini-

tions developed collaboratively with participating data pro-

viders. This represents a strength over previous

international studies that have relied on data in published

reports and were unable to specify a priori definitions.16

Missing data on gestational age were low, with the excep-

tion of Spain, where civil registration data rely on parental

reports,34 and estimated trends in this case must be viewed

with caution.

We requested data on live births instead of total births

because of the differences in registration of stillbirths

between European countries.28,33 Although it is important

to consider the impact of stillbirths because many indicated

preterm deliveries aim to reduce stillbirths, this exclusion is

unlikely to affect our conclusions as preterm stillbirth is a

rare outcome (about 2 per 1000 total births) compared

A

B

Figure 2. Average annual percentage change for birth at <32 weeks of gestation, 32–34 weeks of gestation, and 35–36 weeks of gestation among

singleton live births (A), and among multiple live births (B), 1996–2008.



with live preterm birth.1 We set a common lower inclusion

limit of 22 weeks of gestation for this study, and recom-

puted time trends after the exclusion of births under

24 weeks of gestation to verify that differences between

countries in registration practices for live births at the lim-

its of viability had no impact on our findings.

Our results show that the preterm birth rates for all

births rose in many European countries, as was also found

by the recent WHO study of preterm birth trends based on

publicly available data in 64 countries in developed regions,

Latin America, and the Caribbean.16 Our results add to this

overview, however, by revealing that time trends can differ

substantially between the overall preterm birth rate and the

singleton preterm birth rate, that trends were similar across

gestational age groups, and by documenting changes in

multiple births rates over time and their contribution to

the overall preterm rates.

We found a strong correlation between increases in mul-

tiple births and preterm birth, corroborating previous stud-

ies.18 Policies related to the use of assisted reproductive

technology (ART) are highly variable in Europe, and these

affect the multiple birth rate resulting from ART.17 For

instance, national elective single embryo transfer (eSET)

policies have been adopted by several countries, including

Belgium and Sweden.35 eSET has also been extensively pro-

moted in Finland, despite the fact that it is not mandatory

nor an official policy.36 In contrast, other European coun-

tries have no such policies: in Italy, the law requires the

transfer of all fertilised embryos in each cycle, although it

limits the number of fertilised embryos to three.37 Data

collected by the European Society of Human Reproduction

and Embryology (ESHRE) from IVF centres documents

wide differences in the rates of single embryo transfer

across Europe (from 10 to ~70%)17; countries in our analy-

sis with negative trends in their preterm birth rates, such as

Belgium, Finland, and Sweden, had a high proportion of

eSET (50.4, 62.1, and 69.5%, respectively). In contrast,

countries with increases in their multiple birth rate had a

lower proportion of single embryo transfers (Austria,

22.6%; Ireland, 19.1; and Portugal, 19.0).

Multiple births also affected the overall preterm birth

rate because of increases in the preterm birth rate among

multiples. For multiple births, and with the data on mode

of onset of labour included in the analysis, non-spontane-

ous preterm birth rates increased in almost all countries. In

almost all countries with data on mode of onset of labour,

non-spontaneous preterm birth rates increased. Overall,

our data showed that the population-attributable risk asso-

Table 3. Spontaneous and non-spontaneous preterm births per 100 live births by multiplicity from 1996 to 2008

Country: region/area Singleton births Multiple births

Spontaneous onset Non-spontaneous onset Spontaneous onset Non-spontaneous onset

1996 2000 2004 2008 1996 2000 2004 2008 1996 2000 2004 2008 1996 2000 2004 2008

Austria

Belgium: Flanders 3.8 3.9 4.3 4.2 1.5 2.1 2.1 2.0 29.0 33.0 33.4 30.6 22.7 22.9 27.0 26.7

Czech Republic 3.1 4.4 4.4 1.1 1.6 1.9 23.3 27.0 26.2 19.0 25.7 31.3

Estonia 3.4 3.9 3.8 3.6 1.4 1.1 1.1 1.1 29.9 30.2 30.5 33.5 8.7 16.0 17.1 17.5

Finland 3.3 3.7 3.5 3.2 1.1 1.0 0.9 1.1 30.7 35.9 29.0 31.9 15.8 13.5 15.5 15.5

France* 3.0 2.9 2.7 2.8 1.5 1.7 2.3 2.6 22.6 31.2 20.9 21.8 18.0 17.0 23.1 20.2

Germany: 3 L€ander 3.8 4.0 4.0 3.0 3.1 3.0 27.4 27.8 32.0 32.3 33.1 32.1

Ireland

Lithuania 3.0 3.1 3.1 3.2 1.5 1.5 1.4 1.5 23.0 23.0 23.9 15.1 18.3 19.5 18.5 34.4

Malta** 3.9 3.5 4.2 0.9 2.3 1.1 25.6 32.5 32.6 12.0 19.2 17.4

the Netherlands 4.4 4.4 4.2 3.9 1.7 1.6 1.5 1.8 34.3 32.1 32.8 29.9 15.9 15.4 15.4 20.7

Norway 3.2 3.3 3.1 3.1 1.6 2.1 2.3 2.1 24.5 24.5 25.6 25.3 14.7 19.0 23.1 21.6

Poland

Portugal

Slovakia 4.3 1.2 38.2 12.0

Slovenia 4.1 4.1 4.2 4.2 0.7 1.0 1.0 1.3 41.0 46.5 39.9 37.6 11.7 10.9 15.6 24.7

Spain

Sweden** 3.2 3.3 3.4 3.1 1.6 1.7 1.7 1.7 27.4 28.5 28.1 25.0 16.6 13.9 16.5 17.9

UK: Scotland 4.5 4.8 5.0 4.8 1.3 1.2 1.2 1.3 39.9 36.3 36.9 36.3 13.2 15.3 18.6 18.8

*Data from France come from a nationally representative sample of births, and the years are 1995, 1998, 2003, and 2010.

**2009, instead of 2008 data.


Zeitlin et al.

ciated with multiple pregnancies was substantial, ranging

from 17 to 27%.

We found that many countries had unchanging or

declining singleton preterm birth rates, as also shown by

studies from Finland and the Netherlands over different

time periods,24,27 while elsewhere preterm birth rates rose

considerably. We found increases in non-spontaneous pre-

term births in some countries, corroborating other studies

concluding that these births were a driving force behind

rising preterm birth rates.13,15,22,38 However, we observed

extensive heterogeneity in the proportions of preterm births

by mode of onset of labour, and in the evolution of non-

spontaneous preterm births over time. A consistent pattern

of rising preterm birth rates driven primarily by non-spon-

taneous preterm births was not detected.

We also showed that spontaneous preterm births played

a role in determining overall trends, as reported in other

in-depth studies of preterm birth in Denmark, Scotland,

Australia, Finland, and the Netherlands.11,13,15,24,27 Rates of

spontaneous preterm births rose in some countries, and

where overall preterm birth rates decreased, these trends

affected spontaneous preterm births. The reasons for trends

in the spontaneous preterm birth rate are poorly under-

stood, and countries with similar populations have experi-

enced divergent trends, as in Denmark and Finland, for

instance.11,24 Researchers have proposed a range of factors

that could contribute to varying preterm birth rates

between populations, including older maternal age, obesity,

higher-risk migrant populations, smoking during preg-

nancy, use of IVF, diabetes, Chlamydia trachomatis infec-

tion, and previous induced abortions, but their relative

contribution remains to be established.11,13,15,24,27 Obstetric

practices related to the management of preterm birth risk

(screening for short cervix, use of progesterone, and pre-

scription of bed rest, for instance) may differ across coun-

tries; however, we are not aware of any studies that have

A B

C D

Figure 3. Average annual percentage change for spontaneous (A) and non-spontaneous (B) preterm births among singleton live births, and annual

rate ratios for spontaneous (C) and non-spontaneous (D) preterm births among multiple live births, 1996–2008.



assessed variations in these practices across countries and

their impact on national preterm birth rates. The preva-

lence of work leaves for pregnant women differ in Europe,

and this may reduce the impact of work-related risk factors

on preterm birth.39 Economic factors may also play a role:

some studies find that preterm birth rates have risen more

steeply among women of lower socio-economic status.9

Comparative cross-national studies provide an opportunity

to test these multiple hypotheses; the Euro-Peristat network

as well as birth cohorts that have been established in Eur-

ope are promising platforms for future research in this

area.

Although annual changes in the rate of preterm birth were

modest in most countries, the impact is substantial when

assessed in terms of the numbers of preterm infants. If every

country had experienced trends similar to Finland or the

Netherlands over the study period (–0.6% per year), over

24 000 fewer preterm babies would have been born in 2008,

or 1.2% of the over two million births in the participating

countries. Evaluating the health impact of rising rates is

more complex than computing the number of ‘excess’ pre-

term infants, however. Several studies have suggested that

rises in the rate of indicated preterm births may be associ-

ated with better perinatal outcomes. For twins, more inten-

sive prenatal care was related to higher rates of preterm

birth, and mothers receiving more intensive care had lower

neonatal mortality.40 For singletons, mortality rates were

observed to decline more steeply among non-spontaneous

than spontaneous preterm births.41 On the other hand, there

is a growing body of research documenting the adverse

short- and longer-term health consequences of being born

preterm, even at later gestational ages.6,8 The large variability

in the proportions of non-spontaneous preterm births sug-

gests that there are contrasting interpretations of the current

evidence base related to the positive and negative conse-

quences of inducing a delivery before term.

Conclusion

Time trends in the rates of preterm birth since the mid-

1990s show a striking diversity in 19 European countries.

For multiples, rates have generally increased, although the

range is wide; for singletons, however, the direction of

change differs. These results call for further examination of

reproductive and perinatal health policies and medical

practices in European countries, and for an assessment of

their impact on the population risk of preterm birth. To

enable comparative analyses, data on preterm birth need to

be included in international health databases.

Disclosure of interestsThe authors have no conflicts of interest or disclosures to

declare.

Contribution to authorshipJZ, BB, and KS conceived the study, ND carried out statis-

tical analysis, ADM, JC, LS, LI, MG, and MG contributed

to the interpretation of the results and revised successive

versions of the article. Members of the Euro-Peristat pre-

term birth group were responsible for the provision, accu-

racy, and interpretation of data in their country: they

commented on initial and final versions of the article. All

authors approved the final article.

Details of ethics approvalThis article is based on the analysis of aggregate data pro-

vided from routine data sources, and is exempt from ethical

approvals at INSERM in France. The transmission of data

was consistent with existing authorisations for each routine

data source in terms of the allowable minimum cell sizes.

FundingThis analysis was partially funded by a grant to the Euro-Peri-

stat project from the European Commission (2010 13 01). JZ

also received funding from the European Commission,

Research Directorate, Marie Curie, IOF Fellowship, grant no.

254171. The funding agency was not involved in the study.


Additional Supporting Information may be found in the

online version of this article:

Figure S1. Annual percentage changes of preterm birth

by year, 2000–2008.

Appendix S1. Data sources.&

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