Discussion
Despite the differences in health policies, educational policies and reporting systems across Europe, the available data from routine systems about stillbirths by socioeconomic status pointed to widespread and consistent socioeconomic inequalities in the stillbirth rate. Over three quarters of 29 participating European countries provided data on stillbirths by either mothers’ educational levels or parents’ occupation. While data about mothers’ educational levels were more widely available and comparable than data about mothers’ or fathers’ occupations, some of the larger countries, notably Germany and England and Wales combined only had data by parents’ occupations. Among countries with data, the median RR for stillbirth was 1.9 for women with primary or lower secondary education and 1.4 for those the intermediate category of higher secondary education compared to women with post-secondary education.. Median RR in the lowest occupational categories compared to highest were 1.6 and 1.4, respectively, for mothers’ and fathers’ occupational groups. These differences had substantial impacts at a population-level: if all women faced the stillbirth risks of the most educated, the number of stillbirths would be 25 % lower.
The main strength of our study is the ability to present data from all over Europe collected for the same year using a standardised instrument. We also requested data about mothers’ educational levels using local classifications and mapped these to the ISCED-97 classification to ensure consistency in coding and then checked our coded data with the data providers in each country. Our study also has several limitations. Because we used aggregated data, we were unable to explore the contribution of other demographic or behavioural factors, such as maternal age, parity, migrant status, smoking or body mass index to the higher risks associated with our socioeconomic indicators. Further, even though Euro-Peristat uses a common inclusion threshold of 22 weeks of gestation for births and deaths, not all countries are able to provide these data and even when they can, practices related to recording of early stillbirths differ [
19]. While it is likely that these differences relate primarily to legislation and recording practices and not women’s socioeconomic circumstances, social inequalities may be more acute for early stillbirths and underreporting might thus affect the comparability between countries [
5]. For countries where TOP cannot be differentiated from spontaneous stillbirths, the social gradient may be attenuated as TOP reflect the prevalence of anomalies for which the social gradient is less consistent [
23,
24] as well as access to prenatal screening, which may have an inverse gradient in some countries [
25]. Finally, some countries had missing data on socioeconomic factors which could bias the estimates. This bias likely leads to underestimates of the effects as missing data were more frequent among stillbirths and may also be more frequent for socially disadvantaged and migrant women.[
26]
Because there are no universal measures of social disadvantage, researchers use a wide variety of different indicators: occupation, education, income, other measures of wealth, housing conditions, lack of access to health care, in particular prenatal care, and others. We used two indicators selected in a Delphi process based on assessments of importance and feasibility. The definition of these indicators, level of education and occupational group, were based on common classifications agreed upon by international organizations. However, categories may not reflect similar constructs in all countries or be understood in the same manner by responders or coders.
For mothers’ educational level, comparability issues related to the limit for differentiating between lower and higher secondary schooling, to the classification of vocational tracts and to the inclusion of a category for no or limited schooling, which may be relevant for some migrant women There are also real differences in educational attainment across Europe. Similarly broad variations in maternal education have been documented in comparative studies based on birth cohorts across Europe [
27,
28]. However, despite the differences in the distribution of maternal educational attainment a negative social gradient was observed in most countries when this indicator was used.
For mothers’ and father’ occupation, questions of comparability were more complex as it was not possible to describe original data. Rules for recording and classifying occupations for parents who are not in paid employment or seeking work at the time their babies are born and lone mothers registering births without the involvement of the babies’ fathers were not clear. Compared to mothers’ educational level, there was higher variation in the distribution of categories between countries, RR tended to be lower and did not always follow a linear gradient. Furthermore, while the ISCO classification appeared to be widely used, there are questions about whether a status based classification of occupations is most relevant. Some research suggests that a classification based on employment relations (i.e. employers, employees or self-employed) provides more useful insights into the nature of social inequalities and their potential impact of health [
29,
30] and these principles have been used for the development of a European Classification [
31]. Given these conceptual and practical difficulties, one way of improving comparisons across countries would be to promote the recording of mothers’ educational level in routine systems either directly or through data linkage.
Studies from other high-income countries have documented elevated risks of similar magnitude for women with low socioeconomic position. For instance, using Canadian data, Auger et al. reported relative risks of 1.6 and 1.3 for low and intermediate educational levels compared with women with the highest educational level [
5]. In a large US case control study, the unadjusted OR for educational level were 1.5 and 1.4, respectively for women with primary or some secondary and completed secondary compared to women with a post-secondary education [
32]. The reasons for these elevated risks are likely multiple and interconnected. One UK study investigating stillbirths by area-based deprivation scores found that deprivation gaps existed for all causes, except for mechanical events, with the widest gap for stillbirths due to antepartum haemorrhages [
3]. The study in Canada found differences throughout the gestational age spectrum, although they were more marked at earlier gestational ages [
5].
The finding that social factors are not restricted to specific causes or gestational age groups is not surprising. Many risk factors, including smoking, diet and healthcare factors, affect a number of pregnancy complications such as extremely preterm delivery, growth restriction and congenital anomalies which raise stillbirth risk and are more common among less advantaged groups in the population. Mothers in these groups are more likely to have high body mass indices (BMI) and to smoke during pregnancy and these are important risk factors for stillbirth [
33]. Other risk factors, such as migrant status, also affect a wide range of reproductive health outcomes [
34,
35]. Social differences in screening and termination of pregnancy may also play a role if socially disadvantaged women are less likely to terminate pregnancies with lethal anomalies, either because of lack of access to screening or differences in attitudes to pregnancy terminations [
24,
25,
36]. Antenatal detection of growth restriction may play a role in preventing stillbirth and the extent to which social position affects access to screening should also be considered [
37]. The question of how much of the social gradient is explained by these behavioural and healthcare factors, especially those that are potentially modifiable, is an important area for further research.
While we found consistent associations between risks of stillbirth and social factors in European countries, the magnitude of the social gradient varied. Some of this variation could be related to small sample sizes in some countries as well as to the non-comparability of socioeconomic classifications. However, studies comparing the Nordic countries have found differences in the social gradient of stillbirth risk even within these relatively homogenous societies [
2]. Other studies of socioeconomic inequalities in Europe have uncovered differences in the inequality gradient for overall mortality rates which are partially correlated with differences in the prevalence of smoking and overweight in the population [
38]. Other European studies have also suggested that healthcare can contribute to differences in outcomes, for instance in cancer mortality, which may reflect social inequalities in access and quality of care [
39]. In the perinatal field, this is an important area for further investigation and could be a powerful tool for identifying population-based risk factors and health care policies that contribute to stillbirth etiology and thereby to prevention of stillbirth for the benefit of all women.
Acknowledgements
The authors acknowledge the following contributors to the European Perinatal Health Report: Health and Care of Pregnant Women and Babies in Europe in 2010:
Austria, Gerald Haidinger, The Medical University of Vienna, Department of Epidemiology, Centre of Public Health; Jeannette Klimont, Statistics Austria; Belgium, Sophie Alexander, Wei-Hong Zhang, Michèle Dramaix-Wilmet, Mélissa Van Humbeeck, Université Libre de Bruxelles, School of Public Health, Epidemiology, Biostatistics and Clinical Research Centre; Charlotte Leroy, Anne-Frédérique Minsart, Virginie van Leeuw, Centre d’Epidémiologie Périnatale (Cepip); Evelyne Martens, SPE (Study Center for Perinatal Epidemiology); Myriam De Spiegelaere, Brussels Health and Social Observatory, Freddy Verkruyssen, Michel Willems, FPS Economy, SMEs, Self-employed and Energy; Willem Aelvoet, The Federal Public Service (FPS) Health, Food Chain Safety and Environment; Jean Tafforeau, Francoise Renard, Denise Walckiers, Focal Point for the data collection on national health statistics for Eurostat, OECD and WHO; Deborah Cuignet, Philippe Demoulin, French Community of Belgium; Heidi Cloots, Erik Hendrickx, Anne Kongs, Flemish Agency for Care and Health; Cyprus, Pavlos Pavlou, Despina Stylianou, Theopisti Kyprianou, Ministry of Health, Health Monitoring Unit; Nicos Skordes, Pediatric Department, Makarios III Hospital; Czech Republic, Petr Velebil, Institute for the Care of Mother and Child; Denmark, Jens Langhoff Roos, Obstetrics Clinic, Rigshospitalet, Copenhagen University; Anne-Marie Nybo Anderson, Laust Hvas Mortensen, University of Copenhagen; Estonia, Luule Sakkeus, Estonian Institute for Population Studies, Tallinn University; Finland, Mika Gissler, Anna Heino, Annukka Ritvanen, THL National Institute for Health and Welfare, Health Services Department; France, Béatrice Blondel, Marie-Hélène Bouvier Colle, Marie Delnord, Jennifer Zeitlin, National Institute of Health and Medical Research (INSERM) U1153; Anne Ego, RHEOP Register for Disabled Children and Perinatal Observatory; Grégoire Rey, National Center of Statistics for Medical Causes of Death (CépiDc), National Institute of Health and Medical Research (INSERM); Germany, Nicholas Lack, Bavarian Institute for Quality Assurance; Guenther Heller, AQUA-Institut; Anton Scharl, Department of Obstetrics and Gynaecology; Klinikum Amberg; Greece, Aris Antsaklis, Peter Drakakis, Athens University Medical School, Athens; Hungary, István Berbik, Department of Obstetrics and Gynaecology, Vaszary Kolos Teaching Hospital; Iceland, Helga Sól Ólafsdóttir, Ragnheiður I. Bjarnadottir, Hildur Harðardóttir, Brynja Ragnarsdóttir, Vigdís Stefánsdóttir Landspitali University Hospital; Sigríður Haraldsdóttir, Landlaeknis Directorate of Health; Ireland, Sheelagh Bonham, Aisling Mulligan, The Economic and Social Research Institute (ESRI), Heath Research & Information Division; Italy, Marina Cuttini, Pediatric Hospital of Baby Jesus, Unit of Epidemiology; Cristina Tamburini, Rosaria Boldrini, General Directorate for the Health Information and Statistical System, Italian Ministry of Health; Sabrina Prati, Marzia Loghi, Cinzia Castagnaro, Stefano Marchetti, Alessandra Burgio, Central Directorate for Socio-demographic and Environmental Statistics, Italian National Institute for Statistics-ISTAT; Monica Da Frè, Epidemiology Observatory, Regional Agency for Health of Tuscany Latvia, Janis Misins, Irisa Zile, The Centre for Disease Prevention and Control of Latvia; Lithuania, Jelena Isakova, Rita Gaidelyte, Jone Jaselione, Institute of Hygiene, Health information centre; Luxembourg, Yolande Wagener, Guy Weber Ministry of Health, Department of Health, Division of Preventive and Social Medicine; Audrey Billy, Aline Touvrey-Lecomte, Public Health Research Center; Malta, Miriam Gatt, Dept of Health Information and Research, National,Obstetric Information Systems (NOIS) Register;; Netherlands, Jan Nijhuis, Maastricht University Medical Center, Department of Obstetrics & Gynecology, Maastricht; Karin van der Pal de Bruin and Ashna Hindori-Mohangoo, TNO Healthy Living, Department Child Health, Leiden; Peter Achterberg, National Institute for Public Health and the Environment; Chantal Hukkelhoven and Ger de Winter, The Netherlands Perinatal Registry; Anita Ravelli, Academic Medical Research Center; Greta Rijninks-van Driel, The Royal Dutch College of Midwives; Pieter Tamminga, Paediatric Association of the Netherlands; Martin Groesz, Perinatal Audit Netherlands; Patty Elferink-Stinkens, Statistics Netherlands; Norway, Kari Klungsoyr, Medical Birth Registry of Norway, Norwegian Institute of Public Health and Department of Global Public Health and Primary Care, University of Bergen; Arild Osen, Marta Ebbing, Medical Birth Registry of Norway, The Norwegian Institute of Public Health; Poland, Katarzyna Szamotulska, National Research Institute of Mother and Child, Department of Epidemiology and Biostatistics with collaboration from The Central Statistical Office, the National Health Fund and Ministry of Health; Portugal, Henrique Barros, Sofia Correia, University of Porto Medical School, Department of Clinical Epidemiology, Predictive Medicine and Public Health; Institute of Public Health; Romania, Mihai Horga, Senior Advisor at the East European Institute for Reproductive Health, East European Institute for Reproductive Health; Alexandra Cucu, National Institute of Public Health; Slovakia, Jan Cap, National Health Information Center; Slovenia, Živa Novak-Antolič, University Medical Centre, Perinatology Unit, Ljubljana University; Ivan Verdenik, University Medical Centre, Department of Obstetrics& Gynecology, Research Unit; Spain, Francisco Bolumar, Alcala University Medical School; Mireia Jané, Maria José Vidal, Public Health Surveillance Direction, Catalan Public Health Agency; Carmen Barona, Rosa Mas, Public Health, Generalitat Valenciana; Adela Recio Alcaide, National Institute for Statistics (INE); Sweden, Karin Gottvall, Ellen Lundqvist, The National Board of Health and Welfare, Department of Statistics, Monitoring and Evaluation, Statistics on Public Health and Social Care Unit; Switzerland, Sylvie Berrut, Swiss Federal Statistical Office, Section Health; Claudia König, Monika Schmid, Institut für Hebammen, ZHAW Zürcher, Hochschule für Angewandet Wissenschaften; United Kingdom, Alison Macfarlane, Nirupa Dattani, City University London; Jim Chalmers (now retired), Kirsten Monteath, Information Services Division, NHS National Services Scotland; Marie Climson, National Records of Scotland; Leslie Marr, Healthcare Improvement Scotland; Rod Gibson, Birthchoice UK; Gwyneth Thomas, Rhian Osborne, Health Statistics and Analysis Unit, Welsh Government; Russell Brown, NHS Wales Informatics Service; David Sweet, Joanne Evans, Office for National Statistics; Sinead Magill, Adele Graham, Heather Reid, Public Health Agency; Terry Falconer, Karen McConnell, Northern Ireland Maternal and Child Health, Public Health Agency (now retired); Neil McComb, Human Fertilisation and Embryology Authority.
The Euro-Peristat Scientific Committee: Gerald Haidinger (Austria), Sophie Alexander (Belgium), Pavlos Pavlou (Cyprus), Petr Velebil (Czech Republic), Laust Mortensen (Denmark), Luule Sakkeus (Estonia), Mika Gissler (Finland), Béatrice Blondel (France), Marie Delnord (Project Coordination, France), Jennifer Zeitlin (Project Leader, France) Nicholas Lack (Germany), Aris Antsaklis (Greece), István Berbik (Hungary), Helga Sól Ólafsdóttir (Iceland), Sheelagh Bonham (Ireland), Marina Cuttini (Italy), Janis Misins (Latvia), Jone Jaselioniene (Lithuania), Yolande Wagener (Luxembourg), Miriam Gatt (Malta), Jan Nijhuis (Netherlands), Ashna Hindori-Mohangoo (Project Coordination, Netherlands) Karin van der Pal (Executive board member, Netherlands), Kari Klungsoyr (Norway), Katarzyna Szamotulska (Poland), Henrique Barros (Portugal), Mihai Horga (Romania), Jan Cap (Slovakia), Natasa Tul Mandić (Slovenia), Francisco Bolúmar (Spain), Karin Gottvall (Sweden), Sylvie Berrut (Switzerland), Alison Macfarlane (United Kingdom).
Authors' contributions
JZ had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: JZ, LM, CP, AM, ADH-M, MG, KVP, KS, FB, AMNA, HSO, WHZ, BB; Acquisition, analysis, or interpretation of data: All authors, including authors in the Euro-Peristat SC (GH, PP, PV, LS, NL, AA, IB,SB, MC, JM, JJ, YW, MG, JN, KK, HB, MH, JC, NTM, KG, SB); Drafting of the manuscript: JZ, LM, CP, AM, ADH-M, MG, KVP, KS, FB, AMNA, HSO, WHZ, BB, SA Critical revision of the manuscript for important intellectual content and approval of final version of the manuscript: All authors, including authors listed in Euro-Peristat SC (GH,PP, PV, LS, NL, AA, IB, SB, MC, JM, JJ, YW, MG, JN, KK, HB, MH, JC, NTM, KG, SB); Statistical analysis: CP, JZ, LM; Study supervision: JZ, LM, BB, SA; Obtained funding: JZ, AM, AHM, KVP, BB, KS, SA.