. 2020 Mar;34(2):122-129.

doi: 10.1111/ppe.12655.

Multilevel analyses of related public health indicators: The European Surveillance of Congenital Anomalies (EUROCAT) Public Health Indicators

Kate E Best¹, Judith Rankin¹, Helen Dolk², Maria Loane², Martin Haeusler³, Vera Nelen⁴, Christine Verellen-Dumoulin⁵, Ester Garne⁶, Gerardine Sayers⁷, Carmel Mullaney⁸, Mary T O'Mahony⁹, Miriam Gatt¹⁰, Hermien De Walle¹¹, Kari Klungsoyr¹², Olatz Mokoroa Carolla¹³, Clara Cavero-Carbonell¹⁴, Jennifer J Kurinczuk¹⁵, Elizabeth S Draper¹⁶, David Tucker¹⁷, Diana Wellesley¹⁸, Nataliia Zymak-Zakutnia¹⁹, Nathalie Lelong²⁰, Babak Khoshnood²⁰

Affiliations

¹ Institute of Health & Society, Newcastle University, Newcastle upon Tyne, UK.
² Centre for Maternal, Fetal and Infant Research, Institute of Nursing and Health Research, Ulster University, Ulster, UK.
³ Medical University of Graz, Graz, Austria.
⁴ Provinciaal Instituut voor Hygiëne, Antwerp, Belgium.
⁵ Eurocat Hainaut -Namur, Centre for Human Genetics, Institut de Pathologie et de Génétique, IPG, Charleroi, Belgium.
⁶ Paediatric Department, Hospital Lillebaelt, Kolding, Denmark.
⁷ Health Intelligence, Health Service Executive, Dublin, Ireland.
⁸ Public Health Department, HSE Southeast area, Lacken, Kilkenny, Ireland.
⁹ Department of Public Health, Health Service Executive South, Cork, Ireland.
¹⁰ Department of Health Information and Research, Guardamangia, Malta.
¹¹ Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
¹² Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
¹³ Public Health Division of Gipuzkoa, BioDonostia Research Institute, San Sebastian, Spain.
¹⁴ Rare Diseases Research Unit, Foundation for the Promotion of Health and Biomedical Research of the Valencian Region, Valencia, Spain.
¹⁵ National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
¹⁶ Department Health Sciences, University of Leicester, Leicester, UK.
¹⁷ Congenital Anomaly Register and Information Service for Wales, Public Health Wales, Swansea, UK.
¹⁸ Faculty of Medicine, University of Southampton and Wessex Clinical Genetics Service, Southampton, UK.
¹⁹ OMNI-Net Ukraine and Khmelnytsky Children Hospital, Khmelnytsky, Ukraine.
²⁰ INSERM U1153 (Obstetrical, Perinatal and Pediatric Epidemiology Research Team, Center for Biostatistics and Epidemiology), Maternité Port Royal, Paris, France.

PMID: 32101337
PMCID: PMC7064886
DOI: 10.1111/ppe.12655

Multilevel analyses of related public health indicators: The European Surveillance of Congenital Anomalies (EUROCAT) Public Health Indicators

Kate E Best et al. Paediatr Perinat Epidemiol. 2020 Mar.

. 2020 Mar;34(2):122-129.

doi: 10.1111/ppe.12655.

Authors

Affiliations

¹ Institute of Health & Society, Newcastle University, Newcastle upon Tyne, UK.
² Centre for Maternal, Fetal and Infant Research, Institute of Nursing and Health Research, Ulster University, Ulster, UK.
³ Medical University of Graz, Graz, Austria.
⁴ Provinciaal Instituut voor Hygiëne, Antwerp, Belgium.
⁵ Eurocat Hainaut -Namur, Centre for Human Genetics, Institut de Pathologie et de Génétique, IPG, Charleroi, Belgium.
⁶ Paediatric Department, Hospital Lillebaelt, Kolding, Denmark.
⁷ Health Intelligence, Health Service Executive, Dublin, Ireland.
⁸ Public Health Department, HSE Southeast area, Lacken, Kilkenny, Ireland.
⁹ Department of Public Health, Health Service Executive South, Cork, Ireland.
¹⁰ Department of Health Information and Research, Guardamangia, Malta.
¹¹ Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
¹² Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
¹³ Public Health Division of Gipuzkoa, BioDonostia Research Institute, San Sebastian, Spain.
¹⁴ Rare Diseases Research Unit, Foundation for the Promotion of Health and Biomedical Research of the Valencian Region, Valencia, Spain.
¹⁵ National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
¹⁶ Department Health Sciences, University of Leicester, Leicester, UK.
¹⁷ Congenital Anomaly Register and Information Service for Wales, Public Health Wales, Swansea, UK.
¹⁸ Faculty of Medicine, University of Southampton and Wessex Clinical Genetics Service, Southampton, UK.
¹⁹ OMNI-Net Ukraine and Khmelnytsky Children Hospital, Khmelnytsky, Ukraine.
²⁰ INSERM U1153 (Obstetrical, Perinatal and Pediatric Epidemiology Research Team, Center for Biostatistics and Epidemiology), Maternité Port Royal, Paris, France.

PMID: 32101337
PMCID: PMC7064886
DOI: 10.1111/ppe.12655

Abstract

Background: Public health organisations use public health indicators to guide health policy. Joint analysis of multiple public health indicators can provide a more comprehensive understanding of what they are intended to evaluate.

Objective: To analyse variaitons in the prevalence of congenital anomaly-related perinatal mortality attributable to termination of pregnancy for foetal anomaly (TOPFA) and prenatal diagnosis of congenital anomaly prevalence.

Methods: We included 55 363 cases of congenital anomalies notified to 18 EUROCAT registers in 10 countries during 2008-12. Incidence rate ratios (IRR) representing the risk of congenital anomaly-related perinatal mortality according to TOPFA and prenatal diagnosis prevalence were estimated using multilevel Poisson regression with country as a random effect. Between-country variation in congenital anomaly-related perinatal mortality was measured using random effects and compared between the null and adjusted models to estimate the percentage of variation in congenital anomaly-related perinatal mortality accounted for by TOPFA and prenatal diagnosis.

Results: The risk of congenital anomaly-related perinatal mortality decreased as TOPFA and prenatal diagnosis prevalence increased (IRR 0.79, 95% confidence interval [CI] 0.72, 0.86; and IRR 0.88, 95% CI 0.79, 0.97). Modelling TOPFA and prenatal diagnosis together, the association between congenital anomaly-related perinatal mortality and TOPFA prevalence became stronger (RR 0.70, 95% CI 0.61, 0.81). The prevalence of TOPFA and prenatal diagnosis accounted for 75.5% and 37.7% of the between-country variation in perinatal mortality, respectively.

Conclusion: We demonstrated an approach for analysing inter-linked public health indicators. In this example, as TOPFA and prenatal diagnosis of congenital anomaly prevalence decreased, the risk of congenital anomaly-related perinatal mortality increased. Much of the between-country variation in congenital anomaly-related perinatal mortality was accounted for by TOPFA, with a smaller proportion accounted for by prenatal diagnosis.

Keywords: perinatal mortality; termination of pregnancy for foetal anomaly.

PubMed Disclaimer

Conflict of interest statement

None.

Figures

**Figure 1**
Actual and modelled association between perinatal mortality and TOPFA prevalence

**Figure 2**
Actual and modelled association between perinatal mortality and prenatal diagnosis prevalence. ^¥Prenatal diagnosis available for Hainaut only, ^†Prenatal diagnosis available for Cork and Kerry and SE Ireland but not Dublin

See this image and copyright information in PMC

Cited by

Trends in the incidence of major birth defects after assisted reproductive technologies in Lombardy Region, Northern Italy.
Galati G, Esposito G, Somigliana E, Muzii L, Franchi M, Corrao G, Parazzini F. Galati G, et al. J Assist Reprod Genet. 2023 Apr;40(4):857-863. doi: 10.1007/s10815-023-02732-z. Epub 2023 Feb 10. J Assist Reprod Genet. 2023. PMID: 36763300 Free PMC article.
Perinatal Risks of Neonatal and Infant Mortalities in a Sub-provincial Region of China: A Livebirth Population-based Cohort Study.
Xu Y, Guo X, Pan Z, Zheng G, Li X, Qi T, Zhu X, Wang H, Ding W, Tian Z, Wang H, Yue H, Sun B; Huai’an Perinatal-Neonatal Collaborative Study Group. Xu Y, et al. BMC Pregnancy Childbirth. 2022 Apr 19;22(1):338. doi: 10.1186/s12884-022-04653-8. BMC Pregnancy Childbirth. 2022. PMID: 35440021 Free PMC article.
Analysis of early neonatal case fatality rate among newborns with congenital hydrocephalus, a 2000-2014 multi-country registry-based study.
Gili JA, López-Camelo JS, Nembhard WN, Bakker M, de Walle HEK, Stallings EB, Kancherla V; ECEMC Peripheral Group; Contiero P, Dastgiri S, Feldkamp ML, Nance A, Gatt M, Martínez L, Canessa MA, Groisman B, Hurtado-Villa P, Källén K, Landau D, Lelong N, Morgan M, Arteaga-Vázquez J, Pierini A, Rissmann A, Sipek A, Szabova E, Wertelecki W, Zarante I, Canfield MA, Mastroiacovo P. Gili JA, et al. Birth Defects Res. 2022 Jul 15;114(12):631-644. doi: 10.1002/bdr2.2045. Epub 2022 May 28. Birth Defects Res. 2022. PMID: 35633200 Free PMC article.
Temporal and geographical variations in survival of children born with congenital anomalies in Europe: A multi-registry cohort study.
Santoro M, Coi A, Pierini A, Rankin J, Glinianaia SV, Tan J, Reid A, Garne E, Loane M, Given J, Aizpurua A, Astolfi G, Barisic I, Cavero-Carbonell C, de Walle HEK, Den Hond E, García-Villodre L, Gatt M, Gissler M, Jordan S, Khoshnood B, Kiuru-Kuhlefelt S, Klungsøyr K, Lelong N, Lutke R, Mokoroa O, Nelen V, Neville AJ, Odak L, Rissmann A, Scanlon I, Urhoj SK, Wellesley D, Wertelecki W, Yevtushok L, Morris JK. Santoro M, et al. Paediatr Perinat Epidemiol. 2022 Nov;36(6):792-803. doi: 10.1111/ppe.12884. Epub 2022 Jun 8. Paediatr Perinat Epidemiol. 2022. PMID: 35675091 Free PMC article.
Outcome of neonatal hypoxemic respiratory failure: a livebirth population-based retrospective survey.
Ding S, Xu Y, Wang H, Yue H, Pan Z, Sun B; Huai’an Perinatal-Neonatal Study Group. Ding S, et al. BMC Pediatr. 2022 Sep 17;22(1):552. doi: 10.1186/s12887-022-03603-9. BMC Pediatr. 2022. PMID: 36115974 Free PMC article.

See all "Cited by" articles

References

1. Murray CJL, Lopez AD. Global mortality, disability, and the contribution of risk factors: global Burden of Disease Study. Lancet. 1997;349:1436‐1442. - PubMed
1. Bauer G, Davies JK, Pelikan J, Group ETW . The EUHPID Health Development Model for the classification of public health indicators. Health Promot Int. 2006;21:153‐159. - PubMed
1. European Commission . European core health indicators. 2015. http://ec.europa.eu/health/indicators/echi/list/index_en.htm. Accessed June 1, 2019.
1. World Health Organisation . Global Health Observatory data. 2015. http://www.who.int/gho/indicator_registry/en/. Accessed June 1, 2019.
1. Dolk H, Loane M, Garne E. The prevalence of congenital anomalies in Europe In: Posada de la Paz M, Groft S, eds. Rare Diseases Epidemiology. Dordrecht: Springer Netherlands; 2010; 349‐364. - PubMed

Publication types

Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

Grants and funding

WT_/Wellcome Trust/United Kingdom

LinkOut - more resources

Full Text Sources
Medical
- MedlinePlus Health Information

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Multilevel analyses of related public health indicators: The European Surveillance of Congenital Anomalies (EUROCAT) Public Health Indicators

Affiliations

Multilevel analyses of related public health indicators: The European Surveillance of Congenital Anomalies (EUROCAT) Public Health Indicators

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Similar articles

Cited by

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical

Abstract

Conflict of interest statement

Figures

Similar articles

Cited by

References

Publication types

MeSH terms

Related information

Grants and funding

LinkOut - more resources

Full Text Sources

Medical