Producing valid statistics when legislation, culture, and medical practices differ for births at or before the threshold of survival: Report of a European workshop

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Can the Apgar Score be Used for International Comparisons of Newborn Health?

Background: The Apgar score has been shown to be predictive of neonatal mortality in clinical and population studies, but has not been used for international comparisons. We examined population-level distributions in Apgar scores and associations with neonatal mortality in Europe. Methods: Aggregate data on the 5 minute Apgar score for live births and neonatal mortality rates from countries participating in the Euro-Peristat project in 2004 and 2010 were analysed. Country level associations between the Apgar score and neonatal mortality were assessed using the Spearman rank correlation coefficient. Results: Twenty-three countries or regions provided data on Apgar at 5 minutes, covering 2 183 472 live births. Scores <7 ranged from 0.3% to 2.4% across countries in 2004 and 2010 and were correlated over time (q = 0.88, P < 0.01). There were large differences in healthy baby scores: scores of 10 ranged from 8.8% to 92.7% whereas scores of 9 or 10 ranged from 72.9% to 96.8%. Countries more likely to score 10 s, as opposed to 9 s, for healthy babies had lower proportions of Apgar <7 (q = 0.43, P = 0.04). Neonatal mortality rates were weakly correlated with Apgar score <7 (q = 0.06, P = 0.61), but differences over time in these two indicators were correlated (q =0.56, P = 0.02). Conclusions: Large variations in the distribution of Apgar scores likely due to national scoring practices make the Apgar score an unsuitable indicator for benchmarking newborn health across countries. However, country-level trends over time in the Apgar score may reflect real changes and merit further investigation.This study was funded by grants from the European Commission for the Euro-Peristat project: 2010 13 01 and for the Bridge Health project: 664691. The funding agency was not involved in the study. Marie Delnord received doctoral funding from Paris Descartes University, Paris, France

Cross-Country Individual Participant Analysis of 4.1 Million Singleton Births in 5 Countries with Very High Human Development Index...

Background: Preterm birth is the most common single cause of perinatal and infant mortality, affecting 15 million infants worldwide each year with global rates increasing. Understanding of risk factors remains poor, and preventive interventions have only limited benefit. Large differences exist in preterm birth rates across high income countries. We hypothesized that understanding the basis for these wide variations could lead to interventions that reduce preterm birth incidence in countries with high rates. We thus sought to assess the contributions of known risk factors for both spontaneous and provider-initiated preterm birth in selected high income countries, estimating also the potential impact of successful interventions due to advances in research, policy and public health, or clinical practice. Methods: We analyzed individual patient-level data on 4.1 million singleton pregnancies from four countries with very high human development index (Czech Republic, New Zealand, Slovenia, Sweden) and one comparator U.S. state (California) to determine the specific contribution (adjusting for confounding effects) of 21 factors. Both individual and population-attributable preterm birth risks were determined, as were contributors to cross-country differences. We also assessed the ability to predict preterm birth given various sets of known risk factors. Findings: Previous preterm birth and preeclampsia were the strongest individual risk factors of preterm birth in all datasets, with odds ratios of 4.6–6.0 and 2.8–5.7, respectively, for individual women having those characteristics. In contrast, on a population basis, nulliparity and male sex were the two risk factors with the highest impact on preterm birth rates, accounting for 25–50% and 11–16% of excess population attributable risk, respectively (p < 0.001). The importance of nulliparity and male sex on population attributable risk was driven by high prevalence despite low odds ratios for individual women. More than 65% of the total aggregated risk of preterm birth within each country lacks a plausible biologic explanation, and 63% of difference between countries cannot be explained with known factors; thus, research is necessary to elucidate the underlying mechanisms of preterm birth and, hence, therapeutic intervention. Surprisingly, variation in prevalence of known risk factors accounted for less than 35% of the difference in preterm birth rates between countries. Known risk factors had an area under the curve of less than 0.7 in ROC analysis of preterm birth prediction within countries. These data suggest that other influences, as yet unidentified, are involved in preterm birth. Further research into biological mechanisms is warranted. Conclusions: We have quantified the causes of variation in preterm birth rates among countries with very high human development index. The paucity of explicit and currently identified factors amenable to intervention illustrates the limited impact of changes possible through current clinical practice and policy interventions. Our research highlights the urgent need for research into underlying biological causes of preterm birth, which alone are likely to lead to innovative and efficacious interventions

Neonatal mortality risk for vulnerable newborn types in 15 countries using 125.5 million nationwide birth outcome records, 2000-2020.

OBJECTIVE: To compare neonatal mortality associated with six novel vulnerable newborn types in 125.5 million live births across 15 countries, 2000-2020. DESIGN: Population-based, multi-country study. SETTING: National data systems in 15 middle- and high-income countries. METHODS: We used individual-level data sets identified for the Vulnerable Newborn Measurement Collaboration. We examined the contribution to neonatal mortality of six newborn types combining gestational age (preterm [PT] versus term [T]) and size-for-gestational age (small [SGA], 90th centile) according to INTERGROWTH-21st newborn standards. Newborn babies with PT or SGA were defined as small and T + LGA was considered as large. We calculated risk ratios (RRs) and population attributable risks (PAR%) for the six newborn types. MAIN OUTCOME MEASURES: Mortality of six newborn types. RESULTS: Of 125.5 million live births analysed, risk ratios were highest among PT + SGA (median 67.2, interquartile range [IQR] 45.6-73.9), PT + AGA (median 34.3, IQR 23.9-37.5) and PT + LGA (median 28.3, IQR 18.4-32.3). At the population level, PT + AGA was the greatest contributor to newborn mortality (median PAR% 53.7, IQR 44.5-54.9). Mortality risk was highest among newborns born before 28 weeks (median RR 279.5, IQR 234.2-388.5) compared with babies born between 37 and 42 completed weeks or with a birthweight less than 1000 g (median RR 282.8, IQR 194.7-342.8) compared with those between 2500 g and 4000 g as a reference group. CONCLUSION: Preterm newborn types were the most vulnerable, and associated with the highest mortality, particularly with co-existence of preterm and SGA. As PT + AGA is more prevalent, it is responsible for the greatest burden of neonatal deaths at population level

Cross-Country Individual Participant Analysis of 4.1 Million Singleton Births in 5 Countries with Very High Human Development Index Confirms Known Associations but Provides No Biologic Explanation for 2/3 of All Preterm Births.

BACKGROUND: Preterm birth is the most common single cause of perinatal and infant mortality, affecting 15 million infants worldwide each year with global rates increasing. Understanding of risk factors remains poor, and preventive interventions have only limited benefit. Large differences exist in preterm birth rates across high income countries. We hypothesized that understanding the basis for these wide variations could lead to interventions that reduce preterm birth incidence in countries with high rates. We thus sought to assess the contributions of known risk factors for both spontaneous and provider-initiated preterm birth in selected high income countries, estimating also the potential impact of successful interventions due to advances in research, policy and public health, or clinical practice. METHODS: We analyzed individual patient-level data on 4.1 million singleton pregnancies from four countries with very high human development index (Czech Republic, New Zealand, Slovenia, Sweden) and one comparator U.S. state (California) to determine the specific contribution (adjusting for confounding effects) of 21 factors. Both individual and population-attributable preterm birth risks were determined, as were contributors to cross-country differences. We also assessed the ability to predict preterm birth given various sets of known risk factors. FINDINGS: Previous preterm birth and preeclampsia were the strongest individual risk factors of preterm birth in all datasets, with odds ratios of 4.6-6.0 and 2.8-5.7, respectively, for individual women having those characteristics. In contrast, on a population basis, nulliparity and male sex were the two risk factors with the highest impact on preterm birth rates, accounting for 25-50% and 11-16% of excess population attributable risk, respectively (p<0.001). The importance of nulliparity and male sex on population attributable risk was driven by high prevalence despite low odds ratios for individual women. More than 65% of the total aggregated risk of preterm birth within each country lacks a plausible biologic explanation, and 63% of difference between countries cannot be explained with known factors; thus, research is necessary to elucidate the underlying mechanisms of preterm birth and, hence, therapeutic intervention. Surprisingly, variation in prevalence of known risk factors accounted for less than 35% of the difference in preterm birth rates between countries. Known risk factors had an area under the curve of less than 0.7 in ROC analysis of preterm birth prediction within countries. These data suggest that other influences, as yet unidentified, are involved in preterm birth. Further research into biological mechanisms is warranted. CONCLUSIONS: We have quantified the causes of variation in preterm birth rates among countries with very high human development index. The paucity of explicit and currently identified factors amenable to intervention illustrates the limited impact of changes possible through current clinical practice and policy interventions. Our research highlights the urgent need for research into underlying biological causes of preterm birth, which alone are likely to lead to innovative and efficacious interventions

Vulnerable newborn types: Analysis of population-based registries for 165 million births in 23 countries, 2000-2021.

OBJECTIVE: To examine the prevalence of novel newborn types among 165 million live births in 23 countries from 2000 to 2021. DESIGN: Population-based, multi-country analysis. SETTING: National data systems in 23 middle- and high-income countries. POPULATION: Liveborn infants. METHODS: Country teams with high-quality data were invited to be part of the Vulnerable Newborn Measurement Collaboration. We classified live births by six newborn types based on gestational age information (preterm 90th centile) for gestational age, according to INTERGROWTH-21st standards. We considered small newborn types of any combination of preterm or SGA, and term + LGA was considered large. Time trends were analysed using 3-year moving averages for small and large types. MAIN OUTCOME MEASURES: Prevalence of six newborn types. RESULTS: We analysed 165 017 419 live births and the median prevalence of small types was 11.7% - highest in Malaysia (26%) and Qatar (15.7%). Overall, 18.1% of newborns were large (term + LGA) and was highest in Estonia 28.8% and Denmark 25.9%. Time trends of small and large infants were relatively stable in most countries. CONCLUSIONS: The distribution of newborn types varies across the 23 middle- and high-income countries. Small newborn types were highest in west Asian countries and large types were highest in Europe. To better understand the global patterns of these novel newborn types, more information is needed, especially from low- and middle-income countries

Using Robson's Ten‐Group Classification System for comparing caesarean section rates in Europe: an analysis of routine data from the Euro‐Peristat study

Objective Robson's Ten Group Classification System (TGCS) creates clinically relevant sub‐groups for monitoring caesarean birth rates. This study assesses whether this classification can be derived from routine data in Europe and uses it to analyse national caesarean rates. Design Observational study using routine data. Setting Twenty‐seven EU member states plus Iceland, Norway, Switzerland and the UK. Population All births at ≥22 weeks of gestational age in 2015. Methods National statistical offices and medical birth registers derived numbers of caesarean births in TGCS groups. Main outcome measures Overall caesarean rate, prevalence and caesarean rates in each of the TGCS groups. Results Of 31 countries, 18 were able to provide data on the TGCS groups, with UK data available only from Northern Ireland. Caesarean birth rates ranged from 16.1 to 56.9%. Countries providing TGCS data had lower caesarean rates than countries without data (25.8% versus 32.9%, P = 0.04). Countries with higher caesarean rates tended to have higher rates in all TGCS groups. Substantial heterogeneity was observed, however, especially for groups 5 (previous caesarean section), 6, 7 (nulliparous/multiparous breech) and 10 (singleton cephalic preterm). The differences in percentages of abnormal lies, group 9, illustrate potential misclassification arising from unstandardised definitions. Conclusions Although further validation of data quality is needed, using TGCS in Europe provides valuable comparator and baseline data for benchmarking and surveillance. Higher caesarean rates in countries unable to construct the TGCS suggest that effective routine information systems may be an indicator of a country's investment in implementing evidence‐based caesarean policies. Tweetable abstract Many European countries can provide Robson's Ten‐Group Classification to improve caesarean rate comparisons