Peer-reviewed article
Assessing the impact of social determinants of health on rising preterm birth trends in England. A longitudinal ecological study, 2012-17.
Wilcock A, Bennett D, Taylor-Robinson D, McHale P ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study examined why preterm birth rates increased in England between 2012 and 2017, focusing on social and economic factors. Researchers found that the gap in preterm births between rich and poor communities widened significantly, with the poorest areas experiencing the largest increase. Each percentage point increase in child poverty was associated with more preterm births. The findings suggest that policies addressing child poverty could help reduce inequalities in preterm birth rates.
Key points
- Preterm birth rates rose in England between 2012 and 2017, with the gap between most and least disadvantaged communities widening by 35%
- For each percentage point increase in child poverty, an estimated 0.24 additional births per 1000 were preterm
- Preterm birth is the UK's leading cause of neonatal morbidity and mortality
- The poorest areas of England experienced disproportionate increases in preterm births during this period
- Social determinants of health, particularly child poverty and unemployment, were associated with preterm birth trends
Limitations
This is an ecological study using area-level data for Local Authorities rather than individual-level data, which limits the ability to establish direct causal relationships between specific social determinants and preterm birth. The study cannot account for unmeasured factors or changes in clinical practice that may have contributed to rising preterm birth trends.
Abstract
Background Preterm birth (PTB) is the UK's leading cause of neonatal morbidity and mortality. There is international evidence of socioeconomic inequalities in PTB. Between 2012 and 2017, the proportion of live births occurring prematurely increased in England. This study explores how changes to major social determinants of health (SDH) may have contributed to recent trends. Methods We analysed PTB trends and their correlation with contemporaneous trends in major SDH predictors (socioeconomic status, income, and unemployment) for English Local Authorities. We used both fixed-effects and mixed-effects modelling to estimate the association between SDH and PTB rates between 2012 and 2017. Results The gap in PTB inequalities widened over the study period, with the absolute difference in PTB rates between most and least disadvantaged communities rising by 35%. Mixed-effects analysis demonstrated an association between the proportion of children living in low-income households and PTB; for each percentage point increase in child poverty, an estimated additional 0.24 per 1000 births was preterm. Conclusion We provide evidence of rising PTB rates in England prior to the pandemic, which disproportionately affected the poorest areas of the country. Policies targeting areas with higher child poverty rates are likely to reduce inequalities in PTB in England.