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BackgroundReducing preterm birth and stillbirth and improving outcomes for babies born too soon is essential to reduce under-5 mortality globally. In the context of a rapidly evolving evidence base and issues with extrapolating efficacy data from high- to low-income settings, an assessment of the evidence for maternal and newborn interventions specific to low- and middle-income countries (LMICs) is required.MethodsA systematic review of the literature was done. We included all studies performed in LMICs since the Every Newborn Action Plan,1 between 2013 - 2018, which reported on interventions where the outcome assessed was reduction in preterm birth or stillbirthincidence and/or a reduction in preterm infant neonatal mortality. Evidence was categorised according to maternal or neonatal intervention groups and a narrative synthesis conducted.Findings179 studies (147 primary evidence studies and 32 systematic reviews) were identified in 82 LMICs. 81 studies reported on maternal interventions and 98 reported on neonatal interventions. Interventions in pregnant mothers which resulted in significant reductions in preterm birth and stillbirth were (i) multiple micronutrient supplementation and (ii) enhanced quality of antenatal care. Routine antenatal ultrasound in LMICs increasedidentification of fetal antenatal conditions but did not reduce stillbirth or preterm birth due to the absence of services to manage these diagnoses. Interventions in pre-term neonates which improved their survival included (i) feeding support including probiotics and (ii) thermal regulation. Improved provision of neonatal resuscitation did not improve pre-term mortality rates, highlighting the importance of post-resuscitation care. Communitymobilisation, for example through community education packages, was found to be an effective way of delivering interventions.ConclusionsEvidence supports the implementation of several low-cost interventions with the potential to deliver reductions in preterm birth and stillbirth and improve outcomes for preterm babies in LMICs. These, however, must be complemented by overall health systems strengthening to be effective. Quality improvement methodology and learning health systems approaches can provide important means of understanding and tackling implementation challenges within local contexts. Further pragmatic efficacy trials of interventions in LMICs are essential, particularly for interventions not previously tested in these contexts.

Introduction Preterm delivery is a major global public health challenge. The objective of this study was to determine how preterm delivery rates differ in a country with a very high human development index and to explore rural vs urban environmental and socioeconomic factors that may be responsible for this variation. Material and methods A population‐based study was performed using data from the Swedish Medical Birth Register from 1998 to 2013. Sweden was chosen as a model because of its validated, routinely collected data and availability of individual social data. The total population comprised 1 335 802 singleton births. A multiple linear regression was used to adjust gestational age for known risk factors (maternal smoking, ethnicity, maternal education, maternal age, height, fetal sex, maternal diabetes, maternal hypertension, and parity). A second and a third model were subsequently fitted allowing separate intercepts for each municipality (as fixed or random effects). Adjusted gestational ages were converted to preterm delivery rates and mapped onto maternal residential municipalities. Additionally, the effects of six rural vs urban environmental and socioeconomic factors on gestational age were tested using a simple weighted linear regression. Results The study population preterm delivery rate was 4.12%. Marked differences from the overall preterm delivery rate were observed (rate estimates ranged from 1.73% to 6.31%). The statistical significance of this heterogeneity across municipalities was confirmed by a chi‐squared test (P < 0.001). Around 20% of the gestational age variance explained by the full model (after adjustment for known variables described above) could be attributed to municipality‐level effects. In addition, gestational age was found to be longer in areas with a higher fraction of built‐upon land and other urban features. Conclusions After adjusting for known risk factors, large geographical differences in rates of preterm delivery remain. Additional analyses to look at the effect of environmental and socioeconomic factors on gestational age found an increased gestational age in urban areas. Future research strategies could focus on investigating the urbanity effect to try to explain preterm delivery variation across countries with a very high human development index.