A new model developed by researchers can more accurately and efficiently assess which children are at the highest risk of preventable death.
A new model developed by researchers can more accurately and efficiently assess which children are at the highest risk of preventable death. The findings of the study are published in PLOS ONE and conducted by Antonio Ramos from the Fielding School of Public Health, UCLA, U.S., and colleagues.
‘Identifying at risk children as those in the 20% poorest will miss the majority of children who could benefit from health policy interventions.’
One of UN's Sustainable Development Goals aims to see a substantial reduction in preventable deaths for children five and younger by 2030. However, recent studies have shown that multiple risk factors are implicated in under-5 mortality, and program targeting based purely on poverty can be inefficient.
A new and more comprehensive model developed by Ramos and colleagues used data from multiple demographic variables to measure mortality inequities and identify high-risk subpopulations of kids that would otherwise be left behind.
The authors used data on 1,691,039 births from 182 different surveys across 67 low- and middle-income countries (LMIC). After estimating each child's mortality risk in the dataset, the authors went on to quantify mortality risk within and between socioeconomic groups and describe the highest-risk sub-populations.
Study Results
- More variability in mortality within socioeconomic groups than between them--and within countries observed.
- Socioeconomic membership explained less than 20% of the variation in mortality risk.
- The highest-risk births are from mothers in the lowest socioeconomic group, live in rural areas, and/or already experienced the death of a previous child.
- Poverty is linked to an increased risk in mortality.
Advertisement