What is the relationship between deprivation, modifiable factors and childhood deaths: a cohort study using the English National Child MortalityDatabase.

OBJECTIVES

The aim of this analysis is to identify the patterns of social deprivation and childhood mortality; and identify potential points where public health, social and education interventions, or health policy may be best targeted.

DESIGN

Decile of deprivation and underlying population distribution was derived using Office for National Statistics data. The risk of death was then derived using a Poisson regression model, calculating the increasing risk of death for each increasing deprivation decile.

SETTING

England.

PARTICIPANTS

2688 deaths before 18 years of age reviewed between April 2019 and March 2020.

MAIN OUTCOME MEASURES

The relationship between deprivation and risk of death; for deaths with, and without modifiable factors.

RESULTS

There was evidence of increasing mortality risk with increase in deprivation decile, with children in the least deprived areas having a mortality of 13.25 (11.78-14.86) per 100 000 person-years, compared with 31.14 (29.13-33.25) in the most deprived decile (RR 1.08 (95% CI 1.07 to 1.10)); with the gradient of risk stronger in children who died with modifiable factors than those without (RR 1.12 (95% CI 1.09 to 1.15)) vs (RR 1.07 (95% CI 1.05 to 1.08)). Deprivation subdomains of employment, adult education, barriers to housing and services, and indoor living environments appeared to be the most important predictors of child mortality CONCLUSIONS: There is a clear gradient of increasing child mortality across England as measures of deprivation increase; with a striking finding that this varied little by area, age or other demographic factor. Over one-fifth of all child deaths may be avoided if the most deprived half of the population had the same mortality as the least deprived. Children dying in more deprived areas may have a greater proportion of avoidable deaths. Adult employment, and improvements to housing, may be the most efficient place to target resources to reduce these inequalities.