Changing patterns of gender inequities in childhood mortalities during the Sustainable Development Goals era in Nigeria: findings from an artificial neural network analysis.

ABSTRACT:

Objectives

In line with the child survival and gender equality targets of Sustainable Development Goals (SDG) 3 and 5, we aimed to: (1) estimate the age and sex-specific mortality trends in child-related SDG indicators (ie, neonatal mortality rate (NMR) and under-five mortality rate (U5MR)) over the 1960s-2017 period, and (2) estimate the expected annual reduction rates needed to achieve the SDG-3 targets by projecting rates from 2018 to 2030.

Design

Group method of data handling-type artificial neural network (GMDH-type ANN) time series.

Methods

This study used an artificial intelligence time series (GMDH-type ANN) to forecast age-specific childhood mortality rates (neonatal and under-five) and sex-specific U5MR from 2018 to 2030. The data sets were the yearly histor

SUBMITTER: Adeyinka DA 

PROVIDER: S-EPMC7849876 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature