Estimating subnational under-five mortality rates using a spatio-temporal Age-Period-Cohort model

Area of Science:

• Demography
• Public Health
• Biostatistics

Background:

• Subnational under-five mortality rates (U5MRs) are critical for the UN's Sustainable Development Goals, aiming to reduce mortality inequalities.
• Existing models for U5MRs in Low- and Middle-Income Countries (LMICs) often smooth over birth-cohort trends, potentially obscuring key insights.
• Data sparsity in LMICs presents a significant challenge for accurate mortality estimation.

Purpose of the Study:

• To develop and apply an innovative Age-Period-Cohort (APC) model for estimating subnational U5MRs in Kenya.
• To account for spatial trends and complex survey designs in mortality estimation.
• To provide a more nuanced understanding of under-five mortality by incorporating birth-cohort effects.

Main Methods:

• Utilized survey data from Kenya to implement an APC model.
• The model incorporates age, period, and birth-cohort effects to estimate U5MRs.
• Accounted for spatial trends and complex survey design features within the statistical model.

Main Results:

• The study validated the APC model's results against current estimation methods.
• The inclusion of birth-cohort trends provided novel insights into U5MR patterns.
• The developed method demonstrated flexibility for application in other LMICs.

Conclusions:

• The Age-Period-Cohort model offers a more comprehensive approach to estimating subnational U5MRs.
• Incorporating birth-cohort analysis is crucial for a deeper understanding of child mortality dynamics.
• This flexible methodology can enhance global efforts to reduce child mortality inequalities.