Age- and Cause-specific Mortality Patterns and Trends in an Urban Informal Settlement, Kibera, Kenya, 2009–2018

Abstract

Title: Age and cause specific mortality patterns and trends in an urban informal settlement, Kibera, Kenya, 2009–2018 Background: Effective health services planning and prioritization require reliable and timely mortality data. In addition, data on deaths and causes of death is needed for evaluating the impact of public health interventions. However, these data are lacking for populations in resource-poor settings particularly for those living in urban informal settlements. Kibera slum being the largest urban informal settlements in Kenya is characterized by overcrowding, poor infrastructure and poor sanitation. However, compared to rural settings data on mortality in children and adults residing in informal settlements is lacking. Broad Objective: To determine patterns and trends in age and cause specific mortality rates within an informal settlement in Kibera, Kenya. Specific Objectives: The specific objectives were to determine the age-and cause specific mortality rate and the trend in Age and cause specific mortality rate in an urban informal settlement in Kibera, Kenya. Study Design: This was a retrospective open cohort study of all deaths among residents followed within the KEMRI and CDC population-based infectious disease surveillance (KEMRI Protocol #2761). Methodology: Secondary data was extracted from the KEMRI and CDC population-based infectious disease surveillance database for all deaths occurring among residents of all ages at the time of death, between 1st January 2009 and 31st December 2018. Person years of observation

was computed annually for the period for all individuals who were residents of the study area. A Bayesian probabilistic model (InterVA model) was used for assigning causes of death (CoD) using collected data from verbal autopsy interview data. Cause specific mortality fractions and rates were computed using the generated CoDs. Age-and cause mortality rates were computed as deaths per 1000 person-years of observation. We stratified mortality analysis by sex and age groups. Trends in age-and cause specific mortality rates over time were identified using a non-parametric test; Mann-Kendall trend test............