Multilevel determinants of maternal/neonatal health outcomes in Kisumu and Siaya Counties in western Kenya, in context of Covid-19
1
School of Medicine, Keele University, Keele, United Kingdom
Popul. Med. 2026;8(Supplement Supplement 1):A1383
ABSTRACT
BACKGROUND:
Counties in western Kenya report significantly higher than national average levels of maternal /infant mortality. This paper examines the multilevel determinants, and the role of Covid-19 in moderating the determinants of maternal/neonatal health outcomes in Kisumu and Siaya counties of western Kenya.
METHODS:
The study is based on analysis of routinely collected individual-level data from maternity registers in health facilities in Kisumu and Siaya counties during 2018-2024 period, covering pre and post Covid-19 periods. Individual-level data from health facilities were merged with community-level data from respective community health units (CHUs) to enable examination of multilevel determinants of maternal/neonatal health outcomes. Key outcomes included maternal mortality, stillbirth, neonatal mortality and premature delivery. Analysis involved use of three level Logistic regression models, taking into account individual level-level risk factors (e.g. age, parity, marital status, HIV status, antenatal care visits, labour stage at admission) as well as community/CHU factors (e.g. visits by community health workers, proportion of households in CHU with health insurance, access to health facility ) and health facility factors (e.g. facility level2-5, pregnancy complications at facility, deliveries from HIV+ women). Interactions of Covid-19 period with other key predictors was included in the analyses to help establish the extent to which Covid-19 may have moderated the multilevel determinants of key maternal/neonatal outcomes.
RESULTS:
Preliminary findings (analysis on-going) reveal interesting patterns on the individual, community and facility-level determinants of maternal/neonatal health outcomes at the study setting, moderated by Covid-19 impact. The use of individual level data extracted from maternity registers provides a unique opportunity for improved understanding of multilevel determinants of maternal/neonatal health outcomes, including individual level risk factors, necessary for risk stratification and targeted effective interventions.
CONCLUSIONS:
The paper makes an important contribution in improving understanding of multilevel determinants of maternal mortality and other adverse maternal/neonatal health outcomes.
Counties in western Kenya report significantly higher than national average levels of maternal /infant mortality. This paper examines the multilevel determinants, and the role of Covid-19 in moderating the determinants of maternal/neonatal health outcomes in Kisumu and Siaya counties of western Kenya.
METHODS:
The study is based on analysis of routinely collected individual-level data from maternity registers in health facilities in Kisumu and Siaya counties during 2018-2024 period, covering pre and post Covid-19 periods. Individual-level data from health facilities were merged with community-level data from respective community health units (CHUs) to enable examination of multilevel determinants of maternal/neonatal health outcomes. Key outcomes included maternal mortality, stillbirth, neonatal mortality and premature delivery. Analysis involved use of three level Logistic regression models, taking into account individual level-level risk factors (e.g. age, parity, marital status, HIV status, antenatal care visits, labour stage at admission) as well as community/CHU factors (e.g. visits by community health workers, proportion of households in CHU with health insurance, access to health facility ) and health facility factors (e.g. facility level2-5, pregnancy complications at facility, deliveries from HIV+ women). Interactions of Covid-19 period with other key predictors was included in the analyses to help establish the extent to which Covid-19 may have moderated the multilevel determinants of key maternal/neonatal outcomes.
RESULTS:
Preliminary findings (analysis on-going) reveal interesting patterns on the individual, community and facility-level determinants of maternal/neonatal health outcomes at the study setting, moderated by Covid-19 impact. The use of individual level data extracted from maternity registers provides a unique opportunity for improved understanding of multilevel determinants of maternal/neonatal health outcomes, including individual level risk factors, necessary for risk stratification and targeted effective interventions.
CONCLUSIONS:
The paper makes an important contribution in improving understanding of multilevel determinants of maternal mortality and other adverse maternal/neonatal health outcomes.
| eISSN: | 2654-1459 |
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