TY - JOUR
T1 - Predictors and disparities in neonatal and under 5 mortality in rural Pakistan
T2 - cross sectional analysis
AU - Memon, Zahid
AU - Fridman, Daniel
AU - Soofi, Sajid
AU - Ahmed, Wardah
AU - Muhammad, Shah
AU - Rizvi, Arjumand
AU - Ahmed, Imran
AU - Wright, James
AU - Cousens, Simon
AU - Bhutta, Zulfiqar A.
N1 - Publisher Copyright:
© 2023 The Author(s)
PY - 2023/8
Y1 - 2023/8
N2 - Background: Adopted in 2015, the sustainable development goals (SDGs) have set specific targets (SDG 3.2) for countries to reduce their neonatal mortality rate (NMR) to below 12 deaths per 1000 live births and under 5 mortality rate (U5MR) to below 25 deaths per 1000 live births by 2030. For Pakistan to achieve these targets, there is a need to measure these rates and understand the predictors of child mortality at sub-national level. Launched in 2016, the Umeed-e-Nau (UeN) or New Hope project is based on scaling up proven and effective Maternal and Newborn Child Health (MNCH) interventions in 8 of the highest burden districts of the country, using existing public sector platforms in Pakistan at both the community and facility level. The primary aim of the project is to reduce perinatal mortality in these districts by 20% from baseline. Methods: We report overall neonatal and post neonatal mortality rates for the two years preceding the UeN baseline household survey. Rates were calculated using the synthetic cohort probability method and predictors of neonatal and post neonatal mortality examined using Cox regression. To investigate spatial variations in the mortality rates, we calculated Moran's I at the district level using predicted probabilities of mortality. Finally, we create district level maps of predicted under 5 child mortality using a stochastic partial differentiation approach. Findings: A total of 26,258 children contributed to the analysis of mortality with 838 deaths in the neonatal period and 2236 under-5 deaths during the observation period from March 1, 2015 to March 17, 2017. Overall, we estimated the NMR to be 29.2 per 1000 live births (95% CI: 26.9–31.4) and the U5MR to be 86.1 per 1000 live births (95% CI: 85.5–86.8). We found evidence of within-district geospatial clustering of under 5 mortality (P < 0.0001) and that social factors (poverty, illiteracy, multiparity), poor coverage of community health workers and distance from health facilities were strongly associated with child mortality. Interpretation: Important factors associated with neonatal and post-neonatal mortality in our study population included maternal education, parity, household size and gender. Additionally, antenatal care coverage (at least 4 visits) was specifically associated with neonatal mortality only, whereas, LHW coverage and distance to health facility were strongly associated with post-neonatal mortality. These findings emphasise the need for comprehensive, multisectoral strategies to be implemented for future maternal and child health programs and outreach services in rural areas. Funding: The study was funded by an unrestricted grant from the Bill & Melinda Gates Foundation to the Aga Khan University (Grant OPP 1148892).
AB - Background: Adopted in 2015, the sustainable development goals (SDGs) have set specific targets (SDG 3.2) for countries to reduce their neonatal mortality rate (NMR) to below 12 deaths per 1000 live births and under 5 mortality rate (U5MR) to below 25 deaths per 1000 live births by 2030. For Pakistan to achieve these targets, there is a need to measure these rates and understand the predictors of child mortality at sub-national level. Launched in 2016, the Umeed-e-Nau (UeN) or New Hope project is based on scaling up proven and effective Maternal and Newborn Child Health (MNCH) interventions in 8 of the highest burden districts of the country, using existing public sector platforms in Pakistan at both the community and facility level. The primary aim of the project is to reduce perinatal mortality in these districts by 20% from baseline. Methods: We report overall neonatal and post neonatal mortality rates for the two years preceding the UeN baseline household survey. Rates were calculated using the synthetic cohort probability method and predictors of neonatal and post neonatal mortality examined using Cox regression. To investigate spatial variations in the mortality rates, we calculated Moran's I at the district level using predicted probabilities of mortality. Finally, we create district level maps of predicted under 5 child mortality using a stochastic partial differentiation approach. Findings: A total of 26,258 children contributed to the analysis of mortality with 838 deaths in the neonatal period and 2236 under-5 deaths during the observation period from March 1, 2015 to March 17, 2017. Overall, we estimated the NMR to be 29.2 per 1000 live births (95% CI: 26.9–31.4) and the U5MR to be 86.1 per 1000 live births (95% CI: 85.5–86.8). We found evidence of within-district geospatial clustering of under 5 mortality (P < 0.0001) and that social factors (poverty, illiteracy, multiparity), poor coverage of community health workers and distance from health facilities were strongly associated with child mortality. Interpretation: Important factors associated with neonatal and post-neonatal mortality in our study population included maternal education, parity, household size and gender. Additionally, antenatal care coverage (at least 4 visits) was specifically associated with neonatal mortality only, whereas, LHW coverage and distance to health facility were strongly associated with post-neonatal mortality. These findings emphasise the need for comprehensive, multisectoral strategies to be implemented for future maternal and child health programs and outreach services in rural areas. Funding: The study was funded by an unrestricted grant from the Bill & Melinda Gates Foundation to the Aga Khan University (Grant OPP 1148892).
KW - Geospatial
KW - Neonatal mortality
KW - Post-neonatal mortality
KW - Survival analysis
UR - http://www.scopus.com/inward/record.url?scp=85162231897&partnerID=8YFLogxK
U2 - 10.1016/j.lansea.2023.100231
DO - 10.1016/j.lansea.2023.100231
M3 - Article
AN - SCOPUS:85162231897
SN - 2772-3682
VL - 15
JO - The Lancet Regional Health - Southeast Asia
JF - The Lancet Regional Health - Southeast Asia
M1 - 100231
ER -