Spatial Modeling of Infant Mortality Rate In Sampang Regency : An Ecological Study

Firman Firdauz Saputra; Lily Eky Nursia N; Eva Flourentina Kusumawardani; Nasrianti Syam; Meutia Paradhiba; Mardi Fadillah; Geofrey Ssekalembe

doi:10.30871/jagi.v8i2.7158

Firman Firdauz Saputra Faculty of Public Health, Teuku Umar University, Ujong Tanoh Darot Meulaboh, Aceh Barat, Indonesia https://orcid.org/0000-0001-9780-3034
Lily Eky Nursia N Faculty of Public Health, Teuku Umar University, Ujong Tanoh Darot Meulaboh, Aceh Barat, Indonesia
Eva Flourentina Kusumawardani Faculty of Public Health, Teuku Umar University, Ujong Tanoh Darot Meulaboh, Aceh Barat, Indonesia http://orcid.org/0000-0001-7111-1742
Nasrianti Syam Faculty of Public Health, Teuku Umar University, Ujong Tanoh Darot Meulaboh, Aceh Barat, Indonesia https://orcid.org/0000-0001-8187-2983
Meutia Paradhiba Faculty of Public Health, Teuku Umar University, Ujong Tanoh Darot Meulaboh, Aceh Barat, Indonesia https://orcid.org/0009-0009-7684-7615
Mardi Fadillah Faculty of Public Health, Teuku Umar University, Ujong Tanoh Darot Meulaboh, Aceh Barat, Indonesia https://orcid.org/0000-0002-0494-1110
Geofrey Ssekalembe Amref Health Africa, Uganda

DOI: https://doi.org/10.30871/jagi.v8i2.7158

Abstract

Infant mortality rate (IMR) is one of the indicators to measure public health status and community welfare. In the last 3 years (2014-2016), the infant mortality rate in Sampang Regency has increased. The purpose of this study is to develop spatial-based modeling of factors affecting infant mortality rates in Sampang. Researchers used an ecological study design where secondary data came from the Health Office and the Central Bureau of Statistics in Sampang Regency. The dependent variable is infant mortality rate, while the independent variables are delivery assisted by health workers, exclusive breastfeeding coverage, neonatal complications handled, K4 visit coverage, LBW percentage, midwife to population ratio, percentage of clean and healthy household behavior. Data has been analyzed and processed using Geoda and Quantum GIS applications. Based on statistical tests, the spatial model is obtained: ŷ_i= -21.82+0.706 ∑_(i=1,i≠j)^n w_ijy_i-0.61* childbirth attended by health worker+0.10* neonatal complications attended by health worker+1.89* LBW babies. Each variable of childbirth assisted by health workers increased by 10, it can decrease the infant mortality rate by 6.1 cases. Each variable of neonatal complications not handled by health workers rises 10 units, it can increase the infant mortality rate by 1 case. each variable of LBW babies rises 1 unit and it can increase infant mortality cases by 1.89 cases. The results of this study can be used to reduce infant mortality rates that occur by intervening in existing factors.

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