Identification Of Infant Mortality Rate Factors  Using Spatial Autoregressive Moving Average

Fajar Dwi Cahyoko; Hesteria Friska Armynia Subratha

doi:10.14710/jphtcr.v7i3.24856

DOI: https://doi.org/10.14710/jphtcr.v7i3.24856

Identification Of Infant Mortality Rate Factors Using Spatial Autoregressive Moving Average

Fajar Dwi Cahyoko¹

, Hesteria Friska Armynia Subratha²

¹Demographic and Civil Registration Study Program, Universitas Sebelas Maret, Surakarta, Jawa Tengah, Indonesia

²Faculty of Medicine, Universitas Pendidikan Ganesha,Kota Singaraja, Bali, Indonesia

Received: 29 Oct 2024; Published: 30 Dec 2024.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

BibTex Citation Data :

@article{JPHTCR24856,
    author = {Fajar Dwi Cahyoko and Hesteria Friska Armynia Subratha},
    title = {Identification Of Infant Mortality Rate Factors  Using Spatial Autoregressive Moving Average},
    journal = {Journal of Public Health for Tropical and Coastal Region},
  volume = {7},
    number = {3},
    year = {2024},
    keywords = {infant mortality rate, ordinary least squares, spatial autoregressive moving average, sanitation, low birth weight.},
    abstract = {  Introduction:  Infant mortality rate (IMR) is one of the indicator of the success for maternal and child health programs. Infant mortality rates affected by biological, environmental, socioeconomic factors and quality of healthcare services. This study aimed to analyze the factors affecting infant mortality rates in the East Java Province using a spatial regression model.   Methods:  The research units were all 38 districts and cities in East Java Province. Secondary data from the 2023’ Health Profile of East Java Province was used in this study, which included the number of infant deaths and the biological, environmental, socioeconomic factors, the availability and quality of health services. In this study, spatial modelling was conducted using an area approach and spatial influence using the Spatial Autoregressive Moving Average (SARMA) method with Queen Contiguity spatial weights.   Results : Based on  R 2   and AIC values, the Spatial Autoregressive model was preferable to Ordinary Least Squares. The obtained model showed that low birth weight and the percentage of the population that can access good sanitation were the significant factors influencing infant mortality in this study. The other factors: percentage of deliveries by health workers, obstetric complications handled, percentage of poor people, infants receiving vitamin A, and infants receiving exclusive breastfeeding had no significant effect on Infant Mortality Rates.   Conclusion : Factors that had significant effect on infant mortality rates in this study were low birth weight and percentage of residents who had access to proper sanitation. },
   issn = {2597-4378},   pages = {235--248}  doi = {10.14710/jphtcr.v7i3.24856},
    url = {https://ejournal2.undip.ac.id/index.php/jphtr/article/view/24856}
}

Citation Format:

Abstract

Introduction: Infant mortality rate (IMR) is one of the indicator of the success for maternal and child health programs. Infant mortality rates affected by biological, environmental, socioeconomic factors and quality of healthcare services. This study aimed to analyze the factors affecting infant mortality rates in the East Java Province using a spatial regression model.

Methods: The research units were all 38 districts and cities in East Java Province. Secondary data from the 2023’ Health Profile of East Java Province was used in this study, which included the number of infant deaths and the biological, environmental, socioeconomic factors, the availability and quality of health services. In this study, spatial modelling was conducted using an area approach and spatial influence using the Spatial Autoregressive Moving Average (SARMA) method with Queen Contiguity spatial weights.

Results: Based on R² and AIC values, the Spatial Autoregressive model was preferable to Ordinary Least Squares. The obtained model showed that low birth weight and the percentage of the population that can access good sanitation were the significant factors influencing infant mortality in this study. The other factors: percentage of deliveries by health workers, obstetric complications handled, percentage of poor people, infants receiving vitamin A, and infants receiving exclusive breastfeeding had no significant effect on Infant Mortality Rates.

Conclusion: Factors that had significant effect on infant mortality rates in this study were low birth weight and percentage of residents who had access to proper sanitation.

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Keywords: infant mortality rate, ordinary least squares, spatial autoregressive moving average, sanitation, low birth weight.

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In Vol 7, No 3 (2024): Journal of Public Health for Tropical and Coastal Region

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