Determinan Kematian Bayi di Provinsi Sulawesi Tengah Berdasarkan Data Supas 2015

Mieke Nurmalasari

Abstract


Abstract

One of the goals in Sustainable Development Goals (SDGs) is reducing infant mortality. The trend of infant mortality in Indonesia has decline, but the efforts to decrease the rate is still needed especially in the provinces with high mortality rate such as Sulawesi Tengah. These province infant mortality rates are 85 death per thousand live births, respectively, much higher than national number of 43 deaths per thousand live births. This study is aimed to identify determinants of infant mortality in Sulawesi Tengah, between 2010-2015 using Intercensal Population Survey 2015. Determinants of under five mortality number is investigated using logistic regression. The result shows that gender of the infant, birth type, place of living, age of first delivery and mother’s education impacted mostly to the high mortality rate.

Keyword: logistic regression, infant mortality, mortality rate

Abstrak

Salah satu tujuan dalam Sustainable Development Goals (SGDs) adalah menurunkan angka kematian bayi. Tren angka kematian bayi di Indonesia menurun akan tetapi usaha untuk menurunkan angka kematian masih diperlukan terutama pada provinsi yang tingkat kematian bayinya masih tinggi seperti di provinsi Sulawesi tengah. Tingkat kematian bayi di provinsi ini sebesar 85 per 1000 kelahiran hidup, hal ini masih relatif tinggi dari pada jumlah nasional 43 kematian per 1000 kelahiran hidup. Penelitian ini bertujuan untuk mengidentifikasi tingkat kematian bayi di Sulawesi Tengah antara tahun 2010 sampai tahun 2015 dengan menggunakan Intersenal Survei Populasi 2015 atau SUPAS 2015. Determinan Kematian balita ditentukan dengan menggunakan metode regresi logistik. Hasil menunjukkan bahwa jenis kelamin, tipe kelahiran, tempat tinggal, usia persalinan pertama dan pendidikan ibu memberikan pengaruh terbesar terhadap tingkat kematian balita.

Kata Kunci: regresi logistik, kematian bayi, tingkat kematian bayi 


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References


UNICEF. Under five mortality report 2016 [Internet]. 2016. Available from: https://data.unicef.org/topic/child-survival/under-five-mortality/

Kemenkes RI. Profil Kesehatan Indonesia 2016. 2016.

UN. Economic and Social Council. Vol. 14239. 2016.

Kemenkes RI. Data dan Informasi Kesehatan Provinsi Sulawesi Tengah. 2013.

Dinas Kesehatan. Profil Kesehatan Kot Palu Tahun 2014 [Internet]. 2014. Available from: http://www.depkes.go.id/resources/download/pusdatin/kunjungan-kerja/sulawesi-tengah.pdf

Agresti A. Categorical Data Analysis. Wiley series in probability and statistics. 2002.

Pongou R. Why Is Infant Mortality Higher in Boys Than in Girls? A New Hypothesis Based on Preconception Environment and Evidence From a Large Sample of Twins. Demography. 2013;

Ruggieri A, Anticoli S, D’ambrosio A, Giordani L, Viora M. Monographic section The influence of sex and gender on immunity, infection and vaccination. Ann Ist Super Sanità. 2016;52(2):198–204.

Gebretsadik S, Gabreyohannes E. Determinants of Under-Five Mortality in High Mortality Regions of Ethiopia: An Analysis of the 2011 Ethiopia Demographic and Health Survey Data. 2016; Available from: http://dx.doi.org/10.1155/2016/1602761

Monden CWS, Smits J. Mortality among twins and singletons in sub-Saharan Africa between 1995 and 2014: a pooled analysis of data from 90 Demographic and Health Surveys in 30 countries. Lancet Glob Heal. 2017;

Ifada L. Determinan Ketahanan Hidup Balita di Indonesia Tahun 2015. Sekolah Tinggi Ilmu Statistik; 2017.

Ettarh RR, Kimani J. Determinants of under-five mortality in rural and urban Kenya. Rural Remote Health. 2012;

Bappenas. Laporan Perkembangan Pencapaian Tujuan Pembangunan Milenium Indonesia [Internet]. Jakarta; 2015. Available from: https://www.bappenas.go.id/files/8613/5229/8462/1-laporan-pencapaian-tujuan-pembangunan-milenium-indonesia-2010201011181321170__20101223204310__2813__0.pdf

Kayode GA, Adekanmbi VT, Uthman OA. Risk factors and a predictive model for under-five mortality in Nigeria: Evidence from Nigeria demographic and health survey. BMC Pregnancy Childbirth. 2012;




DOI: https://doi.org/10.47007/inohim.v6i1.146

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