JSTAR
Vol 3 No 01 (2023): Jurnal Statistika Terapan

Karakteristik Wanita Dengan Berat Bayi Lahir Rendah Di Nusa Tenggara Timur

Nofriana Florida Djami Raga (Badan Pusat Statistik Provinsi Nusa Tenggara Timur)



Article Info

Publish Date
28 Jun 2023

Abstract

  In the past half-century, Indonesia has undergone a considerable reduction in infant mortality rates. Upon closer examination of the infants' death distribution, a significant decrease occurs in the postnatal period and only subtly reduces in the neonatal phase. The leading cause of death in neonates is low birthweight (LBW), i.e., the infants' birthweight is below 2,500 grams. NTT is among Indonesia's leading provinces with the highest percentage of LBW. This research investigates the determinants of LBW incidence in NTT by employing the March 2022 Susenas data. A total of 1.793 sample sizes are analyzed through two stages of data analysis: (1) descriptively through simple cross-tabulation, chi-square, and t-test; and (2) multiple binary logistic regression. The result shows that place of residence, island, education, economic status, and mothers' age are statistically significant predictors of LBW in NTT. Overall, women residing in rural areas have higher odds of having LBW infants than those in urban areas. Compared to Sumba and Flores islands, the highest number of LBW cases are found in the Tirosa islands. The higher a woman's education level, the higher the LBW incidence. Meanwhile, the higher the economic status of the mothers, the lower the probability of having light infants at birth. Regarding age, the relationship between women's age and the incidence of LBW illustrates a U-shaped pattern in which the highest probability of LBW is found among women below 20 and above 40 years old.  

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Journal Info

Abbrev

JSTAR

Publisher

Subject

Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

Description

Aim: JSTAR studies applied statistics at the regional and national levels of East Nusa Tenggara which are directed to contribute to the government in making regional development policies. JSTAR pays special attention to official and modeling statistics, big data and data mining, and the application ...