Profile and factors associated with low birth weight in Indonesia: a national data survey
Introduction: The third objective of the UN Sustainable Development Goals (SDGs), 'ensure healthy lives and promote well-being for all at all ages', is manifest in Indonesia's commitment to health. One of the SDG3 targets is to reduce under-five mortality and infant mort...
Saved in:
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
James Cook University
2025-02-01
|
Series: | Rural and Remote Health |
Subjects: | |
Online Access: | https://www.rrh.org.au/journal/article/9170/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
_version_ | 1832569121203552256 |
---|---|
author | Mario Ekoriano Anugerah Widiyanto Muthmainnah Muthmainnah Yuli Devi Bambang Cahyono Izatun Nafsi Teguh Widodo |
author_facet | Mario Ekoriano Anugerah Widiyanto Muthmainnah Muthmainnah Yuli Devi Bambang Cahyono Izatun Nafsi Teguh Widodo |
author_sort | Mario Ekoriano |
collection | DOAJ |
description |
Introduction: The third objective of the UN Sustainable Development Goals (SDGs), 'ensure healthy lives and promote well-being for all at all ages', is manifest in Indonesia's commitment to health. One of the SDG3 targets is to reduce under-five mortality and infant mortality. In rural areas of Indonesia, there is a lack of access to medical facilities (healthcare services, anthropometry tools) and health workers, so low birth weight (LBW, <2500 g) in rural areas remains high. This study aimed to determine the profile of and test the factors that cause LBW in Indonesia.
Methods: This study used secondary data from the National Socio-Economic Survey/Survei Sosial Ekonomi Nasional (SUSENAS) 2021 with a national sample of 4 711 455 women (weighted), which is analyzed descriptively and inferentially. The analysis was conducted descriptively to determine the profile and distribution of LBW at the national and provincial levels, while inferential analysis was performed using logistic regression to determine the variables that most influence LBW.
Results: The prevalence of LBW in Indonesia was found to be 11.7%. North Maluku was the province with the highest LBW rate (20.1%), and West Java had the highest number of LBW infants in Indonesia, with 104 585 infants. This study found that smoking, rural areas, poor nutrition, age of childbirth, age and birth spacing significantly affected the incidence of LBW in Indonesia. In rural Indonesia, women tend to give birth to LBW babies (adjusted odds ratio: 1.249; 95%CI: 1.241-1.256). The incidence of LBW babies in rural areas was higher than in urban areas (12.9% v 10.8%) in Indonesia.
Conclusion: This study concluded that smoking behavior is the main variable that influences the incidence of LBW in Indonesia. Therefore, there should be assistance to families by prioritizing significant factors for LBW (living in a village/rural area, low education, smoking behavior, not or rarely consuming nutritious food, maternal age at first birth 35 years and birth spacing <33 months). Especially for rural areas, governments need to improve access to healthcare facilities including availability of anthropometry tools, health workers, and healthcare services.
|
format | Article |
id | doaj-art-6280a75f55a84a4681e4a252ff20d22c |
institution | Kabale University |
issn | 1445-6354 |
language | English |
publishDate | 2025-02-01 |
publisher | James Cook University |
record_format | Article |
series | Rural and Remote Health |
spelling | doaj-art-6280a75f55a84a4681e4a252ff20d22c2025-02-02T23:11:38ZengJames Cook UniversityRural and Remote Health1445-63542025-02-012510.22605/RRH9170Profile and factors associated with low birth weight in Indonesia: a national data surveyMario Ekoriano0Anugerah Widiyanto1Muthmainnah Muthmainnah2Yuli Devi3Bambang Cahyono4Izatun Nafsi5Teguh Widodo6National Research and Innovation AgencyNational Research and Innovation AgencyUniversitas AirlanggaUniversitas AirlanggaNational Research and Innovation AgencyNational Population and Family Planning BoardNational Research and Innovation Agency [BRIN] Introduction: The third objective of the UN Sustainable Development Goals (SDGs), 'ensure healthy lives and promote well-being for all at all ages', is manifest in Indonesia's commitment to health. One of the SDG3 targets is to reduce under-five mortality and infant mortality. In rural areas of Indonesia, there is a lack of access to medical facilities (healthcare services, anthropometry tools) and health workers, so low birth weight (LBW, <2500 g) in rural areas remains high. This study aimed to determine the profile of and test the factors that cause LBW in Indonesia. Methods: This study used secondary data from the National Socio-Economic Survey/Survei Sosial Ekonomi Nasional (SUSENAS) 2021 with a national sample of 4 711 455 women (weighted), which is analyzed descriptively and inferentially. The analysis was conducted descriptively to determine the profile and distribution of LBW at the national and provincial levels, while inferential analysis was performed using logistic regression to determine the variables that most influence LBW. Results: The prevalence of LBW in Indonesia was found to be 11.7%. North Maluku was the province with the highest LBW rate (20.1%), and West Java had the highest number of LBW infants in Indonesia, with 104 585 infants. This study found that smoking, rural areas, poor nutrition, age of childbirth, age and birth spacing significantly affected the incidence of LBW in Indonesia. In rural Indonesia, women tend to give birth to LBW babies (adjusted odds ratio: 1.249; 95%CI: 1.241-1.256). The incidence of LBW babies in rural areas was higher than in urban areas (12.9% v 10.8%) in Indonesia. Conclusion: This study concluded that smoking behavior is the main variable that influences the incidence of LBW in Indonesia. Therefore, there should be assistance to families by prioritizing significant factors for LBW (living in a village/rural area, low education, smoking behavior, not or rarely consuming nutritious food, maternal age at first birth 35 years and birth spacing <33 months). Especially for rural areas, governments need to improve access to healthcare facilities including availability of anthropometry tools, health workers, and healthcare services. https://www.rrh.org.au/journal/article/9170/child healthIndonesiainfantslow birth weightnutritionsmoking |
spellingShingle | Mario Ekoriano Anugerah Widiyanto Muthmainnah Muthmainnah Yuli Devi Bambang Cahyono Izatun Nafsi Teguh Widodo Profile and factors associated with low birth weight in Indonesia: a national data survey Rural and Remote Health child health Indonesia infants low birth weight nutrition smoking |
title | Profile and factors associated with low birth weight in Indonesia: a national data survey |
title_full | Profile and factors associated with low birth weight in Indonesia: a national data survey |
title_fullStr | Profile and factors associated with low birth weight in Indonesia: a national data survey |
title_full_unstemmed | Profile and factors associated with low birth weight in Indonesia: a national data survey |
title_short | Profile and factors associated with low birth weight in Indonesia: a national data survey |
title_sort | profile and factors associated with low birth weight in indonesia a national data survey |
topic | child health Indonesia infants low birth weight nutrition smoking |
url | https://www.rrh.org.au/journal/article/9170/ |
work_keys_str_mv | AT marioekoriano profileandfactorsassociatedwithlowbirthweightinindonesiaanationaldatasurvey AT anugerahwidiyanto profileandfactorsassociatedwithlowbirthweightinindonesiaanationaldatasurvey AT muthmainnahmuthmainnah profileandfactorsassociatedwithlowbirthweightinindonesiaanationaldatasurvey AT yulidevi profileandfactorsassociatedwithlowbirthweightinindonesiaanationaldatasurvey AT bambangcahyono profileandfactorsassociatedwithlowbirthweightinindonesiaanationaldatasurvey AT izatunnafsi profileandfactorsassociatedwithlowbirthweightinindonesiaanationaldatasurvey AT teguhwidodo profileandfactorsassociatedwithlowbirthweightinindonesiaanationaldatasurvey |