Pre-Pregnancy Body Mass Index and Gestational Weight Gain as Risk Factors for Low Birth Weight

Fitriana Ciptaningtyas; Irwanto; Widati Fatmaningrum

doi:10.33086/jhs.v15i02.2549

Authors

Fitriana Ciptaningtyas Program Studi Pendidikan Bidan Fakultas Kedokteran Universitas Airlangga
Irwanto Departemen Ilmu Kesehatan Anak Fakultas Kedokteran Universitas Airlangga
Widati Fatmaningrum Departeman Ilmu Kesehatan Masyarakat-Kedokteran Pencegahan Universitas Airlangga

DOI:

https://doi.org/10.33086/jhs.v15i02.2549

Abstract

Low weight (LBW) is one of the perinatal complications with high infant mortality and morbidity. At Wonosamodro District in 2018, 4.8% of babies were born with LBW. One of the risk factors for LBW is maternal nutritional factors. This study aims to analyze the correlation between pre-pregnancy body mass index (BMI) and gestational weight gain with the incidence of low birth weight. This study was an analytic observational study using a case-control design. The population was all infants and toddlers with a history of LBW in the case group and normal birth weight (NBW) in the control group in Wonosamodro Sub-District, Boyolali District, born from September 2015 to September 2020. There were 102 samples with consecutive and matching sampling. The characteristics of respondents, BMI, and gestational weight gain processing were done by editing, coding, entry, cleaning, and tabulating. Then, the data analysis used the chi-square test. The study's results at 5% alpha showed that gestational weight gain significantly correlated with LBW incidence (p=0.000). Meanwhile, pre-pregnancy BMI did not significantly correlate with LBW (p=0.096). Mothers with less gestational weight were 5.3 times at risk of delivering LBW babies than mothers with normal gestational weight gain (OR =5.318 95% CI 2.122-13.326). Maternal weight gain during pregnancy is a risk factor for LBW in Wonosamodro Subdistrict, Boyolali District, while pre-pregnancy BMI is not. Further research should use the primary data collection method, a cohort design, a more significant number of samples, and random sampling and examine other variables.

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