Preeclampsia in Pregnancy: Analysis of Sociodemographic and Risk Profiles Based on Multiyear Observations

Preeclampsia is a pregnancy-related hypertensive disorder that occurs in 2-8% of pregnancy complications and causes 9-26% of maternal deaths in low-income countries. This study aims to determine the characteristics of Pregnancy with Preeclampsia at the dr. Rubini Regional General Hospital, Mempawah Regency in 2021-2023. This study is a descriptive study with a cross-sectional approach. Data retrieval was taken from medical records in the form of data on the characteristics of pregnancy with preeclampsia at the dr. Rubini Regional General Hospital, Mempawah Regency based on maternal age, education, occupation, gravida, gestational age, body mass index status, previous medical history, history of miscarriage, hemoglobin status, and leukocyte status since 2021-2023. The data collects on March to April 2024. The samples are 302 samples. The researchers conducted univariate analysis using SPSS 25 computer software. The data obtained from the data collection will be presented in the form of frequency distribution tables and accompanied by data interpretation with explanations in narrative form. The results showed that pregnant women with preeclampsia were more at high-risk age (48%), low education with elementary school graduates (42.7%), work as housewives (94%), had obesity nutritional status (86.1%), no history of disease (61.3%), no history of miscarriage (81.5%), multiparous pregnancy (75.8%), had a gestational age of aterem 67.2%, had normal hemoglobin 57.6% and pregnant women with preeclampsia experienced leukocytosis (59.3%).

Authors

Institutions

Publication Details

Journal
Jurnal Publikasi Kesehatan Masyarakat Indonesia
Published
2025-08-01
DOI
https://doi.org/10.20527/jpkmi.v12i2.21799
Primary Topic
Public Health and Nutrition
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Preeclampsia in Pregnancy: Analysis of Sociodemographic and Risk Profiles Based on Multiyear Observations

Hermin Sabaruddin, Vivin Yulindar
Jurnal Publikasi Kesehatan Masyarakat Indonesia
Public Health and Nutrition
article

Preeclampsia in Pregnancy: Analysis of Sociodemographic and Risk Profiles Based on Multiyear Observations

Hermin Sabaruddin, Vivin Yulindar
article en

Abstract

Preeclampsia is a pregnancy-related hypertensive disorder that occurs in 2-8% of pregnancy complications and causes 9-26% of maternal deaths in low-income countries. This study aims to determine the characteristics of Pregnancy with Preeclampsia at the dr. Rubini Regional General Hospital, Mempawah Regency in 2021-2023. This study is a descriptive study with a cross-sectional approach. Data retrieval was taken from medical records in the form of data on the characteristics of pregnancy with preeclampsia at the dr. Rubini Regional General Hospital, Mempawah Regency based on maternal age, education, occupation, gravida, gestational age, body mass index status, previous medical history, history of miscarriage, hemoglobin status, and leukocyte status since 2021-2023. The data collects on March to April 2024. The samples are 302 samples. The researchers conducted univariate analysis using SPSS 25 computer software. The data obtained from the data collection will be presented in the form of frequency distribution tables and accompanied by data interpretation with explanations in narrative form. The results showed that pregnant women with preeclampsia were more at high-risk age (48%), low education with elementary school graduates (42.7%), work as housewives (94%), had obesity nutritional status (86.1%), no history of disease (61.3%), no history of miscarriage (81.5%), multiparous pregnancy (75.8%), had a gestational age of aterem 67.2%, had normal hemoglobin 57.6% and pregnant women with preeclampsia experienced leukocytosis (59.3%).

Jurnal Publikasi Kesehatan Masyarakat IndonesiaVol. 12(2)
Tanjungpura University (ID), Lambung Mangkurat University (ID)
Zero hunger
Openalex Percentile: Top 70%
Public Health and Nutrition
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.