Detection Mapping of Women with High-Risk Pregnancy in Antenatal Care in Kamonji Public Health Center, Palu City, Indonesia

Abstract

Rosmala Nur, Renata Gita Cahyani Sese, Nurhaya S. Patui, Rasyka Nurul Fajriah.

High-risk pregnancy induces complications, which threaten both mother and fetus during childbirth. Therefore, it is important to detect such cases during antenatal using Geographic Information Systems (GIS). This study aims to map the detection of women with high-risk pregnancy based on age, parity, obstetric history, and the relationship between these three factors. This is analytic, quantitative research with a cross-sectional approach used to carry out its design. The Lemeshow Formula was used to obtain data from 283 respondents and analyzed using the spatial techniques and the Chi-Square test with p> 0.05. The results of spatial analysis using a map scale of 1: 65,000 cm showed that: (1) the highest distribution of women with high-risk pregnancy was discovered in Lere Village, (2) the lowest were found in Ujuna Village, (3) based on age, the highest was detected in Lere Village, (4) in accordance with parity, the highest were found in Ujuna Village, and (5) regarding obstetric history, the majority were discovered in Baru Village. The age (p = 0.010) and obstetric history (p = 0,000) correlated with high-risk pregnancy cases. Meanwhile, parity (p = 0.232) had no significant relationship with this health issue. It can be concluded that Lere Village has the largest number of women with high-risk pregnancy cases, while Ujuna village has the least. Age and obstetric history effect the rate of this high-risk pregnancy.