Predictors of Unintended Pregnancies among Female Students in Kenya: A Case Study of the Siaya National Polytechnic

Authors

Gabriel O. Ng’ong’a

Bondo Technical Training Institute (BTTI) P.O Box 377-40601 Bondo (Kenya)

Violet Atieno

Bondo Technical Training Institute (BTTI) P.O Box 377-40601 Bondo (Kenya)

Mary Mercy Ochieng’

Bondo Technical Training Institute (BTTI) P.O Box 377-40601 Bondo (Kenya)

Maricus Ahomo

Bondo Technical Training Institute (BTTI) P.O Box 377-40601 Bondo (Kenya)

Bernard Manyala

The Siaya National Polytechnic P.O. Box I087-40600 Siaya (Kenya)

Steven Onyango

The Siaya National Polytechnic P.O. Box I087-40600 Siaya (Kenya)

Daniel Randa

The Siaya National Polytechnic P.O. Box I087-40600 Siaya (Kenya)

Article Information

DOI: 10.47772/IJRISS.2026.1026EDU0076

Subject Category: Education

Volume/Issue: 10/26 | Page No: 878-886

Publication Timeline

Submitted: 2026-01-12

Accepted: 2026-01-18

Published: 2026-02-13

Abstract

Despite the global decline in unintended pregnancies, the rate remains high in Kenya, particularly in Siaya County, where The Siaya National Polytechnic (TSNP) is located. The Kenya National Bureau of Statistics reported in the 2023 Demographic and Health Survey that teenage pregnancy in this county stood at 21%. These unplanned pregnancies often result in illegal abortion, health issues, trauma, stigmatization, economic burden due to prolonged study periods and poor academic performance. However, predictors of unintended pregnancies among technical college female students, particularly at TSNP, have not been clearly understood. This study sought to determine potential predictors of unintended pregnancies among female students at TSNP to support prevention, management and inform policy formulation. A cross-sectional survey design was employed. Data was collected using structured questionnaires administered to a sample of 306 female students of TSNP drawn from a population of 1475 female students who consented. Data analysis was conducted using IBM SPSS software version 25.0. Descriptive statistics were used to analyze predictors, while
Chi-square (χ²) tests examined the relationships between predictors and unintended pregnancies. Bivariate logistic regression model tested associations between variables. Odds ratios (ORs) with 95% confidence intervals and a marginal error of 0.05 were used to determine statistical significance. The findings revealed that 73.2% of female students had not conceived, while 26.8% had conceived. Among those who had conceived, 57.3% indicated that their pregnancies were unintended. Unintended pregnancies were significantly associated with the following factors: not using condoms (RO=6.577; 95% CI; 3.623-11.94; P=0.000), age at first sexual intercourse (OR=2.29; 95% CI=1.260-4.140; P=0.010), difficulty in getting meals when in college (OR = 2.333; 95% Cl = 1.094-4.975; P=0.028)) and sleeping arrangements at home (OR = 2.333; 95% Cl = 1.094-4.975; P=0.028). In conclusion, social, demographic, cultural and socioeconomic factors were found to influence unintended pregnancies among female students. Health education should focus on sensitizing TSNP students on condom use, while policies should support access to meals and parental involvement in housing during schooling.

Keywords

unintended pregnancies, TSNP

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References

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