Predictors of Pregnancy-Related Anemia: A Logistic Regression Study at a Maternity Facility in Ghana
Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Background
Anemia during pregnancy remains a major public health concern, particularly in low- and middle-income countries, where it contributes substantially to maternal and neonatal morbidity and mortality. Identifying women at increased risk is essential for timely intervention and improved pregnancy outcomes.
Objective
This study aimed to identify significant predictors of anemia among pregnant women using logistic regression and to evaluate the association between selected clinical characteristics and anemia status.
Methods
A retrospective study was conducted using secondary data obtained from Ayiwa Memorial Maternity Home in the Suame Municipality of the Kumasi Metropolis, Ashanti Region, Ghana, covering the period 2018 to 2023. A sample of 396 pregnant women with complete information on hemoglobin status and candidate predictor variables was analyzed. The outcome variable was whether a woman had ever had anemia (hemoglobin concentration below 11 g/dL). Candidate predictors included maternal age, diastolic and systolic blood pressure, parity, height, weight, gestational age, sickle cell status, employment, and education. Multivariable logistic regression was fitted, with multicollinearity among predictors assessed using variance inflation factors (VIF) and tolerance statistics. Model performance was evaluated using the Hosmer-Lemeshow test, Nagelkerke R 2 , and the area under the receiver operating characteristic curve (AUC).
Results
Of the 396 pregnant women studied, 69.44% were classified as anemic. In the multivariable logistic regression model, gestational age, maternal weight, and diastolic blood pressure were significantly associated with anemia status ( p < 0.05). Higher gestational age was associated with increased odds of anemia (AOR = 1.124, 95% CI: 1.073–1.180), while higher weight (AOR = 0.975, 95% CI: 0.955–0.995) and higher diastolic blood pressure (AOR = 0.964, 95% CI: 0.934–0.993) were associated with reduced odds of anemia. Systolic blood pressure, height, and education were not significantly associated with anemia in the final model. The model showed acceptable discriminatory ability (AUC = 0.752, 95% CI: 0.694–0.810) and adequate calibration (Hosmer-Lemeshow χ 2 = 13.323, p = 0.101), explaining approximately 23.9% of the variation in anemia status (Nagelkerke R 2 = 0.239), with high specificity (91.8%) but limited sensitivity (36.5%).
Conclusion
Gestational age, maternal weight, and diastolic blood pressure were identified as significant predictors of anemia during pregnancy in this population. These findings support intensifying anemia screening as pregnancy advances and incorporating nutritional assessment into routine antenatal care. However, given the model’s limited sensitivity, clinical risk models cannot replace routine laboratory hemoglobin testing. Further prospective, multi-center studies incorporating dietary, infectious, and socioeconomic determinants are recommended to validate these findings.
