What question did this study set out to answer?

The study aims to determine the prevalence and predictors of anemia in newly diagnosed adult solid cancer patients.

July 3, 2026PLoS ONE0 citationsOpen Access

Magnitude and predictors of anemia among adult solid cancer patients in Hawassa, Ethiopia: A cross-sectional study

EAEden AlemuHawassa University ANAbebe Melis NisiroHawassa University ATAlemwosen T/haimanotHawassa University

Key Points

The study aims to determine the prevalence and predictors of anemia in newly diagnosed adult solid cancer patients.
Cross-sectional study conducted among 405 randomly selected newly diagnosed adult solid cancer patients.
Data collection via structured interviews and medical records from public health facilities.
Binary logistic regression was used to analyze associations between variables and anemia.
Anemia prevalence was 26.4% (95% CI: 22.1–30.7%), with normocytic anemia being the most common type.
Significant predictors of anemia include a history of bleeding (AOR = 3.46, 95% CI: 1.94–6.16) and advanced cancer stage (AOR = 2.01, 95% CI: 1.20–3.34).
Higher educational attainment (diploma and above) was protective against anemia (AOR = 0.35, 95% CI: 0.13–0.93).

Abstract

Introduction Anemia is a common and debilitating complication in cancer patients, affecting prognosis, quality of life, and treatment response. The burden of anemia may be higher in resource-limited settings due to nutritional deficiencies and limited healthcare access. However, data on anemia among newly diagnosed cancer patients in Ethiopia remain scarce. This study was aimed to determine the magnitude and predictors of anemia in newly diagnosed adult solid cancer patients in Hawassa, Ethiopia. Methods A cross-sectional study was conducted among randomly selected 405 newly diagnosed adult solid cancer patients at selected public health facilities in Hawassa City, Ethiopia, from June 2021 to October 2021. Data were collected using structured face-to-face interviews and from medical records. Data were entered into EpiData version 3.1 and exported to SPSS version 26 for analysis. Descriptive statistics were computed for all variables. Binary logistic regression was performed to determine the independent effects of potential explanatory variables on the presence of anemia. Adjusted Odds ratios with 95% confidence intervals were calculated. Statistical significance was set at p-value < 0.05. Result The prevalence of anemia was 26.4% (95% CI: 22.1–30.7%), with normocytic anemia (56.1%) being the most common morphological type. Multivariable analysis identified a history of bleeding (AOR = 3.46, 95% CI: 1.94–6.16), advanced cancer stage (AOR = 2.01, 95% CI: 1.20–3.34), and underweight BMI (AOR = 2.14, 95% CI: 1.28–3.55) were significantly associated with anemia. Conversely, higher educational attainment (diploma and above) was protective (AOR = 0.35, 95% CI: 0.13–0.93). Conclusion Anemia affects over one-quarter of newly diagnosed solid cancer patients in Hawassa, with advanced-stage disease, bleeding history, and decreasing body mass index as significant risk factors. These findings highlight the need for routine anemia screening at diagnosis, nutritional interventions, and early bleeding management in oncology settings.

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