Unveiling the Drivers of Anemia: A Multifactorial Analysis

Eky Okviana Armyati (Universitas Muhammadiyah Ponorogo, East Java, Indonesia)
Sugeng Mashudi (Universitas Muhammadiyah Ponorogo, East Java, Indonesia)
Nurul Sri Wahyuni (Universitas Muhammadiyah Ponorogo, East Java, Indonesia)

Journal of Epidemiology and Public Health
Vol. 11 No. 2 (2026)

Background: Anemia remains a major public health concern, particularly in developing countries, due to its multifactorial causes and negative impact on individual productivity and quality of life. Identifying the determinants of anemia is essential for improving prevention strategies and targeted interventions. This study aimed to analyze factors associated with anemia among adult outpatients.
Subjects and Method: The cross-sectional analytic study was conducted at Primary Health Care Ronowijayan, Ponorogo, Indonesia. The study population consisted of adult outpatients aged ≥18 years who visited the health center during the study period. A total of 100 participants were selected using an incidental sampling technique. The dependent variable was anemia, defined as hemoglobin level <12 g/dL in women and <13 g/dL in men, measured using a standardized spectrophotometric method. The independent variables included age, gender, body mass index (BMI), and economic status. BMI was calculated based on measured weight and height, while economic status was classified according to the regional minimum wage. Data were analyzed using Chi-square tests for bivariate analysis and multiple logistic regression for multivariate analysis, with a significance level of α = 0.05.
Results: Most participants were aged <40 years (59.0%), female (54.0%), underweight (59.0%), and of low economic status (82.0%). Bivariate analysis showed that only economic status was significantly associated with anemia (OR = 4.87; p = 0.004). Multivariate analysis confirmed that economic status (OR = 6.77; 95% CI = 1.98–23.10; p= 0.002) and BMI (OR = 1.45; 95% CI = 0.78–2.68; p = 0.035) were significantly associated with anemia, while age (OR = 0.87; 95% CI = 0.27 to 1.24; p = 0.792) and gender (OR = 2.65; 95% CI = 0.07 to 0.33; p = 0.064).
Conclusion: Low economic status was significantly associated with an increased risk of anemia among adult outpatients, while body mass index also showed a significant association. Age and gender were not significantly related to anemia. These findings highlight the importance of addressing socioeconomic disparities and nutritional status in anemia prevention and management at the primary health care level.