|
|
Background: This study aimed to explore the potential association between the ABO blood group system and the incidence probability as well as severity of Iron Deficiency Anemia (IDA), so as to provide a scientific basis for the personalized prevention, diagnosis, and intervention strategies of IDA.
Methods: Statistical analyses were performed using SPSS software, including descriptive statistics, chi-squared test, Tukey HSD, Dunnett T3 multiple comparisons, and binary logistic regression model. A p-value < 0.05 was considered statistically significant.
Results: Regarding hemoglobin distribution, the hemoglobin levels of 1,009 patients showed an approximately normal distribution, with a mean of 71 g/L and a standard deviation of 18 g/L. The median hemoglobin level of patients with blood type O (about 65 g/L) was significantly lower than that of other blood types, and the data distribution was more concentrated. For the association between blood type and gender, the sample size of females was generally larger than that of males, but the chi-squared test showed no significant association between blood type and gender (p > 0.05). In terms of anemia severity comparison, multiple comparison analysis indicated a significant difference only between blood types A and O (p = 0.013). Binary logistic regression showed that the risks of severe anemia in patients with blood type O (OR = 1.831, p = 0.001) and type A (OR = 1.488, p = 0.024) were 1.831 and 1.488 times that of type AB, respectively, while no significant association was found between blood type B and severe anemia (p > 0.05).
Conclusions: The ABO blood group is associated with the severity of IDA. Individuals with blood types O and A have a significantly higher risk of severe IDA than those with blood type AB. This study provides a theoretical basis for blood group-based personalized screening and intervention of IDA, but further studies are needed to clarify the specific mechanism by which blood type affects iron metabolism and to exclude the influence of confounding factors such as eating habits and genetic background.
DOI: 10.7754/Clin.Lab.2025.251049
|
