Abstract
Background:
If hemoglobin (Hb) synthesis is impaired by factors other than a deficiency in free erythrocyte protoporphyrin (FEP) synthesis, the amount of FEP might be increased. In this study, we analyzed the statistical values and contribution of FEP for the monitoring and diagnosis of iron deficient anemia in adolescent female athletes according to various sports.
Methods:
We collected whole blood from 64 adolescent female athletes 13 to 19 years of age. The FEP was measured fluorometrically. After other hematological indices were evaluated, statistical analysis was performed to compare the data among various athletes.
Results:
The mean age was 14.8±1.7 (13∼19) years old. The number of runners, badminton players and shooting athletes were 46.9% (n=30), 12.5% (n=8) and 40.6% (n=26), respectively. The prevalence of anemia, iron deficiency and iron deficiency anemia were 23.4%, 23.4% and 14.0%, respectively. The measured concentration of FEP was 48.7±21.1μg/dL (12∼125). A moderately negative correlation of Hb and FEP was noted and was found to be statistically significant (r=?0.571, P<0.001). Among serum ferritin, TS and FEP, there was no statistically significant correlation. For the diagnosis of iron deficiency anemia, FEP was the most statistically significant index (P<0.001). For iron deficiency, sensitivity, specificity, positive predictive value, and negative predictive value were 88.9%, 30.4%, 33.3%, and 87.5%, respectively. The receiver operating characteristic curves, showed that FEP had excellent diagnostic power to detect iron deficiency. There was a significant difference in the prevalence of iron deficiency among the three athletes, with runners and badminton players tending to be affected more frequently with iron deficiency than static athletes such as the shooters (runners and badminton vs. shooting athletes, 33.3% and 25.0% vs. 19.2%).
Conclusion:
Our results confirmed FEP to be the most significant factor for the diagnosis of iron deficiency in athletes. Proper nutritional counseling and monitoring need to be tailored to various sports, especially in terms of static versus nonstatic sports such as runners and badminton players versus shooting athletes.
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Table 1.
Runners (n=30) | Badminton players (n=8) | Shooting players (n=26) | P-value | |
---|---|---|---|---|
Age (years) | 14.9±1.7 | 16.3±2.5 | 14.4±1.0 | 0.064 |
Hb∗ (g/dL) | 12.3±1.2 | 13.1±1.6 | 13.4±0.8 | 0.002 |
Ferritin (ng/dL) | 18.3±10.5 | 18.6±8.8 | 21.1±1.8 | 0.061 |
TS† (%) | 26.1±14.3 | 26.3±15.3 | 25.5±13.1 | 0.097 |
FEP‡(μg/dL) | 54.8±25.3 | 50.8±19.4 | 41.1±12.7 | 0.048 |
Table 2.
Criteria | Prevalence % (n) | |
---|---|---|
Anemia | Hb∗<12g/dL | 23.4 (15) |
Iron deficiency | Ferritin<12ng/dL | 23.4 (15) |
IDA† | 14.0 (9) | |
NHANES III‡ | 26.6 (17) | |
FEP§ (μg/dL) | FEP≥36μg/dL | 73.4 (47) |
Table 3.
Model | Unstandardized coefficients | Standardized coefficients | t | Sig. | Collinearity statistics | ||
---|---|---|---|---|---|---|---|
B | Sth. error | Beta | Tol.∗ | VIF† | |||
Constant | 14.325 | 0.545 | 26.297 | 0.000 | |||
FEP | ?0.033 | 0.007 | ?0.558 | ?4.989 | 0.000 | 0.894 | 1.118 |
Ferritin | 0.001 | 0.013 | 0.010 | 0.088 | 0.930 | 0.902 | 1.108 |
TS | 0.004 | 0.010 | 0.046 | 0.421 | 0.675 | 0.938 | 1.067 |
R2=0.328 | Adjusted R2=0.294 | F=9.763 | P≒0.000 |
Table 4.
FEP | Runners (n=30) | Badminton players (n=8) | Shooting players (n=26) | |||
---|---|---|---|---|---|---|
ID∗ | IDA† | ID | IDA | ID | IDA | |
n (%) | n (%) | n (%) | n (%) | n (%) | n (%) | |
≥36mg/dL | 9 (30.0) | 6 (20.0) | 2 (25.0) | 2 (25.0) | 4 (15.4) | 1 (3.8) |
<36mg/dL | 1 (3.3) | 0 (0) | 0 (0) | 0 (0) | 1 (3.8) | 0 (0) |
Total | 10 (33.3) | 6 (20.0) | 2 (25.0) | 2 (25.0) | 5 (19.2) | 1 (3.8) |