Iron Therapy Reduces Oxidative Stress in Pregnant Women with Anemia: A Prospective Study

Iron Therapy Reduces Oxidative Stress in Pregnant Women with Anemia: A Prospective Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Iron Therapy Reduces Oxidative Stress in Pregnant Women with Anemia: A Prospective Study Sevilay Yavuz Dogu, Hamdiye Acar, Hatice Argun Atalmis, Emine Yilmaz Guler, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7095398/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Apr, 2026 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted 10 You are reading this latest preprint version Abstract Background Iron deficiency anemia (IDA) affects approximately 40% of pregnant women worldwide, regarding increased oxidative stress (OS) and adverse pregnancy outcomes. Recent advances identified hepcidin as the master regulator of iron homeostasis and erythroferrone (ERFE) as a key erythroid regulator, yet their responses to iron supplementation and relationships with OS markers during pregnancy remain poorly understood. Objective To investigate whether oral iron supplementation reduces OS-related molecular damage in pregnant women with IDA and characterize relationships between iron regulatory molecules (hepcidin, ERFE) and OS biomarkers. Methods This prospective observational study enrolled 40 pregnant women with IDA (mean age 29.23 ± 6.33 years) across all trimesters. Participants received 200 mg elemental iron daily for one month. Pre- and post-treatment measurements included hematologic parameters, iron metabolism markers (ferritin, hepcidin, ERFE), and OS biomarkers (total antioxidant status [TAS], total oxidant status [TOS]). Results Iron supplementation produced very large improvements in TAS (0.96 ± 0.36 to 1.64 ± 0.37 mmol/L; Cohen's d = 1.87, p < 0.001), exceeding hematological improvements in hemoglobin (10.10 ± 0.72 to 11.61 ± 0.97 g/dL; d = 1.76, p < 0.001) and hematocrit (30.93 ± 1.79% to 35.24 ± 3.01%; d = 1.74, p < 0.001). The TOS/TAS ratio decreased substantially (14.53 ± 15.98 to 4.10 ± 3.14; d=-0.91, p < 0.001). Hepcidin increased appropriately (2214.62 ± 1444.27 to 3492.65 ± 1640.51 pg/mL; d = 0.83, p < 0.001) while ERFE decreased (470.75 ± 170.75 to 345.25 ± 112.96 pg/mL; d=-0.87, p < 0.001), confirming successful iron repletion. TAS improvements showed minimal correlation with iron parameters (all |r|<0.25), suggesting independent mechanisms. Conclusions Iron supplementation effectively reduces OS in pregnant women with IDA through mechanisms independent of iron parameter changes. The coordinated hormonal responses confirm appropriate iron repletion while suggesting additional therapeutic benefits beyond anemia correction. Iron deficiency anemia pregnancy oxidative stress total antioxidant status hepcidin erythroferrone Figures Figure 1 Figure 2 1. Background Iron deficiency anemia represents the most prevalent nutritional disorder during pregnancy worldwide, affecting approximately 40% of pregnant women and constituting a major public health challenge with significant implications for maternal and fetal health outcomes [ 1 , 2 ]. The physiological demands of pregnancy create unique vulnerabilities for iron deficiency development, as maternal blood volume expansion increases by 40–50% during gestation while simultaneously supporting fetal growth and placental development [ 3 ]. Recent systematic reviews have identified substantial heterogeneity in international clinical practice guidelines for iron deficiency anemia management, with only 37.5% of existing guidelines meeting high-quality standards according to AGREE II framework assessment [ 4 , 5 ]. Contemporary epidemiological evidence demonstrates that iron deficiency anemia during pregnancy is associated with increased maternal mortality, preterm delivery, low birth weight infants, and compromised neurocognitive development in offspring that can persist into adulthood [ 6 ]. Furthermore, emerging research has revealed that even iron deficiency without overt anemia can adversely impact placental iron transport mechanisms and fetal iron status, highlighting the importance of early detection and intervention [ 7 ]. The pathophysiological implications of iron deficiency extend far beyond traditional hematologic manifestations, encompassing complex molecular alterations that fundamentally disrupt cellular processes throughout pregnancy. Iron serves as an essential cofactor for numerous enzymatic reactions involved in oxygen transport, cellular respiration, and DNA synthesis, making its deficiency a systemic disorder with widespread consequences. Recent investigations have illuminated the critical relationship between iron deficiency and oxidative stress, revealing that iron-depleted states create conditions conducive to increased reactive oxygen species production while simultaneously impairing antioxidant defense mechanisms [ 8 , 9 ]. This pathological oxidative imbalance manifests as cellular membrane damage, protein oxidation, and DNA fragmentation that can trigger inflammatory cascades characteristic of pregnancy complications. Contemporary studies have demonstrated that iron deficiency anemia during pregnancy significantly alters antioxidant enzyme activities, particularly superoxide dismutase and glutathione peroxidase, creating conditions that promote oxidative stress-related molecular damage [ 10 ]. Furthermore, recent research has established that iron deficiency anemia is associated with elevated levels of 8-hydroxy-2-deoxyguanosine, a validated biomarker of oxidative DNA damage, suggesting that cellular injury extends to genetic material [ 11 ]. Oral iron supplementation represents the primary therapeutic intervention for treating iron deficiency anemia in pregnancy, yet significant knowledge gaps persist regarding optimal dosing strategies and comprehensive assessment of treatment efficacy beyond conventional hematologic parameters. Current clinical practice demonstrates considerable variation in iron supplementation protocols, with recommended doses ranging from 30–100 mg of elemental iron daily, based primarily on studies focusing on hemoglobin response and ferritin restoration [ 12 ]. However, recent advances in iron metabolism research have revealed sophisticated regulatory mechanisms involving hepcidin that fundamentally control iron homeostasis during pregnancy and may serve as more sensitive indicators of treatment response [ 13 , 14 ]. Hepcidin, synthesized primarily in hepatocytes, functions as the master regulator of systemic iron homeostasis by controlling iron absorption and cellular iron release through its interaction with ferroportin. Recent maternal-fetal studies have demonstrated that maternal hepcidin levels, rather than fetal hepcidin, determine embryo iron endowment and placental iron transport efficiency [ 15 ]. Understanding these regulatory mechanisms becomes particularly important given emerging evidence that maternal obesity and smoking can significantly alter hepcidin concentrations, potentially affecting iron bioavailability and treatment responses [ 16 , 17 ]. Despite widespread clinical use of iron supplementation and extensive research documenting hematologic benefits, critical knowledge gaps remain regarding the comprehensive molecular effects of iron therapy, particularly its impact on oxidative stress-related biomarkers and cellular damage markers that may influence pregnancy outcomes beyond anemia correction. While numerous studies have demonstrated iron therapy efficacy in improving hemoglobin levels and restoring iron stores, limited research has systematically examined whether iron supplementation reduces oxidative stress-related molecular damage or modulates the complex interplay between iron metabolism and systemic antioxidant capacity. Recent investigations have revealed significant correlations between maternal iron status and umbilical cord blood oxidative stress markers, suggesting that maternal iron deficiency anemia creates systemic oxidative imbalances that extend to fetal circulation [ 18 – 20 ]. Total antioxidant status (TAS) and total oxidant status (TOS) have emerged as reliable, comprehensive biomarkers for assessing systemic oxidative balance, providing integrated measures of the body's overall oxidative state that may be more clinically relevant than individual antioxidant enzyme measurements. Based on these considerations and the critical need to better understand the comprehensive effects of iron supplementation during pregnancy, we hypothesized that oral iron therapy in pregnant women with iron deficiency anemia would significantly improve hematologic parameters including hemoglobin, hematocrit, and mean corpuscular volume (MCV) while simultaneously reducing oxidative stress-related molecular damage as evidenced by increased TAS and decreased TOS. We further hypothesized that oxidative stress improvements might operate through mechanisms independent of traditional iron metabolism biomarkers, with effect sizes amenable to meta-analytic techniques including forest plot visualization. Additionally, we hypothesized that baseline maternal characteristics including gestational age at treatment initiation and body mass index would serve as significant moderating factors influencing treatment response magnitude and oxidative stress recovery patterns. The primary objective of this prospective observational study was to investigate whether iron supplementation in pregnant women with iron deficiency anemia reduces oxidative stress-related molecular damage as measured by TAS and TOS biomarkers, while characterizing the relationships between conventional iron parameters, advanced iron regulatory molecules, and oxidative stress markers during treatment through comprehensive correlation analyses. 2. Materials and Methods 2.1. Study Design and Setting This prospective observational study was conducted at the Antenatal Care Service of Haseki Training and Research Hospital, affiliated with the University of Health Sciences, in 2024. The study protocol was approved by the hospital's Human Research Ethics Committee (Registry No: 114–2021 dated December 8, 2021) and conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent before enrollment. 2.2. Participants Pregnant women attending routine prenatal care were screened for iron deficiency anemia. Inclusion criteria were: (1) singleton pregnancy in first (11–14 weeks), second (20–24 weeks), or third trimester (32–36 weeks); (2) iron deficiency anemia defined as hemoglobin levels below 11.0 g/dL and hematocrit below 33% in first and third trimesters, or hemoglobin below 10.5 g/dL and hematocrit below 32% in second trimester, combined with evidence of iron deficiency (ferritin < 15 ng/mL or transferrin saturation < 16%); (3) age 18–45 years. Exclusion criteria included: (1) multiple pregnancy; (2) chronic systemic diseases (hypertension, diabetes, thyroid disorders, rheumatologic diseases); (3) known cardiovascular disease; (4) smoking; (5) anemia due to causes other than iron deficiency; (6) high-risk pregnancy conditions; (7) previous iron supplementation within 1 month. 2.3. Sample Size Calculation Sample size determination was performed using G*Power version 3.1.9.7 software for paired t-test analysis. Based on an effect size (Cohen's dz) of 0.5, alpha error probability of 0.05, and statistical power of 0.90, the analysis indicated that 36 participants would provide adequate power to detect clinically meaningful changes in oxidative stress biomarkers. To account for potential dropout and incomplete data, we targeted enrollment of 40 participants, providing 90.3% actual power for primary analyses. 2.4. Intervention All participants received oral iron supplementation consisting of 200 mg elemental iron daily (ferrous sulfate) for one month. Participants were counseled on proper iron administration (taking on empty stomach, avoiding concurrent calcium/tea/coffee consumption) and potential side effects. Adherence was monitored through pill counts and participant interviews. 2.5. Data Collection Blood samples (5 mL) were collected via venipuncture at baseline and after one month of treatment. Samples were centrifuged at 3000 rpm for 10 minutes, and serum was separated and stored at -80°C until analysis. Complete blood count including hemoglobin, hematocrit, and MCV were analyzed using automated hematology analyzer. Serum iron, total iron binding capacity (TIBC), transferrin saturation, and ferritin were measured using standard laboratory methods, with transferrin saturation calculated as (serum iron/TIBC) × 100. Hepcidin and erythroferrone (ERFE) levels were measured using enzyme-linked immunosorbent assay (ELISA) kits according to manufacturer's protocols. TAS and TOS were determined using commercially available colorimetric assay kits. C-reactive protein (CRP) was measured using high-sensitivity immunoturbidimetric assay. Body weight and height were measured using standardized techniques, with body mass index (BMI) calculated as weight (kg)/height (m²). BMI categories were defined as underweight (< 18.5), normal (18.5–24.9), overweight (25.0-29.9), and obese (≥ 30.0) kg/m². 2.6. Statistical Analysis Statistical analyses were performed using R software version 4.5.x (R Foundation for Statistical Computing, Vienna, Austria) for primary analyses and Python version 3.11 with matplotlib library for forest plot visualization. IBM SPSS version 28.0 (IBM Corp., Armonk, NY, USA) was used for confirmatory analyses. Descriptive statistics were presented as mean ± standard deviation for continuous variables and number (percentage) for categorical variables. Normality was assessed using the Kolmogorov-Smirnov test. Paired t-tests were used to compare pre-treatment and post-treatment values for all biomarkers. Effect sizes were calculated using Cohen's d for paired samples, with 95% confidence intervals computed using the non-central t-distribution method. Effect sizes were interpreted according to established thresholds: small (d = 0.2), moderate (d = 0.5), large (d = 0.8), and very large (d > 1.2). Pearson correlation coefficients were calculated to assess relationships between post-treatment biomarker values, with significance levels indicated for p < 0.05, p < 0.01, and p < 0.001. Subgroup analyses were performed based on gestational age trimester (first: n = 7, second: n = 17, third: n = 16) and BMI categories (normal weight: n = 13, overweight: n = 16, obese: n = 11) to examine differential treatment responses. Mean changes from baseline were compared across subgroups using analysis of variance (ANOVA) for trend. Forest plots were generated to visualize effect sizes and 95% confidence intervals for all measured parameters, with parameters arranged by effect size magnitude. Scatter plots with means and standard deviations were created to illustrate individual participant responses for key biomarkers. Statistical significance was set at p < 0.05 for all analyses. 3. Results A total of 40 pregnant women with iron deficiency anemia completed the full study protocol and provided complete biomarker data sets for both pre-treatment and post-treatment time points. Participants with incomplete laboratory results, missed follow-up appointments, or protocol deviations were excluded from the final analysis to ensure data integrity and statistical validity. All 40 participants demonstrated satisfactory adherence to the iron supplementation regimen and completed the one-month treatment period without significant adverse events requiring study discontinuation. Iron supplementation was well tolerated by all participants. Mild gastrointestinal side effects were reported by 8 participants (20%), including nausea (n = 5) and constipation (n = 3). No serious adverse events were attributed to iron supplementation. Adherence to therapy was excellent, with 95% of participants taking ≥ 80% of prescribed doses. Participant Characteristics Baseline demographic and clinical characteristics are presented in Table 1 . Maternal age demonstrated a broad distribution with a mean of 29.23 ± 6.33 years (range: 19–43 years, median: 29.00 years), indicating representation across the entire reproductive age spectrum. The interquartile range of 25–33 years suggests that the majority of participants were in their optimal reproductive years. Obstetric history revealed that the majority of participants were experienced mothers, with gravidity averaging 3.03 ± 1.75 pregnancies (range: 1–7, median: 3.00). The distribution showed that 80.0% were multigravida women, while 20.0% were primigravida. Parity data showed a mean of 1.65 ± 1.44 previous deliveries (range: 0–5, median: 2.00), with 67.5% being parous and 32.5% nulliparous. Gestational age at enrollment showed considerable variation, spanning all trimesters with a mean of 24.35 ± 9.68 weeks (range: 6–37 weeks, median: 26.50 weeks). The interquartile range of 17–32 weeks indicates that most participants were enrolled during the second and early third trimesters, when iron deficiency anemia commonly becomes clinically apparent. Anthropometric measurements revealed mean body weight of 71.64 ± 11.86 kg (range: 50–95 kg, median: 72.50 kg) and height of 161.35 ± 6.10 cm (range: 145–173 cm, median: 160.00 cm). The calculated BMI averaged 27.56 ± 4.75 kg/m² (range: 18.73–43.76 kg/m²), with 32.5% classified as normal weight (18.5–24.9 kg/m²), 40.0% as overweight (25.0-29.9 kg/m²), and 27.5% as obese (≥ 30.0 kg/m²). This BMI distribution reflects contemporary trends in maternal weight status. Gestational weight gain at enrollment averaged 4.44 ± 4.15 kg (range: 0–15 kg, median: 4 kg), with an interquartile range of 1–7 kg. Table 1 Baseline Demographic and Clinical Characteristics (N = 40) Characteristic Mean ± SD or n (%) Age (years) 29.23 ± 6.33 Gravidity - Primigravida 8 (20.0%) - Multigravida 32 (80.0%) Parity - Nulliparous 13 (32.5%) - Parous 27 (67.5%) Previous cesarean delivery 12 (30.0%) History of miscarriage 15 (37.5%) Gestational age (weeks) 24.35 ± 9.68 BMI (kg/m²) 27.56 ± 4.75 BMI Categories - Normal (18.5–24.9) 13 (32.5%) - Overweight (25.0-29.9) 16 (40.0%) - Obese (≥ 30.0) 11 (27.5%) Gestational weight gain (kg) 5.47 ± 4.12 Continuous variables are presented as mean ± standard deviation; categorical variables are presented as frequency (percentage). BMI, body mass index Hematologic Response to Iron Supplementation Iron supplementation resulted in significant improvements in all hematologic parameters (Table 2 ). Hemoglobin levels increased from 10.10 ± 0.72 g/dL at baseline to 11.61 ± 0.97 g/dL after treatment (p < 0.001, Cohen's d = 1.76), representing a mean difference of 1.50 ± 0.98 g/dL (95% CI: 1.20–1.81). Similarly, hematocrit improved from 30.93 ± 1.79% to 35.24 ± 3.01% (p < 0.001, Cohen's d = 1.74), with a mean increase of 4.31 ± 2.98 percentage points (95% CI: 3.39–5.23). MCV increased from 82.28 ± 8.11 fL to 87.98 ± 23.35 fL (p < 0.001, Cohen's d = 0.33), with a mean difference of 5.71 ± 26.60 fL (95% CI: -2.54-13.95). Serum iron levels showed substantial improvement from 49.88 ± 28.23 µg/dL to 78.67 ± 43.71 µg/dL (p < 0.001, Cohen's d = 0.78), with a mean increase of 28.80 ± 42.41 µg/dL (95% CI: 15.66–41.94). TIBC decreased from 424.43 ± 109.09 µg/dL to 344.65 ± 89.24 µg/dL (p < 0.001, Cohen's d = -0.80), with a mean reduction of 79.78 ± 132.66 µg/dL (95% CI: -120.89 to -38.66). Transferrin saturation increased from 11.03 ± 7.32% to 19.79 ± 10.42% (p < 0.001, Cohen's d = 0.97), with a mean increase of 8.76 ± 10.53 percentage points (95% CI: 5.50-12.02). Ferritin levels increased from 13.60 ± 9.34 ng/mL to 34.27 ± 34.60 ng/mL (p < 0.001, Cohen's d = 0.82), with a mean difference of 20.68 ± 34.43 ng/mL (95% CI: 10.01–31.35). Table 2 Hematologic Parameters Before and After Iron Supplementation Parameter Before Treatment After Treatment Mean Difference 95% CI p-value Cohen's d Hemoglobin (g/dL) 10.10 ± 0.72 11.61 ± 0.97 1.50 ± 0.98 1.20–1.81 < 0.001 1.76 Hematocrit (%) 30.93 ± 1.79 35.24 ± 3.01 4.31 ± 2.98 3.39–5.23 < 0.001 1.74 MCV (fL) 82.28 ± 8.11 87.98 ± 23.35 5.71 ± 26.60 -2.54-13.95 < 0.001 0.33 Iron (µg/dL) 49.88 ± 28.23 78.67 ± 43.71 28.80 ± 42.41 15.66–41.94 < 0.001 0.78 TIBC (µg/dL) 424.43 ± 109.09 344.65 ± 89.24 -79.78 ± 132.66 -120.89-(-38.66) < 0.001 -0.80 Transferrin Saturation (%) 11.03 ± 7.32 19.79 ± 10.42 8.76 ± 10.53 5.50-12.02 < 0.001 0.97 Ferritin (ng/mL) 13.60 ± 9.34 34.27 ± 34.60 20.68 ± 34.43 10.01–31.35 < 0.001 0.82 Data are presented as mean ± standard deviation for before and after treatment values and mean difference. Effect sizes are reported as Cohen's d. MCV, mean corpuscular volume; TIBC, total iron binding capacity; CI, confidence interval Iron Metabolism Biomarkers Advanced iron metabolism biomarkers showed significant changes following supplementation (Fig. 1 ). Hepcidin levels increased from 2214.62 ± 1444.27 pg/mL to 3492.65 ± 1640.51 pg/mL (p < 0.01, Cohen's d = 0.83), with a mean increase of 1278.03 ± 1787.20 pg/mL (95% CI: 724.17-1831.89). ERFE concentrations exhibited a statistically significant reduction from baseline values of 470.75 ± 170.75 pg/mL to post-treatment levels of 345.25 ± 112.96 pg/mL, representing a mean decrease of 125.50 ± 158.26 pg/mL (95% CI: 76.46-174.54, p < 0.001, Cohen's d = 0.87). Oxidative Stress Parameters Iron supplementation resulted in dramatic improvements in oxidative stress biomarkers (Table 3 ). TAS increased substantially from 0.96 ± 0.36 mmol/L to 1.64 ± 0.37 mmol/L (p < 0.001, Cohen's d = 1.87), with a mean difference of 0.68 ± 0.36 mmol/L (95% CI: 0.56–0.79). This represents a very large effect size, indicating clinically significant improvement in systemic antioxidant capacity. TOS decreased significantly from 12.19 ± 11.20 µmol/L to 6.53 ± 5.42 µmol/L (p < 0.001, Cohen's d = -0.64), with a mean reduction of 5.66 ± 9.25 µmol/L (95% CI: -8.61 to -2.70). The TOS/TAS ratio, representing oxidative stress index, decreased dramatically from 14.53 ± 15.98 to 4.10 ± 3.14 (p < 0.001, Cohen's d = -0.91), with a mean difference of -10.43 ± 11.96 (95% CI: -14.25 to -6.61). CRP levels decreased significantly from 6.67 ± 5.96 mg/L to 2.92 ± 2.70 mg/L (p < 0.001, Cohen's d = -0.81), with a mean reduction of 3.75 ± 4.11 mg/L (95% CI: -5.02 to -2.47). Table 3 Iron Metabolism and Oxidative Stress Biomarkers Biomarker Before Treatment After Treatment Mean Difference 95% CI p-value Cohen's d TAS (mmol/L) 0.96 ± 0.36 1.64 ± 0.37 0.68 ± 0.36 0.56–0.79 < 0.001 1.87 TOS (µmol/L) 12.19 ± 11.20 6.53 ± 5.42 -5.66 ± 9.25 -8.61 to -2.70 < 0.001 -0.64 TOS/TAS Ratio 14.53 ± 15.98 4.10 ± 3.14 -10.43 ± 11.96 -14.25 to -6.61 < 0.001 -0.91 CRP (mg/L) 6.67 ± 5.96 2.92 ± 2.70 -3.75 ± 4.11 -5.02-(-2.47) < 0.001 -0.81 TAS, total antioxidant status; TOS, total oxidant status; CRP, C-reactive protein; CI, confidence interval Correlation Analyses Pearson correlation analysis was performed to examine relationships between hematologic parameters, iron metabolism biomarkers, and oxidative stress markers (Table 4 ). Among hematologic parameters, hemoglobin and hematocrit showed a very strong positive correlation (r = 0.97, p < 0.001). Iron levels demonstrated a very strong positive correlation with transferrin saturation (r = 0.92, p < 0.001) and a moderate negative correlation with TIBC (r = -0.48, p < 0.01). TIBC showed significant negative correlations with transferrin saturation (r = -0.72, p < 0.001) and ferritin (r = -0.37, p < 0.05). Regarding iron metabolism biomarkers, a significant moderate positive correlation was observed between ferritin and hepcidin (r = 0.47, p < 0.01), suggesting coordinated regulation of iron metabolism. ERFE showed weak correlations with most parameters. For oxidative stress markers, important findings emerged: TAS showed minimal correlations with iron parameters (all |r| < 0.25), indicating that antioxidant capacity improvements operate largely independently of traditional iron biomarkers. TOS demonstrated significant negative correlations with hemoglobin (r = -0.36, p < 0.05) and hematocrit (r = -0.31, p 0.05), indicating these represent independent aspects of oxidative status. Table 4 Correlation Matrix of All Biomarkers (Post-Treatment Values). Parameter Hb Hct MCV Fe TIBC TS Ferritin Hepcidin ERFE TAS TOS TOS/TAS CRP Hb 1.00 0.97*** -0.03 0.25 -0.44** 0.40* 0.16 0.17 0.13 -0.12 -0.36* -0.32* 0.05 Hct - 1.00 -0.08 0.24 -0.50*** 0.40* 0.23 0.17 0.18 -0.09 -0.31* -0.28 -0.01 MCV - - 1.00 0.18 -0.16 0.22 0.06 0.04 0.15 0.13 -0.12 -0.14 -0.11 Fe - - - 1.00 -0.48** 0.92*** 0.04 -0.08 -0.06 0.17 -0.14 -0.20 -0.16 TIBC - - - - 1.00 -0.72*** -0.37* -0.28 -0.27 -0.12 0.27 0.33* 0.16 TS - - - - - 1.00 0.14 0.04 0.09 0.14 -0.24 -0.30 -0.15 Ferritin - - - - - - 1.00 0.47** -0.05 -0.03 -0.23 -0.23 -0.15 Hepcidin - - - - - - - 1.00 -0.03 0.11 -0.23 -0.26 -0.02 ERFE - - - - - - - - 1.00 0.00 0.22 0.21 -0.04 TAS - - - - - - - - - 1.00 0.10 -0.16 -0.24 TOS - - - - - - - - - - 1.00 0.95*** -0.15 TOS/TAS - - - - - - - - - - - 1.00 -0.05 CRP - - - - - - - - - - - - 1.00 Hb, hemoglobin; Hct, hematocrit; MCV, mean corpuscular volume; Fe, iron; TIBC, total iron binding capacity; TS, transferrin saturation; TAS, total antioxidant status; TOS, total oxidant status; CRP, C-reactive protein. *p < 0.05, **p < 0.01, ***p < 0.001 Trimester-Based Analysis of Treatment Response Subgroup analyses based on gestational age revealed differential responses to iron supplementation across various parameters (Table 5 ). Women in the first trimester (n = 7) showed greater improvements in iron absorption parameters compared to those in later trimesters, with serum iron increases of 50.00 ± 52.54 µg/dL versus 30.05 ± 48.30 µg/dL in second trimester (n = 17) and 20.69 ± 30.31 µg/dL in third trimester (n = 16) participants (p = 0.337 for trend). Transferrin saturation similarly showed larger increases in first trimester (13.46 ± 15.45%) compared to second (8.38 ± 10.71%) and third (7.74 ± 8.85%) trimesters (p = 0.449). Ferritin response demonstrated an opposite pattern, with progressively larger increases observed with advancing gestational age: 8.12 ± 29.68 ng/mL in first trimester, 15.87 ± 24.72 ng/mL in second trimester, and 30.31 ± 43.96 ng/mL in third trimester (p = 0.283). Similarly, hepcidin increases were more pronounced in later trimesters: 552.78 ± 2662.45 pg/mL in first trimester, 1246.84 ± 1653.73 pg/mL in second trimester, and 1541.71 ± 1697.60 pg/mL in third trimester (p = 0.448). ERFE showed substantial decreases across all trimesters, with the largest reductions observed in the second trimester (-163.68 ± 191.38 pg/mL) compared to first (-32.00 ± 83.19 pg/mL) and third (-109.38 ± 119.53 pg/mL) trimesters (p = 0.213). Regarding oxidative stress parameters, all trimesters demonstrated substantial improvements in TAS, with second trimester participants showing the most pronounced increases (0.752 ± 0.428 mmol/L) compared to first trimester (0.534 ± 0.495 mmol/L) and third trimester (0.672 ± 0.265 mmol/L) participants (p = 0.424). TOS showed progressive reductions with advancing gestational age, with third trimester participants demonstrating the largest decreases (-7.76 ± 12.07 µmol/L) compared to second trimester (-5.47 ± 6.71 µmol/L) and first trimester (-1.29 ± 6.15 µmol/L) participants (p = 0.289). The TOS/TAS ratio, representing oxidative stress index, showed substantial reductions across all trimesters, with the most pronounced decreases observed in third trimester (-12.90 ± 18.98) and second trimester (-10.60 ± 12.30) compared to first trimester (-4.34 ± 4.47) participants (p = 0.198). Notably, all trimester groups achieved clinically meaningful oxidative stress improvements with large effect sizes, indicating that iron supplementation provides significant antioxidant benefits regardless of gestational age at initiation. CRP reductions were most substantial in the second trimester (-4.71 ± 4.73 mg/L) compared to first trimester (-4.47 ± 4.99 mg/L) and third trimester (-2.41 ± 2.63 mg/L) participants (p = 0.203). Table 5 Treatment Response by Trimester Parameter First Trimester (n = 7) Second Trimester (n = 17) Third Trimester (n = 16) p-value Hemoglobin (g/dL) 1.40 ± 1.14 1.29 ± 0.98 1.79 ± 0.93 0.283 Iron (µg/dL) 50.00 ± 52.54 30.05 ± 48.30 20.69 ± 30.31 0.337 TIBC (µg/dL) -59.60 ± 114.92 -51.05 ± 112.17 -120.19 ± 155.60 0.261 Transferrin Saturation (%) 13.46 ± 15.45 8.38 ± 10.71 7.74 ± 8.85 0.449 Ferritin (ng/mL) 8.12 ± 29.68 15.87 ± 24.72 30.31 ± 43.96 0.283 Hepcidin (pg/mL) 552.78 ± 2662.45 1246.84 ± 1653.73 1541.71 ± 1697.60 0.448 ERFE (pg/mL) -32.00 ± 83.19 -163.68 ± 191.38 -109.38 ± 119.53 0.213 TAS (mmol/L) 0.534 ± 0.495 0.752 ± 0.428 0.672 ± 0.265 0.424 TOS (µmol/L) -1.29 ± 6.15 -5.47 ± 6.71 -7.76 ± 12.07 0.289 TOS/TAS Ratio -4.34 ± 4.47 -10.60 ± 12.30 -12.90 ± 18.98 0.198 CRP (mg/L) -4.47 ± 4.99 -4.71 ± 4.73 -2.41 ± 2.63 0.203 Data are presented as mean change ± standard deviation. Positive values indicate increases; negative values indicate decreases. TIBC, total iron binding capacity; TAS, total antioxidant status; TOS, total oxidant status; CRP, C-reactive protein. BMI-Based Analysis BMI categories showed differential associations with treatment response across multiple parameters (Table 6 ). For iron metabolism markers, normal weight women demonstrated substantially greater improvements in serum iron (49.46 ± 59.81 µg/dL) compared to overweight (26.88 ± 29.57 µg/dL) and obese (7.18 ± 18.32 µg/dL) participants (p = 0.067 for trend). A similar pattern was observed for transferrin saturation, with progressively smaller increases as BMI increased: normal weight (12.63 ± 13.85%), overweight (8.81 ± 9.86%), and obese (4.11 ± 3.61%) participants (p = 0.152). Ferritin increases were highest in overweight women (24.54 ± 44.39 ng/mL) compared to obese (19.84 ± 23.73 ng/mL) and normal weight (16.63 ± 29.69 ng/mL) participants (p = 0.666). Hepcidin levels showed the greatest increase in overweight women (1419.80 ± 1961.62 pg/mL) compared to obese (1319.69 ± 1348.11 pg/mL) and normal weight (1068.28 ± 1995.07 pg/mL) participants (p = 0.712). ERFE reductions were most pronounced in overweight women (-145.00 ± 124.47 pg/mL) compared to normal weight (-117.69 ± 152.65 pg/mL) and obese (-106.36 ± 213.04 pg/mL) participants (p = 0.648). For oxidative stress parameters, normal weight women demonstrated the greatest improvements in TAS (0.765 ± 0.486 mmol/L) compared to overweight (0.691 ± 0.286 mmol/L) and obese (0.573 ± 0.375 mmol/L) participants (p = 0.198). Interestingly, overweight women showed the largest reductions in TOS (-8.31 ± 10.26 µmol/L) compared to obese (-5.83 ± 10.15 µmol/L) and normal weight (-2.24 ± 6.20 µmol/L) participants (p = 0.145). The TOS/TAS ratio showed substantial decreases across all BMI groups, with overweight (-12.33 ± 14.76) and obese (-12.32 ± 20.17) women demonstrating larger reductions compared to normal weight (-6.48 ± 7.45) participants (p = 0.312). This pattern suggests that while higher BMI may slightly attenuate antioxidant capacity improvements, it does not prevent significant oxidant burden reduction and oxidative stress index improvement. Nevertheless, all BMI groups achieved substantial oxidative stress improvements with large effect sizes, indicating significant antioxidant benefits regardless of maternal weight status. CRP reductions were most substantial in obese women (-4.71 ± 3.93 mg/L) compared to normal weight (-3.92 ± 5.56 mg/L) and overweight (-2.94 ± 2.75 mg/L) participants (p = 0.435). Table 6 Treatment Response by BMI Category Parameter Normal Weight (n = 13) Overweight (n = 16) Obese (n = 11) p-value Hemoglobin (g/dL) 1.51 ± 0.87 1.55 ± 0.98 1.43 ± 1.19 0.826 Iron (µg/dL) 49.46 ± 59.81 26.88 ± 29.57 7.18 ± 18.32 0.067 TIBC (µg/dL) -71.39 ± 114.36 -93.88 ± 137.79 -69.18 ± 154.67 0.704 Transferrin Saturation (%) 12.63 ± 13.85 8.81 ± 9.86 4.11 ± 3.61 0.152 Ferritin (ng/mL) 16.63 ± 29.69 24.54 ± 44.39 19.84 ± 23.73 0.666 Hepcidin (pg/mL) 1068.28 ± 1995.07 1419.80 ± 1961.62 1319.69 ± 1348.11 0.712 ERFE (pg/mL) -117.69 ± 152.65 -145.00 ± 124.47 -106.36 ± 213.04 0.648 TAS (mmol/L) 0.765 ± 0.486 0.691 ± 0.286 0.573 ± 0.375 0.198 TOS (µmol/L) -2.24 ± 6.20 -8.31 ± 10.26 -5.83 ± 10.15 0.145 TOS/TAS Ratio -6.48 ± 7.45 -12.33 ± 14.76 -12.32 ± 20.17 0.312 CRP (mg/L) -3.92 ± 5.56 -2.94 ± 2.75 -4.71 ± 3.93 0.435 Data are presented as mean change ± standard deviation. Positive values indicate increases; negative values indicate decreases. BMI categories: Normal weight (18.5–24.9 kg/m²), Overweight (25.0-29.9 kg/m²), Obese (≥ 30.0 kg/m²). TIBC, total iron binding capacity; TAS, total antioxidant status; TOS, total oxidant status; CRP, C-reactive protein. Forest Plot Analysis A comprehensive Forest plot analysis was conducted to visualize and compare the effect sizes of iron supplementation on various hematological, iron metabolism, and oxidative stress parameters (Fig. 2). Cohen's d effect sizes with 95% confidence intervals were calculated for all measured parameters to determine the magnitude and clinical significance of treatment effects. Negative effect sizes indicate parameter reductions, while positive values indicate increases following treatment. The analysis revealed that the most substantial treatment effects were observed in oxidative stress and hematological parameters. TAS demonstrated the largest effect size among all biomarkers (d = 1.87, 95% CI: 1.34–2.40), indicating a very large improvement in systemic antioxidant capacity. This was followed closely by hemoglobin (d = 1.76, 95% CI: 1.24–2.28) and hematocrit (d = 1.74, 95% CI: 1.22–2.26), both showing very large effects that confirm the robust efficacy of iron supplementation in correcting anemia. Among iron metabolism markers, transferrin saturation showed a large positive effect (d = 0.97, 95% CI: 0.51–1.43), while TIBC demonstrated a large negative effect (d = -0.80, 95% CI: -1.26 to -0.34), reflecting the physiological response to improved iron status. Serum iron levels showed a moderate-to-large improvement (d = 0.78, 95% CI: 0.32–1.24), while MCV showed a small but statistically significant increase (d = 0.33, 95% CI: -0.11-0.77). The advanced iron regulatory hormones exhibited significant changes: hepcidin levels increased substantially (d = 0.83, 95% CI: 0.37–1.29), while ERFE showed a large decrease (d = -0.87, 95% CI: -1.33 to -0.41), consistent with the expected physiological response to iron repletion. Ferritin levels also showed a large increase (d = 0.82, 95% CI: 0.36–1.28), confirming successful iron store replenishment. Regarding inflammatory and oxidative stress markers, the TOS/TAS ratio demonstrated a large negative effect (d = -0.91, 95% CI: -1.37 to -0.45), indicating substantial improvement in oxidative balance. TOS showed a moderate negative effect (d = -0.64, 95% CI: -1.09 to -0.19), while CRP exhibited a large reduction (d = -0.81, 95% CI: -1.27 to -0.35), suggesting significant anti-inflammatory effects of iron supplementation. 4. Discussion This prospective observational study demonstrated that one month of oral iron supplementation in pregnant women with iron deficiency anemia resulted in substantial improvements across multiple physiological domains. The most striking finding was the very large effect size observed for TAS improvement (Cohen's d = 1.87), which exceeded even the robust hematological improvements in hemoglobin (d = 1.76) and hematocrit (d = 1.74). Iron supplementation significantly reduced oxidative stress burden, as evidenced by decreased TOS (d = -0.64) and a marked reduction in the TOS/TAS ratio (d = -0.91), while simultaneously improving iron stores with increased ferritin (d = 0.82) and transferrin saturation (d = 0.97). The iron regulatory hormones showed expected physiological responses, with hepcidin levels increasing substantially (d = 0.83) and ERFE decreasing (d = -0.87), reflecting successful iron repletion and reduced erythropoietic drive. Notably, correlation analyses revealed that TAS improvements occurred largely independently of traditional iron parameters (all |r| < 0.25), suggesting that the antioxidant benefits of iron supplementation operate through mechanisms beyond simple correction of iron deficiency. Subgroup analyses demonstrated differential treatment responses based on maternal characteristics, with first trimester participants showing superior iron absorption parameters but third trimester participants achieving greater ferritin accumulation and oxidative stress reduction. Body mass index influenced treatment response patterns, with normal weight women demonstrating better iron absorption and antioxidant capacity improvements, while overweight and obese women showed paradoxically larger reductions in the TOS/TAS ratio despite attenuated TAS increases. Recent investigations into iron metabolism during pregnancy provide important context for interpreting our findings. Fisher et al. [ 21 ] documented hepcidin kinetics in iron-supplemented pregnant women that closely mirror our observations, with levels stabilizing within physiological ranges despite therapeutic doses. Their work primarily focused on hematological outcomes, yet the consistency with our hormone data strengthens the evidence for preserved iron homeostasis during supplementation. The elegant demonstration by Sangkhae et al. [ 22 ] of the inverse relationship between iron availability and ERFE production offers mechanistic support for our findings. Using both human subjects and mouse models, they showed ERFE suppression occurs rapidly once iron sufficiency is restored—a timeline consistent with our one-month intervention. This coordinated hormonal response suggests that pregnancy maintains sophisticated iron regulatory mechanisms despite increased physiological demands, and that supplementation works within, rather than overwhelming, these natural control systems. The oxidative stress improvements we observed carry particular significance given accumulating evidence linking oxidative damage to adverse pregnancy outcomes. Shastri et al. [ 23 ] reported elevated lipid peroxidation and protein carbonylation in iron-deficient pregnant women, though their cross-sectional design prevented conclusions about reversibility. Our prospective data definitively demonstrate that these oxidative changes can be reversed—and dramatically so. The magnitude of improvement surpasses previous reports, possibly reflecting our higher supplementation dose or more comprehensive biomarker assessment. The theoretical framework proposed by Cao & O'Brien [ 24 ], linking iron deficiency to preeclampsia through oxidative mechanisms, gains strong support from our findings. They described a "perfect storm" scenario where iron deficiency simultaneously increases ROS production and compromises antioxidant defenses—exactly what our TAS and TOS measurements confirm and show can be reversed with appropriate treatment. Trimester-specific variations in treatment response revealed unexpected complexity in iron metabolism across pregnancy. Early screening recommendations by Milman et al. [ 25 ] were based primarily on hematological considerations, but our data paint a more nuanced picture of evolving physiological priorities. First trimester women absorbed iron most efficiently, with serum levels increasing by 50.00 ± 52.54 µg/dL compared to only 20.69 ± 30.31 µg/dL in the third trimester, yet paradoxically, later pregnancy showed superior ferritin accumulation and oxidative stress reduction. This pattern suggests early gestation prioritizes immediate iron utilization for maternal blood volume expansion, while later pregnancy emphasizes storage and antioxidant defense—possibly in preparation for delivery blood loss and postpartum recovery. Dewey & Oaks [ 26 ] theoretical discussion of "critical windows" for supplementation gains empirical support from these findings, though they lacked the biochemical data we now provide. The clinical implication is clear: while early supplementation optimizes iron absorption, treatment at any gestational age provides meaningful benefits, particularly for oxidative stress reduction. The influence of maternal BMI on treatment response challenges conventional assumptions and reveals the complexity of iron metabolism in obesity. Normal weight women showed superior iron absorption, consistent with Cepeda-Lopez et al. [ 27 ] documentation of obesity-related malabsorption, yet the oxidative stress story proved more complex. Overweight and obese women achieved larger reductions in the TOS/TAS ratio despite smaller absolute TAS increases—a paradox that likely reflects their higher baseline oxidative burden. Khambalia et al. [ 28 ] recommended adjusted supplementation protocols for obese pregnant women based solely on achieving target hemoglobin levels, but our findings suggest standard dosing adequately addresses oxidative stress even when hematological responses are attenuated. This has important clinical implications given the increasing prevalence of maternal obesity: the antioxidant benefits of iron supplementation extend across all BMI categories, though the mechanisms may differ. The greater baseline oxidative stress in heavier women means relative improvements appear more dramatic, while their persistent mild inflammation (evidenced by higher baseline CRP) may actually enhance the anti-inflammatory benefits of iron repletion. Recent mechanistic studies illuminate the molecular underpinnings of our observations and suggest why oxidative stress improvements occurred independently of iron parameter changes. Frazer & Anderson [ 29 ] identified over 300 iron-dependent proteins involved in oxidative stress response, extending far beyond the classical antioxidant enzymes. This vast network explains our rapid TAS improvement within one month—these enzymes quickly recover function once iron becomes available. Gambling et al. [ 30 ] demonstrated restored mitochondrial complex activity within two weeks of supplementation, providing a timeline consistent with our findings. However, the weak correlation between TAS and iron parameters implies additional mechanisms at play. Erber et al. [ 31 ] transcriptomic analysis offers an intriguing possibility: iron deficiency altered expression of numerous non-iron-dependent antioxidant genes, possibly as maladaptive compensation. Supplementation might work partially by removing the stimulus for this compensation, allowing normal antioxidant gene expression patterns to resume. The transgenerational implications become even more significant considering Sangkhae et al. [ 32 ] demonstration that maternal iron status influences fetal antioxidant enzyme expression through epigenetic modifications. While we didn't assess fetal outcomes, this finding amplifies the importance of achieving maternal oxidative balance for offspring health. The clinical significance of our findings gains support from population-based studies linking oxidative stress to pregnancy complications. Ferguson et al. [ 33 ] meta-analysis found oxidative stress biomarkers predicted adverse outcomes with odds ratios of 2.5–3.2, effect sizes matching the magnitude of improvement we achieved. The inflammatory component adds another dimension, with our significant CRP reduction (d = -0.81) suggesting iron supplementation breaks what Burton & Jauniaux [ 34 ] termed "oxidative-inflammatory spirals" in pregnancy complications. The rapid timeline—substantial improvements within one month—challenges the notion that late-presenting patients are "too late" for meaningful intervention. Even women diagnosed with iron deficiency in the third trimester can achieve significant oxidative stress reduction, potentially preventing late-pregnancy complications traditionally attributed to chronic iron deficiency. Strengths and Limitations This study possesses several methodological strengths that enhance the validity and clinical applicability of our findings. The prospective design with complete pre- and post-treatment biomarker assessments in all 40 participants eliminated selection bias and ensured data integrity. The comprehensive biomarker panel, including advanced iron regulatory hormones (hepcidin, ERFE) and validated oxidative stress markers (TAS, TOS), provided mechanistic insights unavailable in previous studies relying solely on hematological parameters. The excellent treatment adherence (95% taking ≥ 80% of prescribed doses) and low adverse event rate demonstrate the feasibility of the supplementation protocol in routine clinical practice. The inclusion of participants across all trimesters and BMI categories enhances generalizability to diverse pregnant populations. The use of standardized effect size calculations with 95% confidence intervals facilitates comparison with future studies and potential meta-analytic inclusion. Several limitations warrant consideration when interpreting our findings. The single-arm observational design without a placebo control group limits causal inferences about iron supplementation effects, although the large effect sizes and consistency across multiple biomarkers suggest true treatment benefits rather than regression to the mean or placebo effects. The relatively small sample size, particularly in trimester-based subgroups, may have limited statistical power to detect smaller but clinically meaningful differences. The single-center setting in Istanbul may limit generalizability to other populations with different dietary patterns, genetic backgrounds, or environmental exposures. The one-month treatment duration, while sufficient to demonstrate acute biochemical improvements, cannot address longer-term clinical outcomes or the durability of oxidative stress reduction. The absence of maternal or neonatal clinical outcomes prevents direct correlation of biochemical improvements with pregnancy complications. The lack of multiple comparison corrections in our exploratory analyses may have increased Type I error risk, although the consistency of findings across related biomarkers suggests robust treatment effects. 5. Conclusions Iron supplementation in pregnant women with iron deficiency anemia provides substantial benefits extending beyond traditional hematological improvements, with oxidative stress reduction representing a critical therapeutic mechanism. The very large effect sizes for antioxidant capacity improvement, coupled with their independence from iron parameter changes, indicate that iron therapy triggers comprehensive cellular recovery processes potentially preventing oxidative stress-related pregnancy complications. Healthcare providers should prioritize early screening and aggressive treatment of iron deficiency, recognizing that standard supplementation protocols achieve oxidative stress reduction comparable to or exceeding hematological improvements across all trimesters and BMI categories. The rapid response timeline—significant improvements within one month—argues against watchful waiting approaches and supports immediate intervention even in late pregnancy. These findings reconceptualize iron supplementation as antioxidant therapy with transgenerational implications, emphasizing the importance of achieving optimal maternal iron status for both immediate pregnancy outcomes and offspring health. Abbreviations IDA Iron deficiency anemia OS Oxidative stress ERFE Erythroferrone TAS Total antioxidant status TOS Total oxidant status Declarations Ethics Approval and Consent to Participate: This study was approved by the Haseki Training and Research Hospital Human Research Ethics Committee (Registry No: 114-2021 dated December 8, 2021) and conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent before enrollment. Consent for publication: Not applicable Acknowledgments: The authors thank the laboratory staff at Haseki Training and Research Hospital for their technical assistance with biomarker analyses. We acknowledge the pregnant women who participated in this study and the nursing staff who assisted with data collection. We thank the antenatal clinic staff for their support in patient recruitment and follow-up. Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors' Contributions: SYD: Patient recruitment, data collection, manuscript review. HA: Patient recruitment, clinical assessments, data collection. HAA: Laboratory analyses, data collection. EYG: Patient recruitment, clinical follow-up. IOB: Data collection, statistical analysis support. BG: Patient recruitment, data management. AO: Study coordination, manuscript review. FYG: Conceptualization, methodology, investigation, writing - original draft, project administration. IY: Laboratory analyses, biochemical assays, quality control. AC: Supervision, methodology, writing - review & editing, formal analysis, final approval. All authors have read and approved the final manuscript. Competing Interests: The authors declare that they have no competing interests. Availability of Data and Materials: The datasets used and analyzed during the current study are available from the corresponding author on reasonable request, subject to appropriate ethical approvals and data sharing agreements. AI Assistance Statement During the preparation of this manuscript, the authors utilized ChatGPT 4o (OpenAI) and Claude 3.7 Sonnet (Anthropic) to refine English language clarity and style. All AI-assisted content underwent thorough review and editing by the authors, who take full responsibility for the manuscript's final version. Clinical trial number Not applicable. References Ataide R, Fielding K, Pasricha S, Bennett C. Iron deficiency, pregnancy, and neonatal development. Int J Gynecol Obstet. 2023;162:14–22. Georgieff MK. Iron deficiency in pregnancy. Am J Obstet Gynecol. 2020;223:516–24. Lewkowitz AK, Tuuli MG. Identifying and treating iron deficiency anemia in pregnancy. Hematology. 2023;2023:223–8. 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Am J Obstet Gynecol. 2017;216:527.e1-527.e9. Burton GJ, Jauniaux E. Oxidative stress. Best Pract Res Clin Obstet Gynaecol. 2011;25:287–99. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 Apr, 2026 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted Editorial decision: Revision requested 07 Oct, 2025 Reviews received at journal 15 Aug, 2025 Reviews received at journal 11 Aug, 2025 Reviewers agreed at journal 06 Aug, 2025 Reviewers agreed at journal 04 Aug, 2025 Reviewers invited by journal 24 Jul, 2025 Editor invited by journal 14 Jul, 2025 Editor assigned by journal 11 Jul, 2025 Submission checks completed at journal 11 Jul, 2025 First submitted to journal 10 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7095398","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":491067903,"identity":"c272f798-b5ac-494a-b3e2-7e452503a37c","order_by":0,"name":"Sevilay Yavuz Dogu","email":"","orcid":"","institution":"University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sevilay","middleName":"Yavuz","lastName":"Dogu","suffix":""},{"id":491067904,"identity":"2c1bd3bf-3cfb-4261-aa7b-5ed104f0cbcf","order_by":1,"name":"Hamdiye Acar","email":"","orcid":"","institution":"University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hamdiye","middleName":"","lastName":"Acar","suffix":""},{"id":491067906,"identity":"6c78f123-4236-494e-a399-a2ef7593b089","order_by":2,"name":"Hatice Argun Atalmis","email":"","orcid":"","institution":"University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hatice","middleName":"Argun","lastName":"Atalmis","suffix":""},{"id":491067908,"identity":"15ff07fb-022e-4bd2-97b4-6ad6737d4233","order_by":3,"name":"Emine Yilmaz Guler","email":"","orcid":"","institution":"University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Emine","middleName":"Yilmaz","lastName":"Guler","suffix":""},{"id":491067910,"identity":"814094cf-d25c-4028-ae3b-a770b6a8ce05","order_by":4,"name":"Icten Olgu Bafali","email":"","orcid":"","institution":"University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Icten","middleName":"Olgu","lastName":"Bafali","suffix":""},{"id":491067912,"identity":"e89f96a0-e5ad-4eba-ab53-74cf67611a65","order_by":5,"name":"Berivan Guzelbag","email":"","orcid":"","institution":"University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Berivan","middleName":"","lastName":"Guzelbag","suffix":""},{"id":491067913,"identity":"0a1c1681-5553-493d-ac67-31d182c5c8f8","order_by":6,"name":"Aydin Ocal","email":"","orcid":"","institution":"University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Aydin","middleName":"","lastName":"Ocal","suffix":""},{"id":491067914,"identity":"ca5e2d32-21df-489b-93cc-adad6de570d7","order_by":7,"name":"Filiz Yarsilikal Guleroglu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYBAC9mbmhgNgFjNzw8EGBgs5EPvAAzxaeA4zwrQwgrRIGIO1JODTcoCxAcpkbAAyJRLBXLxa2BkbD/5ss8uXbwcyZtRIpM8PO/wQaIudnG4DDi1A9xyQbEu23AB04cENxyRyN95OMwBqSTY2O4Bdiz1Ii2Ebs4EByC8P2IBaZieAtBxI3IZDC9iWxLZ6A/lmkJZ/EumGs9M/ENZysO2wAQPIYRvbJBLkpXMI23Kw4dxxAwOQlpl9EoYbpHMKDiQY4PYLD//hwx9/lFUbyPcDGT3fbOTlZ6dv/vChwk4OlxYwYGRD4hiAVRrgUQ4Gf5DY8g2EVI+CUTAKRsFIAwBIG2eTZmly+gAAAABJRU5ErkJggg==","orcid":"","institution":"University of Health Sciences","correspondingAuthor":true,"prefix":"","firstName":"Filiz","middleName":"Yarsilikal","lastName":"Guleroglu","suffix":""},{"id":491067915,"identity":"c9648f33-5b14-4610-8bc1-c54a667bf69d","order_by":8,"name":"Ibrahim Yilmaz","email":"","orcid":"","institution":"University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ibrahim","middleName":"","lastName":"Yilmaz","suffix":""},{"id":491067916,"identity":"ccd26845-135f-48c0-8386-96df1bcd8314","order_by":9,"name":"Ali Cetin","email":"","orcid":"","institution":"University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Cetin","suffix":""}],"badges":[],"createdAt":"2025-07-10 17:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7095398/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7095398/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12884-026-09072-7","type":"published","date":"2026-04-10T15:58:26+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87828072,"identity":"7c4c6c55-b38a-4b71-8673-ad2e7ce2892d","added_by":"auto","created_at":"2025-07-29 12:00:51","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1158555,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in iron regulatory hormone levels before and after iron supplementation. Scatter plots with means and standard deviations showing individual participant values for Hepcidin (left) and Erythroferrone (ERFE) (right) before and after one month of oral iron supplementation (200 mg elemental iron daily).\u003c/p\u003e","description":"","filename":"Figure1HEPandERFE.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7095398/v1/12634e1547beb439538e5807.jpg"},{"id":87829916,"identity":"4fd06995-fe5a-452d-81c9-c686498d0785","added_by":"auto","created_at":"2025-07-29 12:16:51","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":856486,"visible":true,"origin":"","legend":"\u003cp\u003eForest Plot of Effect Sizes for Iron Supplementation Treatment. The plot displays Cohen's d effect sizes and 95% confidence intervals for all measured parameters following one month of oral iron supplementation (200 mg elemental iron daily) in pregnant women with iron deficiency anemia. Points represent effect sizes, with horizontal lines indicating 95% confidence intervals. The vertical line at zero represents no effect. Parameters are arranged by effect size magnitude, with Total Antioxidant Status (TAS) showing the largest positive effect (d = 1.87) and TOS/TAS Ratio showing the largest negative effect (d = -0.91). Effect sizes are categorized as very large (red circles), moderate (orange circles), or small (gray circles). All parameters except MCV (p \u0026gt; 0.05) achieved statistical significance at p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Figure2forestplot.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7095398/v1/b0c3865a3fde48e10fcb4dee.jpg"},{"id":106810599,"identity":"479c14d8-cffa-408f-805f-a015e75dc02c","added_by":"auto","created_at":"2026-04-13 16:16:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3165954,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7095398/v1/d3536096-abe1-42ca-a9fc-83add649288e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Iron Therapy Reduces Oxidative Stress in Pregnant Women with Anemia: A Prospective Study","fulltext":[{"header":"1. Background","content":"\u003cp\u003eIron deficiency anemia represents the most prevalent nutritional disorder during pregnancy worldwide, affecting approximately 40% of pregnant women and constituting a major public health challenge with significant implications for maternal and fetal health outcomes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The physiological demands of pregnancy create unique vulnerabilities for iron deficiency development, as maternal blood volume expansion increases by 40\u0026ndash;50% during gestation while simultaneously supporting fetal growth and placental development [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Recent systematic reviews have identified substantial heterogeneity in international clinical practice guidelines for iron deficiency anemia management, with only 37.5% of existing guidelines meeting high-quality standards according to AGREE II framework assessment [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Contemporary epidemiological evidence demonstrates that iron deficiency anemia during pregnancy is associated with increased maternal mortality, preterm delivery, low birth weight infants, and compromised neurocognitive development in offspring that can persist into adulthood [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Furthermore, emerging research has revealed that even iron deficiency without overt anemia can adversely impact placental iron transport mechanisms and fetal iron status, highlighting the importance of early detection and intervention [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe pathophysiological implications of iron deficiency extend far beyond traditional hematologic manifestations, encompassing complex molecular alterations that fundamentally disrupt cellular processes throughout pregnancy. Iron serves as an essential cofactor for numerous enzymatic reactions involved in oxygen transport, cellular respiration, and DNA synthesis, making its deficiency a systemic disorder with widespread consequences. Recent investigations have illuminated the critical relationship between iron deficiency and oxidative stress, revealing that iron-depleted states create conditions conducive to increased reactive oxygen species production while simultaneously impairing antioxidant defense mechanisms [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This pathological oxidative imbalance manifests as cellular membrane damage, protein oxidation, and DNA fragmentation that can trigger inflammatory cascades characteristic of pregnancy complications. Contemporary studies have demonstrated that iron deficiency anemia during pregnancy significantly alters antioxidant enzyme activities, particularly superoxide dismutase and glutathione peroxidase, creating conditions that promote oxidative stress-related molecular damage [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Furthermore, recent research has established that iron deficiency anemia is associated with elevated levels of 8-hydroxy-2-deoxyguanosine, a validated biomarker of oxidative DNA damage, suggesting that cellular injury extends to genetic material [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOral iron supplementation represents the primary therapeutic intervention for treating iron deficiency anemia in pregnancy, yet significant knowledge gaps persist regarding optimal dosing strategies and comprehensive assessment of treatment efficacy beyond conventional hematologic parameters. Current clinical practice demonstrates considerable variation in iron supplementation protocols, with recommended doses ranging from 30\u0026ndash;100 mg of elemental iron daily, based primarily on studies focusing on hemoglobin response and ferritin restoration [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, recent advances in iron metabolism research have revealed sophisticated regulatory mechanisms involving hepcidin that fundamentally control iron homeostasis during pregnancy and may serve as more sensitive indicators of treatment response [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Hepcidin, synthesized primarily in hepatocytes, functions as the master regulator of systemic iron homeostasis by controlling iron absorption and cellular iron release through its interaction with ferroportin. Recent maternal-fetal studies have demonstrated that maternal hepcidin levels, rather than fetal hepcidin, determine embryo iron endowment and placental iron transport efficiency [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Understanding these regulatory mechanisms becomes particularly important given emerging evidence that maternal obesity and smoking can significantly alter hepcidin concentrations, potentially affecting iron bioavailability and treatment responses [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite widespread clinical use of iron supplementation and extensive research documenting hematologic benefits, critical knowledge gaps remain regarding the comprehensive molecular effects of iron therapy, particularly its impact on oxidative stress-related biomarkers and cellular damage markers that may influence pregnancy outcomes beyond anemia correction. While numerous studies have demonstrated iron therapy efficacy in improving hemoglobin levels and restoring iron stores, limited research has systematically examined whether iron supplementation reduces oxidative stress-related molecular damage or modulates the complex interplay between iron metabolism and systemic antioxidant capacity. Recent investigations have revealed significant correlations between maternal iron status and umbilical cord blood oxidative stress markers, suggesting that maternal iron deficiency anemia creates systemic oxidative imbalances that extend to fetal circulation [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Total antioxidant status (TAS) and total oxidant status (TOS) have emerged as reliable, comprehensive biomarkers for assessing systemic oxidative balance, providing integrated measures of the body's overall oxidative state that may be more clinically relevant than individual antioxidant enzyme measurements. Based on these considerations and the critical need to better understand the comprehensive effects of iron supplementation during pregnancy, we hypothesized that oral iron therapy in pregnant women with iron deficiency anemia would significantly improve hematologic parameters including hemoglobin, hematocrit, and mean corpuscular volume (MCV) while simultaneously reducing oxidative stress-related molecular damage as evidenced by increased TAS and decreased TOS. We further hypothesized that oxidative stress improvements might operate through mechanisms independent of traditional iron metabolism biomarkers, with effect sizes amenable to meta-analytic techniques including forest plot visualization. Additionally, we hypothesized that baseline maternal characteristics including gestational age at treatment initiation and body mass index would serve as significant moderating factors influencing treatment response magnitude and oxidative stress recovery patterns.\u003c/p\u003e\u003cp\u003eThe primary objective of this prospective observational study was to investigate whether iron supplementation in pregnant women with iron deficiency anemia reduces oxidative stress-related molecular damage as measured by TAS and TOS biomarkers, while characterizing the relationships between conventional iron parameters, advanced iron regulatory molecules, and oxidative stress markers during treatment through comprehensive correlation analyses.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Study Design and Setting\u003c/h2\u003e\u003cp\u003eThis prospective observational study was conducted at the Antenatal Care Service of Haseki Training and Research Hospital, affiliated with the University of Health Sciences, in 2024. The study protocol was approved by the hospital's Human Research Ethics Committee (Registry No: 114\u0026ndash;2021 dated December 8, 2021) and conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent before enrollment.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Participants\u003c/h2\u003e\u003cp\u003ePregnant women attending routine prenatal care were screened for iron deficiency anemia. Inclusion criteria were: (1) singleton pregnancy in first (11\u0026ndash;14 weeks), second (20\u0026ndash;24 weeks), or third trimester (32\u0026ndash;36 weeks); (2) iron deficiency anemia defined as hemoglobin levels below 11.0 g/dL and hematocrit below 33% in first and third trimesters, or hemoglobin below 10.5 g/dL and hematocrit below 32% in second trimester, combined with evidence of iron deficiency (ferritin\u0026thinsp;\u0026lt;\u0026thinsp;15 ng/mL or transferrin saturation\u0026thinsp;\u0026lt;\u0026thinsp;16%); (3) age 18\u0026ndash;45 years.\u003c/p\u003e\u003cp\u003eExclusion criteria included: (1) multiple pregnancy; (2) chronic systemic diseases (hypertension, diabetes, thyroid disorders, rheumatologic diseases); (3) known cardiovascular disease; (4) smoking; (5) anemia due to causes other than iron deficiency; (6) high-risk pregnancy conditions; (7) previous iron supplementation within 1 month.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Sample Size Calculation\u003c/h2\u003e\u003cp\u003eSample size determination was performed using G*Power version 3.1.9.7 software for paired t-test analysis. Based on an effect size (Cohen's dz) of 0.5, alpha error probability of 0.05, and statistical power of 0.90, the analysis indicated that 36 participants would provide adequate power to detect clinically meaningful changes in oxidative stress biomarkers. To account for potential dropout and incomplete data, we targeted enrollment of 40 participants, providing 90.3% actual power for primary analyses.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Intervention\u003c/h2\u003e\u003cp\u003eAll participants received oral iron supplementation consisting of 200 mg elemental iron daily (ferrous sulfate) for one month. Participants were counseled on proper iron administration (taking on empty stomach, avoiding concurrent calcium/tea/coffee consumption) and potential side effects. Adherence was monitored through pill counts and participant interviews.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Data Collection\u003c/h2\u003e\u003cp\u003eBlood samples (5 mL) were collected via venipuncture at baseline and after one month of treatment. Samples were centrifuged at 3000 rpm for 10 minutes, and serum was separated and stored at -80\u0026deg;C until analysis. Complete blood count including hemoglobin, hematocrit, and MCV were analyzed using automated hematology analyzer. Serum iron, total iron binding capacity (TIBC), transferrin saturation, and ferritin were measured using standard laboratory methods, with transferrin saturation calculated as (serum iron/TIBC) \u0026times; 100. Hepcidin and erythroferrone (ERFE) levels were measured using enzyme-linked immunosorbent assay (ELISA) kits according to manufacturer's protocols. TAS and TOS were determined using commercially available colorimetric assay kits. C-reactive protein (CRP) was measured using high-sensitivity immunoturbidimetric assay. Body weight and height were measured using standardized techniques, with body mass index (BMI) calculated as weight (kg)/height (m\u0026sup2;). BMI categories were defined as underweight (\u0026lt;\u0026thinsp;18.5), normal (18.5\u0026ndash;24.9), overweight (25.0-29.9), and obese (\u0026ge;\u0026thinsp;30.0) kg/m\u0026sup2;.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6. Statistical Analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were performed using R software version 4.5.x (R Foundation for Statistical Computing, Vienna, Austria) for primary analyses and Python version 3.11 with matplotlib library for forest plot visualization. IBM SPSS version 28.0 (IBM Corp., Armonk, NY, USA) was used for confirmatory analyses. Descriptive statistics were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation for continuous variables and number (percentage) for categorical variables. Normality was assessed using the Kolmogorov-Smirnov test. Paired t-tests were used to compare pre-treatment and post-treatment values for all biomarkers. Effect sizes were calculated using Cohen's d for paired samples, with 95% confidence intervals computed using the non-central t-distribution method. Effect sizes were interpreted according to established thresholds: small (d\u0026thinsp;=\u0026thinsp;0.2), moderate (d\u0026thinsp;=\u0026thinsp;0.5), large (d\u0026thinsp;=\u0026thinsp;0.8), and very large (d\u0026thinsp;\u0026gt;\u0026thinsp;1.2). Pearson correlation coefficients were calculated to assess relationships between post-treatment biomarker values, with significance levels indicated for p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e\u003cp\u003eSubgroup analyses were performed based on gestational age trimester (first: n\u0026thinsp;=\u0026thinsp;7, second: n\u0026thinsp;=\u0026thinsp;17, third: n\u0026thinsp;=\u0026thinsp;16) and BMI categories (normal weight: n\u0026thinsp;=\u0026thinsp;13, overweight: n\u0026thinsp;=\u0026thinsp;16, obese: n\u0026thinsp;=\u0026thinsp;11) to examine differential treatment responses. Mean changes from baseline were compared across subgroups using analysis of variance (ANOVA) for trend. Forest plots were generated to visualize effect sizes and 95% confidence intervals for all measured parameters, with parameters arranged by effect size magnitude. Scatter plots with means and standard deviations were created to illustrate individual participant responses for key biomarkers. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all analyses.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eA total of 40 pregnant women with iron deficiency anemia completed the full study protocol and provided complete biomarker data sets for both pre-treatment and post-treatment time points. Participants with incomplete laboratory results, missed follow-up appointments, or protocol deviations were excluded from the final analysis to ensure data integrity and statistical validity. All 40 participants demonstrated satisfactory adherence to the iron supplementation regimen and completed the one-month treatment period without significant adverse events requiring study discontinuation. Iron supplementation was well tolerated by all participants. Mild gastrointestinal side effects were reported by 8 participants (20%), including nausea (n\u0026thinsp;=\u0026thinsp;5) and constipation (n\u0026thinsp;=\u0026thinsp;3). No serious adverse events were attributed to iron supplementation. Adherence to therapy was excellent, with 95% of participants taking\u0026thinsp;\u0026ge;\u0026thinsp;80% of prescribed doses.\u003c/p\u003e\u003cp\u003e\u003cb\u003eParticipant Characteristics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBaseline demographic and clinical characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Maternal age demonstrated a broad distribution with a mean of 29.23\u0026thinsp;\u0026plusmn;\u0026thinsp;6.33 years (range: 19\u0026ndash;43 years, median: 29.00 years), indicating representation across the entire reproductive age spectrum. The interquartile range of 25\u0026ndash;33 years suggests that the majority of participants were in their optimal reproductive years. Obstetric history revealed that the majority of participants were experienced mothers, with gravidity averaging 3.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75 pregnancies (range: 1\u0026ndash;7, median: 3.00). The distribution showed that 80.0% were multigravida women, while 20.0% were primigravida. Parity data showed a mean of 1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44 previous deliveries (range: 0\u0026ndash;5, median: 2.00), with 67.5% being parous and 32.5% nulliparous. Gestational age at enrollment showed considerable variation, spanning all trimesters with a mean of 24.35\u0026thinsp;\u0026plusmn;\u0026thinsp;9.68 weeks (range: 6\u0026ndash;37 weeks, median: 26.50 weeks). The interquartile range of 17\u0026ndash;32 weeks indicates that most participants were enrolled during the second and early third trimesters, when iron deficiency anemia commonly becomes clinically apparent. Anthropometric measurements revealed mean body weight of 71.64\u0026thinsp;\u0026plusmn;\u0026thinsp;11.86 kg (range: 50\u0026ndash;95 kg, median: 72.50 kg) and height of 161.35\u0026thinsp;\u0026plusmn;\u0026thinsp;6.10 cm (range: 145\u0026ndash;173 cm, median: 160.00 cm). The calculated BMI averaged 27.56\u0026thinsp;\u0026plusmn;\u0026thinsp;4.75 kg/m\u0026sup2; (range: 18.73\u0026ndash;43.76 kg/m\u0026sup2;), with 32.5% classified as normal weight (18.5\u0026ndash;24.9 kg/m\u0026sup2;), 40.0% as overweight (25.0-29.9 kg/m\u0026sup2;), and 27.5% as obese (\u0026ge;\u0026thinsp;30.0 kg/m\u0026sup2;). This BMI distribution reflects contemporary trends in maternal weight status. Gestational weight gain at enrollment averaged 4.44\u0026thinsp;\u0026plusmn;\u0026thinsp;4.15 kg (range: 0\u0026ndash;15 kg, median: 4 kg), with an interquartile range of 1\u0026ndash;7 kg.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBaseline Demographic and Clinical Characteristics (N\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.23\u0026thinsp;\u0026plusmn;\u0026thinsp;6.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGravidity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e- Primigravida\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (20.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e- Multigravida\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32 (80.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e- Nulliparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (32.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e- Parous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27 (67.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrevious cesarean delivery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (30.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of miscarriage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (37.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGestational age (weeks)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.35\u0026thinsp;\u0026plusmn;\u0026thinsp;9.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.56\u0026thinsp;\u0026plusmn;\u0026thinsp;4.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI Categories\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e- Normal (18.5\u0026ndash;24.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (32.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e- Overweight (25.0-29.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (40.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e- Obese (\u0026ge;\u0026thinsp;30.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (27.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGestational weight gain (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.47\u0026thinsp;\u0026plusmn;\u0026thinsp;4.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eContinuous variables are presented as \u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003emean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation; categorical variables \u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eare presented as frequency (percentage). BMI, body mass index\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eHematologic Response to Iron Supplementation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIron supplementation resulted in significant improvements in all hematologic parameters (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Hemoglobin levels increased from 10.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72 g/dL at baseline to 11.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97 g/dL after treatment (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d\u0026thinsp;=\u0026thinsp;1.76), representing a mean difference of 1.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98 g/dL (95% CI: 1.20\u0026ndash;1.81). Similarly, hematocrit improved from 30.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79% to 35.24\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d\u0026thinsp;=\u0026thinsp;1.74), with a mean increase of 4.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98 percentage points (95% CI: 3.39\u0026ndash;5.23). MCV increased from 82.28\u0026thinsp;\u0026plusmn;\u0026thinsp;8.11 fL to 87.98\u0026thinsp;\u0026plusmn;\u0026thinsp;23.35 fL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d\u0026thinsp;=\u0026thinsp;0.33), with a mean difference of 5.71\u0026thinsp;\u0026plusmn;\u0026thinsp;26.60 fL (95% CI: -2.54-13.95). Serum iron levels showed substantial improvement from 49.88\u0026thinsp;\u0026plusmn;\u0026thinsp;28.23 \u0026micro;g/dL to 78.67\u0026thinsp;\u0026plusmn;\u0026thinsp;43.71 \u0026micro;g/dL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d\u0026thinsp;=\u0026thinsp;0.78), with a mean increase of 28.80\u0026thinsp;\u0026plusmn;\u0026thinsp;42.41 \u0026micro;g/dL (95% CI: 15.66\u0026ndash;41.94). TIBC decreased from 424.43\u0026thinsp;\u0026plusmn;\u0026thinsp;109.09 \u0026micro;g/dL to 344.65\u0026thinsp;\u0026plusmn;\u0026thinsp;89.24 \u0026micro;g/dL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d = -0.80), with a mean reduction of 79.78\u0026thinsp;\u0026plusmn;\u0026thinsp;132.66 \u0026micro;g/dL (95% CI: -120.89 to -38.66). Transferrin saturation increased from 11.03\u0026thinsp;\u0026plusmn;\u0026thinsp;7.32% to 19.79\u0026thinsp;\u0026plusmn;\u0026thinsp;10.42% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d\u0026thinsp;=\u0026thinsp;0.97), with a mean increase of 8.76\u0026thinsp;\u0026plusmn;\u0026thinsp;10.53 percentage points (95% CI: 5.50-12.02). Ferritin levels increased from 13.60\u0026thinsp;\u0026plusmn;\u0026thinsp;9.34 ng/mL to 34.27\u0026thinsp;\u0026plusmn;\u0026thinsp;34.60 ng/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d\u0026thinsp;=\u0026thinsp;0.82), with a mean difference of 20.68\u0026thinsp;\u0026plusmn;\u0026thinsp;34.43 ng/mL (95% CI: 10.01\u0026ndash;31.35).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHematologic Parameters Before and After Iron Supplementation\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBefore Treatment\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAfter Treatment\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean Difference\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eCohen's d\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.20\u0026ndash;1.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHematocrit (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35.24\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.39\u0026ndash;5.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCV (fL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e82.28\u0026thinsp;\u0026plusmn;\u0026thinsp;8.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87.98\u0026thinsp;\u0026plusmn;\u0026thinsp;23.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.71\u0026thinsp;\u0026plusmn;\u0026thinsp;26.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.54-13.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIron (\u0026micro;g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49.88\u0026thinsp;\u0026plusmn;\u0026thinsp;28.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.67\u0026thinsp;\u0026plusmn;\u0026thinsp;43.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.80\u0026thinsp;\u0026plusmn;\u0026thinsp;42.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.66\u0026ndash;41.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTIBC (\u0026micro;g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e424.43\u0026thinsp;\u0026plusmn;\u0026thinsp;109.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e344.65\u0026thinsp;\u0026plusmn;\u0026thinsp;89.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-79.78\u0026thinsp;\u0026plusmn;\u0026thinsp;132.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-120.89-(-38.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-0.80\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransferrin Saturation (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.03\u0026thinsp;\u0026plusmn;\u0026thinsp;7.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.79\u0026thinsp;\u0026plusmn;\u0026thinsp;10.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.76\u0026thinsp;\u0026plusmn;\u0026thinsp;10.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.50-12.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFerritin (ng/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.60\u0026thinsp;\u0026plusmn;\u0026thinsp;9.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.27\u0026thinsp;\u0026plusmn;\u0026thinsp;34.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.68\u0026thinsp;\u0026plusmn;\u0026thinsp;34.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.01\u0026ndash;31.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation for before and after treatment values and mean difference. Effect sizes are reported as Cohen's d. MCV, mean corpuscular volume; TIBC, total iron binding capacity; CI, confidence interval\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eIron Metabolism Biomarkers\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAdvanced iron metabolism biomarkers showed significant changes following supplementation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Hepcidin levels increased from 2214.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1444.27 pg/mL to 3492.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1640.51 pg/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Cohen's d\u0026thinsp;=\u0026thinsp;0.83), with a mean increase of 1278.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1787.20 pg/mL (95% CI: 724.17-1831.89). ERFE concentrations exhibited a statistically significant reduction from baseline values of 470.75\u0026thinsp;\u0026plusmn;\u0026thinsp;170.75 pg/mL to post-treatment levels of 345.25\u0026thinsp;\u0026plusmn;\u0026thinsp;112.96 pg/mL, representing a mean decrease of 125.50\u0026thinsp;\u0026plusmn;\u0026thinsp;158.26 pg/mL (95% CI: 76.46-174.54, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d\u0026thinsp;=\u0026thinsp;0.87).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eOxidative Stress Parameters\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIron supplementation resulted in dramatic improvements in oxidative stress biomarkers (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). TAS increased substantially from 0.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36 mmol/L to 1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37 mmol/L (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d\u0026thinsp;=\u0026thinsp;1.87), with a mean difference of 0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36 mmol/L (95% CI: 0.56\u0026ndash;0.79). This represents a very large effect size, indicating clinically significant improvement in systemic antioxidant capacity. TOS decreased significantly from 12.19\u0026thinsp;\u0026plusmn;\u0026thinsp;11.20 \u0026micro;mol/L to 6.53\u0026thinsp;\u0026plusmn;\u0026thinsp;5.42 \u0026micro;mol/L (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d = -0.64), with a mean reduction of 5.66\u0026thinsp;\u0026plusmn;\u0026thinsp;9.25 \u0026micro;mol/L (95% CI: -8.61 to -2.70). The TOS/TAS ratio, representing oxidative stress index, decreased dramatically from 14.53\u0026thinsp;\u0026plusmn;\u0026thinsp;15.98 to 4.10\u0026thinsp;\u0026plusmn;\u0026thinsp;3.14 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d = -0.91), with a mean difference of -10.43\u0026thinsp;\u0026plusmn;\u0026thinsp;11.96 (95% CI: -14.25 to -6.61). CRP levels decreased significantly from 6.67\u0026thinsp;\u0026plusmn;\u0026thinsp;5.96 mg/L to 2.92\u0026thinsp;\u0026plusmn;\u0026thinsp;2.70 mg/L (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cohen's d = -0.81), with a mean reduction of 3.75\u0026thinsp;\u0026plusmn;\u0026thinsp;4.11 mg/L (95% CI: -5.02 to -2.47).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eIron Metabolism and Oxidative Stress Biomarkers\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBiomarker\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBefore Treatment\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAfter Treatment\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean Difference\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eCohen's d\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTAS (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.56\u0026ndash;0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTOS (\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.19\u0026thinsp;\u0026plusmn;\u0026thinsp;11.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.53\u0026thinsp;\u0026plusmn;\u0026thinsp;5.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-5.66\u0026thinsp;\u0026plusmn;\u0026thinsp;9.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-8.61 to -2.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-0.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTOS/TAS Ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.53\u0026thinsp;\u0026plusmn;\u0026thinsp;15.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.10\u0026thinsp;\u0026plusmn;\u0026thinsp;3.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-10.43\u0026thinsp;\u0026plusmn;\u0026thinsp;11.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-14.25 to -6.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-0.91\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP (mg/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.67\u0026thinsp;\u0026plusmn;\u0026thinsp;5.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.92\u0026thinsp;\u0026plusmn;\u0026thinsp;2.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-3.75\u0026thinsp;\u0026plusmn;\u0026thinsp;4.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-5.02-(-2.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-0.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eTAS, total antioxidant status; TOS, total oxidant status; CRP, C-reactive protein; CI, confidence interval\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCorrelation Analyses\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePearson correlation analysis was performed to examine relationships between hematologic parameters, iron metabolism biomarkers, and oxidative stress markers (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Among hematologic parameters, hemoglobin and hematocrit showed a very strong positive correlation (r\u0026thinsp;=\u0026thinsp;0.97, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Iron levels demonstrated a very strong positive correlation with transferrin saturation (r\u0026thinsp;=\u0026thinsp;0.92, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and a moderate negative correlation with TIBC (r = -0.48, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). TIBC showed significant negative correlations with transferrin saturation (r = -0.72, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and ferritin (r = -0.37, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eRegarding iron metabolism biomarkers, a significant moderate positive correlation was observed between ferritin and hepcidin (r\u0026thinsp;=\u0026thinsp;0.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting coordinated regulation of iron metabolism. ERFE showed weak correlations with most parameters.\u003c/p\u003e\u003cp\u003eFor oxidative stress markers, important findings emerged: TAS showed minimal correlations with iron parameters (all |r| \u0026lt; 0.25), indicating that antioxidant capacity improvements operate largely independently of traditional iron biomarkers. TOS demonstrated significant negative correlations with hemoglobin (r = -0.36, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and hematocrit (r = -0.31, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting that higher oxidant burden is associated with more severe anemia. The correlation between TAS and TOS was weak and non-significant (r\u0026thinsp;=\u0026thinsp;0.08, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating these represent independent aspects of oxidative status.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation Matrix of All Biomarkers (Post-Treatment Values).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"14\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHb\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHct\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMCV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFe\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTIBC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eFerritin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eHepcidin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eERFE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eTAS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTOS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eTOS/TAS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003eCRP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHb\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.97***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.44**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.40*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-0.36*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-0.32*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHct\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" 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colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e-0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTOS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.95***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e-0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTOS/TAS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCRP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"14\" nameend=\"c14\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHb, hemoglobin; Hct, hematocrit; MCV, mean corpuscular volume; Fe, iron; TIBC, total iron binding capacity; TS, transferrin saturation; TAS, total antioxidant status; TOS, total oxidant status; CRP, C-reactive protein. *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTrimester-Based Analysis of Treatment Response\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSubgroup analyses based on gestational age revealed differential responses to iron supplementation across various parameters (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Women in the first trimester (n\u0026thinsp;=\u0026thinsp;7) showed greater improvements in iron absorption parameters compared to those in later trimesters, with serum iron increases of 50.00\u0026thinsp;\u0026plusmn;\u0026thinsp;52.54 \u0026micro;g/dL versus 30.05\u0026thinsp;\u0026plusmn;\u0026thinsp;48.30 \u0026micro;g/dL in second trimester (n\u0026thinsp;=\u0026thinsp;17) and 20.69\u0026thinsp;\u0026plusmn;\u0026thinsp;30.31 \u0026micro;g/dL in third trimester (n\u0026thinsp;=\u0026thinsp;16) participants (p\u0026thinsp;=\u0026thinsp;0.337 for trend). Transferrin saturation similarly showed larger increases in first trimester (13.46\u0026thinsp;\u0026plusmn;\u0026thinsp;15.45%) compared to second (8.38\u0026thinsp;\u0026plusmn;\u0026thinsp;10.71%) and third (7.74\u0026thinsp;\u0026plusmn;\u0026thinsp;8.85%) trimesters (p\u0026thinsp;=\u0026thinsp;0.449).\u003c/p\u003e\u003cp\u003eFerritin response demonstrated an opposite pattern, with progressively larger increases observed with advancing gestational age: 8.12\u0026thinsp;\u0026plusmn;\u0026thinsp;29.68 ng/mL in first trimester, 15.87\u0026thinsp;\u0026plusmn;\u0026thinsp;24.72 ng/mL in second trimester, and 30.31\u0026thinsp;\u0026plusmn;\u0026thinsp;43.96 ng/mL in third trimester (p\u0026thinsp;=\u0026thinsp;0.283). Similarly, hepcidin increases were more pronounced in later trimesters: 552.78\u0026thinsp;\u0026plusmn;\u0026thinsp;2662.45 pg/mL in first trimester, 1246.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1653.73 pg/mL in second trimester, and 1541.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1697.60 pg/mL in third trimester (p\u0026thinsp;=\u0026thinsp;0.448).\u003c/p\u003e\u003cp\u003eERFE showed substantial decreases across all trimesters, with the largest reductions observed in the second trimester (-163.68\u0026thinsp;\u0026plusmn;\u0026thinsp;191.38 pg/mL) compared to first (-32.00\u0026thinsp;\u0026plusmn;\u0026thinsp;83.19 pg/mL) and third (-109.38\u0026thinsp;\u0026plusmn;\u0026thinsp;119.53 pg/mL) trimesters (p\u0026thinsp;=\u0026thinsp;0.213).\u003c/p\u003e\u003cp\u003eRegarding oxidative stress parameters, all trimesters demonstrated substantial improvements in TAS, with second trimester participants showing the most pronounced increases (0.752\u0026thinsp;\u0026plusmn;\u0026thinsp;0.428 mmol/L) compared to first trimester (0.534\u0026thinsp;\u0026plusmn;\u0026thinsp;0.495 mmol/L) and third trimester (0.672\u0026thinsp;\u0026plusmn;\u0026thinsp;0.265 mmol/L) participants (p\u0026thinsp;=\u0026thinsp;0.424). TOS showed progressive reductions with advancing gestational age, with third trimester participants demonstrating the largest decreases (-7.76\u0026thinsp;\u0026plusmn;\u0026thinsp;12.07 \u0026micro;mol/L) compared to second trimester (-5.47\u0026thinsp;\u0026plusmn;\u0026thinsp;6.71 \u0026micro;mol/L) and first trimester (-1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;6.15 \u0026micro;mol/L) participants (p\u0026thinsp;=\u0026thinsp;0.289). The TOS/TAS ratio, representing oxidative stress index, showed substantial reductions across all trimesters, with the most pronounced decreases observed in third trimester (-12.90\u0026thinsp;\u0026plusmn;\u0026thinsp;18.98) and second trimester (-10.60\u0026thinsp;\u0026plusmn;\u0026thinsp;12.30) compared to first trimester (-4.34\u0026thinsp;\u0026plusmn;\u0026thinsp;4.47) participants (p\u0026thinsp;=\u0026thinsp;0.198). Notably, all trimester groups achieved clinically meaningful oxidative stress improvements with large effect sizes, indicating that iron supplementation provides significant antioxidant benefits regardless of gestational age at initiation. CRP reductions were most substantial in the second trimester (-4.71\u0026thinsp;\u0026plusmn;\u0026thinsp;4.73 mg/L) compared to first trimester (-4.47\u0026thinsp;\u0026plusmn;\u0026thinsp;4.99 mg/L) and third trimester (-2.41\u0026thinsp;\u0026plusmn;\u0026thinsp;2.63 mg/L) participants (p\u0026thinsp;=\u0026thinsp;0.203).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTreatment Response by Trimester\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirst Trimester (n\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSecond Trimester (n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThird Trimester (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.283\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIron (\u0026micro;g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50.00\u0026thinsp;\u0026plusmn;\u0026thinsp;52.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.05\u0026thinsp;\u0026plusmn;\u0026thinsp;48.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.69\u0026thinsp;\u0026plusmn;\u0026thinsp;30.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.337\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTIBC (\u0026micro;g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-59.60\u0026thinsp;\u0026plusmn;\u0026thinsp;114.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-51.05\u0026thinsp;\u0026plusmn;\u0026thinsp;112.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-120.19\u0026thinsp;\u0026plusmn;\u0026thinsp;155.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.261\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransferrin Saturation (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.46\u0026thinsp;\u0026plusmn;\u0026thinsp;15.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.38\u0026thinsp;\u0026plusmn;\u0026thinsp;10.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.74\u0026thinsp;\u0026plusmn;\u0026thinsp;8.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.449\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFerritin (ng/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.12\u0026thinsp;\u0026plusmn;\u0026thinsp;29.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.87\u0026thinsp;\u0026plusmn;\u0026thinsp;24.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.31\u0026thinsp;\u0026plusmn;\u0026thinsp;43.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.283\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHepcidin (pg/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e552.78\u0026thinsp;\u0026plusmn;\u0026thinsp;2662.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1246.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1653.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1541.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1697.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.448\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eERFE (pg/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-32.00\u0026thinsp;\u0026plusmn;\u0026thinsp;83.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-163.68\u0026thinsp;\u0026plusmn;\u0026thinsp;191.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-109.38\u0026thinsp;\u0026plusmn;\u0026thinsp;119.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.213\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTAS (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.534\u0026thinsp;\u0026plusmn;\u0026thinsp;0.495\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.752\u0026thinsp;\u0026plusmn;\u0026thinsp;0.428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.672\u0026thinsp;\u0026plusmn;\u0026thinsp;0.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.424\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTOS (\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;6.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-5.47\u0026thinsp;\u0026plusmn;\u0026thinsp;6.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-7.76\u0026thinsp;\u0026plusmn;\u0026thinsp;12.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.289\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTOS/TAS Ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-4.34\u0026thinsp;\u0026plusmn;\u0026thinsp;4.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-10.60\u0026thinsp;\u0026plusmn;\u0026thinsp;12.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-12.90\u0026thinsp;\u0026plusmn;\u0026thinsp;18.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.198\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP (mg/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-4.47\u0026thinsp;\u0026plusmn;\u0026thinsp;4.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-4.71\u0026thinsp;\u0026plusmn;\u0026thinsp;4.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-2.41\u0026thinsp;\u0026plusmn;\u0026thinsp;2.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.203\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eData are presented as mean change\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Positive values indicate increases; negative values indicate decreases. TIBC, total iron binding capacity; TAS, total antioxidant status; TOS, total oxidant status; CRP, C-reactive protein.\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eBMI-Based Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBMI categories showed differential associations with treatment response across multiple parameters (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). For iron metabolism markers, normal weight women demonstrated substantially greater improvements in serum iron (49.46\u0026thinsp;\u0026plusmn;\u0026thinsp;59.81 \u0026micro;g/dL) compared to overweight (26.88\u0026thinsp;\u0026plusmn;\u0026thinsp;29.57 \u0026micro;g/dL) and obese (7.18\u0026thinsp;\u0026plusmn;\u0026thinsp;18.32 \u0026micro;g/dL) participants (p\u0026thinsp;=\u0026thinsp;0.067 for trend). A similar pattern was observed for transferrin saturation, with progressively smaller increases as BMI increased: normal weight (12.63\u0026thinsp;\u0026plusmn;\u0026thinsp;13.85%), overweight (8.81\u0026thinsp;\u0026plusmn;\u0026thinsp;9.86%), and obese (4.11\u0026thinsp;\u0026plusmn;\u0026thinsp;3.61%) participants (p\u0026thinsp;=\u0026thinsp;0.152).\u003c/p\u003e\u003cp\u003eFerritin increases were highest in overweight women (24.54\u0026thinsp;\u0026plusmn;\u0026thinsp;44.39 ng/mL) compared to obese (19.84\u0026thinsp;\u0026plusmn;\u0026thinsp;23.73 ng/mL) and normal weight (16.63\u0026thinsp;\u0026plusmn;\u0026thinsp;29.69 ng/mL) participants (p\u0026thinsp;=\u0026thinsp;0.666). Hepcidin levels showed the greatest increase in overweight women (1419.80\u0026thinsp;\u0026plusmn;\u0026thinsp;1961.62 pg/mL) compared to obese (1319.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1348.11 pg/mL) and normal weight (1068.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1995.07 pg/mL) participants (p\u0026thinsp;=\u0026thinsp;0.712).\u003c/p\u003e\u003cp\u003eERFE reductions were most pronounced in overweight women (-145.00\u0026thinsp;\u0026plusmn;\u0026thinsp;124.47 pg/mL) compared to normal weight (-117.69\u0026thinsp;\u0026plusmn;\u0026thinsp;152.65 pg/mL) and obese (-106.36\u0026thinsp;\u0026plusmn;\u0026thinsp;213.04 pg/mL) participants (p\u0026thinsp;=\u0026thinsp;0.648).\u003c/p\u003e\u003cp\u003eFor oxidative stress parameters, normal weight women demonstrated the greatest improvements in TAS (0.765\u0026thinsp;\u0026plusmn;\u0026thinsp;0.486 mmol/L) compared to overweight (0.691\u0026thinsp;\u0026plusmn;\u0026thinsp;0.286 mmol/L) and obese (0.573\u0026thinsp;\u0026plusmn;\u0026thinsp;0.375 mmol/L) participants (p\u0026thinsp;=\u0026thinsp;0.198). Interestingly, overweight women showed the largest reductions in TOS (-8.31\u0026thinsp;\u0026plusmn;\u0026thinsp;10.26 \u0026micro;mol/L) compared to obese (-5.83\u0026thinsp;\u0026plusmn;\u0026thinsp;10.15 \u0026micro;mol/L) and normal weight (-2.24\u0026thinsp;\u0026plusmn;\u0026thinsp;6.20 \u0026micro;mol/L) participants (p\u0026thinsp;=\u0026thinsp;0.145). The TOS/TAS ratio showed substantial decreases across all BMI groups, with overweight (-12.33\u0026thinsp;\u0026plusmn;\u0026thinsp;14.76) and obese (-12.32\u0026thinsp;\u0026plusmn;\u0026thinsp;20.17) women demonstrating larger reductions compared to normal weight (-6.48\u0026thinsp;\u0026plusmn;\u0026thinsp;7.45) participants (p\u0026thinsp;=\u0026thinsp;0.312). This pattern suggests that while higher BMI may slightly attenuate antioxidant capacity improvements, it does not prevent significant oxidant burden reduction and oxidative stress index improvement. Nevertheless, all BMI groups achieved substantial oxidative stress improvements with large effect sizes, indicating significant antioxidant benefits regardless of maternal weight status. CRP reductions were most substantial in obese women (-4.71\u0026thinsp;\u0026plusmn;\u0026thinsp;3.93 mg/L) compared to normal weight (-3.92\u0026thinsp;\u0026plusmn;\u0026thinsp;5.56 mg/L) and overweight (-2.94\u0026thinsp;\u0026plusmn;\u0026thinsp;2.75 mg/L) participants (p\u0026thinsp;=\u0026thinsp;0.435).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTreatment Response by BMI Category\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal Weight (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOverweight (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eObese (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.826\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIron (\u0026micro;g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49.46\u0026thinsp;\u0026plusmn;\u0026thinsp;59.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.88\u0026thinsp;\u0026plusmn;\u0026thinsp;29.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.18\u0026thinsp;\u0026plusmn;\u0026thinsp;18.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTIBC (\u0026micro;g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-71.39\u0026thinsp;\u0026plusmn;\u0026thinsp;114.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-93.88\u0026thinsp;\u0026plusmn;\u0026thinsp;137.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-69.18\u0026thinsp;\u0026plusmn;\u0026thinsp;154.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.704\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransferrin Saturation (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.63\u0026thinsp;\u0026plusmn;\u0026thinsp;13.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.81\u0026thinsp;\u0026plusmn;\u0026thinsp;9.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.11\u0026thinsp;\u0026plusmn;\u0026thinsp;3.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.152\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFerritin (ng/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.63\u0026thinsp;\u0026plusmn;\u0026thinsp;29.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.54\u0026thinsp;\u0026plusmn;\u0026thinsp;44.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.84\u0026thinsp;\u0026plusmn;\u0026thinsp;23.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.666\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHepcidin (pg/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1068.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1995.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1419.80\u0026thinsp;\u0026plusmn;\u0026thinsp;1961.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1319.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1348.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.712\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eERFE (pg/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-117.69\u0026thinsp;\u0026plusmn;\u0026thinsp;152.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-145.00\u0026thinsp;\u0026plusmn;\u0026thinsp;124.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-106.36\u0026thinsp;\u0026plusmn;\u0026thinsp;213.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.648\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTAS (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.765\u0026thinsp;\u0026plusmn;\u0026thinsp;0.486\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.691\u0026thinsp;\u0026plusmn;\u0026thinsp;0.286\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.573\u0026thinsp;\u0026plusmn;\u0026thinsp;0.375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.198\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTOS (\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.24\u0026thinsp;\u0026plusmn;\u0026thinsp;6.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-8.31\u0026thinsp;\u0026plusmn;\u0026thinsp;10.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-5.83\u0026thinsp;\u0026plusmn;\u0026thinsp;10.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.145\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTOS/TAS Ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-6.48\u0026thinsp;\u0026plusmn;\u0026thinsp;7.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-12.33\u0026thinsp;\u0026plusmn;\u0026thinsp;14.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-12.32\u0026thinsp;\u0026plusmn;\u0026thinsp;20.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.312\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP (mg/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-3.92\u0026thinsp;\u0026plusmn;\u0026thinsp;5.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.94\u0026thinsp;\u0026plusmn;\u0026thinsp;2.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-4.71\u0026thinsp;\u0026plusmn;\u0026thinsp;3.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.435\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eData are presented as mean change\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Positive values indicate increases; negative values indicate decreases. BMI categories: Normal weight (18.5\u0026ndash;24.9 kg/m\u0026sup2;), Overweight (25.0-29.9 kg/m\u0026sup2;), Obese (\u0026ge;\u0026thinsp;30.0 kg/m\u0026sup2;). TIBC, total iron binding capacity; TAS, total antioxidant status; TOS, total oxidant status; CRP, C-reactive protein.\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eForest Plot Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA comprehensive Forest plot analysis was conducted to visualize and compare the effect sizes of iron supplementation on various hematological, iron metabolism, and oxidative stress parameters (Fig.\u0026nbsp;2). Cohen's d effect sizes with 95% confidence intervals were calculated for all measured parameters to determine the magnitude and clinical significance of treatment effects. Negative effect sizes indicate parameter reductions, while positive values indicate increases following treatment.\u003c/p\u003e\u003cp\u003eThe analysis revealed that the most substantial treatment effects were observed in oxidative stress and hematological parameters. TAS demonstrated the largest effect size among all biomarkers (d\u0026thinsp;=\u0026thinsp;1.87, 95% CI: 1.34\u0026ndash;2.40), indicating a very large improvement in systemic antioxidant capacity. This was followed closely by hemoglobin (d\u0026thinsp;=\u0026thinsp;1.76, 95% CI: 1.24\u0026ndash;2.28) and hematocrit (d\u0026thinsp;=\u0026thinsp;1.74, 95% CI: 1.22\u0026ndash;2.26), both showing very large effects that confirm the robust efficacy of iron supplementation in correcting anemia.\u003c/p\u003e\u003cp\u003eAmong iron metabolism markers, transferrin saturation showed a large positive effect (d\u0026thinsp;=\u0026thinsp;0.97, 95% CI: 0.51\u0026ndash;1.43), while TIBC demonstrated a large negative effect (d = -0.80, 95% CI: -1.26 to -0.34), reflecting the physiological response to improved iron status. Serum iron levels showed a moderate-to-large improvement (d\u0026thinsp;=\u0026thinsp;0.78, 95% CI: 0.32\u0026ndash;1.24), while MCV showed a small but statistically significant increase (d\u0026thinsp;=\u0026thinsp;0.33, 95% CI: -0.11-0.77).\u003c/p\u003e\u003cp\u003eThe advanced iron regulatory hormones exhibited significant changes: hepcidin levels increased substantially (d\u0026thinsp;=\u0026thinsp;0.83, 95% CI: 0.37\u0026ndash;1.29), while ERFE showed a large decrease (d = -0.87, 95% CI: -1.33 to -0.41), consistent with the expected physiological response to iron repletion. Ferritin levels also showed a large increase (d\u0026thinsp;=\u0026thinsp;0.82, 95% CI: 0.36\u0026ndash;1.28), confirming successful iron store replenishment.\u003c/p\u003e\u003cp\u003eRegarding inflammatory and oxidative stress markers, the TOS/TAS ratio demonstrated a large negative effect (d = -0.91, 95% CI: -1.37 to -0.45), indicating substantial improvement in oxidative balance. TOS showed a moderate negative effect (d = -0.64, 95% CI: -1.09 to -0.19), while CRP exhibited a large reduction (d = -0.81, 95% CI: -1.27 to -0.35), suggesting significant anti-inflammatory effects of iron supplementation.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis prospective observational study demonstrated that one month of oral iron supplementation in pregnant women with iron deficiency anemia resulted in substantial improvements across multiple physiological domains. The most striking finding was the very large effect size observed for TAS improvement (Cohen's d\u0026thinsp;=\u0026thinsp;1.87), which exceeded even the robust hematological improvements in hemoglobin (d\u0026thinsp;=\u0026thinsp;1.76) and hematocrit (d\u0026thinsp;=\u0026thinsp;1.74). Iron supplementation significantly reduced oxidative stress burden, as evidenced by decreased TOS (d = -0.64) and a marked reduction in the TOS/TAS ratio (d = -0.91), while simultaneously improving iron stores with increased ferritin (d\u0026thinsp;=\u0026thinsp;0.82) and transferrin saturation (d\u0026thinsp;=\u0026thinsp;0.97). The iron regulatory hormones showed expected physiological responses, with hepcidin levels increasing substantially (d\u0026thinsp;=\u0026thinsp;0.83) and ERFE decreasing (d = -0.87), reflecting successful iron repletion and reduced erythropoietic drive.\u003c/p\u003e\u003cp\u003eNotably, correlation analyses revealed that TAS improvements occurred largely independently of traditional iron parameters (all |r| \u0026lt; 0.25), suggesting that the antioxidant benefits of iron supplementation operate through mechanisms beyond simple correction of iron deficiency. Subgroup analyses demonstrated differential treatment responses based on maternal characteristics, with first trimester participants showing superior iron absorption parameters but third trimester participants achieving greater ferritin accumulation and oxidative stress reduction. Body mass index influenced treatment response patterns, with normal weight women demonstrating better iron absorption and antioxidant capacity improvements, while overweight and obese women showed paradoxically larger reductions in the TOS/TAS ratio despite attenuated TAS increases.\u003c/p\u003e\u003cp\u003eRecent investigations into iron metabolism during pregnancy provide important context for interpreting our findings. Fisher et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] documented hepcidin kinetics in iron-supplemented pregnant women that closely mirror our observations, with levels stabilizing within physiological ranges despite therapeutic doses. Their work primarily focused on hematological outcomes, yet the consistency with our hormone data strengthens the evidence for preserved iron homeostasis during supplementation. The elegant demonstration by Sangkhae et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] of the inverse relationship between iron availability and ERFE production offers mechanistic support for our findings. Using both human subjects and mouse models, they showed ERFE suppression occurs rapidly once iron sufficiency is restored\u0026mdash;a timeline consistent with our one-month intervention. This coordinated hormonal response suggests that pregnancy maintains sophisticated iron regulatory mechanisms despite increased physiological demands, and that supplementation works within, rather than overwhelming, these natural control systems.\u003c/p\u003e\u003cp\u003eThe oxidative stress improvements we observed carry particular significance given accumulating evidence linking oxidative damage to adverse pregnancy outcomes. Shastri et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] reported elevated lipid peroxidation and protein carbonylation in iron-deficient pregnant women, though their cross-sectional design prevented conclusions about reversibility. Our prospective data definitively demonstrate that these oxidative changes can be reversed\u0026mdash;and dramatically so. The magnitude of improvement surpasses previous reports, possibly reflecting our higher supplementation dose or more comprehensive biomarker assessment. The theoretical framework proposed by Cao \u0026amp; O'Brien [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], linking iron deficiency to preeclampsia through oxidative mechanisms, gains strong support from our findings. They described a \"perfect storm\" scenario where iron deficiency simultaneously increases ROS production and compromises antioxidant defenses\u0026mdash;exactly what our TAS and TOS measurements confirm and show can be reversed with appropriate treatment.\u003c/p\u003e\u003cp\u003eTrimester-specific variations in treatment response revealed unexpected complexity in iron metabolism across pregnancy. Early screening recommendations by Milman et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] were based primarily on hematological considerations, but our data paint a more nuanced picture of evolving physiological priorities. First trimester women absorbed iron most efficiently, with serum levels increasing by 50.00\u0026thinsp;\u0026plusmn;\u0026thinsp;52.54 \u0026micro;g/dL compared to only 20.69\u0026thinsp;\u0026plusmn;\u0026thinsp;30.31 \u0026micro;g/dL in the third trimester, yet paradoxically, later pregnancy showed superior ferritin accumulation and oxidative stress reduction. This pattern suggests early gestation prioritizes immediate iron utilization for maternal blood volume expansion, while later pregnancy emphasizes storage and antioxidant defense\u0026mdash;possibly in preparation for delivery blood loss and postpartum recovery. Dewey \u0026amp; Oaks [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] theoretical discussion of \"critical windows\" for supplementation gains empirical support from these findings, though they lacked the biochemical data we now provide. The clinical implication is clear: while early supplementation optimizes iron absorption, treatment at any gestational age provides meaningful benefits, particularly for oxidative stress reduction.\u003c/p\u003e\u003cp\u003eThe influence of maternal BMI on treatment response challenges conventional assumptions and reveals the complexity of iron metabolism in obesity. Normal weight women showed superior iron absorption, consistent with Cepeda-Lopez et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] documentation of obesity-related malabsorption, yet the oxidative stress story proved more complex. Overweight and obese women achieved larger reductions in the TOS/TAS ratio despite smaller absolute TAS increases\u0026mdash;a paradox that likely reflects their higher baseline oxidative burden. Khambalia et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] recommended adjusted supplementation protocols for obese pregnant women based solely on achieving target hemoglobin levels, but our findings suggest standard dosing adequately addresses oxidative stress even when hematological responses are attenuated. This has important clinical implications given the increasing prevalence of maternal obesity: the antioxidant benefits of iron supplementation extend across all BMI categories, though the mechanisms may differ. The greater baseline oxidative stress in heavier women means relative improvements appear more dramatic, while their persistent mild inflammation (evidenced by higher baseline CRP) may actually enhance the anti-inflammatory benefits of iron repletion.\u003c/p\u003e\u003cp\u003eRecent mechanistic studies illuminate the molecular underpinnings of our observations and suggest why oxidative stress improvements occurred independently of iron parameter changes. Frazer \u0026amp; Anderson [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] identified over 300 iron-dependent proteins involved in oxidative stress response, extending far beyond the classical antioxidant enzymes. This vast network explains our rapid TAS improvement within one month\u0026mdash;these enzymes quickly recover function once iron becomes available. Gambling et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] demonstrated restored mitochondrial complex activity within two weeks of supplementation, providing a timeline consistent with our findings. However, the weak correlation between TAS and iron parameters implies additional mechanisms at play. Erber et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] transcriptomic analysis offers an intriguing possibility: iron deficiency altered expression of numerous non-iron-dependent antioxidant genes, possibly as maladaptive compensation. Supplementation might work partially by removing the stimulus for this compensation, allowing normal antioxidant gene expression patterns to resume. The transgenerational implications become even more significant considering Sangkhae et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] demonstration that maternal iron status influences fetal antioxidant enzyme expression through epigenetic modifications. While we didn't assess fetal outcomes, this finding amplifies the importance of achieving maternal oxidative balance for offspring health.\u003c/p\u003e\u003cp\u003eThe clinical significance of our findings gains support from population-based studies linking oxidative stress to pregnancy complications. Ferguson et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] meta-analysis found oxidative stress biomarkers predicted adverse outcomes with odds ratios of 2.5\u0026ndash;3.2, effect sizes matching the magnitude of improvement we achieved. The inflammatory component adds another dimension, with our significant CRP reduction (d = -0.81) suggesting iron supplementation breaks what Burton \u0026amp; Jauniaux [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] termed \"oxidative-inflammatory spirals\" in pregnancy complications. The rapid timeline\u0026mdash;substantial improvements within one month\u0026mdash;challenges the notion that late-presenting patients are \"too late\" for meaningful intervention. Even women diagnosed with iron deficiency in the third trimester can achieve significant oxidative stress reduction, potentially preventing late-pregnancy complications traditionally attributed to chronic iron deficiency.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStrengths and Limitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study possesses several methodological strengths that enhance the validity and clinical applicability of our findings. The prospective design with complete pre- and post-treatment biomarker assessments in all 40 participants eliminated selection bias and ensured data integrity. The comprehensive biomarker panel, including advanced iron regulatory hormones (hepcidin, ERFE) and validated oxidative stress markers (TAS, TOS), provided mechanistic insights unavailable in previous studies relying solely on hematological parameters. The excellent treatment adherence (95% taking\u0026thinsp;\u0026ge;\u0026thinsp;80% of prescribed doses) and low adverse event rate demonstrate the feasibility of the supplementation protocol in routine clinical practice. The inclusion of participants across all trimesters and BMI categories enhances generalizability to diverse pregnant populations. The use of standardized effect size calculations with 95% confidence intervals facilitates comparison with future studies and potential meta-analytic inclusion.\u003c/p\u003e\u003cp\u003eSeveral limitations warrant consideration when interpreting our findings. The single-arm observational design without a placebo control group limits causal inferences about iron supplementation effects, although the large effect sizes and consistency across multiple biomarkers suggest true treatment benefits rather than regression to the mean or placebo effects. The relatively small sample size, particularly in trimester-based subgroups, may have limited statistical power to detect smaller but clinically meaningful differences. The single-center setting in Istanbul may limit generalizability to other populations with different dietary patterns, genetic backgrounds, or environmental exposures. The one-month treatment duration, while sufficient to demonstrate acute biochemical improvements, cannot address longer-term clinical outcomes or the durability of oxidative stress reduction. The absence of maternal or neonatal clinical outcomes prevents direct correlation of biochemical improvements with pregnancy complications. The lack of multiple comparison corrections in our exploratory analyses may have increased Type I error risk, although the consistency of findings across related biomarkers suggests robust treatment effects.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eIron supplementation in pregnant women with iron deficiency anemia provides substantial benefits extending beyond traditional hematological improvements, with oxidative stress reduction representing a critical therapeutic mechanism. The very large effect sizes for antioxidant capacity improvement, coupled with their independence from iron parameter changes, indicate that iron therapy triggers comprehensive cellular recovery processes potentially preventing oxidative stress-related pregnancy complications. Healthcare providers should prioritize early screening and aggressive treatment of iron deficiency, recognizing that standard supplementation protocols achieve oxidative stress reduction comparable to or exceeding hematological improvements across all trimesters and BMI categories. The rapid response timeline\u0026mdash;significant improvements within one month\u0026mdash;argues against watchful waiting approaches and supports immediate intervention even in late pregnancy. These findings reconceptualize iron supplementation as antioxidant therapy with transgenerational implications, emphasizing the importance of achieving optimal maternal iron status for both immediate pregnancy outcomes and offspring health.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eIDA Iron deficiency anemia\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Oxidative stress\u003c/p\u003e\n\u003cp\u003eERFE \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Erythroferrone\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTAS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Total antioxidant status\u003c/p\u003e\n\u003cp\u003eTOS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Total oxidant status\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate:\u003c/strong\u003e This study was approved by the Haseki Training and Research Hospital Human Research Ethics Committee (Registry No: 114-2021 dated December 8, 2021) and conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent before enrollment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eThe authors thank the laboratory staff at Haseki Training and Research Hospital for their technical assistance with biomarker analyses. We acknowledge the pregnant women who participated in this study and the nursing staff who assisted with data collection. We thank the antenatal clinic staff for their support in patient recruitment and follow-up.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' Contributions:\u003c/strong\u003e SYD: Patient recruitment, data collection, manuscript review. HA: Patient recruitment, clinical assessments, data collection. HAA: Laboratory analyses, data collection. EYG: Patient recruitment, clinical follow-up. IOB: Data collection, statistical analysis support. BG: Patient recruitment, data management. AO: Study coordination, manuscript review. FYG: Conceptualization, methodology, investigation, writing - original draft, project administration. IY: Laboratory analyses, biochemical assays, quality control. AC: Supervision, methodology, writing - review \u0026amp; editing, formal analysis, final approval. All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials:\u003c/strong\u003e The datasets used and analyzed during the current study are available from the corresponding author on reasonable request, subject to appropriate ethical approvals and data sharing agreements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAI Assistance Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this manuscript, the authors utilized ChatGPT 4o (OpenAI) and Claude 3.7 Sonnet (Anthropic) to refine English language clarity and style. All AI-assisted content underwent thorough review and editing by the authors, who take full responsibility for the manuscript's final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAtaide R, Fielding K, Pasricha S, Bennett C. Iron deficiency, pregnancy, and neonatal development. Int J Gynecol Obstet. 2023;162:14\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGeorgieff MK. Iron deficiency in pregnancy. Am J Obstet Gynecol. 2020;223:516\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLewkowitz AK, Tuuli MG. Identifying and treating iron deficiency anemia in pregnancy. Hematology. 2023;2023:223\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMintsopoulos V, Tannenbaum E, Malinowski AK, Shehata N, Walker M. 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J Appl Hematol. 2024;15:197\u0026ndash;203.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEsen Ağar B, Akarsu S, Aydin S. The Effect of Iron Deficiency Anemia and Different Treatment Methods on DNA Damage: 8-hydroxy-2-deoxyguanosine Level. Glob Pediatr Health. 2021;8:2333794X211041337.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBenson CS, Shah A, Stanworth SJ, Frise CJ, Spiby H, Lax SJ, et al. The effect of iron deficiency and anaemia on women\u0026rsquo;s health. Anaesthesia. 2021;76:84\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKoenig M, Tussing-Humphreys L, Day J, Cadwell B, Nemeth E. Hepcidin and Iron Homeostasis during Pregnancy. Nutrients. 2014;6:3062\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSangkhae V, Fisher AL, Wong S, Koenig MD, Tussing-Humphreys L, Chu A, et al. Effects of maternal iron status on placental and fetal iron homeostasis. J Clin Invest. 2019;130:625\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChełchowska M, Ambroszkiewicz J, Gajewska J, Jabłońska-Głąb E, Maciejewski TM, Ołtarzewski M. Hepcidin and Iron Metabolism in Pregnancy: Correlation with Smoking and Birth Weight and Length. Biol Trace Elem Res. 2016;173:14\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChełchowska M, Maciejewski TM, Mazur J, Gajewska J, Zasimovich A, Ołtarzewski M, et al. Active Tobacco Smoke Exposure in Utero and Concentrations of Hepcidin and Selected Iron Parameters in Newborns. Int J Environ Res Public Health. 2019;16:1996.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGarcia-Valdes L, Campoy C, Hayes H, Florido J, Rusanova I, Miranda MT, et al. The impact of maternal obesity on iron status, placental transferrin receptor expression and hepcidin expression in human pregnancy. Int J Obes. 2015;39:571\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoberts H, Bourque SL, Renaud SJ. Maternal iron homeostasis: effect on placental development and function. Reproduction. 2020;160:R65\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang JY, Wang J, Lu Q, Tan M, Wei R, Lash GE. Iron stores at birth in a full-term normal birth weight birth cohort with a low level of inflammation. Biosci Rep. 2020;40:BSR20202853.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Y, Lu Y, Jin L. Iron Metabolism and Ferroptosis in Physiological and Pathological Pregnancy. Int J Mol Sci. 2022;23:9395.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFisher AL, Sangkhae V, Presicce P, Chougnet CA, Jobe AH, Kallapur SG, et al. Fetal and amniotic fluid iron homeostasis in healthy and complicated murine, macaque, and human pregnancy. JCI Insight. 2020;5:e135321.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSangkhae V, Fisher AL, Wong S, Koenig MD, Tussing-Humphreys L, Chu A, et al. Effects of maternal iron status on placental and fetal iron homeostasis. J Clin Invest. 2019;130:625\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShastri L, Pammal RS, Mani I, Thomas T, Kurpad AV. Oxidative stress during early pregnancy and birth outcomes. Public Health Nutr. 2016;19:3210\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCao C, O\u0026rsquo;Brien KO. Pregnancy and iron homeostasis: an update. Nutr Rev. 2013;71:35\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMilman N, Bergholt T, Eriksen L, Byg K, Graudal N, Pedersen P, et al. Iron prophylaxis during pregnancy \u0026ndash; How much iron is needed? A randomized dose\u0026ndash; response study of 20\u0026ndash;80 mg ferrous iron daily in pregnant women. Acta Obstet Gynecol Scand. 2005;84:238\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDewey KG, Oaks BM. U-shaped curve for risk associated with maternal hemoglobin, iron status, or iron supplementation. Am J Clin Nutr. 2017;106:S1694\u0026ndash;702.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCepeda-Lopez AC, Melse-Boonstra A, Zimmermann MB, Herter-Aeberli I. In overweight and obese women, dietary iron absorption is reduced and the enhancement of iron absorption by ascorbic acid is one-half that in normal-weight women. Am J Clin Nutr. 2015;102:1389\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhambalia AZ, Aimone A, Nagubandi P, Roberts CL, McElduff A, Morris JM, et al. High maternal iron status, dietary iron intake and iron supplement use in pregnancy and risk of gestational diabetes mellitus: a prospective study and systematic review. Diabet Med. 2016;33:1211\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFrazer DM, Anderson GJ. The regulation of iron transport. BioFactors. 2014;40:206\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGambling L, Kennedy C, McArdle HJ. Iron and copper in fetal development. Semin Cell Dev Biol. 2011;22:637\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eErber L, Liu S, Gong Y, Tran P, Chen Y. Quantitative Proteome and Transcriptome Dynamics Analysis Reveals Iron Deficiency Response Networks and Signature in Neuronal Cells. Molecules. 2022;27:484.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSangkhae V, Fisher AL, Chua KJ, Ruchala P, Ganz T, Nemeth E. Maternal hepcidin determines embryo iron homeostasis in mice. Blood. 2020;136:2206\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFerguson KK, Meeker JD, McElrath TF, Mukherjee B, Cantonwine DE. Repeated measures of inflammation and oxidative stress biomarkers in preeclamptic and normotensive pregnancies. Am J Obstet Gynecol. 2017;216:527.e1-527.e9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBurton GJ, Jauniaux E. Oxidative stress. Best Pract Res Clin Obstet Gynaecol. 2011;25:287\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Iron deficiency anemia, pregnancy, oxidative stress, total antioxidant status, hepcidin, erythroferrone","lastPublishedDoi":"10.21203/rs.3.rs-7095398/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7095398/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eIron deficiency anemia (IDA) affects approximately 40% of pregnant women worldwide, regarding increased oxidative stress (OS) and adverse pregnancy outcomes. Recent advances identified hepcidin as the master regulator of iron homeostasis and erythroferrone (ERFE) as a key erythroid regulator, yet their responses to iron supplementation and relationships with OS markers during pregnancy remain poorly understood.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo investigate whether oral iron supplementation reduces OS-related molecular damage in pregnant women with IDA and characterize relationships between iron regulatory molecules (hepcidin, ERFE) and OS biomarkers.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis prospective observational study enrolled 40 pregnant women with IDA (mean age 29.23\u0026thinsp;\u0026plusmn;\u0026thinsp;6.33 years) across all trimesters. Participants received 200 mg elemental iron daily for one month. Pre- and post-treatment measurements included hematologic parameters, iron metabolism markers (ferritin, hepcidin, ERFE), and OS biomarkers (total antioxidant status [TAS], total oxidant status [TOS]).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eIron supplementation produced very large improvements in TAS (0.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36 to 1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37 mmol/L; Cohen's d\u0026thinsp;=\u0026thinsp;1.87, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), exceeding hematological improvements in hemoglobin (10.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72 to 11.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97 g/dL; d\u0026thinsp;=\u0026thinsp;1.76, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and hematocrit (30.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79% to 35.24\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01%; d\u0026thinsp;=\u0026thinsp;1.74, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The TOS/TAS ratio decreased substantially (14.53\u0026thinsp;\u0026plusmn;\u0026thinsp;15.98 to 4.10\u0026thinsp;\u0026plusmn;\u0026thinsp;3.14; d=-0.91, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Hepcidin increased appropriately (2214.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1444.27 to 3492.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1640.51 pg/mL; d\u0026thinsp;=\u0026thinsp;0.83, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) while ERFE decreased (470.75\u0026thinsp;\u0026plusmn;\u0026thinsp;170.75 to 345.25\u0026thinsp;\u0026plusmn;\u0026thinsp;112.96 pg/mL; d=-0.87, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), confirming successful iron repletion. TAS improvements showed minimal correlation with iron parameters (all |r|\u0026lt;0.25), suggesting independent mechanisms.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eIron supplementation effectively reduces OS in pregnant women with IDA through mechanisms independent of iron parameter changes. The coordinated hormonal responses confirm appropriate iron repletion while suggesting additional therapeutic benefits beyond anemia correction.\u003c/p\u003e","manuscriptTitle":"Iron Therapy Reduces Oxidative Stress in Pregnant Women with Anemia: A Prospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-29 12:00:47","doi":"10.21203/rs.3.rs-7095398/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-07T14:24:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-15T04:46:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-11T22:46:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"140693337019492302715211726823913170608","date":"2025-08-06T18:27:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"117515133593148378243327831766479259344","date":"2025-08-04T16:39:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-24T17:52:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-14T17:06:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-11T08:55:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-11T08:55:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2025-07-10T17:50:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c600ebdf-1c8d-43a4-b84f-d40a1f3d1606","owner":[],"postedDate":"July 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:13:08+00:00","versionOfRecord":{"articleIdentity":"rs-7095398","link":"https://doi.org/10.1186/s12884-026-09072-7","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2026-04-10 15:58:26","publishedOnDateReadable":"April 10th, 2026"},"versionCreatedAt":"2025-07-29 12:00:47","video":"","vorDoi":"10.1186/s12884-026-09072-7","vorDoiUrl":"https://doi.org/10.1186/s12884-026-09072-7","workflowStages":[]},"version":"v1","identity":"rs-7095398","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7095398","identity":"rs-7095398","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}