How Precision Diets, Through Gut Bacteria, Affect Anemia in Nepalese Adolescent

June 16, 2026 updated by: Rubina Karki, Southern Medical University, China

Gut Microbiota-Mediated Effects of Precision Dietary Interventions on Anemia Among Nepalese Adolescents

This study aims to evaluate whether a food-based nutrition intervention using goat liver can improve anemia among adolescent girls in Kathmandu, Nepal, and compare its effectiveness with the current standard iron and folic acid supplementation. It will also investigate how diet and the gut microbiota (the community of beneficial microorganisms living in the intestine) may influence iron absorption and response to treatment.

Anemia is a major public health problem among adolescent girls in Nepal. During adolescence, rapid growth and the onset of menstruation increase the body's need for iron and other nutrients involved in blood formation. If left untreated, anemia can impair physical growth, reduce learning ability and concentration, decrease work capacity, weaken immunity, and negatively affect future reproductive health. Although weekly iron-folic acid supplementation programs are widely implemented, anemia remains common, suggesting that additional strategies may be needed.

Recent research indicates that gut microbiota may affect iron metabolism by influencing nutrient absorption, inflammation, and overall intestinal health. Dietary habits can alter the composition of gut bacteria, which may partly explain why individuals respond differently to iron interventions. However, little is known about these relationships among Nepalese adolescents. This study seeks to fill that knowledge gap and explore whether a locally available food-based intervention can provide a practical and sustainable alternative or complement to conventional supplementation.

The research will be conducted among adolescent girls aged 15 to 19 years enrolled in selected schools in Kathmandu. The study has two phases. In the first phase, participants will undergo screening to determine the prevalence and types of anemia. Blood samples will be collected to measure hemoglobin, iron status, vitamin B12, folate, and inflammation-related biomarkers. Stool samples will be collected to analyze gut microbiota composition. Information on dietary intake, food frequency, dietary diversity, and other relevant characteristics will also be obtained through structured questionnaires.

Girls identified with anemia and meeting the eligibility criteria will be invited to participate in the randomized intervention phase. Participants will be randomly assigned to receive either the standard iron-folic acid supplementation recommended by national programs or a goat liver-based dietary intervention for 12 weeks. Random assignment ensures a fair comparison between interventions and minimizes bias.

Goat liver was selected because it is rich in highly bioavailable heme iron as well as vitamin B12, folate, vitamin A, and other nutrients important for blood production. As a commonly available food in Nepal, it may represent a culturally acceptable and sustainable nutrition-based strategy for improving anemia.

During the intervention, participants will be monitored regularly to assess adherence and wellbeing. At the end of the 12-week period, blood and stool samples will be collected again to evaluate changes in hemoglobin levels, iron-related biomarkers, nutritional status, and gut microbiota composition. The study will compare improvements between intervention groups and examine whether changes in gut microbiota are associated with better anemia outcomes.

Participation is entirely voluntary. Written informed consent from parents or guardians and informed assent from adolescent participants will be obtained before enrollment. Participants may withdraw from the study at any time without penalty. All personal information and laboratory results will remain confidential and will be stored using coded identifiers to protect privacy.

Blood collection will be performed by trained healthcare professionals using standard safety procedures, and stool samples will be collected using appropriate collection kits and instructions. Participants found to have severe anemia or other important medical conditions during the study will be referred for appropriate medical care according to national guidelines.

The findings from this study are expected to provide important evidence on whether a locally available food-based intervention can effectively improve anemia among adolescent girls while also enhancing understanding of the relationship between diet, gut microbiota, and iron metabolism. The results may help inform future nutrition policies, school health programs, and precision nutrition strategies for anemia prevention and treatment in Nepal and other similar settings.

Study Overview

Detailed Description

  1. INTRODUCTION Anemia represents one of the most significant global public health challenges, affecting an estimated 1.74 billion people worldwide, with disproportionately higher prevalence among adolescent girls and women of reproductive age1,2. Adolescence constitutes a critical developmental window characterized by rapid growth velocity, increased iron requirements, and heightened physiological susceptibility, particularly among females due to the onset of menstruation3. Iron deficiency anemia (IDA) during this developmental period has been associated with impaired cognitive function, reduced physical work capacity, compromised immune competence, and adverse reproductive health outcomes in later life 4.

    While iron deficiency remains the predominant etiological factor for anemia globally, emerging evidence demonstrates that anemia represents a complex, multifaceted disorder influenced by nutritional quality, inflammatory status, infectious disease burden, and biological variables including gut microbiota composition5,6.The gut microbiome has emerged as a critical regulator of systemic iron homeostasis through multiple mechanistic pathways: (1) direct competition with the host for luminal iron; (2) modulation of intestinal inflammation and barrier function; (3) production of short-chain fatty acids (SCFAs), particularly butyrate, which influence hepcidin expression and iron absorption; and (4) immune-mediated regulation of iron absorption7,8.

    We hypothesize that dietary patterns, particularly vegetarian diets prevalent in South Asian populations, alter gut microbiota composition toward phyla producing higher levels of butyrate and propionate, which may downregulate hepcidin expression and enhance intestinal iron absorption. Conversely, dysbiotic microbiota profiles characterized by pathogenic overgrowth may promote intestinal inflammation, upregulate hepcidin, and impair iron bioavailability despite adequate dietary intake.

    South Asia bears one of the highest burdens of adolescent anemia globally, with over 50% of adolescent girls affected according to UNICEF and WHO estimates 9. This elevated prevalence results from the convergence of multiple risk factors: monotonous cereal-based diets with low bioavailable iron content, gender-based nutritional inequities, inadequate sanitation infrastructure, high prevalence of soil-transmitted helminth infections, and limited dietary diversity10. Although Weekly Iron-Folic Acid Supplementation (WIFAS) programs have been implemented throughout the region, their efficacy in reducing anemia prevalence has demonstrated limited success, suggesting that traditional supplementation approaches may be insufficient to address the biological complexity and underlying determinants of anemia in this population11,12.

    Recent advances in nutritional science have highlighted the bidirectional relationship between iron supplementation and gut microbiota composition. Oral iron supplementation has been demonstrated to alter intestinal microbial ecology, potentially promoting pathogenic bacterial proliferation and intestinal inflammation, which may paradoxically impair iron absorption and increase gastrointestinal side effects 13,14. These findings underscore the critical importance of understanding diet-microbiome interactions when developing contextually appropriate anemia interventions.

    Nepal exemplifies the challenges of addressing adolescent anemia in resource-limited settings. According to the Nepal Demographic and Health Survey (NDHS) 2022, anemia affects 39.4% of adolescent females aged 15-19 years, with higher prevalence observed among individuals from lower socioeconomic strata and specific ecological regions15.Despite sustained national nutrition programs emphasizing iron supplementation and dietary diversity promotion, anemia prevalence has demonstrated only modest decline over the past decade16. Iron deficiency and inflammation are further exacerbated by recurrent gastrointestinal infections, poor sanitation, and high dietary phytate content from plant-based staples, which inhibit non-heme iron absorption17,18.

    Research on the molecular mechanisms underlying anemia in Nepal remains substantially underexplored, particularly regarding the relationship between dietary patterns, gut microbiota composition, and iron metabolism in adolescent populations. Existing studies have primarily focused on prevalence quantification, dietary intake assessment, and program evaluation, leaving critical knowledge gaps regarding the biological pathways connecting nutrition, microbiome function, and anemia status 19,20. Closing this evidence gap is essential for developing precision nutrition interventions that are context-specific, physiologically informed, and demonstrably more effective than conventional blanket supplementation approaches.

  2. STATEMENT OF THE PROBLEM Despite the extensive implementation of iron-folic acid supplementation programs and school-based nutrition initiatives, anemia among adolescent girls remains highly prevalent in Nepal, representing a persistent public health priority .Previous research on anemia in Nepal has predominantly employed a population-level epidemiological approach, focusing on prevalence quantification, identification of dietary and socioeconomic risk factors, and assessment of supplementation program compliance11,19. While these studies provide valuable public health insights, they fail to account for inter-individual biological variation in anemia etiology and response to interventions.

    A critical gap in Nepalese anemia research is the paucity of studies examining the role of gut microbiota in iron absorption and anemia outcomes. International evidence demonstrates that gut microbiota composition significantly influences iron bioavailability, inflammatory pathways, and host response to iron interventions 6,7.However, no studies in Nepal have examined how gut microbial profiles interact with dietary patterns to influence anemia status in adolescent girls. Given the high prevalence of enteric infections, subclinical inflammation, dietary iron absorption inhibitors, and soil-transmitted helminth infections in Nepal, this represents a substantial knowledge gap with direct implications for intervention design18,21.Furthermore, Nepal's ongoing nutritional transition, characterized by the coexistence of traditional diets with increasing processed food consumption, may be altering gut microbiota composition and nutritional status in ways that affect anemia risk22. The interaction between helminth infections, gut microbiota, and iron status remains particularly understudied, despite evidence that hookworm and Ascaris infections profoundly affect both intestinal microbial ecology and host iron metabolism21,23.

    The continued application of generalized, non-targeted interventions without mechanistic understanding risks perpetuating suboptimal outcomes and inefficient allocation of limited public health resources. Therefore, there is an urgent need for mechanism-based, precision nutrition approaches to address anemia in Nepalese adolescent girls. This research aims to generate novel, context-specific evidence that can guide more targeted and effective anemia interventions by investigating the relationships between dietary patterns, gut microbiota composition, and anemia status.

  3. OBJECTIVES 3.1 General Objective To determine the prevalence and determinants of anemia in adolescent girls and to study the diet-microbiome interactions in the sub-sample to provide precision nutrition interventions in Kathmandu, Nepal.

3.2 Specific Objectives

  1. To determine the prevalence and typology of anemia among adolescent girls in selected schools of the Kathmandu through comprehensive hematological assessment.
  2. To distinguish gut microbiota among anemic and non-anemic adolescent girls.
  3. To evaluate the efficacy of goat liver supplementation over traditional supplementation in improving anemia-related biomarkers over a 12-week period.
  4. To assess changes in gut microbiota composition following interventions and identify microbial species associated with improved anemia outcomes.

4. RESEARCH QUESTIONS

1. What is the prevalence and distribution of anemia types (iron deficiency and megaloblastic) among adolescent girls in the Kathmandu? 2. How does gut microbiota differ in anemic and non-anemic adolescent girls? 2. Does gut microbiota composition change following precision intervention, and are specific microbial taxa associated with treatment response? 3. What is the effectiveness of nutrition interventions, including animal-source food supplementation, among adolescent girls? 5. SIGNIFICANCE OF THE STUDY This research addresses a critical health priority for Nepal and directly contributes to Sustainable Development Goal 3 (Good Health and Well-being). By generating empirical evidence on diet-microbiota-anemia relationships, this study will fill a significant knowledge gap with direct policy relevance for national nutrition programs.

Understanding how dietary patterns, particularly vegetarian diets, interact with gut microbiota to influence anemia status can inform the development of contextually appropriate nutrition education and dietary guidelines. The evaluation of goat liver as a culturally acceptable, food-based intervention represents a novel approach that could identify sustainable strategies to complement existing supplementation programs. Goat liver is particularly suitable for the Nepalese context due to its high bioavailable iron content (approximately 3.3 mg per 100g), abundant vitamin B12, widespread availability, and relatively low cost compared to other animal-source foods.

This study will be among the first in South Asia to integrate microbiome analysis with nutritional and hematological assessments in an adolescent population, contributing valuable evidence on the feasibility and potential benefits of food based supplement approach in resource-limited settings. The findings will have direct applicability to national adolescent health policy, school feeding programs, and anemia control strategies in Nepal and similar contexts throughout the region.

Furthermore, this research will build local capacity in microbiome and nutrition epidemiology research through collaboration with Nepali institutions, contributing to the development of sustainable research infrastructure for addressing priority public health questions.

6. METHODOLOGY 6.1 Research Design This study employs a mixed-methods design consisting of two sequential phases that integrate quantitative epidemiological assessment with experimental intervention methodology. The design progression moves from descriptive cross-sectional analysis to randomized controlled intervention, enabling both prevalence characterization and causal inference regarding precision nutrition interventions.

Phase 1: Cross-sectional survey Phase 2: Randomized controlled trial (RCT) of precision interventions Phase 1: Cross-Sectional Survey (Baseline Assessment)

Design Characteristics:

Type: Descriptive, observational cross-sectional study Purpose: Establish anemia prevalence, typology distribution, and baseline population characteristics Duration: 3-4 months for data collection and preliminary analysis Analytical Approach: In Phase 1, descriptive statistics will be employed to estimate the prevalence of anemia and its typology within the study population. Following this, exploratory factor analysis will be conducted to identify distinct dietary patterns from the food frequency questionnaire data. Additionally, logistic regression analysis will be performed to assess the association between potential risk factors and anemia status, thereby identifying key determinants of anemia among adolescent girls in the Kathmandu Valley.

Primary Functions of Phase 1:

Prevalence Quantification: Generate representative estimates of anemia types (iron deficiency, megaloblastic, mixed) among adolescent girls in Kathmandu Valley, addressing Research Question 1 Participant Recruitment Pool: Identify and characterize eligible participants for Phase 2 RCT based on hematological profiles Baseline Contextualization: Document dietary patterns, socioeconomic determinants, and gut microbiota composition profiles in the target population Stratification Variables: Establish anemia typology classifications necessary for precision intervention matching in Phase 2

Biological Sample Collection (Phase 1):

Single-timepoint collection: venous blood (10 mL) for complete hematological panel and inflammatory markers; stool sample for gut microbiota baseline characterization All samples collected following standardized protocols with field quality control measures 6.2 Study Setting

The study will be conducted in the Kathmandu, Nepal which was selected for the following reasons:

  • Logistical feasibility: Central location with access to necessary laboratory infrastructure for sample processing and microbiome analysis
  • Population representativeness: Urban and peri-urban adolescent population with diverse socioeconomic and dietary backgrounds
  • Healthcare infrastructure: Existing school health networks and community health centers facilitating participant recruitment and follow-up
  • Laboratory capacity: Availability of advanced diagnostic facilities for hematological and microbiological analyses While the Kathmandu may not represent the highest anemia burden regions of Nepal (rural Terai areas demonstrate higher prevalence), it provides an appropriate setting for this proof-of-concept study examining the feasibility and potential efficacy of microbiome-informed interventions.

6.3 Study Population and Sampling 6.3.1 Phase 1: Cross-sectional Survey The target population consists of adolescent girls aged 15-19 years enrolled in secondary schools in the Kathmandu Valley. This age group was selected based on NDHS 2022 data demonstrating the highest anemia prevalence among female adolescents (MoHP, 2022).

Inclusion Criteria:

  • Female adolescents aged 15-19 years
  • Enrolled in selected schools
  • Resident in Kathmandu for at least 6 months
  • Provision of written informed assent and parental consent

Exclusion Criteria:

  • Current pregnancy
  • Known genetic blood disorders (thalassemia, sickle cell disease)
  • Chronic metabolic, inflammatory, or infectious diseases affecting hematological parameters
  • Acute illness at time of screening
  • Use of iron, folic acid, vitamin B12 supplements, antibiotics, or probiotics within the past 3 months
  • History of helminth infection or deworming treatment within the past 6 months
  • Participation in other nutrition intervention studies

Sample Size Calculation:

The sample size for the cross-sectional survey was calculated using the Cochran's formula:

Cochran's formula: n= {z2 x p x (1-p)}/d2

Where:

n = required sample size Z = 1.96 (95% confidence level) p = prevalence of anemia in Kathmandu d = margin of error Calculations

= (〖1.96〗^(2 ) X 0.393 X (1-0.393))/〖(0.05)〗^2 =366.56

Adjustment for Non-response Non-response rate = 10% n_adjusted= 366.57 X 10% = 403

Sampling Technique:

A multistage stratified random sampling approach will be employed: (1) Selection of municipalities from Kathmandu (random selection); (2) Selection of wards within selected municipalities (random selection); (3) Selection of private schools within selected wards (4) Selection of participants within schools (proportional to enrollment).

6.3.2 Phase 2: Randomized Controlled Trial Participants for the RCT will be recruited from the cross-sectional survey participants who meet the following additional eligibility criteria: confirmed anemia (Hb < 12.0 g/dL) based on baseline hematological assessment, no contraindications to supplementation and commitment to complete 12-week intervention period.

Sample Size Estimation Formula The sample size for the randomized controlled trial was calculated using the Analysis of Covariance (ANCOVA) formula for parallel-group designs with baseline adjustment24.

n= (2×〖(Zα+Zβ)〗^2×σ^2×(1-ρ^2))/Δ^2 +1

Where:

n = required sample size per group Zα = 1.96 (standard normal deviate for two-sided α = 0.05) Zβ = 0.84 (standard normal deviate for power = 80%) σ = standard deviation of hemoglobin = 1.5 g/dL (derived from Nepal Demographic and Health Survey 2022 and regional anemia studies) ρ = correlation between baseline and follow-up hemoglobin measurements = 0.6 (conservative estimate based on repeated measures in iron supplementation trials) Δ = minimum clinically important difference in hemoglobin = 1.2 g/dL (representing shift from moderate to mild anemia classification per WHO criteria)

(1-ρ²) = variance inflation factor accounting for baseline adjustment efficiency

Parameter Justification Parameter Value Scientific Justification Analysis method ANCOVA (baseline-adjusted) Adjusting endline values for baseline measurements reduces error variance and increases statistical efficiency by 30-50% compared to simple comparison of post-treatment means or change scores . ANCOVA is unaffected by chance baseline differences and regression to the mean.

Correlation coefficient (ρ) 0.6 Conservative estimate for correlation between baseline and 12-week hemoglobin25

Detectable difference (Δ) 1.2 g/dL Clinically meaningful threshold representing transition from moderate anemia (Hb 8.0-10.9 g/dL) to mild anemia (Hb 11.0-11.9 g/dL) per WHO 2011 classification. Precision nutrition interventions targeting specific etiologies are hypothesized to produce larger effects than standard blanket supplementation.

Standard deviation (σ) 1.5 g/dL Population estimate from NDHS 2022 and regional studies of adolescent anemia in South Asia .

Power (1-β) 80% Standard for nutritional intervention trials; balances scientific rigor with resource constraints.

Significance level (α) 0.05 (two-sided) Conventional biomedical threshold; accounts for possibility of intervention harm or benefit.

n= (2×〖(1.96+0.84)〗^2×〖1.5〗^2×(1-〖0.6〗^2))/〖1.2〗^2 +1 = 22.68/1.44+1 = 16.75 = 17 per group (unadjusted) Adjustment for Attrition and Design Effect

To account for anticipated attrition and ensure robust intent-to-treat analysis:

Adjustment Factor Calculation Value Base sample size Calculated above 17 per group Attrition rate 15% loss to follow-up over 12 weeks n ÷ 0.85 Final sample size 17 ÷ 0.85 20 per group

Total RCT sample size: 60 participants (20 per group × 3 intervention arms) For microbiome outcomes (exploratory/secondary), we acknowledge that this sample size may be underpowered for detecting significant differences in alpha diversity due to high inter-individual variability. Microbiome analyses will be considered exploratory, with findings informing future adequately powered studies.

Three intervention arms: (1) Control (standard care): n = 20; (2)Standard supplementation: n = 20 (3) (3) Goat liver supplementation: n = 20. Total RCT sample size: 60 participants 6.4 Classification of Anemia Status

Anemia classification will follow WHO guidelines with concurrent assessment of inflammatory status:

6.4.1 Hemoglobin Cut-offs (WHO, 2011) Anemia status will be classified based on hemoglobin concentration levels. The criterion will be based on WHO criteria (2011) for adolescent girls 15 - 19 years.

The World Health Organization guidelines define anemia when the hemoglobin level is less than 12.0 g/dL in non-pregnant females. Severity of anemia will be classified based on hemoglobin levels as follows:

Anemia: Hemoglobin ≤ 12g/dL Non-anemic will be defined as a participant with a hemoglobin of ≥12.0 g/dL 2 6.4.2 Iron Deficiency Anemia Diagnosed when both criteria are met: Hemoglobin < 12.0 g/dL AND Serum ferritin < 15 μg/L (no inflammation) or < 30 μg/L (with inflammation) 6.4.3 Inflammation Assessment CRP and AGP will be measured concurrently to assess inflammation status and adjust ferritin values according to BRINDA project recommendations26,27.

Inflammation Categories: Reference (CRP ≤ 5 mg/L AND AGP ≤ 1.0 g/L); Incubation (CRP > 5 mg/L AND AGP ≤ 1.0 g/L); Early convalescence (CRP > 5 mg/L AND AGP > 1.0 g/L); Late convalescence (CRP ≤ 5 mg/L AND AGP > 1.0 g/L) Ferritin Adjustment: 〖Ferritin〗_adjusted=〖Ferritin〗_unadjusted - β₁(CRPobs - CRPref) - β₂(AGPobs - AGPref), where β coefficients are derived from regression analysis of the study population.

6.4.4. Megaloblastic Anemia 6.4.4.1. Vitamin B12 Cut-offs

Serum vitamin B12 concentration will be determined to assess the vitamin B12 status of the study subjects and to support the diagnosis of megaloblastic anemia. The categorization will be done as per the available clinical reference ranges.Participants will be categorized as follows:

Normal Vitamin B12 status: 193-982 pg/mL Vitamin B12 Deficiency: ≤193 pg/mL 28 6.4.4.2. Folate Cut-offs Determination of serum folate concentration will be done to assess prevalence of folate deficiency in adolescent girls and aid diagnosis of megaloblastic anemia. Folate status will be classified as per WHO guidelines.

A serum folate concentration of less than 3 ng/mL (equivalent to <6.8 nmol/L) is considered a folate deficiency per WHO recommendations29. Participants with serum folate concentration equal or above this level are defined as having an adequate status of folate.

The classification will be utilized with vitamin B12 and iron laboratory markers to further categorize the type of anemia (iron deficiency anemia, megaloblastic anemia, or mixed anemia) and as a guide for interpreting the results of the study.

6.5 Data Collection Tools and Procedures 6.5.1 Dietary Assessment Dietary intake will be assessed using: (1) Validated Food Frequency Questionnaire (FFQ): A semi-quantitative FFQ adapted for Nepali adolescents, covering 112 food items across 10 food groups; (2) 24-hour dietary recalls: conducted through structured interviews; (3) Dietary Diversity Score (DDS): Calculated based on WHO/FAO guidelines.

Vegetarian status will be classified as: Lacto-vegetarian (consumes dairy but no meat, fish, or eggs); Ovo-lacto-vegetarian (consumes dairy and eggs but no meat or fish); Non-vegetarian (consumes meat, fish, or poultry).

6.5.2 Biological Sample Collection and Analysis Hematological Biomarkers: Hemoglobin (cyanmethemoglobin method); Serum ferritin (ECLIA); Serum transferrin receptor (ELISA); C-reactive protein (hs-immunoturbidimetric assay); Alpha-1-acid glycoprotein (immunoturbidimetric assay); Serum folate and vitamin B12 (chemiluminescent immunoassay); Complete blood count (automated hematology analyzer).

6.5.3 Gut Microbiota Analysis Sample Collection: Stool samples will be collected at baseline and endline (12 weeks). Participants will be provided with OMNIgene-GUT collection tubes (OMR-200) containing stabilization buffer. Samples will be stored at room temperature for up to 24 hours, then transferred to -80°C storage.

DNA Extraction: DNA will be extracted using the DNeasy PowerSoil Kit (Qiagen) following manufacturer's protocol with mechanical lysis via bead-beating.

16S rRNA Gene Sequencing: The V4 hypervariable region of the bacterial 16S rRNA gene will be amplified using primers 515F (GTGCCAGCMGCCGCGGTAA) and 806R (GGACTACHVGGGTWTCTAAT). PCR products will be purified and normalized. Sequencing will be performed on the Illumina MiSeq platform using 2×250 bp paired-end chemistry with minimum sequencing depth of 10,000 reads per sample.

Bioinformatic Analysis: Raw sequences will be processed using QIIME2 pipeline. DADA2 will be used for quality filtering, denoising, and amplicon sequence variant (ASV) generation. Taxonomic classification using SILVA 138 database. Alpha diversity metrics: Shannon index, observed ASVs, Faith's phylogenetic diversity. Beta diversity: Bray-Curtis and weighted UniFrac distances. Differential abundance analysis using DESeq2.

6.6 Intervention Design 6.6.1 Standard Supplementation approach In the standard iron-folic acid supplementation group, participants diagnosed with iron deficiency anemia will receive ferrous sulfate tablets providing 60 mg of elemental iron combined with 400 micrograms of folic acid. This dosage aligns with the current national guidelines for weekly iron-folic acid supplementation programs in Nepal and represents the standard of care against which the goat liver supplementation will be compared. The ferrous sulfate formulation is selected due to its established bioavailability and widespread use in public health anemia control programs. Participants will be instructed to consume the supplement on a weekly basis, and adherence will be monitored through pill counts and self-reported consumption logs during scheduled follow-up visits.

6.6.2 Goat Liver Supplementation Rationale for Selection Goat liver was selected as the food-based intervention component to provide iron and folate in quantities comparable to Nepal's national Weekly Iron-Folic Acid Supplementation (WIFAS) program, while offering superior bioavailability through natural food matrices.

Iron and Folate Content Compared to National Supplementation Standards

Iron Content and Bioavailability:

Liver from small ruminants contains approximately 6.0-8.0 mg iron per 100g, with 40-60% present as heme iron . This yields 2.4-4.8 mg of highly bioavailable heme iron per 100g. The 50g cooked portion provided three times weekly delivers approximately 1.2-2.4 mg of heme iron per serving, or 3.6-7.2 mg weekly.

Heme iron demonstrates substantially superior absorption compared to non-heme iron. Research by Bothwell et al. (1979) established that heme iron absorption ranges from 15% to 35%, whereas ferrous sulfate absorption typically achieves only 10-15% in standard conditions, with further reduction in high-phytate diets. The bioavailability advantage is particularly critical in Nepal, where monotonous cereal-based diets with high phytate content inhibit non-heme iron absorption30.

Comparison to WIFAS:

Nepal's national WIFAS program provides 60 mg elemental iron as ferrous sulfate weekly.With typical absorption rates, this yields 6-9 mg absorbed iron weekly.The heme iron from three 50g goat liver portions, with 15-35% absorption rates, provides 1.1-2.5 mg absorbed heme iron weekly 30. While total absorbed iron from goat liver is lower than WIFAS, the absence of absorption inhibitors and presence of absorption enhances (Vitamin A, organic acids) may improve net iron utilization 31. Furthermore, heme iron absorption is less susceptible to competitive inhibition by Calcium, polyphenols, and phytates abundant in Nepalese vegetarian diets 32.

Folate Content:

Liver is among the richest dietary sources of folate.It contains 178±34.9 μg of total folates per 100 gm 33. With 50 gm per serving thrice weekly, it can deliver about 267 μg of folic acid weekly.

Comparison to WIFAS: Nepal's national WIFAS program provides 400 μg synthetic folic acid weekly . At face value, the goat liver intervention provides 33% less folate than the pharmacological supplement. However, three critical physiological factors establish functional equivalence:

Scientific Rationale for Functional Equivalence

  1. Superior Bioavailability of Reduced Folates Goat liver contains naturally occurring 5-methyltetrahydrofolate (5-MTHF) and other reduced folate polyglutamates, which bypass the rate-limiting dihydrofolate reductase (DHFR) step required for synthetic folic acid utilization34. Research by Pietrzik et al. (2010) demonstrates that natural food folates achieve 1.5-2.0 times greater bioavailability than synthetic folic acid on a molar basis when consumed as part of mixed meals, due to direct enterocyte absorption without hepatic reduction35.
  2. Absence of Unmetabolized Folic Acid (UMFA) Synthetic folic acid supplementation at 400 μg weekly produces detectable unmetabolized folic acid in systemic circulation in 10-30% of recipients, with potential concerns regarding immune dysfunction and masking of vitamin B12 deficiency36. Natural folates from liver are exclusively metabolized to bioactive forms, with no UMFA accumulation. This metabolic efficiency ensures that 100% of absorbed folate is physiologically available for erythropoiesis and DNA synthesis.

6.6.3 Intervention Duration The intervention period is 12 weeks, based on: Hematological response to iron supplementation typically observed within 8-12 weeks; Gut microbiota changes detectable within 4-6 weeks of dietary intervention; Logistical feasibility for school-based implementation.

6.7 Ethical Considerations This study has received ethical approval from the Nepal Health Research Council (NHRC) and institutional review boards of participating institutions.

Key ethical considerations include: (1) Informed Consent: Written informed assent from participants and written informed consent from parents/guardians; (2) Confidentiality: All participant data will be de-identified using unique study IDs with personal identifiers stored separately in encrypted files; (3) Data Security: Electronic data stored on password-protected, encrypted servers; physical documents in locked cabinets; (4) Withdrawal: Participants may withdraw at any time without penalty; (5) Referral for Severe Cases: Participants with severe anemia (Hb < 8 g/dL) will be referred for treatment; (6) Stool Sample Handling: BSL-2 precautions for all stool samples; (7) Community Engagement: Ongoing engagement with community leaders and school administrators; (8) Benefit Sharing: Study findings shared with participants, schools, and communities.

REFERENCES

  1. Kassebaum, N. J. et al. A systematic analysis of global anemia burden from 1990 to 2010. Blood 123, 615-624 (2014).
  2. WHO. Global anaemia estimates. https://www.who.int/teams/nutrition-and-food-safety/monitoring-nutritional-status-and-food-safety-and-events/global-anaemia-estimates (2011).
  3. Beard, J. L. Iron biology in immune function, muscle metabolism and neuronal functioning. J. Nutr. 131, 568S-579S; discussion 580S (2001).
  4. Black, R. E. et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet 382, 427-451 (2013).
  5. Camaschella, C. Iron-Deficiency Anemia. N. Engl. J. Med. 372, 1832-1843 (2015).
  6. Paganini, D. & Zimmermann, M. B. The effects of iron fortification and supplementation on the gut microbiome and diarrhea in infants and children: a review. Am. J. Clin. Nutr. 106, 1688S-1693S (2017).
  7. Chen, H. et al. Altered fecal microbial and metabolic profile reveals potential mechanisms underlying iron deficiency anemia in pregnant women in China. Bosn. J. Basic Med. Sci. 22, 923-933 (2022).
  8. Zimmermann, M. B. & Hurrell, R. F. Nutritional iron deficiency. Lancet 370, 511-520 (2007).
  9. UNICEF. Addressing anaemia in adolescent girls | UNICEF Nepal. https://www.unicef.org/nepal/stories/addressing-anaemia-adolescent-girls (2022).
  10. Ghimire, M., Bhandari, S. & Rajbanshi, M. Prevalence of anemia and its associated factors among school-going adolescent girls in schools of Dhankuta municipality, Nepal. PLOS Glob. Public Health 4, e0003684 (2024).
  11. Bhandari, S. et al. Dietary intake patterns and nutritional status of women of reproductive age in Nepal: findings from a health survey. Arch. Public Health Arch. Belg. Sante Publique 74, 2 (2016).
  12. Bhutta, Z. A. et al. Evidence-based interventions for improvement of maternal and child nutrition: what can be done and at what cost? Lancet 382, 452-477 (2013).
  13. Bloor, S. R., Schutte, R. & Hobson, A. R. Oral Iron Supplementation-Gastrointestinal Side Effects and the Impact on the Gut Microbiota. Microbiol. Res. 12, 491-502 (2021).
  14. Jaeggi, T. et al. Iron fortification adversely affects the gut microbiome, increases pathogen abundance and induces intestinal inflammation in Kenyan infants. Gut 64, 731-742 (2015).
  15. NDHS. Nepal demographic and health survey 2022: Key indicators. (2022). *others references did't fit here

Study Type

Interventional

Enrollment (Estimated)

60

Phase

  • Phase 3

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

    • Bagmati
      • Kathmandu, Bagmati, Nepal, 44600

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Female adolescents aged 15-19 years
  • Enrolled in selected schools
  • Resident in Kathmandu for at least 6 months
  • Provision of written informed assent and parental consent

Exclusion Criteria:

  • Current pregnancy
  • Known genetic blood disorders (thalassemia, sickle cell disease)
  • Chronic metabolic, inflammatory, or infectious diseases affecting hematological parameters
  • Acute illness at time of screening
  • Use of iron, folic acid, vitamin B12 supplements, antibiotics, or probiotics within the past 3 months
  • History of helminth infection or deworming treatment within the past 6 months
  • Participation in other nutrition intervention studies

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Other: Control (standard care)
Nutrition education on anemia prevention and control
Nutrition education on anemia prevention and control once a week
Experimental: Standard supplementation
Weekly iron-folic acid tablets with enhanced monitoring
Weekly iron-folic acid tablets with enhanced monitoring
Experimental: Goat liver supplementation
50 grams Cooked goat liver three times per week
50 gms Cooked goat liver three times per week

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Change in hemoglobin concentration
Time Frame: 12 weeks
The main measure of whether the intervention successfully treats anemia. Hemoglobin will be measured using the cyanmethemoglobin method at baseline and after the 12-week intervention period. The study is powered to detect a minimum clinically important difference of 1.2 g/dL, representing a shift from moderate to mild anemia classification per WHO criteria.
12 weeks

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Serum ferritin levels
Time Frame: 12 weeks
Measures iron stores in the body. Will be assessed using electrochemiluminescence immunoassay (ECLIA) and adjusted for inflammation status (CRP and AGP) using BRINDA project recommendations to obtain accurate iron deficiency classification
12 weeks
Serum transferrin receptor (sTfR)
Time Frame: 12 weeks
An additional marker of iron status that reflects tissue iron deficiency, particularly useful when inflammation is present. Measured by ELISA.
12 weeks
Serum folate concentration
Time Frame: 12 weeks
Assesses folate status to identify megaloblastic anemia and evaluate whether goat liver (rich in natural folates) improves folate levels compared to synthetic folic acid tablets. Measured by chemiluminescent immunoassay. Deficiency defined as <3 ng/mL (<6.8 nmol/L) per WHO guidelines.
12 weeks
Gut microbiota composition
Time Frame: 12 weeks
Exploratory/secondary outcome. 16S rRNA gene sequencing of the V4 hypervariable region will assess: alpha diversity (Shannon index, observed ASVs, Faith's phylogenetic diversity); beta diversity (Bray-Curtis and weighted UniFrac distances); and differential abundance of specific taxa (using DESeq2). Stool samples collected using OMNIgene-GUT tubes.
12 weeks
Improved Diet
Time Frame: 12 weeks
Changes in overall dietary quality and diversity, measured by the Dietary Diversity Score (DDS) calculated from food frequency questionnaires and 24-hour dietary recalls. This assesses whether participation in the study leads to broader improvements in eating habits beyond the specific intervention provided.
12 weeks
Vitamin B12 Status
Time Frame: 12 weeks
Serum B12 concentration, critical for diagnosing megaloblastic anemia and evaluating the advantage of goat liver (rich in B12) over standard IFA tablets (which contain no B12). Deficiency defined as ≤193 pg/mL. Measured by chemiluminescent immunoassay.
12 weeks

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Study Director: Longying Zha, Post Doctorate, Southern Medical University, China

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Helpful Links

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

July 1, 2026

Primary Completion (Estimated)

August 1, 2026

Study Completion (Estimated)

November 1, 2026

Study Registration Dates

First Submitted

June 16, 2026

First Submitted That Met QC Criteria

June 16, 2026

First Posted (Actual)

June 22, 2026

Study Record Updates

Last Update Posted (Actual)

June 22, 2026

Last Update Submitted That Met QC Criteria

June 16, 2026

Last Verified

June 1, 2026

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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