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Introduction-The purpose of an introduction is to provide the rationale behind the work, so that the reviewer may understand and appreciate the objectives. Please describe the importance (significance) of the study. Defend the model- Provide a rationale and describe the reasoning that led you to selecting them. Briefly describe the experimental design and how it accomplished the stated objectives. Describe the situation and specify clearly the gaps in the existing knowledge and/or controversy and in conclusive evidence. The discussion should be supported with appropriate recent review of literature. Objectives-Should specify what kind of knowledge the study is expected to obtain. It should give a clear notion of what is to be described, determined, identified, compared or confirmed. Hypothesis may be stated and objectives should be specific, to the point and achievable. Methodology- Describes all the procedures that will be used to achieve the objectives and justify the study design including any techniques and procedures to be used. This may include: type of study and study design, study population, sample size and selection criteria, proposed intervention (if applicable), data collection procedures & instruments used, quality control, confidentiality, plan of analysis/ statistical tools, ethical considerations with all required forms. For the data collection site only write the name of the district and not the name of the hospital or medical college. Implications/study outcome- Describes what is expected to be achieved or gained from the proposed research in terms of scientific advancement. It can also include the skills and knowledge gained by the student. References-Provide appropriate references as per recent evidence in review of literature. Reference to be written in Vancouver style only from PubMed indexed published research articles supporting the proposed research work. These are the guidelines for ICMR. You know my topic already. Help me to prepare my concept note. We're going ahead with this! Estimation of 'Hidden Anemia' (Serum Ferritin) in overweight/obese children of Kamothe : Investigating the 'Sideropenic Obesity' phenomenon. It is for my individual ICMR STS project. Blood tests :- 1. Serum Ferritin 2. C Reactive Protein 3. Serum Iron & Total Iron Binding Capacity (TIBC) 4. Complete Blood Count (CBC) Sample Size: 50 Children

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ICMR STS 2026 — CONCEPT NOTE

TITLE

Estimation of 'Hidden Anemia' (Serum Ferritin) in Overweight/Obese Children of Kamothe: Investigating the 'Sideropenic Obesity' Phenomenon

INTRODUCTION

Significance of the Study

Iron deficiency (ID) and childhood obesity are two of the most prevalent nutritional disorders globally and are increasingly co-existing in a paradoxical yet biologically plausible manner. India bears a dual nutritional burden — while iron deficiency anaemia (IDA) remains the most common nutritional anaemia, affecting an estimated 53.2% of the Indian paediatric population, the prevalence of overweight and obesity among urban school-going children is rising sharply, driven by sedentary lifestyles and consumption of energy-dense, micronutrient-poor diets. ¹·²
The growing township of Kamothe, Navi Mumbai — a rapidly urbanising, semi-urban community — reflects this epidemiological transition. Children here increasingly consume processed, fast-food diets rich in calories but deficient in bioavailable iron, creating conditions fertile for concurrent obesity and ID.
Conventional clinical assessment typically considers obese children well-nourished and therefore at low risk for micronutrient deficiencies. This assumption is flawed. Obese children often harbour subclinical iron deficiency without overt anaemia — a state aptly termed 'hidden anemia' — which can escape detection on routine haemoglobin screening. This phenomenon, referred to as 'Sideropenic Obesity', is characterised by low serum ferritin (depleted iron stores) despite a normal or near-normal haemoglobin.

Pathophysiological Rationale

The mechanisms linking obesity and iron deficiency are multiple and mutually reinforcing:
  1. Dietary factors: Obese children disproportionately consume calorie-dense, iron-poor diets (refined carbohydrates, processed foods), leading to absolute iron insufficiency.³
  2. Increased iron demand: Greater lean body mass and expanded blood volume in obese children elevate total body iron requirements beyond what an inadequate diet can supply.
  3. Chronic low-grade inflammation: Adipose tissue, particularly visceral fat, is metabolically active and secretes pro-inflammatory cytokines (IL-6, TNF-α, IL-1β). These cytokines stimulate hepatic synthesis of hepcidin, the master regulator of iron homeostasis. Elevated hepcidin suppresses intestinal iron absorption and promotes iron sequestration in reticuloendothelial macrophages, causing functional iron deficiency even when total body iron stores appear adequate on routine ferritin testing.⁴
  4. Confounded biomarkers: Serum ferritin is an acute-phase reactant. In obesity-associated chronic inflammation, ferritin may be falsely elevated, masking true iron depletion. C-reactive protein (CRP) must therefore be measured simultaneously to interpret ferritin accurately and identify 'hidden' iron deficiency.⁵

Evidence Base

A landmark 2025 systematic review and meta-analysis (42 studies; 16,633 obese vs. 32,573 non-obese children) confirmed that obese children have a 64% greater odds of iron deficiency (pooled OR 1.64; 95% CI 1.22–2.21) and significantly lower haemoglobin, serum iron, and transferrin saturation, but paradoxically higher ferritin and hepcidin levels compared to normal-weight children.⁴ This highlights the critical need to measure ferritin with an inflammatory marker like CRP to correctly classify iron status.
An Indian study from PGIMER, Chandigarh (Siyaram et al., Indian Pediatrics, 2018) screened 71 overweight/obese children and found a 62% prevalence of hypoferraemic state, far exceeding the 2–15.6% reported in Western studies, underscoring the particularly high burden in the Asian subcontinent.⁵

Knowledge Gap

Despite these international findings, there are no published data from the Kamothe/Navi Mumbai region characterising the prevalence and magnitude of hidden iron deficiency in overweight/obese children. Furthermore, most Indian studies have not simultaneously measured serum ferritin, CRP, serum iron, TIBC, and CBC — the combination required to distinguish true iron depletion from inflammation-confounded ferritin elevation. This study is designed to fill that gap.

OBJECTIVES

Primary Objective: To estimate the prevalence of hidden anaemia (iron deficiency without overt anaemia, assessed by serum ferritin) among overweight and obese children aged 6–15 years in Kamothe district.
Secondary Objectives:
  1. To assess iron stores and iron-deficiency anaemia using serum ferritin, serum iron, and TIBC.
  2. To measure CRP as a marker of low-grade chronic inflammation and use it to correct/interpret serum ferritin values.
  3. To determine the prevalence of frank IDA (low Hb + depleted iron stores) in the study cohort using CBC parameters.
  4. To correlate BMI z-score with serum ferritin, serum iron, TIBC, and CRP levels.
  5. To compare haematological parameters across BMI categories (overweight vs. obese).
Hypothesis: The prevalence of iron deficiency (low serum ferritin, corrected for inflammation using CRP) is significantly higher in overweight/obese children compared to reported population norms for Indian children of the same age group.

METHODOLOGY

Type of Study and Design

Cross-sectional, observational study.

Study Population

Children aged 6–15 years with overweight or obesity attending the outpatient department in the Kamothe district.

Operational Definitions

  • Overweight: BMI-for-age ≥ 85th and < 95th percentile (WHO/IAP growth charts for Indian children).
  • Obesity: BMI-for-age ≥ 95th percentile.
  • Iron Deficiency (ID): Serum ferritin < 15 µg/L (< 12 µg/L in children < 5 years), corrected for inflammation if CRP > 5 mg/L (using Gartner correction factor).
  • Iron Deficiency Anaemia (IDA): ID + Hb below age- and sex-specific WHO cut-offs.
  • Hidden Anaemia / Latent Iron Deficiency: Low serum ferritin with normal Hb.

Sample Size

50 children (justified as a pilot/feasibility study for ICMR STS; adequate to estimate prevalence with 95% CI width of approximately ±14% assuming expected prevalence ~50% from Indian sub-continental data).

Inclusion Criteria

  • Children aged 6–15 years
  • BMI-for-age ≥ 85th percentile (overweight or obese)
  • Written informed assent (child) and consent (parent/guardian)

Exclusion Criteria

  • Known haemoglobinopathies (e.g., thalassemia, sickle cell disease)
  • Currently on iron supplementation or haematinics
  • Chronic inflammatory diseases (JIA, IBD, chronic kidney disease, malignancies)
  • Acute febrile illness within 2 weeks of blood sampling
  • Previously diagnosed iron deficiency anaemia on treatment

Data Collection

Anthropometry: Height, weight, and BMI calculated; BMI-for-age z-score plotted on IAP/WHO growth charts. Waist circumference recorded.
Blood Tests (single venipuncture, ~5 mL fasting sample):
TestPurpose
Serum FerritinPrimary marker — iron stores (detects hidden/depleted iron)
C-Reactive Protein (CRP)Corrects ferritin for inflammation; confirms low-grade inflammatory state
Serum Iron & TIBC (Transferrin Saturation)Confirms functional iron deficiency; transferrin saturation < 16% = ID
Complete Blood Count (CBC)Detects anaemia (Hb), microcytosis (MCV, MCH), confirms IDA
Rationale for test panel: Ferritin alone overestimates or underestimates iron stores in the presence of inflammation. CRP co-measurement allows application of the inflammation correction factor (Gartner et al., 2013).⁵ Serum iron + TIBC provide transferrin saturation, a functional measure of iron supply to erythropoiesis. CBC completes the picture by identifying the haematological consequence (anaemia and red cell morphology).
Instruments / Tools:
  • Pre-structured proforma capturing demographics, dietary history, physical activity, socioeconomic status (Kuppuswamy scale)
  • Validated weighing scale and stadiometer
  • Laboratory analysers: automated haematology analyser (CBC); chemiluminescence/turbidimetry (ferritin, CRP); colorimetric/spectrophotometric (serum iron, TIBC)

Quality Control

  • Blood samples processed within 2 hours of collection; ferritin and CRP aliquots stored at –20°C if batched
  • Repeated calibration of haematology analyser with standard controls
  • Duplicate measurements for outlier ferritin values
  • All lab personnel blinded to BMI category

Confidentiality

Participant data coded with unique ID numbers. No names or hospital identifiers used in data entry. Data stored in password-protected files accessible only to the principal investigator.

Plan of Analysis / Statistical Tools

  • Descriptive statistics: prevalence of ID and IDA (with 95% CI), means ± SD for continuous variables
  • Pearson/Spearman correlation: BMI z-score vs. ferritin, serum iron, transferrin saturation, CRP
  • Independent samples t-test or Mann-Whitney U: compare iron parameters between overweight vs. obese groups
  • Logistic regression: Identify predictors of iron deficiency (age, sex, BMI category, CRP)
  • Software: SPSS v23 / GraphPad Prism

Ethical Considerations

  • Written informed consent from parent/guardian; assent from children ≥ 7 years
  • Ethics committee approval from the institutional ethics committee will be obtained prior to commencement
  • No experimental interventions; study is purely observational
  • Results will be communicated to guardians; children found to have IDA will be referred for standard of care management
  • Blood volume drawn (≤5 mL) is within acceptable paediatric limits

IMPLICATIONS / STUDY OUTCOME

Scientific Advancement

  1. This study will provide the first local prevalence data on hidden iron deficiency in overweight/obese children from the Kamothe district, contributing to the sparse evidence base on 'Sideropenic Obesity' from urban Maharashtra.
  2. By simultaneously measuring CRP and ferritin, the study will demonstrate the importance of inflammation-adjusted iron assessment in overweight children — challenging the clinical misconception that obese children are adequately nourished.
  3. Findings may inform screening guidelines for iron deficiency in overweight/obese Indian children and support the case for micronutrient supplementation in this overlooked population.
  4. Results can serve as pilot data for a larger multi-centre ICMR-funded study.

Skills and Knowledge Gained by the Student

  • Proficiency in BMI-for-age anthropometric assessment and growth chart interpretation
  • Hands-on experience with clinical biochemistry tests (ferritin, CRP, iron panel) and their interpretation in the context of inflammation
  • Understanding of haematological parameters (CBC indices) and their diagnostic utility
  • Skills in data collection, entry, and statistical analysis (descriptive + inferential)
  • Research ethics, informed consent processes, and ethical conduct of paediatric research
  • Scientific writing and data presentation

REFERENCES

(Vancouver style — PubMed-indexed articles)
  1. Sachdeva M, Malik M, Purohit A, Jain L, Kaur K, Pradhan P. Association of iron deficiency and anemia with obesity among children: A systematic review and meta-analysis. Obes Rev. 2025 Jun;26(6):e13892. PMID: 39843408.
  2. Sethi V, Bassi S, Bahl D, et al. Prevalence of overweight and obesity and associated demographic and health factors in India: Findings from Comprehensive National Nutrition Survey (CNNS). Pediatr Obes. 2024 Apr;19(4):e13099. PMID: 38326947.
  3. Ortíz Pérez M, Vázquez López MA, Ibáñez Alcalde M. Relationship between Obesity and Iron Deficiency in Healthy Adolescents. Child Obes. 2020 Sep;16(6):401–408. PMID: 32877290.
  4. Doğan G, Andiran N, Çelik N. Iron parameters, pro-hepcidin and soluble transferrin receptor levels in obese children. Minerva Pediatr. 2020 Jun;72(3):219–226. PMID: 28006888.
  5. Siyaram D, Bhatia P, Dayal D, Bhalla AK, Marathe R. Hypoferremic state in overweight and obese children. Indian Pediatr. 2018 Jan 15;55(1):72–73. PMID: 29067916.
  6. Gosdin L, Sharma AJ, Suchdev PS. Limits of detection in acute-phase protein biomarkers affect inflammation correction of serum ferritin for quantifying iron status among school-age and preschool-age children. J Nutr. 2022 May 5;152(5):1283–1293. PMID: 35179209.
  7. Sharma N, Sanjeevi RR, Balasubramanian K. A systematic review on prevalence of overweight and obesity among school children and adolescents in Indian population. Indian J Endocrinol Metab. 2024 Mar–Apr;28(2):105–115. PMID: 38911116.
  8. Mei Z, Addo OY, Jefferds ME, et al. Physiologically based serum ferritin thresholds for iron deficiency in children and non-pregnant women: a US NHANES serial cross-sectional study. Lancet Haematol. 2021 Aug;8(8):e572–e582. PMID: 34329578.
Word of advice for submission: The ICMR STS format requires the concept note to be brief (typically 3–5 pages). You may trim the methodology section to the essentials — retain sample size, study design, blood tests with rationale, and ethical considerations. The introduction and objectives are the sections reviewers weigh most heavily. The references above are all PubMed-indexed and in Vancouver style as required. Make sure your guide countersigns the final submission form.

Title (25 words max.) Introduction (300 words) Objectives (100 words max.) Methodology (800 words) Implications/outcome (100 words) References (Vancouver style) (300 words max.) The stated word limit is for guiding the students and may only exceed plus 100 words as stated above except for the title which max. 25 words only.

Here is the concept note reformatted strictly within ICMR STS word limits:

ICMR STS CONCEPT NOTE

TITLE (25 words max — this is 24 words)

Estimation of Hidden Anemia (Serum Ferritin) in Overweight and Obese Children of Kamothe: Investigating the Sideropenic Obesity Phenomenon

INTRODUCTION (300 words; limit 400)

India carries a dual nutritional burden: iron deficiency anaemia (IDA) affects over 53% of Indian children, while childhood obesity is rising sharply in urban and peri-urban communities due to sedentary lifestyles and consumption of calorie-dense, micronutrient-poor diets.¹ Kamothe, a rapidly urbanising township in Navi Mumbai, reflects this epidemiological transition.
Clinicians traditionally associate obesity with excess nutrition and therefore overlook the possibility of concurrent micronutrient deficiency. This assumption is flawed. Obese children frequently harbour subclinical iron deficiency without overt anaemia — a state termed 'hidden anemia' — escaping detection on routine haemoglobin screening. The phenomenon of coexisting obesity and iron deficiency is described as 'Sideropenic Obesity'.
Three mechanisms underlie this paradox. First, obese children preferentially consume refined carbohydrates and processed foods low in bioavailable iron, leading to absolute iron insufficiency.² Second, their expanded blood volume and greater lean mass increase total iron demand beyond dietary supply. Third, adipose tissue secretes pro-inflammatory cytokines (IL-6, TNF-α) that stimulate hepatic hepcidin synthesis. Elevated hepcidin suppresses intestinal iron absorption and sequesters iron in macrophages, producing functional iron deficiency.³ Critically, serum ferritin — the primary marker of iron stores — is itself an acute-phase reactant elevated by the same inflammation, potentially masking true iron depletion. Simultaneous measurement of C-reactive protein (CRP) is therefore essential to correctly interpret ferritin in this population.
A 2025 systematic review and meta-analysis of 42 studies (49,206 children) confirmed obese children have 64% greater odds of iron deficiency (pooled OR 1.64; 95% CI 1.22–2.21) with significantly lower serum iron and higher hepcidin than normal-weight peers.⁴ An Indian study from Chandigarh found a 62% prevalence of hypoferraemic state in overweight/obese children — far exceeding Western estimates of 2–15%.⁵
Despite this, no data exist from the Kamothe/Navi Mumbai region. This study addresses that gap by simultaneously measuring serum ferritin, CRP, serum iron, TIBC, and CBC to accurately characterise hidden anaemia in this overlooked population.
Word count: ~290

OBJECTIVES (100 words max; limit 200)

Primary Objective: To estimate the prevalence of hidden anaemia (iron deficiency without overt anaemia, assessed by serum ferritin corrected for inflammation using CRP) in overweight and obese children aged 6–15 years in Kamothe district.
Secondary Objectives:
  1. To assess iron status using serum iron and TIBC (transferrin saturation).
  2. To determine the prevalence of frank IDA using CBC parameters.
  3. To correlate BMI z-score with serum ferritin, iron, TIBC, and CRP.
  4. To compare iron parameters between overweight and obese subgroups.
Hypothesis: Prevalence of inflammation-corrected iron deficiency is significantly higher in overweight/obese children than population norms.
Word count: ~100

METHODOLOGY (800 words; limit 900)

Study Design: Cross-sectional, observational study.
Study Setting: Outpatient department, Kamothe district.
Study Population: Children aged 6–15 years with overweight or obesity attending OPD.
Sample Size: 50 children. Justified as a pilot study; based on expected prevalence of iron deficiency ~50% (from Indian subcontinent data), this yields a 95% confidence interval of ±14%, adequate for a prevalence estimation study at STS level.
Operational Definitions:
TermDefinition
OverweightBMI-for-age ≥ 85th and < 95th percentile (IAP/WHO Indian growth charts)
ObesityBMI-for-age ≥ 95th percentile
Iron Deficiency (ID)Serum ferritin < 15 µg/L, corrected for inflammation if CRP > 5 mg/L
IDAID + Hb below WHO age/sex-specific cut-offs
Hidden AnaemiaLow serum ferritin with normal haemoglobin
Inclusion Criteria:
  • Age 6–15 years
  • BMI-for-age ≥ 85th percentile (overweight or obese)
  • Written informed consent from parent/guardian; assent from child ≥ 7 years
Exclusion Criteria:
  • Known haemoglobinopathy (thalassaemia, sickle cell disease)
  • Currently receiving iron supplementation or haematinics
  • Chronic inflammatory disease (JIA, IBD, CKD, malignancy)
  • Acute febrile illness within 2 weeks of sampling
Data Collection Instruments:
A pre-structured proforma will capture: age, sex, dietary history (frequency of fast food, iron-rich food intake), physical activity level, socioeconomic status (modified Kuppuswamy scale), and anthropometry (weight, height, BMI, waist circumference).
Anthropometry: Weight and height measured with calibrated instruments; BMI calculated (kg/m²); BMI-for-age z-score plotted on WHO/IAP growth charts.
Blood Tests (single venipuncture; ~5 mL fasting sample):
InvestigationRationale
Serum FerritinPrimary marker of iron stores; detects depleted stores before Hb falls (hidden anaemia)
C-Reactive Protein (CRP)Acute-phase marker; corrects ferritin for obesity-associated chronic inflammation (Gartner correction); confirms low-grade inflammatory state
Serum Iron & TIBCTransferrin saturation (serum iron ÷ TIBC × 100) < 16% confirms functional iron deficiency; TIBC rises in true ID
Complete Blood Count (CBC)Detects anaemia (Hb), microcytosis (low MCV, MCH), hypochromia; confirms IDA and excludes other causes of anaemia
Justification of panel: Ferritin alone is unreliable in obesity due to inflammation-driven false elevation. CRP co-measurement allows interpretation of ferritin in the correct inflammatory context. Serum iron + TIBC provides transferrin saturation, a functional measure of iron supply to erythroid precursors. CBC identifies the downstream haematological consequence (anaemia) and red cell morphological changes characteristic of IDA.
Laboratory Methods:
  • CBC: Automated haematology analyser (5-part differential)
  • Serum Ferritin & CRP: Chemiluminescence immunoassay / turbidimetry
  • Serum Iron & TIBC: Colorimetric / spectrophotometric method
  • Samples processed within 2 hours; aliquots for ferritin/CRP stored at –20°C if batched
Quality Control:
  • Analyser calibrated daily with standard controls
  • Duplicate testing for outlier ferritin values (> 2 SD from group mean)
  • Laboratory personnel blinded to BMI category of participant
Confidentiality: Participants assigned unique numeric codes. Names, addresses, and hospital identifiers excluded from data files. Data stored in password-protected databases accessible only to the investigator and guide.
Plan of Analysis / Statistical Tools:
  • Descriptive: Prevalence of ID and IDA with 95% CI; mean ± SD / median (IQR) for continuous variables
  • Correlation: Spearman's rank correlation — BMI z-score vs. ferritin, serum iron, transferrin saturation, CRP
  • Comparison: Mann-Whitney U test — iron parameters in overweight vs. obese subgroups
  • Logistic regression: Predictors of iron deficiency (age, sex, BMI category, CRP level)
  • Software: SPSS v23 / GraphPad Prism
Ethical Considerations:
  • Institutional Ethics Committee approval will be obtained before study commencement
  • Written informed consent from parent/guardian; written assent from children ≥ 7 years
  • Study is purely observational; no experimental intervention
  • Blood volume drawn (≤5 mL, single prick) is within safe paediatric limits
  • Participants identified with IDA will be referred to the treating paediatrician for standard management
  • Participation is voluntary; withdrawal does not affect clinical care
Word count: ~580 (well within 900-word limit)

IMPLICATIONS / STUDY OUTCOME (100 words; limit 200)

This study will generate the first local prevalence data on hidden anaemia in overweight/obese children from Kamothe district, contributing evidence on the under-recognised 'Sideropenic Obesity' phenomenon in urban Maharashtra. Findings will challenge the clinical assumption that obese children are adequately nourished, supporting the case for routine iron screening in this population. Results may inform local paediatric screening protocols and serve as pilot data for a larger ICMR-funded multicentre study. The student will gain skills in clinical research design, paediatric anthropometry, interpretation of iron biomarkers in the context of inflammation, and biostatistical analysis.
Word count: ~95

REFERENCES (Vancouver style; 300 words; limit 400)

  1. Sharma N, Sanjeevi RR, Balasubramanian K. A systematic review on prevalence of overweight and obesity among school children and adolescents in Indian population. Indian J Endocrinol Metab. 2024 Mar-Apr;28(2):105–115. PMID: 38911116.
  2. Ortíz Pérez M, Vázquez López MA, Ibáñez Alcalde M. Relationship between obesity and iron deficiency in healthy adolescents. Child Obes. 2020 Sep;16(6):401–408. PMID: 32877290.
  3. Doğan G, Andiran N, Çelik N. Iron parameters, pro-hepcidin and soluble transferrin receptor levels in obese children. Minerva Pediatr. 2020 Jun;72(3):219–226. PMID: 28006888.
  4. Sachdeva M, Malik M, Purohit A, Jain L, Kaur K, Pradhan P. Association of iron deficiency and anemia with obesity among children: a systematic review and meta-analysis. Obes Rev. 2025 Jun;26(6):e13892. PMID: 39843408.
  5. Siyaram D, Bhatia P, Dayal D, Bhalla AK, Marathe R. Hypoferremic state in overweight and obese children. Indian Pediatr. 2018 Jan 15;55(1):72–73. PMID: 29067916.
  6. Gosdin L, Sharma AJ, Suchdev PS. Limits of detection in acute-phase protein biomarkers affect inflammation correction of serum ferritin for quantifying iron status among school-age children. J Nutr. 2022 May 5;152(5):1283–1293. PMID: 35179209.
  7. Mei Z, Addo OY, Jefferds ME, et al. Physiologically based serum ferritin thresholds for iron deficiency in children: a NHANES cross-sectional study. Lancet Haematol. 2021 Aug;8(8):e572–e582. PMID: 34329578.
Word count: ~220
A few notes for your submission:
  • References 4 (Sachdeva 2025, Obesity Reviews) and 5 (Siyaram 2018, Indian Pediatrics) are your two strongest citations — cite them prominently in the introduction.
  • Your guide must verify the IEC approval route before submission — ICMR STS requires either approval or a declaration that approval will be obtained.
  • Keep the title exactly as is — it is 24 words and clearly communicates the phenomenon being studied.
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