Anemia is a hematological disorder characterized by a reduction in red blood cells or hemoglobin concentration, leading to impaired oxygen transport and compromised physiological function [1]. It can arise from a variety of causes, including deficiencies in iron, vitamin B12, and vitamin A; parasitic infections; and inherited blood disorders [2]. Iron deficiency is the most common cause, as it disrupts hemoglobin synthesis. Similarly, vitamin B12 deficiency impairs red blood cell maturation, resulting in ineffective erythropoiesis [3]. The World Health Organization (WHO) classifies anemia in non-pregnant adolescents based on hemoglobin levels: mild (11.0–11.9 g/dL), moderate (8.0–10.9 g/dL), and severe (<8.0 g/dL) [4].

Anemia remains a major global public health concern, particularly affecting vulnerable populations. Worldwide, it impacts approximately 40% of children aged 6–59 months, 37% of pregnant women, and 30% of women aged 15–49 years [4]. Among adolescents, prevalence rates are considerably higher in developing countries (27%) compared to developed nations (6%) [5]. India, with an estimated 253 million adolescents aged 10–19 years, lacks comprehensive national data for this age group. The National Family Health Survey (NFHS) provides data only for adolescents aged 15–19 years, showing a rise in anemia prevalence among females—from 55.8% in 2005–06 to 59.1% in 2019–21—and a slight increase among males, from 30.2% to 31.1% [6]. In Cameroon, the 2018 Demographic and Health Survey reported a 71.4% prevalence among adolescents aged 12–17 years, with moderate anemia being most common [7].

Adolescents are particularly susceptible to anemia due to the rapid physical growth and hormonal changes that occur during puberty. These physiological changes increase iron requirements for hemoglobin and myoglobin synthesis [8,9]. Anemia during this critical stage can impair physical growth, cognitive development, academic performance, and overall health. Its consequences often persist into adulthood, particularly affecting reproductive health and productivity [10–12]. Additionally, anemia-associated cognitive impairments and reduced work capacity contribute to broader socioeconomic losses [13,14].

The prevalence and severity of anemia among adolescents vary by region. For example, a study in Agra reported a prevalence of 43.3% among school-going adolescents [15], while a rural study in Uttar Pradesh found a higher rate of 60.66%, with moderate anemia being most common [16]. Multiple factors contribute to adolescent anemia, including age, socioeconomic status, dietary diversity, stunting, and parasitic infections—especially malaria [17–19]. Other contributing factors include heavy menstrual bleeding and inadequate intake of iron-rich foods, such as liver and green leafy vegetables [20].

To address this global burden, the World Health Assembly has set a target to reduce anemia prevalence by 50% by 2025 [21]. Despite ongoing interventions, anemia remains a persistent nutritional challenge in low- and middle-income countries [16,19]. Its long-term impact on health, cognitive development, and reproductive outcomes makes it a critical public health priority [10–12,22].

Improving adolescent nutrition and health is essential not only for individual well-being and academic achievement but also for the health of future generations and overall societal development [23]. However, most public health programs and research have traditionally focused on children under five and women of reproductive age, often overlooking the specific needs of school-going adolescents. This study aims to bridge that gap by evaluating the determinants of anemia among school-going adolescents, with the goal of informing targeted and evidence-based interventions.

Study Design and Type

This study was a prospective, cross-sectional observational study aimed at assessing anemia among school-going adolescents.

Study Setting and Period

The study was conducted in three schools located in proximity to FH Medical College and Hospital, Agra. Data collection extended over a period of eighteen months, from May 2023 to December 2024.

Study Population

The target population consisted of adolescents aged 10 to 19 years attending classes 6th through 12th in the selected schools. Inclusion criteria required written informed consent from parents or legal guardians. Adolescents with a history of blood transfusion, congenital anomalies, or whose parents did not provide consent were excluded from the study.

Sampling Procedure

A multistage random sampling technique was used to ensure representative selection across all grades. Eligible students were randomly selected from classes VI to XII, yielding a total sample size of 700. Ethical approval was obtained from the Institutional Ethics Committee prior to the study, and informed consent was secured from parents through school distribution.

Data Collection Instruments and Procedure

Data were collected using a structured interview to obtain socio-demographic information, including age, sex, religion, family structure, parental education, socioeconomic status (Modified Kuppuswamy scale), dietary habits, and anemia-related symptoms. For female participants, menstrual history including age at menarche and presence of menorrhagia was recorded.

Anthropometric measurements were taken using standardized procedures. Weight was measured with a calibrated digital scale and height with a stadiometer. BMI was calculated as weight (kg) divided by height in meters squared (m²) and categorized using age- and sex-specific percentiles: underweight (<5th percentile), overweight (>85th percentile), and obesity (>95th percentile).

A thorough general and systemic examination was conducted, including pallor assessment graded according to WHO criteria.

Blood Sample Collection and Hematological Analysis

Following informed consent, 1 mL of venous blood was collected into EDTA-containing tubes and promptly transported to the laboratory. Hematological parameters were analyzed using the COULTER Ac.T. DIFF™ Analyzer (SUN Diagnostics), an automated cell counter operating on the principle of electrical impedance. The analyzer required only 12 µL of blood per test and measured hemoglobin concentration, hematocrit, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), red blood cell (RBC) count, total white blood cell (WBC) count, and platelet count.

Peripheral blood smears were also prepared and examined microscopically to assess red blood cell morphology.

Definitions and Grading of Anemia

Anemia was defined and graded based on WHO guidelines for adolescents as follows: hemoglobin <11.5 g/dL indicating anemia, with severity categorized as mild (10–11.4 g/dL), moderate (7–9.9 g/dL), and severe (<7 g/dL). [4]

Data Management and Statistical Analysis

Data were entered in Microsoft Excel and analyzed using SPSS version 23.0. The normality of continuous variables was assessed using the Shapiro-Wilk test. Normally distributed variables were summarized as mean ± standard deviation (SD), while non-normally distributed data were presented as median with interquartile range (IQR). Group comparisons were conducted using the student’s t-test or Mann–Whitney U test for continuous variables, and Chi-square test or Fisher’s exact test for categorical variables. A p-value <0.05 was considered statistically significant. Data visualization included pie charts, bar graphs, and histograms to present findings effectively.

Table-2:  Severity of Anemia in study population

Table 2 illustrates the severity of anaemia in the study population (N = 700). A total of 419 participants (59.86%) had normal haemoglobin levels. Among anaemic individuals, 143 (20.42%) had mild anaemia and 138 (19.71%) had moderate anaemia. No cases of severe anaemia were observed. These results indicate a high prevalence of anaemia, predominantly of mild to moderate severity, with no evidence of critical anaemia in this cohort.

Table-3:  Peripheral Smear picture in study population

Table 3 presents the peripheral smear findings in anaemic participants (n = 281; 40.15% of the total sample). The most common morphology was hypochromic microcytic anaemia (n = 164; 23.42%), indicative of iron deficiency. Macrocytic normochromic anaemia was observed in 83 cases (11.85%), suggestive of vitamin B12 or folate deficiency, while normocytic normochromic anaemia was seen in 34 cases (4.85%), commonly associated with chronic disease or acute blood loss. These findings facilitated morphological classification of anaemia in the study cohort.

Table 4: Distribution of Anaemia According to Age, Socio-Economic Status, Residence, and Gender

Table 4 details anaemia distribution across age, socio-economic status, residence, and gender. No significant association was observed with age (χ² = 1.92, p = 0.38) or residence (χ² = 0.02, p = 0.99), indicating uniform prevalence across these groups. While females had a higher anaemia prevalence (44.65%) compared to males (34.96%), the difference was not statistically significant (χ² = 6.79, p = 0.09). A significant association was found with socio-economic status (χ² = 67.10, p < 0.001), with the highest prevalence in lower classes (Class V: 30.60%; Class IV: 26.69%) and lowest in higher classes (Class II: 18.86%). These findings highlight socio-economic status as a key determinant of anaemia, likely reflecting disparities in nutrition, healthcare access, and health awareness.

Table-5.: Distribution of Anaemic females according to menarche status.

Table 5 presents the distribution of anaemic females by menarche status across age groups. Among participants aged 10–13 years (n = 108), 11 (10.37%) had attained menarche. In the 14–16 age group (n = 142), 140 (98.59%) had experienced menarche, and all participants aged 17–19 years (n = 124) had attained menarche (100%). This trend reflects normal pubertal progression, with near-universal menarche by mid to late adolescence.

Table-6: Distribution of Anaemia According to Menstrual, Dietary, Supplementation & Socio-Demographic History.

The study assessed the association of anaemia with demographic, nutritional, and behavioral factors in adolescents. Anaemia was significantly associated with a history of menorrhagia (χ² = 2.85, p < 0.0001) and undernutrition (χ² = 31.56, p < 0.0001), indicating menstrual blood loss and low nutritional status as key contributors. No significant associations were observed with Weekly Iron and Folic Acid Supplementation (WIFS) (p = 0.12), deworming status (p = 0.37), dietary pattern (p = 0.15), junk food consumption (p = 0.17), or maternal education (p = 0.07). These findings underscore the influence of biological and nutritional factors in anaemia, while lifestyle and educational factors may warrant further exploration.

According to the National Family Health Survey (NFHS-5, 2019–2021), anaemia affects 25% of Indian men and 57% of women aged 15–49 years. Among adolescents aged 15–19 years, prevalence is reported at 31.1% in boys and 59.1% in girls [24]. The present study assessed anaemia among adolescents aged 10–19 years, focusing on demographic and socio-economic determinants. The overall prevalence was 40.15%, indicating that nearly two in five adolescents were anaemic. This aligns with findings from states such as Bihar and Uttar Pradesh, where rates of 32.7% in boys and 62% in girls have been documented [25]. Consistently, our study found a higher prevalence among girls (53.4%) compared to boys (46.5%).

With respect to severity, the majority of anaemic participants had mild (20.42%) or moderate (19.71%) anaemia, while no cases of severe anaemia were detected. This pattern suggests a widespread but largely non-critical burden. The absence of severe cases may reflect relatively better nutritional status or healthcare access within the study population. Nonetheless, even mild-to-moderate anaemia can negatively affect growth, cognitive function, and academic performance during adolescence, underscoring the importance of early and sustained intervention. Similar variability in severity has been reported by Mbou AS et al. (2023), indicating that contextual factors significantly influence anaemia burden [26].

Peripheral smear findings showed hypochromic microcytic anaemia as the predominant morphological type (23.42%), strongly suggesting iron deficiency as the principal cause. Less common patterns included macrocytic normochromic (11.85%), likely due to vitamin B12 or folate deficiency, and normocytic normochromic anaemia (4.85%), commonly associated with chronic disease or acute blood loss. These results are consistent with previous studies. For example, Ramana Sastry CPV (2017) reported 9.09% normocytic normochromic anaemia [27], while Khan MA et al. (2024) observed 52.0% microcytic hypochromic, 7.6% macrocytic, and 1.79% dimorphic patterns among adolescents [28].

Demographic variables such as age group (p = 0.38) and residence (urban vs. rural, p = 0.99) showed no significant association with anaemia, suggesting a relatively uniform distribution across these strata. In contrast, socio-economic status was significantly associated with anaemia prevalence (p < 0.001), with higher rates among adolescents from lower socio-economic classes (Class IV and V). This association likely reflects disparities in nutrition, healthcare access, and health awareness. These findings are supported by existing literature, including Agarwal RH et al. (2024), who reported comparable anaemia rates in urban (29.8%) and rural (30.5%) adolescents [29]. Other studies have reported rural prevalence ranging from 42.8% to 48.6% [29,30], while research from Chandigarh revealed distinct urban-rural differences (14.2% vs. 25.4%) [31].

Among female adolescents, menarche was significantly associated with anaemia prevalence. Nearly all girls aged 14 and above had attained menarche, and anaemia was more common post-menarche, likely due to increased iron demands during menstruation [26,29]. Additionally, a history of menorrhagia was strongly associated with anaemia (p < 0.0001), highlighting the impact of menstrual blood loss on iron status.

Lastly, participation in the Weekly Iron and Folic Acid Supplementation (WIFS) programme was inversely associated with anaemia prevalence, suggesting a protective effect. Adolescents not enrolled in WIFS had significantly higher rates of anaemia, reinforcing the importance of such school-based interventions during this critical developmental period.

This study identified a high prevalence of anemia (40.15%) among adolescents, primarily mild (20.42%) or moderate (19.71%) in severity, with no severe cases detected. Peripheral smear findings showed hypochromic microcytic anemia as the predominant pattern, indicating iron deficiency as the leading cause. Sociodemographic analysis revealed a significant association between anemia and lower socioeconomic status, particularly among adolescents in Class IV and V income groups, while age, gender, and residence were not significantly correlated

Given this substantial burden and socioeconomic disparity, immediate public health strategies are essential to prevent anemia’s adverse effects on physical growth and cognitive development. We recommend implementing school-based anemia screening programs combined with nutrition education and iron supplementation, alongside community awareness campaigns targeting low-income families. An integrated school- and community-level approach is critical to reducing anemia prevalence and improving adolescent health and well-being in the region.

Study Limitations and Strengths

This cross-sectional study design limits causal inference and the determination of temporal relationships. The use of self-reported data may have introduced recall bias. Key etiological factors, including malaria, hemoglobinopathies, and other infections, were not assessed. The absence of biochemical assays further limits diagnostic precision.

However, the study's large sample size (N = 700) enhances statistical validity. Peripheral smear analysis offered morphological insights, and significant associations with socio-economic status and menstrual history highlight relevant risk factors. The predominance of mild to moderate iron-deficiency anemia underscores the need for targeted interventions, including nutritional education, iron supplementation, and menstrual health programs.

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