Iron Deficiency Anemia (IDA) is a prevalent nutritional deficiency that has significant public health implications globally, particularly in developing regions. Anemia, characterized by insufficient levels of hemoglobin in the blood, impairs oxygen transport and can lead to various health complications, including fatigue, impaired cognitive development, and decreased physical performance. Among the various forms of anemia, iron deficiency anemia is the most common and is particularly concerning in vulnerable populations such as adolescent girls1.

Adolescence is a critical period marked by rapid growth and development, increasing the demand for iron. For girls, the onset of menstruation further exacerbates their iron requirements, making them particularly susceptible to iron deficiency2. The prevalence of IDA in adolescent girls can have far-reaching effects on their overall health, educational attainment, and quality of life. In regions where nutritional and healthcare resources are limited, such as in Anantnag district of Jammu and Kashmir (J&K), the prevalence of IDA could be higher and more pronounced3. Anantnag, a district located in the southern part of Jammu and Kashmir, is characterized by its diverse socio-economic conditions and varying levels of access to healthcare services. The region faces unique challenges related to geographical remoteness, economic constraints, and fluctuating political stability, which can impact nutritional intake and health outcomes. Traditional dietary habits, combined with contemporary food practices, shape the eating behaviors of adolescents in this region. Factors such as local agricultural practices, cultural influences, and economic conditions contribute to the dietary landscape in Anantnag. Despite these challenges, there is a paucity of comprehensive data on the prevalence of IDA among adolescent girls in this region. Despite the importance of this issue, there is a significant gap in data regarding the dietary patterns of adolescent girls in Anantnag. Understanding these patterns requires a comprehensive assessment of food consumption habits, meal frequency, and nutritional knowledge. This information is crucial for identifying dietary deficiencies and areas for improvement, as well as for guiding public health initiatives aimed at enhancing nutritional status and overall well-being4.

Understanding the prevalence of IDA in Anantnag is crucial for developing targeted interventions and public health strategies to address this issue. This research aims to fill the existing gap in knowledge by determining the prevalence of iron deficiency anemia among adolescent girls in Anantnag. By providing a detailed assessment of the current situation, this study seeks to inform local health policies, enhance awareness, and guide future interventions to improve the nutritional status and overall well-being of this vulnerable population4.

Adolescence represents a pivotal stage of human development, characterized by rapid physical, emotional, and psychological changes. For adolescent girls, this period is particularly significant due to increased nutritional needs driven by growth spurts, the onset of menstruation, and heightened energy requirements. Dietary patterns during this critical phase play a crucial role in influencing health outcomes and developmental trajectories. Consequently, understanding these dietary patterns is essential for identifying potential nutritional deficiencies and formulating effective interventions5.

The objective of this research is to systematically assess the dietary patterns of adolescent girls in District Anantnag, by evaluating their food choices, meal habits, and adherence to dietary guidelines, this study seeks to provide a detailed understanding of their nutritional intake and associated health outcomes. This assessment will be instrumental in highlighting any prevalent nutritional gaps and informing the development of targeted dietary interventions and educational programs. This research aims to offer valuable insights into the dietary practices of adolescent girls in Anantnag, contributing to a deeper understanding of their nutritional needs and challenges. The findings will support the creation of effective strategies to improve dietary habits, address nutritional deficiencies, and enhance the overall health of adolescent girls in the region4.

Iron Deficiency Anemia (IDA) is a significant global health issue, affecting millions of individuals and having far-reaching implications for physical and cognitive development. Characterized by a lack of sufficient iron to produce adequate levels of hemoglobin, IDA can lead to a range of health problems, including fatigue, impaired cognitive function, and reduced physical performance. The prevalence and severity of IDA can vary widely based on a variety of factors, among which socioeconomic status (SES) plays a critical role6.

Socioeconomic status encompasses a range of factors, including income, education, occupation, and access to resources, all of which can profoundly influence nutritional health. Lower SES is often associated with limited access to nutritious food, inadequate healthcare services, and increased exposure to environmental and social stressors. These factors can exacerbate the risk of nutritional deficiencies, including iron deficiency anemia. Conversely, higher SES is generally linked to better access to diverse and nutrient-rich foods, higher levels of health literacy, and improved healthcare access, all of which can contribute to lower rates of IDA7.

Understanding the role of socioeconomic status in the prevalence of IDA is crucial for developing targeted interventions and public health strategies. Socioeconomic disparities can lead to differential access to iron-rich foods, health services, and educational resources about nutrition, all of which influence iron status and overall health. Identifying how these socioeconomic factors contribute to the risk of IDA can help in designing more effective, equitable public health interventions aimed at reducing anemia and improving nutritional outcomes across different socioeconomic groups4.

Despite the known impact of socioeconomic factors on health outcomes, there remains a need for comprehensive research to elucidate the specific mechanisms through which SES influences the prevalence of IDA. By examining how income levels, educational attainment, and access to resources affect iron deficiency anemia, this research aims to contribute valuable insights into the complex interplay between socioeconomic status and nutritional health.

The objective of this research is to investigate the role of socioeconomic status in the prevalence and severity of IDA. By analyzing data across various SES strata, this study seeks to identify key socioeconomic determinants of iron deficiency anemia and to understand how these factors interact to influence health outcomes. The findings will provide critical information for policymakers and health practitioners to develop targeted strategies and interventions that address the socioeconomic disparities contributing to IDA.

In summary, this research will enhance the understanding of how socioeconomic status affects the prevalence of iron deficiency anemia, offering valuable insights for designing interventions and policies to combat anemia and improve health equity.

Aim & Objectives:

Primary objective: To find out the prevalence of IDA among adolescent girls in district Anantnag. Secondary Objective: To assess the dietary patens of adolescent girls in district Anantnag. Tartary Objective: To know the role of socio-economic status in IDA.

A cross-sectional study design was employed to assess the prevalence of anemia and related factors among participants. Data were collected using structured questionnaires designed to gather information on demographic details, physical characteristics, symptoms of anemia, dietary habits, and knowledge about anemia. Hemoglobin estimation was done by Sahli′s Method8.

The questionnaires were administered to the participants in a standardized manner to ensure uniformity in data collection. The collected data were analyzed using descriptive and inferential statistical techniques. Descriptive statistics, including means, standard deviations, and percentages, were calculated to summarize participants' demographic characteristics, physical attributes, symptoms, dietary habits, and knowledge about anemia. For inferential analysis, the chi-square (χ²) test was employed to assess associations between categorical variables such as anemia status, socioeconomic factors, dietary patterns, and reported symptoms. A p-value of less than 0.05 was considered statistically significant, indicating meaningful differences or relationships between the groups (participants with and without anemia). Additionally, t-tests or Mann-Whitney U tests were applied to compare continuous variables, such as height, weight, BMI, and socioeconomic scores, between the two groups. All analyses were performed using statistical software to ensure accuracy and validity, and results were presented in tables and graphs for clarity. Statistical significance was set at a p-value of <0.05. Ethical approval was obtained prior to the study, and informed consent was secured from all participants. Data were anonymized to maintain confidentiality and used solely for research purposes.

Table-1: Descriptive Statistics of Height, Weight, and BMI by Socioeconomic Status among Study Participants:

The table compares anthropometric measurements (height, weight, BMI) and socioeconomic status (SES) between individuals with anemia (N=28) and without anemia (N=22). The Chi-square test and mean differences were used to assess statistical significance. Below is a summary of the research findings:

Table-1: Descriptive Statistics of Height, Weight, and BMI by Socioeconomic Status among Study Participants

Key Findings:

1. Anthropometric Measurements: Height (cm):Individuals without anemia were significantly taller (mean = 155.44 cm, SD = 5.37) compared to those with anemia (mean = 152.24 cm, SD = 5.41; Chi-square = 7.358, P = 0.00). Weight (kg): No significant difference in weight was observed between the two groups (mean = 46.54 kg, SD = 6.84 for anemic individuals vs. mean = 47.24 kg, SD = 6.35 for non-anemic individuals; Chi-square = 5.049, P = 0.00). However, the P-value suggests a statistically significant difference, which may be due to the small sample size. BMI (kg/m²): Individuals without anemia had a slightly higher BMI (mean = 18.7, SD = 1.68) compared to those with anemia (mean = 18.4, SD = 1.73; Chi-square = 2.177, P = 0.029), indicating a statistically significant difference.

2. Socioeconomic Status (SES): Lower SES:A significantly higher proportion of anemic individuals belonged to the lower SES category (60% with anemia vs. 40% without anemia; Chi-square = 4.37, P = 0.022). Middle SES: No significant difference was observed (30% with anemia vs. 55% without anemia; Chi-square = 2.14, P = 0.084). Higher SES: No significant difference was observed (10% with anemia vs. 5% without anemia; Chi-square = 1.00, P = 0.173).

These results suggest that Individuals with anemia were significantly shorter and had a slightly lower BMI compared to those without anemia, suggesting a possible association between anemia and stunted growth or malnutrition. Weight differences, while statistically significant, were minimal and may not be clinically meaningful. A significantly higher proportion of anemic individuals belonged to the lower socioeconomic status group, indicating that SES may be a contributing factor to anemia. No significant differences were observed in middle or higher SES categories, though the small sample size may limit the interpretation of these results.

Table-2: Distribution of Symptoms of Anemia and Dietary Habits among Study Participants:

The research examined the presence of various symptoms and dietary habits in individuals with and without anemia. The table below summarizes the percentages of people reporting certain symptoms and habits, along with the chi-square values and their corresponding p-values.

1. Symptoms of Anemia: Pallor: 27% of individuals with anemia and 20% without anemia reported pallor. The chi-square value was 1.625, with a p-value of 0.062, indicating no significant difference between the two groups. Breathlessness: 68% of those with anemia and 43% without anemia experienced breathlessness. The chi-square value was 2.345, with a p-value of 0.031, which suggests a statistically significant difference. Sleepiness: 73% of individuals with anemia and 24% without anemia experienced sleepiness. The chi-square value was 4.321, with a p-value of 0.003, showing a significant association between sleepiness and anemia. Lack of Concentration: 42% of those with anemia and 16% of those without anemia reported lack of concentration. The chi-square value was 3.321, with a p-value of 0.004, indicating a statistically significant difference. Hypothermia: 35% of people with anemia and 21% without anemia experienced hypothermia. The chi-square value was 2.124, with a p-value of 0.023, which is statistically significant. Others: 25% of those with anemia and 20% without anemia reported other symptoms. The chi-square value was 1.231, with a p-value of 0.070, showing no significant difference between the two groups.
2. Dietary Habits: Non-Vegetarian (regular/often): 26% of individuals with anemia and 58% without anemia consumed non-vegetarian foods regularly or often. The chi-square value was 2.134, with a p-value of 0.023, suggesting a significant relationship between anemia and non-vegetarian food consumption. Non-Vegetarian (rarely): 84% of those with anemia and 32% without anemia consumed non-vegetarian food rarely. The chi-square value was 2.234, with a p-value of 0.31, which is not statistically significant. Green Leafy Vegetables (regular/often): 74% of those with anemia and 71% without anemia consumed green leafy vegetables regularly or often. The chi-square value was 0.123, with a p-value of 0.789, indicating no significant difference. Green Leafy Vegetables (rarely): 26% of individuals with anemia and 29% without anemia consumed green leafy vegetables rarely. The chi-square value was 0.121, with a p-value of 0.812, suggesting no significant association.

Table-2: Distribution of Symptoms of Anemia and Dietary Habits among Study Participants

This shows Significant differences were found between the groups with and without anemia for symptoms such as breathlessness, sleepiness, lack of concentration, and hypothermia. Dietary habits related to the consumption of non-vegetarian food (regular/often) also showed a significant difference between the two groups. However, there were no significant differences in the consumption of green leafy vegetables or rare non-vegetarian consumption.

Table-3: Knowledge of Study Participants Regarding Anemia: Causes, Prevention, and Symptoms:

The table presents the results of a study comparing the prevalence of various factors and symptoms between individuals with anemia (N=28) and without anemia (N=22). The Chi-square test was used to determine the statistical significance of the differences between the two groups. Below is a summary of the research findings:

 Table-3: Knowledge of Study Participants Regarding Anemia: Causes, Prevention, and Symptoms

The study conducted by Emmanuel Ike Ugwuja et.al. Concludes that although undernutrition is minimal among adults in Abakaliki, anaemia is still widespread. Importantly, the research indicates that anaemia does not show a significant relationship with sociodemographic characteristics or body mass index (BMI). This suggests that conventional factors typically associated with anaemia—such as age, gender, and socioeconomic status—do not explain the high prevalence of anaemia in this population.The lack of association between anaemia and these sociodemographic factors is a notable finding, as it challenges common assumptions about the main contributors to anaemia. It highlights that other factors, which may not be as immediately apparent, could be influencing the high rates of anaemia in the region. Potential contributors could include aspects like dietary intake, micronutrient deficiencies, parasitic infections, or environmental influences, which were not explored in depth in this study. The authors suggest that further research is needed to identify other potential factors that may be linked to anaemia. Such studies should consider a broader range of variables that could provide insight into the specific causes of anaemia in this population. Investigating these factors is essential for developing more targeted health interventions that address the root causes of anaemia, rather than relying solely on sociodemographic characteristics or BMI.This conclusion emphasizes the complexity of anaemia as a health issue, pointing to the need for more comprehensive studies to uncover the underlying causes. Future research could ultimately inform better public health strategies to reduce anaemia prevalence and improve overall well-being in Abakaliki and similar regions9.

The authors Gesine Weckmann et.al conclude that symptoms commonly associated with anaemia, such as fatigue, low energy, poor concentration, and shortness of breath, are non-specific and often found in both anemic and non-anemic individuals. They emphasize that diagnostic efforts should not prioritize anaemia when these symptoms are present. Instead, conditions such as depression, heart failure, asthma, and COPD are more likely to be the underlying causes and should be thoroughly considered, particularly in outpatient settings. The study advocates for a more comprehensive approach to diagnosis, ensuring that a wider range of potential conditions are explored to accurately identify the true cause of the symptoms10.

This study conducted by Deepak Chaturvedi et.al. Highlights that adolescent girls are at high risk for anaemia, with mild anaemia being the most common. The severity of anaemia increased from early to late adolescence. Despite most girls having normal BMI, 82% were anemic. Anaemia was more prevalent in vegetarians, especially those with a rice-based diet, and was linked to tea and coffee consumption after meals. Additionally, frequent junk food consumption was strongly associated with anaemia, with 85.83% of girls who ate junk food regularly being anaemic. The findings stress the importance of improving dietary habits, particularly iron intake, to reduce anaemia in adolescent girls11.

The study by Nupura A Vibhute et al. found a high prevalence of anaemia (28.6%) among the study population, with notable occurrences in both underweight and overweight/obese students. The findings highlight that female medical students are particularly vulnerable to anaemia, emphasizing the need for targeted intervention programs in colleges. In response, the authors organized lectures covering the causes, symptoms, prevention, and treatment of anaemia, with a focus on nutrition and healthy eating habits. These efforts underscore the importance of addressing anaemia through education and dietary improvements in this population12.

Limitations

The present study has several limitations that should be acknowledged. First, the small sample size (N=28 with anemia and N=22 without anemia) may limit the generalizability of the findings. A larger and more diverse sample would enhance the robustness and external validity of the results. Second, the study does not account for other potential confounding factors that could influence the prevalence of anemia, such as dietary habits, access to healthcare, or underlying medical conditions. These unmeasured variables may have contributed to the observed outcomes, and their exclusion could affect the accuracy of the conclusions.

Furthermore, while this analysis highlights the potential role of socioeconomic status and anthropometric factors in the prevalence of anemia, the findings should be interpreted with caution. The study design and sample size may not fully capture the complex interplay of factors contributing to anemia. Future research with larger sample sizes, more comprehensive data collection, and a broader consideration of confounding variables is needed to confirm these findings and explore additional contributing factors to anemia. Such efforts would provide a more nuanced understanding of the determinants of anemia and inform targeted interventions.

This study highlights significant differences in anthropometric measurements, socioeconomic status, and symptoms between individuals with and without anemia. Anemic individuals were shorter, had a slightly lower BMI, and were more likely to belong to lower socioeconomic groups. Symptoms such as breathlessness, sleepiness, and lack of concentration were more prevalent in anemic individuals, while regular non-vegetarian food consumption was less common. No significant differences were observed in dietary knowledge or practices between the groups. These findings suggest that socioeconomic factors and dietary habits, particularly non-vegetarian food intake, may influence anemia prevalence. Future research with larger samples is needed to confirm these results and explore additional contributing factors.

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