Literature DB >> 35516663

Prevalence, knowledge, and related factor of anemia among school-going adolescent girls in a remote area of western Rajasthan.

Kamala Verma1, Girish C Baniya2.   

Abstract

Introduction: Anemia is a significant health problem among adolescent girls. This study aimed to determine the prevalence, related factors, and knowledge about anemia among adolescent girls in a remote area of western Rajasthan.
Methods: In a rural area of western Rajasthan, a cross-sectional study of 625 adolescent girls aged 11 to 19 years was carried out. Participants completed a questionnaire that included sociodemographic, clinical, and knowledge questions about anemia and its related factors. An HemoCue was used for hemoglobin analysis and anemia diagnosis.
Results: Anemia was found in 56.32% (n = 352) of the recruited population, with a mean of 9.92 (SD = 1.40). Mild, moderate, and severe anemia were found in 29.12%, 22.24%, and 4.96% of the participants, respectively. Girls aged 11 to 14 (AOR = 3.63, 95% CI: 1.76-6.38, P value = 0.042) and those with lower socioeconomic status (AOR = 4.37, 95% CI: 1.39-8.25, P value = 0.022) were more likely to have anemia than those of older age and higher socioeconomic status. Anemia was less prevalent in only one child/no siblings (AOR = 0.36, 95% CI: 0.16-0.73, P value = 0.041), and more prevalent in girls having less than 21 days of menstruation cycle (AOR = 5.37, 95% CI: 2.38-9.63, P value = 0.013), and 21 to 25 days of menstruation cycle (AOR = 3.81, 95% CI: 1.27-5.94, P value = 0.027). A total of 39.84% stated that anemia was caused by iron deficiency, followed by improper diet (32.64%). Furthermore, 56.32% agreed that the most common symptoms of anemia were weakness, and 51.36% of girls were told that anemia was treated with iron supplementation and a balanced diet (39.68%). Green leafy vegetables were considered a good source of iron by 56.48%, and 53.28% were educated about anemia by a teacher, followed by books (45.44%) and media (43.36%).
Conclusion: The study shows high prevalence of anemia among adolescent females in the remote area of western Rajasthan. To improve girls health, it is necessary to increase their knowledge, attitudes, and practices in this area. Educational intervention and routine health check-up would be excellent ways to accomplish this. Copyright:
© 2022 Journal of Family Medicine and Primary Care.

Entities:  

Keywords:  Anemia; Rajasthan; knowledge; prevalence; remote area; schoolgirls

Year:  2022        PMID: 35516663      PMCID: PMC9067232          DOI: 10.4103/jfmpc.jfmpc_1372_21

Source DB:  PubMed          Journal:  J Family Med Prim Care        ISSN: 2249-4863


Introduction

Anemia is an important public health problem, and it can affect people of all ages and from any region.[1] The most prevalent type of anemia is nutritional anemia, caused by a lack of iron, folate, or vitamin B12.[2] Iron deficiency anemia (IDA) is a quite simple disease to identify, but because of its generic clinical indications, it can lie untreated for a long period.[3] According to the World Health Organization (WHO), adolescent age is defined as a period between the ages of 10 and 19.[4] As the youth age is in a formative developmental year, anemia has long-term implications at this stage in life, including developmental problems, cognitive functioning, decreased immunity, irregular menstrual cycles, and subsequent poor pregnancy effects.[56] Furthermore, a higher prevalence of anemia has been linked to a number of medical conditions such as essential hypertension, hypothyroidism, congestive heart failure, coronary artery disease, and rheumatoid arthritis.[7] Mild-to-severe anemia typically manifests during adolescence, and if treated early, most anemia-related consequences can be avoided.[8] According to the WHO, anemia affects 24.8% of the world’s population and affects 27% of adolescent females in impoverished countries and 6% of adolescent females in affluent nations.[9] According to National Family Health Survey (NFHS-4), 53% of Indian women aged 15 to 49 are anemic.[10] The prevalence of anemia varies significantly across India, with a particularly high prevalence in rural Rajasthan.[11] As a result, it is critical to comprehend the factors linked to anemia in rural regions. Adolescent girls who are aware of anemia and its symptoms will be better prepared to take care of their own health as they grow older. Also, understanding these factors enables the development of a multimodal strategy for the prevention and management of anemia in adolescent girls. Keeping these aspects in mind, the purpose of this study was to determine the prevalence, knowledge, and associated factors of anemia among school-going adolescent girls in a remote area of western Rajasthan.

Material and Methods

Sample and setting

A cross-sectional study was conducted among school-going adolescent girls (11–19 years) in the rural field practice area of Government Medical College, Barmer, Rajasthan, in February 2020. The district Barmer lies between 24,58’ to 26, 32’N Latitudes and 70, 05’ to 72, 52’ E Longitudes in the western part of the Rajasthan, India. The district covers an area of approximately 28,387 square kilometers. Population of Barmer district is 2,923,593. The sex ratio in the Barmer district is 902 females to 1,000 males.[12] The prevalence of anemia in school-going girls is between 40% and 50%. Using this prevalence, with 95% confidence interval and 10% relative error the minimum sample size was 315. The study participants were chosen randomly from secondary schools. This study only included schools for girls, while schools for both boys and girls were excluded. All the girls aged 11 to 19 who gave their consent for hemoglobin estimation were included. Personal interviews were conducted to elicit data using a pretested questionnaire, and hemoglobin estimation was performed using HemoCue (Hb 201). The sensitivity of HemoCue is 75%–91%, and the specificity is 88%–100%. The anemia status of the study participants was scored using WHO cut-off points for anemia diagnosis. Hemoglobin level was used to determine the prevalence of anemia. A semistructured questionnaire was used to collect information about their sociodemographic characteristics, menstrual cycle, eating habits, awareness of anemia, causes, symptoms, and therapy. Weight was determined using a portable manual weighing machine to the nearest 100 g. A measuring tape was mounted to the wall to determine height in centimeters. HemoCue (Hb 201) was used to determine the level of hemoglobin. Mild (11–11.9 g/dL), moderate (8–10.9 g/dL), and severe (8 g/dL) hemoglobin reference ranges were utilized for anemia categorization.

Procedure

An invitation was sent to the various educational institutions, requesting them to participate in the research. Schools that demonstrated an interest and provided written consent were considered for the study. A female investigator clarified the study’s specifics and purpose in classroom to all female students. The importance of the current research, as well as the details of the blood collection were described to them. Girls who decided to participate were required to fill out informed consent forms and questionnaires, which included standardized demographic and clinical characteristics. The researcher assisted in data collection and answered queries pertaining to the questionnaires during the process.

Statistical analysis

Where appropriate, questionnaire data were precoded to facilitate collection and to ensure accuracy. Data were entered into Microsoft Excel 365 and then exported to SPSS V.20 for Windows, a statistical software package for social science. The dependent variable in this study is anemia as per the definition described above. Independent variables included age, socioeconomic status, type of family, religion, type of diet, no of siblings, education level of parents, and menstrual cycle in days. Continuous data were described using descriptive statistics like mean and standard deviation (SD), whereas categorical variables were described using numbers and percentages. An independent sample t-test or Chi-square test was used for each outcome variable to distinguish between girls with and without anemia. Both statistical tests were two-tailed, with 5% degree of statistical significance. The association of independent variables with anemia (the outcome) and the strength of the association was then investigated in multivariable analysis. In the bivariate analysis, only independent variables with a statistically significant effect on anemia and/or mean hemoglobin level were kept for the multivariable analysis. P values and Odds ratios with 95% confidence intervals (95% CI) were presented. Significance was defined as a P value of less than 0.05.

Ethical approval

The institutional ethics committee endorsed the research. This research was carried out in conjunction with the Helsinki Declaration. The ethical issues of the research were all addressed. Before beginning the interview, the participants were given and signed an informed consent form; they were willing participants in the study. They were also assured that all information gathered would be kept private.

Results

Five schools were approached, and three of them agreed to participate in the study, with an 80% turnout. A total of 667 girls from the three schools agreed to have their hemoglobin levels measured and were thus included in the study, with 42 being excluded (15 taking treatment for medical disorder, 27 produced incomplete item responses). As a result, the final sample size was 625 girls. The age range of the participants was 11 to 19 years old (mean = 15.54, SD = 2.72). The average body mass index (BMI) of the participants was 18.55 (SD = 1.71). Two hundred and eighty-nine participants (46.24%) were from a middle socioeconomic class; 418 girls (66.88%) lived in joint families, and 444 girls (71.04%) were Hindus. A total of 455 people (72.80%) of the participants were vegetarian. Two hundred and fourteen (34.24%) of the girls had one sibling, whereas 173 (27.68%) had two. Two hundred and ninety-nine girls (47.84%) had only their father educated, whereas 224 girls (35.84%) had both parents educated. At the time of the study, 547 girls (87.52%) had reached menarche. Their menarche ages ranged from 10 to 15 years old (mean = 12.74, SD = 1.55). The average duration of menstruation days for all girls was 4.35 days (SD = 1.13). Two hundred and forty-three (44.42%) of the teenagers had a menstrual cycle spanning from 26 to 30 days. Participants with anemia were significantly younger (15.14 vs. 15.93), had a lower BMI (18.4 vs. 18.7), were younger at menarche (12.63 vs. 12.85), and had more menstruation period days (4.57 vs. 4.13) than those without anemia (P-value < 0.05). Furthermore, there was a statistically significant difference between the anemic and nonanemic groups in terms of socioeconomic status, family type, number of siblings, and parental education status (P-value < 0.05) [Table 1].
Table 1

Participants’ sociodemographic and clinical characteristics

VariableWith anemia (<12 g/dL) (n=352) (%)Without anemia (≥12 g/dL) (n=273) (%)Total sample (n=625) (%)Chi-square/t-test p
Age (years) Mean (SD)15.14 (2.54)15.93 (2.91)15.54 (2.72)3.618, 0.00*
Age group
 10-14 years93 (26.42)65 (23.81)158 (25.28)7.491, 0.023*
 15-17 years145 (41.19)91 (33.33)236 (37.76)
 18-19 years114 (32.39)117 (42.86)231 (36.96)
Height (cm) Mean (SD)152.24 (5.41)155.44 (5.37)153.84 (5.39)7.358, 0.00*
Weight (kg) Mean (SD)42.54 (6.84)45.24 (6.35)43.89 (6.60)5.049, 0.00*
BMI Mean (SD)18.4 (1.73)18.7 (1.68)18.55 (1.71)2.177, 0.029*
Socioeconomic status
 Lower143 (40.63)87 (31.87)230 (36.80)8.496, 0.014*
 Middle161 (45.74)128 (46.89)289 (46.24)
 Higher48 (13.96)58 (21.25)106 (16.96)
Type of family
 Nuclear105 (29.83)102 (37.36)207 (33.12)3.939, 0.047*
 Joint247 (70.17)171 (62.64)418 (66.88)
Religion
 Hindu255 (72.44)189 (69.23)444 (71.04)0.78, 0.677
 Muslim78 (22.16)68 (24.91)146 (23.36)
 Others19 (5.40)16 (5.86)35 (5.60)
Dietary habit
 Vegetarian263 (74.72)192 (70.33)455 (72.80)1.494, 0.221
 Nonvegetarian89 (25.28)81 (29.67)170 (27.20)
No. of siblings
 Single child/No siblings28 (7.95)36 (13.19)64 (10.24)11.403, 0.022*
 One Sibling110 (31.25)104 (38.10)214 (34.24)
 Two siblings105 (29.83)68 (24.91)173 (27.68)
 Three siblings69 (19.60)36 (13.19)105 (16.80)
 Four or more siblings40 (11.36)29 (10.62)69 (11.04)
Education of parents
 None46 (13.07)27 (9.89)73 (11.68)8.425, 0.037*
 Only father176 (50.00)123 (45.05)299 (47.84)
 Only mother10 (2.84)19 (6.96)29 (4.64)
 Both120 (34.09)104 (38.10)224 (35.84)
Attain menarche
 Yes315 (89.49)232 (84.98)547 (87.52)2.859, 0.091
 No37 (10.51)41 (15.02)78 (12.48)
Menarche age (in years) Mean (SD)12.63 (1.37)12.85 (1.72)12.74 (1.55)−0.481, 0.63
Menstruation duration (days) Mean (SD)4.57 (1.12)4.13 (1.14)4.35 (1.13)−4.507, 0.00*
Menstrual cycle (days)(n=315)(n=232)(n=547)
 <2115 (4.76)7 (3.02)22 (4.02)13.784, 0.017*
 21-2597 (30.79)43 (18.53)140 (25.59)
 26-30129 (40.95)114 (49.14)243 (44.42)
 31-3546 (14.60)48 (20.69)94 (17.18)
 36-4016 (5.08)11 (4.74)27 (4.94)
 >4012 (3.81)9 (3.88)21 (3.84)

*BMI: Body Mass Index; SD: Standard Deviation

Participants’ sociodemographic and clinical characteristics *BMI: Body Mass Index; SD: Standard Deviation Based on WHO criteria, anemia was found in 56.32% (n = 352) of the recruited population, with a mean of 9.92 (SD = 1.40). In terms of severity, mild, moderate, and severe anemia were observed in 29.12%, 22.24%, and 4.96% of the individuals, respectively [Figure 1].
Figure 1

Graph depicting the severity of anemia among study participants

Graph depicting the severity of anemia among study participants The data in the Table 2 indicate the Hb percentiles in increasing order for teenage girls between the ages of 11 and 12, 13 and 14, 15 and 16, and 17 and 19 years. The mean and median (50%) values rose with age, with the exception of the 25th percentile cutovers, which drop-in age groups from 15 to 16 years. Even though the relationship between age and Hb concentration was significant (correlation coefficient was 0.231, with P value of 0.012), the link only emerged in the 11–12 age group (correlation coefficient of 0.39, with P value of 0.046) and the 17–19 age group (correlation coefficient of 0.541, with P value of 0.031). [Table 2].
Table 2

Hemoglobin percentiles (g/dL) in adolescent girls by age group

Percentile11-1213-1415-1617-19
n
5th7.627.857.857.90
10th8.108.247.958.30
25th8.468.468.378.84
50th (Median)9.7610.3510.3510.69
75th10.8511.2411.3411.42
90th11.5311.6411.6611.72
95th11.7711.8211.8611.90
Mean (SD)9.73 (1.33)9.94 (1.38)9.91 (1.43)10.10 (1.46)
(95% C. I.)9.52-9.869.67-10.359.78-0.409.81-10.57
Correlation coefficient with age0.390.0740.0460.541
Significant0.046*0.0780.3480.031*
Hemoglobin percentiles (g/dL) in adolescent girls by age group Two hundred and forty-nine girls (39.84%) stated that anemia was caused by iron deficiency, followed by improper diet (32.64%), vitamin deficiency (19.04%), and 24.48% stated that they had no idea what caused anemia. Three hundred and fifty-two girls (56.32%) agreed that weakness was the most common cause of anemia, followed by vertigo (23.04%) and fatigue (23.04%). Similarly, when it came to knowledge about anemia treatment, 51.36% of girls were told about iron supplementation, followed by a balanced diet (39.68%), whereas 35.20% girls had no knowledge about anemia treatment. Three hundred and fifty-three girls (56.48%) considered green leafy vegetables to be a good source of iron while 35.04% considered pomegranate. Three hundred and thirty-three girls (53.28%) were educated about anemia by a teacher, followed by books (45.44%) and media (43.36%) [Table 3].
Table 3

Knowledge of the study participants regarding anemia

VariableWith anemia (<12 g/dL) (n=352) (%)Without anemia (≥12 g/dL) (n=273) (%)Total sample (n=625) (%)Chi-square, P
Cause of Anemia
 Iron deficiency144 (40.91)105 (38.46)249 (39.84)0.86 0.973
 Improper diet113 (32.10)91 (33.33)204 (32.64)
 Underlying infection21 (5.97)16 (5.86)37 (5.92)
 Vitamin deficiency70 (19.89)49 (17.95)119 (19.04)
 Excessive blood loss25 (7.10)19 (6.96)44 (7.04)
 Do not know83 (23.58)70 (25.64)153 (24.48)
Symptoms of anemia
 Pallor74 (21.02)56 (20.51)130 (20.80)1.625 0.950
 Weakness201 (57.10)151 (55.31)352 (56.32)
 Fatigue78 (22.16)66 (24.18)144 (23.04)
 Headache53 (15.06)44 (16.12)97 (15.52)
 Dizziness/vertigo84 (23.86)60 (21.98)144 (23.04)
 Others62 (17.61)56 (20.51)118 (18.88)
 Do not know60 (17.05)52 (19.05)112 (17.92)
Treatment of Anemia
 Balanced diet142 (40.34)106 (38.83)248 (39.68)0.073 0.999
 Vitamin supplementation63 (17.90)46 (16.85)109 (17.44)
 IFA supplementation183 (51.99)138 (50.55)321 (51.36)
 Treatment of underlying illness28 (7.95)22 (8.06)50 (8.00)
 Do not know127 (36.08)93 (34.07)220 (35.20)
Food item rich in iron
 Green leafy vegetable197 (55.97)156 (57.14)353 (56.48)1.064 0.993
 Carrot70 (19.89)57 (20.88)127 (20.32)
 Sugar beets11 (3.13)7 (2.56)18 (2.88)
 Pomegranate123 (34.94)96 (35.16)219 (35.04)
 Jaggery36 (10.23)29 (10.62)65 (10.40)
 Nonveg14 (3.98)12 (4.40)26 (4.16)
 Others56 (15.91)38 (13.92)94 (15.04)
 Do not know70 (19.89)49 (17.95)119 (19.04)
Received education about anemia
 Parents45 (12.78)36 (13.19)81 (12.96)0.643 0.985
 Teacher186 (52.84)147 (53.85)333 (53.28)
 Books162 (46.02)122 (44.69)284 (45.44)
 Health worker119 (33.81)94 (34.43)213 (34.08)
 Friends32 (9.09)30 (10.99)62 (9.92)
 Media150 (42.61)121 (44.32)271 (43.36)
Knowledge of the study participants regarding anemia Anemia-related factors were determined using binary logistic regression data analysis. In the bivariate analysis, independent variables with P values of 0.025 for anemia were used in multivariate logistic regression. We utilized a P value of 0.05 to identify factors linked with the dependent variable in the multivariate analysis. The final model revealed that girls aged 11 to 14 (AOR = 3.63, 95% CI: 1.76–6.38, P value = 0.042) and those with lower socioeconomic status (AOR = 4.37, 95% CI: 1.39–8.25, P value = 0.022) were more likely to have anemia than those of older age and higher socioeconomic status. Anemia was also substantially less prevalent with a single child or no siblings (AOR = 0.36, 95% CI: 0.16–0.73, P value = 0.041), and more prevalent in girls having less than 21 days of menstruation period (AOR = 5.37, 95% CI: 2.38–9.63, P value = 0.013), and 21 to 25 days of menstruation period (AOR = 3.81, 95% CI: 1.27–5.94, P value = 0.027) [Table 4].
Table 4

Factors associated with anemia in participants with varying sociodemographic and clinical characteristics

VariableAOR95% CI P
Age group
 11-14 years3.631.76-6.380.042*
 15-17 years1.450.42-1.820.267
 18-9 years1.00--
Socioeconomic status
 Lower4.371.39-8.250.022*
 Middle2.140.48-3.260.084
 Higher1.00-0.173
Type of family
 Nuclear1.00
 Joint1.630.62-2.940.252
Religion
 Hindu1.420.63-2.290.351
 Muslim0.860.48-1.260.763
 Others1.00
Type of Diet
 Vegetarian1.190.76-1.740.532
 Nonvegetarian1.00
No. of siblings
 Single child/No siblings0.360.16-0.730.041*
 One sibling0.850.57-1.980.068
 Two siblings1.320.74-2.310.125
 Three siblings1.490.68-1.970.832
 Four or more siblings1.00
Education of parents
 None1.00
 Only father1.640.58-2.130.112
 Only mother0.780.46-1.720.436
 Both1.060.73-1.850.096
Menstrual cycle (days)
 <211.00
 21-255.372.38-9.630.013*
 26-303.811.27-5.940.027*
 31-352.160.74-3.410.143
 36-401.060.87-1.780.479
 >400.730.51-1.620.721

*AOR: Adjusted Odds Ratio

Factors associated with anemia in participants with varying sociodemographic and clinical characteristics *AOR: Adjusted Odds Ratio

Discussion

As only a healthy girl will be able to give birth to a healthy child, and the future of any country will be determined by the health of this half of the country’s populace. The purpose of this study was to determine the prevalence and predictors of anemia in adolescent girls, as well as to assess adolescent girls’ knowledge about anemia. In this study, the total prevalence of anemia among teenage girls was 56.32%, with 51.70% having mild anemia, 39.49% having moderate anemia, and 8.81% having severe anemia. A study by NFHS-4 reported that 53% of adolescents are anemic in Rajasthan.[13] Bodat et al.[14] observed that the overall prevalence of anemia among school-going adolescent girls in a rural area of Pune, Maharashtra was 87.60%, with 47.06%, 52.48%, and 0.46% of the girls having mild, moderate, and severe anemia, respectively. A higher prevalence of anemia was identified in our study because of remote parts of western Rajasthan having an awful environment and poor economic situation, preventing them from accessing sufficient nutrition and healthcare facilities. This is the situation of the girls who were attending school; however, the situation may be worse in the case of girls who dropped out or did not attend school due to poor economic or other family circumstances. Anemia was found, with the mean Hb level of 9.92 (1.40) g/dL, which is much lower than the cut-off of 12 g/dL used to diagnose it. This number is far lower than what we found through studies conducted with a national sample of girls in school (11.3 g/dL) by Kamble et al.,[15] but slightly near in a study by Dhillon et al.,[16] (9.99 g/dL) and Ahankari et al.,[17] (10.1 g/dL) in rural areas of Maharashtra. However, all of these studies noted substantial regional variation and included data for community-based and urban area-based cross-sectional surveys of adolescent girls, who have better option on health and nutrition care as compared with remote area. In this study, significant association of anemia was found with younger age. Other research corroborates these findings.[318] In this time, the demand of iron rises significantly. As girls achieve puberty before boys, so their growth will continue up to the age of 14, and after that linear growth begins up to the age of 18. In the absence of adequate nutritional intake, rapid growth causes increasing depletion of iron reserves, and affects physical and mental health.[19] In our study, lower socioeconomic status of girls and the number of siblings were associated with anemia. Low Hb concentrations were related to poor living conditions with a high prevalence of parasitic diseases and undernutrition, which were exacerbated by substandard housing and sanitary services.[2021] Apart from that, as the number of members increases, the likelihood of receiving nutritious food decreases, and appropriate childcare is also unattainable. Other individual factors associated with anemia were short-cycle length of mensuration period (16 to 20 and 21 to 25 days). More frequency and heavy bleeding were found responsible for low Hb concentrations in girls than those measured less frequently and regularly. When a young girl’s period begins, she is terrified, and she is unable to express herself to anyone for fear of embarrassment, which has an impact on her diet and health.[22] In our study, more than half of participants had insufficient knowledge of cause, symptoms, treatment, and food rich in iron. Similar findings were observed in previous research.[23] However, study conducted in urban areas of school-going adolescent girls found better knowledge of anemia and its related factors.[24] The reason may be for it there is low awareness of the national health program and health and hygienic practice in remote areas of western Rajasthan. Besides this, some studies based on community and on non-school-going adolescents observed poor knowledge of anemia and related factors.[25] The findings of this study underscored the importance of comprehensive anemia education for teenagers, highlighting how limited current educational resources in schools and homes are. Anemia is a straightforward diagnosis that goes missed for a long time due to nonspecific clinical indications and a lack of screening among adolescent girls. We expect that implementing a nutrition education program effectively increases female adolescents’ anemia knowledge, attitude, and practice.[26] It is critical to establish policies and make decisions to care for adolescents by implementing effective educational programs. The results of the study could also help primary care physicians give the right advice and treatment to patients and their families.

Limitations

Sample size was small, so it does not reflect the entire population. Only hemoglobin was calculated. Due to financial constraints, further hematological parameters could not be evaluated. Another drawback is that because this was a cross-sectional study, the cause-and-effect link could not be determined because a long-term investigation would have been required. Despite these limitations, we believe that our study contributed to the generation of ideas for epidemiological investigations on a large scale across this area to overcome these constraints because of the scarcity of literature concerning anemia in the remote area of western Rajasthan.

Conclusion

This study showed a prevalence of anemia of 56.32%. The current study found that the prevalence of anemia among school-going adolescent girls was alarming, raising serious worries about their reproductive potential. The study participants had limited knowledge of anemia, its symptoms, causes, and treatments. To lessen the burden of anemia among adolescent girls, adequate iron and folic acid supplements, iron-rich food intake, good nutrition education, and frequent deworming are required. It should be emphasized that health check-up camps should be held in schools regularly so that timely diagnosis and treatment can be provided for any medical illness. In addition, attention should be paid to the necessity for a female counselor in a girl’s school, who should counsel students regularly about their personal issues so that they do not experience unnecessary stress. Anemia should be routinely checked by the attending primary care physician in any facility for any adolescent girls presenting with any disease, and if anemia is clinically present, a complete hemogram should be evaluated. Our findings regarding the high prevalence of anemia, knowledge, and associated factors in adolescent girls should be expanded and replicated by others, as well as used by primary care physicians for early detection and timely management of anemia with proper counseling of girls and their families, as well as schools. This study’s findings can help policymakers and primary care physicians in the region assess anemia prevalence and create efficient diagnostic approaches.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.
  15 in total

1.  Characterisation of the types of anaemia prevalent among children and adolescents aged 1-19 years in India: a population-based study.

Authors:  Avina Sarna; Akash Porwal; Sowmya Ramesh; Praween K Agrawal; Rajib Acharya; Robert Johnston; Nizamuddin Khan; H P S Sachdev; K Madhavan Nair; Lakshmy Ramakrishnan; Ransi Abraham; Sila Deb; Ajay Khera; Renu Saxena
Journal:  Lancet Child Adolesc Health       Date:  2020-07

2.  Prevalence of iron-deficiency anaemia and risk factors in 1010 adolescent girls from rural Maharashtra, India: a cross-sectional survey.

Authors:  A S Ahankari; P R Myles; A W Fogarty; J V Dixit; L J Tata
Journal:  Public Health       Date:  2016-08-31       Impact factor: 2.427

3.  Prevalence and approaches to manage iron deficiency anemia (IDA).

Authors:  Shikha Bathla; Shalini Arora
Journal:  Crit Rev Food Sci Nutr       Date:  2021-06-07       Impact factor: 11.176

4.  The Adolescent Girls' Anaemia Control Programme: a decade of programming experience to break the inter-generational cycle of malnutrition in India.

Authors:  Víctor M Aguayo; Kajali Paintal; Gayatri Singh
Journal:  Public Health Nutr       Date:  2013-01-24       Impact factor: 4.022

5.  Adolescent girls' Anaemia Control Programme, Gujarat, India.

Authors:  P V Kotecha; S Nirupam; P D Karkar
Journal:  Indian J Med Res       Date:  2009-11       Impact factor: 2.375

6.  Iron deficiency anaemia and low BMI among adolescent girls in India: the transition from 2005 to 2015.

Authors:  Saverio Bellizzi; Giuseppe Pichierri; Catello M Panu Napodano; Paola Salaris; Maura Fiamma; Claudio Fozza; Luca Cegolon
Journal:  Public Health Nutr       Date:  2020-10-26       Impact factor: 4.022

7.  Anemia and iron deficiency in adolescent school girls in kavar urban area, southern iran.

Authors:  M Ramzi; S Haghpanah; L Malekmakan; N Cohan; A Baseri; A Alamdari; N Zare
Journal:  Iran Red Crescent Med J       Date:  2011-02-01       Impact factor: 0.611

8.  Anaemia among adolescent girls in three districts in Ethiopia.

Authors:  Seifu Hagos Gebreyesus; Bilal Shikur Endris; Getahun Teka Beyene; Alinoor Mohamed Farah; Fekadu Elias; Hana Nekatebeb Bekele
Journal:  BMC Public Health       Date:  2019-01-21       Impact factor: 3.295

9.  Prevalence of anaemia among school going adolescent girls attending Test, Treat and Talk (T-3) camp under Anaemia Mukt Bharat in Delhi.

Authors:  Bhushan D Kamble; Mahaur Gunjan; Jethani Sumit; Sunil K Singh; Diwakar Jha; Saudan Singh
Journal:  J Family Med Prim Care       Date:  2021-02-27
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