|Year : 2020 | Volume
| Issue : 3 | Page : 244-249
Anaemia among adolescents: A community-based study using cluster sampling in villages under Sarjapur Primary Health Centre, Bangalore urban district
Avita Rose Johnson, Cency Baburajan, T Sulekha
Department of Community Health, St. John's Medical College, Bengaluru, Karnataka, India
|Date of Submission||31-Jul-2020|
|Date of Acceptance||20-Aug-2020|
|Date of Web Publication||05-Oct-2020|
Dr. Avita Rose Johnson
Department of Community Health, St. John's Medical College, Sarjapur Road, John Nagar, Bengaluru - 560 034, Karnataka
Source of Support: None, Conflict of Interest: None
Background: India has the largest adolescent population in the world, the majority of whom reside in rural areas. Anemia is one of the top five causes of morbidity among adolescents.
Objective: To assess the prevalence of anemia and its associated factors among adolescents aged 10–19 years residing in a rural area.
Methods: Community-based, cross-sectional study in 25 villages and one town under Sarjapur Primary Health Centre (PHC), Bangalore Urban District. Two-staged cluster sampling was done. The interview schedule for sociodemographic details, diet, and physical activity was administered. Nutritional status was estimated by body mass index-for-age. Hemoglobin (Hb) was estimated using photometric analyzer. Chi-square test was done for the association between anemia (Hb <12 g/dl) and independent co-variates.
Results: Of 210 adolescents, 48.1% had anemia, most were mild anemia. No significant association found between anemia and sociodemographic factors such as age, gender, and socioeconomic status or nutrition status, diet, and physical activity. None of the anemic adolescents were investigated or treated for anemia before. None of the subjects were aware of adolescent-friendly health services at the PHC.
Conclusion: Nearly half of adolescents in this rural area were anemic. In addition to on-going Weekly Iron and Folic Acid Supplementation for the prevention of anemia and bi-annual deworming, there is a need for routine screening and treatment of anemia in schools, and follow-up of school drop-outs at household level by auxiliary nurse midwife (ANM). Community-level workers like Accredited Social Health Activist, ANM, and Anganwadi worker must create awareness regarding available adolescent services, treat anemia with iron and folic acid tablets and focus on counseling adolescents to promote healthy eating habits and iron-rich foods.
Keywords: Adolescent health, anemia, cluster sampling, rural
|How to cite this article:|
Johnson AR, Baburajan C, Sulekha T. Anaemia among adolescents: A community-based study using cluster sampling in villages under Sarjapur Primary Health Centre, Bangalore urban district. Indian J Health Sci Biomed Res 2020;13:244-9
|How to cite this URL:|
Johnson AR, Baburajan C, Sulekha T. Anaemia among adolescents: A community-based study using cluster sampling in villages under Sarjapur Primary Health Centre, Bangalore urban district. Indian J Health Sci Biomed Res [serial online] 2020 [cited 2021 May 12];13:244-9. Available from: https://www.ijournalhs.org/text.asp?2020/13/3/244/297192
| Introduction|| |
Adolescence is the crucial period of growth and development between the ages of 10–19 years. India is home to the largest adolescent population in the world, with one in every five persons in the country belonging to this group. World Health Organization (WHO) has listed anemia as one of the top five causes of morbidity among adolescents, along with depressive disorders, asthma, back and neck pain, and anxiety disorders. Anemia can lead to the poor cognitive and physical development of adolescents, which is reflected in poor academic performance or physical performance, reduced work productivity, and frequent infections. Low intake of iron, poor dietary absorption of iron from diets high in phytates or oxalates, hookworm infestation, undernutrition, blood loss from menstruation, and teenage pregnancy are contributing factors for anemia among adolescents.
The Weekly Iron and Folic Acid Supplementation (WIFS) program  and the Bi-annual National deworming day  were initiated in schools and anganwadis to prevent adolescent anemia in response to the National Family Health Survey (NFHS)-3, which reported that 56% girls and 30% boys aged 15–19 in India were anemic. However, the recent NFHS-4 has indicated no significant decline in the levels of adolescent anemia.
With two-thirds of the country residing in rural areas, it is important that we focus on anemia among adolescents in the rural area. There are very few studies, which comprehensively address the issue of adolescent anemia among both boys and girls in the age group from 10 to 19 years. Most research tends to be school-based, which misses out on school-dropouts and older adolescents who have finished their schooling. Identifying the prevalence of anemia among adolescents and its socio-cultural determinants, including nutritional status, will enable targeted interventions towards reducing this public health problem. Hence, this study was conducted to assess the prevalence of anemia and its associated factors among adolescents aged 10–19 years residing in a rural community setting.
| Methods|| |
Study setting: This community-based, cross-sectional study was undertaken among adolescents living in the Sarjapur Primary Health Centre (PHC) area, Anekal Taluk, Bangalore Urban district, with a total population of 30,007 included under three sub-center areas – Mugalur, Kuthaganahalli, and Handenahalli as well as Sarjapur town. Institutional Ethics approval was obtained, and the study was conducted over a 6 month period in 2017. Sampling frame: Adolescents aged 10–19 years of age residing in the Sarjapur PHC area. Sample size estimation: The sample size was based on a 50.8% prevalence of anemia among adolescents from a previous study in Chandigarh. With a 95% confidence interval, 10% absolute precision, design effect of 2 for cluster sampling, and 10% nonresponse rate, the sample size was estimated as 210. Sampling technique: The WHO 30 × 7 or two-staged cluster sampling technique was used. The clusters were first selected using probability proportionate to size. Villages were listed sub-centre-wise and population of all 25 villages and town were noted from PHC records. The sampling interval was calculated by dividing the cumulative population by the number of clusters needed. A random number less than the sampling interval was generated using Microsoft Excel to identify the village in which the first cluster would be located. The next cluster was selected by adding the sampling interval to the random number. Thus, 30 such clusters were identified, with larger villages and Sarjapur town having more than one cluster. To select seven study subjects in each cluster, the researcher went to the center of the village, numbered the streets and using the lottery method randomly selected the street to go house-to-house. The toss of coin helped to decide to begin from the right or left side of the street. If adolescents were not available at their houses on the day of the visit, an attempt was made to contact them at a subsequent visit, failing which they were replaced by another adolescent in the same cluster selected thus. Inclusion criteria: Adolescent between 10 and 19 years, male or female, married or unmarried, including pregnant or physically disabled adolescents, residing in the area since last 1 year. Exclusion criteria: Adolescents who were not available at home over two consecutive visits or not able to comprehend questions due to mental disability. Adolescents who were visiting, not residing in the area. Data collection: Written informed consent was obtained from parent/guardian and assent obtained from the participant. Sociodemographic details and information on reported illness, diet, and physical activity were collected using a pretested, face-validated, structured interview schedule in the local language Kannada. Socioeconomic status was determined using Modified BG Prasad socioeconomic classification. Hemoglobin (Hb) estimation was done by HemoCue ® Hb30 (HemoCue, India), a portable photometric analyzer, which has a sensitivity of around 80% and a specificity of more than 90% as compared to laboratory-based autoanalyzer. Anthropometric assessment of height and weight was done. Height was measured to the nearest 0.1 cm using a portable stadiometer (Seca, Germany), and weight was recorded to the nearest 100 g using a calibrated digital weighing scale (Salter, India). Body mass index (BMI) was calculated by dividing weight in kilograms by the square of height in meters. Nutritional status was categorized according to WHO BMI-for-age z-scores. Operational definitions: Early adolescence: 10–14 years of age. Late adolescence: 15–19 years of age. Underweight: WHO BMI-for-age z-score ≤−2. Overweight: WHO BMI-for-age z-score >+1. Anaemia: Hb value <12 g/dl; mild anaemia: 10–11.9 g/dl, moderate anaemia: 7–9.9 g/dl, severe anaemia: <7 g/dl.
The data were entered in a Microsoft Excel Spreadsheet and analyzed using IBM Statistical Package for the Social Sciences version 20 (New York, USA). Data were checked for normality using Shapiro–Wilk test and normality probability plot. The variables were described by calculating frequencies, proportions, mean and standard deviation. Chi-square test was done to look for an association between the outcome variable (anemia) and various exposure variables like sociodemographic factors, diet, physical activity, and nutritional status. A P < 0.05 was considered to be statistically significant for all analyses.
| Results|| |
Of the 210 adolescents in the study, there were a slightly higher number of girls (56.7%). Majority (72.9%) were early adolescents. Most (95%) were Hindu by religion and belonged to nuclear families (70%). More than half (51.4%) belonged to the upper middle or upper socioeconomic class. Majority (94.3%) were attending school or college, 68.1% of whom were studying in government education institutions. One hundred and ten (52.4) were studying in middle school, 70 (33.3) in high school, and 30 (14.3%) were studying in preuniversity course or college. Twelve (5.7%) had dropped out of school, of whom 2 were male and were working, and the rest were female and married homemakers. None of the adolescents who were sampled were pregnant or physically disabled. None of the subjects were aware of the existence of adolescent-friendly health services (Sneha Clinic) at the PHC, which runs on weekday afternoons.
Nearly half (48.1%) of the adolescents were found to be anemic. As per operational definitions, 109 (51.9%) had no anemia, 88 (41.9%) had mild anemia, 13 (6.2%) had moderate anemia and none of the adolescents were found to have severe anemia. The mean Hb levels were similar among early adolescent boys and girls [Table 1]. Among late adolescents, mean Hb was slightly higher among boys than compared to girls, but this was not statistically significant. The prevalence of anemia was found to be higher among early adolescents, females, and those from upper socioeconomic class, but these findings were not statistically significant [Table 2].
|Table 1: Age and gender distribution of mean hemoglobin levels among the study population (n=210)|
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|Table 2: Association of anemia among adolescents with various exposure variables (n=210)|
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Determinants of anemia
Students studying in government educational institutions had no significant difference in the proportion of anemia as compared to those studying in private institutions. None of the anemic adolescents reported having been investigated before for anemia nor did they report receiving any additional treatment for anemia apart from the regular WIFS received by those in government educational institutions.
Based on BMI-for-age, nutritional status was determined to be normal in only 14.3% of adolescents. Nearly two thirds (63.8%) were underweight and 21.9% were overweight. There was no significant association between nutritional status and anemia.
Illness in the last 6 months was reported by 38.1%, the commonest being viral fever (21.9%), acute respiratory infections (4.3%), dengue (4.3%), and typhoid (3.8%). There was no significant association between anemia and report of any illness in the last 6 months.
There was also no significant association between anemia and any of the dietary factors recorded in the study [Table 3].
|Table 3: Association of anemia among adolescents with dietary factors (n=210)|
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| Discussion|| |
Our study found that nearly half of the adolescents residing in the Sarjapur PHC area were found to be anemic. This is important as anemia is an easily preventable and treatable cause of adolescent mortality, which, if unchecked, had far-reaching consequences that affect the development of children leading to poor academic and work performance, lowered immunity, and increased susceptibility to infections.
Studies among adolescents in Chandigarh  and Nepal  reported a similar prevalence of anemia, 50.8% and 52%, respectively. However, both studies showed a higher prevalence among girls than boys, as compared to our study, which showed equal prevalence among girls and boys. This could have been due to the larger proportion of early adolescents in our study, an age at which difference in anemia levels between boys and girls may not be apparent due to the fewer years of exposure to menstruation among the younger adolescent girls.
Anemia among adolescent girls in our study was found to be 48.7%, which was lower than studies among adolescent girls residing in rural Maharashtra (61%) and rural Chhattisgarh (76%). This could be due to the difference in demographics between the different study populations. Our adolescents came from a higher economic background, with more than half of the subjects hailing from upper-middle and upper socioeconomic class, whereas the subjects in the Maharashtra and Chhattisgarh studies were predominantly of lower socioeconomic class.
A study in Rajasthan among school-going children reported a higher prevalence of anemia among those of lower socioeconomic status. However, such a finding was not demonstrated in our study. Our study did not find any significant association between anemia and sociodemographic factors, similar to the study in rural Maharashtra, which also did not report significant associations with age, socioeconomic status, religion and type of family.
Our study also did not find any link between anemia and diet, which was similarly seen in a study conducted among adolescent females in an urban area in Nagpur.
Research has indicated that adolescents who are underweight have a greater risk of anemia due to calorie and micronutrient (iron) deficiency. Adolescents who are overweight also have a greater risk of anemia due to unhealthy dietary habits of junk food consumption and lack of dietary iron. However, in our study, we were not able to demonstrate an association between anemia and nutritional status. This was also the case in a study among adolescent girls in Kerala.
The lack of any significant associations with diet, exercise, and other factors points us in the direction of thinking about whether adolescent anemia in our study could be a natural progression of untreated childhood anemia. This has been supported by the findings of NFHS-4, which shows almost similar levels of anemia among children aged 6–59 months and adolescents aged 15–19 years. This brings us to the life-cycle approach, where prevention of anemia in one life stage is possible when anemia is treated in the previous life stage. Therefore, one of the strategies to focus on, for the prevention of adolescent anemia, is the diagnosis and treatment of childhood anemia.
None of the adolescents who were found to be anemic in our study reported having been investigated for anemia before, nor had they received treatment for anemia apart from the regular WIFS and biannual deworming received by those enrolled in government educational institutions. This indicates that rather than relying on clinical assessment of pallor, routine testing of Hb levels should be included for school students at the annual school health check-up by providing the Rashtriya Bal Swasthya Karyakram teams with portable photometric haemoglobinometer and microcuvettes, to effectively diagnose and treat anemia. This is further reinforced by the finding in our study that there was no difference in the proportion of anemia among students studying in government versus private educational institutions. WIFS is an evidence-based strategy to prevent anemia; however, it cannot treat anemia or correct low Hb levels. The levels of adolescent anemia have remained relatively unchanged in the 10 years between NFHS-3 and NFHS-4,, despite WIFS program and the bi-annual deworming day being part of the National Health Mission strategies., When nearly half of the adolescents are anemic, this indicates the need to look beyond prevention of anemia with WIFS, and introduce Hb estimation and treatment of anemia in schools as part of annual school health check-up, maintain cumulative health records to track Hb levels and follow-up school drop-outs at the household level by the auxiliary nurse midwife (ANM).
Since none of the adolescents in our study were even aware of the existence of adolescent-friendly health services (Sneha Clinic) at the PHC, community-level workers like Accredited Social Health Activist (ASHA), ANM and Anganwadi worker must create awareness regarding available adolescent services, treat anemia with iron and folic acid tablets and focus on counseling adolescents to promote healthy eating habits and iron-rich foods.
Limitations of the study
Information regarding illness in the last 6 months was based on self-reporting and could have been underestimated due to recall bias. Data on menstrual disorders among girls and history of worm infestation and de-worming was not collected as part of this study. Social desirability bias may have occurred when the subjects responded to questions regarding physical activity and diet.
| Conclusion|| |
Our study found that nearly half of the adolescents residing in the 25 villages and one town under the Sarjapur PHC area were anemic. Majority of anemia was mild (Hb: 10–11.9 g/dl). No significant association was found between anemia and sociodemographic factors like age, gender, and economic status. Nutrition status, diet, physical activity, and reported illness in the last 6 months were also not associated with anemia. None of the adolescents who were found to be anemic in our study, had been investigated for anemia before, nor had they received treatment for anemia. WIFS is an evidence-based strategy to prevent anemia, not treat anemia. Therefore, there is a need for the introduction of routine screening and treatment of anemia in schools, and follow-up of school drop-outs at the household level by the ANM. Since none of the subjects were aware of adolescent-friendly health services (Sneha Clinic) at the PHC, community-level workers like ASHA, ANM and Anganwadi worker must create awareness regarding available adolescent services, treat anemia with iron and folic acid tablets and focus on counseling adolescents to promote healthy eating habits and iron-rich foods.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3]