Rakesh SRa, Ashimsha Aa, Shanavas Ab, Surendran VEb, Rakesh PSc, Subhagan Sd, Salila Ke
a. Primary Health Centre, Mangode, Chithara, Kollam; b. Kerala Health Services;
c. Epidemiologist, Integrated Disease Surveillance Project, District Medical Office, Kollam;
d. District Programme Manager, NRHM, Kollam; e. District Medical Officer, Kollam

Corresponding Author: Dr. Rakesh PS, Epidemiologist, Integrated Disease Surveillance Project, District Medical Office, Kollam. Phone: 9495537333. E-mail : rakeshrenjini@gmail.com

ABSTRACT

Introduction: Anemia is the world’s second leading cause of disability and thus one of the most serious global public health problems.1 Iron deficiency is the most common cause of anemia. Iron deficiency anemia affects aerobic fitness, endurance capacity and efficiency of work.9 It has adverse impacts on cognition by a decrease in the activity of iron containing brain enzymes.10 Iron deficiency is also associated with decreased phagocytosis, decreased response to cytokines and mitogens, decreased cell mediated immunity and suppressed skin test response.11 Iron deficiency has been linked to behavioral and learning problems among children and adolescents.12 All these factors may adversely affect learning and scholastic performance of school going children.

Objectives: Properly conducted studies focusing on prevalence of anemia among school children is lacking from the state of Kerala. The current study included secondary data analysis from a health project for screening all school children for anemia.

Materials and Methods: The screening was done during January- March 2013. Hemoglobin was tested for all school children studying in the classes from 1 to XII, from all the 17 schools in the area. Anemia status was decided as per WHO guidelines; less than 11.5g/dl for children less than12 years; less than 12 g/dl for girls from 12 to 18yrs and boys less than 14 years and less than 13 g/dl for boys from 15 to 18 yrs of age. Severe anemia included hemoglobin less than 7g/dl and moderate anemia included hemoglobin between 7.1 and 10g/ dl.16 Age group 6-11 years was considered as primary school age and 12-17 years as secondary school age for statistical purposes.

The data was entered using the software Epi Info 2001 version 3.2.2 and analysis was done using Statistical Package for Social Sciences (SPSS) for Microsoft windows version 12. Descriptive statistics, univariate and multivariate analysis for factors associated with anemia was done.

Conclusion: A properly conducted research study on the prevalence of anemia among adolescents in Kerala using a standardized technique for hemoglobin estimation, along with estimation of iron stores, is the matter of the hour. Such a study will help to formulate policies on iron supplementation programs at schools and also it would form a baseline for evaluating the anemia control interventions.

Anemia is the world’s second leading cause of disability and thus one of the most serious global public health problems.1 Iron deficiency is the most common cause of anemia. It remains as a major nutritional problem among children and adolescents in India.2-8  This is despite of the fact that decades of nutritional interventions are in place in the country.

Iron deficiency anemia affects aerobic fitness, endurance capacity and efficiency of work.9 It has adverse impacts on cognition by a decrease in the activity of iron containing brain enzymes.10 Iron deficiency is also associated with decreased phagocytosis, decreased response to cytokines and mitogens, decreased cell mediated immunity and suppressed skin test response.11 Iron deficiency has been linked to behavioral and learning problems among children and adolescents.12 All these factors may adversely affect learning and scholastic performance of school going children.

Properly conducted studies focusing on prevalence of anemia among school children is lacking from the state of Kerala. The current study included secondary data analysis from a health project for screening all school children for anemia. The health project was funded by the Local Self Government and implemented through the primary health centre in the area. The project involved screening of all school going children from classes’ I-XII in Chithara panchayat area in Kollam district, Kerala

Methodology

Chithara Panchayat is situated in south east part of Kollam district with a population of 42,206 sharing its border with Thiruvananthapuram district. Scheduled tribes constitute 0.6% of the population. The rural village is bounded by mountains and forest on Eastern side.

The screening was done during January- March 2013. Hemoglobin was tested for all school children studying in the classes from 1 to XII, from all the 17 schools in the area.

Necessary permissions were obtained from the school authorities and the parents. The blood samples were taken after obtaining free and informed verbal consent/ascent of the students. Those students with chronic illness or receiving long-term drugs and needing hospitalization in the last two weeks before the study were excluded.

20 iL capillary blood was collected by finger prick for estimation of hemoglobin by Sahli’s method.13 The hemoglobin tube (STD 14.5gm =100% concentration) was filled with N/10 hydrochloric acid (HCL) up to 2 gm marking. This graduated tube was placed in Sahli’s hemoglobin meter (Comparator with Brown glass). The blood and acid are mixed with glass stirrer and allowed to stand for 5 minutes for acid haematin formation. Drop by drop distilled water was added to dilute the acid haematin compound color till it matches with the standard color plates of the comparator.  Visual matching was done by taking the reading facing the window, with daylight behind the scale. Results were read as g/dl present on the hemoglobin tube. All precautions described by WHO were taken while estimating the hemoglobin value.13

The age of children was ascertained from school registers. Nutritional status was evaluated using World health organization (WHO) recommended age specific cut-off points of body mass index (BMI).15 Each child’s height and weight were measured in the metric system, using standardized techniques. Astadiometer (measuring rod) capable of measuring to an accuracy of 0.1 cm was used to assess height of the subjects. A portable balance with an accuracy of 100 g was used to record the weight of the subjects.

Anemia status  was decided as per WHO guidelines; less than 11.5g/dl for children less than12 years; less than 12 g/dl for girls from 12 to 18yrs and boys less than 14 years and less than 13 g/dl for boys from 15 to 18 yrs of age. Severe anemia included hemoglobin less than 7g/dl and moderate anemia included hemoglobin between 7.1 and 10g/ dl.16  Age group 6-11 years was considered as primary school age and 12-17 years as secondary school age for statistical purposes.

The data was entered using the software Epi Info 2001 version 3.2.2 and analysis was done using Statistical Package for Social Sciences (SPSS) for Microsoft windows version 12. Descriptive statistics, univariate and multivariate analysis for factors associated with anemia was done.

Results

Table 1. Characteristics of the study children (N=4813)

Table 1. Characteristics of the study children (N=4813)

Table 2. Anemia by age and gender

Table 2. Anemia by age and gender

Out of 5600 school children on roll, 4813 (86%) students were screened. The other children were either absent (721), excluded as per criteria (19) or did not give consent/ascent (47). The general characteristics of the children were shown in Table 1. Among the students, 49.7% were males and 60.9% were from a government school. 10.7% had severe malnutrition as evidenced by a BMI of <-3SD.

Among the study children, the prevalence of anemia was 72.3%. Among the subjects, 2.5% had severe anemia, 46% had moderate anemia and 26.3% had mild anemia. Among the female students, 77.5% were anemic while among the males 67% were anemic (p<0.05). Among the female children the prevalence of severe, moderate and mild anemia was 2.4%, 50% and 24.2% while among the males the figures were 2.7%, 36.8% and 27.5% respectively. The prevalence of anemia by gender and age group is shown in table 2.

Table 3. Univariate analysis of factors associated with anemia (N=4813)

Table 3. Univariate analysis of factors associated with anemia (N=4813)

Table 4. Multivariate analysis of factors associated with anemia

Table 4. Multivariate analysis of factors associated with anemia

The results of univariate and multivariate analysis of factors associated with any anemia were shown in Tables 3 and 4. In the final logistic regression model, females had higher prevalence of anemia as compared to males (Adjusted OR 1.7295% CI 1.51-1.97). The odds of being anemic in the 11-14 years were 2.9 (95% CI 2.484-3.203) times higher than the odds of being anemic at 15-19years. The undernourished children (BMI <2SD) had1.30 (95% CI 1.117-1.526) times higher odds of being anemic as compared to the normal BMI category.

Discussion

School age is considered as a dynamic period of growth and development because children undergo physical, mental, emotional and social changes. In other words the foundations of good health and sound mind are laid during the school age period. Anemia is likely to compromise physical work capacity and cognitive functions of children and adolescents in the pubertal phase of development. Further, even mild anemia can have a deleterious effect on these functions. The adverse impact is especially aggravated if both under nutrition and anemia are present.

Adolescent girls are found to be at a higher risk for anemia in the current study. There was no gender difference noticed in the prevalence of anemia till the age of 11. The burden of menstrual blood loss, normal or abnormal, might be precipitating the crises. The age group of 11-15 is having higher risk of developing anemia, as demand for iron would be more during the period due to rapid growth spurt. A number of factors might influence both weight status and iron deficiency, including socioeconomic variables, physical activity and diet.

Iron status is a continuum from iron deficiency with anemia, to iron deficiency with no anemia, to normal iron status with varying amounts of stored iron. Iron deficiency anemia represents the extreme low end of the spectrum of iron status. The hemoglobin concentration is a surrogate indicator of the amount of iron in circulation which is available for new RBC synthesis. Prevalence of anemia of 25–95% was seen in several studies across the Indian subcontinent among adolescents of 11-18 years age group.2-8,17,18

Several studies have found differences in the hemoglobin results estimated by different methods. Sahli’s method of hemoglobin estimation has been used since long. The International Nutritional Anemia Consultive Group (INACG) and International Committee for Standardization in Hematology (ICSH) have recommended the Drabkins as the method of choice and have suggested that all other methods should be adjusted to be comparable to this method.19  The principle in Sahli’s method involves the conversion of hemoglobin to acid hematin and comparing visually the color developed with that of standard tinted glass. Hemoglobin value is directly read from the graduated hemoglobin tube. The Sahli’s method has many disadvantages including subjective visual color comparison. It is not sufficiently accurate because it shows wide scatter in inter observers and intra observer results distribution.20,21 Sahli’s method had good sensitivity in detection of anemic individuals, but low specificity and high rate of false positive results, which may leads to diagnosing healthy individuals as anemic.21,21

Various studies showed that Sahli’s method had lower haemoglobin values than the hemoglobin cyanide method. In a study by Kapil et al Sahli’s method compared to Hemocue had underestimated hemoglobin   concentration by 1.06gms/ dl.22 Natarajan S et al had also found that results of lower hemoglobin by 0.386 gms/dl in capillary blood on comparing Sahli’s method with the coulter auto analyzer.23

All the samples were processed by an experienced laboratory technician ensuring all precautions recommended for using Sahli’s method. However due to the lack of specificity of the Sahli’s method for diagnosing anemia, it would not be appropriate to comment on the higher prevalence of anemia obtained in the study.

WHO / UNICEF strongly advocate that when there is a prevalence of anemia above 40%, a universal supplementation is required and it is not cost-effective to screen children for anemia. This is in light of the fact that iron deficiency is almost universal when dealing with this magnitude of anemia. The findings from the current study justify the universal Weekly Iron and Folic Acid supplementation program for the school children in Kerala.

A properly conducted research study on the prevalence of anemia among adolescents in Kerala using a standardized technique for hemoglobin estimation, along with estimation of iron stores, is the matter of the hour. Such a study will help to formulate policies on iron supplementation programs at schools and also it would form a baseline for evaluating the anemia control interventions.

End Note

Author Information

  1. Dr. Rakesh SR, Medical Officer,
    Primary Health Centre, Mangode, Chithara, Kollam
  2. Dr. Ashimsha A, Medical Officer,
    Primary Health Centre, Madathara, Kollam
  3. Mr. Shanavas A, Health Supervisor,
    Kerala Health Services
  4. Mr Surendran VE, Health Supervisor,
    Kerala Health Services
  5. Dr. Rakesh PS, Epidemiologist,
    Integrated Disease Surveillance Project,
    District Medical Office, Kollam.
    E-mail: rakeshrenjini@gmail.com
    Phone: 9495537333
  6. Dr. Subhagan S, District Programme Manager, NRHM, Kollam
  7. Dr. Salila K, District Medical Officer, Kollam.    

Conflict of Interest: None declared

References

  1. World Health Organization. Anemia prevention and control [Internet]. Geneva:WHO;2011 [cited2013Aug20]
  2. Gupta S, Taraphdar P, Roy TG, Haldar D, Dey SK, Purkait B. The silent burden of anemia in school age children: a community based study in West Bengal. Indian J Med Sci. 2012 Aug; 66(7-8):163–8. [Pubmed][Crossref]
  3. Rawat CMS, Garg SK, Singh JV, Bhatnagar M, Chopra H. Sociodemographic correlates of anemia among adolescent girls in rural area of district Meerut (U.P). Indian J Community Med2001; 26: 173. [Source]
  4. Gupta N, Kochar GK. Pervasiveness Of Anemia In Adolescent Girls Of Low Socio-Economic Group Of The District Of Kurukshetra (Haryana). The Internet Journal of Nutrition and Wellness 2009; 7: 1. [Source]
  5. Rajini S. Prevalence of anemia and factors influencing among rural adolescent girls. Indian journal of maternal and child health 2010.
  6. Kaur S, Deshmukh PR, Garg B. Epidemiological correlates of nutritional anemia in adolescent girls of rural Wardha. Indian J Community Med 2010; 31: 4. [Pubmed]
  7. Rita Singh. Socio-demographic factors causing anemia in adolescent girls in Meerut. Health and Population-Perspectives and Issues 2008; 38: 198-203.  [Source]
  8. Chaudhary SM, Dhage VR. A study of anemia among adolescent females in the urban area of Nagpur. Indian J Community Med 2008; 33: 243-245. [Pubmed]
  9. Brownlie T, Utermohlen V, Hinton PS, Giordano C, Haas JD. Marginal iron deficiency without anemia impairs aerobic adaptation among previously untrained women. Am J Clin Nutr. 2002 Apr;75(4):734–42. [Pubmed] [Source]
  10. Oski FA. The nonhematologic manifestations of iron deficiency. Am. J. Dis. Child. 1979; 133(3):315-22. [Pubmed]
  11. Oppenheimer SJ. Iron and its relation to immunity and infectious disease. J. Nutr. 2001;131(2S-2):616-33. [Pubmed] | [Source]
  12. Grantham-McGregor S, Ani C. A review of studies on the effect of iron deficiency on cognitive development in children. J Nutr. 2001 Feb; 131(2S-2):649S – 666S; discussion 666S – 668S. [Pubmed] | [Source]
  13. Wintrobe MM. ‘Clinical Hematology’ 7th Edition. Philadelphia: Lea and Febiger; 1975, pp 114-115
  14. Anemia Detection Methods in Low- Resource Settings: A Manual for Health Workers. December 1997. Path. U.S. Agency for International Development. [Source]
  15. de Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007 Sep;85(9):660–7. [Pubmed] | [Crossref]
  16. World Health Organization. Iron Deficiency Anaemia: Assessment, Prevention, and Control. A guide for program managers [Internet].Geneva: WHO;2001 [cited 2013 Aug 21. [Source]
  17. Verma M, Chhatwal J, Kaur G. Prevalence of anemia among urban school children of Punjab.Indian Pediatr 1998; 35: 1181–1186. [Pubmed]
  18. Teoteja GS, Singh P. Micronutrient profile in Indian population (Part-l). New Delhi: Indian Council Medical Research, 2002; 131–140.
  19. Cook JD. Measurement of iron status. A report of the International Nutritional Anaemia Consultive Group (INACG).  New York: Washington DC; 1985, Ch.II: pp 4. [Source]
  20. Barduagni P, Ahmed AS, Curtale F, Raafat M, Soliman L. Performance of Sahli and colour scale methods in diagnosing anaemia among school children in low prevalence areas. Trop Med Int Health. 2003 Jul; 8(7):615–8. [Pubmed] | [Crossref]
  21. Barduagni P, Ahmed AS, Curtale F, Raafat M, Soliman L. Performance of Sahli and colour scale methods in diagnosing anaemia among school children in low prevalence areas. Trop Med Int Health. 2003 Jul; 8(7):615–8. [Pubmed] | [Crossref]
  22. Barduagni P, Ahmed A S, Curtale F, Raafat M, Soliman L. Performance of Sahli’s and Color scale method in diagnosing anaemia among school children in low prevalence areas. Tropical Medicine and International Health.2003; 8(7): 615- 618
  23. Morris SS, Ruel MT, Cohen RJ, Dewey KG, de la Brière B, Hassan MN. Precision, accuracy, and reliability of hemoglobin assessment with use of capillary blood. Am J Clin Nutr. 1999 Jun; 69(6):1243–8.[Pubmed] | [Source]
  24. Shrinivasan NM, Kasturba MP. Intra-operative point of care haemoglobin estimation: A comparison of three methods. Sri Lankan Journal of Anaesthesiology.2010; 18(1):15. [Source]