Prevalence and determinants of anemia among school going children in the state of Tamil Nadu, India: applications of two-level logistic regression model

Anil C. Mathew; Sharon Mathew P. R.; Krishna Nair; Kamakshi Priya K.; Ramesh S.

doi:10.18203/2394-6040.ijcmph20233773

Authors

Anil C. Mathew Department of Community Medicine, PSG Institute of Medical Sciences and Research, Tamil Nadu, India
Sharon Mathew P. R. Department of Biostatistics, St. Thomas College, Kerala, India
Krishna Nair Department of Biostatistics, St. Thomas College, Kerala, India
Kamakshi Priya K. Department of Community Medicine, PSG Institute of Medical Sciences and Research, Tamil Nadu, India
Ramesh S. Department of Paediatrics, PSG Institute of Medical Sciences and Research, Tamil Nadu, India

DOI:

https://doi.org/10.18203/2394-6040.ijcmph20233773

Keywords:

Anemia, School going children, Prevalence, Hookworm infection, Tamil Nadu

Abstract

Background: Anemia still remains as one of the major public health problems in India despite implementing preventive measures. The objective was to find the prevalence and determinants of anemia among school going children in Tamil Nadu.

Methods: We used the data from the fourth round of district level household survey (DLHS-4) for Tamil Nadu pertaining to the year 2012-13. Our analysis included 23997 children. Descriptive statistics, Random intercept and empty models of two-level logistic regression analysis were used.

Results: The overall prevalence of anemia was found to be 41.4% (95% CI: 40.77%-42.02%). We observed a district level variation on anemia (District level variance=0.1, p<0.001) and the intra class correlation coefficient was 0.0295. The prevalence of anemia was more in coastal districts as compared to non-coastal districts (43.85% vs. 40.18%, p<0.001). Variables that are found to have significant association with anemia on multilevel analysis were younger age (Adjusted odds ratio (AOR)=1.343, 95% CI: 1.270-1.420), female children (AOR=1.462, 95% CI: 1.387-1.541), more than eight family members in the household (AOR=1.120, 95% CI: 1.008-1.245), rural residence (AOR=1.103, 95% CI: 1.038-1.172) and lower standard of living (AOR=1.203, 95% CI: 1.084-1.334).

Conclusions: Half of school going children were anemic in the state. Geospatial distribution of anemia varied significantly. Governments and regional health centres should take adequate measures to avert the consequences of anemia in school going children considering these factors.

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References

World Health Organization. Conclusions and recommendations of the WHO Consultation on prevention and control of iron deficiency in infants and young children in malaria-endemic areas. Food Nutr Bull. 2007;28:621-7.

Warner MJ, Kamran MT. Iron Deficiency Anemia. StatPearls Treasure Island (FL). 2021.

Lutter CK. Iron deficiency in young children in low-income countries and new approaches for its prevention. J Nutr. 2008;138(12):2523-8.

Onyeneho, NG, Ozumba C, Subramanian SV. Determinants of Childhood Anemia in India. Sci Rep. 2019;9(1):16540.

Calis JC, Phiri KS, Faragher EB, Brabin BJ, Bates I, Cuevas LE et al. Severe anemia in Malawian children. N Engl J Med. 2008;358(9):888-99.

Chaparro CM, Suchdev PS. Anemia epidemiology, pathophysiology, and etiology in low- and middle-income countries. Ann New York Acad Sci. 2019;1450(1):15-31.

Pasricha SR, Black J, Muthayya S, Shet A, Bhat V, Nagaraj S et al. Determinants of anemia among young children in rural India. Pediatrics. 2010;126(1):140-9.

Madhusudan JV, Jeetendrayadav, Singh KH, Utpal Dhar Das. Prevalence and Determinants of Anemia among School going Children in Meghalaya. Demogr India. 2018;47:38-46.

Swain PK, Singh P, Priyadarshini S. Determinants of home deliveries - Findings from India DLHS 4 analysis. J Family Med Prim Care. 2020;9:4723-8.

International Institute for Population Sciences. National Family Health Survey (NFHS-2), 1998–99: India. Mumbai: International Institute for Population Sciences (IIPS) and ORC Macro. 2000.

Solon G, Haider SJ, Wooldridge JM. What Are We Weighting For? J Hum Resource. 2015;50:301-16.

International Institute for Population Sciences. District Level Household and Facility Survey (DLHS-3), 2007-2008; India. Mumbai: IIPS. 2010.

Talukder A, Hossain MZ. Prevalence of Diabetes Mellitus and Its Associated Factors in Bangladesh: Application of Two-level Logistic Regression Model. Sci Rep. 2020;10:10237.

Sommet N, Morselli D. Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS. Int Rev Soc Psycol., 2017;30:203-18.

Park S, Lake ET. Multilevel modeling of a clustered continuous outcome: nurses' work hours and burnout. Nurs Res. 2005;54:406-13.

Anteneh ZA, Van Geertruyden JP. Spatial variations and determinants of anemia among under-five children in Ethiopia, EDHS 2005-2016. PLoS One. 2021;16:e0249412.

World Health Organization. Nutritional anaemias: tools for effective prevention and control. Geneva: World Health Organization. 2017.

Smith JL, Brooker S. Impact of hookworm infection and deworming on anaemia in non-pregnant populations: a systematic review. Trop Med Int Health. 2010;15:776-95.

Hotez PJ, Brooker S, Bethony JM, Bottazzi ME, Loukas A, Xiao S. Hookworm infection. N Engl J Med. 2004;351:799-807.

Kuong K, Fiorentino M, Perignon M, Chamnan C, Berger J, Sinuon M et al. Cognitive Performance and Iron Status are Negatively Associated with Hookworm Infection in Cambodian Schoolchildren. Am J Trop Med Hyg. 2016;95:856-63.

Saljoughian M. Iron Deficiency Anemia: A Closer Look. US Pharm. (2007). 32: HS26-HS37.

Moschovis PP, Wiens MO, Arlington L, Antsygina O, Hayden D, Dzik W et al. Individual, maternal and household risk factors for anaemia among young children in sub-Saharan Africa: a cross-sectional study. BMJ Open. 2018;8:e019654

Kim JY, Shin S, Han K, Lee CK, Kim JH, Choi YS et al. Relationship between socioeconomic status and anemia prevalence in adolescent girls based on the fourth and fifth Korea National Health and Nutrition Examination Surveys. Eur J Clin Nutr. 2014;68:253-8.