Rural-urban disparities in prevalence of anemia among adolescent girls in India
DOI:
https://doi.org/10.18203/2394-6040.ijcmph20175347Keywords:
Anaemia, Prevalence, Hemoglobin level, Adolescent girls and DLHS-4Abstract
Background: Anaemia continues to be a major public health problem at all ages worldwide. Today, every fifth person in India is an adolescent (Census, 2011). Anaemia effects adolescent girls critically by decreasing their capacity to do physical work, affects their growth as a result they are not well prepared for upcoming pregnancy and motherhood challenge. NFHS-3 reports indicated wide rural-urban disparity in prevalence of anaemia. The present study aims to explore rural-urban disparity in prevalence of anaemia and to study the factor associated with anaemia among adolescent girls in India.
Methods: District levels household survey (DLHS-4, 2012-13) was used for the present study. The outcome variables included in the study was anaemia. Bivariate analyses including chi square tests were applied to determine the prevalence of anaemia and logistic regression models to understand the determinants of anaemia. The whole analysis was performed using STATA version 13.0 to take into account the survey design (i.e. sampling weights with clustering and strata), QGIS, and R CRAN.
Results: The prevalence of anaemia was observed high in urban (65.3%) as compared to rural (57.3%). However, the prevalence of severe anaemia was high in rural area as compared to urban area. The mean hemoglobin level of the study population was 10.4±2.22. Prevalence of anaemia varies across key selected individual, household and community characteristics of adolescent girls. Finding of multivariate logistic regression analysis indicated that anemia has a strong relation with age, education, family size, religion, caste, economic status, sanitation facility and place of residence of adolescents.
Conclusions: This study concludes that the prevalence of anaemia is a significant problem of adolescent girls in India. The study also proved that anemia is significantly associated with age, education, income strata and place of residence.
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