Page 120 - 5th APA Conference Program Book Final
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IIPS, Mumbai, India
Categories
4. Mortality, Morbidity, Epidemiology and Causes of Death
Abstract
The present study aims to analyze the nutritional status and vaccination coverage of children aged 12-23 months
in the district and establish a relationship of Encephalitis with the malnutrition status of children in the Muzaffarpur
district, Bihar. We also tried to analyze the situation of clustering of undernutrition and not immunized in the rural
area of Muzaffarpur districts according to poor-non poor households. The latest round of National Family Health
survey, 2015-16, was used and cross-tabulation analysis was conducted to determine the impact of vaccination
coverage and wealth index on the nutritional status of children. The analysis shows that 43% of children were
stunted and did not get full vaccination. The situation of economically poor was even worse i.e. 45% stunted, 48%
wasted and 43% underweight poor children were not fully vaccinated. Also, the wasting in the month of
heatwaves was found to be higher than other months which makes the child more susceptible to acquiring the
morbidity. A proper system is needed to monitor the growth of children. Anganwadi workers should help women
to understand the importance of healthy food. Also, a strong surveillance system together should be
implemented with a high quality of immunization program.
192 Exploring Geographical Variance of Complete Immunization Coverage in India:
A District-level Spatial Modelling Approach
Monirujjaman BISWAS
Jawaharlal Nehru University, New Delhi, India
Categories
4. Mortality, Morbidity, Epidemiology and Causes of Death
Abstract
This study aims to explore place-specific spatially varying relationships between district-level complete
th
immunization coverage and socio-economic and healthcare factors in India using the 4 wave of the National
Family Health Survey (NFHS 2015–16). The dependent variable was fully immunized children aged 12–23 months.
Univariate Moran’s I and LISA, Ordinary least square (OLS) and Geographically weighted regression (GWR) models
were employed to decrypt location-based analysis for 640 districts of India. The GWR results revealed that the
relationships between the outcome and its cofactors were significantly place-specific and spatially clustering in
terms of their respective magnitude, direction, and differences due to the significance of local characteristics.
Regarding model performance and prediction accuracy, the GWR results insight better fit compared to the
traditional one. A modelling based on GWR and OLS regression showed important risk factors as well as to
understand the occurrence of complete immunization hot-spots in India. The findings contribute to the ongoing
debate on India’s complete immunization coverage by highlighting the spatial local dependencies and
heterogeneities cannot be disclosed by a single-story, either government health interventions or socio-economic
and healthcare development. Therefore, place and context-specific policies should be designed to reduce
geographical disparities in immunization coverage in India.
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