DETERMINANTS OF UNDER FIVE MORTALITY OF ODISHA: NFHS-4 DATA ANALYSIS
Keywords:
Under Five Mortality, Logistic Regression, NFHS -4 DataAbstract
This study uses Nfhs-4 data to identify the correlations of under-five child mortality in Odisha, a crucial indicator for community health and economic development. A logistic regression model was used to investigate the impact of selected socioeconomic, demographic, health, and environmental factors on Odisha's child mortality (U5CM). The age of the mother covariates preceding birth interval, place of delivery, breast feeding, mother's education level, toilet facility, number of household members, caste, and source of drinking water. According to the results of data, which are the most important factors of children's death among numerous chosen socioeconomic levels of women. According to the Logit regression study, policymakers should encourage maternal education, late marriage, and increasing birth intervals through family planning to minimize child mortality.
References
I. United Nations. The Millennium Development Goals Report 2012, New York: United Nations. 2012.
II. IIPS and ICF. National Family Health Survey (NFHS-4), 2015-16, India. Mumbai: IIPS; 2017.
III. United Nations. Transforming our World: The 2030 Agenda for Sustainable Development, A/RES/70/1. New York: UN General Assembly; 2015.
IV. Registrar General of India. ‘Sample Registration System Statistical Report 2017’. New Delhi: Government of India; 2017.
V. Registrar General of India. ‘SRS based Abridged Life Tables, 1990-94 and 1991-95’ SRS Analytical Studies, Report No.1 of 1998. New Delhi: Government of India; 1998.
VI. Registrar General of India. SRS based Abridged Life Tables, 2003-07 to 2006-10. New Delhi: Government of India; 2012.
VII. IIPS and ICF. National Family Health Survey (NFHS-4), 2015-16: Odisha. Mumbai: IIPS. 2017.
VIII. Registrar General of India. District Level Estimates of Child Mortality in India based on 2001 census data. New Delhi: Government of India; 2009.
IX. Under-five Mortality Rate in Odisha: An Assessment of Trends and District Level Variations: Sibabrata Das
X. Correlates of under-five child mortality in ethiopia: a logistic regression analysis Kasahun. Takele Geneti and Teshome Kebede Deressa:Advances and Applications in Statistics © 2014 Pushpa Publishing House, Allahabad, India,Published Online: March 2014.
XI. Smith, G. C. (2001). Life-table analysis of the risk of perinatal death at term and post term in singleton pregnancies. American journal of obstetrics and gynecology, 184(3), 489-496.
XII. Liu, L., Hill, K., Oza, S., Hogan, D., Chu, Y., Cousens, S., ... & Black, R. E. (2016). Levels and causes of mortality under age five years. Reproductive, maternal, newborn, and child health, 11, 71.
XIII. Deshingkar, P. (2010). Migration, remote rural areas and chronic poverty in India (Vol. 323). ODI.
XIV. Kumar, C., Singh, P. K., & Rai, R. K. (2012). Under-five mortality in high focus states in India: district level geospatial analysis. Plos one, 7(5), e37515.
XV. Naline, G., & Viswanathan, B. (2019). Predictors of age-specific childhood mortality in India. Madras School of Economics.
XVI. Kundu, D., Pandey, A., Sharma, P., Bhusan, S., Mondal, B., Lahiri, B., ... & Vijh, S. (2018). India: National urban policies and city profiles for Delhi and Madurai. GCRF SHLC.
XVII. Menard, S. W. (2010). Logistic regression: From introductory to advanced concepts and applications. Sage.
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