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Determinants of Antenatal Care Utilisation in India: A Count Data Modelling Approach

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  • Arvind Kumar Yadav
  • Susanta Nag
  • Pabitra Kumar Jena
  • Kirtti Ranjan Paltasingh

Abstract

The article explores the micro-level factors (social, economic and demographic) that determine the utilisation of antenatal care (ANC) services in India using the Bayesian count data regression model. The primary purpose is to rectify the methodological loopholes in the existing literature using a count data regression model that overcomes the problems of overdispersion in the data. Using data from ‘National Family Health Survey’ (NFHS) data on women of reproductive age (15–49 years), we find that about 33% of pregnant women have not availed ANC during their pregnancy. The factors such as women’s education and partner/husband’s education, children’s birth order, household income, availability of basic amenities, like clean drinking water, media exposure, holding of bank accounts and use of mobile phones are statistically significant and positively affect ANC utilisation. Therefore, the study calls for prioritisation of and special attention to uneducated or less educated rural pregnant women. They should be incentivised adequately to utilise ANC services, which may drastically reduce inadequacy in ANC utilisation and improve mothers’ health before and after delivery. Awareness camps should be organised in every village in rural areas about pregnancy-related complications and the benefits of ANC check-ups. Massive infrastructure in the form of primary health centres or community health centres is the need of the hour in rural India.

Suggested Citation

  • Arvind Kumar Yadav & Susanta Nag & Pabitra Kumar Jena & Kirtti Ranjan Paltasingh, 2021. "Determinants of Antenatal Care Utilisation in India: A Count Data Modelling Approach," Journal of Development Policy and Practice, , vol. 6(2), pages 210-230, July.
    • Handle: RePEc:sae:jodepp:v:6:y:2021:i:2:p:210-230
    DOI: 10.1177/24551333211030349
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    References listed on IDEAS

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    1. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    2. Habibov, Nazim N., 2011. "On the socio-economic determinants of antenatal care utilization in Azerbaijan: evidence and policy implications for reforms," Health Economics, Policy and Law, Cambridge University Press, vol. 6(2), pages 175-203, April.
    3. Pravin Trivedi & David Zimmer, 2017. "A Note on Identification of Bivariate Copulas for Discrete Count Data," Econometrics, MDPI, vol. 5(1), pages 1-11, February.
    4. Rainer Winkelmann, 2008. "Econometric Analysis of Count Data," Springer Books, Springer, edition 0, number 978-3-540-78389-3, June.
    5. Deb, Partha & Trivedi, Pravin K, 1997. "Demand for Medical Care by the Elderly: A Finite Mixture Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 313-336, May-June.
    6. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    7. Saleema Razvi & Debashis Chakraborty, 2016. "Does Economic Freedom Influence Major Health Indicators in India? Cross-state Panel Estimation Results," Journal of Development Policy and Practice, , vol. 1(2), pages 203-221, July.
    8. Daniel B. Hall, 2000. "Zero-Inflated Poisson and Binomial Regression with Random Effects: A Case Study," Biometrics, The International Biometric Society, vol. 56(4), pages 1030-1039, December.
    9. Kevin E. Staub & Rainer Winkelmann, 2013. "Consistent Estimation Of Zero‐Inflated Count Models," Health Economics, John Wiley & Sons, Ltd., vol. 22(6), pages 673-686, June.
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