Community effects on public health in India: A hierarchical model


The data on any aspect of public health, including that on infant mortality, has inbuilt hierarchical structure. Using traditional regression approach in data analysis, i.e., ignoring hierarchical structure, either at micro (individual) or at macro (community) level will be avoiding desired assumption related to independence of records. Accordingly, this may result into distortion in the results due to probable underestimation of standard error of the regression coefficients. To be more specific, an irrelevant co-variate may emerge as an important covariate leading to inappropriate public health implications. To overcome this problem, the objective of the present work was to deal with multilevel analysis of the data on infant mortality available under second round of National family Health Survey and notify changes in results under traditional regression analysis that ignores hierarchical structure of data. This method provides more accurate results leading to meaningful public health implications. In addition, estimation of variability at different levels and their covariance are also obtained. The results indicate that the community (e.g., state) level characteristics still have major role regarding infant mortality in India. Further, if computational facilities are available, multilevel analysis may be preferred in dealing with data involving hierarchical structure leading to accurate results having meaningful public health implications.

Share and Cite:

Dwivedi, S. , Begum, S. , Dwived, A. and Pandey, A. (2012) Community effects on public health in India: A hierarchical model. Health, 4, 526-536. doi: 10.4236/health.2012.48084.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Bryk, A.S. and Raudenbush, S.W. (1992) Hierarchical linear models (applications and data analysis methods). Sage Publications, New York.
[2] Goldstein, H. and Healy, M.J.R. (1995) The graphical presentation of a collection of means. Journal of the Royal Statistical Society Series A, 158, 175-177. doi:10.2307/2983411
[3] Mosley, W.H. (1984) Child survival: Research and policy. Population and Development Review, 10, 3-23. doi:10.2307/2807953
[4] Nath, D.C., Kenneth, C.L. and Talukdar, P.K. (1994) Most recent birth interval in a traditional society: A life table and hazards regression analysis. Canadian Studies in Population, 21, 149-164.
[5] Kalbfleisch, J.D. and Prentice, R.L. (1980) The statistical analysis of failure time data. John Wiley and Sons, New York.
[6] Cox, D.R. (1972) Regression models and life tables (with discussion). Journal of Royal Statistical Society, B34, 187-220.
[7] Menken, J., Trussel, J., Stempel, D. and Bahakol, O. (1981) Proportional hazard life table models: An illustrative analysis of socio-economic influences on marriage dissolution in the United States. Demography, 18, 181-200. doi:10.2307/2061092
[8] Retherford, R.D. and Minja, K.C. (1993) Statistical models for casual analysis. John Wiley & Sons, Inc., New York. doi:10.1002/9781118033135
[9] Trussell, J. and Charles, H. (1983) A hazards model analysis of the covariates of infant and child mortality in Sri Lanka. Demography, 20, 1-24. doi:10.2307/2060898
[10] Namboodiri, N.K. and Suchindran, C.M. (1987) Life table techniques and their applications. Academic Press, Orlando.
[11] Kleinbaum, D.G. (1996) Survival Analysis. Statistics in health sciences. Springer-Verlag, New York.
[12] Nath, D.C., Land, K.C. and Singh, K.K. (1994) Birth spacing, breastfeeding, and early child mortality in a traditional Indian society: A hazard model analysis. Social Biology, 41, 168-180.
[13] Hobcraft, J.J., McDonald, W. and Rustien, S. (1983) Child-spacing effects on infant and early child mortality. Population Index, 49, 585-618. doi:10.2307/2737284
[14] Maine, D. and McNamara, R. (1985) Birth spacing and child survival. Center for Population and Family Health, School of Public Health, Faculty of Medicine, Columbia University, New York.
[15] UNFPA (1997) Reproductive rights, reproductive health and family planning: Population issues.
[16] Khorshed, A.B.M., Alam, M. and James, F.P. (1990) A multivariate analysis of social and economic determinants of neonatal and infant mortality in four rural thanas of Bangladesh. Demography India, 19, 167-182.
[17] Swenson, I.E., Nguyen, M.T., Pham, B.S., Vu, Q.N. and Vu, D.M. (1993) Factors influencing infant mortality in Vietnam. Journal of Biosocia Science, 25, 285-302. doi:10.1017/S0021932000020630
[18] Bloland, P., Slutsker, L., Steketee, R.W., Wirima, J.J., Heymann, D.L. and Breman, J.G. (1996) Rates and risk factors for mortality during the first two years of life in rural Malawi. American Journal of Tropical Medicine and Hygiene, 55, 82-86.
[19] Koeing, M.A., Phillips, J.A., Campbell, O. and D’Souza, D. (1990) Birth intervals and childhood mortality in rural Bangladesh. Demography, 27, 251-265. doi:10.2307/2061452
[20] Miller, J.E., Trussell, J., Anne, R.P. and Barbara, V. (1992) Birth spacing and child mortality in Bangladesh and the Philippines. Demography, 29, 305-316. doi:10.2307/2061733
[21] Mturi, A.J. and Curtis, S.L. (1995) The determinants of infant and child mortality in Tanzania. Health Policy Plan, 10, 384-394. doi:10.1093/heapol/10.4.384
[22] Ronsman, C. (1996) Birth spacing and child survival in Rural Senegal. International Journal of Epidemiology, 25, 989-997. doi:10.1093/ije/25.5.989
[23] Manda, S.O. (1999) Birth intervals, breastfeeding and determinants of childhood mortality in Malawi. Social Science Medicine, 48, 301-312. doi:10.1016/S0277-9536(98)00359-1
[24] Chaudhary, S.B., Ibrahim, K.R. and Md. A.M. (2000) Impact of some biosocial variables on infant and child mortality. Demography India, 29, 211-221.
[25] Palloni, A. and Millman, S. (1986) Effects of inter-birth intervals and breastfeeding on infant and early childhood mortality, Population. Studies, 40, 215. doi:10.1080/0032472031000142036
[26] Pandey, A., Minja, K.C., Norman, Y.L., Damodar, S. and Jagdish, C. (1998) Infant and child mortality in India. National Family Health Survey Subject Reports No. 11, IIPS, Bombay and East West Centre Program on Population, Honolulu.
[27] Arnold, F., Minja, K.C. and Roy, T.K. (1998) Son preference, the family-building process and child mortality in Inida. Population Studies, 52, 301-315. doi:10.1080/0032472031000150486
[28] International Institute for Population Sciences (IIPS) (2000) National family health survey, India, 1992-1993.
[29] Dwivedi, S.N. and Sundaram, K.R. (2000) Epidemiological models and related simulation results for understanding of contraceptive adoption in India. International Journal of Epidemiology, 29, 300-307. doi:10.1093/ije/29.2.300
[30] Steele, F., Diamond, I. and Wang, D. (1996) The determinants of contraceptive use in China: A multilevel multinomial discrete hazards modelling approach. Demography, 33, 12-24. doi:10.2307/2061710

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.