Community effects on public health in India: A hierarchical model

Abstract

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 covariate 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.

Determinants of infant mortality in rural India: A three-level model

“…The data used in the present study are from the National Family Health Survey (NFHS), 1998-1999, conducted for the second time in India. The details about sampling methods, used questionnaires, methods of data collection and all other aspects are already documented [1,6]. The detailed information on antenatal, delivery and postnatal care was obtained for the two most recent births that occurred to eligible women during the three years preceding the survey.…”

“…The detailed information on antenatal, delivery and postnatal care was obtained for the two most recent births that occurred to eligible women during the three years preceding the survey. For analysis, to restore the correct proportion in view of no self-weighting of the sample design, the country-level weight was used [1]. As considered earlier [1], in present analysis also, infant mortality was taken as dependent variable (i.e., child who died before his/her first birthday) in the last three years preceding the survey (0 = alive, died = 1).…”

“…The infant mortality rate (IMR) still remains an important public health indicator [2,3]. Its data structures are often hierarchical in nature, especially those available at national/state/district/village/household/individual level [1][2][3][4][5]. Hence, as reported earlier, data on IMR need to be dealt with hierarchical/multilevel analysis that takes hierarchical structure into account and also makes it possible to incorporate variables from all levels and retains them at their own levels [1].…”

“…However, for better epidemiological understanding in rural areas where the largest population of the country lives, data relate to only rural India. The analytical methods involved a three-level model instead of earlier two-level models [1]. At regional level, an appropriate epidemiological understanding from time to time may be helpful to policy planners.…”

Trends and Determinants of Infant Mortality in Emp

“…Both bivariate and multivariate analysis indicate that children born during 2005-2006 and during 1996-99, the hazard risk of infant mortality was less compared to the period 1992-1993. As true in the case of infant mortality in India [27], and earlier study shown that the infant mortality varies by socio-economic and demographic characteristics, and also reveals that those mothers have comparatively lower education whose children are more likely to die before celebrating their first birthday [28]. Earlier studies reveals that the birth order and birth interval of the child significantly associated with mortality [29] and a study on utilization of maternal health care services suggested that higher mortality risk among first order birth could be linked to the early childbearing trends and lower utilization of maternity health care services in developing countries like India [30].…”