Demographic Transition in India: An Evolutionary Interpretation of Population and Health Trends Using ‘Change-Point Analysis’

<div><p>Background and Rationale</p><p>Lack of a robust analytical tool for trend analysis of population and health indicators is the basic rationale of this study. In an effort to fill this gap, this study advances ‘Change-Point analyzer’ as a new analytical tool for assessment of the progress and its pattern in population and health indicators.</p><p>Methodology/Principal Findings</p><p>The defining feature of ‘change-point analyzer’ is that, it detects subtle changes that are often missed in simple trend line plots and also quantified the volume of change that is not possible in simple trend line plots. A long-term assessment of ‘change-point analyses’ of trends in population and health indicators such as IMR, Population size, TFR, and LEB in India show multiple points of critical changes. Measured change points of demographic and health trends helps in understanding the demographic transitional shifts connecting it to contextual policy shifts. Critical change-points in population and health indicators in India are associated with the evolution of structural changes in population and health policy framework.</p><p>Conclusions</p><p>This study, therefore, adds significantly to the evolutionary interpretation of critical change-points in long-term trajectories of population and health indicators vis-a-vis population and health policy shifts in India. The results have not only helped in reassessing the historical past and the current demographic transition trajectory but also advanced a new method of assessing the population and health trends which are necessary for robust monitoring of the progress in population and health policies.</p></div

Change Point Analyses of Trend in Life Expectancy at Birth for India, 1872–2011.

<p>Note: 1. UCL- Upper side of Confidence Level; LCL- Lower side of Confidence Level. 2. Level- Confidence Level. Source: 1. ^# Mitra, 2005 documented LEB estimates based on Registrar General of India and Census during 1872–1941. The estimates presented in the table are male female averages. 2. **Rele, 1987. 3. Office of Registrar General of India, 1970–2006. 4. *UNDP, 2011.</p

Odds ratios showing the relationship of birth preparedness on check up after delivery and other background characteristic - Result of logistic analysis.

<p>Significance levels- p<0.10*, p<0.05**, p<.01***.</p

Composition of women by birth preparedness levels in Nepal, 2011.

<p>Composition of women by birth preparedness levels in Nepal, 2011.</p

Change Point Analyses of Trend in Population Size for India, 1856–2011.

<p>Note: 1. UCL- Upper side of Confidence Level; LCL- Lower side of Confidence Level. 2. Level- Confidence Level. 3. # Estimates based on Mukherjee (1969).</p

Percentage distribution of women by arrangement (Yes/No) of different birth preparedness tools, Nepal, 2011.

<p>Percentage distribution of women by arrangement (Yes/No) of different birth preparedness tools, Nepal, 2011.</p

Levels of Birth Preparedness by background characteristics, Nepal, 2011.

<p>Significance Levels- p<0.10*, p<0.05**, p<.01***.</p

Change Point Analyses of Trend in Infant Mortality Rate for India, 1901–2008.

<p>Note: 1. UCL- Upper side of Confidence Level; LCL- Lower side of Confidence Level. 2. Level- Confidence Level. <i>Source:</i> 1. ^#Rele, 1987. 2. Office of Registrar General of India, 1971–2008. 3. * Excludes Jammu & Kashmir due to non-receipt of returns.</p

Change Point Analyses of Trend in Total Fertility Rate for India, 1951–2009.

<p>Note: 1. UCL- Upper side of Confidence Level; LCL- Lower side of Confidence Level. 2. Level- Confidence Level. 3. * Excludes Jammu & Kashmir due to non-receipt of returns. Source: 1. ^#Rele, 1987. 2. Office of Registrar General of India, 1971–2005.</p

Pathways of Economic Inequalities in Maternal and Child Health in Urban India: A Decomposition Analysis

<div><p>Background/Objective</p><p>Children and women comprise vulnerable populations in terms of health and are gravely affected by the impact of economic inequalities through multi-dimensional channels. Urban areas are believed to have better socioeconomic and maternal and child health indicators than rural areas. This perception leads to the implementation of health policies ignorant of intra-urban health inequalities. Therefore, the objective of this study is to explain the pathways of economic inequalities in maternal and child health indicators among the urban population of India.</p> <p>Methods</p><p>Using data from the third wave of the National Family Health Survey (NFHS, 2005–06), this study calculated relative contribution of socioeconomic factors to inequalities in key maternal and child health indicators such as antenatal check-ups (ANCs), institutional deliveries, proportion of children with complete immunization, proportion of underweight children, and Infant Mortality Rate (IMR). Along with regular CI estimates, this study applied widely used regression-based Inequality Decomposition model proposed by Wagstaff and colleagues.</p> <p>Results</p><p>The CI estimates show considerable economic inequalities in women with less than 3 ANCs (CI  = −0.3501), institutional delivery (CI  = −0.3214), children without fully immunization (CI  = −0.18340), underweight children (CI  = −0.19420), and infant deaths (CI  = −0.15596). Results of the decomposition model reveal that illiteracy among women and her partner, poor economic status, and mass media exposure are the critical factors contributing to economic inequalities in maternal and child health indicators. The residuals in all the decomposition models are very less; this implies that the above mentioned factors explained maximum inequalities in maternal and child health of urban population in India.</p> <p>Conclusion</p><p>Findings suggest that illiteracy among women and her partner, poor economic status, and mass media exposure are the critical pathways through which economic factors operate on inequalities in maternal and child health outcomes in urban India.</p> </div