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Demographic Transition in India: An Evolutionary Interpretation of Population and Health Trends Using ‘Change-Point Analysis’
BACKGROUND AND RATIONALE: 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 i...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3799745/ https://www.ncbi.nlm.nih.gov/pubmed/24204621 http://dx.doi.org/10.1371/journal.pone.0076404 |
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author | Goli, Srinivas Arokiasamy, Perianayagam |
author_facet | Goli, Srinivas Arokiasamy, Perianayagam |
author_sort | Goli, Srinivas |
collection | PubMed |
description | BACKGROUND AND RATIONALE: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS: 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. |
format | Online Article Text |
id | pubmed-3799745 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37997452013-11-07 Demographic Transition in India: An Evolutionary Interpretation of Population and Health Trends Using ‘Change-Point Analysis’ Goli, Srinivas Arokiasamy, Perianayagam PLoS One Research Article BACKGROUND AND RATIONALE: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS: 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. Public Library of Science 2013-10-18 /pmc/articles/PMC3799745/ /pubmed/24204621 http://dx.doi.org/10.1371/journal.pone.0076404 Text en © 2013 Goli, Arokiasamy http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Goli, Srinivas Arokiasamy, Perianayagam Demographic Transition in India: An Evolutionary Interpretation of Population and Health Trends Using ‘Change-Point Analysis’ |
title | Demographic Transition in India: An Evolutionary Interpretation of Population and Health Trends Using ‘Change-Point Analysis’ |
title_full | Demographic Transition in India: An Evolutionary Interpretation of Population and Health Trends Using ‘Change-Point Analysis’ |
title_fullStr | Demographic Transition in India: An Evolutionary Interpretation of Population and Health Trends Using ‘Change-Point Analysis’ |
title_full_unstemmed | Demographic Transition in India: An Evolutionary Interpretation of Population and Health Trends Using ‘Change-Point Analysis’ |
title_short | Demographic Transition in India: An Evolutionary Interpretation of Population and Health Trends Using ‘Change-Point Analysis’ |
title_sort | demographic transition in india: an evolutionary interpretation of population and health trends using ‘change-point analysis’ |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3799745/ https://www.ncbi.nlm.nih.gov/pubmed/24204621 http://dx.doi.org/10.1371/journal.pone.0076404 |
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