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2 - Demographic Dividend in India
- Edited by K. S. James, International Institute for Population Sciences, Mumbai, T. V. Sekher, International Institute for Population Sciences, Mumbai
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- Book:
- India Population Report
- Published online:
- 15 August 2023
- Print publication:
- 27 June 2024, pp 21-45
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Summary
Introduction
The demographic dividend has been the subject matter of immense interest across countries, among both scholars and policymakers in recent decades. It is also known as the demographic window of opportunities, implying that considerable opportunities exist for nations due to the favourable changes in the age structure brought about by fertility decline. The demographic dividend is the result of an increase in the share of the working-age population and a decline in the combined share of the old- and young-age dependant population. The swelling of the working-age population may cause a rise in the supply of labour force in the market, a decline in the child population may cause a shift in demand for household resources from investment in children to greater capital investment, and fertility decline may allow a rise in female workforce participation (Bloom et al., 2009).
The debate on the change in the population structure and economic growth has been a well-researched and discussed issue that was initiated by Thomas Robert Malthus. Later, Coale and Hoover (1958), in a seminal work, estimated the economic benefits of fertility decline, taking India also as an example. Similarly, Kuznets (1967) found that a population increase negatively affects the economic development of a country. On the contrary, Kelley (1988) observed that there is no universal association between population increase and growth in per capita income and savings rates. On the other hand, Lutz et al. (2019), using the panel data of 165 countries, documented that the human capital as measured by educational attainment causes a change in the age structure and economic development. Despite these mixed findings on the relationship between population and development, a large number of studies established that the change in the age structure itself has inevitable economic benefits (Lee and Mason, 2006; Bloom et al., 2010; James, 2008; Joe, Kumar, and Rajpal, 2018; Mason, Lee, and Lee, 2010).
Even while the demographic dividend potential is well recognized in India, there are many pessimistic views expressed on the ability of the country to take advantage of demographic changes due to several institutional constraints. The primary argument against expecting a substantial demographic dividend in India rests on the poor skill levels in the country and the lack of job opportunities. Of these, the lack of significant increase in female labour-force participation has attracted wide attention in recent times (Desai, 2010; Klasen and Pieters, 2012).
Pharmacogenetic Association Between Glutamatergic Genes and Sri Treatment Response in Obsessive Compulsive Disorder
- T. Shukla, R.M.J. Jabeen Taj, K. Kulkarni, P. Shetty, B. Viswanath, M. Purushottam, Y.C. Reddy, S. Jain
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- Journal:
- European Psychiatry / Volume 41 / Issue S1 / April 2017
- Published online by Cambridge University Press:
- 23 March 2020, p. S111
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- Article
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Introduction
Pharmacogenetic studies in obsessive-compulsive disorder (OCD) primarily focussing on serotonergic and dopaminergic polymorphisms, provided inconsistent findings. There is recent evidence for glutamatergic abnormalities in OCD.
AimsExamine the association glutamatergic genes with serotonin reuptake inhibitor (SRI) response in OCD.
ObjectivesTo study pharmacogenetic association between SLC1A1 and GRIN2B polymorphisms with SRI response in OCD.
MethodsDSM-IV OCD patients were recruited from a specialty OCD clinic and evaluated using the Yale-Brown obsessive compulsive scale (YBOCS), Mini International Neuropsychiatric Interview (MINI) plus, Clinical Global Impression scale (CGI). They were subsequently reassessed with YBOCS and CGI. To study extreme phenotypes, we included only full responders (> 35% YBOCS improvement and CGI-I score of 1 or 2) to any SRI (n = 191) and non-responders (< 25% YBOCS improvement and CGI-I score ≥ 4) to adequate trial of at least two SRIs (n = 84). Partial responders were excluded. Genotyping was performed using an ABI9700 PCR machine.
ResultsGenotype frequencies did not deviate significantly from the values predicted by the Hardy-Weinberg equation. Case-control association analyses revealed no significant association between genotype/allele frequencies with SRI response.
ConclusionOur data does not show any association between polymorphisms in glutamatergic genes and SRI response in OCD though such associations have been found in other studies. More SNP's in the same gene could be responsible for the pharmacogenetic associations. More homogenous sample considering symptom dimensions and other phenotypic variables may be needed. It may be critical to go beyond “usual suspect” candidate gene research. In this regard, a novel approach to identify SRI response biomarkers is the use of cellular models.
Disclosure of interestThe authors have not supplied their declaration of competing interest.