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2018 | OriginalPaper | Buchkapitel

6. Deaths in the Family

verfasst von : Vani Kant Borooah

Erschienen in: Health and Well-Being in India

Verlag: Springer International Publishing

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Abstract

The purpose of this chapter is to evaluate the relative strengths of economic and social status in determining deaths in households in India. The first part of the chapter focuses on the “age at death” using National Sample Survey data for 2004 and 2014. The purpose was to ask whether after controlling for non-community factors, the fact that Indians belonged to different social groups, encapsulating different degrees of social status, exercised a significant influence on their age at death? The existence of a social group effect would suggest that there was a “social gradient” to health outcomes in India. The second part of the chapter, using data from the Indian Human Development Survey of 2011, investigated the determinants of infant and child mortality. The overriding concern now is gender bias with girls more likely to die than boys before attaining their first (infant) and fifth (child) birthdays. As this study has shown, gender bias in infant and child mortality rates is, with singular exceptions, a feature of all the social groups. In conducting this investigation, the chapter addresses for India an issue which lies at the heart of social epidemiology: estimating the relative strengths of individual and social factors in determining mortality outcomes.

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Vorheriges Kapitel The Health of Elderly Persons

Nächstes Kapitel Inequality and Well-Being

Psychologists distinguish between stress caused by a high demand on one’s capacities—for example, tight deadlines—and stress engendered by a low sense of control over one’s life.

There are about 85 million Indians classified as belonging to the “Scheduled Tribes”; of these, the term Adivasis (meaning “original inhabitants”) refers to the 70 million who live in the heart of India, in a relatively contiguous hill and forest belt extending across the states of Gujarat, Rajasthan, Maharashtra, Madhya Pradesh, Chhattisgarh, Jharkhand, Andhra Pradesh, Orissa, Bihar and West Bengal (Guha 2007).

The “Scheduled Castes” (or Dalits), who number about 18 million, are those who belong to the formerly “untouchable” castes, i.e. those with whom physical contact—most usually taken to be the acceptance of food or water—is regarded by upper-caste Hindus as ritually polluting or unclean.

The female-to-male ratio is substantially below unity in several developing countries: in 2015, it was 0.94 in China, 0.93 in India, and 0.94 in Pakistan (CIA 2015).

See Tendulkar (2007).

It is important to draw attention to the fact that all the results reported in this chapter are based upon grossing up the Survey data using the observation-specific weights provided by the NSS for each of the Surveys.

Figures for religion relate to the 71st Round. The 60th Round figures are similar and not shown. This category also included 3063 Muslim households. Since Muslim ST persons are entitled to reservation benefits these households have been retained in the ST category.

This category also included some Muslim households. However, since Muslims from the SC are not entitled to SC reservation benefits, these Muslim SC households were moved to the Muslim OBC category.

Including Muslim SC households (see previous footnote).

Of the 2395 households in the 71st NSS Round which reported deaths in the previous year, 2310 households reported a single death, 82 households reported two deaths, and three households reported three deaths; of the 1716 households in the 60th NSS Round which reported deaths in the previous year, 1634 households reported a single death, 70 households reported two deaths, and 12 households reported three deaths.

All the figures in Fig. 6.1 relate to households whose social group was defined in terms of one of the five categories: ST, SC, NMOBC, Muslim, and NMUC. Of the 2395 households which reported a death in the 71st Round, and of the 1716 households which reported a death in the 60th Round, social group was defined for, respectively, 2384 and 1708 households.

Forward States were Himachal, Punjab, Chandigarh, Haryana, Delhi, West Bengal, Gujarat, D&D, D&N Haveli, Maharashtra, AP, Karnataka, Goa, Kerala, TN, Pondicherry, Telangana; Backward States were Uttaranchal, Rajasthan, UP, Bihar, Sikkim, Arunachal, Nagaland, Manipur, Mizoram, Tripura, Meghalaya, Assam, Jharkhand, Odisha, Chhattisgarh, Lakshadweep, A&N Islands.

Following the advice of Long and Freese (2014).

For example, if living in a “forward” state raises the average age at death and if ST households are disproportionately concentrated in “backward” states, then this will show up in the raw data as a low age at death for ST households; however, this age will be raised when the state of residence is controlled for.

The methodology underpinning these computations is that of “recycled predictions”, described in detail in Chapter 2.

For the 71st Round, this difference was only significant at the 10% level.

This Survey, described in Shariff (1999), was the precursor to the Survey data used in this chapter, discussed in the following section.

See, for example, the chapters in Jeffery and Basu (1996). See also Bose (2001) on this point.

See León-Cava et al. (2002) for a review of the benefits of breastfeeding. From these variables, this study had no information on the age of the mother at the time of a specific birth, whether that child was breastfed, and the place of delivery of that birth.

Niti Aayog (National Institution for Transforming India): http://niti.gov.in/content/infant-mortality-rate-imr-1000-live-births. Accessed 18 May 2017.

See Desai et al. (2015).

The distribution of mothers across the households was such that 30,396 households had just one mother and 3199 households had two mothers.

The IMR for India in 2013 was 40 (per 1000 births) and the CMR in 2012 was 52 (per 1000 births) as obtained from the Sample Registration System: http://www.business-standard.com/article/pti-stories/india-unlikely-to-meet-infant-mortality-rate-target-of-2015-114122100067_1.html. Retrieved on 27 April 2017.

For example, a predicted probability of 0.4 of an infant death translated as a predicted IMR of 40 per 1000 births.

In computing these probabilities, all the interactions between gender and social group and gender and region—Eq. (2.3)—were taken into account.

The fifth column of Tables 6.6 and 6.7 shows the probability of exceeding the observed z-value on the null hypothesis of no gender bias.

These are the SC for infant mortality and the ST for child mortality.

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Titel: Deaths in the Family
verfasst von: Vani Kant Borooah
Verlag: Springer International Publishing
Buch: Health and Well-Being in India
Print ISBN: 978-3-319-78327-7

Electronic ISBN: 978-3-319-78328-4

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-78328-4_6

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