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2018 | OriginalPaper | Buchkapitel

5. The Health of Elderly Persons

verfasst von : Vani Kant Borooah

Erschienen in: Health and Well-Being in India

Verlag: Springer International Publishing

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Abstract

This chapter uses data from India’s National Sample Survey (NSS), relating to respondents’ health outcomes between January and June 2014, to quantify a particular form of gender inequality: inequality in self-rated health (SRH) outcomes between men and women aged 60 years or over. In so doing, it makes five contributions to the existing literature. The first is in terms of analytical technique: this study contains a more detailed and nuanced exposition of the regression results than in previous studies. Second, it controls for environmental factors—such as poor drainage, absence of toilets or lack of ventilation in the kitchen—which might adversely impact on health and, in particular, affect the health of women more than that of men. Third, it takes account of interaction effects by which the effect of a variable on an elderly person’s SRH differed according to whether the person was male or female. Lastly, it examines whether SRH is correlated with objective health outcomes. In particular, this study answers two central questions. Did men and women, considered collectively, have significantly different likelihoods of “poor” SRH between the different regions/income classes/social groups/education levels? Did men and women, considered separately, have significantly different likelihoods of a “poor” SRH within a region/income class/social group/education level?

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Help in washing, getting dressed, walking, etc.

See also Maddox and Douglass (1973) and Idler and Benyamini (1997).

Sen (2002), however, cautions that SRH may understate the poor health of those lower down the socio-economic ladder since they may accept as normal ailments that their betters would regard as a health problem.

This may be because men and women suffer from different types of cancers with (possibly) different treatment costs. In the UK, more than half of new cancers to men are prostate, lung or bowel while more than half of new cancers to women are breast, lung or bowel (Cancer Research UK. http://www.cancerresearchuk.org/health-professional/cancer-statistics/incidence/common-cancers-compared. Accessed 2 August 2016).

These options, which are only available from STATA 13.0 onwards, are very demanding of computing power: in spite of using a PC with 32 GB RAM, it took several hours for the calculations to be completed.

The fact that Muslims, too, have their “backward” classes and “forward” classes, with a conspicuous lack of intermarriage between the two groups, meant that it was sensible to separate Muslims into two groups: Muslims from the OBC (MOBC) and Muslims from the “upper classes” (MUC).

Figures relate to the 71st NSS. This category also included a few Muslim households. Since Muslims from the ST are entitled to reservation benefits, these households have been retained in the ST category.

This category also included some Muslim households. 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).

The current BJP government has emphasised the building of toilets under its Swach Bharat Abhiyan (Clean India Programme).

The “other” toilet type was usually a pit, and the “other” fuel type was mostly cow dung cakes.

See Chapter 2 for a discussion of open defecation.

Marital status is defined in this chapter as: married; or single, widowed, divorced.

North (Jammu and Kashmir; Delhi; Haryana; Himachal Pradesh; Punjab; Chandigarh; and Uttaranchal); central (Bihar, Chhattisgarh; Madhya Pradesh; Jharkhand; Rajasthan; and Uttar Pradesh); east (Assam; Manipur; Meghalaya; Manipur, Mizoram; Nagaland; Sikkim; Tripura; Orissa; and West Bengal); west (Daman and Diu; Dadra and Nagar Haveli; Maharashtra; Gujarat; and Goa); south (Andhra Pradesh; Karnataka; Kerala; Puducherry; and Tamil Nadu). The two islands, Lakshadweep and Andaman and Nicobar, were omitted.

The fact that Muslims are more likely to report poor self-reported health has been discussed by Singh et al. (2013) and is ascribed to the social isolation of the Muslims in India and their low educational and economic achievements. The Sachar Committee (2006), in its report to the Government of India, quantified and highlighted the backwardness of Indian Muslims. This report drew attention to a number of areas of disadvantage: inter alia the existence of Muslim ghettos stemming from their concern with physical security; low levels of education engendered by the poor quality of education provided by schools in Muslim areas; pessimism that education would lead to employment; difficulty in getting credit from banks; the poor quality of public services in Muslim areas. In consequence, as the committee reported: one in four Muslim 6–14-year olds had never attended school; less than 4% of India’s graduates were Muslim; only 13% of Muslims were engaged in regular jobs, with Muslims holding less than 3% of jobs in India’s bureaucracy.

It should be emphasised that in computing the predicted PPH all the relevant interaction effects were taken into account.

The fact that Muslim women are more likely to report poor SRH is consistent with the findings of Alam (2006). The fact that non-Muslim OBC women are more likely to report poor SRH relative to their male counterparts is possibly due to patriarchy among the OBC (Menon 2009).

Forward States were Himachal; Punjab; Chandigarh; Haryana; Delhi; Sikkim; West Bengal; Gujarat; Daman and Diu; Dadra and Nagar Haveli; Maharashtra; AP; Karnataka; Goa; Kerala; TN; Pondicherry; Telangana. Backward States were: Uttaranchal; Rajasthan, UP, Bihar; Arunachal; Nagaland; Manipur; Mizoram; Tripura; Meghalaya; Assam; Jharkhand; Odisha; Chhattisgarh; Lakshadweep; Andaman and Nicobar Islands.

After controlling for income, education, age, and region.

In order to compute the standard errors associated with the difference between men and women, in their respective differences of being afflicted by a particular ailment (this calculation being necessary for judging whether the gender difference associated with a particular ailment was statistically significant), we estimated a multinomial logit in which the dependent variable took values 1–10, depending on the ailment (see Table 5.5 for a list of ailments) and the determining variable was gender. The predicted probabilities from this model were the sample proportions for each category but the estimated model had the advantage of providing the estimated standard errors associated with the difference in proportions since a property of the model is that the category predictions for men and women are the sample means of men and women for the categories.

Dividing the difference by the standard error yields the z-value.

There is an assumption that the ε_i are normally distributed results in an ordered probit model.

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Titel: The Health of Elderly Persons
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_5