TABLE 3-9Who Pays for Healthcare?

Respondent CharacteristicsRelies on Family to Pay
Aged 55–640.112
(1.05)
Aged 65–740.242*
(2.12)
Aged 75+0.463**
(2.85)
Female0.437***
(3.94)
Education (yrs)−0.033*
(−2.44)
Rajasthan−1.069***
(−4.10)
Kerala−0.261
(−1.52)
Karnataka−0.824***
(−5.28)
Rural−0.060
(−0.52)
Scheduled caste−0.299
(−1.83)
Scheduled tribe−0.211
(−0.70)
Other backward caste−0.252*
(−2.31)
HH Consumption (middle tertile)−0.225
(−1.74)
HH Consumption (highest tertile)−0.304*
(−2.08)
Episodic memory 1−0.662*
(−2.23)
Episodic memory 2−0.807*
(−2.59)
Episodic memory 3−0.451
(−1.73)
Any ADL disability−0.028
(−0.21)
Chronic condition−0.023
(−0.24)
Working−0.069
(−0.48)
Constant1.399***
(3.72)
N1,311
F-stat6.45***
Estimatorprobit

NOTES: In this model, we create a categorical scheme for our measure of cognitive health using episodic memory recall. We derive four dummies: episodic memory 1 includes respondents (18%) who were able to recall 0 to 5 words out of 20; episodic memory 2 includes respondents with 6 to 10 words (54%); episodic memory 3 includes respondents with 11 to 15 words, and the final category (omitted) was for the 3% of respondents who could recall 16 or more of the 20 possible words. The sample is restricted to respondents who self-reported an age of at least 45. Chronic condition is self-reported diabetes, heart disease, lung disease, stroke or hypertension. Working is defined as engaging in any labor market activity in the past 12 months; and any ADL is a binary indicator for having difficulty with at least one ADL. LASI used a stratified sampling design that sampled respondents independently by state, rural-urban area, and district. All multivariate models are unweighted, and the standard errors have been corrected for design effects of stratification. Table presents coefficients with t statistics in parentheses.

* denotes p < 0.05; ** p < 0.01; *** p < 0.001.

SOURCE: Longitudinal Aging Study in India (LASI) Pilot Wave.

* denotes p < 0.05; ** p < 0.01; *** p < 0.001.

From: 3, Longitudinal Aging Study in India: Vision, Design, Implementation, and Preliminary Findings

Cover of Aging in Asia
Aging in Asia: Findings From New and Emerging Data Initiatives.
National Research Council (US) Panel on Policy Research and Data Needs to Meet the Challenge of Aging in Asia; Smith JP, Majmundar M, editors.
Washington (DC): National Academies Press (US); 2012.
Copyright © 2012, National Academy of Sciences.

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