current factors on health (Smith and Ben-Shlomo, 1997). The stress history - the accumulation
of psychosocial experiences beginning in infancy and continued throughout the life course -
seems to have biological effects that will influence the development of degenerative disease
(Brunner, 1997).
People’s health is influenced by income (both per capita income and national income),
occupation, diet, life courses stress, cultural norms, past socioeconomic factors and
neighbourhoods, levels and pattern of educational attainment (schooling); population growth,
density and age structure; natural resources abundance; personal and government saving
(investment rate); physical capital stock; economic policy, for example liberalization,
globalization and privatization; the quality of public institutions; the geography, for example the
location and climate of a country.
The above studies are based on the macro level secondary data. Little attention has been
given to the micro aspects of health research by the researchers, government, policy makers and
development planners. Further, in India, it is also found that a large proportion of health research
has concentrated on a few key states - Keral, Madhya Pradesh, West Bengal and Uttar Pradesh -
while paying less attention to others (Saigal, 2002). In this connection, the present paper is a
micro level study based on primary data to find out the impact of income and education on
household health expenditure in urban Orissa. The main goal of the paper is to increase
awareness - not only among health researchers but also among policy makers and practitioners
who use health research findings - about the influence of socioeconomic characteristics in terms
of income and education on household health expenditures, as well as to encourage improved
approaches.
II. METHODOLOGY AND DATABASE
The study is based on primary data collected from Bhubaneswar and Cuttack, which are
chosen on the basis of judgment sampling method as both the cities appropriately represent urban
Orissa. Multi-stage random sampling method is adopted to select households (HHs), i.e., the
sampling unit, from each city. The first stage units are the wards and second stage units are the
HHs. Total 125 HHs are surveyed. Data of four HHs are deleted because after cross-checking
they are found fake and irrelevant. Hence, the sample size is one hundred twenty one.