-
This article was downloaded by: [swasti mishra]On: 02 April
2015, At: 22:59Publisher: RoutledgeInforma Ltd Registered in
England and Wales Registered Number: 1072954 Registeredoffice:
Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
Click for updates
Asian GeographerPublication details, including instructions for
authors andsubscription
information:http://www.tandfonline.com/loi/rage20
Understanding needs and AscribedQuality of life through
maternalfactors infant mortality dialecticSwasti Vardhan Mishraaa
Department of Geography, Visva-Bharati, Santiniketan, WestBengal,
IndiaPublished online: 24 Sep 2014.
To cite this article: Swasti Vardhan Mishra (2015) Understanding
needs and Ascribed Quality oflife through maternal factors infant
mortality dialectic, Asian Geographer, 32:1, 19-36,
DOI:10.1080/10225706.2014.962551
To link to this article:
http://dx.doi.org/10.1080/10225706.2014.962551
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy
of all the information (theContent) contained in the publications
on our platform. However, Taylor & Francis,our agents, and our
licensors make no representations or warranties whatsoever as tothe
accuracy, completeness, or suitability for any purpose of the
Content. Any opinionsand views expressed in this publication are
the opinions and views of the authors,and are not the views of or
endorsed by Taylor & Francis. The accuracy of the Contentshould
not be relied upon and should be independently verified with
primary sourcesof information. Taylor and Francis shall not be
liable for any losses, actions, claims,proceedings, demands, costs,
expenses, damages, and other liabilities whatsoever orhowsoever
caused arising directly or indirectly in connection with, in
relation to or arisingout of the use of the Content.
This article may be used for research, teaching, and private
study purposes. Anysubstantial or systematic reproduction,
redistribution, reselling, loan, sub-licensing,systematic supply,
or distribution in any form to anyone is expressly forbidden. Terms
&
-
Conditions of access and use can be found at
http://www.tandfonline.com/page/terms-and-conditions
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
Understanding needs and Ascribed Quality of life through
maternalfactors infant mortality dialectic
Swasti Vardhan Mishra*
Department of Geography, Visva-Bharati, Santiniketan, West
Bengal, India
(Received 7 June 2013; accepted 2 September 2014)
In this paper Needs theory is being redefined as the foundation
block of the Quality of life (Qol)structure and as a starting point
in the lexicon of Qol philosophies. It is argued that theelementary
and the most important characteristic to define Qol is always the
needs-basedapproach through its merging with the means-end
dialectic. Keeping this epistemologyintact, Ascribed Qol (aQol) is
defined as that Qol which transfuses from mother to her childby
meeting the needs of a mother and through that meeting the needs of
her child. Also, thedisjuncture between global and local
estimations is highlighted, reflecting on its implicationsfor
policy prescriptions. Referring to MosleyChens framework for child
survival,empirical study has been made for eight socially and
demographically backward states(EAG (Empowered Action Group)
states) of India to justify the idea of aQol. The OLStechnique and
geographically weighted regression, using the data from the Annual
HealthSurvey, 20102011, were used for conforming to the tenets of
the framework. It isempirically argued that within the aQol frame
mothers education has the most influencingrole in securing survival
of her infant vis-a-vis institutional delivery and full antenatal
checkup.
Keywords: quality of life; need; EAG states; geographically
weighted regression; infantsurvival
1. Introduction
The idea of and concern for human well-being is riveting echoing
since the times of Aristotle(Diener and Suh 1997; Forward 2003) or
perhaps much before than the known history. The ideaof Aristotelian
good life and living well (Forward 2003; Hagerty et al. 2001;
Phillips 2006)percolated into the political arena of the 1930s and
mirrored the material part of the Quality of life(Qol). However, it
was during the second half of the twentieth century that the
realization dawnedon the intellectuals and policy framers that
apart from wealth, non-pecuniary dimensions of lifeform an
intrinsic part of lifes quality or state of human well-being. This
state is materialized withthe meeting of needs and wants (Smith
1977). However, to need and to want is different thedifference is
that of urgency and intensity. A particular material possession (or
in another instancea definite cognitive experience) can be
testified both as a need and as a want by different crosssections
of a society in different times. A need for one can be a want for
the other. Needs areminimalist in nature; they exemplify a level
beyond which an individual can compete anddelve into wants and have
sophisticated Qol. Thus, meeting needs and achieving the resultant
sat-isfaction (term used in the crudest of form rather than in
utilitarian parlance) is the basic Qol.
2014 Hong Kong Geographical Association
*Email: [email protected]
Asian Geographer, 2015Vol. 32, No. 1, 1936,
http://dx.doi.org/10.1080/10225706.2014.962551
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
Lifes quality is ascertained, essentially at the basic level,
from the feasibility with which thebasic needs are met and the
amount of effort one has to put to procure those needs. In this
regard,the individual who wants to attain maximum Qol tries to
achieve the same with more feasibilityand less effort. For basic
Qol, the quality is equated with feasibility and effort, and for
sophisti-cated Qol (i.e. beyond the basic needs threshold) it is
equated with life satisfaction and quantity ofsatisfaction or
utility derived. Basic Qol is not empowered to differentiate
between individualsbased on the satisfaction achieved due to its
inescapable character. On the contrary, sophisticatedQol is
non-mandatory and optional and so facilitates easy
differentiation.
Taking the pre-eminence of needs theory in the Qol domain, the
paper queries about thelinkage that exists in the form of Ascribed
Qol (aQol) between a mother and her child. Thereexists a paramount
correlation between a mothers attributes and her childs health
(Caldwell1979; Mosley and Chen 1984), and this correlation is
explicit in the flow of lifes qualitythrough two proximate
determinants maternal factors and personal illness control
actedupon by a socioeconomic variable individual-level productivity
of the Mosley and Chens(1984) framework of child survival. aQol is,
at the most elementary level, the Qol meted to aninfant by her
mother through meeting the infants basic need of survival, as a
corollary tomeeting the mothers own basic need of health and
literacy.
The main objective of the study is to look for any relationship
between female literacy, fullantenatal checkup, institutional
delivery and infant survival in eight Empowered Action Group(EAG)
states of India, as an exercise to test any existence of aQol. The
objective of the studyis to test the intensity of relationship
between the explanatory variables and explained variablethrough
classical method of OLS at the state level and contemporary
technique of geographicallyweighted regression (GWR) at the
district level. Since, it is not possible for a global measure(OLS)
to account for the spatial non-stationarity and local variance, a
local technique (GWR)is deemed fit for the purpose. Also the
significance of the relationship is tested, for both themodels,
along with the significance of the model itself in case of the
global measure.
The motive behind the study is to show how the disjuncture
between a global and a localmeasure of correlation could induce
widely separated policy prescriptions. Holding a classicalmodel as
a background, it is argued that it holds true even if the
estimations are changed fromglobal to local, but the sub-form of
the model shifts accordingly. Quite tuning to the tenets of
Eco-logical Fallacy, the study adorns a descriptive form,
describing the interactions. And paves wayfor the policy framers to
think at a local scale and meet the local needs.
The following section paraphrases the idea of Needs as
documented by several ways ofknowing it, and its eminent role in
Qol studies. Besides, the idea of aQol is explained in avery subtle
yet simple way for easy understanding. The section that follows
focuses on thecase under study, the type and source of data and the
methodology used for understandingaQol. Research findings are
reflected in the next section, which make way for the adoption
ofaQol understanding, paving the way for the mothers education as
the paramount force tocurtail infant mortality. Also the
disjuncture between the global and local measures of
ascertainingthe relationship is highlighted effectively. The paper
concludes with the contribution this studymakes in understanding
the classical model yet with a contemporary technique, which
wasdeemed fit for the purpose. And, it is also reflected how using
a local measure keeps up thespirit of local governance, if such is
the endeavor of the state.
2. Needs, Qol and aQol: concepts and theoretical
considerations
Defining Qol, despite being pervasively done, is elusive. Even
though the number and scope ofQol studies has increased over time
(Wish 1986 in Trksever and Atalik 2001, 164), the defi-nitions
differ to such an extent that it is impossible to search for their
conformance. Qol concepts
20 S.V. Mishra
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
adorn such characteristics as a consequence of its eclectic
interpretation (Trksever and Atalik2001) and multidimensional
construct (Cummins 1999; Snoek 2000).
Based on the categories of satisfaction a person wants to attain
for enhancing his or her lifesquality Qol is divided into two broad
categories Objective Well-being (OWB) and SubjectiveWell-being
(SWB). OWB, also called material well-being (DAcci 2011), which
concerns itselfwith tangible and material fulfillment of life. OWB
is conspicuous and is equated with meetingneeds (Phillips 2006). On
the other hand, SWB is concerned with subjective interpretation
ofones life happiness and pleasure one gets. It depends upon the
cognitive and psychologicalelements of an individual. Therefore,
SWB besides being externally determined also gets influ-enced by
the dispositional characteristics of an individual (Diener and Suh
1997, 202). SWBmirrors the hedonism (DAcci 2011; Phillips 2006) and
gratification of an individual i.e. thesatisfaction of an
individual with his life, life domains and community conditions and
services(Sirgy 2011). Thus, it is quite explicit that without
reaching the threshold of OWB, enjoyingSWB is not possible. Meeting
needs is that threshold.
Needs approach is the most practical and argues for a minimum
standard for attaining lifesquality. This approach precisely
endeavors to secure three elementary needs literacy, healthand
nutrition. The most important theory to reflect on this approach is
Doyal and GoughsTheory of Human Need (Phillips 2006). Taking a cue
from the basic needs approach and enlar-ging its view, Doyal and
Gough posited that there are two types of needs basic or primary
needsand intermediate needs. In the basic needs category they
included: Avoiding serious harm andminimally disabled social
participation (Phillips 2006, 87). And to meet these two
primaryneeds, at the initial level, eleven intermediate needs have
to be secured, which include, interalia, appropriate health care,
secure childhood and appropriate education. They believe thatthese
two goals or two sets of needs are essentially to be achieved for
human emancipation(Phillips 2006, 86).
Acting both as a means and an end in itself, need-based Qol
thought is a much delved intoperspective of human well-being. In
this regard, Drewnowskis (Smith 1977) and Headeys(Sirgy 2011) ideas
and their analogy to stock and flow concept looms large.
Drewnowskisschema talks of two indices state of well-being index
and level of living index. State ofwell-being is a condition of an
individual at a certain point of time and depends upon the levelof
living he is practicing. And to reflect on the paramountcy of
needs, health and education areincluded in both of his indices.
That means to have a healthy state of existence an individualmust
be practicing life in a healthy manner. Again, following Headey
implicitly, Level ofliving of an individual equates as a stock
concept which determines the flow concept/state ofwell-being of the
individual. However, when Headey talks clearly of stocks and flows,
he doesnot reflect on the stock-flow dialectic as underlined above.
Instead what seems explicit is the dis-crete categorization of Qol
into two categories. However, the satisfaction or dissatisfaction
fromeveryday life (a flow concept) tangentially depends upon the
characteristics of an individual(stocks health, education, social
networks, leisure skills, work skills, etc.).
Health and literacy, essentially, are the basic needs as
exemplified by the measures of humandevelopment index, physical
quality of life index (Roy 1985) and several others (for some
inter-esting projects see Hagerty et al. 2001). For considering
health in the study I have taken the dataon full antenatal checkup,
institutional delivery and infant mortality rate (IMR). Here IMR
servestwo purposes: first, it is a single largest category of
mortality (Singh 2007), and, second, it servesthe idea of aQol. To
know how all these indicators interact, it is essential to revert
back to one ofthe oft-cited theories on child survival Mosley and
Chens (1984) framework. The frameworkstates that child survival
depends upon five proximate determinants maternal factors,
environ-mental contamination, nutrient deficiency, injury and
personal illness control. But these determi-nants do not operate
independently; rather they depend on the independent
socioeconomic
Asian Geographer 21
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
variables. These variables act through the proximate
determinants to influence child survival.Independent variables are
three in number individual-level productivity, household-level
pro-ductivity and community-level productivity. Out of these three,
individual-level productivity(IP) entails maximum command over the
proximate determinants and eventually over theIMR. As it
constitutes different facets of parents including the education, IP
is considered thestrongest of the independent variables to reflect
on the health status of a child. Out of IP,mothers education solely
exerts such an overwhelming influence that Mosley (1983) has
ident-ified the process as Social Synergy (in Mosley and Chen 1984,
35).
The present study focuses on how a socioeconomic determinant of
Mosley and Chens (1984)framework individual-level variable (that of
a mother) works through the proximate determi-nants of maternal
factors and personal illness control to secure the life of an
infant. Personalillness control is an instrument of resilience,
which ascertains that the mother is kept healthythrough preventive
measures during gestation and during parturition, or otherwise
cured tohealthy being through curative means. And as mentioned
earlier maternal factors are the para-mount force to secure infant
survival through multiple means education, health and age at
mar-riage of the mother among others. Full antenatal care (FANC)
and institutional delivery (IN.DEL)fits under personal illness
control determinant, whereas female literacy (working as a proxy
forfemale education) is confined as a maternal factor (LIT), and in
fact the most important.However, all the three explanatory
variables are solely mother centric and limit or enhance
thepossibility of infant survival in what can be termed as
one-to-one strategy of survival.
Female literacy (education) is the most important variable to
influence infant survival (Cald-well 1979) having number of ways of
influencing it. Female literacy affects the other two vari-ables in
question institutional delivery and full antenatal care as
education endows amother with discretionary power to choose the
best among the alternatives, be it modern medi-cine, right dosages
of iron and folic acid, going for institutional delivery or
postpartum care(Gunasekaran 2008; Mosley and Chen 1984). Also,
quite often the mothers education bringsadditional resources to the
family through her engagement in economic opportunities
(Gunase-karan 2008).
Education also provides the power of rationale and economic
thinking and helps in settingpreferences for a child, gauging the
associated cost and contemplating possible trade-offs.Besides, as
Caldwell (1979) puts it female education helps in favorable shift
of intra-householdpower relations, enabling her to take conducive
decisions for her childs survival against the per-vasive
stereotypical norms and traditions. Jejeebhoy has called it womens
decision makingautonomy (Kravdal 2004).
A plethora of research has been conceived, drawing on the
literacyIMR linkage; thoughregional in nature they tend to conform
to the hypothesis of strong negative correlationbetween mothers
literacy and childs survival in the first year of birth (Anand et
al. 2000;Franz and FitzRoy 2006; Kateja 2007). However, there are
few other studies which have not con-sidered the explanatory role
of literacy in determining the level of IMR (Nubler 1995 in
Hagertyet al. 2001; Shimouchi, Ozasa, and Hayashi 1994). While
considering education as the paramountSocioeconomic status (SES) of
mothers that influences child survival, Fuentes-Afflick and
Hessol(1997) posited that low SES of mothers increases the IMR (in
Frisbie 2005). On the contrary, afew authors (Hummer, Eberstein,
and Nam 1992 in Frisbie 2005) think that the absence of
familyincome data in the vital statistic records induces
substituting the absence with data on motherseducation.
To contradict the belief that family income is relatively more
influencing on IMR than themothers education, Tresserras et al.
(1992) concluded that income cannot be accepted as theexplanatory
variable of child survival, as the unequal distribution of income
produces a falseimpression (cited in Watters 2003). Thence,
Tresserras et al. (1992) and Bolam et al. (1998)
22 S.V. Mishra
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
proposed to study of IMR through the status of female education
as the most reliable (as cited inWatters 2003).
Institutional delivery (IN.DEL) is another considerable factor
to determine infant survival. Itbrings into question the hygienic
and appropriate setting of parturition, and tries to control
theexogenous factors negatively affecting the infants life.
Exogenous factors are the environmentalsettings and processes which
affect infant mortality, as against the endogenous factors which
actwithin the body of a mother. Antenatal care influences
endogenous factors. Antenatal care pro-tects a mother from injury,
infection and infirmities and at the same time supplements her
withrequired nutrients, so as to keep both the persons healthy
during gestation and at the time of par-turition. Postpartum care
is as crucial as antenatal care but since the data on institutional
deliveryincludes the postnatal care information (Annual Health
Survey 2012), it is excluded for avoidingredundancy.
There exists a biological link between a mother and her child
(Mosley and Chen 1984). Thusthe characteristics of a child are
dependent upon that of the mother. Taking a cue from the afore-said
paragraphs it is explicit that mothers Qol (literacy and health)
dictates the Qol of her child(health and survival). And, in none of
the other human relations is such a direct influence of apersons
Qol on another beings Qol evident which is biologically, socially,
economicallyand literally administered. This Qol of a child being
dictated by the mothers Qol is what Ipropose to call as aQol. Since
none of the Qol in any of the senses can be so explicit and
axiomaticlike that of a motherchild transfusion, aQol is only
endemic to such a relationship. aQol is thequality of life meted to
an infant by her mother through biological, economical, social and
literalmeans by meeting the infants basic need of survival, as a
corollary to meeting her own basic needof health and literacy
(Figure 1).
Figure 1. The aQol idea.Source: Author.
Asian Geographer 23
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
Biological mechanism of aQol forms the all-inclusive mechanism.
It axiomatically includesthe social, economical and literal
mechanisms of Qol transfusion. A fetus is attached to themother
through the placenta a tube made up of cells. This conduit feeds
and sustains thefetus by getting the required nutrients from the
mother. Though it is also established thatthe exchange is
bi-directional and sustainability is mutual, the transfusion from a
fetus to themother is supplementary while that from mother to fetus
is exclusive and hence more crucialfor life. Therefore, this
channel is the only source of securing a healthy infant during
birth.Furthermore, a favorable power relation in a society and
economic liberty reinforces the biologi-cal mechanism of infant
birth and growth. How such conflation works are elementary and
para-phrased in the next paragraphs.
Economical mechanism is about taking independent economic
decisions by mothers for thesurvival of the infant. An educated
female can only help in securing her infants survival if shehas
access to sufficient resources and have the liberty to utilize them
in the best possible alterna-tive. Having quality food, sufficient
health supplements, opting for the best healthcare facility
andpostpartum care including infant and child immunization are the
best available alternatives havingintense economic
connotations.
Societies, especially in the South Asian realm, have
unscientific traditions and ways of lifewhich turn out to be fatal
for both the infant and the mother. In this context the role and
practicesassigned to females (especially those who are lower in the
family hierarchy, for example, daugh-ter-in-law) are at times
abusive for the survival of the fetus. As mentioned earlier only
educationcan shift the intra-household power relations in favor of
a mother and in that process in favorof the infant. Whether it is
to feed an infant with the colostrums in the first hour of birth or
tonegate the custom of being secluded after birth, an educated
mother is expected to voice allthese, against the social
oddities.
While the former mechanisms implicitly enhance the probability
of infant survival, literalmechanism is more ocular. When a mothers
action, which is to a large extent a cumulative ofthe last three
mechanisms, is visible through implementation it can be called as
the literal mech-anism. For instance, a mother watching her steps
so as not to hurt the fetus, keeping tabs on hermedicinal
schedules, sleeping and relaxing in a correct posture and
maintaining hygienic sur-roundings can be called the literal
mechanism of Qol transfusion.
3. Case, data and methodology
EAG states are the eight states of India showing heightened
socio-demographic backwardness.Constituted in 2001, the states of
Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Rajasthan,Odisha,
Uttar Pradesh and Uttarakhand (Figure 2) have formed EAG in the
Ministry of Healthand Family Welfare, Government of India.
The concern behind is to facilitate area-specific programs, and
alter the effects of ill-govern-ance and bad monitoring system
through effective community involvement.
EAG states have high records in some crucial variables of
Biodemography, for instance,Infant Mortality Rate, Maternal
Mortality Rate, Population growth, Total Fertility Rate and
Ante-natal care. However, the negativities do not only mirror
nonexistence of prompt health care facili-ties or fund
unavailability; but are also fallout of ill-governance and
non-conducible monitoring ofthe implemented programs. To be
precise, the lowest marks are dependent upon both the demandside
and the supply side of the services, which had been mutually
sustaining each other at thelowest levels. Pluralistically burdened
from many facets of society, environment and traditionthe general
conception of the target group in these states has always had a
cynical angle tomodern medication and health services. To
compliment, the lethargy and unaccountability ofthe service
providers have also fueled the situation to a certain extent.
24 S.V. Mishra
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
The core tenet of the EAG states policy is to stabilise
population, where provision of qualityhealth infrastructure forms
the means to attain the said end. As a result, of late, the states
seem tobe moving in the same direction as evident from latest
census data (Census 2011) populationgrowth rate in the EAG states
has decreased by 4% (average) points for the very first time,
theexception being Chhattisgarh where the population growth rate
has rather increased from thelast census.
The EAG states contribute to around 46% of Indias total
population, and the rest by 20 statesand 7 union territories
accommodate the remaining (Table 1).
Infant mortality rate (IMR) of the EAG states fluctuates between
36 and 59 where all the statesexcept two have rates at par and
above the national level by a good margin. The same
situationsurfaces with regard to total fertility rate (TFR) where
only Odisha rate is below the nationalaverage. In fact Odisha has
reached replacement-level fertility. Regarding the percentage
of
Figure 2. The EAG states, India.Source: Author.
Asian Geographer 25
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
effectively protected couple (Effective couple protection rate
(CPR)), the situation in Bihar is theworst 16.5% juxtaposed to
40.4% of the national average. Only two states Rajasthan andMadhya
Pradesh are above the national mean. In the case of maternal
mortality ratio (MMR)all the states are above the national average
(212). Nevertheless, the decline in MMR is remark-able in these
states; dropping from 375 in 20042006 to 308 in 20072009. The
decline in thenational average during the same time span is from
254 to 212.
For the present study data were procured from the first round of
the Annual Health Survey(AHS) (20102011), conducted in eight EAG
states (Bihar, Chattisgarh, Jharkhand, MadhyaPradesh, Odisha,
Rajasthan, Uttar Pradesh and Uttarakhand) and Assam. AHS is the
first of itskind in India which reflects on the district-wise core
indicators of fertility and mortality. At theinitial stage it was
planned for the aforementioned nine high-focus states, which
account for48% of the countrys population (Census 2011). AHS being
a panel survey facilitates easy tem-poral comparison of the
inter-district health scenario. However, in this study only 8 EAG
stateswere selected, which comprises 261 districts. Exclusion of
Assam is justified on account of itsnon-proximity to other states
and therefore its inability to participate and go through spatial
stat-istics treatment.
Approximately 3.5 million ever married women (1549 years) were
surveyed in these eightstates and the criteria for sample size at
the district were ascertained by looking at the IMR valuesand
considering other practical issues related to the execution of the
survey. AHS classifies thedata based on residence (rural or urban)
but the data used for the study are non-categorized (total).
Female literacy rate data are taken from Census 2001, which is
the percentage of females whocan read and write with understanding
in any language. Infant mortality rate is the number ofdeaths of
infants under one-year-old in a given year per 1000 live births in
the same year. Inall the institutional delivery data, postnatal
care is not registered; in the cases where thewomen stayed for 48
hours or more it is presumed that postnatal care was given. Full
antenatalcheckup consists of three visits of antenatal checkup, at
least one tetanus toxoid injection, andIron and Folic Acid tablet
consumption for 100 days or more.
The classical method of OLS is run for getting the correlation
coefficient value. And t-testvalue is estimated to obtain the
significance of the relationships. Besides, f-test is run
forjudging the significance of the model. Confidence level for both
the tests is kept at 95% or more.
The value of r as generated using OLS identifies a single value
to represent a relationship uni-formly all over the space
(including the subunits). However, social processes are
non-stationary(Fotheringham, Charlton, and Brunsdon 1998), i.e.
they are not constant over space like physical
Table 1. Selected estimates of EAG states compared to the
national average.
States Population % of total IMR MMR TFR CPR
Bihar 104,099,452 8.60% 44 261 3.5 16.5Uttar Pradesh 199,812,341
16.51% 57 359 3.3 27.7Rajasthan 68,548,437 5.66% 52 318 2.9
45.7Madhya Pradesh 72,626,809 6.00% 59 269 2.9 46.4Odisha
41,974,218 3.47% 57 258 2.1 25.9Chhattisgarh 25,545,198 2.11% 48
2.7 Jharkhand 32,988,134 2.73% 39 2.8 Uttarakhand 10,086,292 0.83%
36 India 1,210,569,573 44 178 2.4 40.4
Sources: Population figures Census of India, 2011; MMR Special
Bulletin on Maternal Mortality in India 20072009Sample Registration
System, June 2011; CPR Family Welfare Statistics in India 2011; IMR
Sample RegistrationSystem Bulletin, October 2012; TFR Sample
Registration System Statistical Report 2012.
26 S.V. Mishra
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
processes. Hence, it is a fallacy to represent them through a
generalized single value of the stat-istic. Second, different
social processes play differently in spatial subunits; thus the
relationshipsare intrinsically different across space
(Fotheringham, Brunsdon, and Charlton 2002, 9). Third,the
generalized model, which dictates a relationship, may omit the
crucial variable (s) or representthe relationship in an incorrect
functional form (Fotheringham, Brunsdon, and Charlton 2002,10).
Keeping the above contentions in sight, it seems that the single
value of the coefficientsmoves toward an ecological fallacy. To
curtail this fallacy, Fotheringham, Brunsdon, and Charlton(2002)
have introduced a new local measure of Regression GWR. The
difference between thelocal and the global is simple a global
measure tends to generalize, in this case the relationshipbetween
the variables, but a local measure disaggregates this relationship
in accordance with thespatial subunits under study. A local measure
also highlights the anomaly of a single units valuewith respect to
that of the global measure. Clearly, a local measure, taking into
consideration theidea of spatial non-stationarity of a process,
generates local values of a parameter. For instance,where OLS
generates a single value of r, GWR generates the same for every
spatial unit underconsideration. In this regard, GWR conducts
Regression equation on every single spatial unitand generates
estimates for each of them.
The GWR model is written as (Fotheringham, Brunsdon, and
Charlton 2002)
yi = b0(ui, vi) + Skbk(ui, vi)xik + 1i,
where (ui,vi) denotes the coordinates of the ith point in space
and k (ui,vi) is a realization of thecontinuous function k (u,v) at
point i. Keeping in view the unequal size of the districts the
kernelused is adaptive in nature.
Since GWR does not provide for the f-test values for single
subunits the significance of themodel is assumed to exist for the
study.
4. Research findings
4.1. Ordinary least square
Ordinary least square (OLS) regression for all the EAG states
combined (Table 2) shows full ante-natal checkup (r =0.426) as more
important an explanatory factor for lowering infant mortalityrate
than female literacy (r =0.349).
However, institutional delivery turns out to be insignificant
for the relationship (p = .458).Also, both the explanatory terms
account for more than 22% variance in IMR. Overall, themodel aQol
fits well in case of EAG states combined together. Fragmenting the
states for individ-ual state-wise calculation of the statistic
brings into light the prominence and intensity of themodel under
consideration. What we have come across are the problems of
Modifiable ArealUnit Problem (MAUP) (Openshaw 1983) and ecological
fallacy surfacing explicitly. Since wehave changed our unit of
estimation on the same sets of data from a cluster of states to
individualstates our estimates have changed a lot. Besides, the
statistic which was dictating the nature of themodel for the
cluster does not fit well for the individual states.
The model is not significant for the two states of Chhattisgarh
and Odisha. The significancelevel of both the intensity of
relationships (r) and the model is clearly absent in the two
states.Odishas demographic paradox (Pradhan and Arokiasamy 2006) is
mystifying. It has got thesecond-best records among the EAG states
in the dimensions of full antenatal checkup(18.5%), institutional
delivery (71.3%) and female literacy (68%), yet is tabled at the
thirdhighest position in IMR estimates (62). The paradox is
tangentially related to the motherchildinteraction, for Odisha has
got very high rates of underweight married women (39.5%, where
Asian Geographer 27
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
all India average is 32.2%) in the age bracket of 1549 years
(Sengupta and Syamala 2012).Though malnourishment is attested as
one of the prominent reasons of infant mortality, it isstill less
influential than female literacy and antenatal checkup. Pradhan and
Arokiasamy(2006) subscribe to the fact that such a paradox is
fallout of lowered investment in health-careinfrastructure and low
social sector development, like poverty, nutrition and rural
development.
As for Chhattisgarh, a factor other than those included in the
model, malnutrition, seeminglyplays a role in influencing IMR
(39.7% of married women in the age bracket 1549) (Senguptaand
Syamala 2012). Apart from that health infrastructural gap (Palmer
and Kollannur 2010), largetribal population, insufficient public
transport cumulatively influences IMR more than a mothersown Qol in
Chhattisgarh. Nevertheless, Chhattisgarh has the third lowest IMR
value (53) in theEAG cluster and has shown immense improvement from
76 in 2001 (Registrar General 2002) to48 in 2011 (Registrar General
2012). Credit for such a remarkable feat is the state
governmentsown intervention Nava JatanYojana and Mitanin
program.
Regarding other states, IMR in Jharkhand is most influenced by
literacy (r =0.812) fol-lowed by Rajasthan (0.685), Uttarakhand
(0.672) and Uttar Pradesh (0.636). The least influ-enced states are
Bihar (0.540) and Madhya Pradesh (0.427). And when related to the
other two
Table 2. Selected outcomes of the OLS model.
States VariablesRelationship strength with
IMR (R)Relationshipsignificance R2
Modelsignificance
EAG states IN.DEL 0.006 Insignificant 0.227 SignificantLIT 0.349
SignificantFANC 0.426 Significant
Bihar IN.DEL 0.479 Significant 0.282 SignificantLIT 0.540
SignificantFANC 0.384 Significant
Chhattisgarh IN.DEL 0.217 Insignificant InsignificantLIT 0.280
InsignificantFANC 0.288 Insignificant
Jharkhand IN.DEL 0.773 Significant 0.621 SignificantLIT 0.812
SignificantFANC 0.614 Significant
MadhyaPradesh
IN.DEL 0.478 Significant 0.268 SignificantLIT 0.427
SignificantFANC 0.285 Significant
Odisha IN.DEL 0.180 Insignificant InsignificantLIT 0.053
InsignificantFANC 0.055 Insignificant
Rajasthan IN.DEL 0.243 Insignificant 0.435 SignificantLIT 0.685
SignificantFANC 0.393 Significant
UttarPradesh
IN.DEL 0.532 Significant 0.425 SignificantLIT 0.636
SignificantFANC 0.443 Significant
Uttarakhand IN.DEL 0.163 Insignificant 0.651 SignificantLIT
0.672 SignificantFANC 0.040 Insignificant
Notes: Relationship significance is ascertained where p .05.
Model significance is ascertained where p .05 for the
f-testconducted. The value of coefficient of determination (R2) is
adjusted after taking into consideration the number ofexplanatory
terms, and in most of the cases it is smaller than the R2.IN.DEL,
institutional delivery; LIT, female literacy rate; FANC, full
antenatal care.Source: Author.
28 S.V. Mishra
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
variables, literacy is the most influencing in all the states
except in Madhya Pradesh. A consider-able performance in this
regard is shown by Uttarakhand where two explanatory variables
insti-tutional delivery and full antenatal checkup have
insignificant influence on the IMR scenario.Literacy exclusively
dictates around 65% of the variance in IMR in this state.
Barring two indifferent states, Odisha and Chhattisgarh, in none
of the states is literacy insig-nificant for the relationship.
Institutional delivery shows good influence over IMR in the states
ofJharkhand (r =0.773) and Uttar Pradesh (0.532), while not
performing well in Rajasthan(0.243) and Chhattisgarh (0.217).
Inconsistent with the EAG cluster statistic, full antenatalcare
shows least influence on IMR in all the states but Rajasthan.
The coefficient of determination (R2) value ranges between 0.282
in Bihar and 0.651 in Uttar-akhand. In all the states except two
(Bihar and Madhya Pradesh), the explanatory variablesaccount for
more than 40% of the variance in IMR. Thus, employing a classical
method of esti-mating a relationship it is fruitfully argued that
maternal factors have substantial influence oninfant survival,
which helps in explaining the transfusion of Qol from mother to her
child.
4.2. Geographically weighted regression
As a continuation of MAUP and ecological fallacy, a local
regression model (GWR) is employedto understand the statistic
nuances in subunits (districts), and how the relationship fits or
unfits inthe local units of study. Model significance in the local
measure is not possible, so it is assumedthat the model fits well
as it fitted in case of OLS estimates for the EAG cluster. Also, R2
is notestimated for the districts separately, as correlation
coefficient mirrors the same.
The intensity of the relationship between IMR and FANC is
insignificant in 151 of 261 dis-tricts (Figure 3). And out of the
significant districts, four districts three in Chhattisgarh and
onein Madhya Pradesh have shown a positive relationship. In these
four districts maternal factorsplay a less significant role, whose
effect is masked by other variables infrastructural gaps,
tra-ditional prejudices detrimental to safe practices and early
marriage. In all the three districts ofChhattisgarh the percentage
of early marriage (below the legal age of 18 years) among
thefemales is above the state average of 6%. However, in the
district of Madhya Pradesh early mar-riage among females is more
than double (28.6%) the state average of 12.5%. The most
intenseIMRFANC relationship is estimated for Pilibhit district in
Uttar Pradesh (0.929), while theleast performing district is
Madhepura in Bihar (0.426). To argue for female education as
themost important way of securing infant survival, 79 districts out
of 151 insignificant ones (inthe IMRFANC interaction) reflect a
strong relationship between IMR and female literacy.
The linkage shows strong clustering, with most of the values
above 0.7, in the states of UttarPradesh, Uttarakhand, part of
Bihar and Jharkhand and western Madhya Pradesh. Differing fromthe
OLS estimates the linkage is insignificant in Rajasthan; only four
districts have a significantrelationship.
IMR-IN.DEL linkage estimates showmore dismal figures only 90 out
of 261 districts have asignificant relationship (Figure 4). Out of
which 15 have a positive relationship most of them(10 districts)
are located in Odisha and Chhattisgarh and the remaining scattered
in the three statesof Jharkhand, Madhya Pradesh and Rajasthan. The
relationship is mostly clustered in westernUttar Pradesh and
central and south-western Madhya Pradesh. The most intense
relationship isestimated for Bareilly in Uttar Pradesh (0.882) and
the least intense estimate is for Bhagalpurin Bihar (0.428). In 171
insignificant districts (in the IMRINT interaction), 92
districtsshow an intense relationship between IMR and female
literacy.
IMRLIT estimates are the strongest to reflect on the aQol idea
(Figure 5). 161 districts out of261 have a negative relationship
between both the variables. And none of the significant
districtshave any positive value. Thus, female literacy has a
universal influence in enhancing the chances
Asian Geographer 29
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
of infant survival. Odisha and Chhattisgarh have only a few
districts to reflect on the relationship 7 out of 46 districts. The
clustering is observed in western Uttar Pradesh, Uttarakhand,
MadhyaPradesh, eastern Jharkhand and Bihar and Rajasthan. In some
districts of western Uttar Pradeshand nearly the whole state of
Uttarakhand the value is above 0.800. In 25 districts out of
100insignificant ones full antenatal checkup helps in explaining
the aQol, and in only 2 districtsdoes institutional delivery do the
job.
Individual states have a lot to mirror about their interaction
scenario per se (Table 3). Forinstance in Bihar the highest number
of negative relationship is in the IMRFANC interaction 19 districts
out of total 37! Also negative relationship is observed for 18
districts in case ofthe IMRLIT interaction and for the IMRIN.DEL
interaction it is only 7 districts. When
Figure 3. Infant mortality rate and full antenatal checkup
interaction.Source: Author.
30 S.V. Mishra
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
juxtaposed to the OLS values the picture is opposite; there
INT-FANC has the least influence.Only five districts Bhojpur,
Buxar, Patna, Saran and Vaishali have shown a
significantrelationship in all the three interactions, and all the
relationships are negative.
In Chattisgarh only three districts show significant status in
the IMRFANC interaction butwith a positive relationship. Five
districts that are significant in the IMRIN.DEL interactionare all
positive, as well. But in the IMRLIT interaction all the three
significant relationshipsare negative. Only the district of Korba
shows a significant relationship in all the three inter-actions,
but only negative in the IMRLIT interaction, while the other two
are positive. In Jhark-hand 11 significant negative relationships
are observed in the IMRFANC relationship, while the
Figure 4. Infant mortality rate and institutional delivery
interaction.Source: Author.
Asian Geographer 31
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
number is 13 in case of the IMRLIT interaction. Out of three
significant IMRIN.DEL relation-ships, two are negative. Only 2
districts (Kodarma and Ranchi) out of 18 show significance in
allthe three interactions. However, Kodarmas significance in
IMRIN.DEL is positive.
Out of 45 districts only 13 in Madhya Pradesh show a significant
relationship in all the threeinteractions, and these are negative.
The districts are Barwani, Bhopal, Dewas, Dhar, East Nimar,Harda,
Hoshangabad, Indore, Jhabua, Narsimhapur, Raisen, Sehore and West
Nimar. The IMRLIT interaction is more intense in this state with 38
of the districts having a negative significantrelationship, while
it is 23 in case of the IMRFANC interaction. And only 15 have shown
this
Figure 5. Infant mortality rate and female literacy rate
interaction.Source: Author.
32 S.V. Mishra
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
Table 3. Selected outcomes of the GWR model.
StatesNo. ofdistricts
IMRFANC IMRIN.DEL IMRLIT No. ofdistrictshaving
significantvalue in allthe threevariables
No. ofdistrictshaving
significantrelationship
No. ofdistrictshavingnegative
relationship
No. ofdistrictshavingpositive
relationship
No. ofdistrictshaving
significantrelationship
No. ofdistrictshavingnegative
relationship
No. ofdistrictshavingpositive
relationship
No ofdistrictshaving
significantrelationship
No. ofdistrictshavingnegative
relationship
No. ofdistrictshavingpositive
relationship
Bihar 37 19 19 7 7 18 18 5Chattisgarh 16 3 3 5 5 3 3 1Jharkhand
18 11 11 3 2 1 13 13 2MadhyaPradesh
45 24 23 1 18 15 3 38 38 13
Odisha 30 1 1 4 4 4 4 Rajasthan 32 4 4 4 3 1 24 24
UttarPradesh
70 38 38 44 44 47 47 25
Uttarakhand 13 8 8 2 2 13 13 Total 261 108 104 4 87 73 14 160
147 46
Note: Relationship significance is ascertained where p
.05.Source: Author.
Asian
Geographer
33
D
o
w
n
l
o
a
d
e
d
b
y
[
s
w
a
s
t
i
m
i
s
h
r
a
]
a
t
2
2
:
5
9
0
2
A
p
r
i
l
2
0
1
5
-
status in case of the IMRIN.DEL interaction. Three districts in
the IMRIN.DEL interaction andone in the IMRFANC interaction have a
positive relationship.
None of the districts in Odisha and Rajasthan have significant
status in all the three inter-actions. However, in both the states
female literacy has got a significant influence over IMR.And, in
both the states the IMRIN.DEL interaction has one or more districts
showing positiverelationship. In Uttar Pradesh, the aQol seems to
follow a complete circle. With nearly thesame number of districts
in all the three interactions having a significant negative
relationship,it can be assumed that all the explanatory variables
seem to be working at definite spaces tobring down the IMR. Owing
to its largeness, different districts of Uttar Pradesh seem to be
inter-acting with different spatial forces influencing from
different directions (following Toblers(1970) logic), and thus no
predominant explanatory variable can be held accountable. In
Uttarak-hand all the districts (13) show a significant negative
relationship in the IMRLIT interaction, and8 districts and 2
districts in the IMRFANC and IMRIN.DEL interactions,
respectively.
OLS has reflected on the relationships but when GWR was run the
prior estimations wereproved wrong for some cases, and hold correct
for some others. But when GWR estimationswere segregated
state-wise, more interesting conclusions have surfaced vis-a vis
OLS estimations.The unit-level estimations and one variables
eminence over the other two point to differentialneeds of the
districts that could guide policy recommendations in some fruitful
direction. It isobserved that the significance in all the three
variables interactions is found in only few of thedistricts, while
majority of the districts have one or two significant causal
factors. And thesenuances at the local level are what policy
framers can capitalize on for framing parochial policiesor service
provision. Or in another case they can endeavor toward making the
insignificant vari-able significant through effective service
delivery mechanisms.
The mechanism of Qol transfusion is estimated to be working well
for nearly all the socio-demographic backward districts in the EAG
cluster in one way or the other. Only 73 districtshave not
reflected on the aQol idea most of which are in the states of
Chhattisgarh andOdisha (totalling 38 districts). None of the
districts in Uttarakhand have strayed from the ideaof aQol.
Besides, the relationships are spatially visible in clusters,
bringing afresh Geographysown first law that everything is related
to everything else, but near things are more relatedthan distant
things (Tobler 1970).To be precise, any practice (beneficiary
oriented) or any inter-vention (policy oriented) in any specific
district or group of districts has influenced the relatedscenario
of the proximate districts and, following the Gravity model,
decreases its influencewith distance.
5. Concluding remarks
Meeting need is essential it is essential for having a
flourishing life and for enjoying the heavy-weight Qol. The idea of
aQol is about meeting the needs of a mother and in the process
meetingthose of her child. Though it has now become a clich to
speak of motherchild interactions inpopulation sciences, it has not
yet been defined from the humanistic perspective of Qol. Apartfrom
that, any estimation that had been given has got a generalized
picture to present and thesubunit nuances of estimation have been
seldom tried. It has serious policy implications andworks as a road
map in ensuring development from below. Since its 73th and 74th
constitutionalamendments India is keeping herself tied to the
principle of local governance; and a generalizedpicture is sure to
bring failure to her attempts. It is in this regard that the study
is paving the wayfor addressing local hitches in achieving
development, including the most coveted millenniumdevelopment
goals.
In the study, drawing from MosleyChens framework, the survival
of infants is found to beinfluenced by maternal factors, among
which full antenatal checkup is the most important in the
34 S.V. Mishra
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
EAG cluster estimate. Moving along the MAUP, when the unit of
analysis is changed and esti-mates done on state-wise segregated
data, literacy turns out to be the strongest explanatory vari-able.
And the same estimates were obtained for the local regression, thus
conforming to the ideaof Social Synergy. States of Chhattisgarh and
Odisha are indifferent to aQol, showing insignif-icant relationship
with regard to all the three explanatory variables. Main
impediments in boththese states revolve around health
infrastructure, low social sector development and large ruraland
tribal population. These hurdles are too strong to be masked by the
aQol idea. In Rajasthanand Uttarakhand none of the variables except
female literacy is as strong as to determine infantsurvival.
Institutional delivery has the least influence in all the states.
Overall, only 73 districts(including districts showing positive
relation) out of 261 have not shown any syndrome of aQol.
The insignificant districts do have some other explanatory
variables to account for the changein IMR. However, their inclusion
into the model would have made it unmanageable and alsobecause
other left out maternal factors like age, parity and income have a
direct bearing oneither or all of the three variables under
consideration. And, inclusion of any other variable notconcerning a
mother into the model would have questioned the whole idea of
aQol.
Revisiting the framework (Mosley and Chen 1984) is fruitful in
the sense that it still holds itsground in ground realities and
helped to unfurl the whole idea of aQol. The future direction
insuch studies could be to include the left-out variables or try to
strengthen the aQol through rig-orous field-based studies,
including the cultural multiplicities into the model. And, also it
isquite imperative for the future researches to make estimates at
the local level, which will havemultiple implications for issues
ranging from conceptualizing problems, through policyframing, to
service delivery mechanisms.
ReferencesAnand, K., Shashi Kant, Guresh Kumar, and S. K.
Kapoor. 2000. Development Is Not Essential to Reduce
Infant Mortality Rate in India: Experience from the Ballabgarh
Project. Journal of Epidemiology andCommunity Health 54 (4):
247253.
Caldwell, J. C. 1979. Education as a Factor in Mortality Decline
an Examination of Nigerian Data.Population Studies 33 (3):
395413.
Cummins, Robert A. 1999. A Psychometric Evaluation of the
Comprehensive Quality of Life Scale FifthEdition. In Urban Quality
of Life: Critical Issues and Options, edited by Lan Yuan Lim,
BelindaK. P. Yuen, and Christine Lw, 3246. Singapore: School of
Building and Real Estate, NationalUniversity of Singapore.
DAcci, Luca. 2011. Measuring Well-Being and Progress. Social
Indicators Research 104 (1): 4765.Diener, Ed, and Eunkook Suh.
1997. Measuring Quality of Life: Economic, Social, and
Subjective
Indicators. Social Indicators Research 40 (12): 189216.Forward,
Sonja. 2003. State of the Art Report on Life Quality Assessment in
the Field of Transport and
Mobility. FACTUM: Traffic- and Social Analysis. Accessed March
15. http://www.factum.at/asi/download/ASI_D21_final.pdf
Fotheringham, A. Stewart, Chris Brunsdon, and Martin Charlton.
2002. Geographically WeightedRegression the Analysis of Spatially
Varying Relationships. Chicester: John Wiley.
Fotheringham, A. S., M. E. Charlton, and C. Brunsdon. 1998.
Geographically Weighted Regression: ANatural Evolution of the
Expansion Method for Spatial Data Analysis. Environment and
Planning A30: 19051927.
Franz, Jennifer S., and Felix FitzRoy. 2006. Child Mortality and
Environment in Developing Countries.Population and Environment 27
(3): 263284.
Frisbie, W. Parker. 2005. Infant Mortality. In Handbook of
Population, edited by Dudley L. Poston andMichael Micklin, 251282.
New York: Kluwer Academic/Plenum.
Gunasekaran, S. 2008. Determinants of Infant and Child Mortality
in Rural India. New Delhi: Kalpaz.Hagerty, Michael R., Robert A.
Cummins, Abbott L. Ferriss, Kenneth Land, Alex C. Michalos,
Mark
Peterson, Andrew Sharpe, Joseph Sirgy, and Joachim Vogel. 2001.
Quality of Life Indexes forNational Policy: Review and Agenda for
Research. Social Indicators Research 55 (1): 196.
Asian Geographer 35
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
-
Kateja, Alpana. 2007. Role of Female Literacy in Maternal and
Infant Mortality Decline. Social Change37 (2): 2939.
Kravdal, ystein. 2004. Child Mortality in India: The
Community-Level Effect of Education. PopulationStudies: A Journal
of Demography 58 (2): 177192.
Mosley, W. Henry, and Lincoln C. Chen. 1984. An Analytical
Framework for the Study of Child Survival inDeveloping Countries.
Population and Development Review 10: 2545.
Openshaw, S. 1983. The Modifiable Areal Unit Problem. Norwich,
UK: Geo Books.Palmer, Ashley, and Antony Kollannur. 2010.
Strengthening Institutional Capacities for Public Health: The
Case of Chhattisgarh, India. The Power of How. Accessed January
2.
http://www.thepowerofhow.org/uploads/wysiwyg/documents/other_resources/undp/Chhattisgarh%20Health%20Institution_final_6%20October.pdf
Phillips, David. 2006. Quality of Life: Concept, Policy and
Practice. New York: Routledge.Pradhan, Jalandhar, and P.
Arokiasamy. 2006. High Infant and Child Mortality Rates in Orissa:
An
Assessment of Major Reasons. Population, Space and Place 12:
187200.Registrar General, India. 2002. SRS Bulletin, October, 2002.
New Delhi: Vital Statistics Division, Registrar
General, India.Registrar General, India. 2012. SRS Bulletin,
October, 2012. New Delhi: Vital Statistics Division, Registrar
General, India.Roy, B. K. 1985. PQLI Measure of Development: A
Study of Literacy and Basic Resources in India.
GeoJournal 10 (1): 7581.Sengupta, Angan, and T. S. Syamala.
2012. The Changing Face of Malnutrition in India. Journal of
Health
Management 14 (4): 451465.Shimouchi, Akira, Kotaro Ozasa, and
Kyohei Hayashi. 1994. Immunization Coverage and Infant
Mortality
Rate in Developing Countries. Asia-Pacific Journal of Public
Health 7 (4): 228232.Singh, Bir. 2007. Infant Mortality Rate in
India: Still a Long Way to Go. Indian Journal of Pediatrics 74:
454.Sirgy, M. Joseph. 2011. Theoretical Perspectives Guiding QOL
Indicator Projects. Social Indicators
Research 103 (1): 122.Smith, David M. 1977. Human Geography: A
Welfare Approach. London: Arnold-Heinemann.Snoek, F. J. 2000.
Quality of Life: A Closer Look at Measuring Patients Well-Being.
Diabetes Spectrum
13 (1): 2428.Tobler, W. 1970. A Computer Movie Simulating Urban
Growth in the Detroit Region. Economic
Geography 46 (2): 234240.Trksever, A. Nilay Evcil, and Gndz
Atalik. 2001. Possibilities and Limitations for the Measurement
of
the Quality of Life in Urban Areas. Social Indicators Research
53 (2): 163187.Watters, Elisa K. 2003. Literacy for Health: An
Interdisciplinary Model. Journal of Transcultural Nursing
14 (1): 4854.
36 S.V. Mishra
Dow
nloa
ded
by [s
wasti
mish
ra] at
22:59
02 A
pril 2
015
Abstract1. Introduction2. Needs, Qol and aQol: concepts and
theoretical considerations3. Case, data and methodology4. Research
findings4.1. Ordinary least square4.2. Geographically weighted
regression
5. Concluding remarksReferences