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RM1: Research Methodology (Quantitative)/Basic Statistics (September 2016)
Assignment # 1
Semester –5 th – B.A. (2014-17)
Course Professor: Dr. Sunayana Swain
Infant Mortality Rate, Maternal Mortality Rate, and Sex Ratio: A
systematic assessment of indicators of development in the state of
Odisha and Gujarat
IMR, MMR, and SR: A systematic assessment of indicators of development in the state of Odisha and Gujarat – Quantitative Assignment#1 –Sept/2016
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Authors:
Rakshit Mohan (H2014BAMA035)
Parvathy S (H2014BAMA031)
Prajkta G (H2014BAMA033)
KavyaMunduri (H2014BAMA020)
Carolyn (H2014BAMA019)
D Sai Vishwas (H2014BAMA042)
Swarnava Bhadra (H2014BAMA053)
Guide: Dr. Sunayana Swain
Research Question
Given the existing notions of development in India vis-a-vis Gujarat and Odisha, is there a
statistically significant difference between the status of chosen health indicators and sex ratio
between the states and when compared to the national average? Do the chosen indicators act
independently or do the trends exhibit any kind of inter-dependence?
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Index
Introduction
Rationale
Background
Infant Mortality Rate
Maternal Mortality Rate
Sex Ratio
Objectives
Methodology
Research Design
Participants
Instruments of Research: Operational Definitions
Procedure
Data Source
Limitations of Research
Analysis of Results
Discussion
Conclusion
References
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Introduction
The story of development in India has been a story of progress and inequality. India has made
significant progress in the field of development but the progress has come at the expense of
widening inequality of opportunity in access of those resources which lead to well-being. The
performance of a nation in the healthcare sector, education sector and the economic sector
indicates the level of development. Ideally, improvement of performance in one sector should
enhance the performance of other sectors.
India has registered phenomenal growth over the past two and a half decades. However, it has
not performed very well in the healthcare and education sector. Given the importance of the
healthcare sector in the overall development of a country, our group has chosen Infant Mortality
Rate and Maternal Mortality Rate as our indicators. Thereafter, we shall also assess the impact of
IMR, MMR and social stigma against the female gender on sex ratio, and analyse the emerging
trends in sex ratio temporally. Spatially, we have chosen to work on Gujarat from western part of
India and Odisha from eastern part of India.
Finally, we would explore the reasons behind the abysmal performance of the healthcare
indicators in India despite good economic growth.
Rationale
Our group decided to work on the indicators of health like IMR and MMR since these are
comprehensive indicators of development. The above mentioned indicators are influenced by a
wide range of policy interventions in the development sector. Furthermore, the indicators also
IMR, MMR, and SR: A systematic assessment of indicators of development in the state of Odisha and Gujarat – Quantitative Assignment#1 –Sept/2016
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influence the trajectory of development in a nation. In addition, IMR and MMR are affected by
social discrimination against women, nutritional status of women and children, care given to
women during pregnancy, antenatal care, delivery care and postnatal care. Therefore, both the
indicators can be used to comment on the overall state of development in a given region.
IMR and MMR have critical linkages with the sex ratio and, therefore, we chose to analyse the
sex ratio of the given states in order to explain the extent of gender-based discriminations and the
manifestations of such discrimination on the trajectory of development. The underlying
philosophy behind our focus on sex ratio comes from Sen (2005) where he argues that “gender
disparity is not one affliction but a multitude of problems” and that “gender inequality of one
type tends to encourage and sustain gender inequality of other kinds”.
Our emphasis on development isn’t utilitarian and growth oriented since we define development
as a multi-dimensional concept encompassing a state of physical, mental and economic well-
being. The underlying philosophy of our research is that improved health leads to improved well-
being, and that we should strive for achieving good health not because it will improve the
contribution that human beings make to the economy but because it is inherently good.
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Background
Infant Mortality Rate
Infant mortality is one of the prime indicators of development in any state since IMR is
influenced by, and influences, the other indicator of development. It is also an important
indicator of development as it indicates towards poor maternal health, sub-optimal nutritional
status of pregnant women, and low expenditure on social security in poor areas, poor antenatal
care, poor immunization, and poor access to medical resources, insufficient postnatal care and
malnutrition. Since several factors can lead to infant mortality, improvement in IMR can
invariably be linked to improvement of several other factors and rise in the overall level of well-
being.
1991 2001 20110
20406080
100120140
IMR Gujarat v/s Odisha v/s India
Gujarat Odisha India
Year
IMR
India’s IMR has been below sub-optimal levels for decades. However, it has registered an
improvement over a period of time and the current figures (2011) stand at 44 per thousand live
births. The figures of IMR stood at 66 in 2001 and 80 in 1991. The overall improvement is
encouraging but not sufficient since we have fallen short of the millennium development goals
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target of 28 in 2015. This must call for quick and efficient action at the centre and the states level
in order to improve the overall healthcare services provided by the governments.
1971
1981
1991
2001
2011
0 20 40 60 80 100 120 140 160 180155
123
73
68
48
110
89
57
42
27
144
116
69
60
41
IMR of Gujarat
Total Urban Rural
IMR
Yea
r
1971
1981
1991
2001
2011
- 20 40 60 80 100 120 140 160 127
135
124
91
57
131
140
129
94
58
84
68
71
61
40
IMR of Odisha
Urban
Rural
Total
IMR
Yea
r
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The figure are especially interesting for Gujarat and Odisha since, according to the Sample
Registration System figures of 2013, the IMR of Gujarat stands at 36 while the IMR of Odisha
stands at 51. Whereas Gujarat is closer to the MDG target of 28 and above the national average
of 44, Odisha is lagging far behind both MDG targets and national average. The trends have
exhibited that the IMR in Gujarat has fared better than that of Odisha since 1991 with figures of
69 in the former and 124 in the latter. In 2001, Odisha’s IMR reduced significantly to 91 and
Gujarat’s reduced to 60. The gap between IMR of the states has fallen since the 1980s but
Gujarat’s performance has been better than both Odisha and the national average during the
period 1991-2013. The question which we ask is: are the differences statistically significant?
We, therefore, try to examine what makes Gujarat perform better than the nation as a whole and
what leads to the abysmal performance of Odisha during the same period. However, our group
works with the realisation that though Gujarat has fared better than the national average, it has a
lot of ground to cover and incisive policy interventions are needed to match the global
standards.As we shall understand through t-test figures in the subsequent parts, the difference
between these indicators may or may not be statistically significant.
Maternal Mortality Rate
The maternal health status is positively linked to socio-economic development of the society, as
it denotes the status of family planning, pre-natal and post-natal care, and health promotion,
provision of education, and screening and interventions for women of reproductive age.
“The maternal mortality ratio is the number of women who die from any cause related to or
aggravated by pregnancy or its management (excluding accidental or incidental causes) during
pregnancy and childbirth or within 42 days of termination of pregnancy, irrespective of the
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duration and site of the pregnancy, per 100,000 live births” (GOI, 2015). Maternal deaths are
preventable. The fatal delays include: delay in decision to seek help, delay in getting transport
and delay in providing effective treatment. MMR is still high in India largely due to lack of basic
hospital services. Hence, MMR indicates the need to improve the accessibility and quality of
existing health care system.
1998 2001 2003 2006 2009 20120
50100150200250300350400450
MMR - Gujarat v/s Odisha v/s India
Gujarat ORISSA INDIA
Year
MM
R
At the Millennium Summit in 2000, states resolved to reduce maternal mortality by three
quarters by the year 2015. Under 5thMDG, India was supposed to decrease its maternal mortality
ratio to 109, a target the country failed to achieve.
However, maternal deaths in India have declined more than 50% in the last two decades. The
national average MMR stands at 167 (in 2013) compared to 398 in 1997-98. Though the
declining rates indicate positive development, the present status shows that 120 women die of
causes associated with pregnancy every day. Present MMR of the states Gujarat and Odisha,
stands at 122 and 235 respectively. While MMR of Gujarat is less than the national average,
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Odisha's is significantly higher. Although the MMR of both the states have exhibited
considerable decline in the past two decades, the significant gap between both denotes the
varying levels of human development and differences in policy implementation.The question we
ask in the light of the above background is if the differences between Gujarat and Odisha are
statistically significant.
Sex Ratio
1991 2001 2011880
900
920
940
960
980
1000
Sex Ratio Gujarat v/s Odisha v/s India
Gujarat
Odisha
IndiaYear
Sex
Rat
io
Sex ratio entails socio-cultural factors which determine the survival chances of the female infant. As
per Census 2011, sex ratio of India is 943 females per 1000 males. It is a leap from the 2001 figure
according to which only 933 females existed per 1000 males. However, figures regarding child sex
ratio have been discouraging since the ratio has dropped from 976 in 1961 to 914 in 2011.
Furthermore, the decline has not been similar across various states of India.
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1991
2001
2011
800 820 840 860 880 900 920 940 960 980 1000
988
987
989
866
895
932
971
972
979
SEX RATIO OF ODISHA
Total
Urban
Rural
Sex ratio
Yea
r
As per census-2011, the sex ratio for Odisha was 979, which was higher than the national
average of 940. The sex ratio increased from 971 in 1991 to 979 in 2011 registering a growth of
1 in the first decade and a growth of 7 in the subsequent decade. With the current growth rate of
sex ratio in Odisha, the projected sex ratio is 985 and 990 for the year 2021 and 2026
respectively.
In Gujarat, the numbers have been disappointing since the sex ratio has dropped consistently since
1991. The sex ratio peaked at 934 in 1991; it fell to 920 in 2001 and fell further to 919 in 2011. The
rural and urban spaces registered similar trends during the period between 1991 and 2011.
The child sex ratio figures of Gujarat, in 2011, touched the abysmal low of 890 and call for
immediate attention. The decreasing sex ratio in the age group 0-6 years has a cascading effect on
the entire population. The imbalance of child sex ratio is hard to remove since it has manifestations
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in the
future figures.
Taking cues from the figures, the question we ask is whether there is a statistically significant
difference between various sets of data on sex ratio. What can be the possible reasons for such an
abysmal performance in Gujarat despite high economic growth and better status of IMR and MMR
indicators?
Objectives
1) To examine and compare IMR, MMR and sex ratio of Gujarat and Odisha.
2) Comparison on rural and urban of dimensions of the indicators.
IMR, MMR, and SR: A systematic assessment of indicators of development in the state of Odisha and Gujarat – Quantitative Assignment#1 –Sept/2016
1991
2001
2011
840 860 880 900 920 940 960
949
945
949
907
880
880
934
920
904
SEX RATIO OF GUJARAT
Total
Urban
Rural
Sex Ratio
Yea
r
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3) To analyze if there are statistically significant reasons differences between the two states
based on the given parameters.
4) To compare the respective state indicators with national figures
5) To try and understand the possible reasons behind the performance of such indicators in
the states under consideration
6) To suggest minimal basic interventions so that our indicators start exhibiting a positive
trends in the years to come.
Methodology
Research Design
This is a descriptive study of the status of IMR, MMR and sex ratio in the states of Gujarat and
Odisha, and compares the trends of the chosen indicators within the chosen time frames. This
study explains the current status of the above indicators and traces it history.
The study focuses on secondary data in order to analyze and understand macro trends in Odisha
and Gujarat. Primary data has not been used due to lack of time and large scale of operation that
it would entail. The census data of IMR and sex ratio, and SRS data for MMR corresponding to
the chosen state, along with the national averages are studied and analyzed to answer the
research question. Furthermore, the indicators are tested for dependence using the state wise
data. Finally, discussion based on reading of literature related to human development dynamics
relevant to the scope of this study and calculated assumptions regarding the explanation of the
results is put forth.
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The research is based on census year IMR and Sex Ratio data of Gujarat and Odisha, and the
national averages of the same indicators from 1971 – 2011. The national and state-wise (Gujarat
and Odisha) MMR data for every 3 years from 1998 – 2012 is also used. The data of MMR is
collected by the sample registration system (SRS). Other two indicators that the study focuses
on, IMR and sex ratio, are collected by household survey with individual enumeration of the
whole population of the country conducted through the census procedure using elaborate
questionnaires (Government of India, Ministry of home affairs, n.d.).
The study has used t-tests to check the statistical significance of difference between the mean
values of the chosen indicators in Odisha and Gujarat, the comparison of rural and urban values
of the states, and finally comparison of each state with the national average. Pearson’s product
moment correlation which gives the interdependence of two variables and is denoted by the
coefficient of correlation (-1≥r≥1) (Mangal, 2002, p. 79-80), is also used. The research finds the
correlation between different indicators of each state. For instance, correlation between IMR of
Gujarat and MMR of Gujarat is calculated. The results of both these are analyzed to find out the
statistical significance of the difference between the two states based on the given parameters.
Microsoft Office Excel’s data analysis option was used to compute the correlation coefficient
and t values. The study has also presented scattered plots of the correlation data.
Participants
The participants of this research include all the households covered under decadal census from
the state of Odisha and Gujarat. It also includes those households who were sampled for sample
registration system (SRS) since SRS has been used to analyse data on MMR in Odisha, Gujarat
and India.
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It should be noted that there is a crisis of public data on the above mentioned indicators and,
therefore, the study has used data across different time periods. Availability of data was one of
the biggest problem that the study encountered, and the researchers are confident that the study
could have been more reproducible but for the lack of data.
Instruments of Research
Operational Definitions:
Infant is defined as a child who is less than 365 days old, i.e less than one year of age.
Infant mortality rate (IMR) is defined as the number of infant deaths per every thousand
live births.
Maternal Mortality Rate (MMR) is defined as the number of deaths due to maternal
causes in women aged between 15-49 years per every 1,00,000 live births.
Sex ratio is defined as the number of females per thousand males of the population.
Procedure:
The study is based on the background understanding of the health indicators in India.
First, a basic understanding of the health indicators in India was arrived at through
literature on the given sector.
Second, data was collected from secondary sources, arranged in order and analysed.
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Third, statistical tools like Pearson’s product moment correlation and student’s t-test
were used to find relationship and difference between the indicators.
Fourth, the data generated thereof was subjected to discussion based on literature.
Finally, a conclusion was arrived at based on the research question.
Data Source:
First, decadal census data is a complete nation-wide collection of data based on household
survey. It uses a structured questionnaire and collects data from individual households based on
the questionnaire. Second, sample registration system (SRS) was used. They use dual mode
recording: first, continuous enumeration of maternal deaths in the sample areas; and second, a
retrospective survey every six months, recording of maternal deaths with generally consistent
definitions (Government of India, Ministry of Home Affairs, n.d.).
Limitations of Research:
Comprehensive data on health indicators is not available for all the states.
District-wise data is unavailable for Odisha and Gujarat.
Due to use of data from various time periods, as per availability, there is a risk that the
generalizability of the research is lowered since the trends cannot be established in the
same time period. For example, MMR data is available only since 1997 while IMR data
is available since 1971.
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The rural-urban data on MMR is not available and, therefore, description of such trends
or correlation with IMR is not possible. This again reduces the generalizability of the
research.
Analysis of Result s
Figure 1
50 60 70 80 90 100 110 120 130 140960
965
970
975
980
985
990
Correlation between IMR & Sex Ratio of Odisha
SR of OdishaLinear (SR of Odisha)
IMR of Odisha
Sex
Rat
io o
f Odi
sha
Figure 1 reveals that there is an intermediate positive correlation between the IMR and sex ratio
of Odisha. The correlation coefficient equals 0.26 and suggests that the correlation is
intermediate.
Figure 2
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20 40 60 80 100 120 140 160905
910
915
920
925
930
935
940
945
Correlation between IMR & Sex Ratio of Gujarat
SR of GujaratLinear (SR of Gujarat)
IMR of Gujarat
Sex
Rat
io o
f Guj
arat
Contrary to figure 1, figure 2 reveals strong positive correlation between IMR and sex ratio of
Gujarat and the coefficient of correlation is 0.76. The IMR of Gujarat is likely to exhibit similar
movements as the sex ratio of Gujarat.
Figure 3
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35 40 45 50 55 60 650
50
100
150
200
250
Correlation between IMR & MMR of Gujarat
MMR of GujaratLinear (MMR of Gujarat)
IMR of Gujarat
MM
R o
f Guj
arat
Figure 3 establishes high positive correlation between MMR and IMR of Gujarat, and the
coefficient of correlation is 0.96. This indicates that IMR and MMR of Gujarat have made
similar improvements during the period under consideration.
Figure 4
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50 55 60 65 70 75 80 85 90 950
50100150200250300350400450
Correlation between IMR & MMR of Odisha
MMR of OdishaLinear (MMR of Odisha)
IMR of Odisha
MM
R o
f Odi
sha
Figure 4 establishes a strong positive correlation between the IMR and MMR of Odisha with the
coefficient of correlation being 0.97. This indicates, as in the above case, that IMR and MMR
have made similar improvements
Table 1
IMR Gujarat
M SD
IMR Odisha
M SD t P
Total
Rural
Urban
86 42.585
93.4 44.139
65 34.05
106.8 32.51
114 33.83
64.6 14.69
-0.868069
-0.82821
0.024118
<.05
<.05
<.05
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In Table 1 IMR Odisha-Gujarat reveals that there is a statistically insignificant difference
between the total IMR of Odisha and the total IMR of Gujarat given the fact that the t-value of
the given means is lower than the critical value. Though the IMR of Gujarat is lower than the
IMR of Odisha, it must be observed that the Gujarat data has high level of variance since it
started from an initial high. Rural IMR of Odisha and Gujarat reveals that there exists a
statistically insignificant difference between the indicators under consideration. Urban IMR of
Gujarat and Odisha reveals trends similar to Total and Rural IMR of Gujarat and Odisha.
Table 2
IMR Gujarat
M SD
IMR India
M SD t P
Total 86 42.579 85.8 34.002 0.008207 <.05
In Table 2 IMR of Gujarat vis-a-vis India reveals trends similar to Table 1 in terms of statistical
significance and standard deviance analysis.
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Table 3
IMR Odisha
M SD
IMR India
M SD t p
Total 106.8 32.514 85.8 34.002 0.998101 <.05
In Table 3 IMR of Odisha vis-a-vis India reveals trends similar to Table 1 and 2. An analysis of
Table 1, 2, and 3 reveals that the difference between IMR values of Gujarat, Odisha, and India,
and their rural and urban settings is statistically insignificant. Hence, it can be said that there is a
statistical parity between data sets of the states and the nation itself since the difference is
insignificant statistically.
Table 4
SR Gujarat
M SD
SR Odisha
M SD t p
Total
Rural
Urban
929.6 10.237
947.6 2.309
889 15.58
978.4 7.092
988 1
897.6 33.08
-8.761912
-27.7593
-0.41048
<.001
<.001
<.05
In Table 4 Sex ratio of Gujarat and Odisha reveals a statistically significant difference between
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sex ratio of Gujarat and Odisha. Statistically, the t- value of 8.76 exceeds the critical value of
2.36, and hence the difference between variable sets is significant in the given confidence
interval. The variance is higher in case of Sex ratio of Gujarat when compared to Odisha. The
continuous fall of higher magnitude in vase of Gujarat is the possible reason for higher variance
vis-a-vis Odisha. Rural Sex Ratio of Gujarat and Odisha reveal results, which are similar to SR
total of Gujarat and Odisha. However, the results are based on analysis of decadal data from
1991-2011, which could lead to high t-value in the given set of data. Urban Sex Ratio of Gujarat
and Odisha reveal that the difference between Urban Sex Ratio of Gujarat and the Urban Sex
Ratio of Odisha is statistically insignificant since the t-value of 0.41 is lower than the critical
value of 3.18. However, the results are based on analysis of decadal data from 1991-2011, which
could lead to high t-value in the given set of data.
Table 5
SR Gujarat
M SD
SR India
M SD t p
Total 929.6 10.23 933.4 6.024 -0.71533 <.05
Table 5 Sex Ratio of Gujarat vis-a-vis India reveals that the difference between Sex Ratio of
Gujarat and the Sex Ratio of India is statistically insignificant since the t-value of 0.71 is lower
than the critical value of 2.45.
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Table 6
SR Odisha
M SD
SR India
M SD t p
Total 978.4 7.0922 933.4 6.024 10.81281 <.001
Table 6 Sex ratio of Odisha and India reveals a statistically significant difference between sex
ratio of Odisha and India. Statistically, the t- value of 10.81 exceeds the critical value of 2.30,
and hence the difference between variable sets is significant in the given confidence interval.
Table 7
MMR Gujarat
M SD
MMR Odisha
M SD t p
Total 145.6 59.1844 337.8 62.218 -5.0048 <.001
Table 7 MMR of Gujarat and Odisha reveals a statistically significant difference between MMR
of Gujarat and Odisha. Statistically, the t- value of 5.00 exceeds the critical value of 2.30, and
hence the difference between variable sets is significant in the given confidence interval.
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Table 8
MMR Gujarat
M SD
MMR India
M SD t p
Total 145.6 59.184 298.4 71.030 -3.6955 <.001
Table 8 MMR of Gujarat and India reveals a statistically significant difference between MMR of
Gujarat and India. Statistically, the t- value of 3.69 exceeds the critical value of 2.30, and hence
the difference between variable sets is significant in the given confidence interval.
Table 9
MMR Odisha
M SD
MMR India
M SD t p
Total 337.8 62.218 298.4 71.030 0.933005 <.05
Table 9 MMR of Odisha vis-a-vis India reveals that the difference between MMR of Odisha and
the MMR of India is statistically insignificant since the t-value of 0.93 is lower than the critical
value of 2.30.
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Discussion
The examination of MMR and IMR reveal the bleak picture of maternal and child health in
India. For a healthy mother and child, it is necessary that proper care is administered along with
timely management and treatment of the pregnant woman by skilled health professionals during
pregnancy, post-partum and child’s infancy.
Socio-cultural factors like patriarchy has negative effects on maternal health. While preference
for the male children ensures that the female child receives frugal nutrition, the fixation of
gender roles demand that women to be primary care-givers and home makers. The vacuum of
knowledge surrounding reproductive health – cultural and religious rituals which negatively
affect health; the educational status of the girls which is also affected by gender biases; age of
marriage, birth spacing, consumption of tobacco; poor health infrastructure, and discrimination
based on class and caste are all factors that have substantial effect on maternal health.
Anemia is a prominent cause of mortality. It is found that Odhia women are much more prone to
anemia than the average Indian woman. MDG Report of 2014 states that distribution of iron
prophylaxis to pregnant women through Anganwadis can be effective in reducing MMR. Lack of
water is directly linked to sanitation issues, and indirectly increases women’s burden of work.
Furthermore, poor quality of water leads to water-borne diseases. Non-communicable diseases
and household pollution caused by the exposure to biomass fumes are factors that affect maternal
health. In the specific case of Gujarat where beedi rolling industry thrives on cheap labour of
women, even passive smokers are diagnosed with lung ailments.
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The intersection of patriarchy, poor infrastructure and cultural-religious dogma renders women
with no reproductive rights. The lack of knowledge about healthy contraception, medical care or
facilities for abortion increases the risk of maternal mortality.
The cultural and religious factors often supersede educational and economic affluence. The most
vulnerable are the ones belonging to marginalized sections. Therefore, to help the marginalized
women, Chiranjivee scheme (2005) has aimed at ensuring safe deliveries for Below Poverty Line
(BPL) in Gujarat. Under it, private obstetricians were assigned to provide free service to the poor
rural mothers. This significantly increased institutional deliveries and expanded the reach of
healthcare facilities to the most remote areas.
Janani Suraksha Yojana aimed at bringing down IMR and MMR, was successful in identifying
ASHA workers who facilitated institutional deliveries. While this scheme was successful in
Gujarat, it failed in Odisha due to failure of Anganwadi system, lack of ASHA workers, lack of
emergency services and poor infrastructure. However, Janani Shishu Suraksha Karyakram and
Mamta scheme have been launched by the Odisha government, and are expected to yield results.
In the period 1991-2011, Gujarat’s total sex ratio declined from 934 to 904 while Odisha’s
increased from 971 to 979. Overall, rural areas have a higher sex ratio compared to urban areas.
Trends in Urban Gujarat are completely opposite to that of Urban Odisha. While the sex ratio has
declined in the former, it has registered significant increase in the latter. This clearly indicates
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that the character of urbanization is different in both the states and a comprehensive analysis
must look at the interaction of various economic and socio-cultural factors.
Although we have chosen to analyze the trends in the period 1991 – 2011, it must be emphasized
that the present statistics are not just shaped by the immediate past but have historical causes
located at the intersection of caste and patriarchy. In the contemporary times, prenatal sex
determination has contributed to the resilience of these structures, allowing them to function in
qualitatively different ways. It gained widespread significance in the 1980s and the 1990s.
Researchers have estimated that 11 million sex selective abortions were performed in the period
1981-2006 which amounted to 3.6 per cent of female births (Kulkarni, 2007). Research has also
found out that the majority of sex selective abortions have taken place in the Northwestern
region of the country. These regional differences can be explained in terms of differing social
and cultural traditions. It has been remarked that women’s social position has historically been
much better in the south and the east compared to the rest of the country (Bhattacharya, 2012).
In a study conducted by the Health Watch Trust in the district of Mehsana in Gujarat to
understand the reasons for their declining sex ratios, the role of caste specific traditions is clearly
brought out. The preponderance of sex selective abortions was observed in the dominant
Chaudhary caste. Their migration from Haryana had little effect on their patriarchal structures
and values. Such a network of patriarchy and caste was less resilient in Odisha, with a huge
number of tribal groups and higher participation of women in the production process.
Emphasizing on the economic dimension, Gujarat’s high economic development (leading to
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greater access to reproductive technologies) has proved to be detrimental to its sex ratio whereas
Odisha’s low economic development, which has affected its IMR and MMR, has also restricted
access to sex determination technologies.
On a close examination of IMR, it is observed that the rates of girl children is much higher than
that of boys. This observation holds true for both rural and urban areas. It also holds true at the
national level. In both rural and urban areas of Gujarat, the infant mortality rate of girls has
always been always been higher than that of boys throughout the period which we have studied.
The son preferences and neglect of girl children are observed to be the main reasons of declined
sex ratio in Gujarat. When we take into account the infant death rates for children aged between
0-5 months and 6-11 months, the sex differences in mortality is even bleaker and this is because
when a child starts requiring supplementary feeds, the girl child gets lesser attention which
results in the increase of chances of death of the girl child. Although Gujarat has developed
economically, it still has deep rooted traces of patriarchal thought processes, which can be
attributed as causes for higher female IMR. According to NHFS, IMR is found to be higher in
the households, where the head of the family is completely illiterate. Gujarat government
interfered to better the levels of immunization and vaccination of girl children (Visaria, 2005).
Odisha has one of the highest IMRs in India. Even the total number of primary health care
centres is far below that of the national average and Odisha’s target are yet to be achieved.
Almost 60% of the infant deaths that happen in Odisha, happen during the neo-natal period of
the infant i.e., during the first four weeks into life. During the year, 2001 the government of
Odisha launched a special mission to reduce the IMR (NHFS, Orissa) and the results have begun
to show. However, there is still a lot of ground left to be covered.
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Conclusion:
“In a democracy, the well-being, individuality and happiness of every citizen is important for the
overall prosperity, peace and happiness of the nation.” – APJ Abdul Kalam
This paper assiduously brought forth the multi-faceted dynamics in the process of economic
growth and human resource development. By the careful study of IMR, MMR and SR this paper
established that basic tenets of development discourse need a complete overhaul.
Although, Gujarat has performed a lot better than Odisha economically, but when a comparative
study of the Sex Ratio of both the states is done it can be concluded that the figures for Gujarat
have dwindled over the years. This fact goes on to further establish that economic growth in
itself will not lead to better human resource development. The causes for this dwindling sex
ratio can be attributed to the deep-rooted patriarchy coupled with better and improved
technology for sex-selective abortions. On the other hand, Odisha has been able to improve its
sex ratio.
As Saint Teresa of Calcutta once rightly opined that loneliness and the feeling of Unwantedness
is the worst state of mind that one can be in, similar is the case with women and girl children.
Even though there has been policy interventions in this regard with the Ban on sex selective
abortion (Pre-Natal Sex Determination – PNDT, 1994), however these measures have had
limited effectiveness. Given the extremely serious and far-fetched nature of this phenomenon
immediate cognizance needs to be taken in this regard.
Maternal Mortality Rate and Infant Mortality Rate are both lower for Gujarat than Odisha. This
goes on to establish that with economic growth and better medical infrastructure there has been
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considerable improvements made in Gujarat. However when considering the equity perspective,
there still exist huge glaring lacunae; since there hasn’t been equitable distribution of these
improvements, for instance urban areas have fared better than rural areas, and similarly certain
caste groups have performed better than others. This goes on to prove than without proper
monitoring, intervention and accountability mere economic growth would not lead to desired
benefits for society as a whole.
Finally, there is no denying that the contemporaneous milieu has undergone rapid economic
growth, but these resources have been cornered by a very minuscule section of the population
leaving a huge and ever widening gap between the various sections of society. This paper has
pointed out how rural Odisha with one of the worst economic indicators has better Sex Ratio
than Gujarat and all India average. This phenomenon compels us to introspect on the very
fundamental of definitions that we have been using for comparing development of various
regions. Although, economic growth is important but proper intervention in the right direction is
also required so that we are able to truly realize the dream of being a ‘welfare state’.
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