swarnavasayanbhadra.files.wordpress.com · Web viewInfant Mortality Rate, Maternal Mortality Rate, and Sex Ratio: A systemat. ic assessment of indicators of d. evelopment in the

P a g e | 1

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

P a g e | 2

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?


P a g e | 3

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


P a g e | 4

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


P a g e | 5

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.


P a g e | 6

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


P a g e | 7

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


P a g e | 8

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


P a g e | 9

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,


P a g e | 10

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.


P a g e | 11

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


P a g e | 12

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.


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

P a g e | 13

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.


P a g e | 14

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.


P a g e | 15

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.


P a g e | 16

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.


P a g e | 17

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


P a g e | 18

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


P a g e | 19

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


P a g e | 20

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


P a g e | 21

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.


P a g e | 22

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


P a g e | 23

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.


P a g e | 24

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.


P a g e | 25

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.


P a g e | 26

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.


P a g e | 27

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


P a g e | 28

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


P a g e | 29

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.


P a g e | 30

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


P a g e | 31

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’.


P a g e | 32

References

Bhattacharya, P. C. (2013). Gender inequality and the sex ratio in three emerging

economies. Progress in Development Studies, 13(2), 117-133.

Census of India. (2011a). Census and You. Retrieved from Government of India Website

http://censusindia.gov.in

Census of India. (2011b). Census Operations. Retrieved from Government of India Website

http://censusindia.gov.in/Data_Products/Library/Indian_perceptive_link/Census_

Department of Health & Family Welfare, MOHFW, Government of Odisha (2011) Annual

Report 2008-09. Bhubaneswar: Department of Health & Family Welfare, MOHFW,

Government of Odisha.

Drevenstedt, G. L., Crimmins, E. M., Vasunilashorn, S., & Finch, C.E. (2008). The Rise and Fall

of Excess Male Infant Mortality. Proceedings of the National Academy of Sciences of

the United States of America, 105(13). Retrieved from

http://www.jstor.org/stable/25461545

Government of India (2015), Manual on Health Statistics in India, Ministry of Statistics and

Programme Implementation, Government of India (In Collaboration with TISS

Mumbai).

Government of India, Ministry of home affairs.(n.d.). Census of India Website : Office of the

Registrar General & Census Commissioner, India. Retrieved September 22, 2016, from

http://www.censusindia.gov.in/

Government of India. (2016). Compendium of India’s Fertility and Mortality Indicators, 1971-

2013. Retrieved from Census of India

http://www.censusindia.gov.in/vital_statistics/Compendium/Srs_data.html


http://www.censusindia.gov.in/

http://censusindia.gov.in/Data_Products/Library/Indian_perceptive_link/Census_

http://censusindia.gov.in/

P a g e | 33

Gujarat: some observations. International Journal of Social Science & Interdisciplinary

Research, 1(9). Retrieved from

http://indianresearchjournals.com/pdf/IJSSIR/2012/September/9.pdf

India, Ministry of Statistics and Programme Implementation Government of India,

Maternal mortality in Odisha [PDF]. (2015, March). Delhi: Human Rights Law Network

Ministry of Statistics and Programme Implementation.(n.d.).Indian statistical system.

Retrieved from http://mospi.nic.in/nscr/iss.htm

Patel, T. (Ed.). (2007). Sex-selective abortion in India: Gender, society and new reproductive

technologies. Sage.

Reproductive Rights Initiative. Retrieved from:

http://www.hrln.org/hrln/images/stories/pdf/Maternal-Mortality-in-Odisha-Report-

HRLN.pdf

Sinoj, P., & Mishra, S. (2012, September). Status of maternal health and its services in Statistics

Division.(2015). Millennium development goals India country report 2015.Retrieved

from: http://mospi.nic.in/mospi_new/upload/mdg_26feb15.pdf

The New Indian Express. (October, 2013). Odisha tops in maternal, infant mortality rate.

Retreived from http://www.newindianexpress.com/states/odisha/Odisha-tops-in-

maternal-infant- mortality-rate/2013/10/07/article1822831.ece

University of South Carolina. (2016). Organising your social sciences research paper: Types of

research designs. Research Guides. Retrieved from

http://libguides.usc.edu/writingguide/researchdesigns

World Bank. (2014). Public Health Expenditure as percentage of GDP. Retrieved from

http://data.worldbank.org/indicator/SH.XPD.PUBL.ZS


http://data.worldbank.org/indicator/SH.XPD.PUBL.ZS

http://libguides.usc.edu/writingguide/researchdesigns

http://mospi.nic.in/mospi_new/upload/mdg_26feb15.pdf

http://www.hrln.org/hrln/images/stories/pdf/Maternal-Mortality-in-Odisha-Report-HRLN.pdf



http://mospi.nic.in/nscr/iss.htm

http://indianresearchjournals.com/pdf/IJSSIR/2012/September/9.pdf

Documents

swarnavasayanbhadra.files.wordpress.com · Web viewInfant Mortality Rate, Maternal Mortality Rate, and Sex Ratio: A systemat. ic assessment of indicators of d. evelopment in the